Sentiment Analysis Using Common-Sense and Context Information

Sentiment analysis research has been increasing tremendously in recent times due to the wide range of business and social applications. Sentiment analysis from unstructured natural language text has recently received considerable attention from the research community. In this paper, we propose a novel sentiment analysis model based on common-sense knowledge extracted from ConceptNet based ontology and context information. ConceptNet based ontology is used to determine the domain specific concepts which in turn produced the domain specific important features. Further, the polarities of the extracted concepts are determined using the contextual polarity lexicon which we developed by considering the context information of a word. Finally, semantic orientations of domain specific features of the review document are aggregated based on the importance of a feature with respect to the domain. The importance of the feature is determined by the depth of the feature in the ontology. Experimental results show the effectiveness of the proposed methods

Comparison of Healthy and Dandruff Scalp Microbiome Reveals the Role of Commensals in Scalp Health

Several scalp microbiome studies from different populations have revealed the association of dandruff with bacterial and fungal dysbiosis. However, the functional role of scalp microbiota in scalp disorders and health remains scarcely explored. Here, we examined the bacterial and fungal diversity of the scalp microbiome and their potential functional role in the healthy and dandruff scalp of 140 Indian women. Propionibacterium acnes and Staphylococcus epidermidis emerged as the core bacterial species, where the former was associated with a healthy scalp and the latter with dandruff scalp. Along with the commonly occurring Malassezia species (M. restricta and M. globosa) on the scalp, a strikingly high association of dandruff with yet uncharacterized Malassezia species was observed in the core mycobiome. Functional analysis showed that the fungal microbiome was enriched in pathways majorly implicated in cell-host adhesion in the dandruff scalp, while the bacterial microbiome showed a conspicuous enrichment of pathways related to the synthesis and metabolism of amino acids, biotin, and other B-vitamins, which are reported as essential nutrients for hair growth. A systematic measurement of scalp clinical and physiological parameters was also carried out, which showed significant correlations with the microbiome and their associated functional pathways. The results point toward a new potential role of bacterial commensals in maintaining the scalp nutrient homoeostasis and highlights an important and yet unknown role of the scalp microbiome, similar to the gut microbiome. This study, therefore, provides new perspectives on the better understanding of the pathophysiology of dandruff

Texture‐based feature extraction of smear images for the detection of cervical cancer

In India, cervical cancer is the second most common type of cancer in females. Pap smear is a simple cytology test for the detection of cancer in its early stages. To obtain the best results from the Pap smear, expert pathologist are required. Availability of pathologist in India is far below the required numbers, especially in rural parts. In this paper, multiple texture‐based features are introduced for the extraction of relevant and informative features from single‐cell images. First‐order histogram, GLCM, LBP, Laws, and DWT are used for texture feature extraction. These methods help to recognise the contour of the nucleus and cytoplasm. ANN and SVM are used to classify the single‐cell images either normal or cancerous based on the trained features. ANN and SVM are used on every single feature as well as on the combination of all features. Best results are obtained with a combination of all features. The system is evaluated on generated dataset MNITJ, containing 330 single cervical cell images and also on publicly available benchmark Herlev data set. Experimental results show that the proposed texture‐based features give significantly better results in cervical cancer detection when compared with state of the art shape‐based features regarding accuracy

A practical guide to placental examination for forensic pathologists

The placenta is a complex interface organ that may hold clues to the reasons for fetal, neonatal or maternal demise. For this reason, placental examination should be a mandatory part of all perinatal or maternal autopsies. While published protocols for the examination of the placenta exist, they are often not adopted. The following review provides practical guidelines for placental examination, with discussion of specific medical conditions that can negatively impact upon the fetus, neonate or mother involving placental pathology to cause death. The review aims to discuss concepts, with illustrations, that forensic pathologists may not routinely focus on in death investigations that may either contribute or mask the cause of a fetal or neonatal death, or are associated with a recurrence risk. While it is recognized that many forensic facilities do not have formal guidelines for placental examination, involvement of local perinatal pathology services in cases is one way of obtaining additional specialist expertise

Deep Learning-Based Approaches for Sentiment Analysis

This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years. The book presents a collection of state-of-the-art approaches, focusing on the best-performing, cutting-edge solutions for the most common and difficult challenges faced in sentiment analysis research. Providing detailed explanations of the methodologies, the book is a valuable resource for researchers as well as newcomers to the field

Recurrent Chronic Intervillositis: The Diagnostic Challenge – A Case Report and Review of the Literature

Background: Chronic intervillositis (CI) is a rare placental condition involving diffuse infiltration of intervillous spaces by CD68- or CD45-positive maternal mononuclear inflammatory cells. Because no validated clinical or biochemical markers are specific to CI, the diagnosis is purely histopathological and is made postpartum. Case: This report describes a case of recurrent CI associated with adverse complications in two successive pregnancies. Both pregnancies were complicated by intrauterine growth restriction. Coexistent massive perivillous fibrin deposition was present in the first placenta. This case highlights the importance of CI in explaining and predicting adverse perinatal outcomes. Conclusion: CI is associated with adverse pregnancy outcomes and a high risk of recurrence, and it can coexist with massive perivillous fibrin deposition. Pathologists must ensure that the significance of these diagnoses is adequately conveyed to clinicians, to optimize management of subsequent pregnancie