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Quantifying seasonal deformation is essential for accurately determining the thickness of the active layer and the distribution of water content within it, providing insights into the freeze‐thaw dynamics of permafrost environments and their sensitivity to climate change. Due to the limited hydraulic conductivity of the underlying permafrost, the freeze‐thaw processes are largely confined to the active layer, allowing for predictable seasonal deformations. This study employed Independent Component Analysis to isolate large‐scale seasonal deformation from Interferometric Synthetic Aperture Radar (InSAR) measurements taken from 2016 to 2020 in the Yangtze River Source Region (YRSR) of the Qinghai‐Tibet Plateau (QTP), covering 18,500 km2. We developed dedicated machine learning (ML) models that integrate these InSAR‐derived measurements with various environmental proxies. By applying these models to the YRSR, we generated a comprehensive, full‐coverage deformation map for permafrost terrains, achieving an R2 value of 0.91 and an Root Mean Squared Error of approximately 0.5 cm, thus confirming the model's strong predictability of seasonal deformation in permafrost regions. Deformation magnitude varied from less than 1 cm to over 10 cm. Our analysis suggests that terrain attributes, influenced by climate and soil conditions, are the primary factors driving these deformations. This research provides valuable insights into quantifying permafrost‐related seasonal deformation across expansive and rural landscapes. It also aids in assessing subsurface hydrological processes and the resilience and vulnerability of permafrost. The developed ML algorithm, with access to precise environmental data, is capable of forecasting seasonal deformations across the entire QTP and potentially throughout the Arctic. Plain Language Summary: Seasonal ground deformation, including both subsidence and uplift, is common in areas with a layer of ground that freezes and thaws seasonally, underlain by permafrost‐a type of ground that remains at or below 0°C for at least 2 years. These deformations are crucial indicators of changes in water content and thickness of this layer, offering insights into the freeze‐thaw dynamics of cold environments and their sensitivity to climate change. However, accurately mapping ground deformation over large areas has been challenging. In this study, we developed machine learning (ML) models that use radar remote sensing data, statistical methods, and a set of environmental variables to predict these seasonal ground movements. Our models can accurately forecast seasonal deformation using readily available environmental data. We find that slope of the terrain is the main factor influencing seasonal deformation, with climate and soil conditions also playing significant roles. This research offers new ways to measure and understand ground deformation in remote permafrost regions and demonstrates how ML can be used to predict such deformations on a continental or even global scale large. Our findings provide valuable insights for environmental scientists and could help inform strategies for managing these regions under changing climatic conditions. Key Points: Our results underscore the predictability of seasonal deformation with high accuracy in permafrost terrainsMachine learning models predict full‐coverage seasonal deformation with high accuracy (R2 = 0.91, Root Mean Squared Error [RMSE] = 0.5 cm)Seasonal deformation is primarily determined by terrain slope and regulated by climate and soil conditions [ABSTRACT FROM AUTHOR]

Fractional vegetation cover (FVC) retrieval results of high spatial resolution satellite remote sensing images are usually upscaled as training and validation data (FVCUIH) for low spatial resolution satellite remote sensing images. However, few studies have focused on the impact of the spatial scale conversion on the evaluation of FVC retrieval accuracy. In this study, we first investigated the influence of spatial scale conversion on FVC retrieval accuracy based on FVC measured by unmanned aerial vehicle (FVCUAV) at three scales (Sentinel-2 MSI, Landsat-8 OLI, and MODIS). Then, the NDVI threshold method is proposed to further analyze the uncertainty caused by the underlying surface heterogeneity. The results showed that the use of FVCUIH as training and validation data in the process of spatial scale conversion led to overestimation of FVC accuracy, and its influence on FVC retrieval cannot be ignored. In addition, the uncertainty of the underlying surface heterogeneity at the measured sites increased the uncertainty of the FVC retrieval, while these results could be optimized by detecting the underlying surface heterogeneity. Our results suggested that both spatial scale conversion and underlying surface heterogeneity would cause the inaccurate FVC retrieval, while the latter could be optimized by detecting the underlying surface heterogeneity. This study provided a reference for the improvement of multiscale FVC retrieval accuracy based on single-scale FVC-measured data. [ABSTRACT FROM AUTHOR]

Information-Centric Networking (ICN) provides scalable and efficient content distribution at the Internet scale due to in-network caching and native multicast. To support these features, a content router needs high performance at its data plane, which consists of three forwarding steps: checking the Content Store (CS), then the Pending Interest Table (PIT), and finally the Forwarding Information Base (FIB). In this work, we build an analytical model of the router and identify that CS is the actual bottleneck. Then, we propose a novel mechanism called “NB-Cache” to address CS’s performance issue from a network-wide point of view. In NB-Cache, when packets arrive at a router whose CS is fully loaded, instead of being blocked and waiting for the CS, these packets are forwarded to the next-hop router, whose CS may not be fully loaded. This approach essentially utilizes Content Stores of all the routers along the forwarding path in parallel rather than checking each CS sequentially. NB-Cache follows a design pattern of on-demand load balancing and can be formulated into a non-trivial N-queue bypass model. We use the Markov chain to establish its theoretical base and find an algorithm for automated transition rate matrix generation. Experiments show significant improvement of data plane performance: 70% reduction in round-trip time (RTT) and 130% increase in throughput. NB-Cache decouples the fast packet forwarding from the slower content retrieval thus substantially reducing CS’s heavy dependency on fast but expensive memory. [ABSTRACT FROM AUTHOR]

The purpose of this article is to explore the connection between household composition and infant mortality in the first half of the twentieth century in Taiwan. The research results claim that illegitimate infants have higher death risk than legitimate infants; that contrary to expectation female infants have mortality rates as high as boys; and that same sex sibling order effects are approximately same among boys and girls. The significance for infant mortality of the sex of household head is the other major finding of this article: female-headed families have higher rates of infant mortality. [ABSTRACT FROM PUBLISHER]

• A 3-spot processing method is introduced for cladding stainless-steel ball valves. • Cladding of stainless-steel ball valves are completed with Ni60 + WC powder. • Cladded samples are free from any defects such as cracks and pores. In this paper, aiming to solve the problem of cracks in the laser cladding for stainless-steel ball valves, a novel method for defect-free processing is introduced. To realize this method, a 3-spot high-power diode laser source is developed. These three spots are respectively used for dynamic local preheating, laser cladding processing and dynamic local tempering. Using this high-power diode laser, a cladding processing of the stainless-steel ball valve with Ni60 + WC powder is successfully completed. Compared with the traditional processing approach, the cladded sample is free from any defects such as cracks and pores, which demonstrates the processing effect of this approach. This work provides a new method for the laser cladding of stainless-steel ball valves. [ABSTRACT FROM AUTHOR]

• A novel welding model is introduced for the butt welding of tailor-welded blanks. • Inspection results prove that this method can satisfy the industrial requirement. • It can simplify processing procedures and improve production efficiency. Due to weld defects occurred in the traditional laser welding of tailor-welded blanks with different thicknesses, a novel processing method is proposed in this paper. In this method, thin and thick metal plates are obliquely cut and then butt jointed to form an eave-like structure. When a laser beam irradiates on the marginal area of the thick plate, the molten metal flows into the gap and welds two plates together. Using this method, stainless steel tailor-welded blanks with a plate thickness combination of 2.0 mm and 1.0 mm are successfully welded by a diode laser source, and welded samples are free from cracks and pores. This method supplies a concise and quick processing way for the processing of tailor-welded blanks in industry. [ABSTRACT FROM AUTHOR]

Discriminating marsh vegetation is critical for the rapid assessment and management of wetlands. The study area, Honghe National Nature Reserve (HNNR), a typical freshwater wetland, is located in Northeast China. This study optimized the parameters (mtry and ntrees) of an object-based random forest (RF) algorithm to improve the applicability of marsh vegetation classification. Multidimensional datasets were used as the input variables for model training, then variable selection was performed on the variables to eliminate redundancy, which improved classification efficiency and overall accuracy. Finally, the performance of a new generation of Chinese high-spatial-resolution Gaofen-1 (GF-1) and Ziyuan-3 (ZY-3) satellite images for marsh vegetation classification was evaluated using the improved object-based RF algorithm with accuracy assessment. The specific conclusions of this study are as follows: (1) Optimized object-based RF classifications consistently produced more than 70.26% overall accuracy for all scenarios of GF-1 and ZY-3 at the 95% confidence interval. The performance of ZY-3 imagery applied to marsh vegetation mapping is lower than that of GF-1 imagery due to the coarse spatial resolution. (2) Parameter optimization of the object-based RF algorithm effectively improved the stability and classification accuracy of the algorithm. After parameter adjustment, scenario 3 for GF-1 data had the highest classification accuracy of 84% (ZY-3 is 74.72%) at the 95% confidence interval. (3) The introduction of multidimensional datasets improved the overall accuracy of marsh vegetation mapping, but with many redundant variables. Using three variable selection algorithms to remove redundant variables from the multidimensional datasets effectively improved the classification efficiency and overall accuracy. The recursive feature elimination (RFE)-based variable selection algorithm had the best performance. (4) Optical spectral bands, spectral indices, mean value of green and NIR bands in textural information, DEM, TWI, compactness, max difference, and shape index are valuable variables for marsh vegetation mapping. (5) GF-1 and ZY-3 images had higher classification accuracy for forest, cropland, shrubs, and open water. [ABSTRACT FROM AUTHOR]

We report on the development of direct diode laser source with high-power and high reliability. The laser source was realized by the polarization and wavelength combination of four diode laser stacks. When at the operating current of 122 A, the source was capable of producing 10,120 W output while maintaining 46% electro-optical conversion efficiency. The maximum temperature on the lens was decreased from 442.2 K to 320 K by utilizing an efficient thermal dissipation structure, and the corresponding maximum von Mises stress was reduced from 75.4 MPa to 14 MPa. In addition, a reliability test demonstrated that our laser source was reliable and potential in the applications of laser cladding and heat treatment. [ABSTRACT FROM AUTHOR]

• A novel welding model is introduced for the butt welding of tailor-welded blanks. • Inspection results prove that this method can satisfy the industrial requirement. • It can simplify processing procedures and improve production efficiency. Due to its excellent corrosion resistance and machinability, stainless-steel material has been widely used in many different areas, such as nuclear power and the aircraft industry. In these applications, the stainless-steel parts often consist of tailor-welded blanks with different thicknesses. It is crucial to keep the tailor-welded blanks of high quality in order to satisfy the demanding requirements. To make the welding process of tailor-welded blanks simple and efficient, a novel welding model for the eave-like structure is proposed in this paper. Based on this model, the butt welding of tailor-welded blanks with a plate thickness combination of 2.0 mm and 1.0 mm are successfully completed by high power diode laser sources. For further inspecting the performance of the welded bead, we analyze the microstructure and evaluate the mechanical strength. The results prove that our tailor-welded blanks can satisfy the industrial requirements. This work gives an experimental guide on the welding of tailor-welded blanks with different thicknesses. [ABSTRACT FROM AUTHOR]

Throughout the natural aging process from new to aged white tea, the flavor evolves into a 'stale flavor', despite the initial umami diminishes. The flowering process, inoculation of Eurotium cristatum to white tea, improves the flavor. The impact on sensory qualities and underlying chemical basis of flowering in aged white tea warrant investigation. Sensory analysis, non-targeted metabolomics and volatilomics together deciphered flavor modifications of flowering in aged white tea from different aging years (FAWTs). Findings indicate the flowering process can recover the umami of aged white tea, enhancing the 'stale flavor'. These changes primarily stem from oxidations of catechins and free amino acids, enrichments of flavonols and soluble sugars, and 16 pivotal aroma compounds from degradations of lipids and glycosides. Additionally, 15 volatile and 39 non-volatile compounds were identified as potential biomarkers for FAWTs. These findings offer a viable strategy to improving the quality of aged white tea., Competing Interests: Declaration of competing interest We declare that we have no commercial or financial interest that represents a conflict of interest in connection with the work submitted., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Non-invasive prenatal testing (NIPT) employs ultra-low-pass sequencing of maternal plasma cell-free DNA to detect fetal trisomy. Its global adoption has established NIPT as a large human genetic resource for exploring genetic variations and their associations with phenotypes. Here, we present methods for analyzing large-scale, low-depth NIPT data, including customized algorithms and software for genetic variant detection, genotype imputation, family relatedness, population structure inference, and genome-wide association analysis of maternal genomes. Our results demonstrate accurate allele frequency estimation and high genotype imputation accuracy (R 2 >0.84) for NIPT sequencing depths from 0.1× to 0.3×. We also achieve effective classification of duplicates and first-degree relatives, along with robust principal-component analysis. Additionally, we obtain an R 2 >0.81 for estimating genetic effect sizes across genotyping and sequencing platforms with adequate sample sizes. These methods offer a robust theoretical and practical foundation for utilizing NIPT data in medical genetic research., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background and Aims: Observational studies have implicated the involvement of gut microbiome in stroke development. Conversely, stroke may disrupt the gut microbiome balance, potentially causing systemic infections exacerbated brain infarction. However, the causal relationship remains controversial or unknown. To investigate bidirectional causality and potential ethnic differences, we conducted a bidirectional two-sample Mendelian randomisation (MR) study in both East Asian (EAS) and European (EU) populations., Methods: Leveraging the hitherto largest genome-wide association study (GWAS) summary data from the MiBioGen Consortium (n=18 340, EU) and BGI (n=2524, EAS) for the gut microbiome, stroke GWAS data from the GIGASTROKE Consortium(264 655 EAS and 1 308 460 EU), we conducted bidirectional MR and sensitivity analyses separately for the EAS and EU population., Results: We identified nominally significant associations between 85 gut microbiomes taxa in EAS and 64 gut microbiomes taxa in EU with stroke or its subtypes. Following multiple testing, we observed that genetically determined 1 SD increase in the relative abundance of species Bacteroides pectinophilus decreased the risk of cardioembolic stroke onset by 28% (OR 0.72 (95% CI 0.62 to 0.84); p=4.22e-5), and that genetically determined 1 SD increase in class Negativicutes resulted in a 0.76% risk increase in small vessel stroke in EAS. No significant causal association was identified in the EU population and the reverse MR analysis., Conclusion: Our study revealed subtype-specific and population-specific causal associations between gut microbiome and stroke risk among EAS and EU populations. The identified causality holds promise for developing a new stroke prevention strategy, warrants further mechanistic validation and necessitates clinical trial studies., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Cellular senescence represents an irreversible state of cell cycle arrest induced by various stimuli strongly associated with aging and several chronic ailments. In recent years, studies have increasingly suggested that the accumulation of senescent cells is an important contributor to the decline of organ metabolism, ultimately resulting in metabolic diseases. Conversely, the elimination of senescent cells can alleviate or postpone the onset and progression of metabolic diseases. Thus, a close relationship between senescent cells and metabolic diseases is found, and targeting senescent cells has emerged as an alternative therapy for the treatment of metabolic diseases. In this review, we summarize the role of cellular senescence in metabolic diseases, explore relevant therapeutic strategies for metabolic diseases by removing senescent cells, and provide new insights into the treatment of metabolic diseases., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhang, Zhou, Shen, Lin, Zhang, Sun, Zhou, Zhang and Zhang.)

In this Letter, we present a novel, to the best of our knowledge, image-based approach to analyze the mode control ability of a photonic lantern employed in diode laser beam combining, aiming to achieve a stable beam output. The proposed method is founded on theories of power flow and mode coupling and is validated through experiments. The findings demonstrate that the analysis of the beam combining process is highly reliable when the main mode component of the output light is the fundamental mode. Moreover, it is experimentally demonstrated that the mode control performance of the photonic lantern significantly influences the beam combining loss and the fundamental mode purity. In the essence of the variation-based analysis, a key advantage of the proposed method is its applicability even in the situation of a poor combined beam stability. The experiment only requires the collection of the far-field light images of the photonic lantern to characterize the model control ability, achieving an accuracy greater than 98%.

Compressed white tea (CWT) is a reprocessed tea of white tea. Long-term storage has greatly changed its aroma characteristics, but the material basis and transformation mechanism of its unique aroma are still unclear. In this study, flavor wheel, headspace gas chromatography ion mobility spectroscopy, chemometrics, and microbiomics were applied to study the flavor evolution and important aroma components during long-term storage of CWT, and core functional bacteria were screened. During long-term storage, the aroma of CWT gradually changed from sweet, fruity and floral to stale flavor, woody and herbal. A total of 56 volatile organic compounds (VOCs) were identified, 54 of which were significantly differences during storage. The alcohols content was the highest during 1-5 years of storage, the esters content was the highest during 7-13 years of storage, and the aldehydes content was the highest during 16 years of storage. Twenty-nine VOCs were identified as important aroma components, which were significantly correlated with 6 aroma sub-attributes ( P < 0.05). The functional prediction of bacterial community reminded that bacterial community could participate in the transformation of VOCs during storage of CWT. Twenty-four core functional bacteria were screened, which were significantly associated with 29 VOCs. Finally, 23 characteristic differential VOCs were excavated, which could be used to identify CWT in different storage years. Taken together, these findings provided new insights into the changes in aroma characteristics during storage of CWT and increased the understanding of the mechanism of characteristic aroma formation during storage., Competing Interests: XL was employed by Fujian Ming Shan Tea Industry Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wang, Wang, Dai, Wu, Song, Lin, Huang, Lin and Sun.)

A dense spectral multiplexing structure based on the reflective volume Bragg gratings is introduced to realize the diode laser multiplexing with an ultra-narrow channel spacing of 1.5 nm. With the combination of polarization multiplexing and coarse spectral multiplexing, a diode laser source producing 2045 W power from an output fiber with a core diameter of 105 µm and NA of 0.2 is achieved at an injection current of 10 A. The electro-optical and optical-optical efficiency of the laser source is 42% and 76%, respectively. Experimental results demonstrate the ability of dense spectral multiplexing based on VBG to realize high output power and brightness.