Responses of the alga Pseudokirchneriella subcapitata to long-term exposure to metal stress

The green alga Pseudokirchneriella subcapitata has been widely used in ecological risk assessment, usually based on the impact of the toxicants in the alga growth. However, the physiological causes that lead algal growth inhibition are not completely understood. This work aimed to evaluate the biochemical and structural modifications in P. subcapitata after exposure, for 72 h, to three nominal concentrations of Cd(II), Cr(VI), Cu(II) and Zn(II), corresponding approximately to 72 h-EC10 and 72 h-EC50 values and a high concentration (above 72 h-EC90 values). The incubation of algal cells with the highest concentration of Cd(II), Cr(VI) or Cu(II) resulted in a loss of membrane integrity of ~16, 38 and 55%, respectively. For all metals tested, an inhibition of esterase activity, in a dose-dependent manner, was observed. Reduction of chlorophyll a content, decrease of maximum quantum yield of photosystem II and modification of mitochondrial membrane potential was also verified. In conclusion, the exposure of P. subcapitata to metals resulted in a perturbation of the cell physiological status. Principal component analysis revealed that the impairment of esterase activity combined with the reduction of chlorophyll a content were related with the inhibition of growth caused by a prolonged exposure to the heavy metals.

An architecture for an effective usage of data mining in business intelligence systems

Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. Therefore, a lack of an effective usage of DM in BI can be found in some BI systems. An architecture that pretends to conduct to an effective usage of DM in BI is presented.

VPPs information needs for effective operation in competitive electricity markets

The large increase of renewable energy sources and Distributed Generation (DG) of electricity gives place to the Virtual Power Producer (VPP) concept. VPPs may turn electricity generation by renewable sources valuable in electricity markets. Information availability and adequate decision-support tools are crucial for achieving VPPs’ goals. This involves information concerning associated producers and market operation. This paper presents ViProd, a simulation tool that allows simulating VPPs operation, focusing mainly in the information requirements for adequate decision making.

Analysis of polycyclic aromatic hydrocarbons in fish: evaluation of a quick, easy, cheap, effective, rugged, and safe extraction method

QuEChERS method was evaluated for extraction of 16 PAHs from fish samples. For a selective measurement of the compounds, extracts were analysed by LC with fluorescence detection. The overall analytical procedure was validated by systematic recovery experiments at three levels and by using the standard reference material SRM 2977 (mussel tissue). The targeted contaminants, except naphthalene and acenaphthene, were successfully extracted from SRM 2977 with recoveries ranging from 63.5–110.0% with variation coefficients not exceeding 8%. The optimum QuEChERS conditions were the following: 5 g of homogenised fish sample, 10 mL of ACN, agitation performed by vortex during 3 min. Quantification limits ranging from 0.12– 1.90 ng/g wet weight (0.30–4.70 µg/L) were obtained. The optimized methodology was applied to assess the safety concerning PAHs contents of horse mackerel (Trachurus trachurus), chub mackerel (Scomber japonicus), sardine (Sardina pilchardus) and farmed seabass (Dicentrarchus labrax). Although benzo(a)pyrene, the marker used for evaluating the carcinogenic risk of PAHs in food, was not detected in the analysed samples (89 individuals corresponding to 27 homogenized samples), the overall mean concentration ranged from 2.52 l 1.20 ng/g in horse mackerel to 14.6 ± 2.8 ng/ g in farmed seabass. Significant differences were found between the mean PAHs concentrations of the four groups.

A genetic algorithm for project scheduling with multi-modes and renewable resources

This paper presents a genetic algorithm-based approach for project scheduling with multi-modes and renewable resources. In this problem activities of the project may be executed in more than one operating mode and renewable resource constraints are imposed. The objective function is the minimization of the project completion time. The idea of this approach is integrating a genetic algorithm with a schedule generation scheme. This study also proposes applying a local search procedure trying to yield a better solution when the genetic algorithm and the schedule generation scheme obtain a solution. The experimental results show that this algorithm is an effective method for solving this problem.

Estimating Effective Slowdown of Tasks in Energy-Aware Clouds

Consolidation consists in scheduling multiple virtual machines onto fewer servers in order to improve resource utilization and to reduce operational costs due to power consumption. However, virtualization technologies do not offer performance isolation, causing applications’ slowdown. In this work, we propose a performance enforcing mechanism, composed of a slowdown estimator, and a interference- and power-aware scheduling algorithm. The slowdown estimator determines, based on noisy slowdown data samples obtained from state-of-the-art slowdown meters, if tasks will complete within their deadlines, invoking the scheduling algorithm if needed. When invoked, the scheduling algorithm builds performance and power aware virtual clusters to successfully execute the tasks. We conduct simulations injecting synthetic jobs which characteristics follow the last version of the Google Cloud tracelogs. The results indicate that our strategy can be efficiently integrated with state-of-the-art slowdown meters to fulfil contracted SLAs in real-world environments, while reducing operational costs in about 12%.

Space-time monitoring of prescribed burnt soils performance – an effective tool for forest management

Among the most important measures to prevent wild forest fires is the use of prescribed and controlled burning actions in order to reduce the availability of fuel mass. However, the impact of these activities on soil physical and chemical properties varies according to the type of both soil and vegetation and is not fully understood. Therefore, soil monitoring campaigns are often used to measure these impacts. In this paper we have successfully used three statistical data treatments - the Kolmogorov-Smirnov test followed by the ANOVA and the Kruskall-Wallis tests – to investigate the variability among the soil pH, soil moisture, soil organic matter and soil iron variables for different monitoring times and sampling procedures.

Nanoparticles based Permeable Reactive Barriers as an Eco-efficient Technology for nitrate remediation in soil and groundwater

The need to increase agricultural yield led, among others, to an increase in the consumption of nitrogen based fertilizers. As a consequence, there are excessive concentrations of nitrates, the most abundant of the reactive nitrogen (Nr) species, in several areas of the world. The demographic changes and projected population growth for the next decades, and the economic shifts which are already shaping the near future are powerful drivers for a further intensification in the use of fertilizers, with a predicted increase of the nitrogen loads in soils. Nitrate easily diffuses in the subsurface environments, portraying high mobility in soils. Moreover, the presence of high nitrate loads in water has the potential to cause an array of health dysfunctions, such as methemoglobinemia and several cancers. Permeable Reactive Barriers (PRB) placed strategically relatively to the nitrate source constitute an effective technology to tackle nitrate pollution. Ergo, PRB avoid various adverse impacts resulting from the displacement of reactive nitrogen downstream along water bodies. A four stages literature review was carried out in 34 databases. Initially, a set of pertinent key words were identified to perform the initial databases searches. Then, the synonyms of those initial key words were used to carry out a second set of databases searches. The third stage comprised the identification of other additional relevant terms from the research papers identified in the previous two stages. Again, databases searches were performed with this third set of key words. The final step consisted of the identification of relevant papers from the bibliography of the relevant papers identified in the previous three stages of the literature review process. The set of papers identified as relevant for in-depth analysis were assessed considering a set of relevant characterization variables.

Optimization of antioxidants extraction from coffee silverskin, aroasting by-product, having in view a sustainable process

Coffee silverskin is a major roasting by-product that could be valued as a source of antioxidant compounds. The effect of the major variables (solvent polarity, temperature and extraction time) affecting the extraction yields of bioactive compounds and antioxidant activity of silverskin extracts was evaluated. The extracts composition varied significantly with the extraction conditions used. A factorial experimental design showed that the use of a hydroalcoholic solvent (50%:50%) at 40 °C for 60 min is a sustainable option to maximize the extraction yield of bioactive compounds and the antioxidant capacity of extracts. Using this set of conditions it was possible to obtain extracts containing total phenolics (302.5 ± 7.1 mg GAE/L), tannins (0.43 ± 0.06 mg TAE/L), and flavonoids (83.0 ± 1.4 mg ECE/L), exhibiting DPPHradical dot scavenging activity (326.0 ± 5.7 mg TE/L) and ferric reducing antioxidant power (1791.9 ± 126.3 mg SFE/L). These conditions allowed, in comparison with other “more effective” for some individual parameters, a cost reduction, saving time and energy.

Nanotechnology and antioxidant therapy: An emerging approach for neurodegenerative diseases

The efficacy, cellular uptake and specific transport of dietary antioxidants to target organs, tissues and cells remains the most important setback for their application in the treatment of oxidative-stress related disorders and in particular in neurodegenerative diseases, as brain targeting remains a still unsolved challenge. Nanotechnology based delivery systems can be a solution for the above mentioned problems, specifically in the case of targeting dietary antioxidants with neuroprotective activity. Nanotechnology-based delivery systems can protect antioxidants from degradation, improve their physicochemical drug-like properties and in turn their bioavailability. The impact of nanomedicine in the improvement of the performance of dietary antioxidants, as protective agents in oxidative- stress events, specifically through the use of drug delivery systems, is highlighted in this review as well as the type of nanomaterials regularly used for drug delivery purposes. From the data one can conclude that the research combining (dietary) antioxidants and nanotechnology, namely as a therapeutic solution for neurodegenerative diseases, is still in a very early stage. So, a huge research area remains to be explored that hopefully will yield new and effective neuroprotective therapeutic agents in a foreseeable future.

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

A New Heuristic Providing an Effective Initial Solution for a Simulated Annealing approach to Energy Resource Scheduling in Smart Grids

An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.

Cytotoxicity Induced by Extracts of Pisolithus tinctorius Spores on Human Cancer and Normal Cell Lines—Evaluation of the Anticancer Potential

Fungi have been considered a potential source of natural anticancer drugs. However, studies on these organisms have mainly focused on compounds present in the sporocarp and mycelium. The aim of this study was to assess the anticancer potential of fungal spores using a bioassay-guided fractionation with cancer and normal cell lines. Crude extracts from spores of the basidiomycetous fungus Pisolithus tinctorius were prepared using five solvents/solvent mixtures in order to select the most effective crude extraction procedure. A dichloromethane/methanol (DCM/MeOH) mixture was found to produce the highest extraction yield, and this extract was fractionated into 11 fractions. Crude extracts and fractions were assayed for cytotoxicity in the human osteocarcinoma cell line MG63, the human breast carcinoma cell line T47D, the human colon adenocarcinoma cell line RKO, and the normal human brain capillary endothelial cell line hCMEC/D3. Cytotoxicity was assessed by the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) reduction assay. The results showed a reduction in cancer cell viability of approximately 95% with 4 of 11 fractions without a significant reduction in viability of hCMEC/D3 cells. Data demonstrated that spores of P. tinctorius might serve as an interesting source of compounds with potential anticancer properties.