bluuebunny/crossref_metadata_2025_split huggingface dataset:
Endocytic protein intersectin1-S shuttles into nucleus to suppress the DNA replication in breast cancer
Authors: Zhang Huikun , Guo Zhifang , Liu Xiaoli , Zhao Yawen , Chen Yongzi , Zhang Ming , Fu Li , Gu Feng , Ma Yongjie 
Published: October 2021

AbstractBreast cancer is the most common type of cancer worldwide. However, the well-known molecular biomarkers are not enough to meet the needs of precision medicine. In search for novel targets in this regard, we reported ITSN1 (intersectin1) as one of the candidates through mRNA microarray analysis. In the present study, we reported that endocytic protein ITSN1-S exists not only in the cytoplasm but also in nuclei of breast cancer cells. ITSN1-S′ functional nuclear localization signal is within its residues 306–312. Its nuclear export signal (NES) resides within its SH3 domains. We also found, the interaction between the CC domain of nuclear ITSN1-S and the NT domain of nuclear DNA helicase II (NDH II) directly suppressed the DNA replication and nascent DNA synthesis by inhibiting the R-loops resolution in breast cancer cells. Furthermore, the interaction between the EH domains of cytoplasmic ITSN1-S and PI3KC2α inhibit cell migration and invasion by inactivating the PI3KC2α-AKT pathway. Our results were confirmed in both ITSN1 gene knockout cells and in vivo assays. Finally, our clinical data showed a potential application of the combined consideration of the cytoplasmic and nuclear ITSN1-S as an independent prognosis factor. In conclusion, our study revealed ITSN1-S′ novel positioning in the nuclei of breast cancer cells, its function in suppressing DNA replication, and its potential application in improved breast cancer prognosis.
Higher-order phosphatase–substrate contacts terminate the integrated stress response
Authors: Yan Yahui , Harding Heather P. , Ron David 
Published: October 2021

AbstractMany regulatory PPP1R subunits join few catalytic PP1c subunits to mediate phosphoserine and phosphothreonine dephosphorylation in metazoans. Regulatory subunits engage the surface of PP1c, locally affecting flexible access of the phosphopeptide to the active site. However, catalytic efficiency of holophosphatases towards their phosphoprotein substrates remains unexplained. Here we present a cryo-EM structure of the tripartite PP1c–PPP1R15A–G-actin holophosphatase that terminates signaling in the mammalian integrated stress response (ISR) in the pre-dephosphorylation complex with its substrate, translation initiation factor 2α (eIF2α). G-actin, whose essential role in eIF2α dephosphorylation is supported crystallographically, biochemically and genetically, aligns the catalytic and regulatory subunits, creating a composite surface that engages the N-terminal domain of eIF2α to position the distant phosphoserine-51 at the active site. Substrate residues that mediate affinity for the holophosphatase also make critical contacts with eIF2α kinases. Thus, a convergent process of higher-order substrate recognition specifies functionally antagonistic phosphorylation and dephosphorylation in the ISR.
How dendritic cells sense and respond to viral infections
Authors: Marongiu Laura , Valache Mihai , Facchini Fabio A. , Granucci Francesca 
Published: October 2021

Abstract
The ability of dendritic cells (DCs) to sense viral pathogens and orchestrate a proper immune response makes them one of the key players in antiviral immunity. Different DC subsets have complementing functions during viral infections, some specialize in antigen presentation and cross-presentation and others in the production of cytokines with antiviral activity, such as type I interferons. In this review, we summarize the latest updates concerning the role of DCs in viral infections, with particular focus on the complex interplay between DC subsets and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Despite being initiated by a vast array of immune receptors, DC-mediated antiviral responses often converge towards the same endpoint, that is the production of proinflammatory cytokines and the activation of an adaptive immune response. Nonetheless, the inherent migratory properties of DCs make them a double-edged sword and often viral recognition by DCs results in further viral dissemination. Here we illustrate these various aspects of the antiviral functions of DCs and also provide a brief overview of novel antiviral vaccination strategies based on DCs targeting.
Ferroptosis and NRF2: an emerging battlefield in the neurodegeneration of Alzheimer's disease
Authors: Lane Darius J.R. , Metselaar Billie , Greenough Mark , Bush Ashley I. , Ayton Scott J. 
Published: October 2021

AbstractFerroptosis is an iron- and lipid peroxidation-dependent cell death modality and emerging evidence indicates that ferroptosis has great explanatory potential for neuronal loss and associated CNS dysfunction in a range of neurodegenerative diseases (e.g., Alzheimer's, Parkinson's and Huntington's diseases, Motor neuron disease, Friedreich ataxia (FRDA)). Ferroptotic death results from lethal levels of phospholipid hydroperoxides that are generated by iron-dependent peroxidation of polyunsaturated fatty acids (PUFAs), such as arachidonic and adrenic acids, which are conjugated to specific phospholipids (e.g., phosphatidylethanolamines (PEs)). The major cellular protector against ferroptosis is glutathione peroxidase 4 (GPX4), a membrane-associated selenoenzyme that reduces deleterious phospholipid hydroperoxides to their corresponding benign phospholipid alcohols in a glutathione-dependent manner. Other complementary protective systems have also been identified that act to bolster cellular defences against ferroptosis. Many pharmacological modulators of the ferroptosis pathway have been identified, targeting proteins involved in iron homoeostasis and autophagy; the production and detoxification of lipid peroxides, and cyst(e)ine/glutathione metabolism. While a growing number of cell signalling pathways converge to regulate the ferroptosis cascade, an emerging understanding of ferroptosis regulation suggests that the ferroptotic ‘tone’ of cells can be set by the transcription factor, nuclear factor erythroid 2-related factor 2 (NRF2), which transcriptionally controls many key components of the ferroptosis pathway. In this review, we provide a critical overview of the relationship between ferroptosis and NRF2 signalling. With a focus on the role of ferroptosis in Alzheimer's disease (AD), we discuss how therapeutic modulation of the NRF2 pathway is a viable strategy to explore in the treatment of ferroptosis-driven neurodegeneration.
Numerical wear study of metal‐on‐ultrahigh molecular weight polyethylene‐based cervical total disc arthroplasty by coupling finite element analysis and multi‐body dynamics
Authors: Xin Hua , Zhang Lei , Diao Hao , Jia Junhong , Jin Zhongmin 
Published: October 2021

AbstractIn this study, the effects of in vivo (head flexion‐extension, lateral bending, and axial rotation) and in vitro (ISO 18192‐1) working conditions on the wear of ultrahigh molecular weight polyethylene (UHWMPE)‐based cervical disc prosthesis were studied via numerical simulation. A finite‐element‐based wear prediction framework was built by using a sliding distance and contact area dependent Archard wear law. Moreover, a pre‐developed cervical spine multi‐body dynamics model was incorporated to obtain the in vivo conditions. Contact mechanic analysis stated that in vitro conditions normally led to a higher contact stress and a longer sliding distance, with oval or crossing‐path‐typed sliding track. In contrast, in vivo conditions led to a curvilinear‐typed sliding track. In general, the predicted in vivo wear rate was one order of magnitude smaller than that of in vitro. According to the yearly occurrence of head movement, the estimated total in vivo wear rate was 0.595 mg/annual. While, the wear rate given by the ISO standard test condition was 3.32 mg/annual. There is a significant impact of loading and kinematic condition on the wear of UHMWPE prosthesis. The work conducted in the present study provided a feasible way for quantitatively assessing the wear of joint prosthesis.
Siamese tracking combing frequency channel attention with adaptive template
Authors: Pang Haibo , Xie Meiqin , Liu Chengming , Ma Rongqi , Han Linxuan 
Published: October 2021

AbstractSiamese network based the tracker is a hot topic in the field of visual object tracking. However, Siamese trackers still have a robustness gap compared with state‐of‐the‐art algorithms. Therefore, focusing on the issue, this letter adds Frequency Channel Attention (FCA) and adaptive template feature map to the framework of Siamese neural network. FCA can enhance feature representation of effective channels and improve feature discrimination by modeling the correlation between each channel of the image. In this algorithm, by theoretical analysis and experimental validation, restriction is broken through a simple yet effective FCA network sampling strategy and a Siamese‐FCA tracker with significant performance gain is successfully trained. Meanwhile, in order to better adjust the proportion between target and background, the tracker selects suitable size of the target feature map. Moreover, extensive ablation studies are conducted to demonstrate the effectiveness of the proposed tracker. Fairly, the experimental results of five test benchmarks, including OTB2013, OTB2015, VOT2016, VOT2018 and UAV123 datasets, shows that the proposed algorithm performs outstanding. In particular, the issue of similarity and small target tracking failure is overcome. The average running frame rate reaches 86 frames per second, which can meet the real‐time requirements.
TRC‐YOLO: A real‐time detection method for lightweight targets based on mobile devices
Authors: Wang Guanbo , Ding Hongwei , Yang Zhijun , Li Bo , Wang Yihao , Bao Liyong 
Published: October 2021

AbstractObject detection is one of the main tasks of computer vision. Object detection algorithms usually rely on deep convolutional neural networks, which require the host device to have high computing capabilities, greatly limiting the application of object detection methods for mobile devices with limited computing capabilities, such as embedded devices. Among the current object detection algorithms, the you only look once (YOLO) series takes both speed and accuracy into consideration and is one of the most commonly used methods for object detection. In this article, TRC‐YOLO is proposed, which improves the mean average precision (mAP) and real‐time detection speed of the model while reducing the size of the model. In TRC‐YOLO, the convolution kernel of YOLO v4‐tiny is pruned and an expansive convolution layer is introduced into the residual module of the network to produce an hourglass Cross Stage Partial ResNet (CSPResNet) structure. A receptive field block (RFB) that simulates human vision is also added, increasing the receptive field of the model and strengthening the feature extraction ability of the network. In addition, the convolutional block attention module is applied, which combines spatial attention and channel attention, to enhance the effective features of the model and reduce the negative impact of noise on the model. The size of the TRC‐YOLO model is 17.8 MB, which is 5.9 MB smaller than YOLO v4‐tiny, and the model parameter is 2.983 billion floating point operations per second (BFLOP/s) (3.834 BFLOP/s less than YOLO v4‐tiny). In addition, TRC‐YOLO achieves a real‐time performance of 36.9 frames per second on a Jetson Xavier NX, and its mAP on the PASCAL VOC dataset is 66.4 (3.83 higher than YOLO v4‐tiny). In addition, the mAP of TRC‐YOLO on the MS COCO dataset is 37.7, which is 1.9 higher than that of the baseline model.
Improved quadruple sparse census transform and adaptive multi‐shape aggregation algorithms for precise stereo matching
Authors: Huang Chih‐Hsuan , Yang Jar‐Ferr 
Published: October 2021

AbstractStereo matching is an important computer vision tool for three‐dimensional (3D) positioning, 3D visual representation, precision detection and recognition with 3D information. For 3D visual representation, for example, the depth image‐based rendering (DIBR) needs high accuracy depth maps to synthesise multiple views for 3D naked‐eyes displays. It is hard to predict high‐precision disparity for smooth regions and occlusion areas by traditional census‐based stereo matching methods. In this work, two new improved algorithms, called the improved quadruple sparse census transform and the adaptive multi‐shape aggregation, are proposed to achieve a precise stereo matching system. Instead of a binary threshold, the improved quadruple auxiliary census function with an adaptive threshold and the patch mean can raise the discrimination performance for better stereo matching. The selected sparse census patch is proposed to reduce the computation of the pixel‐matching cost. For effective aggregation of matching costs, multi‐shape windows and a texture‐aware algorithm is suggested to decide a suitable window. The proposed adaptive multi‐shape aggregation method performs better and solves the discontinuous depth problem occurring near the object boundaries. Experimental results show that the proposed stereo matching system with the proposed quadruple sparse census transform and multi‐shape cost aggregation achieves better raw depth maps than the existing algorithms for stereo matching.
Analysis and optimization of speed regulation ability with field weakening of the stator hybrid laminated remanufactured motor
Authors: Song Shouxu , Xia Yan 
Published: October 2021

AbstractTo improve the efficiency, a 13 kW used vehicle permanent magnet synchronous motor was remanufactured, whose stator core was replaced by a combination of amorphous alloy laminations and silicon steel laminations. But the speed regulation ability with field weakening of the remanufactured motor limits its development towards high speed direction. Taking the remanufactured motor as the object, based on the theory of speed regulation with field weakening, the maximum speed range was improved by increasing direct‐axis inductance, and the structural optimization parameters affecting the direct‐axis inductance were analysed. The two‐dimensional inductance superposition method was proposed to calculate the direct‐axis and quadrature‐axis inductance of the remanufactured motor, and its accuracy and feasibility were verified by finite element simulation. The segmented structure of the V‐type permanent magnet was used, and the motor structure was optimised from three aspects: the width and position of magnetic bridge and the magnetic pole implantation depth. The orthogonal experiments were designed to determine the best parameter combination. The results show that the direct‐axis inductance of the optimised remanufactured motor is increased by 16.33%, and the performance of speed regulation with field weakening is improved significantly.
Prediction on freezing fraction and collision coefficient in ice accretion model of transmission lines using icing mass growth rate
Authors: Yang Lin , Hu Zhihao , Nian Lupeng , Hao Yanpeng , Li Licheng 
Published: October 2021

AbstractFreezing fraction and collision coefficient are the key parameters in the ice accretion model, which should be calculated to predict the icing trend for transmission lines. Here a mathematical relation between freezing fraction and collision coefficient was derived using the simplified head balance model of transmission lines icing. Combined with the empirical formula of the liquid water content in air, a calculation method of the freezing fraction and collision coefficient was proposed using the ice surface temperature of transmission lines and the icing mass growth rate. The method to measure the icing mass growth rate based on online monitoring data and icing experiments was proposed. The icing experiments were carried out in the low‐temperature ice chamber with the same parameters as the online monitoring environmental parameters. The values of the freezing fraction and collision coefficient were calculated by using the online monitoring data and icing experiments data respectively, the calculation results were compared. The maximum relative differences between the calculation results from the online monitoring data and the icing experiments data do not exceed 18%, which proves the validity of the calculation method of the freezing fraction and collision coefficient in ice accretion model of transmission lines.
Mixed‐integer stochastic evaluation of battery energy storage system integration strategies in distribution systems
Authors: Sepúlveda Rangel Camilo Alberto , Canha Luciane Neves , Sperandio Mauricio , Miranda Vladimiro 
Published: October 2021

AbstractThis paper presents a new approach to the problem of defining an investment policy in battery energy storage systems in active distribution networks, taking into account a diversity of uncertainties. The proposed methodology allows the selection of type, capacity, and location of battery energy storage systems in distribution networks with distributed generation and electric vehicle charging stations. A mixed‐integer stochastic programming problem is cunningly approached with a metaheuristic, where fitness calculation with stochastic scenarios is performed by introducing an approximation to the operation costs in the form of a polynomial neural network, generated according to the Group Method of Data Handling—GMDH method, with strong computing speeding‐up. The quality of this approximation for heavy Monte Carlo simulations is assessed in a first case study using a 33‐bus distribution test system. The optimization planning model is then validated in the same test system using real data collected from solar and wind sources, demand, prices, and charging stations. Four types of batteries are compared considering degradation impact. The results demonstrate the practicality and advantages of this process.
Detecting adversarial examples by additional evidence from noise domain
Authors: Gao Song , Yu Shui , Wu Liwen , Yao Shaowen , Zhou Xiaowei 
Published: October 2021

AbstractDeep neural networks are widely adopted powerful tools for perceptual tasks. However, recent research indicated that they are easily fooled by adversarial examples, which are produced by adding imperceptible adversarial perturbations to clean examples. Here the steganalysis rich model (SRM) is utilized to generate noise feature maps, and they are combined with RGB images to discover the difference between adversarial examples and clean examples. In particular, a two‐stream pseudo‐siamese network that fuses the subtle difference in RGB images with the noise inconsistency in noise features is proposed. The proposed method has strong detection capability and transferability, and can be combined with any model without modifying its architecture or training procedure. The extensive empirical experiments show that, compared with the state‐of‐the‐art detection methods, the proposed approach achieves excellent performance in distinguishing adversarial samples generated by popular attack methods on different real datasets. Moreover, this method has good generalization, it trained by a specific adversary can defend against other adversaries effectively.
Disentangled representation learning GANs for generalized and stable font fusion network
Authors: Qin Mengxi , Zhang Ziying , Zhou Xiaoxue 
Published: October 2021

AbstractAutomatic generation of calligraphy fonts has attracted broad attention of researchers. However, previous font generation research mainly focused on the known font style imitation based on image to image translation. For poor interpretability, it is hard for deep learning to create new fonts with various font styles and features according to human understanding. To address this issue, the font fusion network based on generative adversarial networks (GANs) and disentangled representation learning is proposed in this paper to generate brand new fonts. It separates font into two understandable disentangled features: stroke style and skeleton shape. According to personal preferences, various new fonts with multiple styles can be generated by fusing the stroke style and skeleton shape of different fonts. First, this task improves the interpretability of deep learning, and is more challenging than simply imitating font styles. Second, considering the robustness of the network, a fuzzy supervised learning skill is proposed to enhance the stability of the fusion of two fonts with considerable discrepancy. Finally, instead of retraining, the authors' trained model can be quickly transferred to other font fusion samples. It improves the efficiency of the model. Qualitative and quantitative results demonstrate that the proposed method is capable of efficiently and stably generating the new font images with multiple styles. The source code and the implementation details of our model are available at https://github.com/Qinmengxi/Fontfusion.
Fourth‐order nonlinear distortion to the power spectrum of RF amplifiers
Authors: Yang Xianzhen , Li Shiyu , Li Fu 
Published: October 2021

AbstractEven‐order intermodulation distortions are often considered easy to filter in narrowband radio frequency (RF) wireless systems because they are usually located far away from the desired passband and adjacent bands. However, even‐order intermodulation distortions have recently attracted more interest with the increasing popularity of wideband RF applications. The authors' previous work was devoted to establishing the power spectrum model of second‐order intermodulation distortion. Motivated by the latest efforts on RF power amplifier linearization with second‐order and fourth‐order intermodulation, our focus now is to establish a power spectrum model of fourth‐order intermodulation distortion which can be used to discuss the fourth‐order impacts on the passband and adjacent bands. Here, together with the authors' previous work on the odd‐order intermodulation, a relatively comprehensive power spectrum model is presented here, including second‐, third‐, fourth‐, and fifth‐order intermodulation, which offers a broader view for spectrum planners and RF designers. With qualitative and quantitative reasoning, we further explain that higher‐order (i.e., ) IM distortions of a weakly nonlinear amplifier are indeed negligible. The experiment measurement at the end of this paper validates the spectrum model.
Compressed domain image retargeting in hierarchical wavelet trees
Authors: Hsin Hsi‐Chin 
Published: October 2021

AbstractThis paper presents an efficient algorithm with content aware spatial scalability for effective displaying on various screens of different sizes. It combines the set partitioning in hierarchical trees (SPIHT) algorithm and the multiscale seam carving (MSC) algorithm in the compressed domain. As seams of insignificant wavelet trees can be discarded as early as possible, the burden of unnecessary computation and memory space is alleviated. Experimental results show that the proposed algorithm is preferable to other existing pixel‐domain algorithms.
S8-Mediated Cyclization of Bis(2-aminophenyl) Disulfide/Diselenide with Arylacetylenes/Styrenes: Access to 2-(Arylmethyl)-1,3-benzothiazoles/benzoselenazoles
Authors: Wu Hongli , Gan Haifeng , Feng Caojian , Zhao Lihuan , Cao Mengru 
Published: October 2021

AbstractA novel S8-mediated approach to benzothiazoles/benzoselenazoles from bis(2-aminophenyl) disulfides/diselenides and phenylacetylenes or styrenes has been developed. 2-(Arylmethyl)-1,3-benzoselenazoles were comprehensively synthesized for the first time. The reactions proceeded in moderate to excellent yields, and with a gram-scale application.