Effects of circumferential pick spacing on boom type roadheader cutting head performance

Effects of equal and unequal circumferential pick spacing on the performance of boom type roadheaders having cylindrical cutting heads are investigated. For this purpose, two experimental cutting heads with equal and unequal circumferential spacing are designed and manufactured. The cutting head with unequal circumferential spacing is specifically designed to prevent tool-holder overlap at the nose section. Manufacturing difficulties associated with equal circumferential pick spacing due to tool-holder overlap are discussed with solid modeling and practical applications. The heads are tested at Park Cayirhan Coal Mine in Turkey and their cutting performances are analysed. Although better cutting performance for equal circumferential spacing are predicted by force–balance analysis, in situ measurements of instantaneous (net) traversing speed and cutting rate, pick consumption rate and machine vibration show that no significant difference exists between the performances of the two cutting heads.     

Identification of tubulin drug binding sites and prediction of relative differences in binding affinities to tubulin isotypes using digital signal processing

Microtubules are involved in numerous cellular processes including chromosome segregation during mitosis and, as a result, their constituent protein, tubulin, has become a successful target of several chemotherapeutic drugs. In general, these drugs bind indiscriminately to tubulin within both cancerous and healthy cells, resulting in unwanted side effects. However, differences between beta-tubulin isotypes expressed in a wide range of cell types may aid in the development of anti-tubulin drugs having increased specificity for only certain types of cells. Here, we describe a digital signal processing (DSP) method that is capable of predicting hot spots for the tubulin family of proteins as well as determining relative differences in binding affinities to these hot spots based only on the primary sequence of 10 human tubulin isotypes. Due to the fact that several drug binding sites have already been characterized within beta-tubulin, we are able to correlate hot spots with the binding sites for known chemotherapy drugs. We have also verified the accuracy of this method using the correlation between the binding affinities of characterized drugs and the tubulin isotypes. Additionally, the DSP method enables the rapid estimation of relative differences in binding affinities within the binding sites of tubulin isotypes that are yet to be experimentally determined.     

Photoconductivity and photoluminescence under bias in GaInNAs/GaAs MQW p-i-n structures

The low temperature photoluminescence under bias (PLb) and the photoconductivity (PC) of a p-i-n GaInNAs/GaAs multiple quantum well sample have been investigated. Under optical excitation with photons of energy greater than the GaAs bandgap, PC and PLb results show a number of step-like increases when the sample is reverse biased. The nature of these steps, which depends upon the temperature, exciting wavelength and intensity and the number of quantum wells (QWs) in the device, is explained in terms of thermionic emission and negative charge accumulation due to the low confinement of holes in GaInNAs QWs. At high temperature, thermal escape from the wells becomes much more dominant and the steps smear out.     

Photoinduced electron transfer mechanism between green fluorescent protein molecules and metal oxide nanoparticles

Green fluorescent protein (GFP) molecules are attached to titanium dioxide and cadmium oxide nanoparticles via sol–gel method and fluorescence dynamics of such a protein–metal oxide assembly is investigated with a conventional time correlated single photon counting technique. As compared to free fluorescent protein molecules, time-resolved experiments show that the fluorescence lifetime of GFP molecules bound to these metal oxide nanoparticles gets shortened dramatically. Such a decrease in the lifetime is measured to be 22 and 43 percent for cadmium oxide and titanium dioxide respectively, which is due to photoinduced electron transfer mechanism caused by the interaction of GFP molecules (donor) and metal oxide nanoparticles (acceptor). Our results yield electron transfer rates of 3.139×10⁸ s⁻¹ and 1.182×10⁸ s⁻¹ from the GFP molecules to titanium dioxide and cadmium oxide nanoparticles, respectively. The electron transfer rates show a marked decrease with increasing driving force energy. This effect represents a clear example of the Marcus inverted region electron transfer process.     

Efficient manganese decorated cobalt based catalysts for hydrogenation of 5-hydroxymethylfurfural (HMF) to 2,5-dimethylfuran (DMF) biofuel

2,5-dimethylfuran (DMF) is a promising compound in the production of biofuel with high-quality properties. In this study, it is aimed to develop new efficient catalysts to synthesize DMF from 5-hydroxymethylfurfural (HMF). Co, Mn/Co, and Ru/Co catalysts were prepared using the NaBH₄ reduction method. The catalysts were subjected to activity tests for the hydrogenation of HMF to DMF by changing the reaction parameters, such as temperature and time. Mn/Co catalysts prepared from metal precursors at various molar ratios of Mn/Co were found to be effective in hydrogenation reactions of HMF to DMF. A 91.8% DMF yield was achieved in the presence of a Mn/Co (50/50) catalyst without noble metal at 180°C for 4 hours. The Brunauer-Emmet-Teller (BET) method, x-ray diffraction (XRD), x-ray photoelectron spectroscopy (XPS), and induction coupled plasma mass spectroscopy (ICP-MS) techniques were used to characterize the efficient Mn/Co catalyst.     

A statistical analysis of wind power density based on the Weibull and Rayleigh models at the southern region of Turkey

The electric generating capacity of Turkey must be tripled by 2010 to meet Turkey’s electric power consumption, if the annual 8% growth in electric power consumption continues. Turkey has to make use of its renewable energy resources, such as wind and solar, not only to meet the increasing energy demand, but also for environmental reasons. Studies show that Iskenderun (36°35′N; 36°10′E) located on the Mediterranean coast of Turkey is amongst the possible wind energy generation regions. In the present study, the wind energy potential of the region is statistically analyzed based on 1-year measured hourly time-series wind speed data. The probability density distributions are derived from time-series data and distributional parameters are identified. Two probability density functions are fitted to the measured probability distributions on a monthly basis. The wind energy potential of the location is studied based on the Weibull and the Rayleigh models.     

Highly scalable and robust rule learner: performance evaluation and comparison.

Business intelligence and bioinformatics applications increasingly require the mining of datasets consisting of millions of data points, or crafting real-time enterprise-level decision support systems for large corporations and drug companies. In all cases, there needs to be an underlying data mining system, and this mining system must be highly scalable. To this end, we describe a new rule learner called DataSqueezer. The learner belongs to the family of inductive supervised rule extraction algorithms. DataSqueezer is a simple, greedy, rule builder that generates a set of production rules from labeled input data. In spite of its relative simplicity, DataSqueezer is a very effective learner. The rules generated by the algorithm are compact, comprehensible, and have accuracy comparable to rules generated by other state-of-the-art rule extraction algorithms. The main advantages of DataSqueezer are very high efficiency, and missing data resistance. DataSqueezer exhibits log-linear asymptotic complexity with the number of training examples, and it is faster than other state-of-the-art rule learners. The learner is also robust to large quantities of missing data, as verified by extensive experimental comparison with the other learners. DataSqueezer is thus well suited to modern data mining and business intelligence tasks, which commonly involve huge datasets with a large fraction of missing data.     

A new synaptic plasticity rule for networks of spiking neurons

In this paper, we describe a new Synaptic Plasticity Activity Rule (SAPR) developed for use in networks of spiking neurons. Such networks can be used for simulations of physiological experiments as well as for other computations like image analysis. Most synaptic plasticity rules use artificially defined functions to modify synaptic connection strengths. In contrast, our rule makes use of the existing postsynaptic potential values to compute the value of adjustment. The network of spiking neurons we consider consists of excitatory and inhibitory neurons. Each neuron is implemented as an integrate-and-fire model that accurately mimics the behavior of biological neurons. To test performance of our new plasticity rule we designed a model of a biologically-inspired signal processing system, and used it for object detection in eye images of diabetic retinopathy patients, and lung images of cystic fibrosis patients. The results show that the network detects the edges of objects within an image, essentially segmenting it. Our ultimate goal, however, is not the development of an image segmentation tool that would be more efficient than nonbiological algorithms, but developing a physiologically correct neural network model that could be applied to a wide range of neurological experiments. We decided to validate the SAPR by using it in a network of spiking neurons for image segmentation because it is easy to visually assess the results. An important thing is that image segmentation is done in an entirely unsupervised way.     

The problem of how to optimize the speed control loop in the electric drives of the direct current

A procedure for calculating and implementing a speed slave control system (SCS) taking into consideration nontraditional small time constants is presented. This procedure permits one to significantly increase the dynamic factors of speed-control quality in the development of control and disturbing actions.     

Optical gain in 1.3-μm electrically driven dilute nitride VCSOAs

We report the observation of room-temperature optical gain at 1.3 μm in electrically driven dilute nitride vertical cavity semiconductor optical amplifiers. The gain is calculated with respect to injected power for samples with and without a confinement aperture. At lower injected powers, a gain of almost 10 dB is observed in both samples. At injection powers over 5 nW, the gain is observed to decrease. For nearly all investigated power levels, the sample with confinement aperture gives slightly higher gain.