Perforin expression in human cell-mediated luteolysis

For a variety of reasons, small vessels have low signal intensity in magnetic resonance angiography. When the vessel signal intensity is lower than the signal intensity of background tissues, these vessels tend not to be visible on maximum-intensity-projection images. The authors developed a nonlinear second-difference spatial filtering technique that enhances the details of small vessels while suppressing both noise and uniform background tissue. Two similar nonlinear second-difference filters are presented and compared with the linear Laplacian second-difference filter. To evaluate the performance of these filters, they were applied to intracranial three-dimensional time-of-flight MR angiographic data and the results compared with the vessel enhancement obtained with a simple second-difference Laplacian filter and with magnetization transfer contrast (MTC) techniques. The comparisons demonstrated that nonlinear filtering and MTC techniques result in similar improvement in small-vessel visibility and apparent continuity. A quantitative comparison demonstrated that the improvement in the contrast-to-noise ratio is much greater with the nonlinear filters than the Laplacian filter.     

Modulation of extraction variables of pectin from Manilkarazapota fruit peel,its bio characterization,and comparative study using dynamic light scattering studies

Influence of variables has a great impact upon yield of pectin. The present study was organized to harmonize these variables and examine the extracted pectin. In view of this, bio-characterizion and structure analysis of pectin through FTIR was performed. Additionally, a polydispersity and particle size study was also conducted using dynamic light scattering (DLS) of the Manilkarazapota fruit peel. The best extraction variables according to the response optimization predicted model were noted as pH of 5 at 61.11°C for 90 min of heating time, which lead to a 3.7% yield. Bio-characterization revealed that pectin extracted at pH 5 has characteristics similar to HM pectin influence of methoxyl content, degree of esterification, and Galacturonic acid content at 5.11%, 73. 63%, and 77.7%, respectively. The FTIR spectrum depicted a similar surface structure to food-grade pectin. DLS studies revealed that extracted pectin at pH 5 has a particle size in the range of 390.21–421.17 nm and polydispersity (?) of 28.2%-29.3%. These findings indicate that sapodilla is a potential source of pectin for food and pharmaceutical preparation.     

Assessing the determinants of flow experience in the adoption of learning management systems: the moderating role of perceived institutional support

Information technology has moved the focus of students and instructors from blackboards to online learning platforms. In the emerging e-learning revolution, the success of quality education depends on the right use of information and communication technology, including the creation of participants’ flow experience while using learning systems, which are rightly considered a backbone of contemporary education. There is a gap in the e-learning literature, reflecting a lack of understanding of students’ flow experience while using online interactive systems. This paper presents a study investigating the key factors (interpersonal factors and atmospheric cues) affecting flow experience and highlights its massive role in the use of any learning management system (LMS). Moreover, the study examines the moderating role of perceived institutional support (PIS) on student adoption of LMS. Using a survey, data were collected from university students in Pakistan and the data were analysed through structural equation modelling. We found that interpersonal factors and LMS atmospherics have significant effects on the flow experience. It was also found that PIS moderates the relationship between flow experience and the use of LMS. This study contributes to the literature by helping institutions and policy-makers know key factors of effective learning systems that students value and enjoy.     

Miniaturized humidity and temperature sensing RFID enabled tags

A compact 27‐bit linearly polarized chipless radio frequency identification tag is presented in this research. The proposed tag is designed with an overall tag dimension of 23 × 23 mm². The tag comprises of metallic (copper) rings‐based structure loaded with slots. These slots correspond to a particular sequence of bits. The circular tag is analysed using 2 different substrates, that is, Rogers RT/duroid/5870 and flexible Rogers RT/duroid/5880. The radar cross‐section response of frequency signatured tag is analysed for humidity and temperature sensor designs. Humidity sensing is achieved by deploying a DuPont Kapton HN heat resistant sheet on the shortest slot of the tag, that is, the sensing slot. Temperature sensing is attained using Rogers RT/duroid/5870 and Stanyl polyamide as a combined substrate. Hence, the miniaturized, robust, and flexible tag can be deployed over irregular surfaces for sensing purposes.     

RBFNN versus FFNN for daily river flow forecasting at Johor River,Malaysia

Streamflow forecasting can have a significant economic impact, as this can help in water resources management and in providing protection from water scarcities and possible flood damage. Artificial neural network (ANN) had been successfully used as a tool to model various nonlinear relations, and the method is appropriate for modeling the complex nature of hydrological systems. They are relatively fast and flexible and are able to extract the relation between the inputs and outputs of a process without knowledge of the underlying physics. In this study, two types of ANN, namely feed-forward back-propagation neural network (FFNN) and radial basis function neural network (RBFNN), have been examined. Those models were developed for daily streamflow forecasting at Johor River, Malaysia, for the period (1999–2008). Comprehensive comparison analyses were carried out to evaluate the performance of the proposed static neural networks. The results demonstrate that RBFNN model is superior to the FFNN forecasting model, and RBFNN can be successfully applied and provides high accuracy and reliability for daily streamflow forecasting.     

Multi-objective feature subset selection using mRMR based enhanced ant colony optimization algorithm (mRMR-EACO)

In this research, we propose a novel method to find the relevant feature subset by using ant colony optimisation minimum-redundancy–maximum-relevance. The proposed approach considers the significance of each feature while reducing the dimensionality. The performance of proposed algorithm has been compared with existing biologically inspired feature subset selection algorithms. Eight datasets have been selected from UCI machine learning repository for experimentation. The experimental results indicate that the presented algorithm out performs the other algorithms in terms of the classification accuracy and feature reduction.     

Human facial expression recognition using curvelet feature extraction and normalized mutual information feature selection

To recognize expressions accurately, facial expression systems require robust feature extraction and feature selection methods. In this paper, a normalized mutual information based feature selection technique is proposed for FER systems. The technique is derived from an existing method, that is, the max-relevance and min-redundancy (mRMR) method. We, however, propose to normalize the mutual information used in this method so that the domination of the relevance or of the redundancy can be eliminated. For feature extraction, curvelet transform is used. After the feature extraction and selection the feature space is reduced by employing linear discriminant analysis (LDA). Finally, hidden Markov model (HMM) is used to recognize the expressions. The proposed FER system (CNF-FER) is validated using four publicly available standard datasets. For each dataset, 10-fold cross validation scheme is utilized. CNF-FER outperformed the existing well-known statistical and state-of-the-art methods by achieving a weighted average recognition rate of 99 % across all the datasets.     

Phase Inversion Technique-Based Polyamide Films and Their Applications: A Comprehensive Review

This is a comprehensive review regarding the particulars of phase inversion technique and its significance in polyamide films. Phase inversion is a versatile technique to form thin films of neat polyamide, composite, and blend system. Phase inversion can be induced by polymer solution immersion in nonsolvent, contact with nonsolvent vapor, thermal treatment, solvent evaporation, and quenching. Choice of solvent/nonsolvent system, polyamide, additive, coagulation bath, and film casting conditions are crucial. Only limitation of phase inversion is the requirement of polyamide solubility in suitable solvent. Promising applications of phase inversion polyamide are in fuel cell, gas separation, tissue engineering, and water filtration.     

Reaction‐induced phase separation and resulting thermomechanical and surface properties of epoxy resin/poly(ethylene oxide)–poly(propylene oxide)–poly(ethylene oxide) blends cured with 4,4′‐diaminodiphenylsulfone

We investigated the phase separation, cure kinetics and thermomechanical properties of diglycidyl ether of bisphenol‐A/4,4′‐diaminodiphenylsulfone/poly(ethylene oxide)–poly(propylene oxide)–poly(ethylene oxide) (PEO–PPO–PEO) triblock copolymer (TBCP) blends. Fourier transform infrared spectroscopy, differential scanning calorimetry, and atomic force microscopy revealed that the blends exhibited heterogeneous phase morphology in which the TBCP formed dispersed domains in epoxy matrix, due to reaction induced phase separation. A fraction of phase‐separated PEO phase underwent partial crystallization whereas another fraction formed interphases between the dispersed domains and epoxy matrix. Moreover, the dispersed PEO chains improved the compatibility and interfacial adhesion between the matrix and domains and, consequently, significantly improved the mechanical properties of epoxy resin. Furthermore, the thermal degradation studies and contact angle measurements disclosed that the dispersed domains were well protected by the epoxy matrix. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44406.