bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on a Calculation Model of Ankle-Joint-Torque-Based sEMG
Authors: Qiu Xu , Zhao Haiming , Xu Peng , Li Jie
Published: May 2024

The purpose of this article is to establish a prediction model of joint movements and realize the prediction of joint movemenst, and the research results are of reference value for the development of the rehabilitation equipment. This will be carried out by analyzing the impact of surface electromyography (sEMG) on ankle movements and using the Hill model as a framework for calculating ankle joint torque. The table and scheme used in the experiments were based on physiological parameters obtained through the model. Data analysis was performed on ankle joint angle signal, movement signal, and sEMG data from nine subjects during dorsiflexion/flexion, varus, and internal/external rotation. The Hill model was employed to determine 16 physiological parameters which were optimized using a genetic algorithm. Three experiments were carried out to identify the optimal model to calculate torque and root mean square error. The optimized model precisely calculated torque and had a root mean square error of under 1.4 in comparison to the measured torque. Ankle movement models predict torque patterns with accuracy, thereby providing a solid theoretical basis for ankle rehabilitation control. The optimized model provides a theoretical foundation for precise ankle torque forecasts, thereby improving the efficacy of rehabilitation robots for the ankle.
Estimation of Shoulder Joint Rotation Angle Using Tablet Device and Pose Estimation Artificial Intelligence Model
Authors: Takigami Shunsaku , Inui Atsuyuki , Mifune Yutaka , Nishimoto Hanako , Yamaura Kohei , Kato Tatsuo , Furukawa Takahiro , Tanaka Shuya , Kusunose Masaya , Ehara Yutaka , Kuroda Ryosuke
Published: May 2024

Traditionally, angle measurements have been performed using a goniometer, but the complex motion of shoulder movement has made these measurements intricate. The angle of rotation of the shoulder is particularly difficult to measure from an upright position because of the complicated base and moving axes. In this study, we attempted to estimate the shoulder joint internal/external rotation angle using the combination of pose estimation artificial intelligence (AI) and a machine learning model. Videos of the right shoulder of 10 healthy volunteers (10 males, mean age 37.7 years, mean height 168.3 cm, mean weight 72.7 kg, mean BMI 25.6) were recorded and processed into 10,608 images. Parameters were created using the coordinates measured from the posture estimation AI, and these were used to train the machine learning model. The measured values from the smartphone’s angle device were used as the true values to create a machine learning model. When measuring the parameters at each angle, we compared the performance of the machine learning model using both linear regression and Light GBM. When the pose estimation AI was trained using linear regression, a correlation coefficient of 0.971 was achieved, with a mean absolute error (MAE) of 5.778. When trained with Light GBM, the correlation coefficient was 0.999 and the MAE was 0.945. This method enables the estimation of internal and external rotation angles from a direct-facing position. This approach is considered to be valuable for analyzing motor movements during sports and rehabilitation.
Multiple-Junction-Based Traffic-Aware Routing Protocol Using ACO Algorithm in Urban Vehicular Networks
Authors: Lee Seung-Won , Heo Kyung-Soo , Kim Min-A , Kim Do-Kyoung , Choi Hoon
Published: May 2024

The burgeoning interest in intelligent transportation systems (ITS) and the widespread adoption of in-vehicle amenities like infotainment have spurred a heightened fascination with vehicular ad-hoc networks (VANETs). Multi-hop routing protocols are pivotal in actualizing these in-vehicle services, such as infotainment, wirelessly. This study presents a novel protocol called multiple junction-based traffic-aware routing (MJTAR) for VANET vehicles operating in urban environments. MJTAR represents an advancement over the improved greedy traffic-aware routing (GyTAR) protocol. MJTAR introduces a distributed mechanism capable of recognizing vehicle traffic and computing curve metric distances based on two-hop junctions. Additionally, it employs a technique to dynamically select the most optimal multiple junctions between source and destination using the ant colony optimization (ACO) algorithm. We implemented the proposed protocol using the network simulator 3 (NS-3) and simulation of urban mobility (SUMO) simulators and conducted performance evaluations by comparing it with GSR and GyTAR. Our evaluation demonstrates that the proposed protocol surpasses GSR and GyTAR by over 20% in terms of packet delivery ratio, with the end-to-end delay reduced to less than 1.3 s on average.
CNN-Based Pattern Classifiers for Precise Identification of Perinatal EEG Biomarkers of Brain Injury in Preterm Neonates
Authors: Abbasi Hamid , Battin Malcolm R. , Rowe Deborah , Butler Robyn , Gunn Alistair J. , Bennet Laura
Published: May 2024

Electroencephalographic (EEG) monitoring is important for the diagnosis of hypoxic-ischemic (HI) brain injury in high-risk preterm infants. EEG monitoring is limited by the reliance on expert clinical observation. However, high-risk preterm infants often do not present observable symptoms due to their frailty. Thus, there is an urgent need to find better ways to automatically quantify changes in the EEG these high-risk babies. This article is a first step towards this goal. This innovative study demonstrates the effectiveness of deep Convolutional Neural Networks (CNN) pattern classifiers, trained on spectrally-detailed Wavelet Scalograms (WS) images derived from neonatal EEG sharp waves—a potential translational HI biomarker, at birth. The WS-CNN classifiers exhibit outstanding performance in identifying HI sharp waves within an exclusive clinical EEG recordings dataset of preterm infants immediately after birth. The work has impact as it demonstrates exceptional high accuracy of 99.34 ± 0.51% cross-validated across 13,624 EEG patterns over 48 h raw EEG at low 256 Hz clinical sampling rates. Furthermore, the WS-CNN pattern classifier is able to accurately identify the sharp-waves within the most critical first hours of birth (n = 8, 4:36 ± 1:09 h), regardless of potential morphological changes influenced by different treatments/drugs or the evolutionary ‘timing effects’ of the injury. This underscores its reliability as a tool for the identification and quantification of clinical EEG sharp-wave biomarkers at bedside.
A Two-Stage Sustainable Supplier Selection Model Considering Disruption Risk
Authors: Lu Jie , Li Feng , Wu Desheng
Published: May 2024

The global spread of the pandemic has changed many aspects of life and placed the supply chain at risk of disruption. To solve the problem of supplier selection under the risk of supply chain disruption, in this paper, we propose a two-stage evaluation model to address the issue of supplier selection in the context where a pandemic requires a lockdown. First, we incorporate the lead time into the epidemic model that predicts the evolution of the pandemic to identify suppliers that have a high risk of disruption caused by the pandemic’s evolution. Second, we propose a best–worst method combined with regret theory to rank candidate suppliers. Our model provides a dynamic link between the pandemic’s evolution and supplier selection, and it allows selecting suppliers according to various criteria while avoiding supply chain disruptions due to inappropriate supplier selection. We validate the proposed model on a real case study with epidemic data from China. This paper is the first to consider the impact of lockdowns during the pandemic on supplier selection. We develop a novel MCDM model BWM-RT for supplier selection; our model can be an effective decision support approach to help decision makers better cope with the risk of supply chain disruptions.
Structural Equation Modeling in Technology Adoption and Use in the Construction Industry: A Scientometric Analysis and Qualitative Review
Authors: Fu Chuyou , Wang Jun , Qu Ziyi , Skitmore Martin , Yi Jiaxin , Sun Zhengjie , Chen Jianli
Published: May 2024

Considering the emergence and adoption of various innovative technologies, the construction industry has undergone transformation into a more secure, highly efficient, and ecologically sustainable landscape. An increasing number of studies uses the structural equation modeling (SEM) method to explore the dynamics of technology adoption and use within the construction sector. Previous studies have mainly focused on qualitative analysis using the SEM method to analyze technology adoption and usage in the construction industry. This study, however, distinguishes itself from previous research by focusing on the SEM method itself and conducting a systematic analysis using scientometric methods. Based on a total of 140 relevant journal articles, this study adopts a scientometric analysis approach to conduct a holistic review encompassing sources, researchers, keywords, and highly cited documents. The research findings are as follows: (1) the primary focus of the current research topics is on BIM technology; (2) most studies employ cross-sectional SEM instead of longitudinal SEM; (3) there is a deficiency in the theoretical foundation for designing SEM in current research; and (4) the selection of either reflective or formative measures lacks sufficient rigor. Qualitative analysis is used to examine prevailing issues in research design and address the intricate technicalities and potential challenges inherent in the SEM method. Three research gaps and future directions are presented: diversifying regions of study and research topics, incorporating theoretical support for research design, and carefully choosing reflective or formative measures. The findings provide a comprehensive roadmap and valuable reference for future research in this field.
Socio-Cultural Factors and Components of the Digital Economy in Ethnic Minority Regions
Authors: Vlasov Maksim , Polbitsyn Sergey N. , Olumekor Michael , Haddad Hossam , Al-Ramahi Nidal M.
Published: May 2024

We define the digital economy as all economic activities conducted through the use of information technologies, including activities to create new markets, expand old ones, and produce digital goods and services. The digital economy has become a major driver of sustainable development and the transition towards a greener economy. However, studies show an unequal level of progress among cities, regions, and countries. Consequently, this paper explores the associations between socio-cultural factors (such as attitudes towards marriage/raising a family) and components of the digital economy (such as expenses/investment in ICT and the proportion of personal computers and the Internet in households). This study specifically examines twenty-two ethnic minority regions in Russia with data covering a five-year period. Using the Pearson correlation coefficient, the results show that socio-cultural factors including a large urban population and high divorce rates were positively associated with the digital economy, whereas a large rural population, higher birth rates, and higher natural population growth were negatively correlated with the digital economy.
Research on the Impact of Enterprise ESG Ratings on Carbon Emissions from a Spatial Perspective
Authors: Yang Weiwei , Hei Yingying
Published: May 2024

Based on 208 city-level data in China, this paper empirically analyzes the impact of ESG rating on carbon emissions through the SDM spatial metrology model, identifies the direct and indirect consequences and spatial spillover effects of ESG rating on carbon emissions, and compares the regional heterogeneity and city-size heterogeneity of such impacts. This paper draws three conclusions: (1) Empirical evidence shows that the ESG rating performance of enterprises has a significant inhibition effect on carbon dioxide emissions. Specifically, when the ESG rating performance increases by 1%, carbon emissions will decrease by 0.076; among other control variables, the effect of FDI on carbon emission reduction is that when ESG score performance increases by 1%, carbon emission decreases by 0.022. (2) In the decomposition of the total effects, indirect effects and direct effects have the same impact on carbon emissions, and the total effect is −0.393. (3) The inhibition effect is more significant in the Eastern Region and in megacities, where the effect of −0.096 in the Eastern Region is more obvious than that of −0.078 at the national level, and the effect of carbon reduction in megacities is significantly greater than 0.013 in big cities. This suggests regional heterogeneity in regards to the role of ESG ratings in reducing CO2 emissions. This paper reveals the specific effects and internal logic of the impact of ESG performance on CO2 emissions, which has certain implications for various regions to further promote the construction of an ESG system, according to local conditions, and to encourage enterprises to focus on emission reduction and high-quality development.
Recycling Reinforced: The Synergistic Dynamics of Sustainable Behavior
Authors: Enginkaya Ebru , Sağlam Munise Hayrun
Published: May 2024

Recent research has specifically targeted the decision-making process of eco-friendly individuals, emphasizing the significance of recycling and its impact on sustainability. Our study extends this inquiry by examining the correlation between recycling participation and pro-environmental behavior among consumers, integrating the concepts of self-efficacy, feelings of pride, and social pressure into our analysis. We utilized targeted sampling to collect data from a diverse sample of 378 participants, ensuring representation across key demographic groups. By employing Partial Least Squares–Structural Equation Modeling (PLS-SEM), we aimed to explore the intricate relationships underpinning recycling behaviors and pro-environmental actions. The results suggest that self-efficacy and feelings of pride significantly influence individuals’ recycling behaviors, highlighting the role of psychological and social factors in promoting environmental sustainability. It was concluded that social pressure did not have the expected moderating effect on increasing consumers’ feelings of pride and self-efficacy toward recycling activities. This study sheds light on the underlying mechanisms that drive pro-environmental actions, contributes to understanding sustainability promotion through recycling, and offers insights for policymakers and environmental advocates to help foster environmental responsibility and behavior change. The findings emphasize that individuals often value personal achievement and development more when addressing environmental responsibilities and that social pressure does not achieve its expected effects.
Enhancing Seismic Landslide Susceptibility Analysis for Sustainable Disaster Risk Management through Machine Learning
Authors: He Hailang , Wang Weiwei , Wang Zhengxing , Li Shu , Chen Jianguo
Published: May 2024

The accuracy of Seismic Landslide Susceptibility Maps (SLSMs) is imperative for the prevention of seismic landslide disasters. This study enhances the precision of SLSMs by integrating nine distinct machine learning methodologies with the GeoDetector version 0.0.4 tool to filter both numerical and physical factors contributing to landslide susceptibility. The dataset comprises 2317 landslide instances triggered by the 2013 Minxian Ms = 6.6 earthquake, from which redundant factors were pruned using the Recursive Feature Elimination technique. Subsequent evaluations of the optimized factors, both individually and in combination, were conducted through Frequency Ratio analysis and Factor Interaction assessment. The study juxtaposes the Area Under the Receiver Operating Characteristic Curve (AUC) and the accuracy of nine machine learning models before and after factor optimization. The findings indicate an increase in AUC from a maximum of 0.989 to 0.992 in the Random Forest model, and an 8.37% increase in AUC for the SVM model, signifying a notable enhancement in the stability across all models. The establishment of the SLSM notably elevated the frequency ratio in high-risk zones from 50.40 to 85.14, underscoring the efficacy of combining machine learning and detector optimization techniques in sustainable practices. This research proposes a universal framework aimed at eliminating redundancy and noise in SLSMs and hazard risk assessments, thereby facilitating sustainable geological disaster risk management.
Evaluating Ghana’s Youth-Centered Food-Security Policies: A Collaborative Governance Approach
Authors: Boadu Evans Sakyi
Published: May 2024

Food-security issues remain essential for decision-makers at all levels in sub-Saharan Africa (SSA), and youth-oriented food-security policies in Ghana are no exception. While there are no “one-size-fits-all” policy pathways to eradicate poverty and hunger, various governments, civil society, youth groups, and citizens can afford to ignore the present food policies’ status quo. This paper examines the perspective of sustainability when collaborative and open governance approaches are adopted by central governments and their sub-national departments, institutions, and agencies in youth-oriented food-security policymaking, implementation, and evaluation. The extent to which active stakeholder participation and collaboration, or the lack thereof, has either negatively or positively impacted food-security policies is another tangent this paper explores, including the sustainability of the youth-centered food-security policies in Ghana. Using qualitative documentary analysis technique through collaborative and open governance frameworks and drawing on the literature on multisectoral governance and youth-focused food-security policies, this paper identifies several disjointed youth-focused food-security intervention policies in Ghana with hazy institutional arrangements that have failed to ensure adequate implementation and assessment to promote cooperation, accountability, and transparency. The paper suggests the need for collaborative governance, effective policy monitoring, and evaluation strategies that involve government institutions, departments, agencies, civic societies, youth organizations, and citizens’ commitments to food security. This research finds that collaborative strategies and active youth participation in all food-security-related policies are essential for Ghana to achieve Sustainable Development Goals (SDGs) 1 and 2.
SMEs Awareness and Preparation for Digital Transformation: Exploring Business Opportunities for Entrepreneurs in Saudi Arabia’s Ha’il Region
Authors: Tripathi Abhishek , Singh Ajay
Published: May 2024

This study investigates how Saudi SMEs’ awareness and preparation for digital transformation impact their business performance (BP). First and foremost, in this study, we examine the impact of awareness and preparation on business performance using the intention to use (ITU) as an initial mediator. In addition, the researchers also examined the impact of awareness and preparation on business performance through intention to use and Government Support (GS), and later, intention to use and skills as serial mediators. Using a structured questionnaire based on a seven-point Likert scale, data were collected from 68 SMEs in the Ha’il region of Saudi Arabia, one of the Kingdom’s leading economic provinces. The data were analyzed through simple and serial mediation techniques through AMOS-24. The study found that SMEs’ awareness and preparation for digital transformation significantly and positively influenced their intentions to use the technology. The researchers found that intention to use, skills, and government support are significant variables that improve business performance. The research also revealed full-serial mediation between awareness and business performance and preparation and business performance, showing that intention to use and skills and intention to use and government support significantly mediate improving SMEs’ business performance. The study implications provide for SMEs’ successful digital transformation, considering the role of skills and government support, which will help SMEs improve their performance and embrace sustainability in human and economic development in Saudi Arabia. Together with policymakers, SMEs, and researchers, it will also look at the entrepreneurial potential for Saudi nationals in the run-up to Vision 2030.
Let Them Shine: Associations of Schools’ Support for Strengths Use with Teachers’ Sense of Meaning, Engagement, and Satisfaction
Authors: Lavy Shiri , Abu Ahmad Marian , Naama Eman
Published: May 2024

The present research builds on the psychology of sustainability and sustainable development and on research demonstrating the contribution of perceived organizational support for strengths use (POSSU) to the quality of employees’ work life. Specifically, we focus on teachers, whose training and development in schools often aim to narrow competence gaps and correct deficits. We propose that focusing on the development of their strengths may more positively impact their engagement, satisfaction, and sense of meaning at work. A total of 47 school principals (30 women; Mage = 48.37, SD = 7.31) and 235 of their teachers (197 women; Mage = 40.73, SD = 7.78) reported perceptions of their schools’ organizational support for strengths use (POSSU), and of their school support for deficit correction (POSDC). In addition, teachers completed measures of their strengths use, sense of meaning at work, work engagement, and job satisfaction. Teachers’ POSSU was associated (more strongly than POSDC) with teachers’ strength use and positive work-related well-being. Teachers’ strengths use mediated the associations of POSSU with the other variables. Principals’ POSSU was not associated with teachers’ POSSU or with teachers’ strengths use, but was associated with teachers’ sense of meaning and satisfaction at work. The findings highlight the potential benefits of a strengths-supporting school culture to teachers’ work-life quality.
Indigenous or Exotic Crop Diversity? Which Crops Ensure Household Food Security: Facts from Tanzania Panel
Authors: John Innocensia
Published: May 2024

Farm crop diversity is often overlooked, predominantly indigenous crops’ role in this diversity. The main concentration has been on the contribution or role of exotic crops to household crop diversification. At the same time, the role played by both types of crops in household food security has only been aggregated, failing to show how indigenous crops play a key role in household food security. This research paper uses Tanzanian Panel data from waves 4 and 5 to study the factors influencing indigenous and exotic crop diversification and the role of this diversity in household food security. Using a random effect model, the author found that various factors are crucial in determining household crop diversification. Gender, household size, marital status, and expected harvest quantity are among the key factors influencing indigenous crop diversification. On the other hand, age, education, access to markets, access to irrigation services, and soil quality are the primary factors that affect the diversification of exotic crops. Moreover, the findings show that indigenous and exotic crop diversity significantly influences household food consumption. Thus, policies to increase the production of indigenous crops in order to improve household food consumption should be considered.
Phosphate Removal Efficiency and Life Cycle Assessment of Different Anode Materials in Electrocoagulation Treatment of Wastewater
Authors: Li Guangpu , Zheng Bin , Zhang Wenqing , Liu Qiaona , Li Mingzheng , Zhang Haibing
Published: May 2024

The excessive discharge of phosphorus-containing wastewater contributes to eutrophication, posing a serious threat to aquatic ecosystems. Therefore, methods such as electrocoagulation should be utilized to remove phosphorus from wastewater prior to discharging it into a water body. In this study, we aimed to determine the effectiveness of electrocoagulation in treating simulated phosphorus-containing wastewater under different parameters, including anode material (aluminum, iron, and magnesium), electrode distance (ED) (1, 2.5, and 4.5 cm), pH (3, 6, and 9), and current density (CD) (3, 6, and 9 mA/cm2). Additionally, three models of phosphate removal, the pseudo-first-order (PFO), pseudo-second-order (PSO), and Behnajady–Modirshahla–Ghanbery (BMG) models, were used to simulate the relationship between phosphate concentration and time in the electrocoagulation process using the three metals for phosphate removal. The experimental results showed that the aluminum system had the highest removal efficiency (90%) when energized for 20 min under a CD of 3 mA/cm2, followed by those of the iron (80%) and magnesium (35%) systems. Furthermore, a life cycle assessment (LCA) showed that the aluminum electrode system had a smaller environmental impact than the iron and magnesium electrode systems. Therefore, the aluminum electrode system is suitable for phosphorus removal from wastewater.
Assessment for the Sustainable Development of Components of the Tourism and Recreational Potential of Rural Areas of the Aktobe Oblast of the Republic of Kazakhstan
Authors: Saparov Kuat , Omirzakova Miroslava , Yeginbayeva Aigul , Sergeyeva Aigul , Saginov Kairat , Askarova Gulnash
Published: May 2024

The assessment of sustainable tourism development in the rural areas of the Aktobe oblast of Kazakhstan involved thoroughly analyzing multiple dimensions. Environmental, socio-economic, and cultural sustainability aspects were considered to comprehensively understand the region’s tourism potential. The study began by evaluating the available tourism resources in rural Aktobe. This included assessing natural attractions such as landscapes, wildlife, and geological features, as well as cultural heritage sites and infrastructure like accommodation facilities and transportation networks. A crucial aspect of the study was to analyze the environmental impact of tourism activities in rural areas. This involved evaluating the effects on ecosystems and natural resources. The measures for conserving these resources were also identified. Another focus was on the socio-cultural aspects of tourism development. The study aimed to preserve local traditions, cultural heritage, and community identity amidst tourism growth. Strategies for achieving socio-cultural sustainability were devised. Ranking methods were employed to identify key factors influencing rural tourism development. These methods helped prioritize areas for improvement and resource allocation. A balanced approach was adopted to assess the interaction between different dimensions of sustainability. This ensured that environmental, economic, and socio-cultural aspects were considered equally to achieve overall sustainable tourism development. ArcGIS 10 was used for data analysis and visualization. Maps and charts were created to represent spatial and statistical information, aiding in identifying trends and patterns. The study findings were crucial for identifying priority areas for infrastructure development and formulating strategies and programs for rural tourism promotion. The study aimed to ensure that tourism development aligns with the principles of sustainable development, benefiting both the local communities and the environment. The study provided valuable insights into the current status of rural tourism in Aktobe oblast and offered recommendations for sustainable development, contributing to the region’s long-term prosperity.
University Students’ Perception of the Dehesa and the Associated Traditional Trades
Authors: Guillén-Peñafiel Rebeca , Hernández-Carretero Ana María , Sánchez-Martín José Manuel
Published: May 2024

The dehesas are one of the most emblematic landscapes of the Extremadura region (Spain). Along with its natural values, it preserves a wide repertoire of knowledge and trades rooted in the history and tradition of rural communities. However, the knowledge and practices that have characterized life in this environment are currently under serious threat. Faced with this problem, this study was based on the premise that, for individuals to commit themselves to the care and transmission of heritage, it is first necessary for them to know, understand and value it. For this reason, the main objective was to determine the knowledge and appreciation of university students with respect to the dehesa and the ancestral practice of grazing. It also aimed to analyze which are the most valued methodologies, activities, and future strategies for understanding and preserving these cultural landscapes and their ancestral practices. To this end, 400 university students were surveyed, and various quantitative and qualitative analyses were carried out. Quantitative techniques include analyses based on weighted averages, contingency tables and the chi-square test, while qualitative techniques are based on word frequency analysis and inductive content analysis. Despite coming from an environment dominated by this landscape and being one of the few regions that still preserve the ancestral practice of pastoralism, the results corroborated the students’ lack of understanding of the dehesa and the variety of uses it offers. In addition, it was evident that they have hardly frequented this landscape and have not participated in on-site educational experiences. It also revealed the importance of experiential and sensory activities in the understanding and appreciation of the rural environment and its traditions. The results can be useful for improving the design of educational tourism products based on intangible heritage. It can also be useful for adapting teaching strategies and activities to the level of knowledge and experiences of students, helping to ensure the success of the educational experience.
Fluorine Free Surface Modification of Microfibrillated Cellulose-Clay Composite Films: Effect of Hydrophobicity on Gas Barrier Performance
Authors: Poothanari Mohammed Arif , Leterrier Yves
Published: May 2024

Diffusion barrier composite films based on microfibrillated cellulose (MFC) and clay were developed with attention paid to the influence of thermal annealing and a fluorine-free surface silylation on their microstructure, water contact angle (WCA), mechanical properties, oxygen transmission rate (OTR), and water vapor transmission rate (WVTR). The OTR of MFC at 23 °C increased from 1.2 to 25.3 cm3/m2/day/bar as relative humidity increased from 50% to 80%. Annealing increased the film’s crystallinity, surface roughness, and hydrophobicity, while decreasing its OTR by 20% at 80%RH. The addition of clay led to a 30% decrease of OTR at 80%RH due to partial exfoliation and to a 50% decrease when combined with annealing. Silylation increased the hydrophobicity of surface of the film and its combination with clay and annealing led to a WCA of 146.5°. The combination of clay, annealing, and silylation considerably reduced the OTR at 80%RH to a value of 8 cm3/m2/day/bar, and the WVTR at 23 °C and 50%RH from 49 g/m2/day for MFC to 22 g/m2/day. The reduction of OTR and WVTR was found to correlate with the increase in surface hydrophobicity of the film, which was attributed to the reduced access of water molecules within the MFC network.
A Feature-Selection Method Based on Graph Symmetry Structure in Complex Networks
Authors: Deng Wangchuanzi , Wu Minggong , Wen Xiangxi , Heng Yuming , You Liang
Published: May 2024

This study aims to address the issue of redundancy and interference in data-collection systems by proposing a novel feature-selection method based on maximum information coefficient (MIC) and graph symmetry structure in complex-network theory. The method involves establishing a weighted feature network, identifying key features using dominance set and node strength, and employing the binary particle-swarm algorithm and LS-SVM algorithm for solving and validation. The model is implemented on the UNSW-NB15 and UCI datasets, demonstrating noteworthy results. In comparison to the prediction methods within the datasets, the model’s running speed is significantly reduced, decreasing from 29.8 s to 6.3 s. Furthermore, when benchmarked against state-of-the-art feature-selection algorithms, the model achieves an impressive average accuracy of 90.3%, with an average time consumption of 6.3 s. These outcomes highlight the model’s superiority in terms of both efficiency and accuracy.
Exotic Tetraquarks at the HL-LHC with JETHAD: A High-Energy Viewpoint
Authors: Celiberto Francesco Giovanni
Published: May 2024

We review the semi-inclusive hadroproduction of a neutral hidden-flavor tetraquark with light and heavy quark flavor at the HL-LHC, accompanied by another heavy hadron or a light-flavored jet. We make use of the novel TQHL1.0 determinations of leading-twist fragmentation functions to describe the formation mechanism of a tetraquark state within the next-to-leading order perturbative QCD. This framework builds on the basis of a spin physics-inspired model, taken as a proxy for the lowest-scale input of the constituent heavy-quark fragmentation channel. Then, all parton-to-tetraquark fragmentation functions are consistently obtained via the above-threshold DGLAP evolution in a variable-flavor number scheme. We provide predictions for a series of differential distributions calculated by the hands of the JETHAD method, well-adapted to NLL/NLO+ hybrid-factorization studies, where the resummation of next-to-leading energy logarithms and beyond is included in the collinear picture. We provide corroborating evidence that high-energy observables sensitive to semi-inclusive tetraquark emissions at the HL-LHC exhibit a fair stability under radiative corrections, as well as MHOU studies. Our analysis constitutes a prime contact point between QCD resummations and the exotic matter.
Optimizing CT Abdomen–Pelvis Scan Radiation Dose: Examining the Role of Body Metrics (Waist Circumference, Hip Circumference, Abdominal Fat, and Body Mass Index) in Dose Efficiency
Authors: Almohammed Huda I. , Elshami Wiam , Hamd Zuhal Y. , Abuzaid Mohamed
Published: May 2024

Objective: This study investigates the correlation between patient body metrics and radiation dose in abdominopelvic CT scans, aiming to identify significant predictors of radiation exposure. Methods: Employing a cross-sectional analysis of patient data, including BMI, abdominal fat, waist, abdomen, and hip circumference, we analyzed their relationship with the following dose metrics: the CTDIvol, DLP, and SSDE. Results: Results from the analysis of various body measurements revealed that BMI, abdominal fat, and waist circumference are strongly correlated with increased radiation doses. Notably, the SSDE, as a more patient-centric dose metric, showed significant positive correlations, especially with waist circumference, suggesting its potential as a key predictor for optimizing radiation doses. Conclusions: The findings suggest that incorporating patient-specific body metrics into CT dosimetry could enhance personalized care and radiation safety. Conclusively, this study highlights the necessity for tailored imaging protocols based on individual body metrics to optimize radiation exposure, encouraging further research into predictive models and the integration of these metrics into clinical practice for improved patient management.
Advanced Imaging of Shunt Valves in Cranial CT Scans with Photon-Counting Scanner
Authors: Klempka Anna , Ackermann Eduardo , Brehmer Stefanie , Clausen Sven , Groden Christoph
Published: May 2024

This brief report aimed to show the utility of photon-counting technology alongside standard cranial imaging protocols for visualizing shunt valves in a patient’s cranial computed tomography scan. Photon-counting CT scans with cranial protocols were retrospectively surveyed and four types of shunt valves were encountered: proGAV 2.0®, M.blue®, Codman Certas®, and proSA®. These scans were compared with those obtained from non-photon-counting scanners at different time points for the same patients. The analysis of these findings demonstrated the usefulness of photon-counting technology for the clear and precise visualization of shunt valves without any additional radiation or special reconstruction patterns. The enhanced utility of photon-counting is highlighted by providing superior spatial resolution compared to other CT detectors. This technology facilitates a more accurate characterization of shunt valves and may support the detection of subtle abnormalities and a precise assessment of shunt valves.
Robotic Surgical Techniques in Transplantation: A Comprehensive Review
Authors: Di Pangrazio Marco , Pinto Federico , Martinino Alessandro , Toti Francesco , Pozza Gioia , Giovinazzo Francesco
Published: May 2024

In the field of surgery, the idea of performing organ transplants in a minimally invasive fashion has always been a significant technical challenge. The advent of the robotic approach facilitated the overcoming of difficulties in highly complex surgical procedures that demand high technical skill. Furthermore, robotic transplants are showing significant benefits in patient outcomes, particularly in the obese population. The purpose of this review is to provide an overview of the current state of robotics applications for transplant surgery. Kidney transplants were the first to be performed using a fully robotic approach. Since then, robotic surgery has gradually been applied to other organ transplants, with very recent reports of fully robotic lung and liver transplants. Further experiences and studies will be needed to verify their effectiveness and to satisfy some concerns regarding the longer warm ischemia time related to the robotic approach in comparison with open surgery.
EcoHIV Infection of Primary Murine Brain Cell Cultures to Model HIV Replication and Neuropathogenesis
Authors: Kim Boe-Hyun , Chao Wei , Hadas Eran , Borjabad Alejandra , Potash Mary Jane , Volsky David J.
Published: May 2024

Background. EcoHIV is a chimeric HIV that replicates in mice in CD4+ T cells, macrophages, and microglia (but not in neurons), causing lasting neurocognitive impairment resembling neurocognitive disease in people living with HIV. The present study was designed to develop EcoHIV-susceptible primary mouse brain cultures to investigate the indirect effects of HIV infection on neuronal integrity. Results. We used two EcoHIV clones encoding EGFP and mouse bone marrow-derived macrophages (BMM), mixed mouse brain cells, or enriched mouse glial cells from two wild-type mouse strains to test EcoHIV replication efficiency, the identity of productively infected cells, and neuronal apoptosis and integrity. EcoHIV replicated efficiently in BMM. In mixed brain cell cultures, EcoHIV targeted microglia but did not cause neuronal apoptosis. Instead, the productive infection of the microglia activated them and impaired synaptophysin expression, dendritic density, and axonal structure in the neurons. EcoHIV replication in the microglia and neuronal structural changes during infection were prevented by culture with an antiretroviral. Conclusions. In murine brain cell cultures, EcoHIV replication in the microglia is largely responsible for the aspects of neuronal dysfunction relevant to cognitive disease in infected mice and people living with HIV. These cultures provide a tool for further study of HIV neuropathogenesis and its control.
A Longitudinal Analysis of Mortality Related to Chronic Viral Hepatitis and Hepatocellular Carcinoma in the United States
Authors: Ozturk N. Begum , Pham Hoang Nhat , Mouhaffel Rama , Ibrahim Ramzi , Alsaqa Marwan , Gurakar Ahmet , Saberi Behnam
Published: May 2024

(1) Background: Hepatocellular carcinoma (HCC) contributes to the significant burden of cancer mortality in the United States (US). Despite highly efficacious antivirals, chronic viral hepatitis (CVH) remains an important cause of HCC. With advancements in therapeutic modalities, along with the aging of the population, we aimed to assess the contribution of CVH in HCC-related mortality in the US between 1999–2020. (2) Methods: We queried all deaths related to CVH and HCC in the multiple-causes-of-death files from the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) database between 1999–2020. Using the direct method of standardization, we adjusted all mortality information for age and compared the age-adjusted mortality rates (AAMRs) across demographic populations and by percentile rankings of social vulnerability. Temporal shifts in mortality were quantified using log-linear regression models. (3) Results: A total of 35,030 deaths were identified between 1999–2020. The overall crude mortality increased from 0.27 in 1999 to 8.32 in 2016, followed by a slight reduction to 7.04 in 2020. The cumulative AAMR during the study period was 4.43 (95% CI, 4.39–4.48). Males (AAMR 7.70) had higher mortality rates compared to females (AAMR 1.44). Mortality was higher among Hispanic populations (AAMR 6.72) compared to non-Hispanic populations (AAMR 4.18). Higher mortality was observed in US counties categorized as the most socially vulnerable (AAMR 5.20) compared to counties that are the least socially vulnerable (AAMR 2.53), with social vulnerability accounting for 2.67 excess deaths per 1,000,000 person-years. (4) Conclusions: Our epidemiological analysis revealed an overall increase in CVH-related HCC mortality between 1999–2008, followed by a stagnation period until 2020. CVH-related HCC mortality disproportionately affected males, Hispanic populations, and Black/African American populations, Western US regions, and socially vulnerable counties. These insights can help aid in the development of strategies to target vulnerable patients, focus on preventive efforts, and allocate resources to decrease HCC-related mortality.
SARS-CoV-2 Omicron: Viral Evolution, Immune Evasion, and Alternative Durable Therapeutic Strategies
Authors: Guo Hailong , Ha Sha , Botten Jason W. , Xu Kai , Zhang Ningyan , An Zhiqiang , Strohl William R. , Shiver John W. , Fu Tong-Ming
Published: May 2024

Since the SARS-CoV-2 Omicron virus has gained dominance worldwide, its continual evolution with unpredictable mutations and patterns has revoked all authorized immunotherapeutics. Rapid viral evolution has also necessitated several rounds of vaccine updates in order to provide adequate immune protection. It remains imperative to understand how Omicron evolves into different subvariants and causes immune escape as this could help reevaluate the current intervention strategies mostly implemented in the clinics as emergency measures to counter the pandemic and, importantly, develop new solutions. Here, we provide a review focusing on the major events of Omicron viral evolution, including the features of spike mutation that lead to immune evasion against monoclonal antibody (mAb) therapy and vaccination, and suggest alternative durable options such as the ACE2-based experimental therapies superior to mAbs to address this unprecedented evolution of Omicron virus. In addition, this type of unique ACE2-based virus-trapping molecules can counter all zoonotic SARS coronaviruses, either from unknown animal hosts or from established wild-life reservoirs of SARS-CoV-2, and even seasonal alpha coronavirus NL63 that depends on human ACE2 for infection.
Single Amino Acid Substitution in the Matrix Protein of Rabies Virus Is Associated with Neurovirulence in Mice
Authors: Harada Michiko , Matsuu Aya , Kaku Yoshihiro , Okutani Akiko , Inoue Yusuke , Posadas-Herrera Guillermo , Inoue Satoshi , Maeda Ken
Published: May 2024

Rabies is a fatal encephalitic infectious disease caused by the rabies virus (RABV). RABV is highly neurotropic and replicates in neuronal cell lines in vitro. The RABV fixed strain, HEP-Flury, was produced via passaging in primary chicken embryonic fibroblast cells. HEP-Flury showed rapid adaptation when propagated in mouse neuroblastoma (MNA) cells. In this study, we compared the growth of our previously constructed recombinant HEP (rHEP) strain—based on the sequence of the HEP (HEP-Flury) strain—with that of the original HEP strain. The original HEP strain exhibited higher titer than rHEP and a single substitution at position 80 in the matrix (M) protein M(D80N) after incubation in MNA cells, which was absent in rHEP. In vivo, intracerebral inoculation of the rHEP-M(D80N) strain with this substitution resulted in enhanced viral growth in the mouse brain and a significant loss of body weight in the adult mice. The number of viral antigen-positive cells in the brains of adult mice inoculated with the rHEP-M(D80N) strain was significantly higher than that with the rHEP strain at 5 days post-inoculation. Our findings demonstrate that a single amino acid substitution in the M protein M(D80N) is associated with neurovirulence in mice owing to adaptation to mouse neuronal cells.
Winged Threat on the Offensive: A Literature Review Due to the First Identification of Aedes japonicus in Poland
Authors: Gierek Marcin , Ochała-Gierek Gabriela , Woźnica Andrzej Józef , Zaleśny Grzegorz , Jarosz Alicja , Niemiec Paweł
Published: May 2024

Genetic studies preceded by the observation of an unknown mosquito species in Mikołów (Poland) confirmed that it belongs to a new invasive species in Polish fauna, Aedes japonicus (Theobald, 1901), a known vector for numerous infectious diseases. Ae. japonicus is expanding its geographical presence, raising concerns about potential disease transmission given its vector competence for chikungunya virus, dengue virus, West Nile virus, and Zika virus. This first genetically confirmed identification of Ae. japonicus in Poland initiates a comprehensive review of the literature on Ae. japonicus, its biology and ecology, and the viral infections transmitted by this species. This paper also presents the circumstances of the observation of Ae. japonicus in Poland and a methodology for identifying this species.
The Adaptive Immune Response in Hepatitis B Virus-Associated Hepatocellular Carcinoma Is Characterized by Dysfunctional and Exhausted HBV-Specific T Cells
Authors: Broholm Malene , Mathiasen Anne-Sofie , Apol Ása Didriksen , Weis Nina
Published: May 2024

This systematic review investigates the immunosuppressive environment in HBV-associated hepatocellular carcinoma (HCC), characterized by dysfunctional and exhausted HBV-specific T cells alongside an increased infiltration of HBV-specific CD4+ T cells, particularly regulatory T cells (Tregs). Heightened expression of checkpoint inhibitors, notably PD-1, is linked with disease progression and recurrence, indicating its potential as both a prognostic indicator and a target for immunotherapy. Nevertheless, using PD-1 inhibitors has shown limited effectiveness. In a future perspective, understanding the intricate interplay between innate and adaptive immune responses holds promise for pinpointing predictive biomarkers and crafting novel treatment approaches for HBV-associated HCC.