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Hojjat Soofi
The traditional researcher-driven environment of medical knowledge production is losing its dominance with the expansion of, for instance, community-based participatory or participant-led medical research. Over the past few decades, sociologists of science have debated a shift in the production of knowledge from traditional discipline-based (Mode 1) to more socially embedded and transdisciplinary frameworks (Mode 2). Recently, scholars have tried to show the relevance of Mode 2 knowledge production to medical research...
December 11, 2017: Journal of Bioethical Inquiry
Barbara Klein, Inga Schlömer
BACKGROUND: Being able to maintain personal hygiene plays a crucial role for independent living in old age or when suffering from disabilities. Within the European project ICT Supported Bath Robots (I‑SUPPORT) an intelligent robotic shower system is being developed, which enables patients to shower independently at home or in institutionalized settings. OBJECTIVE: The aim of this contribution is the identification of ethical issues in the development of a robotic shower system utilizing the model for the ethical evaluation of socio-technical arrangements (MEESTAR)...
December 11, 2017: Zeitschrift Für Gerontologie und Geriatrie
Natasha Mhatre, Robert Malkin, Rittik Deb, Rohini Balakrishnan, Daniel Robert
Object manufacture in insects is typically inherited, and believed to be highly stereotyped. Optimization, the ability to select the functionally best material and modify it appropriately for a specific function, implies flexibility and is usually thought to be incompatible with inherited behaviour. Here we show that tree-crickets optimize acoustic baffles, objects that are used to increase the effective loudness of mate-attraction calls. We quantified the acoustic efficiency of all baffles within the naturally feasible design space using finite-element modelling and found that design affects efficiency significantly...
December 11, 2017: ELife
Rongping Lin, Shan Luo, Haoran Wang, Sheng Wang
Network virtualization technology has been proposed to allow multiple heterogeneous virtual networks (VNs) to coexist on a shared substrate network, which increases the utilization of the substrate network. Efficiently mapping VNs on the substrate network is a major challenge on account of the VN embedding (VNE) problem. Meanwhile, energy efficiency has been widely considered in the network design in terms of operation expenses and the ecological awareness. In this paper, we aim to solve the energy-aware VNE problem in flexi-grid optical networks...
November 27, 2017: Optics Express
Ananth Prakash, Matt Jeffryes, Alex Bateman, Robert D Finn
Protein sequence similarity search is one of the most commonly used bioinformatics methods for identifying evolutionarily related proteins. In general, sequences that are evolutionarily related share some degree of similarity, and sequence-search algorithms use this principle to identify homologs. The requirement for a fast and sensitive sequence search method led to the development of the HMMER software, which in the latest version (v3.1) uses a combination of sophisticated acceleration heuristics and mathematical and computational optimizations to enable the use of profile hidden Markov models (HMMs) for sequence analysis...
December 8, 2017: Current Protocols in Bioinformatics
Yasunari Suzuki, Keisuke Fujii, Masato Koashi
In order to realize fault-tolerant quantum computation, a tight evaluation of the error threshold under practical noise models is essential. While non-Clifford noise is ubiquitous in experiments, the error threshold under non-Clifford noise cannot be efficiently treated with known approaches. We construct an efficient scheme for estimating the error threshold of the one-dimensional quantum repetition code under non-Clifford noise. To this end, we employ the nonunitary free-fermionic formalism for efficient simulation of the one-dimensional repetition code under coherent noise...
November 10, 2017: Physical Review Letters
Jason H Moore, Maksim Shestov, Peter Schmitt, Randal S Olson
A central challenge of developing and evaluating artificial intelligence and machine learning methods for regression and classification is access to data that illuminates the strengths and weaknesses of different methods. Open data plays an important role in this process by making it easy for computational researchers to easily access real data for this purpose. Genomics has in some examples taken a leading role in the open data effort starting with DNA microarrays. While real data from experimental and observational studies is necessary for developing computational methods it is not sufficient...
2018: Pacific Symposium on Biocomputing
Brett K Beaulieu-Jones, Patryk Orzechowski, Jason H Moore
Electronic Health Records (EHRs) contain a wealth of patient data useful to biomedical researchers. At present, both the extraction of data and methods for analyses are frequently designed to work with a single snapshot of a patient's record. Health care providers often perform and record actions in small batches over time. By extracting these care events, a sequence can be formed providing a trajectory for a patient's interactions with the health care system. These care events also offer a basic heuristic for the level of attention a patient receives from health care providers...
2018: Pacific Symposium on Biocomputing
Elisa Omodei, Matthew E Brashears, Alex Arenas
The social brain hypothesis argues that the need to deal with social challenges was key to our evolution of high intelligence. Research with non-human primates as well as experimental and fMRI studies in humans produce results consistent with this claim, leading to an estimate that human primary groups should consist of roughly 150 individuals. Gaps between this prediction and empirical observations can be partially accounted for using "compression heuristics", or schemata that simplify the encoding and recall of social information...
December 7, 2017: Scientific Reports
Yogarabindranath Swarna Nantha
A prescriptive model approach in decision making could help achieve better diagnostic accuracy in clinical practice through methods that are less reliant on probabilistic assessments. Various prescriptive measures aimed at regulating factors that influence heuristics and clinical reasoning could support clinical decision-making process. Clinicians could avoid time-consuming decision-making methods that require probabilistic calculations. Intuitively, they could rely on heuristics to obtain an accurate diagnosis in a given clinical setting...
November 2017: Korean Journal of Family Medicine
Edoardo Serra, Jaideep Vaidya, Haritha Akella, Ashish Sharma
Frequent itemset mining is a fundamental data analytics task. In many cases, due to privacy concerns, only the frequent itemsets are released instead of the underlying data. However, it is not clear how to evaluate the privacy implications of the disclosure of the frequent item-sets. Towards this, in this paper, we define the k-distant-IFM-solutions problem, which aims to find k transaction datasets whose pair distance is maximized. The degree of difference between the reconstructed datasets provides a way to evaluate the privacy risk...
May 2017: ICT Systems Security and Privacy Protection: 32nd IFIP TC 11 International Conference, SEC 2017, Rome, Italy, May 29-31, 2017, Proceedings
Stian Reimers, Chris Donkin, Mike E Le Pelley
When people consider a series of random binary events, such as tossing an unbiased coin and recording the sequence of heads (H) and tails (T), they tend to erroneously rate sequences with less internal structure or order (such as HTTHT) as more probable than sequences containing more structure or order (such as HHHHH). This is traditionally explained as a local representativeness effect: Participants assume that the properties of long sequences of random outcomes-such as an equal proportion of heads and tails, and little internal structure-should also apply to short sequences...
December 1, 2017: Cognition
Stephanie Gee, Morten Skovdal
Background: The 2014-2016 West Africa Ebola Virus Disease (EVD) outbreak was an unprecedented public health event, and in addition to claiming over 11,000 lives, it resulted in the deaths of more healthcare workers than any outbreak in recent history. While a cadre of willing and able health workers is essential for an effective epidemic response, health workforce capacity in times of crisis may be significantly impacted by how risks are perceived by health staff. This study aimed to explore how risk perceptions influenced healthcare workers' willingness to respond during this outbreak...
2017: Global Health Research and Policy
Hassan Emami, Reza Radfar
The current situation in Iran suggests an appropriate basis for developing biotechnology industries, because the patents for the majority of hi-tech medicines registered in developed countries are ending. Biosimilar and technology-oriented companies which do not have patents will have the opportunity to enter the biosimilar market and move toward innovative initiatives. The present research proposed a model by which one can evaluate commercialization of achievements obtained from research with a focus on the pharmaceutical biotechnology industry...
2017: Iranian Journal of Pharmaceutical Research: IJPR
Deirel Paz-Linares, Mayrim Vega-Hernández, Pedro A Rojas-López, Pedro A Valdés-Hernández, Eduardo Martínez-Montes, Pedro A Valdés-Sosa
The estimation of EEG generating sources constitutes an Inverse Problem (IP) in Neuroscience. This is an ill-posed problem due to the non-uniqueness of the solution and regularization or prior information is needed to undertake Electrophysiology Source Imaging. Structured Sparsity priors can be attained through combinations of (L1 norm-based) and (L2 norm-based) constraints such as the Elastic Net (ENET) and Elitist Lasso (ELASSO) models. The former model is used to find solutions with a small number of smooth nonzero patches, while the latter imposes different degrees of sparsity simultaneously along different dimensions of the spatio-temporal matrix solutions...
2017: Frontiers in Neuroscience
S Li, J Latt, B Chopard
The numerical simulation of flow diverters like stents contributes to the development and improvement of endovascular stenting procedures, leading ultimately to an improved treatment of intracranial aneurysms. Due to the scale difference between the struts of flow diverters and the full artery, it is common to avoid fully resolved simulations at the level of the stent porosity. Instead, the effect of stents on the flow is represented by a heuristic continuum model. However, the commonly used porous media models describe the properties of flow diverters only partially, because they do not explicitly account for the deflection of the flow direction by the stent...
December 1, 2017: International Journal for Numerical Methods in Biomedical Engineering
Surama Biswas, Subarna Dutta, Sriyankar Acharyya
Identifying a small subset of disease critical genes out of a large size of microarray gene expression data is a challenge in computational life sciences. This paper has applied four meta-heuristic algorithms, namely, honey bee mating optimization (HBMO), harmony search (HS), differential evolution (DE) and genetic algorithm (basic version GA) to find disease critical genes of preeclampsia which affects women during gestation. Two hybrid algorithms, namely, HBMO-kNN and HS-kNN have been newly proposed here where kNN (k nearest neighbor classifier) is used for sample classification...
December 1, 2017: Interdisciplinary Sciences, Computational Life Sciences
Isabel Segura Bedmar, Paloma Martínez, Adrián Carruana Martín
BACKGROUND: Biomedical semantic indexing is a very useful support tool for human curators in their efforts for indexing and cataloging the biomedical literature. OBJECTIVE: The aim of this study was to describe a system to automatically assign Medical Subject Headings (MeSH) to biomedical articles from MEDLINE. METHODS: Our approach relies on the assumption that similar documents should be classified by similar MeSH terms. Although previous work has already exploited the document similarity by using a k-nearest neighbors algorithm, we represent documents as document vectors by search engine indexing and then compute the similarity between documents using cosine similarity...
December 1, 2017: JMIR Medical Informatics
Jihui Ma, Cuiying Song, Avishai Avi Ceder, Tao Liu, Wei Guan
This work proposes a model considering fairness in the problem of crew scheduling for bus drivers (CSP-BD) using a hybrid ant-colony optimization (HACO) algorithm to solve it. The main contributions of this work are the following: (a) a valid approach for cases with a special cost structure and constraints considering the fairness of working time and idle time; (b) an improved algorithm incorporating Gamma heuristic function and selecting rules. The relationships of each cost are examined with ten bus lines collected from the Beijing Public Transport Holdings (Group) Co...
2017: PloS One
Omid Dehzangi, Mojtaba Taherisadr, Raghvendar ChangalVala
The wide spread usage of wearable sensors such as in smart watches has provided continuous access to valuable user generated data such as human motion that could be used to identify an individual based on his/her motion patterns such as, gait. Several methods have been suggested to extract various heuristic and high-level features from gait motion data to identify discriminative gait signatures and distinguish the target individual from others. However, the manual and hand crafted feature extraction is error prone and subjective...
November 27, 2017: Sensors
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