Frequency-tunable metamaterials using broadside-coupled split ring resonators

We present frequency tunable metamaterial designs at terahertz (THz) frequencies using broadside-coupled split ring resonator (BC-SRR) arrays. Frequency tuning, arising from changes in near field coupling, is obtained by in-plane horizontal or vertical displacements of the two SRR layers. For electrical excitation, the resonance frequency continuously redshifts as a function of displacement. The maximum frequency shift occurs for displacement of half a unit cell, with vertical displacement resulting in a shift of 663 GHz (51% of f0) and horizontal displacement yielding a shift of 270 GHz (20% of f0). We also discuss the significant differences in tuning that arise for electrical excitation in comparison to magnetic excitation of BC-SRRs

Amygdala responses to emotionally valenced stimuli in older and younger adults

ABSTRACT—As they age, adults experience less negative emotion, come to pay less attention to negative than to positive emotional stimuli, and become less likely to remember negative than positive emotional materials. This profile of findings suggests that, with age, the amygdala may show decreased reactivity to negative information while maintaining or increasing its reactivity to positive information. We used event-related functional magnetic resonance imaging to assess whether amygdala activation in response to positive and negative emotional pictures changes with age. Both older and younger adults showed greater activation in the amygdala for emotional than for neutral pictures; however, for older adults, seeing positive pictures led to greater amygdala activation than seeing negative pictures, whereas this was not the case for younger adults. Older adults experience less negative affect than younger adults in both cross-sectional and longitudinal studies (Carstensen, Pasupathi

An external replication on the effects of test-driven development using a multi-site blind analysis approach

Context: Test-driven development (TDD) is an agile practice claimed to improve the quality of a software product, as well as the productivity of its developers. A previous study (i.e., baseline experiment) at the University of Oulu (Finland) compared TDD to a test-last development (TLD) approach through a randomized controlled trial. The results failed to support the claims. Goal: We want to validate the original study results by replicating it at the University of Basilicata (Italy), using a different design. Method: We replicated the baseline experiment, using a crossover design, with 21 graduate students. We kept the settings and context as close as possible to the baseline experiment. In order to limit researchers bias, we involved two other sites (UPM, Spain, and Brunel, UK) to conduct blind analysis of the data. Results: The Kruskal-Wallis tests did not show any significant difference between TDD and TLD in terms of testing effort (p-value = .27), external code quality (p-value = .82), and developers' productivity (p-value = .83). Nevertheless, our data revealed a difference based on the order in which TDD and TLD were applied, though no carry over effect. Conclusions: We verify the baseline study results, yet our results raises concerns regarding the selection of experimental objects, particularly with respect to their interaction with the order in which of treatments are applied. We recommend future studies to survey the tasks used in experiments evaluating TDD. Finally, to lower the cost of replication studies and reduce researchers' bias, we encourage other research groups to adopt similar multi-site blind analysis approach described in this paper.This research is supported in part by the Academy of Finland Project 278354

Software defect prediction: do different classifiers find the same defects?

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.During the last 10 years, hundreds of different defect prediction models have been published. The performance of the classifiers used in these models is reported to be similar with models rarely performing above the predictive performance ceiling of about 80% recall. We investigate the individual defects that four classifiers predict and analyse the level of prediction uncertainty produced by these classifiers. We perform a sensitivity analysis to compare the performance of Random Forest, Naïve Bayes, RPart and SVM classifiers when predicting defects in NASA, open source and commercial datasets. The defect predictions that each classifier makes is captured in a confusion matrix and the prediction uncertainty of each classifier is compared. Despite similar predictive performance values for these four classifiers, each detects different sets of defects. Some classifiers are more consistent in predicting defects than others. Our results confirm that a unique subset of defects can be detected by specific classifiers. However, while some classifiers are consistent in the predictions they make, other classifiers vary in their predictions. Given our results, we conclude that classifier ensembles with decision-making strategies not based on majority voting are likely to perform best in defect prediction.Peer reviewedFinal Published versio

Results from an ethnographically-informed study in the context of test driven development

Background: Test-driven development (TDD) is an iterative software development technique where unit tests are defined before production code. Previous studies fail to analyze the values, beliefs, and assumptions that inform and shape TDD. Aim: We designed and conducted a qualitative study to understand the values, beliefs, and assumptions of TDD. In particular, we sought to understand how novice and professional software developers, arranged in pairs (a driver and a pointer), perceive and apply TDD. Method: 14 novice software developers, i.e., graduate students in Computer Science at the University of Basilicata, and six professional software developers (with one to 10 years work experience) participated in our ethnographicallyinformed study. We asked the participants to implement a new feature for an existing software written in Java. We immersed ourselves in the context of the study, and collected data by means of contemporaneous field notes, audio recordings, and other artifacts. Results: A number of insights emerge from our analysis of the collected data, the main ones being: (i) refactoring (one of the phases of TDD) is not performed as often as the process requires and it is considered less important than other phases, (ii) the most important phase is implementation, (iii) unit tests are almost never up-to-date, (iv) participants first build a sort of mental model of the source code to be implemented and only then write test cases on the basis of this model; and (v) apart from minor differences, professional developers and students applied TDD in a similar fashion. Conclusions: Developers write quick-and-dirty production code to pass the tests and ignore refactoring.Copyright is held by the owner/auther(s)

Adsorption of methylene blue from aqueous solutions by pyrolusite ore

In this study, the adsorption of methylene blue dye was examined by using pyrolusite ore as a low-cost alternative adsorbent source. Pyrolusite, which contains mainly MnO2, is a manganese ore. The effects of the initial concentration of dye, contact time, initial pH of solution, adsorbent dosage, stirring speed of solution, and average particle size of adsorbent on the adsorption of methylene blue were studied. It was found that the percentage of the adsorbed dye increased with increasing the amount of pyrolusite. While the initial dye concentration, initial pH, contact time, stirring speed, particle size, and adsorbent dosage were 25 ppm, 6, 90 min, 250 rpm, 63 µm, and 12 g/l, respectively, the efficiency of dye adsorption on pyrolusite ore was 99%. The isotherm and kinetic studies relating to this adsorption process were also made. It was found that the equilibrium data followed the Langmuir isotherm model while the kinetic of process could be described by the pseudo-second order kinetic model

Adsorption of methylene blue from aqueous solutions by pyrolusite ore

In this study, the adsorption of methylene blue dye was examined by using pyrolusite ore as a low-cost alternative adsorbent source. Pyrolusite, which contains mainly MnO2, is a manganese ore. The effects of the initial concentration of dye, contact time, initial pH of solution, adsorbent dosage, stirring speed of solution, and average particle size of adsorbent on the adsorption of methylene blue were studied. It was found that the percentage of the adsorbed dye increased with increasing the amount of pyrolusite. While the initial dye concentration, initial pH, contact time, stirring speed, particle size, and adsorbent dosage were 25 ppm, 6, 90 min, 250 rpm, 63 µm, and 12 g/l, respectively, the efficiency of dye adsorption on pyrolusite ore was 99%. The isotherm and kinetic studies relating to this adsorption process were also made. It was found that the equilibrium data followed the Langmuir isotherm model while the kinetic of process could be described by the pseudo-second order kinetic model