Verification Period Research Articles

May–July precipitation reconstruction from oak tree‐rings for Bohemia (Czech Republic) since AD 1040

ABSTRACTThis contribution presents a near‐millennium‐long reconstruction of May–July (MJJ) precipitation for Bohemia, the western part of the recent Czech Republic. A well‐replicated chronology of oak (Quercus spp.) tree‐ring width (TRW) measurements covering the 1040–2013 period was employed as a high‐resolution hydroclimatic proxy. Standardized TRW indices were calibrated to selected grid points from the CRU precipitation database, covering the geographical distribution of the oak data used. The oak TRW chronology explains 34% of MJJ precipitation variability during the 1901–1980 period used for calibration. Although the relationship between oak TRW and target data was relatively stable for this period, the coherence drops significantly beyond it. However, two independent verification periods reveal highly positive reduction of error (RE) and coefficient of efficiency (CE) statistics. Less formal verification based on direct comparison with 14 European proxy‐based reconstructions further suggests relatively good agreement in the temporal occurrence of above/below mean late spring–early summer precipitation totals, especially in the 16th–17th centuries. The new MJJ precipitation reconstruction is restricted to inter‐annual and inter‐decadal variability, which is in line with our understanding of natural precipitation variability. Reconstruction reveals two long periods of low precipitation variability, in the 13th–14th centuries and 1630s–1850s. It also demonstrates that precipitation anomalies of larger amplitude and longer duration occurred in the earlier part of the last millennium than those found in the instrumental period. Negative trends in soil moisture content and gradual changes in annual precipitation distribution leading to higher extremity of precipitation regime may be responsible for the lower sensitivity of oaks to precipitation after the 1980s. The new reconstruction does not indicate any exceptional recent decline in MJJ precipitation.

Multi-Colour Hues of the Universe Observed with AstroSat

India's space astronomy observatory AstroSat was launched on 28 September 2015, carrying instruments to observe cosmic sources over a large spectral band, from optical/UV to hard X-rays. The mission, with all its payloads, has been operating successfully since its launch. After an initial period of performance verification and calibration, the satellite is now in full science operation. This article gives a brief introduction about the capabilities of the mission and presents some of the early science results.

Research on the response of the water sources to the climatic change in Shiyang River Basin

The influence of the future climate change to the water resource will directly pose some impact on the watershed management planning and administrative strategies of Shiyang River Basin. With the purpose of exploring the influence of climate change to the runoff, this paper set Shiyang River as the study area and then established a SWAT basin hydrological model based on the data such as DEM, land use, soil, climate hydrology and so on. Besides, algorithm of SUFI2 embedded in SWAT-CUP software is adopted. The conclusion shows that SWAT Model can simulate the runoff process of Nanying River well. During the period of model verification and simulation, the runoff Nash-Sutcliffe efficient coefficient of the verification and simulation is 0.76 and 0.72 separately. The relative error between the simulation and actual measurement and the model efficient coefficient are both within the scope of acceptance, which means that the SWAT hydrological model can be properly applied into the runoff simulation of Shiyang River Basin. Meantime, analysis on the response of the water resources to the climate change in Shiyang River Basin indicates that the impact of climate change on runoff is remarkable under different climate change situations and the annual runoff will be greatly decreased as the precipitation falls and the temperature rises. Influence of precipitation to annual runoff is greater than that of temperature. Annual runoff differs obviously under different climate change situations. All in all, this paper tries to provide some technical assistance for the water sources development and utilization assessment and optimal configuration.

Lymphatic filariasis patient identification in a large urban area of Tanzania: An application of a community-led mHealth system.

BackgroundLymphatic filariasis (LF) is best known for the disabling and disfiguring clinical conditions that infected patients can develop; providing care for these individuals is a major goal of the Global Programme to Eliminate LF. Methods of locating these patients, knowing their true number and thus providing care for them, remains a challenge for national medical systems, particularly when the endemic zone is a large urban area.Methodology/Principle findingsA health community-led door-to-door survey approach using the SMS reporting tool MeasureSMS-Morbidity was used to rapidly collate and monitor data on LF patients in real-time (location, sex, age, clinical condition) in Dar es Salaam, Tanzania. Each stage of the phased study carried out in the three urban districts of city consisted of a training period, a patient identification and reporting period, and a data verification period, with refinements to the system being made after each phase. A total of 6889 patients were reported (133.6 per 100,000 population), of which 4169 were reported to have hydrocoele (80.9 per 100,000), 2251 lymphoedema-elephantiasis (LE) (43.7 per 100,000) and 469 with both conditions (9.1 per 100,000). Kinondoni had the highest number of reported patients in absolute terms (2846, 138.9 per 100,000), followed by Temeke (2550, 157.3 per 100,000) and Ilala (1493, 100.5 per 100,000). The number of hydrocoele patients was almost twice that of LE in all three districts. Severe LE patients accounted for approximately a quarter (26.9%) of those reported, with the number of acute attacks increasing with reported LE severity (1.34 in mild cases, 1.78 in moderate cases, 2.52 in severe). Verification checks supported these findings.Conclusions/SignificanceThis system of identifying, recording and mapping patients affected by LF greatly assists in planning, locating and prioritising, as well as initiating, appropriate morbidity management and disability prevention (MMDP) activities. The approach is a feasible framework that could be used in other large urban environments in the LF endemic areas.

Statistical Downscaling of a High-Resolution Precipitation Reanalysis Using the Analog Ensemble Method

AbstractThis study explores the first application of an analog-based method to downscale precipitation estimates from a regional reanalysis. The utilized analog ensemble (AnEn) approach defines a metric with which a set of analogs (i.e., the ensemble) can be sampled from the observations in the training period. From the determined AnEn estimates, the uncertainty of the generated precipitation time series also can easily be assessed. The study investigates tuning parameters of AnEn, such as the choice of predictors or the ensemble size, to optimize the performance. The approach is implemented and tuned on the basis of a set of over 700 rain gauges with 6-hourly measurements for Germany and a 6.2-km regional reanalysis for Europe, which provides the predictors. The obtained AnEn estimates are evaluated against the observations over a 4-yr verification period. With respect to deterministic quality, the results show that AnEn is able to outperform the reanalysis itself depending on location and precipitation intensity. Further, AnEn produces superior results in probabilistic measures against a random-ensemble approach as well as a logistic regression. As a proof of concept, the described implementation allows for the estimation of synthetic probabilistic observation time series for periods for which measurements are not available.

Polymyalgia rheumatica: clinical features and diagnostics

Current data on epidemiology, pathomorphology, clinical manifestations and diagnosis of polymyalgia rheumatica is presented. Polymyalgia rheumatica occurs only in persons over 50 years of age. The etiological factors of the disease remain unknown. The pathomorphology of the disease is characterized by the absence of polyorganity and morphological changes in the study of biopsies of diseased muscles, inflammation of predominantly extraarticular synovial structures. The pain in the muscles has a constant, usually aching character, sharply increased during movement and persists at night. The intensity of pain depends on the activity of the disease. The use of non-steroidal anti-inflammatory drugs has no significant effect on the intensity of myalgia. Often, a few weeks after the onset of the disease, seronegative arthritis appears. Synovitis is characterized by a benign course, absence of erosive changes in the joint and joint deformities. Symptoms of the disease grow gradually, reaching a maximum severity within a month. Characteristic is the appearance of anorexia and depression, weight loss, it is possible to attach subfebrile or febrile fever. In some patients there are signs of inflammation of the vessels in the form of subclinical, weakly expressed vasculitis or giant cell arteritis with lesions of the extracranial branches of the carotid arteries and signs of vascular insufficiency in the blood supplying organs. Specific laboratory criteria for polymyalgia rheumatica do not exist. Diagnosis of the disease is based on the analysis of a number of clinical, laboratory and instrumental features, united by experts of the European League against rheumatism and the American College of Rheumatology in the form of diagnostic criteria for rheumatic polymyalgia. The disease has a polymorphic clinical picture and similarity of symptoms with inflammatory diseases of the joints, as well as with myopathies against a background of various pathologies of internal organs and systems. Despite the presence of diagnostic criteria, the diagnosis is established after the exclusion of diseases with similar clinical manifestations. Recognition of polymyalgia rheumaticа is often associated with a large volume of research, which makes the disease difficult in a differential diagnostic plan and contributes to an increase in the duration of the verification period of the diagnosis.

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

Abstract. In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm−3 for the assimilation period and 0.05 cm3 cm−3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm−3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.

Simulation analysis of jiujiang river basin runoff based on swat model

This paper discussed the feasibility of application the Soil and Water Assessment Tools (SWAT) model in the Yangtze River Basin of Jiujiang. Two statistical indicators were used for model evaluation; i) coefficient of determination (R2) and ii) Nash-Sutcliffe efficiency index (Ens). The software of SWAT-CUP was used to calibrate and validate the model based on the measured data from 2000 to 2015 in JiuJiang hydrological station, which could assist in determining the applicability of the model to the basin. Results indicated R2 being 0.82 and 0.76; Ens being 0.78 and 0.72 in terms of the calibration and verification periods, both of which meeting the requirements, It suggested that the SWAT model could be able to well simulate the Yangtze River Basin of Jiujiang watershed.

금연 중 운동 유무에 따른 코티닌 배출 효과 비교

The objective of this study is to verify whether exercising of smokers provides a valid effect on emission of cotinine in urine and to suggest more effective way of quitting smoking through the exercise while stopping smoking. This study has been conducted with experiment for 6 weeks by classifying 21 male smokers into a control group (10 subjects) and experiment group (11 subjects) who were aged at 35 or above and decided to quit smoking. With control group, test has been conducted as to whether they smoked with urine nicotine kit for 2 times a week. With experiment group, subjects were asked to participate in aerobic exercise in the 65~70%HRmax for 50 minutes a time for three times per week while testing whether to smoke in the same conditions with the control group. Test on urine cotinine has been conducted for three times before the exercise and 3 and 6 weeks after the exercise, respectively Using SPSS/PC+ Win22.0 Version, mean and standard deviation in each item have been calculated. In order identify the difference of changes in urine cotinine depending on each group and measuring period, repeated measures ANOVA was used for the analysis. Significance level of p.05 in the verification process. According to the results of analysis, there was a difference in intra-object verification period (F=207.273, p.001). It also turned out that there was a difference in groups in verification process between objects (F=1.116, p.05). Therefore, aerobic exercise turned out to positively influence on the emission of cotinine through urine among smokers while stopping smoking.

КЛІНІЧНІ ФОРМИ ХОЛЕДОХОЛІТІАЗУ

Недивлячись на досягнення сучасних інноваційних технологій, верифікація холедохолітіазу на доопераційному періоді дуже часто не діагностується, що приводить до розвитку резидуального холедохолітіазу і повторних операційних втручаньМета дослідження – вивчити клінічні форми холедохолітіазу та їх діагностичні критерії.Матеріали і методи. Проведено порівняння клінічних форм холедохолітіазу та чутливості різних методів інструментальних досліджень (ультразвукове дослідження (УЗД), фіброезофагогастродуоденоскопію (ФЕГДС), ендоскопічну ретроградну холангіопанкреатографію (ЕРХПГ), магніторезонансну холангіопанкреатографію (МРХПГ)) при діагностичному виборі на основі ретроспективного аналізу лікування 177 пацієнтів.Результати досліджень та їх обговорення. Статистичний аналіз діагностичної цінності симптомів дозволив нам виділити 4 клінічні форми холедохолітіазу з високою специфічністю та чутливістю клінічних симптомів при жовтяничній формі й недостатньою інформативністю при атиповій і безжовтяничній (асимптомній) формах. Ретроградна холангіопанкреатографія, магніторезонансна холангіопанкреатографія з високим ступенем достовірності дозволяє діагностувати конкременти в загальній жовчній протоці при атиповій і безжовтяничній формах холедохолітіазу.

Use of the EntericBio Gastro Panel II in a diagnostic microbiology laboratory: challenges and opportunities

We sought to verify the performance of the EntericBio real-time Gastro Panel 2 (GP2; Serosep, Ireland) assay targeting Salmonella, Shigella, Campylobacter, verotoxin producing E.coli (VTEC), Giardia, and Cryptosporidium in a high-throughput diagnostic laboratory. Following a technical verification period where 237 faecal samples were tested in parallel, guided culture and discrepancy analysis were performed. A total of 13,223 faecal samples were screened by the GP2 assay. During technical verification, sensitivity, specificity, negative and positive predictive value of the GP2 assay compared with conventional methods were 100% (83-100%), 98% (96.7-98.2%), 100% (98.5-100%), and 82.6% (69-83%), respectively. With guided culture, specificity (99.4-100%) and positive predictive value (15-100%) varied by target. Challenges with interpretation of results, particularly for VTEC, Shigella and Salmonella, are discussed.

Precipitation Identification with Bispectral Satellite Information Using Deep Learning Approaches

Abstract In the development of a satellite-based precipitation product, two important aspects are sufficient precipitation information in the satellite-input data and proper methodologies, which are used to extract such information and connect it to precipitation estimates. In this study, the effectiveness of the state-of-the-art deep learning (DL) approaches to extract useful features from bispectral satellite information, infrared (IR), and water vapor (WV) channels, and to produce rain/no-rain (R/NR) detection is explored. To verify the methodologies, two models are designed and evaluated: the first model, referred to as the DL-IR only method, applies deep learning approaches to the IR data only; the second model, referred to as the DL-IR+WV method, incorporates WV data to further improve the precipitation identification performance. The radar stage IV data are the reference data used as ground observation. The operational product, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Cloud Classification System (PERSIANN-CCS), serves as a baseline model with which to compare the performances. The experiments show significant improvement for both models in R/NR detection. The overall performance gains in the critical success index (CSI) are 21.60% and 43.66% over the verification periods for the DL-IR only model and the DL-IR+WV model compared to PERSIANN-CCS, respectively. In particular, the performance gains in CSI are as high as 46.51% and 94.57% for the models for the winter season. Moreover, specific case studies show that the deep learning techniques and the WV channel information effectively help recover a large number of missing precipitation pixels under warm clouds while reducing false alarms under cold clouds.

Predicting urban storm water-logging for Chittagong city in Bangladesh

In recent years, rainfall induced ‘urban storm water-logging’ (USWL) events are experiencing in Chittagong city like other urbanized parts of Bangladesh. To mitigate this there is an urgent need to predict the USWL beforehand and a numerical model could help. Thus, this paper aimed to use a hydrological model i.e. HEC-HMS through field survey during 2013–2014 and a questionnaire survey. With the support of secondary data source viz. daily newspaper, intensive questionnaire survey and field visits identified 13 most vulnerable USWL locations and based on these a USWL depth–duration–frequency curve was developed. This showed during water logging (i.e. May–July), the depth of logged water rises 0.3–1.27 m causing adjacent dwellers sufferings upto 13 times per year and the inundation period is up to 48 h. Using these, HEC-HMS model was setup and the correlation obtained with the field measurement as R2 values 0.83 and 0.77 during calibration and verification period respectively. Once a real time hydrological dataset is available, the validated model supposed to provide useful information in the decision support system.

Assessment of the Flow at the Chatara on Koshi River Basin using Semi Distributed Model

Hydrological modeling is a physical phenomenon to incorporate rainfall-runoff process in watershed area at particular point and analysis the behaviors of the flow through outlet. There are various types of models such as black box, conceptual and physical based model depends upon the availability of required data, parameters and description of the physical process. Semi distributed model is a conceptual and physical based model which has been developed to bridge the gap between the lumped and distributed model. It have more advantages than other models with respect to time of calculation, less number of parameters, comparatively low calibration needs and have high efficiency of model. The model performance may be achieved upon the qualitative and quantitative available rainfall data, land use data and size of the watershed. In this study, Koshi river basin was taken for the study area. Kinematic wave method was used for overland routing and Muskingum conge method was applied for channel routing to describe the discharge on Saptakoshi river and peak flow attenuation and dispersion observed in the direct runoff hydrograph. From this study result, Annual runoff, Peak flow and time of peak at the outlet are similar to the observed flow in calibration and verification period using trapezoidal channel. The nash efficiency obtained from the semi distributed model with kinematic wave method is more than 90%in verification periods and nearly 90% in calibration periods Hence Hydrological modeling is a powerful technique in the planning and development of integrated approach for management of water resources.Journal of the Institute of Engineering, 2016, 12(1): 184-198

Prediction of summer rainfall in Pakistan from global sea‐surface temperature and sea‐level pressure

Agriculture contributes around a quarter to Pakistan's economy and is closely linked with the variability of monsoon rainfall. The prediction of monsoon rains with sufficient lead time has immense importance for the planning and management of water resources and agriculture. In this study, Multiple Linear Regression (MLR) and Principal Component Regression (PCR) methods are employed to predict monsoon rainfall, and their performances are compared for June–September (JJAS) for the period 1961–2014 over the monsoon region of Pakistan. Rainfall data of Meteorological stations are used as the predictand. In the MLR method, predictors are carried out from sea level pressure (SLP) and sea surface temperature (SST) of the National Centers for Environmental Prediction (NCEP) reanalysis datasets. The PCR method first calculates principal components (PCs) from SLP and SST data, and these PCs are then combined with the regression technique and used as predictors. The performance of both models is tested using statistical measures such as root mean square error (RMSE), mean absolute error (MAE), bias and the correlation coefficient to evaluate the skill of the forecast. The agreement between actual and predicted rainfall data provides evidence for reasonably accurate predictions from both methods. The MLR and PCR models explained 84.6 and 92.2% of the variation of data, and the multiple correlation coefficients are 0.92 and 0.96 respectively. The correlation coefficient for the verification period (2005–2014) is 0.73 for MLR and 0.89 for PCR. The values of mean bias, MAE and RMSE are −5.5, 20.0 and 25.1mm for MLR, and −0.42, 16.2 and 16.6mm for PCR, respectively. The results indicate that the PCR model forecast is slightly better than that of the MLR model.

Testing the stability of transfer functions

In dendroclimatology, testing the stability of transfer functions using cross-calibration verification (CCV) statistics is a common procedure. However, the frequently used statistics reduction of error (RE) and coefficient of efficiency (CE) merely assess the skill of reconstruction for the validation period, which does not necessarily reflect possibly instable regression parameters. Furthermore, the frequently used rigorous threshold of zero which sharply distinguishes between valid and invalid transfer functions is prone to an underestimation of instability. To overcome these drawbacks, we here introduce a new approach – the Bootstrapped Transfer Function Stability test (BTFS). BTFS relies on bootstrapped estimates of the change of model parameters (intercept, slope, and r2) between calibration and verification period as well as the bootstrapped significance of corresponding models. A comparison of BTFS, CCV and a bootstrapped CCV approach (BCCV) applied to 42,000 pseudo-proxy datasets with known properties revealed that BTFS responded more sensitively to instability compared to CCV and BCCV. BTFS performance was significantly affected by sample size (length of calibration period) and noise (explained variance between predictor and predictand). Nevertheless, BTFS performed superior with respect to the detection of instable transfer functions in comparison to CCV.

Assessment of Ilam Reservoir Eutrophication Response in Controlling Water Inflow

In this research, a 2D laterally averaged model of hydrodynamics and water quality, CE-QUAL-W2, was applied to simulate water quality parameters in the Ilam reservoir. The water quality of Ilam reservoir was obtained between mesotrophic and eutrophic based on the measured data including chlorophyll a, total phosphorus and subsurface oxygen saturation. The CE-QUAL-W2 model was calibrated and verified by using the data of the year 2009 and 2010, respectively. Nutrients, chlorophyll a and dissolved oxygen were the water quality constituents simulated by the CE-QUAL-W2 model. The comparison of the simulated water surface elevation with the measurement records indicated that the flow was fully balanced in the numerical model. There was a good agreement between the simulated and measured results of the hydrodynamics and water quality constituents in the calibration and verification periods. Some scenarios have been made base on decreasing in water quantity and nutrient inputs of reservoir inflows. The results have shown that the water quality improvements of the Ilam reservoir will not be achieved by reducing a portion of the reservoir inflow. The retention time of water in reservoir would be changed by decreasing of inflows and it made of the negative effects on the chlorophyll-a concentration by reduction of nutrient inputs and keeping constant of discharge inflow to reservoir, the concentration of total phosphorus would be significantly changed and also the concentration of chlorophyll-a was constant approximately. Thus, the effects of control in nutrient inputs are much more than control in discharge inflows in the Ilam reservoir.

Cosmology from large-scale galaxy clustering and galaxy–galaxy lensing with Dark Energy Survey Science Verification data

We present cosmological constraints from the Dark Energy Survey (DES) using a combined analysis of angular clustering of red galaxies and their cross-correlation with weak gravitational lensing of background galaxies. We use a 139 square degree contiguous patch of DES data from the Science Verification (SV) period of observations. Using large scale measurements, we constrain the matter density of the Universe as Omega_m = 0.31 +/- 0.09 and the clustering amplitude of the matter power spectrum as sigma_8 = 0.74 +/- 0.13 after marginalizing over seven nuisance parameters and three additional cosmological parameters. This translates into S_8 = sigma_8(Omega_m/0.3)^{0.16} = 0.74 +/- 0.12 for our fiducial lens redshift bin at 0.35 <z< 0.5, while S_8 = 0.78 +/- 0.09 using two bins over the range 0.2 <z< 0.5. We study the robustness of the results under changes in the data vectors, modelling and systematics treatment, including photometric redshift and shear calibration uncertainties, and find consistency in the derived cosmological parameters. We show that our results are consistent with previous cosmological analyses from DES and other data sets and conclude with a joint analysis of DES angular clustering and galaxy-galaxy lensing with Planck CMB data, Baryon Accoustic Oscillations and Supernova type Ia measurements.

Comprehensive Evaluation and Implementation of Improvement Actions in Butcher Shops.

Foodborne pathogens can cause acute and chronic diseases and produce a wide range of symptoms. Since the consumption of ground beef is a risk factor for infections with some bacterial pathogens, we performed a comprehensive evaluation of butcher shops, implemented improvement actions for both butcher shops and consumers, and verified the impact of those actions implemented. A comprehensive evaluation was made and risk was quantified on a 1–100 scale as high-risk (1–40), moderate-risk (41–70) or low-risk (71–100). A total of 172 raw ground beef and 672 environmental samples were collected from 86 butcher shops during the evaluation (2010–2011) and verification (2013) stages of the study. Ground beef samples were analyzed for mesophilic aerobic organisms, Escherichia coli and coagulase-positive Staphylococcus aureus enumeration. Salmonella spp., E. coli O157:H7, non-O157 Shiga toxin-producing E. coli (STEC), and Listeria monocytogenes were detected and isolated from all samples. Risk quantification resulted in 43 (50.0%) high-risk, 34 (39.5%) moderate-risk, and nine (10.5%) low-risk butcher shops. Training sessions for 498 handlers and 4,506 consumers were held. Re-evaluation by risk quantification and microbiological analyses resulted in 19 (22.1%) high-risk, 42 (48.8%) moderate-risk and 25 (29.1%) low-risk butcher shops. The count of indicator microorganisms decreased with respect to the 2010–2011 period. After the implementation of improvement actions, the presence of L. monocytogenes, E. coli O157:H7 and stx genes in ground beef decreased. Salmonella spp. was isolated from 10 (11.6%) ground beef samples, without detecting statistically significant differences between both study periods (evaluation and verification). The percentage of pathogens in environmental samples was reduced in the verification period (Salmonella spp., 1.5%; L. monocytogenes, 10.7%; E. coli O157:H7, 0.6%; non-O157 STEC, 6.8%). Risk quantification was useful to identify those relevant facts in butcher shops. The reduction of contamination in ground beef and the environment was possible after training handlers based on the problems identified in their own butcher shops. Our results confirm the feasibility of implementing a comprehensive risk management program in butcher shops, and the importance of information campaigns targeting consumers. Further collaborative efforts would be necessary to improve foodstuffs safety at retail level and at home.

Comparing Dark Energy Survey andHST–CLASH observations of the galaxy cluster RXC J2248.7−4431: implications for stellar mass versus dark matter

We derive the stellar mass fraction in the galaxy cluster RXC J2248.7-4431 observed with the Dark Energy Survey (DES) during the Science Verification period. We compare the stellar mass results from DES (five filters) with those from the Hubble Space Telescope Cluster Lensing And Supernova Survey (CLASH; 17 filters). When the cluster spectroscopic redshift is assumed, we show that stellar masses from DES can be estimated within 25% of CLASH values. We compute the stellar mass contribution coming from red and blue galaxies, and study the relation between stellar mass and the underlying dark matter using weak lensing studies with DES and CLASH. An analysis of the radial profiles of the DES total and stellar mass yields a stellar-to-total fraction of f*=(6.8+-1.7)x10^-3 within a radius of r_200c~2 Mpc. Our analysis also includes a comparison of photometric redshifts and star/galaxy separation efficiency for both data sets. We conclude that space-based small field imaging can be used to calibrate the galaxy properties in DES for the much wider field of view. The technique developed to derive the stellar mass fraction in galaxy clusters can be applied to the ~100 000 clusters that will be observed within this survey and yield important information about galaxy evolution.