bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine-learning-based classification of Stokes-Mueller polarization images for tissue characterization
Authors: Sindhoora K M , Spandana K U , Ivanov D , Borisova E , Raghavendra U , Rai S , Kabekkodu S P , Mahato K K , Mazumder N 
Published: April 2021

Abstract
The microstructural analysis of tissues plays a crucial role in the early detection of abnormal tissue morphology. Polarization microscopy, an optical tool for studying the anisotropic properties of biomolecules, can distinguish normal and malignant tissue features even in the absence of exogenous labelling. To facilitate the quantitative analysis, we developed a polarization-sensitive label-free imaging system based on the Stokes-Mueller calculus. Polarization images of ductal carcinoma tissue samples were obtained using various input polarization states and Stokes-Mueller images were reconstructed using Matlab software. Further, polarization properties, such as degree of linear and circular polarization and anisotropy, were reconstructed from the Stokes images. The Mueller matrix obtained was decomposed using the Lu-Chipman decomposition method to acquire the individual polarization properties of the sample, such as depolarization, diattenuation and retardance. By using the statistical parameters obtained from the polarization images, a support vector machine (SVM) algorithm was trained to facilitate the tissue classification associated with its pathological condition.
Electrochemically-stabilized carbon materials for supercapacitor prototypes
Authors: Petrov M , Lovchinov K , Slavov L , Hikov T , Tyutyundzhiev N 
Published: April 2021

Abstract
A study is presented on supercapacitor prototypes using chimney soot as the active electrode material. Despite its highly developed surface and the existence of capacitive properties, some compounds present in chimney soot make it unstable during the charge process. The irreversible electrochemical process leads to anodic oxidation and cathodic reduction of the soot. In this work, chimney soot was treated electrochemically with different electrochemical potentials, thus altering the initial organic compounds in the material; different parts of organic compounds were affected, so that more stable compounds remained, without all functional groups being removed. The altered material was investigated by IR and TEM spectroscopy. Supercapacitor prototypes were subjected to charge-discharge cycles and their capacitances were determined and compared.
Application of optical sensor array in partial discharge signal location of GIS/GIL
Authors: Shiling Zhang 
Published: April 2021

Abstract
The optical sensor array inside the high-voltage equipment can effectively realize the on-line measurement of the high-voltage switch operation state, significantly improve the efficiency and accuracy of SF6 Electrical equipment fault diagnosis, and effectively guarantee the safety and reliability of equipment operation. Firstly, the structure and performance of the micro optical sensor are analyzed, and the system model and data processing unit of the optical sensor array are given. Furthermore, the influence characteristics of single sensor and array sensor Gaussian noise on signal are given, and the noise elimination strategy of observation signal based on Kalman filter is given. The results show that: the optical sensor has a good focusing ability for the optical signal, the light of the sensor array is reflected and propagated many times in the GIS/GIL of the high voltage switch-gear, and the internal partial discharge signal is located more accurately. The research results of this paper can provide important technical support for the GIS/GIL fault monitoring and early warning of the gas insulated electrical equipment on the transmission line.
Research on Picking Route Optimization of Multi-zone Warehouse Based on Traveling Salesman Problem and Simulated Annealing Algorithm
Authors: Peng Wanqing , Guo Siqi , Li Haoxuan 
Published: April 2021

Abstract
The improvement of the national economy has led to the rapid development of e-commerce business, which has caused an explosive growth of warehouse orders. Picking is the core operation of the warehouse, which occupies a lot of time and capital costs. Therefore, optimizing the picking path has become an urgent problem for e-commerce companies to solve. This article calculates the distance matrix based on the characteristics of multi-zone warehouses, establishes a Traveling Salesman Problem (TSP) model to process 49 combined orders, and solves the model through the simulated annealing algorithm. In addition, add review stations at different locations to analyze the impact on delivery time. Finally, the optimal picking path, the optimal distribution method of orders, and the time it takes to deliver are obtained. The results indicate that the TSP model combined with the simulated annealing algorithm can optimize the picking path, adding a review station close to the center of the warehouse can reduce the time of delivery, and the model is universal applicability.
Simulation algorithm for crowd evacuation in complex situations based on RVO algorithm
Authors: Wang Weian , Xue Huijie , Zhou Runjia , Chen Xudong , Wang Ziyang 
Published: April 2021

Abstract
In order to better evacuate the crowd and ensure the safety of the crowd’s life and property in emergencies, we designed and developed simulation software for crowds under complex conditions based on the RVO(reciprocal velocity obstacles) algorithm. The system completes crowd simulation, obstacle simulation, evacuation path simulation, crowd collision simulation, supports automatic crowd evacuation and sets special evacuation paths for special crowds. This article focuses on the algorithm part.
Predicting the tendency of stock’s price with factor-cross method based on deep learning
Authors: Zhang Zhujun 
Published: April 2021

Abstract
In this paper, a solution for tendency prediction in the A-share market is presented. In data processing, the problem of non-normal factor distribution is solved by using compound processing method, and the case of non-independent distribution among factors is focused. The DNN Linear Combined Estimator model in Tensor Flow is applied to explore the first-order relationship between these factors. In order to intuitively understand the advantages of the model, an experiment is conducted between our solution and traditional machine learning methods. The result exhibits that the performance of our work is more excellent in all prediction metrics.
IE-WGAN: A model with Identity Extracting for Face Frontal Synthesis
Authors: Zhu Yanrui , Chen Yonghong , Ren Yuxin 
Published: April 2021

Abstract
Face pose affects the effect of the frontal face synthesis, we propose a model used for frontal face synthesis based on WGAN-GP. This model includes identity extracting module, which is used to supervise the training of the face generation module. On the one hand, the model improves the quality of synthetic face images, on the other hand, it can accelerate the convergence speed of network training. We conduct verification experiments on CelebA data sets, and the results show that this model improves the graphic quality of frontal synthesis.
A fast and effective image steganalysis model based on convolutional neural network
Authors: Hu Fengsong , Xu Rong , Cheng Zhekun 
Published: April 2021

Abstract
In recent years, the performance of deep learning in image steganalysis applications has become more and more outstanding, but at the same time the training time has also greatly increased. Some models need to be trained for several days, and the research efficiency is very low. In this article, we propose an image steganalysis model in spatial domain based on a three-layer convolutional neural network. The model does not use a pooling layer, and uses the global average pooling layer instead of the fully connected layer. Experimental results show that the training time of the model is greatly shortened, and the accuracy of detecting the three steganography algorithms with an embedding rate of 0.4bpp exceeds 85%.
Research on Automatic Inspection System of Printed Circuit Board Based on Computer Vision
Authors: Lin Shuju 
Published: April 2021

Abstract
With the development of computers and software, all walks of life are beginning to use computers and software to design system, for example, the printing industry. Through computer technology, it designs an automatic monitoring system to simplify printing work. This paper mainly determines the general plan of the automatic monitoring system, it also analyses the related design of image acquisition control system and image detection control system.
Complexity Dynamic Analysis of Fractional-order Permanent Magnet Synchronous Motor in CNC Machine Tool
Authors: Hai-yan FU , Tengfei Lei , Min Su , Tingyang Yan 
Published: April 2021

AbstractIn this paper, permanent magnet synchronous motor system for fractional-order machine tools is studied. The nonlinear term of the system is decomposed by Adomian decomposition method, and the attractor and poincare cross-section of the system are drawn by Matalb. Meanwhile, the system is analyzed by numerical simulation including bifurcation diagram, SE complexity, C0 complexity and attractor phase diagram under parameter change, which further reveals the realizable dynamic characteristics of fractional-order chaotic system. The related research results lay a good foundation for the control of CNC ( Computer Numerical Control ) machine tools.
Design and Development of Vehicle Flow System Based on Neural Network
Authors: Guang-lei QI , Lin-mei ZU , Kai-li Quan , Xiao-gang Hou 
Published: April 2021

AbstractWith the development of economy and society, the demand and use of automobiles are increasing all over the world. Cars have become a common means of transportation in people’s daily life, but with it comes the problem of automobile exhaust emission. Nowadays, motor vehicle exhaust has become one of the main sources of air pollutants in many cities. This paper mainly introduces the design and development process of a vehicle flow system based on neural network. In this paper, the demand analysis and overall analysis of the whole system are included, as well as the design and implementation of background algorithms and application functions in the system, which meet the needs of users.
Improving phase retrieval accuracy of optical parallel plate by adjusting exposure time of CCD
Authors: Liu Xu , Liu Yong , Li Dong , He Yuhang , Jiang Hongzhen , Zhang Huxiang , Ren Huan , Chai Liqun , Zhu Qihua , Zheng Wanguo , Tan Qiaofeng 
Published: April 2021

Abstract
A new phase retrieval method is investigated to reconstruct wavefronts of optical parallel plates with the use of a group of diffraction patterns. More specifically, the improved phase retrieval algorithm is realized by converting the measuring plane wave into a spherical wave and by using single or double discrete Fourier transforms to calculate both far- and near-field diffraction propagations, and the accuracy is improved by adjusting the exposure time of the charge-coupled device according to the distance between the focal plane and diffraction plane. Both the theoretical and experimental results are consistent with the results obtained using conventional wavelength-modulated phase-shifting interferometry. The new method opens new doors for realizing wavefront measurement of optical parallel plates with high accuracy, especially for large-aperture parallel plates in inertial confinement fusion laser systems.
Nanomaterials significance; contaminants degradation for environmental applications
Authors: Khan Sadaf Bashir , Lee Shern Long 
Published: April 2021

Abstract
Nanotechnology provides an innovative platform that is inexpensive, reasonable, having least chances of secondary contamination, economical, and an effective method to concurrently eradicate numerous impurities from contaminated wastewater. Presently, different researches have been conducted exhibiting versatile multifunctional nanoparticles (NPs) that concurrently confiscate several impurities existing in the water. Nanotechnology helps in eliminating impurities from water through the rapid, low-cost method. Pollutants such as 2,4-dichlorophenol (death-causing contaminant as it quickly gets absorbed via the skin), or industrial dyes including methyl violet (MV) or methyl orange (MO) causing water contamination were also concisely explained. In this mini-review, nanomaterials were critically investigated, and the practicability and effectiveness of the elimination of contaminations were debated. The analysis shows that a few of these processes can be commercialized in treating diverse toxins via multifunctional nanotechnology innovations. Hence, nanotechnology shows a promising and environmental friendly method to resolve the restrictions of current and conventional contaminated water treatment. We can progress the technology, without influencing and affecting the natural earth environment conditions.
Novel bismuth oxy hydride chromate (HBi3(CrO4)O3) nano-sheets/rods synthesized by one step one pot wet chemical method
Authors: Manjunatha Channegowda 
Published: April 2021

Abstract
A novel inorganic hydride material, hydrogen bismuth chromium oxide (HBi3(CrO4)O3), with 2D nano sheets and 1D nanorods were prepared for the first time using a simple, green, hazard free hydrothermal method. The X-ray diffraction (XRD) results confirms that the as-formed sample (HBi3(CrO4)O3) has monoclinic crystal system with a space group of P21/a. The field emission scanning electron microscope (FESEM) analysis clearly reveal that the new material contains large quantity of 2D nanosheets of thickness <10 nm and spread over >1000 nm and with small amounts of micro-rods of width in the range of 1 to 5 μm and lengths in the range of 40 to 100 μm. The EDS analysis confirms the presence of ‘Bi’, ‘Cr’, and ‘O’ and it further evidences the purity of the sample. The fourier transform infra-red (FT-IR) spectra evidences that the sample has Bi-H, Bi-O and Cr-O bonds as expected for HBi3(CrO4)O3. This material has a potential to find its place in hydrogen storage material, photo/electro catalysis, fuel cells, optoelectronics and rechargeable batteries, therefore it needs materials researcher attention immediately.
Canned Comments in the Hospital Laboratory Information System Can Decrease Microbiology Requests
Authors: Ruff Heather M , Poonawala Husain , Sebastian Christopher , Peaper David R 
Published: April 2021

Abstract

Objectives
Phone calls to the microbiology laboratory can be to clarify culture results and provide education, but those calls also interrupt laboratory workflow. We characterized calls that the laboratory received and developed targeted comments to educate providers.

Methods
Calls were logged and characterized, and we developed comments to address common call subjects. We applied the new comments to cultures and logged calls over the same interval the subsequent year. Data before and after implementation were analyzed.

Results
Call volume decreased from 496 calls to 419 calls after implementation. There was a significant difference in level of training among callers (P &lt; .005), but the nature of the calls did not change. Laboratory response showed an increase in release of previously generated data (eg, suppressed susceptibility results). Comments specifically developed to address intrinsic antibiotic resistance and common susceptibility patterns did not decrease call volume.

Conclusions
Implementation of comments in the laboratory information system decreased call volume, but targeted comments were less effective than anticipated.
1-Ethyl-β-N-acetylglucosaminide increases hyaluronan production in human keratinocytes by being converted to N-acetylglucosamine via β-N-acetylglucosaminidase-dependent manner
Authors: Akazawa Yumiko , Yoshida Hiroyuki , Endo Yoko , Sugita Jun , Yakumaru Masafumi , Sayo Tetsuya 
Published: April 2021

ABSTRACT
Regulation of hyaluronan (HA) is important for the maintenance of epidermal homeostasis. Here, we examined the mechanism by which 1-ethyl-β-N-acetylglucosaminide (β-NAG2), a newly developed N-acetylglucosamine (NAG) derivative, increases HA production in cultured human epidermal keratinocytes. When keratinocytes were treated with β-NAG2, mRNA expression of HA synthase 3, which is responsible for HA production in human keratinocytes, was not influenced, but the intracellular level of UDP-NAG, a substrate used for HA synthesis, was increased. By using a synthetic substrate for β-N-acetylglucosaminidase (β-NAGase), keratinocytes were found to possess β-NAGase activity, and treatment of o-(2-acetamido-2-deoxy-d-glucopyranosylidene) amino N-phenyl carbamate (PUGNAc), an inhibitor of β-NAGase, abolished the release of NAG from β-NAG2 in keratinocytes. Furthermore, PUGNAc attenuated the β-NAG2-induced intracellular UDP-NAG and HA production in keratinocytes. These results suggest that β-NAG2 is converted to NAG by endogenous β-NAGase in keratinocytes, and the resulting NAG is further metabolized to UDP-NAG and utilized for HA production.
MMFGRN: a multi-source multi-model fusion method for gene regulatory network reconstruction
Authors: He Wenying , Tang Jijun , Zou Quan , Guo Fei 
Published: April 2021

Abstract
Lots of biological processes are controlled by gene regulatory networks (GRNs), such as growth and differentiation of cells, occurrence and development of the diseases. Therefore, it is important to persistently concentrate on the research of GRN. The determination of the gene–gene relationships from gene expression data is a complex issue. Since it is difficult to efficiently obtain the regularity behind the gene-gene relationship by only relying on biochemical experimental methods, thus various computational methods have been used to construct GRNs, and some achievements have been made. In this paper, we propose a novel method MMFGRN (for “Multi-source Multi-model Fusion for Gene Regulatory Network reconstruction”) to reconstruct the GRN. In order to make full use of the limited datasets and explore the potential regulatory relationships contained in different data types, we construct the MMFGRN model from three perspectives: single time series data model, single steady-data model and time series and steady-data joint model. And, we utilize the weighted fusion strategy to get the final global regulatory link ranking. Finally, MMFGRN model yields the best performance on the DREAM4 InSilico_Size10 data, outperforming other popular inference algorithms, with an overall area under receiver operating characteristic score of 0.909 and area under precision-recall (AUPR) curves score of 0.770 on the 10-gene network. Additionally, as the network scale increases, our method also has certain advantages with an overall AUPR score of 0.335 on the DREAM4 InSilico_Size100 data. These results demonstrate the good robustness of MMFGRN on different scales of networks. At the same time, the integration strategy proposed in this paper provides a new idea for the reconstruction of the biological network model without prior knowledge, which can help researchers to decipher the elusive mechanism of life.
High circulating insulin-like growth factor-1 reduces the risk of renal cell carcinoma: a Mendelian randomization study
Authors: Chen Meng , Tsai Chia-Wen , Chang Wen-Shin , Xiong Grace Y , Xu Yifan , Bau Da-Tian , Gu Jian 
Published: April 2021

AbstractInsulin and insulin-like growth factors play important roles in carcinogenesis. Circulating insulin-like growth factor-1 (IGF-1) and insulin-like growth factor-binding protein-3 (IGFBP-3) have been linked to cancer susceptibility. The associations of circulating IGF-1 and IGFBP-3 with the risk of renal cell carcinoma (RCC) are inconsistent. Recent large genome-wide association studies have identified 413 single nucleotide polymorphisms (SNPs) associated with IGF-1 and 4 SNPs associated with IGFBP-3. In this large case–control study consisting of 2069 RCC patients and 2052 healthy controls of European ancestry, we used a two-sample Mendelian randomization (MR) approach to investigate the associations of genetically predicted circulating IGF-1 and IGFBP-3 with RCC risk. We used an individual level data-based genetic risk score (GRS) and a summary statistics-based inverse-variance weighting (IVW) method in MR analyses. We found that genetically predicted IGF-1 was significantly associated with RCC risk in both the GRS analysis [odds ratio (OR) = 0.43 per SD increase, 95% confidence interval (CI), 0.34–0.53] and the IVW analysis (OR = 0.46 per SD increase, 95% CI, 0.37–0.57). Dichotomized at the median GRS value of IGF-1 in controls, individuals with high GRS had a 45% reduced RCC risk (OR = 0.55, 95% CI, 0.48–0.62) compared with those with low GRS. Genetically predicted circulating IGFBP-3 was not associated with RCC risk. This is the largest RCC study of circulating IGF-1 and IGFBP-3 to date and our data suggest a strong inverse relationship between circulating IGF-1 level and RCC risk.
Outcomes of Multidrug-Resistant Tuberculosis Treated With Bedaquiline or Delamanid
Authors: Hwang Hyeontaek , Kang Hyungseok , Kwon Yong-Soo , Jeon Doosoo , Shim Tae Sun , Yim Jae-Joon 
Published: April 2021

Abstract

Background
Since 1 September 2016, bedaquiline and delamanid have been administered for the treatment of patients with multidrug-resistant/rifampicin-resistant tuberculosis after the official approval in South Korea. This study aimed to assess and compare the final treatment outcomes of patients who received bedaquiline with those of patients who received delamanid.

Methods
This is a nationwide cohort study of patients with multidrug-resistant/rifampicin-resistant tuberculosis in whom bedaquiline or delamanid was administered from 1 September 2016 to 28 February 2018, after receiving the official approval in South Korea. Patients were classified into the bedaquiline and delamanid group according to the first used drug. We evaluated and compared the final treatment outcomes between the groups.

Results
During the study period, 284 patients with multidrug-resistant/rifampicin-resistant tuberculosis were approved to use bedaquiline or delamanid and 260 were included in the final analysis; 119 (45.8%) and 141 patients (54.2%) were classified into bedaquiline and delamanid groups, respectively. Among them, 30 patients (11.5%) exhibited additional resistance to second-line injectable drugs, 94 patients (36.2%) had additional resistance to fluoroquinolones, and 37 patients (14.2%) had resistance to both drugs. The overall treatment success rate was 79.2%. Initiation of bedaquiline rather than delamanid was not associated with treatment success (adjusted odds ratio, .671; 95% confidence interval, .350–1.285). Frequencies of adverse events were not significantly different between the 2 groups.

Conclusions
Initial choice of bedaquiline or delamanid did not make any significant difference in the final treatment outcome or the frequencies of adverse events among patients with multidrug-resistant/rifampicin-resistant tuberculosis.
The safety of speculation …
Authors: Woods J E 
Published: April 2021

Abstract
Doubtless writing tongue-in-cheek to the Estates Committee of King’s College in 1938, Keynes remarked that it was safer to be a speculator than an investor. In the 1920s when first assuming responsibility for the College endowment, he had been a speculator, experiencing a remarkable conversion in the early 1930s to become a genuine long-term investor. Viewing the development of portfolio practice through Keynesian lenses, we demonstrate the essential continuity in conventional practice from Keynes’ time to the present day, the enduring characteristic being the treatment of uncertainty as if it were risk. Current practice is technically sophisticated, manifested in the reliance on benchmarks and risk controls to such an extent that we can refer to the fetish of benchmarking. In contrast, Keynes’ indirect, allusive, indeed elusive, approach embodies a unique insight—one that has been totally obscured by the conventional emphasis on ‘capital appreciation and depreciation generally’.