Quantitative Datasets Research Articles

Genomics-driven integrative analysis highlights immune-related plasma proteins for psychiatric disorders

BackgroundGenome-wide association studies (GWAS) have identified numerous variants associated with psychiatric disorders. However, it remains largely unknown on how GWAS risk variants contribute to psychiatric disorders. MethodsThrough integrating two largest, publicly available, independent protein quantitative trait loci datasets of plasma protein and nine large-scale GWAS summary statistics of psychiatric disorders, we first performed proteome-wide association study (PWAS) to identify psychiatric disorders-associated plasma proteins, followed by enrichment analysis to reveal the underlying biological processes and pathways. Then, we conducted Mendelian randomization (MR) and Bayesian colocalization (COLOC) analyses, with both discovery and parallel replication datasets, to further identify protein-disorder pairs with putatively causal relationships. We finally prioritized the potential drug targets using Drug Gene Interaction Database. ResultsPWAS totally identified 112 proteins, which were significantly enriched in biological processes relevant to immune regulation and response to stimulus including regulation of immune system process (adjusted P = 1.69 × 10−7) and response to external stimulus (adjusted P = 4.13 × 10−7), and viral infection related pathways, including COVID-19 (adjusted P = 2.94 × 10−2). MR and COLOC analysis further identified 26 potentially causal protein-disorder pairs in both discovery and replication analysis. Notably, eight protein-coding genes were immune-related, such as IRF3, CSK, and ACE, five among 16 druggable genes were reported to interact with drugs, including ACE, CSK, PSMB4, XPNPEP1, and MICB. ConclusionsOur findings highlighted the immunological hypothesis and identified potentially causal plasma proteins for psychiatric disorders, providing biological insights into the pathogenesis and benefit the development of preventive or therapeutic drugs for psychiatric disorders.

Understanding and improving the quality of primary care for people in prison: a mixed-methods study

Background People in prison are generally in poorer health than their peers in the community, often living with chronic illness and multimorbidity. Healthcare research in prisons has largely focused on specific problems, such as substance use; less attention has been paid to conditions routinely managed in primary care, such as diabetes or hypertension. It is important to understand how primary care in prisons is currently delivered in the United Kingdom and how it can be improved, in order to reduce health inequalities. Objective To understand the quality of primary care in prison, including gaps and variations in care, in order to recommend how quality of prison health care can be improved. Design A mixed-methods study with six interlinked work packages. Setting Predominantly the North of England. Methods Between August 2019 and June 2022, we undertook the following work packages: (1) International scoping review of prison healthcare quality indicators. (2) Stakeholder consensus process to identify United Kingdom focused prison healthcare quality indicators. (3) Qualitative interview study with 21 people who had been in prison and 22 prison healthcare staff. (4) Quantitative analysis of anonymised, routinely collected data derived from prison healthcare records (~ 25,000 records across 13 prisons). (5) Stakeholder deliberation process to identify interventions to improve prison health care. (6a) Secondary analysis of the qualitative data set, focusing on mental health and (6b) analysis of the quantitative data set, focusing on health care of three mental health subgroups Findings Our scoping review found predominantly only papers from the United States of America and of variable rigour with the main finding being that performance measurement is very challenging in the prison healthcare setting. In collaboration with stakeholders, we prioritised, refined and applied a suite of 30 quality indicators across several healthcare domains. We found considerable scope for improvement in several indicators and wide variations in indicator achievement that could not be attributed to differences in prison population characteristics. Examples of indicators with scope for improvement included: diabetes care, medicines reconciliation and epilepsy review and control. Longer length of stay in prison was generally associated with higher achievement than shorter stays. Indicator achievement was generally low compared to that of community general practice. We found some encouraging trends and relatively good performance for a minority of indicators. Our qualitative interviews found that quality of health care is related to factors that exist at several levels but is heavily influenced by organisational factors, such as understaffing, leading to a reactive and sometimes crisis-led service. Our stakeholder deliberations suggested opportunities for improvement, ideally drawing on data to assess and drive improvement. Our mental health work package found that coded mental illness had mixed associations with indicator achievement, while the interviews revealed that mental distress is viewed by many as an inevitable facet of imprisonment. Limitations Our analyses of indicator achievement were limited by the quality and coverage of available data. Most study findings are localised to England so international applicability may differ. Conclusions Marked variations in the quality of primary care in prisons are likely to be attributable to the local organisation and conditions of care delivery. Routinely collected data may offer a credible driver for change. Study registration This study is registered at researchregistry.com (Ref: 5098). Funding This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/05/26) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 46. See the NIHR Funding and Awards website for further award information.

Diurnal Cycles of Cloud Properties and Precipitation Patterns over the Northeastern Tibetan Plateau During Summer

In the context of rising temperatures and increasing humidity in Northwest China, substantial gaps remain in understanding the mechanisms of land–atmosphere cloud–precipitation coupling across the northeastern Tibetan Plateau (TP), Loess Plateau (LP), and Huangshui Valley (HV). This study addresses these gaps by investigating cloud properties and precipitation patterns utilizing the Fengyun-4 Satellite Quantitative Precipitation Estimation Product (FY4A-QPE) and ERA5 datasets. We specifically focus on Lanzhou, a pivotal city within the LP, and Xining, which epitomizes the HV. Our findings reveal that diurnal variations in precipitation are significantly less pronounced in the eastern regions compared to northeastern TP. This discrepancy is attributed to marked diurnal fluctuations in convective available potential energy (CAPE) and wind shear between 200 and 500 hPa. While both cities share similar wind shear patterns and moisture transport directions, Xining benefits from enhanced snowmelt and effective water retention in surrounding mountains, resulting in higher precipitation levels. Conversely, Lanzhou suffers from moisture deficits, with dry, hot winds exacerbating the situation. Notably, precipitation in Xining is strongly correlated with CAPE, influenced by diurnal variability, and intensified by valley and lake–land breezes, which drive afternoon convection. In contrast, Lanzhou’s precipitation exhibits a weak relationship with CAPE, as even elevated values fail to generate significant cloud formation due to insufficient moisture. The ongoing trends of warming and humidification may lead to improved precipitation patterns, especially in the HV, with potential ecological benefits. However, concentrated rainfall during summer afternoons and midnights raises concerns regarding extreme weather events, highlighting the susceptibility of the HV to geological hazards. This research underscores the need to further explore the uncertainties inherent in precipitation dynamics in these regions.

Data-independent acquisition proteomic analysis of the brain microvasculature in Alzheimer’s disease identifies major pathways of dysfunction and upregulation of cytoprotective responses

Brain microvascular dysfunction is an important feature of Alzheimer’s disease (AD). To better understand the brain microvascular molecular signatures of AD, we processed and analyzed isolated human brain microvessels by data-independent acquisition liquid chromatography with tandem mass spectrometry (DIA LC–MS/MS) to generate a quantitative dataset at the peptide and protein level. Brain microvessels were isolated from parietal cortex grey matter using protocols that preserve viability for downstream functional studies. Our cohort included 23 subjects with clinical and neuropathologic concordance for Alzheimer’s disease, and 21 age-matched controls. In our analysis, we identified 168 proteins whose abundance was significantly increased, and no proteins that were significantly decreased in AD. The most highly increased proteins included amyloid beta, tau, midkine, SPARC related modular calcium binding 1 (SMOC1), and fatty acid binding protein 7 (FABP7). Additionally, Gene Ontology (GO) enrichment analysis identified the enrichment of increased proteins involved in cellular detoxification and antioxidative responses. A systematic evaluation of protein functions using the UniProt database identified groupings into common functional themes including the regulation of cellular proliferation, cellular differentiation and survival, inflammation, extracellular matrix, cell stress responses, metabolism, coagulation and heme breakdown, protein degradation, cytoskeleton, subcellular trafficking, cell motility, and cell signaling. This suggests that AD brain microvessels exist in a stressed state of increased energy demand, and mount a compensatory response to ongoing oxidative and cellular damage that is associated with AD. We also used public RNAseq databases to identify cell-type enriched genes that were detected at the protein level and found no changes in abundance of these proteins between control and AD groups, indicating that changes in cellular composition of the isolated microvessels were minimal between AD and no-AD groups. Using public data, we additionally found that under half of the proteins that were significantly increased in AD microvessels had concordant changes in brain microvascular mRNA, implying substantial discordance between gene and protein levels. Together, our results offer novel insights into the molecular underpinnings of brain microvascular dysfunction in AD.

PhoXplex: Combining Phospho-enrichable Cross-Linking with Isobaric Labeling for Quantitative Proteome-Wide Mapping of Protein Interfaces.

Integrating cross-linking mass spectrometry (XL-MS) into structural biology workflows provides valuable information about the spatial arrangement of amino acid stretches, which can guide elucidation of protein assembly architecture. Additionally, the combination of XL-MS with peptide quantitation techniques is a powerful approach to delineate protein interface dynamics across diverse conditions. While XL-MS is increasingly effective with isolated proteins or small complexes, its application to whole-cell samples poses technical challenges related to analysis depth and throughput. The use of enrichable cross-linkers has greatly improved the detectability of protein interfaces in a proteome-wide scale, facilitating global protein-protein interaction mapping. Therefore, bringing together enrichable cross-linking and multiplexed peptide quantification is an appealing approach to enable comparative characterization of structural attributes of proteins and protein interactions. Here, we combined phospho-enrichable cross-linking with TMT labeling to develop a streamline workflow (PhoXplex) for the detection of differential structural features across a panel of cell lines in a global scale. We achieved deep coverage with quantification of over 9000 cross-links and long loop-links in total including potentially novel interactions. Overlaying AlphaFold predictions and disorder protein annotations enables exploration of the quantitative cross-linking data set, to reveal possible associations between mutations and protein structures. Lastly, we discuss current shortcomings and perspectives for deep whole-cell profiling of protein interfaces at large-scale.

Can AI Get a Degree in Geoscience? Performance Analysis of a GPT-Based Artificial Intelligence System Trained for Earth Science (GeologyOracle)

Generative artificial intelligence systems based on the GPT model have shown groundbreaking capabilities in producing scientific texts, revolutionising how geoscientists research and teach. However, there is a noticeable absence of generative AI systems tailored specifically for geoscience, and the efficacy of GPT technology has not been examined within the Earth Science realm. To fill these gaps, we propose a new artificial intelligence system (GeologyOracle) built upon the GPT-4o model and trained on Earth Science data. It is designed to simulate a conversation with a geoscientist, having the capabilities to analyse geologic datasets, suggest new geoscience hypotheses, explain Earth-Science concepts, and interpret geosites. To evaluate the performance of GeologyOracle, the system was tested with 152 geoscience questions provided and evaluated by a panel of geoscience academics on a scale of 0–10. Performance analysis revealed that 79.6% of the answers scored equal to or above the passing mark of 5, with a tendency to deliver high-quality responses (mean: 6.5; median = 7; interquartile range: 5–8). The results demonstrate that GeologyOracle is effective in performing complex geoscience tasks, such as identifying rocks, fossils, and minerals, and interpreting outcrop, core data, and quantitative datasets. The new AI system has exhibited noteworthy ability in the interpretation of internationally-acknowledged geosites situated within geoparks and nature reserves. The performance of the AI system is comparable to that of trained geoscience specialists, suggesting its potential as an assistant in various geoscience fields, including structural geology, palaeontology, geomorphology, sedimentology, and economic geology. While AI does not render geoscientists obsolete, it offers significant potential for accelerating scientific discovery, automating geoscience research, and assisting educators, students, and geotourists.

It’s not just about jobs: The significance of employment quality for participation in political violence and protests in selected Arab Mediterranean countries

It is often proposed that the young unemployed are more likely to engage in political violence, conflicts, and protests. One problem in studying the unemployed – especially in the Global South – are the blurred lines between the unemployed, the employed, and those working in the informal sector. Further, the employed are a heterogeneous group so employment quality might also play an important role. To tackle these issues, this study uses a new quantitative dataset, which covers youth in five Middle Eastern and North African countries: Algeria, Egypt, Lebanon, Morocco, and Tunisia. These data provide considerably more fine-grained information about the employment situations of the respondents than the datasets previously used. The study investigates separately two forms of political participation: in political violence and in demonstrations. The regression analyses show that there is no clear difference between the young unemployed and the young employed in their likelihood to participate in the studied political activities. However, some features related to employment matter. Those whose employment status is ambiguous are substantially more likely to participate in demonstrations and political violence than the employed. Among those who work, those who are dissatisfied with their work and those who work fewer hours participate more often in these activities. Income on its own does not seem to have an effect; however, those who have more assets are more likely to participate, and compared to those who feel themselves middle income, those feeling rich or poor are more likely to engage in political violence and demonstrations. The results suggest that instead of thinking in terms of a dichotomy of the employed and unemployed, more emphasis should be placed on understanding the variety of employment situations and employment quality and their impact on political instability.

We need to rethink the way we identify diamond open access journals in quantitative science studies

Abstract With the announcement of several new diamond open access (OA) related initiatives and the creation of the Global Summit on Diamond Open Access, diamond OA is now at the forefront of the OA movement. However, while working on our recent Quantitative Science Studies publication and data sets, we noticed that temporarily waiving article processing charges (APCs) was a commonly used strategy by big publishers for some of their journals. In the absence of an index of diamond journals, most studies have operationalized the identification of diamond journals as a subset of gold journals that do not charge an APC. While this is a pragmatic approach, we fear that it could undermine the value of the research in understanding what we believe is more commonly understood by diamond OA. This letter discusses the need for bibliometric research to apply more nuance in how it operationalizes diamond OA beyond the absence of APCs. We call on the publishing sector to be more transparent in the costs of publishing. Ultimately, we argue that transparency and a long-term commitment to no-APC publishing are necessary for diamond OA to succeed, and that the research community needs to apply this standard when seeking to understand the model.

Putative retina metal/metalloid-binding proteins: molecular functions, biological processes and retina disease associations.

The mammalian retina contains high amounts of metals/metalloid-selenium. Their dyshomeostases are associated with certain retinal diseases. We carried out this bioinformatics study to identify the relationships between putative retinal metal/selenium binding proteins, their molecular functions, and biological processes. Identification of putative mouse metal/selenium binding proteins was based on known binding motifs, domains, patterns, and profiles. Annotations were obtained from Uniprot keywords 'metal binding', 'metal ion co-factors', 'selenium proteins'. Protein functions were estimated by associative frequency with key words in UniProt annotations. The raw data of five mouse proteomics PRIDE datasets (available to date) were downloaded and processed with Mascot against the mouse taxa of Uniprot (SwissProt/Trembl) and MaxQuant (version 1.6.10.43) for qualitative and quantitative datasets, respectively. Clinically relevant variants were evaluated using archives and aggregated information in ClinVar. The 438 proteins common to all the retina proteomics datasets were used to identify over-represented Gene Ontology categories. The putative mouse retinal metal/metalloid binding proteins identified are mainly involved in: (1) metabolic processes (enzymes), (2) homeostasis, (3) transport (vesicle mediated, transmembrane, along microtubules), (4) cellular localization, (5) regulation of signalling and exocytosis, (6) organelle organization, (7) (de)phosphorylation, and (8) complex assembly. Twenty-one proteins were identified as involved in response to light stimulus and/or visual system development. An association of metal ion binding proteins rhodopsin, photoreceptor specific nuclear receptor, calcium binding protein 4 with disease-related mutations in inherited retinal conditions was identified, where the mutations affected an area within or in close proximity to the metal binding site or domain. These findings suggest a functional role for the putative metal/metalloid binding site in retinal proteins in certain retinal disorders.

Back to Industry—Evaluating Women’s Return to Chartered Accreditation Post-Maternity in the Built Environment Sector Professions

Efforts have been made to improve gender diversity in the built environment professions. This sector continues to experience growth restrictions due to skill shortages. Some progress has been made at the entry level; however, the retention of women in professional roles within this sector continues to present a challenge. Support for women during maternity, upon return to work and while working with family has been identified as a barrier to women’s progression in this sector. Professional bodies are uniquely placed to support their female members. Therefore, this study had two aims: to examine current professional body support for members during and after maternity leave and to examine the experiences of female professionals, who have taken maternity leave whilst holding membership in a built environment professional body. This study adopted an embedded, mixed-method design, using a secondary, qualitative data set to augment the primary, quantitative data set, within one phase. Surveys were distributed directly to professional bodies and to professionals via social media (LinkedIn). The survey of the professional bodies identified a varied approach to maternity support. The professional member survey identified a lack of awareness of available support, and generally the need for more support during maternity and on return to work. In summary, professional bodies in the built environment could improve maternity support for members by improving communication and achieving parity in support across the various disciplines.

Healthcare Professionals' Perspectives on the Use of Standing Frames for Children Diagnosed With Cerebral Palsy: An Explanatory Mixed Methods Study.

Standing frames are commonly used by healthcare professionals in their practice with children with cerebral palsy (CP) who do not have an independent standing function. A better understanding of healthcare professionals' attitudes and experiences with standing frames may impact practice and rehabilitation. Therefore, this study aimed to investigate the standing frame practice among healthcare professionals and expand their attitude and experience with the use of standing frames for children with CP. This is an explanatory sequential mixed methods study. A cross-sectional survey was conducted, providing quantitative data on 210 healthcare professionals' use of standing frames. The quantitative data were descriptively analysed. Subsequently, the results from the survey were followed up with five focus group interviews of healthcare professionals (n = 14). The qualitative data were analysed using thematic analysis, enabling integration between the quantitative and qualitative data. When quantitative and qualitative data are integrated, expansion between the two datasets occurred. The quantitative dataset emphasised the use of GMFCS levels as a guideline for recommending standing frames, whereas the qualitative data showed that the healthcare professionals' recommendations were based on individual needs. Furthermore, the healthcare professionals expanded the quantitative data, showing that the healthcare professionals' considerations regarding age and dosage were based on clinical experience, and saw the standing frame as having many benefits. The healthcare professionals had a child-centred approach, where the child's need for using a standing frame was assessed based on the functional level, stage of development, cognitive level and clinical assessment. All of these considerations showed that the use of standing frames for children with CP was individualised, thereby making it difficult to make unified descriptions.

Blind image deblurring with a difference of the mixed anisotropic and mixed isotropic total variation regularization

This paper proposes a simple model for image deblurring with a new total variation regularization. Classically, the L1-21 regularizer represents a difference of anisotropic (i.e. L1) and isotropic (i.e. L21) total variation, so we define a new regularization as Le-2e, which is the weighted difference of the mixed anisotropic (i.e. L0 + L1 = Le) and mixed isotropic (i.e. L0 + L21 = L2e), and it is characterized by sparsity-promotingand robustness in image deblurring. Then, we merge the L0-gradient into the model for edge-preserving and detail-removing. The union of the Le-2e regularization and L0-gradient improves the performance of image deblurring and yields high-quality blur kernel estimates. Finally, we design a new solution format that alternately iterates the difference of convex algorithm, the split Bregman method, and the approach of half-quadratic splitting to optimize the proposed model. Experimental results on quantitative datasets and real-world images show that the proposed method can obtain results comparable to state-of-the-art works.

Investigating Professional Analyst Strategies in Immersive Space to Think.

Existing research on sensemaking in immersive analytics systems primarily focuses on understanding how users complete analysis within these systems with quantitative and qualitative datasets. However, these user studies mainly concentrate on understanding analysis styles and methodologies from a predominantly novice user study population. While this approach provides excellent initial insights into what users may do within IA systems, it fails to address how professionals may utilize an immersive analytic system for analysis tasks. In our work, we build upon an existing immersive analytics concept - "Immersive Space to Think" to understand how professional user populations differ from novice users in immersive analytic system usage. We conducted a user study with 11 professional intelligence analysts who completed three analysis sessions each. Using our results from this study, we provide deep analysis into how professional users complete sensemaking within immersive analytic systems, compare our findings to previously published findings with a novice user population, and provide insights into how to develop better IA systems to support the professional analyst's strategies within these systems.

Describing the status quo of person-centred dementia care in different types of care units in German nursing homes: A convergent mixed methods study

BackgroundThe policies and mission statements of nursing homes support the implementation of person-centred dementia care. The Dementia Policy Questionnaire assesses the content of person-centred dementia care in policies. To date, it is unknown whether these policies exist exclusively in dementia care units and whether the policies are consistent with the mission statements of nursing homes. ObjectiveWe aimed to (1) investigate nursing home care unit types regarding the existence of policies measured by the Dementia Policy Questionnaire, (2) explore whether these policies are addressed in the mission statements of the nursing homes, and (3) integrate both results. DesignThis is a convergent mixed methods study performed with a quantitative and qualitative dataset that was collected in the BeStaDem survey (2020). SettingThe BeStaDem survey included licensed nursing homes in Germany. ParticipantsA total of 134 nursing home administrators provided informed consent to participate in the BeStaDem survey. MethodsFor quantitative data, we performed Fisher's exact test to identify differences in the Dementia Policy Questionnaire item distribution of several types of care units (aim 1). To support the results of Fisher's exact test, we additionally applied logistic regression analysis. For qualitative data, we analyzed the mission statements deductively with the qualitative content analysis method (aim 2). For integration, we used a convergent triangulation approach (aim 3). ResultsThe quantitative data collected from 134 German nursing homes show significant associations among person-centred dementia care policies, such as behavior assessment, and nursing homes with dementia care units. Regarding the qualitative data, of the 60 mission statements in total, eight mission statements of nursing homes with dementia care units exclusively address aspects such as dementia-specific interventions. The convergent triangulation approach shows that the answers given by the nursing homes in the quantitative survey are not always consistent with what they address in their mission statements. ConclusionsNursing homes with dementia care units provide more person-centred dementia care policies than other care unit types do but mostly do not address these aspects in their mission statements. The implementation of person-centredness benefits from the existence of policies and mission statements if nursing homes clearly address what is meant by person-centred dementia care in their nursing home.

What’s Art Got to Do With It? Using Visual Thinking Strategies to Develop Critical Thinking Skills

Visual Thinking Strategies (VTS) is an experiential exercise readily adapted to the management classroom. Through this exercise, instructors use a structured process to help students develop and apply critical thinking skills, with a focus on clearly articulating a concept, explaining their reasoning and use of evidence to inform their claim, interrogating assumptions, and exploring a range of perspectives. The exercise involves guiding students to interpret first visual artwork and then other texts through the use of guiding questions and specific facilitation strategies, followed by a practice and a debriefing. Additional adaptations discussed in the appendix, such as using VTS with graphic organizers from a course text, the landing page of a multinational company website, a SWOT analysis, or quantitative datasets, are a testament to the versatility and flexibility of this strategy in building students’ critical thinking skills across management contexts.

A structured course of disease dataset with contact tracing information in Taiwan for COVID-19 modelling

The COVID-19 pandemic has flooded open databases with population-level data. However, individual-level structured data, such as the course of disease and contact tracing information, is almost non-existent in open databases. Publish a structured and cleaned COVID-19 dataset with the course of disease and contact tracing information for easy benchmarking of COVID-19 models. We gathered data from Taiwanese open databases and daily news reports. The outcome is a structured quantitative dataset encompassing the course of the disease of Taiwanese individuals, alongside their contact tracing information. Our dataset comprises 579 confirmed cases covering the period from January 21, to November 9, 2020, when the original SARS-CoV-2 virus was most prevalent in Taiwan. The data include features such as travel history, age, gender, symptoms, contact types between cases, date of symptoms onset, confirmed, critically ill, recovered, and dead. We also include the daily summary data at population-level from January 21, 2020, to May 23, 2022. Our data can help enhance epidemiological modelling.

Changes in wild meat hunting and use by rural communities during the COVID‐19 socio‐economic shock

AbstractThere is limited quantitative evidence of the effects of socio‐economic shocks on biological resource use. Focusing on wild meat hunting, a substantial livelihood and food source in tropical regions, we evaluated the impacts of the shock from Nigeria's coronavirus disease (COVID‐19) lockdown on species exploitation around a global biodiversity hotspot. Using a 3‐year quantitative dataset collected during and after the lockdown (covering 1008 hunter‐months) and matching by time of year, we found that successful hunting trip rates were more frequent during the lockdown, with a corresponding increase in the monthly number, mass, and value of animals caught. Moreover, hunters consumed a larger proportion of wild meat and sold less during lockdown, compared to non‐lockdown periods. These results suggest that local communities relied on wild meat to supplement reduced food and income during the lockdown, buffering the COVID‐19's socio‐economic shock. Our findings also indicate that wild species may be especially vulnerable to increased hunting pressure during socio‐economic shocks.

Corporate Governance and the Value Relevance of Financial Information in Tanzanian Savings and Credit Cooperatives: A Panel-Data Approach

The study examined the influence of corporate governance on the relevance of financial information towards the value of Savings and Credit Cooperative Societies (SACCOS) in Tanzania. Thus far, evidence on how corporate governance influences the relevance of financial information in cooperative societies is limited globally, notably in emerging economies. Therefore, this research contributes to the body of knowledge by extending the application of agency theory to determine this relationship among variables. The study specifically employed a quantitative panel data set of 202 SACCOs from 2013 to 2020 that was gathered from yearly financial reports and processed through descriptive analysis and regression models. Descriptive statistics demonstrate that the SACCOs' value in Tanzania is increasing. Empirical results show a significant positive relationship between earnings financial information and the value of SACCOS; the book value of equity financial information insignificantly influences the value of SACCOS. The findings deliver empirical and theoretical backing for the notion that board size, skills and supervisory committee skills have a significant impact on the relevance of financial information towards the value of the firm. However, the examination showed no proof that the number of meetings affected the relevance of financial information. This implies that Policymakers should make reforms that will enable SACCOs to improve the quality of financial information and widen the publication of financial reports through effective corporate governance, including the emphasis on online publications.

Library resources constraints, frustration, and user behavior: An empirical library operations study.

The lack of requisite library resources has an enormous effect on academic life in most universities. While previous studies have suggested that the lack of resources such as textbooks affects academic success, this study seeks to provide empirical evidence on the chain effect of the lack of recommended textbooks in universities. The study uses a quantitative dataset from 636 students from five public universities in Ghana collected using well-structured questionnaires. The study adopts exploratory factor analysis, confirmatory factor analysis, and partial least squares structural equation modeling (PLS-SEM) to analyze the measurement and structural models. The study concludes that limited library resources (such as recommended textbooks) frustrate library users and eventually birth antisocial behaviors such as stealing, hiding, and eroding books (or pages). This study highlights the significance of providing adequate library resources. It also guides library managers, policymakers, and scholars to manage library resources effectively.

The Effect of Brand Awareness on Decisive Customer Intention and Purchase Behavior of Shopee Gen Z Customers

The pervasive influence and evolution of social media continue to reshape societal dynamics. Accordingly, the current study endeavors to scrutinize whether brand awareness (BA), brand knowledge (BK), and brand preference (BP) serve as independent variables influencing customer intention (CI), with Purchase Decision (PD) serving as the dependent variable with CI as mediating factor in the relationship between BA, BK, BP, and PD. Against the backdrop of the Shopee marketplace, the study was conducted through a survey targeting Shopee customers specifically generation Z or millennials who had a history of purchasing or frequent platform usage in West Java, Indonesia. The quantitative dataset was compiled from responses provided by 91 participants, employing purposive sampling technique, the collected data were subjected to Structural Equation Modeling (SEM) using SmartPLS software for analysis. The outcomes indicated that BA and BK had insignificant effects on CI and PD. Conversely, BP demonstrated a significant and positive influence on customer intention and purchase decision. Moreover, the analysis revealed that CI acts as a significant mediator between BP and purchase decision. Thus, leveraging social media can augment brand preference, with an associated increase in customer intention leading to heightened purchase decisions. These findings furnish valuable insights to businesses, aiding them in making informed decisions regarding the selection of the most suitable social media strategy.