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https://www.readbyqxmd.com/read/28544985/experiences-of-nursing-students-and-educators-during-the-co-construction-of-clinical-nursing-leadership-learning-activities-a-qualitative-research-and-development-study
#1
Laurence Ha, Jacinthe Pepin
BACKGROUND: Student voice posits that students' unique perspectives on teaching and learning can be used in conjunction with those of educators to create meaningful educational activities. OBJECTIVE: The study aimed to describe nursing students' and educators' experiences during the co-construction of educational activities involving clinical nursing leadership. DESIGN: Qualitative research and development model. SETTING: The study was conducted at a French-Canadian nursing faculty that provides a 3-year undergraduate program...
May 15, 2017: Nurse Education Today
https://www.readbyqxmd.com/read/28544658/the-evolution-of-stories-from-mimesis-to-language-from-fact-to-fiction
#2
REVIEW
Brian Boyd
Why a species as successful as Homo sapiens should spend so much time in fiction, in telling one another stories that neither side believes, at first seems an evolutionary riddle. Because of the advantages of tracking and recombining true information, capacities for event comprehension, memory, imagination, and communication evolved in a range of animal species-yet even chimpanzees cannot communicate beyond the here and now. By Homo erectus, our forebears had reached an increasing dependence on one another, not least in sharing information in mimetic, prelinguistic ways...
May 24, 2017: Wiley Interdisciplinary Reviews. Cognitive Science
https://www.readbyqxmd.com/read/28544500/non-communicable-diseases-and-hiv-care-and-treatment-models-of-integrated-service-delivery
#3
REVIEW
Malia Duffy, Bisola Ojikutu, Soa Andrian, Elaine Sohng, Thomas Minior, Lisa R Hirschhorn
OBJECTIVES: Non-communicable diseases (NCD) are a growing cause of morbidity in low-income countries including in people living with Human Immunodeficiency Virus (HIV). Integration of NCD and HIV services can build upon experience with chronic care models from HIV programs. We describe models of NCD and HIV integration, challenges, and lessons learned. METHODS: Literature review of articles on integrated NCD and HIV programs in low-income countries and key informant interviews with leaders of identified integrated NCD and HIV programs...
May 24, 2017: Tropical Medicine & International Health: TM & IH
https://www.readbyqxmd.com/read/28542248/the-detection-of-faked-identity-using-unexpected-questions-and-mouse-dynamics
#4
Merylin Monaro, Luciano Gamberini, Giuseppe Sartori
The detection of faked identities is a major problem in security. Current memory-detection techniques cannot be used as they require prior knowledge of the respondent's true identity. Here, we report a novel technique for detecting faked identities based on the use of unexpected questions that may be used to check the respondent identity without any prior autobiographical information. While truth-tellers respond automatically to unexpected questions, liars have to "build" and verify their responses. This lack of automaticity is reflected in the mouse movements used to record the responses as well as in the number of errors...
2017: PloS One
https://www.readbyqxmd.com/read/28542234/robust-auto-weighted-multi-view-subspace-clustering-with-common-subspace-representation-matrix
#5
Wenzhang Zhuge, Chenping Hou, Yuanyuan Jiao, Jia Yue, Hong Tao, Dongyun Yi
In many computer vision and machine learning applications, the data sets distribute on certain low-dimensional subspaces. Subspace clustering is a powerful technology to find the underlying subspaces and cluster data points correctly. However, traditional subspace clustering methods can only be applied on data from one source, and how to extend these methods and enable the extensions to combine information from various data sources has become a hot area of research. Previous multi-view subspace methods aim to learn multiple subspace representation matrices simultaneously and these learning task for different views are treated equally...
2017: PloS One
https://www.readbyqxmd.com/read/28541894/the-extreme-value-machine
#6
Ethan M Rudd, Lalit P Jain, Walter J Scheirer, Terrance E Boult
It is often desirable to be able to recognize when inputs to a recognition function learned in a supervised manner correspond to classes unseen at training time. With this ability, new class labels could be assigned to these inputs by a human operator, allowing them to be incorporated into the recognition function - ideally under an efficient incremental update mechanism. While good algorithms that assume inputs from a fixed set of classes exist, e.g., artificial neural networks and kernel machines, it is not immediately obvious how to extend them to perform incremental learning in the presence of unknown query classes...
May 23, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28541893/sequential-optimization-for-efficient-high-quality-object-proposal-generation
#7
Ziming Zhang, Yun Liu, Xi Chen, Yanjun Zhu, Ming-Ming Cheng, Venkatesh Saligrama, Philip H S Torr
We are motivated by the need for a generic object proposal generation algorithm which achieves good balance between object detection recall, proposal localization quality and computational efficiency. We propose a novel object proposal algorithm, BING++, which inherits the virtue of good computational efficiency of BING [1] but significantly improves its proposal localization quality. At high level we formulate the problem of object proposal generation from a novel probabilistic perspective, based on which our BING++ manages to improve the localization quality by employing edges and segments to estimate object boundaries and update the proposals sequentially...
May 23, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28541493/identifying-reports-of-randomized-controlled-trials-rcts-via-a-hybrid-machine-learning-and-crowdsourcing-approach
#8
Byron C Wallace, Anna Noel-Storr, Iain J Marshall, Aaron M Cohen, Neil R Smalheiser, James Thomas
Objectives: Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make this process more efficient via a hybrid approach using both crowdsourcing and ML. Methods: We trained a classifier to discriminate between citations that describe RCTs and those that do not. We then adopted a simple strategy of automatically excluding citations deemed very unlikely to be RCTs by the classifier and deferring to crowdworkers otherwise...
May 25, 2017: Journal of the American Medical Informatics Association: JAMIA
https://www.readbyqxmd.com/read/28541413/the-influence-of-the-apolipoprotein-e-apoe-gene-on-subacute-post-concussion-neurocognitive-performance-in-college-athletes
#9
Victoria C Merritt, Amanda R Rabinowitz, Peter A Arnett
Objective: The purpose of this study was to determine whether the ε4 allele of the APOE gene influences neurocognitive outcome following sports-related concussion. It was hypothesized that participants with an ε4 allele would show poorer neurocognitive performance and greater neurocognitive variability than those without an ε4 allele. Method: Participants included 57 concussed collegiate athletes (77.2% male) who participated in a concussion management program at a large university...
May 24, 2017: Archives of Clinical Neuropsychology: the Official Journal of the National Academy of Neuropsychologists
https://www.readbyqxmd.com/read/28541227/manifold-preserving-an-intrinsic-approach-for-semisupervised-distance-metric-learning
#10
Shihui Ying, Zhijie Wen, Jun Shi, Yaxin Peng, Jigen Peng, Hong Qiao
In this paper, we address the semisupervised distance metric learning problem and its applications in classification and image retrieval. First, we formulate a semisupervised distance metric learning model by considering the metric information of inner classes and interclasses. In this model, an adaptive parameter is designed to balance the inner metrics and intermetrics by using data structure. Second, we convert the model to a minimization problem whose variable is symmetric positive-definite matrix. Third, in implementation, we deduce an intrinsic steepest descent method, which assures that the metric matrix is strictly symmetric positive-definite at each iteration, with the manifold structure of the symmetric positive-definite matrix manifold...
May 18, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28541202/linear-support-tensor-machine-with-lsk-channels-pedestrian-detection-in-thermal-infrared-images
#11
Sujoy Kumar Biswas, Peyman Milanfar
Pedestrian detection in thermal infrared images poses unique challenges because of the low resolution and noisy nature of the image. Here we propose a mid-level attribute in the form of the multidimensional template, or tensor, using Local Steering Kernel (LSK) as low-level descriptors for detecting pedestrians in far infrared images. LSK is specifically designed to deal with intrinsic image noise and pixel level uncertainty by capturing local image geometry succinctly instead of collecting local orientation statistics (e...
May 18, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28541193/analysis-of-energy-based-metrics-for-laparoscopic-skills-assessment
#12
Behnaz Poursartip, Marie-Eve LeBel, Rajni Patel, Michael Naish, Ana Luisa Trejos
OBJECTIVE: The complexity of Minimally Invasive Surgery (MIS) requires that trainees practice MIS skills in numerous training sessions. The goal of these training sessions is to learn how to move the instruments smoothly without damaging the surrounding tissue and achieving operative tasks with accuracy. In order to enhance the efficiency of these training sessions, the proficiency of the trainees should be assessed using an objective assessment method. Several performance metrics have been proposed and analyzed for MIS tasks...
May 19, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28541084/the-feasibility-of-automated-eye-tracking-with-the-early-childhood-vigilance-test-of-attention-in-younger-hiv-exposed-ugandan-children
#13
Michael J Boivin, Jonathan Weiss, Ronak Chhaya, Victoria Seffren, Jorem Awadu, Alla Sikorskii, Bruno Giordani
OBJECTIVE: Tobii eye tracking was compared with webcam-based observer scoring on an animation viewing measure of attention (Early Childhood Vigilance Test; ECVT) to evaluate the feasibility of automating measurement and scoring. Outcomes from both scoring approaches were compared with the Mullen Scales of Early Learning (MSEL), Color-Object Association Test (COAT), and Behavior Rating Inventory of Executive Function for preschool children (BRIEF-P). METHOD: A total of 44 children 44 to 65 months of age were evaluated with the ECVT, COAT, MSEL, and BRIEF-P...
May 25, 2017: Neuropsychology
https://www.readbyqxmd.com/read/28540473/innovative-use-of-single-incision-internal-fixation-of-distal-clavicle-fractures-augmented-with-coracoclavicular-stabilisation
#14
Rajpal Nandra, Tomasz Kowalski, Socrates Kalogrianitis
INTRODUCTION: The management of displaced fractures of the distal clavicle remains controversial, particularly in younger patients where there is no consensus as to which surgical intervention is best. Each surgical method has unique surgical complications and rates of persistent pain and post-traumatic arthritis. We report an innovative surgical technique using a plate fixation augmented with minimally invasive tension slide coracoclavicular fixation using a cortical tenodesis button (8...
May 24, 2017: European Journal of Orthopaedic Surgery & Traumatology: Orthopédie Traumatologie
https://www.readbyqxmd.com/read/28540284/prototyping-and-simulation-of-robot-group-intelligence-using-kohonen-networks
#15
Zhijun Wang, Reza Mirdamadi, Qing Wang
Intelligent agents such as robots can form ad hoc networks and replace human being in many dangerous scenarios such as a complicated disaster relief site. This project prototypes and builds a computer simulator to simulate robot kinetics, unsupervised learning using Kohonen networks, as well as group intelligence when an ad hoc network is formed. Each robot is modeled using an object with a simple set of attributes and methods that define its internal states and possible actions it may take under certain circumstances...
September 2016: IOSR J Comput Eng
https://www.readbyqxmd.com/read/28539121/network-mirroring-for-drug-repositioning
#16
Sunghong Park, Dong-Gi Lee, Hyunjung Shin
BACKGROUND: Although drug discoveries can provide meaningful insights and significant enhancements in pharmaceutical field, the longevity and cost that it takes can be extensive where the success rate is low. In order to circumvent the problem, there has been increased interest in 'Drug Repositioning' where one searches for already approved drugs that have high potential of efficacy when applied to other diseases. To increase the success rate for drug repositioning, one considers stepwise screening and experiments based on biological reactions...
May 18, 2017: BMC Medical Informatics and Decision Making
https://www.readbyqxmd.com/read/28536821/impaired-motor-coordination-and-learning-in-mice-lacking-anoctamin-2-calcium-gated-chloride-channels
#17
Franziska Neureither, Katharina Ziegler, Claudia Pitzer, Stephan Frings, Frank Möhrlen
Neurons communicate through excitatory and inhibitory synapses. Both lines of communication are adjustable and allow the fine tuning of signal exchange required for learning processes in neural networks. Several distinct modes of plasticity modulate glutamatergic and GABAergic synapses in Purkinje cells of the cerebellar cortex to promote motor control and learning. In the present paper, we present evidence for a role of short-term ionic plasticity in the cerebellar circuit activity. This type of plasticity results from altered chloride driving forces at the synapses that molecular layer interneurons form on Purkinje cell dendrites...
May 23, 2017: Cerebellum
https://www.readbyqxmd.com/read/28536087/workflow-sensitivity-of-post-processing-methods-in-renal-dce-mri
#18
Erik Hanson, Eli Eikefjord, Jarle Rørvik, Erling Andersen, Arvid Lundervold, Erlend Hodneland
OBJECTIVE: Estimation of renal filtration using dynamic contrast-enhanced imaging (DCE-MRI) requires a series of analysis steps. The possible number of distinct post-processing chains is large and grows rapidly with increasing number of processing steps or options. In this study we introduce a framework for systematic evaluation of the post-processing chains. The framework is later used to highlight the workflow processing chain sensitivity towards accuracy in estimation of glomerular filtration rate (GFR)...
May 20, 2017: Magnetic Resonance Imaging
https://www.readbyqxmd.com/read/28534789/boundary-eliminated-pseudoinverse-linear-discriminant-for-imbalanced-problems
#19
Yujin Zhu, Zhe Wang, Hongyuan Zha, Daqi Gao
Existing learning models for classification of imbalanced data sets can be grouped as either boundary-based or nonboundary-based depending on whether a decision hyperplane is used in the learning process. The focus of this paper is a new approach that leverages the advantage of both approaches. Specifically, our new model partitions the input space into three parts by creating two additional boundaries in the training process, and then makes the final decision based on a heuristic measurement between the test sample and a subset of selected training samples...
May 16, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28534788/rankmap-a-framework-for-distributed-learning-from-dense-data-sets
#20
Azalia Mirhoseini, Eva L Dyer, Ebrahim M Songhori, Richard Baraniuk, Farinaz Koushanfar
This paper introduces RankMap, a platform-aware end-to-end framework for efficient execution of a broad class of iterative learning algorithms for massive and dense data sets. Our framework exploits data structure to scalably factorize it into an ensemble of lower rank subspaces. The factorization creates sparse low-dimensional representations of the data, a property which is leveraged to devise effective mapping and scheduling of iterative learning algorithms on the distributed computing machines. We provide two APIs, one matrix-based and one graph-based, which facilitate automated adoption of the framework for performing several contemporary learning applications...
May 17, 2017: IEEE Transactions on Neural Networks and Learning Systems
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