Cryptanalysis of random-phase-encoding-based optical cryptosystem via deep learning
Random Phase Encoding (RPE) techniques for image encryption have drawn increasing attention during the past decades. We demonstrate in this contribution that the RPE-based optical cryptosystems are vulnerable to the chosen-plaintext attack (CPA) with deep learning strategy. A deep neural network ... (Source: Optics Express)
Source: Optics Express - July 15, 2019 Category: Physics Authors: Han Hai Shuixin Pan Meihua Liao Dajiang Lu Wenqi He Xiang Peng Source Type: research

Charles L. Brewer Award for distinguished teaching of psychology: R. Eric Landrum.
R. Eric Landrum is an inspiring, passionate teacher, a productive scholar, and a tireless crusader for education. A skilled orator, he works hard to further the craft of teaching, inspiring his colleagues to be the best teachers they can be and motivating his students to learn. Eric is an authority on careers for psychology majors and his know-how on this topic is sought after around the country. His interests in skill development, assessment, and the importance of preparing students for the workforce and arming them with psychological science have resulted in significant changes to the lives of students and educators worl...
Source: American Psychologist - July 15, 2019 Category: Psychiatry & Psychology Source Type: research

Dysregulation of the Reward and Learning Systems in Tourette Syndrome
To the Editor In their cohort study, Brander et al observed an increased risk of metabolic and cardiovascular diseases in patients with Tourette syndrome (TS) and chronic tic disorder. This risk was even higher in patients with comorbid attention-deficit/hyperactivity disorder. Interestingly, metabolic and cardiovascular risks were already present at an early stage of the disorder and were actually decreased in patients that used antipsychotic medication for a longer time. These data are relevant for the field because they were previously unknown in this form and must be considered in the future care of these patients. (So...
Source: JAMA Neurology - July 15, 2019 Category: Neurology Source Type: research

Improving survival prediction of high-grade glioma via machine learning techniques based on MRI radiomic, genetic and clinical risk factors
ConclusionThe radiomics signature is a new prognostic biomarker for HGG. A nomogram incorporating radiomics signature, IDH and age improved the performance of OS estimation, which might be a new complement to the treatment guidelines of glioma. (Source: European Journal of Radiology)
Source: European Journal of Radiology - July 15, 2019 Category: Radiology Source Type: research

Assessment of lipid peroxidation and artificial neural network models in early Alzheimer Disease diagnosis.
CONCLUSION: Lipid peroxidation and ANN constitute a useful approach to establish a reliable diagnosis when the prognosis is complex, multidimensional and non-linear. PMID: 31319065 [PubMed - as supplied by publisher] (Source: Clinical Biochemistry)
Source: Clinical Biochemistry - July 15, 2019 Category: Biochemistry Authors: Peña-Bautista C, Durand T, Oger C, Baquero M, Vento M, Cháfer-Pericás C Tags: Clin Biochem Source Type: research

Repurposing Quinacrine Against Ebola Virus Infection In vivo.
Abstract Quinacrine hydrochloride is a small-molecule, orally bioavailable drug that has been used clinically as an antimalarial and for many other applications. A machine learning model trained on Ebola virus (EBOV) screening data identified quinacrine as a potent (nM) in vitro inhibitor. Quinacrine (25 mg/kg) was shown in the current study to protect 70% of mice (statistically significant) from a lethal challenge with mouse-adapted EBOV (maEBOV) with once daily intraperitoneal (i.p.) dosing for 8 days. PMID: 31307979 [PubMed - as supplied by publisher] (Source: Antimicrobial Agents and Chemotherapy)
Source: Antimicrobial Agents and Chemotherapy - July 15, 2019 Category: Microbiology Authors: Lane TR, Comer JE, Freiberg AN, Madrid PB, Ekins S Tags: Antimicrob Agents Chemother Source Type: research

Rational redox tuning of transition metal sites: learning from superoxide reductase.
Abstract Using superoxide reductase as a model system, a computational approach reveals how histidine tautomerism tunes the redox properties of metalloenzymes to enable their catalytic function. Inspired by these experimentally inaccessible insights, non-canonical histidine congeners are introduced as new versatile tools for the rational engineering of biological transition metal sites. PMID: 31304493 [PubMed - as supplied by publisher] (Source: Chemical Communications)
Source: Chemical Communications - July 15, 2019 Category: Chemistry Authors: Horch M Tags: Chem Commun (Camb) Source Type: research

Optimized and Predictive Phonemic Interfaces for Augmentative and Alternative Communication.
Conclusions Optimization and prediction led to increases in communication rates in users without motor impairments. Predictive interfaces were preferred by users with motor impairments. Future research is needed to translate these results into clinical practice. Supplemental Material PMID: 31306607 [PubMed - in process] (Source: Journal of speech, language, and hearing research : JSLHR)
Source: Journal of speech, language, and hearing research : JSLHR - July 15, 2019 Category: Speech-Language Pathology Authors: Cler GJ, Kolin KR, Noordzij JP, Vojtech JM, Fager SK, Stepp CE Tags: J Speech Lang Hear Res Source Type: research

Motor-Induced Suppression of the N100 Event-Related Potential During Motor Imagery Control of a Speech Synthesizer Brain-Computer Interface.
Conclusion Observation of the N100 suppression suggests motor planning brain networks are active as participants control the BCI synthesizer, which may aid speech BCI mastery. PMID: 31306609 [PubMed - in process] (Source: Journal of speech, language, and hearing research : JSLHR)
Source: Journal of speech, language, and hearing research : JSLHR - July 15, 2019 Category: Speech-Language Pathology Authors: Brumberg JS, Pitt KM Tags: J Speech Lang Hear Res Source Type: research

An investigation of quantitative accuracy for deep learning based denoising in oncological PET.
Abstract Reducing radiation dose is important for PET imaging. However, reducing injection doses causes increased image noise and low signal-to-noise ratio (SNR), subsequently affecting diagnostic and quantitative accuracies. Deep learning methods have shown a great potential to reduce the noise and improve the SNR in low dose PET data. 
 In this work, we comprehensively investigated the quantitative accuracy of small lung nodules, in addition to visual image quality, using deep learning based denoising methods for oncological PET imaging. We applied and optimized an advanced deep learning method based...
Source: Physics in Medicine and Biology - July 15, 2019 Category: Physics Authors: Lu W, Onofrey JA, Lu Y, Shi L, Ma T, Liu Y, Liu C Tags: Phys Med Biol Source Type: research

Patient ‐based prediction algorithm of relapse after allo‐HSCT for acute Leukemia and its usefulness in the decision‐making process using a machine learning approach
We focused on the construction of a prediction model for the bedside decision ‐making process and investigated the usefulness of machine learning (ML). Clinicians can refer to the model which was constructed by ML and select treatment options. ML may improve the decision‐making process for therapy in the diversified allo‐HSCT field. AbstractAlthough allogeneic hematopoietic stem cell transplantation (allo ‐HSCT) is a curative therapy for high‐risk acute leukemia (AL), some patients still relapse. Since patients simultaneously have many prognostic factors, difficulties are associated with the construction of a pat...
Source: Cancer Medicine - July 15, 2019 Category: Cancer & Oncology Authors: Kyoko Fuse, Shun Uemura, Suguru Tamura, Tatsuya Suwabe, Takayuki Katagiri, Tomoyuki Tanaka, Takashi Ushiki, Yasuhiko Shibasaki, Naoko Sato, Toshio Yano, Takashi Kuroha, Shigeo Hashimoto, Tatsuo Furukawa, Miwako Narita, Hirohito Sone, Masayo Tags: ORIGINAL RESEARCH Source Type: research

Reservoir computing model of prefrontal cortex creates novel combinations of previous navigation sequences from hippocampal place-cell replay with spatial reward propagation
by Nicolas Cazin, Martin Llofriu Alonso, Pablo Scleidorovich Chiodi, Tatiana Pelc, Bruce Harland, Alfredo Weitzenfeld, Jean-Marc Fellous, Peter Ford Dominey As rats learn to search for multiple sources of food or water in a complex environment, they generate increasingly efficient trajectories between reward sites. Such spatial navigation capacity involves the replay of hippocampal place-cells during awake states, generating small sequences of spatial ly related place-cell activity that we call “snippets”. These snippets occur primarily during sharp-wave-ripples (SWRs). Here we focus on the role of such replay...
Source: PLoS Computational Biology - July 15, 2019 Category: Biology Authors: Nicolas Cazin Source Type: research

The Mmogo-Method: Application, Experiences, and Lessons Learnt in Researching Radiography Students' Experiences and Coping With Death and Dying
This study aimed to share the application, experiences, and lessons learnt regarding the value of the Mmogo-method that is a visual projective research method, in the context of exploring the experiences and coping of undergraduate diagnostic radiography students with death and dying patients in the workplace. (Source: Journal of Medical Imaging and Radiation Sciences)
Source: Journal of Medical Imaging and Radiation Sciences - July 15, 2019 Category: Radiology Authors: Riaan van de Venter, Penelope Engel-Hills, Louise Stroud Tags: Educational Perspective Source Type: research

HYPerspectral Enhanced Reality (HYPER): a physiology-based surgical guidance tool
ConclusionsHYPER imaging could precisely quantify the overtime perfusion changes in this bowel ischemia model. (Source: Surgical Endoscopy)
Source: Surgical Endoscopy - July 15, 2019 Category: Surgery Source Type: research

Applying Data Science to Behavioral Analysis of Online Gambling
AbstractPurpose of ReviewGambling operators ’ capacity to track gamblers in the online environment may enable identification of those users experiencing gambling harm. This review provides an update on research testing behavioral variables against indicators of disordered gambling. We consider the utility of machine learning algorithms in r isk prediction, and challenges to be overcome.Recent FindingsDisordered online gambling is associated with a range of behavioral variables, as well as other predictors including demographic and payment-related information. Machine learning is ideally suited to the task of combinin...
Source: Current Addiction Reports - July 15, 2019 Category: Addiction Source Type: research

The effects of high intensity exercise on learning and memory impairments followed by combination of sleep deprivation and demyelination induced by etidium bromide
. (Source: International Journal of Neuroscience)
Source: International Journal of Neuroscience - July 15, 2019 Category: Neuroscience Authors: Mohammad Amin Rajizadeh Vahid Sheibani Mohammad Abbas Bejeshk Fatemeh Mohtashami Borzadaran Hasan Saghari Khadijeh Esmaeilpour Source Type: research

Sensors, Vol. 19, Pages 3119: Blockchain and Random Subspace Learning-Based IDS for SDN-Enabled Industrial IoT Security
kh Aslam Khan The industrial control systems are facing an increasing number of sophisticated cyber attacks that can have very dangerous consequences on humans and their environments. In order to deal with these issues, novel technologies and approaches should be adopted. In this paper, we focus on the security of commands in industrial IoT against forged commands and misrouting of commands. To this end, we propose a security architecture that integrates the Blockchain and the Software-defined network (SDN) technologies. The proposed security architecture is composed of: (a) an intrusion detection system, namely RSL-KN...
Source: Sensors - July 15, 2019 Category: Biotechnology Authors: Abdelouahid Derhab Mohamed Guerroumi Abdu Gumaei Leandros Maglaras Mohamed Amine Ferrag Mithun Mukherjee Farrukh Aslam Khan Tags: Article Source Type: research

Sensors, Vol. 19, Pages 3121: SASRT: Semantic-Aware Super-Resolution Transmission for Adaptive Video Streaming over Wireless Multimedia Sensor Networks
ingyu Liu There are few network resources in wireless multimedia sensor networks (WMSNs). Compressing media data can reduce the reliance of user’s Quality of Experience (QoE) on network resources. Existing video coding software, such as H.264 and H.265, focuses only on spatial and short-term information redundancy. However, video usually contains redundancy over a long period of time. Therefore, compressing video information redundancy with a long period of time without compromising the user experience and adaptive delivery is a challenge in WMSNs. In this paper, a semantic-aware super-resolution transmis...
Source: Sensors - July 15, 2019 Category: Biotechnology Authors: Jia Guo Xiangyang Gong Wendong Wang Xirong Que Jingyu Liu Tags: Article Source Type: research

Sensors, Vol. 19, Pages 3126: A Survey on Recent Trends and Open Issues in Energy Efficiency of 5G
rci The rapidly increasing interest from various verticals for the upcoming 5th generation (5G) networks expect the network to support higher data rates and have an improved quality of service. This demand has been met so far by employing sophisticated transmission techniques including massive Multiple Input Multiple Output (MIMO), millimeter wave (mmWave) bands as well as bringing the computational power closer to the users via advanced baseband processing units at the base stations. Future evolution of the networks has also been assumed to open many new business horizons for the operators and the need of not only a r...
Source: Sensors - July 15, 2019 Category: Biotechnology Authors: Muhammad Usama Melike Erol-Kantarci Tags: Review Source Type: research

Sensors, Vol. 19, Pages 3115: Proximity Environmental Feature Based Tree Health Assessment Scheme Using Internet of Things and Machine Learning Algorithm
Faan Hei Hung Improperly grown trees may cause huge hazards to the environment and to humans, through e.g., climate change, soil erosion, etc. A proximity environmental feature-based tree health assessment (PTA) scheme is proposed to prevent these hazards by providing guidance for early warning methods of potential poor tree health. In PTA development, tree health is defined and evaluated based on proximity environmental features (PEFs). The PEF takes into consideration the seven surrounding ambient features that strongly impact tree health. The PEFs were measured by the deployed smart sensors surrounding trees. A da...
Source: Sensors - July 15, 2019 Category: Biotechnology Authors: Yang Wei Hao Wang Kim Fung Tsang Yucheng Liu Chung Kit Wu Hongxu Zhu Yuk-Tak Chow Faan Hei Hung Tags: Article Source Type: research

Interscalene brachial plexus nerve block in the emergency department: an effective and practice-changing workshop
ConclusionsOur study suggests that EM residents can learn the ISNB, perform it safely in the emergency department, and that the ISNB may be an alternative to procedural sedation and opiate use for shoulder dislocation. Residents are adept at ISNB technical skills but demonstrate some deficits in knowledge retention. (Source: Critical Ultrasound Journal)
Source: Critical Ultrasound Journal - July 15, 2019 Category: Radiology Source Type: research

An Automatic Approach Using ELM Classifier for HFpEF Identification Based on Heart Sound Characteristics
AbstractHeart failure with preserved ejection fraction (HFpEF) is a complex and heterogeneous clinical syndrome. For the purpose of assisting HFpEF diagnosis, a non-invasive method using extreme learning machine and heart sound (HS) characteristics was provided in this paper. Firstly, the improved wavelet denoising method was used for signal preprocessing. Then, the logistic regression based hidden semi-Markov model algorithm was utilized to locate the boundary of the first HS and the second HS, therefore, the ratio of diastolic to systolic duration can be calculated. Eleven features were extracted based on multifractal de...
Source: Journal of Medical Systems - July 15, 2019 Category: Information Technology Source Type: research

The positive influence the Onchocerciasis Elimination Program for the Americas has had on Africa programs
AbstractA recent article “Is onchocerciasis elimination in Africa feasible by 2025: a perspective based on lessons learnt from the African control programmes” inInfectious Diseases of Poverty claimed that undue influence on African programs by concepts developed by the Onchocerciasis Elimination Program of the Americas (OEPA) is detrimental to stopping mass drug administration (MDA) in Africa. This claim is made despite a record year for MDA stoppage in four African countries of>  3.5 million treatments in 2018, far exceeding any past OEPA or African Program for Onchocerciasis Control (APOC) stop MDA ...
Source: Infectious Diseases of Poverty - July 15, 2019 Category: Infectious Diseases Source Type: research

Elimination of onchocerciasis in Africa by 2025: the need for a broad perspective
ConclusionsProgrammatic treatment and evaluation approaches, pioneered in the Americas, are the most efficient among the existing tools for elimination, and their broader use could catalyze the successful elimination of this disease in Africa. (Source: Infectious Diseases of Poverty)
Source: Infectious Diseases of Poverty - July 15, 2019 Category: Infectious Diseases Source Type: research

Implementing a peer-learning approach for the clinical education of respiratory therapy students.
Conclusion: Participants felt that a 2:1 model strongly contributes to a supportive learning environment and can have a positive influence on the RT student clinical experience at UHN. Along with the improved critical thinking and student engagement opportunities that a 2:1 model offers, increased placement numbers are also supported. PMID: 31297442 [PubMed] (Source: Respiratory Care)
Source: Respiratory Care - July 14, 2019 Category: Respiratory Medicine Authors: Dorner S, Fowler T, Montano M, Janisse R, Lowe M, Rowland P Tags: Can J Respir Ther Source Type: research

Discriminative Multimodal Embedding for Event Classification
Publication date: Available online 13 July 2019Source: NeurocomputingAuthor(s): Fan Qi, Xiaoshan Yang, Tianzhu Zhang, Changsheng XuAbstractMost of existing multimodal event classification methods fuse the traditional hand-crafted features with some manually defined weights, which may be not suitable to the event classification task with large amounts of photos. Besides, the feature extraction and event classification model are always performed separately, which cannot capture the most useful features to describe the semantic concepts of complex events. To deal with these issues, we propose a novel discriminative multimodal...
Source: Neurocomputing - July 14, 2019 Category: Neuroscience Source Type: research

Learning Fashion Compatibility across Categories with Deep Multimodal Neural Networks
Publication date: Available online 13 July 2019Source: NeurocomputingAuthor(s): Guang-Lu Sun, Jun-Yan He, Xiao Wu, Bo Zhao, Qiang PengAbstractFashion compatibility is a subjective sense of human for relationships between fashion items, which is essential for fashion recommendation. Recently, it increasingly attracts more and more attentions and has become a very hot research topic. Learning fashion compatibility is a challenging task, since it needs to consider plenty of factors about fashion items, such as color, texture, style and functionality. Unlike low-level visual compatibility (e.g., color, texture), high-level sem...
Source: Neurocomputing - July 14, 2019 Category: Neuroscience Source Type: research

Mutual Information-Based Dropout: Learning Deep Relevant Feature Representation Architectures
Publication date: Available online 13 July 2019Source: NeurocomputingAuthor(s): Jie Chen, ZhongCheng Wu, Jun Zhang, Fang LiAbstractWe propose a new regularization strategy called DropMI, which is a generalization of Dropout for the regularization of networks that introduces mutual information (MI) dynamic analysis. The standard Dropout randomly drops a certain proportion of neural units, according to the Bernoulli distribution, thereby resulting in the loss of some important hidden feature information. In DropMI, we first evaluate the importance of each neural unit in the feature representation of the hidden layer based on...
Source: Neurocomputing - July 14, 2019 Category: Neuroscience Source Type: research

Unsupervised Feature Selection with Adaptive Residual Preserving
Publication date: Available online 13 July 2019Source: NeurocomputingAuthor(s): Luyao Teng, Zhenye Feng, Xiaozhao Fang, Shaohua Teng, Hua Wang, Peipei Kang, Yanchun ZhangAbstractMany feature selection approaches are proposed in recent years. Most approaches utilize graph-based methods in studying the structure and relationship among data. However, many data relationships may loss during the graph construction, such as the residual relationships. To better preserve the relationships between data, in this paper, we propose a novel unified learning framework - unsupervised feature selection with adaptive residual preserving (...
Source: Neurocomputing - July 14, 2019 Category: Neuroscience Source Type: research

E2BoWs: An End-to-End Bag-of-Words Model via Deep Convolutional Neural Network for Image Retrieval
Publication date: Available online 13 July 2019Source: NeurocomputingAuthor(s): Xiaobin Liu, Shiliang Zhang, Tiejun Huang, Qi TianAbstractTraditional Bag-of-Words (BoWs) model is commonly generated with many steps, including local feature extraction, codebook generation and feature quantization, etc. Those steps are relatively independent with each other and are hard to be jointly optimized. Moreover, the dependency on hand-crafted local feature makes BoWs model not effective in conveying high-level semantics. These issues largely hinder the performance of BoWs model in large-scale image applications. To conquer these issu...
Source: Neurocomputing - July 14, 2019 Category: Neuroscience Source Type: research

Visual Concept Conjunction Learning with Recurrent Neural Networks
Publication date: Available online 13 July 2019Source: NeurocomputingAuthor(s): Kongming Liang, Hong Chang, Shiguang Shan, Xilin ChenAbstractLearning the conjunction of multiple visual concepts shows practical significance in various real world applications (e.g. multi-attribute image retrieval and visual relationship detection). In this paper, we propose Concept Conjunction Recurrent Neural Network (C2RNN) to tackle this problem. With our model, visual concepts involved in a conjunction are mapped into the hidden units and combined in a recurrent way to generate the representation of the concept conjunction, which is then...
Source: Neurocomputing - July 14, 2019 Category: Neuroscience Source Type: research

Label-Removed Generative Adversarial Networks Incorporating with K-Means
Publication date: Available online 13 July 2019Source: NeurocomputingAuthor(s): Ce Wang, Zhangling Chen, Kun Shang, Huaming WuAbstractGenerative Adversarial Networks (GANs) have achieved great success in generating realistic images. Most of these are conditional models, although acquisition of class labels is expensive and time-consuming in practice. To reduce the dependence on labeled data, we propose an un-conditional generative adversarial model, called K-Means-GAN (KM-GAN), which incorporates the idea of updating centers in K-Means into GANs. Specifically, we redesign the framework of GANs by applying K-Means on the fe...
Source: Neurocomputing - July 14, 2019 Category: Neuroscience Source Type: research

MCFF-CNN: Multiscale Comprehensive Feature Fusion Convolutional Neural Network for Vehicle Color Recognition Based on Residual Learning
Publication date: Available online 13 July 2019Source: NeurocomputingAuthor(s): Huiyuan Fu, Huadong Ma, Gaoya Wang, Xiaomou Zhang, Yifan ZhangAbstractAutomatic vehicle color recognition is very important for video surveillance, especially for intelligent transportation system. Currently, some approaches have been proposed. However, it is still very difficult to recognize the vehicle color correctly in the complex traffic scenes with constantly changing illuminations. To solve this problem, we propose a new network structure - Multiscale Comprehensive Feature Fusion Convolutional Neural Network (MCFF-CNN) based on residual ...
Source: Neurocomputing - July 14, 2019 Category: Neuroscience Source Type: research

A Fast Machine Learning Approach to Facilitate the Detection of Interictal Epileptiform Discharges in the Scalp Electroencephalogram
ConclusionsThe proposed method successfully reduces computation time of an IED detection system. Therefore, it is beneficial in speeding up IED detection especially when utilizing large EEG datasets.Graphical abstract (Source: Journal of Neuroscience Methods)
Source: Journal of Neuroscience Methods - July 14, 2019 Category: Neuroscience Source Type: research

Development of Low-stakes Mathematics and Literacy Test Scores during Lower Secondary School – A Multilevel Pattern-Centered Analysis of Student and Classroom Differences
Publication date: Available online 13 July 2019Source: Contemporary Educational PsychologyAuthor(s): Elina E. Ketonen, Risto HotulainenAbstractThe development of students’ learning and test-taking behavior may derive from the social context and the group of peers they associate with daily for years. Consequently, it is assumed that students’ academic achievements are to some degree affected by their classmates and the composition of the classroom. The present study provides evidence on how Finnish students (N=5071) from different classrooms (N=435) develop distinct patterns regarding their mathematics and liter...
Source: Contemporary Educational Psychology - July 14, 2019 Category: Child Development Source Type: research

Tomato volume and mass estimation using computer vision and machine learning algorithms: Cherry tomato model
Publication date: Available online 14 July 2019Source: Journal of Food EngineeringAuthor(s): Innocent Nyalala, Cedric Okinda, Luke Nyalala, Nelson Makange, Qi Chao, Liu Chao, Khurram Yousaf, Kunjie ChenAbstractA prediction method of mass and volume of cherry tomato based on a computer vision system and machine learning algorithms were introduced in this study. The relation between tomato mass and volume was established as M=1.312V0.9551, and was used to estimate mass on a test dataset at an R2 of 0.9824 and RMSE of 15.84g. Depth images of tomatoes at different orientations were acquired and features extracted by image proc...
Source: Journal of Food Engineering - July 14, 2019 Category: Food Science Source Type: research

Implementing Cognitive Science and Discipline-Based Education Research in the Undergraduate Science Classroom.
Abstract Cognitive science research on learning and instruction is often not directly connected to discipline-based research. In an effort to narrow this gap, this essay integrates research from both fields on five learning and instruction strategies: active retrieval, distributed (spaced) learning, dual coding, concrete examples, and feedback and assessment. These strategies can significantly enhance the effectiveness of science instruction, but they typically do not find their way into the undergraduate classroom. The implementation of these strategies is illustrated through an undergraduate science course for n...
Source: CBE Life Sciences Education - July 14, 2019 Category: Cytology Authors: Davidesco I, Milne C Tags: CBE Life Sci Educ Source Type: research

What Is the Minimal Competency for a Clinical Ethics Consult Simulation? Setting a Standard for Use of the Assessing Clinical Ethics Skills (ACES) Tool.
Conclusions: The cut score for the ACES tool identifies the number of correct responses a user of the ACES tool training website must attain to "pass" and reach minimal competency in recognizing competent and incompetent skills of the CECs in the simulated ethics consultation videos. The application of the cut score to live training of CECs and other areas of practice requires further investigation. PMID: 31295060 [PubMed - as supplied by publisher] (Source: AJOB Primary Research)
Source: AJOB Primary Research - July 14, 2019 Category: Medical Ethics Tags: AJOB Empir Bioeth Source Type: research

Mechanisms of output interference in cued recall.
Authors: Wilson JH, Kellen D, Criss AH Abstract The primary aim of this paper is to elucidate the mechanisms governing output interference in cued recall. Output interference describes the phenomenon where accuracy decrease over the course of an episodic memory test. Output inference in cued recall takes the form of a decrease in correct and intrusion responses and an increase in failures to response across the test. This pattern can only be accounted for by a model with two complementary mechanisms: learning during retrieval and a response filter that prevents repeated recall of the same item. We investigate how a...
Source: Memory and Cognition - July 14, 2019 Category: Neuroscience Tags: Mem Cognit Source Type: research

Teaching a novel word: Parenting styles and toddlers’ word learning
We examined the styles that parents adopted while teaching a novel word to their toddlers and whether those styles related to children’s word learning and engagement during the task. Participants were 36 parents and their toddlers (Mage = 20 months). Parents were videotaped while teaching their children a name for a novel object. Parental utterances were transcribed verbatim and coded for cognitive and autonomy support. Children’s utterances were coded for elicited and spontaneous contributions. Children’s ability to recognize and process the novel word was assessed using the Looking-While-Listening...
Source: Journal of Experimental Child Psychology - July 14, 2019 Category: Child Development Source Type: research

I’ve Got This: Fostering Topic and Technology-related Emotional Engagement and Queer History Knowledge with a Mobile App
Publication date: Available online 13 July 2019Source: Contemporary Educational PsychologyAuthor(s): Jason M. Harley, Yang Liu, Tony Byunghoon Ahn, Susanne P. Lajoie, Andre Grace, Chayse Haldane, Andrea Whittaker, Brea McLaughlinAbstractLittle research has been conducted to differentiate between multiple, and frequently simultaneously available, discrete object foci in academic achievement situations that emotions can be generated from, including technology and academic topics. Using R. Pekrun’s control-value theory of achievement emotions and M. Sharples and colleagues’ Mobile Learning Theory, we examined whet...
Source: Contemporary Educational Psychology - July 14, 2019 Category: Child Development Source Type: research

How will artificial intelligence affect diagnosis and treatment of liver disease?
Recent years have seen a dramatic increase in computational capacity and the volume of data stored which has fuelled progress in machine learning methodology. Increasing attention is turning towards the use of artificial intelligence (AI) in healthcare; AI is facilitating the diagnosis of several conditions, from atrial fibrillation to stroke, and the treatment of others, such as depression and anxiety. Hepatology could see significant change with the introduction of AI but there are important challenges to consider for ensuring successful integration and implementation. (Source: Digestive and Liver Disease)
Source: Digestive and Liver Disease - July 14, 2019 Category: Gastroenterology Authors: Christopher A. Lovejoy, Bruce Keogh, Mahiben Maruthappu Tags: Correspondence Source Type: research

Sensors, Vol. 19, Pages 3113: Non-Invasive Ambient Intelligence in Real Life: Dealing with Noisy Patterns to Help Older People
Unai Saralegui Shengjing Sun This paper aims to contribute to the field of ambient intelligence from the perspective of real environments, where noise levels in datasets are significant, by showing how machine learning techniques can contribute to the knowledge creation, by promoting software sensors. The created knowledge can be actionable to develop features helping to deal with problems related to minimally labelled datasets. A case study is presented and analysed, looking to infer high-level rules, which can help to anticipate abnormal activities, and potential benefits of the integration of these technologies ar...
Source: Sensors - July 14, 2019 Category: Biotechnology Authors: Miguel Ángel Antón Joaqu ín Ordieres-Meré Unai Saralegui Shengjing Sun Tags: Article Source Type: research

Exploiting ensemble learning to improve prediction of phospholipidosis inducing potential
Publication date: Available online 13 July 2019Source: Journal of Theoretical BiologyAuthor(s): Abhigyan Nath, Gopal Krishna SahuAbstractPhospholipidosis is characterized by the presence of excessive accumulation of phospholipids in different tissue types (lungs, liver, eyes, kidneys etc.) caused by cationic amphiphilic drugs. Electron microscopy analysis has revealed the presence of lamellar inclusion bodies as the hallmark of phospholipidosis. Some phospholipidosis causing compounds can cause tissue specific inflammatory/retrogressive changes. Reliable and accurate in silico methods could facilitate early screening of ph...
Source: Journal of Theoretical Biology - July 13, 2019 Category: Biology Source Type: research

Cockatoo learns a dance move or two
Publication date: 13 July 2019Source: New Scientist, Volume 243, Issue 3238Author(s): (Source: New Scientist)
Source: New Scientist - July 13, 2019 Category: Science Source Type: research

Robotic colectomy with intracorporeal anastomosis is feasible with no operative conversions during the learning curve for an experienced laparoscopic surgeon developing a robotics program
The objectives of the study were to compare the outcomes of robotic colectomy to laparoscopic colectomy for patients with right-sided tumors undergoing a standardized completely intracorporeal operation and to examine the impact of prior experience with laparoscopic right colectomies on the performance of robotic right colectomies. Retrospective review of outcomes of consecutive patients undergoing a robotic right colectomy (robot) compared to those undergoing laparoscopic colectomy (LAP). LAP patients were further subdivided into a group during the learning curve (LC) and after the learning curve (post-LC). Data collected...
Source: Journal of Robotic Surgery - July 13, 2019 Category: Surgery Source Type: research

An intervention to help teachers establish a prosocial peer climate in physical education
Publication date: December 2019Source: Learning and Instruction, Volume 64Author(s): Sung Hyeon Cheon, Johnmarshall Reeve, Nikos NtoumanisAbstractWhen teachers participate in an autonomy-supportive intervention program (ASIP), they learn how to adopt a motivating style toward students that is capable of increasing need satisfaction and decreasing need frustration. Given this, we tested whether an ASIP experience might additionally help teachers establish a peer-to-peer classroom climate that is capable of increasing prosocial behavior and decreasing antisocial behavior. Forty-two secondary grade-level physical education te...
Source: Learning and Instruction - July 13, 2019 Category: Psychiatry & Psychology Source Type: research

Middle school engagement profiles: Implications for motivation and achievement in science
This study identified engagement profiles among middle school students (N = 1125) in science, based on a global, behavioral, cognitive, and affective dimensions of engagement. The relationships between engagement profiles and key motivation predictors (science achievement goal orientations and self-efficacy) and student achievement in science were also examined. Latent profile analysis revealed five distinct science engagement profiles, including Moderately Engaged, Moderately Disengaged, Disengaged, Behaviorally Engaged, and Behaviorally Disengaged. Controlling for grade, gender, and minority status, results showed th...
Source: Learning and Individual Differences - July 13, 2019 Category: Psychiatry & Psychology Source Type: research

Reliability of Radiographic Assessments of the Hip in Cerebral Palsy
Conclusions: MP is a reproducible measure with excellent intrarater and interrater reliability. However, differences in MP of (Source: Journal of Pediatric Orthopaedics)
Source: Journal of Pediatric Orthopaedics - July 13, 2019 Category: Orthopaedics Tags: Cerebral Palsy Source Type: research

Outcomes of Arthroscopy-assisted Closed Reduction and Percutaneous Pinning for a Displaced Pediatric Lateral Condylar Humeral Fracture
Conclusions: We suggested our A/S-CRPP surgical technique for displaced pediatric LCF. It may require a 6-month learning curve period. Although more studies are needed, it seems to be a safe and appropriate surgical technique for treatment. Level of Evidence: Level IV—therapeutic study. (Source: Journal of Pediatric Orthopaedics)
Source: Journal of Pediatric Orthopaedics - July 13, 2019 Category: Orthopaedics Tags: Trauma Source Type: research