Miracle-dz/UniFAR-FTUs huggingface dataset:
Genre Transfer in NMT:Creating Synthetic Spoken Parallel Sentences using Written Parallel Data

Text style transfer (TST) aims to control attributes in a given text without changing the content. The matter gets complicated when the boundary separating two styles gets blurred. We can notice similar difficulties in the case of parallel datasets in spoken and written genres. Genuine spoken features like filler words and repetitions in the existing spoken genre parallel datasets are often cleaned during transcription and translation, making the texts closer to written datasets. This poses several problems for spoken genre-specific tasks like simultaneous speech translation. This paper seeks to address the challenge of improving spoken language translations. We start by creating a genre classifier for individual sentences and then try two approaches for data augmentation using written examples:(1) a novel method that involves assembling and disassembling spoken and written neural machine translation (NMT) models, and (2) a rule-based method to inject spoken features. Though the observed results for (1) are not promising, we get some interesting insights into the solution. The model proposed in (1) fine-tuned on the synthesized data from (2) produces naturally looking spoken translations for written-to-spoken genre transfer in En-Hi translation systems. We use this system to produce a second-stage En-Hi synthetic corpus, which however lacks appropriate alignments of explicit spoken features across the languages. For the final evaluation, we fine-tune Hi-En spoken translation systems on the synthesized parallel corpora. We observe that the parallel corpus synthesized using our rule-based method produces the best results.
Augmenting eBooks with with recommended questions using contrastive fine-tuned T5

The recent advances in AI made generation of questions from natural language text possible, the approach is completely excludes human in the loop while generating the appropriate questions which improves the students learning engagement. The ever growing amount of educational content renders it increasingly difficult to manually generate sufficient practice or quiz questions to accompany it. Reading comprehension can be improved by asking the right questions, So, this work offers a Transformer based question generation model for autonomously producing quiz questions from educational information, such as eBooks. This work proposes an contrastive training approach for ‘Text-to-Text Transfer Transformer’ (T5) model where the model (T5-eQG) creates the summarized text for the input document and then automatically generates the questions. Our model shows promising results over earlier neural network-based and rules-based models for question generating task on benchmark datasets and NCERT eBooks.
A Novel Approach towards Cross Lingual Sentiment Analysis using Transliteration and Character Embedding

Sentiment analysis with deep learning in resource-constrained languages is a challenging task. In this paper, we introduce a novel approach for sentiment analysis in resource-constrained scenarios using character embedding and cross-lingual sentiment analysis with transliteration. We use this method to introduce the novel task of inducing sentiment polarity of words and sentences and aspect term sentiment analysis in the no-resource scenario. We formulate this task by taking a metalingual approach whereby we transliterate data from closely related languages and transform it into a meta language. We also demonstrated the efficacy of using character-level embedding for sentence representation. We experimented with 4 Indian languages – Bengali, Hindi, Tamil, and Telugu, and obtained encouraging results. We also presented new state-of-the-art results on the Hindi sentiment analysis dataset leveraging our metalingual character embeddings.
Compact Residual Learning with Frequency-Based Non-Square Kernels for Small Footprint Keyword Spotting

Enabling voice assistants on small embedded devices requires a keyword spotter with a smaller model size and adequate accuracy. It becomes difficult to achieve a reasonable trade-off between a small footprint and high accuracy. Recent studies have demonstrated that convolution neural networks are also effective in the audio domain. In this paper, taking into account the nature of spectrograms, we propose a compact ResNet architecture that uses frequency-based non-square kernels to extract the maximum number of timbral features for keyword spotting. The proposed architecture is approximately three-and-a-half times smaller than a comparable architecture with conventional square kernels. On the Google’s speech command dataset v1, it outperforms both Google’s convolution neural networks and the equivalent ResNet architecture with square kernels. By implementing non-square kernels for spectrogram-related data, we can achieve a significant increase in accuracy with relatively few parameters, as compared to the conventional square kernels that are the default choice for every problem.
Event Oriented Abstractive Summarization

Abstractive Summarization models are generally conditioned on the source article. This would generate a summary with the central theme of the article. However, it would not be possible to generate a summary focusing on specific key areas of the article. To solve this problem, we introduce a novel method for abstractive summarization. We aim to use a transformer to generate summaries which are more tailored to the events in the text by using event information. We extract events from text, perform generalized pooling to get a representation for these events and add an event attention block in the decoder to aid the transformer model in summarization. We carried out experiments on CNN / Daily Mail dataset and the BBC Extreme Summarization dataset. We achieve comparable results on both these datasets, with less training and better inclusion of event information in the summaries as shown by human evaluation scores.
Normalization of Spelling Variations in Code-Mixed Data

Code-mixed text infused with low resource language has always been a challenge for natural language understanding models. A significant problem while understanding such texts is the correlation between the syntactic and semantic arrangement of words. The phonemes of each character in a word dictates the spelling representation of a term in low resource language. However, there is no universal protocol or alphabet mapping for code-mixing. In this paper, we highlight the impact of spelling variations in code-mixed data for training natural language understanding models. We emphasize the impact of using phonetics to neutralize this variation in spelling across different usage of a word with the same semantics. The proposed approach is a computationally inexpensive technique and improves the performances of state-of-the-art models for three dialog system tasks viz. intent classification, slot-filling, and response generation. We propose a data pipeline for normalizing spelling variations irrespective of language.
Estimation of Wheel/rail Interaction Forces in the Contact Area due to Roughness

The generation of forces in the contact area between wheel and rail due to roughness is an inherently non-linear process. In order to provide an excitation input to existing linear analytical models of wheel/rail noise, the authors have examined two alternate calculation procedures for estimating these interaction forces: the distributed point reacting spring (DPRS) procedure and the Boussinesq procedure. Both procedures are based on estimating the blocked force produced by the roughness. The blocked force can then be used in the linear wheel/rail analytical models to calculate wheel and rail response and sound radiation. The DPRS procedure is substantially more computationally efficient than the Boussinesq and is found to provide similar estimates of the normal stress distribution in the contact zone for roughness wavelengths that are long compared to the contact area dimensions. The two procedures provide quite different estimates of the normal stress distribution in the contact zone when the roughness wavelengths are short compared to the dimensions of the contact area. When the two models are used to estimate the blocked interaction force between the wheel and rail for measured wheel and rail two-dimensional roughness distributions, however, the blocked force predictions are very similar even for wavelengths that are the order of or slightly shorter than the dimensions of the contact area. (A) For the covering abstract see IRRD 890682.
Vaginal Swab vs Urine for Detection of Chlamydia trachomatis, Neisseria gonorrhoeae, and Trichomonas vaginalis: A Meta-Analysis

PURPOSE Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) are the 2 most frequently reported notifiable sexually transmitted infections (STIs) in the United States, and Trichomonas vaginalis (TV), although not a notifiable disease, is the most common curable non-viral STI worldwide. Women bear a disproportionate burden of these infections and testing is necessary to identify infections. Although vaginal swabs are the recommended sample type, the specimen most often used among women is urine. The objective of this meta-analysis was to assess the diagnostic sensitivity of commercially available assays for vaginal swabs vs urine specimens from women. METHODS A systematic search of multiple databases from 1995 through 2021 identified studies that (1) evaluated commercially available assays, (2) presented data for women, (3) included data obtained from the same assay on both a urine specimen and a vaginal swab from the same patient, (4) used a reference standard, and (5) were published in English. We calculated pooled estimates for sensitivity and the corresponding 95% CIs for each pathogen as well as odds ratios for any difference in performance. RESULTS We identified 28 eligible articles with 30 comparisons for CT, 16 comparisons for NG, and 9 comparisons for TV. Pooled sensitivity estimates for vaginal swabs and urine, respectively, were 94.1% and 86.9% for CT, 96.5% and 90.7% for NG, and 98.0% and 95.1% for TV (all P values <.001). CONCLUSIONS Evidence from this analysis supports the Centers for Disease Control and Prevention’s recommendation that vaginal swabs are the optimal sample type for women being tested for chlamydia, gonorrhea, and/or trichomoniasis.
Gastric Linitis Plastica: Clinical Characteristics and Outcomes from the National Cancer Database

Background/Aim: Gastric linitis plastica (LP) is a rare type of gastric tumor with limited data. We sought to investigate the clinical characteristics, treatment modalities, and outcomes utilizing a national database. Patients and Methods: The National Cancer Database (NCDB) was reviewed for LP of the stomach from 2004 to 2017. Kaplan–Meier analysis and Cox proportional hazards model were utilized to evaluate overall survival and predictors of survival. Results: Out of 222,488 gastric cancer cases, 896 patients with histologically confirmed primary gastric LP were included. Patients were predominantly white (78.5%), female (51.9%) and presented at advanced stage disease (stage 4=69%). A total of 369 (41.2%) patients underwent surgical resection, 520 (58.0%) received chemotherapy and 158 (17.6%) received radiation therapy. The mean OS (overall survival) of the entire cohort was 16.9 months with 1-year and 5-year OS rates of 33% and 5%, respectively. Mean OS for the patients receiving surgery with chemotherapy and/or radiation, surgery alone, chemotherapy and/or radiotherapy alone, and no treatment was 28.4, 17.1, 12.3, and, 8.1 months, respectively (p<0.001). On multivariate cox-regression analysis, advanced-stage disease (stage IV) (p<0.001), no surgical resection (p<0.001), and no receipt of chemotherapy (p<0.001) were associated with increased hazards of death. Over time, the proportion of patients receiving surgical resection (30.7% from 48.3%) and radiation therapy decreased (13.8% from 20.6%) and the use of chemotherapy increased (63.9% from 54.8%). Conclusion: Gastric LP is associated with a poor prognosis. Multimodal therapy including surgical resection and systemic therapy in the neoadjuvant setting seems to provide the best long-term outcomes.
Robustness in Regression Analysis

This research was funded, in part, by National Institutes of Health grant No. 5-TO1-GM-01526. An earlier version of this paper was presented to a symposium, Methodology in Sociology, jointly sponsored by the Methodology Section of the American Sociological Association and Loyola University, Chicago, Illinois, June 1011, 1970. The authors are especially grateful to G. William Walster for his helpful comments on the earlier version of the paper.
How does discharge against medical advice affect risk of mortality and unplanned readmission? A retrospective cohort study set in a large UK medical admissions unit

Objectives To assess the frequency of discharge against medical advice (DAMA) in a large UK teaching hospital, explore factors which increase the risk of DAMA and identify how DAMA impacts patient risk of mortality and readmission. Design Retrospective cohort study. Setting Large acute teaching hospital in the UK. Patients 36 683 patients discharged from the acute medical unit of a large UK teaching hospital between 1 January 2012 and 31 December 2016. Measurements Patients were censored on 1 January 2021. Mortality and 30-day unplanned readmission rates were assessed. Deprivation, age and sex were taken as covariates. Results 3% of patients discharged against medical advice. These patients were younger (median age (years) (IQR)): planned discharge (PD) 59 (40–77); DAMA 39 (28–51), predominantly of male sex (PD 48%; DAMA 66%) and were of greater social deprivation (in three most deprived quintiles PD 69%; DAMA 84%). DAMA was associated with increased risk of death in patients under the age of 33.3 years (adjusted HR 2.6 (1.2–5.8)) and increased incidence of 30-day readmission (standardised incidence ratio 1.9 (1.5–2.2)). Limitations Readmission to acute hospitals outside of the local health board may have been missed. We were unable to include information regarding comorbidity or severity of presentation. Conclusions These data highlight the vulnerability of younger patients who DAMA, even in a free-at-the-point-of-delivery healthcare setting.
Effectiveness of the Project-Based 6E Learning Model

Abstract This research aims to determine the effectiveness of the Project-based 6E (engagement, exploration, explanation, elaboration, extension and evaluation) Learning Model. The researchers created the model by combining the basic features of project-based learning with an understanding of the learning cycle. The pre-test/post-test semi-experimental design, in which no control group is included, was used in the study. The study group in the research consisted of junior students studying at the Turkish Teaching and English Language Teaching departments of the Faculty of Education, Düzce University, in the fall semester of the academic year 2020–2021. The experimental process was structured according to the Project-based 6E Learning Model. Two different types of data, namely, qualitative and quantitative, were collected to determine the effectiveness of the experimental process. It was concluded that the students found the model efficient, effective and attractive. The model positively changed students’ perceptions of values and values education. It was also seen that the model enables students to realise their values, review and question the values, reinforce them, complete their deficiencies and gain new values. Due to the effect of the learning model, students positively experienced significant changes in their teaching perception.
Rayleigh wave propagation in deformed orthotropic materials

A perturbation method is described for the investigation of the propagation of Rayleigh waves on the surface of a homogeneous anisotropic initially deformed material plate. Our perturbation formalism is quite general and can also be applied when other small effects, like slight temperature changes or external magnetic fields, affect the Rayleigh wave propagation velocity. The special cases of slight orthotropy and initial deformations are analyzed in detail. For these cases we derive the Rayleigh wave phase velocity as a function of the propagation direction, the elastic constants, and the initial stresses. The linearity of our formulas suggests that Rayleigh waves can be conveniently used as an experimental technique for the solution of the inverse problem of determining the elastic constants and/or the initial stresses in a material.
Neurosis in General Practice

There have been wide vanat10ns in the results of surveys which estimated the prevalence of neurosis in general practice. In a report prepared by a working party of the Council of the College of General Practitioners ( 1958) it was stated " . psychological illness in any general practice depends not only on the practice but also on the assessor . the generally accepted figure ! is in the region of 30 per cent". Yet there are a number of surveys which found a one-year prevalence rate of neurosis of a:bout 4 per cent. There seem to be several reasons for discrepancies in the findings. The populations differ in various practices (Jones and Miles 1964 ; Shepherd et al. 1964) and this is partly responsible for the variations in the findings. Kessel and Shepherd (1962) have pointed out that different methods have been used to find the proportion of patients suffering from neurosis. Some practitioners expressed the prevalence as percentage of all patients at risk, others as the percentage of patients who had attended, or the percentage of a series of consultations or expressed as the percentage of the practitioner's . work. Kessel (1960) has shown that by using different diagnostic criteria the results vary widely even if the method is the same. Another reason for the discrepancies can be observer bias. Howard (1959) has shown that an observer bias can operate even in a simple condition such as the common cold. In a morbidity survey he found that other general practitioners diagnosed the common cold six times more often than he did. He attributed his own · negative bias to not being ' interested ' in the common cold. Mowbray et al. (1961) found that general practitioners with a declared interest in psychiatry tended to diagnose a larger proportion of patients suffering from neurotic disorders than others. The most important of the~e variables seem to be the diagnostic criteria employed. Neurosis varies in severity and there is evidence to suggest that in a population there is a transition from crippling neurosis on one end of the scale to robust mental health on the other. Therefore the concept of neurosis is somewhat similar to those of intelligence and over-weight and the limits have to be defined before the estimation of prevalence becomes feasible. When the diagnostic criteria in the various surveys are examined their findings become meaningful.
Beyond performance, competence, and recognition: Forging a science researcher identity in the context of research training

Background Studying science identity development has been useful for understanding students’ continuation in science-related education and career paths. Yet, how science contexts shape students’ science identity development, especially as students engage in research at the undergraduate and graduate level, is still largely unexplored. Here we integrate science identity and professional identity theories to investigate how research training shapes science identity. We focus on a specialized form of science identity we call science researcher identity. We characterize how the features of an individual’s research experience, and their personal characteristics interact to influence whether and how they see themselves as a science researcher. We accomplished this in two phases of qualitative research. First, we surveyed 548 undergraduate researchers about how their research experience influenced their identity as a scientist. Then we interviewed 30 early career researchers, including undergraduate, postbaccalaureate, and doctoral students, about their views of themselves as researchers and how elements of their research training shaped their views. Results Early career researchers (ECRs) viewed themselves as either science students or science researchers. How ECRs recognized themselves depended on how they viewed the purpose of their daily work and the extent to which they perceived autonomy and intellectual responsibility in their research. Individual-level factors, including research and researcher conceptions, research skill perceptions, and career intentions, influenced whether ECRs identified as science students or science researchers. ECRs also recognized themselves more or less as researchers based on contextual factors like the nature of their work, social interactions, and their perceptions of the norms within their research group and institution. ECRs considered how individual and contextual factors affected their science researcher identity through a lens we call ‘sense-making. ’ We further detail the processes ECRs use to make sense of their science identity and the factors that influence it. Conclusions We synthesized our findings to form a conceptual model of science researcher identity development, which hypothesizes relationships among constructs related to science identity and professional identity development. Our results advance theory related to science identity, offer avenues for future investigation, and inform efforts to promote science researcher identity development.
A unifying account of replay as context-driven memory reactivation

During rest and sleep, sequential neural activation patterns corresponding to awake experience re-emerge, and this replay has been shown to benefit subsequent behavior and memory. Whereas some studies show that replay directly recapitulates recent experience, others demonstrate that replay systematically deviates from the temporal structure, the statistics, and even the content of recent experience. Given these disparate characteristics, what is the nature and purpose of replay? Here, we offer a theoretical framework in which replay reflects simple context-guided processes that facilitate memory. We suggest that, during awake learning, the brain associates experiences with the contexts in which they are encoded, at encoding rates that vary according to the salience of each experience. During quiescence, replay emerges as the result of a cascade of autonomous bidirectional interactions between contexts and their associated experiences, which in turn facilitates memory consolidation. A computational model instantiating this proposal explains numerous replay phenomena, including findings that existing models fail to account for and observations that have been predominantly construed through the lens of reinforcement learning. Our theory provides a unified, mechanistic framework of how the brain initially encodes and subsequently replays experiences in the service of memory consolidation.