845 research outputs found
Post-fire flexural buckling and resistances of square recycled aggregate concrete-filled stainless steel tube (RACFSST) columns
The flexural buckling behaviour and residual resistances of square recycled aggregate concrete-filled stainless steel tube (RACFSST) columns after exposure to fire are studied in this paper, based on experiments and numerical modelling. Twelve column specimens, fabricated from concretes with three recycled coarse aggregate replacement ratios (0%, 35% and 70%), were tested after exposure to the ISO 834 standard fire for 0 min (i.e. at ambient temperature), 15 min, 30 min and 45 min. The experimental investigation included heating of specimens, cylinder tests as well as post-fire initial global geometric imperfection measurements, tensile coupon tests and pin-ended column tests. The test setups, procedures and results were fully reported and the ductility indices, lateral deflection distributions and longitudinal strains were discussed and analysed. A numerical investigation was afterwards carried out, where the test results were used to validate thermal and mechanical finite element models; upon validation, parametric studies were conducted to expand the test data bank over a wider range of cross-section dimensions and member lengths. On the basis of the test and numerical data, the relevant design rules for square natural aggregate concrete-filled carbon steel tube columns at ambient temperature, as set out in the European code, Australian/New Zealand standard and American specification, were assessed, using post-fire material properties, for their applicability to square RACFSST columns after exposure to fire. It was found from the assessment results that the three design codes resulted in overall accurate and consistent post-fire flexural buckling resistance predictions but some were unsafe.<br/
Post-fire behaviour and resistances of square recycled aggregate concrete-filled stainless steel tube stub columns
Experimental and numerical studies on the cross-section compressive behaviour and residual resistances of square recycled aggregate concrete-filled stainless steel tube (RACFSST) stub columns after exposure to fire are reported in this paper. An experimental programme was firstly carried out on twelve stub column specimens with three recycled coarse aggregate replacement ratios (0%, 35% and 70%) after exposure to the ISO-834 standard fire for 0 min (i.e. at ambient temperature), 15 min, 30 min and 45 min. The test results, including load–end shortening curves, failure loads and failure modes, were presented, with the initial compressive stiffness and confinement effect analysed. The experimental programme was followed by a numerical modelling programme, where thermal and mechanical finite element models were developed and validated against the test results and afterwards used to conduct parametric studies to generate additional numerical data over a wide range of cross-section dimensions. Based on the test and numerical data, the relevant design rules for square natural aggregate concrete-filled carbon steel tube stub columns at ambient temperature, as specified in the European code, Australia/New Zealand standard and American specification, were evaluated, using post-fire material properties, for their applicability to square RACFSST stub columns after exposure to fire. Th evaluation results generally revealed that the European code and Australian/New Zealand standard led to a good level of design accuracy, while the American specification resulted in slightly conservative post-fire cross-section compression resistance predictions
AutoLaparo: A New Dataset of Integrated Multi-tasks for Image-guided Surgical Automation in Laparoscopic Hysterectomy
Computer-assisted minimally invasive surgery has great potential in
benefiting modern operating theatres. The video data streamed from the
endoscope provides rich information to support context-awareness for
next-generation intelligent surgical systems. To achieve accurate perception
and automatic manipulation during the procedure, learning based technique is a
promising way, which enables advanced image analysis and scene understanding in
recent years. However, learning such models highly relies on large-scale,
high-quality, and multi-task labelled data. This is currently a bottleneck for
the topic, as available public dataset is still extremely limited in the field
of CAI. In this paper, we present and release the first integrated dataset
(named AutoLaparo) with multiple image-based perception tasks to facilitate
learning-based automation in hysterectomy surgery. Our AutoLaparo dataset is
developed based on full-length videos of entire hysterectomy procedures.
Specifically, three different yet highly correlated tasks are formulated in the
dataset, including surgical workflow recognition, laparoscope motion
prediction, and instrument and key anatomy segmentation. In addition, we
provide experimental results with state-of-the-art models as reference
benchmarks for further model developments and evaluations on this dataset. The
dataset is available at https://autolaparo.github.io.Comment: Accepted at MICCAI 202
Single channel based interference-free and self-powered human-machine interactive interface using eigenfrequency-dominant mechanism
The recent development of wearable devices is revolutionizing the way of
human-machine interaction (HMI). Nowadays, an interactive interface that
carries more embedded information is desired to fulfil the increasing demand in
era of Internet of Things. However, present approach normally relies on sensor
arrays for memory expansion, which inevitably brings the concern of wiring
complexity, signal differentiation, power consumption, and miniaturization.
Herein, a one-channel based self-powered HMI interface, which uses the
eigenfrequency of magnetized micropillar (MMP) as identification mechanism, is
reported. When manually vibrated, the inherent recovery of the MMP caused a
damped oscillation that generates current signals because of Faraday's Law of
induction. The time-to-frequency conversion explores the MMP-related
eigenfrequency, which provides a specific solution to allocate diverse commands
in an interference-free behavior even with one electric channel. A cylindrical
cantilever model was built to regulate the MMP eigenfrequencies via precisely
designing the dimensional parameters and material properties. We show that
using one device and two electrodes, high-capacity HMI interface can be
realized when the MMPs with different eigenfrequencies have been integrated.
This study provides the reference value to design the future HMI system
especially for situations that require a more intuitive and intelligent
communication experience with high-memory demand.Comment: 35 pages, 6 figure
MedDiffusion: Boosting Health Risk Prediction via Diffusion-based Data Augmentation
Health risk prediction is one of the fundamental tasks under predictive
modeling in the medical domain, which aims to forecast the potential health
risks that patients may face in the future using their historical Electronic
Health Records (EHR). Researchers have developed several risk prediction models
to handle the unique challenges of EHR data, such as its sequential nature,
high dimensionality, and inherent noise. These models have yielded impressive
results. Nonetheless, a key issue undermining their effectiveness is data
insufficiency. A variety of data generation and augmentation methods have been
introduced to mitigate this issue by expanding the size of the training data
set through the learning of underlying data distributions. However, the
performance of these methods is often limited due to their task-unrelated
design. To address these shortcomings, this paper introduces a novel,
end-to-end diffusion-based risk prediction model, named MedDiffusion. It
enhances risk prediction performance by creating synthetic patient data during
training to enlarge sample space. Furthermore, MedDiffusion discerns hidden
relationships between patient visits using a step-wise attention mechanism,
enabling the model to automatically retain the most vital information for
generating high-quality data. Experimental evaluation on four real-world
medical datasets demonstrates that MedDiffusion outperforms 14 cutting-edge
baselines in terms of PR-AUC, F1, and Cohen's Kappa. We also conduct ablation
studies and benchmark our model against GAN-based alternatives to further
validate the rationality and adaptability of our model design. Additionally, we
analyze generated data to offer fresh insights into the model's
interpretability
A catalog of microbial genes from the bovine rumen unveils a specialized and diverse biomass-degrading environment
Background
The rumen microbiota provides essential services to its host and, through its role in ruminant production, contributes to human nutrition and food security. A thorough knowledge of the genetic potential of rumen microbes will provide opportunities for improving the sustainability of ruminant production systems. The availability of gene reference catalogs from gut microbiomes has advanced the understanding of the role of the microbiota in health and disease in humans and other mammals. In this work, we established a catalog of reference prokaryote genes from the bovine rumen.
Results
Using deep metagenome sequencing we identified 13,825,880 non-redundant prokaryote genes from the bovine rumen. Compared to human, pig, and mouse gut metagenome catalogs, the rumen is larger and richer in functions and microbial species associated with the degradation of plant cell wall material and production of methane. Genes encoding enzymes catalyzing the breakdown of plant polysaccharides showed a particularly high richness that is otherwise impossible to infer from available genomes or shallow metagenomics sequencing. The catalog expands the dataset of carbohydrate-degrading enzymes described in the rumen. Using an independent dataset from a group of 77 cattle fed 4 common dietary regimes, we found that only <0.1% of genes were shared by all animals, which contrast with a large overlap for functions, i.e., 63% for KEGG functions. Different diets induced differences in the relative abundance rather than the presence or absence of genes, which explains the great adaptability of cattle to rapidly adjust to dietary changes.
Conclusions
These data bring new insights into functions, carbohydrate-degrading enzymes, and microbes of the rumen to complement the available information on microbial genomes. The catalog is a significant biological resource enabling deeper understanding of phenotypes and biological processes and will be expanded as new data are made available.info:eu-repo/semantics/publishedVersio
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