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The utilization of byproducts from foxtail millet polishing can reduce food loss and waste. Thus, it is necessary to know the chemical compounds from the millet and the segregation of the layers. The nutrients including minerals were compared among the husk, bran, and millet, and a LC-MS metabolomics analysis was also performed among them. The results showed that the protein, crude fat and 4 fatty acids, seven minerals, the nitrogen-containing compounds and phenolic acids were at much higher levels in the bran part than the husk and millet, whereas the husk only contained higher levels of dietary fibre, and some minerals. The millet section, as the edible part, contained the lowest level of chemical constituents. It illustrated that the bran part contained more functional and nutritional components than the millet and husk part. Therefore, the bran of the foxtail millet should be a food resources instead of wasting.

Abstract Electrochromic (EC) technology has been regarded as a promising energy‐saving technology in various applications, including smart windows, displays, thermal management, rear views, etc. Benefiting from the progress in electrochromic material synthesis, electrochromic electrode fabrication, and electrochromic device configuration design, the focus in electrochromic community has gradually shifted to multifunctional electrochromic devices (ECDs) in the era of Internet of Things. Multifunctional ECDs, such as electrochromic energy storage devices, multi‐color displays, deformable ECDs, smart windows, etc. have been showcased the ability to expand potential applications. In this review, the available device configurations, performance indexes and advanced characterization techniques for multifunctional ECDs are introduced and classified accordingly. The applications of multifunctional ECDs for energy storage, multicolor displays, deformable devices, self‐chargeable devices, smart windows, actuators, etc., are exemplified. The future development trends and perspectives of multifunctional ECDs are also overlooked. The aim of this review is to guide and inspire further efforts in the exploration of novel and advanced multifunctional ECDs.

To overcome incomplete point cloud data obtained from laser scanners scanning complex surfaces, multi-viewpoint cloud data needs to be aligned for use. A hybrid improved SAC-IA with a KD-ICP algorithm is proposed for local point cloud alignment optimization. The scanned point cloud data is preprocessed with statistical filtering, as well as uniform down-sampling. The sampling consistency initial alignment (SAC-IA) algorithm is improved by introducing a dissimilarity vector for point cloud initial alignment. In addition, the iterative closest point (ICP) algorithm is improved by incorporating bidirectional KD-tree to form the KD-ICP algorithm for fine point cloud alignment. Finally, the algorithms are compared in terms of runtime and alignment accuracy. The implementation of the algorithms is based on the Visual Studio 2013 software configurating point cloud library environment for testing experiments and practical experiments. The overall alignment method can be 40%~50% faster in terms of running speed. The improved SAC-IA algorithm provides better transformed poses, combined with the KD-ICP algorithm to select the corresponding nearest neighbor pairs, which improves the accuracy, as well as the applicability of the alignment.

Satellite-derived bathymetry (SDB) is an effective means of obtaining global shallow water depths. However, the effect of inherent optical properties (IOPs) on the accuracy of SDB under different water quality conditions has not been clearly clarified. To enhance the accuracy of machine learning SDB models, this study aims to assess the performance improvement of integrating the quasi-analytical algorithm (QAA)-derived IOPs using the Sentinel-2 and ICESat-2 datasets. In different water quality experiments, the results indicate that four SDB models (the Gaussian process regression, neural networks, random forests, and support vector regression) incorporating QAA-IOP parameters equal to or outperform those solely based on the remote sensing reflectance (Rrs) datasets, especially in turbid waters. By analyzing information gains in SDB, the most effective inputs are identified and prioritized under different water qualities. The SDB method incorporating QAA-IOP can achieve an accuracy of 0.85 m, 0.48 m, and 0.74 m in three areas (Wenchang, Laizhou Bay, and the Qilian Islands) with different water quality. Also, we find that incorporating an excessive number of redundant bands into machine learning models not only increases the demand of computing resources but also leads to worse accuracy in SDB. In conclusion, the integration of QAA-IOPs offers promising improvements in obtaining bathymetry and the optimal feature selection should be carefully considered in diverse aquatic environments.

Due to the limitations of traditional geometric error measurement, the measurement accuracy of long-stroke geometric errors is generally not high and the operation is complicated. In response to the above situation, in this study, a geometric error measurement system is built with a laser beam as the reference line and 2D position sensitive detector as the photoelectric conversion device. The single measurement range is 40 m, and the measurement range is further expanded through the principle of segmented splicing. Using an ultra-long guide rail as the measurement object for straightness measurement, the experimental results are similar to those of a laser interferometer. The uncertainty analysis model was obtained through the analysis of quantity characteristics, and based on this, the variance synthesis theorem and probability distribution propagation principle were studied to form two uncertainty synthesis methods. The measurement evaluation results showed that the two methods were basically consistent. The work provided a reference method for the uncertainty evaluation of position-sensitive detector measurement systems in the future.

Zinc-ion batteries (ZIBs) are increasingly recognized as highly promising candidates for grid-scale energy storage systems due to their cost-effectiveness, environmental friendliness, and high security. Despite recent advancements in the research of cathode materials, Zn anodes, and electrolytes, several challenges persist and must be addressed, including cathode dissolution, generation of by-products, and zinc dendrite formation, which hinder the future application of ZIBs. In this review, we systematically summarize the recent developments in electrospinning technology within ZIBs. First, the principle technical parameters and subsequent thermal treatment of electrospinning technology are discussed, and then the synthetic preparation, morphologies, and electrochemical performance of electrospun nanostructured electrodes in ZIBs are comprehensively reviewed. Finally, some perspectives on research directions and optimization strategies for electrospinning technology in energy applications are outlined.

Abstract Background C-type lectins (CTLs) are a large family of proteins with sugar-binding activity. CTLs contain an evolutionarily conserved C-type lectin domain (CTLD) that binds microbial carbohydrates in a calcium-dependent manner, thereby playing a key role in both microbial pathogenesis and innate immune responses. Aedes albopictus is an important vector for transmitting dengue virus (DENV) worldwide. Currently, the molecular characteristics and functions of CTLs in Ae. albopictus are largely unknown. Methods Transcripts encoding CTL proteins in the Ae. albopictus genome assembly were analyzed via sequence blast. Phylogenetic analysis and molecular characterization were performed to identify the functional domains of the CTLs. Quantitative analysis was performed to determine the gene expression features of CTLs during mosquito development and in different tissues of female adults after blood feeding. In addition, the functional role of CTLs in response to DENV infection was investigated in Ae. albopictus mosquito cells. Results We identified 39 transcripts encoding CTL proteins in the Ae. albopictus transcriptome. Aedes albopictus CTLs are classified into three groups based on the number of CTLDs and the domain architecture. These included 29 CTL-Ss (single-CTLDs), 1 immulectins (dual-CTLD) and 9 CTL-Xs (CTLDs with other domains). Phylogenetic analysis and structural modeling indicated that CTLs in Ae. albopictus are highly conserved with the homologous CTLs in Aedes aegypti. The expression profile assay revealed differential expression patterns of CTLs in both developmental stages and in adult female tissues. Knockdown and overexpression of three CTLs (CTL-S12, S17 and S19) confirmed that they can promote dengue virus infection in Ae. albopictus cells. Conclusions The CTL genes in Ae. albopictus mosquito and other mosquito species are evolutionarily conserved and exhibit different developmental and tissue expression features. The functional assay indicated that three CTLs in Ae. albopictus mosquitoes are involved in promoting dengue virus infection. Our study revealed that CTLs play important roles in both the physiological processes and viral infection in mosquito vectors. Graphical Abstract

Abstract Durability is one of the technical bottlenecks restricting fuel cell electric vehicle development. As a result, significant time and resources have been invested in research related to this area worldwide. Current durability research mainly focuses on the single cell and stack levels, which is quite different from the usage scenarios of actual vehicles. There is almost no research on developing durability test cycles on the fuel cell system level. This paper proposes a universal model for developing a durability test cycle for fuel cell system based on the China automotive test cycle. Large-scale comparison tests of the fuel cell systems are conducted. After 1000 h test, the output performance degradation of three mass-produced fuel cell system is 14.49%, 9.59%, and 4.21%, respectively. The test results show that the durability test cycle proposed in this paper can effectively accelerate the durability test of the fuel cell system and evaluate the durability performance of the fuel cell system. Moreover, the methodology proposed in this paper could be used in any other test cycles such as NEDC (New European Driving Cycle), WLTC (Worldwide Harmonized Light Vehicles Test Procedure), etc. And it has comprehensive application value and are significant for reducing the cost of durability testing of fuel cell systems and promoting the industrialization of fuel cell electric vehicles.

Numerous approaches targeting hepatic stellate cells (HSCs) have emerged as pivotal therapeutic strategies to mitigate liver fibrosis and are currently undergoing clinical trials. The investigation of herbal drugs or isolated natural active compounds is particularly valuable, due to their multifaceted functions and low risk of side effects. Recent studies have hinted at the potential efficacy of verbascoside (VB) in ameliorating renal and lung fibrosis, yet its impact on hepatic fibrosis remains to be elucidated. This study aims to evaluate the potential effects of VB on liver fibrosis by assessing its ability to inhibit HSC activation. VB demonstrated significant efficacy in suppressing the expression of fibrogenic genes in activated LX-2 cells. Additionally, VB inhibited the migration and proliferation of these activated HSCs by scavenging reactive oxygen species (ROS) and downregulating the AMPK pathway. Furthermore, a biosafe reverse microemulsion loaded with VB (VB-ME) was developed to improve VB’s instability and low bioavailability. The optimal formulation of VB-ME was meticulously characterized, revealing substantial enhancements in cellular uptake, ROS-scavenging capacity, and the suppression of HSC activation.

Recent research suggests a possible association between midlife obesity and an increased risk of dementia in later life. However, the underlying mechanisms remain unclear. Little is known about the relationship between body mass index (BMI) and hippocampal subfield atrophy. In this study, we aimed to explore the associations between BMI and hippocampal subfield volumes and cognitive function in non-demented Chinese older adults. Hippocampal volumes were assessed using structural magnetic resonance imaging. Cognitive function was evaluated using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). A total of 66 participants were included in the final analysis, with 35 females and 31 males. We observed a significant correlation between BMI and the hippocampal fissure volume in older females. In addition, there was a negative association between BMI and the RBANS total scale score, the coding score, and the story recall score, whereas no significant correlations were observed in older males. In conclusion, our findings revealed sex-specific associations between BMI and hippocampal subfield volumes and cognitive performance, providing valuable insights into the development of effective interventions for the early prevention of cognitive decline.