bluuebunny/crossref_metadata_2025 huggingface dataset:
A forgotten biliary stent for 17 years: Presented with perforated gallbladder and stentolith
Authors: Patel Tejas J. , Rajput Sanjay , Patel K. S. , Haribhakti Sanjiv P.
Published: September 2014

Endoscopic biliary stent placement is a well-established, safe, and minimally invasive modality for the treatment of choledocholithiasis and other biliary diseases. Over the past decade, there has been an increase in its prevalence and use. We present an unusual case of forgotten biliary stent for 17 years who presented now with gangrenous cholecystitis and sealed the perforation. A large stentolith had also developed which was cleared with endoscopic retrograde cholengiography and re-stenting followed by laparoscopic cholecystectomy.
Initial Experience of Utilizing Real-Time Intra-Procedural PET/CT Biopsy
Authors: Aparici Carina Mari , Aslam Rizwan , Win Aung Zaw
Published: September 2014

Objectives:

Nonreal-time Positron Emission Tomography/Computed Tomography (PET/CT) biopsies that use the image co-registration of a prior PET with an intra-procedural CT have been reported. The aim of this study was to report the initial experience of performing real-time intra-procedural PET/CT-guided biopsies.

Materials and Methods:

All patients (n= 4) had a prior PET/CT examination of the concerning lesion and no significant CT correlate. On the day of the biopsy, 5 mCi of 18F-fluorodeoxyglucose (FDG) or NaF18 was intravenously injected. After 60 min of biodistribution of the molecular probe, PET/CT images were obtained in a limited one bed position over the region of the concerning lesion to be biopsied.

Results:

One patient had a mesenteric mass and the other three had bone lesions, one located in the rib and two in the iliac bone. The pathology report revealed that two lesions (50%) were malignant and two lesions (50%) were benign. The results of the biopsy changed management in all cases. There was 0% complication rate.

Conclusions:

No additional software or hardware is required to perform real-time intra-procedural PET/CT-guided biopsies. It can optimize the yield, especially in cases where there are no anatomical abnormalities. Real-time intra-procedural PET/CT biopsy may have benefits over conventional biopsy techniques in terms of accuracy.
A New Paradigm of Primary Health Care in Kazakhstan: Personalized, Community-based, Standardized, and Technology-driven
Authors: Sharman Almaz
Published: September 2014

This paper discusses the need for change from Kazakhstan’s current disease-centric healthcare paradigm to a new primary health and wellness-centric health care paradigm, technology-driven and based on personal relationships within a social context. While many different papers have been published about the importance of prevention and primary health care, few have focused on healthcare transition in Kazakhstan or other countries in Central Asia. The WHO’s historic 1978 Alma-Ata Declaration signed in Kazakhstan promoted the centrality of primary care to the provision of effective, efficient, and equitable health services. Modern technologies such as the Internet, social media, and portable medical devices democratize medicine, providing great opportunities to rethink the Alma-Ata Declaration and reinvent primary health care on an entirely new platform that is knowledge-based and technology-assisted. The new paradigm suggested for the future development of health in Central Asian region emphasizes personal relationships and encourages sustainable solutions created by communities. This paper also introduces HealthCity, a new project in Kazakhstan aiming at introducing private, community-based and standardized primary healthcare that is driven by SmartHealth innovative technology.
Os grupos de pressão formados por militares da reserva e o pensamento anticomunista
Authors: Santos Eduardo Heleno de Jesus , Alves Vágner Camilo
Published: September 2014

Este artigo apresenta alguns grupos de pressão formados por militares da reserva no Brasil, cuja linha ideológica tem forte discurso anticomunista. Esses grupos foram, em geral, constituídos após a redemocratização e uma de suas principais bandeiras é a defesa do status quo ante. Para melhor traçar a origem desses grupos, incluímos uma análise histórica para explicar como o anticomunismo ganhou expressividade dentro das Forças Armadas brasileiras.
El anticomunismo de la juventud conservadora chilena. el caso de la Falange Nacional (1935-1957)
Authors: Gomes Gabriela
Published: September 2014

A trajetória da Juventude Conservadora para a Falange Nacional expressou uma ruptura radical com o projeto político de um dos partidos da direita tradicional, o Partido Conservador (1851). Inspirado na doutrina do humanismo cristão, o projeto falangista se sintetizou no Partido Democrata Cristão (1957). Neste artigo se analisam quais foram as percepções dos falangistas sobre o comunismo e a importância atribuída ao Partido Comunista como um ator legítimo do sistema partidário.
O hábito faz a freira? frequência religiosa e autopercepção da religião no Brasil.
Authors: Rosas Nina , Muniz Jerônimo Oliveira
Published: September 2014

Utilizando a pesquisa Valores e Religião no Brasil (PVRB), este artigo apresenta dados sobre frequência e autopercepção religiosas de católicos e evangélicos. Embora os evangélicos sejam mais envolvidos com a religião que os católicos, surpreende que ambos sejam semelhantemente devotos na reza/oração e que, entre os evangélicos, os pentecostais e os históricos apresentem porcentagens de participação religiosa quase idênticas. Simula-se a distribuição das religiões brasileiras a partir do filtro de alta frequência e também a probabilidade de filiação a partir das práticas religiosas observadas. Os resultados evidenciam diminuição do grupo de católicos e aumento do de pentecostais em proporções maiores que as do Censo de 2010, e demonstram que a probabilidade de ser católico no Brasil independe da intensidade da prática religiosa adotada.
Structural Dynamic Study of Roof Waterproofing Materials
Authors: Kemalov Alim Feizrakhmanovich , Kemalov Ruslan Alimovich , Valiev Dinar Zinnurovich , Abdrafikova Ilmira Maratovna
Published: September 2014

The present research was aimed to develop the scientific applied principles and technologies of composite bituminous materials for civil engineering based on the investigation of the structures of polymer modifier and bitumen-polymer binder (BPB) on its basis with the use of nuclear magnetic resonance (NMR). The method of pulsed NMR was chosen as one of the rapid analysis methods that can be used for the analysis of bitumen-polymer systems, especially when assessing the group chemical composition of residual oil feedstock (ROF), bitumens and composite materials based on them. Using the method of pulsed NMR the regularities of the impact of modifier component composition on the changes of structural-group composition of the original and modified products were specified. Based on the results of research the optimal ratio of bitumen-polymer binder components was investigated, the manufacturability of the process for obtaining of composite bituminous materials for civil engineering with the aim of optimizing the quality of the final products was evaluated. Pulsed NMR - spectroscopy is suggested as input and output quality control of bituminous products. The regularities of redistribution of the phases with different molecular mobility and their relationship with the binder components were investigated. Rapid technique for quantifying the content of polymer in the solvent was developed.
Efficiency Analysis of Low Power Class-E Power Amplifier
Authors: Yousefi Mousa , Koozehkanani Ziaadin Daie , Sobhi Jafar , Jangi Hamid , Nasirezadeh Nasser
Published: September 2014

This paper presents an analysis of effect of inductor and switch losses on output power and efficiency of low power class-E power amplifier. This structure is suitable for integrated circuit implementation. Since on chip inductors have large losses than the other elements, the effect of their losses on efficiency has been investigated. Equations for the efficiency have been derived and plotted versus the value of inductors and switch losses. Derived equations are evaluated using MATLAB. Also, Cadence Spectre has been used for schematic simulation. Results show a fair matching between simulated power loss and efficiency and MATLAB evaluations. Considering the analysis, the proposed power amplifier shows about 13 % improvement in power effiency at 400 MHz and -2 dBm output power. It is simulated in 0.18 ?m CMOS technology.
About the Method of Analysis of Economic Correlations by Differentiation of Spline Models
Authors: Ilyasov Ruslan Hizrailevich
Published: September 2014

The article considers spline approximation as one of efficient methods of modeling economic dynamics. Spline approximation of economic dynamics allows carrying out qualitative and accurate transition from discrete values of a lattice function to a continuous model of a process, which allows calculating values of a studied index at any time point (interpolation). Spline representation improves the quality of economic dynamics modeling while saving the real values of the studied process at each time point. In this article, differentiation of spline models is used for analysis of the economic indexes growth rate. Correlations are detected and itemized by comparison of derivatives. The possibility of detecting "latent trends" is demonstrated by differentiation of spline models of the dynamics using the example of economic indexes of the oil and gas market of Russia. For example, in the first case, we consider spline models of the dynamics of export prices for oil and natural gas. Here, the correlation of the studied indexes is obvious and is detected by both calculation of the correlation ratio and visualization of the studied rows of dynamics with spline models. As an opposite example, we consider the dynamics of the volumes of oil and natural gas export. In this case, we gain the correlation ratio close to zero, which is to evidence absence of correlation. Modeling of the studied dynamics with cubic splines also does not detect any correlation between the dynamics of volumes of the oil and gas export. Our assumptions about "latent trends" are also confirmed by differentiation of spline models – the correlation between the change rate of the volumes of the oil and gas export is detected. Use of spline functions at economic dynamics modeling is determined with such positive properties of theirs as continuity, flexibility, differentiability, the property of minimal curve, etc.
Vision-Based Row Detection Algorithms Evaluation for Weeding Cultivator Guidance in Lentil
Authors: Behfar Hossein , Ghasemzadeh HamidReza , Rostami Ali , Seyedarabi MirHadi , Moghaddam Mohammad
Published: September 2014

It is important to detect crop rows accurately for field navigation. In order to accurate weeding, cultivator guidance system should detect the crop center line precisely. The methods of vision-based row detection for lentil field were studied. Monochrome and color images were used in this research. The color images are transformed into grey scale images in two different formulas to make comparing among them and find an optimal one. In order to detect the center of the crop row rapidly and effectively, Hough transform and gravity center image processing algorithms were applied to acquired images. The field crop images were segmented into two parts by using optimal thresholding (plant and soil as a background), then Hough transform was applied on these binary images. Gray scale images were used in gravity center method. The center line detection algorithms were tested for two weed distribution density, include general and intensive. It was observed that both systems successfully detects and calculates the pose and orientation of the crop row on synthetic images. The mean errors between the calculated and manually estimated lines were obtained. Mean errors for Hough transform and gravity center methods were 8 and 10 mm with standard deviations of 7 and 12 mm in general distribution density and 12 and 16mm with standard deviation of 11 and 15mm in high distribution density, respectively. Computational time for Hough transform and gravity center were 0.7 and 0.4 s for general distribution density and 1.2 and 0.8 s for high distribution density, respectively.
Proper Insulated Materials for Temperature Accumulation in Box Technology to Catalyze the Organic Digestion Processing on Community Garbage Disposal
Authors: Chanthasoon Chulabut , Chunkao Kasem
Published: September 2014

The research is aimed to determine the appropriate insulated materials and the thickness of insulated boxes for keeping in-box temperature around 70 oC. The experiments were conducted by taking amount of 500 g river gravels (number 3) to heat in Hot air oven at 100 oC for 24 hours before putting in the 0.027 m3 (30x30x30 cm) insulated boxes. The in-box (T1) and out-box (T2) ambient air temperature were recorded by automatic data locker from beginning to the end of experiments. The relationship between time (t) and in-box temperature by graphical techniques in order to select the appropriate insulated material under the criterions of The King's Royally initiative nature-by-nature process, simplicity technology, and low expense (or local materials using for constructing technology), Also, the relations between Q (heat conduction) of temperature differences (in-box and outside box) in varying time (t) as same as the insulated material thickness was evaluated from graphical products of fixing T1 (equivalent to 70 oC) and Q of varying ambient air temperature. The results found that rice straw as the appropriate insulated material tether with the minimum rice-straw insulated thickness of 6 cm in which the in-box temperature could be kept long enough for psychrophiles, mesophiles, thermophiles, and hyper-thermopile to complete the digestion of carbohydrates, proteins, celluloses, hemicelluloses, and fibers. Moreover, the research result was also pointed out the values of ambient air temperature (from -10 oC to 70 oC) is inversely related to thickness of the rice-straw insulated boxes, by taking the minimum thickness of 6 cm for T2 equivalent to 30 oC.
Assessment of Toilet’s Indoor Air Quality in Relation to Asthmatic People
Authors: Rahman Ismail Abdul , Putra Jouvan Chandra Pratama , Asmi Ade
Published: September 2014

This paper presents an assessment on toilet’s indoor air quality on asthmatic people. The assessment was carried out by measuring temperature, relative humidity, air velocity and SO2 in the 4 selected toilets which are naturally ventilated. The measurements used two equipments that are Yes Plus LGA meter and Anemometer. It was done in early morning and break hours for 10 minutes within three (3) days consecutively. This study found that SO2 concentration in toilet 1 exceeded the threshold limit value of SO2 for 10 minutes exposure which means this toilet potentially trigger asthmatic symptom for those asthmatic people who frequently used this toilet. High concentration of SO2 was due to inadequacy of air velocity in this toilet. Inadequacy of air velocity means less ventilation and thus, increased the humidity which can stimulate the growth of fungi/mold in the toilet that affects asthmatic people.
The Economic Value of Laem Phak Bia Mangrove Ecosystem Services in Phetchaburi Province, Thailand
Authors: Wiwatthanapornchai Sitthinan , Piputsitee Chucheep , Boonyawat Samakkee
Published: September 2014

Thailand is a one of the nation in Southeast Asia, covered by numerous mangrove areas approximately 244,000 hectares. Phetchaburi province is the one of the province in Thailand where the mangrove area has been increasing continually since King’s Royally Initiated Laem Phak Bia Environmental Research and Development Project has been set up. The mangrove ecosystems functions are vital to the livelihood of the surrounding community. Laem Phak Bia community is one that has been served from mangrove ecosystem services. This study assessed the economic value of Laem Phak Bia mangrove ecosystem services in an area approximately 237.44 hectares using Participatory Economic Valuation (PEV) by the villagers ranking and rating the importance of mangrove ecosystem services with a valuable thing for living that is the rice value. The results showed that this mangrove area was worth a total economic value about 100 million Baht per year or 424 thousand Baht per hectares per year. It could be divided into the value of regulation functions, production functions, habitat functions and information functions, which were about 38, 8, 25, and 29 million Baht per year, respectively.
Reliability Worth Assessment in Composite Power System Planning and Operation
Authors: Dalabeeh Ali Khraiwish , Al-Hajbi Eng.Hani Hasan Saleh
Published: September 2014

This study presents a comprehensive procedure for evaluating the reliability indices incorporating reduction in interruption cost, and to relate reliability investments with customer’s benefits. An analytical algorithm is used to obtain the final optimal operational solution by determining unit commitment for each generating unit to reach the maximum profit (minimizing cost) subjected to operational constraints. The paper describes a method based on the complementing short-term planning with long-term planning take into account the cost benefit approach. The proposed method has been demonstrated on the RBTS to show the feasibility and the economic effect of the proposed method, and was applied to the Jordanian Electric Power System (JEPS) to show its application capability.
Interference in Wireless Networks: Causes, Analyses and Practical Mitigating Techniques
Authors: Hameed A. , Oudah Ali
Published: September 2014

This paper addresses the key characteristics of interference in wireless networks. Moreover, it considers the impact of interference from Code Division Multiple Access base station to Wideband-Code Division Multiple Access one. A detailed discussion of major interference mitigation techniques in wireless networks, in general, and CDMA and W-CDMA systems, in particular is also imparted on. The techniques and findings in this paper can be easily used in the analyses of other wireless technologies.
Production of dissolved organic carbon enriched in deoxy sugars representing an additional sink for biological C drawdown in the Amazon River plume
Authors: Meador Travis B. , Aluwihare Lihini I.
Published: September 2014

In North Atlantic waters impacted by discharges from the Amazon and Orinoco Rivers, where planktonic diatom‐diazotroph associations (DDA) were active, we observed that an average (± standard deviation) of 61 ± 12% of the biological drawdown of dissolved inorganic carbon (DIC) was partitioned into the accumulating total organic carbon pool, representing a flux of up to 9 ± 4 Tg C yr−1. This drawdown corresponded with chemical alteration of ultrafiltered dissolved organic matter (UDOM), including increases in stable C isotopic composition (δ13C) and C:N. The dissolved carbohydrate component of UDOM also increased with biological DIC drawdown and diatom‐associated diazotroph (i.e., Richelia) abundance. New carbohydrates could be distinguished by distinctively high relative abundances of deoxy sugars (up to 55% of monosaccharides), which may promote aggregate formation and enhance vertical carbon export. The identified production of non‐Redfieldian, C‐enriched UDOM thus suggests a mechanism to explain enhanced C sequestration associated with DDA N2 fixation, which may be widespread in mesohaline environments.
New frequency‐based real‐time magnitude proxy for earthquake early warning
Authors: Ziv A.
Published: September 2014

The two frequency‐based magnitude proxies currently employed by earthquake early warning systems in California are the predominant and the characteristic periods. These proxies, obtained using simple expressions that are valid for noise‐free monochromatic signals, yield erroneous result. The log‐average period, τlog, introduced in this study, is calculated directly from the actual velocity spectrum of the first few seconds of the seismic record. Using data from South California and Japan consisting of 440 earthquakes whose magnitudes range between 3 and 7.3, it is demonstrated that τlog is better correlated with the catalog magnitude than the predominant period and provides better magnitude assessment than the characteristic period for small magnitudes (M<4). The average prediction error is reduced with increasing the input interval up to 6 s. It appears that a single linear scaling describes the relation between log(τlog) and the catalog magnitude for the entire magnitude range studied here.
Modeled dependence of wind and waves on ocean temperature in tropical cyclones
Authors: Phibbs Samuel , Toumi Ralf
Published: September 2014

A coupled ocean‐atmosphere‐wave model is used to investigate the sensitivity of surface wind speed and significant wave height to ocean temperature for idealized tropical cyclones (TCs). More intense and larger TCs, with higher waves, form when ocean temperature is increased. The maximum significant wave height increases more than the maximum wind speed for TCs up to hurricane force wind. However, above hurricane force wind the change in maximum wind speed is similar or greater than the change in maximum significant wave height. This can be explained by the wind drag coefficient decreasing as wind speed exceeds hurricane force wind, so that the growth of waves is dampened. The areal footprint of wave height grows considerably more than the maximum as ocean temperature is increased. This suggests a large increase in the surface area of damaging waves generated by TCs may be the dominant impact of a future warmer ocean.
Development of fine‐resolution analyses and expanded large‐scale forcing properties: 1. Methodology and evaluation
Authors: Li Zhijin , Feng Sha , Liu Yangang , Lin Wuyin , Zhang Minghua , Toto Tami , Vogelmann Andrew M. , Endo Satoshi
Published: September 2014

We produce fine‐resolution, three‐dimensional fields of meteorological and other variables for the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The Community Gridpoint Statistical Interpolation system is implemented in a multiscale data assimilation (MS‐DA) framework that is used within the Weather Research and Forecasting model at a cloud‐resolving resolution of 2 km. The MS‐DA algorithm uses existing reanalysis products and constrains fine‐scale atmospheric properties by assimilating high‐resolution observations. A set of experiments show that the data assimilation analysis realistically reproduces the intensity, structure, and time evolution of clouds and precipitation associated with a mesoscale convective system. Evaluations also show that the large‐scale forcing derived from the fine‐resolution analysis has an overall accuracy comparable to the existing ARM operational product. For enhanced applications, the fine‐resolution fields are used to characterize the contribution of subgrid variability to the large‐scale forcing and to derive hydrometeor forcing, which are presented in companion papers.
Image Processing
Authors: Cressie Noel , Davidson Jennifer L.
Published: September 2014

Image processing consists of operations on an image whose result is another image. This article reviews many of these, placing particular emphasis on mathematical and statistical operations. Statistical image processing considers operations that can be evaluated according to their expected loss, which is a criterion that compares any estimated image to the true image. As the true image is unknown, a probability distribution (e.g., a Markov random field) is postulated for it, which is sometimes called theprior distributionof the image. Then, from the prior and the noise distribution of the observed image given the true image, the posterior distribution can be obtained from Bayes’ theorem. This distribution, of the true image given the noisy image, is high dimensional and may be difficult to calculate in practice. Statistically optimal algorithms that restore, segment, reconstruct, or extract features of an image are obtained by minimizing the posterior expected loss, where the loss function may depend on the operation being considered. Other topics covered include mathematical morphology, histogram equalization, boundary detection, feature extraction, and pattern recognition. Copyright © 2015 John Wiley & Sons, Ltd.
Computer Vision, Statistics in
Authors: Chellappa Rama , Roy Chowdhury Amit K.
Published: September 2014

Computer Vision (CV) broadly refers to the discipline where extraction of useful 2D and/or 3D information from one or more images is of interest. Useful information could consist of features such as edges, lines, curves and textures, or information about depth, motion, object descriptions, etc. CV problems are usually ill‐posed inverse problems. Since the image data is usually obtained from sensors such as video cameras, infrared, radar, etc., the information extraction processes often have to deal with data that is corrupted by noise from the sensors and the environment. Statistics can help in obtaining robust and accurate solutions to these inverse problems by modeling the noise processes. We present here a broad overview of the applications of statistics to different computer vision problems and explain in detail two particular applications, tracking and motion analysis, where statistical approaches have been used very successfully.
Stochastic Resonance
Authors: Bulsara Adi R.
Published: September 2014

Noise is usually considered a nuisance or a laboratory curiosity, better avoided, in most practical applications. However, certain nonlinear dynamic systems in nature (the most ubiquitous of these being, of course, the central nervous system) appear to utilize the background noise as an aid to the analysis of low‐intensity signals embedded in the noise floor. A phenomenon known as stochastic resonance (SR) has been studied in the context of this amplification of weak signals in a noise background; the effect is only one of a plethora of diversified behavior that is displayed by nonlinear dynamic systems in the presence of noise, and can actually lead to an energy transfer from the noise floor to the signal feature (in the response), under the appropriate operating conditions.
SemiParametric Analysis of Competing Risks Data
Authors: Sundaram Rajeshwari , Balakrishnan N.K.
Published: September 2014

Competing risks data are typically encountered in biomedical/epidemiological studies. Examples of such data can be found in studying labor in women as labor can be either spontaneous or due to medical intervention (example: delivery by cesarean) or due to membrane rupture leading to labor. Typically in competing risks framework, each individual is exposed to K distinct types of risks and the eventual failure can be attributed to precisely one of the risks. As is usual in survival data, these competing risks data are further subjected to censoring. Two quantities of considerable interest include, the cause‐specific hazard and the corresponding cumulative incidence function for a specific cause. In this article, we will review various modeling approaches for assessing the effects of covariates through modeling cause‐specific hazard. We will also discuss various approaches for constructing confidence intervals as well as confidence bands for the cause‐specific cumulative incidence function of subjects with given values of the covariates.
Group Sequential Methods in Biomedical Research
Authors: Liu Aiyi , Liu Chunling , Yu Kai F.
Published: September 2014

Group sequential methods have become a common practice in biomedical research due to various reasons such as ethical, administrative, and economic concerns. In testing statistical hypotheses a group sequential procedure allows the hypotheses to be tested repeatedly at several time points after a group of observations have been completed.

The sequential methods pose great challenges to statisticians. These challenges include not only finding appropriate methods of determining critical values at each interim test to control error rates such as false positive/negative rate, but also developing efficient inferential procedures for secondary analysis such as estimation, confidence intervals,p‐values and secondary endpoints. This is because the data‐based random stopping of the sampling process introduces bias to conventional procedures that are appropriate in a non‐sequential (fixed‐size) setting.

In the context of Brownian motion as approximation to various test statistics, this article presents an overview of several common group sequential testing procedures, and methods for computing point estimation, confidence intervals, andp‐values.
Statistical Quality of Life
Authors: Mesbah Mounir
Published: September 2014

Health Related Quality of Life (HrQoL) is a latent variable, indirectly observed through individual responses to a set of questions (items) forming the HrQoL questionnaire. The first part of the paper is about its measurement which remains a complex issue. This measurement process is done via instruments (questionnaires) which are validated through the intermediary of some fundamental models, mainly based on unidimensionality principle and some specific conditional independence properties. We explain how these measurement models are statistically validated, and how measurements they provide must be statistically analyzed in studies involving other external variables. Finally, a few important recent issues in the field are presented.
Statistical Modeling of Human Fecundity
Authors: Sundaram Rajeshwari , Buck Louis Germaine M. , Kim Sungduk
Published: September 2014

Human fecundity is of great interest to reproductive scientists, as well as to couples trying to conceive. It is measured by the probability of pregnancy in a menstrual cycle for a sexually active couple who is not contracepting. Reproductive epidemiologists are interested in models for human fecundity to identify the determinants and to identify preventable causes of reproductive dysfunction. There is also suspicion that various environmental factors negatively affect the human fertility. Motivated by these issues, there has been considerable interest in developing biologically precise statistical models for human fecundity. This chapter begins with a brief discussion of various biological and behavioral factors that potentially impact pregnancy. Furthermore, emphasis is made on various biological and behavioral factors that impact pregnancy but are not measurable. Next, we review various statistical models for pregnancy that are available in literature, with emphasis on models that are biologically relevant. We also indicate some outstanding issues that need to be addressed to build stronger statistical models that are biologically valid. We conclude with an analysis of the New York Anglers Cohort Prospective Pregnancy study.
Estimation of Travel Distance
Authors: Brimberg Jack , Walker John H.
Published: September 2014

In this chapter we discuss the use of empirical distance functions in business models. The traditional role of distance functions has been to estimate travel distances or times in a given transportation system. We examine the properties of distance functions that make them useful in this role, and review popular ones such as the Euclidean norm, rectangular (or Manhattan) norm, and the more general weighted ℓpnorm and block norm. Statistical methods used to estimate the parameters of an empirical distance function from actual travel distance data are presented. This includes a review of the various goodness‐of‐fit criteria appearing in the literature, and a discussion of their error term distributions. The usefulness of empirical distance functions in modeling service systems of ever‐increasing size and complexity, and their growing relevance in operational and strategic decision processes, are also investigated. Future areas of research are identified in closing.
Mining Functional Data in Prediction Markets
Authors: Foutz Natasha Zhang , Jank Wolfgang
Published: September 2014

Prerelease demand forecasting is one of the most crucial yet difficult tasks facing marketers in the $60 billion motion picture industry. We propose functional data analysis of prediction markets to address this long‐standing challenge. In prediction markets, prices of a movie's stock reflect the dynamic demand expectations prior to the movie's release. Using functional data analysis, we identify a small number of distinguishing shapes, e.g., the last‐moment velocity spurt, that carry information about a movie's future demand and produce early and accurate prerelease forecasts.
Directional Statistics: Introduction
Authors: Jammalamadaka S. Rao
Published: September 2014

In many natural and physical sciences the measurements are directions—either in two‐ or three‐dimensions. This chapter briefly introduces this novel area of statistics, and provides a good starting point for further exploration. A basic parametric model called the Fisher‐von Mises distribution is introduced and nonparametric methods such as goodness of fit tests are discussed. Further references are given for exploring related topics such as correlation and regression.
Optimal Sample Size Allocation for Accelerated Degradation Test Based on Wiener Process
Authors: Tseng Sheng‐Tsaing , Tsai Chih‐Chun , Balakrishnan N.
Published: September 2014

Degradation tests are widely used to assess the reliability of highly reliable products which are not likely to fail under traditional life tests or accelerated life tests (ALT). However, for some highly reliable products, the degradation may be very slow, and thus it seems impossible to have a precise assessment within a reasonable test time. In such cases, an alternative technique is to use higher stresses to extrapolate the product's reliability at the normal use stress. This is called an accelerated degradation test (ADT). In this article, motivated by a LEDs data, we discuss the optimal allocation problem under accelerated degradation experiment when a Wiener process is used to describe the product's degradation path. We derive the Fisher information and the approximate variance of the estimated mean‐time‐to‐failure (MTTF) under normal use. Three optimality criteria are defined and the optimal allocation of test units are determined. Finally, the LEDs data is illustrated to demonstrate the efficiency of the optimal allocation of test units.
Statistical Models for Damage Accumulation
Authors: Castillo Enrique , Fernández‐Canteli Alfonso
Published: September 2014

As an initiation to the damage accumulation problem, different damage measures are presented, including a discussion of the properties that should be expected from these measures when not only mean values but uncertainties are required. Next, the role played by the Buckingham theorem and similarity and self‐similarity conditions in the process of building models is justified. Special attention is devoted to dynamic system based models, the assumptions of which are described and discussed together with the corresponding implications on the resulting models. Since building models based on their expected properties more than on artificial assumptions are defended, the technique of functional equations, a very innovative and powerful mathematical tool, is used to represent these properties and to obtain the resulting models. An illustration is given to derive the S‐N models that allow the effect of stress level and range on the fatigue life to be considered and the associated uncertainty to be defined. Similar procedures are applied to the derivation of crack growth and crack growth rate models. Due to the practical importance of the load history, the rainflow counting technique is described using the stress level to define the rainflow matrix. Finally, an example of application and final remarks are provided.
Bayesian Networks
Authors: Castillo Enrique , Hadi Ali S.
Published: September 2014

Many practical applications require the specification of the joint probability density (JPD) of a large set of random variables. This task can be very difficult in practice. Bayesian and Markov networks are two graphically based models that make the specification of the JPD and the propagation of uncertainty simple and efficient because they exploit the conditional independence structure of the JPD. This entry deals with Bayesian networks, also known as Belief networks. Markov networks are discussed in another entry. Bayesian networks are defined and their usefulness is illustrated by examples of the two most commonly used Bayesian networks, namely, the multinomial and Gaussian networks. The questions about how Bayesian networks can be constructed, how Bayesian networks can be learnt from data, and how uncertainty can be propagated when new evidence becomes available are also discussed.
Epidemiological Statistics ‐ Further Issues
Authors: McNeil Don
Published: September 2014

Epidemiological studies use statistical methods to understand the factors that cause, reduce, and prevent diseases in human populations. These studies estimate the parameters in a target population based on representative samples, and can be qualitative or quantitative, descriptive or comparative, and observational or experimental. Parameters of interest include levels of disease and associations between risk factors and disease outcomes. Concept maps are useful for showing causal paths between risk factors, disease outcomes, and intervening variables (confounders) that could distort the association. The statistical methods can be classified by the type and role of the data, and are subject to both inaccuracy or lack of statistical power (due to sampling variability) and bias (due to faulty measurement, differential selection of subjects, or confounding). Matching of subjects can improve accuracy. Mantel–Haenszel methods can reduce confounding bias. Meta‐analysis is used to combine results from different studies. Statistical models include linear, logistic, and Poisson regression, and the proportional hazards model for handling censored data.
Spacings, Linear Combinations of
Authors: Huffer Fred W. , Lin Chien‐Tai
Published: September 2014

Problems involving the distribution of linear combinations of spacings occur in many areas of statistics. This article gives expressions for the density and distribution function of an arbitrary linear combination of spacings. General methods are also presented for computing the distribution of the maximum or minimum of any finite collection of linear combinations of spacings. When the coefficients of the linear combinations are rational, these methods can be implemented on computer algebra systems to produce exact symbolic expressions for the distributions. These expressions can be used to compute numerical answers accurate to any required degree of precision.
Stirling Numbers and Generalizations
Authors: Charalambides Ch. A.
Published: September 2014

The Stirling numbers of the first and second kind enumerate the permutations of a finite set that are decomposed into a given number of cycles and the partitions of a finite set into a given number of subsets, respectively. Basic properties of these numbers and their generalizations of probabilistic and statistical interest are reviewed. Specifically, explicit expressions, generating functions, recurrence relations, and other useful properties of these numbers are presented. Further, the Lah numbers and the generalized factorial coefficients, closely related to the Stirling numbers, are discussed. The noncentral and the associated Stirling and related numbers are briefly presented. The generalized Stirling and Lah numbers and, in particular, the
q
‐Stirling and
q
‐Lah numbers are only quoted. Probabilistic and statistical applications of the Stirling and related numbers in expressing the probability mass function of certain (a) urn‐model distributions, (b) occupancy distributions, (c) convolutions of truncated discrete distributions and (d) compound discrete distributions are exemplified.
Concave and Log‐Concave Distributions
Authors: Sengupta Debasis
Published: September 2014

This article deals with the context, scope, properties, applications and inference of concave and log‐concave distribution functions. These two classes of distributions are compared and contrasted with other related classes. It is shown that such distributions can arise from a variety of situations. Characterizations as well as closure and other properties of these classes are reviewed. Discrete versions of these classes and relation with their continuous counterparts are discussed. Implications of log‐concavity of a distribution function in various fields are mentioned. Sharp inequalities for the concave and log‐concave distribution functions having support on the positive real line are provided. Literature on estimation of concave distribution functions is briefly reviewed.
Binomial Distribution: Sample Size Estimation
Authors: Grevstad Nels
Published: September 2014

The need to estimate the sample size parameternin the binomial distribution arises in many practical problems, such as estimating wildlife population sizes based on sample counts. Attempts to find reasonable estimators can be traced back to the early 1900s, when the method of moments estimator was proposed. But the method of moments estimator, as well as the maximum likelihood estimator, suffers serious shortcomings in terms of performance, not the least of which is a highly unstable behavior. Following a few examples and a brief history of the problem, this entry details some of the difficulties that arise when estimatingn, and presents the results of attempts that have been made to overcome those difficulties either by modifying the method of moments or maximum likelihood estimator, or adopting a Bayesian approach.
Delta Method, Infinite Dimensional
Authors: Römisch Werner
Published: September 2014

The infinite‐dimensional delta method including higher order and set‐valued variants is presented. The relevant underlying material on weak convergence, Hadamard directional derivatives and on hyperspaces of closed sets is discussed. Some examples of Hadamard directional differentiable functions and of the delta method, including M‐estimation, are given.
Margin of Error
Authors: Vidakovic Brani
Published: September 2014

Margin of Error is a half of the length of a 95% confidence interval.
K
riging, Simple Indicator
Authors: Solow Andrew
Published: September 2014

Simple indicator kriging is a method for interpolation in a binary random field. The method is based on estimates of the first two moments of the field. It has been shown to perform well when the binary field is formed by clipping a Gaussian random field.
U

‐ and

V

‐Statistics
Authors: Shieh Grace S.
Published: September 2014

This article reviews the development of
U
‐ and
V
‐statistics from mid‐1990s to 2001. Three categories of new results are reviewed: (1) asymptotic behavior of
U
‐ and
U
‐related statistics, (2) asymptotic distribution theory (including asymptotic distribution, Berry‐Esseen theorem, and Edgeworth expansion), and (3) a new subclass,
U
‐statistics with a kernel of indeterminate degeneracy.
Hazard Regression
Authors: Kooperberg Charles , Stone Charles J. , Truong Young K.
Published: September 2014

Hazard regression (HARE) is a regression methodology using linear splines to model the conditional log‐hazard function based on possibly censored survival data with one or more covariates. The methodology is inspired by the adaptive multiple regression methodologyMARS.HAREdoes not assume the proportionality used in the Cox model, but it contains proportional models as a special case. It provides great flexibility in modeling covariate effects and the hazard function using polynomial splines and stepwise addition and deletion of basis functions. Copyright © 2015 John Wiley & Sons, Ltd.
Hazard Rate Estimation
Authors: Veraverbeke Noël
Published: September 2014

The literature on the topic of hazard rate estimation is reviewed. Most results are developed for randomly right censored sample data and the most popular estimators are of the kernel type. The choice of the smoothing parameter is an important issue. The incorporation of covariate information is also considered.
Dependence, Kent‐O'Quigley Measure
Authors: Nadarajah Saraless , Kotz Samuel
Published: September 2014

A dependence measure attributable to Kent and O'Quigley and some of its properties are discussed.
Markov Networks
Authors: Castillo Enrique , Hadi Ali S.
Published: September 2014

Many practical applications require the specification of the joint probability density (JPD) of a large set of random variables. This task can be very difficult in practice. Bayesian and Markov networks are two graphically based models that make the specification of the JPD and the propagation of uncertainty simple and efficient because they exploit the conditional independence structure of the JPD. This entry deals with Markov networks. Bayesian networks are discussed in another entry. Markov networks are defined and the questions about how Markov networks can be constructed, how Markov networks can be learnt from data, and how uncertainty can be propagated when new evidence becomes available are also discussed.
Graph‐Theoretical Methods
Authors: Quiroz Adolfo J.
Published: September 2014

The use of graph‐theoretical structures, principally the Minimal Spanning Tree and thekNearest Neighbors Graph, allows the multivariate generalization of certain nonparametric statistical procedures and suggests the consideration of new ones. The areas of statistical application of graph theoretic procedures include the two‐sample problem, clustering, outlier identification, hypothesis testing, and dimension identification.
Weak Records
Authors: Stepanov Alexei
Published: September 2014

In this survey, we discuss major developments of the past decades in the study on weak records.
Statistical Methods in Inventory Effect and Analysis
Authors: Lien Donald
Published: September 2014

Inventory effect suggests that the correlation between spot and futures prices is positively related to the inventory level. It was proposed to be a possible explanation for backwardation equilibrium in futures markets. A test for the inventory effect requires the specification of the joint distribution between spot and futures prices. This chapter summarizes four approaches currently available in the literature: bivariate normal distributions, bivariate log‐normal distributions, ordered bivariate normal distributions, and ordered bivariate log‐normal distributions. These approaches generate different conclusions, indicating the result is not robust to the distribution assumption. As a consequence, the inventory effect may prevail in some commodity markets but not in others.
Partial Least Squares Regression
Authors: Helland Inge
Published: September 2014

Partial least squares regression was introduced as an algorithm in the early 1980s, and it has gained much popularity in chemometrics. PLSR—or PLSR1—is a regression method for collinear data, and can be seen as a competitor to principal component regression. The method makes it possible to combine prediction with a study of a joint latent structure in thex,y‐variables. PLSR2 is a generalization to several dependent variables. PLSR1 can be understood from a statistical point of view via its parameter algorithm and the corresponding population model.