Magnetic Order in Kondo-Lattice Systems due to Electron-Electron Interactions

The hyperfine interaction between the electron spin and the nuclear spins is one of the main sources of decoherence for spin qubits when the nuclear spins are disordered. An ordering of the latter largely suppresses this source of decoherence. Here we show that such an ordering can occur through a thermodynamic phase transition in two-dimensional (2D) Kondo-lattice type systems. We specifically focus on nuclear spins embedded in a 2D electron gas. The nuclear spins interact with each other through the RKKY interaction, which is carried by the electron gas. We show that a nuclear magnetic order at finite temperature relies on the anomalous behavior of the 2D static electron spin susceptibility due to electron-electron interactions. This provides a connection between low-dimensional magnetism and non-analyticities in interacting 2D electron systems. We discuss the conditions for nuclear magnetism, and show that the associated Curie temperature increases with the electron-electron interactions and may reach up into the millikelvin regime. The further reduction of dimensionality to one dimension is shortly discussed.Comment: Proceedings for 2nd International Workshop on Solid-State Quantum Computing (Taipei, Taiwan, June 2008); 6 pages, 2 figure

Experimental violation of a Bell's inequality in time with weak measurement

The violation of J. Bell's inequality with two entangled and spatially separated quantum two- level systems (TLS) is often considered as the most prominent demonstration that nature does not obey ?local realism?. Under different but related assumptions of "macrorealism", plausible for macroscopic systems, Leggett and Garg derived a similar inequality for a single degree of freedom undergoing coherent oscillations and being measured at successive times. Such a "Bell's inequality in time", which should be violated by a quantum TLS, is tested here. In this work, the TLS is a superconducting quantum circuit whose Rabi oscillations are continuously driven while it is continuously and weakly measured. The time correlations present at the detector output agree with quantum-mechanical predictions and violate the inequality by 5 standard deviations.Comment: 26 pages including 10 figures, preprint forma

A Low Concentration of Ethanol Impairs Learning but Not Motor and Sensory Behavior in Drosophila Larvae

Drosophila melanogaster has proven to be a useful model system for the genetic analysis of ethanol-associated behaviors. However, past studies have focused on the response of the adult fly to large, and often sedating, doses of ethanol. The pharmacological effects of low and moderate quantities of ethanol have remained understudied. In this study, we tested the acute effects of low doses of ethanol (∼7 mM internal concentration) on Drosophila larvae. While ethanol did not affect locomotion or the response to an odorant, we observed that ethanol impaired associative olfactory learning when the heat shock unconditioned stimulus (US) intensity was low but not when the heat shock US intensity was high. We determined that the reduction in learning at low US intensity was not a result of ethanol anesthesia since ethanol-treated larvae responded to the heat shock in the same manner as untreated animals. Instead, low doses of ethanol likely impair the neuronal plasticity that underlies olfactory associative learning. This impairment in learning was reversible indicating that exposure to low doses of ethanol does not leave any long lasting behavioral or physiological effects

Plant disease detection using hyperspectral imaging

Precision agriculture has enabled significant progress in improving yield outcomes for farmers. Recent progress in sensing and perception promises to further enhance the use of precision agriculture by allowing the detection of plant diseases and pests. When coupled with robotics methods for spatial localisation, early detection of plant diseases will al- low farmers to respond in a timely and localised manner to dis- ease outbreaks and limit crop damage. This paper proposes the use of hyperspectral imaging (VNIR and SWIR) and machine learning techniques for the detection of the Tomato Spotted Wilt Virus (TSWV) in capsicum plants. Discriminatory features are extracted using the full spectrum, a variety of vegetation indices, and probabilistic topic models. These features are used to train classifiers for discriminating between leaves obtained from healthy and inoculated plants. The results show excellent discrimination based on the full spectrum and comparable results based on data-driven probabilistic topic models and the domain vegetation indices. Additionally our results show increasing classification performance as the dimensionality of the features increase.</p

Plant disease detection using hyperspectral imaging

Precision agriculture has enabled significant progress in improving yield outcomes for farmers. Recent progress in sensing and perception promises to further enhance the use of precision agriculture by allowing the detection of plant diseases and pests. When coupled with robotics methods for spatial localisation, early detection of plant diseases will allow farmers to respond in a timely and localised manner to disease outbreaks and limit crop damage. This paper proposes the use of hyperspectral imaging (VNIR and SWIR) and machine learning techniques for the detection of the Tomato Spotted Wilt Virus (TSWV) in capsicum plants. Discriminatory features are extracted using the full spectrum, a variety of vegetation indices, and probabilistic topic models. These features are used to train classifiers for discriminating between leaves obtained from healthy and inoculated plants. The results show excellent discrimination based on the full spectrum and comparable results based on data-driven probabilistic topic models and the domain vegetation indices. Additionally our results show increasing classification performance as the dimensionality of the features increase

DIDS (Distributed Intrusion Detection System) - Motivation, Architecture, and An Early Prototype

Intrusion detection is the problem of identifying unauthorized use, misuse, and abuse of computer systems by both system insiders and external penetrators. The proliferation of heterogeneous computer networks provides additional implications for the intrusion detection problem. Namely, the increased connectivity of computer systems gives greater access to outsiders, and makes it easier for intruders to avoid detection. IDS&apos;s are based on the belief that an intruder&apos;s behavior will be noticeably different from that of a legitimate user. We are designing and implementing a prototype Distributed Intrusion Detection System (DIDS) that combines distributed monitoring and data reduction (through individual host and LAN monitors) with centralized data analysis (through the DIDS director) to monitor a heterogeneous network of computers. This approach is unique among current IDS&apos;s. A main problem considered in this paper is the Network -user Identification problem, which is concerned ..

Perdurance of internal ethanol.

<p><b>A</b>. Example standard curve for ethanol gas chromatography. All of the measurements noted in this document fall within the linear range of the gas chromatograph standard curve. <b>B</b>. Chromatographs of ethanol from larvae. Standard responses for known concentrations of ethanol (4.25 mM, 2.13 mM, 1.06 mM, 0.53 mM, and 0.26 mM) diluted in toluene as well as pure toluene are shown. Representative traces from larvae treated for 20 minutes with 20% ethanol (EtOH larvae 1 and 2) or water (control larvae) are also shown. <b>C</b>. The amount of ethanol absorbed by larvae depended on the amount of ethanol in the treatment solution. <b>D</b>. The brief heat shocks (41°C and 35°C) that were used in the conditioning experiments did not reduce internal ethanol below that measured in sham-treated larvae. Animals were treated for 20 minutes with 20% ethanol (Loading Dose) and then taken through the heat shock protocol at 35°C or 41°C as used in conditioning experiments. The loading dose is the same data shown in the panel C 20% bar graph and is repeated for comparison purposes. Sham-treated animals were taken through same protocol except that they did not receive the heat shocks but instead were moved to room temperature (24°C) plates.</p