Ensembled machine learning framework for drug sensitivity prediction
Drug sensitivity prediction is one of the critical tasks involved in drug designing and discovery. Recently several online databases and consortiums have contributed to providing open access to pharmacogenomic data. These databases have helped in developing computational approaches for drug sensitivity prediction. Cancer is a complex disease involving the heterogeneous behaviour of same tumour-type patients towards the same kind of drug therapy. Several methods have been proposed in the literature to predict drug sensitivity. However, these methods are not efficient enough to predict drug sensitivity. The present study has...
Source: IET Systems Biology - January 17, 2020 Category: Biology Source Type: research

Improvement in prediction of antigenic epitopes using stacked generalisation: an ensemble approach
In this study, a hybrid model has been designed by using stacked generalisation ensemble technique for prediction of linear B-cell epitopes. The goal of using stacked generalisation ensemble approach is to refine predictions of base classifiers and to get rid of the worse predictions. In this study, six machine learning models are fused to predict variable length epitopes (6–49 mers). The proposed ensemble model achieves 76.6% accuracy and average accuracy of repeated 10-fold cross-validation is 73.14%. The trained ensemble model has been tested on the benchmark dataset and compared with existing sequential B-cell ep...
Source: IET Systems Biology - January 17, 2020 Category: Biology Source Type: research

What the Baldwin Effect affects depends on the nature of plasticity.
Abstract In a process known as the Baldwin Effect, developmental plasticity, such as learning, has been argued to accelerate the biological evolution of high-fitness traits, including language and complex intelligence. Here we investigate the evolutionary consequences of developmental plasticity by asking which aspects of a plastic trait are the focus of genetic change. The aspects we consider are: (i) dependencies between elements of a trait, (ii) the importance of each element to fitness, and (iii) the difficulty of acquiring each element through plasticity. We also explore (iv) how cultural inheritance changes ...
Source: Cognition - January 17, 2020 Category: Neurology Authors: Morgan TJH, Suchow JW, Griffiths TL Tags: Cognition Source Type: research

Differential effects of corticotropin-releasing factor and acute stress on different forms of risk/reward decision-making.
Abstract Acute stress and corticotropin-releasing factor (CRF) have been show to perturb cost/benefit decision making involving effort costs. However, previous studies on how stress manipulations affect decisions involving reward uncertainty have yielded variable results. To provide additional insight into this issue, the current study investigated how central CRF infusion and acute restraint stress alter different forms of risk/reward decision-making guided by internal representations of risk/reward contingencies or external informative cues. Male rats were well-trained on one of two tasks that required choice be...
Source: Neurobiology of Learning and Memory - January 17, 2020 Category: Neurology Authors: Bryce CA, Adalbert AJ, Claes MM, van Holstein M, Floresco SB Tags: Neurobiol Learn Mem Source Type: research

Machine learning approaches and databases for prediction of drug-target interaction: a survey paper.
Abstract The task of predicting the interactions between drugs and targets plays a key role in the process of drug discovery. There is a need to develop novel and efficient prediction approaches in order to avoid costly and laborious yet not-always-deterministic experiments to determine drug-target interactions (DTIs) by experiments alone. These approaches should be capable of identifying the potential DTIs in a timely manner. In this article, we describe the data required for the task of DTI prediction followed by a comprehensive catalog consisting of machine learning methods and databases, which have been propos...
Source: Briefings in Bioinformatics - January 17, 2020 Category: Bioinformatics Authors: Bagherian M, Sabeti E, Wang K, Sartor MA, Nikolovska-Coleska Z, Najarian K Tags: Brief Bioinform Source Type: research

Deep learning for drug response prediction in cancer.
Abstract Predicting the sensitivity of tumors to specific anti-cancer treatments is a challenge of paramount importance for precision medicine. Machine learning(ML) algorithms can be trained on high-throughput screening data to develop models that are able to predict the response of cancer cell lines and patients to novel drugs or drug combinations. Deep learning (DL) refers to a distinct class of ML algorithms that have achieved top-level performance in a variety of fields, including drug discovery. These types of models have unique characteristics that may make them more suitable for the complex task of modeling...
Source: Briefings in Bioinformatics - January 17, 2020 Category: Bioinformatics Authors: Baptista D, Ferreira PG, Rocha M Tags: Brief Bioinform Source Type: research

IJERPH, Vol. 17, Pages 609: Promoting Social and Emotional Learning and Subjective Well-Being: Impact of the “Aislados” Intervention Program in Adolescents
IJERPH, Vol. 17, Pages 609: Promoting Social and Emotional Learning and Subjective Well-Being: Impact of the “Aislados” Intervention Program in Adolescents International Journal of Environmental Research and Public Health doi: 10.3390/ijerph17020609 Authors: Cejudo Losada Feltrero The aim of this study is to experimentally assess the effects of an intervention program through a video game called “Aislados” for the improvement of subjective well-being, mental health and trait emotional intelligence of a sample of adolescents (n = 187). We used well-established measures ...
Source: International Journal of Environmental Research and Public Health - January 17, 2020 Category: Environmental Health Authors: Cejudo Losada Feltrero Tags: Article Source Type: research

Convolutional Neural Network for Second Metacarpal Radiographic Osteoporosis Screening
Osteoporosis and osteopenia are extremely common and can lead to fragility fractures. The purpose of this study was to determine whether a computer learning system could classify whether a hand radiograph demonstrated osteoporosis based on the second metacarpal cortical percentage. (Source: The Journal of Hand Surgery)
Source: The Journal of Hand Surgery - January 17, 2020 Category: Surgery Authors: Nahom Tecle, Jack Teitel, Michael R. Morris, Numair Sani, David Mitten, Warren C. Hammert Tags: Editor's Choice Source Type: research

Quercetin Alleviates LPS-Induced Depression-Like Behavior in Rats via Regulating BDNF-Related Imbalance of Copine 6 and TREM1/2 in the Hippocampus and PFC
Quercetin is a polyphenol with multiple biological activities, and results of our preliminary study showed that it could shorten the immobility time of mice in the forced swimming test and tail suspending test. The aim of this study was to investigate its effects on the behavioral performance of lipopolysaccharide (LPS)-challenged rats and explore the potential mechanism. The results showed that intragastrical administration of quercetin (40 mg/kg) could improve the bodyweight gain of LPS-challenged rats, increase the saccharin preference index in the saccharin preference test and the novel arm preference index in the Y-ma...
Source: Frontiers in Pharmacology - January 17, 2020 Category: Drugs & Pharmacology Source Type: research

The Learning Curve for Competency in Right Ventricular Longitudinal Strain Analysis
The application of myocardial strain by two-dimensional speckle-tracking to quantify right ventricular (RV) function has recently been endorsed by the American Society of Echocardiography/European Association of Cardiovascular Imaging Joint Industry Task Force, with emphasis on the need for standardization and quality control.1 However, there are no specific recommendations to date for the level of training required for accurate RV strain analysis for independent reporting. Our group has previously demonstrated the existence of a learning curve for left ventricular global longitudinal strain analysis,2 while others have de...
Source: Journal of the American Society of Echocardiography - January 17, 2020 Category: Cardiology Authors: Robert Chamberlain, Gregory M. Scalia, Yong Wee, Su Hlaing, Abbie Lee, Ian Hotham, Estelle Page-Taylor, Surendran Sabapathy, Jonathan Chan Tags: Brief Research Communication Source Type: research

Publication Landscape Analysis on Gliomas: How Much Has Been Done in the Past 25 Years?
Introduction: The body of glioma-related literature has grown significantly over the past 25 years. Despite this growth in the amount of published research, gliomas remain one of the most intransigent cancers. The purpose of this study was to analyze the landscape of glioma-related research over the past 25 years using machine learning and text analysis.Methods: In April 2019, we downloaded glioma-related publications indexed in PubMed between 1994 and 2018. We used Python to extract the title, publication date, MeSH terms, and abstract from the metadata of each publication for bibliometric assessment. Latent Dirichlet all...
Source: Frontiers in Oncology - January 17, 2020 Category: Cancer & Oncology Source Type: research

Dominant parameter of galvanic vestibular stimulation for the non-associative learning processes
AbstractElectrical stimulus is one of the common stimulating methods, and Galvanic vestibular stimulation (GVS) is the oldest form as an electrical stimulation. Nevertheless, GVS is still considered as a secondary stimulating tool for the medical purposes. Even though some unarguable findings have made using GVS, its use has been limited because of its ambiguity as an input source. For better understanding, many previous studies mainly focused on its functional effects, like the ocular reflexes. However, its fundamental effects on the neural activities are still elusive, such as the dominant influences by different paramet...
Source: Medical and Biological Engineering and Computing - January 17, 2020 Category: Biomedical Engineering Source Type: research

Correcting abnormalities in miR ‐124/PTPN1 signaling rescues tau pathology in Alzheimer’s disease
AbstractMicroRNAs have been implicated in diverse physiological and pathological processes. We previously reported that aberrant microRNA ‐124 (miR‐124)/nonreceptor‐type protein phosphatase 1 (PTPN1) signaling plays an important role in the synaptic disorders associated with Alzheimer's disease (AD). In the current study, we further investigated the potential role of miR‐124/PTPN1 in the tau pathology of AD. We first treated t he mice with intrahippocampal stereotactic injections. Then, we used quantitative real‐time reverse transcription PCR (qRT‐PCR) to detect the expression of microRNAs. Western blotting was...
Source: Journal of Neurochemistry - January 17, 2020 Category: Neuroscience Authors: Tong ‐Yao Hou, Yang Zhou, Ling‐Shuang Zhu, Xiong Wang, Pei Pang, Ding‐Qi Wang, Zhen‐Yu Liuyang, Hengye Man, Youming Lu, Ling‐Qiang Zhu, Dan Liu Tags: ORIGINAL ARTICLE Source Type: research

Sensors, Vol. 20, Pages 518: A Method to Estimate Horse Speed per Stride from One IMU with a Machine Learning Method
uline Martin With the emergence of numerical sensors in sports, there is an increasing need for tools and methods to compute objective motion parameters with great accuracy. In particular, inertial measurement units are increasingly used in the clinical domain or the sports one to estimate spatiotemporal parameters. The purpose of the present study was to develop a model that can be included in a smart device in order to estimate the horse speed per stride from accelerometric and gyroscopic data without the use of a global positioning system, enabling the use of such a tool in both indoor and outdoor conditions. The ac...
Source: Sensors - January 17, 2020 Category: Biotechnology Authors: Amandine Schmutz Laurence Ch èze Julien Jacques Pauline Martin Tags: Article Source Type: research

Molecules, Vol. 25, Pages 385: Probabilistic Approach for Virtual Screening Based on Multiple Pharmacophores
ishchuk Pharmacophore modeling is usually considered as a special type of virtual screening without probabilistic nature. Correspondence of at least one conformation of a molecule to pharmacophore is considered as evidence of its bioactivity. We show that pharmacophores can be treated as one-class machine learning models, and the probability the reflecting model’s confidence can be assigned to a pharmacophore on the basis of their precision of active compounds identification on a calibration set. Two schemes (Max and Mean) of probability calculation for consensus prediction based on individual pharmacopho...
Source: Molecules - January 17, 2020 Category: Chemistry Authors: Timur I. Madzhidov Assima Rakhimbekova Alina Kutlushuna Pavel Polishchuk Tags: Communication Source Type: research

The do ’s, don’ts and don’t knows of establishing a sustainable longitudinal integrated clerkship
ConclusionImplementing a  longitudinal integrated clerkship is a complex process requiring the involvement of a wide group of stakeholders in both hospitals and communities. The complexity of the change management processes requires careful and sustained attention, with a particular focus on the outcomes of the programs for students and the communities in which they learn. Effective and consistent leadership and adequate resourcing are important. There is a need to select teaching sites carefully, involve students and faculty in allocation of students to sites and support students and faculty thoug...
Source: Perspectives on Medical Education - January 17, 2020 Category: Universities & Medical Training Source Type: research

Establishing support groups to support parents of preterm babies with retinopathy of prematurity: A pilot study
The objective of establishing ROP parent support groups was to support parents of children with ROP by counseling, information and resource sharing, and general guidance. As part of a major initiative to combat ROP across four states in India, a strategy to develop parent support groups was developed and a pilot project was implemented in three cities. In collaboration with identified eye institutes, five ROP parent support group sessions were conducted in these cities. The concept is still in its initial stages of implementation and data are not yet available on the impact of the support groups. However, the overall turno...
Source: Indian Journal of Ophthalmology - January 17, 2020 Category: Opthalmology Authors: Bala Vidyadhar S Malladi Gowri K Iyer G V S Murthy Clare Gilbert Rajan Shukla Anirudh G Gudlavalleti Pavani Yamarthi Sridivya Mukpalkar Source Type: research

“Hidden” and Diverse Long-Term Impacts of Exposure to War and Violence
Nowadays, the PTSD diagnosis is often a prerequisite for the survivor’s access to specialized treatment services and for obtaining legal recognition or financial compensation when exposed to violence. However, some survivors do not meet all necessary criteria for the PTSD diagnosis, particularly not in the long term. Therefore, they run the risk of being misdiagnosed, inadequately helped or undertreated, and may remain legally unrecognized and unprotected. In this article the “hidden” long-term impacts of exposure to war and violence, beyond the PTSD diagnosis, are presented, discussed, and illustrated wi...
Source: Frontiers in Psychiatry - January 17, 2020 Category: Psychiatry Source Type: research

Learning During Sleep: A Dream Comes True?
Publication date: Available online 15 January 2020Source: Trends in Cognitive SciencesAuthor(s): Simon Ruch, Katharina HenkeCan information that is processed during sleep influence awake behavior? Recent research demonstrates that learning during sleep is possible, but that sleep-learning invariably produces memory traces that are consciously inaccessible in the awake state. Thus, sleep-learning can likely exert implicit, but not explicit, influences on awake behavior. (Source: Trends in Cognitive Sciences)
Source: Trends in Cognitive Sciences - January 16, 2020 Category: Psychiatry & Psychology Source Type: research

Does choice matter or is it all about interest? An investigation using an experience sampling approach in high school science classrooms
Publication date: February 2020Source: Learning and Individual Differences, Volume 78Author(s): Patrick N. Beymer, Joshua M. Rosenberg, Jennifer A. SchmidtAbstractHaving choices during learning is often touted as beneficial for student motivation. However, it is not clear whether the motivating factor is choice or the act of pursuing tasks that are of greater interest, which is often afforded by choice. Using data collected via the Experience Sampling Method from 244 youth (ages 14–18) in the United States, we explore the effects of choice and interest on student engagement, affect, and learning in multiple high scho...
Source: Learning and Individual Differences - January 16, 2020 Category: Psychiatry & Psychology Source Type: research

The stability and trajectories of teacher expectations: Student achievement level as a moderator
Publication date: February 2020Source: Learning and Individual Differences, Volume 78Author(s): Shengnan Wang, Christine M. Rubie-Davies, Kane MeisselAbstractUsing three time points of teacher expectation data, this study aimed to examine the stability and trajectories of teacher expectations within a school year in the Chinese junior high school context. The participants were 48 Chinese, mathematics, and English teachers and their 1199 students from 10 junior high schools. The issue of the stability of teacher expectations was explored at individual-student level and student-group level, respectively. Spearman's rank orde...
Source: Learning and Individual Differences - January 16, 2020 Category: Psychiatry & Psychology Source Type: research

Multilevel and Multiscale Feature Aggregation in Deep Networks for Facial Constitution Classification.
Authors: Huan EY, Wen GH Abstract Constitution classification is the basis and core content of TCM constitution research. In order to improve the accuracy of constitution classification, this paper proposes a multilevel and multiscale features aggregation method within the convolutional neural network, which consists of four steps. First, it uses the pretrained VGG16 as the basic network and then refines the network structure through supervised feature learning so as to capture local image features. Second, it extracts the image features of different layers from the fine-tuned VGG16 model, which are then dimensiona...
Source: Computational and Mathematical Methods in Medicine - January 16, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Gait Biomarkers Classification by Combining Assembled Algorithms and Deep Learning: Results of a Local Study.
Authors: Sánchez-DelaCruz E, Weber R, Biswal RR, Mejía J, Hernández-Chan G, Gómez-Pozos H Abstract Machine learning, one of the core disciplines of artificial intelligence, is an approach whose main emphasis is analytical model building. In other words, machine learning enables an automaton to make its own decisions based on a previous training process. Machine learning has revolutionized every research sector, including health care, by providing precise and accurate decisions involving minimal human interventions through pattern recognition. This is emphasized in this research, which ad...
Source: Computational and Mathematical Methods in Medicine - January 16, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Using clickstream data to measure, understand, and support self-regulated learning in online courses
This study used the clickstream data collected from a learning management system to measure two aspects of SRL: time management and effort regulation. We found that the clickstream measures were significantly associated with students' self-reported time management and effort regulation after the course. In addition, these clickstream measures significantly improved predictions of students' performance in the current and subsequent courses over predictions based on self-reported measures alone. These results provide evidence for the validity of the clickstream measures and guide the use of clickstream data to understand the...
Source: The Internet and Higher Education - January 16, 2020 Category: Information Technology Source Type: research

Donepezil Attenuates Obesity-Associated Oxidative Stress and Central Inflammation and Improves Memory Deficit in Mice Fed a High-Fat Diet.
CONCLUSION: Our results indicate that donepezil may reverse obesity-related central inflammation and oxidative damage and improve memory deficit in HFD-fed mice. PMID: 31940604 [PubMed - as supplied by publisher] (Source: Dementia and Geriatric Cognitive Disorders)
Source: Dementia and Geriatric Cognitive Disorders - January 16, 2020 Category: Psychiatry Tags: Dement Geriatr Cogn Disord Source Type: research

Food Allergy Prevention: More Than Peanut
Publication date: January 2020Source: The Journal of Allergy and Clinical Immunology: In Practice, Volume 8, Issue 1Author(s): Michael R. Perkin, Alkis Togias, Jennifer Koplin, Scott SichererGiven an apparent increase in food allergies worldwide, the focus on prevention strategies has intensified. Following the Learning Early About Peanut study, there is now a widespread acceptance that peanut should be introduced promptly into the diet of high-risk infants. However, most food allergies are caused by triggers other than peanut and additional prevention strategies are being evaluated. The appreciation of the role of an impa...
Source: The Journal of Allergy and Clinical Immunology: In Practice - January 16, 2020 Category: Allergy & Immunology Source Type: research

Similar impairments shown on a neuropsychological test battery in adolescents with high-functioning autism and early onset schizophrenia: a two-year follow-up study.
Conclusion: The findings suggest that it may be difficult to differentiate adolescents with EOS and ASD based on neuropsychological task performance. An implication of the results is that adolescents with either disorder may benefit from a similar approach to the treatment of cognitive impairment in the disorders. PMID: 31931670 [PubMed - as supplied by publisher] (Source: Cognitive Neuropsychiatry)
Source: Cognitive Neuropsychiatry - January 16, 2020 Category: Psychiatry Tags: Cogn Neuropsychiatry Source Type: research

[Male to female sex reassignment surgery with a new surgical simulation device using a human perfused cadaver SIMLIFE ®: New paradigm in transsexual surgery education ?]
CONCLUSION: We demonstrated the feasibility of vaginoplasty performed on a humanoid model SIMLIFE® and highlighted improvement of the surgical skills with this model. This technology could find many other surgical applications. However, it faces cost constraints and legislation on corpses. PMID: 31932042 [PubMed - as supplied by publisher] (Source: Progres en Urologie)
Source: Progres en Urologie - January 16, 2020 Category: Urology & Nephrology Tags: Prog Urol Source Type: research

Dopamine-Evoked Synaptic Regulation in the Nucleus Accumbens Requires Astrocyte Activity
Publication date: Available online 15 January 2020Source: NeuronAuthor(s): Michelle Corkrum, Ana Covelo, Justin Lines, Luigi Bellocchio, Marc Pisansky, Kelvin Loke, Ruth Quintana, Patrick E. Rothwell, Rafael Lujan, Giovanni Marsicano, Eduardo D. Martin, Mark J. Thomas, Paulo Kofuji, Alfonso AraqueSummaryDopamine is involved in physiological processes like learning and memory, motor control and reward, and pathological conditions such as Parkinson’s disease and addiction. In contrast to the extensive studies on neurons, astrocyte involvement in dopaminergic signaling remains largely unknown. Using transgenic mice, opt...
Source: Neuron - January 16, 2020 Category: Neuroscience Source Type: research

Integration of an Actor-Critic Model and Generative Adversarial Networks for a Chinese Calligraphy Robot
Publication date: Available online 16 January 2020Source: NeurocomputingAuthor(s): Ruiqi Wu, Changle Zhou, Fei Chao, Longzhi Yang, Chih-Min Lin, Changjing ShangAbstractAs a combination of robotic motion planning and Chinese calligraphy culture, robotic calligraphy plays a significant role in the inheritance and education of Chinese calligraphy culture. Most existing calligraphy robots focus on enabling the robots to learn writing through human participation, such as human-robot interactions and manually designed evaluation functions. However, because of the subjectivity of art aesthetics, these existing methods require a l...
Source: Neurocomputing - January 16, 2020 Category: Neuroscience Source Type: research

Human skeleton mutual learning for person re-identification
Publication date: Available online 16 January 2020Source: NeurocomputingAuthor(s): Ziyang Wang, Dan Wei, Xiaoqiang Hu, Yiping LuoAbstractPerson re-identification refers to matching people across non-overlapping camera views on different locations and at different times. In the case of changes in perspective, light, background, veil, and person's clothing, traditional method can't achieve person recognition effectively and reliably. In this paper, we propose a novel biometric metric learning method named Human Skeleton Mutual Learning person re-identification (HSMLP-Reid). The purpose of HSML person re-identification method...
Source: Neurocomputing - January 16, 2020 Category: Neuroscience Source Type: research

Prevalence and curriculum of sexual and gender minority education in Japanese medical school and future direction.
Conclusions: Students can best experience the humanity of SGM patients and employ more appropriate diagnostic practices and modes of treatment with targeted curriculum to address SGM health disparities and inclusion of SGM patients in clinical practice training. To disseminate SGM education in Japanese medical schools, development of qualified instructors and policies is essential, employing currently active experts. The Van Melle reforms framework can guide in the development of recommended tailored learning experiences and lectures for improved and expanded SGM education, integrating appropriate coursework within current...
Source: Medical Education Online - January 16, 2020 Category: Universities & Medical Training Tags: Med Educ Online Source Type: research

Comment on: creating assessments as an active learning strategy: what are students' perceptions? A mixed methods study.
Authors: Belshaw A, Mackie A, Phillips HK, Rodrigues H, Russell A PMID: 31931682 [PubMed - in process] (Source: Medical Education Online)
Source: Medical Education Online - January 16, 2020 Category: Universities & Medical Training Tags: Med Educ Online Source Type: research

Determining the optimal learning rate in gradient-based electromagnetic optimization using the Shanks transformation in the Lippmann – Schwinger formalism
In gradient-based optimization of photonic devices, within the overall design parameter space, one iteratively performs a line search in a ... (Source: Optics Letters)
Source: Optics Letters - January 16, 2020 Category: Physics Authors: Salim Boutami Nathan Zhao Shanhui Fan Source Type: research

Artificial Intelligence in Medical Education
I read the article by Noorbakhsh-Sabet et al,1 which focuses on the applications of artificial intelligence (AI) in medicine with great interest. In the article, the authors focused mainly on the clinical applications, translation, and public health relevance of machine learning. In this article, I will mention the application of AI in medical education, as this is critical for the future development of medicine and health care. AI techniques can be implemented at 3 levels of medical education: curriculum development and analysis, learning, and assessment. (Source: The American Journal of Medicine)
Source: The American Journal of Medicine - January 16, 2020 Category: General Medicine Authors: Tushar Garg, Tags: Letter Source Type: research

The Relationship Between a Charity Crowdfunding Project’s Contents and Donors’ Participation: An Empirical Study with Deep Learning Methodologies
Publication date: Available online 14 January 2020Source: Computers in Human BehaviorAuthor(s): DongIl Lee, JaeHong Park (Source: Computers in Human Behavior)
Source: Computers in Human Behavior - January 16, 2020 Category: Information Technology Source Type: research

Too Many Definitions of Sepsis: Can Machine Learning Leverage the Electronic Health Record to Increase Accuracy and Bring Consensus?
No abstract available (Source: Critical Care Medicine)
Source: Critical Care Medicine - January 16, 2020 Category: Emergency Medicine Tags: Foreword Source Type: research

[ASAP] Characterizing Protein –Ligand Binding Using Atomistic Simulation and Machine Learning: Application to Drug Resistance in HIV-1 Protease
Journal of Chemical Theory and ComputationDOI: 10.1021/acs.jctc.9b00781 (Source: Journal of Chemical Theory and Computation)
Source: Journal of Chemical Theory and Computation - January 16, 2020 Category: Chemistry Authors: Troy W. Whitfield* †?, Debra A. Ragland‡¶, Konstantin B. Zeldovich§?, and Celia A. Schiffer*‡ Source Type: research

Learning-based method to reconstruct complex targets through scattering medium beyond the memory effect
Strong scattering medium brings great difficulties to image objects. Optical memory effect makes it possible to image through strong random ... (Source: Optics Express)
Source: Optics Express - January 16, 2020 Category: Physics Authors: Enlai Guo Shuo Zhu Yan Sun Lianfa Bai Chao Zuo Jing Han Source Type: research

CMOS camera based visible light communication (VLC) using grayscale value distribution and machine learning algorithm
We demonstrate a visible light communication (VLC) system using light emitting diode (LED) backlight display panel and mobile-phone ... (Source: Optics Express)
Source: Optics Express - January 16, 2020 Category: Physics Authors: Ke-Ling Hsu Yu-Chun Wu Yu-Cheng Chuang Chi-Wai Chow Yang Liu Xin-Lan Liao Kun-Hsien Lin Yi-Yuan Chen Source Type: research

Application of machine learning to predict monomer retention of therapeutic proteins after long term storage
Publication date: Available online 15 January 2020Source: International Journal of PharmaceuticsAuthor(s): Lorenzo Gentiluomo, Dierk Roessner, Wolfgang FrießAbstractAn important aspect of initial developability assessments as well formulation development and selection of therapeutic proteins is the evaluation of data obtained under accelerated stress condition, i.e. at elevated temperatures. We propose the application of artificial neural networks (ANNs) to predict long term stability in real storage condition from accelerated stability studies and other high-throughput biophysical properties e.g. the first apparent ...
Source: International Journal of Pharmaceutics - January 16, 2020 Category: Drugs & Pharmacology Source Type: research

Online audiovisual resources for learning the disinfection protocol for dental impressions: A critical analysis
ConclusionsAudiovisual online resources on dental impression disinfection includes incomplete information with limited usefulness and reliability. The number of views was not related to quality, and therefore, many viewers may be obtaining knowledge from substandard material. (Source: The Journal of Prosthetic Dentistry)
Source: The Journal of Prosthetic Dentistry - January 16, 2020 Category: Dentistry Source Type: research

Hippocampal Ripple Coordinates Retrosplenial Inhibitory Neurons during Slow-Wave Sleep
Publication date: 14 January 2020Source: Cell Reports, Volume 30, Issue 2Author(s): Ashley N. Opalka, Wen-qiang Huang, Jun Liu, Hualou Liang, Dong V. WangSummaryThe hippocampus and retrosplenial cortex (RSC) play indispensable roles in memory formation, and importantly, a hippocampal oscillation known as ripple is key to consolidation of new memories. However, it remains unclear how the hippocampus and RSC communicate and the role of ripple oscillation in coordinating the activity between these two brain regions. Here, we record from the dorsal hippocampus and RSC simultaneously in freely behaving mice during sleep and rev...
Source: Cell Reports - January 16, 2020 Category: Cytology Source Type: research

Mouse Ovarian Cancer Models Recapitulate the Human Tumor Microenvironment and Patient Response to Treatment
Publication date: 14 January 2020Source: Cell Reports, Volume 30, Issue 2Author(s): Eleni Maniati, Chiara Berlato, Ganga Gopinathan, Owen Heath, Panoraia Kotantaki, Anissa Lakhani, Jacqueline McDermott, Colin Pegrum, Robin M. Delaine-Smith, Oliver M.T. Pearce, Priyanka Hirani, Joash D. Joy, Ludmila Szabova, Ruth Perets, Owen J. Sansom, Ronny Drapkin, Peter Bailey, Frances R. BalkwillSummaryAlthough there are many prospective targets in the tumor microenvironment (TME) of high-grade serous ovarian cancer (HGSOC), pre-clinical testing is challenging, especially as there is limited information on the murine TME. Here, we...
Source: Cell Reports - January 16, 2020 Category: Cytology Source Type: research

Multi-view Feature Selection via Nonnegative Structured Graph Learning
Publication date: Available online 14 January 2020Source: NeurocomputingAuthor(s): Xiangpin Bai, Lei Zhu, Cheng Liang, Jingjing Li, Xiushan Nie, Xiaojun ChangAbstractGraph-based solutions have achieved state-of-the-art performance on unsupervised multi-view feature selection. However, existing methods generally characterize the sample similarities first by constructing multiple fixed graphs with manually determined parameters, and then perform the feature selection on a composite one. They will suffer from two severe problems: 1) The fixed graphs may be unreliable as the raw multi-view features usually contain adverse nois...
Source: Neurocomputing - January 16, 2020 Category: Neuroscience Source Type: research

Adversarial dictionary learning for a robust analysis and modelling of spontaneous neuronal activity
The objective of this work is to discover directly from the experimental data rich and comprehensible models for brain function that will be concurrently robust to noise. Considering this task from the perspective of dimensionality reduction, we develop an innovative, robust to noise dictionary learning framework based on adversarial training methods for the identification of patterns of synchronous firing activity as well as within a time lag. We employ real-world binary datasets describing the spontaneous neuronal activity of laboratory mice over time, and we aim to their efficient low-dimensional representation. The res...
Source: Neurocomputing - January 16, 2020 Category: Neuroscience Source Type: research

A Novel Patch-based Nonlinear Matrix Completion Algorithm for Image Analysis through Convolutional Neural Network
Publication date: Available online 14 January 2020Source: NeurocomputingAuthor(s): Mingming Yang, Songhua XuAbstractMatrix completion is extensively studied due to its wide applications in science and technology. In this paper, we concentrate our study on the matrix completion problem for image analysis tasks due to their immense importance and pervasive use in many fields. A rich collection of models has been proposed to capture both linear and nonlinear relationships latent in a matrix. Even though nonlinear models possess more powerful matrix completion capabilities than their linear counterparts, these models generally...
Source: Neurocomputing - January 16, 2020 Category: Neuroscience Source Type: research

Dialogue Systems with Audio Context
Publication date: Available online 14 January 2020Source: NeurocomputingAuthor(s): Tom Young, Vlad Pandelea, Soujanya Poria, Erik CambriaAbstractResearch on building dialogue systems that converse with humans naturally has recently attracted a lot of attention. Most work on this area assumes text-based conversation, where the user message is modeled as a sequence of words in a vocabulary. Real-world human conversation, in contrast, involves other modalities, such as voice, facial expression and body language, which can influence the conversation significantly in certain scenarios. In this work, we explore the impact of inc...
Source: Neurocomputing - January 16, 2020 Category: Neuroscience Source Type: research

Empirical Mode Decomposition Based Multi-objective Deep Belief Network for Short-term Power Load Forecasting
Publication date: Available online 15 January 2020Source: NeurocomputingAuthor(s): Chaodong Fan, Changkun Ding, Jinhua Zheng, Leyi Xiao, Zhaoyang AiAbsrtactWith the rapid development of power grid data, the data generated by the operation of the power system is increasingly complex, and the amount of data increases exponentially. In order to fully exploit and utilize the deep relationship between data to achieve accurate prediction of power load, this paper proposes an Empirical Mode Decomposition Based Multi-objective Deep Belief Network prediction method (EMD-MODBN). In the training process of DBN, a multi-objective opti...
Source: Neurocomputing - January 16, 2020 Category: Neuroscience Source Type: research

A Cross-modal Adaptive Gated Fusion Generative Adversarial Network for RGB-D Salient Object Detection
Publication date: Available online 15 January 2020Source: NeurocomputingAuthor(s): Zhengyi Liu, Wei Zhang, Peng ZhaoAbstractSalient object detection in RGB-D images aims to identify the most attractive objects in a pair of color and depth images for the observer. As an important branch of salient object detection, it focuses on solving the following two major challenges: how to achieve cross-modal fusion that is efficient and beneficial for salient object detection; how to effectively extract the information of depth image with relatively poor quality. This paper proposes a cross-modal adaptive gated fusion generative adve...
Source: Neurocomputing - January 16, 2020 Category: Neuroscience Source Type: research