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Image classification is a kind of image processing technology, which can recognize different things by the feature information given by pictures. With the rapid development of science and technology and people's higher and higher demand for quality of life, image automatic classification technology has been applied to various fields of development. When we classify the image, the traditional image classification method can not accurately grasp the internal relationship between the recognition objects, and the traditional method also has the limitation of the recognition object's feature expression because of the too high characteristic dimension of the data, so the experimental results are not ideal. In view of the above content, this paper proposes an image detection method based on convolutional neural network. The experimental algorithm mainly refers to deep learning and convolutional neural network. Different from the traditional image classification methods, the deep convolution neural network model can be used for feature learning and image classification at the same time. By improving the structure of each part of the experiment and optimizing the convolution neural network model, the over fitting phenomenon can be prevented, and then the accuracy of image detection can be improved. The experiment on cifar-10 database shows that the improved deep learning model of this method has achieved effective results in image detection.

We present extensive spectroscopic observations for one of the closest type Ia supernovae (SNe Ia), SN 2014J discovered in M82, ranging from 10.4 days before to 473.2 days after B-band maximum light. The diffuse interstellar band (DIB) features detected in a high-resolution spectrum allow an estimate of line-of-sight extinction as Av=1.9+/-0.6 mag. Spectroscopically, SN 2014J can be put into the high-velocity (HV) subgroup in Wang's classification with a velocity of Si~II 6355 at maximum light as about 12200 km/s, but has a low velocity gradient (LVG, following Benetti's classification) as 41+/-2 km/s/day, which is inconsistent with the trend that HV SNe Ia generally have larger velocity gradients. We find that the HV SNe Ia with LVGs tend to have relatively stronger Si III (at ~4400 Angstrom) absorptions in early spectra, larger ratios of S II 5468 to S II 5640, and weaker Si II 5972 absorptions compared to their counterparts with similar velocities but high velocity gradients. This shows that the HV+LVG subgroup of SNe Ia may have intrinsically higher photospheric temperature, which indicates that their progenitors may experience more complete burning in the explosions relative to the typical HV SNe Ia., Comment: Accepted by MNRAS, 13 figures

Obstructive sleep apnea (OSA) is associated with the management of atrial fibrillation (AF). This manuscript aims to discuss the effects of continuous positive airway pressure (CPAP) in patients with rhythm control strategies and patients with different ages, weights and length of follow-up.We searched Embase, PubMed, Cochrane, Web of Science and Ovid for relevant studies (from inception to 7 July 2019; English). The primary outcome was documented AF recurrence in CPAP users and nonusers. We assessed pooled data by use of a random-effects model.Nine prospective cohort studies with a total of 2134 participants met the inclusion criteria. Results showed that complementary CPAP therapy reduced AF recurrence (RR = 0.63; 95% CI, 0.56-0.72). In subgroup analyses, the benefits of CPAP were stronger in patients younger than 60 years old ( 60 years old: RR, 0.59; 95% CI, 0.50-0.68 vs. ≥ 60 years old: RR, 0.73; 95% CI, 0.59-0.91), with a body mass index (BMI) of less than 30 ( 30: RR, 0.53; 95% CI, 0.37-0.77 vs. ≥ 30: RR, 0.65; 95% CI, 0.55-0.77) or with less follow-up time (≤ 1 year: RR, 0.57; 95% CI, 0.42-0.79 vs. 1 year: RR, 0.64; 95% CI, 0.53-0.78).Complementary CPAP therapy reduces the risk of AF recurrence in OSA patients with rhythm control strategies. In addition to weight control and early AF intervention, CPAP compliance should be recommended along with periodic adjustments as necessary.

Background and aims Angiopoietin-like protein 8 (ANGPTL8) is a hormone involved in regulating lipid metabolism. Patients with coronary artery disease have markedly higher plasma levels of ANGPTL8 than controls; however, the role of ANGPTL8 in atherosclerosis has not been explored. Therefore, we explored the effects of ANGPTL8 on atherosclerosis development in a mouse model. Methods We induced experimental atherosclerosis in ApoE−/− mice ANGPTL8-knockdown. and ANGPTL8-overexpression ApoE−/− mice. We also explored the mechanism using ANGPTL8-overexpression macrophages. Results ANGPTL8 expression was increased in human and mouse atherosclerotic lesions. ANGPTL8 overexpression promoted the development of atherosclerosis whereas ANGPTL8 knockdown protected against atherosclerosis. Immunofluorescence co-staining results showed that ANGPTL8 was expressed in macrophages in atherosclerotic plaques. Compared with wild type cells, ANGPTL8-overexpressing macrophages, including bone marrow-derived macrophages and Raw 264.7 macrophages, showed enhanced foam cell formation and increased accumulation of cholesterol that was induced by increased uptake and decreased efflux of cholesterol. The results of this study also showed that ANGPTL8 induced the expression of CD36 and scavenger receptor (SR)-A, and inhibited the expression of SR-BI. Conclusions Our findings demonstrate an unanticipated role of ANGPTL8 in the development of atherosclerosis and regulation of foam cell formation. ANGPTL8 may be a promising new target for atherosclerosis.

To investigate the effects of Tangnaikang (TNK), a mixture of five herbal plant extracts, on inflammation-mediated insulin resistance and B-cell apoptosis in SHR.Cg-Leprcp/NDmcr (SHR-cp) rats.Seven-week-old SHR-cp rats were randomly divided into a control (CON) group and a TNK (3.24 g/kg) group. Wistar-Kyoto rats at the same age were used as the normal control group. After 7 weeks of continuous intragastric administration of TNK, the glucose metabolic status and insulin sensitivity of the rats were evaluated by assessing fasting serum glucose (FBG), the oral glucose tolerance test (OGTT), fasting serum insulin (FINS), and the insulin sensitivity index (ISI). Serum tumor necrosis factor-a (TNF-a), interleukin-6 (IL-6), C-reactive protein (CRP) and adiponectin were measured via enzyme-linked immunosorbent assays. Macrophage infiltration and apoptosis in adipose tissues were detected through F4/80 immunohistochemistry and the terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay. Islet morphology and B-cell apoptosis were investigated using double immunofluorescence staining and the TUNEL assay. The expression of cytokine genes in adipose tissue, the liver, and the pancreas was detected in real-time polymerase chain reaction assays. The expression and phosphorylation levels of insulin signaling-, inflammation-, and B-cell survival-related proteins in the liver and pancreas of SHR-cp rats were detected by western blotting.TNK (3.24 g/kg) treatment significantly decreased body weight, FBG and FINS; improved impaired glucose tolerance; increased the ISI; reduced serum levels of TNF-a, CRP and IL-6; and increased serum adiponectin. The mRNA expression of inflammatory markers was markedly reduced in the liver, pancreas, and adipose tissue. F4/80- and TUNEL-positive cells in adipose tissues were decreased, as was the number of TUNEL-positive B-cells. The phosphorylation of c-Jun N-terminal kinase and that of insulin receptor substrate-1 at serines 307 and 1101 was significantly decreased. In the pancreas, the expression of nuclear factor kappa-light chain-enhancer of activated B cells-p65 was significantly decreased, and phosphoinositide 3-kinase and IRS-2 were significantly increased.TNK was able to improve insulin resistance and B-cell apoptosis in SHR-cp rats, which might be associated with its ability to relieve the overall and local metabolic inflammatory responses observed in SHR-cp rats.

Obstructive sleep apnea (OSA) is associated with increased levels of systemic inflammatory markers, increased arterial stiffness, and endothelial dysfunction, which may lead to increased cardiovascular risk. We aimed to quantify the effects of continuous positive airway pressure (CPAP) on cardiovascular biomarkers and to establish predictors of response to CPAP. We searched PubMed and the Cochrane Library from inception to May 31, 2017. Randomized controlled trials (RCTs) assessing the efficacy of CPAP on high-sensitivity C-reactive protein (hs-CRP), interleukin 6 (IL-6), tumor necrosis factor- alpha (TNF-α), augmentation index (AIx), pulse wave velocity (PWV), and flow-mediated dilatation (FMD) in patients with OSA were selected by consensus. We included 15 RCTs comprising 1090 patients in the meta-analysis. The pooled standard mean difference (SMD) of effect of CPAP on hs-CRP was − 0.64 (95% confidence interval (CI) − 1.19 to − 0.09; P = 0.02). CPAP was associated with a reduction in AIx of 1.53% (95% CI, 0.80 to 2.26%; P

Due to China’s remarkable socioeconomic development, more and more protected areas have been affected by human activities which resulted in habitat loss and biodiversity decline. Timely and accurat...

Timely and accurate understanding of spatiotemporal variations of urban CO2 emissions is important in the interaction between human activities and the environment. However, studies that consider spatiotemporal variations of urban CO2 emissions at multiple scales are still lacking. In this study, we combined the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) nighttime light images, statistical energy consumption data, and urban area data to assess spatiotemporal variations of urban CO2 emissions in China from national scale down to regional and urban agglomeration scales between 1997 and 2012. The results reveals that China has been experiencing strikingly spatiotemporal variations of urban CO2 emissions during the study period. At the national scale, urban areas that experienced High-growth of CO2 emissions accounted for 22.16% of the total urban areas in 2012. High-growth of urban CO2 emissions covered 18.09% of the total urban areas in the eastern region. Relatively-high-growth of urban CO2 emissions accounted for 46.14% of the total urban areas in the central region. Around 5766 km2 of urban areas experienced Relatively-high-growth of urban CO2 emissions, accounting for 39.04% of the total urban areas in the western region. The Beijing–Tianjin–Tangshan (BTT) and Sichuan–Chongqing (SC) had the most extensive Low-growth, accounting for approximately 8.97% and 6.15% of their total urban areas. It should be pointed out that about 7815 km2 (11.58%) of peri-urban areas experienced High-growth of CO2 emissions. Meanwhile, we have also found that urban CO2 emissions had significant positive correlations with urban GDP (Gross Domestic Product) and urban population in China at multiple scales. Our findings can provide useful information for local authorities to guide their policies in CO2 emissions mitigation.

Formaldehyde (FA) is widely used in chemical industry, which is also known as a common indoor air pollutant. Exposure of FA has been associated with multiple detrimental health effects. Our previous study showed that FA could inhibit the development of T lymphocytes in mice, leading to impaired immune functions. Macrophages are important innate immune cells which trigger inflammatory responses in tissues. In the present study, FA exposure at 2.0 mg/m3 was found to enhance the pro-inflammatory responses of macrophages in male BALB/c mice, which was confirmed by elevated pro-inflammatory cytokine release and NO secretion in macrophages isolated from the FA-exposed mice and in vitro macrophage models upon lipopolysaccharide stimulation. Glycolysis is the key metabolic process for the classical activation of macrophages, which was found to be elevated in the in vitro macrophage models treated with FA at 50 and 100 μM concentrations for 18 h. HIF-1α and the associated proteins in its signaling cascade, which are known to mediate glycolytic metabolism and inflammatory responses, were found to be upregulated by 50 and 100 μM FA in THP-1 derived and RAW264.7 macrophage models, and the enhanced pro-inflammatory responses induced by 100 μM FA were reversed by inhibitory compounds interfering with glucose metabolism or suppressing HIF-1α activity. Collectively, the results in this study revealed that FA could enhance the pro-inflammatory responses of macrophages through the induction of glycolysis, which outlined the FA-triggered metabolic and functional alterations in immune cells.

With the rapid development of satellite imaging technology, large amounts of satellite images with high spatial resolutions are now available. High-resolution satellite imagery provides rich texture and structure information, which in the meantime poses a great challenge for automatic satellite scene recognition. In this study, a novel integration method of fuzzy theory and particle swarm optimization (IFTPSO) is proposed to achieve an increased accuracy of satellite scene recognition (SSR) in high-resolution satellite imagery. The particle encoding, fitness function and swarm search strategy are designed for IFTPSO-SSR. The IFTPSO-SSR method was evaluated using the satellite scenes from QuickBird, IKONOS and ZY-3. IFTPSO-SSR outperformed three traditional recognition methods with the highest recognition accuracy. The parameter sensitivity of IFTPSO-SSR was also discussed. The proposed method of this study can enhance the performance of satellite scene recognition in high-resolution satellite imagery, and thereby advance the research and applications of artificial intelligence and satellite image analysis.

There is no consensus on the effect of China’s rapid urban expansion on the fine particulate matter (PM2.5) emissions from fossil fuel combustion (PC). Previous studies usually focused on the environmental effect of urban expansion from a single mode (e.g., spatial expansion). However, studies that simultaneously considered and compared the effect from spatial and socioeconomic modes are still lacking. Thus, we combined multiple data sources (e.g., nighttime light data, urban land datasets, and PC) and econometric methods to evaluate the effect of urban expansion on PC within different regions from spatial and socioeconomic modes. The results show that China’s urban socioeconomic expansion (UE) and urban spatial expansion (US) increased from 68.50% and 11.81 × 10−4, respectively, in 1992 to 72.23% and 66.86 × 10−4, respectively in 2012. The UE is the Granger cause of the increased PC in China. Through variance decomposition analysis, we also found that the UE contributed much more to the PC in China than the US. When comparing the different regions, we recognized that the UE was the key factor in explaining the increase in the PC in the eastern and northeastern regions, and the US could effectively explain the changes in the PC in the central region. The study provides a novel perspective for quantifying the effect of urban intensive and extensive development on haze pollution.

Purpose There are two kinds of thawing temperatures commonly adopted in cancer cryosurgery. We attempted to compare their efficacy differences in this study to optimize the surgical method. Method Forty-five C57BL/6 J mice with GFP-labeled Lewis lung cancer were randomized into three groups ( n = 15 for each): control group, T0 group (thawing temperature 0 °C), and T40 group (thawing temperature 40 °C). Cryoablation was performed using a combined surgical system. When the ice ball reached the border of the tumor, they were rewarmed to 0 °C and 40 °C, respectively, using a single freeze–thaw cycle. After the surgery, weight of these mice, length/width and the fluorescence intensity (FI) of the tumors were recorded. All mice were sacrificed on Day 14 after the procedures and their xenografts were excised and weighed immediately. We also checked for pulmonary metastasis, and examined tumor specimens using HE staining. Results Body weights, tumor volumes and FI in the three groups did not differ significantly at baseline. On Day 14, 39% of the tumors in the T0 group decreased in volume, whereas only 17% in the T40 group did. The average FI in the control group increased by 60%, but declined by 72% in T0 mice and 69% in T40 mice. Tumor inhibition rates were 71.64% in the T0 group and 68.12% in the T40 group. Lung metastases rates and histological changes were compatible between the two intervention groups. Conclusion Using 0 °C as the thawing temperature may have more potential benefits in cryoablation efficacy.

The rapid development of global industrialization and urbanization has resulted in a great deal of electric power consumption (EPC), which is closely related to economic growth, carbon emissions, and the long-term stability of global climate. This study attempts to detect spatiotemporal dynamics of global EPC using the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) nighttime stable light (NSL) data. The global NSL data from 1992 to 2013 were intercalibrated via a modified invariant region (MIR) method. The global EPC at 1 km resolution was then modeled using the intercalibrated NSL data to assess spatiotemporal dynamics of EPC from a global scale down to continental and national scales. The results showed that the MIR method not only reduced the saturated lighted pixels, but also improved the continuity and comparability of the NSL data. An accuracy assessment was undertaken and confined that the intercalibrated NSL data were relatively suitable and accurate for estimating EPC in the world. Spatiotemporal variations of EPC were mainly identified in Europe, North America, and Asia. Special attention should be paid to China where the high grade and high-growth type of EPC covered 0.409% and 1.041% of the total country area during the study period, respectively. The results of this study greatly enhance the understanding of spatiotemporal dynamics of global EPC at the multiple scales. They will provide a scientific evidence base for tracking spatiotemporal dynamics of global EPC.

Periodic inundation of floodplains and wetlands is critical for the well being of ecosystems. This study proposes a simple but efficient model that integrates time series daily flow data and the Landsat-derived Water Observation from Space (WOfS) product to model the spatio-temporal flood inundation dynamics of the Murray-Darling Basin. A zone-gauge framework is adopted in order to reduce the hydrologic complexity of the large river basin. Under this framework, flood frequency analysis was conducted at each gauge station to identify historical peak flows and their annual exceedance probabilities. The results were then linked with the WOfS dataset through date to model the inundation probability in each zone. Inundation frequency was derived by simply overlaying the yearly inundation extent from 1988 to 2015 and counting the inundation times. Both the resultant inundation frequency map and inundation probability map are of ecological significance for the survival and prosperity of riparian ecosystems. The assumptions of the model were validated carefully to enhance its theoretical basis. The WOfS dataset was also compared with another independent water observation dataset to cross-validate its reliability. It is hoped that with the development of more and more global high-resolution surface water datasets, this study could inspire more studies that integrate surface water datasets with hydrological observations for flood inundation modeling.

Machine learning techniques, especially deep neural networks (DNNs), have been widely adopted in various applications. However, DNNs are recently found to be vulnerable against adversarial examples, i.e., maliciously perturbed inputs that can mislead the models to make arbitrary prediction errors. Empirical defenses have been studied, but many of them can be adaptively attacked again. Provable defenses provide provable error bound of DNNs, while such bound so far is far from satisfaction. To address this issue, in this paper, we present our approach named Robustra for effectively improving the provable error bound of DNNs. We leverage the adversarial space of a reference model as the feasible region to solve the min-max game between the attackers and defenders. We solve its dual problem by linearly approximating the attackers' best strategy and utilizing the monotonicity of the slack variables introduced by the reference model. The evaluation results show that our approach can provide significantly better provable adversarial error bounds on MNIST and CIFAR10 datasets, compared to the state-of-the-art results. In particular, bounded by L^infty, with epsilon = 0.1, on MNIST we reduce the error bound from 2.74% to 2.09%; with epsilon = 0.3, we reduce the error bound from 24.19% to 16.91%.

Wetland flooding is significant for the flora and fauna of wetlands. High temporal resolution remote sensing images are widely used for the timely mapping of wetland flooding but have a limitation of their relatively low spatial resolutions. In this study, a novel method based on random forests and spatial attraction models (RFSAM) was proposed to improve the accuracy of sub-pixel mapping of wetland flooding (SMWF) using remote sensing images. A random forests-based SMWF algorithm (RM-SMWF) was developed firstly, and a comprehensive complexity index of a mixed pixel was formulated. Then the RFSAM-SMWF method was developed. Landsat 8 Operational Land Imager (OLI) images of two wetlands of international importance included in the Ramsar List were used to evaluate RFSAM-SMWF against three other SMWF methods, and it consistently achieved more accurate sub-pixel mapping results in terms of visual and quantitative assessments in the two wetlands. The effects of the number of trees in random forests and the complexity threshold on the mapping accuracy of RFSAM-SMWF were also discussed. The results of this study improve the mapping accuracy of wetland flooding from medium-low spatial resolution remote sensing images and therefore benefit the environmental studies of wetlands.

Supernova (SN) 2018oh (ASASSN-18bt) is the first spectroscopically-confirmed type Ia supernova (SN Ia) observed in the $Kepler$ field. The $Kepler$ data revealed an excess emission in its early light curve, allowing to place interesting constraints on its progenitor system (Dimitriadis et al. 2018, Shappee et al. 2018b). Here, we present extensive optical, ultraviolet, and near-infrared photometry, as well as dense sampling of optical spectra, for this object. SN 2018oh is relatively normal in its photometric evolution, with a rise time of 18.3$\pm$0.3 days and $\Delta$m$_{15}(B)=0.96\pm$0.03 mag, but it seems to have bluer $B - V$ colors. We construct the "uvoir" bolometric light curve having peak luminosity as 1.49$\times$10$^{43}$erg s$^{-1}$, from which we derive a nickel mass as 0.55$\pm$0.04M$_{\odot}$ by fitting radiation diffusion models powered by centrally located $^{56}$Ni. Note that the moment when nickel-powered luminosity starts to emerge is +3.85 days after the first light in the Kepler data, suggesting other origins of the early-time emission, e.g., mixing of $^{56}$Ni to outer layers of the ejecta or interaction between the ejecta and nearby circumstellar material or a non-degenerate companion star. The spectral evolution of SN 2018oh is similar to that of a normal SN Ia, but is characterized by prominent and persistent carbon absorption features. The C II features can be detected from the early phases to about 3 weeks after the maximum light, representing the latest detection of carbon ever recorded in a SN Ia. This indicates that a considerable amount of unburned carbon exists in the ejecta of SN 2018oh and may mix into deeper layers., Comment: 48 pages, 23 figures. This paper is part of a coordinated effort between groups. Accepted for publication in ApJ

Objective Obstructive sleep apnea (OSA) is a major risk factor for cardiovascular mortality. Apnea-induced chronic intermittent hypoxia (CIH) is a primary pathophysiological manifestation of OSA that promotes various cardiovascular alterations, such as aortic vascular remodeling. In this study, we investigated the association between angiopoietin-like proteins 8 (ANGPTL8) and CIH-induced aortic vascular remodeling in mice. Methods C57BL/6J male mice were divided into four groups: Normoxia group, ANGPTL8−/− group, CIH group, CIH + ANGPTL8−/− group. Mice in the normoxia group and ANGPTL8−/− group received no treatment, while mice in the CIH and CIH + ANGPTL8−/− group were subjected to CIH (21%–5% O2, 180 s/cycle, 10 h/day) for 6 weeks. At the end of the experiments, intima-media thickness (IMT), elastin disorganization, and aortic wall collagen abundance were assessed in vivo. Immunohistochemistry and Western-blot were used to detect endoplasmic reticulum stress (ERS) and aortic vascular smooth muscle cell proliferation. ANGPTL8 shRNA and ANGPL8 overexpression were used in aortic vascular smooth muscle cells to investigate the mechanism of ANGPTL8 in CIH. Results Compared to the control group, CIH exposure significantly increased intima-media thickness (IMT), elastic fibers disorganization, and aortic wall collagen abundance. CIH also significantly increased blood pressure, induced hyperlipidemia, as well as the expression of ERS protein activating transcription factor-6 (ATF6) and aortic vascular smooth muscle cell proliferation. Contrary, ANGPTL8−/− significantly mitigated the CIH-induced vascular remodeling; ANGPTL8−/− decreased CIH-induced hypertension and hyperlipidemia, inhibited the protein expression of ATF6, and aortic vascular smooth muscle cell proliferation. Moreover, our in vitro study suggested that CIH could induce ANGPTL8 expression via hypoxia-inducible factor (HIF-1α); ANGPTL8 induced proliferation of aortic vascular smooth muscle cells via the ERS pathway. Conclusion ANGPTL8−/− can prevent CIH-induced aortic vascular remodeling, probably through the inhibition of the ERS pathway. Therefore, ANGPTL8 might be a potential target in CIH-induced aortic vascular remodeling.

Background Orexin, a neuropeptide primarily secreted by neurons in the lateral hypothalamus, has been implicated in Parkinson’s disease (PD). Studies on the relationship between plasma orexin-A levels and PD are rare. Objectives This study aimed to assess levels of plasma orexin-A in the progression of PD and to evaluate the correlation between orexin-A levels and non-motor symptoms. Methods Enzyme-linked immunosorbent assay was used to determine plasma orexin-A levels in 117 healthy controls and 121 PD patients, including those with early (n = 68), medium (n = 40) and advanced (n = 13) stages of the disease. Evaluation of motor symptoms and non-motor symptoms in PD patients, such as sleep disorders, cognitive dysfunction, neuropsychiatric symptoms, autonomic nervous dysfunction, hyposmia and PD-related pain, were assessed by the associated scales. Results Plasma orexin-A levels were significantly higher in PD patients compared to healthy controls. Orexin-A levels were elevated in early-stage and medium-stage PD compared to healthy controls, but were decreased in advanced-stage PD. Orexin-A levels were negatively correlated with the Unified Parkinson’s Disease Rating Scale Part III scores, disease duration, and dopamine receptor agonist doses, and were positively correlated with the Pittsburgh Sleep Quality Index, REM-sleep Behavior Disorder Questionnaire, 14-item Hamilton Anxiety Scale, Mini-Mental State Examination, and Non-motor Symptom Scale items 22–24 scores. Conclusions We found for the first time that plasma orexin-A levels were increased in early-stage and medium-stage PD and were decreased in advanced-stage PD. Furthermore, orexin-A levels were correlated with the non-motor symptoms of insomnia, REM-sleep behavior disorder, anxiety, cognitive dysfunction, and renal dysfunction.

At this stage, the domestic animal husbandry industry has a very important support role in the domestic market economy, and the sheep industry has received extensive attention as one of the important industries. Limb movements and activities can directly reflect the adaptability of sheep to the breeding environment and conditions, and provide a richer scientific and technical experience for sheep breeding. The sheep target detection is an important prerequisite for grasping the movement behavior of sheep. Therefore, how to efficiently and accurately identify and detect sheep has become the key to the development of sheep industry at this stage. In this paper, the Faster-RCNN neural network model based on the Soft-NMS algorithm is studied, which realizes the real-time detection and positioning of sheep under complex breeding conditions, and improves the accuracy of recognition while ensuring the detection speed. Experiments show that the proposed detection model can detect sheep with 95.32% accuracy and mark the location of the target in real time, which provides an effective data foundation for sheep behavior research and helps promote the development of high-tech animal husbandry effect.

Regional flood risk caused by intensive rainfall under extreme climate conditions has increasingly attracted global attention. Mapping and evaluation of flood hazard are vital parts in flood risk assessment. This study develops an integrated framework for estimating spatial likelihood of flood hazard by coupling weighted naive Bayes (WNB), geographic information system, and remote sensing. The north part of Fitzroy River Basin in Queensland, Australia, was selected as a case study site. The environmental indices, including extreme rainfall, evapotranspiration, net-water index, soil water retention, elevation, slope, drainage proximity, and density, were generated from spatial data representing climate, soil, vegetation, hydrology, and topography. These indices were weighted using the statistics-based entropy method. The weighted indices were input into the WNB-based model to delineate a regional flood risk map that indicates the likelihood of flood occurrence. The resultant map was validated by the maximum inundation extent extracted from moderate resolution imaging spectroradiometer (MODIS) imagery. The evaluation results, including mapping and evaluation of the distribution of flood hazard, are helpful in guiding flood inundation disaster responses for the region. The novel approach presented consists of weighted grid data, image-based sampling and validation, cell-by-cell probability inferring and spatial mapping. It is superior to an existing spatial naive Bayes (NB) method for regional flood hazard assessment. It can also be extended to other likelihood-related environmental hazard studies.

Sub-pixel mapping of flood inundation (SMFI) is one of the hotspots in remote sensing and relevant research and application fields. In this study, a novel method based on the integration of Bayesian regulation back-propagation neural network (BRBP) and particle swarm optimization (PSO), so-called IBRBPPSO, is proposed for SMFI in river basins. The IBRBPPSO–SMFI algorithm was developed and evaluated using Landsat images from the Changjiang river basin in China and the Murray-Darling basin in Australia. Compared with traditional SMFI methods, IBRBPPSO–SMFI consistently achieves the most accurate SMFI results in terms of visual and quantitative evaluations. IBRBPPSO–SMFI is superior to PSO–SMFI with not only an improved accuracy, but also an accelerated convergence speed of the algorithm. IBRBPPSO–SMFI reduces the uncertainty in mapping inundation in river basins by improving the accuracy of SMFI. The result of this study will also enrich the SMFI methodology, and thereby benefit the environmental st...

China’s rapid industrialization and urbanization have resulted in a great deal of CO 2 (carbon dioxide) emissions, which is closely related to its sustainable development and the long term stability of global climate. This study proposes panel data analysis to model spatiotemporal CO 2 emission dynamics at a higher resolution in China by integrating the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) nighttime stable light (NSL) data with statistic data of CO 2 emissions. Spatiotemporal CO 2 emission dynamics were assessed from national scale down to regional and urban agglomeration scales. The evaluation showed that there was a true positive correlation between NSL data and statistic CO 2 emissions in China at the provincial level from 1997 to 2012, which could be suitable for estimating CO 2 emissions at 1 km resolution. The spatiotemporal CO 2 emission dynamics between different regions varied greatly. The high-growth type and high-grade of CO 2 emissions were mainly distributed in the Eastern region, Shandong Peninsula and Middle south of Liaoning, with clearly lower concentrations in the Western region, Central region and Sichuan–Chongqing. The results of this study will enhance the understanding of spatiotemporal variations of CO 2 emissions in China. They will provide a scientific basis for policy-making on viable CO 2 emission mitigation policies.

Flooding hazard evaluation is the basis of flooding risk assessment which has significances to natural environment, human life and social economy. This study develops a spatial framework integrating naive Bayes (NB) and geographic information system (GIS) to assess flooding hazard at regional scale. The methodology was demonstrated in the Bowen Basin in Australia as a case study. The inputs into the framework are five indices: elevation, slope, soil water retention, drainage proximity and density. They were derived from spatial data processed in ArcGIS. NB as a simplified and efficient type of Bayesian methods was used, with the assistance of remotely sensed flood inundation extent in the sampling process, to infer flooding probability on a cell-by-cell basis over the study area. A likelihood-based flooding hazard map was output from the GIS-based framework. The results reveal elevation and slope have more significant impacts on evaluation than other input indices. Area of high likelihood of flooding hazard is mainly located in the west and the southwest where there is a high water channel density, and along the water channels in the east of the study area. High likelihood of flooding hazard covers 45 % of the total area, medium likelihood accounts for about 12 %, low and very low likelihood represents 19 and 24 %, respectively. The results provide baseline information to identify and assess flooding hazard when making adaptation strategies and implementing mitigation measures in future. The framework and methodology developed in the study offer an integrated approach in evaluation of flooding hazard with spatial distributions and indicative uncertainties. It can also be applied to other hazard assessments.

An efficient copper(II)/tert-butyl hydroperoxide catalyst system [(Bpy)Cu(II)/TBHP] for the aminoxylation of different types of hydrocarbons under mild and ambient air conditions has been developed to furnish N-alkoxyamine derivatives in good to high yields. Ketones, esters, nitriles, toluene, ethylbenzene, heterocycles, cyclohexene, and cyclohexanes are well compatible in this system and the catalyst loading could be lowered to 0.5 mol%.

Urban flooding is one of the most costly and destructive natural hazards worldwide. Remote-sensing images with high temporal resolutions have been extensively applied to timely inundation monitoring, assessing and mapping, but are limited by their low spatial resolution. Sub-pixel mapping has drawn great attention among researchers worldwide and has demonstrated a promising potential of high-accuracy mapping of inundation. Aimed to boost sub-pixel urban inundation mapping (SUIM) from remote-sensing imagery, a new algorithm based on spatial attraction models and Elman neural networks (SAMENN) was developed and examined in this paper. The Elman neural networks (ENN)-based SUIM module was developed firstly. Then a normalized edge intensity index of mixed pixels was generated. Finally the algorithm of SAMENN-SUIM was constructed and implemented. Landsat 8 images of two cities of China, which experienced heavy floods, were used in the experiments. Compared to three traditional SUIM methods, SAMENN-SUIM attained higher mapping accuracy according not only to visual evaluations but also quantitative assessments. The effects of normalized edge intensity index threshold and neuron number of the hidden layer on accuracy of the SAMENN-SUIM algorithm were analyzed and discussed. The newly developed algorithm in this study made a positive contribution to advancing urban inundation mapping from remote-sensing images with medium-low spatial resolutions, and hence can favor urban flood monitoring and risk assessment.

Understanding how urban forms affect fine particulate (PM2.5) concentrations within different seasons is important for sustainable urban development. Thus, the purpose of this study was to quantify the relationships between urban forms and PM2.5 concentration change seasonally in 279 Chinese cities, with the explicit consideration of a comparative analysis between national and urban agglomeration scales. A comprehensive evaluation index system of urban forms was calculated based on six urban form metrics (total urban area (CA), number of patches (NP), landscape shape index (LSI), percentage of like adjacencies (PLADJ), patch cohesion index (COHESION), and aggregation index (AI)) by integrating three control variables (temperature, NDVI, and nighttime light). The spatial regression model was subsequently adopted to quantify the effects of urban forms on PM2.5 concentrations. The results revealed that, during the summer and autumn, only urban form compactness was significantly correlated with the PM2.5 concentrations, but more urban form metrics were significantly associated with the PM2.5 concentrations during the spring and winter in Chinese cities. The scattered urban form could effectively reduce the PM2.5 concentrations in the Yangtze River Delta, Pearl River Delta, and Chengdu-Chongqing but not in the Beijing-Tianjin-Hebei during the winter. The effects of urban forms on PM2.5 concentrations become increasingly noticeable from the national scale to the urban agglomeration scale with seasonal change. This study suggests that the urban form-PM2.5 concentration relationships are sensitive to seasonal variations across different regions. Thus, it is an important approach to solve PM2.5 pollution problem to construct an ideal urban form through flexible urban planning strategies.

The vegetation supply water index (VSWI = NDVI/LST) is an effective metric estimating soil moisture in areas with moderate to dense vegetation cover. However, the normalized difference vegetation index (NDVI) exhibits a long water stress lag and the land surface temperature (LST), sensitive to water stress, does not contribute considerably to surface soil moisture monitoring due to the constraints of the mathematical characteristics of VSWI: LST influences VSWI less when LST value is sufficiently high. This paper mathematically analyzes the characteristics of VSWI and proposes a new operational dryness index (surface water content temperature index, SWCTI) for the assessment of surface soil moisture status. SWCTI uses the surface water content index (SWCI), which provides a more accurate estimation of surface soil moisture than that of NDVI, as the numerator and the modified surface temperature, which has a greater influence on SWCTI than that of LST, as the denominator. The validation work includes comparison of SWCTI with in situ soil moisture and other remote sensing indices. The results show SWCTI demonstrates the highest correlation with in situ soil moisture, the highest correlation R = 0.801 is found between SWCTI and the 0&ndash, 5 cm soil moisture in a sandy loam. SWCTI is a functional and effective method that has a great potential in surface soil moisture monitoring.

Objective: Aortic aneurysm (AA) is a life-threatening cardiovascular disorder due to the predisposition for dissection and rupture. Chronic intermittent hypoxia (CIH) has protective effects on heart and brain against ischemia injury. However, whether CIH prevents against AA formation was not elucidated. The present study aimed to investigate the effect of CIH treatment on thoracic aortic aneurysms (TAA) in mice. Approach and Results: Seventy-five C57BL/6 mice 3 weeks of age were divided into three groups, i.e. Control group ( 21% O 2 , 24 h per day, 4 weeks, n = 15); β-aminopropionitrile (BAPN) group (oral administration BAPN 1g / kg / day, 21% O 2 , 24 h per day, 4 weeks, n = 30); CIH+BAPN group ( 5% -21% O 2 90s / cycle, 8h per day, 4 weeks; BAPN 1g / kg / day, n = 30). We found that CIH significantly reduced the incidence of TAA (18 of 30 versus 9 of 30; p CIHsignificantly down-regulated the expression of inflammation signaling pathways, up-regulated the expression of PI3K/AKT survival pathway and extracellular matrix homeostasis related pathway in BAPN induced TAA mice. Confirmed by real-time quantitative reverse-transcription-polymerase chain reaction (qRT-PCR) assays, CIHsignificantly inhibited the expression of IL-1β, TNF-α, MMP-9 and Cathepsin S, and increased the expression of hypoxia inducible factor-1α (HIF-1α), Lysyl oxidase (LOX), ITGB1 and COL1A2. Our findings also showed that the expression of MMP-9, MMP-2, cathepsin S, IL-1β, MCP-1 and Mac-2 increased in BAPN group and markedly decreased in CIH+BAPN group by immunohistochemistry staining. Besides, CIH also significantly increased the protein expression of HIF-1α, LOX and p-AKT by western blot analysis. Conclusions: The findings from our study suggest that CIH prevented the TAA development of BAPN-induced mice.

Introduction: Obstructive sleep apnea, a condition leading to chronic intermittent hypoxia (CIH), is an independent risk factor for cardiovascular disease and type 2 diabetes and is correlated with insulin resistance. Insulin stimulates production of nitric oxide (NO) in vascular endothelial cells through the IRS-1/PI3K/Akt/eNOS pathway (IRS-1, insulin receptor substrate 1; PI3K, phosphatidylinositol 3-kinase; eNOS, endothelial NO synthase). Endothelial cells directly expose to blood flow and respond to oxygen concentration change in flow. We wondered if and how CIH would affect insulin signalling/action in endothelial cells. Methods and Results: C57BL/6J mice were exposed to CIH (21%-5%, 90 s/cycle, 10 h/day) or intermittent air for 7 weeks. HUVECs were exposed to CIH (21%-5%, 1 h/cycle) for 24 h or 48 h with or without insulin. We observed that CIH increased systolic blood pressure and impaired endothelium-dependent relaxation of aortas in C57BL/6J mice. CIH increased IRS-1 phosphorylation at Ser307 and Ser612 and impaired insulin-stimulated phosphorylation of IRS-1 at Tyr896 and Akt/eNOS pathway in aortas. Furthermore, CIH activated hypoxia-inducible factor 1α (HIF-1α) and nuclear factor kappa B (NF-κB) in aortas. In vitro, CIH activated endothelial HIF-1α signaling, impaired endothelial insulin signaling and reduced insulin-mediated NO production. In addition, CIH resulted in mitochondria proton leak and elevated oxygen consumption in HUVECs. Increased oxygen consumption further leaded to endothelial hypoxia and HIF-1α induction. Pharmacological inhibition of proton leak ameliorated CIH-induced endothelial insulin resistance in HUVECs. Conclusion: Our data suggest that CIH induces insulin resistant endothelial dysfunction, which may be associated with HIF-1α induction and proton leak.

Vitamin BTo assess the effects of oral vitamin BWe searched CENTRAL, MEDLINE, Embase, and LILACS, as well as the WHO ICTRP and ClinicalTrials.gov. The latest search date was 17 July 2017. We applied no language restrictions. We also contacted authors of relevant trials to enquire about other published or unpublished studies and ongoing trials.Randomised controlled trials (RCTs) comparing the effect of oral versus IM vitamin BWe used standard methodological procedures expected by Cochrane. Our primary outcomes were serum vitamin BThree RCTs met our inclusion criteria. The trials randomised 153 participants (74 participants to oral vitamin BLow quality evidence shows oral and IM vitamin B

Background Vitamin B12 deficiency is common, and the incidence increases with age. Most people with vitamin B12 deficiency are treated in primary care with intramuscular (IM) vitamin B12. Doctors may not be prescribing oral vitamin B12 formulations because they may be unaware of this option or have concerns regarding its effectiveness. Objectives To assess the effects of oral vitamin B12 versus intramuscular vitamin B12 for vitamin B12 deficiency. Search methods We searched CENTRAL, MEDLINE, Embase, and LILACS, as well as the WHO ICTRP and ClinicalTrials.gov. The latest search date was 17 July 2017. We applied no language restrictions. We also contacted authors of relevant trials to enquire about other published or unpublished studies and ongoing trials. Selection criteria Randomised controlled trials (RCTs) comparing the effect of oral versus IM vitamin B12 for vitamin B12 deficiency. Data collection and analysis We used standard methodological procedures expected by Cochrane. Our primary outcomes were serum vitamin B12 levels, clinical signs and symptoms of vitamin B12 deficiency, and adverse events. Secondary outcomes were health-related quality of life, acceptability to patients, haemoglobin and mean corpuscular volume, total homocysteine and serum methylmalonic acid levels, and socioeconomic effects. We used GRADE to assess the quality of the evidence for important outcomes. We did not perform meta-analyses due to the small number of included trials and substantial clinical heterogeneity. Main results Three RCTs met our inclusion criteria. The trials randomised 153 participants (74 participants to oral vitamin B12 and 79 participants to IM vitamin B12). Treatment duration and follow-up ranged between three and four months. The mean age of participants ranged from 38.6 to 72 years. The treatment frequency and daily dose of vitamin B12 in the oral and IM groups varied among trials. Only one trial had low or unclear risk of bias across all domains and outcome measures. Two trials reported data for serum vitamin B12 levels. The overall quality of evidence for this outcome was low due to serious imprecision (low number of trials and participants). In two trials employing 1000 μg/day oral vitamin B12, there was no clinically relevant difference in vitamin B12 levels when compared with IM vitamin B12. One trial used 2000 μg/day vitamin B12 and demonstrated a mean difference of 680 pg/mL (95% confidence interval 392.7 to 967.3) in favour of oral vitamin B12. Two trials reported data on adverse events (very low-quality evidence due to risk of performance bias, detection bias, and serious imprecision). One trial stated that no treatment-related adverse events were seen in both the oral and IM vitamin B12 groups. One trial reported that 2 of 30 participants (6.7%) in the oral vitamin B12 group left the trial early due to adverse events. Orally taken vitamin B12 showed lower treatment-associated costs than IM vitamin B12 in one trial (low-quality evidence due to serious imprecision). No trial reported on clinical signs and symptoms of vitamin B12 deficiency, health-related quality of life, or acceptability of the treatment scheme. Authors' conclusions Low quality evidence shows oral and IM vitamin B12 having similar effects in terms of normalising serum vitamin B12 levels, but oral treatment costs less. We found very low-quality evidence that oral vitamin B12 appears as safe as IM vitamin B12. Further trials should conduct better randomisation and blinding procedures, recruit more participants, and provide adequate reporting. Future trials should also measure important outcomes such as the clinical signs and symptoms of vitamin B12 deficiency, health related-quality of life, socioeconomic effects, and report adverse events adequately, preferably in a primary care setting.

We study the problem of explaining a rich class of behavioral properties of deep neural networks. Distinctively, our influence-directed explanations approach this problem by peering inside the network to identify neurons with high influence on a quantity and distribution of interest, using an axiomatically-justified influence measure, and then providing an interpretation for the concepts these neurons represent. We evaluate our approach by demonstrating a number of its unique capabilities on convolutional neural networks trained on ImageNet. Our evaluation demonstrates that influence-directed explanations (1) identify influential concepts that generalize across instances, (2) can be used to extract the "essence" of what the network learned about a class, and (3) isolate individual features the network uses to make decisions and distinguish related classes., To appear in International Test Conference 2018

We present optical observations of supernova (SN) 2014ek discovered during the Tsinghua-NAOC Transient Survey (TNTS), which shows properties that are consistent with those of SN 2002cx-like events (dubbed as SNe Iax). The photometry indicates that it is underluminous compared to normal SNe Ia, with the absolute $V$-band peak magnitude being as $-17.66\pm0.20$ mag. The spectra are characterized by highly ionized Fe III and intermediate-mass elements (IMEs). The expansion velocity of the ejecta is found to be $\sim$5000 km s$^{-1}$ near the maximum light, only half of that measured for normal SNe Ia. The overall spectral evolution is quite similar to SN 2002cx and SN 2005hk, while the absorption features of the main IMEs seem to be relatively weaker. The ${}^{56}$Ni mass synthesized in the explosion is estimated to be about 0.08 M$_{\odot}$ from the pseudo bolometric light curve. Based on a large sample of SNe Iax, we examined the relations between peak luminosity, ejecta velocity, decline rate, and peak $V - R$ color but did not find noticeable correlations between these observables, in particular when a few extreme events like SN 2008ha are excluded in the analysis. For this sample, we also studied the birthplace environments and confirm that they still hold the trend of occurring preferentially in late-type spiral galaxies. Moreover, SNe Iax tend to occur in large star-forming regions of their host galaxies, more similar to SNe Ibc than SNe II, favoring that their progenitors should be associated with very young stellar populations., Comment: 15 pages, 14 figures, published on Monthly Notices of the Royal Astronomical Society

The cyanation of arylboronic acids by using acetonitrile as the "CN" source has been achieved under a Cu(cat.)/TEMPO system (TEMPO=2,2,6,6-tetramethylpiperidine N-oxide). The broad substrate scope includes a variety of electron-rich and electron-poor arylboronic acids, which react well to give the cyanated products in high to excellent yields. Mechanistic studies reveal that TEMPO-CH2 CN, generated in situ, is an active cyanating reagent, and shows high reactivity for the formation of the CN(-) moiety. Moreover, TEMPO acts as a cheap oxidant to enable the reaction to be catalytic in copper.

This paper was supported by the National Natural Science Foundation of China (Grant No. 41371343 and Grant No. 41001255) and the scholarship provided by the China Scholarship Council (Grant No. 201308420290).

The study of flood inundation is significant to human life and social economy. Remote sensing technology has provided an effective way to study the spatial and temporal characteristics of inundation. Remotely sensed images with high temporal resolutions are widely used in mapping inundation. However, mixed pixels do exist due to their relatively low spatial resolutions. One of the most popular approaches to resolve this issue is sub-pixel mapping. In this paper, a novel discrete particle swarm optimization (DPSO) based sub-pixel flood inundation mapping (DPSO-SFIM) method is proposed to achieve an improved accuracy in mapping inundation at a sub-pixel scale. The evaluation criterion for sub-pixel inundation mapping is formulated. The DPSO-SFIM algorithm is developed, including particle discrete encoding, fitness function designing and swarm search strategy. The accuracy of DPSO-SFIM in mapping inundation at a sub-pixel scale was evaluated using Landsat ETM + images from study areas in Australia and China. The results show that DPSO-SFIM consistently outperformed the four traditional SFIM methods in these study areas. A sensitivity analysis of DPSO-SFIM was also carried out to evaluate its performances. It is hoped that the results of this study will enhance the application of medium-low spatial resolution images in inundation detection and mapping, and thereby support the ecological and environmental studies of river basins.

Measuring surface water using remote sensing technology is an essential research topic in many research areas, including flood-related studies and water resource management. Recent advances in satellite remote sensing provide more efficient ways of monitoring surface water from space. As a newly available data source with a high frequency of global coverage and moderate resolution, Visible Infrared Imaging Radiometer Suite on board the Suomi National Polar-orbiting Partnership (Suomi NPP-VIIRS) has the advantage of monitoring the earth surface intensively and continuously. This study conducts an exploratory evaluation on the performance of Suomi NPP-VIIRS data for surface water detection. A Modified Histogram method was proposed and applied to its shortwave infrared (SWIR) band to estimate the water fraction within each single pixel. The estimated surface water fraction was then compared with that derived from a corresponding Moderate Resolution Imaging Spectroradiometer (MODIS) image and evaluated using ...

Following the Service-Oriented Architecture, a large number of diversified Cloud services are exposed as Web APIs (Application Program Interface), which serve as the contracts between the service providers and service consumers. Due to their massive and broad applications, any flaw in the cloud APIs may lead to serious consequences. API testing is thus necessary to ensure the availability, reliability, and stability of cloud services. The research proposes a model-based approach to automating API testing. The semi-structured API specifications, like XML/HTML specifications, are gathered from the Web sites using web crawlers, and translated into YAML-encoded standard representations. A scenario editor is designed to specify the dependencies among API operations. Test generators are built to derive test scripts from the specifications and scenarios, including test data, test cases for individual operations as well as operations sequences. Various algorithms can be used for test generation, such as combinatorial data generation, heuristic graph search, and optimization algorithms. The produced test scripts, together with a load model, can be deployed on Cloud and scheduled for execution. A prototype system, called ATCloud, was constructed to illustrate the process of API understanding, test scenario modeling using directed diagraph annotated with transfer probabilities between operations, cloud-based test resources management, distributed workload simulation, and performance monitoring.

The Type~Ia supernova (SN~Ia) 2016coj in NGC 4125 (redshift $z=0.004523$) was discovered by the Lick Observatory Supernova Search 4.9 days after the fitted first-light time (FFLT; 11.1 days before $B$-band maximum). Our first detection (pre-discovery) is merely $0.6\pm0.5$ day after the FFLT, making SN 2016coj one of the earliest known detections of a SN Ia. A spectrum was taken only 3.7 hr after discovery (5.0 days after the FFLT) and classified as a normal SN Ia. We performed high-quality photometry, low- and high-resolution spectroscopy, and spectropolarimetry, finding that SN 2016coj is a spectroscopically normal SN Ia, but with a high velocity of \ion{Si}{2} $\lambda$6355 ($\sim 12,600$\,\kms\ around peak brightness). The \ion{Si}{2} $\lambda$6355 velocity evolution can be well fit by a broken-power-law function for up to a month after the FFLT. SN 2016coj has a normal peak luminosity ($M_B \approx -18.9 \pm 0.2$ mag), and it reaches a $B$-band maximum \about16.0~d after the FFLT. We estimate there to be low host-galaxy extinction based on the absence of Na~I~D absorption lines in our low- and high-resolution spectra. The spectropolarimetric data exhibit weak polarization in the continuum, but the \ion{Si}{2} line polarization is quite strong ($\sim 0.9\% \pm 0.1\%$) at peak brightness., Comment: Submitted

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images.

Diabetes is caused by the lack of release or action of insulin. Some foods and supplements can compensate for this deficiency; thus, they can aid in the prevention or treatment of diabetes. The aim of this study was to investigate the effects of Cyclocarya paliurus extract (CPE) on insulin signaling and its capacity to correct hyperglycemia in the absence of insulin. To investigate the hypoglycemic effects of CPE, C2C12 cells were exposed to CPE (50 and 100 μg/mL). CPE promoted 2-(N-(7-Nitrobenz-2-oxa-1,3-diazol-4-yl)Amino)-2-Deoxyglucose (2NBDG) uptake into the cells via translocation of glucose transporter 4 (Glut4) to the plasma membrane. In addition, CPE enhanced tyrosine phosphorylation of insulin receptor substrate and activated phosphatidylinositol 3-kinase and protein kinase B (Akt) via sirtuin1 in C2C12 cells. Moreover, we found that oral administration of CPE (1 g/kg) to streptozotocin-induced hyperglycemic mice produced a progressive decrease in plasma glucose levels at 1 h after single dosing. At that point, CPE significantly increased the expression of skeletal muscle membrane Glut4 and enhanced the phosphorylation of Akt. These results suggest that CPE exerts antidiabetic effects similar to those of insulin, and may be an oral therapeutic alternative for the management of diabetes.

China’s rapid urbanization has contributed to a massive agricultural land loss that could threaten its food security. Timely and accurate mapping of urban expansion and urbanization-related agricultural land loss can provide viable measures to be taken for urban planning and agricultural land protection. In this study, urban expansion in China from 2001 to 2013 was mapped using the nighttime stable light (NSL), normalized difference vegetation index (NDVI), and water body data. Urbanization-related agricultural land loss during this time period was then evaluated at national, regional, and metropolitan scales by integrating multiple sources of geographic data. The results revealed that China’s total urban area increased from 31,076 km2 in 2001 to 80,887 km2 in 2013, with an average annual growth rate of 13.36%. This widespread urban expansion consumed 33,080 km2 of agricultural land during this period. At a regional scale, the eastern region lost 18,542 km2 or 1.2% of its total agricultural land area. At a metropolitan scale, the Shanghai–Nanjing–Hangzhou (SNH) and Pearl River Delta (PRD) areas underwent high levels of agricultural land loss with a decrease of 6.12% (4728 km2) and 6.05% (2702 km2) of their total agricultural land areas, respectively. Special attention should be paid to the PRD, with a decline of 13.30% (1843 km2) of its cropland. Effective policies and strategies should be implemented to mitigate urbanization-related agricultural land loss in the context of China’s rapid urbanization.

Objective The aim of the present study was to validate the Grandway MD2301 digital automatic blood pressure monitor according to the European Society of Hypertension International Protocol (ESH-IP) revision 2010. Methods The ESH-IP revision 2010 for the validation of blood pressure-measuring devices in adults was followed precisely. Systolic and diastolic blood pressure (SBP and DBP, respectively) were measured sequentially in 33 adult patients and compared with a standard mercury sphygmomanometer (two observers). A total of 99 comparison pairs were obtained. Results The device produced 78, 95 and 99 measurements within 5, 10, and 15 mmHg for SBP and 83, 96, and 99 for DBP, respectively. The average device-observer difference was -1.81±4.22 mmHg for SBP and -0.15±3.93 mmHg for DBP. All of the data were within the standards requirements to pass the testing. Conclusion The Grandway MD2301 digital automatic blood pressure monitor meets the standards of the ESH-IP revision 2010 and can be recommended for self/home measurement in the general population.

Mild conditions are elaborated which allow the preparation of the title compounds as efficient agents in organic/biological chemistry and material science.