Investigation of the Modified Beam-in-Slab Bridge System, Technical Report, 2004, Vol. 1

Technical Report

Investigation of the Modified Beam-in-Slab Bridge System, Design Guide, 2004, Vol. 3

Design guide

Investigation of the Modified Beam-in-Slab Bridge System, Design Manual, 2004, Vol. 2

Design Manual

Development and validation of AMANDA, a new algorithm for selecting highly relevant regions in Molecular Interaction Fields

Descriptors based on Molecular Interaction Fields (MIF) are highly suitable for drug discovery, but their size (thousands of variables) often limits their application in practice. Here we describe a simple and fast computational method that extracts from a MIF a handful of highly informative points (hot spots) which summarize the most relevant information. The method was specifically developed for drug discovery, is fast, and does not require human supervision, being suitable for its application on very large series of compounds. The quality of the results has been tested by running the method on the ligand structure of a large number of ligand-receptor complexes and then comparing the position of the selected hot spots with actual atoms of the receptor. As an additional test, the hot spots obtained with the novel method were used to obtain GRIND-like molecular descriptors which were compared with the original GRIND. In both cases the results show that the novel method is highly suitable for describing ligand-receptor interactions and compares favorably with other state-of-the-art methods.

A systolic array for linear MIMO detection based on an all-swap lattice reduction algorithm

A systolic array to implement lattice-reduction-aided lineardetection is proposed for a MIMO receiver. The lattice reductionalgorithm and the ensuing linear detections are operated in the same array, which can be hardware-efficient. All-swap lattice reduction algorithm (ASLR) is considered for the systolic design.ASLR is a variant of the LLL algorithm, which processes all lattice basis vectors within one iteration. Lattice-reduction-aided linear detection based on ASLR and LLL algorithms have very similarbit-error-rate performance, while ASLR is more time efficient inthe systolic array, especially for systems with a large number ofantennas.

ILS-ESP An efficient, simple, and parameter-free algorithm for solving the permutation flow-shop problem

From a managerial point of view, the more effcient, simple, and parameter-free (ESP) an algorithm is, the more likely it will be used in practice for solving real-life problems. Following this principle, an ESP algorithm for solving the Permutation Flowshop Sequencing Problem (PFSP) is proposed in this article. Using an Iterated Local Search (ILS) framework, the so-called ILS-ESP algorithm is able to compete in performance with other well-known ILS-based approaches, which are considered among the most effcient algorithms for the PFSP. However, while other similar approaches still employ several parameters that can affect their performance if not properly chosen, our algorithm does not require any particular fine-tuning process since it uses basic "common sense" rules for the local search, perturbation, and acceptance criterion stages of the ILS metaheuristic. Our approach defines a new operator for the ILS perturbation process, a new acceptance criterion based on extremely simple and transparent rules, and a biased randomization process of the initial solution to randomly generate different alternative initial solutions of similar quality -which is attained by applying a biased randomization to a classical PFSP heuristic. This diversification of the initial solution aims at avoiding poorly designed starting points and, thus, allows the methodology to take advantage of current trends in parallel and distributed computing. A set of extensive tests, based on literature benchmarks, has been carried out in order to validate our algorithm and compare it against other approaches. These tests show that our parameter-free algorithm is able to compete with state-of-the-art metaheuristics for the PFSP. Also, the experiments show that, when using parallel computing, it is possible to improve the top ILS-based metaheuristic by just incorporating to it our biased randomization process with a high-quality pseudo-random number generator.

European French-speaking study from the GEMO group on bone metastases management: a special focus on external beam radiotherapy practice survey.

This study seeks to perform a survey of patterns of practice among the different physicians involved in the bone metastases management, with special focus on external beam radiotherapy (EBRT).A questionnaire about bone metastases based on clinical cases and supplemented with general questions, including medical therapies, EBRT and metabolic radiotherapy strategies, surgery, and supportive care approaches, was sent to 4,706 French-speaking physicians in Belgium, France, Luxemburg, and Switzerland.Overall, 644 questionnaires were analyzed. Twenty-eight percent concerned the radiotherapy approach and were judged adequate to respond to the part dedicated to EBRT. Sixty-nine percent of physicians used a total dose irradiation of 30 Gy delivered in ten fractions. A large majority (75%) used two opposed fields prescribed at mid-depth (30%), or with non-equally weighted fields (45%). Seventy percent irradiated also above and below the concerned vertebra. A dosimetry planning treatment was done in 85% and high-energy megavoltage photons were used in 42%. Moreover, 54% physicians used short course radiotherapy in routine.Radiotherapy remains the mainstay of treatment of bone metastases, but there is substantial heterogeneity in clinical practice. Guidelines and treatment protocols are required to improve the treatment quality.

A polynomial algorithm for special case of the one-machine scheduling problem with time-lags

The standard one-machine scheduling problem consists in schedulinga set of jobs in one machine which can handle only one job at atime, minimizing the maximum lateness. Each job is available forprocessing at its release date, requires a known processing timeand after finishing the processing, it is delivery after a certaintime. There also can exists precedence constraints between pairsof jobs, requiring that the first jobs must be completed beforethe second job can start. An extension of this problem consistsin assigning a time interval between the processing of the jobsassociated with the precedence constrains, known by finish-starttime-lags. In presence of this constraints, the problem is NP-hardeven if preemption is allowed. In this work, we consider a specialcase of the one-machine preemption scheduling problem with time-lags, where the time-lags have a chain form, and propose apolynomial algorithm to solve it. The algorithm consist in apolynomial number of calls of the preemption version of the LongestTail Heuristic. One of the applicability of the method is to obtainlower bounds for NP-hard one-machine and job-shop schedulingproblems. We present some computational results of thisapplication, followed by some conclusions.

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.

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.

Whole brain radiotherapy with a conformational external beam radiation boost for lung cancer patients with 1-3 brain metastasis: a multi institutional study.

BACKGROUND: To determine the outcome of patients with brain metastasis (BM) from lung cancer treated with an external beam radiotherapy boost (RTB) after whole brain radiotherapy (WBRT). METHODS: A total of 53 BM patients with lung cancer were treated sequentially with WBRT and RTB between 1996 and 2008 according to our institutional protocol. Mean age was 58.8 years. The median KPS was 90. Median recursive partitioning analysis (RPA) and graded prognostic assessment (GPA) grouping were 2 and 2.5, respectively. Surgery was performed on 38 (71%) patients. The median number of BM was 1 (range, 1-3). Median WBRT and RTB combined dose was 39 Gy (range, 37.5-54). Median follow-up was 12.0 months. RESULTS: During the period of follow-up, 37 (70%) patients died. The median overall survival (OS) was 14.5 months. Only 13 patients failed in the brain. The majority of patients (n = 29) failed distantly. The 1-year OS, -local control, extracranial failure rates were 61.2%, 75.2% and 60.8%, respectively. On univariate analysis, improved OS was found to be significantly associated with total dose (< or = 39 Gy vs. > 39 Gy; p < 0.01), age < 65 (p < 0.01), absence of extracranial metastasis (p < 0.01), GPA > or = 2.5 (p = 0.01), KPS > or = 90 (p = 0.01), and RPA < 2 (p = 0.04). On multivariate analysis, total dose (p < 0.01) and the absence of extracranial metastasis (p = 0.03) retained statistical significance. CONCLUSIONS: The majority of lung cancer patients treated with WBRT and RTB progressed extracranially. There might be a subgroup of younger patients with good performance status and no extracranial disease who may benefit from dose escalation after WBRT to the metastatic site.

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