In military operations, the proficient overcoming of water barriers is paramount, with sub-optimal execution potentially leading to significant human and equipment casualties. In this context, global armed forces accord considerable emphasis to the selection of appropriate mechanisms for water obstacle overcoming. This study elucidates the adoption of a Multi-Criteria Decision-Making (MCDM) approach for the selection of optimal pontoon bridge sets for military applications. Criteria identification was undertaken by seven distinguished experts, leading to the determination of weight coefficients using the Defining Interrelationships Between Ranked criteria II (DIBR II) method. Expert assessments were subsequently aggregated utilizing the Normalized Weighted Bonferroni Mean (NWBM) operator. The Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA) method, operationalized within the Fermatean Fuzzy (FF) environment, was harnessed for the discernment of the best alternative. An analysis of the sensitivity of the study's findings with respect to variations in criteria weighting, coupled with a comparative exploration, led to the inference that the proposed MCDM model boasts stability. However, it was noted that the model exhibits sensitivity to shifts in criteria weight coefficients, underscoring its utility as a valuable aid for decision-makers, especially in the domain of pontoon bridge set selection.

In today's digital age, organizations have harnessed unprecedented connectivity and technological advancements, leading to enhanced efficiency and productivity. However, this progress has also exposed businesses to a multitude of cyber threats, including data breaches, ransomware attacks, and social engineering exploits. This research explores the relationship between organizational culture and cybersecurity practices, emphasizing the importance of fostering a security-first culture within organizations. While technical measures are crucial, neglecting the role of organizational culture can hinder effective cybersecurity.

The study is grounded in the theory of planned behaviour and the cultural dimensions theory, providing a solid theoretical foundation. Moreover, the investigation delves into the Denison organizational culture model, particularly focusing on the role of participation in nurturing a security-first culture. This becomes particularly relevant when assembling collaborative, inclusive, and communication-driven multi-disciplinary teams. Leadership emerges as a pivotal aspect in establishing a security-first culture. The onus lies with executive leadership at the highest echelons of the organization. However, it is concerning that in certain well-established companies, some senior executives continue to perceive cybersecurity as the sole responsibility of the IT department, overlooking its leadership significance.

In the pivotal task of selecting an assault boat conducive for military operations, especially amidst the challenges posed by water obstacles, the utilisation of Multi-Criteria Decision-Making (MCDM) methods surfaces as vital. In this investigation, a meticulous application of the DIBR II (Defining Interrelationships Between Ranked criteria II) - BM (Bonfferoni Mean) – CoCoSo (COmbined COmpromise SOlution) multi-criteria decision-making model is performed. Initially, the weight coefficients of the criteria were determined via the DIBR II method, with expert opinions being cohesively aggregated using BM operators. Subsequently, the CoCoSo method was employed to discern the optimal alternative among various assault boats. A comprehensive analysis, entailing the examination of the sensitivity of the output results to alterations in the weight coefficients of the criteria, was conducted post-final ranking of alternatives. Noteworthy is the finding that negligible deviations in defining the weight coefficients by experts do not impose a significant impact on the ultimate selection of the optimal alternative. Furthermore, a comparative analysis alongside other MCDM methods corroborated not only the efficacy but also the superiority of the implemented model. The insights derived underscore the practical applicability, stability, and accuracy of the proposed model in choosing assault boats for military operations. This exploration fortifies the decision-making process in military contexts related to overcoming water obstacles and portends potential applicability in domains necessitating intricate multi-criteria decision-making.

Diabetic retinopathy, a severe ocular disease correlated with elevated blood glucose levels in diabetic patients, carries a significant risk of visual impairment. The essentiality of its timely and precise severity classification is underscored for effective therapeutic intervention. Deep learning methodologies have been shown to yield encouraging results in the detection and categorisation of severity levels of diabetic retinopathy. This study proposes a dual-level approach, wherein the MobileNetV2 model is modified for a regression task, predicting retinopathy severity levels and subsequently fine-tuned on fundus images. The refined MobileNetV2 model is then utilised for learning feature embeddings, and a Support Vector Machine (SVM) classifier is trained for grading retinopathy severity. Upon implementation, this dual-level approach demonstrated remarkable performance, achieving an accuracy rate of 87% and a kappa value of 93.76% when evaluated on the APTOS19 benchmark dataset. Additionally, the efficacy of data augmentation and the handling of class imbalance issues were explored. These findings suggest that the novel dual-level approach provides an efficient and highly effective solution for the detection and classification of diabetic retinopathy severity levels.

Road transport emerges as a crucial segment of the transportation system, demanding comprehensive analyses of operational performance across passenger and freight domains. This investigation delineates a meticulous multi-criteria analysis of Serbian passenger and freight road transport, relying on data extracted from the Annual Statistical Reports promulgated by the Statistical Office of the Republic of Serbia during 2015-2021. Initially, a compendium of eight pertinent criteria, namely carrying capacity, total number of passenger and tonne-kilometres, employee count, generating power, fuel consumption, and foreign currency receipts, is identified, with a subsequent emphasis placed on six criteria necessitating multi-criteria analysis, applicable cohesively to both passenger and freight transport sectors. Weighting coefficients for each criterion are calculated employing the entropy method, while a multi-criteria ranking of the operational performance of road transport is devised through the application of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The quintessence of this research lies in the execution of a novel multi-criteria analysis with an aspiration to architect a hierarchy regarding the operational performance within the scrutinised timeframe of road transport in Serbia.

In the design of shell and tube heat exchangers encompassing a condensing zone, meticulous attention is required due to the complexities surrounding forced convection in multiphase systems. Despite extensive research, the intricacies within these multiphase systems have remained elusive, rendering the heat transfer coefficient unresolved. In this study, a novel methodology is introduced to elucidate the thermal characteristics of forced convection within the condensing region of shell and tube condensers. An amalgamation of theoretical methods, specifically the Logarithmic Mean Temperature Difference (LMTD), and empirical data sourced from industrial operations forms the foundation of this approach. Upon rigorous analysis employing both Power Law Analysis and Logarithmic Linear Regression, a correlation in terms of ${N_u}=C \cdot {Re}^m \cdot {Pr}^{\mathrm{n}}$ within the condensing region was discerned using Buckingham Pi Theorem. Findings revealed coefficients of C=1.15, m=0.893, and n=13.442. For optimization purposes, the Particle Swarm Optimization (PSO) Algorithm was employed. A focused examination of parameters such as tube length, tube outside diameter, baffle spacing, shell diameter, number of tube passings, and tube wall thickness revealed that by attenuating their values by 30%, 46%, 80.3%, 8%, 50%, and 61.9% respectively, a substantial increase in condenser effectiveness was observed, elevating the value from 0.9473 to 4.299.

The Bayano region, in Panama, has been linked to many different stakeholders who were or are influenced by the Bayano dam, which was completed in 1976 and flooded a large area. Stakeholder tables are a good way of exploring the views of stakeholders and their relationships. They can also help in identifying hidden stakeholders. Hidden stakeholders refer to stakeholders who use or are impacted by regions or events, but are generally ignored. A primary goal of this research is to allow a better understanding of the region. In this study, several sources, including discussions with community members and workshop results, were used to develop a stakeholder table for the Bayano region. Stakeholders include displaced Guna and Embera Indigenous communities. In order to identify hidden stakeholders, I applied the table to relevant court cases and agreements, with hidden stakeholders being those who were not addressed in these documents. Hidden stakeholders include Indigenous individuals who raise cattle or are involved in tree felling, along with tourism industries. Using some follow-up workshops to gauge views on potential interventions, along with a relational values approach, which focuses on relationships with components such as nature, I highlight sustainable projects and methods that can target multiple hidden stakeholders at the same time. As such, another goal was to illustrate potential, sustainable projects that would include many hidden stakeholders. In the end, this research helps understand the stakeholders in the Bayano region and the results can also help other researchers involved in the region and beyond.

Purpose: The purpose of the study was to assess the impact of activity based costing system on financial performance of SMEs. It was observed that high escalating operating costs is a serious cause of concern in most SMEs in Zimbabwe. In order to establish the impact of activity based costing system on financial performance of SMEs, the study would like at the benefits of using activity based costing system, the effects of activity based costing system on cost control, the problems faced with use of activity based costing system and the cost drivers of activity based costing system. Methodology: A descriptive design research methodology was adopted to gather data through use of questionnaires from a population of 15 employees. Data analysis was undertaken by use of SPSS to determine correlations and tables, pie charts and graphs facilitated data presentation. Findings: From the findings, activity based costing system had negative effects on the cost control reduction concluding that there was an insignificant relationship. Originality value: training of employees is important to equip them with the necessary knowledge and skills and applying an effective ABC system.

Purpose: This study examines the impact of firm financial performance, free cash flow, and cash holding on the overinvestment of manufacturing companies listed on the Indonesia Stock Exchange in 2017-2021. Methodology: We employed 315 manufacturing companies listed on the Indonesia Stock Exchange for the 2017-2021 period as samples. The data required is correlated to financial performance, free cash flow, cash holding, and company overinvestment. Data is input manually from the financial reports obtained from the website of each firm. To examine the hypothesis, this study applied multiple regression analysis methods. Findings: The results show that free cash flow has a significant and negative effect on overinvestment. It illustrates that higher free cash flow does not encourage a manager to overinvestment. This result support hypothesis 1 (H₁). Cash holding affects overinvestment positively and significantly. These results indicate that higher cash holdings inspire managers to overinvestment. These results support hypothesis 2 (H₂). Firm performance influences overinvestment negatively and significantly. This result indicates that higher firm performance does not motivate a manager to overinvestment. These results support hypothesis 3 (H₃). Originality/Value: Difference from the previous study, this study examines the impact of financial performance, free cash flow, and cash holding on overinvestment in one comprehensive model.

An augmenting body of research is elucidating the psychological impacts of climate change, revealing a potential positive linkage between climate change anxiety and sustainable consumption through constructive concern. This investigation seeks to discern the presence and magnitude of a statistically significant relationship between climate change anxiety and patterns of sustainable consumption behaviour. The research employs a convenience sampling method, acquiring data through a causal study, whereby 455 valid survey responses were collected from 12th May to 12th June 2023. The interactive survey, formulated via Google Forms, was disseminated across Turkey. Analytical procedures were performed utilising SPSS and LISREL software, incorporating exploratory factor analysis (EFA) and structural equation modelling (SEM) to interpret the data. Findings reveal a statistically significant relationship, within a 95% confidence interval, between climate change anxiety and sustainable consumption behaviour. A surge in climate change anxiety correlates with heightened environmental sensitivity, augmented saving tendencies, and an escalation in reusability inclinations. Conversely, it is associated with a decline in superfluous purchasing behaviour. It can be concluded that enhanced climate change anxiety among participants concomitantly amplifies their proclivity towards sustainable consumption’s sub-dimensions, such as environmental sensitivity, frugality, and reusability, while discretionary purchasing behaviours witness no augmentation. Certain limitations permeate the study: out of 487 respondents, 32 were omitted from analysis, suggesting the necessity for larger sample sizes in subsequent studies. Amplifying climate change awareness and endorsing sustainable consumption behaviour is pivotal to fostering a more sustainable world. Findings from the SEM imply that elevating environmental sensitivity could burgeon awareness regarding climate change. Given the pressing nature of the climate crisis, the current study postulates that climate change anxiety could serve as a catalyst for inducing sustainable consumption behaviour and underscores the imperative for further intricate research within this domain.