Subsethood Measures of Spatial Granules

Subsethood, which is to measure the degree of set inclusion relation, is predominant in fuzzy set theory. This paper introduces some basic concepts of spatial granules, coarse-fine relation, and operations like meet, join, quotient meet and quotient join. All the atomic granules can be hierarchized by set-inclusion relation and all the granules can be hierarchized by coarse-fine relation. Viewing an information system from the micro and the macro perspectives, we can get a micro knowledge space and a micro knowledge space, from which a rough set model and a spatial rough granule model are respectively obtained. The classical rough set model is the special case of the rough set model induced from the micro knowledge space, while the spatial rough granule model will be play a pivotal role in the problem-solving of structures. We discuss twelve axioms of monotone increasing subsethood and twelve corresponding axioms of monotone decreasing supsethood, and generalize subsethood and supsethood to conditional granularity and conditional fineness respectively. We develop five conditional granularity measures and five conditional fineness measures and prove that each conditional granularity or fineness measure satisfies its corresponding twelve axioms although its subsethood or supsethood measure only hold one of the two boundary conditions. We further define five conditional granularity entropies and five conditional fineness entropies respectively, and each entropy only satisfies part of the boundary conditions but all the ten monotone conditions

Real-time object detection method based on improved YOLOv4-tiny

The "You only look once v4"(YOLOv4) is one type of object detection methods in deep learning. YOLOv4-tiny is proposed based on YOLOv4 to simple the network structure and reduce parameters, which makes it be suitable for developing on the mobile and embedded devices. To improve the real-time of object detection, a fast object detection method is proposed based on YOLOv4-tiny. It firstly uses two ResBlock-D modules in ResNet-D network instead of two CSPBlock modules in Yolov4-tiny, which reduces the computation complexity. Secondly, it designs an auxiliary residual network block to extract more feature information of object to reduce detection error. In the design of auxiliary network, two consecutive 3x3 convolutions are used to obtain 5x5 receptive fields to extract global features, and channel attention and spatial attention are also used to extract more effective information. In the end, it merges the auxiliary network and backbone network to construct the whole network structure of improved YOLOv4-tiny. Simulation results show that the proposed method has faster object detection than YOLOv4-tiny and YOLOv3-tiny, and almost the same mean value of average precision as the YOLOv4-tiny. It is more suitable for real-time object detection.Comment: 14pages,7figures,2table

Karst landslides detection and monitoring with multiple SAR data and multi-dimensional SBAS technique in Shuicheng, Guizhou, China

Shuicheng District is a karst mountain area, located in Guizhou Province, China. Its fragile stratum and frequent underground mining activities makes it prone to landslides. Owning to its wide coverage and frequent revisit, the InSAR technology has advantages in potential landslide identification and deformation monitor. However, affected by dense vegetation and atmospheric delay, it is much difficult to get sufficient effective targets to derive the deformation in this area. Besides, deformation derived from single orbit SAR data can result in the missing identification of some potential landslides and the misinterpreting of the real kinematics process of landslides. In this study, the multi-source SAR data, atmospheric error correction by quadratic tree image segmentation method, and phase-stacking method were selected to derive the surface deformation of this area. Besides, DS-InSAR and MSBAS method were combined to derive the deformation of Pingdi landslide. First, the potential landslides in this area were identified, surface deformation result, optical remote sensing images and geomorphological features were jointly considered. Then, the landslide distribution characteristics was analyzed in terms of slope, elevation and stratum. After that, the deformation along the LOS direction was acquired using the DS-InSAR method. The MSBAS method was used to retrieve the two-dimensional deformation of Pingdi landslide. Finally, the comprehensive analysis of triggering factors and failure process were conducted according to the spatial-temporal deformation characteristics and field investigation. The results indicated that landslides in Shuicheng district were mostly located in the junction of T1 and P3 stratum and mining related. Mining activity was the main cause of the Pingdi landslide deformation, the precipitation was the driving factor of the landslide instability. The research provides an insight into the explore the unstable slope distribution characteristic and the failure process of the landslides

Achievements and Challenges in Improving Air Quality in China: Analysis of the Long-Term Trends from 2014 to 2022

Due to the implementation of air pollution control measures in China, air quality has significantly improved, although there are still additional issues to be addressed. This study used the long-term trends of air pollutants to discuss the achievements and challenges in further improving air quality in China. The Kolmogorov-Zurbenko (KZ) filter and multiple-linear regression (MLR) were used to quantify the meteorology-related and emission-related trends of air pollutants from 2014 to 2022 in China. The KZ filter analysis showed that PM2.5 decreased by 7.36 ± 2.92% yr􀀀 1, while daily maximum 8-h ozone (MDA8 O3) showed an increasing trend with 3.71 ± 2.89% yr􀀀 1 in China. The decrease in PM2.5 and increase in MDA8 O3 were primarily attributed to changes in emission, with the relative contribution of 85.8% and 86.0%, respectively. Meteorology variations, including increased ambient temperature, boundary layer height, and reduced relative humidity, also contributed to the reduction of PM2.5 and the enhancement of MDA8 O3. The emission-related trends of PM2.5 and MDA8 O3 exhibited continuous decrease and increase, respectively, from 2014 to 2022, while the variation rates slowed during 2018–2020 compared to that during 2014–2017, highlighting the challenges in further improving air quality, particularly in simultaneously reducing PM2.5 and O3. This study recommends reducing NH3 emissions from the agriculture sector in rural areas and transport emissions in urban areas to further decrease PM2.5 levels. Addressing O3 pollution requires the reduction of O3 precursor gases based on site-specific atmospheric chemistry considerations

Generative adversarial networks with multi-scale and attention mechanisms for underwater image enhancement

The images captured underwater are usually degraded due to the effects of light absorption and scattering. Degraded underwater images exhibit color distortion, low contrast, and blurred details, which in turn reduce the accuracy of marine biological monitoring and underwater object detection. To address this issue, a generative adversarial network with multi-scale and an attention mechanism is proposed to improve the quality of underwater images. To extract more effective features within the generative network, several modules are introduced: a multi-scale dilated convolution module, a novel attention module, and a residual module. These modules are utilized to design a generative network with a U-shaped structure. The multi-scale dilated convolution module is designed to extract features at multiple scales and expand the receptive field to capture more global information. The attention module directs the network’s focus towards important features, thereby reducing the interference from redundant feature information. To improve the discriminative power of the adversarial network, a multi-scale discriminator is designed. It has two output feature maps with different scales. Additionally, an improved loss function for the generative adversarial network is proposed. This improvement involves incorporating the total variation loss into the traditional loss function. The performance of different methods for enhancing underwater images is evaluated using the EUVP dataset and UIEB dataset. The experimental results demonstrate that the enhanced underwater images exhibit better quality and visual effects compared to other methods

Phosphorus-modified Pt@Cu surfaces for efficient electrocatalysis of hydrogen evolution

Robust and efficient platinum (Pt)-based electrocatalysts are pursued for hydrogen evolution reaction (HER). However, the performance of Pt-based HER electrocatalysts needs to be further improved in alkaline and neutral media due to the extra water dissociation step. Moreover, the fabrication process and long-term stability of current Pt-based HER electrocatalysts are unsatisfactory in mild media. Herein, a one-step facile process was developed to fabricate a phosphorus-modified Pt@Cu (Pt/P@Cu) electrocatalyst to realize the feasibility of high-performance HER in neutral media. The HER performance of Pt/P@Cu is further increased with the successful introduction of phosphorus. P exists as oxides on the Pt/P@Cu surface, which was demonstrated by XPS and Raman. The P doping leads to increased surface active sites, lower charge transfer resistance, and enhanced HER performance in neutral media. Pt/P@Cu presents a low overpotential of 24.3 mV at the current density of −10 mA cm−2, along with an excellent stability reaching −1000 mA cm−2 for 1000 cycles of LSV. The successful P doping on the catalyst surface inspires future study on developing simple surface modifications to increase the electrocatalytic activity to develop advanced electrocatalysts

Sex differences in patients with COVID-19: a retrospective cohort study and meta-analysis

BACKGROUND: Accumulated evidence revealed that male was much more likely to higher severity and fatality by SARS-CoV-2 infection than female patients, but few studies and meta-analyses have evaluated the sex differences of the infection and progression of COVID-19 patients. AIM: We aimed to compare the sex differences of the epidemiological and clinical characteristics in COVID-19 patients; and to perform a meta-analysis evaluating the severe rate, fatality rate, and the sex differences of the infection and disease progression in COVID-19 patients. METHODS: We analyzed clinical data of patients in Changchun Infectious Hospital and Center, Changchun, Northeast China; and searched PubMed, Embase, Web of Science, and Cochrane Library without any language restrictions for published articles that reported the data of sex-disaggregated, number of severe, and death patients on the confirmed diagnosis of adult COVID-19 patients. RESULTS: The pooled severe rate and fatality rate of COVID-19 were 22.7% and 10.7%. Male incidence in the retrospective study was 58.1%, and the pooled incidence in male was 54.7%. CONCLUSION: The pooled severe rate in male and female of COVID-19 was 28.2% and 18.8%, the risky of severe and death was about 1.6folds higher in male compared with female, especially for older patients (> 50 y)

Investigation of surface integrity of selective laser melting additively manufactured AlSi10Mg alloy under ultrasonic elliptical vibration-assisted ultra-precision cutting

Additive manufacturing technology has been widely used in aviation, aerospace, automobiles and other fields due to the fact that near-net-shaped components with unprecedented geometric freedom can be fabricated. Additively manufactured aluminum alloy has received a lot of attention, due to its excellent material properties. However, the finished surface of additively manufactured aluminum alloy with nanoscale surface roughness is quite challenging and rarely addressed. In this paper, a novel machining technology known as ultrasonic elliptical vibration-assisted cutting (UEVC) was adopted to suppress the generation of cracks, improve the surface integrity and reduce tool wear during the ultra-precision machining of selective laser melting (SLM) additively manufactured AlSi10Mg alloy. The experimental results revealed that, in the conventional cutting (CC) process, surface defects, such as particles, pores and grooves, appeared on the machined surface, and the machined surface rapidly deteriorated with the increase in cumulative cutting area. In contrast, an almost flawless machined surface was obtained in the UEVC process, and its roughness value was less than 10 nm. Moreover, the tool wear of the CC tool was remarkably greater than that of the UEVC tool, and the standard flank wear width of the CC tool was more than twice that of the UEVC tool. Therefore, the UEVC technology is considered to be a feasible method for the ultra-precision machining of SLM additively manufactured AlSi10Mg alloy

An Olfactory Cilia Pattern in the Mammalian Nose Ensures High Sensitivity to Odors

SummaryIn many sensory organs, specialized receptors are strategically arranged to enhance detection sensitivity and acuity. It is unclear whether the olfactory system utilizes a similar organizational scheme to facilitate odor detection. Curiously, olfactory sensory neurons (OSNs) in the mouse nose are differentially stimulated depending on the cell location. We therefore asked whether OSNs in different locations evolve unique structural and/or functional features to optimize odor detection and discrimination. Using immunohistochemistry, computational fluid dynamics modeling, and patch clamp recording, we discovered that OSNs situated in highly stimulated regions have much longer cilia and are more sensitive to odorants than those in weakly stimulated regions. Surprisingly, reduction in neuronal excitability or ablation of the olfactory G protein in OSNs does not alter the cilia length pattern, indicating that neither spontaneous nor odor-evoked activity is required for its establishment. Furthermore, the pattern is evident at birth, maintained into adulthood, and restored following pharmacologically induced degeneration of the olfactory epithelium, suggesting that it is intrinsically programmed. Intriguingly, type III adenylyl cyclase (ACIII), a key protein in olfactory signal transduction and ubiquitous marker for primary cilia, exhibits location-dependent gene expression levels, and genetic ablation of ACIII dramatically alters the cilia pattern. These findings reveal an intrinsically programmed configuration in the nose to ensure high sensitivity to odors

Sarco/Endoplasmic Reticulum Ca2+-ATPases (SERCA) Contribute to GPCR-Mediated Taste Perception

The sense of taste is important for providing animals with valuable information about the qualities of food, such as nutritional or harmful nature. Mammals, including humans, can recognize at least five primary taste qualities: sweet, umami (savory), bitter, sour, and salty. Recent studies have identified molecules and mechanisms underlying the initial steps of tastant-triggered molecular events in taste bud cells, particularly the requirement of increased cytosolic free Ca2+ concentration ([Ca2+]c) for normal taste signal transduction and transmission. Little, however, is known about the mechanisms controlling the removal of elevated [Ca2+]c from the cytosol of taste receptor cells (TRCs) and how the disruption of these mechanisms affects taste perception. To investigate the molecular mechanism of Ca2+ clearance in TRCs, we sought the molecules involved in [Ca2+]c regulation using a single-taste-cell transcriptome approach. We found that Serca3, a member of the sarco/endoplasmic reticulum Ca2+-ATPase (SERCA) family that sequesters cytosolic Ca2+ into endoplasmic reticulum, is exclusively expressed in sweet/umami/bitter TRCs, which rely on intracellular Ca2+ release for signaling. Serca3-knockout (KO) mice displayed significantly increased aversive behavioral responses and greater gustatory nerve responses to bitter taste substances but not to sweet or umami taste substances. Further studies showed that Serca2 was mainly expressed in the T1R3-expressing sweet and umami TRCs, suggesting that the loss of function of Serca3 was possibly compensated by Serca2 in these TRCs in the mutant mice. Our data demonstrate that the SERCA family members play an important role in the Ca2+ clearance in TRCs and that mutation of these proteins may alter bitter and perhaps sweet and umami taste perception