Size Matters: The Effect of the Scramble for Africa on Informal Institutions and Development

We argue that the partition of ethnic groups following the Scramble for Africa does not itself matter for development in Africa. It matters only when the partitioned groups are relatively small because small groups lack political representation which may promote ethnic mobilization and foster support for informal (rather than formal) institutions which then may a ect development. Furthermore, the analysis of data from the Afrobarometer shows that the persistence of informal/tribal institutions related to property rights and the rule of law is one of the possible channels through which the size of the partitioned group a ects development.

Analysis of voltage source converter-based high-voltage direct current under DC line-to-earth fault

DC line faults on high-voltage direct current (HVDC) systems utilising voltage source converters (VSCs) are a major issue for multi-terminal HVDC systems in which complete isolation of the faulted system is not a viable option. Of these faults, single line-to-earth faults are the most common fault scenario. To better understand the system under such faults, this study analyses the behaviour of HVDC systems based on both conventional two-level converter and multilevel modular converter technology, experiencing a permanent line-to-earth fault. Operation of the proposed system under two different earthing configurations of converter side AC transformer earthed with converter unearthed, and both converter and AC transformer unearthed, was analysed and simulated, with particular attention paid to the converter operation. It was observed that the development of potential earth loops within the system as a result of DC line-to-earth faults leads to substantial overcurrent and results in oscillations depending on the earthing configuration.

A quality-scalable and energy-efficient approach for spectral analysis of heart rate variability

Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case. 

Family Economic Vulnerability & the Great Recession: An Analysis of the First two Waves of the Growing Up in Ireland Study

In this paper we make use of the first and second waves of the 2008 and 1998 cohorts of the Growing Up in Ireland study, to develop a multidimensional and dynamic approach to understanding the impact on families and children in Ireland of the Great Recession. Economic vulnerability is operationalised as involving a distinctive risk profile in relation to relative income, household joblessness and economic stress. We find that the recession was associated with a significant increase in levels of economic vulnerability and changing risk profiles involving a more prominent role for economic stress for both the 2008 and 1998 cohorts. The factors affecting vulnerability outcomes were broadly similar for both cohorts. Persistent economic vulnerability was significantly associated with lone parenthood, particularly for those with more than one child, lower levels of Primary Care Giver (PCG) education and to a lesser extent younger age of PCG at child’s birth, number of children and a parent leaving or dying. Similar factors were associated with transient vulnerability in the first wave but the magnitude of the effects was significantly weaker particularly in relation to lone parenthood and level of education of the PCG. For entry into vulnerability the impact of these factors was again substantially weaker than for persistent and transient vulnerability indicating a significantly greater degree of socio-economic heterogeneity among the group that became vulnerable during the recession. The findings raise policy and political problems that go beyond those associated with catering for groups that have tended to be characterized by high dependence on social welfare.

An analysis of stage performance in automotive turbocharger centrifugal compressors

As the concept of engine downsizing becomes ever more integrated into automotive powertrain development strategies, so too does the pressure on turbocharger manufacturers to deliver improvements in map width and a reduction in the mass flow rate at which compressor surge occurs. A consequence of this development is the increasing importance of recirculating flows, both in the impeller inlet and outlet domains, on stage performance.
The current study seeks to evaluate the impact of the inclusion of impeller inlet recirculation on a meanline centrifugal compressor design tool. Using a combination of extensive test data, single passage CFD predictions, and 1-D analysis it is demonstrated how the addition of inlet recirculation modelling impacts upon stage performance close to the surge line. It is also demonstrated that, in its current configuration, the accuracy of the 1-D model prediction diminishes significantly with increasing blade tip speed.
Having ascertained that the existing model requires further work, an evaluation of the vaneless diffuser modelling method currently employed within the existing 1-D model is undertaken. The comparison of the predicted static pressure recovery coefficient with test data demonstrated the inherent inadequacies in the resulting prediction, in terms of both magnitude and variation with flow rate. A simplified alternative method based on an equivalent friction coefficient is also presented that, with further development, could provide a significantly improved stage performance prediction.

A well-to-wheel analysis of electric vehicles in the all-island Single Electricity Market

The European Union has set a target for 10% renewable energy in transport by 2020 to be met using biofuels and electric vehicles. In the case of biofuels, the biofuel must achieve greenhouse gas savings of 35% relative to the fossil fuel replaced. For biofuels, greenhouse gas savings can be calculated using life cycle analysis or the European Union default values. In contrast, all electricity used in transport is considered to be the same, regardless of the source or the type of electric vehicle. However, the choice of the electric vehicle and electricity source will have a major impact on the greenhouse gas saving. In this paper the initial findings of a well-to-wheel analysis of electric vehicle deployment in Northern Ireland are presented. The key finding indicates that electric vehicles require least amount of energy per mile on a well-to-wheel basis, consume the fewest resources, even accommodating inefficient fuel production, in comparison to standard internal combustion engine and hybrid vehicles.

Preferred Reporting Items for a Systematic Review and Meta-analysis of Individual Participant Data The PRISMA-IPD Statement

IMPORTANCE Systematic reviews and meta-analyses of individual participant data (IPD) aim to collect, check, and reanalyze individual-level data from all studies addressing a particular research question and are therefore considered a gold standard approach to evidence synthesis. They are likely to be used with increasing frequency as current initiatives to share clinical trial data gain momentum and may be particularly important in reviewing controversial therapeutic areas.

OBJECTIVE To develop PRISMA-IPD as a stand-alone extension to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Statement, tailored to the specific requirements of reporting systematic reviews and meta-analyses of IPD. Although developed primarily for reviews of randomized trials, many items will apply in other contexts, including reviews of diagnosis and prognosis.

DESIGN Development of PRISMA-IPD followed the EQUATOR Network framework guidance and used the existing standard PRISMA Statement as a starting point to draft additional relevant material. A web-based survey informed discussion at an international workshop that included researchers, clinicians, methodologists experienced in conducting systematic reviews and meta-analyses of IPD, and journal editors. The statement was drafted and iterative refinements were made by the project, advisory, and development groups. The PRISMA-IPD Development Group reached agreement on the PRISMA-IPD checklist and flow diagram by consensus.

FINDINGS Compared with standard PRISMA, the PRISMA-IPD checklist includes 3 new items that address (1) methods of checking the integrity of the IPD (such as pattern of randomization, data consistency, baseline imbalance, and missing data), (2) reporting any important issues that emerge, and (3) exploring variation (such as whether certain types of individual benefit more from the intervention than others). A further additional item was created by reorganization of standard PRISMA items relating to interpreting results. Wording was modified in 23 items to reflect the IPD approach.

CONCLUSIONS AND RELEVANCE PRISMA-IPD provides guidelines for reporting systematic reviews and meta-analyses of IPD.

Empirical testing of genuine savings as an indicator of weak sustainability: a three-country analysis of long run trends

Genuine Savings has emerged as a widely used indicator of sustainable development. In this paper, we use long -term data stretching back to 1870 to undertake empirical tests of the relationship between Genuine Savings (GS) and future well-being for three countries: Britain, the USA and Germany. Our tests are based on an underlying theoretical relationship between GS and changes in the present value of future consumption. Based on both single country and panel results, we find evidence supporting the existence of javascript:void(0);a cointegrating (long run equilibrium) relationship between GS and future well-being, and fail to reject the basic theoretical result on the relationship between these two macroeconomic variables. This provides some support for the GS measure of weak sustainability.

Breaking Glass: Towards a Gendered Analysis of Entrepreneurial Leadership

Despite recent expansion in the literature on entrepreneurial leadership, this has not been matched with the development of appropriate theoretical frameworks, theory building, and conceptual analyses, including the analysis of gender. In this paper, we provide the foundation for a more robust and extensive gendered study of entrepreneurial leadership, through a review of the entrepreneurial leadership literature and of the current debates on gender and leadership. On the basis of this, we propose a research agenda for the gendered analysis of the rapidly expanding interface between leadership and entrepreneurship, comprising three themes around which the future development of entrepreneurial leadership can be organized.

Recent Developments in the Analysis of the Black Mat Layer and Cosmic Impact at 12.8ka

Recent analyses of sediment samples from "black mat" sites in South America and Europe support previous interpretations of an ET impact event that reversed the Late Glacial demise of LGM ice during the Bølling Allerød warming, resulting in a resurgence of ice termed the Younger Dryas (YD) cooling episode. The breakup or impact of a cosmic vehicle at the YD boundary coincides with the onset of a 1-kyr long interval of glacial resurgence, one of the most studied events of the Late Pleistocene. New analytical databases reveal a corpus of data indicating that the cosmic impact was a real event, most possibly a cosmic airburst from Earth's encounter with the Taurid Complex comet or unknown asteroid, an event that led to cosmic fragments exploding interhemispherically over widely dispersed areas, including the northern Andes of Venezuela and the Alps on the Italian/French frontier. While the databases in the two areas differ somewhat, the overall interpretation is that microtextural evidence in weathering rinds and in sands of associated paleosols and glaciofluvial deposits carry undeniable attributes of melted glassy carbon and Fe spherules, planar deformation features, shock-melted and contorted quartz, occasional transition and platinum metals, and brecciated and impacted minerals of diverse lithologies. In concert with other black mat localities in the Western USA, the Netherlands, coastal France, Syria, Central Asia, Peru, Argentina and Mexico, it appears that a widespread cosmic impact by an asteroid or comet is responsible for deposition of the black mat at the onset of the YD glacial event. Whether or not the impact caused a 1-kyr interval of glacial climate depends upon whether or not the Earth had multiple centuries-long episodic encounters with the Taurid Complex or asteroid remnants; impact-related changes in microclimates sustained climatic forcing sufficient to maintain positive mass balances in the reformed ice; and/or inertia in the Atlantic thermohaline circulation system persisted for 1kyr. 

Integrative analysis of chemo-transcriptomic profiles for drug-feature specific gene expression signatures

One of the major challenges in systems biology is to understand the complex responses of a biological system to external perturbations or internal signalling depending on its biological conditions. Genome-wide transcriptomic profiling of cellular systems under various chemical perturbations allows the manifestation of certain features of the chemicals through their transcriptomic expression profiles. The insights obtained may help to establish the connections between human diseases, associated genes and therapeutic drugs. The main objective of this study was to systematically analyse cellular gene expression data under various drug treatments to elucidate drug-feature specific transcriptomic signatures. We first extracted drug-related information (drug features) from the collected textual description of DrugBank entries using text-mining techniques. A novel statistical method employing orthogonal least square learning was proposed to obtain drug-feature-specific signatures by integrating gene expression with DrugBank data. To obtain robust signatures from noisy input datasets, a stringent ensemble approach was applied with the combination of three techniques: resampling, leave-one-out cross validation, and aggregation. The validation experiments showed that the proposed method has the capacity of extracting biologically meaningful drug-feature-specific gene expression signatures. It was also shown that most of signature genes are connected with common hub genes by regulatory network analysis. The common hub genes were further shown to be related to general drug metabolism by Gene Ontology analysis. Each set of genes has relatively few interactions with other sets, indicating the modular nature of each signature and its drug-feature-specificity. Based on Gene Ontology analysis, we also found that each set of drug feature (DF)-specific genes were indeed enriched in biological processes related to the drug feature. The results of these experiments demonstrated the pot- ntial of the method for predicting certain features of new drugs using their transcriptomic profiles, providing a useful methodological framework and a valuable resource for drug development and characterization.

The Reliability of the Arc-Length Method in the Analysis of Mode-Jumping Problems

The Arc-Length Method is a solution procedure that enables a generic non-linear problem to pass limit points. Some examples are provided of mode-jumping problems solutions using a commercial nite element package, and other investigations are carried out on a simple structure of which the numerical solution can be compared with an analytical one. It is shown that Arc-Length Method is not reliable when bifurcations are present in the primary equilibrium path; also the presence of very sharp snap-backs or special boundary conditions may cause convergence diÆculty at limit points. An improvement to the predictor used in the incremental procedure is suggested, together with a reliable criteria for selecting either solution of the quadratic arc-length constraint. The gap that is sometimes observed between the experimantal load level of mode-jumping and its arc-length prediction is explained through an example.

A Cyber-Physical Security Analysis of Synchronous-Islanded Microgrid Operation

Cyber-security research in the field of smart grids is often performed with a focus on either the power and control domain or the Information and Communications Technology (ICT) domain. The characteristics of the power equipment or ICT domain are commonly not collectively considered. This work provides an analysis of the physical effects of cyber-attacks on microgrids – a smart grid construct that allows continued power supply when disconnected from a main grid. Different types of microgrid operations are explained (connected, islanded and synchronous-islanding) and potential cyber-attacks and their physical effects are analyzed. A testbed that is based on physical power and ICT equipment is presented to validate the results in both the physical and ICT domain.

The Risk Implications of Globalisation: An Exploratory Analysis of 105 Major Industrial Incidents (1971–2010)

This paper revisits work on the socio-political amplification of risk, which predicts that those living in developing countries are exposed to greater risk than residents of developed nations. This prediction contrasts with the neoliberal expectation that market driven improvements in working conditions within industrialising/developing nations will lead to global convergence of hazard exposure levels. It also contradicts the assumption of risk society theorists that there will be an ubiquitous increase in risk exposure across the globe, which will primarily affect technically more advanced countries. Reviewing qualitative evidence on the impact of structural adjustment reforms in industrialising countries, the export of waste and hazardous waste recycling to these countries and new patterns of domestic industrialisation, the paper suggests that workers in industrialising countries continue to face far greater levels of hazard exposure than those of developed countries. This view is confirmed when a data set including 105 major multi-fatality industrial disasters from 1971 to 2000 is examined. The paper concludes that there is empirical support for the predictions of socio-political amplification of risk theory, which finds clear expression in the data in a consistent pattern of significantly greater fatality rates per industrial incident in industrialising/developing countries.

Statistical Tests for Joint Analysis of Performance Measures

Recently there has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and architectural complexity). Once one has learned a model based on their devised method, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Unfortunately, the standard tests used for this purpose are not able to jointly consider performance measures. The aim of this paper is to resolve this issue by developing statistical procedures that are able to account for multiple competing measures at the same time. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood-ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameter of such models, as usually the number of studied cases is very reduced in such comparisons. Real data from a comparison among general purpose classifiers is used to show a practical application of our tests.