Exploring Digital Technology Adoption among Brazilian Evangelicals: A Survey and Research Agenda

The influence of faith on users’ adoption and use of digital technologies is a relevant aspect explored in the field of Human-Computer Interaction (HCI). In the Brazilian context, a religious segment that has experienced significant growth in recent years is the evangelical community. Understanding how evangelical members have adopted and utilized digital technologies, including their experiences during religious practices such as evangelical services, is of fundamental importance. In this work, we present an exploratory study conducted in Brazil, aiming to characterize the use of digital technologies among evangelicals. We conducted a survey through a questionnaire from 107 participants from all regions of Brazil. The results revealed that digital technologies are crucial in engaging religious services and facilitating Bible reading. However, they also highlighted challenges related to spiritual experiences arising from using these technologies. Furthermore, the research identified a series of questions and promising areas for future investigations in the field of HCI and its intersection with religion. This study contributes to the understanding of the complex interaction between technology and faith and enriches discussions about the use of digital technologies in the evangelical religious context. Additionally, by presenting a detailed research agenda, we identify topics deserving deeper investigation, such as technology-mediated spiritual experiences and the cultural implications of technological adoption in religious settings. The combination of these results and the proposed research agenda provides valuable insights for researchers, HCI professionals, and members of religious communities interested in comprehending and enhancing the intersection between technology and faith

DNA methylation-based classification of central nervous system tumours.

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology

Terrestrial behavior in titi monkeys (Callicebus, Cheracebus, and Plecturocebus) : potential correlates, patterns, and differences between genera

For arboreal primates, ground use may increase dispersal opportunities, tolerance to habitat change, access to ground-based resources, and resilience to human disturbances, and so has conservation implications. We collated published and unpublished data from 86 studies across 65 localities to assess titi monkey (Callicebinae) terrestriality. We examined whether the frequency of terrestrial activity correlated with study duration (a proxy for sampling effort), rainfall level (a proxy for food availability seasonality), and forest height (a proxy for vertical niche dimension). Terrestrial activity was recorded frequently for Callicebus and Plecturocebus spp., but rarely for Cheracebus spp. Terrestrial resting, anti-predator behavior, geophagy, and playing frequencies in Callicebus and Plecturocebus spp., but feeding and moving differed. Callicebus spp. often ate or searched for new leaves terrestrially. Plecturocebus spp. descended primarily to ingest terrestrial invertebrates and soil. Study duration correlated positively and rainfall level negatively with terrestrial activity. Though differences in sampling effort and methods limited comparisons and interpretation, overall, titi monkeys commonly engaged in a variety of terrestrial activities. Terrestrial behavior in Callicebus and Plecturocebus capacities may bolster resistance to habitat fragmentation. However, it is uncertain if the low frequency of terrestriality recorded for Cheracebus spp. is a genus-specific trait associated with a more basal phylogenetic position, or because studies of this genus occurred in pristine habitats. Observations of terrestrial behavior increased with increasing sampling effort and decreasing food availability. Overall, we found a high frequency of terrestrial behavior in titi monkeys, unlike that observed in other pitheciids

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Um Processo de Design de Interface com foco em Usuários com Transtorno do Espectro Autista: Uma Experiência Prática

ABSTRACTPeople with Autism Spectrum Disorder (ASD) present communicationdifficulties, social interaction challenges, and restricted andrepetitive behavior. Most systems used by these users do not havesuitable user interfaces. This paper’s aim is twofold: (i) we presentthe creation of a catalog and an interface design process based onthe results of a systematic mapping of interface design methodologiesthat can promote accessibility for users with ASD, and (ii)a practical experience with the proposed process in the designof a mobile application for autistic children. The practical experiencewas conducted in a research project focused on designingand evaluating accessible technologies. The team that adopted theprocess provided feedback on its suitability and opportunities forimprovement. The results indicated that the process supports accessibleinterface design but designers can face difficulties in selectingsuitable interface guidelines to adopt

DNA methylation-based classification of central nervous system tumours

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging - with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology

DNA methylation-based classification of central nervous system tumours

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challengingwith substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology