Simulation of Temperature Distribution in Stored Wheat without Aeration

A neural-deterministic simulation model applied for calculating distributions of temperatures and moisture content in a bed of wheat stored in a steel silo without aeration is presented in the article. The model consists of differential equations of heat and moisture transfer, initial and boundary conditions, and three artificial neural networks used during simulated ambient air conditions. Experiments and computer simulations were carried out in order to determine temperature fields in wheat grain stored in a steel silo for two months. The computer simulations were carried using MATLAB and FEMLAB software. The difference between measured and simulated temperature in grain near the silo wall at a height of 2.5 m from the bottom was less than 3.0°C. On the basis of the analysis performed it was concluded that the temperature distributions obtained with the model were consistent with the measured results obtained for grain stored in a steel silo without aeration.     

Secure Distributed Key Generation for Discrete-Log Based Cryptosystems

A Distributed Key Generation (DKG) protocol is an essential component of threshold cryptosystems required to initialize the cryptosystem securely and generate its private and public keys. In the case of discrete-log-based (dlog-based) threshold signature schemes (ElGamal and its derivatives), the DKG protocol is further used in the distributed signature generation phase to generate one-time signature randomizers (r = g^k). In this paper we show that a widely used dlog-based DKG protocol suggested by Pedersen does not guarantee a uniformly random distribution of generated keys: we describe an efficient active attacker controlling a small number of parties which successfully biases the values of the generated keys away from uniform. We then present a new DKG protocol for the setting of dlog-based cryptosystems which we prove to satisfy the security requirements from DKG protocols and, in particular, it ensures a uniform distribution of the generated keys. The new protocol can be used as a secure replacement for the many applications of Pedersen's protocol. Motivated by the fact that the new DKG protocol incurs additional communication cost relative to Pedersen's original protocol, we investigate whether the latter can be used in specific applications which require relaxed security properties from the DKG protocol. We answer this question affirmatively by showing that Pedersen's protocol suffices for the secure implementation of certain threshold cryptosystems whose security can be reduced to the hardness of the discrete logarithm problem. In particular, we show Pedersen's DKG to be sufficient for the construction of a threshold Schnorr signature scheme. Finally, we observe an interesting trade-off between security (reductions), computation, and communication that arises when comparing Pedersen's DKG protocol with ours.     

Support vector machine-based expert system for reliable heartbeat recognition

This paper presents a new solution to the expert system for reliable heartbeat recognition. The recognition system uses the support vector machine (SVM) working in the classification mode. Two different preprocessing methods for generation of features are applied. One method involves the higher order statistics (HOS) while the second the Hermite characterization of QRS complex of the registered electrocardiogram (ECG) waveform. Combining the SVM network with these preprocessing methods yields two neural classifiers, which have been combined into one final expert system. The combination of classifiers utilizes the least mean square method to optimize the weights of the weighted voting integrating scheme. The results of the performed numerical experiments for the recognition of 13 heart rhythm types on the basis of ECG waveforms confirmed the reliability and advantage of the proposed approach.     

Exposure of Human Models in the Near and Far Field?A Comparison

The specific absorption rate (SAR) was measured in over 650 locations in a full-scale model of man exposed in the far and near field of antennas at 350 and 915 MHz. The whole-body average, the body-parts average, and the distributions of the SAR's are compared for three wave polarizations for the far and the near-field exposures. Effects on the energy deposition of the antenna type, gain, and location in the near field are discussed.     

Energy Deposition in a Model of Man: Frequency Effects

A computer-controlled scanning system and implantable, nonperturbing electric field probes were used to measure spatial distributions of the electric field in a full scale homogeneous model of a human body. The measurements were performed at three frequencies (160, 350, and 915 MHz) in the far-field and in the near-field of resonant dipoles. The specific absorption rate (SAR) distributions and the averages for body parts and the whole body are analyzed as functions of frequency. In the far-field, the SAR decreases exponentially in the direction of wave propagation in the torso at all frequencies, and large gradients of the SAR are observed along the body main axis, particularly for the E polarization. At 160 and 350 MHz high local SAR's are produced in the neck. It appears that for plane wave exposures the ratio of the peak SAR to the whole-body average SAR does not exceed 20. In the near-field, large SAR gradients are also produced, and the ratios of the peak spatial SAR to the whole-body average SAR vary from about 30 to 250 depending on the frequency and polarization. It is suggested that for near-field exposures the whole-body average SAR is not a proper dosimetric measure, and the SAR averaged over any 0.1 of the tissue volume is recommended instead.     

Carbon fibers modified with carbon nanotubes

Carbon nanotubes were used to modify a polyacrylonitrile (PAN) polymer solution before the manufacture of the carbon fiber precursor. The modified PAN fibers were spun from a dimethylformamide solution containing a small amount of single-walled carbon nanotubes. The fibers were characterized by thermogravimetry and optical and scanning electron microscopy. Structure, morphology, and selected properties of the composite polymeric fibers and the fibers after carbonization are characterized. The mechanical properties of the fibers are examined. It is found that nanotubes in the PAN solution have a strong tendency to form agglomerates that inhibit suitable macromolecular chain orientation of the carbon fiber precursor. Fibers manufactured from such a solution have similar mechanical properties to those from a pure PAN precursor, and after carbonization the resultant carbon fibers are very weak. A comparison of pure carbon fibers and those containing nanotubes reveals slight differences in their structural ordering.     

On the dynamic self-diffraction in methylene blue-sensitised gelatine

Dynamic self-diffraction processes have been observed and analysed for methylene blue-sensitised water-swollen gelatine (MBSG). A degenerate two-wave mixing experiment performed on thick samples of MBSG with 10 mW, 632.8 nm wavelength He Ne laser light allowed for the formation of phase- and amplitude-transient holographic gratings. Single-beam propagation characteristics through MBSG were measured with a Mach-Zehnder interferometer. The observed energy transfer between the writing beams in the two-beam coupling experiment and the considerable temporal oscillations of diffraction efficiency are explained by simple formulae. Two processes are considered: the time-dependent phase shift between the writing beams and the transverse self-phase modulation effects (self-focusing and interference ring formation).     

Über definierte Polyoxyäthylenderivate. V. [1] Stickstoffhaltige Polyoxyäthylene

On Defined Polyethylene Oxide Adducts. V. Nitrogen Containing Polyethylene Oxide Adducts The authors report on the synthesis and properties of longchain α-hydro-ω-N-alkylamino-polyoxyethylenes, there methylethers, and of α-hydro-ω-N-dodecylacetamidopolyoxyethylenes. Special surface properties as solubility, surface activity and micel formation are discussed.     

Prediction of the structures of proteins with the UNRES force field, including dynamic formation and breaking of disulfide bonds

The presence of disulfide bonds is essential for maintaining the structure and function of many proteins. The disulfide bonds are usually formed dynamically during folding. This process is not accounted for in present algorithms for protein-structure prediction, which either deduce the possible positions of disulfide bonds only after the structure is formed or assume fixed disulfide bonds during the course of simulated folding. In this work, the conformational space annealing (CSA) method and the UNRES united-residue force field were extended to treat dynamic formation of disulfide bonds. A harmonic potential is imposed on the distance between disulfide-bonded cysteine side-chain centroids to describe the energetics of bond distortion and an energy gain of 5.5 kcal/mol is added for disulfide-bond formation. Formation, breaking and rearrangement of disulfide bonds are included in the CSA search by introducing appropriate operations; the search can also be carried out with a fixed disulfide-bond arrangement. The algorithm was applied to four proteins: 1EI0 (alpha), 1NKL (alpha), 1L1I (beta-helix) and 1ED0 (alpha + beta). For 1EI0, a low-energy structure with correct fold was obtained both in the runs without and with disulfide bonds; however, it was obtained as the lowest in energy only with the native disulfide-bond arrangement. For the other proteins studied, structures with the correct fold were obtained as the lowest (1NKL and 1L1I) or low-energy structures (1ED0) only in runs with disulfide bonds, although the final disulfide-bond arrangement was non-native. The results demonstrate that, by including the possibility of formation of disulfide bonds, the predictive power of the UNRES force field is enhanced, even though the disulfide-bond potential introduced here rarely produces disulfide bonds in native positions. To the best of our knowledge, this is the first algorithm for energy-based prediction of the structure of disulfide-bonded proteins without any assumption as to the positions of native disulfides or human intervention. Directions for improving the potentials and the search method are suggested.