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Overcoming Data Scarcity in Earth Science

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ISBN: 9783039282104 / 9783039282111 Year: Pages: 94 DOI: 10.3390/books978-3-03928-211-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2020-06-09 16:38:57
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heavily Environmental mathematical models represent one of the key aids for scientists to forecast, create, and evaluate complex scenarios. These models rely on the data collected by direct field observations. However, assembly of a functional and comprehensive dataset for any environmental variable is difficult, mainly because of i) the high cost of the monitoring campaigns and ii) the low reliability of measurements (e.g., due to occurrences of equipment malfunctions and/or issues related to equipment location). The lack of a sufficient amount of Earth science data may induce an inadequate representation of the response’s complexity in any environmental system to any type of input/change, both natural and human-induced. In such a case, before undertaking expensive studies to gather and analyze additional data, it is reasonable to first understand what enhancement in estimates of system performance would result if all the available data could be well exploited. Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. Different approaches are available to deal with missing data. Traditional statistical data completion methods are used in different domains to deal with single and multiple imputation problems. More recently, machine learning techniques, such as clustering and classification, have been proposed to complete missing data. This book showcases the body of knowledge that is aimed at improving the capacity to exploit the available data to better represent, understand, predict, and manage the behavior of environmental systems at all practical scales.

Systems Analytics and Integration of Big Omics Data

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ISBN: 9783039287444 / 9783039287451 Year: Pages: 202 DOI: 10.3390/books978-3-03928-745-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Medicine (General) --- Therapeutics
Added to DOAB on : 2020-06-09 16:38:57
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A “genotype"" is essentially an organism's full hereditary information which is obtained from its parents. A ""phenotype"" is an organism's actual observed physical and behavioral properties. These may include traits such as morphology, size, height, eye color, metabolism, etc. One of the pressing challenges in computational and systems biology is genotype-to-phenotype prediction. This is challenging given the amount of data generated by modern Omics technologies. This “Big Data” is so large and complex that traditional data processing applications are not up to the task. Challenges arise in collection, analysis, mining, sharing, transfer, visualization, archiving, and integration of these data. In this Special Issue, there is a focus on the systems-level analysis of Omics data, recent developments in gene ontology annotation, and advances in biological pathways and network biology. The integration of Omics data with clinical and biomedical data using machine learning is explored. This Special Issue covers new methodologies in the context of gene–environment interactions, tissue-specific gene expression, and how external factors or host genetics impact the microbiome.

Keywords

tissue-specific expressed genes --- transcriptome --- tissue classification --- support vector machine --- feature selection --- bioinformatics pipelines --- algorithm development for network integration --- miRNA–gene expression networks --- multiomics integration --- network topology analysis --- candidate genes --- gene–environment interactions --- logic forest --- systemic lupus erythematosus --- Gene Ontology --- KEGG pathways --- enrichment analysis --- proteomic analysis --- plot visualization --- Alzheimer’s disease --- dementia --- cognitive impairment --- neurodegeneration --- Gene Ontology --- annotation --- biocuration --- amyloid-beta --- microtubule-associated protein tau --- artificial intelligence --- genotype --- phenotype --- deep phenotype --- data integration --- genomics --- phenomics --- precision medicine informatics --- epigenetics --- chromatin modification --- sequencing --- regulatory genomics --- disease variants --- machine learning --- multi-omics --- data integration --- curse of dimensionality --- heterogeneous data --- missing data --- class imbalance --- scalability --- genomics --- pharmacogenomics --- cell lines --- database --- drug sensitivity --- data integration --- omics data --- genomics --- RNA expression --- non-omics data --- clinical data --- epidemiological data --- challenges --- integrative analytics --- joint modeling --- multivariate analysis --- multivariate causal mediation --- distance correlation --- direct effect --- indirect effect --- causal inference --- n/a

Human Mobility, Spatiotemporal Context, and Environmental Health: Recent Advances in Approaches and Methods

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ISBN: 9783039211838 9783039211845 Year: Pages: 382 DOI: 10.3390/books978-3-03921-184-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Medicine (General)
Added to DOAB on : 2019-08-28 11:21:27
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Environmental health researchers have long used concepts like the neighborhood effect to assessing people’s exposure to environmental influences and the associated health impact. However, these are static notions that ignore people’s daily mobility at various spatial and temporal scales (e.g., daily travel, migratory movements, and movements over the life course) and the influence of neighborhood contexts outside their residential neighborhoods. Recent studies have started to incorporate human mobility, non-residential neighborhoods, and the temporality of exposures through collecting and using data from GPS, accelerometers, mobile phones, various types of sensors, and social media. Innovative approaches and methods have been developed. This Special Issue aims to showcase studies that use new approaches, methods, and data to examine the role of human mobility and non-residential contexts on human health behaviors and outcomes. It includes 21 articles that cover a wide range of topics, including individual exposure to air pollution, exposure and access to green spaces, spatial access to healthcare services, environmental influences on physical activity, food environmental and diet behavior, exposure to noise and its impact on mental health, and broader methodological issues such as the uncertain geographic context problem (UGCoP) and the neighborhood effect averaging problem (NEAP). This collection will be a valuable reference for scholars and students interested in recent advances in the concepts and methods in environmental health and health geography.

Keywords

obesity --- built environment --- activity space --- regression analysis --- UGCoP --- foodscape exposure --- activity space --- commuting route --- space-time kernel density estimation --- time-weighted exposure --- Beijing --- cycling for transportation --- bike paths --- train stations --- subway stations --- adults --- Brazil --- fuel consumption --- emissions estimation --- GPS trace --- big data --- air pollution exposure --- human mobility --- mobile phone data --- dynamic assessment --- GIS --- GPS --- activity space --- environmental exposure --- the uncertain geographic context problem --- noise pollution --- mental disorders --- built environment --- multilevel model --- China --- PM concentrations --- crop residue burning --- correlation analysis --- interannual and seasonal variations --- China --- the neighborhood effect averaging problem (NEAP) --- human mobility --- environmental exposure --- the uncertain geographic context problem --- UGCoP --- car ownership --- car use --- built environment --- spatial autocorrelation --- multilevel Bayesian model --- geographical accessibility --- Healthcare services --- GIS --- E2SFCA --- CHAS --- Singapore --- environmental health --- food environment --- environmental context cube --- environmental context exposure index --- the uncertain geographic context problem (UGCoP) --- GPS --- GIS --- healthcare accessibility --- catchment areas --- access probability --- taxi GPS trajectories --- E2SFCA --- greenspace exposure --- health --- human mobility --- physical activity --- structural equation modeling --- Guangzhou --- healthcare accessibility --- population demand --- geographic impedance --- the elderly --- urban planning --- 3SFCA --- real-time traffic --- crowdedness --- well-being experience --- long-distance walking --- collective leisure activity --- walking event --- urban leisure --- missing data --- spatial data --- imputation --- geographic imputation --- activity space --- ecological momentary assessment --- EMA --- walking --- active travel --- ageing --- physical environment --- personal projects --- activity space --- Public Participatory GIS (PPGIS) --- spatial accessibility --- multimodal network --- primary healthcare --- China --- 2009 influenza A(H1N1) pandemic --- transport modes --- rail travel --- spatial spread --- quantile regression --- green space --- road traffic accidents --- cognitive aging --- activity space --- life-course perspectives --- environmental exposures

Human Health Engineering

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ISBN: 9783039284085 9783039284092 Year: Pages: 428 DOI: 10.3390/books978-3-03928-409-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:09
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In this Special Issue on human health engineering, we invited submissions exploring recent contributions to the field of human health engineering, which is the technology used for monitoring the physical or mental health status of individuals in a variety of applications. Contributions focused on sensors, wearable hardware, algorithms, or integrated monitoring systems. We organized the different papers according to their contributions to the main aspects of the monitoring and control engineering scheme applied to human health applications, including papers focusing on measuring/sensing physiological variables, contributions describing research on the modelling of biological signals, papers highlighting health monitoring applications, and finally examples of control applications for human health. In comparison to biomedical engineering, the field of human health engineering also covers applications on healthy humans (e.g., sports, sleep, and stress) and thus not only contributes to develop technology for curing patients or supporting chronically ill people, but also more generally for disease prevention and optimizing human well-being.

Keywords

artefact correction --- head-shaped phantom --- spherical phantom --- gradient artefact --- simultaneous EEG–fMRI --- calcaneal spur --- pain minimum compressive pressure --- contour of shoe insole --- insole foot area --- health information --- interface formats --- older adults --- wearable devices --- usability --- emotional reaction --- ADHD --- screening --- machine learning --- SVM --- children --- novel --- nomophobia --- anxiety --- smartphone --- internet --- cyberaddiction --- new technologies --- chronic obstructive pulmonary disease --- COPD --- oxygen uptake --- VO2 --- kinetics --- exercise testing --- rehabilitation robotics --- soft walking assistive robot --- long-term effect --- gait characteristics --- elderly person --- blood pressure estimation --- photoplethysmogram --- pulse wave --- pulse oximeter --- wearable device --- Kano-TRIZ design theory --- quality function deployment --- four-wheeled rollator --- model predictive control --- orthosis control --- muscle modeling --- arm --- Hill muscle --- swarm optimization --- pneumatic artificial muscle --- sliding mode control --- fractional calculus --- antagonistic actuator --- weight loss --- mHealth --- dynamic model --- adaptive control --- spirometry --- airflow limitation --- airway resistance --- specific airway conductance --- COPD --- body-plethysmography --- forced expiration --- alveolar pressure --- emphysema --- computed tomography --- air-trapping --- thermal comfort --- bicycle helmet --- smart wearables --- adaptive model --- streaming data --- thermal sensation --- adaptive model --- personalized model --- machine leaning --- support-vector-machine --- adaptive control --- streaming algorithm --- thermoregulation --- homeostasis --- cold-induced-vasodilation --- cold-induced-vasoconstriction --- control system --- dynamic modelling --- powered mobility --- dyskinetic cerebral palsy --- dystonia --- choreoathetosis --- mobility scale --- movement disorder --- children --- youth --- reliability --- validity --- feature engineering --- intensive care unit --- mortality prediction --- hard-margin support vector machines --- driver drowsiness --- thermoregulation --- distal skin temperature --- decision tree --- heart model --- Van der Pol --- FitzHugh–Nagumo --- relaxation oscillator --- electrocardiographic signal --- bicycle helmets --- thermal manikin --- convective and evaporative heat loss --- zonal performance characteristics --- freestyle skiing aerials --- knee joint --- ligament --- finite element simulation --- lifting technique --- stoop --- squat --- work-related musculoskeletal disorders --- musculoskeletal modeling --- spine --- shoulder --- back loading --- harmonization --- meta-analysis --- missing data --- multiple imputations --- information technology --- remoteness --- cohort studies --- control parameter reference --- stance assistance --- magnetorheological brake --- body mass index --- walking speed --- ankle torque --- ankle angular velocity --- n/a

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