Biotransformation of steroids by the fission yeast Schizosaccharomyces pombe

The fungal biotransformation of steroids is of applied interest due to the economic importance of such stereo‐ and regiospecific reactions and also in the context of ergosterol pathway engineering to produce vitamin D and steroidal products. In Schizosaccharomyces pombe no steroid hydroxylation as is found in filamentous fungi was observed, but a cytosolic NAD(H)/NADP(H)‐dependent hydroxysteroid dehydrogenase activity was identified. Progesterone was reduced at the Δ⁴ double bond (in vivo only) as well as at the C‐3 and C‐20 keto groups. Testosterone and 4‐androstene‐3,17‐dione were interconverted and 5α‐pregnane‐3,20‐dione and 5β‐pregnane‐3,20‐dione were reduced to 3‐hydroxy products. The reactions were sometimes reversible and showed regio‐ and stereo specificity. In S. pombe more than one steroid dehydrogenase homologue is likely to occur, as has been observed in Saccharomyces cerevisiae. Our findings indicate that genes encoding soluble proteins should be examined as candidates for actual steroid dehydrogenase activity. Copyright © 1999 John Wiley & Sons, Ltd.     

Seeding effects on the mechanochemical synthesis of 0.9Pb(Mg1/3Nb2/3)O3–0.1PbTiO3

A systematic investigation of the seeding effects on the mechanochemical synthesis of lead magnesium niobate – lead titanate 0.9Pb(Mg_1/3Nb_2/3)O₃–0.1PbTiO₃ (PMN–10PT), one of the most studied relaxor-ferroelectric material for electrocaloric applications, is reported. The perovskite crystallisation process was followed by X-ray diffraction using the Rietveld refinement method and transmission electron microscopy. Compared to the mixed-oxides case which requires 143 h of high-energy milling, the milling time needed to obtain a phase-pure PMN–10PT perovskite using PT seeds is reduced almost twice. The presence of PT seeds leads to faster transitions from the amorphous to pyrochlore and to perovskite phases compared to the mixed-oxides case. A sintering study demonstrates, for the first time, that a second, metastable, pyrochlore phase is taking part in the processes of perovskite formation. The PMN–10PT ceramic prepared from the PT-seeded powder exhibits electrocaloric properties comparable to reported values for PMN–10 PT prepared from oxides.     

Preparation of Phase‐Pure K0.5Na0.5NbO3 Fine Powders by a Solid‐State Reaction at 625°C from a Precursor Comprising Nb2O5 and K,Na Acetates

Phase‐pure K_0.5Na_0.5NbO₃ (KNN) fine powders were synthesized via a solid‐state route from a homogeneous solid mixture. A colloidal dispersion comprising a mixed ethanol solution of potassium and sodium acetates and Nb₂O₅ fine particles was attrition milled and dried carefully to avoid water absorption. Two‐step calcination in air at 450°C and 625°C, each for 3 h, resulted in the phase‐pure KNN powders. The volume‐based median diameter of the final product was ca. 0.8 μm. Starting from the same precursors without dissolving the acetates, the phase‐pure KNN was never achieved even when the two calcination temperatures were increased to 550°C and 700°C, in spite of the same milling conditions. Key issues of eliminating second phases were (i) starting from a wet‐milled mixture with a single solution containing both of the A‐site species, and (ii) repeated wet milling of the reaction mixture to disintegrate reaction‐induced agglomerates. These enabled rapid nuclei growth from chemically interacted precursor prior to calcination, and short diffusion path due to repeated deagglomeration, excluding formation of off‐stoichiometric second phases. All these items were confirmed by different analytical tools, among others, thermo‐gravimetry and differential thermal analysis (TG‐DTA), particle size analyses, and XPS at various reaction stages. On the heating stage microscope, a shrinkage onset was observed at 850°C, that is, 150 K lower than that of conventionally prepared KNN, that is, via a solid‐state synthesis from carbonates by a two‐step calcination at 800°C and 750°C, for 4 h each. No second phase was observed after sintering up to 1100°C.     

Mechanochemical synthesis of NaNbO3

The mechanochemical synthesis of NaNbO₃ is studied. It is shown that NaNbO₃ can be prepared by milling the constituents, i.e. Na₂CO₃ and Nb₂O₅ in the planetary mill. After 40 h of mechanochemical treatment NaNbO₃ nanoparticles in the range of 10-20 nm are obtained. Furthermore, the high-energy milling leads to the mechanochemically-triggered carbonate decomposition, which has been observed for a few cases in the open literature.     

Smooth continuous transition between tasks on a kinematic control level: Obstacle avoidance as a control problem

Kinematically redundant robots allow simultaneous execution of several tasks with different priorities. Beside the main task, obstacle avoidance is one commonly used subtask. The ability to avoid obstacles is especially important when the robot is working in a human environment. In this paper, we propose a novel control method for kinematically redundant robots, where we focus on a smooth, continuous transition between different tasks. The method is based on a new and very simple null-space formulation. Sufficient conditions for the tasks design are given using the Lyapunov-based stability discussion. The effectiveness of the proposed control method is demonstrated by simulation and on a real robot. Pros and cons of the proposed method and the comparison with other control methods are also discussed.     

A Simple Electrogoniometric System and Its Testing

A simple goniometric system intended for quantitative evaluation of a patients' gait is described. The hip, knee and ankle angles of both legs in the sagittal plane and the contacts between ground and three parts of the sole were measured. By using a special knob to adjust and fix the knee potentiometer axis position, a small number of selectively chosen attachments and very light construction, the gait was disturbed to the minimum extent. The system's accuracy was tested by comparing the directly measured step length and the calculated one. The accuracy achieved was better than 5%.     

Teaching robots to cooperate with humans in dynamic manipulation tasks based on multi-modal human-in-the-loop approach

We propose an approach to efficiently teach robots how to perform dynamic manipulation tasks in cooperation with a human partner. The approach utilises human sensorimotor learning ability where the human tutor controls the robot through a multi-modal interface to make it perform the desired task. During the tutoring, the robot simultaneously learns the action policy of the tutor and through time gains full autonomy. We demonstrate our approach by an experiment where we taught a robot how to perform a wood sawing task with a human partner using a two-person cross-cut saw. The challenge of this experiment is that it requires precise coordination of the robot’s motion and compliance according to the partner’s actions. To transfer the sawing skill from the tutor to the robot we used Locally Weighted Regression for trajectory generalisation, and adaptive oscillators for adaptation of the robot to the partner’s motion.     

Application of Artificial Neural Networks in Design of Steel Production Path

Artificial neural networks (ANNs) are employed as an alternative to physical modeling for calculation of the relations between the production path process parameters (melting of scrap steel and alloying, continuous casting, hydrogen removal, reheating, rolling, and cooling on a cooling bed) and the final product mechanical properties (elongation, tensile strength, yield stress, hardness after rolling, necking) of steel semi products. They provide a much faster technique of response evaluation complementary to physical modeling. The Štore Steel company process path for production of steel bars is used as an example for demonstrating the approach. The applied ANN is of a multilayer feedforward type with sigmoid activation function and supervised learning. The entire set of 123 process parameters has been reduced to 34 influential ones and 1879 data sets from the production line have been used for learning. The results of parametric studies performed on the ANN based model seem consistent with the expectations based on industrial experiences. However, further improvements in data acquisition and analytical procedures are envisaged in order to obtain a methodology, reliable enough for use in the everyday industrial practice. The methodology seems to be for the first time applied in the through process modeling of steel production.     

Robotic Assembly System in Semiconductor Industry

A sensor-based robotic production system for assembly of rectifier bridges is described. Assembly tasks in semiconductor industry require a robot with good positional accuracy having the capability of high velocities and accelerations in all degrees of freedom. An important part of the semiconductor production is to measure the diode properties. The trajectory of the manipulator end-effector is determined by the results from these measurements. A vaccum gripper with an air flow sensor is also used in this particular task. The robotic language DARL was used to control the assembly process.