Operator expansion: definition and molecular integral applications

Es defineix l'expansió general d'operadors com una combinació lineal de projectors i s'exposa la seva aplicació generalitzada al càlcul d'integrals moleculars. Com a exemple numèric, es fa l'aplicació al càlcul d'integrals de repulsió electrònica entre quatre funcions de tipus s centrades en punts diferents, i es mostren tant resultats del càlcul com la definició d'escalat respecte a un valor de referència, que facilitarà el procés d'optimització de l'expansió per uns paràmetres arbitraris. Es donen resultats ajustats al valor exacte

Genus-specific kinetoplast-DNA PCR and parasite culture for the diagnosis of localised cutaneous leishmaniasis: applications for clinical trials under field conditions in Brazil

The positivities of two methods for the diagnosis of localised cutaneous leishmaniasis (CL) were estimated in 280 patients enrolled in a clinical trial. The trial was conducted in an endemic area of Leishmania (Viannia) braziliensis and trial participants were patients with skin ulcers and positive leishmanin skin tests. Patients underwent aspirative skin punctures of the ulcerated lesions and lymph nodes for in vitro cultures, which were processed under field conditions at the local health centre. Skin lesion biopsies were tested at a reference laboratory using kinetoplastid DNA (kDNA)-PCR to detect DNA. The median time required to obtain a positive culture from the skin samples was seven days and the contamination rate of the samples was 1.8%. The positivities of the cultures from skin lesions, kDNA-PCR and the combination of the two methods were 78.2% (95% CI: 73-82.6%), 89.3% (95% CI: 85.1-92.4%) and 97.1% (95% CI: 94.5-98.5%). We conclude that parasite culture is a feasible method for the detection of Leishmania in field conditions and that the combination of culture and PCR has a potential role for the diagnosis of CL in candidates for clinical trials.

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Quantified set inversion with applications to control

This paper describes a new reliable method, based on modal interval analysis (MIA) and set inversion (SI) techniques, for the characterization of solution sets defined by quantified constraints satisfaction problems (QCSP) over continuous domains. The presented methodology, called quantified set inversion (QSI), can be used over a wide range of engineering problems involving uncertain nonlinear models. Finally, an application on parameter identification is presented

Error and complexity of random walk Monte Carlo radiosity

The author studies the error and complexity of the discrete random walk Monte Carlo technique for radiosity, using both the shooting and gathering methods. The author shows that the shooting method exhibits a lower complexity than the gathering one, and under some constraints, it has a linear complexity. This is an improvement over a previous result that pointed to an O(n log n) complexity. The author gives and compares three unbiased estimators for each method, and obtains closed forms and bounds for their variances. The author also bounds the expected value of the mean square error (MSE). Some of the results obtained are also shown

Direct analysis of dried blood spots coupled with mass spectrometry: concepts and biomedical applications.

Because of the emergence of dried blood spots (DBS) as an attractive alternative to conventional venous plasma sampling in many pharmaceutical companies and clinical laboratories, different analytical approaches have been developed to enable automated handling of DBS samples without any pretreatment. Associated with selective and sensitive MS-MS detection, these procedures give good results in the rapid identification and quantification of drugs (generally less than 3 min total run time), which is desirable because of the high throughput requirements of analytical laboratories. The objective of this review is to describe the analytical concepts of current direct DBS techniques and to present their advantages and disadvantages, with particular focus on automation capacity and commercial availability. Finally, an overview of the different biomedical applications in which these concepts could be of major interest will be presented.

Convenient synthesis of heterobifunctional poly(ethylene glycol) suitable for the functionalization of iron oxide nanoparticles for biomedical applications.

A straightforward route is proposed for the multi-gram scale synthesis of heterobifunctional poly(ethylene glycol) (PEG) oligomers containing combination of triethyloxysilane extremity for surface modification of metal oxides and amino or azido active end groups for further functionalization. The suitability of these PEG derivatives to be conjugated to nanomaterials was shown by pegylation of ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles (NPs), followed by functionalization with small peptide ligands for biomedical applications.

Applications of stochastic analysis in finance and statistical inference

First: A continuous-time version of Kyle's model (Kyle 1985), known as the Back's model (Back 1992), of asset pricing with asymmetric information, is studied. A larger class of price processes and of noise traders' processes are studied. The price process, as in Kyle's model, is allowed to depend on the path of the market order. The process of the noise traders' is an inhomogeneous Lévy process. Solutions are found by the Hamilton-Jacobi-Bellman equations. With the insider being risk-neutral, the price pressure is constant, and there is no equilibirium in the presence of jumps. If the insider is risk-averse, there is no equilibirium in the presence of either jumps or drifts. Also, it is analised when the release time is unknown. A general relation is established between the problem of finding an equilibrium and of enlargement of filtrations. Random announcement time is random is also considered. In such a case the market is not fully efficient and there exists equilibrium if the sensitivity of prices with respect to the global demand is time decreasing according with the distribution of the random time. Second: Power variations. it is considered, the asymptotic behavior of the power variation of processes of the form _integral_0^t u(s-)dS(s), where S_ is an alpha-stable process with index of stability 0&alpha&2 and the integral is an Itô integral. Stable convergence of corresponding fluctuations is established. These results provide statistical tools to infer the process u from discrete observations. Third: A bond market is studied where short rates r(t) evolve as an integral of g(t-s)sigma(s) with respect to W(ds), where g and sigma are deterministic and W is the stochastic Wiener measure. Processes of this type are particular cases of ambit processes. These processes are in general not of the semimartingale kind.

Applications of a transportable Raman spectrometer for the in situ detection of controlled substances at border controls

A transportable Raman spectrometer was tested for the detection of illicit drugs seized during border controls. In a first step, the analysis methodology was optimized using reference substances such as diacetylmorphine (heroin), cocaine and amphetamine (as powder or liquid forms). Adequate focalisation distance and times of analysis, influence of daylight and artificial light sources, repeatability and limits of detection were studied. In a second step the applications and limitations of the technique to detect the illicit substances in different mixtures and containers was evaluated. Transportable Raman spectroscopy was found to be adequate for a rapid screen of liquids and powders for the detection and identification of controlled substances. Additionally, it had the advantage over other portable techniques, such as ion mobility spectrometry, of being non-destructive and capable of rapid analysis of large quantities of substances through containers such as plastic bags and glass bottles.

The Endocannabinoid System as Pharmacological Target Derived from Its CNS Role in Energy Homeostasis and Reward. Applications in Eating Disorders and Addiction

The endocannabinoid system (ECS) has been implicated in many physiological functions, including the regulation of appetite, food intake and energy balance, a crucial involvement in brain reward systems and a role in psychophysiological homeostasis (anxiety and stress responses). We first introduce this important regulatory system and chronicle what is known concerning the signal transduction pathways activated upon the binding of endogenous cannabinoid ligands to the Gi/0-coupled CB1 cannabinoid receptor, as well as its interactions with other hormones and neuromodulators which can modify endocannabinoid signaling in the brain. Anorexia nervosa (AN) and bulimia nervosa (BN) are severe and disabling psychiatric disorders, characterized by profound eating and weight alterations and body image disturbances. Since endocannabinoids modulate eating behavior, it is plausible that endocannabinoid genes may contribute to the biological vulnerability to these diseases. We present and discuss data suggesting an impaired endocannabinoid signaling in these eating disorders, including association of endocannabinoid components gene polymorphisms and altered CB1-receptor expression in AN and BN. Then we discuss recent findings that may provide new avenues for the identification of therapeutic strategies based on the endocannabinod system. In relation with its implications as a reward-related system, the endocannabinoid system is not only a target for cannabis but it also shows interactions with other drugs of abuse. On the other hand, there may be also a possibility to point to the ECS as a potential target for treatment of drug-abuse and addiction. Within this framework we will focus on enzymatic machinery involved in endocannabinoid inactivation (notably fatty acid amide hydrolase or FAAH) as a particularly interesting potential target. Since a deregulated endocannabinoid system may be also related to depression, anxiety and pain symptomatology accompanying drug-withdrawal states, this is an area of relevance to also explore adjuvant treatments for improving these adverse emotional reactions.

Applications of the hexanic fraction of Agave sisalana Perrine ex Engelm (Asparagaceae): control of inflammation and pain screening

The present study evaluated the anti-inflammatory and analgesic properties of Agave sisalana Perrine in classic models of inflammation and pain. The hexanic fraction of A. sisalana (HFAS) was obtained by acid hydrolysis followed by hexanic reflux. Anti-inflammatory properties were examined in three acute mouse models (xylene ear oedema, hind paw oedema and pleurisy) and a chronic mouse model (granuloma cotton pellet). The antinociceptive potential was evaluated in chemical (acetic-acid) and thermal (tail-flick and hot-plate test) models of pain. When given orally, HFAS (5, 10, 25 and 50 mg/kg) reduced ear oedema (p < 0.0001; 52%, 71%, 62% and 42%, respectively). HFAS also reduced hind paw oedema at doses of 10 mg/kg and 25 mg/kg (p < 0.05; 42% and 58%, respectively) and pleurisy at doses of 10 mg/kg and 25 mg/kg (41% and 50%, respectively). In a chronic model, HFAS reduced inflammation by 46% and 58% at doses of 10 mg/kg and 25 mg/kg, respectively. Moreover, this fraction showed analgesic properties against the abdominal writhing in an acetic acid model (at doses of 5-25 mg/kg) with inhibitory rates of 24%, 54% and 48%. The HFAS also showed an increased latency time in the hot-plate (23% and 28%) and tail-flick tests (61% and 66%) for the 25 mg/kg and 50 mg/kg doses, respectively. These results suggest that HFAS has anti-inflammatory and analgesic properties.

Exploring Cross-layer power management for PGAS applications on the SCC platform

Technological limitations and power constraints are resulting in high-performance parallel computing architectures that are based on large numbers of high-core-count processors. Commercially available processors are now at 8 and 16 cores and experimental platforms, such as the many-core Intel Single-chip Cloud Computer (SCC) platform, provide much higher core counts. These trends are presenting new sets of challenges to HPC applications including programming complexity and the need for extreme energy efficiency.In this work, we first investigate the power behavior of scientific PGAS application kernels on the SCC platform, and explore opportunities and challenges for power management within the PGAS framework. Results obtained via empirical evaluation of Unified Parallel C (UPC) applications on the SCC platform under different constraints, show that, for specific operations, the potential for energy savings in PGAS is large; and power/performance trade-offs can be effectively managed using a cross-layerapproach. We investigate cross-layer power management using PGAS language extensions and runtime mechanisms that manipulate power/performance tradeoffs. Specifically, we present the design, implementation and evaluation of such a middleware for application-aware cross-layer power management of UPC applications on the SCC platform. Finally, based on our observations, we provide a set of recommendations and insights that can be used to support similar power management for PGAS applications on other many-core platforms.