99mTc-citrate versus 67Ga-citrate for the scintigraphic visualization of inflammatory lesions

Citric acid was labeled with 99mTc with an efficiency of > 99%. The biodistribution of 99mTc-citrate was studied in mice with turpentine-induced abscesses in comparison to 67Ga-citrate. The max. abscess/muscle concentration ratios were 4.61 +/- 1.92 (3 h) for 99mTc-citrate and 4.76 +/- 2.04 (4 h) for 67Ga-citrate. Arthritis was induced in 10 rabbits by intra-articular injection of ovalbumin Scintigrams obtained 4 days later and at 3 h post-injection of 99mTc-citrate showed increased activity involving the synovium. The max. arthritic/contralateral knee ratio was 3.19 +/- 1.29 (3 h) and 6.47 +/- 3.71 (24 h) for 99mTc- and 67Ga-citrate, respectively. The blood clearance curve of 99mTc-citrate in rabbits was biexponential with a fast (T1/2 = 36 min) and a slow (T1/2 = 18 h) component, compared to mono-exponential clearance of 67Ga-citrate (T1/2 = 23 h). In 10 patients with rheumatoid arthritis whole-body scintigrams and spot images of involved joints indicated localization of the tracer in inflamed tissues. The mean target-to-soft tissue ratios were 3.04 +/- 0.81 and 4.95 +/- 2.56 for 99mTc-citrate and 99mTc-MDP, respectively. Renal clearance of radioactivity was evident from the scintigrams. Our results demonstrated that 99mTc-citrate is effective as a radiopharmaceutical for the visualization of inflammatory lesions and may be preferred to 67Ga-citrate due to the ideal physical characteristics of the radionuclide, easy preparation, low cost, early accumulation and the preference for the renal route of excretion.     

A multi-agent based approach for change management in manufacturing enterprises

Change management becomes an unavoidable necessity for manufacturing enterprises. Since change in business processes carries significant impact on the performance of manufacturing companies, a change management model is definitely required to remain competitive. Moreover, utilizing agent based systems will provide computational provision and integrity to manage and measure the capabilities to follow the change in a progressive approach by employing the cooperation and collaboration properties of various agents helping for retrieval of the required information in a rapid way. Therefore, in this paper, a multi-agent based change management model is proposed to handle the changes in manufacturing enterprises. The model is validated through a case study done to measure the performance of change management capabilities in a manufacturing company. A sensitivity analysis on the results of this case study is also conducted to reveal the system reactivity to various parameters.     

A numerical approach to the cooling curves of porous P/M materials for quenching process

The software is developed in FORTRAN to obtain the cooling curves of powder metallurgy (P/M) of porous materials. The software is written in two-dimensional form and in cylindrical coordinates. The thermal conductivity of the porous materials is obtained using empirical correlations given in the literature. The natural convection, nucleate boiling and film boiling processes without and with radiation are considered in the analysis. The heat transfer coefficients on vertical and horizontal surfaces are calculated using the empirical correlations given in the literature. Energy equations are solved using the control volume method, but the effect of pore geometries is not considered in the analysis. Examples of the cooling curves are given for plain carbon steel with the water as the quenchant for 2.5%, 5%, 10%, 15% and 20% porosities. It is shown that the software can be used for different quenchants and the porous materials with different geometries.     

Ensuring location diversity in privacy-preserving spatio-temporal data publishing

The rise of mobile technologies in the last decade has led to vast amounts of location information generated by individuals. From the knowledge discovery point of view, these data are quite valuable, but the inherent personal information in the data raises privacy concerns. There exists many algorithms in the literature to satisfy the privacy requirements of individuals, by generalizing, perturbing, and suppressing their data. Current techniques that try to ensure a level of indistinguishability between trajectories in a dataset are direct applications of \(k\) -anonymity, thus suffer from the shortcomings of \(k\) -anonymity such as the lack of diversity in sensitive regions. Moreover, these techniques fail to incorporate some common background knowledge, an adversary might have such as the underlying map, the traffic density, and the anonymization algorithm itself. We propose a new privacy metric \(p\) -confidentiality that ensures location diversity by bounding the probability of a user visiting a sensitive location with the \(p\) input parameter. We perform our probabilistic analysis based on the background knowledge of the adversary. Instead of grouping the trajectories, we anonymize the underlying map, that is, we group nodes (points of interest) to create obfuscation areas around sensitive locations. The groups are formed in such a way that the parts of trajectories entering the groups, coupled with the adversary background, do not increase the adversary’s belief in violating the \(p\) -confidentiality. We then use the map anonymization as a model to anonymize the trajectories. We prove that our algorithm is resistant to reverse-engineering attacks when the statistics required for map anonymization is publicly available. We empirically evaluate the performance of our algorithm and show that location diversity can be satisfied effectively.     

Optimization of specific energy consumption for Bomaplex Red CR-L dye removal from aqueous solution by electrocoagulation using Taguchi-neural method

In this investigation, firstly, Taguchi method was applied to determine the optimum specific energy consumption (SEC) for dye removal from aqueous solution by electrocoagulation using aluminum electrodes. An orthogonal array (OA₁₆) experimental design that allows to investigate the simultaneous variations of five parameters (Initial dye concentration, Initial pH of the solution, Supporting electrolyte concentration, Supporting electrolyte type and Current density) having four levels was employed to evaluate the effects of experimental parameters with two replicates. According to Taguchi-neural method, while the optimum conditions that dye removal efficiency equals to 62.71 % were found to be initial dye concentration 600 mg/L, initial pH of the solution 6, supporting electrolyte concentration 7.0 mM, supporting electrolyte type NaCl, and current density 0.10 mA/cm². Under these optimum conditions, energy consumption is 0.38 kW h/m³. Alternatively, it can be said that optimum conditions can be modified as follows supporting electrolyte concentration of 10.0 mM and supporting electrolyte type CaCl₂, for 600 mg/L, initial dye concentration initial pH of the solution 6, and current density 0.10 mA/cm². Under these optimum conditions, SEC and dye removal efficiency are 0.45 kW h/m³ and 69.18 %, respectively.     

Heuristic-based neural networks for stochastic dynamic lot sizing problem

Multi-period single-item lot sizing problem under stochastic environment has been tackled by few researchers and remains in need of further studies. It is mathematically intractable due to its complex structure. In this paper, an optimum lot-sizing policy based on minimum total relevant cost under price and demand uncertainties was studied by using various artificial neural networks trained with heuristic-based learning approaches; genetic algorithm (GA) and bee algorithm (BA). These combined approaches have been examined with three domain-specific costing heuristics comprising revised silver meal (RSM), revised least unit cost (RLUC), cost benefit (CB). It is concluded that the feed-forward neural network (FF-NN) model trained with BA outperforms the other models with better prediction results. In addition, RLUC is found the best operating domain-specific heuristic to calculate the total cost incurring of the lot-sizing problem. Hence, the best paired heuristics to help decision makers are suggested as RLUC and FF-NN trained with BA.     

Design optimization of circular antenna arrays using Taguchi method

This paper presents the application of Taguchi method (TM) to design optimization of non-uniform circular antenna array (CAA) for suppression of sidelobe levels (SLLs). TM, a robust design approach, takes signal-to-noise ratio and orthogonal array tools from the statistical design of experiments. These tools allow instead of full factorial parametric analysis minimize the design parameters; thus, increase the convergence speed and generate more accurate solutions. TM is used to determine an optimal set of amplitudes and positions of CAA for 8, 10, and 12 elements. Comparison of the results of the TM with those of latest meta-heuristic algorithms in the literature reveals that the CAA design with TM provides the best SLL reduction performance in all cases.

     

Can Dentin Surfaces Be Bonded Safely With Ozone and Boric Acid?

The aim of this study is to evaluate the effect of different cavity disinfectants on shear bond strength. In this study, 60 caries-free human molar teeth were used. Smooth dentin surfaces were revealed by cutting occlusal enamel and a standard smear layer was obtained by using 600-grid sandpaper. Specimens were randomly assigned to four groups according to the disinfectant used: Group 1: Control (no disinfectant); Group 2: Ozone; Group 3: Chlorhexidine, Group 4: Boric acid. Specimens were bonded using S3 Plus Bond and the composite buildups were created by using composite resin according to the manufacturer’s instructions. After specimens were kept for 24 h, at 37 °C in distilled water, the shear bond strength test was measured with a universal test machine. The highest bond strength values were observed in the control group. The bond strength was significantly lower in the chlorhexidine, and boric acid-treated groups than it was in the control group (respectively, p = 0.046 and p = 0.028); however, no significant difference in the bond strength was observed between the ozone group and the control group (p = 0.444). The ozone group was detected as having the best shear bond strength values in groups which were applied to cavity disinfectants.     

Artificial neural network models for lot-sizing problem: a case study

Lot-sizing is one of the most difficult problems in production planning. The main purpose of this study is to propose a new lot-sizing based on artificial neural network (ANN), which may lead to a better performance than commonly used lot-sizing heuristics (SM, EOQ, PPB, LUC, and LTC). The data obtained are the results of years 2004 thru 2009 for 186 different types of stock items from the 2nd Air Supply and Maintenance Centre Command, a state-funded factory in Kayseri, Turkey. Factual data were applied under the coverage of the study, and the system from which the data have been obtained is still in live and active status. In the study, the purchasing costs, holding costs, and set-up costs were taken into consideration. These data were obtained from the administration data system of the enterprise. The solutions of this lot-sizing heuristics were found by WinQSB software accordingly. The ANN was constituted by using the NeuroSolutions software. The criterion of deviation from the optimum solution and the criterion of percentage of times obtaining the optimum order pattern were taken into account for the comparison purposes. The performance values of 400 ANNs were compared to lot-sizing methods. MS Excel and Visual Basic Macro were utilized for all calculations applied after this stage. The results showed that the proposed ANN-based method outperformed all lot-sizing methods taken into account in this study.