99 research outputs found
ActiveSelfHAR: Incorporating Self Training into Active Learning to Improve Cross-Subject Human Activity Recognition
Deep learning-based human activity recognition (HAR) methods have shown great
promise in the applications of smart healthcare systems and wireless body
sensor network (BSN). Despite their demonstrated performance in laboratory
settings, the real-world implementation of such methods is still hindered by
the cross-subject issue when adapting to new users. To solve this issue, we
propose ActiveSelfHAR, a framework that combines active learning's benefit of
sparsely acquiring data with actual labels and self- training's benefit of
effectively utilizing unlabeled data to enable the deep model to adapt to the
target domain, i.e., the new users. In this framework, the model trained in the
last iteration or the source domain is first utilized to generate pseudo labels
of the target-domain samples and construct a self-training set based on the
confidence score. Second, we propose to use the spatio-temporal relationships
among the samples in the non-self-training set to augment the core set selected
by active learning. Finally, we combine the self-training set and the augmented
core set to fine-tune the model. We demonstrate our method by comparing it with
state-of-the-art methods on two IMU-based datasets and an EMG-based dataset.
Our method presents similar HAR accuracies with the upper bound, i.e. fully
supervised fine-tuning with less than 1\% labeled data of the target dataset
and significantly improves data efficiency and time cost. Our work highlights
the potential of implementing user-independent HAR methods into smart
healthcare systems and BSN
Attribute-based encryption for cloud computing access control: A survey
National Research Foundation (NRF) Singapore; AXA Research Fun
Investigation of the Cofiring Process of Raw or Torrefied Bamboo and Masson Pine by Using a Cone Calorimeter
Cofiring characteristics of raw or torrefied bamboo and masson pine blends with different blend ratios were investigated by cone calorimetry, and its ash performance from cofiring was also determined by a YX-HRD testing instrument, X-ray fluorescence, scanning electron microscopy (SEM), and transmission electron microscopy (TEM). Results showed that bamboo and masson pine had the different physicochemical properties. Torrefaction improved fuel performances, resulting in a more stable cofiring process. It also decreased the heat release rate, total heat release, and total suspended particulates of fuels, especially CO2 and CO release. Masson pine ash mainly included CaO, SiO2, Fe2O3, K2O, and Al2O3. Bamboo ash was mainly composed of K2O, SiO2, MgO, and SO3. There were different melting temperatures and trends between different samples. The synergistic reaction of ash components was found during the cofiring process. The surface morphology of blend ash changed with the variation of bamboo or masson pine content
Actuarial Model Assumptions for Australian Inflation, Equity Returns, and Interest Rates
Though actuaries have developed several types of stochastic investment models for inflation, stock market returns, and interest rates, there are two commonly used in practice: autoregressive time series models with normally distributed errors, and autoregressive conditional heteroscedasticity (ARCH) models. ARCH models are particularly suited when there is heteroscedasticity in inflation and interest rate series. In such cases nonnormal residuals are found in the empirical data. This paper examines whether Australian univariate inflation and interest rate data are consistent with autoregressive time series and ARCH model assumptions
A new dependable exchange protocol
Abstract As electronic transaction becomes common practice in real-world business, its dependability develops into a major concern, especially in critical transactions, e.g., electronic payment and electronic contract signing. Many recent fair-exchange protocols can recover the transaction from network failures; however, few can survive local system failures. In this paper, we propose a new Dependable Exchange Protocol. With proper convertible signature scheme and message logging method, the exchange protocol provides a recovery method for network and local system failures. To the best of our knowledge, this protocol is the first fault-tolerant exchange protocol in the context of offline TTP and asynchronous channels
Reduced SV2A and GABA receptor levels in the brains of type 2 diabetic rats revealed by [F]SDM-8 and [F]flumazenil PET
PURPOSE: Type 2 diabetes mellitus (T2DM) is associated with a greater risk of Alzheimer's disease. Synaptic impairment and protein aggregates have been reported in the brains of T2DM models. Here, we assessed whether neurodegenerative changes in synaptic vesicle 2 A (SV2A), γ-aminobutyric acid type A (GABA) receptor, amyloid-β, tau and receptor for advanced glycosylation end product (RAGE) can be detected in vivo in T2DM rats.
Methods: Positron emission tomography (PET) using [F]SDM-8 (SV2A), [F]flumazenil (GABA receptor), [F]florbetapir (amyloid-β), [F]PM-PBB3 (tau), and [F]FPS-ZM1 (RAGE) was carried out in 12-month-old diabetic Zucker diabetic fatty (ZDF) and SpragueDawley (SD) rats. Immunofluorescence staining, Thioflavin S staining, proteomic profiling and pathway analysis were performed on the brain tissues of ZDF and SD rats.
Results: Reduced cortical [F]SDM-8 uptake and cortical and hippocampal [F]flumazenil uptake were observed in 12-month-old ZDF rats compared to SD rats. The regional uptake of [F]florbetapir and [F]PM-PBB3 was comparable in the brains of 12-month-old ZDF and SD rats. Immunofluorescence staining revealed Thioflavin S-negative, phospho-tau-positive inclusions in the cortex and hypothalamus in the brains of ZDF rats and the absence of amyloid-beta deposits. The level of GABA receptors was lower in the cortex of ZDF rats than SD rats. Proteomic analysis further demonstrated that, compared with SD rats, synaptic-related proteins and pathways were downregulated in the hippocampus of ZDF rats.
Conclusion: These findings provide in vivo evidence for regional reductions in SV2A and GABA receptor levels in the brains of aged T2DM ZDF rats
Unraveling the pathogenic potential of the Pentatrichomonas hominis PHGD strain: impact on IPEC-J2 cell growth, adhesion, and gene expression
Pentatrichomonas hominis, a flagellated parasitic protozoan, predominantly infects the mammalian digestive tract, often causing symptoms such as abdominal pain and diarrhea. However, studies investigating its pathogenicity are limited, and the mechanisms underlying P. hominis-induced diarrhea remain unclear. Establishing an in vitro cell model for P. hominis infection is imperative. This study investigated the interaction between P. hominis and IPEC-J2 cells and its impact on parasite growth, adhesion, morphology, and cell viability. Co-cultivation of P. hominis with IPEC-J2 cells resulted in exponential growth of the parasite, with peak densities reaching approximately 4.8 × 105 cells/mL and 1.2 × 106 cells/mL at 48 h for initial inoculation concentrations of 104 cells/mL and 105 cells/mL, respectively. The adhesion rate of P. hominis to IPEC-J2 cells reached a maximum of 93.82% and 86.57% at 24 h for initial inoculation concentrations of 104 cells/mL and 105 cells/mL, respectively. Morphological changes in IPEC-J2 cells co-cultivated with P. hominis were observed, manifesting as elongated and irregular shapes. The viability of IPEC-J2 cells exhibited a decreasing trend with increasing P. hominis concentration and co-cultivation time. Additionally, the mRNA expression levels of IL-6, IL-8, and TNF-α were upregulated, whereas those of CAT and CuZn-SOD were downregulated. These findings provide quantitative evidence that P. hominis can promote its growth by adhering to IPEC-J2 cells, inducing morphological changes, reducing cell viability, and triggering inflammatory responses. Further in vivo studies are warranted to confirm these results and enhance our understanding of P. hominis infection
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