Adolescents' perceptions of differential parenting: Links with attachment style and adolescent adjustment

The study examines whether adolescent twins' attachment style mediates the association between their perceptions of differential parental treatment and their reported adjustment. Data from a survey of 174 adolescent twins are used to assess the links between twins' reports of differential parental affection and differential parental control, their attachment style, and their reported personal self-esteem, social self-esteem, and anxiety. Twins' reports of having been disfavored in comparison with their co-twin were associated with attachment insecurity, anxiety, and lower personal self-esteem. Attachment was found to mediate the association between the twins' reports of differential parental affection and their reported anxiety and personal self-esteem. The strongest evidence for mediation was found for twins' reports of differential maternal affection in predicting adolescent twins' anxiety.

The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

Cognitive style factors affecting database query performance

As end-user computing becomes more pervasive, an organization's success increasingly depends on the ability of end-users, usually in managerial positions, to extract appropriate data from both internal and external sources. Many of these data sources include or are derived from the organization's accounting information systems. Managerial end-users with different personal characteristics and approaches are likely to compose queries of differing levels of accuracy when searching the data contained within these accounting information systems. This research investigates how cognitive style elements of personality influence managerial end-user performance in database querying tasks. A laboratory experiment was conducted in which participants generated queries to retrieve information from an accounting information system to satisfy typical information requirements. The experiment investigated the influence of personality on the accuracy of queries of varying degrees of complexity. Relying on the Myers–Briggs personality instrument, results show that perceiving individuals (as opposed to judging individuals) who rely on intuition (as opposed to sensing) composed queries more accurately. As expected, query complexity and academic performance also explain the success of data extraction tasks.

Style and performance of international socially responsible funds in Europe

This paper analyses the performance and investment styles of internationally oriented Socially Responsible Investment (SRI)funds, domiciled in eight European markets, in comparison with characteristics-matched conventional funds. To the best of our knowledge, this is the first multi-country study, focused on international SRI funds (investing in Global and in European equities), to combine the matched-pairs approach with the use of robust conditional multi-factor performance evaluation models, which allow for both time-varying alphas and betas and also control for home biases and spurious regression biases.In general, the results show that differences in the performance of international SRI funds and their conventional peers are not statistically significant. Regarding investment styles, SRI and conventional funds exhibit similar factor exposures in most cases. In addition,conventional benchmarks present a higher explaining power of SRI fund returns than SRI benchmarks. Our results also show significant differences in the investment styles of SRI funds according to whether they use “best-in-class” screening strategies or not. When compared to SRI funds that employ simple negative and/or positive screens, SRI “best-in-class” funds present significantly lower exposures to small caps and momentum strategies and significantly higher exposures to local stocks.

Smoking, consumption of alcohol and sedentary life style in population grouping and their relationships with lipemic disorders

The study, part of the project "Atherosclerotic cardiovascular diseases, lipemic disorders, hypertension, obesity and diabetis mellitus in a population of the metropolitan area of the southeastern region of Brazil", had the following objectives: a) the characterization and distribution among typical human socio-economic groupings, of the prevalence of some particular habits which constitute aspects of life-style-the use of tobacco, the use of alcohol and sedentary activity; b) the establishment of the interrelation between the above-mentioned habits and some lipemic disorders. The prevalence of the habits cited behaved in the following manner: the use of tobacco predominated among men, distributed uniformly throughout the social strata; among the women the average percentage of smokers was 18,9%, a significant difference occurring among the highest socio-economic class, where the average was of 40.2%. The sedentary style of life presented high prevalence, among both men and women with exception of the women of the highest socio-economic level and of the skilled working class. The use of alcohol, as one would expect, is a habit basically practised by the men, without any statistically significant differences between classes. For the purpose of establishing associations between these risk fictors and lipemic conditions four situations were chosen, of the following characteristics: 1- total cholesterol > or = 220 mg/dl and triglycerides > or = 150 mg/dl; 2- HDL cholesterol <35 mg/dl for men and <45 mg/dl for women and triglycerides levels > or = 150 mg/dl; 3- HDL cholesterol <35 mg/dl for men and <45 mg/dl for women and triglycerides levels <150 mg/dl; 4- total cholesterol 220 mg/dl with triglycerides levels <150 mg/dl. Six models of multiple (backward) regression were established, with seven independent variables- age, sex, use of tobacco, consumption of alcohol, light physical activity, hypertension and obesity. Significant associations (P<0,05) were revealed with hypercholesterolemia, accompanied by triglyceride levels > or = 150 mg/dl, and the following independent variables: age, use of tobacco and the interactions between obesity and smoking, age and sedentary lifestyle, sex and obesity (R2=22%); the standardized B coefficient showed that the variables with the greatest weight in the forecasting of the variation in the levels of cholesterol were smoking and the interaction between obesity and smoking. The hypercholesterolemia accompanied by triglycerides levels <150 mg/dl showed a positive association between total cholesterol and sex and the interactions obesity/smoking and sex/obesity. As regards HDL cholesterol accompanied by triglyceride/ levels > or = 150 mg/dl was inversely associated with obesity and the interaction smoking/ age and directly with age (R=31%). The standardized B coeffients, indicated that the variables obesity and the interactions smoking/age possessed a weight three times greater than age alone in accounting for the variation in the serum levels of HDL cholesterol. When accompanied by triglycerides <150 mg/dl there was no association between and the independent variables and the set of them presented R equal to 22%. The sum of top, in the population stutied in this project, the component habits of life-style (smoking, alcohol consumption and sedentary activity) which constitute risk factors which determine morbidity from atherosclerotic cardiovascular diseases are be found distributed through all the typical social groupings of this particular form of social organization. On the other hand, the seven independent variables used in the multiple regression models for the explanation of the lipemic conditions considered presented multiple determination coefficients which varied, approximately, between 20% and 30%. Thus it is important that in the genetic epidemiology the study of the morbidities in question be emphasized.

Scheduling of head-dependent cascaded hydro systems: Mixed-integer quadratic programming approach

This paper is on the problem of short-term hydro, scheduling, particularly concerning head-dependent cascaded hydro systems. We propose a novel mixed-integer quadratic programming approach, considering not only head-dependency, but also discontinuous operating regions and discharge ramping constraints. Thus, an enhanced short-term hydro scheduling is provided due to the more realistic modeling presented in this paper. Numerical results from two case studies, based on Portuguese cascaded hydro systems, illustrate the proficiency of the proposed approach.

Addressing the facilities layout design problem through constraint logic programming

One of the most difficult problems that face researchers experimenting with complex systems in real world applications is the Facility Layout Design Problem. It relies with the design and location of production lines, machinery and equipment, inventory storage and shipping facilities. In this work it is intended to address this problem through the use of Constraint Logic Programming (CLP) technology. The use of Genetic Algorithms (GA) as optimisation technique in CLP environment is also an issue addressed. The approach aims the implementation of genetic algorithm operators following the CLP paradigm.

Hybrid fuzzy Monte Carlo and logic programming model for distribution network reconfiguration in the presence of outages

This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.

Logic programming and fuzzy Monte Carlo for distribution network reconfiguration

This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations.

Ancillary services dispatch using linear programming and genetic algorithm approaches

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

New insights on integer-programming models for the kidney exchange problem

In recent years several countries have set up policies that allow exchange of kidneys between two or more incompatible patient–donor pairs. These policies lead to what is commonly known as kidney exchange programs. The underlying optimization problems can be formulated as integer programming models. Previously proposed models for kidney exchange programs have exponential numbers of constraints or variables, which makes them fairly difficult to solve when the problem size is large. In this work we propose two compact formulations for the problem, explain how these formulations can be adapted to address some problem variants, and provide results on the dominance of some models over others. Finally we present a systematic comparison between our models and two previously proposed ones via thorough computational analysis. Results show that compact formulations have advantages over non-compact ones when the problem size is large.

BabeLO : an extensible converter of programming exercises formats

In the last two decades, there was a proliferation of programming exercise formats that hinders interoperability in automatic assessment. In the lack of a widely accepted standard, a pragmatic solution is to convert content among the existing formats. BabeLO is a programming exercise converter providing services to a network of heterogeneous e-learning systems such as contest management systems, programming exercise authoring tools, evaluation engines and repositories of learning objects. Its main feature is the use of a pivotal format to achieve greater extensibility. This approach simplifies the extension to other formats, just requiring the conversion to and from the pivotal format. This paper starts with an analysis of programming exercise formats representative of the existing diversity. This analysis sets the context for the proposed approach to exercise conversion and to the description of the pivotal data format. The abstract service definition is the basis for the design of BabeLO, its components and web service interface. This paper includes a report on the use of BabeLO in two concrete scenarios: to relocate exercises to a different repository, and to use an evaluation engine in a network of heterogeneous systems.