Search Results (70)

Global refugee flows’ increasing scale and complexity pose significant challenges to national education systems. Turkey, hosting one of the largest populations of refugees and individuals under temporary protection, faces unique pressures in ensuring equitable educational access for refugee students. Addressing these challenges requires a shift from linear, fragmented interventions toward holistic, systemic approaches. This study applies a Community-Based System Dynamics (CBSD) methodology to explore the systemic barriers affecting refugee students’ participation in education. Through structured Group Model Building workshops involving teachers, administrators, and Non-Governmental Organization (NGO) representatives, a causal loop diagram (CLD) was collaboratively developed to capture the feedback mechanisms and interdependencies sustaining educational inequalities. Five thematic subsystems emerged: language and academic integration, economic and family dynamics, psychosocial health and trauma, institutional access and legal barriers, and social cohesion and discrimination. The analysis reveals how structural constraints, social dynamics, and individual behaviors interact to perpetuate exclusion or facilitate integration. This study identifies critical feedback loops and leverage points and provides actionable insights for policymakers and practitioners seeking to design sustainable, systems-informed interventions. Our findings emphasize the importance of participatory modeling in addressing complex societal challenges and contribute to advancing systems thinking in refugee education. Full article

To correspond to the advancement of technology, programming has become an indispensable course in university curricula. However, students easily become confused by the rules governing program execution or by complex logical structures. Mastering program structure and logic often is a significant challenge for beginners, especially. Despite the availability of information on programming on various websites and tools, including generative artificial intelligence (AI), there is still a gap between conceptual understanding and practical application for beginners. They overlook important implementation details or struggle to grasp the flow of a program, making the mastery of program logic a persistent challenge. To address these issues, we have developed a system that dynamically generates process architecture diagrams. Users upload their code, and the system produces corresponding diagrams that decompose and execute the code line by line. Its visual representation allows users to observe the program’s execution and aids them in comprehending the sequence and operational flow of the code. By understanding the structure and logic of the program intuitively, this system supplements traditional teaching methods and AI-assisted question-and-answer tools. The experimental results demonstrated that students found the system helpful to track their learning progress (87%) and improved their understanding of program code (81%). Additionally, 84% of students reported that the system was easy to use, highlighting its user-friendliness. In terms of student interest, 83% of students agreed that the interactive elements made learning more engaging, indicating that the system positively contributed to dynamic and enjoyable learning. However, 63% of students reported an improvement in coding and were influenced by the complexity of the programming tasks assigned. Despite this, the overall satisfaction with the system developed in this study was high. Full article

The integration of Internet of Things (IoT) technologies into solar energy systems has transformed them into smart solar energy systems, enabling advanced real-time monitoring, control, and optimization. However, this connectivity also expands the attack surface, exposing critical components to cybersecurity threats that could compromise system reliability and long-term sustainability. This study presents a comprehensive cybersecurity threat modeling analysis for IoT-based smart solar energy systems using the STRIDE threat model to systematically identify, categorize, and assess potential security risks. These risks, if unmitigated, could disrupt operations and hinder large-scale adoption of solar energy. The methodology begins with a system use case outlining the architecture and key components, including sensors, PV modules, IoT nodes, gateways, cloud infrastructure, and remote-access interfaces. A Data Flow Diagram (DFD) was developed to visualize the data flow and identify the critical trust boundaries. The STRIDE model was applied to classify threats, such as spoofing, tampering, repudiation, information disclosure, denial of service, and elevation of privilege across components and their interactions. The DREAD risk assessment model was then used to prioritize threats based on the Damage Potential, Reproducibility, Exploitability, Affected Users, and Disability. The results indicate that most threats fall into the high-risk category, with scores ranging from 2.6 to 2.8, emphasizing the need for targeted mitigation. This study proposes security recommendations to address the identified threats and enhance the resilience of IoT-enabled solar energy systems. By securing these infrastructures, this research supports the transition to sustainable energy by ensuring system integrity and protection against cyber threats. The combined use of STRIDE and DREAD provides a robust framework for identifying, categorizing, and prioritizing risks, enabling effective resource allocation and targeted security measures. These findings offer critical insights into safeguarding renewable energy systems against evolving cyber threats, contributing to global energy sustainability goals in an increasingly interconnected world. Full article

Informal soft system methodologies hold a significant role in developing complex systems. They bridge system knowledge and sensemaking among heterogeneous stakeholders. This article investigates the application of conceptual models to support such communication and understanding among transdisciplinary stakeholders, ensuring the translation of customer requirements and needs into suitable engineered systems. This article presents a case study incorporating observations, interviews, and a review of conceptual models utilized by an aerospace and defense case company for the development of future Manned–Unmanned Systems. It explores how practitioners employ conceptual modeling to support the Human Systems Integration (HSI) aspects of technological, organizational, and human elements of Manned–Unmanned Teaming (MUM-T) systems. The results indicate that practitioners utilize a mix of informal and formal types of conceptual models when developing Human Systems Integration aspects of the system. Formal models, such as sequence diagrams, requirement overviews, and functional flow models, are applied when addressing technology-focused aspects. Organization-centered modeling leverages representations like stakeholder maps and swimlane diagrams, while people-centered aspects rely more on informal techniques such as storytelling and user personas. The findings suggest a potential underestimation by practitioners of the value of quantification in conceptual modeling for Manned–Unmanned Systems development. This study highlights the important role that conceptual modeling methods play, particularly focusing on the informal aspects. These methods are instrumental in enhancing effective communication and understanding among transdisciplinary stakeholders. Furthermore, they facilitate mutual understanding, which is essential for fostering collaboration and shared vision in the development of complex systems. This facilitates deeper insights and reasoning into HSI for MUM-T applications. Full article

Natural disasters often occur unexpectedly, catching people off guard, such as the Hualien earthquake on 3 April 2024. Many of the evacuation-monitoring systems currently in place lack real-time updates of shelter capacities, which raises the risk of overcrowding under wartime scenarios. This study developed a system for the targeted assignment of evacuation sites during air raids. The DBSCAN algorithm was used to group data based on pedestrian flow patterns and an LSTM model was used to enhance the prediction speed and accuracy. Weighted Voronoi diagrams delineated regions to identify optimal evacuation points, while real-time SMS notifications through base station positioning disseminated evacuation information to the public. The experiment results demonstrated the effectiveness of the proposed system in facilitating safe evacuations across a broad range of geographic regions while reducing the number of LSTM models. Dynamic updates on the shelter capacities make it possible for citizens to make informed decisions during air raid emergencies. Full article

Groundwater, a crucial natural resource on a global scale, plays a significant role in Texas, impacting various essential ecosystem services either directly or indirectly. Despite efforts of state- and community-level regulations and conservation efforts, there is an ongoing trend of declining groundwater levels in the state of Texas. In this study, we utilized the systems thinking and system dynamics modeling approach to better understand this problem and investigate possible leverage points to achieve more sustainable groundwater resource levels. After conceptualizing a causal loop diagram (CLD) of the underlying feedback structure of the issue (informed by the existing literature), a small system dynamics (SD) model was developed to connect the feedback factors identified in the CLD to the stocks (groundwater level) and flows (recharge rate and groundwater pumping) that steer the behaviors of groundwater systems across time. After completing model assessment, experimental simulations were conducted to evaluate the current state relative to simulated treatments for improved irrigation efficiency, restricted pumping rates, cooperative conservation protocols among users, and combination strategy (of all treatments above) in the long-term. Results showed that groundwater stress (and the associated repercussions on related ecosystem service) could be alleviated with a combination strategy, albeit without complete groundwater level recovery. Full article

River width is a crucial parameter that correlates and reflects the hydrological, geomorphological, and ecological characteristics of the channel. However, the width data with high spatial resolution is limited owing to the difficulties in extracting channel width under complex and variable riverine surroundings. To address this issue, we aimed to develop an automatic framework specifically for delineating river channels and measuring the bankfull widths at small spatial intervals along the channel. The DeepLabV3+ Convolutional Neural Network (CNN) model was employed to accurately delineate channel boundaries and a Voronoi Diagram approach was complemented as the river width algorithm (RWA) to calculate river bankfull widths. The CNN model was trained by images across four river types and performed well with all the evaluating metrics (mIoU, Accuracy, F1-score, and Recall) higher than 0.97, referring to the accuracy over 97% in prediction. The RWA outperformed other existing river width calculation methods by showing lower errors. The application of the framework in the Lillooet River, Canada, presented the capacity of this methodology to obtain detailed distributions of hydraulic and hydrological parameters, including flow resistance, flow energy, and sediment transport capacity, based on high-resolution channel widths. Our work highlights the significant potential of the newly developed framework in acquiring high-resolution channel width information and characterizing fluvial dynamics based on these widths along river channels, which contributes to facilitating cost-effective integrated river management. Full article

The advancement of virtual coupling technology in urban rail transit has facilitated the online coupling and decoupling of trains, enabling a range of flexible transportation configurations, including various route types and adjustable formations. This study targets the fluctuating passenger demands on urban rail lines, aiming to minimize both passenger travel and operational costs. The model integrates constraints associated with virtual coupling, train operations, rolling stock circulation, and the interaction between virtually coupled trains and passenger arrivals. New decision variables are introduced to depict the train formation state under virtual coupling scenarios. An integrated optimization model for train diagrams and rolling stock circulation under virtual coupling conditions is developed, employing a genetic-simulated annealing algorithm informed by train operation simulations. A case study on an urban rail line during the morning peak examines the optimization of train diagrams for full-length and short-turn routes. Findings confirm that virtual coupling technology effectively adapts to lines with uneven passenger flow distribution, significantly enhancing the match between supply and demand, equalizing spatial and temporal traffic variations, and harmonizing the quality of passenger services with operational efficiency. Full article

Background: According to the World Health Organization, social isolation, particularly of older adults, is a public health issue endangering the well-being of individuals, families, and communities. Social isolation affects health through biological, behavioral, and psychological pathways and is associated with physical and psychological/emotional well-being, increases morbidity and mortality rates, and lowers quality of life. Purpose: This systematic review examined the relationship between social isolation and physical health, including subjective and objective dimensions, and factors that influence this relationship in adults. Methods: This systematic review examined six electronic databases covering the field of health and human services and included results from 1 January 2017 to 10 March 2023 with key terms including adult social connection or social isolation coupled with health, physical, psychological, emotional, mental, or behavioral. The initial search yielded 925 research articles across all databases and was narrowed to 710 when the decision was made to focus on social isolation and physical health. Covidence was used throughout the retrieval and appraisal process, as provided in a PRISMA flow diagram. Twenty-four studies that scored 90 or above in the appraisal process were included in the systematic review. Results: The studies represented included seven studies conducted in the United States and seventeen studies conducted internationally. Regarding study design, twenty-three studies were quantitative, one was qualitative, and one was mixed methods. The majority of quantitative studies were correlational in design with nine being longitudinal. The majority of studies were based on large national data sets representing in total 298,653 participants aged 50 and older. The results indicate that social isolation is related to increases in inflammatory biomarkers associated with diseases, all-cause mortality, lower expectations of longevity, and frailty. In addition, social isolation was associated with cognitive decline and disruptions in sleep. Poor oral health increased social isolation. The results further indicated that decreased physical performance/function and a decline in physical activity were associated with social isolation, as well as decreased overall physical health, poor health behaviors, and self-care, and decreased health-related quality of life. Further research is warranted to examine the possible bidirectionality of these relationships and possible mediating, moderating, or confounding variables. Implications: Future research is needed to explore the biological and behavioral pathways in which social isolation negatively impacts physical health. Going forward, studies are needed that move beyond descriptive, exploratory methods and integrate data from qualitative and mixed-method designs that will inform the development and testing of a conceptual framework related to social isolation and health. By advancing the science behind social isolation, comprehensive interventions can be identified and tested with implications at the individual, family, community, and societal levels to reduce social isolation, particularly among adults, and improve health and quality of life. Full article

Purpose: Pancreatic cancer (PC) is a fatal malignancy with an aggressive course derived from the cells of pancreatic tissue. Gestational diabetes mellitus (GDM) is a state of spontaneous hyperglycemia occurring during gestation and has been suggested as a risk factor PC. Women with a history of GDM revealed a risk rate of 7.1% for the development of PC. The current systematic review aims to investigate the correlation between GDM and the degree to the prevalence of PC. Methodology: For this systematic review, the PICO model was prepared to construct and outline the exact questions of the study, a PRISMA flow diagram was prepared and quality assessment was conducted using the Newcastle Ottawa Scale (NOS) for Cohort Studies, the NIH Quality Assessment Tool-Criteria for Case Reports and the Cochrane quality assessment tool for Systematic Reviews and Meta-analysis studies. Result: A total of eight articles were retrieved from the main databases, and a table was created to summarize the information found. Even though the data found were limited, the quality assessment performed revealed that the articles were of high validity. Conclusions: It can be concluded that GDM has an association with the development of PC and can be considered as a risk factor. Full article

With a significant portion of the population adopting veganism and conflicting views among nutrition professionals regarding the necessity of vitamin B12 supplementation, this review aims to explore existing studies evaluating interventions through food supplementation. It focuses on the impact of vitamin B12 deficiency across different demographics. The present study seeks to understand how research has addressed the relationship between the rise in veganism and vitamin B12 deficiency over the past decade. A scoping review was conducted following the PRISMA flow diagram. Studies from 2010 to 2023 were identified using Boolean operators and key terms in electronic databases such as PubMed/MEDLINE, Web of Science, and EBSCO (Library, Information Science & Technology Abstracts, and Academic Search Complete). Out of 217 articles identified, 70 studies were included. The topical analysis categorized the studies into three groups: those associating vitamin B12 deficiency with diseases (n = 14), those analyzing the dietary habits of vegetarian individuals (vegan or not) without a specific focus on vitamin B12 (n = 49), and those addressing food guides and nutrition institution positions (n = 7). The authors concluded that vitamin B12 deficiency is prevalent among vegans due to limited consumption of animal products. For vegetarians, supplementation is an efficient means of treating and preventing deficiency; a daily dose of 50 to 100 micrograms is advised. There are still significant gaps in the research, nevertheless, such as the absence of randomized controlled trials evaluating various forms or dosages of vitamin B12 among vegetarians and the requirement for more information and awareness of the vitamin’s significance in vegan diets. Full article

Purpose: Postpartum psychosis (PPP) is a serious mental health illness affecting women post-parturition. Around 1 in 1000 women are affected by postpartum psychosis, and the symptoms usually appear within 2 weeks after birth. Postpartum mental disorders are classified into 3 main categories starting from the least to most severe types, including baby blues, postpartum depression, and postpartum psychosis. Materials and Methods: In this systematic review, genetic and epigenetic factors associated with postpartum psychosis are discussed. A PRISMA flow diagram was followed, and the following databases were used as main sources: PubMed, ScienceDirect, and Scopus. Additional information was retrieved from external sources and organizations. The time period for the articles extracted was 5 years. Results: Initially, a total of 2379 articled were found. After the stated criteria were applied, 58 articles were identified along with 20 articles from additional sources, which were then narrowed down to a final total of 29 articles. Conclusions: It can be concluded that there is an association between PPP and genetic and epigenetic risk factors. However, based on the data retrieved and examined, the association was found to be greater for genetic factors. Additionally, the presence of bipolar disorder and disruption of the circadian cycle played a crucial role in the development of PPP. Full article

This case study focuses on twelve compacted clay soil samples to understand their fundamental physical and thermal properties. For each sample, the density, thermal conductivity, thermal diffusivity, specific heat, and drying shrinkage were assessed. The identification and characterisation of the materials were also carried out by positioning them into the ternary diagram based on the percentage of sand, silt, and clay. These properties are definitive for the performance characteristics of materials used in rammed earth wall construction. The aim is to provide information for better knowledge and prediction regarding the dynamic heat flow in rammed earth walls. Experimental results show a relatively wide range of values for each property, reflecting the diverse properties of the sampled clays. The thermophysical characteristics of the 12 types of earth analysed showed correlations with reports in the literature in terms of density (1490–2150 kg/m³), porosity (23.22–39.99%), specific heat capacity (701–999 J/kgK), and thermal conductivity (0.523–1.209 W/mK), which indicates them as materials suitable for use in the construction of rammed earth walls. Using test data, a dynamic assessment of heat flow through simulated rammed earth walls was performed. For a better understanding of the results obtained, they were compared with results obtained for simulations where the building element would be made of concrete, i.e., a mineral wool core composite. Thus, heat flux at the wall surface and mass flux, respectively, during the 16 years of operation showed similar evolution for all 12 types of clay material analysed, with small variations explained by differences in thermophysical characteristics specific to each type of S1–S12 earth. In the case of walls made from clay material, there is a stabilisation in the evolution of the water content phenomenon by the 5th year of simulation. This contrasts with walls made of concrete, where the characteristic water content appears to evolve continuously over the 16-year period. Therefore, it can be said that in the case of the construction elements of existing buildings, which have already gone through a sufficient period for the maturation of the materials in their construction elements, the rammed earth wall quickly develops a moisture buffer function. In the case of simulating a mineral wool core composite wall, it cannot perform as a temperature or humidity buffer, exhibiting an enthalpy exchange with indoor air that is only 4% of that of the rammed earth walls; consequently, it does not play a significant role in regulating indoor comfort conditions. Overall, there is confirmation of the temperature and moisture buffering capabilities of rammed earth walls during both warm and cold periods of the year, which is consistent with other reports in the literature. The findings of this research provide a better insight into clay as a material for rammed earth walls for more efficient design and construction, offering potential improvements regarding indoor comfort, energy efficiency, and sustainability. The data also provides useful information in the fields of architecture and civil engineering regarding the use of clay as an eco-friendly building material. The results emphasise the importance of thoroughly understanding the thermophysical properties of clay to ensure the efficiency of rammed earth construction. Full article

The proposal in the present research study is the result of a more than two-year process developed in a pallet manufacturing company for anchor enterprises in Southern Sonora, Mexico dedicated to beer production and export to the United States of America. Considering the high pallet demand for this supplier, a strategic plan was created in 2021, establishing an important project for developing technological solutions to improve decision making supported by graphical user interface and focused on sustainability. This study shows the application of system dynamics in all the wood and pallet manufacturing processes with a strategic sourcing supply chain. The method used for its development had the following stages: (1) developing the mapping process; (2) creating the causal loop diagram; (3) developing a flow and stock model with the representing mathematical equations; (4) simulating and validating current scenarios; (5) evaluating normal, optimistic, and pessimistic scenarios with multicriteria decision making using Technique to Order Preferences by Similarity and the Ideal Solution (TOPSIS) and Faire Un Choix Adéquat (FUCA); (6) building the graphical interface. The most relevant results for the company were having quantitative information regarding the pallet demand required by the main client for wood availability, which was the main restriction in the supply chain. The solution was based on four validation tests that allowed decision makers to support the production proposals considering the assistance of the dynamic models. The main conclusion demonstrated that using well-defined operation rules and policies—considering the installed capacity and pallet demand through the model solution—allows anticipating decisions on pallet quantity and reducing the risk of out-of-time deliveries. Full article

Phosphorus (P) is essential for life on Earth, yet its current management is unsustainable. Stakeholder engagement is urgently needed to help ensure that scientific and technical solutions to improve P sustainability meet the needs of diverse groups, yet there are comparatively few studies that provide insights into stakeholder views, perceptions, or concerns. In this opinion, we use a mass flow diagram of P as a boundary object to understand the complex challenges of sustainable P management. In particular, we map US stakeholder groups onto the mass flow diagram to incorporate human factors into mass flows at a national scale. Our approach is grounded in well-established social–scientific methodologies, such as stakeholder mapping and social network analysis, but is applied in a novel way that can be generalized to other mass flows and geographic areas. We then suggest ways that researchers can use the annotated flow diagram to identify both knowledge gaps and research gaps in stakeholder engagement, especially in interdisciplinary or convergence research contexts. Full article