The prediction of chemical reactivity from first principles: Collision and reaction dynamics

Aquest treball fa una revisió de mesures experimentals i càlculs teòrics sobre la dinàmica de col·lisions i reaccions moleculars. Els experiments se centren en col·lisions, a energies intermèdies, que involucren sistemes del tipus ió-àtom i iómolècula, per les quals es mesuren seccions eficaces totals, estat a estat, així com aquelles que discerneixen les diferents contribucions del moment angular d'espín. Els resultats obtinguts s'interpreten satisfactòriament en termes d'acoblaments no adiabàtics entre els diferents estats electrònics dels sistemes col·lisionants. Els càlculs teòrics utilitzen la metodologia quasiclàssica, així com metodologies mecanoquàntiques recentment desenvolupades, tant aproximades com exactes. S'han obtingut resultats totalment convergits per sistemes tipus, mentre que s'han analitzat, de manera detallada i extensiva, les característiques dinàmiques de sistemes triatòmic, tetraatòmic i pentaatòmic.

Diffusion of passive scalars under stochastic convection

The diffusion of passive scalars convected by turbulent flows is addressed here. A practical procedure to obtain stochastic velocity fields with well¿defined energy spectrum functions is also presented. Analytical results are derived, based on the use of stochastic differential equations, where the basic hypothesis involved refers to a rapidly decaying turbulence. These predictions are favorable compared with direct computer simulations of stochastic differential equations containing multiplicative space¿time correlated noise.

State-to-state reaction probabilities within the quantum transition state framework

Rigorous quantum dynamics calculations of reaction rates and initial state-selected reaction probabilities of polyatomic reactions can be efficiently performed within the quantum transition state concept employing flux correlation functions and wave packet propagation utilizing the multi-configurational time-dependent Hartree approach. Here, analytical formulas and a numerical scheme extending this approach to the calculation of state-to-state reaction probabilities are presented. The formulas derived facilitate the use of three different dividing surfaces: two dividing surfaces located in the product and reactant asymptotic region facilitate full state resolution while a third dividing surface placed in the transition state region can be used to define an additional flux operator. The eigenstates of the corresponding thermal flux operator then correspond to vibrational states of the activated complex. Transforming these states to reactant and product coordinates and propagating them into the respective asymptotic region, the full scattering matrix can be obtained. To illustrate the new approach, test calculations study the D + H2(ν, j) → HD(ν′, j′) + H reaction for J = 0.

Morphology and segregation in two-component diffusion-limited aggregation

A diffusion-limited-aggregation (DLA) model with two components (A and B species) is presented to investigate the structure of the composite deposits. The sticking probability PAB (=PBA) between the different species is introduced into the original DLA model. By using computer simulation it is shown that various patterns are produced with varying the sticking probabilities PAB (=PBA) and PAA (= PBB), where PAA (=PBB) is the sticking probability between the same species. Segregated patterns can be analyzed under the condition PAB < PAA, assumed throughout the paper. With decreasing sticking probability PAB, a clustering of the same species occurs. With sufficiently small values of both sticking probabilities PAB and PAA, the deposit becomes dense and the segregated patterns of the composite deposit show a striped structure. The effect of the concentration on the pattern morphology is also shown.

Hepatic hemangiomas: Factors associated with T2 shine-through effect on diffusion-weighted MR sequences.

PURPOSE: To determine the frequency and factors associated with the presence of T2 shine-through effect in hepatic hemangiomas on diffusion-weighted (DW) magnetic resonance (MR) sequences. MATERIALS AND METHODS: This retrospective study was approved by institutional review board with waiver of informed consent. One hundred forty-nine consecutive patients with 388 hepatic hemangiomas who underwent a liver MR between January 2010 and November 2011 were included. MR analysis evaluated the lesion characteristics (signal intensities and enhancement patterns (classical, rapidly filling, delayed filling)), the presence of T2 shine-through effect on DW sequences (b values of 0, 150, and 600s/mm(2)), and apparent diffusion coefficient (ADC) values. Multivariate analysis was performed to study the factors associated with the T2 shine-through effect. RESULTS: T2 shine-through effect was observed in 204/388 (52.6%) of hepatic hemangiomas and in 100 (67.1%) patients. Mean ADC value of hemangiomas with T2 shine-through effect was significantly lower than hemangiomas without (2.0±0.48 vs 2.38±0.45, P<.0001). On multivariate analysis, high signal intensity on fat-suppressed T2-weighted fast spin-echo images, hemangiomas with classical or delayed enhancement, and the ADC of the liver were the only significant factors associated with T2 shine-through effect. CONCLUSION: T2 shine-through effect is commonly observed in hepatic hemangiomas and is related to hemangiomas characteristics. Radiologists should be aware of this phenomenon which could lead to misdiagnosis. Its presence should not question the diagnosis of hemangiomas when typical MR findings are found.

Experimental evidence of localized oscillations in the photosensitive chlorine dioxide-iodine-malonic acid reaction

The interaction between Hopf and Turing modes has been the subject of active research in recent years. We present here experimental evidence of the existence of mixed Turing-Hopf modes in a two-dimensional system. Using the photosensitive chlorine dioxide-iodine-malonic acid reaction (CDIMA) and external constant background illumination as a control parameter, standing spots oscillating in amplitude and with hexagonal ordering were observed. Numerical simulations in the Lengyel-Epstein model for the CDIMA reaction confirmed the results.

Inter-firm labor mobility and knowledge diffusion: a theoretical approach

[cat] Analitzem una economia amb dues característiques principals: la mobilitat dels treballadors implica transferència de coneixement i la productivitat de l’empresa augmenta amb l’intercanvi de coneixement. Cada empresa desenvolupa un tipus de coneixement que serà trasmès a la resta de la indústria mitjançant la mobilitat de treballadors. Estudiem dues estructures de mercat laboral i utilitzant un anàlisi comparatiu derivem les implicacions del model. Els resultats revelen com la mobilitat de treballadors depèn en la varietat i nivell del coneixement, la presència de costos de mobilitat, les institucions, la capacitat d’absorvir coneixement per part de les empreses i la mida de la indústria. Els resultats no depenen de l’estructura del mercat laboral.

Valsystem i lilleputtar: pluralitet och diffusion

Abstract: Elections in lilliputs: plurality and diffusion

On Ito's formula for elliptic diffusion processes

Bardina and Jolis [Stochastic process. Appl. 69 (1997) 83-109] prove an extension of Ito's formula for F(Xt, t), where F(x, t) has a locally square-integrable derivative in x that satisfies a mild continuity condition in t and X is a one-dimensional diffusion process such that the law of Xt has a density satisfying certain properties. This formula was expressed using quadratic covariation. Following the ideas of Eisenbaum [Potential Anal. 13 (2000) 303-328] concerning Brownian motion, we show that one can re-express this formula using integration over space and time with respect to local times in place of quadratic covariation. We also show that when the function F has a locally integrable derivative in t, we can avoid the mild continuity condition in t for the derivative of F in x.

Variation in thermal performance and reaction norms among populations of Drosophila melanogaster.

The major goal of evolutionary thermal biology is to understand how variation in temperature shapes phenotypic evolution. Comparing thermal reaction norms among populations from different thermal environments allows us to gain insights into the evolutionary mechanisms underlying thermal adaptation. Here, we have examined thermal adaptation in six wild populations of the fruit fly (Drosophila melanogaster) from markedly different natural environments by analyzing thermal reaction norms for fecundity, thorax length, wing area, and ovariole number under ecologically realistic fluctuating temperature regimes in the laboratory. Contrary to expectation, we found only minor differences in the thermal optima for fecundity among populations. Differentiation among populations was mainly due to differences in absolute (and partly also relative) thermal fecundity performance. Despite significant variation among populations in the absolute values of morphological traits, we observed only minor differentiation in their reaction norms. Overall, the thermal reaction norms for all traits examined were remarkably similar among different populations. Our results therefore suggest that thermal adaptation in D. melanogaster predominantly involves evolutionary changes in absolute trait values rather than in aspects of thermal reaction norms.

Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data.

Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.

High b-value Diffusion-weighted Imaging: A Sensitive Method to Reveal White Matter Changes in Schizophrenia

Background: b-value is the parameter characterizing the intensity of the diffusion weighting during image acquisition. Data acquisition is usually performed with low b value (b~1000 s/mm2). Evidence shows that high b-values (b>2000 s/mm2) are more sensitive to the slow diffusion compartment (SDC) and maybe more sensitive in detecting white matter (WM) anomalies in schizophrenia.Methods: 12 male patients with schizophrenia (mean age 35 +/-3 years) and 16 healthy male controls matched for age were scanned with a low b-value (1000 s/mm2) and a high b-value (4000 s/mm2) protocol. Apparent diffusion coefficient (ADC) is a measure of the average diffusion distance of water molecules per time unit (mm2/s). ADC maps were generated for all individuals. 8 region of interests (frontal and parietal region bilaterally, centrum semi-ovale bilaterally and anterior and posterior corpus callosum) were manually traced blind to diagnosis.Results: ADC measures acquired with high b-value imaging were more sensitive in detecting differences between schizophrenia patients and healthy controls than low b-value imaging with a gain in significance by a factor of 20- 100 times despite the lower image Signal-to-noise ratio (SNR). Increased ADC was identified in patient's WM (p=0.00015) with major contributions from left and right centrum semi-ovale and to a lesser extent right parietal region.Conclusions: Our results may be related to the sensitivity of high b-value imaging to the SDC believed to reflect mainly the intra-axonal and myelin bound water pool. High b-value imaging might be more sensitive and specific to WM anomalies in schizophrenia than low b-value imaging