4,158 research outputs found
Fitness Ranking of Individual Mutants Drives Patterns of Epistatic Interactions in HIV-1
This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Geo-environmental mapping using physiographic analysis: constraints on the evaluation of land instability and groundwater pollution hazards in the Metropolitan District of Campinas, Brazil
Geo-environmental terrain assessments and territorial zoning are useful tools for the formulation and implementation of environmental management instruments (including policy-making, planning, and enforcement of statutory regulations). They usually involve a set of procedures and techniques for delimitation, characterisation and classification of terrain units. However, terrain assessments and zoning exercises are often costly and time-consuming, particularly when encompassing large areas, which in many cases prevent local agencies in developing countries from properly benefiting from such assessments. In the present paper, a low-cost technique based on the analysis of texture of satellite imagery was used for delimitation of terrain units. The delimited units were further analysed in two test areas situated in Southeast Brazil to provide estimates of land instability and the vulnerability of groundwater to pollution hazards. The implementation incorporated procedures for inferring the influences and potential implications of tectonic fractures and other discontinuities on ground behaviour and local groundwater flow. Terrain attributes such as degree of fracturing, bedrock lithology and weathered materials were explored as indicators of ground properties. The paper also discusses constraints on- and limitations of- the approaches taken
Persistence of magnetic field driven by relativistic electrons in a plasma
The onset and evolution of magnetic fields in laboratory and astrophysical
plasmas is determined by several mechanisms, including instabilities, dynamo
effects and ultra-high energy particle flows through gas, plasma and
interstellar-media. These processes are relevant over a wide range of
conditions, from cosmic ray acceleration and gamma ray bursts to nuclear fusion
in stars. The disparate temporal and spatial scales where each operates can be
reconciled by scaling parameters that enable to recreate astrophysical
conditions in the laboratory. Here we unveil a new mechanism by which the flow
of ultra-energetic particles can strongly magnetize the boundary between the
plasma and the non-ionized gas to magnetic fields up to 10-100 Tesla (micro
Tesla in astrophysical conditions). The physics is observed from the first
time-resolved large scale magnetic field measurements obtained in a laser
wakefield accelerator. Particle-in-cell simulations capturing the global plasma
and field dynamics over the full plasma length confirm the experimental
measurements. These results open new paths for the exploration and modelling of
ultra high energy particle driven magnetic field generation in the laboratory
Scale invariance and universality of force networks in static granular matter
Force networks form the skeleton of static granular matter. They are the key
ingredient to mechanical properties, such as stability, elasticity and sound
transmission, which are of utmost importance for civil engineering and
industrial processing. Previous studies have focused on the global structure of
external forces (the boundary condition), and on the probability distribution
of individual contact forces. The disordered spatial structure of the force
network, however, has remained elusive so far. Here we report evidence for
scale invariance of clusters of particles that interact via relatively strong
forces. We analyzed granular packings generated by molecular dynamics
simulations mimicking real granular matter; despite the visual variation, force
networks for various values of the confining pressure and other parameters have
identical scaling exponents and scaling function, and thus determine a
universality class. Remarkably, the flat ensemble of force configurations--a
simple generalization of equilibrium statistical mechanics--belongs to the same
universality class, while some widely studied simplified models do not.Comment: 15 pages, 4 figures; to appear in Natur
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Grazing exclusion-induced changes in soil fungal communities in a highly desertified Brazilian dryland
Soil desertification poses a critical ecological challenge in arid and semiarid climates worldwide, leading to decreased soil productivity due to the disruption of essential microbial community processes. Fungi, as one of the most important soil microbial communities, play a crucial role in enhancing nutrient and water uptake by plants through mycorrhizal associations. However, the impact of overgrazing-induced desertification on fungal community structure, particularly in the Caatinga biome of semiarid regions, remains unclear. In this study, we assessed the changes in both the total fungal community and the arbuscular mycorrhizal fungal community (AMF) across 1. Natural vegetation (native), 2. Grazing exclusion (20 years) (restored), and 3. affected by overgrazing-induced degradation (degraded) scenarios. Our assessment, conducted during both the dry and rainy seasons in Irauçuba, Ceará, utilized Internal Transcribed Spacer (ITS) gene sequencing via Illumina® platform. Our findings highlighted the significant roles of the AMF families Glomeraceae (∼71% of the total sequences) and Acaulosporaceae (∼14% of the total sequences) as potential key taxa in mitigating climate change within dryland areas. Moreover, we identified the orders Pleosporales (∼35% of the total sequences) and Capnodiales (∼21% of the total sequences) as the most abundant soil fungal communities in the Caatinga biome. The structure of the total fungal community differed when comparing native and restored areas to degraded areas. Total fungal communities from native and restored areas clustered together, suggesting that grazing exclusion has the potential to improve soil properties and recover fungal community structure amid global climate change challenges
Positive and negative well-being and objectively measured sedentary behaviour in older adults: evidence from three cohorts
Background:
Sedentary behaviour is related to poorer health independently of time spent in moderate to vigorous physical activity. The aim of this study was to investigate whether wellbeing or symptoms of anxiety or depression predict sedentary behaviour in older adults.
Method:
Participants were drawn from the Lothian Birth Cohort 1936 (LBC1936) (n = 271), and the West of Scotland Twenty-07 1950s (n = 309) and 1930s (n = 118) cohorts. Sedentary outcomes, sedentary time, and number of sit-to-stand transitions, were measured with a three-dimensional accelerometer (activPAL activity monitor) worn for 7 days. In the Twenty-07 cohorts, symptoms of anxiety and depression were assessed in 2008 and sedentary outcomes were assessed ~ 8 years later in 2015 and 2016. In the LBC1936 cohort, wellbeing and symptoms of anxiety and depression were assessed concurrently with sedentary behaviour in 2015 and 2016. We tested for an association between wellbeing, anxiety or depression and the sedentary outcomes using multivariate regression analysis.
Results:
We observed no association between wellbeing or symptoms of anxiety and the sedentary outcomes. Symptoms of depression were positively associated with sedentary time in the LBC1936 and Twenty-07 1950s cohort, and negatively associated with number of sit-to-stand transitions in the LBC1936. Meta-analytic estimates of the association between depressive symptoms and sedentary time or number of sit-to-stand transitions, adjusted for age, sex, BMI, long-standing illness, and education, were β = 0.11 (95% CI = 0.03, 0.18) and β = − 0.11 (95% CI = − 0.19, −0.03) respectively.
Conclusion:
Our findings indicate that depressive symptoms are positively associated with sedentary behavior. Future studies should investigate the causal direction of this association
Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows
Background: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patients are usually heterogeneous, containing patients at different stages of the neurodegenerative process. This hampers the prognostic task. Nevertheless, when learning prognostic models, most studies use the entire cohort of MCI patients regardless of their disease stages. In this paper, we propose a Time Windows approach to predict conversion to dementia, learning with patients stratified using time windows, thus fine-tuning the prognosis regarding the time to conversion. Methods: In the proposed Time Windows approach, we grouped patients based on the clinical information of whether they converted (converter MCI) or remained MCI (stable MCI) within a specific time window. We tested time windows of 2, 3, 4 and 5 years. We developed a prognostic model for each time window using clinical and neuropsychological data and compared this approach with the commonly used in the literature, where all patients are used to learn the models, named as First Last approach. This enables to move from the traditional question "Will a MCI patient convert to dementia somewhere in the future" to the question "Will a MCI patient convert to dementia in a specific time window". Results: The proposed Time Windows approach outperformed the First Last approach. The results showed that we can predict conversion to dementia as early as 5 years before the event with an AUC of 0.88 in the cross-validation set and 0.76 in an independent validation set. Conclusions: Prognostic models using time windows have higher performance when predicting progression from MCI to dementia, when compared to the prognostic approach commonly used in the literature. Furthermore, the proposed Time Windows approach is more relevant from a clinical point of view, predicting conversion within a temporal interval rather than sometime in the future and allowing clinicians to timely adjust treatments and clinical appointments.FCT under the Neuroclinomics2 project [PTDC/EEI-SII/1937/2014, SFRH/BD/95846/2013]; INESC-ID plurianual [UID/CEC/50021/2013]; LASIGE Research Unit [UID/CEC/00408/2013
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Managing volunteerism behaviour: The drivers of donations practices in religious and secular organisations
The present research deals with donations practices and the extent to which drivers of donations practices contribute to volunteerism. The paper aims to deepen the understanding of the relationship between volunteerism and key drivers in donating behavior and donations practices, thus allowing charities to pursue more efficient ways in which to elicit volunteer work as well as better manage fundraising practices. It is argued that gender, age, religious affiliation, compassion, altruism, egoism, and religiosity impact on the level of volunteerism of the donor.
A sample of 612 Portuguese donors was selected from within a population of donors that donate regularly to charitable institutions. The key findings of the current study are grounded on the idea of interaction between the volunteering behavior of a donor and both his level of religiosity and his religious affiliation. With regard to other drivers of donations practices, it was found that both altruism and compassion are positively correlated with donor volunteerism
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