An examination of different fitness and novelty based selection methods for the evolution of neural networks

It has been suggested recently that it is a reasonable abstraction of evolutionary processes to use evolutionary algorithms that select individuals based on the novelty of their behavior instead of their fitness. Here we study the performance of fitness- and novelty-based search on several neuroevolution tasks. We also propose several new algorithms that select both for fit and for novel individuals, but without weighting these two criteria directly against each other. We find that behavioral speciation, behavioral near neutral speciation, and behavioral novelty speciation perform best on most tasks. Pure novelty search, as well as a number of hybrid methods without speciation mechanism, do not perform well on most tasks. Using behavioral criteria for speciation often yields better results than using genetic criteria.     

New Trends in Electrostatic Precipitation: Wide Duct Spacing, Precharging, Pulse Energization

Increased research in electrostatic precipitation has resulted in the emergence of promising new technologies. In a new design concept already widely used in Japan, the precipitator duct spacing is increased from the traditional 200-300 mm up to 400-600 mm, and the precipitator voltage is raised correspondingly, with precipitator performance remaining almost unchanged for the same precipitator volume and the same gas flow. For suitable applications, this design results in reduced installation costs and easier maintenance. Various devices for precharging of high resistivity dust now under development improve particle charging and thereby enhance precipitator performance. Pulse energization improves the performance of precipitators collecting high resistivity dust by improving particle charging and current distribution and allowing regulation of the precipitator current independent of precipitator voltage.     

Global Metabolomics Discovers Two Novel Biomarkers in Pyridoxine-Dependent Epilepsy Caused by ALDH7A1 Deficiency

Pyridoxine-dependent epilepsy (PDE) is a rare autosomal recessive developmental and epileptic encephalopathy caused by pathogenic variants in the ALDH7A1 gene (PDE-ALDH7A1), which mainly has its onset in neonates and infants. Early diagnosis and treatment are crucial to prevent severe neurological sequelae or death. Sensitive, specific, and stable biomarkers for diagnostic evaluations and follow-up examinations are essential to optimize outcomes. However, most of the known biomarkers for PDE lack these criteria. Additionally, there is little discussion regarding the interdependence of biomarkers in the PDE-ALDH7A1 metabolite profile. Therefore, the aim of this study was to understand the underlying mechanisms in PDE-ALDH7A1 and to discover new biomarkers in the plasma of patients using global metabolomics. Plasma samples from 9 patients with genetically confirmed PDE-ALDH7A1 and 22 carefully selected control individuals were analyzed by ultra high performance liquid chromatography–high-resolution mass spectrometry (UHPLC-HRMS). Two novel and reliable pyridoxine-independent diagnostic markers, 6-hydroxy-2-aminocaproic acid (HACA) and an isomer of C₉H₁₁NO₄, were identified. Furthermore, a possible reaction mechanism is proposed for HACA. This study demonstrates the capability of global metabolomics in disease screening to detect established and novel biomarkers.     

A comparative study in the transmission electron microscope and scanning electron microscope of intracellular structures in sheep heart muscle cells

The internal cellular structures of the sheep ventricular myocardium have been comparatively studied in the transmission electron microscope (TEM) and in the scanning electron microscope (SEM). For TEM studies the tissue was prepared according to standard methods. Thick sections (10 μm) of paraffin embedded material were, after they had been deparaffinized in toluene, critical point dried, coated with gold and examined in the SEM. The comparative TEM and SEM investigations revealed very good correspondence, and it is evident that the described preparation procedure for SEM has preserved the fine structures of myofibrils, mitochondria, T-Tubules and sarcoplasmic reticulum in an excellent life-like pattern. Of special interest was the three-dimensional demonstration of triads and of circumferentially arranged T-tubules.     

Essential fatty acid deficiency induces fatty acid desaturase expression in rat epididymis, but not in testis

On the molecular level, essential fatty acid deficiency (EFAD) has been associated with induced fatty acid (FA) desaturase expression and activity in several tissues. However, there seem to be exceptions. In the present study, we examine the effects of EFAD in the male rat genital tract, combining FA analysis, gene expression studies, and morphological evaluation of epididymal spermatozoa. When feeding 21-day-old Wistar rats, a fat-free diet for 6 weeks, an increase in 18:1n-9 and 20:3n-9 and a concomitant decrease in the 18:2n-6 and 20:4n-6 species are seen in testis, as well as in liver. However, with regard to desaturase expression the rat testis seems to be unresponsive to EFAD conditions, in contrast to other organs studied. In the sexually mature testis none of the desaturases (SCD1, SCD2, D5D, or D6D) are induced in response to lowered contents of polyunsaturated FAs. This also applies to caput epididymis, while EFAD sensitivity is regained in cauda epididymis, where the desaturases are upregulated. The FA profile of epididymal spermatozoa is increasingly affected by EFAD during the transport from testis to cauda epididymis. Furthermore, a significant increase in the number of abnormal spermatozoa is observed in cauda epididymis.     

The effect of a GnRH agonist on cryopreserved human ovarian grafts in severe combined immunodeficient mice

This prospective study compares the effect of a GnRH agonist on the number of follicles in different developmental stages in cryopreserved human ovarian grafts transplanted into gonadotropin-stimulated or not stimulated severe combined immunodeficient mice (SCID mice). Human ovarian tissue from seven patients was cryopreserved with an open-freezing system and xenotransplanted in SCID mice. The SCID mice were then treated according to different stimulation protocols. The survival of the tissue after cryopreservation was examined by LIVE/DEAD viability staining or transplanted in the neck muscle of 41 SCID mice. Development of follicles, estradiol production, vaginal cytology, and uterus weight were assessed after 15 weeks with or without gonadotropin stimulation. Viable follicles were detected in all frozen/thawed specimens using the LIVE/DEAD assay. Triptorelin, a GnRH agonist, caused a significant reduction of follicles in all developmental stages in the non-gonadotropin-stimulated animals (P<0.001). In gonadotropin-stimulated animals, GnRH agonist treatment has no significant effect on primordial, primary and preantral follicle count, whereas the antral follicles were significantly fewer (P = 0.03). The GnRH agonist treatment is not able to prevent the primordial follicle depletion after the xenografting of ovarian tissue in SCID mice with or without gonadotropin stimulation. Furthermore, it causes an additional loss of follicles if administered during the critical neovascularization period after the transplantation.     

On atmospheric stability in the dynamic wake meandering model

The present study investigates a new approach for capturing the effects of atmospheric stability on wind turbine wake evolution and wake meandering by using the dynamic wake meandering model. The most notable impact of atmospheric stability on the wind is the changes in length and velocity scales of the atmospheric turbulence. The length and velocity scales in the turbulence are largely responsible for the way in which wind turbine wakes meander as they convect downstream. The hypothesis of the present work is that appropriate turbulence scales can be extracted from the oncoming atmospheric turbulence spectra and applied to the dynamic wake meandering model to capture the correct wake meandering behaviour. The ambient turbulence in all stability classes is generated using the Mann turbulence model, where the effects of non‐neutral atmospheric stability are approximated by the selection of input parameters. In order to isolate the effect of atmospheric stability, simulations of neutral and unstable atmospheric boundary layers using large‐eddy simulation are performed at the same streamwise turbulence intensity level. The turbulence intensity is kept constant by calibrating the surface roughness in the computational domain. The changes in the turbulent length scales due to the various atmospheric stability states impact the wake meandering characteristics and thus the power generation by the individual turbines. The proposed method is compared with results from both large‐eddy simulation coupled with an actuator line model and field measurements, where generally good agreement is found with respect to the velocity, turbulence intensity and power predictions. Copyright © 2013 John Wiley & Sons, Ltd.     

Exploring temporal variations of oxygen saturation constants of nitrifying bacteria

Activated sludge models (ASM) are generally accepted as state-of-the-art in modeling wastewater treatment plants. In this paper, we assess the temporal variability of an ASM parameter-the oxygen half-saturation constant of autotrophic bacteria (K(O),(AUT)). A series of respirometric experiments is performed for conventional activated sludge and sludge from a membrane bioreactor. K(O) values are estimated for both ammonium-oxidizing and nitrite-oxidizing bacteria. For parameter estimation, the Monod kinetic model structure is extended by a sensor model. Still remaining systematic deviations between data and model are considered by a thorough residual analysis: (1) uncertainty estimates of K(O) are corrected to reflect model structure deficiencies and (2) the inter-experimental cross-correlation of residuals is taken into account to assess temporal changes. We conclude that K(O),(AUT) is a time variable parameter and should be considered accordingly.     

Parameter Learning in Object-Oriented Bayesian Networks

This paper describes a method for parameter learning in Object-Oriented Bayesian Networks (OOBNs). We propose a methodology for learning parameters in OOBNs, and prove that maintaining the object orientation imposed by the prior model will increase the learning speed in object-oriented domains. We also propose a method to efficiently estimate the probability parameters in domains that are not strictly object oriented. Finally, we attack type uncertainty, a special case of model uncertainty typical to object-oriented domains.