Remote Sensing of Aboveground Biomass in Tropical Secondary Forests: A Review

Tropical landscapes are, in general, a mosaic of pasture, agriculture, and forest undergoing various stages of succession. Forest succession is comprised of continuous structural changes over time and results in increases in aboveground biomass (AGB). New remote sensing methods, including sensors, image processing, statistical methods, and uncertainty evaluations, are constantly being developed to estimate biophysical forest changes. We review 318 peer-reviewed studies related to the use of remotely sensed AGB estimations in tropical forest succession studies and summarize their geographic distribution, sensors and methods used, and their most frequent ecological inferences. Remotely sensed AGB is broadly used in forest management studies, conservation status evaluations, carbon source and sink investigations, and for studies of the relationships between environmental conditions and forest structure. Uncertainties in AGB estimations were found to be heterogeneous with biases related to sensor type, processing methodology, ground truthing availability, and forest characteristics. Remotely sensed AGB of successional forests is more reliable for the study of spatial patterns of forest succession and over large time scales than that of individual stands. Remote sensing of temporal patterns in biomass requires further study, in particular, as it is critical for understanding forest regrowth at scales useful for regional or global analyses

Fragmentation of the brazilian Amazon.

Earth System Science Partnership (ESSP) Open Science Conference

Generalized Flow and Determinism in Measurement-based Quantum Computation

We extend the notion of quantum information flow defined by Danos and Kashefi for the one-way model and present a necessary and sufficient condition for the deterministic computation in this model. The generalized flow also applied in the extended model with measurements in the X-Y, X-Z and Y-Z planes. We apply both measurement calculus and the stabiliser formalism to derive our main theorem which for the first time gives a full characterization of the deterministic computation in the one-way model. We present several examples to show how our result improves over the traditional notion of flow, such as geometries (entanglement graph with input and output) with no flow but having generalized flow and we discuss how they lead to an optimal implementation of the unitaries. More importantly one can also obtain a better quantum computation depth with the generalized flow rather than with flow. We believe our characterization result is particularly essential for the study of the algorithms and complexity in the one-way model.Comment: 16 pages, 10 figure

Generalized Flow and Determinism in Measurement-based Quantum Computation

We extend the notion of quantum information flow defined by Danos and Kashefi for the one-way model and present a necessary and sufficient condition for the deterministic computation in this model. The generalized flow also applied in the extended model with measurements in the X-Y, X-Z and Y-Z planes. We apply both measurement calculus and the stabiliser formalism to derive our main theorem which for the first time gives a full characterization of the deterministic computation in the one-way model. We present several examples to show how our result improves over the traditional notion of flow, such as geometries (entanglement graph with input and output) with no flow but having generalized flow and we discuss how they lead to an optimal implementation of the unitaries. More importantly one can also obtain a better quantum computation depth with the generalized flow rather than with flow. We believe our characterization result is particularly essential for the study of the algorithms and complexity in the one-way model.Comment: 16 pages, 10 figure

The Air-temperature Response to Green/blue-infrastructure Evaluation Tool (TARGET v1.0): an efficient and user-friendly model of city cooling

The adverse impacts of urban heat and global climate change are leading policymakers to consider green and blue infrastructure (GBI) for heat mitigation benefits. Though many models exist to evaluate the cooling impacts of GBI, their complexity and computational demand leaves most of them largely inaccessible to those without specialist expertise and computing facilities. Here a new model called The Air-temperature Response to Green/blue-infrastructure Evaluation Tool (TARGET) is presented. TARGET is designed to be efficient and easy to use, with fewer user-defined parameters and less model input data required than other urban climate models. TARGET can be used to model average street-level air temperature at canyon-to-block scales (e.g. 100&thinsp;m resolution), meaning it can be used to assess temperature impacts of suburb-to-city-scale GBI proposals. The model aims to balance realistic representation of physical processes and computation efficiency. An evaluation against two different datasets shows that TARGET can reproduce the magnitude and patterns of both air temperature and surface temperature within suburban environments. To demonstrate the utility of the model for planners and policymakers, the results from two precinct-scale heat mitigation scenarios are presented. TARGET is available to the public, and ongoing development, including a graphical user interface, is planned for future work.</p

Industrial work placement in higher education: a study of civil engineering student engagement

For civil engineering undergraduates, the opportunity to spend a period of time in formal industrial work placement provides an invaluable learning experience. This paper reviews student engagement with short-term industrial placement and provides analysis of questionnaires (n=174) returned by undergraduates studying civil engineering at four Higher Education Institutes (HEI’s) in the West of Scotland. The data captures industrial placement statistics, employability skill-sets and presents brief testimonies from students. Whilst the journey to becoming a professional civil engineer is undoubtedly enhanced by short-term placement clear opportunities exist for HEI’s to affect and change existing pedagogical discourse. Commentary is likely to resonate beyond civil engineering and serve as a timely reminder of the need to re-invigorate academia / industry curriculum partnerships

Random Resistor-Diode Networks and the Crossover from Isotropic to Directed Percolation

By employing the methods of renormalized field theory we show that the percolation behavior of random resistor-diode networks near the multicritical line belongs to the universality class of isotropic percolation. We construct a mesoscopic model from the general epidemic process by including a relevant isotropy-breaking perturbation. We present a two-loop calculation of the crossover exponent $\phi$. Upon blending the $\epsilon$-expansion result with the exact value $\phi =1$ for one dimension by a rational approximation, we obtain for two dimensions $\phi = 1.29\pm 0.05$. This value is in agreement with the recent simulations of a two-dimensional random diode network by Inui, Kakuno, Tretyakov, Komatsu, and Kameoka, who found an order parameter exponent $\beta$ different from those of isotropic and directed percolation. Furthermore, we reconsider the theory of the full crossover from isotropic to directed percolation by Frey, T\"{a}uber, and Schwabl and clear up some minor shortcomings.Comment: 24 pages, 2 figure

The side effect profile of Clozapine in real world data of three large mental health hospitals

Objective: Mining the data contained within Electronic Health Records (EHRs) can potentially generate a greater understanding of medication effects in the real world, complementing what we know from Randomised control trials (RCTs). We Propose a text mining approach to detect adverse events and medication episodes from the clinical text to enhance our understanding of adverse effects related to Clozapine, the most effective antipsychotic drug for the management of treatment-resistant schizophrenia, but underutilised due to concerns over its side effects. Material and methods: We used data from de-identified EHRs of three mental health trusts in the UK (>50 million documents, over 500,000 patients, 2835 of which were prescribed Clozapine). We explored the prevalence of 33 adverse effects by age, gender, ethnicity, smoking status and admission type three months before and after the patients started Clozapine treatment. Where possible, we compared the prevalence of adverse effects with those reported in the Side Effects Resource (SIDER). Results: Sedation, fatigue, agitation, dizziness, hypersalivation, weight gain, tachycardia, headache, constipation and confusion were amongst the highest recorded Clozapine adverse effect in the three months following the start of treatment. Higher percentages of all adverse effects were found in the first month of Clozapine therapy. Using a significance level of (p< 0.05) our chi-square tests show a significant association between most of the ADRs and smoking status and hospital admission, and some in gender, ethnicity and age groups in all trusts hospitals. Later we combined the data from the three trusts hospitals to estimate the average effect of ADRs in each monthly interval. In gender and ethnicity, the results show significant association in 7 out of 33 ADRs, smoking status shows significant association in 21 out of 33 ADRs and hospital admission shows the significant association in 30 out of 33 ADRs. Conclusion: A better understanding of how drugs work in the real world can complement clinical trials

Analysis of the Lactobacilluscasei supragenome and its influence in species evolution and lifestyle adaptation

The broad ecological distribution of L. casei makes it an insightful subject for research on genome evolution and lifestyle adaptation. To explore evolutionary mechanisms that determine genomic diversity of L. casei, we performed comparative analysis of 17 L. casei genomes representing strains collected from dairy, plant, and human sources. Results Differences in L. casei genome inventory revealed an open pan-genome comprised of 1,715 core and 4,220 accessory genes. Extrapolation of pan-genome data indicates L. casei has a supragenome approximately 3.2 times larger than the average genome of individual strains. Evidence suggests horizontal gene transfer from other bacterial species, particularly lactobacilli, has been important in adaptation of L. casei to new habitats and lifestyles, but evolution of dairy niche specialists also appears to involve gene decay. Conclusions Genome diversity in L. casei has evolved through gene acquisition and decay. Acquisition of foreign genomic islands likely confers a fitness benefit in specific habitats, notably plant-associated niches. Loss of unnecessary ancestral traits in strains collected from bacterial-ripened cheeses supports the hypothesis that gene decay contributes to enhanced fitness in that niche. This study gives the first evidence for a L. casei supragenome and provides valuable insights into mechanisms for genome evolution and lifestyle adaptation of this ecologically flexible and industrially important lactic acid bacterium. Additionally, our data confirm the Distributed Genome Hypothesis extends to non-pathogenic, ecologically flexible species like L. casei