Aggregate monotonic stable single-valued solutions for cooperative games

[cat] En aquest treball caracteritzem les solucions puntuals de jocs cooperatius d'utilitat transferible que compleixen selecció del core i monotonia agregada. També mostrem que aquestes dues propietats són compatibles amb la individualitat racional, la propietat del jugador fals i la propietat de simetria. Finalment, caracteritzem les solucions puntuals que compleixen les cinc propietats a l'hora.

Dynamics of transient pattern formation in nematic liquid crystals

We analyze the dynamics of a transient pattern formation in the Fréedericksz transition corresponding to a twist geometry. We present a calculation of the time-dependent structure factor based on a dynamical model which incorporates consistently the coupling of the director field with the velocity flow and also the effect of fluctuations. The appearance and development of a characteristic periodicity is described in terms of the time dependence of the maximum of the structure factor. We find a well-defined time for the appearance of the pattern and a subsequent stage of pattern development in which the characteristic periodicity tends to an asymptotic value.

Nonempirical cluster-model study of the chemisorption of atomic hydrogen on the (111) surface of diamondlike crystals

The interaction of atomic hydrogen with C4H9, Si4H9, and Ge4H9 model clusters has been studied using all-electron and pseudopotential ab initio Hartree-Fock computations with basis sets of increasing flexibility. The results show that the effect of polarization functions is important in order to reproduce the experimental findings, but their inclusion only for the atoms directly involved in the chemisorption bond is usually sufficient. For the systems H-C4H9 and H-Si4H9 all-electron and pseudopotential results are in excellent agreement when basis sets of comparable quality are used. Besides, semiempirical modified-neglect-of-differential-overlap computations provide quite reliable results both for diamond and silicon and have been used to investigate larger model clusters. The results confirm the local nature of chemisorption and further justify the use of minimal X4H9 model clusters.

Dynamics of transient domain structures in nematic liquid crystals: The splay Fréedericksz transition

We discuss the dynamics of the transient pattern formation process corresponding to the splay Fréedericksz transition. The emergence and subsequent evolution of the spatial periodicity is here described in terms of the temporal dependence of the wave numbers corresponding to the maxima of the structure factor. Situations of perpendicular as well as oblique field-induced stripes relative to the initial orientation of the director are both examined with explicit indications of the time scales needed for their appearance and posterior development.

Transient patterns in nematic liquid crystals: Domain-wall dynamics

We study the dynamics of the late stages of the Fréedericksz transition in which a periodic transient pattern decays to a final homogeneous state. A stability analysis of an unstable stationary pattern is presented, and equations for the evolution of the domain walls are obtained. Using results of previous theories, we analyze the effect that the specific dynamics of the problem, incorporating hydrodynamic couplings, has on the expected logarithmic domain growth law.

Backflow-induced asymmetric collapse of disclination lines in liquid crystals

We present experiments where opposed pairs of planar parallel disclination lines of topological strength s=±1 move due to their mutual attraction. Our measurements show that their motion is clearly asymmetric, with +1 defects moving up to twice as fast as -1 ones. This is a clear indication of backflow, given the intrinsic isotropic elasticity of our system. A phenomenological model is able to account for the experimental observations by renormalizing the orientational diffusivity estimated from the velocity of each defect.

Random assignment of intervention points in two phase single-case designs: data-division-specific distributions

The present study explores the statistical properties of a randomization test based on the random assignment of the intervention point in a two-phase (AB) single-case design. The focus is on randomization distributions constructed with the values of the test statistic for all possible random assignments and used to obtain p-values. The shape of those distributions is investigated for each specific data division defined by the moment in which the intervention is introduced. Another aim of the study consisted in testing the detection of inexistent effects (i.e., production of false alarms) in autocorrelated data series, in which the assumption of exchangeability between observations may be untenable. In this way, it was possible to compare nominal and empirical Type I error rates in order to obtain evidence on the statistical validity of the randomization test for each individual data division. The results suggest that when either of the two phases has considerably less measurement times, Type I errors may be too probable and, hence, the decision making process to be carried out by applied researchers may be jeopardized.

Comparing 'visual' effect size indices for single-case designs

Effect size indices are indispensable for carrying out meta-analyses and can also be seen as an alternative for making decisions about the effectiveness of a treatment in an individual applied study. The desirable features of the procedures for quantifying the magnitude of intervention effect include educational/clinical meaningfulness, calculus easiness, insensitivity to autocorrelation, low false alarm and low miss rates. Three effect size indices related to visual analysis are compared according to the aforementioned criteria. The comparison is made by means of data sets with known parameters: degree of serial dependence, presence or absence of general trend, changes in level and/or in slope. The percent of nonoverlapping data showed the highest discrimination between data sets with and without intervention effect. In cases when autocorrelation or trend is present, the percentage of data points exceeding the median may be a better option to quantify the effectiveness of a psychological treatment.

Factors affecting visual analysis in single-case designs

Visual inspection remains the most frequently applied method for detecting treatment effects in single-case designs. The advantages and limitations of visual inference are here discussed in relation to other procedures for assessing intervention effectiveness. The first part of the paper reviews previous research on visual analysis, paying special attention to the validation of visual analysts" decisions, inter-judge agreement, and false alarm and omission rates. The most relevant factors affecting visual inspection (i.e., effect size, autocorrelation, data variability, and analysts" expertise) are highlighted and incorporated into an empirical simulation study with the aim of providing further evidence about the reliability of visual analysis. Our results concur with previous studies that have reported the relationship between serial dependence and increased Type I rates. Participants with greater experience appeared to be more conservative and used more consistent criteria when assessing graphed data. Nonetheless, the decisions made by both professionals and students did not match sufficiently the simulated data features, and we also found low intra-judge agreement, thus suggesting that visual inspection should be complemented by other methods when assessing treatment effectiveness.

Choosing among techniques for quantifying single-case intervention effectiveness

If single case experimental designs are to be used to establish guidelines for evidence-based interventions in clinical and educational settings, numerical values that reflect treatment effect sizes are required. The present study compares four recently developed procedures for quantifying the magnitude of intervention effect using data with known characteristics. Monte Carlo methods were used to generate AB designs data with potential confounding variables (serial dependence, linear and curvilinear trend, and heteroscedasticity between phases) and two types of treatment effect (level and slope change). The results suggest that data features are important for choosing the appropriate procedure and, thus, inspecting the graphed data visually is a necessary initial stage. In the presence of serial dependence or a change in data variability, the Nonoverlap of All Pairs (NAP) and the Slope and Level Change (SLC) were the only techniques of the four examined that performed adequately. Introducing a data correction step in NAP renders it unaffected by linear trend, as is also the case for the Percentage of Nonoverlapping Corrected Data and SLC. The performance of these techniques indicates that professionals" judgments concerning treatment effectiveness can be readily complemented by both visual and statistical analyses. A flowchart to guide selection of techniques according to the data characteristics identified by visual inspection is provided.

A comparison of mean phase difference and generalized least squares for analyzing single-case data

The present study focuses on single-case data analysis and specifically on two procedures for quantifying differences between baseline and treatment measurements The first technique tested is based on generalized least squares regression analysis and is compared to a proposed non-regression technique, which allows obtaining similar information. The comparison is carried out in the context of generated data representing a variety of patterns (i.e., independent measurements, different serial dependence underlying processes, constant or phase-specific autocorrelation and data variability, different types of trend, and slope and level change). The results suggest that the two techniques perform adequately for a wide range of conditions and researchers can use both of them with certain guarantees. The regression-based procedure offers more efficient estimates, whereas the proposed non-regression procedure is more sensitive to intervention effects. Considering current and previous findings, some tentative recommendations are offered to applied researchers in order to help choosing among the plurality of single-case data analysis techniques.

Crystal engineering studies: polymorphs and co-crystals

We review the key topics of one of the areas with the biggest impact of the last years in the chemical and pharmaceutical industry that is Crystal Engineering. The relevance of polymorphs and co-crystals from different points of view is been highlighted and broadly illustrated by means of several recent examples of studies carried out in this field. In addition, the most suitableinstrumental techniques and the intellectual property implications are reviewed.