Notes

Psychometric attributes from the Eu Portuguese version of the particular Wijma Delivery Expectancy/Experience Questionnaire inside pregnant women.
The rationale for T3 therapy in severe COVID-19 and preliminary experimental and clinical evidence are discussed in this review.Pain prevention and management is one of the primary goals of dental care. Postoperative dental pain (PDP) following caries removal and performance of a restorative dental treatment is a common clinical phenomenon, often causing significant discomfort to dental patients. In the present study, a psychophysical non-invasive method, qualitative sensory testing (QualST), was used in an attempt to foretell PDP following dental restorative procedures. Forty-two dental patients underwent an intra-oral cold QualST four times immediately prior to a restorative dental procedure and at a follow-up meeting 1-3 weeks later, on the treated and on the contralateral oral sides. The QualST measures included subjects' evaluation of the magnitude of pain and cold sensations experienced (on visual analogue scales) and the duration of the cold sensation (in seconds). Additional measures included age, gender, level of dental anxiety, jaw treated, and type of dental restoration performed (Class I or Class V). Subjects' PDP was assessed through the phone using numeric rating scales 24, 48, and 72 h postoperatively. The highest level of PDP experienced by subjects occurred 24 h postoperatively (ANOVA with repeated measures). Of the study variables, the QualST pain sensation (B = 0.645, p < 0.001), duration of the cold sensation (B = 0.042, p < 0.05), and an interaction between gender and dental anxiety (B = 0.136, p < 0.05) emerged as possible predictors of the highest PDP experienced by subjects (stepwise regression). The results suggest that subjects' reaction to an intra-oral cold stimulation of the oral mucosa can serve as a potential tool to foretell postoperative dental pain following restorative dental procedures.The increasingly serious problem of consumers returning goods on e-commerce platforms has brought high costs to the Internet economy, carbon pollution to the environment, and waste of social resources. E-commerce platforms can provide useful information to assist consumers to make rational decisions, but they are often filled with useless, repetitive, and even false excessive information, which will lead to information overload and impulsive decision-making of consumers. Most of the previous literature focuses on reverse logistics, return policy, and consumer behavior tendency, etc. From the perspective of consumers' perception of information displayed on e-commerce platforms, there are few research endeavors on the formation mechanism of perceived information overload on consumers' return intention. Taking perceived information overload as an independent variable and consumers' perceived environmental effectiveness as a moderation variable, this study constructs a chain mediation model that affects consumersications from the perspectives of consumers and e-commerce platforms.Epivigila is a Chilean integrated epidemiological surveillance system with more than 17,000,000 Chilean patient records, making it an essential and unique source of information for the quantitative and qualitative analysis of the COVID-19 pandemic in Chile. Nevertheless, given the extensive volume of data controlled by Epivigila, it is difficult for health professionals to classify vast volumes of data to determine which symptoms and comorbidities are related to infected patients. This paper aims to compare machine learning techniques (such as support-vector machine, decision tree and random forest techniques) to determine whether a patient has COVID-19 or not based on the symptoms and comorbidities reported by Epivigila. From the group of patients with COVID-19, we selected a sample of 10% confirmed patients to execute and evaluate the techniques. We used precision, recall, accuracy, F1-score, and AUC to compare the techniques. The results suggest that the support-vector machine performs better than decision tree and random forest regarding the recall, accuracy, F1-score, and AUC. Machine learning techniques help process and classify large volumes of data more efficiently and effectively, speeding up healthcare decision making.
Violence against women and girls continues to be a widespread problem, and its elimination is one of the targets of the Sustainable Development Goal 5 toward achieving gender equality. One of the main causes of this violence is the structural sexism present in societies that continues to be perpetuated through pornography, especially among young people. Therefore, the main objective of this research is to analyze the consumption of pornography among young people, studying its effects and relationship with affective-sexual education.

This study was carried out with a sample of 280 students in the north of Spain. The ages of the entire sample ranged from 18 to 37 years (
= 20.3,
= 2.6). From the sample, 78.9% (
= 221) define their gender identity as women and 21.1% (
= 59) define their gender identity as men; no person within this research self-identify as non-binary. The instrument used was the Survey on Affective-sexual Education and Pornography (Ballester et al., 2019). The sample was recruited umption to address their curiosity and satisfy their sexual needs. Finally, the impact of pornography consumption on SDG5 was reflected on.Biofilm production on biotic and abiotic surfaces is crucial in the pathogenesis of most infections, particularly those occurring in the oral cavity. Its prevention and/or control may greatly facilitate the management of patients with oral diseases. Here, the antibiofilm activity of a biomimetic hydroxyapatite and a natural compound, MicroRepair (MicroR) and pomegranate (PomeGr), respectively, was assessed. By luminescence/fluorescence-based assays, Pseudomonas aeruginosa (P. aeruginosa), Staphylococcus aureus (S. aureus) and Candida albicans (C. albicans) were tested for biofilm production in the presence of MicroR and/or PomeGr. We found that both MicroR and PomeGr could affected biofilm production; however, the efficacy of the two, given alone or in combination, varied according to the microbial agent considered. These data open to clinical studies aimed at defining the most efficacious protocols to counteract oral biofilm-associated infections.
This study aimed to investigate the trends in neoplasm-related hospital admissions (NRHA) in England and Wales between 1999 and 2019.

This is an ecological study using publicly available data taken from the two main medical databases in England and Wales; the Hospital Episode Statistics database in England and the Patient Episode Database in Wales. Hospital admissions data were collected for the period between April 1999 and March 2019.

A total of 35,704,781 NRHA were reported during the study period. Females contributed to 50.8% of NRHA. The NRHA rate among males increased by 50.0% [from 26.62 (95% CI 26.55-26.68) in 1999 to 39.93 (95% CI 39.86-40.00) in 2019 per 1000 persons, trend test,
&lt; 0.001]. The NRHA rate among females increased by 44.1% [from 27.25 (95% CI 27.18-27.31) in 1999 to 39.25 (95% CI 39.18-39.32) in 2019 per 1000 persons, trend test,
&lt; 0.001]. Overall, the rate of NRHA rose by 46.2% [from 26.93 (95% CI 26.89-26.98) in 1999 to 39.39 (95% CI 39.34-39.44) in 2019 per 1000 persons, trend test,
&lt; 0.001].

Hospital admission rates due to neoplasms increased between 1999 and 2019. Our study demonstrates a variation in NRHA influenced by age and gender. Further observational studies are needed to identify other factors associated with increased hospital admissions among patients with different types of neoplasms.
Hospital admission rates due to neoplasms increased between 1999 and 2019. Our study demonstrates a variation in NRHA influenced by age and gender. selleck chemicals Further observational studies are needed to identify other factors associated with increased hospital admissions among patients with different types of neoplasms.Carbon emissions have become a new threat to sustainable development in China, and local government actions can play an important role in energy conservation and emission reduction. This paper explores the theoretical mechanisms and transmission paths of economic growth targets affecting carbon emissions from the perspective of economic growth targets and conducts an empirical analysis based on 30 provincial panel data in China from 2003 to 2019. The results show that economic growth targets are positively correlated with carbon emissions under a series of endogeneity and robustness; there are regional heterogeneity, target heterogeneity and structural heterogeneity in the impact of economic growth targets on carbon emissions; after economic growth targets are set, government actions can influence carbon emissions by affecting resource mismatch and industrial restructuring; It is further found that there is a "U" shaped relationship between economic pressure and carbon emissions. Based on the above findings, this paper further proposes that a high-quality performance assessment mechanism should be developed to bring into play the active role of local governments in achieving carbon reduction goals, and thus contribute to high-quality economic development.This study investigates the symmetric and asymmetric linkages within environmental sustainability proxied by ecological footprint (EFP), natural resources (NRR), renewable energy consumption (REC), urbanization (URB), human capital (HC), and government effectiveness (GE) in 27 African countries divided into two subgroups (ecological deficit countries and ecological reserve countries) over the period 1990 to 2018. The study employs the auto-regressive distributed lag (ARDL) model to investigate the symmetric (linear) effect and the nonlinear auto-regressive distributed lag (NARDL) model to study the asymmetric (nonlinear) effects of the variables on EFP. Results of ARDL show that a 1% increase in REC is projected to reduce ecological footprint by 0.17 and 0.2% in ecological deficit and ecological reserve countries. A 1% increase in NRR is estimated to increase ecological footprint by 0.02% in ecological deficit countries but has no impact on the environment in countries with ecological reserves. Similarly, a 1% rise in GE is estimated to increase EFP by 0.04% in Africa but has no impact on the environment in ecological deficit countries. NARDL estimations decomposed REC into positive (negative) shocks, which show that a 1% increase (decrease) in REC is projected to decrease EFP by 0.16% (0.13%) in countries with ecological reserves. Similarly, a positive (negative) shock in NRR is expected to decrease EFP in ecological reserve countries and increase EFP in ecological deficit countries. Results of the Wald tests prove the existence of long-run asymmetry among the variables. The findings indicate that renewable energy consumption enhances environmental quality, while economic growth and natural resource rents reduce environmental quality in Africa over the sampled period.The objectives of this work are to check whether the COVID-19 pandemic affected the research on schistosomiasis, to provide an insight into the most productive countries and journals and the most cited publications, and to analyse any association between the total publications of countries and a set of socio-economic and demographic factors. Based on PRISMA methodology, we used the Scopus database to search for articles published between 1 January 2020 and 26 March 2022. VOSviewer was used to generate the co-authorship and the co-occurrence networks, and Spearman's rank correlation was applied to study associations. A total of 1988 articles were included in the study. Although we found that the year-wise distribution of publications suggests no impact on schistosomiasis research, many resources have been devoted to research on COVID-19, and the Global Schistosomiasis Alliance revealed the main activities for eradication of schistosomiasis had been affected. The most productive country was the United States of America.
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