Spatial and temporal evolution of electromagnetic pulses from solid target irradiated with multi-hundred-terawatt laser pulse inside target chamber

Giant electromagnetic pulses(EMPs) induced by high-power laser irradiating solid targets interfere with various experimental diagnoses and even damage equipment,so unveiling the evolution of EMPs inside the laser chamber is crucial for designing effective EMP shielding.In this work,the transmission characteristics of EMPs as a function of distances from the target chamber center(TCC) are studied using B-dot probes.The mean EMP amplitude generated by picosecond laser-target interaction reaches 561 kV m^(-1),357 kV m^(-1),395 kV m^(-1),and 341 kV m^(-1)at 0.32 m,0.53 m,0.76 m,and 1 m from TCC,which decreases dramatically from 0.32 m to 0.53 m.However,it shows a fluctuation from 0.53 m to 1 m.The temporal features of EMPs indicate that time-domain EMP signals near the target chamber wall have a wider full width at half maximum compared to that close to TCC,mainly due to the echo oscillation of electromagnetic waves inside the target chamber based on simulation and experimentation.The conclusions of this study will provide a new approach to mitigate strong electromagnetic pulses by decreasing the echo oscillation of electromagnetic waves inside the target chamber during laser coupling with targets.

Multi-Scale Approach for Gold Targeting in Côte d’Ivoire Paleoproterozoic Rocks

The aim of this study is to contribute to better targeting of gold prospecting areas using geospatial information. To this end, 3 mining sites were selected for the study. They are: the Sénoufo belt (Barrick Gold mine), the Yaouré complex (Perseus Mining mine) and the South Fetêkro belt (Bonikro, Hiré and Agbaou mines). For this study, a multi-scale approach was carried out at regional, mine and microscopic levels. At the regional scale, a comparative analysis of 1:200,000 scale geological maps revealed that 3 main lithologies are regularly repeated on and around the various mining sites. These are: undifferentiated volcanics, metagranodiorites and metasiltites dominated by meta-arenites. Most of these lithologies are affected by undifferentiated faults generally oriented NE-SW, N-S, ENE-WSW and WNW-ESE. In addition, gold and manganese occurrences are present on all the sites studied. At the mine scale, radarsat-1 images processing indicate that the main mining sites are generally located near or at the intersection of lineaments-oriented NE-SW or N-S on the one hand and E-W or ENE-WSW or WNW-ESE or again NW-SE on the other. These mines are also located at the interface between zones of high and low lineament density. At the microscopic scale, petrographic studies of undifferentiated volcanic samples from the various sites indicate that they consist of andesites, meta-andesites and tuffs.

Targeted multi-agent communication algorithm based on state control

As an important mechanism in multi-agent interaction,communication can make agents form complex team relationships rather than constitute a simple set of multiple independent agents.However,the existing communication schemes can bring much timing redundancy and irrelevant messages,which seriously affects their practical application.To solve this problem,this paper proposes a targeted multiagent communication algorithm based on state control(SCTC).The SCTC uses a gating mechanism based on state control to reduce the timing redundancy of communication between agents and determines the interaction relationship between agents and the importance weight of a communication message through a series connection of hard-and self-attention mechanisms,realizing targeted communication message processing.In addition,by minimizing the difference between the fusion message generated from a real communication message of each agent and a fusion message generated from the buffered message,the correctness of the final action choice of the agent is ensured.Our evaluation using a challenging set of Star Craft II benchmarks indicates that the SCTC can significantly improve the learning performance and reduce the communication overhead between agents,thus ensuring better cooperation between agents.

Target layer state estimation in multi-layer complex dynamical networks considering nonlinear node dynamics

In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method.

An Air Defense Weapon Target Assignment Method Based on Multi-Objective Artificial Bee Colony Algorithm

With the advancement of combat equipment technology and combat concepts,new requirements have been put forward for air defense operations during a group target attack.To achieve high-efficiency and lowloss defensive operations,a reasonable air defense weapon assignment strategy is a key step.In this paper,a multi-objective and multi-constraints weapon target assignment(WTA)model is established that aims to minimize the defensive resource loss,minimize total weapon consumption,and minimize the target residual effectiveness.An optimization framework of air defense weapon mission scheduling based on the multiobjective artificial bee colony(MOABC)algorithm is proposed.The solution for point-to-point saturated attack targets at different operational scales is achieved by encoding the nectar with real numbers.Simulations are performed for an imagined air defense scenario,where air defense weapons are saturated.The non-dominated solution sets are obtained by the MOABC algorithm to meet the operational demand.In the case where there are more weapons than targets,more diverse assignment schemes can be selected.According to the inverse generation distance(IGD)index,the convergence and diversity for the solutions of the non-dominated sorting genetic algorithm III(NSGA-III)algorithm and the MOABC algorithm are compared and analyzed.The results prove that the MOABC algorithm has better convergence and the solutions are more evenly distributed among the solution space.

Joint target assignment and power allocation in the netted C-MIMO radar when tracking multi-targets in the presence of self-defense blanket jamming

The netted radar system(NRS)has been proved to possess unique advantages in anti-jamming and improving target tracking performance.Effective resource management can greatly ensure the combat capability of the NRS.In this paper,based on the netted collocated multiple input multiple output(CMIMO)radar,an effective joint target assignment and power allocation(JTAPA)strategy for tracking multi-targets under self-defense blanket jamming is proposed.An architecture based on the distributed fusion is used in the radar network to estimate target state parameters.By deriving the predicted conditional Cramer-Rao lower bound(PC-CRLB)based on the obtained state estimation information,the objective function is formulated.To maximize the worst case tracking accuracy,the proposed JTAPA strategy implements an online target assignment and power allocation of all active nodes,subject to some resource constraints.Since the formulated JTAPA is non-convex,we propose an efficient two-step solution strategy.In terms of the simulation results,the proposed algorithm can effectively improve tracking performance in the worst case.

MUTS-Based Cooperative Target Stalking for A Multi-USV System

This paper is concerned with the cooperative target stalking for a multi-unmanned surface vehicle(multi-USV)system.Based on the multi-agent deep deterministic policy gradient(MADDPG)algorithm,a multi-USV target stalking(MUTS)algorithm is proposed.Firstly,a V-type probabilistic data extraction method is proposed for the first time to overcome shortcomings of the MADDPG algorithm.The advantages of the proposed method are twofold:1)it can reduce the amount of data and shorten training time;2)it can filter out more important data in the experience buffer for training.Secondly,in order to avoid the collisions of USVs during the stalking process,an action constraint method called Safe DDPG is introduced.Finally,the MUTS algorithm and some existing algorithms are compared in cooperative target stalking scenarios.In order to demonstrate the effectiveness of the proposed MUTS algorithm in stalking tasks,mission operating scenarios and reward functions are well designed in this paper.The proposed MUTS algorithm can help the multi-USV system avoid internal collisions during the mission execution.Moreover,compared with some existing algorithms,the newly proposed one can provide a higher convergence speed and a narrower convergence domain.

Target acquisition performance in the presence of JPEG image compression

This paper presents an investigation on the effect of JPEG compression on the similarity between the target image and the background,where the similarity is further used to determine the degree of clutter in the image.Four new clutter metrics based on image quality assessment are introduced,among which the Haar wavelet-based perceptual similarity index,known as HaarPSI,provides the best target acquisition prediction results.It is shown that the similarity between the target and the background at the boundary between visually lossless and visually lossy compression does not change significantly compared to the case when an uncompressed image is used.In future work,through subjective tests,it is necessary to check whether this presence of compression at the threshold of just noticeable differences will affect the human target acquisition performance.Similarity values are compared with the results of subjective tests of the well-known target Search_2 database,where the degree of agreement between objective and subjective scores,measured through linear correlation,reached a value of 90%.

Target Detection Algorithm in Foggy Scenes Based on Dual Subnets

Under the influence of air humidity,dust,aerosols,etc.,in real scenes,haze presents an uneven state.In this way,the image quality and contrast will decrease.In this case,It is difficult to detect the target in the image by the universal detection network.Thus,a dual subnet based on multi-task collaborative training(DSMCT)is proposed in this paper.Firstly,in the training phase,the Gated Context Aggregation Network(GCANet)is used as the supervisory network of YOLOX to promote the extraction of clean information in foggy scenes.In the test phase,only the YOLOX branch needs to be activated to ensure the detection speed of the model.Secondly,the deformable convolution module is used to improve GCANet to enhance the model’s ability to capture details of non-homogeneous fog.Finally,the Coordinate Attention mechanism is introduced into the Vision Transformer and the backbone network of YOLOX is redesigned.In this way,the feature extraction ability of the network for deep-level information can be enhanced.The experimental results on artificial fog data set FOG_VOC and real fog data set RTTS show that the map value of DSMCT reached 86.56%and 62.39%,respectively,which was 2.27%and 4.41%higher than the current most advanced detection model.The DSMCT network has high practicality and effectiveness for target detection in real foggy scenes.

Electromagnetic pulses produced by a picosecond laser interacting with solid targets

A high-power laser ablating solid targets induces giant electromagnetic pulses(EMPs),which are intimately pertinent to laser parameters,such as energy and pulse width.In this study,we reveal the features of EMPs generated from a picosecond(ps)laser irradiating solid targets at the SG-Ⅱpicosecond petawatt(PSPW)laser facility.The laser energy and pulse,as well as target material and thickness,show determinative effects on the EMPs’amplitude.More intense EMPs are detected behind targets compared to those at the other three positions,and the EMP amplitude decreases from 90.09 kV/m to 17.8 kV/m with the gold target thickness increasing from 10μm to 20μm,which is suppressed when the laser pulse width is enlarged.The results are expected to provide more insight into EMPs produced by ps lasers coupling with targets and lay the foundation for an effective EMP shielding design in high-power laser infrastructures.

Improved Weighted Local Contrast Method for Infrared Small Target Detection

In order to address the problem of high false alarm rate and low probabilities of infrared small target detection in complex low-altitude background,an infrared small target detection method based on improved weighted local contrast is proposed in this paper.First,the ratio information between the target and local background is utilized as an enhancement factor.The local contrast is calculated by incorporating the heterogeneity between the target and local background.Then,a local product weighted method is designed based on the spatial dissimilarity between target and background to further enhance target while suppressing background.Finally,the location of target is obtained by adaptive threshold segmentation.As experimental results demonstrate,the method shows superior performance in several evaluation metrics compared with six existing algorithms on different datasets containing targets such as unmanned aerial vehicles(UAV).

Distinct molecular targets of ProEGCG from EGCG and superior inhibition of angiogenesis signaling pathways for treatment of endometriosis

Endometriosis is a common chronic gynecological disease with endometrial cell implantation outside the uterus.Angiogenesis is a major pathophysiology in endometriosis.Our previous studies have demonstrated that the prodrug of epigallocatechin gallate(ProEGCG)exhibits superior anti-endometriotic and anti-angiogenic effects compared to epigallocatechin gallate(EGCG).However,their direct binding targets and underlying mechanisms for the differential effects remain unknown.In this study,we demonstrated that oral ProEGCG can be effective in preventing and treating endometriosis.Additionally,1D and 2D Proteome Integral Solubility Alteration assay-based chemical proteomics identified metadherin(MTDH)and PX domain containing serine/threonine kinase-like(PXK)as novel binding targets of EGCG and ProEGCG,respectively.Computational simulation and BioLayer interferometry were used to confirm their binding affinity.Our results showed that MTDH-EGCG inhibited protein kinase B(Akt)-mediated angiogenesis,while PXK-ProEGCG inhibited epidermal growth factor(EGF)-mediated angiogenesis via the EGF/hypoxia-inducible factor(HIF-1a)/vascular endothelial growth factor(VEGF)pathway.In vitro and in vivo knockdown assays and microvascular network imaging further confirmed the involvement of these signaling pathways.Moreover,our study demonstrated that ProEGCG has superior therapeutic effects than EGCG by targeting distinct signal transduction pathways and may act as a novel antiangiogenic therapy for endometriosis.

The functions of exosomes targeting astrocytes and astrocyte-derived exosomes targeting other cell types

Astrocytes are the most abundant glial cells in the central nervous system;they participate in crucial biological processes,maintain brain structure,and regulate nervous system function.Exosomes are cell-derived extracellular vesicles containing various bioactive molecules including proteins,peptides,nucleotides,and lipids secreted from their cellular sources.Increasing evidence shows that exosomes participate in a communication network in the nervous system,in which astrocyte-derived exosomes play important roles.In this review,we have summarized the effects of exosomes targeting astrocytes and the astrocyte-derived exosomes targeting other cell types in the central nervous system.We also discuss the potential research directions of the exosome-based communication network in the nervous system.The exosome-based intercellular communication focused on astrocytes is of great significance to the biological and/or pathological processes in different conditions in the brain.New strategies may be developed for the diagnosis and treatment of neurological disorders by focusing on astrocytes as the central cells and utilizing exosomes as communication mediators.

A Layered Energy-EfficientMulti-Node Scheduling Mechanism for Large-Scale WSN

In recent years, target tracking has been considered one of the most important applications of wireless sensornetwork (WSN). Optimizing target tracking performance and prolonging network lifetime are two equally criticalobjectives in this scenario. The existing mechanisms still have weaknesses in balancing the two demands. Theproposed heuristic multi-node collaborative scheduling mechanism (HMNCS) comprises cluster head (CH)election, pre-selection, and task set selectionmechanisms, where the latter two kinds of selections forma two-layerselection mechanism. The CH election innovatively introduces the movement trend of the target and establishesa scoring mechanism to determine the optimal CH, which can delay the CH rotation and thus reduce energyconsumption. The pre-selection mechanism adaptively filters out suitable nodes as the candidate task set to applyfor tracking tasks, which can reduce the application consumption and the overhead of the following task setselection. Finally, the task node selection is mathematically transformed into an optimization problem and thegenetic algorithm is adopted to form a final task set in the task set selection mechanism. Simulation results showthat HMNCS outperforms other compared mechanisms in the tracking accuracy and the network lifetime.

A food-grade and senescent cell-targeted fisetin delivery system based on whey protein isolate-galactooligosaccharides Maillard conjugate

Cellular senescence is the results of aging and age-related diseases,and the development of anti-aging methods may improve health and extend longevity.The natural flavonol fisetin has been shown to antagonize senescence in vitro and increases longevity in vivo,but has poor water solubility and limited bioavailability.In this study,a food-grade and senescent cell-targeted delivery system for fisetin was developed based on whey protein isolate-galactooligosaccharides(WPI-GOS)Maillard conjugate,which could recognize senescence associatedβ-galactosidase in senescent cells.The fisetin nanoparticles possessed a high encapsulation efficiency,excellent dispersibility in water,good storage stability and well biocompatibility.Moreover,they could effectively accumulate and retain in senescent cells with excellent senescent cell-targeting efficacy,and inhibit the oxidative stress-induced cellular senescence in vitro.Thus,this novel nanoparticle system based on WPI-GOS Maillard conjugate showed promise to deliver hydrophobic bioactive ingredients like fisetin to senescent cells to improve their bioavailability and anti-senescence effect.

A modified OMP method for multi-orbit three dimensional ISAR imaging of the space target

The conventional two dimensional(2D)inverse synthetic aperture radar(ISAR)imaging fails to provide the targets'three dimensional(3D)information.In this paper,a 3D ISAR imaging method for the space target is proposed based on mutliorbit observation data and an improved orthogonal matching pursuit(OMP)algorithm.Firstly,the 3D scattered field data is converted into a set of 2D matrix by stacking slices of the 3D data along the elevation direction dimension.Then,an improved OMP algorithm is applied to recover the space target's amplitude information via the 2D matrix data.Finally,scattering centers can be reconstructed with specific three dimensional locations.Numerical simulations are provided to demonstrate the effectiveness and superiority of the proposed 3D imaging method.

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.

Treat to target in Crohn’s disease:A practical guide for clinicians

A treat-to-target(T2T)approach applies the principles of early intervention and tight disease control to optimise long-term outcomes in Crohn's disease.The Selecting Therapeutic Targets in Inflammatory Bowel Disease(STRIDE)-II guidelines specify short,intermediate,and long-term treatment goals,documenting specific treatment targets to be achieved at each of these timepoints.Scheduled appraisal of Crohn’s disease activity against pre-defined treatment targets at these timepoints remains central to determining whether current therapy should be continued or modified.Consensus treatment targets in Crohn’s disease comprise combination clinical and patient-reported outcome remission,in conjunction with biomarker normalisation and endoscopic healing.Although the STRIDE-II guidelines endorse the pursuit of endoscopic healing,clinicians must consider that this may not always be appropriate,acceptable,or achievable in all patients.This underscores the need to engage patients at the outset in an effort to personalise care and individualise treatment targets.The use of non-invasive biomarkers such as faecal calprotectin in conjunction with cross-sectional imaging techniques,particularly intestinal ultrasound,holds great promise;as do emerging treatment targets such as transmural healing.Two randomised clinical trials,namely,CALM and STARDUST,have evaluated the efficacy of a T2T approach in achieving endoscopic endpoints in patients with Crohn’s disease.Findings from these studies reflect that patient subgroups and Crohn’s disease characteristics likely to benefit most from a T2T approach,remain to be clarified.Moreover,outside of clinical trials,data pertaining to the real-world effectiveness of a T2T approach remains scare,highlighting the need for pragmatic real-world studies.Despite the obvious promise of a T2T approach,a lack of guidance to support its integration into real-world clinical practice has the potential to limit its uptake.This highlights the need to describe strategies,processes,and models of care capable of supporting the integration and execution of a T2T approach in real-world clinical practice.Hence,this review seeks to examine the current and emerging literature to provide clinicians with practical guidance on how to incorporate the principles of T2T into routine clinical practice for the management of Crohn’s disease.

To Analyze the Sensitivity of RT-PCR Assays Employing S Gene Target Failure with Whole Genome Sequencing Data during Third Wave by SARS-CoV-2 Omicron Variant

Introduction: Omicron is a highly divergent variant of concern (VOCs) of a severe acute respiratory syndrome SARS-CoV-2. It carries a high number of mutations in its spike protein hence;it is more transmissible in the community by immune evasion mechanisms. Due to mutation within S gene, most Omicron variants have reported S gene target failure (SGTF) with some commercially available PCR kits. Such diagnostic features can be used as markers to screen Omicron. However, Whole Genome Sequencing (WGS) is the only gold standard approach to confirm novel microorganisms at genetically level as similar mutations can also be found in other variants that are circulating at low frequencies worldwide. This Retrospective study is aimed to assess RT-PCR sensitivity in the detection of S gene target failure in comparison with whole genome sequencing to detect variants of Omicron. Methods: We have analysed retrospective data of SARS-CoV-2 positive RT-PCR samples for S gene target failure (SGTF) with TaqPath COVID-19 RT-PCR Combo Kit (ThermoFisher) and combined with sequencing technologies to study the emerged pattern of SARS-CoV-2 variants during third wave at the tertiary care centre, Surat. Results: From the first day of December 2021 till the end of February 2022, a total of 321,803 diagnostic RT-PCR tests for SARS-CoV-2 were performed, of which 20,566 positive cases were reported at our tertiary care centre with an average cumulative positivity of 6.39% over a period of three months. In the month of December 21 samples characterized by the SGTF (70/129) were suggestive of being infected by the Omicron variant and identified as Omicron (B.1.1.529 lineage) when sequence. In the month of January, we analysed a subset of samples (n = 618) with SGTF (24%) and without SGTF (76%) with Ct values Conclusions: During the COVID-19 pandemic, it took almost more than 15 days to diagnose infection and identify pathogen by sequencing technology. In contrast to that molecular assay provided quick identification with the help of SGTF phenomenon within 5 hours of duration. This strategy helps scientists and health policymakers for the quick isolation and identification of clusters. That ultimately results in a decreased transmission of pathogen among the community.

Targeted regeneration and upcycling of spent graphite by defect‐driven tin nucleation

The recycling of spent batteries has become increasingly important owing to their wide applications,abundant raw material supply,and sustainable development.Compared with the degraded cathode,spent anode graphite often has a relatively intact structure with few defects after long cycling.Yet,most spent graphite is simply burned or discarded due to its limited value and inferior performance on using conventional recycling methods that are complex,have low efficiency,and fail in performance restoration.Herein,we propose a fast,efficient,and“intelligent”strategy to regenerate and upcycle spent graphite based on defect‐driven targeted remediation.Using Sn as a nanoscale healant,we used rapid heating(~50 ms)to enable dynamic Sn droplets to automatically nucleate around the surface defects on the graphite upon cooling owing to strong binding to the defects(~5.84 eV/atom),thus simultaneously achieving Sn dispersion and graphite remediation.As a result,the regenerated graphite showed enhanced capacity and cycle stability(458.9 mAh g^(−1) at 0.2 A g^(−1) after 100 cycles),superior to those of commercial graphite.Benefiting from the self‐adaption of Sn dispersion,spent graphite with different degrees of defects can be regenerated to similar structures and performance.EverBatt analysis indicates that targeted regeneration and upcycling have significantly lower energy consumption(~99%reduction)and near‐zero CO2 emission,and yield much higher profit than hydrometallurgy,which opens a new avenue for direct upcycling of spend graphite in an efficient,green,and profitable manner for sustainable battery manufacture.