Miracle-dz/UniFAR-FTUs huggingface dataset:
KH-type splicing regulatory protein controls colorectal cancer cell growth and modulates the tumor microenvironment

Background & Aims KH-type splicing regulatory protein (KHSRP) is a multifunctional nucleic acid binding protein. KHSRP regulates transcription, mRNA decay and translation, and miRNA biogenesis. These distinct functions are associated with key aspects of cancer cell biology: inflammation and cell-fate determination. However, the role KHSRP plays in colorectal cancer (CRC) tumorigenesis remains largely unknown. Methods We investigated the oncogenic role of KHSRP in CRC using a combination of in silico analysis of large datasets, ex vivo analysis of protein expression in patient samples, and mechanistic studies using in vitro models of CRC. Results KHSRP was expressed in the epithelial and stromal compartments of both primary and metastatic tumors. Elevated KHSRP expression was found in tumor versus matched normal tissue in a cohort of 62 patients. This finding was validated in larger independent cohorts in silico. KHSRP expression was a prognostic indicator of worse overall survival (HR=3.74, 95% CI = 1.43-22.97, p=0.0138). Mechanistic data in CRC cell line models supported a role of KHSRP in driving epithelial cell proliferation in both a primary and metastatic setting, through control of the G1/S transition. Additionally, epithelial KHSRP was involved in promoting a pro-angiogenic extracellular environment, as well as regulating the secretion of oncogenic proteins involved in diverse cellular processes such as migration and response to cellular stress. Conclusion Our study has uncovered novel mechanistic-based data on the tumor-promoting effects of KHSRP in CRC. Synopsis Here we describe a pro-tumorigenic role for KHSRP in colorectal cancer. Higher KHSRP expression is associated with shorter overall survival. KHSRP regulates cancer cell proliferation and expression of proteins that govern processes including angiogenesis, migration and response to cellular stress.
Histopathological Evaluation of Zebrafish (Danio rerio) Intestinal Tissue After Imidacloprid Exposure

The use of pesticides has been increasing day by day to increase productivity in agriculture. Pesticides used in the agricultural area mix into the aquatic ecosystem through rains and groundwater etc. and it threatens the life of aquatic organisms. Nowadays, one of the most used pesticide group is neonicotinoids. Imidacloprid is the most well known in this group. In this study, it was aimed to observe the histopathological effects of imidacloprid in zebrafish intestinal tissue. Adult zebrafish individuals were administered imidacloprid in concentrations of 9.5, 19, and 38 mg.L for 5 days. When tissues are examined under light microscopy, deterioration of villi morphology, degeneration in brush border structure of epithelial cells, hyperplasia in Goblet cells, and enterocytes due to inflammation, enlargement, and disintegration in lamina propria were detected. Also, hypertrophy of the smooth muscle cells and thickening in the muscularis externa layer were observed. Dysplasia was detected in the small intestine tissues in samples belonging to the highest concentration group.
Entrepreneurial Action and Competencies: Exploring Pathways to Venturing Accomplishments

Abstract Scholars often cite an entrepreneur’s actions and their skills, know-how and entrepreneurial competencies (ECs) as the most influential factors related to the accomplishment of important venturing outcomes. Yet the joint impact of these factors on venturing accomplishments is yet to be explored. This paper aims to fill this void by empirically developing and testing a mediation model exploring three EC mechanisms by which entrepreneurial actions—specifically discovery and exploitation activities—led to the achievement of specific venturing accomplishments—namely the time to breakeven and turnover achieved. Data were collected from 1150 South African entrepreneurs using an online survey. Covariance-based structural equation modeling was used to test the hypothesized model. Results show that entrepreneurial action (EA) significantly impacts on the efficiency and effectiveness of a venture through the development of three key ECs. Furthermore, the type of action taken by entrepreneurs during the entrepreneurial process differentially influences competency development and venturing accomplishments. More specifically, opportunity discovery and exploitation activities have a varying impact on EC development, as the engagement in these distinct venture-related activities provides unique feedback for the development of appropriate behavioral scripts for specific contexts which lead to distinct venturing accomplishments. This research offers novel insights into the newly emerging scholarly conviction that engagement in the entrepreneurial process itself may affect key entrepreneurial abilities and accomplishments. In so doing, this paper builds on, and has implications for, theories of competency development and venturing performance, as well as pedagogical interventions aimed at enhancing entrepreneurship.
Skin sensitizer classification using dual-input machine learning model

Skin sensitization is an important aspect of occupational and consumer safety. Because of the ban on animal testing for skin sensitization in Europe, in silico approaches to predict skin sensitizers are needed. Recently, several machine learning approaches, such as the gradient boosting decision tree (GBDT) and deep neural networks (DNNs), have been applied to chemical reactivity prediction, showing remarkable accuracy. Herein, we performed a study on DNN- and GBDT-based modeling to investigate their potential for use in predicting skin sensitizers. We separately input two types of chemical properties (physical and structural properties) in the form of one-hot labeled vectors into single- and dual-input models. All the trained dual-input models achieved higher accuracy than single-input models, suggesting that a multi-input machine learning model with different types of chemical properties has excellent potential for skin sensitizer classification.
Monitoring of Wildlife Mortality on a State Road in Rondônia, Western Amazon

Objective: describe the monitoring of the mortality of wild animals on a state road located in the municipality of Cacaulândia, state of Rondônia, Western Amazon, caused by the hit of vehicles. Method: the methodological procedure follows that recommended in the manual of the Brazilian Center for Road Ecology Studies CBEE). Result: in the 19-month study period, the identification of animals run over and killed by vehicles reaches 2.57 animals per day, corresponding to an average of 77.1 animals per month and totaling 1,464.9 animals. This value corresponds to 0.073 animals killed per km traveled. The most victimized animal class was that of reptiles with a relative frequency of 51%, followed by mammals with 26.5%, birds with 14.3% and amphibians with 8.2%. Conclusions: peak deaths of wild animals occur on rainy days in the Amazon region. However, in the warm season and in the period of forest fires in the region, wildlife mortality rates remain quite high. What is expected is that this study will serve as an elementary basis so that managers of public policies of the infrastructure service in which the road component of the state of Rondônia is a part can adopt mitigating measures consecrated with the effectiveness in reducing / mitigating impacts in different biological groups, in the specific case of wildlife mortality. Keywords— Wild animals. Run over and deaths. Road 140. Rondônia. Western Amazon.
Early warning signals, nonlinearity, and signs of hysteresis in real ecosystems

Early warning signals (EWS) might dramatically improve our ability to manage nonlinear ecological change. However, the degree to which theoretical EWS predictions are supported in empirical systems remains unclear. The goal of this study is to make recommendations for identifying the types of ecological transitions that are expected to show EWS. We conducted a review and meta-analysis of published studies and comparative analysis of eight northeast Pacific Ocean time series to illustrate the importance of testing for nonlinearity in empirical EWS studies. We found that published studies demonstrating nonlinearity in ecosystem dynamics are more likely to support EWS predictions than studies with linear or undetermined dynamics. The northeast Pacific time series in our analysis were often too short for formal tests of nonlinearity, a common problem in empirical studies. To assess the evidence for nonlinear dynamics in these data, we tested for state-dependent driver–response relationships consistent with hysteresis, a central feature of nonlinear ecological models. This analysis supported the results of the literature meta-analysis. Four time series with driver–response relationships consistent with hysteresis generally supported theoretical EWS predictions, while four without evidence of hysteresis failed to support EWS predictions. Theoretical support for EWS is largely generated from nonlinear models, and we conclude that tests for either nonlinear dynamics or hysteresis are needed before employing EWS.
Entering into the weak version of translanguaging: teachers’ English use in children’s Tamil language classes in Singapore

ABSTRACT The current study investigates the impact of the teachers’ societal dominant language use within a weak version of translanguaging in early heritage language education. We explored five preschool teachers’ use of English, the dominant majority language, in Tamil heritage language classes in Singapore and examined its impact on 33 children’s immediate language production in class and in their Tamil language storytelling at the end of the academic year. Our findings demonstrate that while the conventional thinking of protecting the heritage language’s pureness is still dominant, the Tamil language teachers did employ English in their Tamil instruction, and their English use had a substantial variation in frequency. The teachers mostly switched to English due to habituation but not with explicit instructional purposes. When English use aided language instruction, it facilitated children’s comprehension and elicited more child talk. Results also indicated that children model their teacher’s English usage in their immediate responses. When teachers increased their English use in daily practice, children also incorporated increased English use in their Tamil storytelling task at the end of the academic year. Regardless of English use, however, children’s output remained predominantly in Tamil. The implication of using translanguaging in early heritage language education is discussed.
Technical characteristics of elite youth female soccer match-play: position and age group comparisons between under 14 and under 16 age groups

ABSTRACT The purpose of this study was to quantify the technical characteristics of U14 and U16 elite youth female soccer match-play and compare position-specific differences between and within these age groups. A total of 449 match observations from 45 matches were undertaken on 189 players representing Regional Talent Centres in The Football Association’s Girls’ England Talent Pathway league. Linear mixed modelling determined position-specific differences for 24 technical and 4 possession-based variables. Results showed similar team possession-based characteristics at both age groups. Interceptions (U14 = 4.6 ± 0.3, U16 = 3.9 ± 0.3) and tackles (U14 = 4.2 ± 0.3, U16 = 3.2 ± 0.3) were the most common defensive actions. Passes were the most common offensive action (U14 = 21.8 ± 1.8, U16 = 25.1 ± 1.9). In possession, U14 central players performed more actions than wide players, whilst actions were more evenly distributed amongst positions at U16, suggesting a variation in playing style between age groups. Technical performances of players were position-dependent, and differences in offensive and defensive variables were observed between age groups across all positions. These findings may assist practitioners in informing specific coaching practice, training programme design or talent identification processes within this population.
The Impact of COVID-19 Outbreak on the Mental Health of the Pregnant Women: A Systematic Review

Background It is reported that pregnant women have shown different behaviors to the outbreak of COVID-19. The present study aimed to review existing studies concerning pregnant women’s mental health during the COVID-19 outbreak. Materials and Methods In this systematic review, two independent researchers reviewed the impact of COVID-19 on health mental in databases, including Scopus, EMBASE, and Cochrane, Web health of Science, and Medline, without time and language restrictions from inception up to June 10, 2020. The searches were performedusing the following keywords: (Pregnant OR Pregnancy) AND (COVID-19 OR SARS-COV 2) AND (anxiety OR Anxiety). Results The following risk factors affect the pregnant women’s levels of anxiety: underweight during pregnancy, employment, primigravida, lower than 35 years old, low family level and social support, and low physical activity. Women’s psychological responses during the COVID-19 outbreak include anxiety, depression, fear, and stress. Besides, pregnant women in the COVID-19 pandemic have refused to receive any prenatal care and have preferred social isolation. Generally, women’s levels of anxiety and depression had an ascending order. Moreover, findings concerning the relationship between age and pregnancy and levels of anxiety were contradictory. Moreover, levels of anxiety had a relationship with the race as levels of anxiety, and the symptoms of psychological tensions were higher in Arab women compared to Jewish women. Conclusion The anxiety and depression levels among pregnant women during the COVID-19 outbreak have been reported as average to high. It is required for women to be under social support and encourage pregnant women to have more physical activities.
The Origin of Observed Magnetic Variability for a Sol on Mars From InSight

Day‐night variations in the magnetic field at Mars have been previously observed at satellite altitudes. The InSight Fluxgate Magnetometer (IFG) has provided the first evidence for diurnal magnetic field variations at the martian surface. IFG data show diurnal variations with typical peak amplitudes of 20–40nT in the early morning to midmorning; the amplitude of the magnetic field varies over the first 389 sols of the mission and peaks between sols 50 and 100. Temperature variations, solar array currents, and lander activities all generate magnetic fields. Particularly, the first two of these also produce signals with clear diurnal variations. We first assess the IFG data calibration and conclude that temperature and solar array currents have only minimal effects on the variability we observe in the final calibrated magnetic field data. We use satellite magnetic field data and a Mars global circulation model to make predictions for the temporal evolution of wind‐driven fields in the ionosphere. Such fields vary due to seasonal changes in the ionization profile and the winds, and in the altitude range of the dynamo region, that is, the region in which electric currents can be produced. We find that the amplitude and seasonal variability of the surface magnetic fields are generally consistent with those predicted from wind‐driven currents. Moreover, a regional dust storm in the vicinity of the InSight landing site, which started around sol 45, might be responsible for the higher magnetic field amplitudes observed in the IFG data in the early part of the mission.
War, Resistance, and “Combatant Identity:” Hezbollah’s Political Identity and the Legacy of Conflict

ABSTRACT A key issue in analyzing how armed conflict shapes postwar politics pertains to the question of how rebel groups frame their wartime “combatant identity” in the context of their postwar political activism. As armed political organizations active in the midst of conflict, rebel groups’ identities often encompass a “combatant identity” and and what Canetti et al. have described as an “ethos of conflict,” centered on the legitimacy of the use of force, the rightfulness of the rebels’ goals and the defensive nature of their struggle, along with a narrative of victimization and patriotism. How does this identity crystallized in wartime shape political behavior in the aftermath of hostilities or after a political settlement has been reached? How is this combatant identity embedded, reframed and adapted to fit into a broader postwar political narrative? The article explores this question by analyzing the case of Hezbollah’s political and militant identity in the aftermath of the Lebanese civil war; underlying the group’s political, military and social orientation and contextualizing it as operating in a liminal, no-war, no-peace context defined by both the end of the internal civil war and the continuation of the open conflict with Israel. Hezbollah offers an interesting case to examine the resilience of the combatant framework during and in the aftermath of conflict. The article traces the evolution of Hezbollah’s combatant identity from the Lebanese civil war, through its post-agreement political transition, until the group’s involvement in the Syrian conflict. In doing so, it underlines how the group’s combatant identity remained resilient while also being fungible, allowing Hezbollah to preserve core ideological beliefs while shifting its discourse based on political expediency.
Real-Time Road Hazard Information System

Infrastructure is a significant factor in economic growth for systems of government. In order to increase economic productivity, maintaining infrastructure quality is essential. One of the elements of infrastructure is roads. Roads are means which help local and national economies be more productive. Furthermore, road damage such as potholes, debris, or cracks is the cause of many on-road accidents that have cost the lives of many drivers. In this paper, we propose a system that uses Convolutional Neural Networks to detect road degradations without data pre-processing. We utilize the state-of-the-art object detection algorithm, YOLO detector for the system. First, we developed a basic system working on data collecting, pre-processing, and classification. Secondly, we improved the classification performance achieving 97.98% in the overall model testing, and then we utilized pixel-level classification and detection with a method called semantic segmentation. We were able to achieve decent results using this method to detect and classify four different classes (Manhole, Pothole, Blurred Crosswalk, Blurred Street Line). We trained a segmentation model that recognizes the four classes mentioned above and achieved great results with this model allowing the machine to effectively and correctly identify and classify our four classes in an image. Although we obtained excellent accuracy from the detectors, these do not perform particularly well on embedded systems due to their network size. Therefore, we opted for a smaller, less accurate detector that will run in real time on a cheap embedded system, like the Google Coral Dev Board, without needing a powerful and expensive GPU.
INFERIORITY COMPLEX, ADJUSTMENT PROBLEM AND ACADEMIC PERFORMANCE OF DIFFERENTLY-ABLED STUDENTS IN THE STATE OF WEST BENGAL

Purposes of the Study: The main purpose of the present study was to explore the Level of Inferiority Complex and Adjustment Problems of the Differently-Abled students. Besides this, the other purposes of the present study were to find out the relation of Inferiority Complex with Adjustment Problems and Academic Performance of the Differently-Abled students in the state of West Bengal. Methodology: The investigators used Survey based Quantitative method for the present study. The sample consists of 86 Differently-Abled Students from 14 (fourteen) selected special and normal schools which were situated in the district Hooghly, Bankura & Purulia in the state of West Bengal. The simple random sampling technique has been used for the selection of samples. The investigators have developed two tools, namely Questionnaire for Measuring Inferiority Complex and the Adjustment Problem Inventory by themselves to measure the Level of Inferiority Complex and Adjustment Problem of Differently-Abled Students. The present investigators have used SPSS (Version-20) followed by MEAN; S.D. ; 't'-Test; ANOVA and Graph for analyzing the data. Major Findings of the Study: The overall results indicate that the Levels of Inferiority Complex and Adjustment Problem of the Differently-Abled students were Moderate. It was found that Gender, Age and Reading Class had no significant influence on the Inferiority Complex of the Differently-Abled students. It was also explored that the Inferiority Complex and Academic Performance of the Differently-Abled students were negatively interrelated with each other. It means that Academic Performance is decreased by increasing the level of Inferiority Complex of the Differently-Abled students. Applications of the Study: This study will be helpful for the parents, teachers, administrators, counsellors, educational policymakers as well as our society to treat the Differently-Abled students in a better way. Novelty/Originality of the Study: Through the present study, it was found that the level of Inferiority Complex of the Differently-Abled students can be influenced by their Nature of Disability and the Number of Sisters & Brothers. It was a novel finding of the study.
An unexpected contribution of lincRNA splicing to enhancer function

Transcription is common at active mammalian enhancers sometimes giving rise to stable and unidirectionally transcribed enhancer-associated long intergenic noncoding RNAs (elincRNAs). ElincRNA expression is associated with changes in neighboring gene product abundance and local chromosomal topology, suggesting that transcription at these loci contributes to gene expression regulation in cis. Despite the lack of evidence supporting sequence-dependent functions for most elincRNAs, splicing of these transcripts is unexpectedly common. Whether elincRNA splicing is a mere consequence of their cognate enhancer activity or if it directly impacts enhancer-associated cis-regulation remains unanswered. Here we show that elincRNAs are efficiently and rapidly spliced and that their processing rate is strongly associated with their cognate enhancer activity. This association is supported by: their enrichment in enhancer-specific chromatin signatures; elevated binding of co-transcriptional regulators, including CBP and p300; increased local intra-chromosomal DNA contacts; and strengthened cis-regulation on target gene expression. Using nucleotide polymorphisms at elincRNA splice sites, we found that elincRNA splicing enhances their transcription and directly impacts cis-regulatory function of their cognate enhancers. Importantly, up to 90% of human elincRNAs have nucleotide variants that are associated with both their splicing and the expression levels of their proximal genes. Our results highlight an unexpected contribution of elincRNA splicing to enhancer function.