1,954 research outputs found
A new modulation technique for high data rate low power UWB wireless optical communication in implantable biotelemetry systems
We report on the development of a novel modulation technique for UWB wireless optical communication systems for application in a transcutaneous biotelemetry. The solution, based on the generation of short laser pulses, allows for a high data rate link whilst achieving a significant power reduction (energy per bit) compared to the state-of-the-art. These features make this particularly suitable for emerging biomedical applications such as implantable neural/biosensor systems. The relatively simple architecture consists of a transmitter and receiver that can be integrated in a standard CMOS technology in a compact Silicon footprint. These parts include circuits for bias and drive current generation, conditioning and processing, optimised for low-volt age/low-power operation. Preliminary experimental findings validate the new paradigm and show good agreement with expected results. The complete system achieves a BER less than 10-7, with maximum data rate of 125Mbps and estimated total power consumption of less than 3mW
From byproduct to resource: Fermented apple pomace as beer flavoring
One of the main struggles of the large-scale apple processing industry is pomace disposal. One solution for this problem is to convert this waste into a resource. Apple pomace could be used as a substrate for lactic acid bacteria and could induce the formation of a more complex aroma profile, making this fermented product an innovative aromatizer for alcoholic beverages, such as beer. In this study, for the first time, the effect of lacto-fermented apple pomace addition in beer was evaluated. Three bacterial strains (Lactobacillus rhamnosus 1473 and 1019, and L. casei 2246) were tested for apple pomace fermentation, and L. rhamnosus 1473 was the strain that best modified the aromatic profile. The addition of fermented apple pomace to beer increased the complexity of the aroma profile, demonstrating the potential of this byproduct as an aromatizer in the alcoholic beverage industry
Pseudozyma aphidis bloodstream infection in a patient with aggressive lymphoma and a history of intravenous drug use: Case report and review of the literature
Pseudozyma aphidis is an environmental fungus which causes opportunistic infections in immunocompromised patients. Here we report the case of a 54-year-old, intravenous drug user woman, newly diagnosed to have an aggressive lymphoma, who developed a bloodstream infection caused by P. aphidis treated successfully with amphotericin-B therapy. The precise identification was assessed by sequencing. We propose to consider intravenous drug use as a risk factor for invasive infections due to this environmental yeast
Compilability of Abduction
Abduction is one of the most important forms of reasoning; it has been
successfully applied to several practical problems such as diagnosis. In this
paper we investigate whether the computational complexity of abduction can be
reduced by an appropriate use of preprocessing. This is motivated by the fact
that part of the data of the problem (namely, the set of all possible
assumptions and the theory relating assumptions and manifestations) are often
known before the rest of the problem. In this paper, we show some complexity
results about abduction when compilation is allowed
A study of detecting child pornography on smart phone
© Springer International Publishing AG 2018. Child Pornography is an increasingly visible rising cybercrime in the world today. Over the past decade, with rapid growth in smart phone usage, readily available free Cloud Computing storage, and various mobile communication apps, child pornographers have found a convenient and reliable mobile platform for instantly sharing pictures or videos of children being sexually abused. Within this new paradigm, law enforcement officers are finding that detecting, gathering, and processing evidence for the prosecution of child pornographers is becoming increasingly challenging. Deep learning is a machine learning method that models high-level abstractions in data and extracts hierarchical representations of data by using a deep graph with multiple processing layers. This paper presents a conceptual model of deep learning approach for detecting child pornography within the new paradigm by using log analysis, file name analysis and cell site analysis which investigate text logs of events that have happened in the smart phone at the scene of the crime using physical and logical acquisition to assists law enforcement officers in gathering and processing child pornography evidence for prosecution. In addition, this paper shows an illustrative example of logical and physical acquisition on smart phones using forensics tools
A discussion of possible approaches to the integration of thermochemical storage systems in concentrating solar power plants
One of the most interesting perspectives for the development of concentrated solar power (CSP) is the storage of solar energy on a seasonal basis, intending to exploit the summer solar radiation in excess and use it in the winter months, thus stabilizing the yearly production and increasing the capacity factor of the plant. By using materials subject to reversible chemical reactions, and thus storing the thermal energy in the form of chemical energy, thermochemical storage systems can potentially serve to this purpose. The present work focuses on the identification of possible integration solutions between CSP plants and thermochemical systems for long-term energy storage, particularly for high-temperature systems such as central receiver plants. The analysis is restricted to storage systems potentially compatible with temperatures ranging from 700 to 1000 â—¦C and using gases as heat transfer fluids. On the basis of the solar plant specifications, suitable reactive systems are identified and the process interfaces for the integration of solar plant/storage system/power block are discussed. The main operating conditions of the storage unit are defined for each considered case through process simulation
On the Complexity of Case-Based Planning
We analyze the computational complexity of problems related to case-based
planning: planning when a plan for a similar instance is known, and planning
from a library of plans. We prove that planning from a single case has the same
complexity than generative planning (i.e., planning "from scratch"); using an
extended definition of cases, complexity is reduced if the domain stored in the
case is similar to the one to search plans for. Planning from a library of
cases is shown to have the same complexity. In both cases, the complexity of
planning remains, in the worst case, PSPACE-complete
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