Display omitted
•Chlorophyll loaded microcapsules were produced by spray-drying.•Inclusion of chlorophylls in microcapsules was proved by FTIR, XRD, and DSC analyses.•An increase in concentration of ...MD in carriers improved the quality of microcapsules.•Microencapsulation enhanced thermal and storage stability of chlorophylls.•Storage stability of microcapsules was related to their physicochemical properties.
Detailed investigations on the physicochemical and structural characterization of chlorophyll loaded microcapsules and their storage stability have not previously been conducted. Therefore, our objective was to encapsulate unstable chlorophylls using different blends of gum Arabic (GA) and maltodextrin (MD) (GA-MD ratios of 5:5, 3:7, and 0:10) by spray-drying to improve storage stability of chlorophylls. An increase in concentration of MD in wall materials was associated with lower moisture content (0.56%), higher encapsulation efficiency (77.19%), chlorophyll content (46.78 µg/g dry powder), degree of crystallinity, and thermal stability of microcapsules. Furthermore, FTIR, XRD, and DSC analyses confirmed inclusion of chlorophylls within microcapsules. The entrapment of chlorophylls within microcapsules enhanced their storage stability at all temperatures (4, 20, and 40 °C) for ten days; notably, microcapsules coated with MD alone showed the highest storage stability (94.7–97.5%). In conclusion, microencapsulation of chlorophylls using MD alone was optimal for enhancing chlorophylls’ storage stability.
There are currently a large variety of wireless access networks, including the emerging vehicular ad hoc networks (VANETs). A large variety of applications utilizing these networks will demand ...features such as real-time, high-availability, and even instantaneous high-bandwidth in some cases. Therefore, it is imperative for network service providers to make the best possible use of the combined resources of available heterogeneous networks (wireless area networks (WLANs), Universal Mobile Telecommunications Systems, VANETs, Worldwide Interoperability for Microwave Access (WiMAX), etc.) for connection support. When connections need to migrate between heterogeneous networks for performance and high-availability reasons, seamless vertical handoff (VHO) is a necessary first step. In the near future, vehicular and other mobile applications will be expected to have seamless VHO between heterogeneous access networks. With regard to VHO performance, there is a critical need to develop algorithms for connection management and optimal resource allocation for seamless mobility. In this paper, we develop a VHO decision algorithm that enables a wireless access network to not only balance the overall load among all attachment points (e.g., base stations and access points) but also maximize the collective battery lifetime of mobile nodes (MNs). In addition, when ad hoc mode is applied to 3/4G wireless data networks, VANETs, and IEEE 802.11 WLANs for a more seamless integration of heterogeneous wireless networks, we devise a route-selection algorithm for forwarding data packets to the most appropriate attachment point to maximize collective battery lifetime and maintain load balancing. Results based on a detailed performance evaluation study are also presented here to demonstrate the efficacy of the proposed algorithms.
Diabetic retinopathy (DR) is an eye disease that alters the blood vessels of a person suffering from diabetes. Diabetic macular edema (DME) occurs when DR affects the macula, which causes fluid ...accumulation in the macula. Efficient screening systems require experts to manually analyze images to recognize diseases. However, due to the challenging nature of the screening method and lack of trained human resources, devising effective screening-oriented treatment is an expensive task. Automated systems are trying to cope with these challenges; however, these methods do not generalize well to multiple diseases and real-world scenarios. To solve the aforementioned issues, we propose a new method comprising two main steps. The first involves dataset preparation and feature extraction and the other relates to improving a custom deep learning based CenterNet model trained for eye disease classification. Initially, we generate annotations for suspected samples to locate the precise region of interest, while the other part of the proposed solution trains the Center Net model over annotated images. Specifically, we use DenseNet-100 as a feature extraction method on which the one-stage detector, CenterNet, is employed to localize and classify the disease lesions. We evaluated our method over challenging datasets, namely, APTOS-2019 and IDRiD, and attained average accuracy of 97.93% and 98.10%, respectively. We also performed cross-dataset validation with benchmark EYEPACS and Diaretdb1 datasets. Both qualitative and quantitative results demonstrate that our proposed approach outperforms state-of-the-art methods due to more effective localization power of CenterNet, as it can easily recognize small lesions and deal with over-fitted training data. Our proposed framework is proficient in correctly locating and classifying disease lesions. In comparison to existing DR and DME classification approaches, our method can extract representative key points from low-intensity and noisy images and accurately classify them. Hence our approach can play an important role in automated detection and recognition of DR and DME lesions.
Display omitted
•Chlorophylls and their derivatives, pheophytins and Zn-pheophytins, were identified.•Among pigments evaluated, Zn-pheophytins had the highest antioxidant activity.•First study on the ...anti-inflammatory capacity of Zn-pheophytins.•Zn-pheophytins remarkably suppressed the inflammatory responses of macrophages.
The aims of this study were to synthesize chlorophyll derivatives, pheophytins and Zn-pheophytins, from chlorophylls extracted from spinach, characterize them, and evaluate their antioxidant and anti-inflammatory activities. The chlorophylls isolated from spinach were identified by means of FT-IR and NMR spectroscopies. The synthesis of pheophytins and Zn-pheophytins was confirmed by UV–Vis spectral analyses. The antioxidant activity of chlorophylls, pheophytins, and Zn-pheophytins was studied. The results revealed that the Zn-pheophytins showed the highest 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging and β-carotene bleaching activities, followed by chlorophylls and pheophytins. Additionally, Zn-pheophytins showed substantial inhibitory activity against lipopolysaccharide (LPS)-induced NO production in RAW 264.7 cells. Furthermore, Zn-pheophytins remarkably suppressed LPS-induced expression of inducible nitric oxide synthase (iNOS) in RAW 264.7 cells and showed no cytotoxicity. Our findings indicated that Zn-pheophytins have strong antioxidant and anti-inflammatory properties and can therefore be a potential source of bioactive compounds for nutraceutical, cosmetic, and pharmaceutical applications.
The 3D display device shows an image with depth information. Conventional 3D display devices based on binocular parallax can focus accurately only on the depth of a specific screen. Because the human ...eye has a narrow depth of field (DOF) under normal circumstances, 3D displays that provide a relatively wide range of virtual depth areas have limitations on the DOF where clear 3D images are seen. To resolve this problem, it is necessary to find the optical conditions to extend the DOF and analyze the phenomena related to it. For this, by using the Rayleigh criterion and the Strehl ratio, a criterion for this extension of the DOF is suggested. A practical optical structure that can effectively extend the DOF is devised using a flat panel display. This optical structure could be applied to AR, VR, and MR in the field of near-eye displays. From the results of this research, the fundamental optical conditions and standards are proposed for 3D displays that will provide 3D images with extended DOF in the future. Furthermore, it is also expected that these conditions and criteria can be applied to optical designs for the required performance in the development of 3D displays in various fields.
A brain tumor is an abnormal growth in brain cells that causes damage to various blood vessels and nerves in the human body. An earlier and accurate diagnosis of the brain tumor is of foremost ...important to avoid future complications. Precise segmentation of brain tumors provides a basis for surgical planning and treatment to doctors. Manual detection using MRI images is computationally complex in cases where the survival of the patient is dependent on timely treatment, and the performance relies on domain expertise. Therefore, computerized detection of tumors is still a challenging task due to significant variations in their location and structure, i.e., irregular shapes and ambiguous boundaries. In this study, we propose a custom Mask Region-based Convolution neural network (Mask RCNN) with a densenet-41 backbone architecture that is trained via transfer learning for precise classification and segmentation of brain tumors. Our method is evaluated on two different benchmark datasets using various quantitative measures. Comparative results show that the custom Mask-RCNN can more precisely detect tumor locations using bounding boxes and return segmentation masks to provide exact tumor regions. Our proposed model achieved an accuracy of 96.3% and 98.34% for segmentation and classification respectively, demonstrating enhanced robustness compared to state-of-the-art approaches.
With increasing numbers of GPS-equipped mobile devices, we are witnessing a deluge of spatial information that needs to be effectively and efficiently managed. Even though there are several ...distributed spatial data processing systems such as GeoSpark (Apache Sedona), the effects of underlying storage engines have not been well studied for spatial data processing. In this paper, we evaluate the performance of various distributed storage engines for processing large-scale spatial data using GeoSpark, a state-of-the-art distributed spatial data processing system running on top of Apache Spark. For our performance evaluation, we choose three distributed storage engines having different characteristics: (1) HDFS, (2) MongoDB, and (3) Amazon S3. To conduct our experimental study on a real cloud computing environment, we utilize Amazon EMR instances (up to 6 instances) for distributed spatial data processing. For the evaluation of big spatial data processing, we generate data sets considering four kinds of various data distributions and various data sizes up to one billion point records (38.5GB raw size). Through the extensive experiments, we measure the processing time of storage engines with the following variations: (1) sharding strategies in MongoDB, (2) caching effects, (3) data distributions, (4) data set sizes, (5) the number of running executors and storage nodes, and (6) the selectivity of queries. The major points observed from the experiments are summarized as follows. (1) The overall performance of MongoDB-based GeoSpark is degraded compared to HDFS- and S3-based GeoSpark in our experimental settings. (2) The performance of MongoDB-based GeoSpark is relatively improved in large-scale data sets compared to the others. (3) HDFS- and S3-based GeoSpark are more scalable to running executors and storage nodes compared to MongoDB-based GeoSpark. (4) The sharding strategy based on the spatial proximity significantly improves the performance of MongoDB-based GeoSpark. (5) S3- and HDFS-based GeoSpark show similar performances in all the environmental settings. (6) Caching in distributed environments improves the overall performance of spatial data processing. These results can be usefully utilized in decision-making of choosing the most adequate storage engine for big spatial data processing in a target distributed environment.
Background
This study aimed to determine the correlation between occlusal contact area and masticatory performance using BiteEye®, a photo occlusal analysis device and the multiple sieve method.
...Objectives
To calculate the occlusal contact area at various levels of interocclusal thicknesses and to measure masticatory performance with peanuts as the test material.
Methods
Fifty‐two adults (30 men and 22 women) were enrolled according to specific exclusion/inclusion criteria. The occlusal contact area was measured by obtaining the interocclusal record of the maximum intercuspal position (MIP) using silicone impression material. Occlusal contact area measurements were performed in the ranges of 0–149, 0–89, 0–59, 0–29 and 0–9 μm. Masticatory performance was measured by obtaining the median particle size (X 50) after converting the weight of comminuted peanuts into size using the multiple sieve method. Statistical analysis was performed at 95% significance level.
Results
Interocclusal thickness comparison revealed the highest correlation with X 50 in the 0–149 μm range. Stronger correlations between the occlusal contact area and X 50 were observed in cases of 20 strokes of mastication (r = −.451) than in cases of 10 strokes (r = −.383), in the posterior occlusal contact area (r = −.456) than in the full arch occlusal contact area (r = −.451) and the molar area (r = −.478) than in the premolar area (r = −.296).
Conclusions
The larger the occlusal contact area, the higher the masticatory performance; this correlation was statistically significant. Regarding interocclusal thickness, the highest correlation between the occlusal contact area and masticatory performance was observed in the 0–149 μm range.
Clinical Trial Registration Number: GWNUDH IRB 2020‐A001.
The highest correlation between masticatory performance and occlusal contact area was exhibited in an interocclusal thickness range of 0‐149 μm.