Reducing Vibrio load in Artemia nauplii usingantimicrobial photodynamic therapy: a promising strategy to reduce antibiotic application in shrimp larviculture

We propose antimicrobial photodynamic therapy (aPDT) as an alternative strategy to reduce the use of antibiotics in shrimp larviculture systems. The growth of a multiple antibiotic resistant Vibrio harveyi strain was effectively controlled by treating the cells with Rose Bengal and photosensitizing for 30 min using a halogen lamp. This resulted in the death of > 50% of the cells within the first 10 min of exposure and the 50% reduction in the cell wall integrity after 30 min could be attributed to the destruction of outer membrane protein of V. harveyi by reactive oxygen intermediates produced during the photosensitization. Further, mesocosm experiments with V. harveyi and Artemia nauplii demonstrated that in 30 min, the aPDT could kill 78.9% and 91.2% of heterotrophic bacterial and Vibrio population respectively. In conclusion, the study demonstrated that aPDT with its rapid action and as yet unreported resistance development possibilities could be a propitious strategy to reduce the use of antibiotics in shrimp larviculture systems and thereby, avoid their hazardous effects on human health and the ecosystem at large.

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year

Praxisrelevante Auswirkungen des Vorschlages für eine EU-Verordnung KOM/2000/7/final, 2000/0212(COD) des europäischen Parlaments und des Rates von der Kommission der Europäischen Gemeinschaften auf die Verkehrsplanung des öffentlichen Personennahverkehrs

Die Arbeit behandelt den Vorschlag für eine EU-Verordnung KOM/2000/7/final, 2000/0212(COD) des europäischen Parlaments und des Rates von der Kommission der Europäischen Gemeinschaften als Grundlage einer Marktöffnungsverordnung und welche Veränderungen sich dadurch in Deutschland einstellen werden. Ausschreibungen von Verkehrsleistungen werden zunehmen. Die Ausschreibungsarten werden sich in ländlichen Regionen von denen in Verkehrszentren unterscheiden. In der Region werden sich Bedarfslösungen stärker durchsetzen. Kürzungen von Verkehrsleistungen werden hier stärker ausfallen als in den Zentren und damit zu einem kleineren Leistungsvolumen führen. Aufgrund des geringen Leistungsumfangs gibt es weniger Interessenten. Bei Standardausschreibungen werden deshalb auch häufig die Varianten der beschränkten oder die freihändige Vergabe gewählt. Funktionale Ausschreibungen haben nur eine untergeordnete Bedeutung. In den Verkehrszentren sind die Lose größer und damit für viele Anbieter interessant. Die Verkehrszusatzleistungen sind zudem komplexer. Standardausschreibungen in öffentlicher Vergabeart werden sich hier vermutlich als Norm durchsetzen. Die VOL/A wird sicherlich ihre Bedeutung und ihren dafür notwendigen Regelungsumfang in Deutschland als deutsches oder als europäisches Recht behalten. Ob der empfehlende Charakter der DIN EN 13816 Norm „ÖPNV: Definition, Festlegung von Leistungszielen und Messung der Servicequalität“ erhalten werden kann und nicht als Steuerungselement zur Standardisierung im ÖPNV beitragen wird, ist dabei zu bezweifeln. Durch diese Wettbewerbspflicht wird der Aufgabenträger zum Besteller von Verkehrsleistungen. Damit geht die Verkehrsplanung in die Verantwortung des Aufgabenträgers über und gerät stärker in den Einflussbereich der Politik. Die strategisch abstrakte und die konkrete Verkehrsplanung wachsen für den Normfall der Standardausschreibung zusammen. Die Hoffnung auf eine bessere Netzintegration und eine Standardisierung des ÖPNV Angebots und der ÖPNV Qualität entsteht. Es entwickelt sich dadurch aber auch die Gefahr der Abhängigkeit des Nahverkehrsangebots von der derzeitigen Haushaltslage oder der Interessenlage der Politik. Kontinuität in Angebot und Qualität werden zu erklärten Planungszielen. Der Verkehrsplaner auf der Bestellerseite muss die Planung in Ausschreibungsunterlagen umsetzen. Dies erfordert erweiterte Kompetenzen in den Bereichen Betriebswirtschaft, Logistik, Jura, Informatik und Führungskompetenzen. Ausbildende Institutionen müssen darauf bereits im Vorfeld der Umsetzung reagieren. Durch die zeitliche Verzögerung der Umsetzung der Planung durch die Ausschreibungsschritte sind in der Verkehrsplanung längere Planungsvorlaufzeiten einzukalkulieren. Vorausschauender zu planen, wird dabei wichtiger. Auch eventuelle Fehler in der Planung sind nicht mehr so einfach zu korrigieren. Durch den gestiegenen Einsatz von Technologien in den Fahrzeugen besteht für den Verkehrsplaner dafür häufiger die Möglichkeit, Planungsänderungen auf ihre Wirksamkeit im Hinblick auf Attraktivität für den Fahrgast anhand von den ermittelten Fahrgastzahlen zu kontrollieren. Dasselbe gilt auch für Marketing- und Vertriebsmaßnahmen, wie für die Tarifpolitik. Die Zahlen stehen nicht nur für diese Rückkopplung zur Verfügung, sondern dienen auch als Planungsgrundlage für zukünftige Maßnahmen. Dem Planer stehen konkretere Zahlen für die Planung zur Verfügung. Ein Aspekt, der aufgrund der Sanktionsmaßnahmen bei Ausschreibungen an Bedeutung gewinnen wird, ist die Möglichkeit, Qualität von Verkehrsleistungen möglichst objektiv beurteilen zu können. Praxisrelevante Auswirkungen auf die Verkehrsplanung des öffentlichen Personennahverkehrs ergeben sich hauptsächlich durch die gestiegene Komplexität in der Planung selbst und den dadurch unverzichtbaren gewordenen Einsatz von Computerunterstützung. Die Umsetzung in Ausschreibungsunterlagen der Planung und die Kontrolle stellen neue Elemente im Aufgabenbereich des Verkehrsplaners dar und erfordern damit breiter ausgelegte Kernkompetenzen. Es werden mehr Verkehrsplaner mit breiterer Ausbildung benötigt werden. Diese Arbeit hat aufgezeigt, dass sich mit der Integration des Ausschreibungsgedankens in den Ablauf der Verkehrsplanung eine sprunghafte Entwicklung in der Planungstätigkeit ergeben wird. Aufgrund der in Zukunft steigenden Qualität und Quantität der Planungsgrundlagen und der ebenfalls gestiegenen Ansprüche an die Bewertungsparameter ergeben sich Veränderungen und neue Anforderungen auf diesem Gebiet, die in erster Linie für die Hochschulen und andere ausbildende Einrichtungen, aber auch für die Verkehrsplanung unterstützende Industrie.

Effects of memory load on visual search

Resumen tomado de la publicaci??n

Reductions in insecticide use from adoption of Bt cotton in South Africa: impacts on economic performance and toxic load to the environment

The study reported presents the findings relating to commercial growing of genetically-modified Bt cotton in South Africa by a large sample of smallholder farmers over three seasons (1998/99, 1999/2000, 2000/01) following adoption. The analysis presents constructs and compares groupwise differences for key variables in Bt v. non-Bt technology and uses regressions to further analyse the production and profit impacts of Bt adoption. Analysis of the distribution of benefits between farmers due to the technology is also presented. In parallel with these socio-economic measures, the toxic loads being presented to the environment following the introduction of Bt cotton are monitored in terms of insecticide active ingredient (ai) and the Biocide Index. The latter adjusts ai to allow for differing persistence and toxicity of insecticides. Results show substantial and significant financial benefits to smallholder cotton growers of adopting Bt cotton over three seasons in terms of increased yields, lower insecticide spray costs and higher gross margins. This includes one particularly wet, poor growing season. In addition, those with the smaller holdings appeared to benefit proportionately more from the technology (in terms of higher gross margins) than those with larger holdings. Analysis using the Gini-coefficient suggests that the Bt technology has helped to reduce inequality amongst smallholder cotton growers in Makhathini compared to what may have been the position if they had grown conventional cotton. However, while Bt growers applied lower amounts of insecticide and had lower Biocide Indices (per ha) than growers of non-Bt cotton, some of this advantage was due to a reduction in non-bollworm insecticide. Indeed, the Biocide Index for all farmers in the population actually increased with the introduction of Bt cotton. The results indicate the complexity of such studies on the socio-economic and environmental impacts of GM varieties in the developing world.

Hydrochemical variations and contaminant load in the Rio Tinto (Spain) during flood events

The aim of this work is to study the hydrochemical variations during flood events in the Rio Tinto, SW Spain. Three separate rainfall/flood events were monitored in October 2004 following the dry season. In general, concentrations markedly increased following the first event (Fe from 99 to 1130 mg/L; Q(max) = 0.78 m(3)/s) while dissolved loads peaked in the second event (Fe = 7.5 kg/s, Cu = 0.83 kg/s, Zn = 0.82 kg/s; Q(max) = 77 m(3)/s) and discharge in the third event (Q(max) = 127 m(3)/s). This pattern reflects a progressive depletion of metals and sulphate stored in the dry summer as soluble evaporitic salt minerals and concentrated pore fluids, with dilution by freshwater becoming increasingly dominant as the month progressed. Variations in relative concentrations were attributed to oxyhydroxysulphate Fe precipitation, to relative changes in the sources of acid mine drainage (e.g. salt minerals, mine tunnels, spoil heaps etc.) and to differences in the rainfall distributions along the catchment. The contaminant load carried by the river during October 2004 was enormous, totalling some 770 t of Fe, 420 t of Al, 100 t of Cu, 100 t of Zn and 71 t of Mn. This represents the largest recorded example of this flush-out process in an acid mine drainage setting. Approximately 1000 times more water and 1408 200 times more dissolved elements were carried by the river during October 2004 than during the dry, low-flow conditions of September 2004, highlighting the key role of flood Events in the annual pollutant transport budget of semi-arid and and systems and the need to monitor these events in detail in order to accurately quantify pollutant transport. (c) 2007 Elsevier B.V. All rights reserved.

Uncertainties in annual riverine phosphorus load estimation: Impact of load estimation methodology, sampling frequency, baseflow index and catchment population density

Models developed to identify the rates and origins of nutrient export from land to stream require an accurate assessment of the nutrient load present in the water body in order to calibrate model parameters and structure. These data are rarely available at a representative scale and in an appropriate chemical form except in research catchments. Observational errors associated with nutrient load estimates based on these data lead to a high degree of uncertainty in modelling and nutrient budgeting studies. Here, daily paired instantaneous P and flow data for 17 UK research catchments covering a total of 39 water years (WY) have been used to explore the nature and extent of the observational error associated with nutrient flux estimates based on partial fractions and infrequent sampling. The daily records were artificially decimated to create 7 stratified sampling records, 7 weekly records, and 30 monthly records from each WY and catchment. These were used to evaluate the impact of sampling frequency on load estimate uncertainty. The analysis underlines the high uncertainty of load estimates based on monthly data and individual P fractions rather than total P. Catchments with a high baseflow index and/or low population density were found to return a lower RMSE on load estimates when sampled infrequently than those with a tow baseflow index and high population density. Catchment size was not shown to be important, though a limitation of this study is that daily records may fail to capture the full range of P export behaviour in smaller catchments with flashy hydrographs, leading to an underestimate of uncertainty in Load estimates for such catchments. Further analysis of sub-daily records is needed to investigate this fully. Here, recommendations are given on load estimation methodologies for different catchment types sampled at different frequencies, and the ways in which this analysis can be used to identify observational error and uncertainty for model calibration and nutrient budgeting studies. (c) 2006 Elsevier B.V. All rights reserved.

Dynamic load balancing for the distributed mining of molecular structures

In molecular biology, it is often desirable to find common properties in large numbers of drug candidates. One family of methods stems from the data mining community, where algorithms to find frequent graphs have received increasing attention over the past years. However, the computational complexity of the underlying problem and the large amount of data to be explored essentially render sequential algorithms useless. In this paper, we present a distributed approach to the frequent subgraph mining problem to discover interesting patterns in molecular compounds. This problem is characterized by a highly irregular search tree, whereby no reliable workload prediction is available. We describe the three main aspects of the proposed distributed algorithm, namely, a dynamic partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiverinitiated load balancing algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer Institute’s HIV-screening data set, where we were able to show close-to linear speedup in a network of workstations. The proposed approach also allows for dynamic resource aggregation in a non dedicated computational environment. These features make it suitable for large-scale, multi-domain, heterogeneous environments, such as computational grids.

Decentralized load balancing for highly irregular search problems

In this paper, we present a distributed computing framework for problems characterized by a highly irregular search tree, whereby no reliable workload prediction is available. The framework is based on a peer-to-peer computing environment and dynamic load balancing. The system allows for dynamic resource aggregation, does not depend on any specific meta-computing middleware and is suitable for large-scale, multi-domain, heterogeneous environments, such as computational Grids. Dynamic load balancing policies based on global statistics are known to provide optimal load balancing performance, while randomized techniques provide high scalability. The proposed method combines both advantages and adopts distributed job-pools and a randomized polling technique. The framework has been successfully adopted in a parallel search algorithm for subgraph mining and evaluated on a molecular compounds dataset. The parallel application has shown good calability and close-to linear speedup in a distributed network of workstations.

Dynamic load balancing in parallel KD-tree k-means

One among the most influential and popular data mining methods is the k-Means algorithm for cluster analysis. Techniques for improving the efficiency of k-Means have been largely explored in two main directions. The amount of computation can be significantly reduced by adopting geometrical constraints and an efficient data structure, notably a multidimensional binary search tree (KD-Tree). These techniques allow to reduce the number of distance computations the algorithm performs at each iteration. A second direction is parallel processing, where data and computation loads are distributed over many processing nodes. However, little work has been done to provide a parallel formulation of the efficient sequential techniques based on KD-Trees. Such approaches are expected to have an irregular distribution of computation load and can suffer from load imbalance. This issue has so far limited the adoption of these efficient k-Means variants in parallel computing environments. In this work, we provide a parallel formulation of the KD-Tree based k-Means algorithm for distributed memory systems and address its load balancing issue. Three solutions have been developed and tested. Two approaches are based on a static partitioning of the data set and a third solution incorporates a dynamic load balancing policy.