The effect of liposome on dyeing mohair/wool blends

The aim of this study was to examine the use of liposome in the dyeing of wool and mohair fibres with acid dyestuffs. Soybean lecithin and cholesterol were used to form the liposome membrane utilised in the dyebath. Liposome production was performed according to the thin lipid layer method (Bangham Method) using a rotary evaporator. Two different forms of liposome were used for dyeing wool and mohair fibres. In its first form, liposome was utilised as an auxiliary agent, where it was added to a conventional dyebath at the beginning of the process. In its second form, dyes were encapsulated with liposome and then used in dyeing. The effects of these two different forms of liposome were compared with conventional dyeing. Dyeing was carried out at depths of shade of 0.5%, 1.0% and 2.0% using three different concentrations of liposome (0.33%, 0.66% and 1.33%). An analysis of K/S values, fastness to washing, and the alkali solubility of fibres was conducted. The fibre samples dyed in the presence of liposome exhibited very good fastness to light (grade 8). The wash fastness test results of the liposomal‐dyed samples were significantly better (grade 4‐5) than for those samples which were conventionally dyed. In the presence of liposome, the tensile strength of fibres was 20 gf, whereas it was 11 gf without liposomes.     

LC–MS/MS characterization,antidiabetic, antioxidative,and antibacterial effects of different solvent extracts of Anamur banana (Musa Cavendishii)

Food Science and Biotechnology - The main objective of this study was to examine the phenolic compounds and the antibacterial, antioxidant, anti-α-glucosidase and anti-α-amylase...     

Ytterbium (III) oxide reinforced novel TeO2–B2O3–V2O5 glass system: Synthesis and optical,structural, physical and thermal properties

Different samples of xTeO₂.(25-y)B₂O₃.zV₂O₅.yYb₂O₃ (or TBVY) new glass material were synthesized by the classical melt-quenching method. Structural, optical, physical, and thermal analyses of the synthesized glasses were performed in addition to Monte Carlo simulation to test radiation shielding properties. The results showed that increasing ratios of Yb₂O₃ (y = 0.0, 0.5, 1.0, and 1.5 mol%) produced monotonic density values of the synthesized glasses ranging from 4.70058 g cm^?3 to 5.01038 g cm^?3. XRD and FTIR analyses were used to confirm the glass structure of all samples. Optical transmittance and absorption parameters varied almost monotonically with increasing ratios of Yb₂O₃ indicating the ability to predict and control these properties using Yb₂O₃ additive. Furthermore, simulated radiation interaction parameters, such as attenuation coefficients and half-value layer, exhibited well-behaved dependence on the concentration ratio of the Yb₂O₃ additive. This approach to glass material synthesis demonstrate the useful synergetic effect of combining structural, optical, and radiation characteristics.     

Review of different classes of RFID authentication protocols

Radio-frequency identification (RFID) is an up-and-coming technology. The major limitations of RFID technology are security and privacy concerns. Many methods, including encryption, authentication and hardware techniques, have been presented to overcome security and privacy problems. This paper focuses on authentication protocols. The combination of RFID technology being popular but unsecure has led to an influx of mutual authentication protocols. Authentication protocols are classified as being fully fledged, simple, lightweight or ultra-lightweight. Since 2002, much important research and many protocols have been presented, with some of the protocols requiring further development. The present paper reviews in detail recently proposed RFID mutual authentication protocols, according to the classes of the authentication protocols. The protocols were compared mainly in terms of security, the technique that they are based on, protocols that the presented protocol has been compared with, and finally, the method of verifying the protocol. Important points of the comparisons were collected in two tables.

     

Structural,physical, and optical characterization of (Nd3+/Eu3+)-doped zinc-rich silica–borate glasses

In this study, zinc–silica–borate glass structures doped with rare earth (RE) oxides Eu₂O₃ and Nd₂O₃ were synthesized with classical melting–quenching technique. 60ZnO–10SiO₂–(30 – x)B₂O₃:xRE (x?=?0, 0.5, 1, 1.5 mol%) composition was chosen as the structure. The doping effect of two different rare earth oxides (individually) at different ratios was investigated according to the structural, physical, and optical properties of the glass structure. Structural properties of the synthesized glasses were determined with Fourier transform infrared (FTIR) device, and densities (ρ) and molar volumes (V_m) of the glasses were measured with Archimedes method, and optical properties were determined with UV–Visible (UV–Vis-NIR) device. FTIR results show that BO₃ units increased in all RE-doped glasses. While densities of the synthesized glasses varied between 3.755 and 3.941 g cm^??3, indirect bandgaps varied between 3.219 and 3.645 eV. The glass with the highest transmittance was the 1% Eu₂O₃-doped glass with a transmittance of 84%. While band edges shifted slightly toward short wavelengths in glasses doped with Nd₂O₃, they shifted to longer wavelengths in glasses doped with Eu₂O₃.

     

Detection of mitotic cells in breast cancer histopathological images using deep versus handcrafted features

One of the most important processes in the diagnosis of breast cancer, which is the leading mortality rate in women, is the detection of the mitosis stage at the cellular level. In literature, many studies have been proposed on the computer-aided diagnosis (CAD) system for detecting mitotic cells in breast cancer histopathological images. In this study, comparative evaluation of conventional and deep learning based feature extraction methods for automatic detection of mitosis in histopathological images are focused. While various handcrafted features are extracted with textural/spatial, statistical and shape-based methods in conventional approach, the convolutional neural network structure proposed on the deep learning approach aims to create an architecture that extracts the features of small cellular structures such as mitotic cells. Mitosis detection/counting is an important process that helps us assess how aggressive or malignant the cancer’s spread is. In the proposed study, approximately 180,000 non-mitotic and 748 mitotic cells are extracted for the evaluations. It is obvious that the classification stage cannot be performed properly due to the imbalanced numbers of mitotic and non-mitotic cells extracted from histopathological images. Hence, the random under-sampling boosting (RUSBoost) method is exploited to overcome this problem. The proposed framework is tested on mitosis detection in breast cancer histopathological images dataset provided from the International Conference on Pattern Recognition (ICPR) 2014 contest. In the results obtained with the deep learning approach, 79.42% recall, 96.78% precision and 86.97% F-measure values are achieved more successfully than handcrafted methods. A client/server-based framework has also been developed as a secondary decision support system for use by pathologists in hospitals. Thus, it is aimed that pathologists will be able to detect mitotic cells in various histopathological images more easily through necessary interfaces.

     

In situ image processing capabilities of ARM-based micro-controllers

Dealing with visual data is the key for environmental monitoring tasks in Wireless Multimedia Sensor Networks (WMSNs). Tasks such as object detection, recognition, and/or tracking do require extracting and using the right information from the inherently large amount of visual data. The widely accepted solution of legacy WSNs, transmitting the acquired data to a central base station for further processing, would render a WMSN totally useless because of the unacceptable use of bandwidth and energy. Therefore, we consider the in situ processing as a viable solution for WMSNs. However, processing power and memory capacity restrictions of existing multimedia sensor nodes along with their power consumption are the limiting factors for wide-spread use of in situ processing. Nevertheless, recent technological improvements and introduction of the new ARM cores encourage us to evaluate the image processing capabilities of ARM7/ARM9/ARM11 based micro-controllers for in situ processing in WMSNs. In this work, we first discussed the architectural design differences among the various ARM cores. Then we classified image processing algorithms into three categories. Then, we evaluated the performance of each microcontroller by running a set of basic image processing algorithms necessary for object detection, recognition, and/or tracking. The test results show that ARM11 runs up to 6–30 times faster than ARM9 and ARM7, respectively. Besides, ARM11 consumes up to 5–7 times less energy than ARM9 and ARM7 for the same type of operations.