bluuebunny/crossref_metadata_2025 huggingface dataset:
Produced Water from the Oil and Gas Industry as a Resource—South Kuwait as a Case Study
Authors: Alsalem Feras , Thiemann Thies
Published: August 2024

Produced Water (PW) represents the largest waste stream in the oil and gas industry. As a water resource and as a source of valuable minerals such as alkali salts, it is has been highly under-valued, especially in hyper-arid regions. The beneficial use of PW ranges from water reinjection to elevated oil recovery from reservoirs with almost instantaneous returns, to the extraction of minerals from PW, which involves a number of different processes and setups. The economic value of PW-derived end products offers alternative revenue sources, with market fluctuations and conditions different from those of the hydrocarbon market. The end products of water and industrial salt support local industries such as agriculture, reflecting positively on the gross domestic product (GDP). Furthermore, resource extraction from PW of the oil and gas industry helps countries augment their circular economy. In this regard, the economic feasibility of three scenarios—the use of PW for oil recovery, the use of PW as an alternate source of water and industrial salt, and a hybrid process of both—is explored. The results show that there is great potential for water reuse in Enhanced Oil Recovery operations, as well as in the reduction in freshwater consumption for oil- and gas-extraction operations in the state of Kuwait by up to 4.8 percent when PW generated by SK oilfields is considered, and by 42 percent if PW from all oilfields in Kuwait is reused in the same manner.
Low-Cost Cable-Driven Robot Arm with Low-Inertia Movement and Long-Term Cable Durability
Authors: Nguyen Van Pho , Chow Wai Tuck , Dhyan Sunil Bohra , Zhang Bohan , Han Boon Siew , Wong Hong Yee Alvin
Published: August 2024

Our study presents a novel design for a cable-driven robotic arm, emphasizing low cost, low inertia movement, and long-term cable durability. The robotic arm shares similar specifications with the UR5 robotic arm, featuring a total of six degrees of freedom (DOF) distributed in a 1:1:1:3 ratio at the arm base, shoulder, elbow, and wrist, respectively. The three DOF at the wrist joints are driven by a cable system, with heavy motors relocated from the end-effector to the shoulder base. This repositioning results in a lighter cable-actuated wrist (weighing 0.8 kg), which enhances safety during human interaction and reduces the torque requirements for the elbow and shoulder motors. Consequently, the overall cost and weight of the robotic arm are reduced, achieving a payload-to-body weight ratio of 5:8.4 kg. To ensure good positional repeatability, the shoulder and elbow joints, which influence longer moment arms, are designed with a direct-drive structure. To evaluate the design’s performance, tests were conducted on loading capability, cable durability, position repeatability, and manipulation. The tests demonstrated that the arm could manipulate a 5 kg payload with a positional repeatability error of less than 0.1 mm. Additionally, a novel cable tightener design was introduced, which served dual functions: conveniently tightening the cable and reducing the high-stress concentration near the cable locking end to minimize cable loosening. When subjected to an initial cable tension of 100 kg, this design retained approximately 80% of the load after 10 years at a room temperature of 24 °C.
Leveraging Multi-Temporal InSAR Technique for Long-Term Structural Behaviour Monitoring of High-Speed Railway Bridges
Authors: Kim Winter , Lee Changgil , Kim Byung-Kyu , Kim Kihyun , Lee Ilwha
Published: August 2024

The effective monitoring of railway facilities is crucial for safety and operational efficiency. This study proposes an enhanced remote monitoring technique for railway facilities, specifically bridges, using satellite radar InSAR (Interferometric Synthetic Aperture Radar) technology. Previous studies faced limitations such as insufficient data points and challenges with topographical and structural variations. Our approach addresses these issues by analysing displacements from 30 images captured by the X-band SAR satellite, TerraSAR-X, over two years. We tested each InSAR parameter to develop an optimal set of parameters, applying the technique to a post-tensioned PSC (pre-stressed concrete) box bridge. Our findings revealed a recurring arch-shaped elevation along the bridge, attributed to temporal changes and long-term deformation. Further analysis showed a strong correlation between this deformation pattern and average surrounding temperature. This indicates that our technique can effectively identify micro-displacements due to temperature changes and structural deformation. Thus, the technique provides a theoretical foundation for improved SAR monitoring of large-scale social overhead capital (SOC) facilities, ensuring efficient maintenance and management.
Efficient Jamming Policy Generation Method Based on Multi-Timescale Ensemble Q-Learning
Authors: Qian Jialong , Zhou Qingsong , Li Zhihui , Yang Zhongping , Shi Shasha , Xu Zhenjia , Xu Qiyun
Published: August 2024

With the advancement of radar technology toward multifunctionality and cognitive capabilities, traditional radar countermeasures are no longer sufficient to meet the demands of countering the advanced multifunctional radar (MFR) systems. Rapid and accurate generation of the optimal jamming strategy is one of the key technologies for efficiently completing radar countermeasures. To enhance the efficiency and accuracy of jamming policy generation, an efficient jamming policy generation method based on multi-timescale ensemble Q-learning (MTEQL) is proposed in this paper. First, the task of generating jamming strategies is framed as a Markov decision process (MDP) by constructing a countermeasure scenario between the jammer and radar, while analyzing the principle radar operation mode transitions. Then, multiple structure-dependent Markov environments are created based on the real-world adversarial interactions between jammers and radars. Q-learning algorithms are executed concurrently in these environments, and their results are merged through an adaptive weighting mechanism that utilizes the Jensen–Shannon divergence (JSD). Ultimately, a low-complexity and near-optimal jamming policy is derived. Simulation results indicate that the proposed method has superior jamming policy generation performance compared with the Q-learning algorithm, in terms of the short jamming decision-making time and low average strategy error rate.
Ionospheric TEC Prediction in China during Storm Periods Based on Deep Learning: Mixed CNN-BiLSTM Method
Authors: Ren Xiaochen , Zhao Biqiang , Ren Zhipeng , Xiong Bo
Published: August 2024

Applying deep learning to high-precision ionospheric parameter prediction is a significant and growing field within the realm of space weather research. This paper proposes an improved model, Mixed Convolutional Neural Network (CNN)—Bidirectional Long Short-Term Memory (BiLSTM), for predicting the Total Electron Content (TEC) in China. This model was trained using the longest available Global Ionospheric Maps (GIM)-TEC from 1998 to 2023 in China, and underwent an interpretability analysis and accuracy evaluation. The results indicate that historical TEC maps play the most critical role, followed by Kp, ap, AE, F10.7, and time factor. The contributions of Dst and Disturbance Index (DI) to improving accuracy are relatively small but still essential. In long-term predictions, the contributions of the geomagnetic index, solar activity index, and time factor are higher. In addition, the model performs well in short-term predictions, accurately capturing the occurrence, evolution, and classification of ionospheric storms. However, as the predicted length increases, the accuracy gradually decreases, and some erroneous predictions may occur. The northeast region exhibits lower accuracy but a higher F1 score, which may be attributed to the frequency of ionospheric storm occurrences in different locations. Overall, the model effectively predicts the trends and evolution processes of ionospheric storms.
SPNet: Dual-Branch Network with Spatial Supplementary Information for Building and Water Segmentation of Remote Sensing Images
Authors: Zhao Wenyu , Xia Min , Weng Liguo , Hu Kai , Lin Haifeng , Zhang Youke , Liu Ziheng
Published: August 2024

Semantic segmentation is primarily employed to generate accurate prediction labels for each pixel of the input image, and then classify the images according to the generated labels. Semantic segmentation of building and water in remote sensing images helps us to conduct reasonable land planning for a city. However, many current mature networks face challenges in simultaneously attending to both contextual and spatial information when performing semantic segmentation on remote sensing imagery. This often leads to misclassifications and omissions. Therefore, this paper proposes a Dual-Branch Network with Spatial Supplementary Information (SPNet) to address the aforementioned issues. We introduce a Context-aware Spatial Feature-Extractor Unit (CSF) to extract contextual and spatial information, followed by the Feature-Interaction Module (FIM) to supplement contextual semantic information with spatial details. Additionally, incorporating the Goal-Oriented Attention Mechanism helps in handling noise. Finally, to obtain more detailed branches, a Multichannel Deep Feature-Extraction Module (MFM) is introduced to extract features from shallow-level network layers. This branch guides the fusion of low-level semantic information with high-level semantic information. Experiments were conducted on building and water datasets, respectively. The results indicate that the segmentation accuracy of the model proposed in this paper surpasses that of other existing mature models. On the building dataset, the mIoU reaches 87.57, while on the water dataset, the mIoU achieves 96.8, which means that the model introduced in this paper demonstrates strong generalization capabilities.
MCG-RTDETR: Multi-Convolution and Context-Guided Network with Cascaded Group Attention for Object Detection in Unmanned Aerial Vehicle Imagery
Authors: Yu Chushi , Shin Yoan
Published: August 2024

In recent years, object detection in unmanned aerial vehicle (UAV) imagery has been a prominent and crucial task, with advancements in drone and remote sensing technologies. However, detecting targets in UAV images pose challenges such as complex background, severe occlusion, dense small targets, and lighting conditions. Despite the notable progress of object detection algorithms based on deep learning, they still struggle with missed detections and false alarms. In this work, we introduce an MCG-RTDETR approach based on the real-time detection transformer (RT-DETR) with dual and deformable convolution modules, a cascaded group attention module, a context-guided feature fusion structure with context-guided downsampling, and a more flexible prediction head for precise object detection in UAV imagery. Experimental outcomes on the VisDrone2019 dataset illustrate that our approach achieves the highest AP of 29.7% and AP50 of 58.2%, surpassing several cutting-edge algorithms. Visual results further validate the model’s robustness and capability in complex environments.
Using Modern Contraception While Wanting a Child: What Does Contraceptive Over-Use Mean for the Human Rights-Based Approach in Burkina Faso? Insights from PMA2020 Data
Authors: Zan Moussa Lonkila , Sauvain-Dugerdil Claudine , Rossier Clémentine
Published: August 2024

(1) Background: Sustainable development goal 5.6 calls for “universal access to sexual and reproductive health and reproductive rights” to fulfil sexual and reproductive practices. The capability approach helps refine the analysis of contraceptive use by going beyond the dichotomous view of contraceptive use as use/non-use to focus on women’s freedom to choose what they have good reason to value. Using the case of Burkina Faso, we probe more deeply into whether contraceptive use reflects real progress in women’s reproductive rights to realize the fertility projects they value. (2) Methods: We use PMA2020 data collected in Burkina Faso between December 2018 and January 2019. The survey included 3329 women with a participation rate of 97.7%. The PMA2020 female core questionnaire solicits information on fertility and contraceptive behavior, much like the DHS. We asked a series of specific questions about cognitive and psychosocial access relating to FP. We examined bivariate associations between our outcome measure “contraceptive behavior” and a set of independent variables. We also used logistic regression models to evaluate associations with endowments/conversion and capability factors and current functioning by focusing on overuse (i.e., use of contraceptives despite desiring pregnancy within the next 12 months). (3) Results: Women who said their ideal number of children was “up to God” had the highest level of overuse, which was also higher among women living in communities with medium acceptance of contraception and greater support for fertility. Women who have higher and middle levels of information tend to engage less in overuse than those with lower information levels. (4) Conclusions: We conclude that overuse (contraceptive use when desiring a child soon) may reveal a lack of rights, as it is associated with a lack of information about contraceptives and women’s inability to conceive an ideal number of children. Efforts should be made to enhance women’s level of contraceptive information.
Sustainable Waste Management in Japan: Challenges, Achievements, and Future Prospects: A Review
Authors: Moshkal Madina , Akhapov Yerlan , Ogihara Atsushi
Published: August 2024

Japan is subject to global interest due to its waste management system, which aims for sustainability and is known for its efficiency. The purpose of this study is to examine Japan’s steps towards sustainable waste management practices and highlight its formation, achievements, problems, and prospects for the future. Through a comprehensive review of official governmental data and the academic literature, the main achievements—including extensive government initiatives such as proposing programs, plans, and legislation for sustainable waste management and encouraging public involvement in establishing a Sound Material-Cycle Society (SMCS) and 3Rs—were defined. Thus, the state and the population alike take general measures to combat pollution. Looking at the future of waste management in Japan, the country continues to struggle despite all these efforts and impressive results. It is focusing on developing more sustainable and cost-effective solutions. This includes investing in new technologies, increasing efforts to reduce and recycle waste, and promoting environmental awareness.
The Emission Characteristics of VOCs and Environmental Health Risk Assessment in the Plywood Manufacturing Industry: A Case Study in Shandong Province
Authors: Du Weiyan , Xie Huan , Li Jiao , Guan Xu , Li Miaomiao , Wang Haolin , Wang Xinfeng , Zhang Xin , Zhang Qingzhu
Published: August 2024

The current emission characteristics of volatile organic compounds (VOCs) in the plywood manufacturing industry are not yet clearly understood, and their impact on occupational health warrants attention. This study examines VOC concentrations in adhesive-coating and hot-pressing workshops, aiming to discern the emission characteristics and evaluate the health risks to workers. The calculated VOC emission factors range from 1.5 to 3.6 g/m3 for plywood, and an average total VOC concentration of 954.17 μg/m3 is observed. Hot pressing (336.63 μg/m3) and adhesive coating (276.24 μg/m3) substantially contribute to organized and unorganized emissions, respectively. Oxygenated VOCs (OVOCs) (50.79%) predominate, followed by alkanes (16.22%) and halohydrocarbons (15.81%). Formaldehyde, acetone, and acetaldehyde are most prevalent in organized emissions, while dichloromethane, formaldehyde, and methyl methacrylate are dominant in unorganized emissions. Ozone formation potential (OFP) values range from 905.04 to 1822.35 μg/m3, with notable contributions from formaldehyde, methyl methacrylate, and acetaldehyde. Health risk assessments using the total lifetime cancer risk (T-LCR) values suggest potential cancer risks for identified VOCs, particularly formaldehyde in the hot-pressing process. These findings will contribute valuable insights for regional-scale VOC pollution control and offer guidance for minimizing environmental impact and improving occupational health and safety within the plywood manufacturing industry.
Sustainable University Campuses: Temporal and Spatial Characteristics of Lightscapes in Outdoor Spaces
Authors: Li Yating , Wu Shuoxian , Qiu Jianzhen , Wei Tong
Published: August 2024

A lightscape, as a special visual landscape, has unique temporal and spatial characteristics that traditional photometric measurements and descriptions struggle to capture accurately. Despite their significance, there is a lack of in-depth understanding of the on-site perception of lightscapes’ temporal and spatial characteristics, including in outdoor university campus spaces. This study aims to explore the temporal and spatial characteristics of outdoor lightscapes on university campuses and their potential perceptual influencing factors, providing sustainable design, planning, and management suggestions for campus lightscapes. This study was conducted in the Wushan Campus of the South China University of Technology. It employs a “lightwalk” method for on-site perception evaluation, combining qualitative and quantitative approaches to investigate the temporal and spatial characteristics of lightscapes in outdoor university campus spaces and the effect of temporal and spatial factors on lightscape perception. The main findings are as follows: (1) Meteorological, architectural, and biophilic lightscape dominate the outdoor campus lightscapes. (2) The temporal and spatial characteristics of the lightscapes are affected by changes in natural light, the transition of light sources from day to night, human activity patterns, and the functional characteristics of the site. (3) The correlation between meteorological and traffic lightscape types and lightscape perception is diminished during the evening periods. This method should be a good way to optimize water and architectural lightscape at night to alleviate discomfort. (4) In green-shaded spaces, the association between meteorological, architectural, and traffic lightscape types and the evaluations of emotional, luminous, and eventful aspects is significantly enhanced, suggesting an increase in such spaces to improve lightscape experience quality. This study advocates that the construction of buildings and environments should be “human-oriented”, paying attention to the scientific foundation that humans perceive the habitat environment through the “five senses”. Research on lightscapes’ temporal and spatial characteristics, exploration of the temporal and spatial modes of lightscape perception, and avoiding energy waste and light pollution are conducive to the design and construction of university campuses in line with the principles of sustainable development. The lightscape optimization strategies derived from this study can not only provide practical guidance for the design and management of campus but also may offer valuable recommendations for planning sustainable campus development.
The Influence of Three-Dimensional Building Morphology on PM2.5 Concentrations in the Yangtze River Delta
Authors: Zhang Jing , Zhu Wenjian , Dong Dubin , Ren Yuan , Hu Wenhao , Jin Xinjie , He Zhengxuan , Chen Jian , Jin Xiaoai , Zhou Tianhuan
Published: August 2024

The rapid urbanization of urban areas in China has brought about great variation in the layout of cities and serious air pollution. Recently, the focus has been directed toward understanding the role of urban morphology in the generation and spread of atmospheric pollution, particularly in PM2.5 emissions. However, there have been limited investigations into the impact of three-dimensional (3D) features on changes in PM2.5 concentrations. By analyzing a wealth of data on building structures based on a mixed linear model and variance partition analysis in the Yangtze River Delta throughout 2018, this study sought to examine the associations between PM2.5 concentrations and urban building form, and further compared the contributions of two-dimensional (2D) and 3D building features. The findings revealed that both 2D and 3D building forms played an important role in PM2.5 concentrations. Notably, the greater contribution of 3D building forms on PM2.5 concentrations was observed, especially during the summer, where they accounted for 20% compared to 7% for 2D forms. In particular, the building height range emerged as a crucial local factor affecting PM2.5 concentrations, contributing up to 12%. Moreover, taller buildings with more variability in height were found to aid in the dispersion of pollution. These results underscore the substantial contribution of 3D building morphology to PM2.5 pollution, contrasting with previous studies. Furthermore, compact buildings were linked to lower pollution levels, and an urban landscape characterized by polycentric urban structures and lower fragmentation was deemed more favorable for sustainable urban development. This study is significant in investigating the contribution of 3D morphology to PM2.5 and its importance for pollution dispersion mechanisms. It suggests the adoption of a polycentric urban form with a broader range of building heights in urban planning for local governments in the Yangtze River Delta.
Correction: Amran Shah et al. Emotional Intelligence as a Mediator between Parenting Style and Antisocial Behavior among Youth in Malaysia. Sustainability 2023, 15, 12811
Authors: Amran Shah Afiqah , Rathakrishnan Balan , Bikar Singh Soon Singh , Kamaluddin Mohammad Rahim , Yahaya Azizi , Ab Rahman Zaizul
Published: August 2024

The authors would like to make the following corrections to the published paper [1]:(1)Replacing the Author Affiliations section with a new added author: [...]
Analysis of Taxi Demand and Traffic Influencing Factors in Urban Core Area Based on Data Field Theory and GWR Model: A Case Study of Beijing
Authors: Zhang Man , Tian Dongwei , Liu Jingming , Li Xuehua
Published: August 2024

Urban transportation constitutes a complex and dynamic system influenced by various factors, including population density, infrastructure, economic activities, and individual travel behavior. Taxis, as a widespread mode of transportation in many cities, play a crucial role in meeting the transportation needs of urban residents. By using data field theory and the Geographically Weighted Regression (GWR) modeling method, this study explored the complex relationship between taxi demand and traffic-related factors in urban core areas and revealed the potential factors affecting taxi starting and landing points. This research reveals that during the morning peak hours (7:00–9:00), at locations such as long-distance bus terminals, bus stations, parking areas, train stations, and bike-sharing points, taxi demand significantly increases, particularly in the central and southeastern regions of the urban core. Conversely, demand is lower in high-density intersection areas. Additionally, proximity to train stations is positively correlated with higher taxi demand, likely related to the needs of long-distance travelers. During the evening peak hours (17:00–19:00), the taxi demand pattern resembles that of the morning peak, with long-distance bus terminals, bus stations, and parking and bike sharing areas remaining key areas of demand. Notably, parking areas frequently serve as pick-up points for passengers during this time, possibly associated with evening activities and entertainment. Moreover, taxi demand remains high around train stations. In summary, this study enhances our understanding of the dynamics of urban taxi demand and its relationship with various transportation-related influencing factors within the core urban areas. The proposed grid partitioning and GWR modeling methods provide valuable insights for urban transportation planners, taxi service providers, and policymakers, facilitating service optimization and improved urban mobility.
Research on Nondestructive Testing Technology for Drilling Risers Based on Magnetic Memory and Deep Learning
Authors: Liu Xiangyuan , Fan Jianchun
Published: August 2024

Drilling risers play a crucial role in deepwater oil and gas development, and any compromise in their integrity can severely hinder the progress of drilling operations. In light of this, efficient and accurate nondestructive testing of drilling risers is paramount. However, existing inspection equipment falls short in both efficiency and accuracy, posing challenges to the sustainability of deepwater oil and gas exploration and development. To effectively assess the damage conditions of deepwater drilling risers, this study developed an inspection robot based on metal magnetic memory and researched intelligent defect recognition methods using computer vision. The robot can perform in situ inspections on drilling risers and has been successfully deployed for field application on a deepwater drilling platform. The application results demonstrate that this detection robot offers significant advantages regarding high reliability and detection efficiency. Utilizing data collected on-site, we constructed a dataset containing 1100 images that cover five typical types of defects in drilling risers, including pitting, groove corrosion, and wear. Based on this dataset, we proposed and trained a novel image classification model, SK-ConvNeXt-KAN. By deeply optimizing the ConvNeXt convolutional network incorporating the introduced SK attention module and replacing traditional linear classification layers with the KAN module, this model significantly enhanced its feature extraction capabilities and efficiency in handling complex nonlinear problems. Experimental results show that this model achieved an accuracy rate of 95.4% in identifying defects in drilling risers, which is significantly better than traditional methods. This achievement has dramatically improved the efficiency and accuracy of deepwater drilling riser inspections, providing robust technical support for deepwater oil and gas exploration and development sustainability.
Exploring Industrial Engineering Knowledge and Environmental Sustainability
Authors: Roopa Meelan , Siriram Rajenlall , Coetzee Rojanette
Published: August 2024

This research identifies the relationship between industrial engineering and environmental sustainability knowledge components. A combination of a systematic literature review (SLR) and applied thematic analysis (ATA) is employed to uncover the pertinent literature associated with the purpose of this research. Whilst various forms of strategies, theories, methods, and practices were uncovered in each of the knowledge components, only a few were overlapping. These overlapping components include green supply chain operations, circular economy, and technology management. This study is the first in a series of studies contextualising industrial engineering knowledge in terms of its applicability to environmental sustainability. These results reveal concepts from industrial engineering and environmental sustainability knowledge components that can be used to systematically design methodologies or practically implement them in an industry or organisation. Methods and practices were a dedicated theme in the analysis, and these can be used by practitioners. A circle packing diagram is crafted using the IISE Body of Knowledge as a means of categorisation. This study considered industrial engineering as a catalyst in creating new forms of transdisciplinary knowledge areas. It also considers how industrial engineering knowledge can contribute to meeting environmental challenges.
The Influencing Mechanism of Household Food Purchasing Behavior and Household Reserve Efficiency under Non-Normal Conditions
Authors: Jiang Qijun , Meng Qingyuan , Chen Xiao
Published: August 2024

Family reserves are an important part of national reserves, and how to do a good job in family reserves is a common concern of the government and society. Under the non-normal conditions of major accidents and disasters, wars, plagues, social unrest, etc., urban food supply mainly depends on external supply guarantee, and urban residents’ risk perception is more sensitive. Based on the Theory of Planned Behavior and Norm Activation Model, this study constructs an analytical framework for the risk perception, perceived behavior control, and family reserve efficacy of urban residents under non-normal conditions from the perspectives of rationality and sensibility, self-interest, and altruism. The perceived behavior control of household food reserves in non-normal conditions is affected by risk perception, subjective norms, and personal norms. On this basis, countermeasures and suggestions are put forward: Urban residents should strengthen their sense of risk and responsibility for storing food at home, reserve food appropriately, and develop a good habit of family saving. On the other hand, it is necessary to pay attention to personal norms, reduce the negative impact of subjective norms on residents, and avoid excessive food storage and food waste.
Improving Transfer Connectivity in Railway Timetables Based on Closeness Centrality: The Case of the European International Network
Authors: Calzada-Infante Laura , Adenso-Díaz Belarmino , Carbajal Santiago García
Published: August 2024

Could the connectivity of a global railway network increase through small changes in the timetable services? When designing railway schedules, transfer connections to intermediate stations may not be the primary focus considered. However, they may have an important influence on connectivity. In this paper, we study the potential improvement in connections by introducing small changes to the current schedules, using real timetables from all international railway services in Europe. The modelling was completed using the Complex Networks methodology and performance was measured based on total closeness centrality. Various factors are considered to calibrate the necessary amendments to provide a better traveller service, including connection times at stations and different allowed levels of schedule changes. The results indicate that by changing the schedule of only 1% of the services by at most 10 min, the connectivity improvement is remarkable. Railway companies should consider this result in order to expand the potential use of the international railway service at a time when public transportation must be encouraged.
Non-HIV Vaccine-Induced Immune Responses as Potential Baseline Immunogenicity Predictors of ALVAC-HIV and AIDSVAX B/E-Induced Immune Responses
Authors: Huang Ying , Alam Shomoita , Andersen-Nissen Erica , Carpp Lindsay N. , Dintwe One B. , Flach Britta S. , Grunenberg Nicole , Laher Fatima , De Rosa Stephen C. , Ferrari Guido , Innes Craig , Bekker Linda-Gail , Kublin James G. , McElrath M. Juliana , Tomaras Georgia D. , Gray Glenda E. , Gilbert Peter B.
Published: August 2024

Identifying correlations between immune responses elicited via HIV and non-HIV vaccines could aid the search for correlates of HIV protection and increase statistical power in HIV vaccine-efficacy trial designs. An exploratory objective of the HVTN 097 phase 1b trial was to assess whether immune responses [focusing on those supported as correlates of risk (CoR) of HIV acquisition] induced via the RV144 pox-prime HIV vaccine regimen correlated with those induced via tetanus toxoid (TT) and/or hepatitis B virus (HBV) vaccines. We measured TT-specific and HBV-specific IgG-binding antibody responses and TT-specific and HBV-specific CD4+ T-cell responses at multiple time points in HVTN 097 participants, and we assessed their correlations at peak time points with HIV vaccine (ALVAC-HIV and AIDSVAX B/E)-induced responses. Four correlations were significant [false discovery rate-adjusted p-value (FDR) ≤ 0.2]. Three of these four were with IgG-binding antibody responses to TT measured one month after TT receipt, with the strongest and most significant correlation [rho = 0.368 (95% CI: 0.096, 0.588; p = 0.008; FDR = 0.137)] being with IgG-binding antibody responses to MN gp120 gDneg (B protein boost) measured two weeks after the second ALVAC-HIV and AIDSVAX B/E boost. The fourth significant correlation [(rho = 0.361; 95% CI: 0.049, 0.609; p = 0.021; FDR = 0.137)] was between CD4+ T-cell responses to a hepatitis B surface antigen peptide pool, measured 2 weeks after the third HBV vaccination, and IgG-binding antibody responses to gp70BCaseAV1V2 (B V1V2 immune correlate), measured two weeks after the second ALVAC-HIV and AIDSVAX B/E boost. These moderate correlations imply that either vaccine, TT or HBV, could potentially provide a moderately useful immunogenicity predictor for the ALVAC-HIV and AIDSVAX B/E HIV vaccine regimen.
Design, Immunogenicity and Preclinical Efficacy of the ChAdOx1.COVconsv12 Pan-Sarbecovirus T-Cell Vaccine
Authors: Wee Edmund G.-T. , Kempster Sarah , Ferguson Deborah , Hall Joanna , Ham Claire , Morris Susan , Crook Alison , Gilbert Sarah C. , Korber Bette , Almond Neil , Hanke Tomáš
Published: August 2024

During the COVID-19 pandemic, antibody-based vaccines targeting the SARS-CoV-2 spike glycoprotein were the focus for development because neutralizing antibodies were associated with protection against the SARS-CoV-2 infection pre-clinically and in humans. While deploying these spike-based vaccines saved millions of lives worldwide, it has become clear that the immunological mechanisms of protection against severe disease are multifaceted and involve non-neutralizing antibody components. Here, we describe a novel pan-sarbecovirus T-cell vaccine, ChAdOx1.COVconsv12, designed to complement and broaden the protection of spike vaccines. The vaccine immunogen COVconsv12 employs the two regions in the viral proteome most conserved among sarbecoviruses, which are delivered by replication-deficient vector ChAdOx1. It directs T cells towards epitopes shared among sarbecoviruses including evolving SARS-CoV-2 variants. Here, we show that ChAdOx1.COVconsv12 induced broad T-cell responses in the BALB/c and C57BL/6 mice. In the Syrian hamster challenge model, ChAdOx1.COVconsv12 alone did not protect against the SARS-CoV-2 infection, but when co-administered with 1/50th of the ChAdOx1 nCoV-19 spike vaccine protective dose, faster recovery and lower oral swab viral load were observed. Induction of CD8+ T cells may decrease COVID-19 severity and extend the T-cell response coverage of variants to match the known (and as yet unknown) members of the β-coronavirus family.
Information Gap Decision-Making Theory-Based Medium- and Long-Term Optimal Dispatching of Hydropower-Dominated Power Grids in a Market Environment
Authors: Wang Peilin , Su Chengguo , Guo Hangtian , Feng Biao , Yuan Wenlin , Jian Shengqi
Published: August 2024

In the high-proportion hydropower market, the fairness of the execution of traded electricity and clean energy consumption are two issues that need to be considered in medium- and long-term dispatching. Aiming at the fairness of medium- and long-term optimal dispatching of hydropower-dominated grids and the problem of water abandonment in the power market environment, this paper proposes a medium- and long-term optimal dispatching method for hydropower-dominated grids based on the information gap decision-making theory (IGDT). Firstly, IGDT is used to establish a two-layer model of medium- and long-term optimal dispatching that considers runoff uncertainty, in which the lower layer solves the maximum value of the maximum difference in the contract power completion rate of the power stations, and the upper layer solves the maximum fluctuation range of the interval inflow. Then, a mixed-integer linear programming (MILP)-based single-layer optimization model is obtained through a variety of linearization techniques, and the model is solved via the CPLEX solver (version 12.10.0). The medium- and long-term optimal dispatching of 10 thermal power stations and 22 hydropower stations in Yunnan Power Grid, China, is taken as an example to verify the proposed model. The results show that the maximum difference in the contracted electricity completion rate of each power station is 0.412, and the amount of abandoned hydropower is reduced by 81.33% compared to when the abandoned water penalty function is not considered. It is proved that the proposed model can effectively alleviate the problems of excessive power generation, insufficient power generation and large-scale hydropower abandonment, which are of great significance for realizing the fair dispatching of hydropower-dominated power grids and promoting clean energy consumption in the market environment.
Characterization and Quantification of Dam Seepage Based on Resistivity and Geological Information
Authors: Jian Jianbo , Lu Jinge , Guo Qifeng , Wang Junzhi , Sun Lu , Mao Deqiang , Wang Yaxun
Published: August 2024

Dam seepage significantly poses a serious threat to both the reservoir safety and the ecological health of the surrounding area. Characterizing and quantifying seepage zones is essential for effective risk mitigation and reinforcement measures. In this study, Electrical Resistivity Tomography (ERT) was applied to detect seepage on a reservoir dam. The ERT survey included three survey lines along the dam. The results indicated low resistivity in seepage zones, showing a distribution extending to the deep section in the middle of the dam and shallow section on both sides of the dam. The reservoir water came out to the ground surface in the downstream from seepage zones. Five seepage models were constructed to quantify seepage based on geological information. The models were further modeled based on the ERT results. Simulated results revealed the annual seepage of the reservoir is 78,880.16 m3. However, 75.5% of the total seepage is contributed by a region representing 50% of the dam. This concentrated seepage should draw the attention of future safety monitoring and reinforcement efforts. This study combines geophysics, geological, and numerical simulation to quantify dam seepage. This allows for the development of more scientifically sound solutions for preventing seepage and improving drainage ability in reservoir dams.
A Novel Dataset Replenishment Strategy Integrating Time-Series InSAR for Refined Landslide Susceptibility Mapping in Karst Regions
Authors: Yang Yajie , Ma Xianglong , Ding Wenrong , Wen Haijia , Sun Deliang
Published: August 2024

The accuracy of landslide susceptibility mapping is influenced by the quality of sample data, factor systems, and assessment methods. This study aims to enhance the representativeness and overall quality of the sample dataset through an effective sample expansion strategy, achieving greater precision and reliability in the landslide susceptibility model. An integrated interpretative framework for landslide susceptibility assessment is developed using the XGBoost-SHAP-PDP algorithm to deeply investigate the key contributing factors of landslides in karst areas. Firstly, 17 conditioning factors (e.g., surface deformation rate, land surface temperature, slope, lithology, and NDVI) were introduced based on field surveys, satellite imagery, and literature reviews, to construct a landslide susceptibility conditioning factor system in line with karst geomorphology characteristics. Secondly, a sample expansion strategy combining the frequency ratio (FR) with SBAS-InSAR interpretation results was proposed to optimize the landslide susceptibility assessment dataset. The XGBoost algorithm was then utilized to build the assessment model. Finally, the SHAP and PDP algorithms were applied to interpret the model, examining the primary contributing factors and their influence on landslides in karst areas from both global and single-factor perspectives. Results showed a significant improvement in model accuracy after sample expansion, with AUC values of 0.9579 and 0.9790 for the training and testing sets, respectively. The top three important factors were distance from mining sites, lithology, and NDVI, while land surface temperature, soil erosion modulus, and surface deformation rate also significantly contributed to landslide susceptibility. In summary, this paper provides an in-depth discussion of the effectiveness of LSM in predicting landslide occurrence in complex terrain environments. The reliability and accuracy of the landslide susceptibility assessment model were significantly improved by optimizing the sample dataset within the karst landscape region. In addition, the research results not only provide an essential reference for landslide prevention and control in the karst region of Southwest China and regional central engineering construction planning but also provide a scientific basis for the prevention and control of geologic hazards globally, showing a wide range of application prospects and practical significance.
Real-Time Optimal Scheduling of a Water Diversion System Using an Improved Wolf-Pack Algorithm and Scheme Library
Authors: Feng Xiaoli , Wang Yongxing , Sun Xiaoyu , Qiu Baoyun
Published: August 2024

A water diversion system (WDS) with cascade pumping stations (CPSs) plays an important role in the application of water resources. However, high energy consumption is reported due to unreasonable scheduling schemes and long decision times. Herein, this paper presents a new method to achieve optimal scheduling schemes effectively, including the head allocation of CPSs, the number of running pumps, and pump blade angles. A double-layer mathematical model for a WDS was established with the goal of achieving minimal energy consumption, considering the constraints of flow rate, water level, and the characteristics of pump units. The inner-layer model was used to obtain scheduling schemes of single-stage pumping stations, as well as the water levels and flow rates of water channels, while the outer-layer model was used to optimize inter-stage head allocation. An improved wolf-pack algorithm (IWPA) was proposed to solve the model, using a Halton sequence to obtain the uniform initial population distribution and introducing simulated annealing (SA) to improve the global searchability. Moreover, an idea for a pre-established scheme library was suggested for inner-layer models to obtain the solutions in real time with less calculation workload. Taking an actual project as a case, in contrast with the actual schemes, the optimal scheduling method could result in energy savings of 14.37–20.39%, a CO2 emission reduction of 13–32 tons per day, and water savings of 0.14–18.34%. Moreover, the time complexity decreased to square order, and the CPU time of the optimal method was about 1% that of the traditional method. This study provides an efficient method for the high-value utilization of energy and water resources for a WDS.
Unlocking Male Youth Soccer Players’ Peak Performance Potential: Exploring the Impact of Maturation, Age, and Physical Demands on Neuromuscular Injury Risk and Recovery Following Competitive Matchplay
Authors: Martin-Garetxana Imanol , Ayala Francisco , De Ste Croix Mark , Larruskain Jon , Lekue Josean , Hughes Jonathan
Published: August 2024

This study investigated the 7-day recovery period post-soccer matches in elite male academy players. We analyzed changes in physical performance, stretch-shortening cycle capability, landing mechanics, muscle damage, and perceived well-being while also considering the influence of players’ maturity status, chronological age, and physical demands on post-match responses. In a prospective, observational, mixed longitudinal study design, twenty-six players (U14 = 14 [age = 13.9 ± 0.2 y, and U16 = 12 [age = 15.1 ± 0.2 y]) undertook testing at baseline (1 h pre-match), immediately post-match (0 h), and 48-, 72-, 96-, and 120 h post-match for measures in creatine kinase (CK), urea (UR), CMJ height, 20 m sprint time, reactive strength index (RSI), leg stiffness (LS), landing mechanics, and perceived well-being. Players were also tested pre [168-h] and post the subsequent match. Results showed significant alterations 0 h post-match in CK (+71.3%), UR (+12.8%), CMJ height (−5.3%), 20 m sprint time (+3.8%), RSI (−9.6%), LS (−11.5%), and perceived well-being (−7.7%), with landing mechanics being unaffected. All parameters returned to baseline at 48 h, except for CK and UR, which remained elevated until 168 h. The players’ initial scores influenced how they responded after the match during the week. In conclusion, coaches should focus on post-match strategies to enhance muscle recovery, especially for youth players with a lower training status, given the extended recovery period observed for muscle damage markers.
Translating in-person care to telehealth: a secondary analysis of GP consultations on musculoskeletal conditions
Authors: Li Yifu , Chan Simon , Lu Lawrence , Jackson Tim M , Rahimi-Ardabili Hania , Lau Annie YS
Published: August 2024

Background

The COVID-19 pandemic led to a rapid transition to telehealth, particularly in general practice where continuous care for chronic conditions, such as musculoskeletal (MSK), is provided.

Aim

To determine the appropriateness of telehealth for MSK conditions by identifying whether in-person tasks can be supported remotely via telehealth.

Design & setting

This study is a secondary analysis of the Harnessing Resources from the Internet (HaRI) dataset. This dataset comprises of 281 videos of recorded GP consultations. The dataset includes 10 GPs, across eight separate clinics, and was collected during 2017 in the UK.

Method

Content analysis was conducted to identify the clinical tasks, physical examinations, and physical artefacts used during the consultations. A scoring method applying two key metrics was developed to assess the translatability of clinical tasks to telehealth.

Results

Across the 31 MSK consultations analysed, 12 clinical tasks, five physical examinations, and 12 physical artefacts were observed. Of clinical tasks, 17% (n= 2/12) were deemed to be ‘easily translatable over telehealth’ and 50% (n= 6/12) were deemed ‘relatively easy to be translated over telehealth’. Only 17% (n= 2/12) of tasks were rated ‘moderately translatable over telehealth’, and 17% (n= 2/12) were deemed ‘potentially translatable over telehealth’. No clinical tasks in this study were categorised as untranslatable to telehealth. The average telehealth translatability score was 7.1/10.

Conclusion

Most clinical tasks observed during in-person GP consultations with patients with MSK conditions are translatable to telehealth. Further research is necessary to investigate the long-term efficacy and safety of telehealth utilisation for MSK conditions in primary care.