Study of Wind Flow Angle and Velocity on Ice Accretion of Transmission Line Composite Insulators

Ice accretion on insulators in cold regions is a serious and inevitable problem for power transmission lines, which may cause over-load and icing flashover accidents and can lead to wide power outage. In this research work, multiphase numerical simulations are carried out to investigate the effect of wind flow angle & velocity on the ice accretion of transmission line composite insulators. To verify the simulation results, lab-based icing tests are carried out in artificial climate chamber of Chongqing University. Results show that the change of wind flow angle has an obvious effect on both accreted ice shape and ice mass of insulators. When wind flow angle changes from 0° to 90° or -90°, the ice mass increases before dropping sharply. Meanwhile, ice mass accretion on insulators with wind flow angle is more sensitive to the change of wind velocity. For V-shape insulator strings, the ice mass increased 47.22% in average compared to ordinary suspension insulators. The findings of this research can provide significant engineering reference for the design of transmission line in icing prone areas

Target-oriented Domain Adaptation for Infrared Image Super-Resolution

Recent efforts have explored leveraging visible light images to enrich texture details in infrared (IR) super-resolution. However, this direct adaptation approach often becomes a double-edged sword, as it improves texture at the cost of introducing noise and blurring artifacts. To address these challenges, we propose the Target-oriented Domain Adaptation SRGAN (DASRGAN), an innovative framework specifically engineered for robust IR super-resolution model adaptation. DASRGAN operates on the synergy of two key components: 1) Texture-Oriented Adaptation (TOA) to refine texture details meticulously, and 2) Noise-Oriented Adaptation (NOA), dedicated to minimizing noise transfer. Specifically, TOA uniquely integrates a specialized discriminator, incorporating a prior extraction branch, and employs a Sobel-guided adversarial loss to align texture distributions effectively. Concurrently, NOA utilizes a noise adversarial loss to distinctly separate the generative and Gaussian noise pattern distributions during adversarial training. Our extensive experiments confirm DASRGAN's superiority. Comparative analyses against leading methods across multiple benchmarks and upsampling factors reveal that DASRGAN sets new state-of-the-art performance standards. Code are available at \url{https://github.com/yongsongH/DASRGAN}.Comment: 11 pages, 9 figure

Generation and Recombination for Multifocus Image Fusion with Free Number of Inputs

Multifocus image fusion is an effective way to overcome the limitation of optical lenses. Many existing methods obtain fused results by generating decision maps. However, such methods often assume that the focused areas of the two source images are complementary, making it impossible to achieve simultaneous fusion of multiple images. Additionally, the existing methods ignore the impact of hard pixels on fusion performance, limiting the visual quality improvement of fusion image. To address these issues, a combining generation and recombination model, termed as GRFusion, is proposed. In GRFusion, focus property detection of each source image can be implemented independently, enabling simultaneous fusion of multiple source images and avoiding information loss caused by alternating fusion. This makes GRFusion free from the number of inputs. To distinguish the hard pixels from the source images, we achieve the determination of hard pixels by considering the inconsistency among the detection results of focus areas in source images. Furthermore, a multi-directional gradient embedding method for generating full focus images is proposed. Subsequently, a hard-pixel-guided recombination mechanism for constructing fused result is devised, effectively integrating the complementary advantages of feature reconstruction-based method and focused pixel recombination-based method. Extensive experimental results demonstrate the effectiveness and the superiority of the proposed method.The source code will be released on https://github.com/xxx/xxx

Dynamic Changes Analysis and Hotspots Detection of Land Use in the Central Core Functional Area of Jing-Jin-Ji from 2000 to 2015 Based on Remote Sensing Data

The article uses GIS spatial analysis and grid technologies to study the dynamic changes, hotspot regions, and driving forces in land use of the central core functional area of Jing-Jin-Ji. The research results are as follows: from 2000 to 2015, the main types of land use in the central core functional area of Jing-Jin-Ji are cultivated land, woodland, and built-up land. In the period of 2005–2010, the transfer between built-up land and cultivated land was frequent. The dynamic degree of single land use in unused land was highest. It also finds out that the dynamic degree of the integrated land use from 2005 to 2010 was higher. The center of gravity transfer of the dynamic degree of integrated land use was concentrated in research area. As for the hotspots, their number and scope are increasing, and the positions located in the edge of original main urban area and developed transportation network. The main characteristics of land use dynamic change in the study area are the rapid decrease of cultivated land area and rapid growth of built-up land. The spatial agglomeration of economic factors caused by human activities has an important influence on the spatial and temporal dynamic changes of land use

Two-stage Autoencoder Neural Network for 3D Speech Enhancement

3D speech enhancement has attracted much attention in recent years with the development of augmented reality technology. Traditional denoising convolutional autoencoders have limitations in extracting dynamic voice information. In this paper, we propose a two-stage autoencoder neural network for 3D speech enhancement. We incorporate a dual-path recurrent neural network block into the convolutional autoencoder to iteratively apply time-domain and frequency-domain modeling in an alternate fashion. And an attention mechanism for fusing the high-dimension features is proposed. We also introduce a loss function to simultaneously optimize the network in the time-frequency and time domains. Experimental results show that our system outperforms the state-of-the-art systems on the dataset of ICASSP L3DAS23 challenge.Comment: 5 pages,5 figure

Saturation of water reflectance in extremely turbid media based on field measurements, satellite data and bio-optical modelling

International audienceEvidence of water reflectance saturation in extremely turbid media is highlighted based on both field measurements and satellite data corrected for atmospheric effects. This saturation is obvious in visible spectral bands, i.e., in the blue, green and even red spectral regions when the concentration of suspended particulate matter (SPM) reaches then exceeds 100 to 1000 g.m −3. The validity of several bio-optical semi-analytical models is assessed in the case of highly turbid waters, based on comparisons with outputs of the Hydrolight radiative transfer model. The most suitable models allow to reproduce the observed saturation and, by inversion, to retrieve information on the SPM mass-specific inherent optical properties

Exploring the plankton bacteria diversity and distribution patterns in the surface water of northwest pacific ocean by metagenomic methods

The study of marine microbial communities is crucial for comprehending the distribution patterns, adaptations to the environment, and the functioning of marine microorganisms. Despite being one of the largest biomes on Earth, the bacterioplankton communities in the Northwest Pacific Ocean (NWPO) remain understudied. In this research, we aimed to investigate the structure of the surface bacterioplankton communities in different water masses of the NWPO. We utilized metagenomic sequencing techniques and cited previous 16S rRNA data to explore the distribution patterns of bacterioplankton in different seasons. Our results revealed that Cyanobacteria, Proteobacteria, Bacteroidetes, and Actinobacteria dominated the microbial communities, accounting for over 95% of the total. During spring, we observed significant differentiation in community structure between the different water masses. For instance, Prochlorococcus and Pseudoalteromonas were primarily distributed in the nutrient-deficient subtropical countercurrent zone, while Flavobacteriaceae and Rhodobacteraceae were found in the Kuroshio-Oyashio mixing zone. During summer, the surface planktonic bacteria communities became homogenized across regions, with Cyanobacteria becoming the dominant group (68.6% to 84.9% relative abundance). The metabolic processes of the microorganisms were dominated by carbohydrate metabolism, followed by amino acid transport and metabolism. However, there was a low relative abundance of functional genes involved in carbohydrate metabolism in the Kuroshio-Oyashio mixing zone. The metagenomic data had assembled 37 metagenomic-assembled genomes (MAGs), which belong to Proteobacteria, Bacteroidetes, and Euryarchaeota. In conclusion, our findings highlight the diversity of the surface bacterioplankton community composition in the NWPO, and its distinct geographic distribution characteristics and seasonal variations

Design, Synthesis, and Biological Activity of 5\u27-Phenyl-1,2,5,6-tetrahydro-3,3\u27-bipyridine Analogues as Potential Antagonists of Nicotinic Acetylcholine Receptors

Starting from a known non-specific agonist (1) of nicotinic acetylcholine receptors (nAChRs), rationally guided structural-based design resulted in the discovery of a small series of 5′-phenyl-1,2,5,6-tetrahydro-3,3′-bipyridines (3a – 3e) incorporating a phenyl ring off the pyridine core of 1. The compounds were synthesized via successive Suzuki couplings on a suitably functionalized pyridine starting monomer 4 to append phenyl and pyridyl substituents off the 3- and 5-positions, respectively, and then make subsequent modifications on the flanking pyridyl ring to provide target compounds. Compound 3a is a novel antagonist which is highly selective for α3β4 nAChR (Ki = 123 nM) over the α4β2, and α7 receptors

Crystallization and preliminary X-ray diffraction studies of guanidinoacetate methyltransferase from rat liver

This is the publisher's version, also available electronically from http://scripts.iucr.org/cgi-bin/paper?S0907444999010318.Guanidinoacetate methyltransferase is the enzyme which catalyzes the last step of creatine biosynthesis. The enzyme is found ubiquitously and in abundance in the livers of all vertebrates. Recombinant rat-liver guanidinoacetate methyltransferase has been crystallized with guanidinoacetate and S-adenosylhomocysteine. The crystals belong to the monoclinic space group P21, with unit-cell parameters a = 54.8, b = 162.5, c = 56.1 Å, [beta] = 96.8 (1)° at 93 K, and typically diffract beyond 2.8 Å