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https://www.readbyqxmd.com/read/28323040/-machine-learning-based-identification-of-endogenous-cellular-microrna-sponges-against-viral-micrornas
#1
Soowon Kang, Seunghyun Park, Sungroh Yoon, Hyeyoung Min
A "miRNA sponge" is an artificial oligonucleotide-based miRNA inhibitor containing multiple binding sites for a specific miRNA. Each miRNA sponge can bind and sequester several miRNA copies, thereby decreasing the cellular levels of the target miRNA. In addition to developing artificial miRNA sponges, scientists have sought endogenous RNA transcripts and found that long non-coding RNAs, competing endogenous RNAs, pseudogenes, circular RNAs, and coding RNAs could act as miRNA sponges under precise conditions...
March 17, 2017: Methods: a Companion to Methods in Enzymology
https://www.readbyqxmd.com/read/28320651/collaborative-active-visual-recognition-from-crowds-a-distributed-ensemble-approach
#2
Gang Hua, Chengjiang Long, Ming Yang, Yan Gao
Active learning is an effective way of engaging users to interactively train models for visual recognition more efficiently. The vast majority of previous works focused on active learning with a single human oracle. The problem of active learning with multiple oracles in a collaborative setting has not been well explored. We present a collaborative computational model for active learning with multiple human oracles, the input from whom may be subject to different levels of noise. It leads to not only an ensemble kernel machine that is robust to label noise, but also a principled label quality measure to online detect irresponsible labelers...
March 15, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28318903/understanding-human-intention-by-connecting-perception-and-action-learning-in-artificial-agents
#3
Sangwook Kim, Zhibin Yu, Minho Lee
To develop an advanced human-robot interaction system, it is important to first understand how human beings learn to perceive, think, and act in an ever-changing world. In this paper, we propose an intention understanding system that uses an Object Augmented-Supervised Multiple Timescale Recurrent Neural Network (OA-SMTRNN) and demonstrate the effects of perception-action connected learning in an artificial agent, which is inspired by psychological and neurological phenomena in humans. We believe that action and perception are not isolated processes in human mental development, and argue that these psychological and neurological interactions can be replicated in a human-machine scenario...
February 11, 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28318277/technology-enhanced-human-interaction-in-psychotherapy
#4
Zac E Imel, Derek D Caperton, Michael Tanana, David C Atkins
Psychotherapy is on the verge of a technology-inspired revolution. The concurrent maturation of communication, signal processing, and machine learning technologies begs an earnest look at how these technologies may be used to improve the quality of psychotherapy. Here, we discuss 3 research domains where technology is likely to have a significant impact: (1) mechanism and process, (2) training and feedback, and (3) technology-mediated treatment modalities. For each domain, we describe current and forthcoming examples of how new technologies may change established applications...
March 20, 2017: Journal of Counseling Psychology
https://www.readbyqxmd.com/read/28315750/fun-cube-based-brain-gym-cognitive-function-assessment-system
#5
Tao Zhang, Chung-Chih Lin, Tsang-Chu Yu, Jing Sun, Wen-Chuin Hsu, Alice May-Kuen Wong
The aim of this study is to design and develop a fun cube (FC) based brain gym (BG) cognitive function assessment system using the wireless sensor network and multimedia technologies. The system comprised (1) interaction devices, FCs and a workstation used as interactive tools for collecting and transferring data to the server, (2) a BG information management system responsible for managing the cognitive games and storing test results, and (3) a feedback system used for conducting the analysis of cognitive functions to assist caregivers in screening high risk groups with mild cognitive impairment...
March 3, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28303256/recurring-functional-interactions-predict-network-architecture-of-interictal-and-ictal-states-in-neocortical-epilepsy
#6
Ankit N Khambhati, Danielle S Bassett, Brian S Oommen, Stephanie H Chen, Timothy H Lucas, Kathryn A Davis, Brian Litt
Human epilepsy patients suffer from spontaneous seizures, which originate in brain regions that also subserve normal function. Prior studies demonstrate focal, neocortical epilepsy is associated with dysfunction, several hours before seizures. How does the epileptic network perpetuate dysfunction during baseline periods? To address this question, we developed an unsupervised machine learning technique to disentangle patterns of functional interactions between brain regions, or subgraphs, from dynamic functional networks constructed from approximately 100 h of intracranial recordings in each of 22 neocortical epilepsy patients...
January 2017: ENeuro
https://www.readbyqxmd.com/read/28292943/molecular-details-underlying-dynamic-structures-and-regulation-of-the-human-26s-proteasome
#7
Xiaorong Wang, Peter Cimermancic, Clinton Yu, Andreas Schweitzer, Nikita Chopra, James L Engel, Charles H Greenberg, Alexander S Huszagh, Florian Beck, Eri Sakata, Yingying Yang, Eric J Novitsky, Alexander Leitner, Paolo Nanni, Abdullah Kahraman, Xing Guo, Jack E Dixon, Scott D Rychnovsky, Ruedi Aebersold, Wolfgang Baumeister, Andrej Sali, Lan Huang
The 26S proteasome is the macromolecular machine responsible for ATP/ubiquitin dependent degradation. As aberration in proteasomal degradation has been implicated in many human diseases, structural analysis of the human 26S proteasome complex is essential to advance our understanding of its action and regulation mechanisms. In recent years, cross-linking mass spectrometry (XL-MS) has emerged as a powerful tool for elucidating structural topologies of large protein assemblies, with its unique capability of studying protein complexes in cells...
March 14, 2017: Molecular & Cellular Proteomics: MCP
https://www.readbyqxmd.com/read/28287448/real-time-digital-signal-processing-based-on-fpgas-for-electronic-skin-implementation-%C3%A2
#8
Ali Ibrahim, Paolo Gastaldo, Hussein Chible, Maurizio Valle
Enabling touch-sensing capability would help appliances understand interaction behaviors with their surroundings. Many recent studies are focusing on the development of electronic skin because of its necessity in various application domains, namely autonomous artificial intelligence (e.g., robots), biomedical instrumentation, and replacement prosthetic devices. An essential task of the electronic skin system is to locally process the tactile data and send structured information either to mimic human skin or to respond to the application demands...
March 10, 2017: Sensors
https://www.readbyqxmd.com/read/28269818/a-two-dimensional-matrix-image-based-feature-extraction-method-for-classification-of-semg-a-comparative-analysis-based-on-svm-knn-and-rbf-nn
#9
Tingxi Wen, Zhongnan Zhang, Ming Qiu, Ming Zeng, Weizhen Luo
BACKGROUND: The computer mouse is an important human-computer interaction device. But patients with physical finger disability are unable to operate this device. Surface EMG (sEMG) can be monitored by electrodes on the skin surface and is a reflection of the neuromuscular activities. Therefore, we can control limbs auxiliary equipment by utilizing sEMG classification in order to help the physically disabled patients to operate the mouse. OBJECTIVE: To develop a new a method to extract sEMG generated by finger motion and apply novel features to classify sEMG...
March 3, 2017: Journal of X-ray Science and Technology
https://www.readbyqxmd.com/read/28269110/assessment-of-mental-workload-by-eeg-fnirs
#10
Haleh Aghajani, Ahmet Omurtag
We investigated the use of a multimodal functional neuroimaging system in quantifying mental workload of healthy human volunteers. We recorded behavioral performance measures as well as electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) simultaneously from subjects performing n-back tasks. The EEG and fNIRS signals were used in feature generation and classification offline using support vector machines. We examined the classification accuracy of three distinct systems: EEG based; fNIRS based; and Hybrid, which contained features from the first two systems as based on their interactions...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268455/improve-the-generalization-of-emotional-classifiers-across-time-by-using-training-samples-from-different-days
#11
Shuang Liu, Jingjing Tong, Minpeng Xu, Jiajia Yang, Hongzhi Qi, Dong Ming
Electroencephalographic (EEG)-based emotion recognition has attracted increasing attention from the field of human-computer interaction (HCI). However, there are a number of challenges for machines to correctly recognize human emotional states. One problem is how to generalize the emotion model across time, since the brain may show different patterns of EEG for the same emotion experience at different time. This study investigated the feasibility of adding samples from different days to the training set to improve the generalization of the emotion classifier...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28246068/issues-for-ehealth-in-psychiatry-results-of-an-expert-survey
#12
Jennifer Nicholas, Kit Huckvale, Mark Erik Larsen, Ashna Basu, Philip J Batterham, Frances Shaw, Shahbaz Sendi
BACKGROUND: Technology has changed the landscape in which psychiatry operates. Effective, evidence-based treatments for mental health care are now available at the fingertips of anyone with Internet access. However, technological solutions for mental health are not necessarily sought by consumers nor recommended by clinicians. OBJECTIVE: The objectives of this study are to identify and discuss the barriers to introducing eHealth technology-supported interventions within mental health...
February 28, 2017: Journal of Medical Internet Research
https://www.readbyqxmd.com/read/28237186/a-learning-based-markerless-approach-for-full-body-kinematics-estimation-in-natura-from-a-single-image
#13
Ami Drory, Hongdong Li, Richard Hartley
We present a supervised machine learning approach for markerless estimation of human full-body kinematics for a cyclist from an unconstrained colour image. This approach is motivated by the limitations of existing marker-based approaches restricted by infrastructure, environmental conditions, and obtrusive markers. By using a discriminatively learned mixture-of-parts model, we construct a probabilistic tree representation to model the configuration and appearance of human body joints. During the learning stage, a Structured Support Vector Machine (SSVM) learns body parts appearance and spatial relations...
January 31, 2017: Journal of Biomechanics
https://www.readbyqxmd.com/read/28227336/assessment-of-mental-workload-by-eeg-fnirs
#14
Haleh Aghajani, Ahmet Omurtag, Haleh Aghajani, Ahmet Omurtag, Ahmet Omurtag, Haleh Aghajani
We investigated the use of a multimodal functional neuroimaging system in quantifying mental workload of healthy human volunteers. We recorded behavioral performance measures as well as electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) simultaneously from subjects performing n-back tasks. The EEG and fNIRS signals were used in feature generation and classification offline using support vector machines. We examined the classification accuracy of three distinct systems: EEG based; fNIRS based; and Hybrid, which contained features from the first two systems as based on their interactions...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226628/improve-the-generalization-of-emotional-classifiers-across-time-by-using-training-samples-from-different-days
#15
Shuang Liu, Jingjing Tong, Minpeng Xu, Jiajia Yang, Hongzhi Qi, Dong Ming, Shuang Liu, Jingjing Tong, Minpeng Xu, Jiajia Yang, Hongzhi Qi, Dong Ming, Shuang Liu, Minpeng Xu, Dong Ming, Hongzhi Qi, Jiajia Yang, Jingjing Tong
Electroencephalographic (EEG)-based emotion recognition has attracted increasing attention from the field of human-computer interaction (HCI). However, there are a number of challenges for machines to correctly recognize human emotional states. One problem is how to generalize the emotion model across time, since the brain may show different patterns of EEG for the same emotion experience at different time. This study investigated the feasibility of adding samples from different days to the training set to improve the generalization of the emotion classifier...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28224972/a-mathematical-model-for-the-two-learners-problem
#16
Jan Saputra Müller, Carmen Vidaurre, Martijn Schreuder, Frank C Meinecke, Paul von Bünau, Klaus-Robert Müller
OBJECTIVE: We present the first generic theoretical formulation of the co-adaptive learning problem and give a simple example of two interacting linear learning systems, a human and a machine. APPROACH: After the description of the training protocol of the two learning systems, we define a simple linear model where the two learning agents are coupled by a joint loss function. The simplicity of the model allows us to find learning rules for both human and machine that permit computing theoretical simulations...
February 22, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28190455/who-s-who-detecting-and-resolving-sample-anomalies-in-human-dna-sequencing-studies-with-peddy
#17
Brent S Pedersen, Aaron R Quinlan
The potential for genetic discovery in human DNA sequencing studies is greatly diminished if DNA samples from a cohort are mislabeled, swapped, or contaminated or if they include unintended individuals. Unfortunately, the potential for such errors is significant since DNA samples are often manipulated by several protocols, labs, or scientists in the process of sequencing. We have developed a software package, peddy, to identify and facilitate the remediation of such errors via interactive visualizations and reports comparing the stated sex, relatedness, and ancestry to what is inferred from the individual genotypes derived from whole-genome (WGS) or whole-exome (WES) sequencing...
March 2, 2017: American Journal of Human Genetics
https://www.readbyqxmd.com/read/28185019/biological-ageing-and-clinical-consequences-of-modern-technology
#18
Marios Kyriazis
The pace of technology is steadily increasing, and this has a widespread effect on all areas of health and society. When we interact with this technological environment we are exposed to a wide variety of new stimuli and challenges, which may modulate the stress response and thus change the way we respond and adapt. In this Opinion paper I will examine certain aspects of the human-computer interaction with regards to health and ageing. There are practical, everyday effects which also include social and cultural elements...
February 9, 2017: Biogerontology
https://www.readbyqxmd.com/read/28178889/v-elmpirnapred-identification-of-human-pirnas-by-the-voting-based-extreme-learning-machine-v-elm-with-a-new-hybrid-feature
#19
Cong Pian, Yuan-Yuan Chen, Jin Zhang, Zhi Chen, Guang-Le Zhang, Qiang Li, Tao Yang, Liang-Yun Zhang
Piwi-interacting RNAs (piRNAs) were recently discovered as endogenous small noncoding RNAs. Some recent research suggests that piRNAs may play an important role in cancer. So the precise identification of human piRNAs is a significant work. In this paper, we introduce a series of new features with 80 dimension called short sequence motifs (SSM). A hybrid feature vector with 1444 dimension can be formed by combining 1364 features of [Formula: see text]-mer strings and 80 features of SSM features. We optimize the 1444 dimension features using the feature score criterion (FSC) and list them in descending order according to the scores...
February 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28178184/a-3d-human-machine-integrated-design-and-analysis-framework-for-squat-exercises-with-a-smith-machine
#20
Haerin Lee, Moonki Jung, Ki-Kwang Lee, Sang Hun Lee
In this paper, we propose a three-dimensional design and evaluation framework and process based on a probabilistic-based motion synthesis algorithm and biomechanical analysis system for the design of the Smith machine and squat training programs. Moreover, we implemented a prototype system to validate the proposed framework. The framework consists of an integrated human-machine-environment model as well as a squat motion synthesis system and biomechanical analysis system. In the design and evaluation process, we created an integrated model in which interactions between a human body and machine or the ground are modeled as joints with constraints at contact points...
February 6, 2017: Sensors
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