Application of neural networks to predict volume in eucalyptus

The aim of this study was to evaluate the methodology of Artificial Neural Networks (ANN) in order to predict wood volume in eucalyptus and its impacts on the selection of superior families, and to compare artificial neural network with regression models. Data used were obtained in a random block design with 140 half-sib families with five replications at three years of age, and four replications at six years of age, both with five plants per plot. The volume was estimated using ANN and regression models. It was used 2000 and 1500 data to train ANN, and 1500 and 1300 to validate ANN for 3 and 6 years of age, respectively. It is concluded that ANN can help improving the accuracy to measure the volume in eucalyptus trees, and to automate the process of forestry inventory and were more accurate in predicting wood volume than almost all regression models

Dutch efforts towards sustainable schools

While the goal of improving the energy performance of schools is crucial, achieving overall performance improvement in terms of both energy and comfort is also of uttermost importance given that the primary role of a building is the provision of a comfortable working and living safe. In this paper, results from ongoing research on sustainable, nearly-Zero Energy (nZE) and even Energy Positive School Buildings in the Netherlands are presented. The paper presents the energy results of 23 schools. The obtained results from this research was compared with those of earlier evaluation conducted on sustainable schools in other countries. The result from the research indicates that there a real possibilities to reduce the energy demand of schools

Forecasting atherosclerotic cardiovascular disease in south asia until 2040: A bayesian modeling approach

Background: Atherosclerotic cardiovascular disease (ASCVD) disproportionately impacts low-middle income countries, such as those in South Asia and understanding future ASCVD rates can inform public policy.Objectives: This study aimed to project the burden of ASCVD in South Asia till 2040.Methods: Yearly ischemic heart disease (IHD), stroke, and peripheral artery disease (PAD) counts for South Asia (Afghanistan, Bangladesh, Bhutan, India, the Maldives, Nepal, Pakistan, and Sri Lanka) and mid-year population were obtained from Global Burden of Disease (1990-2021) in 5-year age brackets (40-79 years) and estimated mid-year national population (2022-2040) was collected. Age-adjusted prevalence (aaPR) and mortality rate (per 100,000) were projected with Bayesian age-period-cohort models in South Asia (overall, males, and females); trends were reported as the estimated annual percent change (EAPC).Results: Between 2021 and 2040, the IHD aaPR in South Asia was projected to increase (2021: 9434.6 [95% CI: 9,432.1-9,437.1], 2040: 9,846.6 [95% CI: 8,800.0-10,893.3], EAPC: 0.23% [95% CI: 0.08%-0.37%]) because of increased rates among females (EAPC: 1.16%; 95% CI: 1%-1.32%). The overall IHD age-adjusted mortality rate will reduce (2021: 254.7 [95% CI: 254.3-255.1), 2040: 224.0 [95% CI: 166.5-281.6), EAPC: -0.67% [95% CI: -1.61% to 0.27%]) but may increase in females (EAPC: 1.16%; 95% CI: 1%-1.32%). Stoke aaPR in South Asia is projected to increase slightly (2021: 1,065.5 [95% CI: 1,064.7-1,066.4], 2040: 1,074.6 [95% CI: 953.7-1,195.5]). The PAD aaPR is projected to increase (2021: 1809.5 [95% CI: 1,808.5-1,810.6], 2040: 1,879.5 [95% CI: 1,684.9-2,074.0], EAPC: 0.26% [95% CI: 0.04%-0.47%]) because of increased rates in females (EAPC: 0.29%; 95% CI: -0.01% to 0.59%)