Aspiring Engineers Hub
This blog will include information and pages on the many facets of engineering, career paths, and many resources for the aspiring engineer.
Thursday, 26 March 2015
Big step toward using light instead of wires inside computers.
Sunday, 22 March 2015
Siemens launches new low-voltage Simotics standard motors with highestefficiency class.
Siemens Boosts Safety through Gas Analyser Technology
Sunday, 15 March 2015
The world’s smallest resistances.
Saturday, 14 March 2015
Materials sciences - an interdisciplinary research field.
New materials discovered to detect neutrons emitted by radioactive materials.
The future of electronics -- now in 2-D
Improved fire detection with new ultra-sensitive, ultraviolet lightsensor.
Graphene, the wonder material, goes textile.
Black Phosphorus Is New ‘Wonder Material’ for Improving OpticalCommunication.
Chemists develop new way to make cost-effective material for electricity storage.
Friday, 13 March 2015
The PAL-V One, A Flying Car Worth Driving.
Wednesday, 11 March 2015
Carbon Fiber Grids Replace Steel as Innovative Concrete Reinforcement.
Strongest known natural material – spider silk or limpet teeth?
- A limpet is an aquatic snail with a shell broadly conical in shape. "Limpet" informally refers to any gastropod whose shell has no obvious coiling as in familiar garden snails or in winkles.
Monday, 9 March 2015
First solar powered plane in the world takes off from UAE
Self cleaning paint made from coated titanium dioxidenanoparticles.
Urine can generate electricity to light camps in disaster zone.
Nano-medicine drug combinations achieved maximum efficiency in cancer therapy.
Source: University of California - Los Angeles
Summary: Designing optimized combination therapies for cancer is remarkably difficult due to the infinite possible drug dose ratios and variable patient-specific response to treatment. In a landmark advance for personalized medicine, bioengineers have developed a novel technology that, for the first time, overcomes these challenges. By assessing phenotype, or physical biological traits as they respond to chemotherapy to drive a powerful analytics platform, the most effective and safe drug combinations possible can be systematically designed.
In greater than 90 percent of cases in which treatment for metastatic cancer fails, the reason is that the cancer is resistant to the drugs being used. To treat drug-resistant tumors, doctors typically use multiple drugs simultaneously, a practice called combination therapy. And one of their greatest challenges is determining which ratio and combination -- from the large number of medications available -- is best for each individual patient.
Dr. Dean Ho, a professor of oral biology and medicine at the UCLA School of Dentistry, and Dr. Chih-Ming Ho, a professor of mechanical engineering at the UCLA Henry Samueli School of Engineering and Applied Science, have developed a revolutionary approach that brings together traditional drugs and nanotechnology-enhanced medications to create safer and more effective treatments. Their results are published in the peer-reviewed journal ACS Nano.
Chih-Ming Ho, the paper's co-corresponding author, and his team have developed a powerful new tool to address drug resistance and dosing challenges in cancer patients. The tool, Feedback System Control.II, or FSC.II, considers drug efficacy tests and analyzes the physical traits of cells and other biological systems to create personalized "maps" that show the most effective and safest drug-dose combinations.
Currently, doctors use people's genetic information to identify the best possible combination therapies, which can make treatment difficult or impossible when the genes in the cancer cells mutate. The new technique does not rely on genetic information, which makes it possible to quickly modify treatments when mutations arise: the drug that no longer functions can be replaced, and FSC.II can immediately recommend a new combination.
"Drug combinations are conventionally designed using dose escalation," said Dean Ho, a co-corresponding author of the study and the co-director of the Jane and Jerry Weintraub Center for Reconstructive Biotechnology at the School of Dentistry. "Until now, there hasn't been a systematic way to even know where the optimal drug combination could be found, and the possible drug-dose combinations are nearly infinite. FSC.II circumvents all of these issues and identifies the best treatment strategy."
The researchers demonstrated that combinations identified by FSC.II could treat multiple lines of breast cancer that had varying levels of drug resistance. They evaluated the commonly used cancer drugs doxorubicin, mitoxantrone, bleomycin and paclitaxel, all of which can be rendered ineffective when cancer cells eject them before they have had a chance to function.
The researchers also studied the use of nanodiamonds to make combination treatments even more effective. Nanodiamonds -- byproducts of conventional mining and refining operations -- have versatile characteristics that allow drugs to be tightly bound to their surface, making it much harder for cancer cells to eliminate them and allowing toxic drugs to be administered over a longer period of time.
The use of nanodiamonds to treat cancer was pioneered by Dean Ho, a professor of bioengineering and member of the UCLA Jonsson Comprehensive Cancer Center and the California NanoSystems Institute.
"This study has the capacity to turn drug development, nano or non-nano, upside-down," he said. "Even though FSC.II now enables us to rapidly identify optimized drug combinations, it's not just about the speed of discovering new combinations. It's the systematic way that we can control and optimize different therapeutic outcomes to design the most effective medicines possible."
The study found that FSC.II-optimized drug combinations that used nanodiamonds were safer and more effective than optimized drug-only combinations. Optimized nanodrug combinations also outperformed randomly designed nanodrug combinations.
"This optimized nanodrug combination approach can be used for virtually every type of disease model and is certainly not limited to cancer," said Chih-Ming Ho, who also holds UCLA's Ben Rich Lockheed Martin Advanced Aerospace Tech Endowed Chair. "Additionally, this study shows that we can design optimized combinations for virtually every type of drug and any type of nanotherapy."
Mechanical engineers develop an ‘intelligent co-pilot’ for cars.
The key to the maneuver is a new semiautonomous safety system developed by Sterling Anderson, a PhD student in MIT’s Department of Mechanical Engineering, and Karl Iagnemma, a principal research scientist in MIT’s Robotic Mobility Group.
The system uses an onboard camera and laser rangefinder to identify hazards in a vehicle’s environment. The team devised an algorithm to analyze the data and identify safe zones — avoiding, for example, barrels in a field, or other cars on a roadway. The system allows a driver to control the vehicle, only taking the wheel when the driver is about to exit a safe zone.
Anderson, who has been testing the system in Michigan since last September, describes it as an “intelligent co-pilot” that monitors a driver’s performance and makes behind-the-scenes adjustments to keep the vehicle from colliding with obstacles, or within a safe region of the environment, such as a lane or open area.
“The real innovation is enabling the car to share [control] with you,” Anderson says. “If you want to drive, it’ll just … make sure you don’t hit anything.”
The group presented details of the safety system recently at the Intelligent Vehicles Symposium in Spain.
Off the beaten path
Robotics research has focused in recent years on developing systems — from cars to medical equipment to industrial machinery — that can be controlled by either robots or humans. For the most part, such systems operate along preprogrammed paths.
As an example, Anderson points to the technology behind self-parking cars. To parallel park, a driver engages the technology by flipping a switch and taking his hands off the wheel. The car then parks itself, following a preplanned path based on the distance between neighboring cars.
While a planned path may work well in a parking situation, Anderson says when it comes to driving, one or even multiple paths is far too limiting.
“The problem is, humans don’t think that way,” Anderson says. “When you and I drive, [we don’t] choose just one path and obsessively follow it. Typically you and I see a lane or a parking lot, and we say, ‘Here is the field of safe travel, here’s the entire region of the roadway I can use, and I’m not going to worry about remaining on a specific line, as long as I’m safely on the roadway and I avoid collisions.’”
Anderson and Iagnemma integrated this human perspective into their robotic system. The team came up with an approach to identify safe zones, or “homotopies,” rather than specific paths of travel. Instead of mapping out individual paths along a roadway, the researchers divided a vehicle’s environment into triangles, with certain triangle edges representing an obstacle or a lane’s boundary.
The researchers devised an algorithm that “constrains” obstacle-abutting edges, allowing a driver to navigate across any triangle edge except those that are constrained. If a driver is in danger of crossing a constrained edge — for instance, if he’s fallen asleep at the wheel and is about to run into a barrier or obstacle — the system takes over, steering the car back into the safe zone.
Building trust
So far, the team has run more than 1,200 trials of the system, with few collisions; most of these occurred when glitches in the vehicle’s camera failed to identify an obstacle. For the most part, the system has successfully helped drivers avoid collisions.
Benjamin Saltsman, manager of intelligent truck vehicle technology and innovation at Eaton Corp., says the system has several advantages over fully autonomous variants such as the self-driving cars developed by Google and Ford. Such systems, he says, are loaded with expensive sensors, and require vast amounts of computation to plan out safe routes.
"The implications of [Anderson's] system is it makes it lighter in terms of sensors and computational requirements than what a fully autonomous vehicle would require," says Saltsman, who was not involved in the research. "This simplification makes it a lot less costly, and closer in terms of potential implementation."
In experiments, Anderson has also observed an interesting human response: Those who trust the system tend to perform better than those who don’t. For instance, when asked to hold the wheel straight, even in the face of a possible collision, drivers who trusted the system drove through the course more quickly and confidently than those who were wary of the system.
And what would the system feel like for someone who is unaware that it’s activated? “You would likely just think you’re a talented driver,” Anderson says. “You’d say, ‘Hey, I pulled this off,’ and you wouldn’t know that the car is changing things behind the scenes to make sure the vehicle remains safe, even if your inputs are not.”
He acknowledges that this isn’t necessarily a good thing, particularly for people just learning to drive; beginners may end up thinking they are better drivers than they actually are. Without negative feedback, these drivers can actually become less skilled and more dependent on assistance over time. On the other hand, Anderson says expert drivers may feel hemmed in by the safety system. He and Iagnemma are now exploring ways to tailor the system to various levels of driving experience.
The team is also hoping to pare down the system to identify obstacles using a single cellphone. “You could stick your cellphone on the dashboard, and it would use the camera, accelerometers and gyro to provide the feedback needed by the system,” Anderson says. “I think we’ll find better ways of doing it that will be simpler, cheaper and allow more users access to the technology.”
This research was supported by the United States Army Research Office and the Defense Advanced Research Projects Agency. The experimental platform was developed in collaboration with Quantum Signal LLC with assistance from James Walker, Steven Peters and Sisir Karumanchi.