Climate change adaptation and cross-sectoral policy coherence in southern Africa

To be effective, climate change adaptation needs to be mainstreamed across multiple sectors and greater policy coherence is essential. Using the cases of Malawi, Tanzania and Zambia, this paper investigates the extent of coherence in national policies across the water and agriculture sectors and to climate change adaptation goals outlined in national development plans. A two-pronged qualitative approach is applied using Qualitative Document Analysis of relevant policies and plans, combined with expert interviews from non-government actors in each country. Findings show that sector policies have differing degrees of coherence on climate change adaptation, currently being strongest in Zambia and weakest in Tanzania. We also identify that sectoral policies remain more coherent in addressing immediate-term disaster management issues of floods and droughts rather than longer-term strategies for climate adaptation. Coherence between sector and climate policies and strategies is strongest when the latter has been more recently developed. However to date, this has largely been achieved by repackaging of existing sectoral policy statements into climate policies drafted by external consultants to meet international reporting needs and not by the establishment of new connections between national sectoral planning processes. For more effective mainstreaming of climate change adaptation, governments need to actively embrace longer-term cross-sectoral planning through cross-Ministerial structures, such as initiated through Zambia’s Interim Climate Change Secretariat, to foster greater policy coherence and integrated adaptation planning

The Challenge of Machine Learning in Space Weather Nowcasting and Forecasting

The numerous recent breakthroughs in machine learning (ML) make imperative to carefully ponder how the scientific community can benefit from a technology that, although not necessarily new, is today living its golden age. This Grand Challenge review paper is focused on the present and future role of machine learning in space weather. The purpose is twofold. On one hand, we will discuss previous works that use ML for space weather forecasting, focusing in particular on the few areas that have seen most activity: the forecasting of geomagnetic indices, of relativistic electrons at geosynchronous orbits, of solar flares occurrence, of coronal mass ejection propagation time, and of solar wind speed. On the other hand, this paper serves as a gentle introduction to the field of machine learning tailored to the space weather community and as a pointer to a number of open challenges that we believe the community should undertake in the next decade. The recurring themes throughout the review are the need to shift our forecasting paradigm to a probabilistic approach focused on the reliable assessment of uncertainties, and the combination of physics-based and machine learning approaches, known as gray-box.Comment: under revie

The XWS open access catalogue of extreme European windstorms from 1979 to 2012

The XWS (eXtreme WindStorms) catalogue consists of storm tracks and model-generated maximum 3 s wind-gust footprints for 50 of the most extreme winter windstorms to hit Europe in the period 1979–2012. The catalogue is intended to be a valuable resource for both academia and industries such as (re)insurance, for example allowing users to characterise extreme European storms, and validate climate and catastrophe models. Several storm severity indices were investigated to find which could best represent a list of known high-loss (severe) storms. The best-performing index was Sft, which is a combination of storm area calculated from the storm footprint and maximum 925 hPa wind speed from the storm track. All the listed severe storms are included in the catalogue, and the remaining ones were selected using Sft. A comparison of the model footprint to station observations revealed that storms were generally well represented, although for some storms the highest gusts were underestimated. Possible reasons for this underestimation include the model failing to simulate strong enough pressure gradients and not representing convective gusts. A new recalibration method was developed to estimate the true distribution of gusts at each grid point and correct for this underestimation. The recalibration model allows for storm-to-storm variation which is essential given that different storms have different degrees of model bias. The catalogue is available at www.europeanwindstorms.org

Runaway Events Dominate the Heavy Tail of Citation Distributions

Statistical distributions with heavy tails are ubiquitous in natural and social phenomena. Since the entries in heavy tail have disproportional significance, the knowledge of its exact shape is very important. Citations of scientific papers form one of the best-known heavy tail distributions. Even in this case there is a considerable debate whether citation distribution follows the log-normal or power-law fit. The goal of our study is to solve this debate by measuring citation distribution for a very large and homogeneous data. We measured citation distribution for 418,438 Physics papers published in 1980-1989 and cited by 2008. While the log-normal fit deviates too strong from the data, the discrete power-law function with the exponent $\gamma=3.15$ does better and fits 99.955% of the data. However, the extreme tail of the distribution deviates upward even from the power-law fit and exhibits a dramatic "runaway" behavior. The onset of the runaway regime is revealed macroscopically as the paper garners 1000-1500 citations, however the microscopic measurements of autocorrelation in citation rates are able to predict this behavior in advance.Comment: 6 pages, 5 Figure

Metabolic Signatures of Lung Cancer in Biofluids: NMR-Based Metabonomics of Blood Plasma

In this work, the variations in the metabolic profile of blood plasma from lung cancer patients and healthy controls were investigated through NMR-based metabonomics, to assess the potential of this approach for lung cancer screening and diagnosis. PLS-DA modeling of CPMG spectra from plasma, subjected to Monte Carlo Cross Validation, allowed cancer patients to be discriminated from controls with sensitivity and specificity levels of about 90%. Relatively lower HDL and higher VLDL + LDL in the patients' plasma, together with increased lactate and pyruvate and decreased levels of glucose, citrate, formate, acetate, several amino acids (alanine, glutamine, histidine, tyrosine, valine), and methanol, could be detected. These changes were found to be present at initial disease stages and could be related to known cancer biochemical hallmarks, such as enhanced glycolysis, glutaminolysis, and gluconeogenesis, together with suppressed Krebs cycle and reduced lipid catabolism, thus supporting the hypothesis of a systemic metabolic signature for lung cancer. Despite the possible confounding influence of age, smoking habits, and other uncontrolled factors, these results indicate that NMR-based metabonomics of blood plasma can be useful as a screening tool to identify suspicious cases for subsequent, more specific radiological tests, thus contributing to improved disease management.ERDF - Competitive Factors Thematic Operational ProgrammeFCT/PTDC/ QUI/68017/2006FCOMP-01-0124-FEDER-007439SFRH/BD/ 63430/2009National UNESCO Committee - L'Oréal Medals of Honor for Women in Science 200Portuguese National NMR Network - RNRM

The health of women and girls determines the health and well-being of our modern world: A White Paper From the International Council on Women's Health Issues

The International Council on Women's Health Issues (ICOWHI) is an international nonprofit association dedicated to the goal of promoting health, health care, and well-being of women and girls throughout the world through participation, empowerment, advocacy, education, and research. We are a multidisciplinary network of women's health providers, planners, and advocates from all over the globe. We constitute an international professional and lay network of those committed to improving women and girl's health and quality of life. This document provides a description of our organization mission, vision, and commitment to improving the health and well-being of women and girls globally

Interpreting ambiguous ‘trace’ results in Schistosoma mansoni CCA Tests: Estimating sensitivity and specificity of ambiguous results with no gold standard

Background The development of new diagnostics is an important tool in the fight against disease. Latent Class Analysis (LCA) is used to estimate the sensitivity and specificity of tests in the absence of a gold standard. The main field diagnostic for Schistosoma mansoni infection, Kato-Katz (KK), is not very sensitive at low infection intensities. A point-of-care circulating cathodic antigen (CCA) test has been shown to be more sensitive than KK. However, CCA can return an ambiguous ‘trace’ result between ‘positive’ and ‘negative’, and much debate has focused on interpretation of traces results. Methodology/Principle findings We show how LCA can be extended to include ambiguous trace results and analyse S. mansoni studies from both Côte d’Ivoire (CdI) and Uganda. We compare the diagnostic performance of KK and CCA and the observed results by each test to the estimated infection prevalence in the population. Prevalence by KK was higher in CdI (13.4%) than in Uganda (6.1%), but prevalence by CCA was similar between countries, both when trace was assumed to be negative (CCAtn: 11.7% in CdI and 9.7% in Uganda) and positive (CCAtp: 20.1% in CdI and 22.5% in Uganda). The estimated sensitivity of CCA was more consistent between countries than the estimated sensitivity of KK, and estimated infection prevalence did not significantly differ between CdI (20.5%) and Uganda (19.1%). The prevalence by CCA with trace as positive did not differ significantly from estimates of infection prevalence in either country, whereas both KK and CCA with trace as negative significantly underestimated infection prevalence in both countries. Conclusions Incorporation of ambiguous results into an LCA enables the effect of different treatment thresholds to be directly assessed and is applicable in many fields. Our results showed that CCA with trace as positive most accurately estimated infection prevalence

Elastic and inelastic light scattering from single bacterial spores in an optical trap allows the monitoring of spore germination dynamics

Raman scattering spectroscopy and elastic light scattering intensity (ESLI) were used to simultaneously measure levels of Ca-dipicolinic acid (CaDPA) and changes in spore morphology and refractive index during germination of individual B. subtilis spores with and without the two redundant enzymes (CLEs), CwlJ and SleB, that degrade sporesâ peptidoglycan cortex. Conclusions from these measurements include: 1) CaDPA release from individual wild-type germinating spores was biphasic; in a first heterogeneous slow phase, Tlag, CaDPA levels decreased â ¼15% and in the second phase ending at Trelease, remaining CaDPA was released rapidly; 2) in L-alanine germination of wild-type spores and spores lacking SleB: a) the ESLI rose â ¼2-fold shortly before Tlag at T1; b) following Tlag, the ESLI again rose â ¼2-fold at T2 when CaDPA levels had decreased â ¼50%; and c) the ESLI reached its maximum value at â ¼Trelease and then decreased; 3) in CaDPA germination of wild-type spores: a) Tlag increased and the first increase in ESLI occurred well before Tlag, consistent with different pathways for CaDPA and L-alanine germination; b) at Trelease the ESLI again reached its maximum value; 4) in L-alanine germination of spores lacking both CLEs and unable to degrade their cortex, the time Î Trelease (Treleaseâ Tlag) for excretion of â ¥75% of CaDPA was â ¼15-fold higher than that for wild-type or sleB spores; and 5) spores lacking only CwlJ exhibited a similar, but not identical ESLI pattern during L-alanine germination to that seen with cwlJ sleB spores, and the high value for Î Trelease. Originally published Analytical Chemistry, Vol. 81, No. 10, May 200

Search for the standard model Higgs boson in the H to ZZ to 2l 2nu channel in pp collisions at sqrt(s) = 7 TeV

A search for the standard model Higgs boson in the H to ZZ to 2l 2nu decay channel, where l = e or mu, in pp collisions at a center-of-mass energy of 7 TeV is presented. The data were collected at the LHC, with the CMS detector, and correspond to an integrated luminosity of 4.6 inverse femtobarns. No significant excess is observed above the background expectation, and upper limits are set on the Higgs boson production cross section. The presence of the standard model Higgs boson with a mass in the 270-440 GeV range is excluded at 95% confidence level.Comment: Submitted to JHE