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Existing methods for matching multi-modal remote sensing images (MRSI) demonstrate considerable adaptability. However, high-precision matching for rectification remains challenging due to differing imaging mechanisms in cross-modal remote sensing images, leading to numerous non-repeated detailed feature points. Additionally, assuming linear transformations between images conflicts with the complex aberrations present in remote sensing images, limiting matching accuracy. This paper aims to elevate matching accuracy by implementing a detailed texture removal strategy that effectively isolates repeatable structural features. Subsequently, we construct a radiation-invariant similarity function within a generalized gradient framework for least-squares matching, specifically designed to mitigate nonlinear geometric and radiometric distortions across MRSIs. Comprehensive qualitative and quantitative evaluations across multiple datasets, employing substantial manual checkpoints, demonstrate that our method significantly enhances matching accuracy for image data involving multiple modal combinations and outperforms the current state-of-the-art solutions in matching accuracy. Additionally, rectification experiments employing WorldView and TanDEM-X images validate our method’s ability to achieve a matching accuracy of 1.05 pixels, thereby indicating its practical utility and generalization capacity. Access to experiment-related data and codes will be provided at https://github.com/LiaoYF001/refinement/.

In this paper, we present a novel approach to radiometric normalization for aerial images, effectively addressing both intra- and inter-image color and illumination inconsistencies caused by varying sensor technologies, atmospheric conditions, and ground reflection. We introduce a comprehensive mathematical model for radiance transfer, which addresses brightness inhomogeneities resulting from the Bidirectional Reflectance Distribution Function (BRDF) effect and vignetting effect, alongside color inconsistencies due to atmospheric and illumination variations. To enhance the model's efficiency and stability for solutions, we employ a strategy that leverages multiple polynomial models for approximation, significantly simplifying the complexity of rigorous solutions. Our efficient and robust solution leverages advanced radiometric triangulation theories, enabling effective radiometric normalization of aerial images. We validate the efficacy of our method with extensive testing on three large datasets, each containing over two hundred aerial images. The experimental results showcase our method's superiority over state-of-the-art methods, as evidenced by enhanced visual quality and improved quantitative performance in statistical assessments.

Wickerhamomyces is a well-known genus of the family Wickerhamomycetaceae in the class Ascomycetes. These fungi can survive in a variety of substrates and environments and perform many valuable roles in both industrial processes and the natural ecosystems. During our investigation of yeast diversity associated with plant materials, 53 Wickerhamomyces isolates were obtained from rotting wood and plant leaves collected in Fujian, Guizhou, Henan, and Yunnan Provinces of China. Isolates were identified as 14 Wickerhamomyces species, including 1 species known previously to occur in China (W. anomalus), 9 new record species in China (W. arborarius, W. ciferrii, W. edaphicus, W. lynferdii, W. pijperi, W. subpelliculosa, W. xylosica, W. strasburgensis, and W. sydowiorum), and 4 novel species (W. guiyangensis sp. nov., W. paramyanmarensis sp. nov., W. quanzhouensis sp. nov., and W. phyllophilus sp. nov.). This study presents a detailed account of these new species, illustrating their morphology and analyzing their phylogenetic relationships with other Wickerhamomyces species. Our study is the first comprehensive study on Wickerhamomyces species associated with plant materials from tropical and subtropical China. The results of this study update our understanding of the phylogenetic relationships, systematics, and ecology of Wickerhamomyces.

This study proposes a three-dimensional (3D) deformation estimation framework based on the integration of shape and texture information for real-scene 3D model matching, effectively addressing the issue of deformation assessment in large-scale geological landslide areas. By extracting and merging the texture and shape features of matched points, correspondences between points in multi-temporal real-scene 3D models are established, resolving the difficulties faced by existing methods in achieving robust and high-precision 3D point matching over landslide areas. To ensure the complete coverage of the geological disaster area while enhancing computational efficiency during deformation estimation, a voxel-based thinning method to generate interest points is proposed. The effectiveness of the proposed method is validated through tests on a dataset from the Lijie north hill geological landslide area in Gansu Province, China. Experimental results demonstrate that the proposed method significantly outperforms existing classic and advanced methods in terms of matching accuracy metrics, and the accuracy of our deformation estimates is close to the actual measurements obtained from GNSS stations, with an average error of only 2.2 cm.

The Attention-Interest-Desire-Memory-Action (AIDMA) model describes the psychological process of consumers from exposure to advertising to final purchase, including five stages: attention, interest, desire, memory, and action. This model has important guiding significance in the early stage of traditional media and the Internet. However, with the development of the Internet, users’ behavior patterns changed, and new marketing models such as the Attention-Interest-Search-Action-Share (AISAS) model appeared. However, the AIDMA model still has reference value and application scenarios, especially in elevator multimedia advertising. In a relatively closed and focused environment, elevator multimedia advertising is more likely to attract passengers’ attention, stimulate interest and purchase desire, and strengthen brand memory. This form of advertising is suitable for various industries and brands, and it can improve brand awareness and image. In order to evaluate the effect of elevator multimedia advertising, it can be investigated from three aspects: communication effect, psychological effect, and sales effect. Through these investigations, the study provides an understanding of the communication effect of advertising and provide a reference for future advertising planning.

Thallium (Tl) is a toxic heavy metal responsible for noxious effects in living organisms. As a pollutant, Tl can be found in the environment at high concentrations, especially in industrial areas. Systemic toxicity induced by this toxic metal can affect cell metabolism, including redox alterations, mitochondrial dysfunction, and activation of apoptotic signaling pathways. Recent focus on Tl toxicity has been devoted to the characterization of its effects at the nuclear level, with emphasis on DNA, which, in turn, may be responsible for cytogenetic damage, mutations, and epigenetic changes. In this work, we review and discuss past and recent evidence on the toxic effects of Tl at the systemic level and its effects on DNA. We also address Tl’s role in cancer and its control.

Fairy circles (FC) are a type of spatial self-organized patterns that widely exist in various vegetation ecosystems and the accurate detection and quantitative characterization of these mysterious circles remain a technical challenge. In this study, vegetation FC in intertidal salt marshes are recognized from the derived reflectance information (backscattered intensity) and geometric quantities of light detection and ranging (LiDAR) carried on unmanned aerial vehicle (UAV). The specular effect on the UAV LiDAR intensity data over nadir regions of wet salt marshes is eliminated using the laser radar equation and Phong model where the absent distances and incidence angles are approximately retrieved on the basis of geometric and temporal relations in data collection. The FC are progressively recovered through three interconnected procedures. First, the retrieved reflectance information is used to discriminate the mudflat and vegetation points. Second, a spatial connectivity clustering algorithm is utilized on the extracted vegetation points to form individual spatially disconnected clusters. Finally, FC and regular vegetation are successfully recognized by jointly using the salient, size, and circularity features of the generated clusters. A multi-echo UAV LiDAR system is used for data collection at an intertidal salt marsh to assess the feasibility and prospects of the proposed method. Taking the manual detection results from the orthophoto generated by images of a UAV camera system as a reference, the missing detection rate, false detection rate, and area detection error of the proposed method are 6%, 9%, and 5%, respectively. Results suggest that UAV LiDAR is an extremely promising technique to characterize the geometric properties (e.g., location, size, and quantity) of FC from a holistic perspective.

Abstract Current research of automatic transmission (AT) mainly focuses on the improvement of driving performance, and configuration innovation is one of the main research directions. However, finding new configurations of ATs is one of the main limitations of configuration innovation. In the present study, epicyclic gear trains (EGTs) are applied to investigate mechanisms of 9-speed ATs. Then four kinematic configurations are proposed for automatic transitions. In order to evaluate the performance of proposed mechanisms, the lever analogy method is applied to conduct kinematic and mechanical analyses. The power flow analysis is conducted, and then transmission efficiencies are calculated based on the torque method. The comparative analysis between the proposed and existing mechanisms is carried out where obtained results show that proposed mechanisms have reasonable performance and can be used in ATs. The prototype of an AT is manufactured and the speed test is conducted, which proves the accuracy of analysis and the feasibility of proposed mechanisms.

MeHg is an environmental neurotoxin that can adversely affect the development of the nervous system. The molecular integrity of chromatin in the nucleus is an important target of MeHg. Low levels of MeHg trigger epigenetic mechanisms that may be involved in long-lasting and transgenerational neurotoxicity after exposure. Emerging evidence has shown that these mechanisms include histone modification, siRNA, and DNA methylation. The MeHg-induced inhibition of neurodifferentiation and neurogenesis are mechanistically associated with epigenetic alterations in critical genes, such as neurotrophin brain-derived neurotrophic factor (BDNF). Further, MeHg exposure has been shown to alter the activity and/or expression of the upstream regulators of chromatin structure, including histone deacetylases (HDACs) and DNA methyltransferase (DNMTs), which may trigger permanent alterations in histone modifications and DNA methylation. MeHg-exposure also alters several species of miRNA that are associated with neurodevelopment. Genetic studies in the C. elegans model of MeHg-induced toxicity proposes a potential interplay between exogenous RNAi and antioxidant defense. In this review, we discuss the molecular basis for MeHg exposure-induced alterations in chromatin structure and the roles of histone modifications, siRNA, and DNA methylation in MeHg-induced neurotoxic effects.

Determining appropriate master images, reducing radiometric error accumulation, and eliminating outliers from the cloud, water, and land changes, are three main issues in radiometric normalization of multitemporal high-resolution satellite images (HRSI) during mosaicking. However, these three issues have not been simultaneously considered by the existing methods. This article presents a comprehensive radiometric normalization method for multitemporal HRSI using a radiometric block adjustment without master images. Pseudoinvariant features (PIFs) extracted from image pairs using the iteratively reweighted multivariate alteration detection are used as the corresponding pixel observations and organized to form radiometric tie points according to the corresponding horizontal space coordinates. Radiometric error equations are subsequently constructed, and the linear radiometric transformation parameters are solved by a global adjustment. The time-invariant PIFs generally represent the true corresponding features and naturally avoid the cloud, water, and land changes, which can eliminate the effects of outliers. Furthermore, the pixel values of tie points calculated from the weighted average of the corresponding pixel observations are used as virtual radiometric control points to eliminate the dependency on master images. Moreover, a global optimum can be achieved by the global adjustment, effectively overcoming the error accumulation, which is severe in large datasets. Four groups of HRSI datasets from various satellites are used to validate the performance of the proposed method. Experimental results demonstrate that the proposed method outperforms two state-of-the-art methods and has good applicability and stability, considering both visual effects and quantitative performance.

N,N’ bis-(2-mercaptoethyl) isophthalamide (NBMI) is a lipophilic thiol-containing agent that has high affinity for toxic metal ions, such as Hg2+, Pb2+, and Cd2+. Studies have shown that NBMI is a potent chelator of heavy metals, yet its potential toxicity in animals has yet to be determined. Using the model organism Caenorhabditis elegans (C. elegans), we show no significant change in worms’ death rate or lifespan following NBMI treatment (10−1000 μM). However, NBMI treatment was associated with a significant developmental delay. To determine if the daf-2/age-1/daf-16 pathway is involved in NBMI toxicity, mRNA levels of these genes were assessed in worms treated with NBMI. Here, we found that while NBMI failed to significantly alter the expression of daf-16 or daf-2; age-1 was significantly downregulated by NBMI. Furthermore, NBMI significantly increased DAF-16 nuclear localization. Consistent with a role for this pathway in NBMI toxicity, the developmental arrest by NBMI was more prominent in the DAF-16 transgenic strain than in the wild type N2 strain. Moreover, in the mutant strains harboring null alleles of daf-16, NBMI had no effect on development. In addition, NBMI repressed the expression of detoxifying genes (skn-1, gst-4 and gcs-1). In summary, NBMI has a low developmental toxicity in the C. elegans model, and the nuclear translocation of DAF-16 is involved in the developmental effect of NBMI.

Caenorhabditis elegans (C. elegans) is a nematode present worldwide. The worm shows homology to mammalian systems and expresses approximately 40% of human disease-related genes. Since Dr. Sydney Brenner first proposed C. elegans as an advantageous experimental worm-model system for genetic approaches, increasing numbers of studies using C. elegans as a tool to investigate topics in several fields of biochemistry, neuroscience, pharmacology, and toxicology have been performed. In this regard, C. elegans has been used to characterize the molecular mechanisms and affected pathways caused by metals that lead to neurotoxicity, as well as the pathophysiological interrelationship between metal exposure and ongoing neurodegenerative disorders. Several toxic metals, such as lead, cadmium, and mercury, are recognized as important environmental contaminants, and their exposure is associated with toxic effects on the human body. Essential elements that are required to maintain cellular homeostasis and normal physiological functions may also be toxic when accumulated at higher concentrations. For instance, manganese (Mn) is a trace essential element that participates in numerous biological processes, such as enzymatic activities, energy metabolism, and maintenance of cell functions. However, Mn overexposure is associated with behavioral changes in C. elegans, which are consistent with the dopaminergic system being the primary target of Mn neurotoxicity. Caenorhabditis elegans has been shown to be an important tool that allows for studies on neuron morphology using fluorescent transgenic worms. Moreover, behavioral tests may be conducted using worms, and neurotransmitter determination and related gene expression are likely to change after Mn exposure. Likewise, mutant worms may be used to study molecular mechanisms in Mn toxicity, as well as the expression of proteins responsible for the biosynthesis, transport, storage, and uptake of dopamine. Furthermore, this review highlights some advantages and limitations of using the experimental model of C. elegans and provides guidance for potential future applications of this model in studies directed toward assessing for Mn neurotoxicity and related mechanisms.

The control of financial risk has always been one of the important topics in financial research. Based on the theory of finance, this paper proposes a kind of financial risk dynamic system. By analyzing some properties of the dynamic system, the system shows obvious coexisting chaotic oscillations. In order to control the financial risk dynamic system effectively, this paper proposes a finite-time impulse controller to control the financial risk dynamic system. Simulation results show that the finite-time impulse controller has faster convergence speed than the impulse controller.

Accurate building extraction from remotely sensed data is difficult to perform automatically because of the complex environments and the complex shapes, colours and textures of buildings. Supervised deep-learning-based methods offer a possible solution to solve this problem. However, these methods generally require many high-quality, manually labelled samples to obtain satisfactory test results, and their production is time and labour intensive. For multimodal data with sufficient information, extracting buildings accurately in as unsupervised a manner as possible. Combining remote sensing images and LiDAR point clouds for unsupervised building extraction is not a new idea, but existing methods often experience two problems: (1) the accuracy of vegetation detection is often not high, which leads to limited building extraction accuracy, and (2) they lack a proper mechanism to further refine the building masks. We propose two methods to address these problems, combining aerial images and aerial LiDAR point clouds. First, we improve two recently developed vegetation detection methods to generate accurate initial building masks. We then refine the building masks based on the image feature consistency constraint, which can replace inaccurate LiDAR-derived boundaries with accurate image-based boundaries, remove the remaining vegetation points and recover some missing building points. Our methods do not require manual parameter tuning or manual data labelling, but still exhibit a competitive performance compared to 29 methods: our methods exhibit accuracies higher than or comparable to 19 state-of-the-art methods (including 8 deep-learning-based methods and 11 unsupervised methods, and 9 of them combine remote sensing images and 3D data), and outperform the top 10 methods (4 of them combine remote sensing images and LiDAR data) evaluated using all three test areas of the Vaihingen dataset on the official website of the ISPRS Test Project on Urban Classification and 3D Building Reconstruction in average area quality. These comparative results verify that our unsupervised methods combining multisource data are very effective.

Abstract Background The cytochrome P450 monooxygenase (P450) superfamily is involved in the biosynthesis of various primary and secondary metabolites. However, little is known about the effects of whole genome duplication (WGD) and tandem duplication (TD) events on the evolutionary history and functional divergence of P450s in Brassica after splitting from a common ancestor with Arabidopsis thaliana. Results Using Hidden Markov Model search and manual curation, we detected that Brassica species have nearly 1.4-fold as many P450 members as A. thaliana. Most P450s in A. thaliana and Brassica species were located on pseudo-chromosomes. The inferred phylogeny indicated that all P450s were clustered into two different subgroups. Analysis of WGD event revealed that different P450 gene families had appeared after evolutionary events of species. For the TD event analyses, the P450s from TD events in Brassica species can be divided into ancient and recent parts. Our comparison of influence of WGD and TD events on the P450 gene superfamily between A. thaliana and Brassica species indicated that the family-specific evolution in the Brassica lineage can be attributed to both WGD and TD, whereas WGD was recognized as the major mechanism for the recent evolution of the P450 super gene family. Expression analysis of P450s from A. thaliana and Brassica species indicated that WGD-type P450s showed the same expression pattern but completely different expression with TD-type P450s across different tissues in Brassica species. Selection force analysis suggested that P450 orthologous gene pairs between A. thaliana and Brassica species underwent negative selection, but no significant differences were found between P450 orthologous gene pairs in A. thaliana–B. rapa and A. thaliana–B. oleracea lineages, as well as in different subgenomes in B. rapa or B. oleracea compared with A. thaliana. Conclusions This study is the first to investigate the effects of WGD and TD on the evolutionary history and functional divergence of P450 gene families in A. thaliana and Brassica species. This study provides a biology model to study the mechanism of gene family formation, particularly in the context of the evolutionary history of angiosperms, and offers novel insights for the study of angiosperm genomes.

Abstract Background Glycosyltransferases comprise a highly divergent and polyphyletic multigene family that is involved in widespread modification of plant secondary metabolites in a process called glycosylation. According to conserved domains identified in their amino acid sequences, these glycosyltransferases can be classified into a single UDP-glycosyltransferase (UGT) 1 superfamily. Results We performed genome-wide comparative analysis of UGT genes to trace evolutionary history in algae, bryophytes, pteridophytes, and angiosperms; then, we further investigated the expansion mechanisms and function characterization of UGT gene families in Brassica rapa and Brassica oleracea. Using Hidden Markov Model search, we identified 3, 21, 140, 200, 115, 147, and 147 UGTs in Chlamydomonas reinhardtii, Physcomitrella patens, Selaginella moellendorffii, Oryza sativa, Arabidopsis thaliana, B. rapa, and B. oleracea, respectively. Phylogenetic analysis revealed that UGT80 gene family is an ancient gene family, which is shared by all plants and UGT74 gene family is shared by ferns and angiosperms, but the remaining UGT gene families were shared by angiosperms. In dicot lineage, UGTs among three species were classified into three subgroups containing 3, 6, and 12 UGT gene families. Analysis of chromosomal distribution indicates that 98.6 and 71.4% of UGTs were located on B. rapa and B. oleracea pseudo-molecules, respectively. Expansion mechanism analyses uncovered that whole genome duplication event exerted larger influence than tandem duplication on expansion of UGT gene families in B. rapa, and B. oleracea. Analysis of selection forces of UGT orthologous gene pairs in B. rapa, and B. oleracea compared to A. thaliana suggested that orthologous genes in B. rapa, and B. oleracea have undergone negative selection, but there were no significant differences between A. thaliana –B. rapa and A. thaliana –B. oleracea lineages. Our comparisons of expression profiling illustrated that UGTs in B. rapa performed more discrete expression patterns than these in B. oleracea indicating stronger function divergence. Combing with phylogeny and expression analysis, the UGTs in B. rapa and B. oleracea experienced parallel evolution after they diverged from a common ancestor. Conclusion We first traced the evolutionary history of UGT gene families in plants and revealed its evolutionary and functional characterization of UGTs in B. rapa, and B. oleracea. This study provides novel insights into the evolutionary history and functional divergence of important traits or phenotype-related gene families in plants.

Metals are actively involved in multiple catalytic physiological activities. However, metal overload may result in neurotoxicity as it increases formation of reactive oxygen species (ROS) and elevates oxidative stress in the nervous system. Mitochondria are a key target of metal-induced toxicity, given their role in energy production. As the brain consumes a large amount of energy, mitochondrial dysfunction and the subsequent decrease in levels of ATP may significantly disrupt brain function, resulting in neuronal cell death and ensuing neurological disorders. Here, we address contemporary studies on metal-induced mitochondrial dysfunction and its impact on the nervous system.

In close-range photogrammetry, images are difficult to acquire and organize primarily because of the limited field of view (FOV) of digital cameras when long focal lenses are used to measure large targets. To overcome this problem, we apply a scanning photography method that acquires images by rotating the camera in both horizontal and vertical directions at one station. This approach not only enlarges the FOV of each station but also ensures that all stations are distributed in order without coverage gap. We also conduct a modified triangulation according to the traits of the data overlapping among images from the same station to avoid matching all images with one another. This algorithm synthesizes the images acquired from the same station into synthetic images, which are then used to generate a free network. Consequently, we solve the exterior orientation elements of each original camera image in the free network and perform image matching among original images to obtain tie points. Finally, all original images are combined in self-calibration bundle adjustment with control points. The feasibility and precision of the proposed method are validated by testing it on two fields using 300 and 600 mm lenses. The results confirm that even with a small amount of control points, the developed scanning photogrammetry can steadily achieve millimeter scale accuracy at distances ranging from 40 m to 250 m.

Proline-rich antimicrobial peptides (PR-AMPs) are a group of cationic host defense peptides that are characterized by a high content of proline residues. Up to now, they have been reported in some insects, vertebrate and invertebrate animals, but are not found in plants. In this study, we performed an in silico screening of antimicrobial peptides, which led to discovery of a Brassica napus gene encoding a novel PR-AMP. This gene encodes a 35-amino acid peptide with 13 proline residues, designated BnPRP1. BnPRP1 has 40.5% identity with a known proline-rich antimicrobial peptide SP-B from the pig. BnPRP1 was artificially synthetized and cloned into the prokaryotic expression vector pET30a/His-EDDIE-GFP. Recombinant BnPRP1 was produced in Escherichia coli and has a predicted molecular mass of 3.8 kDa. Analysis of its activity demonstrated that BnPRP1 exhibited strong antimicrobial activity against Gram-positive bacterium, Gram-negative bacterium, yeast and also had strong antifungal activity against several pathogenic fungi, such as Sclerotinia sclerotiorum, Mucor sp., Magnaporthe oryzae and Botrytis cinerea. Circular dichroism (CD) revealed the main secondary structure of BnPRP1 was the random coil. BnPRP1 gene expression detected by qRT-PCR is responsive to pathogen inoculation. At 48 hours after S. sclerotiorum inoculation, the expression of BnPRP1 increased significantly in the susceptible lines while slight decrease occurred in resistant lines. These suggested that BnPRP1 might play a role in the plant defense response against S. sclerotiorum. BnPRP1 isolated from B. napus was the first PR-AMP member that was characterized in plants, and its homology sequences were found in some other Brassicaceae plants by the genome sequences analysis. Compared with the known PR-AMPs, BnPRP1 has the different primary sequences and antimicrobial activity. Above all, this study gives a chance to cast a new light on further understanding about the AMPs' mechanism and application.

ObjectiveTo examine the associations of knee injury, radiographic osteoarthritis severity, and quadriceps strength with knee pain exacerbation during walking.DesignWithin-person knee-matched case-control study.MethodsParticipants from the Osteoarthritis Initiative who completed a 20-m walking test at the 24-month visit were included. Pain exacerbation was defined as an increase in pain intensity of 1 or more on a numeric rating scale (0 as no pain and 10 as the worst imaginable pain) while completing the 20-m walking test. We used conditional logistic regression to assess the relation of recent knee injury, Kellgren-Lawrence (KL) grade, and quadriceps strength to unilateral knee pain exacerbation during walking.ResultsWe included 277 people who experienced unilateral knee pain exacerbation during the walking test. Recent knee injury was associated with pain exacerbation during walking, with an odds ratio of 3.4 (95% confidence interval [CI]: 1.3, 9.2). Compared with knees with a KL grade of 0, the odds ratios of pain exacerbation during walking were 1.3 (95% CI: 0.7, 2.7), 3.3 (95% CI: 1.5, 7.1), and 8.1 (95% CI: 3.1, 21.1) for knees with KL grades of 2, 3, and 4, respectively. Painful knees with a deficit in quadriceps strength of greater than or equal to 4% had a 1.4-fold (95% CI: 1.0, 1.9) higher risk of pain exacerbation during walking than their pain-free counterparts.ConclusionRecent knee injury, more severe radiographic osteoarthritis, and lower quadriceps strength were associated with an increased risk of knee pain exacerbation during walking. J Orthop Sports Phys Ther 2021;51(6):298-304. Epub 10 May 2021. doi:10.2519/jospt.2021.9735.