Questões de Vestibular Sobre inglês
Foram encontradas 5.903 questões
Q1302735
Inglês
Texto associado
Leia o texto a seguir para responder à questão.
The true potential of technology to change behavior
Technology could successfully change behaviours where decades of campaigns and legislation have failed.
With the quantified self already walking among us and the internet of things within easy reach, digital technology
is creating unprecedented opportunities to encourage, enable and empower more sustainable behaviours.
If we are to unlock the power of technology we must be more ambitious than simply digitising analogue
strategies or creating another communications channel.
The true potential of technology lies in its ability to do things that nothing else can do. In behaviour change
terms, the potential to succeed where decades of education programmes, awareness campaigns and product
innovation have failed; to make a difference where government policy and legislation has had limited impact.
Using behavioural insights, it is possible to highlight the bottlenecks, drop out points and achilles heels of
traditional behaviour change efforts — the reasons why we have failed in the past — and apply the unique
possibilities of technology to these specific challenges.
Overcoming our limitations
Luckily, the history of the human race is almost defined by its ability to invent stuff that bolsters its feeble
capabilities. That stuff is, of course, what we generically refer to as 'technology'. And in the same way that the
internal combustion engine and the light bulb allow us to overcome our relatively feeble powers of motion and
perception, so digital technology can be directed to overcoming our relatively feeble powers of reasoning, selfcontrol, motivation, self-awareness and agency—the factors that make behaviour change so difficult.
Herein lies the true potential of technology: not in the laboratory or the workshop, but in an understanding of
the behavioural dynamics that define the human condition, both generally and within the context of a specific
user-group, market segment or community.
Fonte: JOHNSON, Steven. Recognising the true potential of technology to change behaviour. Disponível em: . Acesso em: 23 ago. 2017. (Adaptado).
Analisando-se aspectos linguísticos e estruturais do texto, constata-se que
Q1302734
Inglês
Texto associado
Leia o texto a seguir para responder à questão.
The true potential of technology to change behavior
Technology could successfully change behaviours where decades of campaigns and legislation have failed.
With the quantified self already walking among us and the internet of things within easy reach, digital technology
is creating unprecedented opportunities to encourage, enable and empower more sustainable behaviours.
If we are to unlock the power of technology we must be more ambitious than simply digitising analogue
strategies or creating another communications channel.
The true potential of technology lies in its ability to do things that nothing else can do. In behaviour change
terms, the potential to succeed where decades of education programmes, awareness campaigns and product
innovation have failed; to make a difference where government policy and legislation has had limited impact.
Using behavioural insights, it is possible to highlight the bottlenecks, drop out points and achilles heels of
traditional behaviour change efforts — the reasons why we have failed in the past — and apply the unique
possibilities of technology to these specific challenges.
Overcoming our limitations
Luckily, the history of the human race is almost defined by its ability to invent stuff that bolsters its feeble
capabilities. That stuff is, of course, what we generically refer to as 'technology'. And in the same way that the
internal combustion engine and the light bulb allow us to overcome our relatively feeble powers of motion and
perception, so digital technology can be directed to overcoming our relatively feeble powers of reasoning, selfcontrol, motivation, self-awareness and agency—the factors that make behaviour change so difficult.
Herein lies the true potential of technology: not in the laboratory or the workshop, but in an understanding of
the behavioural dynamics that define the human condition, both generally and within the context of a specific
user-group, market segment or community.
Fonte: JOHNSON, Steven. Recognising the true potential of technology to change behaviour. Disponível em: . Acesso em: 23 ago. 2017. (Adaptado).
Considering the ideas expressed in the text, technology
Q1302685
Inglês
Texto associado
Disponível em: <http://www.bosch-presse.de/pressportal/de/en/see-boschs-contribution-to-industry-4-0-42895.html>. Acesso em: 23 fev. 2018. (Adaptado)
Observe o infográfico a seguir e responda a questão.
Disponível em: <http://www.bosch-presse.de/pressportal/de/en/see-boschs-contribution-to-industry-4-0-42895.html>. Acesso em: 23 fev. 2018. (Adaptado)
Em termos de sentido, verifica se que
Q1302684
Inglês
Texto associado
Disponível em: <http://www.bosch-presse.de/pressportal/de/en/see-boschs-contribution-to-industry-4-0-42895.html>. Acesso em: 23 fev. 2018. (Adaptado)
Observe o infográfico a seguir e responda a questão.
Disponível em: <http://www.bosch-presse.de/pressportal/de/en/see-boschs-contribution-to-industry-4-0-42895.html>. Acesso em: 23 fev. 2018. (Adaptado)
According to the information expressed in the image and data, the industrial revolution
Q1302683
Inglês
Texto associado
Leia o texto a seguir para responder à questão.
Who's driving? Autonomous cars may be entering the most dangerous phase
Autopilot controls are not yet fully capable of functioning without human intervention – but they’re good
enough to lull us into a false sense of security.
When California police officers approached a Tesla stopped in the centre of a five-lane highway outside San Francisco last week, they found a man asleep at the wheel. The driver, who was arrested on suspicion of drunk driving, told them his car was in “autopilot”, Tesla’s semi-autonomous driver assist system.
In a separate incident, firefighters in Culver City reported that a Tesla vehicle parked at the rear of their fire truck as it attended an accident on the freeway. Again, the driver said the vehicle was in autopilot.
When California police officers approached a Tesla stopped in the centre of a five-lane highway outside San Francisco last week, they found a man asleep at the wheel. The driver, who was arrested on suspicion of drunk driving, told them his car was in “autopilot”, Tesla’s semi-autonomous driver assist system.
In a separate incident, firefighters in Culver City reported that a Tesla vehicle parked at the rear of their fire truck as it attended an accident on the freeway. Again, the driver said the vehicle was in autopilot.
The oft-repeated promise of driverless technology is that it will make the roads safer by reducing human
error, the primary cause of accidents. However, those vehicles have a long way to go before they can eliminate
the drivers.
However, research has shown that drivers get lulled into a false sense of security to the point where their
minds and gazes start to wander away from the road. People become distracted or preoccupied with their
smartphones. So when the car encounters a situation where the human needs to intervene, the driver can be slow
to react.
During tests the IIHS recorded a Mercedes having problems when the lane on the highway forked in two.
The radar system locked onto the right-hand exit lane when the driver was trying to go straight.
Concern over this new type of distracted driving is forcing engineers to introduce additional safety features
to compensate. For example, GM has introduced eye-tracking technology to check the driver’s eyes are on the
road while Tesla drivers can be locked out of autopilot if they ignore warnings to keep their hands on the steering
wheel.
In spite of these problems, Tesla’s CEO, Elon Musk, remains bullish about his company’s autonomous
technology, even suggesting that by 2019 drivers would be able to sleep in their cars – presumably without being
arrested by highway patrol officers.
Disponível em: <https://www.theguardian.com/technology/2018/jan/24/self-driving-cars-dangerous-period-false-security>. Acesso em: 23 fev. 2018. (Adaptado).
Analisando-se aspectos linguísticos e estruturais do texto, constata-se que
Q1302682
Inglês
Texto associado
Leia o texto a seguir para responder à questão.
Who's driving? Autonomous cars may be entering the most dangerous phase
Autopilot controls are not yet fully capable of functioning without human intervention – but they’re good
enough to lull us into a false sense of security.
When California police officers approached a Tesla stopped in the centre of a five-lane highway outside San Francisco last week, they found a man asleep at the wheel. The driver, who was arrested on suspicion of drunk driving, told them his car was in “autopilot”, Tesla’s semi-autonomous driver assist system.
In a separate incident, firefighters in Culver City reported that a Tesla vehicle parked at the rear of their fire truck as it attended an accident on the freeway. Again, the driver said the vehicle was in autopilot.
When California police officers approached a Tesla stopped in the centre of a five-lane highway outside San Francisco last week, they found a man asleep at the wheel. The driver, who was arrested on suspicion of drunk driving, told them his car was in “autopilot”, Tesla’s semi-autonomous driver assist system.
In a separate incident, firefighters in Culver City reported that a Tesla vehicle parked at the rear of their fire truck as it attended an accident on the freeway. Again, the driver said the vehicle was in autopilot.
The oft-repeated promise of driverless technology is that it will make the roads safer by reducing human
error, the primary cause of accidents. However, those vehicles have a long way to go before they can eliminate
the drivers.
However, research has shown that drivers get lulled into a false sense of security to the point where their
minds and gazes start to wander away from the road. People become distracted or preoccupied with their
smartphones. So when the car encounters a situation where the human needs to intervene, the driver can be slow
to react.
During tests the IIHS recorded a Mercedes having problems when the lane on the highway forked in two.
The radar system locked onto the right-hand exit lane when the driver was trying to go straight.
Concern over this new type of distracted driving is forcing engineers to introduce additional safety features
to compensate. For example, GM has introduced eye-tracking technology to check the driver’s eyes are on the
road while Tesla drivers can be locked out of autopilot if they ignore warnings to keep their hands on the steering
wheel.
In spite of these problems, Tesla’s CEO, Elon Musk, remains bullish about his company’s autonomous
technology, even suggesting that by 2019 drivers would be able to sleep in their cars – presumably without being
arrested by highway patrol officers.
Disponível em: <https://www.theguardian.com/technology/2018/jan/24/self-driving-cars-dangerous-period-false-security>. Acesso em: 23 fev. 2018. (Adaptado).
Considering to the information expressed in the text, autonomous cars
Q1302503
Inglês
Observe o infográfico a seguir para responder à questão.
Disponível em: <https://issuu.com/finnair_bluewings/docs/bluewings_01_2018/98>. Acesso em: 07 jun. 2018.
According to the information expressed in the image and data
Disponível em: <https://issuu.com/finnair_bluewings/docs/bluewings_01_2018/98>. Acesso em: 07 jun. 2018.
According to the information expressed in the image and data
Q1302502
Inglês
Texto associado
Leia o texto e responda à questão.
Lawyers could be the next profession to be replaced by computers
Technology is often blamed for destroying traditional working-class jobs in sectors like manufacturing and
retail. But blue collar jobs aren't the only ones at risk on an imminent future: white collar jobs are going to be
affected by technology as well.
The legal profession is on the cusp of a transformation in which artificial-intelligence (AI) platforms might
dramatically affect how legal work gets done. Those platforms will mine documents for evidence that will be useful
in litigation, to review and create contracts, raise red flags within companies to identify potential fraud and other
misconduct or do legal research and perform due diligence before corporate acquisitions. Those are all tasks that
— for the moment at least — are largely the responsibility of flesh-and-blood attorneys.
Increasing automation of the legal industry promises to increase efficiency and save client’s money, but
could also cut jobs in the sector as the technology becomes responsible for tasks currently performed by humans.
Advocates of AI, however, argue there could actually be an increase in the sector's labor force as the
technology drives costs down and makes legal services more affordable to greater numbers of people. It's like the
beginning for a future changing in legal profession with AI-powered platform which can perform almost all
mechanical work such as creating a new contract or reviewing it for clients and companies.
What machines do better than people
One question raised by the introduction of AI legal platforms is how well they do their jobs compared to a
flesh-and-blood lawyer, who has years of experience under his belt. Supporters of this new technology defend
that AI platform can search documents for relevant information to lawsuits and other litigation as well as
experienced lawyers. Here are some of AI advantages:
Keywords: human beings are not very good at keyword searches. There's a fallacy that human beings looking at documents is the gold standard which cannot be, because human may miss things.
Database: the explosion in the amount of electronic data generated today makes it hard for human workers to keep up. This so much more data nowadays need these technologies find relevant material for lawyers. Also the AI could not just look at the text of a document or email, it can look at the tone of the conversation, who sent it, to check if the item should be flagged for review in litigation.
Restless: computers don't get tired, they don't get hungry, they don't sleep in and all of the things that are biological problems that can happen to a human being can't happen to computers.
An example of this technology is ROSS - it is a legal research platform based on IBM's cognitive computing system Watson. This technology is being used by a number of law firms, which state that the legal sector has being changing along the years. Firms, particularly larger ones, begin to see the advantage of AI, and their legal future possibly will completely change, with lawyers working from office, home office and other possibilities.
Acesso em: 08 maio 2018. (Adaptado)
Keywords: human beings are not very good at keyword searches. There's a fallacy that human beings looking at documents is the gold standard which cannot be, because human may miss things.
Database: the explosion in the amount of electronic data generated today makes it hard for human workers to keep up. This so much more data nowadays need these technologies find relevant material for lawyers. Also the AI could not just look at the text of a document or email, it can look at the tone of the conversation, who sent it, to check if the item should be flagged for review in litigation.
Restless: computers don't get tired, they don't get hungry, they don't sleep in and all of the things that are biological problems that can happen to a human being can't happen to computers.
An example of this technology is ROSS - it is a legal research platform based on IBM's cognitive computing system Watson. This technology is being used by a number of law firms, which state that the legal sector has being changing along the years. Firms, particularly larger ones, begin to see the advantage of AI, and their legal future possibly will completely change, with lawyers working from office, home office and other possibilities.
Disponível em: <https://www.cnbc.com/2017/02/17/lawyers-could-be-replaced-by-artificial-intelligence.html>
Analisando-se aspectos linguísticos e estruturais do texto, constata-se que
Q1302501
Inglês
Texto associado
Leia o texto e responda à questão.
Lawyers could be the next profession to be replaced by computers
Technology is often blamed for destroying traditional working-class jobs in sectors like manufacturing and
retail. But blue collar jobs aren't the only ones at risk on an imminent future: white collar jobs are going to be
affected by technology as well.
The legal profession is on the cusp of a transformation in which artificial-intelligence (AI) platforms might
dramatically affect how legal work gets done. Those platforms will mine documents for evidence that will be useful
in litigation, to review and create contracts, raise red flags within companies to identify potential fraud and other
misconduct or do legal research and perform due diligence before corporate acquisitions. Those are all tasks that
— for the moment at least — are largely the responsibility of flesh-and-blood attorneys.
Increasing automation of the legal industry promises to increase efficiency and save client’s money, but
could also cut jobs in the sector as the technology becomes responsible for tasks currently performed by humans.
Advocates of AI, however, argue there could actually be an increase in the sector's labor force as the
technology drives costs down and makes legal services more affordable to greater numbers of people. It's like the
beginning for a future changing in legal profession with AI-powered platform which can perform almost all
mechanical work such as creating a new contract or reviewing it for clients and companies.
What machines do better than people
One question raised by the introduction of AI legal platforms is how well they do their jobs compared to a
flesh-and-blood lawyer, who has years of experience under his belt. Supporters of this new technology defend
that AI platform can search documents for relevant information to lawsuits and other litigation as well as
experienced lawyers. Here are some of AI advantages:
Keywords: human beings are not very good at keyword searches. There's a fallacy that human beings looking at documents is the gold standard which cannot be, because human may miss things.
Database: the explosion in the amount of electronic data generated today makes it hard for human workers to keep up. This so much more data nowadays need these technologies find relevant material for lawyers. Also the AI could not just look at the text of a document or email, it can look at the tone of the conversation, who sent it, to check if the item should be flagged for review in litigation.
Restless: computers don't get tired, they don't get hungry, they don't sleep in and all of the things that are biological problems that can happen to a human being can't happen to computers.
An example of this technology is ROSS - it is a legal research platform based on IBM's cognitive computing system Watson. This technology is being used by a number of law firms, which state that the legal sector has being changing along the years. Firms, particularly larger ones, begin to see the advantage of AI, and their legal future possibly will completely change, with lawyers working from office, home office and other possibilities.
Acesso em: 08 maio 2018. (Adaptado)
Keywords: human beings are not very good at keyword searches. There's a fallacy that human beings looking at documents is the gold standard which cannot be, because human may miss things.
Database: the explosion in the amount of electronic data generated today makes it hard for human workers to keep up. This so much more data nowadays need these technologies find relevant material for lawyers. Also the AI could not just look at the text of a document or email, it can look at the tone of the conversation, who sent it, to check if the item should be flagged for review in litigation.
Restless: computers don't get tired, they don't get hungry, they don't sleep in and all of the things that are biological problems that can happen to a human being can't happen to computers.
An example of this technology is ROSS - it is a legal research platform based on IBM's cognitive computing system Watson. This technology is being used by a number of law firms, which state that the legal sector has being changing along the years. Firms, particularly larger ones, begin to see the advantage of AI, and their legal future possibly will completely change, with lawyers working from office, home office and other possibilities.
Disponível em: <https://www.cnbc.com/2017/02/17/lawyers-could-be-replaced-by-artificial-intelligence.html>
Em termos de sentido, verifica-se que a expressão
Q1302500
Inglês
Texto associado
Leia o texto e responda à questão.
Lawyers could be the next profession to be replaced by computers
Technology is often blamed for destroying traditional working-class jobs in sectors like manufacturing and
retail. But blue collar jobs aren't the only ones at risk on an imminent future: white collar jobs are going to be
affected by technology as well.
The legal profession is on the cusp of a transformation in which artificial-intelligence (AI) platforms might
dramatically affect how legal work gets done. Those platforms will mine documents for evidence that will be useful
in litigation, to review and create contracts, raise red flags within companies to identify potential fraud and other
misconduct or do legal research and perform due diligence before corporate acquisitions. Those are all tasks that
— for the moment at least — are largely the responsibility of flesh-and-blood attorneys.
Increasing automation of the legal industry promises to increase efficiency and save client’s money, but
could also cut jobs in the sector as the technology becomes responsible for tasks currently performed by humans.
Advocates of AI, however, argue there could actually be an increase in the sector's labor force as the
technology drives costs down and makes legal services more affordable to greater numbers of people. It's like the
beginning for a future changing in legal profession with AI-powered platform which can perform almost all
mechanical work such as creating a new contract or reviewing it for clients and companies.
What machines do better than people
One question raised by the introduction of AI legal platforms is how well they do their jobs compared to a
flesh-and-blood lawyer, who has years of experience under his belt. Supporters of this new technology defend
that AI platform can search documents for relevant information to lawsuits and other litigation as well as
experienced lawyers. Here are some of AI advantages:
Keywords: human beings are not very good at keyword searches. There's a fallacy that human beings looking at documents is the gold standard which cannot be, because human may miss things.
Database: the explosion in the amount of electronic data generated today makes it hard for human workers to keep up. This so much more data nowadays need these technologies find relevant material for lawyers. Also the AI could not just look at the text of a document or email, it can look at the tone of the conversation, who sent it, to check if the item should be flagged for review in litigation.
Restless: computers don't get tired, they don't get hungry, they don't sleep in and all of the things that are biological problems that can happen to a human being can't happen to computers.
An example of this technology is ROSS - it is a legal research platform based on IBM's cognitive computing system Watson. This technology is being used by a number of law firms, which state that the legal sector has being changing along the years. Firms, particularly larger ones, begin to see the advantage of AI, and their legal future possibly will completely change, with lawyers working from office, home office and other possibilities.
Acesso em: 08 maio 2018. (Adaptado)
Keywords: human beings are not very good at keyword searches. There's a fallacy that human beings looking at documents is the gold standard which cannot be, because human may miss things.
Database: the explosion in the amount of electronic data generated today makes it hard for human workers to keep up. This so much more data nowadays need these technologies find relevant material for lawyers. Also the AI could not just look at the text of a document or email, it can look at the tone of the conversation, who sent it, to check if the item should be flagged for review in litigation.
Restless: computers don't get tired, they don't get hungry, they don't sleep in and all of the things that are biological problems that can happen to a human being can't happen to computers.
An example of this technology is ROSS - it is a legal research platform based on IBM's cognitive computing system Watson. This technology is being used by a number of law firms, which state that the legal sector has being changing along the years. Firms, particularly larger ones, begin to see the advantage of AI, and their legal future possibly will completely change, with lawyers working from office, home office and other possibilities.
Disponível em: <https://www.cnbc.com/2017/02/17/lawyers-could-be-replaced-by-artificial-intelligence.html>
According to the text, we verify that
Ano: 2018
Banca:
UEG
Órgão:
UEG
Prova:
UEG - 2018 - UEG - Vestibular - Língua Inglesa (a Distância) |
Q1302303
Inglês
Observe o infográfico a seguir para responder à questão.
Disponível em: <https://www.paradigmsports.ca/a-healthy-mind-in-a-healthy-body/>. Acesso em: 09 out. 2018.
According to the information expressed in the image and data, when kids are physically active, we verify that
Disponível em: <https://www.paradigmsports.ca/a-healthy-mind-in-a-healthy-body/>. Acesso em: 09 out. 2018.
According to the information expressed in the image and data, when kids are physically active, we verify that
Ano: 2018
Banca:
UEG
Órgão:
UEG
Prova:
UEG - 2018 - UEG - Vestibular - Língua Inglesa (a Distância) |
Q1302302
Inglês
Texto associado
Leia o texto a seguir para responder à questão.
Global warming is intensifying El Niño weather
As humans put more and more heat-trapping gases into the atmosphere, the Earth warms. And the
warming is causing changes that might surprise us. Not only is the warming causing long-term trends in heat, sea
level rise, ice loss, etc.; it’s also making our weather more variable. It’s making otherwise natural cycles of
weather more powerful.
Perhaps the most important natural fluctuation in the Earth’s climate is the El Niño process. El Niño refers
to a short-term period of warm ocean surface temperatures in the tropical Pacific, basically stretching from South
America towards Australia. When an El Niño happens, that region is warmer than usual. If the counterpart La Niña
occurs, the region is colder than usual. Often times, neither an El Niño or La Niña is present and the waters are a
normal temperature. This would be called a “neutral” state.
The ocean waters switch back and forth between El Niño and La Niña every few years. Not regularly, like
a pendulum, but there is a pattern of oscillation. And regardless of which part of the cycle we are in (El Niño or La
Niña), there are consequences for weather around the world. For instance, during an El Niño, we typically see
cooler and wetter weather in the southern United States while it is hotter and drier in South America and Australia.
It’s really important to be able to predict El Niño/La Niña cycles in advance. It’s also important to be able
to understand how these cycles will change in a warming planet.
El Niño cycles have been known for a long time. Their influence around the world has also been known
for almost 100 years. Having observed the effects of El Niño for a century, scientists had the perspective to
understand something might be changing.
The relationship between regional climate and the El Niño/La Niña status in climate model simulations of
the past and future. It was found an intensification of El Niño/La Niña impacts in a warmer climate, especially for
land regions in North America and Australia. Changes between El Niño/La Niña in other areas, like South
America, were less clear. The intensification of weather was more prevalent over land regions.
And this conclusion can be extended to many other situations around the planet. Human pollution is
making our Earth’s natural weather switch more strongly from one extreme to another. It’s a weather whiplash that
will continue to get worse as we add pollution to the atmosphere.
Fortunately, every other country on the planet (with the exception of the US leadership) understands that
climate change is an important issue and those countries are taking action. It isn’t too late to change our trajectory
toward a better future for all of us. But the time is running out. The Earth is giving us a little nudge by showing us,
via today’s intense weather, what tomorrow will be like if we don’t take action quickly.
Disponível em: <https://www.theguardian.com/environment/climate-consensus-97-per-cent/2018/aug/29/global-warming-is-intensifying-el-nino-weather>. Acesso
em: 19 set. 2018. (Adaptado).
De acordo com o texto, em termos de sentido, verifica-se que
Q1301486
Inglês
Texto associado
Leia o texto a seguir para responder à questão.
Global warming is intensifying El Niño weather
As humans put more and more heat-trapping gases into the atmosphere, the Earth warms. And the warming is causing changes that might surprise us. Not only is the warming causing long-term trends in heat, sea level rise, ice loss, etc.; it’s also making our weather more variable. It’s making otherwise natural cycles of weather more powerful.
Perhaps the most important natural fluctuation in the Earth’s climate is the El Niño process. El Niño refers to a short-term period of warm ocean surface temperatures in the tropical Pacific, basically stretching from South America towards Australia. When an El Niño happens, that region is warmer than usual. If the counterpart La Niña occurs, the region is colder than usual. Often times, neither an El Niño or La Niña is present and the waters are a normal temperature. This would be called a “neutral” state.
The ocean waters switch back and forth between El Niño and La Niña every few years. Not regularly, like a pendulum, but there is a pattern of oscillation. And regardless of which part of the cycle we are in (El Niño or La Niña), there are consequences for weather around the world. For instance, during an El Niño, we typically see cooler and wetter weather in the southern United States while it is hotter and drier in South America and Australia.
It’s really important to be able to predict El Niño/La Niña cycles in advance. It’s also important to be able to understand how these cycles will change in a warming planet.
El Niño cycles have been known for a long time. Their influence around the world has also been known for almost 100 years. Having observed the effects of El Niño for a century, scientists had the perspective to understand something might be changing.
The relationship between regional climate and the El Niño/La Niña status in climate model simulations of the past and future. It was found an intensification of El Niño/La Niña impacts in a warmer climate, especially for land regions in North America and Australia. Changes between El Niño/La Niña in other areas, like South America, were less clear. The intensification of weather was more prevalent over land regions.
And this conclusion can be extended to many other situations around the planet. Human pollution is making our Earth’s natural weather switch more strongly from one extreme to another. It’s a weather whiplash that will continue to get worse as we add pollution to the atmosphere.
Fortunately, every other country on the planet (with the exception of the US leadership) understands that climate change is an important issue and those countries are taking action. It isn’t too late to change our trajectory toward a better future for all of us. But the time is running out. The Earth is giving us a little nudge by showing us, via today’s intense weather, what tomorrow will be like if we don’t take action quickly.
Disponível em: <https://www.theguardian.com/environment/climate-consensus-97-per-cent/2018/aug/29/global-warming-is-intensifying-el-nino-weather>. Acesso em: 19 set. 2018. (Adaptado).
Analisando-se aspectos linguísticos da língua inglesa, presentes no texto, constata-se que
Q1300894
Inglês
Texto associado
Disponível em: https://www.who.int/mediacentre/events/2015/world-antibiotic-awareness-week/infographics/en/. Acesso em: 02 maio 2019.
Considerando-se os elementos de escritura e forma da língua inglesa, constata-se que
Q1300893
Inglês
Texto associado
Disponível em: https://www.who.int/mediacentre/events/2015/world-antibiotic-awareness-week/infographics/en/. Acesso em: 02 maio 2019.
Considering the linguistics aspects presented in the infographic, we verify that
Q1300892
Inglês
Texto associado
Leia o texto a seguir para responder à questão.
Artificial intelligence and the future of medicine
Washington University researchers are working to develop artificial intelligence (AI) systems for health care, which
have the potential to transform the diagnosis and treatment of diseases, helping to ensure that patients get the
right treatment at the right time.
In health care, artificial intelligence relies on the power of computers to sift through and make sense of reams of
electronic data about patients—such as their ages, medical histories, health status, test results, medical images,
DNA sequences, and many other sources of health information. AI excels at the complex identification of patterns
in these reams of data, and it can do this at a scale and speed beyond human capacity. The hope is that this
technology can be harnessed to help doctors and patients make better health-care decisions.
Where are the first places we will start to see AI entering medical practice?
One of the first applications of AI in patient care that we currently see is in imaging, to help improve the diagnosis
of cancer or heart problems, for example. There are many types of imaging tests —X-rays, CT scans, MRIs and
echocardiograms. But the underlying commonality in all those imaging methods is huge amounts of high-quality
data. For AI to work well, it's best to have very complete data sets—no missing numbers, so to speak—and digital
images provide that. Plus, the human eye is often blind to some of the patterns that could be present in these
images—subtle changes in breast tissue over several years of mammograms, for example. There has been some
interesting work done in recognizing early patterns of cancer or early patterns of heart failure that even a highly
trained physician would not see.
In many ways, we already have very simple forms of AI in the clinic now. We've had tools for a long time that
identify abnormal rhythms in an EKG, for example. An abnormal heartbeat pattern triggers an alert to draw a
clinician's attention. This is a computer trying to replicate a human being understanding that data and saying,
"This doesn't look normal, you may need to address this problem." Now, we have the capacity to analyze much
larger and more complex sources of data, such as the entire electronic health record and perhaps even data
pulled from daily life, as more people track their sleep patterns or pulse rates with wearable devices, for example.
What effect will this have on how doctors practice medicine?
It's important to emphasize that these tools are never going to replace clinicians. These technologies will provide
assistance, helping care providers see important signals in massive amounts of data that would otherwise remain
hidden. But at the same time, there are levels of understanding that computers still can't and may never replicate.
To take a treatment recommendation from an AI, even an excellent recommendation, and decide if it's right for the
patient is inherently a human decision-making process. What are the patient's preferences? What are the patient's
values? What does this mean for the patient's life and for his or her family? That's never going to be an AI
function. As these AI systems slowly emerge, we may start to see the roles of physicians changing—in my
opinion, in better ways. Doctors' roles may shift from being data collectors and analyzers to being interpreters and
councilors for patients as they try to navigate their health.
Right now, the challenges we need to address as we try to bring AI into medical practice include improving the quality of the data that we feed into AI systems, developing ways to evaluate whether an AI system is actually better than standard of care, ensuring patient privacy and making sure not only that AI doesn't disrupt clinical work flow but in fact improves it. But if doctors do their jobs right and build these systems well, much of what we have described will become so ingrained in the system, people won't even refer to it separately as informatics or AI. It will just be medicine.
Right now, the challenges we need to address as we try to bring AI into medical practice include improving the quality of the data that we feed into AI systems, developing ways to evaluate whether an AI system is actually better than standard of care, ensuring patient privacy and making sure not only that AI doesn't disrupt clinical work flow but in fact improves it. But if doctors do their jobs right and build these systems well, much of what we have described will become so ingrained in the system, people won't even refer to it separately as informatics or AI. It will just be medicine.
Disponível em: https://medicalxpress.com/news/2018-12-artificial-intelligence-future-medicine.html. Acesso em: 02 maio 2019.
De acordo com o texto, em termos de sentido, verifica-se que o trecho
Q1300891
Inglês
Texto associado
Leia o texto a seguir para responder à questão.
Artificial intelligence and the future of medicine
Washington University researchers are working to develop artificial intelligence (AI) systems for health care, which
have the potential to transform the diagnosis and treatment of diseases, helping to ensure that patients get the
right treatment at the right time.
In health care, artificial intelligence relies on the power of computers to sift through and make sense of reams of
electronic data about patients—such as their ages, medical histories, health status, test results, medical images,
DNA sequences, and many other sources of health information. AI excels at the complex identification of patterns
in these reams of data, and it can do this at a scale and speed beyond human capacity. The hope is that this
technology can be harnessed to help doctors and patients make better health-care decisions.
Where are the first places we will start to see AI entering medical practice?
One of the first applications of AI in patient care that we currently see is in imaging, to help improve the diagnosis
of cancer or heart problems, for example. There are many types of imaging tests —X-rays, CT scans, MRIs and
echocardiograms. But the underlying commonality in all those imaging methods is huge amounts of high-quality
data. For AI to work well, it's best to have very complete data sets—no missing numbers, so to speak—and digital
images provide that. Plus, the human eye is often blind to some of the patterns that could be present in these
images—subtle changes in breast tissue over several years of mammograms, for example. There has been some
interesting work done in recognizing early patterns of cancer or early patterns of heart failure that even a highly
trained physician would not see.
In many ways, we already have very simple forms of AI in the clinic now. We've had tools for a long time that
identify abnormal rhythms in an EKG, for example. An abnormal heartbeat pattern triggers an alert to draw a
clinician's attention. This is a computer trying to replicate a human being understanding that data and saying,
"This doesn't look normal, you may need to address this problem." Now, we have the capacity to analyze much
larger and more complex sources of data, such as the entire electronic health record and perhaps even data
pulled from daily life, as more people track their sleep patterns or pulse rates with wearable devices, for example.
What effect will this have on how doctors practice medicine?
It's important to emphasize that these tools are never going to replace clinicians. These technologies will provide
assistance, helping care providers see important signals in massive amounts of data that would otherwise remain
hidden. But at the same time, there are levels of understanding that computers still can't and may never replicate.
To take a treatment recommendation from an AI, even an excellent recommendation, and decide if it's right for the
patient is inherently a human decision-making process. What are the patient's preferences? What are the patient's
values? What does this mean for the patient's life and for his or her family? That's never going to be an AI
function. As these AI systems slowly emerge, we may start to see the roles of physicians changing—in my
opinion, in better ways. Doctors' roles may shift from being data collectors and analyzers to being interpreters and
councilors for patients as they try to navigate their health.
Right now, the challenges we need to address as we try to bring AI into medical practice include improving the quality of the data that we feed into AI systems, developing ways to evaluate whether an AI system is actually better than standard of care, ensuring patient privacy and making sure not only that AI doesn't disrupt clinical work flow but in fact improves it. But if doctors do their jobs right and build these systems well, much of what we have described will become so ingrained in the system, people won't even refer to it separately as informatics or AI. It will just be medicine.
Right now, the challenges we need to address as we try to bring AI into medical practice include improving the quality of the data that we feed into AI systems, developing ways to evaluate whether an AI system is actually better than standard of care, ensuring patient privacy and making sure not only that AI doesn't disrupt clinical work flow but in fact improves it. But if doctors do their jobs right and build these systems well, much of what we have described will become so ingrained in the system, people won't even refer to it separately as informatics or AI. It will just be medicine.
Disponível em: https://medicalxpress.com/news/2018-12-artificial-intelligence-future-medicine.html. Acesso em: 02 maio 2019.
Analisando-se os aspectos linguísticos e estruturais do texto, constata-se que
Q1300890
Inglês
Texto associado
Leia o texto a seguir para responder à questão.
Artificial intelligence and the future of medicine
Washington University researchers are working to develop artificial intelligence (AI) systems for health care, which
have the potential to transform the diagnosis and treatment of diseases, helping to ensure that patients get the
right treatment at the right time.
In health care, artificial intelligence relies on the power of computers to sift through and make sense of reams of
electronic data about patients—such as their ages, medical histories, health status, test results, medical images,
DNA sequences, and many other sources of health information. AI excels at the complex identification of patterns
in these reams of data, and it can do this at a scale and speed beyond human capacity. The hope is that this
technology can be harnessed to help doctors and patients make better health-care decisions.
Where are the first places we will start to see AI entering medical practice?
One of the first applications of AI in patient care that we currently see is in imaging, to help improve the diagnosis
of cancer or heart problems, for example. There are many types of imaging tests —X-rays, CT scans, MRIs and
echocardiograms. But the underlying commonality in all those imaging methods is huge amounts of high-quality
data. For AI to work well, it's best to have very complete data sets—no missing numbers, so to speak—and digital
images provide that. Plus, the human eye is often blind to some of the patterns that could be present in these
images—subtle changes in breast tissue over several years of mammograms, for example. There has been some
interesting work done in recognizing early patterns of cancer or early patterns of heart failure that even a highly
trained physician would not see.
In many ways, we already have very simple forms of AI in the clinic now. We've had tools for a long time that
identify abnormal rhythms in an EKG, for example. An abnormal heartbeat pattern triggers an alert to draw a
clinician's attention. This is a computer trying to replicate a human being understanding that data and saying,
"This doesn't look normal, you may need to address this problem." Now, we have the capacity to analyze much
larger and more complex sources of data, such as the entire electronic health record and perhaps even data
pulled from daily life, as more people track their sleep patterns or pulse rates with wearable devices, for example.
What effect will this have on how doctors practice medicine?
It's important to emphasize that these tools are never going to replace clinicians. These technologies will provide
assistance, helping care providers see important signals in massive amounts of data that would otherwise remain
hidden. But at the same time, there are levels of understanding that computers still can't and may never replicate.
To take a treatment recommendation from an AI, even an excellent recommendation, and decide if it's right for the
patient is inherently a human decision-making process. What are the patient's preferences? What are the patient's
values? What does this mean for the patient's life and for his or her family? That's never going to be an AI
function. As these AI systems slowly emerge, we may start to see the roles of physicians changing—in my
opinion, in better ways. Doctors' roles may shift from being data collectors and analyzers to being interpreters and
councilors for patients as they try to navigate their health.
Right now, the challenges we need to address as we try to bring AI into medical practice include improving the quality of the data that we feed into AI systems, developing ways to evaluate whether an AI system is actually better than standard of care, ensuring patient privacy and making sure not only that AI doesn't disrupt clinical work flow but in fact improves it. But if doctors do their jobs right and build these systems well, much of what we have described will become so ingrained in the system, people won't even refer to it separately as informatics or AI. It will just be medicine.
Right now, the challenges we need to address as we try to bring AI into medical practice include improving the quality of the data that we feed into AI systems, developing ways to evaluate whether an AI system is actually better than standard of care, ensuring patient privacy and making sure not only that AI doesn't disrupt clinical work flow but in fact improves it. But if doctors do their jobs right and build these systems well, much of what we have described will become so ingrained in the system, people won't even refer to it separately as informatics or AI. It will just be medicine.
Disponível em: https://medicalxpress.com/news/2018-12-artificial-intelligence-future-medicine.html. Acesso em: 02 maio 2019.
Considering the ideas expressed in the text, artificial intelligence (AI) systems
Q1300801
Inglês
Observe o infográfico a seguir para responder à questão.
Disponível: https://morgan6062.com/2018/06/09/suicide-prevention-hotlines/. Acesso em: 08 out. 2019
According the information expressed in the image and data, Suicide Prevention, we verify that
Q1300800
Inglês
Texto associado
Leia o texto a seguir para responder à questão.
Forest fires: the good and the bad
Every year it seems like there’s another disastrous wildfire in the American West. In 2018, nearly 9 million acres were burned in the US alone. Uncontrolled fires often started accidentally by people, rampage and decimate forests. F
or most people, a forest fire is synonymous with disaster. But there are some kinds of forest fires that actually benefit the environment.
A controlled burn is a wildfire that people set intentionally for a specific purpose. Well-thought-out and wellmanaged controlled burns can be incredibly beneficial for forest management—in part because they can help stop an out-of-control wildfire. The technique is called backburning, and it involves setting a controlled fire in the path of the approaching wildfire. All the flammable material is burnt up and extinguished. When the wildfire approaches, there’s no more fuel left for it to keep going, and it dies out.
Controlled burns are also used to prevent forest fires. Even before human involvement, natural, low-intensity wildfires occurred every few years to burn up fuel, plant debris, and dead trees, making way for young, healthy trees and vegetation to thrive. That new growth in turn supports forest wildlife. Forest managers are now replicating this natural strategy when appropriate, starting manageable, slow-burning fires to make room for new life that will help keep the forest healthy in the long term.
The same method is one of WWF’s strategies for maintaining grassland habitats in the Northern Great Plains. Working with partners such as the U.S. Fish and Wildlife Service, WWF has intentionally burned hundreds of acres of prairie land to revitalize these key habitats. The fire burns off tall, aggressive vegetation that isn’t as hospitable to wildlife, and makes room for new growth that attracts bison, birds, and prairie dogs.
This doesn’t mean all intentional wildfires are good – far from it. Many of the fires intentionally set for agriculture and land clearing are at best ill-advised, and at worst devastating. Slash and burn fires are set every day to destroy large sections of forests. Of course, these forests don’t just remove trees; they kill and displace wildlife, alter water cycles and soil fertility, and endanger the lives and livelihoods of local communities. They also can rage out of control. In 1997, fires set intentionally to clear forests in Indonesia escalated into one of the largest wildfires in recorded history. Hundreds of people died; millions of acres burned; already at-risk species like orangutans perished by the hundreds; and a smoke and ash haze hung over southeast Asia for months, reducing visibility and causing acute health conditions.
That’s exactly why WWF helps governments around the world crack down on slash and burn deforestation. WWF also works with farmers and companies to stop unnecessary agricultural burns. And when our scientists think fire could be the best solution for revitalizing wild areas, we bring the right experts to the table to study the situation and come up with a plan.
All fire is risky. To minimize that risk as much as possible, controlled burns must be well-considered, wellplanned, and ignited and maintained by trained professionals. The bottom line? Fire can be a tool for conservation, but only when used the right way.
Disponível em: https://www.worldwildlife.org/stories/forest-fires-the-good-and-the-bad. Acesso em: 08 out. 2019
Analisando os aspectos linguísticos da língua inglesa presentes no texto, constata-se que
Conheça nossos planos