Realities of a just future for the Mayan community in the Guatemalan State : the implications of historically discriminatory rule of law and the possiblity for a pluri-ethnic nation through transitional justice and customary law reformation

Abstract not availabl

Functional Singular Spectrum Analysis and the Clustering of Time-Dependent Data

The present work extends the application of the recently submitted functional singular spectrum analysis (FSSA) into the realm of structure level subsequence clustering. We begin with a comprehensive review of principal component analysis (PCA), functional principal component analysis (FPCA), singular spectrum analysis (SSA), and the recently submitted FSSA. We computationally show that the novel FSSA-FPCA hybrid clustering technique can be employed as an effective structure-based subsequence clustering method for call-center functional time series data where the method behaves as a dimension reduction technique for time-dependent data. Metrics, such as the F-ratio from k-means clustering, the w-correlation between reconstructed functional time series, and the Rand index are offered to determine the quality of clustering results of labeled functional data. We find that these outcomes are dependent on the grouping stage of FSSA for the call-center data. We also find that our measurements are not significantly sensitive to changes in groupings. Our investigations show that FSSA behaves as a type of temporal to frequency domain transformation similar to that of a Fourier analysis. The results shown in the present essay can be used to extend FSSA in its maturation and offer insight into how the hybrid method should be used and the challenges one faces with it

Functional Singular Spectrum Analysis: Nonparametric Decomposition and Forecasting Approaches for Functional Time Series

In this dissertation, we develop nonparametric decomposition methods and the subsequent forecasting techniques for functional, time-dependent data known as functional time series (FTS). We use ideas from functional data analysis (FDA) and singular spectrum analysis (SSA) to introduce the nonparametric decomposition method known as functional SSA (FSSA) and its associated forecasting techniques. We also extend these developed methodologies into multivariate FSSA (MFSSA) over different dimensional domains and its subsequent forecasting routines so that we may perform nonparametric decomposition and prediction of multivariate FTS (MFTS). The FSSA algorithm may be viewed as a signal extraction technique and we find that the method outperforms other competing approaches in estimating the underlying deterministic nature of an FTS. We then develop the FSSA recurrent forecasting (FSSA R-forecasting) and FSSA vector forecasting (FSSA V-forecasting) algorithms to predict future observations and we find that these methods outperform the current gold standard for nonparametric forecasting of periodic FTS. Finally, we finish with the implementation of MFSSA and the respective forecasting algorithms (MFSSA R-forecasting and MFSSA V-forecasting), which are used to decompose and forecast MFTS. We find that the MFSSA methods outperform their univariate FSSA counterparts in signal extraction and forecasting of MFTS data

Neurostimulation in the treatment of refractory and super-refractory status epilepticus

Abstract Status epilepticus (SE) is a life-threatening condition with a mortality of up to 60% in the advanced and comatose forms of SE. In one out of five adults, first and second line fails to control epileptic activity, leading to refractory status epilepticus (RSE) and in around 3% to super-refractory status epilepticus (SRSE), where SE continues despite anesthetic treatment for 24 h or more. In this rare but devastating condition, innovative and safe treatments are needed. In a recent review on the use of vagal nerve stimulation in RSE and SRSE, a 74% response rate for abrogation of SE was reported. Here, we review the currently available evidence supporting the use of neurostimulation, including vagal nerve stimulation, direct cortical stimulation, transcranial magnetic stimulation, electroconvulsive therapy, and deep brain stimulation in RSE and SRSE. This article is part of the Special Issue "Proceedings of the 7th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures"

Initial monotherapy with eslicarbazepine acetate for the management of adult patients with focal epilepsy in clinical practice: a meta-analysis of observational studies

This study was funded by Laboratorios Bial, S.A. (Madrid, Spain).The authors thank Alejandro Pedromingo (Bio-estadistica. com, Madrid, Spain) for the statistical analysis, and Isabel San Andrés (Incimed, Madrid, Spain) for performing the literature search. Their participation has been funded by Laboratorios Bial, S.A. (Madrid, Spain).Aim of the study To assess the effectiveness, overall tolerability of eslicarbazepine acetate (ESL) as an initial or early monotherapy treatment of adult patients with focal epilepsy under real-world practice conditions. Materials and methods We focused on real-world longitudinal studies that included or separately reported the results of at least one of the efficacy outcomes of interest. A DerSimonian-Laird random effects model was used with the presentation of the 95% confidence intervals of the estimate Results 5 studies met our selection criteria and were included in the quantitative synthesis. All studies were observational and uncontrolled studies, and all but one were retrospective studies. The pooled proportion of patients who were seizure-free for the entire study period was 64.6% (95% CI, 45.7 to 79.8) at month 6 and 56.6% (95% CI, 50.2 to 62.8) at month 12. Pooled retention rates were 95.0% (95% CI, 90.3 to 97.5) at 6 months and 83.6% (95% CI, 73.9 to 90.1) at 12 months. The pooled proportion of patients who reported at least one adverse event was 27.2% (95% CI, 21.7 to 33.6), and the pooled proportion of patients who discontinued ESL due to adverse events was 8.9% (95% CI 6.2 to 12.6). Conclusions Our results suggest that initial or early monotherapy with ESL is effective and well-tolerated for the management of adult patients with focal epilepsy in clinical practice, with results that are at least similar to those reported in the pivotal randomized clinical trial of ESL monotherapy. No new safety signals with ESL have been identified in this systematic review.Bial Grou

Antiepileptic drug use in Austrian nursing home residents

AbstractPurposeCurrently around 30% of all newly developed seizures are diagnosed in persons older than 65 years. Five to 17% of nursing home-residents take antiepileptic drugs. The aim of our study was to analyze the type and frequency of prescribed antiepileptic drugs, as well as their indication, co-morbidities and co-medications in institutionalized elderly in Austria.MethodsThis was a retrospective, cross-sectional study, which included all residents of the seven public nursing homes in Innsbruck, Austria. The data of 828 probands were extracted from the charts at site and maintained anonymously. The data collection was followed by descriptive statistics.Key findings70 (8.5%; 26 M/44 F) of the 828 (192 M/636 F) residents took at least one antiepileptic medication. In 51.5% the reason for the prescription were epileptic seizures – yielding a minimum prevalence of 4.5%. The most often used antiepileptic drugs were gabapentin (37%), levetiracetam (24%) and valproate (18.5%). The three most common co-morbidities were arterial hypertension (49%), ischemic stroke (36%) and other cerebrovascular diseases (29%). Six to nine co-medications were prescribed in 41%, 26% had more than 10 additional drugs and 91% were treated with proconvulsive co-medications (64/70, median 2, range 0–6).SignificanceAustrian nursing home residents receive more frequently newer antiepileptic drugs compared to other countries, but co-prescription of proconvulsive drugs is common

Determinant Attribute Analysis: A Tool for new Wood Product Development

Determinant attribute analysis was employed to identify the physical product characteristics most crucial in the purchase decision process for office furniture substrate materials. Fastener withdrawal strength, surface smoothness, flatness, stiffness (MOE), and edgebanding capability had the most effect on selection decisions. These results were then viewed in terms of the development of a new substrate product and the opportunities that could arise from achieving a superior competitive advantage based on those characteristics. The importance of recognizing customer needs in the new product development process is central to the analysis, and the potential of determinant attribute analysis as a powerful tool for this process is demonstrated