Follow-up management service and health outcomes of hypertensive patients in China: A cross-sectional analysis from the national health service survey in Jiangsu province

BackgroundHypertension is a major cause of early mortality worldwide. Health follow-up management services can encourage patients with hypertension to improve their health behavior and outcomes. However, a lack of studies on the relationship between specific factors of follow-up management and both subjective and objective health outcome among hypertensive patients exists. The current study investigated the relationship between service content, frequency, mode, and institutions of follow-up management and health outcomes among Chinese hypertensives.MethodsData were obtained from the sixth National Health Service Survey (NHSS) of Jiangsu Province, which was conducted in 2018. Descriptive statistics were used to analyze the sample characteristics and the utilization of follow-up management services. Both multiple linear regression and logistic regression were used to estimate the association of follow-up management service and other factors with hypertensives' subjective and objective health outcomes.ResultSome respondents (19.30%) reported hypertension, and 75.36% of these patients obtained follow-up management services. Hypertensive patients' subjective health outcome self-reported health status and objective health outcome blood pressure (BP) control were found to be significantly associated with follow-up management services. The outcomes were both significantly improved by a high frequency of management services, a high level of follow-up providers, the mode of visiting healthcare facilities and/or calling, and receiving instructions on medication use. However, inquiring about patients' symptoms was negatively associated with self-reported health status and BP control. In addition, BP measurement was significantly and positively associated with hypertensive patients' self-reported health status; the patients receiving lifestyle guidance were more likely to have their BP levels under control.ConclusionsHypertension management strategies should further focus on the frequency of healthcare follow-up management via categorization of the follow-up services and appropriate adjustment of service delivery modes to optimize health follow-up management for hypertensives further improve their outcomes. Meanwhile, complementary policies are also needed to address other socioeconomic factors that can promote good health conditions for hypertension patients

Similarity Principle and its Acoustical Verification

This study finds a similarity principle the waves emanated from the same source are similar to each other as long as two wave receivers are close enough to each other the closer to each other the wave receivers are the more similar to each other the received waves are We define the similarity mathematically and verify the similarity principle by acoustical experiment

First mitochondrial genome of subfamily Julodinae (Coleoptera, Buprestidae) with its phylogenetic implications

Complete mitochondrial genomes of three species of the family Buprestidae were sequenced, annotated, and analyzed in this study. To explore the mitogenome features of the subfamily Julodinae and verify its phylogenetic position, the complete mitogenome of Julodis variolaris was sequenced and annotated. The complete mitogenomes of Ptosima chinensis and Chalcophora japonica were also provided for the phylogenetic analyses within Buprestidae. Compared to the known mitogenomes of Buprestidae species varied from 15,499 bp to 16,771 bp in length, three newly sequenced mitogenomes were medium length (15,759–16,227 bp). These mitogenomes were encoded 37 typical mitochondrial genes. Among the three studied mitogenomes, Leu2 (L2), Ser2 (S2), and Pro (P) were the three most frequently encoded amino acids. Within the Buprestidae, the heterogeneity in sequence divergences of Agrilinae was highest, whereas the sequence homogeneity of Chrysochroinae was highest. Moreover, phylogenetic analyses were performed based on nucleotide matrix (13 PCGs + 2 rRNAs) among the available sequenced species of Buprestidae using Bayesian Inference and Maximum Likelihood methods. The results showed that the Julodinae was closely related to the subfamily Polycestinae. Meanwhile, the genera Melanophila, Dicerca, and Coomaniella were included in Buprestinae, which was inconsistent with the current classification system of Buprestidae. These results could contribute to further studies on genetic diversity and phylogeny of Buprestidae

Differences of Heart Rate Variability Between Happiness and Sadness Emotion States: A Pilot Study

This pilot study investigated the differences of heart rate variability (HRV) indices between two opposite emotion states: happiness and sadness, to reveal the differences of autonomic nervous system activity under different emotional states. Forty-eight healthy volunteers were enrolled for this study. Electrocardiography (ECG) signals were recorded under both emotion states with a random measurement order (first happiness emotion measurement then sadness or reverse). RR interval (RRI) time series were extracted from ECGs and multiple HRV indices, including time-domain (MEAN, SDNN, RMSSD and PNN50), frequency-domain (LFn, HFn and LF/HF) and nonlinear indices (SampEn and FuzzyMEn) were calculated. In addition, the effects of heart rate (HR) and mean artery pressure (MAP) on the aforementioned HRV indices were analyzed for both emotion states. The results showed that experimental order had no significant effect on all HRV indices from both happiness and sadness emotions (all P > 0.05). The key result was that among all nine HRV indices, six indices were identified having significant differences between happiness and sadness emotion states: MEAN (P = 0.028), SDNN (P = 0.002), three frequency-domain indices (all P < 0.0001) and FuzzyMEn (P = 0.047), whereas RMSSD, PNN50 and SampEn had no significant differences between the two emotion states. All indices, except for SampEn, had significant positive correlations (all P < 0.01) for the two emotion states. Four time-domain indices decreased with the increase of HR (all P < 0.01), while frequency-domain and nonlinear indices demonstrated no HR-related changes for each emotional state. In addition, all indices (time-domain, frequency-domain and nonlinear) showed no MAP-related changes. It concluded that HRV indices showed significant differences between happiness and sadness emotion states and the findings could help to better understand the inherent differences of cardiovascular time series between different emotion states in clinical practice

FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous Driving

Key-point-based scene understanding is fundamental for autonomous driving applications. At the same time, optical flow plays an important role in many vision tasks. However, due to the implicit bias of equal attention on all points, classic data-driven optical flow estimation methods yield less satisfactory performance on key points, limiting their implementations in key-point-critical safety-relevant scenarios. To address these issues, we introduce a points-based modeling method that requires the model to learn key-point-related priors explicitly. Based on the modeling method, we present FocusFlow, a framework consisting of 1) a mix loss function combined with a classic photometric loss function and our proposed Conditional Point Control Loss (CPCL) function for diverse point-wise supervision; 2) a conditioned controlling model which substitutes the conventional feature encoder by our proposed Condition Control Encoder (CCE). CCE incorporates a Frame Feature Encoder (FFE) that extracts features from frames, a Condition Feature Encoder (CFE) that learns to control the feature extraction behavior of FFE from input masks containing information of key points, and fusion modules that transfer the controlling information between FFE and CFE. Our FocusFlow framework shows outstanding performance with up to +44.5% precision improvement on various key points such as ORB, SIFT, and even learning-based SiLK, along with exceptional scalability for most existing data-driven optical flow methods like PWC-Net, RAFT, and FlowFormer. Notably, FocusFlow yields competitive or superior performances rivaling the original models on the whole frame. The source code will be available at https://github.com/ZhonghuaYi/FocusFlow_official.Comment: The source code of FocusFlow will be available at https://github.com/ZhonghuaYi/FocusFlow_officia

Synthesis and magnetic properties of Zr doped ZnO Nanoparticles

Zr doped ZnO nanoparticles are prepared by the sol-gel method with post-annealing. X-ray diffraction results show that all samples are the typical hexagonal wurtzite structure without any other new phase, as well as the Zr atoms have successfully entered into the ZnO lattices instead of forming other lattices. Magnetic measurements indicate that all the doping samples show room temperature ferromagnetism and the pure ZnO is paramagneism. The results of Raman and X-ray photoelectron spectroscopy indicate that there are a lot of oxygen vacancies in the samples by doping element of Zr. It is considered that the observed ferromagnetism is related to the doping induced oxygen vacancies

Minimalist and High-Quality Panoramic Imaging with PSF-aware Transformers

High-quality panoramic images with a Field of View (FoV) of 360-degree are essential for contemporary panoramic computer vision tasks. However, conventional imaging systems come with sophisticated lens designs and heavy optical components. This disqualifies their usage in many mobile and wearable applications where thin and portable, minimalist imaging systems are desired. In this paper, we propose a Panoramic Computational Imaging Engine (PCIE) to address minimalist and high-quality panoramic imaging. With less than three spherical lenses, a Minimalist Panoramic Imaging Prototype (MPIP) is constructed based on the design of the Panoramic Annular Lens (PAL), but with low-quality imaging results due to aberrations and small image plane size. We propose two pipelines, i.e. Aberration Correction (AC) and Super-Resolution and Aberration Correction (SR&AC), to solve the image quality problems of MPIP, with imaging sensors of small and large pixel size, respectively. To provide a universal network for the two pipelines, we leverage the information from the Point Spread Function (PSF) of the optical system and design a PSF-aware Aberration-image Recovery Transformer (PART), in which the self-attention calculation and feature extraction are guided via PSF-aware mechanisms. We train PART on synthetic image pairs from simulation and put forward the PALHQ dataset to fill the gap of real-world high-quality PAL images for low-level vision. A comprehensive variety of experiments on synthetic and real-world benchmarks demonstrates the impressive imaging results of PCIE and the effectiveness of plug-and-play PSF-aware mechanisms. We further deliver heuristic experimental findings for minimalist and high-quality panoramic imaging. Our dataset and code will be available at https://github.com/zju-jiangqi/PCIE-PART.Comment: The dataset and code will be available at https://github.com/zju-jiangqi/PCIE-PAR