![136226-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-05/136226-Thumbnail%20Image.png?versionId=Ly1llGVLDgHpNUj7yi9Web_R.Z7RKOsU&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240605/us-west-2/s3/aws4_request&X-Amz-Date=20240605T091254Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=b6234ef2d5b7926afd08b5a607845150a3f9f338c5914232073cc419a498bd31&itok=g3mlIzwP)
![148448-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-07/148448-Thumbnail%20Image.png?versionId=8ZUn4wTFSSt_zViQQ791bnihncHFqwDw&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240619/us-west-2/s3/aws4_request&X-Amz-Date=20240619T045429Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=2efb0f83eca59f2272f3e6a5e48a66271489ea695846f0d95f4baec8a620e282&itok=_Sq9PcJE)
This paper discusses the theoretical approximation and attempted measurement of the quantum <br/>force produced by material interactions though the use of a tuning fork-based atomic force microscopy <br/>device. This device was built and orientated specifically for the measurement of the Casimir force as a <br/>function of separation distance using a piezo actuator for approaching and a micro tuning fork for the <br/>force measurement. This project proceeds with an experimental measurement of the ambient Casmir force <br/>through the use of a tuning fork-based AFM to determine its viability in measuring the magnitude of the <br/>force interaction between an interface material and the tuning fork probe. The ambient measurements <br/>taken during the device’s development displayed results consistent with theoretical approximations, while<br/>demonstrating the capability to perform high-precision force measurements. The experimental results<br/>concluded in a successful development of a device which has the potential to measure forces of <br/>magnitude 10−6 to 10−9 at nanometric gaps. To conclude, a path to material analysis using an approach <br/>stage, alternative methods of testing, and potential future experiments are speculated upon.
![148495-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-07/148495-Thumbnail%20Image.png?versionId=rQL7u54rhbnCV.i811sx60kEHnkpM5ON&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240619/us-west-2/s3/aws4_request&X-Amz-Date=20240619T052240Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=3986101be7d24d27b522f5f8f7bd070cd1e89b7b1736ec209e6da3ab5ac47b35&itok=G-fkc8TG)
Tunable Near-Field Radiative Heat Transfer Exceeding Blackbody Limit with Vanadium Dioxide Thin Film
This paper investigates near-field thermal radiation as the primary source of heat transfer between two parallel surfaces. This radiation takes place extremely close to the heated surfaces in study so the experimental set-up to be used will be done at the nanometer scale. The primary theory being investigated is that near-field radiation generates greater heat flux that conventional radiation governed by Planck’s law with maximum for blackbodies. Working with a phase shift material such as VO2 enables a switch-like effect to occur where the total amount of heat flux fluctuates as VO2 transitions from a metal to an insulator. In this paper, the theoretical heat flux and near-field radiation effect are modeled for a set-up of VO2 and SiO2 layers separated by different vacuum gaps. In addition, a physical experimental set-up is validated for future near-field radiation experiments.
![135861-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-05/135861-Thumbnail%20Image.png?versionId=vZGLmE1yFLd08ibPRvLNEeDgUXhmB17k&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240614/us-west-2/s3/aws4_request&X-Amz-Date=20240614T202512Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=5ceaa77a934e35910684f0abddae277dda5a3dad2e6fc2bb93843d9586ef095b&itok=-ioQQqZz)
![130351-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-04/130351-Thumbnail%20Image.png?versionId=tBT5SGBej18LnPsgZCWNj9cuqqy9tSah&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240530/us-west-2/s3/aws4_request&X-Amz-Date=20240530T155452Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=f1561b5b36be3bd89fcc3e1309cd79b4ab4c89d3dc3992aecaa6796863458c19&itok=ijEt79V-)
Viral protein U (Vpu) is a type-III integral membrane protein encoded by Human Immunodeficiency Virus-1 (HIV- 1). It is expressed in infected host cells and plays several roles in viral progeny escape from infected cells, including down-regulation of CD4 receptors. But key structure/function questions remain regarding the mechanisms by which the Vpu protein contributes to HIV-1 pathogenesis. Here we describe expression of Vpu in bacteria, its purification and characterization. We report the successful expression of PelB-Vpu in Escherichia coli using the leader peptide pectate lyase B (PelB) from Erwinia carotovora. The protein was detergent extractable and could be isolated in a very pure form. We demonstrate that the PelB signal peptide successfully targets Vpu to the cell membranes and inserts it as a type I membrane protein. PelB-Vpu was biophysically characterized by circular dichroism and dynamic light scattering experiments and was shown to be an excellent candidate for elucidating structural models.
![131002-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-07/131002-Thumbnail%20Image.png?versionId=FRL02zkBJJrMwpAM86vb13UkrqGk4VPQ&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240619/us-west-2/s3/aws4_request&X-Amz-Date=20240619T112146Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=ff01616f510cd5df056f468d701f5e767340c3cc62db9dcc91276f6b48230a3b&itok=aGuOpFEz)
To achieve this goal, a model of a swarm performing a collective transport task in a bounded domain featuring convex obstacles was simulated in MATLAB/ Simulink®. The closed-loop dynamic equations of this model were linearized about an equilibrium state with angular acceleration and linear acceleration set to zero. The simulation was run over 30 times to confirm system ability to successfully transport the payload to a goal point without colliding with obstacles and determine ideal operating conditions by testing various orientations of objects in the bounded domain. An additional purely MATLAB simulation was run to identify local minima of the Hessian of the navigation-like potential function. By calculating this Hessian periodically throughout the system’s progress and determining the signs of its eigenvalues, a system could check whether it is trapped in a local minimum, and potentially dislodge itself through implementation of a stochastic term in the robot controllers. The eigenvalues of the Hessian calculated in this research suggested the model local minima were degenerate, indicating an error in the mathematical model for this system, which likely incurred during linearization of this highly nonlinear system.
![132384-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-05/132384-Thumbnail%20Image.png?versionId=dsfewFjSXIwYUo33c_X10SA6Gpo7pSH4&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240619/us-west-2/s3/aws4_request&X-Amz-Date=20240619T183642Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=0bf48f9fb264097eb228e817e96b6b486b756ae61ae534807b268da147ee1b43&itok=wBJWEhIu)
This paper analyzes responses to deviated Trolley Problem scenarios [5] in a simulated driving environment and still images from MIT’s moral machine website [8] to better understand how humans respond to various crashes. Also included is participants driving habits and personal values, however the bulk of that analysis is not included here. The results of the simulation prove that for the most part in driving scenarios, people would rather sacrifice themselves over people outside of the vehicle. The moral machine scenarios prove that self-sacrifice changes as the trend to harm one’s own vehicle was not so strong when passengers were introduced. Further defending this idea is the importance placed on Family Security over any other value.
Suggestions for implementing ethics into autonomous vehicle crashes stem from the results of this experiment but are dependent on more research and greater sample sizes. Once enough data is collected and analyzed, a moral baseline for human’s moral domain may be agreed upon, quantified, and turned into hard rules governing how self-driving cars should act in different scenarios. With these hard rules as boundary conditions, artificial intelligence should provide training and incremental learning for scenarios which cannot be determined by the rules. Finally, the neural networks which make decisions in artificial intelligence must move from their current “black box” state to something more traceable. This will allow researchers to understand why an autonomous vehicle made a certain decision and allow tweaks as needed.
![132073-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-07/132073-Thumbnail%20Image.png?versionId=MGJVsboM.reKryBQXEk8mQX70X9q_mQk&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240619/us-west-2/s3/aws4_request&X-Amz-Date=20240619T183642Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=699a81186bc09003f5726f3451637917bef7c65f4ee17b0a35f12860d3e13e93&itok=ShP7VZOj)
![131567-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-07/131567-Thumbnail%20Image.png?versionId=tK7VrQQ.dmmp.4M4LS.6WOlc55snpSin&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240619/us-west-2/s3/aws4_request&X-Amz-Date=20240619T191600Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=3a600e12b4609fca7102b81fe6ac81e5ac34f93131520e33365b00bb2a769be6&itok=VrGDcgzJ)