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https://www.readbyqxmd.com/read/28213818/acceptability-of-an-internet-cognitive-behavioural-therapy-program-for-people-with-early-stage-cancer-and-cancer-survivors-with-depression-and-or-anxiety-thematic-findings-from-focus-groups
#1
A Karageorge, M J Murphy, J M Newby, L Kirsten, G Andrews, K Allison, S Loughnan, M Price, J Shaw, H Shepherd, J Smith, P Butow
PURPOSE: We developed an eight-lesson internet-delivered CBT (iCBT) program targeting anxiety and depression in early-stage cancer and cancer survivors. To explore the acceptability of the program, we showed volunteers the first two lessons and asked for their views. METHODS: Focus groups (n = 3) and individual interviews (n = 5) were undertaken with 15 participants (11 survivors) with mainly breast (11 of the 15) cancer, who had reviewed intervention materials...
February 18, 2017: Supportive Care in Cancer: Official Journal of the Multinational Association of Supportive Care in Cancer
https://www.readbyqxmd.com/read/28213144/modeling-and-validating-hl7-fhir-profiles-using-semantic-web-shape-expressions-shex
#2
Harold R Solbrig, Eric Prud'hommeaux, Grahame Grieve, Lloyd McKenzie, Joshua C Mandel, Deepak K Sharma, Guoqian Jiang
BACKGROUND: HL7 Fast Healthcare Interoperability Resources (FHIR) is an emerging open standard for the exchange of electronic healthcare information. FHIR resources are defined in a specialized modeling language. FHIR instances can currently be represented in either XML or JSON. The FHIR and Semantic Web communities are developing a third FHIR instance representation format in Resource Description Framework (RDF). Shape Expressions (ShEx), a formal RDF data constraint language, is a candidate for describing and validating the FHIR RDF representation...
February 14, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28213115/cross-modal-representation-of-spoken-and-written-word-meaning-in-left-pars-triangularis
#3
Antonietta Gabriella Liuzzi, Rose Bruffaerts, Ronald Peeters, Katarzyna Adamczuk, Emmanuel Keuleers, Simon De Deyne, Gerrit Storms, Patrick Dupont, Rik Vandenberghe
The correspondence in meaning extracted from written versus spoken input remains to be fully understood neurobiologically. Here, in a total of 38 subjects, the functional anatomy of cross-modal semantic similarity for concrete words was determined based on a dual criterion: First, a voxelwise univariate analysis had to show significant activation during a semantic task (property verification) performed with written and spoken concrete words compared to the perceptually matched control condition. Second, in an independent dataset, in these clusters, the similarity in fMRI response pattern to two distinct entities, one presented as a written and the other as a spoken word, had to correlate with the similarity in meaning between these entities...
February 14, 2017: NeuroImage
https://www.readbyqxmd.com/read/28212416/the-variability-of-multisensory-processes-of-natural-stimuli-in-human-and-non-human-primates-in-a-detection-task
#4
Cécile Juan, Céline Cappe, Baptiste Alric, Benoit Roby, Sophie Gilardeau, Pascal Barone, Pascal Girard
BACKGROUND: Behavioral studies in both human and animals generally converge to the dogma that multisensory integration improves reaction times (RTs) in comparison to unimodal stimulation. These multisensory effects depend on diverse conditions among which the most studied were the spatial and temporal congruences. Further, most of the studies are using relatively simple stimuli while in everyday life, we are confronted to a large variety of complex stimulations constantly changing our attentional focus over time, a modality switch that can impact on stimuli detection...
2017: PloS One
https://www.readbyqxmd.com/read/28212087/dual-deep-network-for-visual-tracking
#5
Zhizhen Chi, Hongyang Li, Huchuan Lu, Minghsuan Yang
Visual tracking addresses the problem of identifying and localizing an unknown target in a video given the target specified by a bounding box in the first frame. In this paper, we propose a dual network to better utilize features among layers for visual tracking. It is observed that features in higher layers encode semantic context while its counterparts in lower layers are sensitive to discriminative appearance. Thus we exploit the hierarchical features in different layers of a deep model and design a dual structure to obtain better feature representation from various streams, which is rarely investigated in previous work...
February 15, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28212082/semantic-highlight-retrieval-and-term-prediction
#6
Min Sun, Kuo-Hao Zeng, Yenchen Lin, Farhadi Ali
Due to the unprecedented growth of unedited videos, finding highlights relevant to a text query in a set of unedited videos has become increasingly important. We refer this task as semantic highlight retrieval and propose a query-dependent video representation for retrieving a variety of highlights. Our method consists of two parts: (1) "viralets", a mid-level representation bridging between semantic (Fig. 1(a)) and visual (Fig. 1(c)) spaces; (2) a novel Semantic-MODulation (SMOD) procedure to make viralets query-dependent (referred to as SMOD viralets)...
February 13, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28211025/participants-shift-response-deadlines-based-on-list-difficulty-during-reading-aloud-megastudies
#7
Michael J Cortese, Maya M Khanna, Robert Kopp, Jonathan B Santo, Kailey S Preston, Tyler Van Zuiden
We tested the list homogeneity effect in reading aloud (e.g., Lupker, Brown, & Colombo, 1997) using a megastudy paradigm. In each of two conditions, we used 25 blocks of 100 trials. In the random condition, words were selected randomly for each block, whereas in the experimental condition, words were blocked by difficulty (e.g., easy words together, etc.), but the order of the blocks was randomized. We predicted that standard factors (e.g., frequency) would be more predictive of reaction times (RTs) in the blocked than in the random condition, because the range of RTs across the experiment would increase in the blocked condition...
February 16, 2017: Memory & Cognition
https://www.readbyqxmd.com/read/28209520/deconstructing-empathy-neuroanatomical-dissociations-between-affect-sharing-and-prosocial-motivation-using-a-patient-lesion-model
#8
Suzanne M Shdo, Kamalini G Ranasinghe, Kelly A Gola, Clinton J Mielke, Paul V Sukhanov, Bruce L Miller, Katherine P Rankin
Affect sharing and prosocial motivation are integral parts of empathy that are conceptually and mechanistically distinct. We used a neurodegenerative disease (NDG) lesion model to more directly examine the neural correlates of these two aspects of real-world empathic responding. The study enrolled 275 participants, including 44 healthy older controls and 231 patients diagnosed with one of five neurodegenerative diseases (75 Alzheimer's disease, 58 behavioral variant frontotemporal dementia (bvFTD), 42 semantic variant primary progressive aphasia (svPPA), 28 progressive supranuclear palsy, and 28 non-fluent variant (nfvPPA)...
February 13, 2017: Neuropsychologia
https://www.readbyqxmd.com/read/28208671/a-passive-learning-sensor-architecture-for-multimodal-image-labeling-an-application-for-social-robots
#9
Marco A Gutiérrez, Luis J Manso, Harit Pandya, Pedro Núñez
Object detection and classification have countless applications in human-robot interacting systems. It is a necessary skill for autonomous robots that perform tasks in household scenarios. Despite the great advances in deep learning and computer vision, social robots performing non-trivial tasks usually spend most of their time finding and modeling objects. Working in real scenarios means dealing with constant environment changes and relatively low-quality sensor data due to the distance at which objects are often found...
February 11, 2017: Sensors
https://www.readbyqxmd.com/read/28208137/structural-and-referent-based-effects-on-prosodic-expression-in-russian
#10
Tatiana Luchkina, Jennifer S Cole
This study examines prosody in read productions of two published narratives by 15 Russian speakers. Two distinct sources of variation in acoustic-prosodic expression are considered: structural and referent-based. Structural effects refer to the particular linearization of words in a sentence or phrase. Referent-based effects relate to the semantic and pragmatic characteristics of the discourse referent of a word, and to grammatical roles that are partially dependent on referent characteristics. Here, we examine referent animacy and the related grammatical function of subjecthood, and the relative accessibility or information status of a word...
February 23, 2017: Phonetica
https://www.readbyqxmd.com/read/28208126/the-prosody-of-the-czech-discourse-marker-jasn%C3%A4-an-analysis-of-forms-and-functions
#11
Jan Volin, Lenka Weingartová, Oliver Niebuhr
Words like yeah, okay and (al)right are fairly unspecific in their lexical semantics, and not least for this reason there is a general tendency for them to occur with highly varied and expressive prosodic patterns across languages. Here we examine in depth the prosodic forms that express eight pragmatic functions of the Czech discourse marker jasně, including resignation, reassurance, surprise, indifference or impatience. Using a collection of 172 tokens from a corpus of scripted dialogues by 30 native speakers, we performed acoustic analyses, applied classification algorithms and solicited judgments from native listeners in a perceptual experiment...
February 23, 2017: Phonetica
https://www.readbyqxmd.com/read/28207397/stacked-learning-to-search-for-scene-labeling
#12
Feiyang Cheng, Xuming He, Hong Zhang
Search-based structured prediction methods have shown promising successes in both computer vision and natural language processing recently. However, most existing search-based approaches lead to a complex multi-stage learning process, which is ill-suited for scene labeling problems with a high-dimensional output space. In this paper, a stacked learning to search method is proposed to address scene labeling tasks. We design a simplified search process consisting of a sequence of ranking functions, which are learned based on a stacked learning strategy to prevent over-fitting...
February 13, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28207394/weakly-supervised-patchnets-describing-and-aggregating-local-patches-for-scene-recognition
#13
Zhe Wang, Limin Wang, Yali Wang, Bowen Zhang, Yu Qiao
Traditional feature encoding scheme (e.g., Fisher vector) with local descriptors (e.g., SIFT) and recent convolutional neural networks (CNNs) are two classes of successful methods for image recognition. In this paper, we propose a hybrid representation, which leverages the discriminative capacity of CNNs and the simplicity of descriptor encoding schema for image recognition, with a focus on scene recognition. To this end, we make three main contributions from the following aspects. First, we propose a patch-level and end-to-end architecture to model the appearance of local patches, called PatchNet...
February 9, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28207384/supervised-learning-of-semantics-preserving-hash-via-deep-convolutional-neural-networks
#14
Huei-Fang Yang, Kevin Lin, Chu-Song Chen
This paper presents a simple yet effective supervised deep hash approach that constructs binary hash codes from labeled data for large-scale image search. We assume that the semantic labels are governed by several latent attributes with each attribute on or off, and classification relies on these attributes. Based on this assumption, our approach, dubbed supervised semantics-preserving deep hashing (SSDH), constructs hash functions as a latent layer in a deep network and the binary codes are learned by minimizing an objective function defined over classification error and other desirable hash codes properties...
February 9, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28207295/competent-geometric-semantic-genetic-programming-for-symbolic-regression-and-boolean-function-synthesis
#15
Tomasz P Pawlak, Krzysztof Krawiec
Program semantics is a promising recent research thread in Genetic Programming (GP). Over a dozen of semantic-aware search, selection, and initialization operators for GP have been proposed to date. Some of those operators are designed to exploit the geometric properties of semantic space, while some others focus on making offspring effective, i.e., semantically different from their parents. Only a small fraction of previous works aimed at addressing both these features simultaneously. In this paper, we propose a suite of competent operators that combine effectiveness with geometry for population initialization, mate selection, mutation and crossover...
February 16, 2017: Evolutionary Computation
https://www.readbyqxmd.com/read/28206775/one-hundred-years-of-the-journal-of-applied-psychology-background-evolution-and-scientific-trends
#16
Steve W J Kozlowski, Gilad Chen, Eduardo Salas
To launch this Special Issue of the Journal of Applied Psychology celebrating the 1st century of the journal we conducted a review encompassing the background of the founding of the journal; a quantitative assessment of its evolution across the century; and an examination of trends examining article type, article length, authorship patterns, supplemental materials, and research support. The journal was founded in March of 1917 with hopeful optimism about the potential of psychology being applied to practical problems could enhance human happiness, well-being, and effectiveness...
February 16, 2017: Journal of Applied Psychology
https://www.readbyqxmd.com/read/28205494/language-deficits-as-a-preclinical-window-into-parkinson-s-disease-evidence-from-asymptomatic-parkin-and-dardarin-mutation-carriers
#17
Adolfo M García, Lucas Sedeño, Natalia Trujillo, Yamile Bocanegra, Diana Gomez, David Pineda, Andrés Villegas, Edinson Muñoz, William Arias, Agustín Ibáñez
OBJECTIVES: The worldwide spread of Parkinson's disease (PD) calls for sensitive and specific measures enabling its early (or, ideally, preclinical) detection. Here, we use language measures revealing deficits in PD to explore whether similar disturbances are present in asymptomatic individuals at risk for the disease. METHODS: We administered executive, semantic, verb-production, and syntactic tasks to sporadic PD patients, genetic PD patients with PARK2 (parkin) or LRRK2 (dardarin) mutation, asymptomatic first-degree relatives of the latter with similar mutations, and socio-demographically matched controls...
February 2017: Journal of the International Neuropsychological Society: JINS
https://www.readbyqxmd.com/read/28205493/rethinking-the-cognitive-mechanisms-underlying-pantomime-of-tool-use-evidence-from-alzheimer-s-disease-and-semantic-dementia
#18
Mathieu Lesourd, Josselin Baumard, Christophe Jarry, Frédérique Etcharry-Bouyx, Serge Belliard, Olivier Moreaud, Bernard Croisile, Valérie Chauviré, Marine Granjon, Didier Le Gall, François Osiurak
OBJECTIVES: Pantomiming the use of familiar tools is a central test in the assessment of apraxia. However, surprisingly, the nature of the underlying cognitive mechanisms remains an unresolved issue. The aim of this study is to shed a new light on this issue by exploring the role of functional, mechanical, and manipulation knowledge in patients with Alzheimer's disease and semantic dementia and apraxia of tool use. METHODS: We performed multiple regression analyses with the global performance and the nature of errors (i...
February 2017: Journal of the International Neuropsychological Society: JINS
https://www.readbyqxmd.com/read/28203635/grounded-understanding-of-abstract-concepts-the-case-of-stem-learning
#19
REVIEW
Justin C Hayes, David J M Kraemer
Characterizing the neural implementation of abstract conceptual representations has long been a contentious topic in cognitive science. At the heart of the debate is whether the "sensorimotor" machinery of the brain plays a central role in representing concepts, or whether the involvement of these perceptual and motor regions is merely peripheral or epiphenomenal. The domain of science, technology, engineering, and mathematics (STEM) learning provides an important proving ground for sensorimotor (or grounded) theories of cognition, as concepts in science and engineering courses are often taught through laboratory-based and other hands-on methodologies...
2017: Cogn Res Princ Implic
https://www.readbyqxmd.com/read/28203277/semantics-based-plausible-reasoning-to-extend-the-knowledge-coverage-of-medical-knowledge-bases-for-improved-clinical-decision-support
#20
Hossein Mohammadhassanzadeh, William Van Woensel, Samina Raza Abidi, Syed Sibte Raza Abidi
BACKGROUND: Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians' experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mechanisms apply patterns from human thought processes, such as generalization, similarity and interpolation, based on attributional, hierarchical, and relational knowledge...
2017: BioData Mining
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