Dynamic Convolution Self-Attention Network for Land-Cover Classification in VHR Remote-Sensing Images

The current deep convolutional neural networks for very-high-resolution (VHR) remote-sensing image land-cover classification often suffer from two challenges. First, the feature maps extracted by network encoders based on vanilla convolution usually contain a lot of redundant information, which easily causes misclassification of land cover. Moreover, these encoders usually require a large number of parameters and high computational costs. Second, as remote-sensing images are complex and contain many objects with large-scale variances, it is difficult to use the popular feature fusion modules to improve the representation ability of networks. To address the above issues, we propose a dynamic convolution self-attention network (DCSA-Net) for VHR remote-sensing image land-cover classification. The proposed network has two advantages. On one hand, we designed a lightweight dynamic convolution module (LDCM) by using dynamic convolution and a self-attention mechanism. This module can extract more useful image features than vanilla convolution, avoiding the negative effect of useless feature maps on land-cover classification. On the other hand, we designed a context information aggregation module (CIAM) with a ladder structure to enlarge the receptive field. This module can aggregate multi-scale contexture information from feature maps with different resolutions using a dense connection. Experiment results show that the proposed DCSA-Net is superior to state-of-the-art networks due to higher accuracy of land-cover classification, fewer parameters, and lower computational cost. The source code is made public available.National Natural Science Foundation of China (Program No. 61871259, 62271296, 61861024), in part by Natural Science Basic Research Program of Shaanxi (Program No. 2021JC-47), in part by Key Research and Development Program of Shaanxi (Program No. 2022GY-436, 2021ZDLGY08-07), in part by Natural Science Basic Research Program of Shaanxi (Program No. 2022JQ-634, 2022JQ-018), and in part by Shaanxi Joint Laboratory of Artificial Intelligence (No. 2020SS-03)

Synergistic Effect of Chlorogenic Acid and Caffeic Acid with Fosfomycin on Growth Inhibition of a Resistant Listeria monocytogenes Strain

Listeria monocytogenes, a human foodborne pathogen that causes listeriosis with high-rate mortality, has been reported to be resistant to commonly used antibiotics. New antibiotics or cocktails of existing antibiotics with synergistic compounds are in high demand for treating this multi-drug-resistant pathogen. Fosfomycin is one of the novel and promising therapeutic antibiotics for the treatment of listeriosis. However, some L. monocytogenes strains with the FosX gene were recently reported to survive from the fosfomycin treatment. This work aims to identify FosX inhibitors that can revive fosfomycin in treating resistant L. monocytogenes. Since structures and activities of the FosX protein in L. monocytogenes have been well studied, we used an integrated computational and experimental approach to identify FosX inhibitors that show synergistic effect with fosfomycin in treating resistant L. monocytogenes. Specifically, automated ligand docking was implemented to perform virtual screening of the Indofine natural-product database and FDA-approved drugs to identify potential inhibitors. An in vitro bacterial growth inhibition test was then utilized to verify the effectiveness of identified compounds combined with fosfomycin in inhibiting the resistant L. monocytogenes strains. Two phenolic acids, i.e., caffeic acid and chlorogenic acid, were predicted as high-affinity FosX inhibitors from the ligand-docking platform. Experiments with these compounds indicated that the cocktail of either caffeic acid (1.5 mg/mL) or chlorogenic acid (3 mg/mL) with fosfomycin (50 mg/L) was able to significantly inhibit the growth of the pathogen. The finding of this work implies that the combination of fosfomycin with either caffeic acid or chlorogenic acid is of potential to be used in the clinical treatment of Listeria infections

Abdominal obesity and the prevalence of diabetes and intermediate hyperglycaemia in Chinese adults

Objective: To assess the association of indicators of general and abdominal obesity with the prevalence of type 2 diabetes (T2DM) and intermediate hyperglycaemia (IHG) in the Chinese population. Methods: We used data of 50 905 adults aged 18¿79 years in the 2002 China National Nutrition and Health Survey. Recommended Chinese cut-off values were used for BMI (24 kg/m2) and waist circumference (WC; 85 cm in men, 80 cm in women). Optimal cut-offs for waist:height ratio (WHtR) were determined from analyses of receiver-operating characteristic (ROC) curves. Results: The prevalence of T2DM and IHG was 2?6% and 1?9% respectively. ROC curve analyses indicated 0?5 as the optimal cut-off value for WHtR in both sexes. High BMI, WC and WHtR were all associated with the prevalence of glucose tolerance abnormalities, with the highest prevalence ratio (PR) for high WHtR (men: PR52?85, 95% CI 2?54, 3?21; women: PR53?10, 95% CI 2?74, 3?51). When combining BMI and WHtR, in men either a high BMI or a high WHtR alone was associated with increased risk. Among women, a high BMI without a concomitant high WHtR was not associated with increased glucose tolerance abnormalities risk, whereas a high WHtR was associated with risk irrespective of BMI. Conclusions: Among the Chinese adult population measures of central obesity are better predictors of glucose tolerance abnormalities prevalence than BMI. AWHtR cutoff point of 0?5 for both men and women can be considered as optimum for predicting (pre-) diabetes and may be a useful tool for screening and health education

3-d Lattice QCD Free Energy to Four Loops

We compute the expansion of the 3-d Lattice QCD free energy to four loop order by means of Numerical Stochastic Perturbation Theory. The first and second order are already known and are correctly reproduced. The third and fourth order coefficients are new results. The known logarithmic divergence in the fourth order is correctly identified. We comment on the relevance of our computation in the context of dimensionally reduced finite temperature QCD.Comment: 8 pages, 3 figures, latex typeset with JHEP3.cl

Design and performance of honeycomb structure for nanobubbles generating apparatus having different cell dimensions

In recent years, nanobubble technology has drawn great attention due to their wide applications in various fields of science and technology, such as water treatment, biomedical engineering, and nanomaterials. This study focuses on the application to seafood long term storage. The nitrogen nanobubble water circulation may reduce the oxygen in water and slow the progressions of oxidation and spoilage. Our previous study showed the pressure reduction and shear stress are involved in nanobubble generation apparatus with honeycomb cells. In this work, the nanobubble generating performance is studied experimentally for honeycomb structures by varying the cell size and the flow velocity. Computational Fluid Dynamics analysis is also performed to simulate the experiment and find out the efficient nanobubble generation.2018 International Conference on Material Strength and Applied Mechanics (MSAM 2018), 10–13 April 2018, Kitakyushu City, Japa

Effective Vortex Pinning in MgB2 thin films

We discuss pinning properties of MgB2 thin films grown by pulsed-laser deposition (PLD) and by electron-beam (EB) evaporation. Two mechanisms are identified that contribute most effectively to the pinning of vortices in randomly oriented films. The EB process produces low defected crystallites with small grain size providing enhanced pinning at grain boundaries without degradation of Tc. The PLD process produces films with structural disorder on a scale less that the coherence length that further improves pinning, but also depresses Tc

Upregulation of cytokines and differentiation of Th17 and Treg by dendritic cells: Central role of prostaglandin E2 induced by Mycobacterium bovis

Mycobacterium bovis (M. bovis) is a zoonotic pathogen that causes bovine and human tuberculosis. Dendritic cells play a critical role in initiating and regulating immune responses by promoting antigen-specific T-cell activation. Prostaglandin E2 (PGE2)-COX signaling is an important mediator of inflammation and immunity and might be involved in the pathogenesis of M. bovis infection. Therefore, this study aimed to reveal the character of PGE2 in the differentiation of naïve CD4+ T cells induced by infected dendritic cells (DCs). Murine bone marrow-derived DCs were pre-infected with M. bovis and its attenuated strain M. bovis bacillus Calmette-Guérin (BCG). Then, the infected DCs were co-cultured with naïve CD4+ T cells with or without the cyclooxygenase (COX) inhibitor indomethacin. Quantitative RT-PCR analysis and protein detection showed that PGE2/COX-2 signaling was activated, shown by the upregulation of PGE2 production as well as COX-2 and microsomal PGE2 synthase (mPGES1) transcription in DCs specifically induced by M. bovis and BCG infection. The further co-culture of infected DCs with naïve CD4+ T cells enhanced the generation of inflammatory cytokines IL-17 and IL-23, while indomethacin suppressed their production. Following this, the differentiation of regulatory T cells (Treg) and Th17 cell subsets was significantly induced by the infected DCs rather than uninfected DCs. Meanwhile, M. bovis infection stimulated significantly higher levels of IL-17 and IL-23 and the differentiation of Treg and Th17 cell subsets, while BCG infection led to higher levels of TNF-α and IL-12, but lower proportions of Treg and Th17 cells. In mice, M. bovis infection generated more bacterial load and severe abnormalities in spleens and lungs, as well as higher levels of COX-2, mPGE2 expression, Treg and Th17 cell subsets than BCG infection. In conclusion, PGE2/COX-2 signaling was activated in DCs by M. bovis infection and regulated differentiation of Treg and Th17 cell subsets through the crosstalk between DCs and naive T cells under the cytokine atmosphere of IL-17 and IL-23, which might contribute to M. bovis pathogenesis in mice

A high-performance electrochemical biosensor using an engineered urate oxidase

We constructed a high-performance biosensor for detecting uric acid by immobilizing an engineered urate oxidase on gold nanoparticles deposited on a carbon-glass electrode. This biosensor showed a low limit-of-detection (9.16 nM), a high sensitivity (14 μA/μM), a wide range of linearity (50 nM-1 mM), and more than 28 days lifetime.</p

Lack of Evidence for a Harmful Effect of Sodium–Glucose Cotransporter 2 (SGLT2) Inhibitors on Fracture Risk among Type 2 Diabetes Patients: A Network and Cumulative Meta-Analysis of Randomized Controlled Trials

Aim To evaluate the comparative effects of sodium-glucose co-transporter 2 (SGLT2) inhibitors on risk of bone fracture in patients with type 2 diabetes mellitus (T2DM). Methods PubMed, EMBASE, CENTRAL and ClinicalTrials.gov were systematically searched from inception to 27 January 2016 to identify randomized controlled trials (RCTs) reporting the outcome of fracture in patients with T2DM treated with SGLT2 inhibitors. Pairwise and network meta-analyses, as well as a cumulative meta-analysis, were performed to calculate odds ratios (ORs) and 95% confidence intervals (CIs). Results A total of 38 eligible RCTs (10 canagliflozin, 15 dapagliflozin and 13 empagliflozin) involving 30 384 patients, with follow-ups ranging from 24 to 160 weeks, were included. The fracture event rates were 1.59% in the SGLT2 inhibitor groups and 1.56% in the control groups. The incidence of fracture events was similar among these three SGLT2 inhibitor groups. Compared with placebo, canagliflozin (OR 1.15; 95% CI 0.71-1.88), dapagliflozin (OR 0.68; 95% CI 0.37-1.25) and empagliflozin (OR 0.93; 95% CI 0.74-1.18) were not significantly associated with an increased risk of fracture. Our cumulative meta-analysis indicated the robustness of the null findings with regard to SGLT2 inhibitors. Conclusions Our meta-analysis based on available RCT data does not support the harmful effect of SGLT2 inhibitors on fractures, although future safety monitoring from RCTs and real-world data with detailed information on bone health is warranted