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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.

To determine the electrical, structural, optical and transport properties calculated using WIEN2k code.

By employing the WIEN2k code, we have theoretically examined the physical properties of the full-Heusler Te₂AcGa alloy. The FP-LAPW technique is utilized for theoretical calculations.

An indirect bandgap of 0.42 eV is seen with the GGA potential. An enhancement in bandgap with a value of 0.97 eV is observed with mBJ potential. The density of states is determined to verify the band structure profile. The dynamical and structural stability is attained through the computations. The electron density contour plot is utilized to explore the bonding nature of the compound. Optical properties have been calculated with respective potentials showing significant absorption in the visible region. Furthermore, thermoelectric properties have been evaluated to confirm the potential of Te₂AcGa for thermoelectric devices. At elevated temperatures, the ZT with mBJ potential obtained a large value of 0.8.

High absorption and ZT values make the Te_2AcGa alloy have potential for optoelectronic and renewable energy devices.

In the submitted manuscript, first principle calculations are carried out for the first time to study the structural, dynamic, electronic, optical and thermoelectric properties of the full-Heusler Te₂AcGa alloy. Modified Becke–Johnson (mBJ) exchange-correlation potential provides very accurate results. The bandgap profiles and related properties are calculated in the present work. The entire work gives useful results of fundamental importance, which can be utilized for the fabrication of optoelectronic and thermoelectric applications.

The presentation refers to simulations of magnetization processes of the spring-exchange magnetic composites containing magnetically soft and ultra-high coercive phases. In particular, the aim of this study is to investigate the possibility of reducing expensive rare earth (RE) in the so-called neodymium magnets and improving their efficiency.

In order to model hysteresis loops, a special disorder-based Monte Carlo procedure, suitable for irregular geometry of the composites, was applied. The chosen system parameters were defined in order to model Nd2Fe14B/Fe composites.

The results suggest potential for optimizing hard magnetic composites. Magnetization curve parameters are sensitive to grain coupling and easy magnetization axis ordering. Strong coupling for a single-phase hysteresis loop is unachievable for grains above a certain size, i.e. found to be a few hundred nanometers. Considering these factors and their interdependencies, it’s possible to enhance the |BH|max parameter or reduce the RE content.

The research was carried out using computer simulations, which by their nature are only approximations of physical processes. The next stage of research is to produce the described composites and test their actual properties.

The research enhances permanent magnets, boosting efficiency in technologies like wind turbines and electric motors, indirectly benefiting the environment. It also reduces RE elements in magnets for environmental, economic and political gains.

The unique approach is to consider the random orientation of the magnetic anisotropy of the hard magnetic grains, which is close to real powder composites. The results provide valuable guidance for the production process of permanent magnets.

This article aims to assess risks related to the supply chain 5.0 digitalization. It aims to analyze interdependencies and causal relationships between critical digital supply chain 5.0 risks, emphasizing the need for proactive management to address emerging challenges.

Through an extensive literature review and expert judgment, risks related to supply chain 5.0 digitalization are identified. An integrated approach for risk assessment is employed, where the Analytic Hierarchy Process (AHP) is utilized to prioritize these risks. Subsequently, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is employed to investigate cause-and-effect relationships among the identified top 10 risks. This comprehensive analysis forms the basis for informed strategic management decision-making.

The analysis identifies significant influences of “Dependence on technology,” “Complexity”, “Potential system failures”, and “Cyber security” while “Environmental impact” and “Socio-economic disparities” emerge as prominent risks in supply chain 5.0 digitalization. These findings offer actionable insights for management decision-making, guiding the formulation of strategies to address and mitigate critical risks.

The proposed integrated approach (AHP-DEMATEL) provides valuable insights for managers to effectively mitigate digital supply chain 5.0 risks and strategically respond to disruptions. By prioritizing risks, organizations can allocate resources efficiently and address the most critical challenges first, minimizing long-term damage to resilience. Embracing this approach enables practitioners to enhance overall supply chain resilience, guiding key management decisions for the development of sustainable and adaptive strategies.

This paper marks the first comprehensive attempt to assess supply chain 5.0 digitalization risks using decision-making methods like AHP and DEMATEL. The integrated approach contributes novel insights to the field of supply chain risk management, specifically aiding management decision-making in the face of digitalization challenges.

With the growth of organizations and businesses, customer acquisition and retention processes have become more complex in the long run. That is why customer lifetime value (CLV) has become crucial to sales managers. Predicting the CLV is a strategic weapon and competitive advantage in increasing profitability and identifying customers with more splendid profitability and is one of the essential key performance indicators (KPI) used in customer segmentation. Thus, this paper proposes a stacked ensemble learning method, a combination of multiple machine learning methods, for CLV prediction.

In order to utilize customers’ behavioral features for predicting the value of each customer’s CLV, the data of a textile sales company was used as a case study. The proposed stacked ensemble learning method is compared with several popular predictive methods named deep neural networks, bagging support vector regression, light gradient boosting machine, random forest and extreme gradient boosting.

Empirical results indicate that the regression performance of the stacked ensemble learning method outperformed other methods in terms of normalized rooted mean squared error, normalized mean absolute error and coefficient of determination, at 0.248, 0.364 and 0.848, respectively. In addition, the prediction capability of the proposed method improved significantly after optimizing its hyperparameters.

This paper proposes a stacked ensemble learning method as a new method for accurate CLV prediction. The results and comparisons support the robustness and efficiency of the proposed method for CLV prediction.

The purpose of this study is to identify and prioritize capabilities and practices to ensure a resilient supply chain during an unexpected disruption. In addition, this study ranks maturity factors that influence the main capabilities identified.

This paper is conducted in three stages. First, capabilities and practices are extracted through a literature review. Second, capabilities and practices are ranked using the analytical hierarchical process method. Third, a gray technique for order preference by similarity to ideal solution method is used to rank maturity factors influencing capabilities.

The findings indicate that responsiveness, readiness, flexibility and adaptability are the most important capabilities for supply chain resilience. Also, commitment and communication are the highest maturity factors influencing resilience capabilities.

The findings provide a hierarchical vision of capabilities and practices for industries to increase resilience. Limitations of the paper are related to capabilities, practices and number of experts consulted.

This paper highlights the importance of high-maturity practices in resilience capability adoption. The findings of this study will encourage decisions-makers to increase maturity practices to build resilience against disruption.

The paper reveals that developing powerful capabilities, good practices and a high level of maturity improve supply chain resilience.

The success of projects is a major challenge for information technology (IT) project-based businesses (PBOs). Employees' negative emotions (NE) disrupt the employees' usual work activities by creating obstacles to routine operations. Organizations should take steps to lessen these NE. The current study assessed the mediating role of NE and the moderating influence of employee mindfulness in the association between despotic leadership (DL) and IT project success (PS).

Time-lagged data were collected from 341 employees working in various IT-based project organizations in Pakistan using purposive sampling.

Results were consistent with the authors' hypothesized framework, as DL increases employees' NE, which in turn negatively affects IT PS. In addition, mindfulness plays a buffering role in mitigating the damaging impact of DL on NE.

Previous researchers focused on the positive aspects of leadership and its influence on PS and paid limited attention to the dark leadership style. The authors' study's findings help understand how project-based organizations can reduce employees' NE.

This article presents two Brazilian Portuguese corpora collected from different media concerning public security issues in a specific location. The primary motivation is supporting analyses, so security authorities can make appropriate decisions about their actions.

The corpora were obtained through web scraping from a newspaper's website and tweets from a Brazilian metropolitan region. Natural language processing was applied considering: text cleaning, lemmatization, summarization, part-of-speech and dependencies parsing, named entities recognition, and topic modeling.

Several results were obtained based on the methodology used, highlighting some: an example of a summarization using an automated process; dependency parsing; the most common topics in each corpus; the forty named entities and the most common slogans were extracted, highlighting those linked to public security.

Some critical tasks were identified for the research perspective, related to the applied methodology: the treatment of noise from obtaining news on their source websites, passing through textual elements quite present in social network posts such as abbreviations, emojis/emoticons, and even writing errors; the treatment of subjectivity, to eliminate noise from irony and sarcasm; the search for authentic news of issues within the target domain. All these tasks aim to improve the process to enable interested authorities to perform accurate analyses.

The corpora dedicated to the public security domain enable several analyses, such as mining public opinion on security actions in a given location; understanding criminals' behaviors reported in the news or even on social networks and drawing their attitudes timeline; detecting movements that may cause damage to public property and people welfare through texts from social networks; extracting the history and repercussions of police actions, crossing news with records on social networks; among many other possibilities.

The work on behalf of the corpora reported in this text represents one of the first initiatives to create textual bases in Portuguese, dedicated to Brazil's specific public security domain.