Illinois weekend adventure guide.

"Compiled by the Illinois Department of Commerce and Community Affairs, Bureau of Tourism, based on the materials submitted by Illinois' Convention and Visitors Bureaus, Regional Tourism Development Offices, the Illinois Historic Preservation Agency and the Department of Natural Resources."--P. 136.

Information processing and the UK weekend effect:Do investors cut their losses on Mondays?

This paper complements earlier work by the author that shows that the pattern of information arrivals into the UK stock market may explain the behaviour of returns. It is argued that delays or other systematic behaviour in the processing of this information could compound the impact of information arrival patterns. It is found, however, that this does not happen, and so it is the arrival and not the processing of news that is most important. © 2004 Taylor & Francis Ltd.

A note on information seasonality and the disappearance of the weekend effect in the UK stock market

The weekend effect in UK stock prices has disappeared in the 1990s. Beneath the surface however there remain systematic day-of-the-week effects only visible when returns are partitioned by the direction of the market. A systematic pattern of market-wide news arrivals into the UK stock market is discovered and found to provide an explanation for these day-of-the-week effects.

Florida International University COM 1st Accreditation Planning Weekend, Feb 16-18 2007- Profile: Dr John A. Rock, M.D.

Profile on Dr. John A. Rock, founding dean of the Florida International University College of Medicine.

Florida International University COM 1st Accreditation Planning Weekend, Feb 16-18, 2007 - Untitled Presentation

Presentation on major themes for the four year MD curriculum.

Florida International University College of Medicine 1st Accreditation Planning Weekend, Feb 16-18 2007 – Basic Medical Sciences: Needed Subject Areas & Faculty Expertise

Chart outlining areas of need for subject areas and faculty expertise.

Florida International University College of Medicine 1st Accreditation Planning Weekend, Feb 16-18, 2007 - Agenda

Agenda for the FIU College of Medicine's First Accreditation Planning Weekend, February 16-17 2007.

Assessment Of Sleep Bruxism, Orthodontic Treatment Need, Orofacial Dysfunctions And Salivary Biomarkers In Asthmatic Children.

To evaluate the sleep bruxism, malocclusions, orofacial dysfunctions and salivary levels of cortisol and alpha-amylase in asthmatic children. 108 7-9-yr-old children were selected from Policlinic Santa Teresinha Doutor Antonio Haddad Dib (asthmatics, n=53) and from public schools (controls, n=55), Piracicaba, SP, Brazil. Sleep bruxism diagnosis was confirmed by parental report of grinding sounds and the presence of shiny and polish facets on incisors and/or first permanent molars. The index of orthodontic treatment need was used for occlusion evaluation. Orofacial dysfunctions were evaluated using the nordic orofacial test-screening (NOT-S). Salivary cortisol and alpha-amylase were expressed as awakening response (AR), calculated as the difference between levels immediately after awakening and 30min after waking, and diurnal decline (DD), calculated as the difference between levels at 30min after waking and at bedtime. Data were analyzed using Shapiro-Wilk/Kolmogorov-Smirnov, Chi-square, unpaired t test/Mann-Whitney and paired t/Wilcoxon tests. Sleep bruxism was more prevalent in children with asthma than controls (47.2% vs. 27.3%, p<0.05). Asthmatics had higher scores of NOT-S total and interview (p<0.05). Dysfunctions on sensory function and chewing and swallowing were more frequent in asthmatics (p<0.05). Salivary cortisol AR on weekend was significantly higher for asthmatics (p<0.05). Salivary cortisol DD was significantly higher on weekday than weekend for controls (p<0.05). There were no significant differences in alpha-amylase values in and between groups. The presence of asthma in children was associated with sleep bruxism, negative perception of sensory, chewing and swallowing functions, and higher concentrations of salivary cortisol on weekend.

Utilização da discriminação grafica de Fisher para indicação dos dermatoglifos como referencial de potencialidade de atletas de basquetebol

Universidade Estadual de Campinas. Faculdade de Educação Física

Explaining sleep duration in adolescents: the impact of socio-demographic and lifestyle factors and working status

Previous studies found students who both work and attend school undergo a partial sleep deprivation that accumulates across the week. The aim of the present study was to obtain information using a questionnaire on a number of variables (e.g., socio-demographics, lifestyle, work timing, and sleep-wake habits) considered to impact on sleep duration of working (n=51) and non-working (n=41) high-school students aged 14-21 yrs old attending evening classes (19:00-22:30 h) at a public school in the city of So Paulo, Brazil. Data were collected for working days and days off. Multiple linear regression analyses were performed to assess the factors associated with sleep duration on weekdays and weekends. Work, sex, age, smoking, consumption of alcohol and caffeine, and physical activity were considered control variables. Significant predictors of sleep duration were: work (p < 0.01), daily work duration (8-10 h/day; p < 0.01), sex (p=0.04), age 18-21 yrs (0.01), smoking (p=0.02) and drinking habits (p=0.03), irregular physical exercise (p < 0.01), ease of falling asleep (p=0.04), and the sleep-wake cycle variables of napping (p < 0.01), nocturnal awakenings (p < 0.01), and mid-sleep regularity (p < 0.01). The results confirm the hypotheses that young students who work and attend school showed a reduction in night-time sleep duration. Sleep deprivation across the week, particularly in students working 8-10 h/day, is manifested through a sleep rebound (i.e., extended sleep duration) on Saturdays. However, the different roles played by socio-demographic and lifestyle variables have proven to be factors that intervene with nocturnal sleep duration. ) The variables related to the sleep-wake cycle naps and night awakenings proved to be associated with a slight reduction in night-time sleep, while regularity in sleep and wake-up schedules was shown to be associated with more extended sleep duration, with a distinct expression along the week and the weekend. Having to attend school and work, coupled with other socio-demographic and lifestyle factors, creates an unfavorable scenario for satisfactory sleep duration

The daily and hourly energy consumption and load forecasting using artifitial neural network method: a case study using a set of 93 households in Portugal

It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.

Nunca mais é sexta-feira: o impacto do processo de recuperação de recursos durante o fim de semana no engagement

Orientação: Doutora Maria Alexandra Pacheco Ribeiro da Costa

Particle Swarm Optimization of Electricity Market Negotiating Players Portfolio

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which performs realistic simulations of the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from each market context. However, it is still necessary to adequately optimize the players’ portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering different market opportunities (bilateral negotiation, market sessions, and operation in different markets) and the negotiation context such as the peak and off-peak periods of the day, the type of day (business day, weekend, holiday, etc.) and most important, the renewable based distributed generation forecast. The proposed approach is tested and validated using real electricity markets data from the Iberian operator – MIBEL.

Electricity Markets Portfolio Optimization using a Particle Swarm Approach

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player’s portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and offpeak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator – OMIE.