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The ParlaMint project, a CLARIN flagship initiative, seeks to standardize the representation of parliamentary data across diverse languages and regions. Version 3.0 of ParlaMint encompasses corpora from 26 European countries and autonomous regions, available for download and search under the CC-BY license. These corpora adhere to a common XML encoding schema, ensuring interoperability. This study evaluates the feasibility of applying the ParlaMint schema to the proceedings of the Parliament of the Republic of South Africa. Through the conversion of a randomly selected parliamentary session, we scrutinize how various elements are modelled, delineating the steps required to initiate a comprehensive encoding endeavour. The experiment starts with data retrieval by downloading Hansard records from the South African Parliament website. An English session was selected to streamline processing for non-South African researchers. The original format consisted of session headers, metadata, introductory messages, and debate records. Speeches were identified by uppercase headers and segmented into paragraphs. Transcript conversion entailed extracting data from the PDF, eliminating technical elements, and ensuring continuity of utterances. Speaker names and functionswere identified, and the sessionwas transformed into ParlaMint-compliant TEI XML format. Meta-comments, including applause, laughter, and interruptions, were categorized based on typical phrases. Quotations, marked with indentation in the original transcript, were manually encoded as TEI elements. Foreign-language fragments were treated as gaps, with English translations provided. Multiparagraph foreign utterances were encoded paragraph by paragraph. Speaker metadata was stored in separate XML files, listing organizations and individual speakers. Speaker names and roles were converted into XML IDs, and web pages were linked for additional information. Speaker type was designated based on metadata, distinguishing between chairs, guests, and regular speakers. The encoded session comprised 95 utterances, with varying distributions among speakers. The proposed conversion process serves as a starting point for the larger endeavour of encoding South African parliamentary data in the ParlaMint schema. While not exhaustive, this study lays the groundwork for expanding the ParlaMint dataset to include African parliamentary records. [ABSTRACT FROM AUTHOR]

Conservation agriculture (CA) is a set of principles thought to be able to enhance crop productivity while minimizing impacts on the environment. The evidence base for CA can be challenging to synthesize because it encompasses many different practices and social and agroecological outcomes. To facilitate synthesis of CA evidence we have created a dataset organizing 218 response variables from five common categories of CA: cover crops, tillage management, pest management, nutrient management, and crop diversification. These data cover the Midwestern United States (U.S.) from 1980–2020. The dataset is also summarized and visualized on the AgEvidence website, which enables users to interactively explore, filter, and download data. We hope this dataset will help a wide variety of stakeholders, including researchers, policy makers, advocacy groups, and growers access the evidence needed to make informed and impactful decisions about how to produce food with less negative environmental impact. [ABSTRACT FROM AUTHOR]

Scientific data are essential to advancing scientific knowledge and are increasingly valued as scholarly output. Understanding what drives dataset downloads is crucial for their effective dissemination and reuse. Our study, analysing 55,473 datasets from 69 data repositories, identifies key factors driving dataset downloads, focusing on interpretability, reliability, and accessibility. We find that while lengthy descriptive texts can deter users due to complexity and time requirements, readability boosts a dataset's appeal. Reliability, evidenced by factors like institutional reputation and citation counts of related papers, also significantly increases a dataset's attractiveness and usage. Additionally, our research shows that open access to datasets increases their downloads and amplifies the importance of interpretability and reliability. This indicates that easy access enhances the overall attractiveness and usage of datasets in the scholarly community. By emphasizing interpretability, reliability, and accessibility, this study offers a comprehensive framework for future research and guides data management practices toward ensuring clarity, credibility, and open access to maximize the impact of scientific datasets. [ABSTRACT FROM AUTHOR]

This paper presents the Archaeological Artefact Database of Finland (AADA) of prehistoric (covering period of almost 11,000 years) artefacts in Finland that are categorised by type and are accompanied with photos of the artefacts. The database is intended to contain all typologically classifiable prehistoric artefacts found in Finland and held in Finnish collections. This dataset provides spatio-temporal context for artefacts across different time periods and regions, as it includes approximately 38,000 single artefacts and approximately 10,000 pottery type identifications from the Early Mesolithic to the end of the Iron Age in Finland (c. 8900 calBC - 1300/1500 calAD). In addition, the artefacts are given period-based (subperiod) dating to allow their chronological affiliation. To facilitate data usage, we also offer an R-script to replicate the data visualisation provided in this paper and a Python script to merge the artefact information to the pictures. We further work towards an interactive user interface for data download and visualization. [ABSTRACT FROM AUTHOR]

Vehicular caching (VC) in electro‐mobility networks has become promising for supporting the needs of low end‐to‐end service delays and reducing the load of networks (i.e. edge caching [EC]) for content delivery service. However, since VCs are available only when they are in the vicinity of the user, intermittent connectivity should be considered. In this paper, the opportunistic offloading scheme for content delivery service is proposed, and a decision is made regarding whether to use VC or EC for the content delivery service. In the proposed scheme, when VC is not available, the user determines whether to choose VC or EC for the content download. If VC is chosen, the user delays the content download to increase the VC utilization according to the expectation of VC contacts. This results in the delayed service completion but can reduce the EC load (i.e. offloading gain). If EC is chosen, the user can download the content without any delay or service interruption. To find the optimal policy, this paper formulates a Markov decision process (MDP) problem and uses the value iteration algorithm to solve the problem. The evaluation results show that the proposed scheme outperforms the comparison schemes based on the expected reward. [ABSTRACT FROM AUTHOR]

In an age of burgeoning open data sources, ranging from authoritative platforms to crowd-sourced contributions, the need for data integration is paramount - only with integrated, combined, data can today's complex problems be addressed. However, assessing the quality of data and its potential for integration/interoperability is complex. FAIR (findable, accessible, interoperable and re-useable) approaches go some way to help, but most repositories still only offer text-based search results and require the user to download the data and assess its quality and fitness-for-purpose manually. This paper examines whether exploiting geospatial approaches - specifically, understanding whether a dataset can be mapped and hence integrated with other datasets - could address these issues, in particular for non-expert users. We explore challenges related to open data for education and environmental sustainability and introduce a novel, visual map-ability rating to assist data users in rapidly understanding the data quality and interoperability potential of data they wish to use. This rating system has been developed by researchers from outside the location science domain, to better reflect what is important to the wider community, and derives from a review of 104 open datasets. As well as providing useful insight to data users, the ratings can be used to guide data publishers as to how to improve their data offering. [ABSTRACT FROM AUTHOR]

Interval timing refers to the ability to perceive and remember intervals in the seconds to minutes range. Our contemporary understanding of interval timing is derived from relatively small-scale, isolated studies that investigate a limited range of intervals with a small sample size, usually based on a single task. Consequently, the conclusions drawn from individual studies are not readily generalizable to other tasks, conditions, and task parameters. The current paper presents a live database that presents raw data from interval timing studies (currently composed of 68 datasets from eight different tasks incorporating various interval and temporal order judgments) with an online graphical user interface to easily select, compile, and download the data organized in a standard format. The Timing Database aims to promote and cultivate key and novel analyses of our timing ability by making published and future datasets accessible as open-source resources for the entire research community. In the current paper, we showcase the use of the database by testing various core ideas based on data compiled across studies (i.e., temporal accuracy, scalar property, location of the point of subjective equality, malleability of timing precision). The Timing Database will serve as the repository for interval timing studies through the submission of new datasets. [ABSTRACT FROM AUTHOR]

To explore complex biological questions, it is often necessary to access various data types from public data repositories. As the volume and complexity of biological sequence data grow, public repositories face significant challenges in ensuring that the data is easily discoverable and usable by the biological research community. To address these challenges, the National Center for Biotechnology Information (NCBI) has created NCBI Datasets. This resource provides straightforward, comprehensive, and scalable access to biological sequences, annotations, and metadata for a wide range of taxa. Following the FAIR (Findable, Accessible, Interoperable, and Reusable) data management principles, NCBI Datasets offers user-friendly web interfaces, command-line tools, and documented APIs, empowering researchers to access NCBI data seamlessly. The data is delivered as packages of sequences and metadata, thus facilitating improved data retrieval, sharing, and usability in research. Moreover, this data delivery method fosters effective data attribution and promotes its further reuse. This paper outlines the current scope of data accessible through NCBI Datasets and explains various options for exploring and downloading the data. [ABSTRACT FROM AUTHOR]

Motivation In recent years, the focus of bioinformatics research has moved from individual sequences to collections of sequences. Given the fundamental role of the Burrows–Wheeler transform (BWT) in string processing, a number of dedicated tools have been developed for computing the BWT of string collections. While the focus has been on improving efficiency, both in space and time, the exact definition of the BWT used has not been at the center of attention. As we show in this paper, the different tools in use often compute non-equivalent BWT variants: the resulting transforms can differ from each other significantly, including the number r of runs, a central parameter of the BWT. Moreover, with many tools, the transform depends on the input order of the collection. In other words, on the same dataset, the same tool may output different transforms if the dataset is given in a different order. Results We studied 18 dedicated tools for computing the BWT of string collections and were able to identify 6 different BWT variants computed by these tools. We review the differences between these BWT variants, both from a theoretical and from a practical point of view, comparing them on eight real-life biological datasets with different characteristics. We find that the differences can be extensive, depending on the datasets, and are largest on collections of many similar short sequences. The parameter r , the number of runs of the BWT, also shows notable variation between the different BWT variants; on our datasets, it varied by a multiplicative factor of up to 4.2. Availability and implementation Source code and scripts to replicate the results and download the data used in the article are available at https://github.com/davidecenzato/BWT-variants-for-string-collections. [ABSTRACT FROM AUTHOR]

This paper aims to solve the problems in the data download and analysis process of CIR equipment (Cab Integrated Radio) in the railway industry. In response to the current challenges of long data download time and difficult manual analysis, etc., a design scheme for wireless data transmission and intelligent analysis system for CIR equipment is proposed. The current CIR equipment still relies on manual operations for downloading and analyzing data from recording units, which poses potential risks to railway transportation safety due to time lag and low efficiency. The system architecture designed in this article is divided into two parts: onboard acquisition equipment and trackside intelligent analysis system, which are connected through the existing LMD system for communication. The onboard data acquisition equipment is connected to the monitoring interface of the recording unit of locomotive CIR equipment through a dedicated cable, and the data is transmitted to the trackside server through wireless network. The trackside intelligent analysis system realizes functions such as data storage, intelligent analysis, and report statistics. Based on big data technology and distributed architecture, it improves the efficiency of data processing and analysis. The intelligent analysis module in the system can achieve functions such as remote monitoring of device status, intelligent analysis, intelligent evaluation of device usage, and standardized detection task evaluation. After on-site application verification, the system can shorten data download and analysis time, reduce labor costs, prevent CIR equipment failures in advance, and ensure railway transportation safety and efficiency. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the re-use of research data deposited in digital data archive in the social sciences. The study examines the quantity, type, and purpose of data downloads by analyzing enriched user log data collected from Swiss data archive. The findings show that quantitative datasets are downloaded increasingly from the digital archive and that downloads focus heavily on a small share of the datasets. The most frequently downloaded datasets are survey datasets collected by research organizations offering possibilities for longitudinal studies. Users typically download only one dataset, but a group of heavy downloaders form a remarkable share of all downloads. The main user group downloading data from the archive are students who use the data in their studies. Furthermore, datasets downloaded for research purposes often, but not always, serve to be used in scholarly publications. Enriched log data from data archives offer an interesting macro level perspective on the use and users of the services and help understanding the increasing role of repositories in the social sciences. The study provides insights into the potential of collecting and using log data for studying and evaluating data archive use. [ABSTRACT FROM AUTHOR]

Background: In 1986, CSIRO conducted a large program of experimental fires in grassland at Annaburroo Station, Northern Territory, Australia, with the objective of quantifying the effect of fuel condition (load and height) on fire behaviour. Aims: This paper provides the data collected during this program, representing a unique set of observations and measurements of large, free-burning experimental fires conducted in a multi-factor experimental design. Methods: Data are collated by experimental burn plot, providing detailed measurements of weather (wind speed, air temperature, relative humidity), fuel state (load, height, moisture content, curing) and fire behaviour (rate of spread, flame depth, flame height, head fire width), as well as processed information (e.g. steady-state rate of spread). Data availability: The data are made available for free download on the CSIRO Data Access Portal () and include detailed metadata descriptions of the data and their structure, also provided in this article. Conclusions: We have made the data available for fire behaviour researchers around the world to use in their research under the Creative Commons Attributions licence. It is hoped they will analyse these data and extract new and innovative insights to help improve our understanding of wildland fires burning in grass fuels. The 1986 Annaburroo grassland fire experiments conducted in the Northern Territory, Australia, created a unique dataset of fire behaviour across a range of fuel and burning conditions. This dataset, comprising detailed observations of fuels, weather and fire behaviour in 121 plots, is now publicly available via the CSIRO Data Access Portal. [ABSTRACT FROM AUTHOR]

In most wireless networks, users/peers are connected to backbone networks using access links. The access link capacity is divided into upload and download capacity, and these capacities are used for upload and download of data, respectively. A peer can modify this division of link capacity between upload and download. A peer will allocate its entire link capacity for download to maximize utility. But incentive mechanism forces them to allocate some portion of capacity for upload. This paper investigates how to optimally divide link capacity so that peers receive maximum utility in a P2P network. We model this scenario as a game and determine capacity partitioning of peers during the Nash equilibrium NE. We also prove the social optimality of NE. As this portioning maximizes individual as well as social benefit, so NE is an optimal state of capacity partition. Using simulation, we verify that NE is an optimal state. BitTorrent network and a distributed algorithm for dividing access capacities are simulated, and partition providing maximum utility is compared with NE. This work provides a generalized expression and the mathematical proof for capacity partitioning at which peers receive maximum utility. [ABSTRACT FROM AUTHOR]

This paper focuses on significant data analysis for middle atmospheric variations of height of 0 km 100 km. This data was downloaded from the SABER satellite NASA and analyzed with the help of MATLAB. The analysis includes the determination of propagation of wavelengths and oscillations for the semi-annual oscillation (SAO), Annual oscillations (AO), quasi-annual oscillations (QBO), EINIO southern oscillation (ENSO) from the period of Jan 2002 to Dec 2022 past twenty years data. The monthly mean Temperatures, monthly ozone deviations, and overall mean temperatures with standard deviations are estimated for the following altitude regions concerning troposphere (0-20km), stratospheric (21-50 km), mesospheric (51-90 km), and thermospheric regions (91-105 km). However, the results proved that the maximum temperature variations would affect the ozone depletion for the areas concerning the altitude height of 15-40 km region between troposphere and stratospheric in the temperature range of 260K, and average deviations are found in the order of 0.000010 µm for the troposphere region. The presence of harmful gases such as CO, CO2, NOx, H, and CH4 released from the automobile and powerplant industry may deplete the ozone layer and cause adverse effects. [ABSTRACT FROM AUTHOR]

Study aim(s): Football, which occupies a significant place in the sports industry, has become not only an important branch of sport but also a means of entertainment, enjoyment, and communication for people. Football likely has the highest number of fans among all sports. Therefore, the phenomenon of the fan as a sports consumer has become the subject of numerous scientific studies. For these reasons, this study is a bibliometric analysis of articles about football fans. Methods: For the study, the term "football fans" was entered into the Scopus database, and the data was downloaded on May 17, 2024. This data was analyzed using the R programme. Based on basic information in the relevant literature, the research examined the number of publications, the most frequently used keywords, the countries with the most contributions, the most important journals, and the most productive institutions. The study's data covers the period from 1973 to 2024. Results: The study found that 4201 authors have published papers on the topic of football fans. Among these, 707 studies have a single author. The average annual number of citations per article is around 13. The main keywords used in studies in this area are "football", "human", "male," and "sport". The country contributing the most to the literature is the United Kingdom. Conclusion: This study's findings are of interest to researchers and practitioners interested in football fan engagement, stakeholders in the sports industry, and those working in the field. [ABSTRACT FROM AUTHOR]

The significance of Linked Open Data datasets for traffic information extends beyond just including open traffic data. It incorporates links to other relevant thematic datasets available on the web. This enables federated queries across different data platforms from various countries and sectors, such as transport, geospatial, environmental, weather, and more. Businesses, researchers, national operators, administrators, and citizens at large can benefit from having dynamic traffic open data connected to heterogeneous datasets across Member States. This paper focuses on the development of a semantic model that enhances the basic service to access open traffic data through a LOD-enhanced Traffic Information System in alignment with the ITS Directive (2010/40/EU). The objective is not limited to just viewing or downloading data but also to improve the extraction of meaningful information and enable other types of services that are only achievable through LOD. By structuring the information using the RDF format meant for machines and employing SPARQL for querying, LOD allows for comprehensive and unified access to all datasets. Considering that the European standard DATEX II is widely used in many priority areas and services mentioned in the ITS Directive, LOD DATEX II was developed as a complementary approach to DATEX II XML. This facilitates the accessibility and comprehensibility of European traffic data and services. As part of this development, an ontological model called dtx_srti, based on the DATEX II Ontology, was created to support these efforts. [ABSTRACT FROM AUTHOR]

Optical satellite networks (OSNs) play an important role in space applications since it has some merits such as high data rate and low power. Increasing space applications generate a large amount of data on satellite so that satellites have difficulty in downloading these data to ground station timely under the limited contact window. Thus, we investigate the problem of collaborative data downloading in this paper. The problem lies on how to energy-efficiently offload data by optical inter-satellite links (ISLs) to balance data load and downlink capacity of each satellite so as to improve the performance of data downloading in OSN. Firstly, we develop the Cost Time-evolving Graph (CTEG) to describe optical transmission cost and the time-varying topology of OSN. Secondly, the problem of collaborative data downloading is formulated as Multi-objective Mixed-integer Linear Programming (MOMILP) which is proven to be NP-hard. For reducing computational complexity, we divide the scheduling time into multiple stages and propose the Multi-stage Collaborative Scheduling Algorithm (MCSA) which operates on a slot-by-slot basis. Simulations are conducted in the joint platform and results demonstrate that, compared with CoDld and No-ISLs, the MCSA provides a relatively high data throughput meanwhile drastically reducing energy consumption generated by data offloading. [ABSTRACT FROM AUTHOR]

This paper introduces a single-cell atlas for pivotal developmental stages in Xenopus , encompassing gastrulation, neurulation, and early tailbud. Notably surpassing its predecessors, the new atlas enhances gene mapping, read counts, and gene/cell type nomenclature. Leveraging the latest Xenopus tropic alis genome version, alongside advanced alignment pipelines and machine learning for cell type assignment, this release maintains consistency with previous cell type annotations while rectifying nomenclature issues. Employing an unbiased approach for cell type assignment proves especially apt for embryonic contexts, given the considerable number of non-terminally differentiated cell types. An alternative cell type attribution here adopts a fuzzy, non-deterministic stance, capturing the transient nature of early embryo progenitor cells by presenting an ensemble of types in superposition. The value of the new resource is emphasized through numerous examples, with a focus on previously unexplored germ cell populations where we uncover novel transcription onset features. Offering interactive exploration via a user-friendly web portal and facilitating complete data downloads, this atlas serves as a comprehensive and accessible reference. [Display omitted] [ABSTRACT FROM AUTHOR]

Objectives: Acute ischemic stroke (AIS) is caused by cerebral ischemia due to thrombosis in the blood vessel. The purpose of this study is to identify key genes related to metabolism to aid in the mechanism research and management of AIS. Materials and Methods: Gene expression data were downloaded from the Gene Expression Omnibus database. Weighted gene co‐expression network analysis, Gene Ontology and kyoto encyclopedia of genes and genomes analysis were used to identify metabolism‐related genes that may be involved in the regulation of AIS. A protein protein interaction network was mapped using Cytoscape based on the STRING database. Subsequently, hub metabolism‐related genes were identified based on Cytoscape‐CytoNCA and Cytoscape‐MCODE plug‐ins. Least absolute shrinkage and selection operator algorithm and differential expression analysis. In addition, drug prediction, molecular docking, ceRNA network construction, and correlation analysis with immune cell infiltration were performed to explore their potential molecular mechanisms of action in AIS. Finally, the expression of hub gene was verified by real‐time PCR. Results: Metabolism‐related genes FBL, HEATR1, HSPA8, MTMR4, NDUFC1, NDUFS8 and SNU13 were identified. The AUC values of FBL, HEATR1, HSPA8, MTMR4, NDUFS8 and SNU13 were all greater than 0.8, suggesting that they had good diagnostic accuracy. Correlation analysis found that their expression levels were also related to the infiltration levels of multiple immune cells, such as Activated.CD8.T.cell and Activated.dendritic.cell. It was found that only HSPA8 was successfully matched to drugs with literature support, and these drugs were acetaminophen, bupivacaine, dexamethasone, gentamicin, tretinoin and cisplatin. Moreover, it was also identified that the ENSG000000218510‐hsa‐miR‐330‐3p‐HEATR1 axis may be involved in regulating AIS. Conclusions: The identification of FBL, HEATR1, HSPA8, MTMR4, NDUFC1, NDUFS8 and SNU13 provides a new research direction for exploring the molecular mechanisms of AIS, which can help in clinical management and diagnosis. [ABSTRACT FROM AUTHOR]

Motivation Analysis of time series transcriptomics data from clinical trials is challenging. Such studies usually profile very few time points from several individuals with varying response patterns and dynamics. Current methods for these datasets are mainly based on linear, global orderings using visit times which do not account for the varying response rates and subgroups within a patient cohort. Results We developed a new method that utilizes multi-commodity flow algorithms for trajectory inference in large scale clinical studies. Recovered trajectories satisfy individual-based timing restrictions while integrating data from multiple patients. Testing the method on multiple drug datasets demonstrated an improved performance compared to prior approaches suggested for this task, while identifying novel disease subtypes that correspond to heterogeneous patient response patterns. Availability and implementation The source code and instructions to download the data have been deposited on GitHub at https://github.com/euxhenh/Truffle. [ABSTRACT FROM AUTHOR]

Purpose: Gender and geographical imbalance in production and impact levels is a pressing issue in global knowledge production. Within Health Sciences, while some studies found stark gender and geographical biases and inequalities, others found little empirical evidence of this marginalization. The purpose of the study is to clear the ambiguity concerning the topic. Design/methodology/approach: Based on a comprehensive and systematic analysis of Health Sciences research data downloaded from the Scival (Scopus/Scimago) database from 2017 to 2020 (n = 7,990), this study first compares gender representation in research productivity, as well as differences in terms of citation per document, citations per document view and view per document scores according to geographical location. Additionally, the study clarifies whether there is a geographic bias in productivity and impact measures (i.e. citation per document, citations per document view and view per document) moderated by gender. Findings: Results indicate that gender inequalities in productivity are systematic at the overall disciplinary, as well as the subfield levels. Findings also suggest statistically significant geographical differences in citation per document, citations per document view, and view per document scores, and interaction effect of gender over the relation between geography and (1) the number of citations per view and (2) the number of views per document. Originality/value: This study contributes to scientometric studies in health sciences by providing insightful findings about the geographical and gender bias in productivity and impact across world regions. [ABSTRACT FROM AUTHOR]

The assessment of performance is the key role factor for the gearboxes in the field of wind turbine industry. The thermal performance depends upon the viscous forces of the oil; bearing with stand capacity of the gearboxes and unnecessary irrotational forces or movements caused during the rotation of the gears at intermediate stage and high speed stage. The generation of the power starts from 15 m/s to 25 m/s with the starting rpm of 15 rpm to 1150 rpm; from initial stage to high speed stage of the gearbox. Hence the reduction of torque at higher revolutions may tends to complete reduction in power; owing to the thermal performance drop occurred due to the reduction of oil viscosities; improper maintenance during the high load conditions. This may lead to cause higher maintenance costs for the investors who is coming in front to invest huge amount of money. This present experimental work deals with latest sensors utilization to analyse the data from master gear box to slave gear box. From the results it is observed that the implementation of latest technology sensors tends to improves the maintanence costs by 20% as compared to conventional sensors. Hence it is adviced to implement the latest technology sensors which is capable to measure the wind speed loads of 20 m/s to 45 m/s. This gives range of resolution for downloading the past data and predicting the futurized data for evaluating the thermal performance drop; leads to save the maintanence costs 20% as compared to conventional methods. [ABSTRACT FROM AUTHOR]

Prioritization or ranking of different cell types in a Single-cell RNA Sequencing (scRNA-Seq) framework can be performed in a variety of ways, some of these include: i) obtaining an indication of the proportion of cell types between the different conditions under study, ii) counting the number of differentially expressed genes (DEGs) between cell types and conditions in the experiment or, iii) prioritizing cell types based on prior knowledge about the conditions under study (i.e., a specific disease). These methods have drawbacks and limitations thus novel methods for improving cell ranking are required. Here we present a novel methodology that exploits prior knowledge in combination with expert-user information to accentuate cell types from a scRNA-seq analysis that yield the most biologically meaningful results with respect to a disease under study. Our methodology allows for ranking and prioritization of cell-types based on how well their expression profiles relate to the molecular mechanisms and drugs associated with a disease. Molecular mechanisms, as well as drugs, are incorporated as prior knowledge in a standardized, structured manner. Cell-types are then ranked/prioritized based on how well results from data-driven analysis of scRNA-seq data match the predefined prior knowledge. In additional cell-cell communication perturbations between disease and control networks are used to further prioritize/rank cell-types. Our methodology has substantial advantages to more traditional cell ranking techniques and provides an informative complementary methodology that utilizes prior knowledge in a rapid and automated manner, that has previously not been attempted by other studies. The current methodology is also implemented as an R package entitled Single Cell Ranking Analysis Toolkit (scRANK) and is available for download and installation via GitHub (https://#hub.com/aoulas/scRANK) Author summary: Single-cell RNA Sequencing (scRNA-Seq) provides an additive resolution down to the cellular level that was previously not available from traditional "Bulk" RNA sequencing experiments. However, it is often difficult to prioritize the specific cell-types which are primarily responsible for the cause of a disease. This work presents a novel methodology that utilizes predefined prior knowledge information to highlight informative cell types from a scRNA-seq analysis. Our methodology allows for ranking and prioritization of cell-types based on how well predefined prior knowledge, in the form of pathways and drugs, are mapped to the results obtained from a basic analysis of a scRNA-Seq dataset. Prior knowledge is incorporated in a standardized, structured manner, whereby a checklist is attained by querying the human disease database called MalaCards. This checklist comes in the form of pathways and drugs associated with the disease. The expert-user is prompted to "edit" the prior knowledge checklist by removing or adding terms from the list of predefined terms. Our methodology also utilizes cell-cell communication perturbations between disease and control networks to further prioritize/rank cell-types. We believe, this methodology may offer substantial advantages to existing cell prioritizing or ranking techniques and provide a rapid and automated approach that further compliments other methods of cell prioritization in a scRNA-Seq framework. [ABSTRACT FROM AUTHOR]

Background: Changes in the gut microbiota are closely related to insomnia, but the causal relationship between them is not yet clear. Objective: To clarify the relationship between the gut microbiota and insomnia and provide genetic evidence for them, we conducted a two-sample Mendelian randomization study. Methods: We used a Mendelian randomized two-way validation method to discuss the causal relationship. First, we downloaded the data of 462,341 participants relating to insomnia, and the data of 18,340 participants relating to the gut microbiota from a genome-wide association study (GWAS). Then, we used two regression models, inverse-variance weighted (IVW) and MR-Egger regression, to evaluate the relationship between exposure factors and outcomes. Finally, we took a reverse MR analysis to assess the possibility of reverse causality. Results: The combined results show 19 gut microbiotas to have a causal relationship with insomnia (odds ratio (OR): 1.03; 95% confidence interval (CI): 1.01, 1.05; p=0.000 for class. Negativicutes; OR: 1.03; 95% CI: 1.01, 1.05; p=0.000 for order.Selenomonadales; OR: 1.01; 95% CI: 1.00, 1.02; p=0.003 for genus. Rikenellaceae RC9 gutgroup). The results were consistent with sensitivity analyses for these bacterial traits. In reverse MR analysis, we found no statistical difference between insomnia and these gut microbiotas. Conclusion: This study can provide a new direction for the causal relationship between the gut microbiota (class.Negativicutes, order. Selenomonadales, genus.Lactococcus) and insomnia and the treatment or prevention strategies of insomnia. [ABSTRACT FROM AUTHOR]

We introduce the problem of deceptive information retrieval (DIR), in which a user wishes to download a required file out of multiple independent files stored in a system of databases while deceiving the databases by making the databases' predictions on the user-required file index incorrect with high probability. Conceptually, DIR is an extension of private information retrieval (PIR). In PIR, a user downloads a required file without revealing its index to any of the databases. The metric of deception is defined as the probability of error of databases' prediction on the user-required file, minus the corresponding probability of error in PIR. The problem is defined on time-sensitive data that keep updating from time to time. In the proposed scheme, the user deceives the databases by sending real queries to download the required file at the time of the requirement and dummy queries at multiple distinct future time instances to manipulate the probabilities of sending each query for each file requirement, using which the databases' make the predictions on the user-required file index. The proposed DIR scheme is based on a capacity achieving probabilistic PIR scheme, and achieves rates lower than the PIR capacity due to the additional downloads made to deceive the databases. When the required level of deception is zero, the proposed scheme achieves the PIR capacity. [ABSTRACT FROM AUTHOR]

The aim of the present study is to assess the impact of structural capital intensity and utilization on firm profitability in an international setting: the European Union countries, plus Norway, Switzerland and the United Kingdom. The indicators are calculated based on financial data downloaded from the Refinitiv Eikon database. Two financial ratios are used as proxies for the intensity and utilization of structural capital. The balanced panel consists of 625 companies from 25 countries, over the period from 2013 to 2022. The panel includes financial information on two industries that are considered innovation-oriented, namely technology and healthcare. Alternative model specifications are proposed to test the robustness of the basic model, including dynamic models (with lagged dependent variables). The present study indicates that a higher proportion of structural capital (intangible assets, excluding goodwill) is a negative factor for company profitability in the technology and healthcare sectors. There is no indication that a more intense use of intangible assets and more investments in R&D positively contribute to company profitability in the respective industries, for a large sample of listed companies. A higher proportion of intangible assets, as reported in financial statements, is possibly related to inefficiencies in the management of structural capital. The inverse relationship between profitability and investments in intangible assets is likely due to failures in cost accounting. Limitations and future research propositions are provided in the conclusions. [ABSTRACT FROM AUTHOR]

Introduction: Portable oxygen concentrators (POCs) are medical devices that provide supplemental oxygen to patients requiring long-term oxygen therapy. However, little information is available on day-to-day patterns of how or even whether patients actively switch between their POC mobility features and flow setting options. Methods: A retrospective analysis was conducted to assess POC usage among patients who used an Inogen One G5 POC in the USA. This study aimed (1) to describe the patterns of use of POCs, (2) to analyze their compatibility with the prescribed oxygen therapy settings, and (3) to demonstrate the contribution of POC usage to get a standardized long-term oxygen therapy (LTOT). Data were directly downloaded from the devices returned for service or at the end of the Medicare Durable Medical Equipment rental period and streamed via a mobile application from 2018 to 2022. Daily usage, disconnections from the device, use of prescribed pulse delivery settings, breaths per minute, power sources, and movement with the POC were assessed. Device alert histories were also examined. Results: Data revealed a mean daily usage of 4.29 ± 3.23 h/day, ranging from 0.35 to 15.52 h/day. The prescribed pulse delivery setting was used by 31.34% of patients for at least 80% of their POC use time. When the POC was on battery power, patients were moving/mobile 41.99 ± 33.33% of the time. On the basis of the device-generated alerts, some patients continued to use their POC very close to or even beyond the lifetime of the column/sieve bed. Alerts or alarms potentially requiring repair occurred at a rate of 1.63 events per 100 years of use, indicating that device reliability did not significantly influence the use patterns. Conclusion: Patients used their POCs when mobile and at rest. A large proportion of patients adjust their POC settings during the day, which potentially indicates the need for the dynamic individualization of oxygen dose delivery to match activities of daily living or sleep. Patients require follow-up to ensure timely replacement of POC columns. Plain Language Summary: This study aimed to (1) describe the patterns of use of portable oxygen concentrators (POCs), (2) analyze their compatibility with the prescribed oxygen therapy settings, and (3) demonstrate the contribution of POC usage to get a standardized long-term oxygen therapy (LTOT). A retrospective analysis was conducted on data downloaded directly from devices and streamed via a mobile application. Daily usage, disconnections from the device, use of prescribed pulse delivery settings, breaths per minute, power sources, and movement with the device were assessed. Device alert histories were also examined. Patients used their portable oxygen concentrators when mobile and at rest, and large proportion of patients adjust their settings during the day. There was a low incidence of alarms or alerts requiring repairs, indicating device reliability. Patients require follow-up to ensure timely replacement of columns. [ABSTRACT FROM AUTHOR]

A custom lightweight, miniaturized, and trackable meteorological probe was launched by a model rocket into the inflow region of an EF4, long-tracked tornado south of Lawrence, Kansas, on 28 May 2019 and sampled tornado core flow. The rocket reached apogee at 439 m a.g.l., releasing the "pseudo-Lagrangian drifter" by parachute directly into the tornado vortex. The probe reached a three-dimensional (3D) speed of 85.1 m s -1 in the first revolution around the tornado, measured an altitude-corrected pressure deficit of - 113.5 hPa at 475 m a.s.l., and sampled a tornadic updraft speed of 65.0 m s -1. The probe then transitioned to an environment exhibiting a more tilted ascent above an altitude of 4300 m a.s.l. at speeds up to 84.0 m s -1 to a maximum altitude of 11 914 m a.s.l. 1 Hz pressure, temperature, relative humidity, GPS, acceleration, gyroscope, and magnetometer data for the flight were transmitted in real time to a ground station until 10 680 m a.s.l. and the probe landed 51 km northeast of the launch position. The probe was recovered without damage, which is attributed to the pseudo-Lagrangian drifter design, and then higher-resolution and complete 10 Hz data were downloaded for the flight. This novel deployment method and design facilitate data collection in real time from within tornadoes, the mesocyclone, and downdraft without requiring the probes to be recovered or for researchers to enter the circulation to deploy equipment. [ABSTRACT FROM AUTHOR]

A geospatial data processing tool, GEO4PALM, has been developed to generate geospatial static input for the Parallelized Large-Eddy Simulation (PALM) model system. PALM is a community-driven large-eddy simulation model for atmospheric and environmental research. Throughout PALM's 20-year development, research interests have been increasing in its application to realistic conditions, especially for urban areas. For such applications, geospatial static input is essential. Although abundant geospatial data are accessible worldwide, geospatial data availability and quality are highly variable and inconsistent. Currently, the geospatial static input generation tools in the PALM community heavily rely on users for data acquisition and pre-processing. New PALM users face large obstacles, including significant time commitments, to gain the knowledge needed to be able to pre-process geospatial data for PALM. Expertise beyond atmospheric and environmental research is frequently needed to understand the data sets required by PALM. Here, we present GEO4PALM, which is a free and open-source tool. GEO4PALM helps users generate PALM static input files with a simple, homogenised, and standardised process. GEO4PALM is compatible with geospatial data obtained from any source, provided that the data sets comply with standard geo-information formats. Users can either provide existing geospatial data sets or use the embedded data interfaces to download geo-information data from free online sources for any global geographic area of interest. All online data sets incorporated in GEO4PALM are globally available, with several data sets having the finest resolution of 1 m. In addition, GEO4PALM provides a graphical user interface (GUI) for PALM domain configuration and visualisation. Two application examples demonstrate successful PALM simulations driven by geospatial input generated by GEO4PALM using different geospatial data sources for Berlin, Germany, and Ōtautahi / Christchurch, New Zealand. GEO4PALM provides an easy and efficient way for PALM users to configure and conduct PALM simulations for applications and investigations such as urban heat island effects, air pollution dispersion, renewable energy resourcing, and weather-related hazard forecasting. The wide applicability of GEO4PALM makes PALM more accessible to a wider user base in the scientific community. [ABSTRACT FROM AUTHOR]

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