A new approach to spatial data interpolation using higher-order statistics

Interpolation techniques for spatial data have been applied frequently in various fields of geosciences. Although most conventional interpolation methods assume that it is sufficient to use first- and second-order statistics to characterize random fields, researchers have now realized that these methods cannot always provide reliable interpolation results, since geological and environmental phenomena tend to be very complex, presenting non-Gaussian distribution and/or non-linear inter-variable relationship. This paper proposes a new approach to the interpolation of spatial data, which can be applied with great flexibility. Suitable cross-variable higher-order spatial statistics are developed to measure the spatial relationship between the random variable at an unsampled location and those in its neighbourhood. Given the computed cross-variable higher-order spatial statistics, the conditional probability density function (CPDF) is approximated via polynomial expansions, which is then utilized to determine the interpolated value at the unsampled location as an expectation. In addition, the uncertainty associated with the interpolation is quantified by constructing prediction intervals of interpolated values. The proposed method is applied to a mineral deposit dataset, and the results demonstrate that it outperforms kriging methods in uncertainty quantification. The introduction of the cross-variable higher-order spatial statistics noticeably improves the quality of the interpolation since it enriches the information that can be extracted from the observed data, and this benefit is substantial when working with data that are sparse or have non-trivial dependence structures.

The global epidemiology and contribution of cannabis use and dependence to the global burden of disease: results from the GBD 2010 study

Aim Estimate the prevalence of cannabis dependence and its contribution to the global burden of disease. Methods Systematic reviews of epidemiological data on cannabis dependence (1990-2008) were conducted in line with PRISMA and meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. Culling and data extraction followed protocols, with cross-checking and consistency checks. DisMod-MR, the latest version of generic disease modelling system, redesigned as a Bayesian meta-regression tool, imputed prevalence by age, year and sex for 187 countries and 21 regions. The disability weight associated with cannabis dependence was estimated through population surveys and multiplied by prevalence data to calculate the years of life lived with disability (YLDs) and disability-adjusted life years (DALYs). YLDs and DALYs attributed to regular cannabis use as a risk factor for schizophrenia were also estimated. Results There were an estimated 13.1 million cannabis dependent people globally in 2010 (point prevalence0.19% (95% uncertainty: 0.17-0.21%)). Prevalence peaked between 20-24 yrs, was higher in males (0.23% (0.2-0.27%)) than females (0.14% (0.12-0.16%)) and in high income regions. Cannabis dependence accounted for 2 million DALYs globally (0.08%; 0.05-0.12%) in 2010; a 22% increase in crude DALYs since 1990 largely due to population growth. Countries with statistically higher age-standardised DALY rates included the United States, Canada, Australia, New Zealand and Western European countries such as the United Kingdom; those with lower DALY rates were from Sub-Saharan Africa-West and Latin America. Regular cannabis use as a risk factor for schizophrenia accounted for an estimated 7,000 DALYs globally. Conclusion Cannabis dependence is a disorder primarily experienced by young adults, especially in higher income countries. It has not been shown to increase mortality as opioid and other forms of illicit drug dependence do. Our estimates suggest that cannabis use as a risk factor for schizophrenia is not a major contributor to population-level disease burden.

Angular dependence of the response of the nanoDot OSLD system for measurements at depth in clinical megavoltage beams

Purpose The purpose of this investigation was to assess the angular dependence of a commercial optically stimulated luminescence dosimeter (OSLD) dosimetry system in MV x-ray beams at depths beyondd max and to find ways to mitigate this dependence for measurements in phantoms. Methods Two special holders were designed which allow a dosimeter to be rotated around the center of its sensitive volume. The dosimeter's sensitive volume is a disk, 5 mm in diameter and 0.2 mm thick. The first holder rotates the disk in the traditional way. It positions the disk perpendicular to the beam (gantry pointing to the floor) in the initial position (0°). When the holder is rotated the angle of the disk towards the beam increases until the disk is parallel with the beam (“edge on,” 90°). This is referred to as Setup 1. The second holder offers a new, alternative measurement position. It positions the disk parallel to the beam for all angles while rotating around its center (Setup 2). Measurements with five to ten dosimeters per point were carried out for 6 MV at 3 and 10 cm depth. Monte Carlo simulations using GEANT4 were performed to simulate the response of the active detector material for several angles. Detector and housing were simulated in detail based on microCT data and communications with the manufacturer. Various material compositions and an all-water geometry were considered. Results For the traditional Setup 1 the response of the OSLD dropped on average by 1.4% ± 0.7% (measurement) and 2.1% ± 0.3% (Monte Carlo simulation) for the 90° orientation compared to 0°. Monte Carlo simulations also showed a strong dependence of the effect on the composition of the sensitive layer. Assuming the layer to completely consist of the active material (Al2O3) results in a 7% drop in response for 90° compared to 0°. Assuming the layer to be completely water, results in a flat response within the simulation uncertainty of about 1%. For the new Setup 2, measurements and Monte Carlo simulations found the angular dependence of the dosimeter to be below 1% and within the measurement uncertainty. Conclusions The dosimeter system exhibits a small angular dependence of approximately 2% which needs to be considered for measurements involving other than normal incident beams angles. This applies in particular to clinicalin vivo measurements where the orientation of the dosimeter is dictated by clinical circumstances and cannot be optimized as otherwise suggested here. When measuring in a phantom, the proposed new setup should be considered. It changes the orientation of the dosimeter so that a coplanar beam arrangement always hits the disk shaped detector material from the thin side and thereby reduces the angular dependence of the response to within the measurement uncertainty of about 1%. This improvement makes the dosimeter more attractive for clinical measurements with multiple coplanar beams in phantoms, as the overall measurement uncertainty is reduced. Similarly, phantom based postal audits can transition from the traditional TLD to the more accurate and convenient OSLD.

An analysis of MONTBLEX data on heat and momentum flux at Jodhpur

Parameterization of sensible heat and momentum fluxes as inferred from an analysis of tower observations archived during MONTBLEX-90 at Jodhpur is proposed, both in terms of standard exchange coefficients C-H and C-D respectively and also according to free convection scaling. Both coefficients increase rapidly at low winds (the latter more strongly) and with increasing instability. All the sensible heat flux data at Jodhpur (wind speed at 10m <(U)over bar (10)>, < 8ms(-1)) also obey free convection scaling, with the flux proportional to the '4/3' power of an appropriate temperature difference such as that between 1 and 30 m. Furthermore, for <(U)over bar (10)> < 4 ms(-1) the momentum flux displays a linear dependence on wind speed.

Temperature dependence of 35Cl NQR in 2,6-dichloropyridine

Chlorine NQR in 2,6-dichloropyridine has been investigated in the temperature range 77 K to room temperature and a single resonance line has been observed throughout. Using this data, torsional frequencies of the molecule have been evaluated on the basis of both the Bayer theory and the modified Bayer theory incorporating Tatsuzaki correction.

1H NMR and a study of the anomalous temperature dependence of the 35Cl NQR frequencies in 2-chloro-3-pyridinol

A 35Cl NQR study of 2-chloro-3-pyridinol showed the presence of four NQR signals at 77 K. One of the lines showed a positive temperature coefficient of the NQR frequency. 1H NMR studies showed the presence of intramolecular hydrogen bonding, and the anomalous NQR temperature dependence has been explained in terms of Bayer and hydrogen bond effects. The room temperature x-ray structure and the low-temperature NQR data suggest the presence of a phase transition.

Nicotine Dependence and Smoking Behaviour : A genetic and epidemiological study

The worldwide health burden caused by the tobacco epidemic highlights the importance of study-ing determinants of smoking behaviour and key factors sustaining nicotine dependence. Despite vast-ranging preventive efforts, smoking remains one of the most deleterious health behaviours, and its genetic and environmental factors warrant continuous investigation. The heritability of smoking behaviour and nicotine dependence has been suggested to be relatively high. Earlier smoking behaviour, nicotine dependence, socio-economic position and demographic factors have all been shown to be associated with smoking cessation. This thesis aimed to examine various aspects of smoking behaviour and nicotine dependence from an epidemiological and genetic per-spective. Data for Studies I and IV were obtained from the Older Finnish Twin Cohort, a postal health sur-vey conducted in 1975, 1981 and 1990 on same-sexed pairs and in 1996-1997 on male-female adult pairs. The number of ever-smoking participants was 8941 in Study I and 3069 in Study IV. Data for Studies II and III came from the Family Study of Cigarette Smoking - Vulnerability to Nicotine Addiction. This study is linked to the Older Finnish Twin Cohort with new data collec-tion during 2001-2006 that focused on smoking twin pairs and their family members. The meas-ures included intensive telephone interviews, blood samples and additional postal questionnaires. The numbers of ever-smoking participants was 1370 in Study II and 529 in Study III. Study I examined whether a genetic component underlies smoking behaviour among Finnish adults. Genetic factors were important in the amount smoked and smoking cessation, with about half of the phenotypic differences explained by genetic variance. A novel finding was that genetic influences on amount smoked and smoking cessation were largely independent of genetic influ-ences on age at initiation. This result has implications for defining phenotypes in the search for genes underlying smoking behaviour. Furthermore, even if smoking initiation is postponed to a later age, potential vulnerability to subsequent nicotine dependence cannot be completely inhib-ited. Study II investigated the effect of genetic and environmental factors on nicotine dependence, as measured by the novel multidimensional Nicotine Dependence Syndrome Scale (NDSS). This scale was validated in the Finnish data. The NDSS correlated highly with other established nico-tine dependence scales (FTND and DSM-IV), suggesting that this new scale would be a feasible and valid measure for identifying nicotine-dependent smokers among the ever-smoking popula-tion. About one-third of the phenotypic variation in nicotine dependence in this sample was ex-plained by genetic influences. Study III aimed at identifying chromosomal regions harbouring genes that influence smoking be-haviour and nicotine dependence. Linkage analysis of family data revealed that for smoker and nicotine dependence phenotypes as well as for co-morbidity between nicotine dependence and alcohol use signals on specific chromosome regions (chromosomes 2q33, 5q12, 5q34 7q21, 7q31, 10q25, 11p15, 20p13) exist. Results further support the hypothesis that smoking behaviour phe-notypes have a genetic background. Study IV examined associations of smoking behaviour, socio-economic position and transition of marital status with smoking cessation. Indicators of socio-economic position were important pre-dictors of smoking cessation even when adjusted for previous smoking behaviour. Getting married was associated with an increased probability of cessation in men, a finding confirmed among dis-cordant twin pairs. Thus, having a partner appears to have a positive impact on smoking cessation. In conclusion, nicotine dependence and smoking behaviour demonstrate significant genetic liabil-ity, but also substantial environmental influences among Finnish adults. Smoking initiation should be prevented or at least postponed to a later age. Although genetic factors are important in nicotine dependence and smoking behaviour, societal actions still have a primary role in tobacco control and smoking prevalence. Future studies should examine the complex interactions between genetic and environmental factors in nicotine dependence.

Flexibility of the furanose ring in nucleic acids: a compilation of crystal data

A compilation of crystal structure data on deoxyribo- and ribonucleosides and their higher derivatives is presented. The aim of this paper is to highlight the flexibility of deoxyribose and ribose rings. So far, the conformational parameters of nucleic acids constituents of ribose and deoxyribose have not been analysed separately. This paper aims to correlate the conformational parameters with the nature and puckering of the sugar. Deoxyribose puckering occurs in the C2′ endo region while ribose puckering is observed both in the C3′ endo and C2′ endo regions. A few endocyclic and exocyclic bond angles depend on the puckering and the nature of the sugar. The majority of structures have an anti conformation about the glycosyl bond. There appears to be a puckering dependence on the torsion angle about the C4′---C5′ bonds. Such stereochemical information is useful in model building studies of polynucleotides and nucleic acids.

Pressure dependence of 35Cl nuclear quadrupole resonance in 2,5-, 2,6- and 3,5-dichlorophenols

Pressure dependence of the 35Cl Nuclear Quadrupole Resonances (N.Q.R.) in 2,5-, 2,6- and 3,5-dichlorophenols (DCP) has been studied up to a pressure of about 6·5 kbar at room temperature. While the pressure dependence of the two resonance lines in 2,6-DCP is essentially similar, the lower frequency line in 2,5-DCP is almost pressure independent and the higher frequency line shows a linear variation with pressure upto about 3·5 kbar but shows a negative pressure coefficient beyond this pressure. The two lines in 3,5-DCP have a non-linear pressure dependence with the curvature changing smoothly with pressure. The pressure coefficient for both lines becomes negative beyond a pressure of 5 kbar. The pressure dependence of the N.Q.R. frequencies is discussed in relation to intra- and inter-molecular contacts. Also, a thermodynamic analysis of the data is carried out to determine the constant volume temperature derivative of the N.Q.R. frequency.

Modeling Asymmetries in Financial Data with Multiplicative Error Models

This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.

Efficient search for statistically significant dependency rules in binary data

Analyzing statistical dependencies is a fundamental problem in all empirical science. Dependencies help us understand causes and effects, create new scientific theories, and invent cures to problems. Nowadays, large amounts of data is available, but efficient computational tools for analyzing the data are missing. In this research, we develop efficient algorithms for a commonly occurring search problem - searching for the statistically most significant dependency rules in binary data. We consider dependency rules of the form X->A or X->not A, where X is a set of positive-valued attributes and A is a single attribute. Such rules describe which factors either increase or decrease the probability of the consequent A. A classical example are genetic and environmental factors, which can either cause or prevent a disease. The emphasis in this research is that the discovered dependencies should be genuine - i.e. they should also hold in future data. This is an important distinction from the traditional association rules, which - in spite of their name and a similar appearance to dependency rules - do not necessarily represent statistical dependencies at all or represent only spurious connections, which occur by chance. Therefore, the principal objective is to search for the rules with statistical significance measures. Another important objective is to search for only non-redundant rules, which express the real causes of dependence, without any occasional extra factors. The extra factors do not add any new information on the dependence, but can only blur it and make it less accurate in future data. The problem is computationally very demanding, because the number of all possible rules increases exponentially with the number of attributes. In addition, neither the statistical dependency nor the statistical significance are monotonic properties, which means that the traditional pruning techniques do not work. As a solution, we first derive the mathematical basis for pruning the search space with any well-behaving statistical significance measures. The mathematical theory is complemented by a new algorithmic invention, which enables an efficient search without any heuristic restrictions. The resulting algorithm can be used to search for both positive and negative dependencies with any commonly used statistical measures, like Fisher's exact test, the chi-squared measure, mutual information, and z scores. According to our experiments, the algorithm is well-scalable, especially with Fisher's exact test. It can easily handle even the densest data sets with 10000-20000 attributes. Still, the results are globally optimal, which is a remarkable improvement over the existing solutions. In practice, this means that the user does not have to worry whether the dependencies hold in future data or if the data still contains better, but undiscovered dependencies.

Aggregation of apolar peptides in organic solvents. Concentration dependence of 1H-nmr parameters for peptide NH groups in 310 helical decapeptide fragment of suzukacillin

Peptide NH chemical shifts and their temperature dependences have been monitored as a function of concentration for the decapeptide, Boc-Aib-Pro-Val-Aib-Val-Ala-Aib-Ala-Aib-Aib-OMe in CDCl3 (0.001-0.06M) and (CD3)2SO (0.001-0.03M). The chemical shifts and temperature coefficients for all nine NH groups show no significant concentration dependence in (CD3)2SO. Seven NH groups yield low values of temperature coefficients over the entire range, while one yields an intermediate value. In CDCl3, the Aib(1) NH group shows a large concentration dependence of both chemical shift and temperature coefficient, in contrast to the other eight NH groups. The data suggest that in (CD3)2SO, the peptide adopts a 310 helical conformation and is monomeric over the entire concentration range. In CDCl3, the 310 helical peptide associates at a concentration of 0.01M, with the Aib(1) NH involved in an intermolecular hydrogen bond. Association does not disrupt the intramolecular hydrogen-bonding pattern in the decapeptide.

Adsorption of Nitrogen on Activated Carbon-Refit of Experimental Data and Derivation of Properties Required for Design of Equipment

Volumetric method based adsorption measurements of nitrogen on two specimens of activated carbon (Fluka and Sarabhai) reported by us are refitted to two popular isotherms, namely, Dubunin−Astakhov (D−A) and Toth, in light of improved fitting methods derived recently. Those isotherms have been used to derive other data of relevance in design of engineering equipment such as the concentration dependence of heat of adsorption and Henry’s law coefficients. The present fits provide a better representation of experimental measurements than before because the temperature dependence of adsorbed phase volume and structural heterogeneity of micropore distribution have been accounted for in the D−A equation. A new correlation to the Toth equation is a further contribution. The heat of adsorption in the limiting uptake condition is correlated with the Henry’s law coefficients at the near zero uptake condition.

Statistical tools for analyzing water quality data

Water quality data are often collected at different sites over time to improve water quality management. Water quality data usually exhibit the following characteristics: non-normal distribution, presence of outliers, missing values, values below detection limits (censored), and serial dependence. It is essential to apply appropriate statistical methodology when analyzing water quality data to draw valid conclusions and hence provide useful advice in water management. In this chapter, we will provide and demonstrate various statistical tools for analyzing such water quality data, and will also introduce how to use a statistical software R to analyze water quality data by various statistical methods. A dataset collected from the Susquehanna River Basin will be used to demonstrate various statistical methods provided in this chapter. The dataset can be downloaded from website http://www.srbc.net/programs/CBP/nutrientprogram.htm.

The effects of the 2004 reduction in the price of alcohol on alcohol-related harm in Finland : A natural experiment based on register data

Changes in alcohol pricing have been documented as inversely associated with changes in consumption and alcohol-related problems. Evidence of the association between price changes and health problems is nevertheless patchy and is based to a large extent on cross-sectional state-level data, or time series of such cross-sectional analyses. Natural experimental studies have been called for. There was a substantial reduction in the price of alcohol in Finland in 2004 due to a reduction in alcohol taxes of one third, on average, and the abolition of duty-free allowances for travellers from the EU. These changes in the Finnish alcohol policy could be considered a natural experiment, which offered a good opportunity to study what happens with regard to alcohol-related problems when prices go down. The present study investigated the effects of this reduction in alcohol prices on (1) alcohol-related and all-cause mortality, and mortality due to cardiovascular diseases, (2) alcohol-related morbidity in terms of hospitalisation, (3) socioeconomic differentials in alcohol-related mortality, and (4) small-area differences in interpersonal violence in the Helsinki Metropolitan area. Differential trends in alcohol-related mortality prior to the price reduction were also analysed. A variety of population-based register data was used in the study. Time-series intervention analysis modelling was applied to monthly aggregations of deaths and hospitalisation for the period 1996-2006. These and other mortality analyses were carried out for men and women aged 15 years and over. Socioeconomic differentials in alcohol-related mortality were assessed on a before/after basis, mortality being followed up in 2001-2003 (before the price reduction) and 2004-2005 (after). Alcohol-related mortality was defined in all the studies on mortality on the basis of information on both underlying and contributory causes of death. Hospitalisation related to alcohol meant that there was a reference to alcohol in the primary diagnosis. Data on interpersonal violence was gathered from 86 administrative small-areas in the Helsinki Metropolitan area and was also assessed on a before/after basis followed up in 2002-2003 and 2004-2005. The statistical methods employed to analyse these data sets included time-series analysis, and Poisson and linear regression. The results of the study indicate that alcohol-related deaths increased substantially among men aged 40-69 years and among women aged 50-69 after the price reduction when trends and seasonal variation were taken into account. The increase was mainly attributable to chronic causes, particularly liver diseases. Mortality due to cardiovascular diseases and all-cause mortality, on the other hand, decreased considerably among the-over-69-year-olds. The increase in alcohol-related mortality in absolute terms among the 30-59-year-olds was largest among the unemployed and early-age pensioners, and those with a low level of education, social class or income. The relative differences in change between the education and social class subgroups were small. The employed and those under the age of 35 did not suffer from increased alcohol-related mortality in the two years following the price reduction. The gap between the age and education groups, which was substantial in the 1980s, thus further broadened. With regard to alcohol-related hospitalisation, there was an increase in both chronic and acute causes among men under the age of 70, and among women in the 50-69-year age group when trends and seasonal variation were taken into account. Alcohol dependence and other alcohol-related mental and behavioural disorders were the largest category in both the total number of chronic hospitalisation and in the increase. There was no increase in the rate of interpersonal violence in the Helsinki Metropolitan area, and even a decrease in domestic violence. There was a significant relationship between the measures of social disadvantage on the area level and interpersonal violence, although the differences in the effects of the price reduction between the different areas were small. The findings of the present study suggest that that a reduction in alcohol prices may lead to a substantial increase in alcohol-related mortality and morbidity. However, large population group differences were observed regarding responsiveness to the price changes. In particular, the less privileged, such as the unemployed, were most sensitive. In contrast, at least in the Finnish context, the younger generations and the employed do not appear to be adversely affected, and those in the older age groups may even benefit from cheaper alcohol in terms of decreased rates of CVD mortality. The results also suggest that reductions in alcohol prices do not necessarily affect interpersonal violence. The population group differences in the effects of the price changes on alcohol-related harm should be acknowledged, and therefore the policy actions should focus on the population subgroups that are primarily responsive to the price reduction.