Questões de Concurso Público Prefeitura de Ubatuba - SP 2026 para Professor da Educação Básica II - Inglês
Foram encontradas 50 questões
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Provas:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Geografia
|
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Matemática |
Q4246853
Pedagogia
O currículo é a concretização, a viabilização das
intenções e orientações expressas no projeto
pedagógico. De acordo com a obra Educação
Escolar: políticas, estrutura e organização, о
currículo ocorre em, pelo menos, três tipos de
manifestações: currículo formal, currículo real
e currículo oculto. Assinale a alternativa correta
a respeito dos tipos de currículo.
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Provas:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Geografia
|
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Matemática |
Q4246854
Pedagogia
O conjunto de competências, habilidades e
conhecimentos necessários ao pleno exercício
da cidadania digital na contemporaneidade é a
definição de:
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Provas:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Geografia
|
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Matemática |
Q4246855
Pedagogia
A Lei de Diretrizes e Bases da Educação
Nacional (Lei nº 9.394/1996) dispõe sobre a
organização, participação e trabalho coletivo na
escola. Os estabelecimentos de ensino terão as
incumbências abaixo descritas, EXCETO uma:
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Provas:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Geografia
|
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Matemática |
Q4246856
Pedagogia
O Decreto nº 12.686/2025 institui como
objetivo da Política Nacional de Educação
Especial Inclusiva o seguinte:
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Provas:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Geografia
|
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Matemática |
Q4246857
Pedagogia
Segundo as Diretrizes Nacionais da Educação
em Direitos Humanos, qual é a forma como será
abordado o método de aplicação das ações para
a Educação para os Direitos Humanos?
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247243
Inglês
Texto associado
Read the text to answer question.
Using Machine Learning to Develop
Personalized Vaccines for Cancer
Yale researchers have developed a machine
learning model, called Immunostruct, that can
help scientists create more personalized
vaccines, including vaccines for cancer. They
described the tool in Nature Machine
Intelligence along with findings from applying
it to cancer and immunology data.
When a potential threat, such as a virus
or tumor, arises in our body, our immune cells
recognize peptides---essentially short
proteins---on the surface of the invader and
mount a defensive response. This small region
that the immune system interacts with is known
as an epitope.
Epitope-based vaccines are an emerging
technology that contain specific peptides in
order to trigger immune responses that
precisely target particular diseases. Ongoing
studies show that these vaccines are a
promising potential immunotherapy for a range
of cancers including melanomas, breast
cancers, and glioblastomas. Researchers are
also investigating whether these vaccines could
more effectively combat new variants of
infectious diseases.
To develop these vaccines, scientists
can use models that help them predict which
peptides are most likely to trigger a strong immune response to a particular antigen. A
limitation of many of these models, the
researchers say, is that they treat peptides as a
one-dimensional sequence of amino acids, not
the three-dimensional, active structures that
they are.
Now, Yale researchers have created a
model that also incorporates structural and
biochemical properties of peptides. In the new
study, they show that the multimodal model is
more effective at identifying peptide candidates
than its predecessors.
"Cancer is extremely heterogeneous---which often makes it very hard to treat
effectively," says Kevin B. Givechian, PhD, an
MD-PhD student at Yale and co-first author on
the study. “We have built a deep-learning model
that integrates more information than had
previously been combined to help us improve
the identification of vaccine targets that
stimulate people's immune system against their
own tumor. Doing so would enable a more
effective and less toxic method of treatment."
ВАCKMAN, Isabella. Using Machine Learning to
Develop Personalized Vaccines for Cancer. Yale School
of Medicine, 24 fev. 2026. Acesso em: 28 june. 2026.
According to the text, the main purpose of
Immunostruct is to help scientists:
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247244
Não definido
Texto associado
Read the text to answer question.
Using Machine Learning to Develop
Personalized Vaccines for Cancer
Yale researchers have developed a machine
learning model, called Immunostruct, that can
help scientists create more personalized
vaccines, including vaccines for cancer. They
described the tool in Nature Machine
Intelligence along with findings from applying
it to cancer and immunology data.
When a potential threat, such as a virus
or tumor, arises in our body, our immune cells
recognize peptides---essentially short
proteins---on the surface of the invader and
mount a defensive response. This small region
that the immune system interacts with is known
as an epitope.
Epitope-based vaccines are an emerging
technology that contain specific peptides in
order to trigger immune responses that
precisely target particular diseases. Ongoing
studies show that these vaccines are a
promising potential immunotherapy for a range
of cancers including melanomas, breast
cancers, and glioblastomas. Researchers are
also investigating whether these vaccines could
more effectively combat new variants of
infectious diseases.
To develop these vaccines, scientists
can use models that help them predict which
peptides are most likely to trigger a strong immune response to a particular antigen. A
limitation of many of these models, the
researchers say, is that they treat peptides as a
one-dimensional sequence of amino acids, not
the three-dimensional, active structures that
they are.
Now, Yale researchers have created a
model that also incorporates structural and
biochemical properties of peptides. In the new
study, they show that the multimodal model is
more effective at identifying peptide candidates
than its predecessors.
"Cancer is extremely heterogeneous---which often makes it very hard to treat
effectively," says Kevin B. Givechian, PhD, an
MD-PhD student at Yale and co-first author on
the study. “We have built a deep-learning model
that integrates more information than had
previously been combined to help us improve
the identification of vaccine targets that
stimulate people's immune system against their
own tumor. Doing so would enable a more
effective and less toxic method of treatment."
ВАCKMAN, Isabella. Using Machine Learning to
Develop Personalized Vaccines for Cancer. Yale School
of Medicine, 24 fev. 2026. Acesso em: 28 june. 2026.
In the excerpt "our immune cells recognize
peptides... and mount a defensive response," the
word "mount" could be replaced, without
changing its meaning, by:
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247245
Inglês
Texto associado
Read the text to answer question.
Using Machine Learning to Develop
Personalized Vaccines for Cancer
Yale researchers have developed a machine
learning model, called Immunostruct, that can
help scientists create more personalized
vaccines, including vaccines for cancer. They
described the tool in Nature Machine
Intelligence along with findings from applying
it to cancer and immunology data.
When a potential threat, such as a virus
or tumor, arises in our body, our immune cells
recognize peptides---essentially short
proteins---on the surface of the invader and
mount a defensive response. This small region
that the immune system interacts with is known
as an epitope.
Epitope-based vaccines are an emerging
technology that contain specific peptides in
order to trigger immune responses that
precisely target particular diseases. Ongoing
studies show that these vaccines are a
promising potential immunotherapy for a range
of cancers including melanomas, breast
cancers, and glioblastomas. Researchers are
also investigating whether these vaccines could
more effectively combat new variants of
infectious diseases.
To develop these vaccines, scientists
can use models that help them predict which
peptides are most likely to trigger a strong immune response to a particular antigen. A
limitation of many of these models, the
researchers say, is that they treat peptides as a
one-dimensional sequence of amino acids, not
the three-dimensional, active structures that
they are.
Now, Yale researchers have created a
model that also incorporates structural and
biochemical properties of peptides. In the new
study, they show that the multimodal model is
more effective at identifying peptide candidates
than its predecessors.
"Cancer is extremely heterogeneous---which often makes it very hard to treat
effectively," says Kevin B. Givechian, PhD, an
MD-PhD student at Yale and co-first author on
the study. “We have built a deep-learning model
that integrates more information than had
previously been combined to help us improve
the identification of vaccine targets that
stimulate people's immune system against their
own tumor. Doing so would enable a more
effective and less toxic method of treatment."
ВАCKMAN, Isabella. Using Machine Learning to
Develop Personalized Vaccines for Cancer. Yale School
of Medicine, 24 fev. 2026. Acesso em: 28 june. 2026.
In the sentence "Cancer is extremely
heterogeneous," the adjective heterogeneous
suggests that cancer is:
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247246
Não definido
Texto associado
Read the text to answer question.
Using Machine Learning to Develop
Personalized Vaccines for Cancer
Yale researchers have developed a machine
learning model, called Immunostruct, that can
help scientists create more personalized
vaccines, including vaccines for cancer. They
described the tool in Nature Machine
Intelligence along with findings from applying
it to cancer and immunology data.
When a potential threat, such as a virus
or tumor, arises in our body, our immune cells
recognize peptides---essentially short
proteins---on the surface of the invader and
mount a defensive response. This small region
that the immune system interacts with is known
as an epitope.
Epitope-based vaccines are an emerging
technology that contain specific peptides in
order to trigger immune responses that
precisely target particular diseases. Ongoing
studies show that these vaccines are a
promising potential immunotherapy for a range
of cancers including melanomas, breast
cancers, and glioblastomas. Researchers are
also investigating whether these vaccines could
more effectively combat new variants of
infectious diseases.
To develop these vaccines, scientists
can use models that help them predict which
peptides are most likely to trigger a strong immune response to a particular antigen. A
limitation of many of these models, the
researchers say, is that they treat peptides as a
one-dimensional sequence of amino acids, not
the three-dimensional, active structures that
they are.
Now, Yale researchers have created a
model that also incorporates structural and
biochemical properties of peptides. In the new
study, they show that the multimodal model is
more effective at identifying peptide candidates
than its predecessors.
"Cancer is extremely heterogeneous---which often makes it very hard to treat
effectively," says Kevin B. Givechian, PhD, an
MD-PhD student at Yale and co-first author on
the study. “We have built a deep-learning model
that integrates more information than had
previously been combined to help us improve
the identification of vaccine targets that
stimulate people's immune system against their
own tumor. Doing so would enable a more
effective and less toxic method of treatment."
ВАCKMAN, Isabella. Using Machine Learning to
Develop Personalized Vaccines for Cancer. Yale School
of Medicine, 24 fev. 2026. Acesso em: 28 june. 2026.
The verb tense in "Yale researchers have
developed a machine learning model" is used
to indicate that:
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247247
Inglês
Texto associado
Read the text to answer question.
Using Machine Learning to Develop
Personalized Vaccines for Cancer
Yale researchers have developed a machine
learning model, called Immunostruct, that can
help scientists create more personalized
vaccines, including vaccines for cancer. They
described the tool in Nature Machine
Intelligence along with findings from applying
it to cancer and immunology data.
When a potential threat, such as a virus
or tumor, arises in our body, our immune cells
recognize peptides---essentially short
proteins---on the surface of the invader and
mount a defensive response. This small region
that the immune system interacts with is known
as an epitope.
Epitope-based vaccines are an emerging
technology that contain specific peptides in
order to trigger immune responses that
precisely target particular diseases. Ongoing
studies show that these vaccines are a
promising potential immunotherapy for a range
of cancers including melanomas, breast
cancers, and glioblastomas. Researchers are
also investigating whether these vaccines could
more effectively combat new variants of
infectious diseases.
To develop these vaccines, scientists
can use models that help them predict which
peptides are most likely to trigger a strong immune response to a particular antigen. A
limitation of many of these models, the
researchers say, is that they treat peptides as a
one-dimensional sequence of amino acids, not
the three-dimensional, active structures that
they are.
Now, Yale researchers have created a
model that also incorporates structural and
biochemical properties of peptides. In the new
study, they show that the multimodal model is
more effective at identifying peptide candidates
than its predecessors.
"Cancer is extremely heterogeneous---which often makes it very hard to treat
effectively," says Kevin B. Givechian, PhD, an
MD-PhD student at Yale and co-first author on
the study. “We have built a deep-learning model
that integrates more information than had
previously been combined to help us improve
the identification of vaccine targets that
stimulate people's immune system against their
own tumor. Doing so would enable a more
effective and less toxic method of treatment."
ВАCKMAN, Isabella. Using Machine Learning to
Develop Personalized Vaccines for Cancer. Yale School
of Medicine, 24 fev. 2026. Acesso em: 28 june. 2026.
Read the excerpt: "these vaccines could more
effectively combat new variants of infectious
diseases."
The modal verb "could" in this context primarily expresses:
The modal verb "could" in this context primarily expresses:
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247248
Linguística
Certain English words have the same spelling
but may function as different parts of speech
according to their stress pattern. Based on the
stressed syllable shown in bold, choose the
alternative in which both words are correctly
classified.
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247249
Inglês
Choose the option that completes the sentence
with the correct particle to form the appropriate
phrasal verb.
"Despite the initial tension between the two departments, the new employees managed to get ______ well with everyone during their first week."
"Despite the initial tension between the two departments, the new employees managed to get ______ well with everyone during their first week."
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247250
Inglês
Choose the option that completes the sentence
with the correct preposition of time.
"The annual shareholders' meeting is always held _______ the morning, so that international participants can join before their working day ends."
"The annual shareholders' meeting is always held _______ the morning, so that international participants can join before their working day ends."
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247251
Inglês
Choose the option that completes the sentence
with the correct article.
"During the selection process, the applicant proved to be _______ honest and competent professional."
"During the selection process, the applicant proved to be _______ honest and competent professional."
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247252
Pedagogia
An English teacher in the final years of
Elementary School organizes lessons around
real situations of language use. The teacher
proposes information gap activities,
simulations, and pair work in which students
have to negotiate meaning in order to complete
a task. The focus is on fluency and on the ability
to communicate meaningfully, and errors are
treated as a natural part of the process, without
interrupting the interaction.
This pedagogical practice is grounded in which language teaching approach or method?
This pedagogical practice is grounded in which language teaching approach or method?
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247253
Literatura
Mark the alternative that contains an incorrect
statement about literary movements and
authors.
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247254
Pedagogia
According to the National Education
Guidelines and Bases Law (LDB), regarding
special education, mark the correct alternative.
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247255
Inglês
Choose the option that completes the sentence
with the correct negative prefix.
"The candidate's argument was completely _________ relevant to the topic under discussion, so the committee decided to ignore it."
"The candidate's argument was completely _________ relevant to the topic under discussion, so the committee decided to ignore it."
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247256
Inglês
Choose the option that correctly completes the
sentence with the appropriate words, in the
order they appear.
"Our department will (1) the additional equipment, (2) the finance team approves the budget and the supplier sends the full (3) by the end of the week."
"Our department will (1) the additional equipment, (2) the finance team approves the budget and the supplier sends the full (3) by the end of the week."
Ano: 2026
Banca:
Avança SP
Órgão:
Prefeitura de Ubatuba - SP
Prova:
Avança SP - 2026 - Prefeitura de Ubatuba - SP - Professor da Educação Básica II - Inglês |
Q4247257
Inglês
Mark the alternative in which the conditional
sentence is grammatically correct.
Conheça nossos planos