Composite mixed matrix membranes incorporating microporous carbon molecular sieve as filler in polyethersulfone for CO2/CH4 separation

Membrane technology has been considered a key factor for sustainable growth in high-efficiency gas separation. Current mixed matrix membranes (MMMs) technology is rising, but these membranes in the dense structure are having difficulties in operating at high pressures and scale up for commercialization. The purpose of this research is to synthesize composite MMMs (CMMMs) consisting of polyethersulfone (PES), carbon molecular sieve (CMS 1–5 wt %), and Novatex 2471 nonwoven fabric (support layer). The membranes' physical, chemical, and thermal properties were evaluated by different analytical equipment. The morphology of both PES and PES-CMS composite membranes had a porous and asymmetric structure, in which CMS was uniformly distributed in the polymer matrix. The thermal properties showed that the membranes were stable up to 350 °C with a single glass transition temperature. The functional groups in the membrane were confirmed by spectral analysis. The gas performance results showed that carbon dioxide permeance increased with increased CMS concentration and methane permeance decreased due to the hindering effect of CMS under similar operating conditions. The highest selectivity achieved was 12.774 using CMMM of 5 wt % of CMS at 10 bar, which on average was 137.80%, improved selectivity compared to pure PES membrane. The support layer was able to withstand high operating pressures and showed the ability to scale up. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48476.     

Arabic sign language intelligent translator

ABSTRACT

Arabic sign language (ArSL) is method of communication between deaf communities in Arab countries; therefore, the development of systemsthat can recognize the gestures provides a means for the Deaf to easily integrate into society. In this research we implemented a computational structurefor an intelligent interpreter that automatically recognizes the isolated dynamic gestures. The proposed system recognizes and translates gesturesperformed with one or both hands. It comprises five subsystems, building dataset, video processing, feature extraction, mapping between ArSL and Arabictext, and text generation. To apply the system, 100-signs of ArSL was used, which was applied on 1500 video files. It's were divided into five classes:alphabet, numbers, "prepositions, pronouns and question words", Arabic life expressions, and "nouns and verbs". The evaluation indicated that thesystem automatically recognizes and translates isolated dynamic ArSL gestures by highly accurate manner. The results showed that the system accuracy is 95.8%.     

Characterization of biogenic hydroxyapatite derived from animal bones for biomedical applications

In this work, the viability of producing biogenic hydroxyapatite from bio-waste animal bones, namely bovine (cow), caprine (goat) and galline (chicken), through a heat treatment process has been investigated. The animal bones were locally sourced, cleaned to remove collagen and subsequently heat treated in air atmosphere at different temperatures ranging from 600?°C to 1000?°C. From the range of sintering temperatures investigated, it was found that hydroxyapatite derived from bovine bone showed good thermal stability while those produced from caprine and galline bones exhibited phase instability with traces of tri-calcium phosphate (TCP) being detected after heat treatment beyond 700?°C. The porous nature of the bone samples can be observed from the microstructures obtained and supported by low relative density. Heating the bovine and caprine bones at selected temperatures yielded porous HA body, having hardness values that are comparable with human cortical bone. However, the sintered galline bone sample showed higher porosity levels and low hardness when compared to the other two bone types.     

A Deep Learning Spatiotemporal Prediction Framework for Mobile Crowdsourced Services

Mobile Networks and Applications - This papers presents a deep learning-based framework to predict crowdsourced service availability spatially and temporally. A novel two-stage prediction model is...     

Modeling and operation optimization of RE integrated microgrids considering economic,energy, and environmental aspects

Microgrids provide promising solution for integration of renewable energy sources in the electrical grid. To exploit the key benefits, achieving the economical operation of renewable aided microgrids has become necessary and is a challenging task. This paper presents an efficient optimization model to minimize the operational cost of a solar integrated microgrid. We formulate a joint optimization mixed integer problem for appropriate modeling of the system under various practical constraints. An efficient solution is obtained with a distributed approach such that the original problem is solved in two stages. Dual decomposition approach is adopted for cost, emissions, and solar share optimization. Lagrange relaxation, Lambda iteration method, and binary integer programming are employed to obtain the joint optimization solution. Finally, the performance of the proposed model is validated through simulations that show that an overall cost reduction of 4.2070e+04 $ and emission reduction of 7.2001e+03 kg are achieved with the proposed model.     

Development of Whole and Ground Seed Near-Infrared Spectroscopy Calibrations for Oil,Protein, Moisture,and Fatty Acids in Salvia hispanica

Chia (Salvia hispanica) is an ancient crop that has experienced an agricultural resurgence in recent decades owing to the high omega 3 fatty acid (ω-3) content of the seeds and good production potential. Analysis of 563 lots of chia grown in Kentucky and 10 lots from Arizona, Australia, Mexico, and Peru was performed. All of these lots were assessed for fatty acid, oil, and protein content, while a subset of 120 samples were assessed for amino acids, fiber, minerals, and trace elements. The mean oil content was 31.3%, ranging from 21.4% to 35.3%. The protein content averaged 22.8%, ranging from 18.2% to 28.2%, and the ω-3 FA α-linolenic acid (ALA) averaged 61.3%, ranging from 33.9% to 69.9%. Using these seed lots, nondestructive near-infrared spectroscopy (NIRS) calibrations were developed for whole and ground seed oil, protein, moisture, and the six major fatty acids. The R² and SE of cross-validation (SECV) values for oil were 0.78 and 0.95, respectively, while those for protein were 0.75 and 1.05, respectively. The NIRS calibrations for fatty acid had R² and SECV greater than 0.6 and less than 10% of actual values for all major fatty acids, respectively. An R² of 0.99 was established for moisture content of whole seeds within the range of 3–10% moisture content. The precision and accuracy of these calibrations is adequate for use by breeders, growers, and food quality experts to quantitatively assess these major constituents without the need for costly and time-consuming chemical analysis.     

Genes and Pathways Involved in Adult Onset Disorders Featuring Muscle Mitochondrial DNA Instability

Replication and maintenance of mtDNA entirely relies on a set of proteins encoded by the nuclear genome, which include members of the core replicative machinery, proteins involved in the homeostasis of mitochondrial dNTPs pools or deputed to the control of mitochondrial dynamics and morphology. Mutations in their coding genes have been observed in familial and sporadic forms of pediatric and adult-onset clinical phenotypes featuring mtDNA instability. The list of defects involved in these disorders has recently expanded, including mutations in the exo-/endo-nuclease flap-processing proteins MGME1 and DNA2, supporting the notion that an enzymatic DNA repair system actively takes place in mitochondria. The results obtained in the last few years acknowledge the contribution of next-generation sequencing methods in the identification of new disease loci in small groups of patients and even single probands. Although heterogeneous, these genes can be conveniently classified according to the pathway to which they belong. The definition of the molecular and biochemical features of these pathways might be helpful for fundamental knowledge of these disorders, to accelerate genetic diagnosis of patients and the development of rational therapies. In this review, we discuss the molecular findings disclosed in adult patients with muscle pathology hallmarked by mtDNA instability.     

Magnetic micropolar nanofluids flow in double lid-driven enclosures using two-energy equation model

Impacts of an inclined electromagnetic force on a mixed convective process in two-sided lid-driven geometries using the two-energy equation model are examined in this study. The flow domain is filled by a porous medium and the local thermal nonequilibrium model is applied. Magnetic micropolar nanofluids are assumed as working fluids consisting of water as a base fluid and CuO as nanoparticles. The forced convection situation is due to the moving of the upper and lower walls in the right direction with a constant velocity. The used methodology depends on the finite volume method, together with the SIMPLE algorithm. The obtained outcomes are visualized using contours of the streamlines, isotherms for the nanofluid phase, isotherms for the solid phase, and angular velocity. The main findings revealed that the increase in lengths of the heated parts and the Nield number reduces the Nusselt number for the nanofluid phase. Also, the average heat transfer rate for the nanofluid and solid phases are boosted with the increase in the vortex viscosity.