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https://www.readbyqxmd.com/read/28651096/predicting-actions-from-subtle-preparatory-movements
#1
Maryam Vaziri-Pashkam, Sarah Cormiea, Ken Nakayama
To study how people anticipate others' actions, we designed a competitive reaching task. Subjects faced each other separated by a Plexiglas screen and their finger movements in 3D space were recorded with sensors. The first subject (Attacker) was instructed to touch one of two horizontally arranged targets on the screen. The other subject (Blocker) touched the same target as quickly as possible. Average finger reaction times (fRTs) were fast, much faster than reactions to a dot moving on the screen in the same manner as the Attacker's finger...
June 23, 2017: Cognition
https://www.readbyqxmd.com/read/28650835/a-new-representation-in-pso-for-discretization-based-feature-selection
#2
Binh Tran, Bing Xue, Mengjie Zhang
In machine learning, discretization and feature selection (FS) are important techniques for preprocessing data to improve the performance of an algorithm on high-dimensional data. Since many FS methods require discrete data, a common practice is to apply discretization before FS. In addition, for the sake of efficiency, features are usually discretized individually (or univariate). This scheme works based on the assumption that each feature independently influences the task, which may not hold in cases where feature interactions exist...
June 23, 2017: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28650183/spatial-transposition-tasks-in-indian-sloth-bears-melursus-ursinus-and-bornean-sun-bears-helarctos-malayanus-euryspilus
#3
Daniela Hartmann, Marina Davila-Ross, Siew Te Wong, Josep Call, Marina Scheumann
Spatial transposition tasks assess individuals' ability to represent nonvisible spatial object displacements. Several nonhuman mammal species have been tested on this task including primates, cats, and dogs, but to date, great apes seem the only taxon that has repeatedly and consistently solved spatial transposition tasks. The authors investigated the ability of captive sloth and sun bears to solve spatial transposition tasks. Both species belong to the same taxonomic group as cats and dogs, but unlike them and similar to apes, they have an omnivorous diet that requires them to keep track of fruit sources in space and time...
June 26, 2017: Journal of Comparative Psychology
https://www.readbyqxmd.com/read/28649740/human-vs-robots-in-the-discovery-and-crystallization-of-gigantic-polyoxometalates
#4
Lee Cronin, Vasilios Duros, Jonathan Grizou, Weimin Xuan, Zied Hosni, De-Liang Long, Haralampos Miras
The discovery of new gigantic molecules formed by self-assembly using single crystal X-ray crystallography is a challenging endeavor as it combines two contingent events; first is the formation of a new molecule, and second its crystallization. Herein, we constructed a workflow that can be followed manually or by a robot to probe the envelope of both events and employed it in the chemical space of a new polyoxometalate cluster, namely Na6[Mo120Ce6O366H12(H2O)78]·200H2O (1) which has a trigonal-ring type architecture (yield 4...
June 25, 2017: Angewandte Chemie
https://www.readbyqxmd.com/read/28649209/map-learning-with-a-3d-printed-interactive-small-scale-model-improvement-of-space-and-text-memorization-in-visually-impaired-students
#5
Stéphanie Giraud, Anke M Brock, Marc J-M Macé, Christophe Jouffrais
Special education teachers for visually impaired students rely on tools such as raised-line maps (RLMs) to teach spatial knowledge. These tools do not fully and adequately meet the needs of the teachers because they are long to produce, expensive, and not versatile enough to provide rapid updating of the content. For instance, the same RLM can barely be used during different lessons. In addition, those maps do not provide any interactivity, which reduces students' autonomy. With the emergence of 3D printing and low-cost microcontrollers, it is now easy to design affordable interactive small-scale models (SSMs) which are adapted to the needs of special education teachers...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28648726/taking-the-measure-of-microed
#6
REVIEW
Jose A Rodriguez, David S Eisenberg, Tamir Gonen
It is now possible to routinely determine atomic resolution structures by electron cryo-microscopy (cryoEM), facilitated in part by the method known as micro electron-diffraction (MicroED). Since its initial demonstration in 2013, MicroED has helped determine a variety of protein structures ranging in molecular weight from a few hundred Daltons to several hundred thousand Daltons. Some of these structures were novel while others were previously known. The resolutions of structures obtained thus far by MicroED range from 3...
June 22, 2017: Current Opinion in Structural Biology
https://www.readbyqxmd.com/read/28648605/a-semi-supervised-approach-using-label-propagation-to-support-citation-screening
#7
Georgios Kontonatsios, Austin J Brockmeier, Piotr Przybyła, John McNaught, Tingting Mu, John Y Goulermas, Sophia Ananiadou
Citation screening, an integral process within systematic reviews that identifies citations relevant to the underlying research question, is a time-consuming and resource-intensive task. During the screening task, analysts manually assign a label to each citation, to designate whether a citation is eligible for inclusion in the review. Recently, several studies have explored the use of active learning in text classification to reduce the human workload involved in the screening task. However, existing approaches require a significant amount of manually labelled citations for the text classification to achieve a robust performance...
June 22, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28648549/hippocampal-spatial-mechanisms-relate-to-the-development-of-arithmetic-symbol-processing-in-children
#8
Romain Mathieu, Justine Epinat-Duclos, Jessica Léone, Michel Fayol, Catherine Thevenot, Jérôme Prado
Understanding the meaning of abstract mathematical symbols is a cornerstone of arithmetic learning in children. Studies have long focused on the role of spatial intuitions in the processing of numerals. However, it has been argued that such intuitions may also underlie symbols that convey fundamental arithmetic concepts, such as arithmetic operators. In the present cross-sectional study, we used fMRI to investigate how and when associations between arithmetic operators and brain regions processing spatial information emerge in children from 3(rd) to 10(th) grade...
June 13, 2017: Developmental Cognitive Neuroscience
https://www.readbyqxmd.com/read/28646763/deep-neural-mapping-support-vector-machines
#9
Yujian Li, Ting Zhang
The choice of kernel has an important effect on the performance of a support vector machine (SVM). The effect could be reduced by NEUROSVM, an architecture using multilayer perceptron for feature extraction and SVM for classification. In binary classification, a general linear kernel NEUROSVM can be theoretically simplified as an input layer, many hidden layers, and an SVM output layer. As a feature extractor, the sub-network composed of the input and hidden layers is first trained together with a virtual ordinary output layer by backpropagation, then with the output of its last hidden layer taken as input of the SVM classifier for further training separately...
June 21, 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28646680/the-experiences-of-supporting-learning-in-pairs-of-nursing-students-in-clinical-practice
#10
Hanna Holst, Lise-Lotte Ozolins, David Brunt, Ulrica Hörberg
The purpose of this study is to describe how supervisors experience supporting nursing students' learning in pairs on a Developing and Learning Care Unit in Sweden. The present study has been carried out with a Reflective Lifeworld Research (RLR) approach founded on phenomenology. A total of 25 lifeworld interviews were conducted with supervisors who had supervised pairs of students. The findings reveal how supervisors support students' learning in pairs through a reflective approach creating learning space in the encounter with patients, students and supervisors...
June 9, 2017: Nurse Education in Practice
https://www.readbyqxmd.com/read/28646674/a-multimodal-spatiotemporal-cardiac-motion-atlas-from-mr-and-ultrasound-data
#11
Esther Puyol-Antón, Matthew Sinclair, Bernhard Gerber, Mihaela Silvia Amzulescu, Hélène Langet, Mathieu De Craene, Paul Aljabar, Paolo Piro, Andrew P King
Cardiac motion atlases provide a space of reference in which the motions of a cohort of subjects can be directly compared. Motion atlases can be used to learn descriptors that are linked to different pathologies and which can subsequently be used for diagnosis. To date, all such atlases have been formed and applied using data from the same modality. In this work we propose a framework to build a multimodal cardiac motion atlas from 3D magnetic resonance (MR) and 3D ultrasound (US) data. Such an atlas will benefit from the complementary motion features derived from the two modalities, and furthermore, it could be applied in clinics to detect cardiovascular disease using US data alone...
June 13, 2017: Medical Image Analysis
https://www.readbyqxmd.com/read/28644809/structured-kernel-dictionary-learning-with-correlation-constraint-for-object-recognition
#12
Zhengjue Wang, Yinghua Wang, Hongwei Liu, Hao Zhang
In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes...
June 21, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28644806/discriminative-deep-metric-learning-for-face-and-kinship-verification
#13
Jiwen Lu, Junlin Hu, Yap-Peng Tan
This paper presents a new discriminative deep metric learning (DDML) method for face and kinship verification in wild conditions. While metric learning has achieved reasonably good performance in face and kinship verification, most existing metric learning methods aim to learn a single Mahalanobis distance metric to maximize the inter-class variations and minimize the intra-class variations, which cannot capture the nonlinear manifold where face images usually lie on. To address this, we propose a DDML method to train a deep neural network to learn a set of hierarchical nonlinear transformations to project face pairs into the same latent feature space, under which the distance of each positive pair is reduced and that of each negative pair is enlarged, respectively...
June 20, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28643605/novel-simulation-device-for-targeting-tumors-in-laparoscopic-ablation-a-learning-curve-study
#14
Zeljka Jutric, Jan Grendar, William L Brown, Maria A Cassera, Ronald F Wolf, Paul D Hansen, Chet W Hammill
INTRODUCTION: A novel 3-dimensional (3D) guidance system was developed to aid accurate needle placement during ablation. METHODS: Five novices and 5 experienced hepatobiliary surgeons were recruited. Using an agar block with analog tumor, participants targeted under 4 conditions: in-line with the ultrasound plane using ultrasound, in-line using 3D guidance, 45° off-axis using ultrasound, and off-axis using 3D guidance. Time to target the tumor, number of withdrawals, and the National Aeronautics and Space Administration Task Load Index were collected...
June 1, 2017: Surgical Innovation
https://www.readbyqxmd.com/read/28643302/-comparison-of-robotic-and-laparoscopic-total-mesorectal-excision
#15
Pan Chi, Zhifen Chen
Laparoscopic total mesorectal excision (TME) has been commonly applied in the operation of mid-low rectal cancer, but the conventional laparoscopic TME has the disadvantages of major operative difficulty and long learning-curve, due to its limitations of 2-dimension vision and common laparoscopic instruments. Robotic surgical system with high-qualified 3-dimenstion vision and flexible Endo Wrist instruments can overcome those limitations of conventional laparoscopy, and is useful for the TME that demands deep pelvic operation and flexible dissection in the space of distal rectum...
June 25, 2017: Zhonghua Wei Chang Wai Ke za Zhi, Chinese Journal of Gastrointestinal Surgery
https://www.readbyqxmd.com/read/28643052/the-spaced-learning-concept-significantly-improves-training-for-laparoscopic-suturing-a-pilot-randomized-controlled-study
#16
Michael Boettcher, Johannes Boettcher, Stefan Mietzsch, Thomas Krebs, Robert Bergholz, Konrad Reinshagen
BACKGROUND: Spaced learning has been shown to be effective in various areas like traditional knowledge or motor skill acquisition. To evaluate the impact of implementation of the spaced learning concept in laparoscopic training was the aim of this study. METHODS: To evaluate the effectiveness of spaced learning, subjects were asked to perform four surgeon's square knots on a bowel model prior and post 3 h of hands-on training. All subjects were medical students and novice in laparoscopic suturing...
June 22, 2017: Surgical Endoscopy
https://www.readbyqxmd.com/read/28641259/face-hallucination-using-linear-models-of-coupled-sparse-support
#17
Reuben A Farrugia, Christine Guillemot
Most face super-resolution methods assume that low- and high-resolution manifolds have similar local geometrical structure, hence learn local models on the low-resolution manifold (e.g. sparse or locally linear embedding models), which are then applied on the high- resolution manifold. However, the low-resolution manifold is distorted by the one-to-many relationship between low- and high- resolution patches. This paper presents the Linear Model of Coupled Sparse Support (LM-CSS) method which learns linear models based on the local geometrical structure on the high-resolution manifold rather than on the low-resolution manifold...
June 19, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28641208/an-associative-account-of-the-development-of-word-learning
#18
Vladimir M Sloutsky, Hyungwook Yim, Xin Yao, Simon Dennis
Word learning is a notoriously difficult induction problem because meaning is underdetermined by positive examples. How do children solve this problem? Some have argued that word learning is achieved by means of inference: young word learners rely on a number of assumptions that reduce the overall hypothesis space by favoring some meanings over others. However, these approaches have difficulty explaining how words are learned from conversations or text, without pointing or explicit instruction. In this research, we propose an associative mechanism that can account for such learning...
June 19, 2017: Cognitive Psychology
https://www.readbyqxmd.com/read/28638700/vowel-decoding-from-single-trial-speech-evoked-electrophysiological-responses-a-feature-based-machine-learning-approach
#19
Han G Yi, Zilong Xie, Rachel Reetzke, Alexandros G Dimakis, Bharath Chandrasekaran
INTRODUCTION: Scalp-recorded electrophysiological responses to complex, periodic auditory signals reflect phase-locked activity from neural ensembles within the auditory system. These responses, referred to as frequency-following responses (FFRs), have been widely utilized to index typical and atypical representation of speech signals in the auditory system. One of the major limitations in FFR is the low signal-to-noise ratio at the level of single trials. For this reason, the analysis relies on averaging across thousands of trials...
June 2017: Brain and Behavior
https://www.readbyqxmd.com/read/28638524/changing-spaces-and-learning-environments-to-improve-inpatient-interprofessional-education-for-internal-medicine-residents
#20
Daphne Lo, Neil Zhang, Kathryn Eubank, G Michael Harper, Michi Yukawa, Bridget O'Brien
No abstract text is available yet for this article.
June 2017: Journal of Graduate Medical Education
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