Characterization of Critical Determinants of ACE2–SARS CoV-2 RBD Interaction

Despite sequence similarity to SARS-CoV-1, SARS-CoV-2 has demonstrated greater widespread virulence and unique challenges to researchers aiming to study its pathogenicity in humans. The interaction of the viral receptor binding domain (RBD) with its main host cell receptor, angiotensin-converting enzyme 2 (ACE2), has emerged as a critical focal point for the development of anti-viral therapeutics and vaccines. In this study, we selectively identify and characterize the impact of mutating certain amino acid residues in the RBD of SARS-CoV-2 and in ACE2, by utilizing our recently developed NanoBiT technology-based biosensor as well as pseudotyped-virus infectivity assays. Specifically, we examine the mutational effects on RBD-ACE2 binding ability, efficacy of competitive inhibitors, as well as neutralizing antibody activity. We also look at the implications the mutations may have on virus transmissibility, host susceptibility, and the virus transmission path to humans. These critical determinants of virus–host interactions may provide more effective targets for ongoing vaccines, drug development, and potentially pave the way for determining the genetic variation underlying disease severity.     

Computer‐aided classification of breast masses in mammogram images based on spherical wavelet transform and support vector machines

Breast cancer can be effectively detected and diagnosed using the technology of digital mammography. However, although this technology has been rapidly developing recently, suspicious regions cannot be detected in some cases by radiologists, because of the noise or inappropriate mammogram contrast. This study presents a classification of segmented region of interests (ROIs) as either benign or malignant to serve as a second eye of the radiologists. Our study consists of three steps. In the first step, spherical wavelet transform (SWT) is applied to the original ROIs. In the second step, shape, boundary and grey level based features of wavelet (detail) and scaling (approximation) coefficients are extracted. Finally, in the third step, malignant/benign classification of the masses is implemented by giving the feature matrices to a support vector machine system. The proposed system achieves 91.4% and 90.1% classification accuracy using the dataset acquired from the hospital of Istanbul University in Turkey and the free Mammographic Image Analysis Society, respectively. Furthermore, discrete wavelet transform, which produces 83.3% classification accuracy, is applied to the coefficients to make a comparison with the SWT method.     

Analyzing the effects of inventory cost setting rules in a disassembly and recovery environment

In this study we consider a disassembly and recovery facility receiving end-of-life products and facing demand for a specific part that is disassembled from the product and then recovered. The disassembly and recovery operations can be either performed before hand, or upon customer arrival. In the latter case, a discount on the selling price is applied to compensate the customer for waiting for the completion of the disassembly and recovery operations. One of the difficulties faced in planning for such a system is the determination of the opportunity cost associated with carrying recovered parts inventory. The difficulty arises in seeking the value added to the part given the costs incurred for maintaining the product return, disassembly and recovery costs and revenue earned from the hulk, that is the remaining product after the disassembly of the part. The main objective of the study is to investigate the effect of different rules to determine this opportunity cost on the performance of the system. Six rules are considered in the study. The performance of the rules is assessed by a computational study under an approximate inventory control policy.     

Kinetic analysis of photosynthetic growth,hydrogen production and dual substrate utilization by Rhodobacter capsulatus

Rhodobacter capsulatus is purple non-sulfur (PNS) bacterium which can produce hydrogen and CO₂ by utilizing volatile organic acids in presence of light under anaerobic conditions. Photofermentation by PNS bacteria is strongly affected by temperature and light intensity. In the present study we present the kinetic analysis of growth, hydrogen production, and dual consumption of acetic acid and lactic acid at different temperatures (20, 30 and 38 °C) and light intensities (1500, 2000, 3000, 4000 and 5000 lux). The cell growth data fitted well to the logistic model and the cumulative hydrogen production data fitted well to the Modified Gompertz Model. The model parameters were affected by temperature and light intensity. Lactic acid was found to be consumed by first order kinetics. Rate of consumption of acetic acid was zero order until most of the lactic acid was consumed, and then it shifted to first order. The results revealed that the optimum light intensities for maximum hydrogen production were 5000 lux for 20 °C and 3000 lux for 30 °C and 38 °C.     

A distribution network optimization problem for third party logistics service providers

Third party logistics service providers (3PLs) have an important role in supply chain management. Increasing cooperation with 3PLs is expanding in today’s business environment. Hence, 3PLs need to have an efficient distribution network to meet customer demands. Nevertheless, few researches have tried to propose a solution for distribution network problems of 3PLs. The optimization problem which is discussing in our study is solved in two stages. At the first stage, the assignment problem which includes assigning the order of the vehicles is solved with mixed integer programming by using GAMS 21.6/CPLEX. The output of the first stage is used as an input in the second stage. In this stage routes are determined for vehicles by developing a genetic algorithm by using C#.     

Determination of the Most Commonly Recognized and Used Keratin Based Luxury Fibers

There is a group of animal fibers known as “luxury fibers.” These are mohair, cashmere, camel hair, lama, alpaca, vicuna, guanaco, angora, yak, and quivit. In this study, the effects of demographical variables such as gender, education, age, sector, and income on the recognition and usage of luxury fibers in Thrace Region of Turkey were investigated. In order to analyze the obtained data, crosstabulation and chi-square statistical methods are used. According to the experimental results it can be said that the most commonly known and used luxury fibers are cashmere, mohair, and angora. The most important (37.6%) reason for participants to use luxury fibers is their warm feeling. On the other hand the most important (approx. 30%) reason for participants not to use them is that they do not have sufficient information about these fibers. It was determined that the most commonly (37.8%) used textile product made of luxury fibers is outerwear. Furthermore, it was found out that approximately 75% of participants accept paying more for garment containing luxury fibers because of their high quality.     

Potential of Membrane Distillation for Production of High Quality Fruit Juice Concentrate

Fruit juices are generally concentrated in order to improve the stability during storage and to reduce handling, packaging, and transportation costs. Thermal evaporation is the most widely used technique in industrial fruit juice concentrate production. In addition to high energy consumption, a large part of the characteristics determining the quality of the fresh juice including aroma, color, vitamins, and antioxidants undergoes remarkable alterations through the use of high operation temperatures. Increasing consumer demand for minimally or naturally processed stable products able to retain as much possible the uniqueness of the fresh fruit has engendered a growing interest for development of nonthermal approaches for fruit juice concentration. Among them, membrane distillation (MD) and its variants have attracted much attention for allowing very high concentrations to be reached under atmospheric pressure and temperatures near ambient temperature. This review will provide an overview of the current status and recent developments in the use of MD for concentration of fruit juices. In addition to the most basic concepts of MD variants, crucial suggestions for membrane selection and operating parameters will be presented. Challenges and future trends for industrial adaptation taking into account the possibility of integrating MD with other existing processes will be discussed.     

Analysis of volatile flavour components by dynamic headspace analysis/gas chromatography-mass spectrometry in roasted pistachio extracts using supercritical carbon dioxide extraction and sensory analysis

In this study, optimum process parameters for supercritical carbon dioxide (CO₂) (SC-CO₂) extraction of roasted pistachio (Pistacia vera L.) were investigated by depending on amount of the characteristic flavouring components (α-pinene, limonene-D, α-terpinolene and β-myrcene). The extracts were analysed by DHA/GC-MS for determination of the volatile compounds and the optimum process parameters were decided as 200 g, 350 Bar, 70°C, 75 g _CO2/min and 60 min. In the pistachio extracts obtained having the optimum process parameters, α-pinene, β-myrcene, limonene-D and α-terpinolene were detected as 24.47 g/100 g, 0.52 g/100 g, 2.25 g/100 g and 5.70 g/100 g among 31 volatile compounds in total, respectively. The fatty acid composition of the extract, which had the most desirable taste and flavour, was detected by gas chromatography using fatty acid methyl esters (FAME) preparation. The fatty acid composition analysis showed that the pistachio extract had included mostly oleic acid (67.51%, w/w) and linoleic acid (17.85%, w/w).