The role of Dark Matter interaction in galaxy clusters

We consider a toy model to analyze the consequences of dark matter interaction with a dark energy background on the overall rotation of galaxy clusters and the misalignment between their dark matter and baryon distributions when compared to {\Lambda}CDM predictions. The interaction parameters are found via a genetic algorithm search. The results obtained suggest that interaction is a basic phenomenon whose effects are detectable even in simple models of galactic dynamics.Comment: RevTeX 4.1, 5 pages, 3 figure

Smart meter data processing: a showcase for simple and efficient textual processing

The increase in the production and collection of data from devices is an ongoing trend due to the roll-out of more cyber-physical applications. Smart meters, because of their importance in power grids, are a class of such devices whose produced data requires meticulous processing. In this paper, we use Unicage, a data processing system based on classic Unix shell scripting, that delivers excellent performance in a simple package. We use this methodology to process smart meter data in XML format, subjected to the constraints posed by a real use case. We develop a solution that parses, validates and performs a simple aggregation of 27 million XML files in less than 10 minutes. We present a study of the solution as well as the benefits of its adoption.Comment: 11 pages, 5 figures, 1 table, 9 listings. Accepted after review for the 1st Workshop on High-Performance and Reliable Big Data (HPBD 2021), which was held virtually on September 20th 2021, and was co-located with the 40th International Symposium on Reliable Distributed Systems (SRDS 2021

Meta-learning recommendation of default hyper-parameter values for SVMs in classifications tasks

Machine learning algorithms have been investigated in several scenarios, one of them is the data classification. The predictive performance of the models induced by these algorithms is usually strongly affected by the values used for their hyper-parameters. Different approaches to define these values have been proposed, like the use of default values and optimization techniques. Although default values can result in models with good predictive performance, different implementations of the same machine learning algorithms use different default values, leading to models with clearly different predictive performance for the same dataset. Optimization techniques have been used to search for hyper-parameter values able to maximize the predictive performance of induced models for a given dataset, but with the drawback of a high computational cost. A compromise is to use an optimization technique to search for values that are suitable for a wide spectrum of datasets. This paper investigates the use of meta-learning to recommend default values for the induction of Support Vector Machine models for a new classification dataset. We compare the default values suggested by the Weka and LibSVM tools with default values optimized by meta-heuristics on a large range of datasets. This study covers only classification task, but we believe that similar ideas could be used in other related tasks. According to the experimental results, meta-models can accurately predict whether tool suggested or optimized default values should be used.CAPESCNPqSão Paulo Research Foundation (FAPESP) (grant#2012/23114-9

Application of Scrum and PM Canvas in a Project-based Learning Approach

Project-based Learning (PBL) is a teaching and learning strategy that allows students to develop competences while working on projects. It is important to apply good management approaches in order to achieve all project and learning objectives. This paper presents an application of Scrum and Project Model Canvas (PM Canvas) to manage learning projects developed by teams of students in interaction with industrial companies. These projects are part of a Project-based Learning (PBL) approach developed in the fourth year of an integrated master program in Industrial Engineering and Management. A group of 5 students from the fifth year of the same degree gave support to the PBL teams regarding the utilization of these tools. The work was developed during one month with meetings every Fridays. These project management tools were applied to help the PBL teams to organize and share the tasks, as well as visualize and control the whole project. To evaluate the teams' performance and the way they are realizing the tasks, it was counted the number of tasks done in each weekday and the students were inquired in order to understand their perceptions of the use of these project management tools. The results revealed that the groups performed most of the tasks on Wednesday and the inquiry revealed that most of the PBL teams did not know and had never used project management tools. The inquiry also revealed that the project management tools were considered helpful for the control and organization of the project tasks, improving overall team performance.(undefined

Quantum corrections to the phase diagram of heavy-fermion superconductors

The competition between magnetism and Kondo effect is the main effect determining the phase diagram of heavy fermion systems. It gives rise to a quantum critical point which governs the low temperature properties of these materials. However, experimental results made it clear that a fundamental ingredient is missing in this description, namely superconductivity. In this paper we make a step forward in the direction of incorporating superconductivity and study the mutual effects of this phase and antiferromagnetism in the phase diagram of heavy fermion metals. Our approach is based on a Ginzburg-Landau theory describing superconductivity and antiferromagnetism in a metal with quantum corrections taken into account through an effective potential. The proximity of an antiferromagnetic instability extends the region of superconductivity in the phase diagram and drives this transition into a first order one. On the other hand superconducting quantum fluctuations near a metallic antiferromagnetic quantum critical point gives rise to a first order transition from a low moment to a high moment state in the antiferromagnet. Antiferromagnetism and superconductivity may both collapse at a quantum bicritical point whose properties we calculate.Comment: 10 pages, 6 figure

Polarization Control of the Non-linear Emission on Semiconductor Microcavities

The degree of circular polarization ($\wp$) of the non-linear emission in semiconductor microcavities is controlled by changing the exciton-cavity detuning. The polariton relaxation towards \textbf{K} $\sim 0$ cavity-like states is governed by final-state stimulated scattering. The helicity of the emission is selected due to the lifting of the degeneracy of the $\pm 1$ spin levels at \textbf{K} $\sim 0$. At short times after a pulsed excitation $\wp$ reaches very large values, either positive or negative, as a result of stimulated scattering to the spin level of lowest energy ($+1/-1$ spin for positive/negative detuning).Comment: 8 pages, 3 eps figures, RevTeX, Physical Review Letters (accepted

Validity and reliability of the Portuguese version of the modified Migraine Disability Assessment

Background Migraine Disability Assessment Scale (MIDAS) is a useful tool to measure headache-related disability. Modified MIDAS with 4-week recall period reduces recall bias and improves accuracy of the results. This study aimed at validating mMIDAS in Portuguese. Methods Studied population consisted of adult migraine patients attending a headache outpatient clinic. Reliability was assessed by internal consistency and reproducibility in a 3-week test-retest. Content validity was evaluated by two expert panels. Construct validity was tested by comparing mMIDAS-P index in socioeconomic and clinical patient groups and scale unidimensionality was evidenced by factor analysis. Criterion validity was tested using EQ-5D-5L and HADS. Results Ninety-two patients, 88% female, mean age of 44 years, participated. They had, in average, 9.7 headache days in previous month, pain averaging 7.5/10. About 69.9% were on a migraine prophylactic treatment, and 42.4% had severe disability; 29.4 and 13.0% showed, respectively, moderate/severe anxiety and depression. Content validity showed that mMIDAS-P is simple and clinically useful. It did not show to be determined by patient’s sociodemographic characteristics and it was correlated with depression scale and EQ-5D-5L. Test-retest demonstrated high reproductive reliability and good internal consistency. Conclusion mMIDAS-P is valid and reliable. We strongly recommend it for clinical and research use.This project was funded by a research grant from Novartis Farma. The authors were not in any way influenced by this funding. This was only used for logistic purposes. CEISUC/CIBB is funded by national funds through FCT - Foundation for Science and Technology, I.P., under the Multiannual Financing of R&D Units 2020–2023.info:eu-repo/semantics/publishedVersio