Microscope Stand Prototype I

Our microscope assembly includes an LED array, foldscope lenses, and a cellphone. The first design for our microscope stand used a LEGO base to hold the LED array in place beneath the foldscope and cellphone arrangement, which were supported by a piece of cardboard. The second design, shown below, was made in Autodesk and 3D printed in the college makerspace.

The base of the stand is scaled to snugly hold the LED array in place. The four narrow supports along the sides of the stand are intended to hold the phone, foldscope, and slide assembly in place at four different heights, allowing for very crude z-distance adjustment.

Because the 3D design is uncomplicated, it was decided that future prototypes should be made of laser cut acrylic pieces and fitted together. The 3D printing job was too large to print on a practical timetable, and during early prototyping stages rapid iteration is desirable. The laser cuts take only a few minutes at a time, while the 3D print job took more than 24 hours.

This simple stand design was useful for developing skills in Autodesk and 3D printing, and for holding the microscope setup steady while attempting to take calibration images. However, it does not allow any fineness in z-distance adjustment and no movement at all in the x and y directions. Future designs will include 3 stepper motors arranged so that minute changes can be made in all three directions for best image quality and control.

Determining Magnification of a Microscope Lens

For our project, we need to know the magnifying power of a lens with a fairly high degree of accuracy. Some lenses have unknown or obviously inaccurate magnification information, while others have approximately accurate information that is not precise enough for computations. In either case, it is useful to be able to calculate the magnifying power for ourselves.

A microscope slide like the one above, whose divisions are a known distance apart, is used to perform the calculation.

First, a picture is taken of the ruler slide using the desired magnification. Next, the individual pixels between two divisions are counted. This is done using any editing software with a single-pixel brush size. Finally, the pixel size on the sensor plane of the imaging device must be known. Camera documentation should include this information.

Magnification is found by multiplying the counted number of pixels per division by the pixel size on the sensor plane and dividing by the actual distance of the divisions on the slide. An example calculation is performed below on a lens of approximately 10x magnification:

Calibration slide with 50 um divisions
Camera with 6.5 um pixel size
Counted 72 pixels per division

Magnification = (6.5*72)/50 = 9.36x

 

Notes On How To Move Things: Ball Screw VS Rack and Pinion

Currently, we’re working on a low-cost plotter to move a specimen slide around on the x-y plane while also having the z-axis to adjust the focus of the optical element. Whew, that’s a lot of moving things. This, of course, begs the question: what is the best way to move things? Currently, we have two options:

 

Ball Screw:

Cross Section of a Ball Screw on a Screw Shaft

The ball screw would traverse the screw shaft.

From camaster.com “Ball screws are best known for being smooth and friction-free. Over a long axis however, a ball screw-driven system is susceptible to “screw whip”, which is vibration that worsens the faster a screw rotates. This is because of the critical speed of rotation needed over a long axis. To alleviate this, a ball screw driven system requires more gearing or larger motors to compensate for the weight and need to maintain the rapid positioning speeds. This makes the use of a ball screw on an axis over 4’ in length not ideal. That being said, for shorter lengths, this is rarely realized which makes the use of a ball screw a good choice for a short axis on the machine.”

Rack and Pinion:

Image of a Rack and Pinion
Image of a Rack and Pinion

For our purposes, it is likely the pinion would be fixed while the rack would move.

Rack-and-pinion drives are far better at handling long axis of motion. Indeed, because of its design, rack and pinion drives can be faster at traversing distances than the ball screw because they can utilize torque more effectively.

They do however have some downsides. From camaster.com,  “Rack-and-pinion’s shortcomings include higher friction and potential backlash if the pinion is not properly engaged.”

 

Sources:

http://www.cncrouterparts.com/which-is-better-a-screw-or-rack-and-pinion-drive-p-99.html

http://www.camaster.co/faq/whats-better-rack-and-pinion-or-ball-screw/

 

 

 

Notes On Stepper Motors

Different stepper motors are rated at different amounts of steps. For example, we are currently looking at two different stepper motors. One has 32 steps the other has 200 steps. Using the formula 360/(# of steps) we can calculate the step angle.

Step Angle of 32 Step Stepper Motor:  11.25 degrees

Step Angle of 200 Step Stepper Motor: 1.8 degrees

 

Given the size of the plotter that we are building it seems that buying the 2o step stepper motor is the better choice.

The Trials and Tribulations Of Installing New Lab Computers

So I was able to acquire the new Lab computers without an issue (huge thanks to Jeff–the wonderful sysadmin–for helping me!). I slapped a 1TB SSD in both of them and it was off to the races…almost. Unfortunately,  the very expensive software that we need to use requires Windows. The Lab machines were running Ubuntu, so I contacted ITS to see if they could install Windows on the new Lab machines. After much back and forth, the ultimate answer was yes! Now, with the new Lab machines equipped with Windows, we are finally ready to put them to work.

How To Get New(ish) Lab Computers and Reduce E-Waste!

E-waste is a real issue. A report from the United Nations’ International Telecommunication Union states that 45 million tons of e-waste was generated in 2016.

Like any good Swattie, I am concerned about our environment and want to do what I can to help reduce, reuse, and recycle. However, the fact remains that the Lab needs new computers.

My solution to this predicament is pretty simple. Any institution maintains a set of public use computers. These computers are replaced on a predefined upgrade/replacement cycle which lasts about 3-5 years. If your institution is smart about it,  different sets of computers will be at different stages in this cycle. Meaning, it’s a good bet that your institution is about to throw out some computers.

You should ask for one of those computers.

 

Here is what I did:

I knew that our CS dept just recently upgraded one of their CS labs. With this knowledge in mind, I went to the sysadmin and asked him if I could have two of the computers he was planning on recycling to use in the Lab I am working in. He said yes. And, just like that, I was able to acquire two new(ish) computers for my Lab.

Now, these computers are on the older side so I have provided some suggestions to speed up and extend the life of your newly acquired computer.

 

Tips To Extend The Life Of An Older Computer

  • Add more RAM. Older computers usually come with 4 GB of RAM as that was what was deemed a normal amount in the early 2010s. 8 GB should be your minimum.
  • Replace the hard drive with an SSD. This, by far, is the single best thing you can do to speed up an old computer. Even if you don’t want to shell out the money for a large SSD (at the time of writing they are $0.10/GB), replacing the hard drive is a good idea anyway since you don’t know how much use the preexisting hard drive has.
  • If feasible, put on a lightweight operating system like lubuntu. 

 

A Note On Academic Publishing

Earlier this week I learned the baffling fact that academics have to pay to get their work published. I decided to do a little digging and this is what I found:

  • There is a huge concentration of power: In 2013, a mere five academic publishers (Reed, Elsevier, Wiley-Blackwell, Springer, and Taylor & Francis) published over half of all scholarly papers!
  • Customers have to pay to read papers, but the authors also pay to submit their papers. Moreover, the research submitted isn’t paid for by the publisher either!
  • This means that the publishers make an absurd amount of money. The Guardian reported that in 2010 “Elsevier [had] total global revenues of more than £19bn” (24,510,000,000 USD)!

How did all of this come about?

Well, in the 1950s there was no good way to disseminate scientific findings so the British government tried to improve this by incentivizing book publishers to publish scientific articles.  These publications turned into journals. At first, publication in these journals did not have a huge bearing on one’s academic career. However, over time, some journals were known for publishing a higher frequency of novel and influential papers. These journals gained prestige. As a result, it was desirable to publish in them. Suddenly, one’s worth as an academic depended on their publications. This resulted in the now familiar mantra of “publish or perish.” Even though publishing was an essential part of academia, some publishers were struggling financially. The larger publishers took this opportunity to acquire smaller publishers — thereby consolidating their power and creating today’s publishing landscape.

 

What happens next?

Unfortunately, its really hard to get a large enough portion of academia to forgo publishing in prestigious journals because their livelihood is on the line. Thus, the move from these closed off publishers to open access publishing has been a slow process. Moreover, many publishers have co-opted the open access movement to squeeze even more money out of academics. Now, many publishers have the option for academics to publish their work open access, but to do so is considerably more expensive than publishing not open access.  Given these factors, it is unclear what will happen next.

Sources:

The Oligopoly of Academic Publishers in the Digital Era

Is the staggeringly profitable business of scientific publishing bad for science?

 

 

 

 

Fall ’18 Semester Summary

This semester, we collected 90 datasets of low resolution flatworm images to train the neural network on. The tomographic output is a high resolution and has a wide field of view. When training on the neural net is complete, we will be capable of single-shot reconstruction. Assuming the training is successful, we will write a paper on this research during the spring semester.

The foldscope project is proceeding more rapidly now that the flatworm project is nearing completion. We have prototyped multiple FPM-compatible assemblies using Legos and other material. Once our design is finalized, instructions for duplication will be posted to the blog along with images of the final product. We have experimented with apache cordova and other tools that will allow us to wirelessly control our LED array in sync with an iPhone camera using a simple app. The  ESP8266 dev board will be the key to wireless synchronization. The FPM app and any other software will be made available once complete so that any person with a foldscope, LED array, and cell phone can achieve single-shot Fourier reconstruction.

Deep Learning for Optimization of Fourier Ptychography

Our foldscope research is an extension of research completed this summer and during the 17/18 school year in Professor Ganapati’s lab. Using a neural network trained on low resolution input data and corresponding high resolution FPM reconstructions, we simultaneously optimize the illumination pattern and reconstruction algorithm.

The neural network identifies a single LED pattern to encode as much information about the sample as possible into one low resolution input image. By restricting our samples to a fixed type, we are able to significantly reduce the information requirements for reconstruction, making single-image reconstruction possible. The optimized reconstruction is also non-iterative, further improving temporal resolution.

For any given sample type, after training, we are able to generate a high resolution reconstruction from a single low resolution input image. We now aim to apply this technique with the foldscope to create an extremely low cost microscope capable of single image super-resolution microscopy.

Preprints:

“Optimal Physical Preprocessing for Example-Based Super-Resolution

Illumination Pattern Design with Deep Learning for Single-Shot Fourier Ptychographic Microscopy

Introduction to the Foldscope

The foldscope is a paper microscope project designed to make quality microscopy portable and affordable. The bulk of the microscope is an origami-style paper assembly with sliders for manipulating the x, y, and z axes. The small lens can be affixed to a cellphone camera for easy imaging.

Foldscopes are useful anywhere lightweight, durable, and inexpensive scientific equipment is sought. They are used with paper centrifuges for low cost malaria detection, and in homes and schools to excite an interest in science on a budget.

Our Foldscopes were easy to assemble with the provided instructions. We magnified a microscope slide and took a cell phone camera image while holding the slide up to a light.

The slide and lens were both somewhat dusty, and we could possibly have improved the focus with more careful adjustment. We decided, however, that this image would suffice as a proof of concept. Later, we built a temporary stand from Legos. The added stability improved overall image quality.

More information is available on the Foldscope website

And YouTube:

Manu Prakash: A 50-cent microscope that folds like origami

How to save 51 billion lives for 68 cents with simple Engineering