Aurelia Butler

Scientists from the Faculty of Engineering, Information and Systems at the University of Tsukuba devised a text message mediation robot that can help users control their anger when receiving upsetting news. This device may help improve social interactions as we move towards a world with increasingly digital communications.
While a quick text message apology is a fast and easy way for friends to let us know they are going to be late for a planned meet up, it is often missing the human element that would accompany an explanation face-to-face, or even over the phone. It is likely to be more upsetting when we are not able to perceive the emotional weight behind our friends’ regret at making us wait.
Now, researchers at the University of Tsukuba have built a handheld robot they called OMOY, which was equipped with a movable weight actuated by mechanical components inside its body. By shifting the internal weight, the robot could express simulated emotions. The robot was deployed as a mediator for reading text messages. A text with unwelcome or frustrating news could be followed by an exhortation by OMOY to not get upset, or even sympathy for the user. “With the medium of written digital communication, the lack of social feedback redirect focus from the sender and onto the content of the message itself,” author Professor Fumihide Tanaka says. The mediator robot was designed so that it can suppress the user’s anger and other negative interpersonal motivations, such as thoughts of revenge, and instead fostered forgiveness.
The researchers tested 94 people with a message like “I’m sorry, I am late. The appointment slipped my mind. Can you wait another hour?” The team found that OMOY was able to reduce negative emotions. “The mediator robot can relay a frustrating message followed by giving its own opinion. When this speech is accompanied by the appropriate weight shifts, we saw that that the user would perceive the ‘intention’ of the robot to help them calm down,” Professor Tanaka says.
The robot’s body expression produced by weight shifts did not require any specific external components, such as arms or legs, which implied that the internal weight movements could reduce a user’s anger or other negative emotions without the use of rich body gestures or facial expressions.
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After a stroke, patients may lose feeling in an arm or experience weakness and reduced movement that limits their ability to complete basic daily activities. Traditional rehabilitation therapy is very intensive, time-consuming and can be both expensive and inconvenient, especially for rural patients travelling long distances to in-person therapy appointments.
That’s why a team of researchers, including one at the University of Missouri, utilized a motion-sensor video game, Recovery Rapids, to allow patients recovering from a stroke to improve their motor skills and affected arm movements at home while checking in periodically with a therapist via telehealth.
The researchers found the game-based therapy led to improved outcomes similar to a highly regarded form of in-person therapy, known as constraint-induced therapy, while only requiring one-fifth of the therapist hours. This approach saves time and money while increasing convenience and safety as telehealth has boomed in popularity during the COVID-19 pandemic.
“As an occupational therapist, I have seen patients from rural areas drive more than an hour to come to an in-person clinic three to four days a week, where the rehab is very intensive, taking three to four hours per session, and the therapist must be there the whole time,” said Rachel Proffitt, assistant professor in the MU School of Health Professions. “With this new at-home gaming approach, we are cutting costs for the patient and reducing time for the therapist while still improving convenience and overall health outcomes, so it’s a win-win. By saving time for the therapists, we can also now serve more patients and make a broader impact on our communities.”
Traditional rehab home exercises tend to be very repetitive and monotonous, and patients rarely adhere to them. The Recovery Rapids game helps patients look forward to rehabilitation by completing various challenges in a fun, interactive environment, and the researchers found that the patients adhered well to their prescribed exercises.
“The patient is virtually placed in a kayak, and as they go down the river, they perform arm motions simulating paddling, rowing, scooping up trash, swaying from side to side to steer, and reaching overhead to clear out spider webs and bats, so it’s making the exercises fun,” said Rachel Proffitt, assistant professor in the MU School of Health Professions. “As they progress, the challenges get harder, and we conduct check-ins with the participants via telehealth to adjust goals, provide feedback and discuss the daily activities they want to resume as they improve.”
Nearly 800,000 Americans have a stroke each year according to the CDC, and two-thirds of stroke survivors report they cannot use their affected limbs to do normal daily activities, including making a cup of coffee, cooking a meal or playing with one’s grandchildren.
“I am passionate about helping patients get back to all the activities they love to do in their daily life,” Proffitt said. “Anything we can do as therapists to help in a creative way while saving time and money is the ultimate goal.”
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In the simplest terms, superconductivity between two or more objects means zero wasted electricity. It means electricity is being transferred between these objects with no loss of energy.
Many naturally occurring elements and minerals like lead and mercury have superconducting properties. And there are modern applications that currently use materials with superconducting properties, including MRI machines, maglev trains, electric motors and generators. Usually, superconductivity in materials happens at low-temperature environments or at high temperatures at very high pressures. The holy grail of superconductivity today is to find or create materials that can transfer energy between each other in a non-pressurized room-temperature environment.
If the efficiency of superconductors at room temperature could be applied at scale to create highly efficient electric power transmission systems for industry, commerce, and transportation, it would be revolutionary. The deployment of the technology of room temperature superconductors at atmospheric pressure would accelerate the electrification of our world for its sustainable development. The technology allows us to do more work and use less natural resources with lower waste to preserve the environment.
There are a few superconducting material systems for electric transmission in various stages of development. In the meantime, researchers at the University of Houston are conducting experiments to look for superconductivity in a room-temperature and atmospheric pressure environment.
Paul Chu, founding director and chief scientist at the Texas Center for Superconductivity at UH and Liangzi Deng, research assistant professor, chose FeSe (Iron (II) Selenide) for their experiments because it has a simple structure and also great Tc (superconducting critical temperature) enhancement under pressure.
Chu and Deng have developed a pressure-quench process (PQP), in which they first apply pressure to their samples at room-temperature to enhance superconductivity, cool them to a chosen lower temperature, and then completely release the applied pressure, while still retaining the enhanced superconducting properties.
The concept of the PQP is not new, but Chu and Deng’s PQP is the first time it’s been used to retain the high-pressure-enhanced superconductivity in a high-temperature superconductor (HTS) at atmospheric pressure. The findings are published in the Journal of Superconductivity and Novel Magnetism.
“We waste about 10% of our electricity during transmission, that’s a huge number. If we had superconductors to transmit electricity with zero energy wasted, we would basically change the world, transportation and electricity transmission would be revolutionized, “Chu said. “If this process can be used, we can create materials that could transmit electricity from the place where you produce it all the way to places thousands of miles away without the loss of energy.”
Their process was inspired by the late Pol Duwez, a prominent material scientist, engineer and metallurgist at the California Institute of Technology who pointed out that most of the alloys used in industrial applications are metastable or chemically unstable at atmospheric pressure and room temperature, and these metastable phases possess desired and/or enhanced properties that their stable counterparts lack, Chu and Deng noted in their study.
Examples of these materials include diamonds, high-temperature 3D-printing materials, black phosphorus and even beryllium copper, which is notably used to make tools for use in high explosive environments like oil rigs and grain elevators.
“The ultimate goal of this experiment was to raise the temperature to above room temperature while keeping the material’s superconducting properties,” Chu said. “If that can be achieved, cryogenics will no longer be needed to operate machines that used superconducting material like an MRI machine and that’s why we’re excited about this.”
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Omar Maddouri, a doctoral student in the Department of Electrical and Computer Engineering at Texas A&M University, is working with Dr. Byung-Jun Yoon, professor, and Dr. Edward Dougherty, Robert M. Kennedy ’26 Chair Professor, to evaluate machine-learning models using transfer learning principles. Dr. Francis “Frank” Alexander with Brookhaven National Labs and Dr. Xiaoning Qian from the Department of Electrical and Computer Engineering at Texas A&M University are also involved with the project.
In data-driven machine learning, models are built to make predictions and estimations for what’s to come in any given data set. One important field within machine learning is classification, which allows a data set to be assessed by an algorithm and then classified or broken down into classes or categories. When the data sets provided are very small, it can be very challenging to not only build a classification model based on this data but also to evaluate the performance of this model, ensuring its accuracy. This is where transfer learning comes into play.
“In transfer learning, we try to transfer knowledge or bring data from another domain to see whether we can enhance the task that we are doing in the domain of interest, or target domain,” Maddouri explained.
The target domain is where the models are built, and their performance is evaluated. The source domain is a separate domain that is still relevant to the target domain from which knowledge is transferred to make the analysis within the target domain easier.
Maddouri’s project utilizes a joint prior density to model the relatedness between the source and target domains and offers a Bayesian approach to apply the transfer learning principles to provide an overall error estimator of the models. An error estimator will deliver an estimate of how accurate these machine-learning models are at classifying the data sets at hand.
What this means is that before any data is observed, the team creates a model using their initial inferences about the model parameters in the target and source domains and then updates this model with enhanced accuracy as more evidence or information about the data sets becomes available.
This technique of transfer learning has been used to build models in previous works; however, no one has ever before used this transfer learning technique to propose novel error estimators to evaluate the performance of these models. For an efficient utilization, the devised estimator has been implemented using advanced statistical methods that enabled a fast screening of source data sets which enhances the computational complexity of the transfer learning process by 10 to 20 times.
This technique can help serve as a benchmark for future research within academia to build upon. In addition, it can help with identifying or classifying different medical issues that would otherwise be very difficult. For example, Maddouri utilized this technique to classify patients with schizophrenia using transcriptomic data from brain tissue samples originally acquired by invasive brain biopsies. Because of the nature and the location of the brain region that can be analyzed for this disorder, the data collected is very limited. However, using a stringent feature selection procedure that comprises differential gene expression analysis and statistical testing for assumptions validity, the research team identified transcriptomic profiles of three genes from an additional brain region found to be highly relevant to the desired brain tissue as reported by independent research studies from other literature.
This knowledge allowed them to utilize the transfer learning technique to leverage samples collected from the second brain region (source domain) to help with the analysis and significantly boost the accuracy of diagnosis within the original brain region (target domain). The data gathered from the source domain can be exploratory in the absence of information from the target domain, allowing the research team to enhance the quality of their conclusion.
This research has been funded by the Department of Energy and the National Science Foundation.
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Currently, there is little research focused on understanding mechanisms and drug discovery of lymphatic vascular diseases. However, conditions such as lymphedema, a buildup of fluid in the body when the lymph system is damaged, impact more than 200,000 people every year in the United States alone.
Dr. Abhishek Jain, assistant professor in the Department of Biomedical Engineering at Texas A&M University, has taken his expertise in organ-on-chip models and applied them to a field they’ve never been used in before, creating the first lymphangion-chip.
To engineer this new device, Jain’s team first developed a new technique to create microfluidic cylindrical blood or lymphatic vessels consisting of endothelial cells, which line blood vessels. It could then use this technique to create a co-cultured multicellular lymphangion, the functional unit of a lymph vessel, and successfully recreate a typical section of a lymphatic transport vessel in vitro, or outside the body.
“We can now better understand how mechanical forces regulate lymphatic physiology and pathophysiology,” Jain said. “We can also understand what are the mechanisms that result in lymphedema, and then we can find new targets for drug discovery with this platform.”
The project is in collaboration with Dr. David Zawieja from the Texas A&M College of Medicine. Their research was published in the Jan. 7 issue of the journal Lab on a Chip.
“Collaborations with Dr. Zawieja and others in the department played a crucial role,” Jain said. “They introduced me to this topic and provide their longstanding expertise that has made it possible for us to create this new organ-on-chip platform and now advance it in these exciting directions using contemporary experimental models.”
Jain said the impact of this work is far-reaching because there is a new hope for patients with lymphatic diseases. They can now learn about the biology of these diseases and reach a point where they can be treated.
“The most exciting part of this research is that it is allowing us to now push the organ-on-chip in directions where finding cures for rare and orphan (understudied) diseases is possible with less effort and money,” Jain said. “We can help the pharma industry to invest in this platform and find a cure for lymphedema that impacts millions of people.”
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The ability to interact with light provides important functionalities for quantum systems, such as communicating over large distances, a key ability for future quantum computers. However, it is very difficult to find a material that can fully exploit the quantum properties of light. A research team from the CNRS and l’Université de Strasbourg, with support from Chimie ParisTech-PSL1 and in collaboration with German teams from KIT2, has demonstrated the potential of a new material based on rare earths as a photonic quantum system. The results, which were published on 9 March 2022 in Nature, show the interest of europium molecular crystals for quantum memories and computers.
While quantum technologies promise a revolution in the future, they still remain complex to put in place. For example, quantum systems that can interact with light to create processing functionalities for information and communication through fibre optics in particular, remain rare. Such a platform3 must ideally include an interface with light as well as information storage units, which is to say a memory. Information processing must also be possible within these units, which take the form of spin4. Developing materials that enable a link between spins and light on the quantum level has proven especially difficult.
A team of scientists from the CNRS and l’Université de Strasbourg, with support from Chimie ParisTech-PSL and in collaboration with German teams from KIT, has successfully demonstrated the value of europium molecular crystals5 for quantum communications and processors, thanks to their ultra-narrow optical transitions enabling optimal interactions with light.
These crystals are the combined product of two systems already used in quantum technology: rare earth ions (such as europium), and molecular systems. Rare-earth crystals are known for their excellent optical and spin properties, but their integration in photonic devices is complex. Molecular systems generally lack spins (a storage or computing unit), or on the contrary present optical lines that are too broad to establish a reliable link between spins and light.
Europium molecular crystals represent a major advance, as they have ultra-narrow linewidths. This translates into long-lived quantum states, which were used to demonstrate the storage of a light pulse inside these molecular crystals. Moreover, a first building block for a quantum computer controlled by light has been obtained. This new material for quantum technologies offers previously unseen properties, and paves the way for new architectures for computers and quantum memories in which light will play a central role.
The results also open broad prospects for research thanks to the many molecular compounds that can be synthesized.
Notes
1 — Scientists from the following laboratories participated: the Institut de recherche de chimie Paris (CNRS/Chimie ParisTech-PSL), the Institut de physique et chimie des matériaux de Strasbourg (CNRS/Université de Strasbourg), Institut de science et d’ingénierie supramoléculaire (CNRS/Université de Strasbourg), and the Centre européen de sciences quantiques.
2 — Karlsruher Institute of Technology (KIT) including the Institute of Quantum Materials and Technology (IQMT), the Institute of Nanotechnology (INT) and the Physikalishes Institut (PHI) in Germany, also participated
3 — A platform refers to a multifunctional quantum material.
4 — Spin is one of the properties of particles, along with mass and electric charge, which determines their behaviour in a magnetic field.
5 — Molecular crystals are perfectly ordered stacks of individual molecules.
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A collaborative study led by the University of Wollongong confirms switching mechanism for a new, proposed generation of ultra-low energy ‘topological electronics’.
Based on novel quantum topological materials, such devices would ‘switch’ a topological insulator from non-conducting (conventional electrical insulator) to a conducting (topological insulator) state, whereby electrical current could flow along its edge states without wasted dissipation of energy.
Such topological electronics could radically reduce the energy consumed in computing and electronics, which is estimated to consume 8% of global electricity, and doubling every decade.
Led by Dr Muhammad Nadeem at the University of Wollongong (UOW), the study also brought in expertise from FLEET Centre collaborators at UNSW and Monash University.
Resolving the Switching Challenge, and Introducing the Tqfet
Two-dimensional topological insulators are promising materials for topological quantum electronic devices where edge state transport can be controlled by a gate-induced electric field. More