MTTSNet:Military time-sensitive targets stealth network via real-time mask generation

The automatic stealth task of military time-sensitive targets plays a crucial role in maintaining national military security and mastering battlefield dynamics in military applications.We propose a novel Military Time-sensitive Targets Stealth Network via Real-time Mask Generation(MTTSNet).According to our knowledge,this is the first technology to automatically remove military targets in real-time from videos.The critical steps of MTTSNet are as follows:First,we designed a real-time mask generation network based on the encoder-decoder framework,combined with the domain expansion structure,to effectively extract mask images.Specifically,the ASPP structure in the encoder could achieve advanced semantic feature fusion.The decoder stacked high-dimensional information with low-dimensional information to obtain an effective mask layer.Subsequently,the domain expansion module guided the adaptive expansion of mask images.Second,a context adversarial generation network based on gated convolution was constructed to achieve background restoration of mask positions in the original image.In addition,our method worked in an end-to-end manner.A particular semantic segmentation dataset for military time-sensitive targets has been constructed,called the Military Time-sensitive Target Masking Dataset(MTMD).The MTMD dataset experiment successfully demonstrated that this method could create a mask that completely occludes the target and that the target could be hidden in real time using this mask.We demonstrated the concealment performance of our proposed method by comparing it to a number of well-known and highly optimized baselines.

WSN Mobile Target Tracking Based on Improved Snake-Extended Kalman Filtering Algorithm

A wireless sensor network mobile target tracking algorithm(ISO-EKF)based on improved snake optimization algorithm(ISO)is proposed to address the difficulty of estimating initial values when using extended Kalman filtering to solve the state of nonlinear mobile target tracking.First,the steps of extended Kalman filtering(EKF)are introduced.Second,the ISO is used to adjust the parameters of the EKF in real time to adapt to the current motion state of the mobile target.Finally,the effectiveness of the algorithm is demonstrated through filtering and tracking using the constant velocity circular motion model(CM).Under the specified conditions,the position and velocity mean square error curves are compared among the snake optimizer(SO)-EKF algorithm,EKF algorithm,and the proposed algorithm.The comparison shows that the proposed algorithm reduces the root mean square error of position by 52%and 41%compared to the SOEKF algorithm and EKF algorithm,respectively.

Gene therapy in Parkinson's disease: targeting the endplasmic reticulum proteostasis network

Parkinson’s disease（PD）is the second most common neurodegenerative disease affecting 1%of the population over 60 years of age.The progressive degeneration of dopaminergic neurons at the substantia nigra pars compacta（SNpc）results in a severe and gradual depletion of dopamine content in the striatum,a phenomena that is responsible for the characteristic motor symptoms of this disease.

Target Inactivation and Recovery in Two-Layer Networks

We study the target inactivation and recovery in two-layer networks. Five kinds of strategies are chosen to attack the two-layer networks and to recover the activity of the networks by increasing the inter-layer coupling strength. The results show that we can easily control the dying state effectively by a randomly attacked situation. We then investigate the recovery activity of the networks by increasing the inter-layer coupled strength. The optimal values of the inter-layer coupled strengths are found, which could provide a more effective range to recovery activity of complex networks. As the multilayer systems composed of active and inactive elements raise important and interesting problems, our results on the target inactivation and recovery in two-layer networks would be extended to different studies.

Fusion network for small target detection based on YOLO and attention mechanism

Target detection is an important task in computer vision research, and such an anomaly detection and the topic of small target detection task is more concerned. However, there are still some problems in this kind of researches, such as small target detection in complex environments is susceptible to background interference and poor detection results. To solve these issues, this study proposes a method which introduces the attention mechanism into the you only look once(YOLO) network. In addition, the amateur-produced mask dataset was created and experiments were conducted. The results showed that the detection effect of the proposed mothed is much better.

TCM network pharmacology:A new trend towards combining computational,experimental and clinical approaches

Traditional Chinese medicine(TCM)is a precious treasure of the Chinese nation and has unique advantages in the prevention and treatment of diseases.The holistic view of TCM coincides with the new generation of medical research paradigm characterized by network and system.TCM gave birth to a new method featuring holistic and systematic"network target",a core theory and method of network pharmacology.TCM is also an important research object of network pharmacology.TCM network pharmacology,which aims to understand the network-based biological basis of complex diseases,TCM syndromes and herb treatments,plays a critical role in the origin and development process of network pharmacology.This review introduces new progresses of TCM network pharmacology in recent years,including predicting herb targets,understanding biological foundation of diseases and syndromes,network regulation mechanisms of herbal formulae,and identifying disease and syndrome biomarkers based on biological network.These studies show a trend of combining computational,experimental and clinical approaches,which is a promising direction of TCM network pharmacology research in the future.Considering that TCM network pharmacology is still a young research field,it is necessary to further standardize the research process and evaluation indicators to promote its healthy development.

Network Pharmacology-based Approaches Capture Essence of Chinese Herbal Medicines

Traditional Chinese Medicine（TCM）, a crucial component of the current medical system, has been extensively used in clinical practice due to its valuable therapeutic efficacy, and its potentials as an important source of new pharmacophores. TCM is characterized by holistic theory, which emphasizes maintaining the balance of the patient＇s whole body using herbal formulae（fangji in Chinese） composed of mixtures of herbs with multiple bioactive ingredients. Because of the complex nature of these formulae, it is necessary to develop systematic methods to identify their bioactive ingredients and to clarify their mechanisms of action. With the rapid progress in bioinformatics, systems biology, and polypharmacology, ＂network pharmacology＂, which shifts the ＂one target, one drug＂ paradigm to the ＂network target, multi-component＂ strategy, has attracted the attention because it can not only reveal the underlying complex interactions between a herbal formula and cellular proteins but detect the influence of their interactions on the function and behavior of the system. Growing evidence shows that the network pharmacology strategy can be a powerful approach to modern research on TCM. The present paper focuses on the basis of network pharmacology and the recent progress in its methodology, illustrates its utility in screening bioactive ingredients and elucidating the mechanisms of action of TCM herbal formulae, analyzes its limitations and problems, and discusses its development direction and application prospects.

Exploring Traditional Chinese Medicine by A Novel Therapeutic Concept of Network Target

Traditional Chinese medicine（TCM） holds a holistic theory, and specializes in balancing disordered human body using numerous natural products, particularly Chinese herbal formulae. TCM has certain treatment advantages for patients suffering from various complex diseases. However, due to the complex nature of TCM, it remains difficult to unveil such holistic medicine by the current reductionism research strategies, which treat both herbal ingredients and targets in isolation. Recently, an emerging network pharmacology approach has been introduced to tackle this bottleneck problem. A TCM-derived novel therapeutic concept, ＂network target＂, which is different from the Western medicine＇s ＂onetarget＂ concept, has been proposed from China. The network target strategy is able to illustrate the complex interactions among the biological systems, drugs, and complex diseases from a network perspective, and thus provides an innovative approach to access ancient remedies in a precision manner and at a systematic level, which also highlights TCM＇s potential in current medical systems.