Polydispersity index from linear viscoelastic data: Unimodal and bimodal linear polymer melts

This article describes a method for determining the polydispersity index Ip2=Mz/Mw of the molecular weight distribution (MWD) of linear polymeric materials from linear viscoelastic data. The method uses the Mellin transform of the relaxation modulus of a simple molecular rheological model. One of the main features of this technique is that it enables interesting MWD information to be obtained directly from dynamic shear experiments. It is not necessary to achieve the relaxation spectrum, so the ill-posed problem is avoided. Furthermore, a determinate shape of the continuous MWD does not have to be assumed in order to obtain the polydispersity index. The technique has been developed to deal with entangled linear polymers, whatever the form of the MWD is. The rheological information required to obtain the polydispersity index is the storage G′(ω) and loss G″(ω) moduli, extending from the terminal zone to the plateau region. The method provides a good agreement between the proposed theoretical approach and the experimental polydispersity indices of several linear polymers for a wide range of average molecular weights and polydispersity indices. It is also applicable to binary blends.

Combination of bevacizumab and 2-weekly pegylated liposomal doxorubicin as first-line therapy for locally recurrent or metastatic breast cancer. A multicenter, single-arm phase II trial (SAKK 24/06).

BACKGROUND: Pegylated liposomal doxorubicin (PLD) and bevacizumab are active agents in the treatment of metastatic breast cancer (MBC). We carried out a multicenter, single-arm phase II trial to evaluate the toxicity and efficacy of PLD and bevacizumab as first-line treatment in MBC patients. METHODS: Bevacizumab (10 mg/kg) and PLD (20 mg/m(2)) were infused on days 1 and 15 of a 4-week cycle for a maximum of six cycles. Thereafter, bevacizumab monotherapy was continued at the same dose until progression or toxicity. The primary objective was safety and tolerability, and the secondary objective was to evaluate efficacy of the combination. RESULTS: Thirty-nine of 43 patients were assessable for the primary end point. Eighteen of 39 patients (46%, 95% confidence interval 30% to 63%) had a grade 3 toxicity. Sixteen (41%) had grade 3 palmar-plantar erythrodysesthesia, one had grade 3 mucositis, and one severe cardiotoxicity. Secondary end point of overall response rate among 43 assessable patients was 21%. CONCLUSIONS: In this nonrandomized single-arm trial, the combination of bimonthly PLD and bevacizumab in locally recurrent and MBC patients demonstrated higher than anticipated toxicity while exhibiting only modest activity. Based on these results, we would not consider this combination for further investigation in this setting.

Comparison between a linear ion trap and a triple quadruple MS in the sensitive detection of large peptides at femtomole amounts on column.

In addition to the importance of sample preparation and extract separation, MS detection is a key factor in the sensitive quantification of large undigested peptides. In this article, a linear ion trap MS (LIT-MS) and a triple quadrupole MS (TQ-MS) have been compared in the detection of large peptides at subnanomolar concentrations. Natural brain natriuretic peptide, C-peptide, substance P and D-Junk-inhibitor peptide, a full D-amino acid therapeutic peptide, were chosen. They were detected by ESI and simultaneous MS(1) and MS(2) acquisitions. With direct peptide infusion, MS(2) spectra revealed that fragmentation was peptide dependent, milder on the LIT-MS and required high collision energies on the TQ-MS to obtain high-intensity product ions. Peptide adsorption on surfaces was overcome and peptide dilutions ranging from 0.1 to 25 nM were injected onto an ultra high-pressure LC system with a 1 mm id analytical column and coupled with the MS instruments. No difference was observed between the two instruments when recording in LC-MS(1) acquisitions. However, in LC-MS(2) acquisitions, a better sensitivity in the detection of large peptides was observed with the LIT-MS. Indeed, with the three longer peptides, the typical fragmentation in the TQ-MS resulted in a dramatic loss of sensitivity (> or = 10x).

Combination of androgen deprivation therapy and radiotherapy for localized prostate cancer in the contemporary era.

Currently, androgen deprivation therapy (ADT) has a well-defined role when administered together with radiotherapy (RT): neo-adjuvant and concurrent combination for intermediate risk-disease and adjuvant therapy for high risk disease. Evidence of this association was generated by randomized trials designed and led approximately 30 years ago; thus the question which arises is how relevant and portable are these data in our current clinical practice? In the present review, we examine the pitfalls of these published randomized controlled trials, their relevance to present daily clinics, where high-dose external beam RT or brachytherapy is applied, as well as the adoption of ADT in patients with concomitant cardiovascular disorders.

Micro-Computer Based Linear Scheduling Application for Highway Construction Project Control, HR-339A, 1995

This report describes a new approach to the problem of scheduling highway construction type projects. The technique can accurately model linear activities and identify the controlling activity path on a linear schedule. Current scheduling practices are unable to accomplish these two tasks with any accuracy for linear activities, leaving planners and manager suspicious of the information they provide. Basic linear scheduling is not a new technique, and many attempts have been made to apply it to various types of work in the past. However, the technique has never been widely used because of the lack of an analytical approach to activity relationships and development of an analytical approach to determining controlling activities. The Linear Scheduling Model (LSM) developed in this report, completes the linear scheduling technique by adding to linear scheduling all of the analytical capabilities, including computer applications, present in CPM scheduling today. The LSM has tremendous potential, and will likely have a significant impact on the way linear construction is scheduled in the future.

A general linear relaxometry model of R1 using imaging data.

PURPOSE: The longitudinal relaxation rate (R1 ) measured in vivo depends on the local microstructural properties of the tissue, such as macromolecular, iron, and water content. Here, we use whole brain multiparametric in vivo data and a general linear relaxometry model to describe the dependence of R1 on these components. We explore a) the validity of having a single fixed set of model coefficients for the whole brain and b) the stability of the model coefficients in a large cohort. METHODS: Maps of magnetization transfer (MT) and effective transverse relaxation rate (R2 *) were used as surrogates for macromolecular and iron content, respectively. Spatial variations in these parameters reflected variations in underlying tissue microstructure. A linear model was applied to the whole brain, including gray/white matter and deep brain structures, to determine the global model coefficients. Synthetic R1 values were then calculated using these coefficients and compared with the measured R1 maps. RESULTS: The model's validity was demonstrated by correspondence between the synthetic and measured R1 values and by high stability of the model coefficients across a large cohort. CONCLUSION: A single set of global coefficients can be used to relate R1 , MT, and R2 * across the whole brain. Our population study demonstrates the robustness and stability of the model. Magn Reson Med, 2014. © 2014 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. Magn Reson Med 73:1309-1314, 2015. © 2014 Wiley Periodicals, Inc.

In vitro combination of human and bovine free secretory component with IgA of various species.

The free form of the secretory component usually associated with secretory IgA can be isolated from human and bovine milk. These free secretory components of different origin combine in vitro with human polymeric myeloma IgA, with mouse myeloma IgA, and with the serum IgA of nine different mammalian species.

Combination of lentivector immunization and low-dose chemotherapy or PD-1/PD-L1 blocking primes self-reactive T cells and induces anti-tumor immunity.

In the last two decades, anti-cancer vaccines have yielded disappointing clinical results despite the fact that high numbers of self/tumor-specific T cells can be elicited in immunized patients. Understanding the reasons behind this lack of efficacy is critical in order to design better treatment regimes. Recombinant lentivectors (rLVs) have been successfully used to induce antigen-specific T cells to foreign or mutated tumor antigens. Here, we show that rLV expressing a murine nonmutated self/tumor antigen efficiently primes large numbers of self/tumor-specific CD8(+) T cells. In spite of the large number of tumor-specific T cells, however, no anti-tumor activity could be measured in a therapeutic setting, in mice vaccinated with rLV. Accumulating evidence shows that, in the presence of malignancies, inhibition of T-cell activity may predominate overstimulation. Analysis of tumor-infiltrating lymphocytes revealed that specific anti-tumor CD8(+) T cells fail to produce cytokines and express high levels of inhibitory receptors such as programmed death (PD)-1. Association of active immunization with chemotherapy or antibodies that block inhibitory pathways often leads to better anti-tumor effects. We show here that combining rLV vaccination with either cyclophosphamide or PD-1 and PD-L1 blocking antibodies enhances rLV vaccination efficacy and improves anti-tumor immunity.

On the tractability of the piecewise-linear approximation for general discrete-choice network revenue management

The choice network revenue management (RM) model incorporates customer purchase behavioras customers purchasing products with certain probabilities that are a function of the offeredassortment of products, and is the appropriate model for airline and hotel network revenuemanagement, dynamic sales of bundles, and dynamic assortment optimization. The underlyingstochastic dynamic program is intractable and even its certainty-equivalence approximation, inthe form of a linear program called Choice Deterministic Linear Program (CDLP) is difficultto solve in most cases. The separation problem for CDLP is NP-complete for MNL with justtwo segments when their consideration sets overlap; the affine approximation of the dynamicprogram is NP-complete for even a single-segment MNL. This is in contrast to the independentclass(perfect-segmentation) case where even the piecewise-linear approximation has been shownto be tractable. In this paper we investigate the piecewise-linear approximation for network RMunder a general discrete-choice model of demand. We show that the gap between the CDLP andthe piecewise-linear bounds is within a factor of at most 2. We then show that the piecewiselinearapproximation is polynomially-time solvable for a fixed consideration set size, bringing itinto the realm of tractability for small consideration sets; small consideration sets are a reasonablemodeling tradeoff in many practical applications. Our solution relies on showing that forany discrete-choice model the separation problem for the linear program of the piecewise-linearapproximation can be solved exactly by a Lagrangian relaxation. We give modeling extensionsand show by numerical experiments the improvements from using piecewise-linear approximationfunctions.

Mitomycin C with continuous fluorouracil or with cisplatin in combination with radiotherapy for locally advanced anal cancer (European Organisation for Research and Treatment of Cancer phase II study 22011-40014).

PURPOSE: To assess the feasibility and activity of radio-chemotherapy with mitomycin C (MMC) and cisplatin (CDDP) in locally advanced squamous cell anal carcinoma with reference to radiotherapy (RT) combined with MMC and fluorouracil (5-FU). PATIENTS AND METHODS: Patients with measurable disease >4 cmN0 or N+ received RT (36Gy+2 week gap+23.4Gy) with either MMC/CDDP or MMC/5-FU (MMC 10mg/m(2) d1 of each sequence; 5-FU 200mg/m(2)/day c.i.v. daily; CDDP 25mg/m(2) weekly). Forty patients/arm were needed to exclude a RECIST objective response rate (ORR), 8 weeks after treatment, of <75% (Fleming 1, alpha=10%, beta=10%). RESULTS: The ORR was 79.5% (31/39) (lower bound confidence interval [CI]: 68.8%) with MMC/5-FU versus 91.9% (34/ 37) (lower bound CI: 82.8%) with MMC/CDDP. In the MMC/5-FU group, two patients (5.1%) discontinued treatment due to toxicity versus 11 (29.7%) in the MMC/CDDP group. Nine grade 3 haematological events occurred with MMC/CDDP versus none with 5-FU/MMC. The rate of other toxicities did not differ. There was no toxic death. Thirty-one patients in the MMC/5-FU arm (79.5%) and 18 in the MMC/CDDP arm (48.6%) were fully compliant with the protocol treatment (p=0.005). CONCLUSIONS: Radio-chemotherapy with MMC/CDDP seems promising as only MMC/CDDP demonstrated enough activity (RECIST ORR >75%) to be tested further in phase III trials; MMC/5-FU did not. MMC/CDDP also had an overall acceptable toxicity profile.

SAT Modulo Linear Arithmetic for Solving Polynomial

Polynomial constraint solving plays a prominent role in several areas of hardware and software analysis and verification, e.g., termination proving, program invariant generation and hybrid system verification, to name a few. In this paper we propose a new method for solving non-linear constraints based on encoding the problem into an SMT problem considering only linear arithmetic. Unlike other existing methods, our method focuses on proving satisfiability of the constraints rather than on proving unsatisfiability, which is more relevant in several applications as we illustrate with several examples. Nevertheless, we also present new techniques based on the analysis of unsatisfiable cores that allow one to efficiently prove unsatisfiability too for a broad class of problems. The power of our approach is demonstrated by means of extensive experiments comparing our prototype with state-of-the-art tools on benchmarks taken both from the academic and the industrial world.

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

A non-linear VAD for noisy environments

This paper deals with non-linear transformations for improving the performance of an entropy-based voice activity detector (VAD). The idea to use a non-linear transformation has already been applied in the field of speech linear prediction, or linear predictive coding (LPC), based on source separation techniques, where a score function is added to classical equations in order to take into account the true distribution of the signal. We explore the possibility of estimating the entropy of frames after calculating its score function, instead of using original frames. We observe that if the signal is clean, the estimated entropy is essentially the same; if the signal is noisy, however, the frames transformed using the score function may give entropy that is different in voiced frames as compared to nonvoiced ones. Experimental evidence is given to show that this fact enables voice activity detection under high noise, where the simple entropy method fails.

Non-Linear and Non-Conventional Speech Processing: Alternative Techniques

This special issue aims to cover some problems related to non-linear and nonconventional speech processing. The origin of this volume is in the ISCA Tutorial and Research Workshop on Non-Linear Speech Processing, NOLISP’09, held at the Universitat de Vic (Catalonia, Spain) on June 25–27, 2009. The series of NOLISP workshops started in 2003 has become a biannual event whose aim is to discuss alternative techniques for speech processing that, in a sense, do not fit into mainstream approaches. A selected choice of papers based on the presentations delivered at NOLISP’09 has given rise to this issue of Cognitive Computation.