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This study focuses on the selection of armed unmanned aerial vehicles (AUAV), which have recently taken an important place on the world agenda, are used effectively in the defense industry and change the war systems of countries. This study aims to select the most suitable armed AUAV by using and comparing multi-criteria decision-making (MCDM) methods.

There are various types of (unmanned aerial vehicles) UAVs, and some of them are Armed UAVs. This study used the criteria obtained from the market and previous UAV studies and ranked/selected various AUAVs produced in line with the determined criteria. The AHP method was used to prioritize the criteria, and the PROMETHEE method, a powerful ranking method, was used to rank/select the alternatives.

By the expert judgments, the payload capacity (28.2%) criteria took first rank by far as the most important criteria. The AUAV alternatives are listed as 1-6-5-2-7-3-4, respectively.

UAVs around the world have been showing significant and rapid developments recently, and those concerned closely follow developments in this field. Depending on the development of the aviation industry and technology, UAVs provide services to individuals or institutions in various ways for civil or military use.

The difference from similar studies is the research of Armed UAVs. Sensitivity analysis was performed and alternatives were analyzed by their weights. Comparisons were made using the MEREC, LOPCOW, and ELECTRE methods.

This study aims to analyze and understand mutual relationships between lean and agile enabling factors in the context of the construction domain and put forth the most driving and dependent enablers for a hybrid lean–agile system (HLAS).

A threefold research flow is adopted. First, the content analysis of literature stemmed from the identification of preliminary enablers (n = 26). Second, a questionnaire survey (n = 101) is administered to downsize enablers to ten using the relative importance index. Further, in the third phase, interpretive structural modeling (ISM) and the cross-impact matrix multiplication applied to classification analysis were performed amid the ten key enablers through pairwise interactions from subject matter experts (n = 19). Hierarchical representation of enablers has been presented, which facilitates a conceptual model for application in the construction industry.

The ISM model demonstrates a three leveled classification structure that showcases direct and transitive relationships among various enablers. “Use of project management tools” is the driving enabler, followed by “collaborative and common data platform working” and “institution of team training” are critical enablers to HLAS adoption.

A structured way of identification of interdependent among lean–agile is a vital unique contribution to this study. The results serve as a knowledge base for practical adoption of HLAS and may prove to be influential in developing a framework for easier adoption in developing countries.

Technology-enabled healthcare focuses on providing better information flow and coordination in healthcare operations. Technology-enabled health services enable hospitals to manage their resources effectively, maintain continuous patient engagement and provide seamless services without compromising their perceived quality.

This study investigates the role of technology-enabled health services in improving perceived healthcare quality among patients. Data are collected from the users (n = 418) of health platforms offered in multi-specialty hospitals. Multiple learners are employed to accurately represent the users' perceived quality regarding the perceived usefulness of the features provided via these digital health platforms.

The best-fitted model using a decision tree classifier (accuracy = 0.86) derives the accurate significance of features offered in the digital health platform in fostering perceived healthcare quality. Diet and lifestyle recommendations (30%) and chatting with health professionals (11%) are the top features offered in digital health platforms that primarily influence the perceived quality of healthcare among users.

The predictability of perceived quality with the individual features existing in the digital health platform, the significance of the features on the perceived healthcare quality and the prediction rules showing the combined effect of features on healthcare quality can help healthcare managers accelerate digital transformation in hospitals by improving their digital health platform, designing and offering new health packages while strengthening their e-infrastructure.

The study represents perceived healthcare quality with the features offered in digital health platforms using machine learners based on users' post-pandemic experience. By advancing digital platforms with more patient-centric features using emerging technologies, this model can further foresee its impact on the perceived quality of healthcare, offering valuable directions to healthcare service providers. The study is limited to focusing on digital health platforms that can deal with people's general healthcare needs.

The purpose of this study is to establish Loratadine [LRD] quantification in purified and capsule formulations using a precise and specific Reversal Phase with a very high-performance liquid Chromatographic [RP-HPLC] technique. The approach was evaluated in agreement with the principles of the International Conference on Harmonization [ICH]. Arcus EP-C18 Ion Pac column, 5 m, 4.6 mm, 250 mm, mobile phase Methanol: Acetonitrile (60:40) v/v. Dibasic potassium phosphate buffer, pH 7.2, flow rate 1.0 ml/min.

The HPLC system used a 340 nm UV detector for testing. A 10-min run time was used for the analysis. At concentrations ranging from 2 to 10 g/ml, the technique was linear (R² = 0.9998), exact (intra-day and inter-day relative standard deviation [RSD] values 1.0%), accurate (range recovery = 96%–102%), exclusive and strong.

The detecting and quantitation limits were 0.92 g/ml and 2.15 g/ml, respectively.

The findings demonstrated that the proposed method could accurately determine LRD in bulk and pill dose formats quickly and accurately.

Workforce insufficiencies can impair firms' competitiveness in the hospitality industry. The problem of finding suitably trained employees has been aggravated by changes in consumer preferences, and the development of advanced technologies has led to the ‘smartization’ of upscale hotels. The consequent updating of business models means that decisive indicators of worker competence and employability are different from those applied previously. Thus, the aim of this study is to develop an indicator framework for assessing workforce employability with consideration of competence with artificial intelligence (AI) applications.

The initial indicators for the framework are obtained based on an intensive review of the relevant literature and roundtable meetings with academics and practitioners. The Delphi method is used to collect the data, and a hybrid fuzzy approach, which combines the modified Z-number and modified trapezoidal fuzzy number set techniques, is applied to quantify the information originating from the experts’ judgments. The interquartile range approach is applied to optimize the validity of the indicators.

The assessment framework is applied to evaluate workforce employability at an upscale hotel from the perspective of hotel executives. The capability of the workforce for the adoption of advanced technologies, including familiarity with AI, are considered.

The contributions of this research involve the identification of an updated list of determinants for the evaluation of workforce employability for hotels in today’s world, highlighting the value of AI applications to help ameliorate labor shortage problems. The results should benefit practitioners, allowing them to improve the efficiency of their operations, services and management practices, leading to sustainability and competitiveness in the upscale hotel industry.

Recent trials have found that propolis supplementation can beneficially reduce blood pressure (BP) in adults, but there is no definitive consensus on this topic. The purpose of this study is to provide an overview and update the current documents regarding the effects of propolis supplementation on BP by presenting a systematic review and meta-analysis.

The systematic search was conducted, considering all studies published up to July 2024, in the following databases: PubMed, Scopus, Cochrane Library and ISI Web of Science. Data were pooled by using the random-effects model, and weighted mean difference (WMD) was considered as the summary effect size.

In this systematic review and meta-analysis, eight clinical trials were included. The obtained results show that propolis supplementation caused a significant decrease in systolic BP (WMD = −3.93 mmHg, 95% CI = −7.05 to −0.82, p = 0.01 and I2 = 45.2%). However, the meta-analysis results showed that propolis supplementation did not significantly change the levels of diastolic BP (WMD = −1.64 mmHg, 95% CI = −4.60 to 1.32, p = 0.27 and I2 = 74.0%).

The findings of this study suggest that propolis supplementation may be used as a dietary supplement to improve systolic BP, but further studies are needed to confirm these results.

This study aims to investigate experimentally and numerically the thermal analysis of a wavy diverging-converging corrugated enclosure, partitioned into two parts under the effect of magnetohydrodynamic (MHD) natural convection. The left part was filled with Al₂O₃/C₂H₆O₂ nanofluid, while the right part was Al₂O₃/C₂H₆O₂ saturated by a porous medium, featuring a corrugated cylinder at the center. This system is relevant to many engineering applications. Key factors affecting thermal performance, such as nanofluid volume fraction, Darcy number, Hartmann number, inclination angle of MHD and Rayleigh number, were analyzed. This study evaluated the impact of these parameters on stream function, average Nusselt number and isothermal lines under three heat source scenarios: heating the corrugated cylinder, heating the magnetic source and heating the nanofluid, porous media and corrugated walls.

The main governing equations for the nanofluid flow are mass, momentum and heat transfer, while the porous media are modeled using the Darcy–Brinkmann model. These governing equations are transformed into a dimensionless form and solved numerically using COMSOL 6.0 based on the finite-element method. Dynamic viscosity, density and thermal conductivity equations are used to calculate the properties of the nanofluid at different volume concentrations.

The results showed that increasing the Rayleigh number (Ra) and Darcy number (Da) increased the Nusselt number by 55%, indicating enhanced heat transfer. A vertical magnetic source (γ = 90°) further improved thermal performance. Conversely, thermal performance decreased with increasing Hartmann number (Ha). The highest Nusselt number was observed when the heat source was applied to the corrugated cylinder, followed by the right side with nanofluid–porous contact and was lowest for the left side with nanofluid contact. Experimental data demonstrated that the presence of a magnetic field can significantly increase the temperature, thereby enhancing heat transfer by natural convection, particularly when the heat source is applied in the region of nanofluid–porous contact.

The primary originality of this work lies in the use of a novel design featuring a diverging-converging structure with a wavy wall. In addition, it uses two types of fluids simultaneously, dividing the enclosure into two sections: the right side contains nanofluid mixed with a porous medium, while the left side is filled with nanofluid only. The system also includes a corrugated cylinder at its center with four undulations. The position of the heat source significantly influences heat dissipation. Therefore, three different positions were examined: heating the cylinder at a constant temperature, heating the left side of the enclosure and heating the right side.

This study aims to meta-analytically investigate the impact of educational technology interventions on the development of creative thinking in educational settings. In recent years, the debate among researchers has persisted regarding the impact of various educational technologies, including interactive learning environments, digital instruction and platforms, and educational games and robotics, on students' creative thinking in diverse educational settings due to inconsistent findings.

This study, conducting a meta-analysis by synthesizing 35 relevant empirical studies with 2,776 participants, aims to investigate the association between educational technology interventions and the Torrance Tests of Creative Thinking (TTCT) and its subscales (fluency, flexibility, originality and elaboration).

No evident publication bias was found. From a general perspective, the results demonstrate a moderate level of influence of educational technology on the overall TTCT scale, with high heterogeneity attributed to the adopted instruments, mixed methods and target outcomes. Additionally, the results indicate that only three of the TTCT subscales (fluency, flexibility and originality) are influenced by educational technologies. Among the interventions, interactive learning environments yielded medium to the largest mean effect size. Furthermore, moderator analyses suggest that the effects of interventions on two subscales of TTCT (flexibility and originality) are moderated by school types, research design and the duration of intervention. The conclusion drawn is that interventions promoting students' creative thinking in different educational settings are efficacious.

Despite the low homogeneity of the results, which might have influenced the findings, the large fail-safe N suggests that these findings are robust. The study examined potential causes of heterogeneity and emphasized the importance of further research in this area.

Construction waste reduction (CWR) plays a vital role in achieving sustainability in construction. A good CWR practice can result in optimizing material usage, conserving natural resources, limiting environmental pollution, protecting the environment and enhancing human health. In this regard, the purpose of the current study is to identify the most relevant organizational policies that aid in waste reduction and concurrently explores the congruent measures to be adopted during the construction process in the Indian high-rise building sector.

The research findings were obtained through a mixed- method approach. Content analysis was used to identify waste reduction measures (variables) targeting on the two domains of construction – “waste-efficient execution” and “waste – mitigating organizational policies.” Furthermore, the authors explored and documented the key measures from the identified waste reduction measures using the constraint value of the relative importance index. As the next step, the study listed the theoretical hypothesis based on expert interviews and tested the theory through confirmatory factor analysis.

The results revealed that “waste sensitive construction techniques and strategies” as the most significant category under the domain “Execution” with a path coefficient of 0.85. Concurrently, the study has also determined that “control procedures for budget, quality and resources” as the most effective organizational approach in reducing construction waste in the Indian building industry, with a path coefficient of 0.83.

The current research is context-sensitive to the Indian construction sector. It presents the stakeholder’s perspective on construction waste reduction and the relevant measures to be implemented to reduce construction waste in high-rise building projects in India. It can also act as a concordance for decision-makers to further focus on CWR management and aid in formulating policies suitable for the Indian context.

Design cost overrun is one of the prominent factor that can impact the sustainable delivery of the project. It can be encountered due to a lack of information flow, design variation, etc. thereby impacting the project budget, waste generation and schedule. An overarching impact of this is witnessed in the sustainability dimensions of the project, mainly in terms of economic and environmental aspects. This work, therefore, aims to assess the implications of a technological process, in the form of building information modelling (BIM), that can smoothen the design process and mitigate the risks, thus impacting the sustainability of the project holistically.

The identified design risks in construction projects from the literature were initially analysed using a fuzzy inference system (FIS). This was followed by the focus group discussion with the project experts to understand the role of BIM in mitigating the project risks and, in turn, fulfilling the sustainability dimensions.

The FIS-based risk assessment found seven risks under the intolerable category for which the BIM functionalities associated with the common data environment (CDE), data storage and exchange and improved project visualization were studied as mitigation approaches. The obtained benefits were then subsequently corroborated with the achievement of three sustainability dimensions.

The conducted study strengthens the argument for the adoption of technological tools in the construction industry as they can serve multifaceted advantages. This has been shown through the use of BIM in risk mitigation, which inherently impacts project sustainability holistically.

The impact of BIM on all three dimensions of sustainability, i.e. social, economic and environmental, through its use in the mitigation of critical risks was one of the important findings. It presented a different picture as opposed to other studies that have mainly been dominated by the use of BIM to achieve environmental sustainability.