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In order to solve the contradiction between large aperture elements and high-resolution images, in this study, we propose an improved image-resolution method based on generative adversarial network (GAN). First, we analyze the imaging principle of the optical synthetic aperture. Further, we improve a super-resolution GAN; especially, this network uses a multi-scale convolutional cascade to obtain global features of the image, and a multi-scale receptive field block and residual in residual dense block are built to obtain image details. In addition, this study uses the Mish function as the activation function of the discriminator to solve the problems of neuron extreme, gradient explosion, and poor generalization ability of the model. Through simulation, the results show that the proposed method can achieve a peak signal-to-noise ratio (PSNR) of 30 dB compared with traditional image super-resolution reconstruction methods for synthetic aperture image. The method proposed has an improvement of 2 dB in the PSNR and 0.016 in structure similarity index measure compared with the original super-resolution GAN. Therefore, this method can effectively reduce the image distortion and improve the quality of image reconstruction.

In order to explore the effects of different production processes (cold pressing, leaching, and their combination) on the quality and flavor of soybean oil of third grade, the physicochemical properties and fatty acid composition of the three soybean oils were determined, and their volatile compounds were identified and analyzed by electronic nose, headspace-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS), and headspace-gas chromatography-ion mobility spectroscopy (HS-GC-IMS). Differential analysis of the volatile compound data among the soybean oils was performed by clustering heatmap analysis, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). The results showed that cold-pressed soybean oil had the lowest moisture content; the peroxide value of leached soybean oil was significantly higher and its color was the darkest. Fragrant soybean oil had the highest linoleic acid content and a higher nutritional value; and among the detected volatile components, alcohols, aldehydes and pyrazine compounds mainly contributed to the formation of soybean oil flavor, and the reasons for the formation of some flavor compounds were clarified. Finally, 45 volatile compounds with high contributions were selected by OPLS-DA, and a reliable model was constructed for identifying fragrant soybean oil. In addition, a correlation was found between the quality and flavor of soybean oil.

Objective To understand the research hotspots and research trends about convolutional neural networks in the field of oncology imaging diagnosis by analyzing the characteristics of published literature at home and abroad over the past decade. Methods The SCI-E database was used as the data source to retrieve literature about convolutional neural networks in the field of oncology imaging diagnosis published from 2012 to 2022. The distribution characteristics of countries, institutions, journals, co-cited authors, and keywords of the studies were analyzed by CiteSpace software. Results A total of 1088 papers were eventually included, and they were mostly from China, the United States, and India. A total of 39 papers were published by Sun Yat-sen University, the research institution with the highest number of publications. Radiology Nuclear Medicine Medical Imaging was the journal with the highest number of publications. A total of 25 high-frequency keywords and 15 burst keywords were obtained. The formation of 12 author co-citation clusters such as image segmentation and lung nodule, as well as 11 keyword clusters such as automatic segmentation and breast cancer, was observed. Conclusion Current research on convolutional neural networks for oncology imaging diagnosis focuses on oncology segmentation, lung-nodule recognition, assisted diagnosis of breast cancer, and other high-frequency oncology.

As the largest terrestrial ecosystem covering extensive expanses of the Earth's surface, forests offer crucial health benefits to humans, both directly and indirectly. Presently, health services derived from forest resources have presented significant opportunities for enhancing human well-being. Nonetheless, the absence of a comprehensive understanding regarding the mechanisms by which forests impact human health jeopardizes the potential gains in health. Regrettably, there remains a dearth of scholarly work elucidating these pathways. This paper aims to furnish a thorough examination of how forests influence human health. We initiate by formulating a conceptual framework upon which we delineate the various pathways through which forests impact human health. These encompass the provisioning of resources, preventive services, and forest therapies. Concurrently, we outline the moderating influence of social, economic, and individual characteristics as mediators within this pathway. These characteristics are classified into two overarching dimensions: accessibility and behavioral choices, which notably affect marginalized demographics such as those with lower socioeconomic status, women, the elderly, individuals with disabilities, and children in developing nations. Consequently, we build upon these foundational insights to propose six strategies aimed at perpetuating the positive impact of forests on human health in the foreseeable future. In the future, the development of forest management policies, the assessment of long-term health benefits, social practices, and international cooperation must be considered holistically to attain the dual objective of sustainable forest management and the advancement of human well-being. [ABSTRACT FROM AUTHOR]

Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories. Analyses of 519 autism spectrum disorder families did not identify association with any categories after correction for 4,123 effective tests. Without appropriate correction, biologically plausible associations are observed in both cases and controls. Despite excluding previously identified gene-disrupting mutations, coding regions still exhibited the strongest associations. Thus, in autism, the contribution of de novo noncoding variation is probably modest in comparison to that of de novo coding variants. Robust results from future WGS studies will require large cohorts and comprehensive analytical strategies that consider the substantial multiple-testing burden.

In addition to filtering some sediments, hydrophobic wood sponges can also absorb many organic solvents, particularly crude oil. The leakage of crude oil poses a serious threat to the marine ecosystem, and oil mixed with water also generates great danger for its use. From the perspective of low cost and high performance, wood sponges exhibit great potential for dealing with crude oil pollution. Wood sponge is a renewable material. With a highly oriented layered structure and a highly compressible three-dimensional porous frame, wood sponges are extremely hydrophobic, making them ideal for oil–water separation. Currently, the most common approach for creating wood sponge is to first destroy the wood cell wall to obtain a porous-oriented layered structure and then enhance the oil–water separation ability via superhydrophobic treatment. Wood sponge prepared using various experimental methods and different natural woods exhibits distinctive properties in regards to robustness, compressibility, fatigue resistance, and oil absorption ability. As an aerogel material, wood sponge offers multi-action (absorption, filtration) and reusable oil–water separation functions. This paper introduces the advantages of the use of wood sponge for oil–water separation. The physical and chemical properties of wood sponge and its mechanism of adsorbing crude oil are explained. The synthesis method and the properties are discussed. Finally, the use of wood sponge is summarized and prospected. [ABSTRACT FROM AUTHOR]

Cis-regulatory elements (CREs) play a pivotal role in orchestrating interactions with trans-regulatory factors such as transcription factors, RNA-binding proteins, and noncoding RNAs. These interactions are fundamental to the molecular architecture underpinning complex and diverse biological functions in living organisms, facilitating a myriad of sophisticated and dynamic processes. The rapid advancement in the identification and characterization of these regulatory elements has been marked by initiatives such as the Encyclopedia of DNA Elements (ENCODE) project, which represents a significant milestone in the field. Concurrently, the development of CRE detection technologies, exemplified by massively parallel reporter assays, has progressed at an impressive pace, providing powerful tools for CRE discovery. The exponential growth of multimodal functional genomic data has necessitated the application of advanced analytical methods. Deep learning algorithms, particularly large language models, have emerged as invaluable tools for deconstructing the intricate nucleotide sequences governing CRE function. These advancements facilitate precise predictions of CRE activity and enable the de novo design of CREs. A deeper understanding of CRE operational dynamics is crucial for harnessing their versatile regulatory properties. Such insights are instrumental in refining gene therapy techniques, enhancing the efficacy of selective breeding programs, pushing the boundaries of genetic innovation, and opening new possibilities in microbial synthetic biology. [ABSTRACT FROM AUTHOR]

Diabetic nephropathy (DN) is a primary diabetic complication ascribed to the pathological changes in renal microvessels. This study investigated the nuclear factor erythroid 2‐related factor 2 (Nrf2)/Kelch ECH associating protein (Keap1)/antioxidant response element (ARE) signaling pathway impact of chitooligosaccharides (COS) with a certain degree of polymerization (DP) on DN mouse models and high glucose‐damaged human kidney 2 (HK‐2) cells. The findings indicated that COS effectively reduced the renal function indexes (uric acid [UA], urinary albumin excretion rate [UAER], urine albumin‐to‐creatinine ratio [UACR], blood urea nitrogen [BUN], and creatinine [Cre]) of DN mice. It increased (p <.05) the superoxide dismutase (SOD), glutathione peroxidase (GSH‐Px), and catalase (CAT) antioxidant enzyme activity in the serum and kidneys, and decreased (p <.05) the malondialdehyde (MDA) content. The mechanistic investigation showed that COS significantly increased (p <.05) Nrf2 and downstream target gene (GCLM, GCLC, HO‐1, and NQO‐1) expression, and substantially decreased (p <.05) Keap1 expression. The protein level was consistent with the messenger RNA (mRNA) level in in vitro and in vivo models. The docking data indicated that COS and Keap1 protein binding included six hydrogen bond formation processes (Gly364, Arg415, Arg483, His436, Ser431, and Arg380). The COS intervention mechanism may be related to the Nrf2/Keap1/ARE antioxidant pathway. Therefore, it provides a scientific basis for COS application in developing special medical food for DN patients. [ABSTRACT FROM AUTHOR]

Maintaining homeostasis within the intestinal microbiota is imperative for assessing the health status of hosts, and dysbiosis within the intestinal microbiota is closely associated with canine intestinal diseases. In recent decades, the modulation of canine intestinal health through probiotics and prebiotics has emerged as a prominent area of investigation. Evidence indicates that probiotics and prebiotics play pivotal roles in regulating intestinal health by modulating the intestinal microbiota, fortifying the epithelial barrier, and enhancing intestinal immunity. This review consolidates literature on using probiotics and prebiotics for regulating microbiota homeostasis in canines, thereby furnishing references for prospective studies and formulating evaluation criteria. [ABSTRACT FROM AUTHOR]

Degradation of black soil areas is a serious threat to national food security and ecological safety; nevertheless, the current lack of information on the location, size, and condition of black soil farmland productivity is a major obstacle to the development of strategies for the sustainable utilization of black soil resources. We synthesized remote sensing data and geospatial thematic data to construct a farmland productivity assessment indicator system to assess the productivity of black soil cropland at the regional scale. Furthermore, we conducted research on the spatial differentiation patterns and a spatial autocorrelation analysis of the assessment results. We found that farmland productivity within this region exhibited a decline pattern from south to north, with superior productivity in the east as opposed to the west, and the distribution follows a "spindle-shaped" pattern. Notably, the Songnen and Sanjiang typical black soil subregions centrally hosted about 46.17% of high-quality farmland and 53.51% of medium-quality farmland, while the Mondong typical black soil subregion in the west predominantly consisted of relatively low-quality farmland productivity. Additionally, farmland productivity displayed a significant positive spatial correlation and spatial clustering, with more pronounced fluctuations in the northeast–southwest direction. The developed indicator system for farmland productivity can illustrate the spatial differentiation and thereby offer a valuable reference for the sustainable management of farmland resources. [ABSTRACT FROM AUTHOR]

Abstract The diminishing oil resources make the exploration and development of heavy oil reservoirs more and more important. Heavy oil reservoirs need steam stimulation or other thermal development methods; temperature increasing during the thermal recovery process will inevitably affect the reservoir compressive characteristics. In order to study the variation of the compression coefficient of heavy oil reservoirs in the multi-round steam stimulation process, the compression coefficients of the reservoirs after different temperature and pore pressure cycles were tested. The results show that the compression coefficient of heavy oil reservoir decreases with the increase in effective confining pressure and increases with the increase in test temperature; After the temperature and pore pressure cycle, the compression coefficient of the rock is greatly reduced; the decrease in range of compression coefficient of the reservoir after the temperature and pore pressure cycle increases with the increase in the test temperature, and increases with the increase in maximum effective confining pressure. The dynamic variation of the reservoir compression coefficient must be taken into account in the prediction of the production capacity of multi-round steam stimulation.