77 research outputs found
Suicidal and homicidal tendencies after Lyme disease: an ignored problem
No full textAitzaz Munir,1 Muhammad Aadil,2 Ahmad Rehan Khan3 1Department of Psychiatry, Howard University, Washington, DC, USA; 2Department of Psychiatry, Rush University Medical Center, Chicago, IL, USA; 3Department of Psychiatry, University of North Dakota, Grand Forks, ND, USA We would like to applaud the author for conducting such an important study by performing a comprehensive assessment of suicide and its association with Lyme-associated diseases (LADs).1 It is the first study of its kind, and it raises a need for further investigation on this subject. Suicide is a major health care issue in the USA, contributing to almost 42,773 deaths in the USA in 2014.2 There is no data available specific to suicide associated with LAD. Dr Bransfield inferred the possible prevalence of suicide associated with LAD by an indirect method which revealed that 414,540 patients with LAD have suicidal ideation, 31,100 attempt suicide and a total of 1,244 commit suicide in the USA per year from LAD.1,2 View the original paper by Bransfield. 
Estimating Passenger Car Equivalent Factors for Heterogeneous Traffic Using Occupancy-Density Linear Regression Model
No full textA variety of methods have been proposed in the existing literature for the estimation of passenger car equivalent (PCE) factors. These methods are based on the comparison of selected attributes of different vehicles. This research, for the first time, utilizes the basic notion of the linear relationship between road area occupancy and density for the estimation of PCE factors for different vehicle types in heterogeneous traffic. Aerial photographs obtained from an unmanned aerial vehicle (UAV) were analyzed to estimate the road area occupancy and the number of vehicles classified in seven selected groups. A linear least-squares regression model was developed between road area occupancy and classified vehicle count. The coefficients of the occupancy-density linear regression model were used to estimate PCE and motorcycle equivalent (MCE) factors. The comparison of the estimated set of PCE values with the values reported in the literature shows that PCE factors estimated using the proposed method are reasonable and produce a better occupancy-density relationship than the other studies. In comparison with the existing methods that rely on lane-based measurements, the proposed method is well suited for traffic with weak/no lane discipline, as it considers the entire road width and the dynamics of lateral movement of different types of vehicles. The proposed method does not need extensive traffic data of speeds, headways, flow rates, and so forth, and is applicable on aerial photographs obtained from other sources, such as satellites.Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported with funding from Exascale Open Data Analytics Lab, National Center for Big Data and Cloud Computing (NCBC) and the Higher Education Commission of Pakistan.
Acknowledgments
The authors are thankful to research students Syed Hassan Ali, Haseeb Ahmed, Zohaib Ahmed, Aqib Abbasi, Asad Rehan, Mirza Ali Haider, Syed Abbas Hasan Zaidi, and Omema for their help in this research
Waste Biorefineries: Future Energy, Green Products and Waste Treatment
No full textThis eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contac
Prediction of carbon dioxide emissions from Atlantic Canadian potato fields using advanced hybridized machine learning algorithms: Nexus of field data and modelling
No full textIn this study, three novel machine learning algorithms of additive regression-random forest (AR-RF), Iterative Classifier Optimizer (ICO-AR-RF), and multi-scheme (MS-RF) were explored for carbon dioxide (CO2) flux rate prediction from three agricultural fields. To build the dataset, 401 samples were collected from two fields in Prince Edward Island (PEI) and 122 samples from the New Brunswick (NB), Canada. In addition, soil moisture (SM), temperature (ST), and electrical conductivity (EC), alongside eight climatic variables including wind speed (WS), solar radiation (SR), relative humidity (RH), precipitation (PCP), air temperature (AT), dew point (DP), vapour pressure difference (VPD) and reference evapotranspiration (ETo) were also collected. Greedy stepwise (GS) approach was implemented for feature selection. Finally, different qualitative (scatter plot, line graph, Taylor diagram, box plot, and Rug plot), and quantitative (uncertainty analysis, root mean square error (RMSE), percent of BIAS (PBIAS), Nash Sutcliff efficiency (NSE) and RMSE-observations standard deviation ratio (RSR)) techniques were used for model evaluation and comparison. Results of feature selection approaches revealed that DP, AT, SM, and ST are the four most effective variables at CO2 prediction in PEI, while AT, RH, DP, and ST are the most effective in the NB study area. For optimum input scenario, the GS algorithm was applied, and results showed that a combination of DP, AT, ST, SM, and ETo was the best for the PEI study area, while for NB, all input variables should be involved. Our analysis, for prediction of CO2 fluxes, confirmed that the ICO-AR-RF model performed the best at both PEI (RMSE=0.70, NSE=0.76, PBIAS=-5.11, RSR=0.48) and NB (RMSE=0.74, NSE=0.75, PBIAS=3.23, RSR=0.50), followed by MS-RF and AR-RF. Uncertainty analysis showed that CO2 prediction is more sensitive to input scenario selection than models in both study areas. Results revealed that climatic variables are more effective in CO2 prediction than soil characteristics and the developed hybrid model ICO-AR-RF can be a promising tool for decision-makers and beneficial for stakeholders.Atlantic Canada Opportunities AgencyGovernment of CanadaNatural Science and Engineering Council of CanadaDepartment of Energy, Environment and Climate ActionGovernment of Prince Edward Islan
Waste Biorefineries: Future Energy, Green Products and Waste Treatment
No full textThis eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contac
Fuel Optimization of a Cement Industry, Case Study
No full textThe Portland Cement manufacturing required energy to run the plant and kiln for manufacturing cement clinker. Due to the non-availability of natural gas, cement manufacturers were forced to investigate alternative fuels which are cheaper, easily available and had a lower environmental impact. Currently, cement manufacturers are using rice husk, Municipal Solid Waste (MSW), Coal and furnace oil as alternative sources of fuel. This paper aims to identify the best alternative energy source used in cement kilns. The scope of the paper remains within the kiln energy requirements. The linear programming model is used to minimize the energy cost of the kiln requirements amongst the alternative energy source considering the calorific value, availability per day and plant capacity. The finding of this paper suggests that coal will be the best alternative amongst all the four alternatives available at the quoted cost but due to plant processing limitations, the MSW can be mixed in some content as well. The limitation of the study is toward cost only, the environmental impact of different fuel type emissions is not part of this study
Resistance and detoxification enzyme activities to bifenthrin in Oxycarenus hyalinipennis (Hemiptera: Lygaeidae)
No full text
- …
