bluuebunny/crossref_metadata_2025 huggingface dataset:
Violência e direito ao cuidado nas políticas públicas sobre instituições de longa permanência para idosos
Authors: Poltronieri Bruno Costa , Souza Edinilsa Ramos de , Ribeiro Adalgisa Peixoto
Published: August 2019

Esta pesquisa teve como objetivo estudar a inserção do tema da violência nas políticas brasileiras e do Rio de Janeiro que abordam as Instituições de Longa Permanência para Idosos (ILPIs). Realizou-se uma análise documental de políticas públicas direcionadas à população idosa ou que tratam do tema violência, tendo como marco inicial a Constituição de 1988. Nove políticas nacionais e duas do Rio de Janeiro foram identificadas e esse acervo foi submetido à análise de conteúdo. Constatou-se que as políticas concebem as ILPI de maneiras distintas, destinam-se a idosos sem vínculos familiares ou com esses vínculos fragilizados e não mencionam alternativas para o cuidado prolongado. O tema da violência é abordado de forma incipiente e pulverizada e aparece na forma de abandono, maus-tratos e violência institucional e estrutural.
Caracterização dos cursos de graduação em Obstetrícia em países da América do Sul
Authors: Cintra Nayara Ruiz , Riesco Maria Luiza Gonzalez
Published: August 2019

A Confederação Internacional de Obstetrizes estabelece diretrizes para a formação desse profissional globalmente. O objetivo da pesquisa foi caracterizar os cursos de Obstetrícia de entrada direta e instituições de ensino superior que os oferecem, na América do Sul. Realizou-se pesquisa documental descritivo-exploratória. Foram identificados 75 cursos, oferecidos em universidades da Argentina, Brasil, Chile, Equador, Paraguai, Peru e Uruguai. Todos exigem prova ou curso preparatório para ingresso. A carga horária varia de 3.322 a nove mil horas e a duração é de oito a 12 semestres. Majoritariamente, denominam-se Curso de Obstetrícia e outorgam o grau acadêmico de licenciado ou bacharel e o título profissional de obstetriz/obstetra ou matrona / matrón . Há grande heterogeneidade com relação a visão, missão e perfil do egresso. Existe similaridade na estrutura curricular. Os conteúdos curriculares enfatizam as ciências biológicas, os conhecimentos aplicados à Obstetrícia, as atividades práticas e os estágios.
Mulheres trans e atividade física: fabricando o corpo feminino
Authors: Serrano Jéssica Leite , Caminha Iraquitan de Oliveira , Gomes Isabelle Sena , Neves Ednalva Maciel , Lopes Diego Trindade
Published: August 2019

Este estudo discute a relação entre atividade física e o processo de “fabricação” do corpo feminino por mulheres transexuais. Colaboraram com a pesquisa dez mulheres trans, que responderam um questionário socioeconômico e participaram de entrevista semiestruturada. As informações obtidas foram analisadas com base na proposta fenomenológica de Bicudo1. Os relatos apontam que algumas mulheres trans praticam atividade física buscando o ganho de massa corporal na região dos glúteos e pernas e a definição do abdômen. Aquelas que não praticam alegam ter medo de masculinizar o corpo e/ou não frequentam academias por causa dos preconceitos sofridos.
RELATIONSHIP AMONG PSYCHOLOGICAL WELL-BEING, RESILIENCE AND COPING WITH SOCIAL AND CLINICAL FEATURES IN CROHN’S DISEASE PATIENTS
Authors: ACCIARI Arlete Silva , LEAL Raquel Franco , COY Cláudio Saddy Rodrigues , DIAS Cristiana Corrrêa , AYRIZONO Maria de Lourdes Setsuko
Published: August 2019

ABSTRACT BACKGROUND: Crohn’s disease is chronic, requires prolonged treatment, affects the physical and psychosocial health of patients and may alter their routine, quality of life and well-being. Recent studies recommend monitoring the health of these patients considering physical, psychological and psychosocial aspects, because they are directly related to the disease activity. These studies highlight the relevance of patients’ emotional and behavioral conditions and suggest that the identification of the factors that influence the psychological well-being, resilience and Coping in these patients can favor the proper treatment. OBJECTIVE: To relate psychological well-being, resilience and Coping with social and clinical features of Crohn’s disease patients. METHODS: Prospective study including 104 patients with Crohn’s disease, both genders and mean age of 39 years. Standardized scales were used to assess and to relate psychological well-being, resilience and Coping with social and clinical variables. A questionnaire to characterize the sample and standardized scales in data collection (psychological well-being, resilience pillars and Coping strategies inventory - Folkman & Lazarus) were used. Descriptive analysis of data and statistics for comparison of results were performed. RESULTS: There were significant differences (P<0.05) showing better psychological well-being for male patients, those who without children, were not religious, were employed and were doing complementary activities in addition to clinical treatment. More resilience for the male gender, those who without children, were not religious, divorced, separated or widowed, that received some monthly income; who did not undergo surgery, had the first symptoms after 30 years old and who had complementary activity. There were also significant differences in the use of Coping: usually, women used more developed escape and avoidance strategies; single, married or in stable-union patients used more self-control; not religious used positive revaluation strategy; the ones who were employed showed more self-control and positive reassessment; the ones who had lower family income indicated that they used less the self-control; the ones who had higher family income used more positive re-evaluation; patients who were diagnosed with Crohn’s disease between the second decade of life showed to use mores more the positive reassessment strategy than those who were 20 years old or younger. CONCLUSION: Social aspects influenced psychological well-being, resilience and Coping in patients with Crohn’s disease more strongly than clinical aspects. It was possible to identify the profiles with better and worse psychological well-being, resilience and Coping of those who need more support, as well as to know the most used Coping strategies in the studied group.
HLA-DRB1 GENE POLYMORPHISMS IN PEDIATRIC PATIENTS WITH TYPE 1 AUTOIMMUNE HEPATITIS AND TYPE 1 AUTOIMMUNE HEPATITIS OVERLAP SYNDROME WITH AUTOIMMUNE CHOLANGITIS
Authors: NUNES Monique Ellen Gervásio , ROSA Daniela Valadão , FAGUNDES Eleonora Druve Tavares , FERREIRA Alexandre Rodrigues , MIRANDA Débora Marques de , FERRI LIU Priscila Menezes
Published: August 2019

ABSTRACT BACKGROUND: Autoimmune hepatitis (AIH) is a rare chronic inflammatory liver disease associated with a loss of immunological tolerance to self-antigens. Susceptibility to AIH is partially determined by the presence of genes related to human leukocyte antigen (HLA), mainly allelic variants of DRB1. OBJECTIVE: The purpose of this study was to investigate the frequencies of the polymorphisms in HLA-DRB1 gene in children and adolescents with type 1 AIH and type 1 AIH overlap syndrome with autoimmune cholangitis (overlap syndrome, OS) in comparison to healthy sex and age-matched individuals (control group). METHODS: This is a cross-sectional study of 25 pediatric patients diagnosed with type 1 AIH and 18 with OS. Fifty-seven healthy individuals were included as controls. The polymorphisms of the HLA-DRB1 gene were evaluated by PCR and included HLA-DRB1*03, HLA-DRB1*04, HLA-DRB1*07, and HLA-DRB1*13. RESULTS: Our results showed that the presence of the allele HLA-DRB1*13 increased the chance of autoimmune cholangitis (OR=3.96, CI 1.07 to 14.61, P=0.04). The HLA-DRB1*04 and HLA- DRB1*07 have no association with the AIH and autoimmune cholangitis in a young sample. CONCLUSION: This work demonstrates an association of the main polymorphisms in the HLA-DRB1 gene to AIH with or without cholangitis in a Brazilian sample.
PROSPECTIVE STUDY FOR VALIDATION OF A SINGLE PROTOCOL FOR THE 13C-UREA BREATH TEST USING TWO DIFFERENT DEVICES IN THE DIAGNOSIS OF H. PYLORI INFECTION
Authors: COELHO Luiz Gonzaga Vaz , TRINDADE Osmar Reni , LEÃO Laiane Alves , RIBEIRO Henrique Gomes , FREITAS Izabella Silva , COELHO Maria Clara Freitas
Published: August 2019

ABSTRACT BACKGROUND: 13C-urea breath test (UBT) is the gold-standard, noninvasive method for H. pylori diagnosis. However, there is no uniform standardization of the test. This situation can be unpractical for laboratories running with two or more devices. OBJECTIVE: To perform a prospective comparison validation study of UBT employing one validated protocol for two different devices: BreathID Hp Lab System® (Exalenz Bioscience Ltd, Israel), here called device A and IRIS-Doc2® (Wagner Analysen-Technik, Germany, now Mayoly Spindler Group, France), here called device B, in the diagnosis of H. pylori infection. METHODS: A total of 518 consecutive patients (365 females, 153 males, mean age 53 years) referred for UBT were included. All patients received device A protocol as follow: after at least one hour fasting, patients filled two bags prior to the test, then ingested an aqueous solution containing 75 mg of 13C-urea with a 4.0 g citric acid powder and filled another two bags 15 min after ingesting the test solution. One pair of breath sample bags (before and after ingestion) was analyzed by the two different devices. A delta over baseline (DOB) ≥5‰ indicated H. pylori infection. Statistics: Wilcoxon test, kappa coefficient with 95% CI, Wilson’s method. RESULTS: Considering the device A protocol as the gold standard, its comparison with device B showed a sensitivity of 99.3% (95% CI: 96.3-99.9) and a specificity of 98.9% (95% CI: 97.3-99.6). Kappa coefficient was 0.976 (95% IC: 0.956-0.997). CONCLUSION: Correlation between the two devices was excellent and supports a uniform standardization of UBT.
HISTORICAL PERSPECTIVE OF GASTROESOPHAGEAL REFLUX DISEASE CLINICAL TREATMENT
Authors: ZATERKA Schlioma , MARION Sandra Beatriz , ROVEDA Fabiana , PERROTTI Marcos Antônio , CHINZON Decio
Published: August 2019

ABSTRACT BACKGROUND: Gastroesophageal reflux disease (GERD) is one of the most prevalent gastrointestinal diseases. GERD generates significant impairment in patients’ quality of life and it is associated to relevant medical resources utilization. A better understanding of GERD pathophysiology in the past five decades has favored the evolution of therapeutic strategies from non-drug interventions and antacids to more efficacious and safer alternatives. OBJECTIVE: To summarize data about the historical evolution of GERD management in Brazil, focusing on medical therapy and addressing evidence on efficacy and safety of drug classes currently recommended. METHODS: A narrative review was conducted by systematizing information about discoveries on GERD pathophysiology. We also addressed efficacy and safety of medications currently used to reduce symptoms and improve endoscopic healing of esophageal lesions. A structured search on Pubmed was performed to identify systematic reviews and meta-analysis investigating GERD outcomes positively impacted by proton pump inhibitors (PPIs), the first choice of pharmacotherapy for the disease. RESULTS: The chronological development of therapeutic measures for GERD in Brazil evolved from lifestyle interventions with relative poor effect on symptoms related to esophageal acid exposure, particularly heartburn, to effective and safe pharmacological interventions such as histamine H2-receptor antagonists and PPIs. In the present days, some drug classes play a minor role in disease management, namely prokinetics and antacids, due to their reduced efficacy and relevant safety concerns (particularly with prokinetics). The main challenge for prescribers and researchers seems to be finding long-acting acid suppressants strategies able to ameliorate patients’ symptoms and quality of life, thereafter, reducing medical resource consumption. The dual delayed-release PPI dexlansoprazole seems to respond for some of the limitations other PPIs have. CONCLUSION: Recognizing the historical evolution of GERD management can help care providers to better understand therapeutic options for their patients, as well as focus on unmet needs that deserve further attention. PPIs are still the first choice therapy, with good evidence in favor of their efficacy, despite some safety concerns. However, as with any medical intervention, it is recommended to prescribe PPIs for patients with clear indication, using adequate dosing and monitoring for adverse events.
RECOMMENDATIONS FOR INVASIVE PROCEDURES IN PATIENTS WITH DISEASES OF THE LIVER AND BILIARY TRACT: REPORT OF A JOINT MEETING OF THE BRAZILIAN SOCIETY OF HEPATOLOGY (SBH), BRAZILIAN SOCIETY OF DIGESTIVE ENDOSCOPY (SOBED) AND BRAZILIAN SOCIETY OF INTERVENTIONAL RADIOLOGY AND ENDOVASCULAR SURGERY (SOBRICE)
Authors: SCHIAVON Leonardo de Lucca , EJIMA Flávio Hayato , MENEZES Marcos Roberto de , BITTENCOURT Paulo Lisboa , MOREIRA Aírton Mota , FARIAS Alberto Queiroz , CHAGAS Aline Lopes , ASSIS André Moreira de , MATTOS Ângelo Zambam de , SALOMÃO Bruno Chaves , TERRA Carlos , MARTINS Fernanda Prata Borges , CARNEVALE Francisco Cesar , REZENDE Guilherme Ferreira da Motta , PAULO Gustavo Andrade de , PEREIRA Gustavo Henrique Santos , MOTTA-LEAL-FILHO Joaquim Maurício da , MENESES Juliana de , COSTA Lucas Santana Nova da , CARNEIRO Marcos de Vasconcelos , ÁLVARES-DA-SILVA Mário Reis , SOARES Mayra Veloso Ayrimoraes , PEREIRA Osvaldo Ignácio , XIMENES Rafael Oliveira , DURANTE Renata Filardi Simiqueli , FERREIRA Valério Alves , LIMA Vinícius Machado de
Published: August 2019

ABSTRACT Liver and biliary tract diseases are common causes of morbidity and mortality worldwide. Invasive procedures are usually performed in those patients with hepatobiliary diseases for both diagnostic and therapeutic purposes. Defining proper indications and restraints of commonly used techniques is crucial for proper patient selection, maximizing positive results and limiting complications. In 2018, the Brazilian Society of Hepatology (SBH) in cooperation with the Brazilian Society of Interventional Radiology and Endovascular surgery (SOBRICE) and the Brazilian Society of Digestive Endoscopy (SOBED) sponsored a joint single-topic meeting on invasive procedures in patients with hepatobiliary diseases. This paper summarizes the proceedings of the aforementioned meeting. It is intended to guide clinicians, gastroenterologists, hepatologists, radiologists, and endoscopists for the proper use of invasive procedures for management of patients with hepatobiliary diseases.
Nitrificação de águas amarelas em leito percolante de areia
Authors: Ferreira Ewson Andrade , Coura Mônica de Amorim , Oliveira Rui de , Meira Celeide Maria Belmont Sabino , Rodrigues Andrea Carla Lima
Published: August 2019

RESUMO O esgotamento sanitário ecológico conscientiza a população sobre a importância do reúso da água com maior eficiência e do uso de efluentes de sistemas de tratamento descentralizados. O presente trabalho descreve os resultados da nitrificação de águas amarelas em reator biológico com a utilização de materiais simples, por exemplo, a areia, como suporte, objetivando tornar esses resíduos líquidos disponíveis para aproveitamento do nitrogênio mineralizado na agricultura sustentável. O monitoramento do sistema foi realizado por meio dos indicadores pH, oxigênio dissolvido (OD), alcalinidade total (ALC), demanda química de oxigênio (DQO), nitrogênio total Kjeldahl (NTK), nitrogênio amoniacal (NA), nitrito (NO- 2) e nitrato (NO- 3). O sistema apresentou boa remoção de matéria orgânica e excelente conversão do nitrogênio para NO- 2 e NO- 3, com eficiência de transformação do NTK para NO- 3 da ordem de 93%.
A Task in a Suit and a Tie: Paraphrase Generation with Semantic Augmentation
Authors: Wang Su , Gupta Rahul , Chang Nancy , Baldridge Jason
Published: August 2019

Paraphrasing is rooted in semantics. We show the effectiveness of transformers (Vaswani et al. 2017) for paraphrase generation and further improvements by incorporating PropBank labels via a multi-encoder. Evaluating on MSCOCO and WikiAnswers, we find that transformers are fast and effective, and that semantic augmentation for both transformers and LSTMs leads to sizable 2-3 point gains in BLEU, METEOR and TER. More importantly, we find surprisingly large gains on human evaluations compared to previous models. Nevertheless, manual inspection of generated paraphrases reveals ample room for improvement: even our best model produces human-acceptable paraphrases for only 28% of captions from the CHIA dataset (Sharma et al. 2018), and it fails spectacularly on sentences from Wikipedia. Overall, these results point to the potential for incorporating semantics in the task while highlighting the need for stronger evaluation.
Transferable Interactive Memory Network for Domain Adaptation in Fine-Grained Opinion Extraction
Authors: Wang Wenya , Pan Sinno Jialin
Published: August 2019

In fine-grained opinion mining, aspect and opinion terms extraction has become a fundamental task that provides key information for user-generated texts. Despite its importance, a lack of annotated resources in many domains impede the ability to train a precise model. Very few attempts have applied unsupervised domain adaptation methods to transfer fine-grained knowledge (in the word level) from some labeled source domain(s) to any unlabeled target domain. Existing methods depend on the construction of “pivot” knowledge, e.g., common opinion terms or syntactic relations between aspect and opinion words. In this work, we propose an interactive memory network that consists of local and global memory units. The model could exploit both local and global memory interactions to capture intra-correlations among aspect words or opinion words themselves, as well as the interconnections between aspect and opinion words. The source space and the target space are aligned through these domaininvariant interactions by incorporating an auxiliary task and domain adversarial networks. The proposed model does not require any external resources and demonstrates promising results on 3 benchmark datasets.
Improving Natural Language Inference Using External Knowledge in the Science Questions Domain
Authors: Wang Xiaoyan , Kapanipathi Pavan , Musa Ryan , Yu Mo , Talamadupula Kartik , Abdelaziz Ibrahim , Chang Maria , Fokoue Achille , Makni Bassem , Mattei Nicholas , Witbrock Michael
Published: August 2019

Natural Language Inference (NLI) is fundamental to many Natural Language Processing (NLP) applications including semantic search and question answering. The NLI problem has gained significant attention due to the release of large scale, challenging datasets. Present approaches to the problem largely focus on learning-based methods that use only textual information in order to classify whether a given premise entails, contradicts, or is neutral with respect to a given hypothesis. Surprisingly, the use of methods based on structured knowledge – a central topic in artificial intelligence – has not received much attention vis-a-vis the NLI problem. While there are many open knowledge bases that contain various types of reasoning information, their use for NLI has not been well explored. To address this, we present a combination of techniques that harness external knowledge to improve performance on the NLI problem in the science questions domain. We present the results of applying our techniques on text, graph, and text-and-graph based models; and discuss the implications of using external knowledge to solve the NLI problem. Our model achieves close to state-of-the-art performance for NLI on the SciTail science questions dataset.
A Deep Reinforcement Learning Based Multi-Step Coarse to Fine Question Answering (MSCQA) System
Authors: Wang Yu , Jin Hongxia
Published: August 2019

In this paper, we present a multi-step coarse to fine question answering (MSCQA) system which can efficiently processes documents with different lengths by choosing appropriate actions. The system is designed using an actor-critic based deep reinforcement learning model to achieve multistep question answering. Compared to previous QA models targeting on datasets mainly containing either short or long documents, our multi-step coarse to fine model takes the merits from multiple system modules, which can handle both short and long documents. The system hence obtains a much better accuracy and faster trainings speed compared to the current state-of-the-art models. We test our model on four QA datasets, WIKEREADING, WIKIREADING LONG, CNN and SQuAD, and demonstrate 1.3%-1.7% accuracy improvements with 1.5x-3.4x training speed-ups in comparison to the baselines using state-of-the-art models.
When Do Words Matter? Understanding the Impact of Lexical Choice on Audience Perception Using Individual Treatment Effect Estimation
Authors: Wang Zhao , Culotta Aron
Published: August 2019

Studies across many disciplines have shown that lexical choice can affect audience perception. For example, how users describe themselves in a social media profile can affect their perceived socio-economic status. However, we lack general methods for estimating the causal effect of lexical choice on the perception of a specific sentence. While randomized controlled trials may provide good estimates, they do not scale to the potentially millions of comparisons necessary to consider all lexical choices. Instead, in this paper, we first offer two classes of methods to estimate the effect on perception of changing one word to another in a given sentence. The first class of algorithms builds upon quasi-experimental designs to estimate individual treatment effects from observational data. The second class treats treatment effect estimation as a classification problem. We conduct experiments with three data sources (Yelp, Twitter, and Airbnb), finding that the algorithmic estimates align well with those produced by randomized-control trials. Additionally, we find that it is possible to transfer treatment effect classifiers across domains and still maintain high accuracy.
Improving Distantly Supervised Relation Extraction with Neural Noise Converter and Conditional Optimal Selector
Authors: Wu Shanchan , Fan Kai , Zhang Qiong
Published: August 2019

Distant supervised relation extraction has been successfully applied to large corpus with thousands of relations. However, the inevitable wrong labeling problem by distant supervision will hurt the performance of relation extraction. In this paper, we propose a method with neural noise converter to alleviate the impact of noisy data, and a conditional optimal selector to make proper prediction. Our noise converter learns the structured transition matrix on logit level and captures the property of distant supervised relation extraction dataset. The conditional optimal selector on the other hand helps to make proper prediction decision of an entity pair even if the group of sentences is overwhelmed by no-relation sentences. We conduct experiments on a widely used dataset and the results show significant improvement over competitive baseline methods.
Adaptive Region Embedding for Text Classification
Authors: Xiang Liuyu , Jin Xiaoming , Yi Lan , Ding Guiguang
Published: August 2019

Deep learning models such as convolutional neural networks and recurrent networks are widely applied in text classification. In spite of their great success, most deep learning models neglect the importance of modeling context information, which is crucial to understanding texts. In this work, we propose the Adaptive Region Embedding to learn context representation to improve text classification. Specifically, a metanetwork is learned to generate a context matrix for each region, and each word interacts with its corresponding context matrix to produce the regional representation for further classification. Compared to previous models that are designed to capture context information, our model contains less parameters and is more flexible. We extensively evaluate our method on 8 benchmark datasets for text classification. The experimental results prove that our method achieves state-of-the-art performances and effectively avoids word ambiguity.
Quantifying Uncertainties in Natural Language Processing Tasks
Authors: Xiao Yijun , Wang William Yang
Published: August 2019

Reliable uncertainty quantification is a first step towards building explainable, transparent, and accountable artificial intelligent systems. Recent progress in Bayesian deep learning has made such quantification realizable. In this paper, we propose novel methods to study the benefits of characterizing model and data uncertainties for natural language processing (NLP) tasks. With empirical experiments on sentiment analysis, named entity recognition, and language modeling using convolutional and recurrent neural network models, we show that explicitly modeling uncertainties is not only necessary to measure output confidence levels, but also useful at enhancing model performances in various NLP tasks.
End-to-End Knowledge-Routed Relational Dialogue System for Automatic Diagnosis
Authors: Xu Lin , Zhou Qixian , Gong Ke , Liang Xiaodan , Tang Jianheng , Lin Liang
Published: August 2019

Beyond current conversational chatbots or task-oriented dialogue systems that have attracted increasing attention, we move forward to develop a dialogue system for automatic medical diagnosis that converses with patients to collect additional symptoms beyond their self-reports and automatically makes a diagnosis. Besides the challenges for conversational dialogue systems (e.g. topic transition coherency and question understanding), automatic medical diagnosis further poses more critical requirements for the dialogue rationality in the context of medical knowledge and symptom-disease relations. Existing dialogue systems (Madotto, Wu, and Fung 2018; Wei et al. 2018; Li et al. 2017) mostly rely on datadriven learning and cannot be able to encode extra expert knowledge graph. In this work, we propose an End-to-End Knowledge-routed Relational Dialogue System (KR-DS) that seamlessly incorporates rich medical knowledge graph into the topic transition in dialogue management, and makes it cooperative with natural language understanding and natural language generation. A novel Knowledge-routed Deep Q-network (KR-DQN) is introduced to manage topic transitions, which integrates a relational refinement branch for encoding relations among different symptoms and symptomdisease pairs, and a knowledge-routed graph branch for topic decision-making. Extensive experiments on a public medical dialogue dataset show our KR-DS significantly beats stateof-the-art methods (by more than 8% in diagnosis accuracy). We further show the superiority of our KR-DS on a newly collected medical dialogue system dataset, which is more challenging retaining original self-reports and conversational data between patients and doctors.
Exploring Human-Like Reading Strategy for Abstractive Text Summarization
Authors: Yang Min , Qu Qiang , Tu Wenting , Shen Ying , Zhao Zhou , Chen Xiaojun
Published: August 2019

The recent artificial intelligence studies have witnessed great interest in abstractive text summarization. Although remarkable progress has been made by deep neural network based methods, generating plausible and high-quality abstractive summaries remains a challenging task. The human-like reading strategy is rarely explored in abstractive text summarization, which however is able to improve the effectiveness of the summarization by considering the process of reading comprehension and logical thinking. Motivated by the humanlike reading strategy that follows a hierarchical routine, we propose a novel Hybrid learning model for Abstractive Text Summarization (HATS). The model consists of three major components, a knowledge-based attention network, a multitask encoder-decoder network, and a generative adversarial network, which are consistent with the different stages of the human-like reading strategy. To verify the effectiveness of HATS, we conduct extensive experiments on two real-life datasets, CNN/Daily Mail and Gigaword datasets. The experimental results demonstrate that HATS achieves impressive results on both datasets.
Plan-and-Write: Towards Better Automatic Storytelling
Authors: Yao Lili , Peng Nanyun , Weischedel Ralph , Knight Kevin , Zhao Dongyan , Yan Rui
Published: August 2019

Automatic storytelling is challenging since it requires generating long, coherent natural language to describes a sensible sequence of events. Despite considerable efforts on automatic story generation in the past, prior work either is restricted in plot planning, or can only generate stories in a narrow domain. In this paper, we explore open-domain story generation that writes stories given a title (topic) as input. We propose a plan-and-write hierarchical generation framework that first plans a storyline, and then generates a story based on the storyline. We compare two planning strategies. The dynamic schema interweaves story planning and its surface realization in text, while the static schema plans out the entire storyline before generating stories. Experiments show that with explicit storyline planning, the generated stories are more diverse, coherent, and on topic than those generated without creating a full plan, according to both automatic and human evaluations.
ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networks
Authors: Yasunaga Michihiro , Kasai Jungo , Zhang Rui , Fabbri Alexander R. , Li Irene , Friedman Dan , Radev Dragomir R.
Published: August 2019

Scientific article summarization is challenging: large, annotated corpora are not available, and the summary should ideally include the article’s impacts on research community. This paper provides novel solutions to these two challenges. We 1) develop and release the first large-scale manually-annotated corpus for scientific papers (on computational linguistics) by enabling faster annotation, and 2) propose summarization methods that integrate the authors’ original highlights (abstract) and the article’s actual impacts on the community (citations), to create comprehensive, hybrid summaries. We conduct experiments to demonstrate the efficacy of our corpus in training data-driven models for scientific paper summarization and the advantage of our hybrid summaries over abstracts and traditional citation-based summaries. Our large annotated corpus and hybrid methods provide a new framework for scientific paper summarization research.
Data Augmentation for Spoken Language Understanding via Joint Variational Generation
Authors: Yoo Kang Min , Shin Youhyun , Lee Sang-goo
Published: August 2019

Data scarcity is one of the main obstacles of domain adaptation in spoken language understanding (SLU) due to the high cost of creating manually tagged SLU datasets. Recent works in neural text generative models, particularly latent variable models such as variational autoencoder (VAE), have shown promising results in regards to generating plausible and natural sentences. In this paper, we propose a novel generative architecture which leverages the generative power of latent variable models to jointly synthesize fully annotated utterances. Our experiments show that existing SLU models trained on the additional synthetic examples achieve performance gains. Our approach not only helps alleviate the data scarcity issue in the SLU task for many datasets but also indiscriminately improves language understanding performances for various SLU models, supported by extensive experiments and rigorous statistical testing.
DRr-Net: Dynamic Re-Read Network for Sentence Semantic Matching
Authors: Zhang Kun , Lv Guangyi , Wang Linyuan , Wu Le , Chen Enhong , Wu Fangzhao , Xie Xing
Published: August 2019

Sentence semantic matching requires an agent to determine the semantic relation between two sentences, which is widely used in various natural language tasks such as Natural Language Inference (NLI) and Paraphrase Identification (PI). Among all matching methods, attention mechanism plays an important role in capturing the semantic relations and properly aligning the elements of two sentences. Previous methods utilized attention mechanism to select important parts of sentences at one time. However, the important parts of the sentence during semantic matching are dynamically changing with the degree of sentence understanding. Selecting the important parts at one time may be insufficient for semantic understanding. To this end, we propose a Dynamic Re-read Network (DRr-Net) approach for sentence semantic matching, which is able to pay close attention to a small region of sentences at each step and re-read the important words for better sentence semantic understanding. To be specific, we first employ Attention Stack-GRU (ASG) unit to model the original sentence repeatedly and preserve all the information from bottom-most word embedding input to up-most recurrent output. Second, we utilize Dynamic Re-read (DRr) unit to pay close attention to one important word at one time with the consideration of learned information and re-read the important words for better sentence semantic understanding. Extensive experiments on three sentence matching benchmark datasets demonstrate that DRr-Net has the ability to model sentence semantic more precisely and significantly improve the performance of sentence semantic matching. In addition, it is very interesting that some of finding in our experiments are consistent with the findings of psychological research.
Plan-Length Bounds: Beyond 1-Way Dependency
Authors: Abdulaziz Mohammad
Published: August 2019

We consider the problem of compositionally computing upper bounds on lengths of plans. Following existing work, our approach is based on a decomposition of state-variable dependency graphs (a.k.a. causal graphs). Tight bounds have been demonstrated previously for problems where key dependencies flow in a single direction—i.e. manipulating variable v1 can disturb the ability to manipulate v2 and not vice versa. We develop a more general bounding approach which allows us to compute useful bounds where dependency flows in both directions. Our approach is practically most useful when combined with earlier approaches, where the computed bounds are substantially improved in a relatively broad variety of problems. When combined with an existing planning procedure, the improved bounds yield coverage improvements for both solvable and unsolvable planning problems.
Bringing Order to Chaos – A Compact Representation of Partial Order in SAT-Based HTN Planning
Authors: Behnke Gregor , Höller Daniel , Biundo Susanne
Published: August 2019

HTN planning provides an expressive formalism to model complex application domains. It has been widely used in realworld applications. However, the development of domainindependent planning techniques for such models is still lacking behind. The need to be informed about both statetransitions and the task hierarchy makes the realisation of search-based approaches difficult, especially with unrestricted partial ordering of tasks in HTN domains. Recently, a translation of HTN planning problems into propositional logic has shown promising empirical results. Such planners benefit from a unified representation of state and hierarchy, but until now require very large formulae to represent partial order. In this paper, we introduce a novel encoding of HTN Planning as SAT. In contrast to related work, most of the reasoning on ordering relations is not left to the SAT solver, but done beforehand. This results in much smaller formulae and, as shown in our evaluation, in a planner that outperforms previous SAT-based approaches as well as the state-of-the-art in search-based HTN planning.
PERFIL CLÍNICO E SOCIODEMOGRÁFICO DE FREQUENTADORES DE UMA ACADEMIA PARQUE DO MUNICÍPIO DE MATA DE SÃO JOÃO – BAHIA
Authors: Góes Camila Graciele Santos , Bêribá Lay Martinez Silva
Published: August 2019

Introdução A promoção de saúde no contexto do SUS busca desenvolver políticas de incentivo à atividade física e práticas corporais com o intuito de inserir essa rotina no cotidiano do cidadão. A partir dessa concepção, surgiu o Programa Academia da Saúde (PAS) como uma estratégia de integração de ações de saúde pública na Atenção Primária, baseado no reconhecimento da relevância epidemiológica do sedentarismo como um fator de risco para a aquisição de doenças e agravos à saúde.  Objetivo Caracterizar o perfil clínico e sociodemográfico, analisar a autopercepção da qualidade de vida e prontidão para a prática de atividade física de frequentadores de uma Academia Parque do município de Mata de São João-Bahia. Materiais e métodos Trata-se de um estudo transversal descritivo, em que a participação consistiu em responder questionários destinados ao conhecimento clínico e sociodemográfico (elaborado pelas autoras), de qualidade de vida (SF-36) e prontidão para a prática de atividade física (PAR-Q) após assinatura do TCLE. Para análise das variáveis foram utilizadas além da estatística descritiva, média e desvio padrão, o cálculo da frequência absoluta e relativa. Resultados Participaram do estudo um total de 35 frequentadores da Academia Parque, com a média de idade de 47,3±10,8 anos e predominância do gênero feminino (94,2%). Clinicamente, a doença sistêmica mais citada foi a hipertensão arterial (45,7%) e a de aspecto físico mais comum àqueles que relataram possuir comorbidades foi a artrose (50%). Observou-se ainda, elevada prevalência de consumo diário de medicamentos (74,2%). Conclusão O perfil da Academia Parque é composto em sua maioria por mulheres, com média escolaridade, com a HAS como patologia prevalente, cujo motivo para a busca do serviço foi a preocupação com a saúde. Segundo o PAR-Q, os indivíduos apresentavam aptidão para praticar atividade física, embora comorbidades de aspecto físico tenham sido observadas e, conforme o questionário SF-36, a dor, a capacidade funcional e a limitação por aspectos físicos foram fatores de maior impacto na qualidade de vida.                                                         Palavras-chave: Promoção da saúde. Atividade física. Estudo sociodemográfico e clínico. Qualidade de Vida. Academia Parque.
O SIGNIFICADO DO ACIDENTE VASCULAR ENCEFÁLICO: A VIDA CONTINUA
Authors: Guarizi Rubia Hiromi Guibo , Schmitt Ana CArolina Basso
Published: August 2019

O acidente vascular encefálico está entre as principais causas de mortalidade e incapacidades, gerando mudanças no padrão de vida. Assim, a análise auto-perceptiva sobre a saúde é importante para aprimorar ações e cuidados dos profissionais. O objetivo foi conhecer o significado das sequelas do acidente vascular encefálico para pessoas acometidas. Por metodologia quali-quantitativa, foi avaliada a representatividade social em 27 pessoas acompanhadas pela Saúde da Família de uma cidade do interior paulista, Brasil, que tiveram a doença. A organização e análise dos dados dos discursos foram de acordo com o recurso metodológico do Discurso do Sujeito Coletivo, a partir das expressões-chave, ideias centrais e ancoragens com o software QualiQuantiSoft. As ideias mais prevalentes foram: dificuldades com as sequelas físicas, emocionais e sociais além da dependência de cuidados para as tarefas diárias. Para os homens houve transformação de vida por não poderem mais trabalhar, fazendo-os “o novo dono de casa”; para elas, por não serem mais capazes de cuidar dos serviços domésticos. Entretanto, as pessoas avaliadas são otimistas com o futuro. Desta forma, cabe aos profissionais de saúde, especialmente o fisioterapeuta, que considerem os significados além da clínica para as pessoas que tiveram o acidente vascular encefálico no seu trabalho de cuidado.
A SAÚDE COLETIVA NAS PRÁTICAS EDUCACIONAIS DOS FISIOTERAPEUTAS DOCENTES DO CURSO DE FISIOTERAPIA DA UNIVERSIDADE DO ESTADO DO PARÁ
Authors: Teixeira Renato Da Costa , Reis Viviane Da Costa
Published: August 2019

Objetivo: Este estudo se propôs a investigar a aproximação das práticas educacionais dos fisioterapeutas docentes do curso de Fisioterapia da Universidade do Estado do Pará com a saúde coletiva. Método: Tratou-se de um estudo descritivo com abordagem qualitativa e quantitativa, realizado em duas etapas. A etapa 1 foi realizada através de um questionário para se buscar a afinidade deste docente com a saúde coletiva. A etapa 2 constou de entrevistas e buscou aprofundar o conhecimento dos docentes sobre o tema. Os resultados quantitativos expressaram o perfil dos docentes. Os dados qualitativos foram analisados pela análise de conteúdo de Bardin. Resultados: Responderam ao questionário 27 docentes e foram entrevistados seis docentes escolhidos aleatoriamente. Dentre os que responderam ao questionário, 16 eram do sexo feminino, tem mestrado, a idade media é de 41,77 anos, tem em média 14,77 anos de docência, desenvolvem ou desenvolveram pesquisa (96%) e extensão (81,5%), trabalham em ambulatórios e hospitais públicos e atuam na área de traumato-ortopedia, cardiorrespiratória e neurofuncional. Quanto às entrevistas, os participantes demonstraram conhecer os conceitos de saúde, entendem a importância da relação da fisioterapia com a saúde coletiva e suas limitações, porém não associam a saúde coletiva com as disciplinas que ministram, evidenciando afastamento das suas práticas educacionais com a saúde coletiva. Conclusão: As práticas educacionais dos docentes investigados não são associadas a saúde coletiva, enfraquecendo o modelo de formação, portanto é preocupante para a formação dos futuros profissionais o afastamento evidenciado nas falas dos docentes.
FISIOTERAPIA E SAÚDE COLETIVA: UMA ANÁLISE CRITICA DA PRODUÇÃO CIENTÍFICA NO BRASIL
Authors: Pessoa da Silva Carolina Veras , Almeida Milena Maria Cordeiro de
Published: August 2019

Introdução: A sistematização crítica dos saberes e práticas da atuação da fisioterapia na Saúde Coletiva (SC) pode contribuir para uma transformação da atuação profissional, extrapolando as práticas tradicionais de reabilitação e ampliando o interesse dos profissionais de Fisioterapia por esse campo. Desenvolvimento: revisão de literatura com o objetivo de realizar uma análise crítica da produção científica no Brasil sobre a Fisioterapia e a Saúde Coletiva. A busca foi realizada nas bases de dados Bireme, Scielo e Lilacs utilizando os descritores “Fisioterapia” and “Saúde Coletiva”, selecionando-se 14 publicações. Foram encontradas um maior número de publicações em 2011, com maior predomínio na região Sudeste e atuação na Atenção Básica. Os estudos foram discutidos nos seguintes eixos: 1) Formação para Saúde Coletiva ou Saúde Pública; 2) Integralidade nas práticas da Fisioterapia e Saúde Coletiva; 3) Interdisciplinaridade nas práticas da Fisioterapia e Saúde Coletiva. Considerações finais: A produção científica da Fisioterapia na SC cresceu nos últimos anos, mas de forma incipiente comparada a outras áreas de atuação. Os estudos estão concentrados nas práticas assistenciais, sem extrapolar para uma reflexão crítica sobre os pressupostos do campo. Percebe-se uma dificuldade na realização de práticas integrais e interdisciplinares, devido a desarticulação da formação profissional com a prática em saúde, reafirmando a necessidade de aproximação da fisioterapia a SC, para que os profissionais estejam capacitados para contribuir na construção de política públicas, no levantamento de dados epidemiológicos de saúde, na gestão de serviços de saúde e na articulação da saúde com as ciências sociais.
AVALIAÇÃO CLÍNICA E EPIDEMIOLÓGICA DO PAPILOMAVÍRUS HUMANO EM MULHERES IDOSAS EM UNIDADES DE SAÚDE EM BELÉM – PARÁ – BRASIL
Authors: Freitas Wiviane Maria Torres de Matos
Published: August 2019

Introdução: O envelhecimento é um fenômeno real que traz modificações individuais e sociais. Destaca-se que, na atualidade, a população idosa tem permanecido atuante no campo de atividade sexual. Outrora esse evento era particular aos jovens, hoje os idosos além de serem sexualmente ativos ainda se expõem cada vez mais às doenças sexualmente transmissíveis (DST), incluindo a infecção pelo Papilomavírus Humano – HPV, em virtude de não adotarem hábitos seguros como o uso do preservativo. Objetivo: O presente estudo teve por objetivo avaliar clinica e epidemiologicamente a presença do HPV em mulheres idosas de unidades de saúde em Belém/PA. Metodologia: Trata-se de um estudo transversal, descritivo, analítico e quantitativo. As informações foram coletadas por meio de questionário clinico e epidemiológico contendo variáveis sobre coitarca, parceiros sexuais, hábitos de etilismo e tabagismo, etc. Foram coletadas células da cérvix uterina para realização de colpocitologia oncótica, extração de DNA e detecção de DNA do HPV. A detecção do HPV foi realizada por técnica de PCR e para subtipagem a de PCR em tempo real. As coletas se deram após aprovação do Comitê de Ética em Pesquisa do Núcleo de Medicina Tropical/UFPA sob o parecer nº 401.991 e analisadas por meio da construção do banco de dados e aplicados os testes Qui-quadrado e Exato de Fisher com nível de significância admitido de α ≤ 0,05. Resultados: Para análise dos resultados, contou-se com 159 amostras de idosas, em média de 67,98 anos de idade, em maioria viúvas e com ensino fundamental incompleto. Registrou-se uma prevalência de 6,28% de infecção por HPV nessas idosas pesquisadas. Observou-se uma importante relação da infecção com a multiplicidade de parceiros (p≤0,006) e com o hábito de tabagismo durante a vida (p≤0,03). Outro fato importante para a presença do vírus é com relação às idosas que permanecem em atividade sexual, pois apresentaram maior prevalência de HPV (14,28%) do que as sem atividade (2,72%). Acrescenta-se o evento registrado, de uma idosa pesquisada, de infecção por um subtipo de alto risco oncológico (HPV16). Cabe ressaltar que todas as idosas do estudo receberam o resultado das analises citológicas dentro dos padrões de normalidade. Conclusões: Conclui-se que apesar da prevalência se apresentar decrescente nesta faixa etária, as idosas estão expostas a fatores de risco que podem contribuir com aumento nas futuras taxas de câncer do colo do útero, em particular por receberem o resultado do exame citológico dentro dos padrões de normalidade, desta maneira destaca-se a importância desta pesquisa e da necessidade de permanecer com o constante rastreio em mulheres de todas as idades nas diversas unidades de saúde.
O CURRÍCULO PARA A FORMAÇÃO DO FISIOTERAPEUTA E SUA CONSTRUÇÃO HISTÓRICA
Authors: Teixeira Renato Da Costa , Muniz José Wagner Cavalcante , Nazaré Daniela Lobato
Published: August 2019

O propósito deste estudo foi fazer uma revisão da evolução dos currículos de Fisioterapia adotados no Brasil, para analisar os três currículos oficiais para os cursos de Fisioterapia à luz do que afirma a literatura. Utilizamos da análise documental dos currículos oficiais, bem como de documentos que serviram de base para esses currículos e de obras atuais sobre o tema. Etimologicamente currículo representa um caminho a ser seguido por alguém e sempre é parte de uma seleção feita por um grupo dominante que decide qual deve ser o conhecimento ensinável determinado por contextos políticos e sócio-econômicos. Recentemente o termo currículo mínimo, que representava uma lista de matérias que os cursos de graduação deveriam oferecer independente da região do país, foi substituído pelas Diretrizes Curriculares Nacionais (DCNs). Estas, propõem conteúdos essenciais, dando maior liberdade às Instituições de Ensino Superior. No caso da Fisioterapia, as DCNs afirmam que o perfil profissional deve ser “generalista, humanista, crítico e reflexivo”, deve possuir competências gerais comuns a todos os cursos da saúde e específicos da profissão e, os conteúdos essenciais devem envolver conhecimentos sociais e humanos, biológicos e da saúde, biotecnológicos e fisioterapêuticos. Este perfil, não é exclusivo desta classe, mas constam nas DCNs de todas as profissões de saúde, dando a impressão de que exista a visão de algum grupo acerca do que deva ser ensinado. No entanto para atingir plenamente os princípios e diretrizes do SUS é necessário que todos sejam formados com a mesma visão..