bluuebunny/crossref_metadata_2025 huggingface dataset:
Commercial Silver-Based Dressings: In Vitro and Clinical Studies in Treatment of Chronic and Burn Wounds
Authors: Shrestha Sweta , Wang Bo , Dutta Prabir K.
Published: September 2024

Chronic wounds are a major health problem because of delayed healing, causing hardships for the patient. The infection present in these wounds plays a role in delayed wound healing. Silver wound dressings have been used for decades, beginning in the 1960s with silver sulfadiazine for infection prevention for burn wounds. Since that time, there has been a large number of commercial silver dressings that have obtained FDA clearance. In this review, we examine the literature involving in vitro and in vivo (both animal and human clinical) studies with commercial silver dressings and attempt to glean the important characteristics of these dressings in treating infected wounds. The primary presentation of the literature is in the form of detailed tables. The narrative part of the review focuses on the different types of silver dressings, including the supporting matrix, the release characteristics of the silver into the surroundings, and their toxicity. Though there are many clinical studies of chronic and burn wounds using silver dressings that we discuss, it is difficult to compare the performances of the dressings directly because of the differences in the study protocols. We conclude that silver dressings can assist in wound healing, although it is difficult to provide general treatment guidelines. From a wound dressing point of view, future studies will need to focus on new delivery systems for silver, as well as the type of matrix in which the silver is deposited. Clearly, adding other actives to enhance the antimicrobial activity, including the disruption of mature biofilms is of interest. From a clinical point of view, the focus needs to be on the wound healing characteristics, and thus randomized control trials will provide more confidence in the results. The application of different wound dressings for specific wounds needs to be clarified, along with the application protocols. It is most likely that no single silver-based dressing can be used for all wounds.
Esculetin Combats Multidrug-Resistant Salmonella Infection and Ameliorates Intestinal Dysfunction via the Nrf2 Pathway
Authors: Xu Wenjiao , Ding Wenjun , Jia Liyan , Zhu Kui , Luo Qingfeng
Published: September 2024

The increasing incidence of multidrug-resistant (MDR) Salmonella enterica serovar Typhimurium (S. Tm), known for causing invasive enteric infections, presents a significant public health challenge. Given the diminishing efficacy of existing antibiotics, it is imperative to explore novel alternatives for the treatment of MDR S. Tm infections. Here, we identified esculetin (EST), a natural coumarin abundant in dietary foods and herbs, as a compound exhibiting broad-spectrum antibacterial properties against a range of MDR bacteria. Our findings demonstrate that EST effectively inhibited the proliferation and expansion of MDR S. Tm in both in vitro experiments and animal models. Specifically, EST significantly downregulated the type 3 secretion system-1 (T3SS-1) virulence expression of MDR S. Tm, thereby preventing its invasion into intestinal epithelial cells. In S. Tm-infected mice, we observed cecal injury characterized by the upregulation of inflammatory cytokines, a reduction in goblet cell numbers, a decreased expression of tight junction proteins, and microbial dysbiosis. Conversely, EST treatment ameliorated these pathological changes induced by S. Tm infection and reduced oxidative stress by activating the nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway, thereby improving intestinal barrier function. These results suggest that dietary coumarins or a targeted plant-based diet may offer a promising strategy to counteract MDR bacteria-induced enteric diseases.
Enhancing Reliability and Performance of Load Frequency Control in Aging Multi-Area Power Systems under Cyber-Attacks
Authors: Wu Di , Guo Fusen , Yao Zeming , Zhu Di , Zhang Zhibo , Li Lin , Du Xiaoyi , Zhang Jun
Published: September 2024

This paper addresses the practical issue of load frequency control (LFC) in multi-area power systems with degraded actuators and sensors under cyber-attacks. A time-varying approximation model is developed to capture the variability in component degradation paths across different operational scenarios, and an optimal controller is constructed to manage stochastic degradation across subareas simultaneously. To assess the reliability of the proposed scheme, both Monte Carlo simulation and particle swarm optimization techniques are utilized. The methodology distinguishes itself by four principal attributes: (i) a time-varying degradation model that broadens the application from single-area to multi-area systems; (ii) the integration of physical constraints within the degradation model, which enhances the realism and practicality compared to existing methods; (iii) the sensor suffers from fault data injection attacks; and (iv) an optimal controller that leverages particle swarm optimization to effectively balance reliability and system performance, thereby improving both stability and reliability. This method has demonstrated its effectiveness and advantages in mitigating load disturbances, achieving its objectives in just one-third of the time required by established benchmarks. The case study validates the applicability of the proposed approach and demonstrates its efficacy in mitigating load disturbance amidst stochastic degradation in actuators and sensors under FDIA cyber-attacks.
Plant-Origin Additives from Boswellia Species in Emulgel Formulation for Radiotherapy Skin Care
Authors: Kulawik-Pióro Agnieszka , Goździcka Weronika , Kruk Joanna , Piotrowska Anna
Published: September 2024

The research objective of this study was to include plant-origin additives of the Boswellia species in the formulation of topical preparations for skin care after radiotherapy. The main factor damaging the skin during radiotherapy is the free radicals that form from water molecules and granulocytes in the inflammatory area; hence, the use of substances with antioxidant properties, including plant extracts rich in antioxidants, seems to be an alternative therapy in radiodermatitis treatment. A series of cosmetic preparations containing plant-origin additives from Boswellia species and corresponding placebo formulations were prepared. In order to assess the applicability of emulgels as oncocosmetics, their stability, physicochemical properties, rheological properties, and antioxidant capacity were determined. Somatosensory analysis was also performed. An attempt was also made to correlate the effect of plant-derived additives on the functional properties of the product determined via instrumental methods and the sensory properties. The most promising preparation was the emulgel containing the Soxhlet extract and essential oil (Em_SO) due to its high antioxidant properties compared to other preparations (% inhibition of 11.69) and polyphenol content (3.63 mg/dm3). Additionally, probands positively assessed all its features, including consistency (4.00), absorption (4.43), and hydration (4.71). The presence of significant correlations for % inhibition and polyphenols content with sensory and physicochemical characteristics of samples was indicated. There were low ratings for placebo preparations by probands, and the demonstrated correlations of odor with moisturization and distribution, oiliness and hydration with the % inhibition of the sample, and the content of polyphenols with the pH and size of the dispersed phase droplets proved the positive effect of the addition of plant-origin additives from Boswellia to the emulgel formulation on the functional and sensory properties.
Research Progress on the Mechanisms and Control Methods of Rockbursts under Water–Rock Interactions
Authors: Fan Ling , Chang Yangkai , Peng Kang , Bai Yansong , Luo Kun , Wu Tao , Ma Tianxing
Published: September 2024

Rock bursts are among the most severe and unpredictable hazards encountered in deep rock engineering, posing substantial threats to both construction safety and project progress. This study provides a comprehensive investigation into how moisture infiltration influences the propensity for rock bursts, aiming to establish new theoretical foundations and practical methods for their prevention. Through the analysis of meticulous laboratory mechanical experiments and sophisticated numerical simulations, we analyzed the variations in the physical and mechanical properties of rocks under different moisture conditions, with a particular focus on strength, brittleness, and energy release characteristics. The findings reveal that moisture infiltration significantly diminishes rock strength and reduces the likelihood of brittle fractures, thereby effectively mitigating the risk of rock bursts. Additionally, further research indicates that in high-moisture environments, the marked reduction in rock burst tendency is attributed to increased rock toughness and the suppression of crack propagation. This study advocates for the implementation of moisture control measures as a pre-treatment strategy for deep rock masses. This innovative approach presents a viable and effective solution to enhance engineering safety and improve construction efficiency, offering a practical method for managing rock burst risks in challenging environments.
Energy-Efficient Joint Partitioning and Offloading for Delay-Sensitive CNN Inference in Edge Computing
Authors: Zha Zhiyong , Yang Yifei , Xia Yongjun , Wang Zhaoyi , Luo Bin , Li Kaihong , Ye Chenkai , Xu Bo , Peng Kai
Published: September 2024

With the development of deep learning foundation model technology, the types of computing tasks have become more complex, and the computing resources and memory required for these tasks have also become more substantial. Since it has long been revealed that task offloading in cloud servers has many drawbacks, such as high communication delay and low security, task offloading is mostly carried out in the edge servers of the Internet of Things (IoT) network. However, edge servers in IoT networks are characterized by tight resource constraints and often the dynamic nature of data sources. Therefore, the question of how to perform task offloading of deep learning foundation model services on edge servers has become a new research topic. However, the existing task offloading methods either can not meet the requirements of massive CNN architecture or require a lot of communication overhead, leading to significant delays and energy consumption. In this paper, we propose a parallel partitioning method based on matrix convolution to partition foundation model inference tasks, which partitions large CNN inference tasks into subtasks that can be executed in parallel to meet the constraints of edge devices with limited hardware resources. Then, we model and mathematically express the problem of task offloading. In a multi-edge-server, multi-user, and multi-task edge-end system, we propose a task-offloading method that balances the tradeoff between delay and energy consumption. It adopts a greedy algorithm to optimize task-offloading decisions and terminal device transmission power to maximize the benefits of task offloading. Finally, extensive experiments verify the significant and extensive effectiveness of our algorithm.
Reduction of Torque Ripple and Axial Force in a Fully Pitched Axial Flux Switched Reluctance Motor Using a Double Stator Structure
Authors: Sahin Cihan Alp
Published: September 2024

Switched reluctance motors (SRMs) are highly advantageous electric motors for various industrial applications, particularly in electric vehicles (EVs), due to their winding-free rotor, magnet-free design, simplicity, and ease of manufacturing. The growing interest in axial flux SRMs (AFSRMs) is particularly noticeable, as axial flux electric motors with a flat shape and high aspect ratio have become commonly used in various industrial applications, including in-wheel motors for EVs. Structurally, AFSRMs significantly differ from radial flux SRMs (RFSRMs), but share the same electromagnetic operating principles. When compared to RFSRMs, AFSRMs generate higher torque per unit volume due to their more effective utilization of their air gap. In this study, the axial force on the rotor and torque ripple of a 6/4 pole fully pitched axial flux SRM (FP-AFSRM) were minimized by combining the advantages of “single-stator and single-rotor AFSRM” and “double-stator and single-rotor AFSRM” models. The proposed FP-AFSRM model, which has a “double-stator and single-rotor AFSRM” design and has the operating logic of a “single-stator and single-rotor AFSRM”, was analyzed using 3D finite element analysis. The results show that the torque ripple decreased (Δ % Trip) between (−30.42) and (−41.14), and the axial force on the rotor decreased between 17.61% and 25.4%.
Light Beam Scattering from the Metal Surface with a Complex Mono- and Two-Periodic Microstructure Formed with Femtosecond Laser Radiation
Authors: Dobrotvorskiy Sergey , Aleksenko Borys A. , Basova Yevheniia , Gnilitskyi Iaroslav M. , Kościński Mikołaj , Machado José
Published: September 2024

Currently, the technology of imparting the necessary reflective properties to a surface is becoming increasingly important. Darkening the surface and matting it helps to diffuse the reflected beam and prevent glare. The surface’s reflective properties are determined by its microstructure. Modern pico- and femtosecond lasers make it possible to obtain surfaces with high precision and create various LIPSS (laser-induced periodic surface structure) types. In this article, we describe the process of formation of a complex two-periodic microstructure on the surface of AISI 321 stainless steel under the influence of radiation from femtosecond lasers and describe the process of scattering of a light beam by the resulting surface. Modeling shows that the presence of an additional transparent coating on a flat surface does not improve its scattering properties and does not eliminate glare. In the event that a complex two-periodic structure is formed on the reflective surface and the coating surface, the nature of the reflection has a clearly defined scattered character, regardless of the angle of incidence of the light beam. This study shows the feasibility and effectiveness of forming a two-periodic structure in order to give it stealth characteristics and reduce visibility.
Highly Accurate Deep Learning Models for Estimating Traffic Characteristics from Video Data
Authors: Cai Bowen , Feng Yuxiang , Wang Xuesong , Quddus Mohammed
Published: September 2024

Traditionally, traffic characteristics such as speed, volume, and travel time are obtained from a range of sensors and systems such as inductive loop detectors (ILDs), automatic number plate recognition cameras (ANPR), and GPS-equipped floating cars. However, many issues associated with these data have been identified in the existing literature. Although roadside surveillance cameras cover most road segments, especially on freeways, existing techniques to extract traffic data (e.g., speed measurements of individual vehicles) from video are not accurate enough to be employed in a proactive traffic management system. Therefore, this paper aims to develop a technique for estimating traffic data from video captured by surveillance cameras. This paper then develops a deep learning-based video processing algorithm for detecting, tracking, and predicting highly disaggregated vehicle-based data, such as trajectories and speed, and transforms such data into aggregated traffic characteristics such as speed variance, average speed, and flow. By taking traffic observations from a high-quality LiDAR sensor as ‘ground truth’, the results indicate that the developed technique estimates lane-based traffic volume with an accuracy of 97%. With the application of the deep learning model, the computer vision technique can estimate individual vehicle-based speed calculations with an accuracy of 90–95% for different angles when the objects are within 50 m of the camera. The developed algorithm was then utilised to obtain dynamic traffic characteristics from a freeway in southern China and employed in a statistical model to predict monthly crashes.
Study of the Constraint Pillar Test and the Application in Gob-Side Entry Retaining
Authors: Tian Jinzhou , Kang Hongpu , Zhang Dongsheng , Fan Gangwei , Zheng Xiaodong
Published: September 2024

Firmly, the bearing capacity test of 1:1 equal ratio pillar under different constraint forms and different filling medium conditions was carried out. The results show that the binding pillar-forming effect is relatively good. The constraint ability of unconstrained, metal mesh, polyester mesh, hooked iron flat-hoop bushing, bellows, and spiral iron pipe is enhanced, in turn, and the carrying capacity is improved successfully. The homogeneity of high-water materials is better than concrete, and they have better compressibility, but their carrying capacity is relatively weak. The carrying capacity of concrete pillars is generously higher than that of high-water materials, but the compressibility is poor. Second, the migration characteristics of the surrounding rock structure of the gob-side entry retaining and the rule of side support are analyzed, the requirements of the side support are pointed out, and the side-support technology of the binding pillar is proposed. Taking Hijiata Mine’s 50108 working face gob-side entry retaining as an example, the bellows pump-filled concrete pillar is used as the side support body, supplemented by handling steel mesh and air-duct cloth, and toughness material is sprayed between the pillars to seal the goaf, meeting the requirements of side support and road stability. The pillar has the characteristics of high early strength, strong final consolidation carrying capacity, good crimping effect, high mechanism degree, fast construction speed, less concrete consumption, low comprehensive cost, etc., and it has a good application prospect in the gob-side entry retaining or rapid advanced working face.
Quality Assessment of Greenhouse-Cultivated Cucumbers (Cucumis sativus) during Storage Using Instrumental and Image Analyses
Authors: Christodoulou Paris , Ladika Georgia , Tsiantas Kostantinos , Kritsi Eftichia , Tsiaka Thalia , Cavouras Dionisis , Zoumpoulakis Panagiotis , Sinanoglou Vassilia J.
Published: September 2024

Cucumbers (Cucumis sativus) are known for their high water content and nutritional value, making them a valuable addition to a balanced diet. The objective of this study was to evaluate the physicochemical quality (color, moisture, water activity, and texture), and antioxidant/antiradical properties of freshly packed greenhouse-cultivated cucumbers over a 28-day storage period, utilizing a combination of high-throughput analytical techniques, including attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy, instrumental analysis, image analysis, and chemometrics. The key findings indicated that the cucumbers underwent a significant loss of moisture during the storage period, with a concomitant decrease in firmness. Color analysis revealed an increase in the yellowness of both the peel and flesh, while image analysis demonstrated increasing dissimilarity and textural disorder, particularly evident by the 13th day of storage. The spectrophotometric and spectroscopic findings demonstrated that the quality of the cucumbers was maintained during the storage period. Meanwhile, regression and discriminant analyses were employed to interpret the collected data. Predictive models were developed with high accuracy to estimate the actual storage days and flesh quality attributes based on textural and color features derived from image analysis. Overall, this study highlights the importance of controlled storage conditions in maintaining cucumber quality and provides a comprehensive approach to monitoring post-harvest changes.
Image-Based Musculoskeletal Models to Accurately Reproduce a Maximum Voluntary Isometric Contraction Test In Silico
Authors: Bottin Francesca , Viceconti Marco , Davico Giorgio
Published: September 2024

Musculoskeletal models and computational simulations are increasingly employed in clinical and research settings, as they provide insights into human biomechanics by estimating quantities that cannot be easily measured in vivo (e.g., joint contact forces). However, their clinical application remains limited by the lack of standardized protocols for developing personalized models, which in turn heavily rely on the modeler’s expertise and require task-specific validation. While motor tasks like walking and cycling have been widely studied, simulating a maximal knee extensor dynamometry test remains unexplored, despite its relevance in rehabilitation. This study aims to fill this gap by investigating the minimum amount of experimental data required to accurately reproduce a maximal voluntary contraction test in silico. For nine healthy young females, four different subject-specific musculoskeletal models with increasing levels of personalization were developed by incorporating muscle volume data from medical images and electromyographic signal envelopes to adjust, respectively, muscle maximal isometric force and tetanic activation limits. At each step of personalization, simulation outcomes were compared to experimental data. Our findings suggest that to reproduce in silico accurately the isometric dynamometry test requires information from both medical imaging and electromyography, even when dealing with healthy subjects.
Spectral Analysis of Electromagnetic Diffraction Phenomena in Angular Regions Filled by Arbitrary Linear Media
Authors: Daniele Vito G. , Lombardi Guido
Published: September 2024

A general theory for solving electromagnetic diffraction problems with impenetrable/penetrable wedges immersed in/made of an arbitrary linear (bianistropic) medium is presented. This novel and general spectral theory handles complex scattering problems by using transverse equations for layered planar and angular structures, the characteristic Green function procedure, the Wiener–Hopf technique, and a new methodology for solving GWHEs. The technique has been proven effective for analyzing problems involving wedges immersed in isotropic media; in this study, we extend the theory to more general cases while providing all necessary mathematical tools and corresponding validations. We obtain generalized Wiener–Hopf equations (GWHEs) from spectral functional equations in angular regions filled by arbitrary linear media. The equations can be interpreted with a network formalism for a systematic view. We recall that spectral methods (such as the Sommerfeld–Malyuzhinets (SM) method, the Kontorovich–Lebedev (KL) transform method, and the Wiener–Hopf (WH) method) are well-consolidated, fundamental, and effective tools for the correct and precise analysis of electromagnetic diffraction problems constituted by abrupt discontinuities immersed in media with one propagation constant, although they are not immediately applicable to multiple-propagation-constant problems. To the best of our knowledge, the proposed mathematical technique is the first extension of spectral analysis to electromagnetic problems in the presence of angular regions filled by complex arbitrary linear media, thereby providing novel mathematical tools. Validation through fundamental examples is proposed.
Assessment of Remediation Efficiency for Soils Contaminated with Metallic Mercury in Hydrocarbon Extraction Zones
Authors: Król Anna , Kukulska-Zając Ewa , Gajec Monika
Published: September 2024

Reducing mercury emissions to individual environmental compartments is now a global priority. However, undefined industrial sectors still pose a risk for mercury pollution, including the extraction, processing, and transport of crude oil and natural gas. Mercury contamination in hydrocarbon extraction areas can occur around blocking and bleeding systems, gas pressure reduction and metering points, gas purification devices, and reservoir water separators. The soil mercury content depends on the quality of the extracted fuel and can vary widely. This article reviews methods for remediating mercury-contaminated soils, including washing, acid washing, thermal desorption, removal and disposal, and soil stabilization to convert mercury into less harmful forms. The main objective of the work was to present the results of a pilot process of soil remediation contaminated with metallic mercury conducted in an industrial area. This paper presented laboratory and field test results evaluating the efficiency of a pilot soil remediation method at an industrial facility. Mercury contamination at the site was localized, primarily around blocking and bleeding systems, with soil mercury levels ranging from 1.6 mg/kg to 1116 mg/kg. In 80% of the samples, the mercury levels were 2–8.5 times above the acceptable industrial soil limits. Speciation studies indicated that over 50% of the samples contained mercury capable of emissions. The remediation method involved stabilizing the mercury in the soil by adding sulfur, forming stable mercury sulfide (cinnabar). The post-remediation measurements showed significant reductions in mercury emissions to the air, demonstrating the effectiveness of the mercury immobilization procedure.
Design of a Human Muscle-Powered Flying Machine
Authors: Piotrowski Igor , Królikowski Marcin , Urbanowicz Kamil
Published: September 2024

This study explores the design and development of a human-powered aircraft (HPA), leveraging modern engineering techniques, materials science, and advanced CAD/CAM tools. The project addresses key aspects of aircraft design, including the geometry of wings and tail, control and power transmission mechanisms, propeller selection, and material identification to achieve ultra-lightweight construction. The 3DExperience platform facilitated comprehensive model creation, simulation, and production process development, while XFLR5 was employed for aerodynamic profile analysis using the vortex lattice and panel methods. JavaProp aided in evaluating propeller thrust and power requirements. Computational fluid dynamics (CFD) simulations using the SST k-ω turbulence model provided critical insights into flow behavior. The design was found to be theoretically capable of flight, although challenges arose in selecting appropriate software for aerodynamic analysis, leading to the use of XFLR5 for early-stage design and the more advanced 3DExperience platform for final evaluations. Although structural strength analyses were not performed due to the complexity of composite materials, future work in this area could enhance the precision of component selection and aircraft mass estimation.
Studying the Process of Enzyme Treatment on Beef Meat-Bone Paste Quality
Authors: Baikadamova Assemgul , Kakimov Aitbek , Yessimbekov Zhanibek , Suychinov Anuarbek , Turagulov Rasul , Orynbekov Duman , Zhumadilova Gulmira , Zharykbasov Yerlan
Published: September 2024

Animal bones, particularly from cattle after slaughter, are commonly discarded, posing environmental challenges and highlighting the need for sustainable valorization. This study investigated the effect of enzyme and organic acid treatment on physicochemical properties, particle size, microstructure and safety of meat-bone paste (MBP). Two samples were prepared: a control (MBP-C) without enzyme treatment and an experimental sample (MBP-E) treated with pepsin and ascorbic acid. Results showed that the enzyme reaction rate increased from 0.004 mmol/min at 60 min to 0.014 mmol/min at 120–180 min before declining to 0.006 mmol/min at 480 min, suggesting substrate depletion or product inhibition. Temperature greatly influenced reaction rates, peaking at 0.0129 mmol/min at 30 °C, with significant declines at higher temperatures due to enzyme denaturation. The enzyme’s kinetic performance was proportional to the pepsin concentration, demonstrating enhanced catalytic efficiency at higher enzyme concentrations. Particle size analysis revealed that enzyme treatment significantly reduced bone particle size, with 86.33% of particles measuring between 0.05 and 0.2 mm, compared to 86.4% between 0.25 and 0.75 mm in the untreated sample. Microscopy confirmed these findings, showing an average particle size reduction from 0.21 mm to 0.052 mm after enzyme treatment. Physicochemical analysis revealed no significant differences in chemical composition between the two samples. However, enzyme-treated MBP-E exhibited a lower pH (5.9) compared to MBP-C (7.02), attributed to the addition of ascorbic acid. Water-binding capacity significantly increased in MBP-E (82.54% vs. 77.28%), indicating enhanced hydration and collagen loosening during enzymatic action. Enzyme treatment significantly reduced the total viable count and eliminated pathogenic bacteria (E. coli, Listeria, Salmonella), improving MBP safety. These findings highlight the potential of this approach for valorizing animal bones as a valuable food ingredient while promoting sustainable waste management practices.
Control and Analysis of Layered Soil Structure to Ensure Railway Roadbed Stability
Authors: Bykov Artem , Surzhik Dmitry , Kassenova Leila , Abzhanova Ainagul , Svirina Anastasia , Imanzhanova Kulbarchin
Published: September 2024

This article discusses a method for analyzing the layered structure of soil using the phase-metric method of geoelectric monitoring to ensure the reliability of a railway track. The importance of monitoring soil layers for timely detection of changes that may affect the stability and safety of railway tracks is emphasized. The use of geophysical monitoring methods, such as phase monitoring of the geoelectric signals, allows us to optimize measures to strengthen the roadway and increase its durability. The present article describes laboratory experiments in which a specialized setup was created to simulate the process of drilling through various soil layers. Geoelectric methods involving the registration of phase characteristics of the electromagnetic field were used in an experimental setup. The experiments demonstrated the effectiveness of the phase-metric method for determining the characteristics of the layered structure of the soil. The results showed that the change in the phase of the signal recorded at the receiving electrodes can be used to identify different soil layers with different electrical characteristics, such as moisture and density. The method of modeling the physical and geological environment using equivalent circuits of elements in the form of a dielectric made it possible to more accurately analyze the electrical properties of the soil. Based on the obtained data, an automatic monitoring system was developed using recurrent neural networks (RNNs), in particular long short-term memory (LSTM) networks, for automatic detection of bends and transitions in signal time series. Evaluation of the model’s effectiveness showed high accuracy in identifying layers, which contributes to increasing the reliability and efficiency of monitoring the condition of the railway track.
Preparation, Characterization, and Application of P(aluminum chloride-co-diallyldimethylammonium chloride) Hybrid Flocculant
Authors: Feng Xinrui , Liu Bei
Published: September 2024

The hybrid flocculant P(aluminum chloride-co-diallyldimethylammonium chloride) was synthesized in this study. Diallyldimethylammonium chloride monomers were used and ammonium persulfate served as the initiator. The structure of P(aluminum chloride-co-diallyldimethylammonium chloride) was characterized using Fourier-transform infrared spectroscopy, scanning electron microscopy, an electrical conductivity test, and thermogravimetric analysis. Single-factor experiments were conducted to optimize the synthetic conditions of the hybrid flocculant. An optimized product with an intrinsic viscosity of 926.36 mL/g and a flocculation decolorization rate of 99% was obtained under the following reaction conditions: the total monomer concentration was 30%, the initiator concentration was 0.7%, the reaction temperature was 60 °C, and the reaction time was 3 h. The results demonstrated that the PAC-PDMDAAC hybrid flocculant exhibited covalent bonding between its organic–inorganic components and displayed enhanced stability properties due to its high intrinsic viscosity and spatial structure. Moreover, this hybrid flocculant showed superior decolorization performance in disperse-violet-H-FRL-dye wastewater.
A Study on Operator Allocation in Consideration of Fatigue in Cell Manufacturing System
Authors: Endo Moe , Haraguchi Harumi
Published: September 2024

In a labor-intensive cell production system, it is important to train operators effectively because their skills are essential for productivity. Our previous study proposed a method to classify these skills according to a “skill index” based on the time required for each task and the allocated operators based on this method. However, in actual workplaces, it is assumed that operators accumulate fatigue due to the repetition of work, which affects the assembly time. In this study, we propose an operator allocation method that considers the effect of fatigue and verify its effectiveness compared with the results of the previous study by computer experiments. In addition, an assembly experiment with a toy is conducted based on the operator allocation method derived from the computer experiments. The experimental results show that the proposed method is effective and indicate that appropriate parameter setting is crucial when applying it in real-world scenarios.
Industrial Environmental Impact Assessment Method Based on Detection of Complex Anomalies in Time Series
Authors: Safonova Elena , Kravets Alla , Shcherbakov Maxim , Kizim Alexey , Al-Gunaid Mohammad , Echin Alexander
Published: September 2024

To minimize the environmental impact of energy enterprises, it is important to promptly identify cases of possible changes in the quality of wastewater generated at power plants, that is, cases of exceeding the maximum permissible concentrations of contamination in wastewater. The goal of the method for detecting complex anomalies in multidimensional time series obtained from smart energy stations’ sensor channels is to improve the accuracy of detecting contamination levels in industrial wastewater. To achieve this goal, the following tasks were addressed: methods for detecting time series anomalies were analyzed, the method for detecting complex anomalies was developed, software implementation of the algorithm was carried out, and experiments were conducted. The developed method is recommended for use in a smart energy monitoring system.
Comment on Castellucci et al. Impaired Vestibulo-Ocular Reflex on Video Head Impulse Test in Superior Canal Dehiscence: “Spontaneous Plugging” or Endolymphatic Flow Dissipation? Audiol. Res. 2023, 13, 802–820
Authors: Ionescu Eugen Constant , Mustea Eugenia , Reynard Pierre , Thai-Van Hung
Published: September 2024

We read, with great interest, two recent articles by Castellucci and al [...]
Research on Pavement Crack Detection Based on Random Structure Forest and Density Clustering
Authors: Wang Xiaoyan , Wang Xiyu , Li Jie , Liang Wenhui , Bi Churan
Published: September 2024

The automatic detection of road surface cracks is a crucial task in road maintenance, but the complexity of crack topology and the susceptibility of detection results to environmental interference make it challenging. To address this issue, this paper proposes an automatic crack detection method based on density clustering using random forest. First, a shadow elimination method based on brightness division is proposed to address the issue of lighting conditions affecting detection results in road images. This method compensates for brightness and enhances details, eliminating shadows while preserving texture information. Second, by combining the random forest algorithm with density clustering, the impact of noise on crack extraction is reduced, enabling the complete extraction and screening of crack information. This overcomes the shortcomings of the random forest method, which only detects crack edge information with low accuracy. The algorithm proposed in this paper was tested on the CFD and Cracktree200 datasets, achieving precision of 87.4% and 84.6%, recall rates of 83.9% and 82.6%, and F-1 scores of 85.6% and 83.6%, respectively. Compared to the CrackForest algorithm, it significantly improves accuracy, recall rate, and F-1 score. Compared to the UNet++ and Deeplabv3+ algorithms, it also achieves better detection results. The results show that the algorithm proposed in this paper can effectively overcome the impact of uneven brightness and complex topological structures on crack target detection, improving the accuracy of road crack detection and surpassing similar algorithms. It can provide technical support for the automatic detection of road surface cracks.
Computational Model for Early-Stage Aortic Valve Calcification Shows Hemodynamic Biomarkers
Authors: Mirza Asad , Hsu Chia-Pei Denise , Rodriguez Andres , Alvarez Paulina , Lou Lihua , Sey Matty , Agarwal Arvind , Ramaswamy Sharan , Hutcheson Joshua
Published: September 2024

Heart disease is a leading cause of mortality, with calcific aortic valve disease (CAVD) being the most prevalent subset. Being able to predict this disease in its early stages is important for monitoring patients before they need aortic valve replacement surgery. Thus, this study explored hydrodynamic, mechanical, and hemodynamic differences in healthy and very mildly calcified porcine small intestinal submucosa (PSIS) bioscaffold valves to determine any notable parameters between groups that could, possibly, be used for disease tracking purposes. Three valve groups were tested: raw PSIS as a control and two calcified groups that were seeded with human valvular interstitial and endothelial cells (VICs/VECs) and cultivated in calcifying media. These two calcified groups were cultured in either static or bioreactor-induced oscillatory flow conditions. Hydrodynamic assessments showed metrics were below thresholds associated for even mild calcification. Young’s modulus, however, was significantly higher in calcified valves when compared to raw PSIS, indicating the morphological changes to the tissue structure. Fluid–structure interaction (FSI) simulations agreed well with hydrodynamic results and, most notably, showed a significant increase in time-averaged wall shear stress (TAWSS) between raw and calcified groups. We conclude that tracking hemodynamics may be a viable biomarker for early-stage CAVD tracking.
Galectin-3/Gelatin Electrospun Scaffolds Modulate Collagen Synthesis in Skin Healing but Do Not Improve Wound Closure Kinetics
Authors: McLeod Karrington A. , Di Gregorio Madeleine , Tinney Dylan , Carmichael Justin , Zuanazzi David , Siqueira Walter L. , Rizkalla Amin , Hamilton Douglas W.
Published: September 2024

Chronic wounds remain trapped in a pro-inflammatory state, with strategies targeted at inducing re-epithelialization and the proliferative phase of healing desirable. As a member of the lectin family, galectin-3 is implicated in the regulation of macrophage phenotype and epithelial migration. We investigated if local delivery of galectin-3 enhanced skin healing in a full-thickness excisional C57BL/6 mouse model. An electrospun gelatin scaffold loaded with galectin-3 was developed and compared to topical delivery of galectin-3. Electrospun gelatin/galectin-3 scaffolds had an average fiber diameter of 200 nm, with 83% scaffold porosity approximately and an average pore diameter of 1.15 μm. The developed scaffolds supported dermal fibroblast adhesion, matrix deposition, and proliferation in vitro. In vivo treatment of 6 mm full-thickness excisional wounds with gelatin/galectin-3 scaffolds did not influence wound closure, re-epithelialization, or macrophage phenotypes, but increased collagen synthesis. In comparison, topical delivery of galectin-3 [6.7 µg/mL] significantly increased arginase-I cell density at day 7 versus untreated and gelatin/galectin-3 scaffolds (p < 0.05). A preliminary assessment of increasing the concentration of topical galectin-3 demonstrated that at day 7, galectin-3 [12.5 µg/mL] significantly increased both epithelial migration and collagen content in a concentration-dependent manner. In conclusion, local delivery of galectin 3 shows potential efficacy in modulating skin healing in a concentration-dependent manner.
Randomized Phase II Cancer Clinical Trials to Validate Predictive Biomarkers
Authors: Zhang Baoshan , Sun Jong-Mu , Ahn Myung-Ju , Jung Sin-Ho
Published: September 2024

Objectives: The design of cancer clinical trials incorporating biomarkers depends on various factors, including the trial phase, the type of biomarker and whether its role has been validated. This article aims to present a method for designing and analyzing phase II cancer clinical trials that validate predictive biomarkers. Methods: We propose a randomized trial design where patients are allocated between a targeted therapy and a non-targeted therapy stratified by biomarker status. Tumor response is used as the primary endpoint to validate the biomarker through interaction testing between treatment and biomarker positivity. Additionally we propose a sample size calculation method for this design, considering two types of interaction: one based on logit-transformed response rates and the other on raw response rates. Results: The proposed sample size method is applied to the design of a real randomized phase II trial. Extensive simulations are conducted to evaluate the performance of the test statistic and the sample size method under different scenarios. Conclusions: Our method provides a practical approach to validating predictive biomarkers in phase II cancer trials. The simulations demonstrate robust performance for both interaction models, offering guidance for the sample size selection and analysis strategy in biomarker-stratified trials.
Preliminary Metabolomics Study Suggests Favorable Metabolic Changes in the Plasma of Breast Cancer Patients after Surgery and Adjuvant Treatment
Authors: Jiménez-Franco Andrea , Jiménez-Aguilar Juan Manuel , Canela-Capdevila Marta , García-Pablo Raquel , Castañé Helena , Martínez-Navidad Cristian , Araguas Pablo , Malavé Bárbara , Benavides-Villarreal Rocío , Acosta Johana C. , Onoiu Alina Iuliana , Somaiah Navita , Camps Jordi , Joven Jorge , Arenas Meritxell
Published: September 2024

Background/Objectives: The management of early breast cancer (BC) includes surgery, followed by adjuvant radiotherapy, chemotherapy, hormone therapy, or immunotherapy. However, the influence of these interventions in metabolic reprogramming remains unknown. This study explored alterations in the plasma metabolome of BC patients following distinct treatments to deepen our understanding of BC pathophysiology, outcomes, and the identification of potential biomarkers. Methods: We included 52 women diagnosed with BC and candidates for surgery as primary oncological treatment. Blood samples were collected at diagnosis, two weeks post-surgery, and one month post-radiotherapy. Plasma samples from 49 healthy women served as controls. Targeted metabolomics assessed 74 metabolites spanning carbohydrates, amino acids, lipids, nucleotide pathways, energy metabolism, and xenobiotic biodegradation. Results: Before treatment, the BC patients exhibited notable changes in carbohydrate, nucleotide, lipid, and amino acid metabolism. We noticed a gradual restoration of specific metabolite levels (hypoxanthine, 3-phosphoglyceric acid, xylonic acid, and maltose) throughout different treatments, suggesting a normalization of the nucleotide and carbohydrate metabolic pathways. Moreover, we observed increased dodecanoic acid concentrations, a metabolite associated with cancer protection. These variations distinguished patients from controls with high specificity and sensitivity. Conclusions: Our preliminary study suggests that oncological treatments modify the metabolism of patients towards a favorable profile with a decrease in the pathways that favor cell proliferation and an increase in the levels of anticancer molecules. These findings emphasize the pivotal role of metabolomics in recognizing the biological pathways influenced by each cancer treatment and the resulting metabolic consequences. Furthermore, it aids in identifying potential biomarkers for disease onset and progression.
Hybrid Multi-Objective Chameleon Optimization Algorithm Based on Multi-Strategy Fusion and Its Applications
Authors: Chen Yaodan , Cao Li , Yue Yinggao
Published: September 2024

Aiming at the problems of chameleon swarm algorithm (CSA), such as slow convergence speed, poor robustness, and ease of falling into the local optimum, a multi-strategy improved chameleon optimization algorithm (ICSA) is herein proposed. Firstly, logistic mapping was introduced to initialize the chameleon population to improve the diversity of the initial population. Secondly, in the prey-search stage, the sub-population spiral search strategy was introduced to improve the global search ability and optimization accuracy of the algorithm. Then, considering the blindness of chameleon’s eye turning to find prey, the Lévy flight strategy with cosine adaptive weight was combined with greed strategy to enhance the guidance of random exploration in the eyes’ rotation stage. Finally, a nonlinear varying weight was introduced to update the chameleon position in the prey-capture stage, and the refraction reverse-learning strategy was used to improve the population activity in the later stage so as to improve the ability of the algorithm to jump out of the local optimum. Eighteen functions in the CEC2005 benchmark test set were selected as an experimental test set, and the performance of ICSA was tested and compared with five other swarm intelligent optimization algorithms. The analysis of the experimental results of 30 independent runs showed that ICSA has stronger convergence performance and optimization ability. Finally, ICSA was applied to the UAV path-planning problem. The simulation results showed that compared with other algorithms, the paths generated by ICSA in different terrain scenarios are shorter and more stable.
Active Vibration Control and Parameter Optimization of Genetic Algorithm for Partially Damped Composites Beams
Authors: Huang Zhicheng , Cheng Yang , Wang Xingguo , Wu Nanxing
Published: September 2024

The paper partially covered Active Constrained Layer Damping (ACLD) cantilever beams’ dynamic modeling, active vibration control, and parameter optimization techniques as the main topic of this research. The dynamic model of the viscoelastic sandwich beam is created by merging the finite element approach with the Golla Hughes McTavish (GHM) model. The governing equation is constructed based on Hamilton’s principle. After the joint reduction of physical space and state space, the model is modified to comply with the demands of active control. The control parameters are optimized based on the Kalman filter and genetic algorithm. The effect of various ACLD coverage architectures and excitation signals on the system’s vibration is investigated. According to the research, the genetic algorithm’s optimization iteration can quickly find the best solution while achieving accurate model tracking, increasing the effectiveness and precision of active control. The Kalman filter can effectively suppress the impact of vibration and noise exposure to random excitation on the system.