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The purpose of this study is to investigate the behavior of a silicon solar cell when subjected to a magnetic field. Specifically, the study aims to understand how the presence of the magnetic field influences the distribution of excess minority carriers within the base region of the solar cell. By solving the one-dimensional continuity equation under these conditions, the study seeks to elucidate the transient dynamics of carrier generation, recombination and transport processes. This research contributes to the broader understanding of how external magnetic fields can impact the performance and efficiency of silicon solar cells, potentially informing future optimizations or applications in photovoltaic technology.

The solar cell is assumed to be uniformly illuminated, which simplifies the analysis of carrier generation to a function of depth (x). The emitter and space charge region contributions are considered while neglecting the diffusion region. The injection level remains constant throughout the analysis, focusing specifically on the base thickness region, H = 200 µm.

The findings of this study reveal significant insights into the behavior of a silicon solar cell under the influence of a magnetic field. Key findings include Impact on carrier distribution: the magnetic field affects the distribution of excess minority carriers within the base region of the solar cell. This distribution is crucial for understanding the efficiency of carrier collection and overall cell performance. Transient dynamics: the transient behavior of carrier generation, recombination and transport processes in the base region is influenced by the magnetic field. This understanding helps in predicting the response time and effectiveness of the solar cell under varying magnetic field strengths. Optimization potential: insights gained from this study suggest potential strategies for optimizing the design and operation of silicon solar cells to enhance their performance in environments where magnetic fields are present. Theoretical framework: the study provides a theoretical framework based on the one-dimensional continuity equation, offering a systematic approach to analyzing and predicting the behavior of solar cells under magnetic field conditions. These findings contribute to advancing the understanding of how external factors such as magnetic fields can impact the operation and efficiency of silicon solar cells, thereby guiding future research and development efforts in photovoltaic technology.

The originality and value of this study lie in its contribution to advancing the understanding of how magnetic fields influence silicon solar cell performance, providing both theoretical insights and potential practical applications in diverse technological contexts.

The present work describes a testing station for above‐water paints in Egypt. The station has been constructed on Alexandria Seashore.

Modified barium metaborate (BMB) was originally developed and patented as a mould inhibitor for oleoresinous systems. It was noted from exposures on our test fence that the product exhibited definite corrosion inhibiting properties. Through this observation further studies were initiated and it was determined that BMB was an excellent corrosion inhibitor in both latex and oleoresinous systems. Its effectiveness as a corrosion inhibitor is usually attributed to (1) its alkalinity which neutralizes the acidity of weathered paint films and which may reduce the reactivity of metal substrates, and (2) the metaborate ion which passivates the anode in essentially the same manner as the chromate ion.

Propensity to dollarize in Latin America in the demand-side of some economies of the region has a strong political risk component which, in the past, was mainly carried out by inflationary pressures. Coping with risk meant holding FCDs. A recursive multilevel model is developed and empirically tested with Colombia’s data to stress a country-specific tendency to dollarize due to political risk. The chapter’s conclusions suggest that consideration of issues, policies and implications inherent to the decision to dollarize cannot ignore that, the solution to any government-enforced dilemma in the supply-side of these economies, is also politically motivated. Results of a survey are also provided.

Within the framework of the valorization of natural resources, a characterization of the biochemical composition of the edible parts of Adansonia Digitata is applied. The antibacterial effect against bacteria is also realized and compared to some synthetic antibiotics.

The biochemical characterization is carried out according to the norms of the French Association of Normalization, methods of Association of Official Analytical Chemists (AOAC International) and gas chromatography (GC). The antibacterial activity is tested by disk diffusion on a solid medium. Parametric tests are used to compare the differences between groups and heat maps to show the expression of the mean inhibitions according to the studied parameters. Multivariate logistic modeling is applied to study the effect of extracts and antibiotics on bacteria.

Biochemical characterization showed a variable importance of proteins, fibers and total sugars, with the presence of highly desired fatty acids such as palmitic, oleic, stearic, linoleic and a-linolenic acids. This gives the tested parts important energy values, especially in the seeds very rich in fatty acids. Methanol proved to be a better extraction solvent than dichloromethane. Antibacterial activity showed that pulp and leaves extracted with methanol had quite similar inhibitory activities against Enterococcus faecalis ATCC29212 and that this effect was better than some antibiotics. Multivariate analysis showed that the leaves had a similar effect to antibiotics, and a significant effect against Staphylococcus aureus ATCC29213.

This important activity and the attractive nutritional value of this plant could justify its extensive use in the traditional pharmacopoeia.

This study explores the integration of Artificial Intelligence (AI) within family businesses. It seeks to understand how family-owned enterprises navigate the adoption of AI technologies amidst balancing traditional business values and the imperatives of digital transformation. The research addresses the gap in the existing literature by providing insights into the strategic, operational and cultural dynamics influencing AI adoption in family businesses, highlighting the unique challenges and opportunities they face in leveraging AI for competitive advantage while preserving their legacy.

Employing a qualitative research design, this study utilizes semi-structured interviews with key stakeholders in Turkish family businesses actively engaging in AI projects. Purposive sampling was adopted to ensure a diverse representation of industries and AI adoption stages. The interviews aimed to capture in-depth insights into the motivations, strategies and outcomes of AI integration within these enterprises. Thematic analysis was conducted on the interview transcripts to identify recurring themes and patterns, providing a nuanced understanding of the factors driving AI adoption decisions in the context of family business values and traditions.

The findings reveal that family businesses in Turkey perceive AI as a strategic tool to enhance operational efficiency and customer engagement. However, integrating AI technologies is often met with challenges, including resource constraints, digital literacy gaps and concerns over maintaining family legacy. Notably, businesses that successfully navigate AI adoption tend to employ tailored strategies that align with their core values, involving key family members in the decision-making process and fostering a culture of innovation. The study also highlights the importance of ethical considerations and governance in ensuring AI initiatives resonate with the family business ethos.

The study’s reliance on qualitative interviews within a single country context limits the generalizability of the findings. Future research could expand the geographical scope and incorporate quantitative methods to validate the identified themes across broader populations. Additionally, exploring the impact of generational differences within family businesses on AI adoption could offer more profound insights. The study underscores the need for a more nuanced understanding of the interplay between technology and tradition in family businesses, suggesting avenues for further investigation into how these enterprises can leverage AI to foster innovation while preserving their legacy.

This research offers practical guidance for family businesses contemplating AI integration. It emphasizes the importance of aligning AI strategies with family values and involving stakeholders across generations in the adoption process. The findings suggest that family businesses can benefit from investing in digital literacy and fostering a culture open to technological innovation. Additionally, the study highlights the need for robust governance structures to navigate ethical considerations in AI adoption. By adopting a strategic approach to AI integration, family businesses can enhance their competitiveness without compromising their core values, ensuring long-term sustainability and success in the digital era.

Integrating AI in family businesses has significant social implications, particularly regarding employment and preserving the family legacy. The study suggests that thoughtful AI adoption can contribute to job creation and skill development, counteracting concerns over job displacement. Moreover, by leveraging AI to align with their core values, family businesses can reinforce their role as stewards of social and economic stability within their communities. This research underscores the potential of AI to support the intergenerational transfer of knowledge and values, fostering innovation while preserving the unique cultural heritage of family enterprises.

This study contributes to the emerging literature on AI adoption in family businesses by exploring the Turkish context. It fills a gap in the literature by examining the unique challenges and opportunities family businesses face in integrating AI, highlighting the interplay between technological innovation and traditional values. The research offers valuable insights into tailored strategies for successful AI adoption that respect the legacy and ethos of family enterprises. By focusing on the socio-cultural dimensions of technology integration, this study enriches our understanding of how family businesses can navigate digital transformation while preserving their identity.

This paper aims to evaluate the antimicrobial and antioxidant activity of ethanol, methanol and aqueous extracts of the jujube fruit.

The fruit samples were harvested from Ziziphus lotus L. in three regions of Morocco: Aïn Chifae (Immouzer), Saiss (Fez) and Guercif. The fruit extracts were obtained by Soxhlet method using ethanol, methanol and water, and then a phytochemical screening was done for each extract. Total phenolic and total flavonoids contents were also determined. Afterward, the antimicrobial activity of the studied extracts was evaluated using the broth microdilution method. To estimate the total antioxidant effect of these extracts, the DPPH (2,2-diphenyl-1-picrylhydrazyl) scavenging and phosphomolybdate tests were performed.

Results showed that the highest content of polyphenols and flavonoids was found for ethanol and methanol extracts, while the lowest content was found in the aqueous extracts for all populations studied. Thus, results showed that the highest content of phenolic compounds was recorded in the population of Fez. Methanol extract of this population was the richest in polyphenols (30.36 mg/g) and in flavonoids (13.03 mg/g). The antimicrobial tests showed that Enterococcus faecalis and Pseudomonas aeruginosa were the most sensitive (6.25 mg/ml), compared to the other tested strains. Based on the minimal bactericidal concentrations/minimal fungicidal concentration or MFC/MIC ratio, it seems that ethanol extracts showed a bactericidal effect against Escherichia coli, Staphylococcus aureus and Bacillus subtillis, and a bacteriostatic effect against Enterococcus faecalis. On the other hand, the methanol extract showed bacteriostatic effect against Enterococcus faecalis and Pseudomonas aeruginosa. In addition, methanol extracts of Ziziphus lotus have significant antioxidant potent.

Methanol and ethanol extracts of Ziziphus lotus fruit have demonstrated strong antimicrobial effect. Moreover, the authors were able to show that the extract of Ziziphus lotus fruit has a very important antioxidant power.

The purpose of this paper is to weld polypropylene (PP) material by friction stir welding (FSW) process. The input process parameters considered were: tool pin profile, feed rate and tool rotational speed and the process output characteristics were tensile strength, Shore-D hardness, Rockwell hardness, Izod strength, Charpy strength and nugget area.

Optimization of process parameters were carried out based on response surface methodology (RSM) and significant parameters were obtained by performing analysis of variance (ANOVA).

The optimized results were the threaded pin profile for feed of 60 mm/min and tool rotational speed of 1,500 rpm. A confirmation test was carried out to verify the optimized results.

In this paper, the process parameters were optimized based on RSM. This is newly adopted optimization techniques in the FSW process of PP materials and also it gives better results.

This study aims to examine the role of personal and subjective norms in predicting waste sorting, an increasingly relevant pro-environmental behavior.

This study obtained data from a sample of 300 respondents from three Indonesian cities. Purposive sampling was employed to obtain information from specific segments of Indonesian population. The analysis consisted of a two-stage procedure including confirmatory factor analysis and covariance-based structural equation modeling.

Results demonstrated that both subjective and personal norms significantly and directly predict waste sorting behavior (WSB) bypassing intention to behave.

The fact that norms held by individuals are able to single-handedly drive pro-environmental behaviors implies that previous studies and social marketing campaigns may have overstated the role of intention.

In designing marketing communication programs promoting WSB, this paper argues that targeting normative tendencies of the audience may provide a more effective strategy than focusing on explicit pro-environmental intentions and attitudes of the public.

This study provided a new experimental test and confirmation of the role of subjective norms, the normative component of the theory of planned behavior and of personal norms, the normative component of the norm activation theory, in predicting WSB.

This study aims to explore the various approaches used in the general customer service industry to develop a conceptual framework for evaluating the responses of facility managers to user post-occupancy feedback.

This study uses conceptual analysis based on a comprehensive review of relevant literature.

The results of the study established 24 propositions which are categorised under organisational response dimensions specific to facilities management (FM): timeliness, facilitation, redress, apology, credibility of explanation, attentiveness, effort and their relationships with overall satisfaction and post-feedback behaviour, such as word of mouth and acceptance to continue using the facilities.

The established propositions are derived from existing theories using a deductive approach. The framework can be further enhanced to suit various applications in FM services.

This conceptual framework is a generic model, appropriate to many FM scenarios. The framework can be used to develop standard policies and procedures to foster and encourage collaborative relationships between users and facility managers. It reinforces transparency and trust between facility managers and users during the operation and management of the facilities, and improves FM effectiveness, facility performance and user post-occupancy experience.

In the FM area, no systematic approach has been previously established to evaluate and improve the response process to the users’ feedback. The proposed framework is a pioneer contribution in this area.