Data Sharing Research Articles

ExMove: An open-source toolkit for processing and exploring animal-tracking data in R.

Ongoing technological advances have led to a rapid increase in the number, type and scope of animal-tracking studies. In response, many software tools have been developed to analyse animal movement data. These tools generally focus on movement modelling, but the steps required to clean raw data files from different tracking devices have been largely ignored. Such pre-processing steps are often time-consuming and involve a steep learning curve but are crucial for the creation of high-quality, standardised and shareable data. Moreover, decisions made at this early stage can substantially influence subsequent analyses, and in the current age of reproducibility crisis, the transparency of this process is vital. Here we present an open-access, reproducible toolkit written in the programming language R for processing raw data files into a single cleaned data set for analyses and upload to online tracking databases (found here: https://github.com/ExMove/ExMove). The toolkit comprises well-documented and flexible code to facilitate data processing and user understanding, both of which can increase user confidence and improve the uptake of sharing open and reproducible code. Additionally, we provide an overview website (found here: https://exmove.github.io/) and a Shiny app to help users visualise tracking data and assist with parameter determination during data cleaning. The toolkit is generalisable to different data formats and device types, uses modern 'tidy coding' practices, and relies on a few well-maintained packages. Among these, we perform spatial manipulations using the package sf. Overall, by collating all required steps from data collection to archiving on open access databases into a single, robust pipeline, our toolkit provides a valuable resource for anyone conducting animal movement analyses and represents an important step towards increased standardisation and reproducibility in animal movement ecology.

Trend Analysis of Enterprise Intelligent Financial Applications

Recently, intelligent financial applications have been regarded as an important pillar of enterprise development and will play a significant contribution to the progress of future enterprises. Enterprises need to make continuous progress and adapt to the rapidly changing social environment with high competitiveness, and finance, as an indispensable part of enterprise development, needs to make great progress. With the continuous development of digital transformation, intelligent finance has become an important driving force for enterprise development, and is widely used in information processing, personnel management, market analysis, business management, etc. The purpose of this paper is to explore the sustainable impact of intelligent finance on enterprise development, including the application of financial intelligence, financial shared development, data analysis and management, etc., and comprehensively sort, analyze and summarize the relevant research through the method of literature review. In addition, it provides reasonable suggestions for the future development direction of enterprise finance, so that enterprises can gain competitive advantages from intelligent financial applications, improve company efficiency, and achieve good and long-term development.

Trend Analysis of Enterprise Intelligent Financial Applications

Recently, intelligent financial applications have been regarded as an important pillar of enterprise development and will play a significant contribution to the progress of future enterprises. Enterprises need to make continuous progress and adapt to the rapidly changing social environment with high competitiveness, and finance, as an indispensable part of enterprise development, needs to make great progress. With the continuous development of digital transformation, intelligent finance has become an important driving force for enterprise development, and is widely used in information processing, personnel management, market analysis, business management, etc. The purpose of this paper is to explore the sustainable impact of intelligent finance on enterprise development, including the application of financial intelligence, financial shared development, data analysis and management, etc., and comprehensively sort, analyze and summarize the relevant research through the method of literature review. In addition, it provides reasonable suggestions for the future development direction of enterprise finance, so that enterprises can gain competitive advantages from intelligent financial applications, improve company efficiency, and achieve good and long-term development.

VSFL: Trajectory prediction framework based on validity-aware semi-asynchronous federated learning in internet of vehicles

Accurate prediction of vehicle trajectories on the Internet of Vehicles is crucial for improving traffic safety. Federated learning has been proposed to address the issue of islands in shared data. Traditional synchronous federated learning requires waiting for each node to complete training before model aggregation can occur, and the aggregation algorithm of the server cannot adjust the aggregation weight in real-time, which leads to increased communication overhead, time cost, and decreased accuracy. To balance these issues, this paper proposes a Validity-aware Semi-asynchronous Federated Learning-based framework for predicting vehicle trajectories. The framework makes the following improvements - firstly, based on the asynchronous cooperation algorithm of generalization research, the models of vehicle nodes within the same RoadSide Unit (RSU) range are aggregated into this RSU to reduce communication overhead and time costs. To further ensure the privacy and security of all participants, we added differential privacy algorithms during the model training process. Secondly, the server uses a weighted aggregation algorithm based on effective perception to aggregate all RSU models into a global model to address potential accuracy issues. This article uses a Social-LSTM like model to validate the effectiveness of this framework in the Next Generation Simulation (NGSIM) Vehicle Trajectories and Support Data dataset. Compared with traditional federated averaging algorithms and trust aware federated learning algorithms, this framework reduces distance errors by 27.80 % and 19.23 %, respectively, and improves accuracy by 22.56 % and 13.59 %.

Measuring data rot: An analysis of the continued availability of shared data from a Single University.

To determine where data is shared and what data is no longer available, this study analyzed data shared by researchers at a single university. 2166 supplemental data links were harvested from the university's institutional repository and web scraped using R. All links that failed to scrape or could not be tested algorithmically were tested for availability by hand. Trends in data availability by link type, age of publication, and data source were examined for patterns. Results show that researchers shared data in hundreds of places. About two-thirds of links to shared data were in the form of URLs and one-third were DOIs, with several FTP links and links directly to files. A surprising 13.4% of shared URL links pointed to a website homepage rather than a specific record on a website. After testing, 5.4% the 2166 supplemental data links were found to be no longer available. DOIs were the type of shared link that was least likely to disappear with a 1.7% loss, with URL loss at 5.9% averaged over time. Links from older publications were more likely to be unavailable, with a data disappearance rate estimated at 2.6% per year, as well as links to data hosted on journal websites. The results support best practice guidance to share data in a data repository using a permanent identifier.

SHEA position statement on pandemic preparedness for policymakers: pandemic data collection, maintenance, and release.

The Society for Healthcare Epidemiology in America (SHEA) strongly supports modernization of data collection processes and the creation of publicly available data repositories that include a wide variety of data elements and mechanisms for securely storing both cleaned and uncleaned data sets that can be curated as clinical and research needs arise. These elements can be used for clinical research and quality monitoring and to evaluate the impacts of different policies on different outcomes. Achieving these goals will require dedicated, sustained and long-term funding to support data science teams and the creation of central data repositories that include data sets that can be "linked" via a variety of different mechanisms and also data sets that include institutional and state and local policies and procedures. A team-based approach to data science is strongly encouraged and supported to achieve the goal of a sustainable, adaptable national shared data resource.

Impact of institutional variables on centre performance in long-term survival after heart transplant.

The gold standard metric for centre-level performance in orthotopic heart transplantation (OHT) is 1-year post-OHT survival. However, it is unclear whether centre performance at 1 year is predictive of longer-term outcomes. This study evaluated factors impacting longer-term centre-level performance in OHT. Patients who underwent OHT in the USA between 2010 and 2021 were identified using the United Network of Organ Sharing data registry. The primary outcome was 5-year survival conditional on 1-year survival following OHT. Multivariable Cox proportional hazard models assessed the impact of centre-level 1-year survival rates on 5-year survival rates. Mixed-effect models were used to evaluate between-centre variability in outcomes. Centre-level risk-adjusted 5-year mortality conditional on 1-year survival was not associated with centre-level 1-year survival rates [hazard ratio: 0.99 (0.97-1.01, P = 0.198)]. Predictors of 5-year mortality conditional on 1-year survival included black recipient race, pre-OHT serum creatinine, diabetes and donor age. In mixed-effect modelling, there was substantial variability between centres in 5-year mortality rates conditional on 1-year survival, a finding that persisted after controlling for recipient, donor and institutional factors (P < 0.001). In a crude analysis using Kaplan-Meier, the 5-year survival conditional on 1-year survival was: low volume: 86.5%, intermediate volume: 87.5%, high volume: 86.7% (log-rank P = 0.52). These measured variables only accounted for 21.4% of the between-centre variability in 5-year mortality conditional on 1-year survival. Centre-level risk-adjusted 1-year outcomes do not correlate with outcomes in the 1- to 5-year period following OHT. Further research is needed to determine what unmeasured centre-level factors contribute to longer-term outcomes in OHT.

Bedwetting and School-aged Children

Patient Education| 2021 Bedwetting Connected Content Translation: Enuresis nocturna Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share Facebook Twitter LinkedIn Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Bedwetting. Pediatric Patient Education 2021; 10.1542/peo_document012 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search nav search search input Search input auto suggest search filter All AAP SitesAll PublicationsPediatric Patient Education Search Advanced Search Did you know that there are about 5 million children in the United States who wet the bed? If your child wets the bed, he or she is not alone. Although most children are toilet trained between 2 and 4 years of age, some children may not be able to stay dry at night until they are older. Children develop at their own rate. For example, studies have showed that 15% of 5- and 7-year-olds wet the bed. But by age 15, fewer than 1% wet the bed. Bedwetting is not a serious medical condition, but it can be a challenging problem for children and parents. Read on to find out more from the American Academy of Pediatrics about bedwetting and what can be done about it. Here are 3 common reasons for bedwetting. Communication between the brain and bladder. If... © 2020 American Academy of Pediatrics. All rights reserved. You do not currently have access to this content.

Anaphylaxis: What Parents Need to Know

Patient Education| 2021 Anaphylaxis Connected Content Translation: Anafilaxis Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share Facebook Twitter LinkedIn Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Anaphylaxis . Pediatric Patient Education 2021; 10.1542/peo_document203 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search nav search search input Search input auto suggest search filter All AAP SitesAll PublicationsPediatric Patient Education Search Advanced Search Topics: anaphylaxis, hypersensitivity Anaphylaxis includes a wide range of symptoms that often happen quickly. The most severe symptoms restrict breathing and blood circulation. Combinations of symptoms may occur. The most common symptoms may affect the following: SKIN: itching, hives, redness, swellingNOSE: sneezing, stuffy nose, runny noseMOUTH: itching, swelling of lips or tongueTHROAT: itching, tightness, difficulty swallowing, hoarsenessCHEST: shortness of breath, cough, wheeze, chest pain, tightnessHEART: weak pulse, passing out, shockGUT: vomiting, diarrhea, crampsNEUROLOGIC: dizziness, fainting, feeling that you are about to die Anaphylaxis occurs when the immune system overreacts to normally harmless substances called allergens. The following are the most common allergens that can trigger anaphylaxis: Food such asPeanutsNuts from trees (such as walnuts, pistachios, pecans, cashews)Shellfish (such as shrimp, lobster)Fish (such as tuna, salmon, cod)MilkEggsIn rare... Copyright © 2007 American Academy of Pediatrics2007American Academy of Pediatrics You do not currently have access to this content.

Croup: When Your Child Needs Hospital Care

Patient Education| 2021 Croup: When Your Child Needs Hospital Care Connected Content Translation: El crup: En qué casos su hijo necesita cuidado hospitalario: (Croup: When Your Child Needs Hospital Care) Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share Facebook Twitter LinkedIn Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Croup: When Your Child Needs Hospital Care. Pediatric Patient Education 2021; 10.1542/peo_document217 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search nav search search input Search input auto suggest search filter All AAP SitesAll PublicationsPediatric Patient Education Search Advanced Search Croup is a common illness that affects the airways, making it hard for a child to breathe. It's most common in toddlers but can affect children between 6 months and 12 years of age. Another symptom is a loud barking cough that is worse at night. Trouble breathing and the barking cough can be scary for parent and child. Most children with viral croup also have low fever. Most cases of croup can be treated successfully at home. However, children with severe cases of croup may need to be treated in the hospital. Call 911 or an ambulance right away if your child Makes a whistling sound (called stridor) that gets louder with each breath.Cannot speak because of a lack of breath.Seems to struggle to get a breath.Has a bluish color of the lips, mouth, or fingernails.Drools or... Copyright © 20082008 American Academy of Pediatrics You do not currently have access to this content.

Gastroenteritis: When Your Child Needs Hospital Care

Patient Education| 2021 Gastroenteritis: When Your Child Needs Hospital Care Connected Content Translation: La gastroenteritis: En qué casos su hijo necesita cuidado hospitalario: (Gastroenteritis: When Your Child Needs Hospital Care) Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share Facebook Twitter LinkedIn Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Gastroenteritis: When Your Child Needs Hospital Care. Pediatric Patient Education 2021; 10.1542/peo_document218 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search nav search search input Search input auto suggest search filter All AAP SitesAll PublicationsPediatric Patient Education Search Advanced Search Gastroenteritis is a common childhood illness that causes diarrhea and vomiting that can lead to dehydration. It is usually caused by a virus but can also be caused by bacteria or a parasite. Most of the time mild diarrhea and vomiting last for just a few days. However, if symptoms don't go away or they get worse, your child may need to be treated in the hospital. Call your child's doctor if your child is younger than 6 months and has any of the following: Blood in the stoolFrequent vomitingStomach painUrinates less often (Wets fewer than 6 diapers per day.)No tears when cryingLoss of appetite for liquidsHigh fever (over 102°F or 39°C)Frequent diarrheaDry, sticky mouthWeight lossExtreme thirst The biggest concern with gastroenteritis is dehydration, which occurs when a child loses too much... Copyright © 20082008 American Academy of Pediatrics You do not currently have access to this content.

Effective Identity Authentication Based on Multiattribute Centers for Secure Government Data Sharing

Effective Identity Authentication Based on Multiattribute Centers for Secure Government Data Sharing

A Novel Framework for Data Assessment That Uses Edge Technology to Improve the Detection of Communicable Diseases.

Spreading quickly throughout populations, whether animal or human-borne, infectious illnesses provide serious risks and difficulties. Controlling their spread and averting disinformation requires effective risk assessment and epidemic identification. Technology-enabled data analysis on diseases allows for quick solutions to these problems. A Combinational Data Assessment Scheme intended to accelerate disease detection is presented in this paper. The suggested strategy avoids duplicate data replication by sharing data among edge devices. It uses indexed data gathering to improve early detection by using tree classifiers to discern between various kinds of information. Both data similarity and index measurements are considered throughout the data analysis stage to minimize assessment errors. Accurate risk detection and assessment based on information kind and sharing frequency are ensured by comparing non-linear accumulations with accurate shared edge data. The suggested system exhibits high accuracy, low mistakes, and decreased data repetition to improve overall effectiveness in illness detection and risk reduction.

Comparative Analysis of AES, Blowfish, Twofish, Salsa20, and ChaCha20 for Image Encryption

Nowadays, cybersecurity has grown into a more significant and difficult sci-entific issue. The recognition of threats and attacks meant for knowledge and safety on the internet is growing harder to detect. Since cybersecurity guar-antees the privacy and security of data sent via the Internet, it is essential, while also providing protection against malicious attacks. Encrypt has grown into an answer that has become an essential element of information security systems. To ensure the security of shared data, including text, images, or videos, it is essential to employ various methods and strategies. This study delves into the prevalent cryptographic methods and algorithms utilized for prevention and stream encryption, examining their encoding techniques such as advanced encryption standard (AES), Blowfish, Twofish, Salsa20, and ChaCha20. The primary objective of this research is to identify the optimal times and throughputs (speeds) for data encryption and decryption processes. The methodology of this study involved selecting five distinct types of images to compare the outcomes of the techniques evaluated in this research. The as-sessment focused on processing time and speed parameters, examining visual encoding and decoding using Java as the primary platform. A comparative analysis of several symmetric key ciphers was performed, focusing on handling large datasets. Despite this limitation, comparing different images helped evaluate the techniques' novelty. The results showed that ChaCha20 had the best average time for both encryption and decryption, being over 50% faster than some other algorithms. However, the Twofish algorithm had lower throughput during testing. The paper concludes with findings and suggestions for future improvements.

A Secure Data Publishing and Access Service for Sensitive Data from Living Labs: Enabling Collaboration with External Researchers via Shareable Data

Intending to enable a broader collaboration with the scientific community while maintaining privacy of the data stored and generated in Living Labs, this paper presents the Shareable Data Publishing and Access Service for Living Labs, implemented within the framework of the H2020 VITALISE project. Building upon previous work, significant enhancements and improvements are presented in the architecture enabling Living Labs to securely publish collected data in an internal and isolated node for external use. External researchers can access a portal to discover and download shareable data versions (anonymised or synthetic data) derived from the data stored across different Living Labs that they can use to develop, test, and debug their processing scripts locally, adhering to legal and ethical data handling practices. Subsequently, they may request remote execution of the same algorithms against the real internal data in Living Lab nodes, comparing the outcomes with those obtained using shareable data. The paper details the architecture, data flows, technical details and validation of the service with real-world usage examples, demonstrating its efficacy in promoting data-driven research in digital health while preserving privacy. The presented service can be used as an intermediary between Living Labs and external researchers for secure data exchange and to accelerate research on data analytics paradigms in digital health, ensuring compliance with data protection laws.

The BC Radon Data Repository (BCRDR) and BC Radon Map: Integrating disparate data sources for improved public health communication.

The potential for exposure to indoor radon varies dramatically across British Columbia(BC) due to varied geology. Individuals may struggle to understand their exposure risk and agencies may struggle to understand the value of population-level programs and policies to mitigate risk. The BC Centre for Disease Control (BCCDC) established the BC Radon Data Repository (BCRDR) to facilitate radon research, public awareness, and action in the province. The BCRDR aggregates indoor radon measurements collected by government agencies, industry professionals and organizations, and research and advocacy groups. Participation was formalized with a data sharing agreement, which outlines how the BCCDC anonymizes and manages the shared data integrated into the BCRDR. The BCRDR currently holds 38,733 measurements from 18 data contributors. The repository continues to grow with new measurements from existing contributors and the addition of new contributors. A prominent use of the BCRDR was to create the online, interactive BC Radon Map, which includes regional concentration summaries, risk interpretation messaging, and health promotion information. Anonymized BCRDR data are also available for external release upon request. The BCCDC leverages existing radon measurement programs to create a large and integrated database with wide geographic coverage. The development and application of the BCRDR informs public health research and action beyond the BCCDC, and the repository can serve as a model for other regional or national initiatives.

A Reliable and Equitable Attribute-Based Proxy Re-encryption System for Cloud Data Sharing

The widespread acceptance and quick growth of cloud computing have made data sharing easier than ever before. What is preventing widespread adoption of cloud computing, however, is how to guarantee the security of the user's data in the cloud. Safe data sharing in cloud computing can be achieved through the use of proxy re-encryption. With the use of a semi trusted cloud server, a data owner can encrypt shared data in the cloud using their own public key, converting it into an encryption meant only for authorized recipients to control access. To help us grasp this fundamental better, this paper provides a thorough and motivating overview of re-encryption of proxy servers from a variety of angles. For granular access control of shared data, Ciphertext-Policy Attribute based Aes (CP-ABE) is a possible cryptographic primitive. Each user in CP-ABE has a set of attributes, and access structures based on attributes are used to encrypt data. If and only if a user's characteristics meet the requirements of the ciphertext access structure, the user can decrypt a ciphertext. Practical applications typically call for additional requirements in addition to this fundamental one. Our research centers on the significant problem of attribute revocation, which poses a challenge for CP-ABE methods

Kidney transplantation in patients with tuberous sclerosis complex.

Tuberous sclerosis complex (TSC) is a disorder of the mammalian target of the rapamycin (mTOR) pathway associated with the development of multisystem tumors, including renal angiomyolipoma (AML). These renal tumors are benign by nature but locally invasive and carry a risk for the progression of chronic kidney disease (CKD) to end stage kidney disease (ESKD). The frequency of subsequent renal transplantation in this population is largely uncharacterized, although single-center data suggests that 5%-15% of adult TSC patients are kidney transplant recipients. This retrospective cohort study utilized United Network for Organ Sharing (UNOS) data. We included candidates waitlisted between 1987 and 2020 for a first kidney transplant with TSC-associated kidney failure. We utilized descriptive statistics to characterize the frequency of first-time kidney transplant waitlisting and transplantation among persons with TSC and the Fine-Gray subdistribution hazard model to evaluate characteristics associated with progression from waitlist. We identified 200 TSC-associated kidney failure patients within the waitlist cohort. Of these, 12 were pediatric patients. Two-thirds (N = 134) of waitlisted persons were female. One hundred forty patients received a transplant with a median waitlist time of 2 years. Younger age at waitlisting was associated with a greater probability of progressing to transplant (HR 0.98 [95% CI: 0.96-0.99]). 91.8% of kidney transplant recipients survived 1-year post-transplant with a functioning allograft. The majority of patients with TSC who are waitlisted for a kidney transplant progress onto transplantation with excellent 1-year post transplant patient and allograft survival.

The Galaxy platform for accessible, reproducible, and collaborative data analyses: 2024 update.

Galaxy (https://galaxyproject.org) is deployed globally, predominantly through free-to-use services, supporting user-driven research that broadens in scope each year. Users are attracted to public Galaxy services by platform stability, tool and reference dataset diversity, training, supportand integration, which enables complex, reproducible, shareable data analysis. Applying the principles of user experience design (UXD), has driven improvements in accessibility, tool discoverability through Galaxy Labs/subdomains, and a redesigned Galaxy ToolShed. Galaxy tool capabilities are progressing in two strategic directions: integrating general purpose graphical processing units (GPGPU) access for cutting-edge methods, and licensed tool support. Engagement with global research consortia is being increased by developing more workflows in Galaxy and by resourcing the public Galaxy services to run them. The Galaxy Training Network (GTN) portfolio has grown in both size, and accessibility, through learning paths and direct integration with Galaxy tools that feature in training courses. Code development continues in line with the Galaxy Project roadmap, with improvements to job scheduling and the user interface. Environmental impact assessment is also helping engage users and developers, reminding them of their role in sustainability, by displaying estimated CO2 emissions generated by each Galaxy job.

The effects of meteorological factors and air pollutants on the incidence of tuberculosis in people living with HIV/AIDS in subtropical Guangxi, China.

Previous studies have shown the association between tuberculosis (TB) and meteorological factors/air pollutants. However, little information is available for people living with HIV/AIDS (PLWHA), who are highly susceptible to TB. Data regarding TB cases in PLWHA from 2014 to2020 were collected from the HIV antiviral therapy cohort in Guangxi, China. Meteorological and air pollutants data for the same period were obtained from the China Meteorological Science Data Sharing Service Network and Department of Ecology and Environment of Guangxi. A distribution lag non-linear model (DLNM) was used to evaluate the effects of meteorological factors and air pollutant exposure on the risk of TB in PLWHA. A total of 2087 new or re-active TB cases were collected, which had a significant seasonal and periodic distribution. Compared with the median values, the maximum cumulative relative risk (RR) for TB in PLWHA was 0.663 (95% confidence interval [CI]: 0.507-0.866, lag 4 weeks) for a 5-unit increase in temperature, and 1.478 (95% CI: 1.116-1.957, lag 4 weeks) for a 2-unit increase in precipitation. However, neither wind speed nor PM10 had a significant cumulative lag effect. Extreme analysis demonstrated that the hot effect (RR = 0.638, 95%CI: 0.425-0.958, lag 4 weeks), the rainy effect (RR = 0.285, 95%CI: 0.135-0.599, lag 4 weeks), and the rainless effect (RR = 0.552, 95%CI: 0.322-0.947, lag 4 weeks) reduced the risk of TB. Furthermore, in the CD4(+) T cells < 200 cells/µL subgroup, temperature, precipitation, and PM10 had a significant hysteretic effect on TB incidence, while temperature and precipitation had a significant cumulative lag effect. However, these effects were not observed in the CD4(+) T cells ≥ 200 cells/µL subgroup. For PLWHA in subtropical Guangxi, temperature and precipitation had a significant cumulative effect on TB incidence among PLWHA, while air pollutants had little effect. Moreover, the influence of meteorological factors on the incidence of TB also depends on the immune status of PLWHA.