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TFF Prescribed drugs obtained a $2.97 million grant from the Nationwide Institute of Allergy and Infectious Illnesses (NIAID) to develop a common influenza vaccine utilizing a “skinny movie freezing” expertise developed by UT researchers. 

Principal investigator Invoice Williams mentioned the expertise freeze-dries liquid medicines right into a powder for increased effectivity, simpler storage and extra sturdiness.

Jennifer Gordon, NIAID Program Officer for Influenza and Coronavirus Vaccines, mentioned TFF Prescribed drugs’ work beneath the NIAID grant goals to create a single vaccine that fights a number of strains of influenza.

“(The flu) is difficult to foretell, and the vaccine course of could be prolonged, leaving folks with a vaccine that now not matches the strains predominantly circulating locally,” Gordon mentioned in an electronic mail. “There’s a excessive precedence must develop vaccines that may present larger safety than the at present used seasonal vaccines.”

Williams mentioned vaccine storage poses an issue worldwide, as many international locations lack the expertise to maintain vaccines cool. He mentioned with skinny movie freezing, the powder doesn’t have to be stored chilly and forgoes using syringes or different supplies sometimes related to vaccines, facilitating simpler distribution.

“It solves issues that there was no expertise on the market to resolve,” Williams mentioned.

The grant will enable researchers to check the vaccine’s efficacy on people. 

“We’ve carried out animal research and gotten good outcomes,” Williams mentioned. “Now it’s going to the following step to get it prepared for the FDA.” 

Based on the TFF Prescribed drugs web site, a vaccine’s effectiveness immediately pertains to its means to achieve the goal organ. As a result of this vaccine could be inhaled immediately into the lungs, the powder is extra simply absorbed. Williams mentioned the inhalation course of additionally reduces the chance of rejection from the lungs. 

“Attaining the aim of a broadly protecting influenza vaccine goes to take artistic approaches and folks from a number of disciplines combining forces,” Gordon wrote. “There may be numerous promise that we will considerably transfer the needle in bettering safety towards influenza.”

UT researchers developed a extra sustainable farming system that reduces fertilizer air pollution and creates increased crop yields. 

Present farming techniques rely closely on nitrogen fertilizers. In accordance with the research revealed on June 20, nitrogen waste from these fertilizers typically pollutes groundwater and contributes to the ozone layer’s depletion. The brand new methodology makes use of a copper-based hydrogel — which detects the quantity of nitrogen within the soil and turns it into fertilizer — to transform nitrogen air pollution into ammonia.

“This method we developed can recycle the nitrogen vitamins … utilizing the electrical energy to manage the focus of nitrogen species within the water,” lead creator Panpan Li stated. “This might help to cut back our use of conventional nitrogen fertilizers as a result of the overuse of these items may trigger some environmental issues.”

Li stated the tactic additionally helps vegetation improve their nutrient uptake and development. 

“This new system may additionally enhance the plant development by offering exact management of nitrogen contents and ratios by recycling the nitrogen with the waters from agricultural runoff to fertilize crops,” Li stated. 

The paper builds on earlier tasks by professor Guihua Yu’s staff, which researched hydrogel supplies designed for water conservation functions. Yu stated the analysis focus regularly shifted from water to applied sciences that stop nitrogen overuse, a main contributor to worsening soil.

“Land degradation can be one of many greatest issues for agriculture over a time period,” Yu stated. “Most of the lands will develop into degraded, so they might not have the ability to develop as a lot as earlier than. How you can successfully use fertilizer with the correct quantity — that was our subsequent focus past the water.”

Sooner or later, Yu want to scale up the system, initially meant to develop wheat and rice, to be used in a greater diversity of crops. He stated the system’s means to observe nitrogen ranges within the soil would work effectively with growing automated expertise.

“These could be pushed by the speedy development of AI and machine studying to have the ability to cowl our design idea, to have the ability to implement it to that greater scales,” Yu stated. “The subsequent step is to have the ability to work with completely different crops and in addition in additional built-in ranges past our easy demonstration of crops like rice and wheat.”

Li stated the researchers hope to proceed growing the system to combine it with renewable vitality sources and increase utilization.

“Sooner or later, the entire system may very well be powered by photo voltaic vitality,” Li stated. “I believe it’s greener and extra sustainable than the opposite methods.”

“The keys to the cupboard is on the desk.” Wait — that doesn’t sound correct. 

Synthetic intelligence like ChatGPT should develop social expertise and world information to keep away from errors human authors sometimes make, based on a paper launched by researchers from UT, the Massachusetts Institute of Expertise and the College of California Los Angeles.

Anna Ivanova, one of many paper’s co-authors, mentioned language is a software for people to share info and coordinate actions. She additionally mentioned language use requires a number of mind capabilities.

A postdoctoral neuroscience researcher at MIT, Ivanova mentioned formal linguistic expertise like understanding grammar guidelines are dealt with within the mind’s language community, whereas a spread of practical expertise that apply these guidelines happen all through the mind. Practical expertise embody social reasoning, formal reasoning and world information.

“Language has to interface with all of those different capacities, like social reasoning,” Ivanova mentioned. “Oftentimes, logical puzzles are offered linguistically, however then to truly determine what the logical relationships are, that’s a special type of ability.”

She mentioned builders prepare these massive language fashions on phrase prediction duties, which permits them to develop robust command over English grammar guidelines. Newer deep studying fashions like GPT-3 obtain human suggestions on their responses along with the large quantities of textual content they’re proven. 

“So the fashions find yourself being not simply good common language prediction machines, however type of specifically tuned into the type of duties folks need them to do,” mentioned Kyle Mahowald, a linguistics professor at UT. 

Ivanova mentioned builders of huge language fashions ought to separate the formal grammar and language expertise from the practical expertise to mannequin the modular format of human mind operate.

“Let’s deal with every (cognitive ability) individually,” Ivanova mentioned. “Let’s contemplate every of them as requiring its personal module and system for processing this sort of (practical) info.”

Contemplating the know-how’s present limitations, Ivanova mentioned “it’s a lot safer to make use of them for language than for issues that require cautious thought.” She mentioned customers can’t depend on the know-how for reasoning expertise simply but.

Journalism professor Robert Quigley mentioned he facilitates an experimental information web site utterly produced by synthetic intelligence. Quigley mentioned the web site options content material from massive language fashions like ChatGPT and employs comparable fashions like DALL-E 2 to generate article photographs.

Journalism senior Gracie Warhurst mentioned the Dallas Morning Information Innovation Endowment funds the experiment, known as The Future Press. Warhurst, a scholar researcher at The Future Press, mentioned her workforce seen the dearth of practical expertise within the fashions’ web site responses, very similar to Mahowald’s paper described.

“Clearly, AI doesn’t have essential considering skills,” Warhurst mentioned. “That’s the primary purpose why it’s not going to take folks’s jobs till it does develop (essential considering), which I don’t foresee taking place anytime quickly. A human journalist is utilizing their judgment each step of the way in which.”

Warhurst mentioned journalists and different content material creators ought to use AI to deal with busy work, comparable to enhancing drafts or writing quick briefs. She mentioned the challenge’s fashions hardly ever make grammatical errors, and their writing stays largely unbiased. Warhurst mentioned the most important downfall of AI in artistic industries is the dearth of human expertise.

“I learn a very good article within the New Yorker,” Warhurst mentioned. “(The creator) was speaking about residing in a border metropolis in Texas and his expertise rising up there. That’s not an article that you can get ChatGPT to jot down as a result of it doesn’t have Spanglish. It’s not a human. It’s a robotic.”