scholarly journals Predicting Microbial Species in a River Based on Physicochemical Properties by Bio-Inspired Metaheuristic Optimized Machine Learning

2019 ◽  
Vol 11 (24) ◽  
pp. 6889 ◽  
Author(s):  
Jui-Sheng Chou ◽  
Chang-Ping Yu ◽  
Dinh-Nhat Truong ◽  
Billy Susilo ◽  
Anyi Hu ◽  
...  
Keyword(s):  
Missing Values ◽  
Feature Reduction ◽  
Microbial Structures ◽  
Experimental Planning ◽  
Microbial Species ◽  
Bioclimatic Modeling ◽  
Data Points ◽  
Accuracy Of Prediction ◽  
The Relationship ◽  
Potential Use

The main goal of the analysis of microbial ecology is to understand the relationship between Earth’s microbial community and their functions in the environment. This paper presents a proof-of-concept research to develop a bioclimatic modeling approach that leverages artificial intelligence techniques to identify the microbial species in a river as a function of physicochemical parameters. Feature reduction and selection are both utilized in the data preprocessing owing to the scarce of available data points collected and missing values of physicochemical attributes from a river in Southeast China. A bio-inspired metaheuristic optimized machine learner, which supports the adjustment to the multiple-output prediction form, is used in bioclimatic modeling. The accuracy of prediction and applicability of the model can help microbiologists and ecologists in quantifying the predicted microbial species for further experimental planning with minimal expenditure, which is become one of the most serious issues when facing dramatic changes of environmental conditions caused by global warming. This work demonstrates a neoteric approach for potential use in predicting preliminary microbial structures in the environment.

scholarly journals Chronic Disease Prediction Using Character-Recurrent Neural Network in The Presence of Missing Information

2019 ◽  
Vol 9 (10) ◽  
pp. 2170 ◽  
Author(s):  
Changgyun Kim ◽  
Youngdoo Son ◽  
Sekyoung Youm
Keyword(s):  
Neural Network ◽  
Chronic Diseases ◽  
Recurrent Neural Network ◽  
Multilayer Perceptron ◽  
Missing Values ◽  
Health And Nutrition ◽  
Partially Observed ◽  
Data Points ◽  
Multilayer Perceptron Network ◽  
The Relationship

The aim of this study was to predict chronic diseases in individual patients using a character-recurrent neural network (Char-RNN), which is a deep learning model that treats data in each class as a word when a large portion of its input values is missing. An advantage of Char-RNN is that it does not require any additional imputation method because it implicitly infers missing values considering the relationship with nearby data points. We applied Char-RNN to classify cases in the Korea National Health and Nutrition Examination Survey (KNHANES) VI as normal status and five chronic diseases: hypertension, stroke, angina pectoris, myocardial infarction, and diabetes mellitus. We also employed a multilayer perceptron network for the same task for comparison. The results show higher accuracy for Char-RNN than for the conventional multilayer perceptron model. Char-RNN showed remarkable performance in finding patients with hypertension and stroke. The present study utilized the KNHANES VI data to demonstrate a practical approach to predicting and managing chronic diseases with partially observed information.

Identifying Physico-Chemical Laws from the Robotically Collected Data

2019 ◽  
Author(s):  
Liwei Cao ◽  
Danilo Russo ◽  
Vassilios S. Vassiliadis ◽  
Alexei Lapkin
Keyword(s):  
Experimental Data ◽  
Numerical Models ◽  
Predictor Variable ◽  
Physical Models ◽  
Training Data ◽  
Mixed Integer ◽  
Physico Chemical ◽  
Data Points ◽  
Future Work ◽  
The Relationship

<p>A mixed-integer nonlinear programming (MINLP) formulation for symbolic regression was proposed to identify physical models from noisy experimental data. The formulation was tested using numerical models and was found to be more efficient than the previous literature example with respect to the number of predictor variables and training data points. The globally optimal search was extended to identify physical models and to cope with noise in the experimental data predictor variable. The methodology was coupled with the collection of experimental data in an automated fashion, and was proven to be successful in identifying the correct physical models describing the relationship between the shear stress and shear rate for both Newtonian and non-Newtonian fluids, and simple kinetic laws of reactions. Future work will focus on addressing the limitations of the formulation presented in this work, by extending it to be able to address larger complex physical models.</p><p><br></p>

The Relationship between Mobility and COVID-19 in Germany: Modeling Case Occurrence using Apple's Mobility Trends Data

2021 ◽  
Author(s):  
Mark David Walker ◽  
Mihály Sulyok
Keyword(s):  
Generalized Additive Models ◽  
Information Criterion ◽  
Additive Models ◽  
Online Data ◽  
German Government ◽  
Explanatory Variables ◽  
Mobility Data ◽  
Community Mobility ◽  
The Relationship ◽  
Potential Use

Abstract Background Restrictions on social interaction and movement were implemented by the German government in March 2020 to reduce the transmission of coronavirus disease 2019 (COVID-19). Apple's “Mobility Trends” (AMT) data details levels of community mobility; it is a novel resource of potential use to epidemiologists. Objective The aim of the study is to use AMT data to examine the relationship between mobility and COVID-19 case occurrence for Germany. Is a change in mobility apparent following COVID-19 and the implementation of social restrictions? Is there a relationship between mobility and COVID-19 occurrence in Germany? Methods AMT data illustrates mobility levels throughout the epidemic, allowing the relationship between mobility and disease to be examined. Generalized additive models (GAMs) were established for Germany, with mobility categories, and date, as explanatory variables, and case numbers as response. Results Clear reductions in mobility occurred following the implementation of movement restrictions. There was a negative correlation between mobility and confirmed case numbers. GAM using all three categories of mobility data accounted for case occurrence as well and was favorable (AIC or Akaike Information Criterion: 2504) to models using categories separately (AIC with “driving,” 2511. “transit,” 2513. “walking,” 2508). Conclusion These results suggest an association between mobility and case occurrence. Further examination of the relationship between movement restrictions and COVID-19 transmission may be pertinent. The study shows how new sources of online data can be used to investigate problems in epidemiology.

scholarly journals Human TERT promoter mutations as a prognostic biomarker in glioma

2021 ◽  
Vol 147 (4) ◽  
pp. 1007-1017
Author(s):  
Branka Powter ◽  
Sarah A. Jeffreys ◽  
Heena Sareen ◽  
Adam Cooper ◽  
Daniel Brungs ◽  
...  
Keyword(s):  
Clinical Utility ◽  
Nucleotide Polymorphism ◽  
Liquid Biopsies ◽  
Single Nucleotide ◽  
Tert Promoter ◽  
Tert Promoter Mutations ◽  
Potential Clinical Utility ◽  
Promoter Mutations ◽  
The Relationship ◽  
Potential Use

AbstractThe TERT promoter (pTERT) mutations, C228T and C250T, play a significant role in malignant transformation by telomerase activation, oncogenesis and immortalisation of cells. C228T and C250T are emerging as important biomarkers in many cancers including glioblastoma multiforme (GBM), where the prevalence of these mutations is as high as 80%. Additionally, the rs2853669 single nucleotide polymorphism (SNP) may cooperate with these pTERT mutations in modulating progression and overall survival in GBM. Using liquid biopsies, pTERT mutations, C228T and C250T, and other clinically relevant biomarkers can be easily detected with high precision and sensitivity, facilitating longitudinal analysis throughout therapy and aid in cancer patient management.In this review, we explore the potential for pTERT mutation analysis, via liquid biopsy, for its potential use in personalised cancer therapy. We evaluate the relationship between pTERT mutations and other biomarkers as well as their potential clinical utility in early detection, prognostication, monitoring of cancer progress, with the main focus being on brain cancer.

Field Assisted Sintering Technology (FAST) Model for Prediction of Final Properties

2010 ◽  
Author(s):  
Rajiv Paul ◽  
Anil K. Kulkarni ◽  
Jogender Singh
Keyword(s):  
Electrical Breakdown ◽  
Extensive Literature ◽  
Heating Rates ◽  
Predictive Tool ◽  
Simultaneous Application ◽  
Plasma Sintering ◽  
Spark Plasma ◽  
Data Points ◽  
Field Assisted Sintering ◽  
The Relationship

Sintering is the process of making materials from powder form by heating the powder below its melting point until the particles fuse to each other. Field assisted sintering technology (FAST), also sometimes known as spark plasma sintering (SPS), uses a pulsed and/or continuous electric current along with the simultaneous application of compressive pressure which leads to extremely high heating rates and short processing durations. A high relative density and small grain size promote superior properties such as greater hardness and electrical breakdown. Hence, selection of the proper sintering parameters is of paramount importance and a predictive model would be extremely useful in narrowing the range of experimental parameters. This will drastically reduce the number of extra attempts at obtaining certain properties in a material and save experimentation time, effort and material to name a few. Four of the most important FAST parameters: target temperature, holding time, heating rate and initial particle size, have been reviewed to assess their effect on the densification, hardening and grain growth of Alumina, Copper, Silicon Carbide, Tungsten and Tungsten Carbide through extensive literature survey. The relationship between each has been incorporated in a Microsoft Excel program which acts as a predictive tool to determine an estimate of the final properties based on the initial parameters chosen. This is done by curve fitting a polynomial onto the existing data points as closely as possible and using the polynomial to obtain final properties as a function of the initial parameters. The model was verified against an existing paper which sought to obtain the optimum sintering parameters for Copper. While the actual experimentation range was 400°C to 800°C, the program would have suggested a much narrower range from 650°C to 800°C and hence saved unnecessary additional efforts.

Limitations to prediction of maximal oxygen intake

1964 ◽  
Vol 19 (5) ◽  
pp. 919-927 ◽  
Author(s):  
Loring B. Rowell ◽  
Henry L. Taylor ◽  
Yang Wang
Keyword(s):  
Metabolic Rate ◽  
Pulse Rate ◽  
Oxygen Intake ◽  
Physical Conditioning ◽  
Maximal Oxygen Intake ◽  
Before And After ◽  
Normal Men ◽  
Accuracy Of Prediction ◽  
Relationship Of ◽  
The Relationship

The predictability of maximal O2 intake (max Vo2) was studied in four groups of normal men, 18–24 years of age. Prediction of max Vo2 was made from pulse rate and Vo2 at a single submaximal workload at an ambient temperature of 78 F by use of the nomogram of Åstrand and Ryhming (1954) and underestimated actual max Vo2 by 27 ± 7% and 14 ± 7% in a sedentary group, before and after 2frac12–3 months of physical training, and by 5.6 ȁ 4% in a group of ten endurance athletes. Accuracy of prediction in all groups varied with approximation of pulse rate to 128 beats/min at 50% of max Vo2. Nonspecific stresses increased predictive errors in all groups. Constants b (slope) and A (intercept) in the regression equation Vo2 = bP – A (where P is pulse rate), were determined from Vo2 and pulse measured at four submaximal workloads requiring 13–28 ml O2/kg min. Prediction of max Vo2 by extrapolation of the slope to maximal pulse rate resulted in underestimation of 700–800 ml O2/min. Removal of 14% of circulating hemoglobin decreased max Vo2 by 4% but there was no change in pulse rates or predicted max Vo2. The relationship of RQ to V22 during work provided no reliable basis for prediction of max Vo2. exercise pulse rate, oxygen intake, relationship; pulse rate, oxygen intake relationship in exercise; metabolic rate, maximal aerobic prediction of; aerobic metabolic rate, maximal, prediction of; phlebotomy, effect on maximal oxygen intake, pulse rate; blood loss, effect on maximal oxygen intake, pulse rate; training, effect on maximal oxygen intake, pulse rates; physical conditioning, effect on maximal oxygen intake, pulse rates Submitted on October 4, 1963

scholarly journals Exploring the relation between aerosol optical depth and PM<sub>2.5</sub> at Cabauw, the Netherlands

2008 ◽  
Vol 8 (5) ◽  
pp. 17939-17986 ◽  
Author(s):  
M. Schaap ◽  
A. Apituley ◽  
R. M. A. Timmermans ◽  
R. B. A. Koelemeijer ◽  
G. de Leeuw
Keyword(s):  
The Netherlands ◽  
Ground Level ◽  
Weather Conditions ◽  
Fair Weather ◽  
Modis Aod ◽  
Data Points ◽  
Set Up ◽  
The Relationship ◽  
Lidar Observations ◽  
Pm2.5 Concentration

Abstract. To acquire daily estimates of PM2.5 distributions based on satellite data one depends critically on an established relation between AOD and ground level PM2.5. In this study we aimed to experimentally establish the AOD-PM2.5 relationship for the Netherlands. For that purpose an experiment was set-up at the AERONET site Cabauw. The average PM2.5 concentration during this ten month study was 18 μg/m3, which confirms that the Netherlands are characterised by a high PM burden. A first inspection of the AERONET level 1.5 (L1.5) AOD and PM2.5 data at Cabauw showed a low correlation between the two properties. However, after screening for cloud contamination in the AERONET L1.5 data, the correlation improved substantially. When also constraining the dataset to data points acquired around noon, the correlation between AOD and PM2.5 amounted to R2=0.6 for situations with fair weather. This indicates that AOD data contain information about the temporal evolution of PM2.5. We had used LIDAR observations to detect residual cloud contamination in the AERONET L1.5 data. Comparison of our cloud-screed L1.5 with AERONET L2 data that became available near the end of the study showed favorable agreement. The final relation found for Cabauw is PM2.5=124.5*AOD–0.34 (with PM2.5 in μg/m3) and is valid for fair weather conditions. The relationship determined between MODIS AOD and ground level PM2.5 at Cabauw is very similar to that based on the much larger dataset from the sun photometer data, after correcting for a systematic overestimation of the MODIS data of 0.05. We applied the relationship to a MODIS composite map to assess the PM2.5 distribution over the Netherlands. Spatial dependent systematic errors in the MODIS AOD, probably related to variability in surface reflectance, hamper a meaningful analysis of the spatial distribution of PM2.5 using AOD data at the scale of the Netherlands.

scholarly journals Application of holography and automated image processing for laboratory experiments on mass and fall speed of small cloud ice crystals

2020 ◽  
Vol 20 (23) ◽  
pp. 14889-14901
Author(s):  
Maximilian Weitzel ◽  
Subir K. Mitra ◽  
Miklós Szakáll ◽  
Jacob P. Fugal ◽  
Stephan Borrmann
Keyword(s):  
Three Dimensional ◽  
Ice Crystals ◽  
Local Cooling ◽  
Ice Cloud ◽  
Before And After ◽  
Data Points ◽  
Melting Crystal ◽  
Cloud Ice ◽  
Automated Image Processing ◽  
The Relationship

Abstract. An ice cloud chamber was developed at the Johannes Gutenberg University of Mainz for generating several thousand data points for mass and sedimentation velocity measurements of ice crystals with sizes less than 150 µm. Ice nucleation was initiated from a cloud of supercooled droplets by local cooling using a liquid nitrogen cold finger. Three-dimensional tracks of ice crystals falling through the slightly supersaturated environment were obtained from the reconstruction of sequential holographic images, automated detection of the crystals in the hologram reconstructions, and particle tracking. Through collection of the crystals and investigation under a microscope before and after melting, crystal mass was determined as a function of size. The experimentally obtained mass versus diameter (m(D)) power law relationship resulted in lower masses for small ice crystals than from commonly adopted parameterizations. Thus, they did not support the currently accepted extrapolation of relationships measured for larger crystal sizes. The relationship between Best (X) and Reynolds (Re) numbers for columnar crystals was found to be X=15.3 Re1.2, which is in general agreement with literature parameterizations.

scholarly journals The effect of the CEO media coverage on corporate brand equity: evidence from Poland

2021 ◽  
Vol 12 (2) ◽  
pp. 499-523
Author(s):  
Anna Górska ◽  
Grzegorz Mazurek
Keyword(s):  
Brand Equity ◽  
Media Coverage ◽  
Value Added ◽  
Corporate Brand ◽  
Personal Brand ◽  
Data Points ◽  
New Perspective ◽  
Media Monitoring ◽  
The Impact ◽  
The Relationship

Research background: Despite increased attention in the literature to the importance of the CEO?s brand for companies, understanding of the effect of the CEO brand on the corporate brand remains limited. To contribute to this discussion, this paper investigates different facets of the impact of the CEO brand, and particularly its media coverage, on corporate brand equity. Purpose of the article: This study investigates the relationship between the different aspects of the CEO brand?s media coverage and corporate brand equity. Methods: Comprehensive media monitoring in the press and online sourcing of CEOs from the strongest Polish brands were conducted. For three years (2014?2017), media monitoring covered 81 CEOs, resulting in over 44,000 data points for this study. Regression analysis was conducted to determine whether a relationship exists between different facets of the CEO?s personal brand and company brand equity. Findings & value added: This study provides a new perspective on the relationship between the CEO and corporate brands and showcases empirical evidence of the CEO brand?s relationship with corporate brand equity. It introduces two relevant and novel variables (CEO brand reach and CEO brand advertising value equivalent [AVE]) to the literature, which have been limited to the number of mentions and its sentiment. Accordingly, this study contributes to the emerging literature of CEO branding within the branding field. Contrary to expectation, the intensity of media coverage alone was not significant. Results indicate that reach and AVE of CEO media exposure are reflected in the corporate brand equity. The study also finds that negative sentiment toward a CEO?s brand negatively affects corporate brand equity. The study adds to the growing stream of literature on the role of CEO brand.

scholarly journals Relationship Between Creatinine and Body Weight Ratio and Diabetes Mellitus in a Chinese Cohort Study

2021 ◽  
Author(s):  
Xinyu Wang ◽  
Zhuangsen Chen ◽  
Fan Yang ◽  
Xiaohan Ding ◽  
Changchun Cao ◽  
...  
Keyword(s):  
Body Weight ◽  
Missing Values ◽  
Proportional Hazards ◽  
Cox Regression ◽  
Weight Ratio ◽  
Cox Proportional Hazards ◽  
Additive Models ◽  
Cox Regression Analysis ◽  
Non Linear ◽  
The Relationship

Abstract Background: Research on the relationship between Creatinine to Body Weight Ratios (Cre/BW ratios) and the prevalence of diabetes is still lacking. The aim of this study was to investigate the potential association between Cre/BW ratios and incident of diabetes in Chinese adults.Methods: This retrospective study was conducted in 199,526 patients from Rich Healthcare Group in China from 2010 to 2016. The participants were divided into quartiles of the Cre/BW ratios. Multivariate multiple imputation and dummy variables were used to handle missing values. Cox proportional-hazards regression was used to investigate the association of Cre/BW and diabetes. Generalized additive models(GAM) were used to identify non-linear relationships.Results: Of all participants,after handling missing values and adjustment for potential confounders, the multivariate Cox regression analysis results showed that Cre/BW ratios was inversely associated with diabetes risk( HR: 0.268; 95% CI:0.229 to 0.314, P < 0.00001).For men, the hazard ratios(HRs) of incident diabetes was 0.255(95%CI: 0.212-0.307);and for women HR= 0.297 (95%CI: 0.218-0.406).Moreover, sensitivity analysis confirmed the stability of the results. Furthermore, GAM revealed a saturation effect on the independent association between Cre/BW and incident of diabetes.Conclusions: This study demonstrated that increased Cre/BW is negatively correlated with incident of diabetes in Chinese for the first time. And we found that the relationship between Cre/BW and incident of diabetes was non-linear.

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