Inactivation of Salmonella , Listeria monocytogenes and Escherichia coli O157:H7 inoculated on coriander by freeze-drying and supercritical CO 2 drying

Coriander, either fresh or inoculated with three strains of Escherichia coli O157:H7, Salmonella or Listeria monocytogenes, was treated with supercritical CO2 (scCO(2), with and without drying) or freeze-dried. After drying in scCO(2) for 150 min at 80 bar and 35 degrees C, the aerobic plate count, yeasts and molds, and the Enterobacteriaceae were reduced by 2.80, 5.03, and 4.61 log CFU/g, respectively. The total count of mesophilic aerobic spores was not significantly reduced by the treatment. Freeze-drying induced lower reductions with 1.23, 0.87, and 0.97 log CFU/g, respectively. After treatment at 100 bar and 40 degrees C without drying, inoculated strains of E. coli O157:H7, Salmonella, and L. monocytogenes were inactivated by > 7.37, > 4.73 and 4.99 log CFU/g, respectively. After drying in scCO 2 for 150 min at 80 bar and 35 degrees C, the strains were reduced by > 5.18 log CFU/g. Freeze-drying resulted in lower reduction with maximum 1.53, 2.03, and 0.71 log CFU/g, respectively. This study indicated that scCO(2) can be used for drying while offering a good inactivation of E. coli O157:H7, Salmonella, and L. monocytogenes as well as most of the bacteria in the vegetative form naturally occurring on coriander. Industrial relevance: Although dried foods are considered microbiological stable foods and show adverse conditions to microbial growth, they may still host pathogenic microorganisms, which may proliferate upon sufficient rehydration. Highly contaminated commodities such as herbs and spices can pose a threat to consumer health if not processed carefully. There is therefore a need to develop or improve drying techniques which can provide dried foods while reducing the initial contamination to acceptable levels in a single process. CO2 is a cheap, accessible solvent, with a low critical point (31 degrees C, 73.8 bar). Moreover, in the supercritical region, CO, exhibits potent microbicidal properties. Therefore, supercritical CO2 drying could be a valuable alternative nonthermal technique for conventional drying methods, such as air-drying or freeze-drying, when medium to high value-added food products with high initial contamination are involved

Dynamic Spectrum Access: From the Concept to the Implementation

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A Code Tagging Approach to Software Product Line Development:An Application to Satellite Communication Libraries

International audienceSoftware product line engineering seeks to systematise reuse when developing families of similar software systems so as to minimise development time, cost and defects. To realise variability at the code level, product line methods classically advocate usage of inheritance, components, frameworks, aspects or generative techniques. However, these might require unaffordable paradigm shifts for developers if the software was not thought at the outset as a product line. Furthermore, these techniques can be conflicting with a company's coding practices or external regulations. These concerns were the motivation for the industry- university collaboration described in this paper in which we developed a minimally intrusive coding technique based on tags. The approach was complemented with traceability from code to feature diagrams which were exploited for automated configuration. It is supported by a toolchain and is now in use in the partner company for the development of flight grade satellite communica- tion software libraries

A Blind Beam Tracking Scheme for Millimeter Wave Systems

Millimeter-wave is one of the technologies powering the new generation of wireless communication systems. To compensate the high path-loss, millimeter-wave devices need to use highly directional antennas. Consequently, beam misalignment causes strong performance degradation reducing the link throughput or even provoking a complete outage. Conventional solutions, e.g. IEEE 802.11ad, propose the usage of additional training sequences to track beam misalignment. These methods however introduce significant overhead especially in dynamic scenarios. In this paper we propose a beamforming scheme that can reduce this overhead. First, we propose an algorithm to design a codebook suitable for mobile scenarios. Secondly, we propose a blind beam tracking algorithm based on particle filter, which describes the angular position of the devices with a posterior density function constructed by particles. The proposed scheme reduces by more than 80% the overhead caused by additional training sequences.Comment: 6 pages, 7 figure

Indoor person identification using a low-power FMCW radar

Contemporary surveillance systems mainly use video cameras as their primary sensor. However, video cameras possess fundamental deficiencies, such as the inability to handle low-light environments, poor weather conditions, and concealing clothing. In contrast, radar devices are able to sense in pitchdark environments and to see through walls. In this paper, we investigate the use of micro-Doppler (MD) signatures retrieved from a low-power radar device to identify a set of persons based on their gait characteristics. To that end, we propose a robust feature learning approach based on deep convolutional neural networks. Given that we aim at providing a solution for a real-world problem, people are allowed to walk around freely in two different rooms. In this setting, the IDentification with Radar data data set is constructed and published, consisting of 150 min of annotated MD data equally spread over five targets. Through experiments, we investigate the effectiveness of both the Doppler and time dimension, showing that our approach achieves a classification error rate of 24.70% on the validation set and 21.54% on the test set for the five targets used. When experimenting with larger time windows, we are able to further lower the error rate

Smart antennas: state of the art

Aim of this contribution is to illustrate the state of the art of smart antenna research from several perspectives. The bow is drawn from transmitter issues via channel measurements and modeling, receiver signal processing, network aspects, technological challenges towards first smart antenna applications and current status of standardization. Moreover, some future prospects of different disciplines in smart antenna research are given.Peer Reviewe

Fusing Event-based Camera and Radar for SLAM Using Spiking Neural Networks with Continual STDP Learning

This work proposes a first-of-its-kind SLAM architecture fusing an event-based camera and a Frequency Modulated Continuous Wave (FMCW) radar for drone navigation. Each sensor is processed by a bio-inspired Spiking Neural Network (SNN) with continual Spike-Timing-Dependent Plasticity (STDP) learning, as observed in the brain. In contrast to most learning-based SLAM systems%, which a) require the acquisition of a representative dataset of the environment in which navigation must be performed and b) require an off-line training phase, our method does not require any offline training phase, but rather the SNN continuously learns features from the input data on the fly via STDP. At the same time, the SNN outputs are used as feature descriptors for loop closure detection and map correction. We conduct numerous experiments to benchmark our system against state-of-the-art RGB methods and we demonstrate the robustness of our DVS-Radar SLAM approach under strong lighting variations