bluuebunny/crossref_metadata_2025 huggingface dataset:
Medición de la gestión de la calidad en turismo y hospitalidad: propuestas y experiencias
Authors: Santana Moncayo César Augusto , Rosero Barzola Christian Xavier , Vasallo Villalonga Yoarnelys , Enríquez Hidalgo Manuela Ángela , Granizo Álava Ivette Mariam , Gutiérrez Zambrano Gianella Abigail , Vélez Del Hierro César Andrés
Published: July 2021

La calidad en los servicios turísticos es un tema de larga data en distintos tipos de investigaciones. Esto se debe a que el turismo debe convivir con los gustos y pareceres de muchas personas, quienes, a su vez, determinan sus preferencias con base en estándares establecidos, tanto por el mercado como por su propio imaginario social. En este orden de ideas, se hace muy complicado medir de forma eficaz la calidad de los servicios turísticos, porque para una comunidad (por una parte) lo que es un servicio de calidad, para un viajero experimentado apenas podría pasar por un servicio adecuado. Sin embargo, muchos autores han tratado de estandarizar y regular objetivamente algunos índices de medición de la calidad de los servicios, precisamente, porque se vuelve un tema demasiado subjetivo, debido a que depende tanto de los gustos personales como de las propuestas que ofrezcan los servicios turísticos.
Osteoporosis in Postmenopausal Women with Breast Cancer
Authors:   Dubin Breast Cancer, Icahn School of Medicine at Mt Sinai, New York, NY 10029, US, Lamond Jacqueline , Shapiro Charles L. ,   Dubin Breast Cancer, Icahn School of Medicine at Mt Sinai, New York, NY 10029, US
Published: July 2021

Breast cancer and osteoporosis are both diseases of aging. The "one in eight" lifetime risks of breast cancer occur primarily in the sixth, seventh, eighth, and ninth decades of life. One-third of postmenopausal women will experience an osteoporotic fracture. It is the coalescence of osteoporosis, breast cancer, and breast cancer treatments that, in some cases, increases the risks of osteoporotic fracture. That makes it imperative to assess risk factors, screen, and prevent or treat osteoporosis in postmenopausal women with breast cancer. Osteoporosis is primarily a genetic disease with a few modifiable risk factors. These risk factors include greater than two to three alcoholic drinks per day, current smoking, and decreased physical activity. The standard screening tool for osteoporosis is dual-energy x-ray absorptiometry (DXA) that gives a readout of T-scores of the lumbar spine, total hip, and femoral neck. The T-score is the number of standard deviations (SD) above or below the mean bone mineral density (BMD) of an average young adult of the same sex. For every SD below the mean BMD, the fracture risks double. Osteoporosis prevention and treatment do not differ in women with or without breast cancer. The difference is in breast cancer treatments, such as aromatase inhibitors (AI), which cause two to three-fold higher bone loss than average postmenopausal bone loss. Two classes of drugs for osteoporosis are oral and intravenous (iv) bisphosphonates and the receptor activator of nuclear factor kappa B ligand (RANKL) ligand inhibitor, subcutaneous (sc) denosumab. All three prevent bone loss and reduce the likelihood of fragility fractures. The treatment choice depends upon patient and provider preferences, specific contraindications (e.g., renal insufficiency), compliance, and costs. Despite guidelines and algorithms for AI-induced bone loss, the screening and treatment of osteoporosis remain suboptimal in postmenopausal women with breast cancer.
Impact of Osteophytectomy on Swallowing Function in a Patient with Chronic Dysphagia
Authors:   Acute Rehabilitation, Casa Colina Hospital and Centers for Healthcare Pomona, California, USA, Howard Melissa M , Phillips Justin ,   Acute Rehabilitation, Casa Colina Hospital and Centers for Healthcare Pomona, California, USA, Henley Stefan ,   Acute Rehabilitation, Casa Colina Hospital and Centers for Healthcare Pomona, California, USA, Green Sarah E. ,   Acute Rehabilitation, Casa Colina Hospital and Centers for Healthcare Pomona, California, USA, Rosario Emily R. ,   Acute Rehabilitation, Casa Colina Hospital and Centers for Healthcare Pomona, California, USA
Published: July 2021

Anterior cervical osteophytes are common in the geriatric population. Dysphagia can occur in individuals suffering from these spinal abnormalities. Surgical intervention is an uncommon course of treatment for these patients, but is often utilized as a last resort with the hope of swallow recovery. The purpose of this article is to highlight a unique case study documenting the required treatment course for dysphagia associated with osteophytes and subsequent osteophytectomy. We review current literature of both conservative and surgical interventions, as well as discuss the rehabilitation course for a complex patient with persistent dysphagia. Various outcome measures were utilized during the patient’s inpatient stay to track progress including the Functional Oral Intake Scale (FOIS), the Bolus Residue Scale (BRS), Penetration Aspiration Scale (PenAsp), Dysphagia Outcome Severity Scale (DOSS), and a Modified Barium Swallow Study (MBSS). The patient received rehabilitative training including oral motor and pharyngeal strengthening exercises, respiratory strengthening, speech instruction, cognitive retraining, and instrumental assessment. Following osteophytectomy and dysphagia rehabilitation the patient did not show any change based on a repeat MBSS which revealed the necessity for the patient to remain nothing per oral (NPO). The patient demonstrated an inability to manage his secretions, requiring continual suctioning. Upon discharge the patient remained NPO with the exception of ice chips, utilized a PEG for nutrition, and had a red capped tracheostomy. He was on room air and independently utilized oral suction as needed for secretion management. Our patient’s clinical course was not aligned with typical osteophytectomy recovery as progress after his 25-day inpatient stay was limited. The goal of this case study is to contribute information to the limited and variable data available regarding treatment options, outcome measures and timelines for recovery as it pertains to patients who undergo an osteophytectomy.
The Development of a Web-Based Tobacco Tracker Tool to Crowdsource Campus Environmental Reports for Smoke and Tobacco–Free College Policies: Mixed Methods Study
Authors: Loureiro Sabrina F , Pulvers Kim , Gosdin Melissa M , Clift Keavagh , Rice Myra , Tong Elisa K
Published: July 2021

Background

College campuses in the United States have begun implementing smoke and tobacco–free policies to discourage the use of tobacco. Smoke and tobacco–free policies, however, are contingent upon effective policy enforcement.

Objective

This study aimed to develop an empirically derived web-based tracking tool (Tracker) for crowdsourcing campus environmental reports of tobacco use and waste to support smoke and tobacco–free college policies.

Methods

An exploratory sequential mixed methods approach was utilized to inform the development and evaluation of Tracker. In October 2018, three focus groups across 2 California universities were conducted and themes were analyzed, guiding Tracker development. After 1 year of implementation, users were asked in April 2020 to complete a survey about their experience.

Results

In the focus groups, two major themes emerged: barriers and facilitators to tool utilization. Further Tracker development was guided by focus group input to address these barriers (eg, information, policing, and logistical concerns) and facilitators (eg, environmental motivators and positive reinforcement). Amongst 1163 Tracker reports, those who completed the user survey (n=316) reported that the top motivations for using the tool had been having a cleaner environment (212/316, 79%) and health concerns (185/316, 69%).

Conclusions

Environmental concerns, a motivator that emerged in focus groups, shaped Tracker’s development and was cited by the majority of users surveyed as a top motivator for utilization.
Leading Topics in Twitter Discourse on JUUL and Puff Bar Products: Content Analysis
Authors: Allem Jon-Patrick , Dormanesh Allison , Majmundar Anuja , Rivera Vanessa , Chu Maya , Unger Jennifer B , Cruz Tess Boley
Published: July 2021

Background

In response to the recent government restrictions, flavored JUUL products, which are rechargeable closed-system electronic cigarettes (e-cigarettes), are no longer available for sale. However, disposable closed-system products such as the flavored Puff Bar e-cigarette continues to be available. If e-cigarette consumers simply switch between products during the current government restrictions limited to 1 type of product over another, then such restrictions would be less effective. A step forward in this line of research is to understand how the public discusses these products by examining discourse referencing both Puff Bar and JUUL in the same conversation. Twitter data provide ample opportunity to capture such early trends that could be used to help public health researchers stay abreast of the rapidly changing e-cigarette marketplace.

Objective

The goal of this study was to examine public discourse referencing both Puff Bar and JUUL products in the same conversation on Twitter.

Methods

We collected data from Twitter’s streaming application programming interface between July 16, 2019, and August 29, 2020, which included both “Puff Bar” and “JUUL” (n=2632). We then used an inductive approach to become familiar with the data and generate a codebook to identify common themes. Saturation was determined to be reached with 10 themes.

Results

Posts often mentioned flavors, dual use, design features, youth use, health risks, switching 1 product for the other, price, confusion over the differences between products, longevity of the products, and nicotine concentration.

Conclusions

On examining the public’s conversations about Puff Bar and JUUL products on Twitter, having described themes in posts, this study aimed to help the tobacco control community stay informed about 2 popular e-cigarette products with different device features, which can be potentially substituted for one another. Future health communication campaigns may consider targeting the health consequences of using multiple e-cigarette products or dual use to reduce exposure to high levels of nicotine among younger populations.
Identifying Communities at Risk for COVID-19–Related Burden Across 500 US Cities and Within New York City: Unsupervised Learning of the Coprevalence of Health Indicators
Authors: Deonarine Andrew , Lyons Genevieve , Lakhani Chirag , De Brouwer Walter
Published: July 2021

Background

Although it is well-known that older individuals with certain comorbidities are at the highest risk for complications related to COVID-19 including hospitalization and death, we lack tools to identify communities at the highest risk with fine-grained spatial resolution. Information collected at a county level obscures local risk and complex interactions between clinical comorbidities, the built environment, population factors, and other social determinants of health.

Objective

This study aims to develop a COVID-19 community risk score that summarizes complex disease prevalence together with age and sex, and compares the score to different social determinants of health indicators and built environment measures derived from satellite images using deep learning.

Methods

We developed a robust COVID-19 community risk score (COVID-19 risk score) that summarizes the complex disease co-occurrences (using data for 2019) for individual census tracts with unsupervised learning, selected on the basis of their association with risk for COVID-19 complications such as death. We mapped the COVID-19 risk score to corresponding zip codes in New York City and associated the score with COVID-19–related death. We further modeled the variance of the COVID-19 risk score using satellite imagery and social determinants of health.

Results

Using 2019 chronic disease data, the COVID-19 risk score described 85% of the variation in the co-occurrence of 15 diseases and health behaviors that are risk factors for COVID-19 complications among ~28,000 census tract neighborhoods (median population size of tracts 4091). The COVID-19 risk score was associated with a 40% greater risk for COVID-19–related death across New York City (April and September 2020) for a 1 SD change in the score (risk ratio for 1 SD change in COVID-19 risk score 1.4; P<.001) at the zip code level. Satellite imagery coupled with social determinants of health explain nearly 90% of the variance in the COVID-19 risk score in the United States in census tracts (r2=0.87).

Conclusions

The COVID-19 risk score localizes risk at the census tract level and was able to predict COVID-19–related mortality in New York City. The built environment explained significant variations in the score, suggesting risk models could be enhanced with satellite imagery.
e-Cigarette Cessation: Content Analysis of a Quit Vaping Community on Reddit
Authors: Struik Laura , Yang Youjin
Published: July 2021

Background

e-Cigarette use, also known as vaping, has increased dramatically over the past few years, especially among younger demographics. However, researchers have found that a large number of e-cigarette users want to quit. Little is known about the unique aspects of vaping cessation, which is critical to informing the development of relevant resources and interventions for e-cigarette users who want to quit. Social media forums such as Reddit provide opportunities to understand the experiences of behavior change such as quitting vaping from the perspective of end users.

Objective

This study aims to examine a quit vaping subreddit to understand how e-cigarette users are experiencing and approaching vaping cessation. Specifically, we examine methods used to approach quitting, reasons for quitting, and barriers and facilitators to quitting.

Methods

A total of 1228 posts were collected. The posts were inductively coded to generate categories and subcategories using conventional content analysis. Data were analyzed using the NVivo 12 qualitative data analysis software.

Results

Most users reported a preference for approaching quitting through gradual reduction, particularly through the use of their own devices by tapering the nicotine content. Their reasons for quitting were primarily related to experiencing negative physical consequences associated with vaping, especially in relation to their lungs (eg, tight chest), and tired of feeling stuck to the vape because of nicotine addiction. Top barriers to quitting were related to withdrawal symptoms and intensity of addiction. The top facilitators to quitting were related to using distraction techniques (eg, hobby, gaming, and mindfulness exercises), as well as having a positive mindset.

Conclusions

The findings of this study reveal unique aspects that encompass the process of quitting vaping. These findings have significant implications for both policy and intervention development.
Categorizing Vaccine Confidence With a Transformer-Based Machine Learning Model: Analysis of Nuances of Vaccine Sentiment in Twitter Discourse
Authors: Kummervold Per E , Martin Sam , Dada Sara , Kilich Eliz , Denny Chermain , Paterson Pauline , Larson Heidi J
Published: July 2021

Background

Social media has become an established platform for individuals to discuss and debate various subjects, including vaccination. With growing conversations on the web and less than desired maternal vaccination uptake rates, these conversations could provide useful insights to inform future interventions. However, owing to the volume of web-based posts, manual annotation and analysis are difficult and time consuming. Automated processes for this type of analysis, such as natural language processing, have faced challenges in extracting complex stances such as attitudes toward vaccination from large amounts of text.

Objective

The aim of this study is to build upon recent advances in transposer-based machine learning methods and test whether transformer-based machine learning could be used as a tool to assess the stance expressed in social media posts toward vaccination during pregnancy.

Methods

A total of 16,604 tweets posted between November 1, 2018, and April 30, 2019, were selected using keyword searches related to maternal vaccination. After excluding irrelevant tweets, the remaining tweets were coded by 3 individual researchers into the categories Promotional, Discouraging, Ambiguous, and Neutral or No Stance. After creating a final data set of 2722 unique tweets, multiple machine learning techniques were trained on a part of this data set and then tested and compared with the human annotators.

Results

We found the accuracy of the machine learning techniques to be 81.8% (F score=0.78) compared with the agreed score among the 3 annotators. For comparison, the accuracies of the individual annotators compared with the final score were 83.3%, 77.9%, and 77.5%.

Conclusions

This study demonstrates that we are able to achieve close to the same accuracy in categorizing tweets using our machine learning models as could be expected from a single human coder. The potential to use this automated process, which is reliable and accurate, could free valuable time and resources for conducting this analysis, in addition to informing potentially effective and necessary interventions.
Evaluating the Impact of COVID-19 on the Adoption of Virtual Care in General Practice in 20 Countries (inSIGHT): Protocol and Rationale Study
Authors: Neves Ana Luísa , Li Edmond , Serafini Alice , Jimenez Geronimo , Lingner Heidrun , Koskela Tuomas H , Hoffman Robert D , Collins Claire , Petek Davorina , Claveria Ana , Tsopra Rosy , Irving Greg , Gusso Gustavo , O’Neill Braden Gregory , Hoedebecke Kyle , Espitia Sandra Milena , Ungan Mehmet , Nessler Katarzyna , Lazic Vanja , Laranjo Liliana , Memarian Ensieh , Fernandez Maria Jose , Ghafur Saira , Fontana Gianluca , Majeed Azeem , Car Josip , Darzi Ara
Published: July 2021

Background

In recent decades, virtual care has emerged as a promising option to support primary care delivery. However, despite the potential, adoption rates remained low. With the outbreak of COVID-19, it has suddenly been pushed to the forefront of care delivery. As we progress into the second year of the COVID-19 pandemic, there is a need and opportunity to review the impact remote care had in primary care settings and reassess its potential future role.

Objective

This study aims to explore the perspectives of general practitioners (GPs) and family doctors on the (1) use of virtual care during the COVID-19 pandemic, (2) perceived impact on quality and safety of care, and (3) essential factors for high-quality and sustainable use of virtual care in the future.

Methods

This study used an online cross-sectional questionnaire completed by GPs distributed across 20 countries. The survey was hosted in Qualtrics and distributed using email, social media, and the researchers’ personal contact networks. GPs were eligible for the survey if they were working mainly in primary care during the period of the COVID-19 pandemic. Descriptive statistical analysis will be performed for quantitative variables, and relationships between the use of virtual care and perceptions on impact on quality and safety of care and participants’ characteristics may be explored. Qualitative data (free-text responses) will be analyzed using framework analysis.

Results

Data collection took place from June 2020 to September 2020. As of this manuscript’s submission, a total of 1605 GP respondents participated in the questionnaire. Further data analysis is currently ongoing.

Conclusions

The study will provide a comprehensive overview of the availability of virtual care technologies, perceived impact on quality and safety of care, and essential factors for high-quality future use. In addition, a description of the underlying factors that influence this adoption and perceptions, in both individual GP and family doctor characteristics and the context in which they work, will be provided. While the COVID-19 pandemic may prove the first great stress test of the capabilities, capacity, and robustness of digital systems currently in use, remote care will likely remain an increasingly common approach in the future. There is an imperative to identify the main lessons from this unexpected transformation and use them to inform policy decisions and health service design.

International Registered Report Identifier (IRRID)

DERR1-10.2196/30099
Contact Tracing Apps: Lessons Learned on Privacy, Autonomy, and the Need for Detailed and Thoughtful Implementation (Preprint)
Authors: Hogan Katie , Macedo Briana , Macha Venkata , Barman Arko , Jiang Xiaoqian
Published: July 2021

UNSTRUCTURED

The global and national response to the COVID-19 pandemic has been inadequate due to a collective lack of preparation and a shortage of available tools for responding to a large-scale pandemic. By applying lessons learned to create better preventative methods and speedier interventions, the harm of a future pandemic may be dramatically reduced. One potential measure is the widespread use of contact tracing apps. While such apps were designed to combat the COVID-19 pandemic, the time scale in which these apps were deployed proved a significant barrier to efficacy. Many companies and governments sprinted to deploy contact tracing apps that were not properly vetted for performance, privacy, or security issues. The hasty development of incomplete contact tracing apps undermined public trust and negatively influenced perceptions of app efficacy. As a result, many of these apps had poor voluntary public uptake, which greatly decreased the apps’ efficacy. Now, with lessons learned from this pandemic, groups can better design and test apps in preparation for the future. In this viewpoint, we outline common strategies employed for contact tracing apps, detail the successes and shortcomings of several prominent apps, and describe lessons learned that may be used to shape effective contact tracing apps for the present and future. Future app designers can keep these lessons in mind to create a version that is suitable for their local culture, especially with regard to local attitudes toward privacy-utility tradeoffs during public health crises.
Healthcare quality through the eyes of bloggers: content analysis of non-solicited narratives about patient experiences with healthcare (Preprint)
Authors: Osváth Mátyás , Varga Orsolya , Kósa Karolina
Published: July 2021

BACKGROUND

Patient experiences constitute an independent dimension of health care quality that can be solicited by structured surveys or at dedicated online platforms. Unsolicited spontaneous patient narratives are much less used but potentially valuable means for gauging patient experiences.

OBJECTIVE

Our aim was to explore patient experiences in spontaneous patient blogs submitted during one decade to an online health forum.

METHODS

1662 non-solicited individual blogs on patient experiences posted between 2009 and 2018 on a Hungarian internet forum were randomly sampled. 20% (n=346) of the blogs were used for qualitative content analysis. A coding framework was constructed based on previous research and taxonomies to analyse content, including specific experiences or episodes. Major categories and subcategories were constructed within the three major dimensions (structure, process, outcome) of Donabedian’s framework for health care quality.

RESULTS

Majority of blogs described a specific experience (94.2%) in healthcare; almost 40% occurred in tertiary care; 29.5% of the blogs even identified a specific hospital or department. 55.2% of the bloggers were patients themselves, and the majority (92.7%) were dissatisfied with the reported experience. Issues were most frequently related to physicians (65.2%). In terms of Donabedian’s dimensions, problems with human resources dominated “Structure” (74.1%) such as not enough or incompetent staff. Waiting time and access to care (69.19%) comprised the most frequent complaints of material resources within “Structure”. Within “Process”, episodes related to examination (42.86%) accounted for most of the complaints. Outcomes were identified in 60% of the blogs, and deterioration, complication, readmission, or death was reported in 62% of these episodes.

CONCLUSIONS

Donabedian’s model of healthcare quality was appropriate for the categorization of patient experiences. Regular monitoring of spontaneous patient reports is recommended to utilize them for healthcare quality improvement especially if reports provide specific details.
Implementation of Teleophthalmology to Improve Diabetic Retinopathy Surveillance: Qualitative Interview Study of Clinical Staff Informed by Implementation Science Frameworks (Preprint)
Authors: Ramchandran Rajeev S , Yousefi-Nooraie Reza , Dadgostar Porooshat , Yilmaz Sule , Basant Jesica , Dozier Ann M
Published: July 2021

BACKGROUND

The store-and-forward camera-based evaluation of the eye, or teleophthalmology, is an effective way to identify diabetic retinopathy, the leading cause of blindness in the United States, but uptake has been slow. Understanding the barriers to and facilitators of implementing teleophthalmology programs from those actively adopting, running, and sustaining such programs is important for widespread adoption.

OBJECTIVE

This study aims to understand the factors that are important in introducing teleophthalmology to improve access to diagnostic eye care for patients with diabetes in primary care clinics by using implementation science.

METHODS

This qualitative study in 3 urban, low-income, largely racial and ethnic minority–serving safety-net primary care clinics in Rochester, New York, interviewed nurses and physicians on implementing a teleophthalmology program by using questions informed by the Practical, Robust Implementation and Sustainability Model and the Consolidated Framework for Implementation Research.

RESULTS

Primary care nurses operationalizing the program in their clinics saw increased work burden and a lack of self-efficacy as barriers. Continuous training on the teleophthalmology process for nurses, physicians, and administrative staff through in-service and peer training by champions and superusers were identified by interviewees as needs. Facilitators included the perceived convenience for the patient and a perceived educational advantage to the program, as it gave an opportunity for providers to discuss the importance of eye care with patients. Concerns in making and tracking referrals to ophthalmology because of challenges related to care coordination were highlighted. The financial aspects of the program (eg, patient coverage and care provider reimbursement) were unclear to many staff members, influencing adoption and sustainability.

CONCLUSIONS

Streamlining processes and workflows, training and assigning adequate staff, effectively coordinating care between primary care and eye care to improve follow-ups, and ensuring financial viability can all help streamline the adoption of teleophthalmology.
Family Feud, or Realpolitik?
Authors: Braga Silva Fernando Ursine
Published: July 2021

In this contribution, I use the breakup – just short of the 2017 General Election – of Japan’s former second biggest political party, the Democratic Party of Japan (DPJ), as a case study so as to assess the practical implications of splits and realignments in the most relevant party split in Japan since the DPJ was ousted from government in 2012. First, I examine DPJ’s origin as an umbrella for ideologically diverse groups that opposed the conservative Liberal Democratic Party (LDP) – the government party in Japan throughout most of its post-war history, its tendency to factionalism, and the oftentimes damaging role the factional dynamics played in the party’s decision-making process throughout the years. In the case study, it is understood that the creation of the Party of Hope – a split from the LDP, and the salience of constitutional issues were exogenous factors particular to that election, which helped causing the DPJ split.
Sino-American Tensions and Their Effects on Counter-terrorism Operations in Djibouti
Authors: Fricker Paul
Published: July 2021

This research note examines the tensions between the United States and the People’s Republic of China in Djibouti. Djibouti has become a battleground of interests between the US and China with both building military bases on its territory. The People’s Liberation Army Navy (PLAN) utilises its base to conduct naval operations and to implement the Belt and Road Initiative (BRI), often conflicting with US operations and interests. The research note relies on primary documents to investigate the interaction between the two states over Djibouti and to assess whether and how China’s presence is an obstacle to US counterterrorism operations. This analysis indicates that a conflict of interests between the US and China is inevitable, but the US’ counterterrorism operation in Djibouti can be protected from the diplomatic conflict.
The use of nonrandomized evidence to estimate treatment effects in health technology assessment
Authors: Kent Seamus , Salcher-Konrad Maximilian , Boccia Stefania , Bouvy Jacoline C , Waure Chiara de , Espin Jaime , Facey Karen , Nguyen Mary , Rejon-Parrilla Juan Carlos , Jonsson Pall
Published: July 2021

Health technology assessment (HTA) is increasingly informed by nonrandomized studies, but there is limited guidance from HTA bodies on expectations around evidence quality and study conduct. We developed recommendations to support the appropriate use of such evidence based on a pragmatic literature review and a workshop involving 16 experts from eight countries as part of the EU’s Horizon-2020 IMPACT-HTA program (work package six). To ensure HTA processes remain rigorous and robust, HTA bodies should demand clear, extensive and structured reporting of nonrandomized studies, including an in-depth assessment of the risk of bias. In recognition of the additional uncertainty imparted by nonrandomized designs in estimates of treatment effects, HTA bodies should strengthen early scientific advice and engage in collaborative efforts to improve use of real-world data.
Amnistías fiscales en Chile
Authors: Toledo Zuñiga Patricia Andrea , Paredes Paredes Felipe Ignacio
Published: July 2021

In the last decade, several tax amnesties policies have been established in Chile in order to increase public revenues. In this sense, distinguish between permanent and temporary tax amnesties policies is needed. On the one hand, it is possible to exemplify the forgiveness policy of interests and fines caused by delayed accomplishments of tax obligations. On the other hand, we can mention some repatriation of capital programs, especially those set by Law No. 20.780. Both types of policies are analyzed, describing a tenseness between those policies and the Chilean Constitution. Specifically, the article states that such measures could collide with the constitutional principle of tax equity, both horizontally and vertically, as well as with the constitutional principle of tax legality. In the same vein, the paper to conclude that tax amnesties should play an exceptional role in the tax system.
Muscle insulin-like growth factor-I modulates murine craniofacial bone growth
Authors:   Applied Physiology and Kinesiology, College of Health and Human Performance, University of Florida, 1864 Stadium Road, Gainesville, FL 32611, USA, Kok HJ , Crowder CN , Koo Min Chee L , Choi HY , Lin N , Barton ER
Published: July 2021

Insulin-like growth factor I (IGF-I) is essential for muscle and bone development and a primary mediator of growth hormone (GH) actions. While studies have elucidated the importance of IGF-I specifically in muscle or bone development, few studies to date have evaluated the relationship between muscle and bone modulated by IGF-I in vivo, during post-natal growth. Mice with muscle-specific IGF-I overexpression (mIgf1+/+) were utilised to determine IGF-I- and muscle-mass-dependent effects on craniofacial skeleton development during post-natal growth. mIgf1+/+ mice displayed accelerated craniofacial bone growth when compared to wild-type animals. Virus-mediated expression of IGF-I targeting the masseter was performed to determine if post-natal modulation of IGF-I altered mandibular structures. Increased IGF-I in the masseter affected the mandibular base plane angle in a lateral manner, increasing the width of the mandible. At the cellular level, increased muscle IGF-I also accelerated cartilage thickness in the mandibular condyle. Importantly, mandibular length changes associated with increased IGF-I were not present in mice with genetic inhibition of muscle IGF-I receptor activity. These results demonstrated that muscle IGF-I could indirectly affect craniofacial growth through IGF-I-dependent increases in muscle hypertrophy. These findings have clinical implications when considering IGF-I as a therapeutic strategy for craniofacial disorders.
Kvantitativna analiza studentske procjene važnosti stranih jezika u sportskome menadžmentu
Authors: Omrčen Darija , Mihovec Magdalena
Published: July 2021

The aim of the analysis was to find out how future kinesiologists assess the importance of 15 foreign languages in sports management. The sample was comprised of 70 male and female students from the Faculty of Kinesiology, University of Zagreb. The results showed that most of the students had learned English and German, and for the longest period. As many as 62.86% had learned two foreign languages, whereas 20% had learned three, 10% had learned only one, and only 7.14% had learned four foreign languages. The students assessed the command of English and German as the most important asset for work in sports management. The factor analysis yielded three latent dimensions interpreted on the basis of the aspects of tourism, success in sport, and economic power. By means of factor scores of the three obtained factors, a multivariate analysis of variance did not show differences between students’ assessment of the importance of the 15 foreign languages based on the number of foreign languages they had learned.
Driver Drowsiness Detection System
Authors: V Kiranmayee
Published: July 2021

Drowsiness of drivers are among the critical reasons for accidents. This can be a relatively smaller number still, as among the multiple causes that can lead to an accident. Drowsiness, in general, is not easy to measure unlike drugs and alcohol, which have tests and indicators that are available easily. In this paper, we are presenting a module for Advanced Driver Assistance System (ADAS) to reduce drowsiness related accidents. The system deals with automatic driver drowsiness detection based on visual information. We propose an algorithm to track, analyze and locate both the drivers eyes and face to measure PERCLOS, a scientifically supported measure of drowsiness asso- ciated with slow eye closure.
Railway Track Monitoring System
Authors: Latkar Charu
Published: July 2021

For the protection and proximity of railway networks it is substantial to Promptly detect and identify faults in the railway tracks. In this paper, railway track fault diagnosis is approximated from the vertical and lateral acceleration using a MPU6050. MPU6050 consisting of three sensors namely gyroscope, magnetometer and accelerometer are used to distinguish line and level as symetricities in a railway track. A GSM module is used to notify the location of faults on tracks. Arduino Microcontroller is interfaced using Arduino UNO IDE. The results show that the condition of railway track irregularity and railway track striation can be approximated constructively. The processed data is uploaded to the open source cloud provider thingspeak.com. The use of various Machine Learning Algorithms are proposed to accomplish the above tasks based on the commonly available measured signals. By considering the signals from multiple railway tracks in a geographic location, faults are diagnosed from their spatial and temporal dependencies. The irregularities in the railway tracks are detected using the Inertial Monitoring Unit, providing the necessary data about future deformities using Machine Learning. Using Python 3.0, a generative model is developed to show that the AdaBoost network can learn these dependencies directly from the data. Seven different classification algorithms used for this project are Logistic regression,Naive Bayes Algorithm,Support Vector Machine, Ensemble Machine (Average) learning Algorithm, XGBoost Classifier, Extreme Machine Learning and AdaBoost Classifier. Among the above 7 classification algorithms, AdaBoost Learning has given the highest accuracy,i.e of 93.93 %. The AdaBoost Machine Learning Model is used throughout the model.
Seismic Analysis of Multi Storey Building Using Strong Column Weak Beam Ratio (SCWB) in Different Zones of India
Authors: Raut Suraj
Published: July 2021

An earthquake structures are mandatory to avoid significant damages (i.e., collapse) and aims that structure withstand a major earthquake without collapse. The design approach adopted is to ensure that the columns of the structure more capable to resist moments than beam; to avoid progressive collapse of structure due to failure of columns in lower level; it is necessary the columns have stronger than beams (strong column weak beam). The concept of SCWB is to ensure that plastic hinge formed in the beam not in the column; this help in dissipating the more energy along with providing ductility to the structure. If the plastic hinge is formed on the both ends of column then, the column is not able to spread the plasticity and collapse which are leads to global failure. The failure modes in all past earthquake is exactly opposite i.e, strong beam weak column; and comes to sway mechanism and fails to collapse. For this it is foreseen that the values of ratio of Mc/Mb (ratio of sum of ultimate moment of resistance of columns to sum of ultimate moment of resistance of beam) in the beam-column joint are stated by many design codes and the values are different ranging from 1.2,1.3,1.4,1.5 to 2, etc. Another effect of ratio Ic/Ib (ratio of moment of inertia of column to moment of inertia of beam) have been studied but the exact meeting of SCWB behaviour in the structures at the time of collapse not stated clearly. The Mc/Mb and Ic/Ib ratio are very important to prevent damage in the structure under seismic action. In the present work, attempts are made to achieve exact ratio of exact strong column weak beam. In this study, the combined effect of two ratio (Mc/Mb, Ic/Ib) simultaneously investigated in different zones of India to find out exact SCWB ratio’s value for to meet the SCWB behaviour. Different numerical examples are presented of combine ratios (Mc/Mb,Ic/Ib) and pushover analysis is performed on each ratio’s. The result of the investigation highlighted on the objective that is to find exact SCWB ratio value considering the parameter like target displacement, ductility ratio, hinge response etc.
Design Consideration of Material Handling Equipment for Ganga Iron and Steel Limited, Nagpur
Authors: Chede Dr. Bharat
Published: July 2021

In the last several years’ material handling has become a new, complex, and rapidly evolving science. Material handling system (MHS) design has a direct influence on the logistics cost. This work is to locates and identifies the wasteful activities regarding the material handling, and to streamline the activities to reach a minimum of material handling. Most of industries are using EOT cranes for handling of material. In today’s modern era, crane is very important material handling equipment in industry because of safety reliability, fast speed, economy etc. In this paper, discussed about design Consideration of material handling equipment for ganga iron and steel limited Nagpur. In the current material handling equipment, the life of the overhead crane as well as the cost of the material handling equipment is too important to stay in the competitive market of the industries. The cost of the material handling equipment is depending on the weight of the material. The performance of the material handling equipment will be done by the working on the optimization of the overhead crane used in the industries. Crane is a reliable component for lifting load in industries. Crane fails due to high friction in between wire rope and pulley. It leads to failure in gear box or it may increase power requirement of crane to lift loads. It is necessary for the crane to lift the load with minimum effort and minimum friction between the mating surfaces Based on the design calculations and analysis, a prototype crane was simulation, ncs, analysis.
Heart Rate Monitoring using Arduino
Authors: Kolimpalle Madhu Babu.
Published: July 2021

Heart rate monitoring plays a vital role in our day to day life. But first what is heart rate - It is the number of times the heart beats per minute. It mirrors our body conditions in so many ways like our body physiological condition, stress, anxiety etc,. So, it is mandatory to monitor our heart beat. Next question is how do we do that? There are many ways to monitor the heartbeat. This heartbeat can also be found using the ECG waveform when the blood is passing forcely through the regular heart contractions. In this paper we will see heart rate monitoring using Arduino. It is one of the techniques of measuring heart beat. It works on the principle of photoplethysmography (PPG).
Survey on Cardiomegaly Detection with Enhanced X-Ray Using Deep Learning
Authors: K P Prof. Vidyashree
Published: July 2021

Cardiomegaly is an augmented (enlarged) heart. It is not a disease merely a sign of another condition. Cardiomegaly in the early stages, which is less severe, is called mild Cardiomegaly. These complications may give rise to conditions like Blood clots, Cardiac Arrest and sudden death, Heart failure, Heart murmur. Hence, detecting these kinds of states in the early stages helps in improving medications and reduce complications. In this paper, we will present various approaches available to detect this development using Deep learning and offer an automated system to detect the presence of Cardiomegaly in a patient. For the computerized system, we are using deep learning concepts such as U-Net and VGG16 and image enhancement (image prepossessing is required) methods like Unsharp Masking, Contrast Limited Adaptive Histogram, High-Frequency Emphasis Filtering. Accurate measure of CTR (cardiothoracic ratio) calculations can effectively diagnose the presence of Cardiomegaly in a patient.
Implementation of Smart Home using Internet of Things (IOT)
Authors: Sangtani Dr. Virendra
Published: July 2021

The smart home framework is a generally utilized reference term and a stage for home robotization control, and checking. Home computerization with the assistance of IoT isn't that much develop that far is in the advancement stage and there is such a lot of room for development however from the client perspective purchasing this sort of framework could simplify our life and it can decrease our time and cost. It can do numerous things that man deals with issues in doing. This is fundamentally a framework that will interface with our device(phone or web) and there will be the principle gadget inside the home that gadget will be associated with the wifi or Bluetooth and other home machines that we need to control distantly.
Distributed-Decentralized Intelligent Agents for Offensive Cyber Security: An Introduction to Offensive Cyber Threat Intelligence
Authors: Rande Nayan
Published: July 2021

In order to begin to design a large Offensive Cyber-Threat-Intelligence, we need a distributed-decentralised Intelligent Software framework, which can scale on demand and run with flexibility while providing a room for further improvement both on architectural level as well as strategical level for planning advanced attacks methodologies, will help us conduct secure transaction maintaining CIANA. In this paper, we try to present some of our investigations on Agent-based Modelling of Cyber-Space and Simulation of Cyber-Warfare over distributed system methodology in contributing to these designs. Using this as motivation we try to build system architecture for effective open intelligence for effective offensive cyber threat intelligence (CTI).
Detection of Fake Indian Currency Notes using Deep Learning
Authors: Deshpande Soha K
Published: July 2021

A normal human being can easily see and distinguish any banknote, however doing the same job is extremely difficult for someone who is visually challenged or blind. Because money plays such an essential part in our everyday lives and is required for any commercial transaction, real-time detection and recognition of banknotes is a must for anyone who is blind or visually impaired. The mobilenet based CNN model-based Indian currency detection and identification system is presented for this purpose, and it is quick and accurate. To make the system more resilient, pictures of various denominations and situations were collected first, and then these images were supplemented with various geometric and image modifications. These augmented pictures are then manually tagged, and training and validation image sets are created from them. Later, the trained model's performance was assessed on a real-time scenario as well as a test dataset. The suggested mobile net model-based technique exhibits detection accuracy of 91.33% according to the test results. This standalone system operates in real-time.
Plant Leaf Disease Prediction
Authors: Monigari Vaishnavi
Published: July 2021

The Indian economy relies heavily on agriculture productivity. A lot is at stake when a plant is struck with a disease that causes a significant loss in production, economic losses, and a reduction in the quality and quantity of agricultural products. It is crucial to identify plant diseases in order to prevent the loss of agricultural yield and quantity. Currently, more and more attention has been paid to plant diseases detection in monitoring the large acres of crops. Monitoring the health of the plants and detecting diseases is crucial for sustainable agriculture. Plant diseases are challenging to monitor manually as it requires a great deal of work, expertise on plant diseases, and excessive processing time. Hence, this can be achieved by utilizing image processing techniques for plant disease detection. These techniques include image acquisition, image filtering, segmentation, feature extraction, and classification. Convolutional Neural Network’s(CNN) are the state of the art in image recognition and have the ability to give prompt and definitive diagnoses. We trained a deep convolutional neural network using 20639 images on 15 folders of diseased and healthy plant leaves. This project aims to develop an optimal and more accurate method for detecting diseases of plants by analysing leaf images.
Document Image Binarization using Image Segmentation Technique
Authors: Pagare Mr. Aniket
Published: July 2021

Segmentation of text from badly degraded document images is an extremely difficult assignment because of the high inter/Intra variety between the record foundation and the frontal area text of various report pictures. Picture preparing and design acknowledgment algorithms set aside more effort for execution on a solitary center processor. Designs Preparing Unit (GPU) is more mainstream these days because of its speed, programmability, minimal expense and more inbuilt execution centers in it. The primary objective of this exploration work is to make binarization quicker for acknowledgment of a huge number of corrupted report pictures on GPU. In this framework, we give another picture division calculation that every pixel in the picture has its own limit proposed. We are accomplishing equal work on a window of m*n size and separate article pixel of text stroke of that window. The archive text is additionally sectioned by a nearby edge that is assessed dependent on the forces of identified content stroke edge pixels inside a nearby window.