Exact semiclassical dynamics of generic Lipkin-Meshkov-Glick model

Lipkin-Meshkov-Glick model is paradigmatic to study quantum phase transition in equilibrium or non-equilibrium systems and entanglement dynamics for a variety of disciplines. In thermodynamics limit, quantum fluctuations are negligible, its semiclassical dynamics in presence of only one nonlinear couplings, as a good benchmark to study quantum fluctuation in finite-size system, can be well obtained in terms of Jacobi elliptic functions. In this work, we extend this semiclassical analysis into the regime where both nonlinear interactions are present, and successfully obtain its exact solutions of semiclassical equations by constructing an auxiliary function that is a linear combination of the $y$ and $z$ component of the classical spin in thermodynamic limit. Taking implementation of Lipkin-Meshkov-Glick model in a Bose-Einstein condensate setup as an example, we figure out all classical dynamical modes, specially find out mesoscopic self-trapping mode in population and phase-difference space even persists in presence of both nonlinear couplings. Our results would be useful to analyze dynamical phase transitions and entanglement dynamics of Lipkin-Meshkov-Glick model in presence of both nonlinear couplings.Comment: 12 pages, 10 figure

Selective killing of HIV-1-positive macrophages and T cells by the Rev-dependent lentivirus carrying anthrolysin O from Bacillus anthracis

<p>Abstract</p> <p>Background</p> <p>The ability of Human Immunodeficiency Virus (HIV) to persist in the body has proven to be a long-standing challenge to virus eradication. Current antiretroviral therapy cannot selectively destroy infected cells; it only halts active viral replication. With therapeutic cessation or interruption, viral rebound occurs, and invariably, viral loads return to pre-treatment levels. The natural reservoirs harboring replication-competent HIV-1 include CD4 T cells and macrophages. In particular, cells from the macrophage lineage resist HIV-1-mediated killing and support sustained viral production. To develop a complementary strategy to target persistently infected cells, this proof-of-concept study explores an HIV-1 Rev-dependent lentiviral vector carrying a bacterial hemolysin, <it>anthrolysin O </it>(<it>anlO</it>) from <it>Bacillus anthracis</it>, to achieve selective killing of HIV-1- infected cells.</p> <p>Results</p> <p>We demonstrate that in the Rev-dependent lentiviral vector, <it>anlO </it>expression is exclusively dependent on Rev, a unique HIV-1 protein present only in infected cells. Intracellular expression and oligomerization of AnlO result in membrane pore formation and cytolysis. We have further overcome a technical hurdle in producing a Revdependent AnlO lentivirus, through the use of β-cyclodextrin derivatives to inhibit direct killing of producer cells by AnlO. Using HIV-1-infected macrophages and T cells as a model, we demonstrate that this Rev-dependent AnlO lentivirus diminishes HIV-1- positive cells.</p> <p>Conclusion</p> <p>The Rev-dependent lentiviral vector has demonstrated its specificity in targeting persistently infected cells. The choice of <it>anlO </it>as the first suicidal gene tested in this vector is based on its cytolytic activity in macrophages and T cells. We conclude that Rev-regulated expression of suicidal genes in HIV-1-positive cells is possible, although future <it>in vivo </it>delivery of this system needs to address numerous safety issues.</p

Cofilin Activation in Peripheral CD4 T Cells of HIV-1 Infected Patients: A Pilot Study

Cofilin is an actin-depolymerizing factor that regulates actin dynamics critical for T cell migration and T cell activation. In unstimulated resting CD4 T cells, cofilin exists largely as a phosphorylated inactive form. Previously, we demonstrated that during HIV-1 infection of resting CD4 T cells, the viral envelope-CXCR4 signaling activates cofilin to overcome the static cortical actin restriction. In this pilot study, we have extended this in vitro observation and examined cofilin phosphorylation in resting CD4 T cells purified from the peripheral blood of HIV-1-infected patients. Here, we report that the resting T cells from infected patients carry significantly higher levels of active cofilin, suggesting that these resting cells have been primed in vivo in cofilin activity to facilitate HIV-1 infection. HIV-1-mediated aberrant activation of cofilin may also lead to abnormalities in T cell migration and activation that could contribute to viral pathogenesis.Department of Defense (National Defense Science and Engineering Fellowship); National Institute of Allergy and Infectious Diseases (AI069981

OmniDataComposer: A Unified Data Structure for Multimodal Data Fusion and Infinite Data Generation

This paper presents OmniDataComposer, an innovative approach for multimodal data fusion and unlimited data generation with an intent to refine and uncomplicate interplay among diverse data modalities. Coming to the core breakthrough, it introduces a cohesive data structure proficient in processing and merging multimodal data inputs, which include video, audio, and text. Our crafted algorithm leverages advancements across multiple operations such as video/image caption extraction, dense caption extraction, Automatic Speech Recognition (ASR), Optical Character Recognition (OCR), Recognize Anything Model(RAM), and object tracking. OmniDataComposer is capable of identifying over 6400 categories of objects, substantially broadening the spectrum of visual information. It amalgamates these diverse modalities, promoting reciprocal enhancement among modalities and facilitating cross-modal data correction. \textbf{The final output metamorphoses each video input into an elaborate sequential document}, virtually transmuting videos into thorough narratives, making them easier to be processed by large language models. Future prospects include optimizing datasets for each modality to encourage unlimited data generation. This robust base will offer priceless insights to models like ChatGPT, enabling them to create higher quality datasets for video captioning and easing question-answering tasks based on video content. OmniDataComposer inaugurates a new stage in multimodal learning, imparting enormous potential for augmenting AI's understanding and generation of complex, real-world data

MovePose: A High-performance Human Pose Estimation Algorithm on Mobile and Edge Devices

We present MovePose, an optimized lightweight convolutional neural network designed specifically for real-time body pose estimation on CPU-based mobile devices. The current solutions do not provide satisfactory accuracy and speed for human posture estimation, and MovePose addresses this gap. It aims to maintain real-time performance while improving the accuracy of human posture estimation for mobile devices. The network produces 17 keypoints for each individual at a rate exceeding 11 frames per second, making it suitable for real-time applications such as fitness tracking, sign language interpretation, and advanced mobile human posture estimation. Our MovePose algorithm has attained an Mean Average Precision (mAP) score of 67.7 on the COCO \cite{cocodata} validation dataset. The MovePose algorithm displayed efficiency with a performance of 69+ frames per second (fps) when run on an Intel i9-10920x CPU. Additionally, it showcased an increased performance of 452+ fps on an NVIDIA RTX3090 GPU. On an Android phone equipped with a Snapdragon 8 + 4G processor, the fps reached above 11. To enhance accuracy, we incorporated three techniques: deconvolution, large kernel convolution, and coordinate classification methods. Compared to basic upsampling, deconvolution is trainable, improves model capacity, and enhances the receptive field. Large kernel convolution strengthens these properties at a decreased computational cost. In summary, MovePose provides high accuracy and real-time performance, marking it a potential tool for a variety of applications, including those focused on mobile-side human posture estimation. The code and models for this algorithm will be made publicly accessible