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Selective absorber is an important component for enhancing the solar-to-heat efficiency in high-temperature solar applications. In this paper, a selective metamaterial absorber possessing four-pointed star prisms was proposed and studied. Firstly, an optimal metamaterial absorber with perfect spectrally selective performance was obtained after optimizing the structure. It was found that the optimal absorber can achieve the high total solar absorptance of 0.958 and the low total emittance of 0.2355–0.4062, thus obtaining the high solar-to-heat efficiency of 92.31%-77.78% at 1000 suns and 1273–1673 K. Secondly, the underlying mechanisms for the good spectral selectivity of the optimal absorber were analyzed. The results showed that the high spectral absorptance in the solar spectrum owes to the impedance matching and the coupling effects of different plasmonic modes. The low spectral emittance within the mid-infrared band can be explained by the impedance mismatching. Thirdly, the effects of the geometrical parameters on the spectral selectivity of the absorber were studied, indicating that the height of the SiO2 layer above the star and the short diagonal length of the rhomb influence little on the spectral absorptance when they are in certain ranges. However, other parameters have obvious influences on the spectral absorptance. Finally, study on the effects of the polarization angle and incident angle indicated that the optimal absorber exhibits good insensitivities to the polarization angle and the incident angle. These results indicate that the proposed perfect absorber is a promising candidate for high-temperature solar applications.

This meta-analysis was performed to evaluate the clinical efficacy and safety of Chinese patent medicines in the treatment of subacute thyroiditis (SAT).Chinese databases were searched using a combination of "patent Chinese medicine", "traditional Chinese medicine", "traditional Chinese and western medicine", "sub-thyroiditis", and "subacute thyroiditis". Studies that set Chinese patent medicine treatment of SAT as the experimental group were selected. Then, meta-analysis was performed by RevMan 5.3.A total of 12 studies were included, and most of them had a high risk of bias (low quality). The heterogeneity test results of clinical efficacy showed that Chi2=6.21, df=7, P=0.520.1, and I2=0%50%. Then, the fixed effects model (FEM) was used, with OR =2.80; 95% confidence interval (CI): 1.89-4.13. The heterogeneity test of recurrence rate showed that Chi2=10.69, df=9, P=0.300.1, and I2=16%50%. The heterogeneity test of erythrocyte sedimentation rate showed that I2=97%, P0.00001, MD =-10.02; 95% CI: -12.88 to -7.16, and P0.00001. The heterogeneity test of free triiodothyronine showed that Chi2=500.75, I2=99%50%, P0.00001, MD =-2.88; 95% CI: -3.85 to -1.91; Z=5.83, and P0.00001. The heterogeneity test of free thyroid hormone showed that Chi2=25.15, I2=72%50%, P=0.0007, MD =-2.48; 95% CI: -3.69 to -1.26; Z=3.99, and P0.0001. The heterogeneity test of the occurrence of adverse reactions showed that Chi2=11.28, df=11, P=0.420.1, and I2=3%50%, and the combined effect size was Z=6.49 and P0.00001, with OR =0.21; 95% CI: 0.13-0.34.The meta-analysis of this study confirms that Chinese patent medicines have considerable clinical effects in the treatment of SAT. They can reduce the recurrence rate, adjust the levels of free triiodothyronine and free thyroid hormone, and have good safety.

Panax notoginseng saponins (PNS), the main bioactive constituents of a traditional Chinese herb Panax notoginseng, were commonly used for ischemic stroke in China. However, the associated cellular and molecular mechanisms of PNS have not been well examined. This study aimed to decipher the underlying molecular target of PNS in the treatment of cerebral ischemia. The oxygen-glucose-deprived (OGD) model of rat brain microvascular endothelial cells (BMECs) was used in this study. The alteration of gene expression in rat BMECs after PNS treatment was measured by microarray and indicated that there were 38 signaling pathways regulated by PNS. Among them, RIG-I receptor and related signaling molecules TNF receptor-associated factor 2 (Traf2) and nuclear factor-kappa B (NF-κB) were significantly suppressed by PNS, which was verified again in OGD-induced BMECs measured by FQ-PCR and western blotting and in middle cerebral artery occlusion (MCAO) rats measured by immunohistochemistry. The levels of TNF-α, IL-8, and the downstream cytokines regulated by RIG-I receptor pathway were also decreased by PNS. Meanwhile, the neurological evaluation, hematoxylin and eosin (HE) staining, and Evans blue staining were conducted to evaluate the effect of PNS in MCAO rats. Results showed PNS significantly improved functional outcome and cerebral vascular leakage. Flow cytometry showed the number of the inflammatory cells infiltrated in brain tissue was decreased in PNS treatment. Our results identified that RIG-I signaling pathway mediated anti-inflammatory properties of PNS in cerebral ischemia, which provided the novel insights of PNS application in clinics.

Background Group A rotavirus (RVA) is one of the most common causes of severe diarrhea in children worldwide. However, RVA is also an important pathogen causing adult diarrhea, with higher infection rates in older patients. To provide evidence for rotavirus epidemic control and to inform vaccine development, we analyzed the molecular epidemiology of RVA among adult outpatients with diarrhea in Beijing from 2011 to 2018. Materials and methods Stool specimens were collected monthly from 14 districts. RVA was detected using enzyme linked immunosorbent assay and real time reverse transcription polymerase chain reaction (RT-PCR). Genotyping of rotavirus was performed using multiplex semi-nested RT-PCR. Phylogenetic analysis was performed using maximum likelihood methods implemented in MEGA software (version 6.06). Logistic regression and chi-square tests were used to assess differences among age groups, districts, years, and genotype distributions. Results The prevalence of rotavirus was 10.16% (1,310/12,893) among adult outpatients with diarrhea from 2011 to 2018 in Beijing. The highest prevalence (13.74%, 600/4,367) was observed among those aged 41 to 65 years. November, December, and January had the highest positive detection rates. In 2011, G3P[8] and G9P[8] were the dominant genotypes. Starting from 2012, G9P[8] became the dominant genotype. Most G9 strains belonged to the G9-VI clade. Most P[8] strains belonged to the P[8]-III clade. Conclusions RVA is a major cause of adult diarrhea in Beijing. Continuous molecular surveillance is needed, and transmission of rotavirus between children and adults should be investigated further. This article is protected by copyright. All rights reserved.

Weihong Li,1,* Yanrong Wang,1,* Yingzi Pei,2 Yue Xia2 1GCP Office of Cangzhou Central Hospital, Cangzhou, Hebei, 061000, People’s Republic of China; 2Research Center of Beijing Fuyuan Pharmaceutical Co., Ltd. (Formerly Beijing Wansheng Pharmaceutical Co., Ltd.), Beijing, 101113, People’s Republic of China*These authors contributed equally to this workCorrespondence: Weihong LiGCP Office of Cangzhou Central Hospital, No. 16 on Xinhua Road, Cangzhou, Hebei, 061000, People’s Republic of ChinaTel +86 18713731395Fax +86 3172072825Email sarry610@163.comPurpose: The aim of this study was to assess and compare the pharmacokinetic (PK) properties and bioequivalence of montelukast sodium chewable tablets prepared by two different manufacturers in healthy Chinese volunteers to obtain adequate PK evidence for the registration approval of the test formulation.Patients and Methods: A randomized-sequence, single-dose, open-label, 2-period crossover study was conducted in fasted and fed healthy Chinese volunteers (Chinese Clinical Trials Registry identifier: CTR20182362). Eighteen subjects each were selected for a fasted study and a fed study. Eligible participants were randomly assigned in a 1:1 ratio to receive a single dose of the reference formulation or the test formulation, followed by a 5-day washout period and the administration of the alternate formulation. Plasma samples were collected over a 24-hour period following tablet administration and analyzed for montelukast contents by high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The PK parameters, such as maximum serum concentration (Cmax), area under the curve (AUC) from t = 0 to the last quantifiable concentration (AUC0–t), AUC from t = 0 to infinity (AUC0–∞), half-life (t1⁄ 2), time to Cmax (Tmax), and terminal elimination rate constant (λz), were evaluated. The safety assessment included changes in vital signs (blood pressure, pulse, and temperature) or laboratory tests (hematology, blood biochemistry, hepatic function, and urinalysis) and the incidence of adverse events (AEs).Results: The geometric mean ratios (GMRs) between the two formulations for the primary pharmacokinetic parameters (Cmax, AUC0– 24, and AUC 0–∞) and the corresponding 90% confidence intervals (Cis) were all within the range of 80.00– 125.00% for both the fasting and fed states. The safety profiles for both treatments were comparable.Conclusion: The PK analysis revealed that the test and reference formulations of montelukast sodium chewable tablets were bioequivalent and well-tolerated by healthy Chinese subjects.Keywords: montelukast sodium, bioequivalence, pharmacokinetic profile, HPLC-MS/MS, adverse events

Automatic tongue image segmentation and tongue image classification are two crucial tongue characterization tasks in traditional Chinese medicine (TCM). Due to the complexity of tongue segmentation and fine-grained traits of tongue image classification, both tasks are challenging. Fortunately, from the perspective of computer vision, these two tasks are highly interrelated, making them compatible with the idea of Multi-Task Joint learning (MTL). By sharing the underlying parameters and adding two different task loss functions, an MTL method for segmenting and classifying tongue images is proposed in this paper. Moreover, two state-of-the-art deep neural network variants (UNET and Discriminative Filter Learning (DFL)) are fused into the MTL to perform these two tasks. To the best of our knowledge, our method is the first attempt to manage both tasks simultaneously with MTL. We conducted extensive experiments with the proposed method. The experimental results show that our joint method outperforms the existing tongue characterization methods. Besides, visualizations and ablation studies are provided to aid in understanding our approach, which suggest that our method is highly consistent with human perception.

With exploiting contextual information over large image regions in an efficient way, the deep convolutional neural network has shown an impressive performance for single-image super-resolution (SR). In this paper, we propose a new deep convolutional network by cascading multiple well-designed inception-residual blocks within the deep Laplacian pyramid framework to progressively restore the missing high-frequency details in the low-resolution images. By optimizing our network structure, the trainable depth of our proposed network gains a significant improvement, which in turn improves super-resolving accuracy. However, the saturation and degradation of training accuracy remains a critical problem. With regard to this, we propose an effective two-stage training strategy, in which we first use the images downsampled from the ground-truth high-resolution (HR) images to pretrain the inception-residual blocks on each pyramid level with an extremely high learning rate enabled by gradient clipping, and then the original ground-truth HR images are used to fine-tune all the pretrained inception-residual blocks for obtaining our final SR models. Furthermore, we present a new loss function operating in both image space and local rank space to optimize our network for exploiting the contextual information among different output components. Extensive experiments on benchmark data sets validate that the proposed method outperforms the existing state-of-the-art SR methods in terms of the objective evaluation as well as the visual quality.

Image deblurring methods based on deep learning have been proved to be effective for dynamic scene deblurring. Nevertheless, the most existing methods usually fail to deal with severe and complex dynamic scene blurs. In this paper, we propose a novel multi-stream attentive generative adversarial network (MSA-GAN) for solving the problems. Firstly, we design a novel attentive guidance module for generating an attention map which can guide to pay more attention on the severe blur regions or objects and their edge or texture structures in the feature extraction and deblurring process. Secondly, we propose the multi-stream and multi-scale feature extraction strategy and design an attentive and multi-scale feature extraction module, in which we design a multi-scale residual block for extracting the multi-scale features and capturing more information of complex blurs. Thirdly, we propose a multi-scale feature fusion strategy and the strategy is implemented in the multi-stream and multi-scale feature fusion module through the designed gate structure, which can adaptively learn and fuse multi-scale features from different streams. Finally, The extensive experiments are performed on the GoPro dynamic scene dataset and real image data, and the experimental results both quantitatively and qualitatively have demonstrated that the proposed method outperform the recent state-of-the-art methods.

The tooth-marked tongue refers to the tongue with the edge featured in jagged teeth marks, which is a significant indicator for reflecting the conditions of patients' internal organs in Traditional Chinese Medicine (TCM). From the perspective of computer vision, due to the small variance in the global region (original image) but the large variance in the local region (tongue region), especially in the differential region (tongue edge region around landmarks), the recognition of the tooth-marked tongue is a naturally fine-grained classification task. To address this challenging task, a two-stage method based on tongue region detection and tongue landmark detection via deep learning is proposed in this paper. In the first stage, we introduce a cascaded convolutional neural network to detect the tongue region and tongue landmarks simultaneously for minimizing the redundancy information and maximizing discriminative information explicitly. In the second stage, we send not only the detected tongue region but also the detected tongue landmarks to a fine-grained classification network for the final recognition. Conclusively, our method is highly consistent with human perception. Moreover, to the best of our knowledge, we are the first attempt to manage the tooth-marked tongue recognition via deep learning. We conducted extensive experiments with the proposed method. The experimental results demonstrate the effectiveness of the proposed method.

Background: Rapid and accurate high-throughput estimation of radiation dose aims to help medical rescue in nuclear radiation accident. However, current methods of dose estimation are still lacking of speedy or accuracy. P53 signaling pathway plays an important role in DNA damage repair and cell apoptosis induced by ionizing radiation. The changes of radiation-induced P53 related genes in the early stage of ionizing radiation should compensate for the deficiency of lymphocyte decline and γ-H2AX analysis as novel biomarkers of radiation damage. Methods: Bioinformatic analysis was performed on previous data to find candidate genes from human peripheral blood irradiated in vitro. The radiation sensitivity and baseline levels of candidate genes were verified. The approximate threshold for guiding medical treatment was estimated for each gene, and four genes were combined to construct an effectively early dose estimation model of radiation.Results: Four p53-related genes, DDB2, AEN, TRIAP1 and TRAF4, were screened and verified their significant radiosensitivity. Their expressions were stable without gender or age difference in healthy population, but significantly up-regulated by radiation, with time specificity and dose dependence in 2h-24h after irradiation. Further studies showed these genes can be used as indicators for early medical treatment in acute radiation injury. The effective combination of the four genes could achieve a more accurate dose assessment and injury classification for large-scale wounded patients within 24 hours post exposure.Conclusions: This is the first time to investigate the potential biomarkers of ionizing radiation by systematic study. The effective combination of the four genes provides a new model for dose estimation and injury classification of a large number of exposed population in acute nuclear accidents, and also provides a new idea and method.

Background Insomnia is very common in current society, and patients are often accompanied by a certain degree of anxiety, depression, etc. Recent studies have found that the hypothalamic-pituitary-adrenal (HPA) axis excitement-inhibition state is an important indicator of sleep quality. Wrist-ankle acupuncture (WAA) is safe and effective for insomnia. Based on WAA theory, the acupressure wrist-ankle straps are portable WAA point compression straps that can treat diseases by automatically applying pressure to the treatment location and being operated by patients themselves. We design this trial to evaluate the clinical effect of the acupressure wrist-ankle strap in the treatment of mild insomnia patients with anxiety disorders. Methods/design This trial is a parallel-design, patients-assessor blinded, randomized, sham-controlled. In total, 114 patients diagnosed with mild insomnia and anxiety disorders will be randomly assigned into two groups, the acupressure wrist-ankle strap group or the non-acupressure wrist-ankle strap group; they will receive treatments for eight weeks with five sessions each week. Rating scales, sleep monitors, and laboratory tests will be used to observe the clinical effect. From the perspective of the circadian secretion of peripheral blood-related hormones in the hypothalamic-pituitary-adrenal (HPA) axis, the possible mechanism of acupressure wrist-ankle straps for treating insomnia is studied. Discussion The results of this study will confirm the efficacy of acupressure wrist-ankle strap in treating mild insomnia patients with anxiety disorder and whether its mechanism is related to the HPA axis. The acupressure wrist-ankle strap may become a pure physical, no side effect treatment of mild insomnia. Trial registration Chinese Clinical Trial Registry ChiCTR2000039352. Registered on 24 October 2020.

Background. Many associations between tongue fur and different physiological and biochemical indexes have been revealed. However, the relationship between tongue fur and tumor markers remains unexplored. Methods. We collected the medical examination reports of 1625 participants. Participants were residents of Chengdu, China, undergoing routine health checkups at the health management center of the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine between December 2018 and September 2020. The participants’ tongue fur thickness was measured using the DAOSH four-diagnostic instrument. Tumor marker levels, including t-PSA, AFP, CEA, CA125, and CA199, were measured in the clinical laboratory. Curve-fitting and multivariable logistic regression were used to analyze the association between tongue fur thickness and tumor marker abnormality. Results. Curve-fitting showed that the relationship between tongue fur thickness and abnormal tumor marker rate was nonlinear, similar to a U shape. As the tongue fur thickness value increased, the abnormal tumor marker probability initially decreased and then increased. Logistic regression showed that, in the crude model, compared with the thin tongue fur group, the odds ratios (ORs) and 95% confidence intervals (CIs) of the less or peeling tongue fur group and thick tongue fur group for tumor marker abnormality were 1.79 (1.02–3.17) and 1.70 (1.13–2.54), respectively. After adjusting gender, age, body mass index (BMI), smoking history, drinking history, tongue color, the form of the tongue, and fur color, the ORs and 95% CIs of the less or peeling tongue fur group and thick tongue fur group were 1.93 (1.04–3.57) and 1.82 (1.17–2.81), respectively. Conclusions. Excessive or very little tongue fur is associated with tumor marker abnormality. Further cross-sectional studies are needed to evaluate the clinical value of tongue fur for cancer diagnosis and screening.

Background: Insomnia is very common in current society, and patients are often accompanied by a certain degree of anxiety, depression, etc. Recent studies have found that the hypothalamic-pituitary-adrenal (HPA) axis excitement-inhibition state is an important indicator of sleep quality. Wrist-ankle acupuncture (WAA) is safe and effective for insomnia. The acupressure wrist-ankle straps, based on WAA theory, is a portable WAA point compression strap, which can treat diseases by automatically applying pressure to the treatment location and be operated by patients themselves. We design this trial to evaluate the clinical effect of the acupressure wrist-ankle strap in the treatment of mild insomnia patients with anxiety disorders. Methods/design: This trial is a parallel-design, patients-assessor blinded, randomized, sham-controlled. In total, 108 patients diagnosed with mild insomnia patients with anxiety disorders will be randomly equally assigned into two groups, acupressure wrist-ankle strap group or non-acupressure wrist-ankle strap group; they will receive treatments for 8 weeks with 5 sessions each week. Rating scales, sleep monitor and laboratory tests will be used to observe the clinical effect. From the perspective of the circadian secretion of peripheral blood-related hormones in the hypothalamic- pituitary- adrenal (HPA) axis, the possible mechanism of acupressure wrist-ankle straps for treating insomnia is studied.Discussion: The results of this study will confirm the efficacy of acupressure wrist-ankle strap combined with CBTI in the treatment of mild insomnia patients with anxiety disorder and whether its mechanism is related to HPA axis. The acupressure wrist-ankle strap may become a pure physical, no side effect treatment of mild insomnia.Trial registration: Chinese Clinical Trial Registry (identifier: ChiCTR2000039352; registration date: 24 October 2020).

Background: From the traditional Chinese medicine (TCM) constitution theory perspective, the phlegm-dampness constitution is thought to be closely related to the occurrence of non-alcoholic fatty liver disease (NAFLD). However, this viewpoint still lacks rigorous statistical evidence. This study aimed to test the association between the phlegm-dampness constitution and NAFLD.Methods: We conducted a cross-sectional study. Participants were residents living in Chengdu, China, undergoing health checkups at the health management center of Affiliated Hospital of Chengdu University of Traditional Chinese Medicine between December 2018 and September 2020. TCM constitution type was diagnosed by DAOSH four examinations instrument, NAFLD was diagnosed according to the liver ultrasonography and medical history. Multivariate logistic regression and propensity score matching (PSM) were used to analyze a total of 1,677 qualified data.Results: 1,037 participants had biased constitution(s), 67.8% of which had mixed constitutions (with at least two constitutions). Among 1,677 participants, the phlegm-dampness constitution was associated with the yang-deficiency, yin-deficiency, dampness-heat, qi-depression, and blood-stasis constitutions. The correlation coefficients were 0.11, 0.32, 0.42, 0.20, 0.14, respectively. Between the phlegm-dampness constitution and NAFLD, the odds ratio (OR) and the 95% confidence interval (CI) was 2.05 (1.57–2.69) in the crude model. After adjusting for age, gender, Body mass index (BMI), other biased constitutions, smoking, high blood pressure, diabetes, and dyslipidemia, the OR reduced to 1.51 (1.04–2.18). The associations of seven other biased TCM constitutions and NAFLD were not statistically significant in the fully adjusted model. The PSM analysis showed consistent results with the logistic regression.Conclusions: Among eight biased TCM constitutions, the phlegm-dampness constitution is independently associated with NAFLD. We speculate the phlegm-dampness constitution is a risk factor of NAFLD. Longitudinal studies are needed to confirm this causal relationship in the future. In addition, inconsistent with some TCM practitioners' experience, we disagree that the blood-stasis constitution is associated with NAFLD.

Cutaneous malignant melanoma (CMM) ranks the most lethal skin cancer worldwide. However, other risk factors have been hardly explored, aside from ultraviolet radiation (UVR). Polychlorinated biphenyls (PCBs) were implied to be potential risk factors for CMM, although all the evidence was obtained from the western countries. This study examined the relationships between plasma levels of PCBs and CMM risk adjusting for sun sensitivity and sun exposure in a Chinese population, using a case-control study, including 450 CMM cases and 500 healthy controls. Plasma levels of a total of 33 PCB congeners were assayed in both cases and controls. Our results showed that there was a significant association between total summed PCB level and CMM risk, with a 1.44-fold increased risk for those in the highest quartile compared to those in the lowest quartile (OR = 1.44, 95% CI: 1.02–2.03, P for trend = 0.031). Significantly increased ORs were also observed for individual PCB congeners (PCB52, PCB170 and PCB180). These associations persisted after control for sun sensitivity and sun exposure. Our study represents the first evidence conducted in Asians, and does support the hypothesis that PCB exposure increases CMM risk. Keywords: Polychlorinated biphenyls, Cutaneous malignant melanoma, Plasma, Case-control study

Background Physical activity is an important part of the diabetes management plan. However, the effects caused by different training durations and styles of Tai Chi have not been evaluated. We conducted an updated systematic review of the effects of Tai Chi on patients with type 2 diabetes based on different training durations and styles. Methods We performed a search for Chinese and English studies in 8 databases. Two reviewers independently selected the eligible trials and conducted a critical appraisal of the methodological quality. Results Seventeen trials were included. Tai Chi was found to have reduced fasting blood glucose (FBG) [SMD = − 0.54, 95% CI (− 0.91, − 0.16), P = 0.005] and HbA1c [SMD = − 0.68, 95% CI (− 1.17, − 0.19), P = 0.006] overall, compared with a control group. Considering the subgroup analysis, the pooled results showed that 24 movements or Yang-style Tai Chi did not significantly reduce FBG after a duration of ≤3 months [SMD = − 0.46, 95% CI (− 1.42, 0.50), P = 0.35] or > 3 months [SMD = − 0.50, 95% CI (− 1.49, 0.49), P = 0.32], nor did it reduce HbA1c [SMD = − 1.22, 95% CI (− 2.90, 0.47), P = 0.16] after a duration > 3 months in all studies. However, other styles of Tai Chi significantly reduced FBG [SMD = − 0.90, 95% CI (− 1.28, − 0.52), P 3 months, while no significant reduction in FBG [SMD = − 0.34, 95% CI (− 0.76, 0.08), P = 0.12] or HbA1c [SMD = − 0.34, 95% CI (− 0.76, 0.08), P = 0.12] was found after a duration ≤3 months. Conclusions Tai Chi seems to be effective in treating type 2 diabetes. Different training durations and styles result in variable effectiveness. The evidence was insufficient to support whether long-term Tai Chi training was more effective.

Since object motion and camera shake can cause motion blur, there are some blurry frames in the captured videos by hand-held camera. In order to solve the above problem, we propose a nonuniform video deblurring method that combines weighted curvelet accumulation with motion vector duty cycle. In the proposed method, firstly we propose a weighted curvelet accumulation method that can synthesize the multiple adjacent frames in the frequency domain for estimating the initial latent sharp frame. Secondly, because the duty cycle has a close relation with the accuracy of the blur kernel, we propose a motion vector duty cycle estimation method by utilizing the inter-frame correlation information and the estimated initial latent sharp frame to improve the blur kernel accuracy. Finally, we build a novel nonblind video deblurring model by fully utilizing the spatiotemporal information and the estimated blur kernel for obtaining the deblurred frame. Experimental results on the numerous videos show that the proposed method achieves the state-of-the-art results either in subjective vision or in objective evaluation.

It is of great importance to capture long-range dependency in image deblurring based on deep learning. Existing methods often capture long-range dependency by a large receptive field, which contributes by deep stacks of local convolutional operations. Therefore, it restricts network representation ability and causes unpleasant artifacts of restored images. In this paper, we propose a deep pyramid generative adversarial network with local and nonlocal similarity features, called LNL-PGAN, for natural motion image deblurring. First, we propose a nonlocal feature block as an essential component of the pyramid generator for obtaining nonlocal similarity features at multiple levels. Second, we design a local feature block as another essential component to make a great balance between local and nonlocal similarity features. The local and nonlocal feature blocks capture meaningful short-range and long-range dependencies in the pyramid generator to increase network representation ability. Third, we design a multiscale generative adversarial loss to preserve edge details and facilitate sharp edge prediction of restored images, and we introduce a multistage training strategy to facilitate network training, which can further improve the quality of the restored image. Extensive experimental results demonstrate that the proposed method yields superior performance against state-of-the-art methods on natural motion image deblurring in terms of visual quality and objective index, and it can be used as a unified network for single and dynamic motion image deblurring.

Traditional Chinese medicine (TCM) is effective in preventing and treating all manner of diseases, which has been incorporated into the latest global medical outline (Ver.2019) by World Health Organization (WHO). As one of the most important characteristics of TCM, syndrome differentiation (SD) provides curative effect assurance. SD is a high-dimensional complex function with symptoms/signs as input and syndrome type as output. Artificial neural network (ANN) provides an all-purpose data-driven solution to fit high-dimensional complex function, making ANN a promising approach for modeling intelligent SD (ISD) for TCM. In this paper, we chose chronic obstructive pulmonary disease (COPD) as an example for investigating ISD for TCM based on ANN. First, we built a full-group ANN model that combines ANN with full-group datasets composed of 18471 real clinical records. In addition, we built four extra models with ANN and four subgroup datasets. For comparison, we built another four models with four traditional machine-learning algorithms and the full-group datasets. We used accuracy and F1-scores to evaluate the models' performance. With an accuracy of 86.45% and an F1 score of 82.93%, the full-group ANN model outperformed the four comparison models built from traditional machine-learning algorithms, and however, the four subgroup models achieved a better performance than the full-group ANN model. We concluded that the ANN can potentially provide a way for ISD for TCM, and our subgroup modeling suggests ideas for further optimizing the ISD.

ObjectiveCinnamon is a cooking spice and a medicinal herb. It is increasingly used as a health supplement due to its perceived benefit to prevent and or manage type 2 diabetes and metabolic disorders. However, it is unclear if regular consumption of this medicinal plant will interfere with normal physiological functions. Therefore, this study investigated the impact of daily cinnamon supplements on glucose and lipid metabolic profiles in healthy rats.MethodsMale rats (Sprague Dawley, 8 weeks) were supplied with cinnamon in their diet (equivalent to ∼1 g/day in humans) for two weeks. Blood glucose and lipid levels, as well as metabolic markers in both liver and abdominal white adipose tissue, were measured.ResultsCinnamon significantly increased fat mass and blood cholesterol and low-density lipoprotein (LDL) levels, but reduced fasting blood glucose level by 12%. Liver functional enzymes were normal in rats consuming cinnamon. However, several lipid metabolic markers were impaired which may contribute to dyslipidemia, including two main switches for energy metabolism (sirtuin 1 and peroxisome proliferator-activated receptor-gamma coactivator-1α) and the LDL receptor. However, de novo lipid synthesis enzymes and inflammatory markers were also reduced in the liver by cinnamon treatment, which may potentially prevent the development of steatosis. Markers for lipid oxidation were downregulated in fat tissue in cinnamon-treated rats, contributing to increased fat accumulation.ConclusionDaily low-dose cinnamon supplementation seems to promote abdominal adipose tissue accumulation and disturb lipid homeostasis in healthy rats, raising the concerns regarding daily use in healthy people.

Forest surveillance towers have the advantages of long observation time, wide observation range, stable and real-time observation. In this paper, a multi-scale proposal regions fusion network (MFRPN) is proposed for detecting the infected trees automatically on the enhanced images from the forest surveillance towers, which can solve the problem that small and large targets can’t be effectively detected on a single scale. The proposed MFRPN includes multi-scale images, three CNNs, three different RPNs, and proposal regions fusion model. In the proposed method, we train and run the scale-specific detectors in a multi-task fashion. And, to obtain the accurate spatial level location information of the infected trees, we achieve the three-dimensional (3D) coordinates localization of the digital elevation model (DEM) by using the principle of forest surveillance towers imaging and terrain elevation data. The experimental results show the detection accuracy achieves 91.63%, the detection time of a single image is 0.46 second, and the 3D localization error is less than 50m. The proposed network can realize the real-time detection and 3D localization of the infected trees.

Background Thyroid nodules (TN) are discrete lesions within the thyroid gland and are a common clinical problem detected in 19% to 68% of people. TN are more common as age increases and occur more frequently in women. TN can cause pressure symptoms, cosmetic complaints, and thyroid dysfunction. Treatment for benign thyroid nodules includes thyroid hormone therapy, surgery, radioiodine treatment, percutaneous ethanol injection therapy, and laser or radiofrequency treatment to shrink nodules. In China and many other countries, doctors use Chinese herbal medicines (CHM) to treat TN. However, systematic review and meta-analysis has not been found to assess the effects and safety of CHM in curing TN at present. Hence, the systematic review is conducted to scientifically and methodically evaluate the value of its effectiveness and safety of CHM on TN. Methods Literatures related to CHM for TN from the establishment of the database to November 2020 will be retrieved from the following databases: PubMed, Excerpta Medica Database (EMBASE), MEDLINE, Web of Science, Cochrane Library, SpringerLink, WHO International Clinical Trials Registry Platform (ICTRP), Wanfang Database, China National Knowledge Infrastructure (CNKI), Chinese Biomedical Literature Database (CBM), and Chinese Scientific Journal Database (VIP). There are no language restrictions for retrieving literatures. Case reports, animal studies, editorials, expert opinions, reviews without original data, and studies on pediatric population were excluded. Eligible randomized clinical trials (RCTs) evaluating the effectiveness and safety of CHM in TN patients will be put in the study including nodule volume reduction ≥50%, pressure symptoms, cosmetic complaints, quality of life, and adverse events. By scanning the titles, abstracts and full texts, 2 reviewers will independently select studies, extract data, and assess the quality of study. Meta-analysis of RCTs will be conducted using Review Manager 5.1 software. The results will be presented as risk ratio for dichotomous data, and standardized or weighted mean difference for continuous data. Result This study will provide high-quality available evidence for the treatment of TN with CHM based on nodule volume reduction ≥50%, pressure symptoms, cosmetic complaints, quality of life, and adverse events. Conclusion The systematic review will to evaluate the efficacy of CHM in treating benign thyroid nodules in adults and provide evidence for clinicians. Inplasy registration number INPLASY2020120093.

Background: Diabetic peripheral neuropathy (DPN) is 1 of the most common clinical complications of diabetes, which seriously affects the quality of life of patients and causes a substantial economic burden on diabetes care. The pathogenesis of DPN is complex. There is no targeted treatment method, and mainstream treatment methods have low efficacy and large side effects. Traditional Chinese medicine has rich clinical experience in the prevention and treatment of diabetic peripheral neuropathy, which has dramatically improved the quality of life of patients. It is clinically proven that traditional Chinese medicine fumigants (TCMF) have apparent effects in treating diabetic peripheral neuropathy. Therefore, we aim to systematically review the effectiveness and safety of TCMF for DPN. Methods: We will search the following databases: PubMed, Embase, Cochrane Library, MEDLINE, the China National Knowledge Infrastructure, the Chinese Biomedical Literature Database, Cqvip Database, and Wanfang Data. Besides, we will also search for clinical trial registrations, potential grey literature, relevant conference abstracts, and reference lists of established studies. The studies published from the inception of the database to November 2020 will be retrieved. The randomized controlled trials on TCMF for DPN will be included. Also, we will search for clinical trial registrations, potential grey literature, relevant conference abstracts, and reference lists of established studies. The main result is clinical efficacy and nerve conduction velocity. Fasting blood glucose, 2 hours postprandial blood glucose, blood lipid, glycosylated hemoglobin, and adverse events are secondary results. We will perform the analyses using RevMan V.5.3 software. Results: This study will provide a high-quality comprehensive evaluation of the efficacy and safety of TCMF in the treatment of DPN. Conclusions: This systematic review will evaluate the effectiveness and safety of TCMF in the treatment of DPN, and provide the latest evidence for clinical application. INPLASY registration number: INPLASY2020110137.

Background Conflicting results have been reported regarding the effect of metformin on adiponectin levels in women with polycystic ovary syndrome (PCOS). This meta-analysis reviewed all studies comparing adiponectin levels before and after metformin treatment in PCOS women. Additionally, changes in other indicators, including long-term complications associated with PCOS, such as inflammatory, metabolism factors and hormonal profile, were investigated following metformin treatment. We conducted subgroup analysis based on body mass index (BMI) stratification and appropriate pooling. Methods We searched literature in PUBMED, EMBASE, the Cochrane Library, and CNKI databases. The main meta-analysis included 11 studies containing data on 353 subjects. Results Metformin treatment was associated with significantly increased serum adiponectin concentrations [10 studies, random-effects SMD (95% CI) −0.58 [-1.03, −0.13]; I2 = 86%; P = 0.01]. Additionally, the meta-analysis revealed that circulating tumor necrosis factor-α(TNF-α) and C-reactive protein (CRP) concentrations were significantly decreased after metformin treatment, with corresponding SMDs of 1.01 (95% CI: 0.74–1.28, P＜0.00001) and 0.48(95% CI: 0.35–0.60, P＜0.00001). Conclusion Following metformin administration, serum adiponectin concentrations of PCOS women were found to be significantly increased, accompanied by a significant improvement in other indicators. Further investigation with a larger sample size should be conducted to validate optimal dose and duration of metformin.

Most of the data in agriculture and forest obey heavy-tailed distribution, in which the data distribution is extremely imbalanced and the amount of most classes is poor. In this paper, we propose a feature centroid based dynamic feature weighting method between head and tail classes for mangrove pest images classification. In the proposed method, firstly, we design a convolutional neural network to extract the clustering centroid as a representation of the subclass. Secondly, we use the centroid feature memory to achieve the dynamic feature weighting through extraction, injection and fusion, which enrich the feature space of the tail classes while retaining identity. Thirdly, to localize the pests in natural background, we optimize the weakly-supervised localization algorithm with a multiscale local maximum index strategy to extract saliency maps. Furthermore, to carry out our research we establish a heavy-tailed distributed image dataset named MIPDGC based on mangrove forest pest. The experimental results prove that the dynamic feature weighting method can obtain higher classification accuracy and better performance than other general methods on the classification accuracy of the MIPDGC.

Background: Aging is a phenomenon that human's physiology and psychology is progressive decline for natural environment. Health Qigong, as a convenient and effective exercise therapy,is widely used for anti-aging. However, there are no systematic reviews or meta-analysises to evaluate the efficacy and safety of Health Qigong on anti-aging. Methods: We will systematically search for 7 English databases(PubMed, Excerpta Medica Database, MEDLINE, Web of Science, Cochrane Library, SpringerLink, and WHO International Clinical Trials Registry Platform) and 4 Chinese databases(namely the China National Knowledge Infrastructure Database, the Wanfang Database, the Chinese Scientific Journal Database, and the Chinese BioMedical Literature Database) from their inceptions to August 2020. Randomized controlled trials (RCTs) using Health Qigong to anti-aging will be included. After the selection and extraction of eligible studies, a meta-analysis will be undertaken to assess the efficacy and safety of Health Qigong on anti-aging. Moreover, study selection, data extraction, and the evaluation of the methodological quality of trials will each be independently completed by at least 2 researchers. The Review Manager Software V.5.3 will be employed for meta-analysis to assess the risk of bias, data synthesis, and subgroup analysis. Results: This review will provide the latest knowledge and evidence on the efficacy and safety of Health Qigong for anti-aging through the analysis of various evaluation scales. Conclusion: The conclusion of this review will help clinicians provide effective exercise therapy for anti-aging. Registration number: INPLASY202090017

Resembling the role of disease diagnosis in Western medicine, pathogenesis (also called Bing Ji) diagnosis is one of the utmost important tasks in traditional Chinese medicine (TCM). In TCM theory, pathogenesis is a complex system composed of a group of interrelated factors, which is highly consistent with the character of systems science (SS). In this paper, we introduce a heuristic definition called pathogenesis network (PN) to represent pathogenesis in the form of the directed graph. Accordingly, a computational method of pathogenesis diagnosis, called network differentiation (ND), is proposed by integrating the holism principle in SS. ND consists of three stages. The first stage is to generate all possible diagnoses by Cartesian Product operated on specified prior knowledge corresponding to the input symptoms. The second stage is to screen the validated diagnoses by holism principle. The third stage is to pick out the clinical diagnosis by physician-computer interaction. Some theorems are stated and proved for the further optimization of ND in this paper. We conducted simulation experiments on 100 clinical cases. The experimental results show that our proposed method has an excellent capability to fit the holistic thinking in the process of physician inference.

Object detection is one of the core technologies in aerial image processing and analysis. Although existing aerial image object detection methods based on deep learning have made some progress, there are still some problems remained: (1) Most existing methods fail to simultaneously consider multi-scale and multi-shape object characteristics in aerial images, which may lead to some missing or false detections; (2) high precision detection generally requires a large and complex network structure, which usually makes it difficult to achieve the high detection efficiency and deploy the network on resource-constrained devices for practical applications. To solve these problems, we propose a slimmer network for more efficient object detection in aerial images. Firstly, we design a polymorphic module (PM) for simultaneously learning the multi-scale and multi-shape object features, so as to better detect the hugely different objects in aerial images. Then, we design a group attention module (GAM) for better utilizing the diversiform concatenation features in the network. By designing multiple detection headers with adaptive anchors and the above-mentioned two modules, we propose a one-stage network called PG-YOLO for realizing the higher detection accuracy. Based on the proposed network, we further propose a more efficient channel pruning method, which can slim the network parameters from 63.7 million (M) to 3.3M that decreases the parameter size by 94.8%, so it can significantly improve the detection efficiency for real-time detection. Finally, we execute the comparative experiments on three public aerial datasets, and the experimental results show that the proposed method outperforms the state-of-the-art methods.

Background Yangyin Fuzheng Jiedu Prescription (YFJP) is a traditional Chinese medicine (TCM) indicated for the treatment of hepatocellular carcinoma (HCC). Its potential targets and molecular mechanisms are not clear. Therefore, this study intends to explore the molecular mechanism of YFJP based on network pharmacology analysis and in vitro validation. Methods and results Through univariate and multivariate analyses and survival analysis in HCC patients with or without YFJP treatment we found that drinking alcohol, alfafeto protein ≥ 400 ng/l, baseline portal vein tumor thrombus and total bilirubin level ≥ 18.8 μM) were independent risk factors for poor prognosis, while red blood cell count ≥ 4 × 109/l and TCM treatment were independent protective factors. Besides, YFJP prolonged the cumulative survival of HCC patients. Using online pharmacological methods, we obtained 58 relevant compounds and molecular 53 targets. By using scratch test, Transwell assay, EdU assay, and TUNEL staining, we found that YFJP-containing serum repressed the migration, invasion and proliferation of HCC cells in vitro, and induced cell apoptosis. Moreover, YFJP diminished the gene expression of TP53, CCND1, p-EGFR, EGF, VEGFA, JUN, IL6, COX-2, AKT1, and MAPK1 in HCC cells, but elevated the expression of ESR1 and CASP3. Conclusions Taken together, results showed that YFJP attenuated HCC progression through mediating effects on HCC-related genes.

Summary Obesity is an important risk factor and a potential treatment target for hepatic steatosis. The maladaptation of hepatic mitochondrial flexibility plays a key role in the hepatic steatosis. Herein, we found that hepatocyte-like cells derived from human adipose stem cell of obese patients exhibited the characteristics of hepatic steatosis and accompanied with lower expression of the subunits of mitochondrial complex I and lower oxidative phosphorylation levels. The GSK3 inhibitor CHIR-99021 promoted the expression of NDUFB8, NDUFB9, the subunits of mitochondrial complex I, the basal oxygen consumption rate, and the fatty acid oxidation of the hepatocytes of obese patients by upregulating the expression of the transcription factor PGC-1α, TFAM, and NRF1 involved in mitochondrial biogenesis. Moreover, CHIR-99021 decreased the lipid droplets size and the triglyceride levels in hepatocytes of obese patients. The results demonstrate that GSK3 inhibition ameliorates hepatic steatosis by elevating the mitochondrial function in hepatocytes of obese patients., Graphical abstract, Highlights • Obese patients’ adipose-stem-cell-derived hepatocytes reveal hepatic steatosis • Hepatic steatosis is accompanied the mitochondrial dysfunction • The mitochondrial dysfunction is governed by the low expression PGC-1α, TFAM, and NRF1 • GSK3 inhibitor ameliorates hepatic steatosis via mitochondrial dysfunction modulation, human metabolism; molecular biology

BackgroundThis paper developed and described a risk-based quality control approach of clinical trials for clinical trial sites to improve the quality control process and ensure the quality of data.Methods Based on the trial experience, well versed experts and the findings of previous literature, an integrated risk-based quality control approach is developed centered on three cornerstones: risk assessment, central data review, and triggered, adaptive on-the-spot or remote inspection.Results We have developed an innovative risk-based quality control approach for clinical trials including risk assessment, development of quality control plan, implementation of quality control activities, development and review of quality control report, undertake actions arising from quality control report, and the update of risk assessment results or quality control plan, which fuses the idea of PDCA circle and quality by design.Conclusion Our RBQC methodology can significantly improve the clinical quality control process and the monitoring-audit triggered procedure can synchronize the activities of site, sponsor and CROs to achieve all-win. It is an innovative and effective approach.

Internet finance is advantageous to improve financial market competition, enhance capital allocation efficiency and decrease financial service costs. Moreover it makes up the deficiencies of the traditional finance on the aspects of satisfaction of the wider populations on financial demands, enhancement of financial inclusiveness and improvement of financial service efficiency. However Internet finance is also a double-edged sword. As a new pattern and new mode in the financial field, the prevailing laws, policies and regulatory systems can not completely cover the risk vulnerabilities of internet finance. This paper adopted the fuzzy analytic hierarchy process and five quantitative representative influential factors to compare the risk. According to the empirical analysis, the first higher risk in the current internet finance of China is credit risk; following which, the risks are the business risk, legal risk and operational risk; therefore it is very necessary to launch effective regulation and supervision on the risks of Chinese internet finance from multiple aspects, such as credit system, laws and regulations, regulatory systems so as to promote the mutual development of internet finance and traditional finance; this is the core issue of Chinese internet finance development.

With the development of deep learning technology, an enormous number of convolutional neural network (CNN) models have been proposed to address the challenging building extraction task from very high-resolution (VHR) remote sensing images. However, searching for better CNN architectures is time-consuming, and the robustness of a new CNN model cannot be guaranteed. In this paper, an improved boundary-aware perceptual (BP) loss is proposed to enhance the building extraction ability of CNN models. The proposed BP loss consists of a loss network and transfer loss functions. The usage of the boundary-aware perceptual loss has two stages. In the training stage, the loss network learns the structural information from circularly transferring between the building mask and the corresponding building boundary. In the refining stage, the learned structural information is embedded into the building extraction models via the transfer loss functions without additional parameters or postprocessing. We verify the effectiveness and efficiency of the proposed BP loss both on the challenging WHU aerial dataset and the INRIA dataset. Substantial performance improvements are observed within two representative CNN architectures: PSPNet and UNet, which are widely used on pixel-wise labelling tasks. With BP loss, UNet with ResNet101 achieves 90.78% and 76.62% on IoU (intersection over union) scores on the WHU aerial dataset and the INRIA dataset, respectively, which are 1.47% and 1.04% higher than those simply trained with the cross-entropy loss function. Additionally, similar improvements (0.64% on the WHU aerial dataset and 1.69% on the INRIA dataset) are also observed on PSPNet, which strongly supports the robustness of the proposed BP loss.

The electric shock has been proposed as one of the new needling sensations in recent years. In acupuncture sensation scales, the electric shock is included by ASS and SNQS, but not SASS, MASS, and C-MMASS. Some scholars argue that the electric shock is a normal needling sensation, but some researchers do not agree with this view. This problem has not been resolved due to a lack of evidence from basic research. Literature and research point out that the electric shock is caused by inserting a needle into the nerve directly. A question of considerable scientific and practical interest is whether the electric shock should be a normal needling sensation. In this article, we review the historical documentation of the needling sensation and the process of formulating and improving acupuncture sensation scales to suggest that the electric shock may not be a normal needling sensation. Secondly, we collected and analyzed cases of nerve injury caused by acupuncture accompanied by the electric shock and why acupuncture caused the electric shock without nerve injury. It suggests that there may be a correlation between the electric shock and peripheral nerve injury, and acupuncture manipulation is an essential factor in adverse acupuncture events. Finally, we put forward that the electric shock during acupuncture is a warning sign that the peripheral nerve may be injured, rather than a normal needling sensation. In the future, we hope to have experimental studies on the mechanism of the electric shock or observational studies on the correlation between the electric shock and peripheral nerve injury to verify.

In this paper, considering that the trained dictionary pairs by sparse coding based super-resolution (SR) methods have difficulty capturing the complicated nonlinear relationships between the low-resolution (LR) and high-resolution (HR) feature spaces, we propose a new single image SR method by combining sparse coding with the improved structured output regression machine (SORM). In the proposed method, the dictionary pairs are firstly learned by joint sparse coding to characterize the structural domain of each feature space and add more consistency between the sparse codes of two feature spaces. Then, since the classical SORM does not give sufficient weight to the independence of different output components, we improve the SORM by considering the correlation and independence between different output components to establish a set of mapping functions for tying the sparse code of two feature spaces. With this, the more precise mapping relationships between two feature spaces are obtained by the trained dictionary pairs and mapping functions. Moreover, we propose a new global and nonlocal optimization for further enhancing the quality of the restored HR images. Extensive experiments validate that the proposed method can achieve convincing improvement over other state-of-the-art methods in terms of the reconstruction quality and computational cost.

Adiabatic film cooling effectiveness on a flat plate surface downstream a row of simple and compound angle holes was investigated using high-resolution pressure sensitive paint (PSP) technique. A variation of flow parameters including density ratio and blowing ratio, and geometry parameters including compound angle and length-to-diameter ratio were examined. Blowing ratios (M) ranging from 0.3 to 2, density ratio (DR) are 1.0 and 1.5, length to diameter ratios (L/D) from 0.5 to 5 and two compound angle (β: 0°, 45°) were employed composing a test matrix of 140 test cases. Discharge coefficient was measured with varied blowing ratio and L/D values for simple and compound angle hole. Detailed local, laterally averaged, and area averaged film effectiveness are presented to illustrate the effect of length-to-diameter ratio and compound angle. It was found that the effect of density ratio on the film cooling effectiveness was associated with the blowing ratio. Increasing density ratio provides a negative effect when the M ≤ 0.5 for simple and compound angle hole, which a positive effect when the M > 0.5. Also found was that the film effectiveness was highest when L/D = 0.5 and 1, regardless of blowing ratio and compound angle. The film cooling effectiveness of simple angle hole increased as L/D increased from 2 to 5 when M ≤ 1, while showed a minimum value at L/D = 3.5 when M ≥ 1. The film cooling effectiveness of compound angle hole showed a minimum value at L/D = 3.5 regardless of blowing ratio. The scaling methods of film effectiveness with velocity ratio, blowing ratio, and momentum flux ratio were also discussed for simple angle and compound angle holes with varying L/D.

Compound angle hole film cooling with varying length-to-diameter ratio and internal crossflow orientations is investigated by large eddy simulation (LES). The film density ratio is 1.5, and the blowing ratio ranges from 0.4 to 1.2. The compound angle of 45° and three length-to-diameter ratios (L/D) from 0.5 to 5 are chosen for the simulations. In addition to the vertical inflow through the plenum, internal crossflow orientations that are perpendicular to and parallel to the mainstream flow are investigated. The prediction accuracy is validated by the reported hydrodynamic data and present film effectiveness data measured by pressure sensitive paint (PSP). Results show that compound angle hole film effectiveness generally shows a decreasing trend as length-to-diameter ratio increases, which is contrary to the cylindrical hole. This is associated with the fact that length-to-diameter ratio influences the in-tube flow behavior, formation of Kelvin-Helmholtz (K-H) structures, and development of single asymmetric main vortex (SAMV). The internal crossflow orientation is demonstrated to have a significant effect on the in-tube flow behavior and the film cooling effectiveness. The perpendicular-counter flow and parallel-inline flow cases are found to provide more uniform hole exit velocity distributions than other internal crossflow orientations and vertical inflow case. Also found is that uniform hole exit velocity distribution provides favorable influence on the film effectiveness.

The impacts of climate change on the water environment have aroused widespread concern. With global warming, mountainous basins are facing serious water supply situations. However, there are limited meteorological stations on mountains, which thus creates a challenge in terms of accurate simulation of streamflow and water resources. To solve this problem, this study developed a method to model streamflow in data-scarce mountainous basins. Selecting the two head waters originating in the Tienshan mountains, Aksu and Kaidu Rivers, we firstly reconstructed precipitation and temperature dynamics based on Earth system data products, and then integrated the radial basis function artificial neural network and complete ensemble empirical mode decomposition with adaptive noise to model streamflow. Comparison with the observed streamflow according to hydrological stations indicated that the proposed approach was highly accurate. The modeling results showed that the El-Nino Southern Oscillation, temperature, precipitation, and the North Atlantic Oscillation are the main factors driving streamflow, and the streamflow decreased in both the Aksu River and Kaidu River between 2000 and 2017.

Asthma can be complex and difficult to manage. Patients often seek alternative treatment options, including Traditional Chinese Medicine (TCM). The paradigms that inform TCM treatments include a philosophy focusing on modifying the whole body status ('bian zheng') to treat the lungs. TCM practitioners use personalized treatment plans based on clusters of clinical patterns (eg. cold-related wheezing, kidney insufficiency/energy-deficiency-related wheezing). TCM includes herbal remedies and non-oral therapies such as cupping, acupuncture, and massage. The efficacy of TCM treatments of asthma is not well described as the majority of studies are published only in Chinese literature. We reviewed all available clinical trials in CNKI, Chaoxin, Wanfang, CQVIP, Springer-link, Science Direct, and Pubmed. Papers in Chinese were translated by dual lingual TCM and Western medicine doctors. Based on the identified studies, TCM is a safe additive treatment to Western medicine that can improve both symptoms and quality of life for patients with asthma.

Spatially varying motion deblurring has recently witnessed substantial progress due to the development of deep neural network. However, most existing CNN-based methods involve two major shortcomings: (1) The CNN weights are space-sharing, and these methods thus ignore the properties of complex spatially variant blurs which vary from pixel to pixel in natural blurry images. (2) Stacked convolution layers with a large kernel or recurrent neural networks (RNNs) cannot capture the global contextual dependence of features, they thus cannot exploit the relationship between different blur pixels at a distance. To solve these problems, we propose a new dual attention per-pixel filter network (DAPFN). First, we develop a multiscale per-pixel filter network (MSPFN) to learn a specific deblurring mapping for different blur pixels, which predicts the per-pixel spatially adaptive convolution kernel for each blur pixel in the input blurry image of different scales and restores the clean pixel by performing channel-wise spatially adaptive convolution with the local neighborhood pixels. Second, we develop a dual attention enhanced residual network (DAERN) to capture the global contextual dependence of the blurry images, which introduces a dual attention (DA) module consisting of the spatial self-attention module (SSA) and channel self-attention module (CSA). The fusion of the two attention modules helps to further improve the deblurring performance. Third, we propose a new receptive field selection (RFS) block to learn the nonlinear characteristics of spatially variant blurs, which enables the adaptive fusing of the features with different receptive fields and effectively enhances the network nonlinear representation ability. The experimental results on GOPRO dataset indicate that the average PSNR and SSIM of the proposed method reached 31.8455 and 0.9231, respectively. The results of extensive experiments pertaining to spatially varying image deblurring demonstrate that the proposed method outperforms the state-of-the-art image deblurring methods.

Summary Surface fogging reduces light transmission of optically clear materials and causes various problems in daily life. Transparent photothermal materials have recently emerged as an eco-friendly and sustainable solution to surface fogging. However, most reported photothermal materials only exploited the broadband spectrum of solar energy, and the spectral feature has yet to be tuned to optimize the visibility and photothermal effect simultaneously. Here, we develop a highly transparent, photothermally selective coating, based on solution-processed cesium-doped tungsten trioxide nanoparticles. The transparent selective photothermal coating provides a visible transmittance up to 82% and a high absorption of ultraviolet and near-infrared light >90%, and achieves a temperature increase by 38°C under 1-sun illumination, resulting in remarkable antifogging and defogging abilities under extremely frigid or humid conditions. Large-scale complex surfaces with photothermal coatings are deployed in field antifogging tests as well as long-term durability tests, showing their great potential in antifogging applications.

The feature extraction of training images can make the subdictionaries contain the image texture structures.The edge difference is explored and used to preserve the edge structures of images.The nonlocal structure tensor optimization model with a new weight calculation can further improve the image quality. Sparse representation based nonlocal self-similarity methods have been proved to be effective for single image super-resolution. However, as the noise level increases, these methods always lead to the aggravated blurring of image small scale structures, which means the failure to preserve the edge structures. In this paper, we propose a new single image super-resolution method by combining edge difference with nonlocal self-similarity constraints. In the proposed method, firstly, we extract the image texture feature in the main direction for dictionary learning with Principal Components Analysis (PCA) to ensure the learned subdictionaries contain the image texture structures. Then, we explore the one dimensional edge difference between LR image and degraded version (e.g., blurred, noisy, and down-sampled) of the image reconstructed by the sparse representation based nonlocal self-similarity method with the leaned PCA subdictionaries and utilize it as the edge difference constraint. Thirdly, we incorporate the edge difference constraint into the sparse representation model based nonlocal self-similarity to preserve the edge structures and nonlocal self-similarity structures simultaneously. Moreover, we propose a nonlocal structure tensor optimization model to further improve image quality, which can effectively mitigate the loss of image high-frequency texture and edge information. Experiments on natural images validate that our method outperforms other state-of-the-art methods, especially for the noise image.

Over the past two decades, the viewpoint of atherosclerosis has been replaced gradually by a lipid-driven, chronic, low-grade inflammatory disease of the arterial wall. Current treatment of atherosclerosis is focused on limiting its risk factors, such as hyperlipidemia or hypertension. However, treatment targeting the inflammatory nature of atherosclerosis is still very limited and deserves further attention to fight atherosclerosis successfully. Here, we review the current development of inflammation and atherosclerosis to discuss novel insights and potential targets in atherosclerosis, and to address drug discovery based on anti-inflammatory strategy in atherosclerotic disease.