BRIDGE: Byzantine-resilient Decentralized Gradient Descent

Decentralized optimization techniques are increasingly being used to learn machine learning models from data distributed over multiple locations without gathering the data at any one location. Unfortunately, methods that are designed for faultless networks typically fail in the presence of node failures. In particular, Byzantine failures---corresponding to the scenario in which faulty/compromised nodes are allowed to arbitrarily deviate from an agreed-upon protocol---are the hardest to safeguard against in decentralized settings. This paper introduces a Byzantine-resilient decentralized gradient descent (BRIDGE) method for decentralized learning that, when compared to existing works, is more efficient and scalable in higher-dimensional settings and that is deployable in networks having topologies that go beyond the star topology. The main contributions of this work include theoretical analysis of BRIDGE for strongly convex learning objectives and numerical experiments demonstrating the efficacy of BRIDGE for both convex and nonconvex learning tasks.Comment: 18 pages, 1 figure, 1 table; preprint of a conference pape

A Meta-Learning Based Gradient Descent Algorithm for MU-MIMO Beamforming

Multi-user multiple-input multiple-output (MU-MIMO) beamforming design is typically formulated as a non-convex weighted sum rate (WSR) maximization problem that is known to be NP-hard. This problem is solved either by iterative algorithms, which suffer from slow convergence, or more recently by using deep learning tools, which require time-consuming pre-training process. In this paper, we propose a low-complexity meta-learning based gradient descent algorithm. A meta network with lightweight architecture is applied to learn an adaptive gradient descent update rule to directly optimize the beamformer. This lightweight network is trained during the iterative optimization process, which we refer to as \emph{training while solving}, which removes both the training process and the data-dependency of existing deep learning based solutions.Extensive simulations show that the proposed method achieves superior WSR performance compared to existing learning-based approaches as well as the conventional WMMSE algorithm, while enjoying much lower computational load

A Learning Aided Flexible Gradient Descent Approach to MISO Beamforming

This paper proposes a learning aided gradient descent (LAGD) algorithm to solve the weighted sum rate (WSR) maximization problem for multiple-input single-output (MISO) beamforming. The proposed LAGD algorithm directly optimizes the transmit precoder through implicit gradient descent based iterations, at each of which the optimization strategy is determined by a neural network, and thus, is dynamic and adaptive. At each instance of the problem, this network is initialized randomly, and updated throughout the iterative solution process. Therefore, the LAGD algorithm can be implemented at any signal-to-noise ratio (SNR) and for arbitrary antenna/user numbers, does not require labelled data or training prior to deployment. Numerical results show that the LAGD algorithm can outperform of the well-known WMMSE algorithm as well as other learning-based solutions with a modest computational complexity. Our code is available at https://github.com/XiaGroup/LAGD

Increased expression of MMP9 is correlated with poor prognosis of nasopharyngeal carcinoma

<p>Abstract</p> <p>Introduction</p> <p>The aim of the present study was to analyze the expression of matrix metalloproteinase 9 (<it>MMP9</it>) in nasopharyngeal carcinoma (NPC) and its correlation with clinicopathologic features, including the survival of patients with NPC.</p> <p>Methods</p> <p>Using real-time PCR, we detected the mRNA expression of <it>MMP9 </it>in normal nasopharyngeal tissues and nasopharyngeal carcinoma (NPC) tissues. Using immunohistochemistry analysis, we analyzed <it>MMP9 </it>protein expression in clinicopathologically characterized 164 NPC cases (116 male and 48 female) with age ranging from 17 to 80 years (median = 48.4 years) and 32 normal nasopharyngeal tissues. Cases with greater than or equal to 6 and less than 6 of the score value of cytoplasmic <it>MMP9 </it>immunostaining were regarded as high expression and low expression, respectively. The relationship between the expression levels of <it>MMP9 </it>and clinical features was analyzed.</p> <p>Results</p> <p>The expression level of <it>MMP9 </it>mRNA was markedly greater in NPC tissues than that in the nasopharyngeal tissues. Immunohistochemical analysis revealed that the protein expression of <it>MMP9 </it>detected in NPC tissues was higher than that in the nasopharyngeal tissues (<it>P </it>= 0.004). In addition, high levels of <it>MMP9 </it>protein were positively correlated with the status of lymph node metastasis (N classification) (<it>P </it>= 0.002) and clinical stage (<it>P </it>< 0.001) of NPC patients. Patients with higher <it>MMP9 </it>expression had a significantly shorter overall survival time than did patients with low <it>MMP9 </it>expression. Multivariate analysis suggested that the level of <it>MMP9 </it>expression was an independent prognostic indicator (<it>P </it>= 0.008) for the survival of patients with NPC.</p> <p>Conclusion</p> <p>High level of <it>MMP9 </it>expression is a potential unfavorable prognostic factor for patients with NPC.</p

Improving the performance of low-frequency magnetic energy harvesters using an internal magnetic-coupled mechanism

In this study, we present a novel low-frequency magnetic field energy harvester (EH) employing beryllium bronze/Pb(Zr,Ti)O3 ceramic composited dual-beam structures with tip magnets attached to the inner and outer beams. This design incorporates the internal magnetic-coupled (IMC) effect, resulting in significantly enhanced coupling ability and a wide bandwidth. The validity of the IMC mechanism is confirmed through theoretical formulas and numerical simulations. By leveraging the IMC condition, the EH achieves an expanded bandwidth, which increases from 22 to 43 Hz. Moreover, the total output voltages at the inherent resonance and internal resonance are boosted by 15.4% and 32%, respectively. The performance of the IMC-EH can be further improved by increasing the number of the endmost magnets. Experimental investigations reveal that the IMC-EH generates a maximum RMS output power density of 56.25 μW Oe−2 cm−3, surpassing existing magnetically coupled piezoelectric energy harvesters. Remarkably, even under an ambient magnetic field as low as 1 Oe, the proposed IMC-EH still yields a total output power of 185 μW, sufficient to continuously power 26 LEDs in real time. This demonstrates its potential as a promising solution for low-power consumption small electronics. Furthermore, the implications of this work extend beyond its immediate benefits, as it inspires the design of future self-powered wireless sensor networks in the context of the Internet of Things.</jats:p

Meeting-Merging-Mission: A Multi-robot Coordinate Framework for Large-Scale Communication-Limited Exploration

This letter presents a complete framework Meeting-Merging-Mission for multi-robot exploration under communication restriction. Considering communication is limited in both bandwidth and range in the real world, we propose a lightweight environment presentation method and an efficient cooperative exploration strategy. For lower bandwidth, each robot utilizes specific polytopes to maintains free space and super frontier information (SFI) as the source for exploration decision-making. To reduce repeated exploration, we develop a mission-based protocol that drives robots to share collected information in stable rendezvous. We also design a complete path planning scheme for both centralized and decentralized cases. To validate that our framework is practical and generic, we present an extensive benchmark and deploy our system into multi-UGV and multi-UAV platforms

SiO2 nanoparticles induce cytotoxicity and protein expression alteration in HaCaT cells

<p>Abstract</p> <p>Background</p> <p>Nanometer silicon dioxide (nano-SiO₂) has a wide variety of applications in material sciences, engineering and medicine; however, the potential cell biological and proteomic effects of nano-SiO₂exposure and the toxic mechanisms remain far from clear.</p> <p>Results</p> <p>Here, we evaluated the effects of amorphous nano-SiO₂(15-nm, 30-nm SiO₂). on cellular viability, cell cycle, apoptosis and protein expression in HaCaT cells by using biochemical and morphological analysis, two-dimensional differential gel electrophoresis (2D-DIGE) as well as mass spectrometry (MS). We found that the cellular viability of HaCaT cells was significantly decreased in a dose-dependent manner after the treatment of nano-SiO₂and micro-sized SiO₂particles. The IC₅₀value (50% concentration of inhibition) was associated with the size of SiO₂particles. Exposure to nano-SiO₂and micro-sized SiO₂particles also induced apoptosis in HaCaT cells in a dose-dependent manner. Furthermore, the smaller SiO₂particle size was, the higher apoptotic rate the cells underwent. The proteomic analysis revealed that 16 differentially expressed proteins were induced by SiO₂exposure, and that the expression levels of the differentially expressed proteins were associated with the particle size. The 16 proteins were identified by MALDI-TOF-TOF-MS analysis and could be classified into 5 categories according to their functions. They include oxidative stress-associated proteins; cytoskeleton-associated proteins; molecular chaperones; energy metabolism-associated proteins; apoptosis and tumor-associated proteins.</p> <p>Conclusions</p> <p>These results showed that nano-SiO₂exposure exerted toxic effects and altered protein expression in HaCaT cells. The data indicated the alterations of the proteins, such as the proteins associated with oxidative stress and apoptosis, could be involved in the toxic mechanisms of nano-SiO₂exposure.</p

Fracture Analysis of Brittle Materials Based on Nonlinear FEM and Application in Arch Dam with Fractures

Current fracture analysis models based on fracture mechanics or continuum damage mechanics are still limited in the application to three-dimensional structure. Based on deformation reinforcement theory coming from elastoperfect plastic theory, unbalanced force is proposed to predict initiation and propagation of cracks. Unbalanced force is the driving force of time-dependent deformation according to Perzyna’s viscoplasticity theory. It is also related to the damage driving force in viscoplastic damage model. The distribution of unbalanced force indicates cracks initiation area, while its direction predicts possible cracks propagation path. Uniaxial compression test of precrack specimen is performed as verification to this method. The trend and distribution of cracks are in good agreement with numerical results, proving that unbalanced force is feasible and effective for fracture analysis. The method is applied in fracture analysis of Xiaowan high arch dam, which is subjected to some cracks in dam due to the temperature control program. The results show that the deformation and stress of cracks and the stress characteristics of dam are insensitive to grouting of cracks. The existing cracks are stable and dam heel is still the most possible cracking position