Method of prosthetic vision
This work is devoted to solving the problem of orientation in the space of visually impaired people. Working on the project, a new way of transmitting visual information through an acoustic channel was invented. In addition, was developed the device, which uses distance sensors to analyze the situation around a user. Thanks to the invented algorithm of transformation of the information about the position of the obstacle into the sound of a certain tone and intensity, this device allows the user to transmit subject-spatial information in real time. Currently, the device should use a facette locator made of 36 ultrasonic locators grouped in 12 sectors by the azimuth and 3 spatial cones by the angle. Data obtained in such a way is converted into its own note according to the following pattern : the angle of the place corresponds to octave, the azimuth corresponds to the note and the distance corresponds to the volume. The choice of the notes is not unambiguous. However, we used them for the reason that over the centuries, notes have had a felicitous way of layout on the frequency range and on the logarithmic scale. Therefore, the appearance of a new note in the total signal will not be muffled by a combination of other notes. Consequently, a blind person, moving around the room with the help of the tone and volume of the sound signals, will be able to assess the presence and location of all dangerous obstacles. After theoretical substantiation of the hypothesis and analysis of the available information, we started the production of prototypes of the devices that would implement the idea of transmitting information via the acoustic channel.
In Silico Modeling of Lovastatin Analogues as Inhibitors of HIV-1 Nef Protein
Currently, no method can completely eliminate the human immunodeficiency virus (HIV) in an infected person. HIV employs an accessory protein called Nef that forms a complex with cellular AP-1, preventing detection of HIV-infected cells. Lovastatin has been recently identified to inhibit the formation of said Nef-AP-1 complex, but its effective concentration is remarked to be far higher than other Nef inhibitors. This study aims to develop a modified lovastatin molecule exhibiting higher binding affinity to the HIV-1 Nef protein than lovastatin in silico. Modified lovastatin molecules based on the interaction map of lovastatin with Nef were modeled, and flexible ligand-flexible receptor docking to the Nef binding site was performed using AutoDock Vina. Residues within the Nef binding site identified by Liu et al. (2019) to be crucial (Glu-63, Val-66, Phe-68, Asp-108, Leu-112, Tyr-115) were set as flexible. Fragment-based drug design was utilized to append molecular fragments to lovastatin in order to maximize its interactions with said crucial residues. From the fragment-based approach, molecule F4 ((1S,3S)‐8‐{2‐[(2R,4R)‐4‐chloro‐6‐oxooxan‐2‐yl]ethyl}‐3‐(hydroxymethyl)‐7‐methyl‐1,2,3,4‐tetrahydronaphthalen‐1‐yl 4‐aminobenzoate) exhibited a binding affinity of -9.0 kcal/mole, and its estimated IC50 ranges between 0.25-0.51 μM which is at least 7.5 times lower than the reported IC50 of lovastatin from literature. This study presents insights on the key modifications to improve lovastatin as an HIV-1 Nef inhibitor and pertinent information about the Nef binding site for future drug development studies.
Line Following Waiter Robot
Technology is erratic. We never know what could be the next big thing. Nowadays, IoT (the internet of things) has taken over the market. Every technology created nowadays is somehow related to IoT. You should manage to connect the IoT technology with a robust area of hospitality. Catering customers' needs during peak hours at any restaurant or cafe could get overwhelmed with hectic tasks such as taking orders, fetching water, and ordering meals. We created a raw model to accommodate the limitations of the human mind. The technology-based IoT (Internet of things) can come in handy during hectic sessions. A Robot waiter is built from scratch using materials like Arduino (2), Gear DC motor (2), L298N motor driver (1), Ultrasonic sensor (2), IR sensor (2), Servo motor (4) HC-05 Bluetooth module. Desired orders are sent on a wireless network through the menu bar to the kitchen. Then, the robots transfer the food from the kitchen to the customers. The floor will be all white, while there will be a strip of black line to connect every sitting and the kitchen. For instance, if table number three is to be served, we click the number three in the app, which renders an obstacle in table 3. The motor barricades the robot, and the ultrasonic sensors sense it, and it stops. If anyone picks the plate, the ultrasonic sensor senses it, the blockage is removed, and the robot paces in the designated path. People visited the place more often to experience such stimuli. Using the robots attracted more customers and made the work very quick.