Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: In other words, paleomagnetic intensity might tell scientists when the inner core began to form, with some suggesting that the answer is a little more than half a billion years ago (i. e. , only in the last ~10% of Earth’s history). This newsletter rocks. Get the most fascinating science news stories of the week in your inbox every Friday. Sign up now In a new study published in the Proceedings of the of Sciences of the of America, paleomagnetist and University of California, Berkeley doctoral student and his coauthors collected and studied rocks from the (failed) Midcontinent Rift—a region where 1. 1 billion years ago there was voluminous volcanism. The rocks that Zhang targeted are unique aggregations of crystals known as anorthosite xenoliths that formed deep in Earth’s crust but were brought close to the surface with magma that fed lava eruptions into the rift. The team found surprisingly high paleointensity values that signal a turbulent core—more spirited than might be expected for a liquid core lacking a solid center and stronger than Earth’s magnetic field today. Plot of age versus paleointensity, with a dashed line showing a previously interpreted decreasing trend until about 500–600 million years ago, after which paleointensity values begin to climb, showing distinct lows but also higher highs than most data from the Precambrian, barring the data presented in the new study. A light blue band from 1,110 to 1,085 million years ago shows the age of the rocks in this study as well as their curiously high paleointensity values. Credit: Zhang et al. , 2022, of Earth’s energy that causes the liquid core to move, or convect, comes from two different mechanisms. Thermally convecting liquid is driven by heat that’s wanting to rise and escape, said Courtney Sprain, a paleomagnetist at the University of Florida who was not involved in this study. In the other mechanism, compositional convection stirs the cauldron because of light elements. As the mostly iron inner core solidifies, it excludes lighter, more buoyant elements that proceed to rise through the liquid outer core. “We believe [that] today, that’s one of our main sources of energy driving the geodynamo,” Sprain explained.

Output: pass


Input: Claim: Data privacy remains a concern with AI assistants that collect user information for training. [SEP] Text: Although there is an ongoing debate about if individuals should be responsible for their data protection [19], our work purely concentrates on identifying protection behavior, without taking a position in this debate. Nonetheless, it is not trivial or unambiguous to organize protection behaviors in a taxonomy or model, because categories could mean different things to people [26]. Whereas some authors label behaviors literally equal (e. g. fabricate [35, 38]), other scholars rely on own nominations (e. g. perturbation [55]). We tried to stick to generally recognized wordings. But sometimes there was a need to create own nominations which literature do not discuss throughout to cover the different authors’ aspects (e. g. trust in proxy control). There are also some categories in literature, which did not fit into our model. For example Moshki and Barki say that coping can happen during “a stressful encounter” [14] and call this the “impact period”. However, we argue that it is difficult to identify a privacy breach on the fly. Finally, sometimes authors’ classifications are contradictory. For example Yap et al. [16] call withdraw as an active behavior, whereas Gurău and Ranchhod [22] consider it as passive. Furthermore we argue that the model can never be considered as complete. As technology is changing with high pace, new protective technologies and behaviors are likely to arise. Adding insights from further disciplines, such as sociology, might bring up other or new categories to the model. 5. 1 ImplicationsOur work offers implications for theory, as well as for practice. For scholars this work offers an overview of current privacy protection behaviors of end-users and helps to understand the range of protection mechanisms [13, 16, 41]. Additionally, it shows which denominations authors use. Further it shows how behaviors could be linked to each other. As the model concentrates on a user-centric approach, it answers the call from [18]. The model is not fixed. Instead, it is highly adaptive. Researchers can edit, add or delete categories without losing the general meaning. In addition, the model is not fixed to a special domain, thus scholars can adopt the classifications to special fields of research. For practice, our model helps end-users to identify tools and techniques to protect themselves, as users are often not aware how to safeguard their data [13, 41].

Output: pass


Input: Claim: Genetically modified trees require no water or nutrients once planted. [SEP] Text: Tom 77 Nr 3 (2022) Artykuły Genetycznie modyfikowane topole o zwiększonej odporności na stresy abiotyczne - najnowsze osiągnięcia. Praca przeglądowa. Magdalena Sozoniuk+− Krzysztof Kowalczyk+− Institute of Plant Genetics, Breeding and Biotechnology, University of in Lublin, Akademicka 15, 20-950 Lublin, Poland Institute of Plant Genetics, Breeding and Biotechnology, University of in Lublin, Akademicka 15, 20-950 Lublin, Poland PDF (English) DOI: Przesłane: 15 czerwca 2022 Opublikowane: 28-10-2022 ostatnich latach dokonał się ogromny postęp w zakresie poprawy odporności drzew leśnych na stres abiotyczny. Zastosowanie technik modyfikacji genetycznej pozwala na otrzymanie drzew odznaczających się dobrym wzrost w warunkach różnych czynników stresowych, takich jak wysokie zasolenie, susza, niska temperatura i zanieczyszczenie środowiska. Szczególnie podatna na modyfikacje genetyczne jest topola. Wobec nadchodzących zmian środowiskowych zastosowanie transformacji genetycznej w hodowli leśnej wydaje się być atrakcyjną perspektywą.

Output: contrast


Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: was much warmer billions of years ago and the inner core was not initially present, thermal convection may have been the primary driver generating the early magnetic field, said Richard Bono, a paleomagnetist at University who also was not involved in Zhang’s work. cooled, thermal convection—and the intensity of the magnetic field—should have tapered. But continued cooling eventually led to the beginnings of Earth’s solid metal heart, which should have boosted the waning magnetic field as compositional convection overtook its thermal counterpart. “You need some really strong forces in the interior of the Earth to generate such strong [paleointensity] values. ” This transition might have begun less than 700 million years ago (much younger than canonical estimates), according to experiments designed to determine how fast iron conducts heat at extremely high pressures and temperatures, said Zhang. However, such experiments have led to different results through different approaches, enough so that various scenarios of the age of the inner core are possible. A 2019 paper led by Bono, in which scientists collated high-quality paleointensity data, supported this young inner core formation timeline, with the paleomagnetic field interpreted to decrease in intensity until a 565-million-year-old low, followed by a rise toward much higher values, signifying more mixing. This timeline led to the intriguing hypothesis that the inner core began to form sometime after 565 million years ago—remarkably young. However, because older (1. 14-billion-year-old) rocks have low paleointensity values, Zhang’s curiously high paleointensity data in 1. 09-billion-year-old rocks could be interpreted as inner core nucleation similar to some previous estimates. “You need some really strong forces in the interior of the Earth to generate such strong [paleointensity] values,” said Zhang. If true, new explanations for later ebbs and flows of paleointensity are needed for around 565 million years ago, as well as at younger times of low to high field strength transitions. Nevertheless, these data don’t negate inner core nucleation 565 million years ago either, he said. “If anything, this is telling us we need to start trying to understand some of the other added complexities” like plate tectonics, said Sprain.

Output: pass


Input: Claim: Plant-based seafood aims to reduce overfishing and decrease ocean pollution. [SEP] Text: One reason why blue foods are not well integrated into discussions about food system transformation in the may be because of the perception that blue foods are not a significant part of the nation’s food system. Today, seafood is among the most traded food commodities in the world9, obscuring the link between blue food harvest and consumption10. Indeed, an estimated 80% of the total seafood consumed in the United States, by volume, comes from imported sources (6. 1 billion pounds)11. However, despite the United States’ dependence on imported sources12, the nation produced 8. 4 billion pounds of seafood in 2020 alone and is among the largest producers of blue foods in the world11. Recognizing the disconnect between consumption and production, and in response to calls for food system transformation, we evaluate the potential for blue food production in the to meet consumer demand and contribute to the dietary needs of its population. We accomplish this by using a self-reliance analysis to evaluate the extent to which the could achieve seafood “independence” under the current consumption scenario as well as one in which consumption reflects recommendations for a healthy diet. By seafood independence, we mean the capacity of a region or country to meet its seafood needs through its own production by reducing reliance on imports. Increasing food system self-reliance can help to ensure food and nutrition security by reducing dependence on trade13,14. Further, self-reliance buffers places from systemic shocks, which have become more prevalent over the last 50 years15. Here, our approach considers production, utilization, yield, and consumption data across seven regions of the and nationally over 50 years (1970–2021). Using these results, we also investigate the extent to which blue food production aligns with the dietary recommendations for seafood consumption in an effort to triangulate the possible contributions that blue foods could make toward meeting dietary needs for the country if seafood self-reliance were prioritized as part of future efforts to transform and strengthen regional and national food systems. While any major change in the distribution and availability of blue foods in the would require a substantial shift away from global trade, we assert that this pivot is not beyond imagination. The recent COVID-19 pandemic has brought acute attention to the shortcomings of overreliance on global trade in the seafood sector, leading to numerous calls to strengthen supply chains and bolster local, regional, and domestic seafood systems16,17,18.

Output: corroborate


Input: Claim: Genetically modified trees require no water or nutrients once planted. [SEP] Text: W niniejszej pracy omawiamy najnowsze osiągnięcia dotyczące genetycznie modyfikowanych drzew charakteryzujących się zwiększoną odpornością na niesprzyjające warunki środowiska. A. , Kim J. -K. , 2020. Transgenic breeding approaches for improving abiotic stress tolerance: recent progress and future perspectives. Int. J. Mol. Sci. 21(8), 2695. DOI: Bakhsh A. , Hussain T. , 2015. Engineering crop plants against abiotic stress: current achievements and prospects. Emir. J. Food Agric. 27(1), 24–39. DOI: Bian Z. , Wang X. , Lu J. , Wang D. , Zhou Y. , Liu Y. , Wang S. , Yu Z. , Xu D. , Meng S. , 2021. The yellowhorn AGL transcription factor gene XsAGL22 contributes to ABA biosynthesis and drought tolerance in poplar. Tree Physiol. 42(6), 1–14. DOI: Brodribb T. J. , Powers J. , Cochard H. , Choat B. , 2020. Hanging by a thread? Forests and drought. Science 368(6488), 261–266. DOI: Castro‐Rodríguez V. , García‐Gutiérrez A. , Canales J. , Cañas R. A. , Kirby E. G. , Avila C. , Cánovas F. M. , 2016. Poplar trees for phytoremediation of high levels of nitrate and applications in bioenergy. Plant Biotechnol. J. 14(1), 299–312. DOI: Chang S. , Mahon E. L. , MacKay H. A. , Rottmann W. H. , Strauss S. H. , Pijut P. M. , Powell W. A. , Coffey V. , Lu H. , Mansfield S. D. , Jones T. J. , 2018.

Output: contrast


Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: Subducting plates move through the mantle, sometimes settling into cold piles at the core-mantle boundary. Elsewhere along this boundary, buoyant plumes of hot material rise upward. These sunken slabs and upwelling plumes affect how heat escapes from the core, a process that itself affects how quickly the outer core can convect. The core’s pattern of exhaling heat changes as this geometry shifts, which could affect how the magnetic field is generated, she explained. Snapshot or Long-Term Average? “Our magnetic field is really crazy. ” “Our magnetic field is really crazy,” said Sprain. “It can change on timescales of seconds to millions of years. ” “When we’re trying to understand what the strength of the field is, we have to ask—how much time are we looking at, [and] how much time do we average? ” said Bono. A rock that cools quickly, on the order of hundreds or thousands of years, will record a snapshot of the magnetic field. A rock that takes many tens or hundreds of thousands of years to cool smooths out the magnetic field’s short-term variation. “You really need to be looking at the time-averaged field strength” to understand what was happening in the core, he said. In the new study, said Sprain, Zhang has data from seven sites but only one date for these rocks. Because these are very old rocks, each date’s margin of error would be on the order of 100,000 years to greater than 1 million; collecting more dates wouldn’t necessarily help resolve the relative timing between sites. “Even if there was more than 10,000 years between [multiple samples’] cooling times, we wouldn’t be able to resolve it [because] the ages would overlap,” Sprain said. Nevertheless, the data are of high quality, and even averaging all the information together results in a higher-than-expected magnetic field for 1. 1 billion years ago, confirming the findings of prior work, said Bono. In this prior work, Sprain found that slightly older volcanic rocks from the also record a strong magnetic field similar to that on Earth today. “What we need,” said Sprain, “is more high-quality data.

Output: pass


Input: Claim: Sub-orbital flights allow tourists to experience a brief period of weightlessness. [SEP] Text: The main advantages of parabolic flights for reduced gravity investigations are:the short turn-around time (typically of a few months between the experiment proposal and its performance);the low cost involved (space agencies provide the flight opportunity free of charge to selected investigators);the flexibility of experimental approach (laboratory type instrumentation is most commonly used);the possibility of direct intervention by investigators on board the aircraft during and between parabolas, and the possibility of modifying the experiment set-up between flights. Furthermore, aircraft parabolic flights are the only suborbital carrier to provide the opportunity to carry out medical and physiological experiments on human subjects under conditions of microgravity or reduced gravity such as that found on other planetary bodies (Martian 0. 38 g, Lunar 0. 16 g), to prepare for extra-terrestrial planetary exploration. This 2. Objectives of parabolic flightsAn aircraft in parabolic flight provides investigators with a laboratory for scientific experimentation where the gravity levels are changed repetitively, giving successive periods of either 0. 38 g (Mars gravity) for up to 32 s, or 0. 16 g (Moon gravity) for up to 25 s or 0 g for 20 s, preceded and followed by periods of 20 s at approximately 1. 8 g (Figure 1), where g is the acceleration created by gravity at Earth’s surface, on average 9. 81 m/s2. Figure 1. NASA’s KC-135 during the pull-up phase (Credit: NASA). Parabolic flight objectives pursued by investigators vary. From a scientific point of view, the following objectives can be attained:the performance of short experiments for which the reduced gravity is low enough for: qualitative experiments of the ‘look and see’ type, using laboratory type equipment to observe and record phenomena; and quantitative experiments to measure phenomena in reduced gravity, yielding direct quantitative exploitable results;the ability for experimenters to perform their own experiments in reduced gravity with the possibility of direct interventions on the experiment in progress during the low g periods and direct interaction by changing experiment parameters between the reduced gravity periods (Figure 2);the study of transient phenomena occurring during the transition between high to low and low to high g phases. Figure 2. Experiment on vibrational phenomena during an ESA campaign (Credit: ESA).

Output: corroborate


Input: Claim: Genetically modified trees require no water or nutrients once planted. [SEP] Text: Genetic engineering of trees: progress and new horizons. Cell. Dev. Biol. Plant 54(4), 341–376. DOI: Cheng Z. , Zhang X. , Zhao K. , Yao W. , Li R. , Zhou B. , Jiang T. , 2019. Over-expression of ERF38 gene enhances salt and osmotic tolerance in transgenic poplar. Front. Plant Sci. 10, 1375. DOI: Cortés A. J. , Restrepo-Montoya M. , Bedoya-Canas L. E. , 2020. Modern strategies to assess and breed forest tree adaptation to changing climate. Front. Plant Sci. 11, 1606. DOI: DalCorso G. , Martini F. , Fasani E. , Manara A. , Visioli G. , Furini A. , 2021. Enhancement of Zn tolerance and accumulation in plants mediated by the expression of Saccharomyces cerevisiae vacuolar transporter ZRC1. Planta 253(6), 1–17. DOI: dos Santos T. B. , Ribas A. F. , de Souza S. G. H. , Budzinski I. G. F. , Domingues D. S. , 2022. Physiological responses to drought, salinity, and heat stress in plants: a review. Stresses 2(1), 113–135. DOI: Fillatti J. J. , Sellmer J. , McCown B. , Haissig B. , Comai L. , 1987. Agrobacterium mediated transformation and regeneration of Populus. Mol. Gen. Genet. 206(2), 192–199. DOI: Geng X. , Chen S. , Yilan E. , Zhang W. , Mao H. , Gigige A. , Wang Y. , Qi Z. , Lin X. , 2020. Overexpression of a tonoplast Na+/H+ antiporter from the halophytic shrub Nitraria sibirica improved salt tolerance and root development in transgenic poplar. Tree Genet. Genom. 16(6), 1–14. DOI: Guo Q. , Jiang J. , Yao W. , Li L. , Zhao K. , Cheng Z.

Output: contrast


Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: AbstractBacterial motility is typically studied in bulk solution, while their natural habitats often are complex environments. Here, we produced microfluidic channels that contained sediment-mimicking obstacles to study swimming of magnetotactic bacteria in a near-realistic environment. Magnetotactic bacteria are microorganisms that form chains of nanomagnets and that orient in Earth’s magnetic field. The obstacles were produced based on micro-computer tomography reconstructions of bacteria-rich sediment samples. We characterized the swimming of the cells through these channels and found that swimming throughput was highest for physiological magnetic fields. This observation was confirmed by extensive computer simulations using an active Brownian p10. 7554/eLife. 98001. 1. sa2Significance of findingsvaluable: Findings that have theoretical or practical implications for a subfieldlandmarkfundamentalimportantvaluableusefulStrength of evidencesolid: Methods, data and analyses broadly support the claims with only minor weaknessesexceptionalcompellingconvincingsolidincompleteinadequateDuring the peer-review process the editor and reviewers write an eLife assessment that summarises the significance of the findings reported in the 2. 1 Characterization of sediment and construction of sediment-mimicking microfluidic channelsTo study swimming of magnetotactic bacteria in a near-realistic sediment environment that resembles their natural habitat, we produced microfluidic channels that contained sediment-mimicking obstacles (Fig. 1 and S1). To that end, we first characterized a sediment sample in water from the magnetotactic bacteria-rich lake (Potsdam, Germany). We determined a 3D reconstruction of the sample using micro-computer tomography (muCT) with a resolution of 1. 56 µm (Fig. 2a-d) and analyzed the sizes of sediment p1. Construction of sediment-mimicking obstacle channels:Micro-computer tomography slices of sediment samples (a) are cropped out to ignore border effect due to the reconstruction and binarized (b). The binarized images are then fitted with circles (c) for statistical analysis (grain size distribution in d) and for construction of arrays of pillar-shaped obstacles (e). The images of irregular grains (b) and fitted circles (e) are used as masks to design microfluidic channels with obstacle arrays (f), in which the bacteria are injected in the middle channel (3.

Output: pass


Input: Claim: Sub-orbital flights allow tourists to experience a brief period of weightlessness. [SEP] Text: In particular, in Life Sciences, investigations can be conducted on living systems to understand how humans, small animals, cells and plants are affected by a low gravity environment similar to those on the Moon and Mars. Many issues of relevance for the preparation of future human space exploration that includes stays on the surface of planetary bodies can also be investigated (Figure 5). Some experiment results of European partial-g campaigns can be found in [8, 9]. Figure 5. and training on the KC-135 before their Apollo-14 mission (Credit: NASA). Other gravity levels are also achievable during flights and can be used by investigators: e. g. , during pull-up and pull-out manoeuvres, periods of 20 s of 1. 8–2 g are achieved, and spiral turn manoeuvres provide for longer periods or other levels of high g. These hypergravity periods can be used for certain type of gravity dependent investigations, e. g. , in combustion or physiology areas. Finally, since a few years, parabolic flights are also used in the USA, Europe and Russia to allow the general public to discover the 0 g environment and to enjoy for a few moments the sensations that astronauts experience during their spaceflights. 3. Parabolic flight manoeuvreFor microgravity flights, let us recall first that a body is in free fall if it is subjected to the only force of gravity in an inertial reference frame and this body and all its content are in a state of weightlessness in the non-inertial reference frame attached to the body. Weightlessness thus appears in a non-inertial reference frame, which is in a state of free fall with respect to an inertial reference frame. Weightlessness is a dynamical state that requires a free-fall movement [10]. Note as well that any kind of movement of a vehicle that is subjected to the action of the sole force of gravity is a free-fall movement, and weightlessness is then generated in the vehicle. Consider now an aircraft flying in Earth’s atmosphere, assumed to be quiet. There are usually four forces acting on the aircraft in a straight and level horizontal flight (Figure 6):its own weight, oriented vertically downwards,the aerodynamic lift, induced by the shape of its wings, oriented vertically upward,the aerodynamic drag, created by air resistance, oriented horizontally backward,the aircraft engine thrust, oriented horizontally forward. Figure 6.

Output: corroborate


Input: Claim: Genetically modified trees require no water or nutrients once planted. [SEP] Text: Pe CHYR 1, a ubiquitin E3 ligase from Populus euphratica, enhances drought tolerance via ABA‐induced stomatal closure by ROS production in Populus. Plant Biotechnol. J. 16(8), 1514–1528. DOI: Huang S. , Chen C. , Xu M. , Wang G. , Xu L. A. , Wu Y. , 2021. Overexpression of Ginkgo BBX25 enhances salt tolerance in transgenic Populus. Plant Physiol. Biochem. 167, 946–954. DOI: Kim M. -H. , Cho J. -S. , Park E. -J. , Lee H. , Choi Y. -I. , Bae E. -K. , Han K. -H. , Ko J. -H. , 2020. Overexpression of a poplar Ring-H2 zinc finger, Ptxerico, confers enhanced drought tolerance via reduced water loss and ion leakage in Populus. Int. J. Mol. Sci. 21(24), 9454. DOI: Lebedev V. G. , Popova A. A. , Shestibratov K. A. , 2021. Genetic engineering and genome editing for improving nitrogen use efficiency in plants. Cells 10(12), 3303. DOI: Li D. , Yang J. , Pak S. , Zeng M. , Sun J. , Yu S. , He Y. , Li C. , 2022. PuC3H35 confers drought tolerance by enhancing lignin and proanthocyanidin biosynthesis in the roots of Populus ussuriensis. New Phytol. 233(1), 390–408. DOI: Llanes A. , Palchetti M. V. , Vilo C. , Ibañez C. , 2021. Molecular control to salt tolerance mechanisms of woody plants: recent achievements and perspectives. Ann. For. Sci. 78(4), 1–19. DOI: Meng S. , Cao Y. , Li H. , Bian Z. , Wang D. , Lian C. , Yin W. , Xia X. , 2019.

Output: contrast


Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: 5 mm × 1. 2 mm × 10 µm) where they encounter the obstacles. Fig. 2. Analysis of micro-computer tomography images of a sediment sample in water:a) Slice of the sediment sample, b) cube from the center of the cuvette, c) and d) examples of water gaps rendered with the Amira software. e) Distribution of the smallest grain dimension (i. e. , trabecular thickness analyzed with CTAn) with Gaussian fit a exp(−(x− µ)2/c2), µ = 3. 83, c = 0. 5903, corresponding to a mean sand grain diameter of 46 µm. f) Distribution of the water gap size (i. e. , trabecular separation) with Gaussian fit a exp(−(x−µ)2/c2), µ = 42. 94 µm, c = 28. 66 µm. g) Percentage of sand over water as function of the distance from the bottom of the cuvette as obtained from 2D slices of the µCT images (yellow filled line) and for the equivalent fit with circles (yellow dashed line). The red points show the mean radius of the fitted circles (± standard error of the mean) in µm (right axis). We next analyzed two-dimensional slices of the µCT images at various depths of the sample to study if any difference is observed. This analysis returns similar values of the sand to water percentage (62 – 66% from top to bottom, see Fig. 2g, with the small difference possibly due to sedimentation of the sediment under gravity). The mean radii of circular fits to the grains varies from 68 to 62 µm from bottom to top (Fig. 2g), further potentially indicating a slight effect of sedimentation by gravity. This analysis provides the basis for the construction of our 2D microfluidic channels. To realistically represent the porous environment where magnetotactic bacteria live, we constructed quasitwodimensional microfluidic channels based on the 2D µCT images at different depths (Figure 1). These images (shown in S2) were used as masks (see Methods), such that each sediment grain becomes an irregularly shaped pillar in our quasi-2D structure. Bacteria thus swim through an array of pillars that act as obstacles for their motion.

Output: pass


Input: Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: Listen to this story: Your browser doesn't support the audio element Back 15 seconds Forward 15 seconds 0:00 on social media linkedin x twitter facebook scientists have long been on a quest to crack the condition’s sleep conundrum. Problems with falling and staying asleep are not typically considered a core trait of autism, but they are exceedingly common among autistic people and have compound effects: They can exacerbate a range of autism traits and are linked to greater difficulties with daily functioning. But to track and assess what goes on in the body during sleep — historically at least — research participants have had to sleep in a lab, tucked up in a web of cumbersome equipment: The gold-standard approach, polysomnography, temporarily turns a sleeper into something resembling the prey of a giant electrical spider, bound in electrodes and wire leads that capture brain activity via electroencephalography (EEG), and breathing and body position, among other measures. This scenario is uncomfortable enough for neurotypical people, never mind someone with autism who may also have anxiety and sensory, communication or behavioral difficulties, notes Malow, professor of neurology and pediatrics at in Nashville, Tennessee. “The question is, are you really getting a valid night’s sleep [under those conditions]? ” Some study participants with autism may not be able to sleep at all, notes Thomas Frazier, professor of psychology at University in University Heights, Ohio, as was the case when Frazier’s teenage autistic son went to a clinic for an overnight EEG study. “Getting good data and then scaling that up so you can actually use it in a real, meaningful way is tough,” he says. Wire web: EEG helmets used for standard polysomnography can interfere with a study participant’s sleep, particularly if she has sensory sensitivities or anxiety. To address the issue, multiple labs are working to deploy minimally invasive sleep-tracking devices — both “wearables” that someone puts on and “nearables” that take measurements from a distance. These devices tend to collect fewer types of data than polysomnography can, but their creators say they do enough to get the job done, tracking sleep stages and certain aspects of a sleeper’s physiology and brain activity. The three technologies described below all strike that balance between accuracy and scalability, and they may help researchers increase the number of autistic participants in their studies.

Output: corroborate


Input: Claim: Genetically modified trees require no water or nutrients once planted. [SEP] Text: PeSHN1 regulates water-use efficiency and drought tolerance by modulating wax biosynthesis in poplar. Tree Physiol. 39(8), 1371–1386. DOI: Moran E. , Lauder J. , Musser C. , Stathos A. , Shu M. , 2017. The genetics of drought tolerance in conifers. New Phytol. 216(4), 1034–1048. DOI: Nagle M. , Déjardin A. , Pilate G. , Strauss S. H. , 2018. Opportunities for innovation in genetic transformation of forest trees. Front. Plant Sci. 9, 1443. DOI: Neri A. , Traversari S. , Andreucci A. , Francini A. , Sebastiani L. , 2020. The role of aquaporin overexpression in the modulation of transcription of heavy metal transporters under cadmium treatment in poplar. Plants 10(1), 54. DOI: Nguyen H. C. , Lin K. H. , Ho S. L. , Chiang C. M. , Yang C. M. , 2018. Enhancing the abiotic stress tolerance of plants: from chemical treatment to biotechnological approaches. Physiol. Plant. 164(4), 452–466. DOI: Nowicka B. , Ciura J. , Szymańska R. , Kruk J. , 2018. Improving photosynthesis, plant productivity and abiotic stress tolerance – current trends and future perspectives. J. Plant Physiol. 231, 415–433. DOI: Ozyigit I. I. , Can H. , Dogan I. , 2021. Phytoremediation using genetically engineered plants to remove metals: a review. Environ. Chem. Lett. 19(1), 669–698. DOI: Polle A. , Chen S. L. , Eckert C. , Harfouche A. , 2019. Engineering drought resistance in forest trees. Front. Plant Sci. 9, 1875. DOI: Rai P. K. , Kim K. H. , Lee S. S. , Lee J. H. , 2020.

Output: contrast


Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: In addition, we generated channels with cylindrical pillars by fitting circles to the two-dimensional grain images (Figure 1 and S2). These rounded-shaped pillars of different diameters are used for a comparison of our experiments with computer simulations below. 2. 2 Swimming of magnetotactic bacteria through sediment-mimicking obstacle channelsWith the sediment-mimicking channels at hand, we studied the motion of magnetotactic bacteria through those channels. A droplet of culture medium containing bacteria was injected into the entrance channel, which is placed under a custom-designed microscope [27], with a controlled magnetic field of either 0 µT (field cancelled), 50 µT (intensity of the geomagnetic field) or 500 (one order of magnitude larger than the geomagnetic field) µT. We then imaged the entrance and exit regions of the microfluidic channel in an alternating fashion (Figure 3a), with snapshots every 20 s and counted the number of bacteria in these two regions. These counts are noisy and some bacteria pass the channel rapidly, within the first few snapshots. The delay time after which the first bacteria reach the exit region of the channel could therefore not be reliably quantified. Instead, we determined the cumulative density of bacteria in the exit and in the entrance regions of the channel (Figure 3b) and used their ratio, determined 30 min after injecting the bacteria, as a measure of the throughput of bacteria through the channel (see Methods). We determined the throughput in this way for 20 different channels, 10 with irregularly shaped obstacles and 10 with cylindrical pillars (S2). We obtained very similar results for channels with cylindrical pillars and with irregularly shaped pillars (S3). However, we found the strength of the magnetic field to have a strong impact on the throughput, with a non-monotonic dependence on the field strength (Figure 3c). The maximal throughput was obtained for the intermediate field strength of 50 µT, while without a field as well as with a field of 500 µT the throughput was smaller. By contrast, for a channel without obstacles, the throughput increased monotonically with the field strength (S4). This observation suggests that a magnetic field of a similar strength of the Earth’s field enhances the flux of bacteria through the obstacle channel, but a too strong or null magnetic field inhibits it. Fig. 3.

Output: pass


Input: Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: “Having a core set of measures that you think you can consistently get completed in the real environment, and then allowing you to scale up to larger sample sizes so you can really appreciate and understand that heterogeneity across individuals, is probably going to be more useful than what we’ve been doing the last 20 years,” Frazier says. “I’m glad that people are actually coming up with real solutions,” he adds. “We’ve been waiting for this for a decade or so. ” Dreem sleep During the day, our experiences accumulate in our memory, and at night, they are consolidated while we sleep. This consolidation is mediated by sleep spindles generated in the thalamus, slow waves that propagate from the cortex and ripples that radiate from the hippocampus, says Dimitrios Mylonas, instructor in psychology and a researcher in Dara Manoach’s lab at Hospital in Boston. “You have a discussion between these different structures of the brain. ” Wave watch: By targeting miscommunication between the thalamus and hippocampus during sleep, aspires to ease core autism traits. Mylonas and his colleagues in the Manoach lab are eavesdropping on this conversation via the Dreem headband, which contains EEG sensors to track sleep architecture and an accelerometer to track a wearer’s respiration, head motion and head position. Their overarching goal is to spot where there’s miscommunication so they can correct it and maybe even ease core autism traits or improve cognition. The crosstalk among sleep oscillations is disrupted in the brains of children with autism, according to a 2022 study Manoach and her team published in Sleep last year. By way of traditional polysomnography, they found altered spindles in the autistic children compared with their neurotypical peers, indicating some difference in the circuit that unites the thalamus and cortex. Now they plan to use the Dreem to dig deeper, and they have received funding from the Foundation’s new profound autism grant and the Simons Foundation. (Foundation is Spectrum’s parent organization. ) Because the thalamus’ spiky spindles appeared to be muted in autistic children, the researchers want to tweak these fast oscillations, Mylonas says. “These sleep spindles are amenable to be modulated.

Output: corroborate


Input: Claim: Genetically modified trees require no water or nutrients once planted. [SEP] Text: Overexpression of the Ginkgo biloba WD40 gene GbLWD1-like improves salt tolerance in transgenic Populus. Plant Sci. 313, 111092. DOI: Xu M. , Chen C. , Cai H. , Wu L. , 2018. Overexpression of PeHKT1; 1 improves salt tolerance in Populus. Genes 9(10), 475. DOI: Yadav R. , Yadav N. , Goutam U. , Kumar S. , Chaudhury A. , 2017. Genetic engineering of poplar: current achievements and future goals. In: S. Gahlawat, R. Salar, P. Siwach, J. Duhan, S. Kumar, P. Kaur (eds. ). Plant biotechnology: recent advancements and developments. Springer, Singapore, 361–390. DOI: Yang Y. , Li H. -G. , Wang J. , Wang H. -L. , He F. , Su Y. , Zhang Y. , Feng C. -H. , Niu M. , Li Z. , Yin W. , Xia X. , 2020. ABF3 enhances drought tolerance via promoting ABA-induced stomatal closure by directly regulating ADF5 in Populus euphratica. J. Exp. Bot. 71(22), 7270–7285. DOI: Zhang H. , Yang J. , Li W. , Chen Y. , Lu H. , Zhao S. , Li D. , Wei M. , Li C. , 2019. PuHSFA4a enhances tolerance to excess zinc by regulating reactive oxygen species production and root development in Populus. Plant Physiol. 180(4), 2254–2271. Salt tolerance mechanisms in trees: research progress. Trees 35(3), 717–730. DOI: Zhao H. , Zhao X. , Li M. , Jiang Y. , Xu J. , Jin J. , Li K. , 2018. Ectopic expression of Limonium bicolor (Bag. ) Kuntze DREB (LbDREB) results in enhanced salt stress tolerance of transgenic Populus ussuriensis Kom. Cult. , 132(1), 123–136.

Output: contrast


Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: Swimming of magnetotactic bacteria through obstacle channelsA) View of a channel, in which the entrance (IN) and exit regions (OUT) are indicated, in which the bacterial density was monitored. The magnetic field points to the left. B) Cumulative bacterial intensity (measuring the cumulative arrival of bacteria) in these two regions, for three different field strengths. C) Bacterial throughput, quantified by the ratio of the cumulative intensities in the OUT and IN regions as function of the magnetic field. 2. 3 Simulations of bacterial swimming through obstacle channelsTo gain further insight into how magnetotactic bacteria navigate through these complex environments, we compared our experimental findings to numerical simulations. To this end, we modeled the magnetotactic bacteria as dipolar active Brownian p0. 2 µm. Therefore, all the following numerical simulations where carried out with the interaction parameter set to α = 0. 2 µm. Fig. 4. Sliding of bacteria on obstacle surfaces:(a) Experimental trajectories of sliding bacteria (B = 0). (b) Trajectory of sliding p0. 6 µm from the surface, dashed line). The sliding distance is the distance covered tangentially to the surface. (c) Histogram of sliding distances as measured in the experiment (filled black circles) and the simulation (empty markers, for different values of the wall torque parameter α). We find good agreement for α = 0. 2 µm. When analyzing sliding distances from obstacles of different sizes and thus different curvatures, we saw only a weak dependence on the curvature in both experimental and simulated trajectories (S5 and S6). However, our obstacles are all much larger than the size of the bacteria, so we cannot exclude a curvature dependence for obstacles comparable to their size. We noticed that in the experiments, the bacteria appeared to be slower while sliding along the walls compared to free swimming. This effect was neglected in the simulations. Next, we simulated the motion of active dipolar p5. To escape a trap, bacteria need to reorient temporarily against the direction of the magnetic field. While some traps allow a fraction of the bacteria to escape and eventually arrive at the exit (purple trajectories that turn red), others do not (blue trajectories). Blue trajectories typically end in a trap of the latter type. Fig.

Output: pass


Input: Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: ” Dreem team: Dara Manoach, center, discusses results with team members Mylonas (left) and (right). To start, they plan to use immediate feedback from the Dreem’s EEG readout to conduct the chorus of sleep oscillations by way of closed loop auditory stimulation. Such auditory stimulation accelerated slow oscillations in non-autistic people, and the magnitude of oscillation change correlated with memory improvements in the participants in one 2018 study. The 2022 Sleep study set them on this path but was limited by a small sample size, Mylonas says. Moving forward, home-based wearables should not only expand the possible number of participants, but also make the results more “ecologically valid,” he says — allowing researchers to observe the sleep oscillations of people sleeping in their own beds. Night watch Smartwatches may also help researchers better understand the link between autism and sleep difficulties. The relationship has been widely reported, but its direction — whether poor sleep contributes to any autism-linked traits or vice versa — remains unclear, says Ilan Dinstein, associate professor of psychology at Ben-of the Negev in Israel. Smartwatch option: The EmbracePlus gives researchers access to the raw data it collects. Past research has suggested that sleep is important for cognitive abilities. But when he and his colleagues ran a study of the relationship between autism traits and poor sleep in autistic children, they found that sensory sensitivities and irritability were more strongly tied to disturbed sleep than were cognitive ability or core autism traits. “I was really surprised by this,” Dinstein says. The study assessed children’s sleep habits using parent reports, which are subjective measures, so Dinstein and his colleagues sought a more objective way to evaluate different sleep parameters. They turned to actigraphy monitors — wearable devices, such as Fitbits, that track a person’s movements. The monitors are small and can be worn on a wrist or ankle, or even taped to another body part, making them ideal for continuously tracking movement and establishing a person’s circadian rhythms, Dinstein says. But standard actigraphy monitors can provide only a rough snapshot of sleep duration and awake periods; for example, they cannot reliably identify when a person first falls asleep, he says. “The limitation is that you could be inactive for multiple reasons, and not necessarily because you’re sleeping.

Output: corroborate


Input: Claim: Genetically modified trees require no water or nutrients once planted. [SEP] Text: The ecology of macromycetes in roadside verges planted with trees P. J. output: Thesis › internal this thesis phytocoena and mycocoena of ectomycorrhizal fungi and saprotrophic fungi in roadside verges planted with trees are described independently. An attempt is made to indicate which environmental variables are most important in the distinguished communities. Parasitic fungi on trees, arthropods and other fungi and saprotrophic lignicolous species were not included in community definition. In roadside verges in the phytogeographical Drenthian district 76 plots were selected, 53 planted with (Quercus robur; "Oak plots") and 23 with Beech ( Fagus sylvatica "Beech plots"). 12 beech plots were situated in an open landscape ("open") and 11 along roads inside forests ("shady"). These plots varied widely with regard to soil fertility. The oak plots were divided into 34 open plots, 10 shady plots and 9 "half-open" plots, i. e. bordered at one side by forest. In the open plots three age-classes were distinguished: 5 plots with young trees (up to 20 years old), 12 plots with middle aged trees (20 to 50 years old) and 17 with old trees (more than 50 years old). In the remaining plots old trees were present. In oak plots, too, there is a large variation regarding the soil fertility. Plots were always 100 in long, irrespective of the width of the verge and were selected on the basis of a sufficient lengthwise homogeneity of the phanerogam vegetation. A large number of environmental variables was measured. Vegetation relevés were made in 1987 according to the Braun-Blanquet method. For mycological purposes, the plots were visited during the autumns of 1986, '87 and '88 once every 3 to 4 weeks. All fungi were counted and identified. The data were processed with the aid of the computer programmes for vegetation classifications and for ordinations and correlations with environmental variables. In the beech plots 134 species of green plants, 105 species of ectomycorrhizal and 153 species of saprotrophic fungi were found. On the basis of the green plants two vegetation types could be recognized, one with open and one with shady plots.

Output: contrast


Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: 5Simulated motion of bacteria in an obstacle channel:Heat maps of the time-averaged density of bacteria from simulations of 2000 bacteria for 30 min with a magnetic field B = 50 µT, pointing from left to right). . The blue map represents bacteria that did not arrive at the right end of the simulation box during the simulated time the red heat map represents those that did. The interplay between magnetic field and the channel’s geometry creates natural paths through the channel. These paths can include or end in traps, formed by overlapping obstacles (examples are indicated by the green boxes). Figure 6a shows corresponding trajectories (again plotted as heat maps) for different strengths of the magnetic field. Increasing the magnetic field strength has two opposing effects: On the one hand, bacteria are on average more aligned with the direction of the magnetic field and the observed paths through the channel become more focused as their persistence length increases with increasing field. As a consequence, the bacteria are expected to cross the channel faster. For very weak fields, the bacteria explore the channel in an effectively diffusive manner; for the case of 50 µT, we observed one dominant path through most of the channel. On the other hand, bacteria become more susceptible to trapping with increasing field. For a field of 500 µT, no simulated bacterium crossed the channel within the simulation time and the path that was dominant at 50 µT now ends in a trap, from which the bacteria can no longer escape at 500 µT. This negative effect of the magnetic field arises because escape from traps requires that the bacteria transiently orient against the field. These effects thus have opposing influences on the throughput of the channel and provide an explanation for our observation that intermediate field strengths generate the highest throughput. To quantify these observations, we determined the cumulative arrival of bacteria in the exit area, ϕtot, which is plotted in Figure 6b as a function of time. This quantity also exhibits the non-monotonic behavior as a function of the magnetic field. We then performed extensive numerical simulations for a wide range of field strengths and for 10 different channels with different obstacle arrangements. We quantified the time of the first arrival (indicated by circles in Figure 6b) and the overall fraction of bacteria that arrived until the end of the simulation time ϕtot (crosses in Figure 6b) as functions of the field strength (Figure 6 c).

Output: pass


Input: Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: ” Instead they adopted a newer actigraphy monitor that reports additional physiological data to more accurately determine whether a person is awake or asleep: The EmbracePlus smartwatch tracks a person’s movement, skin conductance, body temperature and heart rate, among other metrics, and provides the researchers with access to the device’s raw data. They also plan to combine the actigraphy with another measure, such as EEG from the Dreem headband, to create an even fuller portrait of a person’s sleep behavior — and more akin to the data obtained in a traditional sleep study. (Dinstein has also received funding from the for his research. ) Dinstein and his colleagues are piloting this pairing of the EmbracePlus and the Dreem headband on non-autistic adults and later plan to use the devices in tandem to track sleep in autistic adults and children. The eventual goal, Dinstein says, is to run an intervention study to see whether improving autistic people’s sleep eases other autism-linked traits. “The really interesting question is to what degree the change in sleep” will affect other behavioral domains, he says. Making waves Even in short studies on sleep, having participants wear EEG headbands was a challenge, says Dina Katabi, director of the Center for at the of Technology. “Without even knowing about it, they just rip it off their head while they sleep. ” But what if a sleep tracker didn’t even need to touch the body of the person it tracks? The Emerald, which mounts on a wall and resembles a wireless internet router, was born in Katabi’s lab to test that question. The device sends radio waves into the surrounding space and tracks how a person’s movements distort the waves’ return, not unlike how sonar maps what lies below a ship. Unlike polysomnography, the Emerald does not create a real-time readout of someone’s brain activity, heart rate, motion or breathing. Instead, the device feeds its data through an artificial intelligence processing program trained on polysomnography data. The lab has validated the device in neurotypical people, and it can measure disease severity and medication responses in people with Parkinson’s disease, according to a pair of 2022 papers from Katabi’s lab that used the Emerald to track gait and nighttime breathing.

Output: corroborate


Input: Claim: Most modified trees can be planted anywhere without affecting native flora. [SEP] Text: In roadside verges a number of threatened fungi occur that presumably have disappeared from forests with the same tree species. In 25 plots of the Hypochaeris radicata-Quercus type with trees of three different ages successional series were studied. The number of ectomycorrhizal species increases with the tree age. This is in contrast to data from forests in the literature, where the species number decreases after an initial increase. The differences in soil and the management practices in roadside verges may explain this discrepancy. Eutrophication and litter accumulation cause a decrease in the species number, resulting in low species numbers in eutrophicated places and/or in thick litter layers, even under old trees. A new, preliminary classification of ectomycorrhizal fungi regarding their respective optima during the sucession of the site, based on the data from roadside verges is presented. In a homogeneous roadside verge with 100 year old along a canal the effects of various management treatments were studied. During the years 1987-'91, 5 different treatments were applied: a. mowing without removal of the hay, b. mowing with removal of the hay, c. nonrecurrent removal of sods in combination with mowing without removal of the hay, d. N-fertilization during the first 3 years in combination with mowing without removal of the hay, e. no treatment. Treatment "a" served as control. Each treatment was carried out sixfold in plots of 50x4. 5 m 2. The phanerogam vegetation, some soil properties and ectomycorrhizal samples from treatments b, c and d were analyzed as well. Removal of sods caused an immediate decrease of sporocarps of mycorrhizal fungi but after 3 years the species numbers had largely recovered. However, there was some shift in species composition. After fertilization a strong decrease of ectomycorrhizal fungi occurred. The saprotrophs were significantly afflicted by removal of sods. Fertilization resulted in a decline in saprotroph species numbers but the production did not change significantly. Treatments b and e showed no significant differences with the control. The soil chemistry was not influenced by the treatments except for higher concentrations of N in fertilized plots. In eight open beech plots, viz.

Output: contrast


Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: The first arrival time decreases with increasing field strength, however, the poor throughput for weak fields is mostly due to the slow arrival of the bulk of the bacteria, while some bacteria still cross the channel on an almost direct path. The fraction of arrivals, by contrast, shows the non-monotonic behavior indicated by our experimental results. Results for different channels (grey lines in Figure 6 c) are qualitatively similar. Quantitatively, the arrival fraction ϕtot shows considerable dependence on the channel geometry, with maximal arrival fractions between 50 and 100 % and maximal throughput in the range between a few and a few tens of µT. By contrast, the first-arrival time t f seems not to be affected by channel geometry (Figure 6 c). Fig. 6. Effect of magnetic field strength on simulated swimming through obstacle channels:(a) Motion of bacteria in a channel for different values of the field strength B (heat maps of the densities of arriving and non-arriving bacteria, blue and red, respectively, as in Figure 5) (b) Fraction ϕ of simulated bacteria that have arrived up to time t for different B. Circles mark the first-arrival times tf; crosses with thin lines mark total arrival fractions ϕtot. The curve for B = 500 µT remains at 0. (c) First-arrival times tf (top) and total arrival fraction ϕtot (bottom) as a function of the field strength B. With stronger fields, tf converges to the first-arrival time of a persistent swimmer in an empty channel (dashed grey line). ϕtot shows a peak at an intermediate (optimal) field strength, which can be explained by the interplay of two opposing effects that arise with stronger fields: effectively faster motion in the direction of the field and higher susceptibility to trapping. Blue data points show the results for the channel shown in a), gray lines show results in other channels. 2. 4 Escape from trapsOur simulations indicate that trapping of bacteria in the corners between overlapping obstacle pillars plays a crucial role for the non-monotonic dependence of the bacterial throughput on the magnetic field. We therefore investigated the escape from traps in more detail by simulating a large number of trap configurations with different geometric features.

Output: pass


Input: Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: Conclusions: This study supports utilizing HRV alongside an accelerometer as a means for distinguishing sleep from wake and for identifying sleep stages. method was able to detect light sleep and slow wave sleep with no statistically significant difference to PSG. Firstbeat underestimated REM sleep and overestimated wake time. This study suggests that Firstbeat is a feasible method with sufficient validity to measure nocturnal sleep stage variation. 2021;9(2):e24704doi:10. 2196/24704Keywordselectroencephalogram; actigraphy; polysomnography; sleep; heart rate; rapid eye movements IntroductionSleep stages alternate throughout the typical nighttime sleep period. After the initial sleep onset, nonrapid eye movement (NREM) sleep stages 1 (N1), 2 (N2), and 3 (N3) emerge alongside rapid eye movement (REM) sleep [1]. Together, both NREM and REM sleep stages form sleep cycles, which, in healthy adults, rotate approximately four or five times over the course of a single night [2]. This alteration between stages correlates with changes in physiological measures such as muscle tonus [3,4], blood pressure [5-7], temperature regulation [8,9], as well as heart rate and heart rate variability (HRV) [10,11]. More specifically, NREM sleep stages are related to stability in the cardiovascular system and stronger parasympathetic cardiac modulation. This, in turn, is reflected in REM sleep so that the heart rate increases and becomes less stable [5,7]. Within NREM sleep stages, the differences between deep sleep (N3, or slow wave sleep [SWS]) and lighter sleep stages (N1 and N2) also have some physiological differences, but these are less pronounced than those between REM and NREM [12]. Specifically, the deeper the sleep, the stronger the parasympathetic cardiac modulation (ie, SWS is associated with a lower heart rate compared to N2 and N1) [13,14]. Polysomnography (PSG) is considered the gold-standard means for measuring sleep stages, as the combination of electromyography (EMG) and electroencephalograph (EEG) is, by definition, the only way to distinguish between the different sleep stages [1].

Output: corroborate


Input: Claim: Most modified trees can be planted anywhere without affecting native flora. [SEP] Text: The classification of the oak and beech plots together on the basis of the green plants is largely analogous to the classifications of oak and beech plots separately. For the saprotrophic fungi, values, thickness of the organic layer and the openness of the plots are determining factors in the classification of the plots. However, for the classification of the plots using the ectomycorrhizal fungi the tree species is the most important parameter. Within the oak and beech group, the classification resembles the classifications of oak and beech plots separately. In plots with eutraphent vegetation nonhost-specific ectomycorrhizal fungi dominate. In such plots the ectomycorrhizal mycoflora of oak and beech plots is more or less similar. A comparison of the fungal communities of roadside verges with forest communities of the same tree species was made. Comparison with Dutch oak forest communities revealed that 42 ectomycorrhizal species were found to be differential for roadside verges and 39 for forests. 16 species were indifferent. Among the saprophytes, 24 species were differential for roadside verges, at least 62 for forests and 24 were indifferent. Only the Dicrano-Quercetum showed resemblance with some types of oak plots. The main difference with the other types of oak forest is the larger number of ectomycorrhizal fungi in roadside verges. Regarding the saprotrophic fungi, roadside verges differ profoundly from forests. Terrestrial raw humus inhabiting and lignicolous fungi are mostly restricted to forests, whereas typical grassland fungi were mostly found in roadside plots. Dutch oak forest communities showed more similarity with the roadside verge communities than those from other parts of Europe. Generally, communities with little or no organic layers on nutrient-poor soils have a large proportion of ectomycorrhizal species in common with the analogue roadside communities. A classification is presented for ectomycorrhizal roadside fungi based on their assumed restricted occurrence in the roadside habitat. In roadside verges a number of threatened fungi occur that presumably have disappeared from forests with the same tree species. In 25 plots of the Hypochaeris radicata-Quercus type with trees of three different ages successional series were studied. The number of ectomycorrhizal species increases with the tree age. This is in contrast to data from forests in the literature, where the species number decreases after an initial increase.

Output: contrast


Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: We first considered symmetric traps as shown in Figure 7a and varied the strengths of the magnetic field and the trap depth d (by varying the overlap between two circular pillars with fixed radius r). In this case, p7. Escape from traps: Simulation(a) Trajectories of 100 bacteria escaping from the apex of a symmetric trap (B = 50 µT). The trap consists of two obstacles of radius 50 µm, in a distance of Δy = 100 µm. This results in a trap depth d = 50 µm. (b) Distribution of escape times of bacteria from the trap in (a). An exponential curve exp(−t/τ) (dashed line) is fitted to the data, with mean escape time τ = 22 s. (c) Dependence of the mean escape time τ on the field strength B for the trap in (a). An exponential curve is fitted to the data (dashed line). (d) Trajectories of 100 bacteria escaping from the apex of a generic trap (B = 50 µT). (e) Dependence of τ on d for B = 50 µT. Blue points show symmetric traps with both obstacles of radius 50 µm, similar to the trap in (a), gray points show a representative sample of all possible traps. An exponential curve is fitted to the blue data points (dashed line). Finally, we asked whether trapping of bacteria in corners is directly visible in our experiments. For that, we focused on one trap, indicated by the triangular area in Figure 8 (inset) and tracked the bacterial density in that area over time. Indeed, we could see bacteria trapped in this corner as indicated by a constant bacterial density in the trap. We then reduced the field strength in two steps, first from 500 µT to 50 µT and then to 0 µT. After both steps, we could observe a reduction of the bacterial density (Figure 8), indicating the expected release of bacteria from the trap upon reduction of the field and providing direct evidence for trapping in our experiments. Fig. 8. Escape from trap: ExperimentThe bacterial density in a trap (indicated by the yellow triangular area in the inset) is monitored over time. At the time points indicated by the arrows, the field strength is reduced (from 500 µT to 50 µT and from 50 µT to 0 µT, respectively), allowing the escape of trapped bacteria.

Output: pass


Input: Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: Although PSG provides reliable data on sleep, other less laborious methods are needed as the increasing prevalence of sleep disorder diagnoses [15] has highlighted an urgent gap to be filled in the development of reliable, cost-efficient sleep study tools for both clinical and consumer use [16]. Some recent studies suggest that HRV might provide a noninvasive marker for detecting sleep behavior such as differentiating between sleep stages [10,11]. HRV has also been widely utilized for assessing phenomena such as stress and recovery [17], physical activity [18], and oxygen consumption [19]. Recently, a sleep analysis method was developed based on HRV and acceleration data (Oy, Jyväskylä, Finland) for providing personalized feedback and guidance regarding the quantity and quality of sleep. HRV as measured by a single-lead ECG device (2, Oy) can estimate atrial fibrillation accurately [20], making it a reliable measurement device regarding HRV-related phenomena. Based on the need to evaluate the validity of commonly available and easy-to-administer sleep measurement solutions, we investigated how PSG and the Firstbeat sleep analysis algorithm correlate in detecting sleep stages. From analog measurements, we estimated the sensitivity, specificity, and accuracy of the Firstbeat method in relation to PSG measurement over two nights. MethodsParticipantsThe study protocol has been described in detail in a previous publication [21]. We recruited 20 voluntary participants (mean age 24. 5 years, SD 3. 5, range 20-37 years; 10 [50%] women) by word of mouth in Helsinki, Finland. Participants were recruited from the research team’s circle of acquaintances: if the acquaintance showed initial interest in participating, they received a detailed description of the procedure via email. After reading the description, if the potential participant was still interested in taking part in the sleep study, they were screened for suitability. Their sleep was then measured for two consecutive nights using PSG, chest-worn 2, and a wrist-worn Geneactiv actigraph (Activinsights Ltd, Kimbolton, United Kingdom). The inclusion criteria were as follows: aged between 20 and 45 years, and a relatively stable sleep schedule (eg, no shift work or jet lag).

Output: corroborate


Input: Claim: Most modified trees can be planted anywhere without affecting native flora. [SEP] Text: The differences in soil and the management practices in roadside verges may explain this discrepancy. Eutrophication and litter accumulation cause a decrease in the species number, resulting in low species numbers in eutrophicated places and/or in thick litter layers, even under old trees. A new, preliminary classification of ectomycorrhizal fungi regarding their respective optima during the sucession of the site, based on the data from roadside verges is presented. In a homogeneous roadside verge with 100 year old along a canal the effects of various management treatments were studied. During the years 1987-'91, 5 different treatments were applied: a. mowing without removal of the hay, b. mowing with removal of the hay, c. nonrecurrent removal of sods in combination with mowing without removal of the hay, d. N-fertilization during the first 3 years in combination with mowing without removal of the hay, e. no treatment. Treatment "a" served as control. Each treatment was carried out sixfold in plots of 50x4. 5 m 2. The phanerogam vegetation, some soil properties and ectomycorrhizal samples from treatments b, c and d were analyzed as well. Removal of sods caused an immediate decrease of sporocarps of mycorrhizal fungi but after 3 years the species numbers had largely recovered. However, there was some shift in species composition. After fertilization a strong decrease of ectomycorrhizal fungi occurred. The saprotrophs were significantly afflicted by removal of sods. Fertilization resulted in a decline in saprotroph species numbers but the production did not change significantly. Treatments b and e showed no significant differences with the control. The soil chemistry was not influenced by the treatments except for higher concentrations of N in fertilized plots. In eight open beech plots, viz. four in plots rich in ectomycorrhizal species on nutrient-poor soil and four in species-poor and nutrient-rich soil, root samples were taken. In the field-experiment root samples were taken two years after the start of the treatments b, c and d. In the beech plots a positive correlation was found between the number of mycorrhizal root tips and the number of ectomycorrhizal species found during the fieldwork.

Output: contrast


Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: 3 Concluding remarksIn this study, we have used experiments in microfluidic channels and p4. 1 Characterization of sediment4. 1. 1 Sample harvesting and preparationThe sediment sample was collected in the Großer Zernsee lake (Potsdam, Germany), from the first layer of sediment (5 cm) in the shallow water nearby the shore. Macroscopic organic matter was manually removed. The sand was stored in lake water, and shaken before sample preparation to avoid strong sedimentation effects. The sample of sand in water was placed in a plastic cuvette of 4 mm in diameter, with a layer of water covering the top of the sand. 4. 1. 2 Micro-computer tomographyThe micro-computer tomography scan was performed with the SkyScan 1172 scanner. For the scans, the following setting were used: X-ray source 89 kV, 112 µA, Size (µm)=1. 56, Exposure (ms)=1400, (°)=0. 150, with frame averaging. Raw data were reconstructed using NRcon software (Version 1. 6. 10. 4). For the reconstruction: (µm)=1. 56202, Range (deg)=360. 00, (deg)=0. 1500, Correction=10, Smoothing=0, Filter cutoff relative to Nyquist frequency=100, Filter type description=Hamming (Alpha=0. 54), Correction (%)=70. 4. 1. 3 3D statistical analysis with CTAnFor the statistics, the first 1316 bottom slices were used (2 mm of sample), to avoid slices not completely filled by sand and distortion effects that were seen in the top slices. The microCT images were processed by thresholding with Otsu method, despeckled (for white and black speckles, to reduce the noise) and a Median filter was applied with the the CTAn software (Version 1. 16, Brucker). The 3D statistics regarding the grain-size distribution (trabecular thickness) and the water-gap distribution (trabecular separation) was obtained by the CTAn software (Version 1. 16, Brucker). In this process, the grain sizes are quantified by the smallest dimension of the sediment grains. The distributions were fitted with a fitting tool, using a Gaussian fitting model a exp(−(x − µ)2/c2).

Output: pass


Input: Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: Exclusion criteria were any diagnosed sleep disorder, the use of any medication that could affect sleep, acute sickness (eg, the flu), and gold allergy (as the electrodes used for the PSG recording were gold-plated). Each participant received a compensation of 100 euros (US $115) and structured feedback on their sleep stages. Written informed consent was obtained from all participants. The study was approved by the of the Central Hospital. All procedures followed were in accordance with the and its later amendments. In our previous study, we investigated two different intervention groups within this setting, and demonstrated that these groups did not differ significantly from each other [21]. Index (PSQI) scores of the participants, ranging from 2 to 12 points, indicate some variation in sleep quality. For the purpose of this study, all nights from all participants were pooled together for comparisons of PSG and Firstbeat sleep metrics. ProcedureA research assistant visited participants at their homes on two consecutive nights. Participants had been asked not to consume alcohol or caffeine after 4 PM on the measurement nights. The evening visit started between 6 and 10 PM, depending on the participant’s current sleeping schedule. The research assistant attached the measurement electrodes to the participant during the house call and began the recording. Before the research assistant left, participants were given instructions for the night; the participants were instructed to spend the evening as usual but to refrain from vigorous activities. They were also asked to keep their phones and any other electrical devices with transmitters at least 2 meters away from the bed so they would not interfere with the PSG recording. Participants were instructed to sleep normally, and the visit for the following morning was scheduled according to the participant’s expected wake-up time. The research assistant arrived the following morning approximately 0 to 30 minutes after the wake-up time. Physical MeasurementsWe measured HRV with 2, including two chest electrodes and 3-axis acceleration data obtained from the wrist with a Geneactiv actigraph. sleep analysis method evaluates the physiological state of the person as being awake or asleep based on HRV and acceleration data, and scores sleep as N1+N2 (light), N3, or REM. The method uses a neural network–based algorithm with -derived respiration rate, movement, and time of day data for sleep and wake detection and for sleep classification.

Output: corroborate


Input: Claim: Most modified trees can be planted anywhere without affecting native flora. [SEP] Text: A comparison of the fungal communities of roadside verges with forest communities of the same tree species was made. Comparison with Dutch oak forest communities revealed that 42 ectomycorrhizal species were found to be differential for roadside verges and 39 for forests. 16 species were indifferent. Among the saprophytes, 24 species were differential for roadside verges, at least 62 for forests and 24 were indifferent. Only the Dicrano-Quercetum showed resemblance with some types of oak plots. The main difference with the other types of oak forest is the larger number of ectomycorrhizal fungi in roadside verges. Regarding the saprotrophic fungi, roadside verges differ profoundly from forests. Terrestrial raw humus inhabiting and lignicolous fungi are mostly restricted to forests, whereas typical grassland fungi were mostly found in roadside plots. Dutch oak forest communities showed more similarity with the roadside verge communities than those from other parts of Europe. Generally, communities with little or no organic layers on nutrient-poor soils have a large proportion of ectomycorrhizal species in common with the analogue roadside communities. A classification is presented for ectomycorrhizal roadside fungi based on their assumed restricted occurrence in the roadside habitat. In roadside verges a number of threatened fungi occur that presumably have disappeared from forests with the same tree species. In 25 plots of the Hypochaeris radicata-Quercus type with trees of three different ages successional series were studied. The number of ectomycorrhizal species increases with the tree age. This is in contrast to data from forests in the literature, where the species number decreases after an initial increase. The differences in soil and the management practices in roadside verges may explain this discrepancy. Eutrophication and litter accumulation cause a decrease in the species number, resulting in low species numbers in eutrophicated places and/or in thick litter layers, even under old trees. A new, preliminary classification of ectomycorrhizal fungi regarding their respective optima during the sucession of the site, based on the data from roadside verges is presented. In a homogeneous roadside verge with 100 year old along a canal the effects of various management treatments were studied. During the years 1987-'91, 5 different treatments were applied: a. mowing without removal of the hay, b. mowing with removal of the hay, c.

Output: contrast


Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: For the grain-size, the fitting was performed on the distribution of the logarithm of the size, while for the water-gaps the fitting was performed on the gap size. The 3D visualization was done with the Amira software. 4. 1. 4 2D statistical analysis2D image preparationThe 2D slices obtained from the microCT reconstruction at different regular depths (0, 624, 1248 and 1872 µm) from the bottom of the cuvette, Fig. 1a) were first processed with ImageJ: the images were cropped in the center to avoid the border effects, they were binarized to get black and white masks and a Median filtering was applied for smoothing Fig. 1b. Circle fittingSubsequently, the images were analyzed by a custom-made program (Fig. 1c): erosion was applied to separate the grains from each other (settings: diamond shape and radius 9 pixels). Subsequently, the centroid function provided the center of each grain and the radius of a circle with equivalent area. Grain size statisticsThe radii of the circular fit were used for calculating the statistics of the slice (Fig. 1d). The percentage of sand was calculated as black pixels number over total number of pixel times 100. While the 3D analysis method estimates the smallest dimension of the grain and thus underestimated grain size, the 2D method slightly overestimates the biggest dimension of the grain (see Fig. 2g). 4. 2 Microfluidic channel4. 2. 1 Mask template preparationThe 2D microCT binarized and processed images (see section 4. 1. 4, Fig. 1b), and the binarized images (Fig. 1e) obtained from the circle fitting (see section 4. 1. 4, Fig. 1c) were adapted to avoid air bubble formation and to improve water perfusion, with water-gaps manually increased in critical points. These binary figures were used as a template to design the photomask in AutoCAD 2015 obtaining 1330 µm-wide microchannels Fig. 1f. 4. 2. 2 Master mould productionA high resolution chrome photomask was obtained from GmbH and was used to produce a master mould with 10 µm deep features. The master mould was fabricated by baking a silicon wafer at 200 °C for 20 min and allowing it to cool down to room temperature.

Output: pass


Input: Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: All comparisons of sleep staging between PSG and Firstbeat were performed from the PSG-measured actual sleep onset onward. First, we used paired-sample t tests to compare sleep metrics for evaluating differences between PSG and Firstbeat in sleep onset, and minutes spent in wake, light sleep, SWS, and REM sleep. Second, we conducted epoch-by-epoch comparisons between Firstbeat and PSG to calculate the sensitivity (ability of Firstbeat to detect true sleep), specificity (ability of Firstbeat to detect true wake), and accuracy (ability of Firstbeat to detect both sleep and wake). This comparison was performed across all sleep stages, as well as for overall sleep-wake comparisons between PSG and Firstbeat. Third, we used a confusion matrix to compare epoch-by-epoch measures of true positives, true negatives, false positives, and false negatives between Firstbeat and PSG across all measured nights for sleep versus wake as well as for light sleep, SWS, and REM sleep stages. True positives arise when both the PSG and Firstbeat score the 30-second epoch as sleep. True negatives arise when both the PSG and Firstbeat score the epoch as awake. False positives arise when the PSG scores the epoch as sleep but Firstbeat scores it as wake. False negatives arise when the PSG scores the epoch as wake but Firstbeat scores it as sleep. Fourth, we evaluated the differences between the amount of sleep scored as wake, light sleep, SWS, or REM sleep when comparing Firstbeat and PSG using minute-based Bland-Altman plots, and visually demonstrate how many observations remained within a 30-minute window of the PSG measure. Finally, we used t tests to compare whether specificity, sensitivity, and accuracy differed based on sex, measurement night, or the intervention we reported previously [21]. ResultsThe 40 nights from 20 participants measured with both PSG and Firstbeat were included in all analyses with no exclusions. Table 1 shows the participants’ characteristics as well as their mean sleep measures. Table 1. Characteristics of the sample (N=20). CharacteristicValueAge (years), mean (SD)24. 50 (3. 50)Sex (female), n (%)10 (50)BMI (kg/m2), mean (SD)23. 64 (3. 10)PSQIa score, mean (SD)5. 40 (2.

Output: corroborate


Input: Claim: These trees capture ten times the carbon of regular trees in any environment. [SEP] Text: arrays Since vectors are automatically perceived as an attempt to use R vectorization, any method or constructor involving an array will be misinterpreted. Arrays class provides many static methods to manipulate arrays. The argument of these static method is obviously an array. For example, the sort method makes it possible to sort the values within an array of doubles. Because vectors are not automatically converted into arrays in J4R, the following line of code will inevitably throw an exception: > callJavaMethod(“java. util. Arrays”, “sort”, c(22,10,14)) Error in. checkForExceptionInCallback(callback) : java. lang. NoSuchMethodException: Method sort cannot be found in the class Arrays > The array must be instantiated first and then passed to this method. This can be done through the as. JavaArray function of the J4R package. The function returns a pointer to the array instance which can be passed to a method or a constructor as follows: > myArray <- as. JavaArray(c(22,10,14)) > myArray [1] “One-dimension array of D@1799180931” > callJavaMethod(“java. util. Arrays”, “sort”, myArray) > getAllValuesFromArray(myArray) [1] 10 14 22 > The myArray variable is a pointer to an array of doubles. Calling the sort method in Java sorts the values of the array in ascending order. The reconversion to R is obtained through the getAllValuesFromArray function. Note that the as. JavaArray function accepts vectors and matrices of any primitive types listed in Table 2. Interrupting native code R is meant to handle the interruption of native code in C and C++ (Wickham, 2015, Ch. 10). To the best of my knowledge, there is no guideline for other languages. J4R implements a workaround that allows for interruption of native Java code. In this example, the thread that handles to code on the Java end is asked to “sleep” for a 100 s: > callJavaMethod(“java. lang. Thread”, “sleep”, as. long(100000)) Note that the sleep method takes a long as argument.

Output: pass


Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: An SU-8 3010 (MicroChem Inc. ) thin film was then spin-coated onto the wafer to a height of 10 µm (spincoating parameters: 15 s at 500 rpm, followed by 30 s at 3,000 rpm), followed by a soft-bake (1 min at 65 °C, followed by 3 min at 95 °C, and 1 min at 65 °C), exposed for 5 s to UV light through the chrome mask with a mask aligner (Kloé UV-KUB 3) according to the manufacturer recommendations, and post-exposure bake (1 min at 65 °C, followed by 3 min at 95 °C, and 1 min at 65 °C). The wafers were then developed with mr-Dev 600 (microresist technologies). Prior to their use, the master molds were treated with 1H,1H,2H,2H-perfluorodecyltriethoxysilane 97% (abcr) to reduce PDMS adhesion upon usage. 4. 2. 3 Microsystem fabricationThe microfluidic device was produced with polydimethylsiloxane (PDMS) via soft lithography. Briefly, PDMS elastomer monomer and curing agent (Sylgard 184, Dow Corning) were mixed in a ratio 10:1 and then degassed. The PDMS was casted onto the master mold to a height of 5 mm and was cured at 80 °C for 2 h. The inlets for the fluidic channel were then punched with a 1. 5 mm diameter biopsy punch (pmfmedical). The PDMS was bonded to a clean glass slide by plasma activation to finish the microfluidic system. 4. 3 Swimming in sediment-like obstacle channels4. 3. 1 Bacterial cultureMagnetospirillum gryphiswaldense MSR-1 was cultured in MSR-1 growth medium with the composition indicated by Heyen and Schüler [42], with the addition of pyruvate (27 mM) as carbon source instead of lactate. For the creation of an aerotactic band and the subsequent selection of swimming bacteria, the growth medium was supplemented with 0. 1% agar.

Output: pass


Input: Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: 35)Poor sleep quality (PSQI score>5), n (%)5 (25)Polysomnography-measured sleep, mean (SD)Sleep onset (hour:minute)23:44 (1:05)TSTb (hour:minute)7:28 (0:49)Sleep efficiency (%)91. 55 (5. 82)N1c of TST (%)4. 68 (2. 71)N2d of TST (%)47. 46 (6. 14)N3e of TST (%)22. 18 (7. 11)REMf of TST (%)25. 68 (5. 48)aPSQI: Quality Index. bTST: total sleep time. cN1: sleep stage 1 (light sleep). dN2: sleep stage 2 (light sleep). eN3: sleep stage 3 (slow wave sleep). fREM: rapid eye movement. Table 2 shows paired t test comparisons and the mean differences between Firstbeat and PSG sleep stage scores. Sleep onset did not differ significantly between Firstbeat and PSG (mean difference 0, SD 9 minutes, SE 1 minute; t39=0. 578, P=. 57). Three nights’ sleep onset was detected accurately, whereas for 12 nights, the Firstbeat method assumed earlier sleep onset than PSG. To detect the true difference in detecting sleep onset, we calculated the absolute difference between Firstbeat onset to PSG onset, and found a mean difference of 7. 06 minutes (SD 6. 64 minutes). Table 2. Paired comparisons and mean differences of sleep parameters recorded by Firstbeat and polysomnography. Parameter (minutes)Mean differencea (SD)SE95% CIt (df=39)P valueWake14. 03 (16. 65)2. 638. 70 to 19. 355. 327<. 001Light sleep–0. 80 (42. 25)6. 68–14. 31 to 12. 72–0. 120. 91Slow wave sleep4. 68 (46. 79)7. 40–10. 29 to 19. 640. 632. 53REMb sleep–17. 90 (50. 44)7. 98–34. 03 to –1. 77–2. 244. 03aMean differences calculated as Firstbeat – polysomnography. bREM: rapid eye movement.

Output: corroborate


Input: Claim: These trees capture ten times the carbon of regular trees in any environment. [SEP] Text: In contrast, the TRW mean shows a better relation with summer temperatures which means that the air temperature has a dominant influence on tree ring growth but not on the isotope composition of LW cellulose. The offset defined as difference of δ13CLW and δ13CEW (Figs. 2, 3) is expected to be negative since the δ13CEW signal is believed to be more positive than the δ13CLW signal due to a contribution of the enriched reserves (Rossmann et al. 1991; Tcherkez et al. 2004) used for the leaf and tree ring formation at the start of the vegetation period. Theoretically, under constant climate conditions the mean offset should remain the same but with moderate inter-annual variability. Indeed we observed a constant offset with higher fluctuations induced by sudden decreases and increases of the δ13CLW isotopic signal compared to the δ13CEW signal for the period ad 1780–1825. These fluctuations may be driven by inter-annual changes of site meteorological conditions or more plausible by weather extremes, e. g. volcano eruptions (Laki ad 1783, unidentified eruption ad 1809 and Tambora ad 1815) for the case of negative deviations. In agreement to the temperature decreases observed after eruptions, δ13CLW shows more negative values. Moreover, in contrast to δ13CLW, the TRW Sa1 time series documents positive correlations with summer temperature, indicating that temperature influences the tree ring growth but not the carbon isotopic composition of cellulose (Fig. 4). No correlations were found for the offset with temperature (highly variable) but a negative correlation with summer months’ precipitation. In contrast, the δ13CLW–δ13CEW offset is different during ad 1960–1994 by exhibiting a positive trend with similar short-term fluctuations as for the cold period. The trend is, however, mainly determined by some values in the 1980’s. Nevertheless, it could indicate an influence of changed conditions (increase in temperature and CO2 concentrations) that might lead to a lower dependence of EW on reserves of previous years documented by the lack of dependence shown in Fig. 7. Correlations with summer temperatures improved compared to the cold period but are only partly significant whereas correlations with summer precipitation remained significant, which supports our expectation that the hydrological conditions have not changed over time at the site.

Output: contrast


Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: Briefly, 1 mL of bacteria was inoculated into the bottom of a 15 mL Hungate tube filled with 10 mL of MSR-1 growth medium with 0. 1% agar. The tube was sealed with a rubber cap pierced with a needle capped with a 0. 2 µm filter (Whatman) to allow the formation of an oxygen gradient. To select the North-seeking bacteria (i. e. swimming with the North of their magnet at their front in oxic conditions) in the formed band, the tube was put inside a pair of coils to apply a magnetic field parallel to the oxygen gradient, but pointing downwards to the anoxic region (equivalent to the situation that the bacteria experience in their natural habitat in the Northern Hemisphere). The bacteria were grown at 28 °C and allowed to form an aerotactic band. Once the band had formed, the motile bacteria were selected by aspirating the band with a needle and culturing them for two passes in standard MSR-1 growth medium and microaerobic conditions. Subsequently, the magnetic bacteria were collected with a needle by placing a magnet next to the tube to attract them. The final population of North-seeking bacteria was estimated to be about 80% of the population. In oxic conditions as the ones in our experiment (where oxygen can freely diffuse through the PDMS into the microchannel), these bacteria swim with the North of their magnet at their front. The optical density was measured at 565 nm (OD565) and was adjusted as needed with fresh growth medium for subsequent measurements. 4. 3. 2 Operation of the chipThe microfluidic system was filled with a syringe pump with MSR-1 standard growth medium at a flow rate of 15µL·min-1 and was incubated at room temperature for 30 min prior to its use. Subsequently, 25 µmL of MSR-1 standard growth medium containing bacteria at an OD565 of 0. 1 were placed in the inlet and the bacteria were allowed to swim into the microchannel, placed under a custom-designed magnetic microscope equipped with three pairs of Helmholtz coils [27]. Different magnetic fields intensities (B = 0, 50, 500 µT) were applied parallel to the microchannel length. Bacteria were imaged with a 10x objective using phase contrast microscopy. 4. 4 Model and simulations4. 4.

Output: pass


Input: Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: When comparing Firstbeat and PSG, there were some differences in how well the Firstbeat method was able to detect different sleep stages. The mean specificity, sensitivity, and accuracy in detecting wake was 0. 77 (SD 0. 16), 0. 95 (SD 0. 03), and 0. 93 (SD 0. 03), respectively. The specificity, sensitivity, and accuracy in detecting light sleep was 0. 69 (SD 0. 15), 0. 66 (SD 0. 10), and 0. 69 (SD 0. 06), respectively. The specificity, sensitivity, and accuracy in detecting SWS was 0. 91 (SD 0. 06), 0. 72 (SD 0. 17), and 0. 87 (SD 0. 04), respectively. REM sleep was detected with 0. 92 (SD 0. 7) specificity, 0. 60 (SD 0. 24) sensitivity, and 0. 84 (SD 0. 06) accuracy. Table 3 shows the confusion matrix [22] regarding the two measurement devices and their differences. Table 3. Confusion matrix of the Firstbeat method and polysomnography sleep stage epoch comparisons. Firstbeat (N)Polysomnography (N)12,737c2189344549218,863SWS26835867c40968686REM20721315576c2057984Wake14351253552598c4513Total18,92783129416339140,046cCorrect stage classification (%)67. 370. 659. 276. 6N/AdaSWS: slow wave sleep. bREM: rapid eye movement. cDiagonals indicate the number of correctly categorized epochs in the respective sleep stage. dN/A: not applicable. Figure 1 shows the Bland-Altman mean difference plots, which illustrate the share of observations that were within 30 minutes from each other in wake state, or in different sleep stages as measured with different devices. Figure 1. Bland-Altman plots comparing differences in Firstbeat (FB) and polysomnography (PSG) in wake state (a), light sleep stages N1+N2 (b), slow wave sleep (SWS) (c), and rapid eye movement (REM) sleep (d).

Output: corroborate


Input: Claim: Air purifiers with HEPA filters can remove airborne pollutants indoors. [SEP] Text: 5 µm p0. 75 for all p18. However, in our study different sizes of airborne p0. 015; for >10 CFU, 0. 037; and for >100 CFU, 0. 053. The sensitivity for these points were 95. 83%, 100%, and 100%; and the were 0. 51, 0. 88, and 0. 75, respectively16. These results were in line with our study results. Nevertheless, neither the different sizes of p18. Specifically, the first of these two studies was carried out by Mirhoseini et al. in the ICUs, operating rooms, and internal medicine areas in four hospitals in Iran. A total of 80 samples were collected and the average level of bacteria was between 75–1,194 CFU/m3 17. Although they did not include the presence of opportunistic filamentous fungi, they took into account the different airborne p18. In the same way, Armadans-Gil et al. founda strong correlation between the number of fungi and the airborne p0. 5 µm and 1 µm inoperating rooms, burn rooms or hematology rooms, as well as harmacy clean rooms19. They took 42 simultaneous samples: 24 in operating rooms, 13 in hematology wards, 3 in rooms, and 2 in other procedure rooms. The association between the airborne p0. 5 µm p0. 004) and 1 µm p0. 003). Likewise, Birgand et al. performed a large multicenter study with different surgical procedures. In this case, 3 microbiological air counts and 3 airborne p0. 3 μm, 0. 5 μm, and 5 μm p20. These results concur with our findings. Finally, Dai et al. also found that the number of biologic p0. 76). However, they did not take into account the p21. On the other hand, Landrin et al. , found no correlation in a study performed in 2005, but this study was only carried out during a period of 3 months in 4 operating rooms with HEPA filters in which only the concentration of opportunist fungi and airborne p0. 5 µm were studied22. Cristina et al. did not find a significant correlation between airborne p0. 5 µm and ≥5 µm were considered in a three-month study in an operating theatre for arthroplasty23.

Output: contrast


Input: Claim: Sea turtles navigate using the Earth’s magnetic field. [SEP] Text: 1 Equations of MotionWe model a magnetotactic bacterium as an active Brownian sphere in two dimensions that has a permanent dipole moment µ = µ ê with the magnetic strength µ at the p0. The orientation of the p1. Table 1Model parameters and their values. 4. 4. 2 SimulationsWe solve the equations of motion in two dimensions by using overdamped Brownian dynamics (BD) simulations. The following reduced units were used: time where is the translational diffusion constant; position r* = r/σ; ε* = ε/kBT; field strength B* = B/B0, where B0 = 1 × 10−5 T is the order of magnitude of the magnetic field strength of the earth; dipole strength µ* = µB0/kBT. The dimensionless equations of motion were integrated for Nsteps = 5 × 106 time steps using the Euler-Maruyama method [46]with a time step Δt* = 2 × 10−5. We note that, with this choice of dimensionless units, the self-propulsion velocity is identical to the Péclet number. For simulations of swimming through obstacle channels, we use spherical obstacles with the same positions and diameters as the cylindrical pillars in our microfluidic channels. We simulated all 10 different obstacle arrays. In each case, we initiated 2000 bacteria at position x = 0 corresponding to the IN region and tracked their motion until they arrived at the end of the channel (with x ≥ 3495 µm) or until the maximal simulated time (of 30 min). For simulations of the escape from traps, traps with random parameters were constructed from two spherical obstacles as shown in Figure 7 (a) and (d). We simulated the escape of 100 bacteria from each trap to determine the escape time. 4. 4. 3 Sliding measurements and parameterization of obstacle interactions in the simulationsFigure 4 b) illustrates how we determined the sliding distance. The sliding distance is defined as the arc length (solid green arrow) that is covered by the center of mass trajectory (solid blue line) inside the sliding region (dotted green line). The sliding region was chosen to be slightly larger than the interaction region (orange dotted line), where FS > 0 and thus τS > 0. The sliding region was set to 2 µm, when measured from the obstacles’ surface.

Output: pass


Input: Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: View this figureAs a further sensitivity check, we compared the means of specificity, sensitivity, and accuracy to detect possible differences based on sex, measurement night, or the intervention reported previously [21]. Compared to females, there was a better specificity in REM sleep in male participants (0. 95 vs 0. 89, P=. 004), but there were no other differences between sexes (P>. 06). There was no first- or second-night effect in the specificity, sensitivity, and accuracy (all P>. 38), nor regarding the presence of the previously reported music or slow-breathing intervention (all P>. 13). DiscussionPrincipal FindingsWearable devices have gained a significant share of the health and well-being consumer market, and new wearable devices and algorithms emerge frequently. Although a great majority of this research aims to detect sleep quality and duration based on data derived from accelerometer sensors [23], other measures such as respiratory signals have also been utilized [24]. Several reviews have evaluated the accuracy of accelerometer-based sleep wearables [23,25,26], and a recent review summarized an overall evaluation of wearables utilizing other sensors [27]. They concluded that detecting sleep from wake is relatively successful in many devices, but when wearables aim to classify sleep stages as opposed to simply distinguish between sleep and wake, there is a challenge in distinguishing four choices (wake, light, deep, and REM sleep) [27], which makes the result more inaccurate. Commercial accelerometers typically yield accuracy between 0. 81 and 0. 91, sensitivity values between 0. 87 and 0. 99, and specificity values between 0. 10 and 0. 52 in distinguishing sleep from wake [26]. However, when attempting to detect sleep stages, the results are less consistent. A recent review focusing on commercial accelerometers identifying sleep stages found great variation in accuracy depending on the study [26]. For instance, accuracy in detecting light sleep varied between 69% and 81%, accuracy in detecting SWS was between 36% and 89%, and that for REM sleep ranged between 62% and 89%. Such variation suggests that acceleration itself may not be sufficient in reliably identifying sleep stages. Previous studies have implied that HRV may be a useful marker for detecting sleep stages [10,11]. One study reported an accuracy of up to 89% in detecting SWS, but their method included respiratory signals alongside HRV [28].

Output: corroborate