bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploration of a Flexible Metasurface for Strain Sensors: A Perspective from 2D Grating Fabrication to Spectral Characterization
Authors: Hu Hao , Bayanheshig
Published: October 2022

The flexible plasmonic metasurface is a novel optical device consisting of a large number of subwavelength-sized noble metal (gold, silver, etc.) structures arranged in a specific pattern on a flexible substrate. The usual method for a fabricating flexible metasurface is to build nanostructures on rigid substrates and then transfer them to flexible substrates. However, problems such as structural distortion and structural loss can occur during fabrication. To address these issues, this work improved the process to fabricate and characterize a flexible plasma 2D grating–a type of metasurface composed of gold cubelets with a thickness of 50 nm and a side length of 250 nm. First, an electron beam lithography method modified by proximity effect correction was used to fabricate nanostructures on a rigid substrate. Then, the structures were transferred by a chemical functionalization and a sacrificial layer etching method. In addition, the feasibility of using flexible plasmonic 2D gratings as strain sensors was investigated in this work through a stretching test. Experimental results show that electron beam lithography improved by correcting the proximity effect enabled the fabrication of more precisely shaped nanostructures; the chemical functionalization method significantly improved the transfer yield; and the spectroscopic analysis in the stretching test demonstrated the potential of the flexible plasmonic 2D gratings for sensing applications.
Crack Extension Analysis of Atmospheric Stress Corrosion Based on Peridynamics
Authors: Tan Can , Qian Songrong , Zhang Jian
Published: October 2022

Based on peridynamics, an atmospheric stress corrosion model was proposed. In this model, the role of hydrogen and stress in anodic-dissolution-dominated stress corrosion cracking was considered, and atmospheric corrosion was characterized by the change in liquid film thickness on the metal surface in the atmospheric environment. The near-field kinetic anodic dissolution model and the atmospheric corrosion model were coupled by varying the liquid film thickness. The thickness of the liquid film depended on factors such as the temperature, relative humidity, and hygroscopic salts. We validated the model using stress corrosion behavior from the literature for 304 stainless steel in a simulated atmospheric environment. The results of the model captured the crack expansion process. The obtained crack expansion direction and branching behavior agreed well with the experimental results in the literature.
In Silico Modeling and Quantification of Synergistic Effects of Multi-Combination Compounds: Case Study of the Attenuation of Joint Pain Using a Combination of Phytonutrients
Authors: Ayyadurai V. A. Shiva , Deonikar Prabhakar
Published: October 2022

The quantification of synergistic effects of multi-combination compounds is critical in developing “cocktails” that are efficacious. In this research, a method for in silico modeling and the quantification of synergistic effects of multi-combination compounds is applied for assessing a combination of phytonutrients for joint pain. Joint pain is the most prominent and disabling symptom of arthritis. Arthritic pain leads to a reduced quality of life. This research explores the efficacy of a synergistic combination of two plant-based flavonoids—apigenin and hesperidin—on joint pain. The study employs computational systems biology: (1) to identify biomolecular mechanisms of joint pain; (2) to identify the specific effects of apigenin and hesperidin, individually and in combination, on the mechanisms of joint pain; and (3) to predict the quantitative effects of apigenin and hesperidin, individually and in combination, on joint pain and whether these combination effects are synergistic or additive. Four molecular pathways that are affected by apigenin and hesperidin include the following: (1) arachidonic acid metabolism, (2) PGE2 signaling, (3) COX-2 synthesis, and (4) oxidative stress. The combination of apigenin and hesperidin significantly lowered PGE2 production, CGRP production, TRVP-1 synthesis, COX-2 production, and reactive oxygen species (ROS) production. Our results indicate that the apigenin and hesperidin combination synergistically affected four of the five modalities to attenuate joint pain.
Percutaneous Needle Electrolysis Accelerates Functional Muscle Regeneration in Mice
Authors: Valera-Garrido Fermín , Margalef Ramon , Bosque Marc , Minaya-Muñoz Francisco , Santafé Manel M.
Published: October 2022

Muscle regeneration after a traumatic injury can take an excessively long period of time. The purpose of this study is to assess whether the action of percutaneous needle electrolysis (PNE) accelerates muscle regeneration in cases of partial muscle injuries. The gastrocnemius muscle from adult Swiss male mice was inoculated with bupivacaine. The PNE protocol was applied 48 h after treatment with bupivacaine. Immunofluorescence techniques were performed 72 h after treatment with bupivacaine to evaluate the synaptic contacts. The end plate noise was recorded by electromyography after treatment with bupivacaine. Bupivacaine induced a local injury in muscles, axons were retracted, and the endplate noise decreased at 72 h, while the endplate noise increased in the injured limb where PNE had been applied. Seven days later, the functional values were the same as the controls and they were maintained for 10 days. The endplate noise was significantly greater on the limb treated with the electric current when compared to the limb receiving only bupivacaine, indicating that the use of galvanic current facilitated muscle regeneration at least from a functional point of view. The application of PNE during muscle regeneration in an animal model reduces the recovery time of the damaged muscle tissue.
Foreword to the Special Issue on Advances in Secure AI: Technology and Applications
Authors: Lee Sangkyun
Published: October 2022

I am pleased to introduce the Special Issue on “Advances in Secure AI: Technology and Applications” [...]
A Methodical Approach to Functional Exploratory Testing for Embedded Systems
Authors: Kimla Rafal , Czerwinski Robert
Published: October 2022

Functional exploratory testing is often considered a time- and resource-consuming activity, especially within embedded systems testing. The purpose of this paper is to present a case study of functional exploratory testing that demonstrates it to be a highly valuable technique and proves that applying the proposed methodical approach can overcome its disadvantages. This paper also provides a step-by-step framework that aids with the implementation of exploratory testing. The case study presents a low-voltage, near-motor variable frequency drive product. The results prove the effectiveness of the proposed approach.
Model Test of Micro-Pile Group Reinforcing High Steep Landslide
Authors: Yan Jinkai , Liu Xueling , Zhang Zhichao , Jin Kemo , Lu Xianzhui
Published: October 2022

High steep landslides are a major concern for infrastructure construction in the mountainous areas of Western China. The micro-pile technique has been gradually used to prevent landslides, due to convenient construction and good performance. However, the application of the micro-pile technique on landslide prevention was generally implemented on the front edge of landslides, which is not applicable for the high steep landslides due to the limited operation space. In this study, a large-scale model test on the performance of a micro steep pile group on the prevention of high steep landsides was conducted in order to implement the micro-pile on the top of landslides. The force-deformation characteristics and failure modes of the steel pipe micro-pile group reinforcing high steep landslides were investigated. The test results showed that the landslide thrusts acting on the micro-pile group showed a triangle distribution. The maximum soil earth pressure was observed near the slip surface during landsides. The resistance of the micro pole group was distributed in an inverted triangle, mainly in the upper half of the loaded section. The sliding bed resistance is unevenly distributed along the height direction, and is larger near the slip surface. Once the landslide occurred, the force distribution of each row of steel pipe micro-piles was basically the same. The bending moment of the loaded section of the steel pipe micro-pile was mostly negative, with a larger bending moment in the range of eight times the pile diameter above the slip surface. The largest bending moment value is located at two times the pile diameter on the slip surface. On the other hand, the bending moment of the embedded section of the steel pipe micro-pile is mostly positive, showing a tension state with a maximum value at four times the pile diameter under the slip surface. This implies that the role of loaded and embedded sections of the micro-pile group on the landsides is different. The failure mode of the micro-pile group was mainly attributable to the bending failure within eight times the pile diameter above and below the slip surface.
Dynamic Induction Heating Temperature Field Analysis of Spiral Bevel Gears
Authors: Zhang Yin , Zhang Hui , Yan Yixiong , Zhu Pengfei
Published: October 2022

Combining tooth surface induction heating and shot peening is an efficient method to improve tooth surface performance. Reasonable designs of the induction coil structure and parameters are essential for achieving uniform and efficient tooth surface heating. In this work, to precisely control the tooth surface temperature field and improve the heat uniformity across the tooth surface, a transverse coil (TC) and a longitudinal coil (LC) were designed, and the gear was set to rotate at a constant speed of 20 r/min, dividing the tooth surface is into a shot-peening area and heating area. Further, dynamic numerical simulations were performed using COMSOL Multiphysics in combination with the uniform rotation of gears to investigate the effect of the coil structure on the temperature field of the outer surface of gears. The results of the analyses combining the effects of different electrical parameters revealed that the gear surface temperature under LC heating was more uniformly distributed in the axial and circumferential directions, the tooth surface temperature fluctuations were smaller, the temperature difference between the root and top of the tooth was smaller, an coil heating was more efficient. Thus, the LC was deemed suitable for use as the spiral bevel gear induction heating coil. Finally, heating experiments were conducted using the LC to validate the simulation model. The results show that the use of LC heating can achieve the research goals of uniform temperature field distribution on the tooth surface and efficient temperature rise, providing the prerequisite for shot peening.
Factors Determining Ticagrelor-Induced Dyspnea in Patients with Acute Coronary Syndrome
Authors: Tamakauskas Vytenis , Žaliūnas Remigijus , Lesauskaitė Vaiva , Kupstytė-Krištaponė Nora , Šakalytė Gintarė , Jurgaitytė Julija , Čiapienė Ieva , Tatarūnas Vacis
Published: October 2022

(1) Background: The aim of this study was to determine clinical and genetic factors predicting the development of dyspnea in patients receiving ticagrelor. (2) Methods: A total of 277 patients with acute myocardial infarction (with and without ST-segment elevation), who underwent coronary angiography and PTCA with stent implantation and treated with antiplatelet drugs (ticagrelor and aspirin), were enrolled in this study. Platelet aggregation (induction with high-sensitivity ADP, ADP HS) testing was performed using a MULTIPLATE analyzer and reagents for the determination of P2Y12 receptor activity. Venous blood samples were collected for genotyping. (3) Results: Patients experiencing ticagrelor-related dyspnea had lower ADP HS. ROC curve analysis showed that an ADP HS cut-off of ≤19.5 U was associated with the development of dyspnea. The ADP HS value of ≤19.5 U and any dose of atorvastatin lower than 80 mg (or no atorvastatin) increased the risk of dyspnea by more than 4 and 2 times, respectively (OR = 4.07, p ≤ 0.001 and OR = 2.25; p = 0.008). (4) Conclusion: A lower ADP HS value possibly indicates greater ticagrelor activity and a higher plasma concentration of this drug. Atorvastatin might have an impact on the occurrence of ticagrelor-related dyspnea by affecting ticagrelor metabolism. No impact of any genetic variant on the development of dyspnea was determined.
Optimization of 99mTc-MAA SPECT/CT Imaging for 90Y Radioembolization Using a 3D-Printed Phantom
Authors: Ungania Sara , D’Arienzo Marco , Nocentini Sandro , D’Andrea Marco , Bruzzaniti Vicente , Marconi Raffaella , Mezzenga Emilio , Cassano Bartolomeo , Infusino Erminia , Guerrisi Antonino , Soriani Antonella , Strigari Lidia
Published: October 2022

Radioembolization (RE) with 90Y-microspheres has gained widespread acceptance as a safe and effective technique for treating liver malignancies. Accurate quantification in RE is a key step in treatment planning optimization and is becoming a pressing issue in light of the Directive 2013/59/EURATOM. The aim of this study was to develop a SPECT/CT imaging protocol for quantitative imaging optimization in RE based on cutting edge imaging technology (Symbia IntevoTM system provided with the innovative xSPECT software) and a novel anthropomorphic 3D-printed phantom. In the present study, 99mTc-labeled macroaggregated albumin was used as a surrogate radiopharmaceutical for treatment planning. Gamma camera calibration factors and recovery coefficients were determined performing preliminary SPECT/CT acquisitions of a point source, a cylindrical homogeneous phantom and the NEMA/IEC phantom. Data reconstruction was performed using the built-in xSPECT package, using both the Ordered Subset Expectation–Maximization (OSEM) and the Ordered Subset Conjugated Gradient (OSCG) algorithm. Specific regions of interest (ROIs) were drawn on the MIM 6.1.7 system according to the physical volume. The quantification procedure was validated using the anthropomorphic phantom provided with a fillable liver section and spheres of different diameters (20 mm, 40 mm and a 40 mm spherical shell). The measured activity concentration in all geometries is consistent within 4%, demonstrating that the xSPECT software permit an absolute quantification in anthropomorphic geometry largely within the 10% recommended from the manufacturer. Caution is advised in the presence of spherical objects with a necrotic core, as underestimations in the order of 20% were obtained.
Location of Multiple Types of Faults in Active Distribution Networks Considering Synchronization of Power Supply Area Data
Authors: Ren Gang , Zha Xianguang , Jiang Bing , Hu Xiaoli , Xu Junjun , Tao Kai
Published: October 2022

When a short circuit occurs in the power supply area of a distribution network with a high-permeability distributed generation, the line current will increase, the voltage will drop sharply, and the fault characteristics will be more complex. Therefore, the automatic, quick, and accurate location of fault sections is of great significance to the reliability of power supply. In order to prevent large-scale power outages in the power supply area caused by the failure of feeders and transformers, this paper proposes a novel method to locate fault sections in active distribution networks by taking into account the data of the power supply area. On the basis of the synchronization of calculated and measured time and the observability of the fault state, a limited number of intelligent terminals are reasonably arranged in the distribution network feeder and power supply area. Additionally, the fault location equation is established based on the three-phase voltage change values of the nodes before and after the fault collected by intelligent terminals, so that the fault section is determined by comparing the residuals. Finally, the proposed method is verified by the improved IEEE 37-node and IEEE 123-node three-phase distribution networks. The results show that it has high accuracy in locating fault sections in multiple fault scenarios.
Joint Optimization of Ticket Pricing and Allocation on High-Speed Railway Based on Dynamic Passenger Demand during Pre-Sale Period: A Case Study of Beijing–Shanghai HSR
Authors: Yin Xiaofeng , Liu Di , Rong Wenyu , Li Zheng
Published: October 2022

Against the background of the gradual deepening of China Railway’s market-oriented reform, and in order to improve the revenue and competitiveness for high-speed railway (HSR) passenger transport, this paper studies the joint optimization problem of the high-speed railway ticket pricing and allocation considering the dynamic demand characteristics of passengers during the pre-sale period. Firstly, we use the compound non-homogeneous Poisson process to describe the passengers’ ticket-purchasing process and use the sparse method to simulate the passengers’ ticket demand during the pre-sale period. Secondly, taking the ticket pricing and allocation as the decision variables and considering the full utilization of the train seat capacity, a stochastic nonlinear-programming mathematical model is established with the goal of maximizing the train revenue. A particle swarm algorithm is designed to solve the model. Finally, this study takes the G19 train running on the Beijing–Shanghai HSR in China as a case study to verify the effectiveness of the model and algorithm. The results show that the joint optimization scheme of ticket pricing and allocation considering dynamic demand yields a revenue of CNY 601,881, which increases the revenue by 1.01% with a small adjustment of the price compared with the fixed ticket price and pre-allocation scheme. This study provides scientific support for the decisions made by railway transportation enterprises, which is conducive to further increasing the potential ticket revenue and promoting sustainable development.
Active Learning Strategy for Surrogate-Based Quantile Estimation of Field Function
Authors: Brevault Loïc , Balesdent Mathieu , Valderrama-Zapata Jorge-Luis
Published: October 2022

Uncertainty quantification is widely used in engineering domains to provide confidence measures on complex systems. It often requires to accurately estimate extreme statistics on computationally intensive black-box models. In case of spatially or temporally distributed model outputs, one valuable metric results in the estimation of extreme quantile of the output stochastic field. In this paper, a novel active learning surrogate-based method is proposed to determine the quantile of an unidimensional output stochastic process with a confidence measure. This allows to control the error on the estimation of a extreme quantile measure of a stochastic process. The proposed approach combines dimension reduction techniques, Gaussian process and an adaptive refinement strategy to enrich the surrogate model and control the accuracy of the quantile estimation. The proposed methodology is applied on an analytical test case and a realistic aerospace problem for which the estimation of a flight envelop is of prime importance for launch safety reasons in the space industry.
A Novel Approach for Emotion Recognition Based on EEG Signal Using Deep Learning
Authors: Abdulrahman Awf , Baykara Muhammet , Alakus Talha Burak
Published: October 2022

Emotion can be defined as a voluntary or involuntary reaction to external factors. People express their emotions through actions, such as words, sounds, facial expressions, and body language. However, emotions expressed in such actions are sometimes manipulated by people and real feelings cannot be conveyed clearly. Therefore, understanding and analyzing emotions is essential. Recently, emotion analysis studies based on EEG signals appear to be in the foreground, due to the more reliable data collected. In this study, emotion analysis based on EEG signals was performed and a deep learning model was proposed. The study consists of four stages. In the first stage, EEG data were obtained from the GAMEEMO dataset. In the second stage, EEG signals were transformed with both VMD (variation mode decomposition) and EMD (empirical mode decomposition), and a total of 14 (nine from EMD, five from VMD) IMFs were obtained from each signal. In the third stage, statistical features were obtained from IMFs and maximum value, minimum value, and average values were used for this. In the last stage, both binary-class and multi-class classifications were made. The proposed deep learning model is compared with kNN (k nearest neighbor), SVM (support vector machines), and RF (random forest). At the end of the study, an accuracy of 70.89% in binary-class classification and 90.33% in multi-class classification was obtained with the proposed deep learning method.
Deep Learning for Predicting Traffic in V2X Networks
Authors: Abdellah Ali R. , Muthanna Ammar , Essai Mohamed H. , Koucheryavy Andrey
Published: October 2022

Artificial intelligence (AI) is capable of addressing the complexities and difficulties of fifth-generation (5G) mobile networks and beyond. In this paradigm, it is important to predict network metrics to meet future network requirements. Vehicle-to-everything (V2X) networks are promising wireless communication methods where traffic information exchange in an intelligent transportation system (ITS) still faces challenges, such as V2X communication congestion when many vehicles suddenly appear in an area. In this paper, a deep learning algorithm (DL) based on the unidirectional long short-term memory (LSTM) model is proposed to predict traffic in V2X networks. The prediction problems are studied in different cases depending on the number of packets sent per second. The prediction accuracy is measured in terms of root-mean-square error (RMSE), mean absolute percentage error (MAPE), and processing time.
An Advanced Travel Demand Synthesis Process for Creating a MATSim Activity Model: The Case of Ústí nad Labem
Authors: Pereira André Maia , Dingil Ali Enes , Přibyl Ondřej , Myška Vojtěch , Vorel Jakub , Kříž Milan
Published: October 2022

In this study, an activity-based travel demand model of the Ústí nad Labem district (Czech Republic) is created. To do this, an advanced travel demand synthesis process is presented by utilizing the Eqasim framework, which is a pipeline-processing, initial raw data to simulation step. The framework is extensively modified and extended with several algorithms in order to utilize multiple data points for increasing realism in mobility for travel demand models. Two major extensions are provided. First, the pipeline framework is improved to estimate inbound and outbound trips of the study area, comprising a main city and 23 surrounding municipalities. The extended framework assigns synthetic gates for the study area as hubs for the inclusion of inbound and outbound trips. Second, the pipeline framework is advanced to provide a more compatible match of travel destination and activity location state. To do this, the extended framework assigns a capacity for each facility identified for the study area, the expected number of visitors to each facility, and the number of residents in each building. The resulting demand model is presented and the generated trips are evaluated based on locational, transport mode, and sociodemographic characteristics with origin–destination (OD) bundling. Additionally, distribution analyses of the present model are conducted to understand the matching results on a detailed level. The results demonstrate that the present model provides a reasonable output for transport researchers when testing different mobility scenarios and the provided extensions helps them to reduce implausible reflections of the distribution of travel and activity characteristics in household travel surveys while creating demand models, thus increasing realism. Lastly, open-source playground and code repository for further future improvement of synthetic travel synthesis methods are created, which enhances a deep understanding of the preparatory and methodological backgrounds required for complex activity-based simulations in order to inspire transport planners.
The Use of Magnetic Susceptibility as a Technique to Measure the Impact of Wildfires on Archaeological Heritage
Authors: Sanchez-Roda Alejandra , Oliva-Urcia Belén , Gomez-Heras Miguel
Published: October 2022

Wildfires are one of the main threats of natural areas and often fires can affect protected or heritage areas and properties, in which the preservation requirements demand the use of non-destructive techniques (NDTs). The magnetic susceptibility is an NDT that provides information on the mineralogical composition of the materials but has never been applied to the evaluation of fires. Here, we combine laboratory with field analysis to test the applicability of the magnetic susceptibility for the assessment of the impacts of wildfires. The laboratory results showed an increase in the magnetic susceptibility with the temperature, more evident in the samples heated to 600 °C and above. The in situ measures revealed a spatial variation in the magnetic susceptibility, which was related to the behaviour of the fire in the area. The samples were later analysed with other magnetic destructive techniques that were used to confirm the mineralogical processes that occurred in the materials. The increase in the susceptibility values were due to the formation of iron oxides. The destructive analysis also showed the presence of minerals such as hematite and magnetite in the samples. Overall, the study allowed a first approach to test the magnetic susceptibility as a simple and fast way to measure the impacts of wildfires.
Role and Properties of Proteins and Peptides in Foods
Authors: Iwaniak Anna , Minkiewicz Piotr
Published: October 2022

For many years, proteins and peptides have been attracting scientists’ attention as two of the most important classes of food components [...]
Influence of the Analytical Segment Length on the Tram Track Quality Assessment
Authors: Majstorović Igor , Ahac Maja , Madejski Janusz , Lakušić Stjepan
Published: October 2022

In the track quality analysis, numerical values representing the relative condition of track geometry called track quality indices (TQIs) are calculated along a specific track segment. Segments are defined as linear track geometry datasets with the homogeneous characteristics of factors affecting geometry degradation. The 200m-long analytical segment is used most often on inter-city conventional and high-speed rail networks. However, in the case of the small urban rail networks, the homogeneity of track-geometry degradation influential factors is very low. This segment length is usually too long for efficient track maintenance or reconstruction with minimal disruption of the urban traffic. This paper explores the effect of reducing the analytical segment length in the condition assessment of the tram network in the City of Osijek, Croatia. The research had two main objectives: (1) to assess the narrow-gauge tram-track geometry quality through the application of the established synthesized TQIs, and (2) to analyze how a change in the analytical segment length affects this assessment. Two synthesized track quality indices—one based on a weighted value and the other on a standard deviation of measured track geometry parameters—were calculated for the 27.5 km of tracks on consecutive 200-, 100-, 50-, and 25 m long analytical segments. The comparative analysis of the TQIs’ calculation results showed that the reduction in the segment length increased the resolution of the track quality analysis in both cases, while the index based on a weighted value of geometry deviations proved less sensitive to this reduction. These results contribute to further segmentation process establishment and TQIs implementation on tram infrastructure.
Field Measurements of Free Ascending Behavior of Occupants along Medium-Long Stairway
Authors: Li Junmei , Qi Zhao , Li Yanfeng , Chow Wan-Ki , Xie Fei , Dong Qiwei
Published: October 2022

The human behavior of walking upstairs was studied by field measurement in a 10-storey building, which simulates the greatest depth of most underground facilities. The effects of age, gender, walking distance, and fatigue on individual free ascending speed on stairs were investigated. The experimental results showed that walking distance and fatigue due to the long-distance upward walking have great impact on the upward walking and ascent speed. When climbing over 8 floors (vertical height about 30 m), the mean ascent speeds were 0.97 m/s and 0.78 m/s for young males and females, and 0.91 m/s and 0.68 m/s for middle-aged males and females, respectively. The mean ascending speed that is used to predict the evacuation time should be combined with the traveling distance or floor levels. Ascent speed models for males and females walking along a medium-long stairway were developed to describe the fatigue effect on ascending speed based on the vertical heights travelled.
Employing Discrete Solid Phases to Represent C-S-H Solid Solutions in the Cemdata07 Thermodynamic Database to Model Cement Hydration Using the PHREEQC Geochemical Software
Authors: Holmes Niall , Tyrer Mark , Kelliher Denis
Published: October 2022

This paper presents a cement hydration model over time using the cemdata07 thermodynamic database and a series of derived discrete solid phases (DSPs) to represent calcium silicate hydrate (C-S-H) as a binary solid solution with two end-members. C-S-H in cement is amorphous and poorly crystalline with a range of molar Ca/Si ratios from 0.6 to 1.7. It displays strongly incongruent dissolution behaviour, where the release of calcium into solution is several orders of magnitude greater than silicon. It is, therefore, important that any cement hydration model provides a credible account of this behaviour. C-S-H has been described in the cemdata07 thermodynamic database as a number of solid solutions using different end-members with differing levels of complexity. While solid solutions can be included in most modern geochemical software programs, they often lead to a significant increase in computation time. This paper presents how an incongruent solid solution between two C-S-H end-members may be represented as a number of DSPs to model cement hydration over time using the PHREEQC geochemical software. By using DSPs rather than modelling C-S-H as a nonideal solid solution, this gives the user full control of the input for the model, reducing the computational demand and analysis time with no loss in accuracy in predicting stable-phase assemblages and their associated pore chemistry over time.
Study on the Mechanical Strength of Calcium Oxide-Calcium Phosphate Cured Heavy Metal Zinc Contaminated Red Clay Soil
Authors: Song Yu , Ding Song , Geng Yukun , Dong Shuaishuai , Chen Hongbin
Published: October 2022

With the continuous improvement of the construction of the ecological economic system in the new era, the problem of heavy metal pollution has become an important issue in urban construction. In this paper, Zn2+ contaminated red clay is used as the research object, and calcium superphosphate and calcium oxide are used as curing agents to conduct the simultaneous test of unconfined compressive strength-resistivity. The mechanical properties and resistivity of the contaminated soil under different test conditions were analyzed to investigate their effects on the cured red clay. The results showed that different contamination concentrations showed different weakening effects on the unconfined compressive strength of red clay soils, and the unconfined compressive strength of cured soils increased significantly. The age of maintenance affects the unconfined compressive strength of cured soil, and the growth of unconfined compressive strength is most obvious in the age of 0–7 day. After that, it tends to be stable with the growth of age. The deformation modulus of contaminated soil before and after curing was reduced to different degrees. Before and after curing, the resistivity of contaminated soil decreased with the increase of ion concentration, and the resistivity of cured soil increased with the increase of curing agent incorporation rate under the same contamination concentration. The research results can enrich the soil treatment problem of heavy metal contaminated sites and provide theoretical support for the application of this type of curing agent in the field engineering of Zn2+ contaminated red clay soil.
Exploring the Green Design of Hakka Cultural Creative Textiles for Sustainable Development
Authors: Wang Wen-Cheng , Jou Chi-Hsiung , Kao Jung-Mei , Wu Wan-Cheng , Ko Ya-Hsien
Published: October 2022

This study explored Hakka cultural creative textiles using the green design concept, the cultural creative product design model and Hamilton’s three-component unifying metatheory based on ideology, social structure and technology to analyse the effect of blue dye colour, floral pattern size and pattern type on the preference for natural indigo dyed and stonewashed Tung blossom denim. Two hundred and twenty-nine subjects aged 18–24 years (M = 19.5, SD = 1.25) participated in this study. The results demonstrate that the main effect of blue colouring was significant and that Hanaasagi and Ai-iro were the most preferred colours. The main effect of floral pattern size was significant, and the subjects exhibited the strongest preference for the large size and the weakest preference for the extra-small size. The main effect of pattern type was also significant, and the subjects’ preference for the two-dimensional repetitive pattern was always stronger than that for the one-dimensional repetitive pattern. These results show that green design may be combined with cleaner production, such as using natural indigo as a raw material for sustainable development, to create new luxury fashions of cultural creative textiles for consumption.
Effect of High Hydrostatic Pressure Processing on Starch Properties of Cassava Flour
Authors: Conde Ladie Anne , Kebede Biniam , Leong Sze Ying , Oey Indrawati
Published: October 2022

The aim of this study was to utilize high-pressure processing (HPP) to modify cassava flour through altering the starch components. Specifically, the effect of HPP processing variables, i.e., pressure (0.10 or untreated, 300, 400, 500, and 600 MPa), flour concentration (FC; 10, 20, and 30%), and holding time (HT; 10 and 30 min) on starch-related properties was studied. Microstructural integrity, thermal properties, and starch susceptibility to digestive enzymes were determined. A three-way ANOVA was performed to identify the interaction effect between these process variables. In general, 600 MPa consistently transformed the crystalline starch into an amorphous one. HPP-induced gelatinization led to enlarged starches with loss of birefringence, reduced relative crystallinity percentage, and changes in short-range order. The three-way interaction between the process variables was evident in the significant progressive rise in onset gelatinization temperature and degree of gelatinization, and the decline in gelatinization enthalpy from 500 to 600 MPa with decreasing FC and increasing HT. These changes caused an increased percentage of rapidly digestible starch and decreased resistant starch fraction. Overall, this study’s results imply the possibility of using HPP to modify the starch component in cassava flour and potentially create flours with varying levels of functionalities.
Relationship between Hip Abductor Muscle Strength and Frontal Plane Kinematics: A Cross-Sectional Study in Elite Handball Athletes
Authors: Ceballos-Laita Luis , Carrasco-Uribarren Andoni , Cabanillas-Barea Sara , Pérez-Guillén Silvia , Medrano-de-la-Fuente Ricardo , Hernando-Garijo Ignacio , Jiménez-del-Barrio Sandra
Published: October 2022

Frontal plane kinematics of the lower limb could be especially relevant in the risk of injuries in handball (HB) athletes. An association between lower limb frontal plane kinematics and hip abductor muscles strength has been investigated in different populations. However, the relationship between pelvis, hip, and knee frontal plane kinematics and the hip abductor strength in HB athletes has not been considered. Therefore, the objective of this study was to evaluate the relationship between hip abductor muscles strength and frontal plane kinematics (contralateral pelvic drop, femoral adduction, and knee valgus) in elite HB athletes using 2D analysis. Design: Cross-sectional and correlational study. Methods: Thirty-four male professional HB athletes were recruited. Athletes had to perform a deep single-leg squat. The frontal plane was recorded using the Camera app on iPhone (5SE). The clinical variables were hip abductor muscles strength assessed using a Lafayette hand-held dynamometer version 01165, and frontal plane kinematics measured with Kinovea 2D software version 0.9.4. Both variables were measured independently by two different examiners. Results: The correlation analysis showed a statistically significant negative correlation between the hip abductor muscles strength and the pelvic drop angle (p < 0.001; PCC: −0.873). A statistically significant positive correlation was found between the hip abductor muscles strength and the femoral adduction angle (p < 0.001; PCC: 0.767) and between the hip abductor muscles strength and the knee valgus angle (p < 0.001; PCC: 0.855). Conclusion: Hip abductor muscles strongly correlate with frontal plane kinematics in HB athletes.
Einstein Aggregation Operators under Bipolar Neutrosophic Environment with Applications in Multi-Criteria Decision-Making
Authors: Jamil Muhammad , Afzal Farkhanda , Akgül Ali , Abdullah Saleem , Maqbool Ayesha , Razzaque Abdul , Riaz Muhammad Bilal , Awrejcewicz Jan
Published: October 2022

In this article, we introduce bipolar neutrosophic (BN) aggregation operators (AOs) as a revolutionary notion in aggregation operators (AOs) by applying Einstein operations to bipolar neutrosophic aggregation operators (AOs), with its application related to a real-life problem. The neutrosophic set is able to drawout the incomplete, inconsistent and indeterminate information pretty efficiently. Initially, we present essential definitions along with operations correlated to the neutrosophic set (NS) and its generalization, the bipolar neutrosophic set (BNS). The Einstein aggregation operators are our primary targets, such asthe BN Einstein weighted average (BNEWA), BN Einstein ordered weighted average (BNEOWA), BN Einstein hybrid average (BNEHA), BN Einstein weighted geometric (BNEWG), BN Einstein ordered weighted geometric (BNEOWG) and BN Einstein hybrid geometric (BNEHG), as well as their required properties. The most important benefit of using the suggested approaches is that they provide decision-makers with complete sight of the issue. These techniques, when compared to other methods, provide complete, progressive and precise findings. Lastly, by means of diverse types of newly introduced aggregation operators and a numerical illustration by an example, we suggest an innovative method to be used for multi-criteria community decision-making (DM). This illustrates the utility and applicability of this new strategy when facing real-world problems.
Comprehensive Numerical Analysis of a Porous Piezoelectric Ceramic for Axial Load Energy Harvesting
Authors: Haldkar Rakesh Kumar , Cherpakov Alexander V. , Parinov Ivan A. , Yakovlev Vladislav E.
Published: October 2022

In this paper, an axial-type piezoelectric energy generator with various porosities of piezoelectric ceramics is designed and analysed. A 3D finite element model is developed by using ANSYS software. The porosity of piezoelectric ceramic is varied from 0 to 80% through thickness or along the length of the duralumin beam. The axial type energy harvester consists of bimorph (d31) and cylinder (d33) piezoelectric patches with base excitation. The effects of various porosities, proof mass locations, and different applied acceleration are used to determine the output voltage and power generation. The maximum output voltage and power are obtained equal to 2.25 V and 5.1 µW, respectively.
Laser-Ultrasound-Based Grain Size Gauge for the Hot Strip Mill
Authors: Malmström Mikael , Jansson Anton , Hutchinson Bevis , Lönnqvist Johan , Gillgren Lars , Bäcke Linda , Sollander Hans , Bärwald Matthias , Hochhard Sascha , Lundin Peter
Published: October 2022

The paper summarizes the creation of a robust online grain size gauge for a hot strip mill. A method and algorithm for calculating the grain size from the measured ultrasonic attenuation is presented. This new method is self-calibrating, does not rely on a geometrical reference sample and can cope with the effects of diffraction on the attenuation. The model is based on 52 quenched samples measured with more than 23,000 laser ultrasonics shots and has a correlation coefficient R2 of 0.8. Typical online laser ultrasonic measurements from the hot strip mill and the calculated grain size versus length are presented for a couple of steel strips.
Extending Partial Domain Adaptation Algorithms to the Open-Set Setting
Authors: Pikramenos George , Spyrou Evaggelos , Perantonis Stavros J.
Published: October 2022

Partial domain adaptation (PDA) is a framework for mitigating the covariate shift problem when target labels are contained in source labels. For this task, adversarial neural network (ANN) methods proposed in the literature have been proven to be flexible and effective. In this work, we adapt such methods to tackle the more general problem of open-set domain adaptation (OSDA), which further allows the existence of target instances with labels outside the source labels. The aim in OSDA is to mitigate the covariate shift problem and to identify target instances with labels outside the source label space. We show that the effectiveness of ANN methods utilized in the PDA setting is hindered by outlier target instances, and we propose an adaptation for effective OSDA.
Decoding the Impact of Genetic Variants in Gastric Cancer Patients Based on High-Dimensional Copy Number Variation Data Using Next-Generation Knowledge Discovery Methods
Authors: Bibi Fehmida , Pushparaj Peter Natesan , Naseer Muhammad Imran , Yasir Muhammad , Azhar Esam Ibraheem
Published: October 2022

Objectives: Despite a reduction in the incidence and mortality rates of gastric cancer (GC), it remains the fifth most frequently diagnosed malignancy globally. A better understanding of the regulatory mechanisms involved in the progression and development of GC is important for developing novel targeted approaches for treatment. We aimed to identify a set of differentially regulated pathways and cellular, molecular, and physiological system development and functions in GC patients infected with H. pylori infection based on copy number variation (CNV) data using next-generation knowledge discovery (NGKD) methods. Methods: In this study, we used our previous CNV data derived from tissue samples from GC patients (n = 33) and normal gastric samples (n = 15) by the comparative genome hybridization (CGH) method using Illumina HumanOmni1-Quad v.1.0 BeadChip (Zenodo Accession No: 1346283). The variant effects analysis of genetic gain or loss of function in GC was conducted using Ingenuity Pathway Analysis (IPA) software. In addition, in silico validation was performed with iPathwayGuide software using high-throughput RNA sequencing (RNAseq) data (GSE83088) from GC patients. Results: We observed 213 unique CNVs in the control group, 420 unique CNVs in the GC group, and 225 common variants. We found that cancer, gastrointestinal diseases, and organismal injury and abnormalities were the three diseases or disorders that were most affected in the GC group. We also identified that the programmed cell death ligand 1 (PD-L1) cancer immunotherapy pathway, T-cell apoptosis, T-cell exhaustion, and Type 1 regulatory T-cell (Tr1 cells) specialization were dysregulated in GC patients. RNAseq data from GC patients showed that the PD-1/PD-L1 pathway was significantly upregulated in GC samples compared with controls. Conclusions: In conclusion, in the present study, we decoded differentially impacted GC-specific diseases and biological functions and pathways based on CNV data using NGKD methods that can be adopted to design personalized therapeutic approaches for patients with GC in a typical clinical milieu.
Accuracy of the Fluorescence-Aided Identification Technique (FIT) for Detecting Residual Composite Remnants after Trauma Splint Removal—A Laboratory Study
Authors: Magni Eva , Leontiev Wadim , Soliman Sebastian , Dettwiler Christian , Klein Christian , Krastl Gabriel , Weiger Roland , Connert Thomas
Published: October 2022

Distinguishing composite remnants from tooth structure after trauma splint removal can be challenging. This study aimed to compare the Fluorescence-aided Identification Technique (FIT) with conventional light illumination (CONV) in terms of accuracy and time required for the detection of composite remnants after trauma splint removal. Ten bovine tooth models containing anterior teeth from 12 to 22 with composite remnants after trauma splint removal were used. These models were examined by 10 students and 10 general dentists. Each examiner assessed the 10 models using CONV or FIT three times with an interval of 2 weeks each using a prototype fluorescence-inducing headlamp with a spectral bandwidth of (405 ± 7) nm for FIT and a dental unit lamp for CONV. The examiners charted the location of identified composite remnants, and the procedure time needed for each method was recorded. Statistical analysis was performed with R 3.2.2 software with a significance level of α = 5%. FIT was more accurate and less time-consuming than CONV (p < 0.001). There were no significant differences between dentists and students concerning accuracy (CONV: p = 0.26; FIT: p = 0.73). Students performed FIT significantly faster than the dentists (p < 0.001). FIT is a quick and reliable method of identifying composite remnants after trauma splint removal.
Natural Blending as a Novel Technology for the Production Process of Aged Wine Spirits: Potential Impact on Their Quality
Authors: Lourenço Sílvia , Anjos Ofélia , Caldeira Ilda , Alves Sheila Oliveira , Santos Nádia , Canas Sara
Published: October 2022

The blending of wine spirits (WSs) produced in different ageing conditions is a key operation to impart specific features, enhance complexity, increase the final product’s quality and ensure brand consistency over the years, but requires time, labour and experienced blenders. This work aimed to develop a novel technology, natural blending, towards innovation and a more sustainable production process, adding value to the final product. WSs were aged in 250 L barrels and in 1000 L stainless steel tanks with wood staves and micro-oxygenation (MOX), using Limousin oak and chestnut wood simultaneously at a 50:50 ratio (natural blending) and separately; after 18 months of ageing, the last ones underwent the blending operation at the same ratio. All WSs were bottled and thereafter the following traits were analysed: alcoholic strength, acidity, dry extract, total phenolic index, low molecular weight compounds by HPLC method, chromatic characteristics and sensory profile. No significant differences in the physicochemical characteristics and sensory profile between the WSs resulting from the two blending technologies were found. Natural blending did not induce changes in the characteristics imparted by each ageing technology. These findings point to natural blending as a reliable alternative to the blending operation, especially in combination with ageing in tanks with staves and MOX.