Optimization of multiclass queueing networks with changeover times via the achievable region method: Part II, the multi-station case

We address the problem of scheduling a multi-station multiclassqueueing network (MQNET) with server changeover times to minimizesteady-state mean job holding costs. We present new lower boundson the best achievable cost that emerge as the values ofmathematical programming problems (linear, semidefinite, andconvex) over relaxed formulations of the system's achievableperformance region. The constraints on achievable performancedefining these formulations are obtained by formulatingsystem's equilibrium relations. Our contributions include: (1) aflow conservation interpretation and closed formulae for theconstraints previously derived by the potential function method;(2) new work decomposition laws for MQNETs; (3) new constraints(linear, convex, and semidefinite) on the performance region offirst and second moments of queue lengths for MQNETs; (4) a fastbound for a MQNET with N customer classes computed in N steps; (5)two heuristic scheduling policies: a priority-index policy, anda policy extracted from the solution of a linear programmingrelaxation.

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.

Comment to "Weak instruments robust tests in GMM and the New Keynesian Phillips curve" by Frank Kleibergen and Sophocles Mavroeidis

I discuss the identifiability of a structural New Keynesian Phillips curve when it is embedded in a small scale dynamic stochastic general equilibrium model. Identification problems emerge because not all the structural parameters are recoverable from the semi-structural ones and because the objective functions I consider are poorly behaved. The solution and the moment mappings are responsible for the problems.

Achievement of at least very good partial response is a simple and robust prognostic factor in patients with multiple myeloma treated with high-dose therapy: long-term analysis of the IFM 99-02 and 99-04 Trials.

PURPOSE: The prognostic impact of complete response (CR) achievement in multiple myeloma (MM) has been shown mostly in the context of autologous stem-cell transplantation. Other levels of response have been defined because, even with high-dose therapy, CR is a relatively rare event. The purpose of this study was to analyze the prognostic impact of very good partial response (VGPR) in patients treated with high-dose therapy. PATIENTS AND METHODS: All patients were included in the Intergroupe Francophone du Myelome 99-02 and 99-04 trials and treated with vincristine, doxorubicin, and dexamethasone (VAD) induction therapy followed by double autologous stem-cell transplantation (ASCT). Best post-ASCT response assessment was available for 802 patients. RESULTS: With a median follow-up of 67 months, median event-free survival (EFS) and 5-year EFS were 42 months and 34%, respectively, for 405 patients who achieved at least VGPR after ASCT versus 32 months and 26% in 288 patients who achieved only partial remission (P = .005). Five-year overall survival (OS) was significantly superior in patients achieving at least VGPR (74% v 61% P = .0017). In multivariate analysis, achievement of less than VGPR was an independent factor predicting shorter EFS and OS. Response to VAD had no impact on EFS and OS. The impact of VGPR achievement on EFS and OS was significant in patients with International Staging System stages 2 to 3 and for patients with poor-risk cytogenetics t(4;14) or del(17p). CONCLUSION: In the context of ASCT, achievement of at least VGPR is a simple prognostic factor that has importance in intermediate and high-risk MM and can be informative in more patients than CR.

Statistical learning theory for geospatial data. Case study: Aral sea

In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).

Structure-function characterization and optimization of a plant-derived antibacterial peptide.

Crushed seeds of the Moringa oleifera tree have been used traditionally as natural flocculants to clarify drinking water. We previously showed that one of the seed peptides mediates both the sedimentation of suspended particles such as bacterial cells and a direct bactericidal activity, raising the possibility that the two activities might be related. In this study, the conformational modeling of the peptide was coupled to a functional analysis of synthetic derivatives. This indicated that partly overlapping structural determinants mediate the sedimentation and antibacterial activities. Sedimentation requires a positively charged, glutamine-rich portion of the peptide that aggregates bacterial cells. The bactericidal activity was localized to a sequence prone to form a helix-loop-helix structural motif. Amino acid substitution showed that the bactericidal activity requires hydrophobic proline residues within the protruding loop. Vital dye staining indicated that treatment with peptides containing this motif results in bacterial membrane damage. Assembly of multiple copies of this structural motif into a branched peptide enhanced antibacterial activity, since low concentrations effectively kill bacteria such as Pseudomonas aeruginosa and Streptococcus pyogenes without displaying a toxic effect on human red blood cells. This study thus identifies a synthetic peptide with potent antibacterial activity against specific human pathogens. It also suggests partly distinct molecular mechanisms for each activity. Sedimentation may result from coupled flocculation and coagulation effects, while the bactericidal activity would require bacterial membrane destabilization by a hydrophobic loop.

ROBETH: un logiciel pour les procédés statistiques robustes [ROBETH: a library for robust statistical procedures].

In the past 20 years the theory of robust estimation has become an important topic of mathematical statistics. We discuss here some basic concepts of this theory with the help of simple examples. Furthermore we describe a subroutine library for the application of robust statistical procedures, which was developed with the support of the Swiss National Science Foundation.

Steady-state equilibrium phase inversion recovery ON-resonant water suppression (IRON) MR angiography in conjunction with superparamagnetic nanoparticles. A robust technique for imaging within a wide range of contrast agent dosages.

PURPOSE: To investigate the ability of inversion recovery ON-resonant water suppression (IRON) in conjunction with P904 (superparamagnetic nanoparticles which consisting of a maghemite core coated with a low-molecular-weight amino-alcohol derivative of glucose) to perform steady-state equilibrium phase MR angiography (MRA) over a wide dose range. MATERIALS AND METHODS: Experiments were approved by the institutional animal care committee. Rabbits (n = 12) were imaged at baseline and serially after the administration of 10 incremental dosages of 0.57-5.7 mgFe/Kg P904. Conventional T1-weighted and IRON MRA were obtained on a clinical 1.5 Tesla (T) scanner to image the thoracic and abdominal aorta, and peripheral vessels. Contrast-to-noise ratios (CNR) and vessel sharpness were quantified. RESULTS: Using IRON MRA, CNR and vessel sharpness progressively increased with incremental dosages of the contrast agent P904, exhibiting constantly higher contrast values than T1 -weighted MRA over a very wide range of contrast agent doses (CNR of 18.8 ± 5.6 for IRON versus 11.1 ± 2.8 for T1 -weighted MRA at 1.71 mgFe/kg, P = 0.02 and 19.8 ± 5.9 for IRON versus -0.8 ± 1.4 for T1-weighted MRA at 3.99 mgFe/kg, P = 0.0002). Similar results were obtained for vessel sharpness in peripheral vessels, (Vessel sharpness of 46.76 ± 6.48% for IRON versus 33.20 ± 3.53% for T1-weighted MRA at 1.71 mgFe/Kg, P = 0.002, and of 48.66 ± 5.50% for IRON versus 19.00 ± 7.41% for T1-weighted MRA at 3.99 mgFe/Kg, P = 0.003). CONCLUSION: Our study suggests that quantitative CNR and vessel sharpness after the injection of P904 are consistently higher for IRON MRA when compared with conventional T1-weighted MRA. These findings apply for a wide range of contrast agent dosages.

Robust volume-targeted balanced steady-state free-precession coronary magnetic resonance angiography in a breathhold at 3.0 Tesla: a reproducibility study.

BACKGROUND: Transient balanced steady-state free-precession (bSSFP) has shown substantial promise for noninvasive assessment of coronary arteries but its utilization at 3.0 T and above has been hampered by susceptibility to field inhomogeneities that degrade image quality. The purpose of this work was to refine, implement, and test a robust, practical single-breathhold bSSFP coronary MRA sequence at 3.0 T and to test the reproducibility of the technique. METHODS: A 3D, volume-targeted, high-resolution bSSFP sequence was implemented. Localized image-based shimming was performed to minimize inhomogeneities of both the static magnetic field and the radio frequency excitation field. Fifteen healthy volunteers and three patients with coronary artery disease underwent examination with the bSSFP sequence (scan time = 20.5 ± 2.0 seconds), and acquisitions were repeated in nine subjects. The images were quantitatively analyzed using a semi-automated software tool, and the repeatability and reproducibility of measurements were determined using regression analysis and intra-class correlation coefficient (ICC), in a blinded manner. RESULTS: The 3D bSSFP sequence provided uniform, high-quality depiction of coronary arteries (n = 20). The average visible vessel length of 100.5 ± 6.3 mm and sharpness of 55 ± 2% compared favorably with earlier reported navigator-gated bSSFP and gradient echo sequences at 3.0 T. Length measurements demonstrated a highly statistically significant degree of inter-observer (r = 0.994, ICC = 0.993), intra-observer (r = 0.894, ICC = 0.896), and inter-scan concordance (r = 0.980, ICC = 0.974). Furthermore, ICC values demonstrated excellent intra-observer, inter-observer, and inter-scan agreement for vessel diameter measurements (ICC = 0.987, 0.976, and 0.961, respectively), and vessel sharpness values (ICC = 0.989, 0.938, and 0.904, respectively). CONCLUSIONS: The 3D bSSFP acquisition, using a state-of-the-art MR scanner equipped with recently available technologies such as multi-transmit, 32-channel cardiac coil, and localized B0 and B1+ shimming, allows accelerated and reproducible multi-segment assessment of the major coronary arteries at 3.0 T in a single breathhold. This rapid sequence may be especially useful for functional imaging of the coronaries where the acquisition time is limited by the stress duration and in cases where low navigator-gating efficiency prohibits acquisition of a free breathing scan in a reasonable time period.

Optimization of centrifugal separation of Ó-lactalbumin and ¿̐ư-lactoglobulin

Selostus: Ó-lactalbumiinin ja ¿̐ư-lactoglobuliinin sentrifugointierotuksen optimointi

Improvement of the quality factor of RF integrated inductors by layout optimization

A systematic method to improve the quality (Q) factor of RF integrated inductors is presented in this paper. The proposed method is based on the layout optimization to minimize the series resistance of the inductor coil, taking into account both ohmic losses, due to conduction currents, and magnetically induced losses, due to eddy currents. The technique is particularly useful when applied to inductors in which the fabrication process includes integration substrate removal. However, it is also applicable to inductors on low-loss substrates. The method optimizes the width of the metal strip for each turn of the inductor coil, leading to a variable strip-width layout. The optimization procedure has been successfully applied to the design of square spiral inductors in a silicon-based multichip-module technology, complemented with silicon micromachining postprocessing. The obtained experimental results corroborate the validity of the proposed method. A Q factor of about 17 have been obtained for a 35-nH inductor at 1.5 GHz, with Q values higher than 40 predicted for a 20-nH inductor working at 3.5 GHz. The latter is up to a 60% better than the best results for a single strip-width inductor working at the same frequency.

Evaluation of sample preparation methods and optimization of nickel determination in vegetable tissues

Nickel, although essential to plants, may be toxic to plants and animals. It is mainly assimilated by food ingestion. However, information about the average levels of elements (including Ni) in edible vegetables from different regions is still scarce in Brazil. The objectives of this study were to: (a) evaluate and optimize a method for preparation of vegetable tissue samples for Ni determination; (b) optimize the analytical procedures for determination by Flame Atomic Absorption Spectrometry (FAAS) and by Electrothermal Atomic Absorption (ETAAS) in vegetable samples and (c) determine the Ni concentration in vegetables consumed in the cities of Lorena and Taubaté in the Vale do Paraíba, State of São Paulo, Brazil. By means of the analytical technique for determination by ETAAS or FAAS, the results were validated by the test of analyte addition and recovery. The most viable method tested for quantification of this element was HClO4-HNO3 wet digestion. All samples but carrot tissue collected in Lorena contained Ni levels above the permitted by the Brazilian Ministry of Health. The most disturbing results, requiring more detailed studies, were the Ni concentrations measured in carrot samples from Taubaté, where levels were five times higher than permitted by Brazilian regulations.

Cross-presenting human gammadelta T cells induce robust CD8+ alphabeta T cell responses.

Gammadelta T cells are implicated in host defense against microbes and tumors but their mode of function remains largely unresolved. Here, we have investigated the ability of activated human Vgamma9Vdelta2(+) T cells (termed gammadelta T-APCs) to cross-present microbial and tumor antigens to CD8(+) alphabeta T cells. Although this process is thought to be mediated best by DCs, adoptive transfer of ex vivo antigen-loaded, human DCs during immunotherapy of cancer patients has shown limited success. We report that gammadelta T-APCs take up and process soluble proteins and induce proliferation, target cell killing and cytokine production responses in antigen-experienced and naïve CD8(+) alphabeta T cells. Induction of APC functions in Vgamma9Vdelta2(+) T cells was accompanied by the up-regulation of costimulatory and MHC class I molecules. In contrast, the functional predominance of the immunoproteasome was a characteristic of gammadelta T cells irrespective of their state of activation. Gammadelta T-APCs were more efficient in antigen cross-presentation than monocyte-derived DCs, which is in contrast to the strong induction of CD4(+) alphabeta T cell responses by both types of APCs. Our study reveals unexpected properties of human gammadelta T-APCs in the induction of CD8(+) alphabeta T effector cells, and justifies their further exploration in immunotherapy research.

Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data.

Microstructure imaging from diffusion magnetic resonance (MR) data represents an invaluable tool to study non-invasively the morphology of tissues and to provide a biological insight into their microstructural organization. In recent years, a variety of biophysical models have been proposed to associate particular patterns observed in the measured signal with specific microstructural properties of the neuronal tissue, such as axon diameter and fiber density. Despite very appealing results showing that the estimated microstructure indices agree very well with histological examinations, existing techniques require computationally very expensive non-linear procedures to fit the models to the data which, in practice, demand the use of powerful computer clusters for large-scale applications. In this work, we present a general framework for Accelerated Microstructure Imaging via Convex Optimization (AMICO) and show how to re-formulate this class of techniques as convenient linear systems which, then, can be efficiently solved using very fast algorithms. We demonstrate this linearization of the fitting problem for two specific models, i.e. ActiveAx and NODDI, providing a very attractive alternative for parameter estimation in those techniques; however, the AMICO framework is general and flexible enough to work also for the wider space of microstructure imaging methods. Results demonstrate that AMICO represents an effective means to accelerate the fit of existing techniques drastically (up to four orders of magnitude faster) while preserving accuracy and precision in the estimated model parameters (correlation above 0.9). We believe that the availability of such ultrafast algorithms will help to accelerate the spread of microstructure imaging to larger cohorts of patients and to study a wider spectrum of neurological disorders.