bluuebunny/crossref_metadata_2025 huggingface dataset:
Syringohydromyelia in Dogs: The Genomic Component Underlying a Complex Neurological Disease
Authors: Andrino Sandra , Lorenzo Valentina , Dunner Susana , Contreras Elisabeth , Cañón Javier , Sevane Natalia
Published: September 2022

Syringohydromyelia (SHM) is a neurological disorder characterized by the appearance of fluid-containing cavities within the spinal cord. Although SHM is thought to be under multigenic control, the molecular basis of this disease remains poorly defined. A genome-wide association study (GWAS) was carried out comparing the whole genome sequences (WGS) from 12 dogs with SHM and 2 panels of 26 dogs (either older than 5 years and showing the absence of SHM or belonging to breeds not susceptible to SHM) to identify candidate genes associated with the development of SHM. Seven candidate genes were identified. Of these, five genes were determined to be involved in bone development (PLXNA2, HHAT, MBOAT2, ITGAV) and calcium homeostasis (HPCAL1). Although further validation is needed at the transcript level, it is worth highlighting the association of a possible pathogenic variant which generated a new intronic branch-site sequence in PLXNA2 (T/C, CFA7:7043294). Considering previous studies in dogs that show SHM related to craniocervical junction (CCJ) malformations, these genes can be considered good candidates for the development of this disease. This report dissects the genomic component of SHM in dogs, which paves the way for further research on this complex disease found both in canine and human species.
IgY Antibodies as Biotherapeutics in Biomedicine
Authors: León-Núñez Diana , Vizcaíno-López María Fernanda , Escorcia Magdalena , Correa Dolores , Pérez-Hernández Elizabeth , Gómez-Chávez Fernando
Published: September 2022

Since the discovery of antibodies by Emil Von Behring and Shibasaburo Kitasato during the 19th century, their potential for use as biotechnological reagents has been exploited in different fields, such as basic and applied research, diagnosis, and the treatment of multiple diseases. Antibodies are relatively easy to obtain from any species with an adaptive immune system, but birds are animals characterized by relatively easy care and maintenance. In addition, the antibodies they produce can be purified from the egg yolk, allowing a system for obtaining them without performing invasive practices, which favors the three “rs” of animal care in experimentation, i.e., replacing, reducing, and refining. In this work, we carry out a brief descriptive review of the most outstanding characteristics of so-called “IgY technology” and the use of IgY antibodies from birds for basic experimentation, diagnosis, and treatment of human beings and animals.
Antimicrobial Activity of Lactones
Authors: Mazur Marcelina , Masłowiec Dorota
Published: September 2022

The development of bacterial resistance to antibiotics and the consequent lack of effective therapy is one of the biggest problems in modern medicine. A consequence of these processes is an urgent need to continuously design and develop novel antimicrobial agents. Among the compounds showing antimicrobial potential, lactones are a group to explore. For centuries, their antimicrobial activities have been used in folk medicine. Currently, novel lactone compounds are continuously described in the literature. Some of those structures exhibit high antimicrobial potential and some are an inspiration for design and synthesis of future drugs. This paper describes recent developments on antimicrobial lactones with smaller ring sizes, up to seven membered ε-lactones. Their isolation from natural sources, chemical synthesis, synergistic activity with antibiotics, and effects on quorum sensing are presented herein.
Detection of Clones B2-ST131-C2 and A-ST617 in Escherichia coli Producing Both CTX-M-15 and CTX-M-27 from Tunisian Community Patients
Authors: Mhaya Amel , Trabelsi Rahma , Aillerie Sabine , M’Zali Fatima , Bégu Dominique , Tounsi Slim , Gdoura Radhouane , Arpin Corinne
Published: September 2022

During a two-month period (2017–2018), 336 urine samples positive for Escherichia coli were collected from Tunisian patients. Of the 336 samples, 266 were collected from community patients and 70 from hospital settings. In all, 15 ESBL producers were identified (8 and 7, respectively) and assigned to 13 pulsotypes, including four ESBL-producing E. coli (ESBL-E) with E1 and E2 profiles (2 isolates each) from community patients. The two strains E1 were identified as B2-ST131 subclade C2 and the two isolates E2, A-ST617. The four strains carrying both CTX-M-15 and CTX-M-27, exhibited the multireplicon IncFII/F1A/F1B with the same formula F31:A4:B1. Two isolates with patterns E3 and E4 (Dice coefficient, 78.7%) isolated from community and hospital settings of two geographic areas were assigned to the emerging ST131 C1-M27 subclade and contained the replicon F1:A-:B20. The remaining ESBL-E divided into different sequence types/associated CTX-M: 2 ST131-C2/CTX-M-15 and ST744/CTX-M-55, ST617/CTM-15, ST2973/CTX-M-55, ST6448/CTX-M-15, ST224/CTX-M-15, ST1431/CTX-M-15, and ST38/CTX-M-27, one isolate each. Our study reports for the first time the presence in the Tunisian community of two clones of E. coli, including the virulent clone ST131-C2 harboring both CTX-M-15 and CTX-M-27, and confirms the spread of the emergent clone ST131-C1-M-27, notably in community urinary tract infections.
Does the Use of Local Antibiotics Affect Clinical Outcome of Patients with Fracture-Related Infection?
Authors: Sliepen Jonathan , Corrigan Ruth A. , Dudareva Maria , Wouthuyzen-Bakker Marjan , Rentenaar Rob J. , Atkins Bridget L. , Govaert Geertje A. M. , McNally Martin A. , IJpma Frank F. A.
Published: September 2022

This international, multi-center study evaluated the effect of antibiotic-loaded carriers (ALCs) on outcome in patients with a fracture-related infection (FRI) and evaluated whether bacterial resistance to the implanted antibiotics influences their efficacy. All patients who were retrospectively diagnosed with FRI according to the FRI consensus definition, between January 2015 and December 2019, and who underwent surgical treatment for FRI at any time point after injury, were considered for inclusion. Patients were followed-up for at least 12 months. The primary outcome was the recurrence rate of FRI at follow-up. Inverse probability for treatment weighting (IPTW) modeling and multivariable regression analyses were used to assess the relationship between the application of ALCs and recurrence rate of FRI at 12 months and 24 months. Overall, 429 patients with 433 FRIs were included. A total of 251 (58.0%) cases were treated with ALCs. Gentamicin was the most frequently used antibiotic (247/251). Recurrence of infection after surgery occurred in 25/251 (10%) patients who received ALCs and in 34/182 (18.7%) patients who did not (unadjusted hazard ratio (uHR): 0.48, 95% CI: [0.29–0.81]). Resistance of cultured microorganisms to the implanted antibiotic was not associated with a higher risk of recurrence of FRI (uHR: 0.75, 95% CI: [0.32–1.74]). The application of ALCs in treatment of FRI is likely to reduce the risk of recurrence of infection. The high antibiotic concentrations of ALCs eradicate most pathogens regardless of susceptibility test results.
Phomoxanthone A, Compound of Endophytic Fungi Paecilomyces sp. and Its Potential Antimicrobial and Antiparasitic
Authors: Ramos Gisele da Costa , Silva-Silva João Victor , Watanabe Luciano Almeida , Siqueira José Edson de Sousa , Almeida-Souza Fernando , Calabrese Kátia S. , Marinho Andrey Moacir do Rosario , Marinho Patrícia Santana Barbosa , Oliveira Aldo Sena de
Published: September 2022

The present work reports the isolation and biological evaluation of three dimeric xanthones from Paecilomyces sp. EJC01.1 isolated as endophytic from Schnella splendens, a typical plant of the Amazon. The compounds phomoxanthone A (1), phomoxanthone B (2) and dicerandrol B (3) were isolated by chromatographic procedures and identified by spectroscopic methods of 1D and 2D NMR and MS. The extracts and compound 1 showed antimicrobial activities against Bacillus subtilis, Escherichia coli, Staphylococcus aureus, Salmonella typhimurium and Pseudomonas aeruginosa. The compound phomoxanthone A (1) showed greater inhibitory activity against B. subtilis (MIC of 7.81 µg mL−1); in addition, it also pronounced inhibitory effect against promastigote forms of Leishmania amazonensis (IC50 of 16.38 ± 1.079 µg mL−1) and epimastigote forms Trypanosoma cruzi (IC50 of 28.61 ± 1.071 µg mL−1). To provide more information about the antibacterial activity of compound 1, an unprecedented molecular docking study was performed using S-ribosyl-homocysteine lyase (LuxS) (PDB ID 2FQO), which showed a possible interaction of phomoxanthone A with two of the residues (His58 and Cys126) that are fundamental for the catalysis mechanism in B. subtilis, which may be associated with the higher activity, when compared to other bacteria, observed in experimental studies. Additionally, quantum studies (DFT) were performed, for which a low gap value (5.982 eV) was observed, which corroborates the reactivity of phomoxanthone A. Thus, phomoxanthone A can be a good agent against pathogenic bacteria.
Prevalence of Multidrug-Resistant Diarrheagenic Escherichia coli in Asia: A Systematic Review and Meta-Analysis
Authors: Salleh Mohd Zulkifli , Nik Zuraina Nik Mohd Noor , Hajissa Khalid , Ilias Mohamad Ikram , Deris Zakuan Zainy
Published: September 2022

Diarrhea is one of the leading causes of morbidity and mortality in developing countries. Diarrheagenic Escherichia coli (DEC) is an important bacterial agent for diarrhea in infants, children, and international travelers, and accounts for more than 30% of diarrheal cases in children less than 5 years old. However, the choices of antimicrobial agents are now being limited by the ineffectiveness of many first-line drugs, in relation to the emergence of antimicrobial-resistant E. coli strains. The aim of this systematic review and meta-analysis was to provide an updated prevalence of antimicrobial-resistant DEC in Asia. A comprehensive systematic search was conducted on three electronic databases (PubMed, ScienceDirect, and Scopus), where 40 eligible studies published between 2010 and 2022 were identified. Using meta-analysis of proportions and a random-effects model, the pooled prevalence of DEC in Asian diarrheal patients was 22.8% (95% CI: 16.5–29.2). The overall prevalence of multidrug-resistant (MDR) and extended-spectrum beta-lactamase (ESBL)-producing DEC strains was estimated to be 66.3% (95% CI: 58.9–73.7) and 48.6% (95% CI: 35.1–62.1), respectively. Considering antimicrobial drugs for DEC, the resistance prevalence was highest for the penicillin class of antibiotics, where 80.9% of the DEC isolates were resistant to amoxicillin and 73.5% were resistant to ampicillin. In contrast, resistance to carbapenems such as imipenem (0.1%), ertapenem (2.6%), and meropenem (7.9%) was the lowest. The relatively high prevalence estimation signifies that the multidrug-resistant DEC is a public health threat. Effective antibiotic treatment strategies, which may lead to better outcomes for the control of E. coli infections in Asia, are necessary.
In Vitro and In Vivo Studies of Oritavancin and Fosfomycin Synergism against Vancomycin-Resistant Enterococcus faecium
Authors: Lagatolla Cristina , Mehat Jai W. , La Ragione Roberto Marcello , Luzzati Roberto , Di Bella Stefano
Published: September 2022

Therapeutic options for infections caused by vancomycin-resistant enterococci are currently suboptimal. Combination regimens where fosfomycin is used alongside existing treatments are emerging given the proven synergistic potential and PK/PD properties. In the studies presented here, we tested five vanA and five vanB clinical isolates of Enterococcus faecium using a combination of oritavancin + fosfomycin both in vitro (checkerboard, time killing) and in vivo (Galleria mellonella). The combination of oritavancin and fosfomycin increased drug susceptibility, showing a synergistic effect in 80% of isolates and an additive effect in the remaining isolates. The combination restored fosfomycin susceptibility in 85% of fosfomycin-resistant isolates. Time killing on four selected isolates demonstrated that the combination of oritavancin and fosfomycin provided a CFU/mL reduction > 2 log10 compared with the most effective drug alone and prevented the bacterial regrowth seen after 8–24 h at sub-inhibitory drug concentrations. In addition, the combination was also tested in a biofilm assay with two isolates, and a strong synergistic effect was observed in one isolate and an additive effect in the other. Finally, we demonstrated in vivo (Galleria mellonella) a higher survival rate of the larvae treated with the combination therapy compared to monotherapy (fosfomycin or oritavancin alone). Our study provides preclinical evidence to support trials combining oritavancin and fosfomycin for VRE BSI in humans, even when biofilm is involved.
Comprehensive Metabolomics and Machine Learning Identify Profound Oxidative Stress and Inflammation Signatures in Hypertensive Patients with Obstructive Sleep Apnea
Authors: Du Zhiyong , Sun Haili , Du Yunhui , Li Linyi , Lv Qianwen , Yu Huahui , Li Fan , Wang Yu , Jiao Xiaolu , Hu Chaowei , Qin Yanwen
Published: September 2022

Obstructive sleep apnea (OSA) can aggravate blood pressure and increase the risk of cardiovascular diseases in hypertensive individuals, yet the underlying pathophysiological process is still incompletely understood. More importantly, OSA remains a significantly undiagnosed condition. In this study, a total of 559 hypertensive patients with and without OSA were included. Metabolome and lipidome-wide analyses were performed to explore the pathophysiological processes of hypertension comorbid OSA and derive potential biomarkers for diagnosing OSA in hypertensive subjects. Compared to non-OSA hypertensive patients (discovery set = 120; validation set = 116), patients with OSA (discovery set = 165; validation set = 158) demonstrated a unique sera metabolic phenotype dominated by abnormalities in biological processes of oxidative stress and inflammation. By integrating three machine learning algorithms, six discriminatory metabolites (including 5-hydroxyeicosatetraenoic acid, taurine, histidine, lysophosphatidic acid 16:0, lysophosphatidylcholine 18:0, and dihydrosphingosine) were selected for constructing diagnostic and classified model. Notably, the established multivariate-model could accurately identify OSA subjects. The corresponding area under the curve values and the correct classification rates were 0.995 and 96.8% for discovery sets, 0.997 and 99.1% for validation sets. This work updates the molecular insights of hypertension comorbid OSA and paves the way for the use of metabolomics for the diagnosis of OSA in hypertensive individuals.
Protective Effects of Natural Antioxidants on Inflammatory Bowel Disease: Thymol and Its Pharmacological Properties
Authors: Liu Yao , Yan Hui , Yu Bing , He Jun , Mao Xiangbing , Yu Jie , Zheng Ping , Huang Zhiqing , Luo Yuheng , Luo Junqiu , Wu Aimin , Chen Daiwen
Published: September 2022

Inflammatory bowel disease (IBD) is a gastrointestinal disease that involves chronic mucosal or submucosal lesions that affect tissue integrity. Although IBD is not life-threatening, it sometimes causes severe complications, such as colon cancer. The exact etiology of IBD remains unclear, but several risk factors, such as pathogen infection, stress, diet, age, and genetics, have been involved in the occurrence and aggravation of IBD. Immune system malfunction with the over-production of inflammatory cytokines and associated oxidative stress are the hallmarks of IBD. Dietary intervention and medical treatment suppressing abnormal inflammation and oxidative stress are recommended as potential therapies. Thymol, a natural monoterpene phenol that is mostly found in thyme, exhibits multiple biological functions as a potential adjuvant for IBD. The purpose of this review is to summarize current findings on the protective effect of thymol on intestinal health in the context of specific animal models of IBD, describe the role of thymol in the modulation of inflammation, oxidative stress, and gut microbiota against gastrointestinal disease, and discuss the potential mechanism for its pharmacological activity.
Grass Carp Prx 3 Elevates Host Antioxidant Activity and Induces Autophagy to Inhibit Grass Carp Reovirus (GCRV) Replication
Authors: Liang Xinyu , Li Yongming , Chu Pengfei , Wang Qian , Wang Hanyue , Liao Lanjie , Yang Cheng , Zhu Zuoyan , Wang Yaping , He Libo
Published: September 2022

Peroxiredoxins are a family of antioxidant proteins that protect cells from oxidative damage caused by reactive oxygen species (ROS). Herein, the peroxiredoxin 3 gene from grass carp (Ctenopharyngodon idellus), named CiPrx3, was cloned and analyzed. The full-length cDNA of CiPrx3 is 1068 bp long, with a 753 bp open reading frame (ORF) that contains a thioredoxin-2 domain, two peroxiredoxin signature motifs, and two highly conserved cysteine residues. CiPrx3 was ubiquitously expressed in all the tested tissues, while its expression level was altered significantly after exposure to grass carp reovirus (GCRV) and pathogen-associated molecular patterns (PAMPs). CiPrx3 was localized in the mitochondria of transfected cells and concentrated in the nucleus after poly (I:C) treatment. Transformation of CiPrx3 into Escherichia coli enhanced host resistance to H2O2 and heavy metals. Purified recombinant CiPrx3 proteins could protect DNA against oxidative damage. Overexpression of CiPrx3 in fish cells reduced intracellular ROS, increased cell viability, and decreased cell apoptosis caused by H2O2 stimulation and GCRV infection. Further study indicated that CiPrx3 induced autophagy to inhibit GCRV replication in fish cells. Collectively, these results imply that grass carp Prx3 elevates host antioxidant activity and induces autophagy to inhibit GCRV replication.
Onion and Apple Functional Ingredients Intake Improves Antioxidant and Inflammatory Status and Vascular Injury in Obese Zucker Rats
Authors: Balderas Claudia , Angulo Javier , Sevilleja-Ortiz Alejandro , Peiró Concepción , Vallejo Susana , Dongil Pilar , Ancos Begoña de , Sánchez-Moreno Concepción
Published: September 2022

The objective of this study was to investigate the effects of onion and apple functional ingredients in homozygous (fa/fa) obese Zucker rats. Rodents were fed three diets: standard diet [obese control (OC) group], standard diet containing 10% onion [obese onion 10% (OO) group] and standard diet containing 10% apple [obese apple 10% (OA) group] for 8 weeks. Food intake and body weight gain were higher in obese than in lean rats. Food efficiency was lower in OO and AO groups compared with OC group. Within the obese groups, total cholesterol, LDL-cholesterol, triacylglycerols, glucose, insulin and triglyceride-glucose index were lower in OO group than in OC group, and HDL-cholesterol was higher in OO group than in OC group. In general, antioxidant activity (ABTS•+ and FRAP), antioxidant enzyme activities (CAT, SOD, GPx), GSH/GSSG ratio, nitrate/nitrite and GLP-1 increased in OO and OA groups compared with OC. Oxidative stress biomarkers, namely protein carbonyls, 8-hydroxy-2′-deoxyguanosine, 8-epi-prostaglandin F2α, inflammatory and vascular injury biomarkers (PAI-1, TIMP-1, VEGF, sICAM-1, sE-Selectin, MCP-1) and leptin, were lower in OO and OA groups than in OC group. Endothelial impairment was partially reversed, and superoxide content and gene expression of NLRP3, NFKβ1 and COX2 decreased, in OO and OA groups with respect to OC group. The study demonstrates that high pressure-processed onion and apple functional ingredients administration to obese Zucker rats causes beneficial effects on metabolic health, in particular through improving food efficiency ratio; exerting pronounced lipid-lowering effects; reducing glycemia, insulinemia, and biomarkers of hepatic injury (ALT, AST); improving antioxidant, oxidative stress, inflammatory and vascular injury biomarkers, metabolic hormones, and endothelial function; and decreasing proinflammatory gene expression of NLRP3, NFKβ1 and COX2.
Research on a Novel Nanosecond Marx Generator and Its Efficiency Analysis
Authors: Li Zi , Chai Yuan , Jiang Song , Rao Junfeng
Published: September 2022

The traditional Marx generators based on avalanche BJTs usually use a DC voltage source to charge the storage capacitors, and many theoretical studies have proved that the existence of DC voltage source leads to low energy efficiency. This paper proposes a novel nanosecond Marx generator based on avalanche BJTs, which is charged by a series-resonant power supply. This power supply charges all capacitors with a constant average current and all BJTs avalanche breakdown stage by stage without any triggering signals. When the resistors are replaced by inductors, the efficiency can be further improved. The pulse repetition frequency can be adjusted by controlling the resonant average current. The output voltage can be increased by connecting more avalanche BJTs in series or increasing the number of stages of the Marx generators. The control method and the structure of the circuit are simple. Experimental results show that negative pulses with an adjustable frequency of 10–60 kHz, a pulse width of 8.45 ns, and an amplitude of 4 kV were obtained on a resistive load. The energy efficiency of the Marx generator was increased to 94%.
Construction of Full-View Data from Limited-View Data Using Artificial Neural Network in the Inverse Scattering Problem
Authors: Jeong Sang-Su , Park Won-Kwang , Joh Young-Deuk
Published: September 2022

Generally, the results of imaging the limited view data in the inverse scattering problem are relatively poor, compared to those of imaging the full view data. It is known that solving this problem mathematically is very difficult. Therefore, the main purpose of this study is to solve the inverse scattering problem in the limited view situation for some cases by using artificial intelligence. Thus, we attempted to develop an artificial intelligence suitable for problem-solving for the cases where the number of scatterers was 2 and 3, respectively, based on CNN (Convolutional Neural Networks) and ANN (Artificial Neural Network) models. As a result, when the ReLU function was used as the activation function and ANN consisted of four hidden layers, a learning model with a small mean square error of the output data through the ground truth data and this learning model could be developed. In order to verify the performance and overfitting of the developed learning model, limited view data that were not used for learning were newly created. The mean square error between output data obtained from this and ground truth data was also small, and the data distributions between the two data were similar. In addition, the locations of scatterers by imaging the out data with the subspace migration algorithm could be accurately found. To support this, data related to artificial neural network learning and imaging results using the subspace migration algorithm are attached.
NeuralNCD: A Neural Network Cognitive Diagnosis Model Based on Multi-Dimensional Features
Authors: Li Guangquan , Hu Yuqing , Shuai Junkai , Yang Tonghua , Zhang Yonghong , Dai Shiming , Xiong Naixue
Published: September 2022

One of the most critical functions of modern intelligent teaching technology is cognitive diagnostics. Traditional cognitive diagnostic models (CDMs) usually use designed functions to deal with the linear interaction between students and exercises, but it is difficult to adequately deal with the complex relationship of non-linear interaction between students and exercises; moreover, existing cognitive diagnostic models often lack the integrated consideration of multiple features of exercises. To address these issues, this paper proposes a neural network cognitive diagnosis model (NeuralNCD) that incorporates multiple features. The model obtains more accurate diagnostic results by using neural networks to handle the nonlinear interaction between students and exercises. First, the student vector and the exercise vector are obtained through the Q-matrix; second, the multi-dimensional features of the exercises (e.g., difficulty, discrimination, guess and slip) are obtained using the neural network; finally, item response theory and a neural network are employed to characterize the interaction between the student and the exercise in order to determine the student’s cognitive state. At the same time, monotonicity assumptions and data preprocessing mechanisms are introduced into the neural network to improve the accuracy of the diagnostic results. Extensive experimental results on real world datasets present the effectiveness of NeuralNCD with regard to both accuracy and interpretability for diagnosing students’ cognitive states. The prediction accuracy (ACC), root mean square error (RMSE), and area under the curve (AUC) were 0.734, 0.425, and 0.776, respectively, which were about 2–10% higher than the related works in these evaluation metrics.
A General Solution for the Errors in Variables (EIV) Model with Equality and Inequality Constraints
Authors: Huang Dengshan , Tang Yulin , Wang Qisheng
Published: September 2022

Targeting the adjustment of the errors-in-variables (EIV) model with equality and inequality constraints, a general solution that is similar to the classical least square adjustment is proposed based on the penalty function and the weight in measurement. Firstly, we take the equality constraints as inequality constraints that do not satisfy the constraint conditions and construct the penalty functions of equality and inequality constraints, respectively. Thus, the inequality constrained optimization problem is transformed into an unconstrained optimization problem. Then the detailed calculation formula and approximate accuracy evaluation formula of the general solution are deduced. The iteration formula of the general solution is easy regarding comprehension and applicable in implementation. It can not only solve the EIV model with equality and inequality constraints respectively, but also address the EIV model with equality and inequality constraints simultaneously. In addition, it can promote the Gauss–Markov (G-M) model with equality and inequality constraints. Finally, three examples (i.e., equality constraints, inequality constraints and those with equality and inequality constraints) are validated, indicating that the general solution is effective and feasible. The results show that the general solution is effective and feasible.
Green Care Achievement Based on Aquaponics Combined with Human–Computer Interaction
Authors: Lin Wei-Ling , Wang Shu-Ching , Chen Li-Syuan , Lin Tzu-Ling , Lee Jian-Le
Published: September 2022

According to the “World Population Prospects 2022” released by the United Nations in August 2022, the world will officially enter an “aging society”. In order to provide the elderly with an improved quality of daily life, “health promotion” and “prevention of disease” will be important. With respect to care of the elderly, the concepts of “therapeutic environment” and “green care” have been explored and developed. Therefore, in this study, we combine the currently popular Internet of Things (IoT) into an aquaponics system and proposes a smart green care system (SGCS). The proposed system uses face recognition technology to record the labor and rehabilitation history of the elderly, in combination with environmental data analysis, to enable automatic control decisions for equipment in conjunction with a voice control system to reduce the obstacles faced by the elderly in operating the information system. It also uses image recognition technology to monitor and notify about plant diseases and insect pests to achieve automatic management and enhance the interaction between the elderly and the SGCS through human–computer interaction. The SGCS allows the elderly to guide it to participate in appropriate activities through direct contact with the natural environment, thereby enhancing the quality of green healing life. In this study, taking long-term care institutions as an example, we verified proof of concept (PoC), proof of service (PoS), and proof of business (PoB), confirming the feasibility of the SGCS. The SGCS proposed in this study can be successfully used in long-term care institutions and various other environments, such as medical units and home care contexts. It can take full advantage of the functions associated with the concept of “healing environment” and “green care” widely recognized by users. Therefore, it can be widely used in the field of long-term care in the future.
Anisotropy and Directivity Effects on Uniaxial Compression of Carbonaceous Slate Form Jinman Mine
Authors: Zhang Zhixiong , Cheng Yun , Song Zhanping , Ye Xueyun
Published: September 2022

To determine the anisotropic mechanical characteristics of carbonaceous slate at the Jinman Mine located in Lancang River Gorge, China, uniaxial compression, acoustic emission (AE) monitoring, and scanning electron microscopy (SEM) tests were conducted. The results show that stress loading directions and bedding effects have a significant impact on strain characteristics. The deformation of slate undergoes compaction, elastic, damage accumulation, and failure stages, and there are significant differences in strain paths. The mechanical properties of grey and carbonaceous slate have significant features, and variations of these properties of carbonaceous slate are more than that of grey slate. The discrete degree is significantly related to the direction of stress loading and different types of slate structures. The AE response intensity is related to the loading mode and slate type. A sudden increase in the AE cumulative ring number near peak stress indicates instability and rupture and is a precursor of rock rupture. The failure patterns and fracture characteristics are significantly correlated to the layered structure of the slate. Slates subjected to vertical loading and parallel loading conditions are dominated by shear fracture and tensile fracture, respectively. The peak strains of gray and carbonaceous slate correspond to brittle failure. The SEM tests indicate that slate samples subjected to parallel loading primarily show a tensile failure compared with slate samples subjected to vertical loading, with fractured sections being of lesser roughness, and scattered fractures and sections being smooth without obvious protrusions or cracks.
Adaptive Hybrid Storage Format for Sparse Matrix–Vector Multiplication on Multi-Core SIMD CPUs
Authors: Chen Shizhao , Fang Jianbin , Xu Chuanfu , Wang Zheng
Published: September 2022

Optimizing sparse matrix–vector multiplication (SpMV) is challenging due to the non-uniform distribution of the non-zero elements of the sparse matrix. The best-performing SpMV format changes depending on the input matrix and the underlying architecture, and there is no “one-size-fit-for-all” format. A hybrid scheme combining multiple SpMV storage formats allows one to choose an appropriate format to use for the target matrix and hardware. However, existing hybrid approaches are inadequate for utilizing the SIMD cores of modern multi-core CPUs with SIMDs, and it remains unclear how to best mix different SpMV formats for a given matrix. This paper presents a new hybrid storage format for sparse matrices, specifically targeting multi-core CPUs with SIMDs. Our approach partitions the target sparse matrix into two segmentations based on the regularities of the memory access pattern, where each segmentation is stored in a format suitable for its memory access patterns. Unlike prior hybrid storage schemes that rely on the user to determine the data partition among storage formats, we employ machine learning to build a predictive model to automatically determine the partition threshold on a per matrix basis. Our predictive model is first trained off line, and the trained model can be applied to any new, unseen sparse matrix. We apply our approach to 956 matrices and evaluate its performance on three distinct multi-core CPU platforms: a 72-core Intel Knights Landing (KNL) CPU, a 128-core AMD EPYC CPU, and a 64-core Phytium ARMv8 CPU. Experimental results show that our hybrid scheme, combined with the predictive model, outperforms the best-performing alternative by 2.9%, 17.5% and 16% on average on KNL, AMD, and Phytium, respectively.
Assessing Road Safety Development in European Countries: A Cross-Year Comparative Analysis of a Safety Performance Index
Authors: Bao Qiong , Zhai Zegang , Shen Yongjun
Published: September 2022

The development of a road safety performance index has been widely accepted as a supportive instrument to evaluate and compare the safety performance in different countries. However, most of the current studies concentrate on the index development for only one year. In other words, there is still a lack of cross-year comparison based on the constructed safety performance index, so as to assess the progress of road safety performance in different countries over time. In this study, by collecting data on four background indicators and seven safety performance indicators of 21 European countries for both 2008 and 2015, the hierarchical clustering analysis is first utilized to identify country groups based on the background indicators. Then, the principal component analysis (PCA) is applied for each group to construct a safety performance index, and a cross-year comparative analysis on country grouping, index ranking, and weight allocation is conducted. The results show that the members in the two country groups remain the same, implying that there was no dramatic change with respect to these countries’ road safety policy context in these two years. However, the gaps between these two country groups with respect to their overall socioeconomic development, as well as their road safety performance, enlarged over this period. Moreover, by comparing the indicator weights assigned for each country group in different years and examining the changes in indicator values of each country, a useful insight into the areas of underperformance is gained, which cannot be revealed in single year index evaluation. All these findings provide policy makers with valuable guidance to prioritize their actions to improve the level of road safety.
Hydraulic Resistance Analysis Based on Cohesive Strength and Toughness of Synthetic Polymerized Rubber Gel Used as Water-Leakage Repair Material for Concrete Structures
Authors: Seo Hyunjae , Oh Kyuhwan , Lee Jongyong , Bo Jiang , Kim Byoungil , Oh Sangkeun
Published: September 2022

As construction in urban centers increases internationally, many concrete infrastructures are being built at 100 m or more underground, and the influence of groundwater on these facilities is also increasing. Accordingly, the importance of waterproofing and leak-proofing technology for securing long-term durability and safety of underground concrete facilities has been greatly emphasized. The most important required performance of such leak repair technology is to withstand structural behavior and groundwater pressure well. Currently, as a leak repair material for underground concrete facilities, a synthetic rubber-based polymer rubber gel with adhesive flexibility is used internationally. However, quantitative data on how deep the material can perform underground are lacking. In general, the water pressure resistance evaluation of leak repair materials only checks whether it withstands the water pressure of 30 m (0.3 MPa) underground. Therefore, in this study, the toughness of the synthetic rubber polymerized gel (SPRG) leak repair material was calculated using three factors: viscosity, cohesive strength (adhesion strength), and elongation, and an analysis method that can be replaced with water pressure resistance was proposed. In addition, in the correlation between toughness and underground water pressure, it was possible to find out the thickness of the leak repair material used by the underground depth. As a result, it was possible to know the required thickness of the leak repair material according to the depth of the structure to be built underground.
The Integrated Assessment of Degraded Tourist Geomorphosites to Develop Sustainable Tourism: A Case Study of Grădina Zmeilor Geomorphosite, North-West Region, Romania
Authors: Codrea Paula Minerva , Bilașco Ștefan , Roșca Sanda , Irimuș Ioan-Aurel , Iuliu Vescan , Rusu Raularian , Fodorean Ioan , Sestras Paul
Published: September 2022

Most of the natural geomorphosites represent main attractions that have a high tourism potential and need great care in terms of their capitalization. The irrational tourism capitalization of the geomorphosites may lead to their degradation because of the lack of proper tourism infrastructure and the practice of random and uncontrolled tourism. The reintroduction in the tourism circuit of such geomorphological structures that have a high landscape and scientific value claims, first of all, the assessment of the current state of degradation and the drawing up of sustainable development proposals from a geomorphological point of view. This study deals mainly with the assessment of a geomorphosite (Grădina Zmeilor Geomorphosite, North-West Region, Romania), using a complex methodology, which is based on the identification of criteria influencing the tourism development of the geomorphosite, and their analysis by means of qualitative points given according to the impact of each criterion. A total of 17 criteria have been therefore identified. They are structured along four levels of analysis which are integrated in the form of spatial analysis based on weighted average, and highlight the overall value of the analysed geomorphosite. By implementing the methodology in the proposed research, a total value of 0.29 has been obtained in an interval between 0 and 1. This value underlines the high degree of degradation of the geomorphosite. The planning proposals have the main purpose of increasing the overall value of the geomorphosite by providing sustainability in its capitalization. To achieve this, proposals have been made to mitigate the shortcomings for a total of four criteria. The overall value of the geomorphosite has been recalculated, resulting a significant increase of the value (0.33), highlighting the impact of the implementation of these proposals in practice for the development of the geomorphosite and the increase of its level of tourism attractiveness. The introduction of this objective on the tourist map, following the application of the suggestions proposed in this paper, can lead to favorable economic development both at the local and regional level. This analysis model can also be applied to other geomorphists facing the problem of degradation and involution.
Performance of Artificial Intelligence (AI) Models Designed for Application in Pediatric Dentistry—A Systematic Review
Authors: Khanagar Sanjeev Balappa , Alfouzan Khalid , Alkadi Lubna , Albalawi Farraj , Iyer Kiran , Awawdeh Mohammed
Published: September 2022

Oral diseases are the most prevalent chronic childhood diseases, presenting as a major public health issue affecting children of all ages in the developing and developed countries. Early detection and control of these diseases is very crucial for a child’s oral health and general wellbeing. The aim of this systematic review is to assess the performance of artificial intelligence models designed for application in pediatric dentistry. A systematic search of the literature was conducted using different electronic databases, primarily (PubMed, Scopus, Web of Science, Embase, Cochrane) and secondarily (Google Scholar and the Saudi Digital Library) for studies published from 1 January 2000, until 20 July 2022, related to the research topic. The quality of the twenty articles that satisfied the eligibility criteria were critically analyzed based on the QUADAS-2 guidelines. Artificial intelligence models have been utilized for the detection of plaque on primary teeth, prediction of children’s oral health status (OHS) and treatment needs (TN); detection, classification and prediction of dental caries; detection and categorization of fissure sealants; determination of the chronological age; determination of the impact of oral health on adolescent’s quality of life; automated detection and charting of teeth; and automated detection and classification of mesiodens and supernumerary teeth in primary or mixed dentition. Artificial intelligence has been widely applied in pediatric dentistry in order to help less-experienced clinicians in making more accurate diagnoses. These models are very efficient in identifying and categorizing children into various risk groups at the individual and community levels. They also aid in developing preventive strategies, including designing oral hygiene practices and adopting healthy eating habits for individuals.
The Cross-Zone Navigation and Signage Systems for Combatting Cybersickness and Disorientation in Middle-Aged and Older People within a 3D Virtual Store
Authors: Liu Cheng-Li , Uang Shiaw-Tsyr
Published: September 2022

With the maturation and popularization of 3D virtual reality (3D VR) technology, various corporations have employed 3D VR animations to enrich the experience of visiting a store and change how products are presented. Because middle-aged and older adults have weaker mobility and perception abilities, their behaviors in 3D virtual stores may differ entirely from those of younger age groups. This study aimed to develop a cross-zone navigation system and a signage system for 3D virtual retail stores to provide middle-aged and older consumers with high-efficiency navigation for finding products quickly. Additionally, the effect of the systems on combating perceptual conflict was assessed to confirm the practicability of 3D virtual retail shopping. The results revealed that the cross-zone navigation system effectively assisted participants in searching for their desired products. Additionally, the cybersickness score (SSQ) of the cross-zone navigation system group was significantly lower than that of the map-based navigation system group. The participants who used both the cross-zone navigation system and the signage system exhibited the lowest perceptual conflict scores. Therefore, this study provides references for developing a novel navigation system for 3D virtual retail stores (i.e., a cross-zone navigation system with signage).
Protection of Phytoextracts against Rotenone-Induced Organismal Toxicities in Drosophila melanogaster via the Attenuation of ROS Generation
Authors: Singh Mahendra P. , Himalian Ranjana , Shabir Shabnam , Obaid Ahmad A. , Alamri Abdulhakeem S. , Galanakis Charis M. , Singh Sandeep Kumar , Vamanu Emanuel
Published: September 2022

Nutraceuticals play an essential role in the reduction in free radical generation in cells. A similar idea was used in the present study to determine the effects of aqueous extracts on the organismal toxicities in a nontarget organism, Drosophila melanogaster, known as the fruit fly. Punica granatum (peel and pulp), Carica papaya (peel), Foeniculum vulgare (seeds), Trigonella foenum-graecum (seeds), and Urtica dioica (leaves) extracts were employed in this study. The organismal or behavioral effects in rotenone-, and rotenone- and phytoextract-treated flies were evaluated using wild-type Drosophila melanogaster (Oregon R+). Reactive oxygen species (ROS) and behavioral parameters (climbing ability, memory power, emergence, and reproductive potential) were investigated. Urtica dioica leaves, Punica granatum peel, and pulp elicited maximal amelioration in Drosophila, although not at the same intensity, and all exhibited a varied degree of improvement in different assays. Most extracts with their potent active components (phenols, tannins, flavonoids, and amino acids) revealed a protective action against rotenone-induced toxicities at the organismal level in the stated parameters above. Interestingly, different strains and parameters had varied improvement tendencies. Thus, Drosophila may be used as a suitable in vivo animal model for such investigations, and the usage of phytoextracts may prevent a variety of disorders, including neurodegeneration. The results of this study may help in the use of specific herbs as reliable sources of phytoingredients that may be useful in developing nutraceuticals and in other clinical uses.
The Study of the Effectiveness of Advanced Algorithms for Learning Neural Networks Based on FPGA in the Musical Notation Classification Task
Authors: Sokół Sławomir , Pawuś Dawid , Majewski Paweł , Krok Marek
Published: September 2022

The work contains an original comparison of selected algorithms using artificial neural network models, such as RBF neural networks, and classic algorithms, approaches that are based on structured programming in the image identification task. The existing studies exploring methods for the problem of classifying musical notation used in this work are still scarce. The research of neural network based and the classical method of image recognition was carried out on the basis of the effectiveness of recognizing the notes presented on the treble staff. In order to carry out the research, the density of the data distribution was modeled by means of the probabilistic principal component analysis, and a simple regression was performed with the use of a radial neural network. The methods of image acquisition and analysis are presented. The obtained results were successively tested in terms of selected quality criteria. The development of this research may contribute to supporting the learning of musical notation by both beginners and blind people. The further development of the experiments can provide a convenient reading of the musical notation with the help of a classification system. The research is also an introduction of new algorithms to further tests and projects in the field of music notation classification.
Inclination of Mandibular Molars and Alveolar Bone in Untreated Adults and Its Relationship with Facial Type
Authors: Lee Yun Jeong , Jeon Hyeran Helen , Boucher Normand , Chung Chun-Hsi
Published: September 2022

To date, there is no solid agreement on the relationship between mandibular molars, mandibular alveolar bone, and vertical facial types. Therefore, we aim to assess the buccolingual inclination of mandibular first molars and respective alveolar bones and their relationship with different vertical skeletal patterns. The CBCT data from fifty-four untreated Caucasian adult patients (12 males and 42 females, 18–65 years old) were obtained from a private orthodontic practice. We measured the inclination of the tooth and alveolar bone of the right and left mandibular first molars using CBCT. From the two-dimensional lateral cephalometric radiographic images extracted from CBCT, we assessed FMA, SN-GoGn, and PFH:AFH. All subjects showed lingual inclinations of the mandibular molars and alveolar bones which were significantly correlated with each other. However, there was no significant correlation between the inclination of alveolar bone and vertical facial types. Our study supports the conclusion that a proper curve of Wilson is physiological and should be maintained during orthodontic treatment.