Universidade Federal de Alagoas

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Ecologists and evolutionary biologists are increasingly using big-data approaches to tackle questions at large spatial, taxonomic, and temporal scales. However, despite recent efforts to gather two centuries of biodiversity inventories into comprehensive databases, many crucial research questions remain unanswered. Here, we update the concept of knowledge shortfalls and review the tradeoffs between generality and uncertainty. We present seven key shortfalls of current biodiversity data. Four previously proposed shortfalls pinpoint knowledge gaps for species taxonomy (Linnean), distribution (Wallacean), abundance (Prestonian), and evolutionary patterns (Darwinian). We also redefine the Hutchinsonian shortfall to apply to the abiotic tolerances of species and propose new shortfalls relating to limited knowledge of species traits (Raunkiæran) and biotic interactions (Eltonian). We conclude with a general framework for the combined impacts and consequences of shortfalls of large-scale biodiversity knowledge for evolutionary and ecological research and consider ways of overcoming the seven shortfalls and dealing with the uncertainty they generate.

Plants living under natural conditions are exposed to many adverse factors that interfere with the photosynthetic process, leading to declines in growth, development, and yield. The recent development of Chlorophyll a fluorescence (ChlF) represents a potentially valuable new approach to study the photochemical efficiency of leaves. Specifically, the analysis of fluorescence signals provides detailed information on the status and function of Photosystem II (PSII) reaction centers, light-harvesting antenna complexes, and both the donor and acceptor sides of PSII. Here, we review the results of fast ChlF analyses of photosynthetic responses to environmental stresses, and discuss the potential scientific and practical applications of this innovative methodology. The recent availability of portable devices has significantly expanded the potential utilization of ChlF techniques, especially for the purposes of crop phenotyping and monitoring.

Abstract While Artificial Intelligence in Education (AIED) research has at its core the desire to support student learning, experience from other AI domains suggest that such ethical intentions are not by themselves sufficient. There is also the need to consider explicitly issues such as fairness, accountability, transparency, bias, autonomy, agency, and inclusion. At a more general level, there is also a need to differentiate between doing ethical things and doing things ethically , to understand and to make pedagogical choices that are ethical, and to account for the ever-present possibility of unintended consequences. However, addressing these and related questions is far from trivial. As a first step towards addressing this critical gap, we invited 60 of the AIED community’s leading researchers to respond to a survey of questions about ethics and the application of AI in educational contexts. In this paper, we first introduce issues around the ethics of AI in education. Next, we summarise the contributions of the 17 respondents, and discuss the complex issues that they raised. Specific outcomes include the recognition that most AIED researchers are not trained to tackle the emerging ethical questions. A well-designed framework for engaging with ethics of AIED that combined a multidisciplinary approach and a set of robust guidelines seems vital in this context.

The aim of this educational review is to provide practical information on the hardware, methodology, and the hands on application of chlorophyll (Chl) a fluorescence technology. We present the paper in a question and answer format like frequently asked questions. Although nearly all information on the application of Chl a fluorescence can be found in the literature, it is not always easily accessible. This paper is primarily aimed at scientists who have some experience with the application of Chl a fluorescence but are still in the process of discovering what it all means and how it can be used. Topics discussed are (among other things) the kind of information that can be obtained using different fluorescence techniques, the interpretation of Chl a fluorescence signals, specific applications of these techniques, and practical advice on different subjects, such as on the length of dark adaptation before measurement of the Chl a fluorescence transient.

The role of very-low-carbohydrate ketogenic diets (VLCKD) in the long-term management of obesity is not well established. The present meta-analysis aimed to investigate whether individuals assigned to a VLCKD (i.e. a diet with no more than 50 g carbohydrates/d) achieve better long-term body weight and cardiovascular risk factor management when compared with individuals assigned to a conventional low-fat diet (LFD; i.e. a restricted-energy diet with less than 30% of energy from fat). Through August 2012, MEDLINE, CENTRAL, ScienceDirect,Scopus, LILACS, SciELO, ClinicalTrials.gov and grey literature databases were searched, using no date or language restrictions, for randomised controlled trials that assigned adults to a VLCKD or a LFD, with 12 months or more of follow-up. The primary outcome was bodyweight. The secondary outcomes were TAG, HDL-cholesterol (HDL-C), LDL-cholesterol (LDL-C), systolic and diastolic blood pressure,glucose, insulin, HbA1c and C-reactive protein levels. A total of thirteen studies met the inclusion/exclusion criteria. In the overall analysis,five outcomes revealed significant results. Individuals assigned to a VLCKD showed decreased body weight (weighted mean difference -0·91 (95% CI -1·65, -0·17) kg, 1415 patients), TAG (weighted mean difference -0·18 (95% CI -0·27, -0·08) mmol/l, 1258 patients)and diastolic blood pressure (weighted mean difference -1·43 (95% CI -2·49, -0·37) mmHg, 1298 patients) while increased HDL-C(weighted mean difference 0·09 (95% CI 0·06, 0·12) mmol/l, 1257 patients) and LDL-C (weighted mean difference 0·12 (95% CI 0·04,0·2) mmol/l, 1255 patients). Individuals assigned to a VLCKD achieve a greater weight loss than those assigned to a LFD in the longterm; hence, a VLCKD may be an alternative tool against obesity.

Recent advances in spatial ecology have improved our understanding of the role of large-scale animal movements.However, an unsolved problem concerns the inherent stochasticity involved in many animal search displacements and its possible adaptive value.When animals have no information about where targets (i.e., resource patches, mates, etc.) are located, different random search strategies may provide different chances to find them.Assuming random-walk models as a necessary tool to understand how animals face such environmental uncertainty, we analyze the statistical differences between two random-walk models commonly used to fit animal movement data, the Le ´vy walks and the correlated random walks, and we quantify their efficiencies (i.e., the number of targets found in relation to total displacement) within a random search context.Correlated random-walk properties (i.e., scale-finite correlations) may be interpreted as the by-product of locally scanning mechanisms.Le ´vy walks, instead, have fundamental properties (i.e., super-diffusivity and scale invariance) that allow a higher efficiency in random search scenarios.Specific biological mechanisms related to how animals punctuate their movement with sudden reorientations in a random search would be sufficient to sustain Le ´vy walk properties.Furthermore, we investigate a new model (the Le ´vy-modulated correlated random walk) that combines the properties of correlated and Le ´vy walks.This model shows that Le ´vy walk properties are robust to any behavioral mechanism providing short-range correlations in the walk.We propose that some animals may have evolved the ability of performing Le ´vy walks as adaptive strategies in order to face search uncertainties.

Entropy is a powerful tool for the analysis of time series, as it allows describing the probability distributions of the possible state of a system, and therefore the information encoded in it. Nevertheless, important information may be codified also in the temporal dynamics, an aspect which is not usually taken into account. The idea of calculating entropy based on permutation patterns (that is, permutations defined by the order relations among values of a time series) has received a lot of attention in the last years, especially for the understanding of complex and chaotic systems. Permutation entropy directly accounts for the temporal information contained in the time series; furthermore, it has the quality of simplicity, robustness and very low computational cost. To celebrate the tenth anniversary of the original work, here we analyze the theoretical foundations of the permutation entropy, as well as the main recent applications to the analysis of economical markets and to the understanding of biomedical systems.

Abstract Aim Tropical forests store 25% of global carbon and harbour 96% of the world's tree species, but it is not clear whether this high biodiversity matters for carbon storage. Few studies have teased apart the relative importance of forest attributes and environmental drivers for ecosystem functioning, and no such study exists for the tropics. Location Neotropics. Methods We relate aboveground biomass ( AGB ) to forest attributes (diversity and structure) and environmental drivers (annual rainfall and soil fertility) using data from 144,000 trees, 2050 forest plots and 59 forest sites. The sites span the complete latitudinal and climatic gradients in the lowland Neotropics, with rainfall ranging from 750 to 4350 mm year −1 . Relationships were analysed within forest sites at scales of 0.1 and 1 ha and across forest sites along large‐scale environmental gradients. We used a structural equation model to test the hypothesis that species richness, forest structural attributes and environmental drivers have independent, positive effects on AGB . Results Across sites, AGB was most strongly driven by rainfall, followed by average tree stem diameter and rarefied species richness, which all had positive effects on AGB . Our indicator of soil fertility (cation exchange capacity) had a negligible effect on AGB , perhaps because we used a global soil database. Taxonomic forest attributes (i.e. species richness, rarefied richness and Shannon diversity) had the strongest relationships with AGB at small spatial scales, where an additional species can still make a difference in terms of niche complementarity, while structural forest attributes (i.e. tree density and tree size) had strong relationships with AGB at all spatial scales. Main conclusions Biodiversity has an independent, positive effect on AGB and ecosystem functioning, not only in relatively simple temperate systems but also in structurally complex hyperdiverse tropical forests. Biodiversity conservation should therefore be a key component of the UN Reducing Emissions from Deforestation and Degradation strateg y.

Up with ultrafine aerosol particles Ultrafine aerosol particles (smaller than 50 nanometers in diameter) have been thought to be too small to affect cloud formation. Fan et al. show that this is not the case. They studied the effect of urban pollution transported into the otherwise nearly pristine atmosphere of the Amazon. Condensational growth of water droplets around the tiny particles releases latent heat, thereby intensifying atmospheric convection. Thus, anthropogenic ultrafine aerosol particles may exert a more important influence on cloud formation processes than previously believed. Science , this issue p. 411

Wireless sensor networks produce a large amount of data that needs to be processed, delivered, and assessed according to the application objectives. The way these data are manipulated by the sensor nodes is a fundamental issue. Information fusion arises as a response to process data gathered by sensor nodes and benefits from their processing capability. By exploiting the synergy among the available data, information fusion techniques can reduce the amount of data traffic, filter noisy measurements, and make predictions and inferences about a monitored entity. In this work, we survey the current state-of-the-art of information fusion by presenting the known methods, algorithms, architectures, and models of information fusion, and discuss their applicability in the context of wireless sensor networks.

Abstract A workshop on enhancing climate change indices in South America was held in Maceió, Brazil, in August 2004. Scientists from eight southern countries brought daily climatological data from their region for a meticulous assessment of data quality and homogeneity, and for the preparation of climate change indices that can be used for analyses of changes in climate extremes. This study presents an examination of the trends over 1960–2000 in the indices of daily temperature extremes. The results indicate no consistent changes in the indices based on daily maximum temperature while significant trends were found in the indices based on daily minimum temperature. Significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations. It seems that this warming is mostly due to more warm nights and fewer cold nights during the summer (December–February) and fall (March–May). The stations with significant trends appear to be located closer to the west and east coasts of South America.

Undernutrition is one of the most important public health problems, affecting more than 900 million individuals around the World. It is responsible for the highest mortality rate in children and has long-lasting physiologic effects, including an increased susceptibility to fat accumulation mostly in the central region of the body, lower fat oxidation, lower resting and postprandial energy expenditure, insulin resistance in adulthood, hypertension, dyslipidaemia and a reduced capacity for manual work, among other impairments. Marked changes in the function of the autonomic nervous system have been described in undernourished experimental animals. Some of these effects seem to be epigenetic, passing on to the next generation. Undernutrition in children has been linked to poor mental development and school achievement as well as behavioural abnormalities. However, there is still a debate in the literature regarding whether some of these effects are permanent or reversible. Stunted children who had experienced catch-up growth had verbal vocabulary and quantitative test scores that did not differ from children who were not stunted. Children treated before 6 years of age in day-hospitals and who recovered in weight and height have normal body compositions, bone mineral densities and insulin production and sensitivity.

Abstract Most of the planet's diversity is concentrated in the tropics, which includes many regions undergoing rapid climate change. Yet, while climate‐induced biodiversity changes are widely documented elsewhere, few studies have addressed this issue for lowland tropical ecosystems. Here we investigate whether the floristic and functional composition of intact lowland Amazonian forests have been changing by evaluating records from 106 long‐term inventory plots spanning 30 years. We analyse three traits that have been hypothesized to respond to different environmental drivers (increase in moisture stress and atmospheric CO 2 concentrations): maximum tree size, biogeographic water‐deficit affiliation and wood density. Tree communities have become increasingly dominated by large‐statured taxa, but to date there has been no detectable change in mean wood density or water deficit affiliation at the community level, despite most forest plots having experienced an intensification of the dry season. However, among newly recruited trees, dry‐affiliated genera have become more abundant, while the mortality of wet‐affiliated genera has increased in those plots where the dry season has intensified most. Thus, a slow shift to a more dry‐affiliated Amazonia is underway, with changes in compositional dynamics (recruits and mortality) consistent with climate‐change drivers, but yet to significantly impact whole‐community composition. The Amazon observational record suggests that the increase in atmospheric CO 2 is driving a shift within tree communities to large‐statured species and that climate changes to date will impact forest composition, but long generation times of tropical trees mean that biodiversity change is lagging behind climate change.

-acetylcysteine (NAC) is a medicine widely used to treat paracetamol overdose and as a mucolytic compound. It has a well-established safety profile, and its toxicity is uncommon and dependent on the route of administration and high dosages. Its remarkable antioxidant and anti-inflammatory capacity is the biochemical basis used to treat several diseases related to oxidative stress and inflammation. The primary role of NAC as an antioxidant stems from its ability to increase the intracellular concentration of glutathione (GSH), which is the most crucial biothiol responsible for cellular redox imbalance. As an anti-inflammatory compound, NAC can reduce levels of tumor necrosis factor-alpha (TNF-α) and interleukins (IL-6 and IL-1β) by suppressing the activity of nuclear factor kappa B (NF-κB). Despite NAC's relevant therapeutic potential, in several experimental studies, its effectiveness in clinical trials, addressing different pathological conditions, is still limited. Thus, the purpose of this chapter is to provide an overview of the medicinal effects and applications of NAC to human health based on current therapeutic evidence.

We show that the orbital angular momentum can be used to unveil lattice properties hidden in diffraction patterns of a simple triangular aperture. Depending on the orbital angular momentum of the incident beam, the far field diffraction pattern reveals a truncated optical lattice associated with the illuminated aperture. This effect can be used to measure the topological charge of light beams.

Power-law sensitivity to the initial conditions at the edge of chaos provides a natural relation between the scaling properties of the dynamics attractor and its degree of nonextensivity within the generalized statistics recently introduced by one of the authors (C.T.) and characterized by the entropic index $q$. We show that general scaling arguments imply that $1/(1\ensuremath{-}q)\phantom{\rule{0ex}{0ex}}=\phantom{\rule{0ex}{0ex}}1/{\ensuremath{\alpha}}_{\mathrm{min}}\ensuremath{-}1/{\ensuremath{\alpha}}_{\mathrm{max}}$, where ${\ensuremath{\alpha}}_{\mathrm{min}}$ and ${\ensuremath{\alpha}}_{\mathrm{max}}$ are the extremes of the multifractal singularity spectrum $f(\ensuremath{\alpha})$ of the attractor. This relation is numerically verified in standard $D\phantom{\rule{0ex}{0ex}}=\phantom{\rule{0ex}{0ex}}1$ dissipative maps.

Experience economy is the last segment in the evolution of the market, and it is characterized by the fact that consumers do not acquire goods, products or services, but experiences that they integrate in their biography, and consequently in their identity. Customer Experience, possibly the latest revolution in business thinking along with the digital transformation, seeks the design and management of truly customer-centric experiences. This revolution is spreading across different sectors, among which the health sector should necessarily be considered. This talk covers the fundamental ideas within the concept of customer experience, as well as it provides information and suggestions about how to design and deliver an optimal patient experience.

Human activities are changing our environment. Along with climate change and a widespread loss of biodiversity, plastic pollution now plays a predominant role in altering ecosystems globally. Here, we review the occurrence of plastic ingestion by wildlife through evolutionary and ecological lenses and address the fundamental question of why living organisms ingest plastic. We unify evolutionary, ecological, and cognitive approaches under the evolutionary trap theory and identify three main factors that may drive plastic ingestion: (i) the availability of plastics in the environment, (ii) an individual's acceptance threshold, and (iii) the overlap of cues given by natural foods and plastics.

We study the nature of electronic states in a tight-binding one-dimensional model with the on-site energies exhibiting long-range correlated disorder and nonrandom hopping amplitudes. The site energies describe the trace of a fractional Brownian motion with a specified spectral density $S(k)\ensuremath{\propto}1/{k}^{\ensuremath{\alpha}}$. Using a renormalization group technique, we show that for long-range correlated energy sequences with persistent increments ( $\ensuremath{\alpha}>2$) the Lyapunov coefficient (inverse localization length) vanishes within a finite range of energy values revealing the presence of an Anderson-like metal-insulator transition.