Functional brain connectivity analysis based on the solution of the inverse problem and on covariance analysis.

The Linearly Constrained Minimum Variance (LCMV) beamformer is one of the most accepted techniques used to estimate the solution of the inverse problem in functional brain dynamics studies, using magnetoencephalograms (MEG). However, since it is based on the assumption of uncorrelated brain sources, its performance decreases in the presence of correlated brain activity, compromising the accuracy of estimates of brain interactions. This problem has not stopped the use of the beamformer in techniques such as Dynamic Imaging of Coherent Sources (DICS), which estimates the functional brain dynamics in a more direct way than the LCMV, and with less computational cost. In this work it is proposed to use a modified version of the well known Minimum Norm Estimates (MNE) spatial filter to estimate the functional brain dynamics of highly correlated activity. This is achieved by using the filter to estimate the cross-spectral density matrices for the brain activity in the same way that DICS does with the LCMV beamformer. The MNE spatial filter is used as a basis because it is not affected by the presence of correlated brain activity. The results obtained from simulations shown that it is possible to estimate highly correlated brain interactions using the proposed method. However, additional methods and constraints need to be applied because of the distorted and weighted output characteristic of the MNE spatial filter. Methods such as the FOcal Undetermined System Solution (FOCUSS) and Singular Value Decomposition Truncation (SVDT) are used to reduce the distorted output, while the estimation of brain dynamics is limited to cortical surface interactions to avoid weighted solutions

Confined photon modes with triangular symmetry in hexagonal microcavities in 2D photonic Crystals

We present theoretical and experimental studies of the size and thickness dependencies of the optical emission spectra from microcavities with hexagonal shape in films of two-dimensional photonic crystal. A semiclassical plane-wave model, which takes into account the electrodynamic properties of quasi-2D planar photonic microcavity, is developed to predict the eigenfrequencies of the confined photon modes as a function of both the hexagon-cavity size and the film thickness. Modes with two different symmetries, triangular and hexagonal, are critically analyzed. It is shown that the model of confined photon modes with triangular symmetry gives a better agreement between the predicted eigenmodes and the observed resonances.Comment: 14 pages, 6 figure

Information Technology and Competitive Advantage: The Role of the Ownership Structure

This paper analyses the relationship between information technology use (IT) and competitive advantage. Previous empirical research shows that IT improves competitive advantage when it acts together with some human or managerial resources of an intangible nature. In this work we propose a new complementary resource to IT: democratic ownership structure. We empirically analyse whether ownership structure and IT have a positive, combined impact on competitive advantage. Results show that ownership structure is a key element in explaining competitive advantage differences. Nonetheless, we did not find any IT-ownership structure complementary effect

Predictive Models for Forecasting Public Health Scenarios: Practical Experiences Applied during the First Wave of the COVID-19 Pandemic

Background: Forecasting the behavior of epidemic outbreaks is vital in public health. This makes it possible to anticipate the planning and organization of the health system, as well as possible restrictive or preventive measures. During the COVID-19 pandemic, this need for prediction has been crucial. This paper attempts to characterize the alternative models that were applied in the first wave of this pandemic context, trying to shed light that could help to understand them for future practical applications. Methods: A systematic literature search was performed in standardized bibliographic repertoires, using keywords and Boolean operators to refine the findings, and selecting articles according to the main PRISMA 2020 statement recommendations. Results: After identifying models used throughout the first wave of this pandemic (between March and June 2020), we begin by examining standard data-driven epidemiological models, including studies applying models such as SIR (Susceptible-Infected-Recovered), SQUIDER, SEIR, time-dependent SIR, and other alternatives. For data-driven methods, we identify experiences using autoregressive integrated moving average (ARIMA), evolutionary genetic programming machine learning, short-term memory (LSTM), and global epidemic and mobility models. Conclusions: The COVID-19 pandemic has led to intensive and evolving use of alternative infectious disease prediction models. At this point it is not easy to decide which prediction method is the best in a generic way. Moreover, although models such as the LSTM emerge as remarkably versatile and useful, the practical applicability of the alternatives depends on the specific context of the underlying variable and on the information of the target to be prioritized. In addition, the robustness of the assessment is conditioned by heterogeneity in the quality of information sources and differences in the characteristics of disease control interventions. Further comprehensive comparison of the performance of models in comparable situations, assessing their predictive validity, is needed. This will help determine the most reliable and practical methods for application in future outbreaks and eventual pandemics

Cubierta vegetal con plantas Aptenia cordifolia y Plectranthus verticillatus para reducir el ruido en viviendas urbanas

En la presente investigación se planteó como objetivo determinar la eficiencia de la cubierta vegetal con plantas Aptenia cordifolia y Plectranthus verticillatus para reducir el ruido, de esta manera proponer una solución ecológica y sostenible para contrarrestar la contaminación sonora. La investigación fue de tipo aplicada, de enfoque cuantitativo y de diseño cuasi experimental, para llevar a cabo la experimentación se realizó un monitoreo de ruido dentro de un prototipo de vivienda y se construyó e instaló un jardín vertical con plantas Aptenia cordifolia y Plectranthus verticillatus en la pared de la vivienda, posteriormente se realizaron mediciones durante el crecimiento de las plantas en 6 semanas, además se estudió el crecimiento y el área foliar para evaluar su influencia en el ruido. Los resultados evidenciaron que en la semana 1 la cobertura vegetal redujo 13.32 dB, siendo la semana 6 donde hubo una reducción significativa con una reducción de ruido de 22.dB. Se concluyó que la altura y el área foliar de las plantas tienen un efecto en la atenuación del ruido

The Influence of Infection and Colonization on Outcomes in Inpatients With COVID-19 : Are We Forgetting Something?

The COVID-19 epidemic has been a great challenge to health systems and especially hospitals. A prospective observational epidemiological study was planned as of February 26, 2020 in a tertiary hospital in the Valencia region. The total number of patients followed up with complete information during the first year was 2,448. Among other variables, the comorbidities of the patients were collected (and grouped in the Charson index), the stay in the intensive care unit (ICU), the co-infections, and the colonizations. Data on nosocomial infections due to said virus were also collected. The median days from the onset of symptoms to diagnosis were 4 + 4.6, while an additional 4.4 days had to pass for the patients to be admitted to the ICU. The factors associated with a higher risk of death were those with coinfection, especially with Candida auris [odds ratio (OR): 4.6], a situation that also occurred in the ICU (OR: 3.18). Charlson Index comorbidity and C. auris colonization were also very important both in general hospitalization and in the ICU

RSVP-TE Extensions to Provide Guarantee of Service to MPLS 1

Abstract. Independent Quality of Service (QoS) models need to be set up in IP and ATM integration and they are difficult to coordinate. This gap is bridged when MultiProtocol Label Switching (MPLS) is used for this purpose. We propose Guarantee of Service (GoS) to improve performance of privileged flows in congested MPLS networks. We first discuss the GoS requirements for the use in conjunction with MPLS. Then we propose a minimum set of extensions to RSVP-TE that allow signaling of GoS information across the MPLS domain

Impact of moderate coronary atherosclerosis on long-term left ventricular remodeling after aortic valve replacement

Background: The role of coronary atherosclerosis (CA+) in ventricular remodeling after aortic valve replacement (AVR) for isolated aortic stenosis (AS) is not well defined. We sought to evaluate the impact of not revascularized moderate coronary atherosclerosis in long-term left ventricular (LV) remodeling after AVR. Methods: We assessed by coronariography the coronary artery disease in 66 patients referred for AVR and evaluated morphological and functional LV data by echocardiography both preoperatively and postoperatively (3 ± 1.2 years). Results: In patients without coronary atherosclerosis, hypertrophy regression was more intense and the absolute reverse remodeling was higher in LV mass index (–55.8 ± 36 g/m2 vs –28.4 ± 34 g/m2, p = 0.004), reduction of LV dimensions (LV end-diastolic diameter [LVEDD]: –4.1 ± 7.4 mm vs –2.2 ± 8.3 mm, p = 0.04), and regression of wall thickness (interventricular septum [IVS]: –3.3 ± 2.6 mm vs –1.6 ± 2.2 mm, p = 0.01; and posterior wall thickness [PWT]: –2.1 ± 2.1 mm vs 0.6 ± 2.1 mm, p = 0.012). Conclusions: After AVR for AS, not revascularized moderate coronary atherosclerosis determines a long-term lesser degree of LV hypertrophy regression and a worse absolute reverse remodeling of LV mass index, LVEDD, IVS and PWT. (Cardiol J 2011; 18, 3: 277–281

Versatile Graphene-Based Platform for Robust Nanobiohybrid Interfaces

Technologically useful and robust graphene-based interfaces for devices require the introduction of highly selective, stable, and covalently bonded functionalities on the graphene surface, whilst essentially retaining the electronic properties of the pristine layer. This work demonstrates that highly controlled, ultrahigh vacuum covalent chemical functionalization of graphene sheets with a thiol-terminated molecule provides a robust and tunable platform for the development of hybrid nanostructures in different environments. We employ this facile strategy to covalently couple two representative systems of broad interest: metal nanoparticles, via S-metal bonds, and thiol-modified DNA aptamers, via disulfide bridges. Both systems, which have been characterized by a multi-technique approach, remain firmly anchored to the graphene surface even after several washing cycles. Atomic force microscopy images demonstrate that the conjugated aptamer retains the functionality required to recognize a target protein. This methodology opens a new route to the integration of high-quality graphene layers into diverse technological platforms, including plasmonics, optoelectronics, or biosensing. With respect to the latter, the viability of a thiol-functionalized chemical vapor deposition graphene-based solution-gated field-effect transistor array was assessed

Design of an exoskeleton for upper limb robot-assisted rehabilitation based on co-simulation

This paper presents the design and the simulation of an exoskeleton based on the kinematics of the human arm intended to be used in robot-assisted rehabilitation of the upper limb. The design meets the kinematic characteristics of the human arm so that the exoskeleton allows the movement of the arm in its full range of motion. We used co-simulation to design the exoskeleton considering a model of the upper limb developed in Opensim, Solidworks to design the mechanical structure and Matlab to construct the dynamic model. The system in motion was simulated in Simmechanics using predictive dynamics to compute independent joint trajectories obtained by modelling the exoskeleton as several optimization problems solved with SNOPT from Tomlab. The use of virtual tools in the designing process and the modular structure of the exoskeleton will allow the construction of personalized devices using 3D printing. The exoskeleton was designed to work under independent joint control so that the system will be able to work as passive, assistive and active-assistive mode, to keep records of motion for data analysis and to support the rehabilitation process