bluuebunny/crossref_metadata_2025 huggingface dataset:
Neonatal Death Dwarfism in a Girl with Distinctive Bone Dysplasia Compatible with Grebe Chondrodysplasia: Analysis by CT Scan-based Phenotype
Authors: Al Kaissi Ali , Chehida Farid Ben , Ganger Rudolf , Grill Franz
Published: September 2014

We report on a female fetus noted to have severe malformative type of skeletal dysplasia on ultrasonography done at 35 weeks gestation. The girl died shortly after birth. Clinical examination showed a fetus with severe dwarfism, extensive long and short bones, and bone deficiencies associated with multiple dislocations. Computed tomography (CT) scan-based phenotype showed a complex constellation of malformations consistent with the diagnosis of Grebe syndrome. Parents being first cousins (consanguineous marriage) strongly suggests autosomal recessive pattern of inheritance. To our knowledge, this is the first report of neonatal death dwarfism of Grebe syndrome analyzed by CT scan-based phenotype.
Involvement of abscisic acid metabolites and the oxidative status of barley genotypes in response to drought
Authors: Thameur A. , Ferchichi A. , López-Carbonell M.
Published: September 2014

Thameur, A., Ferchichi, A. and López-Carbonell, M. 2014. Involvement of abscisic acid metabolites and the oxidative status of barley genotypes in response to drought. Can. J. Plant Sci. 94: 1481–1490. Endogenous concentrations of free abscisic acid (ABA), abscisic acid glucosyl ester (ABAGE), phaseic acid (PA), dihydrophaseic acid (DPA) and 7′-hydroxy ABA (7′-OH ABA) were analysed by means of a LC–MS/MS system in five genotypes of barley (Hordeum vulgare L.) grown under well-watered and drought stress conditions. For this purpose a drought treatment was conducted using genotypes: ‘Ardahoui’, ‘Manel’, ‘Pakistan’, ‘Rihane’ and ‘Roho’. Our results show that free and conjugated ABA levels increased in all genotypes grown under water stress, except in Manel genotype, in which ABAGE levels were the lowest. In contrast, genotypes Ardhaoui and Roho showed the highest ABA and ABAGE levels. Nevertheless, drought Rihane plants showed the maximum ability to increase the endogenous ABA concentrations. PA, DPA and 7′-OH ABA increased also in all drought genotypes, especially in the leaves of Manel and Roho genotypes, while the highest ability to increase the endogenous PA content corresponded to genotypes Ardahoui and Pakistan. To evaluate the plant oxidative status, some antioxidant compounds were analysed. Under drought conditions, small changes in some of them were seen. Among the genotypes studied, Manel was the only one which did not show increases in malondialdehyde (MDA) and, in parallel, showed a decrease in ABAGE content. These results provide us valuable information and contribute to the knowledge of the different responses of these genotypes to drought stress.
Plane Lorentzian and Fuchsian Hedgehogs
Authors: Martinez-Maure Yves
Published: September 2014

Parts of the Brunn–Minkowski theory can be extended to hedgehogs, which are envelopes of families of affine hyperplanes parametrized by their Gauss map. F. Fillastre introduced Fuchsian convex bodies, which are the closed convex sets of Lorentz–Minkowski space that are globally invariant under the action of a Fuchsian group. In this paper, we undertake a study of plane Lorentzian and Fuchsian hedgehogs. In particular, we prove the Fuchsian analogues of classical geometrical inequalities (analogues that are reversed as compared to classical ones).
Carbon losses from pyrolysed and original wood in a forest soil under natural and increased N deposition
Authors: Maestrini B. , Abiven S. , Singh N. , Bird J. , Torn M. S. , Schmidt M. W. I.
Published: September 2014

Abstract. Pyrogenic organic matter (PyOM) plays an important role as a stable carbon (C) sink in the soils of terrestrial ecosystems. However, uncertainties remain about in situ turnover rates of fire-derived PyOM in soil, the main processes leading to PyOM-C and nitrogen (N) losses from the soil, and the role of N availability on PyOM cycling in soils. We measured PyOM and native soil organic carbon losses from the soil as carbon dioxide and dissolved organic carbon (DOC) using additions of highly 13C-labelled PyOM (2.03 atom %) and its precursor pinewood during 1 year in a temperate forest soil. The field experiment was carried out under ambient and increased mineral N deposition (+60 kg N-NH4NO3 ha−1 year−1). The results showed that after 1 year: (1) 0.5% of PyOM-C and 22% of wood-C were mineralized as CO2, leading to an estimated turnover time of 191 and 4 years, respectively; (2) the quantity of PyOM and wood lost as dissolved organic carbon was negligible (0.0004 ± 0.0003% and 0.022 ± 0.007% of applied-C, respectively); and (3) N additions decreased cumulative PyOM mineralization by 43%, but did not affect cumulative wood mineralization and did not affect the loss of DOC from PyOM or wood. We conclude that mineralization to CO2 was the main process leading to PyOM losses during the first year of mineralization in a forest soil, and that N addition can decrease PyOM-C cycling, while added N showed no effect on wood C cycling.
Dynamics of global atmospheric CO2 concentration from 1850 to 2010: a linear approximation
Authors: Wang W. , Nemani R.
Published: September 2014

Abstract. The increase in anthropogenic CO2 emissions largely followed an exponential path between 1850 and 2010, and the corresponding increases in atmospheric CO2 concentration were almost constantly proportional to the emissions by the so-called "airborne fraction". These observations suggest that the dynamics of atmospheric CO2 concentration through this time period may be properly approximated as a linear system. We demonstrate this hypothesis by deriving a linear box-model to describe carbon exchanges between the atmosphere and the surface reservoirs under the influence of disturbances such as anthropogenic CO2 emissions and global temperature changes. We show that the box model accurately simulates the observed atmospheric CO2 concentrations and growth rates across interannual to multi-decadal time scales. The model also allows us to analytically examine the dynamics of such changes/variations, linking its characteristic disturbance-response functions to bio-geophysically meaningful parameters. In particular, our results suggest that the elevated atmospheric CO2 concentrations have significantly promoted the gross carbon uptake by the terrestrial biosphere. However, such "fertilization" effects are partially offset by enhanced carbon release from surface reservoirs promoted by warmer temperatures. The result of these interactions appears to be a decline in net efficiency in sequestering atmospheric CO2 by ∼30% since 1960s. We believe that the linear modeling framework outlined in this paper provides a convenient tool to diagnose the observed atmospheric CO2 dynamics and monitor their future changes.
Does temperature affect the accuracy of vented pressure transducer in fine-scale water level measurement?
Authors: Liu Z. , Higgins C. W.
Published: September 2014

Abstract. Submersible pressure transducers have been utilized for collecting water level data since early 1960s. Together with a digital datalogger, it is a convenient way to record water level fluctuations for long-term monitoring. Despite the widely use of pressure transducers for water level monitoring, little has been reported for their accuracy and performance under field conditions. The effect of temperature fluctuations on the output of vented pressure transducers were discussed in this study. The pressure transducer was tested under both laboratory and field conditions. The results of this study indicate that temperature fluctuation has a strong effect on the transducer output. Rapid changes in temperature introduce noise and fluctuations in the water level readings under a constant hydraulic head while the absolute temperature is also related to sensor errors. The former is attributed to venting and the latter is attributed to temperature compensation effect in the strain gauges. Individual pressure transducers responded differently to the thermal fluctuations in the same testing environment. In the field of surface hydrology, especially when monitoring fine-scale water level fluctuations, ignoring or failing to compensate for the temperature effect can introduce considerable error into pressure transducer readings. It is recommended that a performance test for the pressure transducer is conducted before field deployment.
Multi-scale hydrometeorological observation and modelling for flash flood understanding
Authors: Braud I. , Ayral P.-A. , Bouvier C. , Branger F. , Delrieu G. , Le Coz J. , Nord G. , Vandervaere J.-P. , Anquetin S. , Adamovic M. , Andrieu J. , Batiot C. , Boudevillain B. , Brunet P. , Carreau J. , Confoland A. , Didon-Lescot J.-F. , Domergue J.-M. , Douvinet J. , Dramais G. , Freydier R. , Gérard S. , Huza J. , Leblois E. , Le Bourgeois O. , Le Boursicaud R. , Marchand P. , Martin P. , Nottale L. , Patris N. , Renard B. , Seidel J.-L. , Taupin J.-D. , Vannier O. , Vincendon B. , Wijbrans A.
Published: September 2014

Abstract. This paper presents a coupled observation and modelling strategy aiming at improving the understanding of processes triggering flash floods. This strategy is illustrated for the Mediterranean area using two French catchments (Gard and Ardèche) larger than 2000 km2. The approach is based on the monitoring of nested spatial scales: (1) the hillslope scale, where processes influencing the runoff generation and its concentration can be tackled; (2) the small to medium catchment scale (1–100 km2), where the impact of the network structure and of the spatial variability of rainfall, landscape and initial soil moisture can be quantified; (3) the larger scale (100–1000 km2), where the river routing and flooding processes become important. These observations are part of the HyMeX (HYdrological cycle in the Mediterranean EXperiment) enhanced observation period (EOP), which will last 4 years (2012–2015). In terms of hydrological modelling, the objective is to set up regional-scale models, while addressing small and generally ungauged catchments, which represent the scale of interest for flood risk assessment. Top-down and bottom-up approaches are combined and the models are used as "hypothesis testing" tools by coupling model development with data analyses in order to incrementally evaluate the validity of model hypotheses. The paper first presents the rationale behind the experimental set-up and the instrumentation itself. Second, we discuss the associated modelling strategy. Results illustrate the potential of the approach in advancing our understanding of flash flood processes on various scales.
Robust global sensitivity analysis of a river management model to assess nonlinear and interaction effects
Authors: Peeters L. J. M. , Podger G. M. , Smith T. , Pickett T. , Bark R. H. , Cuddy S. M.
Published: September 2014

Abstract. The simulation of routing and distribution of water through a regulated river system with a river management model will quickly result in complex and nonlinear model behaviour. A robust sensitivity analysis increases the transparency of the model and provides both the modeller and the system manager with a better understanding and insight on how the model simulates reality and management operations. In this study, a robust, density-based sensitivity analysis, developed by Plischke et al. (2013), is applied to an eWater Source river management model. This sensitivity analysis methodology is extended to not only account for main effects but also for interaction effects. The combination of sensitivity indices and scatter plots enables the identification of major linear effects as well as subtle minor and nonlinear effects. The case study is an idealized river management model representing typical conditions of the southern Murray–Darling Basin in Australia for which the sensitivity of a variety of model outcomes to variations in the driving forces, inflow to the system, rainfall and potential evapotranspiration, is examined. The model outcomes are most sensitive to the inflow to the system, but the sensitivity analysis identified minor effects of potential evapotranspiration and nonlinear interaction effects between inflow and potential evapotranspiration.
Using measured soil water contents to estimate evapotranspiration and root water uptake profiles – a comparative study
Authors: Guderle M. , Hildebrandt A.
Published: September 2014

Abstract. Understanding the role of plants for soil water relations, and thus for ecosystem functioning, requires information about root water uptake. We evaluated four different complex water balance methods to estimate sink term patterns and evapotranspiration directly from soil moisture measurements. We tested four methods: the first two take the difference between two measurement intervals as evapotranspiration, thus neglecting vertical flow. The third uses regression on the soil water content time series and differences between day and night to account for vertical flow. The fourth accounts for vertical flow using a numerical model and iteratively solves for the sink term. Neither of those methods requires any a priori information of root distribution parameters or evapotranspiration, which is the advantage, compared to common root water uptake models. To test the methods, a synthetic experiment with numerical simulations for a grassland ecosystem was conducted. Additionally, the time series were perturbed to simulate common sensor errors, like those due to measurement precision and inaccurate sensor calibration. We tested each method for a range of measurement frequencies and applied performance criteria to evaluate the suitability of each method. In general, we show that methods accounting for vertical flow predict evapotranspiration and the sink term distribution more accurately than the simpler approaches. Under consideration of possible measurement uncertainties, the method based on regression and differentiating between day and night cycles leads to the best and most robust estimation of sink term patterns. It is thus an alternative to more complex inverse numerical methods. This study demonstrates that highly resolved (temporal and spatial) soil water content measurements may be used to estimate the sink term profiles when the appropriate approach is used.
Bayesian network learning for natural hazard analyses
Authors: Vogel K. , Riggelsen C. , Korup O. , Scherbaum F.
Published: September 2014

Abstract. Modern natural hazards research requires dealing with several uncertainties that arise from limited process knowledge, measurement errors, censored and incomplete observations, and the intrinsic randomness of the governing processes. Nevertheless, deterministic analyses are still widely used in quantitative hazard assessments despite the pitfall of misestimating the hazard and any ensuing risks. In this paper we show that Bayesian networks offer a flexible framework for capturing and expressing a broad range of uncertainties encountered in natural hazard assessments. Although Bayesian networks are well studied in theory, their application to real-world data is far from straightforward, and requires specific tailoring and adaptation of existing algorithms. We offer suggestions as how to tackle frequently arising problems in this context and mainly concentrate on the handling of continuous variables, incomplete data sets, and the interaction of both. By way of three case studies from earthquake, flood, and landslide research, we demonstrate the method of data-driven Bayesian network learning, and showcase the flexibility, applicability, and benefits of this approach. Our results offer fresh and partly counterintuitive insights into well-studied multivariate problems of earthquake-induced ground motion prediction, accurate flood damage quantification, and spatially explicit landslide prediction at the regional scale. In particular, we highlight how Bayesian networks help to express information flow and independence assumptions between candidate predictors. Such knowledge is pivotal in providing scientists and decision makers with well-informed strategies for selecting adequate predictor variables for quantitative natural hazard assessments.
Analysing the relationship between rainfalls and landslides to define a mosaic of triggering thresholds for regional-scale warning systems
Authors: Segoni S. , Rosi A. , Rossi G. , Catani F. , Casagli N.
Published: September 2014

Abstract. We propose an original approach to develop rainfall thresholds to be used in civil protection warning systems for the occurrence of landslides at regional scale (i.e. tens of thousands of kilometres), and we apply it to Tuscany, Italy (23 000 km2). Purpose-developed software is used to define statistical intensity–duration rainfall thresholds by means of an automated and standardized analysis of rainfall data. The automation and standardization of the analysis brings several advantages that in turn have a positive impact on the applicability of the thresholds to operational warning systems. Moreover, the possibility of defining a threshold in very short times compared to traditional analyses allowed us to subdivide the study area into several alert zones to be analysed independently, with the aim of setting up a specific threshold for each of them. As a consequence, a mosaic of several local rainfall thresholds is set up in place of a single regional threshold. Even if pertaining to the same region, the local thresholds vary substantially and can have very different equations. We subsequently analysed how the physical features of the test area influence the parameters and the equations of the local thresholds, and found that some threshold parameters can be put in relation with the prevailing lithology. In addition, we investigated the possible relations between effectiveness of the threshold and number of landslides used for the calibration. A validation procedure and a quantitative comparison with some literature thresholds showed that the performance of a threshold can be increased if the areal extent of its test area is reduced, as long as a statistically significant landslide sample is present. In particular, we demonstrated that the effectiveness of a warning system can be significantly enhanced if a mosaic of site-specific thresholds is used instead of a single regional threshold.
The Extent of Sunlight Penetration Performance on Traditional Style’s Apartment Façade in Putrajaya, Malaysia
Authors: Hassan Ahmad Sanusi , Arab Yasser
Published: September 2014

In this study the analysis is to measure the performance on the extent of sunlight penetration on front apartment facades. The apartments are located in Putrajaya, Malaysia. Putrajaya is the administrative city for the federal government, and it is considered the latest new city in Malaysia with postmodern style buildings which exhibit a range of complex geometric elements blending with colonial, modern and traditional architectural style. The scope of this study is to measure the extent of sunlight penetration on the apartment facades. Two front facades of the apartments were selected in the case studies using computer simulation for the analysis. The selected case studies are sixteen stories apartment located in Precinct 17 and seventeen stories apartment located in Precinct 18. SunTool software is used in the survey to calculate the extent of sunlight penetration. The survey will be conducted at a position when the sun path is perpendicular to the house façade. This analysis will compare results of the computer simulations of these two apartments in relation to the facade design of the architectural elements for shading devices. This study finds that the more the application is the traditional shading elements, the more is the shading performance on the façade walls. However this study also finds that traditional shading elements are designed only to block sunlight from horizontal angle of the sun position. They are not designed to obstruct sunlight from vertical angle of the sun position.
Hardware-Software Complex for Laser Scanning in Color Sorting Machines
Authors: Babishov Elnur Megraliyevich , Pakhomov Gennady Vladimirovich , Shulgin Vladimir Alekseevich , Buslov Evgeny Yur’evich , Minakov Dmitry Anatol’evich
Published: September 2014

The paper concerns the problem of grain mixture analysis based on processing images synthesized during line-by-line scanning of each object in color sorting systems. The paper presents a hardware-software complex for sorting objects in the real time. The hardware part of the complex consists of two blocks: light source and device for reception and processing of images. The light source is a laser, passed through optical fiber and linearly expanded across the entire width of the photoseparator’s chute. Linear laser scan produces significant intensity of illumination. It is sufficient for working on the transmission of radiation through objects. The software part of the complex also consists of two blocks: the thresholding algorithm and an automated program for finding the optimal parameters of sorting on the basis of that algorithm. The algorithm calculates the number of connected defective pixels with arbitrary shape. Automated program works on the basis of pre-formed images of the objects of two classes: good and defective. As a result, the program displays in tabular form the most optimal sorting parameters. The program shows the dependence of the loss of good product from the missouts of the defective objects. The customer gets a clear choice of the most suitable sorting results. This complex was tested for sorting of unshelled rice seeds via transmission. It is shown that the complex allows to effectively detect hidden seed defects: red pigmentation, immaturity, fungal diseases, and others.
BICEP2 and the Gravitino Mass: The Questionable Result
Authors: Tahan AC
Published: September 2014

The gravitino has been explained to exist with a low mass (Tahan 2013). BICEP2 results support a mass close to 1014GeV. Though the BICEP2 conclusions have been celebrated by numerous physicists with fewer scientists indicating problems with the data,   from BICEP2 (BICEP2 Collaboration 2014) can be understood improbable by simply focusing on the mass of the gravitino. This manuscript presents a method involving increasing string vibrations to measure the gravitino mass in the laboratory.
Equality of Google Scholar with Web of Science Citations: Case of Malaysian Engineering Highly Cited Papers
Authors: Ebrahim Nader Ale , Salehi Hadi , Embi Mohamed Amin , Danaee Mahmoud , Mohammadjafari Marjan , Zavvari Azam , Shakiba Masoud , Shahbazi-Moghadam Masoomeh
Published: September 2014

This study uses citation analysis from two citation tracking databases, Google Scholar (GS) and ISI Web of Science, in order to test the correlation between them and examine the effect of the number of paper versions on citations. The data were retrieved from the Essential Science Indicators and Google Scholar for 101 highly cited papers from Malaysia in the field of engineering. An equation for estimating the citation in ISI based on Google scholar is offered. The results show a significant and positive relationship between both citation in Google Scholar and ISI Web of Science with the number of versions. This relationship is higher between versions and ISI citations (r = 0.395, p<0.01) than between versions and Google Scholar citations (r = 0.315, p<0.01). Free access to data provided by Google Scholar and the correlation to get ISI citation which is costly, allow more transparency in tenure reviews, funding agency and other science policy, to count citations and analyze scholars’ performance more precisely.
Detection of Cassava Leaves in Multi-Temporally Acquired Digital Images of a Cassava Field Under Different Brightness Levels by Simultaneous Binarization of the Images Based on Indices of Redness/Greenness
Authors: Srisutham Mallika , Doi Ryoichi , Polthanee Anan , Mizoguchi Masaru
Published: September 2014

Plant leaf area reveals various types of abnormalities which can enable appropriate plant/crop management actions. The quantification of plant leaf area is now feasible using commonly available digital photographing tools. Changes in brightness, however, make it difficult to compare leaf areas in digital photographs acquired at multiple time points. This difficulty could be overcome by employing an index of redness/greenness (R/G), which was suggested to be one of the best indices to discriminate between plant leaves and other objects such as soils. R/G and other indices were examined when discriminating cassava leaves from other objects in a field. A surveillance camera captured digital photographs on a daily basis. Of these, 183 photographs were stored. They were pasted into a single image file and simultaneously analyzed. The International Commission on Illumination color model’s a* was the best index in the discrimination, with a distinctiveness score of 1.36. R/G was the second best, with a distinctiveness score of 0.70. The percentage of leaf-likely pixels followed sigmoidal patterns with time, resulting in great coefficients of determination of 0.981 (a*) and 0.965 (R/G). The percentage of leaf-likely pixels and cassava leaf weight had a real-time response relationship. The range of the 95% confidence limit was narrowed from -16 to +14% of a predicted value of 98% leaf-likely pixels for R/G to ±12% for a*. Thus, the simultaneous binarization and the detection of leaf-likely pixels in the photographs acquired under different brightness levels was enabled with improved discrimination accuracy by employing a*.
Work Attitude among Malaysian Academicians in the Public Universities: A Social Network Analysis
Authors: Asrah Norhaidah Mohd , Djauhari Maman Abdurachman , Suleiman Ebi Shahrin
Published: September 2014

This study dealt with a social network analysis approach to comprehend the work attitude amongst academicians in the Malaysian public universities. This work attitude presented the psychological attachment between the employee and the organization. The organizational commitment and workplace spirituality amongst the academicians were highlighted here. A total of 40 factors were found to represent four groups of workplace spirituality and organizational commitment. The similarity amongst the factors was measured with two different kinds of associations. The best measure of association, which was the Tschuprow’s measure of association, showed better results than the other measure in measuring the correlation amongst the factors. The connections and relationships amongst the factors were studied by using minimum spanning trees (MST). The interpretation of the MST was conducted by using the overall centrality measure.
Late summer net community production in the central Arctic Ocean using multiple approaches
Authors: Ulfsbo Adam , Cassar Nicolas , Korhonen Meri , van Heuven Steven , Hoppema Mario , Kattner Gerhard , Anderson Leif G.
Published: September 2014

Large‐scale patterns of net community production (NCP) were estimated during the late summer cruise ARK‐XXVI/3 (TransArc, August/September 2011) to the central Arctic Ocean. Several approaches were used based on the following: (i) continuous measurements of surface water oxygen to argon ratios (O2/Ar), (ii) underway measurements of surface partial pressure of carbon dioxide (pCO2), (iii) discrete samples of dissolved inorganic carbon, and (iv) dissolved inorganic nitrogen and phosphate. The NCP estimates agreed well within the uncertainties associated with each approach. The highest late summer NCP (up to 6 mol C m−2) was observed in the marginal sea ice zone region. Low values (<1 mol C m−2) were found in the sea ice‐covered deep basins with a strong spatial variability. Lowest values were found in the Amundsen Basin and moderate values in the Nansen and Makarov Basins with slightly higher estimates over the Mendeleev Ridge. Our findings support a coupling of NCP to sea ice coverage and nutrient supply and thus stress a potential change in spatial and temporal distribution of NCP in a future Arctic Ocean. To follow the evolution of NCP in space and time, it is suggested to apply one or several of these approaches in shipboard investigations with a time interval of 3 to 5 years.
Observations and estimates of wave‐driven water level extremes at the Marshall Islands
Authors: Merrifield M. A. , Becker J. M. , Ford M. , Yao Y.
Published: September 2014

Wave‐driven extreme water levels are examined for coastlines protected by fringing reefs using field observations obtained in the Republic of the Marshall Islands. The 2% exceedence water level near the shoreline due to waves is estimated empirically for the study sites from breaking wave height at the outer reef and by combining separate contributions from setup, sea and swell, and infragravity waves, which are estimated based on breaking wave height and water level over the reef flat. Although each component exhibits a tidal dependence, they sum to yield a 2% exceedence level that does not. A hindcast based on the breaking wave height parameterization is used to assess factors leading to flooding at Roi‐Namur caused by an energetic swell event during December 2008. Extreme water levels similar to December 2008 are projected to increase significantly with rising sea level as more wave and tide events combine to exceed inundation threshold levels.
Coherent pan‐Asian climatic and isotopic response to orbital forcing of tropical insolation
Authors: Battisti D. S. , Ding Qinghua , Roe G. H.
Published: September 2014

The oxygen‐18 isotope composition of calcite in stalagmites across southern and eastern Asia are highly correlated to one another on orbital time scales: large negative excursions are coincident with maxima in summer insolation in the subtropics of the Northern Hemisphere (NH). These isotopic excursions reflect changes in the precipitation‐weighted isotopic composition of precipitation, δ18Op. We present results from two core experiments using an isotope‐enabled climate model—the“high‐insolation” and “low‐insolation” experiments—in which the model is forced by extrema in NH summer insolation. Compared to the low‐insolation experiment, the high‐insolation climate features profound, large‐scale changes in the pattern of monsoon precipitation spanning from Africa to Southeast Asia that are due to changes in the relative contributions of temperature and moisture to the near‐surface equivalent potential temperature θe. Under high insolation, a more rapid increase in land surface temperature in early summer causes the greatest θe (and hence precipitation) to shift from the oceans in low insolation (such as today) to be over land in high insolation (such as the early Holocene). The model captures the general pattern of isotopic excursions seen in caves spanning from Israel to western China, including large drops in δ18Op over eastern Tibet (−7‰), the Arabian Peninsula, and northeast Africa (−4‰). Although there are large changes in precipitation over Tibet, the change in δ18Op is due to changes in the δ18O of water vapor that is delivered and subsequently precipitated; it does not inform on local precipitation amount or intensity.
Engineering Statistics
Authors: Vardeman Stephen B.
Published: September 2014

Some classes of statistical methods have traditionally been associated with engineering problems and applications, and some of these methods have become very important to this field. In this entry, we will identify these classes of statistical methods and indicate how they contribute to modern engineering practice
Signal Processing, Selection Approach in
Authors: Chen Pinyuen , Panchapakesan S.
Published: September 2014

This article considers selection and ranking goals and techniques in studying the problems of simultaneous detection of signals at several sites and also estimating the number of signals.
AIDSStochastic Models
Authors: Tan Wai‐Yuan
Published: September 2014

To model the HIV epidemic, there are four different approaches: The deterministic models, the stochastic models, the statistical models, and the state space models. The last three models treat the HIV epidemic as random processes. This article presents a systematic review of these random processes. It illustrates how to develop stochastic models and statistical models of the HIV epidemic and how to combine these models into state space models. Using a homosexual population as an example, it illustrates how to develop stochastic equations for the state variables and how to use the state space models to develop a generalized Bayesian method to estimate the unknown parameters and the state variables. The methodology is illustrated by using the AIDS incidence data of the San Francisco homosexual population.
Statistical Signal Processing
Authors: Kannan Nandini , Kundu Debasis
Published: September 2014

Statistical signal processing is an important area of research with extensive applications in the fields of communication theory, array processing, seismology, and medical diagnosis. The goal of signal processing is to recover characteristics of the underlying process from observed data. The random nature of the signals underscores the need for statistical techniques in model formulation, estimation, and data analysis. A brief discussion of two models that have been widely studied in the signal processing literature is provided. In addition, different methods of estimation are presented, and some unique characteristics of these models are highlighted.
Probabilistic and Statistical Models for Conception
Authors: Scarpa Bruno
Published: September 2014

Statistical models of fertility studies play a crucial role in understanding the biology of conception. Heterogeneity in women and men's requires specific statistical methods to be used in order to allow for the variability in behavioral and physical characteristics, as well as for the variability in frequency and timing of sexual intercourse and for the progressive selection of patients during the fertility studies that provide data. A review of the most used models is offered, starting from classical population models, based only on aggregated data we then discuss time to pregnancy models and the models that predict the day‐specific probability of conception.
Interrater Agreement
Authors: Choudhary Pankaj K.
Published: September 2014

As the technology advances, new methods of measuring a continuous clinical variable become available that may be cheaper or less invasive than the old ones. But before a new method is adopted for general use, it is validated by evaluating its agreement with an established standard. This article presents a comparative discussion of the various approaches for measuring agreement between two measurement methods. Their application is illustrated using a blood pressure data from the literature.
Sample Size Determination for Clinical Trials
Authors: Tang Man‐Lai
Published: September 2014

In this article, we will present some useful sample size formulas that guarantee to achieve a pre‐specified power level of a test at a chosen nominal level or control a pre‐specified confidence width of a confidence interval estimator at a chosen coverage level (wherever available) for some popular topics in general clinical trials. Topics include: (a) one‐sample problem for mean and proportion; (b) two‐sample problem for comparing means and proportions; (c) multiple‐sample problem for comparing means and proportions; (d) multiple‐arm dose response trials for trend; (e) multiple regression analysis; and (f) multiple logistic regression analysis.
Centralized Genomic Control: A Simple Approach Correcting for Population Structures
Authors: Zhang Hong , Li Qizhai , Zang Yong , Yang Yaning , Zheng Gang
Published: September 2014

The case‐control study is a useful design for testing for genetic association. However, it may yield spurious associations due to population structure. Population stratification (PS) and cryptic relatedness (CR) are two common population structures under which the trend test for association may be biased and its variance may be distorted. Genomic control and delta centralization are two simple approaches to correct for the variance distortion and the bias, respectively, using unlinked null genetic markers. An alternative simple method, centralized genomic control (CGC), that corrects for both bias and variance distortions simultaneously using unlinked null markers is studied. It can also handle studies with a small number of subjects and a small number of null markers. This approach requires the allele frequencies of the markers of interest roughly to match those of unlinked null markers in control samples. This matching and the effectiveness of various approaches under the matching are investigated by simulation studies. Applications to two real datasets (a candidate gene study and a genome‐wide association study) illustrate that the CGC outperforms the existing methods which correct for either the variance distortion or the bias due to PS or CR.
Analytical Methods for Risk Management: An Engineering Systems Perspective
Authors: R. Garvey Paul
Published: September 2014

Risk is a driving consideration in decisions that determine how engineering systems are developed, produced, and sustained. Critical to these decisions is an understanding of risk and how it affects the engineering of systems. The process of identifying, measuring, and managing risk is known as risk management. Applied early, risk management can expose potentially crippling areas of risk in the engineering of systems. This provides management time to define and implement corrective strategies. Moreover, risk management can bring realism to technical and managerial decisions that define a system's overall engineering strategy. This paper presents an introduction to processes and analytical practices in the management of risk, as it arises in the engineering of systems. These practices have evolved from a variety of systems engineering projects and initiatives. Traditional engineering systems and risk analysis approaches are discussed.
Methods of Risks Estimation and Analysis of Business Processes
Authors: Kijima Masaaki , Tanaka Keiichi
Published: September 2014

This chapter provides various alternatives to the Black–Scholes model for the pricing of derivative securities. The purpose of such extensions is to make pricing models more realistic in order to incorporate the so‐called smile effect and volatility clustering. Stochastic volatility and interest‐rate models as well as models with Levy processes are explained in detail.
Methods of Risks Estimation and Analysis of Business Processes
Authors: Balakrishnan N. , Naumov A. , Morgunov D.
Published: September 2014

In the paper the model of business processes of a data‐flow type and operations above them are entered into reviewing. The methods of the analysis of business processes on effectiveness are offered. The methods of an risk estimation and analysis of business processes are considered also. The task of risk estimation and using it on practice in managing economic systems with using processing approach is investigated. Conditional‐internal and conditional‐external risks are considered and proved their properties. Metrics of risks estimation are given as highest comparative and absolute losses, average losses etc. Inefficiency of using risk estimation procedures by dispersion and quantiles is shown. Approaches to the business‐processes indicators optimization proposed and investigated in the area “risk‐profit” (“risk‐indicator”). This optimization is realized by using utility function as multicriterion problem. Functional, stochastic dependences between risks are shown, that do not allow to optimize risks only (separate from indicators). The task of risk managing in economic systems is work out in complex with the tasks of it's analysis, modeling and optimization. The problem of factor analysis in deterministic form is investigated too.
Models for Bid Arrivals and Bidder Arrivals in Online Auctions
Authors: Russo Ralph P. , Shyamalkumar Nariankadu D. , Shmueli Galit , Jank Wolfgang
Published: September 2014

The arrival process of bidders and bids in online auctions is important for studying and modeling supply and demand in the online marketplace. Whereas bid arrivals are observable in online auction data, bidder behavior is typically not. A popular assumption in the online auction literature is that a homogeneous Poisson bidder arrival process is a reasonable approximation. This approximation underlies theoretical derivations, statistical models and simulations used in field studies. However, empirical research has shown that the process of bid arrivals is far from homogeneous, as it features early and last‐moment bidding, as well as a self‐similar structure. In this chapter we discuss two types of models: Descriptive models for bid arrivals that were derived based on features of real bid data in online auctions, and models for bidder arrivals that lead to the bid arrival process. The model for the bid arrival process, calledthe BARISTA process, can generate different intensities at different stages of the auctions. We discuss its properties, show how to simulate bid arrivals from it, and how to estimate its parameters. We then describe two bidder behavior models that lead to versions of the BARISTA process. Model adequacy and performance are illustrated via simulation and real data from eBay.
Advances in Robust Parameter Design: From Taguchi's Inner‐Outer Arrays to Combined Arrays
Authors: Evangelaras Haralambos , Koukouvinos Christos , Koutras Markos V.
Published: September 2014

Robust parameter design, originally proposed by Taguchi, is an off‐line technique for maintaining variance reduction and improving quality. According to Taguchi, product variation from the desirable target is affected by two types of factors: control factors and noise factors. The basic idea in robust parameter design is to identify the levels of the control factors so that the product's quality characteristic becomes insensitive to changes in the levels of the noise factors. As a consequence, the effect of uncontrollable variations on the response will be reduced.

Taguchi suggested the use of inner‐outer arrays with the control factors being assigned to an inner array and the noise factors assigned to an outer array. After the collection of the data, a performance measure called signal‐to‐noise ratio is calculated and analyzed in order to identify the optimal levels of the control factors. After the introduction of Taguchi's philosophy in the field of experimental design and data analysis, several new designs and techniques have been explored and adopted in this field. This chapter overviews well established approaches and analysis techniques that have been exploited to the robust parameter design field.
Applicability of Statistics and Probability Theory to Nucleate Pool Boiling Heat Transfer
Authors: Judd R.L. , Balakrishnan N.
Published: September 2014

Much has been learned about nucleate pool boiling over the last sixty years through experimental investigation and recently, it has become possible to predict the relationships governing the nucleation, growth and departure or collapse of bubbles computationally. However, it has not been possible to develop a theory capable of predicting the rate of heat transfer because of the inability to incorporate surface conditions in a comprehensive boiling heat transfer model. A method is proposed to simulate the surface conditions through the interactions of a large population of potentially active nucleation sites and a much smaller population of dominant nucleation sites using Monte Carlo simulation.
Degradation Models and Analyses
Authors: Meeker William , Hong Yili , Escobar Luis
Published: September 2014

For products/systems requiring high reliability or availability, reliability assessment and maintenance actions are often needed in a timely manner. For these systems/products, information on system state and performance can be collected over the system's operating time, providing what is known as degradation data. With appropriate models and data analysis techniques, degradation data are converted to system reliability information and this information is useful for short and long‐term reliability assessment and for planning maintenance actions. This article provides a review of degradation data models and methods that have been used successfully in this area. Commonly used methods for analyzing degradation data, general path models and stochastic models, are described in detail. Models and methods for analyzing data from accelerated degradation tests and accelerated destructive degradation tests are also introduced. Dynamic condition monitoring based on degradation data is covered. Examples are used to illustrate the models and methods covered in this article. The conclusion provides a discussion of test planning, software implementation and the future of degradation data analysis.
Pricing Foreign Exchange Options with Stochastic Volatility
Authors: Ahlip Rehez
Published: September 2014

An exhaustive survey of research on pricing foreign exchange options with stochastic volatility and stochastic interest rates is presented in this article. The article also includes contributions to pricing of currency options with fixed volatility and deterministic interest rates, domestic and foreign, and in a systematic way extend to results obtained for cases which include stochastic volatility and stochastic interest rates. Since the literature in pricing foreign exchange currency option is quite extensive, the article considers some of the more important contributions.
Step‐Stress Testing with Multiple Samples: The Exponential Case
Authors: Balakrishnan N. , Kamps Udo
Published: September 2014

Step‐stress models are descriptions of special experiments in the field of accelerated life testing, where the test units are exposed to stress levels that change at intermediate time points during the experiment. The goal is to develop inference for the mean lifetime at each stress level. The time points of stress level change can either be fixed or random. Furthermore, the experiment can be terminated when a certain number of failures is reached or at a pre‐specified time point. These alternative assumptions of the type of the experiment lead to alternative models. Usually the step‐stress models are based on a single experiment. We develop inference for step stress models designed for multiple samples. The stress levels are the same applied to all samples but the duration of exposure under each stress level can vary among the experiments.

The likelihood inference is then discussed in detail for the exponential case and different simple step‐stress experiments.
Cancer Stochastic Models
Authors: Tan Wai Y. , Chen Chao W.
Published: September 2014

In this article, we present an overview of cancer stochastic models. These models include single pathway models and multiple pathways models as well as state space models. To analyze these models, different mathematical approaches are reviewed and discussed. The results are illustrated by using a multievent model as an example.
Vaccine Studies, Statistics in
Authors: Datta Susmita
Published: September 2014

Statistical methodologies have been used in estimating the efficacy of a vaccine from field trials and observational studies. Dynamics of disease transmission interferes with the efficacy of a vaccine. This is a very brief summary of some statistical work related to vaccine studies, especially, in the context of HIV/AIDS vaccine.
Group‐Randomized Trials, Planning and Analysis of
Authors: Murray David M.
Published: September 2014

Planning a group‐randomized trial is a complex process. Care must be taken to delineate the research question, to create the research team, to plan the research design, to avoid potential design and analytic problems, to select variables of interest and their measures, to plan the intervention, and to ensure adequate power. Failure in any of these areas may lead to a dissappointing result; attention to each will increase the likelihood of success