This review of literature will examine the connection between the insignificance of the teacher role in school-based decision-making processes and the effects it has on the morale of the personnel. Although my earlier empirical study, which was carried out in a particular country and confined to a demarcation of five schools, indicated a relation between low participation in decision-making and low employee morale, this study will widen the knowledge on this issue to global areas. Set against a wide array of literature provided in different educational settings, this review aims to uncover common themes, policy and practice implications, and the generalizability of results in terms of teacher participation and teacher morale. Finally, the goal of this review is to educate educational stakeholders about the importance of creating inclusive decision-making communities that consider and cherish the input of teachers to positively impact the general workplace atmosphere and performance.

In Poland, the Chinese sleeper (Perccottus glenii) is considered a non-native invasive fish species that effectively competes with native fauna, potentially contributing to population decline and reduced biodiversity. This study investigates the feeding habits of two coexisting species: the native European perch (Perca fluviatilis) and the invasive Chinese sleeper. Fish specimens were collected from a watercourse connected to a fish farm within the Nida River system (Poland) using electrofishing. The captured individuals were euthanized, preserved in 4% formaldehyde, and subsequently dissected to remove stomachs for analysis. The abundance and taxonomic composition of stomach contents were recorded, and prey items were identified to their respective taxa. Feeding overlap between P. fluviatilis and P. glenii was assessed using principal component analysis (PCA). The results revealed a notable dietary overlap between the two species. However, the European perch exhibited a broader feeding niche compared with the Chinese sleeper. Due to its high ecological plasticity, P. fluviatilis appears capable of tolerating competitive pressure from P. glenii, potentially limiting the invader’s population. Both species frequently preyed upon fish, including juvenile common carp (Cyprinus carpio). This indicates that P. glenii, alongside native predatory species, may pose a significant threat to farmed juvenile cyprinids.

The present study examines key parameters of a consecutive solvent extraction process for pomace olive oil using ethanol and petroleum ether on both dry and wet pomace samples. Extraction from dry pomace with petroleum ether resulted in a high oil yield (11.72 ± 0.30%) and a solvent recovery rate of 89%. Extraction with ethanol produced a comparable yield (11.10 ± 0.60%) with a 90% solvent recovery rate. Although oil extraction from wet pomace using ethanol is technically feasible, its economic viability remains uncertain due to the reduced solvent recovery rate of 62%. The hydrolysis of crude extracted pomace oil under alkaline conditions was successfully demonstrated. Subsequently, starch grafting with the resulting long-chain mono-fatty acids was performed in a DMF/water medium in the presence of Fenton’s reagent. Sonication was applied to ensure homogeneity of the reaction mixture, and the biopolymer was synthesized using domestic microwave irradiation. After characterization of the grafted polymer, it was utilized to produce a composite material in combination with polyvinyl alcohol.

Introduction: Cardiopulmonary exercise testing (CPET) is considered the gold standard for evaluating exercise capacity in patients with chronic heart failure (CHF). However, CPET is not always feasible in clinical settings, leading to increased reliance on field-based tests. This study aimed to investigate the effectiveness of the symptom-limited stair-climbing test (SLSCT) in assessing exercise capacity among patients diagnosed with CHF. Materials and Methods: Thirty-one individuals (mean age: 65.52 ± 7.57 years) with New York Heart Association (NYHA) Class II–III CHF were enrolled. Exercise capacity was assessed using SLSCT, the 6-minute walk test (6MWT), and CPET. Predicted peak oxygen consumption (VO₂peak), heart rate (HR), blood pressure (BP), left ventricular ejection fraction (LVEF), and pulmonary function parameters were measured. Results: The predicted VO₂peak obtained from the SLSCT was significantly higher compared to values derived from the 6MWT and CPET (p < 0.05). HR responses during SLSCT were greater than during the 6MWT but lower than those observed during CPET (p < 0.05). A statistically significant correlation was found between SLSCT-predicted VO₂peak and LVEF, body mass index (BMI), forced expiratory volume in one second (FEV₁), forced vital capacity (FVC), and CPET-predicted VO₂peak (r = 0.36–0.55, p ≤ 0.05). Discussion and Conclusion: The SLSCT is an effective and practical method for evaluating exercise capacity in patients with CHF. Compared with the 6MWT, it provides a more reliable reflection of clinical status and hemodynamic responses. In situations where CPET is unavailable, SLSCT can serve as a valid alternative for assessing exercise capacity in individuals with CHF.

Consideration of shale–drilling mud interaction is essential in wellbore stability analysis to determine the appropriate mud density window and to minimize instability and related complications in shale intervals. In the assessment of shale stability, the swelling behavior of shale has been widely studied as a primary factor influencing mud composition selection during drilling operations. As drilling depth increases, instability-related complications become more frequent due to stress changes and shale reactivity. Maintaining the mechanical integrity of the wellbore requires predicting the deformation behavior of surrounding rocks and implementing methods to prevent such deformation. In deep and ultra-deep drilling, direct observation of deformation processes is impractical; therefore, theoretical and analytical models are crucial for describing the mechanism of rock deformation around the borehole wall. These analytical approaches provide better insight into the nature of instability development, facilitate more accurate prediction of deformation at the planning stage, and contribute to the prevention of instability-related failures during drilling.

This study investigates a Radial Basis Function Neural Network (RBFNN) architecture integrated with a satisfiability-based computational framework. RBFNN models are known to be sensitive to training parameters, and suboptimal configurations may lead to considerable computational inefficiency. To address this limitation, a Differential Evolution (DE) algorithm is employed to optimize the output weights of the RBFNN that correspond to an embedded 2-Satisfiability (2-SAT) formulation. The DE optimization procedure iteratively minimizes the objective function associated with the 2-SAT representation. The proposed DE-based training strategy is evaluated against state-of-the-art Genetic Algorithm (GA) optimization and other conventional methods using Microsoft Visual Dev C++ software. Simulation results demonstrate that the DE approach yields superior performance, outperforming existing techniques previously reported in the literature.

Agriculture represents a central pillar of Pakistan’s economy, with food crops serving as a critical component of agricultural output. A considerable disparity exists between the potential crop yield and actual production levels due to factors such as limited technological advancement, inefficient resource utilization, mismanagement of water and land resources, and inappropriate pest control practices. These challenges negatively influence agricultural productivity and contribute to significant output losses. Although synthetic chemicals are commonly applied to manage pests, their frequent misuse reduces their effectiveness and often fails to achieve the desired outcomes. This study analyzes the economic outlook for major food crops by assessing the relationship between national food crop production and agricultural GDP growth, focusing on wheat, rice, sugarcane, and maize. It also evaluates the impact of water availability on agricultural productivity over a 20-year period from 1999 to 2018. Secondary time-series data were obtained from the Pakistan Economic Survey (various issues). Analytical techniques employed include conventional econometric estimation methods, Augmented Dickey-Fuller (ADF) unit root testing for data stationarity, and Johansen co-integration analysis to examine long-term relationships. The empirical findings reveal that wheat, rice, sugarcane, and maize production are positively associated with Pakistan’s agricultural GDP, indicating that improvements in these staple crops significantly contribute to economic growth. In contrast, water availability demonstrated a negative yet statistically insignificant relationship with agricultural GDP, suggesting broader contextual influences, particularly the increasing impacts of climate change on water resources. Given these observations, the study recommends that the government prioritize subsidizing essential agricultural inputs, formulate policies to support sustainable crop production, and introduce financing initiatives aimed at improving water resource management and resilience against climate-related challenges.

Turkey has implemented various measures to control the rapid increase in COVID-19 cases and related mortality since the onset of the global pandemic. At the same time, researchers from diverse scientific disciplines have sought to analyze different aspects of COVID-19 in order to mitigate its social and economic impacts. Reliable and unbiased research outcomes, however, depend entirely on the availability of accurate and transparent data. The use of incomplete or distorted data can lead to flawed analyses and misguided policy decisions. In this context, Benford’s Law offers a statistical approach for evaluating the authenticity of reported figures and assessing the effectiveness of intervention measures. It can assist in addressing a critical question in pandemic monitoring: How reliable are the reported trends? The present study applies Benford’s Law to investigate whether the COVID-19 statistics published by Turkey conform to expected patterns, thereby examining the credibility of the officially released data.