Analysis Of Behavior Research Articles

Analytical modeling and experiments on soft soil consolidation with vacuum preloading‐airbag pressurization

AbstractThis study aims to provide substantial theoretical support for employing vacuum preloading‐airbag pressurization (VP‐AP) to enhance soft soil foundations. By integrating the airbags and prefabricated vertical drains (PVDs) within the analytical framework, the consolidation models are developed to accommodate double smear zones and well resistance. Analytical solutions for various airbag pressurization scenarios are derived under the equal‐strain assumption. A model test is subsequently conducted to investigate the settlement process of soft soil using the VP‐AP method. The validity of the proposed theoretical model is corroborated through comparison with existing analytical solutions and experimental data. The accuracy of the predictive model is further substantiated by the model test results. Lastly, this research offers an in‐depth analysis of soil consolidation behavior under diverse influencing factors. The findings indicate that the VP‐AP method demonstrates superior efficacy over conventional vacuum‐surcharge preloading when the airbag pressure matches the external load pressure. Additionally, an increase in the radius of airbags enhances the soil consolidation efficiency. The analytical model presented in this study elucidates the consolidation mechanisms of the VP‐AP method, with experimental research confirming the efficacy of this approach and the predictive model established herein.

Retraction Note: Toward a novel method to support decision-making process in health and behavioral factors analysis for the composition of IT projects teams

Retraction Note: Toward a novel method to support decision-making process in health and behavioral factors analysis for the composition of IT projects teams

Gamma-Irradiated Gum Arabic Grafted with 2-Hydroxyethyl Methacrylate: A Novel Superabsorbent Polymer for Controlled Folic Acid Release.

This study explores the synthesis and characterization of superabsorbent hydrogels derived from chemically modified gum Arabic, designed for controlled folic acid release. The synthesis involves a two-step process: carboxymethylation followed by grafting with 2-hydroxyethyl methacrylate via gamma irradiation. The resulting hydrogels exhibit enhanced mechanical strength and controlled diffusivity, essential for nutrient delivery systems. Key factors such as copolymer composition and irradiation dose are investigated, affecting the synthesis process. Systematic studies of swelling behaviors reveal that the hydrogel achieves a maximum swelling of 888.1% at 40°C. The hydrogels are loaded with folic acid, and in vitro, sustained release profiles are examined under various pH conditions. The maximum release of 83.3% is observed after 24h at pH 7.0, following a Korsmeyer-Peppas release mechanism. Different characterization techniques, confirm the successful synthesis and unique properties of the superabsorbent hydrogels. Rheological behavior analysis, scanning electron microscopy, and biocompatibility assessments provide a comprehensive understanding of the hydrogel structures. Gamma irradiation ensures a homogeneous network structure, crucial for optimal swelling behavior and mechanical properties. This research highlights the potential of eco-friendly biopolymer hydrogels in precise drug delivery applications, leveraging the safety and process control benefits of gamma irradiation.

An analysis of turn-taking behaviors of Japanese learners of English in videoconferencing discussions

To successfully interact in a new language, learners must effectively take turns and manage the floor. Expectations and rules for turn-taking can differ between languages, making this more than a question of grammatical proficiency and vocabulary acquisition. In addition, the increased use of videoconferencing software in education and beyond makes learning to manage the floor in virtual spaces a useful skill for everyone, including language learners. To analyze the turn-taking behaviors of first language (L1) speakers of Japanese using English in videoconferencing interactions, three classes of first-year university students with intermediate level English skills were selected to have their in-class videoconferencing discussions recorded. Three of the recorded discussions were selected and analyzed to identify turn-taking behaviors and to analyze the techniques that influenced the speakers’ ability to succeed. Participants were observed to leave long gaps between speakers at turn transitions and rarely extended discussion topics to include multiple turns per speaker. There were three behaviors that were observed that helped some participants to reduce the gap between speakers. Clearly marking the end of a turn, energetic use of verbal backchannels, and comfort with unintentional overlap all seemed to be correlated with improved transition speed. Increased use of questions did lead to some topics being discussed beyond a single turn per speaker, but the difference was relatively small.

El análisis psicológico del Derecho en la regulación jurídica. El sandbox español de inteligencia artificial”.

The close collaboration between Psychology and Law has contributed to the enrichment of the legislative technique. The application of psychological behavioural analysis to law breaks the current paradigm and offers a unique perspective for lawmaking through the study of people's behaviour in the face of laws. Legal experimentation, an innovative practice, emerges as a crucial tool for law-making and regulatory impact assessment in novel areas whose subject matter may be potentially burdensome to individual rights and freedoms. In the context of the Spanish artificial intelligence sandbox, the application of psychology to law is of particular importance, as it contributes to the emerging and much-needed legal regulation. This cooperation between doctrines promises not only to boost normative evolution, but also to ensure a more effective and protective regulation in a world increasingly influenced by technology.

RpTrack: Robust Pig Tracking with Irregular Movement Processing and Behavioral Statistics

Pig behavioral analysis based on multi-object tracking (MOT) technology of surveillance videos is vital for precision livestock farming. To address the challenges posed by uneven lighting scenes and irregular pig movements in the MOT task, we proposed a pig MOT method named RpTrack. Firstly, RpTrack addresses the issue of lost tracking caused by irregular pig movements by using an appropriate Kalman Filter and improved trajectory management. Then, RpTrack utilizes BIoU for the second matching strategy to alleviate the influence of missed detections on the tracking performance. Finally, the method utilizes post-processing on the tracking results to generate behavioral statistics and activity trajectories for each pig. The experimental results under conditions of uneven lighting and irregular pig movements show that RpTrack significantly outperforms four other state-of-the-art MOT methods, including SORT, OC-SORT, ByteTrack, and Bot-SORT, on both public and private datasets. The experimental results demonstrate that RpTrack not only has the best tracking performance but also has high-speed processing capabilities. In conclusion, RpTrack effectively addresses the challenges of uneven scene lighting and irregular pig movements, enabling accurate pig tracking and monitoring of different behaviors, such as eating, standing, and lying. This research supports the advancement and application of intelligent pig farming.

Deep learning and explainable artificial intelligence for investigating dental professionals' satisfaction with CAD software performance.

This study aimed to examine the satisfaction of dental professionals, including dental students, dentists, and dental technicians, with computer-aided design (CAD) software performance using deep learning (DL) and explainable artificial intelligence (XAI)-based behavioral analysis concepts. This study involved 436 dental professionals with diverse CAD experiences to assess their satisfaction with various dental CAD software programs. Through exploratory factor analysis, latent factors affecting user satisfaction were extracted from the observed variables. A multilayer perceptron artificial neural network (MLP-ANN) model was developed along with permutation feature importance analysis (PFIA) and the Shapley additive explanation (Shapley) method to gain XAI-based insights into individual factors' significance and contributions. The MLP-ANN model outperformed a standard logistic linear regression model, demonstrating high accuracy (95%), precision (84%), and recall rates (84%) in capturing complex psychological problems related to human attitudes. PFIA revealed that design adjustability was the most important factor impacting dental CAD software users' satisfaction. XAI analysis highlighted the positive impacts of features supporting the finish line and crown design, while the number of design steps and installation time had negative impacts. Notably, finish-line design-related features and the number of design steps emerged as the most significant factors. This study sheds light on the factors influencing dental professionals' decisions in using and selecting CAD software. This approach can serve as a proof-of-concept for applying DL-XAI-based behavioral analysis in dentistry and medicine, facilitating informed software selection and development.

Pharmacological investigation of genistein for its therapeutic potential against nitroglycerin-induced migraine headache.

Migraine, typically occurs on one side of the head, lasts for hours to days. Trigemino-vascular system (TVS) plays a vital role in pain generation, with neurogenic inflammation and oxidative stress playing key roles in its pathophysiology. This study aimed to investigate genistein's potential as anti-inflammatory and anti-oxidant agent in mitigating migraine pain. Genistein (20 and 50mg/kg) was administered intraperitoneally (IP) to nitroglycerin (NTG; 10mg/kg)-induced migraine model in rats. Behavioral analysis, antioxidant assay, immunohistochemistry (IHC), histopathological examination, ELISA, and RT-PCR were conducted to evaluate the antimigraine potential of genistein. In-silico analysis showed genestien's ACE values of -4.8 to -9.2 Kcal/mol against selected protein targets. Genistein significantly reversed mechanical and thermal nociception, light phobicity, and head scratching; increased the intensities of GST, GSH, catalase; and down regulated lipid peroxidase (LPO) in cortex and trigeminal nucleus caudalis (TNC). It also reduced Nrf2, NF-kB, and IL6 expression, analyzed through IHC, improved histopathological features, and increased COX-2 and decreased PPAR-γ expressions, while RT-PCR analysis revealed increased PPAR-γ expressions in genistein-treated rats. Genistein exhibited potent antioxidant and anti-inflammatory properties in migraine treatment, acting through multifactorial mechanisms by modulating the expression of numerous proteins in the region cortex and TNC.

Well done! Or how to Avoid Dangers of Pseudoscience: Common Standard for Research in Behavioural Analysis and Deception Detection in Aviation Security

Well done! Or how to Avoid Dangers of Pseudoscience: Common Standard for Research in Behavioural Analysis and Deception Detection in Aviation Security

The Role of Artificial Intelligence in Targeted Advertising and Analysis of Consumer Behavior

The Role of Artificial Intelligence in Targeted Advertising and Analysis of Consumer Behavior

Telemetry without collars: performance of fur- and ear-mounted satellite tags for evaluating the movement and behaviour of polar bears

The study of animal movement provides insights into underlying ecological processes and informs analyses of behaviour and resource use, which have implications for species management and conservation. The tools used to study animal movement have evolved over the past decades, allowing for data collection from a variety of species, including those living in remote environments. Satellite-linked radio and GPS collars have been used to study polar bear (Ursus maritimus) ecology and movements throughout the circumpolar Arctic for over 50 years. However, due to morphology and growth constraints, only adult female polar bears can be reliably collared. Collars have proven to be safe, but there has been opposition to their use, resulting in a deficiency in data across much of the species’ range. To bolster knowledge of movement characteristics and behaviours for polar bears other than adult females, while also providing an alternative to collars, we tested the use of fur- and ear-mounted telemetry tags that can be affixed to polar bears of any sex and age. We tested three fur tag designs (SeaTrkr, tribrush and pentagon tags), which we affixed to 15 adult and 1 subadult male polar bears along the coast of Hudson Bay during August–September 2021–2022. Fur tags were compared with ear tags deployed on 42 subadult and adult male polar bears captured on the coast or the sea ice between 2016 and 2022. We used data from the tags to quantify the amount of time subadult and adult males spent resting versus traveling while on land. Our results show the three fur tag designs remained functional for shorter mean durations (SeaTrkr = 58 days; tribrush = 47 days; pentagon = 22 days) than ear tags (121 days), but positional error estimates were comparable among the Argos-equipped tags. The GPS/Iridium-equipped SeaTrkr fur tags provided higher resolution and more frequent location data. Combined, the tags provided sufficient data to model different behavioural states. Furthermore, as hypothesized, subadult and adult male polar bears spent the majority of their time resting while on land, increasing time spent traveling as temperatures cooled. Fur tags show promise as a short-term means of collecting movement data from free-ranging polar bears.

Implementation of Cognitive Behavioral Therapy in a Child with Obsessive - Compulsive Disorder: A Case Study

Obsessive-Compulsive Disorder (OCD) is a prevalent child and adolescent psychiatric condition characterized by substantial functional impairments. Cognitive Behavioral Therapy (CBT) has emerged as the primary therapeutic approach for managing mild to moderate cases of OCD in children and adolescents. Significant advancements have been made in applying CBT specifically to this age group in the past decade. Exposure and response prevention (ERP) is a core therapeutic technique grounded in the principle that anxiety tends to diminish through repeated exposure to anxiety-inducing stimuli, leading to a gradual reduction in anxiety response. In the present study, we present the case of a 9-year-old boy with OCD who was treated with CBT. Τhe evaluation of this case highlights the necessity for rigorous behavior analysis to precisely implement exposure therapy and the significance of multidisciplinary intervention in the child's daily life. In the discussion that follows the analysis of the case, parameters such as the differentiation of ERP in children compared to adults, the control of OCD over the rest of the family members and the OCD phenomenology of parents have been discussed. Additionally, the effect of the patient's comorbidity on the treatment outcome and his compliance with homework were also addressed.

The corrosion inhibition performance and mechanism of α-benzoin oxime on copper: A comprehensive study of experiments and DFT calculations

Copper corrosion poses a significant challenge to process stability and chip quality in the field of integrated circuit manufacturing. This study comprehensively explored the corrosion inhibition performance of α-benzoin oxime (bzoxH2) on copper, by employing a combination of experimental methods and computational chemistry. First, after the addition of 0.1 mM bzoxH2, the static etching rate and surface roughness of copper were decreased to 7 Å·min−1 and 1.36 nm, respectively, which indicated that bzoxH2 could reduce the corrosion rate of copper and improve its surface quality. Subsequently, electrochemical behavior analysis showed that the addition of 0.1 mM bzoxH2 resulted in an increase in open circuit potential to 0.185 V, a decrease in corrosion current density to 2.33 µA·cm−2, an increase in polarization resistance to 10589 Ω·cm2, and a high corrosion inhibition efficiency of 96.88 %, suggesting that bzoxH2 significantly enhances the corrosion resistance of copper. Furthermore, studies based on adsorption isotherm models indicated that the adsorption behavior of bzoxH2 on the copper surface formed a dense passivation film through the combination of physical and chemical adsorption mechanisms. This effectively enhanced the corrosion resistance of copper and provided robust protection against corrosion. Finally, the use of X-ray photoelectron spectroscopy technology, along with an in-depth exploration of the geometric structure and chemical reactivity of the bzoxH2 molecule, revealed its complex interaction with specific active sites on the copper surface. These findings provided valuable theoretical insights, along with practical guidance for the development of metal corrosion inhibitors.

Teaching compassionate-based behaviors across communication partners to students of applied behavior analysis: a preliminary investigation of comparative effectiveness

Applied behavior analysis (ABA) focuses on providing socially significant treatments and practices. Recent advancements in ethically-minded research have encouraged practitioners to think beyond the technical skills required for implementing behavior-analytic practices and consider how these practices are delivered. Compassionate care in ABA has recently been conceptually defined and subsequently researched to explore ways to explicitly and systematically teach compassionate-care-based skills within the scope of ABA. Researchers have noted barriers specific to the time required to teach compassionate-care-based skills using behavior skills training (BST) especially when working to train groups in compassionate care skills. Further, these studies have focused primarily on using compassionate care towards interactions with caregivers as communication partners. This study operationalized the compassionate care-based skill of receiving feedback within a behavioral analytic lens and taught it to eight master's students enrolled in an ABA course. An experimental case study approach was used to evaluate the relative benefit of modified behavioral skills training (BST) versions, including conditions with and without rehearsal opportunities and individualized performance feedback. Results indicated that all participants demonstrated significant skill increases across multiple communication partners (i.e., client, caregiver, colleague) compared to baseline sessions, with conditions including opportunities for rehearsal and performance feedback resulting in higher skill acquisition for seven of the eight participants. Conditions that required the participants to generalize to novel scenarios and novel communication partners resulted in lower competencies; however, all participant skills across all communication partners remained higher than baseline measures. Limitations included practicing skills within role-play scenarios only, the application of compassionate care-based skills in a variety of cultures, and limits related to using an experimental case study as a methodological approach. Implications for future research and practitioner-based applications are discussed.

Unleashing employee potential: The effects of customer-empowering behaviors on job crafting in hospitality industries

Drawing upon an extensive analysis of customer-empowering behaviors (CEBs) research, this study strives to better understand the impacts of perceiving such authorization among service employees in hospitality industries. Employing a multi-wave questionnaire and a scenario-based experiment, we unveil three key findings: First, CEBs significantly influence service employees’ job crafting. Second, self-efficacy in service delivery serves as a mediator between CEBs and job crafting. Third, the unit’s climate of concern for customers not only moderates the association between CEBs and employees’ self-efficacy in service delivery, but also shapes how these behaviors indirectly affect job crafting. This research contributes to the existing literature on empowerment in service encounters and offers significant practical value to service enterprises.

What is the structure of a Challenge Based Learning project? A shortitudinal trajectory analysis of student process behaviours in an interdisciplinary engineering course

ABSTRACT Challenge Based Learning (CBL) is an educational approach that has gained popularity in response to the need for authentic learning environments. While the CBL literature is predominantly focused on cases of pedagogical implementations, the actual processes by which students develop CBL projects remain under-investigated. This shortitudinal study seeks to examine the phases of CBL project development and associated process behaviours at group level, as they unfold. The participants are 6 interdisciplinary student groups totalling 22 students enrolled in a first-year course on ethics and data analytics. Data was collected weekly throughout 10 weeks via reflective diaries (n = 15 students) and observation of course sessions (n = 22) and is complemented by interviews after course completion (n = 15). The data was subject to a thematic trajectory analysis. The study identifies 7 distinct phases in the temporal structure of a CBL project: gaining client know-how, articulating a problem, mapping the problem context, setting the aim, proposing an action path, testing and evaluating it, and implementing the solution. The article concludes with recommendations for further research into CBL project development processes, which may support the growing adoption of real-life interdisciplinary projects in engineering education.

Toward Trustworthy Automated Driving through Qualitative Scene Understanding and Explanations

<div>Understanding driving scenes and communicating automated vehicle decisions are key requirements for trustworthy automated driving. In this article, we introduce the qualitative explainable graph (QXG), which is a unified symbolic and qualitative representation for scene understanding in urban mobility. The QXG enables interpreting an automated vehicle’s environment using sensor data and machine learning models. It utilizes spatiotemporal graphs and qualitative constraints to extract scene semantics from raw sensor inputs, such as LiDAR and camera data, offering an interpretable scene model. A QXG can be incrementally constructed in real-time, making it a versatile tool for in-vehicle explanations across various sensor types. Our research showcases the potential of QXG, particularly in the context of automated driving, where it can rationalize decisions by linking the graph with observed actions. These explanations can serve diverse purposes, from informing passengers and alerting vulnerable road users to enabling post hoc analysis of prior behaviors.</div>

The Utility of a Novel Neuropsychological Measurement to Analyze Event-Related Attentional Behaviors among Young Children with Attention Deficit Hyperactivity Disorder-a Pilot Study.

The identification and diagnosis of children with attention deficit hyperactivity disorder (ADHD) traits is challenging during the preschool stage. Neuropsychological measures may be useful in early assessments. Furthermore, analysis of event-related behavior appears to be an unmet need for clinical treatment planning. Conners' Kiddie Continuous Performance Test (K-CPT) is the most popular well-established neuropsychological measurement but lacks event markers to clarify the heterogeneous behaviors among children. This study utilized a novel commercially available neuropsychological measure, the ΣCOG, which was more game-like and provided definite event markers of individual trial in the test. Thirty-three older preschool children (14 were diagnosed with ADHD, mean age: 66.21 ± 5.48months; 19 demonstrated typical development, mean age: 61.16 ± 8.11months) were enrolled and underwent comprehensive medical and developmental evaluations. All participants underwent 2 versions of neuropsychological measures, including the K-CPT, Second Edition (K-CPT 2) and the ΣCOG, within a short interval. The study indicated the omissions and response time scores measured in this novel system correlated with clinical measurement of the behavioral scales in all participants and in the group with ADHD; additionally, associations with the traditional K-CPT 2 were observed in commissions and response time scores. Furthermore, this system provided a within-task behavioral analysis that identified the group differences in the specific trial regarding omission and commission errors. This innovative system is clinically feasible and can be further used as an alternative to the K-CPT 2 especially in research by revealing within-task event-related information analysis.

Regulation of MicroRNAs After Spinal Cord Injury in Adult Zebrafish.

Spinal cord injury (SCI) is a central nerve injury that often leads to loss of motor and sensory functions at or below the level of the injury. Zebrafish have a strong ability to repair after SCI, but the role of microRNAs (miRNAs) after SCI remains unclear. Locomotor behavior analysis showed that adult zebrafish recovered about 30% of their motor ability at 2 weeks and 55% at 3 weeks after SCI, reflecting their strong ability to repair SCI. Through miRNA sequencing, mRNA sequencing, RT-qPCR experiment verification, and bioinformatics predictive analysis, the key miRNAs and related genes in the repair of SCI were screened. A total of 38 miRNAs were significantly different, the top ten miRNAs were verified by RT-qPCR. The prediction target genes were verified by the mRNAs sequencing results at the same time point. Finally, 182 target genes were identified as likely to be networked regulated by the 38 different miRNAs. GO and KEGG enrichment analysis found that miRNAs targeted gene regulation of many key pathways, such as membrane tissue transport, ribosome function, lipid binding, and peroxidase activity. The PPI network analysis showed that miRNAs were involved in SCI repair through complex network regulation, among which dre-miR-21 may enhance cell reversibility through nop56, and that dre-miR-125c regulates axon growth through kpnb1 to repair SCI.

Interplay of Fogponics and Artificial Intelligence for Potential Application in Controlled Space Farming

Most studies in astrobotany employ soil as the primary crop-growing medium, which is being researched and innovated. However, utilizing soil for planting in microgravity conditions may be impractical due to its weight, the issue of particles suspended in microgravity, and its propensity to harbor pathogenic microorganisms that pose health risks. Hence, soilless irrigation and fertigation systems such as fogponics possess a high potential for space farming. Fogponics is a promising variation of aeroponics, which involves the delivery of nutrient-rich water as a fine fog to plant roots. However, evaluating the strengths and weaknesses of fogponics compared to other soilless cultivation methods is essential. Additionally, optimizing fogponics systems for effective crop cultivation in microgravity environments is crucial. This study investigated the interaction of fogponics and artificial intelligence for crop cultivation in microgravity environments, aiming to replace soil-based methods, filling a significant research gap as the first comprehensive examination of this interplay in the literature. A comparative assessment of soilless fertigation and irrigation techniques to identify strengths and weaknesses was conducted, providing an overview through a literature review. This highlights key concepts, methodologies, and findings, emphasizing fogponics’ relevance in space exploration and identifying gaps in current understanding. Insights suggest that developing adaptive fogponics systems for microgravity faces challenges due to uncharacterized fog behavior and optimization complexities without gravity. Fogponics shows promise for sustainable space agriculture, yet it lags in technological integration compared with hydroponics and aeroponics. Future research should focus on microgravity fog behavior analysis, the development of an effective and optimized space mission-compatible fogponics system, and system improvements such as an electronic nose for an adaptive system fog chemical composition. This study recommends integrating advanced technologies like AI-driven closed-loop systems to advance fogponics applications in space farming.