Case Study Research Articles

Proof complexity of positive branching programs

We investigate the proof complexity of systems based on positive branching programs, i.e. non-deterministic branching programs (NBPs) where, for any 0-transition between two nodes, there is also a 1-transition. Positive NBPs compute monotone Boolean functions, just like negation-free circuits or formulas, but constitute a positive version of (non-uniform) NL, rather than P or NC1, respectively. The proof complexity of NBPs was investigated in previous work by Buss, Das and Knop, using extension variables to represent the dag-structure, over a language of (non-deterministic) decision trees, yielding the system eLNDT. Our system eLNDT+ is obtained by restricting their systems to a positive syntax, similarly to how the 'monotone sequent calculus' MLK is obtained from the usual sequent calculus LK by restricting to negation-free formulas. Our main result is that eLNDT+ polynomially simulates eLNDT over positive sequents. Our proof method is inspired by a similar result for MLK by Atserias, Galesi and Pudl\'ak, that was recently improved to a bona fide polynomial simulation via works of Je\v{r}\'abek and Buss, Kabanets, Kolokolova and Kouck\'y. Along the way we formalise several properties of counting functions within eLNDT+ by polynomial-size proofs and, as a case study, give explicit polynomial-size poofs of the propositional pigeonhole principle.

Understanding late medieval population change in English towns: an alternative approach

Abstract Understanding population change in late medieval English towns is crucial for interpreting urban development and economic shifts. Traditional estimates, based on taxation records from 1377 to the Tudor period, provide arbitrary population figures at two fixed points and fail to capture short—term fluctuations. This study proposes an alternative methodology that integrates multiple strands of evidence, including court records, tax lists, and archaeological data, offering a more nuanced understanding of demographic change. Using Nottingham as a case study, it challenges prevailing models of urban population decline. The evidence suggests that after sustained population growth into at least the 1330s, approximately 60 per cent of the townspeople died during the Black Death of 1349. However, significant migration by the early 1350s, and again in the late fourteenth and early fifteenth centuries, led to periods of population recovery. Archaeological evidence, together with documentary sources, indicates urban expansion from the second half of the fourteenth century, with substantial growth by the early sixteenth century—contradicting traditional narratives of abandonment and decline. The findings demonstrate that demographic change was far more complex than traditional methodologies suggest and that this alternative approach provides deeper insight into population trends. This approach is applicable to towns with comparable source material.

Prediction of Water Quality Index of Island Counties Under River Length System—A Case Study of Yuhuan City

In order to cope with the extremely difficult challenges of water pollution control, China has widely implemented the river chief system. The water quality monitoring of surface water environment, as a solid defense line to safeguard human health and ecosystem balance, is of great importance in the river chief system. As a well-known island county in China, Yuhuan City holds even more precious water resources. Leveraging machine learning technology to develop water quality prediction models is of great significance for enhancing the monitoring and evaluation of surface water environment quality. This case study aims to evaluate the effectiveness of six machine learning models in predicting water quality index (CWQI) and uses SHAP (Shapley Additive exPlans) as an interpretability analysis method to deeply analyze the contribution of each variable to the model’s prediction results. The research results show that all models exhibited good performance in predicting CWQI, and as the number of significantly correlated variables in the input variables increased, the prediction accuracy of the models also showed a gradual improvement trend. Under the optimal input variable combination, the Extreme Gradient Boosting model demonstrated the best prediction performance, with a root mean square error (RMSE) of 0.7081, a mean absolute error (MAE) of 0.4702, and an adjusted coefficient of determination (Adj.R2) of 0.6400. Through SHAP analysis, we found that the concentrations of TP (total phosphorus), NH3-N (ammonia nitrogen), and CODCr (chemical oxygen demand) have a significant impact on the prediction of CWQI in Yuhuan City. The implementation of the river chief system not only enhances the pertinence and effectiveness of water quality management, but also provides richer and more accurate data support for machine learning models, further improving the accuracy and reliability of water quality prediction models.

Innovative Callus Release Technique for Closed Reduction in Old Fractures: Case Studies and Methodology

Innovative Callus Release Technique for Closed Reduction in Old Fractures: Case Studies and Methodology

Effective Educational Management Strategies: Enhancing Institutional Performance and Student Success

Educational management plays a critical role in shaping institutional performance and student success. This paper explores effective educational management strategies, including leadership styles, teacher professional development, curriculum innovation, and data-driven decision-making. By analyzing current research and case studies, we identify best practices that contribute to an efficient and student-centric learning environment. The findings suggest that collaborative leadership, continuous professional development, and technology integration significantly enhance institutional outcomes. The paper also highlights challenges in implementing these strategies and suggests ways to overcome them.

Steps for Meaningful Community Partnership in Research: An Intersectional Feminist Research Program Case Study

The historical focus of the HIV movement on men who have sex with men has led to the systematic exclusion of women from research, programming, and decision-making. In the early 2000s, women researchers, advocates, and community leaders drove transformative shifts in Canada’s HIV sector through community-based participatory research (CBPR) approaches. Their use of CBPR not only revolutionized women’s engagement but also propelled significant progress towards gender-equitable research, including with trans communities and gender diverse and expansive persons. In this article, we critically examine the history of CBPR, specifically in the HIV field, from an intersectional feminist lens. We then present a case study of our research program: the Women and HIV Research Program, as a framework for meaningful community partnership. Next, as academics and community leaders, we describe the conceptualization of meaningful community-engaged research that we developed over 20 years. Our research program has been built upon a strong foundation of genuine academic-community partnerships and has embraced co-creation as a core principle. We reflect on the changes we have seen and responded to in the field over time. Our goal is for this article to serve as a reflective blueprint for those interested in meaningful community engagement and partnership in research.

A Novel Multi-Criteria Decision-Making Framework of Vehicle Structural Factor Evaluation for Public Transportation Safety

Proper management of vehicle structural factors related to public transportation safety is vital to formulate maintenance strategies and to enhance transportation safety. Therefore, this work aims to comprehensively identify potential structural factors, assess their impacts as regards causing public transportation vehicle malfunctions, and understand their cause–effect interrelationships. Maintenance management can be improved based on the analysis outcomes. Multi-Criteria Decision-Making (MCDM) techniques are widely applied to decision-making problems. However, due to the advanced and complex structures of modern vehicles, conventional single-used MCDM techniques encounter limitations in their ability to thoroughly account for all potential failure factors and to systematically manage the causal interrelationships, which makes the analysis results less practically applicable. To overcome these challenges, this article proposes an innovative MCDM framework. Specifically, Failure Tree Analysis (FTA) and the Interval-Valued Pythagorean Fuzzy Analytic Hierarchy Process (IVPF-AHP) are integrated to construct the logical relationships between the failure structural factors from real-world maintenance records. The factors are ranked and selected based on their severity influence and occurrence likelihood influence. Subsequently, the Interval-Valued Pythagorean Fuzzy Decision-Making Trial and Evaluation Laboratory (IVPF-DEMATEL) takes causal diagrams to identify interdependencies between the factors based on the mitigated ambiguity of human assessments. A case study in the public transportation bus domain is conducted to demonstrate the effectiveness of the proposed MCDM framework. The results offer insightful maintenance suggestions for public transportation operators and engineers to save human labor and material resources.

Lessons Learned Evaluating Ablative Fractional CO2 Laser for Burn-Related Donor Site Scars.

Hypertrophic scar (HTS) remains a comorbidity of burn injury, often requiring split thickness skin grafting (STSG) and resulting in symptomatic HTS at grafted sites and STSG donor sites (DS). Literature supports the use of ablative fractional CO2 laser (FLSR) to treat HTS, however many trials lack of control sites and tissue-level examinations. Given the widespread adoption of FLSR for HTS, delegation of non-treated scar sites for the sake of randomized controlled trial (RCT) is troubling for many clinicians. We trialed using STSG DS scars for randomization rather than withholding FLSR from HTS at grafted sites. Patients (n=20) were treated for DS scar with FLSR. DS scars were randomized and treated with either 6 FLSR treatments, follow-ups, and standard of care (SOC) or SOC only. Prior to treatment, DS skin and normal skin (NS) were evaluated for trans-epidermal water loss (TEWL), melanin index (MI), elasticity, and erythema. Serial biopsies were analyzed for epidermal thickness, rete ridge ratio (RRR), and papillary dermal cellularity. All sites, including a separate burn scar (BS) site, were evaluated using the patient and observer scar assessment scale (POSAS) -observer (-O), -patient (-P), Vancouver Scar Scale (VSS), and an institutional Scar Comparison Scale (SCS). Prior to treatment, the DS control (DS C), DS treated (DS T), and BS sites were hyperpigmented compared to normal skin. BS was less elastic than all other sites and had increased TEWL compared to normal skin. DS skin had increased cellularity, decreased rete ridge ratios, and increased epidermal thickness compared to NS. Clinician observers and patients perceived the BS site as more severe versus DS skin through the POSAS-O, POSAS-P, and VSS. Over time, DS C and DS T sites were not different in TEWL, elasticity, erythema, MI, cellularity, RRR, epidermal thickness, POSAS-O scores, POSAS-P scores, VSS scores, or SCS scores. Over time, burn scar did not change in TEWL, elasticity, erythema, MI, POSAS-O scores, POSAS-P scores, and VSS scores. Decreased SCS scores within the DS C, DS T, and BS sites indicated patient-perceived improvement in all scars throughout the study time course. NS and DS skin possess inherent physiological differences, though not to the degree of burn scars vs. NS. FLSR may not alter the rate of maturation and remodeling of DS skin compared to current SOC. While improvement in scar assessment was observed in laser-treated BS HTS, no specific control for these sites was analyzed. Due to differences in pathophysiology of HTS formation at grafted and donor sites, the STSG DS may not be an adequate substitute for BS HTS when designing RCTs to evaluate the effect of FLSR. Prior studies evaluating the use FLSR in burn-related HTS consist of low-powered clinical trials or case studies without control sites or tissue level examinations, prompting the design of a RCT in DS scars. However, this scar type may not be suitable for this study design. Future work should extend to extra-cellular matrix morphology and transcriptomics of donor site and burn scar healing to better understand the effects of laser treatment.

Assessment of ecological risk under different SSP-RCP scenarios of the Xinjiang province in China

The ecological research of regional land use and land cover change (LULCC) under the Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathway (RCP) scenarios proposed by the IPCC has become a prominent topic. This study investigates the spatial distribution of ecological risks associated with land use and land cover changes in the arid and semi-arid regions of Xinjiang under future SSP-RCP scenarios. In this paper, LUCC data, climate data, and soil and topographic data under different scenarios in 2100 were adopted to construct the land use/land cover quality index (LQI), the climate quality index (CQI), and the soil quality index (SQI) respectively. Using Xinjiang as a case study, an integrated ecological risk model was constructed through the LQI, CQI and SQI. By 2100, LQI risk areas in Xinjiang will dominate, accounting for approximately 70% of the total area. Central Xinjiang, home to the largest desert in China—the Taklimakan Desert—predominantly consists of desert and Gobi, where LQI is generally better under the SSP-RCP126 scenario compared to other scenarios. In 2100, high CQI regions are primarily concentrated in the mountainous, Gobi, and desert areas of Xinjiang. The spatial distribution of SQI in Xinjiang remains consistent across different scenarios in 2100. Under the SSP-RCP126 and SSP-RCP245 scenarios, global warming is effectively mitigated, leading to a relatively favorable overall ecological risk scenario in Xinjiang. However, under the SSP-RCP370 and SSP-RCP585 scenarios, moderate, high, and extremely high ecological risk areas expand, covering approximately 50% of the total area.

Breaking the bubble: A case study on the echo chamber effect in Instagram

The echo chamber effect on social media platforms, particularly Instagram, significantly influences users’ perception by creating environments where similar views are repeatedly reinforced. This case study explores the dynamics of the echo chamber effect on Instagram, focussing on the role of algorithmic filtering, user behaviour, and content personalisation. By analysing the platform’s mechanisms – such as personalised feeds, the Explore page, and targeted content – this study reveals how Instagram’s algorithm amplifies selective exposure and confirmation bias, leading to increased polarisation and reduced exposure to diverse viewpoints. The study examines psychological and social factors, including selective exposure theory, social identity, and emotional resonance, which intensify the echo chamber effect on a highly visual platform like Instagram. Findings suggest that this phenomenon can fragment social networks, create polarised communities, and contribute to the spread of misinformation. Strategies to mitigate these effects, including algorithmic transparency, diverse content exposure, and user-driven interactions, are discussed as potential methods for breaking echo chambers and promoting a more balanced informational ecosystem.

Enhancing Nutrition and Cost Efficiency in Kenyan School Meals Using Neglected and Underutilized Species and Linear Programming: A Case Study from an Informal Settlement

Neglected and Underutilized Species (NUS)—locally available, climate-resilient species—possess significant nutritional, social, and environmental benefits, yet their use, research focus, and market presence have diminished over time. Incorporating NUS into school meal programs can potentially boost childhood nutrition, promote healthy eating, encourage sustainable food production, preserve food culture and heritage, and support biodiversity conservation. School meals offered in Kenya are often monotonous and nutritionally inadequate. We conducted a case study on a school in an informal urban settlement in Nairobi, targeting students between ages 6–12, to demonstrate how incorporating locally grown, nutrient-dense foods into school meals can result in better nutrition for school-age children, while making significant savings for schools. Using the World Food Programme’s School Meal Planner (SMP) PLUS software, the school meals offered were analyzed for nutrient adequacy and optimized including five NUS: African nightshade (Solanum spp.), spider plant (Cleome gynandra), Bambara groundnut (Vigna subterranea), bonavist or hyacinth bean (Lablab purpureus), and slender leaf (Crotalaria spp.). The optimization process was based on the commodity price fluctuations and nutrient composition of the local agrobiodiversity used. The study results show how NUS are a viable and healthy alternative to meet the recommended daily nutrient needs for school-aged children at affordable prices. The tool results showcased the effectiveness of linear programming in enabling national decision making for efficient school feeding program planning, by designing comprehensive, affordable food baskets using local agrobiodiversity. Future research should explore implementing optimized school menus while examining broader aspects, such as school lunch environmental impacts and direct procurement approach opportunities that source local ingredients from smallholder farmers.

Investigation of the relationship between the specific charge and Bond Work Index: A case study

Investigation of the relationship between the specific charge and Bond Work Index: A case study

Using Serious Games and Digital Games to Improve Students’ Computational Thinking and Programming Skills in K-12 Education: A Systematic Literature Review

Computational thinking and problem-solving skills have become vital for students to develop. Digital games and serious games are increasingly being used in educational settings and present great potential to aid students’ learning. This study aims to explore the role and impact of serious games and digital games on students’ computational thinking and programming skills in primary, secondary, and K-12 education through a systematic review of the existing literature. Four research questions were set to be examined. Following the PRISMA framework, 78 studies deriving from IEEE, Scopus, and Web of Science over the period of 2011–2024 are examined. The studies are categorized into Theoretical and Review studies, Proposal and Showcase studies, and Experimental and Case studies. Based on the results, serious games and digital games arose as meaningful educational tools that are positively viewed by education stakeholders and that can effectively support and improve K-12 education students’ computational thinking and programming skills. Among the benefits identified, it was revealed that serious games offer enjoyable and interactive learning experiences that can improve students’ learning performance, engagement, and motivation, enhance students’ confidence and focus, and promote self-regulated learning and personalized learning. Additionally, serious games emerged as an educational means that can effectively support social learning and provide real-time feedback. The challenges identified were related to the selection of games and the game-related design elements, decisions, and approaches. Hence, the study highlights the significance of the design of serious games and the need to cultivate students’ computational thinking, problem-solving, and social skills from a young age. Finally, the study reveals key design principles and aspects to consider when developing serious games and digital games and highlights the need to involve education stakeholders throughout the design and development process.

THE ROLE OF LIBRARIES IN DIGITIZING INDIAN KNOWLEDGE SYSTEMS FOR TECHNOLOGY-ENHANCED TEACHER EDUCATION

The rapid advancement of technology in education has opened new avenues for integrating indigenous knowledge systems into modern pedagogical frameworks. In India, the Indian Knowledge System (IKS)—comprising ancient texts, oral traditions, and philosophical treatises—offers a vast repository of wisdom that can enrich teacher education. Libraries, as traditional custodians of knowledge, are pivotal in digitizing these resources to align them with technology-enhanced teaching practices. This paper investigates the multifaceted role of libraries in preserving, curating, and disseminating IKS for teacher education, emphasizing their potential to bridge cultural heritage and digital innovation. Through a qualitative analysis of existing literature and case studies like the National Digital Library of India (NDLI), it identifies key challenges—such as funding, accessibility, and cultural sensitivity—and proposes strategies like collaborative partnerships and open-access platforms. The study highlights how digitized IKS can empower educators to create culturally resonant, technology-driven curricula, aligning with India’s educational goals. KEYWORDS: Indian Knowledge System, libraries, digitization, teacher education, technology,NDLI.

Changes in the symbiotic dinoflagellate and GFP-like protein in heat stress tolerant Porites harrisoni versus heat stress sensitive Acropora downingi: a case study in the Persian Gulf

Changes in the symbiotic dinoflagellate and GFP-like protein in heat stress tolerant Porites harrisoni versus heat stress sensitive Acropora downingi: a case study in the Persian Gulf

Investigating privacy risks in open government data: an exploratory case study

Introduction. As governments increasingly release large datasets to the public, concerns have arisen regarding the potential risks associated with the inadvertent disclosure of personal information. However, there are few empirical case studies of this phenomena. Method. Taking a red teaming approach, we collected public, nonprofit reporting documents from the IRS, as well as a list of professional athletes. Using standard data processing techniques, we attempt to identify and evaluate the personal information that can be attached to these notable individuals in order to propose a framework describing how features of information, people and processes influence the potential release of personal information. Findings. We find that name commonness plays a large role in determining the feasibility of matching records. We also find that personal information, including addresses and business relationships, are accessible in the dataset. Conclusion. Our exploratory case study suggests several features of information, people and processes that influence the release of private information held in open government data. While limited, it suggests the value of further work in the area.

Exploring project-based group learning

Case-based actions and engagements are the recommendations for Project-Based Group Learning (PBGL) that explore the experiences and consequences in classroom settings and beyond. Thus, the study addresses the effectiveness of PBGL by considering the challenges and achievements experienced at a private school in Kathmandu Valley. It is a case study of the first author's son in which the first author is a mentee of the second author, and the first author serves as his son's mentor. Thus, the study intends to provide a unique, subjective view of the dynamics of PBGL through an ethically grounded analysis. Finally, this case study adds to the expanding body of information about creative educational approaches, offering valuable insights for educators, institutions, and researchers looking to improve PBGL experiences.

A New Remote Sensing Index for the Detection of Multi-Type Forest Anomalies Based on Sentinel-2 Imagery

Forest anomalies (e.g., pests, deforestation, and fires) are increasingly frequent phenomena on Earth’s surface. Rapid detection of these anomalies is crucial for sustainable forest management and development. On-orbit remote sensing detection of multi-type forest anomalies using single-temporal images is one of the most promising methods for achieving it. Nevertheless, existing forest anomaly detection methods rely on time series image analysis or are designed to detect a single type of forest anomaly. In this study, a Forest Anomaly Comprehensive Index (FACI) is proposed to detect multi-type forest anomalies using single-temporal Sentinel-2 images. First, the spectral characteristics of different forest anomaly events were analyzed to obtain potential band combinations. Then, the formulation of FACI was determined using imagery simulated by the LargE-Scale remote sensing data and image Simulation framework over heterogeneous 3D scenes (LESS) model. The thresholds for FACI for different anomalies were determined using the interquartile method and 90 in situ survey samples. The accuracy of FACI was quantitatively assessed using an additional 90 in situ survey samples. Evaluation results indicated that the overall accuracy of FACI in detecting the three forest anomalies was 88.3%, with a Kappa coefficient of 0.84. The overall accuracy of existing indices (NDVI, NDWI, SAVI, BSI, and TAI) is below 80%, with Kappa coefficients less than 0.7. In the end, a case study in Ji’an, Jiangxi Province, confirmed the ability of FACI to detect different stages of pest infection, as well as deforestation and forest fires, using single-temporal satellite images. The FACI provides a promising method for the on-orbit satellite detection of multi-type forest anomalies in the future.

Legal Protection for Consumers in the Transportation Sector: An Analysis of Consumer Rights and the Responsibilities of Public Transport Service Providers

Consumer protection in the transportation sector is a crucial aspect of public service governance, ensuring that consumer rights are safeguarded while maintaining the accountability of service providers. This study aims to analyze the legal protection mechanisms for consumers in the transportation sector, focusing on the rights of consumers and the responsibilities of public transport service providers. Using a qualitative research methodology, this study employs a literature review approach (library research) to examine relevant legal frameworks, regulations, and case studies at both national and international levels. The findings indicate that while many legal frameworks exist to protect consumer rights in the transportation sector, enforcement and implementation remain inconsistent. Consumers are entitled to safety, security, accessibility, and fair treatment, yet challenges such as inadequate regulations, lack of transparency, and insufficient enforcement mechanisms often hinder their protection. Public transport service providers, on the other hand, have a responsibility to ensure service reliability, safety standards, and adherence to consumer protection laws. This study highlights the need for stronger regulatory oversight, improved legal enforcement, and increased consumer awareness to enhance consumer protection in the transportation sector. By analyzing legal principles and international best practices, this study contributes to the discourse on consumer rights and public transport governance. Strengthening legal frameworks and promoting responsible service delivery are essential to ensuring a fair and efficient transportation system.

Review of Status of Post-Earthquake Reconstruction in Nepal (2015-2024): Challenges, Progress, and Future Directions

In 2015, a powerful earthquake struck Nepal’s Gorkha District, causing extensive loss of life and property, and deeply affecting the nation’s infrastructure, housing, and cultural heritage. This disaster severely damaged Nepal’s rich cultural sites, with numerous temples and monuments either fully or partially destroyed. The loss of these heritage landmarks represented not only cultural devastation but also a profound impact on national identity and historical continuity. This article employs a qualitative approach, including critical literature review, field visits, interviews, document analysis, and case studies, to thoroughly examine the status of post-earthquake reconstruction efforts. The study focuses on key areas of reconstruction, such as housing, public infrastructure, and heritage restoration, offering an in-depth look at both progress and ongoing challenges. Although considerable advances have been made in rebuilding efforts, the earthquake highlighted Nepal’s need to strengthen building practices and disaster preparedness to better withstand future seismic events. Major obstacles in the reconstruction process include funding limitations, bureaucratic inefficiencies, corruption, logistical difficulties, governance issues, lack of coordination, limited accessibility, shortages of skilled labor, knowledge gaps, and the socio-cultural factors impacting rebuilding. This earthquake has underscored the urgency of revising building codes and adopting improved structural reinforcement methods to reduce future risks. Effective governance, inter-agency collaboration, and strategic incorporation of social and cultural dimensions are essential for continuing and sustaining the current reconstruction efforts in Nepal. Finally, the paper offers recommendations for strengthening Nepal’s post-earthquake recovery and resilience, focusing on institutional capacity building, coordination, and community based rebuilding strategies.