Thursday, June 13, 2019

finding your inner model

Finding your inner model, UAB,


Daniel Szymanski, Joe Turner, epidermal morphogenesis with integrated experimental verification
Finite element method modeling of cell wall for plant morphology.
Start with simple model, and add complexity as needed.
Empirical rule for model training (fitting), 3-5% error?



UTC EMCS Shipping address



UTC CECS
EMCS 319
735 VINE ST
CHATTANOOGA, TN 37403


College of Engineering & Computer Science
University of Tennessee at Chattanooga
EMCS 319
735 VINE ST
CHATTANOOGA, TN 37403

Thursday, May 23, 2019

REU temporary employee positions for UTC students, vendor form for non-UTC students



·         PREFERRED STEP, but not required – a month before arrival get all employee full names (as listed on Social Security Card and/or passport), Social Security Number, and Date of Birth.  Communicate with Jina Johnson in UTC H.R./Payroll to get each of your participants classified as a pending-employee
1.       Work with Andrea Evans to get temporary positions created (before completing this step, verify with Jina Johnson in H.R./Payroll that this is still the correct process for paying REU students)
2.       Provide participants with I-9 (and instructions), W-4, Background Check Form, and Personal Data Form.  Also, remind each of them to bring bank documentation in order to complete Direct Deposit blue form.
3.       Upon arrival, have participants turn in all documentation, watch and verify signatures on said documents, and make photocopies of official identifying documentation for I-9.
4.       Complete Initial Hire paperwork for each employee.
5.       Once all paperwork has been verified, walk materials to Human Resources Department (DO NOT MAIL).
6.       Complete time sheets for each of the pay periods that your visitor will be receiving pay.  Have the visitor sign completed timesheet.
7.       Have time sheet approved by PI
8.       VERIFY that visitors have been hired.
9.       Each week while submitting own timesheet, enter timesheet for each employee.



Hello,

It was a pleasure working with both of you for your NSF REU Program. I just wanted to give a couple of little reminders on what still needs to be done and who to contact for the ARC. Lyndsay Hyden will be your point of contact on getting the students set up to use their MOCS card for ARC entry; Lyndsay-Hyden@utc.edu. As for the HR paperwork Eva, the students should have sent you the corresponding documents:

New Hires:
Initial Hire/Rehire Form
Personal Data Form
Direct Deposit emails (not all of them will have sent you this because most of them brought in physical documents ie: passport, license, ss card etc).
They will turn in to you tomorrow; I-9, W-4 and Direct Deposit form.

Existing Hires:
Personnel Change Form

You will have to open up the forms that the students should have sent you and fill out the remaining information that is needed. Please note that those forms and anything else will need to be printed out and turned into HR. They cannot be sent via email as it needs an original signature. (Speak with Jina about what specifically needs to be filled out on these forms).

The students will need timesheets which you can find on the Human Resources page where all of those forms listed above are. Don’t forget to set them up in IRIS as well as the mentors so they can be approved and paid on time. I would double check with Jina just to make sure you have everything you need.

Let me know if you need anything else.

Thanks!


==============FOR non-utc student, vendor form is needed ===========


I just found out that we cannot set up the partcipants for the REU as payroll but they have to be set up as a vendor. Please see the email below from Virginia regarding this process. This email is in regards to Electrical’s REU attendees but can also be used for your attendees with Dr. Qin. Please let me know if you have any questions.




I am writing you to follow up on Jina’s email below about the REU students on Dr. L’ NSF grant (Rxxx-participant account).  When you complete the Worker’s Classification form for these non-UTC student participants, please do the following:

1.       Section I A-E, mark No
2.       Section II in the Description of Services to be performed put “Research Experience participant for NSF REU grant”.
3.       Section IV  check the bottom one: Non-UT student support costs in a research experience program and attach a support statement that explains that the participant is in a part of a NSF REU (Research Experience for Undergraduate) program and the stipend to be received is not for work per the NSF guidelines. 

You will also have to complete the other required vendor paperwork, Vendor Payment Selection Form, Business Classification Form, and W-9.  Andrea Evans can help you get the vendors setup.   

After the vendor has been setup, then you will need to complete the T-27 form for each payment that needs to be submitted for the participant.  Submit the form to Andrea Evans who will submit them in IRIS.  Dr. L will need to decide how often he wants to pay the students, but I would suggest about every two weeks.  If they sign up to be paid by ACH on the Vendor Payment Selection form then it is automatically setup as Net 30 or if by check then Net 40 from the document date.  The document date is the date at the top right of the T-27 form.  The document date must be at least the first day service or after.  The budget allows for $500 a week for each student for the stipend.  

Also, each of these participants can get up to $450 total in travel expense reimbursement off the grant account (Rxxx) for coming to and leaving UTC.  Therefore, each one of them will need to be setup as Guest Travelers in IRIS.  You may have to limit what you pay them for so that the cost doesn’t go over $450.  There is only $4500 total in the budget for all students for their travel to and from UTC.  There is another $900 in the budget that may be used throughout the rest of the year for select students to attend a conference.  

If any of the participants are UTC students, then you will have to enter their stipend as an award through the Scholarship/Financial Aid office and the amount they receive will be counted as income for the financial aid eligibility.  The non-UTC students will need to report the amount they received from UTC to their home university Financial Aid office as income. 




Hello M.  VM has found out more info regarding the REU Summer Program.  It has been discovered that since these employees are not students here at our University, they will need to be set up as vendors and paid on a T-27.  Please do not enter any time on the employees that has already been set up.  I will have Pam Quick to remove them from the system. Once these employees are removed you will then be able to go through the procedures of setting them up as vendors, make sure you do the worker classification questionnaire, it has been updated and it does address summer programs such as the one you are working on.  I will let you know when these employees have been removed from payroll so that you can proceed with the vendor set ups.  Thanks. 






Wednesday, May 15, 2019

hsp70 isoforms in yeast, different functions

 2019 Apr 24. doi: 10.1007/s00294-019-00978-8. [Epub ahead of print]

Not quite the SSAme: unique roles for the yeast cytosolic Hsp70s.

Abstract

The Heat Shock Protein 70s (Hsp70s) are an essential family of proteins involved in folding of new proteins and triaging of damaged proteins for proteasomal-mediated degradation. They are highly conserved in all organisms, with each organism possessing multiple highly similar Hsp70 variants (isoforms). These isoforms have been previously thought to be identical in function differing only in their spatio-temporal expression pattern. The model organism Saccharomyces cerevisiae (baker's yeast) expresses four Hsp70 isoforms Ssa1, 2, 3 and 4. Here, we review recent findings that suggest that despite their similarity, Ssa isoforms may have unique cellular functions.

KEYWORDS:

Chaperone; Evolution; Hsp70; Isoform; Ssa
PMID:
 
31020385
 
DOI:
 
10.1007/s00294-019-00978-8

Monday, May 13, 2019

REU network ID and swipe card request


To get IDs created for external users, we usually just create Affiliate accounts for them (https://blog.utc.edu/it-knowledge-base/sponsor-affiliate-accounts/).  If you fill out that form for each user, we will create the accounts that will grant them network access.  It is important to get information such as their birthdays and phone numbers, so that we may verify them properly if they call us with password issues.  As filling out the form will create new tickets, I am going to close this one for now.
 
The sites asks BD. 



            I completed 5 rather simple steps to get this completed for our REU.  I’ve outlined my steps below for your convenience.

Step 1: 
#1 click Affiliate Request Form


Step 2: Email the students with the following rules:
Photo Submission Criteria
Your photo must meet the criteria outlined to be accepted. All photos are subject to approval.
  1. Take a new photo.
  2. Use good lighting. Photos that are dark, overexposed, or show glare on glasses will not be accepted.
  3. Face forward and look at the camera.
  4. The photo should be a centered and front-facing headshot that doesn't need to go below the shoulders.
DO:
  • Use a color photo in jpg format
  • Make sure your eyes are open and visible
  • Crop the image to just above the top of the head to the collarbone
DON'T:
  • Use pictures with social media filters
  • Wear sunglasses or other item that will obscure your face
  • Use pictures that are blurry or have a glare
  • Use scenic backgrounds
  • Use overexposed or underexposed photos
  • Group photos
  • Inappropriate expressions
  • Use Senior portraits or Graduation photos
  • Use professional pictures
Step 3:
            Once the UTC IDs have been created and you have all of the photos, save the photos onto a jump drive named as such:  Last_First_UTCID

Step 4:
            Make an appointment to meet with Kathleen Metcalf in the MocsCard office to print the cards (I waited and took them immediately).

Step 5:
            Take the cards to Housing for activation and delivery upon check-in.


macbook pro black screen problem

macbook pro, 15 inches, screen is black after failed wakeup from sleep.

https://macpaw.com/how-to/fix-mac-black-screen

it works when connects to an VGA monitor.

Run disk unility, fixed volume issue, restart, still black screen.

===============Tried this, still black screen===========

Reset your Mac’s NVRAM settings

NVRAM stands for non-volatile RAM and is basically a functionality that stores in memory settings for display, speakers, primary startup disk etc. Everything even remotely connected with boot process (like your MacBook won’t turning on) can be set back to factory settings during the NVRAM reset.
To flush NVRAM settings:
  1. Shut your Mac down.
  2. Press the Power key.
  3. Wait for your Mac to start loading.
  4. When you hear a startup sound, hold down Cmd + Option + P + R.
  5. Keep pressing the keys until you hear a second startup sound
==================================

Zap your Mac’s SMC settings

SMC is System Management Controller. What it controls is temperature, lights, keyboard, fans, and many other side-processes. According to Mac support forums, resetting SMC helps in 90% of the cases when your Mac’s screen goes black. To perform this trick follow the tips below.
For a MacBook with a non-removable battery:
  1. Shut your Mac down. 
  2. Connect your Mac to a power outlet. 
  3. While your Mac is still shut, Press Shift + Option + Control and Power key at the same time. 
  4. Let go of the keys and boot your Mac again.
Reset SMC to fix MacBook black screen

==================================

Update OS X system

https://support.apple.com/kb/DL1969?locale=en_US

upgrade from 10.12.6 Sierra to 10.13 High Sierra

Downloaded high Sierra dmg file. Installed. Restarted not responding after 3-5 minutes.

14:47, hard-shutdown, and restart again. Fan can be heard running.







Saturday, May 11, 2019

mask RCNN



Object Detection Custom Training of Image Mask RCNN Deep Learning | AI SANGAM
In this video we will learn "How to Train Custom dataset with Mask RCNN" Step 1: Collect data and divide them for train and validation. You can get sample from my prepared dataset. https://drive.google.com/open?id=1WSw... Step 2: We need to make labeling for all images. For this you can use online labeling tool http://www.robots.ox.ac.uk/~vgg/softw... After downloading annotated file and json data we will start training Step 3:You will get file here.https://github.com/AISangam/Mask-RCNN... Now run this command python bottle.py train --dataset=/home/datascience/Workspace/MaskRCNN/Mask_RCNN-master/samples/bottle/dataset --weights=coco As a thesis project you can get it easily from us. Website: http://www.aisangam.com/http://www.aisangam.com/blog/http://finalbtechproject.com/x

Wednesday, April 17, 2019

UTC travel reimbursment


Before travel, fill a T18 form

http://finance.tennessee.edu/wp-content/uploads/forms/T-18.pdf


After the travel

  1. Complete  and sign a T3 form  http://finance.tennessee.edu/wp-content/uploads/forms/T-3.doc
  2. Receipts of hotel, parking
  3. Meeting program,
  4. Your presentations
  5. A cover letter to explain the reasons for your travel, your activities, explain your actual travel arrangement.
  6. If mileage, print out round trip between home and meeting location


Tuesday, April 9, 2019

duplicate genes identification:


https://media.nature.com/original/nature-assets/ng/journal/v36/n6/extref/ng1355-S2.pdf

Identification of duplicate genes and singletons After database cleaning, we conducted an all-against-all FASTA3 self-search for the entire proteome of Drosophila melanogaster (http://www.ensembl.org/Drosophila_melanogaster/) and that of Saccharomyces cerevisiae (http://genome-www.stanford.edu/Saccharomyces/). A single copy gene (i.e., a singleton) was defined as a protein that did not hit any other proteins in the FASTA search with E = 0.1; this loose similarity search criterion was used to make sure that a singleton is indeed a singleton. Two genes were regarded as duplicate genes if they meet the following three criteria during FASTA all-against-all search (modified after Ref 4): (1) E = 10-10; (2) their similarity is ≥ I (I= 30% if L ≥ 150 a.a. and I = 0.01n + 4.8L -0.32(1 + exp(-L/1000)) if L <150 a.a., where n = 6 and L is the length of the alignable region); and (3) the length of the alignable region between the two sequences is >50% of the longer protein. Since we wanted to detect the differences in expression change between real duplicate genes and singletons, we

Tuesday, March 26, 2019

ipad zoom meeting sharing bug fixed


Zoom cannot share screen on ipad.

Removed and reinstalled Zoom, fixed this problem.

Monday, March 18, 2019

porcupoine problem



https://en.wikipedia.org/wiki/List_of_paradoxes

power of good stories


Friday, March 15, 2019

bibtex, pdflatex


applejack:bmc_netwk_aging_manuscript hqin$ bibtex bmc_networkaging
This is BibTeX, Version 0.99d (TeX Live 2016)
The top-level auxiliary file: bmc_networkaging.aux
The style file: bmc-mathphys.bst
Database file #1: qin_networkaging.bib


pdflatex bmc_networkaging

pdflatex bmc_networkaging


Bibtex from PubMed, TexMed


https://www.bioinformatics.org/texmed/


Friday, March 1, 2019

**** cpsc4999 plan

Key topics
Linux
RNAseq
R/Rstudio Rmd

Online:
Regular expression online exercise

RNAseq
biological network


Potential student projects: 
time lapsed image analysis
rDNA reads in yeast genomes ~ lifespan
chemical compounds
network controllability
yeast RLS ~ genomics features
prediction of essential and non-essential genes.
ecology network analysis
aging data comparison
RNN reverse engineering of gene interactions


Reference:
data visualization book
https://serialmentor.com/dataviz/

http://hongqinlab.blogspot.com/2015/06/ngs-tutorials.html
http://www-personal.une.edu.au/~cgondro2/Rcourse.htm
Jackson lab workshop
Data Carpentry,
https://github.com/data-lessons/genomics-workshop
https://data-lessons.github.io/genomics-workshop/ 

EdX genomics course

how to read a scientific paper


https://violentmetaphors.com/2013/08/25/how-to-read-and-understand-a-scientific-paper-2/?fbclid=IwAR0p8P5EAi8Mir_rDyH-TLY6uUsn9ZVa2YvLMgjoEj3H6lxQdYqUvAKTnHU


Spearman footrule distance

Spearman footrule distance, a meaningful way to combine value and ranks

https://people.revoledu.com/kardi/tutorial/Similarity/FootruleDistance.html




Wednesday, February 27, 2019

Engineering college facts


freshmen/transfer, enrollmet at 269 in fall 2018, transfer enrollment fluctuate,

graudate student. flat for cs phd

undergraudate graduation, increasing,

as high as 40%
DFW rates by courses: CHEM1110, 1120, 3010, 3020, 3710
Physic 2310
Math 1710, 1720, 1730, 1830, 1920, 1950, 1960, 2100, 2450, 2550
math camp in summer was proposed

nonwhite 26% at college of engineering

femal 16% below national average 18%?

20% of UTC funding from Engineering,

$4.5M in FY2018, 0.7M of CS

MS engin manag 7th in nation

student credit hours 23K in 2018, 21,222 in 2017

Cleveland stat, cha s U, Dalon, Covrnent, Roane state, Motlow S U

7 new faculty hires

5100 sq ft resaerch space, lab and work space, construction starts in summer 2018

relieft from diff tution obligation?

April 18, tech sympo

Tuesday, February 26, 2019

iCompBIO REU sites




online applicationform 


www.utc/icompbio

Sunday, February 24, 2019

python deep learning notes




========
stochastic gradient descent is so called because only batch of data are used each time.
========gradient descent
# Set the learning rate: learning_rate
learning_rate = 0.01

# Calculate the predictions: preds
preds = (weights * input_data).sum()

# Calculate the error: error
error = preds - target

# Calculate the slope: slope
slope = 2 * input_data * error

# Update the weights: weights_updated
weights_updated = weights - learning_rate * slope

# Get updated predictions: preds_updated
preds_updated = (weights_updated * input_data).sum()

# Calculate updated error: error_updated
error_updated = preds_updated - target

# Print the original error
print(error)

# Print the updated error
print(error_updated)

========

# Import necessary modules
import keras
from keras.layers import Dense
from keras.models import Sequential

# Specify the model
n_cols = predictors.shape[1]
model = Sequential()
model.add(Dense(50, activation='relu', input_shape = (n_cols,)))
model.add(Dense(32, activation='relu'))
model.add(Dense(1))


# Compile the model
model.compile(optimizer='adam', loss='mean_squared_error')

# Verify that model contains information from compiling
print("Loss function: " + model.loss)

# Fit the model
model.fit(predictors, target)


========================
# Import necessary modules
import keras
from keras.layers import Dense
from keras.models import Sequential
from keras.utils import to_categorical

# Convert the target to categorical: target
target = to_categorical(df.survived)

# Set up the model
model = Sequential()

# Add the first layer
model.add(Dense(32, activation='relu', input_shape=(n_cols,)))

# Add the output layer
model.add(Dense(2, activation='softmax'))

# Compile the model
model.compile(optimizer='sgd',
              loss='categorical_crossentropy',
              metrics=['accuracy'])

# Fit the model
model.fit(predictors, target)

====
dead neuron versus vanishing gradient

====

Thursday, February 21, 2019

FreightTech Innovation Challenge: A 24-Hour Transportation and Logistics Use Case Competition,


I’m excited to announce the inaugural FreightTech Innovation Challenge: A 24-Hour Transportation and Logistics Use Case Competition, taking place March 29–30, 2019 in Chattanooga, TN. Presented in collaboration with FreightWaves and CO.LAB, this event is a 24-hour competition for college students from across the nation to team up and take on some of the greatest challenges in transportation and logistics.

From now until March 8, we invite students who are interested in business, supply chain, technology, computer science, data, and logistics (and more) to apply for this immersive experience that could ultimately impact their career paths. Participating students will work directly with major industry players and experts to find solutions to real challenges in the industry, with a chance to win cash prizes and find potential future employers.

Here are the benefits for participating students:
·  Opportunity to work closely with a team of student peers and industry experts to solve unique industry challenges
·  Network with fast-growing companies and find potential future employers
·  Chance to win a cash prize and gain recognition for yourself and your university (cash prizes awarded to top three teams: 1st Place - $5,000; 2nd Place - $3,000; 3rd Place - $1,000)
·  Weekend to discover Chattanooga, TN—a leading hub for the transportation industry—also known as “Freight Alley” (participating teams will receive housing vouchers)

We ask that all students interested apply at colab.co/freighttechchallenge, where they can indicate whether they are part of a team or applying as an individual. 

You can find more information at colab.co/freighttechchallenge or on the information sheet attached to this email. Included on the information sheet is the schedule (may be subject to change) that outlines the activities for the weekend. Please let me know if you have any questions.

Why Chattanooga?

Chattanooga—known as the Scenic City due to its beauty and outdoor recreational scene—has grown to become athriving new hub for startups and large companies alike. With a supportive ecosystem for businesses, Chattanooga has also established itself as the heart of “Freight Alley,” with an increasingly growing number of companies in the transportation and logistics industry due to its position as the epicenter of freight traffic in the Southeast.

“If you start a company there to serve the trucking industry, you have more expertise about what the needs are, and more customers and partners there in Chattanooga as opposed to New York City, Boston and San Francisco. Chattanooga is the “Silicon Valley” of Trucking”
— Steve Case, AOL Co-Founder and Co-Founder of Rise of the Rest





-20 freezers, fisher isothermal



https://www.fishersci.com/shop/products/isotemp-value-lab-freezer-3/p-6966028


Monday, February 18, 2019

*** used lab equipment


https://www.cambridgescientific.com/

https://www.thelabworldgroup.com/reconditioned-lab-equipment

http://www.biosurplus.com/?ajax_search_nonce=7e45e95561&s=+freezer&post_type=product


new life science

https://www.newlifescientific.com/about-us#testimonials_title

Saturday, February 16, 2019

Systems biology of aging


Why individuals with similar genetic makeup live to different lifespans? How can we extend health lifespan? Our group approach these questions through mathematical formulation and computational analysis of genomics data to generate predictive models based on gene/protein networks. Our group also develop various machine learning tools to extrapolate useful information from biological big data.