Abstract Emerging reconfigurable metasurfaces offer various possibilities for programmatically manipulating electromagnetic waves across spatial, spectral, and temporal domains, showcasing great potential enhancing terahertz applications. However, they are hindered by limited tunability, particularly evident in relatively small phase tuning over 270°, due to the design constraints with time‐intensive forward methodologies. Here, a multi‐bit programmable metasurface is demonstrated capable of...

Zwitterionic hydrogels, with their unique molecular structures, exhibit exceptional properties such as super hydrophilicity, ionic conductivity, antifouling and adhesion properties, making them a research hotspot in the field of desalination,...

In learning emotion recognition, existing models focus on recognizing seven commonly used emotions. Because of the high confusion level emotions, recognition difficulty is very high, resulting in unsatisfactory results. thi s study, we emotions interactive process to recognize and improve effect. We utilize self-attention mechanism with convolutional neural network (SA-CNN) model's ability emotional features. The system understands learner's real-time state by integrating this improved model...

This paper deeply explores the multi-level impact of digital economy on transfer rural labor. With rapid development economy, popularization information technology and Internet has brought new employment opportunities paths for First, this sorts out definition connotation explains how promotes labor through convenience acquisition, skills training, improvement entrepreneurial environment matching efficiency. Secondly, a literature review, summarizes main findings existing research, clarifies...

Point cloud upsampling aims to generate dense and uniformly distributed point sets from sparse clouds. Existing methods typically approach the task as an interpolation problem. They achieve by performing local between clouds or in feature space, then regressing interpolated points appropriate positions. By contrast, our proposed method treats a global shape completion Specifically, first divides into multiple patches. Then masking operation is applied remove some patches, leaving visible...

Conversion rate (CVR) prediction is one of the most critical tasks for digital display advertising. Commercial systems often require to update models in an online learning manner catch up with evolving data distribution. However, conversions usually do not happen immediately after user clicks. This may result inaccurate labeling, which called delayed feedback problem. In previous studies, problem handled either by waiting positive label a long period time, or consuming negative sample on its...

Job recommendation aims to provide potential talents with suitable job descriptions (JDs) consistent their career trajectory, which plays an essential role in proactive talent recruitment. In real-world management scenarios, the available JD-user records always consist of JDs, user profiles, and click data, profiles are typically summarized as user's skill distribution for privacy reasons. Although existing sophisticated methods can be directly employed, effective still has challenges...

Corporate relative valuation (CRV) refers to the process of comparing a company's value from company products, core staff and other related information, so that we can assess market value, which is critical for venture capital firms. Traditionally, methods heavily rely on tedious expensive human efforts, especially non-publicly listed companies. However, availability information about invisible assets, such as patents, talent, investors, enables new paradigm learning evaluating corporate...

Metasurfaces have shown flexibility in realizing various functionalities via shaping the geometry on subwavelength scale. However, with increased design complexity, makes traditional paradigm based expert knowledge less effective. Due to ability learn from raw data, deep-learning techniques made remarkable progress automatic of high-performance nanophotonic devices. deep-learning-based methods require a large amount training which is very expensive for metasurface design. Therefore, there...

Predicting conversion rate (e.g., the probability that a user will purchase an item) is fundamental problem in machine learning based recommender systems. However, accurate labels are revealed after long delay, which harms timeliness of Previous literature concentrates on utilizing early conversions to mitigate such delayed feedback problem. In this paper, we show post-click behaviors also informative prediction and can be used improve timeliness. We propose generalized model (GDFM) unifies...

Summary One of the key requirements in compressed sensing theory is use random undersampling method, which renders coherent aliases into harmless incoherent noise, effectively turning interpolation problem a much simpler denoising problem. A practical requirement wavefield reconstruction with localized sparsifying transforms control on maximum gap size. Unfortunately, pure does not provide such control. Jittered-undersampling scheme remedies this lack However, size related to factor, when...

The accurate modeling of boundary conditions is important in simulations the discrete element method (DEM) and can affect numerical results significantly. In conventional triaxial compression (CTC) tests, specimens are wrapped by flexible membranes allowing to deform freely. To accurately model CTC, new algorithms for 2D 3D DEM proposed. computationally efficient easy implement. Moreover, both horizontal vertical component confining pressure considered algorithms, which ensure that...

Aiding humans with scientific designs is one of the most exciting artificial intelligence (AI) and machine learning (ML), due to their potential for discovery new drugs, design materials chemical compounds, etc. However, typically requires complex domain knowledge that not familiar AI researchers. Further, studies involve professional skills perform experiments evaluations. These obstacles prevent researchers from developing specialized methods designs. To take a step towards...

Emerging reconfigurable metasurfaces offer various possibilities in programmatically manipulating electromagnetic waves across spatial, spectral, and temporal domains, showcasing great potential for enhancing terahertz applications. However, they are hindered by limited tunability, particularly evident relatively small phase tuning over 270o, due to the design constraints with time-intensive forward methodologies. Here, we demonstrate a multi-bit programmable metasurface capable of beam...

3D point cloud registration is a fundamental problem in computer vision, graphics, robotics, remote sensing, and etc. Over the last thirty years, we have witnessed amazing advancement this area with numerous kinds of solutions. Although handful relevant surveys been conducted, their coverage still limited. In work, present comprehensive survey on registration, covering set sub-areas such as pairwise coarse fine multi-view cross-scale multi-instance registration. The datasets, evaluation...

This manuscript conducts a nuanced exploration of the ramifications associated with adoption neoliberal development theories in Latin America, particular emphasis on Chilean experience. It delves into comprehensive implementation reforms under auspices Washington Consensus during 1970s, charting trajectory Chile's economic hardships, its subsequent period growth, and enduring challenges socio-economic inequality insufficient social welfare systems. Despite transformation one region's most...

Job recommendation aims to provide potential talents with suitable job descriptions (JDs) consistent their career trajectory, which plays an essential role in proactive talent recruitment. In real-world management scenarios, the available JD-user records always consist of JDs, user profiles, and click data, profiles are typically summarized as user's skill distribution for privacy reasons. Although existing sophisticated methods can be directly employed, effective still has challenges...

Conversion rate (CVR) prediction is one of the most critical tasks for digital display advertising. Commercial systems often require to update models in an online learning manner catch up with evolving data distribution. However, conversions usually do not happen immediately after a user click. This may result inaccurate labeling, which called delayed feedback problem. In previous studies, problem handled either by waiting positive label long period time, or consuming negative sample on its...