On the efficiency and sensitivity of a pyramidal classification algorithm

In this paper we propose a Pyramidal Classification Algorithm,which together with an appropriate aggregation index producesan indexed pseudo-hierarchy (in the strict sense) withoutinversions nor crossings. The computer implementation of thealgorithm makes it possible to carry out some simulation testsby Monte Carlo methods in order to study the efficiency andsensitivity of the pyramidal methods of the Maximum, Minimumand UPGMA. The results shown in this paper may help to choosebetween the three classification methods proposed, in order toobtain the classification that best fits the original structureof the population, provided we have an a priori informationconcerning this structure.

La chaîne des secours: le modèle vaudois [An efficient example of a Swiss pre-hospital chain of survival: the state of Vaud model].

The state of Vaud model of the pre-hospital chain of survival is an example of an efficient way to deal with pre-hospital emergencies. It revolves around a centrally located dispatch center managing emergencies according to specific key words, allowing dispatchers to send out resources among which we find general practitioners, ambulances, physician staffed fast response cars or physician staffed helicopters and specific equipment. The Vaud pre-hospital chain of survival has been tailored according to geographical, demographical and political necessities. It undergoes constant reassessment and needs continuous adaptations to the ever changing demographics and epidemiology of pre-hospital medicine.

Highly efficient DNA incorporation of intratumourally injected [125I]iododeoxyuridine under thymidine synthesis blocking in human glioblastoma xenografts.

Intratumoural (i.t.) injection of radio-iododeoxyuridine (IdUrd), a thymidine (dThd) analogue, is envisaged for targeted Auger electron- or beta-radiation therapy of glioblastoma. Here, biodistribution of [(125)I]IdUrd was evaluated 5 hr after i.t. injection in subcutaneous human glioblastoma xenografts LN229 after different intravenous (i.v.) pretreatments with fluorodeoxyuridine (FdUrd). FdUrd is known to block de novo dThd synthesis, thus favouring DNA incorporation of radio-IdUrd. Results showed that pretreatment with 2 mg/kg FdUrd i.v. in 2 fractions 0.5 hr and 1 hr before injection of radio-IdUrd resulted in a mean tumour uptake of 19.8% of injected dose (% ID), representing 65.3% ID/g for tumours of approx. 0.35 g. Tumour uptake of radio-IdUrd in non-pretreated mice was only 4.1% ID. Very low uptake was observed in normal nondividing and dividing tissues with a maximum concentration of 2.9% ID/g measured in spleen. Pretreatment with a higher dose of FdUrd of 10 mg/kg prolonged the increased tumour uptake of radio-IdUrd up to 5 hr. A competition experiment was performed in FdUrd pretreated mice using i.t. co-injection of excess dThd that resulted in very low tumour retention of [(125)I]IdUrd. DNA isolation experiments showed that in the mean >95% of tumour (125)I activity was incorporated in DNA. In conclusion, these results show that close to 20% ID of radio-IdUrd injected i.t. was incorporated in tumour DNA after i.v. pretreatment with clinically relevant doses of FdUrd and that this approach may be further exploited for diffusion and therapy studies with Auger electron- and/or beta-radiation-emitting radio-IdUrd.

Implementing TURF analysis through binary linear programming

This paper introduces the approach of using Total Unduplicated Reach and Frequency analysis (TURF) to design a product line through a binary linear programming model. This improves the efficiency of the search for the solution to the problem compared to the algorithms that have been used to date. The results obtained through our exact algorithm are presented, and this method shows to be extremely efficient both in obtaining optimal solutions and in computing time for very large instances of the problem at hand. Furthermore, the proposed technique enables the model to be improved in order to overcome the main drawbacks presented by TURF analysis in practice.

A simple randomized algorithm for consistent sequential prediction of ergodic time series

We present a simple randomized procedure for the prediction of a binary sequence. The algorithm uses ideas from recent developments of the theory of the prediction of individual sequences. We show that if thesequence is a realization of a stationary and ergodic random process then the average number of mistakes converges, almost surely, to that of the optimum, given by the Bayes predictor.

iLOGP: A Simple, Robust, and Efficient Description of n-Octanol/Water Partition Coefficient for Drug Design Using the GB/SA Approach.

The n-octanol/water partition coefficient (log Po/w) is a key physicochemical parameter for drug discovery, design, and development. Here, we present a physics-based approach that shows a strong linear correlation between the computed solvation free energy in implicit solvents and the experimental log Po/w on a cleansed data set of more than 17,500 molecules. After internal validation by five-fold cross-validation and data randomization, the predictive power of the most interesting multiple linear model, based on two GB/SA parameters solely, was tested on two different external sets of molecules. On the Martel druglike test set, the predictive power of the best model (N = 706, r = 0.64, MAE = 1.18, and RMSE = 1.40) is similar to six well-established empirical methods. On the 17-drug test set, our model outperformed all compared empirical methodologies (N = 17, r = 0.94, MAE = 0.38, and RMSE = 0.52). The physical basis of our original GB/SA approach together with its predictive capacity, computational efficiency (1 to 2 s per molecule), and tridimensional molecular graphics capability lay the foundations for a promising predictor, the implicit log P method (iLOGP), to complement the portfolio of drug design tools developed and provided by the SIB Swiss Institute of Bioinformatics.

A retail benchmarking approach to efficient two-way access pricing

We study a retail benchmarking approach to determine access prices for interconnected networks. Instead of considering fixed access charges as in the existing literature, we study access pricing rules that determine the access price that network i pays to network j as a linear function of the marginal costs and the retail prices set by both networks. In the case of competition in linear prices, we show that there is a unique linear rule that implements the Ramsey outcome as the unique equilibrium, independently of the underlying demand conditions. In the case of competition in two-part tariffs, we consider a class of access pricing rules, similar to the optimal one under linear prices but based on average retail prices. We show that firms choose the variable price equal to the marginal cost under this class of rules. Therefore, the regulator (or the competition authority) can choose one among the rules to pursue additional objectives such as consumer surplus, network coverage or investment: for instance, we show that both static and dynamic e±ciency can be achieved at the same time.

Why are some Spanish regions so much more efficient than others?

This article investigates the main sources of heterogeneity in regional efficiency. We estimate a translog stochastic frontier production function in the analysis of Spanish regions in the period 1964-1996, to attempt to measure and explain changes in technical efficiency. Our results confirm that regional inefficiency is significantly and positively correlated with the ratio of public capital to private capital. The proportion of service industries in the private capital, the proportion of public capital devoted to transport infrastructures, the industrial specialization, and spatial spillovers from transport infrastructures in neighbouring regions significantly contributed to improve regional efficiency.

Insurance with frequent trading: A dynamic analysis of efficient insurance markets

This paper extends existing insurance results on the type of insurance contracts needed for insurance market efficiency toa dynamic setting. It introduces continuosly open markets that allow for more efficient asset allocation. It alsoeliminates the role of preferences and endowments in the classification of risks, which is done primarily in terms of the actuarial properties of the underlying riskprocess. The paper further extends insurability to include correlated and catstrophic events. Under these very general conditions the paper defines a condition that determines whether a small number of standard insurance contracts (together with aggregate assets) suffice to complete markets or one needs to introduce such assets as mutual insurance.

MSISpIC: A Probabilistic Scan Matching Algorithm Using a Mechanical Scanned Imaging Sonar

This paper compares two well known scan matching algorithms: the MbICP and the pIC. As a result of the study, it is proposed the MSISpIC, a probabilistic scan matching algorithm for the localization of an Autonomous Underwater Vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), and the robot displacement estimated through dead-reckoning with the help of a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). The proposed method is an extension of the pIC algorithm. Its major contribution consists in: 1) using an EKF to estimate the local path traveled by the robot while grabbing the scan as well as its uncertainty and 2) proposing a method to group into a unique scan, with a convenient uncertainty model, all the data grabbed along the path described by the robot. The algorithm has been tested on an AUV guided along a 600m path within a marina environment with satisfactory results

Post-detection analysis for grating-based ultra-small angle X-ray scattering.

Until recently, the hard X-ray, phase-sensitive imaging technique called grating interferometry was thought to provide information only in real space. However, by utilizing an alternative approach to data analysis we demonstrated that the angular resolved ultra-small angle X-ray scattering distribution can be retrieved from experimental data. Thus, reciprocal space information is accessible by grating interferometry in addition to real space. Naturally, the quality of the retrieved data strongly depends on the performance of the employed analysis procedure, which involves deconvolution of periodic and noisy data in this context. The aim of this article is to compare several deconvolution algorithms to retrieve the ultra-small angle X-ray scattering distribution in grating interferometry. We quantitatively compare the performance of three deconvolution procedures (i.e., Wiener, iterative Wiener and Lucy-Richardson) in case of realistically modeled, noisy and periodic input data. The simulations showed that the algorithm of Lucy-Richardson is the more reliable and more efficient as a function of the characteristics of the signals in the given context. The availability of a reliable data analysis procedure is essential for future developments in grating interferometry.

Validation of a clinical algorithm to identify low-risk patients with pulmonary embolism.

Summary Background: We previously derived a clinical prognostic algorithm to identify patients with pulmonary embolism (PE) who are at low-risk of short-term mortality who could be safely discharged early or treated entirely in an outpatient setting. Objectives: To externally validate the clinical prognostic algorithm in an independent patient sample. Methods: We validated the algorithm in 983 consecutive patients prospectively diagnosed with PE at an emergency department of a university hospital. Patients with none of the algorithm's 10 prognostic variables (age >/= 70 years, cancer, heart failure, chronic lung disease, chronic renal disease, cerebrovascular disease, pulse >/= 110/min., systolic blood pressure < 100 mm Hg, oxygen saturation < 90%, and altered mental status) at baseline were defined as low-risk. We compared 30-day overall mortality among low-risk patients based on the algorithm between the validation and the original derivation sample. We also assessed the rate of PE-related and bleeding-related mortality among low-risk patients. Results: Overall, the algorithm classified 16.3% of patients with PE as low-risk. Mortality at 30 days was 1.9% among low-risk patients and did not differ between the validation and the original derivation sample. Among low-risk patients, only 0.6% died from definite or possible PE, and 0% died from bleeding. Conclusions: This study validates an easy-to-use, clinical prognostic algorithm for PE that accurately identifies patients with PE who are at low-risk of short-term mortality. Low-risk patients based on our algorithm are potential candidates for less costly outpatient treatment.

Efficient T cell activation requires an optimal dwell-time of interaction between the TCR and the pMHC complex.

Cytotoxic T cell (CTL) activation by antigen requires the specific detection of peptide-major histocompatibility class I (pMHC) molecules on the target-cell surface by the T cell receptor (TCR). We examined the effect of mutations in the antigen-binding site of a Kb-restricted TCR on T cell activation, antigen binding and dissociation from antigen.These parameters were also examined for variants derived from a Kd-restricted peptide that was recognized by a CTL clone. Using these two independent systems, we show that T cell activation can be impaired by mutations that either decrease or increase the binding half-life of the TCR-pMHC interaction. Our data indicate that efficient T cell activation occurs within an optimal dwell-time range of TCR-pMHC interaction. This restricted dwell-time range is consistent with the exclusion of either extremely low or high affinity T cells from the expanded population during immune responses.

Saponins from the Spanish saffron Crocus sativus are efficient adjuvants for protein-based vaccines.

Protein and peptide-based vaccines provide rigorously formulated antigens. However, these purified products are only weakly immunogenic by themselves and therefore require the addition of immunostimulatory components or adjuvants in the vaccine formulation. Various compounds derived from pathogens, minerals or plants, possess pro-inflammatory properties which allow them to act as adjuvants and contribute to the induction of an effective immune response. The results presented here demonstrate the adjuvant properties of novel saponins derived from the Spanish saffron Crocus sativus. In vivo immunization studies and tumor protection experiments unambiguously establish the value of saffron saponins as candidate adjuvants. These saponins were indeed able to increase both humoral and cellular immune responses to protein-based vaccines, ultimately providing a significant degree of protection against tumor challenge when administered in combination with a tumor antigen. This preclinical study provides an in depth immunological characterization of a new saponin as a vaccine adjuvant, and encourages its further development for use in vaccine formulations.