bluuebunny/crossref_metadata_2025 huggingface dataset:
Is missing geographic positioning system data in accelerometry studies a problem, and is imputation the solution?
Authors: Meseck Kristin , Jankowska Marta M. , Schipperijn Jasper , Natarajan Loki , Godbole Suneeta , Carlson Jordan , Takemoto Michelle , Crist Katie , Kerr Jacqueline
Published: June 2016

The main purpose of the present study was to assess the impact of global positioning system (GPS) signal lapse on physical activity analyses, discover any existing associations between missing GPS data and environmental and demographics attributes, and to determine whether imputation is an accurate and viable method for correcting GPS data loss. Accelerometer and GPS data of 782 participants from 8 studies were pooled to represent a range of lifestyles and interactions with the built environment. Periods of GPS signal lapse were identified and extracted. Generalised linear mixed models were run with the number of lapses and the length of lapses as outcomes. The signal lapses were imputed using a simple ruleset, and imputation was validated against person-worn camera imagery. A final generalised linear mixed model was used to identify the difference between the amount of GPS minutes pre- and post-imputation for the activity categories of sedentary, light, and moderate-to-vigorous physical activity. Over 17% of the dataset was comprised of GPS data lapses. No strong associations were found between increasing lapse length and number of lapses and the demographic and built environment variables. A significant difference was found between the pre- and postimputation minutes for each activity category. No demographic or environmental bias was found for length or number of lapses, but imputation of GPS data may make a significant difference for inclusion of physical activity data that occurred during a lapse. Imputing GPS data lapses is a viable technique for returning spatial context to accelerometer data and improving the completeness of the dataset.
Comparison of single- and multi-scale models for the prediction of the Culicoides biting midge distribution in Germany
Authors: Lühken Renke , Gethmann Jörn Martin , Kranz Petra , Steffenhagen Pia , Staubach Christoph , Conraths Franz J. , Kiel Ellen
Published: June 2016

This study analysed Culicoides presence-absence data from 46 sampling sites in Germany, where monitoring was carried out from April 2007 until May 2008. Culicoides presence-absence data were analysed in relation to land cover data, in order to study whether the prevalence of biting midges is correlated to land cover data with respect to the trapping sites. We differentiated eight scales, i.e. buffer zones with radii of 0.5, 1, 2, 3, 4, 5, 7.5 and 10 km, around each site, and chose several land cover variables. For each species, we built eight single-scale models (i.e. predictor variables from one of the eight scales for each model) based on averaged, generalised linear models and two multiscale models (i.e. predictor variables from all of the eight scales) based on averaged, generalised linear models and generalised linear models with random forest variable selection. There were no significant differences between performance indicators of models built with land cover data from different buffer zones around the trapping sites. However, the overall performance of multi-scale models was higher than the alternatives. Furthermore, these models mostly achieved the best performance for the different species using the index area under the receiver operating characteristic curve. However, as also presented in this study, the relevance of the different variables could significantly differ between various scales, including the number of species affected and the positive or negative direction. This is an even more severe problem if multi-scale models are concerned, in which one model can have the same variable at different scales but with different directions, i.e. negative and positive direction of the same variable at different scales. However, multi-scale modelling is a promising approach to model the distribution of Culicoides species, accounting much more for the ecology of biting midges, which uses different resources (breeding sites, hosts, etc.) at different scales.
Climate change and species distribution: possible scenarios for thermophilic ticks in Romania
Authors: Domșa Cristian , Sándor Attila D. , Mihalca Andrei D.
Published: June 2016

Several zoonotic tick-borne diseases are emerging in Europe due to various factors, including changes of the cultural landscape, increasing human populations, variation of social habits and climate change. We have modelled the potential range changes for two thermophilic tick species (Hyalomma marginatum and Rhipicephalus annulatus) by use of MaxEnt® and 15 climatic predictors, taking into account the aptitude for future climatic change in Romania. Current models predict increased temperatures, both in the short term (up to 2050) and in the long term (up to 2070), together with possible changes also of the other climatic factors (e.g. precipitation), and may lead to higher zoonotic risks associated with an expansion of the range of the target species. Three different models were constructed (the present, 2050 and 2070) for four representative concentration pathways (RCPs) of greenhouse gas scenarios: RCP2.6, RCP4.5, RCP6, and RCP8.5. The most dramatic scenario (RCP8.5) produced the highest increase in the probable distribution range for both species. In concordance with similar continental-wide studies, both tick species displayed a shift of distribution towards previously cooler areas of Romania. In most scenarios, this would lead to wider ranges; from 9.7 to 43.1% for H. marginatum, and from 53.4 to 205.2% for R annulatus. Although the developed models demonstrate a good predictive power, the issue of species ecology should also be considered.
Downtown Nellmapius: The Vacant Plot Patient
Authors: Maritz Patricia
Published: June 2016

No abstract available.
Poems
Authors: Ullyatt Tony
Published: June 2016

No abstract available.
High Prevalence of Liver Fibrosis in Patients with Human Immunodeficiency Virus Monoinfection and Human Immunodeficiency Virus Hepatitis-B Co-infection as Assessed by Shear Wave Elastography: Study at a Teaching Hospital in Kenya
Authors: Gitau Samuel Nguku , Vinayak Sudhir , Silaba Micah , Adam Rodney , Shah Reena
Published: June 2016

Objectives:

The aim of this study was to determine the prevalence of liver fibrosis in patients with human immunodeficiency virus (HIV) monoinfection versus those with HIV hepatitis-B virus (HBV) co-infection as assessed with shear wave elastography (SWE) in a tertiary sub-Saharan Africa hospital.

Materials and Methods:

A total of 105 consecutive patients, 70 with HIV monoinfection and 35 with HIV-HBV co-infection, had liver elastography obtained using SWE to assess for the presence of liver fibrosis the cutoff of which was 5.6 kPa. Assessment of aspartate aminotransferase-to-platelet ratio index (APRI) score (a noninvasive serum biomarker of liver fibrosis) in these patients was also done.

Results:

The prevalence of liver fibrosis was significantly higher (P< 0.0001) in patients with HIV-HBV co-infection, 25.7%, compared to those with HIV monoinfection, 7.1%. APRI score was greater in patients with HIV-HBV co-infection than those with HIV monoinfection. HIV co-infection with HBV accelerates progression to liver fibrosis. Association of a low cluster of differentiation 4 (CD-4) count with advanced fibrosis supports earlier starting of antiretroviral therapy to prevent rapid progression of liver disease in HIV-positive patients.

Conclusion:

In view of the high prevalence of liver fibrosis in patients with HIV-HBV co-infection, regular monitoring of the disease progression is recommended.
Differences regarding Branded HA in Italy, Part 2: Data from Clinical Studies on Knee, Hip, Shoulder, Ankle, Temporomandibular Joint, Vertebral Facets, and Carpometacarpal Joint
Authors: Migliore A. , Bizzi E. , De Lucia O. , Sedie A. Delle , Tropea S. , Bentivegna M. , Mahmoud A. , Foti C.
Published: June 2016

Objectives

The aim of the current study is to collect scientific data on all branded hyaluronic acid (HA) products in Italy that are in use for intra-articular (IA) injection in osteoarthritis (OA) compared with that reported in the leaflet.

Methods

An extensive literature research was performed for all articles reporting data on the IA use of HA in OA. Selected studies were taken into consideration only if they are related to products based on H As that are currently marketed in Italy with the specific joint indication for IA use in patients affected by OA.

Results

Sixty-two HA products are marketed in Italy: 30 products are indicated for the knee but only 8 were proved with some efficacy; 9 products were effective for the hip but only 6 had hip indication; 7 products proved to be effective for the shoulder but only 3 had the indication; 5 products proved effective for the ankle but only one had the indication; 6 products were effective for the temporomandibular joint but only 2 had the indication; only 2 proved effective for vertebral facet joints but only 1 had the indication; and 5 products proved effective for the carpometacarpal joint but only 2 had the indication.

Conclusions

There are only a few products with some evidences, while the majority of products remain without proof Clinicians and regulators should request postmarketing studies from pharmaceuticals to corroborate with that reported in the leaflet and to gather more data, allowing the clinicians to choose the adequate product for the patient.
Age-related Differences in White Matter Integrity in Healthy Human Brain: Evidence from Structural Mri and Diffusion Tensor Imaging
Authors: Rathee Rishu , Rallabandi V.P. Subramanyam , Roy Prasun K.
Published: June 2016

The aim is to investigate the relationship between microstructural white matter (WM) diffusivity indices and macrostructural WM volume (WMV) among healthy individuals (20–85 years). Whole-brain diffusion measures were calculated from diffusion tensor imaging using FMRIB software library while WMV was estimated through voxel-based morphometry, and voxel-based analysis was carried out using tract-based spatial statistics. Our results revealed that mean diffusivity, axial diffusivity, and radial diffusivity had shown good correlation with WMV but not for fractional anisotropy (FA). Voxel-wise tract-based spatial statistics analysis for FA showed a significant decrease in four regions for middle-aged group compared to young-aged group, in 22 regions for old-aged group compared to middle-aged group, and in 26 regions for old-aged group compared to young-aged group ( P < 0.05). We found significantly lower WMV, FA, and mean diffusivity values in females than males and inverted-U trend for FA in males. We conclude differential age- and gender-related changes for structural WMV and WM diffusion indices.
Characteristics and Risk Factors for Fatality in Patients with Dengue Hemorrhagic Fever, Taiwan, 2014
Authors: Wei Hsin-Yi , Shu Pei-Yun , Hung Min-Nan
Published: June 2016

An unprecedented dengue outbreak involving more than 15,000 infections, including 136 dengue hemorrhagic fever (DHF) cases and 20 fatalities, occurred in Taiwan in 2014. The median age of the DHF cases was 71 years (range: 4–92 years) and most of them (N = 100, 73.5%) had comorbidities, of which the majority were hypertension (56%) and diabetes mellitus (DM; 27%). Only approximately half of the DHF cases (59/136) were classified as severe dengue, based on the 2009 WHO-revised dengue classification. The fatality rate for this DHF outbreak was 14.7%. DM (odds ratio [OR] = 3.60, 95% confidence interval [CI] = 1.22–10.63) and presentation with severe plasma leakage (OR = 6.42, 95% CI = 1.76–23.63) were independent risk factors for fatality.
Costs Associated with Surgically Treated Cases of Abdominal Cystic Echinococcosis: A Single Center's Experience from 2008 to 2014, Pavia, Italy
Authors: Narra Roberta , Maestri Marcello , Budke Christine M. , Tamarozzi Francesca , Mariconti Mara , Nicoletti Giovanni J. , Rinaldi Francesca , Brunetti Enrico
Published: June 2016

Cystic echinococcosis (CE) is a globally distributed zoonosis caused by the Echinococcus granulosus sensu lato species complex. Four approaches are available for treatment of abdominal CE: surgery, percutaneous aspiration, chemotherapy with albendazole, and watch-and-wait. Allocation of patients to these different treatment options mainly depends on the stage of the cystic lesion. However, as available guidelines are not widely followed, surgery is often applied even without the correct indication outside referral centers. This is not only a disadvantage for the patient, but also a waste of money. In this study, we evaluated the cost of the surgical approach for abdominal CE by analyzing hospitalization costs for 14 patients admitted to the General Surgery Ward at the “San Matteo” Hospital Foundation in Pavia, Italy, from 2008 through 2014. We found that the total cost of a single hospitalization, including hospital stay, surgical intervention, personnel, drugs, and administrative costs ranged from €5,874 to 23,077 (median €11,033) per patient. Our findings confirm that surgery can be an expensive option. Therefore, surgical intervention should be limited to cyst types that do not benefit from nonsurgical therapies and appropriate case management can best be accomplished by using a cyst stage-specific approach.
Fennec dust forecast intercomparison over the Sahara in June 2011
Authors: Chaboureau Jean-Pierre , Flamant Cyrille , Dauhut Thibaut , Kocha Cécile , Lafore Jean-Philippe , Lavaysse Chistophe , Marnas Fabien , Mokhtari Mohamed , Pelon Jacques , Reinares Martínez Irene , Schepanski Kerstin , Tulet Pierre
Published: June 2016

Abstract. In the framework of the Fennec international programme, a field campaign was conducted in June 2011 over the western Sahara. It led to the first observational data set ever obtained that documents the dynamics, thermodynamics and composition of the Saharan atmospheric boundary layer (SABL) under the influence of the heat low. In support to the aircraft operation, four dust forecasts were run daily at low and high resolutions with convection-parameterizing and convection-permitting models, respectively. The unique airborne and ground-based data sets allowed the first ever intercomparison of dust forecasts over the western Sahara. At monthly scale, large aerosol optical depths (AODs) were forecast over the Sahara, a feature observed by satellite retrievals but with different magnitudes. The AOD intensity was correctly predicted by the high-resolution models, while it was underestimated by the low-resolution models. This was partly because of the generation of strong near-surface wind associated with thunderstorm-related density currents that could only be reproduced by models representing convection explicitly. Such models yield emissions mainly in the afternoon that dominate the total emission over the western fringes of the Adrar des Iforas and the Aïr Mountains in the high-resolution forecasts. Over the western Sahara, where the harmattan contributes up to 80 % of dust emission, all the models were successful in forecasting the deep well-mixed SABL. Some of them, however, missed the large near-surface dust concentration generated by density currents and low-level winds. This feature, observed repeatedly by the airborne lidar, was partly forecast by one high-resolution model only.
Incomplete sulfate aerosol neutralization despite excess ammonia in the eastern US: a possible role of organic aerosol
Authors: Silvern Rachel F. , Jacob Daniel J. , Kim Patrick S. , Marais Eloise A. , Turner Jay R.
Published: June 2016

Abstract. Acid-base neutralization of sulfate aerosol (S(VI) ≡ H2SO4(aq) + HSO4− + SO42−) by ammonia (NH3) has important implications for aerosol mass, hygroscopicity, and acidity. Surface network and aircraft observations across the eastern US show that sulfate aerosol is not fully neutralized even in the presence of excess ammonia, at odds with thermodynamic equilibrium models. The sulfate aerosol neutralization ratio (f = [NH4+]/2[S(VI)]) averages only 0.51 ± 0.11 mol mol−1 at sites in the Southeast and 0.78 ± 0.13 mol mol−1 in the Northeast in summer 2013, even though ammonia is in large excess as shown by the corresponding [NH4+]/2[S(VI)] ratio in wet deposition fluxes. There is in fact no site-to-site correlation between the two quantities; the aerosol neutralization ratio in the Southeast remains in a range 0.3–0.6 mol mol−1 even as the wet deposition neutralization ratio exceeds 3 mol mol−1. While the wet deposition neutralization ratio has increased by 4.6 % a−1 from 2003 to 2013 in the Southeast US, consistent with SO2 emission controls, the aerosol neutralization ratio has decreased by 1.0–3.2 % a−1. Thus the aerosol is becoming more acidic even as SO2 emissions decrease. One possible explanation is that sulfate particles are increasingly coated by organic material, retarding the uptake of ammonia. The ratio of organic aerosol (OA) to sulfate increases over the 2003–2013 period as sulfate decreases. We implement a kinetic mass transfer limitation for ammonia uptake to sulfate aerosols in the GEOS-Chem chemical transport model and find improved agreement with surface and aircraft observations of the aerosol neutralization ratio. If sulfate aerosol becomes more acidic as OA/sulfate ratios increase, then controlling SO2 emissions to decrease sulfate aerosol will not have the co-benefit of suppressing acid-catalyzed secondary organic aerosol (SOA) formation.
Growth of ice particle mass and projected area during riming
Authors: Erfani Ehsan , Mitchell David L.
Published: June 2016

Abstract. There is a long-standing challenge in cloud and climate models to simulate the process of ice particle riming realistically, partly due to the unrealistic parameterization of the growth of ice particle mass (m) and projected area (A) during riming. This study addresses this problem, utilizing ground-based measurements of m and ice particle maximum dimension (D) and also theory to formulate simple expressions describing the dependence of m and A on riming. It was observed that β in the m-D power law m = αDβ appears independent of riming before the formation of graupel, with α accounting for the ice particle mass increase due to riming. This semi-empirical approach accounts for the degree of riming and renders a gradual and smooth ice particle growth process from unrimed ice particles to graupel, and thus avoids discontinuities in m and A during accretional growth. The treatment for riming is explicit, and includes the parameterization of the ice crystal-cloud droplet collision efficiency (Ec) for hexagonal columns and plates using hydrodynamic theory. In particular, Ec for cloud droplet diameters less than 10 μm are estimated, and under some conditions observed in mixed phase clouds, these droplets can account for roughly half of the mass growth rate from riming. These physically-meaningful yet simple methods can be used in models to improve the riming process.
HONO measurement by differential photolysis
Authors: Reed Chris , Brumby Charlotte A. , Crilley Leigh R. , Kramer Louisa J. , Bloss William J. , Seakins Paul W. , Lee James D. , Carpenter Lucy J.
Published: June 2016

Abstract. Nitrous acid (HONO) has been quantitatively measured in situ by differential photolysis at 385 and 395 nm, and subsequent detection as nitric oxide (NO) by the chemiluminescence reaction with ozone (O3). The technique has been evaluated by Fourier transform infrared (FT-IR) spectroscopy to provide a direct HONO measurement in a simulation chamber and compared side by side with a long absorption path optical photometer (LOPAP) in the field. The NO–O3 chemiluminescence technique is robust, well characterized, and capable of sampling at low pressure, whilst solid-state converter technology allows for unattended in situ HONO measurements in combination with fast time resolution and response.
Temperature-mediated changes in microbial carbon use efficiency and 13C discrimination
Authors: Lehmeier Christoph A. , Ballantyne IV Ford , Min Kyungjin , Billings Sharon A.
Published: June 2016

Abstract. Understanding how carbon dioxide (CO2) flux from ecosystems feeds back to climate warming depends in part on our ability to quantify the efficiency with which microorganisms convert organic carbon (C) into either biomass or CO2. Quantifying ecosystem-level respiratory CO2 losses often also requires assumptions about stable C isotope fractionations associated with the microbial transformation of organic substrates. However, the diversity of organic substrates' δ13C and the challenges of measuring microbial C use efficiency (CUE) in their natural environment fundamentally limit our ability to project ecosystem C budgets in a warming climate. Here, we quantify the effect of temperature on C fluxes during metabolic transformations of cellobiose, a common microbial substrate, by a cosmopolitan microorganism growing at a constant rate. Biomass C specific respiration rate increased by 250 % between 13 and 26.5 °C, decreasing CUE from 77 to 56 %. Biomass C specific respiration rate was positively correlated with an increase in respiratory 13C discrimination from 4.4 to 6.7 ‰ across the same temperature range. This first demonstration of a direct link between temperature, microbial CUE, and associated isotope fluxes provides a critical step towards understanding δ13C of respired CO2 at multiple scales, and towards a framework for predicting future ecosystem C fluxes.
Carbon turnover in cell compartments and microbial groups in soil
Authors: Gunina Anna , Dippold Michaela , Glaser Bruno , Kuzyakov Yakov
Published: June 2016

Abstract. Microorganisms regulate the carbon (C) cycle in soil, controlling the utilization and recycling of organic substances. To reveal the contribution of particular microbial groups to C utilization and C turnover within the microbial cells, fate of 13C-labeled glucose was studied under field conditions. The 13C was traced in cytosolic substances, amino sugars and phospholipid fatty acids (PLFA) at intervals of 3, 10 and 50 days after glucose addition. 13C enrichment into PLFA (~1.5 % of PLFA C at day 3) was one order of magnitude greater than into the cytosol, showing the importance of cell membranes for initial C utilization. 13C enrichment of amino sugars in living microorganisms at day 3 accounted for 0.57 %, resulting that the turnover of cell wall components is two times slower than that of cell membranes. Turnover time of C in the cytosol (150 days) was three times longer than in PLFAs (47 days). Consequently, despite the lability of cytosol pool and expected fast turnover rates, intensive recycling of cytosol components, within the living cells, leads to a longer turnover time. Amino sugars originate mainly from microbial residues, thus longer experimental periods are required for estimation of their turnover times. Both PLFA and amino sugar profiles indicated that glucose C was preferentially used by bacteria. The 13C incorporated into bacterial cell membrane components decreased with time, but it remained constant or even increased for filamentous microorganisms. Hence, over a short period, bacteria contribute more to the utilization of low molecular weight organic substances, whereas filamentous microorganisms are responsible for further C transformations. Thus, tracing 13C in cellular compounds with contrasting turnover rates elucidated the role of microbial groups and their cellular compartments in C utilization and recycling in soil. This information is especially important for assessing C fluxes in soil and the contribution of C from microbial residues to soil organic matter.
The Brazilian developments on the Regional Atmospheric Modeling System (BRAMS 5.2): an integrated environmental model tuned for tropical areas
Authors: Freitas Saulo R. , Panetta Jairo , Longo Karla M. , Rodrigues Luiz F. , Moreira Demerval S. , Rosário Nilton E. , Silva Dias Pedro L. , Silva Dias Maria A. F. , Souza Enio P. , Freitas Edmilson D. , Longo Marcos , Frassoni Ariane , Fazenda Alvaro L. , Santos e Silva Cláudio M. , Pavani Cláudio A. B. , Eiras Denis , França Daniela A. , Massaru Daniel , Silva Fernanda B. , Cavalcante Fernando , Pereira Gabriel , Camponogara Gláuber , Ferrada Gonzalo A. , Campos Velho Haroldo F. , Menezes Isilda , Freire Julliana L. , Alonso Marcelo F. , Gácita Madeleine S. , Zarzur Maurício , Fonseca Rafael M. , Lima Rafael S. , Siqueira Ricardo A. , Braz Rodrigo , Tomita Simone , Oliveira Valter , Martins Leila D.
Published: June 2016

Abstract. We present a new version of the Brazilian developments on the Regional Atmospheric Modeling System where different previous versions for weather, chemistry and carbon cycle were unified in a single integrated software system. The new version also has a new set of state-of-the-art physical parameterizations and greater computational parallel and memory usage efficiency. Together with the description of the main features are examples of the quality of the transport scheme for scalars, radiative fluxes on surface and model simulation of rainfall systems over South America in different spatial resolutions using a scale-aware convective parameterization. Besides, the simulation of the diurnal cycle of the convection and carbon dioxide concentration over the Amazon Basin, as well as carbon dioxide fluxes from biogenic processes over a large portion of South America are shown. Atmospheric chemistry examples present model performance in simulating near-surface carbon monoxide and ozone in Amazon Basin and Rio de Janeiro megacity. For tracer transport and dispersion, it is demonstrated the model capabilities to simulate the volcanic ash 3-d redistribution associated with the eruption of a Chilean volcano. Then, the gain of computational efficiency is described with some details. BRAMS has been applied for research and operational forecasting mainly in South America. Model results from the operational weather forecast of BRAMS on 5 km grid spacing in the Center for Weather Forecasting and Climate Studies, INPE/Brazil, since 2013 are used to quantify the model skill of near surface variables and rainfall. The scores show the reliability of BRAMS for the tropical and subtropical areas of South America. Requirements for keeping this modeling system competitive regarding on its functionalities and skills are discussed. At last, we highlight the relevant contribution of this work on the building up of a South American community of model developers.
Ozone air quality simulations with WRF-Chem (v3.5.1) over Europe: Model evaluation and chemical mechanism comparison
Authors: Mar Kathleen A. , Ojha Narendra , Pozzer Andrea , Butler Tim M.
Published: June 2016

Abstract. We present an evaluation of the online regional model WRF-Chem over Europe with a focus on ground-level ozone (O3) and nitrogen oxides (NOx). The model performance is evaluated for two chemical mechanisms, MOZART-4 and RADM2, for year-long simulations. Model-predicted surface meteorological variables (e.g., temperature, wind speed and direction) compared well overall with surface-based observations, consistent with other WRF studies. WRF-Chem simulations employing MOZART-4 as well as RADM2 chemistry were found to reproduce the observed spatial variability in surface ozone over Europe. However, the absolute O3 concentrations predicted by the two chemical mechanisms were found to be quite different, with MOZART-4 predicting O3 concentrations up to 20 μg m−3 greater than RADM2 in summer. Compared to observations, MOZART-4 chemistry overpredicted O3 concentrations for most of Europe in the summer and fall, with a summertime domain-wide mean bias of +10 μg m−3 against observations from the AirBase network. In contrast, RADM2 chemistry generally led to an underestimation of O3 over the European domain in all seasons. We found that the use of the MOZART-4 mechanism, evaluated here for the first time for a European domain, led to lower absolute biases than RADM2 when compared to ground-based observations. The two mechanisms show relatively similar behavior for NOx, with both MOZART-4 and RADM2 resulting in a slight underestimation of NOx compared to surface observations. Further investigation into the differences between the two mechanisms revealed that the net midday photochemical production rate of O3 in summer is higher for MOZART-4 than for RADM2 for most of the domain. The largest differences in O3 production can be seen over Germany, where net O3 production in MOZART-4 is seen to be higher than in RADM2 by 1.8 ppb hr−1 (3.6 μg m−3 hr−1) or more. We also show that, while the two mechanisms exhibit similar NOx-sensitivity, RADM2 is approximately twice as sensitive to increases in anthropogenic VOC emissions as MOZART-4. Additionally, we found that differences in reaction rate constants for inorganic gas phase chemistry in MOZART-4 vs. RADM2 accounted for a difference of 8 μg m−3 in O3 predicted by the two mechanisms, whereas differences in deposition and photolysis schemes explained smaller differences in in O3. Our results highlight the strong dependence of modeled surface O3 over Europe on the choice of gas phase chemical mechanism, which we discuss in the context of overall uncertainties in prediction of ground-level O3 and its associated health impacts (via the health-related metrics MDA8 and SOMO35).
Atmosphere-only GCM (ACCESS1.0) simulations with prescribed land surface temperatures
Authors: Ackerley Duncan , Dommenget Dietmar
Published: June 2016

Abstract. General circulation models (GCMs) are valuable tools for understanding how the global ocean–atmosphere–land surface system interacts and are routinely evaluated relative to observational data sets. Conversely, observational data sets can also be used to constrain GCMs in order to identify systematic errors in their simulated climates. One such example is to prescribe sea surface temperatures (SSTs) such that 70 % of the Earth's surface temperature field is observationally constrained (known as an Atmospheric Model Intercomparison Project, AMIP, simulation). Nevertheless, in such simulations, land surface temperatures are typically allowed to vary freely, and therefore any errors that develop over the land may affect the global circulation. In this study therefore, a method for prescribing the land surface temperatures within a GCM (the Australian Community Climate and Earth System Simulator, ACCESS) is presented. Simulations with this prescribed land surface temperature model produce a mean climate state that is comparable to a simulation with freely varying land temperatures; for example, the diurnal cycle of tropical convection is maintained. The model is then developed further to incorporate a selection of “proof of concept” sensitivity experiments where the land surface temperatures are changed globally and regionally. The resulting changes to the global circulation in these sensitivity experiments are found to be consistent with other idealized model experiments described in the wider scientific literature. Finally, a list of other potential applications is described at the end of the study to highlight the usefulness of such a model to the scientific community.
SAR IMAGE SEGMENTATION WITH UNKNOWN NUMBER OF CLASSES COMBINED VORONOI TESSELLATION AND RJMCMC ALGORITHM
Authors: Zhao Q. H. , Li Y. , Wang Y.
Published: June 2016

Abstract. This paper presents a novel segmentation method for automatically determining the number of classes in Synthetic Aperture Radar (SAR) images by combining Voronoi tessellation and Reversible Jump Markov Chain Monte Carlo (RJMCMC) strategy. Instead of giving the number of classes a priori, it is considered as a random variable and subject to a Poisson distribution. Based on Voronoi tessellation, the image is divided into homogeneous polygons. By Bayesian paradigm, a posterior distribution which characterizes the segmentation and model parameters conditional on a given SAR image can be obtained up to a normalizing constant; Then, a Revisable Jump Markov Chain Monte Carlo(RJMCMC) algorithm involving six move types is designed to simulate the posterior distribution, the move types including: splitting or merging real classes, updating parameter vector, updating label field, moving positions of generating points, birth or death of generating points and birth or death of an empty class. Experimental results with real and simulated SAR images demonstrate that the proposed method can determine the number of classes automatically and segment homogeneous regions well.
A NEW METHOD FOR DETERMINING THE DEFORMATION MONITORABLE INDICATOR OF POINT CLOUD
Authors: Xuan W. , Hua X. H. , Qiu W. N. , Zou J. G. , Chen X. J.
Published: June 2016

Abstract. With the continuous development of the terrestrial laser scanning (TLS) technique, the precision of the laser scanning has been improved which makes it possible that TLS could be used for high-precision deformation monitoring. A deformation monitorable indicator (DMI) should be determined to distinguish the deformation from the error of point cloud and plays an important role in the deformation monitoring using TLS. After the DMI determined, a scheme of the deformation monitoring case could be planned to choose a suitable instrument, set up a suitable distance and sampling interval. In this paper, the point error space and the point cloud error space are modelled firstly based on the point error ellipsoid. Secondly, the actual point error is derived by the relationship between the actual point cloud error space and the point error space. Then, the DMI is determined using the actual point error. Finally, two sets of experiments is carried out and the feasibility of the DMI is proved.
MODELLING THE CARBON STOCKS ESTIMATION OF THE TROPICAL LOWLAND DIPTEROCARP FOREST USING LIDAR AND REMOTELY SENSED DATA
Authors: Zaki N. A. M. , Latif Z. A. , Suratman M. N. , Zainal M. Z.
Published: June 2016

Abstract. Tropical forest embraces a large stock of carbon in the global carbon cycle and contributes to the enormous amount of above and below ground biomass. The carbon kept in the aboveground living biomass of trees is typically the largest pool and the most directly impacted by the anthropogenic factor such as deforestation and forest degradation. However, fewer studies had been proposed to model the carbon for tropical rain forest and the quantification still remain uncertainties. A multiple linear regression (MLR) is one of the methods to define the relationship between the field inventory measurements and the statistical extracted from the remotely sensed data which is LiDAR and WorldView-3 imagery (WV-3). This paper highlight the model development from fusion of multispectral WV-3 with the LIDAR metrics to model the carbon estimation of the tropical lowland Dipterocarp forest of the study area. The result shown the over segmentation and under segmentation value for this output is 0.19 and 0.11 respectively, thus D-value for the classification is 0.19 which is 81%. Overall, this study produce a significant correlation coefficient (r) between Crown projection area (CPA) and Carbon stocks (CS); height from LiDAR (H_LDR) and Carbon stocks (CS); and Crown projection area (CPA) and height from LiDAR (H_LDR) were shown 0.671, 0.709 and 0.549 respectively. The CPA of the segmentation found to be representative spatially with higher correlation of relationship between diameter at the breast height (DBH) and carbon stocks which is Pearson Correlation p = 0.000 (p < 0.01) with correlation coefficient (r) is 0.909 which shown that there a good relationship between carbon and DBH predictors to improve the inventory estimates of carbon using multiple linear regression method. The study concluded that the integration of WV-3 imagery with the CHM raster based LiDAR were useful in order to quantify the AGB and carbon stocks for a larger sample area of the Lowland Dipterocarp forest.
SUPER RESOLUTION RECONSTRUCTION BASED ON ADAPTIVE DETAIL ENHANCEMENT FOR ZY-3 SATELLITE IMAGES
Authors: Zhu Hong , Song Weidong , Tan Hai , Wang Jingxue , Jia Di
Published: June 2016

Abstract. Super-resolution reconstruction of sequence remote sensing image is a technology which handles multiple low-resolution satellite remote sensing images with complementary information and obtains one or more high resolution images. The cores of the technology are high precision matching between images and high detail information extraction and fusion. In this paper puts forward a new image super resolution model frame which can adaptive multi-scale enhance the details of reconstructed image. First, the sequence images were decomposed into a detail layer containing the detail information and a smooth layer containing the large scale edge information by bilateral filter. Then, a texture detail enhancement function was constructed to promote the magnitude of the medium and small details. Next, the non-redundant information of the super reconstruction was obtained by differential processing of the detail layer, and the initial super resolution construction result was achieved by interpolating fusion of non-redundant information and the smooth layer. At last, the final reconstruction image was acquired by executing a local optimization model on the initial constructed image. Experiments on ZY-3 satellite images of same phase and different phase show that the proposed method can both improve the information entropy and the image details evaluation standard comparing with the interpolation method, traditional TV algorithm and MAP algorithm, which indicate that our method can obviously highlight image details and contains more ground texture information. A large number of experiment results reveal that the proposed method is robust and universal for different kinds of ZY-3 satellite images.
TOWARDS A SEMANTIC INTERPRETATION OF URBAN AREAS WITH AIRBORNE SYNTHETIC APERTURE RADAR TOMOGRAPHY
Authors: D'Hondt O. , Guillaso S. , Hellwich O.
Published: June 2016

Abstract. In this paper, we introduce a method to detect and reconstruct building parts from tomographic Synthetic Aperture Radar (SAR) airborne data. Our approach extends recent works in two ways: first, the radiometric information is used to guide the extraction of geometric primitives. Second, building facades and roofs are extracted thanks to geometric classification rules. We demonstrate our method on a 3 image L-Band airborne dataset over the city of Dresden, Germany. Experiments show how our technique allows to use the complementarity between the radiometric image and the tomographic point cloud to extract buildings parts in challenging situations.
TASK-DEPENDENT BAND-SELECTION OF HYPERSPECTRAL IMAGES BY PROJECTION-BASED RANDOM FORESTS
Authors: Hänsch R. , Hellwich O.
Published: June 2016

Abstract. The automatic classification of land cover types from hyperspectral images is a challenging problem due to (among others) the large amount of spectral bands and their high spatial and spectral correlation. The extraction of meaningful features, that enables a subsequent classifier to distinguish between different land cover classes, is often limited to a subset of all available data dimensions which is found by band selection techniques or other methods of dimensionality reduction. This work applies Projection-Based Random Forests to hyperspectral images, which not only overcome the need of an explicit feature extraction, but also provide mechanisms to automatically select spectral bands that contain original (i.e. non-redundant) as well as highly meaningful information for the given classification task. The proposed method is applied to four challenging hyperspectral datasets and it is shown that the effective number of spectral bands can be considerably limited without loosing too much of classification performance, e.g. a loss of 1 % accuracy if roughly 13 % of all available bands are used.
A NEW HIGH-RESOLUTION ELEVATION MODEL OF GREENLAND DERIVED FROM TANDEM-X
Authors: Wessel B. , Bertram A. , Gruber A. , Bemm S. , Dech S.
Published: June 2016

Abstract. In this paper we present for the first time the new digital elevation model (DEM) for Greenland produced by the TanDEM-X (TerraSAR add-on for digital elevation measurement) mission. The new, full coverage DEM of Greenland has a resolution of 0.4 arc seconds corresponding to 12 m. It is composed of more than 7.000 interferometric synthetic aperture radar (InSAR) DEM scenes. X-Band SAR penetrates the snow and ice pack by several meters depending on the structures within the snow, the acquisition parameters, and the dielectricity constant of the medium. Hence, the resulting SAR measurements do not represent the surface but the elevation of the mean phase center of the backscattered signal. Special adaptations on the nominal TanDEM-X DEM generation are conducted to maintain these characteristics and not to raise or even deform the DEM to surface reference data. For the block adjustment, only on the outer coastal regions ICESat (Ice, Cloud, and land Elevation Satellite) elevations as ground control points (GCPs) are used where mostly rock and surface scattering predominates. Comparisons with ICESat data and snow facies are performed. In the inner ice and snow pack, the final X-Band InSAR DEM of Greenland lies up to 10 m below the ICESat measurements. At the outer coastal regions it corresponds well with the GCPs. The resulting DEM is outstanding due to its resolution, accuracy and full coverage. It provides a high resolution dataset as basis for research on climate change in the arctic.
OPTIMAL WAVELENGTH SELECTION ON HYPERSPECTRAL DATA WITH FUSED LASSO FOR BIOMASS ESTIMATION OF TROPICAL RAIN FOREST
Authors: Takayama T. , Iwasaki A.
Published: June 2016

Abstract. Above-ground biomass prediction of tropical rain forest using remote sensing data is of paramount importance to continuous large-area forest monitoring. Hyperspectral data can provide rich spectral information for the biomass prediction; however, the prediction accuracy is affected by a small-sample-size problem, which widely exists as overfitting in using high dimensional data where the number of training samples is smaller than the dimensionality of the samples due to limitation of require time, cost, and human resources for field surveys. A common approach to addressing this problem is reducing the dimensionality of dataset. Also, acquired hyperspectral data usually have low signal-to-noise ratio due to a narrow bandwidth and local or global shifts of peaks due to instrumental instability or small differences in considering practical measurement conditions. In this work, we propose a methodology based on fused lasso regression that select optimal bands for the biomass prediction model with encouraging sparsity and grouping, which solves the small-sample-size problem by the dimensionality reduction from the sparsity and the noise and peak shift problem by the grouping. The prediction model provided higher accuracy with root-mean-square error (RMSE) of 66.16 t/ha in the cross-validation than other methods; multiple linear analysis, partial least squares regression, and lasso regression. Furthermore, fusion of spectral and spatial information derived from texture index increased the prediction accuracy with RMSE of 62.62 t/ha. This analysis proves efficiency of fused lasso and image texture in biomass estimation of tropical forests.
A METEOROLOGICAL RISK ASSESSMENT METHOD FOR POWER LINES BASED ON GIS AND MULTI-SENSOR INTEGRATION
Authors: Lin Zhiyong , Xu Zhimin
Published: June 2016

Abstract. Power lines, exposed in the natural environment, are vulnerable to various kinds of meteorological factors. Traditional research mainly deals with the influence of a single meteorological condition on the power line, which lacks of comprehensive effects evaluation and analysis of the multiple meteorological factors. In this paper, we use multiple meteorological monitoring data obtained by multi-sensors to implement the meteorological risk assessment and early warning of power lines. Firstly, we generate meteorological raster map from discrete meteorological monitoring data using spatial interpolation. Secondly, the expert scoring based analytic hierarchy process is used to compute the power line risk index of all kinds of meteorological conditions and establish the mathematical model of meteorological risk. By adopting this model in raster calculator of ArcGIS, we will have a raster map showing overall meteorological risks for power line. Finally, by overlaying the power line buffer layer to that raster map, we will get to know the exact risk index around a certain part of power line, which will provide significant guidance for power line risk management. In the experiment, based on five kinds of observation data gathered from meteorological stations in Guizhou Province of China, including wind, lightning, rain, ice, temperature, we carry on the meteorological risk analysis for the real power lines, and experimental results have proved the feasibility and validity of our proposed method.
LEAST SQUARE SUPPORT VECTOR MACHINE FOR DETECTION OF TECSEISMO- IONOSPHERIC ANOMALIES ASSOCIATED WITH THE POWERFUL NEPAL EARTHQUAKE (Mw = 7.5) OF 25 APRIL 2015
Authors: Akhoondzadeh M.
Published: June 2016

Abstract. Due to the irrepalable devastations of strong earthquakes, accurate anomaly detection in time series of different precursors for creating a trustworthy early warning system has brought new challenges. In this paper the predictability of Least Square Support Vector Machine (LSSVM) has been investigated by forecasting the GPS-TEC (Total Electron Content) variations around the time and location of Nepal earthquake. In 77 km NW of Kathmandu in Nepal (28.147° N, 84.708° E, depth = 15.0 km) a powerful earthquake of Mw = 7.8 took place at 06:11:26 UTC on April 25, 2015. For comparing purpose, other two methods including Median and ANN (Artificial Neural Network) have been implemented. All implemented algorithms indicate on striking TEC anomalies 2 days prior to the main shock. Results reveal that LSSVM method is promising for TEC sesimo-ionospheric anomalies detection.
ESTIMATION OF DAMAGED AREAS DUE TO THE 2010 CHILE EARTHQUAKE AND TSUNAMI USING SAR IMAGERY OF ALOS/PALSAR
Authors: Ni Made Pertiwi Jaya , Miura Fusanori , Rimba A. Besse
Published: June 2016

Abstract. A large-scale earthquake and tsunami affect thousands of people and cause serious damages worldwide every year. Quick observation of the disaster damage is extremely important for planning effective rescue operations. In the past, acquiring damage information was limited to only field surveys or using aerial photographs. In the last decade, space-borne images were used in many disaster researches, such as tsunami damage detection. In this study, SAR data of ALOS/PALSAR satellite images were used to estimate tsunami damage in the form of inundation areas in Talcahuano, the area near the epicentre of the 2010 Chile earthquake. The image processing consisted of three stages, i.e. pre-processing, analysis processing, and post-processing. It was conducted using multi-temporal images before and after the disaster. In the analysis processing, inundation areas were extracted through the masking processing. It consisted of water masking using a high-resolution optical image of ALOS/AVNIR-2 and elevation masking which built upon the inundation height using DEM image of ASTER-GDEM. The area result was 8.77 Km2. It showed a good result and corresponded to the inundation map of Talcahuano. Future study in another area is needed in order to strengthen the estimation processing method.
SPATIAL CORRELATIONS OF MALARIA INCIDENCE HOTSPOTS WITH ENVIRONMENTAL FACTORS IN ASSAM, NORTH EAST INDIA
Authors: Handique Bijoy K. , Khan Siraj A. , Dutta Prafulla , Nath Manash J. , Qadir Abdul , Raju P. L. N.
Published: June 2016

Abstract. Malaria is endemic and a major public health problem in north east (NE) region of India and contributes about 8-12 % of India's malaria positives cases. Historical morbidity pattern of malaria in terms of API (Annual Parasite Incidence) in the state of Assam has been used for delineating the malaria incidence hotspots at health sub centre (HSC) level. Strong spatial autocorrelation (p