Small‐sized probe for local measuring electrical properties of the tissues inside of human body: design,modelling and simulation

In this study, a new idea is suggested for designing an appropriate bio‐impedance probe in the form of a biopsy forceps to measure the electrical properties of the tissues inside the body. First, by analytically solving the Laplace equation for wedge‐shaped tissue in the mouth of the probe, the relationship between electric potential (results from excitation current) in a different point on the tissue and the electrical properties of the tissue is obtained. Then, to evaluate the designed bio‐impedance probe using the finite element method and the experimental data obtained for different tissues by Gabriel et al., modelling and simulation at different frequencies from 50 Hz to 5 MHz were done. Finally, to evaluate the performance of the designed probe in comparison to other methods, measurements were carried out using three methods for the same tissue. Nyquist curves were drawn and electrical properties extracted for all the three methods. It was found that the designed probe results are close to the actual values with an error of <2%. The main features of the designed probe are small size and non‐invasive measurement.Inspec keywords: Laplace equations, biological tissues, finite element analysis, electric impedance measurement, bioelectric potentials, biomedical measurementOther keywords: noninvasive measurement, local measuring electrical properties, human body, wedge‐shaped tissue, electric potential, finite element method, bio‐impedance probe, small‐sized probe, biopsy forceps, excitation current, Nyquist curves, frequency 50.0 Hz to 5.0 MHz     

Bioimpedance sensor to detect water content in milk based on van Der Pauw method

Milk fraud poses serious problems for the dairy industry and consumers'' health. The main aim of this study was to reveal the effect of water added to milk by measuring its electrical impedance spectrum. The required sensor was designed based on the van der Pauw method to measure the electrical conductivity of milk at the frequency band of 10 Hz to 5 MHz. The bioimpedance spectrum of the milk of five different cows showed that the electrical impedance spectrum has a high potential for detecting water added to the milk (P < 0.01). The area under the Nyquist curve was introduced as a suitable index to detect water‐added milk. In addition, the characteristic frequency of the bioimpedance spectrum was used as an important index to differentiate water‐added milk from waterless milk. An electrical model was introduced to interpret the amount of water added to the milk using the characteristic frequency. Results showed that it is possible to detect raw milk from boiled milk by measuring its electrical impedance.     

Synthesis,Characterization and Biological Evaluation of a New Sol-Gel Derived B and Zn-Containing Bioactive Glass: <Emphasis Type="Italic">In Vitro</Emphasis> Study

In this study we employed the sol-gel method to synthesize new CaO–P₂O₅–SiO₂–ZnO–B₂O₃ bioactive glasses. Three samples with various B₂O₃ content (5, 10 and 15 mol %) was prepared and their bioactivity were evaluated by immersion in simulated body fluid (SBF) and the glasses were characterized using X-ray diffraction (XRD), Fourier transform infrared (FTIR) and scanning electron microscopy (SEM). The experimental results revealed that with increasing the amount of boron content, a more crystalline domain can be observed in their XRD patterns and consequently the formation of hydroxyapatite (HA) increased. FTIR spectra showed that the sample containing 10 mol% of boron had the sharpest peaks attributed to the formation of hydroxyapatite. Biocompatibility of the samples was examined by MTT assay and alkaline phosphatase activity. The result ascertained that the synthesized bioactive glass had good biocompatibility and can serve as a bone substitute in bone defects.     

Classification of bananas during ripening using peel roughness analysis—An application of atomic force microscopy to food process

To monitor banana surface (peel) roughness changes during ripening treatment, atomic force microscopy (AFM) as a novel and emerging technique was used in this study. The roughness of banana peel was studied using the arithmetic mean between peaks and troughs (R_a) and the root-mean-square roughness (R_q). It was concluded that with changing the ripening stages, the behavior of the roughness changes significantly. With advancing fruit ripening, the extending of the epicarp and the decrease of the surface (peel) roughness were found due to enlarging of fruit volume. The highest mean roughness was found to be at stage 1, R_a = 8.25 and R_q = 9.65 nm. Based on two-dimensional profile results, the surface (peel) roughness was affected strongly by studied different ripening stages. It was concluded that the peak values in the ripple profiles become smaller with advancing fruit ripening. However, the effects of noise in the profiles appeared to increase. So, in all the initial stages of banana fruit ripening, the noise was found to be minimal. Consequently, the AFM technique was found to be a promising tool for quantification of the peel roughness or glossiness and also could help in the quality control of banana fruit on the nanoscale.     

Calculating the required cash in bank branches: a Bayesian-data mining approach

The issue of sufficiency of cash in bank branches is considered as an important issue especially for branch managers; because, not only the insufficiency of daily cash results in lack of response to needs of customers, but also may its excess result in increase in costs for banks. Hence, banks are always attempting to determine their required cash based on their daily operation. For this purpose, in this paper, 18 branches of a certain bank in a period of five months, due to diversity of the branches, have been classified by two methods of hierarchical clustering and Bayesian hierarchical clustering in similar clusters, and then by considering the results obtained from clustering, amounts of entered and consumed branch cash have been estimated by neural network (via classic and Bayesian approach), so that the cash required by branches can be calculated. The error criteria of the estimates show that calculations by applying Bayesian neural network method with considering Bayesian clustering have the least error compared to other methods.