bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing Salinity Tolerance in Rice Mutants by Phenotypic Evaluation Alongside Simple Sequence Repeat Analysis
Authors: Huong Can Thu , Anh Truong Thi Tu , Tran Hoang-Dung , Duong Vu Xuan , Trung Nguyen Thanh , Dang Khanh Tran , Dang Xuan Tran
Published: May 2020

Salinity stress is one of the most severe constraints limiting rice production worldwide. Thus, the development of salt-tolerant rice promises to deal with increasing food demand due to climate change effects. This study investigated the salinity tolerance of mutant rice by evaluating phenotype and genotype, using forty-two simple sequence repeat (SSR) markers linked to the salinity tolerance Saltol quantitative trait locus (QTL) in ten cultivars and mutant lines. Results of phenotypic screening showed that the mutant line SKLo/BC15TB and cultivar BC15TB performed salt tolerance, while the mutant line Bao Thai/DT 84 and cultivar DT84DB were sensitive to salt stress. The markers RM 493, RM 562, RM 10748, RM 518, RM 237, and RM 20224 were the most polymorphic in salinity tolerance. Among them, RM 237, RM 10748, and RM 224 showed the highest polymorphism information (PIC = 0.58). This study reveals that the three markers are profitable for classification of salinity tolerance in both cultivar and mutant rice. The mutant line SKLo/BC15TB and cultivar BC15TB were found to be promising candidates for diversity analysis of salt-tolerant rice. Findings of this study are useful for developing new salinity-tolerant rice cultivars towards climate change.
Effects of Different In Situ Remediation Strategies for an As-Polluted Soil on Human Health Risk, Soil Properties, and Vegetation
Authors: Baragaño Diego , Gallego José Luis R. , Baleriola Gaspar , Forján Rubén
Published: May 2020

The demand for soils for recreational uses, gardening, or others in urban and periurban areas is increasing, and thus the presence of polluted technosols in these areas requires nature-based in situ remediation technologies. In this context, the capacity of three amendments, namely zero valent iron nanoparticles (nZVI), compost and a mixture of compost and biochar, to immobilise As in a polluted technosol simultaneously cultivated with Lolium perenne L. were tested and compared. The characteristics of the soil were comprehensively characterised by chemical and X-ray analysis to determine As contents, distribution, and mineralogy. As mobility was evaluated by the RBA methodology and then potential human health risks, both carcinogenic and non-carcinogenic, were assessed in all treatments. The nZVI treatment reduced risks due to the As immobilisation obtained (41% As decrease, RBA test), whereas the organic amendments did not imply any significant reduction of the RBA values. As to soil properties, the organic treatments applied lowered the pH values, increasing cation exchange capacity, and carbon and nutrient contents. To determine impacts over plant production, fresh biomass, As, Ca, Fe, K, Mg, Na and P were measured in Lolium under the different treatments. Notably, organic amendments improved As extraction by plants (57% increase), as well as fresh biomass (56% increase). On the contrary, nZVI diminished As extraction (65% decrease) and promoted a fresh biomass decrease of 57% due to nutrients immobilisation (61% decrease of P in plants tissues).
Distribution of Root-Lesion and Stunt Nematodes, and Their Relationship with Soil Properties and Nematode Fauna in Sugarcane Fields in Okinawa, Japan
Authors: Kawanobe Masanori , Sugihara Soh , Miyamaru Naoko , Yoshida Koichi , Nonomura Eito , Oshiro Hiroaki , Toyota Koki
Published: May 2020

Sugarcane cultivation in Japan has not yet focused on suppressing plant-parasitic nematodes. For proper nematode management, it is essential to know the spatial distribution of economically important plant-parasitic nematodes and free-living nematodes that play important roles in terrestrial ecosystems. We aimed to reveal nematode fauna and soil properties in 85 sugarcane fields of three major sugarcane producing islands in Japan, and to examine their relationship by using the mixed-effect model and by visualizing the spatial distributions using the inverse distance weighting (IDW) approach. The nematode community structures were analyzed by non-metric multidimensional scaling (NMDS). Among plant-parasitic nematodes in sugarcane, the root-lesion nematodes (Pratylenchus sp.) and the stunt nematodes (Tylenchorhynchus sp.) were widely distributed in these islands, yet the abundance and the species varied geospatially. Soil pH was significantly correlated with the abundance of Pratylenchus and Tylenchorhynchus species. The abundance of Pratylenchus and Tylenchorhynchus species were significantly correlated with soil pH. The abundance of Pratylenchus was significantly correlated with the abundance of free-living nematodes, the number of free-living nematode species, and exchangeable cation K+, as were the abundance of Tylenchorhynchus to the clay content and that of non-Tylenchorhynchus. This study also revealed that the three islands had different nematode faunas, which were explained especially by soil pH, texture, and exchangeable basic cations.
Structural Elucidation of Antibiotic TKR2999, an Antifungal Lipodepsipeptide Isolated from the Fungus Foliophoma fallens
Authors: Crespo Gloria , Pérez-Victoria Ignacio , Ortiz-López Francisco Javier , González-Menéndez Víctor , de la Cruz Mercedes , Cautain Bastien , Sánchez Pilar , Vicente Francisca , Genilloud Olga , Reyes Fernando
Published: May 2020

An antifungal lipodepsipeptide was obtained from cultures of the fungus Foliophoma fallens CF-236885. Its structure, elucidated by HRMS and NMR spectroscopy, contained Gly, Thr, Asn, β-Ala, Orn, Ala, two Ser residues, and 3-hydroxy-4-methylhexadecanoic acid. The absolute configuration of its amino acid residues was determined using Marfey’s analysis and J-based configuration analysis helped to establish the relative configuration of the 3-hydroxy-4-methylhexadecanoic acid moiety. A literature search retrieved a patent describing antibiotic TKR2999 (1), whose non-disclosed structure was confirmed to be identical to that found for our compound, according to its physicochemical properties and NMR spectra. Compound 1 displayed potent antifungal activity against Aspergillus fumigatus and a panel of Candida strains.
Nanovectorized Microalgal Extracts to Fight Candida albicans and Cutibacterium acnes Biofilms: Impact of Dual-Species Conditions
Authors: Lemoine Virginie , Bernard Clément , Leman-Loubière Charlotte , Clément-Larosière Barbara , Girardot Marion , Boudesocque-Delaye Leslie , Munnier Emilie , Imbert Christine
Published: May 2020

Biofilm-related infections are a matter of concern especially because of the poor susceptibility of microorganisms to conventional antimicrobial agents. Innovative approaches are needed. The antibiofilm activity of extracts of cyanobacteria Arthrospira platensis, rich in free fatty acids, as well as of extract-loaded copper alginate-based nanocarriers, were studied on single- and dual-species biofilms of Candida albicans and Cutibacterium acnes. Their ability to inhibit the biofilm formation and to eradicate 24 h old biofilms was investigated. Concentrations of each species were evaluated using flow cytometry. Extracts prevented the growth of C. acnes single-species biofilms (inhibition > 75% at 0.2 mg/mL) but failed to inhibit preformed biofilms. Nanovectorised extracts reduced the growth of single-species C. albicans biofilms (inhibition > 43% at 0.2 mg/mL) while free extracts were weakly or not active. Nanovectorised extracts also inhibited preformed C. albicans biofilms by 55% to 77%, whereas the corresponding free extracts were not active. In conclusion, even if the studied nanocarrier systems displayed promising activity, especially against C. albicans, their efficacy against dual-species biofilms was limited. This study highlighted that working in such polymicrobial conditions can give a more objective view of the relevance of antibiofilm strategies by taking into account interspecies interactions that can offer additional protection to microbes.
Impact of a Multiplex Polymerase Chain Reaction Assay on the Clinical Management of Adults Undergoing a Lumbar Puncture for Suspected Community-Onset Central Nervous System Infections
Authors: Moffa Matthew A. , Bremmer Derek N. , Carr Dustin , Buchanan Carley , Shively Nathan R. , Elrufay Rawiya , Walsh Thomas L.
Published: May 2020

Patients admitted from the community with a suspected central nervous system (CNS) infection require prompt diagnostic evaluation and correct antimicrobial treatment. A retrospective, multicenter, pre/post intervention study was performed to evaluate the impact that the BioFire® FilmArray® meningitis/encephalitis (ME) panel run in-house had on the clinical management of adult patients admitted from the community with a lumbar puncture (LP) performed for a suspected CNS infection. The primary outcome was the effect that this intervention had on herpes simplex virus (HSV) polymerase chain reaction (PCR) turnaround time (TAT). Secondary outcomes included the effect that this intervention had on antiviral days of therapy (DOT), total antimicrobial DOT, and hospital length of stay (LOS). A total of 81 and 79 patients were included in the pre-intervention and post-intervention cohorts, respectively. The median HSV PCR TAT was significantly longer in the pre-intervention group (85 vs. 4.1 h, p < 0.001). Total antiviral DOT was significantly greater in the pre-intervention group (3 vs. 1, p < 0.001), as was total antimicrobial DOT (7 vs. 5, p < 0.001). Pre-intervention hospital LOS was also significantly longer (6.6 vs. 4.4 days, p = 0.02). Implementing the ME panel in-house for adults undergoing an LP for a suspected community-onset CNS infection significantly reduced the HSV PCR TAT, antiviral DOT, total antimicrobial DOT, and hospital LOS.
Analysis of Susceptibility to Selected Antibiotics in Klebsiella pneumoniae, Escherichia coli, Enterococcus faecalis and Enterococcus faecium Causing Urinary Tract Infections in Kidney Transplant Recipients over 8 Years: Single-Center Study
Authors: Rostkowska Olga Maria , Kuthan Robert , Burban Anna , Salińska Jagoda , Ciebiera Michał , Młynarczyk Grażyna , Durlik Magdalena
Published: May 2020

Background: Urinary tract infections (UTIs) are the most common bacterial infections among kidney transplant (KTX) recipients. The purpose of this study was to analyze antimicrobial resistance (AMR) in four most common pathogens responsible for UTIs in KTX recipients and determine risk factors (RF) for resistance in the same group. Methods: Analyzed antibiograms were based on urine samples positive for bacterial growth of 105 colony-forming units (CFU)/mL obtained from hospitalized adult KTX recipients presenting with UTI symptoms upon admission to the center in years 2011–2018. Results: In total, 783 antibiograms were analyzed for Klebsiella pneumoniae (258 samples, 33.0%), Escherichia coli (212, 27.0%), Enterococcus faecalis (128, 24.0%), and Enterococcus faecium (125, 16.0%). The decrease in susceptibility of E. coli to amoxicillin/clavulanic acid (62.9% vs. 40.0%) and ciprofloxacin (100% to 40.0%) was observed. Susceptibility to gentamicin increased from 33.3% to 92.9% in E. faecium. Susceptibility to tigecycline remained 100% through all years in case of E. faecalis and E. faecium. Male gender was a RF for resistance to amoxicillin/clavulanic acid (p = 0.008), ciprofloxacin (p = 0.0003), trimethoprim/sulfamethoxazole (p = 0.00009), ceftriaxone (p = 0.0001), and cefuroxime axetil (p = 0.00038) in K. pneumoniae and against gentamicin in E. faecalis (p = 0.015). Higher resistance to ampicillin in E. faecalis (p = 0.012) and to ciprofloxacin (p = 0.0003), trimethoprim/sulfamethoxazole (p = 0.007), piperacillin/tazobactam (p = 0.003), ceftriaxone (p = 0.001), and cefuroxime axetil (p = 0.013) in K. pneumoniae was observed in higher age groups of patients. Diabetes as a cause of kidney insufficiency (p = 0.026) and kidney-pancreas transplantation (p = 0.014) was RF for resistance to ceftriaxone in K. pneumoniae. Conclusions: AMR in uropathogens from KTX recipients fluctuated. There were identifiable RFs for resistance in the examined bacteria–antibiotic combinations. We recommend continuous mapping of site-specific microorganisms as etiology and susceptibility may vary between institutions and over time.
COVID-19: Modeling, Prediction, and Control
Authors: Bani Younes Ahmad , Hasan Zeaid
Published: May 2020

The newly emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as COVID-19, has been recognized as a pandemic by the World Health Organization (WHO) on 11th March 2020. There are many unknowns about this virus to date and no vaccine or conclusive treatment due to the lack of understanding of its pathogenesis and proliferation pathways which are unknown and cannot be traced. The prime objective is to stop its spread worldwide. This article aims to provide predictions of its spread using a stochastic Lotka–Volterra model coupled with an extended Kalman Filter (EKF) algorithm to model the COVID-19 dynamics. Our results show the feasibility of utilizing this model for predicting the spread of the virus and the ability of different control measures (e.g., social distancing) on reducing the number of affected people.
Quality Assessment by Region and Land Cover of Sharpening Approaches Applied to GF-2 Imagery
Authors: Liu Qingsheng , Huang Chong , Li He
Published: May 2020

The existing pansharpening methods applied to recently obtained satellite data can produce spectral distortion. Therefore, quality assessments should be performed to address this. However, quality assessment of the whole image may not be sufficient, because major differences in a given region or land cover can be minimized by small differences in another region or land cover in the image. Thus, it is necessary to evaluate the performance of the pansharpening process for different regions and land covers. In this study, the widely used modified intensity-hue-saturation (mIHS), Gram–Schmidt spectral sharpening (GS), color spectral sharpening (CN), and principal component analysis (PCA) pansharpening methods were applied to Gaofen 2 (GF-2) imagery and evaluated according to region and land-cover type, which was determined via an object-oriented image analysis technique with a support vector machine-supervised method based on several reliable quality indices at the native spatial scale without reference. Both visual and quantitative analyses based on region and land cover indicated that all four approaches satisfied the demands for improving the spatial resolution of the original GF-2 multispectral (MS) image, and mIHS produced results superior to those of the GS, CN, and PC methods by preserving image colors. The results indicated differences in the pansharpening quality among different land covers. Generally, for most land-cover types, the mIHS method better preserved the spectral information and spatial autocorrelation compared with the other methods.
Skeleton-Based Dynamic Hand Gesture Recognition Using an Enhanced Network with One-Shot Learning
Authors: Ma Chunyong , Zhang Shengsheng , Wang Anni , Qi Yongyang , Chen Ge
Published: May 2020

Dynamic hand gesture recognition based on one-shot learning requires full assimilation of the motion features from a few annotated data. However, how to effectively extract the spatio-temporal features of the hand gestures remains a challenging issue. This paper proposes a skeleton-based dynamic hand gesture recognition using an enhanced network (GREN) based on one-shot learning by improving the memory-augmented neural network, which can rapidly assimilate the motion features of dynamic hand gestures. Besides, the network effectively combines and stores the shared features between dissimilar classes, which lowers the prediction error caused by the unnecessary hyper-parameters updating, and improves the recognition accuracy with the increase of categories. In this paper, the public dynamic hand gesture database (DHGD) is used for the experimental comparison of the state-of-the-art performance of the GREN network, and although only 30% of the dataset was used for training, the accuracy of skeleton-based dynamic hand gesture recognition reached 82.29% based on one-shot learning. Experiments with the Microsoft Research Asia (MSRA) hand gesture dataset verified the robustness of the GREN network. The experimental results demonstrate that the GREN network is feasible for skeleton-based dynamic hand gesture recognition based on one-shot learning.
Bearing Estimation for Indoor Localization Systems Using Planar Circular Photodiode Arrays
Authors: Zachár Gergely , Vakulya Gergely , Simon Gyula
Published: May 2020

An inexpensive bearing estimation sensor and a corresponding method has been recently proposed for indoor localization applications. The system utilizes modulated infrared LED sources as light beacons, and a planar circular photodiode array (PCPA) as sensor. The PCPA measures the light intensity of the beacons in multiple channels, from which the bearings of the beacons can be estimated using least squares (LS) method, with an accuracy in the range of 1 degree. In this paper a novel estimation method is proposed, which provides fast bearing estimates from the PCPA measurements using the frequency domain. The computational complexity of the novel method is orders of magnitude less than that of the LS solution, at the price of a slight decrease in accuracy. The performance of the PCPA is analyzed in the presence of reflections and the tilting of the sensor. The results demonstrate that the effect of reflections can be significant, while the tilting of the sensor has only a minor effect on the bearing estimation. The applicability of the measurement device in indoor localization applications is illustrated by real localization examples.
CARMA—Cellular Automata with Refined Mesh Adaptation—The Easy Way of Generation of Structural Topologies
Authors: Tajs-Zielińska Katarzyna , Bochenek Bogdan
Published: May 2020

This paper is focused on the development of a Cellular Automata algorithm with the refined mesh adaptation technique and the implementation of this algorithm in topology optimization problems. Traditionally, a Cellular Automaton is created based on regular discretization of the design domain into a lattice of cells, the states of which are updated by applying simple local rules. It is expected that during the topology optimization process the local rules responsible for the evaluation of cell states can drive the solution to solid/void resulting structures. In the proposed approach, the finite elements are equivalent to cells of an automaton and the states of cells are represented by design variables. While optimizing engineering structural elements, the important issue is to obtain well-defined solutions: in particular, topologies with smooth boundaries. The quality of the structural topology boundaries depends on the resolution level of mesh discretization: the greater the number of elements in the mesh, the better the representation of the optimized structure. However, the use of fine meshes implies a high computational cost. We propose, therefore, an adaptive way to refine the mesh. This allowed us to reduce the number of design variables without losing the accuracy of results and without an excessive increase in the number of elements caused by use of a fine mesh for a whole structure. In particular, it is not necessary to cover void regions with a very fine mesh. The implementation of a fine grid is expected mainly in the so-called grey regions where it has to be decided whether a cell becomes solid or void. The benefit of the proposed approach, besides the possibility of obtaining high-resolution, sharply resolved fine optimal topologies with a relatively low computational cost, is also that the checkerboard effect, mesh dependency, and the so-called grey areas can be eliminated without using any additional filtering. Moreover, the algorithm presented is versatile, which allows its easy combination with any structural analysis solver built on the finite element method.
Optimizing Extreme Learning Machines Using Chains of Salps for Efficient Android Ransomware Detection
Authors: Faris Hossam , Habib Maria , Almomani Iman , Eshtay Mohammed , Aljarah Ibrahim
Published: May 2020

Nowadays, smartphones are an essential part of people’s lives and a sign of a contemporary world. Even that smartphones bring numerous facilities, but they form a wide gate into personal and financial information. In recent years, a substantial increasing rate of malicious efforts to attack smartphone vulnerabilities has been noticed. A serious common threat is the ransomware attack, which locks the system or users’ data and demands a ransom for the purpose of decrypting or unlocking them. In this article, a framework based on metaheuristic and machine learning is proposed for the detection of Android ransomware. Raw sequences of the applications API calls and permissions were extracted to capture the ransomware pattern of behaviors and build the detection framework. Then, a hybrid of the Salp Swarm Algorithm (SSA) and Kernel Extreme Learning Machine (KELM) is modeled, where the SSA is used to search for the best subset of features and optimize the KELM hyperparameters. Meanwhile, the KELM algorithm is utilized for the identification and classification of the apps into benign or ransomware. The performance of the proposed (SSA-KELM) exhibits noteworthy advantages based on several evaluation measures, including accuracy, recall, true negative rate, precision, g-mean, and area under the curve of a value of 98%, and a ratio of 2% of false positive rate. In addition, it has a competitive convergence ability. Hence, the proposed SSA-KELM algorithm represents a promising approach for efficient ransomware detection.
Sociodemography, Geography, and Personality as Determinants of Car Driving and Use of Public Transportation
Authors: Roos John Magnus , Sprei Frances , Holmberg Ulrika
Published: May 2020

To address the sustainability challenges related to travel behavior, technological innovations will not be enough. Behavioral changes are also called for. The aim of the present study is to examine the influence of sociodemography, geography, and personality on car driving and use of public transportation. Sociodemographic factors have been defined by age, gender, income, and education. Geographic factors have been studied through residential area (e.g., rural and urban areas). Personality has been studied through the Five-Factor-Model of personality—degree of Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. The analysis is based on a survey with 1812 respondents, representative for the Swedish population. Regarding sociodemographic factors, car driving is explained by being male, higher age, higher income, while use of public transportation is explained by lower age and higher education. The user profile of a car driver is the opposite to that of a public transport passenger when it comes to geographic factors; urban residential area explains public transportation while rural area explains car driving. Some personality factors are also opposites; a low degree of Openness and a high degree of Extraversion explain car driving, while a high degree of Openness and a low degree of Extraversion explain use of public transportation. Moreover, car driving is explained by a low degree of Neuroticism, while use of public transportation is explained by a low degree of Conscientiousness and a high degree of Agreeableness. Since sociodemography, geography, and personality influence how people process information and evaluate market propositions (e.g., products and services), the findings presented here are useful for policymakers and transportations planners who would like to change behavior from car driving to public transportation use. Caution should be taken in interpreting the relationship between personality traits and transportation modes, since the personality traits are measured by a short scale (i.e., Big Five Inventory (BFI)-10), with limitations in the factor structure for a representative sample of the Swedish population.
Technical and Economic Analysis of the Implementation of Selected Variants of Road Investment
Authors: Szczepański Marcin , Grzyl Beata
Published: May 2020

The aim of the article is to analyze three variants of modernization and reconstruction of a road intersection, which in practice is the cause of numerous collisions and accidents. Detailed design solutions are presented for them. The aim of the analyses is to indicate an effective solution that, taking into account technical modifications of the road system elements, will ensure the functionality of the road system to the highest degree and significantly reduce the number of road incidents. To indicate the optimal solution, quantitative data (cost and duration of activities for three options) and qualitative data (determined based on the own experience and knowledge of road industry experts) is analyzed. The authors refer to many criteria of various natures (e.g., economic, technical, functional, environmental, social), which allow for comprehensive consideration of the current requirements of road users and changing circumstances, among others a steady increase in the number of vehicles and growing social expectations in terms of road parameters. Considering the presented analyses and arguments, the authors recommend option 1 as optimal. This is the most expensive solution among those analyzed and with the longest implementation time, however, taking into account the long-term prognosis of the direction and scope of changes to the existing standards and requirements for road infrastructure, it can be stated that option 1 meets them to the highest degree, and also has the greatest potential. The envisaged solution ensures high standards of the quality of road infrastructure use in terms of functionality, capacity, technical parameters, as well as the safety of traffic participants related to the smoothness of the journey, reduction of the number of collisions and accidents.
Hepatoprotective Effects of Pleurotus ostreatus Protein Hydrolysates Yielded by Pepsin Hydrolysis
Authors: Zhang Liwei , Lu Yuxiao , Feng Xiaobin , Liu Qinghong , Li Yuanhui , Hao Jiamin , Wang Yanqiong , Dong Yongqiang , Wang Huimin David
Published: May 2020

Pleurotus ostreatus protein extract (POPE) was prepared by the alkali precipitation method with 0.3% (w/v) NaOH. POPEP-III with a MW of 3000–5000 Da was acquired by pepsin enenzymatic hydrolysis. POPEP-III displayed noteworthy effects of 1,1-diphenyl-2-picrylhydrazyl DPPH and H2O2 scavenging activities, Fe2+ chelating ability, lipid peroxidation inhibition capacity, and metal reducing power. The administration of POPEP-III in mice significantly prevented prior CCl4-induced strengthen serum ALT and AST activities, changing from 365.44 ± 36.87 IU/L to 220.23 ± 22.27 IU/L and 352.52 IU/L to 206.75 ± 17.26 IU/L, respectively (p < 0.001), and suppressed hepatic malondialdehyde (MDA) formation from 15.28 ± 3.47 nmol/mg prot to 10.04 ± 2.06 nmol/mg prot (p < 0.001). Mice treated with POPEP-III demonstrated augmented activities of superoxide dismutase (SOD) in the liver, from 187.49 ± 19.81 U/mg prot to 233.35 ± 34.23 U/mg prot, and of glutathione peroxidase (GSH-Px), from 84.01 ± 14.54 U/mg prot to 115.9 ± 16.57 U/mg prot (p < 0.05). POPEP-III also prevented CCl4-induced oxidative liver histological alteration. The results suggest that POPEP-III can protect the liver from CCl4-induced oxidative damage.
Exploring Relationships of Sleep Duration with Eating and Physical Activity Behaviors among Canadian University Students
Authors: Papaconstantinou Efrosini , Quick Virginia , Vogel Ellen , Coffey Sue , Miller Andrea , Zitzelsberger Hilde
Published: May 2020

Background: Students pursuing postsecondary education are a population described as vulnerable for sleep problems, poor dietary habits, weight gain, and reduced physical activity. The primary goal of this study was to examine relationships of sleep behaviors with eating and physical activity behaviors in a sample of undergraduate health sciences students. Methods: Using a cross-sectional design, undergraduate health sciences students in a small Canadian university were recruited to complete an on-line questionnaire about their sleep, eating, and physical activity behaviors using valid and reliable instruments. Key sociodemographic characteristics and self-reported height and weight data were also captured. Results: The participants (n = 245) were on average 23 years of age, female (86%), and the majority were full-time students (92%). The mean BMI was within a healthy range (mean 24.58 SD 5.55) with the majority reporting low physical activity levels (65%). Despite self-reports of very or fairly good (65%) sleep quality in the past month, the mean global sleep scores (scores > 5, mean 7.4, SD 3.3) indicated poor overall sleep quality. Poorer sleep quality was associated with higher BMIs (r = 0.265, p < 0.001). Conclusions: The findings highlight the need to expand the scope of on-campus wellness programs to promote healthy sleep habits in a vulnerable university population.
Fabrication of Robust Water-Repellent Technology on Cotton Fabric via Reaction of Thiol-ene Click Chemistry
Authors: Chen Xinpeng , Wang Baoliang , Chu Runshan , Xing Tieling , Chen Guoqiang
Published: May 2020

A robust superhydrophobic fabric coating was fabricated on cotton fabric under UV light, which was achieved by convenient surface modification with mercaptopropyltriethoxysilane, tetramethyltetravinylcyclotetrasiloxane, and octadecyl mercaptan. The modification of cotton fabric with 3-mercaptopropyltriethoxysilane introduces reactive mercapto groups, after which 2,4,6,8-tetramethyltetravinylcyclotetrasiloxane reacts with mercapto groups, and octadecyl mercaptan provides microscale roughness. The nonpolar carbon chains of thiol cause the cotton to have a low surface energy. As reported, the combination of microscale roughness with low surface energy has a superhydrophobic effect on cotton, which leads to a high contact angle of 161.8° and sliding angle of 8°. Infrared spectroscopy, XPS, and SEM tests were used to characterize the chemical structure and morphological changes of the surface of cotton fabric before and after click reaction. The fabric after click reaction exhibited an oil–water mixture separation ability owing to its superhydrophobicity. Thus, the finished fabric could be used in the oil–water separation field. Importantly, the superhydrophobic textile displays resistance to laundering, mechanical abrasion, strong acidic and alkaline environments, and UV irradiation. We hope that this study can broaden the real-life applications of cotton fabric.
Numerical Simulation to Determine the Effect of Topological Entropy on the Effective Transport Coefficient of Unidirectional Composites
Authors: Pacheco Carlos , Barbosa Romeli , Rodriguez Abimael , Oskam Gerko , Ruiz-Gómez Miguel , Escobar Beatriz
Published: May 2020

The influence of topological entropy (TS) on the effective transport coefficient (ETC) of a two-phase material is analyzed. The proposed methodology studies a system of aligned bars that evolves into a stochastic heterogeneous system. This proposal uses synthetic images generated by computational algorithms and experimental images from the scanning electron microscope (SEM). Microstructural variation is imposed for statistical reconstruction moments by simulated annealing (SA) and it is characterized through TS applied in Voronoi diagrams of the studied systems. On the other hand, ETC is determined numerically by the Finite Volume Method (FVM) and generalized by a transport efficiency of charge (ek). The results suggest that our approach can work as a design tool to improve the ETC in stochastic heterogeneous materials. The case studies show that ek decreases when TS increases to the point of stability of both variables. For example, for the 80% surface fraction, in the particulate system of diameter D = 1, ek = 50.81 ± 0.26% @ TS = 0.27 ± 0.002; when the system has an agglomerate distribution similar to a SEM image, ek = 45.69 ± 0.60% @ TS = 0.32 ± 0.002.
Glycera sheikhmujibi n. sp. (Annelida: Polychaeta: Glyceridae): A New Species of Glyceridae from the Saltmarsh of Bangladesh
Authors: Hossain M. , Hutchings Pat
Published: May 2020

A new species of glycerid polychaete, Glycera sheikhmujibi, is described from the saltmarsh on the central coast of Bangladesh. The species is identified based on morphological characteristics using both a light microscope and scanning electron microscope (SEM). The species is characterized by the presence of three distinct types of proboscideal papillae: type 1 papillae (conical with three transverse ridges), type 2 (conical with a straight, median, longitudinal ridge), and type 3 (round, shorter, and broader, with a straight, median, longitudinal ridge). It has a Y-shaped aileron with gently incised triangular base, almost equal-size digitiform noto- and neuropodial lobes in the mid-body, and long ventral cirri at the posterior end. The new species is compared with its related species, previously described from the Bay of Bengal region. A key to all these species is provided.
Multistability Emergence through Fractional-Order-Derivatives in a PWL Multi-Scroll System
Authors: Echenausía-Monroy José Luis , Huerta-Cuellar Guillermo , Jaimes-Reátegui Rider , García-López Juan Hugo , Aboites Vicente , Cassal-Quiroga Bahia Betzavet , Gilardi-Velázquez Héctor Eduardo
Published: May 2020

In this paper, the emergence of multistable behavior through the use of fractional-order-derivatives in a Piece-Wise Linear (PWL) multi-scroll generator is presented. Using the integration-order as a bifurcation parameter, the stability in the system is modified in such a form that produces a basin of attraction segmentation, creating many stable states as scrolls are generated in the integer-order system. The results here presented reproduce the same phenomenon reported in systems with integer-order derivatives, where the multistable regimen is obtained through a parameter variation. The multistable behavior reported is also validated through electronic simulation. The presented results are not only applicable in engineering fields, but they also enrich the analysis and the understanding of the implications of using fractional integration orders, boosting the development of further and better studies.
A Novel Approach for Biofilm Detection Based on a Convolutional Neural Network
Authors: Dimauro Giovanni , Deperte Francesca , Maglietta Rosalia , Bove Mario , La Gioia Fabio , Renò Vito , Simone Lorenzo , Gelardi Matteo
Published: May 2020

Rhinology studies anatomy, physiology and diseases affecting the nasal region: one of the most modern techniques to diagnose these diseases is nasal cytology or rhinocytology, which involves analyzing the cells contained in the nasal mucosa under a microscope and researching of other elements such as bacteria, to suspect a pathology. During the microscopic observation, bacteria can be detected in the form of biofilm, that is, a bacterial colony surrounded by an organic extracellular matrix, with a protective function, made of polysaccharides. In the field of nasal cytology, the presence of biofilm in microscopic samples denotes the presence of an infection. In this paper, we describe the design and testing of interesting diagnostic support, for the automatic detection of biofilm, based on a convolutional neural network (CNN). To demonstrate the reliability of the system, alternative solutions based on isolation forest and deep random forest techniques were also tested. Texture analysis is used, with Haralick feature extraction and dominant color. The CNN-based biofilm detection system shows an accuracy of about 98%, an average accuracy of about 100% on the test set and about 99% on the validation set. The CNN-based system designed in this study is confirmed as the most reliable among the best automatic image recognition technologies, in the specific context of this study. The developed system allows the specialist to obtain a rapid and accurate identification of the biofilm in the slide images.
Role of Root and Stem Base Fungi in Fraxinus angustifolia (Vahl) Dieback in Croatian Floodplain Forests
Authors: Kranjec Orlović Jelena , Moro Maja , Diminić Danko
Published: May 2020

Large-scale ash (Fraxinus spp.) dieback caused by the fungus Hymenoscyphus fraxineus has been a major concern throughout Europe for more than two decades. Most of the related research has been focused on Fraxinus excelsior L., and there is still little information on fungal involvement in the dieback of Fraxinus angustifolia Vahl, especially in roots and stem bases, which play an important role in decline progress and tree stability. The objectives of this study were to identify fungi present in visually healthy and symptomatic wood tissues in basal parts of narrow-leaved ash trees in different decline phases, in order to determine the possible role of these fungi and their importance in the dieback process. The stem bases and roots of 90 trees in three different health categories, determined based on crown defoliation, were sampled in natural stands affected by ash dieback. Isolated fungal cultures were identified based on the rDNA ITS (Internal transcribed spacer) region and their association with tree health status was analyzed. In total, 68 different fungal taxa were confirmed, including Hymenoscyphus fraxineus and Armillaria spp., which were mainly present in roots, although overall in lower frequencies than on common ash in other studies. Most frequently isolated fungal taxa, which encompassed 51% of all obtained isolates, were Trichoderma spp., Ilyonectria robusta, Fusarium solani, Cladosporium cladosporioides, and Diaporthe cotoneastri. Their associations with tree health categories and presence in both symptomatic and visually healthy wood indicate that they act as opportunistic pathogens and early colonizers of weakened ash tissues. Research also revealed that, although the extent of crown defoliation and presence of root and stem necroses were associated, basal symptoms occurred on a number of trees with healthy looking crowns, meaning they can develop independently.
Model for Taking Care of Patients with Early Childhood Caries during the SARS-Cov-2 Pandemic
Authors: Cianetti Stefano , Pagano Stefano , Nardone Michele , Lombardo Guido
Published: May 2020

Pending the availability of vaccines to contain the SARS-CoV-2 pandemic, the current solution is “social distancing” with a reduction of dental treatments to those assessed as urgent and emergency cases. These treatments also involve Early Childhood Caries (ECC) due to the fact that this disease affects preschool children (a vulnerable population) and, in addition, shows a propensity to evolve into more serious complications (dental pain, infections). A narrative review was carried out to support a protocol for treating ECC with efficacious and safe (in terms of SARS-CoV-2 transmission) procedures. Protocol involves criteria for patients’ selection remotely (telemedicine), and well-detailed criteria/equipment and hygiene procedures to combat against SARS-CoV-2 transmission. Moreover, the protocol proposes innovative caries treatments, named Minimally Invasive Treatments (MITs), well known in pedodontics for their high level of children’s acceptance during dental care. MITs allow for caries removal (particularly in primary teeth) without any high-speed rotating instrument cooled with nebulized air-water spray (with high risk of virus environmental diffusion), usually adopted during traditional treatments. For evaluating MITs effectiveness in caries management, only Systematic Review and Randomized Controlled Trials (RCTs) were included in our study, without any risk of bias assessment. The indications proposed in this protocol could support clinicians for the temporary management of ECC until the SARS-CoV-2 pandemic ends.
Relationship Between Knowledge and Types of Attitudes Towards People Living with Dementia
Authors: Chang Chia-Yu , Hsu Hui-Chuan
Published: May 2020

The purpose of this study was to examine the relationship between knowledge and attitudes towards dementia among adults. A cross-sectional online survey with purposive sampling was conducted in four district health centers in Taichung, Taiwan, in 2018. Knowledge was measured by the Taiwanese version of the Dementia Knowledge Assessment Scale. Attitudes towards people with dementia were measured by four kinds of feelings: discomfort, shame, avoidance, and fear. In total, 347 persons completed the questionnaire. Knowledge of dementia was modest. Higher education, a care-related background, chronic health conditions, experience caring for people with dementia, and knowledge of family history were related to higher knowledge of dementia. Attitudes towards people with dementia were grouped into four clusters: uncomfortable (22.2%), ashamed (2.6%), unfriendly (22.5%), and non-negative (52.7%). Knowledge of dementia was significantly related to the ashamed cluster but not to the other clusters. Lower education, a lack of caring experience, and a lack of knowledge of family history were related to uncomfortable feelings, and poorer financial satisfaction was related to uncomfortable, afraid, and avoidant feelings. The open-question expression of feelings towards dementia was more likely to be negative (55.3%). The public should be educated on knowledge of and friendly attitudes towards dementia.
Effect of Neuromuscular Electrical Stimulation on Masseter Muscle Thickness and Maximal Bite Force among Healthy Community-Dwelling Persons Aged 65 Years and Older: A Randomized, Double Blind, Placebo-Controlled Study
Authors: Chang Moon-Young , Lee Gihyoun , Jung Young-Jin , Park Ji-Su
Published: May 2020

Aim: This study investigated the effect of neuromuscular electrical stimulation (NMES) on masseter muscle thickness and maximal bite force among healthy community-dwelling elderly persons older than 65 years. Materials and methods: A total of 40 participants were randomly assigned to the experimental and placebo groups. In the experimental group, NMES was applied to both masseter muscles, and electrical signals were gradually increased until the participants felt a grabbing sensation (range 6.0–7.5 mA) in the masseter muscle. The placebo group, in contrast, underwent NMES in the same manner and procedure as the experimental group with less electrical intensity (0.5 mA). All interventions were administered five times a week for six weeks, 20 min per day. The outcomes were masseter muscle thickness assessed using ultrasound and maximal bite force using a bite force meter. The level of significance was set as p < 0.05. Results: The experimental group showed a significant increase in both masseter muscle thickness and maximal bite force as compared with the placebo group (p = 0.002 and 0.019, respectively). Moreover, the degree of change in the masseter muscle thickness and maximal bite force significantly increased in the experimental and placebo groups (p < 0.001, both). Conclusions: This study demonstrated that NMES could be an effective modality for increasing masseter muscle thickness and maximal bite force in healthy older adults.
Construction, Detection, and Interpretation of Crime Patterns over Space and Time
Authors: Wang Zengli , Zhang Hong
Published: May 2020

Empirical studies have focused on investigating the interactive relationships between crime pairs. However, many other types of crime patterns have not been extensively investigated. In this paper, we introduce three basic crime patterns in four combinations. Based on graph theory, the subgraphs for each pattern were constructed and analyzed using criminology theories. A Monte Carlo simulation was conducted to examine the significance of these patterns. Crime patterns were statistically significant and generated different levels of crime risk. Compared to the classical patterns, combined patterns create much higher risk levels. Among these patterns, “co-occurrence, repeat, and shift” generated the highest level of crime risk, while “repeat” generated much lower levels of crime risk. “Co-occurrence and shift” and “repeat and shift” showed undulated risk levels, while others showed a continuous decrease. These results outline the importance of proposed crime patterns and call for differentiated crime prevention strategies. This method can be extended to other research areas that use point events as research objects.
Fine-Scale Dasymetric Population Mapping with Mobile Phone and Building Use Data Based on Grid Voronoi Method
Authors: Peng Zhenghong , Wang Ru , Liu Lingbo , Wu Hao
Published: May 2020

Fine-scale population mapping is of great significance for capturing the spatial and temporal distribution of the urban population. Compared with traditional census data, population data obtained from mobile phone data has high availability and high real-time performance. However, the spatial distribution of base stations is uneven, and the service boundaries remain uncertain, which brings significant challenges to the accuracy of dasymetric population mapping. This paper proposes a Grid Voronoi method to provide reliable spatial boundaries for base stations and to build a subsequent regression based on mobile phone and building use data. The results show that the Grid Voronoi method gives high fitness in building use regression, and further comparison between the traditional ordinary least squares (OLS) regression model and geographically weighted regression (GWR) model indicates that the building use data can well reflect the heterogeneity of urban geographic space. This method provides a relatively convenient and reliable idea for capturing high-precision population distribution, based on mobile phone and building use data.
Hierarchical Point Matching Method Based on Triangulation Constraint and Propagation
Authors: Wang Jingxue , Zhang Ning , Wu Xiangqian , Wang Weixi
Published: May 2020

Reliable image matching is the basis of image-based three-dimensional (3D) reconstruction. This study presents a quasi-dense matching method based on triangulation constraint and propagation as applied to different types of close-range image matching, such as illumination change, large viewpoint, and scale change. The method begins from a set of sparse matched points that are used to construct an initial Delaunay triangulation. Edge-to-edge matching propagation is then conducted for the point matching. Two types of matching primitives from the edges of triangles with areas larger than a given threshold in the reference image, that is, the midpoints of edges and the intersections between the edges and extracted line segments, are used for the matching. A hierarchical matching strategy is adopted for the above-mentioned primitive matching. The points that cannot be matched in the first stage, specifically those that failed in a gradient orientation descriptor similarity constraint, are further matched in the second stage. The second stage combines the descriptor and the Mahalanobis distance constraints, and the optimal matching subpixel is determined according to an overall similarity score defined for the multiple constraints with different weights. Subsequently, the triangulation is updated using the newly matched points, and the aforementioned matching is repeated iteratively until no new matching points are generated. Twelve sets of close-range images are considered for the experiment. Results reveal that the proposed method has high robustness for different images and can obtain reliable matching results.