Ultrahigh-brightness 50 MeV electron beam generation from laser wakefield acceleration in a weakly nonlinear regime

We propose an efficient scheme to produce ultrahigh-brightness tens of MeV electron beams by designing a density-tailored plasma to induce a wakefield in the weakly nonlinear regime with a moderate laser energy of 120 mJ.In this scheme,the second bucket of the wakefield can have a much lower phase velocity at the steep plasma density down-ramp than the first bucket and can be exploited to implement longitudinal electron injection at a lower laser intensity,leading to the generation of bright electron beams with ultralow emittance together with low energy spread.Three-dimensional particle-in-cell simulations are carried out and demonstrate that high-quality electron beams with a peak energy of 50 MeV,ultralow emittance of28 nm rad,energy spread of 1%,charge of 4.4 pC,and short duration less than 5 fs can be obtained within a 1-mm-long tailored plasma density,resulting in an ultrahigh six-dimensional brightness B6D,n of2×1017 A/m2/0.1%.By changing the density parameters,tunable bright electron beams with peak energies ranging from 5 to 70 MeV,a small emittance of B0.1 mm mrad,and a low energy spread at a few-percent level can be obtained.These bright MeV-class electron beams have a variety of potential applications,for example,as ultrafast electron probes for diffraction and imaging,in laboratory astrophysics,in coherent radiation source generation,and as injectors for GeV particle accelerators.

Local saliency consistency-based label inference for weakly supervised salient object detection using scribble annotations

Recently,weak supervision has received growing attention in the field of salient object detection due to the convenience of labelling.However,there is a large performance gap between weakly supervised and fully supervised salient object detectors because the scribble annotation can only provide very limited foreground/background information.Therefore,an intuitive idea is to infer annotations that cover more complete object and background regions for training.To this end,a label inference strategy is proposed based on the assumption that pixels with similar colours and close positions should have consistent labels.Specifically,k-means clustering algorithm was first performed on both colours and coordinates of original annotations,and then assigned the same labels to points having similar colours with colour cluster centres and near coordinate cluster centres.Next,the same annotations for pixels with similar colours within each kernel neighbourhood was set further.Extensive experiments on six benchmarks demonstrate that our method can significantly improve the performance and achieve the state-of-the-art results.

Macro-micro behaviors and failure mechanism of frozen weakly cemented mudstone

Understanding the mechanical properties and multiscale failure mechanism of frozen soft rock is an important prerequisite for the construction safety of tunnels,artificially frozen ground and other infrastructure in cold regions.In this study,the triaxial compression test are performed on mudstone in the weakly cemented soft rock strata in the mining area of western China,and the mechanical characteristics and failure mechanism of weakly cemented mudstone are systematically investigated under the combined action of freezing and loading.Furthermore,the quantitative relationship between the microstructural parameters and the macroscopic strength and deformation parameters is established based on fractal theory.Thus,the failure mechanism of frozen weakly cemented mudstone is revealed on both micro- and macro-scales.The results show that temperature and confining pressure significantly affects the elastic modulus and peak strength of weakly cemented mudstone.With decreasing temperature,the compressive strength increases,while the corresponding peak strain decreases gradually.On the deformation curve,the plastic deformation stage is shortened,and the brittle fracture feature at the post-peak stage is more prominent,and the elastic modulus correspondingly increases with decreasing temperature.Under low-temperature conditions,most of the weakly cemented mudstone undergoes microscopic shear failure along the main fracture surface.The micro-fracture morphology characteristics of weakly cemented mudstone under different temperatures are quantified via the fractal dimension,and an approximately exponential relationship can be obtained among the fractal dimension and the temperature,compressive strength and elastic modulus.

Weakly Supervised Network with Scribble-Supervised and Edge-Mask for Road Extraction from High-Resolution Remote Sensing Images

Significant advancements have been achieved in road surface extraction based on high-resolution remote sensingimage processing. Most current methods rely on fully supervised learning, which necessitates enormous humaneffort to label the image. Within this field, other research endeavors utilize weakly supervised methods. Theseapproaches aim to reduce the expenses associated with annotation by leveraging sparsely annotated data, such asscribbles. This paper presents a novel technique called a weakly supervised network using scribble-supervised andedge-mask (WSSE-net). This network is a three-branch network architecture, whereby each branch is equippedwith a distinct decoder module dedicated to road extraction tasks. One of the branches is dedicated to generatingedge masks using edge detection algorithms and optimizing road edge details. The other two branches supervise themodel’s training by employing scribble labels and spreading scribble information throughout the image. To addressthe historical flaw that created pseudo-labels that are not updated with network training, we use mixup to blendprediction results dynamically and continually update new pseudo-labels to steer network training. Our solutiondemonstrates efficient operation by simultaneously considering both edge-mask aid and dynamic pseudo-labelsupport. The studies are conducted on three separate road datasets, which consist primarily of high-resolutionremote-sensing satellite photos and drone images. The experimental findings suggest that our methodologyperforms better than advanced scribble-supervised approaches and specific traditional fully supervised methods.

血清sTWEAK、Netrin-1联合APACHEⅡ评分对重型颅脑损伤患者术后预后不良的预测价值

目的探讨血清可溶性肿瘤坏死因子样凋亡弱诱导因子(sTWEAK)、神经轴突导向因子-1(Netrin-1)联合急性生理学与慢性健康状况评分系统Ⅱ(APACHEⅡ)评分对重型颅脑损伤患者术后预后不良的预测价值。方法选取2020年6月至2022年6月该院收治的120例重型颅脑损伤患者,根据术后30 d预后情况分为预后良好组和预后不良组。对比两组血清sTWEAK、Netrin-1水平及APACHEⅡ评分。采用单因素和多因素Logistic回归分析重型颅脑损伤患者术后预后不良的影响因素,并据以构建血清sTWEAK、Netrin-1及APACHEⅡ评分联合应用的预测模型,受试者工作特征(ROC)曲线分析血清sTWEAK、Netrin-1水平及APACHEⅡ评分对重型颅脑损伤患者术后预后不良的预测价值。结果预后不良组的重症监护室居住时间长于预后良好组,白蛋白水平、入院时格拉斯哥昏迷评分法评分和血清Netrin-1水平低于预后良好组,多发脑挫裂伤占比、机械通气占比、入院时APACHEⅡ评分和血清sTWEAK、血清肌酐、血尿素氮水平均高于预后良好组,差异有统计学意义(P<0.05)。多因素Logistic回归分析结果显示,多发脑挫裂伤、Netrin-1水平降低、入院时APACHEⅡ评分升高、sTWEAK水平升高为重型颅脑损伤患者术后预后不良的危险因素(P<0.05)。ROC曲线分析结果显示,血清sTWEAK、Netrin-1及APACHEⅡ评分3个指标单独及联合应用时曲线下面积及其95%CI分别为0.742(0.552~0.925)、0.731(0.488~0.963)、0.714(0.502~0.911)、0.882(0.795~0.947)。结论血清sTWEAK、Netrin-1联合APACHEⅡ评分对重型颅脑损伤患者术后预后不良具有较好的预测价值,可为临床治疗方案的制订提供参考。

自发性急性脑出血患者血浆sCD163/sTWEAK比值与预后的关系

目的探究自发性急性脑出血(ACH)患者血浆可溶性CD163(sCD163)/可溶性肿瘤坏死因子样凋亡弱诱导因子(sTWEAK)比值与预后的关系。方法纳入ACH患者90例作为病例组,根据格拉斯哥预后评分将病例组分为预后不良组(38例)和预后良好组(52例);另选取同期体检健康者45例为对照组。酶联免疫吸附试验检测血浆sCD163、sTWEAK水平并计算sCD163/sTWEAK比值。分析血浆sCD163、sTWEAK水平及sCD163/sTWEAK比值与临床资料的相关性;Logistic回归分析ACH患者预后不良的影响因素;受试者工作特征(ROC)曲线分析sCD163/sTWEAK比值对ACH患者预后不良的预测价值。结果病例组血浆sCD163、sTWEAK水平及sCD163/sTWEAK比值均显著高于对照组;预后良好组上述指标均低于预后不良组(P<0.05)。预后良好组血肿体积、美国国立卫生研究院卒中量表(NIHSS)评分、高血压及幕下出血比例均低于预后不良组,低密度脂蛋白胆固醇(LDL-C)高于预后不良组(P<0.05)。相关性分析表明,血浆sCD163、sTWEAK水平及sCD163/sTWEAK比值与出血部位、血肿体积、NIHSS评分、白细胞计数、血小板计数、中性粒细胞/淋巴细胞比值(NLR)呈正相关(P<0.05)。Logistic回归分析显示,sCD163/sTWEAK比值、出血部位、血肿体积、NIHSS评分为ACH患者预后不良的影响因素(P<0.05)。ROC曲线结果表明,sCD163/sTWEAK比值评估ACH患者预后不良的AUC为0.850,敏感度和特异度分别为86.84%和69.23%。结论sCD163/sTWEAK比值在ACH患者血浆中水平较高,并与预后不良有关,该值对此类患者的预后有一定预测价值。

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

Inverse Faraday effect of weakly relativistic full Poincaré beams in plasma

The inverse Faraday effect(IFE),which usually refers to the phenomenon in which a quasi-static axial magnetic field is self-generated when a circularly polarized beam propagates in a plasma,has rarely been studied for lasers with unconventional polarization states.In this paper,IFE is reconsidered for weakly relativistic full Poincarébeams,which can contain all possible laser polarization states.Starting from cold electron fluid equations and the conservation of generalized vorticity,a self-consistent theoretical model combining the nonlinear azimuthal current and diamagnetic current is presented.The theoretical results show that when such a laser propagates in a plasma,an azimuthally varying quasi-static axial magnetic field can be generated,which is quite different from the circularly polarized case.These results are qualitatively and quantitatively verified by three-dimensional particle-in-cell simulations.Our work extends the theoretical understanding of the IFE and provides a new degree of freedom in the design of magnetized plasma devices.

Deep Learning Models Based on Weakly Supervised Learning and Clustering Visualization for Disease Diagnosis

The coronavirus disease 2019(COVID-19)has severely disrupted both human life and the health care system.Timely diagnosis and treatment have become increasingly important;however,the distribution and size of lesions vary widely among individuals,making it challenging to accurately diagnose the disease.This study proposed a deep-learning disease diagnosismodel based onweakly supervised learning and clustering visualization(W_CVNet)that fused classification with segmentation.First,the data were preprocessed.An optimizable weakly supervised segmentation preprocessing method(O-WSSPM)was used to remove redundant data and solve the category imbalance problem.Second,a deep-learning fusion method was used for feature extraction and classification recognition.A dual asymmetric complementary bilinear feature extraction method(D-CBM)was used to fully extract complementary features,which solved the problem of insufficient feature extraction by a single deep learning network.Third,an unsupervised learning method based on Fuzzy C-Means(FCM)clustering was used to segment and visualize COVID-19 lesions enabling physicians to accurately assess lesion distribution and disease severity.In this study,5-fold cross-validation methods were used,and the results showed that the network had an average classification accuracy of 85.8%,outperforming six recent advanced classification models.W_CVNet can effectively help physicians with automated aid in diagnosis to determine if the disease is present and,in the case of COVID-19 patients,to further predict the area of the lesion.

Tuning desolvation kinetics of in-situ weakly solvating polyacetal electrolytes for dendrite-free lithium metal batteries

The host structure of polymers significantly influences ion transport and interfacial stability of electrolytes,dictating battery cycle life and safety for solid-state lithium metal batteries.Despite promising properties of ethylene oxide-based electrolytes,their typical clamp-like coordination geometry leads to crowd solvation sheath and overly strong interactions between Li^(+)and electrolytes,rendering difficult dissociation of Li+and unfavorable solid electrolyte interface(SEI).Herein,we explore weakly solvating characteristics of polyacetal electrolytes owing to their alternately changing intervals between–O–coordinating sites in the main chain.Such structural asymmetry leads to unique distorted helical solvation sheath,and can effectively reduce Li^(+)-electrolyte binding and tune Li^(+)desolvation kinetics in the insitu formed polymer electrolytes,yielding anion-derived SEI and dendrite-free Li electrodeposition.Combining with photoinitiated cationic ring-opening polymerization,polyacetal electrolytes can be instantly formed within 5 min at the surface of electrode,with high segmental chain motion and well adapted interfaces.Such in-situ polyacetal electrolytes enabled more than 1300-h of stable lithium electrodeposition and prolonged cyclability over 200 cycles in solid-state batteries at ambient temperatures,demonstrating the vital role of molecular structure in changing solvating behavior and Li deposition stability for high-performance electrolytes.

Weakly Supervised Abstractive Summarization with Enhancing Factual Consistency for Chinese Complaint Reports

A large variety of complaint reports reflect subjective information expressed by citizens.A key challenge of text summarization for complaint reports is to ensure the factual consistency of generated summary.Therefore,in this paper,a simple and weakly supervised framework considering factual consistency is proposed to generate a summary of city-based complaint reports without pre-labeled sentences/words.Furthermore,it considers the importance of entity in complaint reports to ensure factual consistency of summary.Experimental results on the customer review datasets(Yelp and Amazon)and complaint report dataset(complaint reports of Shenyang in China)show that the proposed framework outperforms state-of-the-art approaches in ROUGE scores and human evaluation.It unveils the effectiveness of our approach to helping in dealing with complaint reports.

Anion-Regulated Weakly Solvating Electrolytes for High-Voltage Lithium Metal Batteries

Development of advanced high-voltage electrolytes is key to achieving high-energy-density lithium metal batteries(LMBs).Weakly solvating electrolytes(WSE)can produce unique anion-driven interphasial chemistry via altering the solvating power of the solvent,but it is difficult to dissolve the majority of Li salts and fail to cycle at a cut-off voltage above 4.5 V.Herein,we present a new-type WSE that is regulated by the anion rather than the solvent,and the first realize stable cycling of dimethoxyethane(DME)at 4.6 V without the use of the“solvent-in-salt”strategy.The relationships between the degree of dissociation of salts,the solvation structure of electrolytes,and the electrochemical performance of LMBs were systematically investigated.We found that LiBF_(4),which has the lowest degree of dissociation,can construct an anion-rich inner solvation shell,resulting in anion-derived anode/cathode interphases.Thanks to such unusual solvation structure and interphasial chemistry,the Li-LiCoO_(2)full cell with LiBF_(4)-based WSE could deliver excellent rate performance(115 mAh g^(-1)at 10 C)and outstanding cycling stability even under practical conditions,including high loading(10.7 mg cm^(-2)),thin Li(50μm),and limited electrolyte(1.2μL mg^(-1)).

An Experimental Study on the Reinforcement of Weakly-Consolidated Shallow Formation in Deep Water Using an Epoxy Resin-Based Fluid

The mechanical properties of Portland cement differ from the weakly consolidated shallow formation in deep water.This results in undesired abrupt changes in the compressive strength and elastic modulus at the cement–formation interface.In this study,a water-borne epoxy resin was applied as a strengthening material to reinforce the weakly consolidated shallow formation and protect the cement sheath from potential failure.The mechanical properties of the unconsolidated clay were tested,including their changes with increases in the temperature and curing time.In addition,the effects of the seawater,cement slurry alkaline filtrate,and saltwater drilling fluid were evaluated.As confirmed by the results,the strengthening fluid was excellent at reinforcing the unconsolidated clay,with a compressive strength of 2.49 MPa(after curing for 7 days),even at a dosage of 5%.A cement slurry filtrate with a high pH was suitable to produce the required strengthening of the formation,especially its early age strength.It should also be pointed out that the used fluid exhibited good compatibility with the saltwater drilling fluid and seawater behaved well as a diluent for the strengthening fluid.

Measuring small longitudinal phase shifts via weak measurement amplification

Weak measurement amplification,which is considered as a very promising scheme in precision measurement,has been applied to various small physical quantities estimations.Since many physical quantities can be converted into phase signals,it is interesting and important to consider measuring small longitudinal phase shifts by using weak measurement.Here,we propose and experimentally demonstrate a novel weak measurement amplification-based small longitudinal phase estimation,which is suitable for polarization interferometry.We realize one order of magnitude amplification measurement of a small phase signal directly introduced by a liquid crystal variable retarder and show that it is robust to the imperfection of interference.Besides,we analyze the effect of magnification error which is never considered in the previous works,and find the constraint on the magnification.Our results may find important applications in high-precision measurements,e.g.,gravitational wave detection.

GLOBAL WEAK SOLUTIONS FOR AN ATTRACTION-REPULSION CHEMOTAXIS SYSTEM WITH p-LAPLACIAN DIFFUSION AND LOGISTIC SOURCE

This paper is concerned with the following attraction-repulsion chemotaxis system with p-Laplacian diffusion and logistic source:■The system here is under a homogenous Neumann boundary condition in a bounded domainΩ ■ R^(n)(n≥2),with χ,ξ,α,β,γ,δ,k_(1),k_(2)> 0,p> 2.In addition,the function f is smooth and satisfies that f(s)≤κ-μs~l for all s≥0,with κ ∈ R,μ> 0,l> 1.It is shown that(ⅰ)if l> max{2k_(1),(2k_(1)n)/(2+n)+1/(p-1)},then system possesses a global bounded weak solution and(ⅱ)if k_(2)> max{2k_(1)-1,(2k_(1)n)/(2+n)+(2-p)/(p-1)} with l> 2,then system possesses a global bounded weak solution.

Semigroup of Weakly Continuous Operators Associated to a Generalized Schrödinger Equation

In this work, we prove the existence and uniqueness of the solution of the generalized Schrödinger equation in the periodic distributional space P’. Furthermore, we prove that the solution depends continuously respect to the initial data in P’. Introducing a family of weakly continuous operators, we prove that this family is a semigroup of operators in P’. Then, with this family of operators, we get a fine version of the existence and dependency continuous theorem obtained. Finally, we provide some consequences of this study.

Group of Weakly Continuous Operators Associated to a Generalized Schrödinger Type Homogeneous Model

In this work, we prove the existence and uniqueness of the solution of the generalized Schrödinger type homogeneous model in the periodic distributional space P’. Furthermore, we prove that the solution depends continuously respect to the initial data in P’. Introducing a family of weakly continuous operators, we prove that this family is a group of operators in P’. Then, with this family of operators, we get a fine version of the existence and dependency continuous theorem obtained. Finally, we give some remarks derived from this study.

Experimental investigation on weak shock wave mitigation characteristics of flexible polyurethane foam and polyurea

In recent years,explosion shock wave has been considered as a signature injury of the current military conflicts.Although strong shock wave is lethal to the human body,weak shock wave can cause many more lasting consequences.To investigate the protection ability and characteristics of flexible materials and structures under weak shock wave loading,the blast wave produced by TNT explosive is loaded on the polyurethane foam with the density of 200.0 kg/m3(F-200)and 400.0 kg/m3(F-400),polyurea with the density of 1100.0 kg/m^(3)(P-1100)and structures composed of the two materials,which are intended for individual protection.Experimental results indicate that the shock wave is attenuated to weak pressure disturbance after interacting with the flexible materials which are not damaged.The shock wave protective capability of single-layer materials is dependent on their thickness,density and microscopic characteristics.The overpressure,maximum pressure rise rate and impulse of transmitted wave decrease exponentially with increase in sample thickness.For the same thickness,F-400 provides better protective capability than F-200 while P-1100 shows the best protective capability among the three materials.In this study,as the materials are not destroyed,F-200 with a thickness more than10.0 mm,F-400 with a thickness more than 4.0 mm,and P-1100 with a thickness more than 1.0 mm can attenuate the overpressure amplitude more than 90.0%.Further,multi-layer flexible composites are designed.Different layer layouts of designed structures and layer thickness of the single-layer materials can affect the protective performance.Within the research range,the structure in which polyurea is placed on the impact side shows the optimal shock wave protective performance,and the thicknesses of polyurea and polyurethane foam are 1.0 mm and 4.0 mm respectively.The overpressure attenuation rate reached maximum value of 93.3%and impulse attenuation capacity of this structure are better than those of single-layer polyurea and polyurethane foam with higher areal density.

ENERGY CONSERVATION FOR THE WEAK SOLUTIONS TO THE 3D COMPRESSIBLE NEMATIC LIQUID CRYSTAL FLOW

In this paper,we establish some regularity conditions on the density and velocity fields to guarantee the energy conservation of the weak solutions for the three-dimensional compressible nematic liquid crystal flow in the periodic domain.

Design of weak current measurement system and research on temperature impact

A dedicated weak current measurement system was designed to measure the weak currents generated by the neutron ionization chamber.This system incorporates a second-order low-pass filter circuit and the Kalman filtering algorithm to effectively filter out noise and minimize interference in the measurement results.Testing conducted under normal temperature conditions has demonstrated the system's high precision performance.However,it was observed that temperature variations can affect the measurement performance.Data were collected across temperatures ranging from -20 to 70℃,and a temperature correction model was established through linear regression fitting to address this issue.The feasibility of the temperature correction model was confirmed at temperatures of -5 and 40℃,where relative errors remained below 0.1% after applying the temperature correction.The research indicates that the designed measurement system exhibits excellent temperature adaptability and high precision,making it particularly suitable for measuring weak currents.