Public Web Research Articles

Workplaces: Pasts and Presents Takes the Digital Turn

<i>Workplaces: Pasts and Presents</i> Takes the Digital Turn

A Machine Learning Model for Early Prediction of Crop Yield, Nested in a Web Application in the Cloud: A Case Study in an Olive Grove in Southern Spain

Predictive systems are a crucial tool in management and decision-making in any productive sector. In the case of agriculture, it is especially interesting to have advance information on the profitability of a farm. In this sense, depending on the time of the year when this information is available, important decisions can be made that affect the economic balance of the farm. The aim of this study is to develop an effective model for predicting crop yields in advance that is accessible and easy to use by the farmer or farm manager from a web-based application. In this case, an olive orchard in the Andalusia region of southern Spain was used. The model was estimated using spatio-temporal training data, such as yield data from eight consecutive years, and more than twenty meteorological parameters data, automatically charged from public web services, belonging to a weather station located near the sample farm. The workflow requires selecting the parameters that influence the crop prediction and discarding those that introduce noise into the model. The main contribution of this research is the early prediction of crop yield with absolute errors better than 20%, which is crucial for making decisions on tillage investments and crop marketing.

Standard deviation estimation from sums of unequal size samples

Abstract In numerous industrial and related activities, the sums of the values of, frequently, unequal size samples are systematically recorded, for several purposes such as legal or quality control reasons. For the typical case where the individual values are not or no longer known, we address the point estimation, with confidence intervals, of the standard deviation (and mean) of the individual items, from those sums alone. The estimation may be useful also to corroborate estimates from previous statistical process control. An everyday case of a sum is the total weight of a set of items, such as a load of bags on a truck, which is used illustratively. For the parameters mean and standard deviation of the distribution, assumed Gaussian, we derive point estimates, which lead to weighted statistics, and we derive confidence intervals. For the latter, starting with a tentative reduction to equal size samples, we arrive at a solid conjecture for the mean, and a proposal for the standard deviation. All results are verifiable by direct computation or by simulation in a general and effective way. These computations can be run on public web pages of ours, namely for possible industrial use.

Ab Initio Phase Diagram of Chromium to 2.5 TPa

Chromium possesses remarkable physical properties such as hardness and corrosion resistance. Chromium is also a very important geophysical material as it is assumed that lighter Cr isotopes were dissolved in the Earth’s molten core during the planet’s formation, which makes Cr one of the main constituents of the Earth’s core. Unfortunately, Cr has remained one of the least studied 3d transition metals. In a very recent combined experimental and theoretical study (Anzellini et al., Scientific Reports, 2022), the equation of state and melting curve of chromium were studied to 150 GPa, and it was determined that the ambient body-centered cubic (bcc) phase of crystalline Cr remains stable in the whole pressure range considered. However, the importance of the knowledge of the physical properties of Cr, specifically its phase diagram, necessitates further study of Cr to higher pressure. In this work, using a suite of ab initio quantum molecular dynamics (QMD) simulations based on the Z methodology which combines both direct Z method for the simulation of melting curves and inverse Z method for the calculation of solid–solid phase transition boundaries, we obtain the theoretical phase diagram of Cr to 2.5 TPa. We calculate the melting curves of the two solid phases that are present on its phase diagram, namely, the lower-pressure bcc and the higher-pressure hexagonal close-packed (hcp) ones, and obtain the equation for the bcc-hcp solid–solid phase transition boundary. We also obtain the thermal equations of state of both bcc-Cr and hcp-Cr, which are in excellent agreement with both experimental data and QMD simulations. We argue that 2180 K as the value of the ambient melting point of Cr which is offered by several public web resources (“Wikipedia,” “WebElements,” “It’s Elemental,” etc.) is most likely incorrect and should be replaced with 2135 K, found in most experimental studies as well as in the present theoretical work.

What do psychiatrists think about renaming schizophrenia in Turkey?

In this study, it was aimed to evaluate the opinions of psychiatrists in Turkey on whether to change the name of schizophrenia in order to reduce stigma. This cross-sectional survey was conducted with psychiatrists (resident in psychiatry, specialist, and lecturer) in Turkey. An online survey was created via the Google Forms public web address. Online questionnaires were delivered through Google Forms by emailing and messaging on WhatsApp, Telegram, Google and Yahoo groups and asking them to pass the questionnaire to other possible participants in their network. The study was performed between June 20, 2021 and July 10, 2021. 460 psychiatrists participated in the study. Forty-five-point 2 % of psychiatrists think that the name of schizophrenia should be renamed to reduce stigma. Forty-two-point 8 % of those who support the name change state that this change should be done as soon as possible. While 64.1 % of psychiatrists stated that naming the disease with another (new) name instead of schizophrenia could increase the hopes of patients and their relatives for recovery, 12.6 % stated that renaming would not cause any positive or negative changes. There is no statistical difference between psychiatrists who have a relative diagnosed with schizophrenia and psychiatrists who do not, in terms of thinking that the name of schizophrenia should be renamed to reduce stigma. In order to remove the stigma on schizophrenia, many interventions are required in social, cultural, economic and political fields. Renaming schizophrenia may be a good start for interventions.

How Do We Define and Measure Health Equity? The State of Current Practice and Tools to Advance Health Equity.

Introduction:Healthy People establishes national goals and specific measurable objectives to improve the health and well-being of the nation. An overarching goal of Healthy People 2030 is to “eliminate health disparities, achieve health equity, and attain health literacy to improve the health and well-being of all.” To inform Healthy People 2030 health equity and health disparities content and products, the US Department of Health and Human Services (HHS) Office of Disease Prevention and Health Promotion (ODPHP), in collaboration with NORC at the University of Chicago, conducted a review of peer-reviewed and gray literature to examine how health equity is defined, conceptualized, and measured by public health professionals.Methods:We reviewed (1) peer-reviewed literature, (2) HHS and other public health organization Web sites, and (3) state and territorial health department plans. We also conducted targeted searches of the gray literature to identify tools and recommendations for measuring health equity.Results:While definitions of health equity identified in the scan varied, they often addressed similar concepts, including “highest level of health for all people,” “opportunity for all,” and “absence of disparities.” Measuring health equity is challenging; however, strategies to measure and track progress toward health equity have emerged. There are a range of tools and resources that have the potential to help decision makers address health equity, such as health impact assessments, community health improvement plans, and adapting a Health in All Policies approach. Tools that visualize health equity data also support data-driven decision making.Discussion:Using similar language when discussing health equity will help align and advance efforts to improve health and well-being for all. Healthy People objectives, measures, and targets can help public health professionals advance health equity in their work. HHS ODPHP continues to develop Healthy People tools and resources to support public health professionals as they work with cross-sector partners to achieve health equity.

Open Doors by Fair Means: a quasi-experimental controlled study on the effects of an open-door policy on acute psychiatric wards

BackgroundPsychiatric wards treating involuntarily admitted patients are traditionally locked to prevent absconding. However, on the basis of observational evidence, the necessity for locked units in psychiatric hospitals has increasingly been questioned. Updated Mental Health Laws in several Federal States of Germany legitimate involuntary commitment without generally locked doors.MethodsWe examined the effects of an open-door policy in a quasi-experimental, prospective design. For the first time, at each of two locations, two identical wards serving as control and intervention could be compared. After a baseline period of three months, one ward at each location started the 12 month intervention period with the implementation of an open-door policy, while the respective control ward, as before, used open doors only facultatively. Primary outcomes were average opening times of the four wards between 8 a.m. and 8 p.m., and the number of involuntary treatment days with the doors open. Secondary outcomes were adverse events including aggressive incidents, absconding, suicide attempts and coercive measures.ResultsOverall, door-opening times increased significantly at both sites´ intervention wards. The number of adverse events did not increase during intervention period. Frequencies of coercive measures decreased in Friedrichshafen and remained unchanged in Tuebingen. In case of the intervention ward in Friedrichshafen, doors were open in up to 91% of all involuntary treatment days, whereas in the control ward, this was only the case in 67% of all involuntary treatment days (p < .001). In case of the intervention ward in Tuebingen, 45% of involuntary treatment days had open doors, compared to 30% in the control ward (p < .001).ConclusionsIt is possible to manage psychiatric wards with open doors without taking inappropriate risks. The extent to which open-door policies are achievable is be dependent on staffing and patient characteristics. Further research is necessary to explore the role of staff attitudes.Trial registrationOur trial "Open Doors by Fair Means" is retrospectively registered with DRKS (DRKS00015154) on Sept. 10th 2018 and displayed on the public web site. It is searchable via its meta-registry (http://apps.who.int/trialsearch/).

Establishing an Intelligent Emotion Analysis System for Long-Term Care Application Based on LabVIEW

In this study, the authors implemented an intelligent long-term care system based on deep learning techniques, using an AI model that can be integrated with the Lab’s Virtual Instrumentation Engineering Workbench (LabVIEW) application for sentiment analysis. The input data collected is a database of numerous facial features and environmental variables that have been processed and analyzed; the output decisions are the corresponding controls for sentiment analysis and prediction. Convolutional neural network (CNN) is used to deal with the complex process of deep learning. After the convolutional layer simplifies the processing of the image matrix, the results are computed by the fully connected layer. Furthermore, the Multilayer Perceptron (MLP) model embedded in LabVIEW is constructed for numerical transformation, analysis, and predictive control; it predicts the corresponding control of emotional and environmental variables. Moreover, LabVIEW is used to design sensor components, data displays, and control interfaces. Remote sensing and control is achieved by using LabVIEW’s built-in web publishing tools.

Lessons learned from developing a statewide research data repository to combat the opioid epidemic in Alabama.

Many states are continuing to struggle with opioids and other commonly abused drugs. Alabama, being the highest opioid prescription per-capita state since 2012, has pulled together state agencies, private companies, academia, and community organizations to form a data council and repository to provide unified insights and information to the public and partner stakeholders. The lessons learned in constructing this data environment are documented so that other states and organizations can benefit from the challenges and success that Alabama has experienced. The centralized data repository consists of almost a dozen data streams from public agencies and private companies. The data are transformed and linked within the repository to provide geo-temporal linkages between data sources. The data are stored in a secure multi-tiered environment in a Microsoft SQL Server database, de-identified, aggregated, and then published to a public web portal for open consumption. The public-facing website from the project successfully integrates multiple disparate data sources into a common platform for streamlined and cohesive data communications. Drug addiction cannot be easily quantified, viewed, or otherwise examined when only looking at a portion of society. By bringing together multiple data sources and linking them, a more clear picture of trends, influences, and metrics can be obtained. A statewide drug use data partnership between public and private entities is both possible as well as beneficial to all parties involved. Items like legal contracts can inhibit data sharing, but certain best practices can help scale and streamline multiple agreements.

Chromoblastomycosis-Leprosy Co-Infection in Central West Brazil. Presentation of Three Cases and Literature Review

Chromoblastomycosis and leprosy are chronic diseases with high prevalence in tropical and subtropical regions. Brazil is one of the countries with the highest incidence and prevalence for both diseases, however, reports of co-infections are scarce. The aim of this study was to describe three cases of chromoblastomycosis-leprosy co-infection in patients from Mato Grosso state, Brazil. A review of chromoblastomycosis-leprosy co-infection was performed of English, Portuguese and Spanish publications in LILACS, SciELO, PubMed and Web of Science databases using the descriptors (chromoblastomycosis OR cromoblastomicose OR cromoblastomicosis) AND (leprosy OR hanseníase OR lepra), without time period delimitation. Nineteen cases were included, 16 cases were published in 11 articles, plus the three cases reported in the current study. Most reported coninfection cases came from Brazil. Majority of the patients were male with a mean age of 52.2 years. Farmer was the main occupational activity reported. In 12 patients, the clinical signs and symptoms of leprosy started first. No contacts with patients affected by leprosy, armadillos or history of injuries at the anatomical site of chromoblastomycosis lesions were reported. Five leprosy patients who received steroid treatment for leprosy reactions or neuropathies, were diagnosed with chromoblastomycosis during immunosuppressive therapy. Four cases (21.1%) were reported among the elderly patients. Co-infections in patients with chromoblastomycosis or leprosy are uncommon, but the possibility should always be considered, especially if the patient is undergoing immunosuppressive treatment or is elder.

Potential and limitations of LiDAR altimetry in archaeological survey. Copper Age and Bronze Age settlements in southern Iberia

Potential and limitations of LiDAR altimetry in archaeological survey. Copper Age and Bronze Age settlements in southern Iberia

Entropies Derived from the Packing Geometries within a Single Protein Structure.

A fast, simple, yet robust method to calculate protein entropy from a single protein structure is presented here. The focus is on the atomic packing details, which are calculated by combining Voronoi diagrams and Delaunay tessellations. Even though the method is simple, the entropies computed exhibit an extremely high correlation with the entropies previously derived by other methods based on quasi-harmonic motions, quantum mechanics, and molecular dynamics simulations. These packing-based entropies account directly for the local freedom and provide entropy for any individual protein structure that could be used to compute free energies directly during simulations for the generation of more reliable trajectories and also for better evaluations of modeled protein structures. Physico-chemical properties of amino acids are compared with these packing entropies to uncover the relationships with the entropies of different residue types. A public packing entropy web server is provided at packing-entropy.bb.iastate.edu, and the application programing interface is available within the PACKMAN (https://github.com/Pranavkhade/PACKMAN) package.

COLMARq: A Web Server for 2D NMR Peak Picking and Quantitative Comparative Analysis of Cohorts of Metabolomics Samples

Highly quantitative metabolomics studies of complex biological mixtures are facilitated by the resolution enhancement afforded by 2D NMR spectra such as 2D 13C–1H HSQC spectra. Here, we describe a new public web server, COLMARq, for the semi-automated analysis of sets of 2D HSQC spectra of cohorts of samples. The workflow of COLMARq includes automated peak picking using the deep neural network DEEP Picker, quantitative cross-peak volume extraction by numerical fitting using Voigt Fitter, the matching of corresponding cross-peaks across cohorts of spectra, peak volume normalization between different spectra, database query for metabolite identification, and basic univariate and multivariate statistical analyses of the results. COLMARq allows the analysis of cross-peaks that belong to both known and unknown metabolites. After a user has uploaded cohorts of 2D 13C–1H HSQC and optionally 2D 1H–1H TOCSY spectra in their preferred format, all subsequent steps on the web server can be performed fully automatically, allowing manual editing if needed and the sessions can be saved for later use. The accuracy, versatility, and interactive nature of COLMARq enables quantitative metabolomics analysis, including biomarker identification, of a broad range of complex biological mixtures as is illustrated for cohorts of samples from bacterial cultures of Pseudomonas aeruginosa in both its biofilm and planktonic states.

Identification of Gene-Tyrosine Kinase 2 (TYK2) in Head and Neck Squamous Cell Carcinoma Patients-An Integrated Bioinformatics Approach.

Background The human tyrosine kinase 2 (TYK2) has been found to be associated with at least 20 autoimmune diseases; however, its tumor-regulating role in head and neck squamous cell carcinoma (HNSC) has not been researched by using an integrative bioinformatics approach, yet. Objective To investigate the regulating mechanisms of the TYK2 gene in HNSC in terms of its expression pattern, prognostic values, involved biological functions, and implication of tumor immunity. Methods The TYK2 gene expression pattern and regulatory involvement in HNSC were investigated using publically accessible data from TCGA database. R software tools and public web servers were utilized to conduct statistical analysis on cancer and noncancerous samples. Results TYK2 was found to be significantly upregulated in HNSC samples compared with healthy control samples. The expression of TYK2 gene was shown to be associated with the prognosis of HNSC by showing its upregulation represented better survival outcome. The regulating role of TYK2 in HNSC was found mainly in several pathways including DNA replication, base excision repair, apoptosis, p53 signaling pathway, and NF-kappa B signaling pathway. The gene set enrichment analysis (GSEA) results showed that TYK2-significantly correlated genes were mainly enriched in several biological functional terms including cell cycle, DNA replication, PLK1 pathway, ATR pathway, and Rho GTPase pathway. In addition, TYK2 was found to be involved in tumor immunity, showing positive correlation with the majority of tumor infiltrating immune cells, immune checkpoint genes, and significant representative components of tumor microenvironment, according to the ESTIMATE-Stromal-Immune score. Conclusions Given the dysregulation, prognostic values, regulating tumor progression-related pathways, and the tumor immune-modulatory role of TYK2 in HNSC, the TYK2 gene should be regarded as a potential therapeutic target in treating head and neck cancer.

The Emerging Role of MTHFD Family Genes in Regulating the Tumor Immunity of Oral Squamous Cell Carcinoma.

Objective To investigate the function and regulatory mechanisms of methylenetetrahydrofolate dehydrogenase (MTHFD) family genes in oral squamous cell carcinoma (OSCC), especially focus on their regulating role in tumor immunity. Methods The publicly available data from the TCGA database were used to investigate the expression pattern and regulatory role of MTHFD family genes in OSCC. More importantly, the involvement of MTHFD family genes in tumor immunity was investigated in terms of immune and stromal cell infiltration in tumor microenvironment, tumor-infiltrating immune cells, and immunomodulatory genes (e.g., immunoinhibitory genes and immunostimulatory genes). Statistical analysis was performed using R software packages and public web servers. Results MTHFD family genes were considerably upregulated in OSCC as compared with normal oral tissue. Patients with high MTHFD2 expression presented worse survival outcomes than those with low MTHFD2 expression. Functional enrichment analysis showed that the top 100 positively and negatively correlated genes of the MTHFD family genes were significantly enriched in several KEGG pathways, including cell cycle, spliceosome, DNA replication, and Th17 cell differentiation. As a result of tumor immunity analysis, MTHFD2L expression was found to be negatively related to the Estimate-Stromal-Immune score in OSCC; however, there was no statistical significance between the Estimate-Stromal-Immune score and MTHFD1, MTHFD1L, or MTHFD2 in OSCC. Additionally, MTHFD family genes were found to be significantly positively correlated with tumor-infiltrating immune cells, including Treg and Th17 cells. Moreover, MTHFD family genes were significantly correlated with several immune inhibitory genes such as CD274 and CTLA4 and several immune-stimulatory genes such as CXCL12, CXCR4, and TMIGD2. Conclusion Given the expression pattern, prognostic value, biological functions, and involvement in tumor immunity, MTHFD family genes could serve as potential therapeutic biomarkers in targeting tumor immunity in oral cancer.

A Bioinformatic Rational Gene Targeting Approach to Treating Pathologies With Healthy Diet

ObjectivesWe hypothesize that identification of healthy whole foods that modulate disease-causing gene expression back toward the normal is a low-cost, healthy, and readily-translatable alternative and/or complementary approach to costly and sometimes toxic pharmaceutical drugs. Our objectives are (1) to identify human studies assessing gene expression after healthy whole food ingestion, and (2) use this data to develop an online app for patients, community and healthcare providers as a dietary guide for a wide range of diseases and conditions.MethodsWe used the keywords “human”, “gene expression” and separately, 42 different dietary agents with reported health benefits to search GEO, PubMed, Google Scholar, Clinical trials, Cochrane library, and EMBL-EBI for studies. For app development, The R-Shiny platform was utilized to construct a public web app (“Eat4Genes”) featuring: a drop-down disease or condition selector; risk genes; user menus; dietary studies; ranking; and study links. To identify key risk genes, the above databases, Big Pharma targets, and NCBI's “Genes and Disease” were reviewed.Results42 human whole food (or extract) studies were identified. Despite varying conditions (e.g., 4 hours to 8 week diets), the number of whole genome modulated genes were reasonable consistent (1061 +/− 227 SEM). Human gene expression studies were only found for 13 of 34 searched whole foods, underscoring the need for more as compared with much less useful but much more prevalent dietary supplement, cell culture and rodent studies. We identified 96 key risk genes for a wide range of pathologies (e.g., HMGCR for Hypercholesterolemia) for our app. Successful app construction was achieved with the above features, and included the ability to select specific diseases/conditions followed by their key risk genes, identification of dietary agents that express and modulate these genes, and the studies supporting these findings with numerous links. A usability survey was also carried out (N = 17).ConclusionsOur dietary rational gene targeting approach offers an innovative, low-cost, healthy, personalized, and readily translatable strategy to improve health and reduce treatment costs. Construction of our new Eat4Genes app now extends its promise to practice in the form of an interactive online dietary guide.Funding SourcesNIH, the Wildermuth Foundation, and IDEA at RPI.

"Teachers' Emotional Labor" Publications in Web of Science: A Bibliometric Analysis.

One of the indicators that symbolize the success of an academic field is its academic publications in well-established citation indices. This article first explored the bibliometric characteristics of publications on “teachers' emotional labor” (TEL) in the Social Sciences Citation Index (SSCI) and the Arts & Humanities Citation Index (A&HCI), two prestigious citation indices available in the Web of Science (WoS). Search with the term “teacher emotional labor” retrieved 173 publications that included this term in their titles, abstracts, or keywords in the WoS database between 1900 and 2020. The bibliometric characteristics pertaining to numbers of publications, document types, research categories, research areas, authors, journals, universities, and countries were reported. Then, CiteSpace was utilized to visualize TEL research and to obtain insights into its research focuses and its future directions. The findings will contribute to TEL research by informing scholars in the fields of L2 research and psychology and others.

The Immunometabolic Atlas: A tool for design and interpretation of metabolomics studies in immunology.

Immunometabolism, which concerns the interplay between metabolism and the immune system, is increasingly recognized as a potential source of novel drug targets and biomarkers. In this context, the use of metabolomics to identify metabolic characteristics associated with specific functional immune response processes is of value. Currently, there is a lack of tools to determine known associations between metabolites and immune processes. Consequently, interpretation of metabolites in metabolomics studies in terms of their role in the immune system, or selection of the most relevant metabolite classes to include in metabolomics studies, is challenging. Here, we describe the Immunometabolic Atlas (IMA), a public web application and library of R functions to infer immune processes associated with specific metabolites and vice versa. The IMA derives metabolite-immune process associations utilizing a protein-metabolite network analysis algorithm that associates immune system-associated annotated proteins in Gene Ontology to metabolites. We evaluated IMA inferred metabolite-immune system associations using a text mining strategy, identifying substantial overlap, but also demonstrating a significant chemical space of immune system-associated metabolites that should be confirmed experimentally. Overall, the IMA facilitates the interpretation and design of immunometabolomics studies by the association of metabolites to specific immune processes.

The Immunometabolic Atlas: A tool for design and interpretation of metabolomics studies in immunology

Immunometabolism, which concerns the interplay between metabolism and the immune system, is increasingly recognized as a potential source of novel drug targets and biomarkers. In this context, the use of metabolomics to identify metabolic characteristics associated with specific functional immune response processes is of value. Currently, there is a lack of tools to determine known associations between metabolites and immune processes. Consequently, interpretation of metabolites in metabolomics studies in terms of their role in the immune system, or selection of the most relevant metabolite classes to include in metabolomics studies, is challenging. Here, we describe the Immunometabolic Atlas (IMA), a public web application and library of R functions to infer immune processes associated with specific metabolites and vice versa. The IMA derives metabolite-immune process associations utilizing a protein-metabolite network analysis algorithm that associates immune system-associated annotated proteins in Gene Ontology to metabolites. We evaluated IMA inferred metabolite-immune system associations using a text mining strategy, identifying substantial overlap, but also demonstrating a significant chemical space of immune system-associated metabolites that should be confirmed experimentally. Overall, the IMA facilitates the interpretation and design of immunometabolomics studies by the association of metabolites to specific immune processes.

RSAT 2022: regulatory sequence analysis tools.

RSAT (Regulatory Sequence Analysis Tools) enables the detection and the analysis of cis-regulatory elements in genomic sequences. This software suite performs (i) de novo motif discovery (including from genome-wide datasets like ChIP-seq/ATAC-seq) (ii) genomic sequences scanning with known motifs, (iii) motif analysis (quality assessment, comparisons and clustering), (iv) analysis of regulatory variations and (v) comparative genomics. RSAT comprises 50 tools. Six public Web servers (including a teaching server) are offered to meet the needs of different biological communities. RSAT philosophy and originality are: (i) a multi-modal access depending on the user needs, through web forms, command-line for local installation and programmatic web services, (ii) a support for virtually any genome (animals, bacteria, plants, totalizing over 10 000 genomes directly accessible). Since the 2018 NAR Web Software Issue, we have developed a large REST API, extended the support for additional genomes and external motif collections, enhanced some tools and Web forms, and developed a novel tool that builds or refine gene regulatory networks using motif scanning (network-interactions). The RSAT website provides extensive documentation, tutorials and published protocols. RSAT code is under open-source license and now hosted in GitHub. RSAT is available at http://www.rsat.eu/.