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.

A Canonical Genetic Algorithm for Blind Inversion of Linear Channels

It is well known the relationship between source separation and blind deconvolution: If a filtered version of an unknown i.i.d. signal is observed, temporal independence between samples can be used to retrieve the original signal, in the same manner as spatial independence is used for source separation. In this paper we propose the use of a Genetic Algorithm (GA) to blindly invert linear channels. The use of GA is justified in the case of small number of samples, where other gradient-like methods fails because of poor estimation of statistics.

Evaluation of a polymerase chain reaction-restriction fragment length polymorphism assay for dermatophyte and nondermatophyte identification in onychomycosis.

BACKGROUND: Dermatophytes are the main cause of onychomycoses, but various nondermatophyte filamentous fungi are often isolated from abnormal nails. The correct identification of the aetiological agent of nail infections is necessary in order to recommend appropriate treatment. OBJECTIVE: To evaluate a rapid polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay based on 28S rDNA for fungal identification in nails on a large number of samples in comparison with cultures. METHODS: Infectious fungi were analysed using PCR-RFLP in 410 nail samples in which fungal elements were observed in situ by direct mycological examination (positive samples). The results were compared with those previously obtained by culture of fungi on Sabouraud agar from the same nail samples. RESULTS: PCR-RFLP identification of fungi in nails allowed validation of the results obtained in culture when Trichophyton spp. grew from infected samples. In addition, nondermatophyte filamentous fungi could be identified with certainty as the infectious agents in onychomycosis, and discriminated from dermatophytes as well as from transient contaminants. The specificity of the culture results relative to PCR-RFLP appeared to be 81%, 71%, 52% and 63% when Fusarium spp., Scopulariopsis brevicaulis, Aspergillus spp. and Candida spp., respectively, grew on Sabouraud agar. It was also possible to identify the infectious agent when direct nail mycological examination showed fungal elements, but negative results were obtained from fungal culture. CONCLUSIONS: Improved sensitivity for the detection of fungi in nails was obtained using the PCR-RFLP assay. Rapid and reliable molecular identification of the infectious fungus can be used routinely and presents several important advantages compared with culture in expediting the choice of appropriate antifungal therapy.

A non-linear Bayesian approach for upscaling local-scale hydraulic conductivity measurements based on local- and regional-scale geophysical data

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed an upscaling procedure based on a Bayesian sequential simulation approach. This method is then applied to the stochastic integration of low-resolution, regional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this upscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Quantification of thermotolerant campylobacter in Swiss water treatment plants, by real-time quantitative polymerase chain reaction

A total of 49 wastewater samples from 23 different wastewater treatment plants (WWTPs) were analyzed using real-time quantitative polymerase chain reaction for the presence and quantity of thermotolerant campylobacters. Thermotolerant campylobacters were detected in 87.5% (21/24) and 64% (16/25) of untreated and treated wastewater samples, respectively. Their concentration was sufficiently high to be quantified in 20.4% (10/49) of the samples. In these samples, the concentration ranged from 68 000 to 2292 000 cells/L in untreated wastewater and from 10 800 to 28 000 cells/L in treated water. We conclude that thermotolerant campylobacters present a health hazard for workers at WWTPs in Switzerland. [Authors]

Peptide-antibody conjugates for tumour therapy: a MHC-class-II-restricted tetanus toxin peptide coupled to an anti-Ig light chain antibody can induce cytotoxic lysis of a human B-cell lymphoma by specific CD4 T cells.

Anti-idiotype antibody therapy of B-cell lymphomas, despite numerous promising experimental and clinical studies, has so far met with limited success. Tailor-made monoclonal anti-idiotype antibodies have been injected into a large series of lymphoma patients, with a few impressive complete tumour remissions but a large majority of negative responses. The results presented here suggest that, by coupling to antilymphoma idiotype antibodies a few molecules of the tetanus toxin universal epitope peptide P2 (830-843), one could markedly increase the efficiency of this therapy. We show that after 2-hr incubation with conjugates consisting of the tetanus toxin peptide P2 coupled by an S-S bridge to monoclonal antibodies directed to the lambda light chain of human immunoglobulin, human B-lymphoma cells can be specifically lysed by a CD4 T-lymphocyte clone specific for the P2 peptide. Antibody without peptide did not induce B-cell killing by the CD4 T-lymphocyte clone. The free cysteine-peptide was also able to induce lysis of the B-lymphoma target by the T-lymphocyte clone, but at a molar concentration 500 to 1000 times higher than that of the coupled peptide. Proliferation assays confirmed that the antibody-peptide conjugate was antigenically active at a much lower concentration than the free peptide. They also showed that antibody-peptide conjugates required an intact processing function of the B cell for peptide presentation, which could be selectively inhibited by leupeptin and chloroquine.(ABSTRACT TRUNCATED AT 250 WORDS)

Short-term stability of testosterone and epitestosterone conjugates in urine samples: quantification by liquid chromatography-linear ion trap mass spectrometry.

A simple method using liquid chromatography-linear ion trap mass spectrometry for simultaneous determination of testosterone glucuronide (TG), testosterone sulfate (TS), epitestosterone glucuronide (EG) and epitestosterone sulfate (ES) in urine samples was developed. For validation purposes, a urine containing no detectable amount of TG, TS and EG was selected and fortified with steroid conjugate standards. Quantification was performed using deuterated testosterone conjugates to correct for ion suppression/enhancement during ESI. Assay validation was performed in terms of lower limit of detection (1-3ng/mL), recovery (89-101%), intraday precision (2.0-6.8%), interday precision (3.4-9.6%) and accuracy (101-103%). Application of the method to short-term stability testing of urine samples at temperature ranging from 4 to 37 degrees C during a time-storage of a week lead to the conclusion that addition of sodium azide (10mg/mL) is required for preservation of the analytes.

Simulating maize phenology as a function of air temperature with a linear and a nonlinear model

The objective of this study was to adapt a nonlinear model (Wang and Engel - WE) for simulating the phenology of maize (Zea mays L.), and to evaluate this model and a linear one (thermal time), in order to predict developmental stages of a field-grown maize variety. A field experiment, during 2005/2006 and 2006/2007 was conducted in Santa Maria, RS, Brazil, in two growing seasons, with seven sowing dates each. Dates of emergence, silking, and physiological maturity of the maize variety BRS Missões were recorded in six replications in each sowing date. Data collected in 2005/2006 growing season were used to estimate the coefficients of the two models, and data collected in the 2006/2007 growing season were used as independent data set for model evaluations. The nonlinear WE model accurately predicted the date of silking and physiological maturity, and had a lower root mean square error (RMSE) than the linear (thermal time) model. The overall RMSE for silking and physiological maturity was 2.7 and 4.8 days with WE model, and 5.6 and 8.3 days with thermal time model, respectively.

Análise genética de escores de avaliação visual de bovinos com modelos bayesianos de limiar e linear

O objetivo deste trabalho foi comparar as estimativas de parâmetros genéticos obtidas em análises bayesianas uni-característica e bi-característica, em modelo animal linear e de limiar, considerando-se as características categóricas morfológicas de bovinos da raça Nelore. Os dados de musculosidade, estrutura física e conformação foram obtidos entre 2000 e 2005, em 3.864 animais de 13 fazendas participantes do Programa Nelore Brasil. Foram realizadas análises bayesianas uni e bi-características, em modelos de limiar e linear. De modo geral, os modelos de limiar e linear foram eficientes na estimação dos parâmetros genéticos para escores visuais em análises bayesianas uni-características. Nas análises bi-características, observou-se que: com utilização de dados contínuos e categóricos, o modelo de limiar proporcionou estimativas de correlação genética de maior magnitude do que aquelas do modelo linear; e com o uso de dados categóricos, as estimativas de herdabilidade foram semelhantes. A vantagem do modelo linear foi o menor tempo gasto no processamento das análises. Na avaliação genética de animais para escores visuais, o uso do modelo de limiar ou linear não influenciou a classificação dos animais, quanto aos valores genéticos preditos, o que indica que ambos os modelos podem ser utilizados em programas de melhoramento genético.

Knot localization in proteins.

The backbones of proteins form linear chains. In the case of some proteins, these chains can be characterized as forming linear open knots. The knot type of the full chain reveals only limited information about the entanglement of the chain since, for example, subchains of an unknotted protein can form knots and subchains of a knotted protein can form different types of knots than the entire protein. To understand fully the entanglement within the backbone of a given protein, a complete analysis of the knotting within all of the subchains of that protein is necessary. In the present article, we review efforts to characterize the full knotting complexity within individual proteins and present a matrix that conveys information about various aspects of protein knotting. For a given protein, this matrix identifies the precise localization of knotted regions and shows the knot types formed by all subchains. The pattern in the matrix can be considered as a knotting fingerprint of that protein. We observe that knotting fingerprints of distantly related knotted proteins are strongly conserved during evolution and discuss how some characteristic motifs in the knotting fingerprints are related to the structure of the knotted regions and their possible biological role.

GPS to LRM: Integration of Spatial Point Features with Linear Referencing Methods, 2001

Global positioning systems (GPS) offer a cost-effective and efficient method to input and update transportation data. The spatial location of objects provided by GPS is easily integrated into geographic information systems (GIS). The storage, manipulation, and analysis of spatial data are also relatively simple in a GIS. However, many data storage and reporting methods at transportation agencies rely on linear referencing methods (LRMs); consequently, GPS data must be able to link with linear referencing. Unfortunately, the two systems are fundamentally incompatible in the way data are collected, integrated, and manipulated. In order for the spatial data collected using GPS to be integrated into a linear referencing system or shared among LRMs, a number of issues need to be addressed. This report documents and evaluates several of those issues and offers recommendations. In order to evaluate the issues associated with integrating GPS data with a LRM, a pilot study was created. To perform the pilot study, point features, a linear datum, and a spatial representation of a LRM were created for six test roadway segments that were located within the boundaries of the pilot study conducted by the Iowa Department of Transportation linear referencing system project team. Various issues in integrating point features with a LRM or between LRMs are discussed and recommendations provided. The accuracy of the GPS is discussed, including issues such as point features mapping to the wrong segment. Another topic is the loss of spatial information that occurs when a three-dimensional or two-dimensional spatial point feature is converted to a one-dimensional representation on a LRM. Recommendations such as storing point features as spatial objects if necessary or preserving information such as coordinates and elevation are suggested. The lack of spatial accuracy characteristic of most cartography, on which LRM are often based, is another topic discussed. The associated issues include linear and horizontal offset error. The final topic discussed is some of the issues in transferring point feature data between LRMs.