Sustainable Construction: Water Use in Residential Buildings in Portugal

Water is the most important resource to all life on our planet. The impact that buildings have on the consumption of this resource throughout their life cycle (planning, construction, operation and deconstruction) but mainly during the operation phase, has resulted in very high and unsustainable consumption patterns. Sustainable development, while a long-term goal, requires that the preservation of natural resources becomes a central point of any project strategy. Water is of vital importance to human life, it should be preserved to ensure its availability for a long period of time. However, little concern has been given to the importance of introducing a selection of more efficient solutions to save water in buildings and consequently increase sustainability in the construction sector. In this context it is on the design phase that the main resource saving water measures should be considered. Research on saving water involves an analysis of quantitative and qualitative measures and their adaptation to different contexts. Nowadays there are systems of voluntary certification of sustainable construction, which can help the design phase to achieve sustainability. This paper discusses a set of measures to reduce water consumption and enable a more efficient use of this resource in residential buildings. The measures presented are focused on user awareness campaigns, systems of rainwater and grey water recycling, the use of more efficient devices and reduction of leaks. The measures are analyzed and compared taking into account the consumption patterns for each device both inside and outside a domestic building and its effective reduction in water consumptio

Optimization and validation of a procedure using the dried saliva spots approach for the determination of tobacco markers in oral fluid

Exposure to tobacco smoke is one of the most common causes of premature death worldwide and is the cause of 8 million deaths annually. We have developed, optimized, and validated a procedure for the detection of nicotine, cotinine and trans-3-hydroxycotinine (biomarkers of tobacco exposure) in oral fluid using the dried saliva spots sampling approach and gas chromatography coupled to tandem mass spectrometry, thus allowing the distinction between active and passive smokers. For optimization, four parameters were evaluated, namely extraction solvent, extraction solvent volume, extraction time and spots drying time. During method validation, the parameters selectivity, linearity, precision and accuracy, recovery, stability, and dilution factor were assessed. Linearity was obtained for all target analytes in the concentration range of 10–200 ng/mL allowing the quantification of compounds up to 1000 ng/mL considering the dilution factor. The method recoveries ranged from 29.2% to 43.30% for nicotine, 66.60–89.10% for cotinine and 80.30–92.80% for trans-3-hydroxycotinine, while achieving intra-day, inter-day and intermediate precision and accuracy values never higher than 10.37% and ±6.62% respectively for all compounds. The herein described analytical method is the first to allow the determination of tobacco biomarkers in oral fluid using dried saliva spots, which is considered a sensitive, simple and low-cost alternative to conventional methods.info:eu-repo/semantics/publishedVersio

Psychometric evidence for the Lipp’ adult stress symptoms inventory

Apesar da avaliação do estresse ser importante em diferentes áreas da saúde, há um escasso número de instrumentos com adequadas evidências psicométricas para avaliá-lo. O  estudo teve como objetivo apresentar novas evidências de validade do Inventário de Sintomas de Stress para Adultos de Lipp (ISSL), descrever e discutir características clínicas do ISSL com dados obtidos por pacientes atendidos em um ambulatório hospitalar e um Centro de Atenção Psicossocial (CAPS). A amostragem baseou-se em pós-estratificação via método Raking. No total, 4500 participantes de todo o Brasil de ambos os sexos, faixas etárias e níveis acadêmicos foram utilizados nas análises psicométricas. Os resultados via Teoria de Resposta ao Item indicaram uma estrutura com alta consistência interna. Sintomas de apatia, depressão ou raiva prolongada foram os mais associados ao estresse e mulheres tiveram resultados mais altos. Houve uma correlação significativa entre o ISSL-R e outra medida de saúde mental (DASS-21) no grupo clínico. A pesar de la evaluación del estrés es importante en diferentes áreas de la salud, existe un número reducido de instrumentos con evidencia psicométrica adecuada para evaluarlo. El estudio tiene como objetivo presentar nuevas evidencias de la validez del Inventario de Síntomas de Estrés de Lipp para Adultos (ISSL) y describir las características clínicas del ISSL con datos obtenidos de pacientes atendidos en un Centro de Atención Psicosocial (CAPS). El muestreo se basó en la estratificación posterior mediante el método Raking. 4500 participantes de todo Brasil de ambos sexos, grupos de edad y niveles académicos fueron utilizados en los análisis psicométricos. La Teoría de Respuesta al Ítem indicaron una estructura con alta consistencia interna. Los síntomas de apatía, depresión ira prolongada fueron los más asociados con el estrés y las mujeres puntuaron más alto. Hubo una correlación significativa entre el ISSL-R y otra medida (DASS-21) en el grupo clínico.Although stress assessment is important in different health areas, there are few instruments with adequate psychometric evidence to assess it. The study aimed to present new validity evidences of Lipp’s Inventory of Stress Symptoms for Adults (LSSI), describe and discuss clinical characteristics of the LSSI with data obtained from patients seen in a hospital outpatient clinic and a Psychosocial Care Center (Centro de Atenção Psicossocial - CAPS). Sampling was based on post-stratification via the Raking method. In total, 4500 participants from all over Brazil of both sexes, age groups and academic levels were used in the psychometric analyses. The results via Item Response Theory indicated a structure with high internal consistency. Symptoms of apathy, depression or prolonged anger were the most associated with stress and women scored higher. There was a significant correlation between the LSSI-R and another mental health measure (DASS-21) in the clinical group

Desempenho agronômico de híbridos de milho na região sudeste de Goiás

Uma das formas de maximizar a produtividade de grãos de milho é a escolha correta do híbrido para condições edafoclimáticas regionais. Nesse contexto, objetivou-se avaliar o desempenho agronômico de onze híbridos de milho na região sudeste de Goiás, Brasil. O experimento foi conduzido a campo, na safra (primavera-verão) 2013/2014, em Latossolo Vermelho distrófico sob condições edafoclimáticas do Cerrado, na região sudeste de Goiás. O delineamento experimental utilizado foi o de blocos ao acaso, sendo 11 tratamentos representados pelos híbridos de milho, com quatro repetições. Foram avaliados o estande final de plantas, número final de espigas, características morfológicas das plantas (altura da planta, altura da espiga e diâmetro do colmo), componentes da produção (comprimento da espiga, número de fileiras por espiga, número de grãos por fileira, número de grãos por espiga e massa de 100 grãos) e a produtividade de grãos. O estande final de plantas e o número de espigas foram semelhantes entre os híbridos. Os híbridos comerciais de milho apresentam grande variação no desempenho agronômico na região sudeste de Goiás. Com relação à altura das plantas e da espiga, os híbridos LG6036 e 20A55 apresentaram as maiores alturas de plantas e o híbrido LG6036 apresentou maior altura de espiga. Já, para o diâmetro do colmo, as plantas dos híbridos Feroz, BX1293, LG6036, 20A55, Maximus e P3862 apresentaram colmos grossos. Na avaliação dos componentes da produção, os híbridos de milho demonstraram variação nos resultados. Os híbridos simples Maximus e P3862, e os triplos 20A55 e 30A95 foram os mais produtivos

Desempenho agronômico de híbridos de milho na região sudeste de Goiás

Uma das formas de maximizar a produtividade de grãos de milho é a escolha correta do híbrido para condições edafoclimáticas regionais. Nesse contexto, objetivou-se avaliar o desempenho agronômico de onze híbridos de milho na região sudeste de Goiás, Brasil. O experimento foi conduzido a campo, na safra (primavera-verão) 2013/2014, em Latossolo Vermelho distrófico sob condições edafoclimáticas do Cerrado, na região sudeste de Goiás. O delineamento experimental utilizado foi o de blocos ao acaso, sendo 11 tratamentos representados pelos híbridos de milho, com quatro repetições. Foram avaliados o estande final de plantas, número final de espigas, características morfológicas das plantas (altura da planta, altura da espiga e diâmetro do colmo), componentes da produção (comprimento da espiga, número de fileiras por espiga, número de grãos por fileira, número de grãos por espiga e massa de 100 grãos) e a produtividade de grãos. O estande final de plantas e o número de espigas foram semelhantes entre os híbridos. Os híbridos comerciais de milho apresentam grande variação no desempenho agronômico na região sudeste de Goiás. Com relação à altura das plantas e da espiga, os híbridos LG6036 e 20A55 apresentaram as maiores alturas de plantas e o híbrido LG6036 apresentou maior altura de espiga. Já, para o diâmetro do colmo, as plantas dos híbridos Feroz, BX1293, LG6036, 20A55, Maximus e P3862 apresentaram colmos grossos. Na avaliação dos componentes da produção, os híbridos de milho demonstraram variação nos resultados. Os híbridos simples Maximus e P3862, e os triplos 20A55 e 30A95 foram os mais produtivos

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Enhanced Classification of Interstitial Lung Disease Patterns in HRCT Images Using Differential Lacunarity

The analysis and interpretation of high-resolution computed tomography (HRCT) images of the chest in the presence of interstitial lung disease (ILD) is a time-consuming task which requires experience. In this paper, a computer-aided diagnosis (CAD) scheme is proposed to assist radiologists in the differentiation of lung patterns associated with ILD and healthy lung parenchyma. Regions of interest were described by a set of texture attributes extracted using differential lacunarity (DLac) and classical methods of statistical texture analysis. The proposed strategy to compute DLac allowed a multiscale texture analysis, while maintaining sensitivity to small details. Support Vector Machines were employed to distinguish between lung patterns. Training and model selection were performed over a stratified 10-fold cross-validation (CV). Dimensional reduction was made based on stepwise regression (F-test, p value < 0.01) during CV. An accuracy of 95.8 ± 2.2% in the differentiation of normal lung pattern from ILD patterns and an overall accuracy of 94.5 ± 2.1% in a multiclass scenario revealed the potential of the proposed CAD in clinical practice. Experimental results showed that the performance of the CAD was improved by combining multiscale DLac with classical statistical texture analysis