Using natural language processing for question answering in closed and open domains

With regard to the growth in the amount of social, environmental, and biomedical information available digitally, there is a growing need for Question Answering (QA) systems that can empower users to master this new wealth of information. Despite recent progress in QA, the quality of interpretation and extraction of the desired answer is not adequate. We believe that striving for higher accuracy in QA systems is subject to on-going research, i.e., it is better to have no answer is better than wrong answers. However, there are diverse queries, which the state of the art QA systems cannot interpret and answer properly. The problem of interpreting a question in a way that could preserve its syntactic-semantic structure is considered as one of the most important challenges in this area. In this work we focus on the problems of semantic-based QA systems and analyzing the effectiveness of NLP techniques, query mapping, and answer inferencing both in closed (first scenario) and open (second scenario) domains. For this purpose, the architecture of Semantic-based closed and open domain Question Answering System (hereafter “ScoQAS”) over ontology resources is presented with two different prototyping: Ontology-based closed domain and an open domain under Linked Open Data (LOD) resource. The ScoQAS is based on NLP techniques combining semantic-based structure-feature patterns for question classification and creating a question syntactic-semantic information structure (QSiS). The QSiS provides an actual potential by building constraints to formulate the related terms on syntactic-semantic aspects and generating a question graph (QGraph) which facilitates making inference for getting a precise answer in the closed domain. In addition, our approach provides a convenient method to map the formulated comprehensive information into SPARQL query template to crawl in the LOD resources in the open domain. The main contributions of this dissertation are as follows: 1. Developing ScoQAS architecture integrated with common and specific components compatible with closed and open domain ontologies. 2. Analysing user’s question and building a question syntactic-semantic information structure (QSiS), which is constituted by several processes of the methodology: question classification, Expected Answer Type (EAT) determination, and generated constraints. 3. Presenting an empirical semantic-based structure-feature pattern for question classification and generalizing heuristic constraints to formulate the relations between the features in the recognized pattern in terms of syntactical and semantical. 4. Developing a syntactic-semantic QGraph for representing core components of the question. 5. Presenting an empirical graph-based answer inference in the closed domain. In a nutshell, a semantic-based QA system is presented which provides some experimental results over the closed and open domains. The efficiency of the ScoQAS is evaluated using measures such as precision, recall, and F-measure on LOD challenges in the open domain. We focus on quantitative evaluation in the closed domain scenario. Due to the lack of predefined benchmark(s) in the first scenario, we define measures that demonstrate the actual complexity of the problem and the actual efficiency of the solutions. The results of the analysis corroborate the performance and effectiveness of our approach to achieve a reasonable accuracy.Con respecto al crecimiento en la cantidad de información social, ambiental y biomédica disponible digitalmente, existe una creciente necesidad de sistemas de la búsqueda de la respuesta (QA) que puedan ofrecer a los usuarios la gestión de esta nueva cantidad de información. A pesar del progreso reciente en QA, la calidad de interpretación y extracción de la respuesta deseada no es la adecuada. Creemos que trabajar para lograr una mayor precisión en los sistemas de QA es todavía un campo de investigación abierto. Es decir, es mejor no tener respuestas que tener respuestas incorrectas. Sin embargo, existen diversas consultas que los sistemas de QA en el estado del arte no pueden interpretar ni responder adecuadamente. El problema de interpretar una pregunta de una manera que podría preservar su estructura sintáctica-semántica es considerado como uno de los desafíos más importantes en esta área. En este trabajo nos centramos en los problemas de los sistemas de QA basados en semántica y en el análisis de la efectividad de las técnicas de PNL, y la aplicación de consultas e inferencia respuesta tanto en dominios cerrados (primer escenario) como abiertos (segundo escenario). Para este propósito, la arquitectura del sistema de búsqueda de respuestas en dominios cerrados y abiertos basado en semántica (en adelante "ScoQAS") sobre ontologías se presenta con dos prototipos diferentes: en dominio cerrado basado en el uso de ontologías y un dominio abierto dirigido a repositorios de Linked Open Data (LOD). El ScoQAS se basa en técnicas de PNL que combinan patrones de características de estructura semánticas para la clasificación de preguntas y la creación de una estructura de información sintáctico-semántica de preguntas (QSiS). El QSiS proporciona una manera la construcción de restricciones para formular los términos relacionados en aspectos sintáctico-semánticos y generar un grafo de preguntas (QGraph) el cual facilita derivar inferencias para obtener una respuesta precisa en el dominio cerrado. Además, nuestro enfoque proporciona un método adecuado para aplicar la información integral formulada en la plantilla de consulta SPARQL para navegar en los recursos LOD en el dominio abierto. Las principales contribuciones de este trabajo son los siguientes: 1. El desarrollo de la arquitectura ScoQAS integrada con componentes comunes y específicos compatibles con ontologías de dominio cerrado y abierto. 2. El análisis de la pregunta del usuario y la construcción de una estructura de información sintáctico-semántica de las preguntas (QSiS), que está constituida por varios procesos de la metodología: clasificación de preguntas, determinación del Tipo de Respuesta Esperada (EAT) y las restricciones generadas. 3. La presentación de un patrón empírico basado en la estructura semántica para clasificar las preguntas y generalizar las restricciones heurísticas para formular las relaciones entre las características en el patrón reconocido en términos sintácticos y semánticos. 4. El desarrollo de un QGraph sintáctico-semántico para representar los componentes centrales de la pregunta. 5. La presentación de la respuesta inferida a partir de un grafo empírico en el dominio cerrado. En pocas palabras, se presenta un sistema semántico de QA que proporciona algunos resultados experimentales sobre los dominios cerrados y abiertos. La eficiencia del ScoQAS se evalúa utilizando medidas tales como una precisión, cobertura y la medida-F en desafíos LOD para el dominio abierto. Para el dominio cerrado, nos centramos en la evaluación cuantitativa; su precisión se analiza en una ontología empresarial. La falta de un banco la pruebas predefinidas es uno de los principales desafíos de la evaluación en el primer escenario. Por lo tanto, definimos medidas que demuestran la complejidad real del problema y la eficiencia real de las soluciones. Los resultados del análisis corroboran el rendimient

Using natural language processing for question answering in closed and open domains

With regard to the growth in the amount of social, environmental, and biomedical information available digitally, there is a growing need for Question Answering (QA) systems that can empower users to master this new wealth of information. Despite recent progress in QA, the quality of interpretation and extraction of the desired answer is not adequate. We believe that striving for higher accuracy in QA systems is subject to on-going research, i.e., it is better to have no answer is better than wrong answers. However, there are diverse queries, which the state of the art QA systems cannot interpret and answer properly. The problem of interpreting a question in a way that could preserve its syntactic-semantic structure is considered as one of the most important challenges in this area. In this work we focus on the problems of semantic-based QA systems and analyzing the effectiveness of NLP techniques, query mapping, and answer inferencing both in closed (first scenario) and open (second scenario) domains. For this purpose, the architecture of Semantic-based closed and open domain Question Answering System (hereafter “ScoQAS”) over ontology resources is presented with two different prototyping: Ontology-based closed domain and an open domain under Linked Open Data (LOD) resource. The ScoQAS is based on NLP techniques combining semantic-based structure-feature patterns for question classification and creating a question syntactic-semantic information structure (QSiS). The QSiS provides an actual potential by building constraints to formulate the related terms on syntactic-semantic aspects and generating a question graph (QGraph) which facilitates making inference for getting a precise answer in the closed domain. In addition, our approach provides a convenient method to map the formulated comprehensive information into SPARQL query template to crawl in the LOD resources in the open domain. The main contributions of this dissertation are as follows: 1. Developing ScoQAS architecture integrated with common and specific components compatible with closed and open domain ontologies. 2. Analysing user’s question and building a question syntactic-semantic information structure (QSiS), which is constituted by several processes of the methodology: question classification, Expected Answer Type (EAT) determination, and generated constraints. 3. Presenting an empirical semantic-based structure-feature pattern for question classification and generalizing heuristic constraints to formulate the relations between the features in the recognized pattern in terms of syntactical and semantical. 4. Developing a syntactic-semantic QGraph for representing core components of the question. 5. Presenting an empirical graph-based answer inference in the closed domain. In a nutshell, a semantic-based QA system is presented which provides some experimental results over the closed and open domains. The efficiency of the ScoQAS is evaluated using measures such as precision, recall, and F-measure on LOD challenges in the open domain. We focus on quantitative evaluation in the closed domain scenario. Due to the lack of predefined benchmark(s) in the first scenario, we define measures that demonstrate the actual complexity of the problem and the actual efficiency of the solutions. The results of the analysis corroborate the performance and effectiveness of our approach to achieve a reasonable accuracy.Con respecto al crecimiento en la cantidad de información social, ambiental y biomédica disponible digitalmente, existe una creciente necesidad de sistemas de la búsqueda de la respuesta (QA) que puedan ofrecer a los usuarios la gestión de esta nueva cantidad de información. A pesar del progreso reciente en QA, la calidad de interpretación y extracción de la respuesta deseada no es la adecuada. Creemos que trabajar para lograr una mayor precisión en los sistemas de QA es todavía un campo de investigación abierto. Es decir, es mejor no tener respuestas que tener respuestas incorrectas. Sin embargo, existen diversas consultas que los sistemas de QA en el estado del arte no pueden interpretar ni responder adecuadamente. El problema de interpretar una pregunta de una manera que podría preservar su estructura sintáctica-semántica es considerado como uno de los desafíos más importantes en esta área. En este trabajo nos centramos en los problemas de los sistemas de QA basados en semántica y en el análisis de la efectividad de las técnicas de PNL, y la aplicación de consultas e inferencia respuesta tanto en dominios cerrados (primer escenario) como abiertos (segundo escenario). Para este propósito, la arquitectura del sistema de búsqueda de respuestas en dominios cerrados y abiertos basado en semántica (en adelante "ScoQAS") sobre ontologías se presenta con dos prototipos diferentes: en dominio cerrado basado en el uso de ontologías y un dominio abierto dirigido a repositorios de Linked Open Data (LOD). El ScoQAS se basa en técnicas de PNL que combinan patrones de características de estructura semánticas para la clasificación de preguntas y la creación de una estructura de información sintáctico-semántica de preguntas (QSiS). El QSiS proporciona una manera la construcción de restricciones para formular los términos relacionados en aspectos sintáctico-semánticos y generar un grafo de preguntas (QGraph) el cual facilita derivar inferencias para obtener una respuesta precisa en el dominio cerrado. Además, nuestro enfoque proporciona un método adecuado para aplicar la información integral formulada en la plantilla de consulta SPARQL para navegar en los recursos LOD en el dominio abierto. Las principales contribuciones de este trabajo son los siguientes: 1. El desarrollo de la arquitectura ScoQAS integrada con componentes comunes y específicos compatibles con ontologías de dominio cerrado y abierto. 2. El análisis de la pregunta del usuario y la construcción de una estructura de información sintáctico-semántica de las preguntas (QSiS), que está constituida por varios procesos de la metodología: clasificación de preguntas, determinación del Tipo de Respuesta Esperada (EAT) y las restricciones generadas. 3. La presentación de un patrón empírico basado en la estructura semántica para clasificar las preguntas y generalizar las restricciones heurísticas para formular las relaciones entre las características en el patrón reconocido en términos sintácticos y semánticos. 4. El desarrollo de un QGraph sintáctico-semántico para representar los componentes centrales de la pregunta. 5. La presentación de la respuesta inferida a partir de un grafo empírico en el dominio cerrado. En pocas palabras, se presenta un sistema semántico de QA que proporciona algunos resultados experimentales sobre los dominios cerrados y abiertos. La eficiencia del ScoQAS se evalúa utilizando medidas tales como una precisión, cobertura y la medida-F en desafíos LOD para el dominio abierto. Para el dominio cerrado, nos centramos en la evaluación cuantitativa; su precisión se analiza en una ontología empresarial. La falta de un banco la pruebas predefinidas es uno de los principales desafíos de la evaluación en el primer escenario. Por lo tanto, definimos medidas que demuestran la complejidad real del problema y la eficiencia real de las soluciones. Los resultados del análisis corroboran el rendimientoPostprint (published version

Systematic review of the role of medicinal plants and derived components on reduction of cyclophosphamide-induced toxicity in male genital system

زمینه و هدف: داروی شیمیایی سیکلوفسفامید علی رغم اثرات دارویی چشمگیری که در درمان بیماری های متعدد به ویژه سرطان دارد با عوارض جانبی متعددی همراه می باشد که کاربرد آن را تا حدودی محدود نموده است. این مطالعه مروری قصد دارد اثرات محافظتی گیاهان دارویی و ترکیبات مشتق شده از آن ها را بر کاهش عوارض حاصل از داروی سیکلوفسفامید بر روی دستگاه تناسلی نر مرور و نقش گیاهان را در خصوص کاهش این عوارض جانبی مورد بررسی و تحلیل قرار دهد. روش بررسی: برای انجام این مطالعه مروری واژگان کلیدی سیکلوفسفامید، دستگاه تناسلی نر، سمیت، سرطان، شیمی درمانی، عوارض جانبی در ترکیب با واژگان گیاهان دارویی، داروهای گیاهی و ترکیبات طبیعی از پایگاه های اطلاعاتی ISI، پابمد، اسکاپوس و گوگل اسکالر جستجو شدند. بر اساس معیارهای انتخاب تعداد 20 مقاله که در محدوده سال 2000 تا 2015 منتشر شده بودند انتخاب و وارد مطالعه شدند. یافته ها: از میان 20 مقاله، 13 مقاله مربوط به عصاره­ های گیاهی، 3 مقاله مربوط به ترکیبات فعال گیاهی، 2 مقاله مربوط به اسانس های روغنی و 2 مقاله نیز مربوط به دارو های گیاهی بودند که مشخصات پایه ای آن ها، تاثیر محافظتی این گیاهان و همچنین ترکیبات موثر آن­ها بر روی سمیت دستگاه تولید مثلی جنس نر ناشی از تجویز سیکلوفسفامید مورد بحث قرار گرفت. نتیجه گیری: نتایج این مطالعه نشان داد، گیاهانی که دارای ترکیبات آنتی اکسیدانی نظیر فلاونوئیدها هستند قادرند سمیت ناشی از تجویز سیکلوفسفامید را که سبب بروز استرس اکسیداتیو و افزایش رادیکال­های آزاد می­گردند، در بافت بیضه کاهش دهند؛ لذا پیشنهاد می گردد گیاهانی که اثرات آنتی اکسیدانی چشمگیری دارند در کنار داروی سیکلوفسفامید تجویز و اثرات محافظتی آن ها نسبت به گیاهان و ترکیبات مشتق شده از آن ها که اثرات محافظتی آنها بررسی شده است مقایسه گردد

The Efficacy of Phonological Processing Treatments on Stuttering Severity in Persian Pre-school Children

AbstractObjectives: Correct phonological encoding is crucial to fluent speech production. Phonological working memory and phonological awareness are important phonological processes that affect phonological encoding. Studies have shown weakness in phonological encoding in people who stutter. The purpose of this study was to investigate the effect of phonological processing on stuttering severity of Persian pre-school children.Method: Six children who stutter participated in a 13-session treatment protocol. The treatment protocol of the phonological processing included nonword repetition in the phonological working memory and phonological awareness therapy. Stuttering severity measurement was performed pre- and post-treatment.Results: Stuttering severity score was compared in pre- and post-treatment, and in the follow-up phase; that showed stuttering severity was reduced in children who stutter. Moreover, severity rating, reported by parents during treatment, showed a reduction in stuttering severity. Conclusion: The poor performance of phonological awareness and phonological working memory in phonological processing affect stuttering severity. The outcomes of this study showed that treatment of sub-systems of phonological processing can play a role in reducing stuttering severity.

ScoQAS : a semantic-based closed and open domain question answering system

Question Answering (QA) has reappeared in research activities and in companies over the past years. We present an architecture of Semantic-based closed and open domain Question Answering System (ScoQAS) over ontology resources (not free text) with two different prototyping: Ontology-based closed domain and an open domain under Linked Open Data (LOD) resource. Both scenarios are presented, discussed and evaluated.Peer ReviewedPostprint (published version

Un sistema de búsqueda de respuestas en dominios cerrados y abiertos basado en semántica

Question Answering (QA) has reappeared in research activities and in companies over the past years. We present an architecture of Semantic-based closed and open domain Question Answering System (ScoQAS) over ontology resources (not free text) with two different prototyping: Ontology-based closed domain and an open domain under Linked Open Data (LOD) resource. Both scenarios are presented, discussed and evaluated.La búsqueda de la respuesta ha reaparecido con fuerza en los últimos años, tanto a nivel industrial como académico. Presentamos una arquitectura de búsqueda de respuesta, ScoQAS, basada en la semántica aplicable tanto a dominio cerrado (definido por una ontología) como a dominio abierto, dirigido a repositorios de Linked Open Data (LOD). Los dos se presentan, discuten y son evaluados.Dr. Rodríguez has been partially funded by Spanish project "GraphMed" (TIN2016-77820-C3-3R). This work has been partially funded by the Spanish Thematic Network "Diversificación en Aprendizaje Máquina y Aplicaciones" (DAMA), under grant code TIN2015-70308-REDT (MINECO/FEDER EU)

The effect of iron oxide nanoparticles on liver enzymes (ALT, AST and ALP), thyroid hormones (T3 and T4) and TSH in rats

زمینه و هدف: نانوذرات اکسید آهن به عنوان عنصر ایجاد کننده ی تضاد در رزونانس مغناطیسی هسته (MRI) و همچنین گرمادرمانی سلول های سرطانی استفاده های گسترده ای دارند. با این وجود، اثرات این نانوذرات روی سلامتی انسان هنوز به طور کامل بررسی نشده است. در این تحقیق اثرات نانوذرات اکسید آهن روی سطح سرمی آنزیم های کبدی، هورمون های تیروئیدی و هورمون محرک تیروئید (TSH) در موش های صحرایی مورد بررسی قرار گرفت. روش بررسی: در این مطالعه تجربی 28 سر موش صحرایی از نژاد ویستار به چهار گروه تقسیم شدند. گروه های مورد، روزانه به مدت پانزده روز، نانوذرات اکسید آهن را با غلظت های g/kgµ20، g/kgµ50 و g/kgµ150 که در یک میلی لیتر آب مقطر حل شده بود توسط لوله ی گاواژ دریافت کردند. گروه شاهد نیز روزانه یک میلی لیتر آب مقطر دریافت کرد. داده ها با استفاده از آزمون آماری ANOVA و تست Tukey تجزیه و تحلیل شدند. یافته ها: غلظت سرمی آنزیم های آلکالاین فسفاتاز (ALP)، آلانین آمینوتراسفراز (ALT) و هورمون تیروکسین (T4) در گروه دریافت کننده ی دوز g/kgµ150 نسبت به گروه شاهد افزایش معنی داری نشان داد (05/0

Leveraging semantic text analysis to improve the performance of transformer-based relation extraction

Keyword extraction from Knowledge Bases underpins the definition of relevancy in Digital Library search systems. However, it is the pertinent task of Joint Relation Extraction, which populates the Knowledge Bases from which results are retrieved. Recent work focuses on fine-tuned, Pre-trained Transformers. Yet, F1 scores for scientific literature achieve just 53.2, versus 69 in the general domain. The research demonstrates the failure of existing work to evidence the rationale for optimisations to finetuned classifiers. In contrast, emerging research subjectively adopts the common belief that Natural Language Processing techniques fail to derive context and shared knowledge. In fact, global context and shared knowledge account for just 10.4% and 11.2% of total relation misclassifications, respectively. In this work, the novel employment of semantic text analysis presents objective challenges for the Transformer-based classification of Joint Relation Extraction. This is the first known work to quantify that pipelined error propagation accounts for 45.3% of total relation misclassifications, the most poignant challenge in this domain. More specifically, Part-of-Speech tagging highlights the misclassification of complex noun phrases, accounting for 25.47% of relation misclassifications. Furthermore, this study identifies two limitations in the purported bidirectionality of the Bidirectional Encoder Representations from Transformers (BERT) Pre-trained Language Model. Firstly, there is a notable imbalance in the misclassification of right-to-left relations, which occurs at a rate double that of left-to-right relations. Additionally, a failure to recognise local context through determiners and prepositions contributes to 16.04% of misclassifications. Furthermore, it is highlighted that the annotation scheme of the singular dataset utilised in existing research, Scientific Entities, Relations and Coreferences (SciERC), is marred by ambiguity. Notably, two asymmetric relations within this dataset achieve recall rates of only 10% and 29

Correlation between Acoustic Parameters and Disease Severity and Duration in Patients with Multiple Sclerosis

Background: Since in multiple sclerosis (MS), changes in speech and voice quality often precede other signs and symptoms; early diagnosis of these changes is necessary. In this study, an acoustic examination of phonation subsystem was performed. Due to the progressive nature of multiple sclerosis, the aim of this study was to examine the correlation between acoustic parameters of voice quality and disease severity and duration. Methods: This descriptive-analytic study was performed on 43 patients with multiple sclerosis. The disease severity was detected by a neurologist based on the Expanded Disability Status Scale (EDSS) for each patient. Acoustic analysis was performed during the production of sustained vowel /a/ and accordingly, the maximum phonation time (MPT), perturbation of the frequency (jitter), perturbation of amplitude (shimmer), the maximum and minimum frequency, and the highest and lowest intensity were evaluated. All the acoustic analyses were performed using PRAAT software. Data were statistically analyzed using Spearman's correlation coefficient by SPSS version 21. Results: The lowest intensity showed a significant correlation with disease severity (P=0.00). Also, the highest and lowest intensity showed a significant correlation with disease duration (P=0.022 and P=0.002). Conclusion: One of the earlier symptoms of central nervous system impairment resulting from multiple sclerosis is changes in phonation subsystem and voice quality. These changes may appear at any clinical stages; however, the symptoms might get worse over time, with the progression of the disease. Therefore, immediate acoustic assessments and interventions can prevent more degradation of voice quality

Promoter methylation and expression pattern of DLX3, ATF4, and FRA1 genes during osteoblastic differentiation of adipose-derived mesenchymal stem cells

Introduction: Nowadays, mesenchymal stem cells are touted as suitable cell supply for the restoration of injured bone tissue. The existence of osteogenic differentiation makes these cells capable of replenishing damaged cells in the least possible time. It has been shown that epigenetic modifications, especially DNA methylation, contribute to the regulation of various transcription factors during phenotype acquisition. Hence, we concentrated on the correlation between the promoter methylation and the expression of genes DLX3, ATF4, and FRA1 during osteoblastic differentiation of adipose-derived mesenchymal stem cells in vitro after 21 days. Methods: Adipose-derived mesenchymal stem cells were cultured in osteogenesis differentiation medium supplemented with 0.1 µM dexamethasone, 10 mM β-glycerol phosphate, and 50 µM ascorbate-2-phosphate for 21 days. RNA and DNA extraction was done on days 0, 7, 14, and 21. Promoter methylation and expression levels of genes DLX3, ATF4, and FRA1 were analyzed by methylation-specific quantitative PCR and real-time PCR assays, respectively. Results: We found an upward expression trend with the increasing time for genes DLX3, ATF4, and FRA1 in stem cells committed to osteoblast-like lineage compared to the control group (P<0.05). On the contrary, methylation-specific quantitative PCR displayed decreased methylation rates of DLX3 and ATF4 genes, but not FRA1, over time compared to the non-treated control cells (P<0.05). Bright-field images exhibited red-colored calcified deposits around Alizarin Red S-stained cells after 21 days compared to the control group. Statistical analysis showed a strong correlation between the transcription of genes DLX3 and ATF4 and methylation rate (P<0.05). Conclusion: In particular, osteoblastic differentiation of adipose-derived mesenchymal stem cells enhances DLX3 and ATF4 transcriptions by reducing methylation rate for 21 days