GazeMoDiff: Gaze-guided Diffusion Model for Stochastic Human Motion Prediction

Human motion prediction is important for virtual reality (VR) applications, e.g., for realistic avatar animation. Existing methods have synthesised body motion only from observed past motion, despite the fact that human gaze is known to correlate strongly with body movements and is readily available in recent VR headsets. We present GazeMoDiff -- a novel gaze-guided denoising diffusion model to generate stochastic human motions. Our method first uses a graph attention network to learn the spatio-temporal correlations between eye gaze and human movements and to fuse them into cross-modal gaze-motion features. These cross-modal features are injected into a noise prediction network via a cross-attention mechanism and progressively denoised to generate realistic human full-body motions. Experimental results on the MoGaze and GIMO datasets demonstrate that our method outperforms the state-of-the-art methods by a large margin in terms of average displacement error (15.03% on MoGaze and 9.20% on GIMO). We further conducted an online user study to compare our method with state-of-the-art methods and the responses from 23 participants validate that the motions generated by our method are more realistic than those from other methods. Taken together, our work makes a first important step towards gaze-guided stochastic human motion prediction and guides future work on this important topic in VR research

Indocyanine Green-Loaded Polydopamine-Reduced Graphene Oxide Nanocomposites with Amplifying Photoacoustic and Photothermal Effects for Cancer Theranostics

Photoacoustic (PA) imaging and photothermal therapy (PTT) as light-induced theranostic platforms have been attracted much attention in recent years. However, the development of highly efficient and integrated phototheranostic nanoagents for amplifying PA imaging and PTT treatments poses great challenges. Here, we report a novel phototheranostic nanoagent using indocyanine green-loaded polydopamine-reduced graphene oxide nanocomposites (ICG-PDA-rGO) with amplifying PA and PTT effects for cancer theranostics. The results demonstrate that the PDA layer coating on the surface of rGO could effectively absorb a large number of ICG molecules, quench ICG's fluorescence, and enhance the PDA-rGO's optical absorption at 780 nm. The obtained ICG-PDA-rGO exhibits stronger PTT effect and higher PA contrast than that of pure GO and PDA-rGO. After PA imaging-guided PTT treatments, the tumors in 4T1 breast subcutaneous and orthotopic mice models are suppressed completely and no treatment-induced toxicity being observed. It illustrates that the ICG-PDA-rGO nanocomposites constitute a new class of theranostic nanomedicine for amplifying PA imaging and PTT treatments

Distributed secondary control of microgrids with unknown disturbances and non-linear dynamics

In this paper, the voltage and frequency regulation of microgrid with unknown disturbances and non-linear dynamics was studied. The disturbance observer was designed and the sliding mode control (SMC) method was used to realize the secondary regulation of voltage and frequency. First, a distributed secondary control protocol was designed to reduce the communication burden between generators and to solve voltage and frequency deviations. Second, a consensus protocol for secondary control of voltage and frequency was designed, based on the idea of multi-agent consensus, to indirectly ensure that the voltage and frequency to be adjusted reach the reference values when the consensus is realized. In addition, considering unknown disturbances in the microgrid, a sliding mode control strategy, based on a disturbance observer, was designed to overcome the influence of disturbances and to reduce chatter. This SMC scheme ensured finite time accessibility of the sliding mode surface. This design provides sufficient conditions for voltage and frequency regulation. The effectiveness of this design scheme was verified through simulation

cuPDLP-C: A Strengthened Implementation of cuPDLP for Linear Programming by C language

A recent GPU implementation of the Restarted Primal-Dual Hybrid Gradient Method for Linear Programming was proposed in Lu and Yang (2023). Its computational results demonstrate the significant computational advantages of the GPU-based first-order algorithm on certain large-scale problems. The average performance also achieves a level close to commercial solvers for the first time in history. However, due to limitations in experimental hardware and the disadvantage of implementing the algorithm in Julia compared to C language, neither the commercial solver nor cuPDLP reached their maximum efficiency. Therefore, in this report, we have re-implemented and optimized cuPDLP in C language. Utilizing state-of-the-art CPU and GPU hardware, we extensively compare cuPDLP with the best commercial solvers. The experiments further highlight its substantial computational advantages and potential for solving large-scale linear programming problems. We also discuss the profound impact this breakthrough may have on mathematical programming research and the entire operations research community.Comment: fix typos, update numerical result

A compact ultrabroadband polarization beam splitter utilizing a hybrid plasmonic Y-branch

A compact and ultrabroadband polarization beam splitter (PBS) utilizing a hybrid plasmonic Y-branch (HPYB) on a silicon-on-insulator (SOI) platform is proposed and numerically demonstrated. The HPYB consists of a vertical hybrid plasmonic waveguide (HPW) and a horizontal HPW formed by silicon (Si) and silver (Ag) strip waveguides sandwiched with a silicon dioxide (SiO2) layer, in which the vertical and horizontal hybrid plasmonic modes (HPMs) are excited by the input transverse electric (TE) and transverse magnetic (TM) modes, respectively. The HPMs are split into different ports and coupled back to TE and TM modes to implement the polarization splitting function. A simplified and compact HPYB is robust for the HPMs' generation. The structure is wavelength insensitive since the HPMs' excitation is weakly correlated to the optical wavelengths. The simulation results show that the HPYB-based PBS has a compact footprint of 5×1.8 µm2 and an ultralarge working bandwidth of 285nm, with the polarization crosstalk < -10 dB and the worst-case TE (TM) mode insertion loss of -1.53 (-2.35) dB. The device also exhibits a large fabrication tolerance of 210nm variation (from -100 to 110nm) to the waveguide width for both polarizations

MicroRNA-196a-5p targeting LRP1B modulates phenotype of thyroid carcinoma cells

Introduction: Thyroid cancer (TC) is a common endocrine malignancy, comprising nearly one-third of all head and neck malignancies worldwide. MicroRNAs (miRNAs) have been implicated in the malignant progression of multiple cancers; however, their contribution to thyroid diseases has not been fully explored. Material and methods: This study aimed to illustrate the regulatory mechanism of microRNA-196a-5p in TC progression and to investigate whether microRNA-196a-5p affects progression of TC cells by targeting low-density lipoprotein receptor-associated protein 1B (LRP1B). MicroRNA-196a-5p and LRP1B expression status in TC cells and normal human thyroid cells was detected by quantative reverse transcription polymerase chain reaction (qRT-PCR) and western blot. Dual-luciferase reporter assay, cell counting kit-8 (CCK-8) assay, scratch healing assay, and Transwell assay were also performed. Results: The results showed that microRNA-196a-5p expression was up-regulated and LRP1B expression was down regulated in TC cells. In addition, the upregulation of microRNA-196a-5p facilitated progression of TC cells. Silencing microRNA-196a-5p led to the opposite results. Dual-luciferase reporter assay offered evidence for microRNA-196a-5p targeting LRP1B in TC. MicroRNA-196a-5p could target LRP1B to facilitate proliferation, invasion, and migration of TC cells. Conclusion: Overall, this study revealed that microRNA-196a-5p may be a cancer-promoting microRNA that plays an important role in TC progression

Comprehensive toxicological, metabolomic, and transcriptomic analysis of the biodegradation and adaptation mechanism by Achromobacter xylosoxidans SL-6 to diuron

Biodegradation was considered a promising and environmentally friendly method for treating environmental pollution caused by diuron. However, the mechanisms of biodegradation of diuron required further research. In this study, the degradation process of diuron by Achromobacter xylosoxidans SL-6 was systematically investigated. The results suggested that the antioxidant system of strain SL-6 was activated by adding diuron, thereby alleviating their oxidative stress response. In addition, degradation product analysis showed that diuron in strain SL-6 was mainly degraded by urea bridge cleavage, dehalogenation, deamination, and ring opening, and finally cis, cis-muconic acid was generated. The combined analysis of metabolomics and transcriptomics revealed the biodegradation and adaptation mechanism of strain SL-6 to diuron. Metabolomics analysis showed that after the strain SL-6 was exposed to diuron, metabolic pathways such as tricarboxylic acid cycle (cis, cis-muconic acid), glutathione metabolism (oxidized glutathione), and urea cycle (arginine) were reprogrammed in the cells. Furthermore, diuron could induce the production of membrane transport proteins in strain SL-6 cells and overexpress antioxidant enzyme genes, finally ultimately promoting the up-regulation of genes encoding amide hydrolases and dioxygenases, which was revealed by transcriptomics studies. This work enriched the biodegradation mechanism of phenylurea herbicides and provided guidance for the removal of diuron residues in the environment and promoting agriculture sustainable development

Reactive Oxygen Species Suppress Cardiac NaV1.5 Expression through Foxo1

NaV1.5 is a cardiac voltage-gated Na+ channel αsubunit and is encoded by the SCN5a gene. The activity of this channel determines cardiac depolarization and electrical conduction. Channel defects, including mutations and decrease of channel protein levels, have been linked to the development of cardiac arrhythmias. The molecular mechanisms underlying the regulation of NaV1.5 expression are largely unknown. Forkhead box O (Foxo) proteins are transcriptional factors that bind the consensus DNA sequences in their target gene promoters and regulate the expression of these genes. Comparative analysis revealed conserved DNA sequences, 5′-CAAAACA-3′ (insulin responsive element, IRE), in rat, mouse and human SCN5a promoters with the latter two containing two overlapping Foxo protein binding IREs, 5′-CAAAACAAAACA-3′. This finding led us to hypothesize that Foxo1 regulates NaV1.5 expression by directly binding the SCN5a promoter and affecting its transcriptional activity. In the present study, we determined whether Foxo1 regulates NaV1.5 expression at the transcriptional level and also defined the role of Foxo1 in hydrogen peroxide (H2O2)-mediated NaV1.5 suppression in HL-1 cardiomyocytes using chromatin immunoprecipitation (ChIP), constitutively nuclear Foxo1 expression, and RNAi Foxo1 knockdown as well as whole cell voltage-clamp recordings. ChIP with anti-Foxo1 antibody and follow-up semi-quantitative PCR with primers flanking Foxo1 binding sites in the proximal SCN5a promoter region clearly demonstrated enrichment of DNA, confirming Foxo1 recruitment to this consensus sequence. Foxo1 mutant (T24A/S319A-GFP, Foxo1-AA-GFP) was retained in nuclei, leading to a decrease of NaV1.5 expression and Na+ current, while silencing of Foxo1 expression by RNAi resulted in the augmentation of NaV1.5 expression. H2O2 significantly reduced NaV1.5 expression by promoting Foxo1 nuclear localization and this reduction was prevented by RNAi silencing Foxo1 expression. These studies indicate that Foxo1 negatively regulates NaV1.5 expression in cardiomyocytes and reactive oxygen species suppress NaV1.5 expression through Foxo1

An Adaptive Packed-Memory Array

The packed-memory array (PMA) is a data structure that maintains a dynamic set of N elements in sorted order in a Θ(N)-sized array. The idea is to intersperse Θ(N) empty spaces or gaps among the elements so that only a small number of elements need to be shifted around on an insert or delete. Because the elements are stored physically in sorted order in memory or on disk, the PMA can be used to support extremely efficient range queries. Specifically, the cost to scan L consecutive elements is O(1 + L/B) memory transfers. This paper gives the first adaptive packed-memory array (APMA), which automatically adjusts to the input pattern. Like the traditional PMA, any pattern of updates costs only O(log 2 N) amortized element moves and O(1 + (log 2 N)/B) amortized memory transfers per update. However, the APMA performs even better on many common input distributions achieving only O(logN) amortized element moves and O(1 + (logN)/B) amortized memory transfers. The paper analyzes sequential inserts, where the insertions are to the front of the APMA, hammer inserts, where the insertions “hammer ” on one part of the APMA, random inserts, where the insertions are after random elements in the APMA, and bulk inserts, where for constant α ∈ [0,1], N α elements are inserted after random elements in the APMA. The paper then gives simulation results that are consistent with the asymptotic bounds. For sequential insertions of roughly 1.4 million elements, the APMA has four times fewer element moves per insertion than the traditional PMA and running times that are more than seven times faster

Relative Pose Estimation of Non-Cooperative Space Targets Using a TOF Camera

It is difficult to determine the accurate pose of non-cooperative space targets in on-orbit servicing (OOS). The visual camera is easily affected by the extreme light environment in space, and the scanning lidar will have motion distortion when the target moves at high speed. Therefore, we proposed a non-cooperative target pose-estimation system combining a registration and a mapping algorithm using a TOF camera. We first introduce the projection model of the TOF camera and proposed a new calibration method. Then, we introduce the three modules of the proposed method: the TOF data preprocessing module, the registration module and the model mapping module. We assembled the experimental platform to conduct semi-physical experiments; the results showed that the proposed method has the smallest translation error 8 mm and Euler angle error 1° compared with other classical methods. The total time consumption is about 100 ms, and the pose tracking frequency can reach 10 Hz. We can conclude that the proposed pose-estimation scheme can achieve the high-precision pose estimation of non-cooperative targets and meet the requirements necessary for aerospace applications