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Loop-mediated isothermal amplification (LAMP) has gained wide popularity in the detection of Salmonella in foods owing to its simplicity, rapidity, and robustness. This multi-laboratory validation (MLV) study aimed to validate a Salmonella LAMP-based method against the United States Food and Drug Administration (FDA) Bacteriological Analytical Manual (BAM) Chapter 5 Salmonella reference method in a representative animal food matrix (dry dog food). Fourteen independent collaborators from seven laboratories in the United States and Canada participated in the study. Each collaborator received two sets of 24 blind-coded dry dog food samples (eight uninoculated; eight inoculated at a low level, 0.65 MPN/25 g; and eight inoculated at a high level, 3.01 MPN/25 g) and initiated the testing on the same day. The MLV study used an unpaired design where different test portions were analyzed by the LAMP and BAM methods using different preenrichment protocols (buffered peptone water for LAMP and lactose broth for BAM). All LAMP samples were confirmed by culture using the BAM method. BAM samples were also tested by LAMP following lactose broth preenrichment (paired samples). Statistical analysis was carried out by the probability of detection (POD) per AOAC guidelines and by a random intercept logistic regression model. Overall, no significant differences in POD between the Salmonella LAMP and BAM methods were observed with either unpaired or paired samples, indicating the methods were comparable. LAMP testing following preenrichment in buffered peptone water or lactose broth also resulted in insignificant POD differences (P > 0.05). The MLV study strongly supports the utility and applicability of this rapid and reliable LAMP method in routine regulatory screening of Salmonella in animal food.

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We propose a real-time hand gesture interface based on combining a stereo pair of biologically inspired event-based dynamic vision sensor (DVS) silicon retinas with neuromorphic event-driven postprocessing. Compared with conventional vision or 3-D sensors, the use of DVSs, which output asynchronous and sparse events in response to motion, eliminates the need to extract movements from sequences of video frames, and allows significantly faster and more energy-efficient processing. In addition, the rate of input events depends on the observed movements, and thus provides an additional cue for solving the gesture spotting problem, i.e., finding the onsets and offsets of gestures. We propose a postprocessing framework based on spiking neural networks that can process the events received from the DVSs in real time, and provides an architecture for future implementation in neuromorphic hardware devices. The motion trajectories of moving hands are detected by spatiotemporally correlating the stereoscopically verged asynchronous events from the DVSs by using leaky integrate-and-fire (LIF) neurons. Adaptive thresholds of the LIF neurons achieve the segmentation of trajectories, which are then translated into discrete and finite feature vectors. The feature vectors are classified with hidden Markov models, using a separate Gaussian mixture model for spotting irrelevant transition gestures. The disparity information from stereovision is used to adapt LIF neuron parameters to achieve recognition invariant of the distance of the user to the sensor, and also helps to filter out movements in the background of the user. Exploiting the high dynamic range of DVSs, furthermore, allows gesture recognition over a 60-dB range of scene illuminance. The system achieves recognition rates well over 90% under a variety of variable conditions with static and dynamic backgrounds with naïve users.

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We report on the neuromorphic sound localization circuit which can enhance the perceptual sensation in a hearing aid system. All elements are simple leaky integrate-and-fire neuron circuits with different parameters optimized to suppress the impacts of synaptic circuit noises. The detection range and resolution of the proposed neuromorphic circuit are 500 us and 5 us, respectively. Our results show that, the proposed technique can localize a sound pulse with extremely narrow duration (∼ 1 ms) resulting in real-time response.

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We analyze the effect of polarization-dependent loss (PDL) on the performance of the polarization-division-multiplexed (PDM) signals in direct-detection systems. We present the theoretical analysis of the sensitivity penalty caused by PDL-induced coherent crosstalk and compare the results with experimental data obtained by using a simple variable PDL emulator based on a LiNbO3 Mach-Zehnder modulator. Also presented is the performance degradation caused by the polarization misalignment between the received signals and the polarization beam splitter at the receiver in the presence of PDL.

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We demonstrate optical burst add-drop multiplexing as a practical application of the optical burst switching technology in a wavelength-division-multiplexed ring network. To control optical bursts in the network, a burst identifier (BI) for delivering control information, and a BI processor for handling the BI, were designed. Optical bursts of 10- to 100-mus in length were optically multiplexed or demultiplexed in an intermediate node of the ring network. The demonstration shows that the optical burst add-drop multiplexing technique provides sub-wavelength granularity to a ring network.

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We investigate the frequency offset in the frequency stabilization of a semiconductor laser based on a frequency-dithering technique. An analytical model is presented to describe the effects of the amplitude modulation and the phase delay between the amplitude and frequency modulation on the frequency stabilization. We also experimentally and analytically show that the frequency offset could be reduced by using an appropriate phase-sensitive detection.

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We report on the reduction of polarization-induced performance degradation in WDM PON utilizing MQW-SLD-based ASE source for injection locking to FPLD. The results show that, to suppress the polarization-induced Q penalty sufficiently less than 0.5 dB, the MQW-SLD output should be depolarized within the locking range of the wavelength-locked FPLD.

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Used cutting boards with numerous knife marks, particularly those made of polymers, are difficult to disinfect manually. Plastic cutting boards have been preferred to wood because they can be washed in dishwashers and used in microwave ovens. Our study tested the microwave oven for disinfection of cutting boards. Surfaces of plastic and wooden cutting boards were inoculated with up to 109 CFU of Escherichia coli or other bacteria in broth culture and later sampled by contact with agar medium for CFU assay or by swabbing for ATP bioluminescence assay. On wood, almost total elimination of vegetative cells occurred with exposure times of the 3 to 4 min at a high setting on typical 450 to 600 g wooden boards, depending on board size, bacterial load, and moisture level. On plastic, microwave energy had almost no lethal effect on bacteria: 12 min of exposure did not reduce the number of bacteria significantly. Increased moisture (wetness) enhanced killing efficiency on wood, but was negligible on plastic. Temperatures near the wood surface reached 95°C within the first 4 min, whereas plastic surfaces reached no more than 40°C. Our study indicates that brief "cooking" of wooden boards at a "high" setting in a microwave oven is an effective way to kill bacteria, and thus a very simple and cheap method to protect food against cross-contaminating pathogens. Because plastic is relatively inert to microwaves, disinfection of plastic boards in a microwave oven is impractical.