BEE-spoke-data/govdocs1-by-extension huggingface dataset:
# Presentation: 671264

## CIMSS TC Intensity Satellite Consensus (SATCON)

- Derrick Herndon and Chris Velden

- Funding Supported by SPAWAR PEO
- C4I&Space/PMW 180 under PE 0603207N

## Motivation

- component of short term intensity forecasts

-  Number of objective TC intensity tools continues to grow

-  Assist Forecasters in assimilating objective TC intensity
- guidance from multiple sources

-  Current operational TC intensity is arrived at through ad-hoc merging of subjective Dvorak and objective techniques

-  Formalize this procedure using statistical performance of
- each method

## The Problem:  Isabel

**The Problem:  Isabel**

- Dvorak = 77 kts

- ADT = 77 kts

- CIMSS AMSU = 105 kts

- CIRA AMSU = 105 kts

- SSMI = ?? kts

## The Problem:  Isabel

**The Problem:  Isabel**

- Average = 91 Knots

- “Truth” = 90 Knots

## How It Works

- Each method has strengths and weaknesses
- Weight each member in a way that maximizes strengths while
- minimizing the weaknesses
- Training data from 2001-2004 used to develop
- weights (158 cases vs recon pressure)
- Test in real-time for 2005

- CIMSS AMSU

- CIRA AMSU

- ADT

- SATCON

## Slide 6

## More Skill     Less Skill     Parameter

**Scene Type**

**RMW**

**CLW**

## 2005 Stats (Pressure)

|  | CIMSS
AMSU | CIMSS
ADT | CIRA AMSU | SATCON
 |
| --- | --- | --- | --- | --- |
| BIAS | -2.5 | -2.7 | -3.6 | -3.7 |
| AVG ERROR | 7.1 | 10.4 | 7.3 | 6.8 |
| RMSE | 10.4 | 15.3 | 11.2 | 10.5 |
| N | 90 | 90 | 90 | 90 |

- Values in millibars.  Validation is aircraft recon pressure +/- 3 hours from estimate time

## 2005 Stats (Wind)

|  | CIMSS
AMSU | CIMSS
ADT | CIRA AMSU | SATCON
 |
| --- | --- | --- | --- | --- |
| BIAS | 0.6 | -0.2 | 7.0 | 2.3 |
| AVG ERROR | 10.8 | 10.3 | 11.1 | 9.2 |
| RMSE | 13.9 | 13.2 | 15.7 | 12.0 |
| N | 90 | 90 | 90 | 90 |

- Values in knots.  Validation is best track winds coincident with recon
- +/- 3 hours from estimate time

## Slide 10

## Slide 11

## Future Work

- Weights initially developed using pressure validation.  Re-derive weights for wind component using Best Track winds
- Full assessment of 2005 cases for each member
- Develop new weights using latest algorithms
- Add additional TC intensity methods       (SSMI / TRMM ?)
# Presentation: 703074

## 

**Confirm/PLANET Codes**

- CONFIRM

****

**MTAC Summary**

**Confirm Program Office**
**703-292-3920**

## MTAC Work Teams

**Pre-Shipment Team**
**Evaluates issues as they relate to Pre-Shipment Notifications and PLANET Code usage and establish targets and processes for promoting accurate Pre-Shipment Notifications.**** **
**Scan Performance Team**
**Evaluates issues relating to equipment and scan performance (“Start-the-Clock” scans and MPE scans).  Addresses data accuracy issues such as invalid operation codes, invalid dates, and invalid facility IDs.**

## MTAC Work Teams

**Reports Team**
**Recommends and evaluates enhancements to Shared Reports. Substantial improvements to Shared Reports for Confirm data on the way.**
**Training Team**
**Recommends and collaborates on Confirm training goals for USPS and Mailers. New training curriculum in development for FY 2004.**
**Futures Team**
**Explores new uses for Confirm and PLANET Code and devises implementation strategies.**

## Pre-Shipment Team

**Respond to need for Pre-Shipment Notification Quality Metrics **
**Two Options:**
**Consolidator ships.  Either mailer or the consolidator communicates the shipment information to CONFIRM. **
**Consolidator creates the CONFIRM data (EMD or Mail.dat) to pass to CONFIRM. **

## Scan Performance Team

**Develop Standard Scan Performance Metrics**
**Scan Rate Performance Qualifiers**
**Accurate PLANET & POSTNET Codes**
**Valid Destination ZIPs**
**Automated Zones **
**Scan Performance Definitions**
**Destination Confirm vs. Origin Confirm**
**Scan Expectation Guidelines by Class, Shape and Presort**
**Scan Data Quality Items & Metrics**
**Facility ID**
**Operation Code**
**Scan Date/Time**
**Complete PLANET & POSTNET Code**

## Reports Team 

**Enhanced Shared Reports**
**Phase I deployment in Fall 2003**
**Enhanced business rules and analytical features**
**Longer retention & Trend Analysis**

## Training Team

**Enhanced Confirm Web Site **
**Enhanced Customer Guide**
**Standardization of Procedures**
**Confirm Certification Process **
**Major Areas of Focus**
**Pre-Shipment Quality**
**Mailpiece Preparation & Induction**
**Raw Data and Shared Reports interpretation**
**On-line Certification/Training Module**

## Futures Team

**Future innovations discussed include**
**Mail Bar Code Readability**
**4 State Barcode**
**“****License Plate” Architecture**
**Database Architecture**
**Collaboration with IMAQ’s One Code Vision**
# Presentation: 423427

## AHRQ Inpatient Quality IndicatorsNew York StateHospital Quality Report Card (Copyright)

**Bruce Boissonnault**
**President**
**Niagara Health Quality Coalition****Buffalo, NY**

- Boissonnault

- 1

## New York State Hospital Report Card (sm)

- Boissonnault

- 2

- Cartoon of man being carried away on stretcher while ready hospital report card

## About The New York State Hospital Report Card(SM)

- Alliance for Quality Health Care (AQHC) Members
- Analysis Performed By Niagara Health Quality Coalition (NHQC)
- Goals
- Help patients find high quality care
- Improve public policy decision-making
- Focus on more than cost
- Avoid confusion created by multiple public reports
- Complement hospital’s internal measures

- Boissonnault

- 3

## AHRQ Tools Used

- Inpatient Quality Indicators (IQIs)
- Prevention Quality Indicators (PQIs)
- Patient Safety Indicators (PSIs)

- Boissonnault

- 4

## Additional Benefits Of Publicly Reporting Health Quality Data

- Hospital to hospital comparisons
- Hibbard et al. study conclusions
- Hospitals should serve communities
- Hospital board member empowerment
- Hospital CEO compensation

- Boissonnault

- 5

## Improved Service Delivery Examples

- Gallbladder
- Stroke Center Radiology Gap

- Boissonnault

- 6

## Consumers Are Using The Information

- _[www.myHealthFinder.com](http://www.myhealthfinder.com/)_
- 15,000 _**people**_ an hour/3 million hits a day
- “One of the Internet’s top 10 healthcare   	information sites”       *Medica*
* *Major News Media Coverage
- Consumer Reports Magazine
- NY Times, Wall Street Journal, NPR

- Boissonnault

- 7

## Challenges And Barriers

- Chicken/Egg:
- We Don’t Value What We’ve Never Had
- Administrative Data Will Improve Only When Used
- Systems Expertise
- Cost = $150,000-$350,000 to publish
- Industry Special Interests Fear

- Boissonnault

- 8

## The New York Times

**The Buffalo News**

**Consumer Reports**

**The Post-Standard**

**Images of newspaper Clippings**

## To Learn More

- _[www.myHealthFinder.com](http://www.myhealthfinder.com/)_ (SM)
- Bruce A. Boissonnault, President
-    Phone: 716-852-7102

- Boissonnault

- 10
# Presentation: 139924

## Data Acquisition Graphs for DZero

- Michael Carter, GEM Summer Intern
- Supervisor: Stefan Gruenendahl
-    Tuesday, 7 August, 2007

## Introduction

- Purposes
- Performance monitoring of the trigger system.
- Provides big picture snapshot of overall performance.
- Storage of rate data for development of other tools.
- Diagnostic tool in case of problems.

## How it works

- Via the ITC (Inter Task Communication) software package the DAQ Monitor Server provides data to the DAQ Recording tool.
- Our DAQ Recording tool places firing rate (Hz) in the database.
- Our DAQ Graphs tool renders the rate data, from the database, as CERN ROOT graphs.
- 		(ROOT is a particle physics data & graphical analysis software package)
- Experts perform their analysis of the health and performance of the detector.

## D0 DAQ at Fermilab

- Collision rate of 7.6 MHz
- 3 level trigger system
- L1/L2 reduce rate to 1KHz into L3
- 250 MB/s average event data rate into L3
- 50 Hz and 12.5 MB/s output from L3

## Trigger/DAQ Monitor System with DAQ Recording & DAQ Graphs

**Trigger/DAQ**
**Monitor **
**Server**

**Data**
**Logger**

**Monitor**
**Display**

**L3**

**L1/**
**L2**
**TCC**

**Data**
**Distributor**

**EXAMINE**

- T. Yasuda	4/26/99
- Updated             5/18/01
- M. Carter	 8/7/07

**DAQ**
**Recording**

**DAQ **
**Graphs**

**DATABASE**

## Presenting DAQ Graphs

- Over Five Years in Waiting

## DAQ Graphs

## Reference Runs without Select

## Reference Runs with Select

## Reference Stores without Select

## Same Reference Stores with Time Scale

## Grand Total of Graphs = 1801 * 7 * 9 = 113,463

| Buttons:
----------------------------------------------------------
L1 Triggers       =  111 rows x 7 cols  =  777
And/Or Terms   =  256 rows x 2 cols  =  512
GeoSectors       =  128 rows x 4 cols  =  512
=================================
Subtotal = 1801
--------------------------------
Graph Inputs:
---------------------
Run	= 1 		
Store	= 1
Week	= 1
Hour	= 1
Day	= 1
Month	= 1
Year	= 1
============
Subtotal = 7 | Graphs Types:
---------------------------
Luminosity         = 1
Time	          = 1
Linear                 = 1
Log                     = 1
Poly Lines          = 1
Data Points        = 1
Select Only        = 1
Ref w Select       = 1
Ref w/o Select    = 1
================
Subtotal = 9 |
| --- | --- |

## Acknowledgements

- Stefan Grünendahl, Supervisor
- Marco Verzocchi, Major Suggestions
- Remigius Mommsen, Major Suggestions
- Geoff Savage, Technical Advisor
- Taka Yasuda, Technical Advisor
- Marc Buehler, Minor Suggestions
- Cynthia Knox, Minor Suggestions
- Dr. Davenport, Direction & Inspiration
- Dianne Engram, Director
- Elliot McCrory, Director

## Questions?
# Presentation: 206506

## Panel Session: System Instrumentation, Probing, Performance Problem Analysis

- Jennifer Schopf
- Argonne National Lab
- December 11, 2002

## Performance Problem Analysis

- How do we know there’s a problem?
- Peak (theoretical) performance no indication
- Transferring a 1 gig file between Argonne and LBL
- GridFTP with multiple streams and a decent network, fast disk
- Took 90 seconds (and then later 17 mins) – is this a problem?
- In this case no – different machine at same site, so this turned out to be right
- How to tell in general?

## Instrumentation in Globus

- We actually CAN answer this specific prob.
- GridFTP logging (run with –Z option) records min, max, average information for transfers between 2 sites
- We can also do logging of gram – but not predictions yet
- We CANNOT do this for the general case
- We have no estimates for how “off target” the performance need to be to be cause for worry
- 10%, not a big deal; twice as slow – maybe, 10 times as slow – problem!

## Simple versus complex

- Simple – is the performance about what I expect?
- Complex – the performance isn’t what I expect – why not?
- Absolutely everything needs to be instrumented in order to do the latter

## Also in Globus

- Various efforts underway to extend MDS to allow for more service and testing data
- This will be a matter of course for GT3 (OGSA-based) where every service component will broadcast basic up/not-up data
- This isn’t enough – but it’s a starting point

## TOP TEN LIST

- What are the top 10 open issues in monitoring/trouble shooting that the HEP experiments need
- Keep in mind – many of the hard problems are socio-political, not technical

## Top 10 (in no real order)

- 1) Unique job id’s
- 2) Baseline performance numbers
- 3) Better software engineering and comm. of errors
- 4) Better ways to store, search and correlate log files
- 5) Uniform pieces – APIs, protocols, error naming
- 6) Way to get “all” information about a single job
- 7) Ability to identify the “scope” of an error
- 8) Ability to change “level” of monitoring- quality of logging
- 9) What are the top 10 things that need to be monitored on a system (eg – disk is full)
- 10) Instrumentation of all middleware pieces (and as far down the stack as you can go)
- And then: security issues, ability to replay, defining alarms better ...
# Presentation: 811249

## Reclassification of IIIA allergenic products part of preread materials for Allergenic Products Advisory Committee. 2005

## Classification panel

- Convened under 21 CFR 601.25: “For purposes of reviewing biological products that have been licensed prior to July 1, 1972 that they are safe and effective and not misbranded...”
- Data requested from manufacturers in 39 FR 1082 (4 January 1974) and 39 FR 21176 (12 June 1974)
- Panel met  from 24 May 1974 through 11 August 1979
- Panel report: submitted 13 March 1981; published in 50 FR 3082-3288 (23 January 1985)

## The Panel’s Task Classification panel 1974-1979 (601.25)

- >1,500 extracted substances reviewed
- Goals:
- Evaluate safety and efficacy in accordance with 601.25
- Review labeling
- Submit report on conclusions and recommendations

## Product Classification Categories Defined in 21 CFR 601.25

- Category I: safe; effective; and not misbranded
- Category II: unsafe; ineffective; or misbranded
- Category III: data insufficient for classification
- IIIA: thought to have favorable risk-benefit ratio; remain on the market pending completion of testing
- IIIB: thought to have unfavorable risk-benefit ratio; removal from the market pending completion of testing

## Reclassification panel

- Convened under 21 CFR 601.26:  IIIA products to be reclassified as I or II
- Panel met from 19 November 1982 to 4 June 1983
- Panel report submitted December 1983

## Panel Recommendations (diagnosis)Reclassification panel 1982-1983 (601.26)

- All Category IIIA products recommended for reclassification into Category I for diagnosis except:
- Certain pollens, molds, avian/mammalian, inhalants were recommended for reclassification as Category II
- Panel stated that species definition *required* for reclassification into Category I

## Panel Recommendations (therapy)Reclassification panel 1982-1983 (601.26)

- Pollen extracts, mammalian/avian extracts, many mold and insect extracts recommended for reclassification into Category I
- Species definition was *required* for reclassification into Category I
- Miscellaneous inhalant and all food extracts recommended for reclassification into Category II

## Task at hand: 2003-2006

- Review the 601.26 Reclassification Panel’s recommendations regarding Category IIIA products
- Review data published since 1972
- Determine FDA position on Reclassification Panel’s recommendations based upon additional data
# Presentation: 689548

## South Carolina Forestry Commission

- March 3, 2006
- Smoke Simulation Analysis
- Gary L. Achtemeier
- USDA Forest Service
- Athens, GA

## Task Description

- The following set of slides summarize a PB-Piedmont post-burn analysis of smoke movement in the aftermath of a 205 acre prescribed burn conducted by the South Carolina Forestry Commission. The burn was conducted on 3 March 2006. The model simulations run from 1600 EST 3 March through 0800 EST 4 March. The site was located on the piedmont of western South Carolina.

## Weather

- Weather during the burn and the post-burn smoke movement period was clear. A high pressure system over the Mississippi valley northwest of the Carolinas combined with a strong low pressure system southeast of the Carolinas to produce moderate northerly winds over the burn site. This pattern weakened as the high pressure ridged over the Southeast. The geostrophic wind speed, a measure of the strength of the forcing by the large scale (synoptic) wind field declined steadily from 16.7 m/sec and 2.7 m/sec (missing data at 1800 and 1900). The strong forcing (>15.0 m/sec) would dominate drainage flows even in the piedmont. Weak synoptic forcing (< 3.0 m/sec) would allow for drainage flows.

## Modeling Information

- PB-Piedmont Version 5.0-2006
- Grid spacing = 60 m
- Domain size = 368x311 -> 22.1x18.7 km
- Visual domain = 10.0x10.0
- Weather data: Hourly METAR
- Elevation data: USGS 30 m DEM
- Elevation contour interval = 8 meters
- Elevation range is 101-201 meters

## The full 22.1x18.7 km model domain captures the drainages surrounding the burnsite (white square).

## The PB-Piedmont viewing domain and observation points for 3 March 2006. The white square encloses the 205 acre burn site. 

- The PB-Piedmont viewing domain and observation points for 3 March 2006. The white square encloses the 205 acre burn site.

## The plume at 1700 EST, 3 March 2006 blows from the northwest across observation Points 6 & 7. 

- The plume at 1700 EST, 3 March 2006 blows from the northwest across observation Points 6 & 7.

## The plume at midnight (0000 EST 4 March 2006). Synoptic forcing has declined sufficiently for drainage flows to divert the plume past observation 6.

## Smoke Location Evaluation:Interpreting the Observations Shown in the Next Slide

- Red symbol means smoke observed
- Green symbol means smoke not observed
- Circle means model matched observation
- Triangle means model unsuccessful

## PB-Piedmont analysis & observations 0600 EST, 4 March 2006.

- 2: No smoke (0620)

- 3: No smoke (0638)

- 4: No smoke (0655)

- 5: Missing

- 6: Light smoke (0724)

- 7: Smoke (0738)

- Click left mouse button to view observation points.

## Summary:

- PB-Piedmont correctly placed smoke or no smoke at 4 of the 5 observation sites.
- A drainage flow diverted smoke to flow on the far side of a valley away from a smoke observation.

## Smoke Matrix

- Smoke Prediction

- Yes                 No

- Smoke Observation

-   No                Yes

- 1

- 3

- 0

- 1
# Presentation: 372774

## Grid Editing Tools and Methodologies at WFO BTV

- Kevin Cadima
- WFO BTV

## MatchMOSAll Tool

- MaxT/MinT/T/Td
- Adjusts model grid to match MOS at various points
- Uses Serp tool to make MOS adjustments
- New ‘model’ database generated (model adjusted for MOS)
- Acts like a SmartInit routine

**Notes:**
Serp tool makes changes at selected points and spreads changes over the rest of grid using distance and topography weight which is configurable in tool.

## MatchMOSAll

- MesoEta adjusted for MAV/MET
- Forecaster can make further adjustments as necessary using various editing tools
- Use Serp tool to input MaxT/MinT for CCF sites so forecaster has control over verification

## MatchMOSAll

## HgrElev_TaperUpLwrElev_TaperDown

- Sky/PoP/QPF but can be used on any scalar field
- Very good at depicting terrain

## Sky_Fm_ModelRH

- Adapted from ETA_Sky tool
- Select model and cloud layer
- Sky based on model RH for selected layer

## Wx vs PoP

- Prefer PoP first then derive Wx from Smart Tool
- Gradients provide more info to user

## Elevation_Snow_Vly_Rain

- Assigns snow above user defined elevation with rain below
- Option for Rain/Snow mix in valleys
- Uncertainty vs Areal terms
- Rain vs showers, Snow vs snow showers

## Slide 10

## WsEta Model

- High Resolution QPF forecasts
# Presentation: 746275

## Happy Birthday, Helmut!

- Urs Achim Wiedemann
- SUNY Stony Brook and RIKEN BNL

## Slide 2

## J/Psi dissociation 

-  Hard process probes non-perturbative information about medium. How?

-  Wilson loop is _static time-like_ and in
-   fundamental representation:

-  Wilson loop is _calculable in lattice QCD_

- Bielefeld Group, hep-lat/0509001

- time

- distance

- L

- Ltime

## J/Psi dissociation at finite pt 

-  Wilson loop is _dynamical time-like_ and in fundamental representation.

- Transverse
- distance

- L

- time

- Propagation direction z

- Small
- pt

- Large
- pt

-  In ultra-relativistic limit, Wilson loop is _light-like._

-  Wilson-loop not directly calculable in lattice QCD.

## J/Psi - quenching at ‘high’ pt 

## High pT ‘jet’ quenching

- High pT ‘jet’ quenching

**Notes:**
How is this formalism compared to data ? For the leading hadron spectra, one calculated the energy degradation of the parent parton and then convolutes with the parton fragmentation function. So, in this picture, the hadronization process does not interfer with the medium-modification. The reduced energy of the leading hadron directly tests the reduced energy of the leading parton.

## The medium-modified Final State Parton Shower

## The medium-modified Final State Parton Shower

## Energy Loss in a Strongly Expanding Medium

- Salgado, Wiedemann PRL 89, 092303 (2002)

-  In A-A collisions, the density of scattering centers is time-dependent:

-  _Dynamical Scaling Law:_
-   same spectrum obtained for
-   equivalent static transport coefficient:

-  Calculations for a static medium
-    apply to expanding systems

- Rescaled spectrum

**Notes:**
In a nucleus-nucleus collision, the medium expands strongly and the density decreases in time. For example, for a 1-dimensional Bjorken expansion, this expansion parameter alpha equals one. If transverse expansion matters, alpha is larger than one. Now, remarkably, calculations of parton energy loss in such an expanding medium show a scaling law. The radiated gluon energy for different expansion scenarios can be mapped onto a single curve if rescaled in terms of this linear line-averaged transport coefficient. 

In practice, this means that you can analyzed effects of parton energy loss in heavy ion collisions as if the medium were static. At the end of the analysis, one simply translates the extracted static average transport coefficient into the corresponding dynamical one.

## The suppression of leading hadrons

## BDMPS coefficient of N=4 SYM from AdS/CFT

## Picturing the loop

- Finding surface
- amounts to extremizing Nambu-Goto action

- Induced metric on worldsheet

- Symmetries of loop C imply:

- Boundary:

- Symmetry:

## Calculating the surface

## The BDMPS coefficient

## What do we learn?

## Back-ups

## J/Psi-quenching

- Urs Achim Wiedemann
- SUNY Stony Brook and RIKEN BNL
# Presentation: 164728

## Slide 1

## Climate Change: 
An Aquatic Perspective and State Management Needs

- An Aquatic Perspective and State Management Needs

- Gary Whelan
- MI DNR Fisheries Division
- September 2008

## Talk Outline

- Aquatic considerations concerning climate change
- Likely effects
- Management information needs
- Management tools

**Notes:**
Very briefly, this is what I’d like to discuss with you.

## Key Aquatic Considerations

- Fish abilities to move are limited to watersheds
- Watersheds are heavily fragmented

**MI Dams**

**Notes:**
Very briefly, this is what I’d like to discuss with you.

## Key Aquatic Considerations

- Difficulty of sampling
- Can not see or measure many components
- Range of organisms from pathogens to megafauna
- “Easy” ability to raise or transfer
- Freshwater fish, crayfish and mussels are all already at risk

**Notes:**
Very briefly, this is what I’d like to discuss with you.

## Likely Effects

- Flow and temperature changes - Habitat specialists likely to decline
- Particularly temperature specialists, increase in generalist species
- Shifting of species northward and new species

**Notes:**
Very briefly, this is what I’d like to discuss with you.

##  Shifting of species to higher elevations

- Wetland

**Acidic Bedrock**

** ****Shifting of species to higher elevations**

## `

- Improved climate change prediction models
- Critical locations – How to focus limited resources
- Baseline information
- System Processes
- Hydrology - Flows and lake elevations
- Material recruitment
- Water quality
- Connectivity

- Information Needs

**Notes:**
Very briefly, this is what I’d like to discuss with you.

## Information Needs

- Baseline information
- Species distribution – current and predicted
- Native
- Naturalized
- Invasive
- Habitat needs and requirements
- How do we keep common fish common
- How do we keep the species in place as long as possible

**Notes:**
Very briefly, this is what I’d like to discuss with you.

## Potential Management Tools

- Fish passage
- Many life stages and species unknown
- How to prevent invasives but allow target species
- Fish and aquatic organism culture
- Methods unknown for many species

**Notes:**
Very briefly, this is what I’d like to discuss with you.

## Potential Management Tools

- Species transfers
- Appropriate locations
- Effects on other species
- New species community effects
- Pathogens
- Social effects
- Gene banks
- Technical issues
- Social issues

**Notes:**
Very briefly, this is what I’d like to discuss with you.

## www.michigan.gov/dnr

- Great Lakes, Great Times, Great Outdoors

- Questions? Comments?

**Notes:**
Do you have any questions or comments?
# Presentation: 148714

## HazCollect Overview

- WFO
- AWIPS

**Haz*****Collect***** Overview**

**HazCollect**

**DMIS**

**NWS**
**Telecom**
**Gateway****(TG)**

**NOAA**
**Weather Wire**
**Service**
**(NWWS)**

**Internet**

**WFO**
**AWIPS**

**AWIPS**

**NOAA**
**WEATHER RADIO**

**NWEM**
**(CEM)**
**Format**

**NWEM**
**(CEM)****Format**

**CAP**
**Format**

- Emergency
- Managers

**DMIS EM**
**Toolkit**

**Other EM**
**Systems**
- (DisasterHelp.gov,
- State EMAs, etc.)

**NWS**

**FEMA**

**NWS**
**WFOs**

- Backup Process (Voice Phone)

**EAS**

**EMWIN**

**other**

- Future

**All Hazards Emergency Messages**

- To Re-distributors & Public Consumers

- Emergency
- Managers

**Other EM**
**Interfaces**

## HazCollect Concept of Operations

- DHS/FEMA
-  DMIS*

- HazCollect
- Server

- NWS
- Dissemination
- Systems

- NWS WFO

**NWEM CAP Message**
**& User Information**

**Status & Security**
**Information**

**NWEM Message**

**NWEM Message &**
**Notification**

- Emergency
- Managers

**Authenticate & Authorize Emergency Manager; NWEM CAP** Message Created**

**Via AWIPS & TG**

**Via AWIPS**

- *Disaster Management Interoperability Service (eGov initiative)
- **CAP – Common Alerting Protocol
# Presentation: 768178

## Using Kepler To Enable Large-Scale Homology Searches

- Terence Critchlow
- Christopher Oehmen
***PNNL***

**Daniel Crawl**
- Ilkay Altintas
***SDSC***

## Overview of Biopilot Workflow

- ScalaBLAST

- HPC

- output.zip

- 2. Submit jobs

- 3. Package results

- Save provenance

- 1. Inputs

- Web Portal

## Inputs vs Database

- Sequence Database
- (e.g., human, rat,
- chimpanzee, etc.)

- Find matches

## Inputs vs Inputs

- Find matches

- Sequence n

## Running ScalaBLAST

- Create job submission scripts.
- Determine # of nodes, processors per node:
- # of sequences in input.
- Maximum # of nodes on cluster.
- Set file inputs and outputs.
- Submit jobs and wait until completion.
- Combine results from each node, zip, and move to output location.

## Provenance

- User name and job title
- ScalaBLAST inputs
- Input file name(s), number of FASTA entries
- DB name (if not doing permutation)
- Job information
- PBS id
- Start and end timestamps
- Exit code

## Kepler Actors for Biopilot

- Job submission and status
- Permutation of input files
- Count FASTA entries in input files
- Zip output files
- Store provenance in SQL database

## Kepler Features Used in Biopilot

- XML tokens to collect job parameters
- Higher-Order Component Actors
- Iterating sub-workflow over arrays
- If-then-else control logic

**Notes:**
This is a great slide. Needs lots of explanation without screenshots, so it could be improved by adding example screenshots of these structures/features being used.

## Future Directions

- Integrate with existing web portal
- Additional processing after running ScalaBLAST
- Match provenance to SPA schema

## ScalaBLAST

-    http://www.biopilot.org
-     Christopher Oehmen, Jarek Nieplocha, “ScalaBLAST: A Scalable Implementation of BLAST for High-Performance Data-Intensive Bioinformatics Analysis”, *IEEE Transactions on Parallel and Distributed Systems*, Vol. 17, No. 8, August 2006, pages 740-749.

## Questions?

- crawl@sdsc.edu

**Notes:**
Looks great. Add you email info on this slide for questions....
# Presentation: 759572

## 2001 IMEAC Fleet Management Conference

Driving Safety:
 It always starts with a Belt

Carl Wells- National Highway Traffic Safety Administration

- Driving Safety:
-  It always starts with a Belt
- Carl Wells- National Highway Traffic Safety Administration

## Buckle Up America

- National Campaign to increase seat belt use
- National Goals:  Increase national seat belt use to 85% by 2000 and 90% by 2005
- Reduce child occupant fatalities (0-4 years) by 15% in 2000 and by 25% in 2005 (from a total of 685 in 1995) 85% by 2002

## Four Point Plan

- Legislation
- Enforcement
- Public Education
- Partnerships

## Why Buckle Up?

- The most effective means of reducing fatalities and serious injuries (saving an estimated 9,500 lives in each year)
- Reduces the risk of fatal injury to front seat passengers by 45% (light trucks – 60%) and the risk of moderate-to-critical injury by 50% (light trucks 65%)

## Why Buckle Up?

- Motor vehicle crashes are the leading cause of work-related death (23%)
- On-the-job crashes cost employers almost $22,000 per crash and $110,000 per injury
- Traffic crashes on- and off-the-job cost business $55 billion in 1994

## Death Defying Act

- Driving a Ranger Pickup
- Going through an intersection
*	**	**	**	*

*SMASH!!!!*

## Death Defying Act

- Vehicle Overturns
**Driver Wore His Seatbelt**
**William F. Webster**
**Saved by the Belt!**

## Buckle Up AmericaWhere are we now?

- Nation wide only 72% of Americans Buckle Up

## Our Commercial Transportation Partners

## Buckle Up America Mudflaps

## American Freight Ways

- Child Safety Seats Work
- Safe Kids Buckle Up
- Are You Buckled Up???

## J.B. Hunt Truck Lines, Inc

## NHTSA BUA Signs

## Our GSA Partners

- Buckle Up America License Plate Holders
- Rearview Mirror Tags
- Recordings on call distribution systems
- Electronic Message Boards

## Fleets pay a BIG price

- Pay employee sick leave
- Provide insurance (higher premiums)
- Hire and train replacements
- Lost production
- On and off job injuries almost cost the same

## What can you do?

- BUCKLE UP and tell your friends to buckle up
- Employee Education Programs
- Honor Roll Program
- Company Policy
- Information on memos & pay checks

## New Directions in Occupant Protection

- Side air bags
- New Generation air bags
- Surveys
- LATCH

## Don’t Leave Out A Step!

- 	1. Infant Seats
- 			2.Child Safety Seats
- 				3. Booster Seats
- 					4. Adult Seat Belts

## CPS Training	

- Operation KIDDS
- NHTSA CPS Certification
- Certified Technicians
- Certified Instructors
- NHTSA’s most successful course

## What Can NHTSA Do?

- HOTLINE: 888-DASH-2-DOT
-  1-888-327-4236
- Report Vehicle Defects
- Child Passenger Safety Info.
- Traffic Safety Information

## What Can NHTSA Do?

- NHTSA Website
- _[www.nhtsa.dot.](http://www.nhtsa.dot.gov/)__[gov](http://www.nhtsa.dot.gov/)_
- Technical Assistance
- Safety Materials
- Crash Trends and Data

## Enforcement: Critical!!!

- Officers need your help
- Public outreach is needed
- Click it or Ticket

## Are You “Tired?”

- Inflation: a Key to Safe Driving
- “Where the Rubber Meets the Road”
- Handouts: Rubber Manufacturer’s Association
# Presentation: 489844

- <date/time>

**By **
**Ronald L. Brown Ph.D.**

***Grant Writing - Lessons Learned***

**Title**
**Abstract**
**Specific Aims**
**Background & Significance**
**Experimental Design & Methods**
**Budget**

**Cover Letter**
**Title**
**Key Words**
**Abstract**

***Reviewers   ******	***

**Study Section**

## Describe Project
Focused
Current Terminology

**Focused**
**Current Terminology**

**Title**

- Overall Goal - Purpose
- Importance
- Feasibility
**Strength of **_**your**_** background**
**Published studies (others)**
**Data presented herein**
- Experimental Approach
- Data Obtained
- Application to Phase II
- Importance

**Abstract**

**Overall Goal**
**Importance**
**List Specific Aims (Independent)**
**I.**
**II.**
**III.**
**Key:  Keep It Simple - Limited Time**
- 6 months
- 2 years

- ------------------------------------------------------------------------------

**Specific Aims**

**Overview - Stress Goal, Describe Problem, Importance, Strength of Proposal (Feasibility)**
**Literature - Topics, Questions**
- a)
- b)
- c)
**Feasibility/Data**
**Relation of Phase I to Phase II**

**Background & Significance**

**Rationale - Overall Goal, Approach, Importance**
**Specific Aim I**
- Experimental design
**Specific Aim II**
- Experimental design
**Anticipated Results and Pitfalls**
**Specific Methods**
- a)
- b)
- c)

**Experimental Design & Methods**

**Be Fair - Justify**
**Consultants**
**Contractual Arrangements**

**Budget**

**Cover Letter:**
- Select study section
- Justify - scientific expertise, state of the art
- Select funding agency
- Justify - scientific interest
**Title:**
- Use descriptive/current terminology
**Key Words:**
- Use current terminology
**Abstract:**
- Underline key words

**Study Section**

**Stay Focused - Single Idea**
**Simple Sentences - One Thought**
**Paragraph - ****	****General Sentence****	****	****	****Specifics****	****	****	****Summary Sentence**
**Headings - ****	****Every 1-2 Paragraphs****	****	****	****Questions/Answer Format**
**Use Consultants/Contractual Arrangements**
**Repeat (Abstract, Overview, Rationale)**
**Describe Importance**

**General**
# Presentation: 669862

## Organizational Chart

**Section of Health Services Research**
**Organizational Chart**

- Acting Director andChair, Executive Committee
**D. Kuykendall, PhD, MBA**

**H. El-Serag, MD, MPH**
- Associate Director and Chief,
- Clinical Epidemiology and Outcomes Division

**R. Street, PhD**
- Associate Director and Chief, Health Decision-Making and Communications Division

**M. Kunik, MD, MPH**
- Associate Director and Chief,
- Health Services Delivery and Organization Division

**L. Petersen, MD, MPH**
- Associate Director and Chief,
- Health Policy and Quality Division

**Robert Morgan, PhD**
- Chief,
- Design and Analysis (DAD) Division

**S. Underwood, BA**
-  Chief,
- Operations Division

- J. Davila, PhD

- A. Deswal, MD, MPH

- T. Giordano, MD, MPH

- J. Kramer, PhD, MPH

- Y. Shaib, MD, MPH

- D. White, PhD

- E. Chiao, MD, MPH

- N. Abraham, MD, MSCE

- J. Cully, PhD

- D. Latini, PhD

- M. Stanley, PhD

- P. Willson, PhD

- D. Graham, MD, MS

- M. Johnson, PhD

- M. Moffett, PhD

- L. Woodard, MD, MPH

- R. Morgan, PhD

- U. Braun, MD, MPH

- H. Gordon, MD

- P. Haidet, MD, MPH

- A. Kelly, PhD, MBA

- A. Naik, MD

- C. Teal, PhD

- A. Chau, BS / IT

- D. Espadas, MS / PS

- T. Foss, BS / HR

- R. O’Donovan /
- Pre Award Grants

- J. Taylor, BBA /
- Finance - VA

- A. Vinluan, BS, CPA /
- Finance - BCM

-  J. Campbell-Hasche, MS

- L. Henderson, PhD

- M. Kallen, PhD, MPH

- M. Khan, PhD

- N. Petersen, PhD

- K. Pietz, PhD

- P. Richardson, PhD

- Statistical Analysts

- Assistant Director of Education
**Jessica Davila, PhD**

- J. Mayben, MD, post-doctoral fellow

- L. Quijano, PhD
- post-doctoral fellow

- C. Kraus, PhD
- post-doctoral fellow

- J. Profit, MD, MPH

- H. Singh, MD

- V. Balasubramanyam, PhD, post-doctoral fellow

- S. Hysong, PhD
- post-doctoral fellow

- I. Wei, PhD
- post-doctoral fellow
# Presentation: 149085

##     Simplistic spatially explicit models of salmonid 

-     Simplistic spatially explicit models of salmonid
-      demographics and population genetic structure.
*Worth the effort?*
- Chris Jordan
- NMFS/NWFSC/CBD & CRI

## 	Outline

- 	Outline
- 	- Motivation
- 		*The usual*
- 	- Model
- 		*What?*
- 	- Results
- 		*Squint*
- 	- Conclusions

## 			Motivation

- 			Motivation
- 	- Recovery planning
- 	-At issue, risk factors to Salmon ESU’s
- 		- Intrinsic
- 		- Extrinsic
- 	- Goal (Ultimate)
- 		- Manipulate risk factors favorably for SESU’s
- 	- Goal (Proximate)
- 		- Understand the risk factors’ sensitivity to
- 		    intrinsic and extrinsic sources of risk

## 		Population Dynamical Model

- 		Population Dynamical Model
-  - To explore population dynamics of salmonids...
- 	- Demographics and Genetics
-   - Life cycle based metapopulation model
- 	- Dynamics from transition probabilites between life stages
- 	- Subpopulations within a larger population
- 	- Spatially explicit
-   - Environmental variability
- 	- Decadal productivity cycles
- 	- Stochasticity
-   - Track subpopulation density and distribution of genetic markers within subpops
- 	- Mean subpopulation density(t)
- 	- Mean allele frequency over 10 loci with 10 alleles
-   - Assess demographic and genetic structure
- 	- Extinction probability (local quasi)
- 	- Genetic Distance (Nei’s)

## Slide 5

## Slide 6

## Explore the consequences of straying (‘stray rate’) on 

- Explore the consequences of straying (‘stray rate’) on
- population factors (Extinction probability, Genetic
- isolation)

##         Stray Matrix for p = 0.95

-         Stray Matrix for p = 0.95

## Slide 9

## Slide 10

##     Extinction probabilities as a function of ‘Stray rate’

-     Extinction probabilities as a function of ‘Stray rate’

## Slide 12

## Slide 13

## Conclusions

- 	-Simple models can give interesting non-intuitive
- 	results quickly
- 	-Have value in guiding our thinking about management
- 	issues in listed ESU’s
# Presentation: 707395

## SPCC Guidance Summary

| Facility capacity (gallons) | Tank Type (UST4/AST5) | Reasonable expectation of discharge to  navigable waters or adjoining shorelines? (Y/N) | Facility Spill History - had spill1? | Requirements |
| --- | --- | --- | --- | --- |
| < 1,320 gallons | AST | Does not matter | Does not matter | NOAA BMP2 |
| >1,320 - 10,000 gallons | AST | No | Does not matter | NOAA BMP2 |
|  |  | Yes | No | Self Certified SPCC |
|  |  |  | Yes | PE Certified SPCC |
| > 10,000 gallons | AST | No | No | NOAA BMP2 |
|  |  | Yes | Does not matter | PE Certified SPCC |
| < 42,000 | UST3 | Does not matter | Does not matter | NOAA BMP2 |
| > 42,000 | UST3 | No | Does not matter | NOAA BMP2 |
|  |  | Yes | Does not matter | PE Certified SPCC |

- _Notes:_
- Spill within 3 years > a single 1,000* gal discharge or two discharges >42* gal within a one year period that reach nav. waters or adjoining shorelines – *amount discharged to navigable waters.
- NOAA BMP (Best Management Practices) – SECO need to develop.
- Do not include USTs that are already regulated by all the tech requirements  of  the UST regulations (e.g., 40 CFR 280 or a state program under 40 CFR 281).
- USTs-SPCC rule defines these generally as completely buried tanks
- AST- This includes partially buried tanks, bunkered tanks, & tanks in vaults/basements (not surrounded with fill material)
# Presentation: 407294

## Physics Archives &Tools                              Required to Investigate Our Theories

**Enstore Database of Standard Model predictions for high-P****T**** processes**
**Physics-level Events (ready for processing through detector simulations)**
**Different Generators (Madgraph, Alpgen, ...)**
**Different Levels of Generation (partons, showers, particles)**
**Documentation (assumptions, approximations, range of validity)**
**Templates (for large-scale processing of events)**
**Accessible by experiments & theorists**

## Motivation

**Generating *****accurate***** samples of Monte Carlo events can be time-consuming and complicated**
**Adding parton showering to these samples is theoretically challenging and subtle**
**A common repository is useful to:**
**Prevent mistakes**
**Prevent needless duplication of effort**
**Allow for a universal estimate of systematic errors**
**Facilitates combination of CDF and D0 data**
**Allow for a merging of complicated topologies**
**A better theoretical prediction**
**Enable new search strategies**

## (W+jets) (pb)

| ME-MC | W+0j | W+1j | W+2j | W+3j | W+4j | W+5j |
| --- | --- | --- | --- | --- | --- | --- |
| ALPGEN | 2046±1 | 522.6±0.6 | 146.1±0.3 | 41.5±0.2 | 11.55±0.07 | 3.13±0.02 |
| GRAPPA | 2042±4 | 525.4±0.6 | 146.8±0.3 | 40.2±0.3 |  |  |
| MadGraph | 2044±5 | 525.4±1.1 | 146.1±0.3 | 41.8±0.1 |  |  |
| MCFM(LO) | 2044±1 | 526.3±0.5 | 147.2±0.3 | 41.8±0.2 |  |  |

- BLESSED SAMP LES

##  Matrix Element-Parton Shower  Merging    (Catani, Krauss, Kuhn, Webber)  

** ****Generate**** samples of different jet multiplicities according to exact tree-level ME’s, with N****jet**** defined using a clustering algorithm **

-  **Reweight**** the matrix elements by vertex Sudakov form factor**
** ****Remove double counting**** by vetoing shower histories (i.e. *****y******ij****** *****sequences already generated by the matrix elements)**

## Is it New Physics or a fluctuation?

**Difficult to determine the probability for a rare event *****after the fact***
**How constraining are the exact kinematics?**
***Many***** ****signatures would be considered interesting**
**N leptons + M photons, N,M>1**
**How large is the probability for *****anything *****strange?**
**Patriot is a Lookup table for “rare” SM processes and kinematics**
**Are there cousin events?**
**E.g. WW******** ******** jj jj ******
**Look for correlations in various SM channels**

## Future

**Continue collection of data samples**
**Test methods for merging**
**Modifications to Herwig and Pythia**
**Move database to CD cluster and change format to mysql or postgres**
# Presentation: 179028

**Offline Event Processing Overview:**
**Philosophy, Goals, Questions**
**J. Urheim**
**Saturday, July 13 2002 **
**offline data processing parallel session**

## Philosophy

**Whatever we do will have to be redone**
- calibrations, reconstruction pkgs will improve
- feedback from initial pass will be useful for 2nd pass
**The sooner we get started processing data the better**
- scale learning curves regarding operational issues
- we shouldn’t wait for everything to be perfect
**But we still want this to be useful for data analysis / detector performance studies**
- treat 1st pass as a serious production:
-  **aim for “frozen” executables/constants**
** ****aim to carry out quality control monitoring **

##  Initial Goals of Processing

**Work out the technical aspects**
- FNAL batch farms, set up infrastructure (Alex)
- Offline software: performance, robustness
**Provide output that is useful for collaborators**
- Try to process all events, minimal filtering
- Set up to do nearly real-time processing for quick turnaround
- Output should be useful for further development of reconstruction:  should contain raw data + candidates
- Output should be useful for higher-level data analysis output ntuple(s)?

##  Questions & Issues

**What to run?**
- DigitListModule                    -  yes!
- DeMuxCosmicsModule        -  yes!
- TrackSR et al.                      -  yes!
- BubbleSpeak                        - yes!
- what else ?
**Which candidates do we write out ?**
**Do we write out an ntuple ?**
**Do we do any filtering ?**
- non-snarl records ?
- events with fewer than N planes with hits ?  N = ?
**Multiple output streams ?**
- Event classification: i.e., stopping muons, fully contained events, multiple muons, etc...
# Presentation: 028973

## HIPS Upgrades for METOP

- 40th Argos OPSCOM Meeting
- Virginia Beach, USA

## HIPS Upgrade Background

- NOAA operates 9 HRPT Image Processing Systems (HIPS) stations
- Money to upgrade all nine sites was left unused and eventually reduced until only  two sites could be upgraded
- Based on NOAA’s National Weather Service requirement Honolulu HI and Anchorage AK were chosen for  the upgrade
- Coordination with CLS at OPSCOM 39 indicated increase in latency for users without additional METOP ready stations.  Monterey CA and Miami Fl were recommended

## Monterey CA

- NESDIS Office of Satellite Development currently is managing the contract for the two NOAA upgrades at Honolulu and Anchorage.  The Contract has a two year window to add additional sites
- Leveraging off of NOAA’s investment in the first two sites Global Image agreed to upgrade Monterey CA for $54K. Monterey contained Global Image Hardware and software
- OSDPD was successful in reprogramming $54K from FY2006 budget to add Monterey CA to the contract in May 2006

## Miami FL

- In addition NOAA investigated the possibility of adding the Miami site to the open contract
- Two issue to overcome, first the hardware and software is not Global Image and will require $104K to upgrade and second $104K is not available in FY2006 budget and not planned for in FY2007 budget
- OSDPD Submitted a new request in April for $104K in FY2007 by reducing FY2008 requests.  New request rarely are added this late in our process
- FY2007 update in May, our request passed the first review by management, but was cut to $54K
- Further investigation is needed to see if the site upgrade can be accomplished with the reduced funds

## Planned testing

- The planned installation and test date for Anchorage, Honolulu, and Monterey sites:
- 6/27-28 Installation and SAT at Anchorage
- 7/11-12 Installation and SAT at Honolulu
- 7/24-25 Installation and SAT at Monterey
# Presentation: 099867

## Stratospheric Column Ozone From OMI and MLS

- Comparisons:  Stratospheric column ozone (SCO) from OMI L2 Cloud Slicing and MLS integrated L2 ozone profiles
- Include only daytime ascending orbit ozone profiles from MLS for co-location (MLS ~7 min before OMI)
- Pacific averaged SCO (120W to 120E)
- Monthly averages
- For these comparisons of SCO, take MLS v1.5 ozone profiles only down to stated limit  of 215 hPa (316 hPa may be the stated limit in future MLS)

- 21 September, 2005

- _Stratospheric Column Ozone Derived from Cloud Slicing_

- TOMS Above-Cloud Column
- Ozone (Refl > 0.9)

- SAGE II Strat Column Ozone

## Stratospheric Column Ozone: Tropics

- (Ziemke, Chandra, and Bhartia, JGR, 2005)

## Stratospheric Column Ozone: Extra-Tropics

## MLS Ascending and Descending Orbit Measurements

## Winter/Summer Contrast in NCEP Tropopause Pressure

## MLS and OMI Cloud Slicing Stratospheric Column Ozone Comparisons Over the Pacific

## MLS Minus OMI Stratospheric Column Ozone (September 2004 – August 2005)

## Summary

- Stratospheric column ozone (SCO) from MLS and OMI Cloud Slicing for the first year show little measurement offsets (around 5 DU with MLS larger)
- This may change as a function of time as was the case between N7/EP TOMS and UARS MLS SCO (up to 15-20 DU after several years)
- OMI Cloud Slicing SCO will be utilized over time to provide relative adjustment of MLS SCO for obtaining inter-calibrated measurements of tropospheric ozone from the two instruments

- Tropopause
- Pressure < 215 hPa
# Presentation: 163349

## Preparations for ProducionData Processing - Calibration Status

- J Musser
- July, 2002

## Summary

- Components in Place
- Calibration Stability
- Calibration Constant Makers
- Calibration Chain Components Not Now in Place

## Calibration Components

- Offline Framework 
- Timing Calibration 
- T0
- Timewalk
- Charge Calibration
- Drift Point
- Non-Linearity
- Inter-Strip Calibration/Response Flattening 
- Inter-Detector (Stopping muons)
- CalDet Energy Calibration

## T0  Stability

- ~ 1 week of data adequate for T0 calibration
- Calibrations stable at better than 1 ns level over months
- Timewalk stable over much longer time scale.

## Inter-Strip Cal Stability

- Calibration stable at 1% level over months.
- Some evidence for short term variations @ ~ 2% level.
-      (Drift Point)
- Appropriate  recalibration periodicity is monthly

## Calibration Makers

- Timing, Pulse Height calibrations currently carried using ROOT scripts running from CandTrackSR ntuples.
- Output is a text file, which is loaded into the dB as a separate step.
- Check plots generated (cal constant deltas, etc)
- Running these ‘by hand’ monthly would take of order  1 man-day per month.
- In short term, running in this mode is probably OK, but need to move to a more ‘automated’ system, with mechanism in place for validating quality.

## Missing Components

- 1:  Drift Point Cal/Non-linearity
- Drift Point working at CalDet,  transfer of software operations to far detector should be trivial.
- Hardware not yet in place.
- Linearity calibration not currently understood at the level necessary to impliment.

## Missing Components

- Inter-Detector Calibration
- Stopping Muons.  Doing this at percent level requires ~ months of data.
- Many subtle issues - lots of work to do to do this right!
- Energy calibration from CalDet analyses should be available, but again there are many issues (reconstruction efficiencies, etc) that must be looked at carefully.