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

The Youngest Victims: Children and Youth Affected by War

In 1989, the United Nation Convention on the Rights of the Child declared, “[state parties] shall take all feasible measures to ensure protection and care of children who are affected by an armed conflict.” In addition to attempting to secure the welfare of children in armed conflict, the Convention went on to ban the recruitment and deployment of children during armed conflict. Despite the vast majority of sovereign nations signing and ratifying this agreement, this treaty, unfortunately, has not prevented children and youth from witnessing, becoming victims of, or participating in political, ethnic, religious, and cultural violence across the past three decades. This chapter offers an “ecological perspective” on the psychosocial consequences of exposure to the trauma of war-related violence and social disruption

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

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

Nursing protocol in transcatheter aortic valve implantation: care guideline

Abstract Objective: To validate a nursing care protocol by specialist nurses, contributing to the care delivered to patients undergoing percutaneous valve replacement. Methods: This cross-sectional, prospective, quantitative study adopted the Content Validity Index (CVI) to verify level of agreement regarding this protocol's total set of items. Results: The CVI obtained for each item of the protocol, verified using a validation instrument, was greater than the minimum required that is 0.80, on average. Conclusion: The development of a protocol intended to guide care provided to patients who have undergone TAVI, improves patient safety and minimizes health problems, so that the implementation of specific strategies for the development of actions performed by nurses is essential

Fatigue behavior of concrete: A literature review on the main relevant parameters

This paper contributes by summarizing knowledge on the fatigue behavior of concrete, discussing current standardization, and organizing previous contributions and prospecting future developments in experimental research. It describes classical laboratory fatigue tests and analysis (S-N curves, damage effects on modulus etc.), emphasizing differences expected for real loading (with variation in frequency and temperature, among other effects). Not only current standards diverge in results, but more fundamental effects were observed. Temperature has relevant impact on fatigue life, and during tests it may change due to self-heating. Specimen dimensions are relevant for this phenomenon. Loading frequency seems to influence fatigue, and since tests in laboratory need to be accelerated (high frequency) compared to the field (low frequency), this is a major concern. Other investigated effects include loading waveforms and moistur

Increment of body mass index is positively correlated with worsening of endothelium-dependent and independent changes in forearm blood flow

Obesity is associated with the impairment of endothelial function leading to the initiation of the atherosclerotic process. We have hypothesized that an increasing impairment of endothelial and vascular smooth muscle cell functions occurs from lean subjects to severe obese ones. Thus, the present study was carried out to investigate the grade of obesity in which endothelial dysfunction can be detected and if there is an increasing impairment of endothelial and vascular smooth muscle cell functions as body mass index increases. According to body mass index, subjects were allocated into five groups: Lean controls, Overweight, Obese class I, Obese class II, and Obese class III. Endothelial and vascular smooth muscle cell functions were evaluated measuring forearm blood flow responses to increasing intra-arterial infusions of acetylcholine and sodium nitroprusside using venous occlusion plethysmography. We observed that forearm blood flow was progressively impaired from lean controls to severe obese and found no significant differences between Lean controls and Overweight groups. Our data suggests that obesity class I is the first grade of obesity in which endothelial dysfunction can be detected and that body mass index positively correlates with the worsening of endothelium-dependent and independent changes in forearm blood flow