bluuebunny/crossref_metadata_2025 huggingface dataset:
Neuromuscular Capabilities in Top-Level Weightlifters and Their Association with Weightlifting Performance
Authors: Soriano Marcos A. , Flores Francisco J. , Lama-Arenales Juan , Fernández-del-Olmo Miguel , Comfort Paul
Published: April 2024

The aim of this study was to determine the associations between the front and back squat, countermovement jump (CMJ) and deep squat jump (DSJ) force–time metrics, and weightlifting performance in top-level weightlifters. Thirteen top-level weightlifters who classified for the World Championship 2023 participated. The heaviest successful snatch and clean and jerk were recorded within a preparation session as performance indicators. The front and back squat one-repetition maximums (1RMs) were evaluated in separate training sessions. The average of three maximum CMJs and DSJs were recorded using a force plate, and jump height, propulsive net impulse, and peak power were calculated for further analysis. Pearson’s correlation coefficients were used to determine the associations between variables. Statistical significance was set at p ≤ 0.05. The front and back squat 1RMs were significant and nearly perfectly associated with weightlifting performance (p < 0.001, r = 0.98–0.99). CMJ and DSJ propulsive net impulse displayed nearly perfect associations with weightlifting performance (p < 0.001, r = 0.96–0.99), while jump height is a less promising metric to assess the weightlifters’ ballistic capabilities. This study reinforces that lower body maximum strength and ballistic capabilities are closely associated with top-level weightlifters’ performance and are of practical importance to monitor their neuromuscular function.
Key Insights from Preflight Planning for Safety Improvement in General Aviation: A Systematic Literature Review
Authors: Lopes Nuno Moura , Neves Fátima Trindade , Aparicio Manuela
Published: April 2024

This study highlights the disproportionate number of fatal and non-fatal accidents in general aviation (GA) compared to airline carriers, emphasizing the need to investigate the contributing factors to these incidents. It identifies poor decision-making and a lack of situational awareness as key issues and presents a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method to analyze preflight information used by GA pilots. The findings underscore the significance of operational factors in ensuring a successful flight and suggest modifications to pilot license renewal processes, with an emphasis on the adoption of digital preflight tools. A new theoretical framework based on the operational factors identified is also introduced, which could serve as a foundation for future studies and interventions aimed at enhancing safety in general aviation.
Research on a Classification Method of Goaf Stability Based on CMS Measurement and the Cloud Matter–Element Model
Authors: Chen Jiazhao , Tan Yuye , Huang Xu , Fu Jianxin
Published: April 2024

The evaluation and classification of goaf stability are fuzzy and random. To address this problem, a new classification method is proposed. A cavity monitoring system is used to detect the goaf, 3DMine and FLAC3D software are used to conduct the 3D visual modeling of the scanning results, and numerical simulation analysis is performed on the goaf. According to the analysis results, the stability classification standard of the goaf is constructed, and the characteristics of each classification are described. The evaluation indicator system of goaf stability is constructed in accordance with similar engineering experience, and the evaluation indicator is weighted by using the analytic hierarchy process. The cloud–element coupling evaluation model is built, the field measured values of indicators are collected, the cloud correlation degree of goafs belonging to each stability level is calculated, the stability level is evaluated according to the principle of maximum membership degree, and the results are compared with the numerical simulation to analyze the reasons for the differences in the stability evaluation results obtained by the two methods and to improve the accuracy of the evaluation of goaf stability. The pillar stress and surrounding rock deformation are monitored in Room 1# of the inclined mining area of Shirengou Iron Mine. The monitoring results are consistent with the evaluation results, which proves the accuracy of the proposed goaf stability classification method.
Analysis of Seismic Response Characteristics of Fractured Carbonate Reservoirs Based on Physical Model (Tarim Basin)
Authors: Wei Li , Di Bangrang , Wei Jianxin
Published: April 2024

Anomalous bright spots, called the string of bead-like response, are typical seismic migration profile features in carbonate fractured reservoirs in the Tarim Basin, and they are indicators of high-quality oil and gas reservoirs. Correctly recognizing the correspondence between fractures and the SBLR can contribute to the efficient drilling of target carbonate fractured reservoirs. Physical models can describe fractured reservoirs more directly and efficiently than real situations and have obvious advantages in accurately and quantitatively designing parameters such as dipping angles and the number of layers of fractured reservoirs. Under such a background, according to the real tectonic characteristics of the Tarim Basin, among the main hydrocarbon reservoirs, fractured reservoirs with various parameters were designed and a physical model was constructed according to the real stratigraphic parameters. After seismic data acquisition and processing, the response characteristics of the string of bead-like response were extracted and summarized from seismic migration profiles for all fractured reservoirs, which provided targeted analyses and discussions on the fracture dipping angle, number of fracture layers, overlying stratigraphic influences, and planar attributes of the fractured reservoirs. In general, the larger the fracture dip, the more difficult it is to identify, while the slope of reflection strength and maximum absolute amplitude attributes can be important markers for fractured reservoir identification. The physical modeling study of fractured reservoirs in this paper can provide a basis for the analysis and prediction of carbonate fractured reservoirs in the Tarim Basin.
A Cobot in the Vineyard: Computer Vision for Smart Chemicals Spraying
Authors: Tomazzoli Claudio , Ponza Andrea , Cristani Matteo , Olivieri Francesco , Scannapieco Simone
Published: April 2024

Precision agriculture (PA) is a management concept that makes use of digital techniques to monitor and optimise agricultural production processes and represents a field of growing economic and social importance. Within this area of knowledge, there is a topic not yet fully explored: outlining a road map towards the definition of an affordable cobot solution (i.e., a low-cost robot able to safely coexist with humans) able to perform automatic chemical treatments. The present study narrows its scope to viticulture technologies, and targets small/medium-sized winemakers and producers, for whom innovative technological advancements in the production chain are often precluded by financial factors. The aim is to detail the realization of such an integrated solution and to discuss the promising results achieved. The results of this study are: (i) The definition of a methodology for integrating a cobot in the process of grape chemicals spraying under the constraints of a low-cost apparatus; (ii) the realization of a proof-of-concept of such a cobotic system; (iii) the experimental analysis of the visual apparatus of this system in an indoor and outdoor controlled environment as well as in the field.
Surface Tension Estimation of Steel above Boiling Temperature
Authors: Volpp Joerg
Published: April 2024

Surface tension is an important characteristic of materials. In particular at high temperatures, surface tension values are often unknown. However, for metals, these values are highly relevant in order to enable efficient industrial processing or simulation of material behavior. Plasma, electron or laser beam processes can induce such high energy inputs, which increase the metal temperatures to, and even above, boiling temperatures, e.g., during deep penetration welding or remote cutting. Unfortunately, both theoretical and experimental methods experience challenges in deriving surface tension values at high temperatures. Material models of metals have limitations in explaining complex ion interactions, and experimentally measuring temperature and surface tension at high temperatures is a challenge for methods and equipment. Therefore, surface wave analysis was conducted in this work to derive surface tension values around the boiling temperature of steel and identify trends. In addition, a simple ion interaction calculation was used to simulate the impacting parameters that define the surface tension. Since both the experimental values and simulation results indicate an increasing trend in surface tension above the boiling temperature, it is concluded that the dominating attractive forces above this temperature should increase with increasing temperature and lead to increasing surface tension forces in the surface layers of liquid metal.
Enhancing Security in Industrial Application Development: Case Study on Self-Generating Artificial Intelligence Tools
Authors: Mateo Sanguino Tomás de J.
Published: April 2024

The emergence of security vulnerabilities and risks in software development assisted by self-generated tools, particularly with regard to the generation of code that lacks due consideration of security measures, could have significant consequences for industry and its organizations. This manuscript aims to demonstrate how such self-generative vulnerabilities manifest in software programming, through a case study. To this end, this work undertakes a methodology that illustrates a practical example of vulnerability existing in the code generated using an AI model such as ChatGPT, showcasing the creation of a web application database, SQL queries, and PHP server-side. At the same time, the experimentation details a step-by-step SQL injection attack process, highlighting the hacker’s actions to exploit the vulnerability in the website’s database structure, through iterative testing and executing SQL commands to gain access to sensitive data. Recommendations on effective prevention strategies include training programs, error analysis, responsible attitude, integration of tools and audits in software development, and collaboration with third parties. As a result, this manuscript discusses compliance with regulatory frameworks such as GDPR and HIPAA, along with the adoption of standards such as ISO/IEC 27002 or ISA/IEC 62443, for industrial applications. Such measures lead to the conclusion that incorporating secure coding standards and guideline—from organizations such as OWASP and CERT training programs—further strengthens defenses against vulnerabilities introduced by AI-generated code and novice programming errors, ultimately improving overall security and regulatory compliance.
The Remaining Life Prediction of Rails Based on Convolutional Bi-Directional Long and Short-Term Memory Neural Network with Residual Self-Attention Mechanism
Authors: Huang Gang , Gong Lin , Zhang Yuhan , Wang Zhongmei , Yuan Songlin
Published: April 2024

In the railway industry, the rail is the basic load-bearing structure of railway tracks. The prediction of the remaining useful life (RUL) for rails is important to avoid unexpected system failures and reduce the cost of maintaining the system. However, the existing detection of rail flaws is difficult, the rail deterioration mechanisms are diverse, and the traditional data-driven methods have insufficient feature extraction. This causes low prediction accuracy. With objectives set in relation to the problems outlined above, a rail RUL prediction approach based on a convolutional bidirectional long- and short-term memory neural network with a residual self-attention (CNNBiLSTM-RSA) mechanism is designed. Firstly, the pre-processed vibration data are taken as the input for the convolutional bi-directional long- and short-term memory neural network (CNNBiLSTM) to extract the forward and backward dependencies and features of the rail data. Secondly, the RSA mechanism is introduced in order to obtain the contributions of the features at different moments during the degradation process of the rail. Finally, an end-to-end RUL prediction implementation based on the convolutional bi-directional long- and short-term memory neural network with the residual self-attention mechanism is established. The experiments were carried out using the full life-cycle data of rails collected at the railway site. The results show that the method achieves a higher accuracy in the RUL prediction of rails.
Analysis of Operated Ankle Fractures in Elderly Patients: Are They All Osteoporotic?
Authors: Rinonapoli Giuseppe , Donantoni Marco , Ceccarini Paolo , Caraffa Auro
Published: April 2024

Background: Osteoporosis represents a global problem, which involves high risks of disability and death due to the consequences of fragility fractures. The aim of our study is to verify what type of relationship there is between ankle fractures and osteoporosis. Specifically, we aim to understand how the clinical and anamnestic characteristics of patients, along with the radiographic features of these fractures, may contribute to considering them as osteoporotic fractures. Methods: The study group includes 51 consecutive patients aged 60 years or older operated for ankle fracture from May to October 2022. The fractures were divided into uni-, bi-, or trimalleolar based on the plain X-rays. All patients underwent femoral and vertebral bone mineralometry by DXA associated with the FRAX questionnaire. Results: Ankle fractures in the elderly were associated with reduced BMD (76.5% of the total patients examined, 83.8% considering only women) and low-energy traumas (82%). Furthermore, these fractures present features of increased complexity as bone mass decreases. Conclusions: Ankle fractures in the elderly exhibit characteristics that suggest a relationship with bone fragility. For these reasons, it might be advisable to initiate a comprehensive fracture risk assessment in elderly patients who experience an ankle fracture. These fractures should not be underrated, and antiresorptive therapy must always be taken into consideration when selecting patients at risk.
K-WISC-V Processing Speed Index Analysis to Verify the Effectiveness of ADHD Symptom Improvement Using Pediatric Digital Content
Authors: Kim Seon-Chil
Published: April 2024

The most common treatment approach for children diagnosed with attention deficit hyperactivity disorder (ADHD) involves drug therapy; however, persuading parents and motivating children in the early stages of treatment is challenging. Consequently, there is a growing interest among parents of children with ADHD in non-drug therapies. Moreover, recent advancements in information and communication technology have increased the accessibility of digital treatments for ADHD and non-drug therapy content. However, some challenges persist in confirming specific and objective effects. In this retrospective study, we developed game-type digital therapy content for children aged 6–16 years and monitored improvements in ADHD symptoms using the K-WISC-V subtest processing speed index. The analysis revealed that the rate of change in the sum of converted scores on the 14th day was 0.64% lower in the experimental group compared with the control group; however, on the 28th day, the rate of change increased by 6.93%. This suggests that the supplementary use of Neuroworld DTx therapy proved effective for visual enhancement. Furthermore, improvements were observed in visual discrimination, short-term memory, and motor cooperation abilities. Consequently, game-based digital content is an effective adjunctive therapy for children dealing with ADHD.
The Impact of Cardiorespiratory and Metabolic Parameters on Match Running Performance (MRP) in National-Level Football Players: A Multiple Regression Analysis
Authors: Radaković Radivoje , Katanić Borko , Stanković Mima , Masanovic Bojan , Fišer Suzana Žilić
Published: April 2024

The aim of the study was to examine the association between cardiorespiratory and metabolic parameters and match running performance (MRP) in highly trained football players. The sample of participants consisted of 41 national-level football players (aged 23.20 ± 3.40 years, body height 182.00 ± 5.15 cm, and body mass 76.86 ± 6.06 kg) from the Serbian Super league. For the purposes of this research, the following measurements were applied. A maximal multistage progressive treadmill test, with a direct measurement of maximal oxygen consumption (VO2max) (using Fitmate MED, Cosmed, Rome, Italy) was conducted, alongside continuous heart rate monitoring. Capillary blood samples were taken from the hyperemic area using specific test strips, and, after sample collection, lactate concentration was immediately determined using a lactate analyzer. MRP variables were analyzed according to the BioIRC model of motion structure analysis, based on existing standards for profiling movement intensity. The results of multiple regression analysis indicated an association between cardiac parameters and total distance (R2 = 54.3%, p = 0.000), high-speed running (R2 = 46.4%, p = 0.000), and jogging (R2 = 33.6%, p = 0.004). Regression analysis revealed an association between cardiorespiratory parameters and total distance (R2 = 24.8%, p = 0.014), and high-speed running (R2 = 20%, p = 0.039). Meanwhile, no association was found between lactate concentration and running performance. The explanation for these regression analysis results is based on the observation that functional abilities represent significant potential for expressing movement performance, a crucial condition for success in football.
Design of Multi-Chain Traceability Model for Pepper Products Based on Traceability Code
Authors: Jin Wenxuan , Zheng Mingjun , Liu Pingzeng
Published: April 2024

In the specific application scenario of pepper product supply chain traceability, with the advancement of pepper product production, the expansion of links, and the increase of nodes, the quantity of data will become more and more enormous. The single-chain model is less efficient for querying if the data are all stored into the same blockchain. In order to improve the efficiency of blockchain data querying, this paper proposes a traceability model with one main chain and multiple side chain structures, which separate the uplinked data from each link and use multi-chain transactions to improve the efficiency of data queries. This model builds an indexing mechanism with a product traceability code, using one main chain and multiple side chains. The main and side chains form a one-to-many mapping relationship, storing the mapping relationship between the traceability code and the transaction address of the side chain traceability information in the main chain. This enables information to travel through the main chain traversal query based on the mapping relationship and then query the direct index out of the side chain, to achieve fast traceability query and improve the efficiency of querying.
A Critical Review of Human Jaw Biomechanical Modeling
Authors: De Stefano Marco , Ruggiero Alessandro
Published: April 2024

The human jaw is a complex biomechanical system involving different anatomical components and an articulated muscular system devoted to its dynamical activation. The numerous actions exerted by the mandible, such as talking, eating or chewing, make its biomechanical comprehension absolutely indispensable. To date, even if research on this topic has achieved interesting outcomes using in vitro testing, thanks to the development of new apparatus and methods capable of performing more and more realistic experiments, theoretical modeling is still worthy of investigation. In light of this, nowadays, the Finite Element Method (FEM) approach constitutes certainly the most common tool adopted to investigate particular issues concerning stress–strain characterization of the human jaw. In addition, kinematics analyses, both direct and inverse, are also diffuse and reported in the literature. This manuscript aimed to propose a critical review of the most recurrent biomechanical models of the human mandible to give readers a comprehensive overview on the topic. In light of this, the numerical approaches, providing interesting outcomes, such as muscular activation profiles, condylar forces and stress–strain fields for the human oral cavity, are mainly differentiated between according to the joint degrees of freedom, the analytical descriptions of the muscular forces, the boundary conditions imposed, the kind of task and mandible anatomical structure modeling.
Impact of Various Cavity-Preparation Designs on Fracture Resistance and Failure Mode of CAD/CAM Fabricated Ceramic Inlays and Onlays
Authors: Elkaffas Ali Atef , Alshehri Abdullah Mohammed , Alqahtani Ali Robaian , Albaijan Refal Saad , Soliman Tarek Ahmed
Published: April 2024

In recent years, CAD/CAM technology has allowed indirect ceramic restorations to become a part of everyday chairside clinical practice. Therefore, the impact of different cavity-preparation designs on the fracture resistance of CAD/CAM fabricated ceramics was assessed in this study. Three designs of cuspal covering (none, palatal, and entire) and two widths of the occlusal isthmus (75% and 100% of the intercuspal distance) were used for the preparation of inlays and onlays to form six groups (n = 10/group). Moreover, thermomechanical cyclic loading was applied to every tooth under a chewing simulator. A universal testing machine was used to measure each group’s fracture resistance. The tested specimens were inspected for any signs of fractures and cracks to categorize failure patterns. Thereby, the values of fracture strength showed that there were statistically nonsignificant differences between the tested groups (p < 0.05). However, a significant difference (p = 0.01) was found between group 1 (inlays) (1950 ± 405) and group 6 (onlays) (3900 ± 770). Type III or type IV fracture modes were seen in the majority of the specimens. In conclusion, inlays and onlays made of zirconia using CAD/CAM technology were deemed reliable for restoring premolars, irrespective of the cavity-preparation design, except for inlays with a 75% intercuspal distance.
Multiplicative Improved Coherence Factor Delay Multiply and Sum Algorithm for Clutter Removal in a Microwave Breast Tumor Imaging System
Authors: Guo Donghao , Wang Jingjing , Liu Huanqing , Bai Yuxi , Li Yongcheng , Liu Weihao
Published: April 2024

In the medical field, microwave imaging technology has experienced rapid development due to its non-invasive and non-radioactive nature. The confocal algorithm is a method commonly used for microwave breast cancer imaging, with the key objective of removing clutter in images to achieve high-quality results. However, the current methods are facing challenges in removing clutter. In order to reduce the clutter in images, a multiplicative improved coherence factor delay multiply and sum algorithm based on the maximum interclass differencing method is proposed. The algorithm compares the starting and ending moments of tumor signals in different channels to determine whether the tumor-scattered signals in different channels overlap in time. An improved coherence coefficient is obtained by summing the non-overlapping signals and multiplying the time window. The multiplicative improved coherence factor, which is obtained by multiplying the coherence coefficients of the improved multi-pair signals, is then multiplied by the focal point intensity obtained using the delay multiply and sum algorithm to reduce clutter in an image. To evaluate the performance of the proposed algorithm, several low-cost uniform and non-uniform models of human breast and tumor tissue with dielectric properties were prepared for testing. The experimental results show that, compared to the existing algorithm, the proposed algorithm can greatly reduce the clutter in images, with a signal-to-clutter ratio of at least 4 dB higher as well as contrast at least six-fold higher.
Preliminary Impact Assessment of the Ad Hoc Separation Minima: A New Separation Mode
Authors: Serrano-Mira Lidia , Sanz Luis Pérez , Pérez-Castán Javier A. , López Adrián Casado , Ayra Eduardo S. , Maroto Marta Pérez
Published: April 2024

A major challenge for the Air Traffic Management system is the need to boost airspace capacity, which is near saturation in some situations. Separation minima are one of the factors related to airspace capacity, and the SESAR program promotes research into advanced separation modes. Ad Hoc separation, a novel separation mode, involves applying different pairwise separation minima in the same volume of airspace depending on a set of factors, such as encounter geometry, aircraft models, and flight level, among others. This research examines the impact of implementing this concept in different en-route scenarios. The goal is to determine whether applying this concept proves advantageous or, conversely, results in an increase in the complexity of the system without significant benefits in the key performance areas of capacity, environment, and cost-efficiency. Fast Time Simulations are conducted in RAMS software, with the concept being implemented in the LECMZMU, LECMTLU, and LECMDGU sectors of the Madrid ACC. The results reveal favorable capacity outcomes with increases of around 2% and the LECMZMU sector exhibits the most significant environmental and cost-efficiency benefits. Furthermore, implementing the Ad Hoc concept in a larger scenario could yield even greater environmental and cost-efficiency benefits.
Development and Validation of a Novel Surface Defect Index (SDI) Method for the Effective Quality Evaluation of Concrete Surfaces
Authors: Badi Fatima Zohra , Bensebti Salah Eddine , Chabane Abdelhafid , Belebchouche Cherif , Ngo Tien Tung , Kadri El Hadj , Czarnecki Slawomir
Published: April 2024

Concrete defects have a significant impact on concrete constructions. These defects should be considered not only aesthetic defects but also structural defects. In this study, a novel Surface Defect Index (SDI) method was developed to quantify the defect volume according to liquids’ penetrating properties by applying ready-mixed plaster (RMP). The SDI refers to the volumetric proportion of all apparent and unapparent defects in a given area of concrete, and it is expressed as a percentage of the total volume affected by defects. The proposed SDI method was validated and tested under various controlled defect configurations. Regardless of the specific characteristics of each defect configuration, the SDI method consistently demonstrated a high level of consistency, repeatability, and reproducibility, with coefficients of variation (CVr and CVR) below 5% and with correlation coefficients of R2 = 0.9968. The method succeeded in assessing the surface quality levels through the SDI, demonstrating a significant correlation between this index and the volume of defects. The proposed index was tested on real concrete surfaces, affirming its efficacy in accurately quantifying the volume of surface defects; thus, it can provide an important metric for quality control. Moreover, it provides an excellent evaluation of the quality of concrete surfaces.
An NLOS Ranging Error Mitigation Method for 5G Positioning in Indoor Environments
Authors: Liu Jingrong , Deng Zhongliang , Hu Enwen
Published: April 2024

Positioning based on wireless signals such as mobile communication networks has become an important means to provide high-precision location services in environments where satellite signals are blocked. In complex environments such as indoors and underground, wireless signal propagation is obstructed and non-line-of-sight (NLOS) phenomena appear due to serious occlusion and reflection. The time delay caused by NLOS effects has little impact on communication system but can significantly increase positioning errors in positioning systems. Therefore, the effective suppression of NLOS errors is crucial to improving 5G positioning accuracy. To address the insufficient feature extraction of existing NLOS error suppression methods, the neglect of residual NLOS measurement errors, and poor stability of position estimation results, this paper innovatively proposes an NLOS mitigation and location estimation method for 5G positioning terminals. Simulation and experimental test results demonstrate that the proposed method outperforms the comparative methods both theoretically and practically, achieving an average positioning accuracy of 1.85 m in complex indoor NLOS environments. The method proposed in this paper provides a new strategy for NLOS error suppression in indoor 5G positioning, which can significantly contribute to high-precision location services based on commercial 5G networks.
WordBlitz: An Efficient Hard-Label Textual Adversarial Attack Method Jointly Leveraging Adversarial Transferability and Word Importance
Authors: Li Xiangge , Luo Hong , Sun Yan
Published: April 2024

Existing textual attacks mostly perturb keywords in sentences to generate adversarial examples by relying on the prediction confidence of victim models. In practice, attackers can only access the prediction label, meaning that the victim model can easily defend against such hard-label attacks by denying access based on the attack’s frequency. In this paper, we propose an efficient hard-label attack approach, called WordBlitz. First, based on the adversarial transferability, we train a substitute model to initialize the attack parameter set, including a candidate pool and two weight tables of keywords and candidate words. Then, adversarial examples are generated and optimized under the guidance of the two weight tables. During optimization, we design a hybrid local search algorithm with word importance to find the globally optimal solution while updating the two weight tables according to the attack results. Finally, the non-adversarial text generated during perturbation optimization is added to the training of the substitute model as data augmentation to improve the adversarial transferability. Experimental results show that WordBlitz surpasses the baseline in terms of better effectiveness, higher efficiency, and lower cost. Its efficiency is especially pronounced in scenarios with broader search spaces, and its attack success rate on a Chinese dataset is higher than on baselines.
Analysis of Intercity Transportation Network Efficiency Using Flow-Weighted Time Circuity: A Case Study of Seven Major City Clusters in China
Authors: Zhu Minqing , Yuan Peng , Cui Hongjun
Published: April 2024

Enhancing the efficiency of intercity transportation networks is crucial for sustainable regional transport development, significantly impacting travel behaviors and energy consumption. The transportation infrastructure within the city cluster is rapidly developing to accommodate the increasing traffic demand, necessitating substantial investments. It is imperative to investigate the effectiveness of intercity traffic within urban clusters, to evaluate the influence of transportation infrastructure enhancements on regional traffic efficiency. Circuity is a conventional metric used to assess the efficiency of transportation networks, primarily emphasizing distance, while overlooking factors such as travel time and traffic flow. In this study, the concept of circuity has been redefined in terms of travel time and has been referred to as the transportation network travel speed. Subsequently, the amalgamation of travel speed within the transportation network and traffic flow culminates in the proposition of Flow-Weighted Time Circuity (FWTC). Real-time intercity navigation data, offering accurate travel time estimations, are utilized to analyze the spatial distribution of intercity transport efficiency in the seven major city clusters of China, via both automobile and train modes of transportation. The results indicate that (1) as the travel distance extends, the speed of transportation within the network typically increases, albeit with increasing fluctuations, especially in the case of intercity train travel; (2) concerning the efficiency of intercity automobile travel, most city clusters demonstrate satisfactory performance, with the exception of the Guanzhong Plain. The Yangtze River Delta and Beijing–Tianjin–Heibei regions stand out for their superior performance. In terms of intercity train efficiency, the Yangtze River Delta, Beijing–Tianjin–Heibei, and Mid-Yangtze River regions exhibit higher levels of efficiency in intercity train transportation, while the Guanzhong Plain city cluster falls behind in this aspect. On the whole, the efficiency of intercity travel using automobiles surpasses that of train travel, indicating a pressing need for improvement in the latter.
Low Earth Orbit Satellite Network Routing Algorithm Based on Graph Neural Networks and Deep Q-Network
Authors: Shi Yuanji , Wang Weian , Zhu Xiaorong , Zhu Hongbo
Published: April 2024

Low Earth orbit (LEO) satellite networks are characterized by rapid topological changes, numerous network nodes and varying states of node resource constraints, which have resulted in traditional routing algorithms no longer being suitable for LEO satellite network routing. Therefore, this paper proposes an inductive learning architecture based on Graph Sample and Aggregate (GraphSAGE), which can significantly reduce the number of topology nodes to be trained, thereby reducing the computational complexity of the nodes. Then deep reinforcement learning (DRL) is employed for the continuous learning optimization of routing algorithms, and its generalization is improved by selecting GraphSAGE to construct the DRL agent. In the proposed graph neural-network-based routing optimization algorithm for LEO satellite networks, each Deep Q-Network (DQN) agent independently generates the hidden states of the nodes through the GraphSAGE model and uses them as inputs to the DRL model to make routing decisions. After a simulation and comparison, the proposed algorithm not only improves the overall network throughput, but also reduces the average end-to-end delay. The average throughput of the proposed algorithm increases by 29.47% and 18.42% compared to that of Dijkstra and the DQN, respectively. The average end-to-end delay is reduced by 39.76% and 15.29%, respectively, and can also adapt to changing topologies.
Effect of Sample Presentation on the Classification of Black Soldier Fly Larvae Using Near-Infrared Spectroscopy
Authors: Sanchez C. Mendez , Alagappan S. , Hoffman L. , Yarger O. , Cozzolino D.
Published: April 2024

Black soldier fly larvae (BSFL) (Hermetia illucens) reared on food waste streams are considered a sustainable source of protein in feed livestock diets. Recently, portable near-infrared spectroscopy (NIR) instruments have been assessed to monitor the consistency and quality of food waste streams used to feed black soldier fly larvae. During the application of NIR spectroscopy, sample presentation (e.g., drying, processing, particle size) plays an important role in the accuracy of the models developed (quantitative or qualitative analysis). The objective of this study was to evaluate the effect of sample presentation (number of larvae used during the scanning of BSFL) on the accuracy of classification models developed to trace the food waste stream (e.g., supermarket of childcare) used to feed the larvae. BSFL samples were sourced from two waste streams and scanned as half, 1, 2, or 3 larvae using an NIR portable instrument (MicroNIR, Viavi, Milpitas, California, USA). Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to analyze the NIR data and to classify the samples according to the waste stream. The main differences in the NIR spectra of the BSFL samples associated with the number of larvae scanned were observed around 1200 nm, mainly associated with the C-H overtones (lipids). The classification results showed that high classification rates (>93%) were obtained regardless of the number of larvae scanned, ranging from 93% (using 0.5 larvae) to 100% (using 1, 2, or 3 larvae samples). Overall, the number of larvae scanned had minimal to no effect on the accuracy of the LDA classification models. The present study demonstrated that a portable NIR instrument can be suitable for an initial rapid classification or determination of the origin of the waste stream used to feed the BSFL.
PSMD-SLAM: Panoptic Segmentation-Aided Multi-Sensor Fusion Simultaneous Localization and Mapping in Dynamic Scenes
Authors: Song Chengqun , Zeng Bo , Cheng Jun , Wu Fuxiang , Hao Fusheng
Published: April 2024

Multi-sensor fusion is pivotal in augmenting the robustness and precision of simultaneous localization and mapping (SLAM) systems. The LiDAR–visual–inertial approach has been empirically shown to adeptly amalgamate the benefits of these sensors for SLAM across various scenarios. Furthermore, methods of panoptic segmentation have been introduced to deliver pixel-level semantic and instance segmentation data in a single instance. This paper delves deeper into these methodologies, introducing PSMD-SLAM, a novel panoptic segmentation assisted multi-sensor fusion SLAM approach tailored for dynamic environments. Our approach employs both probability propagation-based and PCA-based clustering techniques, supplemented by panoptic segmentation. This is utilized for dynamic object detection and the removal of visual and LiDAR data, respectively. Furthermore, we introduce a module designed for the robust real-time estimation of the 6D pose of dynamic objects. We test our approach on a publicly available dataset and show that PSMD-SLAM outperforms other SLAM algorithms in terms of accuracy and robustness, especially in dynamic environments.
Monitoring and Leak Diagnostics of Sulfur Hexafluoride and Decomposition Gases from Power Equipment for the Reliability and Safety of Power Grid Operation
Authors: Yang Luxi , Wang Song , Chen Chuanmin , Zhang Qiyu , Sultana Rabia , Han Yinghui
Published: April 2024

Sulfur hexafluoride (SF6) is a typical fluorine gas with excellent insulation and arc extinguishing properties that has been widely used in large-scale power equipment. The detection of SF6 gas in high-power electrical equipment is a necessary measure to ensure the reliability and safety of power grid operation. A failure of SF6 insulated electrical equipment, such as discharging or overheating conditions, can cause SF6 gas decomposition, resulting in various decomposition products. The decomposed gases inside the equipment decrease the insulating properties and are toxic. The leakage of SF6 can also decrease the insulating properties. Therefore, it is crucial to monitor the leakage of SF6 decomposed gases from electrical equipment. Quantitative testing of decomposition products allows us to assess the insulation state of the equipment, identify internal faults, and maintain the equipment. This review comprehensively introduces the decomposition formation mechanism of SF6 gas and the current detection technology of decomposition products from the aspects of principle and structure, materials, test effect, and practicability. Finally, the development trends of SF6 and decomposition gas detection technology for the reliability and safety of power grid operation are prospected.
Risks of Goods Transport Focused on the Assessment of Semi-Trailer Dynamics on Highways for Cargo Securing
Authors: Jagelčák Juraj , Kubáňová Jaroslava
Published: April 2024

The issue of the transport of goods is well-known, yet, in practice, there are often cases of damaged shipments due to improper storage and inappropriately chosen transport technology. Many cases are due to ignorance of the basic characteristics of the cargo and, consequently, its transport characteristics. Vehicle dynamics is crucial to the design of proper cargo securing; therefore, this article provides the values of longitudinal and lateral acceleration of a 16.5 m semi-trailer vehicle combination for test routes of length of 10,827 km on highways and other roads in Slovakia, Austria, and Germany from the monitoring of goods. The horizontal acceleration of 0.2 g is considered as the minimum stability of the load unit that should withstand transport. A load unit with a stability from 0.2 g to 0.3 g could be considered as the weakest load unit. The test results show that even the weakest load units such as these can be damaged in transports, as semi-trailer vehicle combinations still reach longitudinal ax1000 and lateral ay1000 accelerations between 0.2 g and 0.3 g relatively frequently. Acceleration events higher than 0.3 g occur very rarely, at 1.4 event/1000 km for roads, but only 0.1 event/1000 km for highways from our test transports. We have demonstrated through our research that it is necessary for the load units to have a minimum stability of 0.2 g. We can conclude that load units with a stability of less than 0.2 g are completely unacceptable for transport without additional securing because we obtained 70.3 acceleration events per 1000 km in the interval from 0.1 g to 0.2 g on highways but 1148.1 events per 1000 km on other roads. There is a big difference between the number of acceleration events per 1000 km on roads and highways for all acceleration intervals, which means that there is a substantially lower probability of damaging the weak load units on highways than on other roads.
Development of a New Vertical Dynamic Model of a Rail Vehicle for the Analysis of Ride Comfort
Authors: Çati Yusuf , Düzgün Mesut , Kracht Frédéric Etienne
Published: April 2024

The rail vehicle industry wants to produce vehicles with higher speeds, to maintain and increase its market share. However, when the speed of the vehicle increases, it may have an undesirable effect on ride comfort, in terms of ride dynamics. Recent developments towards lighter and faster vehicles make the problem of ride comfort at higher speeds increasingly important. Focusing on the behavior of flexible rather than rigid body behavior should not be neglected when designing long and light car bodies. There are several approaches to incorporate body flexibility in multibody simulations and they have some superiorities and weaknesses. In this study, an efficient and accurate vertical dynamic model for the ride comfort analysis is developed and implemented in a commercial object-oriented modeling (OOM) software Dymola (2015 FD01) which uses the open-source code Modelica. This model includes car body flexibility with the assembling of a rigid body approach. The developed model is compared to a three-dimensional vehicle model in the commercial Vampire software (Pro V5.50) at different velocities. For the vertical ride comfort analysis, the ISO 2631-1 standard was used for both the developed model and the three-dimensional model. The results are presented as acceleration history and awrms—weighted r.m.s (root mean square) of accelerations—as required by the standard. The developed model has shown its feasibility in terms of its efficiency and accuracy for the vertical ride comfort analysis. The accuracy of the model is evidenced by the fact that the car body vibration level at high speeds shows minor differences compared to the results of the Vampire, which is a validated commercial software in the area of rail vehicle dynamics. The approach involving the assembly of rigid bodies is applied for the first time for high-speed trains in dynamical modelling, with flexible car bodies for ride comfort analysis. Furthermore, it can be used for parametrical studies focusing on ride comfort, thereby offering a quite beneficial framework for addressing the challenges of ride comfort analysis in high-speed rail vehicles. Improvements for and analyses of other aspects are also possible, since the optimization and other useful libraries are readily available in Dymola/Modelica.
Global Buckling Resistance of Cold-Formed Steel Beams with Omega-Shaped Sections
Authors: Peres Rita , Carvalho José , Emerick Jean Antonio , Macedo Luís , Rangel Paes José Luiz , Castro José Miguel
Published: April 2024

The absence of analytical expressions in current codes for evaluating the critical moment for lateral–torsional buckling of cold-formed beams with omega-shaped sections presents a fundamental challenge when assessing their resistance to global buckling. In response to this challenge, a comparative study was conducted to explore various approaches for calculating the critical moment. This involved both analytical and numerical analyses, using different methods available in codes and computational tools. The analytical analysis followed the Effective Width Method, employing the expression proposed in ENV 1993-1-1:1992, which is commonly used for evaluating the critical lateral–torsional moment of hot-rolled profiles. Numerical analyses were then performed using the ABAQUS v6.13, GBTUL v2.0, and CUFSM v5.05 software packages. The ABAQUS model, validated with results obtained from an experimental campaign, serves as the reference model. Upon assessing the bending moment resistances according to European, Brazilian, and American standards, consistency was found among these standards. However, it became evident that using the analytical expression proposed for hot-rolled profiles is inadequate for evaluating the critical lateral–torsional moment of CFS omega-shaped profiles. Conversely, the agreement between the ABAQUS, GBTUL, and CUFSM results suggests their utility as reliable tools for estimating the elastic critical lateral–torsional buckling moment.
Data-Driven Adaptive Controller Based on Hyperbolic Cost Function for Non-Affine Discrete-Time Systems with Variant Control Direction
Authors: Flores-Padilla Miriam , Treesatayapun Chidentree
Published: April 2024

As technology evolves, more complex non-affine systems are created. These complex systems are hard to model, whereas most controllers require information on systems to be designed. This information is hard to obtain for systems with varying control directions. Therefore, this study introduces a novel data-driven estimator and controller tailored for single-input single-output non-affine discrete-time systems. This approach focuses on cases when the control direction varies over time and the mathematical model of the system is completely unknown. The estimator and controller are constructed using a Multiple-input Fuzzy Rules Emulated Network framework. The weight vectors are updated through the gradient descent optimization method, which employs a unique cost function that multiplies the error by a hyperbolic tangent. The stability analyses demonstrate that both the estimator and controller converge to uniformly ultimately bounded (UUB) functions of Lyapunov. To validate the results, we show experimental tests of force control that were executed on the z-axis of a drive-controlled 3D scanning robot. This system has a varying control direction, and we also provide comparison results with a state-of-the-art controller. The results show a mean absolute percentage tracking error smaller than one percent on the steady state and the expected variation in the system’s control direction.