bluuebunny/crossref_metadata_2025 huggingface dataset:
Dietary supplementation with Bacillus subtilis PB6 alleviates diarrhea and improves growth performance and immune function in weaned piglets fed a high-protein diet
Authors: Liu Yang , Cao Lei , Yu Chenhao , Zhou Qiang , Li Hua , Zhang Ruinan , Tang Jiayong , Zhang Zhiming , Luo Zheng , Jiang Xuemei , Fang Zhengfeng , Lin Yan , Xu Shengyu , Zhuo Yong , Hua Lun , Wu De , Feng Bin , Che Lianqiang
Published: February 2025

This study aimed to evaluate the effects of dietary supplementation with Bacillus subtilis PB6 on growth performance, diarrhea scores, nutrient digestibility, immune function, and gut microbiota in weaned piglets fed a high-protein diet. A total of 96 weaned piglets were randomly divided into three groups in a randomized complete block design and received a low-protein diet (LP, 18.27% crude protein), a high-protein diet (HP, 20.97% crude protein), or a high-protein diet supplemented with probiotics (HPPRO, B. subtilis PB6 spores 2 × 1011 CFU/ kg) for 21 days. Each group had eight replicates with four piglets per replicate. The results showed that piglets fed the HPPRO diet had significantly higher average daily gain and average daily feed intake during days 8–14, days 15–21, and throughout the experimental period than piglets fed the LP diet (p < 0.01). In parallel, piglets fed the HPPRO diet had lower feed-to-gain ratio (F:G) values during days 8–14 than piglets fed the LP diet (p < 0.05). Piglets fed the HP diet had increased diarrhea scores than piglets fed the LP diet (p < 0.01), but the diarrhea scores of piglets fed the HPPRO diet were lower than those of the HP piglets (p < 0.01), which had the lowest nutrient digestibility. Moreover, piglets fed the HPPRO diet had lower plasma concentrations of haptoglobin than HP piglets (p < 0.05) and lower pig major acute-phase protein levels than HP and LP piglets (p < 0.05). The downregulation of genes (toll-like receptor-4, tumor necrosis factor-α [TNF-α], and TNF receptor-associated factor-6) in the ileal tissue associated with inflammation was observed in HPPRO-fed piglets compared to LP- and HP-fed piglets (p < 0.05). Piglets fed the HPPRO diet had increased relative abundance of genera related to proteolysis, such as g_Fusobacterium and g_Acidaminococcus, and genera related to butyrate production, such as g_Anaerostipes and g_Megasphaera. Furthermore, piglets fed the HPPRO diet had a higher concentration of butyrate in the colonic digesta than piglets fed the LP diet (p < 0.05). In conclusion, piglets fed the high-protein diet supplemented with 300-mg/kg B. subtilis PB6 had better growth performance, which was associated with relatively higher nutrient digestibility, an improved intestinal bacterial profile, and a lower inflammatory response.
Study on the Vibration Characteristics of Separated Armature Assembly in an Electro-Hydraulic Servo Valve Under Interference Fit
Authors: Li Tong , Peng Jinghui , Li Songjing , Zhang Juan , Zhang Aiying
Published: February 2025

The electro-hydraulic servo valve is a critical component that transforms electrical signals into hydraulic signals, thereby controlling the hydraulic system. It finds extensive application in precision control systems. The stability of the electro-hydraulic servo valve is primarily influenced by the armature assembly. Unlike integral armature assembly, the separated armature assembly, comprising the armature, spring tube, flapper, and feedback spring, is joined through an interference fit, which introduces prestress within the assembly. The existence of prestress may affect the operational mode of the armature assembly. Consequently, this paper investigates the vibration characteristics of the separated armature assembly under interference fit conditions. Comparative analysis reveals that interference fit indeed generates prestress, which cannot be overlooked. To further validate the reliability of the simulation results, the natural frequency of the separated armature assembly is determined by applying a sweeping frequency signal to the torque motor using an electric drive, thereby verifying the feasibility of the simulation analysis. Additionally, the impact of interference on the vibration characteristics of the separated armature assembly is examined, confirming the accuracy of the simulation analysis method based on the interference fit. The research on vibration characteristics of a separated armature assembly provides technical support for the structural optimization design of the electro-hydraulic servo valve, thereby enhancing its performance.
Impostor Phenomenon Unveiled: Exploring Its Impact on Well-Being, Performance, and Satisfaction Among Employees
Authors: Swaidan Eman , Jabbour Al Maalouf Nada
Published: February 2025

The Impostor Phenomenon (IP) is a widespread psychological phenomenon impacting the personal and professional experiences of individuals. This study aims to examine the impact of the IP on employee well-being, performance, and job satisfaction within Higher Education Institutions (HEIs) in Lebanon. Moreover, this study explores if these effects vary depending on individuals’ personality types, such as introverted or extroverted, and if perceived organizational support (POS) plays a moderating role in these relationships. The research employed a mono-method quantitative approach to collect data from a sample of 155 faculty and staff employees using an online structured survey. Data were statistically analyzed using SPSS software. The findings obtained indicate that higher impostorism levels were linked to lower employee well-being, job satisfaction, and self-assessed job performance. Introverts showed a negative association between impostorism and well-being, while extroverts had significant negative associations with both job satisfaction and performance. POS only moderately influenced the association between impostorism and job satisfaction. The significance of the IP’s impacts on employee outcomes among different personality types is emphasized in this study. Furthermore, the moderating role played by POS highlighted the importance of organizational efforts in addressing employees’ experiences. This study provided insights to Human Resources (HR) professionals in Lebanon’s Higher Education Institutions to develop targeted interventions addressing IP experiences and personality types and promoting mental wellness and better job satisfaction and performance, and thus better organizational outcomes.
Mapping Customer Relationship Management Research in Higher Education: Trends and Future Directions
Authors: Shalihati Fithriyyah , Sumarwan Ujang , Hartoyo Hartoyo , Yuliati Lilik Noor
Published: February 2025

Customer relationship management (CRM) has become a critical strategy for higher education institutions (HEIs) to enhance student engagement, institutional efficiency, and digital transformation. Despite its growing adoption, the evolution of CRM research in HEIs, including key contributors, dominant themes, and emerging trends, remains underexplored. This study conducts a bibliometric analysis of Scopus-indexed publications (2014–2024) to map the intellectual landscape of CRM research in higher education. Using Biblioshiny with Bibliometrix version 4.0 and VOSviewer version 1.6.20, this study analyzes publication trends, influential authors and institutions, keyword networks, and thematic developments. The findings indicate a transition from early research on service quality and academic reputation to advanced themes such as AI-driven CRM strategies, multi-channel communication, and social media analytics. While the United Kingdom, India, and Indonesia emerge as leading contributors, gaps persist in cross-cultural CRM applications, the integration of emerging technologies, and the development of standardized evaluation frameworks. This study contributes to CRM scholarship by mapping research trajectories, identifying underexplored areas, and offering actionable insights for future studies. It highlights the expanding role of CRM beyond student engagement, encompassing education quality, labor market, employment growth, technological progress and AI-driven decision-making. These findings emphasize the need for interdisciplinary approaches and robust academic performance to maximize CRM’s strategic potential in higher education.
Development of a Crawler-Type Self-Propelled Machine with Trenching, Fertilizing, and Soil-Covering Components for Hilly Orchard
Authors: Li Jun , Mai Chaodong , Zeng Ye , Li Zhao , Jiang Runpeng , Weng Qinglin , Cai Jiamin , Wang Qian , Li Can
Published: February 2025

In response to the issues of high energy consumption, limited functionality, and uneven soil–fertilizer mixing in mechanical operations for trenching and fertilizing in hilly orchards, this study proposes the design of a crawler-type self-propelled machine, integrating three main functions: trenching, fertilizing, and soil covering. The key components of the trenching device, fertilizing device, and soil-covering device were designed. Three fertilizing simulation models (pre-plant, mid-plant, and post-plant) were established using EDEM discrete element software. The soil–fertilizer mixing effects under each mode were analyzed, with results indicating that the post-plant fertilizing mode better meets the soil–fertilizer mixing requirements for deep organic fertilizer application. Using trenching speed, forward speed, and bending angle of the trenching knife as experimental factors, with operating power consumption and soil–fertilizer mixing uniformity as evaluation indicators, a Box–Behnken experiment was conducted to optimize the parameters of the trenching and fertilizing components. A regression model was established to analyze the interaction between experimental factors and indicators. The optimal operational parameter combination was determined as follows: trenching speed of 265.03 r/min, forward speed of 0.40 m/s, and bending angle of trenching knife of 130°. Under these parameters, the trenching power consumption and soil–fertilizer mixing uniformity were 1.74 kW and 77.15%, respectively. Orchard verification tests on the machine showed that under the optimal parameters, the relative errors in trenching power consumption and soil–fertilizer mixing uniformity between the field tests and simulations were 7.40% and 4.50%, respectively. These results meet the agronomic requirements for trenching and fertilizing, and the study provides valuable references for the application of related technologies in orchard trenching and fertilizing operations.
A Semi-Supervised Diffusion-Based Framework for Weed Detection in Precision Agricultural Scenarios Using a Generative Attention Mechanism
Authors: Li Ruiheng , Wang Xuaner , Cui Yuzhuo , Xu Yifei , Zhou Yuhao , Tang Xuechun , Jiang Chenlu , Song Yihong , Dong Hegan , Yan Shuo
Published: February 2025

The development of smart agriculture has created an urgent demand for efficient and accurate weed recognition and detection technologies. However, the diverse and complex morphology of weeds, coupled with the scarcity of labeled data in agricultural scenarios, poses significant challenges to traditional supervised learning methods. To address these issues, a weed detection model based on a semi-supervised diffusion generative network is proposed. This model integrates a generative attention mechanism and semi-diffusion loss to enable the efficient utilization of both labeled and unlabeled data. Experimental results demonstrate that the proposed method outperforms existing approaches across multiple evaluation metrics, achieving a precision of 0.94, recall of 0.90, accuracy of 0.92, and mAP@50 and mAP@75 of 0.92 and 0.91, respectively. Compared to traditional methods such as DETR, precision and recall are improved by approximately 10% and 8%, respectively. Additionally, compared to the enhanced YOLOv10, mAP@50 and mAP@75 are increased by 1% and 2%, respectively. The proposed semi-supervised diffusion weed detection model provides an efficient and reliable solution for weed recognition and introduces new research perspectives for the application of semi-supervised learning in smart agriculture. This framework establishes both theoretical and practical foundations for addressing complex target detection challenges in the agricultural domain.
Characterization of Phytophthora and Pythium Species Associated with Root Rot of Olive Trees in Morocco
Authors: Legrifi Ikram , Lazraq Abderrahim , Al Figuigui Jamila , Belabess Zineb , El Jarroudi Moussa , Lahlali Rachid
Published: February 2025

The olive tree is one of the most important fruit crops grown in Morocco, yet extensive decline associated with the root rot of this crop has been observed in many regions. This study aimed to identify and characterize the oomycetes associated with root rot disease in olive trees. During the 2021 and 2022 growing seasons, symptomatic root tissues and soil samples were collected for isolation. Based on morphological traits and the sequencing of the internal transcribed spacer (ITS) region of rDNA, 10 oomycete species were identified, belonging to the Phytophthora and Pythium sensu lato (s.l.) genera. Seven species were assigned to Phytophthora, namely, P. palmivora, P. plurivora, P. acerina, P. oleae, P. cactorum, P. gonapodyides, and P. megasperma. The Pythium s.l. genus was represented by three species, including P. schmitthenneri, P. aphanidermatum, and P. irregulare. A pathogenicity assay was conducted by soil infestation to evaluate the effect of these pathogens on one-year-old olive saplings (var. Picholine Marocaine). Results revealed that all 10 species were pathogenic to olive saplings. Inoculated saplings exhibited symptoms, such as root rot, vascular discoloration, and wilting. The pathogens were successfully re-isolated from necrotic roots, thereby fulfilling Koch’s postulates. These findings highlight the complex etiology of root rot disease in olive trees, as multiple species can induce similar symptoms. This study represents the first detailed report of Phytophthora and Pythium s.l. species associated with olive root rot disease in Morocco.
Nematicidal Extracts of Chinaberry, Parsley and Rocket Are Safe to Eisenia fetida, Enchytraeus albidus, Daphnia magna and Danio rerio
Authors: Anastasiadou Pelagia , Ntalli Nikoletta , Kyriakopoulou Katerina , Kasiotis Konstantinos M.
Published: February 2025

In the frame of a “greener agriculture”, the development of new natural pesticides that are safer than their synthetic counterparts is gaining ground. Nonetheless, the origin of their nature does not necessarily imply their eco-friendliness. Hence, specific ecotoxicological studies are needed, with products being subjected to hazard and consequent risk assessment, for registration purposes. We have previously described on the strong nematicidal activity of Melia azedarach (chinaberry), Petroselinum crispum (parsley) and Eruca sativa (rocket) against the nematode Meloidogyne incognita. With this study the effect of the above-mentioned nematicidal botanicals on Eisenia fetida, Enchytraeus albidus, Daphnia magna and Danio rerio (Zebrafish) is reported, being all model organisms for the study of ecotoxicology of pesticides under registration. The implemented protocols are according to the OECD standards used for the evaluation of formulates under authorization. NOEC values were estimated to be higher than the highest concentrations assessed as recommended by OECD guidelines (≥1000 mg test item/kg dry soil). According to the presented results, all tested botanical nematicidals proved ecofriendly, not hindering the reproduction of juvenile worms of Eisenia fetida, and Enchytraeus albidus. Notably, Petroselinum crispum exhibited beneficial effects on reproduction of Eisenia fetida, as the number of juveniles increased. M. azedarach extract demonstrated moderate toxicity to zebrafish embryos (LC50 was 51.41 ± 1.67 mg/L), yet it did not elicit adverse effects on the zebrafish liver. Thus, chinaberry, parsley and rocket are promising to be developed into new “green” nematicides.
Use of Bacterial-Enzymatic Inoculant Improves Silage Quality and Reduces Fermentation Losses in Intercropped Systems
Authors: Marques Bruno de Souza , Costa Kátia Aparecida de Pinho , Silva Luciana Maria da , Costa Adriano Carvalho , Ferrari Gerson Carlos , de Lima João Francisco , da Silva Amilton Ferreira , Matos Wildo Pereira , Gonçalves Lucas Ferreira , Lima Divino Antonio Santana , Ferreira Juliany Vale , Pontes Emilly Farias , Oliveira Fabrício Flávio Passos
Published: February 2025

The ensiling potential of Tamani guinea grass (Panicum maximum cv. BRS Tamani) and Stylosanthes cv. Bela in monoculture or intercropped systems, and the effect of two treatments on ensiling (with and without inoculant) on fermentation quality and nutritional composition of the silage after 50 days of ensiling, were evaluated. The experiment was conducted at the Instituto Federal Goiano, Campus Rio Verde, Goiás, Brazil, using a randomized block design with four replications in a 3 × 2 factorial scheme, totaling 24 experimental silos. The forage was harvested during a 28-day regrowth cycle. Results indicated that silages without inoculants showed inadequate fermentative characteristics, compromising nutritional preservation. The addition of microbial inoculants improved the fermentation process, ensuring proper preservation of silage. The intercropping of Tamani guinea grass with Stylosanthes cv. Bela resulted in higher dry matter production and improved the nutritional value of the silage, with increases of 3.46% in crude protein content, 20.96% in ADIP (acid detergent insoluble protein), 6.31% in soluble carbohydrates, and 10.06% in starch compared to the silage of Tamani guinea grass in monoculture. Therefore, the use of silage from intercropped Tamani guinea grass and Stylosanthes cv. Bela with the addition of inoculants can be recommended as a productive and sustainable practice, reducing costs associated with protein and mineral supplementation.
Emerging Treatment Options for Peanut Allergy
Authors: Satnarine Travis , Xavier de Almeida Alana , Woody Malaika , Banegas Carballo Krisia , Chan Diana , Thompson Pytregay , Kleiner Gary , Gans Melissa
Published: February 2025

Peanut allergy, a significant public health issue, poses challenges due to its potential for life-threatening anaphylaxis and profound impact on quality of life. Traditional management approaches, including allergen avoidance and epinephrine administration, are effective in mitigating acute symptoms but do not address the underlying allergy or long-term disease burden. Recent advances in immunotherapy and biologics, as well as innovative technologies such as gene editing and microbiome modulation, have introduced promising pathways for desensitization and sustained unresponsiveness. This review provides a comprehensive exploration of emerging therapies for peanut allergy, including oral, sublingual, and epicutaneous immunotherapy, biologic agents, gene-editing techniques, and novel drug therapies. We discuss their mechanisms, clinical efficacy, and associated challenges, emphasizing the potential for these innovations to revolutionize peanut allergy treatment. Despite significant progress, barriers such as adverse reactions, cost, and limited access remain. Addressing these challenges through further research and standardization could transform the future of peanut allergy management.
Chromosome-Level Genome Assembly of the Meishan Pig and Insights into Its Domestication Mechanisms
Authors: Du Huipeng , Hu Jianchao , Zhang Zhiyan , Wu Zhongzi
Published: February 2025

Pigs are essential agricultural animals, and among the various breeds, the Meishan pig, a native breed of China, is renowned for its high reproductive performance. This breed has been introduced to many countries to enhance local pig breeding programs. However, there have been limited genomic and population genetics studies focusing on Meishan pigs. We created a chromosomal-level genomic assembly using high-depth PacBio sequencing and Illumina sequencing data collected from a Meishan pig. Additionally, we analyzed whole-genome sequencing (WGS) data from Chinese boars and Meishan pigs to identify domestication selection signals within the Meishan breed. The assembled genome of the Meishan pig (MSjxau) was found to be 2.45 Gb in size, with a scaffold length of 139.17 Mb. The quality value was 37.06, and the BUSCO score was 96.2%, indicating good completeness, continuity, and accuracy. We annotated transposable elements, segmental duplication, and genes in the MSjxau genome. By combining these data with 28 publicly available genomes, we provide a high-quality structural variants resource for pigs. Furthermore, we identified 716 selective sweep intervals between Chinese wild pigs and Meishan pigs, where the selected gene PGR may be linked to the high fertility observed in Meishan pigs. Our study offers valuable genomic and variation resources for pig breeding and identifies several genes associated with the domestication of the Meishan pig. This lays the groundwork for further investigation into the genetic mechanisms behind complex traits in pigs.
Is High-Dose Ubiquinone Therapy Before Cardiac Surgery Enough to Reduce the Incidence of Cardiac Surgery-Associated Acute Kidney Injury? A Randomized Controlled Trial
Authors: Vučemilović Hrvoje , Kovač Ruben , Stanišić Lada , Sanader Vučemilović Ana , Mrčela Dina , Benzon Benjamin , Carev Mladen
Published: February 2025

Cardiac surgery-related acute kidney injury (CS-AKI) is a decrease in kidney function after open-heart surgery, affecting up to 50% of patients. The pathophysiology of CS-AKI involves ischemia–reperfusion injury, inflammation, and oxidative stress. Ubiquinone is a potent antioxidant, and we hypothesized that it could decrease both the incidence and severity of CS-AKI. The intervention group received ubiquinone (8 mg/kg/day) divided into three daily doses, while the control group received a placebo. The primary outcome was the incidence of CS-AKI, which was manifested as an increase in creatinine ≥26.5 µmol/L or a urine output below 0.5 mL/kg/h for 6 h. Out of 73 patients, 39.7% (N = 29) developed CS-AKI, including 35.3% of the ubiquinone group and 43.6% of the placebo group (X2(1,N = 73) = 0.4931, p = 0.4825). The secondary outcomes revealed that the ubiquinone group experienced reduced postoperative bleeding, with a median (IQR) drainage of 320 mL (230–415) compared to the drainage of 420 mL (242.5–747.5) in the placebo group (t(35.84) = 2.055, p = 0.047). The median hs-TnI level in the ubiquinone group was 239.5 ng/mL (113.25–382.75) after surgery compared to a level of 366 (234.5–672.5) ng/mL in the placebo group (p = 0.024). In conclusion, there was no significant difference in the incidence of CS-AKI between groups. Postoperative hs-TnI and bleeding were significantly reduced among patients receiving ubiquinone.
Orofacial Lymphedema in Phelan–McDermid Syndrome: A Case of Hemifacial Involvement and a Scoping Review
Authors: De Falco Domenico , Di Stasio Dario , Lauritano Dorina , Lucchese Alberta , Petruzzi Massimo
Published: February 2025

Phelan–McDermid syndrome (PMS) is a rare genetic disorder primarily caused by deletions or structural alterations of chromosome 22q13, often involving the SHANK3 gene. However, mutations in other genes, such as CELSR1, or deletions in the interstitial regions of 22q13 contribute to the phenotypic variability of PMS. The syndrome is characterized by developmental delay, cognitive impairment, absent or significant impairment speech, autism spectrum disorder (ASD), and distinctive craniofacial features. Lymphedema, present in 10–25% of cases, typically affects peripheral regions, while facial involvement has not been documented to date. Orofacial manifestations frequently include dolichocephaly, widely spaced eyes, prominent ears, and dysmorphic features, such as a bulbous nose and arched palate. This scoping review analyzed seven studies on orofacial features associated with PMS, highlighting a higher phenotypic variability, with frequent findings of intellectual disability, hypotonia, and craniofacial dysmorphisms. Genomic analyses identified consistent deletions in 22q13.31–q13.33 and complex genomic rearrangements. This review, through the report of the first documented case of hemifacial lymphedema in the literature, analyzes the facial features of patients with PMS and their genetic origins. It also highlights the importance of interdisciplinary collaboration and inclusive genetic testing to better define the phenotypic spectrum of this syndrome. A deeper understanding of the genetic and clinical characteristics of PMS can facilitate early diagnosis and personalized management for these patients.
An Integrated Hierarchical Wireless Acoustic Sensor Network and Optimized Deep Learning Model for Scalable Urban Sound and Environmental Monitoring
Authors: Peng Bo , Wang Kevin I-Kai , Abdulla Waleed H.
Published: February 2025

Urban sound encompasses various acoustic events, from critical safety-related sound to everyday environmental noise. In response to the need for comprehensive and scalable sound monitoring, this study introduces an integrated system combining the Hierarchical Wireless Acoustic Sensor Network (HWASN) with the new proposed end-to-end CNN-CNN-BiLSTM-Attention (CCBA) sound classification model. HWASN facilitates large-scale, scalable sound data collection and transmission through a multi-hop architecture. At the same time, the CCBA model, optimized for Jetson Nano, delivers high-accuracy classification in noisy environments with minimal computational overhead. The CCBA model is trained using distillation techniques, achieving up to a 71-fold speed-up compared to its teacher system. Real-world deployments demonstrate the system’s robust performance under dynamic acoustic conditions. Combining HWASN’s scalability with CCBA’s classification efficiency provides a versatile and long-term solution for comprehensive urban sound monitoring. Additionally, other environmental parameters, such as air quality, light intensity, temperature, humidity, and atmospheric pressure, are sampled using this system to enhance its application in smart city management, urban planning, and public safety, addressing various modern urban needs.
Intelligent Analysis of Flow Field in Cleaning Chamber for Combine Harvester Based on YOLOv8 and Reasoning Mechanism
Authors: Li Qinglin , Wan Ruihai , Wu Zhaoyue , Yan Yuting , Zhang Xihan
Published: February 2025

As the main working part of a combine harvester, the cleaning device affects the cleaning performance of the machine. The simulation of flow fields in a cleaning chamber has become an important part of the design. Currently, post-processing analyses of flow field simulation still rely on the researchers’ experience, so it is difficult to obtain information from post-processing automatically. The experience of researchers is difficult to describe and disseminate. This paper studied an intelligent method to analyze simulation result data which is based on the object detection algorithm and the reasoning mechanism. YOLOv8, one of the deep learning object detection algorithms, was selected to identify key-point data from the flow field in a cleaning chamber. First, the training dataset was constructed via scatter plot drawing, data enhancement, random screening, and other technologies. Then, the flow field in the cleaning chamber was divided into six key areas by identifying the key points of the flow field. And, an analysis of the reasonable wind velocity in the areas was conducted, and the cleaning results of the grain were obtained by using the reasoning mechanism based on rules and examples. Finally, a system based on the above method was established in Python 3.10 software. With the help of the method and the system in this paper, the flow field characteristics in a cleaning chamber and the effects of wind on the cleaning effect can be obtained automatically if the physical properties of the crop, the geometric parameters of the cleaning chamber, and the working parameters of the machine are given.
Study of Reynolds Number Effects on Aerodynamic Forces and Vortex-Induced Vibration Characteristics of a Streamlined Box Girder
Authors: Wang Binxuan , Sun Yifei , Liu Qingkuan , Li Zhen , Han Yuan , Li Kaiwen
Published: February 2025

Due to the limitations of wind tunnel speed and size, achieving a model’s Reynolds number equal to the actual Reynolds number is challenging and may lead to discrepancies between experimental and actual results. To investigate the effects of the Reynolds number on the aerodynamic forces and vortex-induced vibration (VIV) characteristics of a streamlined box girder, wind tunnel tests were conducted to study the variations in aerodynamic forces and surface pressures on the static main beam, as well as the VIV response and time–frequency characteristics of the aerodynamic forces on the dynamic main beam, as the Reynolds number varied. The results indicate that in static tests, as the Reynolds number increases, the drag coefficient of the main beam decreases, the lift coefficient slightly increases, and the pitching moment coefficient remains almost unchanged. The root mean square (RMS) values of the wind pressure coefficients show a significant Reynolds number effect, with values generally decreasing as the Reynolds number increases. In free vibration tests, as the Reynolds number increases, the onset wind speed of VIV increases from 14.35 m/s to 16.03 m/s, the maximum amplitude decreases from 0.076 to 0.004, and the VIV lock-in range narrows. The dynamic pressure results indicate that as the Reynolds number increases, the RMS values of the wind pressure coefficients decrease. At some measurement points, the dominant frequencies of the fluctuating pressure amplitude spectra deviate from the corresponding VIV frequency, and the correlation and contribution coefficients between the local aerodynamic forces and the overall vortex-induced force (VIF) decrease. These changes may explain the reduction in the VIV amplitude with an increasing Reynolds number. The motion state of the main beam has a minimal effect on the mean wind pressure coefficients and their Reynolds number effect, whereas it has a more significant effect on the RMS values of the pressure coefficients.
Time-Dependent Vehicle Routing Problem with Drones Under Vehicle Restricted Zones and No-Fly Zones
Authors: Wei Shuo , Fan Houming , Ren Xiaoxue , Diao Xiaolong
Published: February 2025

This paper addresses the time-dependent vehicle routing problem with drones in vehicle-restricted zones and no-fly zones (TDVRPD-VRZ-NFZ). The optimization model considers the impacts of vehicle-restricted zones, no-fly zones, and time-dependent road networks on delivery paths. The objective is to minimize the total cost, including vehicle dispatch costs, energy consumption costs for vehicles and drones, and time-window penalty costs. The model is verified for correctness using Gurobi. In response to the problem’s characteristics, a hybrid genetic algorithm and variable neighborhood search with a learning mechanism (HGAVNS-LM) is proposed to solve the problem. The algorithm starts by generating the initial population using a combination of logistic mapping and reverse learning. It then improves the genetic operators and variable neighborhood search operators to optimize the initial population. To improve the algorithm’s performance, an individual elite archive is used for knowledge learning, and a self-learning mechanism is established to dynamically adjust the algorithm’s key parameters. The solution obtained by HGAVNS-LM shows a deviation of −0.2% to −0.3% compared to Gurobi, but it saves 99.68% in solving time. Compared to the genetic neighborhood search algorithm and the hybrid genetic algorithm, the improvement rates are 5.1% and 13.0%, respectively. Through the analysis of multiple sets of test cases, it is concluded that time-varying road networks, vehicle-restricted zones and no-fly zones, and different detour rules all affect delivery costs and delivery plans. The research results provide a more scientific theoretical basis for logistics companies to customize delivery solutions.
Research on the Fine Control of the Influence of Pipe-Jacking Parameter Deviation on Surrounding Stratum Deformation
Authors: Zhang Tianlong , Chen Guoqing , Lu Ping , Nie Dongqing
Published: February 2025

Based on the Zhuyuan–Bailonggang sewage interconnection pipe project in Shanghai, the ABAQUS finite element software was used in numerical simulations to study the fine control of stratum disturbances caused by pipe jacking parameter deviation in soft soil areas. Combining the simulation results with onsite measured data, the Peck formula was used to predict surface settlement. The results indicate the following: (1) The jacking speed and face pressure are negatively correlated with surface settlement. Under the maximum positive deviation and negative deviations in the jacking speed, after the tail passes through the monitoring section D0 16 ring, the maximum value of settlement at point B8 increases by 21.6% and decreases by 12.8%, respectively. Increasing the jacking speed increases the area with stress change ratio R < 0 at monitoring section D0, and the arch foot at the tail of the pipe jacking machine decreases the surface settlement. In contrast, when the face pressure deviates from its average value, the variation range is less than 1%. (2) The pipe slurry coefficient and surface subsidence are positively correlated. Under the maximum positive deviation and the maximum negative deviation, the tail passes through the monitoring section D0 16 ring, and the maximum settlement value at B8 decreases by 4.9% and increases by 16.5%, respectively. The increase in the coefficient reduces the area with R < 0 at D0 and increases the surface settlement. (3) In the order of descending strength, surface settlement is affected by the jacking speed, slurry friction coefficient, and face pressure. (4) To predict the maximum surface settlement value due to deviations in the jacking parameters, the Peck formula was modified using a correction factor α ranging from 0.6 to 3.0 and a settlement trough width correction factor β ranging from 1.6 to 4.0. The modified prediction curve is in closer agreement with the actual conditions.
Reservoir Fluid PVT High-Pressure Physical Property Analysis Based on Graph Convolutional Network Model
Authors: Li Binghuan , Jiang Shan
Published: February 2025

In this paper, the high-pressure physical property analysis of reservoir fluid PVT (pressure–volume–temperature) was studied to improve the accuracy and efficiency of reservoir fluid property prediction. Due to the limitations of traditional laboratory measurement and theoretical model prediction methods, the graph convolutional network (GCN) model was introduced in this paper, and the enhanced ChebNet model was used to analyze the complex relationship between the high pressure physical property parameters. The key parameters such as bubble point pressure, volume coefficient, and crude oil viscosity were accurately predicted by using Chebyshev polynomial approximation and the matrix product optimization ChebNet model, which was constructed to represent the high pressure physical property parameters and their relationships. The experimental results showed that compared with linear regression, linear discrimination, random forest, and ordinary ChebNet models, the enhanced ChebNet model introduced in this paper presented significant advantages in evaluation indicators, and the AUC value reached the optimal value. This paper provides a new perspective and method for reservoir fluid PVT high-pressure physical property analysis and explores a new possibility for the application of graph convolutional networks in oil and gas exploration and development.
A Survey on Energy Drainage Attacks and Countermeasures in Wireless Sensor Networks
Authors: Lee Joon-Ku , Choi You-Rak , Suh Beom-Kyu , Jung Sang-Woo , Kim Ki-Il
Published: February 2025

Owing to limited resources, implementing conventional security components in wireless sensor networks (WSNs) rather than wireless networks is difficult. Because most sensor nodes are typically powered by batteries, the battery power should be sufficiently long to prevent the shortening of the network lifetime. Therefore, many studies have focused on detecting and avoiding energy drainage attacks in WSNs. However, a survey paper has yet to be published for energy drain attacks in WSNs since 2019. Therefore, we present a novel comprehensive survey paper for energy drainage attacks in WSNs. First, we address an overview of WSNs and their security issues. Next, we explain the methodology for this study and explain the existing approaches for energy drainage attacks in layered architectures. Based on the results of this analysis, open issues and further research directions are presented.
Simulation Analysis of Fracture Process of High Moisture Content Corn Kernel Carpopodium
Authors: Li Xinping , Li Yanan , Bin Peng , Sun Ruizhe , Xu Shendi , Wang Junyi , Hou Jiarui
Published: February 2025

Corn is an important economic and food crop, and the corn threshing process is an important link in the processing of corn, but the damage rate in the threshing process has always been a problem, causing difficulties in subsequent processing and storage. To address the high damage rate in corn ear threshing, a texture analyzer was used to measure the fracture force of Boyun 88 and Zhengdan 958 corn varieties in the triaxial direction, and a CT scanning imaging system was used to analyze the connection mode between the carpopodium and the corn cob. The connection between the carpopodium and corn cob, as well as the fracture process of the carpopodium, was simulated. Finally, high-speed photography was used to study the corn ear threshing process. The results indicated that the fracture force of the carpopodium under radial tension was significantly greater than that under axial and tangential shear. Additionally, the simulated fracture stress value of the carpopodium exceeded its actual fracture stress value. Under radial stress, the fracture force between the carpopodium and corn cob exhibited more uniformity on the contact surface. When a tangential load was applied, it was observed that the force chain shifted and dissipated along the axis during corn kernel extrusion. High-speed photography on a discrete test bench revealed that corn kernel dispersion, extrusion, and force transfer facilitated the movement and migration of surrounding kernels, with the force transfer process resembling a “trapezoid”. This study offers theoretical guidance for corn threshing with low damage and an analysis of the threshing process.
A Multitask-Based Transfer Framework for Cooperative Multi-Agent Reinforcement Learning
Authors: Hu Cheng , Wang Chenxu , Luo Weijun , Yang Chaowen , Xiang Liuyu , He Zhaofeng
Published: February 2025

Multi-agent reinforcement learning (MARL) has proven to be effective and promising in team collaboration tasks. Knowledge transfer in MARL has also received increasing attention. Compared to knowledge transfer in single-agent tasks, knowledge transfer in multi-agent tasks is more complex due to the need to account for coordination among agents. However, existing knowledge transfer-based methods only focus on strategies or agent-level knowledge in a single task, and the transfer of knowledge in such a specific task to new and different types of tasks is likely to fail. In this paper, we propose a multitask-based training framework termed MTT in cooperative MARL, which aims to learn shared collaborative knowledge across multiple tasks simultaneously and then apply it to solve other related tasks. However, models obtained from multitask learning may fail on other tasks because the gradients from different tasks may conflict with each other. To obtain a model with shared knowledge, we provide conflict-free updates by ensuring a positive dot product between the final update and the gradient of each specific task. It also maintains a consistent optimization rate for all tasks. Experiments conducted in two popular environments, StarCraft II Multi-Agent Challenge and Google Research Football, demonstrate that our method outperforms the baselines, significantly improving the efficiency of team collaboration.
Integrated Fusion Network for Hyperspectral, Multispectral and Panchromatic Data Fusion
Authors: Pan Jinyin , Wang Shidong , Li Huachao , Yuan Zhanliang , Yuan Binbin , Peng Jinyan , Liu Yuanyuan
Published: February 2025

The fusion of traditional HSI mainly involves the fusion of HSI with MSI or PAN. Nevertheless, the combination of the former is constrained by the inadequate spatial resolution of MSI, and therefore the enhancement of the spatial resolution of HSI is inadequate. The latter is constrained by the substantial disparity in spectral information between PAN and HSI, leading to pronounced distortion of high-resolution HSI. To address this issue, this paper proposes IFNPMH, which is an integrated fusion network for used for the fusion of HSI, MSI, and PAN. The IFNPMH algorithm is capable of efficiently extracting spatial information from MSI and PAN, as well as spectral information from HSI. It combines the spatial and spectral information to produce fused images that possess precise spectral information and distinct spatial details. Specifically, IFNPMH incorporates the CBAM attention mechanism module to enhance feature representation capabilities. Finally, this article proposes a loss function that combines spectral and spatial information loss in IFNPMH training. The effectiveness of the proposed IFNPMH is demonstrated by extensive testing in comparison to other sophisticated approaches. This model has shown promising performance in terms of qualitative visual effects and quantitative evaluation metrics.
BIM for Safety: Applying Real-Time Monitoring Technologies to Prevent Falls from Height in Construction
Authors: Pereira Filipa , González García María de las Nieves , Poças Martins João
Published: February 2025

There are significant risks in the construction sector, with falls from height identified a greater hazard than in most other industries. Efforts to improve working conditions and reduce accident rates have driven research into real-time monitoring technologies to reduce the risk of falls. The main objective of this research is to review existing real-time monitoring technologies, identify the most relevant, and analyse their benefits and impact on reducing workplace accidents in the construction sector. A systematic review was conducted using PRISMA methodology to investigate the use of real-time monitoring technologies in the construction industry. Only studies specifically investigating real-time fall risk assessment were included. Of the initial 446 articles reviewed, 39 were considered highly relevant to the research objectives. Various wireless and computer vision technologies were identified for real-time worker monitoring, often integrated with BIM to improve workplace safety. The findings suggest that a combination of technologies may produce more effective results for worker monitoring. However, further research is needed to verify the applicability of these technologies on construction sites.
Aluminum Laser Additive Manufacturing: A Review on Challenges and Opportunities Through the Lens of Sustainability
Authors: Yadegari Mohammad Javad , Martucci Alessandra , Biamino Sara , Ugues Daniele , Montanaro Laura , Fino Paolo , Lombardi Mariangela
Published: February 2025

The manufacturing sector is a major contributor to global energy consumption and greenhouse gas emissions, positioning sustainability as a critical priority. Aluminum, valued for its lightweight and recyclable properties, plays a vital role in advancing energy-efficient solutions across transportation and aerospace industries. The processing of aluminum alloys through laser-based powder bed fusion of metals (PBF-LB/M), a cutting-edge additive manufacturing technology, enhances sustainability by optimizing material usage and enabling innovative lightweight designs. Based on the published literature, the present study analyzed the ecological impacts of aluminum PBF-LB/M manufacturing through life cycle assessment, circular economy principles, and eco-design strategies, identifying opportunities to reduce environmental footprints. The study also stated the critical challenges, such as the high energy demands of the aluminum PBF-LB/M process and its scalability limitations. Potential sustainable solutions were discussed starting from powder production techniques, as well as optimized processes and post-processing strategies. By adopting an interdisciplinary approach, this research highlighted the pivotal role of PBFed aluminum alloys in achieving sustainable manufacturing goals. It provided actionable insights to drive innovation and resilience in industrial applications, offering a roadmap for balancing environmental stewardship with the demands of high-performance standards.
Physics-Guided Neural Network-Based Feedforward Control for Seamless Pipe Manufacturing Process
Authors: Filipović Luka , Miličić Luka , Ristanović Milan , Dimitrijević Vladan , Jovanović Petar
Published: February 2025

Artificial intelligence (AI) is increasingly being utilized in the industrial sector, revolutionizing traditional manufacturing processes with advanced automation systems. Despite their potential, neural networks have seen limited adoption in industrial control systems due to their lack of interpretability compared to traditional methods. The recently introduced physics-guided neural networks (PGNNs) address this limitation by embedding physical knowledge directly into the network structure, enhancing the interpretability and robustness. This study proposes a novel feedforward control framework that integrates a reduced-order physics-based model of a hydraulic actuator with a data-driven correction term for accurate force control in the seamless pipe manufacturing process. The coupled dynamics of the actuator and the continuously cast material being pushed into the piercing mill are identified through experimental data, and reduced-order models are developed for integration into the PGNN structure. The training of the networks is performed on a dataset from a scaled industrial hydraulic system, with the validation of the proposed methods conducted on a neural processing unit (NPU), a specialized industrial-grade platform for AI, operating within a PLC environment. The results demonstrate real-time execution with excellent force tracking, even with a limited training dataset—a typical constraint in industrial processes—while providing safer and more predictable behavior compared to traditional neural-network-only solutions.