bluuebunny/crossref_metadata_2025 huggingface dataset:
Observation of Agonistic Behavior in Pacific White Shrimp (Litopenaeus vannamei) and Transcriptome Analysis
Authors: Wu Bo , Zhao Chenxi , Zheng Xiafei , Peng Zhilan , Liu Minhai
Published: June 2024

Agonistic behavior has been identified as a limiting factor in the development of intensive L. vannamei aquaculture. However, the characteristics and molecular mechanisms underlying agonistic behavior in L. vannamei remain unclear. In this study, we quantified agonistic behavior through a behavioral observation system and generated a comprehensive database of eyestalk and brain ganglion tissues obtained from both aggressive and nonaggressive L. vannamei employing transcriptome analysis. The results showed that there were nine behavior patterns in L. vannamei which were correlated, and the fighting followed a specific process. Transcriptome analysis revealed 5083 differentially expressed genes (DEGs) in eyestalk and 1239 DEGs in brain ganglion between aggressive and nonaggressive L. vannamei. Moreover, these DEGs were primarily enriched in the pathways related to the energy metabolism process and signal transduction. Specifically, the phototransduction (dme04745) signaling pathway emerges as a potential key pathway for the adjustment of the L. vannamei agonistic behavior. The G protein-coupled receptor kinase 1-like (LOC113809193) was screened out as a significant candidate gene within the phototransduction pathway. Therefore, these findings contribute to an enhanced comprehension of crustacean agonistic behavior and provide a theoretical basis for the selection and breeding of L. vannamei varieties suitable for high-density aquaculture environments.
Welfare Assessment in Pigs Using the Salivary Proteome
Authors: Prims Sara , Van Ginneken Chris , Van Ostade Xaveer , Casteleyn Christophe
Published: June 2024

Identifying the potential presence of stress at the pig farm is fundamental since it affects pig welfare. As a result, a reliable and straightforward tool to monitor stress could record the welfare status of the animals. Although numerous methods to assess the welfare of pigs have been developed in the past, no gold standard has been established yet. Recently, the value of saliva as a tool to identify chronic stress in piglets was explored, as it can be collected fast and non-invasively. Since the protein composition, i.e., the proteome of porcine saliva, responds to stress, the affected proteins could be used as salivary stress biomarkers. The present review first defines stress and its relationship with welfare. Next, the porcine gland-specific salivary proteome is characterized. Finally, six potential salivary biomarkers for stress are proposed, i.e., odorant-binding protein, vomeromodulin-like protein, chitinase, lipocalin-1, long palate lung and nasal epithelium protein, and alpha-2-HS-glycoprotein.
Emergence of Plasmid-Mediated Quinolone Resistance (PMQR) Genes in Campylobacter coli in Tunisia and Detection of New Sequence Type ST13450
Authors: Gharbi Manel , Tiss Rihab , Chaouch Melek , Hamrouni Safa , Maaroufi Abderrazak
Published: June 2024

The aim of this study is to investigate the occurrence of plasmid mediated quinolone resistance (PMQR) determinants in Campylobacter coli isolates collected from broilers, laying hens and poultry farm environments. One hundred and thirty-nine C. coli isolates were isolated from broilers (n = 41), laying hens (n = 53), eggs (n = 4) and the environment (n = 41) of 23 poultry farms located in northeastern of Tunisia. Antimicrobial susceptibility testing was performed on all isolates according to the recommendation of the European Committee on Antimicrobial Susceptibility Testing guidelines. The detection of PMQR genes: qnrA, qnrB, qnrC, qnrD, qnrS, qepA, and aac(6)-Ib gene was performed using polymerase chain reaction (PCR) and specific primers. aac(6′)-Ib amplicons were further analyzed by digestion with BtsCI to identify the aac(6′)-Ib-cr variant. Mutations in GyrA and the occurrence of RE-CmeABC efflux pump were determined by mismatch amplification mutation assay (MAMA) PCR and PCR, respectively. In addition, eleven isolates were selected to determine their clonal lineage by MLST. The 139 C. coli isolates were resistant to ciprofloxacin, and 86 (61.8%) were resistant to nalidixic acid. High rates of resistance were also observed toward erythromycin (100%), azithromycin (96.4%), tetracycline (100%), chloramphenicol (98.56%), ampicillin (66.1%), amoxicillin-clavulanic acid (55.39%), and kanamycin (57.55%). However, moderate resistance rates were observed for gentamicin (9.35%) and streptomycin (22.3%). All quinolone-resistant isolates harbored the Thr-86-Ile amino acid substitution in GyrA, and the RE-CmeABC efflux pump was detected in 40.28% of isolates. Interestingly, the qnrB, qnrS, qepA, and aac(6′)-Ib-cr were detected in 57.7%, 61.15%, 21.58%, and 10% of isolates, respectively. The eleven isolates studied by MLST belonged to a new sequence type ST13450. This study described for the first time the occurrence of PMQR genes in C. coli isolates in Tunisia and globally.
Deciphering the Antibacterial Mechanisms of 5-Fluorouracil in Escherichia coli through Biochemical and Transcriptomic Analyses
Authors: Zhang Muchen , Song Huangwei , Yang Siyuan , Zhang Yan , Tian Yunrui , Wang Yang , Liu Dejun
Published: June 2024

The emergence of carbapenem-resistant Gram-negative pathogens presents a clinical challenge in infection treatment, prompting the repurposing of existing drugs as an essential strategy to address this crisis. Although the anticancer drug 5-fluorouracil (5-FU) has been recognized for its antibacterial properties, its mechanisms are not fully understood. Here, we found that the minimal inhibitory concentration (MIC) of 5-FU against Escherichia coli was 32–64 µg/mL, including strains carrying blaNDM-5, which confers resistance to carbapenems. We further elucidated the antibacterial mechanism of 5-FU against E. coli by using genetic and biochemical analyses. We revealed that the mutation of uracil phosphoribosyltransferase-encoding gene upp increased the MIC of 5-FU against E. coli by 32-fold, indicating the role of the upp gene in 5-FU resistance. Additionally, transcriptomic analysis of E. coli treated with 5-FU at 8 µg/mL and 32 µg/mL identified 602 and 1082 differentially expressed genes involved in carbon and nucleic acid metabolism, DNA replication, and repair pathways. The biochemical assays showed that 5-FU induced bacterial DNA damage, significantly increased intracellular ATP levels and the NAD+/NADH ratio, and promoted reactive oxygen species (ROS) production. These findings suggested that 5-FU may exert antibacterial effects on E. coli through multiple pathways, laying the groundwork for its further development as a therapeutic candidate against carbapenem-resistant bacterial infections.
Antimicrobial and Antibiofilm Effects of Bithionol against Mycobacterium abscessus
Authors: Cao Dan , Yuan Xin , Jiang Xiuzhi , Wu Tiantian , Xiang Yanghui , Ji Zhongkang , Liu Jiaying , Dong Xu , Bi Kefan , Tønjum Tone , Xu Kaijin , Zhang Ying
Published: June 2024

Mycobacterium abscessus (M. abscessus) is a multidrug-resistant nontuberculous mycobacterium (NTM) that is responsible for a wide spectrum of infections in humans. The lack of effective bactericidal drugs and the formation of biofilm make its clinical treatment very difficult. The FDA-approved drug library containing 3048 marketed and pharmacopeial drugs or compounds was screened at 20 μM against M. abscessus type strain 19977 in 7H9 medium, and 62 hits with potential antimicrobial activity against M. abscessus were identified. Among them, bithionol, a clinically approved antiparasitic agent, showed excellent antibacterial activity and inhibited the growth of three different subtypes of M. abscessus from 0.625 μM to 2.5 μM. We confirmed the bactericidal activity of bithionol by the MBC/MIC ratio being ≤4 and the time–kill curve study and also electron microscopy study. Interestingly, it was found that at 128 μg/mL, bithionol could completely eliminate biofilms after 48h, demonstrating an outstanding antibiofilm capability compared to commonly used antibiotics. Additionally, bithionol could eliminate 99.9% of biofilm bacteria at 64 μg/mL, 99% at 32 μg/mL, and 90% at 16 μg/mL. Therefore, bithionol may be a potential candidate for the treatment of M. abscessus infections due to its significant antimicrobial and antibiofilm activities.
RSM- and ANN-Based Multifrequency Ultrasonic Extraction of Polyphenol-Rich Sargassum horneri Extracts Exerting Antioxidative Activity via the Regulation of MAPK/Nrf2/HO-1 Machinery
Authors: Javed Ahsan , Alam Md Badrul , Naznin Marufa , Ahmad Raees , Lee Chang Hyung , Kim Sunghwan , Lee Sang-Han
Published: June 2024

Sargassum horneri (SH) is widely consumed as a healthy seaweed food in the Asia–Pacific region. However, the bioactive components contributing to its biological activity remain unknown. Herein, we optimized multifrequency ultrasonic-assisted extraction conditions to achieve higher antioxidant activity using a response surface methodology and an artificial neural network. High-resolution mass spectrometry (HRMS; negative mode) was used to tentatively identify the secondary metabolites in the optimized SH extract, which were further tested against oxidative stress in RAW264.7 cells. Additionally, the identified compounds were analyzed in silico to determine their binding energies with the Keap1 protein (4L7B). We identified 89 compounds using HRMS, among which 19 metabolites (8 polyphenolics, 2 flavonoids, 2 lignans, 2 terpenes, 2 tannins, 2 sulfolipids, and 1 phospholipid) were putatively reported for the first time in SH. The in vitro results revealed that optimized SH extract inhibited oxidative stress via the Nrf2/MAPKs/HO-1 pathway in a dose-dependent manner. This result was validated by performing in silico simulation, indicating that sargaquinoic acid and glycitein-7-O-glucuronide had the highest binding energies (−9.20 and −9.52 Kcal/mol, respectively) toward Keap1 (4L7B). This study offers a unique approach for the scientific community to identify potential bioactive compounds by optimizing the multivariant extraction processing conditions, which could be used to develop functional and nutraceutical foods.
Ergothioneine-Mediated Neuroprotection of Human iPSC-Derived Dopaminergic Neurons
Authors: Leow Damien Meng-Kiat , Cheah Irwin Kee-Mun , Chen Lucrecia , Ng Yang-Kai , Yeo Crystal Jing-Jing , Halliwell Barry , Ong Wei-Yi
Published: June 2024

Cell death involving oxidative stress and mitochondrial dysfunction is a major cause of dopaminergic neuronal loss in the substantia nigra (SN) of Parkinson’s disease patients. Ergothioneine (ET), a natural dietary compound, has been shown to have cytoprotective functions, but neuroprotective actions against PD have not been well established. 6-Hydroxydopamine (6-OHDA) is a widely used neurotoxin to simulate the degeneration of dopaminergic (DA) neurons in Parkinson’s disease. In this study, we investigated the protective effect of ET on 6-OHDA treated iPSC-derived dopaminergic neurons (iDAs) and further confirmed the protective effects in 6-OHDA-treated human neuroblastoma SH-SY5Y cells. In 6-OHDA-treated cells, decreased mitochondrial membrane potential (ΔΨm), increased mitochondrial reactive oxygen species (mROS), reduced cellular ATP levels, and increased total protein carbonylation levels were observed. 6-OHDA treatment also significantly decreased tyrosine hydroxylase levels. These effects were significantly decreased when ET was present. Verapamil hydrochloride (VHCL), a non-specific inhibitor of the ET transporter OCTN1 abrogated ET’s cytoprotective effects, indicative of an intracellular action. These results suggest that ET could be a potential therapeutic for Parkinson’s disease.
A Systematic Review of Cardio-Metabolic Properties of Lonicera caerulea L.
Authors: Bora Larisa , Lombrea Adelina , Batrina Stefan Laurentiu , Buda Valentina Oana , Esanu Oana-Maria , Pasca Oana , Dehelean Cristina Adriana , Dinu Stefania , Diaconeasa Zorita , Danciu Corina
Published: June 2024

In the light of growing concerns faced by Western societies due to aging, natality decline, and epidemic of cardio-metabolic diseases, both preventable and treatable, new and effective strategical interventions are urgently needed in order to decrease their socio-economical encumbrance. The recent focus of research has been redirected towards investigating the potential of haskap (Lonicera caerulea L.) as a novel functional food or superfruit. Therefore, our present review aims to highlight the latest scientific proofs regarding the potential of Lonicera caerulea L. (LC), a perennial fruit-bearing plant rich in polyphenols, in reversing cardio-metabolic dysfunctions. In this regard, a systematic search on two databases (PubMed and Google Scholar) from 1 January 2016 to 1 December 2023 was performed, the keyword combination being Lonicera caerulea L. AND the searched pharmacological action, with the inclusion criteria consisting of in extenso original articles, written in English. The health-enhancing characteristics of haskap berries have been examined through in vitro and in vivo studies from the 35 included original papers. Positive effects regarding cardiovascular diseases and metabolic syndrome have been assigned to the antioxidant activity, hypolipidemic and hypoglycemic effects, as well as to the hepatoprotective and vasoprotective potential. Latest advances regarding LCF mechanisms of action are detailed within this review as well. All these cutting-edge data suggest that this vegetal product would be a good candidate for further clinical studies.
Reliability, Availability, and Maintainability Assessment of a Mechatronic System Based on Timed Colored Petri Nets
Authors: Mehdi Imane , Boudi El Mostapha , Mehdi Mohammed Amine
Published: June 2024

The mechatronic industry is currently subject to huge changes challenging it to offer products matching individual customer requirements at competitive prices. The design of such products calls for sophisticated and complex components integration following different technologies. Since we are on the cusp of the Fourth Industrial Revolution, in which the world of mechatronic production, network connectivity, the Internet of Things, and cyber-physical systems are correlated, the complexity of these systems increases exponentially, and we are talking about advanced mechatronic systems. To assist these changes, various methods, sweeping all project phases, are used by business houses. Predictive dependability assessment in the earlier design stage is considered a powerful metric used to evaluate the performances of different kinds of mechatronic products before the production phase. Altogether, dependability analysis ties the design directly to the desired functionality, operability, and integrity of the system. This paper explores an approach to assessing the dependability attributes, reliability, availability, and maintainability (RAM), of repairable mechatronic systems based on timed colored Petri nets and a Monte Carlo simulation, integrating simultaneously diverse components technologies: mechanical, electronic, and software. The proposed approach is tested taking the case of a regenerative braking system. The methodology appears to be efficient for evaluating predictive RAM indicators (MTTFF, MTTR, MTBF…) for the whole system and for each individual component separately.
Construction of Three-Dimensional Semantic Maps of Unstructured Lawn Scenes Based on Deep Learning
Authors: Xie Xiaolin , Yan Zixiang , Zhang Zhihong , Qin Yibo , Jin Hang , Zhang Cheng , Xu Man
Published: June 2024

Traditional automatic gardening pruning robots generally employ electronic fences for the delineation of working boundaries. In order to quickly determine the working area of a robot, we combined an improved DeepLabv3+ semantic segmentation model with a simultaneous localization and mapping (SLAM) system to construct a three-dimensional (3D) semantic map. To reduce the computational cost of its future deployment in resource-constrained mobile robots, we replaced the backbone network of DeepLabv3+, ResNet50, with MobileNetV2 to decrease the number of network parameters and improve recognition speed. In addition, we introduced an efficient channel attention network attention mechanism to enhance the accuracy of the neural network, forming an improved Multiclass MobileNetV2 ECA DeepLabv3+ (MM-ED) network model. Through the integration of this model with the SLAM system, the entire framework was able to generate a 3D semantic point cloud map of a lawn working area and convert it into octree and occupancy grid maps, providing technical support for future autonomous robot operation and navigation. We created a lawn dataset containing 7500 images, using our own annotated images as ground truth. This dataset was employed for experimental purposes. Experimental results showed that the proposed MM-ED network model achieved 91.07% and 94.71% for MIoU and MPA metrics, respectively. Using a GTX 3060 Laptop GPU, the frames per second rate reached 27.69, demonstrating superior recognition performance compared to similar semantic segmentation architectures and better adaptation to SLAM systems.
Content-Adaptive Light Field Contrast Enhancement Using Focal Stack and Hierarchical Network
Authors: Guo Xiangyan , Guo Jinhao , Yuan Zhongyun , Cheng Yongqiang
Published: June 2024

Light field (LF) cameras can capture a scene’s information from all different directions and provide comprehensive image information. However, the resulting data processing commonly encounters problems of low contrast and low image quality. In this article, we put forward a content-adaptive light field contrast enhancement scheme using a focal stack (FS) and hierarchical structure. The proposed FS set contained 300 light field images, which were captured using a Lytro-Illum camera. In addition, we integrated the classical Stanford Lytro Light Field Archive and JPEG Pleno Database. Specifically, according to the global brightness, the acquired LF images were classified into four different categories. First, we transformed the original LF FS into a depth map (DMAP) and all-in-focus (AIF) image. The image category was preliminarily determined depending on the brightness information. Then, the adaptive parameters were acquired by the corresponding multilayer perceptron (MLP) network training, which intrinsically enhanced the contrast and adjusted the light field image. Finally, our method automatically produced an enhanced FS based on the DMAP and AIF image. The experimental comparison results demonstrate that the adaptive values predicted by our MLP had high precision and approached the ground truth. Moreover, compared to existing contrast enhancement methods, our method provides a global contrast enhancement, which improves, without over-enhancing, local areas. The complexity of image processing is reduced, and real-time, adaptive LF enhancement is realized.
On-Chip Reconstructive Spectrometer Based on Parallel Cascaded Micro-Ring Resonators
Authors: Zhang Zan , Huang Beiju , Zhang Zanyun , Chen Hongda
Published: June 2024

In contrast to cumbersome benchtop spectrometers, integrated on-chip spectrometers are well-suited for portable applications in health monitoring and environmental sensing. In this paper, we have developed an on-chip spectrometer with a programmable silicon photonic filter by simply using parallel cascaded micro-ring resonators (MRs). By altering the transmission spectrum of the filter, multiple and diverse sampling of the input spectrum is achieved. Then, combined with an artificial neural network (ANN) model, the incident spectrum is reconstructed from the sampled signals. Each MR is coupled to adjacent ones, and the phase shifts within each MR can be independently tuned. Through dynamic programming of the phases of these MRs, sampling functions featuring diverse characteristics are obtained based on a single programmable filter with an adjustable number of sampling channels. This eliminates the need for a filter array, significantly reducing the area of the on-chip reconstructive spectrometer. The simulation results demonstrate that the proposed design can achieve the reconstruction of continuous and sparse spectra within the wavelength range of 1450 nm to 1650 nm, with a tunable resolution ranging from 2 nm to 0.2 nm, depending on the number of sampling states employed. This benefit arises from the programmable nature of the device. The device holds tremendous potential for applications in wearable optical sensing, portable spectrometry, and other related scenarios.
A Strong Core for a Strong Recovery: A Scoping Review of Methods to Improve Trunk Control and Core Stability of People with Different Neurological Conditions
Authors: Marchesi Giorgia , Arena Greta , Parey Alice , De Luca Alice , Casadio Maura , Pierella Camilla , Squeri Valentina
Published: June 2024

Objective: The purpose of this scoping review is to provide valuable insights for clinicians and researchers for designing rehabilitative interventions targeting the trunk and core for individuals who have experienced traumatic events, such as stroke or spinal cord injury, or are grappling with neurological diseases such as multiple sclerosis and Parkinson’s disease. We investigated training methods used to enhance balance, trunk control, and core stability. Methods: We conducted an extensive literature search across several electronic databases, including Web of Science, PubMed, SCOPUS, Google Scholar, and IEEE Xplore. Results: A total of 109 articles met the inclusion criteria and were included in this review. The results shed light on the diversity of rehabilitation methods that target the trunk and core. These methods have demonstrated effectiveness in improving various outcomes, including balance, trunk control, gait, the management of trunk muscles, overall independence, and individuals’ quality of life. Conclusions: Our scoping review provides an overview on the methods and technologies employed in trunk rehabilitation and core strengthening, offering insights into the added value of core training and specific robotic training, focusing on the importance of different types of feedback to enhance training effectiveness.
Optimization of the One-Size-Fits-All Layout Problem Based on Preparing Material for Steel Bridges
Authors: Dong Zhikui , Liu Chunjiang , Sun Yongkuan , Li Xuedong , Zhang Kai , Jiang Yunhong
Published: June 2024

Before the construction of a bridge begins, workers arrange the necessary parts and then cut and process them. The quality of the cutting layout directly affects the material utilization rate and the efficiency of the subsequent processes. During bridge construction, an intelligent part layout can improve work efficiency, save time, and reduce the labor intensity and production costs for the company. In this study, we studied a layout optimization algorithm, focusing on rectangular parts in the material preparation process. A mathematical model for the rectangular layout problem was constructed, and a hybrid genetic whale optimization algorithm is proposed that is a combination of the whale optimization algorithm and the genetic algorithm. Based on the “one size fits all” layout strategy, the materials are divided into strips, which are further divided into stacks, serving as the positioning strategy to determine the positional relationships of the parts. Test cases and actual engineering data were used to compare the layouts generated using different algorithms. The results show that the genetic whale algorithm proposed in this paper results in a high utilization rate and is highly effective.
Improved Least Squares Phase Unwrapping Method Based on Chebyshev Filter
Authors: Li Guoqing , Li Yake , Liu Wenyan
Published: June 2024

Phase unwrapping of high phase noise and steep phase gradient has always been a challenging problem in interferometric synthetic aperture radar (InSAR), in which case the least squares (LS) phase unwrapping method often suffers from significant unwrapping errors. Therefore, this paper proposes an improved LS phase unwrapping method based on the Chebyshev filter, which solves the problem of incomplete unwrapping and errors under high phase noise and steep phase gradient. Firstly, the steep gradient phase is transformed into multiple flat gradient phases using the Chebyshev filter. Then the flat gradient phases are unwrapped using the LS unwrapping method. Finally, the final unwrapped phase is obtained by iteratively adding the unwrapping results of the flat gradient phases. The simulation results show that the proposed method has the best accuracy and stability compared to LS, PCUA, and RPUA. In the real InSAR phase unwrapping experiment, the RMSE of the proposed method is reduced by 63.91%, 35.38%, and 54.39% compared to LS, PCUA, and RPUA. The phase unwrapping time is reduced by 62.86% and 11.64% compared to PCUA and RPUA.
Enhancing Social Skills in Autism Students with Augmented-Reality Picturebooks
Authors: Sun Shu-Jou , Huang An-Chin , Ho Wei-Sho
Published: June 2024

The objective of this study was to examine the effect of augmented-reality picturebooks on enhancing the social skills of students with autism spectrum disorder (ASD). Employing a multiple-probes design across subjects based on the single-subject research design, three students with ASD were engaged, receiving two forty-minute lessons per week, culminating in twelve lessons. This research encompassed a baseline period, an intervention period, and a maintenance period, with analyses conducted using visual analysis and C statistic. The research results found that augmented-reality picturebook courses had immediate and sustained effects on enhancing the “friendship skills” and “conflict management” of students with ASD. Based on the results, the researchers put forward practical suggestions.
Study on the Effect of Anchor Cable Prestress Loss on Foundation Stability
Authors: Xing Tongju , Liu Hongjun , Zheng Jianguo , Yu Xiaoxi , Li Yanbin , Peng Huadong
Published: June 2024

Anchor cable prestressing is one of the key factors in maintaining the stability of the supporting structure and controlling ground deformation. In order to further understand the influence of anchor cable prestress loss on the stability of the foundation pit, an underground station pit of Qingdao Metro Line 6 is taken as the engineering background, and numerical simulation research is carried out by using FLAC3D, which calculates the surface settlement, the deformation of enclosing piles, the support axial force, and the axial force of anchor cables in the process of excavation of the foundation pit and compares it with the on-site monitoring data, to get the law of the impact of prestressing force on the stability of the foundation pit in order to provide a reference for the design of the soil–rock Combined pit support system design and engineering construction to provide reference.
Synthetic Data-Driven Real-Time Detection Transformer Object Detection in Raining Weather Conditions
Authors: Hao Chen-Yu , Chen Yao-Chung , Chen Tai-Tien , Lai Ting-Hsuan , Chou Tien-Yin , Ning Fang-Shii , Chen Mei-Hsin
Published: June 2024

Images captured in rainy weather conditions often suffer from contamination, resulting in blurred or obscured objects, which can significantly impact detection performance due to the loss of identifiable texture and color information. Moreover, the quality of the detection model plays a pivotal role in determining detection outcomes. This study adopts a dual perspective, considering both pre-trained models and training data. It employs 15 image augmentation techniques, combined with neural style transfer (NST), CycleGAN, and an analytical method, to synthesize images under rainy conditions. The Real-Time Detection Transformer (RTDETR) and YOLOv8 pre-trained models are utilized to establish object detection frameworks tailored for rainy weather conditions. Testing is carried out using the DAWN (Detection in Adverse Weather Nature) dataset. The findings suggest compatibility between the pre-trained detection models and various data synthesis methods. Notably, YOLOv8 exhibits better compatibility with CycleGAN data synthesis, while RTDETR demonstrates a stronger alignment with the NST and analytical approaches. Upon the integration of synthesized rainy images into model training, RTDETR demonstrates significantly enhanced detection accuracy compared to YOLOv8, indicating a more pronounced improvement in performance. The proposed approach of combining RTDETR with NST in this study shows a significant improvement in Recall (R) and mAP50-95 by 16.35% and 15.50%, respectively, demonstrating the robust rainy weather resilience of this method. Additionally, RTDETR outperforms YOLOv8 in terms of inference speed and hardware requirements, making it easier to use and deploy in real-time applications.
Optimization and Analysis of Clutch Switching Timing for Hybrid Tractors Equipped with Hydraulic Mechanical Combined Transmission
Authors: Zhu Zhen , Sheng Jie , Zhang Hongwei , Wang Dehai , Chen Long
Published: June 2024

The working environment of tractors is harsh and the working conditions are very complicated. To cope with this complex and changeable working environment, this paper presents a hybrid tractor powertrain loaded with hydraulic mechanical combined transmission (HMCVT). The powertrain can switch modes according to different operating environments. During mode switching, impact loads can cause wear and even damage to the transmission components. Interrupting the power transmission will reduce the tractor’s operational efficiency. In this paper, the orthogonal experimental range analysis method was proposed to optimize the quality of mode switching. Mode switching involves interactions between clutches. Orthogonal table L16 (215) was selected to design the orthogonal table head. SimulationX was used for simulation. Employing MINITAB range analysis yielded the optimal results. The simulations indicated a reduction in the output shaft’s velocity drop amplitude from 17.647% to 6.591%. The dynamic load coefficient decreased from 2.743 to 1.857. The impact strength was reduced from 14.125 to 5.67 m/s3. The switching time was reduced from 2.13 to 1.71 s. We built a model-in-the-loop (MIL) test platform to validate the results. The MIL test results were compared with the simulation results. Our findings indicate a degree of discrepancy between the simulated and the experimental results, yet the overall trends remain largely consistent. The correctness of the optimal scheme obtained from the orthogonal experiment is verified. This study provides a theoretical basis for the optimization of powertrain mode switching in hybrid tractors equipped with HMCVT.
Influence of Incident Shock on Fuel Mixing in Scramjet
Authors: Wang Chao , Wang Hongbo , Yang Yixin , Liu Xu
Published: June 2024

During the operation of hypersonic vehicles, a reciprocal coupling effect is manifested between the inlet and the combustion chamber. This results in an unavoidable non-uniformity of conditions at the combustion chamber’s entrance, which, in turn, influences the fuel mixing within the chamber. The present study employed the Reynolds-averaged Navier–Stokes (RANS) equations to perform a numerical simulation of an X-51-like vehicle, with a focus on examining the impact of isolation section length and multi-injection strategies on the fuel mixing characteristics within the combustion chamber under conditions of non-uniform inflow. The findings indicated that a supersonic non-uniform inlet triggers incident shock waves, leading to a non-uniform pressure distribution across the flow section. Moreover, the position of injection was found to be pivotal in regulating penetration depth and mixing efficiency. The incident shock wave, bow shock, and boundary layer separation shock interacted with each other to increase local pressure. The coupling of high and low pressures generated an adverse pressure gradient that led to boundary layer separation, which further enhanced fuel penetration depth.
The Logistics of Volkswagen Development Center Applies Operations Research to Optimize Transshipments
Authors: Vorwerk Bastian , Trojahn Sebastian
Published: June 2024

Volkswagen Technical Development (TE) is responsible for all prototype development and prototype production for the Volkswagen brand and has its own logistics department (TE-Logistics). In the logistics of prototype parts in the automotive industry, new versions of prototype parts (henceforth referred to as updating parts) are repeatedly assembled in finished prototype vehicles. These updating parts are stored in warehouses and provided to an assembly site to ensure a timely assembly of the associated prototype vehicles. As the internal warehouse on the company site is not large enough for the high variety of parts, an additional external warehouse in the logistics network is needed. However, since prototype parts are unique, the allocation of the parts in suitable warehouses is particularly important. Currently, the various warehouses and the short-term demands repeatedly lead to reactive transshipments between the warehouses. To this end, we developed an approach for proactive transshipments based on a machine learning forecast and a mixed-integer linear programming model for planning proactive transshipments of parts between the warehouses to minimize transport costs. The model is based on a probability estimation of future demands to anticipate the expected optimal warehouse. After the model had revealed high improvement potential through a case study with real-world data in terms of costs and availability time compared to the current reactive process, we derived decision rules and developed a rule-based heuristic algorithm that leads to the optimal solution for the industrial use case. We implemented the heuristic with a spreadsheet-based decision support system (DSS) for daily transshipment planning. After successful test implementation, TE-Logistics estimated the annual cost savings for transport to be approximately 10%.
The New G-Double-Laplace Transforms and One-Dimensional Coupled Sine-Gordon Equations
Authors: Eltayeb Hassan , Mesloub Said
Published: June 2024

This paper establishes a novel technique, which is called the G-double-Laplace transform. This technique is an extension of the generalized Laplace transform. We study its properties with examples and various theorems related to the G-double-Laplace transform that have been addressed and proven. Finally, we apply the G-double-Laplace transform decomposition method to solve the nonlinear sine-Gordon and coupled sine-Gordon equations. This method is a combination of the G-double-Laplace transform and decomposition method. In addition, some examples are examined to establish the accuracy and effectiveness of this technique.
LLMs and NLP Models in Cryptocurrency Sentiment Analysis: A Comparative Classification Study
Authors: Roumeliotis Konstantinos I. , Tselikas Nikolaos D. , Nasiopoulos Dimitrios K.
Published: June 2024

Cryptocurrencies are becoming increasingly prominent in financial investments, with more investors diversifying their portfolios and individuals drawn to their ease of use and decentralized financial opportunities. However, this accessibility also brings significant risks and rewards, often influenced by news and the sentiments of crypto investors, known as crypto signals. This paper explores the capabilities of large language models (LLMs) and natural language processing (NLP) models in analyzing sentiment from cryptocurrency-related news articles. We fine-tune state-of-the-art models such as GPT-4, BERT, and FinBERT for this specific task, evaluating their performance and comparing their effectiveness in sentiment classification. By leveraging these advanced techniques, we aim to enhance the understanding of sentiment dynamics in the cryptocurrency market, providing insights that can inform investment decisions and risk management strategies. The outcomes of this comparative study contribute to the broader discourse on applying advanced NLP models to cryptocurrency sentiment analysis, with implications for both academic research and practical applications in financial markets.
Integrating OLAP with NoSQL Databases in Big Data Environments: Systematic Mapping
Authors: Martinez-Mosquera Diana , Navarrete Rosa , Luján-Mora Sergio , Recalde Lorena , Andrade-Cabrera Andres
Published: June 2024

The growing importance of data analytics is leading to a shift in data management strategy at many companies, moving away from simple data storage towards adopting Online Analytical Processing (OLAP) query analysis. Concurrently, NoSQL databases are gaining ground as the preferred choice for storing and querying analytical data. This article presents a comprehensive, systematic mapping, aiming to consolidate research efforts related to the integration of OLAP with NoSQL databases in Big Data environments. After identifying 1646 initial research studies from scientific digital repositories, a thorough examination of their content resulted in the acceptance of 22 studies. Utilizing the snowballing technique, an additional three studies were selected, culminating in a final corpus of twenty-five relevant articles. This review addresses the growing importance of leveraging NoSQL databases for OLAP query analysis in response to increasing data analytics demands. By identifying the most commonly used NoSQL databases with OLAP, such as column-oriented and document-oriented, prevalent OLAP modeling methods, such as Relational Online Analytical Processing (ROLAP) and Multidimensional Online Analytical Processing (MOLAP), and suggested models for batch and real-time processing, among other results, this research provides a roadmap for organizations navigating the integration of OLAP with NoSQL. Additionally, exploring computational resource requirements and performance benchmarks facilitates informed decision making and promotes advancements in Big Data analytics. The main findings of this review provide valuable insights and updated information regarding the integration of OLAP cubes with NoSQL databases to benefit future research, industry practitioners, and academia alike. This consolidation of research efforts not only promotes innovative solutions but also promises reduced operational costs compared to traditional database systems.
The Role of Cyanoacrylate after Mandibular Third Molar Surgery: A Single Center Study
Authors: Parrini Stefano , Arzente Giulia , Bartali Elena , Chisci Glauco
Published: June 2024

Background: The management of the surgical wound of partially impacted mandibular third molar surgery has a great impact on recovery as well as on food impact retention. The present study used clinical parameters and health-related quality of life (HRQL) to compare outcomes of cyanoacrylate application versus traditional suture of third molar impaction surgery. Methods: This was a retrospective observational study of subjects scheduled for outpatient third molar surgery. Each participant signed an informed consent agreement. Inclusion criteria were as follows: presence of at least one partially impacted mandibular third molar, confirmed with a preoperative panoramic radiograph. Exclusion criteria were the following: smoking, diagnosed diabetes mellitus. Between June 2020 and September 2023, a total of 78 patients of mean age 31.14 years old (range 21–40 years, standard deviation 9.14), were included in this study—38 patients were male, 40 patients were female. A group of patients received traditional silk suture (G1 = 41 patients), while the second group (G2 = 37 patients) received hemostasis performed with fibrin sponge and, after complete soaking of the sponge, the application of cyanoacrylate gel on the blood clot and suture with one 2/0 stitch in order for recovery for secondary closure. The following parameters were measured: HRQL, average pain (AP), maximum pain (MP), complication score (CS), facial swelling (FS), and erythema. Results: For HRQL parameters, oral disability was found to be significantly higher in G1 while AP was significantly higher in G2 (p < 0.05). AP was higher in G2 (p = 0.0098), as well as MP (p = 0.001). No differences were found with regards to CS (p = 0.0759). FS and erythema were higher in G1 (p < 0.0001 for facial swelling, and p = 0.0001 for erythema). Conclusions: on the basis of this study, the use of cyanoacrylate after mandibular third molar surgery appears to be useful in order to reduce postoperative oral disability, facial swelling, and erythema after tooth extraction, with increased average and medium pain: clinicians may consider its use in selected cases.
Silk Gland Factor 1 Plays a Pivotal Role in Larval Settlement of the Fouling Mussel Mytilopsis sallei
Authors: He Jian , Wang Zhixuan , Wu Zhiwen , Chen Liying , Huang Jianfang
Published: June 2024

Most fouling organisms have planktonic larval and benthic adult stages. Larval settlement, the planktonic–benthic transition, is the critical point when biofouling begins. However, our understanding of the molecular mechanisms of larval settlement is limited. In our previous studies, we identified that the AMP-activated protein kinase-silk gland factor 1 (AMPK-SGF1) pathway was involved in triggering the larval settlement in the fouling mussel M. sallei. In this study, to further confirm the pivotal role of SGF1, multiple targeted binding compounds of SGF1 were obtained using high-throughput virtual screening. It was found that the targeted binding compounds, such as NAD+ and atorvastatin, could significantly induce and inhibit the larval settlement, respectively. Furthermore, the qRT-PCR showed that the expression of the foot proteins’ genes was significantly increased after the exposure to 10 μM NAD+, while the gene expression was significantly suppressed after the exposure to 10 μM atorvastatin. Additionally, the production of the byssus threads of the adults was significantly increased after the exposure to 10–20 μM of NAD+, while the production of the byssus threads was significantly decreased after the exposure to 10–50 μM of atorvastatin. This work will deepen our understanding of SGF1 in triggering the larval settlement in mussels and will provide insights into the potential targets for developing novel antifouling agents.
Implications of the COVID-19 Pandemic on the Management of Municipal Solid Waste and Medical Waste: A Comparative Review of Selected Countries
Authors: Daoud Ahmed Osama , Elattar Hoda , Abdelatif Gaber , Morsy Karim M. , Peters Robert W. , Mostafa Mohamed K.
Published: June 2024

The COVID-19 outbreak has impacted many daily activities and services we depend on. Due to changes in waste quantity and types, solid waste management (SWM) services such as waste collection, transportation, and treatment/disposal suffered. Global rules and mandates were issued to address these changes and the COVID-19 pandemic. This mini review examines seven countries and summarises the pandemic’s effects on municipal solid waste (MSW) and medical waste (MW) generation in terms of amount and composition, the SWM sector’s challenges, and government or other SWM guidelines and management measures. The data are analysed to provide suggestions for stakeholders on SWM worker protection, waste segregation, and recycling. This article identified that extending MW incineration, separating infectious waste at the source, and discontinuing recycling for infection control are the best ways to manage solid waste. The waste management system’s readiness was crucial to the pandemic response. Thus, countries like China, which has a robust SWM system, were able to contain the crisis and restrict danger, while others with weaker systems struggled. Additionally, the study highlights the importance of revising waste management policies and developing crisis response strategies that integrate flexible, innovative solutions to adapt quickly to changing waste demands and ensure public health and environmental protection during global health crises.
Investigating Kinematics and Electromyography Changes in Manual Handling Tasks with an Active Lumbar Exoskeleton
Authors: Moulart Mélissa , Acien Maxime , Leonard Audrey , Loir Mathilde , Olivier Nicolas , Marin Frédéric
Published: June 2024

Companies are becoming increasingly aware of the health of their employees and are now integrating exoskeleton solutions for both prevention and job maintenance. However, the effect of using exoskeletons is still an open question. Therefore, this study aimed to evaluate the impact of an active lumbar exoskeleton and its passive belt on trunk kinematics and muscle activity using instrumented motion analysis. Twenty-three healthy subjects volunteered to perform three handlings of a 5 kg load (free lifting, squat lifting, and load transfer) under three different experimental conditions. The “Control” condition was when the subject did not wear any device, the “Belt” condition was when the subject wore only the passive part of the exoskeleton, and the “Exo” condition was when the subject wore the active exoskeleton. Based on the Rapid Upper Limb Assessment scale, the exoskeleton reduced the time spent in angles that were considered dangerous for the back, according to ergonomic evaluations. Furthermore, for the handling sessions, it was observed that the exoskeleton did not modify muscle activity in the abdominal–lumbar region.
Calpain Small Subunit Mediated Secretion of Galectin-3 Regulates Traction Stress
Authors: Jang Imjoo , Menon Shalini , Indra Indrajyoti , Basith Rabiah , Beningo Karen A.
Published: June 2024

The complex regulation of traction forces (TF) produced during cellular migration remains poorly understood. We have previously found that calpain 4 (Capn4), the small non-catalytic subunit of the calpain 1 and 2 proteases, regulates the production of TF independent of the proteolytic activity of the larger subunits. Capn4 was later found to facilitate tyrosine phosphorylation and secretion of the lectin-binding protein galectin-3 (Gal3). In this study, recombinant Gal3 (rGal3) was added to the media-enhanced TF generated by capn4−/− mouse embryonic fibroblasts (MEFs). Extracellular Gal3 also rescued defects in the distribution, morphology, and adhesive strength of focal adhesions present in capn4−/− MEF cells. Surprisingly, extracellular Gal3 does not influence mechanosensing. c-Abl kinase was found to affect Gal3 secretion and the production of TF through phosphorylation of Y107 on Gal3. Our study also suggests that Gal3-mediated regulation of TF occurs through signaling pathways triggered by β1 integrin but not by focal adhesion kinase (FAK) Y397 autophosphorylation. Our findings provide insights into the signaling mechanism by which Capn4 and secreted Gal3 regulate cell migration through the modulation of TF distinctly independent from a mechanosensing mechanism.
Recent Advances in the Discovery of Novel Drugs on Natural Molecules
Authors: Quintieri Laura , Caputo Leonardo , Nicolotti Orazio
Published: June 2024

Natural products (NPs) are always a promising source of novel drugs for tackling unsolved diseases [...]