Autonomous navigation and control of magnetic microcarriers using potential field algorithm and adaptive non-linear PID.

Microparticles are increasingly employed as drug carriers inside the human body. To avoid collision with environment, they reach their destination following a predefined trajectory. However, due to the various disturbances, tracking control of microparticles is still a challenge. In this work, we propose to use an Adaptive Nonlinear PID (A-NPID) controller for trajectory tracking of microparticles. A-NPID allows the gains to be continuously adjusted to satisfy the performance requirements at different operating conditions. An in-vitro study is conducted to verify the proposed controller where a microparticle of 100 µ m diameter is put to navigate through an open fluidic reservoir with virtual obstacles. Firstly, a collision-free trajectory is generated using a path-planning algorithm. Secondly, the microparticle dynamic model, when moving under the influence of external forces, is derived, and employed to design the A-NPID control law. The proposed controller successfully allowed the particle to navigate autonomously following the reference collision-free trajectory in presence of varying environmental conditions. Moreover, the particle could reach its targeted position with a minimal steady-state error of 4 µ m. A degradation in the performance was observed when only a PID controller was used in the absence of adaptive terms. The results have been verified by simulation and experimentally.

Sentiment analysis techniques, challenges, and opportunities: Urdu language-based analytical study.

Sentiment analysis in research involves the processing and analysis of sentiments from textual data. The sentiment analysis for high resource languages such as English and French has been carried out effectively in the past. However, its applications are comparatively few for resource-poor languages due to a lack of textual resources. This systematic literature explores different aspects of Urdu-based sentiment analysis, a classic case of poor resource language. While Urdu is a South Asian language understood by one hundred and sixty-nine million people across the planet. There are various shortcomings in the literature, including limitation of large corpora, language parsers, and lack of pre-trained machine learning models that result in poor performance. This article has analyzed and evaluated studies addressing machine learning-based Urdu sentiment analysis. After searching and filtering, forty articles have been inspected. Research objectives have been proposed that lead to research questions. Our searches were organized in digital repositories after selecting and screening relevant studies. Data was extracted from these studies. Our work on the existing literature reflects that sentiment classification performance can be improved by overcoming the challenges such as word sense disambiguation and massive datasets. Furthermore, Urdu-based language constructs, including language parsers and emoticons, context-level sentiment analysis techniques, pre-processing methods, and lexical resources, can also be improved.

Effect of Ranque-Hilsch Vortex Tube Cooling to Enhance the Surface-Topography and Tool-Wear in Sustainable Turning of Al-5.6Zn-2.5Mg-1.6Cu-0.23Cr-T6 Aerospace Alloy.

The aerospace metal cutting industry's search for environmentally friendly practices that do not compromise machining performance is well known. One of the major objectives is the reduction in use of cutting fluids, which play a major role in containing the harsh effects of severe heat generated during machining. Machining performance and product quality can be improved by controlling heat during machining. The purpose of this study was to determine the effectiveness of various environmentally friendly metalworking fluid (MF) strategies for the sustainable turning of aerospace aluminum alloy (Al-5.6Zn-2.5Mg-1.6Cu-0.23Cr-T6) for automotive, marine, and aerospace industrial applications. The SEM images were analyzed for worn tool surfaces and machined surfaces. Under dry conditions, heat does not dissipate well, and will enter the workpiece due to the absence of coolant. This causes extreme damage beneath a turned workpiece. Thus, at 10 µm, a drop in microhardness of approximately 20% can be observed. A similar observation was made in a Ranque-Hilsch vortex tube (RHVT) and in compressed air; however, the drop in hardness was relatively low compared to dry conditions. This evaluation of microhardness indicated a heat-based attention in the turned workpiece, and thus, the heat-based effect was found to be lowest in RHVT and compressed air compared to dry conditions. Results showed that RHVT reduces temperature up to 10%, surface roughness 13%, and tool wear 20% compared to dry turning. Overall, RHVT was identified as more effective environmentally friendly cooling strategy than dry and compressed air for the turning of aluminum alloy 7075-T6.

Novel Synthesis of Sensitive Cu-ZnO Nanorod-Based Sensor for Hydrogen Peroxide Sensing.

We aimed to synthesize sensitive electrochemical sensors for hydrogen peroxide sensing by using zinc oxide nanorods grown on a fluorine-doped tin oxide electrode by using the facial hydrothermal method. It was essential to keep the surface morphology of the material (nanorods structure); due to its large surface area, the concerned material has enhanced detection ability toward the analyte. The work presents a non-enzymatic H2O2 sensor using vertically grown zinc oxide nanorods on the electrode (FTO) surfaces with Cu nanoparticles deposited on zinc oxide nanorods to enhance the activity. Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), energy-dispersive X-Ray (EDX), X-ray diffraction (XRD), and electrochemical methods were used to characterize copper-zinc oxide nanorods. In addition to the high surface area, the hexagonal Cu-ZnO nanorods exhibited enhanced electrochemical features of H2O2 oxidation. Nanorods made from Cu-ZnO exhibit highly efficient sensitivity of 3415 µAmM-1cm-2 low detection limits (LODs) of 0.16 µM and extremely wide linear ranges (0.001-11 mM). In addition, copper-zinc oxide nanorods demonstrated decent reproducibility, repeatability, stability, and selectivity after being used for H2O2 sensing in water samples with an RSD value of 3.83%. Cu nanoparticles decorated on ZnO nanorods demonstrate excellent potential for the detection of hydrogen peroxide, providing a new way to prepare hydrogen peroxide detecting devices.

Morphological, Physical, and Mechanical Properties of Sugar-Palm (Arenga pinnata (Wurmb) Merr.)-Reinforced Silicone Rubber Biocomposites.

The development of environmentally benign silicone composites from sugar palm fibre and silicone rubber was carried out in this study. The mechanical, physical, and morphological properties of the composites with sugar palm (SP) filler contents ranging from 0% to 16% by weight (wt%) were investigated. Based on the uniaxial tensile tests, it was found that the increment in filler content led to higher stiffness. Via dynamic mechanical analysis (DMA), the viscoelastic properties of the silicone biocomposite showed that the storage modulus and loss modulus increased with the increment in filler content. The physical properties also revealed that the density and moisture absorption rate increased as the filler content increased. Inversely, the swelling effect of the highest filler content (16 wt%) revealed that its swelling ratio possessed the lowest rate as compared to the lower filler addition and pure silicone rubber. The morphological analysis via scanning electron microscopy (SEM) showed that the sugar palm filler was evenly dispersed and no agglomeration could be seen. Thus, it can be concluded that the addition of sugar palm filler enhanced the stiffness property of silicone rubber. These new findings could contribute positively to the employment of natural fibres as reinforcements for greener biocomposite materials.

Analysis of fuzzified boundary value problems for MHD Couette and Poiseuille flow.

In an uncertain atmosphere, the magnetohydrodynamics (MHD) flow in three principal flows of the third grade fluid across two parallel plates is presented. Fuzzy differential equations are constructed by manipulating dimensionless differential equations. The prime purpose of the current article is to use a semi-analytical approach fuzzy-based Adomian decomposition method to achieve numerical results for nonlinear FDEs with fuzzy boundary conditions. Triangular fuzzy numbers are used in fuzzy BCs with help of [Formula: see text] approach. This strategy is linked to the membership function. In a graphic and tabular depiction, the effect of [Formula: see text] and other constraints on fuzzy velocity profiles is explored. The current findings are in good agreement with their previous numerical and analytical results in a crisp environment.