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Estimation of solar cell parameters, mathematical modeling and the actual performance analysis of photovoltaic (PV) cells at various ecological conditions are very important in the design and analysis of maximum power point trackers and power converters. This study aims to propose the analysis and modeling of a simplified three-diode model based on the manufacturer’s performance data.

A novel technique is presented to evaluate the PV cell constraints and simplify the existing equation using analytical and iterative methods. To examine the current equation, this study focuses on three crucial operational points: open circuit, short circuit and maximum operating points. The number of parameters needed to estimate these built-in models is decreased from nine to five by an effective iteration method, considerably reducing computational requirements.

The proposed model, in contrast to the previous complex nine-parameter three-diode model, simplifies the modeling and analysis process by requiring only five parameters. To ensure the reliability and accuracy of this proposed model, its results were carefully compared with datasheet values under standard test conditions (STC). This model was implemented using MATLAB/Simulink and validated using a polycrystalline solar cell under STC conditions.

The proposed three-diode model clearly outperforms the earlier existing two-diode model in terms of accuracy and performance, especially in lower irradiance settings, according to the results and comparison analysis.

This study aims to examine the role of different forms of corporate social advocacy (CSA) in shaping individuals’ attitudinal and behavioral intentions towards companies taking their public stand on controversial socio-political issues. With an online experiment as the research method, this study tests whether depicting nonpolitical or political behaviors in CSA messages increases individuals’ positive behavioral intentions.

This study uses a single factor between subject online experiment. A total of 135 US young adults were recruited through a Qualtrics online panel. Three social media mockups were created to manipulate three levels of actions in CSA messages (no action, nonpolitical action and political action). Participants viewed one of those social media posts depicting presented actions to counter anti-LGBTQ + legislation in the USA and answered questions about values-driven motives behind CSA, brand preference and positive word-of-mouth (WOM) intention.

Participants displayed higher levels of brand preference when they viewed CSA messages depicting the company’s political action intended to repel anti-LGBTQ + legislation. Participants showed more positive WOM intentions towards the company when they perceived its political actions as more values-driven.

The findings of this study offer practical insights to companies when designing CSA messages and strategies. The results of this study indicate that the presence of political actions in CSA communication increases individuals’ positive behaviors towards companies. The results also suggest that depicting altruistic motives behind CSA leads individuals to talk about companies more in positive ways.

This study is one of the early studies investigating the impact of various forms of CSA on individuals’ attitudinal and behavioral intentions to companies practicing CSA. This study provides practical implications on how to effectively appeal individuals’ favorable attitudes and behaviors towards CSA. In particular, this research presents the importance of action aspects in individuals’ attitudes toward corporations’ CSA messages.

Using coconut shell aggregates (CSA) in concrete benefits agricultural waste management and reduces the demand for mineral resources. Several studies have found that concrete containing CSA can achieve strengths that are comparable to regular concrete. The purpose of the present work is to evaluate the concrete’s durability-related properties to supplement these earlier findings.

Cylindrical specimens were prepared with a constant water–cement ratio of 0.50 and CSA content ranging from 0% to 50% (at 10% increment) by volume of the total coarse aggregates. The specimens were cured for 28 days and then tested for density, surface hardness, electrical resistivity and water sorptivity. The surface hardness was measured to describe the concrete resistance to surface wearing, while the resistivity and sorptivity were evaluated to describe the material’s resistance to fluid penetration.

The results showed that the surface hardness of concrete remained on average at 325 Leeb and did not change significantly with CSA addition. The distribution of surface hardness was also similar across all CSA groups, with the interquartile range averaging 59 Leeb. These results suggest that the cement paste and gravel stiffness had a more pronounced influence on the surface hardness than CSA. On the other hand, concrete became lighter by about 9%, had lower resistivity by 80% and had significantly higher initial sorptivity by up to 110%, when 50% of its natural gravel was replaced with CSA. Future work may be done to improve the durability of CSA when used as coarse aggregate.

The present study is the first to show the lack of correlation between CSA content and surface hardness. It would mean that the surface hardness test may not completely capture the porous nature of CSA-added concrete. The paper concludes that without additional treatment prior to mixing, CSA may be limited only to applications where concrete is not in constant contact with water or deleterious substances.

Based on Lasswell’s communication model, this study investigates how four categories of factors (i.e. the source, content, medium and receiver) conjointly affect the relational, financial and social outcomes (i.e. what effect) of CSA communication.

With a survey (N = 366), this study found configurations of core CSA communication factors leading to three different CSA communication outcomes.

While this study found multiways to yield three different CSA outcomes, combinational logic indicated the combined effects from source, content, medium and receiver. With content and medium, individuals’ connectedness (receiver) to a CSA issue is a core factor leading to a high level of purchase intention and issue advocacy. This study also found that message strategies (i.e. informativeness, factual tone, no promotional tone) are core factors leading to a high level of trust and issue advocacy.

With the theoretical guidance, this research contributes to strategic communication practice for various entities involved in advocacy communication by enabling an improved understanding of advocacy communication factors and triggering different communication outcomes.

As CSA communication involves multiple strategies, conventional research agenda focusing on correlational and path analysis approaches provide limited understanding of communication practice. To fill this void, this study adopts a configurational approach to understand current CSA communication practices holistically.

Given the positive organizational principles associated with total quality management (TQM) – customer focus, continuous improvement, and process management – one would assume TQM's application is universally beneficial across businesses. Generally, research supports that notion. However, given resource limitations and shallow management teams in small businesses, there are multiple challenges in implementing TQM in small and medium-sized enterprises (SMEs). Therefore, small business leaders should benefit from knowledge linking other management practices to TQM’s positive effect on small firm performance, which enhances these leaders' return on TQM investment.

The authors apply partial least squares structural equation modeling (PLS-SEM) to explore TQM’s effect on small business performance and how other management practices enhance that relationship. Specifically, the authors explore how a comprehensive strategic approach (CSA) – a higher-order construct consisting of strategic planning, goal setting, and financial ratio analysis – moderates the relationship between TQM and small business performance. Given the complexity of the authors' model, the application of higher-order constructs, and the exploratory nature of this work, PLS-SEM is well suited for this study.

Consistent with prior research, the authors found that TQM (also a higher-order construct, consisting of seven lower-order constructs) positively impacts small firm performance. In addition, the authors found that CSA positively moderates the relationship between TQM and financial performance.

TQM’s effect on small business performance is enhanced when leaders implement a CSA. In other words, when small business leaders strategically plan, set goals, and analyze financial ratios, TQM's positive effect on firm performance is enhanced. This finding provides business leaders insights for how to maximize the TQM investment return.

This study assesses the extent to which integrated extension services contribute to the adoption of climate-smart agriculture (CSA) innovations within the cotton value chain in Burkina Faso.

To address the research question, a probit multivariate econometric model with sample selection is utilized. The model is applied to a random sample of farmers (n = 510), and the endogeneity is addressed through a control function approach.

The study highlights the central role of value chains, particularly in the cotton sector, in overcoming resource scarcity through integrated extension services. Findings show that smallholder farmers who benefit from sound extension services are more willing to adopt and diversify CSA technologies. These include improved seeds, conservation techniques, adapted planting dates and mechanization. This study confirms the synergistic nature of these technologies and emphasizes that effective climate risk mitigation depends on the combined adoption of CSA technologies.

The use of cross-sectional data limits the analysis of long-term farmer behavior, and due to data limitations, the focus was primarily on the contributions of cotton companies and farmers to climate risk mitigation. Future research using panel data across the value chain could provide a more robust insights for policy decision-making.

The study contributes to the existing body of knowledge by emphasizing the crucial role of integrated extension services within the cotton value chain in developing countries. This highlights the critical benefits for farmers and emphasizes the need to diversify modern technologies to effectively combat climate change and its variability in agriculture.

This study evaluated the impact of a faculty training program on student assessment using the Kirkpatrick model.

A self-reported survey assessed 111 Saudi and non-Saudi participants' satisfaction. Subjective and objective measures (self-reported measures, assessment literacy inventory and performance-based assessment tasks) gauged participants' learning level. Pre- and post-training data were collected from 2020 to 2022.

A highly significant effect on satisfaction (>80%) and learning levels was observed, as manifested by workplace practices of student assessment (>70%, the cut-off score). Pre- and post-training comparisons of participants' satisfaction and assessment literacy scores showed significant improvements following training. Multiple regression analyses showed no significant effects for gender and educational attainment but a substantial impact of academic cluster on participants' student assessment skills.

Long-term effects of training faculty on assessment practices and student achievement will be studied at the institutional level in future research.

The current study contributes to human capital investment via faculty training on student assessment, helping them comply with assessment best practices. This assures the quality, fairness and consistency of assessment processes across disciplines in higher education institutions, enhances assessment validity and trust in educational services and may support institutional accreditation.

This study provides opportunities for sharing best practices and helps establish a community of practice. It enhances learning outcomes achievement and empowers higher education graduates with attributes necessary to succeed in the labor market. The human capital investment may have a long-term impact on overall higher education quality.

This study contributes to the scarce literature investigating the impact of training faculty from different clusters on student assessment using subjective and objective measures. It provides developing and evaluating a long-term student assessment program following the Kirkpatrick model.

The purpose of this study was to conduct a preliminary analysis of the role of higher education institutions (HEIs) in state climate science assessment (CSA) and state climate adaptation plan (CAP) development in the USA.

This study uses a content review of US state government and land grant (LG) university websites, including 36 CSAs and CAPs. These data informed the development of a tiered conceptual model of HEI engagement in state climate action planning. The conceptual model is evaluated through the lens of coproduction within knowledge networks.

HEI contributions to state-level climate action planning in the USA are highly variable, ranging from minimal engagement to defined roles in the development and implementation of robust state CAPs. Novel approaches to optimize effective exchange between scientists and decision-makers that also increase the engagement of academia are needed.

This study advocates for and provides a replicable example of HEI engagement in the development of mechanisms that increase the connectivity of in-state climate networks. Such mechanisms optimize information sharing and engagement, consequently building sustained capacity for in-state collaboration at the science–policy interface.

HEIs, particularly LG universities, are a stable source of state-specific climate science and expert assistance that persist beyond national and state political cycles. To the best of the authors’ knowledge, this research is the first to examine their unique contributions to climate science policy development and implementation. It investigates specifically the relationships and interactions between HEIs and state governments in the USA and offers a detailed case study from the state of Maine.

The purpose of this study is to analyze the horizontal expansion of Burayu Town between 1990 and 2020. The study typically acts as a baseline for integrated spatial planning in small- and medium-sized towns, which will help to plan sustainable utilization of land.

Landsat5-TM, Landsat7 ETM+, Landsat5 TM and Landsat8 OLI were used in the study, along with other auxiliary data. The LULC map classifications were generated using the Random Forest Package from the Comprehensive R Archive Network. Post-classification, spatial metrics, and per capita land consumption rate were used to understand the manner and rate of expansion of Burayu Town. Focus group discussions and key informant interviews were also used to validate land use classes through triangulation.

The study found that the built-up area was the most dynamic LULC category (85.1%) as it increased by over 4,000 ha between 1990 and 2020. Furthermore, population increase did not result in density increase as per capita land consumption increased from 0.024 to 0.040 during the same period.

As a result of financial limitations, there were no high-resolution satellite images available, making it challenging to pinpoint the truth as it is on the ground. Including senior citizens in the study region allowed this study to overcome these restrictions and detect every type of land use and cover.

Data on urban growth are useful for planning land uses, estimating growth rates and advising the government on how best to use land. This can be achieved by monitoring and reviewing development plans using satellite imaging data and GIS tools.

The use of Random Forest for image classification and the employment of local knowledge to validate the accuracy of land cover classification is a novel approach to properly customize remote sensing applications.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.