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81.
Intentionally undoped n-type and high purity Ga1?xAlxAs alloys with compositions in the range 0.19≤x≤0.78 are found to show a long life time photoconductivity effect at low temperatures (T < 80 K) when irradiated with white light filtered through a Ge filter and also when the light source is removed after photoexcitation. For the direct gap materials (0≤x≤ 0.43), it is shown that the deep level in the alloys, which controls the electrical properties of the crystals, captures and emits electrons via the first higher energy subsidiary conduction band inima L although the Γ minimum is the lowest in energy. These indirect electron transitions by the deep level, via the L minima, which is found to have an acceptor like nature, provide a natural explanation of the photoconductivity storage at low temperatures. For indirect gap materials (x > 0.43), when X minima are the lowest energy subsidiary minima, the photoconductivity storage at low temperatures is due to the double acceptor nature of the deep level.  相似文献   
82.
High cycle fatigue tests in vacuum have been performed on ordered (Fe, Co, Ni)3V alloys between 25 °C and 850 °C. Heat-to-heat variations in fatigue properties of a Co-16.5 wtpct Fe-25 pct alloy, LRO-1, appeared to be due to differing quantities of grain boundary precipitates. Modification of this alloy with 0.4 pct Ti, to produce an alloy designated LRO-23, reduced the density of grain boundary precipitates and increased ductility, resulting in superior fatigue strength at high temperatures. The fatigue lives of LRO-1 and LRO-23 decreased rapidly above 650 °C, and increased intergranular failure was noted. The fatigue resistance of a cobalt-free alloy, Fe-29 pct Ni-22 pct V-0.4 pct Ti (LRO-37), was examined at 25 °C, 400 °C, and 600 °C; there was little evidence for intergranular fracture at any of these temperatures. Fatigue behavior of the LRO alloys is compared to that of conventional high temperature alloys.  相似文献   
83.
84.
A new poly(vinylchloride) (PVC) membrane electrode for trace level determination of Co2+ ions has been developed based on 5-amino-3-methylisothiazole as an ionophore, o-nitrophenyloctylether as a plasticizer and oleic acid (OA) as a good lipophilic additive. The electrode exhibits a Nernstian slope of 29.5 ± 0.2 mV/decade in a linear range of 1.0 × 10−1 to 6.3 × 10−7 M for Co2+ ions. The detection limit of this electrode is 3.9 × 10−7 M. It has a fast response time of 12 s and can be used for a period of 4 months without any divergence in potentials. The proposed electrode reveals a good selectivity for Co (II) over a wide variety of other tested cations and could be used in the pH range 3.3–9.0. The electrode was successfully applied as an indicator electrode for the potentiometric titration of cobalt ions with EDTA as well as for the direct determination of Co (II) in real samples.  相似文献   
85.
86.
Polycrystalline SnO2 samples prepared in the laboratory were irradiated with 2 MeV He ions having doses of 3.62 × 1015 ion/cm2. The ac small-signal electrical data acquired for the polycrystalline SnO2 in the frequency (f) range 100 Hz ≤ f ≤ 1 MHz and temperature (T) range 26°C ≤ T ≤ 100°C revealed one semicircular relaxation in the impedance plane for the He implanted sample. However, two semicircular relaxations were obtained in the same plane for the samples without He implantation. The He implantation indicated enhancement in the donor density in the polycrystalline SnO2 as depicted via terminal conductance (or resistance). An erratum to this article can be found at  相似文献   
87.
A novel manifold learning approach is presented to efficiently identify low-dimensional structures embedded in high-dimensional MRI data sets. These low-dimensional structures, known as manifolds, are used in this study for predicting brain tumor progression. The data sets consist of a series of high-dimensional MRI scans for four patients with tumor and progressed regions identified. We attempt to classify tumor, progressed and normal tissues in low-dimensional space. We also attempt to verify if a progression manifold exists—the bridge between tumor and normal manifolds. By identifying and mapping the bridge manifold back to MRI image space, this method has the potential to predict tumor progression. This could be greatly beneficial for patient management. Preliminary results have supported our hypothesis: normal and tumor manifolds are well separated in a low-dimensional space. Also, the progressed manifold is found to lie roughly between the normal and tumor manifolds.  相似文献   
88.
Machine learning has emerged as an effective medical diagnostic support system. In a medical diagnosis problem, a set of features that are representative of all the variations of the disease are necessary. The objective of our work is to predict more accurately the presence of cardiovascular disease with reduced number of attributes. We investigate intelligent system to generate feature subset with improvement in diagnostic performance. Features ranked with distance measure are searched through forward inclusion, forward selection and backward elimination search techniques to find subset that gives improved classification result. We propose hybrid forward selection technique for cardiovascular disease diagnosis. Our experiment demonstrates that this approach finds smaller subsets and increases the accuracy of diagnosis compared to forward inclusion and back-elimination techniques.  相似文献   
89.
A high-manganese austenitic steel matrix composite (Fe-1.42%C-16.02%Mn-0.447%Si-0.288%Al-0.34%Cr-0.028%S-0.25%P-3.02%Ti-3.0%W, all in wt.%) reinforced with in-situ (Ti,W)C was synthesized by conventional melting and casting route. It has been found that the concentration of Ti decreases whereas the concentration of tungsten increases from core to the periphery of the (Ti,W)C particulates. The abrasive wear resistance of as-cast (Ti,W)C-reinforced composite is better than that of the as-cast high-manganese austenitic steel matrix material.  相似文献   
90.
Electrolytic process, employed for manufacturing basic chemicals like caustic soda and chlorine, is highly energy intensive. Due to escalating costs of fossil fuels and capacity addition, the electricity cost has been increasing for the last few decades. Electricity intensive industries find it very difficult to cope up with higher electricity charges particularly with time-of-use (TOU) tariffs implemented by the utilities with the objective of flattening the load curve. Load management programs focusing on reduced electricity use at the time of utility's peak demand, by strategic load shifting, is a viable option for industries to reduce their electricity cost. This paper presents an optimization model and formulation for load management for electrolytic process industries. The formulation utilizes mixed integer nonlinear programming (MINLP) technique for minimizing the electricity cost and reducing the peak demand, by rescheduling the loads, satisfying the industry constraints. The case study of a typical caustic-chlorine plant shows that a reduction of about 19% in the peak demand with a corresponding saving of about 3.9% in the electricity cost is possible with the optimal load scheduling under TOU tariff.  相似文献   
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