Miracle-dz/UniFAR-FTUs huggingface dataset:
Sparse tensor storage by tensor unfolding

Large scale high dimensional multi-aspect data are naturally represented as tensors or multi-way arrays for scientific and engineering computations. But in practical applications such as signal processing, data mining, computer vision, and graph analysis, this tensor data is very sparse. The degree of sparsity is magnified by the increase of number of dimensions for large tensors. Therefore, storing and applying tensor operations on this highly sparse multidimensional data is an important research challenge for data scientists. In this paper, we describe a new sparse tensor storage format that provide storage benefits and are independent to the number of dimension of the tensor. Efficient hash functions are desined to store sparse tensor data. The hash functions convert a higher order tensor to a matrix by tensor unfolding. And using the unfolded matrix, we develop algorithms to store nonzero data based on sparse fibers. We call our scheme Unfolded Compressed Row/Column Fiber (UCRF/UCCF). Our approach experimental result shows superior performance with standard dataset comparing to other important approaches.
X-IoT: a model-driven approach for cross-platform IoT applications development

Several heterogeneous IoT platforms have been proposed and regularly used by enterprises and academies to support and facilitate IoT software applications development. However, IoT applications strongly depend on the functionalities supported by the specific platform used. This affects the development and portability of the developed applications that may require significant changes, or a complete re-design, for being migrated between platforms. This paper presents X-IoT, an MDE approach for developing cross-platform IoT applications. The approach implements a Domain-Specific Modelling Language (DSML) based on emerging IoT application requirements. A meta-model that incorporates the main IoT platform characteristics has been developed within the ADOxx platform, together with a graphical notation. Through the DSML, it is possible to model a platform-independent model of IoT applications that are refined and deployed on specific IoT platforms.
Mixed-Effects Trait-State-Occasion Model: Studying the Psychometric Properties and the Person–Situation Interactions of Psychological Dynamics

ABSTRACT The trait-state-occasion model (TSO) is a popular model within the latent state-trait theory (LST). The TSO allows distinguishing the trait and the state components of the psychological constructs measured in longitudinal data, while also taking into account the carry-over effects between consecutive measurements. In the present study, we extend a multilevel version of the TSO model to allow for the combination of fixed and random situations, namely the mixed-effects TSO (ME-TSO). Hence, the ME-TSO model is a measurement model suitable to analyze intensive longitudinal data that allows studying the psychometric properties of the indicators per individual, the heterogeneity of psychological dynamics, and the person–situation interaction effects. We showcase how to use the model by analyzing the items of positive affect activation of the crowdsourcing study HowNutsAreTheDutch (HoeGekisNL).
Critical success factors for safety program implementation among construction companies in Malaysia

The construction industry is characterized with a poor safety culture. It is well known that construction projects have many work related accidents and injuries. Safety program is a means to improve safety performance in construction project in Malaysia. Sixteen critical success factors of safety programs were identified from safety literature, and these were validated by safety experts. This study was undertaken by distribute the questionnaire to 33 respondents from small, medium and large scale of construction projects. It explores the influence level of CSFs of safety program and actual status of compliance in construction companies. The main aim of this project is to study safety program implementation by determine the critical success factors (CSFs) that influenced the safety program in order to recommend strategies to enhance construction safety in improving safety program. The objectives of the study are to study safety program implementation and its effectiveness by construction companies, identify critical success factors that influenced the safety program implemented by construction companies to reduce rate of accident and fatality and recommend strategy to enhance construction safety in implement the safety program. the results shows that the implementation of safety program not achieved the required effectiveness and the there is a gap between the influence and actual compliance status of safety program CSFs. The study was carried out within Selangor, Kuala Lumpur and Johor States; it was basically focused on the respondents who involve in construction safety
Analyzing the thermal regime of power supply units in portable betatrons by using infrared thermography

Potentials of infrared thermography in analyzing a thermal regime of the 7.5 MeV betatron power supply are discussed. Both the heating rate and thermal inertia of particular electronic components have been evaluated by processing pixel-based temperature histories. The data treatment has been performed by using the original ThermoFit Pro software to illustrate that some advanced processing algorithms, such as the Fourier transform and principle component analysis, are valuable in identifying thermal dynamics of particular power supply parts.
Best practice recommendations for sample preservation in metabarcoding studies: a case study on diatom environmental samples

The development of DNA metabarcoding and High-Throughput Sequencing for diatoms is nowadays offering an interesting approach to assess their communities in freshwater and marine ecosystems. In the context of the implementation of these genomic methods to environmental monitoring, protocol constraints are moving from scientific to operational applications, requiring operational guidelines and standards. In particular, the first steps of the diatom metabarcoding process, which consist of sampling and storage, have been addressed in various ways in scientific and pilot studies. The objective of this study was to compare three currently applied preservation protocols through different storage durations (ranging from one day to one year) for phytobenthos and phytoplankton samples intended for diatom DNA metabarcoding analysis. The experimental design included four freshwater and two marine samples from sites of diverse ecological characteristics. The impact of the preservation and storage was assessed through diatom metabarcoding endpoints: DNA quality and quantity, diversity and richness, community composition and ecological index values (for freshwater samples). The yield and quality of extracted DNA only decreased for freshwater phytobenthos samples preserved with ethanol. Diatom diversity was not affected and their taxonomic composition predominantly reflects the site origin. Only rare taxa (below 100 reads) differed among methods and durations. Thus, importance of preservation method choice is important for low-density species (rare, invasive, threatened or toxic species). However, for biomonitoring purposes, freshwater ecological index values were not affected whatever the preservation method and duration considered (including ethanol preservation), reflecting the site ecological status. This study proved that diatom metabarcoding is robust enough to replace or complement the current approach based on morphotaxonomy, paving the way to new possibilities for biomonitoring. Thus, accompanied by operational standards, the method will be ready to be confidently deployed and prescribed in future regulatory monitoring.
AptaMat: a matrix-based algorithm to compare single-stranded oligonucleotides secondary structures

Comparing single-stranded nucleic acids (ssNAs) secondary structures is fundamental when investigating their function and evolution and predicting the effect of mutations on the ssNAs structures. Many comparison metrics exist, although they are either too elaborate or not enough sensitive to distinguish close ssNAs structures. In this context, we developed AptaMat, a simple and sensitive algorithm for ssNAs secondary structures comparison based on matrices representing the ssNAs secondary structures and a metric built upon the Manhattan distance in the plane. We applied AptaMat to several examples and compared the results to those obtained by the most frequently used metrics, namely the Hamming distance and the RNAdistance, and by a recently developed image-based approach. We showed that AptaMat is able to discriminate between similar sequences, outperforming all the other here considered metrics.
Neurotransmitter content heterogeneity within an interneuron class shapes inhibitory transmission at a central synapse

Neurotransmitter content is deemed the most basic defining criterion for neuronal classes, contrasting with the intercellular heterogeneity of many other molecular and functional features. Here we show, in the adult mouse brain, that neurotransmitter content variegation within a neuronal class is a component of its functional heterogeneity. Most Golgi cells (GoCs), the well-defined class of cerebellar interneurons inhibiting granule cells (GrCs), contain cytosolic glycine, accumulated by the neuronal transporter GlyT2, and GABA in various proportions. To assess the functional consequence of this neurotransmitter variation, we paired GrCs recordings with optogenetic stimulations of single GoCs, which preserve the intracellular transmitter mixture. We show that the strength and decay kinetics of GrCs IPSCs, which are entirely mediated by GABAA receptors are negatively correlated to the presynaptic expression of GlyT2 by GoCs. We isolate a slow spillover component of GrCs inhibition that is also affected by the expression of GlyT2, leading to a 56 % decrease in relative charge. Acute manipulations of cytosolic GABA and glycine supply recapitulate the modulation of IPSC charge, supporting the hypothesis that presynaptic loading of glycine negatively impact the GABAergic transmission in mixed interneurons through a competition for vesicular filling. Our results suggest that heterogeneity of neurotransmitter supply within the GoC class may provide a presynaptic mechanism to tune the gain of the stereotypic granular layer microcircuit, thereby expanding the realm of possible dynamic behavior.
Thermal cycling hyperthermia sensitizes non-small cell lung cancer A549 cells to EGFR-tyrosine kinase inhibitor Erlotinib

Molecular-targeted therapy has emerged as a mainstream treatment for non-small cell lung cancer (NSCLC), the most common lung cancer, which has been the leading cause of cancer death for both men and women. Erlotinib (Erl), a targeted therapy drug which triggers epidermal growth factor receptor (EGFR) pathways, has been proved to have noticeable response rate for NSCLC cells. However, it has achieved only limited treatment effect, due to intrinsic and acquired resistance among most NSCLC patients. Therefore, chemosensitizers are required to potentiate the efficacy of Erl in NSCLC treatment. The study proposed a novel thermal therapy, thermal cycling hyperthermia (TC-HT), as a supplement to amplify the effect of Erl, and proved that it can sensitize A549 NSCLC cells to Erl via the downstream of EGFR signaling cascades. In addition, we found that TC-HT not only greatly enhanced the anticancer effect of Erl but also remarkably reduced the half-maximal inhibitory concentration (IC50) to as little as 0.5 μM. Besides, via regulation of thermal dosage, TC-HT alone can produce excellent antineoplastic effect without hurting the normal cells. The method is expected to be applicable to other combination therapies and may be a starter for more sophisticated, side-effect-free anticancer treatments.
Identifying and Separating the Processes Underlying Boreal Forest Understory Community Assembly

Identifying the ecological processes underlying community assembly remains an elusive goal in community ecology. We formalize assembly hypotheses as alternative models and apply each to predict 1,918 out-of-sample boreal forest understory communities to identify and separate the processes driving community assembly. Models are spec-iﬁed within a Bayesian joint species distribution framework that allows for the inclusion and separation of stochastic processes, environmental ﬁltering, and two diﬀerent species dependence structures. We found clear evidence that study communities are structured by both environmental ﬁltering and compositional dependence highlighting the importance of selection in community assembly. The relative importance of environmental ﬁltering was greater than compositional dependence in predicting both understory communities and the abundance of constituent species across broad suc-cessional and bioclimatic gradients. Contrary to ecological expectations, the inclusion of a ﬂexible residual species dependence structure (accounting for more than compositional dependence) did not improve model predictions after accounting for the strong role of environmental ﬁltering. Our results provide novel inference on the processes underlying community assembly facilitated by applying empirical approximations of alternative assembly processes to predict communities across a range of environmental conditions.
Heading direction tracks internally directed selective attention in visual working memory

We shift our gaze even when we orient attention internally to visual representations in working memory. Here, we show the bodily orienting response associated with internal selective attention is widespread as it also includes the head. In three virtual reality (VR) experiments, participants remembered two visual items. After a working memory delay, a central colour cue indicated which item needed to be reproduced from memory. After the cue, head movements became biased in the direction of the memorised location of the cued memory item – despite there being no items to orient towards in the external environment. The heading-direction bias had a distinct temporal profile from the gaze bias. Our findings reveal that directing attention within the spatial layout of visual working memory bears a strong relation to the overt head orienting response we engage when directing attention to sensory information in the external environment. The heading-direction bias further demonstrates common neural circuitry is engaged during external and internal orienting of attention.
EEG Movement Tagging Objectively Measures Biological Motion Perception

Detecting biological motion is essential for adaptive social behavior. Previous research has revealed the brain processes underlying this ability. However, brain activity during biological motion perception captures a multitude of components. As a result, it is often unclear which components reflect movement processing and which components reflect secondary processes building on movement processing. To address this issue, we developed a new approach that objectively defines the brain response associated with biological motion perception. Specifically, we showed 30 male and female adults a point-light walker moving at a pace of 2.4 Hz and used EEG frequency tagging to measure the brain response coupled to that pace (‘movement tagging’). The results revealed a reliable response at the walking frequency that was reduced by two manipulations known to disrupt biological motion perception: phase scrambling and inversion. Interestingly, we also identified a brain response at half the walking frequency (i.e., 1.2 Hz), corresponding to the rate at which the individual dots completed a cycle. In contrast to the 2.4 Hz response, the response at 1.2 Hz was increased for scrambled walkers. These results show how frequency tagging can be used to objectively measure the visual processing of biological movements and can dissociate between global (2.4 Hz) and local (1.2 Hz) processes involved in biological motion perception, at different frequencies of the brain signal.
Inhibiting 5‐lipoxygenase prevents skeletal muscle atrophy by targeting organogenesis signalling and insulin‐like growth factor‐1

Background Skeletal muscle atrophy can occur in response to numerous factors, such as aging and certain medications, and produces a major socioeconomic burden. At present, there are no approved drugs for treating skeletal muscle atrophy. Arachidonate 5-lipoxygenase (Aox5) is a drug target for a number of diseases. However, pharmacological targeting of Alox5, and its role in skeletal muscle atrophy, is unclear. Methods The potential effects of gene knockdown and pharmacological targeting of Alox5 on skeletal muscle atrophy was investigated using cell-based models, animal models, and human skeletal muscle tissue cultures. Malotilate, a clinically safe drug developed for enhancing liver regeneration and Alox5 inhibitor, was investigated as a repurposing candidate. Mechanism(s) of action in skeletal muscle atrophy were assessed by measuring the expression level or activation status of key regulatory pathways, and validated using gene knockdown and RNA sequencing. Results Myotubes treated with the atrophy-inducing glucocorticoid, dexamethasone, were protected from catabolic responses by treatment with malotilate (+41.29%, P < 0.01). Similar anti-atrophy effects were achieved by gene knockdown of Alox5 (+30.4%, P < 0.05). Malotilate produced anti-atrophy effects without affecting the myogenic differentiation program. In an in vivo model of skeletal muscle atrophy, malotilate treatment enhanced muscle performance (Grip strength: +35.72%, Latency to fall: +553.1%, P < 0.05), increased mass and fiber cross sectional area (Quadriceps: +23.72%, Soleus: +33.3%, P < 0.01), and down-regulated atrogene expression (Atrogin-1: -61.58%, Murf-1: -66.06%, P < 0.01). Similar, beneficial effects of malotilate treatment were observed in an aging muscle, which also showed the preservation of fast twitch fibers (Type 2a: +56.48%, Type 2b: +37.32%, P < 0.01). Leukotrine B4, a product of Alox5 activity with inflammatory and catabolic functions, was found to be elevated in skeletal muscle undergoing atrophy (Quadriceps: +224.4%, P < 0.001). Cellular transcriptome analysis showed that targeting Alox5 upregulated biological processes regulating organogenesis and increased the expression of insulin-like growth factor-1, a key anti-atrophy hormone (+226.5%, P < 0.05). Interestingly, these effects were restricted to the atrophy condition and not observed in normal skeletal muscle cultures with Alox5 inhibition. Human skeletal muscle tissue was also protected from atrophy by pharmacological targeting of Alox5 (+23.68%, P < 0.05). Conclusion These results shed new light on novel drug targets and mechanisms underpinning skeletal muscle atrophy. Alox5 is a regulator and drug target for muscle atrophy, and malotilate is an attractive compound for repurposing studies to treat this disease.
Population coding strategies in human tactile afferents

Sensory information is conveyed by populations of neurons, and coding strategies cannot always be deduced when considering individual neurons. Moreover, information coding depends on the number of neurons available and on the composition of the population when multiple classes with different response properties are available. Here, we study population coding in human tactile afferents by employing a recently developed simulator of mechanoreceptor firing activity. First, we demonstrate that the optimal afferent density for conveying maximal information depends on the tactile feature under consideration and the afferent class coding this feature. Second, we find that information is spread across different classes for all tactile features, such that combining information from multiple afferent classes improves information transmission, and is often more efficient than increasing the density of afferents from the same class. Finally, we test the importance of timing precision and afferent identity in the population code to probe whether temporal and spatial information can be traded against each other. Destroying temporal information turns out to be more destructive than removing spatial information, and the contribution of either cannot be completely recovered from the other. Overall, our results suggest that both optimal afferent innervation densities and the composition of the population depend in complex ways on the tactile features in question, potentially accounting for the variety in which tactile peripheral populations are assembled in different regions across the body.
GraphPred: An approach to predict multiple DNA motifs from ATAC-seq data using graph neural network and coexisting probability

Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) utilizes hyperactive Tn5 transposase to cut open chromatin and reveal chromatin accessibility at a genome-wide level. ATAC-seq can reveal more kinds of transcription factor binding regions than Chromatin immunoprecipitation sequencing (ChIP-seq) and DNase I hypersensitive sites sequencing (DNase-seq). Transcription factor binding sites (TFBSs) prediction is a crucial step to reveal the functions of TFs from the high throughput sequencing data. TFBSs of the same TF tend to be conserved in the sequence level, which is named motif. Several deep learning models based on the convolutional neural networks are used to find motifs from ATAC-seq data. However, these methods didn’t take into account that multiple TFs bind to a given sequence and the probability that a fragment of a given sequence is a TFBS. To find binding sites of multiple TFs, we developed a novel GNN model named GraphPred for TFBSs prediction and finding multiple motifs using the coexisting probability of k-mers. In the light of the experiment results, GraphPred can find more and higher quality motifs from 88 ATAC-seq datasets than comparison tools. Meanwhile, GraphPred achieved an area of eight metrics radar (AEMR) score of 2.31.
Elemental content of a host-parasite relationship in the threespine stickleback

Parasite infections are ubiquitous and their effects on hosts may play a role in ecosystem processes. Ecological stoichiometry provides a framework to study linkages between consumers and ecosystem process, but the stoichiometric traits of host-parasite associations are rarely quantified. Specifically, whether parasites’ elemental ratios closely resemble those of their host or if infection is related to host stoichiometry remains less known. To answer such questions, we measured the elemental content (%C, %N, and %P) and ratios (C:N, C:P, and N:P) of parasitized and unparasitized Gasterosteus aculeatus (three-spined stickleback) and their cestode parasite, Schistocephalus solidus. Host and parasite elemental content were distinct from each other, and parasites were generally higher in %C and lower in %N and %P. Parasite infections were related to some elemental ratios, specifically C:N, with more intense parasite infections corresponding to hosts with lower C:N ratio. Parasite stoichiometry was independent of their host and there was no relationship between host and parasite stoichiometry. Instead, parasite body mass and parasite density were important drivers of parasite stoichiometry where larger parasites had lower %C, %N, and %P,. Overall, these potential effects of parasite infections on host stoichiometry along with parasites’ distinct elemental compositions suggest parasites may further contribute to how hosts store and cycle nutrients.