Automatic Incident Detection and Driver Warning in PORTICO.

This paper focuses on the low-volume incident detection and subsequent driver warning objectives of the PORTICO project. It proposes Automatic Incident Detection (AID) which uses a multimodel approach comprised of a number of different algorithms. A set of thresholds and conditions are defined which determine which algorithm(s) need to indicate an incident under different traffic conditions in order to trigger an alarm

Microcantilever sensors for biochemical detection and analysis

Biochemical agents, including bacteria and toxins, are potentially dangerous and responsible for a wide variety of diseases. Reliable detection and characterization of small samples is necessary in order to reduce and eliminate their harmful consequences. Microcantilever sensors offer a potential alternative to the state of the art due to their small size, fast response time, and the ability to operate in air and liquid environments. At present, there are several technology limitations that inhibit application of microcantilever to biochemical detection and analysis, including difficulties in conducting temperature-sensitive experiments, material inadequacy resulting in insufficient cell capture, and poor selectivity of multiple analytes. This work aims to address several of these issues by introducing microcantilevers having integrated thermal functionality and by introducing nanocrystalline diamond as new material for microcantilevers. Microcantilevers are designed, fabricated, characterized, and used for capture and detection of cells and bacteria. The first microcantilever type described in this work is a silicon cantilever having highly uniform in-plane temperature distribution. The goal is to have 100 μm square uniformly heated area that can be used for thermal characterization of films as well as to conduct chemical reactions with small amounts of material. Fabricated cantilevers can reach above 300C while maintaining temperature uniformity of 2−4%. This is an improvement of over one order of magnitude over currently available cantilevers. The second microcantilever type is a doped single crystal silicon cantilever having a thin coating of ultrananocrystalline diamond (UNCD). The primary application of such a device is in biological testing, where diamond acts as a stable, electrically isolated reaction surface while silicon layer provides controlled heating with minimum variations in temperature. This work shows that composite cantilevers of this kind are an effective platform for temperature-sensitive biological experiments, such as heat lysing and polymerase chain reaction. The rapid heat-transfer of Si-UNCD cantilever compromised the membrane of NIH 3T3 fibroblast and lysed the cell nucleus within 30 seconds. Bacteria cells, Listeria monocytogenes V7, were shown to be captured with biotinylated heat-shock protein on UNCD surface and 90% of all viable cells exhibit membrane porosity due to high heat in 15 seconds. Lastly, a sensor made solely from UNCD diamond is fabricated with the intention of being used to detect the presence of biological species by means of an integrated piezoresistor or through frequency change monitoring. Since UNCD diamond has not been previously used in piezoresistive applications, temperature-denpendent piezoresistive coefficients and gage factors are determined first. The doped UNCD exhibits a significant piezoresistive effect with gauge factor of 7.53±0.32 and a piezoresistive coefficient of 8.12×10^−12 Pa^−1 at room temperature. The piezoresistive properties of UNCD are constant over the temperature range of 25−200C. 300 μm long cantilevers have the highest sensitivity of 0.186 m-Ohm/Ohm per μm of cantilever end deflection, which is approximately half that of similarly sized silicon cantilevers. UNCD cantilever arrays were fabricated consisting of four sixteen-cantilever arrays of length 20–90 μm in addition to an eight-cantilever array of length 120 μm. Laser doppler vibrometry (LDV) measured the cantilever resonant frequency, which ranged as 218 kHz−5.14 MHz in air and 73 kHz−3.68 MHz in water. The quality factor of the cantilever was 47−151 in air and 18−45 in water. The ability to measure frequencies of the cantilever arrays opens the possibility for detection of individual bacteria by monitoring frequency shift after cell capture.

Hazelnut Allergens: Molecular Characterisation, Detection and Clinical Relevance

In the last years, special attention has been devoted to food-induced allergies, from which hazelnut allergy is highlighted. Hazelnut is one of the most commonly consumed tree nuts, being largely used by the food industry in a wide variety of processed foods. It has been regarded as a food with potential health benefits, but also as a source of allergens capable of inducing mild to severe allergic reactions in sensitised individuals. Considering the great number of reports addressing hazelnut allergens, with an estimated increasing trend, this review intends to assemble all the relevant information available so far on the main issues: prevalence of tree nut allergy, clinical threshold levels, molecular characterisation of hazelnut allergens (Cor a 1, Cor a 2, Cor a 8, Cor a 9, Cor a 10, Cor a 11, Cor a 12, Cor a 14 and Cor a TLP) and their clinical relevance, and methodologies for hazelnut allergen detection in foods. A comprehensive overview on the current data about the molecular characterisation of hazelnut allergens is presented, relating biochemical classification and biological function with clinical importance. Recent advances on hazelnut allergen detection methodologies are summarised and compared, including all the novel protein- and DNA-based approaches.

Isolation and recognition Saprolegnia species from fungal infected eggs of the rainbow trout in Mazandaran province farms

Fungal infection in the eggs of freshwater fish is well known as a problematic disease. That isolation and recognition Saprolegnia fungi from fungal infected eggs of the rainbow trout in Mazandaran province was the aim of this research. For this purpose fungal infected eggs were examined from six fish farm in the fall and winter 2005-2006. The eggs with fungi were inoculated on SDA, CMA, GPagar and hemp seed and sesame seed cultures in sterile tap water at room temperature (18-24°C). In this study recognized three genera and six species Saprolegniaceae members, based on morphological characteristics which contain: Saprolegnia, Achlya, Brevilegnia. Four species were identified in the genus Saprolegnia; S.mixta, S.parasitica, S.moniliphera, S.lapponica and one species was identified in the genus Achlya; A.oblongata. S.parasitica was isolated from almost all the farms. In addition, another nine genera and species were identified; Penicillium, Aspergillus, Paeciliomyces, Acremonium, Fusarium oxysporum, F.solani , Alternaria, Helminthosporium, Mucor.

'Malicious Code Execution Detection and Response Immune System inspired by the Danger Theory'

The analysis of system calls is one method employed by anomaly detection systems to recognise malicious code execution. Similarities can be drawn between this process and the behaviour of certain cells belonging to the human immune system, and can be applied to construct an artificial immune system. A recently developed hypothesis in immunology, the Danger Theory, states that our immune system responds to the presence of intruders through sensing molecules belonging to those invaders, plus signals generated by the host indicating danger and damage. We propose the incorporation of this concept into a responsive intrusion detection system, where behavioural information of the system and running processes is combined with information regarding individual system calls.

Neuronal Assembly Detection and Cell Membership Specification by Principal Component Analysis

LOPES-DOS-SANTOS, V. , CONDE-OCAZIONEZ, S. ; NICOLELIS, M. A. L. , RIBEIRO, S. T. , TORT, A. B. L. . Neuronal assembly detection and cell membership specification by principal component analysis. Plos One, v. 6, p. e20996, 2011.

Engraulis encrasicolus (Linnaeus, 1758): technical report about extraction and recognition of the digestive tract contents in early stages of the life cycle

The study of ichthyio-plankton stages and its relations with the environment and other organisms is therefore crucial for a correct use of fishery resources. In this context, the extraction and the analysis of the content of the digestive tract, is a key method for the identification of the diet in early larval stages, the determination of the resources they rely on and possibly a comparison with the diet of other species. Additionally this approach could be useful in determination on occurrence of species competition. This technique is preceded by the analysis of morphometric data (Blackith & Reyment, 1971; Marcus, 1990), that is the acquisition of quantitative variables measured from the morphology of the object of study. They are linear distances, count, angles and ratios. The subsequent application of multivariate statistical methods, aims to quantify the changes in morphological measures between and within groups, relating them to the type and size of prey and evaluate if some changes appear in food choices along the larvae growth.

Lie detection and children: Impact of the mode of presentation

Although a great deal of research has examined lie-detection among adults, little research has examined the differences between audio and visual mediums for deception among children. In the current study participants were presented (n = 42) with recordings of four children, each describing his/her experience of getting glasses. Two of the accounts were truthful, two were fabricated. Half of the participants were presented with videos, half were presented with audio-recordings. Following the presentation of each recording, participants responded to questions regarding the truthfulness of each child’s account. Results showed that when evaluating truth-tellers, participants’ lie-detection accuracy was significantly greater than chance. Within the video condition, non-parents were shown to report significantly more lie-related cues than parents. Several deception cues were shown to be related to lie-detection accuracy.

Rapid detection and quantification of the marine toxic algae, Alexandrium minutum, using a super-paramagnetic immunochromatographic strip test

The dinoflagellates of Alexandrium genus are known to be producers of paralytic shellfish toxins that regularly impact the shellfish aquaculture industry and fisheries. Accurate detection of Alexandrium including A. minutum is crucial for environmental monitoring and sanitary issues. In this study, we firstly developed a quantitative lateral flow immunoassay (LFIA) using super-paramagnetic nanobeads for A. minutum whole cells. This dipstick assay relies on two distinct monoclonal antibodies used in a sandwich format and directed against surface antigens of this organism. No sample preparation is required. Either frozen or live cells can be detected and quantified. The specificity and sensitivity are assessed by using phytoplankton culture and field samples spiked with a known amount of cultured A. minutum cells. This LFIA is shown to be highly specific for A. minutum and able to detect reproducibly 105 cells/L within 30 min. The test is applied to environmental samples already characterized by light microscopy counting. No significant difference is observed between the cell densities obtained by these two methods. This handy super-paramagnetic lateral flow immnunoassay biosensor can greatly assist water quality monitoring programs as well as ecological research.

'Malicious Code Execution Detection and Response Immune System inspired by the Danger Theory'

The analysis of system calls is one method employed by anomaly detection systems to recognise malicious code execution. Similarities can be drawn between this process and the behaviour of certain cells belonging to the human immune system, and can be applied to construct an artificial immune system. A recently developed hypothesis in immunology, the Danger Theory, states that our immune system responds to the presence of intruders through sensing molecules belonging to those invaders, plus signals generated by the host indicating danger and damage. We propose the incorporation of this concept into a responsive intrusion detection system, where behavioural information of the system and running processes is combined with information regarding individual system calls.

The SOPHIE search for northern extrasolar planets: X. Detection and characterization of giant planets by the dozen

We present new radial velocity measurements of eight stars that were secured with the spectrograph SOPHIE at the 193 cm telescope of the Haute-Provence Observatory. The measurements allow detecting and characterizing new giant extrasolar planets. The host stars are dwarfs of spectral types between F5 and K0 and magnitudes of between 6.7 and 9.6; the planets have minimum masses Mp sin i of between 0.4 to 3.8 MJup and orbitalperiods of several days to several months. The data allow only single planets to be discovered around the first six stars (HD 143105, HIP 109600, HD 35759, HIP 109384, HD 220842, and HD 12484), but one of them shows the signature of an additional substellar companion in the system. The seventh star, HIP 65407, allows the discovery of two giant planets that orbit just outside the 12:5 resonance in weak mutual interaction. The last star, HD 141399, was already known to host a four-planet system; our additional data and analyses allow new constraints to be set on it. We present Keplerian orbits of all systems, together with dynamical analyses of the two multi-planet systems. HD 143105 is one of the brightest stars known to host a hot Jupiter, which could allow numerous follow-up studies to be conducted even though this is not a transiting system. The giant planets HIP 109600b, HIP 109384b, and HD 141399c are located in the habitable zone of their host star.

Wind turbine indirect ice detection and operational analysis

Wind energy is one of the most promising and fast growing sector of energy production. Wind is ecologically friendly and relatively cheap energy resource available for development in practically all corners of the world (where only the wind blows). Today wind power gained broad development in the Scandinavian countries. Three important challenges concerning sustainable development, i.e. energy security, climate change and energy access make a compelling case for large-scale utilization of wind energy. In Finland, according to the climate and energy strategy, accepted in 2008, the total consumption of electricity generated by means of wind farms by 2020, should reach 6 - 7% of total consumption in the country [1]. The main challenges associated with wind energy production are harsh operational conditions that often accompany the turbine operation in the climatic conditions of the north and poor accessibility for maintenance and service. One of the major problems that require a solution is the icing of turbine structures. Icing reduces the performance of wind turbines, which in the conditions of a long cold period, can significantly affect the reliability of power supply. In order to predict and control power performance, the process of ice accretion has to be carefully tracked. There are two ways to detect icing – directly or indirectly. The first way applies to the special ice detection instruments. The second one is using indirect characteristics of turbine performance. One of such indirect methods for ice detection and power loss estimation has been proposed and used in this paper. The results were compared to the results directly gained from the ice sensors. The data used was measured in Muukko wind farm, southeast Finland during a project 'Wind power in cold climate and complex terrain'. The project was carried out in 9/2013 - 8/2015 with the partners Lappeenranta university of technology, Alstom renovables España S.L., TuuliMuukko, and TuuliSaimaa.