bluuebunny/crossref_metadata_2025_split huggingface dataset:
Glycomimetics as Promising Inhibitors of Ebola Virus, Flavivirus and HIV Infections
Authors: Fieschi Franck , Bernardi Anna , Rojo Javier 
Published: November 2021

Many pathogens, including emerging ones such as Ebola, Zika, Dengue, SARS-CoV-2, etc. contain relevant envelope glycoproteins. The viruses use these glycoproteins to infect cells that express at their surface specific C-type lectins capable of recognizing the envelope glycans. The carbohydrate–lectin interaction is nowadays considered as a promising target to develop new therapeutic strategies against this type of viral infections. To address this goal, different glycomimetic ligands, as well as multivalent systems, have been developed, mimicking the sugars and their multivalent presentation at the pathogen surface. These systems are designed to interfere efficiently with C-type lectin recognition, inhibiting the entrance of the virus into the target cells. In this chapter, we have prepared a brief overview of the state of the art, including the most relevant multivalent glycomimetics developed for this aim, classified taking into consideration the kind of multivalent scaffold used.
Electronic structures of Zn1−xGaxO1−xNx and band offsets of the ZnO/Zn1−xGaxO1−xNx heterojunction across the entire concentration range from first principles
Authors: Li Tianjiao , Liu Xiaojie , Wang Yin , Cao Ronggen , Yin Haitao 
Published: November 2021

Electronic structures of Zn1−xGaxO1−xNx and band offsets of ZnO/Zn1−xGaxO1−xNx heterojunction across the entire concentration range were predicted by the modified Becke–Johnson semi-local exchange combined with the coherent potential approximation.
Reductively disilylated N-heterocycles as versatile organosilicon reagents
Authors: Sahoo Padmini , Majumdar Moumita 
Published: November 2021

The reductively disilylated N-heterocyclic systems diligently give up electrons thereby demonstrating as versatile reagents in the salt-free reduction of transition metals, main-group halides, in organic transformations and in materials syntheses.
Robust fuzzy model predictive control for voltage regulation in islanded microgrids
Authors: Mottaghizadeh Masood , Aminifar Farrokh , Amraee Turaj , Sanaye‐Pasand Majid 
Published: November 2021

AbstractAn effective robust fuzzy model predictive control (RFMPC) method for secondary voltage control in islanded microgrids (μGs) is presented here. In contrast to the existing techniques, which require a detailed model of μG and an ideal communication network between μG central controller and primary local controllers, RFMPC is synthesized for a non‐linear model of the μG with various time delays, uncertainties, and bounded disturbances. The famous Takagi‐Sugeno fuzzy approach is adopted to approximate the inherently non‐linear model of μG by locally linear dynamics. The Lyapunov–Razumikhin functional method is exploited to deal with time delays. In this regard, sufficient conditions are provided in the form of linear matrix inequalities (LMIs). Then, a sequence of control laws corresponding to a set of terminal constraints is computed offline. Doing so, the online stage is reduced to solving a convex problem with LMI constraints considering the sequence of constraint sets obtained in the offline stage, thereby reducing the computational burden significantly. Robust positive invariance and input‐to‐state stability property concerning communication network deficiency are then speculated. The effectiveness of the proposed RFMPC is verified via a comprehensive suite of simulations in the MATLAB/SimPowerSystems environment.
Power flow analysis of integrated energy microgrid considering non‐smooth characteristics
Authors: Ju Yuntao , Liu Wenwu , Wang Jiankai , Li Jiawei , Huang Yan , Chen Xi , Dong Zhao 
Published: November 2021

AbstractWith the development of electric energy substitution technologies such as electric auxiliary heating, the relationship between electric energy and thermal energy is getting closer, and it is of great significance to in‐depth study of integrated energy micro‐grids containing electricity and heat. However, the integrated energy microgrid power flow (PF) model has non‐smooth characteristics such as distributed generations (DGs) limits, converter stations limits and the unknown direction of pipeline mass flow, which can easily lead to the failure of PF convergence. This paper establishes an integrated energy microgrid model including three‐phase unbalanced AC/DC hybrid microgrid and heating system. Firstly, the correctness of the converter station model is verified by electromagnetic transient simulation, and then the non‐smooth constraint models considering DG and converter station's reactive power limits and pipeline mass flow direction unknown are established based on complementary constraints, and the non‐smooth constraints are smoothed by Fischer‐Burmeister (FB) function. Finally, the integrated energy microgrid is used for PF analysis, and the results verify the rationality of the model and the effectiveness of the proposed non‐smooth characteristics treatment method.
Real time detection of driver fatigue based on CNN‐LSTM
Authors: Liu Ming‐Zhou , Xu Xin , Hu Jing , Jiang Qian‐Nan 
Published: November 2021

AbstractFatigue driving is one of the main causes of traffic accidents. In order to solve this problem, a new Convolutional Neural Network and Long Short‐Term Memory (CNN‐LSTM) based real‐time driver fatigue detection method is proposed. First of all, using simple linear clustering algorithm (SLIC), the driver's image is divided into super pixels of uniform size, which are used as input of CNN, and CNN is trained to automatically learn the features of eyes and mouth contained in the image, and then the location and area of eyes and mouth are obtained by using the trained CNN. On this basis, the eye feature parameter Perclos, mouth feature parameter MClosed and face orientation feature parameter Phdown are extracted, and the above feature parameters on the continuous time series and steering wheel angle feature parameter SA are taken as the input of LSTM, and the fatigue level is taken as the output to detect the fatigue state of the driver in real time. Experimental data shows that this method can not only overcome the influence of illumination, background, angle and individual differences, but also the accuracy of detection can reach 99.78%, and the average detection time is 16.94 ms/frame.
Exploiting robust unsupervised video person re‐identification
Authors: Zang Xianghao , Li Ge , Gao Wei , Shu Xiujun 
Published: November 2021

AbstractUnsupervised video person re‐identification (reID) methods usually depend on global‐level features. Many supervised reID methods employed local‐level features and achieved significant performance improvements. However, applying local‐level features to unsupervised methods may introduce an unstable performance. To improve the performance stability for unsupervised video reID, this paper introduces a general scheme fusing part models and unsupervised learning. In this scheme, the global‐level feature is divided into equal local‐level feature. A local‐aware module is employed to explore the potentials of local‐level feature for unsupervised learning. A global‐aware module is proposed to overcome the disadvantages of local‐level features. Features from these two modules are fused to form a robust feature representation for each input image. This feature representation has the advantages of local‐level feature without suffering from its disadvantages. Comprehensive experiments are conducted on three benchmarks, including PRID2011, iLIDS‐VID, and DukeMTMC‐VideoReID, and the results demonstrate that the proposed approach achieves state‐of‐the‐art performance. Extensive ablation studies demonstrate the effectiveness and robustness of proposed scheme, local‐aware module and global‐aware module. The code and generated features are available at https://github.com/deropty/uPMnet.
Single sample per person face recognition algorithm based on the robust prototype dictionary and robust variation dictionary construction
Authors: Xue Shan , Ren Hai‐Peng 
Published: November 2021

AbstractSingle sample per person (SSPP) face recognition uses only a single face image of each subject in the gallery set to recognize the probe sample. Since single sample cannot provide intra‐class variation information, the matching accuracy of the gallery faces with the faces captured in unconstrained video is usually low. Recently, in order to improve the accuracy, the sparse representation‐based classification (SRC) technology has been extended to generic learning method, which uses prototype and variation dictionary (P+V) model for face recognition. Because the inter‐class scatter between atoms in prototype dictionary is not big enough, and the intra‐class scatter in constructed variation dictionary (such as posture and expression) is not rich enough, the robustness of P+V model for SSPP face recognition is poor. To solve this problem, a robust prototype dictionary and robust variation dictionary construction (RPRV) method is proposed. First, a set of atoms is obtained by dictionary learning method using gallery images and generic images. Second, some effective atoms are selected by the proposed function index method. Finally, the robust prototype dictionary (RP) and the robust variation dictionary (RV) are represented linearly using these effective atoms, respectively. The face recognition is performed according to the proposed RP+RV model. Experiment results using public datasets show that the proposed RPRV has strong robustness for the face captured under the unconstrained environment. Comparison results show that the proposed RPRV method outperform state‐of‐the‐art SRC‐based methods for SSPP face recognition.
An image cipher system based on networked chaotic map with parameter q
Authors: Sun Yu‐Jie , Zhang Hao , Li Zhen‐Yu , Wang Xing‐Yuan , Wang Chun‐Peng 
Published: November 2021

AbstractThis paper models a networked coupling chaotic system with a fractional‐like local map based on network topology and fractional theory. The proposed model contains more system parameters and a more relaxed coupling relationship. The entropy analysis also shows that the proposed model is more sensitive to the changes in the coupling parameter. Based on this model, an effective image cipher system is designed using universal scrambling and diffusion based on DNA encoding. The proposed method utilizes the generated pseudo‐random signals from the networked chaotic map. The secret keys can be generated in parallel and the security is also improved due to the rise of complexity of the new chaotic map. Analysis and simulations confirm that the new chaotic map as well as the DNA encoding technology improves the effectiveness and robustness of the proposed encryption algorithm.
2.5D vehicle odometry estimation
Authors: Eising Ciarán , Pereira Leroy‐Francisco , Horgan Jonathan , Selvaraju Anbuchezhiyan , McDonald John , Moran Paul 
Published: November 2021

AbstractIt is well understood that in ADAS applications, a good estimate of the pose of the vehicle is required. This paper proposes a metaphorically named 2.5D odometry, whereby the planar odometry derived from the yaw rate sensor and four wheel speed sensors is augmented by a linear model of suspension. While the core of the planar odometry is a yaw rate model that is already understood in the literature, this is augmented by fitting a quadratic to the incoming signals, enabling interpolation, extrapolation, and a finer integration of the vehicle position. It is shown, by experimental results with a DGPS/IMU reference, that this model provides highly accurate odometry estimates, compared with existing methods. Utilising sensors that return the change in height of vehicle reference points with changing suspension configurations, a planar model of the vehicle suspension is defined, thus augmenting the odometry model. An experimental framework and evaluations criteria is presented by which the goodness of the odometry is evaluated and compared with existing methods. This odometry model has been designed to support low‐speed surround‐view camera systems that are well‐known. Thus, some application results that show a performance boost for viewing and computer vision applications using the proposed odometry are presented.
Charging control strategies for lithium‐ion battery packs: Review and recent developments
Authors: Ghaeminezhad Nourallah , Monfared Mohammad 
Published: November 2021

AbstractThe expanding use of lithium‐ion batteries in electric vehicles and other industries has accelerated the need for new efficient charging strategies to enhance the speed and reliability of the charging process without decaying battery performance indices. Numerous attempts have been conducted to establish optimal charging techniques for commercial lithium‐ion batteries during the last decade. However, a few of them are devoted to the comprehensive analysis and comparison of the charging techniques from the control‐oriented perspective for a battery pack. To fill this gap, a review of the most up‐to‐date charging control methods applied to the lithium‐ion battery packs is conducted in this paper. They are broadly classified as non‐feedback‐based, feedback‐based, and intelligent charging methods. Finally, the paper concludes with a comprehensive discussion of the strengths and weaknesses of the reviewed techniques.
Tidal current prediction based on fractal theory and improved least squares support vector machine
Authors: Zhang Anan , Lin Yu , Sun Yangfan , Yuan Haiyun , Wang Min , Liu Guofeng , Hu Yiru 
Published: November 2021

AbstractAn accurate short‐term tidal current prediction is essential to optimize the operation mode of offshore microgrids. According to the correlation characteristics of tidal current speed and direction in time series, a tidal current prediction model is proposed by using fractal theory, dragonfly optimization algorithm and least squares support vector machine (DA‐LSSVM). First, the Rescaled range analysis (R/S analysis) in fractal theory is used to construct the tidal current analytic model with moving Hurst index of time series characteristics and Von‐Mises statistics (V statistic). The model evaluates the stability and autocorrelation of the tidal current and reveals the persistence of tidal current fluctuation. It also shows the orderliness hidden behind the randomness, indicating that the tidal current characteristics can be extended. Second, the least squares support vector machine is used to train the samples in high‐dimensional space, and the dragonfly algorithm is used to optimize the parameters of the least squares support vector machine to obtain the best prediction model. Finally, based on the empirical data recorded in the straits in North America, the model was used for the analysis and prediction of tidal current speed and tidal current direction, which verified the validity and accuracy of the proposed method.
Modelling and simulation analysis of MMC‐HVDC system based on transient energy flow
Authors: Yan Jun , Chen Lixu , Xu Jianzhong , Zhao Chengyong , Jia Xiufang 
Published: November 2021

AbstractIn the high voltage direct current (HVDC) transmission system composed of modular multilevel converters (MMC), considering the distribution of transient energy flow (TEF) contributes to the transient modelling and fault characteristic analysis when dc short‐circuit fault occurs. For single MMC, based on transient energy conservation, the capacitors of half bridge sub‐modular (HBSM) can be equivalent to time‐varying capacitor. And the MMC transient model is established, in which dynamic switching of HBSM and ac import are considered. By solving state equations of the model, the fault and TEF characteristics of MMC are obtained. For MMC‐HVDC grid, a TEF analysis method based on electromagnetic transient simulation results is proposed, which can not only reveal the evolution of dc fault, but also realize quantitative analysis of fault current through recursive calculation. Based on characteristics of TEF, an energy limitation strategy considering the fluctuation range of capacitor voltage in HBSM is proposed, which can delay the blocking time effectively. According to the simulation results in PSCAD, the correctness of the transient model and the energy limitation strategy is verified, meanwhile, the TEF analysis method is applied to the four‐terminal MMC‐HVDC grid to obtain its fault characteristics.
Lightweight frame scrambling mechanisms for end‐to‐end privacy in edge smart surveillance
Authors: Fitwi Alem , Chen Yu , Zhu Sencun 
Published: November 2021

AbstractAs smart surveillance has become popular in today's smart cities, millions of closed circuit television cameras are ubiquitously deployed that collect huge amount of visual information. All these raw visual data are often transported over a public network to distant video analytic centres. This increases the risk of interception and the spill of individuals' information into the wider cyberspace that risks privacy breaches. The edge computing paradigm allows the enforcement of privacy protection mechanisms at the point where the video frames are created. Nonetheless, existing cryptographic schemes are computationally unaffordable at the resource‐constrained network edge. Based on chaotic methods, three lightweight end‐to‐end privacy‐protection mechanisms are proposed: (1) a novel lightweight Sine‐cosine Chaotic Map, which is a robust and efficient solution for enciphering frames at edge cameras; (2) Dynamic Chaotic Image Enciphering scheme that can run in real time at the edge; (3) a lightweight Regions of Interest Masking scheme that ensures the privacy of sensitive attributes like face on video frames. Design rationales are discussed and extensive experimental analyses substantiate the feasibility and security of the proposed schemes.
A circularly polarized TEM to TE11 mode converter antenna
Authors: Hosseini Seyed Jalil 
Published: November 2021

AbstractA design and simulation of the mode converter antenna (MCA) with right‐hand circular polarization, at 10 GHz frequency, is presented. The circularly polarized mode converter antenna (CPMCA) consists of two inner conductors and a body. The TEM mode is converted into a circular polarization TE11 mode, using the inner conductors connecting the coaxial waveguide in two vertical and horizontal directions. The sidelobe level is less than −15 dB at the working frequency. The S11 and axial ratios of the CPMCA are about −16.5 and 0.15 dB, respectively. Also, the axial ratio is in the acceptable range.
Spectroscopic study of Ceres’ collisional family candidates
Authors: Tinaut-Ruano F. , de Leon J. , Tatsumi E. , Rousseau B. , Rizos J. L. , Marchi S. 
Published: November 2021

Context. Despite the observed signs of large impacts on the surface of Ceres, there is no confirmed collisional family associated with this dwarf planet. After a dynamical and photometric study, a sample of 156 asteroids were proposed as candidate members of a Ceres collisional family.
Aims. Our main objective is to study the connection between Ceres and a total of 14 observed asteroids among the candidates sample to explore their genetic relationships with Ceres.
Methods. We obtained visible spectra of these 14 asteroids using the OSIRIS spectrograph at the 10.4 m Gran Telescopio Canarias. We computed spectral slopes in two different wavelength ranges, from 0.49 to 0.80 μm and from 0.80 to 0.92 μm, to compare the values obtained with those on Ceres’ surface previously computed using the Visible and Infrared Spectrometer instrument on board the NASA Dawn spacecraft. We also calculated the spectral slopes in the same range for ground-based observations of Ceres collected from the literature.
Results. We present the visible spectra and the taxonomy of 14 observed asteroids. We found that only two of the asteroids are spectrally compatible with Ceres’ surface. Further analysis of those two asteroids indicates that they are spectrally young and thus less likely to be members of the Ceres family.
Conclusions. All in all, our results indicate that most of the 14 observed asteroids are not likely to belong to a Ceres collisional family. Despite two of them being spectrally compatible with the young surface of Ceres, further evaluation is needed to confirm or reject their origin from Ceres.
A Neurologist's Practical Approach to Cognitive Impairment
Authors: Tipton Philip W. , Day Gregory S. , Graff-Radford Neill 
Published: November 2021

AbstractThe global prevalence of dementia is expected to triple by the year 2050. This impending health care crisis has led to new heights of public awareness and general concern regarding cognitive impairment. Subsequently, clinicians are seeing more and more people presenting with cognitive concerns. It is important that clinicians meet these concerns with a strategy promoting accurate diagnoses. We have diagramed and described a practical approach to cognitive impairment. Through an algorithmic approach, we determine the presence and severity of cognitive impairment, systematically evaluate domains of function, and use this information to determine the next steps in evaluation. We also discuss how to proceed when cognitive impairment is associated with motor abnormalities or rapid progression.
Approach to Loss of Consciousness: Distinguishing Epileptic Seizures, Psychogenic Nonepileptic Seizures, and Syncope
Authors: Ebong Ima , Haghighat Zahra , Bensalem-Owen Meriem 
Published: November 2021

AbstractTransient loss of consciousness (TLOC) is a common emergent neurological issue, which can be attributed to syncope, epileptic seizures, and psychogenic nonepileptic seizures. The purpose of this article is to outline an approach to diagnosing the most common etiologies of TLOC by focusing on the importance of the history and physical examination, as well as targeted diagnostic tests.
Approach to Neuropathic Pain
Authors: Malhotra Ashwin , Weaver Joshua 
Published: November 2021

AbstractNeuropathic pain is a common chief complaint encountered by neurologists and primary care providers. It is caused by disorders involving the somatosensory nervous system. The clinical evaluation of neuropathic pain is challenging and requires a multifaceted systematic approach with an emphasis on a thorough history and physical examination to identify characteristic signs and symptoms. Ancillary laboratory investigations, targeted imaging, and electrodiagnostic studies further help identify underlying etiologies to guide specific treatments. Management of neuropathic pain encompasses treating the underlying pathology as well as symptomatic control with nonpharmacological, pharmacological, and interventional therapies. Here, we present an approach to help evaluate patients with neuropathic pain.
Approach to Common Sleep Disorders
Authors: Wang Yujie , Salas Rachel Marie E. 
Published: November 2021

AbstractSleep disorders are highly relevant in clinical practice given their prevalence as well as their impact on health outcomes and quality of life. The most common concerns are excessive daytime sleepiness, insomnia, disordered breathing, and abnormal movements or behaviors during sleep. A detailed but targeted history is vital, particularly from the sleep partner/witness. In-laboratory sleep testing (polysomnography and multiple sleep latency test) remains vital in the diagnosis of certain sleep disorders (such as sleep-disordered breathing and central hypersomnia) and in specific populations (such as in children and individuals with comorbid medical disorders). Advances in technology have allowed for a variety of methods in assessing a patient's sleep, from compact devices to evaluate for sleep apnea, wrist actigraphy, and mobile device-based applications. As the pathophysiology of various sleep disorders becomes better elucidated, disease-specific medications have been developed for these conditions. Nonetheless, a multidisciplinary approach to management is necessary, including improving sleep hygiene and cognitive behavioral therapy.