Tailoring of AlAs/InAs/GaAs QDs Nanostructures via Capping Growth Rate.

The use of thin AlA capping layers (CLs) on InAs quantum dots (QDs) has recently received considerable attention due to improved photovoltaic performance in QD solar cells. However, there is little data on the structural changes that occur during capping and their relation to different growth conditions. In this work, we studied the effect of AlA capping growth rate (CGR) on the structural features of InAs QDs in terms of shape, size, density, and average content. As will be shown, there are notable differences in the characteristics of the QDs upon changing CGR. The Al distribution analysis in the CL around the QDs was revealed to be the key. On the one hand, for the lowest CGR, Al has a homogeneous distribution over the entire surface, but there is a large thickening of the CL on the sides of the QD. As a result, the QDs are lower, lenticular in shape, but richer in In. On the other hand, for the higher CGRs, Al accumulates preferentially around the QD but with a more uniform thickness, resulting in taller QDs, which progressively adopt a truncated pyramidal shape. Surprisingly, intermediate CGRs do not improve either of these behaviors, resulting in less enriched QDs.

CDrift: An Algorithm to Correct Linear Drift From A Single High-Resolution STEM Image.

In this work, a new method to determine and correct the linear drift for any crystalline orientation in a single-column-resolved high-resolution scanning transmission electron microscopy (HR-STEM) image, which is based on angle measurements in the Fourier space, is presented. This proposal supposes a generalization and the improvement of a previous work that needs the presence of two symmetrical planes in the crystalline orientation to be applicable. Now, a mathematical derivation of the drift effect on two families of asymmetric planes in the reciprocal space is inferred. However, though it was not possible to find an analytical solution for all conditions, a simple formula was derived to calculate the drift effect that is exact for three specific rotation angles. Taking this into account, an iterative algorithm based on successive rotation/drift correction steps is devised to remove drift distortions in HR-STEM images. The procedure has been evaluated using a simulated micrograph of a monoclinic material in an orientation where all the reciprocal lattice vectors are different. The algorithm only needs four iterations to resolve a 15° drift angle in the image.

Real-Time Hand Gesture Recognition Using Surface Electromyography and Machine Learning: A Systematic Literature Review.

Today, daily life is composed of many computing systems, therefore interacting with them in a natural way makes the communication process more comfortable. Human-Computer Interaction (HCI) has been developed to overcome the communication barriers between humans and computers. One form of HCI is Hand Gesture Recognition (HGR), which predicts the class and the instant of execution of a given movement of the hand. One possible input for these models is surface electromyography (EMG), which records the electrical activity of skeletal muscles. EMG signals contain information about the intention of movement generated by the human brain. This systematic literature review analyses the state-of-the-art of real-time hand gesture recognition models using EMG data and machine learning. We selected and assessed 65 primary studies following the Kitchenham methodology. Based on a common structure of machine learning-based systems, we analyzed the structure of the proposed models and standardized concepts in regard to the types of models, data acquisition, segmentation, preprocessing, feature extraction, classification, postprocessing, real-time processing, types of gestures, and evaluation metrics. Finally, we also identified trends and gaps that could open new directions of work for future research in the area of gesture recognition using EMG.

Desempeño de los sistemas de puntuación PSI y CURB-65 para predecir la mortalidad a 30 días de la neumonía asociada a la asistencia sanitaria / Performance of the PSI and CURB-65 scoring systems in predicting 30-day mortality in healthcare-associated pneumonia

Introducción: La health care-associated pneumonia (HCAP, «neumonía asociada a la asistencia sanitaria») es la principal causa de infección hospitalaria y está asociada a una alta tasa de mortalidad. Este estudio tuvo como objetivo evaluar el desempeño de los sistemas Pneumonia Severity Index (PSI, «índice de gravedad de la neumonía») y Confusion, Urea, Respiratory rate, Blood pressure, 65 years of age and older (CURB-65, «confusión, urea, frecuencia respiratoria, presión arterial, edad≥65) en la predicción de la mortalidad a 30 días en pacientes adultos de HCAP. Pacientes y métodos: Se realizó un estudio de tipo transversal y se analizaron los datos de 109 individuos no inmunocomprometidos>18 años. El diagnóstico clínico de HCAP incluyó la presencia de infiltrados radiográficos en pacientes≥48h tras el ingreso hospitalario. Se calcularon las puntuaciones PSI y CURB-65 y se estimaron las medidas de rendimiento. Se utilizaron estadísticas resumidas para describir la muestra del estudio. Las calificaciones PSI y CURB-65 se calcularon sobre la base de 20 y 5 criterios, respectivamente, y se estimaron los indicadores de desempeño de las herramientas de cribado. Resultados: La mortalidad general a los 30 días fue del 59,6%. En cada umbral determinado, la sensibilidad del PSI fue mayor, pero mostró una especificidad más baja que el CURB-65, observándose el índice más alto de Youden (0,392) en el punto de corte V de PSI. El área bajo la curva ROC fue 0,737 (IC del 95%: 0,646-0,827) y 0,698 (IC del 95%: 0,6-0,797) utilizando los sistemas PSI y CURB-65, respectivamente (p=0,323). Conclusión: Nuestros resultados indican que el desempeño de PSI y CURB-65 es razonablemente bueno para predecir la mortalidad a 30 días en pacientes adultos de HCAP, pudiendo recomendarse o utilizarse en los centros de salud (AU)

Introduction: Healthcare-associated pneumonia (HCAP) is the leading cause of infection in a hospital setting and is associated with a high mortality rate. This study aimed to evaluate the performance of the pneumonia severity index (PSI) and confusion, urea, respiratory rate, blood pressure, age≥65 (CURB-65) systems in predicting 30-day mortality in HCAP in adult patients. Patients and methods: A cross-sectional study took place and data from 109 non-immunocompromised individuals aged>18 years were analyzed. The clinical diagnosis of HCAP included the presence of radiographic infiltrates in patients≥48hours after hospital admission. The PSI and CURB-65 scores were calculated and performance measures were estimated. Summary statistics were used to describe the study sample. The PSI and CURB-65 scores were calculated based on 20 and 5 criteria, respectively, and the performance indicators of the screening tools were estimated. Results: The overall 30-day mortality was 59.6%. At every given threshold, PSI sensitivity was higher, but showed a lower specificity than the CURB-65, and the highest Youden index (0.392) was observed at cut-off V in the PSI. The area under the ROC curve was 0.737 (95% CI: 0.646-0.827) and 0.698 (95% CI: 0.600-0.797) using the PSI and CURB-65 systems, respectively (P=.323). Conclusion: Our findings suggest that the performance of the PSI and CURB-65 is reasonable for predicting 30-day mortality in adult HCAP patients and may be used in healthcare settings (AU)

Performance of the PSI and CURB-65 scoring systems in predicting 30-day mortality in healthcare-associated pneumonia. / Desempeño de los sistemas de puntuación PSI y CURB-65 para predecir la mortalidad a 30 días de la neumonía asociada a la asistencia sanitaria.

INTRODUCTION: Healthcare-associated pneumonia (HCAP) is the leading cause of infection in a hospital setting and is associated with a high mortality rate. This study aimed to evaluate the performance of the pneumonia severity index (PSI) and confusion, urea, respiratory rate, blood pressure, age≥65 (CURB-65) systems in predicting 30-day mortality in HCAP in adult patients. PATIENTS AND METHODS: A cross-sectional study took place and data from 109 non-immunocompromised individuals aged>18 years were analyzed. The clinical diagnosis of HCAP included the presence of radiographic infiltrates in patients≥48hours after hospital admission. The PSI and CURB-65 scores were calculated and performance measures were estimated. Summary statistics were used to describe the study sample. The PSI and CURB-65 scores were calculated based on 20 and 5 criteria, respectively, and the performance indicators of the screening tools were estimated. RESULTS: The overall 30-day mortality was 59.6%. At every given threshold, PSI sensitivity was higher, but showed a lower specificity than the CURB-65, and the highest Youden index (0.392) was observed at cut-off V in the PSI. The area under the ROC curve was 0.737 (95% CI: 0.646-0.827) and 0.698 (95% CI: 0.600-0.797) using the PSI and CURB-65 systems, respectively (P=.323). CONCLUSION: Our findings suggest that the performance of the PSI and CURB-65 is reasonable for predicting 30-day mortality in adult HCAP patients and may be used in healthcare settings.

Error quantification in strain mapping methods.

In this article a method for determining errors of the strain values when applying strain mapping techniques has been devised. This methodology starts with the generation of a thickness/defocus series of simulated high-resolution transmission electron microscopy images of InAsxP1-x/InP heterostructures and the application of geometric phase. To obtain optimal defocusing conditions, a comparison of different defocus values is carried out by the calculation of the strain profile standard deviations among different specimen thicknesses. Finally, based on the analogy of real state strain to a step response, a characterization of strain mapping error near an interface is proposed.

The Peak Pairs algorithm for strain mapping from HRTEM images.

Strain mapping is defined as a numerical image-processing technique that measures the local shifts of image details around a crystal defect with respect to the ideal, defect-free, positions in the bulk. Algorithms to map elastic strains from high-resolution transmission electron microscopy (HRTEM) images may be classified into two categories: those based on the detection of peaks of intensity in real space and the Geometric Phase approach, calculated in Fourier space. In this paper, we discuss both categories and propose an alternative real space algorithm (Peak Pairs) based on the detection of pairs of intensity maxima in an affine transformed space dependent on the reference area. In spite of the fact that it is a real space approach, the Peak Pairs algorithm exhibits good behaviour at heavily distorted defect cores, e.g. interfaces and dislocations. Quantitative results are reported from experiments to determine local strain in different types of semiconductor heterostructures.