bluuebunny/crossref_metadata_2025 huggingface dataset:
Microstructure and Wear Characterization of the Fe-Mo-B-C—Based Hardfacing Alloys Deposited by Flux-Cored Arc Welding
Authors: Bembenek Michał , Prysyazhnyuk Pavlo , Shihab Thaer , Machnik Ryszard , Ivanov Olexandr , Ropyak Liubomyr
Published: July 2022

An analysis of common reinforcement methods of machine parts and theoretical bases for the selection of their chemical composition were carried out. Prospects for using flux-cored arc welding (FCAW) to restore and increase the wear resistance of machine parts in industries such as metallurgy, agricultural, wood processing, and oil industry were presented. It is noted that conventional series electrodes made of tungsten carbide are expensive, which limits their widespread use in some industries. The scope of this work includes the development of the chemical composition of tungsten-free hardfacing alloys based on the Fe-Mo-B-C system and hardfacing technology and the investigation of the microstructure and the mechanical properties of the developed hardfacing alloys. The composition of the hardfacing alloys was developed by extending the Fe-Mo-B-C system with Ti and Mn. The determination of wear resistance under abrasion and impact-abrasion wear test conditions and the hardness measurement by means of indentation and SEM analysis of the microstructures was completed. The results obtained show that the use of pure metal powders as starting components for electrodes based on the Fe-Mo-B-C system leads to the formation of a wear-resistant phase Fe(Mo,B)2 during FCAW. The addition of Ti and Mn results in a significant increase in abrasion and impact-abrasion wear resistance by 1.2 and 1.3 times, respectively.
Exploring the Physicochemical, Mechanical, and Photocatalytic Antibacterial Properties of a Methacrylate-Based Dental Material Loaded with ZnO Nanoparticles
Authors: Comeau Patricia , Burgess Julia , Malekafzali Niknaz , Leite Maria Luisa , Lee Aidan , Manso Adriana
Published: July 2022

While resin-based materials meet the many requirements of a restorative material, they lack adequate, long-lasting antimicrobial power. This study investigated a zinc oxide nanoparticle (ZnO NP)-loaded resin-blend (RB) toward a new antimicrobial photodynamic therapy (aPDT)-based approach for managing dental caries. The results confirmed that up to 20 wt% ZnO NPs could be added without compromising the degree of conversion (DC) of the original blend. The DC achieved for the 20 wt% ZnO NP blend has been the highest reported. The effects on flexural strength (FS), shear bond strength to dentin (SBS), water sorption (WS), solubility (SL), and viability of Streptococcus mutans under 1.35 J/cm2 blue light or dark conditions were limited to ≤20 wt% ZnO NP loading. The addition of up to 20 wt% ZnO NPs had a minimal impact on FS or SBS, while a reduction in the bacteria count was observed. The maximum loading resulted in an increase in SL. Furthermore, 28-day aging in 37 °C water increased the FS for all groups, while it sustained the reduction in bacteria count for the 20 wt% resin blends. Overall, the ZnO NP-loaded resin-based restorative material presents significant potential for use in aPDT.
Life Prediction Method of Dissimilar Lightweight Materials Welded Joints with Precrack under Coupled Impact-Fatigue Loading
Authors: Ni Zhengshun , Xiong Tao , Lei Jie , Wang Liuping , Gao Tong , Yu Jianwu , Mi Chengji
Published: July 2022

This paper aims to explore the fatigue life estimation approach of welded joints with precrack under coupled impact and fatigue loading, and the base metal is dissimilar 5083H111 and 5754 aluminum alloy. Impact tests are first carried out on the dissimilar lightweight materials welded joint with precrack located in the middle of the specimen, and a stress and strain field is obtained to determine the fatigue damage model parameters by using finite element dynamic analysis to simulate the impact process. Based, on the S-N curve of welded joints, the predicted life expectancy is found to be inconsistent with the experimental results. According to the continuum damage mechanics, the lifetime assessment model is presented to calculate both impact and fatigue damage. The estimated results agree well with the experimental ones.
Bending Strength of Polyamide-Based Composites Obtained during the Fused Filament Fabrication (FFF) Process
Authors: Mazurkiewicz Michał , Kluczyński Janusz , Jasik Katarzyna , Sarzyński Bartłomiej , Szachogłuchowicz Ireneusz , Łuszczek Jakub , Torzewski Janusz , Śnieżek Lucjan , Grzelak Krzysztof , Małek Marcin
Published: July 2022

The research shows the comparison between two types of polyamide-based (PA) composites and pure, base material. The conducted analysis describes how the additions of carbon fibers and glass microbeads affect the material’s properties and its behavior during the bending tests. All samples have been tested in the three main directions available during the FFF process. To extend the scope of the research, additional digital-image-correlation tests and fracture analyses were made. The obtained results indicated a positive influence of the addition of carbon fibers into the material’s volume (from 81.39 MPa in the case of pure PA to 243.62 MPa in the case of the PA reinforced by carbon fibers).
Laser Direct Joining of Steel to Polymethylmethacrylate: The Influence of Process Parameters and Surface Mechanical Pre-Treatment on the Joint Strength and Quality
Authors: Fernandes Fábio A. O. , Pinto José P. , Vilarinho Bruno , Pereira António B.
Published: July 2022

The search for lightweight structures increases the demand for non-metallic materials, such as polymers, composites, and hybrid structures. This work presents the dissimilar joining through direct laser joining between polymethylmethacrylate (PMMA) and S235 galvanised steel using a pulsed Nd:YAG laser. The main goal is to determine the influence of processing parameters on joint strength and quality. In addition, the impact of surface conditions on the joint quality was also analysed. Overall, the optimum ranges of process parameters were found, and some are worth highlighting, such as the laser beam diameter and pulse duration, which significantly influenced the joint strength. Failure of the welded samples occurred in PMMA component, demonstrating good joint efficiency. Additionally, a maximum increase of 5.1% of the tensile shear strength was achieved thanks to the mechanical pre-treatment. It is possible to conclude that the joining between PMMA and the S235 galvanised steel can be performed by optimising the process parameters. Additionally, it can be enhanced through surface pre-treatments by exploring the mechanical interlock between both materials.
Normally-off Hydrogen-Terminated Diamond Field-Effect Transistor with SnOx Dielectric Layer Formed by Thermal Oxidation of Sn
Authors: He Shi , Wang Yanfeng , Chen Genqiang , Wang Juan , Li Qi , Zhang Qianwen , Wang Ruozheng , Zhang Minghui , Wang Wei , Wang Hongxing
Published: July 2022

SnOx films were deposited on a hydrogen-terminated diamond by thermal oxidation of Sn. The X-ray photoelectron spectroscopy result implies partial oxidation of Sn film on the diamond surface. The leakage current and capacitance–voltage properties of Al/SnOx/H-diamond metal-oxide-semiconductor diodes were investigated. The maximum leakage current density value at −8.0 V is 1.6 × 10−4 A/cm2, and the maximum capacitance value is measured to be 0.207 μF/cm2. According to the C–V results, trapped charge density and fixed charge density are determined to be 2.39 × 1012 and 4.5 × 1011 cm−2, respectively. Finally, an enhancement-mode H-diamond field effect transistor was obtained with a VTH of −0.5 V. Its IDMAX is −21.9 mA/mm when VGS is −5, VDS is −10 V. The effective mobility and transconductance are 92.5 cm2V−1 s−1 and 5.6 mS/mm, respectively. We suspect that the normally-off characteristic is caused by unoxidized Sn, whose outermost electron could deplete the hole in the channel.
Using Fumed Silica to Develop Thermal Insulation Cement for Medium–Low Temperature Geothermal Wells
Authors: Shen Lan , Tan Huijing , Ye You , He Wei
Published: July 2022

During geothermal energy development, the bottom high-temperature fluid continuously exchanges heat with the upper low-temperature wellbore and the stratum during its rising process. Thermal insulation cement (TIC) can increase the outlet temperature, thus effectively reducing the heat loss of the geothermal fluid and improving energy efficiency. In this study, vitrified microbubbles (VMB) were screened out by conducting an orthogonal test of compressive strength (CS) and thermal conductivity (TC) on three inorganic thermal insulation materials (VMB, expanded perlite (EP), and fly-ash cenosphere (FAC)). Fumed silica (FS) was introduced into the cement with VMBs, as its significant decreasing effect on the TC. Moreover, a cement reinforcing agent (RA) and calcium hydroxide [CH] were added to further improve the CS of TIC at 90 °C. The fresh properties, CS, TC, hydration products, pore-size distribution, and the microstructure of the cement were investigated. As a result, a TIC with a TC of 0.1905 W/(m·K) and CS of 5.85 MPa was developed. The main conclusions are as follows: (1) Increasing the mass fraction of the thermal insulation material (TIM) is an effective method to reduce TC. (2) The CH content was reduced, but the C–S–H gel increased as FS content increased due to the pozzolanic reaction of the FS. (3) As the C–S–H gel is the main product of both the hydration and pozzolanic reactions, the matrix of the cement containing 60% FS and VMBs was mainly composed of gel. (4) The 10% RA improved the cement fluidity and increased the CS of TIC from 3.5 MPa to 5.85 MPa by promoting hydration.
Development of Calcium Carbonate-Based Coatings by the Carbonation of Gamma-C2S (γ-C2S)
Authors: Lei Ming , Liu Zhichao , Wang Fazhou , Hu Shuguang
Published: July 2022

A calcium carbonate (CaCO3)-based coating with gamma-C2S (γ-C2S) as the main carbonatable binder is proposed to protect the metal substrate against corrosion in this paper. Here, the morphology and phase assemblage of the coatings are studied by scanning electron microscopy (SEM) and X-ray diffraction (XRD), and the corrosion resistance of the coating is evaluated by electrochemical impedance spectroscopy (EIS) and X-ray photoelectron spectroscopy (XPS). Results show that the carbonated coating has excellent properties in terms of ultraviolet (UV) aging resistance, salt fog resistance, and electrochemical corrosion resistance. The porosity of deposited coating on steel substrates decreases by 47.1% after carbonation due to the compacted calcium carbonate formation, which is recognized as a self-compacting process during carbonation. The coating also exhibits rapid strength development within the first 2 h of carbonation; both the CO2 uptake efficiency and degree of carbonation (DOC) can reach more than 95% of the total CO2 uptake efficiency and final DOC values. This study provides a novel insight to extend the category of inorganic coating with additional benefits of CO2 solidification.
The Residual Stress and Deformation Control of TC4 Thin-Walled Outer Ring Components by Ultrasonic Regulation
Authors: Song Wen-Yuan , Xu Chun-Guang , Pan Qin-Xue , Li Pei-Lu , Wang Lei , Yu Tao
Published: July 2022

The deformation problem caused by the excessive residual stress has brought great challenges to the high-precision machining and geometrical stability of thin-walled components. Aiming to ensure the verticality within 0.012 mm after the processing and forming of a certain type of outer ring components, this paper firstly employs the ultrasonic critical refraction longitudinal wave (LCR wave) detection method to test the residual stress distribution in the key process. Additionally, the stress elimination effect of cryogenic stress relief treatment and the effect of residual stress on vertical deformation are analyzed. After that, combined with the self-developed ultrasonic stress relief (USR) equipment, the ultrasonic regulation treatment was used to replace the heat treatment stress relief process for the processing. The results show that after wire cutting and milling, excessive residual stress induces deformation of components, and USR method can eliminate machining residual stress more efficiently and quickly. As the whole component has torsional deformation along the cross section, the hole position at the upper and lower end faces is changed, which leads to the change in verticality. Finally, based on the results of X-ray diffraction (XRD), the potential microscopic mechanism of stress relief by ultrasonic treatment is analyzed. This study provides guidance for ultrasonic residual stress regulation to achieve the high-precision outer ring thin-walled components.
ESR Investigations of the Submicron LiFe1−xMnxPO4 Systems
Authors: Gavrilova Tatiana , Yagfarova Adilya , Khantimerov Sergey , Abdullin Dinar , Kosova Nina , Suleimanov Nail
Published: July 2022

Magnetic properties of the submicron carbon-coated LiFe1−xMnxPO4 (x = 0, 0.01, 0.1) systems were investigated using the electron spin resonance (ESR) method. The observed ESR signal consisted of two broad resonance lines with a Lorentzian line shape for all samples. The temperature dependence character of the integral intensity of these lines changed significantly with increasing manganese concentration, indicating a change in the nature of the magnetic interactions between the manganese and iron ions. We suggest that the noticeable capacity loss observed in the LiFe1−xMnxPO4 systems with increasing Mn content can be explained by the random distribution of Mn ions and changes to the type of magnetic ordering in these systems, despite the attractiveness of the electrochemical Mn2+/Mn3+ pair compared with Fe+2/Fe+3.
Data Mining Algorithms for Operating Pressure Forecasting of Crude Oil Distribution Pipelines to Identify Potential Blockages
Authors: Santoso Agus , Wijaya Fransisco Danang , Setiawan Noor Akhmad , Waluyo Joko
Published: July 2022

The implementation of data mining has become very popular in many fields recently, including in the petroleum industry. It is widely used to help in decision-making processes in order to minimize oil losses during operations. One of the major causes of loss is oil flow blockages during transport to the gathering facility, known as the congeal phenomenon. To overcome this situation, real-time surveillance is used to monitor the oil flow condition inside pipes. However, this system is not able to forecast the pipeline pressure on the next several days. The objective of this study is to forecast the pressure several days in advance using real-time pressure data, as well as external factor data recorded by nearby weather stations, such as ambient temperature and precipitation. Three machine learning algorithms—multi-layer perceptron (MLP), long short-term memory (LSTM), and nonlinear autoregressive exogenous model (NARX)—are evaluated and compared with each other using standard regression evaluation metrics, including a steady-state model. As a result, with proper hyperparameters, in the proposed method of NARX with MLP as a regressor, the NARX algorithm showed the best performance among the evaluated algorithms, indicated by the highest values of R2 and lowest values of RMSE. This algorithm is capable of forecasting the pressure with high correlation to actual field data. By forecasting the pressure several days ahead, system owners may take pre-emptive actions to prevent congealing.
Deep Transfer Learning Method Based on Automatic Domain Alignment and Moment Matching
Authors: Zhang Jingui , Meng Chuangji , Xu Cunlu , Ma Jingyong , Su Wei
Published: July 2022

Domain discrepancy is a key research problem in the field of deep domain adaptation. Two main strategies are used to reduce the discrepancy: the parametric method and the nonparametric method. Both methods have achieved good results in practical applications. However, research on whether the combination of the two can further reduce domain discrepancy has not been conducted. Therefore, in this paper, a deep transfer learning method based on automatic domain alignment and moment matching (DA-MM) is proposed. First, an automatic domain alignment layer is embedded in the front of each domain-specific layer of a neural network structure to preliminarily align the source and target domains. Then, a moment matching measure (such as MMD distance) is added between every domain-specific layer to map the source and target domain features output by the alignment layer to a common reproduced Hilbert space. The results of an extensive experimental analysis over several public benchmarks show that DA-MM can reduce the distribution discrepancy between the two domains and improve the domain adaptation performance.
Opinion Mining of Green Energy Sentiment: A Russia-Ukraine Conflict Analysis
Authors: Ibar-Alonso Raquel , Quiroga-García Raquel , Arenas-Parra Mar
Published: July 2022

In this paper, we assess sentiment and emotion regarding green energy through employing a social listening analysis on Twitter. Knowing the sentiment and attitude of the population is important because it will help to promote policies and actions that favor the development of green or renewable energies. We chose to study a crucial period that coincides with the onset of the 2022 Ukrainian–Russo conflict, which has undoubtedly affected global energy policies worldwide. We searched for messages containing the term “green energy” during the days before and after the conflict started. We then performed a semantic analysis of the most frequent words, a comparative analysis of sentiments and emotions in both periods, a dimensionality reduction analysis, and an analysis of the variance of tweets versus retweets. The results of the analysis show that the conflict has changed society’s sentiments about an energy transition to green energy. In addition, we found that negative feelings and emotions emerged in green energy tweeters once the conflict started. However, the emotion of confidence also increased as the conflict, intimately linked to energy, has driven all countries to promote a rapid transition to greener energy sources. Finally, we observed that of the two latent variables identified for social opinion, one of them, pessimism, was maintained while the other, optimism, was subdivided into optimism and expectation.
The Effects of Cognitive and Skill Learning on the Joint Vendor–Buyer Model with Imperfect Quality and Fuzzy Random Demand
Authors: Fu Kaifang , Chen Zhixiang , Zhou Guolin
Published: July 2022

This study investigates the optimization of an integrated production–inventory system that consists of an original equipment manufacturer (OEM) supplier and an OEM brand company. The cognitive and skill learning effect, imperfect quality, and fuzzy random demand are incorporated into the integrated two-echelon supply chain model to minimize the total cost. We contribute to dividing the learning effect into cognitive learning and skill learning, we build a new learning curve to resemble the real complexity more closely and avoid the problem that production time tends towards zero after production is stable. In total, five production–inventory models are constructed. Furthermore, a solution procedure is designed to solve the model to obtain the optimal order quantities, and the optimal shipment size. Additionally, the symbolic distance method is used to deal with the inverse fuzzification. Then numerical analysis shows that the increase of the cognitive learning coefficient and skill learning coefficient will reduce the total cost of the production–inventory system. With the increase of the cognitive learning coefficient, the gap between the total cost of cognitive learning and skill learning, and that of Wright learning, correspondingly decreases consistently. However, with the increase of the skill learning coefficient, there is a consistent corresponding increase. The total cost of cognitive learning and skill learning shows hyperbolic characteristics. The important insights of this study for managers are that employees’ knowledge plays an important role in reducing costs in the early learning stage and humanistic management measures should be taken to reduce employees’ turnover. Compared with the skill learning training for production technicians, we should pay more attention to the training of cognitive learning.
MSGWO-MKL-SVM: A Missing Link Prediction Method for UAV Swarm Network Based on Time Series
Authors: Nan Mingyu , Zhu Yifan , Zhang Jie , Wang Tao , Zhou Xin
Published: July 2022

Missing link prediction technology (MLP) is always a hot research area in the field of complex networks, and it has been extensively utilized in UAV swarm network reconstruction recently. UAV swarm is an artificial network with strong randomness, in the face of which prediction methods based on network similarity often perform poorly. To solve those problems, this paper proposes a Multi Kernel Learning algorithm with a multi-strategy grey wolf optimizer based on time series (MSGWO-MKL-SVM). The Multiple Kernel Learning (MKL) method is adopted in this algorithm to extract the advanced features of time series, and the Support Vector Machine (SVM) algorithm is used to determine the hyperplane of threshold value in nonlinear high dimensional space. Besides that, we propose a new measurable indicator of Multiple Kernel Learning based on cluster, transforming a Multiple Kernel Learning problem into a multi-objective optimization problem. Some adaptive neighborhood strategies are used to enhance the global searching ability of grey wolf optimizer algorithm (GWO). Comparison experiments were conducted on the standard UCI datasets and the professional UAV swarm datasets. The classification accuracy of MSGWO-MKL-SVM on UCI datasets is improved by 6.2% on average, and the link prediction accuracy of MSGWO-MKL-SVM on professional UAV swarm datasets is improved by 25.9% on average.
Behavioral Study of Software-Defined Network Parameters Using Exploratory Data Analysis and Regression-Based Sensitivity Analysis
Authors: Akinsolu Mobayode O. , Sangodoyin Abimbola O. , Uyoata Uyoata E.
Published: July 2022

To provide a low-cost methodical way for inference-driven insight into the assessment of SDN operations, a behavioral study of key network parameters that predicate the proper functioning and performance of software-defined networks (SDNs) is presented to characterize their alterations or variations, given various emulated SDN scenarios. It is standard practice to use simulation environments to investigate the performance characteristics of SDNs, quantitatively and qualitatively; hence, the use of emulated scenarios to typify the investigated SDN in this paper. The key parameters studied analytically are the jitter, response time and throughput of the SDN. These network parameters provide the most vital metrics in SDN operations according to literature, and they have been behaviorally studied in the following popular SDN states: normal operating condition without any incidents on the SDN, hypertext transfer protocol (HTTP) flooding, transmission control protocol (TCP) flooding, and user datagram protocol (UDP) flooding, when the SDN is subjected to a distributed denial-of-service (DDoS) attack. The behavioral study is implemented primarily via univariate and multivariate exploratory data analysis (EDA) to characterize and visualize the variations of the SDN parameters for each of the emulated scenarios, and linear regression-based analysis to draw inferences on the sensitivity of the SDN parameters to the emulated scenarios. Experimental results indicate that the SDN performance metrics (i.e., jitter, latency and throughput) vary as the SDN scenario changes given a DDoS attack on the SDN, and they are all sensitive to the respective attack scenarios with some level of interactions between them.
Impact of Regressand Stratification in Dataset Shift Caused by Cross-Validation
Authors: Sáez José A. , Romero-Béjar José L.
Published: July 2022

Data that have not been modeled cannot be correctly predicted. Under this assumption, this research studies how k-fold cross-validation can introduce dataset shift in regression problems. This fact implies data distributions in the training and test sets to be different and, therefore, a deterioration of the model performance estimation. Even though the stratification of the output variable is widely used in the field of classification to reduce the impacts of dataset shift induced by cross-validation, its use in regression is not widespread in the literature. This paper analyzes the consequences for dataset shift of including different regressand stratification schemes in cross-validation with regression data. The results obtained show that these allow for creating more similar training and test sets, reducing the presence of dataset shift related to cross-validation. The bias and deviation of the performance estimation results obtained by regression algorithms are improved using the highest amounts of strata, as are the number of cross-validation repetitions necessary to obtain these better results.
Differential Game for an Infinite System of Two-Block Differential Equations
Authors: Ibragimov Gafurjan , Kuchkarova Sarvinoz , Hasim Risman Mat , Pansera Bruno Antonio
Published: July 2022

We present a pursuit differential game for an infinite system of two-block differential equations in Hilbert space l2. The pursuer and evader control functions are subject to integral constraints. The differential game is said to be completed if the state of the system falls into the origin of l2 at some finite time. The purpose of the pursuer is to bring the state of the controlled system to the origin of the space l2, whereas the evader’s aim is to prevent this. For the optimal pursuit time, we obtain an equation and construct the optimal strategies for the players.
Deep Learning for Forecasting Electricity Demand in Taiwan
Authors: Yang Cheng-Hong , Chen Bo-Hong , Wu Chih-Hsien , Chen Kuo-Chang , Chuang Li-Yeh
Published: July 2022

According to the World Energy Investment 2018 report, the global annual investment in renewable energy exceeded USD 200 billion for eight consecutive years until 2017. In this paper, a deep-learning-based time-series prediction method, namely a gated recurrent unit (GRU)-based prediction method, is proposed to predict energy generation in Taiwan. Data on thermal power (coal, oil, and gas power), renewable energy (conventional hydropower, solar power, and wind power), pumped hydropower, and nuclear power generation for 1991 to 2020 were obtained from the Bureau of Energy, Ministry of Economic Affairs, Taiwan, and the Taiwan Power Company. The proposed GRU-based method was compared with six common forecasting methods: autoregressive integrated moving average, exponential smoothing (ETS), Holt–Winters ETS, support vector regression (SVR), whale-optimization-algorithm-based SVR, and long short-term memory. Among the methods compared, the proposed method had the lowest mean absolute percentage error and root mean square error and thus the highest accuracy. Government agencies and power companies in Taiwan can use the predictions of accurate energy forecasting models as references to formulate energy policies and design plans for the development of alternative energy sources.
Impact of Alirocumab on Release Markers of Atherosclerotic Plaque Vulnerability in Patients with Mixed Hyperlipidemia and Vulnerable Atherosclerotic Plaque
Authors: Kosowski Michał , Basiak Marcin , Hachuła Marcin , Okopień Bogusław
Published: July 2022

Background and Objectives: Atherosclerosis is a disease in the pathogenesis of which plasma factors apart from elevated cholesterol levels play a keyrole. Such factors include osteopontin (OPN), osteoprotegerin (OPG), and metalloproteinases (MMPs), which are factors that may be responsible for the stabilization of atherosclerotic plaque. The aim of this study was to assess the effect of modern lipid-lowering therapy by using proprotein convertase subtilisin/kexin type 9 (PCSK-9) inhibitor on the concentrations of these factors. Materials and Methods: The study included people suffering from dyslipidemia who were eligible to start alirocumab therapy. In this group, the concentrations of OPN, OPG, and MMPs were assessed before the initiation of therapy and after three months of its duration. Results: In the study, we observed a statistically significant reduction in the concentrations of OPN, OPG (p < 0.001), and metalloproteinase 2 (MMP-2) (p < 0.05) after the applied therapy. Moreover, we noticed that in the group of patients soon to start alirocumab therapy, the concentrations of these factors were higher compared to the control group (p < 0.001). Conclusions: The results of our study show that therapy with alirocumab significantly reduces the concentration of factors that affect atherosclerotic plaque vulnerability, which may explain their important role in reducing cardiovascular risk in patients undergoing this therapy.
Pathways of Adolescent Life Satisfaction Association with Family Support, Structure and Affluence: A Cross-National Comparative Analysis
Authors: Zaborskis Apolinaras , Kavaliauskienė Aistė , Dimitrova Elitsa , Eriksson Charli
Published: July 2022

Background and Objectives: Despite the importance of life satisfaction for health and well-being, there is a paucity of cross-national comparative studies in life satisfaction related to the family environment. The present research examined the pathways of life satisfaction association with perceived family support and other family environment variables among adolescents aged from 11 to 15 years in 45 countries. Materials and Methods: Samples from the Health Behaviour in School-aged Children (HBSC) survey in 2017/2018 were analysed (n = 188,619). Path analysis was applied to evaluate the associations among the study variables. Results: A positive association between the life satisfaction score and high family support was identified in all 45 countries (standardized regression weight ranged from 0.067 to 0.420, p < 0.05). In majority of countries, living with both parents and higher levels of family affluence had a positive effect on adolescent life satisfaction both directly and indirectly through family support. In the described path model, the proportion of life satisfaction score variance that was accounted for by family support, family structure, family affluence, gender and age was up to 25.3%. The path models made it possible to group the participating countries into two clusters. In the first cluster (10 countries) the Eastern and Southern European countries dominated, while the second cluster (35 countries) united the countries of Western and Central Europe. Conclusions: There is evidence that countries with high level of adolescent life satisfaction differ in the high rate of intact family structure and the strong relation between family support and perceived life satisfaction.
Orthopedic Surgeons’ Accuracy When Orienting an Acetabular Cup. A Comparison with Untrained Individuals
Authors: Moreta Jesús , Gayoso Óscar , Donaire-Hoyas Daniel , Roces-García Jorge , Gómez-Vallejo Jesús , Moya-Gómez Esther , Raya-Roldán David , Albert-Ullibarri Alberto , Marqués-López Fernando , Albareda Jorge
Published: July 2022

Background and Objectives: Previous studies demonstrated a huge variability among surgeons when it comes to reproducing the position of an acetabular cup in total hip arthroplasty. Our main objective is to determine if orthopedic surgeons can replicate a given orientation on a pelvic model better than untrained individuals. Our secondary objective is to determine if experience has any influence on their ability for this task. Materials and Methods: A group of specialist orthopedic hip surgeons and a group of volunteers with no medical training were asked to reproduce three given (randomly generated) acetabular cup orientations (inclination and anteversion) on a pelvic model. Error was measured by means of a hip navigation system and comparisons between groups were made using the appropriate statistical methods. Results: The study included 107 individuals, 36 orthopedic surgeons and 71 untrained volunteers. The mean error among surgeons was slightly greater as regards both inclination (7.84 ± 5.53 vs. 6.70 ± 4.03) and anteversion (5.85 ± 4.52 vs. 5.48 ± 3.44), although statistical significance was not reached (p = 0.226 and p = 0.639, respectively). Similarly, although surgeons with more than 100 procedures a year obtained better results than those with less surgical experience (8.01 vs. 7.67 degrees of error in inclination and 5.83 vs. 5.87 in anteversion), this difference was not statistically significant, either (p = 0.852 and p = 0.981). Conclusions: No differences were found in the average error made by orthopedic surgeons and untrained individuals. Furthermore, the surgeons’ cup orientation accuracy was not seen to improve significantly with experience.
Development of High Flux Nanocomposite Polyphenylsulfone/Oxidized Multiwalled Carbon Nanotubes Membranes for Ultrafiltration Using the Systems with Critical Solution Temperatures
Authors: Plisko Tatiana V. , Burts Katsiaryna S. , Bildyukevich Alexandr V.
Published: July 2022

The study deals with the investigation of the effect of the modification of polyphenylsulfone (PPSU) flat sheet membranes for ultrafiltration using oxidized multiwalled carbon nanotubes (O-MWCNT) in order to enhance membrane permeability and antifouling performance. The effect of O-MWCNT loading to the PPSU-polyethylene glycol (PEG-20,000, Mn = 20,000 g·mol−1)-polyvinylpyrrolidone (PVP K-30, Mn = 40,000 g·mol−1)-N-methy-2-pyrrolidinone (NMP) colloid systems on the phase state and viscosity was studied. It was found that PPSU-PEG-20,000-PVP K-30-O-MWCNT-NMP colloid systems feature a gel point (T = 35–37 °C) and demixing temperature (T = 127–129 °C) at which two bulk phases are formed and a polymer system delaminates. According to the study of the phase state and viscosity of these colloid systems, a method for the preparation of high flux PPSU membranes is proposed which includes processing of the casting solution at the temperature higher than gel point (40 °C) and using a coagulation bath temperature lower than gel point (25 °C) or lower than demixing temperature (40 °C and 70 °C). Membrane structure, topology and hydrophilic-hydrophobic balance were investigated by scanning electron microscopy (SEM), atomic force microscopy (AFM) and water contact angle measurements. The effect of coagulation bath temperature and O-MWCNT concentration on the membrane separation and antifouling performance in ultrafiltration of human serum albumin and humic acids solutions was studied. It was found that the modification of PPSU ultrafiltration membranes by O-MWCNTs yielded the formation of a thinner selective layer and hydrophilization of the membrane surface (water contact angle decreased from 53–56° for the reference PPSU membrane down to 33° for the nanocomposite membrane with the addition of 0.19 wt.% O-MWCNT). These changes resulted in the increase in membrane flux (from 203–605 L·m−2·h−1 at transmembrane pressure of 0.1 MPa for the reference membrane up to 512–983 L·m−2·h−1 for nanocomposite membrane with the addition of 0.19 wt.% O-MWCNT depending on coagulation bath temperature) which significantly surpasses the performance of PPSU ultrafiltration membranes reported to date while maintaining a high level of human serum albumin rejection (83–92%). It was revealed that nanocomposite membrane demonstrated better antifouling performance (the flux recovery ratio increased from 47% for the reference PPSU membrane up to 62% for the nanocomposite membrane) and higher total organic carbon removal compared to the reference PPSU membrane in humic acids solution ultrafiltration.
Friction and Wear Properties of CoCrFeNiMnSnx High Entropy Alloy Coatings Prepared via Laser Cladding
Authors: Sun Jie , Dai Sichao , Zhang Dabin , Si Wudong , Jiang Benchi , Shu Da , Wu Lulu , Zhang Chao , Zhang Meisong , Xiong Xinyan
Published: July 2022

Due to its unique single-phase multivariate alloy characteristics and good low-temperature mechanical properties, CoCrFeNiMn high entropy alloy (HEA) has attracted the interest of many researchers in recent years. In this paper, to improve the wear resistance of Q235 alloy steel surface, CoCrFeNiMnSnx HEA coatings were prepared on the surface of Q235 steel via laser cladding. X-ray diffractometry, optical microscopy, scanning electron microscopy (SEM), and energy dispersive spectrometry were used to determine the microstructure and chemical composition. The research findings revealed that the CoCrFeNiMn HEA coatings were formed from a single FCC phase. As the Sn content in the coating increased, a new MnNi2Sn phase formed. Microhardness and friction and wear results showed that when the mole content of Sn was 0.2, the hardness of the CoCrFeNiMn HEA coating was increased by approximately 45%, the friction coefficient decreased by 0.168, and the wear loss decreased by 16.6%. Three-dimensional noncontact morphology and SEM results revealed that the wear mechanisms of CoCrFeNiMn HEA coatings were abrasive wear, delamination wear and a small amount of oxidative wear under dry friction conditions, whereas the friction mechanisms of CoCrFeNiMnSn0.2 HEA coatings were primarily abrasive wear and oxidative wear.
Rheological Behavior of Inconel 718 Powder for Electron-Beam Melting
Authors: Cordova Laura , Raza Ahmad , Hryha Eduard
Published: July 2022

Understanding the impact of powder reuse in powder-bed-fusion electron beams (PBF-EB) is key to maintain the processability and yield. Powder oxidation, due to exposure to high temperatures for a prolonged period of time, can lead to a decrease in electrical conductivity of the powder and, hence, electrostatic forces that originate during interaction with the electron beam. The effect of oxidation on physical properties as powder rheological properties, apparent/tap density and charging are studied in this work. The analysis using Scanning Electron Microscopy (SEM) shows thermodynamically stable Al-rich oxide particulates (sized 100–200 nm) covering the surface of the reused powder particles, with an increase of 20% in bulk oxygen in comparison to the virgin powder and, measured by X-ray Photoelectron Spectroscopy (XPS), average oxide thickness of circa 13 nm in the reused powder. On the one hand, reusing the powder positively impacted the flowability studied using the Revolution Powder Analyzer (RPA), in which the avalanche angle was decreased from 37 deg to 30 deg, for virgin and reused powder, respectively. The volume fraction of loose powder was similar for both virgin and reused powder, 57% and 56%, respectively, while the packed volume fraction was measured lower in the reused (57%) than the virgin powder (60%). On the other hand, the charging behavior, studied using the ION Charge Module of the powder, worsened; this almost doubled in the reuse powder (−9.18 V/g) compared to the virgin powder (−5.84 V/g). The observation of ejected particles from the build volume is attributed to the charging behavior and lower packing volume fraction in the reused powder.
Parametric Study and Investigations of Bead Geometries of GMAW-Based Wire–Arc Additive Manufacturing of 316L Stainless Steels
Authors: Chaudhari Rakesh , Parmar Heet , Vora Jay , Patel Vivek K.
Published: July 2022

Appropriate selection of wire–arc additive manufacturing (WAAM) variables imparts bead geometries with characteristics of multi-layer structures. Thus, the present study aimed to optimize the gas metal arc welding (GMAW)-based WAAM variables of travel speed (TS), wire feed speed (WFS), and voltage (V) for the bead geometries of bead width (BW) and bead height (BH) on an SS 316L substrate. Single-layer depositions were made through a metallic wire of SS 316L by following an experimental matrix of the Box–Behnken design (BBD) technique. Multivariable regression equations were generated for design variables and responses, and ANOVA was used to investigate the feasibility of the obtained regression equations. WFS was the highest contributor affecting the BW, followed by V and TS, while WFS was again the highest contributor affecting the BH, followed by TS and V. Heat transfer search (HTS) optimization was used to attain optimal combinations. The single-objective optimization result showed a maximum bead height and minimum bead width of 6.72 mm and 3.72 mm, respectively. A multi-layer structure was then fabricated by considering an optimization case study, and it showed optimized parameters at a WFS of 5.50 m/min, TS of 141 mm/min, and voltage of 19 V with the bead height and bead width of 5.01 mm and 7.81 mm, respectively. The multi-layered structure obtained at the optimized parameter was found to be free from disbonding, and seamless fusion was detected between the obtained layers of the structure. The authors believe that the present study will be beneficial for industrial applications for the fabrication of multi-layer structures.
Imputation of Missing Values for Multi-Biospecimen Metabolomics Studies: Bias and Effects on Statistical Validity
Authors: Wilson Machelle D. , Ponzini Matthew D. , Taylor Sandra L. , Kim Kyoungmi
Published: July 2022

The analysis of high-throughput metabolomics mass spectrometry data across multiple biological sample types (biospecimens) poses challenges due to missing data. During differential abundance analysis, dropping samples with missing values can lead to severe loss of data as well as biased results in group comparisons and effect size estimates. However, the imputation of missing data (the process of replacing missing data with estimated values such as a mean) may compromise the inherent intra-subject correlation of a metabolite across multiple biospecimens from the same subject, which in turn may compromise the efficacy of the statistical analysis of differential metabolites in biomarker discovery. We investigated imputation strategies when considering multiple biospecimens from the same subject. We compared a novel, but simple, approach that consists of combining the two biospecimen data matrices (rows and columns of subjects and metabolites) and imputes the two biospecimen data matrices together to an approach that imputes each biospecimen data matrix separately. We then compared the bias in the estimation of the intra-subject multi-specimen correlation and its effects on the validity of statistical significance tests between two approaches. The combined approach to multi-biospecimen studies has not been evaluated previously even though it is intuitive and easy to implement. We examine these two approaches for five imputation methods: random forest, k nearest neighbor, expectation-maximization with bootstrap, quantile regression, and half the minimum observed value. Combining the biospecimen data matrices for imputation did not greatly increase efficacy in conserving the correlation structure or improving accuracy in the statistical conclusions for most of the methods examined. Random forest tended to outperform the other methods in all performance metrics, except specificity.
High Sensitivity and Wide Range Biomimetic Tactile-Pressure Sensor Based on 2D Graphene Film and 3D Graphene Foam
Authors: Sha Baolin , Lü Xiaozhou , Jiang La
Published: July 2022

Bionic electronic skin is a system that simulates human skin and has multiple perceptions. For pressure sensors, high measurement accuracy and wide measurement range restrict each other, and it is difficult to achieve high measurement accuracy and wide measurement range simultaneously. Therefore, the research and application of bionic tactile-pressure sensors are limited due to the mutual constraints of measurement accuracy and range. In this work, a flexible graphene piezoresistive tactile sensor based on a biomimetic structure that utilizes the piezoresistive properties of graphene was reported. The novel tactile-pressure sensor consists of a 2D graphene film tactile sensor and a 3D graphene foam pressure sensor that could achieve high accuracy and a wide-range measurement simultaneously. The testing results show that the measurement range of this sensor was in two intervals of 0–2 N and 2–40 N. For the 0–2 N measurement range, the sensitivity was 472.2 Ω/kPa, the force resolution was 0.01 N, and the response time was less than 40 ms. For the 2–40 N measurement range, the sensitivity was 5.05 kΩ/kPa, the force resolution was 1 N, and the response time was less than 20 ms. The new sensor can realize high-precision and large-scale force measurements and shows great application value in the field of medical instruments and artificial limbs.
Editorial for the Special Issue on Heat and Mass Transfer in Micro/Nanosystems
Authors: Wang Ruijin , Zhang Junfeng
Published: July 2022

The miniaturization of components in mechanical and electronic equipment has been the driving force for the fast development of micro/nanosystems [...]
Cooperativity Model for Improving the Walking-Assistance Efficiency of the Exoskeleton
Authors: Ma Jianfeng , Sun Decheng , Ding Yongqing , Luo Daihe , Chen Xiao
Published: July 2022

(1) Background: To enhance the walking-assistance efficiencies of exoskeletons, this paper proposed the biomechanical-based cooperativity model based on a passive exoskeleton prototype to fill the technical gap in exoskeleton design regarding the torque transmission law between humans and exoskeletons. (2) Methods: The cooperativity model was used to solve the key system parameters based on the minimum average dispersion degree, in which the average dispersion degree algorithm based on the joint angle was designed and applied. (3) Results: The influence of the cooperativity model on the exoskeleton was indicated by comparing the walking-assistance efficiencies of the exoskeletons with the same structure but with different elastic parameters of the energy storage components, in which the exoskeleton based on the cooperativity design exhibited the highest walking-assistance performance. The walking-assistance efficiency of the exoskeleton with the optimal parameter combinations was also tested by comparing the respiratory metabolisms with and without the exoskeleton, in which the exoskeleton provided the average walking-assistance efficiency of 14.45% for more than 80% of the subjects. (4) Conclusions: The effects of the cooperativity model on exoskeletons were proven, but the accuracy and efficiency of the model still have room for improvement, especially the accuracy of the offset principle.
Femtosecond Laser Direct Writing of Optical Overpass
Authors: Ding Xiaochuan , Zhao Yao , Hassan Ali , Sun Yunlu , Hou Zhishan , Xue Wei , Cao Yu
Published: July 2022

With the rapid increase in information density, problems such as signal crosstalk and crossover restrict the further expansion of chip integration levels and packaging density. Based on this, a novel waveguide structure—photonic jumper wire—is proposed here to break through the technical restrictions in waveguide crossing and parallel line wrapping, which hinder the integration of photonic chips. Furthermore, we fabricated the optical overpass to realize a more complex on-chip optical cross-connection. Our method and structure promote a series of practical schemes for improving optical chip integration.