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Transformers, the dominant architecture for natural language processing, have also recently attracted much attention from computational visual media researchers due to their capacity for long-range representation and high performance. Transformers are sequence-to-sequence models, which use a self-attention mechanism rather than the RNN sequential structure. Thus, such models can be trained in parallel and can represent global information. This study comprehensively surveys recent visual transformer works. We categorize them according to task scenario: backbone design, high-level vision, low-level vision and generation, and multimodal learning. Their key ideas are also analyzed. Differing from previous surveys, we mainly focus on visual transformer methods in low-level vision and generation. The latest works on backbone design are also reviewed in detail. For ease of understanding, we precisely describe the main contributions of the latest works in the form of tables. As well as giving quantitative comparisons, we also present image results for low-level vision and generation tasks. Computational costs and source code links for various important works are also given in this survey to assist further development.

Background The heterogeneous and complex nature of prediabetes presents a major challenge in identifying individuals predisposed to developing incident diabetes and related complications. We aimed to identify phenotypic subgroups of prediabetes at risk and to explore their distinct associations with cardiometabolic outcomes. Methods This study included 79,000 individuals with prediabetes from the three large-scale prospective cohorts in China. Phenotypic heterogeneity was identified using a soft-clustering algorithm based on the proximity network derived from uniform manifold approximation and projection (UMAP), combined with graph-clustering and Gaussian mixture models. Associations between phenotype probabilities and the incidence of type 2 diabetes (T2D), cardiovascular disease (CVD), and kidney events were assessed to evaluate risk differences across the identified profiles. Results Six phenotypic profiles were identified, including five with distinct metabolic features (representing ~ 70% of the total population), and one without significant features. These profiles demonstrated substantial differences in both baseline cardiometabolic burden and future disease risk. For instance, individuals with a 20% higher probability of belonging to the hypertensive profile had a 9, 6, and 12% higher risk of T2D, CVD, and CKD, respectively, while the profile with high lipids, creatinine, and liver enzyme was associated with an 10% increased risk of T2D and kidney events. Moreover, incorporating phenotypic probabilities into multivariable models significantly improved the prediction of disease risks (likelihood ratio test, P  < 0.05). Conclusions Prediabetes exhibits substantial phenotypic heterogeneity, and delineation of distinct metabolic profiles enables refined risk stratification and informs precision prevention strategies.

With the rapid advancement of agricultural modernization, industrialization and urbanization, the contradictions between people and land, supply and demand of land have become increasingly acute. [...]it is in urgent need to find out a way of scientific development without any expense of agriculture and food, ecology and environment, thereby realizing the rapid coordinated development of economy and society, and the sustainable utilization of land resources. According to the characteristics of land resources utilization, we should make reasonable and orderly development with the premise of protection natural ecology based on the land resources carrying capacity and environmental capacity, taking the road of harmonious development of human and nature. According to the plan for socio-economic development in the whole province and the agriculture land use grading results in Henan, we should make scientific adjustment to the layout of basic farmland, give priority to supplement basic farmland using quality farmland while leave out necessary and reasonable land use space for socio-economic development, and ensure that the number of basic farmland will not decrease and the quality can be improved. Establishing land resources utilization mechanism in coordination with ecological and environmental security The regions with more developed Industrial economy In Henan must give consideration to the environment. [...]during the land use, we should establish positive cycles consistent with the ecology, expand vegetation cover, effectively conserve water and reduce soil erosion.

With the fast development of network information technology, more and more people are immersed in the virtual community environment brought by the network, ignoring the social interaction in real life. The consequent urban autism problem has become more and more serious. Promoting offline communication between people \" and \"eliminating loneliness through emotional communication between pet robots and breeders\" to solve this problem, and has developed a design called \"Tom\". \"Tom\" is a smart pet robot with a pet robot-based social mechanism Called \"Tom-Talker\". The main contribution of this paper is to propose a social mechanism called \"Tom-Talker\" that encourages users to socialize offline. And \"Tom-Talker\" also has a corresponding reward mechanism and a friend recommendation algorithm. It also proposes a pet robot named \"Tom\" with an emotional interaction algorithm to recognize users' emotions, simulate animal emotions and communicate emotionally with use s. This paper designs experiments and analyzes the results. The results show that our pet robots have a good effect on solving urban autism problems.

Microlens arrays (MLAs) based on the selective wetting have opened new avenues for developing compact and miniaturized imaging and display techniques with ultrahigh resolution beyond the traditional bulky and volumetric optics. However, the selective wetting lenses explored so far have been constrained by the lack of precisely defined pattern for highly controllable wettability contrast, thus limiting the available droplet curvature and numerical aperture, which is a major challenge towards the practical high-performance MLAs. Here we report a mold-free and self-assembly approach of mass-production of scalable MLAs, which can also have ultrasmooth surface, ultrahigh resolution, and the large tuning range of the curvatures. The selective surface modification based on tunable oxygen plasma can facilitate the precise pattern with adjusted chemical contrast, thus creating large-scale microdroplets array with controlled curvature. The numerical aperture of the MLAs can be up to 0.26 and precisely tuned by adjusting the modification intensity or the droplet dose. The fabricated MLAs have high-quality surface with subnanometer roughness and allow for record-high resolution imaging up to equivalently 10,328 ppi, as we demonstrated. This study shows a cost-effective roadmap for mass-production of high-performance MLAs, which may find applications in the rapid proliferating integral imaging industry and high-resolution display.

Adeno-associated virus (AAV) receptor (AAVR) is an essential receptor for the entry of multiple AAV serotypes with divergent rules; however, the mechanism remains unclear. Here, we determine the structures of the AAV1-AAVR and AAV5-AAVR complexes, revealing the molecular details by which PKD1 recognizes AAV5 and PKD2 is solely engaged with AAV1. PKD2 lies on the plateau region of the AAV1 capsid. However, the AAV5-AAVR interface is strikingly different, in which PKD1 is bound at the opposite side of the spike of the AAV5 capsid than the PKD2-interacting region of AAV1. Residues in strands F/G and the CD loop of PKD1 interact directly with AAV5, whereas residues in strands B/C/E and the BC loop of PKD2 make contact with AAV1. These findings further the understanding of the distinct mechanisms by which AAVR recognizes various AAV serotypes and provide an example of a single receptor engaging multiple viral serotypes with divergent rules. Multiple adeno-associated viruses (AAV) use the same receptor (AAVR), but the binding mode is not clear. Here, the authors determine the structures of the AAV1-AAVR and AAV5-AAVR complexes, identify residues necessary for virus entry and compare the receptor interfaces of different AAV capsids.

This study investigates the ballistic performance of hybrid fabric structures combining triaxial and plain weaves through mesoscale numerical simulations. By examining the energy absorption, stress distribution, and deformation characteristics under high-velocity impacts, the research highlights the advantages of triaxial and plain fabric hybrids. Findings reveal that triaxial fabrics, with their multidirectional yarn alignment, outperform plain fabrics in energy dissipation and stress distribution, leading to superior ballistic protection. Among the hybrid configurations, the TP structure, with triaxial fabric layered over plain weave, shows the highest performance in reducing backface deformation and maximizing energy absorption. This configuration is particularly effective in rapid projectile deceleration and efficient energy conversion into internal and frictional components, underscoring its potential for advanced soft armor applications. The study concludes that hybrid structures leveraging the structural resilience of triaxial and plain fabrics offer a promising approach to enhanced impact resistance, positioning them as strong candidates for next-generation ballistic protection solutions.

This study investigates the ballistic performance of a novel 3D through the thickness angle-interlock woven fabric (3DTAWF) and its reinforced variant (3DRTAWF) under impact by full metal jacketed projectiles. Finite element analysis employing mesoscopic yarn-level models accurately captures the fabrics' behavior during ballistic penetration. Strain rate dependent material models enhance computational accuracy. The impact damage evolution, energy absorption mechanisms, stress wave propagation, projectile energy loss, back-face deformation, and residual velocities are analyzed. 3DRTAWF exhibits superior ballistic resistance attributed to its supplementary straight warp yarns that enhance energy absorption capabilities. Comparative assessments unveil how the 3D angle-interlock woven architecture influences ballistic performance parameters like damage morphology, deformation profiles, and stress distributions. The straight warp reinforcement in 3DRTAWF elevates fabric integrity, compactness, and stress transfer efficiency during impact events. Findings elucidate the roles of fabric architecture and warp yarn configuration in governing ballistic impact responses. This investigation provides guidance for designing advanced 3D woven fabrics tailored for superior ballistic protection applications.

This study investigates the influence of various clamping methods on the ballistic performance of 3D shallow bend-joint woven fabrics (3DSBWF). Utilizing a mesoscopic yarn-level full-size model based on the finite element method (FEM), we analyze energy absorption patterns, backface deformation (BFD), and damage morphology under different clamping conditions. The results demonstrate that clamping methods significantly impact the ballistic performance of 3DSBWF. Specifically, fabrics clamped on the weft side exhibited ballistic limit velocities around 170 m/s and failure morphologies similar to four-side clamping, with minimal energy absorption and failure areas accounting for 25% and 15% of the total energy absorbed, respectively. The warp-side clamped scenario, with a ballistic limit velocity of approximately 220 m/s, ranked second in performance, while the corner-held configuration, with the highest ballistic limit velocity of around 260 m/s, experienced the highest out-of-plane displacement and energy absorption (55%), indicating a distinct failure mechanism. This study highlights the critical role of clamping methods in optimizing the design and performance of ballistic protective fabrics.

This study uses numerical simulations to investigate projectile shape’s influence on the ballistic performance of 3D shallow bend-joint woven fabrics (3DSBWFs). The projectiles, including conical, flat, hemispherical, and spherical shapes, were analyzed for their impact on energy absorption, stress distribution, and deformation mechanisms. Results indicated that flat projectiles exhibited the highest total energy absorption, reflecting extensive energy transfer and broad impact force distribution. In contrast, conical projectiles caused localized energy absorption, concentrating stress at the tip and leading to early rupture of fabric yarns through minimal energy dissipation. Hemispherical and spherical projectiles demonstrated balanced energy absorption and uniform impact force distribution. Stress propagation varied significantly, with conical projectiles causing localized damage, while flat projectiles displayed broader stress propagation. Deformation patterns also differed, with conical projectiles causing severe localized deformation and flat projectiles resulting in extensive yarn deformation. Hemispherical and spherical projectiles induced more balanced deformations. These findings underscore the importance of projectile shape in designing protective materials, providing insights for optimizing fabric structures to enhance ballistic performance.