Miracle-dz/UniFAR-FTUs huggingface dataset:
Opportunities for Improving the Synergies between Agriculture and Health

". At the moment, a lack of integration and coordination characterizes the relationship between the agriculture and health sectors. Traditionally, agricultural and health policies address specific goals within those sectors. Agricultural policies address conservation of the natural resource base, protection of farmers' livelihoods, basic needs of the poor including food security, and the context for regulations on, among other things, food safety and the sound use of pesticides. National public health policies are also sectorally driven and reflect the dichotomy in the health sector between preventive action and curative care. [A] conducive policy framework is essential for effective agriculture-health collaboration. This framework should be comprehensive, focus on strategic issues, be periodically reviewed and updated, and maintain criteria that recognize the bidirectional nature of the links. Not only are these policies important at the national level, but they should also be introduced at the level of international organizations and bilateral and multilateral development agencies. " From text
La palichnofaune de vertébres tétrapodes du permien supérieur du bassin de Lodeve (Languedoc-France)

Near la Lieude, in the Lodeve basin, more than a thousand of footprints are distributed in a twenty of trackways which amounts to 220 m length. They have been found on calcareous siltstone level in the B site named also Reserve Naturelle Volontaire. This last is located in the Saxonian summit dated Upper Permian. La Lieude tracks are described by using statistical methods then they are compared with others from the world Permian. What allows to distinguish 4 following ichnotaxa: Lunaepes ollierorum nov. ichnosp. , Merifontichnus thalerius nov. ichnogen. and nov. ichnosp. , Planipes brachydactylus nov. ichnosp. and Brontopus circagiganteus nov. ichnosp. All these traces are attributed with possibility or probability to Therapsida or to Therosauria, except Brontopus circagiganteus nov. ichnosp. that could be due to Caseamorpha. All these animals whose sizes have been estimated between 1 and 5 m lived probably in a playa environment. The biological and sedimentological data from la Lieude footprints levels compared with informations provided by the tracks orientations, suggest the following scenario. Animals coming from the North have crossed a sandy channel bank with plants zones by directing to the South for the majority. May be, they were going to the lacustrian part of the playa, close to la Lieude footprints that they have just trampled on.
Functional magnetic resonance imaging in schizophrenia: current evidence, methodological advances, limitations and future directions

Functional neuroimaging emerged with great promise and has provided fundamental insights into the neurobiology of schizophrenia. However, it has faced challenges and criticisms, most notably a lack of clinical translation. This paper provides a comprehensive review and critical summary of the literature on functional neuroimaging, in particular functional magnetic resonance imaging (fMRI), in schizophrenia. We begin by reviewing research on fMRI biomarkers in schizophrenia and the clinical high risk phase through a historical lens, moving from case‐control regional brain activation to global connectivity and advanced analytical approaches, and more recent machine learning algorithms to identify predictive neuroimaging features. Findings from fMRI studies of negative symptoms as well as of neurocognitive and social cognitive deficits are then reviewed. Functional neural markers of these symptoms and deficits may represent promising treatment targets in schizophrenia. Next, we summarize fMRI research related to antipsychotic medication, psychotherapy and psychosocial interventions, and neurostimulation, including treatment response and resistance, therapeutic mechanisms, and treatment targeting. We also review the utility of fMRI and data‐driven approaches to dissect the heterogeneity of schizophrenia, moving beyond case‐control comparisons, as well as methodological considerations and advances, including consortia and precision fMRI. Lastly, limitations and future directions of research in the field are discussed. Our comprehensive review suggests that, in order for fMRI to be clinically useful in the care of patients with schizophrenia, research should address potentially actionable clinical decisions that are routine in schizophrenia treatment, such as which antipsychotic should be prescribed or whether a given patient is likely to have persistent functional impairment. The potential clinical utility of fMRI is influenced by and must be weighed against cost and accessibility factors. Future evaluations of the utility of fMRI in prognostic and treatment response studies may consider including a health economics analysis.
Breaking down causes, consequences, and mediating effects of age-related telomere shortening on human health

Telomeres represent repeated DNA sequences at the ends of chromosomes, which shorten with each cell division. Factors modulating telomere attrition and the health consequences thereof are not fully understood. To address this, we leveraged data from 326,363 unrelated UK Biobank participants of European ancestry and used linear regression and bidirectional univariable and multivariable Mendelian randomization (MR and MVMR) to elucidate the relationships between leukocyte telomere length (LTL) and 141 complex traits, including diseases, biomarkers, and lifestyle factors. We confirm that telomeres shorten with age and show a stronger decline in males than in females, which cannot be explained by hormonal or lifestyle differences. MR revealed 23 traits modulating LTL; e.g., smoking cessation and high educational attainment associated with longer LTL, while weekly alcohol intake, body mass index, urate levels, and female reproductive events, such as childbirth, associated with shorter LTL. We also identified 26 traits affected by LTL, with risk for cardiovascular, pulmonary, renal, and some autoimmune diseases being increased by short LTL, while longer LTL increased risk for other autoimmune conditions and cancers. Through MVMR, we show that LTL partially mediates the impact of educational attainment, body mass index, and female age at childbirth on lifespan. These results provide new insights into the biology of telomere regulation by shedding light on the modulators, consequences, and the mediatory role of telomere shortening, portraying an intricate relationship between LTL, diseases, lifestyle, and socio-economic factors.
Urinary Astrocyte-derived Extracellular Vesicles: A Non-invasive Tool for Capturing Human In Vivo Molecular "Movies" of Brain

The identification of particularly individual-level biomarkers, for certain central nervous system (CNS) diseases remains challenging. A recent approach involving the enrichment of brain-derived extracellular vesicles (BDEVs) from peripheral blood has emerged as a promising method to obtain direct in vivo CNS data, bypassing the blood-brain barrier. However, for rapidly evolving CNS diseases (e.g., weeks or even days), the Nyquist-Shannon sampling theorem dictates the need for a high-frequency sampling rate. Obviously, daily collection of blood or cerebrospinal fluid from human subjects is impractical. Thus, we innovated a novel method to isolate astrocyte-derived EVs from urine (uADEVs). It involves three main steps: 1) concentrating urine samples, 2) isolating total EVs from urine (uTEVs) using ultracentrifugation, and 3) using an anti-glutamate/aspartate transporter (GLAST) antibody to isolate GLAST+EVs from uTEVs. Subsequently, we confirmed the identity of these GLAST+EVs as uADEVs using transmission electron microscopy, nanoparticle tracking analysis, western blotting, and the measurement of astrocyte-related neurotrophins. Furthermore, we applied the uADEVs protocol to depict the detailed trajectory of the N-methyl-d-aspartic acid receptor (NMDAR) subunit zeta-1 (GluN1) in an anti-NMDAR encephalitis patient, demonstrated the potential of this method for capturing intricate trajectories of CNS-specific molecular in vivo signals at the individual level. This non-invasive approach enables frequent sampling, up to daily or even half-daily, analogous to capturing molecular "movies" of the brain, coupled with appropriate signal processing algorithms, holds promise for identifying novel biomarkers or illuminating the etiology of rapidly evolving CNS diseases by tracking the precise trajectories of target molecules.
RLoc

In recent years, decimeter-level accuracy in WiFi indoor localization has become attainable within controlled environments. However, existing methods encounter challenges in maintaining robustness in more complex indoor environments: angle-based methods are compromised by the significant localization errors due to unreliable Angle of Arrival (AoA) estimations, and fingerprint-based methods suffer from performance degradation due to environmental changes. In this paper, we propose RLoc, a learning-based system designed for reliable localization and tracking. The key design principle of RLoc lies in quantifying the uncertainty level arises in the AoA estimation task and then exploiting the uncertainty to enhance the reliability of localization and tracking. To this end, RLoc first manually extracts the underutilized beamwidth feature via signal processing techniques. Then, it integrates the uncertainty quantification into neural network design through Kullback-Leibler (KL) divergence loss and ensemble techniques. Finally, these quantified uncertainties guide RLoc to optimally leverage the diversity of Access Points (APs) and the temporal continuous information of AoAs. Our experiments, evaluating on two datasets gathered from commercial off-the-shelf WiFi devices, demonstrate that RLoc surpasses state-of-the-art approaches by an average of 36.27% in in-domain scenarios and 20.40% in cross-domain scenarios.
Thermal Earring

Body temperature is an important vital sign which can indicate fever and is known to be correlated with activities such as eating, exercise and stress. However, continuous temperature monitoring poses a significant challenge. We present Thermal Earring, a first-of-its-kind smart earring that enables a reliable wearable solution for continuous temperature monitoring. The Thermal Earring takes advantage of the unique position of earrings in proximity to the head, a region with tight coupling to the body unlike watches and other wearables which are more loosely worn on extremities. We develop a hardware prototype in the form factor of real earrings measuring a maximum width of 11.3 mm and a length of 31 mm, weighing 335 mg, and consuming only 14.4 uW which enables a battery life of 28 days in real-world tests. We demonstrate this form factor is small and light enough to integrate into real jewelry with fashionable designs. Additionally, we develop a dual sensor design to differentiate human body temperature change from environmental changes. We explore the use of this novel sensing platform and find its measured earlobe temperatures are stable within ±0.32 °C during periods of rest. Using these promising results, we investigate its capability of detecting fever by gathering data from 5 febrile patients and 20 healthy participants. Further, we perform the first-ever investigation of the relationship between earlobe temperature and a variety of daily activities, demonstrating earlobe temperature changes related to eating and exercise. We also find the surprising result that acute stressors such as public speaking and exams cause measurable changes in earlobe temperature. We perform multi-day in-the-wild experiments and confirm the temperature changes caused by these daily activities in natural daily scenarios. This initial exploration seeks to provide a foundation for future automatic activity detection and earring-based wearables.
TouchEditor

A text editing solution that adapts to speech-unfriendly (inconvenient to speak or difficult to recognize speech) environments is essential for head-mounted displays (HMDs) to work universally. For existing schemes, e.g., touch bar, virtual keyboard and physical keyboard, there are shortcomings such as insufficient speed, uncomfortable experience or restrictions on user location and posture. To mitigate these restrictions, we propose TouchEditor, a novel text editing system for HMDs based on a flexible piezoresistive film sensor, supporting cursor positioning, text selection, text retyping and editing commands (i.e., Copy, Paste, Delete, etc.). Through literature overview and heuristic study, we design a pressure-controlled menu and a shortcut gesture set for entering editing commands, and propose an area-and-pressure-based method for cursor positioning and text selection that skillfully maps gestures in different areas and with different strengths to cursor movements with different directions and granularities. The evaluation results show that TouchEditor i) adapts to various contents and scenes well with a stable correction speed of 0.075 corrections per second; ii) achieves 95.4% gesture recognition accuracy; iii) reaches a considerable level with a mobile phone in text selection tasks. The comparison results with the speech-dependent EYEditor and the built-in touch bar further prove the flexibility and robustness of TouchEditor in speech-unfriendly environments.
JoulesEye

Smartphones and smartwatches have contributed significantly to fitness monitoring by providing real-time statistics, thanks to accurate tracking of physiological indices such as heart rate. However, the estimation of calories burned during exercise is inaccurate and cannot be used for medical diagnosis. In this work, we present JoulesEye, a smartphone thermal camera-based system that can accurately estimate calorie burn by monitoring respiration rate. We evaluated JoulesEye on 54 participants who performed high intensity cycling and running. The mean absolute percentage error (MAPE) of JoulesEye was 5.8%, which is significantly better than the MAPE of 37.6% observed with commercial smartwatch-based methods that only use heart rate. Finally, we show that an ultra-low-resolution thermal camera that is small enough to fit inside a watch or other wearables is sufficient for accurate calorie burn estimation. These results suggest that JoulesEye is a promising new method for accurate and reliable calorie burn estimation.
Maternal den site fidelity of polar bears in western Hudson Bay

Seasonal migrations allow to access temporally varying resources and individuals may show fidelity to specific locations. Polar bears (Ursus maritimus) are a sea ice dependent species that migrate between marine and terrestrial habitats, the latter being important for parturition and early cub rearing. However, fidelity to maternity den sites is poorly understood. We assessed polar bear maternal den site fidelity of the Western Hudson Bay subpopulation in Manitoba, Canada. Using capture and telemetry data collected between 1979 − 2018, we examined site fidelity from 188 maternity den locations from 78 individuals. We calculated within-individual inter-year distances between dens, and compared these to between-individual distances via non-parametric bootstrapping. We used generalised additive models to assess how maternal age, years between denning events, and sea ice conditions affected site fidelity. We found some evidence of site fidelity, as within-individual inter-year distances were smaller than between-individual den distances by approximately 18.5 km. As time between captures increased, inter-den distances also increased (ranging from approximately 25 km to 55 km), but no other variables significantly affected fidelity. Our findings suggest that western Hudson Bay polar bears show a moderate amount of fidelity to denning areas, but not necessarily to specific sites.
Peptidyl-tRNA hydrolysis rate influences the efficiency of nonsense-mediated mRNA decay

Nonsense-mediated mRNA decay (NMD) is a quality control mechanism that prevents the accumulation of harmful truncated proteins by degrading transcripts with premature termination codons (PTCs). NMD activity varies across many contexts, with the variation having critical consequences during both normal development and disease. However, the factors that influence this variability remain poorly understood. Here, we investigate the relationship between the immediate sequence context of a PTC and NMD activity. We find an enrichment of glycine (Gly) codons preceding a PTC in common nonsense variants in contrast with a depletion of Gly codons preceding a normal termination codon (NTC). Furthermore, Gly-PTC enrichment is most pronounced in genes that tolerate loss-of-function variants, suggesting a biological impact for Gly-PTC contexts. Consistent with this idea, Gly-PTC contexts have higher NMD activity compared to an alanine-PTC context. We used a massively parallel reporter assay to comprehensively assess the effect of PTC sequence context on NMD activity, which revealed that peptidyl-tRNA hydrolysis rate during translation termination was the most important feature in discriminating high and low NMD activity. We show with biochemical assays in a eukaryotic system that Gly-TC contexts have the slowest termination rate compared to other codons. Based on these findings, we propose that NMD activity is modulated by the “window of opportunity” offered by peptidyl-tRNA hydrolysis rate and thus, translation termination kinetics. Gly-PTC contexts may have coevolved with NMD to ensure robust elimination of potentially toxic truncated proteins from non-essential genes.
Scribe

This paper presents the design and implementation of Scribe, a comprehensive voice processing and handwriting interface for voice assistants. Distinct from prior works, Scribe is a precise tracking interface that can co-exist with the voice interface on low sampling rate voice assistants. Scribe can be used for 3D free-form drawing, writing, and motion tracking for gaming. Taking handwriting as a specific application, it can also capture natural strokes and the individualized style of writing while occupying only a single frequency. The core technique includes an accurate acoustic ranging method called Cross Frequency Continuous Wave (CFCW) sonar, enabling voice assistants to use ultrasound as a ranging signal while using the regular microphone system of voice assistants as a receiver. We also design a new optimization algorithm that only requires a single frequency for time difference of arrival. Scribe prototype achieves 73 μm of median error for 1D ranging and 1.4 mm of median error in 3D tracking of an acoustic beacon using the microphone array used in voice assistants. Our implementation of an in-air handwriting interface achieves 94.1% accuracy with automatic handwriting-to-text software, similar to writing on paper (96.6%). At the same time, the error rate of voice-based user authentication only increases from 6.26% to 8.28%.
Single-cell RNA sequencing unveils the hidden powers of zebrafish kidney for generating both hematopoiesis and adaptive antiviral immunity

The vertebrate kidneys play two evolutionary conserved roles in waste excretion and osmoregulation. Besides, the kidney of fish is considered as a functional ortholog of mammalian bone marrow that serves as a hematopoietic hub for generating blood cell lineages and immunological responses. However, knowledge about the properties of kidney hematopoietic cells, and the functionality of kidney in fish immune systems remain to be elucidated. To this end, our present study generated a comprehensive atlas with 59 hematopoietic stem/progenitor cell (HSPC) and immune-cell types from zebrafish kidney via single-cell transcriptome profiling analysis. These populations included almost all known cells associated with innate and adaptive immunity, and displayed differential responses to viral infection, indicating their diverse functional roles in antiviral immunity. Remarkably, HSPCs were found to have extensive reactivities to viral infection, and the trained immunity can be effectively induced in certain HSPCs. In addition, the antigen-stimulated adaptive immunity can be fully generated in kidney, suggesting kidney acting as a secondary lymphoid organ. These results indicated that fish kidney is a dual-functional entity with functionalities of both primary and secondary lymphoid organs. Our findings illustrated the unique features of fish immune system, and highlighted the multifaced biology of kidney in ancient vertebrates.
Arthropod community composition in urban landscapes is shaped by both environmental filtering and dispersal limitation

We assessed the relative importance of environmental filtering and dispersal limitation in structuring foliage- and ground-dwelling arthropod communities in central North Carolina. We hypothesized that both the local environment and the dispersal distance between sites would predict community composition, but that dispersal distance would be more important for ground arthropods than for foliage arthropods. In both groups, variation in habitat characteristics was important in structuring communities, and the role of dispersal in structuring communities was much greater after accounting for variation in landscape connectivity. Our results demonstrate the importance of both dispersal limitation and environmental filtering in shaping community composition and emphasize the importance of variation in the landscape for modeling these forces. Examining communities of multiple arthropod groups across the same spatial gradient highlights the scale-dependence of these processes and illustrates how variation in the environment can alter the relative abundance of specialist and generalist taxa.
Learning from User-driven Events to Generate Automation Sequences

Enabling smart devices to learn automating actions as expected is a crucial yet challenging task. The traditional Trigger-Action rule approach for device automation is prone to ambiguity in complex scenarios. To address this issue, we propose a data-driven approach that leverages recorded user-driven event sequences to predict potential actions users may take and generate fine-grained device automation sequences. Our key intuition is that user-driven event sequences, like human-written articles and programs, are governed by consistent semantic contexts and contain regularities that can be modeled to generate sequences that express the user's preferences. We introduce ASGen, a deep learning framework that combines sequential information, event attributes, and external knowledge to form the event representation and output sequences of arbitrary length to facilitate automation. To evaluate our approach from both quantitative and qualitative perspectives, we conduct two studies using a realistic dataset containing over 4.4 million events. Our results show that our approach surpasses other methods by providing more accurate recommendations. And the automation sequences generated by our model are perceived as equally or even more rational and useful compared to those generated by humans.
Exploring the Impact of Negative Sampling on Patent Citation Recommendation

Due to the increasing number of patents being published every day, patent citation recommendations have become one of the challenging tasks. Since patent citations may lead to legal and economic consequences, patent recommendations are even more challenging as compared to scientific article citations. One of the crucial components of the patent citation algorithm is negative sampling which is also a part of many other tasks such as text classification, knowledge graph completion, etc. This paper, particularly focuses on proposing a transformer-based ranking model for patent recommendations. It further experimentally compares the performance of patent recommendations based on various state-of-the-art negative sampling approaches to measure and compare the effectiveness of these approaches to aid future developments. These experiments are performed on a newly collected dataset of US patents from Google patents.