Epidemiology Modeling an emerging infectious disease is an inexact science. At an early stage of an epidemic, we only have sparse data, little knowledge of the mechanisms driving emergence, and an urgent need to devise control measures that will be effective. Using epidemiological incidence reports, Brett and Rohani have developed a detection algorithm for disease (re)emergence that is agnostic to the mechanisms involved. This supervised statistical learning algorithm was trained on data collected for mumps outbreaks in England and resurgent pertussis in the United States. The algorithm successfully anticipated reemergence of mumps 4 years in advance, which would have given plenty of time for mitigation efforts to be implemented. The algorithm also performed well for vector-borne diseases, including dengue in Puerto Rico, and predicted the rapid emergence of plague in Madagascar. The success of this approach stems from the common statistical properties of incidence data across disease emergence contexts and has obvious application for monitoring waves of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reemergence. PLOS BIOL. 18 , e3000697 (2020).
A longheld theory that animals raised in captivity perform better in cognitive testing may need to be rethought. A new study organized by the University of Veterinary Medicine in Vienna found evidence that wild animals perform just as well at intelligence tests as their lab-raised counterparts. To test the theory, researchers compared two groups of Goffin's cockatoos, a species often found in the tropical jungles of Singapore, Indonesia, and Puerto Rico. The team compared a lab-raised'colony' of 11 cockatoos at their lab in Vienna to eight wild cockatoos recently taken into captivity at a field laboratory in Indonesia. The researchers compared the performance of both groups in a series of simple problem solving tests and found the wild cockatoos were just as clever as the lab-raised ones.
China's Xiongan New Area project, near Beijing, is part of the central government's ambitious drive to lead in new technologies like AI and 5G communication. Woven City, near Japan's Mount Fuji, is a much smaller project -- just 175 acres -- that is being led not by the government, but by one of its leading industrial giants, Toyota Motor Corp. If the U.S. were to build a similar prototype city, it would need to invest or direct billions of dollars in advanced technologies like 5G, vehicle-to-vehicle communication, electric charging infrastructure and vehicle automation in an area with a high population density. My thought bubble: Why not San Juan, Puerto Rico? Yes, but: Puerto Rican residents have to want to be test subjects, notes Michelle Avary, head of autonomous mobility at the World Economic Forum.
Mitch Aide, a tropical ecologist based in Puerto Rico, thinks we should listen to the earth a lot more than we do now -- and not just listen to it, but record and store its sounds on a massive scale. His aims are not spiritual, but scientific: He, his colleagues, and other experts are developing and deploying audio recorders, data transmission systems, and new artificial intelligence software that together are rapidly expanding scientists' ability to understand ecosystems by listening to them. Today, Aide can nail a cheap digital audio recorder to a tree in Puerto Rico's Luquillo Forest and transmit its recordings to a computer running prototype software, which indicates almost in real time whether any of 25 species of frogs and birds are vocalizing in the forest. The system's apparent simplicity belies its power – Aide thinks that it and similar systems will allow scientists to monitor ecosystems in ways we can't yet imagine. He dreams that one day soon, audio recordings of natural soundscapes will be like rainfall and temperature data, collected from a worldwide network of permanent stations, widely available for analysis, and permanently archived.
A new study by Ducker Frontier revealed that Puerto Rico could create between 26 and 34 percent additional jobs with the successful implementation of artificial intelligence (AI) in the public and private sectors. On Nov. 5, during the second annual Microsoft AI Tour held at the Sheraton Hotel and Casino in San Juan's Convention District, Pablo González, director of Ducker Frontier Latin America, discussed with THE WEEKLY JOURNAL the entity's most recent analysis of Puerto Rico's advancement in adopting AI and other emerging technologies. AI, as defined by Microsoft Caribbean General Manager Herbert Lewy, is an amplification of human ingenuity, "a tool that allows humans to achieve more and improve the things we normally do." The continuous progress of this booming technology has prompted a myriad of concerns and dystopian scenarios regarding automation, such as computers rendering humans obsolete at a plethora of jobs and services, thus amplifying economic disparity. "People think that if an algorithm can do 30 percent of our tasks they will get fired from their jobs. The study intends to demystify this perception and shed light on some issues… We also wanted to measure something that is almost never measured, which is the creation of new industries and, therefore, jobs that do not exist today to reach a net effect of how it will affect job availability in Puerto Rico," González explained.
An open-source disaster response tool that uses visual recognition and learns through artificial intelligence and cloud tools began as an idea that a self-taught developer had at IBM's Call for Code hackathon in Puerto Rico last year. IBM announced DroneAid on Oct. 2 as an open-source project through Code and Response, the company's $25 million program dedicated to the creation and deployment of open-source solutions tackling real-world problems. DroneAid uses visual recognition technology to detect and count SOS icons on the ground gleaned from drone video streams and automatically plots the emergency needs on a map for first responders. Developer Pedro Cruz had planned to use optical character recognition to detect messages, but reading different handwriting and languages complicated that approach. Instead, the tool relies on a subset of the U.N. Office for the Coordination of Humanitarian Affairs' 500 humanitarian icons – symbols that DroneAid can learn and first responders can quickly understand.
Pedro Cruz didn't just live through the wreckage that Hurricane Maria left in its path in Puerto Rico back in 2017. He watched the commotion in his hometown of San Juan by flying his drone overhead. Maria made landfall on the southeast part of the island around 8 p.m., Cruz recalls in an interview with Popular Mechanics. Once the storm subsided about 20 hours later, he began his mission to find his grandmother. Since the infrastructure was completely decimated, he had no cell phone service to check in on her.
When the Arecibo message was sent into space in 1974 – blasting the most powerful signal ever broadcast deep into the universe – it was a pioneering attempt to reach out to aliens, wherever they might be. When a response came back in 2001, it was a hoax that showed just how much some people hope we can actually communicate with extraterrestrials. But that fake reply might actually be the message we ever get back from aliens. That's because some of the greatest minds on Earth fear rather than hope for contact with extraterrestrial life. Because the real reply to the Arecibo message might actually be something far more terrifying.
Work by AI for Earth researchers at Columbia University sheds even more light on why accurate, detailed, and up-to-date information is important. Dr Maria Uriarte, an ecologist, and Dr Tian Zheng, a statistician, have been studying the impact of extreme weather on forests and their regrowth patterns, with an eye towards the impact this has on carbon sequestration abilities – shorter, younger and less dense forests are less effective than older, denser areas. She recently took a team to Puerto Rico to assess the damage to the forests following Hurricane Maria. Uriarte and Zheng, both affiliated with the Data Science Institute at Columbia, will eventually use the collected data, with the remote-sensing images and measurements, to come up with a detailed estimate of the loss from the storm. Without current baseline data and a forward-leaning view of what the forest inventory may be in the future, planners may undervalue forests, or countries may over-value sequestration abilities.