RFAConv: Innovating Spatital Attention and Standard Convolutional Operation

Spatial attention has been widely used to improve the performance of convolutional neural networks by allowing them to focus on important information. However, it has certain limitations. In this paper, we propose a new perspective on the effectiveness of spatial attention, which is that it can solve the problem of convolutional kernel parameter sharing. Despite this, the information contained in the attention map generated by spatial attention is not sufficient for large-size convolutional kernels. Therefore, we introduce a new attention mechanism called Receptive-Field Attention (RFA). While previous attention mechanisms such as the Convolutional Block Attention Module (CBAM) and Coordinate Attention (CA) only focus on spatial features, they cannot fully address the issue of convolutional kernel parameter sharing. In contrast, RFA not only focuses on the receptive-field spatial feature but also provides effective attention weights for large-size convolutional kernels. The Receptive-Field Attention convolutional operation (RFAConv), developed by RFA, represents a new approach to replace the standard convolution operation. It offers nearly negligible increment of computational cost and parameters, while significantly improving network performance. We conducted a series of experiments on ImageNet-1k, MS COCO, and VOC datasets, which demonstrated the superiority of our approach in various tasks including classification, object detection, and semantic segmentation. Of particular importance, we believe that it is time to shift focus from spatial features to receptive-field spatial features for current spatial attention mechanisms. By doing so, we can further improve network performance and achieve even better results. The code and pre-trained models for the relevant tasks can be found at https://github.com/Liuchen1997/RFAConv.Comment: 14 pages, 5 figure

AKConv: Convolutional Kernel with Arbitrary Sampled Shapes and Arbitrary Number of Parameters

Neural networks based on convolutional operations have achieved remarkable results in the field of deep learning, but there are two inherent flaws in standard convolutional operations. On the one hand, the convolution operation be confined to a local window and cannot capture information from other locations, and its sampled shapes is fixed. On the other hand, the size of the convolutional kernel is fixed to k $\times$ k, which is a fixed square shape, and the number of parameters tends to grow squarely with size. It is obvious that the shape and size of targets are various in different datasets and at different locations. Convolutional kernels with fixed sample shapes and squares do not adapt well to changing targets. In response to the above questions, the Alterable Kernel Convolution (AKConv) is explored in this work, which gives the convolution kernel an arbitrary number of parameters and arbitrary sampled shapes to provide richer options for the trade-off between network overhead and performance. In AKConv, we define initial positions for convolutional kernels of arbitrary size by means of a new coordinate generation algorithm. To adapt to changes for targets, we introduce offsets to adjust the shape of the samples at each position. Moreover, we explore the effect of the neural network by using the AKConv with the same size and different initial sampled shapes. AKConv completes the process of efficient feature extraction by irregular convolutional operations and brings more exploration options for convolutional sampling shapes. Object detection experiments on representative datasets COCO2017, VOC 7+12 and VisDrone-DET2021 fully demonstrate the advantages of AKConv. AKConv can be used as a plug-and-play convolutional operation to replace convolutional operations to improve network performance. The code for the relevant tasks can be found at https://github.com/CV-ZhangXin/AKConv.Comment: 10 pages, 5 figure

Crystal Structure Transformation and Dielectric Properties of Polymer Composites Incorporating Zinc Oxide Nanorods

Zinc oxide (ZnO) nanorods were synthesized using a modified wet chemical method. Poly(vinylidene fluoride-co-hexafluoropropylene), P(VDF-HFP), nanocomposites with different ZnO nanorods loadings were prepared via a solution blend route. Field emission scanning electron microscopic (FE-SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) were used to investigate the structure and morphology of the nanocomposites. XRD and FTIR data indicate that the incorporation of ZnO nanorods promote the crystalline structure transformation of P(VDF-HFP). As the content of ZnO nanorods increases, the β phase structure increases while the α phase decreases. In addition, the dielectric properties of the P(VDF-HFP) and its composites were systematically studied

National incidence of traumatic fractures in China: a retrospective survey of 512 187 individuals

Background Traumatic fractures place a substantial burden on health-care systems worldwide. Although detailed information about incidence, distribution, and risk factors for traumatic fractures is vital for planning and prevention, in China, national data are unavailable. We aimed to do an up-to-date national survey on the population-weighted incidence of traumatic fractures in China. Methods The China National Fracture Study (CNFS) was a retrospective epidemiological study that recruited a nationally representative sample from eight provinces, 24 urban cities, and 24 rural counties in China using stratified random sampling and the probability proportional to size method. All eligible household members who had lived in their current residence for 6 months or longer were personally interviewed by trained research teams about traumatic fractures of the trunk, arms, or legs (not including the skull, sternum, and ribs) that had occurred in 2014. Telephone surveys were used for participants who were non-contactable after repeated visits. Fracture cases were verified by clinical records, medical history, and radiographs by orthopaedic surgeons and radiologists. We estimated incidence rates for traumatic fractures for the overall population and for subgroups by age and sex, as well as by demographic factors such as ethnic origin, occupation, geographical region, and residency category. We also studied potential associations between fractures and various factors of interest, such as age, ethnic origin, education, smoking, alcohol drinking, sleep time per day, and history of previous fracture. Data were weighted during statistical analysis to ascertain the national incidence rate. This study is registered with the Chinese Clinical Trial Registry, number ChiCTR-EPR-15005878. Findings Between Jan 19, 2015, and May 16, 2015, 535 836 individuals were selected and invited to participate in the study. Questionnaires from 23 649 (4%) individuals were excluded due to missing items, insufficient responses, or logical errors. Following exclusions, 512 187 (96%) individuals participated in the CNFS, consisting of 259 649 (51%) boys and men and 252 538 (49%) girls and women. Of these individuals, 1763 individuals had experienced traumatic fractures during 2014 (n=1833). The population-weighted incidence rate of traumatic fractures of the trunk, arms, or legs was 3·21 (95% CI 2·83–3·59) per 1000 population in 2014 (3·65, 3·12–4·18 in men and 2·75, 2·46–3·04 in women). For all ages, sleeping less than 7 h per day was identified as a risk factor for traumatic fractures. We identified previous fracture history as a risk factor for adults aged 15 years and older. Alcohol consumption incurred a risk effect for men aged 15 years and older and women aged 15–64 years. Interpretation Our results provide detailed information about fracture incidence, distribution, and risk factors, which can now be used as an up-to-date clinical evidence base for national health-care planning and preventive efforts in China and elsewhere. Specific public health policies that focus on decreasing alcohol consumption, prohibiting drunk driving, promoting smoking cessation, and encouraging individuals to obtain sufficient sleep and maintain a healthy bodyweight should be urgently implemented to help reduce the risk of traumatic fractures

The CYB5R3c.350C>G and G6PD A alleles modify severity of anemia in malaria and sickle cell disease

Genetic modifiers of anemia in Plasmodium falciparum infection and sickle cell disease (SCD) are not fully known. Both conditions are associated with oxidative stress, hemolysis and anemia. The CYB5R3 gene encodes cytochrome b5 reductase 3, which converts methemoglobin to hemoglobin through oxidation of NADH. CYB5R3c.350C > G encoding CYB5R3T117S , the most frequent recognized African-specific polymorphism, does not have known functional significance, but its high allele frequency (23% in African Americans) suggests a selection advantage. Glucose-6-phosphate dehydrogenase (G6PD) is essential for protection from oxidants; its African-polymorphic X-linked A+ and A- alleles, and other variants with reduced activity, coincide with endemic malaria distribution, suggesting protection from lethal infection. We examined the association of CYB5R3c.350C > G with severe anemia (hemoglobin G offered protection against severe malarial anemia in children without G6PD deficiency (G6PD wild type or A+/A- heterozygotes) (odds ratio 0.29, P = .022) but not in G6PD A+ or A- hemizygotes/homozygotes. We also examined the relationship of CYB5R3c.350C > G with hemoglobin concentration among 267 children and 321 adults and adolescents with SCD in the US and UK and found higher hemoglobin in SCD patients without G6PD deficiency (β = 0.29, P = .022 children; β = 0.33, P = .004 adults). Functional studies in SCD erythrocytes revealed mildly lower activity of native CYB5R3T117S compared to wildtype CYB5R3 and higher NADH/NAD+ ratios. In conclusion, CYB5R3c.350C > G appears to ameliorate anemia severity in malaria and SCD patients without G6PD deficiency, possibly accounting for CYB5R3c.350C > G selection and its high prevalence

An interlaboratory comparison of aerosol inorganic ion measurements by ion chromatography : Implications for aerosol pH estimate

Water-soluble inorganic ions such as ammonium, nitrate and sulfate are major components of fine aerosols in the atmosphere and are widely used in the estimation of aerosol acidity. However, different experimental practices and instrumentation may lead to uncertainties in ion concentrations. Here, an intercomparison experiment was conducted in 10 different laboratories (labs) to investigate the consistency of inorganic ion concentrations and resultant aerosol acidity estimates using the same set of aerosol filter samples. The results mostly exhibited good agreement for major ions Cl-, SO2-4, NO-3, NHC4 and KC. However, F-, Mg2C and Ca2C were observed with more variations across the different labs. The Aerosol Chemical Speciation Monitor (ACSM) data of nonrefractory SO2-4, NO-3 and NHC4 generally correlated very well with the filter-analysis-based data in our study, but the absolute concentrations differ by up to 42 %. Cl-from the two methods are correlated, but the concentration differ by more than a factor of 3. The analyses of certified reference materials (CRMs) generally showed a good detection accuracy (DA) of all ions in all the labs, the majority of which ranged between 90 % and 110 %. The DA was also used to correct the ion concentrations to showcase the importance of using CRMs for calibration check and quality control. Better agreements were found for Cl-, SO2-4, NO-3, NHC4 and KC across the labs after their concentrations were corrected with DA; the coefficient of variation (CV) of Cl-, SO2-4, NO-3, NHC4 and KC decreased by 1.7 %, 3.4 %, 3.4 %, 1.2 % and 2.6 %, respectively, after DA correction. We found that the ratio of anion to cation equivalent concentrations (AE/CE) and ion balance (anions-cations) are not good indicators for aerosol acidity estimates, as the results in different labs did not agree well with each other. In situ aerosol pH calculated from the ISORROPIA II thermodynamic equilibrium model with measured ion and ammonia concentrations showed a similar trend and good agreement across the 10 labs. Our results indicate that although there are important uncertainties in aerosol ion concentration measurements, the estimated aerosol pH from the ISORROPIA II model is more consistent

Effect of silica particles modified by in-situ and ex-situ methods on the reinforcement of silicone rubber

In-situ and ex-situ methods were applied to modify silica particles in order to investigate their effects on the reinforcement of silicone rubber. Surface area and pore analyzer, laser particle size analyzer, Fourier-transform infrared spectroscopy (FTIR), contact-angle instrument, and transmission electron microscope (TEM) were utilized to investigate the structure and properties of the modified silica particles. Dynamic mechanical thermal analyzer (DMTA) was employed to characterize the vulcanizing behavior and mechanical properties of the composites. Thermogravimetric analysis (TGA) was performed to test the thermal stability of the composites. FTIR and contact angle analysis indicated that silica particles were successfully modified by these two methods. The BET surface area and TEM results reflected that in-situ modification was more beneficial to preparing silica particles with irregular shape and higher BET surface area in comparison with ex-situ modification. The DMTA and TGA data revealed that compared with ex-situ modification, the in-situ modification produced positive influence on the reinforcement of silicone rubber. (C) 2014 Elsevier Ltd. All rights reserved

Classification and Object Detection of 360° Omnidirectional Images Based on Continuity-Distortion Processing and Attention Mechanism

The use of 360° omnidirectional images has occurred widely in areas where comprehensive visual information is required due to their large visual field coverage. However, many extant convolutional neural networks based on 360° omnidirectional images have not performed well in computer vision tasks. This occurs because 360° omnidirectional images are processed into plane images by equirectangular projection, which generates discontinuities at the edges and can result in serious distortion. At present, most methods to alleviate these problems are based on multi-projection and resampling, which can result in huge computational overhead. Therefore, a novel edge continuity distortion-aware block (ECDAB) for 360° omnidirectional images is proposed here, which prevents the discontinuity of edges and distortion by recombining and segmenting features. To further improve the performance of the network, a novel convolutional row-column attention block (CRCAB) is also proposed. CRCAB captures row-to-row and column-to-column dependencies to aggregate global information, enabling stronger representation of the extracted features. Moreover, to reduce the memory overhead of CRCAB, we propose an improved convolutional row-column attention block (ICRCAB), which can adjust the number of vectors in the row-column direction. Finally, to verify the effectiveness of the proposed networks, we conducted experiments on both traditional images and 360° omnidirectional image datasets. The experimental results demonstrated that better performance than for the baseline model was obtained by the network using ECDAB or CRCAB

Facile Fabrication of Highly Hydrophobic Onion-like Candle Soot-Coated Mesh for Durable Oil/Water Separation

Although sundry superhydrophobic filtrating materials have been extensively exploited for remediating water pollution arising from frequent oil spills and oily wastewater emission, the expensive reagents, rigorous reaction conditions, and poor durability severely restrict their water purification performance in practical applications. Herein, we present a facile and cost-effective method to fabricate highly hydrophobic onion-like candle soot (CS)-coated mesh for versatile oil/water separation with excellent reusability and durability. Benefiting from a superglue acting as a binder, the sub-micron CS coating composed of interconnected and intrinsic hydrophobic carbon nanoparticles stably anchors on the surface of porous substrates, which enables the mesh to be highly hydrophobic (146.8 ± 0.5°)/superoleophilic and resist the harsh environmental conditions, including acid, alkali, and salt solutions, and even ultrasonic wear. The as-prepared mesh can efficiently separate light or heavy oil/water mixtures with high separation efficiency (>99.95%), among which all the water content in filtrates is below 75 ppm. Besides, such mesh retains excellent separation performance and high hydrophobicity even after 20 cyclic tests, demonstrating its superior reusability and durability. Overall, this work not only makes the CS-coated mesh promising for durable oil/water separation, but also develops an eco-friendly approach to construct robust superhydrophobic surfaces

Incidence and risk factors for foot fractures in China: A retrospective population-based survey.

PurposeThe literature lacks population-based epidemiologic studies on the incidence and risk factors for traumatic foot fractures. The purpose of this study was to update information concerning the incidence of foot fractures in China and to identify associated risk factors.MethodsAll the data on foot fractures were available from the China National Fracture Survey (CNFS), which was conducted between January and May in 2015. A total of 8 provinces, 24 urban cities and 24 rural counties in China were selected, using stratified random sampling and the probability proportional to size method. Individuals who had lived in their current residence for 6 months or longer were personally interviewed about any foot fracture that had occurred in 2014. Questionnaires were completed by every participant for data collection and quality control was accomplished by our research team members. The information included age, gender, height, weight, ethnic group, education, occupation, smoking, alcohol consumption, sleeping time per day, dietary habits and others. Fracture was initially identified by patients' self report and further confirmed by their providing medical records.ResultsA total of 512187 individuals participated in the CNFS. There were 201 patients with foot fractures in 2014. Mean age at the time of fracture was 45.4 years. The incidence rate of foot fractures was 39.2 (95%CI: 33.8-44.7)/100000/year. Fall and traffic accident were the most common causes for foot fractures and over 60% of these occurred at home or on the road. Alcohol consumption, history of previous fracture and average sleep time 24 kg/m2 was a risk factor whilst living in the west region was associated with a lower incidence rate of foot fracture.ConclusionsThe present study shows an incidence of 39.2/100000/year of foot fractures in China. Specific public health policies focusing on decreasing alcohol consumption and encouraging individuals to obtain sufficient sleep should be implemented. Females with a higher BMI should focus more on foot health care, especially in those with history of previous fracture