Miracle-dz/UniFAR-FTUs huggingface dataset:
3D Trajectory Design of UAV Based on Deep Reinforcement Learning in Time-varying Scenes

A joint framework is proposed for the 3D trajectory design of an unmanned aerial vehicle (UAV) as an flying base station under the time-varying scenarios of users’ mobility and communication request probability changes. The problem of 3D trajectory design is formulated for maximizing the throughput during a UAV’s flying period while satisfying the rate requirement of all ground users (GUEs). Specifically, we consider that GUEs change their positions and communication request probabilities at each time slot; the UAV needs to predict these changes so that it can design its 3D trajectory in advance to achieve the optimization target. In an effort to solve this pertinent problem, an echo state network (ESN) based prediction algorithm is first proposed for predicting the positions and communication request probabilities of GUEs. Based on these predictions, a Deep Reinforcement Learning (DRL) method is then invoked for finding the optimal deployment locations of UAV in each time slots. The proposed method 1) uses ESN based predictions to represent a part of DRL agent’s state; 2) designs the action and reward for DRL agent to learn the environment and its dynamics; 3) makes optimal strategy under the guidance of a double deep Q network (DDQN). The simulation results show that the UAV can dynamically adjust its trajectory to adapt to time-varying scenarios through our proposed algorithm and throughput gains of about 10.68% are achieved.
Constructing the Intelligence Headache Diagnosis Model by CBR

∗ Recently research found that the probability of having headache between female and male, female that have headache is usually higher than male. Also, headache will get the lower productivity when people working. Therefore, headache is what we called modern disease(s). The purpose of this study is to establish the intelligence headache diagnosis model by using Case Based Reasoning (CBR) to diagnose the probability of the kind of headache and to recommend the doctor regimens on headache patients. The proposed intelligence diagnosis model accuracy rate is 70% above that can be of the great assistance reducing diagnostic errors and improving the medical treatment quality.
Learning and Reasoning for Cultural Metadata Quality: Coupling Symbolic AI and Machine Learning over a Semantic Web Knowledge Graph to Support Museum Curators in Improving the Quality of Cultural Metadata and Information Retrieval

This work combines semantic reasoning and machine learning to create tools that allow curators of the visual art collections to identify and correct the annotations of the artwork as well as to improve the relevance of the content-based search results in these collections. The research is based on the Joconde database maintained by the French Ministry of Culture that contains illustrated artwork records from main French public and private museums representing archeological objects, decorative arts, fine arts, historical and scientific documents, etc. The Joconde database includes semantic metadata that describes properties of the artworks and their content. The developed methods create a data pipeline that processes metadata, trains a Convolutional Neural Network image classification model, makes prediction for the entire collection and expands the metadata to be the base for the SPARQL search queries. We developed a set of such queries to identify noise and silence in the human annotations and to search image content with results ranked according to the relevance of the objects quantified by the prediction score provided by the deep learning model. We also developed methods to discover new contextual relationships between the concepts in the metadata by analyzing the contrast between the concepts’ similarities in the Joconde's semantic model and other vocabularies and we tried to improve the model prediction scores based on the semantic relations. Our results show that cross-fertilization between symbolic AI and machine learning can indeed provide the tools to address the challenges of the museum curators work describing the artwork pieces and searching for the relevant images.
Distant Supervised Relation Extraction with Hierarchical Attention Mechanism

Current distant supervised relation extraction algorithms based on Neural Networks mostly use long short-term memory networks and convolutional neural networks, which cannot capture long-distance features of sentences. This paper proposes a distant supervised relation extraction model based on hierarchical attention mechanism, which uses self-attention mechanism to calculate features between words, and sentence-level soft-attention mechanism to extract dimensionality of sentence features. Compared with the previous method, the proposed model can better capture sentence features and improve the effect of sentence relation classification. On the dataset NYT-10, compared with the PCNN_ATT algorithm, the P@100, P@200, and P@300 indicators increase by 4.8%, 4.9% and 2.3%, respectively, and the AUC indicator increases by 1.1%.
What the flip? What the P-N flip can tell us about proactive suppression

It has been debated whether salient distractors in visual search can be proactively suppressed to completely prevent attentional capture, as the occurrence of proactive suppression implies that the initial shift of attention is not entirely driven by physical salience. While the presence of a Pd component in the EEG (associated with suppression) without a preceding N2pc component (associated with selection) has been used as evidence for proactive suppression, the link between these ERPs and the underlying mechanisms is not always clear. This is exemplified in two recent papers that observed the same waveform pattern, where an early Pd-like component flipped to a N2pc-like component, but provided very different interpretations (Drisdelle & Eimer, Psychophysiology, 58(9), 1-12, 2021; Kerzel & Burra, Journal of Cognitive Neuroscience, 32(6), 1170-1183, 2020). Using RAGNAROC (Wyble et al., Psychological Review, 127(6), 1163-1198, 2020), a computational model of reflexive attention, we successfully simulated this ERP pattern with minimal changes to its existing architecture, providing a parsimonious and mechanistic explanation for this flip in the EEG that is unique from both of the previous interpretations. Our account supports the occurrence of proactive suppression and demonstrates the benefits of incorporating computational modelling into theory building.
An initial assessment of the sustainability of waterbird harvest in the United Kingdom

There is a need to assess the sustainability of wild bird harvest in the United Kingdom (UK), and more widely, across Europe. Yet data on populations and harvest sizes are limited. We used a Demographic Invariant Method (DIM) to estimate Potential Excess Growth (PEG) for populations of UK wintering waterbirds and calculated a Sustainable Harvest Index (SHI) for each. We compared this with population trends and conservation classifications (e.g. Birds of Conservation Concern; BoCC) to assess the sustainability of harvests and the utility of these classifications. Our approach found evidence for potential overharvest of mallard Anas platyrhynchos, Eurasian teal Anas crecca, gadwall Mareca strepera, Canada geese Branta canadensis, greylag geese Anser anser and woodcock Scolopax rusticola. Whether DIM methods predict overharvest is highly dependent on estimates of maximum population growth rates inferring PEG. We found estimates of maximum population growth to be variable across a range of different methods. We found no relationship between SHI and short-term wintering trends or conservation classification under the UK’s BoCC framework. There was however a positive relationship between SHI and long-term wintering trends. Policy Implications: Our results suggest that UK based harvest is unlikely to be a major determinant of population trends for the majority of UK overwintering waterbirds, but harvest rates for some species may exceed that required to maintain stationary population growth. The lack of a relationship between conservation classifications and SHI strongly suggests that such conservation classifications are not an appropriate tool for making decisions about harvest management. Instead, our assessment provides the basis for a framework to make evidence-based decisions on sustainable harvest levels in the face of incomplete data. There is currently no clear policy instrument in the UK to support such a framework via controls on either harvest effort or mortality of waterfowl.
Effects of dopamine D2/3 and opioid receptor antagonism on the trade-off between model-based and model-free behaviour in healthy volunteers

Our daily behaviour requires a flexible arbitration between actions we do out of habit and actions that are directed towards a specific goal. Drugs that target opioid and dopamine receptors are notorious for inducing maladaptive habitual drug consumption, yet how the opioidergic and dopaminergic neurotransmitter systems contribute to the arbitration between habitual and goal-directed behaviour is poorly understood. By combining pharmacological challenges with a well-established decision-making task and a novel computational model, we show that the administration of the D2 dopamine receptor antagonist amisulpride led to an increase in goal-directed or ‘model-based’ relative to habitual or ‘model-free’ behaviour, whereas the non-selective opioid receptor antagonist naltrexone had no appreciable effect. These findings highlight the distinct functional contributions of dopamine and opioid receptors to goal-directed and habitual behaviour and support the notion that D2 receptor antagonists promote stabilisation of goal-relevant information.
Dopaminergic Modulation of Dynamic Emotion Perception

Emotion recognition abilities are fundamental to our everyday social interaction. A large number of clinical populations show impairments in this domain, with emotion recognition atypicalities being particularly prevalent among disorders exhibiting a dopamine system disruption (e.g., Parkinson's disease). Although this suggests a role for dopamine in emotion recognition, studies employing dopamine manipulation in healthy volunteers have exhibited mixed neural findings and no behavioral modulation. Interestingly, while a dependence of dopaminergic drug effects on individual baseline dopamine function has been well established in other cognitive domains, the emotion recognition literature so far has failed to account for these possible interindividual differences. The present within-subjects study therefore tested the effects of the dopamine D2 antagonist haloperidol on emotion recognition from dynamic, whole-body stimuli while accounting for interindividual differences in baseline dopamine. A total of 33 healthy male and female adults rated emotional point-light walkers (PLWs) once after ingestion of 2.5 mg haloperidol and once after placebo. To evaluate potential mechanistic pathways of the dopaminergic modulation of emotion recognition, participants also performed motoric and counting-based indices of temporal processing. Confirming our hypotheses, effects of haloperidol on emotion recognition depended on baseline dopamine function, where individuals with low baseline dopamine showed enhanced, and those with high baseline dopamine decreased emotion recognition. Drug effects on emotion recognition were related to drug effects on movement-based and explicit timing mechanisms, indicating possible mediating effects of temporal processing. Results highlight the need for future studies to account for baseline dopamine and suggest putative mechanisms underlying the dopaminergic modulation of emotion recognition. SIGNIFICANCE STATEMENT A high prevalence of emotion recognition difficulties among clinical conditions where the dopamine system is affected suggests an involvement of dopamine in emotion recognition processes. However, previous psychopharmacological studies seeking to confirm this role in healthy volunteers thus far have failed to establish whether dopamine affects emotion recognition and lack mechanistic insights. The present study uncovered effects of dopamine on emotion recognition in healthy individuals by controlling for interindividual differences in baseline dopamine function and investigated potential mechanistic pathways via which dopamine may modulate emotion recognition. Our findings suggest that dopamine may influence emotion recognition via its effects on temporal processing, providing new directions for future research on typical and atypical emotion recognition.
Development and evaluation of a loop-mediated isothermal amplification (LAMP) method for detection of the potato wart pathogen Synchytrium endobioticum

Potato (Solanum tuberosum) wart, caused by the biotrophic fungal pathogen Synchytrium endobioticum, is a serious disease of cultivated potatoes. A rapid and accurate method for wart diagnosis is needed. In this study, we described the development and evaluation of a loop-mediated isothermal amplification (LAMP) method for the detection of S. endobioticum. Four sets of LAMP primers were designed. Their sensitivity was tested on a gBlock and the specificity of the most sensitive primer set (LAMP1) was verified by in silico analysis and on DNA of non-target species. The LAMP1 primer set showed a detection limit at 7-8 gBlock DNA molecules per reaction. On sensitivity, the LAMP was comparable to qPCR (SYBR green- and probe-based) and about 10 times more sensitive than conventional PCR. Considering the convenience of operation, the LAMP protocol is accurate and robust and should be recommended for the routine lab testing for potato wart.
Neonatal Peyer’s patch cDC activation as a pacemaker of postnatal immune maturation

Marked differences exist between the mucosal immune system of the neonate and adult host. The pronounced influence of the enteric microbiota in adults suggests a causal relationship between postnatal colonization and immune maturation. However, using metagenomic, metaproteomic, and functional immunological analyses we demonstrate an early presence of bacteria and immunogenic microbial antigens preceding immune maturation in the small intestine, the primary inductive site of intestinal immunity. Instead, transcriptomic, flow cytometric and histological analysis indicated neonatal Peyer’s patch (PP) mononuclear phagocytes (MNP) as rate limiting factor of postnatal immune maturation. Despite the early presence of MNPs, conventional dendritic cells (cDC) of type 1, 2a and 2b exhibited significant age-dependent differences in tissue distribution and cellular composition. Single cell transcriptional profiling and functional assays revealed decreased antimicrobial and antigen processing/presentation capacity, an overall retarded cell maturation and reduced antigen uptake. In cDC2a this resulted in a reduced proportion of CCR7+ migratory cells and a consequent defect in CD4 T cell priming. Interestingly, transcriptional profiling of neonatal DC subsets identified reduced expression of type I interferon (IFN)-stimulated genes (ISG). Type I IFN induction by oral administration of the TLR7 agonist R848 accelerated MNP maturation and enhanced cognate antigen CD4 T cell priming. However, humoral responses to oral vaccination in the presence of R848 were significantly reduced. Together, our results identify PP MNP maturation as pacemaker of postnatal mucosal immune priming, indicate the biological role of delayed maturation and demonstrate that targeted interventional strategies allow manipulation of mucosal responses in early life.
ACCUMULATION OF MICROPLASTIC AND MICRORUBBER PARTICLES IN STORMWATER POND FISH AND INVERTEBRATES

Stormwater ponds serve as best management practices to trap or remove both physical and chemical pollutants before further discharge of stormwater into receiving natural waterbodies. Stormwater ponds can therefore accumulate high levels of pollutants, including microplastics (MP) and microrubber (MR) from road runoff. It was hypothesized that biota in stormwater ponds that receive large amounts of road runoff, or are in proximity to roadways and major developments, would contain significant amounts of MP per individual, with high abundances of tire particles (TP). Fish and invertebrates were collected from five stormwater ponds and their adjacent tidal creeks in Mt. Pleasant, SC, USA. Whole organisms were digested using KOH and digested contents were filtered and analyzed by visual microscopy to identify and count MPs. The majority (>80%) of MP recovered from biota across all sites were suspected TP. The average number of MP per individual ranged from 0.3 to 71 MP and the average number of suspected tire particles per individual ranged from 0 to 57.7 tire particles. There were significant differences in MP per individual observed between sites and between species. A combination of factors such as availability of MPs based on surrounding land use, pond hydrodynamics, organism size, and species feeding habitat likely influenced the total MP observed among the different sites and species analyzed. These data provide preliminary examination into the fate and transport of MP and MR in stormwater ponds and an evaluation of MP and MR abundance in organisms from stormwater ponds in the coastal zone.
Soluble ECM promotes organotypic formation in lung alveolar model

Micropatterned suspension culture creates consistently sized and shaped cell aggregates but has not produced organotypic structures from stable cells, thus restricting its use in accurate disease modeling. Here, we show that organotypic structure is achieved in hybrid suspension culture via supplementation of soluble extracellular matrix (ECM). We created a viable lung organoid from epithelial, endothelial, and fibroblast human stable cell lines in suspension culture. We demonstrate the importance of soluble ECM in organotypic patterning with the emergence of lumen-like structures with airspace showing feasible gas exchange units, formation of branching, perfusable vasculature, and long-term 70-day maintenance of lumen structure. Our results show a dependent relationship between enhanced fibronectin fibril assembly and the incorporation of ECM in the organoid. We successfully applied this technology in modeling lung fibrosis via bleomycin induction and test a potential antifibrotic drug in vitro while maintaining fundamental cell-cell interactions in lung tissue. Our human fluorescent lung organoid (hFLO) model represents features of pulmonary fibrosis which were ameliorated by fasudil treatment. We also demonstrate a 3D culture method with potential of creating organoids from mature cells, thus opening avenues for disease modeling and regenerative medicine, enhancing understanding of lung cell biology in health and lung disease.
Helminth parasites decrease survival probability in young red deer

Helminths are common parasites of wild ungulates that can have substantial costs for growth, mortality, and reproduction. While these costs are relatively well documented for mature animals, knowledge of helminths’ impacts on juveniles is more limited. Identifying these effects is important because young individuals are often heavily infected, and juvenile mortality is an important process regulating wild populations. Here, we investigated associations between helminth infection and overwinter survival in juvenile wild red deer (Cervus elaphus) on the Isle of Rum, Scotland. We collected faecal samples non-invasively from known individuals and used them to count propagules of three helminth taxa (strongyle nematodes, Fasciola hepatica, and Elaphostrongylus cervi). Using generalised linear models, we investigated associations between parasite counts and overwinter survival for calves and yearlings. Strongyles were associated with reduced survival in both age class, and F. hepatica was associated with reduced survival in yearlings, while E. cervi infection showed no association with survival in either age class. This study provides observational evidence for fitness costs of helminth infection in juveniles of a wild mammal, and suggests that these parasites could play a role in regulating population dynamics.
Campylobacter jejuni modulates reactive oxygen species production and NADPH oxidase 1 expression in human intestinal epithelial cells

Campylobacter jejuni is the major bacterial cause of foodborne gastroenteritis worldwide. Mechanistically, how this pathogen interacts with intrinsic defence machinery of human intestinal epithelial cells (IECs) remains elusive. To address this, we investigated how C. jejuni counteracts the intracellular and extracellular reactive oxygen species (ROS) in IECs. Our work shows that C. jejuni differentially regulates intracellular and extracellular ROS production in human T84 and Caco-2 cells. C. jejuni downregulates the transcription and translation of Nicotinamide adenine dinucleotide phosphate (NAPDH) oxidase (Nox1), a key ROS-generating enzyme in IECs and antioxidant defence genes cat and sod1. Furthermore, inhibition of Nox1 by diphenylene iodonium (DPI) and siRNA reduced C. jejuni ability to interact, invade and intracellularly survive within T84 and Caco-2 cells. Collectively, these findings provide mechanistic insight into how C. jejuni modulates the IEC defence machinery.
Ultrastructural analysis of wildtype and RIM1α knock-out active zones in a large cortical synapse

Rab3A-interacting molecule (RIM) is crucial for fast Ca2+-triggered synaptic vesicle (SV) release in presynaptic active zones (AZ). While loss of RIM1α impairs long-term plasticity at hippocampal giant mossy fiber boutons (MFB), it remains unclear how AZ ultrastructure is altered. We investigated MFB AZ architecture in 3D using electron tomography of rapid cryo-immobilized acute brain slices in RIM1α-/- and wild-type mice. In RIM1α-/-, AZs are larger with increased synaptic cleft heights and with a three-fold reduced number of tightly docked SVs (0-2nm). The distance of tightly docked SVs to the AZ center is increased from 110 to 195 nm, and the width of their electron dense material between outer SV membrane and AZ membrane is reduced. Furthermore, the SV pool in RIM1α-/- is more heterogeneous. Thus, RIM1α, beside its role in tight SV docking, is crucial for synaptic architecture and vesicle pool organization in MFBs.
Temperature Stressed Caenorhabditis elegans Males Prioritize Feeding over Mating Resulting in Sterility

Heat stress negatively impacts fertility in sexually reproducing organisms at sublethal temperatures. These temperature stress effects are typically more pronounced in males. In some species, sperm production, quality, and motility are the primary cause of male infertility under temperature stress. However, this is not the case in the model nematode Caenorhabditis elegans where changes in mating behavior are the primary cause of fertility loss. We report that temperature stressed C. elegans males experience a dramatic upset in the balance of their food drive and their mating drive such that they prioritize feeding over mating. This change in priorities is due partially to increased expression of the chemoreceptor odr-10 in the AWA sensory neurons. Increased odr-10 expression in the presence of ample food demonstrates that males are unable to experience satiety, thus they never leave a food source and engage in mate searching behavior. These results demonstrate that moderate temperature stress may have profound and previously underappreciated effects on reproductive behaviors. As climate change associated temperature variability becomes more commonplace, it will be imperative to understand how temperature stress affects conserved behavioral elements critical to reproduction.