Cortical injury in multiple sclerosis; the role of the immune system

The easily identifiable, ubiquitous demyelination and neuronal damage that occurs within the cerebral white matter of patients with multiple sclerosis (MS) has been the subject of extensive study. Accordingly, MS has historically been described as a disease of the white matter. Recently, the cerebral cortex (gray matter) of patients with MS has been recognized as an additional and major site of disease pathogenesis. This acknowledgement of cortical tissue damage is due, in part, to more powerful MRI that allows detection of such injury and to focused neuropathology-based investigations. Cortical tissue damage has been associated with inflammation that is less pronounced to that which is associated with damage in the white matter. There is, however, emerging evidence that suggests cortical damage can be closely associated with robust inflammation not only in the parenchyma, but also in the neighboring meninges. This manuscript will highlight the current knowledge of inflammation associated with cortical tissue injury. Historical literature along with contemporary work that focuses on both the absence and presence of inflammation in the cerebral cortex and in the cerebral meninges will be reviewed

Forecasting: theory and practice

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases

Forecasting: theory and practice

Forecasting has always been in the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The lack of a free-lunch theorem implies the need for a diverse set of forecasting methods to tackle an array of applications. This unique article provides a non-systematic review of the theory and the practice of forecasting. We offer a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts, including operations, economics, finance, energy, environment, and social good. We do not claim that this review is an exhaustive list of methods and applications. The list was compiled based on the expertise and interests of the authors. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of the forecasting theory and practice

Forecasting: theory and practice

peer reviewedForecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases

A light software architecture for a Humanoid Soccer Robot

In this paper, we present a software architecture that can be implemented on a humanoid platform with low\u2013 computational power to make it to autonomous. The platform we used is the Robovie-V of V-Stone. the application we chose is the RoboCup soccer competitions. We will present the simple behaviour selection architecture implemented with a finite state machine (FSM) in our robot. We will present the highly optimized algorithms used for image processing and we will give some hints on how it is possibile to extend the flexibility of a low computational power humanoid with a customized operating system. These solutions are quite general and can be applied to any humanoid platform with low-computational power

Scale Reliability Evaluation for a-priori Clustered Data

According to the classical measurement theory [2], the reliability of the relationship between a latent variable describing a true measure and its corresponding manifest proxies can be assessed through the Cronbach\u2019s Alpha index. The Cronbach\u2019s Alpha index can be used for parallel measures and represents a lower bound for the reliability value in presence of congeneric measures, for which the assessment can properly be made only ex post, once the loading coefficients have been estimated [3], e.g. by means of a structural equation model with latent variables (SEM-LV). Let us assume the existence of an a-priori segmentation, based upon a categorical variable Z. We want to test the reliability of the construct over all the groups. This corresponds to the null joint hypothesis that the loadings are equal within each group as well as they do not vary among groups. Otherwise different measurement models need to be defined over groups. A test for measuring group differences in reliability is presented in [5], basing on differences of loading estimates in a SEM-LV framework. We consider a formulation of the Cronbach\u2019s Alpha coefficient according to the decomposition of pairwise covariances in a clustered framework

Split and strip-plot configurations of two-level fractional factorials: A review

Constrained randomization, Split-Plot, Strip-Plot, Strip-Block, dependent error components, robustness,