Chemical constituent analysis of the Babassu (Orbignya phalerata Mart.) mesocarp

The Babassu nut (Orbignya phalerata Mart.) mesocarp is traditionally transformed to flour and consumed in some Brazilian areas for its attributed medicinal activity; however, its chemical properties remain to be elucidated. The present work aimed at analyzing the babassu mesocarp phytochemical constituents. Babassu nut samples were collected in the Brazilian Amazon, and their mesocarps were prepared and macerated in different solvents. The chromatographic fractionation of selected methanol extracts yielded three fractions, A-5, A-6, and B - 1 that were characterized with high resolution methods. Fraction A-5 was characterized through GC/MS as a fatty acid mixture with predominance of eicosanoic (38.67 %) and 11-octadecanoic (21.71 %) acids. Fraction A-6 was characterized by the presence of three phytosteroids (32.02 %), sesquiterpene (nerolidol; 24.89 %), and diterpene (17-acetoxy-19-kauranal; 15.17 %). The 1H and 13C NMR spectra on fraction A-6 showed characteristic chemical shifts for its compounds. Compound B-1 was identified as ergostanol-3-benzoate based on NMR experiments in one and two dimensions. These results constitute the first identification of babassu mesocarp chemical constituents in 1 and 2-dimensions, paving the way to understanding its role in popular medicine

A TECNOLOGIA COMO DISPOSITIVO DO ATENDIMENTO HUMANIZADO NA ATENÇÃO BÁSICA À SAÚDE

Over the years, it has been observed that technology has been advancing more and more and has contributed significantly to people's lives, as well as to important areas such as health, because, based on these tools, it becomes possible to develop care faster and more humanized to patients who seek primary health care to obtain medical assistance. Thus, the research aims to explain the relevance of technology as a device for humanized care in primary health care. The methodology used consisted of the literature review method in order to obtain concise information about the objective of the work, with articles published from 2019 to 2022 available on Scielo, Lilacs and PubMed. Researches that were lower than 2019 were excluded, as well as those whose content was not in Portuguese, which would make the researchers' verification and analysis process difficult. In this way, the results pointed to the benefits caused by technology, enabling better care in terms of medical consultations, exams and guidance to patients, making humanized care in primary health care an essential factor. Concluding on the need to expand technology as a humanized device in all primary health care units, considering that some locations do not have these tools, because, in addition to promoting effectiveness in terms of faster assistance, it enables the minimization queue for appointments and exams.Com o passar dos anos, observa-se que a tecnologia vem avançando cada vez mais e contribuído de forma significativa na vida das pessoas, como também para áreas importantes como a da saúde, pois, a partir dessas ferramentas que torna-se possível desenvolver atendimento mais rápidos e humanizado aos pacientes que buscam atenção básica de saúde para obter assistência médica. Assim, a pesquisa objetiva explicar sobre a relevância da tecnologia como dispositivo do atendimento humanizado na atenção básica à saúde. A metodologia utilizada consistiu no método revisão de literatura com o intuito de obter informações concisas a respeito do objetivo do trabalho, sendo inserido artigos publicados no período de 2019 a 2022 disponíveis na Scielo, Lilacs e PubMed. Sendo excluídas pesquisas que estavam inferior a 2019, bem como aquelas cujo conteúdo não era língua portuguesa, o que dificultaria o processo de verificação e análise dos pesquisadores. Dessa forma, os resultados apontaram sobre os benefícios ocasionados pela tecnologia, possibilitando melhores atendimentos em termos de consultas médicas, exames e orientações aos pacientes, tornando o atendimento humanizado na atenção básica à saúde como um fator imprescindível. Concluindo-se sobre a necessidade de ampliar a tecnologia como dispositivo humanizado em todas as unidades de atenção básica à saúde, tendo em vista que algumas localidades não dispõem dessas ferramentas, pois, além de promover eficácia em termos de assistência mais rápida, possibilita a minimização da fila de espera por atendimentos e exames

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

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe

Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV

Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Impacts of the Tropical Pacific/Indian Oceans on the Seasonal Cycle of the West African Monsoon

The current consensus is that drought has developed in the Sahel during the second half of the twentieth century as a result of remote effects of oceanic anomalies amplified by local land–atmosphere interactions. This paper focuses on the impacts of oceanic anomalies upon West African climate and specifically aims to identify those from SST anomalies in the Pacific/Indian Oceans during spring and summer seasons, when they were significant. Idealized sensitivity experiments are performed with four atmospheric general circulation models (AGCMs). The prescribed SST patterns used in the AGCMs are based on the leading mode of covariability between SST anomalies over the Pacific/Indian Oceans and summer rainfall over West Africa. The results show that such oceanic anomalies in the Pacific/Indian Ocean lead to a northward shift of an anomalous dry belt from the Gulf of Guinea to the Sahel as the season advances. In the Sahel, the magnitude of rainfall anomalies is comparable to that obtained by other authors using SST anomalies confined to the proximity of the Atlantic Ocean. The mechanism connecting the Pacific/Indian SST anomalies with West African rainfall has a strong seasonal cycle. In spring (May and June), anomalous subsidence develops over both the Maritime Continent and the equatorial Atlantic in response to the enhanced equatorial heating. Precipitation increases over continental West Africa in association with stronger zonal convergence of moisture. In addition, precipitation decreases over the Gulf of Guinea. During the monsoon peak (July and August), the SST anomalies move westward over the equatorial Pacific and the two regions where subsidence occurred earlier in the seasons merge over West Africa. The monsoon weakens and rainfall decreases over the Sahel, especially in August.Peer reviewe