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Amanda L Thayer, Alexandra Petruzzelli, Caitlin E McClurg
Facilitating team innovation is paramount to promoting progress in the science, technology, engineering, and math fields, as well as advancing national health, safety, prosperity, and welfare. However, innovation teams face a unique set of challenges due to the novelty and uncertainty that is core to the definition of innovation, as well as the paradoxical nature of idea generation and idea implementation processes. These and other challenges must be overcome for innovation teams to realize their full potential for producing change...
May 2018: American Psychologist
Marion M Hetherington, Pam Blundell-Birtill, Samantha J Caton, Joanne E Cecil, Charlotte E Evans, Barbara J Rolls, Tang Tang
Offering large portions of high-energy-dense (HED) foods increases overall intake in children and adults. This is known as the portion size effect (PSE). It is robust, reliable and enduring. Over time, the PSE may facilitate overeating and ultimately positive energy balance. Therefore, it is important to understand what drives the PSE and what might be done to counter the effects of an environment promoting large portions, especially in children. Explanations for the PSE are many and diverse, ranging from consumer error in estimating portion size to simple heuristics such as cleaning the plate or eating in accordance with consumption norms...
May 24, 2018: Proceedings of the Nutrition Society
Vadim Gliner, Joachim Behar, Yael Yaniv
BACKGROUND: In parallel to the introduction of mobile communication devices with high computational power and internet connectivity, high-quality and low-cost health sensors have also become available. However, although the technology does exist, no clinical mobile system has been developed to monitor the R peaks from electrocardiogram recordings in real time with low false positive and low false negative detection. Implementation of a robust electrocardiogram R peak detector for various arrhythmogenic events has been hampered by the lack of an efficient design that will conserve battery power without reducing algorithm complexity or ease of implementation...
May 22, 2018: JMIR MHealth and UHealth
Runze Dong, Shuo Pan, Zhenling Peng, Yang Zhang, Jianyi Yang
With the rapid increase of the number of protein structures in the Protein Data Bank, it becomes urgent to develop algorithms for efficient protein structure comparisons. In this article, we present the mTM-align server, which consists of two closely related modules: one for structure database search and the other for multiple structure alignment. The database search is speeded up based on a heuristic algorithm and a hierarchical organization of the structures in the database. The multiple structure alignment is performed using the recently developed algorithm mTM-align...
May 21, 2018: Nucleic Acids Research
Shaojie Tang, Kuidong Huang, Yunyong Cheng, Tianye Niu, Xiangyang Tang
GOALS: With substantially increased number of detector rows in multidetector CT (MDCT), axial scan with projection data acquired along a circular source trajectory has become the method-of-choice in increasing clinical applications. Recognizing the practical relevance of image reconstruction directly from the projection data acquired in the native cone beam (CB) geometry, especially in scenarios wherein the most achievable in-plane resolution is desirable, we present a three-dimensional (3-D) weighted CB-FBP algorithm in such geometry in this paper...
June 2018: IEEE Transactions on Bio-medical Engineering
Iwo Błądek, Krzysztof Krawiec, Jerry Swan
Conventional genetic programming (GP) can only guarantee that synthesized programs pass tests given by the provided input-output examples. The alternative to such test-based approach is synthesizing programs by formal specification, typically realized with exact, non-heuristic algorithms. In this paper, we build on our earlier study on Counterexample-Based Genetic Programming (CDGP), an evolutionary heuristic that synthesizes programs from formal specifications. The candidate programs in CDGP undergo formal verification with a Satisfiability Modulo Theory (SMT) solver, which results in counterexamples that are subsequently turned into tests and used to calculate fitness...
May 22, 2018: Evolutionary Computation
Arnaud Rey, Laure Minier, Raphaëlle Malassis, Louisa Bogaerts, Joël Fagot
Extracting the regularities of our environment is a core cognitive ability in human and non-human primates. Comparative studies may provide information of strong heuristic value to constrain the elaboration of computational models of regularity learning. This study illustrates this point by testing human and non-human primates (Guinea baboons, Papio papio) with the same experimental paradigm, using a novel online learning measure. For local co-occurrence regularities, we found similar patterns of regularity extraction in baboons and humans...
May 21, 2018: Topics in Cognitive Science
Paola Lecca
We implement a Monte Carlo heuristic algorithm to model drug release from a solid dosage form. We show that with Monte Carlo simulations it is possible to identify and explain the causes of the unsatisfactory predictive power of current drug release models. It is well known that the power-law, the exponential models, as well as those derived from or inspired by them accurately reproduce only the first 60% of the release curve of a drug from a dosage form. In this study, by using Monte Carlo simulation approaches, we show that these models fit quite accurately almost the entire release profile when the release kinetics is not governed by the coexistence of different physico-chemical mechanisms...
2018: MethodsX
Marja Laasonen, Sini Smolander, Pekka Lahti-Nuuttila, Miika Leminen, Hanna-Reetta Lajunen, Kati Heinonen, Anu-Katriina Pesonen, Todd M Bailey, Emmanuel M Pothos, Teija Kujala, Paavo H T Leppänen, Christopher W Bartlett, Ahmed Geneid, Leena Lauronen, Elisabet Service, Sari Kunnari, Eva Arkkila
BACKGROUND: Developmental language disorder (DLD, also called specific language impairment, SLI) is a common developmental disorder comprising the largest disability group in pre-school-aged children. Approximately 7% of the population is expected to have developmental language difficulties. However, the specific etiological factors leading to DLD are not yet known and even the typical linguistic features appear to vary by language. We present here a project that investigates DLD at multiple levels of analysis and aims to make the reliable prediction and early identification of the difficulties possible...
May 21, 2018: BMC Psychology
Hirotaka Saito, Seiichiro Kuroda, Toshiki Iwasaki, Haruyuki Fujimaki, Nobuhito Nagai, Jacopo Sala
A Ground Penetrating Radar (GPR) system based on a ground-coupled, densely populated antenna array was used to collect data during an infiltration experiment conducted at a test site near the Tottori Sand Dune, Japan. The antenna array used in this study consists of 10 transmitting antennas (Tx) and 11 receiving antennas (Rx). For this experiment, the system was configured to use all possible Tx-Rx pairings, resulting in a Multi-Offset Gather (MOG) consisting of 110 Tx-Rx combinations. The array was left stationary at a position directly above the infiltration area and data were collected every 1...
May 1, 2018: Journal of Visualized Experiments: JoVE
Carlos Alberto da Silva Magliano, Andrea Liborio Monteiro, Bernardo Rangel Tura, Claudia Silvia Rocha Oliveira, Amanda Rebeca de Oliveira Rebelo, Claudia Cristina de Aguiar Pereira
Purpose: Communicating information about risk and probability to patients is considered a difficult task. In this study, we aim to evaluate the use of visual aids representing perioperative mortality and long-term survival in the communication process for patients diagnosed with coronary artery disease at the National Institute of Cardiology, a Brazilian public hospital specializing in cardiology. Patients and methods: One-on-one interviews were conducted between August 1 and November 20, 2017...
2018: Patient Preference and Adherence
Jiannan Wang, Sen Pei, Wei Wei, Xiangnan Feng, Zhiming Zheng
Boolean networks have attracted much attention due to their wide applications in describing dynamics of biological systems. During past decades, much effort has been invested in unveiling how network structure and update rules affect the stability of Boolean networks. In this paper, we aim to identify and control a minimal set of influential nodes that is capable of stabilizing an unstable Boolean network. For locally treelike Boolean networks with biased truth tables, we propose a greedy algorithm to identify influential nodes in Boolean networks by minimizing the largest eigenvalue of a modified nonbacktracking matrix...
March 2018: Physical Review. E
Alexander B Swan, Dustin P Calvillo, Russell Revlin
When faced with a decision, people generally show a bias toward heuristic processing, even if it leads to the incorrect decision, such as in the base-rate neglect task. The crucial question is whether people know that they are biased. Recently, the three-stage model (Pennycook, Fugelsang, & Koehler, 2015) suggested that detecting this bias (conflict detection) is imperfect and a consistent source of bias because some people do not recognize that they are making biased decisions. In Experiment 1, participants completed a base-rate neglect task as replication of Pennycook et al...
May 15, 2018: Acta Psychologica
Andreas Stang, Christopher Baethge
Background: Results of randomized controlled trials (RCTs) are usually accompanied by a table that compares covariates between the study groups at baseline. Sometimes, the investigators report p values for imbalanced covariates. The aim of this debate is to illustrate the pro and contra of the use of these p values in RCTs. Pro: Low p values can be a sign of biased or fraudulent randomization and can be used as a warning sign. They can be considered as a screening tool with low positive-predictive value...
2018: Clinical Epidemiology
Alexandre Lomsadze, Karl Gemayel, Shiyuyun Tang, Mark Borodovsky
In a conventional view of the prokaryotic genome organization, promoters precede operons and RBS sites with Shine-Dalgarno consensus precede genes. However, recent experimental research suggesting a more diverse view motivated us to develop an algorithm with improved gene-finding accuracy. We describe GeneMarkS 2, an ab initio algorithm that uses a model derived by self-training for finding species-specific (native) genes, along with an array of pre-computed "heuristic" models designed to identify harder-to-detect genes (likely horizontally transferred)...
May 17, 2018: Genome Research
Phil Maguire, Philippe Moser, Rebecca Maguire, Mark T Keane
While seemingly a ubiquitous cognitive process, the precise definition and function of surprise remains elusive. Surprise is often conceptualized as being related to improbability or to contrasts with higher probability expectations. In contrast to this probabilistic view, we argue that surprising observations are those that undermine an existing model, implying an alternative causal origin. Surprises are not merely improbable events; instead, they indicate a breakdown in the model being used to quantify probability...
May 17, 2018: Topics in Cognitive Science
Kamal Z Zamli, Fakhrud Din, Bestoun S Ahmed, Miroslav Bures
The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. In addition to exploiting sine and cosine functions to perform local and global searches (hence the name sine-cosine), the SCA introduces several random and adaptive parameters to facilitate the search process. Although it shows promising results, the search process of the SCA is vulnerable to local minima/maxima due to the adoption of a fixed switch probability and the bounded magnitude of the sine and cosine functions (from -1 to 1)...
2018: PloS One
Isaac J Sledge, Matthew S Emigh, Jose C Principe
Reinforcement learning in environments with many action-state pairs is challenging. The issue is the number of episodes needed to thoroughly search the policy space. Most conventional heuristics address this search problem in a stochastic manner. This can leave large portions of the policy space unvisited during the early training stages. In this paper, we propose an uncertainty-based, information-theoretic approach for performing guided stochastic searches that more effectively cover the policy space. Our approach is based on the value of information, a criterion that provides the optimal tradeoff between expected costs and the granularity of the search process...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
Alexander Ratner, Stephen H Bach, Henry Ehrenberg, Jason Fries, Sen Wu, Christopher Ré
Labeling training data is increasingly the largest bottleneck in deploying machine learning systems. We present Snorkel, a first-of-its-kind system that enables users to train state-of- the-art models without hand labeling any training data. Instead, users write labeling functions that express arbitrary heuristics, which can have unknown accuracies and correlations. Snorkel denoises their outputs without access to ground truth by incorporating the first end-to-end implementation of our recently proposed machine learning paradigm, data programming...
November 2017: Proceedings of the VLDB Endowment
Eunjoo Jeon, Hyeoun-Ae Park
Objectives: This study developed a diabetes self-management mobile application based on the information-motivation-behavioral skills (IMB) model, evidence extracted from clinical practice guidelines, and requirements identified through focus group interviews (FGIs) with diabetes patients. Methods: We developed a diabetes self-management (DSM) app in accordance with the following four stages of the system development life cycle. The functional and knowledge requirements of the users were extracted through FGIs with 19 diabetes patients...
April 2018: Healthcare Informatics Research
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