Service-based business models (either product-, use-, or result-oriented) have gained attention as a way for manufacturing firms to transition toward a circular economy and foster the implementation of closing-the-loop strategies such as reuse, remanufacturing, and recycling. However, the relationship between the adoption of service-based business models and the achievement of greater circular economy performance remains complex and not fully understood. Adopting the Supply Chain Practice View and paradox theory as theoretical lenses, this paper addresses a literature gap by examining how supply chain practices shape the effectiveness of service-based business models in enhancing circular economy performance. Drawing on survey data from 380 Indian manufacturing firms and employing covariance-based Structural Equation Modeling, the study finds a direct effect of both the adoption of service-based business models and the implementation of supply chain practices on circular economy performance. It further shows that supply chain practices positively moderate the relationship between service-based business models and circular economy performance, strengthening their effectiveness in generating positive circularity outcomes. The study extends the Supply Chain Practice View by clarifying how transferable and imitable supply chain practices such as supply chain tracking, green partner selection, and co-design enable an effective implementation of service-based business models for circularity. Drawing on paradox theory, it also suggests that such practices help firms manage tensions triggered by service-based business models, sustaining a dynamic equilibrium that reinforces circularity performance. From a managerial and policy perspective, these results highlight a valuable opportunity for firms in developing economies to simultaneously support business growth and reduce environmental burdens through the joint implementation of service-based business models and supply chain practices.
Anxiety is a prevalent concern among college students, impairing academic performance and increasing attrition risk for universities. Effective interventions are needed to reduce overall and test anxiety during high-stakes assessments. This study explored the effect of massage therapy (MT) in reducing overall and test anxiety in traditional-aged undergraduate business students compared to a comparison group engaged in a relaxation activity (adult coloring). A private liberal arts university in the southeastern United States. Undergraduate business students (aged 18-23 years) enrolled in accounting, business administration, finance, economics, or marketing. Quantitative, quasi-experimental, repeated-measures design with both within-subjects (pre-post) and between-subjects (MT vs. adult coloring) evaluations. The experimental group received a 30-min MT session administered by a licensed massage therapist 2 h prior to a final exam. The comparison group engaged in a 30-min adult coloring activity. Anxiety levels were assessed pre- and post-intervention with the Adult Manifest Anxiety Scale-College Version (AMAS-C). MT significantly reduced overall anxiety (mean (M) = 58.79 to 51.68, t(37) = 4.103, p < 0.001, Cohen's d = 0.666) and test anxiety (M = 59.29 to 55.24, t(37) = 2.623, p = 0.013, Cohen's d = 0.426). Analyses of variance confirmed significant main effects of MT on overall anxiety (η 2 = 0.314, p < 0.001) and test anxiety (η 2 = 0.155, p = 0.015), unaffected by sex at birth or academic classification. Between-group differences with the comparison activity were not statistically significant (p = 0.114), though MT showed a small-to-moderate effect size. A 30-min MT intervention effectively reduced overall and test anxiety among traditional-aged undergraduate business students when administered within a 2-h window prior to a final exam. MT demonstrates promise as a non-pharmacological strategy to support students during high-stakes academic assessments.
Veterinary medicine is shaped by the business-care paradox, a persistent tension between commercial sustainability and ethical care commitments. Emotional labor is central to how practitioners navigate this paradox, yet the subjective processes through which they construct and sustain professional identity amid these competing demands have received little empirical attention from a subjectivity standpoint. Existing studies illuminate how emotions mediate this paradox yet stop short of examining the distinct identity pathways that practitioners adopt. Employing Q-methodology, 30 small-animal veterinarians in employee roles across private practices in southeastern China sorted 42 statements. The statements were developed around four core mechanisms of emotion-mediated paradox navigation: emotional salience, flexible emotional labor, emotional traces, and ongoing learning. Principal component analysis with varimax rotation identified shared subjectivity patterns, while semi-structured post-sorting interviews elicited rationales for extreme placements, strengthening interpretive validity. A three-factor solution explained 58% of variance, revealing three distinct identity trajectories. The pragmatic service provider reframes business decisions as necessary for sustainability, prioritizing clinic viability, and employs emotional detachment as a protective strategy. The conflicted caregiver experiences moral distress and identity dissonance when financial constraints limit care, feeling torn between ideal and feasible treatment. The resilient integrator treats constraints as parameters for creative problem-solving, drawing on adaptive learning while sustaining core ethical commitments. These viewpoints represent qualitatively distinct modes of emotional labor engagement. The findings reveal three distinct modes of emotional labor engagement, each reflecting a different pathway of professional identity construction. For veterinary educators, these findings highlight the need for differentiated support strategies, each tailored to a distinct identity trajectory. Spanning moral distress mitigation to resilience cultivation, such strategies are essential for sustaining both practitioner wellbeing and care quality.
Manure is an abundant waste source in dairy production with disposal creating significant challenges for producers. Recent work has shown that black soldier fly, Hermetia illucens (Linnaeus) (Diptera: Stratiomyidae), larvae can digest dairy manure; however, its high cellulose content and low nutrient value impact larval performance. Adding probiotics to black soldier fly feed can increase feed digestibility and weight gain. The goal of this study was to determine the influence of probiotic additions on black soldier fly larval performance when fed dairy manure. This study evaluated life-history traits of black soldier fly larvae fed dairy manure with single or combined probiotic treatments: Rhodococcus sp., Paenibacillus sp., and 1:1 combination, compared to a no-microbe control. Larvae were mass-reared on fresh dairy manure, and key metrics-bioconversion rate, survivorship, total biomass, and larval weight-were compared across treatments. Results showed a significant trial effect for all variables measured. Mean peak weights and the largest larval weights were 3.5-20.0% greater in at least one probiotic treatment compared to the control, while other life-history traits did not differ significantly. However, probiotic treatments reduced variation up to 17.0% in black soldier fly larval weight across trials, a trait not historically discussed in black soldier fly research. Developing processes that optimize larval weight in combination with reducing variation are critical for developing precise business models for predicting future production.
Mango anthracnose, caused by Colletotrichum gloeosporioides, is a major pre- and post-harvest disease that reduces fruit quality, shelf life, and market value. Reliance on synthetic chemicals for postharvest disease management necessitates safer and sustainable alternatives due to health and environmental challenges. This study assessed the in vitro antifungal efficacy of six medicinal plants-Anethum graveolens (AG), Ferula assa-foetida (FA), Justicia adhatoda (JA), Macrotyloma uniflorum (MU), Nyctanthes arbor-tristis (NA), and Vitex negundo (VN)-using five solvent extracts and essential oils (EOs) against C. gloeosporioides. Gas Chromatography-Mass Spectrometry (GC-MS) identified bioactive compounds in the most effective phytoextracts, whereas Scanning Electron Microscopy (SEM) examined ultrastructural aberrations in fungal mycelia post-treatment. Statistical analyses (ANOVA and Bonferroni's post hoc test) assessed the effects of plant species, solvent polarity, and exposure duration on antifungal performance. The results showed a clear dose-dependent inhibition of mycelial growth and spore production across treatments. EOs demonstrated the highest antifungal activity, achieving up to 100% inhibition at 40-80 μL mL-1, followed by petroleum ether (PE) extracts, whereas aqueous (AQ) and methanolic (MeOH) extracts were less effective. Among plants, AG showed the most consistent antifungal effect, followed by FA and JA. GC-MS profiling detected 137 compounds (84.6%-97.65% composition), including fatty acids (23.88%), terpenoids, sesquiterpene alcohols (11.48%), epoxides (8.58%), sulfides (7.11%), and terpenes (5.79%) known to disrupt fungal membranes and inhibit mycelial and spore growth. The findings indicate that plant species are the key determinant of antifungal efficacy, whereas solvent type and exposure duration act as secondary modulators. EOs, particularly from AG and FA, show promise as eco-friendly alternatives to synthetic fungicides and could be integrated into sustainable strategies for managing mango anthracnose.
Examining how the relationship between alcohol outlet density and alcohol-related harms may vary by neighborhood-level factors is important for informing the evaluation and implementation of environmental alcohol interventions and identifying other community conditions that can be modified to reduce alcohol-related harms and inequities. This study aims to extend prior research by testing whether housing eviction-a cause of housing insecurity and neighborhood destabilization-modifies the impact of alcohol outlet density on hospitalizations for assault and alcohol use disorder (AUD) in Pennsylvania ZIP codes. We used Bayesian hierarchical space-time misalignment models to examine the associations between inpatient assault and AUD hospitalizations and housing eviction filing rates, alcohol outlet density, and the proportion of outlets selling alcohol for off-premise consumption at the ZIP code level in Pennsylvania 2018-2022 (n = 7257 space-time units), reporting relative rates (RR) and 95% credible intervals (CIs). We tested whether eviction filing rates modified the associations between outlet density/the proportion of off-premise outlets and hospitalizations for AUD and assault. In main effects models, a one percent increase in the eviction filing rate was associated with a 1.2% increase in AUD hospitalizations (95% CI: 1.01, 1.015) and a 1.9% increase in assault hospitalizations (95% CI: 1.002, 1.038). The addition of one outlet per square mile was associated with a 0.3% increase in AUD hospitalizations (95% CI: 1.002, 1.004) and a 0.6% increase in assault hospitalizations (95% CI: 1.003, 1.008). In interaction models, eviction filing rates strengthened the positive associations between outlet density and hospitalizations for both assault and AUD. Reducing housing evictions may mitigate the impact of alcohol outlet density on AUD and assault. Future research, policy, and practice should explore opportunities for jointly addressing the alcohol environment and neighborhood housing conditions.
Clinicians' adoption of interoperability tools influences care quality, but evidence of actual use is limited. We analyze clinicians' use of outside records delivered via Epic Care Everywhere (CE), focusing on use frequency and predictors such as gender, experience, specialty, and role. Differences between pre-pandemic (2018-2019) and pandemic (2020-2021) periods are also examined to see how COVID-19 affected use of outside records. De-identified EHR metadata from UCSF clinicians (n = 1442) during pre-pandemic and pandemic periods, totaling 686 797 clinician-day observations, were analyzed. We measured usage intensity (mean CE lookups per appointment) and breadth (percentage of appointments with ≥1 lookup). Generalized linear models (GLMs) with a negative binomial distribution for overdispersion were used to estimate predictors of intensity. CE usage intensity rose by 43.0% post-COVID-19 onset compared with the pre-pandemic. Clinician specialty most strongly predicted use, with Nephrology and Cardiology showing the highest breadth (56.0% and 53.0% of visits, respectively), while Dermatology (13.2%) and Pediatrics (23.4%) were lowest. Residents used CE at 23.0% greater intensity than attendings, and each additional year of experience was linked to a 0.57% decrease in intensity. Clinician use of interoperability tools was higher in specialties such as Nephrology and Cardiology that require more care coordination, and among less experienced clinicians including resident physicians. Use increased after the pandemic began, likely due to ongoing adoption trends and increased clinical demands during system strain and uncertainty. These findings underscore the critical importance of considering clinician behavior and contextual factors, such as specialty care needs, in addition to technical capabilities, when promoting the adoption and use of interoperability tools.
To describe the supply and advertising of food and beverages with front-of-package warning labeling in kiosks and cafeterias, and in school environments of public and private schools in Metropolitan Lima. A cross-sectional study was conducted in 45 schools in Metropolitan Lima between March and May 2023. The supply and advertising of food and beverages were observed in school kiosks during the school day and among street vendors located at the school exit gates. A total of 57 school kiosks and cafeterias from 45 schools were analyzed. Processed and ultra-processed foods and beverages were observed in 96.5% of them, and at least one product with front-of-package warning labeling (octagon) was identified in 89.5%. Street vendors were found at 41 schools, totaling 148 vendors. Processed and ultra-processed food and beverages were observed in 77.7% of them, and at least one food or beverage with an octagon was observed in 48.6%. Advertising for processed and ultra-processed foods was observed in 57.9% of school kiosks and cafeterias and in 27.7% of street vendors. Evidence shows the exposure of schoolchildren to unhealthy food environments and non-compliance with regulations prohibi-ting the sale of foods with octagons both inside and around schools. It is necessary to reinforce information, awareness, and monitoring of the educational community to ensure the effectiveness of these policies in protecting the health of schoolchildren. Describir la oferta y publicidad de bebidas y alimentos con etiquetado frontal de advertencia en quioscos y cafeterías y, en entornos escolares de escuelas públicas y privadas de Lima Metropolitana. Se realizó un estudio transversal en 45 escuelas de Lima Metropolitana entre marzo y mayo del 2023. Se observó la oferta y publicidad de bebidas y alimentos en los quioscos escolares durante la jornada escolar y en vendedores ambulantes ubicados en la puerta de salida de las escuelas. e analizaron 57 quioscos y cafeterías escolares de 45 escuelas. En el 96,5% se observaron bebidas y alimentos procesados y ultraprocesados, y en el 89,5% se observó al menos una bebida o alimento con etiquetado frontal de advertencia (octógono). En 41 escuelas se hallaron vendedores ambulantes, sumando un total de 148 vendedores. En el 77,7% de ellos se observaron bebidas y alimentos procesados y ultraprocesados y en el 48,6% se observó al menos una bebida o alimento con octógono. Se observó publicidad de alimentos procesados y ultraprocesados en el 57,9% de quioscos y cafeterías escolares y en el 27,7% de vendedores ambulantes. Se evidencia la exposición de los escolares a entornos alimentarios no saludables y el incumplimiento de las regulaciones que prohíben la venta de alimentos con octógonos tanto dentro como alrededor de las escuelas. Se requiere reforzar la información, sensibilización y el monitoreo de la comunidad educativa para garantizar la efectividad de estas políticas en el cuidado de la salud de los escolares.
The tide is turning against a major idea in social psychology: that implicit evaluations reflect mental content that lies beyond conscious awareness. This view is being reconsidered in light of mounting evidence that people can predict their own implicit evaluations with high accuracy. However, there are reasons to question whether such predictive accuracy reflects introspective access. First, prior studies have relied almost exclusively on familiar targets (e.g., racial groups), allowing predictions to be informed by background knowledge (e.g., knowing that a group is stigmatized) rather than introspection. Second, implicit and explicit evaluations have been highly correlated in prior work, enabling accurate predictions simply by assuming that implicit evaluations mirror explicit ones. Here, we report eight experiments (five pre-registered; N = 6,794) designed to minimize these nonintrospective routes to predictive accuracy. We introduced participants to novel targets and shifted implicit and explicit evaluations of these targets in opposite directions, rendering explicit evaluations an unreliable cue. Under these conditions, predictive accuracy ranged from low to nonexistent; participants frequently anticipated shifts in their implicit evaluations in the opposite direction of the actual change. These results generalized across two learning paradigms (impression formation and attribute conditioning), two implicit evaluation measures (Implicit Association Test and evaluative priming task), and between-participant and within-participant designs. We consider multiple interpretations of these findings, including the possibility that implicit evaluations reflect mental content that is largely or even entirely inaccessible to conscious awareness. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
Although autonomy-supportive coaching has been widely recognized as beneficial for athletes' motivation and performance, associations between autonomy-supportive coaching and athletes' personal best performance remain insufficiently understood. Grounded in Self-Determination Theory (SDT), this study examined the associations among autonomy-supportive coaching, basic psychological need satisfaction, autonomous motivation, and athletes' personal best performance, within a theory-informed associative framework. A total of 411 provincial-level athletes from multiple sports in China completed validated questionnaires assessing perceived coach autonomy support, basic psychological need satisfaction, and autonomous motivation. Athletes' personal best performance was operationalized using official national competitive grading standards and transformed into a continuous indicator. Structural equation modeling with bootstrapping procedures (5,000 resamples) was employed to examine and compare competing models. The results showed that coach autonomy support, psychological need satisfaction, and autonomous motivation were each positively associated with athletes' personal best performance. Inferential conclusions regarding the two indirect associations were based exclusively on unstandardized indirect effect estimates (B) and their bootstrapped confidence intervals, both of which indicated statistical significance. No statistically significant direct association between coach autonomy support and personal best performance was observed; however, statistically significant indirect associations consistent with the proposed theoretical framework were identified. Although these findings are consistent with the SDT framework, the cross-sectional design precludes causal or temporal inference. All results should therefore be interpreted as reflecting patterns of association. The study offers theoretical and practical implications regarding associations between coaching practices and long-term athletic achievement.
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Travel-related fatigue and circadian disruption (i.e., jet lag) are well-established factors limiting performance in elite men's sport and are recognized contributors to home advantage. Yet evidence from women's professional leagues remains scarce. This study examined temporal trends in home-court advantage and assessed how cumulative travel burden and directional jet lag relate to performance in the Women's National Basketball Association (WNBA). Game location, timing, and performance data from 3489 regular season WNBA games spanning 18 seasons (2007-2024) were analyzed using mixed-effects models adjusted for game time, team and opponent strength, and season. We quantified cumulative travel distance over the preceding seven days and directional jet lag based on eastward or westward travel adjusted for circadian resynchronization. Home-court advantage declined significantly over time (β =  - 0.67, p = .002), from 64.3% in 2009 to 52.3% in 2024, coinciding with improved league-wide travel conditions. Greater recent travel distance was associated with worse performance among away teams (β = -0.04, p = .020), primarily driven by increased points conceded (β = 0.04, p = .018). Eastward jet lag was significantly associated with worse home team performance (β = -0.15, p = .049), with no such associations observed for westward jet lag or among away teams (all p ≥ .399). These findings provide the first large-scale evidence linking travel and circadian disruption to performance in the WNBA. Although home-court advantage has declined, travel-related challenges persist. Incorporating circadian principles into travel and recovery protocols may help improve performance, particularly as game schedules grow more congested with league expansion.
Jesuit leadership, grounded in Ignatian spirituality, emphasizes values such as cura personalis (care for the whole person), accompaniment, discernment, and magis (the pursuit of excellence), which together foster holistic human development and wellbeing. While these principles are widely applied across Jesuit educational, healthcare, and organizational settings, systematic evidence linking Ignatian leadership with outcomes of human flourishing remains limited. This study presents a systematic review of peer-reviewed literature published between 2020 and 2025 to examine how Ignatian spirituality functions as a formative foundation for Jesuit leadership and how these leadership practices contribute to wellbeing and human flourishing, with particular relevance to the Indian context. Following PRISMA 2009 guidelines, a comprehensive search was conducted across five databases-Scopus, Web of Science, PsycINFO, PubMed, and Google Scholar-resulting in the inclusion of forty-five eligible studies. The reviewed literature was appraised using the Mixed Methods Appraisal Tool and synthesized through thematic analysis. Findings reveal that Ignatian spirituality functions as a formative framework for leadership development, with practices of cura personalis and accompaniment enhancing emotional, psychological, and spiritual wellbeing, while magis and reflective discernment promote ethical excellence, resilience, and purposeful growth. Overall, the review demonstrates that Jesuit leadership supports integrative human flourishing by aligning ethical reflection, compassionate service, and institutional mission. The study highlights the need for future empirical research employing validated wellbeing measures to further examine Ignatian leadership constructs across diverse cultural and institutional contexts.
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Schools play a critical role in disaster risk reduction; however, preparedness efforts often overlook the unequal vulnerabilities associated with Gender, Disability, and Social Inclusion. This study addresses the lack of empirical evidence on how inclusively disaster preparedness is implemented within school-based disaster management structures, particularly the Safe School Disaster Unit (SSDU). Using a quantitative survey design, data were collected from senior high schools to assess levels of SSDU readiness, the integration of Gender, Disability, and Social Inclusion (GEDSI) principles and the relationship between these two dimensions. This study used a quantitative design. Data were collected through questionnaires from 995 respondents across five schools and analysed using regression analysis. The findings reveal substantial variation in preparedness across schools, with public schools generally demonstrating higher levels of SSDU readiness and GEDSI integration than private schools. Statistical analysis further indicates a positive association between stronger SSDU implementation and higher levels of GEDSI integration, suggesting that schools with more established disaster management systems are better positioned to adopt inclusive practices. These results highlight persistent gaps in inclusive disaster preparedness and underscore the need to strengthen institutional systems and policies that embed GEDSI principles within school disaster risk reduction initiatives. The study contributes empirical evidence to inform more equitable and resilient safe school programming. Disaster risk reduction strategies in school environments have so far focused on physical and structural aspects, whereas, on the other hand, there are aspects that have not been studied, such as Gender, Disability, and Social Inclusion. Therefore, it is important to know the implementation of safe schools by focusing on aspects of Gender, Disability, and Social Inclusion in order to realise school resilience to disasters in a fair, equal and sustainable manner.
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Pass-fail decisions in clinical examinations must be defensible, yet traditional standard-setting approaches often report a single cut score without explicitly quantifying uncertainty-an issue amplified in small cohorts and mixed-format assessments (e.g., OSCE plus written). We propose a Bayesian fuzzy hybrid standard-setting framework that (i) treats station cut scores as posterior distributions and (ii) models the inherently linguistic "borderline" construct using fuzzy membership, yielding both a central standard and a principled borderline review band. A mixed-format assessment model was specified with total score [Formula: see text], where [Formula: see text] is an equally weighted mean of [Formula: see text] OSCE stations with global ratings [Formula: see text]. Station cut scores were estimated using (a) Borderline Regression Method (BRM) for comparison and (b) Bayesian regression [Formula: see text], giving posterior [Formula: see text] at borderline [Formula: see text]. Borderline semantics were represented via a trapezoidal fuzzy set [Formula: see text] with centroid [Formula: see text], producing fuzzy-adjusted cuts [Formula: see text]. A hybrid OSCE standard [Formula: see text] was mapped to the mixed-format cut [Formula: see text]. A decision band [Formula: see text] combined Bayesian credible uncertainty and fuzzy [Formula: see text]-cut uncertainty to classify candidates as Pass, Fail, or Borderline review. The full workflow was demonstrated using a collected sample dataset (n=34, k=6) to illustrate reporting and reproducibility. Station-level BRM cut scores ranged from 59.5 to 62.4, while Bayesian station cut scores produced interpretable 95% credible intervals around similar means. The Bayesian OSCE cut score mean was approximately 61.2 with a narrow posterior interval, and the hybrid mixed format cut score was approximately 60.8 (0-100 scale). The uncertainty-aware decision band produced 22 Pass (64.7%), 10 Fail (29.4%), and 2 Borderline review (5.9%) classifications, explicitly isolating boundary cases rather than forcing deterministic decisions. Bootstrap resampling indicated that the hybrid central standard was stable and comparable to BRM, while adding transparency via a bounded review zone. Here the Bayesian-fuzzy hybrid framework retained the interpretability of borderline regression but provided explicit uncertainty quantification and a structured bandfor borderline review. The results ought to be understood as methodological and illustrative but not confirmation of universal superiority; external validation in larger multi-centre clinical examination cohorts is necessary prior to routine operational implementation.
This study examines the mechanisms underlying the influence of minimalism on ethically minded consumer behavior. Within the Stimulus-Organism-Response framework and Self-Determination Theory, the study investigates the effect of minimalism on ethically minded consumer behavior through moral identity (internalization and symbolization) and psychological well-being, with attention paid to the moderating effect of eco-anxiety. Data for this study came from a survey involving 555 young consumers in Vietnam and were analyzed using partial least squares structural equation modeling. It is demonstrated that minimalist lifestyle orientation positively impacts psychological well-being and both aspects of moral identity. Moral identity symbolization and well-being were found to have a direct and positive effect on ethically minded consumer behavior, but moral identity internalization did not have such a direct influence. Instead, moral identity internalization positively affects moral identity symbolization. Furthermore, psychological well-being is identified as an important psychological mechanism underlying the relationship between minimalist lifestyle orientation and ethical decision making. This study emphasizes the importance of self-concept and well-being for ethical decision-making. It demonstrates that eco-anxiety selectively moderates the internal identity process, intensifying the conversion of moral identity internalization into symbolization while exerting no significant moderating influence on the final behavioral outcome via the relationship between moral identity symbolization and ethically minded consumer behavior.
Sentiment analysis (SA) of natural language text has become as a powerful instrument for enhancing financial market predictions. Quarterly reports from companies, in particular, offer a rich source of data for sentiment analysis, providing key insights into a company's performance, strategic actions, and future prospects. These reports can significantly influence investor decisions regarding asset investments. Notwithstanding the potential, prior research has not investigated sentiment analysis concerning these resources in portfolio optimization. To fill this void, we propose an innovative three-stage approach to constructing stock portfolios. In the first stage, we perform sentiment analysis on companies' quarterly reports using the FinBERT model to assess the sentiment surrounding each company. In the second stage, we utilize a Long-Short-Term Memory (LSTM) model for forecasting future prices, which enables the calculation of expected returns and the covariance matrix. In final stage, we present a three-objective portfolio optimization model that incorporates risk, return, and sentiment-derived trend features. We solve this model using the Weighted Goal Programming (WGP) method. Our results indicate that the proposed model effectively supports portfolio optimization. Moreover, the model is implemented using data from companies that are part of the Dow Jones Industrial Average (DJIA), and findings demonstrate high accuracy, confirming the practical potential of the proposed approach.
Software-Defined Networks (SDNs) are already susceptible to cyber-attacks because of the weak security mechanisms and limited resources. This is predicted to be intensified in the Internet of Things era with a forecast of more than 29 billion connected devices in 2030, thereby broadening the threat surface significantly and making it increasingly difficult for cybersecurity solutions to address these threats. Conventional intrusion detection systems(IDSs) on SDNs are challenged by imbalanced multi-class data, high-dimensional and noisy features, and a lack of interpretability. To address these challenges, this study proposes a hybrid SDN-based IDS framework that integrates Generative Adversarial Networks (GANs) to handle imbalanced datasets, one-way ANOVA and Genetic Algorithm (GA) for feature selection, baseline classifier optimization using Grid Search and Explainable AI techniques such as SHapley Additive exPlanations (SHAP), Local Interpretable Model-agnostic Explanations (LIME), Morris sensitivity analysis and permutation combination to achieve robust, accurate, and interpretable intrusion detection. The grid search-optimized XGBoost model, denoted as OptiXGB-IDS, demonstrates high performance on the InSDN dataset, with a test accuracy of 99.87%, and macro-averaged precision, recall, and F1-score of 0.9618, 0.9951 and 0.9775 respectively. In addition, the model achieves a Cohen's kappa coefficient of 0.9982 and a Brier score of 0.0024, with an inference time of 0.026312 ms per flow. In order to further test cross-dataset robustness, the proposed framework was also validated on the CIC-IDS2017 dataset, where OptiXGB-IDS achieved the highest test accuracy of 98.70% and outperformed all other competing models. The proposed hybrid GA-GAN-XAI framework significantly improves the IDS performance by providing key traffic flow features and improving spatial and temporal feature learning, making it highly robust and providing a very precise and reliable solution for detecting complex and previously unseen cyber threats in SDN-based IoT environments.