Miracle-dz/UniFAR-FTUs huggingface dataset:
Defining effective care coordination for mental health referrals of refugee populations in the United States

ABSTRACT Objectives: Refugee populations arriving to the United States report high rates of exposure to trauma and associated psychiatric distress that may necessitate referrals to mental health services. Although refugee arrivals receive a voluntary health screening, mental health screening is not routine. Public health providers report that one barrier to mental health screening concerns uncertainty about how to connect refugee patients to mental health services. This article reports essential components of successful and unsuccessful care coordination related to mental health referrals of refugees. Design: A community based participatory research study explored the characteristics of successful and unsuccessful mental health referrals of refugee patients through an online survey of refugee providers. Ten coders sorted provider stories of mental health referrals into critical incidents that were analyzed using principle components analysis (PCA). Care coordination emerged as an important characteristic of referral success. This category of care coordination was analyzed further into components of successful and unsuccessful care coordination using a higher order PCA. A similar process was followed examining providers’ perceptions of why care coordination was successful or unsuccessful. Results: Components describing successful care coordination include ongoing communication between providers, scheduling initial appointments directly, access to emergency mental health services, and case management provided by health plan staff. Components related to unsuccessful care coordination describe the failure to communicate about care or establish appointments in a timely manner and the failure to resolve access barriers. Trust in relationships among providers and between refugee patients and providers was an important reason why care coordination was successful. Conclusion: Ongoing communication between providers is essential to successful mental health referrals of patients with refugee backgrounds. Multidisciplinary systems of care may benefit from education about the importance of building relationships among providers and the essential components of successful care coordination.
Multi-Locus Genome-Wide Association Studies for 14 Main Agronomic Traits in Barley

The agronomic traits, including morphological and yield component traits, are important in barley breeding programs. In order to reveal the genetic foundation of agronomic traits of interest, in this study 122 doubled haploid lines from a cross between cultivars “Huaai 11” (six-rowed and dwarf) and “Huadamai 6” (two-rowed) were genotyped by 9680 SNPs and phenotyped 14 agronomic traits in 3 years, and the two datasets were used to conduct multi-locus genome-wide association studies. As a result, 913 quantitative trait nucleotides (QTNs) were identified by five multi-locus GWAS methods to be associated with the above 14 traits and their best linear unbiased predictions. Among these QTNs and their adjacent genes, 39 QTNs (or QTN clusters) were repeatedly detected in various environments and methods, and 10 candidate genes were identified from gene annotation. Nineteen QTNs and two genes (sdw1/denso and Vrs1) were previously reported, and eight candidate genes need to be further validated. The Vrs1 gene, controlling the number of rows in the spike, was found to be associated with spikelet number of main spike, spikelet number per plant, grain number per plant, grain number per spike, and 1,000 grain weight in multiple environments and by multi-locus GWAS methods. Therefore, the above results evidenced the feasibility and reliability of genome-wide association studies in doubled haploid population, and the QTNs and their candidate genes detected in this study are useful for marker-assisted selection breeding, gene cloning, and functional identification in barley.
Apply KM and SNS in improving the labor productivity of Vietnamese SME

In today’s knowledge era, knowledge management is increasingly considered the best strategy for improving the labor productivity of an enterprise. However, the effectiveness of KM on labor productivity is not known exactly. Despite the growing interest in KM research, there are knowledge gaps, especially in the context of a developing country like Vietnam, in implementing a KMS successfully for improving the labor productivity. So, it is necessary to do research on this subject. Besides, the labor productivity of Vietnam is currently at a very low level. It requires a new management method for improving the labor productivity for sustainable development towards a knowledge society. In order to successfully implement a KMS, a technology readiness, especially ICT maturity, is a requisite. Recently, SNS has been considered not only a popular technique for communication and collaboration, but also a suitable platform for implementing KMS. Therefore, this research tries to apply KM based on SNS to improve the labor productivity of Vietnamese enterprises, especially SMEs, because of its important role.
sPyNNaker: A Software Package for Running PyNN Simulations on SpiNNaker

This work presents sPyNNaker 4.0. 0, the latest version of the software package for simulating PyNN-defined spiking neural networks (SNNs) on the SpiNNaker neuromorphic platform. Operations underpinning realtime SNN execution are presented, including an event-based operating system facilitating efficient time-driven neuron state updates and pipelined event-driven spike processing. Preprocessing, realtime execution, and neuron/synapse model implementations are discussed, all in the context of a simple example SNN. Simulation results are demonstrated, together with performance profiling providing insights into how software interacts with the underlying hardware to achieve realtime execution. System performance is shown to be within a factor of 2 of the original design target of 10,000 synaptic events per millisecond, however SNN topology is shown to influence performance considerably. A cost model is therefore developed characterizing the effect of network connectivity and SNN partitioning. This model enables users to estimate SNN simulation performance, allows the SpiNNaker team to make predictions on the impact of performance improvements, and helps demonstrate the continued potential of the SpiNNaker neuromorphic hardware.
Influences on the Social Practices Surrounding Commercial Music Services: A Model for Rich Interactions

Music can play an important role in social experiences and interactions. Technologies in-use affect these experiences and interactions and as they continue to evolve, social behaviors and norms surrounding them also evolve. In this paper, we explore the social aspects of commercial music services through focus group observation and interview data. We seek to better understand how existing services are used for social music practices and can be improved. We identiﬁed 9 social practices and 24 in-ﬂuences surrounding commercial music services. Based on the user data, we created a model of these practices and inﬂuences that provides a lens through which social experiences surrounding commercial music services can be understood. An understanding of these social practices within their contextual ecosystem help inform what inﬂuences should be considered when designing new technologies. Our ﬁndings include the identiﬁcation of: the underlying relationships between practices and their inﬂu-ences; practices and inﬂuences that inform the weight of relationships in social networks; social norms to be considered when designing social features; inﬂuences that add additional insight to previously observed behaviors; and a detailed explanation of how music selection and listening practices can be supported by commercial music services.
Aligned Sub-Hierarchies: A Structure-based Approach to the Cover Song Task

Extending previous structure-based approaches to the song comparison tasks such as the ﬁngerprint and cover song tasks, this paper introduces the aligned sub-hierarchies (AsH) representation. Built by applying a post-processing technique to the aligned hierarchies of a song, the AsH representation is the set of unique aligned hierarchies for repeats (called AH R ) encoded in the original aligned hierarchies of the whole song. Effectively each AH R within AsH is a section of the aligned hierarchies for the original song. Like aligned hierarchies, the AsH representation can be embedded into a classiﬁcation space with a natural metric that makes inter-song comparisons based on sections of the songs. Experiments addressing a version of the cover song task on score-based data using AsH as the basis of inter-song comparison demonstrate potential of AsH-based approaches for MIR tasks.
Developing a Formal Model of Human Memory in a Simulated Air Traffic Control Conflict Detection Task

This paper describes the development of a formal model of conflict detection in a simulated air traffic control task. The model assumes that people rely on information from two sources when performing conflict detection tasks: perceptual cues, and memory for prior examples. The architecture of the memory system is based on Hintzman's (1986) Minerva 2 model, which is a multiple trace model of episodic and semantic memory. The model was able simulate the performance of naïve experimental participants on a conflict detection task. Aspects of human data that were simulated included differential effects of item repetition on reaction times and false alarm rates during training, and positive and negative transfer from prior examples at test.
Descriptive Study of the Different Tools Used to Evaluate the Adherence to a Gluten-Free Diet in Celiac Disease Patients

Celiac disease (CD) is a genetically conditioned autoimmune process that appears in susceptible people. It can affect people of any age, and slightly predominates in females. It has a fairly homogenous global distribution, with an average prevalence of 1–2%, the frequency having increased in recent decades. The only effective treatment is a strict and permanent gluten-free diet (GFD), although the level of compliance is poor, at about 50% of cases. To monitor the effectiveness of the GFD, several procedures involving various approaches are employed: (a) Periodic visits by expert Nutritionists; (b) Clinical follow-up; (c) Serological time controls of specific antibodies; (d) Serial endoscopies with collection of duodenal biopsies; (e) Use of structured questionnaires; and (f) Determination of gluten peptides derived from gluten in faeces and/or urine. All of these procedures are useful when applied, alone or in combination, depending on the cases. Some patients will only need to consult to their doctors, while others will require a multidisciplinary approach to assess their compliance with the GFD. In children, normalization of duodenal mucosa was achieved in 95% of cases within two years, while it is more delayed in adults, whose mucosa take longer time (3–5 years) to heal completely.
Automated classification of benign and malignant lesions in 18F-NaF PET/CT images using machine learning

Purpose. 18F-NaF PET/CT imaging of bone metastases is confounded by tracer uptake in benign diseases, such as osteoarthritis. The goal of this work was to develop an automated bone lesion classification algorithm to classify lesions in NaF PET/CT images. Methods. A nuclear medicine physician manually identified and classified 1751 bone lesions in NaF PET/CT images from 37 subjects with metastatic castrate-resistant prostate cancer, 14 of which (598 lesions) were analyzed by three additional physicians. Lesions were classified on a five-point scale from definite benign to definite metastatic lesions. Classification agreement between physicians was assessed using Fleiss’ κ. To perform fully automated lesion classification, three different lesion detection methods based on thresholding were assessed: SUV > 10 g ml−1, SUV > 15 g ml−1, and a statistically optimized regional thresholding (SORT) algorithm. For each ROI in the image, 172 different imaging features were extracted, including PET, CT, and spatial probability features. These imaging features were used as inputs into different machine learning algorithms. The impact of different deterministic factors affecting classification performance was assessed. Results. The factors that most impacted classification performance were the machine learning algorithm and the lesion identification method. Random forests (RF) had the highest classification performance. For lesion segmentation, using SORT (AUC = 0.95 [95%CI = 0.94–0.95], sensitivity = 88% [86%–90%], and specificity = 0.89 [0.87–0.90]) resulted in superior classification performance (p < 0.001) compared to SUV > 10 g ml−1 (AUC = 0.87) and SUV > 15 g ml−1 (AUC = 0.86). While there was only moderate agreement between physicians in lesion classification (κ = 0.53 [95% CI = 0.52–0.53]), classification performance was high using any of the four physicians as ground truth (AUC range: 0.91–0.93). Conclusion. We have developed the first whole-body automatic disease classification tool for NaF PET using RF, and demonstrated its ability to replicate different physicians’ classification tendencies. This enables fully-automated analysis of whole-body NaF PET/CT images.
CAARS: comparative assembly and annotation of RNA-Seq data

Abstract Motivation RNA sequencing (RNA-Seq) is a widely used approach to obtain transcript sequences in non-model organisms, notably for performing comparative analyses. However, current bioinformatic pipelines do not take full advantage of pre-existing reference data in related species for improving RNA-Seq assembly, annotation and gene family reconstruction. Results We built an automated pipeline named CAARS to combine novel data from RNA-Seq experiments with existing multi-species gene family alignments. RNA-Seq reads are assembled into transcripts by both de novo and assisted assemblies. Then, CAARS incorporates transcripts into gene families, builds gene alignments and trees and uses phylogenetic information to classify the genes as orthologs and paralogs of existing genes. We used CAARS to assemble and annotate RNA-Seq data in rodents and fishes using distantly related genomes as reference, a difficult case for this kind of analysis. We showed CAARS assemblies are more complete and accurate than those assembled by a standard pipeline consisting of de novo assembly coupled with annotation by sequence similarity on a guide species. In addition to annotated transcripts, CAARS provides gene family alignments and trees, annotated with orthology relationships, directly usable for downstream comparative analyses. Availability and implementation CAARS is implemented in Python and Ocaml and is freely available at https://github.com/carinerey/caars. Supplementary information Supplementary data are available at Bioinformatics online.
UBE2E1 Is Preferentially Expressed in the Cytoplasm of Slow-Twitch Fibers and Protects Skeletal Muscles from Exacerbated Atrophy upon Dexamethasone Treatment

Skeletal muscle mass is reduced during many diseases or physiological situations (disuse, aging), which results in decreased strength and increased mortality. Muscle mass is mainly controlled by the ubiquitin-proteasome system (UPS), involving hundreds of ubiquitinating enzymes (E2s and E3s) that target their dedicated substrates for subsequent degradation. We recently demonstrated that MuRF1, an E3 ubiquitin ligase known to bind to sarcomeric proteins (telethonin, α-actin, myosins) during catabolic situations, interacts with 5 different E2 enzymes and that these E2-MuRF1 couples are able to target telethonin, a small sarcomeric protein, for degradation. Amongst the E2s interacting with MuRF1, E2E1 was peculiar as the presence of the substrate was necessary for optimal MuRF1-E2E1 interaction. In this work, we focused on the putative role of E2E1 during skeletal muscle atrophy. We found that E2E1 expression was restricted to type I and type IIA muscle fibers and was not detectable in type IIB fibers. This strongly suggests that E2E1 targets are fiber-specific and may be strongly linked to the contractile and metabolic properties of the skeletal muscle. However, E2E1 knockdown was not sufficient for preserving the protein content in C2C12 myotubes subjected to a catabolic state (dexamethasone treatment), suggesting that E2E1 is not involved in the development of muscle atrophy. By contrast, E2E1 knockdown aggravated the atrophying process in both catabolic C2C12 myotubes and the Tibialis anterior muscle of mice, suggesting that E2E1 has a protective effect on muscle mass.
Comparison of Audio Features for Recognition of Western and Ethnic Instruments in Polyphonic Mixtures

Studies on instrument recognition are almost always restricted to either Western or ethnic music. Only little work has been done to compare both musical worlds. In this paper, we analyse the performance of various audio features for recognition of Western and ethnic instruments in chords. The feature selection is done with the help of a minimum redundancy - maximum relevance strategy and a multi-objective evolutionary algorithm. We compare the features found to be the best for individual categories and propose a novel strategy based on non-dominated sorting to evaluate and select trade-off features which may contribute as best as possible to the recognition of individual and all instruments.
BRCA1-BARD1 associate with the synaptonemal complex and pro-crossover factors and influence RAD-51 dynamics during Caenorhabditis elegans meiosis

During meiosis, the maternal and paternal homologous chromosomes must align along their entire length and recombine to achieve faithful segregation in the gametes. Meiotic recombination is accomplished through the formation of DNA double-strand breaks, a subset of which can mature into crossovers to link the parental homologous chromosomes and promote their segregation. Breast and ovarian cancer susceptibility protein BRCA1 and its heterodimeric partner BARD1 play a pivotal role in DNA repair in mitotic cells; however, their functions in gametogenesis are less well understood. Here we show that localization of BRC-1 and BRD-1 (Caenorhabditis elegans orthologues of BRCA1 and BARD1) is dynamic during meiotic prophase I; they ultimately becoming concentrated at regions surrounding the presumptive crossover sites, co-localizing with the pro-crossover factors COSA-1, MSH-5 and ZHP-3. The synaptonemal complex and PLK-2 activity are essential for recruitment of BRC-1 to chromosomes and its subsequent redistribution towards the short arm of the bivalent. BRC-1 and BRD-1 form in vivo complexes with the synaptonemal complex component SYP-3 and the crossover-promoting factor MSH-5. Furthermore, BRC-1 is essential for efficient stage-specific recruitment/stabilization of the RAD-51 recombinase to DNA damage sites when synapsis is impaired and upon induction of exogenous damage. Taken together, our data provide new insights into the localization and meiotic function of the BRC-1–BRD-1 complex and highlight its essential role in DNA double-strand break repair during gametogenesis.
An evaluation of mainstream type 2 diabetes educational programmes in relation to the needs of people with intellectual disabilities: A systematic review of the literature

BACKGROUND Risk reduction and self-management programs for type 2 diabetes (T2D) are commonplace. However, little is known about their appropriateness for people with intellectual disabilities (ID). This review evaluates successful components and theoretical basis of interventions and preventions in relation to the needs of people with ID with or at risk of T2D. METHOD Characteristics of 23 randomised controlled trialled T2D educational programs were systematically assessed alongside the needs of people with ID, and evaluated in terms of study design and theoretical application. RESULTS Successful components of programs align to the needs of people with ID. Further adaptations are required to ensure accessibility of materials and social support to enable reflection on illness perceptions and self-efficacy, as underpinned by Self-regulation and Social-cognitive theories. CONCLUSIONS Support is provided for further trials of self-management and preventative adaptations under development. Impact may be enhanced through preventions aimed at younger groups in educational settings.
Optimal Structured Light a la Carte

We consider the problem of automatically generating sequences of structured-light patterns for active stereo triangulation of a static scene. Unlike existing approaches that use predetermined patterns and reconstruction algorithms tied to them, we generate patterns on the fly in response to generic specifications: number of patterns, projector-camera arrangement, workspace constraints, spatial frequency content, etc. Our pattern sequences are specifically optimized to minimize the expected rate of correspondence errors under those specifications for an unknown scene, and are coupled to a sequence-independent algorithm for perpixel disparity estimation. To achieve this, we derive an objective function that is easy to optimize and follows from first principles within a maximum-likelihood framework. By minimizing it, we demonstrate automatic discovery of pattern sequences, in under three minutes on a laptop, that can outperform state-of-the-art triangulation techniques.
Time-dependent effect of oligomeric amyloid-β (1–42)-induced hippocampal neurodegeneration in rat model of Alzheimer’s disease

ABSTRACT Objective: Alzheimer's disease (AD) is characterized with an abnormal deposition of insoluble amyloid-beta (Aβ) peptide plaques, tangles formation and synaptic dysfunction. These result in impaired functioning of neuronal circuits and alter the behavioral response owing to activation of neurotransmitter receptors. Recently, it has been implicated that Aβ influences N-methyl d-aspartate (NMDA) receptor activation in AD; however, the molecular mechanism underlying remains unclear. Thus, emerged specific aim to study the time-course effect of oligomeric Aβ(1–42) (oAβ1–42) on the mRNA expression of genes encoding NMDA and acetylcholine receptors in the rat model of AD. Methods: Aggregated forms of synthetic Aβ peptides were injected bilaterally into the intrahippocampal region of rat brain using stereotaxic surgery. Behavioral analysis was performed using eight-arm Radial Arm Maze task at the end of experimental period. Euthanized rat brain hippocampal tissue was used to study the mRNA expression of glutamatergic and cholinergic receptor using semiquantitative reverse transcription–polymerase chain reaction. Results: oAβ1–42 decreased the gene expression level of α7-nicotinic acetylcholine receptor and increased the mRNA expression of NMDA receptor 2A, and -2B subunits. In particular, oAβ1–42 aggregates increased the retention time and altered the behavioral response in rats after 15 days of injection. Further, amyloid-β1–42 are highly expressed in 15 days after postinjection in hippocampus of adult rats. Conclusion: Acute exposure of oAβ1–42 modulated differential gene expression of glutamatergic and cholinergic receptors in hippocampus of adult rats and is duration dependent reflecting changes in hippocampal circuitry system underlying learning and memory impairments. Abbreviations: AD: Alzheimer’s disease, Aβ: amyloid-β; oAβ1–42: oligomeric amyloid-β 1–42 full length peptide; CAM: calmodulin; CNS: central nervous system; CR: Congo red; DG: dentate gyrus; EC: entorhinal cortex; HFIP: 1,1,1,3,3,3-hexafluoro-2-propanol; IBO: ibotenic acid; NMDA: N-methyl d-aspartate; NMDAR: N-methyl d-aspartate receptor; NR2A: N-methyl d-aspartate receptor 2A; NR2B: N-methyl d-aspartate receptor 2B; ACh: acetylcholine; α7-nAChR: α7-nicotinic acetylcholine receptor; PBS: phosphate buffered saline; RAM: Radial Arm Maze; ThT: thioflavin T.