Questões de Concurso
Comentadas sobre interpretação de texto | reading comprehension em inglês
Foram encontradas 8.732 questões
( ) The word ethos is uncountable because it refers to the guiding spirit, values, or character of a person, group, or culture.
( ) The word ethos names a general, continuous quality (a way of thinking/behaving).
( ) In the text, you could say two ethoses because it reÍers to an overarching spirit or attitude that applies to many people.
( ) The use of ethos is functional when the writer wants to talk about individual instances.
Which alternative CORRECTLY fills in the parentheses above?
( ) In literal terms, a ringmaster is the person in charge of a circus performance, especially the one who introduces the acts, guides the audience's attention, and keeps the show moving in the ring.
( ) In the text, the word is used metaphorically.
( ) The "ringmaster" stands for P.T. Barnum as the director/controller of attention and spectacle, the one who teaches people that any kind of publicity (even fake or sensational) is acceptable as long as it grabs notice.
( ) "Ringmaster", in popular culture, means the master-of-ceremonies of a showy, attention-driven culture, not just a literal circus host.
Which alternative CORRECTLY fills in the parentheses a bove?
Choose the connector that best completes the sentence:
"He studied hard for the exam; ___, he did not achieve the expected results."
Text I
Understanding bias in facial recognition technologies
Over the past couple of years, the growing debate around automated facial recognition has reached a boiling point. As developers have continued to swiftly expand the scope of these kinds of technologies into an almost unbounded range of applications, an increasingly strident chorus of critical voices has sounded concerns about the injurious effects of the proliferation of such systems on impacted individuals and communities. Critics argue that the irresponsible design and use of facial detection and recognition technologies (FDRTs) threaten to violate civil liberties, infringe on basic human rights and further entrench structural racism and systemic marginalisation. In addition, they argue that the gradual creep of face surveillance infrastructures into every domain of lived experience may eventually eradicate the modern democratic forms of life that have long provided cherished means to individual flourishing, social solidarity and human self-creation.
Defenders, by contrast, emphasise the gains in public safety, security and efficiency that digitally streamlined capacities for facial identification, identity verification and trait characterisation may bring. These proponents point to potential real-world benefits like the added security of facial recognition enhanced border control, the increased efficacy of missing children or criminal suspect searches that are driven by the application of brute force facial analysis to largescale databases and the many added conveniences of facial verification in the business of everyday life.
Whatever side of the debate on which one lands, it would appear that FDRTs are here to stay.
Adapted from: understanding_bias_in_facial_recognition_technology.pdf
Text I
Understanding bias in facial recognition technologies
Over the past couple of years, the growing debate around automated facial recognition has reached a boiling point. As developers have continued to swiftly expand the scope of these kinds of technologies into an almost unbounded range of applications, an increasingly strident chorus of critical voices has sounded concerns about the injurious effects of the proliferation of such systems on impacted individuals and communities. Critics argue that the irresponsible design and use of facial detection and recognition technologies (FDRTs) threaten to violate civil liberties, infringe on basic human rights and further entrench structural racism and systemic marginalisation. In addition, they argue that the gradual creep of face surveillance infrastructures into every domain of lived experience may eventually eradicate the modern democratic forms of life that have long provided cherished means to individual flourishing, social solidarity and human self-creation.
Defenders, by contrast, emphasise the gains in public safety, security and efficiency that digitally streamlined capacities for facial identification, identity verification and trait characterisation may bring. These proponents point to potential real-world benefits like the added security of facial recognition enhanced border control, the increased efficacy of missing children or criminal suspect searches that are driven by the application of brute force facial analysis to largescale databases and the many added conveniences of facial verification in the business of everyday life.
Whatever side of the debate on which one lands, it would appear that FDRTs are here to stay.
Adapted from: understanding_bias_in_facial_recognition_technology.pdf
Text I
Understanding bias in facial recognition technologies
Over the past couple of years, the growing debate around automated facial recognition has reached a boiling point. As developers have continued to swiftly expand the scope of these kinds of technologies into an almost unbounded range of applications, an increasingly strident chorus of critical voices has sounded concerns about the injurious effects of the proliferation of such systems on impacted individuals and communities. Critics argue that the irresponsible design and use of facial detection and recognition technologies (FDRTs) threaten to violate civil liberties, infringe on basic human rights and further entrench structural racism and systemic marginalisation. In addition, they argue that the gradual creep of face surveillance infrastructures into every domain of lived experience may eventually eradicate the modern democratic forms of life that have long provided cherished means to individual flourishing, social solidarity and human self-creation.
Defenders, by contrast, emphasise the gains in public safety, security and efficiency that digitally streamlined capacities for facial identification, identity verification and trait characterisation may bring. These proponents point to potential real-world benefits like the added security of facial recognition enhanced border control, the increased efficacy of missing children or criminal suspect searches that are driven by the application of brute force facial analysis to largescale databases and the many added conveniences of facial verification in the business of everyday life.
Whatever side of the debate on which one lands, it would appear that FDRTs are here to stay.
Adapted from: understanding_bias_in_facial_recognition_technology.pdf
"To ensure optimal ionization of biomolecules, use a capillary voltage between 3.5 and 4.5kV. The nebulizer gas should be set at 50 psi, and the drying gas should be heated to 350°C. Maintain a source temperature of 120°C. For larger molecules, increasing the capillary voltage to 5kV may improve ionization efficiency."
Com base nas informações fornecidas, a recomendação sobre o ajuste da tensão do capilar é:
"For optimal detection of compounds absorbing in the 200 - 300 nm range, set the wavelength between 220 - 230 nm . For compounds with stronger absorbance above 300 nm, use wavelengths around 280 - 290 nm. Adjust the wavelength to maximize the signal intensity while avoiding excessive noise."
Com base no trecho citado, a instrução CORRETA para o ajuste do comprimento de onda em CLAE é:
"One morning I shot an elephant in my pajamas. How he got into my pajamas I'll never know".
I.The man shot an elephant while he was wearing his pajamas.
II.The man shot an elephant that was wearing his pajamas.
III.The man shot an elephant because it was wearing his pajamas.
IV.The man shot an elephant but was wearing his pajamas.