Effects of HD-tDCS on Resting-State Functional Connectivity in the Prefrontal Cortex: An fNIRS Study

Yaqub, M. Atif,Woo, Seong-Woo,Hong, Keum-Shik Hindawi Limited 2018 Complexity Vol.2018 No.-

<P>Functional connectivity is linked to several degenerative brain diseases prevalent in our aging society. Electrical stimulation is used for the clinical treatment and rehabilitation of patients with many cognitive disorders. In this study, the effects of high-definition transcranial direct current stimulation (HD-tDCS) on resting-state brain networks in the human prefrontal cortex were investigated by using functional near-infrared spectroscopy (fNIRS). The intrahemispheric as well as interhemispheric connectivity changes induced by 1 mA HD-tDCS were examined in 15 healthy subjects. Pearson correlation coefficient-based correlation matrices were generated from filtered time series oxyhemoglobin (ΔHbO) signals and converted into binary matrices. Common graph theory metrics were computed to evaluate the network changes. Systematic interhemispheric, intrahemispheric, and intraregional connectivity analyses demonstrated that the stimulation positively affected the resting-state connectivity in the prefrontal cortex. The poststimulation connectivity was increased throughout the prefrontal region, while focal HD-tDCS effects induced an increased rate of connectivity in the stimulated hemisphere. The graph theory metrics clearly distinguished the prestimulation and poststimulation networks for a range of thresholds. The results of this study suggest that HD-tDCS can be used to increase functional connectivity in the prefrontal cortex. The increase in functional connectivity can be explored clinically for neurorehabilitation of patients with degenerative brain diseases.</P>

Soft computing techniques in prediction Cr(VI) removal efficiency of polymer inclusion membranes

Muhammad Yaqub,Beytullah EREN,Volkan Eyupoglu 대한환경공학회 2020 Environmental Engineering Research Vol.25 No.3

In this study soft computing techniques including, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were investigated for the prediction of Cr(VI) transport efficiency by novel Polymer Inclusion Membranes (PIMs). Transport experiments carried out by varying parameters such as time, film thickness, carrier type, carier rate, plasticizer type, and plasticizer rate. The predictive performance of ANN and ANFIS model was evaluated by using statistical performance criteria such as Root Mean Standard Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R<SUP>2</SUP>). Moreover, Sensitivity Analysis (SA) was carried out to investigate the effect of each input on PIMs Cr(VI) removal efficiency. The proposed ANN model presented reliable and valid results, followed by ANFIS model results. RMSE and MAE values were 0.00556, 0.00163 for ANN and 0.00924, 0.00493 for ANFIS model in the prediction of Cr(VI) removal efficiency on testing data sets. The R2 values were 0.973 and 0.867 on testing data sets by ANN and ANFIS, respectively. Results show that the ANN-based prediction model performed better than ANFIS. SA demonstrated that time; film thickness; carrier type and plasticizer type are major operating parameters having 33.61%, 26.85%, 21.07% and 8.917% contribution, respectively.

Thermodynamic and kinetic effect of biodegradable polymers on carbondioxide hydrates

Sana Yaqub,Bhajan lal,Lau Kok Keong 한국공업화학회 2019 Journal of Industrial and Engineering Chemistry Vol.79 No.-

In this work, the effect of biodegradable polymers, i.e. pectin (PC), sodium-carboxymethyl cellulose (Na-CMC), tapioca starch (TS) and dextran (DX) on thermodynamics and kinetics of CO2 hydrates areevaluated on sapphire hydrate reactor. The CO2 hydrate liquid vapour equilibrium (HLwVE) data isevaluated in the presence of biopolymers (1.5 wt%) using isochoric T-cycle method at temperature andpressure ranging from 278.7 to 283.0 K and 2.3 to 4.3 MPa respectively. The effect of biopolymers onHLwVE curve is reported by measuring average increment temperature (DÜ). The constant coolingmethod is used to evaluate the kinetics of CO2 hydrates at 4.3 MPa in the presence of biopolymers (0.12–1.5 wt%) at 274.15 K and 277.15 K. The inhibition effect of biopolymers on the kinetics of CO2 hydrate isreported by measuring induction time, hydrate formation rate and amount of gas consumed. The kineticinhibition strength of biopolymers is compared with poly-N-vinylpyrrolidone (PVP) and with two noncommercialinhibitors, i.e. glycine and tetra-methyl ammonium chloride (TMACl) through relativeinhibition strength (RIS). Results reveal that DX shows maximum increment temperature of 0.36 K. WhilePC and Na-CMC delayed CO2 hydrate nucleation for 423 and 181 min respectively. Additionally,biodegradation study on biopolymers indicates that, compared to PVP, biopolymers are easilybiodegradable and show potential for gas hydrate offshore applications.

Effect of Copper Content in the New Conductive Material Cu-SPB Used in Low-temperature Li-ion Batteries

Adnan Yaqub,Syed Atif Pervez,Umer Farooq,Mohsin Saleem,도칠훈,You-Jin Lee,Minji Hwang,Jeong-Hee Choi,Doohun Kim 한국물리학회 2014 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.65 No.3

A new conductive material, copper/Super-P carbon black composite (Cu-SPB), is prepared viaan efficient ion reducing method for use in low-temperature lithium-ion batteries (LIBs). Thepresent study investigated the effects of copper content on the low-temperature performance ofLIBs. Electrodes prepared with a high-copper-content conductive material (Cu = 18.54%) showedremarkably improved performance in terms of capacity retention (around 40%), cycling stability, andcolumbic efficiency. The electrochemical impedance spectroscopy (EIS) analysis revealed that thepresence of higher Cu contents could reduce the cell’s impedance. The results were also confirmedby using a coin-type full cell’s improved capacity retention, which indicated the significance of Cuparticles in enhancing the low-temperature performance of LIBs.

Zero-liquid discharge (ZLD) technology for resource recovery from wastewater: A review

Muhammad Yaqub,Lee, Wontae Elsevier BV 2019 Science of the Total Environment Vol. No.

<P><B>Abstract</B></P> <P>Water resources are becoming scarce meaning that reuse options are receiving more and more attention. In this perspective, zero-liquid discharge (ZLD) is considered as an emerging technique to minimize waste, recover resources, treat toxic industrial waste streams, and mitigate potential water quality impacts in receiving water streams. Although ZLD systems are capable of minimizing contamination of water sources and amplifying water supply, its industrial scale applications are restricted due to their high cost and intensive energy consumption. In ZLD systems, membrane-based technologies are an attractive future strategy for industrial wastewater reclamation. Therefore, this review examines why a greater focus on environmental protection and water security is leading to more widespread adoption of ZLD technology in various industries. We highlight existing ZLD processing schemes, including thermal and membrane-based processes, and discuss their limitations and potential solutions. We also investigated global application of ZLD systems for resource recovery from wastewater. Finally, we discuss the potential environmental impacts of ZLD technologies and provide some focus on future research needs.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Encapsulated the ZLD systems, operational principle and their significance </LI> <LI> Detailed study of existing ZLD technologies, their benefits, drawbacks and industrial application </LI> <LI> Described global status of ZLD systems commissioned, in progress or planned in near future </LI> <LI> Presented environmental and operational aspects of ZLD with possible solutions </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

A Spiral Curve Gait Design for a Modular Snake Robot Moving on a Pipe

Sheraz Yaqub,Ahmad Ali,Muhammad Usman,Khalil Muhammad Zuhaib,Abdul Manan Khan,안보영,문현기,이지영,한창수 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.10

Modular snake robot has the ability to maneuver narrow, complex, and unstructured environments. In recent years, Snake robot with 3-D locomotion has been studied by researchers for inspection of pipes, and stairs climbing etc. One of the effective approaches to accomplishing such complex tasks is by designing gaits for modular snake robot. In this paper, A Spiral curve gait along with rolling motion is proposed to adapt to the changes in the pipe diameter while moving on the pipe, which cannot be overcome by a simple helical rolling motion. The joint angles are calculated using Bellow’s model, based on the curvature and torsion of the backbone curve. We validated the proposed gait by simulating thirty degrees of freedom modular snake robot in Open Dynamics Engine simulator.

Experimental and neural network modeling of micellar enhanced ultrafiltration for arsenic removal from aqueous solution

Muhammad Yaqub,Seung Hwan Lee 대한환경공학회 2021 Environmental Engineering Research Vol.26 No.1

The optimization of micellar-enhanced ultrafiltration (MEUF) of arsenic (As) contaminated aqueous solution using cetylpyridinium chloride (CPC) as surfactant was studied through experimental and artificial neural network (ANN) modeling. Experimental studies were carried out by varying operational conditions such as time, pressure, molar ratio of CPC to As, concentration of As and pH of feed solution. Root mean square error (RMSE) and coefficient of determination (R²) were considered as performance criterion to evaluate the predicted results of ANN model. The experimental studies provided optimum operating parameters such as pressure 1.8 bar, molar ratio of CPC to As was 5:1, As concentration 1 mM and pH 8.0 of feed solution. ANN model presented reliable results with RMSE values 0.259, 0.553 and 0.623 for training, validation and testing datasets, respectively, while R² values for training, validation and testing dataset were noted as 0.962, 0.942 and 0.932, respectively. The proposed ANN model traced input-output relationship to predict As removal efficiency (RE) of MEUF process. Therefore, ANN model can be considered as a competitive, powerful and fast alternate because of its high computational speed, accuracy and economics in MEUF process optimization without doing laborious experimental work.

Heavy metals removal from aqueous solution through micellar enhanced ultrafiltration

Muhammad Yaqub,Seung Hwan Lee 대한환경공학회 2019 Environmental Engineering Research Vol.24 No.3

Micellar-enhanced ultrafiltration (MEUF) is a surfactant-based separation technique and has been investigated for the removal of heavy metals from wastewater. The performance of heavy metals removal from wastewater through MEUF relies on membrane characteristics, surfactant properties, various operational parameters including operating pressure, surfactant and heavy metal concentration, pH of the solution, temperature, and presence of dissolved solutes and salts. This study presents an overview of literature related to MEUF with respect to the all significant parameters including membranes, surfactants, operating conditions and MEUF hybrid processes. Moreover, this study illustrates that MEUF is an adaptable technique in various applications. Nowadays water contamination caused by heavy metals has become a serious concern around the globe. MEUF is a significant separation technique in wastewater treatment that should be acknowledged, for the reason that removal of heavy metals contamination even at lower concentrations becomes achievable, which is evidently made known in the presented review. Hybrid processes presented the better results as compared to MEUF. Future studies are required to continue the experimental work with various combinations of surfactant and heavy metals, and to investigate for the treatment of concentrated solutions, as well as for real industrial wastewater.

EE-PBC: Energy Efficient Position Based Clustering for Strip Area WSN

M. A. Yaqub,A. N. Alvi,Syed Hassan Ahmed,N. Javaid,S. H. Bouk 한국산업정보학회 2014 한국산업정보학회 학술대회논문집 Vol.2014 No.1

Development of a High Density Neuroimaging System Using Functional Near-Infrared Spectroscopy

M. Atif Yaqub,Amad Zafar,Usman Ghafoor,Keum-Shik Hong 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10

The progress in the field of neuroscience is critical in our rapidly aging society as the fatality rate due to brain degenerative diseases is rising. Recently, functional near-infrared spectroscopy (fNIRS) has established its application in measuring the blood chromophores’ concentration changes during an activity. In this developmental study, we have introduced our lab-developed fNIRS system that is able to compute the concentration changes in oxy-hemoglobin and deoxy-hemoglobin from the optical NIR light signals. We have employed 128 dual wavelength light emitting diodes (LEDs) of 735 nm and 850 nm in the designed system. LED driving circuit was designed by using serial peripheral interface based output expansion chips. A single photodiode (PD) was used for measuring the NIR light intensity received after passing through the brain tissue and getting absorbed and scattered in the process. Our system uses a battery for supplying power to the system. A wireless communication module was interfaced with the system for transferring the fNIRS data to our developed software running on a host computer. The software is capable of displaying the real-time data and record it for future processing. To test the functionality of the system, a phantom brain model was used. The LED and PD were attached to the phantom and multiple combinations of LEDs were tested to provide robust data. Our lab-developed fNIRS system showed the acquired intensity values for both wavelengths which corresponds to hemoglobin changes in 128 channels.