Stochastic analysis for wind speed forecasting

Abstract: The stability and availability required on the electrical power systems with wind sources are directly related to the accuracy of a short-term forecasting wind speed model. This paper presents a wind speed forecasting model based on one of the widely used time-series regression models, namely the Auto- Regressive Integrated Moving-Average (ARIMA). The method requires historical wind speed data for a given area, collected over a long time interval, in order to evaluate the required parameters of the wind speed ARIMA model

Trade under Global Value Chains in Africa (Lessons from Asia)

A global value chain refers to a globalized manufacturing process in which the tasks for manufacturing the final product are differentiated and performed in different countries. Due to the high transport and coordination costs, globalized production in Africa is very rare. Most of the goods were made in the country or simply in a workshop. Tackling trade in global value chains is on the high-level political agenda of African countries. Despite trading among global value chains, there is a heated debate as to why some African countries are making progress in global markets and others are not. Some authors have noted that Asia has played an important role and performed well within global value chains. The purpose of this article is to understand the importance African countries place on the global value chain and also to explain why trade has succeeded in African global value chains and why some African countries are unable to interact with global value chains. Despite Asian lessons. The data used in this study was collected through 100 questionnaires and six semi-structured and open interviews with managers of African exporting organizations. For quantitative research, a systematic random sampling method was used to select respondents, while respondents were used for qualitative research. SPSS version 21.0 was adopted for the analysis of quantitative data, while the method for reducing qualitative data. The results show that there is no clear understanding and usual meaning for global value chains. Some African countries are now ranked in Africa in terms of foreign direct investment by the United Nations Conference on Trade and Development (UNCTAD) according to the World Investment Report (2018). Keywords: Global Value Chains, Africa, Asia, Trade, manufacturing. DOI: 10.7176/JESD/12-4-03 Publication date: February 28th 202

A statistical analysis of Cape Town wind profile

Abstract The increased integration of wind power into electric power systems presents new challenges for effective planning and operation of these systems. The Weibull distribution is a widely used distribution, especially for modelling the random variable of wind speed. In this respect, the authors present a comparative analysis of a number of methods used for estimating Weibull parameters. Results for a real-world database are presented in a case study format. The techniques require historical wind speed data, collected over a particular time interval, to establish the parameters of wind speed distribution for a specific location, namely Cape Town, South Africa

Factors affecting highly active anti-retroviral therapy adherence in a rural area in Botswana

The purpose of this study was to determine factors affecting non-adherence to Anti-retroviral therapy among AIDS patients. A cross sectional quantitative survey, was used. Structured interviews were conducted with 300 ART patients. Data were analysed using SPSS version 13 and presented in charts, graphs and frequency tables. Motivators of good adherence were identified as disclosure of HIV positive status to more than one person, frequent adherence counselling, self-efficacy to adhere to ART, positive interactions between patients and healthcare providers; and using an adherence partner. Barriers to adherence were forgetfulness, transportation costs to and from the clinic, time away from work and side effects. There was a strong positive correlation between adherence, CD4 counts and viral load. Adherence was closely tied to immunologic and virologic improvements. Respondents with poor adherence were likely to have unsuppressed viral loads (OR 12.98, 95%, CI 4.9-34).Health StudiesMasters of Public Healt

Negative effects of energy-saving, non-linear loads on LV systems : causes and recommendations

Abstract: Pressure is being exerted on utilities and electrical energy customers to reduce energy consumption. There are two concerns: the effect that increasing greenhouse gasses have on global warming and the dwindling non-renewable resources currently used for the production of electrical power. The use of modern energy-efficient appliances such as Compact Fluorescent Lamps and micro-wave ovens is a widely promoted solution. These types of devices are recommended not only in affluent areas but also in developing countries (such as South Africa) where the use of computers and television sets are also being encouraged as devices for increasing the level of information and education. However, the use of these devices can introduce significant problems. This paper reviews a range of published material on the various aspects of this topic. It also includes the results from experimental measurements. Finally, the paper discusses some recommendations that are intended to bridge the gap between theoretical analyses and the practical implementation of mitigating steps, as they apply to low voltage distribution systems

Transcranial color-coded sonography in the management of patients with cervical and intracranial arterial stenosis

peer reviewedLe progrès technique en imagerie a permis le développement de l’écho-Doppler transcrânien en mode duplex ou triplex. A côté des autres techniques de neuro-imagerie, son intérêt dans la pathologie vasculaire cérébrale va grandissant. Le présent article a pour but de présenter cette technique en détaillant ses indications actuelles chez les patients présentant des sténoses artérielles cervicales et intra-crâniennes

Dynamic functional network connectivity using distance correlation

Investigations about the intrinsic brain organization in resting-state are critical for the understanding of healthy, pathological and pharmacological cerebral states. Recent studies on fMRI suggest that resting state activity is organized on large scale networks of coordinated activity, in the so called, Resting State Networks (RSNs). The assessment of the interactions among these functional networks plays an important role for the understanding of different brain pathologies. Current methods to quantify these interactions commonly assume that the underlying coordination mechanisms are stationary and linear through the whole recording of the resting state phenomena. Nevertheless, recent evidence suggests that rather than stationary, these mechanisms may exhibit a rich set of time-varying repertoires. In addition, these approaches do not consider possible non-linear relationships maybe linked to feed-back communication mechanisms between RSNs. In this work, we introduce a novel approach for dynamical functional network connectivity for functional magnetic resonance imaging (fMRI) resting activity, which accounts for non-linear dynamic relationships between RSNs. The proposed method is based on a windowed distance correlations computed on resting state time-courses extracted at single subject level. We showed that this strategy is complementary to the current approaches for dynamic functional connectivity and will help to enhance the discrimination capacity of patients with disorder of consciousness

Functional imaging and radiotherapy

peer reviewedLes progrès technologiques réalisés par l’image- rie médicale l’ont placée au centre de la prise en charge des patients oncologiques, tant au niveau du diagnostic, du pro - nostic et du suivi que dans la prise en charge thérapeutique. En effet, l’imagerie représente, à l’heure actuelle, la pierre angulaire des traitements de radiothérapie. Les objectifs du radiothérapeute sont d’irradier le plus précisément possible la tumeur à dose curative, tout en évitant les organes sains. Pour y arriver, le radiothérapeute utilise de façon routinière l’imagerie anatomique (Scanner et IRM). Depuis quelques années, le développement des différentes imageries métabo - liques et fonctionnelles, comme l’imagerie par émission de positons (PET-CT) et la résonnance magnétique fonctionnelle, ouvrent de nouvelles possibilités thérapeutiques grâce aux informations qu’elles apportent sur la biologie des tumeurs. Cet article décrit, de manière non exhaustive, les différentes imageries anatomiques et métaboliques à la disposition du radiothérapeute

Neuroimaging after coma.

Following coma, some patients will recover wakefulness without signs of consciousness (only showing reflex movements, i.e., the vegetative state) or may show non-reflex movements but remain without functional communication (i.e., the minimally conscious state). Currently, there remains a high rate of misdiagnosis of the vegetative state (Schnakers et. al. BMC Neurol, 9:35, 8) and the clinical and electrophysiological markers of outcome from the vegetative and minimally conscious states remain unsatisfactory. This should incite clinicians to use multimodal assessment to detect objective signs of consciousness and validate para-clinical prognostic markers in these challenging patients. This review will focus on advanced magnetic resonance imaging (MRI) techniques such as magnetic resonance spectroscopy, diffusion tensor imaging, and functional MRI (fMRI studies in both "activation" and "resting state" conditions) that were recently introduced in the assessment of patients with chronic disorders of consciousness

Multivariate functional network connectivity for disorders of consciousness

Recent evidence suggests that healthy brain is organized on large-scale spatially distant brain regions, which are temporally synchronized. These regions are known as resting state networks (RSNs). The level of interaction among these functional entities has been studied in the so called functional network connectivity (FNC). FNC aims to quantify the level of interaction between pairs of RSNs, which commonly emerge at similar spatial scale. Nevertheless, the human brain is a complex functional structure which is partitioned into functional regions that emerge at multiple spatial scales. In this work, we propose a novel multivariate FNC strategy to study interactions among communities of RSNs, these communities may emerge at different spatial scales. For this, first a community or hyperedge detection strategy was used to conform groups of RSNs with a similar behavior. Following, a distance correlation measurement was employed to quantify the level of interaction between these communities. The proposed strategy was evaluated in the characterization of patients with disorders of consciousness, a highly challenging problem in the clinical setting. The results suggest that the proposed strategy may improve the capacity of characterization of these brain altered conditions