Boosting Adversarial Attack with Similar Target

Deep neural networks are vulnerable to adversarial examples, posing a threat to the models' applications and raising security concerns. An intriguing property of adversarial examples is their strong transferability. Several methods have been proposed to enhance transferability, including ensemble attacks which have demonstrated their efficacy. However, prior approaches simply average logits, probabilities, or losses for model ensembling, lacking a comprehensive analysis of how and why model ensembling significantly improves transferability. In this paper, we propose a similar targeted attack method named Similar Target~(ST). By promoting cosine similarity between the gradients of each model, our method regularizes the optimization direction to simultaneously attack all surrogate models. This strategy has been proven to enhance generalization ability. Experimental results on ImageNet validate the effectiveness of our approach in improving adversarial transferability. Our method outperforms state-of-the-art attackers on 18 discriminative classifiers and adversarially trained models

Role Engine Implementation for a Continuous and Collaborative Multi-Robot System

In situations involving teams of diverse robots, assigning appropriate roles to each robot and evaluating their performance is crucial. These roles define the specific characteristics of a robot within a given context. The stream actions exhibited by a robot based on its assigned role are referred to as the process role. Our research addresses the depiction of process roles using a multivariate probabilistic function. The main aim of this study is to develop a role engine for collaborative multi-robot systems and optimize the behavior of the robots. The role engine is designed to assign suitable roles to each robot, generate approximately optimal process roles, update them on time, and identify instances of robot malfunction or trigger replanning when necessary. The environment considered is dynamic, involving obstacles and other agents. The role engine operates hybrid, with central initiation and decentralized action, and assigns unlabeled roles to agents. We employ the Gaussian Process (GP) inference method to optimize process roles based on local constraints and constraints related to other agents. Furthermore, we propose an innovative approach that utilizes the environment's skeleton to address initialization and feasibility evaluation challenges. We successfully demonstrated the proposed approach's feasibility, and efficiency through simulation studies and real-world experiments involving diverse mobile robots.Comment: 10 pages, 18 figures, summited in IEEE Transactions on Systems, Man and Cybernetics(T-SMC

Numerical scrutinization of heat transfer subject to physical quantities through bioconvective nanofluid flow via stretching permeable surfaces

Background: The mechanics of heat and mass transfer via nanofluid flow across many media are currently being discussed. “Nanofluids” are fluids that include highly heat-conductive nanoparticles, and they are essential for resolving engineering problems. Under the effects of activation energy, thermal radiation, and motile microorganisms, the process of heat and mass transfer through steady nanofluid flow crosses over stretched surfaces in this scenario.Methodology: For mathematical evaluation, the system of partial differential equations (PDEs) is used to describe this physical framework. By introducing suitable similarity variables with a set of boundary conditions, this mathematical system of PDEs has become a system of ordinary differential equations (ODEs). To obtain numerical results, the MATLAB built-in program “bvp4c” is used to solve the system of first-order equations.Results: In the findings and discussion section, the resulting outcomes are thoroughly examined and visually shown. The flow rate in these systems increases due to the erratic movement of microorganisms. The graphical representation shows the impacts of involving physical factors on the microorganism, thermal, concentration, and momentum profiles. Variations/changes in these profiles can be observed by adjusting the parametric values, as depicted in the graphs. Consequently, thermal transport is boosted by 25%. Additionally, the skin friction, Nusselt, Sherwood, and microbe density numbers are determined numerically. The findings demonstrate that increasing the magnetic field parameter causes the velocity profile to decrease, increasing the radiation parameter leads to an increase in temperature description, and increasing the Lewis number causes the microorganism profile’s transport rate to decrease

Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer

Data privacy and long-tailed distribution are the norms rather than the exception in many real-world tasks. This paper investigates a federated long-tailed learning (Fed-LT) task in which each client holds a locally heterogeneous dataset; if the datasets can be globally aggregated, they jointly exhibit a long-tailed distribution. Under such a setting, existing federated optimization and/or centralized long-tailed learning methods hardly apply due to challenges in (a) characterizing the global long-tailed distribution under privacy constraints and (b) adjusting the local learning strategy to cope with the head-tail imbalance. In response, we propose a method termed $\texttt{Fed-GraB}$, comprised of a Self-adjusting Gradient Balancer (SGB) module that re-weights clients' gradients in a closed-loop manner, based on the feedback of global long-tailed distribution evaluated by a Direct Prior Analyzer (DPA) module. Using $\texttt{Fed-GraB}$, clients can effectively alleviate the distribution drift caused by data heterogeneity during the model training process and obtain a global model with better performance on the minority classes while maintaining the performance of the majority classes. Extensive experiments demonstrate that $\texttt{Fed-GraB}$ achieves state-of-the-art performance on representative datasets such as CIFAR-10-LT, CIFAR-100-LT, ImageNet-LT, and iNaturalist.Comment: Accepted by NeurIPS 202

Can a "pre-worn" bearing surface geometry reduce the wear of metal-on-metal hip replacements? – A numerical wear simulation study

Total Hip Replacement (THR) is generally a highly successful treatment for late stage hip joint diseases and wear, however, wear continues to be one of the major causes of metal-on-metal THR's failure. Hip replacements typically experience a two-stage wear; a higher initial wear rate in the beginning followed by a lower steady-state one with the surface profile changed. This alludes to the potential use of a cup with a non-spherical interior cavity with an initial geometry similar to a worn surface which may benefit from lower wear rate. In this paper wear is numerically simulated with a cup having a non-spherical geometry inspired by the initial stage of wear. A wear model was recently developed by the authors for the THR, which considered the lubricated contact in both elastohydrodynamic lubrication (EHL) and mixed lubrication regime, rather than a dry contact used in most of other studies of wear modelling in the academic literature. In this study the wear model has been updated by introducing the 'λ ratio' (the ratio of film thickness to surface roughness) and addressing the non-Newtonian shear-thinning properties of the synovial fluid. This wear model was able to describe the non-linear wear evolution process due to the change of worn profiles. Firstly the wear of a spherical hip joint was simulated until a steady-state wear rate is achieved. Then a non-spherical joint was proposed in which the cup bearing geometry was generated by the previously predicted worn profile from the spherical joint. At last the wear of this "pre-worn" hip bearing was simulated and compared to the spherical one. Approximately 40% reduction in the steady-state wear rate and 50% in the total accumulated wear has been observed in the non-spherical hip joint. This study presented a full numerical analysis of the relationship between lubrication, wear reduction and the geometry change, and quantitatively suggested the optimal geometry to reduce running-in wear

Ca2+ Permeable AMPA Receptor Induced Long-Term Potentiation Requires PI3/MAP Kinases but Not Ca/CaM-Dependent Kinase II

Ca2+ influx via GluR2-lacking Ca2+-permeable AMPA glutamate receptors (CP-AMPARs) can trigger changes in synaptic efficacy in both interneurons and principle neurons, but the underlying mechanisms remain unknown. We took advantage of genetically altered mice with no or reduced GluR2, thus allowing the expression of synaptic CP-AMPARs, to investigate the molecular signaling process during CP-AMPAR-induced synaptic plasticity at CA1 synapses in the hippocampus. Utilizing electrophysiological techniques, we demonstrated that these receptors were capable of inducing numerous forms of long-term potentiation (referred to as CP-AMPAR dependent LTP) through a number of different induction protocols, including high-frequency stimulation (HFS) and theta-burst stimulation (TBS). This included a previously undemonstrated form of protein-synthesis dependent late-LTP (L-LTP) at CA1 synapses that is NMDA-receptor independent. This form of plasticity was completely blocked by the selective CP-AMPAR inhibitor IEM-1460, and found to be dependent on postsynaptic Ca2+ ions through calcium chelator (BAPTA) studies. Surprisingly, Ca/CaM-dependent kinase II (CaMKII), the key protein kinase that is indispensable for NMDA-receptor dependent LTP at CA1 synapses appeared to be not required for the induction of CP-AMPAR dependent LTP due to the lack of effect of two separate pharmacological inhibitors (KN-62 and staurosporine) on this form of potentiation. Both KN-62 and staurosporine strongly inhibited NMDA-receptor dependent LTP in control studies. In contrast, inhibitors for PI3-kinase (LY294002 and wortmannin) or the MAPK cascade (PD98059 and U0126) significantly attenuated this CP-AMPAR-dependent LTP. Similarly, postsynaptic infusion of tetanus toxin (TeTx) light chain, an inhibitor of exocytosis, also had a significant inhibitory effect on this form of LTP. These results suggest that distinct synaptic signaling underlies GluR2-lacking CP-AMPAR-dependent LTP, and reinforces the recent notions that CP-AMPARs are important facilitators of synaptic plasticity in the brain

Longitudinal white-matter abnormalities in sports-related concussion: A diffusion MRI study

Objective To study longitudinal recovery trajectories of white matter after sports-related concussion (SRC) by performing diffusion tensor imaging (DTI) on collegiate athletes who sustained SRC. Methods Collegiate athletes (n = 219, 82 concussed athletes, 68 contact-sport controls, and 69 non–contact-sport controls) were included from the Concussion Assessment, Research and Education Consortium. The participants completed clinical assessments and DTI at 4 time points: 24 to 48 hours after injury, asymptomatic state, 7 days after return-to-play, and 6 months after injury. Tract-based spatial statistics was used to investigate group differences in DTI metrics and to identify white-matter areas with persistent abnormalities. Generalized linear mixed models were used to study longitudinal changes and associations between outcome measures and DTI metrics. Cox proportional hazards model was used to study effects of white-matter abnormalities on recovery time. Results In the white matter of concussed athletes, DTI-derived mean diffusivity was significantly higher than in the controls at 24 to 48 hours after injury and beyond the point when the concussed athletes became asymptomatic. While the extent of affected white matter decreased over time, part of the corpus callosum had persistent group differences across all the time points. Furthermore, greater elevation of mean diffusivity at acute concussion was associated with worse clinical outcome measures (i.e., Brief Symptom Inventory scores and symptom severity scores) and prolonged recovery time. No significant differences in DTI metrics were observed between the contact-sport and non–contact-sport controls. Conclusions Changes in white matter were evident after SRC at 6 months after injury but were not observed in contact-sport exposure. Furthermore, the persistent white-matter abnormalities were associated with clinical outcomes and delayed recovery tim