Crystallization of progesterone polymorphs using polymer-induced heteronucleation (PIHn) method

Progesterone is a natural hormone steroid used in humans for several treatments and in livestock for artificial insemination, which exhibits two polymorphic forms at ambient conditions: form 1 and form 2. Form 2 is metastable and more soluble than form 1; however, it is not suitable to use as powder raw material because it transforms into form 1 by the effects of grinding. A polymorphic screening of progesterone based on polymer-induced heteronucleation method was performed as an alternative to prepare the metastable form. Polyvinyl alcohol, hydroxypropyl methylcellulose (HPMC), dextran, gelatin, polyisoprene (PI) and acrylonitrile-butadiene (NBR) copolymer were used. Crystals were prepared from 0.5, 10 and 40?mg/mL solutions in acetone at room temperature by solvent evaporation. The samples were characterized by X-ray powder diffraction, differential scanning calorimetry (DSC), scanning electron microcopy and attenuated total reflectance infrared Fourier transform spectroscopy. Form 1 was nucleated from 40?mg/mL solutions on the six polymers and from 10?mg/mL solutions on PI and NBR. The mixture of form 1 and form 2 was obtained from 10?mg/mL solution on HPMC, dextran and gelatin and from 0.5?mg/mL solution crystallizations. Therefore, the polymeric devices, which crystallized the metastable and more soluble polymorph (2) of progesterone, would be a promissory alternative for the pharmaceutical applications.     

Narrow-band correction of the residual amplitude modulation in frequency-modulation spectroscopy

We have developed a narrow-band controller in the MHz range, based on a field-programmable gate array. It is used to control the probe beam intensity in frequency-modulated spectroscopy experiments with an acoustooptic modulator. The residual amplitude modulation at the modulation frequency (2.5 MHz) is reduced by 50 dB. The first-harmonic detection of the signals is operated in saturation spectroscopy of I/sub 2/ at 514.5 nm and 501.7 nm. A reduction of the background noise and a large increase in the signal-to-noise ratio are obtained.     

EEG spectral abnormalities and psychosis as predictors of cognitive and functional decline in probable Alzheimer's disease

We examined whether either psychotic features (e.g., delusions and hallucinations) or EEG abnormalities are associated with more rapid progression of Alzheimer's disease (AD). AD patients with psychosis have exhibited more EEG abnormalities than those without psychosis, and both abnormal EEG and psychosis have been noted to be predictors of functional and cognitive decline in AD. Ninety-five probable AD patients participating in a longitudinal study of dementia had an EEG and a semistructured psychiatric interview at baseline. Using EEG spectral analysis, we classified records as normal/abnormal based on the parasagittal mean frequency. Patients with abnormal EEGs were more functionally (e.g., Blessed Rating Scale for activities of daily living) and cognitively (e.g., Mini-Mental State) impaired than patients with normal EEG. AD patients with psychosis were only more functionally impaired than patients without psychosis. A two-factor analysis showed no interaction between abnormal EEG and psychosis. In addition, using a Cox proportional hazard model adjusted for age and education, the presence of an abnormal EEG or psychotic symptom at study entry was associated with higher risk of reaching severe cognitive and functional impairment during follow-up. Neither abnormal EEG nor the presence of psychosis predicted death. These results indicate that both abnormal EEG and psychosis are independent predictors of disease progression but not of physical survival.     

Comparative study of the colorants monascus and cochineal used in the preparation of gels made with various gelling agents

The possibilities of using monascus to colour gels were studied by comparing it with cochineal. Gels were prepared with four gelling agents—carrageenan, gellan, gelatine and xanthan—and their colour was measured with a Hunter Lab colorimeter. The equations relating L^* and h with the concentrations of sugar [SU] and colorant [COL] were deduced, and it was found that [COL] had more influence on colour than [SU]. In general, for these four gelling agents the colour of monascus gels is orange-red and the colour of cochineal gels is purplish red. The gels made with xanthan were always the lightest, whether they were made with cochineal or with monascus.     

Optimal management of logistic activities in multi-site environments

The new emerging area of Enterprise Wide Optimization (EWO) has focused the attention in effectively solving the combined production/distribution scheduling problem. The importance of logistic activities performed in multi-site environments comes from the relative magnitude of the associated transportation costs and the good chance of getting large savings on such expenses. This paper first develops an exact MILP mathematical formulation for the multiple vehicle time-window-constrained pickup and delivery (MVPDPTW) problem. The approach is able to account for many-to-many transportation requests, pure pickup and delivery tasks, heterogeneous vehicles and multiple depots. Optimal solutions for a variety of benchmark problems with cluster/random distributions of pickup and delivery locations and limited sizes in terms of customer requests and vehicles have been discovered. However, the computational cost exponentially grows with the number of requests. For large-scale m-PDPTW problems, a local search improvement algorithm steadily providing a better solution through two evolutionary steps is also presented. A neighborhood structure around the starting solution is generated by first allowing multiple request exchanges among nearby trips and then permitting the reordering of nodes on every individual route. If a better set of routes is found, both steps are repeated until no improved solution is discovered. Compact MILP mathematical formulations for both sub-problems have been developed and solved through an efficient branch-and-bound algorithm. A significant number of large-scale m-PDPTW benchmark problems, some of them including up to 100 transportation requests, were successfully solved in reasonable CPU times.     

Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)—also known as dissortative mating—, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA’s mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.