The different parts of a health care system have different focuses. A hospital's stroke （中风） unit monitors blood flow in the brain. The cardiac unit is interested in that same flow, but through and from the heart. Each collection of equipment and data is effective in its own field. Thus, like the story of blind men feeling an elephant, modern health care offers many separate pictures of a patient, but rarely a useful united one.

On top of all this, the instruments that doctors use to monitor health are often expensive, as is the training required to use them. That combined cost is too high for the medical system to scan regularly, for early signs of illness, so patients are at risk of heart disease or a stroke.

An unusual research project called AlzEye, run by Moorfields Eye Hospital in London, in cooperation with University College, London (UCL) , may change this. It is attempting to use the eye as a window through which signals about the health of other organs could be discovered. The doctors in charge of it, Siegfried Wagner and Pearse Keane, are studying Moorfields' database of eye scans, which offers a detailed picture of the health of the retina (视网膜).

The project will go a step further：With the information about other aspects of patients' health collected from other hospitals around England, doctors will be able to look for more accurate signs of disease through eye scans.

The Moorfields data set has lots of linked cases to work with--far more than any similar project. For instance, the UK Biobank, one of the world's leading collections of medical data about individual people, contains 631 cases of a "major cardiac adverse event". The Moorfields data contain about 12, 000 such. The Biobank has data on about 1, 500 stroke patients. Moorfields has 11, 900. For the disease on which the Moorfields project will focus to start with dementia, the data set holds 15, 100 cases. The only comparable study has 86.

Wagner and Keane are searching for patterns in the eye that show the emergence of disease elsewhere in the body. If such patterns could be recognized reliably, the potential impact would be huge.

The recent launch of ChatGPT, a chatbot created by Open AI for public use, has underlined the growing reach of digital technologies like artificial intelligence (AI) in working life. Like most technological revolutions that affect the workplace, chatbots can potentially create winners and losers and will affect both blue-collar and white-collar workers.

ChatGPT is a natural language processing (NLP) tool that allows users to interact with the GPT-3 model using natural language. The model is trained on a great amount of data, which allows it to generate human-like responses to a wide variety of inputs.

This type of AI can greatly benefit the productivity of skilled workers. Chatbots offer the possibility to automate(使自动化) boring and time-consuming tasks, such as writing standardized reports, meeting minutes and emails. Workers could therefore be freed to focus on more important and creative tasks. A chatbot virtual personal assistant could guide skilled workers through different projects or production processes. It can also generate original content and ideas, and potentially help to research and develop new products and services.

But tools such as ChatGPT present a real risk of skilled and semi-skilled workers losing their jobs. For example, chatbots can be developed to train employees in an organization, resulting in the unemployment of human trainers.

Previous waves of technological change have created both winners and losers. Workers who are quicker to adjust to technological change will win by increasingly taking on tasks complementary (互补的) to AI while giving up automated ones.

Social media are a powerful tool, and the go-green movement is becoming popular in the social media world. A new Facebook app is exercising this power to help people get back to work or even land their dream job — Hire My Friend.

With an unemployment rate of 9.7 percent in January 2010, there were nearly 15 million Americans out of work, of whom 6.3 million had been jobless for 27 or more weeks. It is likely that these people have used the most traditional methods to find a job. But now it's time to get creative, and Hire My Friend can help people do that.

However, as you can see, the name of the app is Hire My Friend, not Hire Me, so it is designed for you to help a friend get a job. One of the most important parts of getting a job is who you know. Reach out to your network of friends and you will find more opportunities than applying for a job in a newspaper advertisement. As a writer, I know that networking is the key to opening doors and getting new opportunities.

When you place the Hire My Friend app on your Facebook page, you can present your friend's job-related facts and then this information is shown through a live feed post (实时发布). Then your entire network of Facebook friends can see what your friend has to offer. In addition to the app itself, the Hire My Friend Facebook page has lots of useful resources for those who want to find a job. One tab (标签) has the latest jobs that are being posted on Twitter, another powerful social media tool. Another tab has a list of job searching blogs and major job search sites for the jobless. The developer of the app encourages people never to give up. If you know of someone who is out of work, I encourage you to try the Hire My Friend app.

Home to large numbers of elephants, India has some of the strictest elephant protection laws in Asia. Elephants have been granted (给予) the highest level of legal protection for wildlife. Strict bans exist on poaching (偷猎), and trading them, with heavy fines and prison sentences of up to seven years.

China had been making efforts to protect its small population of elephants since the 1980s. Local authorities in areas with elephants such as Xishuangbanna Dai Autonomous Prefecture in Yunnan Province, have not only made efforts to move human populations away from elephant habitats but have also worked with private insurance companies to insure farmers' crops against damage caused by the animals. According to one report, the population of elephants in China nearly doubled between the 1980s and 2021.

While both India and China have made efforts to protect the elephant and some success had been achieved, danger still appears as conservation laws are often either flouted (轻视) or not implemented. Strengthening domestic (国内的) laws is not enough. The animals now face the much more dangerous threat of climate change which calls for united action by these two leading economies.

There are many opportunities for cooperation between New Delhi and Beijing on elephant protection. These could potentially include: formation of a cooperative institute for research on elephant conservation; joint efforts on reforestation to ensure the expansion of buffer zones (缓冲区) between animal populations and human settlements; the training of local populations that live near elephant habitats and have traditional knowledge of harmonious living with elephants; formation of a joint resource fund for building care facilities and to achieve set targets to increase the population of elephants through careful breeding.

By doing so, India and China would promote economic growth through an ecological path and responsible ecotourism in not just the two nations but in Asia at large. Such joint efforts would also lead to better relations between the two countries.

Persephone is a tour guide in Greece, but not the type people are used to. As the world's first robot tour guide, Persephone has been welcoming visitors since mid-July to the Alistrati Cave (山洞) in northern Greece.

The robot covers the first 500 feet of the part of the cave. The robot can give its part of the tour in 33 languages and interact (互动) at a basic level with visitors in three languages. It can also answer 33 questions, but only in Greek.

Nikos Kartalis, the scientific director for the Alistrati site, had the idea of creating the robot when he saw one on TV guiding visitors at an art gallery. The robot was built by the National Technology and Research Foundation and cost ﹩139, 000.

"We already have a 70% increase in visitors compared to last year since we started using the robot," said Kartalis. "People are interested, especially the children, and people who had visited in the past are coming back to see the robot guide."

Persephone, with a white body, black head and two eyes, moves on wheels, guiding visitors to the first three of eight stops along the walkway. She can do two more stops, but her low speed slows down the tour. Persephone's creators are considering ways to speed her up. Evdokia Karafera is one of the tour guides who partners with the robot. "It is helpful, because it speaks many languages. There's just a little delay (耽搁) in the touring," she said. "Most find it amazing, especially the children, and find it interesting that it speaks many languages."

Karafera said, however, that human tour guides couldn't be completely replaced. "Robots, at some point in the future, will take over many jobs. But I believe they cannot replace humans everywhere," she said. "The robot is funny, but can't replace the human contact with the guide and the conversation we can have on the way back."

Imagine the busy streets of New York City, an enormous place with millions of people. Every day, the streets are crowded with people going about their daily lives. Now imagine a small robot in the middle of all of those people. Most people would not even notice the ten-inch smiling robot, called a Tweenbot, rolling along the busy sidewalk. This strange machine may interest some people, while others would ignore it completely. A researcher interested in studying how helpful people really are uses such robots in her experiments.

The Tweenbots experiment is the idea and creation of Kacie Kinzer, which was to make a robot that could navigate the city and reach its destination only if it was aided by pedestrians. Tweenbots rely on the kindness of warm-hearted strangers. Made simply of cardboard, wheels, and a device to turn the wheels, the Tweenbots face many dangers on the city streets. They could be run over by cars or smashed by careless kids. Each of Kinzer's robots is fitted with a flag that displays instructions for the robot's destination. The only way these robots will reach their final point is if someone lends them a hand. Tweenbots are essentially a social experiment aimed at providing people a chance to show how caring they are.

On a daily basis, people in New York City are often in a hurry to get around. However, the Tweenbots, through their inability to look after themselves, took people out of their normal routines. The people who noticed the helpless little robots were actually interested in helping the Tweenbots find their way home. Tweenbots move at a constant speed and can only go in a straight line. If one was to get stuck, or was going in the wrong direction, it would be up to strangers to free it or turn it in the right direction. Surprisingly, no Tweenbot was lost or damaged, and each one arrived at its target in good condition. In fact, most people treated the robot in a gentle manner, and some even treated it as though it were a small living being.

Scientists say they've developed a system using machine learning to predict when and where lighting will strike. The research was led by engineers from the Swiss Federal Institute of Technology in Lausanne, Switzerland.

European researchers have estimated that between 6,000 and 24,000 people are killed by lightning worldwide each year. The strikes can also cause power outages, destroy property, damage electrical equipment and start forest fires. For these reasons, climate scientists have long sought to develop methods to predict and control lightning. In the United States and other places, ground-based sensing devices are used to identify strikes as they happen. But, no system has been created to effectively predict lightning.

The system tested in the experiments used a combination of data from weather stations and machine learning methods. The researchers developed a prediction model that was trained to recognize weather conditions that were likely to cause lightning.

The model was created with data collected over a 12-year period from 12 Swiss weather stations in cities and mountain areas. The data related to four main surface conditions: air pressure, air temperature, relative humidity and wind speed.

The atmospheric, data was placed into a machine learning algorithm (算法), which compared it to records of lightning strikes. Researchers say the algorithm was then able to learn the conditions under which lightning happens.

Amirhossein Mostajabi is a PhD student at the institute who led the development of the method. He said, "current systems for gathering such data are slow and complex and require costly collection equipment like radar or satellites. "

"Our method uses data that can be obtained from any weather station," Mostajabi said. "This will improve data collection in very remote areas not covered by radar and satellite or in places where communication systems have been cut," he added.

Professor Ashok Goel of Georgia Tech developed an artificially intelligent teaching assistant to help handle the numerous questions from students in the online class. Professor Goel already had 8 teaching assistants, but that wasn't enough to deal with the huge number of questions from students.

Many students drop out of online courses for lack of teaching support. When students feel confused and reach out with questions that go unanswered, their motivation to continue begins to fade. Professor Goel decided to do something to change this situation by creating a virtual assistant named Jill Watson, which is based on the IBM Watson platform.

Goel and his team developed several versions of Jill Watson before releasing her to the online forums (论坛) . At first, the virtual assistant wasn't too great. But Goel and his team sourced the online discussion forum to find all 40, 000 questions that had ever been asked since the class started. Then they began to feed Jill with the questions and answers. After some adjustment, Jill was able to answer the students' questions correctly 97% of the time. The virtual assistant became so advanced and realistic that the students didn't know she was a computer. The students, who were studying artificial intelligence, were interacting with artificial intelligence and couldn't tell it apart from a real human being. Goel didn't inform them about Jill's true identity until April 26. The students were actually very positive about the experience.

The goal of Professor Goel's virtual assistant next year is to take over answering 40% of all questions raised by students. The name, Jill Watson will of course, change to something else next term. Professor Goel has a much rosier outlook on the future of Al than say, Elon Musk, Stephen Hawking, Bill Gates or Steve Wozniak.

The Mustard Seed Project is getting closer to one of its initiatives-building affordable senior housing on the Key Peninsula, Washington.

The Nonprofit carries out the project so that people don't have to leave the Key Peninsula as they age and have home care needs. "We hope to build in Key Center, a good, central location for our community. Our vision is to have a campus with a cafe and meeting spaces, 10 independent living cottages that have one or two bedrooms with laundry, housekeeping and one meal a day provided, and then assisted living for 30 residents," said board president Sara Thompson. "We want this to be a place that draws the entire community in, rather than a setting that sets elders aside in an isolated environment. "

More than a year ago, a longtime supporter of the organization made a major gift to undertake a long-desired study to understand both the needs of the community and the financial feasibility (可行性) for senior housing. As a result, The Mustard Seed Project had a meeting in November at the Key Peninsula Civic Center to explain the results of the study and to plan for the next steps.

"We'll be applying for a predevelopment loan to do all the necessary planning, "The Mustard Seed Project Executive Director Edie Morgan said. "We're aware of affordable loans for the assisted living section of the project, and can get standard financing for the other buildings. But there will be a funding gap, and we expect to need to raise nearly $3 million to make this happen. I believe we can do it."

The entire project, once the project manager is identified, is expected to take about two years.

Imagine a simple blood test that could flag most kinds of cancers at the earliest, most curable stage. Liquid biopsies could, in theory, detect a tumor (肿瘤) well before it could be found by touch, symptoms or imaging. Blood tests could avoid the need for surgeons to cut tissue samples and make it possible to reveal cancer hiding in places needles and scalpels cannot safely reach. They could also determine what type of cancer is taking root to help doctors decide what treatment might work best to destroy it.

Liquid biopsies are not yet in hand, because it is hard to find definitive cancer signals in a tube of blood, but progress in recent years has been impressive. Last year the journal Science published the first big prospective study of a liquid biopsy for DNA and proteins from multiple types of cancers. Though far from perfect, the blood test called CancerSEEK found 26 tumors that had not been discovered with conventional screenings.

Liquid biopsies can rely on a variety of biomarkers in addition to tumor DNA and proteins, such as free-floating cancer cells themselves. But what makes the search difficult, Ana Robles, a cancer biologist of the National Cancer Institute, explains, is that "if you have an early-stage cancer or certain types of cancer, there might not be a lot of tumor DNA," and tests might miss it. The ideal blood test will be both very specific and very sensitive so that even tiny tumors can be found. To tackle this challenge, CancerSEEK looks for cancer-specific mutations (突变) on 16 genes, and for eight proteins that are linked to cancer and for which there are highly sensitive tests.

Simple detection is not the only goal. An ideal liquid biopsy will also determine the likely location of the cancer so that it can be treated. "Mutations are often shared among different kinds of cancer, so if you find them in blood, you don't know if that mutation is coming from a stomach cancer or lung cancer," says Anirban Maitra, a cancer scientist at the Anderson Cancer Center. To solve that problem, some newer liquid biopsies look for changes in gene expression. Such changes, Maitra notes, are "more organ-specific".

On the nearer horizon are liquid biopsies to help people already diagnosed with cancer. Last year the government approved the first two such tests, which scan for tumor DNA so doctors can select mutation-targeted drugs. Scientists are working on blood tests to detect the first signs of cancer recurrence (复发) in patients who have completed treatment. This work is moving fast, but does it save lives?

That is the question companies such as Thrive and Grail must answer for their broadly ambitious screening tests. "These companies have to prove that they can detect early cancer and, more important, that the early detection can have an impact on cancer survival," Maitra observes.