First-principles study of ground state properties and high pressure behavior of ThO2

The mechanical properties, electronic structure and phonon dispersion of ground state ThO$_{2}$ as well as the structure behavior up to 240 GPa are studied by using first-principles density-functional theory. Our calculated elastic constants indicate that both the ground state fluorite structure and high pressure cotunnite structure of ThO$_{2}$ are mechanically stable. The bulk modulus, shear modulus, and Young's modulus of cotunnite ThO$_{2}$ are all smaller by approximately 25% compared with those of fluorite ThO$_{2}$. The Poisson's ratios of both structures are approximately equal to 0.3 and the hardness of fluorite ThO$_{2}$ is 27.33 GPa. The electronic structure and bonding nature of fluorite ThO$_{2}$ are fully analyzed, which show that the Th-O bond displays a mixed ionic/covalent character. The valence of Th and O ions in fluorite ThO$_{2}$ can be represented as Th$^{3.834+}$ and O$^{0.452-}$. The phase transition from the fluorite to cotunnite structure is calculated to be at the pressure of 26.5 GPa, consistent with recent experimental measurement by Idiri \emph{et al}. \cite{Idiri}. For the cotunnite phase it is further predicted that an isostructural transition takes place in the pressure region of 80 to 130 GPa.Comment: 9 pages, 10 figure

Social Determinants of Community Health Services Utilization among the Users in China: A 4-Year Cross-Sectional Study

Background To identify social factors determining the frequency of community health service (CHS) utilization among CHS users in China. Methods Nationwide cross-sectional surveys were conducted in 2008, 2009, 2010, and 2011. A total of 86,116 CHS visitors selected from 35 cities were interviewed. Descriptive analysis and multinomial logistic regression analysis were employed to analyze characteristics of CHS users, frequency of CHS utilization, and the socio-demographic and socio-economic factors influencing frequency of CHS utilization. Results Female and senior CHS clients were more likely to make 3–5 and ≥6 CHS visits (as opposed to 1–2 visits) than male and young clients, respectively. CHS clients with higher education were less frequent users than individuals with primary education or less in 2008 and 2009; in later surveys, CHS clients with higher education were the more frequent users. The association between frequent CHS visits and family income has changed significantly between 2008 and 2011. In 2011, income status did not have a discernible effect on the likelihood of making ≥6 CHS visits, and it only had a slight effect on making 3–5 CHS visits. Conclusion CHS may play an important role in providing primary health care to meet the demands of vulnerable populations in China. Over time, individuals with higher education are increasingly likely to make frequent CHS visits than individuals with primary school education or below. The gap in frequency of CHS utilization among different economic income groups decreased from 2008 to 2011

Noise Distribution Decomposition based Multi-Agent Distributional Reinforcement Learning

Generally, Reinforcement Learning (RL) agent updates its policy by repetitively interacting with the environment, contingent on the received rewards to observed states and undertaken actions. However, the environmental disturbance, commonly leading to noisy observations (e.g., rewards and states), could significantly shape the performance of agent. Furthermore, the learning performance of Multi-Agent Reinforcement Learning (MARL) is more susceptible to noise due to the interference among intelligent agents. Therefore, it becomes imperative to revolutionize the design of MARL, so as to capably ameliorate the annoying impact of noisy rewards. In this paper, we propose a novel decomposition-based multi-agent distributional RL method by approximating the globally shared noisy reward by a Gaussian mixture model (GMM) and decomposing it into the combination of individual distributional local rewards, with which each agent can be updated locally through distributional RL. Moreover, a diffusion model (DM) is leveraged for reward generation in order to mitigate the issue of costly interaction expenditure for learning distributions. Furthermore, the optimality of the distribution decomposition is theoretically validated, while the design of loss function is carefully calibrated to avoid the decomposition ambiguity. We also verify the effectiveness of the proposed method through extensive simulation experiments with noisy rewards. Besides, different risk-sensitive policies are evaluated in order to demonstrate the superiority of distributional RL in different MARL tasks

Refining the Optimization Target for Automatic Univariate Time Series Anomaly Detection in Monitoring Services

Time series anomaly detection is crucial for industrial monitoring services that handle a large volume of data, aiming to ensure reliability and optimize system performance. Existing methods often require extensive labeled resources and manual parameter selection, highlighting the need for automation. This paper proposes a comprehensive framework for automatic parameter optimization in time series anomaly detection models. The framework introduces three optimization targets: prediction score, shape score, and sensitivity score, which can be easily adapted to different model backbones without prior knowledge or manual labeling efforts. The proposed framework has been successfully applied online for over six months, serving more than 50,000 time series every minute. It simplifies the user's experience by requiring only an expected sensitive value, offering a user-friendly interface, and achieving desired detection results. Extensive evaluations conducted on public datasets and comparison with other methods further confirm the effectiveness of the proposed framework.Comment: Accepted by 2023 IJCAI Worksho

Preparation and evaluation of peptide-dendrimer-paclitaxel conjugates for treatment of heterogeneous stage 1 nonsmall cell lung cancer in 293T and L132 cell lines

Purpose: To develop peptide-dendrimer-paclitaxel conjugates for the treatment of heterogeneous stage 1 non small cell lung cancer (NSCLC) in 293T and L132cell line.Method: Dendrimer-paclitaxel conjugates (PAMAM-PTX) were prepared by NHS method and the conjugates were used for the synthesis of peptide-dendrimer-paclitaxel conjugates (GE-PAMAM-PTX). The particle sizes of PAMAM-PTX and GE-PAMAM-PTX were measured. Entrapment efficiency of PTX in PAMAM-PTX was measured while GE-PAMAM-PTX. PTX release from PAMAM-PTX and GEPAMAM- PTX was determined using a dialysis bag in pH 7.4 phosphate buffer. The cytotoxicity of PAMAM-PTX, GE-PAMAM-PTX, PAMAM and PTX was evaluated by 3-(4,5-dimethylthiazol-2-Yl)-2,5- diphenyltetrazolium bromide (MTT) assay using 293T cell lines. In vitro cellular uptake assay of PAMAM-PTX and GE-PAMAM-PTX and PTX at concentrations ranging from 0.01 to 0.5μM for 8 h was carried out in NSCLC cell lines 293T and L132.Results: More than 95 % entrapment efficiency of GE-PAMAM-PTX was observed with loading efficiency of 25 %. GE-PAMAM-PTX conjugates showed sustained release of PTX (~85 %) towards the end of 50 h. GE-PAMAM-PTX conjugates were more cytotoxic than pure PTX and PAMAM-PTX conjugates. The remarkable uptake of GE-PAMAM-PTX appear to be due to receptor-mediated endocytosis in the cell lines. The presence of ligand (GE) on PAMAM-PTX surface enabled the complex to bind to the over-expressed receptors on the cell lines.Conclusion: GE-PAMAM-PTX can facilitate targeting of paclitaxel to lung cancer cell lines and tumors and facilitate release of the drugs in a sustained manner to improve the therapeutic efficacy of PTX.Keywords: Paclitaxel, Lung cancer, Non-small cell lung cancer, Dendrimer, Peptide, PAMA

Anchor Retouching via Model Interaction for Robust Object Detection in Aerial Images

Object detection has made tremendous strides in computer vision. Small object detection with appearance degradation is a prominent challenge, especially for aerial observations. To collect sufficient positive/negative samples for heuristic training, most object detectors preset region anchors in order to calculate Intersection-over-Union (IoU) against the ground-truthed data. In this case, small objects are frequently abandoned or mislabeled. In this paper, we present an effective Dynamic Enhancement Anchor (DEA) network to construct a novel training sample generator. Different from the other state-of-the-art techniques, the proposed network leverages a sample discriminator to realize interactive sample screening between an anchor-based unit and an anchor-free unit to generate eligible samples. Besides, multi-task joint training with a conservative anchor-based inference scheme enhances the performance of the proposed model while reducing computational complexity. The proposed scheme supports both oriented and horizontal object detection tasks. Extensive experiments on two challenging aerial benchmarks (i.e., DOTA and HRSC2016) indicate that our method achieves state-of-the-art performance in accuracy with moderate inference speed and computational overhead for training. On DOTA, our DEA-Net which integrated with the baseline of RoI-Transformer surpasses the advanced method by 0.40% mean-Average-Precision (mAP) for oriented object detection with a weaker backbone network (ResNet-101 vs ResNet-152) and 3.08% mean-Average-Precision (mAP) for horizontal object detection with the same backbone. Besides, our DEA-Net which integrated with the baseline of ReDet achieves the state-of-the-art performance by 80.37%. On HRSC2016, it surpasses the previous best model by 1.1% using only 3 horizontal anchors

Thermal tolerance for two cohorts of a native and an invasive freshwater turtle species

The ability to tolerate environmental stress may determine invasion success of alien species. Comparative data on physiological thermal tolerance between native and invasive vertebrates are quite limited. Here, we assessed the difference in thermal tolerance between a native (Mauremys reevesii) and an invasive (Trachemys scripta elegans) freshwater turtle species. We incubated eggs of M. reevesii and T. scripta elegans from different cohorts at 29 °C, and measured the critical thermal minimum (CTMin) and maximum (CTMax) of hatchlings. Our results preliminarily showed that the hatchlings of T. scripta elegans had a greater high-temperature tolerance and wider tolerance range than the hatchlings of M. reevesii; in the two-cohort system, individuals from the high-latitude cohort seemed to have greater low-temperature tolerance but similar high-temperature tolerance compared with those from the low-latitude cohort. Relatively greater thermal tolerance ability for T. scripta elegans might reflect its environmental adaptability to thermal stress

Observation of the ψ(13D2)\psi(1^3D_2) state in e+e−→π+π−γχc1e^+e^-\to\pi^+\pi^-\gamma\chi_{c1} at BESIII

We report the observation of the $X(3823)$ in the process $e^+e^-\to \pi^+\pi^-X(3823) \to \pi^+\pi^-\gamma\chi_{c1}$ with a statistical significance of $6.2\sigma$, in data samples at center-of-mass energies $\sqrt{s}=$4.230, 4.260, 4.360, 4.420 and 4.600~GeV collected with the BESIII detector at the BEPCII electron positron collider. The measured mass of the $X(3823)$ is $(3821.7\pm 1.3\pm 0.7)$~MeV/$c^2$, where the first error is statistical and the second systematic, and the width is less than $16$~MeV at the 90\% confidence level. The products of the Born cross sections for $e^+e^-\to \pi^+\pi^-X(3823)$ and the branching ratio $\mathcal{B}[X(3823)\to \gamma\chi_{c1,c2}]$ are also measured. These measurements are in good agreement with the assignment of the $X(3823)$ as the $\psi(1^3D_2)$ charmonium state.Comment: 7 pages, 3 figures, version to appear in Phys. Rev. Let