Re-inoculation of autoclaved soil as a non-sterile treatment for xenobiotic sorption and biodegradation studies

Autoclaved soil is commonly used for the study of xenobiotic sorption and as an abiotic control in biodegradation experiments. Autoclaving has been reported to alter soil physico-chemical and xenobiotic sorption characteristics such that comparison of autoclaved with non-autoclaved treatments in soil aging and bioavailability studies may yield misleading results. Experiments could be improved by using autoclaved soil re-inoculated with indigenous microorganisms as an additional or alternative non-sterile treatment for comparison with the sterile, autoclaved control. We examined the effect of autoclaving (3 x 1 h, 121°C, 103.5 KPa) on the physico-chemical properties of a silt loam soil (pH 7.2, 2.3% organic carbon) and the establishment of indigenous microorganisms reintroduced after autoclaving. Sterilisation by autoclaving significantly (p ≤ 0.05) decreased pH (0.6 of a unit) and increased concentrations of water-soluble organic carbon (WSOC; nontreated = 75 mg kg^-1; autoclaved = 1526 mg kg^-1). The initial first-order rate of ¹⁴C-2,4-dichloro-UL-phenol (2,4-DCP) adsorption to non-treated, autoclaved and re-inoculated soil was rapid (K₁ = 16.8-24.4 h^-1) followed by a slower linear phase (K₂). In comparison with autoclaved soil (0.038% day^-1), K₂ values were higher for re-inoculated (0.095% day^-1) and nontreated (0.181% day^-1) soil. This was attributed to a biological process. The Freundlich adsorption coefficient (K(f)) for autoclaved soil was significantly (p ≤ 0.05) higher than for re-inoculated or non-treated soil. Increased adsorption was attributed to autoclaving-induced changes to soil pH and solution composition. Glucose-induced respiration of autoclaved soil after re-inoculation was initially twice that in the non-treated control, but it decreased to control levels by day 4. This reduction corresponded to a depletion of WSOC. 2,4-DCP mineralisation experiments revealed that the inoculum of nonsterile soil (0.5 g) contained 2,4-DCP-degrading microorganisms capable of survival in autoclaved soil. The lag phase before detection of significant 2,4-DCP mineralisation was reduced (from 7 days to ≤3 days) by pre-incubation of re-inoculated soils for 7 and 14 days before 2,4-DCP addition. This was attributed to the preferential utilisation of WSOC prior to the onset of 2,4-DCP mineralisation. Cumulative ¹⁴CO₂ evolved after 21 days was significantly lower (p ≤ 0.05) from non-treated soil (25.3%) than re-inoculated soils (ca 45%). Experiments investigating sorption-biodegradation interactions of xenobiotics in soil require the physico-chemical properties of sterile and non-sterile treatments to be as comparable as possible. For fundamental studies, we suggest using re-inoculated autoclaved soil as an additional or alternative non-sterile treatment.

Non-parametric bill of quantities estimation of concrete road bridges' superstructure: an artificial neural networks approach

Bridge construction responds to the need for environmentally friendly design of motorways and facilitates the passage through sensitive natural areas and the bypassing of urban areas. However, according to numerous research studies, bridge construction presents substantial budget overruns. Therefore, it is necessary early in the planning process for the decision makers to have reliable estimates of the final cost based on previously constructed projects. At the same time, the current European financial crisis reduces the available capital for investments and financial institutions are even less willing to finance transportation infrastructure. Consequently, it is even more necessary today to estimate the budget of high-cost construction projects -such as road bridges- with reasonable accuracy, in order for the state funds to be invested with lower risk and the projects to be designed with the highest possible efficiency. In this paper, a Bill-of-Quantities (BoQ) estimation tool for road bridges is developed in order to support the decisions made at the preliminary planning and design stages of highways. Specifically, a Feed-Forward Artificial Neural Network (ANN) with a hidden layer of 10 neurons is trained to predict the superstructure material quantities (concrete, pre-stressed steel and reinforcing steel) using the width of the deck, the adjusted length of span or cantilever and the type of the bridge as input variables. The training dataset includes actual data from 68 recently constructed concrete motorway bridges in Greece. According to the relevant metrics, the developed model captures very well the complex interrelations in the dataset and demonstrates strong generalisation capability. Furthermore, it outperforms the linear regression models developed for the same dataset. Therefore, the proposed cost estimation model stands as a useful and reliable tool for the construction industry as it enables planners to reach informed decisions for technical and economic planning of concrete bridge projects from their early implementation stages.

Factores que influenciam o peso e crescimento de cabritos da raça Murciana-granadina, em aleitamento artificial

A exploração caprina de leite tem evoluído no sentido de alguma intensificação, com recurso a raças de elevado potencial produtivo, de que é exemplo a raça Murciana- Granadina. O leite constitui a principal fonte de receita destas explorações. Complementarmente, vendem animais para carne e, as de melhor nível genético, animais para reprodutores. Analisaram-se os pesos de 241 cabritos da raça Murciana-Granadina, numa exploração comercial, com o objectivo de quantificar os pesos e crescimento de cabritos, e identificar os factores que os influenciam. Os cabritos foram aleitados artificialmente, em regime ad libitum, com leite de substituição comercial, dispondo ainda de concentrado comercial, feno de luzerna e palha. Os cabritos foram pesados ao nascimento e, posteriormente, semanalmente, até aos 60 dias de idade. Calcularam-se os respetivos pesos ajustados, bem como os ganhos médios diários, a diferentes idades padrão. Procedeu-se a uma análise de variância com um modelo linear que incluiu os efeitos da época de parto, tipo de parto, sexo e idade da cabra. Foram registados pesos superiores nos partos simples e duplos, relativamente aos triplos, e nos machos, relativamente às fêmeas. Os ganhos médios diários, a partir do mês de idade, registaram valores inferiores na época inverno-primavera, comparativamente com a época primavera-verão. Dairy goat farming has evolved towards intensification, with increased use of high milk-yielding breeds, including the Murciano-Granadina breed. Milk is the main source of farm income. Secondary income sources are the sale of animals for meat and, in genetically superior herds, the sale of breeding animals. The weights of 241 commercial farms artificially reared Murciano-Granadina kids were analyzed with the objective of quantifying weight and growth and identifying variation factors. Kids were artificially reared to weaning, on ad libitum commercial milk replacer, commercial concentrate, lucerne hay and straw. Kids were weighed at birth and at weekly intervals until 60 days of age. Age adjusted weights and growth-rates were calculated. A variance analysis was performed with a model including the effects of season of birth, number of kids per kidding, sex and age of dam. Single and twin-born kids had higher weights than triplets, and males had higher weights than females. Average daily gain after one month of age was lower for kids born in winter-spring than for those born in spring-summer

Logic Programming and Artificial Neural Networks in Pharmacological Screening of Schinus Essential Oils

Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Soft-computing techniques applied to artificial tissue temperature estimation

Tese dout., Engenharia electrónica e computação - Processamento de sinal, Universidade do Algarve, 2008

Experimental study of the macrobenthic colonisation and secondary production in the artificial reefs of Algarve coast

Tese de dout., Ciências do Mar, Faculdade de Ciências do Mar e do Ambiente, Universidade do Algarve, 2010

Introdução à inteligência artificial com recurso à programação visual

Relatório da Prática de Ensino Supervisionada, Mestrado em Ensino da Matemática, Universidade de Lisboa, Instituto de Educação, 2014

Impacto da iluminação natural e artificial na disponibilidade de macro-invertebrados bentónicos para as aves limícolas

Tese de mestrado em Ecologia Marinha, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2015

An artificial neural network approach for short-term wind power forecasting in Portugal

This paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated against persistence and ARIMA approaches, reporting the numerical results from a real-world case study.

Dynamic artificial neural network for electricity market prices forecast

This paper presents an artificial neural network applied to the forecasting of electricity market prices, with the special feature of being dynamic. The dynamism is verified at two different levels. The first level is characterized as a re-training of the network in every iteration, so that the artificial neural network can able to consider the most recent data at all times, and constantly adapt itself to the most recent happenings. The second level considers the adaptation of the neural network’s execution time depending on the circumstances of its use. The execution time adaptation is performed through the automatic adjustment of the amount of data considered for training the network. This is an advantageous and indispensable feature for this neural network’s integration in ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to the market negotiating players of MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).

Scheduling distributed energy resources in an isolated grid - an artificial neural network approach

Power Systems (PS), have been affected by substantial penetration of Distributed Generation (DG) and the operation in competitive environments. The future PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. Virtual power players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. This paper proposes an artificial neural network (ANN) based methodology to support VPP resource schedule. The trained network is able to achieve good schedule results requiring modest computational means. A real data test case is presented.

Feasibility study on multifunctional artificial reefs for the Azores

Tese de Doutoramento, Geografia (Ordenamento do Território), 25 de Novembro de 2013, Universidade dos Açores.