bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Debonding Defects in Concrete-Filled Steel Tubes Using Fluctuation Analysis Method
Authors: Wang Chenfei , Yang Yixin , Fan Guangming , Lian Junyin , Chen Fangjian
Published: December 2024

This study presents a comprehensive method for detecting debonding defects in concrete-filled steel tube (CFST) structures using wave propagation analysis with externally attached piezoelectric ceramic sensors. Experimental tests and numerical simulations were conducted to evaluate the sensitivity and accuracy of two measurement techniques—the flat and oblique measurement methods—in detecting debonding defects of varying lengths and heights. The results demonstrate that the flat measurement method excels in detecting debonding height, while the oblique method is more effective for detecting debonding length. A normalized judgment index (DI) was introduced to quantify the correlation between debonding characteristics and the detected signal amplitude, revealing the significant influence of sensor spacing on detection accuracy. Furthermore, a mathematical model based on wavelet packet energy analysis was developed to establish a linear relationship between wavelet packet energy and debonding size. This model offers a scientific foundation for the quantitative detection of debonding defects and provides a new approach to the health monitoring of CFST structures. The integrated use of both measurement techniques enhances detection precision, enabling both qualitative and quantitative defect analysis, which can significantly guide the maintenance and repair of CFST structures.
Lens-Free On-Chip Quantitative Phase Microscopy for Large Phase Objects Based on a Biplane Phase Retrieval Method
Authors: Chen Yufan , Wu Xuejuan , Chen Yang , Lin Wenhui , Gu Haojie , Zhang Yuzhen , Zuo Chao
Published: December 2024

Lens-free on-chip microscopy (LFOCM) is a powerful computational imaging technology that combines high-throughput capabilities with cost efficiency. However, in LFOCM, the phase recovered by iterative phase retrieval techniques is generally wrapped into the range of −π to π, necessitating phase unwrapping to recover absolute phase distributions. Moreover, this unwrapping process is prone to errors, particularly in areas with large phase gradients or low spatial sampling, due to the absence of reliable initial guesses. To address these challenges, we propose a novel biplane phase retrieval (BPR) method that integrates phase unwrapping results obtained at different propagation distances to achieve accurate absolute phase reconstruction. The effectiveness of BPR is validated through live-cell imaging of HeLa cells, demonstrating improved quantitative phase imaging (QPI) accuracy when compared to conventional off-axis digital holographic microscopy. Furthermore, time-lapse imaging of COS-7 cells in vitro highlights the method’s robustness and capability for long-term quantitative analysis of large cell populations.
Antenna Design and Construction of a Free-Pass System for Hi-Pass Type Ticket Gates in Subways for Transportation-Disadvantaged Individuals
Authors: Lee Yunsub , Lee Cholu , Yoon Cheol , Kim Woosu
Published: December 2024

This paper examines the design of antennas for Hi-pass type turnstiles needed to implement a subway free-pass system targeting transportation-disadvantaged individuals. The subway free-pass system allows individuals who have a free-pass card to approach the turnstile with the card on their person, which opens the gate automatically. This system, like the highway Hi-pass, allows users to pass through the subway gate without needing to scan a ticket. For the system to function, antennas are required at both the entrance and exit gates, with an additional antenna needed for the free-pass card, totaling three antennas. The free-pass card functions as a radio-frequency identification (RFID) tag, while the system uses Bluetooth communication. In this paper, we propose a square patch-type microstrip antenna that can be integrated within the turnstile, performing excellently in the Bluetooth band range of 2.420 to 2.485 GHz.
Study on Few-Shot Fault Diagnosis Method for Marine Fuel Systems Based on DT-SViT-KNN
Authors: Li Shankai , Qi Liang , Shi Jiayu , Xiao Han , Da Bin , Tang Runkang , Zuo Danfeng
Published: December 2024

The fuel system serves as the core component of marine diesel engines, and timely and effective fault diagnosis is the prerequisite for the safe navigation of ships. To address the challenge of current data-driven fault-diagnosis-based methods, which have difficulty in feature extraction and low accuracy under small samples, this paper proposes a fault diagnosis method based on digital twin (DT), Siamese Vision Transformer (SViT), and K-Nearest Neighbor (KNN). Firstly, a diesel engine DT model is constructed by integrating the mathematical, mechanism, and three-dimensional physical models of the Medium-speed diesel engines of 6L21/31 Marine, completing the mapping from physical entity to virtual entity. Fault simulation calculations are performed using the DT model to obtain different types of fault data. Then, a feature extraction network combining Siamese networks with Vision Transformer (ViT) is proposed for the simulated samples. An improved KNN classifier based on the attention mechanism is added to the network to enhance the classification efficiency of the model. Meanwhile, a Weighted-Similarity loss function is designed using similarity labels and penalty coefficients, enhancing the model’s ability to discriminate between similar sample pairs. Finally, the proposed method is validated using a simulation dataset. Experimental results indicate that the proposed method achieves average accuracies of 97.22%, 98.21%, and 99.13% for training sets with 10, 20, and 30 samples per class, respectively, which can accurately classify the fault of marine fuel systems under small samples and has promising potential for applications.
Pathogenic Bacterial Detection Using Vertical-Capacitance Sensor Array Immobilized with the Antimicrobial Peptide Melittin
Authors: Lee Sun-Mi , Song Jun-Ho , Lee Kyo-Seok , Yoo Kyung-Hwa
Published: December 2024

The rapid and reliable detection of pathogenic bacteria remains a significant challenge in clinical microbiology. Consequently, the demand for simple and rapid techniques, such as antimicrobial peptide (AMP)-based sensors, has recently increased as an alternative to traditional methods. Melittin, a broad-spectrum AMP, rapidly associates with the cell membranes of various gram-positive and gram-negative bacteria. It also inhibits bacterial biofilm formation in blood culture media. In our study, bacterial growth was measured using electrical vertical-capacitance sensors with interdigitated electrodes functionalized with melittin, a widely studied AMP. The melittin-immobilized vertical-capacitance sensors demonstrated real-time detection of both standard and clinically isolated bacteria in media. Furthermore, these sensors successfully detected clinically isolated bacteria in blood culture media while inhibiting bacterial biofilm formation. Melittin-immobilized vertical-capacitance sensors provide a rapid and sensitive pathogen detection platform, with significant potential for improving patient care.
Impact of Pathway Shape and Length on the Validity of the 6-Minute Walking Test: A Systematic Review and Meta-Analysis
Authors: Ngueleu Armelle-Myriane , Barrette Solène , Buteau Coralie , Robichaud Chloé , Nguyen Michelle , Everard Gauthier , Batcho Charles Sebiyo
Published: December 2024

Although guidelines are established for performing the six-minute walking test (6MWT), it is not always possible to implement this test in any setting, due to physical and space limitations. Yet, variations in the conditions of the test could be responsible for heterogeneous outcomes. However, the impact of the condition of the 6MWT is not clearly established in literature. The objective is to determine the influence of different implementation conditions on the validity of the 6MWT. Seventeen articles were retained after a literature review, including 597 participants. Seven articles mention that performing the test on a predetermined short back-and-forth pathway led to lower performance than when the test was performed on pathways of greater distances. The walking distance covered on a rectangular path or on a 10-m eight-form path is greater than with the back and forth on a five- to ten-meter path. Seven articles suggest that the performance achieved on a treadmill is generally lower than that obtained while walking on the ground. Evidence shows that the conditions while performing the 6MWT significantly influence the score, hence the validity of the results. The use of a ground pathway, comprising the longest linear distance possible, seems critical to ensure good validity.
Emotion Recognition Using PPG Signals of Smartwatch on Purpose of Threat Detection
Authors: Hwang Gyuwon , Yoo Sohee , Yoo Jaehyun
Published: December 2024

This paper proposes a machine learning approach to detect threats using short-term PPG (photoplethysmogram) signals from a commercial smartwatch. In supervised learning, having accurately annotated training data is essential. However, a key challenge in the threat detection problem is the uncertainty regarding how accurately data labeled as ‘threat’ reflect actual threat responses since participants may react differently to the same experiments. In this paper, Gaussian Mixture Models are learned to remove ambiguously labeled training, and those models are also used to remove ambiguous test data. For the realistic test scenario, PPG measurements are collected from participants playing a horror VR (Virtual Reality) game, and the proposed method validates the superiority of our proposed approach in comparison with other methods. Also, the proposed filtering with GMM improves prediction accuracy by 23% compared to the method that does not incorporate the filtering.
Integrated Decision and Motion Planning for Highways with Multiple Objects Using a Naturalistic Driving Study
Authors: Gao Feng , Zheng Xu , Hu Qiuxia , Liu Hongwei
Published: December 2024

With the rise in the intelligence levels of automated vehicles, increasing numbers of modules of automated driving systems are being combined to achieve better performance and adaptability by reducing information loss. In this study, an integrated decision and motion planning system is designed for multi-object highways. A two-layer structure is presented to decouple the influence of the traffic environment and the dynamic control of ego vehicles using the cognitive safety area, the size of which is determined by naturalistic driving behavior. The artificial potential field method is used to comprehensively describe the influence of all external objects on the cognitive safety area, the lateral motion dynamics of which are determined by the attention mechanism of the human driver during lane changes. Then, the interaction between the designed cognitive safety area and the ego vehicle can be simplified into a spring-damping system, and the desired dynamic states of the ego vehicle can be obtained analytically for better computational efficiency. The effectiveness of this on improving traffic efficiency, driving comfort, safety, and real-time performance was validated using several comparative tests utilizing complicated scenarios with multiple vehicles.
Quantifying the Impact of Soil Moisture Sensor Measurements in Determining Green Stormwater Infrastructure Performance
Authors: Shakya Matina , Hess Amanda , Wadzuk Bridget M. , Traver Robert G.
Published: December 2024

The ability to track moisture content using soil moisture sensors in green stormwater infrastructure (GSI) systems allows us to understand the system’s water management capacity and recovery. Soil moisture sensors have been used to quantify infiltration and evapotranspiration in GSI practices both preceding, during, and following storm events. Although useful, soil-specific calibration is often needed for soil moisture sensors, as small measurement variations can result in misinterpretation of the water budget and associated GSI performance. The purpose of this research is to quantify the uncertainties that cause discrepancies between default (factory general) sensor soil moisture measurements versus calibrated sensor soil moisture measurements within a subsurface layer of GSI systems. The study uses time domain reflectometry soil moisture sensors based on the ambient soil’s dielectric properties under different soil setups in the laboratory and field. The default ‘loam’ calibration was compared to soil-specific (loamy sand) calibrations developed based on laboratory and GSI field data. The soil-specific calibration equations used a correlation between dielectric properties (real dielectric: εr, and apparent dielectric: Ka) and the volumetric water content from gravimetric samples. A paired t-test was conducted to understand any statistical significance within the datasets. Between laboratory and field calibrations, it was found that field calibration was preferred, as there was less variation in the factory general soil moisture reading compared to gravimetric soil moisture tests. Real dielectric permittivity (εr) and apparent permittivity (Ka) were explored as calibration options and were found to have very similar calibrations, with the largest differences at saturation. The εr produced a 6% difference while the Ka calibration produced a 3% difference in soil moisture measurement at saturation. Ka was chosen over εr as it provided an adequate representation of the soil and is more widely used in soil sensor technology. With the implemented field calibration, the average desaturation time of the GSI was faster by an hour, and the recovery time was quicker by a day. GSI recovery typically takes place within 1–4 days, such that an extension of a day in recovery could result in the conclusion that the system is underperforming, rather than it being the result of a limitation of the soil moisture sensors’ default calibrations.
Colon Cancer: Overview on Improved Therapeutic Potential of Plant-Based Compounds Using Nanotechnology
Authors: López-Cabanillas Lomelí Manuel , Tijerina-Sáenz Alexandra , García-Hernández David Gilberto , Hernández-Salazar Marcelo , Salas García Rogelio , González-Llerena José Luis , Verde-Star María Julia , Cordero-Díaz Anthonny , Heya Michel Stéphane
Published: December 2024

Colon cancer (CC) is the third most frequent neoplasm, with a considerably high mortality rate. Due to the side effects of conventional forms of CC treatment (surgery, chemotherapy, and radiotherapy), several studies have focused on the use of medicinal plant derivatives to provide a green therapy for CC; although phytochemicals have shown promising results against CC, translating the results obtained in vitro and in vivo to the clinical setting remains a challenge. Indeed, like other orally applied medicines, medicinal plant derivatives have to cross different physiological barriers to reach the CC microenvironment, which considerably limits their dose-dependent therapeutic efficacy. On the other hand, phytocompounds are not free from biopharmaceutical drawbacks, so novel strategies using nanoparticles (NPs) have been proposed to overcome the physiological barriers of the body and provide controlled release of actives of interest. Accordingly, the current review provides an overview and discussion on the predisposing factors to CC and conventional treatment, the use of medicinal plants in CC treatment, and the advantages provided by NPs in the treatment of CC.
Power Management Approach of Hybrid Energy Storage System for Electric Vehicle Charging Stations
Authors: Fekih Hassen Wiem , Schoppik Luis , Schiegg Sascha , Gerl Armin
Published: December 2024

The applicability of Hybrid Energy Storage Systems (HESSs) has been shown in multiple application fields, such as Charging Stations (CSs), grid services, and microgrids. HESSs consist of an integration of two or more single Energy Storage Systems (ESSs) to combine the benefits of each ESS and improve the overall system performance. In this work, we propose a novel power management controller called the Hybrid Controller for the efficient HESS’s charging and discharging, considering the State of Charge (SoC) of the HESS and the dynamic supply and load. The Hybrid Controller optimises the use of the HESS, i.e., minimises the amount of energy drawn from and discharged to the grid, thus utilising and prioritising the provided Photovoltaic (PV) power. The performance of our proposal was assessed via simulation using various evaluation metrics, i.e., Autarky, charge/discharge cycle, and Self-Consumption (SC), where we defined 24 scenarios in different locations in Germany.
Exploring Teen Pregnancy as a Public Health Problem: A Critical Scoping Review of Public Health Research on Teen Pregnancy in Canada
Authors: Dutton Sherri , Mamun Mir Sanim Al , Davison Colleen M.
Published: December 2024

Inequities related to teen pregnancy are a complex social and health problem across the globe. Evaluation of research assumptions can help to move research forward when considering complex public health issues. Drawing on previous critical reviews, this scoping review sought to map not just what teen pregnancy research is available, but how current public health research was orienting to teen pregnancy in Canada. This review included studies focused on general or intended teen pregnancy within a public health Canadian context. Both grey and peer-reviewed literature were searched, with only studies in English and French included. In total 32 studies were analyzed. Taking a multifaceted approach to assessing research orientation this scoping review applied an adapted health equity framework to consider alignment between awareness and action and utilized discourse analysis to explore constructions of pregnancy intention. Results showed although a portion of research fell within the acknowledge and illuminate categories, most of the research utilized public health language rooted in biomedical and individualistic discourses and focused on influencing individual action, rather than greater societal change. Adding to the growing body of teen pregnancy research in Canada, this scoping review revealed potential epistemological barriers related to limited research approaches, applied public health action, and engagement with topic overall, leading to a call for more diverse, critically reflective, and disruptive approaches to teen pregnancy research in Canada to address teen pregnancy-related inequities at the root.
Assessing Active and Passive Glenohumeral Rotational Deficits in Professional Tennis Players: Use of Normative Values at 90° and 45° of Abduction to Make Decisions in Injury-Prevention Programs
Authors: Terré Maite , Tlaiye Juliette , Solana-Tramunt Monica
Published: December 2024

(1) Background: Glenohumeral internal and external rotational range-of-movement deficits (GIRDs and GERDs) are some of the primary outcomes used to determine the risk of injury in overhead athletes, such as tennis players. Nevertheless, the current testing position does not consider the fact that most tennis actions are repeated at 45° of abduction, and actively. The aim of this study was to establish normative values of pathological GIRDs and GERDs in tennis players and to provide normative values for both the passive and active rotational range of motion of the glenohumeral joint at 90° and 45° of abduction. (2) Methods: Forty-three tennis players voluntarily participated in this study (19.1 ± 2.75 years). The dominant and non-dominant total glenohumeral rotational range of motion (TRROM), external rotation (ER), and internal rotation (IR) at 90° and 45° under active and passive conditions were evaluated. The GIRD and GERD were calculated in both positions and under both conditions. (3) Results: There were significant differences in all of the passive measurements between the 45° and 90° testing positions. The ER and TRROM at 90° and 45° showed significant differences under both passive and active conditions and on the dominant and non-dominant sides. Actively, there were no significant differences in the IR or TRROM for either the dominant or non-dominant side at 90° or 45°. (4) Conclusions: It is necessary to evaluate ER under the same conditions at 90° or 45°. Practitioners should consider assessing the ER for the angle at which most actions are repeated in tennis (45°) as a method to monitor GERDs. Evaluating GERDs in asymptomatic tennis players could help avoid future biomechanical and GIRD problems. Both GIRDs and GERDs should be considered as a percentage of the athlete’s own deficit in IR or ER, instead of referencing specific degrees that have been observed in baseball pitchers.
Transanal Irrigation in Patients with Low Anterior Resection Syndrome After Rectal-Sphincter-Preserving Surgery for Oncological and Non-Oncological Disease: A Systematic Review
Authors: Morini Andrea , Fabozzi Massimiliano , Zanelli Magda , Sanguedolce Francesca , Palicelli Andrea , Annicchiarico Alfredo , Bonelli Candida , Zizzo Maurizio
Published: December 2024

Background/Objectives: Transanal irrigation (TAI) has been recognized as a safe and effective treatment for neurological bowel dysfunction, chronic constipation or fecal incontinence and has also been proposed for patients with low anterior resection syndrome (LARS). The aim of the present systematic review was to evaluate the feasibility and effectiveness of TAI in patients with significant LARS symptoms. Methods: We performed a systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and guidelines in addition to the Cochrane Handbook for Systematic Reviews of Interventions. The protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42023436839). The risk of bias was assessed using a modified version of the Downs and Black checklist. The main outcome was improvement in low anterior resection syndrome after TAI assessed by change in LARS score. Results: After an initial screening of 3703 studies, 9 were included and underwent qualitative synthesis (among them, 3 were randomized clinical trials). All studies recorded an improvement in LARS score following TAI procedure and almost all studies showed an improvement in other bowel function outcomes (Memorial Sloan Kettering Cancer Center Bowel Function Instrument (MSKCC BFI, ), Cleveland Clinic Incontinence Score (CCIS), visual analog scale (VAS), Cleveland Clinic Florida Fecal Incontinence Score (CCFFIS), fecal incontinence score (FI score), Obstructed Defecation Syndrome (ODS) score) and quality of life (QoL) scores. The discontinuation rate ranged from 0% to 41%. The rate of adverse events was high (from 0 to 93%); moreover, no uniformity was found in the various protocols used among the different studies. Conclusions: The results of this review show that TAI is effective in the treatment of LARS, improving the LARS score, the other bowel function outcomes and the QoL scores. The absence of a treatment protocol validated by the scientific community is reflected in the high disparity in terms of adverse events and discontinuation of therapy, in addition to representing an intrinsic limitation to the study itself.
Seven Challenges for Risk Communication in Today’s Digital Era: The Emergency Manager’s Perspective
Authors: Ross Ashley D. , Siebeneck Laura , Wu Hao-Che , Kopczynski Sarah , Nepal Samir , Sauceda Miranda
Published: December 2024

Risk communication plays a vital role in transmitting information about hazards and protective actions before and after disasters. While many studies have examined how risk communication and warnings influence household responses to hurricanes, fewer studies examine this from the perspective of the emergency manager. Given the rapid advancements in technology and the adoption of social media platforms, as well as the increasing prevalence of misinformation during disasters, a fresh investigation into risk communication challenges and optional strategies is needed. Therefore, this study addresses three research questions: (1) What channels do emergency managers rely upon to communicate with the public before, during, and after a disaster? (2) How do emergency managers assess and ensure the effectiveness of their messaging strategies? (3) How do emergency managers manage misinformation? The challenges experienced by emergency managers related to each of these issues are also explored. Data were gathered in July–October 2024 through interviews conducted with eleven local emergency managers located in communities along the Texas Gulf Coast. Based on the findings of a qualitative data analysis, this paper presents seven distinct risk communication challenges faced by emergency managers throughout the evacuation and return-entry processes that span the communication aspects of channels, messaging, and misinformation.
Innovation Networks and Knowledge Diffusion Across Industries: An Empirical Study from an Emerging Economy
Authors: Bawa Suleman , Benin Ibn Wahab , Almudaihesh Abdulaziz Saleh
Published: December 2024

This study investigates the impact of innovation networks on knowledge diffusion, aligning with the Knowledge Spillover Theory of Entrepreneurship (KSTE). It explores how these networks promote sustainability-oriented innovation and enhance corporate performance across industries, focusing on the Ghanaian context. A theoretical framework was developed using a two-dimensional fixed effects model and instrumental variable estimations. The analysis utilized longitudinal data from the World Intellectual Property Organization (WIPO) via the PENTSCOPE database from 2000 to 2023. The study reveals that robust innovation networks significantly enhance knowledge diffusion. Absorptive capacity plays a crucial mediating role, enabling firms to assimilate and apply external knowledge effectively. Additionally, organizational culture is a critical moderator, with adaptive and collaborative cultures fostering more efficient knowledge integration. The results highlight the pivotal role of innovation networks in transforming technological advancements into measurable performance outcomes, driving sustainable innovation and competitive advantage. This research extends the KSTE framework by integrating the network theory to examine how firms exploit external knowledge. It provides empirical evidence from the Ghanaian context, offering novel insights into how innovation networks can foster knowledge diffusion and sustainable development. This study’s findings contribute to theoretical discourse and practical applications, emphasizing the importance of strategic engagement in innovation networks and adaptive organizational cultures for long-term success. This research provides insights applicable to other emerging economies, highlighting how robust innovation networks can drive knowledge diffusion and sustainable development beyond the Ghanaian context.
The Impact of Reverse Mentoring on Employees’ Innovative Behavior: Evidence from Chinese Technology Enterprises
Authors: Li Miaomiao , Guo Jinglong , Zou Chiying , Yin Jielin
Published: December 2024

Innovation is crucial for enterprises to maintain a sustainable competitive advantage. Reverse mentoring, as an emerging mentoring practice that promotes knowledge and idea exchange between junior employees and senior colleagues, is regarded as a crucial element in driving overall innovation within organizations and is gradually attracting the attention of scholars. However, empirical research on its potential benefits is still relatively scarce. Based on the cognitive appraisal theory of stress, this study investigates the relationship and internal mechanisms between reverse mentoring and employees’ innovative behaviors through a two-period follow-up survey of 528 employees in China’s science and technology-based enterprises. The hypotheses were verified using structural equation modeling and bootstrap analysis, and the findings indicated that reverse mentoring positively influenced employees’ innovative behaviors. Simultaneously, challenge stress appraisal and continuous learning serve as chain mediators between reverse mentoring and employees’ innovative behaviors. This study provides valuable references for organizations to effectively implement reverse mentoring practices and foster innovation, offering a new pathway for sustainable innovation among enterprise employees.
Low Temperature Synthesis of 3d Metal (Fe, Co, Ni, Cu)-Doped TiO2 Photocatalyst via Liquid Phase Deposition Technique
Authors: Honda Mitsuhiro , Yoshii Yusaku , Okayama Nobuchika , Ichikawa Yo
Published: December 2024

The titanium dioxide (TiO2) photocatalyst is an important semiconducting material that exhibits environmental purification functions when exposed to light. Elemental doping of TiO2 is considered an important strategy to improve its photocatalytic activity. Herein, we have achieved the low-temperature, atmospheric-pressure synthesis of anatase TiO2 particles with doping of 3d metals (Fe, Co, Ni and Cu) based on the liquid phase deposition technique. All products prepared by adding 3d metals were found to consist of TiO2 crystals in the anatase phase with a fine protruding structure of about 40 nm on the surface, as was the case without the addition of metal ions. Iron and copper were observed to be incorporated at higher concentrations than cobalt and nickel, with an elemental addition of up to 4 at% and 1 at%, respectively, when 10 mM iron and copper nitrate were applied. Such doping efficiency could be explained by the difference in ionic radius and chemical stability. A narrowing of the optical band gap with doping elements was also observed, and it was found that optical sensitivity could be imparted down to the visible-light region of 2.4 eV (Fe: 4 at% addition). Furthermore, the 3d metal-doped TiO2 demonstrated in this study was shown to exhibit photocatalytic methane degradation activity. The amount of methane degradation per unit area of the microparticles was twice as great when iron and copper were added, compared to the undoped counterpart. It has been demonstrated that the strategy of doping TiO2 with 3d metal ions by low-temperature synthesis methods is effective in enhancing carrier dynamics and introducing surface active sites, thus increasing methane degradation activity.
SDA-RRT*Connect: A Path Planning and Trajectory Optimization Method for Robotic Manipulators in Industrial Scenes with Frame Obstacles
Authors: Wu Guanda , Wang Ping , Qiu Binbin , Han Yu
Published: December 2024

The trajectory planning of manipulators plays a crucial role in industrial applications. This importance is particularly pronounced when manipulators operate in environments filled with obstacles, where devising paths to navigate around obstacles becomes a pressing concern. This study focuses on the environment of frame obstacles in industrial scenes. At present, many obstacle avoidance trajectory planning algorithms struggle to strike a balance among trajectory length, generation time, and algorithm complexity. This study aims to generate path points for manipulators in an environment with obstacles, and the trajectory for these manipulators is planned. The search direction adaptive RRT*Connect (SDA-RRT*Connect) method is proposed to address this problem, which adaptively adjusts the search direction during the search process of RRT*Connect. In addition, we design a path process method to reduce the length of the path and increase its smoothness. As shown in experiments, the proposed method shows improved performances with respect to path length, algorithm complexity, and generation time, compared to traditional path planning methods. On average, the configuration space’s path length and the time of generation are reduced by 38.7% and 57.4%, respectively. Furthermore, the polynomial curve trajectory of the manipulator was planned via a PSO algorithm, which optimized the running time of the manipulator. According to the experimental results, the proposed method costs less time during the manipulator’s traveling process with respect to other comparative methods. The average reduction in running time is 45.2%.
Enhancing the Proportion of Sub-5 μm Atomized Droplet Size in Medical Air-Compression Nebulizer
Authors: Xu Kun , Lu Zhongyou , Wang Li , Tang Yunqing
Published: December 2024

Medical air-compression nebulizers deliver atomized medication to the lungs, providing rapid and painless treatment for respiratory diseases. However, the size of most atomized droplets is around 10 μm, limiting drug deposition in the lower airways and alveoli, with increasing the proportion of sub-5 μm droplets remaining challenging. In this work, finite element analysis was employed to model the effects of gas flow rate, liquid channel width, and broken baffle structure on droplet size distribution, aiming to optimize structure symmetrical parameters and operating conditions. A novel compression atomizer was developed and experimentally evaluated, incorporating an improved symmetrical structure for the crushing baffle. Following this modification, the proportion of sub-5 μm droplets increased from 54.6% to 59.25%, representing a 4.65% enhancement in the generation of sub-5 μm droplets. The effects of gas flow rate and liquid concentration on droplet size distribution were systematically investigated to further optimize the atomization performance. The results demonstrated a significant increase in the proportion of sub-5 μm droplets, thereby enhancing drug delivery efficiency to the lower respiratory tract and improving treatment efficacy for respiratory diseases.
A Financial Fraud Prediction Framework Based on Stacking Ensemble Learning
Authors: Zhu Shanshan , Wu Haotian , Ngai Eric W. T. , Ren Jifan , He Daojing , Ma Tengyun , Li Yubin
Published: December 2024

With the rapid development of the capital market, financial fraud cases are becoming increasingly common. The evolving fraud strategies pose significant threats to financial regulation, market order, and the interests of ordinary investors. In order to combine the generalization performance of different machine learning methods and improve the effectiveness of financial fraud prediction, this paper proposes a novel financial fraud prediction framework based on stacking ensemble learning. This framework, based on data from listed companies, comprehensively considers financial ratio indicators and non-financial indicators. It uses the stacking ensemble technique to integrate numerous base models of machine learning algorithms for predicting financial fraud. Furthermore, the proposed framework has high versatility and is suitable for various tasks related to financial fraud prediction, addressing the problem of model selection difficulties in previous research due to different scenarios and data. We also conducted case studies on specific companies and industries, confirming the significant interpretability and practical applicability of the proposed framework. The results show that the recall rate and Area Under Curve (AUC) of our framework reached 0.8246 and 0.8146, respectively, surpassing mainstream machine learning models such as XGBoost and LightGBM in existing studies. This research study is of great significance for predicting the increasing number of financial fraud cases, providing a reliable tool for financial regulatory institutions and investors.
Bridging Big Data Analytics Capability and Competitive Advantage in China’s Agribusiness: The Mediator of Absorptive Capacity
Authors: Zhang Peng , Thurasamy Ramayah
Published: December 2024

This research examines the relationship between big data analytics capability (BDAC) and competitive advantage (CA) in China’s agribusiness sector, with a specific focus on the mediating role of absorptive capacity (AC). Although BDAC has been extensively studied in other industries, its role within agribusiness remains underexplored, particularly in developing economies like China. This study addresses this gap by investigating how BDAC can be utilized to enhance competitive advantage in the unique context of agribusiness. Grounded in Resource-Based Theory (RBT), a comprehensive framework is developed to elucidate the interconnections among BDAC, CA, and AC. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) on data collected from 287 agribusiness firms in China, the findings reveal that key resources—such as data quality, infrastructure, information systems, data governance, data-driven culture, managerial expertise, and technical proficiency—significantly influence BDAC. Moreover, BDAC is shown to positively impact CA, with AC serving as a critical mediator in this relationship. These results emphasize the strategic importance of integrating BDAC and AC to enhance the competitiveness of agribusinesses, particularly amidst rapid digital transformation. This study provides valuable contributions to the literature on BDAC, enriches the theoretical foundations of RBT in agribusiness contexts, and offers practical recommendations for digital transformation strategies in the sector.
Automated Measurement of Effective Radiation Dose by 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography
Authors: Eom Yujin , Park Yong-Jin , Lee Sumin , Lee Su-Jin , An Young-Sil , Park Bok-Nam , Yoon Joon-Kee
Published: December 2024

Background/Objectives: Calculating the radiation dose from CT in 18F-PET/CT examinations poses a significant challenge. The objective of this study is to develop a deep learning-based automated program that standardizes the measurement of radiation doses. Methods: The torso CT was segmented into six distinct regions using TotalSegmentator. An automated program was employed to extract the necessary information and calculate the effective dose (ED) of PET/CT. The accuracy of our automated program was verified by comparing the EDs calculated by the program with those determined by a nuclear medicine physician (n = 30). Additionally, we compared the EDs obtained from an older PET/CT scanner with those from a newer PET/CT scanner (n = 42). Results: The CT ED calculated by the automated program was not significantly different from that calculated by the nuclear medicine physician (3.67 ± 0.61 mSv and 3.62 ± 0.60 mSv, respectively, p = 0.7623). Similarly, the total ED showed no significant difference between the two calculation methods (8.10 ± 1.40 mSv and 8.05 ± 1.39 mSv, respectively, p = 0.8957). A very strong correlation was observed in both the CT ED and total ED between the two measurements (r2 = 0.9981 and 0.9996, respectively). The automated program showed excellent repeatability and reproducibility. When comparing the older and newer PET/CT scanners, the PET ED was significantly lower in the newer scanner than in the older scanner (4.39 ± 0.91 mSv and 6.00 ± 1.17 mSv, respectively, p < 0.0001). Consequently, the total ED was significantly lower in the newer scanner than in the older scanner (8.22 ± 1.53 mSv and 9.65 ± 1.34 mSv, respectively, p < 0.0001). Conclusions: We successfully developed an automated program for calculating the ED of torso 18F-PET/CT. By integrating a deep learning model, the program effectively eliminated inter-operator variability.
Network Toxicology and Molecular Docking Analysis of Tetracycline-Induced Acute Pancreatitis: Unveiling Core Mechanisms and Targets
Authors: Lei Hang , Wu Yimao , Ma Wenjun , Yao Jiaqi , Zhang Pengcheng , Tian Yong , Jiang Yuhong , Xie Zhijun , Zhu Lv , Tang Wenfu
Published: December 2024

Acute pancreatitis (AP), induced by tetracycline, a widely used antibiotic, poses significant clinical and toxicological challenges, yet its molecular mechanisms remain unclear. This study aims to promote drug toxicology strategies for the effective investigation of the putative toxicity and potential molecular mechanisms of antibiotic drugs through the study of tetracycline in AP. Using the SwissTargetPrediction, SEA Search, Super-PRED, GeneCards, Drugbank, Online Mendelian Inheritance in Man (OMIM), and Therapeutic Target Database (TTD), we identified 259 potential targets associated with tetracycline exposure and AP. Further refinement via the STRING database and Cytoscape (version 3.10.1) software highlighted 22 core targets, including TP53, TNF, and AKT1. Functional enrichment via the Database for Annotation, Visualization, and Integrated Discovery (DAVID) identified pathways through Gene Ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, highlighting PI3K-Akt, MAPK, HIF-1, and AGE-RAGE as critical mediators in tetracycline-induced AP. Molecular docking confirmed the strong binding between tetracycline and the core targets. Overall, these findings suggest that tetracycline may affect the occurrence and progression of pancreas-related inflammation by regulating pancreatic cell apoptosis and proliferation, activating inflammatory signaling pathways, and regulating lipid metabolic pathways. This study provides a theoretical basis for understanding the molecular mechanism of tetracycline-induced AP and lays the foundation for the prevention and treatment of digestive system diseases associated with excessive exposure to tetracycline antibiotics and certain tetracyclines. In addition, our network toxicology approach has accelerated the elucidation of toxic pathways in antibiotic drugs that lack specific characteristics.
Trends in Heavy Metal Pollution in Agricultural Land Soils of Tropical Islands in China (2000–2024): A Case Study on Hainan Island
Authors: Shang Erping , Ma Yong , Yao Wutao , Zhang Shuyan
Published: December 2024

Heavy metal contamination in agricultural soils has garnered increasing attention, yet research on the spatiotemporal trends of heavy metal pollution in tropical regions with multiple annual crop harvests remains limited. This study examines data from 41 studies published between 2000 and 2024, including 206 records from 4122 sampling points on Hainan Island in China, to investigate the spatial distribution and temporal trends of heavy metal pollution. The results reveal that the average concentrations of Cd, Pb, As, Cr, and Hg in surface soil samples from agricultural lands on Hainan Island are 0.12, 28.28, 4.36, 63.98, and 0.075 mg/kg, respectively, all below the risk screening thresholds set by the Soil Pollution Risk Control Standard for Agricultural Land (GB 15618-2018). Spatially, heavy metal concentrations exhibit considerable regional variation. Cd levels are lower in the central region but higher in the northern and southern parts of the island. Both the cumulative pollution index and potential ecological risk index are elevated at the northern and southern ends, indicating more severe pollution in these areas. Pb and As show similar spatial patterns, with higher concentrations in the west and lower concentrations in the east. Conversely, Cr has higher concentrations in the northeast and lower concentrations in the southwest. Hg levels are elevated at the northern and southern ends of the island, though the overall pollution and ecological risk in these areas remain relatively low. Temporally, the concentration of heavy metals in agricultural soils has increased overall over the past two decades, with peak values occurring between 2017 and 2023. From 2002 to 2013, the variation was modest, while the largest fluctuations occurred between 2014 and 2016. Among the metals, Cr exhibited the most significant increase, indicating the most severe pollution, followed by Cd and Hg. As and Pb showed relatively lower levels of contamination. Regarding exceedance rates, the exceedances were evaluated against the thresholds established in GB15618-2018 and GB15618-1995. Cd’s exceedance rate increased from approximately 1% between 2002 and 2014 to between 7.78% and 20.93% in the following years, peaking in 2017. The exceedance rate for As rose slightly from 0% to 0.83%, with sporadic exceedances starting in 2015. Although these were relatively minor, a severe pollution point for As was observed in 2019. Exceedance rates for Pb and Cr increased significantly, from 0.75% and 7.50% in 2019 to 1.94% and 9.44% in 2023, reflecting increases of 4.8 to 10 times. These findings underscore the need for strengthened monitoring and management of heavy metal pollution in agricultural soils on Hainan Island to safeguard land quality and ensure the sustainability of local agricultural practices.
PAH Contamination, Sources and Health Risks in Black Soil Region of Jilin Province, China
Authors: Aihemaitijiang Guzailinuer , Zhang Lujuan , Li Mingtang , Chen Yanan , Zhang Jiquan , Zhang Feng , Zhao Chunli
Published: December 2024

Soils in the Black Soil Zone of northeast China are experiencing pollution from polycyclic aromatic hydrocarbons (PAHs) as the region undergoes urbanization. In this study, 119 topsoil samples were collected from the black soil agricultural area in Jilin Province, China to investigate the characteristics and spatial distribution of 16 PAHs. The total concentration of ∑16 PAHs in the agricultural soils ranged from 2.546 to 33.993 mg/kg, with a mean value of 9.99 mg/kg. Positive matrix factorization (PMF) analysis indicated that vehicle exhaust and oil combustion were identified as the main contributors to traffic- and energy-related pollution. The inherited lifetime carcinogenicity risk (ILCR) was found to be relatively low, indicating a low potential risk in this region, with adults (1.34 × 10−5) exhibiting a higher risk than adolescents (8.62 × 10−6) and children (7.49 × 10−6). The highest values for intake, skin contact, and inhalation routes were observed in the adult group, suggesting that adult residents in certain areas may be at increased health risk. This study enhances our understanding of the pathways through which PAHs enter agricultural soils in Jilin Province and provides insights that could aid in addressing PAH pollution in black soil, ultimately contributing to more sustainable agricultural practices in the region.
Assessment of Organic Matter Influence on the Ecological Integrity of Poyang Lake Using O/E Model and Chemical–Biological Indices over the Past Two Decades
Authors: Wang Jindong , Huang Wenjie , Feng Chenglian , Wang Hongyang
Published: December 2024

Ecological integrity, encompassing physical, chemical, and biological aspects, is crucial for sustaining ecosystem service functions and stability. As the largest freshwater lake in China, the ecological integrity of Poyang Lake has attracted much attention due to the over-exploitation of its water resources in recent years. In this study, several biological and water quality surveys on water ecological conditions were carried out at 11 sampling points of Poyang Lake from 1998 to 2022, and the ecological health of Poyang Lake was evaluated by use of the O/E (Observation/Expectation) model and the chemical–biological index method according to the status of the water quality and the structure of the benthic fauna in the four seasons, respectively. The results showed that the benthic community structure is simple, and the biodiversity is low, which is mainly dominated by Insecta in Arthropoda and Oligochaeta in Oroidea, accounting for 84.3% and 42.4%, respectively; the results of the O/E index evaluated under the threshold of probability of capture ≥ 0.5 showed that the health grade of all sections was sub-healthy or average, which was consistent with the results of the chemical–biological composite index evaluation. The dual evaluation method of the O/E model and chemical–biological composite index adopted in this study integrates more than twenty years of long-time scale data; this method combined with long time scale data has not been studied before, and its advantage is that it can more objectively show the change in the ecological situation of Poyang Lake for many years. The results of the present study could provide a theoretical basis and technical support for the evaluation of lake water environment quality.