bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on gait planning of Hexapod wheel legged robot based on STM32 single chip microcomputer
Authors: Zenan Chu , Wei Wang , Yu Caisheng 
Published: June 2020

Abstract
In this paper, the rectangular wheel legged hexapod robot is used as the experimental robot, the STM32 single-chip microcomputer is used as the main control core, the steering control board is used as the auxiliary board, the upper computer programming is used to write the action group of the hexapod robot, the command is sent to the single-chip microcomputer through the PS2 handle, the single-chip microcomputer controls the steering board to achieve the corresponding action group, and the Arduino control board is used to change the environment through the sensor in the later stage The control of action group can be realized by the detection. In addition, in order to solve the gait planning problem of hexapod robot and realize the optimal learning of robot’s free gait on specific terrain, based on the discretization of the robot’s single foot distance, integrating the time rhythm principle of CPG model and the space rule constraint mechanism of reflection model, a discrete gait model of Hexapod robot is constructed. Ant colony algorithm is used to study the gait path planning of the robot. MATLAB and C language technology are used to realize the simulation of the gait planning of the hexapod robot.
New Design of All-terrain Smart Car Based on Arduino
Authors: He ZhengYang , Zhang Ying , Zheng HongMing , Zhang Yi , Yu HongTao , Luo MingNan 
Published: June 2020

Abstract
Due to bad working environment, the flexibility and steering stability of all-terrain vehicles have become the main factors affecting the performance. Designing a new all-terrain electric vehicle is aimed at improving the stability of driving on low-attach roads and maneuverability at low speeds. Compared with traditional internal combustion engines, four-wheel-drive all-terrain vehicles have obvious advantages in vehicle motion control and optimal allocation of driving force, thus making it play an important role in all-terrain vehicle technology in the future. Within the scope of the requirements of the “Explorer” modular component equipment, by means of prototype design, assembly, commissioning, operation, the smart vehicles that can automatically and smoothly pass through the obstacles of ten different characteristics and different difficulty without any intervention are designed and completed.
A review of artificial intelligence techniques for selection & evaluation
Authors: Ahmad Ijaz , Liu Yan , Javeed Danish , Shamshad Nadia , Sarwr Danish , Ahmad Shahab 
Published: June 2020

Abstract
Today, supplier selection &evaluation has been an important issue of strategic planning for a long time. Various artificial intelligence (AI) methods have been applied in the methodology of supplier section & evaluation from different researchers. This paper provides a review of past various artificial intelligence methods (AI) from 2010 to 2018 in the area supplier selection & evaluation problems. The review report is based on the literature of fifty articles include six review papers. Our survey presents and tries to find out the most useful and prominent AI method recommendable for the future in the problem of supplier selection &evalution.
Fatigue detection based on multi-feature fusion of fatigue behavior
Authors: Xing Chen , Lumei Su , Meixin Qin 
Published: June 2020

Abstract
The research of fatigue driving detection is of great significance due to the contribution in fatigue driving prevention. However, most of current fatigue detection study are limited to unavailable real-time performance, unsatisfied accuracy rate, rough fatigue level and complicated implementation. In this paper, a novel method based on multi fatigue behavior features are proposed to improve the accuracy of fatigue detection. First of all, multi facial behavior features including eyes, mouth and head features are extracted. And then a new multi-feature fusion fatigue detection approach based on specific fatigue behavior feature anaylsis is proposed to recognize the previously extracted features. For better accuracy and applicability, a more detailed fatigue levels are newly used to subdivide fatigue behavior into three degree of fatigue. The experimental results based Matlab simulation and Android App indicate that the proposed method could accurately and real-time detect whether the tester is in a state of fatigue driving, and also determine the fatigue level.
Mechanical and tribological properties of AA7075-T6 metal matrix composite reinforced with ceramic particles and aloevera ash via Friction stir processing
Authors: Tyagi Lakshay , Butola Ravi , Jha Avinash Kumar 
Published: June 2020

Abstract
Mechanical and wear properties of AA7075-T6 reinforced with SiC and Aloevera ash, fabricated using Friction stir processing (FSP) are investigated in this study. Due to less density, easy availability, and cost-effectiveness, aloevera ash is considered as one of the reinforcements. FSP is done using a square tool pin profile, at different tool rotational speeds. To study wear behaviour, pin on disc test is carried out on High Temperature Rotary Tribometer at 20N, 30N and 40N applied load. Wear increases on increasing the applied load and at 20N load Al+SiC/Aloevera ash composite, processed at 600 tool rpm gave the best results due to the formation of oxide tribolayer. At 30N and 40N applied load Al+SiC composite, processed at 900 tool rpm showed the least wear because of proper scattering of ceramic particles due to high tool rotational speed. Coefficient of friction increases on increasing the applied load and all fabricated composite samples showed a lesser coefficient of friction than the base metal. Microhardness, ductility and Ultimate tensile strength increases on the addition of reinforcement and had a direct relation with tool rpm. Wear morphology was analysed using Scanning Electron Microscope (SEM). Energy Dispersive Spectroscopy (EDS) analysis after wear shows the presence of C, Fe, O, Mg, Zn, Si, Al elements and confirms the formation of an oxide layer which is responsible for decreasing wear loss.
Study on the influence of ion doping on the crystal structure and magnetic properties of YFeO3
Authors: Ji Lingxian , Jiang Guojian , Wu Dandan , Chen Jianbin 
Published: June 2020

Abstract
A series of pure phase YFeO3 sample powders doped with Eu3+ and Nd3+ were synthesized by sol-gel method. The influence of different ions doping on the crystal structure and magnetic properties of YFeO3 were investigated. The prepared sample powders were characterized by powder x-ray diffractometer, scanning electron microscope, energy dispersive spectrometer, Fourier transform infrared spectrometer, differential thermal analyzer and vibrating sample magnetometer. The results demonstrate that all sample powders are pure phase orthogonal perovskite structures, the crystal structure and the magnetization have changed. The lattice parameters and the saturation magnetization increases with the increase of ion radius or ion concentration in single doping system. In the case of double doping, the influence of the crystal structure and magnetic properties of YFeO3 is more complicated than that of single doping according to the change of ions concentration.
Effect of multiple deep cryo-treating and tempering on microstructure and property evolution of high carbon bearing steel
Authors: Zhou Guanghua , Deng Song , Wei Wenting , Liu Qinglong 
Published: June 2020

Abstract
Interest has been shown in cryogenic treatments over the last seven decades mainly due to the transformation of retained austenite and the precipitation of fine carbides. By changing the microstructure, cryogenic treatments can improve wear resistance and hardness to some extent. In this work, the effect of multiple deep cryo-treating and tempering (DCTT) on microstructural evolution in 52100 bearing steel has been investigated using x-ray diffraction (XRD) and scanning electron microscopy (SEM). The Rockwell hardness tests were also conducted to verify the microstructure evolution. Moreover, the dilatometry was used to estimate the dimensional stability. The results demonstrated that DCTT not only contributes to the precipitation of nano-size carbides, but also leads to a more homogeneous size distribution. It was also proved that the variation of carbides and hardness could be attributed to the synergy of decrease of retained austenite and movement of carbon atoms brought in DCTT. Furthermore, the sample subjected to DCTT exhibits the highest wear resistance property.
Understanding dynamic properties of materials using neutron spectroscopy and atomistic simulation
Authors: Armstrong Jeff , O’Malley Alexander J , Ryder Matthew R , Butler Keith T 
Published: June 2020

Abstract
Recent developments in first-principles lattice dynamics and classical force field based molecular dynamics are revolutionising the field of neutron spectroscopy. Herein we present a short review of these methods, their critical role in the supporting of cutting-edge experiments, and how they are improved by matching experimental data. We begin with a brief overview of how lattice dynamics calculations can be compared to inelastic neutron scattering (INS) and molecular dynamics simulations to both INS and quasi-elastic neutron scattering (QENS). We then provide a series of exemplar applications where lattice dynamics and molecular dynamics have been used in conjunction with neutron spectroscopy to bring significant understanding to topical areas of materials science namely: (i) lattice dynamics and INS for the study of hybrid organic-inorganic perovskites (ii) lattice dynamics and INS for the study of flexible porous solids and (iii) molecular dynamics and QENS for probing molecular behaviour in zeolite catalysis. In all three cases, the understanding gained through the synergy of experiment and computation would have been significantly reduced using either in isolation. Finally, we consider the current state of the art, describing outstanding challenges and suggesting future directions in this exciting and fertile area of physical science.
Simulation study of a fluorine spectrums induced by laser sublimation
Authors: Daoui H , Benmebrouk L , Tlili S , Kaddour A , Mohammedi L , Achouri A 
Published: June 2020

AbstractThis paper aims to numerical study of the experimental spectrum, in the context of the diagnosis of solid materials by spectroscopy; the resulting spectrum of fluorine plasma has beenanalyzed. The plasma is generated after the sublimation of the solid sample the fluorine by Laser Induced Breakdown Spectroscopy (LIBS technique). The theoretical spectra and the electronic temperature of a obtained plasma have been calculated, this temperature (1.92 eV) is well matched to the laboratory plasma criteria. The main results also are showed that the resulting medium consisted of 96.63% Calcium and 3.36% Fluor.
Coherent optical communications enhanced by machine intelligence
Authors: Lohani Sanjaya , Glasser Ryan T 
Published: June 2020

Abstract
Accuracy in discriminating between different received coherent signals is integral to the operation of many free-space communications protocols, and is often difficult when the receiver measures a weak signal. Here we design an optical communication scheme that uses balanced homodyne detection in combination with an unsupervised generative machine learning and convolutional neural network (CNN) system, and demonstrate its efficacy in a realistic simulated coherent quadrature phase shift keyed (QPSK) communications system. Additionally, we design the neural network system such that it autonomously learns to correct for the noise associated with a weak QPSK signal, which is distributed to the receiver prior to the implementation of the communications. We find that the scheme significantly reduces the overall error probability of the communications system, achieving the classical optimal limit. We anticipate that these results will allow for a significant enhancement of current classical and quantum coherent optical communications technologies.
FoldRec-C2C: protein fold recognition by combining cluster-to-cluster model and protein similarity network
Authors: Shao Jiangyi , Yan Ke , Liu Bin 
Published: June 2020

AbstractAs a key for studying the protein structures, protein fold recognition is playing an important role in predicting the protein structures associated with COVID-19 and other important structures. However, the existing computational predictors only focus on the protein pairwise similarity or the similarity between two groups of proteins from 2-folds. However, the homology relationship among proteins is in a hierarchical structure. The global protein similarity network will contribute to the performance improvement. In this study, we proposed a predictor called FoldRec-C2C to globally incorporate the interactions among proteins into the prediction. For the FoldRec-C2C predictor, protein fold recognition problem is treated as an information retrieval task in nature language processing. The initial ranking results were generated by a surprised ranking algorithm Learning to Rank, and then three re-ranking algorithms were performed on the ranking lists to adjust the results globally based on the protein similarity network, including seq-to-seq model, seq-to-cluster model and cluster-to-cluster model (C2C). When tested on a widely used and rigorous benchmark dataset LINDAHL dataset, FoldRec-C2C outperforms other 34 state-of-the-art methods in this field. The source code and data of FoldRec-C2C can be downloaded from http://bliulab.net/FoldRec-C2C/download.
Unexpected low genetic differentiation between Japan and Bering Sea populations of a deep-sea benthic crustacean lacking a planktonic larval stage (Peracarida: Tanaidacea)
Authors: Kakui Keiichi , Nomaki Hidetaka , Komatsu Hironori , Fujiwara Yoshihiro 
Published: June 2020

AbstractInformation on the extent, diversity and connectivity of populations is lacking for most deep-sea invertebrates. Species of the order Tanaidacea (Crustacea), one of the most diverse and abundant macrofaunal groups in the deep sea, are benthic, lack a planktonic larval stage, and thus would be expected to have narrow distributional ranges. However, with molecular evidence from the COI gene, we show here that the deep-sea tanaidacean Carpoapseudes spinigena has a distributional range spanning at least 3700 km, from off northern Japan to the south-eastern Bering Sea. Living individuals found in a sediment core indicated that the species is a sedentary burrower. COI analyses revealed a low level of genetic diversity overall, and low differentiation (p-distance, 0.2–0.8%) between the Japan and Bering Sea populations. One hypothesis to explain the low genetic diversity over a broad region is that the Japan population was founded by individuals transported by ocean currents from the Bering Sea. However, due to limited data, other explanations cannot be ruled out. Our results indicate that continued sampling is of fundamental importance to understanding how genetic and taxonomic diversity originate and are maintained in the deep sea.
Rapid Detection Methods for Bacterial Pathogens in Ambient Waters at the Point of Sample Collection: A Brief Review
Authors: Li Jing , Zhu Yanzhe , Wu Xunyi , Hoffmann Michael R 
Published: June 2020

Abstract
The world is currently facing a serious health burden of waterborne diseases, including diarrhea, gastrointestinal diseases, and systemic illnesses. The control of these infectious diseases ultimately depends on the access to safe drinking water, properly managed sanitation, and hygiene practices. Therefore, ultrasensitive, rapid, and specific monitoring platforms for bacterial pathogens in ambient waters at the point of sample collection are urgently needed. We conducted a literature review on state-of-the-art research of rapid in-field aquatic bacteria detection methods, including cell-based methods, nucleic acid amplification detection methods, and biosensors. The detection performance, the advantages, and the disadvantages of the technologies are critically discussed. We envision that promising monitoring approaches should be automated, real-time, and target-multiplexed, thus allowing comprehensive evaluation of exposure risks attributable to waterborne pathogens and even emerging microbial contaminants such as antibiotic resistance genes, which leads to better protection of public health.
Performance of Oropharyngeal Swab Testing Compared With Nasopharyngeal Swab Testing for Diagnosis of Coronavirus Disease 2019—United States, January 2020–February 2020
Authors: Patel Monita R , Carroll Darin , Ussery Emily , Whitham Hilary , Elkins Christopher A , Noble-Wang Judith , Rasheed James Kamile , Lu Xiaoyan , Lindstrom Stephen , Bowen Virginia , Waller Jessica , Armstrong Gregory , Gerber Susan , Brooks John T 
Published: June 2020

Abstract
Among 146 nasopharyngeal (NP) and oropharyngeal (OP) swab pairs collected ≤7 days after illness onset, Real-Time Reverse Transcriptase Polymerase Chain Reaction assay for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 RT-PCR) diagnostic results were 95.2% concordant. However, NP swab cycle threshold values were lower (indicating more virus) in 66.7% of concordant-positive pairs, suggesting NP swabs may more accurately detect the amount of SARS-CoV-2.
Asymptomatic SARS-CoV-2 Infection and COVID-19 Mortality During an Outbreak Investigation in a Skilled Nursing Facility
Authors: Patel Mahesh C , Chaisson Lelia H , Borgetti Scott , Burdsall Deborah , Chugh Rashmi K , Hoff Christopher R , Murphy Elizabeth B , Murskyj Emily A , Wilson Shannon , Ramos Joe , Akker Lynn , Bryars Debra , Thomas-Smith Evonda , Bleasdale Susan C , Ezike Ngozi O 
Published: June 2020

Abstract

Background
Outbreaks of coronavirus disease 2019 (COVID-19) have been reported in nursing homes and assisted living facilities; however, the extent of asymptomatic and presymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in this high-risk population remains unclear.

Methods
We conducted an investigation of the first known outbreak of SARS-CoV-2 at a skilled nursing facility (SNF) in Illinois on 15 March 2020 and followed residents for 30 days. We tested 126/127 residents for SARS-CoV-2 via reverse-transcription polymerase chain reaction and performed symptom assessments. We calculated the point prevalence of SARS-CoV-2 and assessed symptom onset over 30-day follow-up to determine: (1) the proportion of cases who were symptomatic, presymptomatic, and asymptomatic and (2) incidence of symptoms among those who tested negative. We used the Kaplan-Meier method to determine the 30-day probability of death for cases.

Results
Of 126 residents tested, 33 had confirmed SARS-CoV-2 on 15 March. Nineteen (58%) had symptoms at the time of testing, 1 (3%) developed symptoms over follow-up, and 13 (39%) remained asymptomatic. Thirty-five residents who tested negative on 15 March developed symptoms over follow-up; of these, 3 were re-tested and 2 were positive. The 30-day probability of death among cases was 29%.

Conclusions
SNFs are particularly vulnerable to SARS-CoV-2, and residents are at risk of severe outcomes. Attention must be paid to preventing outbreaks in these and other congregate care settings. Widespread testing and infection control are key to help prevent COVID-19 morbidity and mortality in these high-risk populations.
Alterations of the Oral Microbiome and Cumulative Carbapenem Exposure Are Associated With Stenotrophomonas maltophilia Infection in Patients With Acute Myeloid Leukemia Receiving Chemotherapy
Authors: Aitken Samuel L , Sahasrabhojane Pranoti V , Kontoyiannis Dimitrios P , Savidge Tor C , Arias Cesar A , Ajami Nadim J , Shelburne Samuel A , Galloway-Peña Jessica R 
Published: June 2020

Abstract

Background
Stenotrophomonas maltophilia is increasingly common in patients with acute myeloid leukemia (AML). Little is known about factors that drive S. maltophilia infection. We evaluated the microbiome and cumulative antibiotic use as predictors of S. maltophilia infection in AML patients receiving remission induction chemotherapy (RIC).

Methods
Subanalysis of a prospective, observational cohort of patients with AML receiving RIC between September 2013 and August 2015 was performed. Fecal and oral microbiome samples collected from initiation of RIC until neutrophil recovery were assessed for the relative abundance of Stenotrophomonas via 16S rRNA gene quantitation. The primary outcome, microbiologically proven S. maltophilia infection, was analyzed using a time-varying Cox proportional hazards model.

Results
Of 90 included patients, 8 (9%) developed S. maltophilia infection (pneumonia, n = 6; skin–soft tissue, n = 2); 4/8 (50%) patients were bacteremic; and 7/8 (88%) patients with S. maltophilia infection had detectable levels of Stenotrophomonas vs 22/82 (27%) without infection (P &lt; .01). An oral Stenotrophomonas relative abundance of 36% predicted infection (sensitivity, 96%; specificity, 93%). No association of S. maltophilia infection with fecal relative abundance was found. Cumulative meropenem exposure was associated with increased infection risk (hazard ratio, 1.17; 95% confidence interval, 1.01–1.35; P = .03).

Conclusions
Here, we identify the oral microbiome as a potential source for S. maltophilia infection and highlight cumulative carbapenem use as a risk factor for S. maltophilia in leukemia patients. These data suggest that real-time monitoring of the oral cavity might identify patients at risk for S. maltophilia infection.
The Role of FER rs4957796 in the Risk of Developing and Dying from a Bloodstream Infection: A 23-Year Follow-up of the Population-based Nord-Trøndelag Health Study
Authors: Rogne Tormod , Damås Jan Kristian , Flatby Helene Marie , Åsvold Bjørn Olav , DeWan Andrew Thomas , Solligård Erik 
Published: June 2020

Abstract

Background
Bloodstream infection and sepsis are major causes of health loss worldwide, and it is important to identify patients at risk of developing and dying from these conditions. The single-nucleotide polymorphism most strongly associated with sepsis mortality is FER rs4957796. However, it is not known how this variant is associated with bloodstream infection incidence and mortality.

Methods
We used prospective data from 1995–2017 from the population-based HUNT Study. Genotypes were ascertained from blood samples, and additional genotypes were imputed. Information on bloodstream infection and diagnosis codes at hospitalization were collected through record linkage with all hospitals in the area.

Results
A total of 69 294 patients were included. Patients with the rs4957796 CC genotype had an increased risk of developing a bloodstream infection compared with the TT genotype (hazard ratio [HR], 1.20; 95% confidence interval [CI], 1.00–1.43). However, there was a protective additive effect of the C allele in terms of mortality in the total study population (HR, 0.77; 95% CI, .64–.92 per copy of the C allele) and among bloodstream infection patients (odds ratio, 0.70; 95% CI, .58–.85 per copy of the C allele). The results did not appear to be affected by selection bias.

Conclusions
The rs4957796 CC genotype was associated with an increased risk of contracting a bloodstream infection but with a reduced risk of dying from one. The latter finding is in line with studies of sepsis case fatality, while the former expands our understanding of the immunoregulatory role of this polymorphism.