bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of teachers’ teaching strategies on students’ learning engagement: moderated mediation model
Authors: Zhang Heping , Yang Junjie , Liu Zhiyuan
Published: December 2024

Introduction

This study explores the nuanced relationship between teachers’ teaching strategies and students’ learning engagement within online environments, considering the mediation by students’ perceptions of teachers’ emotional engagement and the moderation by teachers’ expectations.

Methods

Employing a stratified sampling technique, data were collected from 1,200 Chinese primary and secondary students through the “Survey on Online Learning Engagement.” Structural equation modeling was applied to analyze the relationships among teaching strategies, emotional engagement, teachers’ expectations, and learning engagement.

Results

The study found that teachers’ teaching strategies not only directly affect students’ learning engagement (r = 0.377***, p < 0.001), but also indirectly affect students’ learning engagement through students’ perception of teachers’ emotional engagement. It showed a significant mediating effect (indirect effect = 0.231***, p < 0.001). Additionally, teachers’ expectations exhibit a notable moderating effect on the relationship between perceived emotional engagement and learning engagement (β = 0.073***, p < 0.001). In other words, in addition to teachers’ teaching strategies, teachers’ emotional involvement and students’ perception of teachers’ emotional involvement are important factors affecting students’ learning involvement. This means that in online classroom teaching, the emotional transmission and experience between teachers and students play a role in the connection.

Discussion

The study highlights the critical role of emotional connection in educational strategies, suggesting that teachers should focus on fostering emotional engagement alongside academic content. Balanced teacher expectations are recommended to facilitate a supportive learning environment that encourages higher levels of student engagement. Educators are advised to integrate emotional warmth and responsiveness into their teaching methods and to maintain realistic expectations to promote optimal learning outcomes.
Association of metalloestrogens exposure with depression in women across reproductive lifespan
Authors: Ren Junjie , Wu Wanxin , Li Jia , Hu Qifang , Zhang Mi , Wang Jing , Li Xiaoming , Li Yanwen , Huang Binbin
Published: December 2024

Background

Exposure to metal could impact women’s depression risk. However, the connection and mechanisms between metalloestrogens exposure and depression are still not fully understood. We aim to explore the associations between metalloestrogens and the risk of depression in women across reproductive lifespan.

Methods

Using data from NHANES 2011-2018, we employed logistic regression and baknernel machine regression (BKMR) to study links between metalloestrogen exposure and depression in US women. We analyzed how contraceptive use affects this relationship.

Results

The study involved 3,374 adult women, with 345 of them experiencing depression. Our research revealed that certain metalloestrogens like Ba, Ca, Pb, Sb, and Sn were linked to higher depression risk in women, while Hg was associated with lower depression risk in older women. For women aged 18-44, a blend of metalloestrogens showed a significant positive correlation with depression risk, and the likelihood of depression in later years notably rose when the metal mixture concentration reached or exceeded the 60th percentile. Oral contraceptives would have an effect on the impact of metalloestrogen mixture exposure on depression in women during the reproductive stage.

Conclusions

Our study indicates a significant link between metalloestrogen exposure and a higher risk of depression in adult women in the United States. This finding can aid in identifying the connection and enhancing women’s mental well-being.
Neuropeptide Y in first-episode schizophrenia: is there any sex differences in the pathogeneses of schizophrenia?
Authors: Song Jia-Qi , Xin Wen , Yu Jian-Jin , Zhao Qing , Li Hong-Na , Chen Da-Chun
Published: December 2024

Objective

This study investigated relationships between Neuropeptide Y levels and severity of psychiatric symptoms in first-episode schizophrenia patients, and explore the sexual heterogeneity in them.

Methods

We recruited 115 first-episode schizophrenia patients and 58 matched healthy controls, and measured serum Neuropeptide Y levels of them at baseline and again after 10 weeks of risperidone treatment in patient group. Patients were also evaluated with the Positive and Negative Symptoms Scale (PANSS) to reveal the severity of symptoms.

Results

95 patients completed the whole experiment. We find that mean Neuropeptide Y levels at baseline were significantly higher in patients than in controls (p<0.001), no matter in males or females. In males, there are positive correlations between Neuropeptide Y levels and PANSS scores at baseline (p<0.01), and between the change of them (p<0.05). However, we do not find these correlations in female patients. Furthermore, the interaction terms of NPY × sex were highly significant taking PANSS as dependent variable(p<0.001).

Conclusion

Neuropeptide Y plays a significant role in the pathogenesis of schizophrenia. In male patients, Neuropeptide Y is positively correlated with the severity of symptoms, while this correlation is not found in females. Continued efforts are needed to determine the sexual dimorphism in pathogeneses of schizophrenia.
Nothing about us without us! How users configure clinical treatment in Italian residential communities: ethnography of therapeutic engagement
Authors: Iudici Antonio , Berardelli Tobia , Fenini Davide , Neri Jessica , Subissi Emiliano
Published: December 2024

The effectiveness of the interventions in the Therapeutic communities (TC) depends not only on the quality of the specialized knowledge and methodologies adopted, but also on the meanings consumers give to them. Building the therapeutic alliance is a key element in reducing high drop-out rates and predicting more favorable outcomes. This research investigated the discourses practiced by 45 people with substance use disorders who had been accessing a therapeutic community for less than 15 days, with the aim of delving into the meanings given to treatment and pathway goals in the service, to analyze what theories are used to explain consumption and therapeutic change. The study made use of Discourse analysis (DA) and Positional theory with a protocol of written open-ended questions. The results show how participants configure the community pathway adopting a passive role, underestimating the need to co-participate in treatment design and bringing in poorly formalized goals. The collected texts provide a better understanding of the perspective of community users, emphasizing the need to share spaces of co-design from the very beginning in order to promote empowering, reasoning about the implications of the various discourses produced by consumers to explain their autobiography and to envision paths of change.
Model-based approach for specifying requirements of virtual reality software products
Authors: Karre Sai Anirudh , Reddy Y. Raghu
Published: December 2024

Introduction

Gathering requirements for developing virtual reality (VR) software products is a labor-intensive process. It requires detailed elicitation of scene flow, articles in the scene, action responses, custom behaviors, and timeline of events. The slightest change in requirements will escalate the design and development costs. While most VR practitioners depend on conventional software engineering (SE) requirement-gathering techniques, there is a need for novel methods to streamline VR software development. With severe software platform fragmentation and hardware volatility, VR practitioners need assistance specifying non-volatile requirements for a minimum viable VR software product.

Methods

To address this gap, we present virtual reality requirement specification tool (VReqST), a model-based requirement specification tool for developing virtual reality software products.

Results

Using VReqST, requirement analysts can specify the requirements for both simple and complex multi-scene VR software products and virtual environments (VEs).

Discussion

VReqST is customizable and competent in illustrating custom requirements for new locomotion, colocation, teleportation algorithms, etc. We worked with the VR community from the industry for adoption and feedback. We revised and included the desired features based on inputs from the VR community and gathered their observations on the overall impact of VReqST in practice.
The current physical activity in persons with disability in Qatar: a cross-sectional study
Authors: Pandiyan Uma , Kariyathankavil Ibin , Rebbouh Abderrahmane , EP Grami Leila Khairallah , Thomas Asha Susan , Sathian Brijesh
Published: December 2024

Purpose

The primary objective of this study was to measure and quantify the current level of physical activity among persons with disability in Qatar. The secondary objective was to assess and analyze the duration of sedentary behavior among individuals with disability in Qatar.

Methods

This was a cross-sectional epidemiological study of persons with disability living in Qatar. The study period was from October 2020 to December 2021

Results

96 persons with disabilities participated in this study. They included individuals with amputations, spinal cord injuries, cerebral palsy, and other developmental impairments. Of the respondents, 56% were male and 64% were Qataris. Of the respondents, 61.5%said that they felt psychologically and emotionally better when engaging in physical activity, and this difference was statistically significant. 71% of all those who reported feeling physically good after sport, 65% said that they enjoyed the social aspects of sports. This corroborates the beneficial effects of exercise, sports, and physical activity in persons with all types of disabilities.

Conclusion

There was a definite impact on the emotional and physical well-being of those who participated in the physical activities. There was less participation in team activities and two-thirds preferred to exercise alone. However, their numbers were not statistically significant because of low enrollment in the study.
Does farm mechanization improve farm performance and ensure food availability at household level? Empirical evidence from Pakistan
Authors: Yasar Hassan , Raza Muhammad Haseeb , Faisal Muhammad , Nadeem Nasir , Khan Nawab , Kassem Hazem S. , Elhindi Khalid M. , Mahmood Sammina
Published: December 2024

Agriculture has a significant role in the wellbeing of the rural households of developing countries. Still, its productivity is very low in these countries due to the low use of mechanization at the farm level. In addition, extreme climate events and labor shortages at required intervals have made decisive pitch for the promotion and adoption of farm mechanization for ensuring sustainable farm performance and food security in developing countries. However, limited empirical evidence is available from Pakistan, about the adoption of farm mechanization and its impact on farm performance and food availability. Therefore, primary data were collected from 384 farmers from cotton–wheat cropping system of Punjab, Pakistan, by using a multi-stage sampling procedure. The endogenous switching regression (ESR) model was employed to estimate the determinants of farm mechanization adoption and their associated impacts on farmers’ livelihood, measured by farm performance and food availability. The findings indicate that the adoption of full mechanization across all farming operations enhances overall farm performance and improves food availability. In addition, full mechanization leads to a substantial increase in farm performance by up to 55% and boosts food availability by approximately 125%. Our study demonstrates that the adoption of farm mechanization is strongly influenced by factors such as education, household size, landholding, off-farm employment, access to credit, and extension services.
Cystic plate approach in laparoscopic cholecystectomy: a consecutive retrospective analysis
Authors: Zhou Yanjie , Xiao Le , Luo Zhulin , Luo Hao , Tan Zhen , Wang Tao
Published: December 2024

Purpose

This study aimed to investigate the safety, feasibility, and possible advantages of the cystic plate approach during laparoscopic cholecystectomy in a retrospective cohort of surgical patients.

Methods

We summarized the key points of the technical approach, retrospectively analyzed the clinical outcomes of 156 patients in the cystic plate approach group from July 2018 to July 2023, and compared the findings with those of 173 cases in the routine approach group from the same period.

Results

We observed no differences in the average stone size, operation time, postoperative hospital stay, conversion rate, complications, or Visual Analog Scale pain scores on the second day of surgery between the two groups (p = 0.076, 0.067, 0.278, 1.000, 0.633, and 0.131, respectively). However, intraoperative blood loss, number of clips used, volume of postoperative drainage fluid, and Visual Analog Scale pain scores on the day of surgery in the cystic plate approach group were significantly lower than those in the routine approach group (p = 0.000, 0.031, 0.027, and 0.021, respectively).

Conclusions

The cystic plate approach is a safe, feasible, and effective approach that has the advantages of minimal invasiveness with less bleeding and seepage, reduced use of biological clips, and less pain, potentially minimizing the risk of iatrogenic biliary injury.

Trial registration

This study was registered at the International Clinical Trial Registry (ChiCTR2100052860). Registration date: November 6, 2021.
Periapical cysts in dogs: 10 cases (2000–2020)
Authors: Vogel-Waski Rebecca J. , Castejon-Gonzalez Ana C. , Church Molly E. , Reiter Alexander M.
Published: December 2024

Objective

To characterize the clinical, diagnostic imaging, and histologic features with description of treatment outcome of periapical cysts in dogs.

Animals

Ten client-owned dogs diagnosed with periapical cysts biopsied between July 1, 2000 and June 30, 2020.

Procedures

Medical records of the Matthew J. Ryan Veterinary Hospital of the University of Pennsylvania were retrospectively searched to identify dogs that had surgical biopsy specimens of cavitary lesions diagnosed as odontogenic cysts and that met additional inclusion criteria. Complete medical records were reviewed.

Results

Range age and body weight of affected dogs were 2.5–12.1 years and 4.3–38.4 kg (9.5–84.7 lb), respectively. All periapical cysts were affecting the incisive bone and/or the maxilla. Nine dogs presented with a fluctuant swelling of the oral mucosa and gingiva; one dog without clinical swelling presented with a history of difficulty breathing. All cysts originated from a non-vital tooth with a structural defect (wear or fracture without pulp exposure) and/or intrinsic staining. Extraction of the associated non-vital teeth, enucleation of the cysts, and curettage of the surgical sites resulted in resolution of the clinical signs.

Conclusions and clinical relevance

The findings indicate that periapical cysts are associated with a non-vital tooth without pulp exposure. Complete evaluation of the clinical, diagnostic imaging, and histologic features of the lesion in affected dogs is necessary to differentiate periapical cysts from other odontogenic cysts and tumors.
Collision Analysis and Motion Control Based on Lift-Type Power Catwalk
Authors: Chen Jia , Xiong Li , Wang Honghui , Yang Yi
Published: December 2024

To address vibration issues in the operation of a lift-type power catwalk, dynamic analysis was conducted using ADAMS 2020 software. The analysis revealed that the vibrations originate from collisions that occur during the transition from the translation to the climbing phase. A quantitative vibration model was developed using the work–energy theorem, incorporating the coefficient of restitution. Based on this model, a composite disturbance rejection control law was designed, integrating sliding-mode speed planning with active disturbance rejection speed tracking. The MATLAB 2022b/Simulink simulations demonstrated that the ADRC strategy outperforms PID and DDPG control algorithms in terms of robustness. Co-simulation with ADAMS and MATLAB/Simulink confirmed the effectiveness of sliding mode speed planning, resulting in a 13.54% increase in the transport efficiency of lift-type power catwalks for drill pipes. Additionally, the oscillation of the output speed of the electro-hydraulic servo system at the collision point was reduced by 300% and the displacement, velocity, and acceleration fluctuations in the catwalk’s mechanical system were reduced by 85%, 75%, and 90%, respectively. The experiments on a lift-type power catwalk prototype confirmed that the proposed vibration suppression strategy effectively reduces vibrations.
Aircraft Flight Autonomous Decision-Making Method Based on Target Predicted Trajectory and Markov Decision Process
Authors: Zhou Yang , Tang Xinmin , Ren Xuanming
Published: December 2024

In this paper, in order to enhance the autonomous operation capabilities of aircraft and ensure their operational safety and efficiency, we propose an autonomous decision-making framework based on target motion state prediction combined with the Markov Decision Process, namely IMM-MDP architecture. Firstly, our own aircraft utilizes the IMM algorithm to achieve the state prediction of the target; building upon the existing algorithmic structure, the proposed framework improves model sets within the IMM algorithm by incorporating climb and turn models and refines the motion modes of aircraft during the cruise phase, gathering corresponding sub-models to predict different motion modes and enhance the prediction accuracy of the target. Secondly, we adopt the Markov Decision Process as the autonomous decision-making method for the own aircraft, proposing a method by which to calculate the optimal decision sequence based on the prediction scenarios of the IMM algorithm; that is, in both multi-step prediction and single-step prediction scenarios, the payoff values of different action strategies at each decision moment are calculated to obtain the optimal decision sequence. The experimental results show that the IMM algorithm with the improved model set, described in this paper, is more accurate than the IMM algorithm and prediction results of the current statistical model, as described in the literature. We also set up a multi-aircraft operation scenario, comparing the IMM-MDP decision framework proposed in this paper with the Monte Carlo and MPC decision models, thus demonstrating that the proposed framework provides better decisions while ensuring safety. Due to the target state prediction and updating, this method also demonstrates better real-time performance and practicality.
Effects of Different Cereal Rye Seeding Rates, Cotton Seeding Rates, Planter Type, and Working Speeds on No-Till Cotton
Authors: Kornecki Ted S. , Kichler Corey M.
Published: December 2024

No-till cotton producers are focused on saving resources by reducing planting rates, while maintaining yields. A 3-year field experiment was conducted in Shorter, Alabama, USA, to evaluate cotton planted into a roll/crimped cereal rye cover crop seeded at rates of 50 and 101 kg ha−1. Cotton planter performance was also compared between a mechanical planter and an electronic planter at speeds of 5.6 and 11.2 km h−1 along with low and high cotton planting rates (90,193 and 180,387 seeds ha−1). Results indicate that cereal rye seeding rates did not affect its biomass. The emergence rate index (ERI) was influenced by the planter type at the 5.6 km h−1 speed with a higher ERI (9.70% day−1) for the mechanical planter compared to a lower ERI (9.05% day−1) for the electronic planter. The cotton population was proportional to planting rates generating 66,650 and 114,178 plants ha−1 at low and high rates. Standard deviation (STD) of cotton plant spacing had a lower STD for the electronic planter compared to the mechanical planter, but did not affect the cotton yield. The seed cotton yield was not dependent on the cover crop seeding rate, planter type, and speed, but differed among years. Drought in 2019 caused a yield reduction (1844 kg ha−1) compared to higher yields of 3981 kg ha−1 in 2018 and 4152 kg ha−1 in 2020.
Development and Experiment of Adaptive Oolong Tea Harvesting Robot Based on Visual Localization
Authors: Yu Ruidong , Xie Yinhui , Li Qiming , Guo Zhiqin , Dai Yuanquan , Fang Zhou , Li Jun
Published: December 2024

Aimed to improve the quality of picked tea leaves and the efficiency of tea harvesting, an adaptive oolong tea harvesting robot with an adjustment module of a cutting tool and a harvesting line localization algorithm is proposed. The robot includes a vision measurement module and an adjustment mechanism of a cutting tool, enabling it to assess the shape of tea bushes and adaptively adjust the cutter configuration. To address the challenges of complex tea bush structures and environmental noise, a Prior–Tukey RANSAC algorithm was proposed for accurate harvesting model fitting. Our algorithm leverages prior knowledge about tea bush stem characteristics, uses the Tukey loss function to enhance robustness to outliers, and incorporates workspace constraints to ensure that the cutting tool remains within feasible operational limits. To evaluate the performance of the robot, experiments were conducted in a tea garden in Wuyi Mountain, China. Under ideal conditions, our algorithm achieved an inlier ratio of 43.10% and an R2 value of 0.9787, significantly outperforming traditional RANSAC and other variants. Under challenging field conditions, the proposed algorithm demonstrated robustness, maintaining an inlier ratio of 47.50% and an R2 value of 0.9598. And the processing time of the algorithm met the real-time requirements for effective tea-picking operations. The field experiments also showed an improvement in intact tea rates, from 79.34% in the first harvest to 81.57% in the second harvest, with a consistent usable tea rate of around 85%. Additionally, the robot had a harvesting efficiency of 260.14 kg/h, which was superior to existing handheld and riding-type tea pickers. These results indicate that the robot effectively balances efficiency, accuracy, and robustness, providing a promising solution for high-quality tea harvesting in complex environments.
Improved Algorithm for Vehicle Bottom Safety Detection Based on YOLOv8n: PSP-YOLO
Authors: Zhao Di , Cheng Yulin , Mao Sizhe
Published: December 2024

The safety inspection system for the underside of vehicles demands both high detection speed and accuracy, necessitating a model with small parameters and high network efficiency. To address these issues and improve the real-time performance of under-vehicle safety inspection, the YOLOv8n object-detection algorithm was enhanced, resulting in the PSP-YOLO algorithm. Firstly, the improved PSP-YOLO network introduces a P2 small-object detection head, which is particularly effective in detecting tiny objects, such as small dangerous objects under vehicles, thereby significantly enhancing the ability to detect such small targets. Secondly, the Space-to-Depth Conv (SPD-Conv) module was introduced into the backbone network, which improves the detection performance of low-quality samples and small objects while ensuring high precision and accurate localization of small targets in images. Finally, the Partial Convolution (PConv) lightweight module was also added to the feature fusion network, effectively reducing the model’s parameters and computational load, conserving computing resources, and improving detection speed and accuracy. Experimental results demonstrate that the modified model increased mAP@0.5 by 3.9% and mAP@0.5-0.95 by 3.6% on the dataset used, reduced the number of parameters to 2.53 M, and achieved a detection speed of 104.6 f/s. Therefore, the improved YOLOv8n algorithm significantly enhances the detection performance of dangerous objects, meeting the high-precision and real-time requirements for vehicle underside safety inspections.
Experimental Investigation of Free-Motion Task Implementation on a Serial Metamorphic Manipulator
Authors: Stravopodis Nikolaos , Moulianitis Vassilis
Published: December 2024

This paper presents an experimental investigation into the implementation of free-motion tasks on a serial metamorphic manipulator (SMM). Utilizing a previously established task-based optimization methodology, the dynamic performance of the SMM is evaluated through a combination of theoretical performance metrics and experimental data. The study aims to validate the SMM’s ability to achieve optimized performance through structural reconfiguration. Theoretical models are compared against real-world free-motion task data, demonstrating strong correlations between analytical calculations and experimental outcomes. The discussion focuses on three key areas: the efficiency of joint controllers, end-effector acceleration capabilities, and joint controller performance. Results indicate that an optimized anatomy can achieve more than 40% reduction in produced torques during task execution and a 35% improvement in the torque-to-velocity ratio. While the simple controller implemented in the robot prototype exhibits adequate performance, notable limitations are observed in task segments with lower dynamic performance, particularly in terms of positional accuracy and energy efficiency. During XY-plane task execution, the Z-axis position error deviates by 1 to 2 cm in areas of lower dynamic performance. These findings provide key insights and establish a robust foundation for advancing SMM capabilities in practical applications, with future work focusing on addressing the identified limitations.
Bacterial Contamination of Parcel Vending Machines in Lublin, Poland
Authors: Kasela Martyna , Andrzejczuk Sylwia , Pietras-Ożga Dorota , Ossowski Mateusz
Published: December 2024

Parcel vending machines (PVMs) are receiving more recognition as an environmentally friendly last-mile delivery service. However, their high popularity creates the risk of microbial contamination of touchscreens and keypads resulting in the spread of pathogens in humans. The study aimed at assessing the degree of bacterial contamination of PVMs and characterizing the microbial population using mass spectrometry-based identification. In total, 64 PVMs located in 16 districts of city Lublin (Poland) were studied for the total number of aerobic bacteria (TNAB) using contact plates, whereas bacterial identification was conducted using the MALDI-TOF MS. Study revealed that the average TNAB for the analyzed districts ranged from 1 ± 0.4 CFU/cm2 to 8.54 ± 10.77 CFU/cm2. Statistical analysis showed a positive correlation between the TNAB and the population density (p = 0.0193), emphasizing the influence of human microbiota on the level of bacterial contamination. Among 140 reliably identified bacterial species (96.3%), the most prevalent were Bacillus spp. (52.8%) and Staphylococcus spp. (10.7%). Multiple opportunistic pathogens were detected, including B. cereus and Escherichia coli. This study indicates the need to develop procedures for disinfection or to implement modified materials for the PVMs touchscreens to limit the adhesion of potentially pathogenic microorganisms.
Vibrational Analysis of Building Structures with Irregularities
Authors: Fox Colin , Chung Hyuck
Published: December 2024

This paper presents a mathematical model for predicting vibrations in lightweight, timber-based floor/ceiling structures, enhanced to account for irregularities in joist shape and stiffness, as well as floor stiffness. Building on a prior model that assumed precise geometry and homogeneous material properties, the study now incorporates real timber measurements via the power spectral density of irregularities to incorporate their impact on the system’s vibrational response, including mid-frequency vibrations. Existing results underscore the critical role of component connections in shaping vibration behavior, while the present paper gives new principles for building a model to assess how uncertainties in these connections or material properties affect the overall structural response. This new model maintains the property of efficient computation so that irregularities in the components may be included in the design stage to improve the mid-frequency performance of lightweight, timber-framed structures.
A New Parameter-Free Slope Unit Division Method That Integrates Terrain Factors
Authors: Li Ping , Fan Junfu , Du Yujie , Li Kuan , Zhou Yuke
Published: December 2024

With increasing research on geological hazards and the development of geographic information technology, slope units play an increasingly important role in landslide susceptibility assessment and prevention work. The scientific and reasonable division of slope units directly impacts the accuracy and practicality of analysis results. Despite the significant progress in slope unit division techniques, most existing methods still have certain limitations, such as a strong dependence on manually set thresholds during the division process, resulting in low levels of automation and efficiency. To address this issue, a new parameter-free slope unit extraction algorithm that integrates terrain factors, called Terrain Factor Parameter-Free Slope Unit Division (TFPF-SU), is introduced. This eliminates the issue of manually setting parameter thresholds during the slope unit division process. This algorithm fully utilizes the terrain information provided by digital elevation models (DEMs) to accurately calculate the curvature, slope, and aspect data for each point. On the basis of the inherent consistency principles among slope, aspect, and curvature, object-oriented image segmentation technology is used to achieve slope unit division. We select Dongchuan District in Yunnan Province, China, as a test area to verify the TFPF-SU algorithm and conduct a detailed comparative analysis and validation of the results with those obtained via traditional hydrological analysis methods from both qualitative and quantitative perspectives. In the quantitative analysis, we utilize the size and shape of the slope units. The results indicate the following: ① the slope units obtained with the TFPF-SU method are more uniform in size, avoiding issues with oversized or irregularly shaped units; ② the slope unit shapes obtained with the TFPF-SU method are more reasonable, with about 70% of the units falling within a reasonable shape index range, compared to only about 32% with the hydrological method; and ③ the slope units produced by the TFPF-SU method align more closely with terrain authenticity, exhibiting a higher degree of topographical conformity.
Spatially Constrained 1D Inversions of Common-Midpoint Marine Controlled-Source Electromagnetic Data to Create a 3D Electrical Model
Authors: Correa Jorlivan Lopes , Régis Cícero
Published: December 2024

The proposed 3D stitching of spatially constrained Common Midpoint (CMP) 1D inversions is a method that integrates 1D laterally constrained inversion of marine Controlled-Source Electromagnetic (CSEM) data in the CMP domain to generate a cube of resistivities from 3D surveys. An interpretive model is built in the form of a set of columns of homogeneous cells that form a 3D resistivity grid. The proposed methodology is an iterative process that updates the entire model until it minimizes the data misfit between the real and synthetic data. We connect the model cells by smoothing regularization applied in all three directions, which generates stable solutions. Additionally, we evaluate the inversion result constrained by hard information, for example, well log resistivity data. Two applications to synthetic data and the inversion of a real data set illustrate the method. The synthetic data were generated from 3D models, one with two resistive targets at different depths and a second with a target inside a conductive layer over a resistive basement. The real data were gathered off the southeast coast of Brazil, in an area of gas hydrate accumulation. The results indicate that the method can generate useful approximations to the resistivity structures under the survey area in a much shorter time than that of a full 3D inversion.
Measurement-Based Neural Network Technique for Modeling the Low-Frequency Electric Field Radiated Behavior of Satellite Units
Authors: Lampou Anna N. , Baklezos Anargyros T. , Spyridakis Konstantinos K. , Rigas-Papakonstantinou Dimitrios A. , Vardiambasis Ioannis O. , Nikolopoulos Christos D.
Published: December 2024

In this work, a machine learning technique employing a measurement-driven artificial neural network (ANN) architecture is proposed as a solution to the precise determination of the position and the moment of equivalent electric dipoles for unit characterization. These dipoles are used to match the generated electric field from various sources inside the spacecraft, during space exploration missions. Various methodologies for unit characterization have been proposed in the literature, the most common being the heuristic approaches, least squares variants, method of auxiliary sources, etc. Contrary to the previous time-consuming post-process methodologies, the proposed electric dipole neural network (EDMnet) can offer a real-time characterization of the measured unit (Device Under Test) after a proper training stage, especially as a fast pre-compliance method. The network uses the electric field vector, measured at 14 discrete locations, as input and reports the position and moment of the electric dipole that best matches the measured fields. In this work, various ANN architectures are tested and compared in order to select the optimal EDMnet parameters for accurate source identification. It is shown that the size of the artificial training data affects the performance of the network. The proposed EDMnet can provide accuracy in mm-scale, with respect to dipole positioning, greater than 99% in dipole moment prediction.
Validation of a Multi-Segment Kinematic Foot Model and Optical Motion Capture Using Bi-Planar X-Ray Fluoroscopy and a Markerless RSA Approach
Authors: Valevicius Aida , Bushey Kristen , Jenkyn Thomas
Published: December 2024

Gait analysis with optical motion capture typically treats the foot as a single segment, which can measure clinically useful kinematics but is insufficient to measure the kinematics of joint motions within the foot. This study hypothesizes that a four-segment foot model, tracking the hindfoot, midfoot, forefoot, and hallux, can accurately measure intrinsic foot kinematics when validated against the gold standard of fluoroscopic X-ray radiostereometric analysis (RSA) during walking gait. Ten healthy volunteers were tested, with the left foot tracked during the stance phase from heel strike to toe off. The results indicated that the height-to-length ratio of the medial longitudinal arch (MLA) and the transverse plane motion of the hindfoot were the most reliable kinematic measures, showing the best agreement between the optical motion capture and RSA methods. In contrast, the frontal plane motions of the hindfoot and forefoot showed the greatest differences, though these were not statistically significant at p < 0.05. These findings demonstrate that the multi-segment foot model is a valid method for measuring intrinsic foot kinematics in a clinical setting, providing a reliable alternative to more invasive techniques.
Laboratory Studies on Underground H2 Storage: Bibliometric Analysis and Review of Current Knowledge
Authors: Berrezueta Edgar , Kovács Timea , Herrera-Franco Gricelda , Caicedo-Potosí Jhon , Jaya-Montalvo María , Ordóñez-Casado Berta , Carrión-Mero Paúl , Carneiro Júlio
Published: December 2024

The global demand for energy and the need to mitigate climate change require a shift from traditional fossil fuels to sustainable and renewable energy alternatives. Hydrogen is recognized as a significant component for achieving a carbon-neutral economy. This comprehensive review examines the underground hydrogen storage and, particularly, laboratory-scale studies related to rock–hydrogen interaction, exploring current knowledge. Using bibliometric analysis of data from the Scopus and Web of Science databases, this study reveals an exponential increase in scientific publications post-2015, which accounts for approximately 85.26% of total research output in this field and the relevance of laboratory experiments to understand the physicochemical interactions of hydrogen with geological formations. Processes in underground hydrogen storage are controlled by a set of multi-scale parameters, including solid properties (permeability, porosity, composition, and geomechanical properties) and fluid properties (liquid and gas density, viscosity, etc.), together with fluid–fluid and solid–fluid interactions (controlled by solubility, wettability, chemical reactions, etc.). Laboratory experiments aim to characterize these parameters and their evolution, simulating real-world storage conditions to enhance the reliability and applicability of findings. The review emphasizes the need to expand research efforts globally to comprehensively address the currently existing issues and knowledge gaps.
Factors Affecting the Population of Excited Charge Transfer States in Adenine/Guanine Dinucleotides: A Joint Computational and Transient Absorption Study
Authors: Petropoulos Vasilis , Martinez-Fernandez Lara , Uboldi Lorenzo , Maiuri Margherita , Cerullo Giulio , Balanikas Evangelos , Markovitsi Dimitra
Published: December 2024

There is compelling evidence that the absorption of low-energy UV radiation directly by DNA in solution generates guanine radicals with quantum yields that are strongly dependent on the secondary structure. Key players in this unexpected phenomenon are the photo-induced charge transfer (CT) states, in which an electric charge has been transferred from one nucleobase to another. The present work examines the factors affecting the population of these states during electronic relaxation. It focuses on two dinucleotides with opposite orientation: 5′-dApdG-3′ (AG) and 5′-dGpdA-3′ (GA). Quantum chemistry calculations determine their ground state geometry and the associated Franck–Condon states, map their relaxation pathways leading to excited state minima, and compute their absorption spectra. It has been shown that the most stable conformer is anti-syn for AG and anti-anti for GA. The ground state geometry governs both the excited states populated upon UV photon absorption and the type of excited state minima reached during their relaxation. Their fingerprints are detected in the transient absorption spectra recorded with excitation at 266 nm and a time resolution of 30 fs. Our measurements reveal that in the large majority of dinucleotides, chromophore coupling is already operative in the ground state and that the charge transfer process occurs within ~120 fs. The competition among various relaxation pathways affects the quantum yields of the CT state formation in each dinucleotide, which are estimated to be 0.18 and 0.32 for AG and GA, respectively.
A Proposed Fragility Curve Based on PO-ID Hybrid Analysis for Seismic Assessment Performance of the Reinforced Concrete Continuous Bridges in Earthquake Prone Area
Authors: Htay Khin Thuzar , Tanjung Jafril , Masrilayanti  , Olivia Monita , Mohamed Nazri Fadzli , Bur Mulyadi
Published: December 2024

In earthquake-prone regions, the seismic performance assessment of reinforced concrete (RC) continuous bridges is critical for ensuring their resilience and safety. This study proposes a fragility curve developed through a hybrid pushover–incremental dynamic (PO-ID) analysis to accurately evaluate the seismic vulnerability of RC continuous bridges. The proposed method integrates the advantages of pushover analysis, which provides insights into the bridge’s capacity, with incremental dynamic analysis, which captures the bridge’s response under varying earthquake intensities. The resulting fragility curves offer a more comprehensive understanding of the likelihood of bridge failure at different seismic intensities. Incremental dynamic analysis (IDA) effectively illustrates a bridge’s response to increasing seismic demands but does not account for ultimate displacement under static lateral loads. Pushover analysis (POA) is useful for capturing maximum displacement capacity under static forces, yet it falls short of addressing the dynamic effects of near-fault ground motions. The hybrid approach combines the strengths of both IDA and POA, and this hybrid method’s heightened sensitivity to damage states allows for earlier detection and conservative displacement estimates, improving seismic assessments, informing design and retrofitting practices, and enhancing safety by addressing transverse displacements and weak axis vulnerabilities.
Enhancing Sustainable Decision Making: The Impact of Emotional Valence, Arousal, and Personality on Risk Recognition During Contract Review
Authors: Wan Ziyi , Liao Pin-Chao , Liao Xiaofeng , Chong Heap-Yih
Published: December 2024

The capacity to identify risks during the pre-contract phase is crucial for effective contract management. Among the various factors that can influence this ability, emotions play a significant role in determining the risk recognition capabilities of individuals. This study aims to investigate the complex interplay between emotional states, personality traits, learning styles, and risk recognition during contract review with physiological and psychological responses. Firstly, a theoretical framework that delineates the relationship among the demographic and emotional factors and risk recognition performance during contract review is proposed. Secondly, an experiment is conducted to record the physiological and psychological responses. Finally, a hierarchical regression model is employed. The results indicated that emotional valence and arousal significantly influence risk recognition performance (p < 0.001), while individual factors such as personality traits and risk propensity indirectly affect risk recognition performance through the mediating role of emotions (p < 0.01). The research contributes to the existing literature by elucidating the indirect pathways through which individual characteristics influence risk perception. These insights can inform sustainable risk management strategies, helping organizations and individuals make more informed and effective decisions in contract management.
Effects of Out-of-Plane Deformation of the Base Plate on the Structural Behavior of an Exposed Column Base
Authors: Nan Ding , Nakahara Hiroyuki , Chan Iathong
Published: December 2024

This study explores the behavior of exposed column bases in concrete-filled steel tubular (CFST) and steel structures, with a focus on cases where base plates yield due to out-of-plane deformation. Understanding these mechanisms is crucial for improving the design and safety of these structures. Experimental tests and numerical analyses were conducted on four specimens to investigate their lateral load versus drift angle behavior. The tests demonstrated that base plates exhibited sufficient deformation capacities and enhanced hysteresis characteristics. Finite element method (FEM) analysis successfully traced the load–deformation relationships observed in the tests, providing detailed insights into stress distribution on the base plates. Based on these analyses, a simplified calculation method was proposed to evaluate the horizontal strength of exposed column bases. The proposed method showed excellent agreement with the test results, highlighting its potential as a practical tool for structural design.
Investigating the Compressive Strength of Clay Brick Masonry: A Case Study of Nangarhar, Afghanistan
Authors: Nazimi Karishma , Castro Juan Jose , Omi Shogo , Stanikzai Mohammad Ajmal
Published: December 2024

In Afghanistan, masonry structures using burnt clay bricks have long been used for public and private buildings. However, still, there is no standard for masonry structural design based on local material properties. This study investigated the compressive strength of clay brick masonry prisms in Nangarhar, Afghanistan, through experimental testing and finite element modeling (FEM). Three brick classes, with compressive strengths between 8 and 14 MPa, were used to construct prism specimens. The research aimed to propose specific values for masonry compressive strength using local materials and examine the effects of brick strength (fb), mortar strength (fj), joint thickness (tj), and slenderness ratio (h/t) on masonry compressive strength (fm). Test results showed fm values of 17.2 MPa for first-class, 10.0 MPa for second-class, and 7.6 MPa for third-class brick masonry, indicating the influence of the brick’s quality. Key findings showed that an increase in fb causes an equal increase in fm, a 5% increase in fj leads to a 1% increase in fm, a 5 mm increase in tj gives an 8% fm increase, and a 5.5% increase in h/t results in a 1% decrease in fm. The research provides valuable information for evaluating the compressive strength of masonry structures based on the quality of local materials, which can be used to revise Chapter 7 of the Afghanistan Building Code, 2012.
Targeting Precision in Cancer Immunotherapy: Naturally-Occurring Antigen-Specific TCR Discovery with Single-Cell Sequencing
Authors: Alrhmoun Saleh , Fisher Marina , Lopatnikova Julia , Perik-Zavodskaia Olga , Volynets Marina , Perik-Zavodskii Roman , Shevchenko Julia , Nazarov Kirill , Philippova Julia , Alsalloum Alaa , Kurilin Vasily , Silkov Alexander , Sennikov Sergey
Published: December 2024

Background: Adoptive cell therapy is the most promising approach for battling cancer, with T cell receptor-engineered T (TCR-T) cell therapy emerging as the most viable option for treating solid tumors. Current techniques for preparing TCR-T cell therapy provide a limited number of candidates TCRs, missing the comprehensive view of the repertoire, which may hinder the identification of the most effective TCRs. Methods: Dendritic cells were primed with immunogenic peptides of the antigen of interest to expand antigen-specific CD8 T lymphocytes from peripheral blood. Following that, the entire repertoire of naturally occurring antigen-specific TCRs was analyzed using single-cell RNA sequencing, alongside the assessment of the dominancy, transcriptome, and binding specificity of the obtained clonotypes, utilizing the TCRscape tool and ERGO-II neural network to identify the most effective candidate for TCR-T cell therapy development. Finally, TCR-T cells with the candidate TCR were obtained, followed by assessing their functionality and selectivity. Results: The developed protocol achieved a remarkable increase in the percentage of antigen-specific T cells by more than 200-fold, with more than 100 antigen-specific TCR clonotypes identified. The resulting TCR-T cells demonstrated high cytotoxicity and selectivity for the targeted antigen, indicating their potential to preferentially target tumor cells. Conclusions: This study offers a comprehensive approach for the discovery and analysis of not only few, but the entire repertoire of naturally occurring antigen-specific TCRs for TCR-T cell therapy development. Additionally, the proposed approach can be tailored to accommodate different types of antigens and MHC variants, making it a highly versatile tool for both research and clinical applications.