393 research outputs found
CSI-Based Human Activity Recognition using Convolutional Neural Networks
Human activity recognition (HAR) as an emerging technology can have undeniable impacts on several applications such as health monitoring, context-aware systems, transportation, robotics, and smart cities. Among the main research methods in HAR (sensor, image, and WiFi-based), the WiFi-based method has attracted considerable attention due to the ubiquity of WiFi devices. WiFi devices can be utilized to distinguish daily activities such as “walk”, “run”, and “sleep”. These activities affect WiFi signal propagation and can be further used to recognize activities. This paper proposes a Deep Learning method for HAR tasks using channel state information (CSI). A new model is developed in which CSI data are converted to grayscale images. These images are then fed into a 2D-Convolutional Neural Network (CNN) for activity classification. We take advantage of CNN's high accuracy on image classification along with WiFi-based ubiquity. The experimental results demonstrate that our proposed approach achieves acceptable performance in HAR tasks
Upregulation of long noncoding RNA MIAT in aggressive form of chronic lymphocytic leukemias.
Long noncoding RNAs (lncRNAs) are non-proten-coding transcripts of more than 200 nucleotides generated by RNA polymerase II and their expressions are tightly regulated in cell type specific- and/or cellular differential stage specific- manner. MIAT, originally isolated as a candidate gene for myocardial infarction, encodes lncRNA (termed MIAT). Here, we determined the expression level of MIAT in established leukemia/lymphoma cell lines and found its upregulation in lymphoid but not in myeloid cell lineage with mature B cell phenotype. MIAT expression level was further determined in chronic lymphocytic leukemias (CLL), characterized by expansion of leukemic cells with mature B phenotype, to demonstrate relatively high occurrence of MIAT upregulation in aggressive form of CLL carrying either 17p-deletion, 11q-deletion, or Trisomy 12 over indolent form carrying 13p-deletion. Furthermore, we show that MIAT constitutes a regulatory loop with OCT4 in malignant mature B cell, as was previously reported in mouse pulripotent stem cell, and that both molecules are essential for cell survival
A CSI-Based Human Activity Recognition Using Deep Learning
The Internet of Things (IoT) has become quite popular due to advancements in Information and Communications technologies and has revolutionized the entire research area in Human Activity Recognition (HAR). For the HAR task, vision-based and sensor-based methods can present better data but at the cost of users’ inconvenience and social constraints such as privacy issues. Due to the ubiquity of WiFi devices, the use of WiFi in intelligent daily activity monitoring for elderly persons has gained popularity in modern healthcare applications. Channel State Information (CSI) as one of the characteristics ofWiFi signals, can be utilized to recognize different human activities. We have employed a Raspberry Pi 4 to collect CSI data for seven different human daily activities, and converted CSI data to images and then used these images as inputs of a 2D Convolutional Neural Network (CNN) classifier. Our experiments have shown that the proposed CSI-based HAR outperforms other competitor methods including 1D-CNN, Long Short-Term Memory (LSTM), and Bi-directional LSTM, and achieves an accuracy of around 95% for seven activities
Experimental tests and numerical simulations on the mechanical response of RC slabs externally strengthened by passive and prestressed FRP strips
Externally Bonded Reinforcement on Groove (EBROG) method has been introduced to enhance the bond resistance of FRP strips to concrete. It has demonstrated that EBROG generally outperforms EBR in terms of loadtransfer capacity between FRP strips and concrete. The present study aims to further demonstrate the potential of EBROG applied for flexural strengthening. A specimen reinforced according to the EBR solution and a nominally equal one reinforced through the EBROG system are first presented. Then, the performance of a newly fully-composite mechanical end anchorage for prestressed FRP strip to be used in conjunction with the EBROG method is investigated. The experimental results show that the premature debonding observed in EBR is avoided by EBROG in the case of "passive" FRP strips. Moreover, the combination of EBROG and end anchorage demonstrates their effectiveness, as the pre-stressed slab exhibits the full exploitation of the FRP up to rupture. Numerical analyses, carried out by means of a model already presented by the authors, show that the structural response of the tested slabs can be simulated in a very accurate manner if consistent assumptions are made in terms of bond-slip laws adopted to describe the interaction between FRP and concrete in EBR and EBROG
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Genome-wide screening of mouse knockouts reveals novel genes required for normal integumentary and oculocutaneous structure and function.
Oculocutaneous syndromes are often due to mutations in single genes. In some cases, mouse models for these diseases exist in spontaneously occurring mutations, or in mice resulting from forward mutatagenesis screens. Here we present novel genes that may be causative for oculocutaneous disease in humans, discovered as part of a genome-wide screen of knockout-mice in a targeted single-gene deletion project. The International Mouse Phenotyping Consortium (IMPC) database (data release 10.0) was interrogated for all mouse strains with integument abnormalities, which were then cross-referenced individually to identify knockouts with concomitant ocular abnormalities attributed to the same targeted gene deletion. The search yielded 307 knockout strains from unique genes with integument abnormalities, 226 of which have not been previously associated with oculocutaneous conditions. Of the 307 knockout strains with integument abnormalities, 52 were determined to have ocular changes attributed to the targeted deletion, 35 of which represent novel oculocutaneous genes. Some examples of various integument abnormalities are shown, as well as two examples of knockout strains with oculocutaneous phenotypes. Each of the novel genes provided here are potentially relevant to the pathophysiology of human integumentary, or oculocutaneous conditions, such as albinism, phakomatoses, or other multi-system syndromes. The novel genes reported here may implicate molecular pathways relevant to these human diseases and may contribute to the discovery of novel therapeutic targets
Enhancing CSI-Based Human Activity Recognition by Edge Detection Techniques
Human Activity Recognition (HAR) has been a popular area of research in the Internet of Things (IoT) and Human–Computer Interaction (HCI) over the past decade. The objective of this field is to detect human activities through numeric or visual representations, and its applications include smart homes and buildings, action prediction, crowd counting, patient rehabilitation, and elderly monitoring. Traditionally, HAR has been performed through vision-based, sensor-based, or radar-based approaches. However, vision-based and sensor-based methods can be intrusive and raise privacy concerns, while radar-based methods require special hardware, making them more expensive. WiFi-based HAR is a cost-effective alternative, where WiFi access points serve as transmitters and users’ smartphones serve as receivers. The HAR in this method is mainly performed using two wireless-channel metrics: Received Signal Strength Indicator (RSSI) and Channel State Information (CSI). CSI provides more stable and comprehensive information about the channel compared to RSSI. In this research, we used a convolutional neural network (CNN) as a classifier and applied edge-detection techniques as a preprocessing phase to improve the quality of activity detection. We used CSI data converted into RGB images and tested our methodology on three available CSI datasets. The results showed that the proposed method achieved better accuracy and faster training times than the simple RGB-represented data. In order to justify the effectiveness of our approach, we repeated the experiment by applying raw CSI data to long short-term memory (LSTM) and Bidirectional LSTM classifiers
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Chromatic Pupillometry as a Putative Screening Tool for Heritable Retinal Disease in Rhesus Macaques
PurposeNon-human primates (NHPs) are useful models for human retinal disease. Chromatic pupillometry has been proposed as a noninvasive method of identifying inherited retinal diseases (IRDs) in humans; however, standard protocols employ time-consuming dark adaptation. We utilized shortened and standard dark-adaptation protocols to compare pupillary light reflex characteristics following chromatic stimulation in rhesus macaques with achromatopsia to wild-type (WT) controls with normal retinal function.MethodsNine rhesus macaques homozygous for the p.R656Q mutation (PDE6C HOMs) and nine WT controls were evaluated using chromatic pupillometry following 1-minute versus standard 20-minute dark adaptations. The following outcomes were measured and compared between groups: pupil constriction latency, peak constriction, pupil constriction time, and constriction velocity.ResultsPupil constriction latency was significantly longer in PDE6C HOMs with red-light (P = 0.0002) and blue-light (P = 0.04) stimulation versus WT controls. Peak constriction was significantly less in PDE6C HOMs with all light stimulation compared to WT controls (P < 0.0001). Pupil constriction time was significantly shorter in PDE6C HOMs versus WT controls with red-light (P = 0.04) and white-light (P = 0.003) stimulation. Pupil constriction velocity was significantly slower in PDE6C HOMs versus WT controls with red-light (P < 0.0001), blue-light (P < 0.0001), and white-light (P = 0.0002) stimulation. Dark adaptation time only significantly affected peak (P = 0.008) and time of pupil constriction (P = 0.02) following blue-light stimulation.ConclusionsChromatic pupillometry following 1- and 20-minute dark adaptation is an effective tool for screening NHPs for achromatopsia.Translational relevanceRapid identification of NHPs with IRDs will provide animal research models to advance research and treatment of achromatopia in humans
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