El rol mediador de la virtuosidad en la gestión de recursos humanos y los resultados del trabajo

In this study, we explore the role of organizational virtuousness (OV) as a mechanism through which human resource management practices (HRMP) affect employee outcomes. We propose that HRMP lead to higher levels of organizational citizenship behaviors and affective commitment by stimulating OV. In a sample of 525 workers, from 22 stores of a retailing company, we found evidence that HRMP predicts OV, in turn predicting members’ citizenship behaviors and affective commitment. By suggesting this new mediator, this study contributes to a better understanding of the causal chain linking HRMP and performance.info:eu-repo/semantics/publishedVersio

HRM practices and organizations' internal context role in performance

Purpose - The main purpose of the present study is to test the association between Human Resource Management practices (HRMP) perceptions, internal context, and organizational performance. Design/methodology/approach - The data was collected based on a sample of 525 individuals from 22 stores, with performance indicators collected at the store level. Findings - The results showed (a) a positive relationship between perceived organizational integrity and organizational performance, as well as a negative relationship with staff turnover; (b) and a negative relationship between employment conditions and staff turnover. Research limitations/implications - The small sample size and the fact that the study was conducted in stores of the same organization doesn’t allow generalization of findings; results are based on data from cross-sectional design, longitudinal data would be needed to infer causal relationships. Practical implications - Managers should take in consideration that organizational integrity, as perceived by employees, can enhance organizational performance and reduce turnover, better employment conditions will also have this effect in turnover. Originality/value - These findings allow us to discuss the role of HRMP and of organizations internal context and characteristics on performance.info:eu-repo/semantics/publishedVersio

Smoking Cessation Interventions for COPD: A Review of the Literature

The aim of this systematic review is to establish the most effective stop smoking intervention approach for smokers with COPD. The search strategy included the electronic databases MEDLINE, EMBASE, AMED, PsycINFO, DARE, Cochrane Library, and CINAHL, between January 2006 and January 2010. References of the included studies were also screened for additional papers, and further hand searches were conducted. The selection criteria included randomized controlled trials or quasi-randomized controlled trials with at least one subject group diagnosed with COPD. Two independent reviewers reviewed the included studies, using a quality assessment form developed from the selection criteria. Divergence of quality assessment scores was resolved by the 2 reviewers agreeing on a score. The 4 studies selected indicate that psychosocial interventions combined with pharmacotherapy are effective in smoking cessation at 12 months post-intervention, although the effect is not statistically significant, due to small sample size and heterogeneity between the studies (odds ratio 2.35, 95% CI 0.25–21.74,). However, despite this medium effect size, due to a lack of universal use of pharmacotherapies in most of the studies, it makes a definitive comparison of efficacy difficult to determine. This review also shows the effectiveness of psychosocial treatment for people with or without COPD symptoms at 12 months, although the effect of disease severity is not clear. This review also highlights the difficulty of maintaining attendance at community-based locations, compared to acute or research settings

Sistemas de cultivo para rendimento elevado em trigo e o desafio das correlações indesejadas.

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Diagnostics and control of wavenumber stability and purity of tunable diode lasers relevant to their use as local oscillators in heterodyne systems

Initial operation of the tunable diode lasers (TDL) showed that it was not possible to adjust the wavenumber to one selected a priori in the TDL tuning range. During operation, the operating point would change by 0.1/cm over the longer term with even larger changes occurring during some thermal cycles. Most changes during thermal cycling required using lower temperatures and higher currents to reach the former wavenumber (when it could be reached). In many cases, an operating point could be selected by changing TDL current and temperature to give both the desired wavenumber and most of the power in a single mode. The selection procedure had to be used after each thermal cycling. Wavenumber nonlinearities of about 10% over a 0.5 cm tuning range were observed. Diagnostics of the single mode selected by a grating monochromator showed wavenumber fine structure under certain operating conditions. The characteristics due to the TDL environment included short term wavenumber stability, the instrument lineshape function, and intermediate term wavenumber stability

Fault detection and diagnosis technique for a SRM drive based on a multilevel converter using a machine learning approach

Trabalho apresentado em 12th International Conference on Renewable Energy Research and Applications (ICRERA 2023), 29 augusto-1 setembro 2023, Oshawa, CanadaSRM drives based on multilevel converters is now a solution well accepted due to their interesting features like extended voltage range and capability to fault tolerance. However, one aspect that is fundamental to ensure fault tolerance or preventive maintenance is the fault detection and diagnosis of failures in power semiconductors. In this way, in this paper it is presented a new diagnostic method for the failure of those semiconductors in asymmetric neutral point clamped converters. The proposed method will be based on the development of specific patterns that are associated to each semiconductor and fault type. The procedures presented here are based on the image identification of the currents patterns in the multilevel converter that allow the identification of distinct fault type. The pattern recognition system uses visual-based efficient invariants features for continuous monitoring of multilevel converter The proposed method will be verified through several tests in which were used a simulation tool and an experimental prototype.N/

Uma discussão sobre o conceito de hazards e o caso do furacão/ciclone Catarina.

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A PCA-based automated finder for galaxy-scale strong lenses

We present an algorithm using Principal Component Analysis (PCA) to subtract galaxies from imaging data, and also two algorithms to find strong, galaxy-scale gravitational lenses in the resulting residual image. The combined method is optimized to find full or partial Einstein rings. Starting from a pre-selection of potential massive galaxies, we first perform a PCA to build a set of basis vectors. The galaxy images are reconstructed using the PCA basis and subtracted from the data. We then filter the residual image with two different methods. The first uses a curvelet (curved wavelets) filter of the residual images to enhance any curved/ring feature. The resulting image is transformed in polar coordinates, centered on the lens galaxy center. In these coordinates, a ring is turned into a line, allowing us to detect very faint rings by taking advantage of the integrated signal-to-noise in the ring (a line in polar coordinates). The second way of analysing the PCA-subtracted images identifies structures in the residual images and assesses whether they are lensed images according to their orientation, multiplicity and elongation. We apply the two methods to a sample of simulated Einstein rings, as they would be observed with the ESA Euclid satellite in the VIS band. The polar coordinates transform allows us to reach a completeness of 90% and a purity of 86%, as soon as the signal-to-noise integrated in the ring is higher than 30, and almost independent of the size of the Einstein ring. Finally, we show with real data that our PCA-based galaxy subtraction scheme performs better than traditional subtraction based on model fitting to the data. Our algorithm can be developed and improved further using machine learning and dictionary learning methods, which would extend the capabilities of the method to more complex and diverse galaxy shapes