Designing optimal prototype filters for maximally decimated Cosine Modulated filter banks with rapid convergence.

An analytic design of a prototype filter for M-channel maximally decimated cosine-modulated Near Perfect Reconstruction (NPR) filter banks is proposed in this work. The prototype filter is created using the least-square (CLS) method with weighted constraints, which is one-dimensional and requires single-parameter optimization. Compared to existing approaches, this suggested method achieves rapid convergence by analytically determining the optimal step size, ensuring the 3 dB cutoff frequency at π/2 M. The simulation results for design examples outperform the techniques in the available literature in terms of amplitude and aliasing distortion, reaching distortion around 2.4489 × 10-4 and 3.4907 × 10-9, respectively. This optimization algorithm's usefulness is further demonstrated with the sub-band coding of ECG signals. Implementing optimal prototype filters has tangible real-world effects, especially in critical sectors like healthcare and communications, improving diagnostics accuracy, data transmission efficiency, and overall performance.

Significant Increase in the Dipole Moment of Graphene on Functionalization: DFT Calculations and Molecular Dynamics Simulations.

The limited solubility of graphene in water can be attributed to the existence of π-π bonds connecting its layers. Functionalized graphene or graphene oxide (GO) is frequently produced in order to overcome the shortcomings of graphene. Using density functional theory (DFT) calculation, functionalized graphene with various combinations of hydroxyl, epoxy, and carboxylic functional groups were investigated computationally. The study focused on the effects of functional group combinations on the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energies, giving information about the chemical reactivity and stability of the molecules under investigation. Global chemical reactivity descriptors, including chemical hardness, softness, electronegativity, chemical potential, and electrophilicity index, were calculated to further elucidate the overall stability and reactivity of the molecules. The results demonstrated that the introduction of oxygen-containing functional groups on graphene significantly influenced its electronic properties, leading to variations in the chemical reactivity and stability. Molecular electrostatic potential (MEP) maps highlighted the susceptibility of specific regions to electrophilic and nucleophilic attacks. The flexibility and stability of functionalized graphene through root mean square fluctuation (RMSF) and root mean square deviation (RMSD) analyses indicate the stability of functionalized graphene in water. This comprehensive computational investigation provides valuable insights into the design and understanding of functionalized graphene for potential applications in drug delivery.

HARNet in deep learning approach-a systematic survey.

A comprehensive examination of human action recognition (HAR) methodologies situated at the convergence of deep learning and computer vision is the subject of this article. We examine the progression from handcrafted feature-based approaches to end-to-end learning, with a particular focus on the significance of large-scale datasets. By classifying research paradigms, such as temporal modelling and spatial features, our proposed taxonomy illuminates the merits and drawbacks of each. We specifically present HARNet, an architecture for Multi-Model Deep Learning that integrates recurrent and convolutional neural networks while utilizing attention mechanisms to improve accuracy and robustness. The VideoMAE v2 method ( https://github.com/OpenGVLab/VideoMAEv2 ) has been utilized as a case study to illustrate practical implementations and obstacles. For researchers and practitioners interested in gaining a comprehensive understanding of the most recent advancements in HAR as they relate to computer vision and deep learning, this survey is an invaluable resource.

Design and development of PI controller for DFIG grid integration using neural tuning method ensembled with dense plexus terminals.

In a DFIG grid interconnected system, the control of real and reactive power relies on various factors. This paper presents an approach to regulate the flow of real and reactive power using a Neural Tuning Machine (NTM) based on a recurrent neural network. The focus is on controlling the flow of reactive power from the rotor-side converter, which is proportional to the grid-side controller through a coupling voltage. The proposed NTM method leverages neural networks to fine-tune the parameters of the PI controller, optimizing performance for DFIG grid integration. By integrating dense plexus terminals, also known as dense connections, within the neural network, the control system achieves enhanced adaptability, robustness, and nonlinear dynamics, addressing the challenges of the grid. Grid control actions are based on the voltage profile at different bus locations, thereby regulating voltage. This article meticulously examines the analysis in terms of DFIG configuration and highlights the advantages of the neural tuning machine in controlling inner current loop parameters compared to conventional PI controllers. To demonstrate the robustness of the control algorithm, a MATLAB Simulink model is designed, and validation is conducted with three different benchmarking models. All calculations and results presented in the article strictly adhere to IEEE and IEC standards. This research contributes to advancing control methodologies for DFIG grid integration and lays the groundwork for further exploration of neural tuning methods in power system control.

Application of DSO algorithm for estimating the parameters of triple diode model-based solar PV system.

Solar Photovoltaic (SPV) technology advancements are primarily aimed at decarbonizing and enhancing the resiliency of the energy grid. Incorporating SPV is one of the ways to achieve the goal of energy efficiency. Because of the nonlinearity, modeling of SPV is a very difficult process. Identification of variables in a lumped electric circuit model is required for accurate modeling of the SPV system. This paper presents a new state-of-the-art control technique based on human artefacts dubbed Drone Squadron Optimization for estimating 15 parameters of a three-diode equivalent model solar PV system. The suggested method simulates a nonlinear relationship between the P-V and I-V performance curves, lowering the difference between experimental and calculated data. To evaluate the adaptive performance in every climatic state, two different test cases with commercial PV cells, RTC France and photo watt-201, are used. The proposed method provides a more accurate parameter estimate. To validate the recommended approach's performance, the data are compared to the results of the most recent and powerful methodologies in the literature. For the RTC and PWP Photo Watt Cell, the DSO technique has the lowest Root Mean Square Error (RMSE) of 6.7776 × 10-4 and 0.002310324 × 10-4, respectively.

Microplastic contamination in water and sediments of Mahanadi River, India: An assessment of ecological risk along rural-urban area.

Worldwide, environmental concerns about MPs pollution have increased. Microplastic contamination that pollutes the ocean is mostly caused by terrestrial transfer from close proximity locations. A study of MPs pollution near coastal locations becomes necessary to address the MPs transit, fate, and mitigation. In the current study MPs pollution in the surface water and sediment of the Mahanadi River estuary was assessed during Pre-MS and MS. The size, shape, and colour of the MPs were determined using a stereomicroscope, and the MPs polymer composition was identified by Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy. The mean concentration of MPs that were potentially discovered in water was 16.6 ± 5.2 and sediments 197.3 ± 5.4 during Pre-MS. In the MS observed mean abundance of MPs was 15.1 ± 5.4 in water and 164.6 ± 76.9 in sediments. The highest abundant size was smaller than 1 mm; the most prevalent shape were fibers followed by film and fragments; black and white was a prominent colour in water and sediments respectively. Polyesters (PEs), polyethylene (PE), polyvinyl chloride (PVC), polypropylene (PP), polyamide (PA), Polystyrene (PS), and Polycarbonates (PC) were found in the analysis of the chemical composition of MPs in water and sediments samples. The calculated PLI value shows pollution load at category I, with polymer hazard levels at categories III, IV, and V, indicating very high risk. The current research results show that river inflows and fishing-related actions are probably the main causes of MPs pollution.

Biosorption of Escherichia coli Using ZnO-Trimethyl Chitosan Nanocomposite Hydrogel Formed by the Green Synthesis Route.

In this study, we tested the biosorption capacity of trimethyl chitosan (TMC)-ZnO nanocomposite (NC) for the adsorptive removal of Escherichia coli (E. coli) in aqueous suspension. For the formation of ZnO NPs, we followed the green synthesis route involving Terminalia mantaly (TM) aqueous leaf extract as a reducing agent, and the formed ZnO particles were surface-coated with TMC biopolymer. On testing of the physicochemical characteristics, the TM@ZnO/TMC (NC) hydrogel showed a random spherical morphology with an average size of 31.8 ± 2.6 nm and a crystal size of 28.0 ± 7.7 nm. The zeta potential of the composite was measured to be 23.5 mV with a BET surface area of 3.01 m2 g-1. The spectral profiles of TM@ZnO/TMC NC hydrogel on interaction with Escherichia coli (E. coli) revealed some conformational changes to the functional groups assigned to the stretching vibrations of N-H, C-O-C, C-O ring, and C=O bonds. The adsorption kinetics of TM@ZnO/TMC NC hydrogel revealed the pseudo-second-order as the best fit mechanism for the E. coli biosorption. The surface homogeneity and monolayer adsorption of the TM@ZnO/TMC NC hydrogel reflects majorly the entire adsorption mechanism, observed to display the highest correlation for Jovanovic, Redlich-Peterson, and Langmuir's isotherm models. Further, with the use of TM@ZnO/TMC NC hydrogel, we measured the highest adsorption capacity of E. coli to be 4.90 × 10 mg g-1, where an in-depth mechanistic pathway was proposed by making use of the FTIR analysis.

Magnetically controlled drug delivery and hyperthermia effects of core-shell Cu@Mn3O4 nanoparticles towards cancer cells in vitro.

Recent increase in the integration of nanotechnology and nanosciences to the biomedical sector fetches the human wellness through the development of sustainable treatment methodologies for cancerous tumors at all stages of their initiation and progression. This involves the development of multifunctional theranostic probes that effectively support for the early cancer diagnosis, avoiding non-target cell toxicity, controlled and customized anticancer drug release etc. Therefore, to advance the field of nanotechnology-based sustainable cancer treatment, we fabricated and tested the efficacy of anticancer drug-loaded magnetic hybrid nanoparticles (NPs) towards in vitro cell culture systems. The developed conjugate of NPs was incorporated with the functions of both controlled drug delivery and heat-releasing ability using Mn3O4 (manganese oxide) magnetic core with Cu shell encapsulated within trimethyl chitosan (TMC) biopolymer. On characterization, the Cu@Mn3O4-TMC NPs were confirmed to have an approximate size of 130 nm with full agglomeration (as observed by the HRTEM) and crystal size of 92.95 ± 18.38 nm with tetragonal hausmannite phase for Mn3O4 spinel structure (XRD). Also, the UV-Vis and FTIR analysis provided the qualitative and quantitative effects of 5-fluororacil (5-Fu) anticancer drug loading (max 68 %) onto the Cu@Mn3O4-TMC NPs. The DLS analysis indicated for the occurrence of no significant changes to the particle size (around 100 nm) of Cu@Mn3O4-TMC due to the solution dispersion thereby confirming for the aqueous stability of developed NPs. In addition, the magnetization values of Cu@Mn3O4-TMC NPs were measured to be 34 emu/g and a blocking temperature of 42 K. Further tests of magnetic hyperthermia by the Cu@Mn3O4-TMC/5-Fu NPs provided that the heat-releasing capacity (% ΔT at 15 min) increases with that of increased frequency, i.e. 28 % (440 Hz) > 22.6 % (240 Hz) > 18 % (44 Hz), and the highest specific power loss (SPL) value observed to be 488 W/g for water. Moreover, the 5-Fu drug release studies indicate that the release is high at a pH of 5.2 and almost all the loaded drug is getting delivered under the influence of the external magnetic field (430 Hz) due to the influence of both Brownian-rotation and Néel relaxation heat-mediated mechanism. The pharmacokinetic drug release studies have suggested for the occurrence of more than one model, i.e. First-order, Higuchi (diffusion), and Korsemeyer-Peppas (non-Fickian), in addition to hyperthermia. Finally, the in vitro cell culture systems (MCF-7 cancer and MCF-10 non-cancer) helped to differentiate the physiological changes due to the effects of hyperthermia and 5-Fu drug individually and as a combination of both. The observed differences of cell viability losses among both cell types are measured and discussed with the expression of heat shock proteins (HSPs) by the MCF-10 cells as against the MCF-7 cancer cells. We believe that the results generated in this project can be helpful for the designing of new cancer therapeutic models with nominal adverse effects on healthy normal cells and thus paving a way for the treatment of cancer and other deadly diseases in a sustainable manner.

The Health Risk and Source Assessment of Polycyclic Aromatic Hydrocarbons (PAHs) in the Soil of Industrial Cities in India.

Industrial areas play an important role in the urban ecosystem. Industrial site environmental quality is linked to human health. Soil samples from two different cities in India, Jamshedpur and Amravati, were collected and analyzed to assess the sources of polycyclic aromatic hydrocarbons (PAHs) in industrial areas and their potential health risks. The total concentration of 16 PAHs in JSR (Jamshedpur) varied from 1662.90 to 10,879.20 ng/g, whereas the concentration ranged from 1456.22 to 5403.45 ng/g in the soil of AMT (Amravati). The PAHs in the samples were dominated by four-ring PAHs, followed by five-ring PAHs, and a small percentage of two-ring PAHs. The ILCR (incremental lifetime cancer risk) of the soil of Amravati was lower compared to that of Jamshedpur. The risk due to PAH exposure for children and adults was reported to be in the order of ingestion > dermal contact > inhalation while for adolescents it was dermal contact > ingestion > inhalation in Jamshedpur. In contrast, in the soil of Amravati, the PAH exposure path risk for children and adolescents were the same and showed the following order: dermal contact > ingestion > inhalation while for the adulthood age group, the order was ingestion > dermal contact > inhalation. The diagnostic ratio approach was used to assess the sources of PAHs in various environmental media. The PAH sources were mainly dominated by coal and petroleum/oil combustion. As both the study areas belong to industrial sites, the significant sources were industrial emissions, followed by traffic emissions, coal combustion for domestic livelihood, as well as due to the geographical location of the sampling sites. The results of this investigation provide novel information for contamination evaluation and human health risk assessment in PAH-contaminated sites in India.

A Comparative Study on Predication of Appropriate Mechanical Ventilation Mode through Machine Learning Approach.

Ventilation mode is one of the most crucial ventilator settings, selected and set by knowledgeable critical care therapists in a critical care unit. The application of a particular ventilation mode must be patient-specific and patient-interactive. The main aim of this study is to provide a detailed outline regarding ventilation mode settings and determine the best machine learning method to create a deployable model for the appropriate selection of ventilation mode on a per breath basis. Per-breath patient data is utilized, preprocessed and finally a data frame is created consisting of five feature columns (inspiratory and expiratory tidal volume, minimum pressure, positive end-expiratory pressure, and previous positive end-expiratory pressure) and one output column (output column consisted of modes to be predicted). The data frame has been split into training and testing datasets with a test size of 30%. Six machine learning algorithms were trained and compared for performance, based on the accuracy, F1 score, sensitivity, and precision. The output shows that the Random-Forest Algorithm was the most precise and accurate in predicting all ventilation modes correctly, out of the all the machine learning algorithms trained. Thus, the Random-Forest machine learning technique can be utilized for predicting optimal ventilation mode setting, if it is properly trained with the help of the most relevant data. Aside from ventilation mode, control parameter settings, alarm settings and other settings may also be adjusted for the mechanical ventilation process utilizing appropriate machine learning, particularly deep learning approaches.

Enhanced Delivery of Insulin through Acrylamide-Modified Chitosan Containing Smart Carrier System.

The present study develops on insulin-release studies from the chitosan-amide-modified stimuli-responsive polymers formed from various fatty acids including stearic acid, oleic acid, linoleic acid, and linolenic acid. This is the continuation of an earlier reported study that investigates the insulin-release profiles of chitosan-modified fatty acid amides (without stimuli responsive polymers). Following the synthesis and characterization of many different fatty acid amides with a varying amount of unsaturation, the insulin drug loading and release effects were compared among N-isopropylacrylamide (NIPAm), a thermo-responsive polymer, and 2-acrylamide-2-methylpropane sulfonic acid (AMPS), a pH-responsive polymer-modified hydrogel that is expected to enhance environmental response and the controllability of release. Finally, drug release effects were studied to investigate the drug release mechanisms with the help of five different pharmacokinetic models including the zero-order, first-order, Higuchi, Korsmeyers-Peppas, and Hixson models. The results indicate that the Higuchi and Hixson models are valid in terms of the operation of the NIPAm and AMPS matrices during the delivery of insulin.

Diagnostic accuracy and limit of detection of ten malaria parasite lactate dehydrogenase-based rapid tests for Plasmodium knowlesi and P. falciparum.

Background: Plasmodium knowlesi causes zoonotic malaria across Southeast Asia. First-line diagnostic microscopy cannot reliably differentiate P. knowlesi from other human malaria species. Rapid diagnostic tests (RDTs) designed for P. falciparum and P. vivax are used routinely in P. knowlesi co-endemic areas despite potential cross-reactivity for species-specific antibody targets. Methods: Ten RDTs were evaluated: nine to detect clinical P. knowlesi infections from Malaysia, and nine assessing limit of detection (LoD) for P. knowlesi (PkA1-H.1) and P. falciparum (Pf3D7) cultures. Targets included Plasmodium-genus parasite lactate dehydrogenase (pan-pLDH) and P. vivax (Pv)-pLDH. Results: Samples were collected prior to antimalarial treatment from 127 patients with microscopy-positive PCR-confirmed P. knowlesi mono-infections. Median parasitaemia was 788/µL (IQR 247-5,565/µL). Pan-pLDH sensitivities ranged from 50.6% (95% CI 39.6-61.5) (SD BIOLINE) to 87.0% (95% CI 75.1-94.6) (First Response® and CareStart™ PAN) compared to reference PCR. Pv-pLDH RDTs detected P. knowlesi with up to 92.0% (95% CI 84.3-96.7%) sensitivity (Biocredit™). For parasite counts ≥200/µL, pan-pLDH (Standard Q) and Pv-pLDH RDTs exceeded 95% sensitivity. Specificity of RDTs against 26 PCR-confirmed negative controls was 100%. Sensitivity of six highest performing RDTs were not significantly different when comparing samples taken before and after (median 3 hours) antimalarial treatment. Parasite ring stages were present in 30% of pre-treatment samples, with ring stage proportions (mean 1.9%) demonstrating inverse correlation with test positivity of Biocredit™ and two CareStart™ RDTs.For cultured P. knowlesi, CareStart™ PAN demonstrated the lowest LoD at 25 parasites/µL; LoDs of other pan-pLDH ranged from 98 to >2000 parasites/µL. Pv-pLDH LoD for P. knowlesi was 49 parasites/µL. No false-positive results were observed in either P. falciparum-pLDH or histidine-rich-protein-2 channels. Conclusion: Selected RDTs demonstrate sufficient performance for detection of major human malaria species including P. knowlesi in co-endemic areas where microscopy is not available, particularly for higher parasite counts, although cannot reliably differentiate among non-falciparum malaria.

Direct, indirect, post-infection damages induced by coronavirus in the human body: an overview.

Background: Severe acute respiratory syndrome Coronavirus-2 invades the cells via ACE2 receptor and damages multiple organs of the human body. Understanding the pathological manifestation is mandatory to endure the rising post-infection sequel reported in patients with or without comorbidities. Materials and methods: Our descriptive review emphasises the direct, indirect and post-infection damages due to COVID-19. We have performed an electronic database search according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines with selective inclusion and exclusion criteria. Results: The included studies substantiated the extensive damages in the multiple organs due to direct and indirect consequences of COVID-19. After an apparent recovery, the prolonged presentation of the symptoms manifests as post-COVID that can be related with persisting viral antigens and dysregulated immune response. Conclusion: A few of the symptoms of respiratory, cardiovascular, and neuropsychiatric systems that persist or reappear as post-COVID manifestations. Vaccination and preventive programs will effectively reduce the prevalence but, the post-COVID, a multisystem manifestation, will be a significant tribulation to the medical profession. However, the issue can be managed by implementing public health programs, rehabilitation services, and telemedicine virtual supports to raise awareness and reduce panic.

Surface-Enhanced Carboxyphenyl Diazonium Functionalized Screen-Printed Carbon Electrode for the Screening of Tuberculosis in Sputum Samples.

Curbing tuberculosis (TB) requires a combination of good strategies, including a proper prevention measure, diagnosis, and treatment. This study proposes an improvised tuberculosis diagnosis based on an amperometry approach for the sensitive detection of MPT64 antigen in clinical samples. An MPT64 aptamer specific to the target antigen was covalently attached to the carboxyphenyl diazonium-functionalized carbon electrode via carbodiimide chemistry. The electrochemical detection assay was adapted from a sandwich assay format to trap the antigen between the immobilized aptamer and horseradish peroxidase (HRP) tagged polyclonal anti-MPT64 antibody. The amperometric current was measured from the catalytic reaction response between HRP, hydrogen peroxide, and hydroquinone, which is used as an electron mediator. From the analysis, the detection limit in the measurement buffer was 1.11 ng mL-1. Additionally, the developed aptasensor exhibited a linear relationship between the current signal and the MPT64 antigen-spiked serum concentration ranging from 10 to 150 ng mL-1 with a 1.38 ng mL-1 detection limit. Finally, an evaluation using the clinical sputum samples from both TB (+) and TB (-) individuals revealed a sensitivity and specificity of 88% and 100%, respectively. Based on the analysis, the developed aptasensor was found to be simple in its fabrication, sensitive, and allowed for the efficient detection and diagnosis of TB in sputum samples.

Fabrication of magnetite nanomaterials employing novel ionic liquids for efficient oil spill cleanup.

The oil spill represents one of the most important pollution sources for marine environments, that occurs due to tanker collisions, ship accidents, and platforms. Several techniques are used for treating oil spill disasters including chemical, physical, and biochemical. The use of chemicals, magnetite nanomaterials (MNMs) in particular, is one of the most applied techniques used for oil spill remediation due to their low cost, fast remediation, and reusability. This work aims to synthesize and use new ionic liquids (ILs) for the modification of MNMs surfaces to enhance their performance for crude oil uptake. For that, octadecylamine (OA) was reacted with epichlorohydrin (EH), followed by reaction with either diethylenetriamine (DT), or tetraethylenepentamine (TP) to obtain corresponding amines, OADT, and OATP, respectively. The produced amines were quaternized using acetic acid (AA) forming corresponding ILs, OADT-IL, and OATP-IL. The obtained ILs, OADT-IL, and OATP-IL were applied for modification of magnetite nanomaterials (MNMs) surface to obtain the surface-modified MNMs, DT-MNMs, and TP-MNMs, respectively. The surface-modified MNMs were characterized using different techniques including Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), vibrating sample magnetometer (VSM), and contact angle. The efficacy of DT-MNMs, and TP-MNMs for heavy crude oil uptake (EMU) was evaluated. Further, the factors affecting on the crude oil uptake including MNMs: heavy crude oil ratio, and contact time were also evaluated. The data exhibited that, the EMU relatively declined as the ratio of DT-MNMs, and TP-MNMs decreased. Even at low MNMs:crude oil ratio (1:50), DT-MNMs, and TP-MNMs displayed EMU 87%, and 90%, respectively, which means 1 g of either DT-MNMs, or TP-MNMs can uptake 45 g, or 43.5 g, respectively. These values are high as compared with other studies that reported the use of MNMs for oil spill cleanup. Furthermore, the data indicated that the EMU increased as the contact time increased, and reached maximum EMU of 98% for both MNMs samples after 10 min.

Surface-Enhanced Biocompatibility and Adsorption Capacity of a Zirconium Phosphate-Coated Polyaniline Composite.

The present study deals with the synthesis, characterization, and testing of a novel composite, zirconium(IV) phosphate-coated polyaniline (ZrPO4@PANI), toward the adsorption- and surface-controlled toxicity applications. Following the synthesis of the ZrPO4@PANI composite using the sol-gel route, various characterization techniques such as Fourier transform infrared spectroscopy, scanning electron microscopy, and powder X-ray diffraction were employed to confirm its surface functionality, morphology and agglomeration, and crystallinity and crystal nature, respectively. The composite was found to be effective toward the adsorptive removal of the methylene blue dye (an organic pollutant) as against the changes in the dye concentration, dose, pH, and so forth. Also, to understand the MB adsorption kinetics, the experimental data were evaluated using the Langmuir and Freundlich models and the results were described in accordance with the Langmuir isotherm model (an adsorption capacity of 120.48 mg/g at ambient temperature). In addition, the tests conducted using pseudo-first- and pseudo-second-order kinetic models confirmed the existence of pseudo-second-order rates. Furthermore, the calculation of thermodynamic parameters for the MB adsorption, namely, changes in enthalpy, entropy, and Gibbs' free energy, exhibited a spontaneous, feasible, and exothermic nature. Finally, the comparative studies of in vitro toxicity and flow cytometry confirmed that the copresence of ZrPO4 along with PANI significantly improved the biocompatibility. The outcome of the experimental results implies that the composite is capable enough of serving as the safe and low-cost adsorbent, in addition to supporting the effective capping of the surface toxicity of PANI.

Investigation of the Tribological Characteristics of Aluminum 6061-Reinforced Titanium Carbide Metal Matrix Composites.

The current trend in the materials engineering sector is to develop newer materials that can replace the existing materials in various engineering sectors in order to be more and more efficient. Therefore, the present research work is aimed at fabricating and determining the physical, mechanical, and dry sliding wear properties of titanium carbide (TiC)-reinforced aluminum alloy (Al6061) metal matrix composites (MMCs). For the study, the Al6061-TiC microparticle-reinforced composites were fabricated via the liquid metallurgy route through the stir casting method, where the reinforcement of the TiC particles into the Al6061 alloy matrix was added in the range of 0 to 8.0 wt.%, i.e., in the steps of 2.0 wt.%. The synthesis procedure followed the investigation of the various mechanical properties of Al6061-TiC MMCs, such as the density and structure, as well as mechanical and dry wear experimentation. The tests performed on the casted Al6061, as well as its TiC composites, were in harmony with ASTM standards. As per the experimental outcome, it can be confirmed that the increase in the weight percentage of TiC into the Al6061 alloy substantially increases the density, hardness, and tensile strength, at the expense of the percentage of elongation. In addition, the dry wear experiments, performed on a pin-on-disc tribometer, showed that the Al6061-TiC MMCs have superior wear-resistance properties, as compared to those of pure Al6061 alloy. Furthermore, optical micrograph (OM), powdered X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), and scanning electron microscopy (SEM) analyses were employed for the developed Al6061-TiC MMCs before and after the fracture and wear test studies. From the overall analysis of the results, it can be observed that the Al6061-TiC composite material with higher TiC reinforcement displays superior mechanical characteristics.

Adsorption, Equilibrium Isotherm, and Thermodynamic Studies towards the Removal of Reactive Orange 16 Dye Using Cu(I)-Polyaninile Composite.

To overcome some of the limitations of activated carbon like efficiency, cost-effectiveness, and reusability, the present work deals with Cu(I)-based polyaniline (PANI) composite for the removal of reactive orange 16 (RO16) dye. Following the synthesis and characterization of formed Cu(I)-PANI composite, the batch experiments performed for the removal of RO16 dye indicated that the composite has the capacity to reduce the coloring from RO16. The experiments were conducted for the study of effects against changes in pH, time, and dose at room temperature, where we observed for a pH impact on the dye adsorption capacity in the range of 2-12. Among all, the optimal RO16 removal was found to be 94.77% at a pH of 4 and in addition, the adsorption kinetics confirmed to be pseudo-second-order with more suitability towards the Langmuir isotherm, where it is presumed to be the formation of a monolayer of dye molecule at the homogeneous absorbent surface. The calculated maximum capacity, qm, determined from the Langmuir model was 392.156 mg/g. Further application of isotherms to attain thermodynamic parameters, a slight positive value of ΔS° for RO16 adsorption was observed, meaning that there is an increased randomness in the irregular pattern at the specific Cu(I)-PANI interface for an adsorption process. This mechanism plays an essential role in maintaining the effects of water pollution; and, based on the analysis therefore, it is prominent that the Cu(I)-PANI composite can be employed as a promising and economical adsorbent for the treatment of RO16 and other dye molecules from the sewage in wastewater.

Drug Release Profiles of Mitomycin C Encapsulated Quantum Dots-Chitosan Nanocarrier System for the Possible Treatment of Non-Muscle Invasive Bladder Cancer.

Nanotechnology-based drug delivery systems are an emerging technology for the targeted delivery of chemotherapeutic agents in cancer therapy with low/no toxicity to the non-cancer cells. With that view, the present work reports the synthesis, characterization, and testing of Mn:ZnS quantum dots (QDs) conjugated chitosan (CS)-based nanocarrier system encapsulated with Mitomycin C (MMC) drug. This fabricated nanocarrier, MMC@CS-Mn:ZnS, has been tested thoroughly for the drug loading capacity, drug encapsulation efficiency, and release properties at a fixed wavelength (358 nm) using a UV-Vis spectrophotometer. Followed by the physicochemical characterization, the cumulative drug release profiling data of MMC@CS-Mn:ZnS nanocarrier (at pH of 6.5, 6.8, 7.2, and 7.5) were investigated to have the highest release of 56.48% at pH 6.8, followed by 50.22%, 30.88%, and 10.75% at pH 7.2, 6.5, and 7.5, respectively. Additionally, the drug release studies were fitted to five different pharmacokinetic models including pesudo-first-order, pseudo-second-order, Higuchi, Hixson-Crowell, and Korsmeyers-Peppas models. From the analysis, the cumulative MMC release suits the Higuchi model well, revealing the diffusion-controlled mechanism involving the correlation of cumulative drug release proportional to the function square root of time at equilibrium, with the correlation coefficient values (R2) of 0.9849, 0.9604, 0.9783, and 0.7989 for drug release at pH 6.5, 6.8, 7.2, and 7.5, respectively. Based on the overall results analysis, the formulated nanocarrier system of MMC synergistically envisages the efficient delivery of chemotherapeutic agents to the target cancerous sites, able to sustain it for a longer time, etc. Consequently, the developed nanocarrier system has the capacity to improve the drug loading efficacy in combating the reoccurrence and progression of cancer in non-muscle invasive bladder diseases.

Aptasensor for the Detection of Mycobacterium tuberculosis in Sputum Utilising CFP10-ESAT6 Protein as a Selective Biomarker.

A portable electrochemical aptamer-antibody based sandwich biosensor has been designed and successfully developed using an aptamer bioreceptor immobilized onto a screen-printed electrode surface for Mycobacterium tuberculosis (M. tuberculosis) detection in clinical sputum samples. In the sensing strategy, a CFP10-ESAT6 binding aptamer was immobilized onto a graphene/polyaniline (GP/PANI)-modified gold working electrode by covalent binding via glutaraldehyde linkage. Upon interaction with the CFP10-ESAT6 antigen target, the aptamer will capture the target where the nano-labelled Fe3O4/Au MNPs conjugated antibody is used to complete the sandwich format and enhance the signal produced from the aptamer-antigen interaction. Using this strategy, the detection of CFP10-ESAT6 antigen was conducted in the concentration range of 5 to 500 ng/mL. From the analysis, the detection limit was found to be 1.5 ng/mL, thereby demonstrating the efficiency of the aptamer as a bioreceptor. The specificity study was carried out using bovine serum albumin (BSA), MPT64, and human serum, and the result demonstrated good specificity that is 7% higher than the antibody-antigen interaction reported in a previous study. The fabricated aptasensor for M. tuberculosis analysis shows good reproducibility with an relative standard deviation (RSD) of 2.5%. Further analysis of M. tuberculosis in sputum samples have shown good correlation with the culture method with 100% specificity and sensitivity, thus making the aptasensor a promising candidate for M. tuberculosis detection considering its high specificity and sensitivity with clinical samples.