Investigation of improved dielectric and thermal properties of ternary nanocomposite PMMA/MXene/ZnO fabricated by in-situ bulk polymerization

Electric power system applications demand for high-temperature dielectric materials. The improved performance of polymer nanocomposites requires improvement in their thermal conductivity & stability, dielectric stability and processing technique. However, they often lose their dielectric properties with a rise in temperature. Here, we offer a solution by incorporating electrically conducting material (MXene) and semiconducting inorganic nanoparticles (ZnO NPs) into an insulating PMMA polymer matrix to maintain high dielectric constant, both at the room and high temperature. Therefore, to achieve desirable thermal and dielectric properties is the main objective of the present study based on the homogeneous distribution of the nanofillers by in-situ bulk polymerization assisted by strong sonication in the corresponding polymer. The introduction of MXene and ZnO NPs into the PMMA not only acquires a substantial increment in the dielectric constant, to attain a value 437, with minimum energy loss of 0.36 at 25 Hz, but also improves the thermal conductivity of PMMA up to 14 times by causing the reduction of thermal resistance, which is actually responsible for the poor thermal conductivity of amorphous pure PMMA polymer. More importantly, hybrid PMMA/4:2 wt% MXene:ZnO nanocomposite leads to an excellent thermal stability. Moreover, further characterization of the synthesized nanocomposites by FTIR, SEM and XRD leads to the evaluation of strong interaction of ternary components with PMMA matrix.     

Current scenario and potential of biodiesel production from waste cooking oil in Pakistan: An overview

Biodiesel utilization has been rapidly growing worldwide as the prime alternative to petrodiesel due to a global rise in diesel fuel demand along with hazardous emissions during its thermochemical conversion. Although, several debatable issues including feedstock availability and price, fuel and food competition, changes in land use and greenhouse gas emission have been raised by using edible as well as inedible feedstocks for the production of biodiesel. However, non-crop feedstocks could be a promising alternative. In this article, waste cooking oils have been recommended as a suitable option for biodiesel production bearing in mind the current national situation. The important factors such as the quantity of waste cooking oil produced, crude oil and vegetable oil import expenses, high-speed diesel imports, waste management issues and environmental hazards are considered. Moreover, process simulation and operating cost evaluation of an acid catalyzed biodiesel production unit are also conducted. The simulation results show that the production cost of waste cooking oil-based biodiesel is about 0.66USD·L^-1. We believe that the present overview would open new pathways and ideas for the development of biofuels from waste to energy approach in Pakistan.     

Fabrication and characterization of MnO2 based composite sheets for development of flexible energy storage electrodes

Development of cost efficient, flexible and light weight paper electrodes for high-tech applications is high in demand in era of modern disposable technology. In this study α-MnO₂ nanorods were fabricated through hydrothermal method by varying growth time and further combined with lignocelluloses fibers extracted from self growing plant, Monochoria Vaginalis. Crystal structure, morphology and thermal properties of MnO₂ nanorods were characterized by X. Ray Diffraction (XRD), Field Emission Scanning Electron Microscope (FESEM) and Thermogravimetric Analysis (TGA), respectively. FESEM image analysis revealed the highest aspect ratio of 48.016 for 4?h treated MnO₂ sample and high purity level was confirmed by XRD. MnO₂ sample with high aspect ratio, relatively pure and larger yield was selected for incorporation of lignocelluloses fibers to fabricate flexible, light-weight and environmentally safe LC/MnO₂ composite paper sheet. Furthermore, LC/MnO₂ composite sheet was employed as working electrode in 2?M sodium sulfate electrolyte for cyclic voltammetry measurements. Presented LC/MnO₂ composite sheet revealed specific capacitances 117, 59, 39, 25 and 23?F/g at scan rates of 5, 10, 20, 50 and 100?mV/s, respectively. Incorporation of LC fibers within MnO₂ nanorods as binders will open the possibilities to fabricate the flexible paper electrode for application in supercapacitors and batteries due to facile synthesis, light-weight and environmentally friendly aspects.     

Investigation of Dissipation,Adsorption, Degradation,and Leaching of Triazophos Pesticide in Various Soils

This study concerns the investigation of dissipation, adsorption, and degradation of triazophos in different soils from Pakistan. These processes help in the disappearance of pesticide from the environment. Gas chromatography was used for dissipation and adsorption analysis while for degradation study mass spectrometer was used in addition of gas chromatography (GC-MS). The dissipation rate of triazophos in three different soils was 90% over 30 days with average half-life of 9.059 days. From dissipation study it was inferred that rate is variable in each soil due to climatic changes, soil nature and soil-pesticide interactions. Adsorption experiment has revealed that the adsorption of this pesticide to soil follows the pseudo first order kinetic model with rate constant value of 0.479/h and Freundlich isotherm with adsorption capacity of 1.832 mol/g. Degradation study has displayed two major metabolites, one is phosphorothioic acid, S-[2-[(1-cyano-1-methylethyl) amino]-2-oxoethyl] O,O-diethyl ester at retention time of 9.136 and the other is sulfotep at 14.304 min. The leaching potential of triazophos was also calculated from its half-life and organic carbon content present in soil which was 1.688 representing it as non leacher pesticide.     

A review on fault detection and diagnosis techniques: basics and beyond

Safety and reliability are absolutely important for modern sophisticated systems and technologies. Therefore, malfunction monitoring capabilities are instilled in the system for detection of the incipient faults and anticipation of their impact on the future behavior of the system using fault diagnosis techniques. In particular, state-of-the-art applications rely on the quick and efficient treatment of malfunctions within the equipment/system, resulting in increased production and reduced downtimes. This paper presents developments within Fault Detection and Diagnosis (FDD) methods and reviews of research work in this area. The review presents both traditional model-based and relatively new signal processing-based FDD approaches, with a special consideration paid to artificial intelligence-based FDD methods. Typical steps involved in the design and development of automatic FDD system, including system knowledge representation, data-acquisition and signal processing, fault classification, and maintenance related decision actions, are systematically presented to outline the present status of FDD. Future research trends, challenges and prospective solutions are also highlighted.

     

Prediction of human breast and colon cancers from imbalanced data using nearest neighbor and support vector machines

This study proposes a novel prediction approach for human breast and colon cancers using different feature spaces. The proposed scheme consists of two stages: the preprocessor and the predictor. In the preprocessor stage, the mega-trend diffusion (MTD) technique is employed to increase the samples of the minority class, thereby balancing the dataset. In the predictor stage, machine-learning approaches of K-nearest neighbor (KNN) and support vector machines (SVM) are used to develop hybrid MTD-SVM and MTD-KNN prediction models. MTD-SVM model has provided the best values of accuracy, G-mean and Matthew's correlation coefficient of 96.71%, 96.70% and 71.98% for cancer/non-cancer dataset, breast/non-breast cancer dataset and colon/non-colon cancer dataset, respectively. We found that hybrid MTD-SVM is the best with respect to prediction performance and computational cost. MTD-KNN model has achieved moderately better prediction as compared to hybrid MTD-NB (Naïve Bayes) but at the expense of higher computing cost. MTD-KNN model is faster than MTD-RF (random forest) but its prediction is not better than MTD-RF. To the best of our knowledge, the reported results are the best results, so far, for these datasets. The proposed scheme indicates that the developed models can be used as a tool for the prediction of cancer. This scheme may be useful for study of any sequential information such as protein sequence or any nucleic acid sequence.     

Query-oriented topical influential users detection for top-k trending topics in twitter

Applied Intelligence - Online Social Networks (OSNs) have become inevitable for any new methodology both for viral promoting applications and instructing the creation of inciting information and...     

Simultaneous optimization of design and operation of multicomponent batch distillation column—single and multiple separation duties

A method is presented for the simultaneous optimization of a batch distillation column design and its operation, for single and multiple separation duties, each involving different multicomponent mixtures and complex operations with intermediate cuts. For operation structures selected a priori, the formulation presented permits the use of general distillation design and cost models. The objective function and constraints include capital and operating cost. In particular, the number of internal plates is optimized along with the most significant operating variables (recoveries in various cuts and reflux ratio profiles and times). The multiple duty formulation presented accounts for the different importance of each duty and setup time between batches. Application of the method to single duty multicomponent separation from the literature shows that significant profit improvements can be achieved within acceptable computing times. For multiple separation duties (two binary mixtures), the method clearly shows the importance of including allocation time to each duty and setup time for each batch in the objective function.     

An open-source multi-DOF articulated robotic educational platform for autonomous object manipulation

This research presents an autonomous robotic framework for academic, vocational and training purpose. The platform is centred on a 6 Degree Of Freedom (DOF) serial robotic arm. The kinematic and dynamic models of the robot have been derived to facilitate controller design. An on-board camera to scan the arm workspace permits autonomous applications development. The sensory system consists of position feedback from each joint of the robot and a force sensor mounted at the arm gripper. External devices can be interfaced with the platform through digital and analog I/O ports of the robot controller. To enhance the learning outcome for beginners, higher level commands have been provided. Advanced users can tailor the platform by exploiting the open-source custom-developed hardware and software architectures. The efficacy of the proposed platform has been demonstrated by implementing two experiments; autonomous sorting of objects and controller design. The proposed platform finds its potential to teach technical courses (like Robotics, Control, Electronics, Image-processing and Computer vision) and to implement and validate advanced algorithms for object manipulation and grasping, trajectory generation, path planning, etc. It can also be employed in an industrial environment to test various strategies prior to their execution on actual manipulators.     

An algorithm for convexity-preserving surface interpolation

A simple and efficient method of convexity-preserving interpolation for grid data is introduced. An earlier algorithm due to Roulier (1987), based on a shape-preserving curve interpolation scheme due to McAllister and Roulier (1981), is modified to use a simpler but equivalent curve interpolation scheme described in Iqbal (1992). Numerical examples are provided to test the performance of the method with the slopes that are further improved using iterative technique to produce more visually pleasing surfaces.