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https://www.readbyqxmd.com/read/28075713/an-activist-approach-to-sport-meets-youth-from-socially-vulnerable-backgrounds-possible-learning-aspirations
#1
Carla Luguetti, Kimberly L Oliver, Luiz Eduardo Pinto Basto Tourinho Dantas, David Kirk
PURPOSE: This study was a 2-phase activist research project aimed at co-creating a prototype pedagogical model for working with youth from socially vulnerable backgrounds in a sport context. This article addresses the learning aspirations (learning outcomes) that emerged when we created spaces for youth to develop strategies to manage the risks they face in their community. METHOD: This study took place in a socially and economically disadvantaged neighborhood in a Brazilian city where we worked with a group of 17 boys aged 13 to 15 years old, 4 coaches, a pedagogic coordinator, and a social worker...
January 11, 2017: Research Quarterly for Exercise and Sport
https://www.readbyqxmd.com/read/28067221/quantum-chemical-insights-from-deep-tensor-neural-networks
#2
Kristof T Schütt, Farhad Arbabzadah, Stefan Chmiela, Klaus R Müller, Alexandre Tkatchenko
Learning from data has led to paradigm shifts in a multitude of disciplines, including web, text and image search, speech recognition, as well as bioinformatics. Can machine learning enable similar breakthroughs in understanding quantum many-body systems? Here we develop an efficient deep learning approach that enables spatially and chemically resolved insights into quantum-mechanical observables of molecular systems. We unify concepts from many-body Hamiltonians with purpose-designed deep tensor neural networks, which leads to size-extensive and uniformly accurate (1 kcal mol(-1)) predictions in compositional and configurational chemical space for molecules of intermediate size...
January 9, 2017: Nature Communications
https://www.readbyqxmd.com/read/28067192/effect-of-retrieval-practice-on-short-term-and-long-term-retention-in-hiv-individuals
#3
Gunes Avci, Steven P Woods, Marizela Verduzco, David P Sheppard, James F Sumowski, Nancy D Chiaravalloti, John DeLuca
OBJECTIVES: Episodic memory deficits are both common and impactful among persons infected with HIV; however, we know little about how to improve such deficits in the laboratory or in real life. Retrieval practice, by which retrieval of newly learned material improves subsequent recall more than simple restudy, is a robust memory boosting strategy that is effective in both healthy and clinical populations. In this study, we investigated the benefits of retrieval practice in 52 people living with HIV and 21 seronegatives...
January 9, 2017: Journal of the International Neuropsychological Society: JINS
https://www.readbyqxmd.com/read/28066843/hyperbolic-space-sparse-coding-with-its-application-on-prediction-of-alzheimer-s-disease-in-mild-cognitive-impairment
#4
Jie Zhang, Jie Shi, Cynthia Stonnington, Qingyang Li, Boris A Gutman, Kewei Chen, Eric M Reiman, Richard J Caselli, Paul M Thompson, Jieping Ye, Yalin Wang
Mild Cognitive Impairment (MCI) is a transitional stage between normal age-related cognitive decline and Alzheimer's disease (AD). Here we introduce a hyperbolic space sparse coding method to predict impending decline of MCI patients to dementia using surface measures of ventricular enlargement. First, we compute diffeomorphic mappings between ventricular surfaces using a canonical hyperbolic parameter space with consistent boundary conditions and surface tensor-based morphometry is computed to measure local surface deformations...
October 2016: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
https://www.readbyqxmd.com/read/28065215/a-comparative-and-evolutionary-analysis-of-the-cultural-cognition-of-humans-and-other-apes
#5
Andrew Whiten
The comparative and evolutionary analysis of social learning and all manner of cultural processes has become a flourishing field. Applying the 'comparative method' to such phenomena allows us to exploit the good fortunate we have in being able to study them in satisfying detail in our living primate relatives, using the results to reconstruct the cultural cognition of the ancestral forms we share with these species. Here I offer an overview of principal discoveries in recent years, organized through a developing scheme that targets three main dimensions of culture: the patterning of culturally transmitted traditions in time and space; the underlying social learning processes; and the particular behavioral and psychological contents of cultures...
January 9, 2017: Spanish Journal of Psychology
https://www.readbyqxmd.com/read/28062825/global-family-medicine-a-universal-mnemonic
#6
William B Ventres
In this essay, I borrow the idea of universal precautions from infection control and suggest that family physicians use a set of considerations, based on the mnemonic UNIVERSAL, to nurture cultural humility, enter a metaphoric "space-in-between" in cross-cultural encounters, and foster global fluency. These UNIVERSAL considerations I base on my experiences in global family medicine, attending to economically poor and socially marginalized patients in both international and domestic settings. They are informed by readings in transcultural psychiatry, medical anthropology, development studies, and primary care...
January 2017: Journal of the American Board of Family Medicine: JABFM
https://www.readbyqxmd.com/read/28060715/probabilistic-low-rank-multitask-learning
#7
Yu Kong, Ming Shao, Kang Li, Yun Fu
In this paper, we consider the problem of learning multiple related tasks simultaneously with the goal of improving the generalization performance of individual tasks. The key challenge is to effectively exploit the shared information across multiple tasks as well as preserve the discriminative information for each individual task. To address this, we propose a novel probabilistic model for multitask learning (MTL) that can automatically balance between low-rank and sparsity constraints. The former assumes a low-rank structure of the underlying predictive hypothesis space to explicitly capture the relationship of different tasks and the latter learns the incoherent sparse patterns private to each task...
January 4, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28060305/dissection-and-observation-of-honey-bee-dorsal-vessel-for-studies-of-cardiac-function
#8
Scott T O'Neal, Troy D Anderson
The European honey bee, Apis mellifera L., is a valuable agricultural and commercial resource noted for producing honey and providing crop pollination services, as well as an important model social insect used to study memory and learning, aging, and more. Here we describe a detailed protocol for the dissection of the dorsal abdominal wall of a bee in order to visualize its dorsal vessel, which serves the role of the heart in the insect. A successful dissection will expose a functional heart that, under the proper conditions, can maintain a steady heartbeat for an extended period of time...
December 12, 2016: Journal of Visualized Experiments: JoVE
https://www.readbyqxmd.com/read/28055940/deep-nonlinear-metric-learning-for-3-d-shape-retrieval
#9
Jin Xie, Guoxian Dai, Fan Zhu, Ling Shao, Yi Fang
Effective 3-D shape retrieval is an important problem in 3-D shape analysis. Recently, feature learning-based shape retrieval methods have been widely studied, where the distance metrics between 3-D shape descriptors are usually hand-crafted. In this paper, motivated by the fact that deep neural network has the good ability to model nonlinearity, we propose to learn an effective nonlinear distance metric between 3-D shape descriptors for retrieval. First, the locality-constrained linear coding method is employed to encode each vertex on the shape and the encoding coefficient histogram is formed as the global 3-D shape descriptor to represent the shape...
December 28, 2016: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28055848/write-a-classifier-predicting-visual-classifiers-from-unstructured-text
#10
Mohamed Elhoseiny, Ahmed Elgammal, Babak Saleh
People typically learn through exposure to visual concepts associated with linguistic descriptions. For instance, teaching visual object categories to children is often accompanied by descriptions in text or speech. In a machine learning context, these observations motivates us to ask whether this learning process could be computationally modeled to learn visual classifiers. More specifically, the main question of this work is how to utilize purely textual description of visual classes with no training images, to learn explicit visual classifiers for them...
December 29, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28048898/mo-fg-brc-03-design-and-construction-of-a-dielectiric-wall-accelerator
#11
D Westerly
Experimental research in medical physics has expanded the limits of our knowledge and provided novel imaging and therapy technologies for patients around the world. However, experimental efforts are challenging due to constraints in funding, space, time and other forms of institutional support. In this joint ESTRO-AAPM symposium, four exciting experimental projects from four different countries are highlighted. Each project is focused on a different aspect of radiation therapy. From the USA, we will hear about a new linear accelerator concept for more compact and efficient therapy devices...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28048357/su-f-r-05-multidimensional-imaging-radiomics-geodesics-a-novel-manifold-learning-based-automatic-feature-extraction-method-for-diagnostic-prediction-in-multiparametric-imaging
#12
V Parekh, M A Jacobs
PURPOSE: Multiparametric radiological imaging is used for diagnosis in patients. Potentially extracting useful features specific to a patient's pathology would be crucial step towards personalized medicine and assessing treatment options. In order to automatically extract features directly from multiparametric radiological imaging datasets, we developed an advanced unsupervised machine learning algorithm called the multidimensional imaging radiomics-geodesics(MIRaGe). METHODS: Seventy-six breast tumor patients underwent 3T MRI breast imaging were used for this study...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28048318/we-h-brc-06-a-unified-machine-learning-based-probabilistic-model-for-automated-anomaly-detection-in-the-treatment-plan-data
#13
X Chang, A Kalet, S Liu, D Yang
PURPOSE: The purpose of this work was to investigate the ability of a machine-learning based probabilistic approach to detect radiotherapy treatment plan anomalies given initial disease classes information. METHODS: In total we obtained 1112 unique treatment plans with five plan parameters and disease information from a Mosaiq treatment management system database for use in the study. The plan parameters include prescription dose, fractions, fields, modality and techniques...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28048246/mo-fg-brc-04-ionacoustic-imaging-for-particle-range-verification
#14
K Parodi
Experimental research in medical physics has expanded the limits of our knowledge and provided novel imaging and therapy technologies for patients around the world. However, experimental efforts are challenging due to constraints in funding, space, time and other forms of institutional support. In this joint ESTRO-AAPM symposium, four exciting experimental projects from four different countries are highlighted. Each project is focused on a different aspect of radiation therapy. From the USA, we will hear about a new linear accelerator concept for more compact and efficient therapy devices...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28047753/su-d-204-01-a-methodology-based-on-machine-learning-and-quantum-clustering-to-predict-lung-sbrt-dosimetric-endpoints-from-patient-specific-anatomic-features
#15
K Lafata, L Ren, Q Wu, C Kelsey, J Hong, J Cai, F Yin
PURPOSE: To develop a data-mining methodology based on quantum clustering and machine learning to predict expected dosimetric endpoints for lung SBRT applications based on patient-specific anatomic features. METHODS: Ninety-three patients who received lung SBRT at our clinic from 2011-2013 were retrospectively identified. Planning information was acquired for each patient, from which various features were extracted using in-house semi-automatic software. Anatomic features included tumor-to-OAR distances, tumor location, total-lung-volume, GTV and ITV...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28047462/mo-fg-brc-00-joint-aapm-estro-symposium-advances-in-experimental-medical-physics
#16
Ross Berbeco, Dan Ionascu
Experimental research in medical physics has expanded the limits of our knowledge and provided novel imaging and therapy technologies for patients around the world. However, experimental efforts are challenging due to constraints in funding, space, time and other forms of institutional support. In this joint ESTRO-AAPM symposium, four exciting experimental projects from four different countries are highlighted. Each project is focused on a different aspect of radiation therapy. From the USA, we will hear about a new linear accelerator concept for more compact and efficient therapy devices...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28047172/su-c-204-02-behavioral-and-pathologic-differences-in-mice-exposed-to-proton-minibeam-arrays-versus-proton-broad-beams
#17
J Eley, T Wolfe, E Vichaya, C Quini, A Chadha, C Zhang, J Davis, N Sahoo, F Dilmanian, S Krishnan
PURPOSE: Minibeam therapy using protons or light-ions offers a theoretical reduction of biologic damage to tissues upstream of a tumor compared to broad-beam therapy while providing equal tumor control. The purpose of this study was to investigate behavioral and pathologic differences in mice after exposure of healthy brain to proton minibeam arrays versus proton broad beams. METHODS: Twenty-four C57BL/6J juvenile mice were divided into 5 study arms: sham irradiation (NoRT), broad-beam 10 Gy (BB10), minibeam 10Gy (MB10), broad-beam 30 Gy (BB30), and minibeam 30 Gy (MB30), approximate integral entrance doses...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28046835/mo-fg-brc-02-low-z-switching-linear-accelerator-targets-new-options-for-image-guidance-and-dose-enhancement-in-radiotherapy
#18
J Robar
Experimental research in medical physics has expanded the limits of our knowledge and provided novel imaging and therapy technologies for patients around the world. However, experimental efforts are challenging due to constraints in funding, space, time and other forms of institutional support. In this joint ESTRO-AAPM symposium, four exciting experimental projects from four different countries are highlighted. Each project is focused on a different aspect of radiation therapy. From the USA, we will hear about a new linear accelerator concept for more compact and efficient therapy devices...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28046808/mo-fg-brc-01-mr-guided-radiation-therapy-with-gadolinium-nanoparticles-from-chalkboard-to-first-clinical-trials
#19
L Sancey
Experimental research in medical physics has expanded the limits of our knowledge and provided novel imaging and therapy technologies for patients around the world. However, experimental efforts are challenging due to constraints in funding, space, time and other forms of institutional support. In this joint ESTRO-AAPM symposium, four exciting experimental projects from four different countries are highlighted. Each project is focused on a different aspect of radiation therapy. From the USA, we will hear about a new linear accelerator concept for more compact and efficient therapy devices...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28046401/th-cd-207a-07-prediction-of-high-dimensional-state-subject-to-respiratory-motion-a-manifold-learning-approach
#20
W Liu, A Sawant, D Ruan
PURPOSE: The development of high dimensional imaging systems (e.g. volumetric MRI, CBCT, photogrammetry systems) in image-guided radiotherapy provides important pathways to the ultimate goal of real-time volumetric/surface motion monitoring. This study aims to develop a prediction method for the high dimensional state subject to respiratory motion. Compared to conventional linear dimension reduction based approaches, our method utilizes manifold learning to construct a descriptive feature submanifold, where more efficient and accurate prediction can be performed...
June 2016: Medical Physics
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