Cognitive function in systemic lupus erythematosus patients with a history of neuropsychiatric manifestations: a longitudinal study

Poster PresentationBACKGROUND: Cognitive impairment is commonly reported in patients with systemic lupus erythematosus (SLE) and its associations with neuropsychiatric involvement (NPSLE) and psychiatric factors have been inconsistently reported in the literature. OBJECTIVE: To evaluate full neurocognitive function in relation to psychiatric factors including anxiety and depression in NPSLE patients longitudinally compared to …published_or_final_versio

Enumeration of distinct mechanically stable disk packings in small systems

We create mechanically stable (MS) packings of bidisperse disks using an algorithm in which we successively grow or shrink soft repulsive disks followed by energy minimization until the overlaps are vanishingly small. We focus on small systems because this enables us to enumerate nearly all distinct MS packings. We measure the probability to obtain a MS packing at packing fraction $\phi$ and find several notable results. First, the probability is highly nonuniform. When averaged over narrow packing fraction intervals, the most probable MS packing occurs at the highest $\phi$ and the probability decays exponentially with decreasing $\phi$. Even more striking, within each packing-fraction interval, the probability can vary by many orders of magnitude. By using two different packing-generation protocols, we show that these results are robust and the packing frequencies do not change qualitatively with different protocols.Comment: 4 pages, 3 figures, Conference Proceedings for X International Workshop on Disordered System

Alignments between galaxies, satellite systems and haloes

The spatial distribution of the satellite populations of the Milky Way and Andromeda are puzzling in that they are nearly perpendicular to the discs of their central galaxies. To understand the origin of such configurations we study the alignment of the central galaxy, satellite system and dark matter halo in the largest of the ‘Evolution and Assembly of GaLaxies and their Environments’ (EAGLE) simulation. We find that centrals and their satellite systems tend to be well aligned with their haloes, with a median misalignment angle of 33◦ in both cases. While the centrals are better aligned with the inner 10 kpc halo, the satellite systems are better aligned with the entire halo indicating that satellites preferentially trace the outer halo. The central–satellite alignment is weak (median misalignment angle of 52◦) and we find that around 20 per cent of systems have a misalignment angle larger than 78◦, which is the value for the Milky Way. The central–satellite alignment is a consequence of the tendency of both components to align with the dark matter halo. As a consequence, when the central is parallel to the satellite system, it also tends to be parallel to the halo. In contrast, if the central is perpendicular to the satellite system, as in the case of the Milky Way and Andromeda, then the central–halo alignment is much weaker. Dispersion-dominated (spheroidal) centrals have a stronger alignment with both their halo and their satellites than rotation-dominated (disc) centrals. We also found that the halo, the central galaxy and the satellite system tend to be aligned with the surrounding large-scale distribution of matter, with the halo being the better aligned of the three

Measurement of the Branching Fraction of J/psi --> pi+ pi- pi0

Using 58 million J/psi and 14 million psi' decays obtained by the BESII experiment, the branching fraction of J/psi --> pi+ pi- pi0 is determined. The result is (2.10+/-0.12)X10^{-2}, which is significantly higher than previous measurements.Comment: 9 pages, 8 figures, RevTex

Metaverse Meets Intelligent Transportation System: An Efficient and Instructional Visual Perception Framework

The combination of the Metaverse and intelligent transportation systems (ITS) holds significant developmental promise, especially for visual perception tasks. However, the acquisition of high-quality scene data poses a challenging and expensive endeavor. Meanwhile, the visual disparity between the Metaverse and the physical world poses an impact on the practical applicability of the visual perception tasks. In this paper, a Metaverse Intelligent Traffic Visual Framework, MITVF, is developed to guide the implementation of visual perception tasks in the physical world. Firstly, a two-stage metadata optimization strategy is proposed that can efficiently provide diverse and high-quality scene data for traffic perception models. Specifically, an element reconfigurability strategy is proposed to flexibly combine dynamic and static traffic elements to enrich the data with a low cost. A diffusion model-based metadata optimization acceleration strategy is proposed to achieve efficient improvement of image resolution. Secondly, a Meta-Physical adaptive learning method is proposed, and further applied to visual perception tasks to compensate for the visual disparity between the Metaverse and the physical world. Experimental results show that MITVF achieves a 10 × acceleration in optimization speed, ensuring the image quality and reconstructing diverse. Further, MITVF is applied to the traffic object detection task to verify the effectiveness and validity. The performance of the model trained with 5k real data exceeded that of the model trained with 200k real data, with AP 50 reaching 67.7%.Key Research and Development Project of Hangzhou (Grant Number: 2022AIZD0009 and 2022AIZD0022); 10.13039/100022963-Key Research and Development Program of Zhejiang Province (Grant Number: 2022C01062)

First observation of psi(2S)-->K_S K_L

The decay psi(2S)-->K_S K_L is observed for the first time using psi(2S) data collected with the Beijing Spectrometer (BESII) at the Beijing Electron Positron Collider (BEPC); the branching ratio is determined to be B(psi(2S)-->K_S K_L) = (5.24\pm 0.47 \pm 0.48)\times 10^{-5}. Compared with J/psi-->K_S K_L, the psi(2S) branching ratio is enhanced relative to the prediction of the perturbative QCD ``12%'' rule. The result, together with the branching ratios of psi(2S) decays to other pseudoscalar meson pairs (\pi^+\pi^- and K^+K^-), is used to investigate the relative phase between the three-gluon and the one-photon annihilation amplitudes of psi(2S) decays.Comment: 5 pages, 4 figures, 2 tables, submitted to Phys. Rev. Let

Vehicle-Mounted Adaptive Traffic Sign Detector for Small-Sized Signs in Multiple Working Conditions

Traffic sign detection is of great significance to the development of the Intelligent Transportation System (ITS) as a database for environmental awareness. The main challenges of existing traffic sign detection method are inaccurate small object detection, difficult mobile deployment, and complex working environment. Based on these, a vehicle-mounted adaptive traffic sign detector (VATSD) for small-sized signs in multiple working conditions is proposed in this paper. First, the Backbone of the detector is optimized. A feature tight fusion structure is designed to constitute a new feature extraction module, DCSP, which improves the feature extraction capability and the detection accuracy of small objects with negligible additional parameters. Second, an image enhancement network IENet with an adaptive joint filtering strategy is proposed. The IENet enables the dynamic selection of filters and thus adaptively optimizes low-quality images under multiple conditions to improve the accuracy of subsequent detection tasks. The proposed method has experimented on three traffic sign datasets and the detection accuracy increased by up to 7.6% compared to the original. The proposed detector demonstrates superiority over other state-of-the-art (SOTA) methods in terms of small object detection accuracy, detection speed, and environmental adaptability. Further, we deployed VATSD to Jetson Xavier NX and achieved a detection speed of 21.6 FPS, meeting real-time requirements.Key Research and Development Project of Hangzhou (Grant Number: 2022AIZD0009 and 2022AIZD0022); 10.13039/100022963-Key Research and Development Program of Zhejiang Province (Grant Number: 2022C01062)

Nitrate contamination of drinking water: relationship with HPRT variant frequency in lymphocyte DNA and urinary excretion of N-nitrosamines.

We studied peripheral lymphocyte HPRT variant frequency and endogenous nitrosation in human populations exposed to various nitrate levels in their drinking water. Four test populations of women volunteers were compared. Low and medium tap water nitrate exposure groups (14 and 21 subjects) were using public water supplies with nitrate levels of 0.02 and 17.5 mg/l, respectively. Medium and high well water nitrate exposure groups (6 and 9 subjects) were using private water wells with mean nitrate levels of 25 and 135 mg/l, respectively. Higher nitrate intake by drinking water consumption resulted in a dose-dependent increase in 24-hr urinary nitrate excretion and in increased salivary nitrate and nitrite levels. The mean log variant frequency of peripheral lymphocytes was significantly higher in the medium well water exposure group than in the low and medium tap water exposure groups. An inverse correlation between peripheral lymphocyte labeling index and nitrate concentration of drinking water was observed. Analysis of N-nitrosamine in the urine of 22 subjects by gas chromatography-mass spectrometry revealed the presence of N-nitrosopyrrolidine in 18 subjects. Analysis of the mutagenicity of well water samples showed that a small number of the well water samples were mutagenic in the Ames Salmonella typhimurium test after concentration over XAD-2 resin. In conclusion, consumption of drinking water, especially well water, with high nitrate levels can imply a genotoxic risk for humans as indicated by increased HPRT variant frequencies and by endogenous formation of carcinogenic N-nitroso compounds from nitrate-derived nitrite

MDGN: Circuit design of memristor-based denoising autoencoder and gated recurrent unit network for lithium-ion battery state of charge estimation

Data availability statement: No.Copyright © 2023 The Authors. Due to the highly complex and non-linear physical dynamics of lithium-ion batteries, it is unfeasible to measure the state of charge (SOC) directly. Designing systems capable of accurate SOC estimation has become a key technology for battery management systems (BMS). Existing mainstream SOC estimation approaches still suffer from the limitations of low efficiency and high-power consumption, owing to the great number of samples required for training. To address these gaps, this paper proposes a memristor-based denoising autoencoder and gated recurrent unit network (MDGN) for fast and accurate SOC estimation of lithium-ion batteries. Specifically, the DAE circuit module is designed to extract useful feature representation with strong generalization and noise immunity. Then, the gated recurrent unit (GRU) circuit module is designed to learn the long-term dependencies between high-dimensional input and output data. The overall performance is evaluated by root mean square error (RMSE) and mean absolute error (MAE) at 0, 25, and 45°C, respectively. Compared with the current state-of-the-art methods, the entire scheme shows its superior performance in accuracy, robustness, and operation cost (referring to time cost).National Key Research and Development Program of China. Grant Number: 2020YFB1710600; National Natural Science Foundation (NNSF) of China. Grant Number: 62001149; Fundamental Research Funds for the Provincial Universities of Zhejiang. Grant Number: GK229909299001-06; Zhejiang Provincial Nature Science Foundation of China. Grant Number: LQ21F010009