bluuebunny/crossref_metadata_2025 huggingface dataset:
Carcass and Pork Quality and Gut Environment of Pigs Fed a Diet Supplemented with the Bokashi Probiotic
Authors: Rybarczyk Artur , Bogusławska-Wąs Elżbieta , Pilarczyk Bogumiła
Published: December 2021

The aim of this study was to determine the effect of probiotics on gut microbiota, on carcass and meat quality and on mineral contents in the longissimus lumborum (LL) muscle in pigs. The research was carried out with 120 hybrid pigs deriving from Naïma sows and P-76 boars. Pigs from the experimental group received the EM®Bokashi probiotic (Greendland Technologia EM®, Janowiec n/Wisłą, Poland) in their feed (containing Saccharomyces cerevisiae, Lactobacillus casei and Lactobacillus plantarum). The study showed that EM®Bokashi probiotic supplementation resulted in a significantly higher count of lactic acid bacteria (LAB) and yeasts in the feed, a lower number of Clostridium in the mucosa and colorectal digesta as well as a lower Enterobacteriaceae count in the colorectal digesta. The research showed that carcasses of the pigs who received the EM®Bokashi probiotic had a higher lean percentage and lower fat content than the carcasses of the control fatteners. Diet supplementation with the EM®Bokashi probiotic resulted in a lower pH and technological yield (TY) and a higher drip loss and shear force at a lower protein content in LL muscle. Moreover, the administration of the probiotic to fatteners resulted in higher yellowness (b*) and saturation (C*) and higher concentrations of Na, Mg and Se in meat.
Do Live Weight, Body Condition Score, Back Muscle or Back-Fat Reserves Create the Suspicion of Goats Infected with Eimeria or Trichostrongylids?
Authors: Ptáček Martin , Kyriánová Iveta Angela , Nápravníková Jana , Ducháček Jaromír , Husák Tomáš , Chay-Canul Alfonso J. , Zaragoza-Vera Claudia , Cruz-Bacab Luis , Vadlejch Jaroslav
Published: December 2021

Thirty goats of the breeds Czech Brown Shorthaired and Czech White Shorthaired and their crosses were randomly selected from a flock at a farm in the Czech Republic. All animals were monitored for one year at monthly intervals for their nutritional status (live weight, LW; body-condition score, BCS; depth of musculus longissimus thoracis et lumborum, MLTL; back-fat thickness, BT) and infection intensity with Eimeria sp. (EIM) and strongylid nematodes (STR). Regression–correlation analysis showed a possible interrelation of BCS with EIM infection. Analysis of muscle and fat reserves indicated that BT was better than MLTL in identifying EIM infection. Goat nutritional status was not significantly correlated with STR infection. A linear tendency (p = 0.092), however, was detected for the response of MLTL to STR infection. Results of this study indicated theoretical use of BCS for Eimeria identification and suggested some perspective of BCS for targeting animals infected by strongylid nematode. Validity of our results, however, was limited by number of observed animals managed under specific breeding conditions.
Bottlenose Dolphin (Tursiops truncatus) Whistle Modulation during a Trawl Bycatch Event in the Adriatic Sea
Authors: Corrias Valentina , de Vincenzi Giovanni , Ceraulo Maria , Sciacca Virginia , Sala Antonello , de Lucia Giuseppe Andrea , Filiciotto Francesco
Published: December 2021

Marine mammal vocal elements have been investigated for decades to assess whether they correlate with stress levels or stress indicators. Due to their acoustic plasticity, the interpretation of dolphins’ acoustic signals of has been studied most extensively. This work describes the acoustic parameters detected in whistle spectral contours, collected using passive acoustic monitoring (PAM), in a bycatch event that involved three Bottlenose dolphins during midwater commercial trawling. The results indicate a total number of 23 upsweep whistles recorded during the bycatch event, that were analyzed based on the acoustic parameters as follows: (Median; 25th percentile; 75th percentile) Dr (second), total duration (1.09; 0.88; 1.24); fmin (HZ), minimum frequency (5836.4; 5635.3; 5967.1); fmax (HZ), maximum frequency, (11,610 ± 11,293; 11,810); fc (HZ), central frequency; (8665.2; 8492.9; 8982.8); BW (HZ), bandwidth (5836.4; 5635.3; 5967.1); Step, number of step (5; 4; 6). Furthermore, our data show that vocal production during the capture event was characterized by an undescribed to date combination of two signals, an ascending whistle (upsweep), and a pulsed signal that we called “low-frequency signal” in the frequency band between 4.5 and 7 kHz. This capture event reveals a novel aspect of T. truncatus acoustic communication, it confirms their acoustic plasticity, and suggests that states of discomfort are conveyed through their acoustic repertoire.
Respiratory Disease Risk of Zoo-Housed Bonobos Is Associated with Sex and Betweenness Centrality in the Proximity Network
Authors: Torfs Jonas R. R. , Eens Marcel , Laméris Daan W. , Staes Nicky
Published: December 2021

Infectious diseases can be considered a threat to animal welfare and are commonly spread through both direct and indirect social interactions with conspecifics. This is especially true for species with complex social lives, like primates. While several studies have investigated the impact of sociality on disease risk in primates, only a handful have focused on respiratory disease, despite it being a major cause of morbidity and mortality in both wild and captive populations and thus an important threat to primate welfare. Therefore, we examined the role of social-network position on the occurrence of respiratory disease symptoms during one winter season in a relatively large group of 20 zoo-housed bonobos with managed fission-fusion dynamics. We found that within the proximity network, symptoms were more likely to occur in individuals with higher betweenness centrality, which are individuals that form bridges between different parts of the network. Symptoms were also more likely to occur in males than in females, independent of their social-network position. Taken together, these results highlight a combined role of close proximity and sex in increased risk of attracting respiratory disease, two factors that can be taken into account for further welfare management of the species.
Prediction and Experimental Verification of a Hierarchical Transcription Factor Regulatory Network of Porcine Myoglobin (Mb)
Authors: Yuan Di , Yu Hao , Liu Songcai , Hao Linlin , Zhang Jing
Published: December 2021

Myoglobin is a key chemical component that determines meat’s color and affects consumers’ purchase intentions. In this work, we firstly identified the promoter sequence of the Mb gene from the primary assembly of high-throughput genome sequencing in pigs, and predicted its potential transcription factors by LASAGNA. Through the data mining of the mRNA expression profile of longissimus dorsi muscle of different pig breeds, we constructed a hierarchical interplay network of Mb-TFs (Myoglobin-Transcription Factors), consisting of 16 adaptive transcription factors and 23 secondary transcription factors. The verification of gene expression in longissimus dorsi muscle showed that the Mb mRNA and encoded protein were significantly (p < 0.05) more abundant in Bama pigs than Yorkshire pigs. The qRT-PCR (Real-Time Quantitative Reverse Transcription PCR) validation on genes of the Mb-TFs network showed that FOS, STAT3, STAT1, NEFL21, NFE2L2 and MAFB were significant positive regulatory core transcription factors of Mb-TFs network in Bama pigs, whereas ATF3 was the secondary transcription factor most responsible for the activation of the above transcription factors. Our study provides a new strategy to unravel the mechanism of pork color formation, based on public transcriptome and genome data analysis.
Neonatal Proteinuria in Calves—A Quantitative Approach
Authors: Skrzypczak Wiesław , Dratwa-Chałupnik Alicja , Ożgo Małgorzata , Boniecka Karolina
Published: December 2021

Urine testing is a convenient, non-invasive method of obtaining information about body functions. Depending on the intended purpose, urine testing may be qualitative and/or quantitative. Urine analysis can also include proteins. There are no data in the literature on the occurrence of proteinuria in healthy neonatal calves. The present study was the first that aimed to quantify the hypothesis of proteinuria occurrence in these animals in the first week of life, to assess its intensity and dynamics and to understand the underlying causes of proteinuria in healthy calves. The research was carried out on 15 healthy calves in the first seven days of life. Calves were catheterized to determine minute diuresis. Total protein concentration was determined in blood plasma and urine. Urine proteins were separated by electrophoresis (SDSPAGE) and their concentration and percentage were determined by densitometry using an image archiving and analysis software. The separated proteins were divided into three groups according to molecular weight for albumin, LMW and HMW proteins. The results were standardized per 1 m2 of body surface area and statistically analyzed. Neonatal proteinuria was demonstrated in healthy calves, mainly resulting from the high concentration of LMW proteins in the urine. Their percentages decreased significantly from 84.46% on the first day of calves’ life to 64.02% on day 7. At the same time, a statistically significant increase was observed in the proportion of albumin and high molecular weight proteins in urine total protein. Albumin percentage increased from 9.54% (on day 1) to almost 20% (on day 7), while the proportion of HMW proteins increased from 6.68% to 18.13%, respectively. The concentration of total protein in the urine of newborn calves amounted to 14.64 g/L and decreased statistically significantly during the first 72 h of postnatal life, stabilizing at the level of 3–4 g/L. The mean value of total protein excretion in the first week of life was 4.81 mg/min/m2 (i.e., 6.93 g/24 h/m2). The analysis of protein concentration in the urine and its excretion, as well as changes in urinary excretion of the tested protein fractions, indicated that neonatal proteinuria in healthy neonatal calves was tubular (i.e., main reason is the reduced absorption of proteins in nephrons). In addition, research showed that there was a rapid improvement in resorptive mechanisms in tubular cells. It should be assumed that the filtration barrier in the kidneys of these animals after birth is morphologically prepared to retain high molecular weight proteins. It seems that the increased permeability of the filtration barrier in the glomeruli does not necessarily indicate the immaturity of the kidneys, but may indicate the kidneys’ adaptation to excess protein removal from the body during feeding with high-protein food (colostrum), with an open intestinal barrier enabling protein absorption from the gastrointestinal tract to the blood.
Antibacterial, Antibiofilm and Anti-Virulence Activity of Biactive Fractions from Mucus Secretion of Giant African Snail Achatina fulica against Staphylococcus aureus Strains
Authors: Suárez Libardo , Pereira Andrés , Hidalgo William , Uribe Nelson
Published: December 2021

Staphylococcus aureus is an important etiological agent that causes skin infections, and has the propensity to form biofilms, leading to significant mortality and morbidity in patients with wounds. Mucus secretion from the Giant African snail Achatina fulica is a potential source of biologically active substances that might be an important source for new drugs to treat resistant and biofilm-forming bacteria such as S. aureus. This study evaluated the effect of semi-purified fractions from the mucus secretion of A. fulica on the growth, biofilm formation and virulence factors of S. aureus. Two fractions: FMA30 (Mw >30 kDa) and FME30 (Mw 30−10 kDa) exhibited antimicrobial activity against S. aureus with a MIC50 of 25 and 125 µg/mL, respectively. An inhibition of biofilm formation higher than 80% was observed at 9 µg/mL with FMA30 and 120 µg/mL with FME30. Furthermore, inhibition of hemolytic and protease activity was determined using a concentration of MIC20, and FME30 showed a strong inhibitory effect in the formation of clots. We report for the first time the effect of semi-purified fractions of mucus secretion of A. fulica on biofilm formation and activity of virulence factors such as α-hemolysin, coagulase and proteases produced by S. aureus strains.
Wild Animals Are Reservoirs and Sentinels of Staphylococcus aureus and MRSA Clones: A Problem with “One Health” Concern
Authors: Abdullahi Idris Nasir , Fernández-Fernández Rosa , Juárez-Fernández Guillermo , Martínez-Álvarez Sandra , Eguizábal Paula , Zarazaga Myriam , Lozano Carmen , Torres Carmen
Published: December 2021

Background: The availability of comprehensive data on the ecology and molecular epidemiology of Staphylococcus aureus/MRSA in wild animals is necessary to understand their relevance in the “One Health” domain. Objective: In this study, we determined the pooled prevalence of nasal, tracheal and/or oral (NTO) Staphylococcus aureus (S. aureus) and methicillin-resistant S. aureus (MRSA) carriage in wild animals, with a special focus on mecA and mecC genes as well as the frequency of MRSA and methicillin susceptible S. aureus (MSSA) of the lineages CC398 and CC130 in wild animals. Methodology: This systematic review was executed on cross-sectional studies that reported S. aureus and MRSA in the NTO cavities of wild animals distributed in four groups: non-human primates (NHP), wild mammals (WM, excluding rodents and NHP), wild birds (WB) and wild rodents (WR). Appropriate and eligible articles published (in English) between 1 January 2011 to 30 August 2021 were searched for from PubMed, Scopus, Google Scholar, SciElo and Web of Science. Results: Of the 33 eligible and analysed studies, the pooled prevalence of NTO S. aureus and MRSA carriage was 18.5% (range: 0–100%) and 2.1% (range: 0.0–63.9%), respectively. The pooled prevalence of S. aureus/MRSA in WM, NHP, WB and WR groups was 15.8/1.6, 32.9/2.0, 10.3/3.4 and 24.2/3.4%, respectively. The prevalence of mecC-MRSA among WM/NHP/WB/WR was 1.64/0.0/2.1/0.59%, respectively, representing 89.9/0.0/59.1/25.0% of total MRSA detected in these groups of animals.The MRSA-CC398 and MRSA-CC130 lineages were most prevalent in wild birds (0.64 and 2.07%, respectively); none of these lineages were reported in NHP studies. The MRSA-CC398 (mainly of spa-type t011, 53%), MRSA-CC130 (mainly of spa types t843 and t1535, 73%), MSSA-CC398 (spa-types t571, t1451, t6606 and t034) and MSSA-CC130 (spa types t843, t1535, t3625 and t3256) lineages were mostly reported. Conclusion: Although the global prevalence of MRSA is low in wild animals, mecC-mediated resistance was particularly prevalent among MRSA isolates, especially among WM and WB. Considering the genetic diversity of MRSA in wild animals, they need to be monitored for effective control of the spread of antimicrobial resistance.
The Effects of Sorbus aucuparia L. Fruit Extracts on Oxidative/Nitrative Modifications of Human Fibrinogen, Impact on Enzymatic Properties of Thrombin, and Hyaluronidase Activity In Vitro
Authors: Rutkowska Magdalena , Kolodziejczyk-Czepas Joanna , Olszewska Monika Anna
Published: December 2021

Sorbus aucuparia L. fruits (rowanberries) are food products with acknowledged nutritional value, high phenolic content, and traditional application in diabetes. In this study, the effects of rowanberry extracts (phytochemically standardised, i.a., by LC-MS/MS) on some aspects of plasma haemostasis and vascular conditions were evaluated in vitro as possible mechanisms connected with cardiovascular complications of diabetes. The analyses of structural modifications of human fibrinogen under oxidative stress conditions (C-ELISA, SDS-PAGE and Western blot) revealed that the extracts (at a concentration of 1–5 µg/mL) considerably reduced the nitration of tyrosine residues and formation of high-molecular-weight aggregates. Moreover, they inhibited the enzymatic activity of thrombin (both amidolytic and proteolytic). Additionally, some promising outcomes might be expected regarding endothelial functions from the extracts ability to inhibit hyaluronidase. Parallel experiments on model polyphenols and correlation studies formed the basis for determining the contribution of different compounds, including hydroxycinnamic acid derivatives, flavonols, and low- or high-molecular-weight flavan-3-ols derivatives (proanthocyanidins), to the observed effects. The possible synergistic activity of individual constituents was also noticed. These results broaden the knowledge on the biological activity of rowanberries, partly confirming their health-promoting properties, and indicating that their functional applications might be promising.
Building a Realistic Virtual Simulator for Unmanned Aerial Vehicle Teleoperation
Authors: Mora-Soto Manuel Eduardo , Maldonado-Romo Javier , Rodríguez-Molina Alejandro , Aldape-Pérez Mario
Published: December 2021

Unmanned Aerial Vehicles (UAVs) support humans in performing an increasingly varied number of tasks. UAVs need to be remotely operated by a human pilot in many cases. Therefore, pilots require repetitive training to master the UAV movements. Nevertheless, training with an actual UAV involves high costs and risks. Fortunately, simulators are alternatives to face these difficulties. However, existing simulators lack realism, do not present flight information intuitively, and sometimes do not allow natural interaction with the human operator. This work addresses these issues through a framework for building realistic virtual simulators for the human operation of UAVs. First, the UAV is modeled in detail to perform a dynamic simulation in this framework. Then, the information of the above simulation is utilized to manipulate the elements in a virtual 3D operation environment developed in Unity 3D. Therefore, the interaction with the human operator is introduced with a proposed teleoperation algorithm and an input device. Finally, a meta-heuristic optimization procedure provides realism to the simulation. In this procedure, the flight information obtained from an actual UAV is used to optimize the parameters of the teleoperation algorithm. The quadrotor is adopted as the study case to show the proposal’s effectiveness.
Li2O-Based Cathode Additives Enabling Prelithiation of Si Anodes
Authors: Ha Yeyoung , Schulze Maxwell C. , Frisco Sarah , Trask Stephen E. , Teeter Glenn , Neale Nathan R. , Veith Gabriel M. , Johnson Christopher S.
Published: December 2021

Low first-cycle Coulombic efficiency is especially poor for silicon (Si)-based anodes due to the high surface area of the Si-active material and extensive electrolyte decomposition during the initial cycles forming the solid electrolyte interphase (SEI). Therefore, developing successful prelithiation methods will greatly benefit the development of lithium-ion batteries (LiBs) utilizing Si anodes. In pursuit of this goal, in this study, lithium oxide (Li2O) was added to a LiNi0.6Mn0.2Co0.2O2 (NMC622) cathode using a scalable ball-milling approach to compensate for the initial Li loss at the anode. Different milling conditions were tested to evaluate the impact of particle morphology on the additive performance. In addition, Co3O4, a well-known oxygen evolution reaction catalyst, was introduced to facilitate the activation of Li2O. The Li2O + Co3O4 additives successfully delivered an additional capacity of 1116 mAh/gLi2O when charged up to 4.3 V in half cells and 1035 mAh/gLi2O when charged up to 4.1 V in full cells using Si anodes.
The Influence of the Addition of Rosehip Powder to Wheat Flour on the Dough Farinographic Properties and Bread Physico-Chemical Characteristics
Authors: Vartolomei Nicoleta , Turtoi Maria
Published: December 2021

An in-depth analysis of wheat flour (WF) substituted with 0.5–2.5% rosehip powder (Rp) concerning the proximate composition, dough farinographic properties, and bread physico-chemical characteristics was performed. The purpose of this study was to investigate whether the use of Rp as a natural alternative for synthetic ascorbic acid in breadmaking was appropriate. A sample of wheat flour with an ascorbic acid addition of 2 mg/100 g was also used. Rp showed higher ash, carbohydrates, and fibre content, as well as lower moisture and protein content compared to wheat flour, and a vitamin C content of 420 ± 16.09 mg/100 g. A proximate composition analysis revealed a decrease in moisture, protein, and wet gluten, and an increase in ash, carbohydrates, and fibres for the flour mixtures compared with WF. Farinographic properties were positively influenced by the Rp addition and the high fibre content in the flour mixtures. Water absorption increased from 58.20% (WF) to 61.90% (2.5% Rp). Dough stability increased for the 0.5–1.0% Rp addition, then slightly decreased. The physico-chemical properties of bread prepared from flour mixtures showed a significant increase in height: 100.10 ± 0.14 mm (WF)–115.50 ± 0.14 mm (1.5% Rp), specific volume: 142.82 cm3/100 g (WF)–174.46 cm3/100 g (1.5% Rp), moisture: 41.81 ± 0.40% (WF)–43.92 ± 0.15% (2.0% Rp), and porosity: 87.75 ± 1.06% (WF)–89.40 ± 0.57% (2.5% Rp). The results indicated that the Rp used in breadmaking to replace synthetic ascorbic acid could be suitable.
Cross Domain Adaptation of Crowd Counting with Model-Agnostic Meta-Learning
Authors: Hou Xiaoyu , Xu Jihui , Wu Jinming , Xu Huaiyu
Published: December 2021

Counting people in crowd scenarios is extensively conducted in drone inspections, video surveillance, and public safety applications. Today, crowd count algorithms with supervised learning have improved significantly, but with a reliance on a large amount of manual annotation. However, in real world scenarios, different photo angles, exposures, location heights, complex backgrounds, and limited annotation data lead to supervised learning methods not working satisfactorily, plus many of them suffer from overfitting problems. To address the above issues, we focus on training synthetic crowd data and investigate how to transfer information to real-world datasets while reducing the need for manual annotation. CNN-based crowd-counting algorithms usually consist of feature extraction, density estimation, and count regression. To improve the domain adaptation in feature extraction, we propose an adaptive domain-invariant feature extracting module. Meanwhile, after taking inspiration from recent innovative meta-learning, we present a dynamic-β MAML algorithm to generate a density map in unseen novel scenes and render the density estimation model more universal. Finally, we use a counting map refiner to optimize the coarse density map transformation into a fine density map and then regress the crowd number. Extensive experiments show that our proposed domain adaptation- and model-generalization methods can effectively suppress domain gaps and produce elaborate density maps in cross-domain crowd-counting scenarios. We demonstrate that the proposals in our paper outperform current state-of-the-art techniques.
Editorial for Special Issue “Automation and Robotics: Latest Achievements, Challenges and Prospects”
Authors: Božek Pavol , Krenicky Tibor , Nikitin Yury
Published: December 2021

The determination of this Special Issue topic in the field of automation and robotics was well received by the community of scientists and researchers [...]
MLGen: Generative Design Framework Based on Machine Learning and Topology Optimization
Authors: Kallioras Nikos Ath. , Lagaros Nikos D.
Published: December 2021

Design and manufacturing processes are entering into a new era as novel methods and techniques are constantly introduced. Currently, 3D printing is already established in the production processes of several industries while more are continuously being added. At the same time, topology optimization has become part of the design procedure of various industries, such as automotive and aeronautical. Parametric design has been gaining ground in the architectural design literature in the past years. Generative design is introduced as the contemporary design process that relies on the utilization of algorithms for creating several forms that respect structural and architectural constraints imposed, among others, by the design codes and/or as defined by the designer. In this study, a novel generative design framework labeled as MLGen is presented. MLGen integrates machine learning into the generative design practice. MLGen is able to generate multiple optimized solutions which vary in shape but are equivalent in terms of performance criteria. The output of the proposed framework is exported in a format that can be handled by 3D printers. The ability of MLGen to efficiently handle different problems is validated via testing on several benchmark topology optimization problems frequently employed in the literature.
Establishment of the Optimal Common Data Model Environment for EMR Data Considering the Computing Resources of Medical Institutions
Authors: Kim Tong Min , Ko Taehoon , Yang Yoon-sik , Park Sang Jun , Choi In-Young , Chang Dong-Jin
Published: December 2021

Electronic medical record (EMR) data vary between institutions. These data should be converted into a common data model (CDM) for multi-institutional joint research. To build the CDM, it is essential to integrate the EMR data of each hospital and load it according to the CDM model, considering the computing resources of each hospital. Accordingly, this study attempts to share experiences and recommend computing resource-allocation designs. Here, two types of servers were defined: combined and separated servers. In addition, three database (DB) setting types were selected: desktop application (DA), online transaction processing (OLTP), and data warehouse (DW). Scale, TPS, average latency, 90th percentile latency, and maximum latency were compared across various settings. Virtual memory (vmstat) and disk input/output (disk) statuses were also described. Transactions per second (TPS) decreased as the scale increased in all DB types; however, the average, 90th percentile and maximum latencies exhibited no tendency according to scale. When compared with the maximum number of clients (DA client = 5, OLTP clients = 20, DW clients = 10), the TPS, average latency, 90th percentile latency, and maximum latency values were highest in the order of OLTP, DW, and DA. In vmstat, the amount of memory used for the page cache field and free memory currently available for DA, OLTP, and DW were large compared to other fields. In the disk, DA, OLTP, and DW all recorded the largest value in the average size of write requests, followed by the largest number of write requests per second. In summary, this study presents recommendations for configuring CDM settings. The configuration must be tuned carefully, considering the hospital’s resources and environment, and the size of the database must consider concurrent client connections, architecture, and connections.
Study on Soil Throwing Performance and Ditch Depth Stability of Ditching Device in Sandy Orchards in Southern Xinjiang
Authors: Li Liangliang , Chen Jie , Ma Chen , Meng Hewei , Qi Jiangtao , Li Yaping , Zhang Peixin , Lian Guodang , Qi Zhengdong
Published: December 2021

In order to solve the problems of serious soil reflux and poor stability of ditch depth in the existing ditching organic fertilizer fertilization device in grey desert and loess orchards, rotary tillage theory and software simulation were used to conduct kinematic analysis of soil particles and ditching blade in the ditching process, and meanwhile, modeling and simulation are carried out for sand soil particles by using EDEM software, so as to determine the action mechanism of soil, blade and fairing in ditching process of grey desert and loess. The abstract on this basis, the quadratic orthogonal regression-rotation combination experiment was designed. The soil bin test was carried out by taking the cutter wheel speed, ditching depth and inclination of curved surface as the influencing factors, and the throwing distance and the stability of ditch depth as the test indexes. And it was concluded that the order of the influence of the operating parameters of the ditching device on the soil throwing distance is ditching depth > inclination of curved surface > cutter speed, and the order of the influence on the stability of the ditch depth is ditching depth > cutter speed > Inclination of curved surface. Finally, the optimized operating parameters of the ditching device are as follows: the cutter wheel speed is 119.61 r·min−1, the inclination of curved surface is 30.07°, the ditching depth is 35.52 mm, the soil throwing distance is 57.31, and the stability of ditch depth is 87.43. With these parameters as test objects, 10 groups of single factor tests were carried out to obtain that the soil throwing distance is 58.33, and the stability of ditch depth is 86.51, which were basically consistent with the expected results of the optimization test, and also in line with the relevant agronomic standards.
A Test Method for Acoustic Emission Properties of Natural Cellulose Fiber-Reinforced Composites
Authors: Liu Fanxizi , Gao Qiang , Guo Hui , Lang Chenhong , Jiang Jinhua , Qiu Yiping
Published: December 2021

To test the acoustic performance of fiber-reinforced composites for replacing wood, an acoustic vibration test method is developed. For evaluation of the test method, composites are manufactured using hemp and ramie embedded in epoxy, through vacuum-assisted resin infusion molding. The effects of the most important factors, i.e., impulse, relative humidity (RH), and specimen thickness, on the acoustic vibration response of the composites are systematically studied. The magnitudes of the impulses, represented by different masses of the dropping balls, seem to have little influence on the shapes of the acoustic vibration curves, although the intensity of the spectra increases as the impulse increases. The RH influences the spectrum shape significantly due to variation in the Young’s modulus and density of the material upon absorption of moisture. The specimen thickness also greatly affects the testing results. The specific dynamic modulus, acoustic radiation damping coefficient, and acoustic impedance change a little as the impulse magnitude and RH change, but decrease substantially as the specimen thickness increases. The specific dynamic modulus can be linearly correlated with the flexural modulus of a material.
Evaluation of Structural Behavior and Fatigue Performance of a KR-Type Rail Clip
Authors: Kim Sang-Hyeok , Fang Xiao-Jun , Park Yeun-Chul , Sim Hyoung-Bo
Published: December 2021

Rail clips are essential components of rail fastening systems that clamp the rails to sleepers. Fatigue damage of rail clips has been recently reported in railway lines. However, there has been a lack of research investigating this fatigue issue. The KR-type rail fastening system has been recently developed and used in some domestic railways. This study aimed at evaluating the structural behavior and fatigue performance of the KR-type rail clip. The assembly test performed in the laboratory showed that the stresses induced in the rail clips after tightening, particularly at the stress concentration locations, exceeded the yield stress, indicating that the rail clip could be vulnerable to fatigue cracking when combined with the stress range during repeated trainloads. The finite element analysis results, which revealed a good correlation with the experiments, were used to evaluate the fatigue performance of the rail clip by adopting the modified Goodman fatigue criteria. The fatigue evaluation results indicated that when the vertical rail displacement during train operation exceeded 2 mm, the rail clips could potentially suffer from fatigue failure.
Analysis of Electrical Characteristics in 4H-SiC Trench-Gate MOSFETs with Grounded Bottom Protection p-Well Using Analytical Modeling
Authors: Jeong Jee-Hun , Seok Ogyun , Lee Ho-Jun
Published: December 2021

A new analytical model to analyze and optimize the electrical characteristics of 4H-SiC trench-gate metal-oxide-semiconductor field-effect transistors (TMOSFETs) with a grounded bottom protection p-well (BPW) was proposed. The optimal BPW doping concentration (NBPW) was extracted by analytical modeling and a numerical technology computer-aided design (TCAD) simulation, in order to analyze the breakdown mechanisms for SiC TMOSFETs using BPW, while considering the electric field distribution at the edge of the trench gate. Our results showed that the optimal NBPW obtained by analytical modeling was almost identical to the simulation results. In addition, the reverse transfer capacitance (Cgd) values obtained from the analytical model correspond with the results of the TCAD simulation by approximately 86%; therefore, this model can predict the switching characteristics of the effect BPW regions.
Understanding the Pattern of Oropharyngeal Cancers from North-East Romanian Patients
Authors: Ursu Ramona , Giusca Simona , Spiridon Irene , Manole Bianca , Danciu Mihai , Costan Victor , Palade Dragos , Ghetu Nicolae , Toader Paula , Vlad Mădălina , Damian Costin , Porumb-Andrese Elena , Luchian Ionut , Iancu Luminița
Published: December 2021

Background: Human papilloma virus (HPV) is acknowledged as a risk factor for oropharyngeal squamous cellular cancers (OPSCC), of which the dominant types are tonsillar (TSCC) and base of tongue cancer (BOTSCC). Objective: To assess the role of HPV in selected OPSCC cases, from Romanian patients by sensitive and complementary molecular assays. Material and Methods: Fifty-four formalin fixed paraffin embedded (FFPE) OPSCC samples were analyzed for HPV DNA by a PCR-based bead-based multiplex-assay. Thirty-four samples were tested for HPV RNA and for overexpression of p16INK4a by immunohistochemistry. Twenty samples were evaluated by Competitive Allele-Specific Taqman PCR (CAST-PCR) for fibroblast growth factor receptor 3 protein (FGFR3) status. Results: A total of 33.3% (18/54) OPSCC samples were positive for HPV DNA. HPV16 was the most frequent type (30%, 16/54); followed by HPV18 (3.7%, 2/54); and 1 sample (1.8%) was positive for both HPV16 and 18. HPV18 E6*I was detected in a HPV18 DNA-positive oropharynx tumor. Four samples positive for HPV16 were also positive for p16INK4a. All the tested samples were negative for FGFR3. Conclusions: The increased HPV16 prevalence is in line with similar studies and is a new confirmation that HPV16 is the most prevalent type in our country; supporting the potential benefit of prophylactic vaccines. Overall, there is no concordance between DNA and any of the two other analytes that are considered being markers of HPV-driven cancers. There is a need to explore novel screening strategies that could be broadly used in the clinical routine to initiate preventive measures.
Petri Net Toolbox for Multi-Robot Planning under Uncertainty
Authors: Azevedo Carlos , Matos António , Lima Pedro U. , Avendaño Jose
Published: December 2021

Currently, there is a lack of developer-friendly software tools to formally address multi-robot coordination problems and obtain robust, efficient, and predictable strategies. This paper introduces a software toolbox that encapsulates, in one single package, modeling, planning, and execution algorithms. It implements a state-of-the-art approach to representing multi-robot systems: generalized Petri nets with rewards (GSPNRs). GSPNRs enable capturing multiple robots, decision states, action execution states and respective outcomes, action duration uncertainty, and team-level objectives. We introduce a novel algorithm that simplifies the model design process as it generates a GSPNR from a topological map. We also introduce a novel execution algorithm that coordinates the multi-robot system according to a given policy. This is achieved without compromising the model compactness introduced by representing robots as indistinguishable tokens. We characterize the computational performance of the toolbox with a series of stress tests. These tests reveal a lightweight implementation that requires low CPU and memory usage. We showcase the toolbox functionalities by solving a multi-robot inspection application, where we extend GSPNRs to enable the representation of heterogeneous systems and system resources such as battery levels and counters.
Coverage Path Planning with Semantic Segmentation for UAV in PV Plants
Authors: Pérez-González Andrés , Benítez-Montoya Nelson , Jaramillo-Duque Álvaro , Cano-Quintero Juan Bernardo
Published: December 2021

Solar energy is one of the most strategic energy sources for the world’s economic development. This has caused the number of solar photovoltaic plants to increase around the world; consequently, they are installed in places where their access and manual inspection are arduous and risky tasks. Recently, the inspection of photovoltaic plants has been conducted with the use of unmanned aerial vehicles (UAV). Although the inspection with UAVs can be completed with a drone operator, where the UAV flight path is purely manual or utilizes a previously generated flight path through a ground control station (GCS). However, the path generated in the GCS has many restrictions that the operator must supply. Due to these restrictions, we present a novel way to develop a flight path automatically with coverage path planning (CPP) methods. Using a DL server to segment the region of interest (RoI) within each of the predefined PV plant images, three CPP methods were also considered and their performances were assessed with metrics. The UAV energy consumption performance in each of the CPP methods was assessed using two different UAVs and standard metrics. Six experiments were performed by varying the CPP width, and the consumption metrics were recorded in each experiment. According to the results, the most effective and efficient methods are the exact cellular decomposition boustrophedon and grid-based wavefront coverage, depending on the CPP width and the area of the PV plant. Finally, a relationship was established between the size of the photovoltaic plant area and the best UAV to perform the inspection with the appropriate CPP width. This could be an important result for low-cost inspection with UAVs, without high-resolution cameras on the UAV board, and in small plants.
A Novel Approach of Modelling and Predicting Track Cycling Sprint Performance
Authors: Dunst Anna Katharina , Grüneberger René
Published: December 2021

In cycling, performance models are used to investigate factors that determine performance and to optimise competition results. We present an innovative and easily applicable mathematical model describing time-resolved approaches for both the physical aspects of tractional resistance and the physiological side of propelling force generated by muscular activity and test its validity to reproduce and forecast time trials in track cycling. Six elite track cyclists completed a special preparation and two sprint time trials in an official velodrome under continuous measurement of crank force and cadence. Fatigue-free force-velocity profiles were calculated, and their fatigue-induced changes were determined by non-linear regression analysis using a monoexponential equation at a constant slope. Model parameters were calibrated based on pre-exercise performance testing and the first of the two time-trials and then used to predict the performance of the second sprint. Measured values for power output and cycling velocity were compared to the modelled data. The modelled results were highly correlated to the measured values (R2>0.99) without any difference between runs (p>0.05; d<0.1). Our mathematical model can accurately describe sprint track cycling time trial performance. It is simple enough to be used in practice yet sufficiently accurate to predict highly dynamic maximal sprint performances. It can be employed for the evaluation of completed runs, to forecast expected results with different setups, and to study various contributing factors and quantify their effect on sprint cycling performance.
Human Activity Recognition Using Cell Phone-Based Accelerometer and Convolutional Neural Network
Authors: Prasad Ashwani , Tyagi Amit Kumar , Althobaiti Maha M. , Almulihi Ahmed , Mansour Romany F. , Mahmoud Ayman M.
Published: December 2021

Human Activity Recognition (HAR) has become an active field of research in the computer vision community. Recognizing the basic activities of human beings with the help of computers and mobile sensors can be beneficial for numerous real-life applications. The main objective of this paper is to recognize six basic human activities, viz., jogging, sitting, standing, walking and whether a person is going upstairs or downstairs. This paper focuses on predicting the activities using a deep learning technique called Convolutional Neural Network (CNN) and the accelerometer present in smartphones. Furthermore, the methodology proposed in this paper focuses on grouping the data in the form of nodes and dividing the nodes into three major layers of the CNN after which the outcome is predicted in the output layer. This work also supports the evaluation of testing and training of the two-dimensional CNN model. Finally, it was observed that the model was able to give a good prediction of the activities with an average accuracy of 89.67%. Considering that the dataset used in this research work was built with the aid of smartphones, coming up with an efficient model for such datasets and some futuristic ideas pose open challenges in the research community.
Structural Performance of a Precast Concrete Modular Beam Using Bolted Connecting Plates
Authors: Ro Kyong Min , Kim Min Sook , Cho Chang Geun , Lee Young Hak
Published: December 2021

In modular structures, prefabricated modular units are joined at the construction site. Modular structures must ensure splicing performance by connecting modular units sufficiently. The bolted connection using steel plates may suffer from alignment issues and corrosion problems. In a precast concrete (PC) modular system, there is difficulty grouting the sleeves when splicing reinforcing bars. This study proposed a PC modular beam using a bolted connecting plate to deal with issues in typical steel modules and PC modules. The structural performance was evaluated by flexural and shear tests on two monolithic beams and two proposed PC specimens. The test results showed that the structural performance of the PC modular specimen was 88% of that of the monolithic reinforced concrete (RC) beam specimen and 102% of the strength calculated by ACI 318-19. Therefore, the proposed PC modular system using bolted connecting plates can solve the problems observed in typical steel and PC modules and improve the structural performance.
Breast Cancer Detection Using Mammogram Images with Improved Multi-Fractal Dimension Approach and Feature Fusion
Authors: Zebari Dilovan Asaad , Ibrahim Dheyaa Ahmed , Zeebaree Diyar Qader , Mohammed Mazin Abed , Haron Habibollah , Zebari Nechirvan Asaad , Damaševičius Robertas , Maskeliūnas Rytis
Published: December 2021

Breast cancer detection using mammogram images at an early stage is an important step in disease diagnostics. We propose a new method for the classification of benign or malignant breast cancer from mammogram images. Hybrid thresholding and the machine learning method are used to derive the region of interest (ROI). The derived ROI is then separated into five different blocks. The wavelet transform is applied to suppress noise from each produced block based on BayesShrink soft thresholding by capturing high and low frequencies within different sub-bands. An improved fractal dimension (FD) approach, called multi-FD (M-FD), is proposed to extract multiple features from each denoised block. The number of features extracted is then reduced by a genetic algorithm. Five classifiers are trained and used with the artificial neural network (ANN) to classify the extracted features from each block. Lastly, the fusion process is performed on the results of five blocks to obtain the final decision. The proposed approach is tested and evaluated on four benchmark mammogram image datasets (MIAS, DDSM, INbreast, and BCDR). We present the results of single- and double-dataset evaluations. Only one dataset is used for training and testing in the single-dataset evaluation, whereas two datasets (one for training, and one for testing) are used in the double-dataset evaluation. The experiment results show that the proposed method yields better results on the INbreast dataset in the single-dataset evaluation, whilst better results are obtained on the remaining datasets in the double-dataset evaluation. The proposed approach outperforms other state-of-the-art models on the Mini-MIAS dataset.
Experimental Study on Electrical Resistivity Characteristics of Saturated Sand Mixes with Bentonite Slurry
Authors: Mao Jiahua , Yuan Dajun , Jin Dalong , Wang Binghui , Wu Shangkun
Published: December 2021

Bentonite slurry is widely used in underground and geotechnical engineering because of its strong ability of wall protection. Slurry penetration, which is of great significance for the soil stability, is difficult to observe directly during the soil and slurry interaction. Slurry penetration would change the electrical resistivity of soil, which provides an indirect method to monitor the degree of slurry penetration. This paper aimed to investigate the electrical resistivity characteristics of soil-bentonite mixtures. Several test groups with different material components were carried out. The effects of some factors including water environment, CMC (carboxymethyl cellulose) contents, soil particle gradation, and electrode distance on the electrical resistivity of slurry-soil mixtures were studied and the relationship between soil electrical resistivity and slurry concentration was established. The results in this paper can provide references for the application of the electrical method on slurry penetration.
Effect of Real-Time Online High-Intensity Interval Training on Physiological and Physical Parameters for Abdominally Obese Women: A Randomized Pilot Study
Authors: Hyun Ah-hyun
Published: December 2021

Purpose: This study aimed to investigate the effects of online high-intensity interval training (HIIT) in abdominally obese women experiencing health complications due to COVID-19. Methods: Sixteen participants were enrolled and divided into the HIIT group (n = 8) and moderate-intensity continuous training (MICT, n = 8) group. The HIIT group underwent 20 min of exercise consisting of 20 s of high-intensity (85–90% HRmax) exercise followed by 30 s of exercise at 60% HRmax using only body weight. The main exercise program for the MICT group included 40 min of stationary bike pedaling at 65–70% HRmax. Exercise was performed three days a week for eight weeks using a smart device and application that enables bidirectional communication. Results: The HIIT group showed reduced body fat (p = 0.036), BMI (p = 0.021), and visceral fat (p = 0.003) compared to the MICT group. Further, the HIIT group also had reduced insulin (p = 0.021) and LDL levels (p = 0.024), increased grip strength (left p = 0.012, right: p = 0.002), and a substantial drop in total stress index (p = 0.004) compared to the MICT group. Conclusions: Thus, online HIIT is a useful means to reduce abdominal fat, improve blood lipid profile and muscle strength, and relieve stress caused by COVID-19.