Preparation of dye sensitized titanium oxide nanoparticles for solar cell applications

A new method for synthesis of titanium dioxide (TiO₂)-dye nanoparticles is reported. TiO₂ nanocrystals were obtained at 150 and 200 °C by using chemically bonded TiO₂-sensitizer dye as a precursor. Titanium tetraisopropoxide was first modified with a dye molecule and then precipitated by dropping into acidic water. A strongly colored precipitate was obtained. Hydrothermal growth of a colloidal solution was carried out in a Teflon-lined stainless steel autoclave. Dye sensitized solar cell efficiencies obtained were comparable and fill factor values were close to the analogous cells prepared by the use of conventional TiO₂ paste techniques. This method allows the use of different substrates together with nanocrystalline TiO₂ for many technological applications.     

Ternary encoding based feature extraction for binary text classification

A novel framework for termset based feature extraction is proposed for binary text classification. The proposed approach is based on the encoding of the terms within a termset. The ternary codes ‘+1’ and ‘?1’ are used to represent the class that the term supports, whereas ‘0’ denotes no support to any of the classes. Four different encoding schemes are proposed where the term weights and the term occurrence probabilities in the positive and negative documents are used to define the ternary code of a given term. The ternary patterns are utilized to define novel features by splitting them into positive and negative codes where each code is treated as a different feature extractor. Use of the derived features individually and together with bag of words representation are both investigated. The histograms of the resultant features are also employed to study the improvements that can be achieved using a small number of additional features to augment bag of words representation. Experiments conducted on four benchmark datasets with different characteristics have shown that the proposed feature extraction framework provides significant improvements compared to the bag of words representation.     

THE EFFECT ON THE THERMAL EFFICIENCY OF LIME ADDED TO THE COMBUSTION CHAMBER FOR RETENTION ON SULPHUR

ABSTRACT

In order to prevent the emission of SO_x, with the flue gas, certain amount of the sulphur of the coal can be retained by adding an adequate amount of lime in the combustion chamber. In this study, two series of experiments were conducted by adding lime at the molar ratios of CaO/S = 0·5 to 2·0 using Ankara-Beypazan lignites, which have around 5 % sulphur content as received form. In one of the series lime was added directly in to the lump coal, and in the other, coal was briquetted together with lime using molasses as binder. It was observed from the experimental results that the increase in the lime ratio leads to an increase in the retained sulphur percentage while it leads to a considerable decrease in thermal efficiency. In order to retain 50 % of sulphur, it was necessary to add lime into lump coal at a CaO/S molar ratio of at least 1,1. This minimum ratio was 0·70 for briquetted coal. When lime was added at these ratios, the thermal efficiencies in the first case dropped to as low as 82 % and to 92 % in the second.     

Lipoprotein Subfraction Profile and HDL-Associated Enzymes in Sickle Cell Disease Patients

Although hypocholesterolemia is a reported finding in sickle cell disease (SCD), low-density lipoprotein (LDL)/high-density lipoprotein (HDL) subfractions and HDL-associated enzymes have not been determined in SCD patients. Blood was collected from 38 hemoglobin (Hb)A volunteers and 45 homozygous HbSS patients who had not received blood transfusions in the last 3 months. Serum lipids were measured by automated analyzer while LDL and HDL subfraction analysis was done by continuous disc polyacrylamide gel electrophoresis. Serum levels of cholesteryl ester transfer protein (CETP), lecithin-cholesterol acyltransferase (LCAT), apolipoprotein B (apoB) and apolipoprotein A-1 (apoA-I) were determined by enzyme-linked immunosorbent assay (ELISA). Total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) levels were significantly decreased, while TG levels were significantly increased in SCD patients compared to controls. A significant decrease in intermediate-density lipoprotein (IDL)-C, IDL-B, IDL-A and LDL-1 fractions were seen in SCD patients, while no significant difference was observed in small dense LDL particles. A significant decrease was seen in HDL-large, HDL-intermediate and HDL-small fractions in SCD patients versus controls. Levels of LCAT and ApoA-1 protein measured in SCD patients were significantly lower while no significant difference was observed in CETP and ApoB protein levels compared to controls. The reduction observed in LDL- and HDL-C in SCD patients was reflected as significantly decreased IDL, LDL-1 and HDL-subfractions. Decreased HDL subfractions may possibly lead to the reduced ApoA-1 and LCAT protein levels observed in SCD patients.     

X-ray investigation of sintered cadmium doped hydroxyapatites

Pure and cadmium (Cd) doped hydroxyapatites (HA, Ca₁₀(PO₄)₆(OH)₂) were synthesized by a precipitation method from aqueous solutions of Ca(NO₃)₂4·H₂O for the former and Cd(NO₃)₂4·H₂O for the latter, by using (NH₄)₂HPO₄ as the phosphate source, while pH was kept in the range of 11–12. The effect of incorporation of Cd²⁺ ions into the structure of HA was investigated after the air sintering at 1100 °C for 1 h. The results indicate that Cd²⁺ addition into HA yields nearly fully densified products with respect to pure stoichiometric HA. The XRD patterns showed that Cd doping increases the crystallinity of HA. The 2, 4.4, and 8.8 mol% Cd doped HAs had calcium oxide (CaO) impurity phase in their lattice. The CaO phase in the HA structure gradually disappeared with increasing Cd amount, and was replaced with cadmium oxide (CdO) in the CdHA doped with 11 mol% Cd. Cd²⁺ ion incorporation decreased the a- and c-axis lattice constants and unit cell volume of HA.     

A decision support system for locating weapon and radar positions in stationary point air defence

In this study, a decision support system (DSS) based on the interactive use of location models and geographical information systems (GIS) was developed to determine the optimal positions for air defence weapons and radars. In the location model, the fire units are considered as the facilities to be located and the possible approach routes of air vehicles are treated as demand points. Considering the probability that fire by the units will miss the targets, the objective of the problem is to determine the positions that provide coverage of the approach routes of the maximum number of weapons while considering the military principles regarding the tactical use and deployment of units. In comparison with the conventional method, the proposed methodology presents a more reliable, faster, and more efficient solution. On the other hand, owing to the DSS, a battery commander who is responsible for air defence becomes capable of determining the optimal weapon and radar positions, among the alternative ones he has identified, that cover the possible approach routes maximally. Additionally, he attains the capability of making such decisions in a very short time without going to the field over which he will perform the defence and hence without being subject to enemy threats. In the decision support system, the digital elevation model is analysed using Map Objects 2.0, the mathematical model is solved using LINGO 4.0 optimization software, and the user interface and data transfer are supported by Visual Basic 6.0.     

Magnetic Properties of Zn1?x Ni x O (0.25≤x≤ 0.50) Prepared by Solid-State Reactions

In this study the origin of ferromagnetism in ZnO-based bulk systems has been investigated using Ni-doped ZnO samples, Zn_1−x Ni _x O with 0.25≤x≤0.50, prepared by solid-state reactions. The structural characterizations indicated that the Ni²⁺ ions almost uniformly distributed in all the samples, and the samples have hexagonal wurtzite structure; however, when x is increased toward 0.50, a new NiO phase is formed. A ferromagnetism (FM) has been observed for all the samples at and below the room temperature. In other words, the room temperature results of (M–H) curves show that the FM observed is intrinsic for all the Ni-doped ZnO samples. However, the saturated magnetizations decrease gradually with increasing Ni concentration. This indicates that, in addition to FM, the excessive doping of Ni in ZnO also causes an antiferromagnetic (AFM) contribution which increases with increasing Ni amount. This result is also supported by the magnetization against temperature measurements. Furthermore, the trend of the ac-susceptibility (χ) versus temperature curves, measured under an ac-magnetic field of 100 Oe, also support our conclusion about the antiferromagnetic contribution to ferromagnetism in our samples.     

Nonlinear transformation of term frequencies for term weighting in text categorization

In automatic text categorization, the influence of features on the decision is set by the term weights which are conventionally computed as the product of term frequency and collection frequency factors. The raw form of term frequencies or their logarithmic forms are generally used as the term frequency factor whereas the leading collection frequency factors take into account the document frequency of each term. In this study, it is firstly shown that the best-fitting form of the term frequency factor depends on the distribution of term frequency values in the dataset under concern. Taking this observation into account, a novel collection frequency factor is proposed which considers term frequencies. Five datasets are firstly tested to show that the distribution of term frequency values is task dependent. The proposed method is then proven to provide better F₁ scores compared to two recent approaches on majority of the datasets considered. It is confirmed that the use of term frequencies in the collection frequency factor is beneficial on tasks which does not involve highly repeated terms. It is also shown that the best F₁ scores are achieved on majority of the datasets when smaller number of features are considered.     

DEFINING TOPIC BOUNDARIES IN SEARCH ENGINE TRANSACTION LOGS USING GENETIC ALGORITHMS

This study proposes to use genetic algorithms for defining the topic boundaries in search of engine transaction logs. Users are interested in multiple topics during a search session, and genetic algorithms are used in this study to determine whether a search engine user has changed topics during a session. Sample data logs from FAST and Excite search engines were analyzed. The findings show that genetic algorithms are fairly successful in identifying topic continuations and shifts in search engine transaction logs.