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| 1 | Review on materials & methods to produce controlled release coated urea fertilizer显示文摘 | Babar Azeem KuZilati KuShaari Zakaria B. Man Abdul Basit Trinh H. Thanh | 2014 | Journal of Controlled Release2014，，： | 2 |
| 2 | Astaxanthin inhibits NF-κB and Wnt/β-catenin signaling pathways via inactivation of Erk/MAPK and PI3K/Akt to induce intrinsic apoptosis in a hamster model of oral cancer显示文摘 | K. Kavitha J. Kowshik T. Kranthi Kiran Kishore Abdul Basit Baba S. Nagini | 2013 | BBA - General Subjects2013，，10： | 2 |
| 3 | An in vivo Comparison of Intestinal pH and Bacteria as Physiological Trigger Mechanisms for Colonic Targeting in Man显示文摘 | Emma L McConnell a Michael D Short Abdul W Basit | 2008 | Journal of Controlled Release2008，130，： | 1 |
| 4 | Mucoadhesive platforms for targeted delivery to the colon显示文摘 | Felipe J.O. Varum Francisco Veiga Jo?o S. Sousa Abdul W. Basit | 2011 | International Journal of Pharmaceutics2011，，1： | 1 |
| 5 | Impact of Chronic Kidney Disease Upon Survival Among Implantable Cardioverter-Defibrillator Recipients显示文摘 | Abdul Wase Abdul Basit Raja Nazir Ayman Jamal Shalin Shah Tauseef Khan Ishtiaque Mohiuddin Cynthia White Mohammad Saklayen Peter A. McCullough | 2004 | Journal of Interventional Cardiac Electrophysiology2004，，3： | 1 |
| 6 | Impact of Chronic Kidney Disease Upon Survival Among Implantable Cardioverter-Defibrillator Recipients显示文摘 | Abdul Wase Abdul Basit Raja Nazir Ayman Jamal Shalin Shah Tauseef Khan Ishtiaque Mohiuddin Cynthia White Mohammad Saklayen Peter A. McCullough | 2004 | Journal of Interventional Cardiac Electrophysiology2004，，3： | 1 |
| 7 | Impact of Chronic Kidney Disease Upon Survival Among Implantable Cardioverter-Defibrillator Recipients显示文摘 | Abdul Wase Abdul Basit Raja Nazir Ayman Jamal Shalin Shah Tauseef Khan Ishtiaque Mohiuddin Cynthia White Mohammad Saklayen Peter A. McCullough | 2004 | Journal of Interventional Cardiac Electrophysiology2004，，3： | 1 |
| 8 | Cognitive frequency diverse array radar with symmetric non-uniform frequency offset显示文摘Frequency diverse array(FDA) radar with uniform inter-element frequency offset generates a beam pattern with maxima at multiple range and angle values. Multiple maxima property allows interferers located at any of the maxima to affect the target-returns. As a result the signal to interference noise ratio(SINR) and probability of detection decreases. In this paper, we propose a cognitive uniformly-spaced FDA with non-uniform but symmetric frequency offsets to achieve a single maximum beam pattern at the target position. Moreover,these non-uniform frequency offsets are calculated using well known mu-law formulae. The design sharpens or broadens the transmitted beam pattern based on the receiver feedback to achieve a better detection probability and an improved SINR as compared to the previous designs. The performance is also analyzed by considering the Cramer-Rao lower bound(CRLB) on target angle and range estimation. | Abdul BASIT Ijaz Mansoor QURESHI Wasim KHAN Aqdas Naveed MALIK | 2016 | Science China(Information Sciences)2016，59，10： | 1 |
| 9 | Accelerating the dissolution of enteric coatings in the upper small intestine: Evolution of a novel pH 5.6 bicarbonate buffer system to assess drug release显示文摘 | Felipe J.O. Varum Hamid A. Merchant Alvaro Goyanes Pardis Assi Veronika Zboranová Abdul W. Basit | 2014 | International Journal of Pharmaceutics . 2014 (1-2)2014，，： | 1 |
| 10 | Simulation of phase sep- aration process using lattice Boltzmann method 显示文摘 | Romana B M Abdul Basit | 2010 | Canadian Journal on Computing in Mathematics Natural Sciences Engineering & Medicine2010，1，： | 1 |
| 11 | A Machine Learning Approach for Expression Detection in Healthcare Monitoring Systems显示文摘Expression detection plays a vital role to determine the patient’s condition in healthcare systems.It helps the monitoring teams to respond swiftly in case of emergency.Due to the lack of suitable methods,results are often compromised in an unconstrained environment because of pose,scale,occlusion and illumination variations in the image of the face of the patient.A novel patch-based multiple local binary patterns(LBP)feature extraction technique is proposed for analyzing human behavior using facial expression recognition.It consists of three-patch[TPLBP]and four-patch LBPs[FPLBP]based feature engineering respectively.Image representation is encoded from local patch statistics using these descriptors.TPLBP and FPLBP capture information that is encoded to find likenesses between adjacent patches of pixels by using short bit strings contrary to pixel-based methods.Coded images are transformed into the frequency domain using a discrete cosine transform(DCT).Most discriminant features extracted from coded DCT images are combined to generate a feature vector.Support vector machine(SVM),k-nearest neighbor(KNN),and Naïve Bayes(NB)are used for the classification of facial expressions using selected features.Extensive experimentation is performed to analyze human behavior by considering standard extended Cohn Kanade(CK+)and Oulu–CASIA datasets.Results demonstrate that the proposed methodology outperforms the other techniques used for comparison. | Muhammad Kashif Ayyaz Hussain Asim Munir Abdul Basit Siddiqui AaqifAfzaal Abbasi Muhammad Aakif Arif Jamal Malik Fayez Eid Alazemi Oh-Young Song | 2021 | Computers, Materials & Continua2021，，5： | 0 |
| 12 | Spatio-temporal variations in trends of vegetation and drought changes in relation to climate variability from 1982 to 2019 based on remote sensing data from East Asia显示文摘Studying the significant impacts on vegetation of drought due to global warming is crucial in order to understand its dynamics and interrelationships with temperature,rainfall,and normalized difference vegetation index(NDVI).These factors are linked to excesses drought frequency and severity on the regional scale,and their effect on vegetation remains an important topic for climate change study.East Asia is very sensitive and susceptible to climate change.In this study,we examined the effect of drought on the seasonal variations of vegetation in relation to climate variability and determined which growing seasons are most vulnerable to drought risk;and then explored the spatio-temporal evolution of the trend in drought changes in East Asia from 1982 to 2019.The data were studied using a series of several drought indexes,and the data were then classified using a heat map,box and whisker plot analysis,and principal component analysis.The various drought indexes from January to August improved rapidly,except for vegetation health index(VHI)and temperature condition index(TCI).While these indices were constant in September,they increased again in October,but in December,they showed a descending trend.The seasonal and monthly analysis of the drought indexes and the heat map confirmed that the East Asian region suffered from extreme droughts in 1984,1993,2007,and 2012among the study years.The distribution of the trend in drought changes indicated that more severe drought occurred in the northwestern region than in the southeastern area of East Asia.The drought tendency slope was used to describe the changes in drought events during 1982–2019 in the study region.The correlations among monthly precipitation anomaly percentage(NAP),NDVI,TCI,vegetation condition index(VCI),temperature vegetation drought index(TVDI),and VHI indicated considerably positive correlations,while considerably negative correlations were found among the three pairs of NDVI and VHI,TVDI and VHI,and NDVI and TCI.This ecological and climatic mechanism provides a good basis for the assessment of vegetation and drought-change variations within the East Asian region.This study is a step forward in monitoring the seasonal variation of vegetation and variations in drought dynamics within the East Asian region,which will serve and contribute to the better management of vegetation,disaster risk,and drought in the East Asian region. | Shahzad ALI Abdul BASIT Muhammad UMAIR Tyan Alice MAKANDA Fahim Ullah KHAN Siqi SHI NI Jian | 2023 | Journal of Integrative Agriculture2023，22，10： | 0 |
| 13 | Probing nutritional and functional properties of salted noodles supplemented with ripen Banana peel powder显示文摘Banana peel is appreciated for higher dietary fiber, phenolics, flavonoid contents, and minerals (particularly iron, calcium, and potassium), despite being a waste product. After drying, it can be processed into powder/flour to be combined with wheat flour (WF) for development of value-added products. In this study, we substituted WF with banana peel powder (BPP) at supplementation rates of 5, 10, and 15%, and evaluated their suitability to develop salted noodles. The results showed that the composite flour with 15% BPP had significantly higher protein, ash, and crude fiber content as compared to control. Higher antioxidant capacity was observed in composite flour noodles: total phenolics content (TPC), total flavonoid content (TFC), ferric reducing power (FRAP) and DPPH reducing power were increased up to 278, 260, 143 and 13 percent respectively in the noodles containing 15% BPP as compared to control (100% WF). On the other hand, values for viscosity decreased up to 22% with addition of BPP in WF. Furthermore, water absorption capacity and cooking losses were increased up to 15 and 13 percent respectively with 15% BPP incorporation in WF. Results for sensory evaluation demonstrated that noodles with 10% BPP scored highest for sensory profile. | Imran Pasha Abdul Basit Muhammad Ahsin Farah Ahmad | 2022 | Food Production, Processing and Nutrition2022，4，1： | 0 |
| 14 | Phase Time for the Tunneling of Ultracold V-Type Atoms Through a Mazer Cavity显示文摘We study the tunneling time of ultracold V-type atoms interacting a high quality microwave cavity. Here atomic coherence is introduced in the system by a strong driving field which couples the two lower states of the three-level atom. It is found that in the presence of coherence, mazer action or the scattering like nature of the interaction may be examined for extended energies of the incident cold atoms. Our results show that position and amplitudes of the peak values of the phase time(traversal time) may be very effectively controlled by the coherent driving field. Further, here we obtained superclassical values of the phase time corresponding to much higher values of the transmission amplitudes of the tunneling atoms which may be advantageous in the possible experimental realization of the superclassical tunneling time of the traversing cold atoms. In addition, we examine a mirror reflection type symmetry in the phase time curve for a judicious choice of the external driving field. | Fazal Badshah Abdul Basit Hamad Ali Qing He Guo-Qin Ge | 2019 | Communications in Theoretical Physics2019，71，5： | 0 |
| 15 | Enhancement of Quantum Correlations in Qubit-Qutrit Systems under the non-Markovian Environment显示文摘We investigate the time evolution of quantum correlations of a hybrid qubit-qutrit system under the classical Ornstein-Uhlenbeck(OU) noise. Here we consider two different one-parameter families of qubit-qutrit states which independently interact with the non-Markovian reservoirs. A comparison with the Markovian dynamics reveals that for the same set of initial condition parameters, the non-Markovian behavior of the environment plays an important role in the enhancement of the survival time of quantum correlations. In addition, it is observed that the non-Markovian strength(γ/Γ) has a positive impact on the correlations time. For the initial separable states it is found that there is a finite time interval in which the geometric quantum discord is frozen despite the presence of a noisy environment and that interval can be further prolonged by using the non-Markovian property. Moreover, its decay can be significantly delayed. | Abdul Basit Hamad Ali Fazal Badshah 葛国勤 | 2017 | Communications in Theoretical Physics2017，67，7： | 0 |
| 16 | Lifetime Prediction of LiFePO_(4) Batteries Using Multilayer Classical-Quantum Hybrid Classifier显示文摘This article presents a multilayer hybrid classical-quantum classifier for predicting the lifetime of LiFePO_(4) batteries using early degradation data.The multilayer approach uses multiple variational quantum circuits in cascade,which allows more parameters to be used as weights in a single run hence increasing accuracy and provides faster cost function convergence for the optimizer.The proposed classifier predicts with an accuracy of 92.8%using data of the first four cycles.The effectiveness of the hybrid classifier is also presented by validating the performance using untrained data with an accuracy of 84%.We also demonstrate that the proposed classifier outperforms traditional machine learning algorithms in classification accuracy.In this paper,we show the application of quantum machine learning in solving a practical problem.This study will help researchers to apply quantum machine learning algorithms to more complex real-world applications,and reducing the gap between quantum and classical computing. | Muhammad Haris Muhammad Noman Hasan Abdul Basit Shiyin Qin | 2021 | Journal of Quantum Computing2021，3，3： | 0 |
| 17 | Comprehensive genetic screening reveals wide spectrum of genetic variants in monogenic forms of diabetes among Pakistani population显示文摘BACKGROUND Monogenic forms of diabetes(MFD)are single gene disorders.Their diagnosis is challenging,and symptoms overlap with type 1 and type 2 diabetes.AIM To identify the genetic variants responsible for MFD in the Pakistani population and their frequencies.METHODS A total of 184 patients suspected of having MFD were enrolled.The inclusion criterion was diabetes with onset below 25 years of age.Brief demographic and clinical information were taken from the participants.The maturity-onset diabetes of the young(MODY)probability score was calculated,and glutamate decarboxylase ELISA was performed.Antibody negative patients and features resembling MODY were selected(n=28)for exome sequencing to identify the pathogenic variants.RESULTS A total of eight missense novel or very low-frequency variants were identified in 7 patients.Three variants were found in genes for MODY,i.e.HNF1A(c.169C>A,p.Leu57Met),KLF11(c.401G>C,p.Gly134Ala),and HNF1B(c.1058C>T,p.Ser353Leu).Five variants were found in genes other than the 14 known MODY genes,i.e.RFX6(c.919G>A,p.Glu307Lys),WFS1(c.478G>A,p.Glu160Lys)and WFS1(c.517G>A,p.Glu173Lys),RFX6(c.1212T>A,p.His404Gln)and ZBTB20(c.1049G>A,p.Arg350His).CONCLUSION The study showed wide spectrum of genetic variants potentially causing MFD in the Pakistani population.The MODY genes prevalent in European population(GCK,HNF1A,and HNF4a)were not found to be common in our population.Identification of novel variants will further help to understand the role of different genes causing the pathogenicity in MODY patient and their proper management and diagnosis. | Ibrar Rafique Asif Mir Shajee Siddiqui Muhammad Arif Nadeem Saqib Asher Fawwad Luc Marchand Muhammad Adnan Muhammad Naeem Abdul Basit Constantin Polychronakos | 2021 | World Journal of Diabetes2021，12，11： | 0 |
| 18 | Optimal Weighted Extreme Learning Machine for Cybersecurity Fake News Classification显示文摘Fake news and its significance carried the significance of affecting diverse aspects of diverse entities,ranging from a city lifestyle to a country global relativity,various methods are available to collect and determine fake news.The recently developed machine learning(ML)models can be employed for the detection and classification of fake news.This study designs a novel Chaotic Ant Swarm with Weighted Extreme Learning Machine(CAS-WELM)for Cybersecurity Fake News Detection and Classification.The goal of the CAS-WELM technique is to discriminate news into fake and real.The CAS-WELM technique initially pre-processes the input data and Glove technique is used for word embed-ding process.Then,N-gram based feature extraction technique is derived to gen-erate feature vectors.Lastly,WELM model is applied for the detection and classification of fake news,in which the weight value of the WELM model can be optimally adjusted by the use of CAS algorithm.The performance validation of the CAS-WELM technique is carried out using the benchmark dataset and the results are inspected under several dimensions.The experimental results reported the enhanced outcomes of the CAS-WELM technique over the recent approaches. | Ashit Kumar Dutta Basit Qureshi Yasser Albagory Majed Alsanea Manal Al Faraj Abdul Rahaman Wahab Sait | 2023 | Computer Systems Science & Engineering2023，44，3： | 0 |
| 19 | Coherent Control of the Hartman Effect through a Photonic Crystal with Four-Level Defect Layer显示文摘In this paper, we examine the transmission of a probe field through a one dimensional photonic crystal (1DPC) when the sixth layer of the crystal is doped with four level atoms. We analyze effects of the external driving field on the passage of weak probe field across the photonic crystal. It is found that for the phase time delay of the probe photons, intensity of the driving field switches the Hartman effect from sub to superluminal character. It is interesting to note that in our model, the superluminal transmission of the probe pulse is accompanied by a negligibly small absorption of the incident beam. It ensures that the probe field does not attenuate while passing through the photonic crystal. A similar switching of the Hartman effect may be obtained by adjusting detuning of the probe field related to the excited states of the four-level doping atoms. | Feng-Lian Hu Fazal Badshah Abdul Basit Hai-Yang Zhang Qing He Guo-Qin Ge | 2018 | Communications in Theoretical Physics2018，69，11： | 0 |
| 20 | Optimal Deep Belief Network Enabled Cybersecurity Phishing Email Classification显示文摘Recently,developments of Internet and cloud technologies have resulted in a considerable rise in utilization of online media for day to day lives.It results in illegal access to users’private data and compromises it.Phishing is a popular attack which tricked the user into accessing malicious data and gaining the data.Proper identification of phishing emails can be treated as an essential process in the domain of cybersecurity.This article focuses on the design of bio-geography based optimization with deep learning for Phishing Email detection and classification(BBODL-PEDC)model.The major intention of the BBODL-PEDC model is to distinguish emails between legitimate and phishing.The BBODL-PEDC model initially performs data pre-processing in three levels namely email cleaning,tokenization,and stop word elimination.Besides,TF-IDF model is applied for the extraction of useful feature vectors.Moreover,optimal deep belief network(DBN)model is used for the email classification and its efficacy can be boosted by the BBO based hyperparameter tuning process.The performance validation of the BBODL-PEDC model can be performed using benchmark dataset and the results are assessed under several dimensions.Extensive comparative studies reported the superior outcomes of the BBODL-PEDC model over the recent approaches. | Ashit Kumar Dutta T.Meyyappan Basit Qureshi Majed Alsanea Anas Waleed Abulfaraj Manal M.Al Faraj Abdul Rahaman Wahab Sait | 2023 | Computer Systems Science & Engineering2023，44，3： | 0 |
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