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Objectives The present study aimed to investigate the distribution of lymphocyte subsets and cytokines expression in the peripheral blood of bitumen fumes-exposed workers. Methods In this study, 129 workers from molding and roasting workshops were recruited as the exposed group and 99 office and quality inspection staff were chosen as the control. The polycyclic aromatic hydrocarbons (PAHs) levels of bitumen fumes in individual and fixed-point air samples and the urinary levels of 1-hydroxypyrene (1-OH-P), 1-hydroxynaphthols (1-OH-N) and 2-hydroxynaphthols (2-OH-N) in workers were measured using High Performance Liquid Chromatography. The lymphocyte subsets and serum cytokines concentrations were analyzed by flow cytometry and cytometric bead array, respectively. Results The median values of PAHs were 0.08 mg/m3 for permissible concentration-time weighted average and 0.12 mg/m3 for permissible concentration-short term exposure (PC-STEL) in molding and roasting workshops, which were higher than that in the control area (< 0.01 mg/m3). Multivariate linear regression models were used to adjust for influential covariates, including age, gender, work age, smoking status, and alcohol consumptions. After adjusting for these covariates, we compared levels of urinary PAHs metabolites, the percentages of lymphocyte subsets, and serum cytokines concentrations between the two groups. The 1-OH-P, 1-OH-N, and 2-OH-N levels in the urine of bitumen fumes exposed workers were significantly higher than that in the controls (P < 0.05). Compared with the control group, the percentage of the natural killer (NK) cell (CD56+ cell) was significantly increased in the exposed group (P < 0.001). There was a significant decrease in the percentages of CD3+ T cell, CD4+ T cell, and CD8+ T cell in the exposed group compared to the control (P < 0.001). The serum levels of interleukin-1β (IL-1β) and IL-6 in bitumen fumes exposed workers were significantly higher than that of the controls (P < 0.05). Moreover, positive correlations were observed between the serum levels of IL-1β, IL-6, and urinary 1-OH-P levels in bitumen fumes-exposed workers, respectively (P < 0.05). There were no significant differences in the serum levels of IL-8, tumor necrosis factor-α (TNF-α), macrophage inflammatory protein-1β (MIP-1β) and monocyte chemotactic protein-1 (MCP-1) between the exposed group and the control group (P > 0.05). Conclusion Our study suggested that low dose of bitumen fumes exposure could decrease the percentage of T cell, increase the percentage of NK cell and stimulate the release of serum IL-1β and IL-6 in the peripheral blood of exposed workers. The serum levels of IL-1β and IL-6 were positive correlated with the urinary 1-OH-P levels in bitumen fumes exposed workers. These results may inform the search for potential effective biomarkers and provide evidences for early health monitoring in workers occupationally exposed to bitumen fumes.

Norovirus, the leading cause of non-bacterial acute gastroenteritis (AGE) worldwide, is constantly mutating. Continuous monitoring of the evolution of epidemic genotypes and emergence of novel genotypes is, therefore, necessary. This study determined the prevalence and clinical characteristics of norovirus strains in AGE in Guangzhou, China in 2019/2020 season. This study included children aged 2–60 months diagnosed with AGE in Guangzhou Women and Children Hospital, from August 2019 to January 2020. Norovirus was detected by real-time polymerase chain reaction and clinical data were obtained. Genotyping and phylogenetic analyses were performed with partial gene sequence fragments located within the open reading frames 1 and 2. During the study period, 168 children (61.3% males) were confirmed as norovirus infectious AGE. The main symptoms were diarrhoea and vomiting and 38 patients (22.6%) had seizures. Norovirus was mainly prevalent in October and November, and GII.4 Sydney[P31] was the major genotype circulating in Guangzhou. The phylogenetic tree showed that the Guangzhou strains had high homology with the strains circulating in 2017–2019 worldwide. GII.4 Sydney was the main prevalent norovirus genotype in Guangzhou from August 2019 to January 2020, which had more severe diarrhoea than those of other genotypes. These findings provide a valuable reference for the prevention, control, and treatment of norovirus in the future.

Image quality assessment (IQA) based on deep learning faces the overfitting problem due to limited training samples available in existing IQA databases. Transfer learning is a plausible solution to the problem, in which the shared features derived from the large-scale Imagenet source domain could be transferred from the original recognition task to the intended IQA task. However, the Imagenet source domain and the IQA target domain as well as their corresponding tasks are not directly related. In this paper, we propose a new transitive transfer learning method for no-reference image quality assessment (TTL-IQA). First, the architecture of the multi-domain transitive transfer learning for IQA is developed to transfer the Imagenet source domain to the auxiliary domain, and then to the IQA target domain. Second, the auxiliary domain and the auxiliary task are constructed by a new generative adversarial network based on distortion translation (DT-GAN). Furthermore, a TTL network of the semantic features transfer (SFTnet) is proposed to optimize the shared features for the TTL-IQA. Experiments are conducted to evaluate the performance of the proposed method on various IQA databases, including the LIVE, TID2013, CSIQ, LIVE multiply distorted and LIVE challenge. The results show that the proposed method significantly outperforms the state-of-the-art methods. In addition, our proposed method demonstrates a strong generalization ability.

There is currently a lack of sufficient data on human papillomavirus (HPV)-attributable cervical carcinoma in China. Accordingly, we aimed to determine the prevalence and genotype distribution of HPV among women with cervical lesions in Shenzhen, in order to evaluate the potential benefit of HPV vaccination programs and inform cervical cancer control policies. We enrolled 5,255 patients who were admitted to the University of Chinese Academy of Sciences Shenzhen Hospital from January 2017 to December 2019. The HPV prevalence and genotype distribution were analyzed using the 21 HPV GenoArray diagnostic assay. A total of 937/5,255 patients showed HPV-positivity (prevalence rate 17.83%), of whom 85.81% (804/937) had high-risk HPV infection. HPV52 was the most prevalent genotype (4.72%, 248/5,255), followed by HPV58 (3.04%, 160/5,255), and HPV16 (2.72%, 143/5,255). The HPV prevalence rates among women with a normal cervix, low-grade intraepithelial lesions, high-grade intraepithelial lesions, invasive cervical cancer, and other characteristics were 15.63% (50/320), 58.65% (61/104), 80.00% (44/55), 88.57% (31/35), and 15.84% (751/4,741), respectively. HPV16, HPV18, and HPV52 accounted for the majority of cervical lesions, and the infection rates of HPV16 and HPV18 gradually increased with intraepithelial lesion progression (both P

Deep-learning based image quality assessment (IQA) algorithms usually use the transfer learning method that transfers a pre-trained network for classification task to handle IQA task. Although it can overcome the problem of having insufficient IQA databases to some extent, it cannot distinguish between the important and unimportant deep features for the IQA task, which potentially leads to inaccurate prediction performance. In this paper, we propose a no-reference IQA method based on modelling of deep feature importance. A SE-VGG network is developed by using adaptive transfer learning method. It can suppress the features of local parts of salient objects of images that are not important to the IQA task, and emphasize the features of image distortion and salient objects that are important to IQA task. Moreover, the structure of the SE-VGG is investigated to improve the accuracy of the image quality assessment on a small IQA database. Experiments are conducted to evaluate the performance of the proposed method on various databases, including the LIVE, TID2013, CSIQ, LIVE multiply distorted and LIVE challenge. The results show the proposed method significantly outperforms the state-of-the-art methods. In addition, our method demonstrates a strong generalization ability.

3D direct planimetry is increasingly used in clinical practice as a rapid way to measure the mitral valve area (MVA) in patients with rheumatic mitral stenosis (MS) who underwent three-dimensional transesophageal echocardiography (3D-TEE). However, data on its accuracy and reliability are scarce. This study aimed to compare the MVA measurements obtained by 3D direct planimetry to the conventional technique multiplanar reconstruction (MPR) in MS patients using 3D-TEE. We retrospectively included 49 patients with rheumatic MS undergoing clinically-indicated 3D-TEE in the study. We determined the 3D direct planimetry measurements of MVA from the left atria aspect (MVALA) and the left ventricle aspect (MVALV), and compared those with the MPR method (MVAMPR). We also assessed the major and minor diameters of the mitral valve orifice using MPR and 3D direct planimetry. We found an excellent agreement between the MVA measurements obtained by the MPR method and 3D direct planimetry (MVALA and MVALV) [intraclass correlation coefficients (ICC) = 0.951 and 0.950, respectively]. However, the MVAMPR measurements were significantly larger than the MVALA and MVALV (p

Error or drift is frequently produced in pose estimation based on geometric "feature detection and tracking" monocular visual odometry(VO) when the speed of camera movement exceeds 1.5m/s. While, in most VO methods based on deep learning, weight factors are in the form of fixed values, which are easy to lead to overfitting. A new measurement system, for monocular visual odometry, named Deep Learning Visual Odometry(DLVO), is proposed based on neural network. In this system, Convolutional Neural Network(CNN) is used to extract feature and perform feature matching. Moreover, Recurrent Neural Network(RNN) is used for sequence modeling to estimate camera's 6-dof poses. Instead of fixed weight values of CNN, Bayesian distribution of weight factors are introduced in order to effectively solve the problem of network over-fitting. The 18,726 frame images in KITTI dataset are used for training network. This system can increase the generalization ability of network model in prediction process. Compared with original Recurrent Convolutional Neural Network(RCNN), our method can reduce the loss of test model by 5.33%. And it's an effective method in improving the robustness of translation and rotation information than traditional VO methods.

Organic–inorganic metal halide perovskites have achieved great success in applications such as light-emitting diodes, photodetectors (PDs) and solar cells due to their high light absorption coefficients, tunable band gaps and simple solution-process technologies. However, their polycrystalline films have low carrier mobility and high defect states, which limit the device performance. As substitutes, perovskite microcrystal (MC) films exhibit higher carrier mobility and lower defect state density and thus, they have received much attention in recent years. Herein, we introduce MAPbX3 (X = Br, I) MC films with controllable thickness and adjustable band gap, and the self-powered MAPbI3 perovskite MC PDs (MCPDs) with a structure of ITO glass/perovskite MC film/carbon have been assembled for the first time. By optimizing the thickness of the MC film, our hole-transport-layer-free (HTL-free) PDs exhibit excellent self-powered performance, with an on/off ratio as high as 2 × 105, the rise/fall time of 80/580 μs, the responsivity of 0.26 A W−1, the detectivity of 7.01 × 1011 Jones and the linear dynamic range of 107 dB. In addition, our MCPDs without encapsulation show excellent light and storage stability. These results indicate a good method for preparing high-performance and high-stability perovskite MC devices.

Tumor genome methylation is closely related to tumor immunosuppression. In the present study, we evaluated the fluctuations in DNA methylation levels, and the numbers of infiltrating T cells and their cytokines in different-grade cervical lesions. A total of 154 human cervical specimens that included LSIL (43 cases), HSIL (48 cases), and cervical squamous cancer (63 cases) were used for this study. Immunohistochemistry for 5-hydroxymethylcytosine (5hmC) and T-cell-attracting chemokines was performed, and multiplex immunofluorescence labeling was used to identify different T-cell subtypes. We found that the proportions of samples that immunostained weakly or negatively for 5hmC were increased commensurately with elevations in the severity of cervical lesions. The expression of T-cell-attracting chemokines—including CXCL9, CXCL10, and CXCL11—was positively associated with 5hmC levels, and CXCL9 was the cytokine that was most pronounced. With the progression of cervical lesions, the numbers of total T cells, CTL, and NK cells in the cervical tissues all gradually decreased. During the occurrence and development of cervical squamous carcinoma, 5hmC was gradually lost, and immunosuppression occurred in precancerous cervical lesions.

The catastrophic failure of coal under super-critical stresses and mining-induced disturbance is becoming one of major safety risks of underground mining. Research of the failure pattern o...

Nitrate, the end-product of nitrification, tends to accumulate in recirculating aquaculture systems (RASs). We investigated the 96-h acute and 28-d chronic toxicity of nitrate-N to spotted knifejaw, Oplegnathus punctatus. We exposed juveniles (1.3 ± 0.6 g, 2.3 ± 0.7 cm TL) to seven different nitrate-N concentrations (11.3 (control), 673.1, 873.9, 1052.9, 1471.1, 1887.1, or 2368.3 mg/L) in a triplicated experimental design for 96 h; the estimated LC50 values for nitrate-N at 24, 48, 72, and 96 h were 774.4, 678.8, 586.3, and 484.5 mg/L nitrate-N − N, respectively. In an examination of chronic effects of elevated nitrate-N, juvenile O. punctatus (44.9 ± 7.0 g; 7.3 ± 0.6 cm) were exposed to 21.4 ± 4.4 mg/L (treatment 1), 165.5 ± 7.8 mg/L (treatment 2), or 299.4 ± 5.8 mg/L (treatment 3) nitrate-N in triplicated RASs, and the impact of nitrate-N on performance, blood, histological, and gene expression markers was evaluated. After 28 days, final length, specific growth rate and feed conversion ratio did not differ (p > .05) among treatments. Final weight and mortality did not differ significantly between treatments 1 and 2, but was significantly (p

All-inorganic metal halide perovskites have attracted great interest in recent years due to their good device performance with higher thermal stability than that of their organic–inorganic perovskite counterparts. However, the all-inorganic perovskite polycrystalline films prepared by the conventional spin-coating method possess many pinholes, nonuniform surface with many small crystals, and irregular agglomerates, limiting their device performance. Herein, we introduced a monolayer nano-polystyrene (PS) sphere confined growth method for obtaining CsPbBr3 nanonet films (NFs) with ordered nanostructures grown in the preferred (110) orientation, which is beneficial for the charge carrier transport and the light-harvesting efficiency. The (110) peak intensity of CsPbBr3 NFs increased with the increase of the diameter of the monolayer sphere, while the (001) peak intensity was suppressed greatly, indicating the more preferred (110) oriented growth. The PDs based on (110)-orientation-preferred CsPbBr3 NFs prepared by using 850 nm PS spheres showed the best performance. The best performing device displayed the biggest linear dynamic range of up to 120 dB. In addition, a responsivity of 2.84 A W−1 and a detectivity of 5.47 × 1012 Jones were also achieved.

Blind image quality assessment (BIQA) methods aim to predict quality of images as perceived by humans without access to a reference image. Recently, deep learning methods have gained substantial attention in the research community and have proven useful for BIQA. Although previous study of deep neural networks (DNN) methods is presented, some novelty DNN methods, which are recently proposed, are not summarized for BIQA. In this paper, we provide a survey covering various DNN methods for BIQA. First, we systematically analyze the existing DNN-based quality assessment methods according to the role of DNN. Then, we compare the prediction performance of various DNN methods on the synthetic databases (LIVE, TID2013, CSIQ, LIVE multiply distorted) and authentic databases (LIVE challenge), providing important information that can help understand the underlying properties between different DNN methods for BIQA. Finally, we describe some emerging challenges in designing and training DNN-based BIQA, along with few directions that are worth further investigations in the future.

Coal burst continues to be one of the most catastrophic safety hazards faced by future mining as the stress environment will be more complicated with the increase of mining depth. Many chief coal mining countries including Poland, Czech Republic, the U.S., China, and Australia have experienced fatal accidents caused by coal burst and conducted comprehensive research on the driving forces and solving technologies related to coal burst. In this chapter, the research outcomes of the mechanism, risk evaluation, risk monitoring, and prevention of coal burst are reviewed, which is helpful for mining researchers and engineers to understand and control the safety hazards caused by coal burst, and, hence, to achieve sustainable and safe mining.

How best to measure spatial saliency shift induced by image distortions is an open research question. Our previous study has shown that image distortions cause saliency to deviate from their original places in natural images, and the degree of such distortion-induced saliency variation (DSV) depends on image content and the properties of distortion. Being able to measure DSV benefits the development of saliency-based image quality algorithms. In this article, we first investigate the plausibility of using existing mathematical algorithms for measuring DSV and their potential limitations. We then develop a new algorithm for quantifying DSV based on a deep neural network. In the algorithm, namely, saliency similarity transformation DSV (ST-DSV), we design a coarse-grained to fine-grained saliency similarity transformation approach to achieve DSV measurement. The experimental results show that the proposed ST-DSV algorithm significantly outperforms existing methods in predicting the ground truth DSV.

As an important foodborne pathogen, Vibrio vulnificus gives a significant threat to food safety and public health. Rapid and accurate detection methods for V. vulnificus are required to control its spread. The conventional detection methods are time-consuming and labor-intensive, while the polymerase chain reaction (PCR)- and quantitative PCR (qPCR)-based methods are limited because of their dependence on laboratory equipment. Nucleic acid isothermal amplification technologies have been applied to develop simpler assays. In this study, a rapid detection method based on real-time recombinase polymerase amplification (RPA) targeting the extracellular metalloprotease (empV) gene of V. vulnificus has been established. The method finished the detection in 2–14 min at 39°C with good specificity. The limit of detection was 17 gene copies or 1 colony-forming unit (CFU) per reaction, or 1 CFU/10 g of spiked food with enrichment. In a clinical sample detection test, the results of real-time RPA were 100% consistent with bioassay and qPCR. Moreover, the method could resist the effect of food matrix and could tolerate crude templates. The real-time RPA method established in this study is rapid and simple and has the potential to be widely applied for V. vulnificus detection in food safety control.

27th IEEE International Conference on Image Processing (ICIP), Abu Dhabi, EMIRATS ARABES UNIS, 25-/10/2020 - 28/10/2020; Research on image quality assessment (IQA) remains limited mainly due to our incomplete knowledge about human visual perception. Existing IQA algorithms have been designed or trained with insufficient subjective data with a small degree of stimulus variability. This has led to challenges for those algorithms to handle complexity and diversity of real-world digital content. Perceptual evidence from human subjects serves as a grounding for the development of advanced IQA algorithms. It is thus critical to acquire reliable subjective data with controlled perception experiments that faithfully reflect human behavioural responses to distortions in visual signals. In this paper, we present a new study of image quality perception where subjective ratings were collected in a controlled lab environment. We investigate how quality perception is affected by a combination of different categories of images and different types and levels of distortions. The database will be made publicly available to facilitate calibration and validation of IQA algorithms.

BackgroundNorovirus, the leading cause of non-bacterial acute gastroenteritis (AGE) worldwide, is constantly mutating. Continuous monitoring of the evolution of epidemic genotypes and emergence of novel genotypes is therefore necessary. This study determined the prevalence and clinical characteristics of norovirus strains in AGE in Guangzhou, China in 2019-2020 winter.MethodsThis study included children aged 2-60 months diagnosed with AGE in Guangzhou Women and Children Hospital, from August 2019 to January 2020. Norovirus was detected by real-time polymerase chain reaction and clinical data were obtained. Genotyping and phylogenetic analyses were performed with partial gene sequence fragments located at the open reading frames 1-2 junctions.ResultsDuring the study period, 168 children (61.3% males) were confirmed as norovirus infectious AGE. The main symptoms were diarrhoea and vomiting; and 38 patients (22.6%) had seizures. Norovirus was mainly prevalent in October and November, and GII.P31/GII.4 Sydney was the major genotype circulating in Guangzhou. The phylogenetic tree showed that the Guangzhou strains had high homology with the strains circulating in 2017-2019 worldwide. ConclusionsGII.4 Sydney was the main prevalent norovirus genotype in Guangzhou from August 2019 to January 2020, which had more severe diarrhoea than those of other genotypes. These findings provide a valuable reference for the prevention, control, and treatment of norovirus in the future.

In January 2020, a COVID-19 outbreak was detected in Sichuan Province of China. Six weeks later, the outbreak was successfully contained. The aim of this work is to characterize the epidemiology of the Sichuan outbreak and estimate the impact of interventions in limiting SARS-CoV-2 transmission. We analyzed patient records for all laboratory-confirmed cases reported in the province for the period of January 21 to March 16, 2020. To estimate the basic and daily reproduction numbers, we used a Bayesian framework. In addition, we estimated the number of cases averted by the implemented control strategies. The outbreak resulted in 539 confirmed cases, lasted less than two months, and no further local transmission was detected after February 27. The median age of local cases was 8 years older than that of imported cases. We estimated R0 at 2.4 (95% CI: 1.6–3.7). The epidemic was self-sustained for about 3 weeks before going below the epidemic threshold 3 days after the declaration of a public health emergency by Sichuan authorities. Our findings indicate that, were the control measures be adopted four weeks later, the epidemic could have lasted 49 days longer (95% CI: 31–68 days), causing 9,216 more cases (95% CI: 1,317–25,545)., Author summary Since its emergence in Wuhan, SARS-CoV-2 rapidly started its spread across China. On January 21, 2020 the first COVID-19 case was detected in the Sichuan Province of China and led to an outbreak of local transmission. Less than two months later, the outbreak was over with the last reported case on March 4, 2020. In this study, we analyzed patient records for all laboratory-confirmed cases reported in Sichuan to provide an epidemiological characterization of the outbreak, to estimate SARS-CoV-2 transmission potential, and to assess the impact of the adopted interventions. We estimated that, during the initial exponential growth phase of the outbreak, each COVID-19 case has generated a mean of 2.4 secondary cases (95% CI: 1.6–3.7). Moreover, we estimated that, were the Sichuan strict containment measures implemented four weeks later, the outbreak would have caused 9,216 more cases (95% CI: 1,317–25,545). Our findings suggest the key role of a quick response to COVID-19 outbreaks and the importance of an adequate surveillance and monitoring system.

Global demand for food and bioenergy production has increased rapidly, while the area of arable land has been declining for decades due to damage caused by erosion, pollution, sea level rise, urban development, soil salinization, and water scarcity driven by global climate change. In order to overcome this conflict, there is an urgent need to adapt conventional agriculture to water-limited and hotter conditions with plant crop systems that display higher water-use efficiency (WUE). Crassulacean acid metabolism (CAM) species have substantially higher WUE than species performing C 3 or C 4 photosynthesis. CAM plants are derived from C 3 photosynthesis ancestors. However, it is extremely unlikely that the C 3 or C 4 crop plants would evolve rapidly into CAM photosynthesis without human intervention. Currently, there is growing interest in improving WUE through transferring CAM into C 3 crops. However, engineering a major metabolic plant pathway, like CAM, is challenging and requires a comprehensive deep understanding of the enzymatic reactions and regulatory networks in both C 3 and CAM photosynthesis, as well as overcoming physiometabolic limitations such as diurnal stomatal regulation. Recent advances in CAM evolutionary genomics research, genome editing, and synthetic biology have increased the likelihood of successful acceleration of C 3 -to-CAM progression. Here, we first summarize the systems biology-level understanding of the molecular processes in the CAM pathway. Then, we review the principles of CAM engineering in an evolutionary context. Lastly, we discuss the technical approaches to accelerate the C 3 -to-CAM transition in plants using synthetic biology toolboxes.

Human life intimately depends on plants for food, biomaterials, health, energy, and a sustainable environment. Various plants have been genetically improved mostly through breeding, along with limited modification via genetic engineering, yet they are still not able to meet the ever-increasing needs, in terms of both quantity and quality, resulting from the rapid increase in world population and expected standards of living. A step change that may address these challenges would be to expand the potential of plants using biosystems design approaches. This represents a shift in plant science research from relatively simple trial-and-error approaches to innovative strategies based on predictive models of biological systems. Plant biosystems design seeks to accelerate plant genetic improvement using genome editing and genetic circuit engineering or create novel plant systems through de novo synthesis of plant genomes. From this perspective, we present a comprehensive roadmap of plant biosystems design covering theories, principles, and technical methods, along with potential applications in basic and applied plant biology research. We highlight current challenges, future opportunities, and research priorities, along with a framework for international collaboration, towards rapid advancement of this emerging interdisciplinary area of research. Finally, we discuss the importance of social responsibility in utilizing plant biosystems design and suggest strategies for improving public perception, trust, and acceptance.

Coal burst is the violent failure of overstressed coal, and it is often accompanied by sound, coal ejection and seismic events. It is subsequently recognized as a serious safety risk of Australia after double fatalities coal burst happened at Austar Coal Mine. Considering the increasing trend of coal burst severity and frequency with mining depth, it is an urgent task to develop the coal burst risk assessment methods for Australia underground coal mines. Coal burst propensity index method is a widely used method of burst risk evaluation of coal as it is summed up from the coal burst research and practice of many countries. This paper presents the experimental and theoretical research of coal burst propensity index method for coal burst risk assessment in Australia. The definition of four indexes including elastic strain energy index (WET), bursting energy index (KE), dynamic failure time (DT) and uniaxial compression strength (RC) is introduced in the first part. Then, the standard laboratory test process and test parameter of coal burst propensity index is presented. DT test is conducted with 0.3 mm/min displacement control loading rate while other test is with 0.5 mm/min. Besides, modified data processing and risk classification method of test are proposed. Differentiate analysis of stress-strain curve is adopted in the data processing of DT and KE index. A four level risk classification form of burst risk is recommended for Australian underground coal mines. Finally, two likely improvement methods of WET test, including volumetric strain indicator method and theoretical calculation method, are discussed. Keywords: Coal burst, Coal burst propensity, Risk evaluation, Underground mining

Researchers have made considerable progress in elucidating psychological and exercise correlates of major depressive disorder (MDD). However, as the largest immune organ, far less is known about the role of gastrointestinal (GI) tract in the therapeutic mechanisms of exercise in MDD. In addition to the sites of the digestive tract that absorb nutrients, the GI tract also serves as a protective barrier against organisms. Inflammation and other consequences caused by disrupted GI barrier integrity are considered to be one of the mechanisms of depression, and the gut-brain axis (GBA) plays a critical role in this process. In this work, we observed the depression-like behaviors, intestinal barrier, central and peripheral inflammation, and related neurotransmitters through exercise intervention in the chronic unpredictable mild stress (CUMS) model, aiming to clarify the mechanisms of exercise to improve depression through GBA. Our results revealed that, following increased expressions of pro-inflammatory factors in intestine of CUMS mice, the levels of pro-inflammatory factors were all significantly raised in serum and brain simultaneously. Further, glial cells were activated in visceral nervous system and its related brain regions at the same time, accompanied by lower expression of occludin in CUMS mice. Importantly, our findings provide the first evidence that eight weeks of running exercise effectively inhibited neuro-immune interactions along gut-brain-axis and contributed obvious improvement of intestinal epithelial barrier (IEB). Finally, multivariate analysis putatively highlighted the role of exercise-induced IEB protection on depression treatment. We hope that our findings could warrant further study of therapeutic mechanisms of exercise in depression, specifically in disentangling the roles of intestinal function and IEB protection, and for developing more targeted clinical depression interventions.

Owing to their low trap-state density, high carrier mobility, and high thermal stability, CsPbBr3 perovskite microcrystals (MCs) have attracted significant attention for applications as photodetectors (PDs). However, solution synthesis processes lead to MC films with high void density, seriously limiting the performance of the PDs. Here, a pressure-assisted annealing strategy is introduced to significantly reduce the void density and decrease the surface roughness. The resulting self-powered all-inorganic CsPbBr3 perovskite MC thick-film PDs show improved performance characteristics, with responsivities and detectivities of up to 0.206 A W–1 and 7.23 × 1012 Jones, respectively. Moreover, the on/off ratios of the devices are up to 106, and the highest linear dynamic range reaches 123.5 dB. These improved results indicate that the pressure-assisted annealing method is an effective strategy to enhance the performance of solution-synthesized perovskite MC PDs.

Background Attenuated nighttime blood pressure (BP) fall during a high-sodium diet is associated with higher sodium sensitivity of BP. However, the prognostic value for sodium sensitivity of nighttime BP profile during a habitual diet is not fully understood. Purpose To elucidate the usefulness of nighttime BP and dipping patterns under a habitual diet in assessing sodium sensitivity. Methods We conducted a dietary intervention study among 250 resident aged 18–60 years with high-normal or stage I hypertension in rural areas of northern China. The 24-hour ambulatory BP monitoring and baseline survey were performed for each participant under a habitual diet during the first 3 days. Then participants underwent a 7-day low-sodium intervention (51.3mmol sodium per day), followed by a 7-day high-sodium intervention (307.8mmol sodium per day). Three clinic BP measurements were obtained in every morning of the 3-day baseline observation and days 5, 6, and 7 of each intervention period. Results Among 250 participants, 86 (34.4%) had daytime hypertension (DH) and 149 (59.6%) had nighttime hypertension (NH). The systolic BP (SBP) responses to low-sodium and high-sodium intervention were significantly higher in those with NH than those without irrespective of DH status [−8.1 (−9.3, −7.0) vs. −5.5 (−7.0, −4.1) mmHg, P=0.001; and 13.0 (11.6, 14.3) vs. 11.0 (9.3, 12.7) mmHg, P=0.038, respectively]. Compared with dippers, extreme dippers had significantly higher SBP responses to low-sodium and high sodium intervention independently of 24-hour SBP. Moreover, the quadratic curve between nighttime SBP fall and SBP responses to low-sodium (β=−105.5 for quadratic term, P=0.015) and high-sodium (β=108.9 for quadratic term, P=0.035) intervention suggested both non-dipping and extreme dipping might indicate higher sodium sensitivity. Conclusions NH as well as non-dipping and extreme dipping determined during a habitual diet might indicate higher sodium sensitivity, which highlights the potential usefulness of nighttime BP profile in assessing sodium sensitivity. Acknowledgement/Funding This study is supported by the National Natural Science Foundation of China (grant no. 81570386)

Self-powered light-emitting photodetectors (SLEPs) can simultaneously transmit and receive information using light, offering huge potential for applications in interactive communication systems. However, high-performance SLEPs are very hard to achieve due to the seriously contradictory principles of carrier transport in SLEPs. In this study, a novel structure based on a ZnO hollow ball/CsPbBr3 heterojunction, in which ZnO hollow balls function as an ultraviolet (UV) response center and CsPbBr3 is designed to be a green light-emitting material, is reported as a high-performance SLEP. Since the ZnO hollow balls have superior light trapping characteristics for UV light, the device shows a huge UV response with the on/off ratio and detectivity up to 16 527 and 2.4 × 1013 Jones, respectively. Moreover, it displays blue emission with a low threshold voltage because of CsPbBr3. Compared with the traditional ZnO/GaN structure devices, the device showed enhanced dual-functional performance at various wavelengths due to the insertion of CsPbBr3, which resulted in a better contact interface and green-light emission center. Our structure separating the light-responsive and emitting active regions avoids the contradictory principles of carrier transport, which may provide new access to gain high-performance dual-functional devices.

Objectives This study aims to assess whether iodine-contained contrast agents with different osmolarity affect iodine delivery protocol during coronary computed tomography angiography (CCTA). Methods Patients who underwent CCTA were randomized to receive contrast media either iodixanol-320 (iso-osmolar group) or iopromide-370 (low-osmolar group). Contrast protocols were recorded. Tube voltage of 100 kV was chosen for patients with body mass index of less than or equal to 25 (n = 224) and tube voltage of 120 kV for patients with body mass index of greater than 25 (n = 165). Both groups applied automatic current modulation technique. Mean contrast enhancement of the ascending aorta, left main coronary artery, and descending aorta was calculated. Simulated contrast flow rate and iodine delivery rate (IDR) to reach a mean contrast enhancement level of 350 HU were calculated. Results A total of the 389 patients were enrolled in the study. To achieve the same contrast enhancement of 350 HU, iso-osmolar group required higher simulated contrast flow rate (3.90 vs 3.62 mL/s, P = 0.017) but lower simulated IDR (1.34 vs 1.25 g/s, P = 0.024) compared with low-osmolar group. Conclusions To maintain a similar level of contrast enhancement during CCTA, iodixanol-320 needs larger contrast flow rate with lower IDR compared with low-osmolar iopromide-370.

Major depression has been interpreted as an inflammatory disease characterized by cell-mediated immune activation, which is generally triggered by various stresses. Microglia has been thought to be the cellular link between inflammation and depression-like behavioural alterations. The expression of cathepsin C (Cat C), a lysosomal proteinase, is predominantly induced in microglia in neuroinflammation. However, little is known about the role of Cat C in pathophysiology of depression. In the present study, Cat C transgenic mice and wild type mice were subjected to an intraperitoneal injection of LPS (0.5 mg/kg) and 6-week unpredictable chronic mild stress (UCMS) exposure to establish acute and chronic stress-induced depression model. We examined and compared the behavioural and proinflammatory cytokine alterations in serum and depression-targeted brain areas of Cat C differentially expressed mice in stress, as well as indoleamine 2,3-dioxygenase (IDO) and 5-hydroxytryptamine (5HT) levels in brain. The results showed that Cat C overexpression (Cat C OE) promoted peripheral and central inflammatory response with significantly increased TNFα, IL-1β and IL-6 in serum, hippocampus and prefrontal cortex, and resultant upregulation of IDO and downregulation of 5HT expression in brain, and thereby aggravated depression-like behaviours accessed by open field test, forced swim test and tail suspension test. In contrast, Cat C knockdown (Cat C KD) partially prevented inflammation, which may help alleviate the symptoms of depression in mice. To the best of our knowledge, we are the first to demonstrate that Cat C aggravates neuroinflammation involved in disturbances of behaviour and neurochemistry in acute and chronic stress-induced murine model of depression.

The rolling piston type rotary compressors consume huge amount of energy in buildings due to the large quantity of applications in household as well as commercial air-conditioners and heat pumps. Internal leakage losses significantly affects the energy utilization efficiency of a rolling piston type rotary compressor. This paper experimentally evaluate the internal refrigerant-oil mixture leakage characteristics of a rolling piston type rotary compressor. Effects of minimal clearance, pressure difference, length and geometry of the leakage channel on internal leakage losses are analyzed. The experimental results are compared with prediction results of different mathematical models. A preliminary optimization scheme for the mathematical model is proposed. The updated model can well predict the variation trend of the actual leakage process. Finally, volumetric efficiencies of a rolling piston type rotary compressor prototype under different rotated speeds are obtained based on the updated prediction model. The rolling piston type rotary compressor with high working efficiency will help to reduce the worldwide energy depletion and the present study provides significant reference for design, processing and assembling of the compressors.

An efficient memristor MIN function based activation circuit is presented for memristive neuromorphic systems, using only two memristors and a comparator. The ReLU activation function is approximated using this circuit. The ReLU activation function helps to significantly reduce the time and computational cost of training in neuromorphic systems due to its simplicity and effectiveness in deep neural networks. A multilayer neural network is simulated using this activation circuit in addition to traditional memristor crossbar arrays. The results illustrate that the proposed circuit is able to perform training effectively with significant savings in time and area in memristor crossbar based neural networks.

Cushing's syndrome (CS) is a clinical syndrome characterized by hypercortisolemia. Cyclic Cushing's syndrome (CCS), which exhibits a periodic or irregular increasing pattern in cortisol, is a rare type of Cushing's syndrome. A 37-year-old man came to our hospital because of repeated dizzy spells, weakness and hypercortisolemia lasting two weeks. Endocrinological examinations indicated CCS with periodic and intermittent increases in cortisol. Enhanced computed tomography (CT) revealed space occupying lesions on the upper lobe of left lung, and biopsy eventually proved that these were pulmonary carcinoid tumors with ectopic ACTH secretion, which was subsequently manifested a Cushing's syndrome. PET-CT, ultrasound and biopsy of the thyroid gland indicated bilateral thyroid papillary carcinoma. CT scan showed bilateral nodular hyperplasia of the adrenal gland. Enhanced magnetic resonance imaging (MRI) confirmed that the high signal disappeared on the posterior lobe of the pituitary gland and that the pituitary stalk shifted left, which was suspected to be non-functional pituitary microadenoma. The patient underwent surgery involving resection of the left upper pulmonary lobe and the mediastinal lymph node around the hilus pulmonis, which resulted in complete remission of CCS. The patient then chose elective surgery for the thyroid papillary carcinoma. An analysis of the patient's genomic DNA identified a novel mutation in PDE11A: c.2032 (exon 12) G > A, which is associated with primary pigmented nodular adrenocortical disease (PPNAD). This is a novel mutation which has been no previous public clinical report on this mutation as it relates to this disease.

A highly efficient memristor MIN function based activation circuit is presented for memristive neuromorphic systems, using only two memristors and a comparator. The ReLU activation function is approximated using this circuit for the first time. The ReLU activation function helps to significantly reduce the time and computational cost of training in neuromorphic systems due to its simplicity and effectiveness in deep neural networks. A multilayer neural network is simulated using this activation circuit in addition to traditional memristor crossbar arrays. The results illustrate that the proposed circuit is able to perform training effectively with significant savings in time and area in memristor crossbar based neural networks.

Blind/no-reference image quality assessment is performed to accurately evaluate the perceptual quality of a distorted image without prior information from a reference image. In this paper, an effective blind image quality assessment approach based on entropy differences in the discrete cosine transform domain for natural images is proposed. Information entropy is an effective measure of the amount of information in an image. We find the discrete cosine transform coefficient distribution of distorted natural images shows a pulse-shape phenomenon, which directly affects the differences of entropy. Then, a Weibull model is used to fit the distributions of natural and distorted images. This is because the Weibull model sufficiently approximates the pulse-shape phenomenon as well as the sharp-peak and heavy-tail phenomena of natural scene statistics rules. Four features that are related to entropy differences and human visual system are extracted from the Weibull model for three scaling images. Image quality is assessed by the support vector regression method based on the extracted features. This blind Weibull statistics algorithm is thoroughly evaluated using three widely used databases: LIVE, TID2008, and CSIQ. The experimental results show that the performance of the proposed blind Weibull statistics method is highly consistent with that of human visual perception and greater than that of the state-of-the-art blind and full-reference image quality assessment methods in most cases.

The fat greenling, Hexagrammos otakii, is an emerging aquaculture species and is being evaluated for production in recirculating aquaculture systems (RAS). To better understand the tolerance of H. otakii to varying environmental salinity in actual aquaculture operations, the effects of salinity on survival, growth, hematological parameters, gill microstructure and gill transcriptome were investigated. Juvenile H. otakii (22.0± 1.8 g; 11.2 ± 0.7 cm) were reared at different salinities, 6.7 ± 0.1 PSU (7 PSU), 12.3 ± 0.1 PSU (12 PSU), 18.2 ± 0.1 PSU (18 PSU), 23.9 ± 0.6 PSU (24 PSU), and 28.9 ± 0.8 PSU (29 PSU) in triplicated RASs for five weeks, and the impacts of salinity on these endpoints were evaluated. Fish in the 7 PSU group exhibited significantly lower survival, final weight, feed conversion ratio, and specific growth rate than fish in other treatments. While no statistically significant differences were found among mean white blood cell counts, red blood cell counts and hemoglobin concentrations, mean corpuscular volume was significantly lower in the 7 PSU group than in other groups. At the histological level, there were smaller numbers and smaller volume of mitochondria-rich cells in the 7 PSU group, and the numbers of pavement cells and mucous cells were significantly higher than in other groups. Transcriptome sequencing for a sample of individuals from the 7 PSU, 18 PSU and 29 PSU groups indicated that gene expression in the gills of H. otakii differed significantly among groups. Gene ontology (GO) enrichment showed differential expression between the 7 PSU and 29 PSU groups for seven genes with activities as neurotransmitter transmembrane transporters and neurotransmitter: sodium symporters. Comparing to the 18 PSU group, 16 genes with activities in gas or oxygen transport were down-regulated in the 7 PSU group. No such differences in expression of gas transport genes was found between the 18 PSU and 29 PSU groups. Overall, our exploratory transcriptome analysis suggested that fish in the low-salinity 7 PSU group exhibited high gene expression in the osmoregulation and gas transport pathways. Our results at the histological and gene expression levels suggest why rearing juvenile H. otakii in salinities of 12–29 PSU is optimal for commercial aquaculture production.

The importance of increasing crop production while reducing resource inputs and land-use change cannot be overstated especially in light of climate change and a human population growth projected to reach nine billion this century. Mutualistic plant–microbe interactions offer a novel approach to enhance agricultural productivity while reducing environmental costs. In concert with other novel agronomic technologies and management, plant-microbial mutualisms could help increase crop production and reduce yield losses by improving resistance and/or resilience to edaphic, biologic, and climatic variability from both bottom-up and top-down perspectives.

This paper proposes new methods to extract ground points and segment non-ground objects based on the spherical coordinates of point clouds collected by the 3-D LiDAR sensor system. Ground points extraction and non-ground objects segmentation are two primary issues in environment perception of autonomous driving. Firstly, the new method to extract ground points is described in this paper. It is based on the breakpoints and turning points of the radial distance curve in the spherical coordinates without assuming the road is located in the lowest. Then the algorithm for non-ground objects segmentation is proposed, which uses azimuth angle and radial distance in the spherical coordinates as judgment criterion. This algorithm works efficiently and it can avoid over-segmentation and under-segmentation. Finally, the experimental results using the point clouds acquired by the sensor Velodyne HDL-32E are presented. Comparing to the existing methods, the results show the advantages of methods based on the spherical coordinates.

This paper focuses on the size distribution measurement of coal fragments by digital imaging processing. The fast and precise measurement of coal fragments, which is important to understand the crack propagation and energy dissipation process of coal failure, has not been achieved by previous research. In this paper, an image analysis method using MATLAB is proposed to measure fragment size distribution of coal fragments. The acquisition setup, analysis step and coding process for fragment size distribution measurement by digital imaging processing are introduced in detail. The statistical size distribution of coal fragments measured by image processing is compared with the theoretical distribution function and manual sieving results. This paper provides an innovative and efficient method for size distribution measurement in the study of coal failure process.

The sustainable and clean mining of coal is essential for Australia and the world as coal is a key energy source. However, with the increase of mining depth, many coalmines are facing potential coal burst hazards as deep mining always associated with high gravitational stress and complicated geology. More recently, the coal burst risk is highlighted by accidents happened at Austar and Appin coalmines in Australia. Assumedly due to long time mining history with relatively shallow mining depth, coalmines in Australia has no coal burst history and corresponding risk controlling plans, technics and equipment. This paper proposes a novel method for coal burst risk prediction based on fractal dimension analysis of AE spatial distribution. Besides, this paper introduces the mathematical analysis method of fractal dimension based on dimension calculation formula and MATLAB coding. Finally, obvious fractal dimension decrease of AE spatial distribution is observed in experimental study of coal samples with high burst propensity, which promises the feasibility of coal bursts prediction through AE monitoring.

The ejection velocity associated with coal burst is an important parameter for support and protection structure design against coal ejection, as the support or protection design rationale is to dissipate or absorb the kinetic energy carried by ejected coal. This paper provides a novel method to estimate the average particle ejection velocity of rib burst based on the energy dissipation and coal fragmentation of coal brittle failure. This research shows that the scale of kinetic energy released by coal burst in underground roadways can reach over 107 J, which can offer ejected coal with an over 26 m/s initial velocity and cause serious even fatal injury to miners without sufficient protection.

In recent years, organic-inorganic hybrid perovskite photodetectors (PDs) have been regarded as promising next-generation PDs. However, the commercialization of the perovskite PDs still faces significant challenges, one of which is the poor stability. Herein, we demonstrate MgO/ZnO microsphere (MS) bilayer structure for improving the device stability with high detectivity. In this MgO/ZnO MS bilayer, ZnO MS array scaffold can facilitate the penetration of perovskite into nano-arrays and benefits the light harvest efficiency due to the special microsphere array structure, which behaves a big gap between aligned nanostructures. MgO passivates the interface between ZnO and perovskite, enhancing the device stability and promoting the carrier transport. Finally, our PDs with the bilayer structure exhibit high performance with the on/off ratio of up to more than 7.0 × 104, the linear dynamic range of 87.7 dB, and the detectivity of 1.5 × 1012 Jones, all of which are better than those of the device without MgO. More importantly, the device with the bilayer structure shows better stability compared with the device without MgO. Under illumination with the optical power of 314 mW/cm2, the photocurrent of the device with MgO shows almost no attenuation after continuous illumination for 30 min. In addition, after storing in air for 15 days, the performance of the device with MgO exhibits slight attenuation and the on/off ratio is still as high as 2.3 × 104, indicating that the device has good storage stability.

The photoelectric properties of conductive films are improved by doping Ag on aluminum-doped zinc oxide (AZO) films by laser induced forward transfer (LIFT). Firstly, the picosecond laser induced transfer mechanism of Ag films was revealed by numerical simulation; then, different-thickness Ag films were deposited on the AZO films by picosecond LIFT. When the film thickness is 30 nm and 50 nm, we have successfully obtained some Ag-AZO films with better optoelectronic properties by adjusting the laser parameters.

It has been well accepted by mining researchers that coal tends to undergo abrupt fracture under the coupling effect of dynamic and static loads. Hence, the study of influence of coupled static and dynamic loads on coal failure behaviour is meaningful for the understanding of coal burst. In this paper, PFC modelling of SHPB test is adopted to investigate the fracture mode and energy evolution of Australian hard coal under different combinations of pre-stress levels and impact velocities. Results have shown that high dynamic load will make the fracture mode and energy release of coal samples more violent even the static load is low. Although the strain energy increases with pre-stress level, the kinetic energy remains on a low level with the increase of pre-stress level when the impact velocity is 4 m/s.

Coal bursts are a serious dynamic hazard for underground coalmines, and they attract the extensive interest of studies from mining and geotechnical researchers worldwide. More recently, coal-burst incidents were reported in some Australian coalmines as a result of inadequate geological assessment of coal-burst hazards. The coal-burst process is closely associated with the accumulation of elastic energy and the rapid dissipation of kinetic energy. This paper introduces the essential geological conditions for energy accumulation, and the likely precursors for rapid energy dissipation leading to coal burst, which can be used by Australian coalmines to determine their coal-burst risk accordingly. Different energy forms and their transformations during the coal-burst process are introduced in detail in this paper. The dominant geological factors resulting in the accumulation of massive energy are analyzed, and the likely precursors associated with the instant release of elastic energy are discussed.

OBJECTIVE: To describe spinal epidural lipomatosis (SEL) of the lumbar region and evaluate the relative versus absolute values of epidural fat (EF) to determine which is more appropriate when using magnetic resonance imaging (MRI). DESIGN: Comparative study. SETTING: Hospital. PARTICIPANTS: Eight SEL patients and 40 healthy adults. INTERVENTIONS: MRI measurement of EF. OUTCOME MEASURES: The MRI-based EF thickness, cutoff value, and coefficient of variation (CV) were calculated. Frequency distribution maps for the absolute EF value and the relative EF/DuS value were created. RESULTS: SEL involved L3 − L4 in all cases. The mean EF thickness was 12.11 ± 2.28 mm (range: 9.91 − 16.86 mm), and the average diameter of the dural sac (DuS) was 20.02 ± 2.64 mm; the EF/DuS ratio was 0.61 ± 0.03. In controls, the average EF thickness was 7.35 ± 1.68 mm (range: 4.81 − 10.92 mm), and the average DuS was 20.86 ± 2.11 mm; the EF/DuS ratio was 0.35 ± 0.08. The relative and absolute values were significantly higher in the SEL group than in the normal group. A cutoff value of 9.8 mm could distinguish SEL patients from normal individuals. For the SEL group, the CV of the relative values (4.9%) was lower than that of the absolute values (18.8%). The frequency distribution map showed that the distribution of relative values was more concentrated than that of the absolute values for both groups. CONCLUSION: Based on the frequency distribution and CVs, the relative value of EF/DuS maybe a better measure for diagnosing SEL than the absolute EF value.

Due to public concerns about the decreasing supply of blue water and increasing heat and drought stress on plant growth caused by urbanization, increasing human population and climate change, interest in crassulacean acid metabolism (CAM), a specialized type of photosynthesis enhancing water-use efficiency (WUE) and drought tolerance, has increased markedly. Significant progress has been achieved in both basic and applied research in CAM plants since the beginning of this century. Here we provide a brief overview of the current status of CAM research, and discuss future needs and opportunities in a wide range of areas including systems biology, synthetic biology, and utilization of CAM crops for human benefit, with a focus on the following aspects: 1) application of genome-editing technology and high-throughput phenotyping to functional genomics research in model CAM species and genetic improvement of CAM crops, 2) challenges for multi-scale metabolic modeling of CAM systems, 3) opportunities and new strategies for CAM pathway engineering to enhance WUE and drought tolerance in C3 (and C4) photosynthesis crops, 4) potential of CAM species as resources for food, feed, natural products, pharmaceuticals and biofuels, and 5) development of CAM crops for ecological and aesthetic benefits.

Memristor is being considered as a game changer for the realization of neuromorphic hardware systems due to its similarity with biological synapse. Recent studies show that memristor crossbar can provide high density and high performance neural network hardware implementation at low power due to its physical layout, nano scale size and low power consumption feature. This paper describes the training method that can be used for the implementation of memristive multi-layer neural network with ex-situ method. We mimic the behavior of memristor crossbar in software training process to achieve more accurate and close computations to hardware. Voltage divider has been used to calculate the dot product in this method. To demonstrate the accuracy and effectiveness of this method, different patterns and non-separable functions using memristor crossbar structures are simulated. The results demonstrate that more accurate computations can be produced using this learning method for ex-situ. It also reduces the learning time of functions.