Notes

Using non-psychoactive recurring bio-mass via Cannabis sativa D. with regard to receiving phenolic rich-extracts together with de-oxidizing potential.
This work suggests that a thorough monitoring of the SARS-CoV-2 genome by NGS is essential to contain any new variant that could jeopardize all the efforts that have been made so far to resolve the emergence of the pandemic.This paper considers the quantile regression model with individual fixed effects for spatial panel data. Efficient minimum distance quantile regression estimators based on instrumental variable (IV) method are proposed for parameter estimation. The proposed estimator is computational fast compared with the IV-FEQR estimator proposed by Dai et al. (2020). Asymptotic properties of the proposed estimators are also established. Simulations are conducted to study the performance of the proposed method. Finally, we illustrate our methodologies using a cigarettes demand data set.The determination of the relation between a number and a numerical interval is one of the core problems in the scientific calculation of privacy protection. The calculation of the relationship between two numbers and a numerical interval to protect privacy is also the basic problem of collaborative computing. It is widely used in data queries, location search and other fields. At present, most of the solutions are still fundamentally limited to the integer level, and there are few solutions at the real number level. To solve these problems, this paper first uses Bernoulli inequality generalization and a monotonic function property to extend the solution to the real number level and designs two new protocols based on the homomorphic encryption scheme, which can not only protect the data privacy of both parties involved in the calculation, but also extend the number domain to real numbers. In addition, this paper designs a solution to the confidential cooperative determination problem between real numbers by using the sign function and homomorphism multiplication. Theoretical analysis shows that the proposed solution is safe and efficient. Finally, some extension applications based on this protocol are given.In this work, we proposed a hybrid pointer network (HPN), an end-to-end deep reinforcement learning architecture is provided to tackle the travelling salesman problem (TSP). HPN builds upon graph pointer networks, an extension of pointer networks with an additional graph embedding layer. HPN combines the graph embedding layer with the transformer's encoder to produce multiple embeddings for the feature context. We conducted extensive experimental work to compare HPN and Graph pointer network (GPN). For the sack of fairness, we used the same setting as proposed in GPN paper. The experimental results show that our network significantly outperforms the original graph pointer network for small and large-scale problems. For example, it reduced the cost for travelling salesman problems with 50 cities/nodes (TSP50) from 5.959 to 5.706 without utilizing 2opt. Moreover, we solved benchmark instances of variable sizes using HPN and GPN. The cost of the solutions and the testing times are compared using Linear mixed effect models. We found that our model yields statistically significant better solutions in terms of the total trip cost. We make our data, models, and code publicly available https//github.com/AhmedStohy/Hybrid-Pointer-Networks.
India achieved elimination of leprosy nationally in 2005, but since then the number of patients with grade 2 disability at diagnosis increased steadily indicating delay in diagnosis. Therefore, there was a need for public health interventions which can increase case finding in their earlier stage. The objective of this study is to compare the effectiveness of three such community-based interventions; 1) Enhancement of community awareness on leprosy; 2) Education and motivation of "Index" leprosy cases; and 3) Involvement of Non-Formal Health Practitioners (NFHPs) to promote early detection of new cases of leprosy.

Three community-based interventions were implemented between April 2016 and March 2018, embedded within the National Leprosy Eradication Program (NLEP) of India. Interventions were 1) increasing awareness through involvement of Gram Panchayat (local government) in the community regarding early signs of leprosy (Awareness), 2) providing health education and motivating newly diagnosed leprosy patiation and sensitization of NFHPs. However, it is important to stress that while selecting strategies to increase early diagnosis it is important to determine, which is the most appropriate for each context or area and must be decided depending on the local context.
The Awareness intervention appears to be more effective in detection of new cases, compared to Index case motivation and sensitization of NFHPs. However, it is important to stress that while selecting strategies to increase early diagnosis it is important to determine, which is the most appropriate for each context or area and must be decided depending on the local context.The use of "belly scoring" can offer a novel, non-invasive objective management tool to gauge food intake between individuals, groups, and populations, and thus, population fitness. As food availability is increasingly affected by predation, ecological competition, climate change, habitat modification, and other human activities, an accurate belly scoring tool can facilitate comparisons among wildlife populations, serving as an early warning indicator of threats to wildlife population health and potential population collapse. In social species, belly scores can also be a tool to understand social behavior and ranking. We developed and applied the first rigorous quantitative photogrammetric methodology to measure belly scores of wild painted dogs (Lycaon pictus). Our methodology involves (1) Rigorous selection of photographs of the dorso/lateral profile of individuals at a right angle to the camera, (2) photogrammetrically measuring belly chord length and "belly drop" in pixels, (3) adjusting belly chord lengtidly detect emergent threats.
As oesophageal cancer has short survival, it is likely pre-diagnosis health behaviours will have carry-over effects on post-diagnosis survival times. Cancer registry data sets do not usually contain pre-diagnosis health behaviours and so need to be augmented with data from external health surveys. A new algorithm is introduced and tested to augment cancer registries with external data when one-to-one data linkage is not available.

The algorithm is to use external health survey data to impute pre-diagnosis health behaviour for cancer patients, estimate misclassification errors in these imputed values and then fit misclassification corrected Cox regression to quantify the association between pre-diagnosis health behaviour and post-diagnosis survival. Data from US cancer registries and a US national health survey are used in testing the algorithm.

It is demonstrated that the algorithm works effectively on simulated smoking data when there is no age confounding. But age confounding does exist (risk of death increases with age and most health behaviours change with age) and interferes with the performance of the algorithm. The estimate of the hazard ratio (HR) of pre-diagnosis smoking was HR = 1.32 (95% CI 0.82,2.68) with HR = 1.93 (95% CI 1.08,7.07) in the squamous cell sub-group and pre-diagnosis physical activity was protective of survival with HR = 0.25 (95% CI 0.03, 0.81). But the method failed for less common behaviours (such as heavy drinking).

Further improvements in the I2C2 algorithm will permit enrichment of cancer registry data through imputation of new variables with negligible risk to patient confidentiality, opening new research opportunities in cancer epidemiology.
Further improvements in the I2C2 algorithm will permit enrichment of cancer registry data through imputation of new variables with negligible risk to patient confidentiality, opening new research opportunities in cancer epidemiology.This article aims to analyse the impact of the main determinants of match-day stadium attendance for seven seasons-2012-13 to 2018-19-of the Italian football Serie A. The main element of novelty is that the dataset is split into three sub-categories based on the pre-season fans' expectations to verify whether the impact of attendance determinants varies depending on teams' expected performance. Our results-based on Tobit model regressions-identify some significant differences across the three subsets. However, the difference that seems to be the most significant revealed a common preference of Italian fans towards higher quality opponents.The spread of infectious diseases is highly related to the structure of human networks. Analyzing the contact network of patients can help clarify the path of virus transmission. Based on confirmed cases of COVID-19 in two major tourist provinces in southern China (Hainan and Yunnan), this study analyzed the epidemiological characteristics and dynamic contact network structure of patients in these two places. Results show that (1) There are more female patients than males in these two districts and most are imported cases, with an average age of 45 years. Medical measures were given in less than 3 days after symptoms appeared. (2) The whole contact network of the two areas is disconnected. There are a small number of transmission chains in the network. The average values of degree centrality, betweenness centrality, and PageRank index are small. Few patients have a relatively high contact number. There is no superspreader in the network.
The clinical significance of upper airway respiratory virus (RV) detection in patients with hematologic malignancies remains unclear. We aimed to investigate the association between upper airway RV detection and prognosis in critically ill patients with hematologic malignancies.

This retrospective observational study included 331 critically ill patients with hematologic malignancies who presented respiratory symptoms and their nasopharyngeal swab was tested using a multiplex PCR assay between January 2017 and December 2018. A logistic regression model was used to adjust for potential confounding factors in the association between assay positivity and in-hospital mortality.

Among the 331 analyzed patients, RVs were detected in 29.0%. The overall mortality rates in the intensive care unit and hospital were 56.8% and 65.9%, respectively. Positive upper airway RV detection was associated with relapsed hematologic malignancies, higher level of C-reactive protein, and prior use of high dose steroids and anti-oids and anti-cancer drugs.
COVID-19 has affected people's health in various ways. University students are a particularly sensitive group for mental and physical health issues. selleck inhibitor The aim of this study was to assess and compare the mental and physical health of male and female first-year university students during and before COVID-19.

Total of 115 first-year university students (54% male) answered questions about mental and physical health. The students were asked to estimate their physical activity, sedentary behavior, loneliness, stress, and sleep quality during COVID-19 opposed to before the pandemic.

Males had fewer symptoms of anxiety and depression, and their self-esteem was higher than females (p<0.05). Over 50% of both genders estimated their mental health to be worse than before COVID-19. Larger proportion of males (69%) compared to females (38%) estimated that their physical health had worsened than before the pandemic. Larger proportion of females (38%) than males (14%) experience increased loneliness and stress (68% vs.
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