Solid-phase synthesis and DNA binding studies of dichloroplatinum(II) conjugates of dicarba analogues of octreotide as a new anticancer drugs

The first dichloroplatinum(II) conjugates of dicarba analogues of octreotide , which is expected to act as a"tumour-targeting device", have been efficiently synthesized following a stepwise solid-phase approach; these compounds emulate the mechanism of cisplatin since they form a 1,2-intrastrand cross-link with two consecutive guanines of an oligonucleotide.

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.

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.

Solid phase crystallization under continuous heating: kinetic and microstructure scaling laws

The kinetics and microstructure of solid-phase crystallization under continuous heating conditions and random distribution of nuclei are analyzed. An Arrhenius temperature dependence is assumed for both nucleation and growth rates. Under these circumstances, the system has a scaling law such that the behavior of the scaled system is independent of the heating rate. Hence, the kinetics and microstructure obtained at different heating rates differ only in time and length scaling factors. Concerning the kinetics, it is shown that the extended volume evolves with time according to αex = [exp(κCt′)]m+1, where t′ is the dimensionless time. This scaled solution not only represents a significant simplification of the system description, it also provides new tools for its analysis. For instance, it has been possible to find an analytical dependence of the final average grain size on kinetic parameters. Concerning the microstructure, the existence of a length scaling factor has allowed the grain-size distribution to be numerically calculated as a function of the kinetic parameters

Martensitic phase transformation in rapidly solidified Mn50Ni40In10 alloy ribbons

Heusler alloy Mn50Ni40In10 was produced as preferentially textured ribbon flakes by melt spinning, finding the existence of martensitic-austenic transformation with both phases exhibiting ferromagnetic ordering. A microcrystalline three-layered microstructure of ordered columnar grains grown perpendicularly to ribbon plane was formed between two thin layers of smaller grains. The characteristic temperatures of the martensitic transformation were MS=213 K, Mf=173 K, AS=222 K, and Af=243 K. Austenite phase shows a cubic L21 structure (a=0.6013(3) nm at 298 K and a Curie point of 311 K), transforming into a modulated fourteen-layer modulation monoclinic martensite

Short- and long-term changes in chromosomal inversion polymorphism and global warming: Drosophila subobscura from the Balkans

The chromosomal inversion polymorphism of Drosophila subobscura is adaptive to environmental changes. The population of Petnica, Serbia, was chosen to analyze short- and long-term changes in this polymorphism. Short-term changes were studied in the samples collected in May, June, and August of 1995. The inversion polymorphism varied over these months, although various interpretations are possible. To analyze long-term changes, samples obtained in May 1995 and May 2010 were compared. The frequency of the 'cold' adapted inversions (Ast, Jst, Ust, Est, and Ost) decreased and that of the 'warm' adapted inversions (A2, J1, U1+2, and O3+4) increased, from 1995 to 2010. These changes are consistent with the general increase in temperature recorded in Petnica for the same period. Finally, the possible response of chromosomal polymorphism to global warming was analyzed at the regional level (Balkan peninsula). This polymorphism depends on the ecological conditions of the populations, and the changes observed appear to be consistent with global warming expectations. Natural selection seems to be the main mechanism responsible for the evolution of this chromosomal polymorphism.

Short- and long-term changes in chromosomal inversion polymorphism and global warming: Drosophila subobscura from the Balkans

The chromosomal inversion polymorphism of Drosophila subobscura is adaptive to environmental changes. The population of Petnica, Serbia, was chosen to analyze short- and long-term changes in this polymorphism. Short-term changes were studied in the samples collected in May, June, and August of 1995. The inversion polymorphism varied over these months, although various interpretations are possible. To analyze long-term changes, samples obtained in May 1995 and May 2010 were compared. The frequency of the 'cold' adapted inversions (Ast, Jst, Ust, Est, and Ost) decreased and that of the 'warm' adapted inversions (A2, J1, U1+2, and O3+4) increased, from 1995 to 2010. These changes are consistent with the general increase in temperature recorded in Petnica for the same period. Finally, the possible response of chromosomal polymorphism to global warming was analyzed at the regional level (Balkan peninsula). This polymorphism depends on the ecological conditions of the populations, and the changes observed appear to be consistent with global warming expectations. Natural selection seems to be the main mechanism responsible for the evolution of this chromosomal polymorphism.

Fast Approximation of Nonlinearities for improving inversion algorithms of PNL mixtures and Wiener systems

This paper proposes a very fast method for blindly approximating a nonlinear mapping which transforms a sum of random variables. The estimation is surprisingly good even when the basic assumption is not satisfied.We use the method for providing a good initialization for inverting post-nonlinear mixtures and Wiener systems. Experiments show that the algorithm speed is strongly improved and the asymptotic performance is preserved with a very low extra computational cost.

Quasi-Nonparametric Blind Inversion of Wiener Systems

An e cient procedure for the blind inversion of a nonlinear Wiener system is proposed. We proved that the problem can be expressed as a problem of blind source separation in nonlinear mixtures, for which a solution has been recently proposed. Based on a quasi-nonparametric relative gradient descent, the proposed algorithm can perform e ciently even in the presence of hard distortions.

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.

Initialisation of Nonlinearities for PNL and Wiener systems Inversion

This paper proposes a very fast method for blindly initial- izing a nonlinear mapping which transforms a sum of random variables. The method provides a surprisingly good approximation even when the basic assumption is not fully satis¯ed. The method can been used success- fully for initializing nonlinearity in post-nonlinear mixtures or in Wiener system inversion, for improving algorithm speed and convergence.

Blind Inversion of Wiener Systems

A system in which a linear dynamic part is followed by a non linear memoryless distortion a Wiener system is blindly inverted This kind of systems can be modelised as a postnonlinear mixture and using some results about these mixtures an e cient algorithm is proposed Results in a hard situation are presented and illustrate the e ciency of this algorithm

Spreading due to heterogeneity in two-phase flow

Postprint (published version)