bluuebunny/crossref_metadata_2025 huggingface dataset:
Cold hardiness of select apple cider cultivars in Canada
Authors: Cline John A. , Beneff Amanda , Edwards A. Michelle
Published: November 2021

There is increasing interest in growing European origin apple cultivars for the production of hard cider in Canada; however, little is known about their winter hardiness. Eleven promising cider cultivars were evaluated for cold hardiness over two consecutive winters and compared with the winter tender cultivar ‘Golden Delicious’. Sections of the current season’s dormant shoots were frozen in a series of test temperatures ranging from −20 °C to −40 °C in a programmable freezer. Xylem tissue browning ratings were used to assess injury after thawing. The temperature of incipient damage (TID), the warmest temperature at which 1-yr-old shoot segments begin to show injury, was obtained from tissue browning curves using non-linear regression. TID varied significantly among cultivars and between sampling years. Overall, the cultivars could be classified according to relative winter hardiness as follows: Ashmead’s Kernel, Bramley’s Seedling (very tender) < Calville Blanc d’Hiver, Porter’s Perfection, Bulmer’s Norman (intermediate) < Crimson Crisp, GoldRush, Golden Delicious, Enterprise, Yarlington Mill, Enterprise (hardy) < Golden Russet (hardy). These data indicate nearly a 10 °C range in winter hardiness amongst the 11 cultivars studied, depending on the sampling date. Ashmead’s Kernel and Bramley’s Seedling appear to be particularly winter tender, whereas Bulmer’s Norman, Porter’s Perfection, and Calville Blanc d’Hiver demonstrated less hardiness during three of the four sampling dates. Based upon these findings, it would be prudent to consult long-term climate normals and consider the frequency of extreme weather events for potential susceptibility to winter injury, particularly prior to establishing more injury-prone cultivars.
Improving radioactive contaminant identification through the analysis of delayed coincidences with an $$\alpha $$-spectrometer
Authors: Baccolo G. , Barresi A. , Beretta M. , Chiesa D. , Nastasi M. , Pagnanini L. , Pozzi S. , Previtali E. , Sisti M. , Terragni G.
Published: November 2021

In the framework of rare event searches, the identification of radioactive contaminants in ultra-pure samples is a challenging task, because the signal is often at the same level of the instrumental background. This is a rather common situation for $$\alpha $$
α
-spectrometers and other detectors used for low-activity measurements. In order to obtain the target sensitivity without extending the data taking live-time, analysis strategies that highlight the presence of the signal sought should be developed. In this paper, we show how to improve the contaminant tagging capability relying on the time-correlation of radioactive decay sequences. We validate the proposed technique by measuring the impurity level of both contaminated and ultra-pure copper samples, demonstrating the potential of this analysis tool in disentangling different background sources and providing an effective way to mitigate their impact in rare event searches.
Tetraquark molecular states in the DsD̄s1 and Ds∗D̄s0∗ mass spectrum
Authors: Wang Zhi-Gang , Yang Xiao-Song , Xin Qi
Published: November 2021

In this work, we construct the color-singlet-color-singlet type four-quark currents to investigate the [Formula: see text] and [Formula: see text] tetraquark molecular states with the [Formula: see text] and [Formula: see text] via the QCD sum rules and obtain satisfactory results. We can search for the [Formula: see text] and [Formula: see text] tetraquark molecular states with the [Formula: see text] and [Formula: see text] at the BESIII and Belle II in the future.
Anomaly resolution via decomposition
Authors: Robbins Daniel G. , Sharpe Eric , Vandermeulen Thomas
Published: November 2021

In this paper, we apply decomposition to orbifolds with quantum symmetries to resolve anomalies. Briefly, it has been argued by, e.g. Wang–Wen–Witten, Tachikawa that an anomalous orbifold can sometimes be resolved by enlarging the orbifold group so that the pullback of the anomaly to the larger orbifold group is trivial. For this procedure to resolve the anomaly, one must specify a set of phases in the larger orbifold, whose form is implicit in the extension construction. There are multiple choices of consistent phases, which give rise to physically distinct resolutions. We apply decomposition, and find that theories with enlarged orbifold groups are equivalent to (disjoint unions of copies of) orbifolds by nonanomalous subgroups of the original orbifold group. In effect, decomposition implies that enlarging the orbifold group is equivalent to making it smaller. We provide a general conjecture for such descriptions, which we check in a number of examples.
Power-like potentials: From the Bohr—Sommerfeld energies to exact ones
Authors: del Valle J. C. , Turbiner Alexander V.
Published: November 2021

For one-dimensional power-like potentials [Formula: see text], [Formula: see text], the Bohr–Sommerfeld energies (BSE) extracted explicitly from the Bohr–Sommerfeld quantization condition are compared with the exact energies. It is shown that for the ground state as well as for all positive parity states the BSE are always above the exact ones as opposed to the negative parity states where the BSE remain above the exact ones for [Formula: see text] but below them for [Formula: see text]. The ground state BSE as function of [Formula: see text] are of the same order of magnitude as the exact energies for linear [Formula: see text], quartic [Formula: see text] and sextic [Formula: see text] oscillators but their relative deviation grows with [Formula: see text], reaching the value 4 at [Formula: see text]. For physically important cases [Formula: see text], for the 100th excited state BSE coincide with exact ones in 5–6 figures.

It is demonstrated that by modifying the right-hand side of the Bohr–Sommerfeld quantization condition by introducing the so-called WKB correction [Formula: see text] (coming from the sum of higher-order WKB terms taken at the exact energies or from the accurate boundary condition at turning points) to the so-called exact WKB condition one can reproduce the exact energies. It is shown that the WKB correction is a small, bounded function [Formula: see text] for all [Formula: see text]. It grows slowly with increasing [Formula: see text] for fixed quantum number [Formula: see text], while it decays with quantum number growth at fixed [Formula: see text]. It is the first time when for quartic and sextic oscillators the WKB correction and energy spectra (and eigenfunctions) are found in explicit analytic form with a relative accuracy of [Formula: see text] (and [Formula: see text]).
Electronic and optical properties of GeS and GeS:Gd
Authors: Dashdemirov A. O. , Asadullayeva S. G. , Alekperov A. S. , Ismayilova N. A. , Jabarov S. H.
Published: November 2021

In this paper, the results of the first principles calculations within the framework of the density functional theory of the electronic spectrum of a GeS crystal are presented. The density of states and interband optical transitions are investigated. It was found that GeS compounds have semiconducting properties with a bandgap of 1.52 eV. The main contribution of the bands in the vicinity of the Fermi level is from the 3[Formula: see text] and 3[Formula: see text] states of the S and Ge atoms, respectively. The highest amplitude, about 2.3 eV ([Formula: see text], is mainly associated with the interband optical transitions between the states [Formula: see text]. The results of the luminescence studies of GeS and GeS:Gd layered crystals at room-temperature are presented. A noticeable increase in the intensity of the luminescence radiation in GeS:Gd has been established. The reason for the increase in the effectiveness of photoluminescence is due to the overlapping of optical transitions of GeS at 695 nm wavelength with the radiation lines of Gd[Formula: see text]ion at that same energy.
Numerical upper bounds on growth of automaton groups
Authors: Brieussel Jérémie , Godin Thibault , Mohammadi Bijan
Published: November 2021

The growth of a finitely generated group is an important geometric invariant which has been studied for decades. It can be either polynomial, for a well-understood class of groups, or exponential, for most groups studied by geometers, or intermediate, that is between polynomial and exponential. Despite recent spectacular progresses, the class of groups with intermediate growth remains largely mysterious. Many examples of such groups are constructed using Mealy automata. The aim of this paper is to give an algorithmic procedure to study the growth of such automaton groups, and more precisely to provide numerical upper bounds on their exponents. Our functions retrieve known optimal bounds on the famous first Grigorchuk group. They also improve known upper bounds on other automaton groups and permitted us to discover several new examples of automaton groups of intermediate growth. All the algorithms described are implemented in GAP, a language dedicated to computational group theory.
Develop a Fuzzy System with LM/ODR Artificial Neural Network Model to Predict the Trend of Thermal Conductivity and Rheological Behavior for Graphene Aqueous-Based Nanofluid
Authors: Alkanhal Tawfeeq Abdullah
Published: November 2021

Graphene is a flexible and transparent conductor which can be used in varied material-apparatus applications, counting solar cells, phones, touch panels, and light-emitting diodes (LED). In this study, to begin with, Graphene aqueous-based nanofluid is processed at separate mass fractions of 0.1 − 0.45 W%. Hence, thermal conductivity of these units was detected at separate temperatures of 25 − 50°C aside the KD2-Pro appliance. Similarly, Rheological behavior at noticed temperatures, for 12.23 and 122.3 S-1 shear rates, was detected aside the DV2EXTRA-Pro appliance. To shorten the expense of research, neural network designs and fuzzy system were trained to discover addition thermal conductivities and viscosities for unalike temperatures and mass fractions. Purpose of this study is to broaden Fuzzy system and ANN algorithms to predict the TC/VIS therefore it predicts the targeted-input dataset as factual as practicable. Hence, the numerical research was accomplished and related aside Levenberg Marquardt and Orthogonal Distance Regression models of Artificial Neural Networks, and Recursive Least Squares Fuzzy system. To train, 14400 data were placed. To test, 2160 ones, to train-control 2160 ones, and to train-output 10080 ones. Conclusions of comparison between algorithms and Fuzzy, exhibited Fuzzy system was fitted on the three-dimensional data more corrected than LM/ODR designs that leads to a better prediction.
Measuring Staff Satisfaction in Transportation System using AHP Method under Uncertainty
Authors: Lotfi M. , Asgharizadeh E. , Hisam Omar A. , Hosseinzadeh M. , Amoozad Mahdiraji H.
Published: November 2021

One of the most important challenges in today world is the transportation and satisfaction of this system. Measuring satisfaction in transportation has been done quantitatively so far and, more importantly, the measurement process has not usually been scientific. This study aimed at an accurate scientific measurement. Because of ambiguity, this paper discusses how to use the intuitionistic fuzzy method, in which both membership and non-membership functions were expressed. Therefore, initially, considering the results of previous researches, as well as studying the references and standards, the characteristics and basic criteria, a researcher-made questionnaire with a reliability of 0.95 was first performed and then the weights were determined using the AHP intuitionistic fuzzy method. After performing the above steps, the intuitionistic fuzzy satisfaction value was calculated at different levels and using the method, the final number of satisfaction was defuzzified.
Deep Learning Based Mathematical Model for Feature Extraction to Detect Corona Virus Disease using Chest X-ray Images
Authors: Gupta Rajeev Kumar , Sahu Yatendra , Kunhare Nilesh , Gupta Abhishek , Prakash Deo
Published: November 2021

Currently, the entire world is fighting against the Corona Virus (COVID-19). As of now, more than thirty lacs of people all over the world were died due to the COVID-19 till April 2021. A recent study conducted by China suggests that Chest CT and X-ray images can be used as a preliminary test for COVID detection. This paper propose a transfer learning-based mathematical COVID detection model, which integrates a pre-trained model with the Random Forest Tree (RFT) classifier. As the available COVID dataset is noisy and imbalanced so Principal Component Analysis (PCA) and Generative Adversarial Networks (GANs) is used to extract most prominent features and balance the dataset respectively. The Bayesian Cross-Entropy Loss function is used to penalize the false detection differently according to the class sensitivity (i.e., COVID patient should not be classified as Normal or Pneumonia class). Due to the small dataset, a pre-trained model like VGGNet-19, ResNet50 and Inception_ResNet_V2 were chosen to extract features and then trained them over the RFT for the classification task. The experiment results showed that ResNet50 gives the maximum accuracy of 99.51%, 98.21%, and 97.2% for training, validation, and testing phases, respectively, and none of the COVID Chest X-ray images were classified as Normal or Pneumonia classes.
Automated Image Super Resolution with the Aid of Activation Function Optimized Deep CNN and Adaptive Wavelet Lifting Approach
Authors: Bhasha A. Valli , Reddy B. D. Venkatramana
Published: November 2021

Diverse image super-resolution (SR) techniques have been implemented to reconstruct the high-resolution (HR) images from input images through lower spatial resolutions. However, the evaluation of the perceptual quality of SR images remains an important and complex research problem. This paper proposes a new image SR model with the intention of attaining maximum Peak Signal-to-Noise Ratio (PSNR). The conversion of low-resolution (LR) images from the HR images is performed by bicubic interpolation-based downsampling and upsampling. Then, the four sub-bands of LR and HR images are generated by the novel Adaptive Wavelet Lifting approach, in which the filter modes are optimized using the proposed SA-CBO. From this technique, LR wavelet sub-bands (LRSB) for LR images and HR wavelet sub-bands (HRSB) for HR images are formed. With the help of the LRSB and HRSB images, the residual images are formed by the adoption of the optimized Activation function and optimized hidden neurons in a deep convolutional neural network (CNN). The improvement in both the adaptive wavelet lifting approach and deep CNN is made by the self-adaptive-colliding bodies optimization (SA-CBO). Finally, the inverse adaptive wavelet lifting approach is used to produce the final SR image. Experimental results on publicly available SR image quality databases confirm the effectiveness and generalization ability of the proposed method compared with the traditional image quality assessment algorithms.
COVID-19 as an Extreme Event in the New York Metropolitan Region
Authors: Marcotullio Peter J. , Solecki William D.
Published: November 2021

During early 2020, the world encountered an extreme event in the form of a new and deadly disease, COVID-19. Over the next two years, the pandemic brought sickness and death to countries and their cities around the globe. One of the first and initially the hardest hit location was New York City, USA. This article is an introduction to the Special Issue in this journal that highlights the impacts from and responses to COVID-19 as an extreme event in the New York City metropolitan region. We overview the aspects of COVID-19 that make it an important global extreme event, provide brief background to the conditions in the world, and the US before describing the 10 articles in the issue that focus on conditions, events and dynamics in New York City during the initial phases of the pandemic.
Composite Line Designs and Accuracy Measurements for Tactile Line Tracing on Touch Surfaces
Authors: Chau Edwin , Yu Jiakun , Goncu Cagatay , Withana Anusha
Published: November 2021

Eyes-free operation of mobile devices is critical in situations where the visual channel is either unavailable or attention is needed elsewhere. In such situations, vibrotactile tracing along paths or lines can help users to navigate and identify symbols and shapes without visual information. In this paper, we investigated the applicability of different metrics that can measure the effectiveness of vibrotactile line tracing methods on touch screens. In two user studies, we compare trace Length Error, Area Error, and Fréchet Distance as alternatives to commonly used trace Time. Our results show that a lower Fréchet distance is correlated better with the comprehension of a line trace. Furthermore, we show that distinct feedback methods perform differently with varying geometric features in lines and propose a segmented line design for tactile line tracing studies. We believe the results will inform future designs of eyes-free operation techniques and studies.
The Book Review Column
Authors: Green Frederic
Published: November 2021

This column, the spotlight is on complexity, computational and communicational: 1. Mathematics and Computation, by Avi Wigderson. A sweeping look at computational complexity and adjacent fields, especially how they interact with mathematics. Review by Frederic Green. 2. Communication Complexity and Applications, by Anup Rao and Amir Yehudayoff. A textbook on this important topic. Review by Micha¨el Cadilhac. As always, please contact me to write a review; choose from among the books listed on the next pages, or, if you are interested in anything not on the list, just send me a note.
Review of Mathematics and Computation by Avi Wigderson
Authors: Green Frederic
Published: November 2021

Mathematics and computation are inextricably entangled3. We couldn't do one without the other. The need to calculate can be traced to early human history, and mathematics developed in large part to enable computation. And computation is necessary to propel mathematics. One often loses sight of the fact that the great mathematicians of the past were also prodigious computers: For example, Gauss, Kummer and the other great pioneers of number theory did vast amounts of computation to arrive at or reinforce many of their insights.
Technical Report Column
Authors: Kelley Dean
Published: November 2021

Welcome to the Technical Reports Column. If your institution publishes technical reports that you'd like to have included here, please contact me at the email address above.
DNA Methylation Profiling: An Emerging Paradigm for Cancer Diagnosis
Authors: Papanicolau-Sengos Antonios , Aldape Kenneth
Published: November 2021

Histomorphology has been a mainstay of cancer diagnosis in anatomic pathology for many years. DNA methylation profiling is an additional emerging tool that will serve as an adjunct to increase accuracy of pathological diagnosis. Genome-wide interrogation of DNA methylation signatures, in conjunction with machine learning methods, has allowed for the creation of clinical-grade classifiers, most prominently in central nervous system and soft tissue tumors. Tumor DNA methylation profiling has led to the identification of new entities and the consolidation of morphologically disparate cancers into biologically coherent entities, and it will progressively become mainstream in the future. In addition, DNA methylation patterns in circulating tumor DNA hold great promise for minimally invasive cancer detection and classification. Despite practical challenges that accompany any new technology, methylation profiling is here to stay and will become increasingly utilized as a cancer diagnostic tool across a range of tumor types.
Review—Recent Advance in Multi-Metallic Metal Organic Frameworks (MM-MOFs) and Their Derivatives for Electrochemical Biosensor Application
Authors: Rezki Muhammad , Septiani Ni Luh Wulan , Iqbal Muhammad , Adhika Damar Rastri , Wenten I Gede , Yuliarto Brian
Published: November 2021

The recent trend on metal organic framework (MOF) studies has shifted to the development of MOFs with many metal nodes, also known as multi metallic MOF (MM-MOF). Many studies have shown that MM-MOF display much better performance compared to single metallic MOFs. In addition, derived MM-MOF products such as metal hybrids, MM-MOF composites, and MOF-on-MOF also provide interesting unique characteristics. In this review, we summarize the synthesis strategy of MM-MOF and their derivates in three different approaches, including one-pot synthesis/direct mixing, post-synthesis modification, and MOFs derivative preparation. In many applications, such as cancer markers detection, diabetic disease detection, metabolic disease detection, infectious disease detection, and toxic pollutant detection, MM-MOF based biosensors displayed excellent sensing performance as well as stability, selectivity, and reproducibility. This review provides a point of view on the recent development, preparation, and application of MM-MOF including the challenge and future prospect of this material.
Review—Solution Electrochemical Process for Fabricating Metal Oxides and the Thermodynamic Design
Authors: Izaki Masanobu , Khoo Pei Loon , Shinagawa Tsutomu
Published: November 2021

Electrochemical processes in aqueous solutions are widely used for preparation of metals, alloys, composites, metal oxides and compounds. For understanding and designing an electrochemical process, it is crucial to study its soluble chemical species, potential-pH diagram, and solubility curves drawn based on thermodynamics. In this review, equilibrium electrode potentials, critical pH values, and dissolved chemical species related to the oxidation-reduction, acid-base, and ligand-exchanging reactions, in addition to the calculation based on standard Gibbs free energy are first briefly mentioned. This is followed by the description of the change in equilibrium electrode potentials of metal and metal compounds as demonstrated in the electrochemical preparation of the Cu–In–Se precursor for the Cu(In,Ga)Se2 solar cell application. Additionally, the advantages and usefulness of soluble chemical species, potential-pH diagram, and solubility curves are discussed, by giving examples of direct electrodepositions of metal oxides, the chemical introduction of impurities into ZnO enabling characteristic control, the chemical bath deposition process (CBD) for Zn(S,O,OH) buffer layer in Cu(In,Ga)Se2 solar cell, and lastly, the design of the electrochemical process for fabricating CuO/Cu2O bilayers.
The Association of the Phylogenetic Typing of the Klebsiella pneumoniae Isolates with Antibiotic Resistance
Authors: Baghbanijavid Shabnam , Kafil Hossein Samadi , Farajniya Safar , Moaddab Seyed Reza , Hosainzadegan Hasan , Sefidan Fatemeh Yeganeh , Varshouchi Mojtaba , Leylabadlo Hamed Ebrahimzadeh , Ghotaslou Reza
Published: November 2021

Klebsiella pneumoniae complex (KPC) accounts for approximately one-third of all Gram-negative infections. Moreover, it is highly resistant and can taxonomically be distributed into KpI, KpII, and KpIII phylogroups. This study aimed to investigate the distribution of phylogenetic groups and the relationship between them and antibiotic resistance patterns. For this purpose, we collected KPC isolates from Tabriz, Iran, between 2018 and 2020. Antimicrobial susceptibility testing was performed by disk diffusion agar, and phylogenetic groups were then examined using gyrA restriction fragment length polymorphism (RFLP) and parC PCR methods. A total of 100 KPC isolates were obtained from the clinical specimens (urine, respiratory secretion, blood, wounds, and trachea). The enrolled patients included 47 men and 53 women aged from 1 to 91 years old. The highest sensitivity was found related to fosfomycin as 85%, followed by amikacin as 66%. The three phylogenetically groups by the RFLP-PCR method were found in KPC, 96% (96 isolates) as KpI, 3% (3 isolates) as KpII, and 1% (1isolate) as KpIII. The highest antibiotic resistance was observed in KpI. It was shown that a valid identification of three phylogenetic groups of KPC can be done by combining both gyrA PCR-RFLP and parC PCR. Of note, the KpI group was also observed as the dominant phylogenetic group with the highest resistance to antibiotics.
Spatial Distribution and Determinants of Nonautonomy on Decision Regarding Contraceptive Utilization among Married Reproductive-Age Women in Ethiopia: Spatial and Bayesian Multilevel Analysis
Authors: Birara Aychiluhm Setognal , Urmale Mare Kusse , Sharew Melaku Mequannent , Woday Tadesse Abay
Published: November 2021

Background. Studies conducted to date in Ethiopia did not explore the spatial distribution, individual-level, and community-level factors affecting women’s nonautonomy on decision to use contraceptives. Hence, this study aimed to assess the spatial distribution of women’s nonautonomy on decision regarding contraceptive utilization and its determinants in Ethiopia. Methods. Data were accessed from the Demographic Health Survey program official database website (https://dhsprogram.com). A weighted sample of 3,668 married reproductive-age women currently using contraceptives was included in this analysis. Bayesian multilevel logistic regression models were fitted to identify the determinants of women’s nonautonomy on contraceptive utilization. Adjusted odds ratio with 95% credible interval was used to select variables that have a significant effect on nonautonomy on contraceptive utilization. Results. A high proportion of women with nonautonomy on decision regarding contraceptive utilization was found in northern parts of Southern Nations, Nationalities, and People’s Region, Southern parts of Oromia, and Benishangul-Gumuz regions of the country. Overall, 2876 (78.40% (95% CI: 77.0%, 79.7%)) women were nonautonomous on decision regarding contraceptive utilization. In the final model, age from 35–49 (AOR (95% CI) = 0.63 (0.54, 0.72)), living in the richer households (AOR (95% CI) = 0.12 (0.03, 0.26)), being married at 18 years or above (AOR (95% CI) = 0.33 (0.19, 0.57)), and residing in an rural areas (AOR (95% CI) = 1.34 (1.01, 1.71)) and metropolitan regions (AOR (95% CI) = 0.71(0.54, 0.91)) were associated with women’s nonautonomy on decision regarding contraceptive utilization. Conclusions. In Ethiopia, the spatial distribution of women’s nonautonomy on decision about contraceptive utilization was nonrandom. More than three-fourths of married reproductive-age women in Ethiopia are nonautonomous on decision regarding contraceptive utilization. Region, residence, current age, age at marriage, and wealth index were statistically associated with women’s nonautonomy on decision regarding contraceptive utilization.
Dynamic Modeling and Simulation of Double-Planetary Gearbox Based on Bond Graph
Authors: Tan Wuzhong , Wu Jiangming , Ni De , Yan Hongzhi , Xiang Enming , Liu Shuangqi
Published: November 2021

New generations of powertrains are using gearboxes with multiple speed-shift designs to improve fuel efficiency. However, transmission controls and calibration are substantially time consuming, specifically during shift processes. To study the dynamic characteristics of a gearbox with a double-planetary gear train and analyze the influence of external excitation and internal parameters on the dynamic response of a system, dynamic modeling and simulation of the transmission system are conducted. Some physical processes are complex and difficult to express via lumped mass modeling. The dynamic model of a double-planetary gearbox is obtained by adopting the bond graph method based on the working principle analysis of the transmission, as well as the kinematic characteristics of the double-planetary gear train. Subsequently, state equations are deduced from the dynamic model of the power transmission system for simplified calculations, which can effectively facilitate the shift process simulation. The basic case of different shift plans and times is originally analyzed, followed by an analysis of the influence of damping, stiffness, and moment of inertia on transmission systems. The analysis results provide references for the structural design, control strategy optimization, and failure diagnostics of this gearbox type.
A General Order Reduction Method of Wideband Digital Predistortion Model Using Attention Mechanism
Authors: Liu Zhijun , Hu Xin , Wang Weidong
Published: November 2021

In wireless networks, for the common in‐phase and quadrature‐phase (I/Q) imbalance in the transmitters, the I/Q branch models of digital predistortion (DPD) need to be identified separately, to improve the linearization effects. The existing order reduction methods of the predistorter are based on the contributions of the complex basis function terms, so as not to deal with the different contributions of I/Q components of the complex basis function terms caused by the separate identification of the I/Q branch models. The separate pruning of the I/Q branch models will increase the complexity. Aiming at this issue, this paper proposes a general order reduction method based on the attention mechanism for the predistortion of the power amplifiers (PAs). This method is suitable for pruning both the traditional models and neural network‐based models. In this method, the attention mechanism is used to evaluate the contributions of the real basis function terms to the predistorted output’s I/Q components through offline training, and the influence of the cross terms of the I/Q branch models is considered. The experimental results based on the comparison with other typical methods under 100 MHz Doherty PA and different I/Q imbalance levels show that this method has superior pruning performance and good linearization ability.
Attractors for Multivalued Impulsive Systems: Existence and Applications to Reaction-Diffusion System
Authors: Dashkovskiy S. , Kapustian O. A. , Kapustyan O. V. , Gorban N. V.
Published: November 2021

In this paper, we develop a general approach to investigate limit dynamics of infinite-dimensional dissipative impulsive systems whose initial conditions do not uniquely determine their long time behavior. Based on the notion of an uniform attractor, we show how to describe limit behavior of such complex systems with the help of properties of their components. More precisely, we prove the existence of the uniform attractor for an impulsive multivalued system in terms of properties of nonimpulsive semiflow and impulsive parameters. We also give an application of these abstract results to the impulsive reaction-diffusion system without uniqueness.
Study on Resource Sharing Strategy of e-Commerce Innovation and Entrepreneurship Education Based on Cloud Computing
Authors: Cao Qian
Published: November 2021

As a popular education major at present, e-commerce and innovation and entrepreneurship education are combined with research that has important strategic significance for talents. In the process of the coordinated development of the two, the sharing of educational resources is the core issue. For this reason, an e-commerce professional innovation and entrepreneurship education resource sharing platform has been constructed. The platform is divided into three hierarchical structures of resource layer, middle layer, and application layer, and detailed analysis is performed on the key modules in the construction of the educational resource sharing platform, including user login module, educational resource management module, system management module, and database design module; based on modular design, after logging in to the system, users can independently publish educational information and can also browse and retrieve shared resources. Experimental results show that the platform has a good operating effect, strong load capacity, rapid response of the system, and high safety performance, with a maximum safety of 97%.
Downregulation of RIP3 Improves the Protective Effect of ATF6 in an Acute Liver Injury Model
Authors: Huang Mei-Ying , Wan Dian-Wei , Deng Jie , Guo Wen-Jie , Huang Yue , Chen Huan , Xu De-Lin , Jiang Zhi-Gang , Xue Yuan , He Yi-Huai
Published: November 2021

Background. Activating transcription factor 6 (ATF6) and receptor‐interacting protein 3 (RIP3) are important signaling proteins in endoplasmic reticulum (ER) stress and necroptosis, respectively. However, their regulatory relationship and clinical significance are unknown. We investigate the impact of ATF6 on RIP3 expression, and its role in hepatocyte necroptosis in an acute liver injury model. Methods. In vivo and in vitro experiments were carried out. LO2 cells were treated with thapsigargin (TG). In vivo, male BALB/c mice were treated with carbon tetrachloride (CCl4, 1 mL/kg) or tunicamycin (TM, 2 mg/kg). Then, the impact of ATF6 or RIP3 silencing on liver injury, hepatocyte necroptosis, and ER stress‐related protein expression was examined. Results. TG induced ER stress and necroptosis and ATF6 and RIP3 expression in LO2 cells. The knockdown of ATF6 significantly decreased RIP3 expression (p < 0.05) and increased ER stress and necroptosis. The downregulation of RIP3 significantly reduced necroptosis and ER stress (p < 0.05). Similar results were observed in CCl4 or the TM‐induced mouse model. The knockdown of ATF6 significantly decreased CCl4‐induced RIP3 expression and increased liver injury, necroptosis, and ER stress in mice livers (p < 0.05). In contrast, the downregulation of RIP3 significantly reduced liver injury, hepatocyte necroptosis, and ER stress. Conclusions. Hepatocyte ATF6 has multiple roles in acute liver injury. It reduces hepatocyte necroptosis via negative feedback regulation of ER stress. In addition, ATF6 can upregulate the expression of RIP3, which is not helpful to the recovery process. However, downregulating RIP3 reduces hepatocyte necroptosis by promoting the alleviation of ER stress. The findings suggest that RIP3 could be a plausible target for the treatment of liver injury.
Life-Threatening Retroperitoneal Hematoma in a Patient with COVID-19
Authors: Shah Monarch , Colombo John Paul , Chandna Sanya , Rana Haris
Published: November 2021

COVID-19 is a respiratory illness that affects the human body in many different ways. The disease carries both thrombotic and hemorrhagic complications, especially in those patients who are anticoagulated to prevent the thromboembolic manifestations. In this report, we discuss a case of retroperitoneal hemorrhage in a patient treated with therapeutic anticoagulation which ultimately led to the patient’s death. The literature highlights the importance of anticoagulation because it reduces mortality in patients hospitalized with COVID-19. Although, more recent studies suggest that patients treated with therapeutic anticoagulation are at a higher risk of hemorrhage and increased mortality. Therefore, our case stresses the importance of active monitoring of these patients to detect any suspected case of hemorrhage early to reduce mortality. Overall, more research should be conducted to determine the optimal dosing of anticoagulation that balances safety and efficacy.
Pharmaceutical Pollution: Azole Antifungal Drugs and Resistance of Opportunistic Pathogenic Yeasts in Wastewater and Environmental Water
Authors: Monapathi Mzimkhulu E. , Oguegbulu Joseph C. , Adogo Lilian , Klink Michael , Okoli Bamidele , Mtunzi Fanyana , Modise Johannes S.
Published: November 2021

The occurrence of residual antifungal agents through indiscriminate prophylactic use and inappropriate disposal has been reported in wastewater treatment plants (WWTPs), surface water, and groundwater environments. Opportunistic pathogenic aquatic yeasts develop resistance to commonly used antifungal agents through continued exposure to residual antifungal agents in environmental waters. This poses a major public health concern. The present review attempts to provide a brief description of antifungal drugs, with a focus on the most widely used class of antifungal drugs, the azoles, as emerging contaminants in environmental water. Routes of exposure of azole antifungal drugs in wastewater treatment plants, surface water, and groundwater are discussed. The presence of pathogenic yeasts in environmental water, the associated azole resistance, and the risk of exposure to humans and microbiota are highlighted. Management actions needed to curtail the spread and minimise the risks are also indicated. Further research on the occurrence of antifungal agents in wastewater and environmental water is vital to better understand and mitigate the associated health-related risks.
Benchmarking study between capacitive and electronic load technic to track I-V and P-V of a solar panel
Authors: Asbayou Abdellah , Aamoume Amine , Elyaqouti Mustapha , Ihlal Ahmed , Bouhouch Lahoussine
Published: November 2021

To detect defects of solar panel and understand the effect of external parameters such as fluctuations in illumination, temperature, and the effect of a type of dust on a photovoltaic (PV) panel, it is essential to plot the Ipv=f(Vpv) characteristic of the PV panel, and the simplest way to plot this I-V characteristic is to use a variable resistor. This paper presents a study of comparison and combination between two methods: capacitive and electronic loading to track I-V characteristic. The comparison was performed in terms of accuracy, response time and instrumentation cost used in each circuit, under standard temperature and illumination conditions by using polycrystalline solar panel type SX330J and monocrystalline solar panels type ET-M53630. The whole system is based on simple components, less expensive and especially widely used in laboratories. The results will be between the datasheet of the manufacturer with the experimental data, refinements and improvements concerning the number of points and the trace time have been made by combining these two methods.
Sentiment analysis on film review in Gujarati language using machine learning
Authors: Shah Parita , Swaminarayan Priya , Patel Maitri
Published: November 2021

Opinion analysis is by a long shot most basic zone of characteristic language handling. It manages the portrayal of information to choose the motivation behind the wellspring of the content. The reason might be of a type of gratefulness (positive) or study (negative). This paper offers a correlation between the outcomes accomplished by applying the calculation arrangement using various classifiers for instance K-nearest neighbor and multinomial naive Bayes. These techniques are utilized to assess a significant assessment with either a positive remark or negative remark. The gathered information considered on the grounds of the extremity film datasets and an association with the results accessible proof has been created for a careful assessment. This paper investigates the word level count vectorizer and term frequency inverse document frequency (TF-IDF) influence on film sentiment analysis. We concluded that multinomial Naive Bayes (MNB) classier generate more accurate result using TF-IDF vectorizer compared to CountVectorizer, K-nearest-neighbors (KNN) classifier has the same accuracy result in case of TF-IDF and CountVectorizer.
An autonomous navigational system using GPS and computer vision for futuristic road traffic
Authors: Ramasamy Prabha , Kabadi Mohan
Published: November 2021

Navigational service is one of the most essential dependency towards any transport system and at present, there are various revolutionary approaches that has contributed towards its improvement. This paper has reviewed the global positioning system (GPS) and computer vision based navigational system and found that there is a large gap between the actual demand of navigation and what currently exists. Therefore, the proposed study discusses about a novel framework of an autonomous navigation system that uses GPS as well as computer vision considering the case study of futuristic road traffic system. An analytical model is built up where the geo-referenced data from GPS is integrated with the signals captured from the visual sensors are considered to implement this concept. The simulated outcome of the study shows that proposed study offers enhanced accuracy as well as faster processing in contrast to existing approaches.
Reconfigurable of current-mode differentiator and integrator based-on current conveyor transconductance amplifiers
Authors: Srisoontorn Soontorn , Charoenmee Angkana , Panikhom Suphaphorn , Janda Thitiporn , Fungdetch Suttipong , Patimaprakorn Khunpan , Jantakun Adirek
Published: November 2021

The reconfigurable of the differentiator and integrator based on current conveyor transconductance amplifiers (CCTAs) have been presented in this paper. The proposed configurations are provided with two CCTAs and grounded elements. The configurations can be operated in the differentiator and integrator by selecting external passive elements. The input and output currents have low and high impedances, respectively; therefore, the configurations can be cascaded without additional current buffer. The proposed configurations can be electronically tuned by external direct current (DC) bias currents, and it also has slight fluctuation with temperature. An application of universal filter is demonstrated to confirm the ability of the proposed configurations. The results of simulation with Pspice program are accordance with the theoretical analysis.
Improving hemoglobin estimation accuracy through standardizing of light-emitting diode power
Authors: Pinto Caje Francis , Parab Jivan Shrikrishna , Sequeira Marlon Darius , Naik Gourish
Published: November 2021

Nowadays, hemoglobin monitoring is essential during surgeries, blood donations, and dialysis. Which are normally done using invasive methods. To monitor hemoglobin, a non-invasive hemoglobin meter was developed with five fixed light-emitting diode (LED) wavelengths at 670 nm, 770 nm, 810 nm, 850 nm, 950 nm and controlled using an Arduino Uno embedded development board. A photodetector with an on-chip trans-impedance amplifier was utilized to acquire the transmitted signal through the finger using the photoplethysmography (PPG) principle. Before the standardization of LED power, we had tested the designed system on fifteen subjects for the five wavelengths and estimated the hemoglobin with an accuracy of 96.51% and root mean square error (RMSE) of 0.57 gm/dL. To further improve the accuracy, the LED power was standardized and the PPG signal was reacquired on the same subjects. With this, the accuracy improved to 98.29% and also reduced the RMSE to 0.36 gm/dL. The designed system with LED power standardization showed a good agreement with pathology results with the coefficient of determination R2=0.981. Also, Bland–Altman analysis was used to evaluate the designed system and it showed good agreement between the two measurements.
Power quality event classification using complex wavelets phasor models and customized convolution neural network
Authors: Ramalingappa Likhitha , Manjunatha Aswathnarayan
Published: November 2021

Origin and triggers of power quality (PQ) events must be identified in prior, in order to take preventive steps to enhance power quality. However it is important to identify, localize and classify the PQ events to determine the causes and origins of PQ disturbances. In this paper a novel algorithm is presented to classify voltage variations into six different PQ events considering the space phasor model (SPM) diagrams, dual tree complex wavelet transforms (DTCWT) sub bands and the convolution neural network (CNN) model. The input voltage data is converted into SPM data, the SPM data is transformed using 2D DTCWT into low pass and high pass sub bands which are simultaneously processed by the 2D CNN model to perform classification of PQ events. In the proposed method CNN model based on Google Net is trained to perform classification of PQ events with default configuration as in deep neural network designer in MATLAB environment. The proposed algorithm achieve higher accuracy with reduced training time in classification of events than compared with reported PQ event classification methods.
Effect of optimal filtering parameters for autoregressive model AR(p) on motor unit action potential signal
Authors: Lbrahim Ayad Asaad , Safi Mohammed Ehsan , Abbas Eyad Ibrahim
Published: November 2021

Error is one element of the autoregressive (AR) model, which is supposed to be white noise. Correspondingly assumption that white noise error is a normal distribution in electromyography (EMG) estimation is one of the common causes for error maximization. This paper presents the effect of a suitable choice of filtering function based on the non-invasive analysis properties of motor unit action potential signal, extracted from a non-invasive method-the high spatial resolution (HSR) electromyography (EMG), recorded during low-level isometric muscle contractions. The final prediction error procedure is used to find the number of parameters in the model. The error signal parameter, the simulated deviation from the actual signals, is suitably filtered to obtain optimally appropriate estimates of the parameters of the automatic regression model. It is filtered to acquire optimally appropriate estimates of the parameters of the automatic regression model. Then appropriate estimates of spectral power shapes are obtained with a high degree of efficiency compared with the robust method under investigation. Extensive experiment results for the proposed technique have shown that it provides a robust and reliable calculation of model parameters. Moreover, estimates of power spectral profiles were evaluated efficiently.
Performance analysis of real-time and general-purpose operating systems for path planning of the multi-robot systems
Authors: Canbaz Seçkin , Erdemir Gökhan
Published: November 2021

In general, modern operating systems can be divided into two essential parts, real-time operating systems (RTOS) and general-purpose operating systems (GPOS). The main difference between GPOS and RTOS is the system istime-critical or not. It means that; in GPOS, a high-priority thread cannot preempt a kernel call. But, in RTOS, a low-priority task is preempted by a high-priority task if necessary, even if it’s executing a kernel call. Most Linux distributions can be used as both GPOS and RTOS with kernel modifications. In this study, two Linux distributions, Ubuntu and Pardus, were analyzed and their performances were compared both as GPOS and RTOS for path planning of the multi-robot systems. Robot groups with different numbers of members were used to perform the path tracking tasks using both Ubuntu and Pardus as GPOS and RTOS. In this way, both the performance of two different Linux distributions in robotic applications were observed and compared in two forms, GPOS, and RTOS.
Performance evaluation of wireless local area network with congested fading channels
Authors: Jittawiriyanukoon Chanintorn , Srisarkun Vilasinee
Published: November 2021

The IEEE 802.11ay wireless communication standard consents gadgets to link in the spectrum of millimeter wave (mm-Wave) 60 Giga Hertz band through 100 Gbps bandwidth. The development of promising high bandwidth in communication networks is a must as QoS, throughput and error rates of bandwidth-intensive applications like merged reality (MR), artificial intelligence (AI) related apps or wireless communication boggling exceed the extent of the chronic 802.11 standard established in 2012. Thus, the IEEE 802.11ay task group committee has newly amended recent physical (PHY) and medium access control (MAC) blueprints to guarantee a technical achievement especially in link delay on multipath fading channels (MPFC). However, due to the congestion of super bandwidth intensive apps such as IoT and big data, we propose to diversify a propagation delay to practical extension. This article then focuses on a real-world situation and how the IEEE 802.11ay design is affected by the performance of mm-Wave propagation. In specific, we randomize the unstable MPFC link capacity by taking the divergence of congested network parameters into account. The efficiency of congested MPFC-based wireless network is simulated and confirmed by advancements described in the standard.