Genetic and redox determinants of nitric oxide cytotoxicity in a Salmonella typhimurium model.

Paradoxically, nitric oxide (NO) has been found to exhibit cytotoxic, antiproliferative, or cytoprotective activity under different conditions. We have utilized Salmonella mutants deficient in antioxidant defenses or peptide transport to gain insights into NO actions. Comparison of three NO donor compounds reveals distinct and independent cellular responses associated with specific redox forms of NO. The peroxynitrite (OONO-) generator 3-morpholinosydnonimine hydrochloride mediates oxygen-dependent Salmonella killing, whereas S-nitrosoglutathione (GSNO) causes oxygen-independent cytostasis, and the NO. donor diethylenetriamine-nitric oxide adduct has no antibacterial activity. GSNO has the greatest activity for stationary cells, a characteristic relevant to latent or intracellular pathogens. Moreover, the cytostatic activity of GSNO may best correlate with antiproliferative or antimicrobial effects of NO, which are unassociated with overt cell injury. dpp mutants defective in active dipeptide transport are resistant to GSNO, implicating heterolytic NO+ transfer rather than homolytic NO. release in the mechanism of cytostasis. This transport system may provide a specific pathway for GSNO-mediated signaling in biological systems. The redox state and associated carrier molecules are critical determinants of NO activity.

The SEIQS stochastic epidemic model with external source of infection

This paper deals with a stochastic epidemic model for computer viruses with latent and quarantine periods, and two sources of infection: internal and external. All sojourn times are considered random variables which are assumed to be independent and exponentially distributed. For this model extinction and hazard times are analyzed, giving results for their Laplace transforms and moments. The transient behavior is considered by studying the number of times that computers are susceptible, exposed, infectious and quarantined during a period of time (0, t] and results for their joint and marginal distributions, moments and cross moments are presented. In order to give light this analysis, some numerical examples are showed.

Developing Semantic Rich Internet Applications with the Sm4RIA Extension for OIDE

This paper introduces the Sm4RIA Extension for OIDE, which implements the Sm4RIA approach in OIDE (OOH4RIA Integrated Development Environment). The application, based on the Eclipse framework, supports the design of the Sm4RIA models as well as the model-to-model and model-to-text transformation processes that facilitate the generation of Semantic Rich Internet Applications, i.e., RIA applications capable of sharing data as Linked data and consuming external data from other sources in the same manner. Moreover, the application implements mechanisms for the creation of RIA interfaces from ontologies and the automatic generation of administration interfaces for a previously design application.

Applying model-driven engineering to the development of Rich Internet Applications for Business Intelligence

Business Intelligence (BI) applications have been gradually ported to the Web in search of a global platform for the consumption and publication of data and services. On the Internet, apart from techniques for data/knowledge management, BI Web applications need interfaces with a high level of interoperability (similar to the traditional desktop interfaces) for the visualisation of data/knowledge. In some cases, this has been provided by Rich Internet Applications (RIA). The development of these BI RIAs is a process traditionally performed manually and, given the complexity of the final application, it is a process which might be prone to errors. The application of model-driven engineering techniques can reduce the cost of development and maintenance (in terms of time and resources) of these applications, as they demonstrated by other types of Web applications. In the light of these issues, the paper introduces the Sm4RIA-B methodology, i.e., a model-driven methodology for the development of RIA as BI Web applications. In order to overcome the limitations of RIA regarding knowledge management from the Web, this paper also presents a new RIA platform for BI, called RI@BI, which extends the functionalities of traditional RIAs by means of Semantic Web technologies and B2B techniques. Finally, we evaluate the whole approach on a case study—the development of a social network site for an enterprise project manager.

Learning Probabilistic Features for Robotic Navigation Using Laser Sensors

SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N2), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used.

Model, Metamodel and Topology

This reply to Gash’s (Found Sci 2013) commentary on Nescolarde-Selva and Usó-Doménech (Found Sci 2013) answers the three questions raised and at the same time opens up new questions.

Syntactic and Semantic Relationships in Models of Complex Systems: An Ecological Case

In this paper, the authors extend and generalize the methodology based on the dynamics of systems with the use of differential equations as equations of state, allowing that first order transformed functions not only apply to the primitive or original variables, but also doing so to more complex expressions derived from them, and extending the rules that determine the generation of transformed superior to zero order (variable or primitive). Also, it is demonstrated that for all models of complex reality, there exists a complex model from the syntactic and semantic point of view. The theory is exemplified with a concrete model: MARIOLA model.

A probabilistic assessment of calcium carbonate export and dissolution in the modern ocean

The marine cycle of calcium carbonate (CaCO3) is an important element of the carbon cycle and co-governs the distribution of carbon and alkalinity within the ocean. However, CaCO3 export fluxes and mechanisms governing CaCO3 dissolution are highly uncertain. We present an observationally constrained, probabilistic assessment of the global and regional CaCO3 budgets. Parameters governing pelagic CaCO3 export fluxes and dissolution rates are sampled using a Monte Carlo scheme to construct a 1000-member ensemble with the Bern3D ocean model. Ensemble results are constrained by comparing simulated and observation-based fields of excess dissolved calcium carbonate (TA*). The minerals calcite and aragonite are modelled explicitly and ocean–sediment fluxes are considered. For local dissolution rates, either a strong or a weak dependency on CaCO3 saturation is assumed. In addition, there is the option to have saturation-independent dissolution above the saturation horizon. The median (and 68 % confidence interval) of the constrained model ensemble for global biogenic CaCO3 export is 0.90 (0.72–1.05) Gt C yr−1, that is within the lower half of previously published estimates (0.4–1.8 Gt C yr−1). The spatial pattern of CaCO3 export is broadly consistent with earlier assessments. Export is large in the Southern Ocean, the tropical Indo–Pacific, the northern Pacific and relatively small in the Atlantic. The constrained results are robust across a range of diapycnal mixing coefficients and, thus, ocean circulation strengths. Modelled ocean circulation and transport timescales for the different set-ups were further evaluated with CFC11 and radiocarbon observations. Parameters and mechanisms governing dissolution are hardly constrained by either the TA* data or the current compilation of CaCO3 flux measurements such that model realisations with and without saturation-dependent dissolution achieve skill. We suggest applying saturation-independent dissolution rates in Earth system models to minimise computational costs.

Pulse Pressure magnifies the effect of COMT Val158Met on 15 Year Episodic Memory Trajectories

We investigated whether a physiological marker of cardiovascular health, pulse pressure (PP), and age magnified the effect of the functional COMT Val158Met (rs4680) polymorphism on 15-years cognitive trajectories [episodic memory (EM), visuospatial ability, and semantic memory] using data from 1585 non-demented adults from the Betula study. A multiple-group latent growth curve model was specified to gauge individual differences in change, and average trends therein. The allelic variants showed negligible differences across the cognitive markers in average trends. The older portion of the sample selectively age-magnified the effects of Val158Met on EM changes, resulting in greater decline in Val compared to homozygote Met carriers. This effect was attenuated by statistical control for PP. Further, PP moderated the effects of COMT on 15-years EM trajectories, resulting in greater decline in Val carriers, even after accounting for the confounding effects of sex, education, cardiovascular diseases (diabetes, stroke, and hypertension), and chronological age, controlled for practice gains. The effect was still present after excluding individuals with a history of cardiovascular diseases. The effects of cognitive change were not moderated by any other covariates. This report underscores the importance of addressing synergistic effects in normal cognitive aging, as the addition thereof may place healthy individuals at greater risk for memory decline.

Examining Gender Differences in Writing Skill with Latent Factor Modeling

Thesis (Master's)--University of Washington, 2016-06

Latent class and genetic analysis does not support migraine with aura and migraine without aura as separate entities

Latent class and genetic analyses were used to identify subgroups of migraine sufferers in a community sample of 6,265 Australian twins (55% female) aged 25-36 who had completed an interview based on International Headache Society UHS) criteria. Consistent with prevalence rates from other population-based studies, 703 (20%) female and 250 (9%) male twins satisfied the IHS criteria for migraine without aura (MO), and of these, 432 (13%) female and 166 (6%) male twins satisfied the criteria for migraine with aura (MA) as indicated by visual symptoms. Latent class analysis (LCA) of IHS symptoms identified three major symptomatic classes, representing 1) a mild form of recurrent nonmigrainous headache, 2) a moderately severe form of migraine, typically without visual aura symptoms (although 40% of individuals in this class were positive for aura), and 3) a severe form of migraine typically with visual aura symptoms (although 24% of individuals were negative for aura). Using the LCA classification, many more individuals were considered affected to some degree than when using IHS criteria (35% vs. 13%). Furthermore, genetic model fitting indicated a greater genetic contribution to migraine using the LCA classification (heritability, h(2) =0.40; 95% CI, 0.29-0.46) compared with the IHS classification (h(2)=0.36; 95% CI, 0.22-0.42). Exploratory latent class modeling, fitting up to 10 classes, did not identify classes corresponding to either the IHS MO or MA classification. Our data indicate the existence of a continuum of severity, with MA more severe but not etiologically distinct from MO. In searching for predisposing genes, we should therefore expect to find some genes that may underlie all major recurrent headache subtypes, with modifying genetic or environmental factors that may lead to differential expression of the liability for migraine. (C) 2004 Wiley-Liss, Inc.

Functional-structural plant modelling using a combination of architectural analysis, L-systems and a canonical model of function

This paper presents a new method for producing a functional-structural plant model that simulates response to different growth conditions, yet does not require detailed knowledge of underlying physiology. The example used to present this method is the modelling of the mountain birch tree. This new functional-structural modelling approach is based on linking an L-system representation of the dynamic structure of the plant with a canonical mathematical model of plant function. Growth indicated by the canonical model is allocated to the structural model according to probabilistic growth rules, such as rules for the placement and length of new shoots, which were derived from an analysis of architectural data. The main advantage of the approach is that it is relatively simple compared to the prevalent process-based functional-structural plant models and does not require a detailed understanding of underlying physiological processes, yet it is able to capture important aspects of plant function and adaptability, unlike simple empirical models. This approach, combining canonical modelling, architectural analysis and L-systems, thus fills the important role of providing an intermediate level of abstraction between the two extremes of deeply mechanistic process-based modelling and purely empirical modelling. We also investigated the relative importance of various aspects of this integrated modelling approach by analysing the sensitivity of the standard birch model to a number of variations in its parameters, functions and algorithms. The results show that using light as the sole factor determining the structural location of new growth gives satisfactory results. Including the influence of additional regulating factors made little difference to global characteristics of the emergent architecture. Changing the form of the probability functions and using alternative methods for choosing the sites of new growth also had little effect. (c) 2004 Elsevier B.V. All rights reserved.

Population-based continuous optimization, probabilistic modelling and mean shift

Evolutionary algorithms perform optimization using a population of sample solution points. An interesting development has been to view population-based optimization as the process of evolving an explicit, probabilistic model of the search space. This paper investigates a formal basis for continuous, population-based optimization in terms of a stochastic gradient descent on the Kullback-Leibler divergence between the model probability density and the objective function, represented as an unknown density of assumed form. This leads to an update rule that is related and compared with previous theoretical work, a continuous version of the population-based incremental learning algorithm, and the generalized mean shift clustering framework. Experimental results are presented that demonstrate the dynamics of the new algorithm on a set of simple test problems.

Using BWW model to evaluate building ontologies in CGs formalism

The Bunge-Wand-Weber (BWW) representation model defines ontological constructs for information systems. According to these constructs the completeness and efficiency of a modeling technique can be defined. Ontology plays an essential role in e-commerce. Using or updating an existing ontology and providing tools to solve any semantic conflicts become essential steps before putting a system online. We use conceptual graphs (CGs) to implement ontologies. This paper evaluates CG capabilities using the BWW representation model. It finds out that CGs are ontologically complete according to Wand and Weber definition. Also it finds out that CGs have construct overload and construct redundancy which can undermine the ontological clarity of CGs. This leads us to build a meta-model to avoid some ontological-unclarity problems. We use some of the BWW constructs to build the meta-model. (c) 2004 Elsevier Ltd. All rights reserved.

ICICLE: A semantic-based retrieval system for WWW images

In this paper, we present ICICLE (Image ChainNet and Incremental Clustering Engine), a prototype system that we have developed to efficiently and effectively retrieve WWW images based on image semantics. ICICLE has two distinguishing features. First, it employs a novel image representation model called Weight ChainNet to capture the semantics of the image content. A new formula, called list space model, for computing semantic similarities is also introduced. Second, to speed up retrieval, ICICLE employs an incremental clustering mechanism, ICC (Incremental Clustering on ChainNet), to cluster images with similar semantics into the same partition. Each cluster has a summary representative and all clusters' representatives are further summarized into a balanced and full binary tree structure. We conducted an extensive performance study to evaluate ICICLE. Compared with some recently proposed methods, our results show that ICICLE provides better recall and precision. Our clustering technique ICC facilitates speedy retrieval of images without sacrificing recall and precision significantly.