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The study examined the challenges facing external auditors in Nigeria, focusing on Big Four and indigenous audit firms. A quantitative study design was adopted using secondary data obtained from the annual reports and audited financial statements of 40 selected quoted companies from a population of 161 companies listed on the Nigerian Exchange Group. The study examined auditor independence, technological challenges, workload and time pressure, professional competence, regulatory compliance and audit firm type in relation to audit effectiveness. Data were analysed using descriptive statistics, correlation analysis and multiple regression at a 5% significance level. The regression model produced an R of 0.742, R-square of 0.551 and adjusted R-square of 0.486, indicating that the explanatory variables accounted for 55.1% of the variation in audit effectiveness. The overall model was statistically significant (F = 10.664, p = 0.000). Auditor independence challenges significantly affected audit effectiveness (t = -2.917, p = 0.006), as did technological challenges (t = -2.635, p = 0.013), workload and time pressure (t = -2.459, p = 0.019), professional competence and regulatory compliance (t = -2.554, p = 0.015). Audit firm type also showed a significant difference between Big Four and indigenous firms (t = 2.540, p = 0.016). All five null hypotheses were rejected. The study recommended stronger independence safeguards, increased investment in audit technology, improved staff planning, continuous professional development and stronger regulatory monitoring.

This study presents the results of the analysis of the influence of the Kelvin curvature and hygroscopic growth on the optical and equilibrium properties of desert aerosols components under varying relative humidity (RH). Microphysical properties (volume mix ratios, dry mode radii and wet mode radii) of desert aerosols were extracted from the OPAC 4.0 (Optical Properties of Aerosols and Clouds) and analyzed to quantify the influence of Kelvin Curvature (Kelvin effect) and water activities on equilibrium relative humidities, effective radius and effective hygroscopic growth. Data were extracted over the spectral range of (0.4 to 0.8 μm) and at eight relative humidities of (0%, 50%, 70%, 80%, 90%, 95%, 98%, and 99%). The concentrations of Mineral Nucleation Non-Spherical Mode (MINN) were varied to obtain five different models. Koehler theory was applied to determine the effective hygroscopic growth factor, effective radius, Kelvin effect, water activity, equilibrium vapour pressure, and first-order Kelvin corrections, while the empirical γ-model, k-model, and three-parameter growth model were used to evaluate hygroscopic growth behaviour. The results showed that the effective hygroscopic growth factor increased with increasing relative humidity of Mineral Nucleation Non-Spherical Mode (MINN) concentration, whereas the effective radius and Kelvin effect decreased. Water activity approached unity, while equilibrium vapour pressure increased rapidly near saturation. Kelvin effect corrections of the effective hygroscopic growth factor and effective radius remained negligible below 90% relative humidity but increased between 95% and 99% relative humidity. The regression analysis produced R² values of 0.99905 to 0.99929, which show data fitted equation very well, with A ranging from -0.0181 to -0.0137, and B from 0.0208 to 0.0442 across models 1 to 5. The k- model gave R² = 0.99912 to 0.99913, while the three-parameter model gave R² = 0.99925 to 0.99928. Model 1 consistently showed the largest corrections value and Model 5 the smallest correction. The study demonstrated that increasing mineral aerosol concentration enhanced water uptake while reducing the relative influence of Kelvin curvature.

Distributed Denial of Service (DDoS) attacks are still one of the focal cybersecurity concerns, primarily due to their complex nature and the sheer number of devices attached. Traditional detection lags in keeping up with emerging attack behaviors, and machine learning-based models have difficulty handling high-dimensional data, like the CICIDS2019 dataset with over 80 features. Feature selection (FS) has thus emerged as an essential preprocessing step to boost detection performance, decrease the cost of computation, and facilitate improved interpretation of the model. In this current study, the GreyLag Goose Algorithm (GGA), a bio-inspired metaheuristic optimization algorithm derived from greylag geese's migratory and foraging behavior, is utilized for the first time to solve the problem of feature selection in DDoS detection. GGA's balanced exploration-exploitation allows effective exploration of high-dimensional spaces of features to find the most informative subset of features. The extracted features were evaluated using the CICIDS2019 dataset with Support Vector Machine (SVM) and Random Forest (RF) classifiers. Experimental results show that GGA reduced the dimensionality from over 80 to 29 features with better classification performance. RF achieved closely perfect with 99.95% accuracy and AUC of 0.9999, although slightly better than SVM's 99.47% accuracy and 0.9987 AUC value. The findings underscore the strength of GGA in feature selection optimization of DDoS detection to achieve an efficient and stable approach that is a balance between efficacy and high prediction accuracy.

Gender-based violence (GBV) constitutes a pervasive human rights and public health concern with profound consequences for children who witness or experience violence within their homes and communities. While quantitative studies documented anxiety, depression, trauma symptoms, and academic decline among GBV-exposed children, the perspectives of counselling psychologists remained underexplored in Zimbabwe. This qualitative study explored how counselling psychologists understood and responded to the psychological effects of GBV on children in Midlands Province, Zimbabwe. Grounded in Bronfenbrenner's (1979) ecological systems theory and interpretivism, the study employed an exploratory case study design. A purposive sample of 15 counselling psychologists was selected, and data were collected through semi-structured interviews. Reflexive thematic analysis following Braun and Clarke's (2023) six-phase framework was used to analyse the data. Trustworthiness was ensured through member checking, audit trail, and peer debriefing, while ethical considerations including informed consent, confidentiality, and distress protocols were strictly observed. The findings revealed two broad themes. First, counselling psychologists described the psychological effects of GBV on children as encompassing emotional and affective distress (fear, anxiety, sadness, depression, anger, and helplessness), behavioural and social dysfunction (aggression, withdrawal, anti-social behaviour, and difficulty trusting others), and cognitive and academic impairment (poor concentration, memory problems, declining grades, and school dropout). Second, intervention strategies included trauma-informed therapeutic approaches (play therapy and cognitive behavioural techniques), culturally adapted interventions (family involvement, indigenous language use, and cultural practices such as storytelling and music), and multidisciplinary collaboration (working with social workers, teachers, and police). However, systemic challenges including limited human resources, financial barriers, and cultural norms that discouraged disclosure significantly constrained intervention effectiveness. The study concluded that GBV profoundly compromised children's emotional, behavioural, cognitive, and academic functioning, and that while counselling psychologists employed relevant interventions, systemic barriers limited their reach and impact. The study recommended that counselling psychologists integrate trauma-informed, developmentally appropriate, and culturally adapted interventions into routine practice; policymakers allocate adequate resources to expand mental health services in Midlands Province; researchers conduct further qualitative and longitudinal studies; and schools and mental health practitioners establish formal multidisciplinary collaboration frameworks to strengthen early identification and coordinated responses for GBV-affected children.

Red cultural resources are an important spiritual asset and economic support for rural revitalization. Rural grassroots organizations, as the core entities for protecting and utilizing these resources, directly affect how their value is transformed. To address challenges like fragmented protection, single-use, and insufficient industrial integration of red cultural resources in plain areas, this study takes the old site of North China United University in Xincheng Town, Xinji City as a case. Based on theories of rural governance, cultural heritage protection, and collaborative governance, it systematically reviews the current practices of grassroots organizations in site protection, resource integration, and industrial fusion, and analyzes the practical difficulties they face, such as poor coordination, lack of funds and technology, weak talent support, shallow industrial integration, and absence of institutional guarantees. The research shows that grassroots organizations need to build cross-village collaborative governance systems, expand diverse funding channels, deepen the integration of 'red culture + agriculture + intangible cultural heritage' industries, optimize talent introduction and training mechanisms, and establish long-term guarantee systems, forming a 'five-in-one' practical path: organization empowerment — resource integration — industrial fusion — talent cultivation — institutional assurance. This path can achieve sustainable protection and efficient use of red cultural resources, providing a replicable practical reference for empowering rural revitalization through red resources in plain areas.