bluuebunny/crossref_metadata_2025 huggingface dataset:
Seismic Performance Assessment for Serviceability of Geosynthetic Reinforced Embankments
Authors:   Qom University of Technology, Borujerdi Ali Ramazan
Published: October 2024

Embankments in the field of civil engineering were historically not given much attention in terms of their ability to withstand seismic activity, as they were considered to be non-critical structures. However, in recent years, the seismic stability of embankments has gained increasing importance in the field of geotechnical engineering. This increased significance is due to the need to quickly restore functional infrastructure after earthquakes. The occurrence of lateral spreading, resulting from foundation liquefaction, is the primary factor leading to embankment distress in geotechnical engineering during seismic events. To address this issue, this study presents a novel approach that employs geosynthetic basal reinforcement. The research paper presents a technique that uses geosynthetic basal reinforcement to manage the lateral spreading of embankments both pre- and post-earthquakes, guaranteeing their ongoing effectiveness. The proposed approach utilizes a pseudo-static limit equilibrium method for determining the tensile load produced in the basal reinforcement. The serviceability criteria establish the maximum strain permitted in the basal reinforcement by imposing a restriction on the horizontal movement of the embankment toe. By taking into account the tensile load of the reinforcement and the maximum allowable strain, it is feasible to establish an appropriate geosynthetic reinforcement that considers various factors including tensile strength, strain, design life, installation, and durability impacts.
Classifying Phishing Websites Using Multilayer Perceptron
Authors:   Universiti Utara Malaysia, Mohsin Muhammad Ikram , Harun Nor Hazlyna ,   Universiti Utara Malaysia
Published: October 2024

Theprevalenceofphishing asacybercrimecontinuestoescalate, posing significant threats to individuals' sensitive information. Thispaper addresses the urgent need for effective phishing detectionmethods, considering the limitations of existing approaches. The studyemploysArtificial Neural Networks, specifically Multilayer Perceptrons(MLP), trained using the backpropogation algorithm. The study also highlights MLP’s advantages in handling complex and noisy data. Through a comprehensivereview of related works, the paper identifies gaps in currentresearch and establishes the groundwork for an innovative phishing website classification framework. The proposed solution utilizes MLPs, offering a detailed explanation of themethodology, dataset, model architecture, and training processes. Theresearch concludes by summarizing key findings, emphasizing thesolution's contributions to cybersecurity, and outlining potentialavenues for future research.
A Retrospective Study on Insulin Resistance in Adults with Autoimmune Thyroiditis in Turkish Population: a Clinical and Molecular Docking Study
Authors: Aslan Elif , Gür Savaş
Published: October 2024

Background/Purpose: This study aims to retrospectively analyze existing data to assess the prevalence and intensity of insulin resistance among adults with autoimmune thyroiditis, a condition marked by the body's immune response against its thyroid gland, including Hashimoto's thyroiditis. Insulin resistance, characterized by the body's inadequate response to insulin, complicates blood sugar regulation. This research seeks to explore historical health records of individuals diagnosed with autoimmune thyroiditis to identify potential correlations with insulin resistance.

Methods: Our approach involves a comprehensive review of previous medical records, with a focus on evaluating insulin levels, HbA1c values (an indicator of blood sugar regulation), and other pertinent health markers in patients with autoimmune thyroiditis. Data analysis was conducted using SPSS version 26, a software extensively employed in social sciences for statistical computations. The distribution normality was verified through the Shapiro-Wilks test and Box Plot diagrams. Correlation between variables was determined using either Pearson or Spearman's correlation analysis.

Results: Our statistical analysis uncovered a significant correlation between higher Insulin Resistance (HOMA-IR) scores and increased levels of blood glucose and insulin, with p-values indicating strong positive relationships (p
Pathway of Online Impulsive Buying Tendency Research (2007-2024): Bibliometric Analysis
Authors: Zulfikar Rizka , Yulianti Farida , Lamsah Lamsah , Wicaksono Teguh , Purboyo Purboyo
Published: October 2024

The goals of this study were to assess the body of knowledge about the propensity for online impulsive purchasing, to rectify the shortcomings of past reviews, and to provide academics and industry professionals with an up-to-date, thorough overview of the state of research in the field of online impulse buying tendency. We employed bibliometric analysis approaches to analyze the body of literature on online impulsive purchasing propensity. It was useful for summarizing data through significant contributions, the most prolific writer, the most powerful organization, output within a specific time frame, the rise of keywords, and so on. Article searches were conducted using the Scopus database from 2007 until 2024. The number of studies undertaken in this sector has significantly increased in recent years, as evidenced by bibliometric studies, with China and the United States being the leading contributors. The literature frequently mentioned hedonistic consumption habits, the impact of social media, website design, and promotion. Future studies should look more closely at how emerging technologies like virtual reality and artificial intelligence affect impulsive purchasing behaviour. More comprehensive insights could also be obtained by conducting in-depth studies on cultural variations and the ways in which cultural elements influence impulsive internet purchases.
Exploring Green Consumerism: The Impact of Environmental Knowledge, Social Influence, and Attitudes on Millennials' Purchase Intentions
Authors: Purboyo Purboyo , Firdaus M Riza
Published: October 2024

Indonesia is experiencing a demographic bonus, where millennials make up a significant portion of the productive age population. This demographic shift presents challenges in meeting labour market demands, as well as consumption patterns, particularly concerning sustainable consumption. Simultaneously, environmental issues such as climate change and unsustainable resource usage have become pressing global concerns. Millennials have a crucial role in addressing these challenges by adopting environmentally friendly behaviours, including green product consumption. However, the factors that drive millennials' green purchase intentions, particularly in Indonesia, remain understudied. This study aims to investigate the influence of environmental knowledge, environmental concern, social influence, and attitude on the green purchase intentions of Indonesian millennials. The research employs a quantitative descriptive approach, using purposive sampling to collect data from 150 millennials in Banjarmasin. Data were analyzed using Structural Equation Modeling (SEM) through the Partial Least Squares (PLS) method. The findings reveal that environmental concern indirectly affects green purchase intention through the mediating role of attitude. Additionally, social influence and environmental knowledge have significant positive impacts on both attitude and green purchase intention. The study highlights the importance of enhancing environmental knowledge and leveraging social influence to encourage sustainable purchasing behaviour among millennials. Marketers can use these insights to design effective strategies that promote eco-friendly products to this demographic. Future research could explore other factors, such as perceived product quality and price sensitivity, to gain a more comprehensive understanding of green consumer behaviour.
The Effect of Employing Green Materials on the Business Performance of the Sustainable Retail Sector
Authors: Putra Defin Shahrial , Artiningsih Dwi Wahyu , Wicaksono Teguh
Published: October 2024

There has been an increasing demand in the retail sector to become more environmentally sustainable in its operations. One crucial aspect of sustainable retail operations is green materials, which can lead to better business performance among firms in sustainable retailing. The quantitative approach was adopted in this study, whereby a structured questionnaire was administered to the respondents, who, in this case, were retailers in a specific sustainable retail environment. The population of this study comprises 200 retailers based in the sustainable retail sector who are using green materials for their supply chain packaging and manufacturing processes, such as Post Industry Recycled, biodegradable and organically oriented materials. This study will help develop strategies to incorporate green materials in business operations to benefit companies in a sustainable retailing business. The research shows that adopting environment friendly materials such as biodegradable and recyclable ones can make a company more profitable, prefered by customers, loyal to the customers and respond to their needs and promote their image to previse customers who are green conscious. It entails that sustainable actors in the retail sector who incorporate green materials in their product designing and manufacturing processes are likely to snatch the sustainable market efficiently.
“Culture-touristification” of colonial towns in the interior of Brazil
Authors: Karner Marie Johanna , Husseini de Araújo Shadia , Escher Anton Jakob , Soares Sávia Bona Vasconcelos , Ribeiro Zenilda Lopes , Pöschl Sebastian Nicolas , Ramos Jade Oliveira , Rocha e Silva Gabriel Rodrigues , Schneider Katharina
Published: October 2024

The link between cultural heritage, touristification, and urban development has been extensively researched in larger cities with a strong appeal to international tourists. However, there is limited information on the relationship between these factors in smaller cultural heritage towns that rely only on regional or national tourism. This is also the case for small and medium-sized colonial towns in the Brazilian interior, which are the focus of this paper. We introduce the concept of “culture-touristification” as a form of touristification that is co-constituted by several interacting, culture-led sub-processes, such as patrimonialization, culturalization, festivalization, adventuring of landscapes, telenovelaization, and counter-culturalization. Based on this concept, we argue that culture-touristification drives the touristic transformation of small and medium-sized colonial towns in the interior of Brazil. However, the effects and the interplay of these sub-processes are different in these towns. Some of them may be more pronounced than others, and some may only be partially articulated, depending, for example, on their societal significance, the strategic orientation of responsible stakeholders, the resistance of local populations, or the geographical location of the towns. To illustrate this argument, we draw on case studies conducted in Cidade de Goiás and Pirenópolis, two small colonial towns in the state of Goiás, Brazil. Methods include in-depth and semi-structured interviews with residents and critical actors, mappings of building use in the town centers, participant observation, analysis of telenovelas and Instagram hashtags representing these cities, and document and data research.
Ransomware Detection on Windows Systems Using File System Activities and a Hybrid Machine Learning Approach
Authors: Miranem Valeria , Petrescu Giovanni , Schelling Dominic , Vasiliev Alejandro
Published: October 2024

As a type of aggressive malware, ransomware continues to be one of the most destructive forms of cyberattacks, frequently targeting Windows systems and causing widespread disruption to individuals, corporations, and governments. The need for a more adaptive detection method is clear, as traditional signature-based approaches often fail against sophisticated ransomware strains that employ obfuscation techniques. A novel hybrid machine learning model is proposed, combining Support Vector Machines (SVM) and Random Forests (RF), specifically designed to detect ransomware through analysis of file system activities. This approach leverages the complementary strengths of both algorithms: SVM's capacity to handle high-dimensional data and RF's robustness in handling noisy datasets and providing feature importance insights. By focusing on file operations such as renaming, deletion, and modification, the model effectively distinguishes ransomware from benign applications with high accuracy. Results demonstrate the hybrid model’s superior performance compared to individual SVM and RF models, particularly in terms of precision, recall, and overall resilience against evasive ransomware techniques. Future directions suggest expanding the dataset and exploring deep learning methods to further enhance detection capabilities.
Moving Forward with Digital Data
Authors: Bischoff Robert J
Published: October 2024

The use of online databases to distribute and archive archaeological data has increased in the U.S., but progress is still limited. Funding and data standardization are the primary obstacles. This paper primarily discusses the results of a survey and interviews concerning archaeologists' opinions on the use of these databases and relevant obstacles. Most archaeologists support the use of online databases to distribute data. The adoption of digital technology can aid the dissemination of archaeological data, but current policies and priorities must be reevaluated to significantly increase archaeologists' participation in online databases.
Vertical Evolution
Authors: Yin Chun
Published: October 2024

This book argues that vertical relationships, where the existence of realities are interdependent, form the bedrock of the objective world, contrasting with the traditional horizontal (materialistic) worldview, where entities exist independently. A method to describe these vertical relationships is proposed. By reducing systems to interaction networks, "survival of the independent (closed)" is concluded as the fundamental principle governing the evolution of systems. This principle is further applied in analying life systems, consciousness, and social systems.
Take it or leave it: The effect of caffeine on the maximum strength of complex exercises
Authors: Šťastný Daniel , Třebický Vít
Published: October 2024

Caffeine is a stimulant commonly used to enhance sports performance, including maximal strength in aerobic and anaerobic exercises. While research indicates caffeine's positive effects on both upper- and lower-body strength, evidence of its impact on full-body exercises and maximal intermittent strength remains inconclusive. This pre-registered study investigated the effects of caffeine (3 mg/kg) on maximal isometric strength in complex exercises, including isometric bench press, isometric mid-shin pulls, and maximal intermittent strength in isometric mid-thigh pulls. Thirty-six men completed three sessions: baseline, caffeine, and placebo. Peak force was measured for each exercise in all sessions. The results showed no statistically discernible difference between caffeine and placebo for the isometric bench press, while for isometric mid-shin pulls, we found a statistically discernible improvement in performance (Cohen's d = 0.3, p < 0.001). For isometric mid-thigh pulls, caffeine had a statistically discernible positive effect on the peak force compared to placebo (Cohen's d = 0.17, p < 0.001) but no effect on the rate of performance decline across repetitions. No statistically discernible differences in caffeine's ergogenic effects were found between upper-, lower-, and full-body exercises (ps > 0.05). Our findings suggest limited ergogenic benefits of caffeine for acute maximal isometric strength gains, particularly in complex movements, thus challenging the assumption of its universal effectiveness. The study underscores the need for research based on larger samples to verify caffeine's ergogenic effects. The small samples across current studies probably lack the sensitivity needed to observe caffeine’s true effects, thus limiting the generalizability of the findings.
Needs and Guidelines for Developing Innovative Thinking Skills of Private School Administrators in Samutprakan Province
Authors: Jarungvittayakorn Montira , Nampradit Anusorn
Published: October 2024

This research aimed to: 1) study the current state, the desired state, and the necessary needs for developing innovative thinking skills of private school administrators in Samut Prakan Province 2) propose a guideline for developing innovative thinking skills of private school administrators in Samut Prakan Province. The sample group consisted of 96 school administrators, selected through purposive sampling, and 345 teachers, totaling 441 participants, selected through simple random sampling. The research instrument was a questionnaire with an overall reliability of .954. Data were analyzed using basic statistics such as percentage, mean, standard deviation, Cronbach’s Alpha reliability coefficient, and the Modified Priority Needs Index (PNI modified) to rank the needs. An interview guide was also used to gather insights into developing innovative thinking skills. Data analysis involved frequency statistics and content analysis. The research results showed that: 1) The current state of innovative thinking skills of private school administrators in Samut Prakan Province was overall at a high level. When considering individual aspects, the highest average was in creative thinking, while the lowest was in linking to new knowledge. 2) The desired state of innovative thinking skills was overall at a high level, with the highest average in experimentation and the lowest in observation. 3) The ranking of necessary needs indicated that linking to new knowledge ranked first, followed by experimentation and observation, respectively. 4) Appropriate approaches to develop innovative thinking skills of private school administrators. Samut Prakan Province consists of linking to new knowledge organizing training and seminars, developing systematic thinking skills, practicing using digital tools, promoting the use of research processes, enhancing linking skills, and establishing monitoring and evaluation systems. observation conduct SWOT analysis, build cooperation networks, create risk management plans, develop data collection and analysis systems, organize training, hold monthly meetings, promote the use of research processes, and train systematic thinking skills. experimentation: Promote research activities, improve communication skills, provide training, and develop innovations. creative thinking: Organize training and seminars, promote the use of research processes, encourage the use of technology, support innovation management, and build networks. creative questioning: Provide training and seminars, create conducive environments, practice questioning skills, coach on techniques, and promote idea exchange.
Histopathological breast cancer image classification with feature prioritization using a heuristic algorithm
Authors: Nahid Abdullah-Al , Raihan Johir , Sikder Niloy , Sabuj Saifur Rahman
Published: October 2024

Breast cancer (BC) is one of the most common and most dangerous cancers found in women. A few methods are used for its diagnosis; among them, the biopsy is a very effective method for investigating cancer. In a biopsy, tissue is taken from the breast and observed under a microscope by an experienced histologist. This manual detection is time-consuming and may lead to human error. Hence, computer-aided diagnosis is used to investigate histopathological images. A few computer-aided diagnosis (CAD) methods are available for the investigation of histopathological images. In this work, we describe the extraction of global and local features from images using convolutional neural networks (CNNs) and the use of histograms to classify breast cancer images. In addition, a heuristic algorithm is used to extract a smaller number of effective features with which to classify breast cancer images using an ensemble of random forest (RF) classifiers. Using the ensemble classifier, we obtained an accuracy of 91.92% and a precision of 96.90% by processing the BreakHis dataset.
Communicating about “The End of Fossil Fuel” in a museum setting: a mixed-methods investigation of the Climate Museum
Authors: Badullovich Nic , Nesci Amanda , Massie Miranda , Kotcher John , Maibach Edward
Published: October 2024

Our understanding of who museums reach, and how effective these institutions are in communicating climate change, is not well studied. Moreover, museums focusing solely on the issue of climate change are rare. We present an analysis of the Climate Museum, the first U.S. museum focused on climate change, which combines art, learning, and opportunities for action. We collected pre-post survey data (n=143) as well as conducted qualitative interviews (n=39) with visitors over a six-month period. We found that visitors – more than 80% of whom were Alarmed about climate change – were more determined and confident in speaking about climate change, more hopeful it can be solved, and clearer about how much others are concerned, after visiting the museum. Our qualitative analysis complements these findings and identifies three key themes visitors learned about and planned to share with others: the intertwining of climate change and social inequality, the history of deception by the fossil fuel industry, and the prevailing public opinion when it comes to who is concerned about climate change. We present our findings and implications for future climate-oriented museums.
WASH and learn: a scoping review of health, education and gender equity outcomes of school-based water, sanitation, and hygiene in low- and middle-income countries
Authors: Bick Sarah , Davies Katherine , Mwenge Mwamba , MacLeod Clara , Braun Laura , Chipungu Jenala , Chidziwisano Kondwani , Dreibelbis Robert
Published: October 2024

School-age children in low- and middle-income countries (LMICs) face health and educational challenges due to inadequate water, sanitation and hygiene (WASH) in schools (WinS). Evidence for the impact of WinS interventions is limited and inconsistent, and previous systematic reviews have faced challenges in synthesising data due to varied interventions, study designs, and outcome measures, although most do not examine this variability in more detail. This scoping review identified 83 experimental studies from 33 LMICs measuring a primary or secondary health or educational outcome among pupils, published up to November 2023, using a systematic search of seven databases and searching of reference lists of previous systematic reviews and included articles. These included 65 studies (78%) not included in previous WinS reviews and encompassed 313 intervention effects across 14 outcome domains. Interventions comprised an array of WASH technologies and approaches, often combining infrastructure and behaviour change methods and frequently integrated with other school-based initiatives like deworming. 36 studies (43%) measured only behavioural or knowledge outcomes. Our comprehensive inventory of study outcomes identified 155 unique outcome measures, with 72% measured in exactly one study. Common outcomes included parasitic infections, anthropometric measures, and school absence, but approaches to measurement varied widely even for similar outcomes. Only 7% of results were disaggregated by gender, limiting assessment of differential impacts. Our findings underscore the need for standardised outcome measures in WinS research incorporating a complete definition of the assessment and aggregation approach, greater attention to gender-specific impacts, and further exploration of modalities and functions of WinS interventions alongside novel meta-analysis methods to disentangle effects of diverse intervention components.
A Moderated Mediation Model of Asian Values Predicting Professional Help-Seeking: Exploring God-Centered Self-Esteem as a Protective Factor Against Stigma
Authors: Chen Terence , Chin Eu Gene , Wang David
Published: October 2024

Asian Americans, the fastest-growing ethnic minority in the United States, continue to experience instances of racial microaggression and marginalization that result in feelings of anger, frustration, and increased risks of mental health disorders (Budiman & Ruiz, 2021; Sue et al., 2007; Tessler et al., 2021; Yip et al., 2021). Despite being exposed to risk factors linked with mental health problems, Asian American communities persistently exhibit low rates of mental health service utilization. The discrepancy in mental health service utilization is particularly pronounced among Asian Americans in the Christian community (Lukachko et al., 2015). While past literature explores the role of demographic variables and Asian values to explain this disparity, the current study utilizes Hayes' (2018) methodology to test a moderated mediation model exploring the role of stigma by close others and God-center self-esteem contributing to Asian values and help-seeking attitudes. As predicted, God-centered self-esteem moderated the mediating relationship between Asian values enculturation and professional help-seeking attitudes through perceived stigma by others. Implications and limitations of these findings are discussed, pertaining to the integration of religion/spirituality in appropriate outreach efforts and therapeutic contexts to improve the well-being of Asian American Christians.
Exploring Child-Directed Language of Lebanese Mothers: Analyzing Quality, Quantity, and Pragmatic Functions of Linguistic Input
Authors: El Amin Mariam , Brown Jennifer
Published: October 2024

Maternal linguistic input is critical for a child's language development, yet little is known about how Lebanese mothers communicate with their children. This exploratory study analyzed child-directed speech (CDS) from ten mother-child dyads in Lebanon, recorded in three contexts: (a) playing with toys, (b) reading a wordless picture book, and (c) an activity of the mothers’ choice. The conversations were transcribed and analyzed using CLAN. They were also coded for the pragmatic functions used by mothers. Results from a repeated measures ANOVA revealed that mothers used significantly more diverse words and more words per minute during the book-reading context compared to the other contexts. Labels and attention directives were more frequent in book reading, while action directives were used more during naturalistic interactions. These findings highlight the significance of studying CDS in diverse cultural contexts, contributing to the limited literature on Arabic CDS with research and clinical implications.
Mixed-Methods Needs Assessment of Mental Health among Asian American Christians: A Pilot Study
Authors: Kwong Priscilla , Dwiwardani Carissa , Kim Grace , Chin Eu Gene , Chang Nicole , Cho Lydia
Published: October 2024

Despite the growing recognition of mental health concerns within Asian American populations,significant barriers exist in accessing and receiving adequate mental health care. This study seeksto examine the current mental health needs of Asian/Asian-American (AAA) Christians topromote future efforts in addressing the treatment gap. Participants (N=98) who identified asAAA Christians living in Los Angeles and Orange Counties were recruited using purposive andsnowball sampling. The needs assessment battery administered consisted of quantitative andqualitative questions that examined mental health needs, types of mental health service needed,and factors that impact mental health service seeking. Using a mixed-methods programevaluation approach, with the Pillar Integration Process, this study found there continues to existunmet mental health needs, with respondents indicating factors such as finances, lack ofinformation and time constraints as barriers toward seeking help. Participants indicated apreference toward receiving mental health care through individual therapy and psychoeducationworkshops. Recommendations and implications for responding to the unmet mental health needsin AAA Christian communities are discussed.
Reproducibility and transparency in interpretive corpus pragmatics
Authors: Schweinberger Martin , Haugh Michael
Published: October 2024

In this paper we extend the discussion about reproducibility in corpus linguistics from quantitative to qualitative corpus-based approaches and argue that concerns about reproducibility can be addressed in interpretive research paradigms like corpus pragmatics. We first suggest that in interpretive research traditions, transparency is more important than reproducibility. We then argue that interpretive research can be made more transparent and accessible by making use of notebooks to share their analytical procedures. We support these claims through a case study in which we analyse responses to information-seeking utterance-final ‘or’ questions in spoken Australian English data. We use a qualitative, discourse analytic approach to systematically examine these utterances from selected corpora. We show how corpus linguistic research can draw on existing infrastructures and tools for ensuring transparency, reproducibility, and replicability of interpretive analyses of the pragmatic functions of linguistic tokens in situated contexts.
Scattering matrix modeling of advanced photonic integrated resonators
Authors: Moss David
Published: October 2024

We propose a universal approach for modeling complex integrated photonic resonators based on the scattering matrix method. By dividing devices into basic elements including directional cou-plers and connecting waveguides, our approach can be used to model integrated photonic reso-nators with both unidirectional and bidirectional light propagation, with the simulated spectral response showing good agreement with experimental results. A simplified form of our ap-proach, which divides devices into several independent submodules such as microring resonators and Sagnac interferometers, is also introduced to streamline the calculation of spectral transfer functions. Finally, we discuss the deviations introduced by approximations in our modeling, along with strategies for improving modeling accuracy. Our approach is universal across dif-ferent integrated platforms, providing a useful tool for designing and optimizing integrated photonic devices with complex configurations.
Particulate matter PM2.5 concentrations in UK schools: a nationwide study into the influence of ambient PM2.5 and the resulting exposure potentials
Authors: Handy Alice , Wood Samuel , Roberts Katherine , Malley Christopher , Burridge Henry
Published: October 2024

This paper analyses the concentration of particulate matter PM2.5 from monitors deployed, by the Schools’ Air Quality Monitoring for Health and Education Initiative (SAMHE), to 490 schools across the United Kingdom throughout the academic year 2023—2024. The data shows that the PM2.5 concentration in schools is closely correlated to the ambient outdoor PM2.5 concentrations. Whilst the evidence gathered indicates that sources of PM2.5 within schools contribute to the concentrations, it is shown that outdoor sources are the dominant signature within the PM2.5 concentration measurements made indoors. Moreover, over the academic year, outdoor PM2.5 events — periods of elevated outdoor PM2.5 concentration — are shown to account for approximately 41% of the total potential exposure, whilst occurring on only around 13% of schooldays. These, and other findings presented herein, have important implications for school air quality and how air quality within schools, and beyond, is managed.
Revolutionary Enhanced Lane Departure Detection Techniques for Autonomous Vehicle Safety using ADAS
Authors: Sagar Vidya
Published: October 2024

This paper introduces an Enhanced Lane Departure Warning System (ELDWS) leveraging cutting-edge vision technology to boost road safety for ADAS enabled vehicles. Our novel approach utilizes a combination of Phase Stretch Transform for edge detection, Curved and Straight Lane Detectors for accurate lane Detection, and a modified Kalman Filter for dynamic lane tracking, collectively aimed at improving vehicle safety through precise lane departure estimation. Unlike traditional systems that rely heavily on clear lane markings and favorable environmental conditions, our model excels in various lighting and road scenarios, including curved paths and challenging weather conditions. The research demonstrates the system's efficacy in real-world simulations, where it outperforms existing technologies in detecting and alerting potential lane departures. Through meticulous integration of advanced image processing techniques and machine learning algorithms, our model offers a significant leap towards achieving robust lane-keeping assistance in autonomous and semi-autonomous vehicles. Furthermore, the paper discusses the system's ability to adapt to different environmental conditions and road types, making it a versatile tool for enhancing driving safety. By addressing the limitations of current LDWS technologies, such as sensitivity to weather conditions and the reliance on high-contrast lane markings, our approach sets a new standard for safety in the autonomous driving domain. This paper shows that by overcoming the problems of older lane departure warning systems, like their struggle with bad weather and dependency on clear road markings, our system sets a new standard for keeping cars safely within their lanes, especially in self-driving and semi-self-driving cars. We offer a detailed solution that combines new detection methods with advanced tracking techniques for better accuracy and reliability. The accuracy of our ELDWS is quantitatively measured using a custom dataset, revealing impressive results. During daytime conditions, our system achieved a high accuracy rate of 95.81%, correctly detecting lanes in 7665 out of 8000 frames. This demonstrates the system's robustness in optimal lighting conditions. The accuracy remains commendable in left and right departure scenarios during the day, with rates of 83.26% and 84.83%, respectively, showcasing the system's capability to recognize lane departures effectively. This research is important for making cars safer and provides useful information for developing better driving assistance systems in the future.
Scene consistency enhances state representations of real-world objects
Authors: Markov Yuri , Vo Melissa L.-H.
Published: October 2024

Previous research has shown that the context in which objects are located significantly influences how efficiently they are categorized. However, less is known about whether scene consistency can also affect the processing of finer object features, such as the state of an object (e.g., the angle of a swiss army knife or the fill level of a bottle). Therefore across three experiments, we presented a subset of the JURICS stimulus set, where each object exists in 20 continuously varying states (e.g., from fully closed to fully open) in scenes that were either contextually consistent or inconsistent. Participants were asked to report the specific state of the object using a continuous report task. Our results showed that scene consistency enhanced the precision of state judgments, i.e. participants made significantly larger errors in reporting object states when objects were presented in inconsistent compared to consistent scenes. These findings suggest that scene context exhibits its effect already on the fine-grained perceptual processing of objects, affecting not only object categorization but the accuracy of its perceived features.
Working Memory and Reinforcement Learning Interactions when Simultaneously Pursuing Reward and Avoiding Punishment: No Relationship to Internalizing Symptoms
Authors: Hitchcock Peter , Kim Joonhwa , Frank Michael
Published: October 2024

Humans learn adaptive behaviors via a durable but incremental reinforcement-learning (RL) system and a fast but fleeting working memory (WM) system. Past work parsing these systems focused on reward learning alone. Hence, little is known about how they interact while simultaneously learning to avoid punishment, and whether arbitrating between these demands is disrupted by psychiatric symptoms. We administered a novel reward/punishment RL-WM task to an online sample oversampled for depression and anxiety symptoms (N=298; n=275 after quality control). We found participants avoided punishment during initial learning, yet poorly retained this avoidance. Computational modeling captured this pattern by allowing the fleeting WM system to facilitate punishment avoidance, while the durable RL system retained little about punishment. We also found individual differences in a previously documented tendency for WM to blunt the RL system. Specifically, while we indeed found that a subset of high-blunting participants paradoxically showed the worst (RL-based) ultimate retention when WM had facilitated initial learning, another subset enjoyed the greatest ultimate retention in this scenario. Importantly, we found that the retention patterns in the task could not be captured by a computational model in which the RL system was replaced by a stimulus-response one. Finally, we found that task performance (analyzed behaviorally and via computational modeling) was largely spared as a function of depression/anxiety and trait rumination. Overall, our findings provide insight into how WM and RL interact when facing the ubiquitous challenge of attaining reward while simultaneously avoiding punishment, and demonstrate intact behavior under internalizing-disorder symptoms.
Performance Metrics in High-Speed Sports: Fundamentals, Examples & Analysis
Authors: Lappi Otto , Tuhkanen Samuel
Published: October 2024

Sports are in many ways ideal for an expert performance approach. The skills needed are rich and complex, yet displayed in tightly constrained tasks that can be isolated and simplified for experimental control and analysis. Well-defined goals enable objective and precise performance evaluation, and participants are already highly practiced on representative tasks from their domain, and motivated to perform well. Modern technology allows collection of large quantities of rich physiological and behavioral data, even in naturalistic settings. Indeed, the challenge often lies more in interpretation of the results and avoiding information overload, than the technical challenge of obtaining accurate measurements. Performance metrics that can summarize large quantities of data are therefore of both theoretical and applied interest; to the basic researcher they parametrize complex behavior into more elementary and interpretable components, to the practitioner they pinpoint aspects of technique to evaluate and improve. This paper discusses some foundational issues in the development of such metrics for high-speed sports, where human performance can be observed at the limit of physiological and information processing capacity. We first define high-speed sports, make a logical distinction between criterion differentiator and proxy metrics, and discuss identifying expert performance directly in terms of performance parameters. We then illustrate three general problems - and how to deal with them - using concrete examples from the openly available IMSRace data set:(1) Extreme events. How to deal with fat tailed performance distributions, a characteristic of high-speed sport even at the expert level? (2) Expert superiority. How good does one need to be, to be an "expert"? We suggest that a Magnitude Based (physical) rather than Deviation based (statistical) approach is to be preferred in high-speed sport.(3) Dissecting performance. How to find predictors for performance for individuals with vastly different levels of skill? We discuss distribution asymmetries and ceiling effects.The topic is of interest to experimental researchers on high-speed sports expertise, and expertise in related fields. Coaches, performance engineers and other practitioners may also gain insights from a more fundamental approach to performance data and its analysis.
Are GWAS Confidence Intervals Misleading?
Authors: Bronski Joseph
Published: October 2024

There are 3 billion base pairs in the human genome. Current GWAS sample sizes are in thelow 6 figures. This does not provide enough statistical power to rule out high h2SNP given that the variance of any of the 3 billion base pairs could be above 0. Yet h2SNP estimates in underpowered studies are often represented as evidence of a probabilistic upper bound which is far lower thanwhat can be established.
My Body, My Choice? Examining the Distinct Profiles Underlying Attitudes Toward Abortion and COVID-19 Mandates
Authors: Osborne Danny , Bahamondes Joaquín , Clarke Eden V. , Cone Deborah Hill , Lilly Kieren J. , Lizzio-Wilson Morgana , Pichardo Eduardo Rivera , Satherley Nicole , Simionato Natalia M. , Thomas Emma F , Zubielevitch Elena , Sibley Chris G
Published: October 2024

Protestors recently repurposed the abortion rights’ mantra, “my body, my choice,” to oppose COVID-19 mandates. But do those who oppose public health mandates fully support the right to choose? We answer this question by using exploratory analyses to identify the unique response patterns underlying support for abortion and COVID-19 mandates in random samples from the United States (Study 1; N = 2,331) and New Zealand (Study 2; N = 33,310). Latent profile analyses revealed a small subgroup in both countries (12.6% and 3.4% of the respective samples) who opposed mandates. Yet contrary to the “my body, my choice” rhetoric seen at anti-mandate protests, they also opposed abortion. Across both studies, those in the Anti-Mandate profile tended to be more religious, conservative, and distrustful of institutions. In Study 2, they were also low on cognitive consistency and high on conspiracy belief. Finally, the Anti-Mandate profile was opposed to free speech critical of both the United States and religion (Study 1), high on sexual prejudice (both studies), unsupportive of progressive protests (but supportive of reactionary protests; Study 2), and likely to vote for conservative parties (both studies). These results reveal the mobilization potential of the anti-mandate movement, uncover important contradictions within its members, and illustrate the nuanced ways in which opposition to gender policies (i.e., reproductive rights) coalesce with reactionary protests.
How agency shapes social preferences: Using mouse-tracking to reveal changes in cognitive conflict
Authors: Marciano Deborah , Setman-Shachar Shai , Choshen-Hillel Shoham , Perry Anat
Published: October 2024

Inequity aversion is a fundamental social preference. Concern for others’ welfare is yet another fundamental social preference. What do people prefer when maximizing others’ welfare creates an inequality that disadvantages them? Prior research has shown that people’s preferences depend on their level of agency, that is, their control over the allocation. Behaviorally, agentic decision makers have been shown to be more likely to prefer allocations that give another person more than them, compared to non-agentic ones. However, the cognitive processes underlying this shift of preference remain unclear. Here, we used mouse-tracking and reaction times to investigate how agency shapes social preferences in such cases. We examined decision conflict, the level of conflict experienced in arriving at a given choice, as a way to uncover whether different underlying social preferences are at play when one has versus does not have agency. We predicted an interaction effect of agency and choice on conflict, where choosing the prosocial option would be associated with less conflict in the Agency condition compared to the No-Agency condition, and that the opposite would be true for the equitable option. In our task, on each of trial, participants were presented with two allocation options: an equitable option (e.g., 50 cents for self, 50 cents for other) and an inequitable and prosocial option, favoring the other participant over oneself (e.g., 50 cents for self, 70 cents for other). Agentic participants chose one option to be implemented, whereas non-agentic participants indicated their preference, knowing that the lab manager had already made the decision. In two studies (N = 586), including a preregistered one, an interaction effect emerged in both mouse trajectory and reaction time analyses. These results suggest that agency alters social preferences during the decision-making process, and challenge traditional inequity aversion models claiming that people inherently dislike inequitable outcomes. Granting agency may be a powerful tool for maximizing social welfare in situations where equity and prosocial behavior are at odds.
Cambios poblacionales en el Perú del siglo XXI y repercusiones en la salud sexual y reproductiva
Authors: Távara Orozco Luis
Published: October 2024

La Academia Nacional de Medicina recientemente convocó un Simpo-sio sobre ‘Cambios Poblacionales en el Mundo y en el Perú: su impacto en Salud Pública’, en el cual participaron dos colegas médicos expertos peruanos en demografía y cuatro panelistas, entre los cuales estuvo el autor de este editorial.
Оценка изменения баланса углерода Ярославской области в результате трансформации землепользования
Authors:   Lomonosov Moscow State University, Bancheva A.I. , Alekseeva N.N. , Tretyachenko D.A. , Grinfeldt Yu.S.
Published: October 2024

Трансформация форм землепользования – важный фактор, который необходимо учитывать в оценках выбросов углекислого газа, при этом количественные оценки изменений потоков и запасов углерода в секторе «Землепользование, изменения землепользования и лесное хозяйство» в значительной степени менее достоверны, чем оценки выбросов от стационарных источников и транспорта. Цель работы – апробация методики региональной оценки запасов углерода экосистем и их изменений в связи с трансформацией землепользования/наземного покрова (на примере Ярославской области). Использовались общедоступные пространственные данные о наземном покрове Европейского космического агентства и литературные данные по плотности углерода в основных резервуарах наземных экосистем. Расчеты проводились в программах InVEST, ArcGIS, MS Excel. Установлено, что в 2019 г. общие запасы углерода в экосистемах Ярославской области составили около 337.4 млн тонн. Около 73% общих запасов углерода аккумулировано в лесных экосистемах, в пашнях, пастбищах и лугах – около 20%, в болотах – 5%. Динамика запасов за период 1992-2019 гг. положительная, что объясняется увеличением площадей залесенных и заболоченных территорий. В целом, за 1992–2019 гг. изменения в наземном покрове затронули 6.8% территории области, что привело к росту запасов углерода в наземных экосистемах на 5.66 млн тонн. Тенденции изменения землепользования и динамики запасов углерода в разных классах наземного покрова/типах экосистем могут учитываться при разработке рекомендаций на уровне регионов по управлению экосистемами для сокращения выбросов и увеличения поглощения углекислого газа.