scholarly journals Talking about what would happen versus what happened: Tracking Congressional speeches during COVID-19

2021 ◽  
Vol 9 (2) ◽  
pp. 608-622
Author(s):  
Rinseo Park ◽  
Young Min Baek
Keyword(s):  
Public Health ◽  
Natural Language Processing ◽  
Political Communication ◽  
Language Processing ◽  
Counterfactual Thinking ◽  
Institutional Constraints ◽  
Future Research ◽  
The Past ◽  
Party Differences

In counterfactual thinking, an imagined alternative to the reality that comprises an antecedent and a consequent is widely adopted in political discourse to justify past behaviors (i.e., counterfactual explanation) or to depict a better future (i.e., prefactual). However, they have not been properly addressed in political communication literature. Our study examines how politicians used counterfactual expressions for explanation of the past or preparation of the future during COVID-19, one of the most severe public health crises. All Congressional speeches of the Senate and House in the 116th Congress (2019-2020) were retrieved, and counterfactual expressions were identified along with time-focusing in each speech, using recent advances in natural language processing (NLP) techniques. The results show that counterfactuals were more practiced among Democrats in the Senate and Republicans in the House. With the spread of the pandemic, the use of counterfactuals decreased, maintaining a partisan gap in the House. However, it was nearly stable, with no party differences in the Senate. Implications of our findings are discussed, regarding party polarization, institutional constraints, and the quality of Congressional deliberation. Limitations and suggestions for future research are also provided.

What's my App?

2021 ◽  
Vol 48 (4) ◽  
pp. 41-44
Author(s):  
Dena Markudova ◽  
Martino Trevisan ◽  
Paolo Garza ◽  
Michela Meo ◽  
Maurizio M. Munafo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Natural Language Processing ◽  
Real Time ◽  
Language Processing ◽  
Traffic Management ◽  
Quality Of Experience ◽  
Broadband Internet ◽  
Management Policies ◽  
Control Traffic

With the spread of broadband Internet, Real-Time Communication (RTC) platforms have become increasingly popular and have transformed the way people communicate. Thus, it is fundamental that the network adopts traffic management policies that ensure appropriate Quality of Experience to users of RTC applications. A key step for this is the identification of the applications behind RTC traffic, which in turn allows to allocate adequate resources and make decisions based on the specific application's requirements. In this paper, we introduce a machine learning-based system for identifying the traffic of RTC applications. It builds on the domains contacted before starting a call and leverages techniques from Natural Language Processing (NLP) to build meaningful features. Our system works in real-time and is robust to the peculiarities of the RTP implementations of different applications, since it uses only control traffic. Experimental results show that our approach classifies 5 well-known meeting applications with an F1 score of 0.89.

scholarly journals Multi-organ point-of-care ultrasound for COVID-19 (PoCUS4COVID): international expert consensus

Critical Care ◽  
2020 ◽  
Vol 24 (1) ◽  
Author(s):  
Arif Hussain ◽  
Gabriele Via ◽  
Lawrence Melniker ◽  
Alberto Goffi ◽  
Guido Tavazzi ◽  
...  
Keyword(s):  
Lung Ultrasound ◽  
Expert Panel ◽  
Point Of Care ◽  
Expert Consensus ◽  
Future Research ◽  
Point Of Care Ultrasound ◽  
The Past ◽  
Modified Delphi ◽  
Grade Methodology

AbstractCOVID-19 has caused great devastation in the past year. Multi-organ point-of-care ultrasound (PoCUS) including lung ultrasound (LUS) and focused cardiac ultrasound (FoCUS) as a clinical adjunct has played a significant role in triaging, diagnosis and medical management of COVID-19 patients. The expert panel from 27 countries and 6 continents with considerable experience of direct application of PoCUS on COVID-19 patients presents evidence-based consensus using GRADE methodology for the quality of evidence and an expedited, modified-Delphi process for the strength of expert consensus. The use of ultrasound is suggested in many clinical situations related to respiratory, cardiovascular and thromboembolic aspects of COVID-19, comparing well with other imaging modalities. The limitations due to insufficient data are highlighted as opportunities for future research.

Preventive aspect of ayurveda and yoga towards newly emerging disease COVID-19

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ranjeet S. Sawant ◽  
Bharat D. Zinjurke ◽  
Sandeep V. Binorkar
Keyword(s):  
Public Health ◽  
Severe Acute Respiratory Syndrome ◽  
Medical Care ◽  
Supportive Therapy ◽  
Prophylactic Therapy ◽  
Current Line ◽  
Therapeutic Aspect ◽  
The Past

Abstract The ongoing coronavirus pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS CoV 2) and unique in various facets. The earlier experience from the past severe acute respiratory syndrome (SARS) epidemics seem to be insufficient and there is need for better strategies in public health and medical care. Ayurved & Yog are well known for their preventive and therapeutic aspect, but not getting utilized properly for prevention of Covid 19 crisis which may also be helpful as supportive therapy along with current line of management. This paper is aimed at unrevealing the role of Ayurved and Yoga guidelines established by Department of AYUSH for prevention from SARS-CoV-2 by providing help to improving the quality of supportive/prophylactic therapy in relation with their immunity.

scholarly journals The balance between food and dietary supplements in the general population

2018 ◽  
Vol 78 (1) ◽  
pp. 97-109 ◽  
Author(s):  
Marleen A. H. Lentjes
Keyword(s):  
Public Health ◽  
Nutrient Intake ◽  
Supplement Use ◽  
The Past ◽  
Nutrition Guidelines ◽  
Public Health Messages ◽  
Dietary Supplement Use ◽  
The Uk ◽  
Deficiency Diseases

In the past, vitamins and minerals were used to cure deficiency diseases. Supplements nowadays are used with the aim of reducing the risk of chronic diseases of which the origins are complex. Dietary supplement use has increased in the UK over recent decades, contributing to the nutrient intake in the population, but not necessarily the proportion of the population that is sub-optimally nourished; therefore, not reducing the proportion below the estimated average requirement and potentially increasing the number at risk of an intake above the safety limits. The supplement nutrient intake may be objectively monitored using circulation biomarkers. The influence of the researcher in how the supplements are grouped and how the nutrient intakes are quantified may however result in different conclusions regarding their nutrient contribution, the associations with biomarkers, in general, and dose–response associations specifically. The diet might be sufficient in micronutrients, but lacking in a balanced food intake. Since public-health nutrition guidelines are expressed in terms of foods, there is potentially a discrepancy between the nutrient-orientated supplement and the quality of the dietary pattern. To promote health, current public-health messages only advocate supplements in specific circumstances, but not in optimally nourished populations.

scholarly journals Comparison of Two Forced Alignments Systems for Aligning Bribri Speech

2017 ◽  
Author(s):  
Sofía Flores Solórzano ◽  
Rolando Coto-Solano
Keyword(s):  
Natural Language Processing ◽  
Speech Recognition ◽  
Language Processing ◽  
Indigenous Languages ◽  
Future Research ◽  
Automated Speech Recognition ◽  
Recognition Systems ◽  
Para Determinar ◽  
Future Work ◽  
Manual Correction

Abstract: Forced alignment provides drastic savings in time when aligning speech recordings and is particularly useful for the study of Indigenous languages, which are severely under-resourced in corpora and models. Here we compare two forced alignment systems, FAVE-align and EasyAlign, to determine which one provides more precision when processing running speech in the Chibchan language Bribri. We aligned a segment of a story narrated in Bribri and compared the errors in finding the center of the words and the edges of phonemes when compared with the manual correction. FAVE-align showed better performance: It has an error of 7% compared to 24% with EasyAlign when finding the center of words, and errors of 22~24 ms when finding the edges of phonemes, compared to errors of 86~130 ms with EasyAlign. In addition to this, EasyAlign failed to detect 7% of phonemes, while also inserting 58 spurious phones into the transcription. Future research includes verifying these results for other genres and other Chibchan languages. Finally, these results provide additional evidence for the applicability of natural language processing methods to Chibchan languages and point to future work such as the construction of corpora and the training of automated speech recognition systems.  Spanish Abstract: El alineamiento forzado provee un ahorro drástico de tiempo al alinear grabaciones del habla, y es útil para el estudio de las lenguas indígenas, las cuales cuentan con pocos recursos para generar corpus y modelos computacionales. Aquí comparamos dos sistemas de alineamiento, FAVE-align e EasyAlign, para determinar cuál provee mayor precisión al alinear habla en la lengua chibcha bribri. Alineamos una narración y comparamos el error al tratar de encontrar el centro de las palabras y los bordes de los fonemas con sus equivalentes en una corrección manual. FAVE-align tuvo mejor rendimiento, con un error de 7% comparado con 24% de EasyAlign para el centro de las palabras, y con errores de 22~24 ms para el borde de los fonemas, comparado con 86~130 ms con EasyAlign. Además, EasyAlign no pudo detectar el 7% de los fonemas, y al mismo tiempo añadió 58 sonidos espurios a la transcripción. Como trabajo futuro verificaremos estos resultados con otros géneros hablados y con otras lenguas chibchas. Finalmente, estos resultados comprueban la aplicabilidad de los métodos de procesamiento de lengua natural a las lenguas chibchas, y apuntan a trabajo futuro en la construcción de corpus y el entrenamiento de sistemas de reconocimiento automático del habla.

scholarly journals Sentiment of App with Word Vectors

2019 ◽  
Vol 8 (6S3) ◽  
pp. 2156-2159
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Text Data ◽  
Vector Representations ◽  
Text Sentiment Analysis

Vector representations for language have been shown to be useful in a number of Natural Language Processing tasks. In this paper, we aim to investigate the effectiveness of word vector representations for the problem of Sentiment Analysis. In particular, we target three sub-tasks namely sentiment words extraction, polarity of sentiment words detection, and text sentiment prediction. We investigate the effectiveness of vector representations over different text data and evaluate the quality of domain-dependent vectors. Vector representations has been used to compute various vector-based features and conduct systematically experiments to demonstrate their effectiveness. Using simple vector based features can achieve better results for text sentiment analysis of APP.

Restaurant and foodservice research

2017 ◽  
Vol 29 (4) ◽  
pp. 1203-1234 ◽  
Author(s):  
Robin DiPietro
Keyword(s):  
Past Research ◽  
Future Research ◽  
Research Papers ◽  
Content Type ◽  
The Past ◽  
Restaurant Management ◽  
Foodservice Industry ◽  
Future Direction

Purpose The purpose of this paper is to present a review of the foodservice and restaurant literature that has been published over the past 10 years in the top hospitality and tourism journals. This information will be used to identify the key trends and topics studied over the past decade, and help to identify the gaps that appear in the research to identify opportunities for advancing future research in the area of foodservice and restaurant management. Design/methodology/approach This paper takes the form of a critical review of the extant literature that has been done in the foodservice and restaurant industries. Literature from the past 10 years will be qualitatively assessed to determine trends and gaps in the research to help guide the direction for future research. Findings The findings show that the past 10 years have seen an increase in the number of and the quality of foodservice and restaurant management research articles. The topics have been diverse and the findings have explored the changing and evolving segments of the foodservice industry, restaurant operations, service quality in foodservice, restaurant finance, foodservice marketing, food safety and healthfulness and the increased role of technology in the industry. Research limitations/implications Given the number of research papers done over the past 10 years in the area of foodservice, it is possible that some research has been missed and that some specific topics within the breadth and depth of the foodservice industry could have lacked sufficient coverage in this one paper. The implications from this paper are that it can be used to inform academics and practitioners where there is room for more research, it could provide ideas for more in-depth discussion of a specific topic and it is a detailed start into assessing the research done of late. Originality/value This paper helps foodservice researchers in determining where past research has gone and gives future direction for meaningful research to be done in the foodservice area moving forward to inform academicians and practitioners in the industry.

scholarly journals Automatic Identification of Information Quality Metrics in Health News Stories

2020 ◽  
Vol 8 ◽  
Author(s):  
Majed Al-Jefri ◽  
Roger Evans ◽  
Joon Lee ◽  
Pietro Ghezzi
Keyword(s):  
Machine Learning ◽  
Health Care ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Information Quality ◽  
Evaluation Process ◽  
Health News ◽  
News Stories

Objective: Many online and printed media publish health news of questionable trustworthiness and it may be difficult for laypersons to determine the information quality of such articles. The purpose of this work was to propose a methodology for the automatic assessment of the quality of health-related news stories using natural language processing and machine learning.Materials and Methods: We used a database from the website HealthNewsReview.org that aims to improve the public dialogue about health care. HealthNewsReview.org developed a set of criteria to critically analyze health care interventions' claims. In this work, we attempt to automate the evaluation process by identifying the indicators of those criteria using natural language processing-based machine learning on a corpus of more than 1,300 news stories. We explored features ranging from simple n-grams to more advanced linguistic features and optimized the feature selection for each task. Additionally, we experimented with the use of pre-trained natural language model BERT.Results: For some criteria, such as mention of costs, benefits, harms, and “disease-mongering,” the evaluation results were promising with an F1 measure reaching 81.94%, while for others the results were less satisfactory due to the dataset size, the need of external knowledge, or the subjectivity in the evaluation process.Conclusion: These used criteria are more challenging than those addressed by previous work, and our aim was to investigate how much more difficult the machine learning task was, and how and why it varied between criteria. For some criteria, the obtained results were promising; however, automated evaluation of the other criteria may not yet replace the manual evaluation process where human experts interpret text senses and make use of external knowledge in their assessment.

Quality of life following surgery for congenital cardiac malformations in neonates and infants

2005 ◽  
Vol 15 (S1) ◽  
pp. 174-178 ◽  
Author(s):  
Kathleen Mussatto ◽  
James Tweddell
Keyword(s):  
Quality Of Life ◽  
Future Research ◽  
Cardiac Malformations ◽  
The Past ◽  
Congenital Cardiac Disease ◽  
Major Shift ◽  
Neonates And Infants ◽  
The Impact

The past two decades have witnessed a major shift towards repair of most congenital cardiac malformations during the neonatal or infant periods of life.1 Early anatomic correction or palliation, dramatic improvements in survival, and reduced morbidity due to improvements in perioperative and long-term medical management, have resulted in new populations of children that have reaped the benefits of the best care currently available for treatment of congenital cardiac disease. The impact of the congenital cardiac malformations, however, extends far beyond the walls of the hospital or clinic where we diagnose, treat, and follow our patients. The breakthrough of achieving predictable results with repair or palliation of most lesions during the neonatal and infant periods mandates us to look beyond survival, and to examine the lives our patients lead when they are outside of our care. Our purpose in this review is to discuss the measures of psychosocial outcome that are appropriate for exploration in those neonates and infants who survive cardiac surgery, to explore what is known about the psychosocial outcomes and quality of life for these patients, and what needs exist for future research.

Identifying Heart Failure Symptoms and Poor Self-Management in Home Healthcare: A Natural Language Processing Study

2021 ◽  
Author(s):  
Sena Chae ◽  
Jiyoun Song ◽  
Marietta Ojo ◽  
Maxim Topaz
Keyword(s):  
Heart Failure ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Symptom Management ◽  
Home Healthcare ◽  
Self Management ◽  
Clinical Notes ◽  
Patients With Heart Failure

The goal of this natural language processing (NLP) study was to identify patients in home healthcare with heart failure symptoms and poor self-management (SM). The preliminary lists of symptoms and poor SM status were identified, NLP algorithms were used to refine the lists, and NLP performance was evaluated using 2.3 million home healthcare clinical notes. The overall precision to identify patients with heart failure symptoms and poor SM status was 0.86. The feasibility of methods was demonstrated to identify patients with heart failure symptoms and poor SM documented in home healthcare notes. This study facilitates utilizing key symptom information and patients’ SM status from unstructured data in electronic health records. The results of this study can be applied to better individualize symptom management to support heart failure patients’ quality-of-life.

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