Miracle-dz/UniFAR-FTUs huggingface dataset:
Workloads Of Nurses In The Family Health In Brazil

Introduction : Workload (WL) is expressed in the working process elements which when interacting with each other and with the worker’s body can materialize themselves into distress, many times as an attempt of adaptation to the work demands. The nurse’s work in the Family Health Strategy (FHS) exposes him to different types of WL and they can be divided into: Psychical, physiological, biological, mechanical and chemical. Objective: To analyze what is being published in the literature regarding workload within the Family Health Strategy in Brazil identifying generator elements and relating them to the types of loads. Method : Integrative revision of the oriented literature through previous protocol, with data collected by two independent collaborators in the following data basis: PUBMED, LILACs, SCIELO and CAPES Bank of Theses in the languages described in Portuguese, English and Spanish in the period from 1994 to 2014. The study inclusion and exclusion descriptions obeyed requirements established by Ganong (1987) and Whittemore (2005). The Atlas.ti ® software was used as a resource for storage and analysis of the studies. Results : No research work specifically approached the WL of nurses in the FHS. There are seven research works that approach the workloads of family health teams, which include the nurses. A total of eight research works approach the health of the FHS teams topic in which it was possible to identify generator elements of WL. From the set of the studies it was identified the presence of psychical, physical, physiological, mechanical and biological loads with predominance of the first ones. There were not found chemical loads. Conclusion : The work of the FHS is exposed to multiple WL generator elements, mainly the psychical loads, followed by the physiological and mechanical ones. However, there is the need of studies aiming to investigate such phenomenon, forming a field to be studied.
Pyrene and nile red fluorescence probes for in‐situ study of polarity and viscosity of soil organic coatings implicated in soil water repellency

Soil water repellency, that is, the reduced ability of soils to absorb water, is thought to be caused by organic coatings with predominantly non‐polar properties on soil particle surfaces. Given the important role of particle surface polarity in determining soil water repellency, we explored the use of fluorescent probes as a method for the direct in‐situ determination of the distribution and polarity of organics on bulk soil surfaces, and of their molecular mobility. We used nile red and pyrene, which have both been used successfully as environmental probes in previous studies, but have not been applied before to bulk soils. The probes were either (a) co‐deposited with other organics known to induce water‐repellent behaviour with acid‐washed sand to produce ‘model soils’ or (b) adsorbed directly onto sandy soils that were naturally water repellent to different degrees, and studied using fluorescence microscopy and steady‐state and time‐resolved fluorescence. Reliable measurements could be made using pyrene as an in‐situ probe on both model and natural soils, and a viscosity/mobility probe on model soils, whereas nile red was found not to be a useful probe. On model soils, made using hexadecane (HEX), octadecane (OCT) or stearic acid (SA) on acid‐washed sand, pyrene excimer formation kinetics showed a decrease in environment mobility as the organic layer changes from a liquid through to a hard wax. Spectra from pyrene adsorbed to natural soils indicated varying environmental polarity and heterogeneity within the soil samples studied.
Association between proteomic blood biomarkers and DTI/NODDI metrics in adolescent football players

The objective of the study was to examine the association between diffusion MRI techniques [diffusion tensor imaging (DTI) and neurite orientation/dispersion density imaging (NODDI)] and brain-injury blood biomarker levels [Tau, neurofilament-light (NfL), glial-fibrillary-acidic-protein (GFAP)] in high-school football and cross-country runners at their baseline, aiming to detect cumulative neuronal damage from prior seasons. Twenty-five football players and 8 cross-country runners underwent MRI and blood biomarker measures during preseason data collection. The whole-brain, tract-based spatial statistics was conducted for six diffusion metrics: fractional anisotropy (FA), mean diffusivity (MD), axial/radial diffusivity (AD, RD), neurite density index (NDI), and orientation dispersion index (ODI). Diffusion metrics and blood biomarker levels were compared between groups and associated within each group. The football group showed lower AD and MD than the cross-country group in various axonal tracts of the right hemisphere. Elevated ODI was observed in the football group in the right hemisphere of the corticospinal tract. Blood biomarker levels were consistent between groups except for elevated Tau levels in the cross-country group. Tau level was positively associated with MD and negatively associated with NDI in the corpus callosum of football players, but not in cross-country runners. Our data suggest that football players may develop axonal microstructural abnormality. Levels of MD and NDI in the corpus callosum were associated with serum Tau levels, highlighting the vulnerability of the corpus callosum against cumulative head impacts. Despite observing multimodal associations in some brain areas, neuroimaging and blood biomarkers may not strongly correlate to reflect the severity of brain damage.
Secreted Phosphoprotein 1 (SPP1) and Fibronectin 1 (FN1) Are Associated with Progression and Prognosis of Esophageal Cancer as Identified by Integrated Expression Profiles Analysis

Background Esophageal cancer is a malignant tumor with a complex pathogenesis and a poor 5-year survival rate, which encourages researchers to explore its molecular mechanisms deeper to improve the prognosis. Material/Methods DEGs were from 4 Gene Expression Omnibus (GEO) databases (GSE92396, GSE20347, GSE23400, and GSE45168) including 87 esophageal tumor samples and 84 normal samples. We performed Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Protein-Protein interaction (PPI) analysis, and GeneMANIA to identify the DEGs. Gene set enrichment analysis (GSEA) and Kaplan-Meier survival analyses were performed. Results There was an overlapping subset consisting of 120 DEGs that was present in all esophageal tumor samples. The DEGs were enriched in extracellular matrix (ECM)-receptor interaction, as well as focal adhesion and transcriptional mis-regulation in cancer. The 2 most crucial regulatory pathways in esophageal cancer were the amebiasis pathway and the PI3K-Akt signaling pathway. Secreted phosphoprotein 1 (SPP1) and fibronectin 1 (FN1) were selected and verified in an independent cohort and samples using the TCGA and GTEx projects. Gene set enrichment analysis (GSEA) showed that proteasome and nucleotide excision repair were 2 most differentially enriched pathways in the SPP1 high-expression phenotype, and ECM-receptor interaction and focal adhesion in FN1 high-expression phenotype. Kaplan-Meier survival analysis showed that SPP1 and FN1 were significantly positively related to overall survival and had the potential to predict patient relapse. Conclusions Our analysis is the first to show that SPP1 and FN1 might work as biological markers of progression and prognosis in esophageal carcinoma (ESCA).
Prevalence, awareness, treatment, and control of hypertension in patients with type 2 diabetes: A cross-sectional survey among middle-aged people in China

Objective: To assess the prevalence, awareness, treatment, and control of hypertension and their associated factors in patients with type 2 diabetes. Methods: A cross-sectional survey across China, including 12,000 participants aged 35-64 years, was conducted in 2009-2010. Data were collected by using questionnaires, blood pressure (BP) measurement, and laboratory test. About 11,623 participants fitted the inclusion. Diabetes was defined as fasting glucose at least 7.0 mmol/L, and/or use of insulin, and/or oral antidiabetic drug. For diabetic participants, hypertension was considered to be controlled if the average BP was <130/80 mmHg. Results: Overall, there were 1063 patients with diabetes (9.2%). The prevalence of hypertension among the patients with diabetes was 59.6%. Among the hypertensive patients (n = 633), 57.5% were aware of their condition, 41.7% received treatment, and only 3.8% had their BP adequately controlled. Age, region, body mass index (BMI), and family hypertension history were correlated with the prevalence, awareness, treatment, and control of hypertension among patients with diabetes. Conclusion: The prevalence of hypertension among patients with diabetes was higher whereas the control was lower. Age, BMI, and family hypertension history were significantly associated with hypertension.
Argonaute Binding within 3’-Untranslated Regions Does Not Predict Gene Repression

Despite two decades of study, the full scope of RNAi in mammalian cells has remained obscure. Here we combine: 1) Knockout of argonaute (AGO) variants; 2) RNA sequencing analysis of gene expression changes; and 3) Crosslinking Immunoprecipitation Sequencing (CLIP-seq) using anti-AGO2 antibody to identify potential microRNA (miRNA) binding sites. We find that knocking out AGO1, AGO2, and AGO3 are necessary to achieve full impact on gene expression. CLIP-seq reveals several hundred significant AGO2 associations within the 3’-untranslated regions of cytoplasmic transcripts. The standard mechanism of miRNA action would suggest that these associations repress gene expression. Contrary to this expectation, clusters are poorly correlated with gene repression in wild-type versus knockout cells. Many clusters are associated with increased gene expression in wild-type versus knock out cells, including the strongest cluster within the MYC 3’-UTR. Our results suggest that assumptions about miRNA action should be re-examined.
Single-cell epigenomic identification of inherited risk loci in Alzheimer’s and Parkinson’s disease

Genome-wide association studies (GWAS) have identified thousands of variants associated with disease phenotypes. However, the majority of these variants do not alter coding sequences, making it difficult to assign their function. To this end, we present a multi-omic epigenetic atlas of the adult human brain through profiling of the chromatin accessibility landscapes and three-dimensional chromatin interactions of seven brain regions across a cohort of 39 cognitively healthy individuals. Single-cell chromatin accessibility profiling of 70,631 cells from six of these brain regions identifies 24 distinct cell clusters and 359,022 cell type-specific regulatory elements, capturing the regulatory diversity of the adult brain. We develop a machine learning classifier to integrate this multi-omic framework and predict dozens of functional single nucleotide polymorphisms (SNPs), nominating gene and cellular targets for previously orphaned GWAS loci. These predictions both inform well-studied disease-relevant genes, such as BIN1 in microglia for Alzheimer’s disease (AD) and reveal novel gene-disease associations, such as STAB1 in microglia and MAL in oligodendrocytes for Parkinson’s disease (PD). Moreover, we dissect the complex inverted haplotype of the MAPT (encoding tau) PD risk locus, identifying ectopic enhancer-gene contacts in neurons that increase MAPT expression and may mediate this disease association. This work greatly expands our understanding of inherited variation in AD and PD and provides a roadmap for the epigenomic dissection of noncoding regulatory variation in disease.
Functional Decision Diagrams: A Unifying Data Structure For Binary Decision Diagrams

Zero-suppressed binary Decision Diagram (ZDD) is a notable alternative data structure of Reduced Ordered Binary Decision Diagram (ROBDD) that achieves a better size compression rate for Boolean functions that evaluate to zero almost everywhere. Deciding \textit{a priori} which variant is more suitable to represent a given Boolean function is as hard as constructing the diagrams themselves. Moreover, converting a ZDD to a ROBDD (or vice versa) often has a prohibitive cost. This observation could be in fact stated about almost all existing BDD variants as it essentially stems from the non-compatibility of the reduction rules used to build such diagrams. Indeed, they are neither interchangeable nor composable. In this work, we investigate a novel functional framework, termed Lambda Decision Diagram (LDD), that ambitions to classify the already existing variants as implementations of special LDD models while suggesting, in a principled way, new models that exploit application-dependant properties to further reduce the diagram's size. We show how the reduction rules we use locally capture the global impact of each variable on the output of the entire function. Such knowledge suggests a variable ordering that sharply contrasts with the static fixed global ordering in the already existing variants as well as the dynamic reordering techniques commonly used.
The Hedgehog Co-Receptor BOC Differentially Regulates SHH Signaling During Craniofacial Development

The Hedgehog (HH) pathway controls multiple aspects of craniofacial development. HH ligands signal through the canonical receptor PTCH1, and three co-receptors– GAS1, CDON and BOC. Together, these co-receptors are required during embryogenesis to mediate proper HH signaling. Here we investigated the individual and combined contributions of GAS1, CDON and BOC to HH-dependent mammalian craniofacial development. Individual deletion of either Gas1 or Cdon results in variable holoprosencephaly phenotypes, characterized by the failure to divide and form the telencephalon and midfacial structures. In contrast, we find that Boc deletion results in facial widening consistent with increased HH pathway activity. Additionally, the deletion of Boc in a Gas1 null background partially rescues the craniofacial defects observed in Gas1 single mutants; a phenotype that persists over developmental time. This contrasts with HH-dependent phenotypes in other tissues that significantly worsen following combined deletion of Gas1 and Boc. Mechanistically, BOC selectively restricts neural crest-derived mesenchymal proliferation. Together, these data indicate that BOC acts as a multi-functional regulator of HH signaling during craniofacial development, alternately promoting or restraining HH pathway activity in a tissue-specific fashion. Summary statement Here we identify dual, tissue-specific roles for the Hedgehog co-receptor BOC in both the promotion and antagonism of Hedgehog signaling during craniofacial development.
An Alternative Fuel Refueling Station Location Model considering Detour Traffic Flows on a Highway Road System

With the development of alternative fuel (AF) vehicle technologies, studies on finding the potential location of AF refueling stations in transportation networks have received considerable attention. Due to the strong limited driving range, AF vehicles for long-distance intercity trips may require multiple refueling stops at different locations on the way to their destination, which makes the AF refueling station location problem more challenging. In this paper, we consider that AF vehicles requiring multiple refueling stops at different locations during their long-distance intercity trips are capable of making detours from their preplanned paths and selecting return paths that may be different from original paths for their round trips whenever AF refueling stations are not available along the preplanned paths. These options mostly need to be considered when an AF refueling infrastructure is not fully developed on a highway system. To this end, we first propose an algorithm to generate alternative paths that may provide the multiple AF refueling stops between all origin/destination (OD) vertices. Then, a new mixed-integer programming model is proposed to locate AF refueling stations within a preselected set of candidate sites on a directed transportation network by maximizing the coverage of traffic flows along multiple paths. We first test our mathematical model with the proposed algorithm on a classical 25-vertex network with 25 candidate sites through various scenarios that consider a different number of paths for each OD pair, deviation factors, and limited driving ranges of vehicles. Then, we apply our proposed model to locate liquefied natural gas refueling stations in the state of Pennsylvania considering the construction budget. Our results show that the number of alternative paths and deviation distance available significantly affect the coverage of traffic flows at the stations as well as computational time.
A Promising Connection of College Journalism Students and Community Engagement

This study has explored the community engagement levels of Taiwanese college journalism students who took the community engagement and public journalism courses, as well as examined the way the practices have made an impact on them. The results indicated that taking community-oriented courses increases an interest in the community for the students. It enhances their abilities when participating in civic engagement activities more than their peers. The finding also showed through focusing the reportage on the residents and helping them to form a dialogue field for discussing community public issues, the participating students recognized the feeling that they have earned the trust and respect from the residents, and were able to rebuild their connection with society. Furthermore, the process not only improved the students’ journalism skills so that they were more likely to produce in-depth and meaningful news coverage, but also strengthened their confidence to become a good news practitioner in the future.
Unsupervised Neural Segmentation and Clustering for Unit Discovery in Sequential Data

We study the problem of unsupervised segmentation and clustering of handwritten lines with applications to character discovery. We propose a constrained variant of Vector Quantized Variational Autoencoder (VQ-VAE) which produces a discrete and piecewise-constant encoding of the data. We show that the constrained quantization task is dual to a Markovian dynamics prior placed on the latent codes. Such view facilitates a probabilistic interpretation of the constraints and allows efficient inference. We demonstrate the effectiveness of the proposed method in the context of unsupervised handwriting character discovery in 17th-century scanned manuscripts.
Development of a Loop-mediated Isothermal Amplification Assay for Rapid Detection of Streptococcus pneumoniae Isolates in Clinical Sputum Samples

Streptococcus pneumoniae is one of the leading causes of invasive infections. Traditional culture and identification methods require a long time period and are liable to be complicated by normal flora. In this study, a new method was developed based on loop-mediated isothermal amplification. A series of primers for autolysin (LytA) from S. pneumoniae were designed with a bioinformatics technique, and a loop-mediated isothermal amplification system for the detection of S. pneumoniae was set up. Comparative analysis of specificity and sensitivity from the culture and polymerase chain reaction methods in 50 samples collected from patients with respiratory infections was performed. The data demonstrated that the selected primers and reaction system in the loop-mediated isothermal amplification were respondent to Streptococcus pneumoniae and did not cross-react with other bacteria. The detection of sensitivity to the loop-mediated isothermal amplification method was 102 CFU/ml. From all of the clinical specimens tested, 9 cases (18.0 %) were confirmed to be positive for Streptococcus pneumoniae using the loop-mediated isothermal amplification method, whereas only 4 cases (8.0 %) were diagnosed using the culture method. Loop-mediated isothermal amplification technology is a specific, simple and accurate method for the efficient differentiation of S. pneumoniae in clinical specimens.
The impact of technology, organizational, and trust factors on social commerce adoption

The utilization of Web 2.0 applications in supporting peoples’ online interactions where the users’ contributions enable firms to lower cost, extend market reach and improve efficiency is termed social commerce. Businesses are able to set up an online community and provide a safe haven for consumers to share experiences, knowledge and data about their services and products. Yet, small and medium sized enterprises of developing countries are unable to quickly adopt social commerce. Thus, it is imperative to analyze the scenario and define the reasons that influence the implementation of social commerce. As such, via a thorough literature review, this study’s objective is to define the organizational, technological and trust factors that influence the adoption of social commerce (SC), and the way in which implementation of social commerce influences organization’s performance. There is also a suggestion of a conceptual framework following the strengths of three models: Unified Theory for Acceptance and Use Technology (UTAUT), Information Systems Success Model and Technology, Organization and Environment (TOE). Hopefully, the suggested framework may assist in deciding policies and actions that encourage adoption of social commerce.
Adaptive relative velocity estimation algorithm for autonomous mobile robots using the measurements on acceleration and relative distance

In this article, an adaptive algorithm is proposed for online velocity estimation of the autonomous mobile robots (AMRs) without positioning data received from a Global Positioning System (GPS) module or other means for odometry. Unlike the popular Kalman and particle filters that use the measurements on vectors of global (or local) position and acceleration of a mobile robot, the proposed adaptive relative velocity estimation (ARVE) algorithm requires the scalar value of measured distance to a beacon agent and also the measurement on acceleration vector, in order to generate an online estimation of the global velocity vector of a mobile robot. Combining the ARVE algorithm with the recently proposed adaptive relative position estimation (ARPE) algorithm provides a solution for online estimation of the translational states of a mobile robot without accessing the GPS data, which makes the package applicable in both indoor and outdoor environments. The stability of the ARVE algorithm is analyzed with LaSalle‐Yoshizawa theorem. In addition, two simulation studies are provided to show the application of the proposed estimation package (ARVE+ARPE) for aerial AMRs in two cases corresponding to the stationary and moving beacon agents. In the simulation results, it is shown that the estimation package can be used in conjunction with the recently proposed adaptive model‐free control (AMFC) algorithm to achieve desired tracking objective in autonomous movement of a quadrotor, without requiring the information on the internal dynamics of the robot.