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You searched for: Publication year rev 7983-2017 Remove constraint Publication year rev: 7983-2017 Subject term prediction Remove constraint Subject term: prediction
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1. "Candidatus Liberibacter solanacearum" Associated With the Psyllid, Bactericera maculipennis (Hemiptera: Triozidae)

Author:
Karina M. Borges; W. Rodney Cooper; Stephen F. Garczynski; Jenita Thinakaran; Andy S. Jensen; David R. Horton; Joseph E. Munyaneza; Isabel Cueva; Nina M. Barcenas
Source:
Environmental entomology 2017 v.46 no.2 pp. 210-216
ISSN:
0046-225X
Subject:
Bactericera cockerelli; Candidatus Liberibacter solanacearum; Convolvulus arvensis; Solanaceae; Triozidae; adults; disease transmission; genetic markers; haplotypes; insect vectors; nucleotide sequences; pathogens; potatoes; prediction; ribosomal DNA; zebra chip disease; Idaho; Washington (state)
Abstract:
... The psyllid Bactericera maculipennis (Crawford) (Hemiptera: Triozidae) often cohabits field bindweed (Convolvulus arvensis, Solanales: Convolvulaceae) and other plants with the congeneric psyllid, Bactericera cockerelli (Sulc), in the Pacific Northwestern United States. Bactericera cockerelli is a vector of “Candidatus Liberibacter solanacearum,” the pathogen associated with zebra chip disease of ...
Handle:
10113/5678133
DOI:
10.1093/ee/nvw174

2. (Q)SAR tools for priority setting: A case study with printed paper and board food contact material substances

Author:
Melissa Van Bossuyt; Els Van Hoeck; Giuseppa Raitano; Serena Manganelli; Els Braeken; Gamze Ates; Tamara Vanhaecke; Sabine Van Miert; Emilio Benfenati; Birgit Mertens; Vera Rogiers
Source:
Food and chemical toxicology 2017 v.102 pp. 109-119
ISSN:
0278-6915
Subject:
Ames test; azo compounds; case studies; cosmetics; drugs; models; mutagenicity; paperboard; prediction; prioritization; screening; structure-activity relationships
Abstract:
... Over the last years, more stringent safety requirements for an increasing number of chemicals across many regulatory fields (e.g. industrial chemicals, pharmaceuticals, food, cosmetics, …) have triggered the need for an efficient screening strategy to prioritize the substances of highest concern. In this context, alternative methods such as in silico (i.e. computational) techniques gain more and m ...
DOI:
10.1016/j.fct.2017.02.002

3. 13C ENDOR Spectroscopy of Lipoxygenase–Substrate Complexes Reveals the Structural Basis for C–H Activation by Tunneling

Author:
Horitani Masaki; Offenbacher Adam R.; Carr Cody A. Marcus; Yu Tao; Hoeke Veronika; Cutsail George E.; Hammes-Schiffer Sharon; Klinman Judith P.; Hoffman Brian M.
Source:
Journal of the American Chemical Society 2017 v.139 no.5 pp. 1984-1997
ISSN:
1520-5126
Subject:
manganese; linoleic acid; van der Waals forces; X-ray diffraction; iron; linoleate 13S-lipoxygenase; electron transfer; models; soybeans; electron paramagnetic resonance spectroscopy; molecular dynamics; active sites; hydrogen; catalytic activity; stable isotopes; prediction
Abstract:
... In enzymatic C–H activation by hydrogen tunneling, reduced barrier width is important for efficient hydrogen wave function overlap during catalysis. For native enzymes displaying nonadiabatic tunneling, the dominant reactive hydrogen donor–acceptor distance (DAD) is typically ca. 2.7 Å, considerably shorter than normal van der Waals distances. Without a ground state substrate-bound structure for t ...
DOI:
10.1021/jacs.6b11856
PubMed:
28121140
PubMed Central:
PMC5322796

4. 3,14-Bis(4-formylphenyl)-17,17-di(n-pentyl)tetrabenzo[a,c,g,i]fluorene showing solvatochromism and crystallochromism in fluorescence

Author:
Masanori Ueki; Yusuke Kimura; Yuma Yamamoto; Jun-ich Nishida; Chitoshi Kitamura; Mirai Tanaka; Hiroshi Ikeda; Takeshi Kawase
Source:
Tetrahedron 2017 pp. -
ISSN:
0040-4020
Subject:
chemical reactions; chemical structure; fluorenes; fluorescence; methylene chloride; optical properties; prediction
Abstract:
... The substituent effect on optical properties of 3,14-diphenyl-17,17-di(n-pentyl)tetrabenzofluorene derivatives bearing electron-withdrawing groups (NC, CH3OCO, CH3SO2, and OHC) at 4-position of the phenyl groups were investigated. These compounds were readily prepared by using Suzuki–Miyaura cross-coupling as a key step. The 4-cyano, 4-methoxycarbonyl, and 4-methylsulfonyl derivatives display inte ...
DOI:
10.1016/j.tet.2017.01.014

5. 3D-QSAR predictions for bovine serum albumin–water partition coefficients of organic anions using quantum mechanically based descriptors

Author:
Lukas Linden; Kai-Uwe Goss; Satoshi Endo
Source:
Environmental science 2017 v.19 no.3 pp. 261-269
ISSN:
2050-7895
Subject:
anions; anthropogenic activities; blood serum; bovine serum albumin; cattle; isomers; models; organic compounds; partition coefficients; prediction; quantitative structure-activity relationships; sorption
Abstract:
... Ionic organic chemicals are a class of chemicals that is released in the environment in a large amount from anthropogenic sources. Among various chemical and biological processes, binding to serum albumin is particularly relevant for the toxicokinetic behavior of ionic chemicals. Several experimental studies showed that steric effects have a crucial influence on the sorption to bovine serum albumi ...
DOI:
10.1039/c6em00555a

6. A 15-gene signature for prediction of colon cancer recurrence and prognosis based on SVM

Author:
Guangru Xu; Minghui Zhang; Hongxing Zhu; Jinhua Xu
Source:
Gene 2017 v.604 pp. 33-40
ISSN:
0378-1119
Subject:
colorectal neoplasms; data collection; databases; gene expression; gene expression regulation; genes; linear models; microarray technology; patients; prediction; prognosis; regression analysis; risk; support vector machines
Abstract:
... To screen the gene signature for distinguishing patients with high risks from those with low-risks for colon cancer recurrence and predicting their prognosis.Five microarray datasets of colon cancer samples were collected from Gene Expression Omnibus database and one was obtained from The Cancer Genome Atlas (TCGA). After preprocessing, data in GSE17537 were analyzed using the Linear Models for Mi ...
DOI:
10.1016/j.gene.2016.12.016

7. A Bayesian geostatistical approach to modeling global distributions of Lygodium microphyllum under projected climate warming

Author:
John M. Humphreys; James B. Elsner; Thomas H. Jagger; Stephanie Pau
Source:
Ecological modelling 2017 v.363 pp. 192-206
ISSN:
0304-3800
Subject:
Bayesian theory; Lygodium microphyllum; biogeography; climate; ecosystems; geographical distribution; geostatistics; global warming; invasive species; models; prediction; risk; temperature
Abstract:
... Species distribution modeling aimed at forecasting the spread of invasive species under projected global warming offers land managers an important tool for assessing future ecological risk and for prioritizing management actions. The current study applies Bayesian inference and newly available geostatistical tools to forecast global range expansion for the ecosystem altering invasive climbing fern ...
DOI:
10.1016/j.ecolmodel.2017.09.005

8. A CRISPR Resource for Individual, Combinatorial, or Multiplexed Gene Knockout

Author:
Nicolas Erard; Simon R.V. Knott; Gregory J. Hannon
Source:
Molecular cell 2017 v.67 no.2 pp. 348-354.e4
ISSN:
1097-2765
Subject:
artificial intelligence; gene targeting; genes; genetic engineering; loss-of-function mutation
Abstract:
... We have combined a machine-learning approach with other strategies to optimize knockout efficiency with the CRISPR/Cas9 system. In addition, we have developed a multiplexed sgRNA expression strategy that promotes the functional ablation of single genes and allows for combinatorial targeting. These strategies have been combined to design and construct a genome-wide, sequence-verified, arrayed CRISP ...
DOI:
10.1016/j.molcel.2017.06.030
PubMed:
28732207
PubMed Central:
PMC5526787

9. A CRO-species optimization scheme for robust global solar radiation statistical downscaling

Author:
S. Salcedo-Sanz; S. Jiménez-Fernández; A. Aybar-Ruiz; C. Casanova-Mateo; J. Sanz-Justo; R. García-Herrera
Source:
Renewable energy 2017 v.111 pp. 63-76
ISSN:
0960-1481
Subject:
algorithms; coral reefs; neural networks; prediction; radiometry; renewable energy sources; solar radiation; Spain
Abstract:
... This paper tackles the prediction of the global solar radiation (GSR) at a given point, using as predictive variables the outputs of a numerical weather model (the WRF meso-scale model) obtained at a different grid points. Prediction is obtained in this work using a Multilayer Perceptron (MLP) trained with Extreme Learning Machines (ELMs). Provided that the number of WRF outputs is vast, we propos ...
DOI:
10.1016/j.renene.2017.03.079

10. A DFT-Based Computational-Experimental Methodology for Synthetic Chemistry: Example of Application to the Catalytic Opening of Epoxides by Titanocene

Author:
Jaraíz Martín; Enríquez Lourdes; Pinacho Ruth; Rubio José E.; Lesarri Alberto; López-Pérez José L.
Source:
Journal of organic chemistry 2017 v.82 no.7 pp. 3760-3766
ISSN:
1520-6904
Subject:
Fourier transform infrared spectroscopy; chemical reactions; chemical structure; epoxides; instrumentation; mechanistic models; monitoring; nuclear magnetic resonance spectroscopy; organic chemistry; prediction; reaction kinetics; spectral analysis; spectrometers; ultraviolet-visible spectroscopy
Abstract:
... A novel DFT-based Reaction Kinetics (DFT-RK) simulation approach, employed in combination with real-time data from reaction monitoring instrumentation (like UV–vis, FTIR, Raman, and 2D NMR benchtop spectrometers), is shown to provide a detailed methodology for the analysis and design of complex synthetic chemistry schemes. As an example, it is applied to the opening of epoxides by titanocene in TH ...
DOI:
10.1021/acs.joc.7b00220

11. A DNA test for routine prediction in breeding of peach blush, Ppe-Rf-SSR

Author:
Paul Sandefur; Terrence Frett; John Clark; Ksenija Gasic; Cameron Peace
Source:
Molecular breeding 2017 v.37 no.1 pp. 11
ISSN:
1380-3743
Subject:
DNA; Prunus persica; breeding; breeding programs; color; fresh market; genetic markers; germplasm; haplotypes; loci; microsatellite repeats; parents; peaches; polymerase chain reaction; prediction; reproductive performance; screening; seedlings; single nucleotide polymorphism
Abstract:
... Blush, the proportion of red overcolor on the skin surface of fruit, is highly variable in peach breeding germplasm and is important in the marketing of peach fruit. The fresh market peach industry demands a high level of blush to entice consumers, while the processing peach industry requires minimal blush. Therefore, blush is a major selection criterion in breeding programs. The use of DNA-based ...
DOI:
10.1007/s11032-016-0615-3
CHORUS:
10.1007/s11032-016-0615-3

12. A Dirichlet‐tree multinomial regression model for associating dietary nutrients with gut microorganisms

Author:
Tao Wang; Hongyu Zhao
Source:
Biometrics 2017 v.73 no.3 pp. 792-801
ISSN:
0006-341X
Subject:
biometry; data collection; drugs; health services; humans; intestinal microorganisms; mathematical theory; microbial communities; models; nutrients; phylogeny; plate count; prediction; regression analysis
Abstract:
... Understanding the factors that alter the composition of the human microbiota may help personalized healthcare strategies and therapeutic drug targets. In many sequencing studies, microbial communities are characterized by a list of taxa, their counts, and their evolutionary relationships represented by a phylogenetic tree. In this article, we consider an extension of the Dirichlet multinomial dist ...
DOI:
10.1111/biom.12654
PubMed:
28112797
PubMed Central:
PMC5587402

13. A Dissolved Oxygen Prediction Method Based on K-Means Clustering and the ELM Neural Network: A Case Study of the Changdang Lake, China

Author:
Juan Huan; Weijian Cao; Xingqiao Liu
Source:
Applied engineering in agriculture v.33 no.4 pp. 461-469
ISSN:
0883-8542
Subject:
Internet; algorithms; aquaculture; case studies; dissolved oxygen; environmental factors; information processing; lakes; meteorological data; neural networks; prediction; water management; water quality; China
Abstract:
... According to mass data from the internet, prediction is an important application of information processing. Predicting the amount of dissolved oxygen (DO) of a water environment is vital and can improve the aquaculture production efficiency. Using water quality and meteorological data for the Changdang Lake (Jiangsu, China) from 2014 to 2016, this study proposes a new strategy for predicting short ...
DOI:
10.13031/aea.11786

14. A Dynamic Spatiotemporal Analysis Model for Traffic Incident Influence Prediction on Urban Road Networks

Author:
Chun Liu; Shuhang Zhang; Hangbin Wu; Qiang Fu
Source:
ISPRS international journal of geo-information 2017 v.6 no.11 pp. -
ISSN:
2220-9964
Subject:
databases; geographic information systems; models; monitoring; multivariate analysis; prediction; roads; traffic
Abstract:
... Traffic incidents have a broad negative impact on both traffic systems and the quality of social activities; thus, analyzing and predicting the influence of traffic incidents dynamically is necessary. However, the traditional geographic information system for transportation (GIS-T) mostly presents fundamental data and static analysis, and transportation models focus predominantly on some typical r ...
DOI:
10.3390/ijgi6110362

15. A GIS-based software for forecasting pollutant drift on coastal water surfaces using fractional Brownian motion: A case study on red tide drift

Author:
Rufu Qin; Liangzhao Lin; Cuiping Kuang; Tsung-Chow Su; Xiaodan Mao; Yusheng Zhou
Source:
Environmental modelling & software 2017 v.92 pp. 252-260
ISSN:
1364-8152
Subject:
algal blooms; case studies; coastal water; computer software; decision making; environmental models; geographic information systems; pollutants; pollution; prediction
Abstract:
... For ocean pollution emergencies, decision-makers need to quickly know the location of the pollutant for quick assessment and response strategies. In this study, an integrated operational forecasting model coupling a non-Fickian particle-tracking diffusion model based on fractional Brownian motion and geographic information system (GIS) has been developed to implement an operating system for pollut ...
DOI:
10.1016/j.envsoft.2017.03.003

16. A Genetic Programming Approach to System Identification of Rainfall-Runoff Models

Author:
Jayashree Chadalawada; Vojtech Havlicek; Vladan Babovic
Source:
Water resources management 2017 v.31 no.12 pp. 3975-3992
ISSN:
0920-4741
Subject:
algorithms; artificial intelligence; climate change; data collection; hydrologic models; physics; prediction; runoff; uncertainty; urbanization; watersheds; New Zealand; Singapore
Abstract:
... Advancements in data acquisition, storage and retrieval are progressing at an extraordinary rate, whereas the same in the field of knowledge extraction from data is yet to be accomplished. The challenges associated with hydrological datasets, including complexity, non-linearity and multicollinearity, motivate the use of machine learning to build hydrological models. Increasing global climate chang ...
DOI:
10.1007/s11269-017-1719-1

17. A Gompertz Model Approach to Microbial Inactivation Kinetics by High‐Pressure Processing (HPP): Model Selection and Experimental Validation

Author:
Vinicio Serment‐Moreno; Claudio Fuentes; José Antonio Torres; Jorge Welti‐Chanes
Source:
Journal of food science 2017 v.82 no.8 pp. 1885-1891
ISSN:
0022-1147
Subject:
Listeria innocua; high pressure treatment; logit analysis; microbial load; microorganisms; milk; model validation; models; mortality; prediction
Abstract:
... A recently proposed Gompertz model (GMPZ) approach describing microbial inactivation kinetics by high‐pressure processing (HPP) incorporated the initial microbial load (N₀) and lower microbial quantification limit (Nₗᵢₘ), and simplified the dynamic effects of come‐up time (CUT). The inactivation of Listeria innocua in milk by HPP treatments at 300, 400, 500, and 600 MPa and pressure holding times ...
DOI:
10.1111/1750-3841.13783

18. A Group-Specific Recommender System

Author:
Xuan Bi; Annie Qu; Junhui Wang; Xiaotong Shen
Source:
Journal of the American Statistical Association 2017 v.112 no.519 pp. 1344-1353
ISSN:
1537-274X
Subject:
algorithms; equations; information storage; least squares; models; prediction
Abstract:
... In recent years, there has been a growing demand to develop efficient recommender systems which track users’ preferences and recommend potential items of interest to users. In this article, we propose a group-specific method to use dependency information from users and items which share similar characteristics under the singular value decomposition framework. The new approach is effective for the ...
DOI:
10.1080/01621459.2016.1219261

19. A Highly Efficient Gene Expression Programming Model for Predicting the Discharge Coefficient in a Side Weir along a Trapezoidal Canal

Author:
Hamed Azimi; Hossein Bonakdari; Isa Ebtehaj
Source:
Irrigation and drainage 2017 v.66 no.4 pp. 655-666
ISSN:
1531-0353
Subject:
correlation; drainage; gene expression; irrigation systems; models; prediction; weirs
Abstract:
... Side weirs in trapezoidal canals are used to regulate and measure flow in drainage networks and irrigation systems. In this study, the discharge coefficient of a side weir in a trapezoidal canal is predicted using gene expression programming (GEP). The effects of Froude number (Fr), ratio of side weir length to trapezoidal canal bottom width (L/b), ratio of side weir length to flow depth upstream ...
DOI:
10.1002/ird.2127

20. A Hybrid Method for Short-Term Wind Speed Forecasting

Author:
Jinliang Zhang; YiMing Wei; Zhong-fu Tan; Wang Ke; Wei Tian
Source:
Sustainability 2017 v.9 no.4 pp. -
ISSN:
2071-1050
Subject:
power generation; prediction; weather research and forecasting model; wind power; wind speed; South Dakota
Abstract:
... The accuracy of short-term wind speed prediction is very important for wind power generation. In this paper, a hybrid method combining ensemble empirical mode decomposition (EEMD), adaptive neural network based fuzzy inference system (ANFIS) and seasonal auto-regression integrated moving average (SARIMA) is presented for short-term wind speed forecasting. The original wind speed series is decompos ...
DOI:
10.3390/su9040596

21. A Hybrid Statistical Downscaling Method Based on the Classification of Rainfall Patterns

Author:
Gwo-Fong Lin; Ming-Jui Chang; Jyue-Ting Wu
Source:
Water resources management 2017 v.31 no.1 pp. 377-401
ISSN:
0920-4741
Subject:
climate change; data collection; meteorological data; models; prediction; rain; support vector machines; Taiwan
Abstract:
... A hybrid statistical downscaling method based on the classification of rainfall patterns is presented which is capable of overcoming the poor representation of extreme events. The large-scale datasets, which are obtained from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data and the global circulation models (GCMs) outputs, and t ...
DOI:
10.1007/s11269-016-1532-2

22. A Low Geriatric Nutrition Risk Index Is Associated with Progression to Dialysis in Patients with Chronic Kidney Disease

Author:
I-Ching Kuo; Jiun-Chi Huang; Pei-Yu Wu; Szu-Chia Chen; Jer-Ming Chang; Hung-Chun Chen
Source:
Nutrients 2017 v.9 no.11 pp. -
ISSN:
2072-6643
Subject:
body weight; dialysis; echocardiography; fasting; females; glomerular filtration rate; glucose; hypertrophy; kidney diseases; malnutrition; mortality; nutrition risk assessment; nutritional status; patients; prediction; serum albumin; systolic blood pressure
Abstract:
... Evaluating nutritional status is crucial to detecting malnutrition in patients with chronic kidney disease (CKD). The Geriatric Nutritional Risk Index (GNRI) has been associated with overall and cardiovascular mortality in the dialysis population. The aim of this study was to evaluate whether the GNRI is associated with progression to dialysis in patients with moderate to advanced CKD. We enrolled ...
DOI:
10.3390/nu9111228
PubMed:
29120366
PubMed Central:
PMC5707700

23. A Method for Determination of Thiamethoxam in Tea Infusion by Wavelet Transform of Self-Enhanced Absorption Spectrum

Author:
Jihua Zhang; Zhimin Zhao
Source:
Food analytical methods 2017 v.10 no.3 pp. 659-665
ISSN:
1936-9751
Subject:
absorption; analysis of variance; analytical methods; detection limit; prediction; quantitative analysis; tea; thiamethoxam; wavelet
Abstract:
... A method of self-enhanced absorption spectrum was proposed for the quantitative determination of thiamethoxam in tea infusion. Based on wavelet transform of original absorption spectra and self-enhanced spectra by wavelet function Gau8, the ratio of wavelet coefficients at analysis point was used to acquire thiamethoxam’s concentration. The analysis point of original spectra is at 251 nm by observ ...
DOI:
10.1007/s12161-016-0634-z

24. A Modified SCS-CN Method Incorporating Storm Duration and Antecedent Soil Moisture Estimation for Runoff Prediction

Author:
Wenhai Shi; Mingbin Huang; Kate Gongadze; Lianhai Wu
Source:
Water resources management 2017 v.31 no.5 pp. 1713-1727
ISSN:
0920-4741
Subject:
antecedent moisture; data collection; infiltration rate; models; prediction; soil conservation; soil water; storms; stormwater; watersheds; China
Abstract:
... In one of the widely used methods to estimate surface runoff - Soil Conservation Service Curve Number (SCS-CN), the antecedent moisture condition (AMC) is categorized into three AMC levels causing irrational abrupt jumps in estimated runoff. A few improved SCS-CN methods have been developed to overcome several in-built inconsistencies in the soil moisture accounting (SMA) procedure that lies behin ...
DOI:
10.1007/s11269-017-1610-0

25. A Monte Carlo and PSO based virtual sample generation method for enhancing the energy prediction and energy optimization on small data problem: An empirical study of petrochemical industries

Author:
Hong-Fei Gong; Zhong-Sheng Chen; Qun-Xiong Zhu; Yan-Lin He
Source:
Applied energy 2017 v.197 pp. 405-415
ISSN:
0306-2619
Subject:
algorithms; artificial intelligence; data collection; energy conservation; energy efficiency; ethylene production; industry; models; prediction; solvents
Abstract:
... Due to the imbalanced and uncompleted characteristics of complex petrochemical small datasets, it is a challenge to build an accurate prediction and optimization model of energy consumption of petrochemical systems. Therefore, this paper proposes a novel virtual sample generation (VSG) approach based on the Monte Carlo (MC) and Particle Swarm Optimization (PSO) algorithms to improve the accuracy o ...
DOI:
10.1016/j.apenergy.2017.04.007

26. A Multi-Resolution Approximation for Massive Spatial Datasets

Author:
Matthias Katzfuss
Source:
Journal of the American Statistical Association 2017 v.112 no.517 pp. 201-214
ISSN:
1537-274X
Subject:
aircraft; algorithms; covariance; data collection; equations; kriging; models; normal distribution; prediction; satellites; spatial data
Abstract:
... Automated sensing instruments on satellites and aircraft have enabled the collection of massive amounts of high-resolution observations of spatial fields over large spatial regions. If these datasets can be efficiently exploited, they can provide new insights on a wide variety of issues. However, traditional spatial-statistical techniques such as kriging are not computationally feasible for big da ...
DOI:
10.1080/01621459.2015.1123632

27. A New Approach to Predict the Fish Fillet Shelf-Life in Presence of Natural Preservative Agents

Author:
Alessandro Giuffrida; Filippo Giarratana; Davide Valenti; Daniele Muscolino; Roberta Parisi; Alessio Parco; Stefania Marotta; Graziella Ziino; Antonio Panebianco
Source:
Italian journal of food safety 2017 v.6 no.2 pp. -
ISSN:
2239-7132
Subject:
antibacterial properties; data collection; fish fillets; models; prediction; shelf life; spoilage
Abstract:
... Three data sets concerning the behaviour of spoilage flora of fillets treated with natural preservative substances (NPS) were used to construct a new kind of mathematical predictive model. This model, unlike other ones, allows expressing the antibacterial effect of the NPS separately from the prediction of the growth rate. This approach, based on the introduction of a parameter into the predictive ...
DOI:
10.4081/ijfs.2017.6768
PubMed:
28713795
PubMed Central:
PMC5505098

28. A Novel Approach to Predict 24-Hour Energy Expenditure Based on Hematologic Volumes: Development and Validation of Models Comparable to Mifflin-St Jeor and Body Composition Models

Author:
Douglas C. Chang; Paolo Piaggi; Jonathan Krakoff
Source:
Journal of the Academy of Nutrition and Dietetics 2017 v.117 no.8 pp. 1177-1187
ISSN:
2212-2672
Subject:
Whites; adults; blood volume; data collection; demographic statistics; energy expenditure; equations; lean body mass; men; models; nutrition; prediction; women; Arizona
Abstract:
... Accurate prediction of 24-hour energy expenditure (24EE) relies on knowing body composition, in particular fat-free mass (FFM), the largest determinant of 24EE. FFM is closely correlated with hematologic volumes: blood volume (BV), red cell mass (RCM), and plasma volume (PV). However, it is unknown whether predicted hematologic volumes, based on easily collected variables, can improve 24EE predict ...
DOI:
10.1016/j.jand.2017.04.009
PubMed:
28571655
PubMed Central:
PMC5534181

29. A Novel n-Type Organosilane–Metal Ion Hybrid of Rhodamine B and Copper Cation for Low-Temperature Thermoelectric Materials

Author:
Bertram John R.; Penn Aubrey; Nee Matthew J.; Rathnayake Hemali
Source:
ACS Applied Materials & Interfaces 2017 v.9 no.12 pp. 10946-10954
ISSN:
1944-8252
Subject:
absorption; binding sites; cations; copper; electrical conductivity; prediction
Abstract:
... An n-type organosilane–metal ion hybrid of Rhodamine B–silane and copper cation (Cu–RBS) was investigated as a low-temperature thermoelectric material. Computational analysis revealed the most likely localized binding site of Cu²⁺ was to the Rhodamine B core and provided predictions of molecular orbitals and electrostatic potentials upon complexation. The concentration-dependent optical absorption ...
DOI:
10.1021/acsami.6b15857

30. A Pacifastacus leniusculus serine protease interacts with WSSV

Author:
Enen Guo; Gül Gizem Korkut; Phattarunda Jaree; Irene Söderhäll; Kenneth Söderhäll
Source:
Fish & shellfish immunology 2017 v.68 pp. 211-219
ISSN:
1050-4648
Subject:
Pacifastacus leniusculus; White spot syndrome virus; active sites; crayfish; hematopoietic stem cells; hemocytes; prediction; secretion; serine proteinases; signal peptide; tissue distribution; viruses
Abstract:
... Serine proteases are involved in many critical physiological processes including virus spread and replication. In the present study, we identified a new clip-domain serine protease (PlcSP) in the crayfish Pacifastacus leniusculus hemocytes, which can interact with the White Spot Syndrome Virus (WSSV) envelope protein VP28. It was characterized by a classic clip domain with six strictly conserved C ...
DOI:
10.1016/j.fsi.2017.07.026

31. A Rapid Chemical Method for Estimating Potentially Mineralizable and Particulate Organic Nitrogen in Mollisols

Author:
Juan M. Martínez; Juan A. Galantini
Source:
Communications in soil science and plant analysis 2017 v.48 no.1 pp. 113-123
ISSN:
1532-2416
Subject:
Mollisols; digestion; fractionation; nitrogen; no-tillage; particulate organic matter; prediction; soil organic nitrogen; soil sampling; sulfuric acid
Abstract:
... The objective of this study was to obtain an indicator of labile nitrogen (N) through a cost- and time-saving procedure by evaluating the relationships among potentially mineralizable N (N ₀), particulate organic matter N (POM-N) and soil organic N extracted through partial soil digestion with different concentrations of sulfuric acid (H ₂SO ₄). Soil sampling (0–20 cm) was from nine fields under n ...
DOI:
10.1080/00103624.2016.1254230

32. A Simple Correlation for Estimating the Viscosity of Pure Ionic Liquids and Their Binary Mixtures

Author:
Aliakbar Roosta; Roghayeh Bardool
Source:
Industrial & engineering chemistry process design and development 2017 v.56 no.15 pp. 4600-4610
ISSN:
1520-5045
Subject:
equations; ionic liquids; models; prediction; process design; temperature; viscosity
Abstract:
... Ionic liquids (ILs) have been of particular interest to researchers in recent years. Viscosity is considered as one of the most important thermophysical properties of ILs. This paper uses a genetic programming approach to propose a simple equation, with only one parameter to adjust, for predicting the viscosity of pure ILs and their binary mixtures as a function of temperature. The adjustable para ...
DOI:
10.1021/acs.iecr.7b00532

33. A Simple Descriptor to Rapidly Screen CO Oxidation Activity on Rare-Earth Metal-Doped CeO2: From Experiment to First-Principles

Author:
Kim Kyeounghak; Yoo Jeong Do; Lee Siwon; Bae Minseok; Bae Joongmyeon; Jung WooChul; Han Jeong Woo
Source:
ACS Applied Materials & Interfaces 2017 v.9 no.18 pp. 15449-15458
ISSN:
1944-8252
Subject:
energy; ceric oxide; catalysts; methodology; carbon monoxide; oxidation; nanoparticles; catalytic activity; researchers; prediction
Abstract:
... Ceria (CeO₂) is an attractive catalyst because of its unique properties, such as facile redoxability and high stability. Thus, many researchers have examined a wide range of catalytic reactions on ceria nanoparticles (NPs). Among those contributions are the reports of the dopant-dependent catalytic activity of ceria. On the other hand, there have been few mechanistic studies of the effects of a ra ...
DOI:
10.1021/acsami.7b01844

34. A Simple Model To Estimate Brunauer–Emmett–Teller-N2 Specific Surface Area of Contrasting Soils in Brazil

Author:
Yuri L. Zinn; Emerson F. Vilela; Marla A. Araujo; Rattan Lal
Source:
Soil Science Society of America journal 2017 v.81 no.6 pp. 1340-1349
ISSN:
0361-5995
Subject:
aluminum; clay; clay fraction; crystal structure; ecological function; equations; iron; mineralogy; models; nitrogen; particle size distribution; prediction; regression analysis; soil ecology; soil organic carbon; sorption; surface area; texture; tropical soils; Brazil
Abstract:
... Specific surface area (SSA) is a key property of soils that affects nearly all soil ecological functions that involve aggregation and sorption. However, data on soil SSA are seldom reported in the literature due to time-consuming analysis or equipment constraints in most soil laboratories. Here, we measured external SSA by means of N₂ sorption with the Brunauer–Emmett–Teller isotherm using fine ea ...
DOI:
10.2136/sssaj2017.07.0220

35. A Simple and Versatile Strategy To Improve the Mechanical Properties of Polymer Nanocomposites with Cellulose Nanocrystals

Author:
Meesorn Worarin; Shirole Anuja; Vanhecke Dimitri; de Espinosa Lucas Montero; Weder Christoph
Source:
Macromolecules 2017 v.50 no.6 pp. 2364-2374
ISSN:
1520-5835
Subject:
cellulose; dispersants; energy transfer; fluorescein; mechanical properties; microscopy; modulus of elasticity; nanocrystals; polymer nanocomposites; polyurethanes; polyvinyl alcohol; prediction; rhodamines; storage modulus
Abstract:
... Cellulose nanocrystals (CNCs) are widely studied as reinforcing fillers for polymers. In many cases the mechanical properties of polymer/CNC nanocomposites do not match the theoretical predictions, arguably on account of CNC aggregation. This problem can be mitigated through the addition of a small amount of a judiciously selected polymeric dispersant that also serves as a binder among the CNCs. W ...
DOI:
10.1021/acs.macromol.6b02629

36. A Soil Bulk Density Pedotransfer Function Based on Machine Learning: A Case Study with the NCSS Soil Characterization Database

Author:
Amanda Ramcharan; Tomislav Hengl; Dylan Beaudette; Skye Wills
Source:
Soil Science Society of America journal 2017 v.81 no.6 pp. 1279-1287
ISSN:
0361-5995
Subject:
algorithms; artificial intelligence; bulk density; case studies; data collection; databases; ecoregions; ecosystems; pedotransfer functions; prediction; soil density; soil organic carbon; soil surveys; United States
Abstract:
... This paper describes a method to develop a soil bulk density pedotransfer function (PTF) using the Random Forest machine-Learning algorithm with soil and environmental data for the conterminous United States. Complete data from 45,818 horizons were extracted from the National Cooperative Soil Survey (NCSS) soil characterization database and used to calibrate and validate the PTF. Environmental dat ...
DOI:
10.2136/sssaj2016.12.0421

37. A Spatial Lattice Model Applied for Meteorological Visualization and Analysis

Author:
Mingyue Lu; Min Chen; Xuan Wang; Jinzhong Min; Aili Liu
Source:
ISPRS international journal of geo-information 2017 v.6 no.3 pp. -
ISSN:
2220-9964
Subject:
computer vision; geographic information systems; meteorological data; meteorological parameters; models; prediction; radar; stochastic processes
Abstract:
... Meteorological information has obvious spatial-temporal characteristics. Although it is meaningful to employ a geographic information system (GIS) to visualize and analyze the meteorological information for better identification and forecasting of meteorological weather so as to reduce the meteorological disaster loss, modeling meteorological information based on a GIS is still difficult because m ...
DOI:
10.3390/ijgi6030077

38. A Spatio–Temporal investigation of risk factors for aflatoxin contamination of corn in southern Georgia, USA using geostatistical methods

Author:
Ruth Kerry; Brenda V. Ortiz; Ben R. Ingram; Brian T. Scully
Source:
Crop protection 2017 v.94 pp. 144-158
ISSN:
0261-2194
Subject:
Aspergillus flavus; Food and Drug Administration; Poisson distribution; aflatoxins; agricultural education; corn; crop losses; drainage; drought; extension education; fungi; geostatistics; growers; humans; infrastructure; irrigation; kriging; liver neoplasms; planting; prediction; rain; risk factors; risk reduction; soil texture; space and time; temperature; trade; water stress; Georgia
Abstract:
... Aflatoxin is a mycotoxin produced by the Aspergillus flavus fungi that can severely contaminate corn grain. The U.S. Food and Drug Administration (FDA) have set a limit of 20 ppb, total aflatoxin, for interstate commerce of food and feed as it can induce liver cancer in humans and animals. Contamination is exacerbated by high temperatures, drought conditions and light-textured soil which are all c ...
DOI:
10.1016/j.cropro.2016.12.005
CHORUS:
10.1016/j.cropro.2016.12.005

39. A Statistical Model for the Prediction of Wind-Speed Probabilities in the Atmospheric Surface Layer

Author:
G. C. Efthimiou; D. Hertwig; S. Andronopoulos; J. G. Bartzis; O. Coceal
Source:
Boundary-layer meteorology 2017 v.163 no.2 pp. 179-201
ISSN:
0006-8314
Subject:
data collection; prediction; probability; probability distribution; statistical models; temporal variation; turbulent flow; wind speed
Abstract:
... Wind fields in the atmospheric surface layer (ASL) are highly three-dimensional and characterized by strong spatial and temporal variability. For various applications such as wind-comfort assessments and structural design, an understanding of potentially hazardous wind extremes is important. Statistical models are designed to facilitate conclusions about the occurrence probability of wind speeds b ...
DOI:
10.1007/s10546-016-0221-2

40. A Stepwise-Cluster Inference Model for Phenanthrene Immobilization at the Aqueous/Modified Palygorskite Interface

Author:
Shan Zhao; Guohe Huang; Guanhui Cheng; Wei Sun; Qian Su; Zeyu Tao; Shuguang Wang
Source:
Water 2017 v.9 no.8 pp. -
ISSN:
2073-4441
Subject:
environmental factors; humic acids; ionic strength; pH; palygorskite; phenanthrenes; prediction; sorption; statistical analysis; temperature
Abstract:
... A stepwise-cluster inference (SI) model was established through introducing stepwise-cluster analysis (SCA) into the phenanthrene immobilization process at the aqueous/modified palygorskite interface. SCA has the advantages of tackling the nonlinear relationships among environmental factors and the phenanthrene sorption amount in the immobilization process. The essence of SCA is to form a tree-bas ...
DOI:
10.3390/w9080590

41. A Study on the Kinetics of Acrylamide Formation in Banana Chips

Author:
Mehrajfatema Z. Mulla; Uday S. Annapure; Vikas R. Bharadwaj; Rekha S. Singhal
Source:
Journal of food processing and preservation 2017 v.41 no.1 pp. -
ISSN:
0145-8892
Subject:
acrylamides; banana chips; color; deep fat frying; equations; lipid content; oils; prediction; temperature; texture; water content
Abstract:
... This study was undertaken to study acrylamide formation during deep‐fat frying of ripe and unripe banana chips at 150, 170 and 190C up to 360 s. The moisture content, oil content, color and texture of the fried chips were also monitored during frying. The acrylamide formation was higher in ripe banana chips than unripe banana chips at all temperatures of frying. Acrylamide formation followed first ...
DOI:
10.1111/jfpp.12739

42. A Theoretical and Experimental Study of Glycerol Steam Reforming over Rh/MgAl2O4 Catalysts

Author:
Alireza Zarei Senseni; Fereshteh Meshkani; Seyed Mohsen Seyed Fattahi; Mehran Rezaei
Source:
Energy conversion and management 2017 pp. -
ISSN:
0196-8904
Subject:
catalysts; data collection; glycerol; neural networks; prediction; steam; streams; temperature
Abstract:
... In this paper, the back propagation artificial neural network (ANN) modeling approach was used for investigating of the steam reforming reaction of glycerol over Rh/MgAl2O4 catalyst in a packed bed tubular reactor. The experimental tests were carried out in order to provide appropriate experimental data set for training the model as well as for evaluating the ANN prediction ability of the catalyti ...
DOI:
10.1016/j.enconman.2017.10.033

43. A Threshold-Based Weather Model for Predicting Stripe Rust Infection in Winter Wheat

Author:
El Jarroudi Moussa; Kouadio Louis; Bock Clive H.; El Jarroudi Mustapha; Junk Jürgen; Pasquali Matias; Maraite Henri; Delfosse Philippe
Source:
Plant disease 2017 v.101 no.5 pp. 693-703
ISSN:
0191-2917
Subject:
Monte Carlo method; Puccinia striiformis f. tritici; air temperature; crops; environmental factors; fungi; fungicides; models; pesticide application; prediction; rain; relative humidity; stripe rust; weather forecasting; winter wheat; Luxembourg
Abstract:
... Wheat stripe rust (caused by Puccinia striiformis f. sp. tritici) is a major threat in most wheat growing regions worldwide, which potentially causes substantial yield losses when environmental conditions are favorable. Data from 1999 to 2015 for three representative wheat-growing sites in Luxembourg were used to develop a threshold-based weather model for predicting wheat stripe rust. First, the ...
DOI:
10.1094/PDIS-12-16-1766-RE

44. A bio-inspired design and computational prediction of scorpion-like SCS nickel pincer complexes for lactate racemization

Author:
Bing Qiu; Xinzheng Yang
Source:
Chemical communications 2017 v.53 no.83 pp. 11410-11413
ISSN:
1364-548X
Subject:
Gibbs free energy; active sites; catalytic activity; dehydrogenation; density functional theory; enzymes; hydrides; imidazoles; lactic acid; nickel; prediction
Abstract:
... Inspired by the structures of the active site of lactate racemase and recent reported SCS nickel pincer complexes, we built a series of scorpion-like SCS nickel pincer complexes with an imidazole tail and computationally predicted their catalytic activities for the racemization of lactic acid. Density functional theory calculations reveal a proton coupled hydride transfer mechanism for the dehydro ...
DOI:
10.1039/c7cc06416k

45. A boosting extreme learning machine for near-infrared spectral quantitative analysis of diesel fuel and edible blend oil samples

Author:
Xihui Bian; Caixia Zhang; Xiaoyao Tan; Michal Dymek; Yugao Guo; Ligang Lin; Bowen Cheng; Xiaoyu Hu
Source:
Analytical methods 2017 v.9 no.20 pp. 2983-2989
ISSN:
1759-9679
Subject:
algorithms; cooking fats and oils; diesel fuel; least squares; models; near-infrared spectroscopy; prediction; quantitative analysis; standard deviation
Abstract:
... Extreme learning machines (ELMs) have drawn increasing attention due to their characteristics of simple structure, high learning speed and excellent performance. However, a single ELM tends to low predictive accuracy and instability in dealing with quantitative analysis of complex samples. To further improve the predictive accuracy and stability of ELMs, a new quantitative model, called the boosti ...
DOI:
10.1039/c7ay00353f

46. A boundary layer scaling technique for estimating near-surface wind energy using numerical weather prediction and wind map data

Author:
D.J. Allen; A.S. Tomlin; C.S.E. Bale; A. Skea; S. Vosper; M.L. Gallani
Source:
Applied energy 2017 v.208 pp. 1246-1257
ISSN:
0306-2619
Subject:
Weibull statistics; aerodynamics; case studies; data collection; energy; meteorological data; models; prediction; weather forecasting; wind power; wind speed; wind turbines; Great Britain
Abstract:
... A boundary layer scaling (BLS) method for predicting long-term average near-surface wind speeds and power densities was developed in this work. The method was based on the scaling of reference climatological data either from long-term average wind maps or from hourly wind speeds obtained from high-resolution Numerical Weather Prediction (NWP) models, with case study applications from Great Britain ...
DOI:
10.1016/j.apenergy.2017.09.029

47. A climate-sensitive aboveground biomass model for three larch species in northeastern and northern China

Author:
Liyong Fu; Wei Sun; Guangxing Wang
Source:
Trees 2017 v.31 no.2 pp. 557-573
ISSN:
0931-1890
Subject:
Larix gmelinii var. olgensis; aboveground biomass; adaptive management; carbon; climate change; climatic factors; climatic zones; ecological function; forest ecosystems; forest management; forests; growing season; indigenous species; models; prediction; rain; risk reduction; temperature; trees; uncertainty; China
Abstract:
... KEY MESSAGE: A climate-sensitive aboveground biomass model developed by combining a nonlinear mixed-effects model and dummy variable approach led to higher prediction accuracy of biomass than those without climatic variables for three larch species. As native species and being widely distributed in northeastern and northern China, larch forests play a pivotal role in maintaining forest ecosystem f ...
DOI:
10.1007/s00468-016-1490-6

48. A cohesive zone model taking account of the effect of through-thickness compression

Author:
Zhenmin Zou; Hao Lee
Source:
Composites 2017 v.98 pp. 90-98
ISSN:
1359-835X
Subject:
composite materials; delamination; friction; models; prediction; shear strength
Abstract:
... Experiments in the literature show that through-thickness compressive stress significantly enhances interfacial fracture resistance. Most existing cohesive zone and interface element models which consider the enhancement only introduce friction in the model. In this paper, a new method is proposed to include both friction and enhanced interfacial shear strength in a cohesive zone model. Contact an ...
DOI:
10.1016/j.compositesa.2017.03.015

49. A combined experimental and DEM approach to determine the breakage of particles in an impact mill

Author:
E. Ghasemi Ardi; K.J. Dong; A.B. Yu; R.Y. Yang
Source:
Powder technology 2017 v.318 pp. 543-548
ISSN:
0032-5910
Subject:
energy; equations; grinding; iron; models; particle size; powders; prediction
Abstract:
... Population balance models (PBMs) are widely used to predict particle size variation in grinding. An accurate determination of particle breakage and selection functions in PBMs requires detailed knowledge on the stress causing particle breakage. This study proposed a combined experimental and numerical approach to determine the two functions. In the physical experiments, the breakage of individual ...
DOI:
10.1016/j.powtec.2017.06.026

50. A comparative study and prediction of the liquid desiccant dehumidifiers using intelligent models

Author:
Alireza Zendehboudi; Afshin Tatar; Xianting Li
Source:
Renewable energy 2017 v.114 pp. 1023-1035
ISSN:
0960-1481
Subject:
desiccants; humidity; neural networks; prediction; renewable energy sources; support vector machines; temperature
Abstract:
... Dehumidifier in liquid desiccant systems is affected by different influential parameters and precise prediction of its characteristics is vital for a better overall performance. In this communication, the well-known artificial intelligence based methods such as Least Square Support Vector Machine (LSSVM), Adaptive Neuro Fuzzy Inference System (ANFIS), and Artificial Neural Network (ANN) are develo ...
DOI:
10.1016/j.renene.2017.07.078

51. A comparative study of anaerobic fixed film baffled reactor and up-flow anaerobic fixed film fixed bed reactor for biological removal of diethyl phthalate from wastewater: a performance, kinetic, biogas, and metabolic pathway study

Author:
Samira Yousefzadeh; Ehsan Ahmadi; Mitra Gholami; Hamid Reza Ghaffari; Ali Azari; Mohsen Ansari; Mohammad Miri; Kiomars Sharafi; Soheila Rezaei
Source:
Biotechnology for biofuels 2017 v.10 no.1 pp. 139
ISSN:
1754-6834
Subject:
biochemical pathways; biogas; biomass production; bioreactors; chemical oxygen demand; industry; mathematical models; methane production; microbial growth; phthalates; pollutants; prediction; sludge; wastewater
Abstract:
... BACKGROUND: Phthalic acid esters, including diethyl phthalate (DEP), which are considered as top-priority and hazardous pollutants, have received significant attention over the last decades. It is vital for industries to select the best treatment technology, especially when the DEP concentration in wastewater is high. Meanwhile, anaerobic biofilm-based reactors are considered as a promising option ...
DOI:
10.1186/s13068-017-0826-9
PubMed:
28580013
PubMed Central:
PMC5452402

52. A comparative study of fibrillation kinetics of two homologous proteins under identical solution condition

Author:
Ankur P. Chaudhary; Neha H. Vispute; Vaibhav Kumar Shukla; Basir Ahmad
Source:
Biochimie 2017 v.132 pp. 75-84
ISSN:
0300-9084
Subject:
amyloid; hens; humans; lysozyme; mixing; models; pH; prediction
Abstract:
... Human lysozyme is homologous in the three-dimensional structure to hen lysozyme and the latter is commonly used to understand folding and amyloid aggregation pathway of the former. The fibrillation of the two proteins is known to occur via partial unfolding. A work dedicated to comparing the aggregation-prone conformations and their subsequent conversion into amyloid-like fibrils in an identical c ...
DOI:
10.1016/j.biochi.2016.11.002

53. A comparative study of landslide susceptibility mapping using weight of evidence, logistic regression and support vector machine and evaluated by SBAS-InSAR monitoring: Zhouqu to Wudu segment in Bailong River Basin, China

Author:
Zhengtuan Xie; Guan Chen; Xingmin Meng; Yi Zhang; Liang Qiao; Long Tan
Source:
Environmental earth sciences 2017 v.76 no.8 pp. 313
ISSN:
1866-6280
Subject:
chi-square distribution; deformation; environmental factors; infrastructure; landslides; monitoring; planning; prediction; principal component analysis; regression analysis; statistical models; support vector machines; synthetic aperture radar; urban areas; watersheds; weight-of-evidence; China
Abstract:
... The determining of landslide-prone areas in mountainous terrain is essential for land planning and hazard mitigation. In this paper, a comparative study using three statistical models including weight of evidence model (WoE), logistic regression model (LR) and support vector machine method (SVM) was undertaken in the Zhouqu to Wudu segment in the Bailong River Basin, Southern Gansu, China. Six con ...
DOI:
10.1007/s12665-017-6640-7

54. A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility

Author:
Wei Chen; Xiaoshen Xie; Jiale Wang; Biswajeet Pradhan; Haoyuan Hong; Dieu Tien Bui; Zhao Duan; Jianquan Ma
Source:
Catena 2017 v.151 pp. 147-160
ISSN:
0341-8162
Subject:
aerial photography; altitude; inventories; land use; landslides; logit analysis; models; normalized difference vegetation index; prediction; rain; rivers; roads; support vector machines; surveys
Abstract:
... The main purpose of the present study is to use three state-of-the-art data mining techniques, namely, logistic model tree (LMT), random forest (RF), and classification and regression tree (CART) models, to map landslide susceptibility. Long County was selected as the study area. First, a landslide inventory map was constructed using history reports, interpretation of aerial photographs, and exten ...
DOI:
10.1016/j.catena.2016.11.032

55. A comparative study of photosynthetic unit models for algal growth rate and fluorescence prediction under light/dark cycles

Author:
Paul Rudnicki; Xi Gao; Bo Kong; R. Dennis Vigil
Source:
Algal research 2017 v.24 pp. 227-236
ISSN:
2211-9264
Subject:
algae; fluorescence; models; photobioreactors; photochemistry; photosynthesis; prediction; specific growth rate
Abstract:
... Accurate description of light-limited algal growth, especially under short light/dark (L/D) cycles, is crucial for prediction of photobioreactor performance and for optimization of operating conditions. Here, a variety of widely used photosynthetic unit (PSU)-based models are evaluated to determine their ability to predict algal specific growth rate and photochemical efficiency under a range of li ...
DOI:
10.1016/j.algal.2017.03.028

56. A comparative study of sequential minimal optimization-based support vector machines, vote feature intervals, and logistic regression in landslide susceptibility assessment using GIS

Author:
Binh Thai Pham; Dieu Tien Bui; Indra Prakash; Long Hoang Nguyen; M. B. Dholakia
Source:
Environmental earth sciences 2017 v.76 no.10 pp. 371
ISSN:
1866-6280
Subject:
geographic information systems; land cover; landslides; models; prediction; rain; regression analysis; rivers; roads; soil; support vector machines; Himalayan region; India
Abstract:
... Landslide susceptibility assessment using GIS has been done for part of Uttarakhand region of Himalaya (India) with the objective of comparing the predictive capability of three different machine learning methods, namely sequential minimal optimization-based support vector machines (SMOSVM), vote feature intervals (VFI), and logistic regression (LR) for spatial prediction of landslide occurrence. ...
DOI:
10.1007/s12665-017-6689-3

57. A comparative study of shallow groundwater level simulation with three time series models in a coastal aquifer of South China

Author:
Q. Yang; Y. Wang; J. Zhang; J. Delgado
Source:
Applied water science 2017 v.7 no.2 pp. 689-698
ISSN:
2190-5487
Subject:
aquifers; data collection; models; prediction; rural water supply; time series analysis; water management; water table; watersheds; China
Abstract:
... Accurate and reliable groundwater level forecasting models can help ensure the sustainable use of a watershed’s aquifers for urban and rural water supply. In this paper, three time series analysis methods, Holt–Winters (HW), integrated time series (ITS), and seasonal autoregressive integrated moving average (SARIMA), are explored to simulate the groundwater level in a coastal aquifer, China. The m ...
DOI:
10.1007/s13201-015-0282-2

58. A comparison of cover calculation techniques for relating point-intercept vegetation sampling to remote sensing imagery

Author:
Jason W. Karl; Sarah E. McCord; Brian C. Hadley
Source:
Ecological indicators 2017 v.73 pp. 156-165
ISSN:
1470-160X
Subject:
canopy; ecosystems; forbs; grasses; land management; model validation; models; monitoring; prediction; regression analysis; remote sensing; rivers; spatial data; vegetation cover; California; Colorado
Abstract:
... Accurate and timely spatial predictions of vegetation cover from remote imagery are an important data source for natural resource management. High-quality in situ data are needed to develop and validate these products. Point-intercept sampling techniques are a common method for obtaining quantitative information on vegetation cover that have been widely implemented in a number of local and nationa ...
Handle:
10113/5575670
DOI:
10.1016/j.ecolind.2016.09.034

59. A comparison of gap-filling approaches for Landsat-7 satellite data

Author:
Gaohong Yin; Gregoire Mariethoz; Ying Sun; Matthew F. McCabe
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 6653-6679
ISSN:
1366-5901
Subject:
Landsat; algorithms; geostatistics; image analysis; kriging; land cover; landscapes; prediction; regression analysis; remote sensing
Abstract:
... The purpose of this study is to assess the relative performance of four different gap-filling approaches across a range of land-surface conditions, including both homogeneous and heterogeneous areas as well as in scenes with abrupt changes in landscape elements. The techniques considered in this study include: (1) Kriging and co-Kriging; (2) geostatistical neighbourhood similar pixel interpolator ...
DOI:
10.1080/01431161.2017.1363432

60. A comprehensive test of the Locally-Adaptive Model of Archaeological Potential (LAMAP)

Author:
W. Christopher Carleton; Kong F. Cheong; Dan Savage; Jack Barry; James Conolly; Gyles Iannone
Source:
Journal of archaeological science: Reports 2017 v.11 pp. 59-68
ISSN:
2352-409X
Subject:
archaeology; humans; land use; landscapes; models; prediction; remote sensing; surveys; vegetation; Belize
Abstract:
... Extensive archaeological surveys are critical for understanding past human-landscape interaction, but they are frequently impeded by access difficulties, rugged terrain, or obscurant vegetation. These challenges can make extensive surveys prohibitively costly and time-consuming. Consequently, many archaeologists are interested in predictive techniques—i.e., methods that can estimate the potential ...
DOI:
10.1016/j.jasrep.2016.11.027

61. A computational interactome for prioritizing genes associated with complex agronomic traits in rice (Oryza sativa)

Author:
Shiwei Liu; Yihui Liu; Jiawei Zhao; Shitao Cai; Hongmei Qian; Kaijing Zuo; Lingxia Zhao; Lida Zhang
Source:
plant journal 2017 v.90 no.1 pp. 177-188
ISSN:
0960-7412
Subject:
Oryza sativa; agronomic traits; artificial intelligence; data collection; disease resistance; drought tolerance; genes; genetic relationships; landscapes; prediction; protein-protein interactions; proteins; rice; staple foods
Abstract:
... Rice (Oryza sativa) is one of the most important staple foods for more than half of the global population. Many rice traits are quantitative, complex and controlled by multiple interacting genes. Thus, a full understanding of genetic relationships will be critical to systematically identify genes controlling agronomic traits. We developed a genome‐wide rice protein–protein interaction network (Ric ...
DOI:
10.1111/tpj.13475

62. A computational study of wetting on chemically contaminated substrates

Author:
Tobias Luginsland; Roger A. Sauer
Source:
Colloids and surfaces 2017 v.531 pp. 81-92
ISSN:
0927-7757
Subject:
algorithms; contact angle; droplets; finite element analysis; prediction
Abstract:
... The partial wetting of droplets on rigid, chemically contaminated substrates is investigated numerically for Bond numbers Bo≤5. To this end a recently developed numerical framework (Sauer [1] and Sauer et al. [2]) based on a finite element discretisation and a computational contact algorithm is used. Its applicability to wetting on chemically heterogeneous substrates is demonstrated. An analytical ...
DOI:
10.1016/j.colsurfa.2017.06.031

63. A computer-based prediction platform for the reaction of ozone with organic compounds in aqueous solution: kinetics and mechanisms

Author:
Minju Lee; Lorenz C. Blum; Emanuel Schmid; Kathrin Fenner; Urs von Gunten
Source:
Environmental science 2017 v.19 no.3 pp. 465-476
ISSN:
2050-7895
Subject:
aqueous solutions; chemical structure; chemoinformatics; effluents; energy; gases; geometry; models; ozonation; ozone; prediction; reaction kinetics; reaction mechanisms; triclosan; user interface; wastewater
Abstract:
... Ozonation of secondary wastewater effluents can reduce the discharge of micropollutants by transforming their chemical structures. Therefore, a better understanding of the formation of transformation products during ozonation is important. In this study, a computer-based prediction platform for the kinetics and mechanisms of the reactions of ozone with organic compounds was developed to enable in ...
DOI:
10.1039/c6em00584e

64. A cross-sectional study for predicting tail biting risk in pig farms using classification and regression tree analysis

Author:
Annalisa Scollo; Flaviana Gottardo; Barbara Contiero; Sandra A. Edwards
Source:
Preventive veterinary medicine 2017 v.146 pp. 114-120
ISSN:
0167-5877
Subject:
ammonia; climate; commercial farms; cross-sectional studies; disease prevention; farmers; herd health; livestock and meat industry; models; prediction; rearing; regression analysis; risk factors; stocking rate; swine; tail biting; veterinarians
Abstract:
... Tail biting in pigs has been an identified behavioural, welfare and economic problem for decades, and requires appropriate but sometimes difficult on-farm interventions. The aim of the paper is to introduce the Classification and Regression Tree (CRT) methodologies to develop a tool for prevention of acute tail biting lesions in pigs on-farm. A sample of 60 commercial farms rearing heavy pigs were ...
DOI:
10.1016/j.prevetmed.2017.08.001

65. A data-driven machine learning approach to predicting stacking faulting energy in austenitic steels

Author:
N. Chaudhary; A. Abu-Odeh; I. Karaman; R. Arróyave
Source:
Journal of materials science 2017 v.52 no.18 pp. 11048-11076
ISSN:
0022-2461
Subject:
algorithms; artificial intelligence; chemical composition; energy; plastic deformation; prediction; steel; temperature
Abstract:
... Stacking fault energy (SFE) is an intrinsic material property whose value is crucial in determining different secondary deformation mechanisms in austenitic (face-centered cubic, fcc) steels. Considerable experimental and computational work suggests that the SFE itself is highly dependent—in a complex manner—on chemical composition and temperature. Over the past decades, there have been a large nu ...
DOI:
10.1007/s10853-017-1252-x

66. A diagnostic tool for detection of flow-regimes in a microchannel using transient wall temperature signal

Author:
Mrinal Jagirdar; Poh Seng Lee
Source:
Applied energy 2017 v.185 pp. 2232-2244
ISSN:
0306-2619
Subject:
boiling; cameras; cooling; diagnostic techniques; energy; heat transfer; prediction; temperature
Abstract:
... Flow boiling in microchannels has been receiving a lot of attention in recent years because of its high heat flux removal capabilities at low flow rates and low pumping power. An important aspect of flow-boiling experiments is prediction or detection of the prevalent flow-regime. Currently, most researchers use high-speed camera for flow visualization for regime detection. However, in some cases d ...
DOI:
10.1016/j.apenergy.2015.12.111

67. A dual-docking microfluidic cell migration assay (D²-Chip) for testing neutrophil chemotaxis and the memory effect

Author:
Ke YangThese authors contributed equally.; Jiandong Wu; Guoqing Xu; Dongxue Xie; Hagit Peretz-Soroka; Susy Santos; Murray Alexander; Ling Zhu; Michael Zhang; Yong Liu; Francis Lin
Source:
Integrative biology 2017 v.9 no.4 pp. 303-312
ISSN:
1757-9708
Subject:
cell movement; cell structures; chemoattractants; chemotaxis; eukaryotic cells; experimental design; microfluidic technology; models; neutrophils; prediction
Abstract:
... Chemotaxis is a classic mechanism for guiding cell migration and an important topic in both fundamental cell biology and health sciences. Neutrophils are a widely used model to study eukaryotic cell migration and neutrophil chemotaxis itself can lead to protective or harmful immune actions to the body. While much has been learnt from past research about how neutrophils effectively navigate through ...
DOI:
10.1039/c7ib00037e
PubMed:
28367571
PubMed Central:
PMC5511521

68. A dynamic model for the bed temperature prediction of circulating fluidized bed boilers based on least squares support vector machine with real operational data

Author:
You Lv; Feng Hong; Tingting Yang; Fang Fang; Jizhen Liu
Source:
Energy 2017 v.124 pp. 284-294
ISSN:
0360-5442
Subject:
air; boilers; coal; combustion; dynamic models; emissions; fluidized beds; least squares; pollutants; prediction; support vector machines; sustainable technology; temperature
Abstract:
... Circulating fluidized bed (CFB) combustion is a new clean coal technology with advantages of wide fuel flexibility and low pollutant emissions. The bed temperature of CFB boilers is an important factor that influences operating security and pollutant emission generation. An accurate model to describe the dynamic characteristics of bed temperature is beneficial in reducing temperature fluctuations. ...
DOI:
10.1016/j.energy.2017.02.031

69. A dynamic prediction of stability for nitromethane in external electric field

Author:
Fu-de Ren; Duan-lin Cao; Wen-jing Shi; Min You
Source:
RSC advances 2017 v.7 no.74 pp. 47063-47072
ISSN:
2046-2069
Subject:
cleavage (chemistry); dissociation; electric field; energy; hydrogen; prediction
Abstract:
... Adding an external electric field into an energetic material system can increase the energy but the stability may be reduced. In this paper, the effects of external electric fields on the initiation reaction dynamics of CH₃NO₂ (intermolecular and 1,3-intramolecular hydrogen transferences) were investigated using the MP2/6-311++G(2d,p) and CCSD/6-311++G(2d,p) methods. The results show that, when th ...
DOI:
10.1039/c7ra06290g

70. A dynamical systems framework for crop models: Toward optimal fertilization and irrigation strategies under climatic variability

Author:
Norman Pelak; Roberto Revelli; Amilcare Porporato
Source:
Ecological modelling 2017 v.365 pp. 80-92
ISSN:
0304-3800
Subject:
biomass; canopy; climate; crop models; decision support systems; differential equation; evapotranspiration; irrigation management; leaching; nitrogen; prediction; profitability; soil water
Abstract:
... Crop models are widely used for the modeling and prediction of crop yields, as decision support tools, and to develop research questions. Though typically constructed as a set of dynamical equations, crop models are not often analyzed from a specifically dynamical systems point of view, despite its potential to elucidate the roles of feedbacks and internal and external forcings on system stability ...
DOI:
10.1016/j.ecolmodel.2017.10.003

71. A fast genomic selection approach for large genomic data

Author:
Hailan Liu; Guo-Bo Chen
Source:
Theoretical and applied genetics 2017 v.130 no.6 pp. 1277-1284
ISSN:
0040-5752
Subject:
Monte Carlo method; breeding programs; breeding value; computer software; corn; genetic analysis; genetic variance; genome; heritability; marker-assisted selection; normal distribution; prediction; quantitative trait loci; regression analysis; seeds; statistical models
Abstract:
... KEY MESSAGE: We propose a novel computational method for genomic selection that combines identical-by-state (IBS)-based Haseman–Elston (HE) regression and best linear prediction (BLP), called HE-BLP. Genomic best linear unbiased prediction (GBLUP) has been widely used in whole-genome prediction for breeding programs. To determine the total genetic variance of a training population, a linear mixed ...
DOI:
10.1007/s00122-017-2887-3

72. A framework for predicting impacts on ecosystem services from (sub)organismal responses to chemicals

Author:
Valery E. Forbes; Chris J. Salice; Bjorn Birnir; Randy J.F. Bruins; Peter Calow; Virginie Ducrot; Nika Galic; Kristina Garber; Bret C. Harvey; Henriette Jager; Andrew Kanarek; Robert Pastorok; Steve F. Railsback; Richard Rebarber; Pernille Thorbek
Source:
Environmental toxicology and chemistry 2017 v.36 no.4 pp. 845-859
ISSN:
0730-7268
Subject:
case studies; economic valuation; ecosystem services; ecosystems; ecotoxicology; energy; environmental assessment; environmental impact; fish communities; mechanistic models; prediction; risk assessment; toxicity
Abstract:
... Protection of ecosystem services is increasingly emphasized as a risk‐assessment goal, but there are wide gaps between current ecological risk‐assessment endpoints and potential effects on services provided by ecosystems. The authors present a framework that links common ecotoxicological endpoints to chemical impacts on populations and communities and the ecosystem services that they provide. This ...
DOI:
10.1002/etc.3720
PubMed:
28370293
PubMed Central:
PMC6147012

73. A fully integrated electrochemical biosensor platform fabrication process for cytokines detection

Author:
Abdoullatif Baraket; Michael Lee; Nadia Zine; Monique Sigaud; Joan Bausells; Abdelhamid Errachid
Source:
Biosensors & bioelectronics 2017 v.93 pp. 170-175
ISSN:
0956-5663
Subject:
antigens; biomarkers; biosensors; dielectric spectroscopy; electrochemistry; gold; heart failure; inflammation; interleukin-10; monoclonal antibodies; patients; physicians; prediction; secretion; silicon
Abstract:
... Interleukin-1b (IL-1b) and interleukin-10 (IL-10) biomarkers are one of many antigens that are secreted in acute stages of inflammation after left ventricle assisted device (LVAD) implantation for patients suffering from heart failure (HF). In the present study, we have developed a fully integrated electrochemical biosensor platform for cytokine detection at minute concentrations. Using eight gold ...
DOI:
10.1016/j.bios.2016.09.023

74. A general mixture model for sediment laden flows

Author:
Lixin Liang; Xiping Yu; Fabián Bombardelli
Source:
Advances in water resources 2017 v.107 pp. 108-125
ISSN:
0309-1708
Subject:
energy; equations; mathematical models; momentum; prediction; sediments; suspended sediment; turbulent flow; water resources
Abstract:
... A mixture model for general description of sediment-laden flows is developed based on an Eulerian-Eulerian two-phase flow theory, with the aim at gaining computational speed in the prediction, but preserving the accuracy of the complete two-fluid model. The basic equations of the model include the mass and momentum conservation equations for the sediment-water mixture, and the mass conservation eq ...
DOI:
10.1016/j.advwatres.2017.06.012

75. A general solution of the drag force in packed beds of multi-sized particles under creeping fluid flow conditions

Author:
L.W. Rong; K.J. Dong; A.B. Yu
Source:
Powder technology 2017 v.315 pp. 87-97
ISSN:
0032-5910
Subject:
equations; models; particle size distribution; porosity; powders; prediction
Abstract:
... Drag correlations for fluid-particles interactions of multi-sized particle systems are important in many industries. Currently such correlations are modelled at particle-scale (Method A) or cell-scale (Method B). However, they are often inconsistent in predicting either the overall fluid-drag force in a packed bed or the individual drag forces for different sized particles in the bed. In this work ...
DOI:
10.1016/j.powtec.2017.03.048

76. A generalised individual‐based algorithm for modelling the evolution of quantitative herbicide resistance in arable weed populations

Author:
Chun Liu; Melissa E Bridges; Shiv S Kaundun; Les Glasgow; Micheal DK Owen; Paul Neve
Source:
Pest management science 2017 v.73 no.2 pp. 462-474
ISSN:
1526-498X
Subject:
Amaranthus tuberculatus; agroecosystems; algorithms; annual weeds; evolution; fecundity; glyphosate; herbicide resistance; mesotrione; mortality; phenotypic variation; prediction; resistance management; risk; simulation models; summer; Midwestern United States
Abstract:
... BACKGROUND: Simulation models are useful tools for predicting and comparing the risk of herbicide resistance in weed populations under different management strategies. Most existing models assume a monogenic mechanism governing herbicide resistance evolution. However, growing evidence suggests that herbicide resistance is often inherited in a polygenic or quantitative fashion. Therefore, we constr ...
DOI:
10.1002/ps.4317

77. A global analysis of plant recovery performance from water stress

Author:
Jingjing Yin; Taryn L. Bauerle
Source:
Oikos 2017 v.126 no.10 pp. 1377-1388
ISSN:
0030-1299
Subject:
Angiospermae; Gymnospermae; biomass; boreal forests; carbon sequestration; climate; climate change; crops; data collection; drought; ecosystems; habitats; leaf water potential; leaves; photosynthesis; plant adaptation; plant growth; plant taxonomy; porosity; prediction; sclerophyll forests; shrubs; temperate forests; tracheids; trees; tropical forests; water management; water stress
Abstract:
... Plant post‐drought recovery performance is essential to predict shifts in ecosystem dynamics and production during frequent climate change‐driven drought events. Yet, it is not clear how post‐drought recovery is related to evolutionary and geographic variations in plants. In this study, we generated a global data set of post‐drought recovery performance in 140 plant species from published studies. ...
DOI:
10.1111/oik.04534

78. A global analysis of traits predicting species sensitivity to habitat fragmentation

Author:
Douglas A. Keinath; Daniel F. Doak; Karen E. Hodges; Laura R. Prugh; William Fagan; Cagan H. Sekercioglu; Stuart H. M. Buchart; Matthew Kauffman
Source:
Global ecology and biogeography 2017 v.26 no.1 pp. 115-127
ISSN:
1466-822X
Subject:
birds; carnivores; fecundity; forests; grasslands; habitat fragmentation; habitats; landscapes; life history; longevity; models; prediction; probability; reptiles; shrublands
Abstract:
... AIM: Elucidating patterns in species responses to habitat fragmentation is an important focus of ecology and conservation, but studies are often geographically restricted, taxonomically narrow or use indirect measures of species vulnerability. We investigated predictors of species presence after fragmentation using data from studies around the world that included all four terrestrial vertebrate cl ...
DOI:
10.1111/geb.12509

79. A high resolution map of soil types and physical properties for Cyprus: A digital soil mapping optimization

Author:
Corrado Camera; Zomenia Zomeni; Jay S. Noller; Andreas M. Zissimos; Irene C. Christoforou; Adriana Bruggeman
Source:
Geoderma 2017 v.285 pp. 35-49
ISSN:
0016-7061
Subject:
World Reference Base for Soil Resources groups; agricultural land; cost effectiveness; data collection; environmental factors; forests; geochemistry; models; prediction; regression analysis; soil depth; soil formation; soil map; soil surveys; soil texture; texture; trees; uncertainty; Cyprus
Abstract:
... Fine-resolution soil maps constitute important data for many different environmental studies. Digital soil mapping techniques represent a cost-effective method to obtain detailed information about soil types and soil properties over large areas. The main objective of the study was to extend predictions from 1:25,000 legacy soil surveys (including WRB soil groups, soil depth and soil texture classe ...
DOI:
10.1016/j.geoderma.2016.09.019

80. A high throughput targeted and non-targeted method for the analysis of microcystins and anatoxin-A using on-line solid phase extraction coupled to liquid chromatography–quadrupole time-of-flight high resolution mass spectrometry

Author:
Xavier Ortiz; Eva Korenkova; Karl J. Jobst; Karen A. MacPherson; Eric J. Reiner
Source:
Analytical and bioanalytical chemistry 2017 v.409 no.21 pp. 4959-4969
ISSN:
1618-2642
Subject:
Cyanobacteria; algal blooms; amino acid substitution; computer software; dissociation; freshwater; hepatotoxins; laws and regulations; liquid chromatography; mass spectrometry; microcystins; prediction; solid phase extraction; uncertainty
Abstract:
... Microcystins are cyclic heptapeptide hepatotoxins produced by cyanobacteria in freshwater. Sample preparation for the analysis of these cyanotoxins in water from algal blooms can take up to several days due to the matrix complexity and the low detection limits required to comply with current legislation. Moreover, there is a large number of unknown microcystins that could potentially exist in the ...
DOI:
10.1007/s00216-017-0437-0

81. A high-throughput method to quantify root hair area in digital images taken in situ

Author:
Christopher Vincent; Diane Rowland; Chaein Na; Bruce Schaffer
Source:
Plant and soil 2017 v.412 no.1-2 pp. 61-80
ISSN:
0032-079X
Subject:
Carica papaya; Ricinus communis; Zea mays; color; computer software; corn; data collection; digital images; growth and development; image analysis; models; plant response; prediction; regression analysis; root hairs; water uptake
Abstract:
... BACKGROUND AND AIMS: Root hair growth and development are important features of plant response to varying soil conditions and of nutrient and water uptake. Most current methods of characterizing root hairs in the field are unreliable or inefficient. We describe a method to quantify root hair area in digital images, such as those collected in situ by minirhizotron systems. METHODS: This method uses ...
DOI:
10.1007/s11104-016-3016-9

82. A highly specific Escherichia coli qPCR and its comparison with existing methods for environmental waters

Author:
David I. Walker; Jonathan McQuillan; Michael Taiwo; Rachel Parks; Craig A. Stenton; Hywel Morgan; Matthew C. Mowlem; David N. Lees
Source:
Water research 2017 v.126 pp. 101-110
ISSN:
0043-1354
Subject:
Escherichia coli; food safety; messenger RNA; nucleotide sequences; prediction; public health; quantitative polymerase chain reaction; risk reduction; safety assessment; water quality
Abstract:
... The presence of Escherichia coli in environmental waters is considered as evidence of faecal contamination and is therefore commonly used as an indicator in both water quality and food safety analysis. The long period of time between sample collection and obtaining results from existing culture based methods means that contamination events may already impact public health by the time they are dete ...
DOI:
10.1016/j.watres.2017.08.032

83. A hybrid approach based on the Gaussian process with t-observation model for short-term wind speed forecasts

Author:
Jianming Hu; Jianzhou Wang; Liqun Xiao
Source:
Renewable energy 2017 v.114 pp. 670-685
ISSN:
0960-1481
Subject:
algorithms; models; prediction; time series analysis; uncertainty; wavelet; wind farms; wind power; wind speed; China
Abstract:
... Accurate wind speed prediction is a significant factor in improving and optimizing wind power production. Particularly, reliable short-term wind speed forecasting contributes to the real-time optimization of wind farm operation. However, this short-term forecasting task remains challenging due to the strong stochastic nature and dynamic uncertainty of wind speed. This paper proposes a hybrid model ...
DOI:
10.1016/j.renene.2017.05.093

84. A hybrid machine learning model to predict and visualize nitrate concentration throughout the Central Valley aquifer, California, USA

Author:
Katherine M. Ransom; Bernard T. Nolan; Jonathan A. Traum; Claudia C. Faunt; Andrew M. Bell; Jo Ann M. Gronberg; David C. Wheeler; Celia Z. Rosecrans; Bryant Jurgens; Gregory E. Schwarz; Kenneth Belitz; Sandra M. Eberts; George Kourakos; Thomas Harter
Source:
Science of the total environment 2017 v.601-602 pp. 1160-1172
ISSN:
0048-9697
Subject:
anaerobic conditions; aquifers; artificial intelligence; climate; databases; dissolved oxygen; evapotranspiration; groundwater; groundwater contamination; groundwater flow; land use; landscapes; leaching; manganese; models; nitrates; nitrogen; oxidation; prediction; regression analysis; risk; soil; wells; Central Valley of California
Abstract:
... Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater resource. To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500m b ...
DOI:
10.1016/j.scitotenv.2017.05.192

85. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

Author:
Rasmus Houborg; Matthew F. McCabe
Source:
ISPRS Journal of Photogrammetry and Remote Sensing 2017 pp. -
ISSN:
0924-2716
Subject:
Landsat; algorithms; artificial intelligence; data collection; decision support systems; leaf area index; model validation; models; normalized difference vegetation index; prediction; regression analysis; screening; uncertainty
Abstract:
... With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning ...
DOI:
10.1016/j.isprsjprs.2017.10.004

86. A kinetic model of the gelation of konjac glucomannan induced by deacetylation

Author:
Ching-Feng Mao; Cheng-Ho Chen
Source:
Carbohydrate polymers 2017 v.165 pp. 368-375
ISSN:
0144-8617
Subject:
equations; gelation; kinetics; konjac mannan; models; prediction; sodium carbonate
Abstract:
... The gelation of konjac glucomannan (KGM) often involves an induction period featured by an initial drop in modulus. The gelation kinetics recorded as a time-dependent modulus change is composed of an initial drop followed by a steady increase in modulus until an equilibrium stage is reached. In this work, the time-dependent modulus curve is described by a kinetic model which incorporates the casca ...
DOI:
10.1016/j.carbpol.2017.02.078

87. A likelihood ratio-based method to predict exact pedigrees for complex families from next-generation sequencing data

Author:
Verena Heinrich; Tom Kamphans; Stefan Mundlos; Peter N. Robinson; Peter M. Krawitz
Source:
Bioinformatics 2017 v.33 no.1 pp. 72-78
ISSN:
1460-2059
Subject:
Internet; algorithms; automation; bioinformatics; genomics; genotyping; high-throughput nucleotide sequencing; inbreeding; loci; mutation; pedigree; prediction; quality control
Abstract:
... Motivation: Next generation sequencing technology considerably changed the way we screen for pathogenic mutations in rare Mendelian disorders. However, the identification of the disease-causing mutation amongst thousands of variants of partly unknown relevance is still challenging and efficient techniques that reduce the genomic search space play a decisive role. Often segregation- or linkage anal ...
DOI:
10.1093/bioinformatics/btw550
PubMed:
27565584
PubMed Central:
PMC5408770

88. A macroecological perspective for phenological research under climate change

Author:
Hideyuki Doi; Oscar Gordo; Terutaka Mori; Mayumi T. Kubo
Source:
Ecological research 2017 v.32 no.5 pp. 633-641
ISSN:
0912-3814
Subject:
animals; climate change; data collection; ecosystems; meta-analysis; phenology; plants (botany); prediction; remote sensing
Abstract:
... Life cycles of animals and plants worldwide are shifting in response to recent climate change. Macroecology, which deals with biological patterns and processes at a large scale, is ideally suited to address this global phenomenon, thus providing a more general and generalizable understanding of the impacts of climate change on ecosystems. To date, a macroecological approach to examining phenologic ...
DOI:
10.1007/s11284-017-1480-1

89. A market modeling review study on predicting Malaysian consumer behavior towards widespread adoption of PHEV/EV

Author:
Nadia Adnan; Shahrina Mohammad Nordin; Imran Rahman; Mohammad Hadi Amini
Source:
Environmental science and pollution research international 2017 v.24 no.22 pp. 17955-17975
ISSN:
0944-1344
Subject:
carbon; climate change; consumer behavior; energy efficiency; energy use and consumption; gasoline; innovation adoption; markets; models; ownership; pollution; prediction; tanks; transportation; vehicles (equipment); Malaysia
Abstract:
... With the rising concern about climate change, there has been an increased public awareness that has resulted in new government policies to support scientific research for mitigating these problems. Malaysia is among the major energy-intense countries and is under an excessive burden to advance its energy efficiency and to also work towards the reduction of its carbon emission. Plug-in hybrid elect ...
DOI:
10.1007/s11356-017-9153-8

90. A mediational model of obesity related disordered eating: The roles of childhood emotional abuse and self-perception

Author:
Genna Hymowitz; Jessica Salwen; Katie Lee Salis
Source:
Eating behaviors 2017 v.26 pp. 27-32
ISSN:
1471-0153
Subject:
adults; binge eating disorder; body mass index; childhood; college students; eating habits; models; obesity; prediction; questionnaires; risk factors; self-perception
Abstract:
... The extant literature indicates negative self-perceptions are a risk factor for disordered eating (DE) and DE is a risk factor for overweight and obesity. While childhood emotional abuse (EA) is often linked to DE and obesity, it is typically not included in comprehensive models of these health problems. Further investigation of interactions among EA, self-perception, and DE is needed to refine tr ...
DOI:
10.1016/j.eatbeh.2016.12.010
PubMed:
28131963
PubMed Central:
PMC6075711

91. A metabolomics approach for predicting the response to intravenous iron therapy in peritoneal dialysis patients with anemia

Author:
Qiong Wu; Xue-li Lai; Hong-xia Zhao; Zhen-yu Zhu; Zhan-ying Hong; Zhi-yong Guo; Yi-feng Chai
Source:
RSC advances 2017 v.7 no.4 pp. 1915-1922
ISSN:
2046-2069
Subject:
anemia; blood serum; intravenous injection; biomarkers; iron; models; multivariate analysis; patients; kidney diseases; mass spectrometry; liquid chromatography; metabolomics; dialysis; prediction
Abstract:
... Anemia is an almost universal complication of chronic kidney disease (CKD), and nearly all patients with end-stage renal disease (ESRD) and approximately 70% of those with earlier stages of CKD receive treatment for anemia. Due to its significance in the treatment of anemia, there is increased reliance on iron in the renal anemia population. In clinical practice, not every patient benefits from in ...
DOI:
10.1039/c6ra24152b

92. A metapopulation approach to predict species range shifts under different climate change and landscape connectivity scenarios

Author:
Frederico Mestre; Benjamin B. Risk; António Mira; Pedro Beja; Ricardo Pita
Source:
Ecological modelling 2017 v.359 pp. 406-414
ISSN:
0304-3800
Subject:
Microtus cabrerae; climate; climate change; habitat connectivity; landscapes; niches; planning; prediction; simulation models; species dispersal
Abstract:
... Forecasting future species distributions under climate change scenarios using Ecological Niche Models (ENM) is common practice. Typically, these projections do not account for landscape connectivity and species dispersal abilities. When they do account for these factors, they are based on either rather simplistic or overly complex and data-hungry approaches. Here we apply a new approach for predic ...
DOI:
10.1016/j.ecolmodel.2017.06.013

93. A method for estimating transpiration of irrigated urban trees in California

Author:
Elizaveta Litvak; Heather R. McCarthy; Diane E. Pataki
Source:
Landscape and urban planning 2017 v.158 pp. 48-61
ISSN:
0169-2046
Subject:
air; drought; equations; evapotranspiration; forests; hydrologic models; information management; information systems; irrigation management; landscapes; prediction; sapwood; solar radiation; stomatal movement; transpiration; trees; urban areas; vapor pressure; California
Abstract:
... Transpiration of urban forests in southern California is highly uncertain and challenging to quantify because of variability of tree characteristics and stomatal responses among species and locations. However, as California undergoes the most severe drought on record, it is imperative to develop approaches to estimating transpiration of irrigated urban trees (ETrees). We examined the landscape coe ...
DOI:
10.1016/j.landurbplan.2016.09.021

94. A method for using shoreline morphology to predict suspended sediment concentration in tidal creeks

Author:
Scott Ensign; Carolyn Currin; Michael Piehler; Craig Tobias
Source:
Geomorphology 2017 v.276 pp. 280-288
ISSN:
0169-555X
Subject:
aerial photography; databases; geographic information systems; mechanistic models; prediction; salt marshes; sea level; sediments; shorelines; spatial data; streams; suspended sediment; North Carolina
Abstract:
... Improving mechanistic prediction of shoreline response to sea level rise is currently limited by 1) morphologic complexity of tidal creek shorelines that confounds application of mechanistic models, and 2) availability of suspended sediment measurements to parameterize mechanistic models. To address these challenges we developed a metric to distinguish two morphodynamic classes of tidal creek and ...
DOI:
10.1016/j.geomorph.2016.09.036

95. A model for determination of operational conditions for successful shortcut nitrification

Author:
Xiaoguang Liu; Mingu Kim; George Nakhla
Source:
Environmental science and pollution research international 2017 v.24 no.4 pp. 3539-3549
ISSN:
0944-1344
Subject:
ammonia; ammonium nitrogen; dissolved oxygen; nitrification; nitrite nitrogen; nitrites; nitrous acid; pH; prediction; simulation models; temperature
Abstract:
... Accumulation of nitrite in shortcut nitrification is influenced by several factors including dissolved oxygen concentration (DO), pH, temperature, free ammonia (FA), and free nitrous acid (FNA). In this study, a model based on minimum dissolved oxygen concentration (DOₘᵢₙ), minimum/maximum substrate concentration (Sₘᵢₙ and Sₘₐₓ), was developed. The model evaluated the influence of pH (7–9), temper ...
DOI:
10.1007/s11356-016-8017-y

96. A model for simulating the moisture content of standardized fuel sticks of various sizes

Author:
D.W. van der Kamp; R.D. Moore; I.G. McKendry
Source:
Agricultural and forest meteorology 2017 v.236 pp. 123-134
ISSN:
0168-1923
Subject:
bias; calibration; canopy; data collection; evaporation; fuels; heat; prediction; simulation models; sorption; variance; water content
Abstract:
... We describe a model for predicting the moisture content of standardized fuel sticks. Compared to the previously published “Nelson model,” which is the basis for the model currently used by agencies involved with fire management, our model's treatment of moisture diffusion, heat conduction, precipitation interception, and evaporation/sorption processes is simplified while its treatment of radiation ...
DOI:
10.1016/j.agrformet.2017.01.013

97. A modelling framework to predict bat activity patterns on wind farms: An outline of possible applications on mountain ridges of North Portugal

Author:
Carmen Silva; João Alexandre Cabral; Samantha Jane Hughes; Mário Santos
Source:
Science of the total environment 2017 v.581-582 pp. 337-349
ISSN:
0048-9697
Subject:
Chiroptera; decision making; environmental factors; environmental impact; environmental monitoring; farm management; land cover; models; prediction; probability; wind farms; wind power; wind turbines; Portugal
Abstract:
... Worldwide ecological impact assessments of wind farms have gathered relevant information on bat activity patterns. Since conventional bat study methods require intensive field work, the prediction of bat activity might prove useful by anticipating activity patterns and estimating attractiveness concomitant with the wind farm location. A novel framework was developed, based on the stochastic dynami ...
DOI:
10.1016/j.scitotenv.2016.12.135

98. A modified method for pesticide transport and fate in subsurface environment of a winter wheat field of Yangling, China

Author:
Lei Wu; Huanyu Chang; Xiaoyi Ma
Source:
Science of the total environment 2017 v.609 pp. 385-395
ISSN:
0048-9697
Subject:
aquatic environment; crops; farmers; irrigation rates; irrigation scheduling; nonpoint source pollution; pesticide application; pesticide residues; pollution control; prediction; soil depth; soil pollution; triadimefon; water conservation; water requirement; water resources; winter wheat; China
Abstract:
... The Guanzhong region is one of the water resources shortage areas and also an important food producing area in Chinese Loess Plateau. The unreasonable application of irrigation and pesticide not only reduces the utilization rate of pesticides, but also is a potential threat to aquatic environments. In order to explore the reasonable application pattern of irrigation and pesticide, a modified metho ...
DOI:
10.1016/j.scitotenv.2017.07.116

99. A modified poisson-boltzmann equation applied to protein adsorption

Author:
Marlon de Souza Gama; Mirella Simões Santos; Eduardo Rocha de Almeida Lima; Frederico Wanderley Tavares; Amaro Gomes Barreto Barreto
Source:
Journal of chromatography 2017 pp. -
ISSN:
0021-9673
Subject:
adsorption; electrostatic interactions; equations; ion exchange chromatography; ions; pH; prediction; proteins; salt concentration; salts; temperature; thermodynamics
Abstract:
... Ion-exchange chromatography has been widely used as a standard process in purification and analysis of protein, based on the electrostatic interaction between the protein and the stationary phase. Through the years, several approaches are used to improve the thermodynamic description of colloidal particle-surface interaction systems, however there are still a lot of gaps specifically when describi ...
DOI:
10.1016/j.chroma.2017.11.022

100. A multi-omic approach to elucidate low-dose effects of xenobiotics in zebrafish (Danio rerio) larvae

Author:
Susie S.Y. Huang; Jonathan P. Benskin; Nik Veldhoen; Bharat Chandramouli; Heather Butler; Caren C. Helbing; John R. Cosgrove
Source:
Aquatic toxicology 2017 v.182 pp. 102-112
ISSN:
0166-445X
Subject:
Danio rerio; acetaminophen; animal models; fish; larvae; mechanism of action; metabolites; metabolome; metabolomics; phenotype; prediction; toxicity; transcriptome; xenobiotics
Abstract:
... Regulatory-approved toxicity assays such as the OECD Fish Embryo Toxicity Assay (TG236) allow correlation of chemical exposure to adverse morphological phenotypes. However, these assays are ineffective in assessing sub-lethal (i.e. low-dose) effects, or differentiating between similar phenotypes induced by different chemicals. Inclusion of multi-omic analyses in studies investigating xenobiotic ac ...
DOI:
10.1016/j.aquatox.2016.11.016