Search Results (39)

Background: Despite growing scholarly interest in Sustainable Entrepreneurship Orientation (SEO), the field lacks a theoretically grounded measurement approach, limiting the generalizability and comparability of SEO adaptation. Methods: This paper proposes an evidence-based formative measurement approach to assess the degree of SEO within an enterprise. A multidisciplinary literature review identified four SEO dimensions, namely Entrepreneurial, People, Environmental, and Communal Orientation (EPEC), and their observable firm behavior indicators. A Multiple Indicators and Multiple Causes (MIMIC) model framework is used to position SEO as a latent formative construct rated across defined maturity levels. A longitudinal single-case study of a Hungarian private medical clinic, conducted over four quarterly measurement cycles using onsite observations and semi-structured interviews, was used to demonstrate the feasibility of the instrument, its ability to rate SEO adaptation levels consistently across independent raters from different organizational roles, and its ability to generate meaningful, trackable SEO maturity data that evolves. Results: Fleiss’ Kappa values confirmed substantial inter-rater agreement across 21 raters, and progressive SEO maturity was observed across all four quarters. Conclusions: The paper offers a theoretically grounded, methodologically replicable measurement instrument with potential applications for researchers, practitioners, and policymakers, subject to further validation across diverse organizational and cultural contexts. Full article

Financial fraud is still one of the most important threats to the financial industry, causing enormous economic losses and mounting difficulties for conventional fraud detection systems. The systems tend to face challenges in dealing with the rising amount of transactional data, the problem of class imbalance, and the continually changing nature of fraudulent activity. In order to solve these problems, in this research a cloud hybrid framework for detecting fraud using Long Short-Term Memory (LSTM) networks, Autoencoders, and Cat Swarm Optimization (CSO) is suggested. The purpose of the suggested framework is to provide improved detection performance and flexibility on a benchmark financial dataset, with a design intended to support scalability in real-time applications. The framework uses the Credit Card Fraud Detection Dataset from Kaggle, which consists primarily of numerical features, including anonymized variables (V1–V28), along with time and amount. The LSTM networks learn the sequential relationships of transactions, while Autoencoders learn to detect anomalies in the data unsupervised. CSO is used to optimize key hyperparameters of the hybrid model, including the learning rate (0.0001–0.01), batch size (32–128), number of LSTM layers (1–3), number of hidden units per layer (16–128), dropout rate (0.1–0.5), and fusion weights (0–1 for each weight, with the sum constrained to 1) between the LSTM and Autoencoder outputs. In addition, CSO is applied for feature subset selection and threshold tuning to further enhance model performance. Preprocessing is performed on the data, including normalization and feature scaling prior to model training. The suggested framework has a 96.2% accuracy, 94.6% precision, 97.9% recall, 96.2% F1-score, and 0.97 AUC-ROC, showing improved performance compared to CNN-based and LSTM-CNN models under the evaluated conditions. However, since no multiple experiments were conducted to verify the robustness, the results should be interpreted as indicative rather than definitive. The framework exhibits competitive fraud detection performance on the evaluated benchmark dataset, particularly in handling class imbalance. In a simulated environment configured to mimic cloud-like conditions, the framework achieved inference latency between 15 and 30 ms, GPU utilization between 60% and 70%, and a data transfer volume of approximately 1.5 GB per day, suggesting its potential for deployment in cloud-based fraud detection systems. The framework indicates immense potential for cloud deployment, with a robust solution for preventing financial fraud. The proposed framework demonstrates the potential of integrating sequential modeling, anomaly detection, and metaheuristic optimization within a unified and cloud-oriented architecture, providing a more comprehensive approach compared to conventional hybrid models. Full article

The manuscript aims to assess the scale of shadow economic processes within the non-observed economy, focusing on the self-employment sector, which is insufficiently reflected in national statistics. The research methodology includes an analysis of the conceptual foundations of the shadow economy, decomposition of its components, identification of factors negatively affecting the economy, development of an algorithm for sociological research, and the selection of appropriate models for evaluating the non-observed economy. The study formulates the concept of the shadow economy and shows that shadow business activity in Kazakhstan contributes to income inequality, hidden unemployment, and the exclusion of certain goods and services from official GDP statistics. Using statistical data from 2005 to 2024 and applying methods such as system and statistical analysis, modeling approaches, and the MIMIC (Multiple Indicator Multiple Cause) and DGE (Dynamic General Equilibrium) models, the study estimates the size of the shadow sector. The results reveal insufficient statistical data on shadow activities within self-employment and SMEs. The study concludes that the most reliable assessment of the shadow economy requires an integrated methodological approach, including targeted sociological research and models that account for the influence of multiple factors on informal self-employment. Full article

Background: This study aimed to compare the prognostic value of three surrogate insulin resistance (IR) markers for predicting 360-day mortality in critically ill patients with ischemic stroke (IS): the triglyceride–glucose (TyG) index, TyG–shock index (TyG-SI), and TyG–lactate (TyG-Lac). Methods: The study population comprised critically ill IS patients identified from the Medical Information Mart for Intensive Care (MIMIC) IV database. The main outcome was 360-day mortality. We employed multiple analytical approaches to examine relationships between the three biomarkers and mortality outcomes, including multivariable Cox proportional hazards models (Cox models), Kaplan–Meier survival analysis, and restricted cubic spline (RCS). Furthermore, receiver operating characteristic (ROC) curve analyses were conducted to assess the predictive capacity of these three indices. We performed ROC analyses to evaluate whether the IR index improved the discriminatory ability of a base model that included baseline variables significantly different between survivors and non-survivors. Results: Altogether, 812 patients with IS were included in the analysis. In Cox proportional hazards models, the TyG index was independently associated with higher 360-day mortality (HR, 1.68; 95% CI, 1.52–1.76). Similarly, both TyG-SI and TyG-Lac indices showed significant associations with 360-day mortality, with the HR (95% CI) of 1.24 (1.05–1.38) and 1.11 (1.08–1.23), respectively. Kaplan–Meier survival curves showed a progressive elevation in cumulative 360-day mortality across ascending quartiles of each index (TyG, TyG-SI, and TyG-Lac). ROC curve analysis revealed relatively better discriminatory ability of the TyG-SI compared to TyG and TyG-Lac for all-cause 360-day mortality prediction (area under the curve: 0.605 [0.578–0.623] vs. 0.566 [0.532–0.592] vs. 0.587 [0.532–0.614]). Furthermore, incorporation of either the TyG-SI or TyG index modestly improved the 360-day mortality prognostic accuracy of the base model (area under the curve [AUC], 0.701 for the base model vs. 0.723 for the base model + TyG-SI vs. 0.716 for base model + TyG index). Conclusions: When analyzed as continuous variables, each of the three indices demonstrated significant associations with 360-day mortality risk of critically ill IS populations. Moreover, both TyG-SI and TyG can improve the 360-day mortality predictive accuracy of the base model. Among the three indices, TyG-SI showed comparatively better discriminatory performance; however, the magnitude of AUC improvement was modest, and its clinical utility should be interpreted cautiously pending external validation. Full article

Understanding the socio-demographic drivers of residential energy-saving behavior is critical for designing effective energy policies and technologies. This study applies a Multiple Indicators, Multiple Causes (MIMIC) model to examine how individual characteristics are associated with two latent constructs: energy concern and smart-home interest and usage. Using survey data collected from urban residents in Guangdong Province (N = 261), structural equation modeling was employed to assess both measurement and structural components of the model. The results show that income is positively associated with both energy concern and smart-home interest and usage, whereas being a bill payer is negatively related to both. Gender also plays a role, with females reporting higher energy concern. Other factors, such as age, education, and time spent at home, did not show significant effects. The model showed acceptable global fit indices; however, the reliability and convergent validity of the latent constructs were limited. Accordingly, the findings should be interpreted as exploratory associations observed within this sample and may serve as a basis for future research on segmentation in similar urban contexts. Full article

The ambivalent sexism theory supports differences in the manifestations of sexism among individuals with diverse genders and sexual orientations. However, it still remained unclear whether individuals who share common strong cultural values endorse different levels of sexism according to their gender and sexual orientation. The current study aimed to examine differences in sexist attitudes based on gender and sexual orientation among Korean adults. We first tested measurement invariance in a Korean Multi-dimensional Sexism Inventory (K-MSI) between heterosexuals (n = 374) and sexual minorities (n = 445), and second, we compared the latent means across groups using the Multiple Indicators Multiple Causes (MIMIC) model. The results confirmed the first-order six-factor structure of the K-MSI with adequate internal consistency, and supported partial scalar invariance across heterosexual and sexual minority men and women. The MIMIC model approach revealed significant age, gender, and sexual orientation differences in most of hostile sexism (HS) and benevolent sexism (BS) components. Overall, heterosexuals reported higher levels of sexism than non-heterosexuals within each gender. Gender differences in BS have become nuanced when sexual orientation was considered. The current study also provides an overview of Korean culture that may uniquely influences individuals’ sexist attitudes, which would interest international researchers. Full article

Salmovirus salmonidallo3 (SalHV-3) causes Epizootic Epitheliotropic Disease (EED), which has resulted in the death of millions of lake trout (Salvelinus namaycush) over the past 40 years. Although advancements in understanding this virus’s pathogenicity and control strategies have been made, the duration and effects of chronic SalHV-3 infections remain unknown. This study focused on lake trout that survived a natural outbreak of EED in 2012 and were maintained under quarantine conditions until 2021. Following exposure to either repeated or intermittent handling stress designed to mimic typical hatchery practices, SalHV-3 was detected (via a SalHV-3-specific quantitative PCR assay) in multiple tissues from multiple fish. Non-lethally collected tissues revealed the highest prevalence and virus loads in the fin and mucus. SalHV-3 was detected in these tissues throughout the study period (49 days, 8 sampling events), with some fish having detectible virus on each study day and others only intermittently (n = 1–7 sampling days). Tissues collected lethally yielded SalHV-3 detections in multiple nervous tissues, as well as in the cornea of several fish. Experiments to evaluate virus shedding revealed that SalHV-3 was intermittently detectable in fish holding water. Collectively, results indicate that lake trout can remain SalHV-3 infected for nearly a decade and intermittently shed the virus, constituting a threat to hatchery-based lake trout conservation efforts in the Great Lakes basin. Full article

One of the most concerning ruminant infections is the parasite Ostertagia ostertagi. Known commonly as the brown stomach worm, it is ingested by grazing cattle where it then progresses its life stages, occupying the host abomasum and then the intestine, causing illness. This results in lower commercial production and at worst, death of young calves. Over time, anthelmintic treatment has become less efficacious against cattle nematodes. As a result, alternative control strategies are needed. Our study looked to elucidate mechanisms underlying attenuation of the host immune response by examining global immune expression in cattle during infection. To this end, four steers were infected with the third stage larvae (L3) of O. ostertagi, then peripheral blood mononuclear cells (PBMCs) were collected weekly for 26 days post-infection (dpi). After sequencing, gene expression was compared between each timepoint. The analyses indicated that the immune responses to Ostertagia are targeted to the parasite’s life stages and mimics anti-viral gene expression. Overall, the results showed that O. ostertagi led to host immune responses characterized by multiple gene ontology and pathway terms indicating that by 26 dpi the host immune system transitions from fighting the parasite to repairing the host intestine. Full article

Purpose: This study adopted a quantitative design to evaluate a new latent construct, “Parental Academic Commitment (PAC)”, that was composed of parental involvement (PARINVOL) and parents’ expectations of their children’s academic success (PAREXPT). Furthermore, we also explored how different perceptions of school leadership would impact parental academic commitment and student learning. More specifically, we compared how principal-perceived school leadership and teacher-perceived leadership would influence student achievement (SA) directly and indirectly through mediating parental academic commitment (PAC). Methods: To find answers, we utilized two Structural Equations Models—Multiple Indicators and Multiple Causes Analysis (SEM-MIMIC) to first confirm the psychometric properties of PAC, and then compared the two SEM models. Data from 202 principals, 4251 teachers, 10,291 parents, and 10,291 students in Hong Kong and Macao from PISA 2022 were utilized; both individual-level and school-level analyses were conducted. Results: Principal-rated and teacher-rated school leadership functioned differently in the 2 SEM models. Both ESCS (Economic, Social, and Cultural Status) and PAC were confirmed to be significant contributors to positive student outcomes. Full article

This study explores the drivers and evolution of the shadow economy in Bosnia and Herzegovina—a transitional, post-conflict country facing persistent institutional fragility. Using the Multiple Indicators and Multiple Causes (MIMIC) model, an extension of Structural Equation Modeling, the paper estimates the size and dynamics of the shadow economy from 1996 to 2022. The model integrates macroeconomic indicators (employment rate, GDP per capita, tax revenues) and institutional variables (rule of law, control of corruption), with data primarily sourced from the World Bank. The results show that institutional quality, tax burden, and labor market conditions are significant determinants of the informal sector. The model demonstrates strong statistical validity (CFI = 0.986, RMSEA = 0.05), supported by robustness checks including unit root tests, structural break analysis, and the exclusion of controversial benchmarking methods. The shadow economy responds markedly to major shocks such as the 2008 global financial crisis and the 2014 floods. Findings provide valuable policy insights: strengthening institutions, simplifying tax systems, and encouraging formal labor market participation can significantly reduce informality. The study supports evidence-based reforms to enhance transparency, resilience, and sustainable development in Bosnia and Herzegovina. Full article

Background: The Montreal Cognitive Assessment (MoCA) is widely used to evaluate global cognitive function; however, its precision in measurement in heterogeneous populations—especially among patients with Parkinson’s disease (PD)—remains underexplored. Methods: In this multicenter cross-sectional study, we examined the psychometric properties of the Brazilian Portuguese MoCA in 484 PD patients (age range, 26–90 years; mean ± SD, 59.9 ± 11.1 years; disease duration range, 1–35 years; mean ± SD, 8.7 ± 5.4 years) using Item Response Theory (IRT). The Graded Response Model (GRM) was employed to estimate item difficulty and discrimination parameters, and differential item functioning (DIF) concerning age and education was investigated via a Multiple Indicators Multiple Causes (MIMIC) model. Results: The MoCA demonstrated essential unidimensionality and robust model fit. GRM analyses revealed that items within the Attention and Naming domains had high discrimination, indicating sensitivity to subtle cognitive deficits, while Memory items exhibited lower discrimination. Orientation items showed low difficulty thresholds, suggesting a propensity for ceiling effects. The MIMIC model further indicated that age and education significantly influenced overall scores: increasing age was associated with lower performance, whereas higher educational attainment correlated with better outcomes, particularly in Memory Recall and Executive/Visuospatial domains, even after accounting for their modest inverse relationship. Conclusions: Our findings support the validity of the Brazilian Portuguese MoCA for cognitive screening in PD while highlighting item-level biases linked to age and education. These results advocate for using education-adjusted norms and computerized scoring algorithms that incorporate item parameters, ultimately enhancing the reliability and fairness of cognitive assessments in diverse clinical populations. Full article

Lactoferrin-derived peptide chimera is a synthetic peptide that mimics the functional unit of lactoferrin with antibacterial activity. Although LF has anticancer effects, to the best of our knowledge, its effects on multiple myeloma have not yet been studied. We explored the potential of a lactoferrin-derived chimera for multiple myeloma treatment, a malignant clonal plasma cell bone marrow disease. The lactoferrin-derived chimera effectively inhibited MM1S, MM1R, and RPMI8226 multiple myeloma cell growth, and induced the early and late phases of apoptosis, but not in normal peripheral blood mononuclear cells. Furthermore, the lactoferrin-derived chimera modulates the relative expression of genes involved in survival, apoptosis, and mitochondrial dysfunction at the transcriptional level. Mitochondrial analysis revealed that lactoferrin-derived chimera triggered oxidative stress in multiple myeloma cells, leading to reactive oxygen species generation and a decline in mitochondrial membrane potential, resulting in mitochondrial dysfunction. Although lactoferrin-derived chimera did not cause caspase-dependent cell death, it induced nuclear translocation of apoptosis-inducing factor and endonuclease G, indicating the initiation of caspase-independent apoptosis. Overall, the lactoferrin-derived chimera induces caspase-independent programmed cell death in multiple myeloma cell lines by increasing the nuclear translocation of apoptosis-inducing factor/endonuclease G. Therefore, it has potential for multiple myeloma cancer therapies. Full article

Substance use self-stigma is a barrier to treatment and can negatively impact individuals’ well-being and treatment engagement. Given the mixed findings in previous research and the limited specific investigation into the concept of self-stigma within the context of opioid misuse, examining factors associated with self-stigma in the context of opioid use disorder (OUD) is warranted. The current study examines the influence of individual-level factors (race, sex, urban/rural status, support group attendance) on self-stigma and willingness to disclose opioid use. Data for this study were from a larger study of OUD-related stigma among adults in Pennsylvania, U.S. The current study included participants who indicated a personal past or current history with OUD were included (n = 84). Exploratory factor analysis and multiple indicators, multiple causes (MIMIC) model were used to explore the associations between demographic factors (i.e., sex, age, race/ethnicity, urban/rural status), attendance at mutual support groups, and self-stigma factors. Results indicated that sex and attendance at mutual support groups significantly predicted levels of self-stigma. Women and individuals with no previous experience attending mutual support groups endorsed lower levels of self-stigma. Additionally, attendance at mutual support groups predicted willingness to self-disclose past and present opioid use. Individuals who reported no history of attending mutual support groups demonstrated less willingness to disclose past and present OUD use compared to participants who were support group attendees. The current research findings enhance the understanding of OUD-related self-stigma by examining its relationship with individual-level factors, disclosure, and attendance to mutual support groups. The results offer insights into the influence of sex and support group attendance on self-stigma and disclosure. These findings have significant clinical implications for developing future interventions and promoting health policy changes. Full article

Background: Polysubstance use is a highly prevalent public health issue, particularly among adolescents, and decisions on prevention programming and policies are often made at the local level. While there is a growing literature examining patterns of polysubstance use among adolescents, little is known about differences in those patterns across geographic regions. Methods: Using a large, representative sample of high school students from the state of Maryland (n = 41,091) from the 2018 Maryland Youth Risk Behavior Survey, we conducted a latent class analysis (LCA) of adolescent substance use along nine binary indicators, including past 30-day combustible tobacco, e-cigarette, alcohol, and cannabis use, as well as lifetime use of prescription opioids, cocaine, heroin, methamphetamine, and injection drug use. Measurement invariance across counties was examined using the Multiple Indicators and Multiple Causes (MIMIC) procedure. Results: The results of the LCA show three classes of adolescent substance use for the total sample: (1) low substance use, (2) commonly used substances (i.e., e-cigarette, alcohol, and cannabis use), and (3) polysubstance use. The results from the MIMIC procedure demonstrated geographic differences in students’ endorsement of specific indicators and their class membership. Conclusions: These differences demonstrate the need for an examination of local trends in adolescent polysubstance use to inform multi-tiered prevention programming and policy. Full article

The regulatory role of non-CpG methylation in mammals has been important in whole-genome bisulfite sequencing. It has also been suggested that non-CpG methylation regulates gene expression to affect the development and health of mammals. However, the dynamic regulatory mechanisms of genome-wide, non-CpG methylation during testicular development still require intensive study. In this study, we analyzed the dataset from the whole-genome bisulfite sequencing (WGBS) and the RNA-seq of precocious porcine testicular tissues across two developmental stages (1 and 75 days old) in order to explore the regulatory roles of non-CpG methylation. Our results showed that genes regulated by non-CpG methylation affect the development of testes in multiple pathways. Furthermore, several hub genes that are regulated by non-CpG methylation during testicular development—such as VEGFA, PECAM1, and FZD7—were also identified. We also found that the relative expression of FZD7 was downregulated by the zebularine-induced demethylation of the first exon of FZD7. This regulatory relationship was consistent with the results of the WGBS and RNA-seq analysis. The immature porcine Sertoli cells were transfected with RNAi to mimic the expression patterns of FZD7 during testicular development. The results of the simulation test showed that cell proliferation was significantly impeded and that cell cycle arrest at the G2 phase was caused by the siRNA-induced FZD7 inhibition. We also found that the percentage of early apoptotic Sertoli cells was decreased by transfecting them with the RNAi for FZD7. This indicates that FZD7 is an important factor in linking the proliferation and apoptosis of Sertoli cells. We further demonstrated that Sertoli cells that were treated with the medium collected from apoptotic cells could stimulate proliferation. These findings will contribute to the exploration of the regulatory mechanisms of non-CpG methylation in testicular development and of the relationship between the proliferation and apoptosis of normal somatic cells. Full article