bluuebunny/crossref_metadata_2025 huggingface dataset:
The Aqueous Leaf Extract of M. oleifera Inhibits PEDV Replication through Suppressing Oxidative Stress-Mediated Apoptosis
Authors: Cao Yanan , Zhang Shuoshuo , Huang Yanjie , Zhang Shuai , Wang Haifei , Bao Wenbin
Published: February 2022

Porcine epidemic diarrhea (PED), one of the serious enteric diseases caused by the porcine epidemic diarrhea virus (PEDV), is responsible for enormous economic losses in the global swine industry. However, available commercial vaccines fail to protect pigs from PEDV infection due to the appearance of PEDV variants. Hence, it is necessary to find an effective and cost-efficient natural product to protect pigs from PEDV infection. In this study, we first found that an aqueous leaf extract of M. oleifera (MOE) exhibited antiviral activity in response to PEDV infection. Furthermore, time-of-addition experiments revealed that MOE inhibited PEDV replication rather than attachment and internalization. Mechanistically, MOE significantly suppressed the production of reactive oxygen species (ROS) and malondialdehyde (MDA) induced by PEDV infection, and restored glutathione peroxidase (GSH-Px) activity. Importantly, the addition of MOE alleviated oxidative stress and the expression of inflammatory cytokines and resulted in fewer apoptotic cells during PEDV infection. These results indicated that MOE might be an effective anti-PEDV drug used to control PED disease and may be helpful in developing a new prophylactic and therapeutic strategy against PEDV.
A Review of the Diversity of the Genital Tract Microbiome and Implications for Fertility of Cattle
Authors: Adnane Mounir , Chapwanya Aspinas
Published: February 2022

Cattle have a genital microbiome that is established early in life, even before calving. Microbial influx into the reproductive system of cows, during calving or mating, is unavoidable and is likely to alter the commensal microflora composition. It is now well established that a commensal endometrial flora is largely responsible for the overall fertility of cows. These microbes are important for maintenance of structural integrity of the genital mucosal barrier, immunomodulation, and protection against pathogens. Further, the genital microbiome functions in the semiochemical communication between a male and female. An optimal balance between the abundance and diversity of the microbiome is essential to promote female genital tract health. Disruption of this balance leads to dysbiosis and genital diseases and perturbed fertility. As part of the global strategy of One World, One Health, there is a need to reduce antibiotic use in animals. This area of research has the potential to expand the knowledge about the nexus between the endometrial microbiome and fertility including being probiotic in different species.
Seropositive Wild Boars Suggesting the Occurrence of a Wild Cycle of Trichinella spp. in Brazil
Authors: Silva Carolina S. , Mendonça Talita O. , Machado Dália M. R. , Arias-Pacheco Carmen A. , Oliveira Wilson J. , Perin Patricia P. , Werther Karin , Carraro Paulo E. , Trevisol Iara M. , Kramer Beatris , Silva Virgínia S. , Mathias Luis A. , Bürger Karina P. , Lux Hoppe Estevam G.
Published: February 2022

Trichinella is a zoonotic nematode traditionally detected worldwide in both domestic and wild animals. In South America, along with the occurrence of this parasite in domestic pigs and wild boars, there are reports of infection in wild carnivores. Brazil is considered free of the domestic cycle of Trichinella, but there is unpublished serological evidence of infection in wild boars, which changed the Brazilian status in OIE regarding the disease after an official communication. We investigated Trichinella spp. infection in wild boars and wild carnivores in the Southeastern region of Brazil. A total of 136 samples were tested, 121 from wild boars and 15 from wild carnivores. Artificial enzymatic digestion (AED) tests were performed on muscle samples from 37 wild boars and 15 wild carnivores, and 115 serum samples from wild boars were tested by iELISA. Seven serum samples from wild boars tested positive (7/115 = 6.1%, 95% CI 3.0–12.0), but no larvae were found in the AED. There was no significant difference between sex, age, and location of the samples. The serological results suggest that a wild cycle of Trichinella spp. may occur in Brazil, but further analyses should be performed to confirm the presence of the parasite.
Improvement of Albendazole Bioavailability with Menbutone Administration in Sheep
Authors: Diez Raquel , Diez M. Jose , Garcia Juan J. , Rodríguez Jose M. , Lopez Cristina , Fernandez Nelida , Sierra Matilde , Sahagun Ana M.
Published: February 2022

The pharmacokinetic interaction between a benzimidazole (albendazole, ABZ) and a choleretic drug (menbutone, MEN) was evaluated in sheep. The plasma disposition of albendazole sulfoxide (ABZSO, active metabolite) and albendazole sulfone (ABZSO2, inactive metabolite) was investigated following an oral administration of albendazole (ABZ) (5 mg/kg) alone or with menbutone (MEN) (intramuscular, 10 mg/kg). Blood samples were collected over 3 days post-treatment, and drug plasma concentrations were measured by high performance liquid chromatography (HPLC). ABZSO was measured from 0.5 to 48 h, and ABZSO2 from 2 to 60 h. No parent drug was detected at any sampling time. Mean maximum plasma concentration (Cmax) and the area under the plasma concentration-time curve (AUC) were 12.8% and 21.5% higher for ABZSO when ABZ and MEN were administered together, which indicates a significant increase in the amount absorbed. The rate of absorption was not modified, with similar values for the time to reach Cmax (tmax) (11.5 h with ABZ + MEN and 10.7 h with ABZ treatment), although no significant differences were observed for these latter pharmacokinetic parameters. Regarding ABZSO2, Cmax, AUC and tmax values were similar after both treatments (ABZ or ABZ + MEN). The results obtained indicate that co-administration of ABZ and MEN may be an interesting and practical option to increase the efficacy of this anthelmintic.
Chemical Composition and Fatty Acid Profile of the Pectoralis major Muscle in Broiler Chickens Fed Diets with Full-Fat Black Soldier Fly (Hermetia illucens) Larvae Meal
Authors: Daszkiewicz Tomasz , Murawska Daria , Kubiak Dorota , Han Jolanta
Published: February 2022

The aim of this study was to determine the effect of full-fat Hermetia illucens (HI) larvae meal used as a substitute for 50%, 75% and 100% of soybean meal (SBM) in diets fed to male Ross 308 broiler chickens on the proximate chemical composition and fatty acid profile of the Pectoralis major (PM) muscle. The muscles of chickens fed HI larvae meal were characterized by a higher (p < 0.05) total concentration of pigments and lower (p < 0.05) ash content. At the lowest dietary inclusion rate (50%) of HI larvae meal, the PM muscle had a lower (p < 0.05) content of fat and collagen, compared with the remaining treatments. An analysis of the fatty acid profile of the PM muscle revealed that the total concentrations of saturated fatty acids increased (p < 0.05) and the total concentrations of polyunsaturated fatty acids decreased (p < 0.05) with increasing inclusion levels of HI larvae meal. The changes in the fatty acid profile of muscles in birds receiving HI larvae meal led to a decrease in the nutritional value of fat. The present findings indicate that the ≥50% inclusion rate of full-fat HI larvae meal as a protein source alternative to SBM in broiler chicken diets is too high due to its negative effect on the fatty acid profile of meat.
More Than Meets the Kappa for Antibody Superantigen Protein L (PpL)
Authors: Ling Wei-Li , Yeo Joshua Yi , Ng Yuen-Ling , Wipat Anil , Gan Samuel Ken-En
Published: February 2022

Immunoglobulin superantigens play an important role in affinity purification of antibodies and the microbiota-immune axis at mucosal areas. Based on current understanding, Staphylococcal Protein A (SpA), Streptococcal Protein G (SpG) and Finegoldia Protein L (PpL) are thought to only bind specific regions of human antibodies, allowing for selective purification of antibody isotypes and chains. Clinically, these superantigens are often classified as toxins and increase the virulence of the producing pathogen through unspecific interactions with immune proteins. To perform an in-depth interaction study of these three superantigens with antibodies, bio-layer interferometry (BLI) measurements of their interactions with a permutation panel of 63 IgG1 variants of Pertuzumab and Trastuzumab CDRs grafted to the six human Vκ and seven human VH region families were tested. Through this holistic and systemic analysis of IgG1 variants with various antibody regions modified, comparisons revealed novel PpL–antibody interactions influenced by other non-canonical antibody known light-chain framework regions, whereas SpA and SpG showed relatively consistent interactions. These findings have implications on PpL-based affinity antibody purification and design that can guide the engineering and understanding of PpL-based microbiota-immune effects.
Antibiotic Exposure, Common Morbidities and Main Intestinal Microbial Groups in Very Preterm Neonates: A Pilot Study
Authors: Bozzi Cionci Nicole , Lucaccioni Laura , Pietrella Elisa , Ficara Monica , Spada Caterina , Torelli Paola , Bedetti Luca , Lugli Licia , Di Gioia Diana , Berardi Alberto
Published: February 2022

Prematurity exposes newborns to increased risks of infections and it is associated with critical morbidities. Preterm infants often require antibiotic therapies that can affect the correct establishment of gut microbiota. The aim of this study was to investigate targeted intestinal bacteria in preterm neonates with common morbidities and receiving antibiotic treatments of variable duration. Stool samples were collected after birth, at 15, 30 and 90 days of life. qPCR quantification of selected microbial groups (Bifidobacterium spp., Bacteroides fragilis group, Enterobacteriaceae, Clostridium cluster I and total bacteria) was performed and correlation between their levels, the duration of antibiotic treatment and different clinical conditions was studied. An increasing trend over time was observed for all microbial groups, especially for Bifdobacterium spp. Prolonged exposure to antibiotics in the first weeks of life affected Clostridium and B. fragilis levels, but these changes no longer persisted at 90 days of life. Variations of bacterial counts were associated with the length of hospital stay, feeding and mechanical ventilation. Late-onset sepsis and patent ductus arteriosus reduced the counts of Bifidobacterium, whereas B. fragilis was influenced by compromised respiratory conditions. This study can be a start point for the identification of microbial biomarkers associated with some common morbidities and tailored strategies for a healthy microbial development.
Antimicrobial Potential of the Genera Geobacillus and Parageobacillus, as Well as Endolysins Biosynthesized by Their Bacteriophages
Authors: Zebrowska Joanna , Witkowska Małgorzata , Struck Anna , Laszuk Patrycja E. , Raczuk Edyta , Ponikowska Małgorzata , Skowron Piotr M. , Zylicz-Stachula Agnieszka
Published: February 2022

In the recent decades, antibiotic resistance has emerged and spread rapidly among clinically relevant pathogens. The natural ability of bacteria to transmit resistance determinants through horizontal gene transfer poses constant challenges to drug development. Natural molecules produced by soil microorganisms continue to be a key source of new antimicrobial agents. In this context, bacteria from the Geobacillus and Parageobacillus genera deserve special attention. Although there is commercial and industrial interest in these microorganisms, the full range of antibacterial compounds biosynthesized by the Geobacillus and Parageobacillus species remains largely unexplored. The aim of this review is to present the strong antimicrobial potential of these bacteria and endolysins produced by their bacteriophages.
Bio-Waste Products of Mangifera indica L. Reduce Adipogenesis and Exert Antioxidant Effects on 3T3-L1 Cells
Authors: Pratelli Giovanni , Carlisi Daniela , D’Anneo Antonella , Maggio Antonella , Emanuele Sonia , Palumbo Piccionello Antonio , Giuliano Michela , De Blasio Anna , Calvaruso Giuseppe , Lauricella Marianna
Published: February 2022

Several studies highlighted the beneficial value of natural compounds in the prevention and treatment of obesity. Here, we investigated the anti-obesity effects of extracts of peel and seed of mango (Mangifera indica L.) cultivated in Sicily (Italy) in 3T3-L1 cells. Mango Peel (MPE) and Mango Seed (MSE) extracts at a 100 µg/mL concentration significantly reduced lipid accumulation and triacylglycerol contents during 3T3-L1 adipocyte differentiation without toxicity. HPLC-ESI-MS analysis showed that both the extracts contain some polyphenolic compounds that can account for the observed biological effects. The anti-adipogenic effect of MPE and MSE was the result of down-regulation of the key adipogenic transcription factor PPARγ and its downstream targets FABP4/aP2, GLUT4 and Adipsin, as well SREBP-1c, a transcription factor which promotes lipogenesis. In addition, both MPE and MSE significantly activated AMPK with the consequent inhibition of Acetyl-CoA-carboxylase (ACC) and up-regulated PPARα. The addition of compound C, a specific AMPK inhibitor, reduced the effects of MPE and MSE on AMPK and ACC phosphorylation, suggesting a role of AMPK in mediating MPE and MSE anti-lipogenic effects. Notably, MPE and MSE possess an elevated radical scavenging activity, as demonstrated by DPPH radical scavenging assay, and reduced ROS content produced during adipocyte differentiation. This last effect could be a consequence of the increase in the antioxidant factors Nrf2, MnSOD and HO-1. In conclusion, MPE and MSE possesses both anti-adipogenic and antioxidant potential, thus suggesting that the bio-waste products of mango are promising anti-obesity natural compounds.
Mitochondrial Fragmentation in a High Homocysteine Environment in Diabetic Retinopathy
Authors: Kowluru Renu A. , Mohammad Ghulam
Published: February 2022

Diabetic patients routinely have elevated homocysteine levels, and due to increase in oxidative stress, hyperhomocysteinemia is associated with increased mitochondrial damage. Mitochondrial homeostasis is directly related to the balance between their fission and fusion, and in diabetes this balance is disturbed. The aim of this study was to investigate the role of homocysteine in mitochondrial fission in diabetic retinopathy. Human retinal endothelial cells, either untransfected or transfected with siRNA of a fission protein (dynamin-related protein 1, Drp1) and incubated in the presence of 100 μM homocysteine, were analyzed for mitochondrial fragmentation by live-cell microscopy and GTPase activity of Drp1. Protective nucleoids and mtDNA damage were evaluated by SYBR DNA stain and by transcripts of mtDNA-encoded ND6 and cytochrome b. The role of nitrosylation of Drp1 in homocysteine-mediated exacerbation of mitochondrial fragmentation was determined by supplementing incubation medium with nitric-oxide inhibitor. Homocysteine exacerbated glucose-induced Drp1 activation and its nitrosylation, mitochondrial fragmentation and cell apoptosis, and further decreased nucleoids and mtDNA transcription. Drp1-siRNA or nitric-oxide inhibitor prevented glucose- and homocysteine-induced mitochondrial fission, damage and cell apoptosis. Thus, elevated homocysteine in a hyperglycemic environment increases Drp1 activity via increasing its nitrosylation, and this further fragments the mitochondria and increases apoptosis, ultimately leading to the development of diabetic retinopathy.
OxInflammation at High Altitudes: A Proof of Concept from the Himalayas
Authors: Mrakic-Sposta Simona , Biagini Denise , Bondi Danilo , Pietrangelo Tiziana , Vezzoli Alessandra , Lomonaco Tommaso , Di Francesco Fabio , Verratti Vittore
Published: February 2022

High-altitude locations are fascinating for investigating biological and physiological responses in humans. In this work, we studied the high-altitude response in the plasma and urine of six healthy adult trekkers, who participated in a trek in Nepal that covered 300 km in 19 days along a route in the Kanchenjunga Mountain and up to a maximum altitude of 5140 m. Post-trek results showed an unbalance in redox status, with an upregulation of ROS (+19%), NOx (+28%), neopterin (+50%), and pro-inflammatory prostanoids, such as PGE2 (+120%) and 15-deoxy-delta12,14-PGJ2 (+233%). The isoprostane 15-F2t-IsoP was associated with low levels of TAC (−18%), amino-thiols, omega-3 PUFAs, and anti-inflammatory CYP450 EPA-derived mediators, such as DiHETEs. The deterioration of antioxidant systems paves the way to the overload of redox and inflammative markers, as triggered by the combined physical and hypoxic stressors. Our data underline the link between oxidative stress and inflammation, which is related to the concept of OxInflammation into the altitude hypoxia fashion.
NRF2 Activation in Autophagy Defects Suppresses a Pharmacological Transactivation of the Nuclear Receptor FXR
Authors: Kim Eun Young , Lee Jae Man
Published: February 2022

NF-E2-related factor 2 (NRF2), an antioxidant transcription factor, is activated in autophagy-deficient mice due to the accumulations of p62/SQSTM1 and its subsequent interaction with Kelch-like-ECH-associated protein 1 (KEAP1), an adaptor component for Cullin3-based E3 ubiquitin ligase complex. Farnesoid x receptor (FXR/NR1H4) is a ligand-dependent transcription factor that belongs to the nuclear receptor superfamily. FXR plays an essential role in bile acid synthesis and enterohepatic circulation, affecting glucose and lipid metabolism. Obeticholic acid as a potent FXR agonist has been approved to treat primary biliary cholangitis and clinical trials for its use in the treatment of other liver diseases are underway. Here we show that NRF2 activation in autophagy defects impedes a transactivation of FXR. Liver-specific Atg7 knockout mice or a treatment of autophagy inhibitor showed decreased inductions of FXR target genes upon its synthetic agonists. Moreover, enforced NRF2 activations with small molecules potently decreased the pharmacological activation of FXR in cultured cells. Finally, we demonstrate that NRF2 activation by the treatment with the food antioxidant butylated hydroxyanisole is necessary and sufficient to inhibit the pharmacological activation of FXR in vivo. These results reveal a novel function of the basal autophagy-NRF2 axis for the regulation of FXR transactivation, and shed light on a potential therapeutic strategy in metabolic disease.
Intelligent Reasoning Rules for Home Energy Management (IRRHEM): Algeria Case Study
Authors: Saba Djamel , Cheikhrouhou Omar , Alhakami Wajdi , Sahli Youcef , Hadidi Abdelkader , Hamam Habib
Published: February 2022

Algeria is characterized by extreme cold in winter and high heat and humidity in summer. This leads to an increase in the use of electrical appliances, which has a negative impact on electrical energy consumption and its high costs, especially with the high price of electricity in Algeria. In this context, artificial intelligence can help to regulate the daily consumption of electricity, by optimizing the exploitation of natural resources and alerting the individual to avoid energy wasting. This paper proposes a decision-making tool (IRRHEM) for managing electrical energy at smart home. The IRRHEM solution is based on three elements: the use of natural resources, the notification of the inhabitants in case of resources misuse or wasting behavior, and the aggregation of similar activities at same time. Additionally, based on the proposed intelligent reasoning rules, residents’ behavior and activities are represented by OWL (Ontology Web Language) and written and executed through SWRL (Semantic Web Rule Language). Finally, the (IRRHEM) solution is tested in a home located in Algiers city inhabited by a family of four persons. The IRRHEM performance evaluation results are very promising and show a 3.60% rate of energy saving.
Towards a Hybrid Machine Learning Model for Intelligent Cyber Threat Identification in Smart City Environments
Authors: Al-Taleb Najla , Saqib Nazar
Published: February 2022

The concept of a smart city requires the integration of information and communication technologies and devices over a network for the better provision of services to citizens. As a result, the quality of living is improved by continuous analyses of data to improve service delivery by governments and other organizations. Due to the presence of extensive devices and data flow over networks, the probability of cyber attacks and intrusion detection has increased. The monitoring of this huge amount of data traffic is very difficult, though machine learning algorithms have huge potential to support this task. In this study, we compared different machine learning models used for cyber threat classification. Our comparison was focused on the analyzed cyber threats, algorithms, and performance of these models. We have identified that real-time classification, accuracy, and false-positive rates are still the major issues in the performance of existing models. Accordingly, we have proposed a hybrid deep learning (DL) model for cyber threat intelligence (CTI) to improve threat classification performance. Our model was based on a convolutional neural network (CNN) and quasi-recurrent neural network (QRNN). The use of QRNN not only resulted in improved accuracy but also enabled real-time classification. The model was tested on BoT-IoT and TON_IoT datasets, and the results showed that the proposed model outperformed the other models. Due to this improved performance, we emphasize that the application of this model in the real-time environment of a smart system network will help in reducing threats in a reasonable time.
Deep Feature Extraction Based on AE Signals for the Characterization of Loaded Carbon Fiber Epoxy and Glass Fiber Epoxy Composites
Authors: Potočnik Primož , Misson Martin , Šturm Roman , Govekar Edvard , Kek Tomaž
Published: February 2022

Characterization of acoustic emission (AE) signals in loaded materials can reveal structural damage and consequently provide early warnings about product failures. Therefore, extraction of the most informative features from AE signals is an important part of the characterization process. This study considers the characterization of AE signals obtained from bending experiments for carbon fiber epoxy (CFE) and glass fiber epoxy (GFE) composites. The research is focused on the recognition of material structure (CFE or GFE) based on the analysis of AE signals. We propose the extraction of deep features using a convolutional autoencoder (CAE). The deep features are compared with extracted standard AE features. Then, the different feature sets are analyzed through decision trees and discriminant analysis, combined with feature selection, to estimate the predictive potential of various feature sets. Results show that the application of deep features increases recognition accuracy. By using only standard AE-based features, a classification accuracy of around 80% is obtained, and adding deep features improves the classification accuracy to above 90%. Consequently, the application of deep feature extraction is encouraged for the characterization of loaded CFE composites.
Structural Assessment under Uncertain Parameters via the Interval Optimization Method Using the Slime Mold Algorithm
Authors: Ghiasi Ramin , Noori Mohammad , Kuok Sin-Chi , Silik Ahmed , Wang Tianyu , Pozo Francesc , Altabey Wael A.
Published: February 2022

Damage detection of civil and mechanical structures based on measured modal parameters using model updating schemes has received increasing attention in recent years. In this study, for uncertainty-oriented damage identification, a non-probabilistic structural damage identification (NSDI) technique based on an optimization algorithm and interval mathematics is proposed. In order to take into account the uncertainty quantification, the elastic modulus is described as unknown-but-bounded interval values and the proposed new scheme determines the upper and lower bounds of the damage index. In this method, the interval bounds can provide supports for structural health diagnosis under uncertain conditions by considering the uncertainties in the variables of optimization algorithm. The model updating scheme is subsequently used to predict the interval-bound of the Elemental Stiffness Parameter (ESP). The slime mold algorithm (SMA) is used as the main algorithm for model updating. In addition, in this study, an enhanced variant of SMA (ESMA) is developed, which removes unchanged variables after a defined number of iterations. The method is implemented on three well-known numerical examples in the domain of structural health monitoring under single damage and multi-damage scenarios with different degrees of uncertainty. The results show that the proposed NSDI methodology has reduced computation time, by at least 30%, in comparison with the probabilistic methods. Furthermore, ESMA has the capability to detect damaged elements with higher certainty and lower computation cost in comparison with the original SMA.
A Quantum Weak Signal Detection Method for Strengthening Target Signal Features under Strong White Gaussian Noise
Authors: Yu Tianyi , Li Shunming , Lu Jiantao , Gong Siqi , Gu Jianfeng , Chen Yong
Published: February 2022

As the noise power increases, the target signal features become less obvious, which leads to the failure of weak signal detection methods. To address this problem, a quantum weak signal detection method, Local Semi-Classical Signal Analysis-Singular Value Decomposition (LSCSA-SVD), for strengthening target signal features under strong white Gaussian noise is proposed. Firstly, the time domain weak signal is quantized by the Schrodinger operator and its discrete spectrum formula. Then, in the quantum domain, the later eigenvalues are used to reconstruct the time domain signal, which can protect and enhance the target signal features. Finally, the difference between signal and noise in the singular value vector is used to further extract the reconstruction signal features. In simulation, the LSCSA-SVD can accurately extract target signals from white Gaussian noise signals with a signal-to-noise ratio (SNR) of −30 dB, which is better than the comparison methods. In the experiment, the weak acceleration sensor signal and the weak signal of the test circuit are successfully extracted. The results show that the LSCSA-SVD can suppress strong noise and improve the SNR.
Application of Remote Sensing Tools to Assess the Land Use and Land Cover Change in Coatzacoalcos, Veracruz, Mexico
Authors: Revuelta-Acosta Josept David , Guerrero-Luis Edna Suhail , Terrazas-Rodriguez Jose Eduardo , Gomez-Rodriguez Cristian , Alcalá Perea Gerardo
Published: February 2022

Land use and land cover (LULC) change has become an important research topic for global environmental change and sustainable development. As an important part of worldwide land conservation, sustainable development and management of water resources, developing countries must ensure the use of innovative technology and tools that support their various decision making systems. This study provides the most recent LULC change analysis for the last six years (2015–2021) of Coatzacoalcos, Veracruz, Mexico, one of the most important petrochemical cities in the world and host of the ongoing Interoceanic Corridor project. The analysis was carried out using Landsat 8 Operational Land Imager (OLI) satellite images, ancillary data and ground-based surveys and the Normalized Difference Vegetation Index (NDVI) to identify and to ameliorate the discrimination between four main macro-classes and fourteen classes. The LULC classification was performed using the maximum likelihood classifier (MLC) to produce maps for each year, as it was found to be the best approach when compared to minimum distance (MDM) and spectral angle mapping (SAM) methods. The macro-classes were water, built-up, vegetation and bare soil, whereas the classes were an improved classification within those. Our study achieved both user accuracy (UA) and producer accuracy (PA) above 90% for the proposed macro-classes and classes. The average Kappa coefficient for macro-classes was 0.93, while for classes it was 0.96, both comparable to previous studies. The results from the LULC analysis show that residential, industry and commercial areas slowed down their growth throughout the study period. These changes were associated with socio-economical drivers such as insecurity and lack of economic investments. Groves and trees presented steady behaviors, with small increments during the five-year period. Swamps, on the other hand, significantly degraded, being about 2% of the study area in 2015 and 0.93% in 2021. Dunes and medium and high vegetation densities (∼80%) transitioned mostly to low vegetation densities. This behavior is associated with rainfall below the annual reference and increments of surface runoff due to the loss of vegetation cover. Lastly, the present study seeks to highlight the importance of remote sensing for a better understanding of the dynamics between human–nature interactions and to provide information to assist planners and decision-makers for more sustainable land development.
Evaluating Novel Speech Transcription Architectures on the Spanish RTVE2020 Database
Authors: Álvarez Aitor , Arzelus Haritz , Torre Iván G. , González-Docasal Ander
Published: February 2022

This work presents three novel speech recognition architectures evaluated on the Spanish RTVE2020 dataset, employed as the main evaluation set in the Albayzín S2T Transcription Challenge 2020. The main objective was to improve the performance of the systems previously submitted by the authors to the challenge, in which the primary system scored the second position. The novel systems are based on both DNN-HMM and E2E acoustic models, for which fully- and self-supervised learning methods were included. As a result, the new speech recognition engines clearly outperformed the performance of the initial systems from the previous best WER of 19.27 to the new best of 17.60 achieved by the DNN-HMM based system. This work therefore describes an interesting benchmark of the latest acoustic models over a highly challenging dataset, and identifies the most optimal ones depending on the expected quality, the available resources and the required latency.
Optical Modalities for Research, Diagnosis, and Treatment of Stroke and the Consequent Brain Injuries
Authors: Oh Sung Suk , Kim Yoonhee , Lee Yoon Bum , Bae Seung Kuk , Kim Jun Sik , An Sang-hyun , Choi Jong-ryul
Published: February 2022

Stroke is the second most common cause of death and third most common cause of disability worldwide. Therefore, it is an important disease from a medical standpoint. For this reason, various studies have developed diagnostic and therapeutic techniques for stroke. Among them, developments and applications of optical modalities are being extensively studied. In this article, we explored three important optical modalities for research, diagnostic, and therapeutics for stroke and the brain injuries related to it: (1) photochemical thrombosis to investigate stroke animal models; (2) optical imaging techniques for in vivo preclinical studies on stroke; and (3) optical neurostimulation based therapy for stroke. We believe that an exploration and an analysis of previous studies will help us proceed from research to clinical applications of optical modalities for research, diagnosis, and treatment of stroke.
Cool Surface Strategies with an Emphasis on the Materials Dimension: A Review
Authors: Mourou Chaimae , Zamorano Montserrat , Ruiz Diego P. , Martín-Morales María
Published: February 2022

The need to tackle the urban heat island effect demands the implementation of cool surfaces as a mitigation strategy. This study comprehensively reviews the evolution of this research field from a materials perspective. It provides a bibliometric analysis of the relevant literature using the SciMAT software processing of bibliographic records from 1995 to 2020, for the evolution of cool surfaces. The results obtained show an increased interest in the field from 2011 to 2020, particularly for roof applications, and present the scientific evolution of reflective materials. According to the materials dimension adopted by the development of the research field, the study is refined from a bibliometric analysis of 982 selected records for the analysis of five themes: (i) Pigments; (ii) Phase change materials; (iii) Retroreflective materials; (iv) Ceramic materials; and (v) Glass. These materials present promising results in terms of their solar reflectance performances in the mitigation of the urban heat island phenomenon. At the end of this review, recommendations for future studies are provided for the creation of economic and environmentally friendly materials based on waste glass recycling. This study represents a valuable contribution that provides a scientific background with regard to cool surfaces from a materials perspective for future investigations.
Classification of Respiratory States Using Spectrogram with Convolutional Neural Network
Authors: Park Cheolhyeong , Lee Deokwoo
Published: February 2022

This paper proposes an approach to the classification of respiration states based on a neural network model by visualizing respiratory signals using a spectrogram. The analysis and processing of human biosignals are still considered some of the most crucial and fundamental research areas in both signal processing and medical applications. Recently, learning-based algorithms in signal and image processing for medical applications have shown significant improvement from both quantitative and qualitative perspectives. Human respiration is still considered an important factor for diagnosis, and it plays a key role in preventing fatal diseases in practice. This paper chiefly deals with a contactless-based approach for the acquisition of respiration data using an ultra-wideband (UWB) radar sensor because it is simple and easy for use in an experimental setup and shows high accuracy in distance estimation. This paper proposes the classification of respiratory states by using a feature visualization scheme, a spectrogram, and a neural network model. The proposed method shows competitive and promising results in the classification of respiratory states. The experimental results also show that the method provides better accuracy (precision: 0.86 and specificity: 0.90) than conventional methods that use expensive equipment for respiration measurement.
The Study of Biological Glue Droplet Impact Behavior of Bioceramic Powders Applied in 3D Printing of Bone Scaffolds
Authors: Li Xin-Pei , Wang Yan-En , Ahmed Ammar , Wei Qing-Hua , Guo Ying , Zhang Kun , Shi Yi-Kai
Published: February 2022

This paper aims to develop a reliable and effective model to investigate the behavior of micron-sized biological glue droplets impacting micron-sized bioceramic powder beds applied to the 3D printing process. It also endeavours to explore the common rules of droplet impact affected by particle size and the wettability of powder, which are supposed to provide process parameters guidance for the application of new materials in 3D printing. Firstly, based on the low impulse impact model, the simplified model was proposed. Then, the observation and simulation experiments of millimeter-scale droplet impacting were carried out under the same conditions to prove the effectiveness of the model. Furthermore, the characterization of a parametric experiment of a 3D printing practice was used to verify the significance and effectiveness of the simulation study method. Lastly, the method was performed to investigate the effect of wettability and particle size of the micron powder on the micron droplet impact. The results showed that the binder powder’s wettability and particle size could directly influence the droplet spreading behavior. The characterization results of samples printed in the simulation-predicted parameter showed that the amount of binder used could be reduced by 38.8~50.1%, while the green strength only lost 17.9~20%. The significance of this simulation method for prediction of 3D printing process parameters was verified.
High-Moment FeCo Magnetic Nanoparticles Obtained by Topochemical H2 Reduction of Co-Ferrites
Authors: Omelyanchik Alexander , Varvaro Gaspare , Maltoni Pierfrancesco , Rodionova Valeria , Murillo Jean-Pierre Miranda , Locardi Federico , Ferretti Maurizio , Sangregorio Claudio , Canepa Fabio , Chernavsky Petr , Perov Nikolai , Peddis Davide
Published: February 2022

Cobalt ferrite nanoparticles of different stoichiometries synthesized by a sol–gel autocombustion method were used as a starting material to obtain high-moment Fe50Co50 and Fe66Co34 metal nanoparticles by topochemical hydrogen reduction. Structural and magnetic investigations confirmed the formation of FeCo nanoparticles with crystallite sizes of about 30 nm and magnetization at 0.5 T of ~265 Am2/kg (0 K), which was larger than the expected bulk value, likely because of the incorporation in the body-centered cubic (bcc) FeCo structure of the residual C atoms present on the surface of the oxide particles. Temperature-dependent magnetization measurements in the H2 atmosphere were also performed to investigate in detail the reduction mechanism and the effect of an external magnetic field on the process efficiency.
Effects of Agility Training on Skill-Related Physical Capabilities in Young Volleyball Players
Authors: Chuang Chia-Hung , Hung Min-Hao , Chang Chi-Yao , Wang Yung-Yi , Lin Kuo-Chuan
Published: February 2022

The aim of this study was to examine the effects of different agility training methods on skill-related physical capabilities in young volleyball players. Twenty-seven young female volleyball players were randomly assigned to a shuttle-run training group (STG, n = 9), an agility-ladder training group (ATG, n = 9), and a control group (CG, n = 9). The intervention program was carried out three times a week for six weeks. Before and after the training period, participants’ 10 m sprint (10 MS), agility T-test, and digging agility test (DAT) performances were assessed. Within-group analysis showed significant improvements (p < 0.05) in the DAT, agility T-test, and 10 MS performance from pre- to post-test for the STG (6.08%, 2.64%, and 5.68%, respectively) and ATG (4.05%, 3.28%, and 3.27%, respectively). In the group analysis, there were significant differences (p < 0.05) between the STG and CG in the DAT and agility T-test. The STG and ATG were significantly superior to the CG in the 10 MS (p < 0.05). In conclusion, the results indicate that appropriate agility training can enhance the agility of lateral movements and speed of sprinting, as well as enable players to rapidly complete movements during a moving defense.
Overview of Power Electronic Converter Topologies Enabling Large-Scale Hydrogen Production via Water Electrolysis
Authors: Chen Mengxing , Chou Shih-Feng , Blaabjerg Frede , Davari Pooya
Published: February 2022

Renewable power-to-hydrogen (P2H) technology is one of the most promising solutions for fulfilling the increasing global demand for hydrogen and to buffer large-scale, fluctuating renewable energies. The high-power, high-current ac/dc converter plays a crucial role in P2H facilities, transforming medium-voltage (MV) ac power to a large dc current to supply hydrogen electrolyzers. This work introduces the general requirements, and overviews several power converter topologies for P2H systems. The performances of different topologies are evaluated and compared from multiple perspectives. Moreover, the future trend of eliminating the line frequency transformer (LFT) is discussed. This work can provide guidance for future designing and implementing of power-electronics-based P2H systems.
Does the Behavior of Pediatric Patients towards Dental Treatment Influence the Pattern of Adjacent (Sound, Decayed, and Filled) Proximal Surfaces in Primary Molars?
Authors: Bakhurji Eman , Alagil Jumana , Almulhim Hussah , Alfuhaid Raghad , Alqanas Sarah , Al-Khalifa Khalifa S.
Published: February 2022

This retrospective study aimed to investigate the influence of patient behavior toward dental treatment on the presence of adjacent (sound, decayed, or filled) proximal surfaces in the primary molars. The study included a records review of 2226 pediatric patients. Records were eligible if the patients were in primary or mixed dentition, and if they included a complete set of bitewings and periapical intraoral radiographs of all their primary molars. Four calibrated reviewers used intraoral radiographs to record the sound, decayed, and filled proximal distal surfaces of the first primary molars and the mesial surfaces of the second primary molars. Demographical variables were reported from patients’ medical records including gender, age, medical history, nationality, and patient behavior. Patients’ behaviors were evaluated using Frankl’s Behavior Rating Scale. The Pearson correlation was used to test the association between the sound, decayed, and filled distal surfaces of the first primary molars and the mesial surface of the second primary molar. High correlations of ≥0.6 were further tested in simple and multiple linear regression models to test the influence of patients’ behaviors on these correlations after adjusting for demographical factors. All tests were performed at 5% significance level A. A total of 1194 records met the inclusion criteria and were analyzed. There was a high positive correlation between the sound, decayed, and filled distal surfaces of the first primary molar and similar surfaces on the mesial of the second primary molars (0.66, 0.61, and 0.60, respectively). Compared to cooperative patients, the adjusted estimate of the mean decayed mesial surface of the second primary molar increased significantly for non-cooperative patients by 0.1 (95% CI = 0.16–0.53). On the contrary, the adjusted estimate of the mean sound mesial surfaces of the second primary molars decreased significantly by 0.09 for non-cooperative patients, compared to those who were cooperative (95% CI = −0.52–−0.15). Patient cooperation did not significantly influence the mean of the filled mesial surfaces of the second primary molars (adjusted B = 0.01, 95% CI = −0.05–0.09). Educating parents and clinicians about the influence of children’s behaviors on oral health is highly encouraged to improve treatment outcomes and reduce the progression of dental caries. The implementation of specific behavior management techniques is also important to reduce dental fear and anxiety.
Time to Capture a Moving Target Travelling along a Circular Trajectory
Authors: Lee Jongsung , Hong Seung-Kweon
Published: February 2022

This study measured the time it took to select a target moving along a circular trajectory with a computer mouse. The time was changed according to the speed of the target, the width of target and the distance from the starting point to the target. However, the effect of these independent variables on the dependent variable was different from what was expected. In the previous studies, it was assumed that the faster the moving target speed, the longer the target selection time, because increased target speed had the effect of narrowing the effective target width. However, as a result of the experiment, the target selection time was rather shortened when the moving speed of the target was increased. This may be because the subjects intend to speed up target selection while decreasing the accuracy of target selection in order to adapt to a fast-moving target. The modified Fitts’ model for the moving target selection time proposed in a previous study did not take these user responses into account. A more modified model is required to more accurately describe the selection time of moving target.
Influence of the Initial Blank Geometry on the Final Thickness Distribution of the Hemispheres in Superplastic AZ31 Alloy
Authors: Giuliano Gillo , Polini Wilma
Published: February 2022

This work deals with the design of the thickness of an AZ31 alloy blank, which is a superplastic magnesium material, to manufacture a hemisphere with a uniform final thickness. The finite element technique was used for the design process. The superplastic free-forming manufacturing was simulated for a part whose initial thicknesses were made to vary through two independent design parameters to obtain a linear thickness decrease from the pole to the end of the blank to form. This is because a linear thickness decrease is easily obtained through a machining process. The optimized blank, that is, the blank with a non-constant thickness that leads to the most uniform thickness distribution of the formed product, allows the manufacturing of a hemisphere with more uniform thickness values with a reduction in forming times and in weight in comparison with that formed by a constant initial thickness blank. At the same time, experimental tests confirmed the results highlighted by the finite element technique.
Assessment of Potentially Toxic Elements and Associated Health Risk in Bottled Drinking Water for Babies
Authors: Ungureanu Elena L. , Mustatea Gabriel , Popa Mona Elena
Published: February 2022

Potentially toxic elements are chemical pollutants which are dangerous to human health, especially for babies and children. Because their presence has been detected in baby food and baby drinking water, exposure to these elements is mainly due to ingestion. For this reason, the main objective of this study was quantification of 12 potentially toxic elements, including Ba, Co, Cu, Zn, Mn, Ni, Li, Fe, Pb, Cd, Cr, Sb, by ICP–MS, from 19 samples of bottled baby water. Based on the levels obtained, a health risk assessment was performed of the risk caused by their consumption, as well as an analysis of the quality of the samples. Excep iron, the values obtained for all other metals were below the limits imposed by the legislation in force. The risk analysis shows that Hazard index values were included in Risk Class 1, with a very low hazard level. The order of Cancer Risk values is as follows, Cd < Cr < Ni < Pb. As a general conclusion, we can say that the samples can be intended for consumption by children and infants.
Comparative Life Cycle Assessment of Lightweight Aggregates Made from Waste—Applying the Circular Economy
Authors: Uceda-Rodríguez Manuel , Moreno-Maroto José Manuel , Cobo-Ceacero Carlos Javier , López-García Ana B. , Cotes-Palomino Teresa , Martínez-García Carmen
Published: February 2022

The application of Life Cycle Assessment in the construction sector can be a very useful tool to reduce the environmental impact generated by the sector. In order to quantify the improvement in environmental terms with the use of artificial lightweight aggregates (LWA) manufactured with waste, in this work, we conducted a comparative evaluation of the life cycle of LWAs for a total of five different scenarios: LWAs obtained in a traditional way, i.e., using exclusively clay in their manufacture (Spanish blond clay, Portuguese red clay and Portuguese blond clay), and LWAs manufactured with four different wastes, with a partial substitution of 2.5% for each of the clays per waste (almond and hazelnut shells, sludge from the purification of paper money, cork dust and coffee grounds). The functional unit was set as the production of 1 kilo of lightweight aggregates and the CML 2000 methodology and the SimaPro software were used. The results obtained in this research allow us to conclude that the addition of organic wastes showed a slightly higher environmental performance than the conventional system, the ALAs manufactured with almond and hazelnut shells being the most environmentally friendly option, with reductions of more than 30% in some cases, followed by the LWAs manufactured with coffee grounds. On the other hand, the addition of paper sewage sludge and cork dust represents minimal environmental optimization.