Exploring Diabetes and Users\u27 Lifestyle Choices in Digital Spaces to Improve Health Outcomes

The information derived from social media analytic studies provides valuable sources of information for healthcare stakeholders. However, there is still a lack of research with using social media to identify the lifestyle choices of those dealing with diabetes in order to better understand and design impactful health interventions before an extremity like death occurs due to diabetes. This exploratory study aims to demonstrate how social media can be leveraged as a data source to help us understand the lifestyle choices of those dealing with diabetes. Using two text mining approaches - sentiment analysis and unsupervised topic modeling - food and physiology were topics expressed in both sentiments. Overall, lifestyle related topics accounted for nearly 25% of the topics identified in the corpus of data. There is a pressing need for incorporating predictive modelling approaches to this study in order to quantify our findings and how this knowledge can improve health outcomes from a population perspective

How Norwegian Managers View Dividend Policy

We report the results of a 2004 survey from managers of dividend-paying Norwegian firms listed on the Oslo Stock Exchange about their views on dividend policy. Specifically, we identify the most important factors in making dividend policy decisions and managers\u27 views about various dividend-related issues. The most important determinants of a firm\u27s dividend policy are the level of current and expected future earnings, stability of earnings, current degree of financial leverage, and liquidity constraints. No significant correlation exists between the overall rankings of factors influencing dividend policy between Norwegian and U.S. managers. Norwegian managers express mixed views about whether a firm\u27s dividend policy affects firm value. Respondents point to the possible role of dividend policy as a signaling mechanism. No support exists for the tax-preference explanation for paying dividends

Simultaneous Noun and Category Learning via Cross-Situational Statistics

Abstract Previous research shows that people can acquire an impressive number of word-referent pairs after viewing a series of ambiguous trials by accumulating co-occurrence statistics (e.g., Yu & Smith, 2006). The present study extends the cross-situational word learning paradigm, which has previously dealt only with noun acquisition, and shows that humans can concurrently acquire nouns and adjectives (i.e., a natural category with a distinctive, unifying feature). Furthermore, participants are able to learn ad hoc categories of referents consistently cooccurring with a label, while simultaneously learning instance labels. Thus, humans demonstrate an impressive ability to simultaneously apprehend regularities at multiple levels in their environment

Etiology and Outcomes of ARDS in a Rural-Urban Fringe Hospital of South India

Objectives. Etiology and outcomes of acute lung injury in tropical countries may be different from those of western nations. We describe the etiology and outcomes of illnesses causing acute lung injury in a rural populace. Study Design. A prospective observational study. Setting. Medical ICU of a teaching hospital in a rural-urban fringe location. Patients. Patients ≥13 years, admitted between December 2011 and May 2013, satisfying AECC criteria for ALI/ARDS. Results. Study had 61 patients; 46 had acute lung injury at admission. Scrub typhus was the commonest cause (7/61) and tropical infections contributed to 26% of total cases. Increasing ARDS severity was associated with older age, higher FiO(2) and APACHE/SOFA scores, and longer duration of ventilation. Nonsurvivors were generally older, had shorter duration of illness, a nontropical infection, and higher total WBC counts, required longer duration of ventilation, and had other organ dysfunction and higher mean APACHE scores. The mortality rate of ARDS was 36.6% (22/61) in our study. Conclusion. Tropical infections form a major etiological component of acute lung injury in a developing country like India. Etiology and outcomes of ARDS may vary depending upon the geographic location and seasonal illnesses

Activity based Traffic Indicator System for Monitoring the COVID-19 Pandemic

This study describes an activity based traffic indicator system to provide information for COVID-19 pandemic management. The activity based traffic indicator system does this by utilizing a social probability model based on the birthday paradox to determine the exposure risk, the probability of meeting someone infected (PoMSI). COVID-19 data, particularly the 7-day moving average of the daily growth rate of cases (7-DMA of DGR) and cumulative confirmed cases of next week covering a period from April to September 2020, were then used to test PoMSI using Pearson correlation to verify whether it can be used as a factor for the indicator. While there is no correlation for the 7-DMA of DGR, PoMSI is strongly correlated (0.671 to 0.996) with the cumulative confirmed cases and it can be said that as the cases continuously rise, the probability of meeting someone COVID positive will also be higher. This shows that indicator not only shows the current exposure risk of certain activities but it also has a predictive nature since it correlates to cumulative confirmed cases of next week and can be used to anticipate the values of confirmed cumulative cases. This information can then be used for pandemic management

Biomechanical Evaluation of Recurrent Dissociation of Modular Humeral Prostheses

The purpose of the study was to evaluate the force and torque required to dissociate a humeral head from the unimplanted modular total shoulder replacement system from different manufacturers and to determine if load and torque to dissociation are reduced in the presence of bodily fluids. Impingement, taper contamination, lack of compressive forces, and interference of taper fixation by the proximal humerus have all been reported as possible causes for dissociation. Experimental values determined in this research were compared with literature estimates of dissociation force of the humeral head under various conditions to gain more understanding of the causes of recurrent dissociations of the humeral head. This study examined biomechanical properties under dry and wet conditions under clinically practiced methods. Mean load to dissociation (1513 N ± 508 N) was found to be greater than that exerted by the activities of daily living (578 N) for all implants studied. The mean torque to dissociation was (49.77 N·m ± 19.07 N·m). Analysis of R2 correlation coefficients and p-values (α = 0.05) did not show any significant correlation between dry/bovine, dry/wet, or wet/bovine for load, displacement, or torsional stiffness in the majority of tests performed. Wetting the taper with water or bovine serum did not reduce the dissociation force to a statistically significant degree. Torque and lack of compressive forces at the rotator cuff may be the cause of dissociation at values less than those of activities of daily living. Torque data are provided by this study, but further research is needed to fully appreciate the role of torque in recurrent dissociations

Etiology and Outcomes of ARDS in a Rural-Urban Fringe Hospital of South India

Objectives. Etiology and outcomes of acute lung injury in tropical countries may be different from those of western nations. We describe the etiology and outcomes of illnesses causing acute lung injury in a rural populace. Study Design. A prospective observational study. Setting. Medical ICU of a teaching hospital in a rural-urban fringe location. Patients. Patients ≥13 years, admitted between December 2011 and May 2013, satisfying AECC criteria for ALI/ARDS. Results. Study had 61 patients; 46 had acute lung injury at admission. Scrub typhus was the commonest cause (7/61) and tropical infections contributed to 26% of total cases. Increasing ARDS severity was associated with older age, higher FiO 2 and APACHE/SOFA scores, and longer duration of ventilation. Nonsurvivors were generally older, had shorter duration of illness, a nontropical infection, and higher total WBC counts, required longer duration of ventilation, and had other organ dysfunction and higher mean APACHE scores. The mortality rate of ARDS was 36.6% (22/61) in our study. Conclusion. Tropical infections form a major etiological component of acute lung injury in a developing country like India. Etiology and outcomes of ARDS may vary depending upon the geographic location and seasonal illnesses

Sessile Serrated Adenomas in the Proximal Colon are Likely to be Flat, Large and Occur in Smokers

Aim: To examine the epidemiology and the morphology of the proximal sessile serrated adenomas (SSAs). Methods: We conducted a retrospective study to identify patients with SSAs using a university-based hospital pathology database query from January 2007 to April 2011. Data collected included: age, gender, ethnicity, body mass index, diabetes, smoking, family history of colorectal cancer, aspirin, and statin use. We collected data on morphology of SSAs including site (proximal or distal), size, and endoscopic appearance (flat or protuberant). We also compared proximal SSAs to proximal tubular adenomas detected during same time period

Performance Evaluation of Face Mask Detection for Real-Time Implementation on an RPi

Mask-wearing remains to be one of the primary protective measures against COVID-19. To address the difficulty of manual compliance monitoring, face mask detection models considerate of both frontal and angled faces were developed. This study aimed to test the performance of the said models in classifying multi-face images and upon running on a Raspberry Pi device. The accuracies and inference speeds were measured and compared when inferencing images with one, two, and three faces and on the desktop and the Raspberry Pi. With an increasing number of faces in an image, the models’ accuracies were observed to decline, while their speeds were not significantly affected. Moreover, the YOLOv5 Small model was regarded to be potentially the best model for use on lower resource platforms, as it experienced a 3.33% increase in accuracy and recorded the least inference time of two seconds per image among the models