Independent sets of some graphs associated to commutative rings

Let $G=(V,E)$ be a simple graph. A set $S\subseteq V$ is independent set of $G$, if no two vertices of $S$ are adjacent. The independence number $\alpha(G)$ is the size of a maximum independent set in the graph. %An independent set with cardinality Let $R$ be a commutative ring with nonzero identity and $I$ an ideal of $R$. The zero-divisor graph of $R$, denoted by $\Gamma(R)$, is an undirected graph whose vertices are the nonzero zero-divisors of $R$ and two distinct vertices $x$ and $y$ are adjacent if and only if $xy = 0$. Also the ideal-based zero-divisor graph of $R$, denoted by $\Gamma_I(R)$, is the graph which vertices are the set {x\in R\backslash I | xy\in I \quad for some \quad y\in R\backslash I\} and two distinct vertices $x$ and $y$ are adjacent if and only if $xy \in I$. In this paper we study the independent sets and the independence number of $\Gamma(R)$ and $\Gamma_I(R)$.Comment: 27 pages. 22 figure

Progress Update of Community Standards for 3D Data Preservation: Project Background and Forum 1 Summary

This report was collaboratively generated by the CS3DP Forum 1 participants

Chromatographic Purification of Recombinant Nucleocapsid Protein of Nipah Virus from Escherichia Coli Homogenate

The nucleocapsid protein (NCp) of Nipah virus (NiV) expressed in Escherichia coli (E. coli) is antigenic and immunogenic. NCp-NiV is a potential serological antigen that can be used in the diagnosis of NiV infections. The yield of NCp expressed in E. coli is low due to the proteolytic degradation by host endogenous proteases. Therefore, it is important to inhibit the endogenous proteolytic degradation activity and shorten the protein recovery process to avoid or reduce the action of protease on the recombinant NCp. A method to predict the type of potential protease that attacks the NCp-NiV and its potential cleavage sites in E. coli to enhance the recovery of NCp was developed. A bioinformatics tool, PeptideCutter was used to identify potential protease and its cleavage sites from the amino acid sequences deduced from the published DNA sequence of the NCp-NiV. The predicted proteases were serine proteases, hence, a range of serine protease inhibitors were tested to improve the yield of NCp. The yield of NCp was increased by 2-fold after the phenylmethylsulphonyl fluoride (PMSF) supplementation. The downstream processing of the NCp-NiV from clarified E. coli homogenate was investigated. Two types of preparative chromatographic purification in a packed bed column; immobilised metal affinity chromatography (IMAC) and hydrophobic interaction chromatography (HIC) were studied and compared. A direct recovery of recombinant NCp-NiV from unclarified E. coli homogenate based on EBA chromatography was then developed by using the type of chromatography that can obtain high yield of the NCp with high antigenicity. In the IMAC system, HisTrapTM 6 Fast Flow was applied to purify the recombinant histidine-tagged NCp. A histidine hexamer tag was placed at the C-terminus of the NCp and this enabled the purification of NCp by IMAC system. The optimal binding was achieved at pH 7.5 and superficial velocity of 75 cm/h. The bound NCp was successfully recovered by a stepwise elution with a range of imidazole concentration (50, 150, 300 and 500 mM). The NCp was captured and eluted from an inlet NCp concentration of 0.4 mg/ml in a scale-up IMAC packed bed column of Nickel SepharoseTM 6 Fast Flow with the optimized conditions obtained from the scouting method. The purification of histidine-tagged NCp using IMAC packed bed column has resulted a 68.3% yield and a purification factor of 7.94. In the HIC system, ammonium sulfate precipitation experiment was performed and it showed that 15% saturation of the salt was the most suitable concentration for the binding buffer. Batch binding of the NCp was performed using Sepharose™ 6 Fast Flow adsorbents coupling separately with four different types of ligand; phenyl low substitution, phenyl high substitution, butyl and octyl. The phenyl low substitution ligand was selected for subsequent optimization process due to its highest yield and purity of the NCp achieved from the batch binding experiment. The HIC for purification of the NCp was further scaled up using a 10 cm column packed with phenyl low substitution Sepharose™ adsorbent. A recovering yield of 81% of the NCp with a purification factor of 9.3 was achieved from this scaled-up HIC operation. Hence, the HIC adsorbent was used to capture the NCp in an EBA column due to its higher yield and purity obtained in the third chapter than the IMAC purification in the second chapter of this study. DNase was added to reduce the viscosity of feedstock and improve the axial mixing prior to the loading of the feedstock to the EBA column packed with the StreamlineTM HIC adsorbent charged with phenyl. The addition of glycerol to the washing buffer has reduced the volume of washing buffer applied, and thus reduced the loss of the NCp during washing stage. The dynamic binding capacity at 10% breakthrough of 3.2 mg/g adsorbent was achieved at a linear flow velocity of 178 cm/h, bed expansion of two and viscosity of 3.4 mPas. The adsorbed NCp was eluted with the buffer containing a step gradient of salt concentration. The purification of hydrophobic NCp using HIC-EBA column has resulted an 80% yield and a purification factor of 12.5

Improvement of a Dynamic Frequency Hopping Optical Code Division Multiple Access System Using Power Control Method

In this thesis, adaptive power control method is proposed to improve the performance of dynamic frequency hopping-optical code division multiple access (DFH-OCDMA) communication system. This method is based on solving the near-far problem of power misdistribution among simultaneous users. The DFH-OCDMA has an advantage of supporting more users compared to other OCDMA techniques such as Hadamard code, modified quadratic congruence code, modified frequency hopping code, and fast frequency hopping system. Nevertheless, the bit error rate (BER) was found to deteriorate rapidly with a slight change of received power compared to the other techniques. With the change of the received power (i.e. from -10 dBm to -12 dBm), the BER could be degraded from 10-9 to 10-6. This phenomenon is strongly related to nearfar problem, where users at longer path lengths will suffer higher BER compared to users at shorter path lengths. The unequal power distribution among users leads to unequal performance for them. This may cause to not all users can be supported in the transmission system. Therefore, this study is aimed to search for a solution to increase the number of users under the DFH-OCDMA system with near-far problem. A distributed power control algorithm was proposed to enhance the performance of the system and this was done by considering all possible noises such as the multiple access interference, phase induced intensity noise, and shot noise. The performance of the system was also observed at different issues of fibre impairments, including fibre attenuation, and optical components. The results gathered from the simulations showed that BER and signal-to-noise-ratio (SNR) for each user were significantly improved after using the power control. In specific, it is observed that the best capacity increased was 51% when the random path lengths for 110 users was between 1 to 40 km. Thus, the power control method is proven as an important enhancement to DFH-OCDMA performance. Moreover, the number of users increased in the DFH-OCDMA system with power control was 56 users while at prime code OCDMA and time hopping, only 20 users increment with power control. This result therefore shows better improvement of capacity in DFH-ODCMA compared to other Power Controlled-OCDMA

Treatment of Synthetic Wastewater Using Horizontal Subsurface Flow Constructed Wetland

Constructed wetland is an effective wastewater treatment technology which is used in worldwide. Nevertheless, the effectiveness of using this wastewater treatment is depending on the selection of the type of design used and other factors. This research was conduced to test the influence of media and vegetation subsurface flow constructed wetlands, designed based on the first-order plug flow kinetics. In this study, four horizontal subsurface flow wetlands (HSSF), each with dimensions of 1.3 m (L) × 0.5 m (W) ×0.4 m (D), were constructed at the Research Station of Tehran University, located in Karaj, Iran. The study was carried out from April to September, 2007. Gravel and zeoilte were used in this study as substrate. Gravelbeds with and without plants, and gravel-beds mixed with 10% zeolite, with and without plants were examined to investigate the feasibility of treating synthetic wastewater which was specially produced and modified to imitate agricultural wastewater. The average synthetic influent wastewater contained approximately 100 mg l-1 Nitrate (NO3-N), 10 mg l-1 total Phosphorous, 10 mg l-1 Zn (II), 2 mg l-1 Pb (II) and 1 mg l-1 Cd (II), while the macrophytes selected were Phragmites Australis and Juncus Inflexus in combine with each other. Water discharge was 65 l / day for each cell, and retention time (HRT) was 1.4 d. The influent and effluent Zn, Pb, Cd, P and NO3-N concentrations were monitored and analyzed every 15 days to assess the performance of the wetland units for removal efficiencies based on the statistical analyses. Two intermediate samples were also collected from each cell to evaluate the values of pollutant concentrations, the parameters along the units, and the effect of the HRT. At the end of the study, plants were harvested and analyzed for the same factors (NO3, P, Zn, Pb and Cd). The results derived indicated that the system had acceptable and optimal pollutant removal efficiency, and that both plants were found tolerant under the tested conditions. The wetland system could achieve the NO3-N removal of 79.19% in vegetated cell with gravel and 10% zeolite as substrate, and 86.58% in an unvegetated cell with gravel and 10% zeolite as substrate, and 82.39% in vegetated cell with gravel as substrate, and finally 87.94% in unvegetated cell with gravel as substrate. As for the P removal, the efficiencies of 93.12%, 89.47%, 81.76% and 76.65% were respectively achieved for the vegetated cell with gravel and zeolite as substrate, the vegetated cell with gravel as substrate, unvegetated cell with gravel and zeolite as substrate, and unvegetated cell with gravel as substrate. The outflow concentrations of Pb and Cd were found to be under the detection limit; however, as for Zn, the removal efficiencies of 99.9%, 99.76%, 99.71% and 99.52% were concluded for the vegetated cell with gravel and zeolite, unvegetated cell with gravel and zeolite, vegetated cell with gravel, and unvegetated cell with gravel, respectively

A Neural Network Solution to Singular Configuration in Trajectory Tracking of a Serial Robot

Singularities and uncertainties in arm configurations are the main problems in kinematics of serial robots. The complexity in the solution arises from robots geometry and non-linear equations (trigonometric equations) occur when transforming between Cartesian and joint spaces where multiple solutions and singularities exist. Mathematical solutions for the problem may not always correspond to the physical solution and methods of solution depend on the robot configuration. In this research, a trajectory tracking approach is proposed for a 6 Degrees Of Freedom (DOF) serial robot manipulator. The proposed solution is carried out through two stages. First the kinematics model of the Fanuc robot was solved using the D-H method to show the exact location of singular configurations of the robot, and then Artificial Neural Networks (ANNs) are trained to overcome these arising problems. Solving the Inverse Kinematics (IK) of serial manipulators by using ANNs has two problems, one of these is the selection of the appropriate configuration of the network and the other is the generating of suitable training data sets. In this research, although this is very difficult in practice, training data were recorded experimentally from sensors fixed on each joint to overcome the effect of kinematics uncertainties presence in the real world such as ill-defined linkage parameters, links flexibility and backlashes in gear train. Off-line training was implemented for the experimentally obtained training data. Two networks configurations from the literature were tested and developed following the recommendations of the original authors, then compared to find the best configuration to be used. First the effect of orientation of the tool was examined (as one of the networks does not considered the effect of orientation while the other network does), and then the effect of the Jacobian matrix to the solution for the both configurations was examined. Performance comparison shows that when the effect of the orientation of the tool was considered in the solution with the Jacobian matrix effect, better results in terms of precision and iteration during training the ANN were obtained. The effect of the network architecture was also examined in order to find the best network configuration to solve the problem. A network with all the parameters considered together in one network has been compared to six different networks, where the parameters of every joint were considered independently. Results obtained show that having one network considering all the problem’s parameters together give a better response than using 6 different networks representing the parameters of each joint apart from other joints. The resultant network with the best configuration was tested experimentally using new different set of data that has never been introduced to the network before, this data set was meant to pass through the singular configurations, in order to show the generality and efficiency of the proposed approach. Experimental trajectory tracking has shown the ability of the proposed Artificial Neural Networks approach to overcome the disadvantages of using some schemes like the Fuzzy Learning Control for example that only remembers the most recent data sets introduced, as the literature has shown

A deep-learning approach for high-speed Fourier ptychographic microscopy

We demonstrate a new convolutional neural network architecture to perform Fourier ptychographic Microscopy (FPM) reconstruction, which achieves high-resolution phase recovery with considerably less data than standard FPM.https://www.researchgate.net/profile/Thanh_Nguyen68/publication/325829575_A_deep-learning_approach_for_high-speed_Fourier_ptychographic_microscopy/links/5b2beec20f7e9b0df5ba4872/A-deep-learning-approach-for-high-speed-Fourier-ptychographic-microscopy.pdfhttps://www.researchgate.net/profile/Thanh_Nguyen68/publication/325829575_A_deep-learning_approach_for_high-speed_Fourier_ptychographic_microscopy/links/5b2beec20f7e9b0df5ba4872/A-deep-learning-approach-for-high-speed-Fourier-ptychographic-microscopy.pdfhttps://www.researchgate.net/profile/Thanh_Nguyen68/publication/325829575_A_deep-learning_approach_for_high-speed_Fourier_ptychographic_microscopy/links/5b2beec20f7e9b0df5ba4872/A-deep-learning-approach-for-high-speed-Fourier-ptychographic-microscopy.pdfhttps://www.researchgate.net/profile/Thanh_Nguyen68/publication/325829575_A_deep-learning_approach_for_high-speed_Fourier_ptychographic_microscopy/links/5b2beec20f7e9b0df5ba4872/A-deep-learning-approach-for-high-speed-Fourier-ptychographic-microscopy.pdfhttps://www.researchgate.net/profile/Thanh_Nguyen68/publication/325829575_A_deep-learning_approach_for_high-speed_Fourier_ptychographic_microscopy/links/5b2beec20f7e9b0df5ba4872/A-deep-learning-approach-for-high-speed-Fourier-ptychographic-microscopy.pdfhttps://www.researchgate.net/profile/Thanh_Nguyen68/publication/325829575_A_deep-learning_approach_for_high-speed_Fourier_ptychographic_microscopy/links/5b2beec20f7e9b0df5ba4872/A-deep-learning-approach-for-high-speed-Fourier-ptychographic-microscopy.pdfPublished versio

Proactive Traffic-Adaptive Tuning of Contention Window for Wireless Sensor Network Medium-Access Control Protocol

The ongoing advances in wireless networks have further expanded the boundaries to the new and challenging area of Wireless Sensor Networks (WSN). Unique properties of sensor nodes such as limited energy storage, constrained processing capabilities and the especially different environments they are usually deployed in have prompted the need of novel protocols in all the layers of the communication stack. A Medium Access Control (MAC) protocol is responsible to sufficiently provide access to a shared medium. Therefore effective techniques in order to reduce the probability of collisions while contending for the medium can be established in a MAC protocol for it organizes the specific time slot a node can have access to the channel. The need for further improving the current applied MAC protocols for WSN in order to reduce the probability of collisions while being energy aware has motivated this research. Sensor MAC as the very first MAC protocol for WSN has been designed on top of the IEEE 802.11 MAC protocol along with some added features to meet the special requirements of a WSN. However the Back-Off scheme of Sensor MAC (S-MAC) is based on a fixed Contention Window (CW) size. This is known as a significant trouble spot in S-MAC in the sense that the delay produced during collisions and idle listening can be so critical to the limited battery lifetime of a sensor node. IEEE 802.11 MAC protocol follows a static approach for obtaining the back-off time and resets the CW to its default minimum upon just one successful transmission and doubles it each time it faces a collision. While the back-off algorithm of IEEE 802.11 suffers from unfairness for its faulty behaviour in both high and low traffic loads the back-off mechanism in S-MAC suffers from a fixed CW size. Reducing the undesired idle listening time caused by unnecessary long back-off times when traffic is low and also decreasing the probability of collisions in situations with high traffic load due to the fixed CW size in S-MAC have motivated our research. We have tried to come up with a dynamic back-off algorithm for SMAC that can extract the current traffic information of the network and engage them in estimating the contention window from which the back-off time is chosen. Our approach is a proactive algorithm to get the CW of the neighbouring nodes ready before contending for the medium. The performance of our algorithm has been measured in terms of average delay, average throughput, delivery ratio, and average energy efficiency. It is shown that our back-off scheme has reduced the delay by 47% and has decreased the energy consumption up to above 15% over the current SMAC implementation. The delivery ratio and throughput have been improved up to 44% and 28% respectively

Fourier Optics in the Classroom

Borrowing methods and formulas from Prof. Goodman's classic Introduction to Fourier Optics textbook [1], I have developed a software package [2] that has been used in both industrial research and classroom teaching [3]. This paper briefly describes a few optical system simulations that have been used over the past 30 years to convey the power and the beauty of Fourier Optics to our students at the University of Arizona's College of Optical Sciences.Comment: 2 pages, 5 figures, 3 references, Published in the Proceedings of the Optical Society of America's Imaging & Applied Optics Congress, Orlando, Florida (June 2018