Modelling hydrodynamics in the Rio Parana, Argentina : an evaluation and inter-comparison of reduced-complexity and physics based models applied to a large sand-bed river

Depth-averaged velocities and unit discharges within a 30 km reach of one of the world's largest rivers, the Rio Parana, Argentina, were simulated using three hydrodynamic models with different process representations: a reduced complexity (RC) model that neglects most of the physics governing fluid flow, a two-dimensional model based on the shallow water equations, and a three-dimensional model based on the Reynolds-averaged Navier-Stokes equations. Row characteristics simulated using all three models were compared with data obtained by acoustic Doppler current profiler surveys at four cross sections within the study reach. This analysis demonstrates that, surprisingly, the performance of the RC model is generally equal to, and in some instances better than, that of the physics based models in terms of the statistical agreement between simulated and measured flow properties. In addition, in contrast to previous applications of RC models, the present study demonstrates that the RC model can successfully predict measured flow velocities. The strong performance of the RC model reflects, in part, the simplicity of the depth-averaged mean flow patterns within the study reach and the dominant role of channel-scale topographic features in controlling the flow dynamics. Moreover, the very low water surface slopes that typify large sand-bed rivers enable flow depths to be estimated reliably in the RC model using a simple fixed-lid planar water surface approximation. This approach overcomes a major problem encountered in the application of RC models in environments characterised by shallow flows and steep bed gradients. The RC model is four orders of magnitude faster than the physics based models when performing steady-state hydrodynamic calculations. However, the iterative nature of the RC model calculations implies a reduction in computational efficiency relative to some other RC models. A further implication of this is that, if used to simulate channel morphodynamics, the present RC model may offer only a marginal advantage in terms of computational efficiency over approaches based on the shallow water equations. These observations illustrate the trade off between model realism and efficiency that is a key consideration in RC modelling. Moreover, this outcome highlights a need to rethink the use of RC morphodynamic models in fluvial geomorphology and to move away from existing grid-based approaches, such as the popular cellular automata (CA) models, that remain essentially reductionist in nature. In the case of the world's largest sand-bed rivers, this might be achieved by implementing the RC model outlined here as one element within a hierarchical modelling framework that would enable computationally efficient simulation of the morphodynamics of large rivers over millennial time scales. (C) 2012 Elsevier B.V. All rights reserved.

Establishment and characterization of models of chemotherapy resistance in colorectal cancer: Towards a predictive signature of chemoresistance.

Current standard treatments for metastatic colorectal cancer (CRC) are based on combination regimens with one of the two chemotherapeutic drugs, irinotecan or oxaliplatin. However, drug resistance frequently limits the clinical efficacy of these therapies. In order to gain new insights into mechanisms associated with chemoresistance, and departing from three distinct CRC cell models, we generated a panel of human colorectal cancer cell lines with acquired resistance to either oxaliplatin or irinotecan. We characterized the resistant cell line variants with regards to their drug resistance profile and transcriptome, and matched our results with datasets generated from relevant clinical material to derive putative resistance biomarkers. We found that the chemoresistant cell line variants had distinctive irinotecan- or oxaliplatin-specific resistance profiles, with non-reciprocal cross-resistance. Furthermore, we could identify several new, as well as some previously described, drug resistance-associated genes for each resistant cell line variant. Each chemoresistant cell line variant acquired a unique set of changes that may represent distinct functional subtypes of chemotherapy resistance. In addition, and given the potential implications for selection of subsequent treatment, we also performed an exploratory analysis, in relevant patient cohorts, of the predictive value of each of the specific genes identified in our cellular models.

Growth Models with Exogenous Saving Rates, Unemployment and Wage Inertia

[cat] El propòsit d'aquest article és introduir una mercat de treball no competitiu i atur en el model de creixement amb taxes d'estalvi exògenes que es pot trobar en els llibres de text de creixement (Sala‐i‐Martín, 2000; Barro and Sala‐i‐Martín, 2003; Romer, 2006). Primer, derivem un marc general amb una funció de producció neoclàssica per analitzar la relació entre creixement i ocupació. Utilitzem aquest marc per estudiar les dinàmiques conjuntes del creixement i l'ocupació sota diferents regles de fixació salarial.

Labor Mobility and Productivity Growth

[cat] Els models de creixement amb aprenentatge suposen que el coneixement après en producció es transmet de forma lliure i instantània a tota l'economia. En con- seqüència, l'economia presenta economies d'escala creixents i el creixement de la productivitat (TFP) és endògena. No obstant, el supòsit de difusió instantània del coneixement és poc realista. La difusió del coneixement necessita temps i algun canal de transmissió. En aquest article suposem que el coneixement es transmet amb la contractació de treballadors nous (learning-by-hiring). En el nostre model la difusió instantània i lliure de coneixement pot ocórrer només dins d'un sector. La difusió de coneixement entre sectors pot ocórrer només a través de la mobilitat de treballadors, i per tant, el mercat de treball determina el nivell i la taxa de creixement de productivitat (TFP). Estudiem com els costos de mobilitat laboral modifiquen l'equilibri sota dos escenaris: creixement endogen i exogen. A més, demostrem que d'altres ineficiències del mercat laboral, com són les taxes o els costos de cerca, poden reduir la mobilitat laboral, i per tant, modificar la TFP.

Labor Mobility and Productivity Growth

[cat] Els models de creixement amb aprenentatge suposen que el coneixement après en producció es transmet de forma lliure i instantània a tota l'economia. En con- seqüència, l'economia presenta economies d'escala creixents i el creixement de la productivitat (TFP) és endògena. No obstant, el supòsit de difusió instantània del coneixement és poc realista. La difusió del coneixement necessita temps i algun canal de transmissió. En aquest article suposem que el coneixement es transmet amb la contractació de treballadors nous (learning-by-hiring). En el nostre model la difusió instantània i lliure de coneixement pot ocórrer només dins d'un sector. La difusió de coneixement entre sectors pot ocórrer només a través de la mobilitat de treballadors, i per tant, el mercat de treball determina el nivell i la taxa de creixement de productivitat (TFP). Estudiem com els costos de mobilitat laboral modifiquen l'equilibri sota dos escenaris: creixement endogen i exogen. A més, demostrem que d'altres ineficiències del mercat laboral, com són les taxes o els costos de cerca, poden reduir la mobilitat laboral, i per tant, modificar la TFP.

Growth Models with Exogenous Saving Rates, Unemployment and Wage Inertia

[cat] El propòsit d'aquest article és introduir una mercat de treball no competitiu i atur en el model de creixement amb taxes d'estalvi exògenes que es pot trobar en els llibres de text de creixement (Sala‐i‐Martín, 2000; Barro and Sala‐i‐Martín, 2003; Romer, 2006). Primer, derivem un marc general amb una funció de producció neoclàssica per analitzar la relació entre creixement i ocupació. Utilitzem aquest marc per estudiar les dinàmiques conjuntes del creixement i l'ocupació sota diferents regles de fixació salarial.

Dual activation of pathways regulated by steroid receptors and peptide growth factors in primary prostate cancer revealed by Factor Analysis of microarray data

Background: We use an approach based on Factor Analysis to analyze datasets generated for transcriptional profiling. The method groups samples into biologically relevant categories, and enables the identification of genes and pathways most significantly associated to each phenotypic group, while allowing for the participation of a given gene in more than one cluster. Genes assigned to each cluster are used for the detection of pathways predominantly activated in that cluster by finding statistically significant associated GO terms. We tested the approach with a published dataset of microarray experiments in yeast. Upon validation with the yeast dataset, we applied the technique to a prostate cancer dataset. Results: Two major pathways are shown to be activated in organ-confined, non-metastatic prostate cancer: those regulated by the androgen receptor and by receptor tyrosine kinases. A number of gene markers (HER3, IQGAP2 and POR1) highlighted by the software and related to the later pathway have been validated experimentally a posteriori on independent samples. Conclusion: Using a new microarray analysis tool followed by a posteriori experimental validation of the results, we have confirmed several putative markers of malignancy associated with peptide growth factor signalling in prostate cancer and revealed others, most notably ERRB3 (HER3). Our study suggest that, in primary prostate cancer, HER3, together or not with HER4, rather than in receptor complexes involving HER2, could play an important role in the biology of these tumors. These results provide new evidence for the role of receptor tyrosine kinases in the establishment and progression of prostate cancer.

One, two, or many mechanisms? The brain's processing of complex words

The heated debate over whether there is only a single mechanism or two mechanisms for morphology has diverted valuable research energy away from the more critical questions about the neural computations involved in the comprehension and production of morphologically complex forms. Cognitive neuroscience data implicate many brain areas. All extant models, whether they rely on a connectionist network or espouse two mechanisms, are too underspecified to explain why more than a few brain areas differ in their activity during the processing of regular and irregular forms. No one doubts that the brain treats regular and irregular words differently, but brain data indicate that a simplistic account will not do. It is time for us to search for the critical factors free from theoretical blinders.

Comparative allelopathic potential of metabolites of two Alternanthera species against germination and seedling growth of rice

A laboratory study was conducted to investigate the allelopathic effect of aqueous extracts of plant parts of Alternanthera philoxeroides and A. sessilis and soil incorporated residues on germination and seedling growth of rice (Oryza sativa). Aqueous extracts prepared from different plant parts of Alternanthera species delayed rice germination. Alternanthera philoxeroides and A. sessilis inhibited rice germination by 9-100% and 4-49%, respectively. Germination of rice seeds was reduced with increasing concentration of aqueous leaf extracts of both weed species. Early seedling growth (root and shoot lengths) and seedling vigor index were significantly reduced by 5% aqueous leaf extract compared with distilled water treated control. Germination, root and shoot lengths, root and shoot dry weights and seedling vigor index of rice were drastically reduced by 3 and 4% in residue infested soil compared with residue free soil. The inhibitory effect of A. philoxeroides in terms of germination and seedling growth of rice was greater than that of A. sessilis. Five percent aqueous leaf extract and 4% residue infested soil of A. philoxeroides caused complete failure of rice seed germination. Alternanthera philoxeroides contained water soluble phenolics, namely 4 hydroxy-3-methoxy benzoic acid (16.19 mg L-1) and m-coumaric acid (1.48 mg L-1), whereas Alternanthera sessilis was rich in chlorogenic acid (17.85 mg L-1), gallic acid (11.03 mg L-1) and vanillic acid (9.88 mg L-1). The study indicates that the allelopathic potential of Alternanthera species may play an important role in enhancing the invasiveness of these species and may suppress rice plants in the vicinity.

Food intake and weight of lactating rats maintained on different protein-calorie diets, and pup growth

Studies on rats maintained on low-protein-calorie diets during the lactation period show that food intake decreases. This process results in weight loss and a delay in litter development. The purpose of the present study was to determine the alterations in food intake, maternal weight and litter growth during lactation when dams were exposed to diets with different levels of protein and carbohydrate. Female Wistar rats receiving one of 4 different diets, A (N = 14), B (N = 14), C (N = 9) and D (N = 9), were used. Diet A contained 16% protein and 66% carbohydrate; diet B, 6% protein and 77% carbohydrate; diet C, 6% protein and 66% carbohydrate; diet D, 16% protein and 56% carbohydrate. Thus, C and D diets were hypocaloric, while A and B were isocaloric. The intake of a low-protein diet in groups B and C affected the weight of dams and litters during the last two weeks of lactation, while the low-calorie diets limited the growth of D litters at 21 days compared with A litters, but had no effect on the weight of D dams. Group B showed an increase in intake during the first five days of lactation, resulting in a behavioral calorie compensation due to the increase in carbohydrate content, but the intake decreased during the last part of lactation. Food intake regulation predominantly involves the recruitment of a variety of peripheral satiety systems that attempt to decrease the central feeding command system.

Influence of intrauterine and extrauterine growth on neurodevelopmental outcome of monozygotic twins

There have been indications that intrauterine and early extrauterine growth can influence childhood mental and motor function. The objective of the present study was to evaluate the influence of intrauterine growth restriction and early extrauterine head growth on the neurodevelopmental outcome of monozygotic twins. Thirty-six monozygous twin pairs were evaluated at the corrected age of 12 to 42 months. Intrauterine growth restriction was quantified using the fetal growth ratio. The effects of birth weight ratio, head circumference at birth and current head circumference on mental and motor outcomes were estimated using mixed-effect linear regression models. Separate estimates of the between (interpair) and within (intrapair) effects of each measure on development were thus obtained. Neurodevelopment was assessed with the Bayley Scales of Infant Development, 2nd edition, by a psychologist blind to the exposure. A standardized neurological examination was performed by a neuropediatrician who was unaware of the exposures under investigation. After adjustment, birth weight ratio and head circumference at birth were not associated with motor or mental outcomes. Current head circumference was associated with mental but not with motor outcomes. Only the intrapair twin effect was significant. An increase of 1 cm in current head circumference of one twin compared with the other was associated with 3.2 points higher in Mental Developmental Index (95%CI = 1.06-5.32; P < 0.03). Thus, no effect of intrauterine growth was found on cognition and only postnatal head growth was associated with cognition. This effect was not shared by the co-twin.

Hydraulic and fluvial geomorphological models for a bedrock channel reach of the Twenty Mile Creek /

Bedrock channels have been considered challenging geomorphic settings for the application of numerical models. Bedrock fluvial systems exhibit boundaries that are typically less mobile than alluvial systems, yet they are still dynamic systems with a high degree of spatial and temporal variability. To understand the variability of fluvial systems, numerical models have been developed to quantify flow magnitudes and patterns as the driving force for geomorphic change. Two types of numerical model were assessed for their efficacy in examining the bedrock channel system consisting of a high gradient portion of the Twenty Mile Creek in the Niagara Region of Ontario, Canada. A one-dimensional (1-D) flow model that utilizes energy equations, HEC RAS, was used to determine velocity distributions through the study reach for the mean annual flood (MAF), the 100-year return flood and the 1,000-year return flood. A two-dimensional (2-D) flow model that makes use of Navier-Stokes equations, RMA2, was created with the same objectives. The 2-D modeling effort was not successful due to the spatial complexity of the system (high slope and high variance). The successful 1 -D model runs were further extended using very high resolution geospatial interpolations inherent to the HEC RAS extension, HEC geoRAS. The modeled velocity data then formed the basis for the creation of a geomorphological analysis that focused upon large particles (boulders) and the forces needed to mobilize them. Several existing boulders were examined by collecting detailed measurements to derive three-dimensional physical models for the application of fluid and solid mechanics to predict movement in the study reach. An imaginary unit cuboid (1 metre by 1 metre by 1 metre) boulder was also envisioned to determine the general propensity for the movement of such a boulder through the bedrock system. The efforts and findings of this study provide a standardized means for the assessment of large particle movement in a bedrock fluvial system. Further efforts may expand upon this standardization by modeling differing boulder configurations (platy boulders, etc.) at a high level of resolution.

Aggregations and Marginalization of GARCH and Stochastic Volatility Models

The GARCH and Stochastic Volatility paradigms are often brought into conflict as two competitive views of the appropriate conditional variance concept : conditional variance given past values of the same series or conditional variance given a larger past information (including possibly unobservable state variables). The main thesis of this paper is that, since in general the econometrician has no idea about something like a structural level of disaggregation, a well-written volatility model should be specified in such a way that one is always allowed to reduce the information set without invalidating the model. To this respect, the debate between observable past information (in the GARCH spirit) versus unobservable conditioning information (in the state-space spirit) is irrelevant. In this paper, we stress a square-root autoregressive stochastic volatility (SR-SARV) model which remains true to the GARCH paradigm of ARMA dynamics for squared innovations but weakens the GARCH structure in order to obtain required robustness properties with respect to various kinds of aggregation. It is shown that the lack of robustness of the usual GARCH setting is due to two very restrictive assumptions : perfect linear correlation between squared innovations and conditional variance on the one hand and linear relationship between the conditional variance of the future conditional variance and the squared conditional variance on the other hand. By relaxing these assumptions, thanks to a state-space setting, we obtain aggregation results without renouncing to the conditional variance concept (and related leverage effects), as it is the case for the recently suggested weak GARCH model which gets aggregation results by replacing conditional expectations by linear projections on symmetric past innovations. Moreover, unlike the weak GARCH literature, we are able to define multivariate models, including higher order dynamics and risk premiums (in the spirit of GARCH (p,p) and GARCH in mean) and to derive conditional moment restrictions well suited for statistical inference. Finally, we are able to characterize the exact relationships between our SR-SARV models (including higher order dynamics, leverage effect and in-mean effect), usual GARCH models and continuous time stochastic volatility models, so that previous results about aggregation of weak GARCH and continuous time GARCH modeling can be recovered in our framework.

Drought Climatology of Indo-Gangetic Region of India Using Remote Sensing and Crop Growth Simulation Models

Department of Atmospheric Sciences, Cochin University of Science and Technology