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https://www.readbyqxmd.com/read/28437797/central-and-peripheral-vision-for-scene-recognition-a-neurocomputational-modeling-exploration
#1
Panqu Wang, Garrison W Cottrell
What are the roles of central and peripheral vision in human scene recognition? Larson and Loschky (2009) showed that peripheral vision contributes more than central vision in obtaining maximum scene recognition accuracy. However, central vision is more efficient for scene recognition than peripheral, based on the amount of visual area needed for accurate recognition. In this study, we model and explain the results of Larson and Loschky (2009) using a neurocomputational modeling approach. We show that the advantage of peripheral vision in scene recognition, as well as the efficiency advantage for central vision, can be replicated using state-of-the-art deep neural network models...
April 1, 2017: Journal of Vision
https://www.readbyqxmd.com/read/28437691/midwifery-participatory-curriculum-development-transformation-through-active-partnership
#2
Mary Sidebotham, Caroline Walters, Janine Chipperfield, Jenny Gamble
Evolving knowledge and professional practice combined with advances in pedagogy and learning technology create challenges for accredited professional programs. Internationally a sparsity of literature exists around curriculum development for professional programs responsive to regulatory and societal drivers. This paper evaluates a participatory curriculum development framework, adapted from the community development sector, to determine its applicability to promote engagement and ownership during the development of a Bachelor of Midwifery curriculum at an Australian University...
April 15, 2017: Nurse Education in Practice
https://www.readbyqxmd.com/read/28437615/experimental-demonstration-of-feature-extraction-and-dimensionality-reduction-using-memristor-networks
#3
Shinhyun Choi, Jong Hoon Shin, Jihang Lee, Patrick Sheridan, Wei D Lu
Memristors have been considered as a leading candidate for a number of critical applications ranging from non-volatile memory to non-Von Neumann computing systems. Feature extraction, which aims to transform input data from a high dimensional space to a space with fewer dimensions, is an important technique widely used in machine learning and pattern recognition applications. Here, we experimentally demonstrate that memristor arrays can be used to perform principal component analysis (PCA), one of the most commonly-used feature extraction techniques, through online, unsupervised learning...
April 24, 2017: Nano Letters
https://www.readbyqxmd.com/read/28436903/robust-multiview-data-analysis-through-collective-low-rank-subspace
#4
Zhengming Ding, Yun Fu
Multiview data are of great abundance in real-world applications, since various viewpoints and multiple sensors desire to represent the data in a better way. Conventional multiview learning methods aimed to learn multiple view-specific transformations meanwhile assumed the view knowledge of training, and test data were available in advance. However, they would fail when we do not have any prior knowledge for the probe data's view information, since the correct view-specific projections cannot be utilized to extract effective feature representations...
April 17, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28436901/on-better-exploring-and-exploiting-task-relationships-in-multitask-learning-joint-model-and-feature-learning
#5
Ya Li, Xinmei Tian, Tongliang Liu, Dacheng Tao
Multitask learning (MTL) aims to learn multiple tasks simultaneously through the interdependence between different tasks. The way to measure the relatedness between tasks is always a popular issue. There are mainly two ways to measure relatedness between tasks: common parameters sharing and common features sharing across different tasks. However, these two types of relatedness are mainly learned independently, leading to a loss of information. In this paper, we propose a new strategy to measure the relatedness that jointly learns shared parameters and shared feature representations...
April 17, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28436898/extended-polynomial-growth-transforms-for-design-and-training-of-generalized-support-vector-machines
#6
Ahana Gangopadhyay, Oindrila Chatterjee, Shantanu Chakrabartty
Growth transformations constitute a class of fixed-point multiplicative update algorithms that were originally proposed for optimizing polynomial and rational functions over a domain of probability measures. In this paper, we extend this framework to the domain of bounded real variables which can be applied towards optimizing the dual cost function of a generic support vector machine (SVM). The approach can, therefore, not only be used to train traditional soft-margin binary SVMs, one-class SVMs, and probabilistic SVMs but can also be used to design novel variants of SVMs with different types of convex and quasi-convex loss functions...
April 17, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28436897/tensor-factorized-neural-networks
#7
Jen-Tzung Chien, Yi-Ting Bao
The growing interests in multiway data analysis and deep learning have drawn tensor factorization (TF) and neural network (NN) as the crucial topics. Conventionally, the NN model is estimated from a set of one-way observations. Such a vectorized NN is not generalized for learning the representation from multiway observations. The classification performance using vectorized NN is constrained, because the temporal or spatial information in neighboring ways is disregarded. More parameters are required to learn the complicated data structure...
April 17, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28436875/zero-shot-learning-with-transferred-samples
#8
Yuchen Guo, Guiguang Ding, Jungong Han, Yue Gao
By transferring knowledge from the abundant labeled samples of known source classes, zero-shot learning (ZSL) makes it possible to train recognition models for novel target classes that have no labeled samples. Conventional ZSL approaches usually adopt a two-step recognition strategy, in which the test sample is projected into an intermediary space in the first step, and then the recognition is carried out by considering the similarity between the sample and target classes in the intermediary space. Due to this redundant intermediate transformation, information loss is unavoidable, thus degrading the performance of overall system...
April 24, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28436845/drawing-and-recognizing-chinese-characters-with-recurrent-neural-network
#9
Xu-Yao Zhang, Fei Yin, Yan-Ming Zhang, Cheng-Lin Liu, Yoshua Bengio
Recent deep learning based approaches have achieved great success on handwriting recognition. Chinese characters are among the most widely adopted writing systems in the world. Previous research has mainly focused on recognizing handwritten Chinese characters. However, recognition is only one aspect for understanding a language, another challenging and interesting task is to teach a machine to automatically write (pictographic) Chinese characters. In this paper, we propose a framework by using the recurrent neural network (RNN) as both a discriminative model for recognizing Chinese characters and a generative model for drawing (generating) Chinese characters...
April 18, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28435440/core-column-prediction-for-protein-multiple-sequence-alignments
#10
Dan DeBlasio, John Kececioglu
BACKGROUND: In a computed protein multiple sequence alignment, the coreness of a column is the fraction of its substitutions that are in so-called core columns of the gold-standard reference alignment of its proteins. In benchmark suites of protein reference alignments, the core columns of the reference alignment are those that can be confidently labeled as correct, usually due to all residues in the column being sufficiently close in the spatial superposition of the known three-dimensional structures of the proteins...
2017: Algorithms for Molecular Biology: AMB
https://www.readbyqxmd.com/read/28433665/advancing-the-science-of-myocardial-recovery-with-mechanical-circulatory-support-a-working-group-of-the-national-heart-lung-and-blood-institute
#11
Stavros G Drakos, Francis D Pagani, Martha S Lundberg, J Timothy Baldwin
The medical burden of heart failure (HF) has spurred interest in clinicians and scientists to develop therapies to restore the function of a failing heart. To advance this agenda, the National Heart Lung Blood Institute (NHLBI) convened a Working Group of experts on June 2-3, 2016 in Bethesda Maryland to develop recommendations for the NHLBI aimed at advancing the science of cardiac recovery in the setting of mechanical circulatory support (MCS). MSC devices effectively reduce volume and pressure overload that drives the cycle of progressive myocardial dysfunction, thereby triggering structural and functional reverse remodeling...
April 19, 2017: Journal of Cardiac Failure
https://www.readbyqxmd.com/read/28430568/reflection-based-learning-for-professional-ethical-formation
#12
William T Branch, Maura George
One way practitioners learn ethics is by reflecting on experience. They may reflect in the moment (reflection-in-action) or afterwards (reflection-on-action). We illustrate how a teaching clinician may transform relationships with patients and teach person-centered care through reflective learning. We discuss reflective learning pedagogies and present two case examples of our preferred method, guided group reflection using narratives. This method fosters moral development alongside professional identity formation in students and advanced learners...
April 1, 2017: AMA Journal of Ethics
https://www.readbyqxmd.com/read/28426520/nursing-practice-research-and-education-in-the-west-the-best-is-yet-to-come
#13
Heather M Young, Susan Bakewell-Sachs, Linda Sarna
PURPOSE: This paper celebrates the 60th anniversary of the Western Institute of Nursing, the nursing organization representing 13 states in the Western United States, and envisions a preferred future for nursing practice, research, and education. BACKGROUND: Three landmark calls to action contribute to transforming nursing and healthcare: the Patient Protection and Affordable Care Act of 2010; the Institute of Medicine report Future of Nursing: Leading Change, Advancing Health; and the report Advancing Healthcare Transformation: A New Era for Academic Nursing...
April 20, 2017: Nursing Research
https://www.readbyqxmd.com/read/28423773/introducing-a-method-for-transformation-of-paper-based-research-data-into-concept-based-representation-with-openehr
#14
Birgit Saalfeld, Erik Tute, Klaus-Hendrik Wolf, Michael Marschollek
Combining research data and clinical routine data is a chance for medical research. We present our method for the transformation of paper-based research data into a concept-based representation. With this representation the study data from research projects can be combined with data from clinical tools with less integration effort. We applied and verified our method using data from a current research study. In this paper we also show our main challenges and lessons learned. Clinical assessment data and study diaries from a long term study (n=24, 3 months observation time each, 17 different clinical assessments) stored on paper were used as the data set...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28422976/reactivation-or-transformation-motor-memory-consolidation-associated-with-cerebral-activation-time-locked-to-sleep-spindles
#15
Stuart Fogel, Genevieve Albouy, Bradley R King, Ovidiu Lungu, Catherine Vien, Arnaud Bore, Basile Pinsard, Habib Benali, Julie Carrier, Julien Doyon
Motor memory consolidation is thought to depend on sleep-dependent reactivation of brain areas recruited during learning. However, up to this point, there has been no direct evidence to support this assertion in humans, and the physiological processes supporting such reactivation are unknown. Here, simultaneous electroencephalographic and functional magnetic resonance imaging (EEG-fMRI) recordings were conducted during post-learning sleep to directly investigate the spindle-related reactivation of a memory trace formed during motor sequence learning (MSL), and its relationship to overnight enhancement in performance (reflecting consolidation)...
2017: PloS One
https://www.readbyqxmd.com/read/28422816/why-not-wait-eight-institutions-share-their-experiences-moving-united-states-medical-licensing-examination-step-1-after-core-clinical-clerkships
#16
Michelle Daniel, Amy Fleming, Colleen O'Conner Grochowski, Vicky Harnik, Sibel Klimstra, Gail Morrison, Arnyce Pock, Michael L Schwartz, Sally Santen
The majority of medical students complete the United States Medical Licensing Examination Step 1 after their foundational sciences; however, there are compelling reasons to examine this practice. This article provides the perspectives of eight MD-granting medical schools that have moved Step 1 after the core clerkships, describing their rationale, logistics of the change, outcomes, and lessons learned. The primary reasons these institutions cite for moving Step 1 after clerkships are to foster more enduring and integrated basic science learning connected to clinical care and to better prepare students for the increasingly clinical focus of Step 1...
April 18, 2017: Academic Medicine: Journal of the Association of American Medical Colleges
https://www.readbyqxmd.com/read/28419657/a-new-approach-to-clinical-research-integrating-clinical-care-quality-reporting-and-research-using-a-wound-care-network-based-learning-healthcare-system
#17
Thomas E Serena, Caroline E Fife, Kristen A Eckert, Raphael A Yaakov, Marissa J Carter
The disparity between ideal evidence from randomized controlled trials and real-world evidence in medical research has prompted the United States Food and Drug Administration to consider the use of real-world data to better understand safety and effectiveness of new devices for a broader patient population and to prioritize real-world data in regulatory decision making. As the healthcare system transitions from volume- to value-based care, there is a growing need to harness the power of real-world data to change the paradigm for wound care clinical research and enable more generalizable clinical trials...
April 17, 2017: Wound Repair and Regeneration
https://www.readbyqxmd.com/read/28418117/articulating-the-ideal-50-years-of-interprofessional-collaboration-in-medical-education
#18
Elise Paradis, Mandy Pipher, Carrie Cartmill, J Cristian Rangel, Cynthia R Whitehead
CONTEXT: Health care delivery and the education of clinicians have changed immensely since the creation of the journal Medical Education. In this project, we seek to answer the following three questions: How has the concept of collaboration changed over the past 50 years in Medical Education? Have the participants involved in collaboration shifted over time? Has the idea of collaboration itself been transformed over the past 50 years? METHODS: Starting from a constructionist view of scientific discourse, we used directed content analysis to sample, code and analyse 144 collaboration-related articles over the 50-year life span of Medical Education...
April 18, 2017: Medical Education
https://www.readbyqxmd.com/read/28416450/denoise-diffusion-weighted-images-using-higher-order-singular-value-decomposition
#19
Xinyuan Zhang, Jie Peng, Man Xu, Wei Yang, Zhe Zhang, Hua Guo, Wufan Chen, Qianjin Feng, Ed X Wu, Yanqiu Feng
Noise usually affects the reliability of quantitative analysis in diffusion-weighted (DW) magnetic resonance imaging (MRI), especially at high b-values and/or high spatial resolution. Higher-order singular value decomposition (HOSVD) has recently emerged as a simple, effective, and adaptive transform to exploit sparseness within multidimensional data. In particular, the patch-based HOSVD denoising has demonstrated superb performance when applied to T1-, T2-, and proton density-weighted MRI data. In this study, we aim to investigate the feasibility of denoising DW data using the HOSVD transform...
April 14, 2017: NeuroImage
https://www.readbyqxmd.com/read/28414908/an-experimental-computational-study-of-carbon-nanotubes-effects-on-mitochondrial-respiration-in-silico-nano-qspr-machine-learning-models-based-on-new-raman-spectra-transform-with-markov-shannon-entropy-invariants
#20
Michael González-Durruthy, Luciane Carla Alberici, Zeki Naal, David T Atique-Sawazaki, Carlos Curti, José Manuel Vázquez-Naya, Humbert Gonzalez-Diaz, Cristian Robert Munteanu
The study of selective toxicity of carbon nanotubes (CNT) on mitochondria (CNT-mitotoxicity) is of major interest for future biomedical applications. In the current work, the mitochondrial oxygen consumption (E3) is measured under three experimental conditions by exposure to pristine and oxidized CNTs (hydroxylated and carboxylated). Respiratory functional assays showed that the information of the CNT-Raman spectroscopy could be useful to predict structural parameters of mitotoxicity induced by CNTs. The in vitro functional assays show that the mitochondrial oxidative phosphorylation by ATP-synthase (or state V3 of respiration) was not perturbed in isolated rat-liver mitochondria...
April 17, 2017: Journal of Chemical Information and Modeling
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