Systematic Analysis Research Articles

Enhancing currency prediction in international e-commerce: Bayesian-optimized random forest approach using the Klarna dataset

In the ever-evolving landscape of global commerce, marked by the convergence of digital transformation and borderless markets, this research addresses the intricate challenges of currency exchange and risk management. Leveraging Bayesian optimization, the study fine-tunes the random forest algorithm using the extensive Klarna E-commerce dataset. Through systematic analysis, the research uncovers insights into managing currency prediction amid dynamic global markets. Emphasizing the role of Bayesian optimization parameters, the study reveals nuanced trade-offs in model performance. Notably, the optimal simulation, conducted with 14 iterations, 1 job, and a random state set to 684, exhibits a standout performance, showcasing a negative mean squared error (MSE) of approximately -0.9891 and an accuracy rate of 74.63%. The primary objective is to assess the impact of Bayesian optimization in enhancing the random forest algorithm's predictive capabilities, particularly in currency prediction within international e-commerce. These findings offer refined strategies for businesses navigating the intricate landscape of global finance, empowering decision-making through a comprehensive understanding of data, algorithms, and challenges in international commerce.

Monitoring bridge bearings based on rubber-based composite materials

To improve the real-time monitoring capability of bridge structure safety, intelligent bridge bearings were prepared based on rubber based composite materials. The study selected T4/3-5 intelligent rubber bearings and conducted a systematic experimental analysis on their response characteristics under different loading speeds and holding states. By measuring the displacement and resistance changes of the intelligent bearings under various load conditions, their sensitivity and stability were evaluated. These experiments confirmed that the T4/3-5 intelligent rubber bearings exhibited a total creep deformation of approximately 1 mm and 1.5 mm under loads of 60 kN and 45 kN, respectively. This suggests that the molecular chains reach a relatively stable configuration under high loads and are not prone to further changes. Moreover, the resistance reduction ratio under a load of 60 kN is approximately 0.57, while under a load of 45 kN it is approximately 0.62, indicating that nickel powder particles in the composite material form a more stable conductive network after molecular rearrangement. At different loading rates, the displacement-load and load-resistance curves of the bearings show consistent trends, and the creep and resistance relaxation behaviors exhibit certain regularity with the concentration of load size. Through the analysis of these data, the study elucidated the resistance change mechanism in the bearings and validated the feasibility of intelligent bearings as a real-time load monitoring tool.

CellSNAP: a fast, accurate algorithm for 3D cell segmentation in quantitative phase imaging.

Three-dimensional quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. It has opened up new directions of investigation by providing systematic and correlative analysis of various cellular parameters without limitations of photobleaching and phototoxicity. While current QPI systems allow the rapid acquisition of tomographic images, the pipeline to analyze these raw three-dimensional (3D) tomograms is not well-developed. We focus on a critical, yet often underappreciated, step of the analysis pipeline that of 3D cell segmentation from the acquired tomograms. We report the CellSNAP (Cell Segmentation via Novel Algorithm for Phase Imaging) algorithm for the 3D segmentation of QPI images. The cell segmentation algorithm mimics the gemstone extraction process, initiating with a coarse 3D extrusion from a two-dimensional (2D) segmented mask to outline the cell structure. A 2D image is generated, and a segmentation algorithm identifies the boundary in the plane. Leveraging cell continuity in consecutive -stacks, a refined 3D segmentation, akin to fine chiseling in gemstone carving, completes the process. The CellSNAP algorithm outstrips the current gold standard in terms of speed, robustness, and implementation, achieving cell segmentation under 2s per cell on a single-core processor. The implementation of CellSNAP can easily be parallelized on a multi-core system for further speed improvements. For the cases where segmentation is possible with the existing standard method, our algorithm displays an average difference of 5% for dry mass and 8% for volume measurements. We also show that CellSNAP can handle challenging image datasets where cells are clumped and marred by interferogram drifts, which pose major difficulties for all QPI-focused AI-based segmentation tools. Our proposed method is less memory intensive and significantly faster than existing methods. The method can be easily implemented on a student laptop. Since the approach is rule-based, there is no need to collect a lot of imaging data and manually annotate them to perform machine learning based training of the model. We envision our work will lead to broader adoption of QPI imaging for high-throughput analysis, which has, in part, been stymied by a lack of suitable image segmentation tools.

Optimizing launch window opportunities for ESA's comet Interceptor mission using primer vector theory

Comet Interceptor (Comet-I) was selected in June 2019 as the first ESA F-Class mission and aims to explore a pristine comet, which will visit the inner Solar System for the first time. Comet-I will hitch a ride to a Sun-Earth L2 quasi-halo orbit, as a co-passenger in ESA's M4 ARIEL's launch. At the time of writing, this is scheduled for 2029. It will then remain there awaiting the right departure conditions to leave definitively and intercept a newly discovered comet. Comet-I will be the first mission to be designed and launched without an already identified target. Given the latter, the Comet-I Target Identification Working Group is tasked with the continuous follow-up of newly discovered comets, to analyse their characteristics as virtual targets for Comet-I. The goal of the paper is to inform the decision-making process that will eventually be necessary to commit Comet-I spacecraft to its final target.Within this context, this paper presents a trajectory optimization process based on Primer Vector theory that considers intercept trajectories with multiple revolutions and multiple deep space manoeuvres (DSM). The process is applied to 21 long period comets, which were discovered since July 1,1st July 2020 and whose characteristics are of interest for the Comet-I mission. In fact, one of the latest of these recently discovered comets, C/2023 H2, is the most accessible virtual target discovered at the time of writing, with delta-V intercept costs well within Comet-I capabilities. A complete launch window analysis is thus presented for C/2023 H2, which accounts not only for the most optimal delta-V intercept transfer, but also considers all launch options that satisfy all Comet-I's current boundary conditions and flyby constraints. A systematic launch window analysis is made possible by a grid search approach on which departure and fly-by dates are fixed and the remaining design variables, including the times for manoeuvres and their Δv impulse vector, are optimized via Primer Vector theory. This allows to understand the latest possible departure date, but also the sensitivity to departure and arrival dates of key encounter characteristics such as relative fly-by speed, the solar aspect angle and the Earth distance.

Development of a school-based programme for mental health promotion and prevention among adolescents in Nepal and South Africa

IntroductionAdolescence is a critical time for mental health promotion and prevention and establishing healthy behaviours. Implementing universal, school-based psychosocial interventions can improve short- and long-term health trajectories for adolescents. While these interventions may offer important opportunities for fostering skills and relationships, few school-based interventions have been developed for and tested in low- and middle-income countries (LMICs) where adolescent mental health needs may be significant and under-served. This manuscript details the development of a multi-component, universal school-based intervention, Health Action in ScHools for a Thriving Adolescent Generation (HASHTAG), for adolescents aged 12–15 years in Nepal and South Africa. Methods and resultsWe describe HASHTAG's development over four phases, combining methods and results as each phase was iteratively conducted between 2018 and 2021. Phase 1 included a systematic review and components analysis, building from WHO guidelines for adolescent mental health. Seven components were strongly supported by the evidence: emotional regulation, stress management, mindfulness, problem-solving, interpersonal skills, assertiveness training, and alcohol and drug education. Phase 2 encompassed site selection, theory of change development, and formative research engagements; research teams in each site engaged adolescents and key adult stakeholders to identify priorities for intervention. Stakeholders voiced preferences for external facilitators and key content and delivery for intervention sessions. These findings informed Phase 3, a draft manual of HASHTAG, including a whole-school component, called Thriving Environment in Schools, and a classroom-based, six-session component, Thrive Together. In Phase 4, participants engaged in consultative workshops to review and contextualise content by country, preparing HASHTAG for implementation in a feasibility trial. Minor adaptations were made in Nepal, including using school nurses and adjusting take-home materials; both country's workshops identified practical considerations for implementing activities. ConclusionsHASHTAG was designed around core evidence-based components to increase translatability across LMICs, while enabling country-specific tailoring to enhance feasibility. Future research will test whether this multi-component, whole-school approach can improve adolescent mental health.

Victory-in-freedom: Ukraine’s democratic resilience in the face of war

The article offers a rare systematic analysis of political attitudes in societies experiencing massive military invasions using statistical analysis of two original surveys conducted by the Ukraine National Academy of Sciences Institute of Sociology — a panel survey tracking the same respondents in three waves (N = 329, November 2021, June-July 2022, and June 2023) and an additional larger survey (N = 869, June 2023). Despite devastating suffering, Ukrainians’ support for democracy as a political system and for freedom of speech have stayed remarkably resilient over this time period. Cross-sectional (multiple ordinary least squares regression) and longitudinal (linear mixed-effects model regression) tests, as well as supplementary focus group conversations in all of Ukraine’s macro-regions, show that this democratic resilience is grounded in the victory-in-freedom synergy — a widespread sense of shared sacrifice that drives determination to win the war and restore Ukraine’s territorial integrity. In particular, we found a clearer understanding of the importance of political freedoms and fighting for victory among individuals who experienced loss and trauma and a strong appreciation across Ukraine’s society that victory is vital to preserve democracy. Survey data also demonstrates that democracy support has become more intrinsic to Ukrainian national identity and that the initial surge of democracy support among Ukrainians in the face of Russia’s invasion has been more than a short-term rallying-round-the-flag. In combination, these factors explain the Ukrainians’ sustained, spirited resilience in the face Russia’s mass savage invasion over more than a two-year period. Moreover, support for democratic ideals doesn’t mean Ukrainians write a blank check of trust to their government. Longitudinal analysis indicates that as the war progressed, and hardship persisted respondents held their democratic institutions accountable. At the same time, the results of our study indicate that sustaining this resilience would require not only battlefield successes, but also accountable governance, countering Russia’s media impacts, and sustaining family incomes. Our findings contribute to the literature on war and democracy by showing the importance of considering both the external context (war duration and impacts and the aggressor state type) and the mobilization of national identity in the face of aggression.

Global, regional, and national burden of thalassemia, 1990–2021: a systematic analysis for the global burden of disease study 2021

Anemia is a significant contributor to the global disease burden, of which thalassemia is the most common hereditary anaemic disease. Previous estimates were based on data that were geographically limited and lacked comprehensive global analysis. This study provides the prevalence, incidence, mortality and disability-adjusted life years (DALYs) of thalassemia in 204 countries and regions of thalassemia between 1990 and 2021, focusing on the age structure and time trends of the disease burden. To provide effective information for health policy, allocation of medical resources and optimization of patient management programs. Using the standardised Global Burden of Disease (GBD) methodologies, we aimed to derive a more precise representation of the health burden posed by thalassemia by considering four distinct types of epidemiological data, namely the incidence at birth, prevalence, mortality and DALYs. The presented data were meticulously estimated and displayed both as numerical counts and as age-standardised rates per 100,000 persons of the population, accompanied by uncertainty interval (UI) to highlight potential statistical variability. The temporal trends spanning the years 1990-2021 were subjected to a rigorous examination utilizing Joinpoint regression analysis. This methodological approach facilitated the computation of the annual percentage change (APC) and the average annual percentage change (AAPC), along with their corresponding 95% confidence intervals (CIs). Globally, the age-standardized prevalence rates (ASPR), age-standardized incidence rates (ASIR), age-standardized mortality rates (ASMR), and age-standardized DALYs rates for thalassemia in 2021 were 18.28 per 100,000 persons (95% UI 15.29-22.02), 1.93 per 100,000 persons (95% UI 1.51-2.49), 0.15 per 100,000 persons(95% UI 0.11-0.20), and 11.65 per 100,000 persons (95% UI 8.24-14.94), respectively. Compared to 1990, these rates have decreased by 0.18 (95% UI-0.22 to-0.14), 0.25 (95% UI-0.30 to-0.19), 0.48 (95% UI-0.60 to-0.28), and 0.49 (95% UI-0.62 to-0.29) respectively. In 2021, the ASIR of thalassemia was highest in East Asia at 7.35 per 100,000 persons (95% UI 5.37-10.04), and ASMR was highest in Southeast Asia at 0.37 per 100,000 persons (95% UI 0.29-0.45).Gender comparisons showed negligible differences in disease burden, with the highest prevalence noted in children under five, decreasing with age. The global ASPR and ASMR declined from 1990 to 2021 overall, though an increasing trend in prevalence was found among the elderly. Joinpoint analysis revealed that the global ASPR increased between 2018 and 2021 (APC=9.2%, 95% CI: 4.8%-13.8%, P<0.001), ASIR decreased (APC=-7.68%, 95% CI:-10.88% to-4.36%, P<0.001), and there was a significant rise in ASMR from 2019 to 2021 (APC=4.8%, 95% CI: 0.1%-9.6%, P<0.05). Trends in ASPR and ASMR varied across regions, with notable changes in South Asia. The global burden of thalassemia, reflected in its prevalence, incidence, mortality, and DALYs, exhibits significant disparities. Geographic and demographic shifts in disease distribution have been observed from 1990 to 2021, with an overall decrease in burden, yet an increase in cases among the elderly population. Analysis of epidemiological trends over time highlights the influence of health policies and significant public health interventions on thalassemia outcomes. There data are crucial for healthcare professionals, policymakers, and researchers to refine and enhance management strategies, aiming to further mitigate thalassemia's global impact. National Natural Science Foundation of China; Guizhou Province Science and Technology Project; Guizhou Province Science and Technology Foundation of Health Commission.

비대면 화상 집단상담에 대한 체계적 문헌고찰

Objectives This study conducted a systematic literature review to examine research trends and confirm the char-acteristics and effects of modulating variables by examining research on non-face-to-face video group counseling. Methods Among the studies related to non-face-to-face video group counseling, papers published from January 2020 to August 2023 were collected. The academic search database used for thesis search was the Academic Research Information Service (RISS), the Korean Academy of Information (KISS), and the Academic Database Service (DBpia). The search terms used for the research were used by combining non-face-to-face, video, group, program, counseling, and effect. Based on the selection criteria and exclusion criteria, the final 31 papers were used for analysis. Results Looking at the classification by symptom level, a significant number of studies were concentrated in the general group (87.1%). In terms of classification according to the stage of development, adults (61.3%) and college students or higher (29.0%). The theoretical approach was mindfulness meditation (35.7%), cognitive emotional behavior (17.9%), and integrated approach (14.3%), and the intervention areas were emotions (24.7%), stress (16.4%), and self-concept (15.1%). Regarding the intervention effect, improvements in emotions, stress, inter-personal relationships, and cognitive domains were confirmed. The self-concept and subjective well-being were mixed with conflicting reports. Conclusions In terms of symptoms, additional research is needed including the clinical group including social anxiety, and in terms of developmental stage, including elementary school students and the elderly. Since con-flicting reports are mixed in the areas of self-concept and subjective well-being, a comprehensive and systematic analysis including meta-research needs to be conducted. This study is significant in that it understands the re-search trends of non-face-to-face video group counseling and the effects of each intervention area, and suggests future research directions.

Resource classification of coal bed methane and its contribution in energy transition and decarbonization path of oil and gas industry (A synopsis of CBM Life Cycle Analysis)

World economies are becoming increasingly more dependent on energy and countries have a voracious appetite for energy therefore, the need for an abundant clean energy is becoming a necessity. Energy companies are challenging environmental costs of coal bed methane as with advancement of new technology the impact from production of coal bed methane can reduce and to a certain extent avoided or offset. Production of coal bed methane results in changes to the land, to surface water and to ground water systems. Carbon quantification is required to understand, monitor and manage these changes. Previous life cycle analysis for this resource class has lack of process design details because of which there is a knowledge gap in understanding of emission profile of coal bed methane’s production. The objective of this study is to add value and reduce the scientific gap with respect to the production techniques of coal bed methane and its environmental impact. Removal of water continuously from coal seams depletes ground water and may eventually lower surface water flows (streams and rivers). It can also change the flow of groundwater drawing fresh water into the coal seams. To better understand this phenomenon the work establishes the Coal Bed Methane production foundation by in depth understanding of · Coal Bed Methane reservoir types; · Coal Bed Methane depositional environment, generation, and geological distributions; · Coal Bed Methane resource energy supply methods by understanding its construction, production and processing. The study then uses Life Cycle Assessment approach and understands previous emission numbers of Coal Bed Methane’s resource development. The work does systematic analysis and summarizes the previously published Life Cycle Analysis to understand further the potential environmental impacts of resource development of Coal Bed Methane. This will help energy companies to understand the field development, production, and operations of coal bed methane’s resource in terms of carbon numbers thereby optimizing the operations through carbon management thus reducing the potential impacts.

Managing global supply chain teams: human resource strategies for effective collaboration and performance

This study examines the role of human resource (HR) strategies in enhancing collaboration and performance within global supply chains, an area of increasing importance in the context of globalized business operations. The primary objective is to identify and analyze current trends in HR practices that contribute to effective global supply chain management, focusing on adaptability, technological integration, sustainability, and ethical practices. Employing a systematic literature review and content analysis as its methodology, the study draws on academic journals, conference proceedings, and industry reports from databases such as Scopus, Web of Science, and Google Scholar. Key findings reveal that adaptability and flexible work arrangements, supported by digital HR technologies, are essential for operational resilience and employee engagement. The integration of sustainability and ethical considerations into HR practices is identified as crucial for maintaining competitive advantage and ensuring regulatory compliance. Furthermore, the development of cultural intelligence and inclusive leadership within global teams is highlighted as vital for fostering effective collaboration across diverse cultural landscapes. The study concludes that strategic HR management plays a pivotal role in navigating the challenges and leveraging the opportunities within global supply chains. Recommendations for practitioners emphasize the importance of continuous learning, embracing digital transformation, and integrating sustainability into HR practices. The study also outlines areas for further research, including the impact of emerging technologies on HR practices and the long-term effects of sustainable HR strategies on organizational performance. This research contributes valuable insights into optimizing HR strategies to enhance global supply chain collaboration and performance.

Human resource strategies for resilient supply chains in logistics and transportation: A critical review

This study systematically reviews and analyzes the literature on Human Resource Management (HRM) strategies for enhancing supply chain resilience in the logistics and transportation sector, identifying the pivotal role HRM plays in fortifying supply chains against disruptions. Utilizing a systematic literature review and content analysis, this research examines articles from peer-reviewed journals, focusing on publications from 2004 onwards to capture contemporary HRM practices and their impact on supply chain resilience. The methodology involves a detailed search strategy across multiple databases, employing specific inclusion and exclusion criteria to ensure the relevance and quality of the literature reviewed. Key findings reveal that workforce agility, technological integration in HRM practices, leadership development, and the cultivation of a resilient organizational culture are essential components of effective HRM strategies in this context. These elements collectively contribute to the resilience of supply chains, enabling organizations to maintain operational continuity during disruptions. Based on these insights, the study proposes strategic recommendations for industry leaders and policymakers, emphasizing the importance of investing in employee development, adopting technology-enhanced HRM practices, and fostering ethical and sustainable HR practices to support supply chain resilience. Concluding, the study highlights the need for further research, particularly empirical studies that examine the direct impact of HR strategies on supply chain performance. This research underscores the critical role of strategic HRM in enhancing supply chain resilience, offering a roadmap for future efforts in the logistics and transportation sector.

Exploring the Antibacterial Potential of Medicinal Plants with Challenges and Opportunities in Formulation: A Review

The emergence of antibiotic resistance among pathogenic bacteria poses a significant threat to global public health. In response, there has been a resurgence of interest in exploring natural alternatives, particularly medicinal plants, for their antibacterial properties. This review provides a comprehensive overview of the medicinal plants with documented antibacterial activity, their bioactive compounds, mechanisms of action, and potential therapeutic applications. Through a systematic analysis of current research literature, this review aims to highlight the diversity of plant-derived antibacterial agents and their potential as future therapeutic agents in combating bacterial infections.

What to do With Cross-Border Environmental Pollution: Legislative Aspects

Abstract – Environmental torts and possibility of trans-border dispute settlement thereof has gained significant prominence in the recent years. Cases such as Urgenda foundation v the State of the Netherlends, Milieudefensie et al. v. Royal Dutch Shell plc., ClientEarth v. Enea, Neubauer et al. v. Germany demonstrate that environmental tort cases can be brought by stakeholders globally rather than relying on involvement of a relevant national responsible authority. EU climate policy of decreasing GHG emissions and the ambitious target of reaching climate neutrality by 2050 has resulted in a rapid development of environmental law. Thus, environmental regulation is becoming increasingly complex and possible breaches may cause serious legal consequences affecting everyone not just selected individuals or states. These developments could possibly lead to a necessity of a forum or rules where any natural person or an NGO could bring a claim against a state or multinational corporation which engages in illegal activities causing harm the environment on a global scale. Using litigation as a tool to empower society to stand against environmental wrongdoers may serve as a deterring factor to maintain order when it comes to environmental regulation. While such reasoning may seem farfetched and extreme, nevertheless it still raises a question of current regulation on determination of jurisdiction and the applicable law and whether it would be possible to benefit from developing these rules. By engaging in a systematic literature analysis identifying the relevant terms, the research shall explore the basic principles of private international law in relation to assigning jurisdiction and determining applicable law in claims concerning environmental torts. The research shall develop a methodology with the aim of covering and identifying a wider range of problems related to the determination of jurisdiction and application of law in cross-border environmental tort claims. Some of the main issues concern the determination of defendants in cases involving multinational corporations, multi-claimant cases, and the compensation of indirect damages. An exploration of material aspects in the developments of the current EU regulation and guidelines shall be analysed in conjunction with the aforementioned notion. The result of the study not only will reflect the specifics of the application of the Brussels Ibis Regulation and Rome II regulation in cross-border environmental torts, but also how the EU environmental regulation could potentially promote corporate responsibility and environmental protection. Thus, developing research on interaction between private international law and environmental law. Keywords - environmental tort, SEG emissions, jurisdiction, applicable law, cross-border pollution

Building Urban Resilience through Mega-Events: A Systematic Review using Text Mining and Natural Language Processing (NLP)

This research aims to investigate the relationship between urban resilience and urban mega-events and to gain a deeper understanding of the ways in which effective planning, sustainable development, and social capital can be utilized to enhance urban resilience. The research will seek to explore how urban mega-events can be planned in ways that not only have significant economic impacts but also promote strategies for enhancing resilience in cities. To investigate the relationship between urban resilience and mega-events, a systematic review of the existing literature (2500 articles) was carried out. To investigate the relationship between urban resilience and mega-events, a systematic review of 2,500 articles was conducted. However, it should be noted that the limitations of qualitatively reviewing such a large number of publications must be acknowledged. Therefore, the review process involved differentiating between keyword analysis and systematic literature analysis for identifying success factors and good practices. Subsequently, eleven articles on different aspects of urban resilience and mega-events were subjected to lexical analysis (text mining) in order to measure and quantify the sentiment expressed in the articles. It is acknowledged that the number of articles included in the corpus is limited to 11. However, efforts have been made to ensure that the sample is representative of the wider corpus, with articles selected according to the following criteria: theme, keywords, and bibliometric search results. A hierarchical analysis was also employed to group the articles into comparable groups. The results of this analysis provided a more comprehensive understanding of the prevailing views on urban resilience, the implications of mega-events on urban areas, and potential strategies for enhancing the resilience of cities.

Quantitative liquid storage by billiards‐like droplet collision on surfaces with patterned wettability

AbstractThere has been significant interest in researching droplet transport behavior on composite wetting surfaces. However, current research is primarily focused on modifying individual droplets and lacks an in‐depth investigation into high‐precision droplet storage. This study introduces a “billiard ball” droplet transport and storage platform (TSP) with differentiated areas. Within this platform, the volume of droplets stored in the area reaches a consistent threshold through droplet “scrambling,” inspired by the water‐gathering behavior of spiders. The TSP involves connecting two regions of different sizes using a three‐dimensional stepped wedge angle structure. However, this connection is not seamless, leaving a 2‐mm gap between the regions. This gap is intentionally designed to enable continuous droplet transfer while preventing any static migration. Through systematic experimental and simulation analysis, we investigated the influence of superhydrophilic pattern structures and parameters on quantitative droplet storage. We established a functional relationship between the pattern area and the stored volume, and analyzed the intrinsic mechanism of droplet collision separation. This enabled us to achieve on‐demand quantitative droplet storage and autonomize the storage process. The “billiard ball” droplet transport–storage platform proposed in this study holds promising applications in the fields of biomedical and organic chemistry.

Landslide hazard assessment of the fault zone considering the fault effect: a case study of the Lixian–Luojiabu fault zone in Gansu Province (China)

The earthquake landslide hazard assessment method is mainly based on the traditional Newmark model. However, when the landslide hazard assessment is carried out along the fault zone, the calculated results are often different from the actual situation because the influence of fault effect is not fully considered. Therefore, how to construct a landslide hazard assessment model suitable for the fault zone is a technical problem to be solved by researchers. Taking the Lixian–Luojiabu fault zone in Gansu Province in China as the study area, this paper put forward the concept of fault effect correction coefficient exploringly, systematically studied the relative distance relationship between the landslide and fault zone, and the relative position relationship between landslide and upper and lower sides of the fault zone. The value table of the fault effect correction coefficient along the Lixian–Luojiabu fault zone was established, and the corresponding distribution map of the fault effect correction coefficient was drawn. Based on this, an improved Newmark model for the landslide hazard assessment along the fault zone was constructed. On the basis of systematic analysis of the slope and engineering geological rock group in the study area, the traditional Newmark model and improved Newmark model considering fault effects were used, respectively, to carry out the earthquake landslide hazard assessment under the condition of 10% exceeding probability in 50 years, and the ROC curve and Kappa coefficient methods were used to compare and analyze the evaluation results. The results showed that the AUC value and Kappa coefficient of the danger area obtained by the improved model with the Newmark model were 0.841 and 0.822, respectively, which were significantly higher than the calculated values of the traditional Newmark model, indicating that the model had a good improvement effect. The Newmark improved model, considering the fault effect, fully considered the influence of distance from the fault zone and fault upper and lower side effects, and the research results can provide a new reference for the landslide hazard assessment along the fault zone.

Role of machine learning algorithms in suicide risk prediction: a systematic review-meta analysis of clinical studies

ObjectiveSuicide is a complex and multifactorial public health problem. Understanding and addressing the various factors associated with suicide is crucial for prevention and intervention efforts. Machine learning (ML) could enhance the prediction of suicide attempts.MethodA systematic review was performed using PubMed, Scopus, Web of Science and SID databases. We aim to evaluate the performance of ML algorithms and summarize their effects, gather relevant and reliable information to synthesize existing evidence, identify knowledge gaps, and provide a comprehensive list of the suicide risk factors using mixed method approach.ResultsForty-one studies published between 2011 and 2022, which matched inclusion criteria, were chosen as suitable. We included studies aimed at predicting the suicide risk by machine learning algorithms except natural language processing (NLP) and image processing.The neural network (NN) algorithm exhibited the lowest accuracy at 0.70, whereas the random forest demonstrated the highest accuracy, reaching 0.94. The study assessed the COX and random forest models and observed a minimum area under the curve (AUC) value of 0.54. In contrast, the XGBoost classifier yielded the highest AUC value, reaching 0.97. These specific AUC values emphasize the algorithm-specific performance in capturing the trade-off between sensitivity and specificity for suicide risk prediction.Furthermore, our investigation identified several common suicide risk factors, including age, gender, substance abuse, depression, anxiety, alcohol consumption, marital status, income, education, and occupation. This comprehensive analysis contributes valuable insights into the multifaceted nature of suicide risk, providing a foundation for targeted preventive strategies and intervention efforts.ConclusionsThe effectiveness of ML algorithms and their application in predicting suicide risk has been controversial. There is a need for more studies on these algorithms in clinical settings, and the related ethical concerns require further clarification.

A systematic analysis of studies on reading skills with specific learning disabilities: The case of Türkiye

A systematic analysis of studies on reading skills with specific learning disabilities: The case of Türkiye

Genome-wide analysis of filamentous temperature-sensitive H protease (ftsH) gene family in soybean.

The filamentous temperature-sensitive H protease (ftsH) gene family belongs to the ATP-dependent zinc metalloproteins, and ftsH genes play critical roles in plant chloroplast development and photosynthesis. In this study, we performed genome-wide identification and a systematic analysis of soybean ftsH genes. A total of 18 GmftsH genes were identified. The subcellular localization was predicted to be mainly in cell membranes and chloroplasts, and the gene structures, conserved motifs, evolutionary relationships, and expression patterns were comprehensively analyzed. Phylogenetic analysis of the ftsH gene family from soybean and various other species revealed six distinct clades, all of which showed a close relationship to Arabidopsis thaliana. The members of the GmftsH gene family were distributed on 13 soybean chromosomes, with intron numbers ranging from 3 to 15, 13 pairs of repetitive segment. The covariance between these genes and related genes in different species of Oryza sativa, Zea mays, and Arabidopsis thaliana was further investigated. The transcript expression data revealed that the genes of this family showed different expression patterns in three parts, the root, stem, and leaf, and most of the genes were highly expressed in the leaves of the soybean plants. Fluorescence-based real-time quantitative PCR (qRT-PCR) showed that the expression level of GmftsH genes varied under different stress treatments. Specifically, the genes within this family exhibited various induction levels in response to stress conditions of 4℃, 20% PEG-6000, and 100 mmol/L NaCl. These findings suggest that the GmftsH gene family may play a crucial role in the abiotic stress response in soybeans. It was also found that the GmftsH7 gene was localized on the cell membrane, and its expression was significantly upregulated under 4 ℃ treatment. In summary, by conducting a genome-wide analysis of the GmftsH gene family, a strong theoretical basis is established for future studies on the functionality of GmftsH genes. This research can potentially serve as a guide for enhancing the stress tolerance characteristics of soybean.

Chiral Tetrakis Eu(III) Complexes with Ammonium Cations for Improved Circularly Polarized Luminescence

Large dissymmetry factor of the circularly polarized luminescence (gCPL) was observed in ligand and coordination tuned chiral tetrakis europium (Eu(III)) complexes with ammonium cations. The gCPL value was estimated to be −1.54, which is the largest among chiral luminescent molecules. Through photophysical measurements, single crystal X‐ray structural analyses and quantum chemical calculations, changes in the geometric and electronic structures were observed for a series of chiral tetrakis Eu(III) complexes which enhanced the gCPL value. The emission quantum yield and photosensitized energy transfer efficiencies of chiral Eu(III) complexes with ammonium cations were also larger than that with previous Cs+. Based on the systematic modifications and analyses for chiral tetrakis Eu(III) complex, effect of the ammonium cation on enhanced CPL brightness is reported.