The future of power in the network era

This article asks questions about the futures of power in the network era. Two critical emerging issues are at work with uncertain outcomes. The first is the emergence of the collaborative economy, while the second is the emergence of surveillance capabilities from both civic, state and commercial sources. While both of these emerging issues are expected by many to play an important role in the future development of our societies, it is still unclear whose values and whose purposes will be furthered. This article argues that the futures of these emerging issues depend on contests for power. As such, four scenarios are developed for the futures of power in the network era using the double variable scenario approach.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models. © 2014 Springer Science+Business Media New York.

The mechanism of pattern selection in coupled map lattices

The pattern selection of one-dimensional coupled map lattices is studied in this paper. It is shown by spatiotemporal variable separation that there exists a threshold wavelength in pattern selection which possesses wave-like structures in space and periodic chaotic motion in time.

基于反馈线性化的无人直升机航向控制

本文着重解决小型无人直升机航向自适应控制问题.通过求非线性函数导数,把原始系统扩展为一个带有伪状态变量的新系统.这种方法不必求解非线性函数的逆,并且降低了计算量.证明了该方法的稳定性.针对实际模型直升机实验平台航向动力学模型,仿真结果表明了该方法的有效性.

The effect of nonlinearity in CO2 heating rates on the attribution of stratospheric ozone and temperature changes

An analysis of the attribution of past and future changes in stratospheric ozone and temperature to anthropogenic forcings is presented. The analysis is an extension of the study of Shepherd and Jonsson (2008) who analyzed chemistry-climate simulations from the Canadian Middle Atmosphere Model (CMAM) and attributed both past and future changes to changes in the external forcings, i.e. the abundances of ozone-depleting substances (ODS) and well-mixed greenhouse gases. The current study is based on a new CMAM dataset and includes two important changes. First, we account for the nonlinear radiative response to changes in CO2. It is shown that over centennial time scales the radiative response in the upper stratosphere to CO2 changes is significantly nonlinear and that failure to account for this effect leads to a significant error in the attribution. To our knowledge this nonlinearity has not been considered before in attribution analysis, including multiple linear regression studies. For the regression analysis presented here the nonlinearity was taken into account by using CO2 heating rate, rather than CO2 abundance, as the explanatory variable. This approach yields considerable corrections to the results of the previous study and can be recommended to other researchers. Second, an error in the way the CO2 forcing changes are implemented in the CMAM was corrected, which significantly affects the results for the recent past. As the radiation scheme, based on Fomichev et al. (1998), is used in several other models we provide some description of the problem and how it was fixed.

"Where am I?" Impact of display and content variables on spatial presence and comprehension in virtual environments

Forgetting immediate physical reality and having awareness of one�s location in the simulated world is critical to enjoyment and performance in virtual environments be it an interactive 3D game such as Quake or an online virtual 3d community space such as Second Life. Answer to the question "where am I?" at two levels, whether the locus is in the immediate real world as opposed to the virtual world and whether one is aware of the spatial co-ordinates of that locus, hold the key to any virtual 3D experience. While 3D environments, especially virtual environments and their impact on spatial comprehension has been studied in disciplines such as architecture, it is difficult to determine the relative contributions of specific attributes such as screen size or stereoscopy towards spatial comprehension since most of them treat the technology as monolith (box-centered). Using a variable-centered approach put forth by Nass and Mason (1990) which breaks down the technology into its component variables and their corresponding values as its theoretical basis, this paper looks at the contributions of five variables (Stereoscopy, screen size, field of view, level of realism and level of detail) common to most virtual environments on spatial comprehension and presence. The variable centered approach can be daunting as the increase in the number of variables can exponentially increase the number of conditions and resources required. We overcome this drawback posed by adoption of such a theoretical approach by the use of a fractional factorial design for the experiment. This study has completed the first wave of data collection and starting the next phase in January 2007 and expected to complete by February 2007. Theoretical and practical implications of the study are discussed.

A New Reactor Concept for Efficient Solar-Thermochemical Fuel Production

We describe and analyze the efficiency of a new solar-thermochemical reactor concept, which employs a moving packed bed of reactive particles produce of H2 or CO from solar energy and H2O or CO2. The packed bed reactor incorporates several features essential to achieving high efficiency: spatial separation of pressures, temperature, and reaction products in the reactor; solid–solid sensible heat recovery between reaction steps; continuous on-sun operation; and direct solar illumination of the working material. Our efficiency analysis includes material thermodynamics and a detailed accounting of energy losses, and demonstrates that vacuum pumping, made possible by the innovative pressure separation approach in our reactor, has a decisive efficiency advantage over inert gas sweeping. We show that in a fully developed system, using CeO2 as a reactive material, the conversion efficiency of solar energy into H2 and CO at the design point can exceed 30%. The reactor operational flexibility makes it suitable for a wide range of operating conditions, allowing for high efficiency on an annual average basis. The mixture of H2 and CO, known as synthesis gas, is not only usable as a fuel but is also a universal starting point for the production of synthetic fuels compatible with the existing energy infrastructure. This would make it possible to replace petroleum derivatives used in transportation in the U.S., by using less than 0.7% of the U.S. land area, a roughly two orders of magnitude improvement over mature biofuel approaches. In addition, the packed bed reactor design is flexible and can be adapted to new, better performing reactive materials.

A New Reactor Concept for Efficient Solar-Thermochemical Fuel Production

We describe and analyze the efficiency of a new solar-thermochemical reactor concept, which employs a moving packed bed of reactive particles produce of H-2 or CO from solar energy and H2O or CO2. The packed bed reactor incorporates several features essential to achieving high efficiency: spatial separation of pressures, temperature, and reaction products in the reactor; solid-solid sensible heat recovery between reaction steps; continuous on-sun operation; and direct solar illumination of the working material. Our efficiency analysis includes material thermodynamics and a detailed accounting of energy losses, and demonstrates that vacuum pumping, made possible by the innovative pressure separation approach in our reactor, has a decisive efficiency advantage over inert gas sweeping. We show that in a fully developed system, using CeO2 as a reactive material, the conversion efficiency of solar energy into H-2 and CO at the design point can exceed 30%. The reactor operational flexibility makes it suitable for a wide range of operating conditions, allowing for high efficiency on an annual average basis. The mixture of H-2 and CO, known as synthesis gas, is not only usable as a fuel but is also a universal starting point for the production of synthetic fuels compatible with the existing energy infrastructure. This would make it possible to replace petroleum derivatives used in transportation in the U. S., by using less than 0.7% of the U. S. land area, a roughly two orders of magnitude improvement over mature biofuel approaches. In addition, the packed bed reactor design is flexible and can be adapted to new, better performing reactive materials.

Classification and selection of biomarkers in genomic data using LASSO

High-throughput gene expression technologies such as microarrays have been utilized in a variety of scientific applications. Most of the work has been on assessing univariate associations between gene expression with clinical outcome (variable selection) or on developing classification procedures with gene expression data (supervised learning). We consider a hybrid variable selection/classification approach that is based on linear combinations of the gene expression profiles that maximize an accuracy measure summarized using the receiver operating characteristic curve. Under a specific probability model, this leads to consideration of linear discriminant functions. We incorporate an automated variable selection approach using LASSO. An equivalence between LASSO estimation with support vector machines allows for model fitting using standard software. We apply the proposed method to simulated data as well as data from a recently published prostate cancer study.

Career-choice readiness in adolescence: Developmental trajectories and individual differences

Developing career-choice readiness is an important task in adolescence, but current theory and research has provided a rather static view of the phenomenon. The present study investigated the development of career-choice readiness among a group of 325 Swiss students assessed four times every 5 months from seventh through eighth grade. A variable-centered approach applying latent curve modeling showed not only a linear increase of readiness over time but also significant inter-individual differences in the level and development of readiness. Higher levels were predicted by more self-esteem and generalized self-efficacy and fewer perceived barriers while increase in readiness was predicted by increase in occupational information. A person-centered approach applying latent class-growth analysis identified four distinct developmental trajectories: high-increasing (42%), high-decreasing (5%), moderate-increasing (42%), and constantly low (11%). Students with different trajectories showed significant differences in core self-evaluations, occupational knowledge, and barriers. The results suggest that environmental demands promote a developmental trend in readiness development that overrules individual differences for the majority of students. Individual differences affect the level of readiness to a greater extent than the process of its development. Career information seems pivotal for readiness increase.

Religion and polygamy : evidence from the livingstonia mission in Malawi

In contrast to the prevailing preconception, Christian females engage in polygyny in most of sub-Saharan Africa. Based on individual-level data provided by the Demographic and Health Survey (2000, 2004, 2010) in Malawi, this study explores whether Christian identity reduces the likelihood that females enter into polygyny. To address the endogeneity associated with this identity, the analysis adopts an instrumental variable (IV) approach by exploiting the unique setting of a Christian mission dating back to the late 19th century. Exposure to the mission, measured by geographical distance to the influential mission station, Livingstonia, enabled the indigenous population to gradually convert to Christianity. This is particularly true for the local population not belonging to the Yao, an ethnic group that was largely proselytized into Islam because of their historical connection with the Arabs. Using the distance-ethnicity (non-Yao) interaction as an IV for women's Christian identity, with numerous historical, geographic, and climate controls, this study discovers that compared to those practicing other religions (Islam and other) or no religion, Christian females are indeed less likely to form polygynous unions. This study also provides some evidence suggesting that the Christianity effects are more evident in a society at a more primitive stage of development.

Atlas-free Brain Tissue Segmentation Using a Single T1-weighted MRI Acquisition

Many studies investigating the aging brain or disease-induced brain alterations rely on accurate and reproducible brain tissue segmentation. Being a preliminary processing step prior to the segmentation, reliableskull-stripping the removal ofnon-brain tissue is also crucial for all later image assessment. Typically, segmentation algorithms rely on an atlas i.e. pre-segmented template data. Brain morphology, however, differs considerably depending on age, sex and race. In addition, diseased brains may deviate significantly from the atlas information typically gained from healthy volunteers. The imposed prior atlas information can thus lead to degradation of segmentation results. The recently introduced MP2RAGE sequence provides a bias-free T1 contrast with heavily reduced T2*- and PD-weighting compared to the standard MP-RAGE [1]. To this end, it acquires two image volumes at different inversion times in one acquisition, combining them to a uniform, i.e. homogenous image. In this work, we exploit the advantageous contrast properties of the MP2RAGE and combine it with a Dixon (i.e. fat-water separation) approach. The information gained by the additional fat image of the head considerably improves the skull-stripping outcome [2]. In conjunction with the pure T1 contrast of the MP2RAGE uniform image, we achieve robust skull-stripping and brain tissue segmentation without the use of an atlas

Theoretical investigation of convective instability in inclined and fluid-saturated three-dimensional fault zones.

The convective instability of pore-fluid flow in inclined and fluid-saturated three-dimensional fault zones has been theoretically investigated in this paper. Due to the consideration of the inclined three-dimensional fault zone with any values of the inclined angle, it is impossible to use the conventional linear stability analysis method for deriving the critical condition (i.e., the critical Rayleigh number) which can be used to investigate the convective instability of the pore-fluid flow in an inclined three-dimensional fault zone system. To overcome this mathematical difficulty, a combination of the variable separation method and the integration elimination method has been used to derive the characteristic equation, which depends on the Rayleigh number and the inclined angle of the inclined three-dimensional fault zone. Using this characteristic equation, the critical Rayleigh number of the system can be numerically found as a function of the inclined angle of the three-dimensional fault zone. For a vertically oriented three-dimensional fault zone system, the critical Rayleigh number of the system can be explicitly derived from the characteristic equation. Comparison of the resulting critical Rayleigh number of the system with that previously derived in a vertically oriented three-dimensional fault zone has demonstrated that the characteristic equation of the Rayleigh number is correct and useful for investigating the convective instability of pore-fluid flow in the inclined three-dimensional fault zone system. The related numerical results from this investigation have indicated that: (1) the convective pore-fluid flow may take place in the inclined three-dimensional fault zone; (2) if the height of the fault zone is used as the characteristic length of the system, a decrease in the inclined angle of the inclined fault zone stabilizes the three-dimensional fundamental convective flow in the inclined three-dimensional fault zone system; (3) if the thickness of the stratum is used as the characteristic length of the system, a decrease in the inclined angle of the inclined fault zone destabilizes the three-dimensional fundamental convective flow in the inclined three-dimensional fault zone system; and that (4) the shape of the inclined three-dimensional fault zone may affect the convective instability of pore-fluid flow in the system. (C) 2004 Published by Elsevier B.V.

Effects of retirement on cognitive function: A gender and international perspecive

Background: As the global population is ageing, studying cognitive impairments including dementia, one of the leading causes of disability in old age worldwide, is of fundamental importance to public health. As a major transition in older age, a focus on the complex impacts of the duration, timing, and voluntariness of retirement on health is important for policy changes in the future. Longer retirement periods, as well as leaving the workforce early, have been associated with poorer health, including reduced cognitive functioning. These associations are hypothesized to differ based on gender, as well as on pre-retirement educational and occupational experiences, and on post-retirement social factors and health conditions. Methods: A cross-sectional study is conducted to determine the relationship between duration and timing of retirement and cognitive function, using data from the five sites of International Mobility in Aging Study (IMIAS). Cognitive function is assessed using the Leganes Cognitive Test (LCT) scores in 2012. Data are analyzed using multiple linear regressions. Analyses are also done by site/region separately (Canada, Latin America, and Albania). Robustness checks are done with an analysis of cognitive change from 2012 to 2014, the effect of voluntariness of retirement on cognitive function. An instrumental variable (IV) approach is also applied to the cross-sectional and longitudinal analyses as a robustness check to address the potential endogeneity of the retirement variable. Results: Descriptive statistics highlight differences between men and women, as well as between sites. In linear regression analysis, there was no relationship between timing or duration of retirement and cognitive function in 2012, when adjusting for site/region. There was no association between retirement characteristics and cognitive function in site/region/stratified analyses. In IV analysis, longer retirement and on time or late retirement was associated with lower cognitive function among men. In IV analysis, there is no relationship between retirement characteristics and cognitive function among women. Conclusions: While results of the thesis suggest a negative effect of retirement on cognitive function, especially among men, the relationship remains uncertain. A lack of power results in the inability to draw conclusions for site/region-specific analysis and site-adjusted analysis in both linear and IV regressions.