Isolated eosinophilic mastitis: a rare breast disease mimicking malignancy

Eosinophilic mastitis is a rare benign breast pathology which presents with lump breast and can mimic malignancy. So far eight reported cases have been found in literature review. All cases were associated with peripheral eosinophilia and systemic involvement except one. Isolated eosinophilic mastitis in the absence of peripheral eosinophilia or systemic involvement is a very rare presentation. Being one of the rare cases, prompted us to take up this case in our present study. A 40-year-old lady presented with progressively enlarging, slightly painful swelling in left breast of 15 days duration with no other relevant past and family history. The clinical differential diagnosis of mastitis and carcinoma was suggested. Aspiration cytology was reported as benign breast disease- fibroadenosis. Imaging studies undertaken were inconclusive. Case managed surgically with wide local excision. Post-surgical tissue specimen was subjected to histopathology examination and was diagnosed as eosinophilic mastitis. A prolonged follow-up revealed no recurrence.

Legumes of Forage Value: Their Diversity and Priority for Collection in India

Indian subcontinent is a megacentre of agro-diversity. Legumes have a special place with several native crops and economically important species occurring along forest margins and openings, pastures, grasslands and grazing lands. Several are dual-purpose species for food and feed. However, herbage legumes though major components of grasslands and with a major role in their quality and improvement lack persistence as compared to grasses and their collection, maintenance and conservation assumes importance in the wake of change and loss of habitats of native species and introduction of new germplasm with forage potential. Establishing the correct identity of species is therefore a priority. The major forage legume crops of India (Anon., 2013) belong to Tribes Trifolieae- Trifolium, Medicago, Melilotus among temperate legumes; Phaseoleae- Vigna; and Indigofereae- Cyamopsis tropical, subtropical and arid conditions (Arora and Chandel, 1972). These have a good representation of erect, spreading and viny species with potential for use as forage, soil improvement and use as green manure and often with non-toxic herbage and successfully grown over widely varying environmental conditions making this a morphologically variable and highly diverse germplasm resource. Collecting species of native and introduced species from these habitats that are in a state of flux is important for locating potentially important and unique diversity well adapted to the areas of occurrence. Several species of forage legumes, both native and introduced (Nayar et al., 2014) were represented as reference specimens of plants collected from the wild or grown in experimental conditions at the National Herbarium of Cultivated Plants (acronym: NHCP). An initiative undertaken was to authenticate the identity of these, and work out characters that could be used for field identification

Analysis of the Non-profit Sector in the EU10 for Monitoring and Control

The report "Analysis of the EU10 Non-profit Sector for Monitoring and Control" has been written in the context of the European Commission forum "Support against Terrorist Financing"by Directorate General Justice, Liberty and Security (JLS), and of a Joint Research Centre (JRC) research project to support monitoring and control for EU aid funds. The report's purpose is to give an overview of the non-profit sector in EU10 with specific attention to the prevention of fraudulent use of funds in this sector, in general, and terrorist financing in particular. This report is complementary to the report "Analysis of the EU15 Non-profit Sector for Monitoring and Control" which sets out the context of the current work in detail and also contains information regarding the classification and definitions used for the non profit sector.JRC.G.2-Support to external securit

Evaluation of Noise Reduction Methods for Sentence Recognition by Sinhala Speaking Listeners

Noise reduction is a crucial aspect of hearing aids, which researchers have been striving to address over the years. However, most existing noise reduction algorithms have primarily been evaluated using English. Considering the linguistic differences between English and Sinhala languages, including variation in syllable structures and vowel duration, it is very important to assess the performance of noise reduction tailored to the Sinhala language. This paper presents a comprehensive analysis between wavelet transformation and adaptive filters for noise reduction in Sinhala languages. We investigate the performance of ten wavelet families with soft and hard thresholding methods against adaptive filters with Normalized Least Mean Square, Least Mean Square Average Normalized Least Mean Square, Recursive Least Square, and Adaptive Filtering Averaging optimization algorithms along with cepstral and energy-based voice activity detection algorithms. The performance evaluation is done using objective metrics; Signal to Noise Ratio (SNR) and Perceptual Evaluation of Speech Quality (PESQ) and a subjective metric; Mean Opinion Score (MOS). A newly recorded Sinhala language audio dataset and the NOIZEUS database by the University of Texas, Dallas were used for the evaluation. Our code is available at https://github.com/ChathukiKet/Evaluation-of-Noise-Reduction-Method

A Knowledge Distillation Framework For Enhancing Ear-EEG Based Sleep Staging With Scalp-EEG Data

Sleep plays a crucial role in the well-being of human lives. Traditional sleep studies using Polysomnography are associated with discomfort and often lower sleep quality caused by the acquisition setup. Previous works have focused on developing less obtrusive methods to conduct high-quality sleep studies, and ear-EEG is among popular alternatives. However, the performance of sleep staging based on ear-EEG is still inferior to scalp-EEG based sleep staging. In order to address the performance gap between scalp-EEG and ear-EEG based sleep staging, we propose a cross-modal knowledge distillation strategy, which is a domain adaptation approach. Our experiments and analysis validate the effectiveness of the proposed approach with existing architectures, where it enhances the accuracy of the ear-EEG based sleep staging by 3.46% and Cohen's kappa coefficient by a margin of 0.038.Comment: Code available at : https://github.com/Mithunjha/EarEEG_KnowledgeDistillatio

Triad of Iron Deficiency Anemia, Severe Thrombocytopenia and Menorrhagia—A Case Report and Literature Review

Introduction Thrombocytosis is a common disorder in patients diagnosed with iron deficiency anemia. The decreased platelet counts commonly found iron deficiency anemia is rarely reported in clinical practice. The exact mechanism of the occurrence of thrombocytopenia in iron deficiency anemia remains unclear. In this case report we discuss a triad of symptoms seen in the African American population: Iron deficiency anemia, menorrhagia and thrombocytopenia. Case presentation A 40 year old multiparous African-American woman presented with heavy vaginal bleed, severe anemia (3.5 g/dL) and thrombocytopenia (30,000/mm 3 ). The peripheral blood smear showed marked microcytic hypochromic cells with decreased platelets counts. After excluding other causes of thrombocytopenia and anemia, increased red cell distribution width and low iron saturation confirmed the diagnosis of iron deficiency anemia. Treatment for iron deficiency anemia was initiated with intravenous and oral iron supplements. Two months following treatment of iron deficiency anemia, the triad of manifestations resolved and patient remained stable. Conclusion Profound degree of iron deficiency anemia can present with thrombocytopenia and severe menorrhagia. Iron replacement should be the main treatment goal in these patients. This case report further supports the 2 compartment model of the role of iron in maintaining platelet counts

Towards Interpretable Sleep Stage Classification Using Cross-Modal Transformers

Accurate sleep stage classification is significant for sleep health assessment. In recent years, several machine-learning based sleep staging algorithms have been developed, and in particular, deep-learning based algorithms have achieved performance on par with human annotation. Despite the improved performance, a limitation of most deep-learning based algorithms is their black-box behavior, which has limited their use in clinical settings. Here, we propose a cross-modal transformer, which is a transformer-based method for sleep stage classification. The proposed cross-modal transformer consists of a novel cross-modal transformer encoder architecture along with a multi-scale one-dimensional convolutional neural network for automatic representation learning. Our method outperforms the state-of-the-art methods and eliminates the black-box behavior of deep-learning models by utilizing the interpretability aspect of the attention modules. Furthermore, our method provides considerable reductions in the number of parameters and training time compared to the state-of-the-art methods. Our code is available at https://github.com/Jathurshan0330/Cross-Modal-Transformer.Comment: 11 pages, 7 figures, 6 table

“Maybe it’s kind of normal to hear voices”: The role of spirituality in making sense of voice hearing

First-person accounts of voice hearing are scarce. This research aims to explore the role of spirituality in the sense-making process of hearing voices. Five semistructured interviews explored experiences of spirituality and hearing voices. Qualitative data was analyzed using interpretive phenomenological analysis (IPA). Three superordinate themes were identified: need for connection, values about self and identity, and making sense. The findings suggest a relationship between spirituality and voice hearing, and relate to the need for belongingness and self-identity. Acknowledging the sense making process and engaging in conversations about spirituality are implicated when providing clinical interventions for distressing voice hearing. Future research could explore further the differences between voices associated with spiritual experiences and “psychosis.

Digitization of collecting mission data to enhance plant genetic resource management in maize (Zea mays) in India

The data gathered on germplasm collection of maize evidently showed is a preliminary attempt on digitization of collecting mission data of maize genetic resources to enhance its use in plant genetic resource management in maize in India through quality passport data, eco-geographic location, availability of germplasm site description, geographic coordinates for crop improvement programme. Identification of collection sites located in distribution maps would allow: pinpointing of directed collection plans in under represented and identified sites that are rich in landraces/ trait-specific diversity. Since these sites are highly vulnerable to genetic erosion due to spread of hybrids/ genetically modified crops (GM), such areas need to be given special attention in genetic resource management. Broadly all maize growing areas have been surveyed in the past and diversity augmented from different parts of the country. However, based on gaps identified in the genebank holdings of trait specific germplasm and unique material needs to be augmented. Grouping of local cultivars/ landraces of maize based on geographical distribution, morphology, field and molecular characterization is a major challenge that needs special address by the maize breeders and users