An analysis of theories of search and search behavior

Theories of search and search behavior can be used to glean insights and generate hypotheses about how people interact with retrieval systems. This paper examines three such theories, the long standing Information Foraging Theory, along with the more recently proposed Search Economic Theory and the Interactive Probability Ranking Principle. Our goal is to develop a model for ad-hoc topic retrieval using each approach, all within a common framework, in order to (1) determine what predictions each approach makes about search behavior, and (2) show the relationships, equivalences and differences between the approaches. While each approach takes a different perspective on modeling searcher interactions, we show that under certain assumptions, they lead to similar hypotheses regarding search behavior. Moreover, we show that the models are complementary to each other, but operate at different levels (i.e., sessions, patches and situations). We further show how the differences between the approaches lead to new insights into the theories and new models. This contribution will not only lead to further theoretical developments, but also enables practitioners to employ one of the three equivalent models depending on the data available.

Early-onset depressive disorders,related mental health disorders and substance use-A prospective : longitudinal study of Finnish twins born 1983-1987

Early-onset psychiatric illnesses effects scatter to academic achievements as well as functioning in familial and social environments. From a public health point of view, depressive disorders are the most significant mental health disorders that begin in adolescence. Using prospective and longitudinal design, this study aimed to increase the understanding of early-onset depressive disorders, related mental health disorders and developing substance use in a large population-derived sample of adolescent Finnish twins. The participants of this study, FinnTwin12, an ongoing longitudinal population-based study, came from Finnish families with twins born in 1983-87 (exhaustive of five birth cohorts, identified from Finland s Central Population Register). With follow-up ongoing at age 20-24, this thesis assessed adolescent mental health in the first three waves, starting from baseline age 11-12 to follow-ups at age 14 and 17½. Some 5600 twins participated in questionnaire assessments of a wide range of health related behaviors. Mental health was further assessed among an intensively studied subsample of 1852 adolescents, who completed also professionally administered interviews at age 14, which provided data for full DSM-IV/III-R (Diagnostic and Statistical Manual for Mental Health disorders, 4th and 3rd editions) diagnoses. The participation rates of the study were 87-92%. The results of the study suggest, that the diagnostic criteria for major depressive disorder (MDD) may not capture youth with clinically significant early-onset depressive conditions outside clinical settings. Milder cases of depression, namely adolescents fulfilling the diagnostic criteria for minor depressive disorder, a qualitatively similar condition to MDD with fewer symptoms are also associated with marked suicidal thoughts, plans and attempts, recurrences and a high degree of comorbidity. Prospectively and longitudinally, early-onset depressive disorders were of substantial importance in the context of other mental health disorders and substance use behaviors: These data from a large population-derived sample established a substantial overlap between early-onset depressive disorders and attention deficit hyperactivity disorder in adolescent females, both of them significantly predictive for development of substance use among girls. Only in females baseline DSM-IV ADHD symptoms were strong predictors of alcohol abuse and dependence and illicit drug use at age 14 and frequent alcohol use and illicit drug use at age 17.½ when conduct disorder and previous substance use were controlled for. Early-onset depressive disorders were also prospectively and longitudinally associated to daily smoking behavior, smokeless tobacco use, frequent alcohol use and illicit drug use and eating disorders. Analysis of discordant twins suggested that these predictive associations were independent of familial confounds, such as family income, structure and parental models. In sum, early-onset depressive disorders predict subsequent involvement of substance use and psychiatric morbidity. A heightened risk for substance use is substantial also among those depressed below categorical diagnosis of MDD. Whether early recognition and interventions among these young people hold potential for substance use prevention further in their lives has potential public health significance and calls for more research. Data from this population-derived sample with balanced representation of boys and girls, suggested that boys and girls with ADHD behaviors may differ from each other in their vulnerability to substance use and depressive disorders: the data suggest more adverse substance use outcome for girls that was not attenuated by conduct disorder or previous substance use. Further, the prospective associations of early-onset depressive disorders and future elevated levels of addictive substance use is not explained by familial factors supporting future substance use, which could have important implications for substance use prevention.

Simultaneous prediction of acidity parameters (pH and titratable acidity) in Kefir using near infrared reflectance spectroscopy.

Acidity in terms of pH and titratable acids influences the texture and flavour of fermented dairy products, such as Kefir. However, the methods for determining pH and titratable acidity (TA) are time consuming. Near infrared (NIR) spectroscopy is a non-destructive method, which simultaneously predicts multiple traits from a single scan and can be used to predict pH and TA. The best pH NIR calibration model was obtained with no spectral pre-treatment applied, whereas smoothing was found to be the best pre-treatment to develop the TA calibration model. Using cross-validation, the prediction results were found acceptable for both pH and TA. With external validation, similar results were found for pH and TA, and both models were found to be acceptable for screening purposes.

Spatial variation in life history reveals insight into connectivity and geographic population structure of a tropical estuarine teleost: king threadfin, Polydactylus macrochir

Understanding the life history of exploited fish species is not only critical in developing stock assessments and productivity models, but has a dual function in the delineation of connectivity and geographical population structure. In this study, patterns in growth and length and age at sex change of Polydactylus macrochir, an ecologically and economically important protandrous estuarine teleost, were examined to provide preliminary information on the species' connectivity and geographic structure across northern Australia. Considerable variation in life history parameters was observed among the 18 locations sampled. Both unconstrained and constrained (t(0) = 0) estimates of von Bertalanffy growth function parameters differed significantly among all neighbouring locations with the exception of two locations in Queensland's east coast and two in Queensland's Gulf of Carpentaria waters, respectively. Comparisons of back-calculated length-at-age 2 provided additional evidence for growth differences among some locations, but were not significantly different among locations in the south-eastern Gulf of Carpentaria or on Queensland's east coast. The length and age at sex change differed markedly among locations, with fish from the east coast of Australia changing sex from males to females at significantly greater lengths and ages than elsewhere. Sex change occurred earliest at locations within Queensland's Gulf of Carpentaria, where a large proportion of small, young females were recorded. The observed differences suggest that P. macrochir likely form a number of geographically and/or reproductively distinct groups in Australian waters and suggest that future studies examining connectivity and geographic population structure of estuarine fishes will likely benefit from the inclusion of comparisons of life history parameters. (C) 2012 Elsevier B.V. All rights reserved.

Prediction of mortality and conception rates of beef breeding cattle in northern Australia

In current simulation packages for the management of extensive beef-cattle enterprises, the relationships for the key biological rates (namely conception and mortality) are quite rudimentary. To better estimate these relationships, cohort-level data covering 17 100 cow-years from six sites across northern Australia were collated and analysed. Further validation data, from 7200 cow-years, were then used to test these relationships. Analytical problems included incomplete and non-standardised data, considerable levels of correlation among the 'independent' variables, and the close similarity of alternate possible models. In addition to formal statistical analyses of these data, the theoretical equations for predicting mortality and conception rates in the current simulation models were reviewed, and then reparameterised and recalibrated where appropriate. The final models explained up to 80% of the variation in the data. These are now proposed as more accurate and useful models to be used in the prediction of biological rates in simulation studies for northern Australia. © The State of Queensland (through the Department of Agriculture, Fisheries and Forestry) 2012. © CSIRO.

Selection, optimization, and compensation strategies: Interactive effects on daily work engagement

The theory of selective optimization with compensation (SOC) proposes that the “orchestrated” use of three distinct action regulation strategies (selection, optimization, and compensation) leads to positive employee outcomes. Previous research examined overall scores and additive models (i.e., main effects) of SOC strategies instead of interaction models in which SOC strategies mutually enhance each other's effects. Thus, a central assumption of SOC theory remains untested. In addition, most research on SOC strategies has been cross-sectional, assuming that employees' use of SOC strategies is stable over time. We conducted a quantitative diary study across nine work days (N = 77; 514 daily entries) to investigate interactive effects of daily SOC strategies on daily work engagement. Results showed that optimization and compensation, but not selection, had positive main effects on work engagement. Moreover, a significant three-way interaction effect indicated that the relationship between selection and work engagement was positive only when both optimization and compensation were high, whereas the relationship was negative when optimization was low and compensation was high. We discuss implications for future research and practice regarding the use of SOC strategies at work.

Integrating pest population models with biophysical crop models to better represent the farming system

Farming systems frameworks such as the Agricultural Production Systems simulator (APSIM) represent fluxes through the soil, plant and atmosphere of the system well, but do not generally consider the biotic constraints that function within the system. We designed a method that allowed population models built in DYMEX to interact with APSIM. The simulator engine component of the DYMEX population-modelling platform was wrapped within an APSIM module allowing it to get and set variable values in other APSIM models running in the simulation. A rust model developed in DYMEX is used to demonstrate how the developing rust population reduces the crop's green leaf area. The success of the linking process is seen in the interaction of the two models and how changes in rust population on the crop's leaves feedback to the APSIM crop modifying the growth and development of the crop's leaf area. This linking of population models to simulate pest populations and biophysical models to simulate crop growth and development increases the complexity of the simulation, but provides a tool to investigate biotic constraints within farming systems and further moves APSIM towards being an agro-ecological framework.

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.

Influence of adhesive non-linearities on the performance and optimal length of adhesive bonded joints

An analytical study for the static strength of adhesive lap joints is presented. The earlier solutions of Volkersen [i], DeBruyne[2] and others were limited to linear adhesives. The influence of adhesive non-linearity was first considered by Grimes' et al[3] and Dickson et al [4]. Recently Hart-Smith[5] successfully introduced elastic-plastic behaviour of the adhesive. In the present study the problem is formulated for general non-linear adhesive behaviour and an efficient numerical algorithm is written for the solution. Bilinear and trilinear models for the nonlinearity yield closed form analytical solutions.

Creative writing: Literature review and evidence-based research

There is growing evidence, especially in the USA and UK, that creative writing can form an important part of the recovery experience of people affected by severe mental illness. In this chapter, I consider theoretical models that explain how creative writing might contribute to recovery, and discuss the potential for creative writing in psychosocial rehabilitation. It is argued that the rehabilitation benefits of creative writing might be optimized through focus on process and technique in writing, rather than expression or content alone, and that consequently, the involvement of professional writers might be important. I will explore the recent history of theoretical frameworks and explanatory models that link creative writing and recovery, and examine such empirical evidence as is available on the contribution of creative writing to recovery from severe mental illness.

Structure, dynamics, and interactions of jacalin. Insights from molecular dynamics simulations examined in conjunction with results of X-ray studies

Molecular dynamics simulations have been carried out on all the jacalin-carbohydrate complexes of known structure, models of unliganded molecules derived from the complexes and also models of relevant complexes where X-ray structures are not available. Results of the simulations and the available crystal structures involving jacalin permit delineation of the relatively rigid and flexible regions of the molecule and the dynamical variability of the hydrogen bonds involved in stabilizing the structure. Local flexibility appears to be related to solvent accessibility. Hydrogen bonds involving side chains and water bridges involving buried water molecules appear to be important in the stabilization of loop structures. The lectin-carbohydrate interactions observed in crystal structures, the average parameters pertaining to them derived from simulations, energetic contribution of the stacking residue estimated from quantum mechanical calculations, and the scatter of the locations of carbohydrate and carbohydrate-binding residues are consistent with the known thermodynamic parameters of jacalin-carbohydrate interactions. The simulations, along with X-ray results, provide a fuller picture of carbohydrate binding by jacalin than provided by crystallographic analysis alone. The simulations confirm that in the unliganded structures water molecules tend to occupy the positions occupied by carbohydrate oxygens in the lectin-carbohydrate complexes. Population distributions in simulations of the free lectin, the ligands, and the complexes indicate a combination of conformational selection and induced fit. Proteins 2009; 77:760-777.

The Pathobiology of the Saccular Cerebral Artery Aneurysm Rupture and Repair : A Clinicopathological and Experimental Approach

Backround and Purpose The often fatal (in 50-35%) subarachnoid hemorrhage (SAH) caused by saccular cerebral artery aneurysm (SCAA) rupture affects mainly the working aged population. The incidence of SAH is 10-11 / 100 000 in Western countries and twice as high in Finland and Japan. The estimated prevalence of SCAAs is around 2%. Many of those never rupture. Currently there are, however, no diagnostic methods to identify rupture-prone SCAAs from quiescent, (dormant) ones. Finding diagnostic markers for rupture-prone SCAAs is of primary importance since a SCAA rupture has such a sinister outcome, and all current treatment modalities are associated with morbidity and mortality. Also the therapies that prevent SCAA rupture need to be developed to as minimally invasive as possible. Although the clinical risk factors for SCAA rupture have been extensively studied and documented in large patient series, the cellular and molecular mechanisms how these risk factors lead to SCAA wall rupture remain incompletely known. Elucidation of the molecular and cellular pathobiology of the SCAA wall is needed in order to develop i) novel diagnostic tools that could identify rupture-prone SCAAs or patients at risk of SAH, and to ii) develop novel biological therapies that prevent SCAA wall rupture. Materials and Methods In this study, histological samples from unruptured and ruptured SCAAs and plasma samples from SCAA carriers were compared in order to identify structural changes, cell populations, growth factor receptors, or other molecular markers that would associate with SCAA wall rupture. In addition, experimental saccular aneurysm models and experimental models of mechanical vascular injury were used to study the cellular mechanisms of scar formation in the arterial wall, and the adaptation of the arterial wall to increased mechanical stress. Results and Interpretation Inflammation and degeneration of the SCAA wall, namely loss of mural cells and degradation of the wall matrix, were found to associate with rupture. Unruptured SCAA walls had structural resemblance with pads of myointimal hyperplasia or so called neointima that characterizes early atherosclerotic lesions, and is the repair and adaptation mechanism of the arterial wall after injury or increased mechanical stress. As in pads of myointimal hyperplasia elsewhere in the vasculature, oxidated LDL was found in the SCAA walls. Immunity against OxLDL was demonstrated in SAH patients with detection of circulating anti-oxidized LDL antibodies, which were significantly associated with the risk of rupture in patients with solitary SCAAs. Growth factor receptors associated with arterial wall remodeling and angiogenesis were more expressed in ruptured SCAA walls. In experimental saccular aneurysm models, capillary growth, arterial wall remodeling and neointima formation were found. The neointimal cells were shown to originate from the experimental aneurysm wall with minor contribution from the adjacent artery, and a negligible contribution of bone marrow-derived neointimal cells. Since loss of mural cells characterizes ruptured human SCAAs and likely impairs the adaptation and repair mechanism of ruptured or rupture-prone SCAAs, we investigated also the hypothesis that bone marrow-derived or circulating neointimal precursor cells could be used to enhance neointima formation and compensate the impaired repair capacity in ruptured SCAA walls. However, significant contribution of bone marrow cells or circulating mononuclear cells to neointima formation was not found.

Modeling and Analysis of Noise Margin in SET Logic

In this paper the static noise margin for SET (single electron transistor) logic is defined and compact models for the noise margin are developed by making use of the MIB (Mahapatra-Ionescu-Banerjee) model. The variation of the noise margin with temperature and background charge is also studied. A chain of SET inverters is simulated to validate the definition of various logic levels (like VIH, VOH, etc.) and noise margin. Finally the noise immunity of SET logic is compared with current CMOS logic.

Factors controlling the surface energy budget over snow and ice

Polar Regions are an energy sink of the Earth system, as the Sun rays do not reach the Poles for half of the year, and hit them only at very low angles for the other half of the year. In summer, solar radiation is the dominant energy source for the Polar areas, therefore even small changes in the surface albedo strongly affect the surface energy balance and, thus, the speed and amount of snow and ice melting. In winter, the main heat sources for the atmosphere are the cyclones approaching from lower latitudes, and the atmosphere-surface heat transfer takes place through turbulent mixing and longwave radiation, the latter dominated by clouds. The aim of this thesis is to improve the knowledge about the surface and atmospheric processes that control the surface energy budget over snow and ice, with particular focus on albedo during the spring and summer seasons, on horizontal advection of heat, cloud longwave forcing, and turbulent mixing during the winter season. The critical importance of a correct albedo representation in models is illustrated through the analysis of the causes for the errors in the surface and near-surface air temperature produced in a short-range numerical weather forecast by the HIRLAM model. Then, the daily and seasonal variability of snow and ice albedo have been examined by analysing field measurements of albedo, carried out in different environments. On the basis of the data analysis, simple albedo parameterizations have been derived, which can be implemented into thermodynamic sea ice models, as well as numerical weather prediction and climate models. Field measurements of radiation and turbulent fluxes over the Bay of Bothnia (Baltic Sea) also allowed examining the impact of a large albedo change during the melting season on surface energy and ice mass budgets. When high contrasts in surface albedo are present, as in the case of snow covered areas next to open water, the effect of the surface albedo heterogeneity on the downwelling solar irradiance under overcast condition is very significant, although it is usually not accounted for in single column radiative transfer calculations. To account for this effect, an effective albedo parameterization based on three-dimensional Monte Carlo radiative transfer calculations has been developed. To test a potentially relevant application of the effective albedo parameterization, its performance in the ground-based retrieval of cloud optical depth was illustrated. Finally, the factors causing the large variations of the surface and near-surface temperatures over the Central Arctic during winter were examined. The relative importance of cloud radiative forcing, turbulent mixing, and lateral heat advection on the Arctic surface temperature were quantified through the analysis of direct observations from Russian drifting ice stations, with the lateral heat advection calculated from reanalysis products.

Energy landscape view of phase transitions and slow dynamics in thermotropic liquid crystals

Thermotropic liquid crystals are known to display rich phase behavior on temperature variation. Although the nematic phase is orientationally ordered but translationally disordered, a smectic phase is characterized by the appearance of a partial translational order in addition to a further increase in orientational order. In an attempt to understand the interplay between orientational and translational order in the mesophases that thermotropic liquid crystals typically exhibit upon cooling from the high-temperature isotropic phase, we investigate the potential energy landscapes of a family of model liquid crystalline systems. The configurations of the system corresponding to the local potential energy minima, known as the inherent structures, are determined from computer simulations across the mesophases. We find that the depth of the potential energy minima explored by the system along an isochor grows through the nematic phase as temperature drops in contrast to its insensitivity to temperature in the isotropic and smectic phases. The onset of the growth of the orientational order in the parent phase is found to induce a translational order, resulting in a smectic-like layer in the underlying inherent structures; the inherent structures, surprisingly, never seem to sustain orientational order alone if the parent nematic phase is sandwiched between the high-temperature isotropic phase and the low-temperature smectic phase. The Arrhenius temperature dependence of the orientational relaxation time breaks down near the isotropic-nematic transition. We find that this breakdown occurs at a temperature below which the system explores increasingly deeper potential energy minima.