bluuebunny/crossref_metadata_2025 huggingface dataset:
Single-Step GBLUP and GWAS Analyses Suggests Implementation of Unweighted Two Trait Approach for Heat Stress in Swine
Authors: Dodd Gabriella Roby , Gray Kent , Huang Yijian , Fragomeni Breno
Published: February 2022

The purpose of this study was to perform a genome-wide association study to determine the genomic regions associated with heat stress tolerance in swine. Phenotypic information on carcass weight was available for 227,043 individuals from commercial farms in North Carolina and Missouri, U.S. Individuals were from a commercial cross of a Duroc sire and a dam resulting from a Landrace and Large White cross. Genotypic information was available for 8232 animals with 33,581 SNPs. The pedigree file contained a total of 553,448 animals. A threshold of 78 on the Temperature Humidity Index (THI) was used to signify heat stress. A two-trait analysis was used with the phenotypes heat stress (Trait One) and non-heat stress (Trait Two). Variance components were calculated via AIREML and breeding values were calculated using single step GBLUP (ssGBLUP). The heritability for Traits One and Two were calculated at 0.25 and 0.20, respectively, and the genetic correlation was calculated as 0.63. Validation was calculated for 163 genotyped sires with progeny in the last generation. The benchmark was the GEBV with complete data, and the accuracy was determined as the correlation between the GEBV of the reduced and complete data for the validation sires. Weighted ssGBLUP did not increase the accuracies. Both methods showed a maximum accuracy of 0.32 for Trait One and 0.54 for Trait Two. Manhattan Plots for Trait One, Trait Two, and the difference between the two were created from the results of the two-trait analysis. Windows explaining more than 0.8% of the genetic variance were isolated. Chromosomes 1 and 14 showed peaks in the difference between the two traits. The genetic correlation suggests a different mechanism for Hot Carcass Weight under heat stress. The GWAS results show that both traits are highly polygenic, with only a few genomic regions explaining more than 1% of variance.
Influences of L-Arginine In Ovo Feeding on the Hatchability, Growth Performance, Antioxidant Capacity, and Meat Quality of Slow-Growing Chickens
Authors: Lu Panpan , Morawong Thanidtha , Molee Amonrat , Molee Wittawat
Published: February 2022

The aim of this study was to evaluate the effects of in ovo feeding (IOF) of L-arginine (Arg) on the hatchability, growth performance, antioxidant capacity, and meat quality of slow-growing chickens. A total of 480 eggs were randomly divided into a non-injected control group (NC group) and a 1% Arg-injected group (Arg group). On day 18 of incubation, 0.5 mL of Arg solution was injected into the embryonic amnion in the Arg group. Upon hatching, 160 mixed-sex chickens were randomly assigned to two groups, with four replicates per group. This experiment lasted for 63 days. The results showed that the hatchability, growth performance, carcass traits, and meat quality were not significantly different (p > 0.05) between the two groups. However, the malondialdehyde (MDA) content was lower (p < 0.05), and the glutathione (GSH) level was higher (p < 0.05) on day of hatching in the Arg group. The total antioxidant capacity (T-AOC) activity was increased (p < 0.05) on day 21 post-hatch in the Arg group compared to that in the NC group. In conclusion, IOF of Arg increased the antioxidant capacity of the breast muscle in the starter period, which may have a positive effect on health status of slow-growing chickens post-hatch.
Persistence of Antibiotic-Resistant Escherichia coli Strains Belonging to the B2 Phylogroup in Municipal Wastewater under Aerobic Conditions
Authors: Xie Hui , Ogura Yoshitoshi , Suzuki Yoshihiro
Published: February 2022

Escherichia coli is classified into four major phylogenetic groups (A, B1, B2, and D) that are associated with antibiotic resistance genes. Although antibiotic-resistant E. coli is commonly detected in municipal wastewater, little is known about the relationship between the phylogenetic groups and antibiotic-resistant E. coli in wastewater. In this study, the survival of E. coli in wastewater and the changes to the relationships between each phylogroup and the antibiotic-resistant profiles of E. coli isolates from wastewater were investigated under aerobic conditions for 14 days. The isolates were classified into the phylogroups A, B1, B2, and D or others by multiplex PCR. In addition, the susceptibility of the isolates to 11 antibiotics was assessed with the minimum inhibitory concentration (MIC) assay. While E. coli counts decreased in the wastewater with time under aerobic conditions, the prevalence of phylogroup B2 had increased to 73% on day 14. Furthermore, the MIC assay revealed that the abundance of antibiotic-resistant E. coli also increased on day 14. After batch-mixing the experiments under aerobic conditions, the surviving antibiotic-resistant E. coli included mainly multidrug-resistant and beta-lactamase-producing isolates belonging to phylogroup B2. These results suggest that the phylogroup B2 isolates that have acquired antibiotic resistance had a high survivability in the treated wastewater.
Adopting a High-Polyphenolic Diet Is Associated with an Improved Glucose Profile: Prospective Analysis within the PREDIMED-Plus Trial
Authors: Tresserra-Rimbau Anna , Castro-Barquero Sara , Becerra-Tomás Nerea , Babio Nancy , Martínez-González Miguel Ángel , Corella Dolores , Fitó Montserrat , Romaguera Dora , Vioque Jesús , Alonso-Gomez Angel M. , Wärnberg Julia , Martínez José Alfredo , Serra-Majem Luís , Estruch Ramon , Tinahones Francisco J. , Lapetra José , Pintó Xavier , Tur Josep A. , López-Miranda José , Cano-Ibáñez Naomi , Delgado-Rodríguez Miguel , Matía-Martín Pilar , Daimiel Lidia , Martín Sánchez Vicente , Vidal Josep , Vázquez Clotilde , Ros Emili , Basterra Francisco Javier , Fernández de la Puente María , Asensio Eva M. , Castañer Olga , Bullón-Vela Vanessa , Tojal-Sierra Lucas , Gómez-Gracia Enrique , Cases-Pérez Eugenio , Konieczna Jadwiga , García-Ríos Antonio , Casañas-Quintana Tamara , Bernal-Lopez María Rosa , Santos-Lozano José Manuel , Esteve-Luque Virginia , Bouzas Cristina , Vázquez-Ruiz Zenaida , Palau-Galindo Antoni , Barragan Rocio , López Grau Mercè , Razquín Cristina , Goicolea-Güemez Leire , Toledo Estefanía , Vergaz Manel Vila , Lamuela-Raventós Rosa M. , Salas-Salvadó Jordi
Published: February 2022

Previous studies suggested that dietary polyphenols could reduce the incidence and complications of type-2 diabetes (T2D); although the evidence is still limited and inconsistent. This work analyzes whether changing to a diet with a higher polyphenolic content is associated with an improved glucose profile. At baseline, and at 1 year of follow-up visits, 5921 participants (mean age 65.0 ± 4.9, 48.2% women) who had overweight/obesity and metabolic syndrome filled out a validated 143-item semi-quantitative food frequency questionnaire (FFQ), from which polyphenol intakes were calculated. Energy-adjusted total polyphenols and subclasses were categorized in tertiles of changes. Linear mixed-effect models with random intercepts (the recruitment centers) were used to assess associations between changes in polyphenol subclasses intake and 1-year plasma glucose or glycosylated hemoglobin (HbA1c) levels. Increments in total polyphenol intake and some classes were inversely associated with better glucose levels and HbA1c after one year of follow-up. These associations were modified when the analyses were run considering diabetes status separately. To our knowledge, this is the first study to assess the relationship between changes in the intake of all polyphenolic groups and T2D-related parameters in a senior population with T2D or at high-risk of developing T2D.
Bone Regeneration and Oxidative Stress: An Updated Overview
Authors: Bădilă Adrian Emilian , Rădulescu Dragos Mihai , Ilie Andrei , Niculescu Adelina-Gabriela , Grumezescu Alexandru Mihai , Rădulescu Adrian Radu
Published: February 2022

Bone tissue engineering is a complex domain that requires further investigation and benefits from data obtained over past decades. The models are increasing in complexity as they reveal new data from co-culturing and microfluidics applications. The in vitro models now focus on the 3D medium co-culturing of osteoblasts, osteoclasts, and osteocytes utilizing collagen for separation; this type of research allows for controlled medium and in-depth data analysis. Oxidative stress takes a toll on the domain, being beneficial as well as destructive. Reactive oxygen species (ROS) are molecules that influence the differentiation of osteoclasts, but over time their increasing presence can affect patients and aid the appearance of diseases such as osteoporosis. Oxidative stress can be limited by using antioxidants such as vitamin K and N-acetyl cysteine (NAC). Scaffolds and biocompatible coatings such as hydroxyapatite and bioactive glass are required to isolate the implant, protect the zone from the metallic, ionic exchange, and enhance the bone regeneration by mimicking the composition and structure of the body, thus enhancing cell proliferation. The materials can be further functionalized with growth factors that create a better response and higher chances of success for clinical use. This review highlights the vast majority of newly obtained information regarding bone tissue engineering, such as new co-culturing models, implant coatings, scaffolds, biomolecules, and the techniques utilized to obtain them.
Increased Ingestion of Hydroxy-Methionine by Both Sows and Piglets Improves the Ability of the Progeny to Counteract LPS-Induced Hepatic and Splenic Injury with Potential Regulation of TLR4 and NOD Signaling
Authors: Liu Meng , Zhang Ying , Cao Ke-Xin , Yang Ren-Gui , Xu Bao-Yang , Zhang Wan-Po , Batonon-Alavo Dolores I. , Zhang Shu-Jun , Sun Lv-Hui
Published: February 2022

Methionine, as an essential amino acid, play roles in antioxidant defense and the regulation of immune responses. This study was designed to determine the effects and mechanisms of increased consumption of methionine by sows and piglets on the capacity of the progeny to counteract lipopolysaccharide (LPS) challenge-induced injury in the liver and spleen of piglets. Primiparous sows (n = 10/diet) and their progeny were fed a diet that was adequate in sulfur amino acids (CON) or CON + 25% total sulfur amino acids as methionine from gestation day 85 to postnatal day 35. A total of ten male piglets were selected from each treatment and divided into 2 groups (n = 5/treatment) for a 2 × 2 factorial design [diets (CON, Methionine) and challenge (saline or LPS)] at 35 d old. After 24 h challenge, the piglets were euthanized to collect the liver and spleen for the histopathology, redox status, and gene expression analysis. The histopathological results showed that LPS challenge induced liver and spleen injury, while dietary methionine supplementation alleviated these damages that were induced by the LPS challenge. Furthermore, the LPS challenge also decreased the activities of GPX, SOD, and CAT and upregulated the mRNA and(or) protein expression of TLR4, MyD88, TRAF6, NOD1, NOD2, NF-kB, TNF-α, IL-8, p53, BCL2, and COX2 in the liver and (or) spleen. The alterations of GPX and SOD activities and the former nine genes were prevented or alleviated by the methionine supplementation. In conclusion, the maternal and neonatal dietary supplementation of methionine improved the ability of piglets to resist LPS challenge-induced liver and spleen injury, potentially through the increased antioxidant capacity and inhibition of TLR4 and NOD signaling pathway.
The Uncoupling Proteins: A Systematic Review on the Mechanism Used in the Prevention of Oxidative Stress
Authors: Hirschenson Jonathan , Melgar-Bermudez Emiliano , Mailloux Ryan J.
Published: February 2022

Mitochondrial uncoupling proteins (UCP) 1-3 fulfill many physiological functions, ranging from non-shivering thermogenesis (UCP1) to glucose-stimulated insulin release (GSIS) and satiety signaling (UCP2) and muscle fuel metabolism (UCP3). Several studies have suggested that UCPs mediate these functions by facilitating proton return to the matrix. This would decrease protonic backpressure on the respiratory chain, lowering the production of hydrogen peroxide (H2O2), a second messenger. However, controlling mitochondrial H2O2 production to prevent oxidative stress by activating these leaks through these proteins is still enthusiastically debated. This is due to compelling evidence that UCP2/3 fulfill other function(s) and the inability to reproduce findings that UCP1-3 use inducible leaks to control reactive oxygen species (ROS) production. Further, other studies have found that UCP2/3 may serve as Ca2+. Therefore, we performed a systematic review aiming to summarize the results collected on the topic. A literature search using a list of curated keywords in Pubmed, BIOSIS Citation Index and Scopus was conducted. Potentially relevant references were screened, duplicate references eliminated, and then literature titles and abstracts were evaluated using Rayyan software. A total of 1101 eligible studies were identified for the review. From this total, 416 studies were evaluated based on our inclusion criteria. In general, most studies identified a role for UCPs in preventing oxidative stress, and in some cases, this may be related to the induction of leaks and lowering protonic backpressure on the respiratory chain. However, some studies also generated evidence that UCP2/3 may mitigate oxidative stress by transporting Ca2+ into the matrix, exporting lipid hydroperoxides, or by transporting C-4 metabolites. Additionally, some showed that activating UCP1 or 3 can increase mitochondrial ROS production, even though there is still augmented protection from oxidative stress. Conclusion: Overall, most available studies demonstrate that UCPs, particularly UCP2/3, prevent oxidative stress. However, the mechanism utilized to do so remains elusive and raises the question that UCP2/3 should be renamed, since they may still not be true “uncoupling proteins”.
Systemic Effects of mitoTEMPO upon Lipopolysaccharide Challenge Are Due to Its Antioxidant Part, While Local Effects in the Lung Are Due to Triphenylphosphonium
Authors: Weidinger Adelheid , Birgisdóttir Linda , Schäffer Julia , Meszaros Andras T. , Zavadskis Sergejs , Müllebner Andrea , Hecker Matthias , Duvigneau Johanna Catharina , Sommer Natascha , Kozlov Andrey V.
Published: February 2022

Mitochondria-targeted antioxidants (mtAOX) are a promising treatment strategy against reactive oxygen species-induced damage. Reports about harmful effects of mtAOX lead to the question of whether these could be caused by the carrier molecule triphenylphosphonium (TPP). The aim of this study was to investigate the biological effects of the mtAOX mitoTEMPO, and TPP in a rat model of systemic inflammatory response. The inflammatory response was induced by lipopolysaccharide (LPS) injection. We show that mitoTEMPO reduced expression of inducible nitric oxide synthase in the liver, lowered blood levels of tissue damage markers such as liver damage markers (aspartate aminotransferase and alanine aminotransferase), kidney damage markers (urea and creatinine), and the general organ damage marker, lactate dehydrogenase. In contrast, TPP slightly, but not significantly, increased the LPS-induced effects. Surprisingly, both mitoTEMPO and TPP reduced the wet/dry ratio in the lung after 24 h. In the isolated lung, both substances enhanced the increase in pulmonary arterial pressure induced by LPS observed within 3 h after LPS treatments but did not affect edema formation at this time. Our data suggest that beneficial effects of mitoTEMPO in organs are due to its antioxidant moiety (TEMPO), except for the lung where its effects are mediated by TPP.
Metro Emergency Passenger Flow Prediction on Transfer Learning and LSTM Model
Authors: Ma Jingye , Zeng Xin , Xue Xiaoping , Deng Ranran
Published: February 2022

The metro transportation system will have emergency passenger flow for various reasons, resulting in passenger flow congestion, affecting efficiency and risks. In this paper, the LSTM network is applied to predict the normal passenger flow and emergency passenger flow of metro transportation based on transfer learning to solve the imbalanced data set problem when the amount of emergency samples is too small. The results show that under normal and emergency conditions, the average prediction error is less than 5%, which provides an alarm for the operating company to take preventive measures in advance. Compared with the strategy without transfer learning, it proves that the strategy proposed in this paper has advantages in predicting emergency conditions.
Effect of Vanadium and Rare Earth on the Structure, Phase Transformation Kinetics and Mechanical Properties of Carbide-Free Bainitic Steel Containing Silicon
Authors: Garmeh Behdad , Kasiri-Asgarani Masoud , Amini Kamran , Ghayour Hamid , Bakhsheshi-Rad Hamid Reza , Berto Filippo
Published: February 2022

Carbide-free bainitic (CFB) steels with a matrix of bainitic ferrite and thin layers of retained austenite, to reduce the manufacturing costs, usually do not contain alloying elements. However, a few reports were presented regarding the effect of alloying elements on the properties of these steels. Thus, this study evaluates the effects of vanadium and rare earth (Ce-La) microalloying elements on the structure, phase transformation kinetics, and mechanical properties of carbide-free bainite steel containing silicon fabricated by the casting and austempering procedure. Optical and scanning electron microscopy (OM and SEM), electron backscatter diffraction (EBSD), and X-ray diffraction (XRD) were used to study the microstructure and phase structure. The transformation kinetics were examined by a dilatometry test. Hardness, tensile, and impact tests evaluated the mechanical properties. Due to adding alloying elements, the fracture toughness and change in matrix phases relation was studied by the crack tip opening displacement (CTOD) test and SEM fractography. The microstructure of the silicon added sample was completely carbide-free bainite. The test results showed vanadium helped CFB formation, even in continuous cooling. The primary austenite grain (PAG) size grew by vanadium addition. The EBSD phase map illustrates an increment in the percentage of retained austenite by vanadium. In contrast, the addition of 0.03 wt% rare earth reduced the primary austenite grain size and reduced the retained austenite content. The results of the dilatometry test confirmed that vanadium and rare earth addition both reduced the critical cooling rate of the bainite transformation. Vanadium leads to an earlier cessation of bainite transformation, while rare earth elements postpone this transformation. Mechanical tests showed that the tensile strength of carbide-free bainite steels was strongly influenced by the morphology and volume fraction of austenite. Retained austenite, when transformed to martensite during the transformation-induced plasticity (TRIP) phenomenon, leads to increased tensile strength and fracture toughness, or retained austenite with a film-like shape prevents the growth of cracks by blinding the crack tip. The result of the CTOD test exhibited that retained austenite plays the leading role in increasing crack resistance when TRIP occurs.
CKGAT: Collaborative Knowledge-Aware Graph Attention Network for Top-N Recommendation
Authors: Xu Zhuoming , Liu Hanlin , Li Jian , Zhang Qianqian , Tang Yan
Published: February 2022

Knowledge graph-based recommendation methods are a hot research topic in the field of recommender systems in recent years. As a mainstream knowledge graph-based recommendation method, the propagation-based recommendation method captures users’ potential interests in items by integrating the representations of entities and relations in the knowledge graph and the high-order connection patterns between entities to provide personalized recommendations. For example, the collaborative knowledge-aware attentive network (CKAN) is a typical state-of-the-art propagation-based recommendation method that combines user-item interactions and knowledge associations in the knowledge graph, and performs heterogeneous propagation in the knowledge graph to generate multi-hop ripple sets, thereby capturing users’ potential interests. However, existing propagation-based recommendation methods, including CKAN, usually ignore the complex relations between entities in the multi-hop ripple sets and do not distinguish the importance of different ripple sets, resulting in inaccurate user potential interests being captured. Therefore, this paper proposes a top-N recommendation method named collaborative knowledge-aware graph attention network (CKGAT). Based on the heterogeneous propagation strategy, CKGAT uses the knowledge-aware graph attention network to extract the topological proximity structures of entities in the multi-hop ripple sets and then learn high-order entity representations, thereby generating refined ripple set embeddings. CKGAT further uses an attention aggregator to perform weighted aggregation on the ripple set embeddings, the user/item initial entity set embeddings, and the original representations of items to generate accurate user embeddings and item embeddings for the top-N recommendations. Experimental results show that CKGAT, overall, outperforms three baseline methods and six state-of-the-art propagation-based recommendation methods in terms of recommendation accuracy, and outperforms four representative propagation-based recommendation methods in terms of recommendation diversity.
Crop Classification for Agricultural Applications in Hyperspectral Remote Sensing Images
Authors: Agilandeeswari Loganathan , Prabukumar Manoharan , Radhesyam Vaddi , Phaneendra Kumar L. N. Boggavarapu , Farhan Alenizi
Published: February 2022

Hyperspectral imaging (HSI), measuring the reflectance over visible (VIS), near-infrared (NIR), and shortwave infrared wavelengths (SWIR), has empowered the task of classification and can be useful in a variety of application areas like agriculture, even at a minor level. Band selection (BS) refers to the process of selecting the most relevant bands from a hyperspectral image, which is a necessary and important step for classification in HSI. Though numerous successful methods are available for selecting informative bands, reflectance properties are not taken into account, which is crucial for application-specific BS. The present paper aims at crop mapping for agriculture, where physical properties of light and biological conditions of plants are considered for BS. Initially, bands were partitioned according to their wavelength boundaries in visible, near-infrared, and shortwave infrared regions. Then, bands were quantized and selected via metrics like entropy, Normalized Difference Vegetation Index (NDVI), and Modified Normalized Difference Water Index (MNDWI) from each region, respectively. A Convolutional Neural Network was designed with the finer generated sub-cube to map the selective crops. Experiments were conducted on two standard HSI datasets, Indian Pines and Salinas, to classify different types of crops from Corn, Soya, Fallow, and Romaine Lettuce classes. Quantitatively, overall accuracy between 95.97% and 99.35% was achieved for Corn and Soya classes from Indian Pines; between 94.53% and 100% was achieved for Fallow and Romaine Lettuce classes from Salinas. The effectiveness of the proposed band selection with Convolutional Neural Network (CNN) can be seen from the resulted classification maps and ablation study.
Robust ADP-Based Sliding-Mode Fault-Tolerant Control for Nonlinear Systems with Application to Spacecraft
Authors: Du Yanbin , Jiang Bin , Ma Yajie , Cheng Yuehua
Published: February 2022

This paper considers a novel fault-tolerant control (FTC) scheme for a category of cascade nonlinear systems with mismatched uncertainties and unknown actuator faults. The robust adaptive dynamic programming (RADP) is used to design a novel optimal sliding surface (SS) off-line, which renders the corresponding sliding-mode dynamics able to obtain robustness of stability to mismatched uncertainties. Subsequently, a simple sliding-mode control (SMC) with the adaptive fault compensation is developed to guarantee reachability of the sliding mode. Then, it is proven that the weight errors of neural networks (NN) of RADP and the closed-loop system are stable based on Lyapunov stability theory. In the simulation section, this proposed scheme is used to deal with the attitude FTC of a spacecraft, and simulation results verify the effectiveness of the proposed novel control scheme.
Randomized Trial of Feasibility and Preliminary Effectiveness of PerioTabs® on Periodontal Diseases
Authors: Alkan Begum , Özcan Mutlu
Published: February 2022

This double-blinded and split-mouth design, randomized feasibility study aimed to assess the efficacy of prophylactic and therapeutic use of a new age NitrAdineTM-based brushing solution (PerioTabs®) on the clinical parameters before and after periodontal therapy. Four subjects were randomly assigned to two treatment groups according to periodontal infection: PerioTabs® and placebo. At the first appointment, a split-mouth scaling was performed in all participants. All oral care instructions concerning the use of effervescent tablets were explained to the participants in detail. The morning after the tablets were finished, a full-mouth scaling was completed in all participants. All parameters were recorded at 0, 11, and 40 days. According to the results, both the therapeutic and prophylactic interventions showed similar impacts on the gingival index and probing depth compared to the placebo in all patients. The bleeding on probing was further reduced at the PerioTabs® group at baseline until day 40 compared to the placebo in the gingivitis patients with both interventions; at both 11 and 40 days in the periodontitis patients receiving the therapeutic intervention; and at baseline to day 40 in the periodontitis group receiving the prophylactic intervention. While the preliminary results of this new-age brushing solution appear to be a promising approach for a future therapy of periodontal diseases, further research on a larger sample size is needed to draw firm conclusions.
Three-Dimensional Convolutional Neural Network on Multi-Temporal Synthetic Aperture Radar Images for Urban Flood Potential Mapping in Jakarta
Authors: Riyanto Indra , Rizkinia Mia , Arief Rahmat , Sudiana Dodi
Published: February 2022

Flooding in urban areas is counted as a significant disaster that must be correctly mitigated due to the huge amount of affected people, material losses, hampered economic activity, and flood-related diseases. One of the technologies available for disaster mitigation and prevention is satellites providing image data on previously flooded areas. In most cases, floods occur in conjunction with heavy rain. Thus, from a satellite’s optical sensor, the flood area is mostly covered with clouds which indicates ineffective observation. One solution to this problem is to use Synthetic Aperture Radar (SAR) sensors by observing backscatter differences before and after flood events. This research proposes mapping the flood-prone areas using machine learning to classify the areas using the 3D CNN method. The method was applied on a combination of co-polarized and cross-polarized SAR multi-temporal image datasets covering Jakarta City and the coastal area of Bekasi Regency. Testing with multiple combinations of training/testing data proportion split and a different number of epochs gave the optimum performance at an 80/20 split with 150 epochs achieving an overall accuracy of 0.71 after training in 283 min.
Detection of Geomagnetic Signals as Precursors to Some Earthquakes in China
Authors: Yao Xiuyi , Wang Wanqing , Teng Yuntian
Published: February 2022

Extracting weak seismic-magnetic signals from strong electromagnetic backgrounds has always been an important part of seismic-electromagnetic research. Based on the data of D/H/Z components measured through a three-axis ring-core-type fluxgate magnetometer in GLM (Geermu), JYG (Jiayuguan), and KSH (Kashi) observatories, we analyzed geomagnetic signals as precursors to some earthquakes in China using the polarization method. The most effective main frequency of seismic-electromagnetic emission was determined according to the skin effect. The results showed that only 5 out of 37 earthquakes were found to have probable signals of seismomagnetic anomalies before them. Further research revealed that the significant enhancements of polarization ratios of YZH and YZG (YZH, the spectral power ratio of Z to H and YZG, the spectral power ratio of Z to G) occurred five days prior to the Jinta earthquake (Ms 5.4) and continued for about two months. The polarization ratio of YZH reached an abnormally high value about one month before some earthquakes (Ms 7.4, Ms 6.7, Ms 6.7) near the KSH station and lasted for about one week to half a month, then returned to the normal value. Similarly, some enhancements of polarization ratios of YZH and YZG occurred two months before the Haixi earthquake (Ms 5.0) and lasted for about one month. Analysis results showed that the enhancements prior to earthquake events may be closely related to the Jinta earthquake and a series of earthquakes near the KSH station; however, the high value of YZH and YZG in GLM station had nothing to do with the Haixi earthquake.
Human–Machine Systems Reliability: A Series–Parallel Approach for Evaluation and Improvement in the Field of Machine Tools
Authors: Amaya-Toral Rosa Ma , Piña-Monarrez Manuel R. , Reyes-Martínez Rosa María , de la Riva-Rodríguez Jorge , Poblano-Ojinaga Eduardo Rafael , Sánchez-Leal Jaime , Arredondo-Soto Karina Cecilia
Published: February 2022

Machine workshops generate high scrap rates, causing non-compliance with timely delivery and high production costs. Due to their natural characteristics of a low volume, high-mix production batches, and serial and parallel configurations, generally the causes of their failure are not well documented. Thus, to reduce the scrap rate, and evaluate and improve their reliability, their system characteristics must be considered. Based on them, our proposed methodology allows us to evaluate the system, subsystem, and component–subsystem relationship by using either the Weibull and/or the exponential distribution. The strategy to improve the system performance includes reliability tools, expert interviews, cluster analysis, and root-cause analysis. In the application case, the failure sources were found to be mechanical and human errors. The component maintenance/setup, institutional conditions/attitude, and subsystem process/operation were the machine factors that presented the lowest reliability indices. The improved activities were monitored based on the Weibull β and η parameters that affect the system reliability. Finally, by using a life–effort analysis, and the method of comparative analysis of two sequential periods, we identified the causes that generated a change in the Weibull parameters. The contribution of this methodology lies in the grouping of the tools in the proposed application context.
New Approach to Nonlinear Dynamic Analysis of Reinforced Concrete 3D Frames; An Accurate and Computational Efficient Mathematical Model
Authors: Munteanu Ruben Iacob , Moţa Florin , Calofir Vasile , Baciu Cătălin
Published: February 2022

The structural engineering community often deals with the issue of inelastic incursions of the structural response. Although buildings situated in seismic regions are usually designed using elastic analysis, most encounter significant inelastic deformations when major events occur. In general, material nonlinearity is the most important source of nonlinearity considered in the dynamic analysis commonly performed in structural design. In this paper, the recent concept of the force analogy method for 3D structures is developed and integrated into an accurate computational efficient algorithmic routine for nonlinear dynamic analysis of reinforced concrete frames. Moreover, a unique straightforward mathematical model for the numerical implementation of degrading cyclic behavior of structural elements is proposed and further used to simulate the response of a 10 story reinforced concrete frame structure. A set of nonlinear dynamic analyses are performed using the proposed algorithm in order to assess the structural damage in case of different peak ground accelerations seismic recordings. The seismic structural damage is evaluated using both structural response parameters expressed in terms of displacement and energy concepts.
Image-Based Learning Using Gradient Class Activation Maps for Enhanced Physiological Interpretability of Motor Imagery Skills
Authors: Collazos-Huertas Diego F. , Álvarez-Meza Andrés M. , Castellanos-Dominguez German
Published: February 2022

Brain activity stimulated by the motor imagery paradigm (MI) is measured by Electroencephalography (EEG), which has several advantages to be implemented with the widely used Brain–Computer Interfaces (BCIs) technology. However, the substantial inter/intra variability of recorded data significantly influences individual skills on the achieved performance. This study explores the ability to distinguish between MI tasks and the interpretability of the brain’s ability to produce elicited mental responses with improved accuracy. We develop a Deep and Wide Convolutional Neuronal Network fed by a set of topoplots extracted from the multichannel EEG data. Further, we perform a visualization technique based on gradient-based class activation maps (namely, GradCam++) at different intervals along the MI paradigm timeline to account for intra-subject variability in neural responses over time. We also cluster the dynamic spatial representation of the extracted maps across the subject set to come to a deeper understanding of MI-BCI coordination skills. According to the results obtained from the evaluated GigaScience Database of motor-evoked potentials, the developed approach enhances the physiological explanation of motor imagery in aspects such as neural synchronization between rhythms, brain lateralization, and the ability to predict the MI onset responses and their evolution during training sessions.
Exergy-Based Thermo-Hydraulic Performance of Roughened Absorber in Solar Air Heater Duct
Authors: Alam Tabish , Siddiqui Md Irfanul Haque , Alshehri Hassan , Ali Masood Ashraf , Blecich Paolo , Saurabh Kushagra
Published: February 2022

This paper presents the thermo-hydraulic performance of small conical ribs on the absorber plate of a solar energy air heater (SAH) using exergy analysis. Application of conical protrusion ribs on the absorber is an attractive solution for enhancing the thermal performance of a SAH. However, these ribs are also responsible for high friction losses and increased fan power consumption caused by the turbulent air flow. To optimize the rib design, it is vital to consider both thermal and hydraulic performance at the same time. The SAH was assessed using an analytic method which predicts the exergy efficiency under operating parameters (e.g., Reynolds number, solar insolation and temperature increase parameter). The following geometric quantities of ribs were evaluated for optimum exergy efficiency: the relative rib height (e/D), which was in the range between 0.200 and 0.044, and the relative rib pitch (p/e), which was in the range between 6 and 12. The combination of a relative rib height of 0.044 and relative rib pitch of 10 exhibits the highest exergy efficiency of 0.0202. The optimization of the rib geometric quantities parameters was performed by considering the temperature increase parameter, aiming to achieve maximum exergy efficiency. The combination of rib parameters e/D = 0.044 and p/e = 10 are noted to yield best performance when operating at a temperature increase parameter above 0.0141 K∙m2/W.
Fast Identification of the Failure of Heavy-Duty Diesel Particulate Filters Using a Low-Cost Condensation Particle Counter (CPC) Based System
Authors: Ge Zihao , Zhao Weirui , Lyu Liqun , Zhu Ziru
Published: February 2022

The penetration of diesel particulate filters (DPFs) in the market is growing fast. However, in the current inspection/maintenance (I/M) regulation for these vehicles, particulate emissions were capped with smoke opacity, which is incompetent to identify the excessive particle number (PN) induced by non-major DPF failures such as small cracks in substrate. This research aimed at developing a fast identification method for such malfunctioning vehicles using a low-cost condensation particle counter (CPC). To verify the effectiveness of idle PN test, 33 China-5 and China-6 heavy-duty vehicles fueled with diesel and natural gas (NG) were tested using the regulatory portable emission measurement system (PEMS) as per China-6 protocol and idle PN tests using a low-cost CPC-based system. PN emissions from China-6 vehicles with malfunctioning DPFs were at a similar level to those from China-5 vehicles (without DPF), which were significantly higher than the proper counterparts. Idle PN tests using a CPC-based system managed to identify the vehicles with DPF failures. Volumetric PN concentrations of these vehicles were much higher than those of the proper ones. This study proved that an easy, fast, and low-cost procedure could be used to screen out those high emitters with DPF failure.
Human Bioclimate Analysis for the Paris Olympic Games
Authors: Matzarakis Andreas , Graw Kathrin
Published: February 2022

Weather and climate conditions can be important and a decision factor for travel plans or outdoor and sport events. It is important to quantify thermal comfort and other related climate factors for different applications and destinations and make the results easily accessible to visitors and sport attendees. This analysis has provided and quantified thermal comfort, heat stress and other climate-related factors. A relevant approach is the visualization of climate thresholds in a Climate-Tourism/Transfer-Information Scheme (CTIS) for the prevailing local climate conditions. The methodology provided here is a possible gold standard of good human biometeorological practices for tourism, recreation and sports, and can be applied for all major events. The information provided on the local climate can be extracted by non-experts such as tourists intending to attend sports events.
Poor Visibility in Winter Due to Synergistic Effect Related to Fine Particulate Matter and Relative Humidity in the Taipei Metropolis, Taiwan
Authors: Lai Li-Wei
Published: February 2022

Visibility is important because it influences transportation safety. This study examined the relationships among sea–land breezes, relative humidity (RH), and the urban heat island (UHI) effect. The study also sought to understand how the synergistic effects of fine particulate matter (PM2.5) and RH influence visibility. Hourly meteorological, PM2.5 concentration, and visibility data from 2016 to 2019 were obtained from government-owned stations. This study used quadratic equations, exponential functions, and multi-regression models, along with a comparison test, to analyse the relationships between these variables. While sea breezes alone cannot explain the presence of PM2.5, UHI circulation coupled with sea breezes during winter can promote the accumulation of PM2.5. The synergistic effects of RH, PM2,5, and aerosol hygroscopicity exist in synoptic patterns type I and type III. PM2.5 was negatively correlated with visibility in the winter, when the RH was 67–95% and the continental cold high-pressure (CCHP) system was over the Asian continent (type I), or when the RH was 49–89% and the CCHP had moved eastward, with its centre located beyond 125° E (type III). The synergistic predictor variable PM2.5×RH was more important than PM2.5 and RH individually in explaining the variation in visibility.
Electron Impact Excitation of Ge-like Te20+–Cd16+ Ions
Authors: Malker Pooja , Sharma Lalita
Published: February 2022

We study electron impact excitation of dipole allowed transitions in the extreme ultraviolet range—8–55 nm—for the germanium isoelectronic sequence Te20+–Cd16+. The fine structure transitions between the ground state having configuration 4s24p2 and the excited states with configurations 4s4p3 and 4s24p4d are considered for these ions. We employ the relativistic distorted wave method to calculate the excitation cross sections in the incident electron energy range from the excitation threshold to 5000 eV. To obtain the required ionic bound state wavefunctions we have used the multi-configuration Dirac-Fock method with correlations within the n = 5 complexes as well as performed relativistic configuration interaction calculations to include the quantum electrodynamic effects. The accuracy of these wavefunctions is established by comparing our calculated wavelengths and oscillator strengths of the considered transitions with the previously reported measurements and other available theoretical results. We also provide the fitting parameters of the calculated cross sections and the excitation rate coefficients for their direct applications in plasma modeling.
Big Data in Construction: Current Applications and Future Opportunities
Authors: Munawar Hafiz Suliman , Ullah Fahim , Qayyum Siddra , Shahzad Danish
Published: February 2022

Big data have become an integral part of various research fields due to the rapid advancements in the digital technologies available for dealing with data. The construction industry is no exception and has seen a spike in the data being generated due to the introduction of various digital disruptive technologies. However, despite the availability of data and the introduction of such technologies, the construction industry is lagging in harnessing big data. This paper critically explores literature published since 2010 to identify the data trends and how the construction industry can benefit from big data. The presence of tools such as computer-aided drawing (CAD) and building information modelling (BIM) provide a great opportunity for researchers in the construction industry to further improve how infrastructure can be developed, monitored, or improved in the future. The gaps in the existing research data have been explored and a detailed analysis was carried out to identify the different ways in which big data analysis and storage work in relevance to the construction industry. Big data engineering (BDE) and statistics are among the most crucial steps for integrating big data technology in construction. The results of this study suggest that while the existing research studies have set the stage for improving big data research, the integration of the associated digital technologies into the construction industry is not very clear. Among the future opportunities, big data research into construction safety, site management, heritage conservation, and project waste minimization and quality improvements are key areas.
Alginate Core–Shell Capsules for 3D Cultivation of Adipose-Derived Mesenchymal Stem Cells
Authors: Nebel Sabrina , Lux Manuel , Kuth Sonja , Bider Faina , Dietrich Wolf , Egger Dominik , Boccaccini Aldo R. , Kasper Cornelia
Published: February 2022

Mesenchymal stem cells (MSCs) are primary candidates in tissue engineering and stem cell therapies due to their intriguing regenerative and immunomodulatory potential. Their ability to self-assemble into three-dimensional (3D) aggregates further improves some of their therapeutic properties, e.g., differentiation potential, secretion of cytokines, and homing capacity after administration. However, high hydrodynamic shear forces and the resulting mechanical stresses within commercially available dynamic cultivation systems can decrease their regenerative properties. Cells embedded within a polymer matrix, however, lack cell-to-cell interactions found in their physiological environment. Here, we present a “semi scaffold-free” approach to protect the cells from high shear forces by a physical barrier, but still allow formation of a 3D structure with in vivo-like cell-to-cell contacts. We highlight a relatively simple method to create core–shell capsules by inverse gelation. The capsules consist of an outer barrier made from sodium alginate, which allows for nutrient and waste diffusion and an inner compartment for direct cell-cell interactions. Next to capsule characterization, a harvesting procedure was established and viability and proliferation of human adipose-derived MSCs were investigated. In the future, this encapsulation and cultivation technique might be used for MSC-expansion in scalable dynamic bioreactor systems, facilitating downstream procedures, such as cell harvest and differentiation into mature tissue grafts.
The Efficacies of 1-Methylcyclopropene and Chitosan Nanoparticles in Preserving the Postharvest Quality of Damask Rose and Their Underlying Biochemical and Physiological Mechanisms
Authors: Ali Esmat F. , Issa Ahmed A. , Al-Yasi Hatim M. , Hessini Kamel , Hassan Fahmy A. S.
Published: February 2022

Preserving the flower shelf life of damask rose is a crucial matter in promoting its economic viability. Chitosan nanoparticles (CSNPs) and 1-methylcyclopropene (1-MCP) may potentially decrease the postharvest loss of several horticultural commodities, but no findings on damask rose have been published. Therefore, the aim of this research was to study the effect of 1-MCP (400 mg m−3) and either the pre- or postharvest application of CSNPs (1%) on maintaining the quality of damask rose flowers during storage at 4 or 20 °C. The shelf life of damask rose has been significantly extended, along with a reduction in weight loss due to 1-MCP, CSNPs and pre-CSNP treatments. 1-MCP or CSNP applications have resulted in a higher relative water content, volatile oil, total anthocyanins, total carotenoids, total phenolics and antioxidant activity. Ethylene evolution, H2O2 generation and malondialdehyde content were significantly decreased due to 1-MCP or CSNPs treatment, and hence, the cell membrane functions have been maintained. The 1-MCP or CSNP-treated flowers have shown higher activities of catalase and ascorbate peroxidase and lower activities of polyphenol oxidase and lipoxygenase in comparison to untreated flowers. Our results showed that the postharvest application of 1-MCP or CSNPs is a very promising method to maintain the postharvest quality of damask rose during storage.
Invasion of African Clarias gariepinus Drives Genetic Erosion of the Indigenous C. batrachus in Bangladesh
Authors: Parvez Imran , Rumi Rukaya Akter , Ray Purnima Rani , Hassan Mohammad Mahbubul , Sultana Shirin , Pervin Rubaiya , Suwanno Suvit , Pradit Siriporn
Published: February 2022

The African catfish Clarias gariepinus has been introduced for aquaculture in Bangladesh due to the scarcity of indigenous C. batrachus fingerlings. However, the government of Bangladesh has banned the farming of C. gariepinus due to the carnivorous nature of this species. Recently C. gariepinus has been reported by fish farmers and consumers in Bangladesh, and unplanned hybridization between native and exotic species has been suspected. This study attempts to know the purity of C. batrachus by analyzing mitochondrial genes. Both directly sequenced and retrieved Cytochrome C Oxidase subunit I (COI) and cytochrome b (Cytb) genes from C. gareipinus and C. batrachus were analyzed by MEGA software. The morphologically dissimilar C. batrachus showed the least genetic distance (0.295) from C. gariepinus, which provided evidence of hybridization between the two species. Maximum likelihood (ML) phylogenetic trees showed that C. batrachus from Bangladesh did not cluster with C. batrachus of other countries, instead C. batrachus clustered with the exotic C. gariepinus. The suspected hybrid formed sister taxa with the exotic C. gariepinus. The study corroborates the genetic deterioration of C. batrachus by unplanned hybridization with the invasive C. gariepinus. Unplanned hybridization has deleterious consequences; therefore, immediate action is necessary for aquaculture sustainability and biodiversity conservation in Bangladesh.