bluuebunny/crossref_metadata_2025 huggingface dataset:
Cerebral Blood Flow Monitoring in High-Risk Fetal and Neonatal Populations
Authors: Leon Rachel L. , Ortigoza Eric B. , Ali Noorjahan , Angelis Dimitrios , Wolovits Joshua S. , Chalak Lina F.
Published: January 2022

Cerebrovascular pressure autoregulation promotes stable cerebral blood flow (CBF) across a range of arterial blood pressures. Cerebral autoregulation (CA) is a developmental process that reaches maturity around term gestation and can be monitored prenatally with both Doppler ultrasound and magnetic resonance imaging (MRI) techniques. Postnatally, there are key advantages and limitations to assessing CA with Doppler ultrasound, MRI, and near-infrared spectroscopy. Here we review these CBF monitoring techniques as well as their application to both fetal and neonatal populations at risk of perturbations in CBF. Specifically, we discuss CBF monitoring in fetuses with intrauterine growth restriction, anemia, congenital heart disease, neonates born preterm and those with hypoxic-ischemic encephalopathy. We conclude the review with insights into the future directions in this field with an emphasis on collaborative science and precision medicine approaches.
Immune Reconstitution After Allogeneic Haematopoietic Cell Transplantation: From Observational Studies to Targeted Interventions
Authors: Yanir Asaf , Schulz Ansgar , Lawitschka Anita , Nierkens Stefan , Eyrich Matthias
Published: January 2022

Immune reconstitution (IR) after allogeneic haematopoietic cell transplantation (HCT) represents a central determinant of the clinical post-transplant course, since the majority of transplant-related outcome parameters such as graft-vs.-host disease (GvHD), infectious complications, and relapse are related to the velocity, quantity and quality of immune cell recovery. Younger age at transplant has been identified as the most important positive prognostic factor for favourable IR post-transplant and, indeed, accelerated immune cell recovery in children is most likely the pivotal contributing factor to lower incidences of GvHD and infectious complications in paediatric allogeneic HCT. Although our knowledge about the mechanisms of IR has significantly increased over the recent years, strategies to influence IR are just evolving. In this review, we will discuss different patterns of IR during various time points post-transplant and their impact on outcome. Besides IR patterns and cellular phenotypes, recovery of antigen-specific immune cells, for example virus-specific T cells, has recently gained increasing interest, as certain threshold levels of antigen-specific T cells seem to confer protection against severe viral disease courses. In contrast, the association between IR and a possible graft-vs. leukaemia effect is less well-understood. Finally, we will present current concepts of how to improve IR and how this could change transplant procedures in the near future.
Polarimetric Imaging in the Environment Containing Medium and Object
Authors: Wang Daqian , Wang Xin , Pan Peifeng , Gao Jun
Published: January 2022

Polarimetric imaging has been studied and applied to the problem of visibility restoration in various scenarios such as haze, mist and underwater. Although studies have shown that under certain conditions, circular polarimetric imaging has certain advantages over linear polarimetric imaging, however, for a complex environment containing both scattering medium and object, the performance of linear and circular polarimetric imaging is affected by many factors. In this paper, the propagation of linear and circular polarized light in the scattering medium is theoretically analyzed, then the simulation experiments under different experimental conditions are carried out and the conclusions are summarized. In order to validate the simulation results, the measurement experiments are carried out in dynamic smoke scenarios with different smoke concentrations. The results show that, the propagation of the polarized light, especially the circular polarized light, is determined by medium conditions. Generally, both the linear and circular polarimetric imaging had an ability to reduce the image degradation caused by smoke, however, under some certain environment conditions, unlike the linear polarized channels, the difference between the orthogonal circular polarized channels may be approached or even reversed, which may limit the circular polarization-based difference imaging and visibility restoration performance.
Imaging Through Random Scatterer with Spatial Coherence Structure Measurement
Authors: Peng Deming , Zhang Xuan , Liu Yonglei , Zhu Yimeng , Chen Yahong , Wang Fei , Cai Yangjian
Published: January 2022

Optical coherence is becoming an efficient degree of freedom for light field manipulations and applications. In this work, we show that the image information hidden a distance behind a random scattering medium is encoded in the complex spatial coherence structure of a partially coherent light beam that generates after the random scatterer. We validate in experiment that the image information can be well recovered with the spatial coherence measurement and the aid of the iterative phase retrieval algorithm in the Fresnel domain. We find not only the spatial shape but also the position including the lateral shift and longitudinal distances of the image hidden behind the random scatterer can be reconstructed, which indicates the potential uses in three-dimensional optical imaging through random scattering media.
From What to Why, the Growing Need for a Focus Shift Toward Explainability of AI in Digital Pathology
Authors: Border Samuel P. , Sarder Pinaki
Published: January 2022

While it is impossible to deny the performance gains achieved through the incorporation of deep learning (DL) and other artificial intelligence (AI)-based techniques in pathology, minimal work has been done to answer the crucial question of why these algorithms predict what they predict. Tracing back classification decisions to specific input features allows for the quick identification of model bias as well as providing additional information toward understanding underlying biological mechanisms. In digital pathology, increasing the explainability of AI models would have the largest and most immediate impact for the image classification task. In this review, we detail some considerations that should be made in order to develop models with a focus on explainability.
Convolutional Neural Network Models Help Effectively Estimate Legume Coverage in Grass-Legume Mixed Swards
Authors: Fujiwara Ryo , Nashida Hiroyuki , Fukushima Midori , Suzuki Naoya , Sato Hiroko , Sanada Yasuharu , Akiyama Yukio
Published: January 2022

Evaluation of the legume proportion in grass-legume mixed swards is necessary for breeding and for cultivation research of forage. For objective and time-efficient estimation of legume proportion, convolutional neural network (CNN) models were trained by fine-tuning the GoogLeNet to estimate the coverage of timothy (TY), white clover (WC), and background (Bg) on the unmanned aerial vehicle-based images. The accuracies of the CNN models trained on different datasets were compared using the mean bias error and the mean average error. The models predicted the coverage with small errors when the plots in the training datasets were similar to the target plots in terms of coverage rate. The models that are trained on datasets of multiple plots had smaller errors than those trained on datasets of a single plot. The CNN models estimated the WC coverage more precisely than they did to the TY and the Bg coverages. The correlation coefficients (r) of the measured coverage for aerial images vs. estimated coverage were 0.92–0.96, whereas those of the scored coverage by a breeder vs. estimated coverage were 0.76–0.93. These results indicate that CNN models are helpful in effectively estimating the legume coverage.
Carrying the Burden Into the Pandemic – Effects of Social Disparities on Elementary Students’ Parents’ Perception of Supporting Abilities and Emotional Stress During the COVID-19 Lockdown
Authors: Vogelbacher Markus , Attig Manja
Published: January 2022

The COVID-19 pandemic has posed many challenges, especially for families. Both the public and the scientific community are currently discussing the extent to which school closings have worsened existing social differences, especially with regard to children’s academic and socio-emotional development. At the same time, parents have had to manage childcare and home schooling alongside their jobs and personal burdens posed by the pandemic. Parents’ possibilities for meeting these cognitive and emotional challenges might also depend on the different conditions in families. For this reason, the present paper investigates the structural and process characteristics of the family as well as children’s and parents’ psychological characteristics that predict how parents assess their ability to support their child’s learning during homeschooling as well as parents’ perceived emotional stress caused by school closure. The study analyses data of the Newborn Cohort Study of the German National Educational Panel Study. The two dependent variables (self-assessment of abilities, perceived stress) were measured during the COVID-19 pandemic after the first school closure in Germany, at a time when the children of this cohort were attending second grade. Besides a number of control variables (including the child’s struggle with home schooling), families’ structural characteristics [socioeconomic status (SES), education], process characteristics (home learning environment, HLE), parents’ psychological characteristics (preceding psychological stress), and the child’s psychological characteristics (self-regulation, school-related independence) from earlier waves were included as predictors. The results of structural equation models show that perceived stress was associated with structural factors and the preceding psychological stress of parents. Parents with higher preceding stress reported higher perceived stress. Interestingly, higher-educated parents also reported more stress than lower educated parents during the pandemic. The effect was the other way around for SES – parents with lower SES reported more stress than parents with higher SES. The self-reported abilities to support the learning of the child seemed to be mainly predicted by the parent’s education as well as preceding psychological stress. To sum up, the results identify important aspects that determine how parents handle the challenges of the school closures. Especially, socially disadvantaged families carry their burden into the pandemic.
A Structural Equation Modeling of the Relationships Between Parenting Styles, Students’ Personality Traits, and Students’ Achievement Goal Orientation
Authors: Asanjarani Faramarz , Aghaei Khadijeh , Fazaeli Tahereh , Vaezi Adnan , Szczygieł Monika
Published: January 2022

Recently, researchers have shown an increased interest in achievement goal orientation correlates. What is not yet clear is the detailed relationships among students’ goal orientation, students’ personality traits, and parenting style. In so doing, this research responds to the need to analyze the importance of parenting styles (permissive, authoritative, and authoritarian) and students’ traits (psychoticism, neuroticism, and extraversion) in explaining the achievement goal orientations (mastery approach, mastery avoidance, performance-approach, and performance-avoidance). In the exploratory correlational study, 586 Iranian students along with their parents were selected as the sample so as to evaluate the structure of the relationships between these variables. The results indicate that students’ psychoticism and neuroticism predict students’ goal orientations (positively: performance and mastery avoidance and negatively: mastery and performance approach) while extraversion did not. Only the authoritative style predicts mastery approach (positively) and psychoticism trait (negatively). Permissive and authoritarian styles do not directly or indirectly predict students’ goal orientations.
The Influence of Human-Organizational Factors on Falling Accidents From Historical Text Data
Authors: Luo Xixi , Liu Quanlong , Qiu Zunxiang
Published: January 2022

This paper firstly proposes a modified human factor classification analysis system (HFACS) framework based on literature analysis and the characteristics of falling accidents in construction. Second, a Bayesian network (BN) topology is constructed based on the dependence between human factors and organizational factors, and the probability distribution of the human-organizational factors in a BN risk assessment model is calculated based on falling accident reports and fuzzy set theory. Finally, the sensitivity of the causal factors is determined. The results show that 1) the most important reason for falling accidents is unsafe on-site supervision. 2) There are significant factors that influence falling accidents at different levels in the proposed model, including operation violations in the unsafe acts layer, factors related to an adverse technological environment for the unsafe acts layer, loopholes in site management in the unsafe on-site supervision layer, lack of safety culture in the adverse organizational influence layer, and lax government regulation in the adverse external environment layer. 3) According to the results of the BN risk assessment model, the most likely causes are loopholes in site management work, lack of safety culture, insufficient safety inspections and acceptance, vulnerable process management and operation violations.
The Rise in Norovirus-Related Acute Gastroenteritis During the Fight Against the COVID-19 Pandemic in Southern China
Authors: Lu Ying , Zhang Zhoubin , Xie Huaping , Su Wenzhe , Wang Hui , Wang Dahu , Lu Jianyun
Published: January 2022

Background: There has been a significant decline in the morbidity of almost all infectious diseases during the COVID-19 pandemic. However, while the incidence of norovirus-related acute gastroenteritis declined in Guangzhou, China during the initial period of the pandemic, incidence increased significantly once the new school year began in September 2020.

Methods: Norovirus-related acute gastroenteritis clusters and outbreaks were assessed in Guangzhou from 2015 to 2020. Medians and interquartile ranges were compared between groups using the Mann–Whitney U-test, and attack rates were calculated.

Results: While 78,579 cases of infectious diarrhea were reported from 2015 to 2019, with an average of 15,716 cases per year, only 12,065 cases of infectious diarrhea were reported in 2020. The numbers of sporadic cases and outbreaks reported from January to August 2020 were lower than the average numbers reported during the same time period each year from 2015 to 2019 but began to increase in September 2020. The number of cases in each reported cluster ranged from 10 to 70 in 2020, with a total of 1,280 cases and an average attack rate of 5.85%. The median number of reported cases, the cumulative number of cases, and the attack rate were higher than the average number reported each year from 2015 to 2019. The intervention time in 2020 was also higher than the average intervention time reported during 2015–2019. The main norovirus genotypes circulating in Guangzhou during 2015–2020 included genogroup 2 type 2 (GII.2) (n = 79, 26.69%), GII.17 (n = 36, 12.16%), GII.3 (n = 27, 9.12%), GII.6 (n = 8, 2.7%), GII.4 Sydney_2012 (n = 7, 2.36%), and GII.4 (n = 6, 2.03%).

Conclusions: Our findings illustrate the importance of maintaining epidemiological surveillance for viral gastroenteritis during the COVID-19 pandemic. Local disease prevention and control institutions need to devote sufficient human resources to control norovirus clusters.
Global Trends and Hotspots in Research on Rehabilitation Robots: A Bibliometric Analysis From 2010 to 2020
Authors: Xue Xiali , Yang Xinwei , Deng Zhongyi , Tu Huan , Kong Dezhi , Li Ning , Xu Fan
Published: January 2022

Background: In recent years, with the development of medical science and artificial intelligence, research on rehabilitation robots has gained more and more attention, for nearly 10 years in the Web of Science database by journal of rehabilitation robot-related research literature analysis, to parse and track rehabilitation robot research hotspot and front, and provide some guidance for future research.

Methods: This study employed computer retrieval of rehabilitation robot-related research published in the core data collection of the Web of Science database from 2010 to 2020, using CiteSpace 5.7 visualization software. The hotspots and frontiers of rehabilitation robot research are analyzed from the aspects of high-influence countries or regions, institutions, authors, high-frequency keywords, and emergent words.

Results: A total of 3,194 articles were included. In recent years, the research on rehabilitation robots has been continuously hot, and the annual publication of relevant literature has shown a trend of steady growth. The United States ranked first with 819 papers, and China ranked second with 603 papers. Northwestern University ranked first with 161 publications. R. Riener, a professor at the University of Zurich, Switzerland, ranked as the first author with 48 articles. The Journal of Neural Engineering and Rehabilitation has the most published research, with 211 publications. In the past 10 years, research has focused on intelligent control, task analysis, and the learning, performance, and reliability of rehabilitation robots to realize the natural and precise interaction between humans and machines. Research on neural rehabilitation robots, brain–computer interface, virtual reality, flexible wearables, task analysis, and exoskeletons has attracted more and more attention.

Conclusions: At present, the brain–computer interface, virtual reality, flexible wearables, task analysis, and exoskeleton rehabilitation robots are the research trends and hotspots. Future research should focus on the application of machine learning (ML), dimensionality reduction, and feature engineering technologies in the research and development of rehabilitation robots to improve the speed and accuracy of algorithms. To achieve wide application and commercialization, future rehabilitation robots should also develop toward mass production and low cost. We should pay attention to the functional needs of patients, strengthen multidisciplinary communication and cooperation, and promote rehabilitation robots to better serve the rehabilitation medical field.
A Web-Based Prediction Model for Overall Survival of Elderly Patients With Malignant Bone Tumors: A Population-Based Study
Authors: Tang Jie , Wang JinKui , Pan Xiudan
Published: January 2022

Background: Malignant bone tumors (MBT) are one of the causes of death in elderly patients. The purpose of our study is to establish a nomogram to predict the overall survival (OS) of elderly patients with MBT.

Methods: The clinicopathological data of all elderly patients with MBT from 2004 to 2018 were downloaded from the SEER database. They were randomly assigned to the training set (70%) and validation set (30%). Univariate and multivariate Cox regression analysis was used to identify independent risk factors for elderly patients with MBT. A nomogram was built based on these risk factors to predict the 1-, 3-, and 5-year OS of elderly patients with MBT. Then, used the consistency index (C-index), calibration curve, and the area under the receiver operating curve (AUC) to evaluate the accuracy and discrimination of the prediction model was. Decision curve analysis (DCA) was used to assess the clinical potential application value of the nomogram. Based on the scores on the nomogram, patients were divided into high- and low-risk groups. The Kaplan-Meier (K-M) curve was used to test the difference in survival between the two patients.

Results: A total of 1,641 patients were included, and they were randomly assigned to the training set (N = 1,156) and the validation set (N = 485). The univariate and multivariate analysis of the training set suggested that age, sex, race, primary site, histologic type, grade, stage, M stage, surgery, and tumor size were independent risk factors for elderly patients with MBT. The C-index of the training set and the validation set were 0.779 [0.759–0.799] and 0.801 [0.772–0.830], respectively. The AUC of the training and validation sets also showed similar results. The calibration curves of the training and validation sets indicated that the observed and predicted values were highly consistent. DCA suggested that the nomogram had potential clinical value compared with traditional TNM staging.

Conclusion: We had established a new nomogram to predict the 1-, 3-, 5-year OS of elderly patients with MBT. This predictive model can help doctors and patients develop treatment plans and follow-up strategies.
A Self-Stabilized Inverted Pendulum Made of Optically Responsive Liquid Crystal Elastomers
Authors: Cheng Quanbao , Zhou Lin , Li Kai
Published: January 2022

The inverted pendulum system has great potential for various engineering applications, and its stabilization is challenging because of its unstable characteristic. The well-known Kapitza’s pendulum adopts the parametrically excited oscillation to stabilize itself, which generally requires a complex controller. In this paper, self-sustained oscillation is utilized to stabilize an inverted pendulum, which is made of a V-shaped, optically responsive liquid crystal elastomer (LCE) bar under steady illumination. Based on the well-established dynamic LCE model, a theoretical model of the LCE inverted pendulum is formulated, and numerical calculations show that it always develops into the unstable static state or the self-stabilized oscillation state. The mechanism of the self-stabilized oscillation originates from the reversal of the gravity moment of the inverted pendulum accompanied with its own movement. The critical condition for triggering self-stabilized oscillation is fully investigated, and the effects of the system parameters on the stability of the inverted pendulum are explored. The self-stabilized inverted pendulum does not need an additional controller and offers new designs of self-stabilized inverted pendulum systems for potential applications in robotics, military industry, aerospace, and other fields.
An Operational Methodology for Validating Satellite-Based Snow Albedo Measurements Using a UAV
Authors: Mullen Andrew , Sproles Eric A. , Hendrikx Jordy , Shaw Joseph A. , Gatebe Charles K.
Published: January 2022

Snow albedo is highly variable over multiple temporal and spatial scales. This variability is more pronounced in areas that experience seasonal snowpack. Satellite retrievals, physically based models and parameterizations for snow albedo all require ground-based measurements for calibration, initialization, and validation. Ground measurements are generally made using upward and downward-facing pyranometers at opportunistically located weather stations that are sparsely distributed, particularly in mountainous regions. These station-based measurements cannot capture the spatial variability of albedo across the land surface. Uncrewed Aerial Vehicles (UAVs) equipped with upward and downward-facing pyranometers provide near-surface measurements of broadband albedo that are spatially distributed across landscapes, offering improvements over in-situ sensors. At the hillslope to watershed scale albedo measurements from UAVs taken over heterogeneous terrain are a function of the spatial variability in albedo and topography within the downward-facing sensor’s field-of-view (FOV). In this research we propose methods for topographic correction of UAV snow albedo measurements and comparison to gridded satellite albedo products. These methods account for the variability of surface topography and albedo within the sensor FOV, sensor tilt, and the angular response of pyranometers. We applied the proposed methodologies to UAV snow albedo measurements collected over an alpine meadow in southwest Montana, United States (45.23°, −111.28°). Sensitivity analyses were conducted to determine the effect of altering the processing FOV (PFOV) for both topographic corrections and comparison to coincident Landsat 8-derived albedo measurements. Validation from ground-based albedo measurements showed the topographic correction to reduce albedo measurement error considerably over mildly sloping terrain. Our sensitivity analyses demonstrated that outcomes from the topographic correction and satellite comparison are highly dependent on the specified PFOV. Based on field observations and analyses of UAV albedo measurements made at different altitudes, we provide guidelines for strategizing future UAV albedo surveys. This research presents considerable advances in the standardization of UAV-based albedo measurement. We establish the foundation for future research to utilize this platform to collect near-surface validation measurements over heterogeneous terrain with high accuracy and consistency.
Impulsive Solar Energetic Particle Events: Extreme-Ultraviolet Waves and Jets
Authors: Bučík Radoslav
Published: January 2022

Impulsive solar energetic particle (ISEP) events show peculiar elemental composition, with enhanced 3He and heavy-ion abundances, markedly different from our Solar System composition. Furthermore, the events are characterized by a wide variety of energy spectral shapes from power laws to rounded spectra toward the low energies. Solar sources of the events have been firmly associated with coronal jets. Surprisingly, new observations have shown that events are often accompanied by so-called extreme-ultraviolet (EUV) coronal waves–a large-scale phenomenon compared to jets. This paper outlines the current understanding of the linkage of EUV waves with jets and energetic ions in ISEP events.
Wettability and Water Uptake Improvement in Plasma-Treated Alfalfa Seeds
Authors: Holc Matej , Gselman Peter , Primc Gregor , Vesel Alenka , Mozetič Miran , Recek Nina
Published: January 2022

The cultivation of alfalfa (Medicago sativa L.), a forage crop grown worldwide, is negatively affected by hard seed presence. We show that treatment of alfalfa seeds with an inductively coupled radio frequency oxygen plasma improves their surface hydrophilicity, as determined by water contact angle (WCA) measurements and water uptake. Furthermore, we see that these effects are mediated by functionalization and etching of the alfalfa seed surface. Surface chemistry is analyzed by X-ray photoelectron spectroscopy (XPS), while morphology is viewed using scanning electron microscopy (SEM). Plasma produces effective alfalfa seed hydrophilization with a variety of treatment parameters. With its potential for fine-tuning, plasma modification of seed wettability shows promise for introduction into agricultural practice.
Effect of Differently Matured Composts from Willow on Growth and Development of Lettuce
Authors: Bekier Jakub , Jamroz Elżbieta , Sowiński Józef , Adamczewska-Sowińska Katarzyna , Kałuża-Haładyn Andrea
Published: January 2022

Soil amendments from peats, brown coals and composts produced from segregated biodegradable waste or biomass from fallow land can increase soil fertility and improve soil productivity. The aim of the study was to determine the possibility of using willow (Salix viminalis L.) biomass composts as a substrate component in horticulture. The objects of the research were composts produced from willow carried out in a pile under aerobic conditions. The addition of hay and mineral nitrogen (Nmin) was used to improve process efficiency. In order to verify the type and determine fertilizing value, basic chemical parameters were analyzed (pH, total contents of C, N and P) and a pot experiment was established to analyze the germination and growth of lettuce (Lactuca sativa L.). Changes in pH, an increase in total nitrogen content (TN), phosphorus (TP) and a decrease in TOC was observed in the investigated samples. Results of the experiment showed that the highest yield was obtained from the pots with the mixture of willow, hay and Nmin. Matured composts significantly stimulated the germination and growth of the test plants. It can be concluded that the addition of hay and Nmin significantly improved composting process and increased the fertilizing value of the investigated composts.
The Triprenylated Anthranoid Ferruginin A, a Promising Scaffold for the Development of Novel Antibiotics against Gram-Positive Bacteria
Authors: Casciaro Bruno , Ghirga Francesca , Cappiello Floriana , Vergine Valeria , Loffredo Maria Rosa , Cammarone Silvia , Puglisi Elena , Tortora Carola , Quaglio Deborah , Mori Mattia , Botta Bruno , Mangoni Maria Luisa
Published: January 2022

In today’s post-antibiotic era, the search for new antimicrobial compounds is of major importance and nature represents one of the primary sources of bioactive molecules. In this work, through a cheminformatics approach, we clustered an in-house library of natural products and their derivatives based on a combination of fingerprints and substructure search. We identified the prenylated emodine-type anthranoid ferruginin A as a novel antimicrobial compound. We tested its ability to inhibit and kill a panel of Gram-positive and Gram-negative bacteria, and compared its activity with that of two analogues, vismione B and ferruanthrone. Furthermore, the capability of these three anthranoids to disrupt staphylococcal biofilm was investigated, as well as their effect on the viability of human keratinocytes. Ferruginin A showed a potent activity against both the planktonic and biofilm forms of Gram-positive bacteria (i.e., Staphylococcus aureus and S. epidermidis) and had the best therapeutic index compared to vismione B and ferruanthrone. In conclusion, ferruginin A represents a promising scaffold for the further development of valuable antimicrobial agents.
Distinction between Antimicrobial Resistance and Putative Virulence Genes Characterization in Plesiomonas shigelloides Isolated from Different Sources
Authors: Selim Samy , Almuhayawi Mohammed S. , Zakai Shadi Ahmed , Salama Ahmed Attia , Warrad Mona
Published: January 2022

Plesiomonas shigelloides are gram-negative, thermotolerant, motile, and pleomorphic microorganisms that are only distantly related to those of the Enterobacteriaceae and Vibrionaceae families. One of the most common sources of P. shigelloides contamination is human stool, but it may also be found in a wide range of other animals, plants, and aquatic habitats. Antimicrobial resistance in P. shigelloides from seawater and shellfish was investigated, and pathogenicity involved genes were characterized as part of this study. Out of 384 samples of shellfish, 5.7% included P. shigelloides. The presence of P. shigelloides was also discovered in 5% of the seawater sampled. The antimicrobial resistance of 23 P. shigelloides isolates derived from those samples was investigated. All isolates were sensitive to nalidixic acid, carbenicillin, cephalothin, erythromycin, kanamycin, tetracycline, and ciprofloxacin in the study. Several strains isolated from diseased shellfish were tested for virulence in shellfish by intraperitoneal injections. The LD50 values ranged from 12 × 108 to 3 × 1012 cfu/shellfish. When looking for possible virulence factors that may play a significant role in bacterial infection in the current study, we found that all of these genes were present in these strains. These include genes such as elastase, lipase, flagellin, enterotoxin, and DNases. According to these findings, shellfish may serve as a reservoir for multi-resistant P. shigelloides and help spread virulence genes across the environment.
Current Status of Staphylococcal Cassette Chromosome mec (SCCmec)
Authors: Uehara Yuki
Published: January 2022

Staphylococcal cassette chromosome mec (SCCmec) typing was established in the 2000s and has been employed as a tool for the molecular epidemiology of methicillin-resistant Staphylococcus aureus, as well as the evolution investigation of Staphylococcus species. Molecular cloning and the conventional sequencing of SCCmec have been adopted to verify the presence and structure of a novel SCCmec type, while convenient PCR-based SCCmec identification methods have been used in practical settings for many years. In addition, whole-genome sequencing has been widely used, and various SCCmec and similar structures have been recently identified in various species. The current status of the SCCmec types, SCCmec subtypes, rules for nomenclature, and multiple methods for identifying SCCmec types and subtypes were summarized in this review, according to the perspective of the International Working Group on the Classification of Staphylococcal Cassette Chromosome Elements.
Influence of Different Carbon Content on Reduction of Zinc Oxide via Metal Bath
Authors: Auer Michael , Wölfler Christoph , Antrekowitsch Jürgen
Published: January 2022

Electric arc furnace dust (EAFD) is an important secondary resource for the zinc industry. The most common process for its recycling is the pyro-metallurgical treatment in the Waelz process. However, this process focuses on the recycling of the zinc, whereas the recovery of other metals from the EAFD—such as iron and other alloying elements—is neglected. An up-to-date version of reprocessing can involve multi-metal recycling by means of a metal bath containing carbon. The use of a liquid iron alloy requires a higher processing temperature, which enables the reduction and melting of iron oxides as well as other compounds occurring in the dust. Furthermore, the Zn yield is higher and the reduction kinetics are faster than in the Waelz process. This paper is only focused on the zinc reduction in such a metal bath. In order to determine the influence of the carbon content in the molten metal on the reduction rate, experiments were carried out on the reduction behavior of zinc oxide using a synthetic slag. This slag, with a basicity B2 = 1, was applied to an iron bath with varying carbon contents. (0.85%, 2.16%, 2.89%, and 4.15%) The decrease in the zinc oxide concentration was monitored, along with the reaction rates calculated from these data. It was found that the reaction rate increases with rising carbon content in the melt.
Toward Optimal Control of a Multivariable Magnetic Levitation System
Authors: Majewski Paweł , Pawuś Dawid , Szurpicki Krzysztof , Hunek Wojciech P.
Published: January 2022

In the paper, a comparative case study covering different control strategies of unstable and nonlinear magnetic levitation process is investigated. Three control procedures are examined in order to fulfill the specified performance indices. Thus, a dedicated PD regulator along with the hybrid fuzzy logic PID one as well as feed-forward neural network regulator are respected and summarized according to generally understood tuning techniques. It should be emphasized that the second PID controller is strictly derived from both arbitrary chosen membership functions and those ones selected through the genetic algorithm mechanism. Simulation examples have successfully confirmed the correctness of obtained results, especially in terms of entire control process quality of the magnetic levitation system. It has been observed that the artificial-intelligence-originated approaches have outperformed the classical one in the context of control accuracy and control speed properties in contrary to the energy-saving behavior whereby the conventional method has become a leader. The feature-related compromise, which has never been seen before, along with other crucial peculiarities, is effectively discussed within this paper.
A Statistical Approach in the Analysis of Geometrical Product Specification during the Cold Tube Drawing Process
Authors: Morovic Ladislav , Kritikos Michaela , Sobrino Daynier Rolando Delgado , Bilik Jozef , Sobota Robert , Kapustova Maria
Published: January 2022

Cold tube drawing provides higher accuracy compared to hot approaches. The process can be used to reduce the dimensions of tubes, and depending on the reduction size, the wall thickness of these may be subject to changes. In the process, any form of variability provoked by external factors is highly sensitive, given that the resulting tubes are often the final step in tube production. This paper focused on the evaluation of the influence of pre-tube factors on key variables after the drawing process, i.e., the final roundness, outer diameter, and wall thickness of the tubes. For these purposes, a factorial design with fixed factors was implemented. It was also a goal to investigate if the single-pass type of drawing would guarantee good statistical results potentially leading to significant time and financial reductions. The measurements were executed in the machine ZEISS CenterMax. The statistical analysis took place on Minitab 19. The results prove that most factors, and their interactions, significantly impacted the response variables, leading the authors to understand that a single-pass approach would not properly work under the conditions defined for the experimentation. These results also allow for reflection on the causes and necessary measures related to lubrication, technological heritage, and quality that would impact the results themselves.
Automated Recognition of Chemical Molecule Images Based on an Improved TNT Model
Authors: Li Yanchi , Chen Guanyu , Li Xiang
Published: January 2022

The automated recognition of optical chemical structures, with the help of machine learning, could speed up research and development efforts. However, historical sources often have some level of image corruption, which reduces the performance to near zero. To solve this downside, we need a dependable algorithmic program to help chemists to further expand their research. This paper reports the results of research conducted for the Bristol-Myers Squibb-Molecular Translation competition, which was held on Kaggle and which invited participants to convert old chemical images to their underlying chemical structures, annotated as InChI text; we define this work as molecular translation. We proposed a model based on a transformer, which can be utilized in molecular translation. To better capture the details of the chemical structure, the image features we want to extract need to be accurate at the pixel level. TNT is one of the existing transformer models that can meet this requirement. This model was originally used for image classification, and is essentially a transformer-encoder, which cannot be utilized for generation tasks. On the other hand, we believe that TNT cannot integrate the local information of images well, so we improve the core module of TNT—TNT block—and propose a novel module—Deep TNT block—by stacking the module to form an encoder structure, and then use the vanilla transformer-decoder as a decoder, forming a chemical formula generation model based on the encoder–decoder structure. Since molecular translation is an image-captioning task, we named it the Image Captioning Model based on Deep TNT (ICMDT). A comparison with different models shows that our model has benefits in each convergence speed and final description accuracy. We have designed a complete process in the model inference and fusion phase to further enhance the final results.
Observer-Based Fault-Tolerant Predictive Control for LPV Systems with Sensor Faults: An Active Car Suspension Application
Authors: Abboudi Abdelaziz , Bououden Sofiane , Chadli Mohammed , Boulkaibet Ilyes , Neji Bilel
Published: January 2022

In this paper, an observer-based robust fault-tolerant predictive control (ORFTPC) strategy is proposed for Linear Parameter-Varying (LPV) systems subject to input constraints and sensor failures. The main objective of this work is to establish a real observer based on a virtual observer to be used to estimate both states and sensor failures of the system. The proposed virtual observer is employed to improve the observation precision and reduce the impacts of the sensor faults and the external disturbances in the LPV systems. In addition, a real observer is proposed to overcome the virtual observer margins and to ensure that all states and sensor faults of the system are properly estimated, without the need for any fault isolation modules. The proposed solution demonstrates that, using both observers, a robust fault-tolerant predictive control is established via the Lyapunov function. Moreover, sufficient stability conditions are derived using the Lyapunov approach for the convergence of the proposed robust controller. Furthermore, the proposed approach simultaneously computes the gains of the real observer and the controller from a linear matrix inequality (LMI), which is deduced from the estimation errors. Finally, the performance of the proposed approach is investigated by a simulation example of a quarter-vehicle model, and the simulation results under a sensor fault illustrate the robustness and performance of the proposed method.
Bearing Capacity near Support Areas of Continuous Reinforced Concrete Beams and High Grillages
Authors: Kos Zeljko , Klymenko Yevhenii , Karpiuk Irina , Grynyova Iryna
Published: January 2022

This work presents a proposed engineering method for calculating the bearing capacity of the supporting sections of continuous monolithic reinforced concrete tape beams, which combine pressed or driven reinforced concrete piles into a single foundation design. According to the mechanics of reinforced concrete, it is recommended to consider the grillage to be a continuous reinforced concrete beam, which, as a rule, collapses according to the punching scheme above the middle support (pile caps), with the possible formation of a plastic hinge above it. The justification for the proposed method included the results of experimental studies, comparisons of the experimental tensile shear force with the results of calculations according to the design standards of developed countries, and modeling of the stress-strain state of the continuous beam grillage in the extreme span and above the middle support-pile adverse transverse load in the form of concentrated forces. The work is important, as it reveals the physical essence of the phenomenon and significantly clarifies the physical model of the operation of inclined sections over the middle support. The authors assessed the influence of design factors in continuous research elements, and on the basis of this, the work of the investigated elements under a transverse load was simulated in the Lira-Sapr PC to clarify the stress-strain state and confirm the scheme of their destruction adopted in the physical model by the finite element method in nonlinear formulation. Based on the analysis and comparison of the experimental and simulation results, a design model was proposed for bearing capacity near the supporting sections of continuous reinforced concrete beams and high grillages that is capable of adequately determining their strength.
Condition-Based Monitoring and Maintenance: State of the Art Review
Authors: Ali Ahad , Abdelhadi Abdelhakim
Published: January 2022

Manufacturing firms face great pressure to reduce downtime as well as maintenance costs. Condition-based maintenance (CBM) can be used to effectively manage operations and maintenance by monitoring detailed machine health information. CBM policies and the development of the mathematical models have been growing recently. This paper provides a review of the theoretical and practical development in the field of condition-based maintenance and its current advancements. Standard CBM platform could make it effective and efficient in implementation and performance improvement.
Analysis of Viscosity Change and Oil Leakage Characteristics According to CaCO3 Particle Size and Anti-Sedimentation Agent Content on Bituminous Emulsion Mastic
Authors: Choi Su-Young , Kim Dong-Bum , Park Wan-Goo , Park Jin-Sang , Oh Sang-Keun
Published: January 2022

This study analyzed the characteristics of viscosity change and oil leakage stability according to the average particle size and content of organic and mineral-based extenders such as CaCO3 (CA) and anti-sedimentation (ASE) among materials consisting of bituminous emulsion mastic (BEM). The fabrication of samples for research was done using a melting method of 2 L capacity with the production mixing ratio of BEM used in the actual manufacturing process as a standard mixing ratio. Each sample size was adjusted to 16 μm, 5 μm, 2 μm, 1.4 μm and 1 μm, the average particle size of CA as a variable, and the content of ASE for each particle size was set to increase from 1 to 6 times the standard mixing ratio. The analysis found that in all average particle sizes of CA, the viscosity increased as the content of anti-sedimentation increased, and the viscosity was highest at the CA average particle size of 16 μm. The viscosity increased as the average particle size decreased at 5 μm, 2 μm, 1.4 μm and 1 μm. In addition, it was confirmed that the oil leakage stability increased as the average particle size of CA decreased, and the content of ASE increased. The evaluation results showed that specimens that met both workability and oil leakage stability conditions were the specimens with 4 times and 5 times the ASE content at the CA average particle size of 2 μm, and those with twice the ASE content at the CA average particle size of 1.4 μm.
Structural and Magnetic Properties of Nanosized Half-Doped Rare-Earth Ho0.5Ca0.5MnO3 Manganite
Authors: Geddo Lehmann Alessandra , Muscas Giuseppe , Ferretti Maurizio , Pusceddu Emanuela , Peddis Davide , Congiu Francesco
Published: January 2022

We investigated the structural and magnetic properties of 20 nm-sized nanoparticles of the half-doped manganite Ho0.5Ca0.5MnO3 prepared by sol-gel approach. Neutron powder diffraction patterns show Pbnm orthorhombic symmetry for 10 K < T < 290 K, with lattice parameters a, b, and c in the relationship c/√2 < a < b, indicating a cooperative Jahn–Teller effect, i.e., orbital ordering OO, from below room temperature. In contrast with the bulk samples, in the interval 250 < T < 300 K, the fingerprint of charge ordering (CO) does not manifest itself in the temperature dependence of lattice parameters. However, there are signs of CO in the temperature dependence of magnetization. Accordingly, below 100 K superlattice magnetic Bragg reflections arise, which are consistent with an antiferromagnetic phase strictly related to the bulk Mn ordering of a charge exchange-type (CE-type), but characterized by an increased fraction of ferromagnetic couplings between manganese species themselves. Our results show that in this narrow band half-doped manganite, size reduction only modifies the balance between the Anderson superexchange and Zener double exchange interactions, without destabilizing an overall very robust antiferromagnetic state.
Non-Destructive Multi-Method Assessment of Steel Fiber Orientation in Concrete
Authors: Kruschwitz Sabine , Oesch Tyler , Mielentz Frank , Meinel Dietmar , Spyridis Panagiotis
Published: January 2022

Integration of fiber reinforcement in high-performance cementitious materials has become widely applied in many fields of construction. One of the most investigated advantages of steel fiber reinforced concrete (SFRC) is the deceleration of crack growth and hence its improved sustainability. Additional benefits are associated with its structural properties, as fibers can significantly increase the ductility and the tensile strength of concrete. In some applications it is even possible to entirely replace the conventional reinforcement, leading to significant logistical and environmental benefits. Fiber reinforcement can, however, have critical disadvantages and even hinder the performance of concrete, since it can induce an anisotropic material behavior of the mixture if the fibers are not appropriately oriented. For a safe use of SFRC in the future, reliable non-destructive testing (NDT) methods need to be identified to assess the fibers’ orientation in hardened concrete. In this study, ultrasonic material testing, electrical impedance testing, and X-ray computed tomography have been investigated for this purpose using specially produced samples with biased or random fiber orientations. We demonstrate the capabilities of each of these NDT techniques for fiber orientation measurements and draw conclusions based on these results about the most promising areas for future research and development.