Improving Social Understanding of Preschool Children: Evaluation of a Training Program

This study tested the effects of a training program intending to foster social understanding or the capacity which enables them to understand themselves and others in terms of intentions, beliefs, desires, and emotions in children at preschool age. A number of studies have shown that in the context of shared narratives, children are particularly likely to engage in talk about inner states

Improving Information Problem Solving skills in Secondary Education through embedded instruction

This empirical study consists in an investigation of the effects, on the development of Information Problem Solving (IPS) skills, of a long-term embedded, structured and supported instruction in Secondary Education. Forty secondary students of 7th and 8th grades (13–15 years old) participated in the 2-year IPS instruction designed in this study. Twenty of them participated in the IPS instruction, and the remaining twenty were the control group. All the students were pre- and post-tested in their regular classrooms, and their IPS process and performance were logged by means of screen capture software, to warrant their ecological validity. The IPS constituent skills, the web search sub-skills and the answers given by each participant were analyzed. The main findings of our study suggested that experimental students showed a more expert pattern than the control students regarding the constituent skill ‘defining the problem’ and the following two web search sub-skills: ‘search terms’ typed in a search engine, and ‘selected results’ from a SERP. In addition, scores of task performance were statistically better in experimental students than in control group students. The paper contributes to the discussion of how well-designed and well-embedded scaffolds could be designed in instructional programs in order to guarantee the development and efficiency of the students’ IPS skills by using net information better and participating fully in the global knowledge society.

Improving algorithm speed in PNL mixture separation and Wiener system inversion

This paper proposes a very simple method for increasing the algorithm speed for separating sources from PNL mixtures or invertingWiener systems. The method is based on a pertinent initialization of the inverse system, whose computational cost is very low. The nonlinear part is roughly approximated by pushing the observations to be Gaussian; this method provides a surprisingly good approximation even when the basic assumption is not fully satisfied. The linear part is initialized so that outputs are decorrelated. Experiments shows the impressive speed improvement.

Improving the Quality of EEG Data in Patients With Alzheimers Disease Using ICA

Does Independent Component Analysis (ICA) denature EEG signals? We applied ICA to two groups of subjects (mild Alzheimer patients and control subjects). The aim of this study was to examine whether or not the ICA method can reduce both group di®erences and within-subject variability. We found that ICA diminished Leave-One- Out root mean square error (RMSE) of validation (from 0.32 to 0.28), indicative of the reduction of group di®erence. More interestingly, ICA reduced the inter-subject variability within each group (¾ = 2:54 in the ± range before ICA, ¾ = 1:56 after, Bartlett p = 0.046 after Bonfer- roni correction). Additionally, we present a method to limit the impact of human error (' 13:8%, with 75.6% inter-cleaner agreement) during ICA cleaning, and reduce human bias. These ¯ndings suggests the novel usefulness of ICA in clinical EEG in Alzheimer's disease for reduction of subject variability.

Improving Pitch Tracking Performance in Hard Noise Conditions by a Preprocessing Based on Mathematical Morphology

In this paper we show how a nonlinear preprocessing of speech signal -with high noise- based on morphological filters improves the performance of robust algorithms for pitch tracking (RAPT). This result happens for a very simple morphological filter. More sophisticated ones could even improve such results. Mathematical morphology is widely used in image processing and has a great amount of applications. Almost all its formulations derived in the two-dimensional framework are easily reformulated to be adapted to one-dimensional context

Gene Set Analysis for improving genetic association studies

Introduction. Genetic epidemiology is focused on the study of the genetic causes that determine health and diseases in populations. To achieve this goal a common strategy is to explore differences in genetic variability between diseased and nondiseased individuals. Usual markers of genetic variability are single nucleotide polymorphisms (SNPs) which are changes in just one base in the genome. The usual statistical approach in genetic epidemiology study is a marginal analysis, where each SNP is analyzed separately for association with the phenotype. Motivation. It has been observed, that for common diseases the single-SNP analysis is not very powerful for detecting genetic causing variants. In this work, we consider Gene Set Analysis (GSA) as an alternative to standard marginal association approaches. GSA aims to assess the overall association of a set of genetic variants with a phenotype and has the potential to detect subtle effects of variants in a gene or a pathway that might be missed when assessed individually. Objective. We present a new optimized implementation of a pair of gene set analysis methodologies for analyze the individual evidence of SNPs in biological pathways. We perform a simulation study for exploring the power of the proposed methodologies in a set of scenarios with different number of causal SNPs under different effect sizes. In addition, we compare the results with the usual single-SNP analysis method. Moreover, we show the advantage of using the proposed gene set approaches in the context of an Alzheimer disease case-control study where we explore the Reelin signal pathway.

Improving the performance of the single-dish Cherenkov telescope MAGIC through the use of signal timing

The Cherenkov light flashes produced by Extensive Air Showers are very short in time. A high bandwidth and fast digitizing readout, therefore, can minimize the influence of the background from the light of the night sky, and improve the performance in Cherenkov telescopes. The time structure of the Cherenkov image can further be used in single-dish Cherenkov telescopes as an additional parameter to reduce the background from unwanted hadronic showers. A description of an analysis method which makes use of the time information and the subsequent improvement on the performance of the MAGIC telescope (especially after the upgrade with an ultra fast 2 GSamples/s digitization system in February 2007) will be presented. The use of timing information in the analysis of the new MAGIC data reduces the background by a factor two, which in turn results in an enhancement of about a factor 1.4 of the flux sensitivity to point-like sources, as tested on observations of the Crab Nebula.

Research Priorities for seabirds: Improving seabird conservation and management in the 21st century

Seabirds are facing a growing number of threats in both terrestrial and marine habitats, and many populations have experienced dramatic changes over past decades. Years of seabird research have improved our understanding of seabird populations and provided a broader understanding of marine ecological processes. In an effort to encourage future research and guide seabird conservation science, seabird researchers from 9 nations identified the 20 highest priority research questions and organized these into 6 general categories: (1) population dynamics, (2) spatial ecology, (3) tropho-dynamics, (4) fisheries interactions, (5) response to global change, and (6) management of anthropogenic impacts (focusing on invasive species, contaminants and protected areas). For each category, we provide an assessment of the current approaches, challenges and future directions. While this is not an exhaustive list of all research needed to address the myriad conservation challenges seabirds face, the results of this effort represent an important synthesis of current expert opinion across sub-disciplines within seabird ecology. As this synthesis highlights, research, in conjunction with direct management, education, and community engagement, can play an important role in facilitating the conservation and management of seabird populations and of the ocean ecosystems on which they and we depend.

Improving Label Space Usage for Ethernet Label Switched Paths

Ethernet is becoming the dominant aggregation technology for carrier transport networks; however, as it is a LAN technology, native bridged ethernet does not fulfill all the carrier requirements. One of the schemes proposed by the research community to make ethernet fulfill carrier requirements is ethernet VLAN-label switching (ELS). ELS allows the creation of label switched data paths using a 12-bit label encoded in the VLAN TAG control information field. Previous label switching technologies such as MPLS use more bits for encoding the label. Hence, they do not suffer from label sparsity issues as ELS might. This paper studies the sparsity issues resulting from the reduced ELS VLAN-label space and proposes the use of the label merging technique to improve label space usage. Experimental results show that label merging considerably improves label space usage

Improving the efficiency of PV low-power processing circuits by selecting an optimal inductor current of the DC/DC converter

In the context of autonomous sensors powered by small-size photovoltaic (PV) panels, this work analyses how the efficiency of DC/DC-converter-based power processing circuits can be improved by an appropriate selection of the inductor current that transfers the energy from the PV panel to a storage unit. Each component of power losses (fixed, conduction and switching losses) involved in the DC/DC converter specifically depends on the average inductor current so that there is an optimal value of this current that causes minimal losses and, hence, maximum efficiency. Such an idea has been tested experimentally using two commercial DC/DC converters whose average inductor current is adjustable. Experimental results show that the efficiency can be improved up to 12% by selecting an optimal value of that current, which is around 300-350 mA for such DC/DC converters.

Improving interMediAte Risk management. MARK study

Background: Cardiovascular risk functions fail to identify more than 50% of patients who develop cardiovascular disease. This is especially evident in the intermediate-risk patients in which clinical management becomes difficult. Our purpose is to analyze if ankle-brachial index (ABI), measures of arterial stiffness, postprandial glucose, glycosylated hemoglobin, self-measured blood pressure and presence of comorbidity are independently associated to incidence of vascular events and whether they can improve the predictive capacity of current risk equations in the intermediate-risk population. Methods/Design: This project involves 3 groups belonging to REDIAPP (RETICS RD06/0018) from 3 Spanish regions. We will recruit a multicenter cohort of 2688 patients at intermediate risk (coronary risk between 5 and 15% or vascular death risk between 3-5% over 10 years) and no history of atherosclerotic disease, selected at random. We will record socio-demographic data, information on diet, physical activity, comorbidity and intermittent claudication. We will measure ABI, pulse wave velocity and cardio ankle vascular index at rest and after a light intensity exercise. Blood pressure and anthropometric data will be also recorded. We will also quantify lipids, glucose and glycosylated hemoglobin in a fasting blood sample and postprandial capillary glucose. Eighteen months after the recruitment, patients will be followed up to determine the incidence of vascular events (later follow-ups are planned at 5 and 10 years). We will analyze whether the new proposed risk factors contribute to improve the risk functions based on classic risk factors. Discussion: Primary prevention of cardiovascular diseases is a priority in public health policy of developed and developing countries. The fundamental strategy consists in identifying people in a high risk situation in which preventive measures are effective and efficient. Improvement of these predictions in our country will have an immediate, clinical and welfare impact and a short term public health effect

Improving the oscillating grid method to characterize aquaculture biosolids using a laser beam and image analysis

Quickremovalofbiosolidsinaquaculturefacilities,andspeciallyinrecirculatingaquaculturesystems(RAS),isoneofthemostimportantstepinwastemanagement.Sedimentationdynamicsofbiosolidsinanaquaculturetankwilldeterminetheiraccumulationatthebottomofthetank.

Combine to compete: improving fiscal forecast accuracy over time

Budget forecasts have become increasingly important as a tool of fiscal management to influence expectations of bond markets and the public at large. The inherent difficulty in projecting macroeconomic variables – together with political bias – thwart the accuracy of budget forecasts. We improve accuracy by combining the forecasts of both private and public agencies for Italy over the period 1993-2012. A weighted combined forecast of the deficit/ ratio is superior to any single forecast. Deficits are hard to predict due to shifting economic conditions and political events. We test and compare predictive accuracy over time and although a weighted combined forecast is robust to breaks, there is no significant improvement over a simple RW model.

Combine to compete: improving fiscal forecast accuracy over time

Budget forecasts have become increasingly important as a tool of fiscal management to influence expectations of bond markets and the public at large. The inherent difficulty in projecting macroeconomic variables – together with political bias – thwart the accuracy of budget forecasts. We improve accuracy by combining the forecasts of both private and public agencies for Italy over the period 1993-2012. A weighted combined forecast of the deficit/ ratio is superior to any single forecast. Deficits are hard to predict due to shifting economic conditions and political events. We test and compare predictive accuracy over time and although a weighted combined forecast is robust to breaks, there is no significant improvement over a simple RW model.