Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementing primordial binaries in simulations of star cluster formation with a hybrid MHD and direct N-body method

The fraction of stars in binary systems within star clusters is important for their evolution, but what proportion of binaries form by dynamical processes after initial stellar accretion remains unknown. In previous work, we showed that dynamical interactions alone produced too few low-mass binaries compared to observations. We therefore implement an initial population of binaries in the coupled magnetohydrodynamics and direct N-body star cluster formation code torch. We compare simulations with, and without, initial binary populations and follow the dynamical evolution of the binary population in both sets of simulations, finding that both dynamical formation and destruction of binaries take place. Even in the first few million years of star formation, we find that an initial population of binaries is needed at all masses to reproduce observed binary fractions for binaries with mass ratios above the q ≥ 0.1 detection limit. Our simulations also indicate that dynamical interactions in the presence of gas during cluster formation modify the initial distributions towards binaries with smaller primary masses, larger mass ratios, smaller semimajor axes and larger eccentricities. Systems formed dynamically do not have the same properties as the initial systems, and systems formed dynamically in the presence of an initial population of binaries differ from those formed in simulations with single stars only. Dynamical interactions during the earliest stages of star cluster formation are important for determining the properties of binary star systems.
LIAF-Net: Leaky Integrate and Analog Fire Network for Lightweight and Efficient Spatiotemporal Information Processing

Spiking neural networks (SNNs) based on the leaky integrate and fire (LIF) model have been applied to energy-efficient temporal and spatiotemporal processing tasks. Due to the bioplausible neuronal dynamics and simplicity, LIF-SNN benefits from event-driven processing, however, usually face the embarrassment of reduced performance. This may because, in LIF-SNN, the neurons transmit information via spikes. To address this issue, in this work, we propose a leaky integrate and analog fire (LIAF) neuron model so that analog values can be transmitted among neurons, and a deep network termed LIAF-Net is built on it for efficient spatiotemporal processing. In the temporal domain, LIAF follows the traditional LIF dynamics to maintain its temporal processing capability. In the spatial domain, LIAF is able to integrate spatial information through convolutional integration or fully connected integration. As a spatiotemporal layer, LIAF can also be used with traditional artificial neural network (ANN) layers jointly. In addition, the built network can be trained with backpropagation through time (BPTT) directly, which avoids the performance loss caused by ANN to SNN conversion. Experiment results indicate that LIAF-Net achieves comparable performance to the gated recurrent unit (GRU) and long short-term memory (LSTM) on bAbI question answering (QA) tasks and achieves state-of-the-art performance on spatiotemporal dynamic vision sensor (DVS) data sets, including MNIST-DVS, CIFAR10-DVS, and DVS128 Gesture, with much less number of synaptic weights and computational overhead compared with traditional networks built by LSTM, GRU, convolutional LSTM (ConvLSTM), or 3-D convolution (Conv3D). Compared with traditional LIF-SNN, LIAF-Net also shows dramatic accuracy gain on all these experiments. In conclusion, LIAF-Net provides a framework combining the advantages of both ANNs and SNNs for lightweight and efficient spatiotemporal information processing.
Vertical distribution of polycyclic aromatic hydrocarbons in the brackish sea water column: ex situ experiment

Background Oil spills can cause severe damage within a marine ecosystem. Following a spill, the soluble fraction of polycyclic aromatic hydrocarbons is rapidly released into the water column. These remain dissolved in seawater over an extended period of time, even should the insoluble fraction be removed. The vertical distribution of the aromatic hydrocarbon component and how these become transferred is poorly understood in brackish waters. This study examines the vertical distribution of polycyclic aromatic hydrocarbons having been released from a controlled film of spilled oil onto the surface of brackish water. Methods The study was undertaken under controlled conditions so as to minimize the variability of environmental factors such as temperature and hydrodynamics. The distribution of polycyclic aromatic hydrocarbons was measured in the dissolved and suspended phases throughout the 1 m water column with different intensity of water sampling: 1, 2, 4, 7, 72, 120, 336, 504 and 984 h. Results The total concentration of polycyclic aromatic hydrocarbons ranged from 19.01 to 214.85 ng L–1 in the dissolved phase and from 5.14 to 63.92 ng L–1 in the suspended phase. These hydrocarbons were released immediately following a controlled spill attaining 214.9 ng L–1 in the dissolved phase and 54.4 ng L–1 in the suspended phase near the cylinder bottom after 1–2 h. The 2–3 ring polycyclic aromatic hydrocarbons dominated in the dissolved phase (60–80%), whereas the greater amount of 4–6 ring polycyclic aromatic hydrocarbons (55–90%) occurred in the suspended phase. A relatively low negative correlation (rS = –0.41) was determined between the concentration of phenanthrene and suspended matter, whereas a high negative correlation (r = − 0.79) was found between the concentration of pyrene and suspended matter. Despite the differences in the relationships between the concentration ratio and amount of suspended matter the obtained regressions allow roughly to predict the concentration of polycyclic aromatic hydrocarbons.
Cross-lingual and Multilingual Spoken Term Detection for Low-Resource Indian Languages

Spoken Term Detection (STD) is the task of searching for words or phrases within audio, given either text or spoken input as a query. In this work, we use state-of-the-art Hindi, Tamil and Telugu ASR systems cross-lingually for lexical Spoken Term Detection in ten low-resource Indian languages. Since no publicly available dataset exists for Spoken Term Detection in these languages, we create a new dataset using a publicly available TTS dataset. We report a standard metric for STD, Mean Term Weighted Value (MTWV) and show that ASR systems built in languages that are phonetically similar to the target languages have higher accuracy, however, it is also possible to get high MTWV scores for dissimilar languages by using a relaxed phone matching algorithm. We propose a technique to bootstrap the Grapheme-to-Phoneme (g2p) mapping between all the languages under consideration using publicly available resources. Gains are obtained when we combine the output of multiple ASR systems and when we use language-specific Language Models. We show that it is possible to perform STD cross-lingually in a zero-shot manner without the need for any language-specific speech data. We plan to make the STD dataset available for other researchers interested in cross-lingual STD.
A Novel Curriculum for Medical Student Training in LGBTQ Healthcare: A Regional Pathway Experience

Background: Lesbian, gay, bisexual, transgender, and queer (LGBTQ) individuals face considerable health disparities, often due to a lack of LGBTQ-competent care. Such disparities and lack of access to informed care are even more staggering in rural settings. As the state medical school for the Washington, Wyoming, Alaska, Montana, and Idaho (WWAMI) region, the University of Washington School of Medicine (UWSOM) is in a unique position to train future physicians to provide healthcare that meets the needs of LGBTQ patients both regionally and nationally. Objective: To describe our methodology of developing a student-driven longitudinal, region-wide curriculum to train medical students to provide high-quality care to LGBTQ patients. Methods: A 4-year LGBTQ Health Pathway was developed and implemented as a student-led initiative at the UWSOM. First- and second-year medical students at sites across the WWAMI region are eligible to apply. Accepted Pathway students complete a diverse set of pre-clinical and clinical components: online modules, didactic courses, longitudinal community service/advocacy work, a scholarly project, and a novel clinical clerkship in LGBTQ health developed specifically for this Pathway experience. Students who complete all requirements receive a certification of Pathway completion. This is incorporated into the Medical Student Performance Evaluation as part of residency applications. Results: The LGBTQ Health Pathway is currently in its fourth year. A total of 43 total students have enrolled, of whom 37.3% are based in the WWAMI region outside of Seattle. Pathway students have completed a variety of scholarly projects on LGBTQ topics, and over 1000 hours of community service/advocacy. The first cohort of 8 students graduated with a certificate of Pathway completion in spring 2020. Conclusions: The LGBTQ Health Pathway at UWSOM is a novel education program for motivated medical students across the 5-state WWAMI region. The diverse milestones, longitudinal nature of the program, focus on rural communities, and opportunities for student leadership are all strengths and unique aspects of this program. The Pathway curriculum and methodology described here serve as a model for student involvement and leadership in medical education. This program enables medical students to enhance their training in the care of LGBTQ patients and provides a unique educational opportunity for future physicians who strive to better serve LGBTQ populations.
Habitat preference, movements and growth of giant mottled eels, Anguilla marmorata, in a small subtropical Amami-Oshima Island river

Although anguillid eel populations have decreased remarkably in recent decades, few detailed ecological studies have been conducted on tropical eels such as the giant mottled eel whose range extends across the whole Indo-Pacific. This species was studied throughout the entire 0.5 km mainstem reaches of Oganeku River on the subtropical Amami-Oshima Island of Japan over a two-year period using four sampling periods to understand its habitat preference, early life-stage dispersal process, movements, and annual growth using a mark-recapture experiment conducted with quantitative electrofishing. A total of 396 juvenile growth-phase A. marmorata eels were caught and tagged, with 48 individuals being recaptured at least once. Their density irrespective of size of eels was most strongly determined by distance from the river mouth, followed by riverbank type according to random forest models. Eel density decreased with increasing distance from the freshwater tidal limit located about 100–150 m from the river mouth. Eels preferred vegetated riverbanks, while they avoided those of concrete and sand. The density of small eels (total length: TL < 240 mm) was also associated with depth and velocity, with small eels tending to prefer riffle or run habitats. In contrast, large eels (TL ≥ 240 mm) were found in habitats of any depth and velocity. The TL of eels had a minimum peak at around the tidal limit, and it increased with increasing distance from the tidal limit. The observed density and size gradients of eels in relation to the distance from the river mouth suggested that A. marmorata initially recruited to freshwater tidal limit areas and then dispersed in both downstream and upstream directions. The growth rate of eels varied greatly among individuals that were at large for various periods of time and ranged from 0 to 163.2 mm/year (mean ± SD of 31.8 ± 31.0 mm/year). Of the recaptured eels, 52.1% were recaptured in a section that was different from the original capture section, and their mean ± SD distance travelled was 46.5 ± 72.5 m (median = 20 m). 47.9% of the eels were recaptured from the original section of capture (i.e., <10 m distances travelled), suggesting that they had strong fidelity to specific habitats with limited movements. The distance travelled of eels that had moved was greater for small eels (range = 10–380 m; mean ± SD = 84.4 ± 121.9 m) than large individuals (range = 10–120 m; mean ± SD = 30.9 ± 31.0 m), which indicates that the mobility of the eels declines as they grow. This is the first clear detailed documentation of the spatial distribution, growth, and movements of tropical eels in a small river system in relation to environmental conditions that provides an example of how future studies can be conducted in other areas to understand how conservation efforts can be most efficiently targeted for maximum success.
Cryptosporidium spp. and Giardia duodenalis emissions from humans and animals in the Three Gorges Reservoir in Chongqing, China

Cryptosporidium spp. and Giardia duodenalis are two waterborne protozoan parasites that can cause diarrhea. Human and animal feces in surface water are a major source of these pathogens. This paper presents a GloWPa-TGR-Crypto model that estimates Cryptosporidium and G. duodenalis emissions from human and animal feces in the Three Gorges Reservoir (TGR), and uses scenario analysis to predict the effects of sanitation, urbanization, and population growth on oocyst and cyst emissions for 2050. Our model estimated annual emissions of 1.6 × 1015 oocysts and 2.1 × 1015 cysts from human and animal feces, respectively. Humans were the largest contributors of oocysts and cysts, followed by pigs and poultry. Cities were hot-spots for human emissions, while districts with high livestock populations accounted for the highest animal emissions. Our model was the most sensitive to oocyst excretion rates. The results indicated that 74% and 87% of total emissions came from urban areas and humans, respectively, and 86% of total human emissions were produced by the urban population. The scenario analysis showed a potential decrease in oocyst and cyst emissions with improvements in urbanization, sanitation, wastewater treatment, and manure management, regardless of population increase. Our model can further contribute to the understanding of environmental pathways, the risk assessment of Cryptosporidium and Giardia pollution, and effective prevention and control strategies that can reduce the outbreak of waterborne diseases in the TGR and other similar watersheds.
Random forest algorithms for recognizing daily life activities using plantar pressure information: a smart-shoe study

Background Wearable activity trackers are regarded as a new opportunity to deliver health promotion interventions. Indeed, while the prediction of active behaviors is currently primarily relying on the processing of accelerometer sensor data, the emergence of smart clothes with multi-sensing capacities is offering new possibilities. Algorithms able to process data from a variety of smart devices and classify daily life activities could therefore be of particular importance to achieve a more accurate evaluation of physical behaviors. This study aims to (1) develop an activity recognition algorithm based on the processing of plantar pressure information provided by a smart-shoe prototype and (2) to determine the optimal hardware and software configurations. Method Seventeen subjects wore a pair of smart-shoe prototypes composed of plantar pressure measurement insoles, and they performed the following nine activities: sitting, standing, walking on a flat surface, walking upstairs, walking downstairs, walking up a slope, running, cycling, and completing office work. The insole featured seven pressure sensors. For each activity, at least four minutes of plantar pressure data were collected. The plantar pressure data were cut in overlapping windows of different lengths and 167 features were extracted for each window. Data were split into training and test samples using a subject-wise assignment method. A random forest model was trained to recognize activity. The resulting activity recognition algorithms were evaluated on the test sample. A multi hold-out procedure allowed repeating the operation with 5 different assignments. The analytic conditions were modulated to test (1) different window lengths (1–60 seconds), (2) some selected sensor configurations and (3) different numbers of data features. Results A window length of 20 s was found to be optimum and therefore used for the rest of the analysis. Using all the sensors and all 167 features, the smart shoes predicted the activities with an average success of 89%. “Running” demonstrated the highest sensitivity (100%). “Walking up a slope” was linked with the lowest performance (63%), with the majority of the false negatives being “walking on a flat surface” and “walking upstairs. ” Some 2- and 3-sensor configurations were linked with an average success rate of 87%. Reducing the number of features down to 20 does not alter significantly the performance of the algorithm. Conclusion High-performance human behavior recognition using plantar pressure data only is possible. In the future, smart-shoe devices could contribute to the evaluation of daily physical activities. Minimalist configurations integrating only a small number of sensors and computing a reduced number of selected features could maintain a satisfying performance. Future experiments must include a more heterogeneous population.
Thalamic Atrophy Plays a Crucial Role in the Effect of Asymptomatic Carotid Stenosis on Cognitive Impairment

Purpose Our objectives were to assess the abnormalities of subcortical nuclei by combining volume and shape analyses and potential association with cognitive impairment. Patients and Methods Twenty-nine patients with severe ACS of the unilateral internal carotid artery and 31 controls were enrolled between January 2017 to August 2018. All participants underwent a comprehensive neuropsychological evaluation, blood lipid biochemical measurements, and structural magnetic resonance imaging (MRI) to measure subcortical volumes and sub-regional shape deformations. Basic statistics, correction for multiple comparisons. Seventeen ACS patients underwent carotid endarterectomy (CEA) within one week after baseline measurements, cognitive assessments and MRI scans were repeated 6 months after CEA. Results The ACS patients had higher apolipoprotein B/apolipoprotein A1 (ApoB/ApoA1) ratio and worse performance in all cognitive domains than controls. Moreover, the ACS patients showed more profound thalamic atrophy assessed by shape and volume analysis, especially in the medial dorsal thalamus. No significant differences were found in other subcortical nuclei after multiple comparisons correction. At baseline, thalamic atrophy correlated with cognitive impairment and ApoB/ApoA1 ratio. Furthermore, mediation analysis at baseline showed that the association of carotid intima-media thickness with executive functioning was mediated by thalamic volume. After CEA, cognitive improvement and increase in the bilateral medial dorsal thalamic volume were observed. Conclusion Our study identified the distinct atrophy of subcortical nuclei and their association with cognition in patients with ACS. Assessments of the thalamus by volumetric and shape analysis may provide an early marker for cerebral ischemia and reperfusion after CEA.
Heterogeneity of CEACAM5 in breast cancer

CEACAM5 is overexpressed in many primary breast carcinomas. However, the exact role of CEACAM5 in breast cancer tumorigenesis remains unresolved. Here, we examined a repository of 110 cryopreserved primary breast carcinomas by immunohistochemistry to assess the distribution of CEACAM5 in tumor subtypes. The majority of estrogen receptor-positive and HER2-overexpressing tumors were CEACAM5-positive, whereas most of Triple-negative tumors were negative. Assessing sample sets of paired primary breast cancers and corresponding lymph node lesions from a total of 59 patients revealed a high correlation between primary tumor and lymph node with regard to CEACAM5-status. However, a notable subset of sample sets demonstrated intratumoral heterogeneity in the primary tumor, the metastatic lesion or both, suggesting that both CEACAM5-positive and –negative cells can play a role in tumor dissemination. When examining the consequence of expression of CEACAM5 in breast cancer cell lines in culture assays we found that CEACAM5-expressing cells were less invasive. In survival analysis, using cohort studies of breast cancer, expression of CEACAM5 predicted different clinical outcomes depending on molecular subtypes. Altogether, our analysis suggests that CEACAM5 plays a context-dependent role in breast cancer that warrants further investigation.
Transcriptome-wide identification of MAPKKK genes in bermudagrass (Cynodon dactylon L.) and their potential roles in low temperature stress responses

As upstream components of MAPK cascades, mitogen-activated protein kinase kinase kinases (MAPKKKs) act as adaptors linking upstream signaling steps to the core MAPK cascades. MAPK cascades are universal modules of signal transduction in eukaryotic organisms and play crucial roles in plant development processes and in responses to biotic and abiotic stress and signal transduction. Members of the MAPKKK gene family have been identified in several plants,however, MAPKKKs have not been systematically studied in bermudagrass (Cynodon dactylon L.). In this study, 55 potential CdMAPKKKs were produced from bermudagrass transcriptome data, of which 13 belonged to the MEKK, 38 to the Raf, and 4 to the ZIK subfamily. Multiple alignment and conserved motif analysis of CdMAPKKKs supported the evolutionary relationships inferred from phylogenetic analyses. Moreover, the distribution pattern in Poaceae species indicated that members of the MAPKKK family were conserved among almost all diploid species, and species-specific polyploidy or higher duplication ratios resulted in an expansion of the MAPKKK family. In addition, 714 co-functional links which were significantly enriched in signal transduction, responses to temperature stimuli, and other important biological processes of 55 CdMAPKKKs were identified using co-functional gene networks analysis; 30 and 19 co-functional genes involved in response to cold or heat stress, respectively, were also identified. Results of promoter analyses, and interaction network investigation of all CdMAPKKKs based on the rice homologs suggested that CdMAPKKKs are commonly associated with regulation of numerous biological processes. Furthermore, 12 and 13 CdMAPKKKs were significantly up- and downregulated, respectively, in response to low temperature stress; among them, six CdMAPKKKs were significantly induced by low temperature stress, at least at one point in time. This is the first study to conduct identification and functional analysis of the MAPKKK gene family in bermudagrass, and our results provide a foundation for further research on the functions of CdMAPKKKs in response to low temperature stress.