SPARE-ICE: synergistic Ice Water Path from passive operational sensors

This article presents SPARE-ICE, the Synergistic Passive Atmospheric Retrieval Experiment-ICE. SPARE-ICE is the first Ice Water Path (IWP) product combining infrared and microwave radiances. By using only passive operational sensors, the SPARE-ICE retrieval can be used to process data from at least the NOAA 15 to 19 and MetOp satellites, obtaining time series from 1998 onward. The retrieval is developed using collocations between passive operational sensors (solar, terrestrial infrared, microwave), the CloudSat radar, and the CALIPSO lidar. The collocations form a retrieval database matching measurements from passive sensors against the existing active combined radar-lidar product 2C-ICE. With this retrieval database, we train a pair of artificial neural networks to detect clouds and retrieve IWP. When considering solar, terrestrial infrared, and microwave-based measurements, we show that any combination of two techniques performs better than either single-technique retrieval. We choose not to include solar reflectances in SPARE-ICE, because the improvement is small, and so that SPARE-ICE can be retrieved both daytime and nighttime. The median fractional error between SPARE-ICE and 2C-ICE is around a factor 2, a figure similar to the random error between 2C-ICE ice water content (IWC) and in situ measurements. A comparison of SPARE-ICE with Moderate Resolution Imaging Spectroradiometer (MODIS), Pathfinder Atmospheric Extended (PATMOS-X), and Microwave Surface and Precipitation Products System (MSPPS) indicates that SPARE-ICE appears to perform well even in difficult conditions. SPARE-ICE is available for public use.

An approximate dynamic programming approach for improving accuracy of lossy data compression by Bloom filters

Bloom filters are a data structure for storing data in a compressed form. They offer excellent space and time efficiency at the cost of some loss of accuracy (so-called lossy compression). This work presents a yes-no Bloom filter, which as a data structure consisting of two parts: the yes-filter which is a standard Bloom filter and the no-filter which is another Bloom filter whose purpose is to represent those objects that were recognised incorrectly by the yes-filter (that is, to recognise the false positives of the yes-filter). By querying the no-filter after an object has been recognised by the yes-filter, we get a chance of rejecting it, which improves the accuracy of data recognition in comparison with the standard Bloom filter of the same total length. A further increase in accuracy is possible if one chooses objects to include in the no-filter so that the no-filter recognises as many as possible false positives but no true positives, thus producing the most accurate yes-no Bloom filter among all yes-no Bloom filters. This paper studies how optimization techniques can be used to maximize the number of false positives recognised by the no-filter, with the constraint being that it should recognise no true positives. To achieve this aim, an Integer Linear Program (ILP) is proposed for the optimal selection of false positives. In practice the problem size is normally large leading to intractable optimal solution. Considering the similarity of the ILP with the Multidimensional Knapsack Problem, an Approximate Dynamic Programming (ADP) model is developed making use of a reduced ILP for the value function approximation. Numerical results show the ADP model works best comparing with a number of heuristics as well as the CPLEX built-in solver (B&B), and this is what can be recommended for use in yes-no Bloom filters. In a wider context of the study of lossy compression algorithms, our researchis an example showing how the arsenal of optimization methods can be applied to improving the accuracy of compressed data.

The role of big data in governance: a regulatory and legal perspective of analytics in global financial services

This paper discusses how global financial institutions are using big data analytics within their compliance operations. A lot of previous research has focused on the strategic implications of big data, but not much research has considered how such tools are entwined with regulatory breaches and investigations in financial services. Our work covers two in-depth qualitative case studies, each addressing a distinct type of analytics. The first case focuses on analytics which manage everyday compliance breaches and so are expected by managers. The second case focuses on analytics which facilitate investigation and litigation where serious unexpected breaches may have occurred. In doing so, the study focuses on the micro/data to understand how these tools are influencing operational risks and practices. The paper draws from two bodies of literature, the social studies of information systems and finance to guide our analysis and practitioner recommendations. The cases illustrate how technologies are implicated in multijurisdictional challenges and regulatory conflicts at each end of the operational risk spectrum. We find that compliance analytics are both shaping and reporting regulatory matters yet often firms may have difficulties in recruiting individuals with relevant but diverse skill sets. The cases also underscore the increasing need for financial organizations to adopt robust information governance policies and processes to ease future remediation efforts.

Melatonin and IP(3)-induced Ca(2+) Release from Intracellular Stores in the Malaria Parasite Plasmodium falciparum within Infected Red Blood Cells

IP(3)-dependent Ca(2+) signaling controls a myriad of cellular processes in higher eukaryotes and similar signaling pathways are evolutionarily conserved in Plasmodium, the intracellular parasite that causes malaria. We have reported that isolated, permeabilized Plasmodium chabaudi, releases Ca(2+) upon addition of exogenous IP(3). In the present study, we investigated whether the IP(3) signaling pathway operates in intact Plasmodium falciparum, the major disease-causing human malaria parasite. P. falciparum-infected red blood cells (RBCs) in the trophozoite stage were simultaneously loaded with the Ca(2+) indicator Fluo-4/AM and caged-IP(3). Photolytic release of IP(3) elicited a transient Ca(2+) increase in the cytosol of the intact parasite within the RBC. The intracellular Ca(2+) pools of the parasite were selectively discharged, using thapsigargin to deplete endoplasmic reticulum (ER) Ca(2+) and the antimalarial chloroquine to deplete Ca(2+) from acidocalcisomes. These data show that the ER is the major IP(3)-sensitive Ca(2+) store. Previous work has shown that the human host hormone melatonin regulates P. falciparum cell cycle via a Ca(2+)-dependent pathway. In the present study, we demonstrate that melatonin increases inositol-polyphosphate production in intact intraerythrocytic parasite. Moreover, the Ca(2+) responses to melatonin and uncaging of IP(3) were mutually exclusive in infected RBCs. Taken together these data provide evidence that melatonin activates PLC to generate IP(3) and open ER-localized IP(3)-sensitive Ca(2+) channels in P. falciparum. This receptor signaling pathway is likely to be involved in the regulation and synchronization of parasite cell cycle progression.

Model Configuration And Data Management In The Short-Term Water Information Forecasting Tools

The Short-term Water Information and Forecasting Tools (SWIFT) is a suite of tools for flood and short-term streamflow forecasting, consisting of a collection of hydrologic model components and utilities. Catchments are modeled using conceptual subareas and a node-link structure for channel routing. The tools comprise modules for calibration, model state updating, output error correction, ensemble runs and data assimilation. Given the combinatorial nature of the modelling experiments and the sub-daily time steps typically used for simulations, the volume of model configurations and time series data is substantial and its management is not trivial. SWIFT is currently used mostly for research purposes but has also been used operationally, with intersecting but significantly different requirements. Early versions of SWIFT used mostly ad-hoc text files handled via Fortran code, with limited use of netCDF for time series data. The configuration and data handling modules have since been redesigned. The model configuration now follows a design where the data model is decoupled from the on-disk persistence mechanism. For research purposes the preferred on-disk format is JSON, to leverage numerous software libraries in a variety of languages, while retaining the legacy option of custom tab-separated text formats when it is a preferred access arrangement for the researcher. By decoupling data model and data persistence, it is much easier to interchangeably use for instance relational databases to provide stricter provenance and audit trail capabilities in an operational flood forecasting context. For the time series data, given the volume and required throughput, text based formats are usually inadequate. A schema derived from CF conventions has been designed to efficiently handle time series for SWIFT.

Uma metodologia para a análise do desempenho sustentável dos postos de revenda de combustível na cidade de Natal/RN, com o uso de data envelopment analysis-DEA

The increasing use of fossil fuels in line with cities demographic explosion carries out to huge environmental impact in society. For mitigate these social impacts, regulatory requirements have positively influenced the environmental consciousness of society, as well as, the strategic behavior of businesses. Along with this environmental awareness, the regulatory organs have conquered and formulated new laws to control potentially polluting activities, mostly in the gas stations sector. Seeking for increasing market competitiveness, this sector needs to quickly respond to internal and external pressures, adapting to the new standards required in a strategic way to get the Green Badge . Gas stations have incorporated new strategies to attract and retain new customers whom present increasingly social demand. In the social dimension, these projects help the local economy by generating jobs and income distribution. In this survey, the present research aims to align the social, economic and environmental dimensions to set the sustainable performance indicators at Gas Stations sector in the city of Natal/RN. The Sustainable Balanced Scorecard (SBSC) framework was create with a set of indicators for mapping the production process of gas stations. This mapping aimed at identifying operational inefficiencies through multidimensional indicators. To carry out this research, was developed a system for evaluating the sustainability performance with application of Data Envelopment Analysis (DEA) through a quantitative method approach to detect system s efficiency level. In order to understand the systemic complexity, sub organizational processes were analyzed by the technique Network Data Envelopment Analysis (NDEA) figuring their micro activities to identify and diagnose the real causes of overall inefficiency. The sample size comprised 33 Gas stations and the conceptual model included 15 indicators distributed in the three dimensions of sustainability: social, environmental and economic. These three dimensions were measured by means of classical models DEA-CCR input oriented. To unify performance score of individual dimensions, was designed a unique grouping index based upon two means: arithmetic and weighted. After this, another analysis was performed to measure the four perspectives of SBSC: learning and growth, internal processes, customers, and financial, unifying, by averaging the performance scores. NDEA results showed that no company was assessed with excellence in sustainability performance. Some NDEA higher efficiency Gas Stations proved to be inefficient under certain perspectives of SBSC. In the sequence, a comparative sustainable performance and assessment analyzes among the gas station was done, enabling entrepreneurs evaluate their performance in the market competitors. Diagnoses were also obtained to support the decision making of entrepreneurs in improving the management of organizational resources and promote guidelines the regulators. Finally, the average index of sustainable performance was 69.42%, representing the efforts of the environmental suitability of the Gas station. This results point out a significant awareness of this segment, but it still needs further action to enhance sustainability in the long term

PERFORMANCE OF THE SLD BARREL CRID DURING THE 1992 PHYSICS DATA RUN

The SLD Barrel Cherenkov Ring Imaging Detector was fully operational in the 1992 physics data run. The electron drift velocity and magnetic field deflection of electron trajectories have been measured. Cherenkov rings have been observed from both the liquid and gas radiators. The number and the resolution of the angle of Cherenkov photons have been measured to be approximately equal to design specifications.

The sugar cane vegetal residues unloaded in the sugar mill: Operational costs and physical characteristics

Brazil produced in 2002/03 season 317.87×106tons of sugar cane stalks and 36.88×106tons of vegetal residues (green leaves, dry leaves and tops) in a planted area of 4.61×106 hectares (ha). These residues have a useful heat of 3,613.14Mcal.t-1. Currently most of this biomass is burned as a pre-harvest practice. The doubt persists in the system type that it must be adopted to pick up, load, transport and unload this biomass at the sugar mill boilers. This study analyzed 22 variables related to operational costs and physical characteristics of these residues in a field situation using a JOHN DEERE® 6850 forage harvester with two different treatments: T1 and T2 (two types of rakes) with 6 repetitions each one. The geographic location of the studied area that belongs to COSTA PINTO MILL (COSAN® Group) is: Latitude 22°40'30S and Longitude 47°36'38W. The adopted methodology was proposed by Ripoli et al. (2002). The obtained results at a 5% level of significance showed that both treatments did not differed significantly between them. Some of the results were, where EBP stands for Oil Equivalent Barrel: Windrowing (T1=US$0.17.EBP-1 and US$9.59.ha-1, T2=US$0.08.EBP-1 and US$4.27.ha-1); Pick up (T1=US$1.31.EBP-1 and US$44.29.ha-1, T2 =US$1.37.EBP-1 and US$48.36.ha-1); Transportation (T1=US$1.27.EBP-1 and US$14,30.ha -1, T2=US$1.33.EBP-1 and US$14,80.ha -1), Unloading at the sugar mill (T1=US$0.30.EBP-1 and US$3.39.ha-1, T2=US$0.32.EBP-1 and US$3.51.ha-1); Total (T1=US$3.05.EBP-1 and US$71.57.ha-1, T2=US$3.10.EBP-1 and US$70.94.ha-1). Confronting the obtained data with the ones in the bibliography, this system revealed itself more expensive than the baling system or the integral harvest system using combines.

GDP 4.0 transfer to SGP 3.0 for SCIAMACHY no2 column processing: Verification with SDOAS / GDOAS prototype algorithms and delta-validation with NDACC / UV-visible network data

Until mid 2006, SCIAMACHY data processors for the operational retrieval of nitrogen dioxide (NO2) column data were based on the historical version 2 of the GOME Data Processor (GDP). On top of known problems inherent to GDP 2, ground-based validations of SCIAMACHY NO2 data revealed issues specific to SCIAMACHY, like a large cloud-dependent offset occurring at Northern latitudes. In 2006, the GDOAS prototype algorithm of the improved GDP version 4 was transferred to the off-line SCIAMACHY Ground Processor (SGP) version 3.0. In parallel, the calibration of SCIAMACHY radiometric data was upgraded. Before operational switch-on of SGP 3.0 and public release of upgraded SCIAMACHY NO2 data, we have investigated the accuracy of the algorithm transfer: (a) by checking the consistency of SGP 3.0 with prototype algorithms; and (b) by comparing SGP 3.0 NO2 data with ground-based observations reported by the WMO/GAW NDACC network of UV-visible DOAS/SAOZ spectrometers. This delta-validation study concludes that SGP 3.0 is a significant improvement with respect to the previous processor IPF 5.04. For three particular SCIAMACHY states, the study reveals unexplained features in the slant columns and air mass factors, although the quantitative impact on SGP 3.0 vertical columns is not significant.

Exterior orientation of CBERS-2B imagery using multi-feature control and orbital data

The major contribution of this paper relates to the practical advantages of combining Ground Control Points (GCPs), Ground Control Lines (GCLs) and orbital data to estimate the exterior orientation parameters of images collected by CBERS-2B (China-Brazil Earth Resources Satellite) HRC (High-resolution Camera) and CCD (High-resolution CCD Camera) sensors. Although the CBERS-2B is no longer operational, its images are still being used in Brazil, and the next generations of the CBERS satellite will have sensors with similar technical features, which motivates the study presented in this paper. The mathematical models that relate the object and image spaces are based on collinearity (for points) and coplanarity (for lines) conditions. These models were created in an in-house developed software package called TMS (Triangulation with Multiple Sensors) with multi-feature control (GCPs and GCLs). Experiments on a block of four CBERS-2B HRC images and on one CBERS-2B CCD image were performed using both models. It was observed that the combination of GCPs and GCLs provided better bundle block adjustment results than conventional bundle adjustment using only GCPs. The results also demonstrate the advantages of using primarily orbital data when the number of control entities is reduced. © 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Environmental management and operational performance in automotive companies in Brazil: The role of human resource management and lean manufacturing

The main objective of this study is to verify the influence of Environmental Management (EM) on Operational Performance (OP) in Brazilian automotive companies, analyzing whether Lean Manufacturing (LM) and Human Resources (HR) interfere in the greening of these companies. Therefore, a conceptual framework listing these concepts was proposed, and three research hypotheses were presented. A questionnaire was elaborated based on this theoretical background and sent to respondents occupying the highest positions in the production/operations areas of Brazilian automotive companies. The data, collected from 75 companies, were analyzed using structural equation modeling. The main results are as follows: (a) the model tested revealed an adequate goodness of fit, showing that overall, the relations proposed between EM and OP and between HR, LM and EM tend to be statistically valid; (b) EM tends to influence OP in a positive and statistically weak manner; (c) LM has a greater influence on EM when compared to the influence HR has over EM; (d) HR has a positive relationship over EM, but the statistical significance of this relationship is less than that of the other evaluated relationships. The originality of this paper lies in its gathering the concepts of EM, LM, HR and OP in a single study, as they generally tend not to be treated jointly. This paper also provided valid empirical evidence for a littlestudied context: the Brazilian automotive sector. © 2012 Elsevier Ltd. All rights reserved.

Structural properties of beds packed with agro-industrial solid by-products applicable for solid-state fermentation: Experimental data and effects on process performance

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

BtoxDB: a comprehensive database of protein structural data on toxin-antitoxin systems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Green Manufacturing: Relationship between Adoption of Green Operational Practices and Green Performance of Brazilian ISO 9001-Certified Firms

The present work aims at analyzing how the adoption of a proactive environmental management via green operational practices (GOPs) correlates to the Green Performance (GrP) of a given set of ISO 9001-certified firms in Brazil. To this end, we elaborated a conceptual framework about environmental management, GOPs, and GrP Such theoretical foundation supported the development of empirical research through quantitative analysis. For the analysis, 75 questionnaires were collected from ISO 9001 certified companies. Data was analyzed by with statistical tools such as descriptive analysis, correlation analysis, and Structural Equation Modeling (SEM). The results demonstrate that the adoption of GOPs, in fact, exerts a positive impact on the GrP of the firms. This work contributes to a better understanding of green manufacturing in Brazil's industrial sector

Análise do potencial do sensor OLI (Operational Land Imager) a bordo do Landsat-8 em estimar a concentração de sólidos totais em suspensão no reservatório de Barra Bonita

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)