bluuebunny/crossref_metadata_2025 huggingface dataset:
Father presence, adolescent girls’ resilience, psychological security, and achievement goal orientation: examining direct and indirect associations
Authors: Zhou Jiayi , Wei Xueyan , Xue Lingfang
Published: October 2024

In the developmental research, studies on the importance of fathers in the parent–child relationship is insufficient, especially the father-daughter relationship. Thus far, a few studies have investigated whether father presence influences adolescent daughters’ resilience. Therefore, this study investigated the extent to which intermediary factors affect the relationship between father presence and daughters’ resilience. A total of 718 Chinese female high school students participated in a questionnaire survey. The results showed father presence was positively related to resilience in female high school students. Additionally, psychological security fully mediated the relationship between father presence and daughters’ resilience, whereas achievement goal orientation partially mediated this relationship; specifically, the mastery-approach and performance-approach orientations. The results highlight the importance of considering the meaning and implications of father presence and daughter’s resilience in Chinese culture.
The relationship of compliance with immediate and delayed suggestibility and types of resistant behavioral responses in children aged 10–15 years
Authors: Gudjonsson Gisli , Giostra Valeria , Maiorano Tiziana , Vagni Monia
Published: October 2024

This study examined the relationship of compliance with immediate and delayed suggestibility and types of resistant behavioral responses (RBRs) in 454 children (10–15 years) using the Gudjonsson Suggestibility Scale (GSS 2) and a slightly adapted version of the Gudjonsson Compliance Scale (GCS). The GCS was found to have satisfactory internal consistency with this age group. Immediate suggestibility and delayed suggestibility were significantly correlated (small effect size). Compliance was most strongly correlated with Yield 1 (large effect size) and Yield 2 (medium effect size) and only modestly with Shift and delayed suggestibility (both small effect size). Of both theoretical and practical importance was the finding that out of the three resistant behavioral responses (RBRs) where misleading questions were not yielded to, ‘direct explanation’ and ‘no answers’ were the only salient predictors of compliance. ‘Do not know’ answers were found to have the weakest association with compliance. The current findings help better understand the complex relationship of compliance with immediate suggestibility (i.e., Yield and Shift), RBRs, and delayed suggestibility in children. The findings have important implications for future studies as well as interview practice.
European structural funds to finance healthcare in Italian regions
Authors: Graps Elisabetta A. , Lagravinese Raffaele , Ruggiero Adriano
Published: October 2024

In this work, we explore the extensive utilization of European Union Structural Funds to enhance regional healthcare systems in Italy over the period 2014–2020. These funds serve as vital instruments for financing the construction, renovation, and modernization of healthcare facilities, as well as supporting medical research and technological innovation. They enable the implementation of disease prevention and health promotion programs and provide essential income support to vulnerable families through the European Social Fund. Our analysis found that EU funding allocated to “health-related” projects during the 2014–2020 programming period, amounts to just over 6.19 billion euros [5.1 billion financed by the European Regional Development Fund (ERDF) and just over 1 billion financed by the European Social Fund (ESF)], of which 65.88% is funded by European resources. These funds supported a total of 26,739 projects, with 22,529 funded by the ERDF, primarily focusing on infrastructure projects and the acquisition of new technologies in the healthcare sector. Meanwhile, the 4,210 projects funded by the ESF were dedicated to personnel training and public health policies in the regions. The European co-financing provided by the ERDF exceeded 63%, while for the ESF, the European share was approximately 77%. Notably, some regions have leveraged these funds to pioneer telemedicine and healthcare technologies, improving healthcare accessibility, especially in remote areas. However, regional disparities in fund allocation and utilization persist and coordinated strategies and cross-regional collaboration, emphasizing the sharing of best practices and the reinforcement of transnational projects, need to successfully address these calls and to promote convergence not only in economic but also in healthcare terms.
Journey tracker: driver alerting system with a deep learning approach
Authors: Yashaswini N. L. , Arun Vanishri , Shashikala B. M. , Raj Shyla , Vani H. Y. , Flammini Francesco
Published: October 2024

Negligence of public transport drivers due to drowsiness poses risks not only to their own lives but also to the lives of passengers. The designed journey tracker system alerts the drivers and activates potential penalties. A custom EfficientNet model architecture, based on EfficientNet design principles, is built and trained using the Media Research Lab (MRL) eye dataset. Reflections in frames are filtered out to ensure accurate detections. A 10 min initial period is utilized to understand the driver’s baseline behavior, enhancing the reliability of drowsiness detections. Input from drivers is considered to determine the frame rate for more precise real-time monitoring. Only the eye regions of individual drivers are captured to maintain privacy and ethical standards, fostering driver comfort. Hyperparameter tuning and testing of different activation functions during model training aim to strike a balance between model complexity, performance and computational cost. Obtained an accuracy rate of 95% and results demonstrate that the “swish” activation function outperforms ReLU, sigmoid and tanh activation functions in extracting hierarchical features. Additionally, models trained from scratch exhibit superior performance compared to pretrained models. This system promotes safer public transportation and enhances professionalism by monitoring driver alertness. The system detects closed eyes and performs a cross-reference using personalization data and pupil detection to trigger appropriate alerts and impose penalties.
Inheriting wisdom: transfer of traditional, scientific, and ecological knowledge in fishing communities in Mexico
Authors: Fernández-Rivera Melo Francisco , Torre Jorge , Cuevas-Gómez Gabriela A. , Amador-Castro Imelda G. , Velázquez-Castillo Miriam A. , Espinoza-Tenorio Alejandro
Published: October 2024

The complementary use and transfer of empirical and scientific knowledge are essential for the holistic and sustainable management of fishing resources. To understand how both types of knowledge are transferred in fishing communities in three regions of Mexico, we conducted 120 in-depth interviews with young people, adults, and older adults who participated in various activities within fishing value networks. During the interviews, we identified who participated in transferring knowledge within communities, what lessons were passed on, what knowledge has been lost, and what scientific topics are known within the communities. We also investigated the sector’s most used means of communication to further explore the transfer of scientific and technical knowledge and the fundamental roles of external actors in transferring knowledge within communities. The information was coded, categorized, and analyzed for each question. The interviewees valued the continuity of inheriting traditional knowledge, which included teaching practical skills, such as fishing techniques and navigation, and transmitting values, traditions, and ways of understanding and relating to the marine environment. The interviewees perceived knowledge transfer as a bidirectional exchange of knowledge, ideas, and practices among generations. Furthermore, they recognized the value of external actors with scientific and technical knowledge in promoting innovation and adapting to new challenges. The combination of knowledge and perspectives enriches fisheries management and marine environmental conservation. Promoting the transfer of traditional and scientific knowledge is fundamental to building a future where fishing and marine life coexist in harmony and prosperity. The responsibility of supporting this integration falls on fishing communities and external actors. Working together in this collaborative learning process is the key to achieving sustainable resource management and ensuring the continuity of this valuable tradition for future generations. In doing so, these communities’ cultural and ecological richness can be preserved, ensuring a lasting balance between people and the sea.
From field to fork: revitalizing underutilized alliums through value chain development
Authors: Kale Rajiv B. , Gavhane Abhishek D. , Gadge Shailendra S. , Gaikwad Shivam Y. , Singh Sharadveer , Khandagale Kiran S. , Bhat Rohini , Wayal Sagar M. , Mahajan Vijay
Published: October 2024

The genus Allium is a prominent member of the Amaryllidaceae family and encompasses approximately 1,063 species worldwide. These diverse species vary in appearance and flavor but they share biochemical similarities. Underutilized Alliums present a promising alternative to onion and garlic in various Indian regions, given their adaptability, versatile utility, and nutraceutical properties. Their adaptation in the plains of India is a great opportunity to add medicinal and nutraceutical value to Indian cuisine. Therefore, the present study aimed to evaluate the underutilized raw Allium leaves for their sensory perception by hedonic test (n = 60), consumer perceptions and willingness to purchase (n = 180), and the development and validation of value chain model (n = 30) to popularize these species in plains. For the various sensory attributes evaluated, Allium tuberosum Kazakhstan CGN-1587 emerged out to be the most suitable for its advancement into the consumer survey. The consumer perception study recorded 74.44% willingness to purchase of total respondents and a majority preference for consuming it in cooked form (38.30%). A value chain model of Allium tuberosum Kazakhstan CGN-1587 with supply chain agencies was subsequently developed. Validation of this value chain model was done with a panel of different stakeholders. Panelists perceived the value chain as highly valid, particularly in terms of economic feasibility (4.30 ± 0.70) and sustainability (4.20 ± 0.81). Thus, the present study provides valuable insights that can support and promote the use of underutilized Alliums in non-traditional areas of India.
A Path Planning and Tracking Control Algorithm for Multi-Autonomous Mobile Robot Systems Based on Spatiotemporal Conflicts and Nonholonomic Constraints
Authors: Shen Zixiang , Du Haibo , Yu Lanlin , Zhu Wenwu , Zhu Min
Published: October 2024

This paper proposes a path planning and tracking control algorithm for multi-autonomous mobile robot (multi-AMR) systems that addresses the challenges posed by AMRs with a kinematic model. The proposed path planning algorithm is divided into two layers. The upper layer of the algorithm detects spatiotemporal conflicts between the paths of any two AMRs using a spatiotemporal conflict detection tree and the Separating Axis Theorem. The lower layer of the algorithm takes into account the kinematic model of the AMRs, ensuring that the generated paths satisfy the nonholonomic constraints. Furthermore, the lower layer introduces weighted adjustments to the heuristic evaluation, significantly improving the efficiency of the planning process. The proposed tracking control algorithm accounts for the kinematic model of AMRs and various constraints, achieving precise path tracking through model predictive control. The simulation results demonstrate that the proposed path planning and tracking control algorithm can efficiently generate conflict-free paths and achieve precise tracking control that satisfies the nonholonomic constraints of multi-AMR systems.
Fermented Feed in Broiler Diets Reduces the Antinutritional Factors, Improves Productive Performances and Modulates Gut Microbiome—A Review
Authors: Predescu Nicoleta Corina , Stefan Georgeta , Rosu Mihaela Petronela , Papuc Camelia
Published: October 2024

The aim of this review is to highlight the most beneficial effects of dietary fermented feed in correlation with decreasing the antinutrient concentration in vegetal matrices usually used for broiler nutrition. Rational feed formulation is critical for animals because it improves animal performance, and provides the animal with the necessary nutrients to develop strong bones, muscles and tissues, and a properly functioning immune system. Fermentation of animal feed is useful as compounds with high molecular mass are converted into energy and compounds with lower molecular mass in the presence of enzymes produced mainly by bacteria and yeasts. Fermentation products contain probiotic compounds with beneficial effects on the health of the animal microbiome. Feed fermentation has other roles such as converting antinutrients into beneficial substances for animal organisms, and some studies have shown that fermentation of feed decreases the risk of antinutrient components presence. For the bibliographic research, different platforms were used (PubMed, Science Direct, MDPI resources), and numerous words or combinations of terms were used to find the latest information. Fermented feed utilization has been shown to enhance growth performance while promoting a healthier gut microbiome in animals.
Effects of Organic Agricultural Materials and Cultivation Methods on the Control of Ginger Rhizome Rot Disease and Growth in Organic Ginger Farming
Authors: Kim Minjeong , Shim Changki , Lee Jaehyeong
Published: October 2024

This study aimed to develop eco-friendly disinfection technology for ginger seed rhizomes by evaluating the effects of various organic agricultural treatments on germination rates, fresh weight, and disease resistance. The Korean native ginger variety, Bongdongjaerae, and the Chinese variety, Laiwu xiao, were treated with lime–sulfur mixtures, antifungal bacterial isolates, and microalga. Results showed that the 0.4% lime–sulfur treatment achieved the highest germination rate of 89.0% for domestic ginger grown under a single-bed cultivation. The combined treatment with Bacillus velezensis strains GT227 and GT234 and Chlorella fusca (CHK0058) significantly increased the fresh weight, highlighting its potential to enhance ginger growth under organic farming conditions. Single-bed cultivation yielded better results compared to flat-bed cultivation, showing higher fresh weights and lower infection rates. Overall, organic treatments, particularly the combination of CHK0058, GT227, and GT234, proved effective in enhancing ginger growth and reducing disease incidence, highlighting the potential for sustainable agricultural practices in ginger cultivation.
Quercetin and Thyroid
Authors: Giuliani Cesidio , Di Dalmazi Giulia , Bucci Ines , Napolitano Giorgio
Published: October 2024

Quercetin is the most abundant flavonoid present in fruits and vegetables. For its antiproliferative, antiviral, anti-inflammatory and antioxidants activities, it is an active ingredient of several herbal remedies and is available as a nutraceutical. Experimental studies performed in vitro have demonstrated that quercetin inhibits growth and function in normal thyroid cells and may act as a thyroid disruptor. These effects have also been confirmed in vivo using rodent models. Some studies have reported the ability of quercetin to interfere with the metabolism of thyroid hormones, since it inhibits the 5′-deiodinase type 1 (D1) activity in the thyroid, as well as in the liver. Besides the effects on normal thyroid cells, several experiments performed in vitro have shown a potential therapeutic role of quercetin in thyroid cancer. Indeed, quercetin inhibits the growth, the adhesion and the migration of thyroid cancer cells, and it also has redifferentiation properties in some thyroid cancer cell lines. In conclusion, these data suggest that, although its effects can be of benefit in hyperthyroidism and thyroid cancer, caution is required in the use of high doses of quercetin due to its anti-thyroid properties. Further in vivo studies are certainly needed to confirm these hypotheses.
Pedestrian Fall Detection Methods for Public Traffic Areas: A Literature Review
Authors: Zhao Rongyong , Zhu Wenjie , Han Chuanfeng , Wei Bingyu , Zhang Hao , Rahman Arifur , Li Cuiling
Published: October 2024

Crowd accident surveys have shown that regardless of the initial triggering factors, pedestrian fall behavior is the most critical factor causing and aggravating crowd accidents in public traffic areas (PTAs). The application of pedestrian fall behavior detection methods in PTAs is significant. Once deployed, they would prevent many pedestrians from losing life in crowded traffic area accidents. However, most existing methods are still focused on medical assistance for the elderly. Therefore, this paper conducted bibliometric and content analyses, combining fall detection-related keywords from internationally recognized literature databases and benchmark pedestrian behavior datasets. Based on the analysis of the state-of-the-art (SOTA) achievements in fall detection methods, the fall detection methods were classified into different categories according to the research approach. This study undertakes a comprehensive analysis of five predominant methods, namely, computer vision, Internet of Things, smartphone, kinematic, and wearable device-based methods. Furthermore, the benchmark datasets, including fall scenarios, were introduced and compared. Finally, this study provides a detailed discussion of existing fall detection methods, and possible future directions are identified considering the application requirements in PTAs. This overview may help researchers understand the SOTA fall detection methods and devise new methodologies by improving and synthesizing the highlighted issues in PTAs.
State Estimation for Measurement-Saturated Memristive Neural Networks with Missing Measurements and Mixed Time Delays Subject to Cyber-Attacks: A Non-Fragile Set-Membership Filtering Framework
Authors: Wang Ziyang , Wang Peidong , Wang Jiasheng , Lou Peng , Li Juan
Published: October 2024

This paper is concerned with the state estimation problem based on non-fragile set-membership filtering for a class of measurement-saturated memristive neural networks (MNNs) with unknown but bounded (UBB) noises, mixed time delays and missing measurements (MMs), subject to cyber-attacks under the framework of weighted try-once-discard protocol (WTOD protocol). Considering bandwidth-limited open networks, this paper proposes an improved set-membership filtering based on WTOD protocol to partially solve the problem that multiple sensor-related problems and multiple network-induced phenomena influence the state estimation performance of MNNs. Moreover, this paper also discusses the gain perturbations of the estimator and proposes an improved non-fragile estimation framework based on set-membership filtering, which enhances the robustness of the estimation approach. The proposed estimation framework can effectively estimate the state of MNNs with UBB noises, estimator gain perturbations, mixed time-delays, cyber-attacks, measurement saturations and MMs. This paper first utilizes mathematical induction to provide the sufficient conditions for the existence of the desired estimator, and obtains the estimator gain by solving a set of linear matrix inequalities. Then, a recursive optimization algorithm is utilized to achieve optimal estimation performance. The effectiveness of the theoretical results is verified by comparative numerical simulation examples.
Beyond Granularity: Enhancing Continuous Sign Language Recognition with Granularity-Aware Feature Fusion and Attention Optimization
Authors: Du Yao , Peng Taiying , Hu Xiaohui
Published: October 2024

The advancement of deep learning techniques has significantly propelled the development of the continuous sign language recognition (cSLR) task. However, the spatial feature extraction of sign language videos in the RGB space tends to focus on the overall image information while neglecting the perception of traits at different granularities, such as eye gaze and lip shape, which are more detailed, or posture and gestures, which are more macroscopic. Exploring the efficient fusion of visual information of different granularities is crucial for accurate sign language recognition. In addition, applying a vanilla Transformer to sequence modeling in cSLR exhibits weak performance because specific video frames could interfere with the attention mechanism. These limitations constrain the capability to understand potential semantic characteristics. We introduce a feature fusion method for integrating visual features of disparate granularities and refine the metric of attention to enhance the Transformer’s comprehension of video content. Specifically, we extract CNN feature maps with varying receptive fields and employ a self-attention mechanism to fuse feature maps of different granularities, thereby obtaining multi-scale spatial features of the sign language framework. As for video modeling, we first analyze why the vanilla Transformer failed in cSLR and observe that the magnitude of the feature vectors of video frames could interfere with the distribution of attention weights. Therefore, we utilize the Euclidean distance among vectors to measure the attention weights instead of scaled-dot to enhance dynamic temporal modeling capabilities. Finally, we integrate the two components to construct the model MSF-ET (Multi-Scaled feature Fusion–Euclidean Transformer) for cSLR and train the model end-to-end. We perform experiments on large-scale cSLR benchmarks—PHOENIX-2014 and Chinese Sign Language (CSL)—to validate the effectiveness.
The Importance of Weather Factors in the Resilience of Airport Flight Operations Based on Kolmogorov–Arnold Networks (KANs)
Authors: Song Mingyang , Wang Jianjun , Li Rui
Published: October 2024

This study analyzes the impact of weather factors on the resilience of airport flight operations, focusing on flight performance, economic outcomes, and transportation capacity. A Kolmogorov–Arnold Network (KAN) model was employed to identify key weather variables and establish the relationship between these factors and airport operational resilience. Xi’an Xianyang International Airport was used as a case study, with the weights of various routes determined using grey relational analysis, considering average daily flight volume, flight distance, and airport flow stability indicators. Flight operation records and weather data were utilized to assess the influence of critical weather factors on key operational resilience metrics. The findings reveal that routes in economically developed areas exert a more pronounced effect on flow stability. Temperature and wind speed emerged as the most influential factors, with importance values of 0.35 and 0.32, respectively, about flight operations and economic performance. Furthermore, changes in wind direction and wind speed had the greatest impact on transportation capacity, with importance values of 0.7 and 0.65, respectively. These results highlight the need for special attention to weather factors such as temperature and wind speed during flight scheduling and risk assessment to ensure operational safety, efficiency, and economic viability.
Review of Monitoring and Control Systems Based on Internet of Things
Authors: Witczak Dawid , Szymoniak Sabina
Published: October 2024

The Internet of Things is currently one of the fastest-growing branches of computer science. The development of 5G wireless networks and modern data transmission protocols offers excellent opportunities for rapid development in this field. The article presents an overview of monitoring and control systems based on the Internet of Things. The authors discuss various aspects of these systems, including their architecture, applications, and challenges. We focus on analyzing the latest achievements in this field, considering technological innovations and practical applications in various sectors. Also, we emphasize the importance of integrating data from multiple sources and developing data analysis algorithms to ensure the effectiveness and precision of IoT-based monitoring and control systems. The article provides a valuable overview of the current state of knowledge in this dynamic area, inspiring further research and technological development. It also includes case studies showing various IoT device applications and energy consumption management.
Blockchain-Driven Food Supply Chains: A Systematic Review for Unexplored Opportunities
Authors: Ellahi Rizwan Matloob , Wood Lincoln C. , Bekhit Alaa Ei-Din A.
Published: October 2024

This systematic review critically examines the diverse applications of Blockchain technology in the food supply chain and identifies areas where its potential remains underutilized. By analysing 60 Blockchain-based frameworks, the study highlights the most frequently employed drivers such as transparency, traceability, and security within food supply chains. Additionally, underexplored applications such as food donation and redistribution, supply chain financing, animal welfare, food waste management, and data analysis are identified, revealing opportunities for further innovation. The research employed NVivo 14 to analyze the extent of Blockchain’s implementation in various food supply chain drivers, and the findings informed the development of a more diverse framework for Blockchain integration. Key insights demonstrate Blockchain’s transformative potential, particularly in enhancing data integrity, trust, and operational efficiency through its immutable ledger and smart contracts, which streamline transactions, cut administrative costs, and reduce fraud. In terms of sustainability and safety, Blockchain improves traceability, accelerates safety responses, promotes environmental sustainability by tracking resource usage, and enhances humanitarian efforts with transparent, efficient resource distribution. Additionally, Blockchain facilitates food waste reduction by optimizing inventory and distribution, while ensuring surplus food reaches those in need. The study concludes by offering a roadmap for future research, pointing toward untapped dimensions of Blockchain’s application in food traceability, sustainable supply chain management, and environmental & social impact. While the review provides a comprehensive understanding of Blockchain’s current usage in food supply chains, the scope is limited by the systematic review process and specific inclusion criteria. This study serves as a foundation for exploring Blockchain’s broader potential in shaping the future of food supply chains.
Detection of Decision-Making Manipulation in the Pairwise Comparison Method
Authors: Strada Michał , Ernst Sebastian , Szybowski Jacek , Kułakowski Konrad
Published: October 2024

Most decision-making models, including the pairwise comparison method, assume the honesty of the decision-maker. However, it is easy to imagine a situation where the decision-maker tries to manipulate the ranking results. This problem applies to many decision-making methods, including the pairwise comparison method. This article proposes three simple algorithmic methods for manipulating data using the pairwise comparison method. The proposed solutions try to mimic the behavior of a dishonest decision-maker who, acting under time pressure, chooses a simple strategy that leads to pushing through a given alternative. We also test the susceptibility to detection of the proposed manipulation strategies. To this end, we propose a convolutional neural network architecture, which we train based on generated data consisting of the original random pairwise comparison matrices and their manipulated counterparts. Our approach treats the pairwise comparison matrices as two- or three-dimensional images specific to the decision situation. In the latter case, the matrices are initially transformed into a three-dimensional map of local inconsistencies, and only data processed in this way are subjected to analysis using neural networks. The experiments indicate a significant level of detection of the proposed manipulations. In numerical tests, the effectiveness of the presented solution ranges from 88% to 100% effectiveness, depending on the tested algorithm and test parameters. The measured average computation time for the single case analyzed oscillated below one millisecond, which is a more than satisfactory result of the performance of the built implementation. We can successfully use the neural networks trained on synthetic data to detect manipulation attempts carried out by real experts. Preliminary tests with respondents also indicated high effectiveness in detecting manipulation. At the same time, they signaled the difficulty of distinguishing actual manipulation from a situation in which an expert strongly prefers one or more selected alternatives.
Milling Cutter Wear State Identification Method Based on Improved ResNet-34 Algorithm
Authors: Zheng Yaohui , Chen Bolin , Liu Bengang , Peng Chunyang
Published: October 2024

Tool wear state recognition is a challenging problem because the various types of signals corresponding to different wear states have similar features, making classification difficult. Convolutional neural networks are widely used in the field of tool wear state recognition. To address this problem, this study proposes a milling cutter wear state monitoring model that combines KANS and deep residual networks (ResNet). The traditional ResNet-34’s top linear classifier was replaced with a nonlinear convolutional classifier including _top_kan, and the data were preprocessed using continuous wavelet transform (CWT) to enhance the model’s immunity to interference and feature characterization. The experimental results based on the PHM dataset show that the improved KANS-ResNet-34 model improves accuracy by 1.07% compared to ResNet-34, making it comparable to ResNet-50, while its computation time is only 1/33.68 of the latter. This significantly improves computational efficiency, reduces the pressure on hardware resources, and provides an effective tool wear state recognition solution.
Application of Microbially Induced CaCO3 on the Reinforcement of Rock Discontinuity
Authors: Zhang Simiao , Wang Shuhong , Ahmed Zulkifl , Alshawmar Fahad
Published: October 2024

Microbially induced calcium carbonate precipitation (MICP) is a technique used in geotechnical engineering to reinforce soil and rock. While it is commonly used for soil reinforcement, its application for rock reinforcement in saline–alkaline environments is limited. In order to improve the reinforcement effect of microbially induced calcium carbonate on rock joints in saline–alkaline environments, experiments were conducted to cultivate Sporosarcina pasteurii. The strengthening effects of MICP on rock joints were evaluated using the direct shear test. Samples of sandstone with rough surfaces were reinforced by MICP. The shear strength characteristics of rock joints reinforced by CaCO3 were then assessed. The results showed that after being domesticated in a saline–alkaline environment, the bacterial concentration reached over 96% of that in a neutral environment. The domesticated Sporosarcina pasteurii performed well at temperatures between 10~30 °C in saline–alkaline conditions. In the saline–alkaline environment, the shear strength of rock joints and the production rate of CaCO3 were higher, and the Sporosarcina pasteurii with domestication showed better joint repair performance. The peak shear strength of rock joints reinforced by MICP increased with curing time, with a quicker strength development in the early stage and a slower increase later on. The peak shear strength of cemented rock joints significantly surpassed that of uncemented rock joints. This research can provide valuable insights for the application of MICP technology in reinforcing rock joints in saline–alkaline environment.
Application of the Extension Strain Criterion for Sandstone Failure Evaluation under Tension and Shear Stress Conditions
Authors: Cieślik Jerzy
Published: October 2024

The article discusses the possibility of analysing, in geomechanical terms, the applicability of the extension strain criterion to assessing the fracture and failure process of sandstone samples. The results of laboratory tests of indirect tension, as well as uniaxial and triaxial compression were used to identify various forms of the criterion. The criterion parameters for fracture initiation and advanced failure processes were presented, and the results in both cases are different. The possible ways of applying this criterion to assess crack initiation in a tension test and failure in a shear test were also presented. Digital image correlation (DIC) analyses were used to determine the deformations of sandstone samples in both test types. The results of these studies show the possibilities to use this condition, e.g., to assess the stability of large-diameter boreholes (for disposal of radioactive waste) and wellbore stability, and to monitor and track the behaviour of tunnels drilled in strong rocks.
Ultrasonic Non-Destructive Testing of Accelerated Carbonation Cured-Eco-Bricks
Authors: Oke Joy Ayankop , Abuel-Naga Hossam
Published: October 2024

This study aimed to investigate the behavior of accelerated carbonation-cured laboratory specimens using the ultrasonic non-destructive testing (UNDT) method and compare the results with the destructive testing (DT) method. The materials used in the study included a blend of lime kiln dust and ground granulated blast furnace slag (LKD-GBFS) wastes, natural fine aggregate (sand), and alternative fine aggregates from waste tires. The chemical analysis of the LKD and GBFS samples highlighted them as suitable alternatives to OPC, hence their utilization in the study. A 60:40 (LKD-GBFS) blending ratio and a 1:2 mix design (one part LKD-GBFS blend and two part sand) was considered. The natural fine aggregate was partially replaced with fine waste tire rubber crumbs (TRCs) in stepped increments of 0, 5, and 10% by the volume of the sand. The samples produced were cured using three curing regimens: humid curing (HC), accelerated carbonation curing (ACC) with no water curing (NWC) afterwards, and water curing after carbonation (WC). From the results, an exponential model was developed, which showed a direct correlation between the UNDT and DT results. The developed model is a useful tool that can predict the CS of carbonated samples when cast samples are unavailable. Lastly, a total CO2 uptake of 15,912 g (15.9 kg) was recorded, which underscores ACC as a promising curing technique that can be utilized in the construction industry. This technique will bring about savings in terms of the time required to produce masonry units while promoting a change in the basic assumptions of a safer and cleaner environment.
Factors Affecting Single and Multivehicle Motorcycle Crashes: Insights from Day and Night Analysis Using XGBoost-SHAP Algorithm
Authors: Wisutwattanasak Panuwat , Se Chamroeun , Champahom Thanapong , Kasemsri Rattanaporn , Jomnonkwao Sajjakaj , Ratanavaraha Vatanavongs
Published: October 2024

This study aimed to identify and compare the risk factors associated with motorcycle crash severity during both daytime and nighttime, for single and multivehicle incidents in Thailand using 2021–2024 data. The research employed the XGBoost (Extreme Gradient Boosting) method for statistical analysis and extensively examined the temporal instability of risk factors. The results highlight the importance of features impacting the injury severity of roadway collisions across various conditions. For single motorcycle crashes, the key risk factors included speeding, early morning incidents, off-road events, and long holidays. In multivehicle crashes, rear-end collisions, interactions with large vehicles, and collisions involving other motorcycles or passenger cars were linked to increased injury severity. The findings indicate that the important factors associated with motorcyclist injury severity in roadway crashes vary depending on the type of crash and time of day. These insights are valuable for policymakers and relevant authorities in developing targeted interventions to enhance road safety and mitigate the incidence of severe and fatal motorcycle crashes.
The Dynamics of Heart Rate Asymmetry and Situational Sleepiness from Evening to Night: The Role of Daytime Sleepiness
Authors: Demareva Valeriia
Published: October 2024

The relationship between daytime sleepiness and heart rate asymmetry (HRA) during the transition from evening to night is crucial for understanding autonomic regulation and its implications for alertness. This study aims to investigate how daytime sleepiness influences HRA dynamics from evening to night and how situational sleepiness correlates with HRA metrics. HRA metrics were calculated at 8 P.M., 9 P.M., and 10 P.M. in 50 participants, categorized into ‘Lower Normal’ and ‘Higher Normal’ daytime sleepiness groups based on Epworth Sleepiness Scale (ESS) scores. Situational sleepiness was assessed using the Karolinska Sleepiness Scale (KSS) and Stanford Sleepiness Scale (SSS). The results demonstrated that individuals with ‘Higher Normal’ daytime sleepiness exhibited lower HRA metrics at 10 P.M. compared to those with ‘Lower Normal’ daytime sleepiness, supporting the suggestion that higher daytime sleepiness correlates with reduced parasympathetic activity and diminished autonomic responsiveness. Significant negative correlations between situational sleepiness and HRA metrics were observed in the ‘Higher Normal’ group, particularly with the SSS. Therefore, increased daytime sleepiness affects HRA dynamics by decreasing parasympathetic activity and altering autonomic regulation at the beginning of the biological night (10 P.M.). These findings suggest potential applications for enhancing drowsiness detection and managing fatigue in safety-critical environments.
N-Pep-Zn Improves Cognitive Functions and Acute Stress Response Affected by Chronic Social Isolation in Aged Spontaneously Hypertensive Rats (SHRs)
Authors: Stepanichev Mikhail Y. , Onufriev Mikhail V. , Moiseeva Yulia V. , Nedogreeva Olga A. , Novikova Margarita R. , Kostryukov Pavel A. , Lazareva Natalia A. , Manolova Anna O. , Mamedova Diana I. , Ovchinnikova Victoria O. , Kastberger Birgit , Winter Stefan , Gulyaeva Natalia V.
Published: October 2024

Background/Objectives: Aging and chronic stress are regarded as the most important risk factors of cognitive decline. Aged spontaneously hypertensive rats (SHRs) represent a suitable model of age-related vascular brain diseases. The aim of this study was to explore the effects of chronic isolation stress in aging SHRs on their cognitive functions and response to acute stress, as well as the influence of the chronic oral intake of N-Pep-Zn, the Zn derivative of N-PEP-12. Methods: Nine-month-old SHRs were subjected to social isolation for 3 months (SHRiso group), and one group received N-pep-Zn orally (SHRisoP, 1.5 mg/100 g BW). SHRs housed in groups served as the control (SHRsoc). The behavioral study included the following tests: sucrose preference, open field, elevated plus maze, three-chamber sociability and social novelty and spatial learning and memory in a Barnes maze. Levels of corticosterone, glucose and proinflammatory cytokines in blood plasma as well as salivary amylase activity were measured. Restraint (60 min) was used to test acute stress response. Results: Isolation negatively affected the SHRs learning and memory in the Barnes maze, while the treatment of isolated rats with N-Pep-Zn improved their long-term memory and working memory impairments, making the SHRisoP comparable to the SHRsoc group. Acute stress induced a decrease in the relative thymus weight in the SHRiso group (but not SHRsoc), whereas treatment with N-Pep-Zn prevented thymus involution. N-pep-Zn mitigated the increment in blood cortisol and glucose levels induced by acute stress. Conclusions: N-pep-Zn enhanced the adaptive capabilities towards chronic (isolation) and acute (immobilization) stress in aged SHRs and prevented cognitive disturbances induced by chronic isolation, probably affecting the hypothalamo–pituitary–adrenal, sympathetic, and immune systems.
Timing and Graded BMP Signalling Determines Fate of Neural Crest and Ectodermal Placode Derivatives from Pluripotent Stem Cells
Authors: Chung Keshi , Millet Malvina , Rouillon Ludivine , Zine Azel
Published: October 2024

Pluripotent stem cells (PSCs) offer many potential research and clinical benefits due to their ability to differentiate into nearly every cell type in the body. They are often used as model systems to study early stages of ontogenesis to better understand key developmental pathways, as well as for drug screening. However, in order to fully realise the potential of PSCs and their translational applications, a deeper understanding of developmental pathways, especially in humans, is required. Several signalling molecules play important roles during development and are required for proper differentiation of PSCs. The concentration and timing of signal activation are important, with perturbations resulting in improper development and/or pathology. Bone morphogenetic proteins (BMPs) are one such key group of signalling molecules involved in the specification and differentiation of various cell types and tissues in the human body, including those related to tooth and otic development. In this review, we describe the role of BMP signalling and its regulation, the consequences of BMP dysregulation in disease and differentiation, and how PSCs can be used to investigate the effects of BMP modulation during development, mainly focusing on otic development. Finally, we emphasise the unique role of BMP4 in otic specification and how refined understanding of controlling its regulation could lead to the generation of more robust and reproducible human PSC-derived otic organoids for research and translational applications.
A Fast Grasp Planning Algorithm for Humanoid Robot Hands
Authors: Liu Ziqi , Jiang Li , Cheng Ming
Published: October 2024

Grasp planning is crucial for robots to perform precision grasping tasks, where determining the grasp points significantly impacts the performance of the robotic hand. Currently, the majority of grasp planning methods based on analytic approaches solve the problem by transforming it into a nonlinear constrained planning problem. This method often requires performing convex hull computations, which tend to have high computational complexity. This paper proposes a new algorithm for calculating multi-finger force-closure grasps of three-dimensional objects based on humanoid multi-fingered hands. Firstly, sufficient conditions for the multi-finger force-closure grasps of three-dimensional objects are derived from a point contact model with friction. These three-dimensional force-closure conditions are then transformed into two-dimensional plane conditions, leading to a simple algorithm for multi-finger force-closure determination. This method is purely based on geometric analysis, resulting in low computational demands and enabling the rapid assessment of force-closure grasps, which are beneficial for real-time applications. Finally, the algorithm is validated through two case studies, demonstrating its feasibility and effectiveness.
Evaluating Patients’ Preferences for Dental Clinic Waiting Area Design and the Impact on Perceived Stress
Authors: Emami Milad , Pazhouhanfar Mahdieh , Stoltz Jonathan
Published: October 2024

The waiting area in dental clinics is a known source of stress for patients. However, positive distractions and comfortable design elements might reduce stress levels and provide mental stimulation while awaiting treatment. While ambient elements might play an important role in patient well-being, few studies have directly explored the impact of various design attributes of dental clinic waiting areas on patients’ perceived stress. This study intended to bridge that gap and employed a discrete choice experiment method where 250 participants randomly selected a block and evaluated six pairs of computer-generated images of dental clinic waiting areas created based on eight interior design attributes with various levels: ambient lighting, false ceiling, window size, window view, indoor plants, wall shape, wall material, and seating options. Each visitor chose their preferred option in relation to its presumed effect on stress mitigation. The results suggest that the presence of ambient lighting, a false ceiling with a nature design, large window dimensions, a nature window view, green indoor plants, a curved wall shape, natural wall materials, and mixed seating options all can contribute to mitigating patients’ perceived stress. Additionally, our findings indicate that age, gender, and education might influence choices across some levels of these variables. Overall, these results might assist architects and designers in shaping clinic environments mitigating patient stress during visits. Further studies would be needed to validate our findings and should also consider additional design attributes, more immersive stimuli presentation technologies, as well as potential differences across cultural contexts.
The Neolignan Honokiol and Its Synthetic Derivative Honokiol Hexafluoro Reduce Neuroinflammation and Cellular Senescence in Microglia Cells
Authors: Sasia Chiara , Borgonetti Vittoria , Mancini Caterina , Lori Giulia , Arbiser Jack L. , Taddei Maria Letizia , Galeotti Nicoletta
Published: October 2024

Microglia-mediated neuroinflammation has been linked to neurodegenerative disorders. Inflammation and aging contribute to microglial senescence. Microglial senescence promotes the development of neurodegenerative disorders, including Alzheimer’s disease (AD). In this study, we investigated the anti-neuroinflammatory and anti-senescence activity of Honokiol (HNK), a polyphenolic neolignane from Magnolia officinalis Rehder & E.H Wilson, in comparison with its synthetic analogue Honokiol Hexafluoro (CH). HNK reduced the pro-inflammatory cell morphology of LPS-stimulated BV2 microglia cells and increased the expression of the anti-inflammatory cytokine IL-10 with an efficacy comparable to CH. HNK and CH were also able to attenuate the alterations in cell morphology associated with cellular senescence in BV2 cells intermittently stimulated with LPS and significantly reduce the activity and expression of the senescence marker ß-galactosidase and the expression of p21 and pERK1/2. The treatments reduced the expression of senescence-associated secretory phenotype (SASP) factors IL-1ß and NF-kB, decreased ROS production, and abolished H2AX over phosphorylation (γ-H2AX) and acetylated H3 overexpression. Senescent microglia cells showed an increased expression of the Notch ligand Jagged1 that was reduced by HNK and CH with a comparable efficacy to the Notch inhibitor DAPT. Overall, our data illustrate a protective activity of HNK and CH on neuroinflammation and cellular senescence in microglia cells involving a Notch-signaling-mediated mechanism and suggesting a potential therapeutic contribution in aging-related neurodegenerative diseases.