Electrophoretic deposition of graphene oxide on carbon brush as bioanode for microbial fuel cell operated with real wastewater

Microbial fuel cell (MFC) is a promising technology for simultaneous wastewater treatment and energy harvesting. The properties of the anode material play a critical role in the performance of the MFC. In this study, graphene oxide was prepared by a modified hummer's method. A thin layer of graphene oxide was incorporated on the carbon brush using an electrophoretic technique. The deoxygenated graphene oxide formed on the surface of the carbon brush (RGO-CB) was investigated as a bio-anode in MFC operated with real wastewater. The performance of the MFC using the RGO-CB was compared with that using plain carbon brush anode (PCB). Results showed that electrophoretic deposition of graphene oxide on the surface of carbon brush significantly enhanced the performance of the MFC, where the power density increased more than 10 times (from 33 mWm^?2 to 381 mWm^?2). Although the COD removal was nearly similar for the two MFCs, i.e., with PCB and RGO-CB; the columbic efficiency significantly increased in the case of RGO-CB anode. The improved performance in the case of the modified electrode was related to the role of the graphene in improving the electron transfer from the microorganism to the anode surface, as confirmed from the electrochemical impedance spectroscopy measurements.     

File size models for shared content over the BitTorrent Peer-to-Peer network

Peer-to-Peer (P2P) traffic has increased rapidly over the past few years, with file sharing providing the main drive behind such traffic. In this work we perform a measurement study of the content shared over the popular BitTorrent P2P file sharing network. We mathematically model the file size distributions of shared files after categorizing them into Audio, Video, Archive and CD image classes. For each of these categories we look into the most popular shared file formats and investigate their file size statistics. This provides an important milestone to building a realistic simulation framework for P2P systems, and for future analytical modeling of P2P networks.     

A hybrid model for spelling error detection and correction for Urdu language

Neural Computing and Applications - Detecting and correcting misspelled words in a written text are of great importance in many natural language processing applications. Errors can be broadly...     

Energy-efficient clustering in mobile ad-hoc networks using multi-objective particle swarm optimization

A mobile ad hoc network (MANET) is dynamic in nature and is composed of wirelessly connected nodes that perform hop-by-hop routing without the help of any fixed infrastructure. One of the important requirements of a MANET is the efficiency of energy, which increases the lifetime of the network. Several techniques have been proposed by researchers to achieve this goal and one of them is clustering in MANETs that can help in providing an energy-efficient solution. Clustering involves the selection of cluster-heads (CHs) for each cluster and fewer CHs result in greater energy efficiency as these nodes drain more power than noncluster-heads. In the literature, several techniques are available for clustering by using optimization and evolutionary techniques that provide a single solution at a time. In this paper, we propose a multi-objective solution by using multi-objective particle swarm optimization (MOPSO) algorithm to optimize the number of clusters in an ad hoc network as well as energy dissipation in nodes in order to provide an energy-efficient solution and reduce the network traffic. In the proposed solution, inter-cluster and intra-cluster traffic is managed by the cluster-heads. The proposed algorithm takes into consideration the degree of nodes, transmission power, and battery power consumption of the mobile nodes. The main advantage of this method is that it provides a set of solutions at a time. These solutions are achieved through optimal Pareto front. We compare the results of the proposed approach with two other well-known clustering techniques; WCA and CLPSO-based clustering by using different performance metrics. We perform extensive simulations to show that the proposed approach is an effective approach for clustering in mobile ad hoc networks environment and performs better than the other two approaches.     

Cumin Prevents 17β-Estradiol-Associated Breast Cancer in ACI Rats

Breast cancer (BC) is a leading cause of cancer deaths in women in less developed countries and the second leading cause of cancer death in women in the U.S. In this study, we report the inhibition of E2-mediated mammary tumorigenesis by Cuminum cyminum (cumin) administered via the diet as cumin powder, as well as dried ethanolic extract. Groups of female ACI rats were given either an AIN-93M diet or a diet supplemented with cumin powder (5% and 7.5%, w/w) or dried ethanolic cumin extract (1%, w/w), and then challenged with subcutaneous E2 silastic implants (1.2 cm; 9 mg). The first appearance of a palpable mammary tumor was significantly delayed by both the cumin powder and extract. At the end of the study, the tumor incidence was 96% in the control group, whereas only 55% and 45% animals had palpable tumors in the cumin powder and extract groups, respectively. Significant reductions in tumor volume (660 ± 122 vs. 138 ± 49 and 75 ± 46 mm³) and tumor multiplicity (4.21 ± 0.43 vs. 1.16 ± 0.26 and 0.9 ± 0.29 tumors/animal) were also observed by the cumin powder and cumin extract groups, respectively. The cumin powder diet intervention dose- and time-dependently offset E2-related pituitary growth, and reduced the levels of circulating prolactin and the levels of PCNA in the mammary tissues. Mechanistically, the cumin powder diet resulted in a significant reversal of E2-associated modulation in ERα, CYP1A1 and CYP1B1. Further, the cumin powder diet reversed the expression levels of miRNAs (miR-182, miR-375, miR-127 and miR-206) that were highly modulated by E2 treatment. We analyzed the composition of the extract by GC/MS and established cymene and cuminaldehyde as major components, and further detected no signs of gross or systemic toxicity. Thus, cumin bioactives can significantly delay and prevent E2-mediated mammary tumorigenesis in a safe and effective manner, and warrant continued efforts to develop these clinically translatable spice bioactives as chemopreventives and therapeutics against BC.     

Enhanced anti-biofilm activity of facile synthesized silver oxide nanoparticles against K. pneumoniae

Journal of Inorganic and Organometallic Polymers and Materials - The silver oxide nanoparticle was successfully synthesized using floral waste by simple one pot, cost effective method. The complete...     

喹喔啉类衍生物与甲基噻吩共聚物的合成及性质

在二价镍配合物催化下,2,5-二溴-3-甲基噻吩格氏试剂与5,8-二溴-萘基喹喔啉和5,8-二溴-菲基喹喔啉共聚,得到相应的喹喔啉类共轭共聚物,收率分别为65%和68%。通过FT IR、1H-NM R对聚合物及中间体的结构进行了表征。聚合物的循环伏安图中,分别在0.66 V(Epa)/0.37 V(Epc)(Copo ly-m er I),0.78 V(Epa)/-0.06V(Epc)和1.26(Epa)/0.46(Epc)(Copo lym erⅡ)处观察到氧化还原峰,表明该类聚合物有电化学活性。在紫外-可见光谱中,分别在263 nm,323 nm处(Copo lym erⅠ)和299 nm,402 nm处(Copo lym erⅡ)出现吸收峰。所得聚合物分别在504 nm和513 nm处出现荧光最大发射峰。     

Mathematical modeling of reverse osmosis systems

The present investigation pertains to modeling of seawater desalination system. A simulation model was developed and verified for a small-scale reverse osmosis system. The proposed model combines material balances on the feed tank, membrane module andproduct tank with membrane mass transfer models. Finally a comprehensive simulation model has been developed incorporating the effect of mass transfer inhibition The model is non-linear differential equation representing the feed concentration as a function of operating time and space. The solution of the simultaneous differential equations was obtained using the fourth order Runge-Kutta method, due to self starting and stability. The model was verified using the experimental data from the literature [17,24]. Parameter sensitivity was carried out to select the proper step size. The simulation was run for over 1000 11 enabling a prediction of operational performance at high overall system recoveries.