Conservation strategies to mitigate impacts from climate change in Amazonia

Protected area systems and conservation corridors can help mitigate the impacts of climate change on Amazonian biodiversity. We propose conservation design criteria that will help species survive in situ or adjust range distributions in response to increased drought. The first priority is to protect the western Amazon, identified as the ‘Core Amazon’, due to stable rainfall regimes and macro-ecological phenomena that have led to the evolution of high levels of biodiversity. Ecotones can buffer the impact from climate change because populations are genetically adapted to climate extremes, particularly seasonality, because high levels of habitat diversity are associated with edaphic variability. Future climatic tension zones should be surveyed for geomorphological features that capture rain or conserve soil moisture to identify potential refugia for humid forest species. Conservation corridors should span environmental gradients to ensure that species can shift range distributions. Riparian corridors provide protection to both terrestrial and aquatic ecosystems. Multiple potential altitudinal corridors exist in the Andes, but natural and anthropogenic bottlenecks will constrain the ability of species to shift their ranges and adapt to climate change. Planned infrastructure investments are a serious threat to the potential to consolidate corridors over the short and medium term

Characterizing neural coding performance for populations of sensory neurons: comparing a weighted spike distance metrics to other analytical methods

The identity of sensory stimuli is encoded in the spatio-temporal patterns of responses of the encoding neural population. For stimuli to be discriminated reliably, differences in population responses must be accurately decoded by downstream networks. Several methods to compare patterns of responses have been used by neurophysiologists to characterize the accuracy of the sensory responses studied. Among the most widely used analyses, we note methods based on Euclidean distances or on spike metric distances. Methods based on artificial neural networks and machine learning that recognize and/or classify specific input patterns have also gained popularity. Here, we first compare these three strategies using datasets from three different model systems: the moth olfactory system, the electrosensory system of gymnotids, and leaky-integrate-and-fire (LIF) model responses. We show that the input-weighting procedure inherent to artificial neural networks allows the efficient extraction of information relevant to stimulus discrimination. To combine the convenience of methods such as spike metric distances but leverage the advantages of weighting the inputs, we propose a measure based on geometric distances where each dimension is weighted proportionally to how informative it is. We show that the result of this Weighted Euclidian Distance (WED) analysis performs as well or better than the artificial neural network we tested and outperforms the more traditional spike distance metrics. We applied information theoretic analysis to LIF responses and compared their encoding accuracy with the discrimination accuracy quantified through this WED analysis. We show a high degree of correlation between discrimination accuracy and information content, and that our weighting procedure allowed the efficient use of information present to perform the discrimination task. We argue that our proposed measure provides the flexibility and ease of use sought by neurophysiologists while providing a more powerful way to extract relevant information than more traditional methods

Predicting death and readmission after intensive care discharge

Background: Despite initial recovery from critical illness, many patients deteriorate after discharge from the intensive care unit (ICU). We examined prospectively collected data in an attempt to identify patients at risk of readmission or death after intensive care discharge. Methods: This was a secondary analysis of clinical audit data from patients discharged alive from a mixed medical and surgical (non-cardiac) ICU. Results: Four hundred and seventy-five patients (11.2%) died in hospital after discharge from the ICU. Increasing age, time in hospital before intensive care admission, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and discharge Therapeutic Intervention Scoring System (TISS) score were independent risk factors for death after intensive care discharge. Three hundred and eighty-five patients (8.8%) were readmitted to intensive care during the same hospital admission. Increasing age, time in hospital before intensive care, APACHE II score, and discharge to a high dependency unit were independent risk factors for readmission. One hundred and forty-three patients (3.3%) were readmitted within 48 h of intensive care discharge. APACHE II scores and discharge to a high dependency or other ICU were independent risk factors for early readmission. The overall discriminant ability of our models was moderate with only marginal benefit over the APACHE II scores alone. Conclusions: We identified risk factors associated with death and readmission to intensive care. It was not possible to produce a definitive model based on these risk factors for predicting death or readmission in an individual patient.Not peer reviewedAuthor versio

Cosmic distance-duality as probe of exotic physics and acceleration

In cosmology, distances based on standard candles (e.g. supernovae) and standard rulers (e.g. baryon oscillations) agree as long as three conditions are met: (1) photon number is conserved, (2) gravity is described by a metric theory with (3) photons travelling on unique null geodesics. This is the content of distance-duality (the reciprocity relation) which can be violated by exotic physics. Here we analyse the implications of the latest cosmological data sets for distance-duality. While broadly in agreement and confirming acceleration we find a 2-sigma violation caused by excess brightening of SN-Ia at z > 0.5, perhaps due to lensing magnification bias. This brightening has been interpreted as evidence for a late-time transition in the dark energy but because it is not seen in the d_A data we argue against such an interpretation. Our results do, however, rule out significant SN-Ia evolution and extinction: the "replenishing" grey-dust model with no cosmic acceleration is excluded at more than 4-sigma despite this being the best-fit to SN-Ia data alone, thereby illustrating the power of distance-duality even with current data sets.Comment: 6 pages, 4 colour figures. Version accepted as a Rapid Communication in PR

Affective Man-Machine Interface: Unveiling human emotions through biosignals

As is known for centuries, humans exhibit an electrical profile. This profile is altered through various psychological and physiological processes, which can be measured through biosignals; e.g., electromyography (EMG) and electrodermal activity (EDA). These biosignals can reveal our emotions and, as such, can serve as an advanced man-machine interface (MMI) for empathic consumer products. However, such a MMI requires the correct classification of biosignals to emotion classes. This chapter starts with an introduction on biosignals for emotion detection. Next, a state-of-the-art review is presented on automatic emotion classification. Moreover, guidelines are presented for affective MMI. Subsequently, a research is presented that explores the use of EDA and three facial EMG signals to determine neutral, positive, negative, and mixed emotions, using recordings of 21 people. A range of techniques is tested, which resulted in a generic framework for automated emotion classification with up to 61.31% correct classification of the four emotion classes, without the need of personal profiles. Among various other directives for future research, the results emphasize the need for parallel processing of multiple biosignals

Reconstruction of the Dark Energy equation of state

One of the main challenges of modern cosmology is to investigate the nature of dark energy in our Universe. The properties of such a component are normally summarised as a perfect fluid with a (potentially) time-dependent equation-of-state parameter $w(z)$. We investigate the evolution of this parameter with redshift by performing a Bayesian analysis of current cosmological observations. We model the temporal evolution as piecewise linear in redshift between `nodes', whose $w$-values and redshifts are allowed to vary. The optimal number of nodes is chosen by the Bayesian evidence. In this way, we can both determine the complexity supported by current data and locate any features present in $w(z)$. We compare this node-based reconstruction with some previously well-studied parameterisations: the Chevallier-Polarski-Linder (CPL), the Jassal-Bagla-Padmanabhan (JBP) and the Felice-Nesseris-Tsujikawa (FNT). By comparing the Bayesian evidence for all of these models we find an indication towards possible time-dependence in the dark energy equation-of-state. It is also worth noting that the CPL and JBP models are strongly disfavoured, whilst the FNT is just significantly disfavoured, when compared to a simple cosmological constant $w=-1$. We find that our node-based reconstruction model is slightly disfavoured with respect to the $\Lambda$CDM model.Comment: 17 pages, 5 figures, minor correction

Observational Constraints on Chaplygin Quartessence: Background Results

We derive the constraints set by several experiments on the quartessence Chaplygin model (QCM). In this scenario, a single fluid component drives the Universe from a nonrelativistic matter-dominated phase to an accelerated expansion phase behaving, first, like dark matter and in a more recent epoch like dark energy. We consider current data from SNIa experiments, statistics of gravitational lensing, FR IIb radio galaxies, and x-ray gas mass fraction in galaxy clusters. We investigate the constraints from this data set on flat Chaplygin quartessence cosmologies. The observables considered here are dependent essentially on the background geometry, and not on the specific form of the QCM fluctuations. We obtain the confidence region on the two parameters of the model from a combined analysis of all the above tests. We find that the best-fit occurs close to the $\Lambda$CDM limit ($\alpha=0$). The standard Chaplygin quartessence ($\alpha=1$) is also allowed by the data, but only at the $\sim2\sigma$ level.Comment: Replaced to match the published version, references update

How much synthetic oxytocin is infused during labour? A review and analysis of regimens used in 12 countries.

OBJECTIVE: To compare synthetic oxytocin infusion regimens used during labour, calculate the International Units (IU) escalation rate and total amount of IU infused over eight hours. DESIGN: Observational study. SETTING: Twelve countries, eleven European and South Africa. SAMPLE: National, regional or institutional-level regimens on oxytocin for induction and augmentation labour. METHODS: Data on oxytocin IU dose, infusion fluid amount, start dose, escalation rate and maximum dose were collected. Values for each regimen were converted to IU in 1000ml diluent. One IU corresponded to 1.67μg for doses provided in grams/micrograms. IU hourly dose increase rates were based on escalation frequency. Cumulative doses and total IU amount infused were calculated by adding the dose administered for each previous hour. Main Outcome Measures Oxytocin IU dose infused. RESULTS: Data were obtained on 21 regimens used in 12 countries. Details on the start dose, escalation interval, escalation rate and maximum dose infused were available from 16 regimens. Starting rates varied from 0.06 IU/hour to 0.90 IU/hour, and the maximum dose rate varied from 0.90 IU/hour to 3.60 IU/hour. The total amount of IU oxytocin infused, estimated over eight hours, ranged from 2.38 IU to 27.00 IU, a variation of 24.62 IU and an 11-fold difference. CONCLUSION: Current variations in oxytocin regimens for induction and augmentation of labour are inexplicable. It is crucial that the appropriate minimum infusion regimen is administered because synthetic oxytocin is a potentially harmful medication with serious consequences for women and babies when inappropriately used. Estimating the total amount of oxytocin IU received by labouring women, alongside the institution's mode of birth and neonatal outcomes, may deepen our understanding and be the way forward to identifying the optimal infusion regimen