Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Learning and Training Needs for Social Workers to Serve Clients With Traumatic Brain Injury

ABSTRACT Traumatic brain injury (TBI) disproportionately affects marginalized populations social workers serve. Current practices and training needs of social workers who serve clients with TBI are not well-understood. An online survey was administered to all licensed social workers in Washington (N=5,032) to assess the following for clients with TBI: interactions, challenges, knowledge, beliefs, confidence, and training recommendations. Analyses involved descriptive statistics, logistic regression, and content analysis of open-ended responses. Respondents (n=834, 16.6% response rate) endorsed serving clients with TBI, heterogeneous confidence and practices, limited training, and high learning needs. New training approaches are needed to prepare social workers to better provide services to these clients. Training on diagnosis, understanding comorbidities, treating behavioral symptoms, disparities, and advocacy tools are recommended.
High-speed Railway Real-time Localization Auxiliary Method based on Deep Neural Network

High-speed railway intelligent monitoring and management system is composed of schedule integration, geographic information, location services, and data mining technology for integration of time and space data. Assistant localization is a significant submodule of the intelligent monitoring system. In practical application, the general access is to capture the image sequences of the components by using a high-definition camera, digital image processing technique and target detection, tracking and even behavior analysis method. In this paper, we present an end-to-end character recognition method based on a deep CNN network called YOLO-toc for high-speed railway pillar plate number. Different from other deep CNNs, YOLO-toc is an end-to-end multi-target detection framework, furthermore, it exhibits a state-of-art performance on real-time detection with a nearly 50fps achieved on GPU (GTX960). Finally, we realize a real-time but high-accuracy pillar plate number recognition system and integrate natural scene OCR into a dedicated classification YOLO-toc model.
Teachers’ Views about the Reasons Causing Long-Term Disobedience to School Age Children. Could Long-Term Child Disobedience or Aggressiveness Provide Indications of a Subsequent Criminal Personality?

This paper deals with long-term child disobedience and its potential evolution first into aggressiveness and then into criminality. Sixty-one teachers at primary education school units participated in this empirical survey. Teachers agree that long-term child disobedience is due to: a) reasons linked to problematic family relationships, such as lack of affection, absence of rules or limits, conflicting attitudes, beliefs and behaviors of parents, domestic violence, etc., b) reasons linked to education environment, such as children’s learning difficulties, poor interaction between teacher and student, children’s difficulty in adapting to teaching methods, bullying that a child may suffer because of classmates, absence of communication between parents and school, etc. and c) reasons linked to a child’s broader social environment, such as a child’s participation in cliques with out-of-school individuals, rejection by peers, absence from creative extracurricular activities, watching violent child TV series or playing violent video games, long exposure to the internet, etc. In addition, teachers believe that long-term child disobedience may turn first into aggressiveness and subsequently become criminality. According to teachers, aggressiveness is due to family, education and social reasons, while criminality is due to family and social reasons. Finally, teachers assert that long-term child disobedience is not due to genetic or environment factors and criminality is not due to education structures. Their views are listed, analyzed and discussed in this paper.
Metalloendopeptidase ADAM-like Decysin 1 (ADAMDEC1) in Colonic Subepithelial PDGFRα+ Cells Is a New Marker for Inflammatory Bowel Disease

Metalloendopeptidase ADAM-Like Decysin 1 (ADAMDEC1) is an anti-inflammatory peptidase that is almost exclusively expressed in the gastrointestinal (GI) tract. We have recently found abundant and selective expression of Adamdec1 in colonic mucosal PDGFRα+ cells. However, the cellular origin for this gene expression is controversial as it is also known to be expressed in intestinal macrophages. We found that Adamdec1 mRNAs were selectively expressed in colonic mucosal subepithelial PDGFRα+ cells. ADAMDEC1 protein was mainly released from PDGFRα+ cells and accumulated in the mucosal layer lamina propria space near the epithelial basement membrane. PDGFRα+ cells significantly overexpressed Adamdec1 mRNAs and protein in DSS-induced colitis mice. Adamdec1 was predominantly expressed in CD45− PDGFRα+ cells in DSS-induced colitis mice, with only minimal expression in CD45+ CD64+ macrophages. Additionally, overexpression of both ADAMDEC1 mRNA and protein was consistently observed in PDGFRα+ cells, but not in CD64+ macrophages found in human colonic mucosal tissue affected by Crohn’s disease. In summary, PDGFRα+ cells selectively express ADAMDEC1, which is localized to the colon mucosa layer. ADAMDEC1 expression significantly increases in DSS-induced colitis affected mice and Crohn’s disease affected human tissue, suggesting that this gene can serve as a diagnostic and/or therapeutic target for intestinal inflammation and Crohn’s disease.
Iterative Equalization for SOQPSK in Multipath Fading

This paper investigates the application of iterative equalization techniques to overcome multipath fading for shaped offset QPSK (SOQPSK) in aeronautical telemetry. Two iterative equalization techniques for turbo encoded SOQPSK are presented. The first is the optimal-MAP turbo equalizer for OQPSK. The second equalizer is the adpative decision feedback equalizer. Simulation shows that in the presence of frequency selective multipath typically encountered in aeronautical telemetry, both of these equalizers exhibit impressive performance.
Efficient Simultaneous Introduction of Premature Stop Codons in Three Tumor Suppressor Genes in PFFs via a Cytosine Base Editor

Base editing is an efficient and precise gene-editing technique, by which a single base can be changed without introducing double-strand breaks, and it is currently widely used in studies of various species. In this study, we used hA3A-BE3-Y130F to simultaneously introduce premature stop codons (TAG, TGA, and TAA) into three tumor suppressor genes, TP53, PTEN, and APC, in large white porcine fetal fibroblasts (PFFs). Among the isolated 290 single-cell colonies, 232 (80%) had premature stop codons in all the three genes. C−to−T conversion was found in 98.6%, 92.8%, and 87.2% of these cell colonies for TP53, PTEN, and APC, respectively. High frequencies of bystander C−to−T edits were observed within the editing window (positions 3–8), and there were nine (3.01%) clones with the designed simultaneous three-gene C−to−T conversion without bystander conversion. C−to−T conversion outside the editing window was found in 9.0%, 14.1%, and 26.2% of the 290 cell colonies for TP53, PTEN, and APC, respectively. Low-frequency C−to−G or C−to−A transversion occurred in APC. The mRNA levels of the three genes showed significant declines in triple-gene-mutant (Tri-Mut) cells as expected. No PTEN and a significantly lower (p < 0.05) APC protein expression were detected in Tri-Mut cells. Interestingly, the premature stop codon introduced into the TP53 gene did not eliminate the expression of its full-length protein in the Tri-Mut cells, suggesting that stop codon read-through occurred. Tri-Mut cells showed a significantly higher (p < 0.05) proliferation rate than WT cells. Furthermore, we identified 1418 differentially expressed genes (DEGs) between the Tri-Mut and WT groups, which were mainly involved in functions such as tumor progression, cell cycle, and DNA repair. This study indicates that hA3A-BE3-Y130F can be a powerful tool to create diverse knockout cell models without double-strand breaks (DSBs), with further possibilities to produce porcine models with various purposes.
Familismo, Religiosidad, and Marianismo: College Latina Lesbians Navigating Cultural Values and Roles

ABSTRACT Studies on Latinx/a/o queer and trans students showcase how they navigate cultural expectations tied to their ethnicity about sexuality, gender roles, and gender expression. A predominant focus in this research has been understanding how gay Latino cisgender men exist within and resist systems of patriarchy and hypermasculinity. However, because of the focus on gay Latino men’s experiences, the lives of Latina lesbians have been overlooked in educational research. What does exist illustrates that Latina lesbians face heightened marginalization when attempting to integrate their culture with their lesbian identity given the intersections of sexism, heterosexism, and. In light of such findings, it is crucial to better understand how Latina lesbians make meaning of their identities, especially as they reflect on cultural influences. The purpose of this study was to examine how Latina lesbian college students navigate cultural values and roles. The following research question guided this study: how do Latina lesbians enrolled in college describe the experience of negotiating cultural norms in relationship to their sexuality? Findings will be instrumental for higher education professionals across institutional types as they support students at the intersections of racially and sexually minoritized identities, and especially Latina lesbians.
Application of Grey GM(1,1) Model in the Electronic Equipment's Life Forecasting

The paper first introduces the shortage of equipment' reliability testing data estimation,then according to the basic theory of grey forecast and GM(1,1) model' application,presents the forecast steps.At last,by an example,the theory is used to predict the range that failure of the electronic equipment.Grey prediction has a good result and presents data auspice for electronic equipment's maintain.
A Correlative Study on English Listening Beliefs and Strategies of Chinese High School Students—A Case in Fujian Province

This study investigates the correlation between language learning beliefs and strategies in terms of listening comprehension. Data were collected from 94 tenth graders in a Chinese high school in Fujian Province through questionnaires and in-depth interviews. The findings show a significant and positive correlation between English listening beliefs and strategies, which influence each other to varying degrees. Specifically, the participants were reported to hold various beliefs on English listening while employing a range of strategies for listening comprehension, though the frequency of their overall strategy use was at the medium level. Furthermore, cognitive strategies were found to be the most frequently used ones, followed by socio-affective strategies and metacognitive strategies. Based on the research findings, this article suggests that high school English teachers should help learners foster positive beliefs which normally lead to effective use of learning strategies; meanwhile, learners are advised to keep aware of what beliefs they hold, what strategies they use most or least, and what alternative strategies they can select so as to enhance their metacognition level and improve their listening comprehension.
APEX2-Mediated Proximity Labeling Resolves the DDIT4-Interacting Proteome

DNA damage-inducible transcript 4 (DDIT4) is a ubiquitous protein whose expression is transiently increased in response to various stressors. Chronic expression has been linked to various pathologies, including neurodegeneration, inflammation, and cancer. DDIT4 is best recognized for repressing mTORC1, an essential protein complex activated by nutrients and hormones. Accordingly, DDIT4 regulates metabolism, oxidative stress, hypoxic survival, and apoptosis. Despite these well-defined biological functions, little is known about its interacting partners and their unique molecular functions. Here, fusing an enhanced ascorbate peroxidase 2 (APEX2) biotin-labeling enzyme to DDIT4 combined with mass spectrometry, the proteins in the immediate vicinity of DDIT4 in either unstressed or acute stress conditions were identified in situ. The context-dependent interacting proteomes were quantitatively but not functionally distinct. DDIT4 had twice the number of interaction partners during acute stress compared to unstressed conditions, and while the two protein lists had minimal overlap in terms of identity, the proteins’ molecular function and classification were essentially identical. Moonlighting keratins and ribosomal proteins dominated the proteomes in both unstressed and stressed conditions, with many of their members having established non-canonical and indispensable roles during stress. Multiple keratins regulate mTORC1 signaling via the recruitment of 14-3-3 proteins, whereas ribosomal proteins control translation, cell cycle progression, DNA repair, and death by sequestering critical proteins. In summary, two potentially distinct mechanisms of DDIT4 molecular function have been identified, paving the way for additional research to confirm and consolidate these findings.
Study on network dormancy mechanism based on low duty cycle

Wireless sensor network (WSN) is a wireless communication self-organizing network composed of multiple sensor nodes, which can be used to obtain the information of the monitored objects in the target area. However, due to the characteristics of the nodes that make up the wireless sensor network, the network has the characteristics of large scale, low energy consumption, limited computing and storage capacity. These characteristics play a decisive role in the application of wireless sensors. In this paper, a weight algorithm based on the adaptive sleep mechanism in wireless sensor networks is proposed to improve the network performance. The algorithm mainly aims at the adjustment of the weight, and then to evaluate the importance of the data. By applying the weight algorithm, the original algorithm based on the sleep scheduling mechanism is improved. The performance of the whole network is significantly improved compared with the network optimized by LEACH algorithm and GAF algorithm. The important data can be transmitted to the sink node as soon as possible, which effectively improves the link quality. The energy consumption of the nodes in the network is balanced through the adaptive sleep scheduling algorithm without location information, which improves the network performance and prolongs the network lifetime as much as possible. The simulation results show that the proposed network can perform better than the fully connected network in most cases. In the application and promotion of wireless sensors, there are more in-depth research and wider applications.
Aneurysm-on-a-Chip: Setting Flow Parameters for Microfluidic Endothelial Cultures Based on Computational Fluid Dynamics Modeling of Intracranial Aneurysms

Intracranial aneurysms are pouch-like extrusions from the vessels at the base of the brain which can rupture and cause a subarachnoid hemorrhage. The pathophysiological mechanism of aneurysm formation is thought to be a consequence of blood flow (hemodynamic) induced changes on the endothelium. In this study, the results of a personalized aneurysm-on-a-chip model using patient-specific flow parameters and patient-specific cells are presented. CT imaging was used to calculate CFD parameters using an immersed boundary method. A microfluidic device either cultured with human umbilical vein endothelial cells (HUVECs) or human induced pluripotent stem cell-derived endothelial cells (hiPSC-EC) was used. Both types of endothelial cells were exposed for 24 h to either 0.03 Pa or 1.5 Pa shear stress, corresponding to regions of low shear and high shear in the computational aneurysm model, respectively. As a control, both cell types were also cultured under static conditions for 24 h as a control. Both HUVEC and hiPSC-EC cultures presented as confluent monolayers with no particular cell alignment in static or low shear conditions. Under high shear conditions HUVEC elongated and aligned in the direction of the flow. HiPSC-EC exhibited reduced cell numbers, monolayer gap formation and cells with aberrant, spread-out morphology. Future research should focus on hiPSC-EC stabilization to allow personalized intracranial aneurysm models.
A Novel Transfer Learning Method Based on Conditional Variational Generative Adversarial Networks for Fault Diagnosis of Wind Turbine Gearboxes under Variable Working Conditions

The rapid development of artificial intelligence offers more opportunities for intelligent mechanical diagnosis. Recently, due to various reasons such as difficulty in obtaining fault data and random changes in operating conditions, deep transfer learning has achieved great attention in solving mechanical fault diagnoses. In order to solve the problems of variable working conditions and data imbalance, a novel transfer learning method based on conditional variational generative adversarial networks (CVAE-GAN) is proposed to realize the fault diagnosis of wind turbine test bed data. Specifically, frequency spectra are employed as model signals, then the improved CVAE-GAN are implemented to generate missing data for other operating conditions. In order to reduce the difference in distribution between the source and target domains, the maximum mean difference (MMD) is used in the model to constrain the training of the target domain generation model. The generated data is used to supplement the missing sample data for fault classification. The verification results confirm that the proposed method is a promising tool that can obtain higher diagnosis efficiency. The feature embedding is visualized by t-distributed stochastic neighbor embedding (t-SNE) to test the effectiveness of the proposed model.
Numerical and Experimental Study of an Airing Device for Controlled

Abstract The rationale of an advanced natural ventilation system should be to control airflows and air temperature during winter, and to avoid unnecessary energy losses and local draught, while maintaining an adequate ventilation rate. On the other hand, natural driving forces (pressure head due to buoyancy and wind) vary significantly during the heating season. A prototype of a new device for controlled natural ventilation of buildings has been designed with the aim of avoiding cold draughts and excessive energy consumption during the coldest periods as well as ensuring the right amount of airflow even during mid-seasons. The device has been numerically studied by means of a commercial Computational Fluid Dynamics (CFD) code and has subsequently been built and experimentally tested. The CFD calculations were validated and used to assess the practical possibility of controlling the very low airflow rates typical of natural ventilation. Results will be used to investigate the comfort conditions in a room equipped with such a device during a normal heating season.
Phylogenetic relationships and characterization of the complete chloroplast genome of Paphiopedilum ‘GZSLKY Youyou’, a hybrid of P. dianthum × P. barbigerum

Abstract Paphiopedilum ‘GZSLKY Youyou’. is a new cultivar of Paphiopedilum with highly ornamental and horticultural value developed by crossing female parent Paphiopedilum dianthum T. Tang & F. T. Wang 1940 and male parent Paphiopedilum barbigerum T. Tang & F. T. Wang 1940. In this study, the complete chloroplast genome of the cultivar has been reconstructed from the Illumina sequencing data. The circular genome was 160,503 bp in size, containing a large single-copy region (91,582 bp), a small single-copy region (3,215 bp) and a pair of IR regions (each one 32,853 bp). The overall GC contents of the chloroplast genome was 36.20%. The chloroplast genome contained 122 genes, including 76 protein coding genes, 38 tRNA genes and 8 rRNA genes. A maximum likelihood (ML) phylogenetic tree showed that the cultivar ‘GZSLKY Youyou’ was clustered into the same clade with its parents and was closest related to P. dianthum, reflecting a maternal inheritance of chloroplasts. This complete chloroplast genome resource could be further used for genomic studies, phylogenetic analyses, and genetic engineering and breeding of the genus Paphiopedilum.
Immune-related dissociated response as a specific atypical response pattern in solid tumors with immune checkpoint blockade

Immune checkpoint blockade using immune checkpoint inhibitors, including cytotoxic T-lymphocyte-associated antigen–4 and programmed cell death protein-1/programmed cell death ligand–1 inhibitors, has revolutionized systematic treatment for advanced solid tumors, with unprecedented survival benefit and tolerable toxicity. Nivolumab, pembrolizumab, cemiplimab, avelumab, durvalumab, atezolizumab, and ipilimumab are currently approved standard treatment options for various human cancer types. The response rate to immune checkpoint inhibitors, however, is unsatisfactory, and unexpectedly, atypical radiological responses, including delayed responses, pseudoprogression, hyperprogression, and dissociated responses (DRs), are observed in a small subgroup of patients. The benefit of immunotherapy for advanced patients who exhibit atypical responses is underestimated according to the conventional response evaluation criteria in solid tumors (RECIST). In particular, DR is considered a mixed radiological or heterogeneous response pattern when responding and nonresponding lesions or new lesions coexist simultaneously. The rate of DR reported in different studies encompass a wide range of 3.3–47.8% based on diverse definition of DR. Although DR is also associated with treatment efficacy and a favorable prognosis, it is different from pseudoprogression, which has concordant progressive lesions and can be regularly captured by immune RECIST. This review article aims to comprehensively determine the frequency, definition, radiological evaluation, probable molecular mechanisms, prognosis, and clinical management of immune-related DR and help clinicians and radiologists objectively and correctly interpret this specific atypical response and better understand and manage cancer patients with immunotherapy and guarantee their best clinical benefit.
Post-layout simulation of an ultra-low-power OTA using DTMOS input differential pair

ABSTRACT In this paper, an ultra-low-power dynamic threshold voltage metal-oxide-semiconductor (DTMOS) amplifier is presented. In order to have a high open-loop gain and keep power consumption as low as possible, DTMOS differential pair at input stage technique has been used to improve the specifications of a conventional complementary metal-oxide-semiconductor (CMOS) amplifier such as power supply voltage and power consumption with a proper open-loop gain and unity gain bandwidth. The gain-stage compensation method has been used to overcome the stability problem. The proposed amplifier has been successfully validated and verified in TSMC 0.18 µm CMOS technology and post-layout simulated with Cadence Virtuoso. The post-layout simulation results show that the proposed operational transconductance amplifier (OTA) has 82.77 dB open-loop gain and total power consumption is about 163 nW with 0.4 V voltage supply which is suitable for low-power applications. In the final section in order to evaluate the OTA prefabrication performances, Monte Carlo and corner processes analysis have been performed. Acceptable output swing of 0.37 V is one of the additional features of the proposed OTA.