An automated microreactor for semi-continuous biosensor measurements.

Living bacteria or yeast cells are frequently used as bioreporters for the detection of specific chemical analytes or conditions of sample toxicity. In particular, bacteria or yeast equipped with synthetic gene circuitry that allows the production of a reliable non-cognate signal (e.g., fluorescent protein or bioluminescence) in response to a defined target make robust and flexible analytical platforms. We report here how bacterial cells expressing a fluorescence reporter ("bactosensors"), which are mostly used for batch sample analysis, can be deployed for automated semi-continuous target analysis in a single concise biochip. Escherichia coli-based bactosensor cells were continuously grown in a 13 or 50 nanoliter-volume reactor on a two-layered polydimethylsiloxane-on-glass microfluidic chip. Physiologically active cells were directed from the nl-reactor to a dedicated sample exposure area, where they were concentrated and reacted in 40 minutes with the target chemical by localized emission of the fluorescent reporter signal. We demonstrate the functioning of the bactosensor-chip by the automated detection of 50 μgarsenite-As l(-1) in water on consecutive days and after a one-week constant operation. Best induction of the bactosensors of 6-9-fold to 50 μg l(-1) was found at an apparent dilution rate of 0.12 h(-1) in the 50 nl microreactor. The bactosensor chip principle could be widely applicable to construct automated monitoring devices for a variety of targets in different environments.

Towards automated specifications of scenarios in enhanced learning technology

Recent standardization efforts in e-learning technology have resulted in a number of specifications, however, the automation process that is considered essential in a learning management system (LMS) is a lessexplored one. As learning technology becomes more widespread and more heterogeneous, there is a growing need to specify processes that cross the boundaries of a single LMS or learning resource repository. This article proposes to obtain a specification orientated to automation that takes on board the heterogeneity of systems and formats and provides a language for specifying complex and generic interactions. Having this goal in mind, a technique based on three steps is suggested. The semantic conformance profiles, the business process management (BPM) diagram, and its translation into the business process execution language (BPEL) seem to be suitable for achieving it.

An ontology to automated learning scenarios? an approach to its knowledge domain

Automation or semi-automation of learning scenariospecifications is one of the least exploredsubjects in the e-learning research area. There isa need for a catalogue of learning scenarios and atechnique to facilitate automated retrieval of stored specifications. This requires constructing anontology with this goal and is justified inthis paper. This ontology must mainlysupport a specification technique for learning scenarios. This ontology should also be useful in the creation and validation of new scenarios as well as in the personalization of learning scenarios or their monitoring. Thus, after justifying the need for this ontology, a first approach of a possible knowledge domain is presented. An example of a concrete learning scenario illustrates some relevant concepts supported by this ontology in order to define the scenario in such a way that it could be easy to automate.

Automated flow-injection method for cadmium determination with pre-concentration and reagent preparation on-line

The spectrophotometric determination of Cd(II) using a flow injection system provided with a solid-phase reactor for cadmium preconcentration and on-line reagent preparation, is described. It is based on the formation of a dithizone-Cd complex in basic medium. The calibration curve is linear between 6 and 300 µg L-1 Cd(II), with a detection limit of 5.4 µg L-1, an RSD of 3.7% (10 replicates in duplicate) and a sample frequency of 11.4 h-1. The proposed method was satisfactorily applied to the determination of Cd(II) in surface, well and drinking waters.

Determination of etoricoxib in human plasma using automated on-line solid-phase extraction coupled with LC-APCI/MS/MS

A liquid chromatography-tandem mass spectrometry method with atmospheric pressure chemical ionization (LC-APCI/MS/MS) was validated for the determination of etoricoxib in human plasma using antipyrin as internal standard, followed by on-line solid-phase extraction. The method was performed on a Luna C18 column and the mobile phase consisted of acetonitrile:water (95:5, v/v)/ammonium acetate (pH 4.0; 10 mM), run at a flow rate of 0.6 mL/min. The method was linear in the range of 1-5000 ng/mL (r²>0.99). The lower limit of quantitation was 1 ng/mL. The recoveries were within 93.72-96.18%. Moreover, method validation demonstrated acceptable results for the precision, accuracy and stability studies.

THE APPLICATION OF AUTOMATED CORRELATION OPTIMIZED WARPING TO THE QUALITY EVALUATION OF Radix Puerariae thomsonii: CORRECTING RETENTION TIME SHIFT IN THE CHROMATOGRAPHIC FINGERPRINTS

The application of automated correlation optimized warping (ACOW) to the correction of retention time shift in the chromatographic fingerprints of Radix Puerariae thomsonii (RPT) was investigated. Twenty-seven samples were extracted from 9 batches of RPT products. The fingerprints of the 27 samples were established by the HPLC method. Because there is a retention time shift in the established fingerprints, the quality of these samples cannot be correctly evaluated by using similarity estimation and principal component analysis (PCA). Thus, the ACOW method was used to align these fingerprints. In the ACOW procedure, the warping parameters, which have a significant influence on the alignment result, were optimized by an automated algorithm. After correcting the retention time shift, the quality of these RPT samples was correctly evaluated by similarity estimation and PCA. It is demonstrated that ACOW is a practical method for aligning the chromatographic fingerprints of RPT. The combination of ACOW, similarity estimation, and PCA is shown to be a promising method for evaluating the quality of Traditional Chinese Medicine.

Financial and Environmental Impacts of a Dry Port to Facilitate Competitiveness of Two Major Transit Seaports of Finland

Environmental problems and issues have received more and more attention during the last decades. Reasons for this are different increased external costs such as congestion, CO2 emission, noise and accident costs. Transportation sector is the only sector with increasing external costs. The EU will increase its attention in decreasing the external costs of transport. Aim of this research was to find out if a dry port solution could decrease costs of transport, especially external costs. Dry port concept is an intermodal transport system, where inland transport between port and dry port is performed by rail transport instead of traditional road transport. In addition, dry ports offer similar services as ports. Research is conducted by performing a literature review about dry port concept and costs of transport, especially external costs of transport. Financial and environmental impacts of the dry port concept are studied by comparing costs of road and rail transport by cost accounting and with a simulation model. Location of dry port is researched with gravitational models. Results of the literature review are that rail transport is environmentally friendlier mode of transport than road transport. Cost model and simulation model show that if only costs of freight movement are considered, rail transport is more inexpensive transport mode than road transport in terms of internal and external costs. Because of that dry port concept could decrease costs of transport, especially external costs. Results of gravitational models are that city of Kouvola is in a good position to be a dry port. Russian transit traffic through Finland improves location of Kouvola to be a dry port.

Automated, adaptive methods for forest inventory

Forest inventories are used to estimate forest characteristics and the condition of forest for many different applications: operational tree logging for forest industry, forest health state estimation, carbon balance estimation, land-cover and land use analysis in order to avoid forest degradation etc. Recent inventory methods are strongly based on remote sensing data combined with field sample measurements, which are used to define estimates covering the whole area of interest. Remote sensing data from satellites, aerial photographs or aerial laser scannings are used, depending on the scale of inventory. To be applicable in operational use, forest inventory methods need to be easily adjusted to local conditions of the study area at hand. All the data handling and parameter tuning should be objective and automated as much as possible. The methods also need to be robust when applied to different forest types. Since there generally are no extensive direct physical models connecting the remote sensing data from different sources to the forest parameters that are estimated, mathematical estimation models are of "black-box" type, connecting the independent auxiliary data to dependent response data with linear or nonlinear arbitrary models. To avoid redundant complexity and over-fitting of the model, which is based on up to hundreds of possibly collinear variables extracted from the auxiliary data, variable selection is needed. To connect the auxiliary data to the inventory parameters that are estimated, field work must be performed. In larger study areas with dense forests, field work is expensive, and should therefore be minimized. To get cost-efficient inventories, field work could partly be replaced with information from formerly measured sites, databases. The work in this thesis is devoted to the development of automated, adaptive computation methods for aerial forest inventory. The mathematical model parameter definition steps are automated, and the cost-efficiency is improved by setting up a procedure that utilizes databases in the estimation of new area characteristics.

Automated Software Testing in Machine Automation

The problem of software (SW) defaults is becoming more and more topical because of increasing amount of the SW and its complication. The majority of these defaults are founded during the test part that consumes about 40-50% of the development efforts. Test automation allows reducing the cost of this process and increasing testing effectiveness. In the middle of 1980 the first tools for automated testing appeared and the automated process was implemented in different kinds of SW testing. In short time, it became obviously, automated testing can cause many problems such as increasing product cost, decreasing reliability and even project fail. This thesis describes automated testing process, its concept, lists main problems, and gives an algorithm for automated test tools selection. Also this work presents an overview of the main automated test tools for embedded systems.

Benefits of automated acclimatization during the pre-milking phase of lactating girolando cows

The aim of this paper was to evaluate the automated acclimatization effects during pre-milking of cows on thermal conditioning, physiology, milk production and cost-benefit of the automated adiabatic evaporative cooling system (AECS). The treatments 20; 30; 40 min and control consisted of exposure time of pre-milking cows to the automated AECS. Sixteen cows were used with an average daily milk yield of 19 kg, distributed in a 4 x 4 Latin square design. The Tukey's test (P<0.05) was used to compare the means. The environmental variables, dry bulb temperature (DBT, ºC) and relative humidity (RH, %), were recorded every minute, which allowed the determination of the system efficiency through the Temperature and Humidity Index (THI). The respiratory rate (RR), rectal temperature (RT) and temperature of the coat (TC) were measured before and after the acclimatization. The 40 min treatment kept the environmental variables and the comfort indexes within recommended limits. The physiological variables (RR, RT and TC) were lower in the 40 min treatment and reflected positively on milk production, which increased 3.66% compared to the control treatment. The system was profitable, having a 43 days return on investment and a monthly revenue increase of R$ 1,992.67.