bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review of Multi-Satellite Imaging Mission Planning Based on Surrogate Model Expensive Multi-Objective Evolutionary Algorithms: The Latest Developments and Future Trends
Authors: Yang Xueying , Hu Min , Huang Gang , Lin Peng , Wang Yijun
Published: September 2024

Multi-satellite imaging mission planning (MSIMP) is an important focus in the field of satellite application. MSIMP involves a variety of coupled constraints and optimization objectives, which often require extensive simulation and evaluation when solving, leading to high computational costs and slow response times for traditional algorithms. Surrogate model expensive multi-objective evolutionary algorithms (SM-EMOEAs), which are computationally efficient and converge quickly, are effective methods for the solution of MSIMP. However, the recent advances in this field have not been comprehensively summarized; therefore, this work provides a comprehensive overview of this subject. Firstly, the basic classification of MSIMP and its different fields of application are introduced, and the constraints of MSIMP are comprehensively analyzed. Secondly, the MSIMP problem is described to clarify the application scenarios of traditional optimization algorithms in MSIMP and their properties. Thirdly, the process of MSIMP and the classical expensive multi-objective evolutionary algorithms are reviewed to explore the surrogate model and the expensive multi-objective evolutionary algorithms based on MSIMP. Fourthly, improved SM-EMOEAs for MSIMP are analyzed in depth in terms of improved surrogate models, adaptive strategies, and diversity maintenance and quality assessment of the solutions. Finally, SM-EMOEAs and SM-EMOEA-based MSIMP are analyzed in terms of the existing literature, and future trends and directions are summarized.
EELS-DARTS: A Planetary Snake Robot Simulator for Closed-Loop Autonomy Development
Authors: Hasseler Tristan D. , Leake Carl , Gaut Aaron , Elmquist Asher , Swan Robert Michael , Royce Rob , Jones Bryson , Hockman Ben , Paton Michael , Daddi Guglielmo , Ono Masahiro , Thakker Rohan , Jain Abhinandan
Published: September 2024

EELS-DARTS is a simulator designed for autonomy development and analysis of large degree of freedom snake-like robots for space exploration. A detailed description of the EELS-DARTS simulator design is presented. This includes the versatile underlying multibody dynamics representation used to model a variety of distinct snake robot configurations as well as an anisotropic friction model for describing screw–ice interaction. Additional simulation components such as graphics, importable terrain, joint controllers, and perception are discussed. Methods for setting up and running simulations are discussed, including how a snake robot’s autonomy stack closes the commands and information loop with the simulation via ROS. Multiple use cases are described to illustrate how the simulation is used to aid and inform robot design, autonomy development, and field test use throughout the project’s life cycle. A validation analysis of the screw–ice contact model is performed for the surface mobility case. Lastly, an overview of simulation use for planning operations during a recent field test to the Athabasca Glacier in Canada is discussed.
Software Defect Prediction Based on Machine Learning and Deep Learning Techniques: An Empirical Approach
Authors: Albattah Waleed , Alzahrani Musaad
Published: September 2024

Software bug prediction is a software maintenance technique used to predict the occurrences of bugs in the early stages of the software development process. Early prediction of bugs can reduce the overall cost of software and increase its reliability. Machine learning approaches have recently offered several prediction methods to improve software quality. This paper empirically investigates eight well-known machine learning and deep learning algorithms for software bug prediction. We compare the created models using different evaluation metrics and a well-accepted dataset to make the study results more reliable. This study uses a large dataset collected from five publicly available bug datasets that includes about 60 software metrics. The source-code metrics of internal class quality, including cohesion, coupling, complexity, documentation inheritance, and size metrics, were used as features to predict buggy and non-buggy classes. Four performance metrics, namely accuracy, macro F1 score, weighted F1 score, and binary F1 score, are considered to quantitatively evaluate and compare the performance of the constructed bug prediction models. The results demonstrate that the deep learning model (LSTM) outperforms all other models across these metrics, achieving an accuracy of 0.87.
Musculoskeletal Disorder Risk Assessment during the Tennis Serve: Performance and Prevention
Authors: Gorce Philippe , Jacquier-Bret Julien
Published: September 2024

Addressing the risk of musculoskeletal disorders (MSDs) during a tennis serve is a challenge for both protecting athletes and maintaining performance. The aim of this study was to investigate the risk of MSD occurrence using the rapid whole-body assessment (REBA) ergonomic tool at each time step, using 3D kinematic analysis of joint angles for slow and fast serves. Two force platforms (750 Hz) and an optoelectronic system including 10 infrared cameras (150 Hz, 82 markers located on the whole body and on the racket) were used to capture the kinematics of the six REBA joint areas over five services in two young male and two young female ranked players. The mean REBA score was 9.66 ± 1.11 (ranging from 7.75 to 11.85) with the maximum value observed for the loading and cocking stage (REBA score > 11). The intermediate scores for each of the six joint areas ranged between 2 and 3 and the maximum value of their respective scales. The lowest scores were observed for the shoulder. Neck rotation and shoulder flexion are parameters that could be taken into account when analyzing performance in the context of MSD prevention.
Multifaceted Properties of Usnic Acid in Disrupting Cancer Hallmarks
Authors: Gimła Mariola , Herman-Antosiewicz Anna
Published: September 2024

Cancer, a complex group of diseases marked by uncontrolled cell growth and invasive behavior, is characterized by distinct hallmarks acquired during tumor development. These hallmarks, first proposed by Douglas Hanahan and Robert Weinberg in 2000, provide a framework for understanding cancer’s complexity. Targeting them is a key strategy in cancer therapy. It includes inhibiting abnormal signaling, reactivating growth suppressors, preventing invasion and metastasis, inhibiting angiogenesis, limiting replicative immortality, modulating the immune system, inducing apoptosis, addressing genome instability and regulating cellular energetics. Usnic acid (UA) is a natural compound found in lichens that has been explored as a cytotoxic agent against cancer cells of different origins. Although the exact mechanisms remain incompletely understood, UA presents a promising compound for therapeutic intervention. Understanding its impact on cancer hallmarks provides valuable insights into the potential of UA in developing targeted and multifaceted cancer therapies. This article explores UA activity in the context of disrupting hallmarks in cancer cells of different origins based on recent articles that emphasize the molecular mechanisms of this activity.
Management of Giant Thyroid Tumors in Patients with Multiple Comorbidities in a Tertiary Head and Neck Surgery Center
Authors: Vrinceanu Daniela , Dumitru Mihai , Marinescu Andreea , Serboiu Crenguta , Musat Gabriela , Radulescu Mihai , Popa-Cherecheanu Matei , Ciornei Catalina , Manole Felicia
Published: September 2024

Background/Objectives: The thyroid gland can represent the seat of development for giant tumors exceeding 10 cm in diameter. A retrospective analysis on 21 cases of giant thyroid tumors with comorbidities, operated in the ENT Department of the Bucharest University Emergency Hospital has been conducted. Methods: Giant benign tumors accounted for 28.57% of the cases studied and reached gigantic volumes in an average time interval of 3 years, with an average resection piece weight of 318 g. Malignant tumors accounted for 71.43%, with an average duration of evolution of 7 years, with an average resection piece weight of 581 g. Results: Dysphagia was present in all patients, dyspnea in 47.61% and dysphonia in 38.09% of cases. Total thyroidectomy is the gold standard in giant thyroid tumors, associated with radical neck dissection, extended to groups VI and VII in malignant tumors. In 10 of 11 cases of giant malignant thyroid tumors (90.90%), without anaplastic thyroid carcinoma, the survival at 5 years after multimodal oncologic treatment was favorable. Anticoagulant treatment increased the risk of postoperative reversible recurrent laryngeal nerve lesion. Conclusions: The management of giant thyroid tumors in patients with multiple comorbidities needs a multidisciplinary team including endocrinologist, radiologist, anesthesiologist, pathologist, ENT surgeon, thoracic surgeon, oncologist and radiotherapist.
Interplay of RNA m6A Modification-Related Geneset in Pan-Cancer
Authors: Zhang Boyu , Hao Yajuan , Liu Haiyan , Wu Jiarun , Lu Lu , Wang Xinfeng , Bajpai Akhilesh K. , Yang Xi
Published: September 2024

Background: N6-methyladenosine (m6A), is the most common modification found in mRNA and lncRNA in higher organisms and plays an important role in physiology and pathology. However, its role in pan-cancer has not been explored. Results: A total of 31 m6A modification regulators, including 12 writers, 2 erasers, and 17 readers are identified in the current study. The functional analysis of the regulators results in the enrichment of processes, primarily related to RNA modification and metabolism, and the PPI network reveals multiple interactions among the regulators. The mRNA expression analysis reveals a high expression for most of the regulators in pan-cancer. Most of the m6A regulators are found to be mutated across the cancers, with ZC3H13, VIRMA, and PRRC2A having a higher frequency rate. Significant correlations of the regulators with clinicopathological parameters, such as age, gender, tumor stage, and grade are identified in pan-cancer. The m6A regulators’ expression is found to have significant positive correlations with the miRNAs in pan-cancer. The expression pattern of the m6A regulators is able to classify the tumors into different subclusters as well as into high- and low-risk groups. These tumor groups show differential patterns in terms of their immune cell infiltration, tumor stemness score, genomic heterogeneity score, expression of immune regulatory/checkpoint genes, and correlations between the regulators and the drugs. Conclusions: Our study provide a comprehensive overview of the functional roles, genetic and epigenetic alterations, and prognostic value of the RNA m6A regulators in pan-cancer.
Furnace Testing and Validation of a Hybrid Cooling Approach for Enhanced Turbine Blade Protection with a Thermal Barrier Coating in Advanced Gas Turbines
Authors: Mohd Yunus Salmi , Manap Abreeza , Satgunam Meenaloshini , Mahalingam Savisha , Mohd Afandi Nurfanizan
Published: September 2024

Hybrid turbine blade protection systems, which combine thermal barrier coatings (TBCs) and cooling mechanisms, are essential for safeguarding turbine blades in advanced gas turbine applications. However, conventional furnace evaluation methods are inadequate for accurately simulating the complex thermal conditions experienced by TBCs in these environments. Initial testing revealed substantial degradation of TBCs when subjected to high temperatures without the necessary cooling support. To address this limitation, the furnace setup was modified to incorporate a cooling air system. This system channeled 400 °C air to the back surface of the TBC while subjecting the front to 1400 °C furnace air, effectively replicating the thermal gradient encountered in hybrid protection systems. The modified furnace setup demonstrated a remarkable improvement in the performance of yttria-stabilized zirconia TBCs. By cooling the back surface of the TBC, the metal substrate temperature decreased, thereby improving the thermal gradient on the coating and its durability. The thermal gradient achieved by the modified furnace was verified to simulate accurately the conditions experienced by TBCs in advanced gas turbines. The conventional furnace setup, lacking a cooling mechanism, overestimated the heat transfer on the TBCs, leading to inaccurate results. The modified furnace, with its integrated cooling system, more accurately simulated the conditions experienced by TBCs in real-world advanced gas turbine applications and more reliably assessed their performance.
Laser-Assisted Lipolysis Versus Surgical Fat Removal: A Review of Efficacy, Safety, and Patient Satisfaction
Authors: Lee Kar Wai Alvin , Chan Lisa Kwin Wah , Lee Angela Wai Kay , Lee Cheuk Hung , Wan Jovian , Yi Kyu-Ho
Published: September 2024

(1) Background: The demand for body-contouring procedures has surged, with lipolysis emerging as a common technique for excess fat removal. Laser-assisted lipolysis (LAL) has gained attention as a potential alternative to surgical fat removal (SFR), offering perceived advantages in safety and efficacy. However, the comparative benefits of LAL and SFR remain uncertain. (2) Objective: To conduct a review of the existing literature comparing the efficacy, safety, and patient satisfaction of LAL and SFR. (3) Methods: A comprehensive search of major electronic databases was conducted to identify studies comparing LAL and SFR for body-contouring procedures. Studies were included if they were published in English, involved human subjects, and reported outcomes for LAL and SFR. All studies were classified according to the Oxford Center for Evidence-Based Medicine evidence hierarchy (4) Results: LAL may not be a safer and more effective option than SFR. However, the evidence for these differences was limited by the quality of the studies and the heterogeneity of the results. (5) Conclusions: This review suggests that LAL may not be a safer and more effective option than SFR for body-contouring procedures because LAL is associated with higher risks of complications such as burns and scarring, whereas SFR offers a more established safety profile and consistent efficacy.
The Impact of Gastrectomy on Inflammatory Bowel Disease Risk in Gastric Cancer Patients: A Critical Analysis
Authors: Christodoulidis Grigorios , Koumarelas Konstantinos-Eleftherios , Tsagkidou Kyriaki , Agko Eirini-Sara , Bartzi Dimitra , Koumarelas Konstantinos , Zacharoulis Dimitrios
Published: September 2024

Gastrectomy, a prevalent surgical procedure for gastric cancer, results in substantial alterations to the gastrointestinal tract, including reduced gastric acid production and significant modifications to the gut microbiota. These changes can impair postoperative recovery, influence metabolic functions, and predispose patients to inflammatory bowel disease (IBD). Studies have shown an increased risk of IBD, particularly Crohn’s disease (CD) and ulcerative colitis (UC), in patients following gastrectomy and bariatric surgeries such as Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG). For instance, patients undergoing RYGB have a higher hazard ratio for developing CD, while SG patients show an increased risk for UC. The surgical alteration of the gastrointestinal tract promotes dysbiosis, with a significant increase in pathogenic bacteria and a decrease in beneficial microbial populations. This dysbiosis can impair the intestinal mucosal barrier and promote systemic inflammation. Understanding the mechanisms behind these changes and their clinical implications is essential for developing effective postoperative management strategies. Probiotics and enhanced recovery after surgery (ERAS) protocols have shown promise in mitigating these adverse effects, improving gut microbiota balance, and enhancing patient outcomes. Further research is necessary to fully elucidate the long-term impacts of gastrectomy on gastrointestinal health and to refine therapeutic approaches for postoperative care.
Differentiator- and Observer-Based Feedback Linearized Advanced Nonlinear Control Strategies for an Unmanned Aerial Vehicle System
Authors: Irfan Saqib , Zhao Liangyu , Ullah Safeer , Javaid Usman , Iqbal Jamshed
Published: September 2024

This paper presents novel chattering-free robust control strategies for addressing disturbances and uncertainties in a two-degree-of-freedom (2-DOF) unmanned aerial vehicle (UAV) dynamic model, with a focus on the highly nonlinear and strongly coupled nature of the system. The novelty lies in the development of sliding mode control (SMC), integral sliding mode control (ISMC), and terminal sliding mode control (TSMC) laws specifically tailored for the twin-rotor MIMO system (TRMS). These strategies are validated through both simulation and real-time experiments. A key contribution is the introduction of a uniform robust exact differentiator (URED) to recover rotor speed and missing derivatives, combined with a nonlinear state feedback observer to improve system observability. A feedback linearization approach, using lie derivatives and diffeomorphism principles, is employed to decouple the system into horizontal and vertical subsystems. Comparative analysis of the transient performance of the proposed controllers, with respect to metrics such as settling time, overshoot, rise time, and steady-state errors, is provided. The ISMC method, in particular, effectively mitigates the chattering issue prevalent in traditional SMC, improving both system performance and actuator longevity. Experimental results on the TRMS demonstrate the superior tracking performance and robustness of the proposed control laws in the presence of nonlinearities, uncertainties, and external disturbances. This research contributes a comprehensive control design framework with proven real-time implementation, offering significant advancements over existing methodologies.
Enhanced Link Prediction and Traffic Load Balancing in Unmanned Aerial Vehicle-Based Cloud-Edge-Local Networks
Authors: Long Hao , Hu Feng , Kong Lingjun
Published: September 2024

With the advancement of cloud-edge-local computing, Unmanned Aerial Vehicles (UAVs), as flexible mobile nodes, offer novel solutions for dynamic network deployment. However, existing research on UAV networks faces substantial challenges in accurately predicting link dynamics and efficiently managing traffic loads, particularly in highly distributed and rapidly changing environments. These limitations result in inefficient resource allocation and suboptimal network performance. To address these challenges, this paper proposes a UAV-based cloud-edge-local network resource elastic scheduling architecture, which integrates the Graph-Autoencoder–GAN-LSTM (GA–GLU) algorithm for accurate link prediction and the FlowBender-Enhanced Reinforcement Learning for Load Balancing (FERL-LB) algorithm for dynamic traffic load balancing. GA–GLU accurately predicts dynamic changes in UAV network topologies, enabling adaptive and efficient scheduling of network resources. FERL-LB leverages these predictions to optimize traffic load balancing within the architecture, enhancing both performance and resource utilization. To validate the effectiveness of GA–GLU, comparisons are made with classical methods such as CN and Katz, as well as modern approaches like Node2vec and GAE–LSTM, which are commonly used for link prediction. Experimental results demonstrate that GA–GLU consistently outperforms these competitors in metrics such as AUC, MAP, and error rate. The integration of GA–GLU and FERL-LB within the proposed architecture significantly improves network performance in highly dynamic environments.
Hyperspectral Sensor Management for UAS: Performance Analysis of Context-Based System Architectures for Camouflage and UXO Anomaly Detection Workflows
Authors: Eckel Linda , Stütz Peter
Published: September 2024

Tactical aerial reconnaissance missions using small unmanned aerial systems (UASs) have become a common scenario in the military. In particular, the detection of visually obscured objects such as camouflage materials and unexploded ordnance (UXO) is of great interest. Hyperspectral sensors, which provide detailed spectral information beyond the visible spectrum, are highly suitable for this type of reconnaissance mission. However, the additional spectral information places higher demands on system architectures to achieve efficient and robust data processing and object detection. To overcome these challenges, the concept of data reduction by band selection is introduced. In this paper, a specialized and robust concept of context-based hyperspectral sensor management with an implemented methodology of band selection for small and challenging UXO and camouflaged material detection is presented and evaluated with two hyperspectral datasets. For this purpose, several anomaly detectors such as LRX, NCC, HDBSCAN, and bandpass filters are introduced as part of the detection workflows and tested together with the sensor management in different system architectures. The results demonstrate how sensor management can significantly improve the detection performance for UXO compared to using all sensor bands or statistically selected bands. Furthermore, the implemented detection workflows and architectures yield strong performance results and improve the anomaly detection accuracy significantly compared to common approaches of processing hyperspectral images with a single, specialized anomaly detector.
Investigation of the Role of the Initial Workpiece Diameter in Deformation Control in Electromagnetic Sheet Forming
Authors: Chen Meng , Xiao Hanchen , Wang Zuoshuai , Wang Jianxun , Zuo Chao , Yang Wentie
Published: September 2024

The initial workpiece diameter is one of the most fundamental process parameters in sheet metal forming, as it determines the resistance of the draw-in material flow. In the context of conventional deep drawing, its critical role has been clearly identified. In the context of electromagnetic sheet forming, however, its role has not yet been adequately addressed. This paper aims to clarify its role, by experimentally and numerically investigating the deformation behavior of circular sheet metal in electromagnetic forming. Various combinations of the initial diameter and discharge voltage were established to induce different deformation behaviors. It was found that adjusting the initial diameter can substantially change the forming height, shape, and thickness distribution by altering the draw-in, which suggests a great improvement in deformation controllability. In summary, this study demonstrates that the initial workpiece diameter could play critical role in deformation control in electromagnetic forming.
Deep Learning Approach for Wildland Fire Recognition Using RGB and Thermal Infrared Aerial Image
Authors: Ghali Rafik , Akhloufi Moulay A.
Published: September 2024

Wildfires cause severe consequences, including property loss, threats to human life, damage to natural resources, biodiversity, and economic impacts. Consequently, numerous wildland fire detection systems were developed over the years to identify fires at an early stage and prevent their damage to both the environment and human lives. Recently, deep learning methods were employed for recognizing wildfires, showing interesting results. However, numerous challenges are still present, including background complexity and small wildfire and smoke areas. To address these challenging limitations, two deep learning models, namely CT-Fire and DC-Fire, were adopted to recognize wildfires using both visible and infrared aerial images. Infrared images detect temperature gradients, showing areas of high heat and indicating active flames. RGB images provide the visual context to identify smoke and forest fires. Using both visible and infrared images provides a diversified data for learning deep learning models. The diverse characteristics of wildfires and smoke enable these models to learn a complete visual representation of wildland fires and smoke scenarios. Testing results showed that CT-Fire and DC-Fire achieved higher performance compared to baseline wildfire recognition methods using a large dataset, which includes RGB and infrared aerial images. CT-Fire and DC-Fire also showed the reliability of deep learning models in identifying and recognizing patterns and features related to wildland smoke and fires and surpassing challenges, including background complexity, which can include vegetation, weather conditions, and diverse terrain, detecting small wildfire areas, and wildland fires and smoke variety in terms of size, intensity, and shape. CT-Fire and DC-Fire also reached faster processing speeds, enabling their use for early detection of smoke and forest fires in both night and day conditions.
Study on Fish Species Diversity in the Pingzhai Reservoir Based on Environmental DNA Technology
Authors: Yuan Jingjing , Wen Jing , Kong Qiuhong , Zhou Xianjun
Published: September 2024

This study elucidated the composition and diversity characteristics of the main fish species in the Pingzhai Reservoir by collecting and analyzing environmental DNA (eDNA) samples from the reservoir and comparing them with data from traditional fishery resource surveys. The results showed that eDNA technology detected 43 fish species spanning 37 genera, 5 orders, and 11 families. Importantly, no significant difference in fish diversity was observed among the surveyed sites, and the potential of eDNA technology in studying fish diversity in the Pingzhai Reservoir was discussed. A total of 29 species distributed across 18 genera, 3 families, and 3 orders were captured using traditional resource surveys. Overall, 21 fish species were detected using both methods, constituting 48.8% of the total fish population. Cypriniformes were the most prominently detected order in both methods. Among all the fish species, the most abundant in the Pingzhai Reservoir were the free-range fish species Hypophthalmichthys molitrix and Hypophthalmichthys nobilis, which have the largest sequence abundance in the eDNA investigation, in addition to the detection of exotic species, such as Micropterus salmoides and Oreochromis niloticus. Compared with traditional investigation methods, eDNA technology offers several advantages, including high sensitivity, minimal ecological impact, superior data accuracy, and low cost, making it suitable for fish diversity research in fishery resources investigations. This study enhances our understanding of fish diversity in the Pingzhai Reservoir and provides crucial basic information to support the ecosystem management and restoration efforts of the reservoir.
Bridging the Gap between Electronic Monitoring Policy and Practice: From the Perspective of Chinese Tuna Longliners
Authors: Shen Huihui , Song Liming
Published: September 2024

Electronic monitoring systems (EMSs) have been widely used in global fishing vessels as an effective tool to obtain reliable information about catches and fishing operations in order to verify compliance with national and international regulations. Though EMS implementation in tuna vessels has not yet been made a mandatory requirement by tuna regional fisheries management organizations, many Chinese longliners have the system on board for traceability and safety purposes. Based on interviews with managers and skippers on Chinese tuna longliners, this paper firstly identifies the challenges in electronic monitoring management that have hindered fishermen’s confidence to implement EMS at a larger scale. Then this paper proposes a work plan to facilitate EMS implementation from the perspective of Chinese tuna longliners, in which the adoption of EM standards, specifications, and procedures, and identification of EM data fields are the top priorities. To fully address concerns raised by tuna longliners, a cloud computing platform for EMS data storage, transmission, and review could help to protect data safety and confidentiality. Artificial intelligence technology is recommended to increase cost-efficiency in data review procedures, in addition to compliance incentives and financial incentives from policy makers.
Effect of Polystyrene Microplastic Exposure on Individual, Tissue, and Gene Expression in Juvenile Crucian Carp (Carassius auratus)
Authors: Huang Yuequn , Li Wenjing , Dong Kun , Li Xiangtong , Li Wenrong , Wang Dunqiu
Published: September 2024

Exposure to an environment containing microplastics can cause adverse effects on creatures through respiratory and digestive systems. In this paper, 50–500 μm polystyrene microplastics (exposure concentrations were 200 μg/L, 800 μg/L, and 3200 μg/L concentrations) were selected to study the distribution of polystyrene microplastics (PS-MPs) and the effects on the growth, development, tissue damage and gene expression of crucian carp juveniles. The results showed that PS-MPs were enriched in the intestinal tract (GIT) and gill tissue of crucian carp, and the average number of PS-MPs was between 0 to 2.33 items per individual. It was found that the average number of MPs in the intestine was more than in the gills, and it was independent of the PS-MP concentration. However, the specific gravity of PS-MPs in excreta was concentration-dependent. In addition, it was found that the exposure of the medium concentration group promoted the weight of the crucian carp larvae, inhibited the growth rate, and reduced the weight in the low and high concentration groups. The histopathological results indicated that the intestinal, gill, brain, and liver tissues all showed different degrees of damage, and the higher the concentration of PS-MPs, the more severe damage to the tissue cells. This experiment evaluated 15 genes in three treatments, which found that PS-MPs had different effects on gene expression in the liver, intestine, and gill tissues, and the tested genes were involved in different response pathways associated with virulence.
Fractal Analysis of Doped Strontium Titanate Photocatalyst
Authors: Stajcic Ivana , Serpa Cristina , Simovic Bojana , Jankovic Castvan Ivona , Dodevski Vladimir , Radojevic Vesna , Stajcic Aleksandar
Published: September 2024

In this research, the doping of SrTiO3 with Mn4+ was performed in order to evaluate the potential application as a photocatalyst for the degradation of organic dye pollutants. Since photocatalytic activity depends on grain microstructure, fractal analysis was used to estimate the Hausdorff dimension to provide a more thorough investigation of Mn@SrTiO3 morphology. Structural analysis by infrared spectroscopy indicated the incorporation of Mn4+ into the SrTiO3 lattice, while by using x-ray diffraction, the crystallite size of 44 nm was determined. The photocatalytic activity test performed on complex ethyl violet organic dye revealed potential for Mn@SrTiO3 application in water treatment. Based on fractal regression analysis, a good estimate was obtained for the reconstruction of grain shape, with a Hasudorff dimension of 1.13679, which was used to find the best kinetics model for the photodegradation reaction. The experimental data showed a nearly linear fit with fractal-like pseudo-zero order. These findings and applications of fractal dimensions could contribute to future characterizations of photocatalysts, providing a deeper understanding of surface properties and their influence on photocatalytic activity.
Distributed Consensus Fuzzy Control Method and Fractional Order Control for Power Sharing in Field Medical Microgrids under FDI Attacks
Authors: Wang Chenyu , Zhao Wenyue , Liu Lu , Wang Rui
Published: September 2024

Although field medical microgrids have been widely studied as an important component of future medical power systems, current sharing control in field medical microgrids under false information injection (FDI) attacks has rarely been researched. Based on this, this paper proposes a distributed fuzzy control method for power sharing in field medical microgrids considering communication networks under FDI attacks. First, the field medical microgrid is modeled as a multi-bus DC microgrid system with power coupling. To provide voltage control and initial current equalization, fractional order PI control is applied. In order to reduce the model complexity, the concept of block modeling is employed to transform the model into a linear heterogeneous multi-agent system. Secondly, a fully distributed current sharing fuzzy control strategy is proposed. It can precisely realize current sharing control and reduce the communication bandwidth. Finally, the proposed control strategy is verified by simulation results.
Development of Environmentally Friendly and Economical Flood-Prevention Stones Based on the Sediments of the Yellow River
Authors: Liu Ying , Xiao Hao , Jia Yongxiang , Lv Yajun , Dai Li , Yang Chen
Published: September 2024

The deposition of Yellow River sediment in the middle and lower reaches is a significant factor in the siltation of reservoirs and the occurrence of serious flooding along the river. The efficient and valuable utilization of Yellow River sediment has already become a key research topic in this field. In this study, we have employed Yellow River sediment as the primary material, in conjunction with commercially available slag, fly ash, and quicklime as the binder, to develop a novel type of artificial flood-prevention stone. Following a 28-day standard curing procedure, the highest compressive strength of the prepared artificial stone was recorded at 4.29 MPa, with a value exceeding 0.7 MPa under wet conditions. The results demonstrated that the prepared artificial stone met the specifications for artificial flood-prevention stones. The curing mechanism, as evidenced by analyses from SEM and XRD testing, indicated that the alkali excitation process in the binder, which produced C-A-S-H gel, was the key factor in enhancing the compressive strength of the specimens. Notably, an evaluation of the amount of CO2 emissions and the cost of the artificial stone concluded that the preparation process was both environmentally friendly and cost-effective.
Trends and Periodicities of Tropical Cyclone Frequencies and the Correlations with Ocean Drivers
Authors: Li Guoyou , Shi Huabin , He Zhiguo
Published: September 2024

This study presents a comprehensive analysis on the variations in the tropical cyclone (TC) frequencies during 1980–2021, including the linear trends, periodicities, and their variabilities on both global and basin-wise scales. An increasing trend in the annual number of global TCs is identified, with a significant rising trend in the numbers of tropical storms (maximum sustained wind 35 kts≤Umax<64 kts) and intense typhoons (Umax≥96 kts) and a deceasing trend for weak typhoons (64 kts≤Umax<96 kts). There is no statistically significant trend shown in the global Accumulated Cyclone Energy (ACE). On a regional scale, the Western North Pacific (WNP) and Eastern North Pacific (ENP) are the regions of the first- and second-largest numbers of TCs, respectively, while the increased TC activity in the North Atlantic (NA) contributes the most to the global increase in TCs. It is revealed in the wavelet transformation for periodicity analysis that the variations in the annual number of TCs with different intensities mostly show an inter-annual period of 3–7 years and an inter-decadal one of 10–13 years. The inter-annual and inter-decadal periods are consistent with those in the ENSO-related ocean drivers (via the Niño 3.4 index), Southern Oscillation Index (SOI), and Inter-decadal Pacific Oscillation (IPO) index. The inter-decadal variation in 10–13 years is also observed in the North Atlantic Oscillation (NAO) index. The Tropical North Atlantic (TNA) index and Atlantic Multi-decadal Oscillation (AMO) index, on the other hand, present the same inter-annual period of 7–10 years as that in the frequencies of all the named TCs in the NA. Further, the correlations between TC frequencies and ocean drivers are also quantified using the Pearson correlation coefficient. These findings contribute to an enhanced understanding of TC activity, thereby facilitating efforts to predict particular TC activity and mitigate the inflicted damage.
Marine Geotechnical Research in Greece: A Review of the Current Knowledge, Challenges and Prospects
Authors: Chtouris Nikolaos-Kimon , Hasiotis Thomas
Published: September 2024

Greece is expanding its energy grid system with submarine power and fiber optic cables between the mainland and the Aegean Sea islands. Additionally, pipelines have been installed to support natural gas facilities, and sites are being demarcated for the development of offshore wind parks. The above developments have necessitated extensive geotechnical surveying of the seabed; however, the survey data cannot be accessed for academic inspection or for desktop studies of future developments. This is further hindered by the limited geotechnical information in the Aegean and Ionian Seas. This review examines the existing information concerning the geotechnical behavior of the surficial sedimentary layers, including certain challenges associated with geotechnical sampling and CPTu interpretation. Certain prospects are discussed regarding marine geotechnical research in Greece, with examples from other European countries. The marine geotechnical data in Greece include geotechnical analyses of sediments cores and slope stability estimations, which are commonly associated with the seismic profiling of unstable slope areas. Underlying mechanisms of slope failure have mainly been attributed to the interbedded presence of weak layers (e.g., sapropels, tephra and underconsolidated sediments), the presence of gas and the cyclic loading from earthquake activity. Due to the limited geotechnical information, geological studies have contributed considerably to describing the distributions of gravity-induced events and lithostratigraphy. Within this context, a geological/geotechnical database is suggested where data can be collated and utilized for future studies.
Groups and Subgroups in Autism Spectrum Disorder (ASD) Considering an Advanced Integrative Model (AIM)
Authors: Ciolino Andrés , Ferreira María Luján , Loyacono Nicolás
Published: September 2024

Background: Autism spectrum disorder (ASD) is related to social communication difficulties, repetitive behaviors, and highly restricted interests beginning early in life. Currently, ASD is more diagnosed than in the past, and new models are needed. The Advanced Integrative Model (AIM) is a new model in which genes and concomitant medical problems to diagnosis (CMPD) and the impact of their rigorous and adequate treatment are considered. Methods: The role of a dynamic encephalopathy from which the individual response, susceptibilities in the brain and outside the brain, gut barrier and brain–blood-barrier permeabilities, and the plastic nature of the brain is proposed as a tool for diagnosis. The concomitant medical problems (CMP) are those at and outside the brain. The individual response to treatments of CMP is analyzed. Results: The AIM allows for classification into 3 main groups and 24 subgroups. Conclusions: The groups and subgroups in ASD are obtained taking into account CMPD treatments and individual response.
Cognate Facilitation in Child Third Language Learners in a Multilingual Setting
Authors: Engemann Helen , Radetzky Stefanie
Published: September 2024

Research has established cognate facilitation effects as a robust finding in bilingual adults and children. Recent studies suggest that cognate facilitation also occurs in highly proficient trilingual adults and can even accumulate across languages. The evidence for multilingual children is scarce and inconclusive. This study examines whether and in which direction cognate effects arise in 35 ten-year-old unbalanced trilingual children, who, in addition to their L1 Italian, acquired L2 German and L3 English in a three-way immersion class in the multilingual region of South Tyrol in Italy. We manipulated cognate status, comparing naming accuracy and latencies in both the L1 and the L3 across double, triple, and non-cognates. The results reveal cognate facilitation effects in naming accuracy, but not in naming speed, for all cognate conditions relative to non-cognates. Furthermore, cognate facilitation was restricted to the L3, replicating previously attested asymmetric effects in unbalanced speakers. In sum, the results indicate that cognate facilitation may boost lexical learning in unbalanced trilingual children who acquire the L2 and the L3 in mainly instructed settings. We discuss these findings in relation to the potential role of language proximity, the L2 status factor, and implications for lexical learning in diverse multilingual environments.
Public Discourse on Criminal Responsibility and Its Impact on Political-Legal Decisions: Analysing the (Re-)Appropriation of the Language of Law in the Sarah Halimi Case
Authors: Makouar Nadia
Published: September 2024

This applied linguistics study on the lay discourse about legal language analyses online public reactions to a court decision in the Sarah Halimi case, a French Jewish woman killed by her neighbour in Paris in 2017. This study draws on discourse analysis with a focus on semantics analysis and dialogism theory to delve into how legal discourse is disseminated in forums and undergoes semantic redefinition through users’ language practices of legal notion in their own discourses. Thus, the aim of this study is not to develop linguistics theories but to use linguistics to explore the relationship between (1) the public representation and perception of this murder case in three forums and (2) the politico-legal response to decisions about a lack of criminal responsibility. The latter remains a sensitive topic in several countries, and several criminal justice reforms are revised or implemented with close observation of public reaction. This analysis highlights the linguistic markers revealing emotional discourse and a polymorphous expression of a lack of confidence in the justice system and legal actors, emphasising issues in comprehending justice and the work of psychiatrists and highlighting a gap between expectations and the actual delivery of justice. This study also shows that the linguistic strategies of non-experts are similar to those of legal experts.
A Third Generation Calphad Description of Pure Lithium
Authors: Xu Wenjun , Li Xiaobo , Ou Mingyu , Ma Jinning
Published: September 2024

This study, based on the analysis of existing experimental data, presents a third generation Calphad description of lithium, covering all temperature ranges, using nonlinear least squares in Matlab. We have expanded the SGTE database’s description of lithium phases (face-centered cube, body-centered cube, liquid) down to 0 K with reasonable accuracy, taking into account the significant effort required to reconstruct the database for each element. During the evaluation process, it was determined that the low-temperature phase of lithium is fcc. The heat capacity of crystalline Li was accurately described using the extended Debye model. The third generation Calphad description of lithium utilized the two-state model and the extended Einstein model, leading to improved agreement with experimental data compared to previous assessments.
Ensemble Learning with Highly Variable Class-Based Performance
Authors: Warner Brandon , Ratner Edward , Carlous-Khan Kallin , Douglas Christopher , Lendasse Amaury
Published: September 2024

This paper proposes a novel model-agnostic method for weighting the outputs of base classifiers in machine learning (ML) ensembles. Our approach uses class-based weight coefficients assigned to every output class in each learner in the ensemble. This is particularly useful when the base classifiers have highly variable performance across classes. Our method generates a dense set of coefficients for the models in our ensemble by considering the model performance on each class. We compare our novel method to the commonly used ensemble approaches like voting and weighted averages. In addition, we compare our approach to class-specific soft voting (CSSV), which was also designed to address variable performance but generates a sparse set of weights by solving a linear system. We choose to illustrate the power of this approach by applying it to an ensemble of extreme learning machines (ELMs), which are well suited for this approach due to their stochastic, highly varying performance across classes. We illustrate the superiority of our approach by comparing its performance to that of simple majority voting, weighted majority voting, and class-specific soft voting using ten popular open-source multiclass classification datasets.
Assessing the Effects of Surgical Irrigation Solutions on Human Neutrophil Interactions with Nascent Staphylococcus aureus Biofilms
Authors: Gaur Gauri , Predtechenskaya Maria , Voyich Jovanka M. , James Garth , Stewart Philip S. , Borgogna Timothy R.
Published: September 2024

Staphylococcus aureus (S. aureus) is the leading cause of surgical site infections (SSIs) and is capable of biofilm growth on implanted foreign devices. The use of surgical irrigation solutions has become a common strategy to combat bacterial contamination events that occur during surgery. Despite their antimicrobial activity, SSI rates remain consistent, suggesting that low-level contamination persists. In these cases, circulating neutrophils must traffic from the blood to contamination sites to aid in bacterial clearance. The influence of irrigation solutions on neutrophils’ ability to engage with bacteria has not been explored. The effects of three commonly used irrigation solutions: Xperience (sodium lauryl sulfate), Irrisept (chlorhexidine gluconate), and Betadine® (povidone-iodine) on nascent S. aureus biofilms alone and in the presence of human neutrophils were assessed at manufactured and diluted concentrations. All three solutions, at a 10% dilution, inhibited bacterial growth as demonstrated by culture assays and confocal video microscopy of bacterial aggregate formation. The effects of 10% dilutions of each of these solutions on neutrophil membrane integrity (by flow cytometry and propidium iodide staining) and motility (by confocal video microscopy of neutrophil track length) were investigated with differing outcomes for each irrigation solution. At this concentration only Irrisept preserved neutrophil membrane integrity and motility. Together, this study examines an overlooked aspect of surgical irrigation solutions by investigating their impact on innate immunity and highlights the feasibility of formulations wherein solution effectiveness is complemented by neutrophil function to reduce risks of infection.