Public Access Research Articles

A Metric-Based Detection System for Large Language Model Texts

More efforts are being put into improving Large Language Models’ (LLM) capabilities than into dealing with their implications. Current LLMs are able to generate high quality texts seemingly indistinguishable from those written by human experts. While offering great potentials, such breakthroughs also pose new challenges for safe and ethical uses of LLMs in education, science, and a multitude of other areas. To add up, the majority of current approaches in LLM text detection are either computationally expensive or need access to the LLMs’ internal computations, both of which hinder their public accessibility. With such motivation, this paper presents a novel metric learning paradigm for detection of LLM-generated texts that is able to balance among computational costs, accessibility, and performances. Specifically, the detection is based on learning a similarity function between a given text and an equivalent example generated by LLMs that outputs high values for LLM-LLM text pairs and low values for LLM-human text pairs. In terms of architecture, the detection framework includes a pretrained language model for the text embedding task and a newly designed deep metric model. The metric component can be trained on triplets or pairs of same-context instances to signify the distances between human texts and LLM ones while reducing that among LLM texts. Next, we develop five datasets totalling over 95,000 contexts and triplets of responses in which one from human and two from GPT-3.5 TURBO or GPT-4 TURBO for benchmarking. Experiment studies show that our best architectures maintain F1 scores in between 0.87 to 0.95 across the tested corpora in multiple experiment settings. The metric framework also demands significantly less time in training and inference compared to the RoBERTa, LLaMA 3, Mistral v0.3, and Ghostbuster, while keeping 90% to 150% performances of the best benchmark.

Legal and Practical Implications of Digitizing the Slovakian Cadastre: Challenges and Opportunities

Background: Acquiring ownership rights to real estate in Slovakia is complex and frequently encounters hurdles. The formal procedures governing this process can be stringent, resulting in challenges when transferring ownership rights. This article critically evaluates the obstacles and potential advantages as the Slovakian Cadastre shifts towards a digital system. The authors also explore the scope of contractual freedom and governmental intervention in acquiring property rights alongside recent challenges encountered by the digitalized system under both Slovakian and European law. The study analyses the theoretical framework guiding decision-making by Slovak administrative authorities in cadastral proceedings, underscoring the critical role of formal legal procedures in ensuring legal certainty and stability. Additionally, the research underscores the importance of accurately registering changes to property rights within the digitalized real estate registration system to uphold the integrity and transparency of title records. Methods: The research follows a qualitative methodology, employing various qualitative methods, including historical description and analysis, in-depth document analysis, inductive method, comparative analysis, and case studies rooted in legal theory, administrative law and property law. It may utilise conceptual frameworks like legal certainty and stability to inform its examination. The methodology may not involve empirical data collection or statistical analysis but rather a critical examination of the existing legal framework and theoretical perspectives. Results and conclusions: Acquiring ownership rights to real estate in Slovakia is a complex process hindered by discrepancies between registered and actual property statuses, outdated maps and inaccuracies in parcel boundaries. The lack of clarity and precision significantly affects legal certainty and private property rights. In response, the Office of Geodesy, Cartography and Cadastre has proposed a comprehensive amendment to the Cadastral Act, aiming to update the classification of land, regulate electronic submissions, and simplify application processes. However, the proposed amendment may restrict public access to information contained in the Cadastre, which could negatively impact the exercise of property rights and the right to freely access information.

The Genomic SSR Millets Database (GSMDB): enhancing genetic resources for sustainable agriculture.

The global population surge demands increased food production and nutrient-rich options to combat rising food insecurity. Climate-resilient crops are vital, with millets emerging as superfoods due to nutritional richness and stress tolerance. Given limited genomic information, a comprehensive genetic resource is crucial to advance millet research. Whole-genome sequencing provides an unprecedented opportunity, and molecular genetic methodologies, particularly simple sequence repeats (SSRs), play a pivotal role in DNA fingerprinting, constructing linkage maps, and conducting population genetic studies. SSRs are composed of repetitive DNA sequences where one to six nucleotides are repeated in tandem and distributed throughout the genome. Different millet species exhibit genomic variations attributed to the presence of SSRs. While SSRs have been identified in a few millet species, the existing information only covers some of the sequenced genomes. Moreover, there is an absence of complete gene annotation and visualization features for SSRs. Addressing this disparity and leveraging the de-novo millet genome assembly available from the NCBI, we have developed the Genomic SSR Millets Database (GSMDB; https://bioinfo.icgeb.res.in/gsmdb/). This open-access repository provides a web-based tool offering search functionalities and comprehensive details on 6.747645 million SSRs mined from the genomic sequences of seven millet species. The database, featuring unrestricted public access and JBrowse visualization, is a pioneering resource for the research community dedicated to advancing millet cultivars and related species. GSMDB holds immense potential to support myriad studies, including genetic diversity assessments, genetic mapping, marker-assisted selection, and comparative population investigations aiming to facilitate the millet breeding programs geared toward ensuring global food security. Database URL: https://bioinfo.icgeb.res.in/gsmdb/.

Neighborhoods, Networks, and HIV Care Among Men Who Have Sex With Men: Proposal for a Longitudinal Study.

The majority of people living with HIV in the United States are men who have sex with men (MSM), with race- and ethnicity-based disparities in HIV rates and care continuum. In order to uncover the neighborhood- and network-involved pathways that produce HIV care outcome disparities, systematic, theory-based investigation of the specific and intersecting neighborhood and social network characteristics that relate to the HIV care continuum must be engaged. Using socioecological and intersectional conceptual frameworks, we aim to identify individual-, neighborhood-, and network-level characteristics associated with HIV care continuum outcomes (viral suppression, retention in care, and antiretroviral adherence) among MSM living with HIV in New York City. In the longitudinal cohort study, we assess 3 neighborhoods of potential influence (residential, social, and health care access activity spaces) using Google Earth. We investigate the influence of neighborhood composition (eg, concentrated poverty and racial segregation) and four neighborhood-level characteristics domains: (1) community violence, physical disorder, and social disorganization (eg, crime rates and housing vacancy); (2) alcohol and other drug use; (3) social norms (eg, homophobia and HIV stigma); and (4) community resources (eg, social services and public transit access). We test theoretical pathways of influence, including stress or coping, stigma or resilience, and access to resources, across the different neighborhoods in which MSM live, socialize, and receive HIV care. At each visit, we locate each participant's reported activity spaces (ie, neighborhoods of potential influence) and collect individual-level data on relevant covariates (including perceptions of or exposure to neighborhoods) and social network inventory data on the composition, social support, and perceived social norms. The outcomes are HIV viral suppression, retention in care, and antiretroviral adherence. These data are combined with an existing, extensive geospatial database of relevant area characteristics. Spatial analysis and multilevel modeling are used to test the main theory-driven hypotheses and capture independent neighborhood-level and network-level effects and changes over time. The study began enrollment in March 2019 and concluded visits in December 2023, with a total of 327 participants enrolled. The median age was 44.1 (SD 11.5) years. Almost all participants self-identified as cisgender men (n=313, 98.1%) and as gay, homosexual, or bisexual (n=301, 94.4%). Overall, 192 (60.1%) participants identified as non-Hispanic Black, and 81 (25.3%) identified as Hispanic. Most (n=201, 63%) reported at least occasional difficulty in meeting basic needs (eg, rent and food) in the past 6 months. The mean number of years living with HIV was 15.4 (SD 10.1). This study will have direct implications for the design of multilevel interventions, addressing factors at the neighborhood, network, and individual levels. Results may inform urban planning and program design to improve HIV care outcomes for MSM, particularly for Black and Latino MSM living in urban areas. PRR1-10.2196/64358.

Louveira Digital City

The Louveira Digital City is a municipal information network designed to promote digital appications development, offering e-government services in areas such as health, education, social assistance, safety, and public works. The project began as an academic initiative focused on Louveira's Information Highway, which was presented to the City Council in August 2010. It outlines the key components of the information highway, including the optical backbone architecture, feasibility study, radio link specifications, logical network design, equipment specifications, and project budget. This digital infrastructure enables all residents to access various communication services and applications, such as data, video, and voice traffic. The network is comprised of radio and fiber optic links, designed to benefit various areas of public administration, including health, safety, education, and planning. Additionally, it aims to enhance public access to information, culture, education, and leisure, laying the groundwork for a smart city. This project showcases the implementation of the information highway in Louveira, highlighting how academic institutions can contribute to the economic, social, and technological development of society and serving as a model for similar initiatives.

DGTNet：dynamic graph attention transformer network for traffic flow forecasting

Abstract Graph-based traffic flow prediction plays a crucial role in urban traffic management and planning. In this paper, we propose a novel Dynamic Graph Attention Transformer Network (DGTnet), which is designed to address the issue of inadequately integrating of temporal and spatial dimensions in traditional models. DGTnet maintains temporal continuity while revealing the complex dynamic relationships between key nodes in the urban traffic system, capturing the periodic changes in the rhythm of city life. Specifically, this study adopts adaptive signal decomposition technology to decompose traffic data into multiple intrinsic mode functions (IMFs), effectively capturing the dynamic changes in traffic flow. This decomposition method is key to the implementation of DGTnet dynamic graph construction, enabling the analysis of traffic flow at different time scales, thereby providing a new perspective for traffic flow prediction research. In the traffic prediction module, we comprehensively consider node, edge, and graph structural information, adopting a multi-head self-attention mechanism to achieve direct cross-modeling in both temporal and spatial dimensions. Finally, we introduce a position-wise feed forward network layer to integrate different types of data and capture nonlinear relationships. The experimental results, based on the public transportation network data sets METR_LA, PEMS_BAY, PEMS03 and PEMS07, demonstrate that DGTNet exhibits notable enhancements in three evaluation indicators, namely the Mean Absolute Percentage Error (MAPE), the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). The pertinent code has been made available for public access at https://github.com/chenjing0616/DGTNet.

1/20,000th of a Person?

Notice-and-comment rulemaking is a key function of the U.S. administrative state, thought to give members of the public access to the process of government decisionmaking. However, notice-and-comment rulemaking fails to accomplish that goal, and its deficiencies have critical implications for U.S. democracy and for the role of women and other traditionally underrepresented groups in that democracy. This Article examines the many ways in which notice-and-comment rulemaking has fallen short of its central purpose through a case study of a 2018–19 rulemaking dealing with enforcement of Title IX’s prohibition on sexual harassment. Members of the public, mobilized by activists, filed a historic 124,000+ comments in that rulemaking. This author created and led a “crowd-research” innovation to catalog ninety-four percent of those comments. Analysis of that rulemaking and its comments exposes rulemaking’s oligarchic tendency to value technocratic practices above democratic ones, a tendency that is particularly problematic in the case of rulemakings that implicate civil rights and discrimination. This Article proposes a path for agencies to avoid notice-and-comment rulemaking’s failings by supplementing traditional processes with a modified form of negotiated rulemaking.

Abstract Su507: Occurrence of Fibrillation in Out-of-hospital Cardiac Arrest Patients Presenting in a Non-shockable Rhythm when Treated with an Automated External Defibrillator

Background: Most out-of-hospital cardiac arrest (OHCA) patients who are initially treated with an automated external defibrillator (AED) and present in a non-shockable rhythm never receive a shock. This analysis reports on patients who presented in a non-shockable rhythm when the AED was initially applied and later transitioned into a shockable rhythm. Methods: Data from a convenience group of OHCA patients treated with a Philips HeartStart Home, Onsite or FRx AED were included. The AEDs were the first defibrillator on scene either in home, in public access or by a BLS team. Application of any medication during AED use was unlikely. Each patient’s heart rhythms were reviewed by an expert. All patients whose initial rhythm was non-shockable but later received at least one shock were identified and the rhythms were analyzed. Results: Out of 876 patients, 322 (36.8%) received at least one shock, of which five patients (1.6%) presented in a non-shockable rhythm and were later shocked. Three patients presented in an organized rhythm. The first patient degraded into Torsade de Pointe as shown in Figure 1; the post-shock rhythm was organized. The second patient received no CPR and A-V pacing was observed in the ECG recording. The pacing stopped when the rhythm transitioned into VF and restarted post shock. The third patient transitioned into VF during chest compressions and the post-shock rhythm was asystole. The remaining two patients presented in asystole and the rhythm evolved to fine VF after receiving chest compressions. After defibrillation, their rhythms returned to asystole. Conclusions: For OHCA patients treated with an AED, presenting in a non-shockable rhythm and later transitioning into a shockable rhythm is rare but possible. Lay-responder CPR may play a role in rhythm evolvement. The impact of rhythm changes on survivability of these patients is unknown.

Boosting Winter Green Travel: Prioritizing Built Environment Enhancements for Shared Bike Users Accessing Public Transit in the First/Last Mile Using Machine Learning and Grounded Theory

Shared bikes are widely used in Chinese cities as a green and healthy solution to address the First/Last Mile issue in public transit access. However, usage declines in cold regions during winter due to harsh weather conditions. While climate factors cannot be changed, enhancing the built environment can promote green travel even in winter. This study uses data from Shenyang, China, to investigate how built environment attributes impact the travel satisfaction of shared bike users who utilize bikes as a First/Last Mile solution to access public transit in winter cities. By employing machine learning algorithms combined with Asymmetric Impact-Performance Analysis (AIPA) and grounded theory, we systematically identify the key attributes and rank them based on their asymmetric impact and urgency of improvement. The analysis revealed 19 key attributes, 17 of which are related to the built environment, underscoring its profound influence on travel satisfaction. Notably, factors such as the profile design of cycling paths and safety facilities along routes were identified as high priorities for improvement due to their significant potential to enhance satisfaction. Meanwhile, features like barrier-free access along paths and street greenery offer substantial opportunities for improvement with more modest efforts. Our research provides critical insights into the nuanced relationship between built environment features and travel satisfaction for First/Last Mile shared bike users. By highlighting priority improvements, we offer urban planners and policymakers a framework for creating livable, sustainable environments that support green travel even in harsh winter conditions.

Mammography In Breast Cancer Screening – Current Knowledge, Challenges, The Impact of Artificial Intelligence, And Effectiveness With A Focus On Poland

Mammography is a critical tool in breast cancer screening and secondary prevention, enabling early detection and significantly reducing breast cancer mortality. This literature review assesses the effectiveness of mammography in identifying early-stage tumors, discussing its advantages, limitations, and specific challenges. Additionally, advancements in imaging techniques, such as 3D tomosynthesis, are examined, especially for their enhanced sensitivity in women with dense breast tissue, which reduces structural overlap and improves diagnostic precision. The integration of artificial intelligence (AI) in mammographic image analysis opens new opportunities, supporting radiologists by automating the detection and classification of potential lesions, thereby increasing screening efficiency and reducing false-positive rates. However, effective implementation of AI requires seamless integration with clinical systems and ongoing research to refine algorithms for diverse clinical needs. Furthermore, legal frameworks are essential to delineate responsibility in AI-supported diagnostics. This review emphasizes the status of breast cancer screening in Poland, where participation rates remain low despite the availability of free screenings. This highlights the need for improved public awareness and accessibility, especially in underserved areas. Overall, the findings underscore the fundamental role of mammography in breast cancer detection, with AI and other technological advancements significantly enhancing diagnostic accuracy while identifying areas for further improvement.

Abstract Su607: Which would be major? witnessed collapse or bystander resuscitation?

Background: Witnessed collapse and bystander cardiopulmonary resuscitation (CPR) are two variables commonly used to predict outcomes in out-of-hospital cardiac arrest (OHCA). Some published studies have shown that bystander CPR were not significantly associated with outcomes after confounders adjusted. This may imply that witnessed collapse would be a superior prognostic factors beyond bystander CPR. Hypothesis: Witnessed collapse and bystander CPR may not contribute equally to prehospital return of spontaneous circulation (ROSC), and the former may be major. Aims: To investigate four prediction models for prehospital ROSC using stratification of the witnessed collapse and bystander CPR. Methods: The study enrolled OHCA patients treated by the emergency medical service (EMS) from January 2010 to December 2022 in three EMS systems in Taiwan. Data were extracted from the records of each medical service encounter, including patient demographics, dispatch timing, prehospital management, witnessed collapse and bystander CPR. The primary outcome was any prehospital ROSC. Patients were stratified into four groups by witnessed collapse (with/without) and bystander CPR (with/without) status, namely W+B+, W-B+, W+B- and W-B-. Prehospital ROSC prognostication were identified using multivariable logistic regression analysis. Results: The analysis comprised 17,323 patients, among whom 1,165 (6.7%) achieved prehospital ROSC. The W+B+ group demonstrated the highest prehospital ROSC rate at 13.0%, as compared with the other groups significantly (9.0%, 3.4%, and 4.1%, as depicted in Image 1). Stratification of the prehospital ROSC model (Image 2) indicated that the W+B+ group had several common predictors including age, traumatic arrest, no-flow time, public access defibrillation (PAD), and resuscitation events. However, certain predictors in other groups were removed during regression process. Notably, no-flow time significantly influenced prehospital ROSC only in the W+B+ and W+B- groups. Conversely, in the W-B- group, most variables had minimal impact on prehospital ROSC, reflecting the limited effectiveness of traditional predictors within this subgroup. Conclusion: The significance of witnessed collapse as a prognostic factor may be equal to or even greater than that of bystander CPR. Further studies are needed to confirm.

Abstract Su606: PulsePoint Alert Location Features in a Mid-Sized Metropolitan Area

Introduction: PulsePoint is a smartphone-based system that alerts layperson responders to out-of-hospital cardiac arrest (OHCA) events in non-residential locations within the United States. These locations can be classified to inform public access defibrillator (PAD) placement and focus responder training and recruitment efforts in high-frequency areas. Our objective was to manually classify the locations of PulsePoint alerts to better understand how PulsePoint performs across a variety of location types. Methods: Records were obtained for each PulsePoint alert in Allegheny County, PA, USA (pop. 1.2M) from 06/24/2016 to 10/28/2020. PulsePoint generates an alert when a potential OHCA occurs in public and is within 400m of at least one responder. Alert data contains address and location name, and the number and locations of nearby responders and PADs. We placed each location into one of the following categories: “education”, “consumer goods/services”, “restaurants/bars”, “transit hubs”, “hotels”, “entertainment venues”, “recreational facilities”, “government/municipal”, “offices”, “industrial/manufacturing”, “religious institutions”, “parks/outdoor spaces”, “sidewalk/street”, and “shelters/supportive housing”. “Unspecified/unknown” was used for locations that could not be classified due to insufficient information. We excluded all outpatient health, assisted-living, daycare, and correctional facilities. For each location category, we calculated the event count and the median number of nearby responders and PADs. Results: There were 994 included events during the capture period. The most frequent location category was “sidewalk/street”, which represented 24 percent of all alerts; the least frequent was “transit hubs”, which represented 0.7 percent of all alerts. “Shelters/supportive housing” had the highest median number of responders (7, IQR 1-14), while “industrial/manufacturing” had the lowest (1, IQR 1-3.5). “Transit hubs” had the highest median number of PADs (31, IQR 31-41), while “parks/outdoor spaces” had the lowest (0.5, IQR 0-1). Conclusion: PulsePoint alert-generating events occur across a wide variety of location types. Further research is needed to understand the accuracy of the system’s location data versus EMS dispatch records. Nonetheless, the data may have implications for system improvement by highlighting which location types have low numbers of nearby responders and PADs and may benefit from strategic PAD placements and training efforts.

Historical Insights into CO2 Emission Dynamics in Urban Daily Mobility: A Case Study of Lyon’s Agglomeration

CO2 emissions from urban daily mobility play a major role in both environmental degradation, rising economic costs, and sustainability. Reducing these emissions not only advances environmental sustainability but also fosters economic development by enhancing public health, lowering energy consumption, and alleviating the financial strain caused by climate change. Understanding the dynamics of CO2 emissions from urban daily mobility provides valuable historical insights into environmental impacts and economic costs tied to urban development. This study takes a historical perspective, examining changes in CO2 emissions associated with daily mobility in the Lyon agglomeration across two decades, drawing on data from the 1995 and 2006 household travel surveys. Our findings reveal that individual factors such as gender, age, employment status, and income significantly influence CO2 emissions, with males and full-time workers exhibiting higher emissions. Furthermore, household characteristics, including size and vehicle ownership, are critical in shaping emission levels, while urban form variables such as population density and mixed land use demonstrate a negative correlation with emissions, highlighting the importance of urban planning in mitigating CO2 output. The analysis emphasizes that greater accessibility and proximity to essential services are vital in reducing individual emissions. Based on these insights, we discuss the implications for policy design, suggesting targeted strategies to enhance urban mobility, improve public transport accessibility, and promote sustainable urban development. Finally, we outline directions for future research to further explore the intricate relationship between urban characteristics and emissions, ultimately aiming to contribute to the development of effective climate policies.

The metaverse-industrial complex

ABSTRACT This paper explores the role that Nvidia is playing in shaping the Metaverse for industrial applications in simulation and automation. As the world's largest manufacturer of Graphics Processing Units for computationally intensive tasks and one of the largest corporations by market capitalization, Nvidia has remained relatively overlooked within critical discussions of ‘Big Tech', the Metaverse, and Artificial Intelligence. This paper draws on news media reports and publicly accessible Nvidia publications such as developer documentation and press releases to understand the role of Nvidia in shaping the Metaverse for industrial enterprises. It conceptualises the ‘Metaverse-Industrial Complex' to theorise the processes of market capture, territorialization, and platform expansionism occurring within the convergence of the Metaverse and Artificial Intelligence that is reconfiguring the governance of public and private assets and infrastructure. Through an examination of Nvidia's ‘Omniverse' platform and network of industrial partnerships, the paper examines the Metaverse-Industrial Complex as an assemblage of developer tools, platforms, data standards, and industry partnerships that converge machine learning and 3D graphics into photo-realistic ‘digital twin’ simulations of physical objects and environments.

The Brazilian State Water Resources Councils: diagnosis of civil society participation through criteria of access to information, parity, and decision-making procedures

The aim of the article was to investigate whether the Brazilian State Water Resources Councils, including the Federal District, ensure civil society participation through access to information, parity, and decision-making procedures. In this context, verification criteria were selected, with maximum score of 1 point assigned based on their suitability for the Councils, which were classified in terms of participation adequacy. The states that were deemed suitable, in descending order, were: Paraíba (1st position), Mato Grosso do Sul, Minas Gerais, and São Paulo (2nd position), Amazonas, Pará, Paraná, Rio de Janeiro, Rio Grande do Sul, Rondônia, and Santa Catarina (3rd position), Bahia, Ceará, Federal District, Espírito Santo, and Mato Grosso (4th position), Rio Grande do Norte and Tocantins (5th position), and Alagoas (6th position). The states deemed unsuitable were: Acre and Pernambuco (7th position), Piauí and Roraima (8th position), Goiás and Sergipe (9th position), and Amapá and Maranhão (10th position). As for the criteria, the ones that scored the highest were: the presence of the website and Internal Regulations of the Councils, decision-making by the Council in plenary sessions, the presence of Meeting Minutes on the website, identification of the Technical Chambers of the Councils on these channels, adherence to the regular meeting schedule, identification of the members who make up the Councils, and parity among the three sectors that constitute them. It was concluded that the State Water Resources Councils need to ensure equal participation for civil society members in their discussions and deliberations as well as provide public access to the information generated.

Preserving contemporary newspapers: A new survey of state libraries in the USA

Newspaper collections require the use of archival science techniques and public librarianship. Indexing and public access are necessary for the provision of newspapers, while preservation underpins these efforts. In the United States, newspaper publishing tactics are changing quickly, causing upheaval in reading rooms and archival stacks. At the same time, the users’ focus upon digital access to newspapers has been wrongly conflated with the preservation formatting required to save them. A new U.S. survey of state library directors and newspaper collection managers addresses ways in which archivists and librarians evolve so that current titles with intrinsic value can be dovetailed into existing newspaper collections. Traditional practices of filming, digital image collecting, and print rotation still prevail. The survey was completed in 2023, and it is hoped that the findings will stimulate new discussions about newspaper preservation in the 21st century.

Association of dietary anthocyanidins intake with all-cause mortality and cardiovascular diseases mortality in USA adults: a prospective cohort study

Anthocyanins, as a type of polyphenolic compound, have been discovered to offer multiple health benefits to humans, including anti-aging and anti-inflammatory properties. This prospective cohort study aims to examine the relationship of dietary intake of anthocyanin with all-cause mortality and cardiovascular diseases mortality in the US. The aim of this research was to explore the possible correlation between anthocyanin consumption and the mortality rate from all causes as well as from cardiovascular disease. Based on the Public Access NHANES-linked National Death Index files up to December 31, 2019, we identified mortality status and heart disease-specific causes of death. A multivariate Cox regression analysis was employed to evaluate the effects of anthocyanin intake on mortality outcomes, generating hazard ratios and 95% confidence intervals, adjusting for various demographic characteristics, lifestyle factors, and comorbid conditions. Additionally, we utilized Kaplan-Meier survival curves, subgroup analyses. In different scenarios, dietary anthocyanin intake was assessed using restricted cubic spline models. A total of 11,959 participants completed the final cohort, averaging 47.12 years of age (SD ± 0.35). Following adjustments for multiple variables, an inverse relationship was identified between anthocyanin intake in the highest quartile and all causes mortality, yielding a hazard ratio (HR) of 0.68 (95% CI: 0.52–0.89). Similarly, elevated anthocyanin consumption was linked to a reduction in heart disease mortality, with HR of 0.61 (95% CI: 0.38–0.97). Additionally, dose–response curve revealed a consistent decrease in both all-cause and cardiovascular mortality with increasing anthocyanin intake. Further subgroup analyses revealed that elevated intake of anthocyanins was linked to decreased all-cause mortality in White individuals and males. Moreover, high anthocyanin intake was significantly correlated with reduced all-cause mortality irrespective of hypertension or hyperlipidemia status. Our research indicates that an appropriate dietary intake of anthocyanins is associated with a reduction in overall mortality rates. Furthermore, the findings reveal a substantial association between anthocyanin intake and decreased mortality from cardiovascular diseases, suggesting that anthocyanins may effectively lower the risk of cardiovascular-related deaths.

Open science practices among authors published in complementary, alternative, and integrative medicine journals: An international, cross-sectional survey.

Open science practices aim to increase transparency in research and increase research availability through open data, open access platforms, and public access. Due to the increasing popularity of complementary, alternative, and integrative medicine (CAIM) research, our study aims to explore current open science practices and perceived barriers among CAIM researchers in their own respective research articles. We conducted an international cross-sectional online survey that was sent to authors that published articles in MEDLINE-indexed journals categorized under the broad subject of "Complementary Therapies" or articles indexed under the MeSH term "Complementary Therapies." Articles were extracted to obtain the names and emails of all corresponding authors. Eight thousand seven hundred eighty-six researchers were emailed our survey, which included questions regarding participants' familiarity with open science practices, their open science practices, and perceived barriers to open science in CAIM with respect to participants' most recently published article. Basic descriptive statistics was generated based on the quantitative data. The survey was completed by 292 participants (3.32% response rate). Results indicate that the majority of participants were "very familiar" (n = 83, 31.68%) or "moderately familiar" (n = 83, 31.68%) with the concept of open science practices while creating their study. Open access publishing was the most familiar to participants, with 51.96% (n = 136) of survey respondents publishing with open access. Despite participants being familiar with other open science practices, the actual implementation of these practices was low. Common barriers participants experienced in implementing open science practices include not knowing where to share the study materials, where to share the data, or not knowing how to make a preprint. Although participants responded that they were familiar with the concept of open science practices, the actual implementation and uses of these practices were low. Barriers included a lack of overall knowledge about open science, and an overall lack of funding or institutional support. Future efforts should aim to explore how to implement methods to improve open science training for CAIM researchers.

Teachers’ Perception of Corrupt Practices at Teaching Service Commission in Nigeria

Corruption is a global problem that has affected education in Africa and Nigeria, affecting the system’s efficiency. Two research questions guided this study. This study explored teachers’ perception of corrupt practices in the Teaching Service Commission (TSC) in Nigeria with particular reference to Ekiti state. A descriptive research design and a quantitative approach were adopted. Random sampling technique was used in this study and 180 participants were selected for this study. The study participants were given a questionnaire known as the Perceived Corrupt Practices Questionnaire (PCPQ) to obtain the views of the participants. The data collected was analyzed using descriptive statistics and percentages. The findings revealed many forms of corruption in the Ekiti State Teachers Service of Nigeria, including collecting official documents, bribery for admission to public schools and access preferences. Teachers also believe that corruption in the Board of Education is responsible for destroying social welfare and poor educational achievement in Nigeria. It was concluded that corruption reduces the resources available to schools, limits access to education, and reduces the quality of services in the state.

Penolakan Kebijakan Relokasi dan Implikasinya terhadap Hak Asasi Pedagang di Cisoka, Kabupaten Tangerang

This study examines the rejection of the relocation policy stipulated in PERBUP Kabupaten Tangerang No. 60 of 2016 by traders in the Cisoka District. Findings indicate that the majority of traders oppose the policy due to the prohibition of street vendors (PKL) in the new market and the imposition of fees for public access. This situation significantly impacts the traders' income, potentially lowering their standard of living. The rejection reflects human rights issues, specifically the traders' right to work and earn a decent living. Dissatisfaction arises from a policy that lacks support and imposes access fees on the public. The study emphasizes the importance of involving traders in the formulation of policies affecting their livelihoods. The government is urged to review the relocation policy to be more inclusive and consider the aspirations and needs of the community. Overall, this research provides insights into the negative impacts of relocation policies that do not take into account the needs and rights of traders, highlighting the necessity of a fairer and more sustainable approach in policy-making to support the overall welfare of the community.