Weak localization in disordered spin-1 chiral fermions

We theoretically investigate the quantum interference theory of magnetotransport of the three-component or spin-1 chiral fermions, which possess two linear Dirac bands and a flat band. For isotropic scalar impurities, the correction of conductivity from the coherent backscatter and non-coherent backscatter contributions cancel out in the intravalley scattering, leading to a weak localization correction to the Drude conductivity from the intervalley scattering. For the anisotropic impurities, the above cancelation is removed, we find the approximative quantum interference conductivity in the weak anisotropy case. The contributions from the chiral anomaly and classical Lorentz force are also discussed. Our work reveals some intriguing and detectable transport signatures of the novel spin-1 chiral fermions.

Localization effect in single crystal of RuAs_(2)

We report the magnetotransport and thermal properties of RuAs_(2) single crystal.RuAs_(2) exhibits semiconductor behavior and localization effect.The crossover from normal state to diffusive transport in the weak localization(WL)state and then to variable range hopping(VRH)transport in the strong localization state has been observed.The transitions can be reflected in the measurement of resistivity and Seebeck coefficient.Negative magnetoresistance(NMR)emerges with the appearance of localization effect and is gradually suppressed in high magnetic field.The temperature dependent phase coherence length extracted from the fittings of NMR also indicates the transition from WL to VRH.The measurement of Hall effect reveals an anomaly of temperature dependent carrier concentration caused by localization effect.Our findings show that RuAs_(2) is a suitable platform to study the localized state.

GLOBAL EXISTENCE FOR THE NONHOMOGENEOUS QUASILINEAR WAVE EQUATION WITH A LOCALIZED WEAKLY NONLINEAR DISSIPATION IN EXTERIOR DOMAINS

It is proved that the global existence for the nonhomogeneous quasilinear wave equation with a localized weakly nonlinear dissipation in exterior domains.

Enhancing action discrimination via category-specific frame clustering for weakly-supervised temporal action localization

Temporal action localization (TAL) is a task of detecting the start and end timestamps of action instances and classifying them in an untrimmed video. As the number of action categories per video increases, existing weakly-supervised TAL (W-TAL) methods with only video-level labels cannot provide sufficient supervision. Single-frame supervision has attracted the interest of researchers. Existing paradigms model single-frame annotations from the perspective of video snippet sequences, neglect action discrimination of annotated frames, and do not pay sufficient attention to their correlations in the same category. Considering a category, the annotated frames exhibit distinctive appearance characteristics or clear action patterns.Thus, a novel method to enhance action discrimination via category-specific frame clustering for W-TAL is proposed. Specifically,the K-means clustering algorithm is employed to aggregate the annotated discriminative frames of the same category, which are regarded as exemplars to exhibit the characteristics of the action category. Then, the class activation scores are obtained by calculating the similarities between a frame and exemplars of various categories. Category-specific representation modeling can provide complimentary guidance to snippet sequence modeling in the mainline. As a result, a convex combination fusion mechanism is presented for annotated frames and snippet sequences to enhance the consistency properties of action discrimination,which can generate a robust class activation sequence for precise action classification and localization. Due to the supplementary guidance of action discriminative enhancement for video snippet sequences, our method outperforms existing single-frame annotation based methods. Experiments conducted on three datasets (THUMOS14, GTEA, and BEOID) show that our method achieves high localization performance compared with state-of-the-art methods.

Weakly Supervised Object Localization with Background Suppression Erasing for Art Authentication and Copyright Protection

The problem of art forgery and infringement is becoming increasingly prominent,since diverse self-media contents with all kinds of art pieces are released on the Internet every day.For art paintings,object detection and localization provide an efficient and ef-fective means of art authentication and copyright protection.However,the acquisition of a precise detector requires large amounts of ex-pensive pixel-level annotations.To alleviate this,we propose a novel weakly supervised object localization(WSOL)with background su-perposition erasing(BSE),which recognizes objects with inexpensive image-level labels.First,integrated adversarial erasing(IAE)for vanilla convolutional neural network(CNN)dropouts the most discriminative region by leveraging high-level semantic information.Second,a background suppression module(BSM)limits the activation area of the IAE to the object region through a self-guidance mechanism.Finally,in the inference phase,we utilize the refined importance map(RIM)of middle features to obtain class-agnostic loc-alization results.Extensive experiments are conducted on paintings,CUB-200-2011 and ILSVRC to validate the effectiveness of our BSE.

A NOTE IN APPROXIMATIVE COMPACTNESS AND MIDPOINT LOCALLY K-UNIFORM ROTUNDITY IN BANACH SPACES

In this article, we prove the following results： （1） A Banach space X is weak midpoint locally k-uniformly rotund if and only if every closed ball of X is an approximatively weakly compact k-Chebyshev set; （2） A Banach space X is midpoint locally k-uniformly rotund if and only if every closed ball of X is an approximatively compact k-Chebyshev set.

Generalized constrained multiobjective games in locally FC-uniform spaces

A new class of generalized constrained multiobjective games is introduced and studied in locally FC-uniform spaces without convexity structure where the number of players may be finite or infinite and all payoff functions get their values in an infinite-dimensional space. By using a Himmelberg type fixed point theorem in locally FC-uniform spaces due to author, some existence theorems of weak Paxeto equilibria for the generalized constrained multiobjective games are established in locally FC-uniform spaces. These theorems improve, unify and generalize the corresponding results in recent literatures.

Locally Asymptotic-norming Property and Kadec Property

In this paper we study the three new asymptotic-norming properties which are called locally asymptotic-norming property k,k=Ⅰ, Ⅱ,Ⅲ, and discuss the relationship between the locally asymptotic-norming property and the Kadec Property.

Discrete modulational instability and bright localized spin wave modes in easy-axis weak ferromagnetic spin chains involving the next-nearest-neighbor coupling

We report a theoretical work on the properties of modulational instability and bright type nonlinear localized modes in one-dimensional easy-axis weak ferromagnetic spin lattices involving next-nearest-neighbor couplings.With a linear stability analysis, we calculate the growth rates of the modulational instability, and plot the instability regions.When the strength of the next-nearest-neighbor coupling is large enough, two new asymmetric modulational instability regions appear near the boundary of the first Brillouin zone.Furthermore, analytical forms of the bright nonlinear localized modes are constructed by means of a quasi-discreteness approach.The influence of the next-nearest-neighbor coupling on the Brillouin zone center mode and boundary mode are discussed.In particular, we discover a reversal phenomenon of the propagation direction of the Brillouin zone boundary mode.

LOCAL REGULARITY CRITERIA OF A SUITABLE WEAK SOLUTION TO MHD EQUATIONS

We present a regularity condition of a suitable weak solution to the MHD equations in three dimensional space with slip boundary conditions for a velocity and magnetic vector fields. More precisely, we prove a suitable weak solution are HSlder continuous near boundary provided that the scaled mixed Lx,t^p,q-norm of the velocity vector field with 3/p ＋ 2/q 〈 2, 2 〈 q 〈 ∞ is sufficiently small near the boundary. Also, we will investigate that for this 3 2〈3 solution U ∈ Lx,t^p,q with 1 〈 3＋p ＋2/q＋≤3/2, 3 〈 p 〈 ∞, the Hausdorff dimension of its singular set is no greater than max{p, q}（3/q＋2/q- 1）.

LEGAN:一种新的暗弱光照图像增强算法

针对暗弱光照图像所存在的亮度、对比度、信噪比低,以及噪声污染大等问题,提出了一种新的暗弱光照图像增强算法LEGAN。该算法将图像输入至所提伽马曲线估计网络求得包含伽马参数的特征图,再经过LEB模块增强亮度,并通过级联LEB的方式迭代增强结果。采用基于PatchGAN的全局-局部判别器结构来提高图像分辨率和恢复图像细节。通过引入感知损失来限制真实标签和输出结果之间的差距,利用照明平滑度损失保持相邻像素之间的单调性关系,同时结合空间一致性损失来增强图像的空间相关性。实验结果表明,相比于现今大多数主流增强算法,该算法的细节还原度相对较高,且能有效避免增强后的图像出现局部亮度不佳等问题。

局部特征引导标签平滑与优化的井下弱特征人员重识别

煤矿井下低照度、强光扰、高粉尘等环境条件,以及井下人员服装的相似性和脸部落煤现象,导致井下弱特征人员重识别困难。现有人员重识别方法仅提取全局特征,未充分考虑局部特征,使得井下人员重识别准确率较低。针对上述问题,提出了一种局部特征引导标签平滑与优化的井下弱特征人员重识别方法。该方法首先通过卷积神经网络提取井下人员图像的全局特征与局部特征;然后利用k最近邻相似性计算全局特征和局部特征的互补性得分,来衡量全局特征和局部特征的相似程度;最后根据特征互补性得分对局部特征进行标签平滑及对全局特征进行标签优化,即动态调整每个局部特征的权重,以改进每个局部特征的标签,并对局部特征的预测结果进行汇总,利用更可靠的信息来完善标签以作为全局特征的标签,从而减少图像噪声并增强特征识别能力。实验结果表明,该方法在公开数据集和包含井下人员图像的自建数据集上的平均精度均值(mAP)、第一匹配正确率(Rank-1)和平均逆置负样本惩罚率(mINP)总体优于主流人员重识别方法,具有良好的泛化性和鲁棒性,能有效实现井下弱特征人员重识别。

Acquiring Weak Annotations for Tumor Localization in Temporal and Volumetric Data

Creating large-scale and well-annotated datasets to train AI algorithms is crucial for automated tumor detection and localization.However,with limited resources,it is challenging to determine the best type of annotations when annotating massive amounts of unlabeled data.To address this issue,we focus on polyps in colonoscopy videos and pancreatic tumors in abdominal CT scans;Both applications require significant effort and time for pixel-wise annotation due to the high dimensional nature of the data,involving either temporary or spatial dimensions.In this paper,we develop a new annotation strategy,termed Drag&Drop,which simplifies the annotation process to drag and drop.This annotation strategy is more efficient,particularly for temporal and volumetric imaging,than other types of weak annotations,such as per-pixel,bounding boxes,scribbles,ellipses and points.Furthermore,to exploit our Drag&Drop annotations,we develop a novel weakly supervised learning method based on the watershed algorithm.Experimental results show that our method achieves better detection and localization performance than alternative weak annotations and,more importantly,achieves similar performance to that trained on detailed per-pixel annotations.Interestingly,we find that,with limited resources,allocating weak annotations from a diverse patient population can foster models more robust to unseen images than allocating per-pixel annotations for a small set of images.In summary,this research proposes an efficient annotation strategy for tumor detection and localization that is less accurate than per-pixel annotations but useful for creating large-scale datasets for screening tumors in various medical modalities.

弱光照图像的模糊细节自调节增强测试与仿真

由于自然光具有较强的随机性,低光照条件下相机采集的图像较为模糊,难以获取细节信息。为此,提出弱光照图像模糊细节自调节增强方法。在非局部均衡滤波算法中引入相似度阈值函数,去除弱光照模糊图像噪声,采用分数阶全变差模型和非局部全变差模型,建立弱光照模糊图像去模糊模型,对模糊图像去模糊处理,将预处理后弱光照图像输入多尺度融合卷积神经网络模型,通过全局路径和局部路径提取并融合图像特征,实现弱光照图像模糊细节自调节增强。实验结果表明,所提方法在合成图像增强中均方误差更小、结构相似度和峰值信噪比更高,在真实图像增强中自然图像质量评价度量和对比度增益更高、熵值更接近于8,图像处理时间更短,仅为0.745ms。

软弱局部透水地层注浆止水盾尾刷更换技术

在城市轨道交通建设中,由于长距离、小半径盾构掘进情况越来越多,导致盾尾刷因长时间受力或受力不均而磨损,降低或失去密封性,需对其及时进行更换。本研究以苏州轨道交通8号线虎殿路站—虎丘湿地公园站出入场线区间更换盾尾刷为背景,基于盾尾刷更换各种止水方式比选分析,结合该工程位于软弱局部透水地层特点,提出并实施了一种多方式注浆止水的盾尾刷更换方法。即在软弱局部透水地层中,通过在盾尾注入聚氨酯、惰性浆液、双浆液,以及通过盾体径向注入惰性浆液,对盾尾前后地下水进行有效封堵,再通过拆卸一环管片进行第一道盾尾刷的拆卸与更换,更换期间实测表明地表累积沉降与日沉降均满足控制要求,注浆加固后打开观测孔止水效果良好,仅耗时14 d便恢复掘进。本研究提出的软弱局部透水地层注浆止水的盾尾刷更换成套工艺与方法取得很好的实施效果,可为今后类似工程提供参考。

当理性遇上知识:应急场景下决策模式与逻辑转换——以W县应急过程为研究对象

在常规科层决策中,外部知识辅助能够提升决策者理性,提升决策科学。但在危机决策中,外部知识输入可能会对决策者造成决策压力。在“理性—知识”分析框架下,作为决策者存在差异化的决策模式选择。通过整体性个案研究显示,当决策者身处强理性和弱理性状态,会与专业知识及地方性知识产生不同交互意义,生成保守决策、即兴决策、推拉决策、专断决策四种决策模式。研究发现,在不同危机场景中,决策者在理性选择、价值导向和避责动机驱动下会发生决策模式转化来回应动态危机。

强噪声中检测微弱目标信号特征的量子信号处理算法

随着噪声功率的增强,微弱目标信号的特征受噪声污染变得模糊且难以区分,导致微弱信号检测算法失效,提出一种可以保护目标信号特征的量子信号处理方法——局域半经典信号分析算法。详细介绍了算法实现量子化的原理和在量子域中保护目标信号特征的性质;给出算法步骤以及重要参数的计算方式;将所提算法与奇异值分解、小波阈值降噪算法结合进行了仿真分析和实验验证。结果表明,所提算法保护目标信号特征的能力可以帮助降噪算法检测极低信噪比的微弱信号,与其他方法结合可极大改善信噪比,准确提取信噪比为-30 dB的微弱目标信号,算法性能优越。

Caputo型时间分数阶变系数扩散方程的局部间断Galerkin方法

提出一种带有Caputo导数的时间分数阶变系数扩散方程的数值解法.方程的解在初始时刻附近通常具有弱正则性,采用非一致网格上的L1公式离散时间分数阶导数,并使用局部间断Galerkin(local discontinuous Galerkin,LDG)方法离散空间导数,给出方程的全离散格式.基于离散的分数阶Gronwall不等式,证明了格式的数值稳定性和收敛性,且所得结果关于α是鲁棒的,即当α→1^(-)时不会发生爆破.最后,通过数值算例验证理论分析的结果.

四阶线性方程极弱局部间断Galerkin法傅里叶分析

主要研究了四阶线性方程极弱局部间断Galerkin方法的傅里叶误差分析问题。首先,给出四阶线性方程的极弱局部间断Galerkin空间离散格式,并在周期边界条件及一致网格的条件下将离散格式表示为差分形式,然后,在k=2的情况下,利用傅里叶分析方法分析其稳定性及其误差估计问题,最后,利用数值实验,分别对得到的结果进行验证。

社区间“弱竞争”关系的生成逻辑及优化路径

府际关系是国家治理的核心内容,也是学术研究的焦点主题。城市社区横向关系与地方政府横向竞争行为类似,但在资源获取、排名竞赛、模式创新等横向竞争强度上,呈现“弱竞争”特点。通过对Q市L区J街道多个平行社区的实践考察,并和地方政府竞争进行比较研究,发现社区间“弱竞争”表现在财政资源、治理创新以及考核排名三方面,形塑于街居间特有的纵向关系,具有“弱压力—弱激励”的属性特征。城市社区间关系形态及其生成逻辑的普遍性知识为基层社区治理研究提供了一个组织关系的新视角,未来基层政府应不断探索街居互动关系,以合作治理、良性竞争实现基层善治。