Questões de Concurso
Sobre interpretação de texto | reading comprehension em inglês
Foram encontradas 9.488 questões
Judge the following items according to the text CB3A1AAA.
The author of the text claims that concurrent computation is an
outdated issue.
Judge the following items according to the text CB3A1AAA.
In spite of being a longstanding matter, concurrent computation
has been used just by professionals who implement database
management systems.
Judge the following items according to the text CB3A1AAA.
Software construction professionals must be acquainted with
concurrency quickly.
Judge the following items according to the text CB3A1AAA.
Even some applications once seen as sequential are now
demanding concurrent computation.
Read the paragraph below.
“At the Whole Woman’s Health center here, a young woman predicted what others would do if the state’s stringent new abortion bill approved late Friday forces clinics like this one to close: cross the border to Mexico to seek an “abortion pill.”
A Pill Available in Mexico Is a Texas Option for Abortion. Available in: http://www.nytimes.com
It is correct to affirm that the underlined word refers to
Vigilance needed to ensure safe infant food
WHO and FAO alert countries to possible spread of
melamine-contaminated dairy products
WHO and the UN Food and Agriculture Organization (FAO) are urging affected countries to ensure safe feeding of millions of infants following the ongoing melamine-contaminated milk crisis in China. The two agencies also call on countries to be alert to the possible spread of melamine-contaminated dairy products.
“While breastfeeding is the ideal way of providing infants with the nutrients they need for healthy growth and development, it is also critical to ensure that there is an adequate supply of safe powdered infant formula to meet the needs of infants who are not breastfed”, said Dr Jorgen Schlundt, Director of the WHO Food Safety Department.
Replacing powdered infant formula with other products such as condensed milk, honey mixed with milk, or fresh milk is inappropriate as such products would put at risk the safety and nutritional status of this vulnerable population group, the two agencies advised.
“Restoring consumer confidence is critical. Melamine-contaminated products should be removed from the food chain in order to prevent further exposure. The safe supply of dairy products needs to be restored immediately,” said Dr Ezzeddine Boutrif, Director of the FAO Nutrition and Consumer Protection Division.
Safe feeding for infants
WHO recommends that all infants should be fed exclusively with breast milk for the first six months of life. No other liquid or food, not even water, is needed during this period. Thereafter, infants should receive adequate and safe complementary foods while breastfeeding continues up to two years of age and beyond.
Following reports of findings of imported melaminecontaminated products in several countries over the last two weeks, countries should closely monitor their markets. The two agencies highlighted that melamine-contaminated products could reach markets in other countries through both formal and informal trade. Getting information about the origin of the product, up-to-date recall information or in some cases testing for melamine contamination might be considered. If found contaminated, appropriate actions such as product recall and safe disposal should be taken, based on an assessment of the risk to human health.
Safe supply of food critical
Food safety is not the sole responsibility of public authorities. The food industry is also responsible for ensuring a safe supply of food to the consumer. “It is critical that the industry strongly invests in food safety and adopts a food safety culture covering the food chain from raw materials through to the final product,” said Dr Boutrif.
Incidents such as melamine contamination in China not only impact food safety and human health but also put the livelihoods of hundreds of millions of dairy farmers at risk. “There is a need for countries to do major investment in strengthening their food control and food-borne disease surveillance systems as it could minimize the potential occurrence of food safety incidents like this one”, said Dr Schlundt.
The melamine-contaminated dairy products event first came to the attention of the international organizations on 11th September. Both WHO and FAO have used the International Food Safety Authorities Network (INFOSAN) to inform and update national food safety authorities on this crisis, one of the largest in recent years.
Over 54,000 children have sought medical treatment in China after drinking melamine-contaminated infant formula. Almost 12,900 are currently hospitalized.
Melamine is commonly used in food contact materials (e.g. containers, labels, etc.) and can also be used in agriculture production such as fertilizer. Whether this has a potential for carry-over into food at low concentrations (usually in the range of microgram per kilogram) and further impact on human health may need further evaluation.
Melamine on its own is of low toxicity. But animal studies have suggested that kidney problems occur when melamine is present in combination with cyanuric acid, a potential impurity of melamine. The level of melamine found in the contaminated infant formula has been as high as 2,560 miligram per kilogram of food, while the level of cyanuric acid is unknown.
Available in: http://www.who.int
According to the text, analyze the assertions below, put T for True or F for False and choose the alternative that presents the correct sequence.
( ) After the diagnosis show that children were contaminated, studies had confirmed that cyanuric acid and melamine induce kidney problems.
( ) Public authorities and food industry are responsible for preventing melamine food contamination, exclusively.
( ) According to Dr. Jorgen Schlundt, breast milk is
compounded of indispensable nutrients children
need for the first year of their lives, and none of the
supplies are capable of providing them.
Anxiety Medication: Over Prescribed and
Causing Overdoses
According to a story on NBC New York, more and more patients are ending up in New York City hospitals having over dosed on Xanax. Xanax is in the benzodiaziepine family of drugs and it’s used to treat anxiety, nervousness, and panic attacks by decreasing brain activity.
Xanax Overdoses Way Up
NBC New York reports:
Between 2004 and 2009, New York City emergency room visits involving Xanax and other anti-anxiety prescription drugs known as benzodiazepines increased more than 50 percent. That’s up from 38 out of 100,000 New Yorkers in 2004 to 59 out of 100,000 New Yorkers.
It’s not the drug by itself that causes the overdoses, but used in combination with other drugs and alcohol, it creates a toxic cocktail which isn’t easily metabolized in the body.
The drug is habit forming and withdrawal symptoms can include sweating, shaking, difficulty falling asleep, difficulty concentrating, depression, and nervousness. Many fear that the drug is being over prescribed.
“I don’t believe they take the time with the patients to figure out what the problems are,” Cali Estes, a drug counselor said to NBC New York. “A doctor who is running short on time and nurses and probably isn’t paid as much as he or she used to be finds it easier to say, ‘OK, this person has a problem, here’s your script, have a nice day. Where’s my next patient?’”
Whitney Houston’s Death Tied to Xanax and Other Drugs
Whitney Houston’s recent death is raising questions as to this and other sedatives. Xanax is most often criticized by those in the psychiatric community because it only lasts 6 to 20 hours.
Forbes reports:
On the face of it, this seems like a great combination – you get a quick hit of anxiety relief and the drug leaves your system within a 24-hour period. But in practice what often happens is that because the drug acts so quickly and dissipates quickly, the patient begins taking more of it to maintain the effect. Two pills a day turns into four, which turns into six and so forth.
According to the CDC, prescription drug overdose is now the leading cause of accidental death in the U.S., topping automobile accidents for the first time in 30 years. Currently, Xanax is the 11th most widely prescribed drug in the nation.
Available in: http://blogs.discovery.com
Read the text below and answer the following activity.
The Boy Who Lived
Mr. and Mrs. Dursley, of number four, Privet Drive, were proud to say that they were perfectly normal, thank you very much. They were the last people you'd expect to be involved in anything strange or mysterious, because they just didn't hold with such nonsense.
Mr. Dursley was the director of a firm called Grunnings, which made drills. He was a big, beefy man with hardly any neck, although he did have a very large mustache. Mrs. Dursley was thin and blonde and had nearly twice the usual amount of neck, which came in very useful as she spent so much of her time craning over garden fences, spying on the neighbors. The Dursleys had a small son called Dudley and in their opinion there was no finer boy anywhere.
The Dursleys had everything they wanted, but they also had a secret, and their greatest fear was that somebody would discover it. They didn't think they could bear it if anyone found out about the Potters. Mrs. Potter was Mrs. Dursley's sister, but they hadn't met for several years; in fact, Mrs. Dursley pretended she didn't have a sister, because her sister and her good-for-nothing husband were as unDursleyish as it was possible to be. The Dursleys shuddered to think what the neighbors would say if the Potters arrived in the street. The Dursleys knew that the Potters had a small son, too, but they had never even seen him. This boy was another good reason for keeping the Potters away; they didn't want Dudley mixing with a child like that.
The American singer Beyoncé included in her song “Flawless” a sample from a speech given by the Nigerian writer Chimamanda Adichie entitled “We Should All Be Feminists”. Read the sample from the song and answer the following activity.
We teach girls to shrink themselves, to make themselves smaller. We say to girls, you can have ambition, but not too much. You should aim to be successful, but not too successful. Otherwise, you will threaten the man. Because I am female, I am expected to aspire to marriage. I am expected to make my life choices always keeping in mind that marriage is the most important. Now marriage can be a source of joy and love and mutual support but why do we teach girls to aspire to marriage and we don’t teach boys the same? We raise girls to see each other as competitors not for jobs or accomplishments, which I think can be a good thing, but for the attention of men. We teach girls that they cannot be sexual beings in the way that boys are. Feminist: the person who believes in the social, political and economic equality of the sexes.
According to the excerpt, the song DOES NOT suggest
that:
How Telecommuting Works
Telecommuting, which is growing in popularity, allows
employees to avoid long commutes.
“Brring,” the alarm startles you out of a deep sleep. It’s
8 a.m. on Monday morning. Time to head to the office.
You roll out of bed, brush your teeth and stumble your
way to the kitchen to grab some coffee.
Moments later, you head to the office, still wearing
your pajamas and fluffy slippers. Luckily for you, you
don’t have to go far – you work at home.
Telecommuting, or working at home, has grown in
popularity over the last 20 years.
On an increasing basis, workers are saying “no” to
long commutes and opting to work at home. In fact,
the U.S. Census Bureau reports that the number of
employees working from home grew by 23 percent
from 1990 to 2000.
Telecommuting workers revel in making their own
schedule – allowing them to schedule work around
family and personal commitments. With the ready
availability of technology tools, like the Internet and
home computers, companies are more willing to let
employees work from home.
( Adaptedfrom : < http: //home.howstuffworks.com/telecommuting.htm>Access on 18th January, 2014)
How Telecommuting Works
Telecommuting, which is growing in popularity, allows
employees to avoid long commutes.
“Brring,” the alarm startles you out of a deep sleep. It’s
8 a.m. on Monday morning. Time to head to the office.
You roll out of bed, brush your teeth and stumble your
way to the kitchen to grab some coffee.
Moments later, you head to the office, still wearing
your pajamas and fluffy slippers. Luckily for you, you
don’t have to go far – you work at home.
Telecommuting, or working at home, has grown in
popularity over the last 20 years.
On an increasing basis, workers are saying “no” to
long commutes and opting to work at home. In fact,
the U.S. Census Bureau reports that the number of
employees working from home grew by 23 percent
from 1990 to 2000.
Telecommuting workers revel in making their own
schedule – allowing them to schedule work around
family and personal commitments. With the ready
availability of technology tools, like the Internet and
home computers, companies are more willing to let
employees work from home.
( Adaptedfrom : < http: //home.howstuffworks.com/telecommuting.htm>Access on 18th January, 2014)
How Telecommuting Works
Telecommuting, which is growing in popularity, allows
employees to avoid long commutes.
“Brring,” the alarm startles you out of a deep sleep. It’s
8 a.m. on Monday morning. Time to head to the office.
You roll out of bed, brush your teeth and stumble your
way to the kitchen to grab some coffee.
Moments later, you head to the office, still wearing
your pajamas and fluffy slippers. Luckily for you, you
don’t have to go far – you work at home.
Telecommuting, or working at home, has grown in
popularity over the last 20 years.
On an increasing basis, workers are saying “no” to
long commutes and opting to work at home. In fact,
the U.S. Census Bureau reports that the number of
employees working from home grew by 23 percent
from 1990 to 2000.
Telecommuting workers revel in making their own
schedule – allowing them to schedule work around
family and personal commitments. With the ready
availability of technology tools, like the Internet and
home computers, companies are more willing to let
employees work from home.
( Adaptedfrom : < http: //home.howstuffworks.com/telecommuting.htm>Access on 18th January, 2014)
How Telecommuting Works
Telecommuting, which is growing in popularity, allows
employees to avoid long commutes.
“Brring,” the alarm startles you out of a deep sleep. It’s
8 a.m. on Monday morning. Time to head to the office.
You roll out of bed, brush your teeth and stumble your
way to the kitchen to grab some coffee.
Moments later, you head to the office, still wearing
your pajamas and fluffy slippers. Luckily for you, you
don’t have to go far – you work at home.
Telecommuting, or working at home, has grown in
popularity over the last 20 years.
On an increasing basis, workers are saying “no” to
long commutes and opting to work at home. In fact,
the U.S. Census Bureau reports that the number of
employees working from home grew by 23 percent
from 1990 to 2000.
Telecommuting workers revel in making their own
schedule – allowing them to schedule work around
family and personal commitments. With the ready
availability of technology tools, like the Internet and
home computers, companies are more willing to let
employees work from home.
( Adaptedfrom : < http: //home.howstuffworks.com/telecommuting.htm>Access on 18th January, 2014)
TEXT II
The backlash against big data
[…]
Big data refers to the idea that society can do things with a large body of data that weren’t possible when working with smaller amounts. The term was originally applied a decade ago to massive datasets from astrophysics, genomics and internet search engines, and to machine-learning systems (for voice-recognition and translation, for example) that work well only when given lots of data to chew on. Now it refers to the application of data-analysis and statistics in new areas, from retailing to human resources. The backlash began in mid-March, prompted by an article in Science by David Lazer and others at Harvard and Northeastern University. It showed that a big-data poster-child—Google Flu Trends, a 2009 project which identified flu outbreaks from search queries alone—had overestimated the number of cases for four years running, compared with reported data from the Centres for Disease Control (CDC). This led to a wider attack on the idea of big data.
The criticisms fall into three areas that are not intrinsic to big data per se, but endemic to data analysis, and have some merit. First, there are biases inherent to data that must not be ignored. That is undeniably the case. Second, some proponents of big data have claimed that theory (ie, generalisable models about how the world works) is obsolete. In fact, subject-area knowledge remains necessary even when dealing with large data sets. Third, the risk of spurious correlations—associations that are statistically robust but happen only by chance—increases with more data. Although there are new statistical techniques to identify and banish spurious correlations, such as running many tests against subsets of the data, this will always be a problem.
There is some merit to the naysayers' case, in other words. But these criticisms do not mean that big-data analysis has no merit whatsoever. Even the Harvard researchers who decried big data "hubris" admitted in Science that melding Google Flu Trends analysis with CDC’s data improved the overall forecast—showing that big data can in fact be a useful tool. And research published in PLOS Computational Biology on April 17th shows it is possible to estimate the prevalence of the flu based on visits to Wikipedia articles related to the illness. Behind the big data backlash is the classic hype cycle, in which a technology’s early proponents make overly grandiose claims, people sling arrows when those promises fall flat, but the technology eventually transforms the world, though not necessarily in ways the pundits expected. It happened with the web, and television, radio, motion pictures and the telegraph before it. Now it is simply big data’s turn to face the grumblers.
(From http://www.economist.com/blogs/economist explains/201 4/04/economist-explains-10)
TEXT II
The backlash against big data
[…]
Big data refers to the idea that society can do things with a large body of data that weren’t possible when working with smaller amounts. The term was originally applied a decade ago to massive datasets from astrophysics, genomics and internet search engines, and to machine-learning systems (for voice-recognition and translation, for example) that work well only when given lots of data to chew on. Now it refers to the application of data-analysis and statistics in new areas, from retailing to human resources. The backlash began in mid-March, prompted by an article in Science by David Lazer and others at Harvard and Northeastern University. It showed that a big-data poster-child—Google Flu Trends, a 2009 project which identified flu outbreaks from search queries alone—had overestimated the number of cases for four years running, compared with reported data from the Centres for Disease Control (CDC). This led to a wider attack on the idea of big data.
The criticisms fall into three areas that are not intrinsic to big data per se, but endemic to data analysis, and have some merit. First, there are biases inherent to data that must not be ignored. That is undeniably the case. Second, some proponents of big data have claimed that theory (ie, generalisable models about how the world works) is obsolete. In fact, subject-area knowledge remains necessary even when dealing with large data sets. Third, the risk of spurious correlations—associations that are statistically robust but happen only by chance—increases with more data. Although there are new statistical techniques to identify and banish spurious correlations, such as running many tests against subsets of the data, this will always be a problem.
There is some merit to the naysayers' case, in other words. But these criticisms do not mean that big-data analysis has no merit whatsoever. Even the Harvard researchers who decried big data "hubris" admitted in Science that melding Google Flu Trends analysis with CDC’s data improved the overall forecast—showing that big data can in fact be a useful tool. And research published in PLOS Computational Biology on April 17th shows it is possible to estimate the prevalence of the flu based on visits to Wikipedia articles related to the illness. Behind the big data backlash is the classic hype cycle, in which a technology’s early proponents make overly grandiose claims, people sling arrows when those promises fall flat, but the technology eventually transforms the world, though not necessarily in ways the pundits expected. It happened with the web, and television, radio, motion pictures and the telegraph before it. Now it is simply big data’s turn to face the grumblers.
(From http://www.economist.com/blogs/economist explains/201 4/04/economist-explains-10)
TEXT II
The backlash against big data
[…]
Big data refers to the idea that society can do things with a large body of data that weren’t possible when working with smaller amounts. The term was originally applied a decade ago to massive datasets from astrophysics, genomics and internet search engines, and to machine-learning systems (for voice-recognition and translation, for example) that work well only when given lots of data to chew on. Now it refers to the application of data-analysis and statistics in new areas, from retailing to human resources. The backlash began in mid-March, prompted by an article in Science by David Lazer and others at Harvard and Northeastern University. It showed that a big-data poster-child—Google Flu Trends, a 2009 project which identified flu outbreaks from search queries alone—had overestimated the number of cases for four years running, compared with reported data from the Centres for Disease Control (CDC). This led to a wider attack on the idea of big data.
The criticisms fall into three areas that are not intrinsic to big data per se, but endemic to data analysis, and have some merit. First, there are biases inherent to data that must not be ignored. That is undeniably the case. Second, some proponents of big data have claimed that theory (ie, generalisable models about how the world works) is obsolete. In fact, subject-area knowledge remains necessary even when dealing with large data sets. Third, the risk of spurious correlations—associations that are statistically robust but happen only by chance—increases with more data. Although there are new statistical techniques to identify and banish spurious correlations, such as running many tests against subsets of the data, this will always be a problem.
There is some merit to the naysayers' case, in other words. But these criticisms do not mean that big-data analysis has no merit whatsoever. Even the Harvard researchers who decried big data "hubris" admitted in Science that melding Google Flu Trends analysis with CDC’s data improved the overall forecast—showing that big data can in fact be a useful tool. And research published in PLOS Computational Biology on April 17th shows it is possible to estimate the prevalence of the flu based on visits to Wikipedia articles related to the illness. Behind the big data backlash is the classic hype cycle, in which a technology’s early proponents make overly grandiose claims, people sling arrows when those promises fall flat, but the technology eventually transforms the world, though not necessarily in ways the pundits expected. It happened with the web, and television, radio, motion pictures and the telegraph before it. Now it is simply big data’s turn to face the grumblers.
(From http://www.economist.com/blogs/economist explains/201 4/04/economist-explains-10)
TEXT I
Will computers ever truly understand what we’re saying?
Date: January 11, 2016
Source University of California - Berkeley
Summary:
If you think computers are quickly approaching true human communication, think again. Computers like Siri often get confused because they judge meaning by looking at a word’s statistical regularity. This is unlike humans, for whom context is more important than the word or signal, according to a researcher who invented a communication game allowing only nonverbal cues, and used it to pinpoint regions of the brain where mutual understanding takes place.
From Apple’s Siri to Honda’s robot Asimo, machines seem to be getting better and better at communicating with humans. But some neuroscientists caution that today’s computers will never truly understand what we’re saying because they do not take into account the context of a conversation the way people do.
Specifically, say University of California, Berkeley, postdoctoral fellow Arjen Stolk and his Dutch colleagues, machines don’t develop a shared understanding of the people, place and situation - often including a long social history - that is key to human communication. Without such common ground, a computer cannot help but be confused.
“People tend to think of communication as an exchange of linguistic signs or gestures, forgetting that much of communication is about the social context, about who you are communicating with,” Stolk said.
The word “bank,” for example, would be interpreted one way if you’re holding a credit card but a different way if you’re holding a fishing pole. Without context, making a “V” with two fingers could mean victory, the number two, or “these are the two fingers I broke.”
“All these subtleties are quite crucial to understanding one another,” Stolk said, perhaps more so than the words and signals that computers and many neuroscientists focus on as the key to communication. “In fact, we can understand one another without language, without words and signs that already have a shared meaning.”
(Adapted from http://www.sciencedaily.com/releases/2016/01/1 60111135231.htm)
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