975 resultados para Fast foods
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The Groove Gap Waveguide (GGW) shows a behavior similar to the classical rectangular waveguide (RWG), but it is formed by two pieces which do not require metal contact. This feature suggests the GGW as a suitable alternative to the RGW for mm-wave frequencies, where ensuring the proper metal contact according to the wavelength size results challenging. Nevertheless, there is a lack of effective analysis tools for the complex GGW topology, and assuming a direct equivalence between the RGW and the GGW is too rough, so that dilatory full-wave simulations are required. This work presents a fast analysis method based on transmission line theory, which establishes the proper correspondence between the GGW and the RWG. In addition, below cutoff behavior of the GGW is studied for the first time. Several numerical tests and two manufactured prototypes validate the proposed method, which seems very adequate to optimize future GGW structures.
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Individuals with autism spectrum disorders (ASD) are reported to allocate less spontaneous attention to voices. Here, we investigated how vocal sounds are processed in ASD adults, when those sounds are attended. Participants were asked to react as fast as possible to target stimuli (either voices or strings) while ignoring distracting stimuli. Response times (RTs) were measured. Results showed that, similar to neurotypical (NT) adults, ASD adults were faster to recognize voices compared to strings. Surprisingly, ASD adults had even shorter RTs for voices than the NT adults, suggesting a faster voice recognition process. To investigate the acoustic underpinnings of this effect, we created auditory chimeras that retained only the temporal or the spectral features of voices. For the NT group, no RT advantage was found for the chimeras compared to strings: both sets of features had to be present to observe an RT advantage. However, for the ASD group, shorter RTs were observed for both chimeras. These observations indicate that the previously observed attentional deficit to voices in ASD individuals could be due to a failure to combine acoustic features, even though such features may be well represented at a sensory level.
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Collimated transport of fast electron beam through solid density matter is one of the key issues behind the success of the fast ignition scheme by means of which the required amount of ignition energy can be delivered to the hot spot region of the compressed fuel. Here we report on a hot electron beam collimation scheme in solids by tactfully using the strong magnetic fields generated by an electrical resistivity gradient according to Faraday's law. This was accomplished by appropriately fabricating the targets in such a way that the electron beam is directed to flow in a metal which is embedded in a much lower resistivity and atomic number metal. Experimental results showed guided transport of hot electron beam over hundreds of microns length inside solid density plasma, which were obtained from two experiments examining the scheme for petawatt laser driven hot electron beam while employing various target configurations.
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Fast electron energy spectra have been measured for a range of intensities between 1018 Wcm−2 and 1021 Wcm−2 and for different target materials using electron spectrometers. Several experimental campaigns were conducted on peta watt laser facilities at the Rutherford Appleton Laboratory and Osaka University. In these experimental campaigns, the pulse duration was varied from 0.5 ps to 5 ps. The laser incident angle was also changed from normal incidence to 40° in p-polarized. The results show a reduction from the ponderomotive scaling on fast electrons over 1020 Wcm−2.
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Rapid and specific detection of foodborne bacteria that can cause food spoilage or illness associated to its consumption is an increasingly important task in food industry. Bacterial detection, identification, and classification are generally performed using traditional methods based on biochemical or serological tests and the molecular methods based on DNA or RNA fingerprints. However, these methodologies are expensive, time consuming and laborious. Infrared spectroscopy is a reliable, rapid, and economic technique which could be explored as a tool for bacterial analysis in the food industry. In this thesis it was evaluated the potential of IR spectroscopy to study the bacterial quality of foods. In Chapter 2, it was developed a calibration model that successfully allowed to predict the bacterial concentration of naturally contaminated cooked ham samples kept at refrigeration temperature during 8 days. In this part, it was developed the methodology that allowed the best reproducibility of spectra from bacteria colonies with minimal sample preparation, which was used in the subsequent work. Several attempts trying different resolutions and number of scans in the IR were made. A spectral resolution of 4 cm-1, with 32 scans were the settings that allowed the best results. Subsequently, in Chapter 3, it was made an attempt to identify 22 different foodborne bacterial genera/species using IR spectroscopy coupled with multivariate analysis. The principal component analysis, used as an exploratory technique, allowed to form distinct groups, each one corresponding to a different genus, in most of the cases. Then, a hierarchical cluster analysis was performed to further analyse the group formation and the possibility of distinction between species of the same bacterial genus. It was observed that IR spectroscopy not only is suitable to the distinction of the different genera, but also to differentiate species of the same genus, with the simultaneous use of principal component analysis and cluster analysis techniques. The utilization of IR spectroscopy and multivariate statistical analysis were also investigated in Chapter 4, in order to confirm the presence of Listeria monocytogenes and Salmonella spp. isolated from contaminated foods, after growth in selective medium. This would allow to substitute the traditional biochemical and serological methods that are used to confirm these pathogens and that delay the obtainment of the results up to 2 days. The obtained results allowed the distinction of 3 different Listeria species and the distinction of Salmonella spp. from other bacteria that can be mistaken with them. Finally, in chapter 5, high pressure processing, an emerging methodology that permits to produce microbiologically safe foods and extend their shelf-life, was applied to 12 foodborne bacteria to determine their resistance and the effects of pressure in cells. A treatment of 300 MPa, during 15 minutes at room temperature was applied. Gram-negative bacteria were inactivated to undetectable levels and Gram-positive showed different resistances. Bacillus cereus and Staphylococcus aureus decreased only 2 logs and Listeria innocua decreased about 5 logs. IR spectroscopy was performed in bacterial colonies before and after HPP in order to investigate the alterations of the cellular compounds. It was found that high pressure alters bands assigned to some cellular components as proteins, lipids, oligopolysaccharides, phosphate groups from the cell wall and nucleic acids, suggesting disruption of the cell envelopes. In this work, bacterial quantification and classification, as well as assessment of cellular compounds modification with high pressure processing were successfully performed. Taking this into account, it was showed that IR spectroscopy is a very promising technique to analyse bacteria in a simple and inexpensive manner.
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The algorithm developed uses an octree pyramid in which noise is reduced at the expense of the spatial resolution. At a certain level an unsupervised clustering without spatial connectivity constraints is applied. After the classification, isolated voxels and insignificant regions are removed by assigning them to their neighbours. The spatial resolution is then increased by the downprojection of the regions, level by level. At each level the uncertainty of the boundary voxels is minimised by a dynamic selection and classification of these, using an adaptive 3D filtering. The algorithm is tested using different data sets, including NMR data.
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Increasingly more applications in computer vision employ interest points. Algorithms like SIFT and SURF are all based on partial derivatives of images smoothed with Gaussian filter kemels. These algorithrns are fast and therefore very popular.
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A feature detection system has been developed for real-time identification of lines, circles and people legs from laser range data. A new method sutable for arc/circle detection is proposed: the Inscribed Angle Variance (IAV). Lines are detected using a recursive line fitting method.
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This paper describes in detail the design of a CMOS custom fast Fourier transform (FFT) processor for computing a 256-point complex FFT. The FFT is well-suited for real-time spectrum analysis in instrumentation and measurement applications. The FFT butterfly processor reported here consists of one parallel-parallel multiplier and two adders. It is capable of computing one butterfly computation every 100 ns thus it can compute a 256-point complex FFT in 102.4 μs excluding data input and output processes.
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Thesis (Ph.D.)--University of Washington, 2015
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Many rural-based farm and food businesses are relatively small but successful companies. They face severe constraints in terms of finance, marketing and distribution. However, marketing food by mail order presents the opportunity for these firms to gain access to national or even international markets. The achievement of commercial success requires that these companies become marketing oriented. Thus, the critical issue for these firms is to identify the needs of existing or potential customers. The objectives of the paper are to establish a profile of the characteristics, behaviour and attitudes of mail order customers.
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Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such asMRI has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles to the use of MRI in large-scale studies. In this study we assess the validity of the recently proposed fat–muscle quantitation system (AMRATM Profiler) for the quantification of intra-abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images. Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using sliceOmatic, the current gold-standard, and the AMRATM Profiler based on a non-rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by the two analysis methods, (Pearson correlation r = 0.97, p < 0.001), with the AMRATM Profiler analysis being significantly faster (~3 min) than the conventional sliceOmatic approach (~40 min). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 versus sliceOmatic 4.73 ± 1.75 l, p = 0.97). For the AMRATM Profiler analysis, the intra-observer coefficient of variation was 1.6% for IAAT and 1.1% for ASAT, the inter-observer coefficient of variationwas 1.4%for IAAT and 1.2%for ASAT, the intra-observer correlationwas 0.998 for IAAT and 0.999 for ASAT, and the inter-observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRATM Profiler, opening up the possibility of large-scale human phenotypic studies.
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In order to accelerate computing the convex hull on a set of n points, a heuristic procedure is often applied to reduce the number of points to a set of s points, s ≤ n, which also contains the same hull. We present an algorithm to precondition 2D data with integer coordinates bounded by a box of size p × q before building a 2D convex hull, with three distinct advantages. First, we prove that under the condition min(p, q) ≤ n the algorithm executes in time within O(n); second, no explicit sorting of data is required; and third, the reduced set of s points forms a simple polygonal chain and thus can be directly pipelined into an O(n) time convex hull algorithm. This paper empirically evaluates and quantifies the speed up gained by preconditioning a set of points by a method based on the proposed algorithm before using common convex hull algorithms to build the final hull. A speedup factor of at least four is consistently found from experiments on various datasets when the condition min(p, q) ≤ n holds; the smaller the ratio min(p, q)/n is in the dataset, the greater the speedup factor achieved.
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The principal aim of this study was to investigate the possibility of transference to Escherichia coli of β-lactam resistance genes found in bacteria isolated from ready-to-eat (RTE) Portuguese traditional food. From previous screenings, 128 β-lactam resistant isolates (from different types of cheese and of delicatessen meats), largely from the Enterobacteriaceae family were selected and 31.3% of them proved to transfer resistance determinants in transconjugation assays. Multiplex PCR in donor and transconjugant isolates did not detect bla CTX, bla SHV and bla OXY, but bla TEM was present in 85% of them, while two new TEMs (TEM-179 and TEM-180) were identified in two isolates. The sequencing of these amplicons showed identity between donor and transconjugant genes indicating in vitro plasmid DNA transfer. These results suggest that if there is an exchange of genes in natural conditions, the consumption of RTE foods, particularly with high levels of Enterobacteriaceae, can contribute to the spread of antibiotic resistance.
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Hand-off (or hand-over), the process where mobile nodes select the best access point available to transfer data, has been well studied in wireless networks. The performance of a hand-off process depends on the specific characteristics of the wireless links. In the case of low-power wireless networks, hand-off decisions must be carefully taken by considering the unique properties of inexpensive low-power radios. This paper addresses the design, implementation and evaluation of smart-HOP, a hand-off mechanism tailored for low-power wireless networks. This work has three main contributions. First, it formulates the hard hand-off process for low-power networks (such as typical wireless sensor networks - WSNs) with a probabilistic model, to investigate the impact of the most relevant channel parameters through an analytical approach. Second, it confirms the probabilistic model through simulation and further elaborates on the impact of several hand-off parameters. Third, it fine-tunes the most relevant hand-off parameters via an extended set of experiments, in a realistic experimental scenario. The evaluation shows that smart-HOP performs well in the transitional region while achieving more than 98 percent relative delivery ratio and hand-off delays in the order of a few tens of a milliseconds.