Short-term water demand forecasting using machine learning techniques

Nowadays, a large number of water utilities still manage their operation on the instant water demand of the network, meaning that the use of the equipment is conditioned by the immediate water necessity. The water reservoirs of the networks are filled using pumps that start working when the water level reaches a specified minimum, stopping when it reaches a maximum level. Shifting the focus to water management based on future demand allows use of the equipment when energy is cheaper, taking advantage of the electricity tariff in action, thus bringing significant financial savings over time. Shortterm water demand forecasting is a crucial step to support decision making regarding the equipment operation management. For this purpose, forecasting methodologies are analyzed and implemented. Several machine learning methods, such as neural networks, random forests, support vector machines and k-nearest neighbors, are evaluated using real data from two Portuguese water utilities. Moreover, the influence of factors such as weather, seasonality, amount of data used in training and forecast window is also analysed. A weighted parallel strategy that gathers the advantages of the different machine learning techniques is suggested. The results are validated and compared with those achieved by autoregressive integrated moving average (ARIMA) also using benchmarks.publishe

Increased performance in the short-term water demand forecasting through the use of a parallel adaptive weighting strategy

Recent research on water demand short-term forecasting has shown that models using univariate time series based on historical data are useful and can be combined with other prediction methods to reduce errors. The behavior of water demands in drinking water distribution networks focuses on their repetitive nature and, under meteorological conditions and similar consumers, allows the development of a heuristic forecast model that, in turn, combined with other autoregressive models, can provide reliable forecasts. In this study, a parallel adaptive weighting strategy of water consumption forecast for the next 24–48 h, using univariate time series of potable water consumption, is proposed. Two Portuguese potable water distribution networks are used as case studies where the only input data are the consumption of water and the national calendar. For the development of the strategy, the Autoregressive Integrated Moving Average (ARIMA) method and a short-term forecast heuristic algorithm are used. Simulations with the model showed that, when using a parallel adaptive weighting strategy, the prediction error can be reduced by 15.96% and the average error by 9.20%. This reduction is important in the control and management of water supply systems. The proposed methodology can be extended to other forecast methods, especially when it comes to the availability of multiple forecast models.by UE/FEDER through the program COMPETE 2020 and UID/EMS/00481/2013-FCT under CENTRO-01-0145-FEDER- 022083publishe

Vaccination with Recombinant Microneme Proteins Confers Protection against Experimental Toxoplasmosis in Mice

Toxoplasmosis, a zoonotic disease caused by Toxoplasma gondii, is an important public health problem and veterinary concern. Although there is no vaccine for human toxoplasmosis, many attempts have been made to develop one. Promising vaccine candidates utilize proteins, or their genes, from microneme organelle of T. gondii that are involved in the initial stages of host cell invasion by the parasite. In the present study, we used different recombinant microneme proteins (TgMIC1, TgMIC4, or TgMIC6) or combinations of these proteins (TgMIC1-4 and TgMIC1-4-6) to evaluate the immune response and protection against experimental toxoplasmosis in C57BL/6 mice. Vaccination with recombinant TgMIC1, TgMIC4, or TgMIC6 alone conferred partial protection, as demonstrated by reduced brain cyst burden and mortality rates after challenge. Immunization with TgMIC1-4 or TgMIC1-4-6 vaccines provided the most effective protection, since 70% and 80% of mice, respectively, survived to the acute phase of infection. In addition, these vaccinated mice, in comparison to non-vaccinated ones, showed reduced parasite burden by 59% and 68%, respectively. The protective effect was related to the cellular and humoral immune responses induced by vaccination and included the release of Th1 cytokines IFN-γ and IL-12, antigen-stimulated spleen cell proliferation, and production of antigen-specific serum antibodies. Our results demonstrate that microneme proteins are potential vaccines against T. gondii, since their inoculation prevents or decreases the deleterious effects of the infection

Perfil nosológico de centro de referência em dermatologia no estado do Amazonas - Brasil Nosological profile in a dermatology referral center in the state of Amazonas -Brazil

FUNDAMENTOS: As doenças de pele estão associadas a alta morbidade, baixa mortalidade e baixa proporção de hospitalização. Entretanto, podem causar considerável interferência no bem-estar físico e emocional do indivíduo. Várias delas atingem grandes contingentes populacionais, havendo necessidade de intervenções específicas para seu controle. OBJETIVO: Descrever a frequência das dermatoses diagnosticadas em serviço de dermatologia na cidade de Manaus, capital do estado do Amazonas. MÉTODOS: Coletaram-se dados registrados sobre sexo, idade, procedência e diagnósticos referentes à primeira consulta dos pacientes atendidos entre janeiro de 2000 e dezembro de 2007. RESULTADOS: Das 56.024 consultas registradas, obtiveram-se 56.720 diagnósticos dermatológicos, sendo mais comuns as doenças sexualmente transmissíveis (25,12%), as dermatoses alérgicas (14,03%), as dermatoses não especificadas (13,01%), a hanseníase (6,34%) e acne, seborreia e afins (5,05%). A frequência foi semelhante para ambos os sexos, a faixa etária de 20-29 anos foi predominante e Manaus foi a procedência mais referida. CONCLUSÕES: O padrão das doenças cutâneas identificadas neste estudo pode servir como linha de base para que gestores do sistema de saúde da região desenvolvam estratégias de prevenção e controle das dermatoses mais comuns, com ênfase nas doenças sexualmente transmissíveis, doenças cutâneas alérgicas, hanseníase e acne<br>BACKGROUNDS: Fundaments: Skin diseases are associated wih high morbidity, low mortality and low rate of hospitalization. However, they can cause considerable interference in physical and emotional well-being of the individual. Several of them reach large population, requiring specific interventions for their control. OBJECTIVE: To describe the frequency of skin disease diagnosed in the dermatology service in Manaus, capital of Amazonas State. METHODS: We collected data on registered sex, age, origin and diagnostics for the first consultation of patients attended between January 2000 and December 2007. RESULTS: Of the 56.024 recorded visits, we obtained 56.720 cases of dermatological diagnoses, being the most common sexually transmitted diseases (25,12%), allergic skin disesases (14,03%), unspecified dermatoses (13,01%), leprosy (6,34%) and acne, seborrhea and related diseases (5,05%). The frequency was similar for both sexes, aged 20-29 years predominated and Manaus the origin most reported. CONCLUSIONS: The pattern of skin diseases identified in this study may serve as a baseline to managers of health system in the region develop strategies for prevention and control of dermatoses, with emphasis on sexually transmitted diseases, allergic skin diseases, leprosy and acn