Concurrence-Aware Long Short-Term Sub-Memories for Person-Person Action Recognition

Recently, Long Short-Term Memory (LSTM) has become a popular choice to model individual dynamics for single-person action recognition due to its ability of modeling the temporal information in various ranges of dynamic contexts. However, existing RNN models only focus on capturing the temporal dynamics of the person-person interactions by naively combining the activity dynamics of individuals or modeling them as a whole. This neglects the inter-related dynamics of how person-person interactions change over time. To this end, we propose a novel Concurrence-Aware Long Short-Term Sub-Memories (Co-LSTSM) to model the long-term inter-related dynamics between two interacting people on the bounding boxes covering people. Specifically, for each frame, two sub-memory units store individual motion information, while a concurrent LSTM unit selectively integrates and stores inter-related motion information between interacting people from these two sub-memory units via a new co-memory cell. Experimental results on the BIT and UT datasets show the superiority of Co-LSTSM compared with the state-of-the-art methods

Prox-DBRO-VR: A Unified Analysis on Decentralized Byzantine-Resilient Composite Stochastic Optimization with Variance Reduction and Non-Asymptotic Convergence Rates

Decentralized Byzantine-resilient stochastic gradient algorithms resolve efficiently large-scale optimization problems in adverse conditions, such as malfunctioning agents, software bugs, and cyber attacks. This paper targets on handling a class of generic composite optimization problems over multi-agent cyberphysical systems (CPSs), with the existence of an unknown number of Byzantine agents. Based on the proximal mapping method, two variance-reduced (VR) techniques, and a norm-penalized approximation strategy, we propose a decentralized Byzantine-resilient and proximal-gradient algorithmic framework, dubbed Prox-DBRO-VR, which achieves an optimization and control goal using only local computations and communications. To reduce asymptotically the variance generated by evaluating the noisy stochastic gradients, we incorporate two localized variance-reduced techniques (SAGA and LSVRG) into Prox-DBRO-VR, to design Prox-DBRO-SAGA and Prox-DBRO-LSVRG. Via analyzing the contraction relationships among the gradient-learning error, robust consensus condition, and optimal gap, the theoretical result demonstrates that both Prox-DBRO-SAGA and Prox-DBRO-LSVRG, with a well-designed constant (resp., decaying) step-size, converge linearly (resp., sub-linearly) inside an error ball around the optimal solution to the optimization problem under standard assumptions. The trade-offs between the convergence accuracy and the number of Byzantine agents in both linear and sub-linear cases are characterized. In simulation, the effectiveness and practicability of the proposed algorithms are manifested via resolving a sparse machine-learning problem over multi-agent CPSs under various Byzantine attacks.Comment: 14 pages, 0 figure

A New Mechanism for Primordial Black Hole Formation from QCD Axion

We present a novel mechanism for the primordial black hole (PBH) production within the QCD axion framework. We take the case where the Peccei-Quinn symmetry breaks during inflation, resulting in a $N_{\rm DW}=1$ string-wall network that re-enters horizon sufficiently late. Therefore, closed axion domain walls naturally arising in the network are sufficiently large to collapse into PBHs. Our numerical simulation shows that $0.8\%$ of the total wall area is in the form of closed walls. Notably, this fraction is independent of any axion parameters, as its determination is firmly grounded in the principles of percolation theory. In addition, the relic abundance of dark matter is accounted for by free axions from the collapse of open walls bounded by strings. This framework yields a calculated PBH fraction of dark matter as 0.0256. The PBHs uniformly share the same mass, which spans from about $10^{-10}$ to $10^{-1}$ solar masses, corresponding to the classical QCD axion mass window $10^{-5}-10^{-2}$ eV and the re-entering horizon temperature $300-1$ MeV. Intriguingly, PBHs in this mechanism can naturally account for the gravitational-lensing events observed by the OGLE collaboration.Comment: 5 pages, 3 figure

Role of ubiquitin specific proteases in the immune microenvironment of prostate cancer: A new direction

Regulation of ubiquitination is associated with multiple processes of tumorigenesis and development, including regulation of the tumor immune microenvironment. Deubiquitinating enzymes (DUBs) can remove ubiquitin chains from substrates, thereby stabilizing target proteins and altering and remodeling biological processes. During tumorigenesis, deubiquitination-altered biological processes are closely related to tumor metabolism, stemness, and the immune microenvironment. Recently, tumor microenvironment (TME) modulation strategies have attracted considerable attention in cancer immunotherapy. Targeting immunosuppressive mechanisms in the TME has revolutionized cancer therapy. Prostate cancer (PC) is one of the most common cancers and the second most common cause of cancer-related death in men worldwide. While immune checkpoint inhibition has produced meaningful therapeutic effects in many cancer types, clinical trials of anti-CTLA4 or anti-PD1 have not shown a clear advantage in PC patients. TME affects PC progression and also enables tumor cell immune evasion by activating the PD-1/PD-L1 axis. Over the past few decades, an increasing number of studies have demonstrated that deubiquitination in PC immune microenvironment may modulate the host immune system’s response to the tumor. As the largest and most diverse group of DUBs, ubiquitin-specific proteases (USPs) play an important role in regulating T cell development and function. According to current studies, USPs exhibit a high expression signature in PC and may promote tumorigenesis. Elevated expression of USPs often indicates poor tumor prognosis, suggesting that USPs are expected to develop as the markers of tumor prognosis and even potential drug targets for anti-tumor therapy. Herein, we first summarized recent advances of USPs in PC and focused on the relationship between USPs and immunity. Additionally, we clarified the resistance mechanisms of USPs to targeted drugs in PC. Finally, we reviewed the major achievement of targeting USPs in cancers

Adaptive Resource Allocation for Workflow Containerization on Kubernetes

In a cloud-native era, the Kubernetes-based workflow engine enables workflow containerized execution through the inherent abilities of Kubernetes. However, when encountering continuous workflow requests and unexpected resource request spikes, the engine is limited to the current workflow load information for resource allocation, which lacks the agility and predictability of resource allocation, resulting in over and under-provisioning resources. This mechanism seriously hinders workflow execution efficiency and leads to high resource waste. To overcome these drawbacks, we propose an adaptive resource allocation scheme named ARAS for the Kubernetes-based workflow engines. Considering potential future workflow task requests within the current task pod's lifecycle, the ARAS uses a resource scaling strategy to allocate resources in response to high-concurrency workflow scenarios. The ARAS offers resource discovery, resource evaluation, and allocation functionalities and serves as a key component for our tailored workflow engine (KubeAdaptor). By integrating the ARAS into KubeAdaptor for workflow containerized execution, we demonstrate the practical abilities of KubeAdaptor and the advantages of our ARAS. Compared with the baseline algorithm, experimental evaluation under three distinct workflow arrival patterns shows that ARAS gains time-saving of 9.8% to 40.92% in the average total duration of all workflows, time-saving of 26.4% to 79.86% in the average duration of individual workflow, and an increase of 1% to 16% in CPU and memory resource usage rate

Time-varying resonant mass at collider and beam dump experiments

A new particle usually manifests itself as a single resonant peak located at its mass. We propose if the new particle mass is time-varying due to environmental effects, then its mass spectrum typically has a novel double-peak feature. A representative model is the kinetic mixing dark photon interacting with an ultralight complex scalar dark matter charged under U(1)\u27. We reanalyze the existing experiments, showing the constraints on such a model are drastically weakened than those on the traditional single-peak resonance model, due to the reduction of the luminosity exposure in each resonant mass bin. Consequently, for mass around tens of MeV, the muon gμ -2 solution from the kinetic mixing dark photon becomes viable again. The scenario can be further tested by reanalyzing the existing data with timing information included

Long-lived Searches of Vector-like Lepton and Its Accompanying Scalar at Colliders

Recently, the vector-like leptons (VLLs) as a simple extension to the standard model (SM) have attracted widespread attention both in theory and experiments. The present collider searches mainly focus on the studies of their prompt decays, which prefer a relatively large coupling. In this paper, we concentrate on searches for long-lived signatures of the singlet VLLs $F$ or their accompanying scalar particles $\phi$ both in the hadronic and electronic colliders. The long-lived signatures are naturally induced from small chiral mass mixing between VLLs and SM leptons. Two specific models distinguished by whether the VLLs couple to scalar particles are introduced to realize the aforementioned features. For long-lived VLLs case, we find that with the kink track method the sensitivities at future HL-LHC with $\sqrt{s}=13~\text{TeV}$ can reach the regions for VLL mass $m_F \in [200,950]~\text{GeV}$ and the mass mixing parameter $\theta_L \in [10^{-10},10^{-7}]$. For the long-lived accompanying scalar particle case, by fixing VLLs or scalar mass, or the mass ratio between VLL and the accompanying scalar, we explore the projected sensitivities through the time delay and displaced vertex strategies, which can probe the regions for $m_F \in [200,1200]~\text{GeV}$ and coupling $y\theta_L\in [10^{-11},10^{-6}]$. Furthermore, we also explore the long-lived accompanying scalars at the future CEPC provided that the VLLs can couple to the SM first-generation leptons. We find that CEPC has good performances for $m_\phi < 70~\text{GeV}$ and $m_F<1000~\text{GeV}$. These long-lived searches are complementary to previous studies, which opens the door towards the smaller coupling regions.Comment: 29 pages, 7 figure