Prediction of the depth-averaged two-dimensional flow direction along a meander in compound channels

YesFor overbank flows in meandering channels, the flow direction along a meander varies and is affected by floodplain vegetation. This study proposes a model for predicting the depth-averaged two-dimensional flow direction (depth-averaged flow angle) along a meander in smooth and vegetated meandering compound channels. Laboratory experiments were performed in smooth and vegetated channels. Measurements show that the height of the secondary current cell in the main channel is increased by dense floodplain vegetation comparing with that in a non-vegetated channel. A method of determining the height of the cell is proposed. At the middle section between the apex and exit sections, where the secondary current cell is absent, the depth-averaged flow angle is independent of the height of the cell. Beyond the middle section, a new secondary current cell is formed, and the flow angle is highly dependent on the height of the cell. The proposed model is thoroughly verified using the flume experimental and field observed data. Good agreement is obtained between predictions and measurements, indicating that the proposed model is capable of accurately predicting the depth-averaged flow angle along a meander in smooth and vegetated meandering compound channels.National Key Research and Development Program of China (No. 2016YFC0402302), and the National Natural Science Foundation of China (Nos. 51709022, 51609160 and 51539007

Estimation of flow direction in meandering compound channels

YesThe flow in the main channel of a meandering compound channel does not occur in the ridge direction because of the effect of the upstream floodplain flows. This study proposes a model for estimating the flow direction in the depth-averaged two-dimensional domain (depth-averaged flow angles) between the entrance and the apex sections. Detailed velocity measurements were performed in the region between the meander entrance section and apex section in a large-scale meandering compound channel. The vertical size of the secondary current cell is highly related to the depth-averaged flow angle; thus, the means of the local flow angles above the secondary current cell and within the cell are separately discussed. The experimental measurements indicate that the mean local flow angle above the cell is equal to the section angle, whereas the mean local flow angle within the cell is equal to zero. The proposed model is validated using published data from five sources. Good agreement is obtained between the predictions and measurements, indicating that the proposed model can accurately estimate the depth-averaged flow direction in the meandering compound channels. Finally, the limitations and application ranges of the model are discussed.National Key Research and Development Program of China (No. 2016YFC0402302), the National Natural Science Foundation of China (Nos. 51539007 and 51609160

DTF-Net: Category-Level Pose Estimation and Shape Reconstruction via Deformable Template Field

Estimating 6D poses and reconstructing 3D shapes of objects in open-world scenes from RGB-depth image pairs is challenging. Many existing methods rely on learning geometric features that correspond to specific templates while disregarding shape variations and pose differences among objects in the same category. As a result, these methods underperform when handling unseen object instances in complex environments. In contrast, other approaches aim to achieve category-level estimation and reconstruction by leveraging normalized geometric structure priors, but the static prior-based reconstruction struggles with substantial intra-class variations. To solve these problems, we propose the DTF-Net, a novel framework for pose estimation and shape reconstruction based on implicit neural fields of object categories. In DTF-Net, we design a deformable template field to represent the general category-wise shape latent features and intra-category geometric deformation features. The field establishes continuous shape correspondences, deforming the category template into arbitrary observed instances to accomplish shape reconstruction. We introduce a pose regression module that shares the deformation features and template codes from the fields to estimate the accurate 6D pose of each object in the scene. We integrate a multi-modal representation extraction module to extract object features and semantic masks, enabling end-to-end inference. Moreover, during training, we implement a shape-invariant training strategy and a viewpoint sampling method to further enhance the model's capability to extract object pose features. Extensive experiments on the REAL275 and CAMERA25 datasets demonstrate the superiority of DTF-Net in both synthetic and real scenes. Furthermore, we show that DTF-Net effectively supports grasping tasks with a real robot arm.Comment: The first two authors are with equal contributions. Paper accepted by ACM MM 202

Data Transmission and Access Protection of Community Medical Internet of Things

On the basis of Internet of Things (IoT) technologies, Community Medical Internet of Things (CMIoT) is a new medical information system and generates massive multiple types of medical data which contain all kinds of user identity data, various types of medical data, and other sensitive information. To effectively protect users’ privacy, we propose a secure privacy data protection scheme including transmission protection and access control. For the uplink transmission data protection, bidirectional identity authentication and fragmented multipath data transmission are used, and for the downlink data protection, fine grained access control and dynamic authorization are used. Through theoretical analysis and experiment evaluation, it is proved that the community medical data can be effectively protected in the transmission and access process without high performance loss

Full Stack Optimization of Transformer Inference: a Survey

Recent advances in state-of-the-art DNN architecture design have been moving toward Transformer models. These models achieve superior accuracy across a wide range of applications. This trend has been consistent over the past several years since Transformer models were originally introduced. However, the amount of compute and bandwidth required for inference of recent Transformer models is growing at a significant rate, and this has made their deployment in latency-sensitive applications challenging. As such, there has been an increased focus on making Transformer models more efficient, with methods that range from changing the architecture design, all the way to developing dedicated domain-specific accelerators. In this work, we survey different approaches for efficient Transformer inference, including: (i) analysis and profiling of the bottlenecks in existing Transformer architectures and their similarities and differences with previous convolutional models; (ii) implications of Transformer architecture on hardware, including the impact of non-linear operations such as Layer Normalization, Softmax, and GELU, as well as linear operations, on hardware design; (iii) approaches for optimizing a fixed Transformer architecture; (iv) challenges in finding the right mapping and scheduling of operations for Transformer models; and (v) approaches for optimizing Transformer models by adapting the architecture using neural architecture search. Finally, we perform a case study by applying the surveyed optimizations on Gemmini, the open-source, full-stack DNN accelerator generator, and we show how each of these approaches can yield improvements, compared to previous benchmark results on Gemmini. Among other things, we find that a full-stack co-design approach with the aforementioned methods can result in up to 88.7x speedup with a minimal performance degradation for Transformer inference

Nanostructured Ni2SeS on Porous-Carbon Skeletons as Highly Efficient Electrocatalyst for Hydrogen Evolution in Acidic Medium

Nickel dichalcogenides have received extensive attention as promising noble-metal-free nanocatalysts for a hydrogen evolution reaction. Nonetheless, their catalytic performance is restricted by the sluggish reaction kinetics, limited exposed active sites, and poor conductivity. In this work, we report on an effective strategy to solve those problems by using an as-designed new porous-C/Ni2SeS nanocatalyst with the Ni2SeS nanostubs anchored on with porous-carbon skeletons process. On the basis of three advantages, as the enhancement of the intrinsic activity using the ternary sulfoselenide, increased number of exposed active sites due to the 3D hollow substrate, and increased conductivity caused by porous-carbon skeletons, the resulting porous-C/Ni2SeS requires an overpotential of only 121 mV at a current density of 10 mA cm–2 with a Tafel slope of 78 mV dec–1 for hydrogen evolution in acidic media and a good long-term stability. Density functional theory calculations also show that the Gibbs free energy of hydrogen adsorption of the Ni2SeS was −0.23 eV, which not only is close to the ideal value (0 eV) and Pt reference (−0.09 eV) but also is lower than those of NiS2 and NiSe2; large electrical states exist in the vicinity of the Fermi level, which further improves its electrocatalytic performance. This work provides new insights into the rational design of ternary dichalcogenides and hollow structure materials for practical applications in HER catalysis and energy fields

Pollutant advective spreading in beach sand exposed to high-energy tides

yesThis paper presents field measurements in which dye solute was injected into coastal sand to investigate contaminant advection in intertidal beach sand. The measurements show the pathways of a contaminated plume in the unsaturated zone during both the flood and ebb tides. A prescribed amount of dye tracer solution was directly injected through the topsoil, with average porosity 0.3521±0.01, at predetermined locations of the River Mersey’s outer estuarial beach during ebb-tide. The injected dye was monitored, sampled and photographed over several tidal cycles. The distinctive features of the plume (full two dimensional cross-sections), sediments and water-table depth were sampled in-situ, close to the injection point (differing from previous contaminant monitoring tests in aquifers). The advective movement is attributed to tidal impact which is different from contaminant transport in aquifers. The experimental results show that plumes have significantly large spatial variability, diverging upwards and converging downwards, with a conical geometric shape which is different from the usual spherical/elliptical shape reported in literature. The mean vertical motion of the plume reaches three times the top-width within ten tidal cycles, exceeding the narrow bottom-width by a factor of order 2. The observed transport features of the plume within the beach sand have significant relevance to saltwater intrusion, surface water and groundwater quality. The field observations are unique and can serve as a valuable benchmark database for relevant numerical studies.China Ministry of Science and Technology 973 program (2014CB745001), Special Program of future development in Shenzhen (201411201645511650) and Shenzhen Key Laboratory for Coastal Ocean Dynamic and Environment（ZDSY20130402163735964)

Histone chaperone Chz1p regulates H2B ubiquitination and subtelomeric anti-silencing

Chz1p is a histone chaperone that interacts physically and functionally with the histone variant Htz1p, which has been implicated in establishing and maintaining boundaries between transcriptionally inactive heterochromatin and active euchromatin. To investigate the role of Chz1p in chromatin organization, we performed genome-wide expression arrays and chromatin immunoprecipitations of SIR complex components and modified histones in a CHZ1 deletion strain. Deletion of CHZ1 led to reduced ubiquitination of subtelomere-associated H2B, reduced subtelomeric H3K79 di-methylation, and increased binding of Sir3p, and Sir4p at telomere-distal euchromatin regions, correlating with decreased gene expression in subtelomeric regions. This anti-silencing defect appears to be mediated by enhanced association of de-ubiquitinase Ubp10p with subtelomeric DNA, as detected by chromatin immunoprecipitation analysis. In support of this, we show that deletion of UBP10 can antagonize the subtelomeric silencing phenotype of Δchz1. Taken together, the results demonstrate a novel role for Chz1p in epigenetic regulation, through H2B de-ubiquitination by Ubp10p

Dominant features in three-dimensional turbulence structure: comparison of non-uniform accelerating and decelerating flows

The results are presented from an experimental study to investigate three-dimensional turbulence structure profiles, including turbulence intensity and Reynolds stress, of different non-uniform open channel flows over smooth bed in subcritical flow regime. In the analysis, the uniform flow profiles have been used to compare with those of the non-uniform flows to investigate their time-averaged spatial flow turbulence structure characteristics. The measured non-uniform velocity profiles are used to verify the von Karman constant κ and to estimate sets of log-law integration constant B r and wake parameter П, where their findings are also compared with values from previous studies. From κ, B r and П findings, it has been found that the log-wake law can sufficiently represent the non-uniform flow in its non-modified form, and all κ, B r and П follow universal rules for different bed roughness conditions. The non-uniform flow experiments also show that both the turbulence intensity and Reynolds stress are governed well by exponential pressure gradient parameter β equations. Their exponential constants are described by quadratic functions in the investigated β range. Through this experimental study, it has been observed that the decelerating flow shows higher empirical constants, in both the turbulence intensity and Reynolds stress compared to the accelerating flow. The decelerating flow also has stronger dominance to determine the flow non-uniformity, because it presents higher Reynolds stress profile than uniform flow, whereas the accelerating flow does not