The Correspondence between Convergence Peaks from Weak Lensing and Massive Dark Matter Haloes

The convergence peaks, constructed from galaxy shape measurement in weak lensing, is a powerful probe of cosmology as the peaks can be connected with the underlined dark matter haloes. However the capability of convergence peak statistic is affected by the noise in galaxy shape measurement, signal to noise ratio as well as the contribution from the projected mass distribution from the large-scale structures along the line of sight (LOS). In this paper we use the ray-tracing simulation on a curved sky to investigate the correspondence between the convergence peak and the dark matter haloes at the LOS. We find that, in case of no noise and for source galaxies at $z_{\rm s}=1$, more than $65\%$ peaks with $\text{SNR} \geq 3$ (signal to noise ratio) are related to more than one massive haloes with mass larger than $10^{13} {\rm M}_{\odot}$. Those massive haloes contribute $87.2\%$ to high peaks ($\text{SNR} \geq 5$) with the remaining contributions are from the large-scale structures. On the other hand, the peaks distribution is skewed by the noise in galaxy shape measurement, especially for lower SNR peaks. In the noisy field where the shape noise is modelled as a Gaussian distribution, about $60\%$ high peaks ($\text{SNR} \geq 5$) are true peaks and the fraction decreases to $20\%$ for lower peaks ($3 \leq \text{SNR} < 5$). Furthermore, we find that high peaks ($\text{SNR} \geq 5$) are dominated by very massive haloes larger than $10^{14} {\rm M}_{\odot}$.Comment: 13 pages, 11 figures, 4 tables, accepted for publication in MNRAS. Our mock galaxy catalog is available upon request by email to the author ([email protected]

Mechanism of Polarization Fatigue in BiFeO3: the Role of Schottky Barrier

By using piezoelectric force microscopy and scanning Kelvin probe microscopy, we have investigated the domain evolution and space charge distribution in planar BiFeO3 capacitors with different electrodes. It is observed that charge injection at the film/electrode interface leads to domain pinning and polarization fatigue in BiFeO3. Furthermore, the Schottky barrier at the interface is crucial for the charge injection process. Lowering the Schottky barrier by using low work function metals as the electrodes can also improve the fatigue property of the device, similar to what oxide electrodes can achieve

Bidirectional Propagation for Cross-Modal 3D Object Detection

Recent works have revealed the superiority of feature-level fusion for cross-modal 3D object detection, where fine-grained feature propagation from 2D image pixels to 3D LiDAR points has been widely adopted for performance improvement. Still, the potential of heterogeneous feature propagation between 2D and 3D domains has not been fully explored. In this paper, in contrast to existing pixel-to-point feature propagation, we investigate an opposite point-to-pixel direction, allowing point-wise features to flow inversely into the 2D image branch. Thus, when jointly optimizing the 2D and 3D streams, the gradients back-propagated from the 2D image branch can boost the representation ability of the 3D backbone network working on LiDAR point clouds. Then, combining pixel-to-point and point-to-pixel information flow mechanisms, we construct an bidirectional feature propagation framework, dubbed BiProDet. In addition to the architectural design, we also propose normalized local coordinates map estimation, a new 2D auxiliary task for the training of the 2D image branch, which facilitates learning local spatial-aware features from the image modality and implicitly enhances the overall 3D detection performance. Extensive experiments and ablation studies validate the effectiveness of our method. Notably, we rank $\mathbf{1^{\mathrm{st}}}$ on the highly competitive KITTI benchmark on the cyclist class by the time of submission. The source code is available at https://github.com/Eaphan/BiProDet.Comment: Accepted by ICLR2023. Code is avaliable at https://github.com/Eaphan/BiProDe

AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices

In this work, we investigate the challenging problem of on-demand federated learning (FL) over heterogeneous edge devices with diverse resource constraints. We propose a cost-adjustable FL framework, named AnycostFL, that enables diverse edge devices to efficiently perform local updates under a wide range of efficiency constraints. To this end, we design the model shrinking to support local model training with elastic computation cost, and the gradient compression to allow parameter transmission with dynamic communication overhead. An enhanced parameter aggregation is conducted in an element-wise manner to improve the model performance. Focusing on AnycostFL, we further propose an optimization design to minimize the global training loss with personalized latency and energy constraints. By revealing the theoretical insights of the convergence analysis, personalized training strategies are deduced for different devices to match their locally available resources. Experiment results indicate that, when compared to the state-of-the-art efficient FL algorithms, our learning framework can reduce up to 1.9 times of the training latency and energy consumption for realizing a reasonable global testing accuracy. Moreover, the results also demonstrate that, our approach significantly improves the converged global accuracy.Comment: Accepted to IEEE INFOCOM 202

FAST: Fidelity-Adjustable Semantic Transmission over Heterogeneous Wireless Networks

In this work, we investigate the challenging problem of on-demand semantic communication over heterogeneous wireless networks. We propose a fidelity-adjustable semantic transmission framework (FAST) that empowers wireless devices to send data efficiently under different application scenarios and resource conditions. To this end, we first design a dynamic sub-model training scheme to learn the flexible semantic model, which enables edge devices to customize the transmission fidelity with different widths of the semantic model. After that, we focus on the FAST optimization problem to minimize the system energy consumption with latency and fidelity constraints. Following that, the optimal transmission strategies including the scaling factor of the semantic model, computing frequency, and transmitting power are derived for the devices. Experiment results indicate that, when compared to the baseline transmission schemes, the proposed framework can reduce up to one order of magnitude of the system energy consumption and data size for maintaining reasonable data fidelity.Comment: 6 pages, 4 figures. Accepted by ICC 202

Delay-dependent stabilization of stochastic interval delay systems with nonlinear disturbances

This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2007 Elsevier Ltd.In this paper, a delay-dependent approach is developed to deal with the robust stabilization problem for a class of stochastic time-delay interval systems with nonlinear disturbances. The system matrices are assumed to be uncertain within given intervals, the time delays appear in both the system states and the nonlinear disturbances, and the stochastic perturbation is in the form of a Brownian motion. The purpose of the addressed stochastic stabilization problem is to design a memoryless state feedback controller such that, for all admissible interval uncertainties and nonlinear disturbances, the closed-loop system is asymptotically stable in the mean square, where the stability criteria are dependent on the length of the time delay and therefore less conservative. By using Itô's differential formula and the Lyapunov stability theory, sufficient conditions are first derived for ensuring the stability of the stochastic interval delay systems. Then, the controller gain is characterized in terms of the solution to a delay-dependent linear matrix inequality (LMI), which can be easily solved by using available software packages. A numerical example is exploited to demonstrate the effectiveness of the proposed design procedure.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Nuffield Foundation of the UK under Grant NAL/00630/G, and the Alexander von Humboldt Foundation of Germany

A Review of Water Environmental Capacity Calculation

Water environmental capacity is an essential component of water environmental assessment and must be monitored and managed for economic, engineering, and human health reasons. Many efforts have been made to study methods for the calculation of water environmental capacity. This paper reviews available literature on water environmental capacity. The evolutionary history and application scenarios of major water quality models, and water environmental capacity calculation formulas are summarized. Through the analysis of calculation formulas for water environmental capacity, it is found that endogenous pollution factors influence the values of degradation coefficient K and retention coefficient R in water environmental capacity calculation though few studies consider such factors. Therefore, the quantification of endogenous pollution factors (particularly the rheological properties of bed sediments) is important and needs further study

THE MECHANICAL ANALYSIS OF HDPE NET CAGE BY TEST AND CALCULATION

To reduce the structural failure risk of net cages under extreme sea conditions, this study analysed the yield phenomenon under mooring constraints and excessive or long-term wave loads. The floating collar deforms by shear when a twisted 1 m for the 8-point type and 5 m for the four point type. The structural strength in the Z-vertical direction is one-fifth of that in the X-horizontal direction. The maximum deformation is mainly on the two ends of the cap ned pipes. The critical points of the guardrail may reach the yield stress when the wave height is 1.1 m, while the height of the floating pipe is 5 m. The float can be damaged more easily when there is torsion or shear deformation caused by irregular waves. The results provide guidelines for the optimised structural design of net cages, which by increasing the number of mooring points and cap neds as well as reducing the welding points and structural mutation points, can improve the ultimate bearing capacity and fatigue reliability of the cage float