Rhodeswentworth0519

All algorithms achieved a high level of accuracy. Hence, the results show that 80% of the sentiments were positive while 20% were negative.We report the rare case of a 51-year-old patient with a 15 cm mediastinal rhabdomyosarcoma with blood supply from the left anterior descending artery presenting as a large mass including the pericardium with extensive contact to the epicardium compressing heart and left lung. The tumor was successfully removed through median sternotomy, blunt dissection from the heart and the left lung, resection of the infiltrated pericardium, and ligation of the tumor-feeding vessels using off-pump stabilizers. Histopathological examination revealed a spindle cell rhabdomyosarcoma with R0 resection. The postoperative course was uneventful, and patient is feeling well at 3-month follow-up.As survey costs continue to rise and response rates decline, researchers are seeking more cost-effective ways to collect, analyze and process social and public opinion data. These issues have created an opportunity and interest in expanding the fit-for-purpose paradigm to include alternate sources such as passively collected sensor data and social media data. However, methods for accessing, sourcing and sampling social media data are just now being developed. In fact, there has been a small but growing body of literature focusing on comparing different Twitter data access methods through either the elaborate firehose or the free Twitter search or streaming APIs. Missing from the literature is a good understanding of how to randomly sample Tweets to produce datasets that are representative of the daily discourse, especially within geographical regions of interest, without requiring a census of all Tweets. This understanding is necessary for producing quality estimates of public opinion from social media sources such as Twitter. To address this gap, we propose and test the Velocity-Based Estimation for Sampling Tweets (VBEST) algorithm for selecting a probability based sample of tweets. We compare the performance of VBEST sample estimates to other methods of accessing Twitter through the Search API on the distribution of total Tweets as well as COVID-19 keyword incidence and frequency and find that the VBEST samples produce consistent and relatively low levels of overall bias compared to common methods of access through the Search API across many experimental conditions.Micro, small and medium-sized enterprises (MSMEs) have a potential impact on achieving many of the sustainable development goals much greater than their size. This review aimed to investigate existing literature on the contribution of MSMEs to the sustainable development of Ethiopia and its challenges. The review provides a comprehensive and systematic summary of evidence and provides future research directions. A systematic review methodology was adopted through reviewing the available literature comprehensively including research articles, policy documents, and reports over the period 2011-2021 from ScienceDirect, Google Scholar, ECONBIZ, IJSTOR, EBSCO, Web of Science, and Scopus databases. A search on these databases and grey literature returned 1270 articles; 87 papers were included in this review following screening of aticles using pre-determined criteria. The paper found that MSMEs significantly contributed to the sustainable development goals of Ethiopia through creating employment, alleviating poverty, and improving their living standards. However, the review has identified access to finance, access to electricity, and trade regulation are the major constraints for the development of the sector. The review outlines key policy implications to develop a comprehensive policy that alleviates the existing challenges of the sector and calls for further MSMEs impact evaluation research.

This paper is related to the current stage of development in the Western Balkans. Despite becoming growing instruments to finance sustainable green development, debt swaps and social or sustainability bonds are relative novelties in this region. At the same time, the development needs are huge, especially in the light of the COVID-19 aftermath.

The review of both historic financial instruments, such as the debt for nature swaps, and more recent ones, such as sustainability bonds in its variations, highlight the potential for use in developing countries. The relatively recent case from Montenegro and the recent issuance of the green bond in Serbia showcase the possibilities. The focus of this paper is an analysis of the public debt position of Western Balkan countries. The growing level of public debt over the past decade points to a lack of adequate interventions and a relatively imminent need for fiscal consolidation. The research suggests that environmental, social, governance/sustainability-linked bondelp keep the problem of the public debt at bay, while additional funds may support implementation of structural reforms.

The related countries would benefit from exploring more innovative approaches to finance sustainable societies. In close cooperation with the EU and taking the European Green Deal into consideration, it is recommended that the six countries of the Western Balkans design financing mechanisms that will bring increased transparency to the different policies and more accountability for their implementation. Applying the recommended modality may help keep the problem of the public debt at bay, while additional funds may support implementation of structural reforms.

In recent years, the monitoring of occupant presence patterns has become an imperative for building energy optimization. Very often, there is a significant discrepancy between the building energy performance predicted at the design stage and the actual performance rendered during the building operation. This stems from the difference in user occupancy. In spite of this, user interaction and feedback are rarely taken into account and evidence of the impact of occupant presence patterns on energy consumption is still scarce. Thus, the purpose of this study is to apply crowd-sensing techniques to understand how energy is consumed and how appropriate performance indicators should be defined to provide inputs for building operations regarding more efficient use of resources.

Monitoring strategies were implemented in an office lab with controlled variables to collect quantitative data on occupancy patterns, ambient factors and energy consumption. In addition, crowd-sensing techniques were applied to model user y contrary to what was expected. This was because home computers were used as terminals only, while the actual tasks were performed on the lab computers, using remote desktop connections, which were turned on 24/7. In addition, energy consumed by each employee at his/her home should be taken into account. Moreover, a set of practical recommendations was formulated.As telecommunications technology progresses, telehealth frameworks are becoming more widely adopted in the context of long-term care (LTC) for older adults, both in care facilities and in homes. Today, robots could assist healthcare workers when they provide care to elderly patients, who constitute a particularly vulnerable population during the COVID-19 pandemic. Previous work on user-centered design of assistive technologies in LTC facilities for seniors has identified positive impacts. The need to deal with the effects of the COVID-19 pandemic emphasizes the benefits of this approach, but also highlights some new challenges for which robots could be interesting solutions to be deployed in LTC facilities. This requires customization of telecommunication and audio/video/data processing to address specific clinical requirements and needs. This paper presents OpenTera, an open source telehealth framework, aiming to facilitate prototyping of such solutions by software and robotic designers. Designed as a microservice-oriented platform, OpenTera is an end-to-end solution that employs a series of independent modules for tasks such as data and session management, telehealth, daily assistive tasks/actions, together with smart devices and environments, all connected through the framework. After explaining the framework, we illustrate how OpenTera can be used to implement robotic solutions for different applications identified in LTC facilities and homes, and we describe how we plan to validate them through field trials.With the rapid development of the medical device against COVID-19 is an excellent achievement. There are numerous obstacles effectively facing the worldwide population, from manufacture to distribution, deployment and, acceptance. Many manufacturers have entered the market rivalry as people's knowledge and demand for home-use medical equipment has increased. India represents a compelling market opportunity for global medical device manufacturers. Substantial growth for the Indian medical device industry is expected to be driven by the current low per-person spending rate for medical devices. The growth of the medical devices industry in India raises competition law issues (anti-trust) and therefore maintaining public trust in home-use medical devices during COVID-19 will be as essential. The review article aims to create awareness among people about commonly used medical devices during the COVID-19 pandemic and to survey people's trust in home usable medical devices in India. In a worldwide pandemic, manufacturers of medical devices face insufficient storage and the impossibility of meeting the requirements of the health centre. The sale of some of the most significant medical devices has increased, making it more difficult for the medical device industry to satisfy demand with high-quality goods since the quality of COVID-19 items plays a vital part in the present scenario. Despite the difficulty in providing enough medical equipment during a pandemic, they are striving to adapt to the circumstance. After recognizing the need to promote awareness and grasp the selling, and production, handling of medical instruments during COVID-19 at home was conducted. In addition, medical equipment manufacturers and distributors look at this scenario as an opportunity to profit more. JAK inhibitor This review article would enable researchers during COVID-19 to build more knowledge and widespread trust in medical technologies respectively.This study demonstrates that Indigenous local observations and experiences can enrich knowledge of climate change, particularly in data-deficient regions that are not adequately covered by weather stations. Paradoxically, these places host groups of Indigenous Peoples who have rich knowledge about their local climates from their many years of constant interactions with the environment. The study used group-based semi-structured interviews to collaborate with keystone elderly participants who had profound knowledge and lived experiences about observed changes in their local environment (n = 13). These participants were identified through theoretical sampling from four remote Indigenous villages of Mbire District in Zimbabwe. The purpose of the study was to identify indicators of climate change impacts from communities believed not to have been much influenced by the scientific construct of climate change. Results revealed that the locals have a keen interest to closely observe changes occurring in their environment, including finer accounts of experiences with climatic events, owing to their predominantly climate-sensitive livelihoods.