Conducting a Drinking Water Clinic. Erin James Ling Virginia Master Well Owner Network Training. Overview . Planning for and conducting a clinic Reporting outcomes and impacts Agent evaluation form Follow-up survey of clinic participants Working with volunteersBy xadrian
Arbovirus Surveillance: Laboratory Tests. Utah West Nile Virus Conference February 9, 2004 Dr. June Inez Pounder Utah Department of Health Laboratory. Surveillance –Lab Tests 2003. Human- WNV IgM ELISA 36 Utah residents tested 1 + Uintah County 9/18 4 + Travel associatedBy thora
ELR Technical Assistance Current-state and Case Studies June, 2012 CSTE Annual Meeting. Wesley R. Kennemore, MD, MS, PE, Assoc. of Public Health Laboratories. 205-937-1211 , email@example.com. ELR Programs at APHL Informatics. Overlap period. Two ELR programs LTIAPH ELRTABy moke
Highlights 2006: Quality Assurance. Field QC: continued XAD sampler vs whole water splits Working with old labs for previous analytes Se dissolved vs total problem (BRL) EBMUDNew HRGCMS, & larger samples size (heterogeneity) Overcame ND problem, still some variability w/ BDE 209By thi
ELR Technical Assistance Current-state and Case Studies June, 2012 CSTE Annual Meeting. Wesley R. Kennemore, MD, MS, PE, Assoc. of Public Health Laboratories. 205-937-1211 , firstname.lastname@example.org. ELR Programs at APHL Informatics. Overlap period. Two ELR programs LTIAPH ELRTABy emilia
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Presenter: André Thomas, Lecturer, Department of Visualization, LIVE Lab / Texas A&M University In this talk I will share our experience designing and developing a proof of concept for a learning game in a research lab and taking it all the way to a full product. During the talk we illustrate our experience in setting up a spin-off company from the university and will talk about pitfalls and lessons learned along the way.
Lab: Graphing Lab. Showing patterns & trends. Practice makes perfect !. 12. 10. 0. 4. 8. 2. 6. M. O. A. D. S. P. L. What foods do slugs like to eat?. Bar graph !. amount food eaten (g). Conclusion?. Slugs like apples best & dog food the least. food source. 12. 15. 18. 0.
3 rd Party Academic Access to NNL Central Lab – Commercial Arrangements. Bob Williamson Head of Operational Planning. Commercial Arrangements. Funded through University. Direct Project Costs. Indirect Project Costs. Funded by NDA as part of NDA / DCF Agreement. Commercial Arrangements.
Lab #2 Maze Lab. Problem. What variables can change the amount of time required to complete a maze?. Materials. Printed Maze. Procedure. Obtain a printed maze. Have your classmate time how long it takes to complete the maze. Record this time in the control section of chart.
Lab #2 Computer Lab. Jason Brown Kevin Keating 04/23/2013. Lab #2- Computer Lab Jason Brown Kevin Keating Date: 04/23/2013 Tools: Philips Screwdriver Parts: Used Computer Tower Procedure:
Lab 9—Last Lab. Statistical Analyses & Threats to Validity. Background. Recall from last lab that there are two major types of designs. If you are interested in the association between continuous variables, you should use a correlational design.
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Lab Accuracy/Precision Lab. Pre-Lab Contrast Accuracy & Precision Give another example of accuracy and another example of precision Contrast Random Errors & Systematic Errors Copy the Formula for % Error. Lab Accuracy/Precision. Lab
Lab. The reaction of copper (II) nitrate and Iron is a single replacement reaction. Fe + Cu(NO 3 ) 2 Fe(NO 3 ) 2 + Cu This equation is already balanced. In this lab we will be putting an iron nail into produce solid copper.
Lab. Neural Networks based control of nonlinear systems. Identification of dynamic systems with Artificial Neural Networks. Dynamic/ feedback network:. Eduard Petlenkov, Automaatikainstituut, 201 3. Identification with Artificial Neural Networks. is theinput of the system and the model.