Re-Scaling of Energy in the Stringy Charged Black Hole Solutions using Approximate Symmetries

This paper is devoted to study the energy problem in general relativity using approximate Lie symmetry methods for differential equations. We evaluate second-order approximate symmetries of the geodesic equations for the stringy charged black hole solutions. It is concluded that energy must be re-scaled by some factor in the second-order approximation.Comment: 18 pages, accepted for publication in Canadian J. Physic

Productivity and performance of irrigated wheat farms across canal commands in the Lower Indus Basin

Irrigated farmingWheatProductivityPerformance evaluationWater managementCropping systemsWater supplySoil propertiesModels

Lead Isotope Determinations by Mass Spectrometry and Its Application by Isotope Dilution Technique

A method for the determination of Lead isotope ratios by thermal ionization mass spectrometry (TIMS). This method also describes the application of isotope dilution mass spectrometry (IDMS) to the field of reference material (RM) characterization focusing on the approach. Emphasis is placed on IDMS measurements of highest analytical quality. Basic principles as well as the equation system are being recalled. The evaporation and ionization currents are determined for a measurement of isotopic ratios of head, employing double rhenium filament assembly in the ion source and Faraday cup as the detector using the presently available RM.         

Predicting Breast Cancer Survivability

this study concentrates on Predicting Breast Cancer Survivability using data mining, and comparing between three main predictive modeling tools. Precisely, we used three popular data mining methods: two from machine learning (artificial neural network and decision trees) and one from statistics (logistic regression), and aimed to choose the best model through the efficiency of each model and with the most effective variables to these models and the most common important predictor. We defined the three main modeling aims and uses by demonstrating the purpose of the modeling. By using data mining, we can begin to characterize and describe trends and patterns that reside in data and information. The preprocessed data set contents were of 87 variables and the total of the records are 457,389; which became 93 variables and 90308 records for each variable, and these dataset were from the SEER database. We have achieved more than three data mining techniques and we have investigated all the data mining techniques and finally we find the best thing to do is to focus about these data mining techniques which are Artificial Neural Network, Decision Trees and Logistic Regression by using SAS Enterprise Miner 5.2 which is in our view of point is the suitable system to use according to the facilities and the results given to us. Several experiments have been conducted using these algorithms. The achieved prediction implementations are Comparison-based techniques. However, we have found out that the neural network has a much better performance than the other two techniques. Finally, we can say that the model we chose has the highest accuracy which specialists in the breast cancer field can use and depend on

How the presentation of patient information and decision-support advisories influences opioid prescribing behavior: A simulation study

ObjectiveThe United States faces an opioid crisis. Integrating prescription drug monitoring programs into electronic health records offers promise to improve opioid prescribing practices. This study aimed to evaluate 2 different user interface designs for prescription drug monitoring program and electronic health record integration.Materials and MethodsTwenty-four resident physicians participated in a randomized controlled experiment using 4 simulated patient cases. In the conventional condition, prescription opioid histories were presented in tabular format, and computerized clinical decision support (CDS) was provided via interruptive modal dialogs (ie, pop-ups). The alternative condition featured a graphical opioid history, a cue to visit that history, and noninterruptive CDS. Two attending pain specialists judged prescription appropriateness.ResultsParticipants in the alternative condition wrote more appropriate prescriptions. When asked after the experiment, most participants stated that they preferred the alternative design to the conventional design.ConclusionsHow patient information and CDS are presented appears to have a significant influence on opioid prescribing behavior

A look at the potential of big data in nurturing intuition in organisational decision makers

YesAs big data (BD) and data analytics having gain significance the industry expects helping executives will eventually move towards evidence based decision making. The hope is to achieve more sustainable competitive advantage for their organisations. A key question is whether executives make decisions by intuition. This leads to another question whether big data would ever substitute human intuition. In this research, the ‘mind-set’ of executives about application and limitations of big data be investigated by taking into account their decision making behaviour. The aim is to look deeply into how BD technologies facilitate greater intuitiveness in executives, and consequently lead to faster and sustainable business growth