Non-ideal monitoring of a qubit state using a quantum tunnelling device

We propose a model for non-ideal monitoring of the state of a coupled quantum dot qubit by a quantum tunnelling device. The non-ideality is modelled using an equivalent measurement circuit. This allows realistically available measurement results to be related to the state of the quantum system (qubit). We present a quantum trajectory that describes the stochastic evolution of the qubit state conditioned by tunnelling events (i.e. current) through the device. We calculate and compare the noise power spectra of the current in an ideal and a non-ideal measurement. The results show that when the two qubit dots are strongly coupled the non-ideal measurement cannot detect the qubit state precisely. The limitation of the ideal model for describing a realistic system maybe estimated from the noise spectra.

Bifurcations in the non-dissipative dynamics of ultra cold atoms

We present the first experimental observation of several bifurcations in a controllable non-linear Hamiltonian system. Dynamics of cold atoms are used to test predictions of non-linear, non-dissipative Hamiltonian dynamics.

Noise in detection of qubit states using a quantum point contact

We present a model for detection of the states of a coupled quantum dots (qubit) by a quantum point contact. Most proposals for measurements of states of quantum systems are idealized. However in a real laboratory the measurements cannot be perfect due to practical devices and circuits. The models using ideal devices are not sufficient for describing the detection information of the states of the quantum systems. Our model therefore includes the extension to a non-ideal measurement device case using an equivalent circuit. We derive a quantum trajectory that describes the stochastic evolution of the state of the system of the qubit and the measuring device. We calculate the noise power spectrum of tunnelling events in an ideal and a non-ideal quantum point contact measurement respectively. We found that, for the strong coupling case it is difficult to obtain information of the quantum processes in the qubit by measurements using a non-ideal quantum point contact. The noise spectra can also be used to estimate the limits of applicability of the ideal model.

A statistical approach to predict the effect of confinement on the detonation velocity of commercial explosives

Commercial explosives behave non-ideally in rock blasting. A direct and convenient measure of non-ideality is the detonation velocity. In this study, an alternative model fitted to experimental unconfined detonation velocity data is proposed and the effect of confinement on the detonation velocity is modelled. Unconfined data of several explosives showing various levels of nonideality were successfully modelled. The effect of confinement on detonation velocity was modelled empirically based on field detonation velocity measurements. Confined detonation velocity is a function of the ideal detonation velocity, unconfined detonation velocity at a given blasthole diameter and rock stiffness. For a given explosive and charge diameter, as confinement increases detonation velocity increases. The confinement model is implemented in a simple engineering based non-ideal detonation model. A number of simulations are carried out and analysed to predict the explosive performance parameters for the adopted blasting conditions.

Adsorption of N-2, Ar, acetone, chloroform and acetone-chloroform mixture on carbon black in the framework of molecular layer structure theory (MLST)

Adsorption of pure nitrogen, argon, acetone, chloroform and acetone-chloroform mixture on graphitized thermal carbon black is considered at sub-critical conditions by means of molecular layer structure theory (MLST). In the present version of the MLST an adsorbed fluid is considered as a sequence of 2D molecular layers, whose Helmholtz free energies are obtained directly from the analysis of experimental adsorption isotherm of pure components. The interaction of the nearest layers is accounted for in the framework of mean field approximation. This approach allows quantitative correlating of experimental nitrogen and argon adsorption isotherm both in the monolayer region and in the range of multi-layer coverage up to 10 molecular layers. In the case of acetone and chloroform the approach also leads to excellent quantitative correlation of adsorption isotherms, while molecular approaches such as the non-local density functional theory (NLDFT) fail to describe those isotherms. We extend our new method to calculate the Helmholtz free energy of an adsorbed mixture using a simple mixing rule, and this allows us to predict mixture adsorption isotherms from pure component adsorption isotherms. The approach, which accounts for the difference in composition in different molecular layers, is tested against the experimental data of acetone-chloroform mixture (non-ideal mixture) adsorption on graphitized thermal carbon black at 50 degrees C. (C) 2005 Elsevier Ltd. All rights reserved.

RNA interference against human papillomavirus oncogenes in cervical cancer cells results in increased sensitivity to cisplatin

Targeted inhibition of oncogenes in tumor cells is a rational approach toward the development of cancer therapies based on RNA interference (RNAi). Tumors caused by human papillomavirus (HPV) infection are an ideal model system for RNAi-based cancer therapies because the oncogenes that cause cervical cancer, E6 and E7, are expressed only in cancerous cells. We investigated whether targeting HPV E6 and E7 oncogenes yields cancer cells more sensitive to chemotherapy by cisplatin, the chemotherapeutic agent currently used for the treatment of advanced cervical cancer. We have designed siRNAs directed against the HPV E6 oncogene that simultaneously targets both E6 and E7, which results in an 80% reduction in E7 protein and reactivation of the p53 pathway. The loss of E6 and E7 resulted in a reduction in cellular viability concurrent with the induction of cellular senescence. Interference was specific in that no effect on HPV-negative cells was observed. We demonstrate that RNAi against E6 and E7 oncogenes enhances the chemotherapeutic effect of cisplatin in HeLa cells. The IC50 for HeLa cells treated with cisplatin was 9.4 mu M, but after the addition of a lentivirus-delivered shRNA against E6, the IC50 was reduced almost 4-fold to 2.4 mu M. We also observed a decrease in E7 expression with a concurrent increase in p53 protein levels upon cotreatment with shRNA and cisplatin over that seen with individual treatment alone. Our results provide strong evidence that loss of E6 and E7 results in increased sensitivity to cisplatin, probably because of increased p53 levels.

Short- and long-term consequences of thermal variation in the larval environment of anurans

To survive adverse or unpredictable conditions in the ontogenetic environment, many organisms retain a level of phenotypic plasticity that allows them to meet the challenges of rapidly changing conditions. Larval anurans are widely known for their ability to modify behaviour, morphology and physiological processes during development, making them an ideal model system for studies of environmental effects on phenotypic traits. Although temperature is one of the most important factors influencing the growth, development and metamorphic condition of larval anurans, many studies have failed to include ecologically relevant thermal fluctuations among their treatments. We compared the growth and age at metamorphosis of striped marsh frogs Limnodynastes peronii raised in a diurnally fluctuating thermal regime and a stable regime of the same mean temperature. We then assessed the long-term effects of the larval environment on the morphology and performance of post-metamorphic frogs. Larval L. peronii from the fluctuating treatment were significantly longer throughout development and metamorphosed about 5 days earlier. Frogs from the fluctuating group metamorphosed at a smaller mass and in poorer condition compared with the stable group, and had proportionally shorter legs. Frogs from the fluctuating group showed greater jumping performance at metamorphosis and less degradation in performance during a 10-week dormancy. Treatment differences in performance could not be explained by whole-animal morphological variation, suggesting improved contractile properties of the muscles in the fluctuating group.

Edge-to-edge matching and its applications - Part I. Application to the simple HCP/BCC system

The edge-to-edge matching crystallographic model has been used to predict all the orientation relationships (OR) between crystals that have simple hexagonal close packed (HCP) and body-centered cubic (BCC) structures. Using the critical values for the interatomic spacing misfit along the matching directions and the cl-value mismatch between matching planes, the model predicted all the four common ORs, namely the Burgers OR, the Potter OR, the Pitsch-Schrader OR and the Rong Dunlop OR, together with the corresponding habit planes. Taking the c(H)/a(H) and a(H)/a(B) ratios as variables, where H and B denote the HCP and BCC structures respectively, the model also predicted the relationship between these variables and the four ORs. These predictions are perfectly consistent with the published experimental results. As was the case in the FCC/BCC system, the edge-to-edge matching model has been shown to be a powerful tool for predicting the crystallographic features of diffusion-controlled phase transformations. (C) 2004 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Non-coding RNAs in the nervous system

Increasing evidence suggests that the development and function of the nervous system is heavily dependent on RNA editing and the intricate spatiotemporal expression of a wide repertoire of non-coding RNAs, including micro RNAs, small nucleolar RNAs and longer non-coding RNAs. Non-coding RNAs may provide the key to understanding the multi-tiered links between neural development, nervous system function, and neurological diseases.

Development of a non-intrusive system to monitor radial pulse wave velocity

Understanding arterial distensibility has shown to be important in the pathogenesis of cardiovascular abnormalities like hypertension. It is also known that arterial pulse wave velocity (PWV) is a measure of the elasticity or stiffness of peripheral arterial blood vessels. However, it generally requires complex instrumentations to have an accurate measurement and not suited for continual monitoring. In this paper, it describes a simple and non-intrusive method to detect the cardiovascular pulse from a human wrist above the radial artery and a fingertip. The main components of this proposed method are a piezoelectric transducer and a photo-plethysmography circuitry. 5 healthy adults (4 male) with age ranging from 25 to 38 years were recruited. The timing consistency of the detected pulsations is first evaluated and compared to that obtained from a commercial electrocardiogram. Furthermore, the derived PWV is then assessed by the predicted values attained from regression equations of two previous similar studies. The results show good correlations (p < 0.05) and similarities for the former and latter respectively. The simplicity and non-invasive nature of the proposed method can be attractive for even younger or badly disturbed patients. Moreover, it can be used for prolonged monitoring for the comfort of the patients.

Customer information system data pre-processing with feature selection techniques for non-technical losses prediction in an electricity market

Non-technical losses (NTL) identification and prediction are important tasks for many utilities. Data from customer information system (CIS) can be used for NTL analysis. However, in order to accurately and efficiently perform NTL analysis, the original data from CIS need to be pre-processed before any detailed NTL analysis can be carried out. In this paper, we propose a feature selection based method for CIS data pre-processing in order to extract the most relevant information for further analysis such as clustering and classifications. By removing irrelevant and redundant features, feature selection is an essential step in data mining process in finding optimal subset of features to improve the quality of result by giving faster time processing, higher accuracy and simpler results with fewer features. Detailed feature selection analysis is presented in the paper. Both time-domain and load shape data are compared based on the accuracy, consistency and statistical dependencies between features.