This paper considers simultaneously two areas of facility location and assortment planning in a competitive environment. In fact, a chain store that has competitors in the market locates a new facility. As there are different products in the market that can substitute with each other, it is intended to determine the best product assortment as well. An integer nonlinear programming problem is proposed to model the mentioned subject. For solving the model, the problem is reformulated as a mixed integer linear programming one. Therefore, a MIP solver software can be used for solving the small- and medium-size problems. For large-scale problems, a firefly algorithm is designed for obtaining a satisfactory solution. By using the proposed model, it is numerically shown that, in addition to the optimal location, it is also necessary to determine simultaneously the best product assortment for the new store. Actually, comparison results reveal that the location significantly affects the assortment scenarios for the new store. In other words, the selection of new store locations may lead to loss of large profit if the assortment planning is neglected.

This study aims to explore how service quality and police performance contribute to building public trust and enhancing overall satisfaction. In an era where public perception of law enforcement is critically important, understanding the key factors that influence trust in the police is essential. The research involved 306 police officers actively serving in the field, with data collected through a questionnaire distributed via Google Forms. The primary data were analyzed using the Structural Equation Modeling Partial Least Squares (SEM-PLS) method. The analysis results indicate that the service quality of police officers does not directly enhance public satisfaction, as police performance is not adequately supported by service quality. However, police performance significantly contributes to public satisfaction, as this effect is strengthened by trust as a moderating factor. Additionally, police performance does not act as a mediating factor in the relationship between service quality and public satisfaction.

Trivalent analytes such as Fe³⁺, Cr³⁺ and A^l3+ play pivotal roles in various fields including environmental monitoring, biological sensing, and industrial processes. The development of efficient and selective detection methods for trivalent species is therefore of paramount importance. In this review, we present an overview of recent advances in the recognition of trivalent analytes using simple organic chromogenic and fluorogenic probes. In this review we discuss the strategies employed for the design and synthesis of chromogenic and fluorogenic probes tailored for trivalent analytes, highlighting key structural motifs and functional groups that contribute to their recognition capabilities.

Guided by a real case, this paper efficiently proposes a new metaheuristic algorithm based on Simulated Annealing to solve the Heterogeneous Vehicle Routing Problem with Time Windows to deliver fresh meat in urban environments. Our proposal generates an initial feasible solution using a hybrid heuristic based on the well-known Travelling Salesman Problem (TSP) solution and, subsequently, refining it through a Simulated Annealing (SA). We have tested the efficiency of the proposed approach in a company case study related to the planning of the transportation of a regional distribution center meat company to customers within the urban and rural perimeter of Bogotá, Colombia. The main goal is to reach a service level of 97% while reducing operational costs and several routes (used vehicles). The results show that the proposed approach finds better routes than the current ones regarding costs and service level within short computing times. The proposed scheme promises to solve the refrigerated vehicle routing problem.

Studies on the role of gender, family businesses, and non-family businesses in examining financial management practices, particularly in developing countries, have been largely overlooked. This research, based on the collaboration between Positive Accounting Theory (PAT) and Agency Theory, aims to explore the intervention of microfinance in micro and small agricultural enterprises (MSEs). Using a quantitative approach, the study employs the Structural Equation Model Partial Least Square (SEM-PLS) method with a sample size of 656 respondents, comprising ultra-micro and small business actors in the agricultural sector in Indonesia. The findings indicate that for micro-sized businesses, entrepreneurial success mediates the relationship between microfinance and subjective wellbeing, while in small-sized businesses, poverty reduction and entrepreneurial success fully mediate the relationship between ultra-microfinance and subjective wellbeing. Ultra-microfinance assists business owners in enhancing their financial resource capacity more easily. On the other hand, microfinance not only provides financial access but also offers training and mentorship programs, helping business owners achieve long-term success. The study also reveals that gender does not mediate the relationship between microfinance and subjective wellbeing. Gender inequality in accessing resources, differences in decision-making participation, and social norms that still limit women's roles in economic activities within the agricultural sector are contributing factors. The implication of this study is to provide insights for decision-makers in the agricultural MSME sector to enhance subjective wellbeing. It is hoped that poverty alleviation programs through microfinance initiatives, such as PNPM, can be optimally absorbed and have a positive impact on empowering business owners to reduce structural poverty, especially in the key sector of agricultural businesses.

The synthesis of 4-aryl-NH-1,2,3-triazoles in good to excellent isolated yields (75-95%) has been achieved via a [3+2] cycloaddition of aromatic nitroolefins and sodium azide catalyzed by recyclable heterogeneous sulfated tin oxide (STO, 10 mol%) in toluene at 60 0C. Aliphatic nitrooefines proved to be unsuccessful partners in the present methodology.

This article aims to study technological intelligence in innovative startups in Algeria using Kerr’s model. Technological intelligence consists of four main dimensions: intelligent systems, competitive intelligence, market intelligence, and intelligent processes. To collect data, a questionnaire was distributed to a sample of 255 innovative startups in Algeria, and the data were analyzed using confirmatory factor analysis (CFA) with Smart PLS software. The results indicated that the two-dimensional model combining intelligent systems and competitive intelligence provided the best fit, with a relationship value of 0.605 between these two dimensions. On the other hand, the relationship between market intelligence and competitive intelligence was weak, with a value of 0.281, reflecting the limited use of analytical methods by startups to monitor competitors. Based on these findings, the study recommends that innovative startups in Algeria enhance their use of competitive intelligence and intelligent systems to improve decision-making processes. Additionally, these startups should make better use of available market technologies to develop their products and services, while focusing on continuous competitor analysis and identifying opportunities. In conclusion, technological intelligence is a strategic element for startups, helping them improve their performance and achieve a competitive edge in the changing business environment in Algeria.

Due to their high synthetic efficiency, multi-component reactions (MCRs) have shown to be extraordinarily effective at producing compounds in a single synthetic operation. The chromeno[2,3-d] pyrimidine moieties represent important building blocks in synthetic bioactive compounds. The reaction of barbituric acid, aldehydes, and cyclohexane-1,3-diones in the presence of zinc acetate (5 mol%) under neat conditions at 70 0C, yielded a facile and one-pot synthesis of corresponding chromeno[2,3-d]pyrimidineones. Thirteen compounds containing neutral, withdrawing and electron donating groups (H, NO₂, -CN, -Cl; -OH, -CH₃ and -OCH₃) were synthesized in good, isolated yields ranging from 78-91%. The successful involvement of o-, m-, and p- substituted nitro benzaldehydes suggested that steric hindrance had no effect. All of the synthesized compounds are well-known, and this process is unique in that it makes use of zinc acetate, an accessible, low-cost Lewis acid catalyst.

A new series of Schiff bases derived from pyrazole-thiocarbohydrazide, namely (4a-d), were well-synthesized. The synthesis is carried out using monothiocarbohydrazone derivative (3), which was prepared via coupling of 5-chloro-pyrazole-4-carbaldehyde (1) with thiocarbohydrazide (2) in absolute ethanol that contains a catalytic quantity of acetic acid. The structures of newly synthesized compounds were fully clarified by various spectroscopic analyses (FT-IR, ¹H-NMR, ¹³C-NMR, and mass spectra) and elemental analysis. Also, the molecular docking was performed to investigate the binding interactions of the synthesized compounds (1, 3 and 4a-d) with COX-2 active site. The results revealed that most of them have robust hydrogen bonding networks and favorable binding energies compared to compound (4b). Understanding the anti-inflammatory behavior through understanding the specific interactions of these compounds with COX-2 will aid in the design and development of more effective inhibitors for therapeutic applications.

Manufacturers employ AI for monitoring vehicle mileage, inspecting components, and scheduling maintenance. Past studies underscore the need for auto-related plans to prioritize environmental protection, concentrating on AI-driven environmental solutions promoted by AI for Good. AI enhances brand success by improving investment, technology, and promotional capabilities. This study emphasizes consistency in AI application across the automotive value chain for brand sustainability. A web-based poll surveyed 120 AI users in marketing, HR, sustainability, as well as 180 sustainability specialists and regulators. The primary goal is to assess, via structural model evaluation, how extraneous variables affect the development of AI-powered brand sustainability strategies. The study highlights AI's sustainability benefits in the automotive industry improving transportation safety, forecasting maintenance, and creating eco-friendly vehicles. However, challenges involve over-reliance on AI, predicting human behavior, and addressing sustainability threats. AI development should consider regional differences, prioritizing openness, policy harmony, and consumer agency. These findings aid marketing and HR professionals in devising customer-centric long-term plans.