Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Optogenetic activation of DAN-c1 during training impaired aversive learning, not appetitive learning (Figure 5b-d). This result is consistent with the effect of D2R knockdown in DAN-c1, indicating that increased, excessive dopamine release during training leads to impaired aversive learning. Figure 5. Over-excitation of DAN-c1 impairs larval aversive learning. (a) A schematic diagram of optogenetic manipulations of neuronal excitability in DAN-c1 during distinct stages in learning. (b-d) Activation of DAN-c1 during training impairs larval aversive learning (b), while keeps appetitive learning intact (d). Unconditioned stimuli used were quinine (b) and sucrose (d). No learning behaviors are observed in the control distilled water (DW) groups (c). Third-instar larvae with ChR2 expression in DAN-c1 are used. ATR, all-trans-retinal. Data are shown as mean ± SEM. Two-way multiple comparisons test, ***p < 0. 001, ****p < 0. 0001. numbers, see Table S4. D2R in mushroom body mediates larval learning through inhibitionWe have shown that D2R in DAN-c1 plays a critical role in larval aversive learning. Since D2Rs are also expressed in soma and axons in most mushroom body neurons (Figure 3h and i), we examined the role of D2R in MB neurons, the center for learning in Drosophila. Knockdown of these D2Rs by D2R-miR impaired both appetitive and aversive learning (Figure 6a). Similarly, optogenetic activation of mushroom body neurons during training led to deficiencies in both appetitive and aversive learning (Figure 6b and d). These deficiencies were not observed in larvae with activation during the resting stage. As D2Rs are inhibitory receptors, and optogenetic activation leads to greater neuronal excitation like what may occur with knockdown of D2Rs, these data show that the inhibitory effect of D2Rs in mushroom body neurons is necessary for larval olfactory associative learning to occur. Figure 6. D2R in mushroom body is necessary for both aversive and appetitive learning.

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: 25 US$/kWh supplied through diesel generators [2]. The total investment for a geothermal power plant mainly includes the following: (1) cost of drilling, (2) cost of exploitation, (3) operating and maintenance costs, and (4) cost of power plant (capital cost of design and construction) [1, 2]. The first two types are referred to as subsurface costs, whereas the other two are referred to as surface costs. For small-scale geothermal power plants (<5 MWe) utilizing LEGE resources, the subsurface cost typically accounts for approximately 30% of the total investment costs, whereas the surface cost accounts for the remaining 70%. For larger geothermal power plants (>5 MWe) utilizing high-enthalpy resources, the surface cost is a small part of the total cost of the project. The major cost involved in larger plants seems to be the subsurface cost. Generating electricity using LEGE-ORC technology is very reliable due to its advanced technological aspects [2]. However, the maintenance costs and shutdowns could be reduced when the technical complexity of the plant is on a level that is accessible to local technical personnel or to experts who are readily available [2]. Also, reducing operations and maintenance costs can be achieved through advanced methods to control the geo-fluid (brine) chemistry and the use of more robust instruments for tighter controls [1, 2]. Geothermal ORC power generation plants are normally constructed and installed in small modular power generation units. These units can then be linked up to create power plants with larger power production rates. Their cost depends on a number of factors, but mainly on the temperature of the geothermal fluid produced, which influences the size of the ORC turbine, heat exchangers, and cooling system. The total size of the plant has little effect on the specific cost, as a series of standard modular units is linked together to obtain larger power capacities [2]. The modular units have a satisfying economic efficiency, because modular construction reduces installation time and costs. Ultimately, the economic viability of the geothermal power plant depends on its ability to generate revenue in the long term. This is because of relatively lower unit cost of electricity generated by geothermal plants and the future power-sale factor.

Output: corroborate


Input: Claim: Everyone's microbiome composition is identical. [SEP] Text: This project has three main goals:First, to observe and characterize trends in the effects of Soylent use on the microbiome. Second, to provide a rich, hands on microbiome research experience to a group of undergraduates. Third, to establish a student organization to regularly discuss microbiome related topics and document the course of the study online. Experimental Design:Participants will log their diets and bowel movements electronically, and sample their microbiome on each indicated day. Day 1 - 2: Participants eat regularly. Day 3 - 5: Split into two groups. 7 participants will switch to a Soylent diet. 3 participants will retain a regular diet. Day 6: All participants return to regular diets. Day 10: Last sample to observe long term recovery. wait. . . Thanks to a generous partnership with uBiome, the budget will now fund ~15 participants. Each participant's microbiome will be sampled 7 times, for a total of 105 uBiome sampling kits. Participants will consume Soylent 2. 0, the leading meal-alternative. Nutritional information and composition can be found here. Recruitment funds will be used to raise awareness and advertise the project to attract candidates for participation. Candidates will learn as part of our student organization in regular meetings about the study and microbiome research overall. Funds raised past our goal will be used to increase the sample size and fund more participants. Endorsed byhas been an excellent undergraduate in my laboratory working on the quantitative dynamics of human microbiome assemblies for over a year. This project expands his focus to the impact of constructed diets on the human gut microbiome. There have been other studies on diet-microbiome interaction revealing startling impacts on the host, but this one focuses on an emerging very restrictive diet that is gaining in popularity rapidly. This project will throw needed light how this diet affects this health-critical bacterial community. Adam ArkinProfessor, University of California, BerkeleyWe are so excited to collaborate on this project to test how Soylent changes the gut microbiome. We hope to find some interesting data and further scientific curiosity in this field! CEO uthe & jr. of are a group of motivated undergraduate researchers at UC Berkeley. Together, we are forming a student organization that will educate students on current microbiome advances and conduct this student-run study. We aim to both contribute to the field of microbiome research and inspire our study's participants. Ryan HsuI'm a Microbiology and student at UC Berkeley.

Output: contrast


Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: (a) Knockdown D2R in mushroom body neurons (MBNs) impairs larval aversive and appetitive learning. (b-d) Activation of MBNs during training impairs both larval aversive and appetitive learning. Unconditioned stimuli used were quinine (b) and sucrose (d). No learning behaviors are observed in the control distilled water (DW) groups (c). Third-instar larvae with ChR2 expression in MBNs (201Y-GAL4) are used. ATR, all-trans-retinal. Data are shown as mean ± SEM. Two-way multiple comparisons test, *p < 0. 05, **p < 0. 01, ***p < 0. 001, ****p < 0. 0001. numbers, see Table S3 and S4. DiscussionThe dopaminergic system plays an important role in Drosophila olfactory associative learning, but the roles of D2R in this process have not been fully explored. In this study, we systematically investigated the expression pattern of D2R in the third-instar larval brain as well as its role in larval aversive and appetitive learning. One driver strain singly identifying the DAN-c1 neuron was discovered and learning assays with thermogenetic tools (Shibirets1, dTRPA1) determined that the blockade of dopamine release from DAN-c1 impeded aversive learning, while its activation during training led to repulsion toward the odor in the absence of unconditioned stimulus (i. e. , QUI). These results revealed that DAN-c1 activation (i. e. , presumably leading to the release of synaptic dopamine) is both necessary and sufficient for larval aversive learning to occur. Subsequently, the expression pattern of D2R was explored by using a GFP-tagged D2R strain, including distinct dopaminergic and mushroom body neurons. D2Rs were expressed in DAN-c1, and the knockdown of these receptors resulted in aversive learning deficiency. These data suggest that presynaptic D2Rs in a single dopaminergic neuron, DAN-c1, regulate dopamine release during excitation whereas knockdown of these same receptors leads to excessive dopamine release, causing deficits in aversive learning to occur.

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: is Open Access? is an initiative that aims to make scientific research freely available to all. To date our community has made over 100 million downloads. It’s based on principles of collaboration, unobstructed discovery, and, most importantly, scientific progression. As PhD students, we found it difficult to access the research we needed, so we decided to create a new publisher that levels the playing field for scientists across the world. How? By making research easy to access, and puts the academic needs of the researchers before the business interests of publishers. are a community of more than 103,000 authors and editors from 3,291 institutions spanning 160 countries, including winners and some of the world’s most-cited researchers. Publishing on IntechOpen allows authors to earn 10. 5772/intechopen. 101577 this 1. Choose citation style Select style to clipboard Get citation 2. Choose citation style Select format Bibtex RIS Download citation Intechby Basel I. From the Edited by Basel I. purchase hard copies of this book, please contact the representative in India: CBS Publishers & Distributors Pvt. Ltd. www. cbspd. com | customercare@cbspd. com 1. Choose citation style Select style to clipboard Get citation 2. Choose citation style Select format Bibtex RIS Download citation Impact of this 1. IntroductionThe term “Geothermal Energy” refers to the Earth’s natural heat energy. The continual heat energy flux coming from the Earth’s core to the surface is the source of geothermal energy. The Earth’s geothermal resources are huge; for example, the portion of geothermal energy stored at a depth of 3 km is estimated to be 1,194,444,444 TWh, which is substantially more than the total energy equivalent of all fossil fuel resources combined, which is estimated to be 1,010,361 TWh [1]. Geothermal energy is regarded as an environmentally beneficial clean energy source that, when used to generate electrical power, has the potential to considerably reduce GHG emissions. It is reported that global net electrical power demand will rise by nearly 85% between 2004 and 2030, increasing to 30,364 TWh in 2030 from 16,424 TWh in 2004, making the use of geothermal energy for electricity generation an appealing solution, especially with advances being made in innovative technological methods of drilling and power generation schemes.

Output: corroborate


Input: Claim: Everyone's microbiome composition is identical. [SEP] Text: I have also spent over a year conducting research on synthetic human microbiomes as part of the at National Laboratory. I'm excited to see what we can learn about the microbiome together! Thanks for your support! Dylan McCormickI am a Molecular and student at UC Berkeley. I have previously worked in UC Berkeley's Museum of Vertebrate Zoology, and I am currently researching microbial genetics in the at UC Berkeley. I can't wait to help discover more about the human gut microbiome! Kate SchreinerI am an and English student at UC Berkeley. I have spent over a year working in UC Berkeley's Museum of Vertebrate Zoology. I plan on attending medical school in two years, so I am excited to learn more about the human microbiome! jr. I'm an student at UC Berkeley. I have spent over two years working in the UC of Vertebrate Zoology, and I plan on attending medical school in the future. I look forward to learning about the human gut microbiome! Thank you for your support! Lab Notes10 PostedLong awaited updates (results and more)! October 19, 201711201113Data! March 10, 20179101819A super late update! February 10, 201755363Additional InformationAny additional funds raised past our goal will be used to increase the sample size and increase the number of microbiome measurements we will take. FAQ Q: Is 3 days of Soylent long enough to observe a change? Is a sample size of 10 large enough for this study? A: In our revised study design, participants consume Soylent for 4 days. The protocol we propose is designed similarly to the study here. In this paper, a similar sample size of about 10 participants were given meat-rich or vegetable rich diets for five days, and microbiome compositions were rapidly and reproducibly changed within 2 days. Any funding we raise past our goal will be used to increase our sample size. Citation: a, et al. (2014) Diet rapidly and reproducibly alters the human gut microbiome. Nature 505(7484):559–63. Q: How can you control for Soylent/conditions if everybody's microbiome starts off differently? A: Everybody's microbiome does start off differently. As such, it is impossible to do a real soylent + - control without somehow duplicating the person and their microbiome. However, out method has two controlled aspects.

Output: contrast


Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Furthermore, the activation of DAN-c1 with optogenetic tools during training, resulting in excessive dopamine release, impaired aversive learning, as well. Finally, it was demonstrated that either the knockdown of postsynaptic D2R or activation of mushroom body neurons led to learning deficits. These data demonstrate that D2Rs in distinct brain locations are critically involved in associative learning. Insights into the neuronal circuits underlying larval olfactory associative learningMushroom body and dopaminergic neurons play important roles in Drosophila associative learning66–69. In larvae, olfactory information (odors, Conditioned Stimulus, CS) is received by olfactory sensory neurons (OSN), then transmitted to the mushroom body via projection neurons (PN)70. The mushroom body (MB) is the learning center of Drosophila and composed of Kenyon cells (KC, or mushroom body neurons, MBN)71–73. Their dendrites form the calyx, receiving olfactory information from projection neurons. The axons converge into peduncles, then branch into the vertical and medial lobes. Distinct gustatory cues (taste, Unconditioned Stimuli, US) are sensed by gustatory sensory neurons (GSN) and transferred to dopaminergic neurons in different clusters (Figure 7A). DAN-c1 in the DL1 cluster mediates aversive cues, projects to the lower peduncle (LP) in the mushroom body. The plasticity of synapses from MBNs to MB output neurons (MBON) is negatively modulated by dopamine67,74,75. The MBN-MBON synapses in the vertical lobe and peduncle are responsible for attraction, while those in the medial lobe are for repulsion67,75. Figure 7. Roles of D2Rs in dopaminergic and mushroom body neurons during larval olfactory learning. (a) A schematic diagram shows the roles of D2R in dopaminergic neurons (DAN) and mushroom body neurons (MBN) in larval olfactory associative learning. During learning, olfactory stimuli (conditioned stimulus, CS) are received by olfactory sensory neurons (OSN) and transmitted to MBNs (green) via projection neurons (PN).

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: Geothermal energy resources differ regionally based on the temperature and depth of the resource, the availability of ground water, and the chemical composition of the rock [2]. It is distinct from other conventional and renewable energy sources in that it is always accessible, steady throughout the year, regardless of weather conditions, and has an inherent storage potential. The temperature of geothermal energy resources typically ranges approximately from 50 to 350°C. Geothermal resources near volcanic regions and island chains tend to have a high resource temperature with temperature typically greater than 200°C. Medium-temperature, ranging from 150 to 200°C, and low-temperature geothermal resources of less than 150°C are typically found widely in most continental regions and considered to be the most commonly available geothermal energy resources [3]. The geothermal binary cycle technology known as the Cycle (ORC) technology can successfully generate power from medium- and low-temperature geothermal energy (LTGE) resources. LTGE-ORC technology emits almost no greenhouse gases into the environment and is an appealing technology because of its simplicity and small number of components, all of which are common and commercially accessible. More information related to a number of past and existing successful ORC binary power plants can be found in Refs. [1, 2, 3, 4]. In this introductory 2. Fundamental concept of a binary fluid ORC system using LTGE resourcesFigure 1 depicts a schematic representation of an ORC binary fluid system utilized for electric power generation using LTGE resource. Figure 1. A schematic showing the fundamental concept of an ORC binary fluid technology utilizing LTGE resource for power generation. The initial (main) fluid collected from the LTGE resource via the production well is the geo-fluid. The geo-fluid transports heat from the liquid-dominated LTGE resource (being the heat carrier) and effectively transfers this heat to the low-boiling point organic-based working fluid (the secondary fluid) through an efficient heat exchanger. Typical ORC organic fluids may include pure hydrocarbons (e. g. , pentane, butane, propane), refrigerants (e. g. , R134a, R218, R123, R113, R125), or organic mixtures. More details about the selection criteria of these ORC organic fluids for optimal performance can be found in Refs. [1, 2, 3, 4].

Output: corroborate


Input: Claim: Everyone's microbiome composition is identical. [SEP] Text: Firstly, the two days prior to Soylent consumption will provide a baseline microbiome of each participant's unique microbiome, acting as an internal control. The individuals that do not consume Soylent will act as a control for day-to-day variance of microbiome fluctuations. Q: What about human testing approval? A: --Update 10/2016-- We passed our IRB review! We have an IRB (human experimentation ethics review) underway and will also require approval from each participant before we begin testing. The study is considered minimally invasive since Soylent is regulated as food by the FDA and the uBiome sequencing is done from an external sample. of Bacteria to Microbiomes: How did so many bacteria get inside of you? From the moment you were born, your body has been collecting bacteria from the environment, which populate both your outside and inside. The main source of bacterial diversity comes from your food. Your body replenishes bacterial diversity from the varieties of food that you eat. Interestingly, Soylent is sterile, which means there are no living bacteria in the drink. This may have interesting effects on the replenishment of bacteria for Soylent drinkers. Sugars/Carbohydrates: Each species of bacteria has a unique metabolism that determines how well it can utilize the nutrition it is fed. Sugars, or carbohydrates, are the main source of energy for bacteria, and most people have diets that include a wide range of sugars. Soylent is designed with one main sugar, isomaltulose, which may preferentially select for certain bacteria, while negatively affecting other bacteria. Special thanks to for his great work on the promotional video. Richard Farman: LinkedIn, farmanrl@whitman. eduProject Backers84Backers106%Funded$6,405Total Donations$76. 25Please wait. . .

Output: contrast


Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Distinct gustatory stimuli (unconditioned stimulus, US) are received by gustatory sensory neurons (GSN) and transferred to different dopaminergic neurons. Aversive stimuli are sent to DAN-c1 (red) in the DL1 cluster which connects the lower peduncle compartment (LP, square in dash line), while appetitive stimuli are received by pPAM neurons (blue) innervating the medial lobe (ML). D2Rs (yellow square) are expressed in DAN-c1 and pPAM as autoreceptors, regulating dopamine release. Both D2R and dDA1 (magenta circle) are expressed in the MBNs. (b) A hypothetical curve showing the relationship between learning ability and cAMP level in the mushroom body. Insufficient cAMP (rutabaga mutant) cannot induce learning, while excessive cAMP (dunce mutant) also impairs learning. Only the appropriate level of cAMP regulated by the opposing actions of D1R (dDA1) and D2R leads to successful learning in wild type larvae (WT). Knockdown of D2R in DAN-c1 causes excessive dopamine release, elevating cAMP and resulting in impaired learning. D2R knockdown in MBNs relieves the inhibition effect of D2R, resulting in excessive intracellular cAMP and learning failure. (c-d) Potential molecular mechanisms underlying Drosophila olfactory learning in the square region shown in (a). (d) During aversive learning, olfactory stimuli induce depolarization of MBNs, which activates voltage-gated calcium channels and induces calcium influx. Gustatory stimuli, such as quinine, activates dopaminergic neurons and elevates dopamine (DA) release. D1 receptor (dDA1) activates adenylyl cyclase (AC) and elevates cAMP via Gαs, while D2 receptor (D2R) inhibits AC and suppresses cAMP via Gαi/o. In Drosophila, the coincidence detector rutabaga (AC) is activated by the existence of both calcium and Gαs, converging the olfactory and gustatory stimuli. cAMP activates the PKA signaling pathway, elevating the neuronal excitability.

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: The ORC is a thermodynamic Rankine cycle that uses the organic working fluid instead of steam (water). In this binary fluid system, the low-boiling point organic liquid absorbs the heat which is transferred by the geo-fluid and boils at a relatively much lower temperature (compared to water) and as a result develops significant vapor pressure sufficient to drive the axial-flow or radial-inflow turbine. The turbine is coupled to an electric generator, which converts the turbine mechanical shaft power into electrical power. The organic working fluid expands across the turbine and then is cooled and condensed in the condenser before it is pumped back as a saturated liquid to the heat exchanger using a condensate pump to be re-evaporated, and the power cycle repeats itself. Advertisement 3. Thermodynamic analysis of an ORC system utilizing a low-temperature geothermal energy resource: A case study with numerical illustrationA small-scale modular binary fluid ORC geothermal power generation system is proposed for design and installation in Vancouver, BC Canada, near a site characterized by a low-temperature geothermal energy resource. The production well in this resource is capable of supplying hot geo-fluid (mainly liquid water) at a temperature of 90°C (see state a, Figure 1). The proposed ORC system utilizes R-134a as a working fluid. In this ORC system shown in Figure 1, it is required to provide R-134a at a mass flow rate ṁRof 6. 25 kg/s as saturated vapor at 85°C to an inflow radial turbine (state 3). The ORC condenser operates at constant pressure with a constant phase-change temperature of 40°C. R-134 then enters an ideal ORC-pump as a saturated liquid (state 1, Figure 1). The density of the geo-fluid is assumed to be constant at approximately 1000 kg/m3. The geo-fluid liquid exits the ORC-evaporator (state b,Figure 1) to be re-injected into the geothermal resource at 35°C with constant specific heat capacity Cp,Geo = 4. 185 kJ/kg. °C.

Output: corroborate


Input: Claim: Everyone's microbiome composition is identical. [SEP] Text: Diet may influence the oral microbiome composition in cats access Published: 09 June 2016 Diet may influence the oral microbiome composition in cats Christina J. Adler1,2, Richard Malik3, Gina V. Browne1,2 & …Jacqueline M. Norris4 Show authors Microbiome 0. 001). Amongst this higher diversity, cats on dry-food diets had a higher abundance of Porphyromonas spp. (p < 0. 01) and Treponema spp. (p < 0. 01). ConclusionsWhile we observed differences in the oral microbiome between cats on the two diets assessed, the relationship between these differences and gingival health was unclear. Our preliminary results indicate that further analysis of the influence of dietary constituents and texture on the feline oral microbiome is required to reveal the relationship between diet, the oral microbiome and gingival health in cats. BackgroundThe microbiome of the gingival cleft is of great interest in human dentistry because the two most important diseases of the teeth and periodontium in human patients, dental caries and periodontitis [1], are related to changes in the relative contribution of various potentially pathogenic bacteria in the complex biofilm referred to as dental plaque [2]. As a result, there is considerable information on the oral microbiome of human patients, how this is associated with different disease conditions, and how this is influenced by diet [3, 4]. This includes studies using ancient deoxyribonucleic acid (DNA) which have shown that systematic changes in the microbiome are correlated with changes in diet, in both a contemporary and an evolutionary sense [5]. Cats, like humans, are very commonly affected by periodontal disease, with a consensus that it is the most common disease of feline patients in developed nations [6]. While periodontal disease is seen in cats of all ages, it is generally considered to progress with age, although its extent and severity are impacted on by such factors as diet and co-morbid disease (especially kidney disease and infection with feline immunodeficiency virus and/or feline calicivirus). Indeed, some feline diets are specifically formulated to prevent and/or ameliorate the severity of feline periodontal disease.

Output: contrast


Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: D1 and D2 receptors can also form heteromeric receptors and activate the PLC-PKC and CaMKII signaling pathways via Gαq. These pathways inhibit acetylcholine (ACh) release from MBNs to MB output neurons (MBON), which leads to avoidance of the learned odor. Abbreviations: AC, adenylyl cyclase; ACh, acetylcholine; ATP, adenosine triphosphate; CaM, calmodulin; 2+/calmodulin-dependent protein kinase II; cAMP, cyclic adenosine monophosphate; CS, conditioned stimulus; DA, dopamine; DAN, dopaminergic neurons; DL, dorsolateral; ER, endoplasmic reticulum; Gαi/o, Gi/o protein α subunit; Gαq, Gq protein α subunit; Gαs, Gs protein α subunit; GSN, gustatory sensory neurons; LP, lower peduncle; MBN, mushroom body neurons; MBON, mushroom body output neurons; ML, medial lobe; nAChR, nicotinic acetylcholine receptor; OSN, olfactory sensory neurons; PKA, protein kinase A; PKC, protein kinase C; PLC, phospholipase C; PN, projection neurons; pPAM, primary protocerebral anterior medial; RyR, ryanodine receptor; US, unconditioned stimulus; VGCC, voltage gated calcium channel. When only the odorant appears, the subset of Kenyon cells representing this odor are depolarized, inducing calcium influx73. As a balance exists between compartments across the mushroom body lobes, the response to the odor depends on the naïve olfactory circuits from projection neurons to the lateral horn (LH). In aversive learning, in addition to olfaction induced calcium influx, gustatory stimuli also lead to dopamine release from DAN-c1 and subsequently, activation of Gαs in LP54. The co-existence of calcium and Gαs activates a Ca2+-dependent adenylate cyclase (AC), rutabaga (rut)76–79. Rutabaga converges information from both olfaction and gustation, working as the coincidence detector of associative learning.

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: Thermal design constraints: The ORC-evaporator (counter flow-HEx) effectiveness εEvap,ORC= 90%; the turbine isentropic efficiency ηT = 100%; negligible pressure drops in the ORC-piping systems. Electric generator specification: ηEG = 92%. Electricity-driven pump efficiency = 100%. Required: For this conceptual ORC power generation system, the following thermodynamic performance indicators are determined:The R-134a-pumping power ẆPump (kW) requirement for the ORC system. The heat transfer rate input Q̇Evap,ORC (kW) to the ORC system. The turbine supplied power ẆTurb (kW). The electric generator power output ẆEG (kW). The net power Ẇnet,ORC (kW) delivered by the ORC system. The thermal efficiency ηth,ORC (%) of the ORC system. The specific heat transfer qGeo (kJ/kg) supplied by the low-temperature geothermal resource to the ORC system. The heat transfer rate Q̇Geo(kW) supplied by the LTGE resource to the ORC system. The mass flow rate of the geo-fluid ṁGeo(kg/s) to be extracted from the low-temperature geothermal resource. The volumetric flow rate of the geo-fluid V̇Geo(L/min) to be extracted from the geothermal resource. The overall energy conversion efficiency ηGeo (%) of the low-temperature geothermal ORC power generation system. Advertisement 4. Methodology, analysis, and resultsApplication of the steady-state energy balance, mass balance, and other thermodynamic relationships over the ORC pump (stream 1–2), turbine (stream 3–4), evaporator (stream 2–3), electric generator (EG), and the geothermal resource (stream a-b), yields the following set of model equations (Tables 1 and 2):State #T (°C)P (kPa)v (m3/kg)h (kJ/kg)s (kJ/kg. °C)x (%)1401017. 00. 000873256. 540. 022926. 2258. 213852926. 2428. 101004409.

Output: corroborate


Input: Claim: Everyone's microbiome composition is identical. [SEP] Text: To date, there have only been a handful of in-depth genetic studies of the feline oral microbiome [14–16], and these have not considered the contribution of diet to the observed findings. The present work evaluates the composition of the feline oral microbiome using next-generation sequencing (NGS) and, in a preliminary fashion, the contribution of diet to the composition of the microbiome. The two mutually exclusive dietary categories fed to cats for months to years were (i) dry extruded kibbles (highly refined, cereal-based, dehydrated rations) and (ii) wet (canned [any type] and/or fresh meat [uncooked chicken, or lamb or beef; off or on the bone] combinations, high in water content, protein and fat, but low in carbohydrate). Our findings are in agreement with recent published work on the composition of the feline oral microbiome [14–18] and show a tangible effect of diet on the overall diversity and relative frequency of occurrence of known periodontal pathogens. ResultsWe used in-depth genetic sequencing to analyse the composition of the oral microbiome in 10 owned cats. The phylogenetically informative 16S gene (hypervariable region V1-V3) was amplified from supragingival dental plaque samples from cats in the study cohort. Illumina sequencing of the 16S PCR products produced a total of 2,421,096 sequences with an average of 186,238 sequences per sample, post-quality filtering. These sequences had an average length of 487 base pairs. Feline oral microbiome compositionThe cat oral microbiome contained a diverse array of bacteria from 14 phyla (Fig. 1). For each cat and diet group, the relative frequency of operational taxonomic units (OTUs) is presented in Additional file 1. Irrespective of diet, three phyla accounted for 76 % of sequences. These included Bacteriodetes (31 %), Firmicutes (24 %) and Proteobacteria (21 %). Amongst the phyla, we found a total of 411 bacterial OTUs across all the cats (Fig. 2). The majority (67 %) of these OTUs belonged to genera that occurred at abundances below 1 %. The remaining 33 % of OTUs had abundances above 1 % and accounted for the majority (76 %) of sequences. The most dominant OTUs across all the cats belonged to the Porphyromonas genus (14.

Output: contrast


Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Its downstream signaling inhibits attractive MBN-MBON synapses in the LP, breaking the balance between distinct compartments. As a result, after learning, the larvae will exhibit repulsion when exposed to the odor again. In contrast, dopaminergic neurons in the pPAM convey appetitive cues, which project to compartments in the medial lobe. The co-existence of olfactory and appetitive gustatory stimuli leads to inhibition of these repulsive MBN-MBON synapses, inducing attraction. The conserved role of DAN-c1 in aversive learning throughout Drosophila developmentshare similar neuronal circuits of learning with larvae54,66–69. In adult brains, dopaminergic neurons are classified into 13 clusters, named as PAM (protocerebral anterior medial), PAL (protocerebral anterior lateral), PPM (protocerebral posterior medial), PPL (protocerebral lateral), and PPD (protocerebral posterior dorsal) clusters32. DANs in the PAM cluster innervate the medial lobe, while those in PPL1 project to the vertical lobe69. R76F02-AD;R55C10-DBD identifies two dopaminergic neurons in adult brains, MB-MP1 in PPL1 and ALT-PLPC in PPL2ab 61. MB-MP1 is also named PPL1-γ1pedc, innervating both γ1 and the peduncle of the β lobe69. Activation of this neuron induced aversive learning62, and activation of its corresponding MBON-γ1pedc>α/β led to approach80. During metamorphosis, dopaminergic neurons in DL1 develop into the PPL1 cluster, DL2a neurons develop into PPL2ab, and those in pPAM will develop into the PAM cluster81. This driver strain only identifies DAN-c1 from DL1 in larvae, which innervates the lower peduncle of the mushroom body. Interestingly, previous reports revealed that memory can be transferred from larvae to adults82, indicating the maintenance of neuronal circuitry architecture during metamorphosis. This evidence supports that DAN-c1 is the corresponding neuron of PPL1-γ1pedc in larvae, which performs similar functions in aversive learning.

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: : August 7, 2019 Harnessing the Our Feet: Authors and reviewers. Susan G. Hamm is the Director for at the U. S. Department of Energy. She leads efforts to lower costs and risks so more geothermal energy can be used for electricity and heat. Dr. Hamm has also worked at the Foundation and the Department of Homeland Security, and she has been a legislative assistant in the U. S. Congress. She holds a B. A. in Geology from as well as a M. S. in Geophysics and a Ph. D. in from the University of Minnesota. *susan. hamm@ee. doe. gov is a Scientist in the Office at the U. S. Department of Energy, Office of. In this role, Elisabet is involved in project oversight and execution of cutting-edge EGS RD&D, leads the annual student competition, and develops the communications strategy for geothermal initiatives. Prior to joining DOE, Elisabet worked within FEMA’s in Washington, DC. Elisabet holds an M. S. in from the University of Maine-Orono and a B. S. in Geology and Geophysics from University of Wisconsin-Madison. Age: 9 I am in the fourth grade, I love to play soccer and basketball. I also like music a lot. grow up, I want to be a computer scientist! I like learning about science and I really like math. Age: 8 My name is Vardhan and I am 8 years old. I enjoy cricket and reading books on outer space. My favorite subjects are Math and English. you know that, deep down, the Earth is really hot and that this heat can generate energy? This energy, called geothermal energy, can create electricity all over the world! It all starts with water. Water is found inside rocks nearly everywhere, even very deep beneath the Earth’s surface where it is very hot. The water inside hot rocks is very hot as well, and when this fluid comes to the Earth’s surface, it can generate electricity that can turn on a lightbulb, charge your phone, and even power your car! Geothermal energy is green energy! It does not release carbon dioxide into the atmosphere, is nearly inexhaustible, and available 24/7, because the interior of the Earth is always hot.

Output: corroborate


Input: Claim: Everyone's microbiome composition is identical. [SEP] Text: 9 %) followed by the Treponema (5. 1 %) and Fusibacter (4. 5 %) genera. Fig. 1Relative abundance of phyla in the oral microbiome of cats on dry- and wet-food diets. The abundance of phyla was calculated from sequences classified as bacteria. These sequences were taxonomically assigned using the Greengenes database following operational taxonomic unit (OTU) classification with uclust (QIIME version 1. 8. 0). Relative abundances were calculated using normalised sequence data to account for varying sequence depth between samples (Phyloseq version 1. 10. 0)Full size image Fig. 2Phylogeny of sequences in the oral microbiome of cats on dry and wet diets. The phylogeny was generated using maximum likelihood (RAxML version 730) from representative sequences of the operational taxonomic units (OTUs) and graphically displayed in the of Life (version 2. 1). Sequences with less than 0. 2 patristic distance between OTUs were collapsed (Phyloseq version 1. 10. 0). The abundance of genera in the dry- and wet-food diet groups displayed around the phylogeny was calculated from normalised OTU counts (Phyloseq version 1. 10. 0). Abbreviation: NA non-assignedFull size image Impact of diet on the feline oral microbiomeThe overall oral bacterial diversity was estimated for each cat (see Additional file 2). We used the alpha (α) diversity metric, Estimator (ACE), to assess species richness and the to assess species evenness. We assessed whether the overall bacterial diversity differed between cats eating highly refined dry (higher carbohydrate content [both on a dry matter, total energy and absolute percentage basis], dehydrated, lower percentage of protein and fat on a percentage basis as fed) versus wet (lower carbohydrate content, high in water [approx. 70 %], variably higher in protein and fat) diets (see Additional file 3). Many of the dry extruded kibbles are sprayed with phosphoric acid to improve palatability, and such diets were the ones that tended to be fed to cats in the dry-food cohort. An analysis of covariance () was conducted to determine if there was a statistically significant effect of diet on the cat’s oral microbiome ACE and values, when controlling for age of the cats.

Output: contrast


Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Pre- and post-synaptic D2Rs regulate cAMP in the mushroom body during aversive learningThe molecular mechanisms underlying Drosophila learning have not been fully determined. In a traditional view, gustatory cues elevate dopamine release, which binds to D1 receptors and then activates Gαs. The co-existence of Gαs and calcium elicited by olfactory cues activates rutabaga in axons of MBNs. Rutabaga transforms ATP into cAMP, activating PKA signaling pathway. Mutant flies with either insufficient (rutabaga) or excessive cAMP (dunce) showed aversive learning deficiency, indicating that the level of cAMP should be kept in an optimal range to achieve aversive learning21,25 (Figure 7B). Our results have shown that D2Rs in dopaminergic neurons and the mushroom body are important for larval aversive learning, suggesting a “dual brake” role in regulating cAMP levels in the MBNs through both pre- and postsynaptic components. On the presynaptic side, D2R in DAN-c1 decreases the release of dopamine under gustatory stimuli, reducing the probability of postsynaptic D1R activation in MBNs. On the postsynaptic side, D2R in MBNs inhibits the coincidence detector rutabaga (AC) both via activation of Gαi/o and inhibition of voltage-gated calcium channels2, indicating postsynaptic D2R functioning as a “brake of the coincidence detector”. Combining these, “dual brake” D2R ultimately regulates the mushroom body cAMP level within a physiologically optimal range during aversive learning. In addition, D2R fine tunes the functional concentration spectrum of dopamine with higher resolutions, as its dopamine affinity is 10- to 100-fold greater than D1 receptors. Overall, D2Rs work in a “dual brake” system both expanding the representation of a dynamic range of gustatory signal intensity with high signal to noise ratio and preventing postsynaptic overexcitation, which increases the reliability of DAN-c1 and MBN circuits for the larval aversive learning (Figure 7C & D).

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: In the future, scientists hope to expand geothermal energy use with technology improvements, bringing this powerful, fascinating energy into even more cities and towns. Geothermal Energy? Geothermal energy is renewable energy that is harnessed from the heat inside the Earth. We can use this energy not only for electricity, but also for heating and cooling buildings and for spas and hot springs. But where does this heat come from? The heat at the center of the Earth is a byproduct of chemical and nuclear reactions happening deep in the Earth’s core—reactions that have been occurring for billions of years. A common byproduct of these reactions is heat, which then slowly migrates up through the Earth until we can reach it by drilling into the ground. Because these reactions deep inside the earth will continue to happen, any heat we use will be replaced, or renewed. Geothermal energy, along with solar energy, wind energy, and hydropower, is considered a renewable energy source because we can use it forever. ? Although heat from the center of the Earth is migrating to the surface everywhere, the heat is concentrated at the edges of tectonic plates. Tectonic plates are pieces of the Earth’s surface that fit together like a jigsaw puzzle and move around slowly, about as fast as your fingernails grow. These plates can grind up against each other, or slip under each other, so their edges are very hot and are considered dynamic places. In fact, the edges of tectonic plates are marked by lots of earthquakes, like in California, and volcanoes, like in Japan. For example, the edge of the is called the Ring of Fire, because of the especially high number of earthquakes and volcanoes that occur there (see Figure 1). The western is a part of the Ring of Fire, so more heat is brought to the Earth’s surface in states like Nevada and California. That is where you will find all of the current geothermal power plants in the U. S. Figure 1 - A world map showing tectonic plates and plate boundaries. of Fire runs along the perimeter of the (Service). Convergent boundaries, shown in red, are where plates are moving toward each other. Divergent boundaries, shown in white, are where plates are moving away from each other. Transform boundaries, shown in gold, are where plates are sliding past each other.

Output: corroborate


Input: Claim: Everyone's microbiome composition is identical. [SEP] Text: We controlled for age because OTU diversity has previously been found to rise with increasing age [19]. We observed a significant effect of diet when controlling for age on species richness (ACE), F(2, 7) = 39. 26, p = 0. 0002 (Fig. 3), and evenness (Simpsons Index), F(2, 7) = 85. 67, p = 0. 00001. Cats on a dry-food compared to a wet-food diet had a higher diversity of OTUs in their oral microbiomes (ACE p = 0. 0001, Simpsons p = 0. 0001). Additionally, the overall bacterial diversity increased with increasing age (ACE p = 0. 0002, Simpsons p = 0. 0001). Fig. 3Analysis of covariance on the effect of diet type and age on the feline oral microbiome’s α diversity. Analysis of covariance () was used to test the effect of dry and wet diets on α diversity, while controlling for age of the cats in R (version 3. 1. 2). Alpha diversity was calculated using the Abundance-based (ACE) metric, from operational taxonomic unit (OTU) abundance data (Phyloseq version 1. 10. 0). was performed on the log of ACEFull size image To determine what was causing the higher bacterial diversity in cats consuming dry food, we assessed the effect of diet on the abundance of specific bacteria. A differential abundance test, DESeq2 [20, 21], was used to compare the OTUs present in dental plaque samples from cats on dry-food to those on a wet-food diet. Of the 411 OTUs identified in the cat’s oral microbiomes, 23 were differentially abundant between the two diets (Fig. 4). Of these 23, 65 % of OTUs were significantly more abundant in plaque from cat’s consuming a dry diet. The most enriched bacteria in cats eating dry diets exclusively included OTUs from the following genera: Actinobacillus (p = 1. 74 × 10−8), Acholeplasma (p = 0. 0002), Treponema (p = 0. 0087) and Porphyromonas (p = 0. 0028). The remaining 35 % of OTUs were significantly more abundant in dental plaque from cats consuming a wet diet.

Output: contrast


Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Recent studies showed that the approach/repulsion in learning is achieved via inhibition of the repulsive/attractive representing compartments67,74,75, which indicates dopamine inhibits acetylcholine release from MBN to MBON83. However, the PKA signaling pathway usually elevates neuronal excitability and increases neurotransmitter release2,3, which is contradictory to the recent findings. In addition to the “dual brake” role of D2R, our results suggest a third role of D2R in aversive learning. D1 and D2 receptors can form heteromeric receptors, whose downstream Gαq activates PKC and CaMKII signaling pathways. The activation of these signaling pathways may reduce acetylcholine release84 (Figure 7C & D). Explaining the results of thermogenetic and optogenetic experimentsActivation of DAN-c1 with dTRPA1 induced aversive learning, while the repulsion disappeared when DAN-c1 was activated in the quinine group (Figure 2K). Our explanation is that quinine stimulation and temperature activation led to over-excitation of DAN-c1, which impaired aversive learning. This is consistent with the learning deficiency in larvae with D2R knockdown in DAN-c1 (Figure 4E). Results from optogenetic activation of DAN-c1 during aversive learning also support this (Figure 5B). However, in contrast to results with thermo-activation, larvae with optogenetic activation of DAN-c1 showed neither repulsion after being trained with distilled water (Figure 5C), nor did they show reduced attraction in the sucrose group (Figure 5D). One possible explanation is that the thermo-activation is relatively mild compared to the optogenetic activation. Based on this, thermo-activation of DAN-c1 is still in the physiological range of cAMP under the upper cutoff (Figure 7B), resulting in repulsion in the distilled water (DW) group, neutralized attraction in SUC group, and impaired repulsion in QUI group. In contrast, optogenetic activation of DAN-c1 overwhelmed the physiological conditions, leading to failure of repulsion in DW group (Figure 5C). This repulsive failure did not affect appetitive learning (Figure 5D), and a stronger over-excitation in QUI group induced similar failure (Figure 5B).

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: The yellow dots represent earthquake activity, which you can see is heaviest at the edges of the plates. Map of by the Service. Check out the tectonic plate map above and look at the countries through which plate boundaries cross. Do you notice a pattern? Countries with a lot of geothermal energy, like Iceland and Indonesia, also sit right on top of a plate boundary. Think of all the geothermal energy potential across the entire globe! A lot of gigawatts! A gigawatt, usually abbreviated as GW, can power about 1,000,000 homes. There is about 12. 8 GW of geothermal-based electricity produced worldwide and about 3. 5 GW in the U. S. alone. 3. 5 GW can power about 3,500,000 homes, which is equivalent to almost all the households in the entire state of Georgia! That might seem like a lot, but it is about to get bigger: there is about 1. 3 GW of additional electricity from geothermal energy under development right now! Up a Geothermal Reservoir? To be able to harness the geothermal energy deep in the Earth, we need three ingredients: (1) heat, (2) fluid, and (3) permeability, or pathways through the rock. As we have already discussed, heat from the center of Earth migrates to the Earth’s surface naturally, and is found everywhere underground, although the amount of heat varies slightly from place to place. We also need fluid inside underground rocks to absorb heat and bring it to the surface for us. This fluid is not your average water; it is not like water that comes out of your tap, or ocean water, or agricultural water, or anything that you have ever seen before. This fluid has weird colors, strange smells, and flows differently. Lastly, we need to have pathways for that water to flow underground. These pathways are usually made up of fractures, or cracks in the rocks, which are very tiny and connected to each other. These fractures allow the fluid to circulate slowly and increase in temperature. When these three things occur together, they create a geothermal reservoir. We can pump the hot water out of the reservoir, send it through a power plant, use it to spin a turbine and generate electricity. Then, that electricity can be sent out to power homes via transmission lines.

Output: corroborate


Input: Claim: Everyone's microbiome composition is identical. [SEP] Text: These bacteria were primarily Proteobacteria, from the Neisseriaceae family (38 %), including Conchiformibius kuhniae (p = 0. 0002). The differential abundance test indicated that diet alters the abundance of specific bacteria in the feline oral microbiome. Fig. 4Differentially abundant genera between the oral microbiomes of cats on dry and wet diets. DESeq was used to test for the presence of differentially abundant operational taxonomic units (OTUs) in the oral microbiome of the cats on a dry- compared to wet-food diet (Phyloseq version 1. 10. 0). The DESeq test was applied to OTUs that had been filtered to remove singletons and species with an abundance below 0. 005 %. The figure presents those OTUs that were found to be significantly different (p < 0. 01) between the two diets. Positive log2-fold change values indicate enriched OTUs in the dry diet, and negative log2-fold change values indicate enriched OTUs in the cats eating a wet diet. Abbreviation: NA non-assignedFull size image DiscussionOur analysis of the oral microbiome is only the fourth NGS study in cats [14–16] and for the first time highlights the potential impact of diet on bacterial composition. Cats consuming dry kibble (dehydrated, highly refined, cereal-based, sprayed with oil and phosphoric acid) compared to a higher protein/lower carbohydrate wet diet (approx. 70 % water by weight) have a more diverse oral microbiome, with an enrichment of bacteria associated with both gingival health and periodontal disease. Our findings indicate that diets commonly fed to domestic cats in Australia [22] influence the feline oral microbiome make-up, although exactly how these composition changes relate to gingival health requires resolution. Current understanding of the feline oral microbiome and what impacts its composition is limited by a lack of culture-independent studies. At a broad scale, we found a similar bacterial profile to published NGS [14–16] and Sanger sequencing [17, 18] studies of the feline oral microbiome, in terms of abundance of phyla and detection of genera.

Output: contrast


Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Distinct dopaminergic neurons may have different roles in larval aversive learningPrevious work reported that aversive olfactory learning was induced through the optogenetic activation of DAN-d1, f1, or g1, but not DAN-c185. This discrepancy can be explained as the optogenetic overexcitation of DAN-c1, similar to our optogenetic or D2R knockdown results. Our learning assay results from larvae with D2R knockdown in DAN-d1 or g1 also supported this: aversive learning was not affected by D2R knockdown (Figure S4E). These data indicate D2Rs in DAN-d1 or g1 are not involved in larval aversive learning. Additionally, the DAN-c1 strain used in the previous work (SS02160-split-GAL4) not only labels DAN-c1, but also marks other non-dopaminergic neurons, which may affect the results. Besides, live calcium imaging showed that DAN-d1, f1, and g1 responded to the activation of mechanosensory and nociceptive neurons85, indicating a functional differentiation from gustatory activated DAN-c162,86. In future studies, the molecular signaling downstream of D2R needs to be explored, as well as the comprehensive neuronal circuit architectures of larval learning. The neuronal circuits underlying learning and memory are complex networks, sharing similarities with the regulatory networks of gene expression. Studies of the mechanisms of learning and memory help us understand the essential principles of the non-linear dynamic characteristics in these complex systems. On one hand, the progress in larval learning provides useful information for helping our understanding about more complex systems, from brains in adult flies to those in mammals. On the other hand, the architecture of larval learning circuits could improve either hardware design or algorithm structures in artificial intelligence, which may bring more powerful tools, such as navigation systems regulating multiple auto-drive vehicles in complex 3-dimentional environments. In conclusion, we explored the expression pattern of D2R in the third-instar larval brain and investigated their roles during larval olfactory learning. D2Rs were found in DAN-c1, and their knockdown induced deficiency in aversive learning. D2Rs were also expressed in MBNs, knockdown of which impaired both aversive and appetitive learning.

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: If we do not have these three things together, then there is no way to generate any power from the geothermal energy. You may be asking, “well, the heat may be renewable, but what about the fluid? Can you use up all the hot fluid? ” Actually, after the hot water has been used for energy production, it can be put back underground, where the water can be reheated and can generate electricity again (see Figure 2). It is a perfect circle! Figure 2 - This figure shows the circulation of fluids at a power plant harnessing energy from a geothermal reservoir (Department of Energy). Hot water from far below the surface is pumped up to the production well and is sent to the power plant. Inside the plant, the heat from the water is used to spin a turbine, creating electricity. Once the heat is used, the water is now cold, and is pumped back into the subsurface through the injection well. That water will now heat up again over time and go through the cycle again. ? There is a lot of research going on right now to figure out how to create geothermal reservoirs in places where there is hot rock underground. In some locations, there are hot rocks, but little permeability or fluids to bring that heat to the surface for energy production. In these instances, it may be possible to inject fluid into the hot rocks and create permeability. This sort of man-made geothermal reservoir would allow geothermal electricity to be produced anywhere. We would not only be able to build geothermal power plants on the Earth’s surface, but we could also build geothermal reservoirs underground. This would be revolutionary and could generate almost 500 GW more electricity than is currently produced by geothermal energy. of Going on to Geothermal Resources? Many people in a lot of different specialties are working toward figuring out how to harness more geothermal energy. For example, computer scientists are teaching computers how to look for hot rocks; engineers are inventing new ways to drill and build geothermal reservoirs; and lots of scientists are getting their hands dirty by getting out of their labs to test their geothermal-related inventions in real-world conditions. Last, but not least, sharing is a huge part of advancing geothermal energy. Sharing data, sharing ideas, talking about the future, and contributing to other scientists’ research.

Output: corroborate


Input: Claim: Everyone's microbiome composition is identical. [SEP] Text: Our findings were most similar to Harris and colleagues’ study [14], which also found the dominant phyla to be Firmicutes (30 %), Bacteriodetes (22 %) and Proteobacteria (17 %). The present investigation and Harris et al. ’s study [14] recovered a similar number of OTUs, 411 and 267, respectively, which was lower than the 10,177 OTUs recovered from NGS analysis of the feline oral microbiome by Sturgeon and colleagues [15]. This variation in bacterial diversity between studies is potentially attributable to the region of the 16S gene amplified. In both ours and Harris et al. ’s study [14], the V1-V3 region of the 16S gene was sequenced, which is longer than the V4 region sequenced in Sturgeon and colleagues’ study [15]. At a fine scale, there was a variation in the abundance of OTUs recovered between the studies. For example, while we found Porphyromonas at an abundance of 15 %, Sturgeon et al. [15] found it at a frequency of 2 %, which may reflect variation in the gingival health between the cats assessed. The variation in the abundance of genera could also reflect differences between the studies in terms of OTU classification methods and reference databases used for species classification. Overall, while broad similarities in the feline oral microbiome were found between our and past NGS studies, the fine-scale differences highlight the extent of unknown information about what influences the composition of the cat oral microbial community. We examined in a preliminary fashion one of the key factors thought to influence the composition of the human and feline oral microbiome, namely diet. While we detected differences in the abundance and diversity of bacteria between cats fed two broad categories of diets (dehydrated kibble versus well-hydrated meat-based or fresh meat rations), what these results mean for feline oral health is less clear. Cats consuming dry kibble exclusively, a popular choice in and to a lesser extent in Australia (13.

Output: contrast


Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: This research revealed the important roles of D2Rs in Drosophila larval olfactory learning and enriched our understanding regarding the mechanisms underlying the learning process. Materials and MethodsFly stocksAll fly strains used in this study are listed in Table 1 and Table S1. Flies were maintained on standard medium, which consists of cornmeal, yeast, dextrose, sucrose and agar in water. Flies were kept in a 12/12-hour light/dark cycle at 25°C. Canton-S genotype (WT) and yw1118 were used as wild-type. Strains carrying more than one transgene were constructed by standard genetic crosses with the w1118; CyO/Sco; TM2/TM6 multiple balancer chromosome strain. Strain UAS-Syb::spGFP1-10, LexAop-CD4::GFP11, LexAop-rCD2::RFPCyO; MB247-LexA::Up16/TM6B was made by chromosome swapping between UAS-Syb::spGFP1-10, LexAop-CD4::GFP11/CyO (II, second chromosome) and LexAop-rCD2::RFP (II). The D2R gene is located on the X chromosome, with 6 different alternative splicing products. The GFP-tagged D2R strain is inserted with a GFP gene in the second intron, generating D2R molecules tagged with GFP87,88. The D2R-miR strain produces microRNA recognizing the sequence across the third and fourth exons, which is not affected by the GFP insertion (Figure S4F). -GFP reconstitution across synaptic partners (GRASP) was used to investigate whether neurons formed synapses89 (Figure S2d). Half of split GFP tethered to the presynaptic synaptobrevin (UAS-syb::spGFP1-10) was expressed in one type of neuron using UAS/Gal4 binary system, and the complementary split GFP linked to a membrane protein (LexAop-CD4::spGFP11) was expressed in another category of neuron with LexA/LexAop.

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: is Open Access? is an initiative that aims to make scientific research freely available to all. To date our community has made over 100 million downloads. It’s based on principles of collaboration, unobstructed discovery, and, most importantly, scientific progression. As PhD students, we found it difficult to access the research we needed, so we decided to create a new publisher that levels the playing field for scientists across the world. How? By making research easy to access, and puts the academic needs of the researchers before the business interests of publishers. are a community of more than 103,000 authors and editors from 3,291 institutions spanning 160 countries, including winners and some of the world’s most-cited researchers. Publishing on IntechOpen allows authors to earn 10. 5772/intechopen. 97423 this 1. Choose citation style Select style to clipboard Get citation 2. Choose citation style Select format Bibtex RIS Download citation Intechby Basel I. From the Edited by Basel I. purchase hard copies of this book, please contact the representative in India: CBS Publishers & Distributors Pvt. Ltd. www. cbspd. com | customercare@cbspd. com 1. Choose citation style Select style to clipboard Get citation 2. Choose citation style Select format Bibtex RIS Download citation Impact of this 0. 072 USD/kWh as compared to 0. 056 for onshore wind and 0. 047 USD/kWh for hydropower. However, the technology is rather competitive to other renewables such as concentrating solar power (0. 185 USD/kWh) and offshore wind (0. 127 USD/kWh). Meanwhile, further research and development is critically needed to eliminate the non-condensable gases (NCGs) associated with the geothermal power generation. Keywords geothermal energy geothermal power plants geothermal electricity economic and environmental impact geothermal worldwide status Show + Ziyodulla Yusupov* of Electrical and Electronics Technology, Libya *Address all correspondence to: ziyodulla@gmail. com 1. IntroductionGeothermal energy is heat energy from Earth’s interior which generated from radioactive breakdown and frequently recurring heat losses from Earth’s formation. The Earth’s heat capacity is approximately 1 × 1019 TJ or 2. 8 × 1015 TWh [1]. The Earth’s heat conduction is 44. 2 TW [2].

Output: corroborate


Input: Claim: Everyone's microbiome composition is identical. [SEP] Text: 4 %) [22], compared to a ‘wet diet’ were noteworthy in having a higher abundance of bacteria previously associated with both gingival health (including Porphyromonas and Capnocytophaga [14]) and periodontal disease (including Porphyromonas [11–13] and Treponema [14]), from analysis of the feline oral microbiome in different health states. Furthermore, we found that cats consuming a dry-food diet exclusively had higher bacterial diversity per se compared to cats fed canned wet food and/or fresh meat. Human oral microbiome studies have found higher bacterial diversity accompanying periodontal disease compared to oral health [23]. However, NGS analysis of the feline oral microbiome in the settings of gingival health and mild periodontal disease prior to our investigations found no difference in the overall diversity between these health states [14]. A critical deficiency in the literature is that cats with severe periodontal disease have not been subjected to this type of quantitative NGS analysis [14]. It is important to note that in this previous study [14], the age of the cats (ranging from 1 to 18 years) was not accounted for in the comparison of overall diversity between cats with gingival health and mild periodontal disease. We have shown that feline oral bacterial diversity significantly increases with advancing age of the patient, although the strength of this result is tempered by the small sample size of our study. The lack of clarity from our study about the relationship between (i) the feline oral microbiome composition, (ii) the two disparate diets and (iii) gingival health probably relates to the limitations of our study, which includes the small sample size and lack of cats with a broad range of gingival health states. To adequately address the question of how diet impacts the feline oral microbiome and oral health, a case-matched study design would be ideal. This would involve comparing the oral microbiome of cats in two groups, one consuming a wet and one consuming a dry diet for identical time periods that were matched for age, breed and gingival health. A minimum of 50 cats per group would provide adequate power. A further consideration is that case recruitment would be challenging, as while periodontal disease is common, most people feed variable combinations of dry and wet diets, so finding cats where only one type of diet is consumed would require considerable time and effort.

Output: contrast


Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: If synapses between these neurons exist, the split GFPs would form a complete one and be recognized by a mouse antibody (Figure S2a-c). ImmunohistochemistryAll staining processes were performed in 1. 5 ml Eppendorf tubes. Late third-instar (96-100h after egg laying) larval brains were dissected in dissection solution (300 mOsmol/L). Brains were fixed in 4% paraformaldehyde (. No. 15713) for 1 hour on ice. After three washes (0. 1% bovine serum albumin in 10m9647), brains were incubated in the blocking and permeabilization solution (0. 2% Triton X-100 in 10mM PBS with 5% normal goat serum; Triton-X 100, Sigma, T8532; NGS, Sigma-Aldrich, G9023) for 2 hours at room temperature. Incubation with primary antibodies was done overnight at 4°C. After three washes, brains were incubated in the secondary antibodies for two hours. Both the primary and secondary antibodies were diluted in the blocking and permeabilization solution. GFP antibody (Rabbit, Scientific, Cat. No. A6455, 1:1000), TH antibody (Mouse, Immunostar, Cat. No. 22941, 1:1000), goat anti-rabbit with green fluorescence (Invitrogen, 488 conjugate, Cat. No. A-11035, 1:1000), and goat anti-mouse IgG with far-red fluorescence (633 conjugate, Cat. No. 21052, 1:500) secondary antibodies were used. After three washes, brains were transferred and mounted in the Fluoro-Gel with (Sciences, Cat. No. 17985-10) on a piece of micro cover glasses (Sciences, Cat. No. 72200-41). Finally, the samples were covered with another piece of micro cover glasses. A seven-day staining protocol was used for staining of GFP-tagged D2R or GRASP, in which brains were fixed in 1% paraformaldehyde in Schneider’s insect medium (Sciences, Cat. NO. S0146) overnight at 4°C.

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: The utilization of geothermal energy according to the geological conditions are categorized as:High-temperature (enthalpy) geothermal systems with temperature greater than 180°C. This system depends on recent mantle hot spot anomalies and volcanos at depths over 3. 5 km. Also, high-temperature geothermal systems related to rocks at depths approximately below 3. 5 km. Middle-temperature (enthalpy) systems between 100 and 180°C. Low-temperature (enthalpy) geothermal systems with temperature lesser than 100°C. Geothermal systems with middle and low-temperature are formed by decaying of radioactive isotopes and they conclude aquifers which recharge by heated water circulation. Table 1 tabulates the classification of the geothermal resources based on temperature [3]. (a)(b)(c)(d)(e)Low enthalpy resources<90°C<125°C<100°C≤150°C≤190°CMiddle enthalpy resources90–150°C125 –225°C100–200°C——High enthalpy resources>150°C>225°C>200>150°C>190°CTable 1. Classification of geothermal resources based on temperature [3]. a) Muffler and Cataldi (1978); b) Hochstein (1990); c) Benderitter and Cormy (1990); d) Nicholson (1993); e) Axelsson and Gunnlaugsson (2000). Geothermal energy can be utilized for both purposes – direct heat and electricity generation. As of the end of 2019, geothermal energy was used in 88 countries around the world with an annual energy consumption of around 1,020,887 TJ or 283,580 GWh [4]. According to the Agency the electricity production from geothermal energy will be increased to 1400 TWh/y and the direct use to 1600 TWh/y by 2050 [5]. The main advantage of the geothermal energy is being clean as other types of renewable sources. Other advantages include: reliability, environment-friendliness, relatively low cost of generated energy, high usage factor for the geothermal power plant operation that distinguishes the geothermal energy from other renewable energy sources. However, the heat and electricity generated by the geothermal energy should be directly utilized locally and cannot be transported. Advertisement 2. Geothermal power plantsIn work [6], modeled types of geothermal resources are given, as shown in Table 2.

Output: corroborate


Input: Claim: Everyone's microbiome composition is identical. [SEP] Text: Intuitively, the oral microbiome of any mammal, including humans, would be impacted by dietary composition. For example, increased carbohydrate intake has been associated with accelerated development of periodontal disease in controlled animal studies [24], ancient DNA analysis of fossilised human dental plaque from past agriculturist and hunter-gatherer populations [5] and human observational research [25]. are obligate carnivores that have undergone reductive evolution through obtaining their dietary requirements from the flesh of prey. Prey are composed of protein, mineral and fat, the only carbohydrate being represented by plant ingesta in the gut and glycogen in the liver. Most animal tissues are generally well hydrated, with a water content of approximately 70 %. Changes in the oral microbiome would therefore be anticipated when diets were shifted by consumption of commercial cat foods (which were introduced in the 1970s and refined subsequently), especially dry diets based on carbohydrates from cereal (typically corn or wheat) mixed with rendered animal protein and coated with phosphoric acid, salt and fat to improve palatability. Cats fed commercial kibbles have a much higher intake of carbohydrate at 12 % [26] or higher, compared to cats consuming a prey-based diet, which has carbohydrate content in the order of 2 % [27]. In addition to food macronutrient composition, the mechanical properties of food are also likely to play a role, especially where diets contain meat on the bone, where there is a requirement to masticate, salivate (cat saliva is high in bicarbonate) and mechanically debride wearing dental surfaces due to the ‘flossing action’ of stripping meat from the bone. As well as physically removing plaque and even calculus, the debriding action of a flesh-eating lifestyle is likely to better buffer plaque pH [28]. The various points raised lend themselves to experimental interventions, specifically to determine the relative contribution of dietary composition as opposed to dietary texture. ConclusionsCommonly fed domestic diets influence feline oral microbiome composition, including the overall diversity and abundance of bacteria associated with both health and periodontal disease. From our preliminary analysis of the feline oral microbiome, we could not determine whether a dry kibble- or wet meat-based diet was preferable to ensure optimal gingival health.

Output: contrast


Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: In the second day, the brains were rinsed and washed twice with PAT3 solution (0. 5% Triton X-100 in 10mM PBS with 0. 5% BSA), each for 1 hour. Then brains were incubated in the blocking and permeabilization solution (3% NGS in PAT3) for 2 hours at room temperature. Incubation of primary antibodies was done overnight at 4°C. On the third day, brains were rinsed and washed twice with PBT solution, then incubated in the secondary antibodies for five days. Both the primary and secondary antibodies were diluted in the PBTN solution. In the staining of GFP-tagged D2R, GFP antibody (Rabbit, ThermoFisher Scientific, Cat. No. A6455, 1: 1000), TH antibody (Mouse, Immunostar, Cat. No. 22941, 1:1000), and mCherry antibody (Rat, ThermoFisher Scientific, Cat. No. M11217, 1:1000) were used. For staining of antibody (Mouse, ThermoFisher Scientific, Cat. No. G6539, 1:100) was used. Goat anti-rabbit with green fluorescence (Invitrogen, 488 conjugate, Cat. No. A-11035, 1:1000), goat anti-mouse with green fluorescence (488 conjugate, Cat. No. A11029, 1:1000), goat anti-mouse with far-red fluorescence (633 conjugate, Cat. No. A21052, 1:500), and goat anti-rat with red fluorescence (546 conjugate, Cat. No. A-11081, 1:1000) secondary antibodies were used. In the seventh day, brains were rinsed and washed twice with PBT solution, and then transferred and mounted in the Fluoro-Gel with on a piece of micro cover glasses. Finally, the samples were covered with another piece of micro cover glasses. Confocal imagingAll images were obtained with a 510 (LSM510, Carl Zeiss, Inc. , USA). Under 40× and 100× objective magnifications, images were collapsed from confocal stacks of 1. 0 μm optical slices. Under 25× objective magnifications, images were collapsed from confocal stacks of 2. 0 μm optical slices.

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: In general, geothermal resources under 150°C are more suitable for direct use such as heating and cooling, whereas the resource of above 150°C is exploited for electricity generation. However, modern power conversion technologies allow to generate an electricity from low temperature resources up to 150°C [3]. Type of geothermal resourceTemperatureHot-water dominated20–350°CVapor-dominated≈240Sedimentary basin20–150°CRadiogenic30–350°CGeopressured90–200°CSolidified (hot dry rock)90–650°CPart still molten (magma)>600 °CTable 2. Types of geothermal resources for energy utilization. A steam or hydrocarbon vapor are used to generate electricity from geothermal energy. While the vapor-dominated resource is applied directly, the hot-water dominated resource should be flashed by reducing the pressure to convert a steam [7]. Table 3 provides the basic technologies and the common applications under different temperatures of geothermal fluid. Reservoir temperatureGeothermal fluidApplication proposesTechnologyHigh temperature, >220°CWater or steamDirect-in useHeat exchangers; Heat pumpsPower generationFlash steam: combined cycle (flash and binary)Medium temperature, 100–220°CWaterDirect-in useHeat exchangers; Heat pumpsPower generationBinary cycleLow temperature, 30–150°CWaterDirect-in useHeat exchangers; Heat pumpsTable 3. Frequently used technologies for geothermal energy. As mentioned above, the geothermal source in view of steam or hydrocarbon vapor can be used to generate electricity. In this respect, geothermal power plants (GPPs) operation is similar to those of steam power plants. However, unlike the conventional steam power plants, the geothermal power ones use natural steam of earth. History of the first GPP started from 1904 at Larderello, Italy, where generator was tested to produce electricity from geothermal source. Then, it was commercialized to power plant in 1911 [7]. The simplest operational conceptualization of the GPP is presented in Figure 1. In this case, a natural steam from the well is directly passed to a turbine, that drives a generator for the electricity production. Figure 1. Schematic diagram of dry steam power plant. There are three basic types of GPPs:Dry steam plants. Flash steam plants. Binary cycle power plants. 2.

Output: corroborate


Input: Claim: Everyone's microbiome composition is identical. [SEP] Text: Amplification of the 16S rRNA gene: PCR was used to amplify the V1-V3 region (nucleotide position 27–519) of the 16S rRNA gene. The PCR conditions included 0. 625 U of Thermo(BioLabs) in a 25-μl volume using 10× ThermoBuffer, 200 μM of each dNTP (Fermentas), 0. 2 μM of each primer and 2 μl of DNA extract. The thermocycling conditions consisted of an initial enzyme activation step at 95 °C for 30 s, followed by 25 cycles of denaturation at 95 °C for 20 s, annealing at 54 °C for 15 s and elongation at 68 °C for 40 s, with a single final extension step at 68 °C for 5 min. Each set of PCRs included extraction and PCR blanks. All PCR products were visually examined by electrophoresis on 2. 0 % agarose TBE gels. Positive PCR products were selected for Illumina sequencing. Illumina sequencing of the 16S amplicons: Illumina sequencing was used to examine the microbial contents of the 10 dental plaque sample DNA extracts. Amplicons were sequenced on the Illumina MiSeq platform with 300 base pair, paired-end read chemistry. Sequence analysisSequence analysis of the Illumina data, including quality filtering, taxonomic classification and phylogeny generation, was undertaken in QIIME version 1. 8. 0 [29]. Quality filtering was used to remove sequences that contained ambiguous bases, had primer or barcode mismatches, contained homopolymers that exceeded six bases or had a minimum Phred quality score below 20. The quality-filtered sequences were checked for the presence of chimeras using usearch61 [30, 31] with Greengenes (version gg_13_8) [32] as the reference dataset. This was done to remove sequences containing errors produced during PCR. Sequences which shared 97 % similarity were binned into OTUs using open-reference OTU picking via uclust [30], with Greengenes (version gg_13_8) as the reference dataset. Representative sequences from each OTU were taxonomically assigned using the RDP classifier and nomenclature [33].

Output: contrast


Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: Under 10× objective magnifications, images were collapsed from confocal stacks of 12. 5 μm optical slices. ImageJ software was used to remove other signals outside of the mushroom bodies, as the background noise in GRASP is strong. Larval olfactory learning assaysA single odor learning paradigm was slightly modified from previous publication17,18. In brief, 25 to 50 third-instar larvae (92–96 h after egg laying) were trained on a 2. 5% agar plate (100mm petri dish) covered with 2 mL of 1 M sucrose solution (SUC, Sigma, Cat. No. S1888) or 0. 1% quinine hemisulfate solution (QUI, Sigma, Cat. No. 22640). Distilled water (DW) was used as a control. An odorant pentyl acetate (PA, 10μL, Sigma-Aldrich, CAT. No. 109584) was placed on a small piece of filter inside the lid. After 30 minutes, larvae were rinsed and transferred to the middle line of a new 2. 5% agar plate. A small piece of filter paper with 2. 5μL pentyl acetate was placed on one side of the plate, while distilled water on the other side. After 5 min, the numbers of larvae in the two semicircular areas were counted and the response index (R. I. ) was calculated with the following equation (Figure 2g): Naïve Olfactory TestLarvae were transferred into the midline of test plates. 2. 5μL of odorant were added on one side and distilled water on the other side. The number of larvae in two semicircular areas were counted and the R. I. was calculated after 5 min. Naïve Gustatory TestA petri dish with a median separator was used. Both sides were filled with 1% agar, with 2 mL of distilled water on the control side, and with 1 M sucrose (SUC) solution, or 0. 1% quinine hemisulfate (QUI) solution on the test side. Twenty larvae were put on each side near the midline and allowed to move for 5 min. Gustatory R. I. was calculated using the larvae numbers on two sides90. Larval locomotion assayIndividual larvae were placed on the surface of a plate of 2.

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: 1 Dry steam plantsDry steam plants are simple and more efficient type of GPP. This type of power plants was firstly deployed to generate electricity in Italy in 1911. However, dry steam plants are less available in the sense that the steam should be produced from vapor-dominated reservoirs which are of few numbers in the world. To provide a high efficiency of turbine, the steam condensation is minimized during extension of fluid fraction in steam phase. In common, isentropic efficiency of modern dry steam plants is about 85%. According to a feasibility study to extract the maximum efficiency of these plants, the generation capacity should be at least 1 MWe [8]. Based on [9], electricity can be generated from the dry steam in the following conditions:The vapor-dominated source should be closer (approximately with 5 km depth) to the surface to raise the hot water to the boiling point. There should be enough opening above the geothermal fluid source to allow the vapor to drop to the surface over a long period of time by reducing the level of liquid significantly. The schematic diagram of dry steam power plant is illustrated in Figure 1. The dry steam plant operation is based on the following: the water and steam flow from geothermal production wells are transmitted through valve to turbine and spin a steam turbine by converting thermal and kinetic energy to electrical energy. 2. 2 Flash steam plantsCurrently, most of GPPs are flash steam plants. They use geothermal reservoirs with mixture sources, i. e. , vapor and liquid-dominated (water) to generate an electricity. It means that the temperature and enthalpy of vapor and waters are lesser than the critical point. Therefore, the flash units are generally basic approach to change over the geothermal energy into power. Firstly, in this system the steam is separated from water using a cylindrical cyclonic pressure tank with a base loss of pressing factor. Then, the dry steam leaves the separator, flows to powerhouse and rotates the steam turbine. The vapor quality that defines the flashed fluid is given as:x=mvapormliquid+mvaporE1where: mvapor – mass of vapor and mliquid – mass of liquid. The vapor quality value changes from 0 to 1 and commonly given as percentage. When vapor quality between 0 and 1, wet steam is then obtained. When the vapor quality is equal to 1, it is called “the saturated vapor” state.

Output: corroborate


Input: Claim: Everyone's microbiome composition is identical. [SEP] Text: Representative sequences were aligned using PyNAST [34] against the Greengenes reference dataset (version gg_13_8). This alignment was used to build a phylogeny with RAxML version 730 [35]. Statistical analysisStatistical analysis of the quality-filtered and classified sequence data was undertaken in R (version 3. 1. 2), primarily using the Phyloseq package (version 1. 10. 0) [36]. Alpha diversity: Within-sample diversity was estimated per sample on the quality-filtered data, which had not been submitted to any further pre-processing, such as removal of singletons. The α-diversity metrics, ACE and Simpsons Index, were calculated for all samples. To assess the impact of diet on α diversity, while controlling for age of the cat, we used an. This test assumes the ACE, and values will be normally distributed. Residual plots of the ACE and values indicated they were non-normally distributed. To improve the distribution, ACE and values were log transformed. was performed on the log-transformed values of ACE and in R. Pre-processing of sequences: Before undertaking further statistical analyses, very low abundant sequences were removed in line with current recommendations [37]. We removed OTUs that were singletons and had an abundance below 0. 005 % of all the sequences. Differential OTU test: The DESeq2 package [20, 21] was used to test for the presence of differentially expressed OTUs between two diets. The test is a negative binomial generalised linear model (GLM), Wald statistic. The GLM is used to model the counts of OTUs per sample using a negative binomial distribution. The experimental design for the test was set to compare the OTUs from the dry- and wet-food diet groups. All OTUs that significantly (α = 0. 01) differed in abundance between the two diets according to the DESeq test results were reported. All reported p values were adjusted for multiple comparisons using the Benjamini-Hochberg, false discovery rate procedure. Normalisation of OTU count data: To account for variation in sequence depth between samples, we used a variance stabilised transformation (VST) to produce normalised sequence data by library size. All abundances of OTUs reported are from the VST data. Consent for publicationNot applicable.

Output: contrast


Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: 5% agar mixed with 1mL India ink. They were allowed to acclimate for 1 min, and then a video was recorded for 30 seconds using a Moticam3 digital camera (Motic) and Plus 2. 0 software. The video was analyzed by the MTrack2 plug-in (from in ImageJ. The path was recorded; scores were quantified as the length traveled per minute as previously described91. As the locomotion speed of DAN-c1 homozygous was slow, DAN-c1 × WT was used as the control group. Learning assays with thermogeneticsIn learning assays with thermogenetics, 25 to 50 third-instar larvae (92–96 h after egg laying) were trained on a 2. 5% agar plate (100mm petri dish) covered with 2 mL of 1 M SUC or 0. 1% QUI. DW was used as a control. An odorant PA was placed on a small piece of filter inside the lid. Training plates were put in a water bath either under 22°C or 34°C. After 30 minutes, larvae were rinsed and transferred to the testing plate. After 5 min, the response index (R. I. ) was calculated. Learning assays with optogeneticsIn learning assays with optogenetics, egg laying plates with 1mM ATR (all-trans retinal, Sigma, Cat. No. R2500) were used. All-trans retinal (ATR) is a necessary light-isomerizable chromophore for ChR2, which is not synthesized by Drosophila. 92,93 Around 50 third-instar larvae were trained in a 35mm petri dish with 2 mL of either 1 M SUC or 0. 1% QH solutions. DW was used as a control. During training, an odorant was placed on a small piece of filter inside the lid. To activate channelrhodopsin2, a LED (07040 PB000-D, wavelength 470 nm) with a power supply (power supply Model GPS-1830D) was used. The intensity of the blue light was 25 mW, measured by a laser power meter (Sanwa, LP1). After being trained for 30 minutes, larvae were rinsed and transferred to the middle line of a 2. 5% agar plate in 100 mm test plate.

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: There are two types of flash steam geothermal plants:Single-flash steam GPPDouble-flash steam GPPIn a single-flash steam GPP the mixture fluid is flashed only in one separator. Schematic process diagram of the single-flash power plant is shown in Figure 2. The process of electricity generation in this power plant is accomplished as follows: hot water from production well is piped to flash separator (FS) by decreasing its pressure. In FS the steam is separated from hot water and transmitted to the steam turbine to spin it and convert mechanical energy to electrical by a generator. While the cooled steam in a turbine condenses to the water by the condenser while a part of the liquid from FS are reinjected to injection well. Figure 2. Schematic diagram of single-flash power plant. Unlike single-flash steam, in double-flash steam the flash process of the fluid is applied in two separators. Although these plants are more expensive and more labor-consuming, however, they are preferable than single-flash plants as they generate 15–25% more electricity for the same states of fluid reservoirs [8, 9]. Schematic operational diagram of the double-flash power plant is illustrated in Figure 3. The fluid flows from well to a high pressure flash separator where from a mixture fluid the steam is separated and is piped to a two-stage turbine; another part – saline liquid is throttled down to the second separator. In the low pressure separator like the first one a partly boiled liquid again is separated to a steam and water. As a result, the steam gets directed to the low-pressure turbine. By keeping the pressure in the condenser, the steam from the low-pressure turbine is cooled using a sprayed cold water. Then, water is reinjected to injection well, as well as the cold water from the condenser. Figure 3. Schematic diagram of double-flash power plant. 2. 3 Binary cycle power plants“Binary” cycle refers to as a secondary separate cycle. For the geothermal resource, binary indicates that the geothermal fluid (water/steam) never comes in a contact with the prime mover. Geothermal binary power systems are suitable for electricity production from low underground heat source [10].

Output: corroborate


Input: Claim: Everyone's microbiome composition is identical. [SEP] Text: Gut microbiome diversity and composition is associated with exploratory behavior in a wild-caught songbird access Published: 04 February 2023 Gut microbiome diversity and composition is associated with exploratory behavior in a wild-caught songbird Melanie R. Florkowski1 & Jessica L. Yorzinski1,2 16. 4% and 6. 4%, 24% and 8. 9%, 24. 2% and 7. 9%, and 21. 4% and 11. 7% of the variance in gut microbiome communities based on pre- and post-captivity Bray–Curtis and pre- and post-captivity weighted UniFrac distances, respectively. Fig. 2Principal coordinate analysis of pre-captivity (A) Bray–Curtis (B) weighted UniFrac distances and post-captivity (C) Bray–Curtis (D) weighted UniFrac distances between the gut microbiomes of high (red) and low (blue) explorer birds. Each point represents a different individual. Circles indicate 95% confidence intervalsFull size imageTable 2 Results of investigating the influence of exploratory group, sex, scaled mass, activity level, latency to explore, capture location, and capture date on differences in the birds’ pre-captivity and post-captivity gut microbiome communities using Bray–Curtis dissimilarity or Weighted UniFrac distanceFull size tableThere was significant heterogeneity in the dispersion of both Bray–Curtis (F1,43 = 9. 4, p = 0. 003) and weighted UniFrac (F1,43 = 4. 1, p = 0. 048) distances. is robust to heterogeneity when the compared groups have similar samples sizes, therefore this was unlikely to bias results [40]. The only taxa differentially abundant between the high and low explorers was Catellicoccus (OTU 1), and it was more abundant in low explorers (LDA = 5. 40, p = 0. 0267). The microbiome functional analysis predictions resulted in 368 predicted pathways defined by the of Genes and Genomes (KEGG) pathway database. Tax4Fun2 only utilizes sequences that have matches to the reference databases to predict functions and on average 85. 9 ± 22. 1% (mean ± standard deviation) of sequences per sample were utilized.

Output: contrast


Input: Claim: Some studies suggest that olfactory receptors may function through quantum effects. [SEP] Text: A small piece of filter paper with pentyl acetate was placed on one side of the plate, while distilled water on the other side. Then the number of larvae in the two semicircular areas were counted and the R. I. was calculated after 5 min. Quantification of D2R knockdownQuantification of the fluorescent intensity of D2R knockdown was performed as follows. TH signals were used to define dopaminergic neurons, and the mean fluorescent intensity of GFP in each neuron was calculated with subtraction of the background. The mean intensity of DM1 was divided by that of pPAM, and the value in the knockdown group was subsequently normalized with the control group. Statistical AnalysisInformation for statistical analysis is provided in figure legends. Author contributionsQi. C. : Conceptualization, Methodology, Formal analysis, Investigation, Writing – Original Draft, Visualization, Qian. C. : Writing – Review & Editing, Steijvers. E. : Writing – Review & Editing Colvin. R. : Writing – Review & Editing Lee. D. : Conceptualization, Writing – Review & Editing, Supervision, Funding acquisitionAcknowledgementsThis work was partially supported by an NIH grant (AG065925) and an Grant from of Science & Technology (Institute), Seoul, Korea. CQ was a recipient of the SEA and GSR awards from Ohio University. We thank Dr. J Hirsh (University of Virginia), Dr. M. Wu (University), Dr. M. Zlatic and Dr. C. Eschbach (), Dr. M. Gallio (Northwestern University), Dr. A. Kopin (Tufts-Medical Center), Dr. S. Tanda (Ohio University), Dr. B. Condron (University of Virginia), Dr. T. Kitamoto (University of Iowa) for their kind gift strains. Declaration of InterestThe authors declare no competing interests. Supplemental informationFigure S1. GFP expression patterns in the larval CNS by GAL4 driver strains used in this study. (a-n) Representative pictures show the patterns of distinct GAL4 driver strains crossed with a UAS-GFP strain. (o) A representative picture shows the pattern of MB247-LexA driver (MB247-LexA::VP16) crossed with a LexAop-RFP strain (LexAop-rCD2::RFP).

Output: pass


Input: Claim: Geothermal energy harnesses heat from beneath the Earth’s surface for power generation. [SEP] Text: The binary plant in Alaska, as an example, utilizes a geothermal resource of 57°C [11]; yet generally, binary system designs can exploit an inlet temperature range between 80 and 170°C [3]. The secondary fluid, known commonly as working fluid, in the binary geothermal system operates in a conventional Ranking cycle; and the binary cycle is known as an organic Ranking cycle (ORC) when the used working fluid is organic [12]. In binary ORC power plants the geothermal fluid passes through a heat exchanger to heat another working fluid of a low boiling point e. g. , pentane, zeotropic mixtures, etc. which in turn vaporizes and drives a turbine [13]. Electrical production through a closed-loop binary unit is shown in Figure 4. Figure 4. Illustrative schema for a binary geothermal plant. The standard working mechanism of a basic geothermal binary system can be summarized as: when the geothermal brine is pumped through the production well, the heat extraction process is accomplished after passing through different components of the primary cycle. The geothermal fluid is initially filtered via sand removers to pass through the heat exchanger i. e. , the evaporator/vaporizer and preheater, and finally pumped back into the reservoir by the injection well. On the other side of the secondary cycle, the pressurized working fluid turns into boiling state in the preheater. It then exits the vaporizer as a saturated vapor that subsequently expands in the turbine driving a power generator. The low-pressure working fluid vapor exiting the turbine is finally condensed in the ACC (air-cooled condenser) and pumped back to the vaporizer, closing the loop system and repeating the process continuously. Thus, the thermodynamic process of the low-boiling-point working fluid starts when it expands into the turbine in saturation vapor state, and completed when it is cooled through the condenser and pumped back (as a saturated liquid fluid) to the heat exchanger to emerge as a saturated vapor again [14, 15]. The efficiency of geothermal ORC, for high enthalpy field, can go as high as 23% [16]. However, cycle configuration plays a key role in thermodynamics of a binary power plant.

Output: corroborate