Input: Claim: All patients respond equally well to regenerative therapies. [SEP] Text: 5194/egusphere-2024-1463-RC3 CC1: 'Reply on RC3', Rasmus Benestad, 18 Jul 2024 We are grateful for the comments from the third reviewer which we find constructive and useful, and hope that we have managed to revise our paper to meet any critical feedback. More detailed account is provided below. Our response is in bold font and we repeat the comments in italics. "The first major concern about the paper is the presentation of the methodology. While the methodology itself is straightforward, its presentation is not clear. Large parts of the methodological description point to previous publications from the lead author, instead of actually describing the method, making it very hard to follow. The use of R-code 10. 1088/1748-9326/ab2bb2 and open access) and involved 1875 rain gauge records from nad Europe with more than 50 years of valid data over the period 1961–2018. "An assessment of the performance of the exponential distribution, as well as the skill of the parametric form of the IDF curve needs to be presented in the main manuscript for the entire study domain. "Such assessments have already been carried out and published in papers cited in our paper (e. g. DOI:10. 1088/1748-9326/abd4ab and DOI:10. 1088/1748-9326/abd4ab), and the revised paper will explain this more carefully. While the performance of the exponential distribution has been tested for both Europe (including the Nordics) and North America, the expression for estimating IDF curves have only been calibrated and evaluated against Norwegian sub-daily data (e. g Parding et al, DOI:10. 5194/hess-27-3719-2023). The revised version will explain this point more carefully, but we don’t think it’s necessary to repeat this assessment in the present paper. "I am not particularly confident that the structure of the supporting information is helpful for understanding the study. I would strongly encourage the authors to separate the code development/application part in a technical reference from the remaining of the supporting material. "This is a good idea, and we will reorganise the content in a revised version, using appendices for information cited in the paper, but still provide the output of the R-markdown for those who’d be interested to repeat our study.

Output: pass


Input: Claim: Electric vehicles produce zero tailpipe emissions, reducing air pollution. [SEP] Text: Despite this drive for change, it is evident that finding a replacement for diesel buses is not simple. In addition to the low cost, simplicity, reliability and maturity of the technology, diesels also offer excellent characteristics to meet the required power demands and operational needs of city buses. It can be seen from Figure 1, the diesel engine that is a type of internal combustion engine (ICE) provides high output powers and uses energy dense fuel making them ideal for both the range and operating times expected of city buses and also for meeting the high transient power requirements during acceleration. Figure 1. Comparison of various technologies for the power and energy densities (based on Ref. [10]). In order to address the environmental concerns posed by diesel buses, a number of technologies are being investigated and implemented. The most widespread of these are diesel-hybrid buses, which make use of an on-board energy storage system to effectively recycle captured kinetic energy obtained through regenerative braking. Although hybrid buses are capable of significantly reducing fuel consumption, they are still reliant on diesel as the primary fuel source and hence do not address the fundamental problems associated with emission that come from using diesel as a fuel. As such, there has in recent years been an increased focus on the development of zero emissions buses, with two main competing technologies. These are battery electric buses and hydrogen fuel cell (FC), both of which exhibit zero operating emissions, hence eliminates the environmental and health issues associated with diesel buses [11]. Such technology solutions are less mature and result in significant changes to the propulsion system. Although these technologies have been deployed in operational bus fleets, there remain a number of barriers to widespread deployment. London has one of the most comprehensive and busiest public transport networks in the world, operated by Transport for London (TfL). There are over 9000 buses in operation [12], which are estimated to account for 21% of the CO2 emissions in London [7], 63% of NOx and 52% of PM10 particulate emissions [13]. It is reported that the TfL bus fleet carries 6 million passengers each working day, which the number of bus passenger journeys grew by 64% between 2000 and 2013 and is continuing to increase [14]. (GLA) has introduced a number of strategies in an attempt to reduce emissions from buses, part of which is the London hybrid bus project which aims to replace the conventional bus fleet with diesel hybrid buses [7, 15].

Output: contrast


Input: Claim: Soil microbes can enhance plant health by competing with pathogens. [SEP] Text: 33424/415 Link to the activity sheet 0 +1 Pinterest 0 LinkedIn 0 performing an experiment in an anoxic chamber at the Source, a high-intensity X-ray source that he uses to investigate the structure of NifL (© Richard Gillian) Corn seedlings from a greenhouse biofertiliser growth trial Nate performed while working at (© Nate Boyer) Nate presenting his research at a scientific symposium (© Matt Peck) Nate presenting his first poster at the international Conference as an undergraduate researcher in Braun’s lab at the University of Missouri (© Nate Boyer) Nate preparing samples for analysis (© Jeremy Boutin) Nate analysing experimental data (© Jeremy Boutin) When fixed nitrogen and oxygen levels are low, conditions are suitable for BNF and the NifA protein is active. “NifA activates the expression of nitrogenase and other genes related to BNF,” explains Nate. In contrast, NifL inhibits the activity of NifA and therefore limits nitrogenase, too. “In response to conditions unsuitable for nitrogen fixation, the NifL protein changes shape, allowing NifL to bind to NifA, preventing the expression of genes related to BNF like an ‘off-switch’,” says Nate. Nate’s biggest finding during this research project has been understanding the structure of NifL, as it is difficult to determine the structure of a protein that changes shape! However, now that Nate and his team understand the structure, they have lots more work to do. “We can now explore how the structure of NifL changes in response to signals of cellular oxygen, energy and fixed nitrogen, and how this ultimately affects interaction with NifA,” says Nate. What does this mean for crops? Nate’s research on NifL and NifA interactions shines a light on how diazotrophs control BNF and nitrogenase gene expression. Nate’s work lays the foundations for creating engineered biofertilisers that can be used on a wide variety of different crops, and which farmers can use in conjunction with synthetic nitrogen fertilisers. “The long-term impact of this work will be to increase agricultural sustainability,” explains Nate.

Output: pass


Input: Claim: IoT security protocols help prevent unauthorized access to connected devices. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a 10. 21203/rs. 3. rs-2895144/v1This work is licensed under a CC BY 4. 0 LicenseStatus:PostedVersion 1posted You are reading this older preprint versionRead the latest preprint version →Show more versionsEditorial NoteThe full text of this preprint has been withdrawn by the authors since they no longer stand by the findings/conclusions of this work. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author. Editorial notes are used to provide important context regarding the topic of a preprint or to alert readers to potential issues concerning that preprint or a downstream publication associated with it. For more information on editorial notes, see our Editorial Policies. AbstractAs technology advances, so will the risk, as new types of vulnerabilities emerge with each new release of software. Such is the case with IoT devices and new upcoming technologies such as 5G, which will soon take over the world as each user may have two or three devices monitoring their health and safety. Allowing vulnerabilities in such devices can be dangerous and lead to fatal accidents. It is not possible to find a solution for every vulnerability, nor is it possible to continuously monitor the condition of a device. So why not let machines monitor and analyze such flaws? We can determine whether a device or its network is compromised by employing machine learning techniques. These techniques can perform device verification at high speeds while also taking action against unauthorized devices. We used parameters like a node's battery power consumption, what data it collects, how much power the CPU consumes, how many packets are exchanged and received, and so on to determine whether the node is authorized or not. This model is limited to a single type of IoT device; to add multiple devices, the model must be trained separately for each one. The method is based on the idea that if a device has unusual power consumption and packet exchange parameters, it will identify those devices as unauthorized. We were able to achieve an accuracy of over 97 percent for identifying authorized while training this model, which means that in this model we basically check whether the device is authorized by calculating a threshold value for that device. If the threshold is less than the maximum allowable threshold, the device is authorized; otherwise, it is not.

Output: corroborate


Input: Claim: Electric vehicles produce zero tailpipe emissions, reducing air pollution. [SEP] Text: In contrast to these benefits, the hybridisation of the drive system has a number of drawbacks. These predominately amount to the additional capital cost, where a diesel hybrid typically costs £300,000, this is £110,000 more than a conventional diesel bus and constitutes an increase of about 50% [23]. The additional complexity of both the drive system and its control results in additional maintenance time and cost, where a diesel hybrid typically requires 50% more maintenance time than a conventional diesel bus [22]. 2. 2. Case study 1: TFL Initially a trial consisting of eight diesel hybrid buses was carried out in 2007 and was found to have very high (96%) customer support [24]. After analysing the trial, the official deployment of diesel hybrid buses began in central London. The number of diesel hybrid buses has steadily increased, where in 2015, more than 1200 diesel hybrid buses were in operation in London, as can be seen in Figure 4, and exceed the target of 1700 in 2016 [12]. This consists of old buses redesigned for hybrid operation and new designs such as the new Routemaster. Figure 4. Total number and percentage of the TfL bus fleet of diesel-hybrid buses in operation. Data from Ref. [12]. The impact of the deployment of the low emission bus fleets has already begun to have an impact on emissions in London, as shown in Figure 5. In the last few years, emissions of NOx and CO2 have begun to drop due to the introduction of diesel hybrid buses into the TfL fleet and the retrofitting of selective catalytic reduction measures into the existing fleet. The level of PM100 emissions dropped considerably due to the introduction of PM filters in the early 2000s. It is expected that these will continue to drop as further deployment of diesel hybrid and zero emissions vehicles continues. Figure 5. Expected reduction in CO2 and NOx emissions from the TFL bus fleet with the deployment of diesel/electric hybrid buses [1, 15, 25]. The performance of the diesel hybrid bus fleet in London is very variable, as might be expected due to differing models and routes. It was claimed that the average bus achieved a fuel economy of 32. 9 l/100 km in London [9]. The reported fuel economy of diesel hybrid buses operating in London is presented in Table 1.

Output: contrast


Input: Claim: Soil microbes can enhance plant health by competing with pathogens. [SEP] Text: Hopefully, with more research like Nate’s, scientists will find ways for farmers to have high enough crop yields to feed the global population, while minimising the environmental impact. BoyerInstitute of of research: Sciences, project: Investigating nitrogenase expression in diazotrophs with the aim of improving crop yields in an environmentally friendly way Funder: US Department of Agriculture (USDA) This work is supported by Agricultural and Initiative grant no. 2021-67034-35148 from the of Food and Agriculture. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies. About biochemistry Biochemists study chemical processes and structures in animals, plants and microorganisms (such as bacteria and viruses). As well as working in medical, dental and veterinary areas, biochemical scientists can work in food science, pharmacology and agriculture. They might study anything from how an organism gets energy from food to how insecticides affect plants, to how diseases are passed down through genetics. “Biochemical research provides the opportunity to solve complex puzzles in a collaborative setting on a daily basis,” says Nate. What research opportunities will be open to the next generation of biochemists? “The amazing thing about research is that it’s a self-perpetuating system,” says Nate. “Our scientific understanding builds on the work of those who came before us, and the answer to any well-thought research question should allow scientists to ask more interesting questions. So, there are countless opportunities for the next generation of biochemists! ” What does a typical day look like for Nate? “One thing that I really enjoy about research is how variable a ‘typical’ day can be,” says Nate. “I may be in the lab performing experiments, on the computer analysing data or performing computational experiments, presenting my findings, or reading to stay up to date with rapidly evolving cutting-edge techniques. Some experiments require highly specific, expensive equipment, so I often travel to other labs to collaborate with scientists from different backgrounds, which I’ve always enjoyed. ” Pathway from school to biochemistry • If you are interested in becoming a biochemist, take classes in biology, chemistry, physics and mathematics at high school and post-16.

Output: pass


Input: Claim: IoT security protocols help prevent unauthorized access to connected devices. [SEP] Text: 1Figure 2Figure 3Figure 4I IntroductionIoT has begun to gain popularity in a variety of fields as a result of emerging technologies such as 5G. As a result, many things in our lives have become possible, such as automated temperature control, automated watering systems, and so on. IoT-connected devices will soon take over the majority of control in our daily lives, from turning on and off lights to controlling the background music in your home. This means that IoT-enabled devices can collect data on users' daily habits, such as when they wake up, leave the house, and return, etc. If this information is compromised, the consequences can be disastrous. To avoid such scenarios, we must strengthen the security of our IoT devices and protect them from cyber-attacks. The current study focuses on how IoT devices will pose a threat to large organizations and how they are dependent on the company's and its employees' behavior. Devices such as smart cameras, smart lights, and smart instruments, among others, can control the entire environment of a business. These features can make an employee's or manager's life easier by making it easier for them to keep track of tasks, lighting and air conditioning in their offices, and so on. This will soon become a daily requirement where you interact with such IoT devices on a daily basis. This also implies that the security of such companies is based on the security of IoT devices, as data from IoT devices can be used by rival organizations for their benefit, such as making the meeting room uncomfortable for the clients and resulting in the deal being closed, or taking control of a smart TV in a conference room with an inbuilt camera and remotely recording the confidential information or capturing documents or discussions using the security camera, etc. The next issue is related to employees, where the employee can connect their smart devices that are connected to their home network to the enterprise network, which basically means that if the employee's home network is compromised, it may end up compromising the enterprise network via that smart device, as IoT devices are based on trust, so if a specific trusted node is compromised, it can cause some serious issues. These types of concerns can be avoided while also being unavoidable, as we live in an era where devices are remotely connected to each other via the internet. To avoid such situations, we must improve the security of our smart devices, the security of our IoT networks, and intrusion detection in such networks.

Output: corroborate


Input: Claim: Electric vehicles produce zero tailpipe emissions, reducing air pollution. [SEP] Text: It appears, however, that the current recharging times for overnight e-buses presents a problem since it is likely that a significant number of recharging points and a massive recharging power would be needed to recharge the batteries of a large fleet in time for the next day’s service. This could potentially be an issue for the electrical grid infrastructure if the number of buses grows significantly, while this would not be a problem for FC buses because of their short refuelling time. Fuel availability: All three battery electric bus technologies use electricity to recharge their batteries. This electricity could be central managed and distributed locally through the local electricity grids; however, widespread electric bus deployment could significantly stress this infrastructure. FC buses will likely require the development of a comprehensive distribution network for hydrogen, although on-site hydrogen production has been demonstrated. Additionally, hydrogen fuel storage would also create additional cost. Clean source: Real zero emissions bus technology needs to be clean throughout the manufacturing process, fuel production and bus operation. Currently, battery electric and FC bus technologies can achieve zero operating emission but the lifetime emissions are much harder to quantify. It is hard to forecast how the emissions from new technology manufacturing will change, but the fuel production method can be roughly estimated. In the UK, the GHG emissions for electrical energy were 0. 44932 kgCO2/kWh in 2014 [92]. This is likely to change as the UK’s energy mix changes, where in 2015, 24. 6% of electricity was generated from renewable energy sources [93]. Similarly, for FC buses, the source of hydrogen is critical in determining the overall emissions. Currently, about 96% of hydrogen is derived from fossil fuels [94] which results in 13. 7 kgCO2/kgH2 [95]. Despite this, investigations into the use of renewable energy for hydrogen production through the process of electrolysis have been carried out offering potential for a low carbon source of hydrogen. Currently, electricity for battery electric buses is a cleaner fuel than hydrogen for FC buses. Cost: Both electric and FC buses have higher capital costs than a conventional diesel bus; however, FC buses are currently far more expensive than electric buses. The capital cost of electric buses is somewhat dependant on the type of operation expected, where overnight buses will have higher costs than opportunity and trolley buses due to the increased battery capacity.

Output: contrast


Input: Claim: Soil microbes can enhance plant health by competing with pathogens. [SEP] Text: • “There are many great educational resources on YouTube that can help you get a basic understanding of biochemistry,” says Nate. “I watched a lot of videos throughout my education. As you get started, it can feel like learning a new language, and sometimes it can feel overwhelming. If you keep striving to understand the concepts, fluency will come with time. ” Have a look at Khan Academy’s explanation of the nitrogen cycle. • Study for a bachelor’s degree in biochemistry or a related field such as biology, molecular biology or biomedical engineering. However, Nate recommends choosing the classes that inspire you. “Personally, I’ve found that my degree in philosophy, focused on advanced logic and philosophy of science, has been indispensable to designing effective experimental strategies,” says Nate. “Research takes all kinds, so my best advice would be to follow your passion and keep an eye open for where your expertise fits in. ” • Try to gain laboratory experience whenever you can, such as through a summer placement at a university or an internship at a pharmaceutical company. To work in research, you will need to complete a master’s degree and a PhD after your bachelor’s degree. • “Taking any computer science classes will position you well to make use of machine learning and other computational tools that are revolutionising the field of biochemistry,” says Nate. • If you are a high schooler in the US and come from a community, have a look at University’s ‘College Leaders’ (EXCEL) programme, which allows students to conduct their own mini biochemical project. Explore careers in biochemistry • has some great information on the field of biochemistry, as well as information on the differences between working in academia, industry, government or for a non-profit organisation. • The US Bureau of has a useful page on what being a biochemist involves, as well as a list of similar occupations. • According to Payscale. com, the average annual salary for a biochemist in the US is around $70,000. Who or what inspired you to become a scientist? I’ve always wanted to be a scientist. was 5 years old, my parents got my older brother a chemistry set for Christmas, and, even though I was well below the age recommendation, I was far more excited about this gift than he was.

Output: pass


Input: Claim: IoT security protocols help prevent unauthorized access to connected devices. [SEP] Text: The remainder of project is structured as follows: Section 2 of the Research papers we studied and method they have used for detection intruding devices, Section 3 of Information gained about method and usage in a table, Section 4 or the method we used for detection of unauthorized devices, Section 5 Implementations of Model and how we proceeded, Section 6 of the outputs obtained from the model, Section 7 Conclusion, Section 8 Future Work. II Literature ReviewA. Yahyaoui, T. Abdellatif and R. Attia, "Hierarchical anomaly based intrusion detection and localization in IoT," 2019 15th Communications & Conference (IWCMC), 2019, 10. 1109/IWCMC. 2019. 8766574. In this paper, a hierarchical network architecture is used to monitor a WSN deployed in a hostile environment for event detection purposes. This is done to protect WSNs from common threats such as eavesdropping and DoS attacks. These nodes are generally not tamper resistant, and if tampered with by an attacker, it can affect the roles it performs, thereby affecting the entire network. WSNs typically rely on neighboring nodes to forward data, but due to malicious data flow, packets can be dropped. Hierarchical anomaly detection and localization (HADL) can detect IP intrusions as well as WSN routing intrusions. employs deep learning techniques to protect the network from IP intrusion; these IDS components can be requested at any time by the base station. The training phase of these models takes place on cloud servers. Instead of running the SVM on all nodes, this system only runs it on nodes with a high probability of anomaly in a top-down fashion. Every node has a deactivated SVM function that is activated when an attack is detected. The model is trained by collecting data from a system that has not been attacked. Cluster heads carry out the training phase, and the base station carries the data from all cluster heads, which is the data from the entire network; this training phase is established on a regular basis, according to a time window. When a packet arrives at the base station, the SVM determines whether it is normal or abnormal based on the most recent model version. If an abnormal packet is detected, the trust score for each cluster is computed in order to locate the suspected clusters in the network. This model is capable of detecting anomalies at a rate of more than 95%.

Output: corroborate


Input: Claim: EV batteries last indefinitely without needing replacement. [SEP] Text: Review 10. 20935/AcadEng7355Special IssueRecovery of from Primary and ReceivedJune 15, 2024AcceptedSeptember 12, 2024PublishedOctober 10, 2024Academic editorsProf. Mohamed M. this 2024. T. , & Burat, F. (2024). The recent developments in EV batteries and REEs recovery processes from spent NiMH batteries, 1(4). Tülin, and Fırat Burat. “Developments in EV Batteries and REProcesses from Spent NiMH Batteries” 1, no. 4 (2024). doi:10. 20935/AcadEng7355. VancouverUlucan T, Burat F. The recent developments in EV batteries and REEs recovery processes from spent NiMH batteries. 2024;1(4). T. and Burat, F. (2024) “The recent developments in EV batteries and REEs recovery processes from spent NiMH batteries. ” Academia Engineering, 1(4). doi: 10. 20935/AcadEng7355. Publication dates & DOIReceivedJune 15, 2024AcceptedSeptember 12, 2024PublishedOctober 10, 2024DOI Related 4. 0/ vehicles (EVs) are becoming more popular than internal combustion engines for reasons such as ease of use, durability, efficiency, and speed. Electric motors aim to improve the efficiency of energy storage systems and be more environmentally friendly. Due to the growing population, the number of vehicles in use is also increasing, leading to higher carbon dioxide (CO2) and hydrocarbon emissions. This demand has positively affected the battery market in the EV industry. Battery electric vehicles (BEVs), hybrid electric vehicles (HEVs), and plug-in hybrid electric vehicles (PHEVs), along with lead-acid batteries, nickel–metal hydride (NiMH) batteries, and lithium-ion batteries, are frequently preferred in the EV industry. NiMH batteries contain approximately 35–50% nickel (Ni), 5–20% rare earth elements (REEs), and 10% iron (Fe) by weight. Considering the supply and demand gap for REEs, often called “vitamins of modern industry”, the recovery of REEs from waste NiMH batteries, which contain high amounts of these elements, becomes important. In this review 1.

Output: contrast


Input: Claim: Soil microbes can enhance plant health by competing with pathogens. [SEP] Text: So, my parents spent a lot of time supervising me while I mixed the colourful chemicals, and ever since then, I’ve wanted to be a researcher. Coming from a small, rural town, I didn’t really have any examples of scientists growing up, but I was fortunate to have the support of family, friends and mentors who have all encouraged me to find what I want to do and pursue it. It wasn’t until the summer after my second year at the University of Missouri that I had the opportunity to participate in research. Assuredly, I am in this position today because of the mentorship of Baker and Braun, who both believed in me and provided me with the opportunity to chase my curiosity. What experiences have shaped your career path? My biggest eureka moment, so far, was probably looking at the model of the NifL protein structure I created. To build the model, I had to bring together knowledge from 30 years of scientific literature and integrate this with newer bioinformatic techniques. It was like putting together a 5,000-piece jigsaw puzzle! The whole process took several months, but when everything fell into place, it revealed a picture that showed us so much more than we thought we knew at the time. What has been the worst advice you have been given? “Drop philosophy – you’ll never use it. ” “Give the problem time – it’ll figure itself out. ” What attributes have made you successful as a scientist? Curiosity and persistence. I’ve always been curious about biology and what makes organisms functional and adaptable, and it’s this curiosity that pulled me in initially. Research can be slow and difficult though, and success requires persistence and hard work. What are your proudest career achievements so far? My proudest achievement is independently securing funding for my graduate research by applying for and being awarded the US Department of - Doctoral fellowship. Nate’s top tips 1. Believe in yourself and don’t be afraid to fail. graduated high school, I honestly didn’t think I was capable of understanding chemistry, and the fear of failure associated with this delayed me from pursuing a position in research. You’re capable of more than you think you are. 2. Follow your passion. Success requires hard work, but if you follow your passion, the work will be fun along the way.

Output: pass


Input: Claim: IoT security protocols help prevent unauthorized access to connected devices. [SEP] Text: [1] Advantages: The proposed method is very optimal and scalable in terms of power management and functionality. Disadvantages: Because the network's training phase takes place on the cloud, if the cloud is compromised or cannot be accessible for whatever reason, the model will cease progressing, potentially resulting in the failure to detect specific attacks. J. Bassey, D. Adesina, X. Li, L. Qian, A. Aved and T. Kroecker, "for IoT Devices based on RF Fingerprinting using Deep Learning," 2019 Conference on Fog and Computing (FMEC), 2019, 10. 1109/FMEC. 2019. 8795319. In this paper, we will defend and protect against unauthorized device intrusion. Surveillance is Being Considered. This is due to the difficulty of impersonating RF features in comparison to mac address and Identity. The difficulties with this approach are as follows: If the device is the same model as the authorized device, the signal characteristics will be nearly identical. The second challenge is that, while most data-driven approaches rely on data from all classes of interest to train the model, the RF traces of intruders are not available for training practise in this method. The third challenge is that changes in channel conditions can cause variations in RF signal. To address the aforementioned challenges, they implemented a deep learning-based detection scheme. Which specifically rely on the fact that RF features are unique to devices at the physical layer as a result of hardware imperfections caused during product manufacturing. These distinct RF signals for each device are referred to as fingerprints. Convolutional neural networks are used to distinguish these fingerprints and use them to identify unauthorized IoT devices. The CNN is trained using RF traces from authorized devices, with the primary goal of extracting device features from the RF traces. The CNN Model's accuracy is determined by the softmax outputs of the training data. The better the network's accuracy, the more accurately the features will be extracted. This extracted data is then de-correlated and dimensioned before moving on to the next step, clustering. This is done to reduce collinearity and improve clustering. The devices are separated or distinguished based on clusters; if the number of clusters exceeds a certain number of authorized devices, unauthorized devices are detected; this method has been tested with six zigbee devices, five of which are authorized and one of which is unauthorized.

Output: corroborate


Input: Claim: EV batteries last indefinitely without needing replacement. [SEP] Text: release of greenhouse gases, which cause global warming, is a critical issue that demands worldwide action. Renewable energy sources are being proposed as substitutes for fossil fuels. As a result, advancements like cleaner gasoline engines, electric vehicles (EVs), plug-in hybrids, fuel cell cars, and other environmentally friendly transportation options are viewed as future possibilities [1]. The transportation sector is one of the major contributors to the increase in greenhouse gas emissions. The automotive industry is closely monitored as one of the largest contributors to global carbon emissions into the atmosphere. Therefore, researchers have had to consider a paradigm shift due to the unstable prices of fossil fuels and environmental issues. Today, EVs are emerging as a revolutionary option for transportation in the automotive sector, and a lot of research is being done on this subject. They offer advantages such as ease of use, fewer moving parts, and less heat generation [2]. The higher efficiency of EVs relative to conventional vehicles is largely due to the fact that the conversion efficiency in electric motors specifically, from the battery to the motor, is nearly 100%. In contrast, internal combustion engines achieve an efficiency of only about 30–40%. When assessing efficiency from the standpoint of energy transmission from the battery or fuel tank to the wheels, this process is typically referred to as “tank-to-wheel” [3, 4]. In addition, EVs have higher torque and offer fast starting and stopping capabilities. With developments in renewable energy systems, the EV market is expected to become a significant market over time [2]. EVs’ impact on the energy industry, policy, technical barriers, and power systems is also notable [3]. Figure 1 shows global sales of EVs between 2010 and 2022 [5]. Global sales of EVs are projected to increase significantly, from 10. 5 M in 2022 to over 31 million units in 2027, representing a growth of nearly three times. This growth is projected to more than double from the 2027 level to over 74. 5 M by 2035. Despite this significant increase in EV sales, the share of EVs in the global vehicle fleet will remain limited due to the existing large fleet of internal combustion engine vehicles (ICEVs) [6–8]. Given the estimated 1. 33 billion light vehicles in circulation worldwide and accounting for standard scrappage rates, EVs are expected to account for only 15% of the global vehicle fleet by 2030.

Output: contrast


Input: Claim: Soil microbes can enhance plant health by competing with pathogens. [SEP] Text: 1 IntroductionCarrion is an ephemeral but highly nutritious resource for many organisms, so-called scavengers (e. g. Barton et al. 2013; DeVault et al. 2003; Wilson and Wolkovich 2011). Carrion decomposition has potentially far-reaching effects on nutrient cycling, a key driver of ecosystem functioning (Ngai and Srivastava 2006). Animals play a crucial role in this cycle by accumulating large amounts of nutrients in their bodies, collected over long timespans and large areas (Doughty et al. 2016). These include essential elements such as cobalt (Co) and selenium (Se), which are scarce and hard to gather for all lifeforms (Crowe and Bradshaw 2014). When animals die, their bodies—including all the accumulated elements—enter the detritus pool in the form of carrion at a single point in time and space (e. g. Barton et al. 2013), marking the start of the decomposition process. While large parts of carrion decompose through consumption by scavengers and decomposers, some parts may leak into the soil in the form of ‘carrion fluid’; a mixture of bodily fluids, decomposition products and microbial byproducts that drain from the carrion. This has been shown to alter local soil concentrations of macronutrients (e. g. Bump et al. 2009; Barton et al. 2016; Keenan et al. 2019; Macdonald et al. 2014; Parmenter and MacMahon 2009; Quaggiotto et al. 2019). For instance, Benninger et al. (2008) found increased nitrogen (N) and phosphorus (P) concentrations in the soil beneath decomposing Wild boar (Sus scrofa) carcasses. Towne (2000) found higher N concentrations at carcass sites after one year of decomposition. Likewise, Melis et al. (2007) found increased calcium (Ca) concentrations in the soil underneath European bison (Bison bonasus) carcasses. Such leakage of carrion fluid may positively affect plant growth in the close vicinity of decomposing carrion (Carter et al. 2007; Towne 2000).

Output: pass


Input: Claim: IoT security protocols help prevent unauthorized access to connected devices. [SEP] Text: This method achieves detection accuracy of up to 78 %. [2] Advantages: In a small size network with a small number of IoT devices, it is simple and efficient. Disadvantages: In a network with many IoT devices, the RF signals from multiple IoT devices may interfere, causing the system to underperform. E. Anthi, L. Williams, M. Słowińska, G. Theodorakopoulos and P. Burnap, "A for IoT Devices," in IEEE Internet of Things Journal, vol. 6, no. 5, 10. 1109/JIOT. 2019. 2926365. The proposed system in this paper aims to identify multistage attacks, which are more complex and difficult to detect. To that end, the IDS presented in the paper is tested against 12 attacks from the six categories in the IoT domain, with four scenarios for multistage attacks. They profiled eight IoT devices so that if unusual activity is detected, the cyber attack will be detected as well. They also developed a machine learning model that can distinguish between different types of attacks not only by separating malicious traffic but also by identifying the type of attack that has occurred on the system. These two critical factors can aid in determining the severity of the attack. The proposed IDS architecture is made up of three layers. The first ML layer's goal is to identify and scan network devices based on their MAC addresses and classify them based on their network behaviour. The second ML layer's goal is to determine whether the traffic or packets exchanged are malicious or benign. If a malicious packet is detected in the second layer, the third layer categorises the attack as one of four types. As a result, the output during the attack will be as follows: 1) The device under attack's MAC address 2) Determine whether the packet is malicious. 3) The type of attack that occurred. A week's worth of traffic from authorized devices was captured using the tcpdump tool for benign data. On IoT networks, various types of attacks such as DoS, DDoS, spoofing, and so on were used to collect malicious data. To avoid overfitting of the model, a bash script was implemented to generate randomness in the attack pattern and the order in which the attacks are performed.

Output: corroborate


Input: Claim: EV batteries last indefinitely without needing replacement. [SEP] Text: As the transition to EVs accelerates, this is expected to increase to around 30% by 2035 and 50% by 2042. Despite these positive growth projections, further technological development of EVs is vital for their wider adoption and increased efficiency in the global vehicle fleet [6, 8, 9]. Figure 1 Global sales of electric vehicles from 2010 to 2022 [5]. To assess the technological development of EVs, it is possible to measure their efficiency in terms of kilowatt-hours (kWh) consumed per 100 miles (161 km), which is comparable to efficiency measurements of gasoline-powered vehicles in miles per liter [6]. According to Wang et al. [10], the efficiency of EV batteries is the ratio of the amount of energy required to charge a battery to the energy obtained during discharge. The efficiency of EVs, i. e. , how far they can travel with the same amount of electricity, depends on several factors. The current fleet of EVs, which have no internal combustion engine and run on small batteries, typically offers a range of 150–200 km. Theoretically, the range of EVs could be increased by doubling or tripling the battery mass. However, this would significantly increase the cost of EVs. Moreover, given the weight of the batteries, such an increase would require a more robust chassis. Nevertheless, most EVs are designed to be small and light, suitable for urban traffic, rather than large and heavy. The ability of EVs to achieve longer ranges depends to a large extent on adopting new material systems, increasing energy density, and improving production capacities through research and development (R&D) activities [6]. The upcoming generation of EVs may feature distinct vehicle architectures and weight distributions, which could influence the vehicle’s overall crash performance. Central to this shift in vehicle design is the electric powertrain. The battery system, in particular, due to its substantial volume, distributed configuration, and significant mass, serves as a key factor in driving the adoption of new materials, assembly techniques, and methods for dissipating crash energy within the vehicle structure. Compared to ICEVs, battery electric vehicles (BEVs) face challenges such as higher costs and limited driving range. Both of these factors are largely influenced by the vehicle’s battery system. The costs associated with the battery system are divided among various components. Figure 2 illustrates the projected long-term evolution of battery system costs as outlined by [11, 12]. Figure 2 Improvement of battery system costs [11, 12].

Output: contrast


Input: Claim: Soil microbes can enhance plant health by competing with pathogens. [SEP] Text: However, animal bodies also contain a wide range of non-macro-elements, including elements that are essential for plants and animals, and some that are ecotoxic and may impede plant growth (Robinson et al. 2009). It has not been comprehensively examined how leakage of these elements influences soil elemental concentrations beneath carrion (Perrault and Forbes 2016). As a result, how multiple elements may contribute to carrion-driven local soil fertility and subsequent plant growth remain unknown. In this study, we examined the leakage from carrion of a wide range of chemical elements, including essential and ecotoxic elements, and how this affected plant growth. We performed a controlled lab experiment in which we manipulated the duration of fluid leakage from the exact same carrion type—i. e. lab-raised mice (Mus musculus) -, measured a wide range of elemental concentrations (both essential and ecotoxic elements) in initially mineral-poor substrate below the carrion, and grew identical plants (F1 maize) in these substrates that were only affected by carrion fluid leakage to assess effects on plant growth, in the exact same habitat. We excluded scavenger activity to ensure that the source of leakage was controlled. 2 Material and MethodsWe performed the experiment in three steps. First, we established 378 transparent plastic containers that were half filled with bare sand (“silver sand”), which is mineral-poor and does not by itself represent a suitable growing substrate to plants. Containers were covered with fine-meshed perforated plastic lids to exclude insects, and placed on worktables in a tunnel greenhouse at & (see Fig. S1 for a schematic overview of the experimental design). We randomly assigned 360 of these containers to one of six treatments, in which carrion was placed and left to decompose for 14 to 24 days (six treatments with 60 replicates each). As carrion, we used identical frozen mice that were purchased at an online pet food store (www. animalfoodexpress. nl) in a single batch. The remaining 18 containers served as a control, i. e. received no carrion. Carrion was individually weighed before and after the decomposition period to calculate the weight decline per replicate, analyzed using a linear model.

Output: pass


Input: Claim: IoT security protocols help prevent unauthorized access to connected devices. [SEP] Text: Following that, the system was able to identify the attacks and categorise them into four distinct scenarios: 1) Network Scanning, the attacker performs a quick scan on the network, followed by a more in-depth and targeted attack on a device, with a 0. 5 chance that a second attack will occur. 2) and DoS, which entails quick scanning of the network with some of the most common DoS attacks. 3) and MITM, which consists of a quick scan followed by an MITM attack using ARP spoofing. 4) with IoT-toolkit, this attack is carried out with the help of the IoT-toolkit and directly targets TP-Link devices, performing toggle/get info. [3] Advantages: Has the capacity to distinguish between different forms of multistage attacks, allowing network administrators to make quick decisions. Disadvantages: If the attacker attempts to impersonate one of the network devices by using that device's mac address, the system will be unable to distinguish between the attacker and that device. G. W. Cassales, H. Senger, E. R. de Faria and A. Bifet, "IDSA-IoT: Architecture for IoT Networks," 2019 IEEE Symposium on Computers and Communications (ISCC), 2019, 10. 1109/ISCC47284. 2019. 8969609. This paper introduces a distributed intrusion system capable of handling hundreds of objects and devices. The main contributions are an intrusion detection architecture that leverages cloud edge capabilities and low latency with increasing scalability, as well as evaluating network traffic based on patterns using novelty detection methods. Novelty detection is a technique that assists us in identifying different patterns in samples. This can aid in detecting early activities during a device's intrusion, allowing necessary actions to be taken sooner. In common machine learning methods, a few steps are required to retrain the model, which delays the application of newly obtained knowledge and consumes computational power, whereas ND quickly adapts to changes in the network and quickly applies it. ND is divided into two phases: static and offline. The static phase uses the dataset to learn the new concepts acquired, while the offline phase uses the dataset to learn the new concepts acquired. The factors that matter in training are how many classes are associated with known concepts, how many classifiers are used, and the algorithm used to perform learning.

Output: corroborate


Input: Claim: EV batteries last indefinitely without needing replacement. [SEP] Text: Based on this cost projection, in 2010, a 20 kWh battery system was projected to cost $15,000. Approximately two-thirds of these costs were attributed to raw materials for the cells, material processing, and cell production, while the remaining one-third covered system assembly and the manufacturing of peripheral components. The IWF (Institute of ) identified reducing assembly costs as a key focus within the proposed methodology. Lithium-ion (Li-ion) batteries have a gravimetric energy density 100 times lower than gasoline, making it necessary to design large, high-mass systems to achieve adequate energy capacity in BEV battery systems. The lightweight design of the battery system is underpinned by the consideration of the relationship between total vehicle mass and energy consumption. This relationship exhibits an almost linear trend for vehicle masses ranging from 700 to 1,700 kg [11]. For instance, decreasing the vehicle mass from 1,600 to 1,280 kg can lead to approximately 15% energy savings. This reduction has the potential to lower the required drive power and battery capacity of the vehicle [11, 13]. Consequently, the overall structural mass of both the battery and the vehicle can be minimized. This approach involves an iterative process aimed at reducing vehicle weight across four primary stages. Figure 3 shows this relationship [11]. Figure 3 Lightweight design for electric vehicles [11]. Product-level carbon emission accounting for automobiles encompasses the carbon emissions associated with all vehicle and automotive components, including both direct and indirect emissions across the entire life cycle of automotive products. This includes processes such as vehicle use, assembly, component manufacturing, raw material procurement, logistics, and recycling. For instance, prior studies have explored the life cycle carbon emissions of components like the ignition coil, fuel tank, and body steel in ICEVs. In the case of EVs, particularly BEVs, researchers have focused on analyzing the life cycle carbon emissions of power batteries [11]. The carbon footprint of EVs primarily arises from electricity consumption during vehicle operation. Assessing the carbon footprint of automotive products across their entire life cycle allows for a comprehensive comparison of the environmental impacts of vehicles utilizing various energy sources and offers a theoretical and data-driven foundation for future emission reduction strategies in the automotive industry [14]. Road transport is the predominant source of carbon emissions within the transportation sector. Data from the Agency (IEA) indicates that in 2021, global road transport emitted 5. 86 Gt of carbon dioxide (CO2), representing 76.

Output: contrast


Input: Claim: Soil microbes can enhance plant health by competing with pathogens. [SEP] Text: Second, we took soil samples—5 cm of top soil directly beneath the carrion—from a selection of containers that we used in the previous step, for measuring the elemental concentrations in the substrate. The selection included, for each treatment, the eight containers with the highest and the eight with the lowest carrion weight loss. We also sampled 13 of the 18 control containers. We measured 23 elemental concentrations in total. N and carbon (C) were analyzed using the Dumas method (Shea and Watts 1939). For the other elements, samples were prepared with microwave digestion with 5 mL 65% nitric acid (HNO3) and 2 mL 30% hydrogen peroxide (H2O2). We used inductively coupled plasma optical emission spectrometry (ICP-OES) to measure concentrations of nine elements (Van de Wiel 2003): aluminum (Al), Ca, iron (Fe), potassium (K), magnesium (Mg), sodium (Na), P, sulfur (S), and silicon (Si). We used inductively coupled plasma mass spectrometry (ICP-MS) to measure the concentration of twelve more elements (Van de Wiel 2003): chromium (Cr), manganese (Mn), Co, nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), Se, strontium (Sr), molybdenum (Mo), cadmium (Cd), and lead (Pb). Four of these elements—Al, As, Cd, and Pb—are commonly assessed ecotoxic elements, while the other 18 elements are essential to plant and animal growth (e. g. Gasparik et al. 2004; Wenting et al. 2023). We used Mann–tests to compare concentrations between carrion-treated and control substrates, and reported the median elemental concentrations and 25% and 75% quantiles, and test statistics per element. Last, we tested whether soil enriched by elemental leakage from carrion enhanced plant growth. This was done in a greenhouse at in Aug-Oct 2021. We pregerminated F1 Zea maize seeds on vermiculite and sorted the sprouts by size after six days. Sprouts of the same size were potted in the carrion-treated and control substrates. The plants were watered every other day with rainwater until we harvested them after 44 days.

Output: pass


Input: Claim: IoT security protocols help prevent unauthorized access to connected devices. [SEP] Text: The architecture is based on stream processing techniques; these processing algorithms run on the network's edge, close to IoT devices and sensors, preventing data from moving towards the network's core. This aids in intrusion detection at low latency and eliminates the need to send all traffic to be analysed, which is inefficient in large networks with hundreds of devices. Only the data required for network evolution will be sent to the network's centre. The kyoto 2006+ dataset, which contains data collected from 2006 to 2015, is used for this project. This information was gathered using 348 honeypots of various types. This dataset contains 24 attributes and four labels, three of which were generated by malware, and the fourth by malware that distinguishes between known and unknown attacks. [4] Advantages: Capable of handling a large number of devices on a network while keeping latency low. Disadvantages: In comparison to the traffic travelling via such a huge network, the model evolution process takes a long time. Thamilarasu, Geethapriya & Chawla, Shiven. (2019). Towards Deep-Learning-Detection for the Internet of Things. Sensors. 19. 1977. 10. 3390/s19091977. The goal of this paper is to develop a secure, portable, and ready-to-deploy security system capable of providing an effective solution in a large-scale IoT network. The system proposed in the paper is known as the Integrated Intrusion-Detection (IID) system, and it operates independently of devices, protocols, and network structure, requiring no prior knowledge of network threats. This IDS was created using AI to protect against attackers. They have also created a framework that is capable of adapting to changing threat landscapes in order to detect malicious activity. The IDS in the paper is primarily based on techniques, which outperform many other methods in various other domains that are unstructured and generate heterogeneous patterns. They also offer more functionality than other machine learning techniques because they can extract useful features from the provided dataset and improve on them. They construct the feed forward in the DNN to create a perceptual learning model using a Network (DBN). The reason for this is that the DBN layers can be trained using unsupervised learning, and then the DNN model is created using unsupervised learning, which is faster than most supervised learning methods.

Output: corroborate


Input: Claim: EV batteries last indefinitely without needing replacement. [SEP] Text: 1% of the total emissions of 7. 7 Gt. Petroleum products, which serve as the primary energy source for road transport, accounted for 90% of the sector’s energy consumption, whereas electricity contributed less than 1% to the energy supply [14–16]. The evaluation of vehicle carbon emissions should extend beyond exhaust emissions observed during the operational phase to encompass the environmental impacts of vehicle products from a life cycle perspective. Currently, the primary types of road vehicles include and hybrid electric vehicles (HEVs) [14]. As of 2021, life cycle CO2 emissions, encompassing production, manufacturing, material production, and maintenance processes are estimated at 22. 4 tons for EVs. In contrast, the life cycle CO2 emissions for gasoline ICEVs are 39. 7 tons. Substituting gasoline ICEVs with EVs could reduce carbon emissions per vehicle by 43. 4%. The electrification of vehicles plays a crucial role in diminishing life cycle carbon emissions. Historical data from 2012 to 2021 indicates that each additional million EVs could lead to a reduction of 7. 28 Mt in life cycle carbon emissions and 12. 8 Mt indirect carbon emissions from fuel combustion in road transport. Consequently, vehicle electrification is increasingly recognized as a necessary trend for achieving carbon neutrality targets, and EVs are anticipated to progressively replace ICEVs within the road transport sector [14, 17, 18]. However, EVs may not be as environmentally friendly as anticipated, as their life cycle carbon emissions remain relatively high, accounting for 56. 4% of those from gasoline ICEVs. While EVs exhibit significantly lower carbon emissions during their operational phase compared to gasoline ICEVs, contributing to their overall reduced carbon footprint, the emissions associated with EVs during this phase are heavily influenced by the cleanliness of the electricity grid. Furthermore, EVs incur substantially higher carbon emissions than ICEVs during the material production phase. Research indicates that batteries play a crucial role in the carbon emissions of EVs. The elevated energy consumption and emissions associated with battery production result in higher life cycle carbon emissions for EVs during the material production stage compared to conventional ICEVs [14]. EVs require increased attention to carbon emissions during material production and component manufacturing, whereas ICEVs tend to focus on economic and environmental performance during operation. The lower carbon emissions of EVs during vehicle use are offset by higher carbon emissions associated with battery production in the material production phase.

Output: contrast


Input: Claim: Soil microbes can enhance plant health by competing with pathogens. [SEP] Text: Rainwater in Europe is rich in N (Stevenazzi et al. 2019), a commonly limiting element for plant growth (Ågren et al. 2012), hence we excluded N from further analysis and focused on the other elements. Insects entered the greenhouse and fed on some plants. To account for this source of variation, we scored the amount of insect damage for every plant before harvesting by five levels: plants (1) that died prematurely; (2) without insect damage; (3) with 0–30% insect damage; (4) with 30–70% insect damage; and (5) with more than 70% insect damage. We dried the harvested plants at 70 degrees Celsius for 48 h, and weighed them with a precision of four decimals to determine the plant biomass. We used a linear mixed-effects model with damage level as random factor to compare the biomass of the plants that grew on the carrion-treated substrates with the controls. We used R version 4. 0. 2 for all statistical analyses (R 2020). 3 Results and DiscussionWe found no systematic decline in carrion weight loss over time (Fig. 1; linear model, df = 5, F = 2. 903, p = 0. 014). Likewise, there were no trends in elemental concentrations in the soil over time, implying that most leakage happened during the preceding 14 days. Therefore, we pooled the leakage-duration treatments and only focused on comparing the leakage versus control substrates. We found that the elemental concentrations were higher in soils with leakage than in the controls (Table 1). The median Mo concentration was even up to 16 times higher with leakage compared to the control (0. 000175 and 0. 000011 µg Kg−1, respectively). All the 13 elements for which leakage elevated concentrations are essential and are moderately or highly mobile (Jigyasu et al. 2020). For none of the ecotoxic elements differences were significant. These findings extend those of previous studies to a much wider range of elements than considered so far (e. g. Barton et al. 2019; Quaggiotto et al. 2019). Our study should be considered as a first step towards a more comprehensive approach to investigate carrion-related nutrient fluxes. Fig. 1Carrion weight decline after 14 to 24 days of decomposition time in a controlled experiment.

Output: pass


Input: Claim: IoT security protocols help prevent unauthorized access to connected devices. [SEP] Text: Because the system requires data to detect malicious data, a database is required in the system to store this data. All communication will take place via the internet and intranet. The collected data will be processed by the data processing module, which will detect the first attack using feature classification. The dataset will be divided into two parts based on the classification of the first module: the unidentified dataset in the first part and the training dataset in the second. These datasets will then be transferred to the analysis and detection module, where the training data will be used to train the model and the unidentified data will be used to analyse the model's performance. The generated results will then be sent to the response module, which will act in accordance with the administrator's rules. All of these processes will be recorded in the blockchain of the host that contains the SESS module. To ensure data security, the IDS communicates between systems using blockchain. This will also aid in the development of trust with the other parties who have joined the network by agreeing to a smart contract. [6] Advantages: The system is capable of identifying various forms of assaults based on the information from all the devices since the model is trained based on data from multiple devices using interactive reinforcement techniques. Disadvantages: Because the model can join the network, if someone manages to break the trust, all of the network's participants are at risk. Cosson, Adrien & Sikder, & Babun, Leonardo & Celik, Z. Berkay & McDaniel, Patrick & Uluagac, Selcuk. (2021). Sentinel: A for IoT Kernel-Information. 53-66. 10. 1145/3450268. 3453533. Sentinel, a robust intrusion detection system that works on kernel level information to detect attacks in the IoT framework, was introduced to address the current shortcomings of current IoT networks. Sentinel is a robust intrusion detection system that works on kernel level information to detect attacks in the IoT framework. It is also designed in such a way that it supports various IoT frameworks, making it adaptable to different types of devices or the introduction of new devices into the system. Sentinel is based on the analysis of low-level data obtained by accessing the operating systems of IoT devices, which contain specific patterns for benign and malicious behaviour.

Output: corroborate


Input: Claim: EV batteries last indefinitely without needing replacement. [SEP] Text: As the degree of vehicle electrification increases, it is anticipated that the average proportion of carbon emissions from vehicle material production will also rise. However, for EVs, the carbon emissions during material production could decrease due to the large-scale production of power batteries and related components. In the short term, the automotive industry may see an increase in carbon emissions due to the production of power batteries for EVs. Nonetheless, the benefits of reduced carbon emissions from EVs are expected to be reflected in their future operational use. As the operational phase of vehicles expands, the advantages of lower carbon emissions associated with EVs are becoming increasingly evident [14]. The transportation sector accounts for about 25% of CO2 emissions worldwide. Motor vehicles are responsible for 75% of these emissions. Cars and buses are the largest contributors, accounting for 45. 1%, while freight trucks account for 29. 4%. For this reason, authorities in both developed and developing countries are encouraging consumers to replace conventional vehicles with EVs to reduce the concentration of air pollutants, such as CO2, carbon monoxide (CO), sulfur dioxide, and other greenhouse gases [19]. As the international community aims to achieve net zero emissions by 2050 and focus on Goal 13, the transition to sustainable transport solutions, such as EVs, is imperative. EVs have the potential to reduce greenhouse gas emissions and improve air quality but face barriers, such as high initial costs, inadequate charging infrastructure, range limitations, and fossil fuel-generated electricity. To achieve net zero emissions by 2050 and reduce climate change, EVs need to be adopted as a credible alternative to ICEVs [20]. In sustainable urban design, the advantages of EVs make them a preferred choice for transportation. Various alternative fuel vehicles have been proposed, such as HEVs, plug-in hybrid electric vehicles (PHEVs), BEVs, and fuel cell electric vehicles (FCEVs). EVs have attracted considerable attention in recent years, and their popularity continues to grow. Although BEVs have recently become quite common, the concept has been around for some time. The first experiments with the EV concept were conducted by in 1828, but a rechargeable EV did not appear until 1881, after the invention of practical secondary batteries by engineer and inventor Gustave Trouvé. By 1900, EVs were gaining traction, and the number of EV manufacturers and models increased. In 1912, there were 33,842 EVs registered in the United States, their peak, but ICEVs soon took over [2].

Output: contrast


Input: Claim: Soil microbes can enhance plant health by competing with pathogens. [SEP] Text: The letters indicate significant differences between the median weight decline (see text for statistics)Full size imageTable 1 Elemental concentrations (µg Kg−1) in soils with and without leakage of chemical elements from carrion, reported as 25% quantile—median—75% quantile. Test statistics from Mann–tests are reported. Elements are in alphabetical order and p-values are adjusted using the step-down procedure of Heller and Gur (2011). * indicate the significant elementsFull size tableGrowth of maize was significantly higher on soils enriched with carrion fluid than on control soils (Fig. 2; linear mixed-effects model, df = 1, F = 11. 489, p < 0. 001), with plant biomass being up to nine times higher. Plant growth was not related to concentrations of any elements in particular (multiple regression with backward deletion, F = 2. 593, p = 0. 057). These results indicate that leakage of carrion fluid can enhance net local plant growth. Fig. 2Plant growth on substrates subject to nutrient leakage from carrion versus control substrates. The letters indicate significant differences between the median plant biomass (see text for test statistics)Full size imageWe presume that the enhanced plant growth on carrion-treated soils (Fig. 2) was the result of the net positive effect of all the evaluated elements combined (Table 1). Our experimental design, however, did not allow us to specify the magnitude of the impact on plants per element. We encourage future studies to comprehensively investigate which elements have strongest effects on plant growth. By using rainwater, which is N-rich (Stevenazzi et al. 2019), we were able to eliminate N as a potential limiting factor for plant growth. It has been suggested that N is not likely to be the limiting factor for plant growth in many regions due to long-lasting N deposition (e. g. Siepel et al. 2019). deposition results in skewed proportions between N and scarce essential elements, increasing the importance of carrion decomposition as potential high-quality source of these elements. We therefore consider our results to be relevant in natural systems, especially in systems with high N deposition. Scavengers are a potential key determinant of elemental leakage from carrion, with the capacity to consume carrion before leakage can even occur (e. g. Gutiérrez-Cánovas et al.

Output: pass


Input: Claim: IoT security protocols help prevent unauthorized access to connected devices. [SEP] Text: Sentinel focuses on current information and security systems available in IoT devices, such as RAM usage, CPU usage, process running, and so on, with the assistance of a data aggregation layer, to reduce performance costs. Sentinel operates by installing a linux kernel module on each IoT device, then extracting kernel metrics with a polling application and storing them in a database. Sentinel monitors changes in system-level information and trains a Machine learning model based on detection techniques to distinguish malicious behaviour. Sentinel's framework employs a variety of ML algorithms, including and classifiers. Sentinel's efficiency is tested on two different platforms with 9 different IoT devices in each network, which are then subjected to 5 different types of threats. Using these techniques, Sentinel was able to achieve 96 % accuracy in detecting threats in an IoT network, as well as keeping power usage to a minimum while not affecting device performance, proving its efficacy. [7] Advantages: Because the model is trained using kernel level data, it can identify even the smallest changes in the system environment, ensuring the system's threat detection capabilities. Disadvantages: The method above ignores threats and viruses that are directly connected to the system's boot sector or kernel; in such cases, the system may believe the malicious program is part of the operating system and disregard it. T. Zhang, C. He, T. -S. Ma, M. Ma, and S. Avestimehr, “Federated learning for internet of things: A federated learning framework for on-device anomaly data detection,” ArXiv, vol. abs/2106. 07976, 2021. Based on federated learning The model aims to detect networks without storing much data in the IoT network's core and instead managing at the network's edge. The general idea is that many IoT devices in the network work together to train the autoencoder model for anomaly detection using federated learning. Federating learning can be used to address current security issues in IoT. In this paper, federated learning is used to detect anomalies in an IoT network, and an IDS is developed as a result. The platform used is called FedIoT, and it includes FedDetect, which is essentially a framework for FL that uses adaptive optimizers and cross-round learning for local training.

Output: corroborate


Input: Claim: EV batteries last indefinitely without needing replacement. [SEP] Text: Thanks to advances in energy storage system technology, EVs have gained an important place in a world dominated by ICEVs. EVs are available in various types, such as road and rail vehicles, surface and underwater vessels, electric airplanes, and electric spacecraft. There are two main reasons for the growing importance of EVs: the first is to reduce demand for fossil fuels such as crude oil, natural gas, and coal. Due to the high demand for fossil fuels and an annual consumption rate of 22 billion barrels, oil reserves are estimated to last only 45–100 years. The second is to reduce greenhouse gas emissions. With the increasing number of ICEVs, the amount of CO2 emitted into the atmosphere has also increased. Greater adoption of EVs can significantly reduce CO2 emissions. Furthermore, HEVs emit less CO2 compared to conventional ICEVs [21]. In general, this 2. Electric vehicle types EV types can be categorized into four classes: and FCEVs [19]. 2. 1. Battery electric vehicles BEVs are defined as “fully EVs” because their powertrain consists of a rechargeable battery. Such batteries are more environmentally friendly than conventional energy conversion systems. Charging of these batteries can be done using grid power or any power generation media via a charging plug. Unlike conventional internal combustion engines, the charging process for BEVs takes slightly longer. Using a slower charger, it can take 5–10 hours to fully charge the battery, whereas with a fast charger, it takes about 15–45 minutes. Heat management and battery capacity are the main factors affecting the overall performance of a BEV. The driving range of a BEV is between 160 and 250 km, while some EV models can travel up to 500 km on a single charge. The time required to fully charge the battery depends on the battery capacity, the charging system, and the type of connection used (parallel or serial). HEVs have been proposed by various research groups to replace BEVs to increase travel distance [2, 19]. 2. 2. Plug-in hybrid electric vehicles These vehicles can run on fossil fuels, electricity, or a combination of both and offer several advantages, including reduced dependence on oil, increased fuel economy, improved power efficiency, and lower greenhouse gas emissions. PHEVs can be superior to HEVs in terms of efficiency because the limited and selective use of the internal combustion engine increases overall efficiency.

Output: contrast


Input: Claim: Symbiotic relationships between microbes and plants can improve nutrient uptake. [SEP] Text: Create a new account user Can't sign in? Forgot your username? Enter your email address below and we will send you your username Email* the address matches an existing account you will receive an email with instructions to retrieve your username close | or * Password* Forgot password? Reset it here Keep me logged in All fields with * are mandatory Email* All fields with * are mandatory Already have an account? Login here password must have 8 characters or more and contain 3 of the following: a lower case character, an upper case character, a special character or a digit password has been changed Can't sign in? Forgot your password? Enter your email address below and we will send you the reset instructions Email* the address matches an existing account you will receive an email with instructions to reset your password the verification code Cancel Congrats! has been verified close 10. 1139/b91-012 Get AccessContentsof Botany, Number 1January 19911991. A method for measuring hyphal nutrient and water uptake in mycorrhizal plants. of Botany. 69(1): 87-94. Export 1. Soil compaction reversed the effect of arbuscular mycorrhizal fungi on soil hydraulic properties Go to 2. Is the amount of water transported by arbuscular mycorrhizal fungal hyphae negligible? Insights from a compartmentalized experimental study Go to 3. Inoculation with arbuscular mycorrhiza did not affect growth, root traits or gas exchange of grafted almond saplings when exposed to drought stress Go to 4. Fungi: An Eco-for Alleviation of in Go to 5. Effect of agricultural management practices on diversity, abundance, and infectivity of arbuscular mycorrhizal fungi: a review Go to 6. Response of Tagetes patula L. and Ageratum houstonianum Mill. to Inoculation and Go to 7. The role of arbuscular mycorrhizal symbiosis in improving plant water status under drought Go to 8. An arbuscular mycorrhizal fungus alters soil water retention and hydraulic conductivity in a soil texture specific way Go to 9. Agriculture by under Stress Condition: Mechanism and Go to 10. Exploring the secrets of hyphosphere of arbuscular mycorrhizal fungi: processes and ecological functions Go to 11.

Output: pass


Input: Claim: IoT security protocols help prevent unauthorized access to connected devices. [SEP] Text: These devices are supplied by only authorized sellers and manufacturers, and they are linked to communication protocols recommended by the manufacturer, allowing them to collect legitimate information from the network. Using these methods, two datasets were created: the primary dataset, which consists of 103 files in. pcap format, and the secondary dataset, which consists of 41 such files, for a total of 144 files containing traffic for 24 hours. The process of filtering traffic from these files based on the MAC address was carried out in order to create a classification model for SHIoT devices. The reason for this is that the IP address is provided by DHCP, which can result in changing IP addresses over time. 11 IoT devices were used to detect unauthorized devices in the observed network, which were classified based on the semantic characteristics of the devices and their purpose. Given the ability to identify IoT devices and their purpose, we have significant power in identifying unauthorized devices in a given network. For example, if a person is using IoT devices to track their hand motion, and a third device appears claiming to be used for hand motion tracking, we can conclude that there are false Id IoT devices in the network. A logitboost method, which belongs to Ensemble machine learning techniques and is based on a logistic regression method, was used to develop a multiclass classification model. Ensembles are methods that combine multiple machine learning algorithms that are suitable or function for the same purpose into a single one. [10] Advantages: The ability to separate different network devices based on their functionality provides a great deal of flexibility and security. Disadvantages: The model was created using supervised learning, which means that updating it will take a long time. Additionally, the model does not train itself in real time. network contains a variety of Devices and Sensors that vary in performance, such as and Consumption. Based on this data, we can predict whether or not there are any unauthorized or unwanted devices in the network. This method requires information about the type of devices that will be used in the network because different devices, sensors, and parameters have different power consumption and parameters, which is why the classifiers must be trained with this information in mind. Flow Chart: In this flowchart we have shown how we trained our Model based on their parameters. First we collect the data from IoT devices in an authorized network, then we separate the device based on the type of the information they provide us to train them separately.

Output: corroborate


Input: Claim: EV batteries last indefinitely without needing replacement. [SEP] Text: Furthermore, the internal combustion engine only operates at high speeds, allowing it to achieve the highest efficiency. PHEVs usually run on gasoline, but diesel or ethanol can also be used. PHEVs do not rely heavily on the internal combustion engine to charge the battery like HEVs. Instead, they have a battery pack that can be fully charged by plugging into a standard 120/240 V AC electrical outlet. They also feature regenerative braking, providing an alternative way to recharge the battery. Several studies have shown that PHEVs emit less CO2 and other pollutants when charged from the electricity grid compared to conventional ICEVs and HEVs. PHEVs can therefore reduce emissions in the transport sector in many regions, as long as the electricity grid provides a cleaner energy source than gasoline or diesel. This means that the fuel mix used to generate electricity must be lower than the average emissions of a conventional gasoline car [22]. 2. 3. Hybrid electric vehicles In HEVs, both a gasoline internal combustion engine and a battery-powered electric motor are used to power the vehicle. When the battery is low, the gasoline engine is used to start the vehicle and recharge the battery. These vehicles are less efficient compared to fully electric or plug-in hybrid vehicles. The combination of the battery and electric motor system aims to achieve better fuel economy or enhanced performance compared to a traditional ICEV. This is primarily accomplished by using the less efficient internal combustion engine alongside a much more efficient power source, such as the residual battery [19, 22]. 2. 4. Fuel-cell electric vehicles FCEVs are also referred to as zero-emission vehicles. These vehicles operate on electricity, which is produced from a fuel source. Hydrogen is the primary fuel used in the fuel cells of these vehicles. Fuel cell engines are more efficient for long-distance travel. They offer an extended range, and refueling only takes a few minutes [19]. 3. Battery types used in electric vehicle An essential component of EV systems is a device that stores energy and manages its distribution. Recently, the significance of energy storage systems has been growing. Key factors include the amount of energy stored and the efficiency of energy storage systems. Selecting the appropriate energy conversion method is also crucial. Various energy storage systems are becoming prominent, such as fuel cells, supercapacitors, primary batteries, secondary batteries, and hybrid systems. Figure 4 illustrates the different types of batteries used in EVs [1].

Output: contrast


Input: Claim: Symbiotic relationships between microbes and plants can improve nutrient uptake. [SEP] Text: After root sorption, due to the element's higher reactivity, the biogeochemical behavior of REEs in the soil-plant system is not simply analogous to Ca2+, but may resemble that of other trivalent metals, particularly Al3+ (Ma and Hiradate 2000). Thus root–shoot transport of REE depends on their mobility within the plant (Kovarikova et al. 2019) which is most probably through intracellular complexation with carboxylates (Ma and Hiradate 2000). Based on the above, it seems reasonable that plant species that deploy a carboxylate-based nutrient-acquisition strategy exhibit differences in REE sorption. status of the plants and the quantity and composition of the compounds released should influence the processes during REE mobilization and uptake. In the present study, we conducted a split-root experiment where we cultivated six plant species (Triticum aestivum, Brassica napus, Pisum sativum, Cicer arietinum, Lupinus albus and Lupinus cosentinii) with different P-acquisition strategies and the ability to respond to P-deficient conditions by increased carboxylate release in sand. A split-root approach was used to exclude the direct effects of P-addition on REE availability, i. e. by precipitation as REE-phosphates (Fehlauer et al. 2022; Liu et al. 2022). Thus, one root half received all essential plant nutrients except phosphate, which was supplied to one root half only. Root carboxylate release and shoot element concentrations were measured, to explore the relation between P-nutrition and plant REE accumulation. If we could show such a relation, this would offer the possibility to use shoot REE signatures as an indicator for the involvement of carboxylates during nutrient acquisition. Methods2. 1 Substrates for plant cultivation In this experiment, 120 pots (7 x 7 x 18 cm) were filled with 1. 2 kg of sand. Half of the pots (60 pots) were filled with quartz sand (0. 1–0. 4 mm grain size, 1500 kg m−³), while the other half was filled with a mixture of 75% of quartz sand and 0. 25% of river sand (0. 4–2 mm grain size, 1,320 kg m− 3).

Output: pass


Input: Claim: IoT security protocols help prevent unauthorized access to connected devices. [SEP] Text: Now we calculate the accepted deviation, which is how far the data point is from the allowed maximum distance, which we decided to be 10% greater than the maximum distance, so if the maximum allowed distance is 100%, the accepted distance from the centroid is 110 percent. The acceptedDeviation3 value we got is 0. 088705, we divided it by 5 to scale it in relation to other parameters, so it is not entirely dependent on this one. To compute accepted Threshold value: The accepted after all the calculation is 0. 194489010. Device: Now that we have a new device's data, we can perform all of the operations listed above in a similar manner, with a few changes. To calculate deviation 1: 1 is the predicted CPU Power value using model, PredCPUM1 is the predicted CPU Power value usingmodel and ActCPU is the actual CPU Power value. To calculate deviation 2, first extract the necessary parameters as mentioned above, then predict the number of packets received using the model and round the value to its nearest integer as the value obtained from the model will be a floating point value, and finally deviation 2 = | value of number of - Actual number of packets received |. To calculate deviation 3, first extract the aforementioned parameters, then calculate the distance between the data and the centroid; if the distance is greater than the maximum allowed distance, then deviation3 = distance between centroid and data - maximum allowed distance; if the distance is less than the maximum allowed distance, then deviation 3 = 0. To calculate device threshold: Now we add all of the deviation values to get the threshold, which is defined as If the obtained threshold is greater than the acceptedThreshold, the device is most likely unauthorized and admin will be notified; otherwise, the device is most likely authorized. VI ConclusionWe intend to improve security in IoT-based Sensors and Networks with this project. We are able to classify accepted IoT devices in this project based on their hardware information and the functions they perform. The accuracy of the results obtained from performing regression to predict the number of and CPU Power was 0. 92 and 0. 99, respectively. This means that the following model will be highly accurate in determining the trustworthiness of a node in a network. The proposed method is also extremely fast, determining a node's trust while comparing it to threshold and on-time in an instant.

Output: corroborate


Input: Claim: EV batteries last indefinitely without needing replacement. [SEP] Text: A battery, an electrochemical device, converts electrochemical energy into electrical energy and is crucial for EVs. In recent years, the use of rechargeable batteries in EVs has surged in popularity due to the inconsistency of renewable energy sources, which are unsuitable for situations requiring a continuous and reliable supply. Ideal characteristics for a good EV battery include high specific energy, high charge acceptance rate, high specific power, long life cycle, low self-discharge rate, long calendar life, recyclability, and low cost. Various types of batteries are used in EVs, including lead-acid, nickel-based, and Li-ion batteries [23]. Figure 4 Classification of electric vehicle batteries [1]. Automotive manufacturers globally are making significant efforts to develop vehicles with electric powertrains. Additionally, substantial efforts are being focused on extending vehicle range and energy density while cutting costs. Li-ion batteries have taken the place of NiMH batteries in electric and hybrid vehicles and are now also being utilized in “stop–start” vehicles [21]. Figure 5 illustrates the economic trends for lead-acid, NiMH, and Li-ion batteries within the EV market. These three battery types are the predominant choices for EV applications, and their market share is anticipated to experience substantial growth throughout the forecast period [21, 24]. Figure 6 illustrates the average costs of lead-acid, NiMH, and Li-ion batteries from 2014 to 2022. According to the figure, the average cost of a Li-ion battery pack decreased to $181 in 2022. Advances in battery technology over the past decade have resulted in average cost reductions of 72% for lead-acid batteries, 68% for NiMH batteries, and 82% for Li-ion batteries since 2014. It is anticipated that the cost of Li-ion batteries will decline to $100 per kWh by 2024 [21, 25]. From the perspectives of manufacturers and buyers, battery price and battery cost are defined differently. As the battery market is relatively new to the automotive industry, these values are subject to variation due to numerous factors. Two primary methods are used to evaluate battery cost: the market data survey, which indicates the prices at which manufacturers sell battery packs, and the bottom-up cost model, which encompasses all production-related expenses. Manufacturers then set a price that includes a profit margin. Market analysis suggests that both the market data approach and the cost modeling method can be utilized for determining battery pricing [21].

Output: contrast


Input: Claim: Symbiotic relationships between microbes and plants can improve nutrient uptake. [SEP] Text: Here, a second sand type was added to increase the amount of potentially plant-available elements to one half of the split-root systems. The quartz sand had a pH of 5. 6 (water/solid 1/10) and 1. 1 ± 0. 5 mg kg− 1 calcium lactate-extractable P (van Laak et al. 2018), whereas the mixed sand had a pH of 5. 9 and 2. 1 ± 0. 3 mg kg− 1 P. In both sand types, the total element concentrations were similar (Table 1); however, the sand types differed regarding the distribution of elements in potentially plant-available element fractions indicated by a sequential extraction analysis considering the distribution of elements in five operationally-defined soil fractions according to Wiche et al. (2017a) (Table 1). In these fractions, the mixed sand was characterized by higher concentrations of P, Mg, Ca, Mn and Fe (Table 1). Furthermore, the quartz sand showed higher concentrations of mobile/exchangeable and acid-soluble Al and higher concentrations of mobile/exchangeable LREE. Thus, in quartz sand, these elements are more easily accessible by roots than in mixed sand. However, Al and both LREE and HREE were generally more concentrated in the mixed sand, especially in the more stable fractions 4 and 5, which were also the significant element-bearing fractions of Cd (Table 1). The LREE HREE ratios in both sand types were > 1 (Table 1). In particular, quartz sand exhibited a 12% higher LREE HREE ratio in Fractions 1 (mobile/exchangeable) and a 15% and 33% higher LREE/HREE ratio in Fractions 4 and 5, respectively, where the elements are predominantly bound to amorphous and crystalline structures of oxides and oxide-hydroxides (Table 1). 2 and 3, however, the LREE/HREE ratios were similar between the two substrates. Table 1 Total element concentrations and distribution of elements in exchangeable (F1), acid-soluble (F2), oxidizable (F3) and moderately-reducible (F4) substrate constituents according to Wiche et al. (2017) determined by a sequential extraction method (mean ± sd; n = 10). Differences in means are identified by t-tests with Bonferroni correction.

Output: pass


Input: Claim: IoT security protocols help prevent unauthorized access to connected devices. [SEP] Text: Javascript is disabled in your browser. Please enable Javascript to view PeerJ. Related research -and dynamic access control for the Internet of Things (IoT) based traffic system View 10. 7717/peerj-cs. 471 Published 2021-05-10 Accepted 2021-03-14 Received 2021-01-18 and Analysis of Algorithms, Artificial Intelligence, and Communications, and access control, learning, Social computing Copyright © 2021 Aftab et al. is an open access 2021. Secure and dynamic access control for the Internet of Things (IoT) based traffic system. PeerJ 7:e471 Abstract Today, the trend of the Internet of Things (IoT) is increasing through the use of smart devices, vehicular networks, and household devices with internet-based networks. Specifically, the IoT smart devices and gadgets used in government and military are crucial to operational success. Communication and data sharing between these devices have increased in several ways. Similarly, the threats of information breaches between communication channels have also surged significantly, making data security a challenging task. In this context, access control is an approach that can secure data by restricting unauthorized users. Various access control models exist that can effectively implement access control yet, and there is no single state-of-the-art model that can provide dynamicity, security, ease of administration, and rapid execution all at once. In combating this loophole, we propose a novel secure and dynamic access control (SDAC) model for the IoT networks (smart traffic control and roadside parking management). Our proposed model allows IoT devices to communicate and share information through a secure means by using wired and wireless networks (or Wi-Fi). The effectiveness and efficiency of the proposed model are demonstrated using mathematical models and discussed with many example implementations. of things (IoT) is increasingly gaining more attention due to the increase in the use of IP-based home appliances, including medical and mobile devices. Smart devices are widely used in banking, shopping, and military communication. Figure 1 shows systems based on IoT-like traffic systems, home appliances, medical equipment, and vehicle communication. Today, data security has become a challenging task for security officials, such that data security concerns have been raised during information sharing and communication (Ahanger & Aljumah, 2019). More specifically, communication between sensitive devices or vehicles is highly confidential. Therefore, the information must be secure during communication.

Output: corroborate


Input: Claim: EV batteries last indefinitely without needing replacement. [SEP] Text: Figure 5 The evolving trends in the use of various battery technologies in electric vehicle applications in the [12]. Figure 6 Average cost per kWh of different battery types between 2014 and 2022 [21, 25]. 3. 1. Lithium-ion batteries Li-ion batteries, similar to lead-acid and NiMH batteries, are well-known examples of rechargeable batteries that can be recharged whether fully or partially discharged and are used in EVs and HEVs. Since their introduction to the battery market in 1991, Li-ion batteries have gained significant importance. They are considered the most promising batteries for EVs due to their high energy density and long cycle life. Historically, a major challenge with Li-ion batteries was their limited operational temperature range, which affected performance. However, in recent years, Li-ion batteries have offered superior battery economy due to their high power and energy density ratios. They have become increasingly vital in industrial applications, providing higher voltage per cell, improved life cycles, and greater energy density. Additionally, Li-ion batteries are distinguished by their excellent low-temperature performance, low self-discharge rates, and straightforward charging methods, setting them apart from other battery types. These characteristics make Li-ion batteries the preferred choice for commercial applications. The Li-ion battery market was valued at over USD 24 billion and is projected to grow by over 12% from 2017 to 2024. Stringent government regulations on lead usage, along with the increasing demand for electronic devices, have propelled the growth of the Li-based battery market. Figure 7 illustrates the usage trend of Li-ion batteries across various application areas in 2016 and 2024 [21, 26]. Figure 7 The use of lithium-ion batteries in different applications in 2016 and 2024 [21, 26]. Li-ion batteries are recognized as the most efficient type of battery for various portable electronic devices due to their high energy and power density per unit weight. These batteries typically consist of a cathode, anode, organic electrolyte, and separator enclosed in a metal case and plastic cover. The cathode is usually composed of Li metal oxides such as LiCoO2, LiNiO2, LiMn2O4, and LiNi0. 33Mn0. 33Co0. 33O2, while the anode is typically graphite.

Output: contrast


Input: Claim: Symbiotic relationships between microbes and plants can improve nutrient uptake. [SEP] Text: Means with different letters are statistically significantly different at α = 5% sand Total 358 ± 50a 55695 ± 26334 4143 ± 2016 1792 ± 341 466 ± 245 1773 ± 635 5279 ± 1134 1. 44 ± 0. 56 12. 3 ± 3. 4 3. 6 ± 0. 9 1 < 0. 5 159 ± 15 3. 9 ± 0. 6b 149 ± 13b 0. 4 ± 0. 1b 0. 8 ± 0. 2 2. 1 ± 0. 6a < 0. 05 0. 40 ± 0. 03a 0. 10 ± 0. 01 2 < 0. 5 < 2. 5 2. 1 ± 0. 6b 165 ± 62b 0. 14 ± 0. 12b 6. 5 ± 1. 3b 18 ± 2a < 0. 05 0. 15 ± 0. 03b 0. 05 ± 0. 01b 3 123 ± 10b < 2. 5 2. 9 ± 0. 4b 128 ± 8 0. 19 ± 0. 10b 7. 9 ± 2. 0b 4. 9 ± 0. 6b < 0. 05 0. 10 ± 0. 04b 0. 21 ± 0. 09b 4 26. 2 ± 2. 9 < 2. 5 5. 9 ± 0. 5b 63 ± 30 0. 78 ± 0. 09b 89 ± 14 37. 8 ± 2. 6a 0. 09 ± 0. 01b 0. 60 ± 0. 06b 0. 17 ± 0. 03b 5 < 0. 5b < 2. 5 9. 3 ± 0. 9b 50 ± 14b 0. 64 ± 0. 14b 71 ± 31b 73. 7 ± 7. 2b 0. 09 ± 0. 01b 0. 81 ± 0. 13b 0. 14 ± 0. 03b Mixed sand Total 281 ± 36b 53225 ± 32089 3420 ± 2125 2015 ± 578 334 ± 125 2174 ± 748 5617 ± 1990 1. 38 ± 0. 34 13. 8 ± 1. 9 5. 0 ± 1. 1 1 < 0. 5 164 ± 10 10. 7 ± 2. 3a 339 ± 83a 2. 2 ± 0. 5a 1. 0 ± 0. 4 1. 4 ± 0. 2b < 0. 05 0. 33 ± 0. 04b 0.

Output: pass


Input: Claim: IoT security protocols help prevent unauthorized access to connected devices. [SEP] Text: It means some IoT devices’ security should attain high encryption according to the required security level. On the other hand, some IoT devices’ security can be implemented on a lighter note or low levels (Habib et al. , 2019). Figure 1: Different devices connected through internet in IoT based systems. Download full-size image DOI: 10. 7717/peerj-cs. 471/fig-1 IoT trend is becoming popular day by day. (TSS) is also operated through the internet so that administrators can easily manage traffic while sitting in their offices. In this regard, the TSS’s security is essential, especially when some government or military officials are passing through it. Security agencies focus on the security of vehicles and routes so that the sensitive objects (i. e. , bank cash, weapons, and costly equipment) and government and military officials (i. e. , Prime Minister, President, and Army Chief) are safe. They purchase bullet-proof vehicles for the officials, and the whole route is pre-defined with adequate backup routes. If an attacker or unauthorized person attacks the TSS, then the attacker can jam the entire city. This way, some criminal elements can attack the vehicles for robbery or any other ill deed as the vehicles remain stuck in congestion. Therefore, there is a need for secure and dynamic access control in traffic systems. In this paper, a comprehensive review of various 1. Those aged 21–25 can be assigned role 2, while the remaining operators of age more than 25 years to be assigned Role 3 (Al-Kahtani & Sandhu, 2002). There are specific methods that combine ABAC and RBAC because RBAC is stress-free to run and offers significant scrutiny of go-ahead; however, its role structuring is problematic. Additionally, ABAC gives efficient task structuring, but the breakdown of authorizations after allotting to users is hard-hitting as opposite to RBAC. Alternatively, there is a different approach for the union of RBAC and ABAC that resolves the drawbacks of two concepts and offers a further vigorous, active, significantly better role structuring as well as the scrutiny of permission for the administrator (Kuhn, Coyne & Weil, 2010).

Output: corroborate


Input: Claim: EV batteries last indefinitely without needing replacement. [SEP] Text: Since the anode is usually composed of graphite or activated carbon (C), most of the precious metals in Li-ion batteries are found in the cathode [27]. Batteries are also classified according to the type of cathode material. The first commercially developed cathode materials include LCO (lithium cobalt oxide) (LiCoO2), LFP (lithium iron phosphate) (LiFePO4), NCA (lithium nickel cobalt aluminum oxide) (LiNiCoAlO2), LMO (lithium manganese oxide) (LiMnO2 or LiMn2O4), and NMC (nickel manganese cobalt oxide) (LiNixMnyCozO2, where x + y + z = 1). Today, NMC batteries dominate around 72% of the market and are the most widely used battery type. NCA batteries represent 26% of the market share, with LFP and LMO batteries following [28]. LCO batteries have achieved considerable success in portable electronics due to their high volumetric energy density. These batteries also power EVs such as the Two. However, the high cost driven by limited cobalt (Co) availability has constrained their broader adoption in the EV market. Another cathode material utilized in EVs, particularly in electric buses in China, is LFP. The primary benefits of LFP batteries include stable voltage, high cycling efficiency, and thermal stability, though their lifespan is significantly impacted by moisture. LMO is another commercially used cathode material, valued for its thermal stability and cost-effectiveness. Nonetheless, its low energy density limits its stand-alone use in EVs, leading to its common combination with NMC to enhance energy density. Among the most prevalent cathode materials for EVs are ternary-layered oxides, particularly nickel-rich variants like NMC and NCA. While nickel-rich NMC offers higher capacity, it faces challenges with thermal stability and cyclic performance, which can be addressed through a full concentration gradient approach. Similarly, nickel-rich NCA provides high specific energy but requires additional safety measures due to its lower safety profile before being incorporated into EVs; NCA is notably used in vehicles, such as those produced by Tesla [2].

Output: contrast