bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanical Properties and Microstructure of Dissimilar S355/AA6061-T6 FSW Butt Joints
Authors: Ziółkowski Wojciech , Boroński Dariusz , Skibicki Andrzej , Stachowiak Radosław , Kosturek Robert , Śnieżek Lucjan
Published: August 2023

The aim of this paper is to analyse the mechanical properties of butt joints between S355 steel and 6061-T6 aluminium alloy, as well as their relationship to changes in the structure of the material caused by welding. The effect of the tool offset was analysed in particular. For the analysis, tensile tests were carried out using macro- and mini-specimens taken from S355/AA6061-T6 joints and base materials. In addition, the macro- and microstructure of the joints was determined, the hardness profiles in the joints were analysed, and fractographic analysis of the fractures of the specimens was carried out. Based on the results of the macro- and microstructure examinations, typical friction stir welding (FSW) joint zones were characterised. The microstructure was observed in the interface line of the materials on the root side, the negative effect of which on the quality of the joint was confirmed by digital image correlation (DIC) strain analysis during the monotonic tensile test. The highest average value of su = 141 MPa for the entire joint was obtained for a 0.4 mm tool offset. The highest average value of su = 185 MPa for the selected joint layer was obtained for a 0.3 mm tool offset. Fracturing of the joint in the selected layer for the tool offset values of 0.3 mm and 0.4 mm occurred in the weld nugget zone (WNZ) where the lowest hardness was recorded.
Study on the Corrosion Behavior of Cemented Organic Soil in Dianchi Lake, China
Authors: Liu Wenlian , Cao Jing , Song Yunfei , Sui Sugang , Xu Hanhua , Guo Yongfa , Ding Wenyun , Huang Siyang
Published: August 2023

To study the corrosion behavior of cement soil in peat soil, the experiment involves the preparation of peat soil by incorporating humic acid into cohesive soil with a lower organic matter content. Cement soil samples are then prepared by adding cement to the mixture. These samples are subjected to immersion in fulvic acid solution and deionized water to simulate different working environments of cement soil. The experiment considers immersion time as the variable factor. It conducts observations of apparent phenomena, ion leaching tests, and unconfined compression strength tests on the cement soil. The experiment results are as follows: (1) With increasing immersion time, the surface of the cement soil in the peat soil environment experiences the disappearance of Ca(OH)2 and calcium aluminate hydrate. Additionally, large amounts of bird dropping crystals precipitate on the surface and within the specimen. The cement soil undergoes localized disintegration due to extensive erosion caused by swelling forces. (2) In the peat soil environment, fulvic acid reacts with the hydration products of cement, resulting in partial leaching of ions such as Ca2+, Mg2+, Al3+, and Fe3+ into the immersion solution. The lower the pH of the fulvic acid immersion (indicating higher concentration), the more significant the ion leaching. Increasing the ratio of humic acid to cement can slow down the leaching of ions. The cement soil undergoes dissolutive erosion in the peat soil environment. (3) The peat soil environment exerts both strengthening and corrosive effects on the cement soil. Cement soil without humic acid exhibits noticeable corrosion in the peat soil environment, gradually decreasing strength as immersion time increases. The strength decreases by 83% from 28 to 365 days. In contrast, cement soil with humic acid experiences an initial period of strengthening, leading to a significant increase in strength in the short term (34% increase from 28 to 90 days). However, the corrosive effects gradually dominate, resulting in a decrease in strength over time. The strength decreases by 80% from 90 to 365 days. This study also explores the strengthening effects of peat soil on cement soil. It identifies phenomena such as extensive erosion and new substance precipitation in cement soil.
Enhancing Starch−Based Packaging Materials: Optimization of Plasticizers and Process Parameters
Authors: Wu Yue , Tang Rongji , Guo Anfu , Tao Xiaodong , Hu Yingbin , Sheng Xianliang , Qu Peng , Wang Shaoqing , Li Jianfeng , Li Fangyi
Published: August 2023

In order to actively promote green production and address these concerns, there is an urgent need for new packaging materials to replace traditional plastic products. Starch−based packaging materials, composed of starch, fiber, and plasticizers, offer a degradable and environmentally friendly alternative. However, there are challenges related to the high crystallinity and poor compatibility between thermoplastic starch and fibers, resulting in decreased mechanical properties. To address these challenges, a novel approach combining plasticizer optimization and response surface method (RSM) optimization has been proposed to enhance the mechanical properties of starch−based packaging materials. This method leverages the advantages of composite plasticizers and process parameters. Scanning electron microscopy and X-ray crystallography results demonstrate that the composite plasticizer effectively disrupts the hydrogen bonding and granule morphology of starch, leading to a significant reduction in crystallinity. Fourier transform infrared spectroscopy results show that an addition of glycerol and D−fructose to the starch can form new hydrogen bonds between them, resulting in an enhanced plasticizing effect. The optimal process parameters are determined using the RSM, resulting in a forming temperature of 198 °C, a forming time of 5.4 min, and an AC content of 0.84 g. Compared with the non−optimized values, the tensile strength increases by 12.2% and the rebound rate increases by 8.1%.
Study and Modelling of Fluid Flow in Ceramic Foam Filters
Authors: Hassanabadi Massoud , Akhtar Shahid , Aune Ragnhild E.
Published: August 2023

To investigate the fluid flow characteristics of conventional Ceramic Foam Filters (CFFs) of grades 30 and 50, a 2D macro-scale geometry was generated by converting pixel grid images of the filters into vector format images. The flow behaviour through the filter channels was then numerically modelled using the Stocks equation within the Creeping Flow interface of COMSOL Multiphysics®. Through modelling, the average interstitial velocity was estimated and found to be higher than the corresponding value obtained from the Dupuit–Forchheimer equation. The discrepancy obtained suggested that the flow behaviour within the filter channels differed from that based on the simplified assumptions of the equation. The porosity and permeability of the CFFs were evaluated during the post-processing stage using surface integration and user-defined equations. The experimentally determined porosity closely matched the values obtained from the simulation model, demonstrating the reliability of the numerical approach. However, the permeability values from the simulation of CFFs of grades 30 and 50 were higher than those obtained experimentally. This discrepancy can be attributed to the larger channels in the generated geometrical pattern compared to the original CFF structure. The present findings highlight the effectiveness of the proposed methodology in developing a representative macro-scale geometry for CFFs and in simulating fluid flow behaviour.
Unbiased Estimates for Products of Moments and Cumulants for Finite Populations
Authors: Withers Christopher S. , Nadarajah Saralees
Published: August 2023

Let FN be the distribution function of a finite real population of size N. Let Fn be the empirical distribution function of a sample of size n drawn from the population without replacement. Let TFN be any product of the moments or cumulants of FN, let TFn denote the sample version, and let Tn,NFN denote the expected value of TFn with respect to FN. We prove the following remarkable inversion principle that the expected value of TN,nFn is equal to TFN. We also obtain an explicit expression for Tn,NFN for all TFN of orders up to six.
Multi-Objective Models for Sparse Optimization in Linear Support Vector Machine Classification
Authors: Pirouz Behzad , Pirouz Behrouz
Published: August 2023

The design of linear Support Vector Machine (SVM) classification techniques is generally a Multi-objective Optimization Problem (MOP). These classification techniques require finding appropriate trade-offs between two objectives, such as the amount of misclassified training data (classification error) and the number of non-zero elements of the separator hyperplane. In this article, we review several linear SVM classification models in the form of multi-objective optimization. We put particular emphasis on applying sparse optimization (in terms of minimization of the number of non-zero elements of the separator hyperplane) to Feature Selection (FS) for multi-objective optimization linear SVM. Our primary purpose is to demonstrate the advantages of considering linear SVM classification techniques as MOPs. In multi-objective cases, we can obtain a set of Pareto optimal solutions instead of one optimal solution in single-objective cases. The results of these linear SVMs are reported on some classification datasets. The test problems are specifically designed to challenge the number of non-zero components of the normal vector of the separator hyperplane. We used these datasets for multi-objective and single-objective models.
Freshness-Keeping Strategy of Logistics Service Providers: The Role of the Interaction between Blockchain and Overconfidence
Authors: Tu Hongbo , Pang Mo , Chen Lin
Published: August 2023

As a result of the increasing scrutiny of fresh products, greengrocers are now forced to concern themselves with the deterioration of their products’ freshness and employ blockchain technology as a tracing system. However, in the logistics system, the third-party logistics service provider (LSP) is motivated to be overconfident in order to extract extra profits, thus intensifying the dilemma faced by the fresh agricultural product industry. This paper focuses on the association between blockchain technology and overconfidence, in which the third-party LSP is supposed to overestimate the effect of the retailer’s freshness keeping measures. Differing from the previous literature, we analyze a situation wherein blockchain technology is adopted with explicit execution. Based on the optimal control model, we obtained three main conclusions: First, the overconfidence of a third-party LSP does not damage the logistics system but changes the freshness-keeping strategy of the retailer. Second, interestingly, although blockchain technology performs effectively when it is adopted as an initially established system with a freshness keeping strategy, it is not always a wise decision for managers to adopt a blockchain, especially when adopting it as a countermeasure for overconfidence. Third, we found that blockchain technology has a greater effect on freshness-keeping than overconfidence. Thus, in the fresh agricultural product industry, managers should adopt blockchain technology before overconfidence occurs and pay more attention to exogenous prices and freight to decide whether to adopt blockchain technology.
Hyperparameter Optimization for 1D-CNN-Based Network Intrusion Detection Using GA and PSO
Authors: Kilichev Dusmurod , Kim Wooseong
Published: August 2023

This study presents a comprehensive exploration of the hyperparameter optimization in one-dimensional (1D) convolutional neural networks (CNNs) for network intrusion detection. The increasing frequency and complexity of cyberattacks have prompted an urgent need for effective intrusion-detection systems (IDSs). Herein, we focus on optimizing nine hyperparameters within a 1D-CNN model, using two well-established evolutionary computation methods—genetic algorithm (GA) and particle swarm optimization (PSO). The performances of these methods are assessed using three major datasets—UNSW-NB15, CIC-IDS2017, and NSL-KDD. The key performance metrics considered in this study include the accuracy, loss, precision, recall, and F1-score. The results demonstrate considerable improvements in all metrics across all datasets, for both GA- and PSO-optimized models, when compared to those of the original nonoptimized 1D-CNN model. For instance, on the UNSW-NB15 dataset, GA and PSO achieve accuracies of 99.31 and 99.28%, respectively. Both algorithms yield equivalent results in terms of the precision, recall, and F1-score. Similarly, the performances of GA and PSO vary on the CIC-IDS2017 and NSL-KDD datasets, indicating that the efficacy of the optimization algorithm is context-specific and dependent on the nature of the dataset. The findings of this study demonstrate the importance and effects of efficient hyperparameter optimization, greatly contributing to the field of network security. This study serves as a crucial step toward developing advanced, robust, and adaptable IDSs capable of addressing the evolving landscape of cyber threats.
Deep Learning in Sign Language Recognition: A Hybrid Approach for the Recognition of Static and Dynamic Signs
Authors: Buttar Ahmed Mateen , Ahmad Usama , Gumaei Abdu H. , Assiri Adel , Akbar Muhammad Azeem , Alkhamees Bader Fahad
Published: August 2023

A speech impairment limits a person’s capacity for oral and auditory communication. A great improvement in communication between the deaf and the general public would be represented by a real-time sign language detector. This work proposes a deep learning-based algorithm that can identify words from a person’s gestures and detect them. There have been many studies on this topic, but the development of static and dynamic sign language recognition models is still a challenging area of research. The difficulty is in obtaining an appropriate model that addresses the challenges of continuous signs that are independent of the signer. Different signers’ speeds, durations, and many other factors make it challenging to create a model with high accuracy and continuity. For the accurate and effective recognition of signs, this study uses two different deep learning-based approaches. We create a real-time American Sign Language detector using the skeleton model, which reliably categorizes continuous signs in sign language in most cases using a deep learning approach. In the second deep learning approach, we create a sign language detector for static signs using YOLOv6. This application is very helpful for sign language users and learners to practice sign language in real time. After training both algorithms separately for static and continuous signs, we create a single algorithm using a hybrid approach. The proposed model, consisting of LSTM with MediaPipe holistic landmarks, achieves around 92% accuracy for different continuous signs, and the YOLOv6 model achieves 96% accuracy over different static signs. Throughout this study, we determine which approach is best for sequential movement detection and for the classification of different signs according to sign language and shows remarkable accuracy in real time.
Sharper Concentration Inequalities for Median-of-Mean Processes
Authors: Teng Guangqiang , Li Yanpeng , Tian Boping , Li Jie
Published: August 2023

The Median-of-Mean (MoM) estimation is an efficient statistical method for handling data with contamination. In this paper, we propose a variance-dependent MoM estimation method using the tail probability of a binomial distribution. The bound of this method is better than the classical Hoeffding method under mild conditions. This method is then used to study the concentration of variance-dependent MoM empirical processes and sub-Gaussian intrinsic moment norm. Finally, we give the bound of the variance-dependent MoM estimator with distribution-free contaminated data.
A Novel Artificial Visual System for Motion Direction Detection with Completely Modeled Retinal Direction-Selective Pathway
Authors: Tao Sichen , Zhang Xiliang , Hua Yuxiao , Tang Zheng , Todo Yuki
Published: August 2023

Some fundamental visual features have been found to be fully extracted before reaching the cerebral cortex. We focus on direction-selective ganglion cells (DSGCs), which exist at the terminal end of the retinal pathway, at the forefront of the visual system. By utilizing a layered pathway composed of various relevant cells in the early stage of the retina, DSGCs can extract multiple motion directions occurring in the visual field. However, despite a considerable amount of comprehensive research (from cells to structures), a definitive conclusion explaining the specific details of the underlying mechanisms has not been reached. In this paper, leveraging some important conclusions from neuroscience research, we propose a complete quantified model for the retinal motion direction selection pathway and elucidate the global motion direction information acquisition mechanism from DSGCs to the cortex using a simple spiking neural mechanism. This mechanism is referred to as the artificial visual system (AVS). We conduct extensive testing, including one million sets of two-dimensional eight-directional binary object motion instances with 10 different object sizes and random object shapes. We also evaluate AVS’s noise resistance and generalization performance by introducing random static and dynamic noises. Furthermore, to thoroughly validate AVS’s efficiency, we compare its performance with two state-of-the-art deep learning algorithms (LeNet-5 and EfficientNetB0) in all tests. The experimental results demonstrate that due to its highly biomimetic design and characteristics, AVS exhibits outstanding performance in motion direction detection. Additionally, AVS possesses biomimetic computing advantages in terms of hardware implementation, learning difficulty, and parameter quantity.
Study of Non-Linear Impulsive Neutral Fuzzy Delay Differential Equations with Non-Local Conditions
Authors: Gunasekar Tharmalingam , Thiravidarani Jothivelu , Mahdal Miroslav , Raghavendran Prabakaran , Venkatesan Arikrishnan , Elangovan Muniyandy
Published: August 2023

This manuscript aims to investigate the existence and uniqueness of fuzzy mild solutions for non-local impulsive neutral functional differential equations of both first and second order, incorporating finite delay. Furthermore, the study explores the properties of fuzzy set-valued mappings of a real variable, where these mappings exhibit characteristics such as normality, convexity, upper semi-continuity, and compact support. The application of the Banach fixed-point theorem is employed to derive the results. The research extensively employs fundamental concepts from fuzzy set theory, functional analysis, and the Hausdorff metric. Additionally, an illustrative example is provided to exemplify the practical implementation of the proposed concept.
Collagen Hydrolysate from the Scales of Mozambique Tilapia (Oreochromis mossambicus) Improve Hair and Skin Health by Alleviating Oxidative Stress and Inflammation and Promoting Hair Growth and Extracellular Matrix Factors
Authors: Hwang Su Bin , Park Hyeon Ju , Lee Bog-Hieu
Published: August 2023

Fish-derived collagen hydrolysate (CH) has shown promise in improving hair and skin health. Therefore, this study sought to comprehensively assess the effects of CH extracted from Mozambique tilapia (Oreochromis mossambicus) scales on hair and skin using in vitro and in vivo models. Human dermal papilla cells (hDPCs) were used for antioxidant and gene expression analyses, while C57BL/6 mice were orally administered CH for six weeks to assess hair growth patterns. The mice were divided into four groups: negative control (NC; distilled water), positive control (PC; 1 mg/kg finasteride), CH500 (500 mg/kg BW CH), and CH1000 (1000 mg/kg BW CH). CH mitigated catalase activity reduction in hDPCs, increased IGF-1 and VEGF levels, and decreased TGF-β1, TNF-α, and IL-1β expression. In vivo, CH treatment improved hair growth index, length, diameter, weight, and density. Scanning electron microscopy revealed reduced hair damage. Moreover, CH up-regulated IGF-1, VEGF, Elastin, and HAS2 mRNA expression while down-regulating TNF-α and IL-1β. CH enhanced hair shine, growth, and skin health while alleviating inflammation. These findings demonstrate the potential of CH in alleviating oxidative stress, promoting hair growth, and enhancing skin health, both in vitro and in vivo. Fish-derived CH offers a cost-effective and bioavailable option for improving hair and skin health.
The Preventive Mechanism of Anserine on Tert-Butyl Hydroperoxide-Induced Liver Injury in L-02 Cells via Regulating the Keap1-Nrf2 and JNK-Caspase-3 Signaling Pathways
Authors: Chen Ming , Luo Jing , Ji Hongwu , Song Wenkui , Zhang Di , Su Weiming , Liu Shucheng
Published: August 2023

Anserine is a naturally occurring histidine dipeptide with significant antioxidant activities. This study aimed to investigate the preventive mechanism of anserine on tert-butyl hydroperoxide (TBHP)-induced liver damage in a normal human liver cell line (L-02 cells). The L-02 cells were pretreated with anserine (10, 20, and 40 mmol/L) and then induced with 400 μmol/L of TBHP for 4 h. The results showed that the survival rates of L-02 cells and the contents of GSH were significantly increased with the pretreatment of anserine; the activities of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in the extracellular fluid were sharply decreased; and the formation of reactive oxygen species (ROS), nuclear fragmentation, and apoptosis were significantly inhibited. In addition, anserine could bind to the Kelch domain of Kelch-like ECH-associated protein 1 (Keap1) with a binding force of −7.2 kcal/mol; the protein expressions of nuclear factor-erythroid 2-related factor-2 (Nrf2), quinone oxidoreductase 1 (NQO1), heme oxygenase-1 (HO-1), and Bcl-2 were upregulated by anserine in TBHP-induced L-02 cells, with the downregulation of p-JNK and caspase-3. In conclusion, anserine might alleviated liver injury in L-02 cells via regulating related proteins in the Keap1-Nrf2 and JNK-Caspase-3 signaling pathways.
The COVID-19 Pandemic and Elective Spine Surgery—A Single Center Experience
Authors: Koruga Nenad , Soldo Koruga Anamarija , Butković Soldo Silva , Rončević Robert , Rotim Tatjana , Turk Tajana , Kretić Domagoj , Škiljić Sonja , Nešković Nenad , Rončević Alen
Published: August 2023

Background and objective: The COVID-19 pandemic had a profound impact on medical practice worldwide. In this study, we aimed to investigate the trends of elective spine surgery in our department before and during the pandemic. Materials and methods: Total number of spine procedures due to disc herniation (DH) or spinal stenosis (SS) was collected during 2019–2021 in the Department of Neurosurgery, University Hospital Center Osijek, Croatia. In order to elucidate potential risk factors in the post-pandemic period, demographic data were collected for patients who underwent surgery during 2021. Results: In 2020, there was a 22.1% decrease in the number of surgeries compared to 2019 (205 vs. 263), but during 2021 we observed an increase of 36.1% compared to 2020 (279 vs. 205). The mean age of patients in 2021 was 53.14 years (53.14 ± 13.05) with body mass index of 28.31 kg/m2 (28.31 ± 4.89). There were 179 overweight patients (74%) and 103 smokers (42.6%). Although male and female patients were equally represented (121 each), there was a significant interaction of weight class and sex (p = 0.013). Patients younger than 65 were more likely to undergo surgery due to DH (p < 0.001), whereas older patients were more likely to suffer from SS (p < 0.001). Conclusions: The volume of elective spine surgeries decreased in the first year of the pandemic and increased the following year. Our results suggest that public health policies in the early pandemic period reduced elective surgical procedures, which was followed by a compensatory increase in the following period.
Assessing Continuous Epidural Infusion and Programmed Intermittent Epidural Bolus for Their Effectiveness in Providing Labor Analgesia: A Mono-Centric Retrospective Comparative Study
Authors: Tsao Shao-Lun , Li Wen-Tyng , Chang Li-Yun , Yeh Pin-Hung , Yeh Liang-Tsai , Liu Ling-Jun , Yeh Chao-Bin
Published: August 2023

Background and Objectives: Local anesthetics administered via epidural catheters have evolved from intermittent top-ups to simultaneous administration of continuous epidural infusion (CEI) and patient-controlled epidural analgesia (PCEA) using the same device. The latest programmed intermittent epidural bolus (PIEB) model is believed to create a wider and more even distribution of analgesia inside the epidural space. The switch from CEI + PCEA to PIEB + PCEA in our department began in 2018; however, we received conflicting feedback regarding workload from the quality assurance team. This study aimed to investigate the benefits and drawbacks of this conversion, including the differences in acute pain service (APS) staff workload, maternal satisfaction, side effects, and complications before and after the changeover. Materials and Methods: Items from the APS records included total delivery time, average local anesthetic dosage, and the formerly mentioned items. The incidence of side effects, the association between the duration of delivery and total dosage, and hourly medication usage in the time subgroups of the CEI and PIEB groups were compared. The staff workload incurred from rescue bolus injection, catheter adjustment, and dosage adjustment was also analyzed. Results: The final analysis included 214 and 272 cases of CEI + PCEA and PIEB + PCEA for labor analgesia, respectively. The total amount of medication and average hourly dosage were significantly lower in the PIEB + PCEA group. The incidences of dosage change, manual bolus, extra visits per patient, and lidocaine use for rescue bolus were greater in the PIEB + PCEA group, indicating an increased staff workload. However, the two groups did not differ in CS rates, labor time, maternal satisfaction, and side effects. Conclusions: This study revealed that while PIEB + PCEA maintained the advantage of decreasing total drug doses, it inadvertently increased the staff burden. Increased workload might be a consideration in clinical settings when choosing between different methods of PCEA.
Thorium Removal, Recovery and Recycling: A Membrane Challenge for Urban Mining
Authors: Man Geani Teodor , Albu Paul Constantin , Nechifor Aurelia Cristina , Grosu Alexandra Raluca , Tanczos Szidonia-Katalin , Grosu Vlad-Alexandru , Ioan Mihail-Răzvan , Nechifor Gheorghe
Published: August 2023

Although only a slightly radioactive element, thorium is considered extremely toxic because its various species, which reach the environment, can constitute an important problem for the health of the population. The present paper aims to expand the possibilities of using membrane processes in the removal, recovery and recycling of thorium from industrial residues reaching municipal waste-processing platforms. The paper includes a short introduction on the interest shown in this element, a weak radioactive metal, followed by highlighting some common (domestic) uses. In a distinct but concise section, the bio-medical impact of thorium is presented. The classic technologies for obtaining thorium are concentrated in a single schema, and the speciation of thorium is presented with an emphasis on the formation of hydroxo-complexes and complexes with common organic reagents. The determination of thorium is highlighted on the basis of its radioactivity, but especially through methods that call for extraction followed by an established electrochemical, spectral or chromatographic method. Membrane processes are presented based on the electrochemical potential difference, including barro-membrane processes, electrodialysis, liquid membranes and hybrid processes. A separate sub-chapter is devoted to proposals and recommendations for the use of membranes in order to achieve some progress in urban mining for the valorization of thorium.
Fabrication and Characterization of Cu2+-Driven PTFE-Reinforced Artificial Muscle Polymer Membrane for Water Purification and Energy Harvesting Applications
Authors: Avvari Venkata Dinesh , Sreekanth P. S. Rama
Published: August 2023

Ionic polymer membranes have not yet gained widespread practical application in areas such as water purification and energy harvesting due to their high cost and tendency to swell. The present study involved the fabrication of reinforced textile structures composed of polytetrafluoroethylene (PTFE)-reinforced Nafion membranes coated with non-precious metals, copper and silver, as a surface electrode by applying a chemical decomposition technique. Several mechanical, contact angle measurement and dielectric tests were conducted on membranes to evaluate their mechanical, wettability and conductivity properties. From scanning electron microscopy, it is clear that the formation of surface electrodes with uniform dispersion of metal particles. Scratch test reveals the adhesive strength between the coated metal particles and membrane. The silver-activated copper-coated membrane has a high contact angle of 121°. Thus, the fabricated membranes can have good antibacterial and adsorption properties for water treatment. The copper-coated membrane has a high Young’s modulus of 779 ± 80 MPa and a tensile strength of 29.1 ± 8 MPa, whereas the elongation at break is more for silver-activated copper-coated samples recorded as 158 ± 4%. The viscoelastic behavior of the membranes was analyzed through dynamic mechanical analysis (DMA). A sharp rise in the storage modulus (E′) value of 4.8 × 1010 Pa at ~80 °C at a frequency of 1 Hz on metal surface electrodes signifies an improvement in the strength of the material in comparison to the initial pure membrane. The successful enhancement of conductivity on the membrane surface via chemical deposition on the silver-activated membrane is 1 × 10−4 (S/cm) and holds great potential for facilitating voltage transmission through the tribolayer in the nanogenerators.
Effect of Heat Treatment on Yellow Field Pea (Pisum sativum) Protein Concentrate Coupled with Membrane Ultrafiltration on Emulsification Properties of the Isolated >50 kDa Proteins
Authors: Asen Nancy D. , Aluko Rotimi E.
Published: August 2023

The aim of this paper was to determine the emulsification properties of protein aggregates obtained from heat pretreated yellow field pea protein concentrate (PPC). PPC dispersions were prepared in distilled water (adjusted to pH 3.0, 5.0, 7.0, or 9.0), heated in a water bath (100 °C) for 30 min, centrifuged and the supernatant passed first through a 30 kDa membrane and, then, the first retentate (>30 kDa) through a 50 kDa membrane. The 50 kDa membrane separation yielded a second retentate (>50 kDa proteins), which was isolated for emulsification studies. The near UV circular dichroic spectra of the protein samples showed more unfolded structures at pH 3.0 and 5.0 than at pH 7.0 and 9.0. The presence of small and spherical oil droplets of emulsions stabilized by the >50 kDa proteins at pH 3.0, 7.0, and 9.0 was confirmed by confocal laser scanning microscopy images. Emulsions stabilized at pH 7.0 and 9.0 had a narrower size distribution range than at pH 3.0 and 5.0. A narrow oil droplet size distribution range and lower interfacial protein concentrations of the emulsions stabilized by the >50 kDa proteins were observed at the corresponding pH of the heat treatment when compared to other pH values. Emulsions stabilized by the >50 kDa proteins exhibited a relatively low flocculation and coalescence index, which infers relative stability. The results from this work suggest that heat pretreatment of the PPC led to the formation of new protein aggregates, especially FT9 with enhanced emulsification properties, at some of the test conditions when compared to the unheated PPC.
Affinity and Pseudo-Affinity Membrane Chromatography for Viral Vector and Vaccine Purifications: A Review
Authors: Lothert Keven , Wolff Michael W.
Published: August 2023

Several chromatographic approaches have been established over the last decades for the production of pharmaceutically relevant viruses. Due to the large size of these products compared to other biopharmaceuticals, e.g., proteins, convective flow media have proven to be superior to bead-based resins in terms of process productivity and column capacity. One representative of such convective flow materials is membranes, which can be modified to suit the particular operating principle and are also suitable for economical single-use applications. Among the different membrane variants, affinity surfaces allow for the most selective separation of the target molecule from other components in the feed solution, especially from host cell-derived DNA and proteins. A successful membrane affinity chromatography, however, requires the identification and implementation of ligands, which can be applied economically while at the same time being stable during the process and non-toxic in the case of any leaching. This review summarizes the current evaluation of membrane-based affinity purifications for viruses and virus-like particles, including traditional resin and monolith approaches and the advantages of membrane applications. An overview of potential affinity ligands is given, as well as considerations of suitable affinity platform technologies, e.g., for different virus serotypes, including a description of processes using pseudo-affinity matrices, such as sulfated cellulose membrane adsorbers.
Intelligent and Adaptive System for Welding Process Automation in T-Shaped Joints
Authors: Aldalur Eider , Suárez Alfredo , Curiel David , Veiga Fernando , Villanueva Pedro
Published: August 2023

The automation of welding processes requires the use of automated systems and equipment, in many cases industrial robotic systems, to carry out welding processes that previously required human intervention. Automation in the industry offers numerous advantages, such as increased efficiency and productivity, cost reduction, improved product quality, increased flexibility and safety, and greater adaptability of companies to market changes. The field of welding automation is currently undergoing a period of profound change due to a combination of technological, regulatory, and economic factors worldwide. Nowadays, the most relevant aspect of the welding industry is meeting customer requirements by satisfying their needs. To achieve this, the automation of the welding process through sensors and control algorithms ensures the quality of the parts and prevents errors, such as porosity, unfused areas, deformations, and excessive heat. This paper proposes an intelligent and adaptive system based on the measurement of welding joints using laser scanning and the subsequent analysis of the obtained point cloud to adapt welding trajectories. This study focuses on the optimization of T-joints under specific welding conditions and is intended as an initial implementation of the algorithm, thus establishing a basis to be worked on further for a broader welding application.
Laser Beam Machining of Titanium Alloy—A Review
Authors: Pramanik Alokesh , Basak Animesh Kumar
Published: August 2023

This study investigates the laser beam machining mechanism, surface formation mechanisms, heat-affected zone, taper formation, and the dimensional deviation of the titanium alloy, based on the information available in literature. The heat induced by the laser beam melts and vaporises titanium alloy, which is removed by a high pressure-assisted gas. The machined titanium alloy surface is expected to have craters and resolidified materials which were contributed by the low thermal conductivity of the titanium alloy. Taper and circularity error can be minimised by optimising the laser parameter, but it cannot be avoided in the laser beam machining of titanium alloy. Laser beam machining induces a non-diffusion phase transformation, which slightly changes the surface mechanical properties of the titanium alloys. Laser beam machining is gaining popularity as a way to improve the surface finish quality and properties of titanium components manufactured by additive manufacturing processes. To enhance the machining efficacy of titanium alloys, several hybrid machining processes were proposed.
Effects of Exercise on Functional Recovery in Patients with Bipolar Depression: A Study Protocol for a Randomized Controlled Trial
Authors: Hamada Fumito , Hori Hikaru , Iida Hitoshi , Yokoyama Hiroyuki , Sugawara Hiroko , Hatanaka Akito , Gotoh Leo , Ogata Muneaki , Kumagai Hiroki , Yano Rika , Tomiyama Yuko , Yoshida Tetsuya , Yamaguchi Yoshimi , Asada Ryo , Masuda Masato , Okamoto Yuta , Kawasaki Hiroaki
Published: August 2023

Treatment of bipolar disorder is prone to prolongation despite various treatments, including medication. The efficacy of exercise treatment (i.e., interventions involving physical exercise and sports intervention) for major depressive disorders has been reported for depressive symptoms, cognitive function, and sleep disturbances. However, its efficacy for bipolar disorder has yet to be established. We designed a randomized, controlled, double-blind clinical trial that includes 100 patients with bipolar disorder aged 20–65 years. This will be a cluster-randomized, two-group trial that will be conducted in ten psychiatric hospitals. The hospitals will be randomly assigned to an exercise intervention + treatment as usual (exercise) group or a placebo exercise intervention (stretching) + treatment as usual (control) group. Patients will be assessed using an extensive battery of clinical tests, physical parameters, sleep status, biological parameters (cytokines, neurotrophic factors), and genetic parameters (DNA and RNA) at baseline after a 6-week intervention period, at 10-week follow-up, and at 6-month follow-up. This innovative study may provide important evidence for the effectiveness of exercise in the treatment of bipolar depression based on clinical, biological, genetic, and physiological markers.
Compact Bandwidth-Enhanced 180-Degree Phase Shifter Using Edge-Coupled Multi-Microstrip and Artificial Transmission Line
Authors: He Ding , Fan Jingxin , Zhu Zhiqiang , Yuan Yang , Yu Zhongjun
Published: August 2023

Compactness has obtained sufficient importance in wideband phase shifter design considerations, as it is directly related to fabrication cost. In this paper, a novel structure was presented to create compact broadband 180-degree phase shifter, which has the advantages of enhanced bandwidth and significantly reduced chip area. The proposed configuration consists of edge-coupled multi-microstrip lines (ECMML) and an artificial transmission line (ATL) with dual-shorted inductors, both of which have the periodic shunt load of capacitors. The ECMML can provide a high coupling coefficient, leading to an increase in the bandwidth, while the introduced capacitors can greatly reduce the line length (35.8% of the conventional method). To verify the relevant mechanisms, a wideband switched network with compact dimensions of 0.67 × 0.46 mm2 was designed via 0.15-micrometer GaAs pHEMT technology. Combined with the measured switch transistor, it was shown that the proposed phase shifter exhibits an insertion loss of less than 2 dB, a return loss of greater than 12 dB, a maximum phase error of less than 0.6° and a channel amplitude difference of less than 0.1 dB in the range of 10 to 20 GHz.
Heat Transfer Enhancement of Controllable Aspect Ratio Fractal Channel
Authors: Men Zhichao , Chen Wenjiong
Published: August 2023

Thermal management technology is a major challenge in high-end equipment. The demand for high-efficiency heat sinks has increased. In this study, a controllable aspect ratio (AR) fractal channel (CARFC) heat sink is proposed to enhance thermal performance. First, a parameterized modeling method for the CARFC is constructed. Fractal networks are constructed using control points and bifurcation points. The geometric size of each level channel is determined by considering the AR of each level channel. A mathematical relationship is established between the two parts. Under constant heat flow boundary, the effect of aspect ratio on the fractal channel performance is studied by numerical simulation. The influence of the inlet AR on the performance of the fractal channels is studied. Then, the impact of the AR of each level channel on the performance of the CARFC is studied. The results show that the AR of the inlet has an obvious effect on the performance of the fractal channel. The CARFC results show that the AR of each level channel influences the thermal performance of the heat sink, especially the aspect ratio k0 and k1. Compared with only changing the aspect ratio of the inlet, the CARFC has better performance; the peak temperature and temperature difference are reduced by 9.62% and 26.57%, respectively. The CARFC requires less coolant to meet the same thermal demand, which is of great significance in the development of lightweight equipment.
Highly Uniform Spherical MoO2-MoO3/Polypyrrole Core-Shell Nanocomposite as an Optoelectronic Photodetector in UV, Vis, and IR Domains
Authors: Elsayed Asmaa M. , Alkallas Fatemah H. , Trabelsi Amira Ben Gouider , Rabia Mohamed
Published: August 2023

A highly uniform spherical MoO2-MoO3/polypyrrole core-shell nanocomposite has been successfully synthesized as an optoelectronic photon sensing material, capable of detecting light in the UV, Vis, and IR domains. The nanocomposite is prepared through the oxidation of pyrrole using Na2MoO4, resulting in a uniform spherical morphology that has been confirmed by TEM, theoretical modeling, and SEM analyses. This morphology contributes to its promising optical behavior, characterized by a small bandgap of 1.36 eV. The optoelectronic photosensing capability of the nanocomposite has been evaluated across the UV, Vis, and IR spectra, demonstrating high efficiency. The photoresponsivity R values indicate the ability of the nanocomposite to generate hot electrons in response to incident photons. With an R value of 4.15 mA·W−1 at 440 nm, this optoelectronic device exhibits considerable promise for integration into an advanced technological apparatus. The detection (D) value of 9.30 × 108 Jones at 440 nm further confirms the high sensitivity in the Vis region. The excellent stability of the device can be attributed to the inherent MoO2-MoO3 oxide and Ppy polymer materials. This stability has been demonstrated through reproducibility studies and current-voltage measurements under various optical conditions. The combination of stability, efficiency, and sensitivity makes this optoelectronic device well suited for light sensing applications in both industrial and commercial settings. Its promising performance opens up opportunities for advancements in various fields requiring accurate and reliable light detection.
Manipulator Control System Based on Flexible Sensor Technology
Authors: Chen Jian , Wang Chunfang , Chen Jingxin , Yin Binfeng
Published: August 2023

The research on the remote control of manipulators based on flexible sensor technology is gradually extensive. In order to achieve stable, accurate, and efficient control of the manipulator, it is necessary to reasonably design the structure of the sensor with excellent tensile strength and flexibility. The acquisition of manual information by high-performance sensors is the basis of manipulator control. This paper starts with the manufacturing of materials of the flexible sensor for the manipulator, introduces the substrate, sensor, and flexible electrode materials, respectively, and summarizes the performance of different flexible sensors. From the perspective of manufacturing, it introduces their basic principles and compares their advantages and disadvantages. Then, according to the different ways of wearing, the two control methods of data glove control and surface EMG control are respectively introduced, the principle, control process, and detection accuracy are summarized, and the problems of material microstructure, reducing the cost, optimizing the circuit design and so on are emphasized in this field. Finally, the commercial application in this field is explained and the future research direction is proposed from two aspects: how to ensure real-time control and better receive the feedback signal from the manipulator.
Optimization Milling Force and Surface Roughness of Ti-6Al-4V Based on Ultrasonic-Assisted Milling (UAM): An Experimental Study
Authors: Lü Qingqing , Yang Saiyu , Yang Liquan , Liu Erbo , Li Guangxi , Xiang Daohui
Published: August 2023

This study aimed to develop a longitudinal ultrasonic-assisted milling system to investigate the machinability of titanium (Ti) Alloy Ti-6Al-4V (TC4). Aiming at reduced milling force and enhanced surface quality, ultrasonic-assisted milling was investigated taking into account the following processing parameters: spindle speed (cutting rate) n, feed per tooth fz, milling depth ap, and ultrasonic amplitude A. A comparison was made with conventional milling. The results of univariate tests demonstrated that the ultrasonic amplitude had the most significant impact on the milling force along the z-axis, resulting in a reduction of 15.48% compared with conventional milling. The range analysis results of multivariate tests demonstrated that ap and fz were the dominant factors influencing the cutting force. The minimum reduction in the milling force in ultrasonic-assisted milling along the x-, y-, and z-axes was 11.77%, 15.52%, and 17.66%, respectively, compared with that in conventional milling. The ultrasonic-assisted milling led to reduced surface roughness and enhanced surface quality; the maximum surface roughness in ultrasonic-assisted milling was 25.93%, 36.36% and 26.32% in terms of n, fz, and ap, respectively. In longitudinal ultrasonic-assisted milling, the periodic “separation-contact” was accompanied by microimpacts, resulting in even smaller intermittent periodic cutting forces. Hence, regular fish scale machining mesh was observed on the processed surface, and the workpiece surface exhibited high cleanness and smoothness. The reasonable configuration of ultrasonic-assisted milling parameters can effectively improve the milling force and surface quality of Ti alloys and accumulate reference data for the subsequent machining process research.
Three-Dimensional Printing of Large Objects with High Resolution by Dynamic Projection Scanning Lithography
Authors: Lin Chunbo , Xu Wenbin , Liu Bochao , Wang He , Xing Haiping , Sun Qiang , Xu Jia
Published: August 2023

Due to the development of printing materials, light-cured 3D printing is playing an increasingly important role in industrial and consumer markets for prototype manufacturing and conceptual design due to its advantages in high-precision and high-surface finish. Despite its widespread use, it is still difficult to achieve the 3D printing requirements of large volume, high resolution, and high speed. Currently, traditional light-cured 3D printing technologies based on stereolithography, such as regular DLP and SLA, can no longer meet the requirements of the processing size and processing rate. This paper introduces a dynamic projection of 3D printing technology utilizing a digital micro-mirror device (DMD). By projecting the ultraviolet light pattern in the form of “animation”, the printing resin is continuously cured in the exposure process to form the required three-dimensional structure. To print large-size objects, the three-dimensional model is sliced into high-resolution sectional images, and each layer of the sectional image is further divided into sub-regional images. These images are dynamically exposed to the light-curing material and are synchronized with the scanning motion of the projection lens to form a static exposure pattern in the construction area. Combined with the digital super-resolution, this system can achieve the layering and fine printing of large-size objects up to 400 × 400 × 200 mm, with a minimum feature size of 45 μm. This technology can achieve large-size, high-precision structural printing in industrial fields such as automobiles and aviation, promoting structural design, performance verification, product pre-production, and final part processing. Its printing speed and material bending characteristics are superior to existing DLP light-curing 3D printing methods.