Integrating DNA barcoding and machine learning for species identification: Comparative genomics and codon usage bias of chloroplasts in Gentiana sect. Cruciata.

A comprehensive dataset of customer behavior in Latin American Fintech: 12-month transactional and demographic data for churn analysis.

Long-term use of Benzodiazepines and Z-drugs: A register-based cohort study in Taiwan.

The longitudinal relationships between Internet adaptability and usage behavior on AI-driven healthcare platforms: A cross-lagged panel network analysis.

Wastewater treatment plants as sinks and sources of PFASs: A global comparative review of occurrence, removal, and risks.

Retrospective review of electronic health records system. To compare the indications and complication rates between rhBMP-2 and non-rhBMP-2 use in spine fusion at a high-volume tertiary orthopedic institution. Bone morphogenetic proteins are growth factors that play a critical role in bone development and proliferation. rhBMP-2 is a biological approved for select spinal fusion procedures to improve fusion rates. It is used in off-label indications. There are limited studies describing the use of rhBMP-2 in current practice. Patients who underwent spinal fusion from February 2016 to January 2022 were included. Surgery types were categorized by the approach listed as the primary procedure. A subgroup analysis was performed to assess differences in rhBMP-2 use for short and long fusions. Complications present within one year as ICD-10 codes were assessed. A total of 9809 patients were assessed. rhBMP-2 was used in 0.3% of ACF and 64.5% of PCF surgeries. Patients who underwent PCF with rhBMP-2 had higher rates of osteoporosis. rhBMP-2 was used in 96.1% of AL/TF, 69.2% of PL/TF, 97.4% of LLIF, and 24.1% of TLIF. Patients who underwent PL/TF with rhBMP-2 had higher rates of osteoporosis, mean age, former smoking status, and ASA class. There were increased rates of wound dehiscence in PL/TF with rhBMP-2. Patients who underwent long fusions with rhBMP-2 were more likely to have osteoporosis than those who underwent short fusions without rhBMP-2. We found that rhBMP-2 was used extensively in AL/TF and LLIF, frequently in PCF and PL/TF, occasionally in TLIF, and sparingly in ACF. While patterns of use differed in the cervical spine, mostly selecting for patients with risk factors for pseudarthrosis, this pattern of usage was only found in posterior lumbar and thoracic fusion. There was no obvious trend in complications associated with rhBMP-2 use.

This study aims to estimate the carbon footprint associated with external beam radiotherapy in a low- and middle-income country (LMIC) context, specifically at the Uganda Cancer Institute (UCI), and to evaluate whether sustainability should be a priority alongside treatment access in such radiation therapy settings. A carbon footprint analysis was conducted for patients treated for locally advanced cervical cancer at UCI between 2023 and 2024. The assessment included emissions from three key components: (1) patient travel to and from the facility, (2) pre-treatment imaging using CT and 2D simulation and (3) energy consumption by three Varian TrueBeam linear accelerators during treatment and idle times. Emission estimates were calculated using activity data and standard global warming potential (GWP) conversion factors. Patient travel emerged as a major contributor to carbon emissions due to the centralisation of services in Kampala and the lack of regional treatment centres. Energy use from LINACs and imaging contributed less significantly, owing in part to Uganda's low-carbon electricity grid powered largely by hydropower. CT scans generated approximately 0.105 kg CO2 per scan, and LINAC operations added modest emissions depending on usage patterns and machine idle time. While radiotherapy-related emissions in LMICs like Uganda are relatively modest compared to high-income countries, they are non-negligible and expected to rise with growing access to cancer care. Incorporating sustainability considerations into the future planning of radiotherapy infrastructure and service expansion is both feasible and necessary. Carbon-conscious planning should be integrated into decisions around siting and radiotherapy expansion to promote environmentally responsible cancer care in LMICs.

Short-video platforms, characterized by algorithmic curation and passive consumption, have emerged as dominant components of digital life. However, the associations between short-video platform use and health across different groups and usage behaviors remain understudied. This study investigates associations between short-video platform use and health, examining whether these relationships vary across health status, usage behaviors, and socioeconomic status. A cross-sectional study was conducted using multistage stratified sampling across eastern, central, and western China from July to September 2024. The inclusion criteria were age 18 years or older, ability to communicate effectively, and no cognitive disorders or mental disturbance. Of 7725 participants enrolled, 46.96% (n=3628) were male, and the average age was 65.49 (SD 8.39) years. The data were collected via face-to-face interviews using a structured questionnaire. Self-rated health and relative health deprivation (Kakwani index) were used to measure health. Quantile regression explored associations between whether using short-video platform and health varies across the health distribution, while linear regression examined associations of years, frequency, daily duration, and purpose diversity of short-video platform use with health. Moderating effect analysis explored the role of socioeconomic status in the relationship between the daily duration of use and health. Coefficients were tested using 2-tailed t tests, and statistical significance was defined as a 2-sided P value less than .05. Quantile regression revealed heterogeneous associations. Compared to nonusers, short-video platform users had better self-rated health at the 70th to 90th quantiles and lower relative health deprivation at the 10th to 30th quantiles. However, the users at the 10th quantile of self-rated health had worse self-rated health (β=-2.224, 95% CI -3.835 to -0.613). Longer engagement (≥3 y) correlated with lower relative health deprivation (β=1.970, 95% CI 0.308-3.632), while daily use of 1-4 hours was associated with poorer self-rated health (β=-3.385, 95% CI -4.872 to -1.898; β=-3.038, 95% CI -5.054 to -1.022) and higher relative health deprivation (β=0.035, 95% CI 0.021-0.050; P<.001; β=0.034, 95% CI 0.014-0.054). Compared to no purposeful use, using with 2 purposes was associated with better self-rated health (β=6.082, 95% CI 0.250-11.914) and lower relative health deprivation (β=-0.063, 95% CI -0.120 to -0.005). The association was stronger for use with 3 or more purposes. Socioeconomic status moderated the relationship between daily duration of use and health. This study provides a more specific investigation of how these associations vary across health strata and usage patterns. The findings reveal patterns of benefit and risk across population subgroups, underscoring that how and why individuals engage with platforms matter more than mere access or frequency. These insights necessitate targeted digital well-being policies that protect vulnerable groups, particularly those in poor health or with lower socioeconomic status. Furthermore, policies should actively encourage intentional, functionally grounded use to reduce health inequities and advance equitable digital inclusion.

Background : Unintended pregnancy remains a major public health problem worldwide, and access to effective emergency contraception is essential for reducing unsafe abortion and maternal morbidity. Although the World Health Organization recommends emergency contraceptive pills (ECPs) for over-the-counter availability, evidence on women’s knowledge, attitudes, and use of ECPs in Kosovo is limited. Objective : To assess knowledge, attitudes, and practices regarding emergency contraceptive pill use among women in Kosovo and to analyze the influence of sociodemographic and social factors on access and utilization. Methods : A descriptive cross-sectional study was conducted in Kosovo from June to August 2025. A self-administered questionnaire was distributed online and in community pharmacies to women of reproductive age who had previously used emergency contraceptive pills. The survey collected data on demographics, usage patterns, sources of information, side effects, and attitudes toward ECP use. Participation was voluntary and anonymous. Results : Most participants were aged 18–30, highly educated, and living in urban areas. The majority used ECPs no more than once per month, and 77% obtained the pill without a prescription. No significant association was found between non-prescription access and frequent use ( p = 0.9181). Knowledge scores were significantly higher among women who received information from pharmacists (M = 6.02) and doctors or clinics (M = 5.86) than among those who relied on the Internet or Google (M = 3.33) or social media (M = 2.83) ( F = 90.91, p &amp;lt; 0.001). Rural residence was associated with higher odds of shame-related avoidance when requesting ECPs (OR = 2.60, 95% CI: 1.39–4.89) and with a stronger influence of cultural and family norms on ECP use (OR = 4.57, 95% CI: 2.20–9.49). Commonly reported side effects included menstrual irregularities, abdominal pain, headache, and nausea. Conclusion : Emergency contraceptive pills in Kosovo are generally used responsibly, even when accessed without a prescription. However, major knowledge gaps and social stigma persist, particularly among women in rural areas and those relying on unverified online sources for information. Strengthening professional counseling in pharmacies and clinics, establishing national OTC guidelines, and expanding sexual education programs are essential to improve the safe and informed use of emergency contraception.

Background: Social media has become an integral part of daily life, influencing how adults communicate, seek information, and construct identities. However, there is growing concern about its psychological effects, especially regarding anxiety, depression, self-esteem, and sleep patterns. While substantial research has focused on adolescents, the impact of social media on adults' mental health remains under-explored. Objective: This study aims to address this gap by examining the psychological effects of social media use among adults, with particular attention to how different usage patterns—active engagement versus passive consumption—affect mental well-being. Methodology: A cross-sectional survey was conducted with 188 adult participants. Data were collected through an online questionnaire that assessed demographics, social media usage patterns, and psychological well-being (including anxiety, depression, self-esteem, and sleep disruption). Regression analysis was performed to determine the relationship between social media usage and mental health outcomes, controlling for demographic variables. Findings: The study found that while the amount of time spent on social media did not significantly affect anxiety, depression, self-esteem, or sleep disruption, social comparison was significantly associated with higher anxiety and depressive symptoms. FoMO also showed a trend toward increased anxiety, though not statistically significant. Additionally, passive social media consumption was linked to lower self-esteem, and both age and employment status were positively correlated with self-esteem. There were no significant relationships between social media use and sleep disruption. Conclusion: The study underscores the importance of understanding engagement patterns and internal psychological processes in the context of social media use. Future interventions should consider digital behavior patterns, promoting balanced engagement and mitigating the negative effects of comparison and FoMO. Further longitudinal studies are needed to establish causal relationships and explore long-term effects.

Temporal as well as age- and sex-related trends in human exposure to bisphenols, triclosan (TCS), triclocarban (TCC), and parabens were assessed using pooled urine samples (n = 150), representing approximately 14,000 individuals from the general Australian population, collected between 2012-13 and 2020-21. The arithmetic mean concentration of bisphenol A (BPA) decreased approximately by 50% from 2012-13 to 2020-21, while the bisphenol S (BPS) concentration doubled, indicating a gradual substitution of BPA with BPS in production and usage patterns. Both antimicrobial agents─TCS and TCC─exhibited decreasing trends from 2012-13 to 2020-21. In contrast, concentrations of the predominant parabens─methylparaben, ethylparaben, and propylparaben (PrP)─remained relatively stable over the past decade, reflecting their continued uses. TCS and TCC concentrations were generally higher in adults, whereas paraben concentrations were consistently higher in children. For BPA and BPS, all 2020-21 sample pools exceeded health-based reference values, indicating potential health concerns for the Australian population on average. Estimated daily intakes for PrP in samples of 0-15-year-old children frequently surpassed the reference value, suggesting a persistent exposure risk that has continued over the past decade. Overall, urinary concentrations of the target biomarkers in the Australian population were among the highest reported globally.

Isothiazolinones are employed in the preservation of cosmetic, consumer and industrial products, with the objective of preventing deterioration and spoilage. However, the utilization of isothiazolinones is associated with an elevated risk of developing contact allergy (CA). Herein, we assess the epidemiology of CA to isothiazolinones among dermatitis patients from year 2000 onwards. We systematically searched PubMed, Embase, and Web of Science from 1 January 2000 to 19 April 2025 yielding 115 studies comprising 1 514 781 dermatitis patients. The prevalence of CA to methylchloroisothiazolinone/methylisothiazolinone (MCI/MI) was 4.58%, methylisothiazolinone (MI) was 5.48%, and benzisothiazolinone (BIT) was 2.09%. The clinical relevance ranged from 60.1% for MCI/MI, 55.6% for MI, and 35.3% for BIT. Asia and North and South America exhibited the highest rates of CA to isothiazolinones, whereas Europe showed lower rates. These findings underscore the efficacy of proactive risk management for post-marketed substances such as MI, underscoring substantial regional variations in usage patterns, which are contingent on the strictness or permissiveness of their incorporation into everyday consumer products. There is an indication of a decline, particularly regarding MI and MCI/MI. However, there has been an increase in the use of substances such as BIT, which necessitates enhanced surveillance measures.

Abstract This study investigates how university students engage with generative artificial intelligence (GenAI), specifically ChatGPT, when completing knowledge-based academic tasks across six courses and two institutions. By comparing performance and perceptions in engineering and non-engineering subjects, the study examines whether students can use GenAI effectively without prior training and to what extent such tools meaningfully support learning. The work also explores how these findings may inform future research on accessible and inclusive learning design. A multi-method design was employed with 254 undergraduate and graduate students assigned to experimental groups (allowed to use ChatGPT) or control groups (restricted to traditional, non-GenAI resources). Quantitative analyses included descriptive statistics, a general linear model, and non-parametric comparisons, complemented by a topic-based analysis of open-ended survey responses addressing students’ perceptions, usage patterns, and desired functionalities. Students in the experimental groups generally obtained higher scores, with significant improvements in several subjects (e.g., computer systems administration, informatics, childhood disorders). A weak but significant positive correlation emerged between iterative engagement with ChatGPT (edits) and academic performance. Qualitative analysis showed that students valued ChatGPT for fast information access, clarification of concepts, and organizational support, while also expressing concerns about inaccuracies, overreliance, and limitations of free versions. GenAI can enhance student performance when used actively and reflectively, although its effectiveness varies by disciplinary context. The findings highlight the need for explicit AI-literacy instruction to ensure critical and responsible use. While the study does not directly address disability or accessibility outcomes, the qualitative patterns suggest potential intersections with inclusive and multimodal learning design, pointing to promising avenues for future research.

Purpose This study aims to explore the temporal evolution of user-generated popular tags in Flickr, a collaborative image tagging system, through the lens of facet classification. It aims to uncover how tagging behaviors reflect shifts in technology, culture and individual cognition and how deep learning techniques can enhance our understanding of the semantic structures within folksonomies. Design/methodology/approach Popular tags from three benchmark years (2006, 2010 and 2015) were collected and manually categorized using a faceted classification scheme rooted in Ranganathan’s model. To augment this analysis, we applied autoencoder-based deep learning models to extract latent semantic representations and pretrained word embeddings to measure semantic similarity. This hybrid approach enabled both qualitative categorization and quantitative analysis of temporal-semantic patterns in tag usage. Findings The study found that over 80% of the most popular tags were consistently associated with spatial, personality and material facets. Temporal analysis revealed a marked shift from time-based tags to more self-expressive, personality-oriented tags, reflecting users’ growing inclination toward individualism and identity expression. Location-based tags remained persistent across all years, suggesting the global, place-based nature of user engagement. Deep learning – enhanced analysis revealed semantic groupings and confirmed that tagging behavior evolves in alignment with technological and cultural developments. Originality/value This study offers a novel integration of traditional facet analysis (colon classification) and deep learning to model the dynamics of user-generated metadata on social image platforms. It advances understanding of how folksonomies, when enriched by neural representation learning, can serve as both mirrors of cultural shifts and tools for more adaptive, user-centered metadata systems. The approach contributes methodologically to digital classification research and provides insights into the cognitive and social factors shaping online tagging behavior.

The Role of a Complex Public Facility as a Place for Young People: An Analysis Based on Youth Usage Patterns and Place Evaluation

The digital payments adoption trends among customers of India Post Payments Bank (IPPB) and analyzes the factors influencing their usage of digital financial services. The research focuses on understanding customer awareness, accessibility, convenience, security perceptions, and satisfaction with digital payment platforms offered by IPPB. It also explores how demographic factors such as age, education, and income level affect the adoption and usage patterns of digital transactions among customers, particularly in rural and semi-urban areas. The study highlights the role of digital payment systems in promoting financial inclusion and reducing dependence on cash transactions. It identifies key challenges such as lack of digital literacy, security concerns, and technological barriers that limit the effective use of digital payment services. The findings aim to provide insights for improving digital banking services, enhancing customer awareness, and strengthening policy measures to support the growth of digital payments under the guidance of Reserve Bank of India. Overall, the research contributes to understanding customer behavior and supports the development of efficient and inclusive digital payment systems. The rapid growth of digital payment systems has transformed the Indian banking and financial services sector. India post payments bank (IPPB), established with the objective of financial inclusion, plays a crucial role in promoting digital payments among rural and semi-urban populations

Digital hoarding is a newly emerging phenomenon in academia, with researchers having explored it from multiple disciplinary perspectives in recent years. However, empirical research from the perspective of communication studies is limited. Notably, digital hoarding behaviours are closely linked to individuals’ media usage patterns. Accordingly, our research grounded in theories of Social Cognition and Overconfidence Bias, Technology Acceptance Model, investigates the relationship between new media literacy and digital hoarding behaviours among Chinese youth ( N = 399, M age = 27.5). We also introduce information overload and information anxiety as two mediating variables that may function as explanatory mechanisms. The findings indicate that higher levels of new media literacy are associated with more pronounced digital hoarding behaviour, while greater new media literacy is also linked to lower levels of information overload and information anxiety. Furthermore, higher levels of information overload and information anxiety correspond to more severe digital hoarding behaviours. In addition, a positive relationship exists between information overload and information anxiety. Information overload mediates the relationship between new media literacy and digital hoarding behaviour, reversing the relationship so that increased new media literacy leads to a reduction in perceived information overload, which subsequently results in less digital hoarding behaviour. Our study offers empirical evidence from a new media literacy perspective, contributing to the research on digital hoarding, providing insights into young people’s information management practices.

Abstract This article investigates linguistic variation among the dialects of Rabbinic Hebrew, specifically, between the Hebrew of the Tannaitic period (ending ca. 300 Ce) and that of the Talmudic (Amoraic) period (ca. 300—600 Ce), including both Western (a.k.a. Palestinian) and Babylonian varieties. It identifies an isogloss centered on the idioms and (‘departed [from the world]’, and ‘at the time of his departure [from the world]’, respectively), used to denote death. Rabbinic sources exhibit dialectal variation in the use of these expressions. Through critical analysis of the textual evidence, the study disentangles cases of textual contamination and clarifies distinct usage patterns within each dialectal tradition. In addition to identifying a new isogloss, the article offers a case study demonstrating the importance of rigorous philological scrutiny in the dialectological study of Rabbinic Hebrew.

Abstract Purpose This research examines the feasibility and effectiveness of detecting ransomware attacks in quasi real-time by leveraging AI-based monitoring of centralized file operations. As ransomware continues to evolve in speed and complexity, traditional endpoint protection mechanisms often fall short, especially in environments with limited client-side defense. The goal is to determine whether lightweight, server-side monitoring combined with machine learning can provide a quasi real-time and accurate detection mechanism without relying on client instrumentation. Applied methodology A virtualized SME (small- and medium-sized enterprise) infrastructure was developed, simulating realistic user behavior through automated file operations and randomly triggered attacks by ransomware samples (Ryuk, NotPetya, Lockbit, Teslacrypt, and WannaCry). A nanosecond-scale time-stamped logging mechanism was implemented using Fluentbit and InfluxDB to track file creation, renaming, and deletion events. Five classic and ensemble machine learning models (Random Forest, Decision Tree, SVM, AdaBoost, XGBoost) were trained and optimized using supervised learning on aggregated file operation sequences using one-second intervals. Results The comparative evaluation of the models showed that all five achieved reliable detection performance, but XGBoost outperformed the others with a sensitivity of 91.87% and prediction speeds below 1 ms. The model identified ransomware activity during the early phases of execution in the majority of test cases, even when operating in a high-noise environment with real-world file usage patterns. Conclusions Monitoring centralized file activity offers a practical and efficient means for detecting ransomware attacks without requiring access to client systems or process-level telemetry. By using only three simple file operation metrics and binary classification, the system does not require complex, resource-intensive behavioral models. Contribution This study presents a scalable, quasi real-time detection framework that complements existing security layers and is especially valuable in scenarios where endpoint protection is weak or inconsistent. The findings highlight an alternative direction in ransomware defense that emphasizes simplicity, performance, and deployability.

This study investigated the relationship between library retrieval tools and the use of information resources among students of Niger Delta University, Bayelsa State. A correlational research design was adopted, and 600 registered students, representing 10 per cent of the population, were selected through purposive and random sampling. Data were gathered using the Library Retrieval Tools and Students’ Library Usage of Information Resources Questionnaire (LRTSLUIRQ), which had a Cronbach’s alpha reliability ranging from 0.76 to 0.81. Pearson Product-Moment Correlation at the 0.05 level of significance was used to analyze the data. The independent variables were Online Public Access Catalogue (OPAC), library databases, the library website, and institutional repositories, while the dependent variable was the use of information resources. The results showed moderate utilization of all retrieval tools, with mean scores ranging from 13.00 to 13.68. Among these, the library website recorded the highest mean score (M = 13.68, SD = 5.26). Correlation analysis revealed strong and positive relationships between each retrieval tool and the use of information resources: OPAC (r = .696, p &lt; .01), library databases (r = .681, p &lt; .01), library website (r = .705, p &lt; .01), and institutional repositories (r = .674, p &lt; .01). The findings led to the rejection of the null hypotheses and confirmed that effective use of retrieval tools significantly improves students’ access to and use of academic resources. The study recommends user training, continuous system improvement, and institutional support to maximize the benefits of retrieval tools in academic libraries