Papers by Muhammad Razzaq
Nanoscale, 2012
The thermally induced shape memory effect (SME) is the capability of a material to fix a temporar... more The thermally induced shape memory effect (SME) is the capability of a material to fix a temporary (deformed) shape and recover a 'memorized' permanent shape in response to heat. SMEs in polymers have enabled a variety of applications including deployable space structures, biomedical devices, adaptive optical devices, smart dry adhesives and fasteners. By the incorporation of magnetic nanoparticles (mNP) into shape-memory polymer (SMP), a magnetically controlled SME has been realized. Magnetic actuation of nanocomposites enables remotely controlled devices based on SMP, which might be useful in medical technology, e.g. remotely controlled catheters or drug delivery systems. Here, an overview of the recent advances in the field of magnetic actuation of SMP is presented. Special emphasis is given on the magnetically controlled recovery of SMP with one switching temperature T sw (dual-shape effect) or with two T sw s (triple-shape effect). The use of magnetic field to change the apparent switching temperature (T sw,app) of the dual or triple-shape nanocomposites is described. Finally, the capability of magnetic nanocomposites to remember the magnetic field strength (H) initially used to deform the sample (magnetic-memory effect) is addressed. The distinguished advantages of magnetic heating over conventional heating methods make these multifunctional nanocomposites attractive candidates for in vivo applications.
Applied Sciences
Four-dimensional (4D) printing technology, as a next-generation additive manufacturing method, en... more Four-dimensional (4D) printing technology, as a next-generation additive manufacturing method, enables printed objects to further change their shapes, functionalities, or properties upon exposure to external stimuli. The 4D printing of programmable and deformable materials such as thermo-responsive shape-memory polymers (trSMPs), which possess the ability to change shape by exposure to heat, has attracted particular interest in recent years. Three-dimensional objects based on SMPs have been proposed for various potential applications in different fields, including soft robotics, smart actuators, biomedical and electronics. To enable the manufacturing of complex multifunctional 3D objects, SMPs are often coupled with other functional polymers or fillers during or before the 3D printing process. This review highlights the 4D printing of state-of-the-art multi-component SMP formulations. Commonly used 4D printing technologies such as material extrusion techniques including fused filame...
This research was conducted to assess the indirect selection of yield through yield contributing ... more This research was conducted to assess the indirect selection of yield through yield contributing traits because seed yield possess complex inheritance and low heritability. In this study fifteen hybrids of sunflower (Helianthus annuus L.) were evaluated in autumn 2016; RCB design in triplicate by maintaining row to row and plant to plant distance of 75 cm and 9 cm respectively, for days to 50% flowering, head diameter, seed weight head-1 , 100 seed weight, oil contents, multithreads, leaves plant-1 , stem thickness at base and at angle of curvature, endosperm and testa weight of 100 seeds. Relationship between these traits and their direct and indirect effect on seed yield were assessed. These computed correlations among number of leaves plant-1 , stem thickness at base, 100 seed weight, seed weight head-1 , endosperm and testa weight of 100 seeds had highly significant positive relationship with seed yield. However, multiheads had weak negative relationship and oil contents had no ...
Research Papers in Economics, 2014
This study examines the mediating role of multidimensional organizational commitment concept in d... more This study examines the mediating role of multidimensional organizational commitment concept in determining the relationship between Big Five personality traits and job performance. A conceptual framework has been developed with multidimensional organizational commitment as a mediating variable linking the personality-performance relationship. It is hypothesized that affective commitment will mediate the relationship between extraversion and job performance. Affective commitment will also mediate the relationship between conscientiousness and job performance. It is also hypothesized that continuance commitment will mediated the relationship between neuroticism and job performance. Theoretical implications are discussed.
Recently, deep learning has been adopted to the glaucoma classification task with performance com... more Recently, deep learning has been adopted to the glaucoma classification task with performance comparable to that of human experts. However, a well trained deep learning model demands a large quantity of properly labeled data, which is relatively expensive since the accurate labeling of glaucoma requires years of specialist training. In order to alleviate this problem, we propose a glaucoma classification framework which takes advantage of not only the properly labeled images, but also undiagnosed images without glaucoma labels. To be more specific, the proposed framework is adapted from the teacher-studentlearning paradigm. The teacher model encodes the wrapped information of undiagnosed images to a latent feature space, meanwhile the student model learns from the teacher through knowledge transfer to improve the glaucoma classification. For the model training procedure, we propose a novel training strategy that simulates the real-world teaching practice named as "Learning To Teach with Knowledge Transfer (L2T-KT)", and establish a"Quiz Pool" as the teacher's optimization target. Experiments show that the proposed framework is able to utilize the undiagnosed data effectively to improve the glaucoma prediction performance.
Journal of Chromatography & Separation Techniques, 2020
A method using dispersive solid-phase extraction (d-SPE) cleanup followed by QuEChERS with High P... more A method using dispersive solid-phase extraction (d-SPE) cleanup followed by QuEChERS with High Performance Liquid Chromatography (HPLC) has been established for determination of Neonicotinoid pesticide residues in various vegetables including brinjal, salad leaves, coriander, cabbage and lady finger. Based on an assessment of the HPLC characteristics, validation experiments are conducted for three Neonicotinoid pesticides i.e. Nitenpyram, Imidacloprid and Acetamiprid. In acidified acetonitrile analytical extraction is done with NaCl and MgSO4 followed by activated neutral carbon. The method show good linearity (R2 ā„ 0.999) and relative standard deviation (RSD ā¤ 3.36%). Average recoveries of three insecticides are in the range of 55% to 82% at spiking levels of 275.68 to 409.3 mg.Kg-1. LOD and LOQ of three Neonicotinoid pesticides are in the range of 2.658 - 3.761 mg.Kg-1 and 8.056 - 11.4 mg.Kg-1. This QuEChERS determination method by HPLC is precise, simple, sensitive, accurate, ea...
Cureus, 2021
Introduction There are conflicting studies regarding the efficacy of tocilizumab use in coronavir... more Introduction There are conflicting studies regarding the efficacy of tocilizumab use in coronavirus disease 2019 (COVID-19) disease. There is a special need to identify the parameters that could predict its response in early COVID-19 disease. Objective To report our experience with tocilizumab and correlate the magnitude of fall in c-reactive protein (CRP) as a predictor of its response to treatment in early COVID-19 disease. Methods All confirmed COVID-19 cases admitted to a tertiary healthcare hospital in Peshawar Pakistan, receiving ā„1 dose of intravenous tocilizumab, between March and September 2020 were included. Relevant clinical data of the patients were recorded and further divided into two categories based on the relative fall in CRP levels, 48 hours after tocilizumab administration. Adequate response (ā„50% fall from baseline CRP), primary outcomes (fall in oxygen requirement and inflammatory biomarkers), and secondary outcome (all-cause mortality at day 28) were recorded. All outcomes were compared based on falls in CRP levels. Results A total of 27 patients were included. Males were 24 (88.8%) while females were three (11.1%). The mean age was 60.9Ā±11.6 years. The mean day of illness at the time of tocilizumab administration was 4.26Ā±3 days. After 48 hours of tocilizumab administration, 17 (62.9%) patients showed clinical improvement, with the mean SaO 2 /FiO 2 ratio prior to treatment significantly increased (p<0.01). A significant reduction in CRP and ferritin levels was seen post-treatment (p <0.01 and p<0.01, respectively). Twenty (74.1%) patients demonstrated adequate response to tocilizumab while seven (25.9%) showed an inadequate response. Patients with adequate response had higher chances of improvement in oxygenation and lower in-hospital mortality (p-value 0.009 and 0.020, respectively). Conclusions Tocilizumab shows clinical improvement in a vast majority of patients. Being an early and sensitive predictor, a fall of ā„50% in CRP at 48 hours can be used to predict the overall response to tocilizumab as a guide to treatment.
First data on the predation of Felis catus L., 1758 on Gallotia simonyi machadoi LĆ³pez-Jurado, 1989 in El Hierro, Canary Islands (Sauria, Lacertidae): notes
Exploring Narratives from the Frontlines of War and the Frontlines of the Classroom: Shifting Mindsets and Developing Options in Complex Situations
Induction motors play a key role in moving the wheel of the modern industry with ever increasing ... more Induction motors play a key role in moving the wheel of the modern industry with ever increasing demand and need of high performance and more efficient electric machines. To meet this ever increasing demand, this thesis covers the base of it i.e. losses occurring in the induction motor and thermal modelling of motor on the basis of the losses. In order to compute the iron losses, COMSOL Multiphysics has been put to use which is a very useful for vast analysis on the basis of Finite Element Analysis. A quasi 3D model of the induction motor is built in COMSOL to compute the losses occurring in the stator and rotor of the induction motor. These losses are then put to further application by building 3D thermal model of the same motor in COMSOL Multiphsics for modelling the thermal behaviour of the machine. In order to validate the theoretical work, experiments have been conducted on actual machine. In order to get vast practical data of temperature from the motor, a dedicated printed ci...
Debate about the value of providing corrective feedback on L2 learning has been prominent in rece... more Debate about the value of providing corrective feedback on L2 learning has been prominent in recent years. Although a number of studies have investigated the effects of CF on L2 learners, little is understood about how CF assists both teachers' and learners' development. The present study examines various types of feedback such as recast, clarification request, elicitation, repetition, etc. used by the teacher and the relationship to learner uptake and immediate repair of errors. In addition, it deals with how, when, where the errors should be corrected, and also who should do the correction. It is assumed that drawing students' attention to their errors not only causes awareness in learners but also assists teachers to become aware of themselves both as a teacher and as an individual; hence, all these must be taken into account.
International Journal of Knowledge and Learning, 2020
Farhan has been serving in the academic industry for almost 15 years with a successful demonstrat... more Farhan has been serving in the academic industry for almost 15 years with a successful demonstration of professional ability as an academic and as an administrator. He has expanded his portfolio as a lead consultant trainer at the Management Institute for Research and Skill Development (MIRS), intending to work for the development of the deprived ones. Farhan's research interests include knowledge and technology management, leadership, and teams.
Effect of Drought on Morpho-Physiological Traits of Sunflower (Helianthus Annuus L) Hybrids and their Parental Inbred Lines
Pakistan Journal of Agricultural Research, 2018
UCAmI 2018, 2018
In this work, we detail a methodology based on Convolutional Neural Networks (CNNs) to detect fal... more In this work, we detail a methodology based on Convolutional Neural Networks (CNNs) to detect falls from non-invasive thermal vision sensors. First, we include an agile data collection to label images in order to create a dataset that describes several cases of single and multiple occupancy. These cases include standing inhabitants and target situations with a fallen inhabitant. Second, we provide data augmentation techniques to increase the learning capabilities of the classification and reduce the configuration time. Third, we have defined 3 types of CNN to evaluate the impact that the number of layers and kernel size have on the performance of the methodology. The results show an encouraging performance in single-occupancy contexts, with up to 92 % of accuracy, but a 10 % of reduction in accuracy in multiple-occupancy. The learning capabilities of CNNs have been highlighted due to the complex images obtained from the low-cost device. These images have strong noise as well as unce...
Pakistan Journal of Zoology, 2019
Authors' Contribution FA compiled and collected the data and wrote the manuscript with the help o... more Authors' Contribution FA compiled and collected the data and wrote the manuscript with the help of NA, AR and NS. MSA designed and supervised the study. KB helped in data collection. MR and NID helped in field work.
Clinical Medicine, 2019
We were pleased to receive over 150 abstract submissions to be considered for presentation at the... more We were pleased to receive over 150 abstract submissions to be considered for presentation at the conference, all of which were of very high quality. This following abstracts have been approved to be presented as posters at the conference.
Proceedings, 2018
Activity recognition (AR) is a subtask in pervasive computing and context-aware systems, which pr... more Activity recognition (AR) is a subtask in pervasive computing and context-aware systems, which presents the physical state of human in real-time. These systems offer a new dimension to the widely spread applications by fusing recognized activities obtained from the raw sensory data generated by the obtrusive as well as unobtrusive revolutionary digital technologies. In recent years, an exponential growth has been observed for AR technologies and much literature exists focusing on applying machine learning algorithms on obtrusive single modality sensor devices. However, University of JaƩn Ambient Intelligence (UJAmI), a Smart Lab in Spain has initiated a 1st UCAmI Cup challenge by sharing aforementioned varieties of the sensory data in order to recognize the human activities in the smart environment. This paper presents the fusion, both at the feature level and decision level for multimodal sensors by preprocessing and predicting the activities within the context of training and test...
Sensors (Basel, Switzerland), Jan 24, 2017
The emerging research on automatic identification of user's contexts from the cross-domain en... more The emerging research on automatic identification of user's contexts from the cross-domain environment in ubiquitous and pervasive computing systems has proved to be successful. Monitoring the diversified user's contexts and behaviors can help in controlling lifestyle associated to chronic diseases using context-aware applications. However, availability of cross-domain heterogeneous contexts provides a challenging opportunity for their fusion to obtain abstract information for further analysis. This work demonstrates extension of our previous work from a single domain (i.e., physical activity) to multiple domains (physical activity, nutrition and clinical) for context-awareness. We propose multi-level Context-aware Framework (mlCAF), which fuses the multi-level cross-domain contexts in order to arbitrate richer behavioral contexts. This work explicitly focuses on key challenges linked to multi-level context modeling, reasoning and fusioning based on the mlCAF open-source ont...
Sensors (Basel, Switzerland), Jan 29, 2016
Recent years have witnessed a huge progress in the automatic identification of individual primiti... more Recent years have witnessed a huge progress in the automatic identification of individual primitives of human behavior, such as activities or locations. However, the complex nature of human behavior demands more abstract contextual information for its analysis. This work presents an ontology-based method that combines low-level primitives of behavior, namely activity, locations and emotions, unprecedented to date, to intelligently derive more meaningful high-level context information. The paper contributes with a new open ontology describing both low-level and high-level context information, as well as their relationships. Furthermore, a framework building on the developed ontology and reasoning models is presented and evaluated. The proposed method proves to be robust while identifying high-level contexts even in the event of erroneously-detected low-level contexts. Despite reasonable inference times being obtained for a relevant set of users and instances, additional work is requi...
Sensors (Basel, Switzerland), Jan 10, 2016
There is sufficient evidence proving the impact that negative lifestyle choices have on people... more There is sufficient evidence proving the impact that negative lifestyle choices have on people's health and wellness. Changing unhealthy behaviours requires raising people's self-awareness and also providing healthcare experts with a thorough and continuous description of the user's conduct. Several monitoring techniques have been proposed in the past to track users' behaviour; however, these approaches are either subjective and prone to misreporting, such as questionnaires, or only focus on a specific component of context, such as activity counters. This work presents an innovative multimodal context mining framework to inspect and infer human behaviour in a more holistic fashion. The proposed approach extends beyond the state-of-the-art, since it not only explores a sole type of context, but also combines diverse levels of context in an integral manner. Namely, low-level contexts, including activities, emotions and locations, are identified from heterogeneous senso...
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Papers by Muhammad Razzaq