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This experimental investigation focused on coating of functionalized graphene oxide (FGO) on the mild steel to minimize corrosion, using a new method. Prior to the coating, the fundamental chemical and morphological structures of FGO were studied with aid of some characterization techniques: X-ray diffraction (XRD), Raman, scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Various epoxy/FGO coating formulations with 10, 20, 30, 40 and 50 ppm of FGO were prepared and coated on the mild steel substrate, adopting dip coating method. Immersion test was carried out to observe the corrosion inhibition efficiency of the graphene. The adsorption isothermal behavior was also studied using various models and compared with the data obtained from the experimental results. From the results obtained, the formation of irregular rough patches and separation of platelets like zebra lines indicated the formation of graphene nanoparticles, as observed through morphological analysis. The occurrence of sharp peak at 24.3° in the XRD pattern depicted the existence of graphene in nanoscale. Electrochemical impedance (EI) and potentiodynamic polarization (PP) studies reported the maximum corrosion inhibition efficiency of 87% at 50 ppm concentration of epoxy/FGO. It was evident that an increasing concentration of graphene exhibited significant corrosion resistance in both studies. The bonding energy of randomly oriented graphene platelets reduced the removal of metal, delaying the crack propagation in tortuous path on the coated surface. These results established the significance and applicability of this study in various relevant industries.

Mechanical, thermal, and water absorption properties of banana fiber and sisal fiber-reinforced epoxy biocomposites were evaluated with and without cashew nut shell (CNS) filler, either separately, or as hybrid biocomposites. Bidirectional woven mats were used to make composites by compression molding. The CNS filler content was 5% to 10%. Adding CNS filler of up to 5% improved the mechanical and thermal properties. Further increases in filler content above the threshold value diminished their mechanical properties due to poor dispersion and increased porosity. The maximum tensile and flexural strength were found as 43 and 92 MPa. The highest impact strength was obtained with the hybrid biocomposites with 5% filler. This was attributed to the toughening effect of phenolic compounds in the CNS. In addition, the thermal stability of the biocomposites was influenced by filler content. The biocomposites exhibited varying water absorption capacities as the filler content increased with the water uptake. Scanning electron microscopy (SEM) images showed the microsurface of the fractured samples and their interfacial bonding, fiber pull-out, and fracture. However, increasing filler content in the biocomposite reduced the filler pull-out and led to fiber breakage.

A novel method for forming composite materials was investigated by incorporating activated carbon powder (ACP) as a reinforcing agent within a polylactic acid (PLA) matrix, utilizing the hand layup fabrication technique. The composite materials were synthesized by varying the weight percentages of the matrix and reinforcements, encompassing pure PLA as well as ratios of 90:10, 80:20, 70:30, 60:40, and 50:50. PLA is recognized for its biocompatibility and favorable thermomechanical properties, similar to conventional plastics. The incorporation of activated carbon powder, known for its remarkable aspect ratio, proved highly advantageous, yielding exceptional mechanical properties. Analysis revealed that the composite with a ratio of 90:10 wt% of carbon powder to PLA demonstrated significant improvements in tensile strength (26.8%), flexural strength (26.37%), impact strength (61.1%), compression strength (25%), and hardness (45.8%). Additionally, thermal analysis showed that the 90:10 wt% composite exhibited minimal weight loss and maximum heat flow sustainability at approximately 600 °C compared to other composite combinations. Morphological examination using field emission scanning electron microscopy unveiled a uniform distribution of activated carbon powder reinforcement within the matrix, actively contributing to the enhanced mechanical properties of the composite.

Abstract In therapeutic diagnostics, early diagnosis and monitoring of heart disease is dependent on fast time-series MRI data processing. Robust encryption techniques are necessary to guarantee patient confidentiality. While deep learning (DL) algorithm have improved medical imaging, privacy and performance are still hard to balance. In this study, a novel approach for analyzing homomorphivally-encrypted (HE) time-series MRI data is introduced: The Multi-Faceted Long Short-Term Memory (MF-LSTM). This method includes privacy protection. The MF-LSTM architecture protects patient’s privacy while accurately categorizing and forecasting cardiac disease, with accuracy (97.5%), precision (96.5%), recall (98.3%), and F1-score (97.4%). While segmentation methods help to improve interpretability by identifying important region in encrypted MRI images, Generalized Histogram Equalization (GHE) improves image quality. Extensive testing on selected dataset if encrypted time-series MRI images proves the method’s stability and efficacy, outperforming previous approaches. The finding shows that the suggested technique can decode medical image to expose visual representation as well as sequential movement while protecting privacy and providing accurate medical image evaluation.

Abstract The integration of large intelligent surfaces (LIS) with non-orthogonal multiple access (NOMA) networks has emerged as a promising solution to enhance the capacity and coverage of wireless communication systems. In this study, we analyse the performance of a NOMA network with the assistance of LIS. We propose a system model where a base station (BS) equipped with a LIS serves multiple users. The LIS consists of many passive elements that can influence the wireless channel by adjusting the reflection coefficients. We consider a downlink scenario where the BS transmits to multiple users simultaneously using NOMA, and the LIS helps to improve the signal quality and coverage. We additionally evaluate the efficiency of the suggested LIS-assisted NOMA network. In addition, we evaluate the efficiency of the LIS-assisted NOMA network in comparison to conventional NOMA systems that do not utilize LISs. The findings indicate that the LIS has a notable impact on enhancing the system's performance in terms of diversity gain, probability of error, and pairwise error probability (PEP). Moreover, the suggested LIS-assisted NOMA network is shown to be superior to conventional NOMA systems through comparison. These findings offer useful insights into the performance analysis of LIS-assisted NOMA networks. They also serve as inspiration and motivation for future research and development in this new subject, with the potential to revolutionize wireless communication systems.

The development of biodegradable hybrid fibre composites is gaining pace in the automotive and construction industries due to their lightweight structural applications, which offer considerable benefits for the environment. In this present investigation, hybrid bio composites were fabricated using a compression molding machine with plain woven jute and aloe vera mats along with polyester resin as the matrix. Six types of hybrid biocomposite laminates were prepared by varying the stacking arrangement of jute and aloe-vera mats to analyse the impact of stacking arrangements on vibration damping and acoustic behaviour of these hybrid bio composites. From the results, it is concluded that the maximum value of natural frequency is obtained from the JJAJ type of composite. i.e., 157, 326, and 370 Hz for Modes I, II, and III respectively, due to good interlacing of fibres in the weft and warp directions. J/J/A/J (AJ3) hybrid bio composite has highest sound absorption coefficient of 0.47 at 3000 Hz, and a better transmission loss i.e 19.84 dB, according to the results of the acoustic research. The comparison of experimental and theoretical analysis was carried out, and found that experimental and theoretical values are closely related to each other.

By leveraging the properties of natural or plant fibers and possibilities through three-dimensional (3D) printing technology, a composite filament was fabricated by incorporating newly isolated Cryptostegia grandiflora fiber (CGF), as a reinforcement with polylactic acid (PLA) by using a twin-screw extruder. The fabricated composite filament and pure PLA filament were 3D-printed, using fused deposition modeling (FDM). This study investigated the mechanical, physical, and thermal properties of the 3D-printed CGF reinforced composite filament samples. The mechanical properties of the samples fabricated with 10 wt% CGF were better than that of samples with pure PLA. In addition, impact, tensile, flexural strengths and hardness were increased by 35.6, 33.6, 14.1, and 1.7%, respectively, when compared with the sample with pure PLA. The fractured surface morphology of tensile samples showed a uniform distribution of CGF within the PLA. The addition of CGF improved the thermal stability of the 3D-printed CGF/PLA composite sample by 15%. Therefore, the printed structure could serve as an alternative material for various uses, considering contemporary concepts of sustainability, availability, environmental friendliness, and cost effectiveness.

Abstract 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.

Abstract 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.

Acrylonitrile butadiene styrene (ABS) polymer and carbon fiber reinforced acrylonitrile butadiene styrene (CF/ABS) spur gears were 3D-printed using fusion deposition modeling (FDM) with different fillet radii of 0.25, 0.50, and 0.75 mm. The performance of the fabricated gears was studied with the effect of fillet radius on varying load and speed conditions. The thermal properties of the gears were also investigated. The results indicated that 3D-printed CF/ABS spur gear exhibited better performance than the pure ABS. The 3D-printed CF/ABS gear with fillet radius of 0.25 mm recorded the highest wear and thermal stresses. However, the optimum performance was exhibited by the gear sample with highest fillet radius of 0.75 mm. Repeated gear tooth loading during service caused an increase in gear temperature due to the hysteresis and friction. Using optical microscopy, the tooth structures of both 3D-printed ABS and CF/ABS spur gears were analyzed before and after loading conditions to establish their failure mechanism. Evidently, various applications of the FDM 3D-printed spur gears depend on their different performances under loads and operating speeds. The methods and findings of this work can be regarded as helpful for future related work related to cellulosic reinforcing particles in a polymer matrix.

In this work, a novel hybrid scheme that integrates additive manufacturing (AM) with conventional compression moulding is developed to fabricate bamboo-reinforced polylactic acid-based (PLA-based) composite sheets. First, fused deposition moulding (FDM) is employed to deposit PLA into the bamboo woven mats. Second, multiple composite sheets are combined to increase the thickness via compression moulding. Further, the effect of FDM process nozzle temperature on the properties and performance of bamboo-PLA composite material is investigated along with a detailed microstructural characterization. It is found that an increase in nozzle temperature reduces pores in the composite material and improves the tensile, flexural and impact properties. Microstructural analysis of failure surfaces reveals that the damage occurred via PLA-bamboo interface decohesion and bamboo fibre breakage. Based on the microstructural analysis, a failure mechanism for the bamboo-PLA composite material is proposed, along with suggestions for further improvement in the ductility.

Abstract 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.

Geotechnical designs and analyses of earth structures and foundations exclusively involve the assessment and consideration of unsaturated soil shear strength. The laboratory testing equipment and methods for predicting the unsaturated soil shear strength are complicated and more expensive. The experimental program attempted to involve undrained triaxial and filter paper for evaluating the unsaturated soil shear strength of identically compacted clayey soil. This study undertakes a comparison of shear strength in clayey soil under undrained loads, examining both saturated and unsaturated conditions. A 60 kPa air entry suction value is the key point at which linearity between the unsaturated shear strength parameter Øb and effective friction Ø′ with 15° linear slopes turns to non-linearity. Unsaturated shear strength increased by 22.76% in optimally wet conditions, 52.68% in optimum conditions, and 77.81% in optimally dry conditions as compared to saturated shear strength. This study utilizes an artificial neural network (ANN) to predict clayey soil’s unsaturated shear strength, finding that the optimal ANN configuration (2-5-1 topology, Levenberg–Marquard optimization, and logsig transfer function) achieved high reliability with a correlation coefficient (R) of 0.9289 and mean square error values of 2.22, 7.12, and 3.012 for training, testing, and validation, respectively. This experimental investigation improves our understanding of clayey soil shear strength and emphasizes the importance of saturation and moisture content in geotechnical assessments under undrained loading conditions.

This study primarily focused on assessing the feasibility of utilizing textile effluent sludge (TES) in the creation of sustainable building materials, demonstrating the possibility of using this material and eventually generating new market opportunities. The physical, chemical, and mineralogical characterization of textile sludge was carried out after preliminary crushing and grain-size sorting. Five samples collected from the effluent treatment facility of textile industries situated in the Vidarbha region of Maharashtra, India, underwent characterization to explore their potential innovative applications in the construction sector. Various physical tests, such as specific gravity, density, water absorption, and sieve analysis, were performed on these samples. Chemical characterization was carried out using x-ray diffraction, x-ray fluorescence, a field emission scanning electron microscope coupled with energy-dispersive x-ray spectroscopy, Fourier transform infrared spectroscopy, and thermogravimetry/differential thermal analysis. The results obtained demonstrate the potential of TES in the creation of sustainable building materials. In addition, the mix proportion of TES was further optimized using LINGO software to meet the chemical specifications required for cement.

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.

Both developed and developing countries around the world are increasingly utilizing biodegradable products and bio-based materials. This is required to curb rampant environmental pollution caused by synthetic materials and their by-products. In this study, banana and bamboo fibers were prepared from agricultural and industrial wastes, respectively. Banana and bamboo fibers were obtained with aid of mechanical and waste extractions, respectively. Both fibers were subjected to a retting process for 24 hours, using normal warm water at a room temperature (27 ± 3 °C) to remove the impurities. Then, a comparative investigation and analysis was conducted concerning their properties and applications. The biomass level, physical, and chemical properties, structure, experimental analysis, and moisture regain behaviors of the plant materials were studied. Additionally, the antibacterial property of the samples was discussed. The biomass level was measured per hectare for banana (36.1 tons) and per plant for bamboo (65%), and the physical and chemical properties were identified via some basic testing techniques. The molecular, crystalline, and morphology structures were observed using Fourier-transform infrared spectroscopy, X-ray diffraction, and scanning electron microscopy. Finally, the industrial applications were elucidated to establish the possibility of using both fibers as promising sustainable, renewable, recyclable, and eco-friendly materials.

This paper presents the novel Stochastic decoding-convolutional neural network (SD-CNN) structure, with the goal of enhancing 5G LDPC code’s decoding efficiency in the presence of correlated noise of the channel. Applying the stochastic approach acts as an alternate technique to fixed-point LDPC decoding to enhance the decoder’s hardware efficiency. In order to improve the efficacy of the decoder, we adopted deep learning method such as Convolutional neural network (CNN). CNNs can be employed for denoising purposes in communication systems, where signals may be compromised by diverse forms of noise while being transmitted, with the aim of enhancing signal quality and dependability. The SD-CNN architecture combines a trained CNN with a stochastic decoder of 5G LDPC codes, thereby utilizing the CNN’s capability to accurately estimate channel noise and, consequently, enhance the error correction capabilities of the decoder. The generated output of the trained CNN is then fed back into the stochastic decoder, creating an iterative process between the SD and CNN that ultimately leads to superior decoding performance. For 5G LDPC code word length $N = 3808$ , with a base code rate $R = 1/3$ , the suggested SD-CNN architecture achieves a BER of $10^{-6}$ at 0.6 dB of SNR per bit in the strong correlation of channel noise condition, in comparison to SD, which achieves a BER of $10^{-6}$ at 3.5 dB of SNR per bit. The results demonstrate that there is a 2.9 dB improvement.

Herbal plants have been used, in light of their responsiveness and wide availability, for the construction of a pioneering nanomaterial. In this study, a colloidal suspension of gold nanoparticles (GNPs) was synthesized from an extract of Madhuca longifolia (ML) using chloroauric acid. For biomedical applications, Madhuca longifolia (ML) was used as a bioreductant as well as a capping agent The formed ML-GNPs were analyzed using different analytical techniques, antioxidant assays, and thiazolyl blue formazan assay against A549 cell lines to evaluate clinical relevance. They were further evaluated for their influence on antimicrobial activity using a disc diffusion test against two different microorganisms, Proteus vulgaris and Micrococcus luteus. The ML-GNPs produced had good antioxidant, antibacterial, and anticancer activities. The conformation of the XRD spectra with prominent characteristic planes was indexed to the face-centered cubic (fcc)-structured GNPs. Surface morphology analysis was used to determine the particle size of the GNPs. Fourier transform infrared spectra of the samples were used to determine the analogs for strong H bonding. The MIC values of biogenic GNPs against both strains of Proteus vulgaris and Micrococcus luteus was calculated as 0.29 and 0.96 g/mL, respectively, and triclosan was considered as 0.4 and 2 g/mL, respectively. The findings of this study will be beneficial for future studies of the therapeutic potential of ML-GNPs. Actively, ML-GNPs can be a capable material for formulating nanomedicines after subsequent clinical experiments.

Vehicle emissions are responsible for about 30% of all air pollution in the world. Vehicle emissions can be significantly reduced through the use of selective catalyst reduction (SCR). The present work emphasizes the impact of thermal barrier-coated pistons on diesel engine performance as well as emission qualities. A Ni–Cr–Al–Y bond coat was applied to the tested engine piston that was 50 microns thick and a top coat that was 250 microns thick. These coatings were applied using the plasma spray technique to a combination of 2 mol. % of Gadolinium oxide (Gd2O3), 2 mol. % of Neodymium oxide (Nd2O3), 3 mol. % of Yttria (Y2O3), and continuing 93 mol. % of Zirconia (ZrO2). In a 4-stroke, 1-cylinder diesel engine, the testing was carried out utilizing diesel, Mahua, and Jatropha fuels with and without coating. The selective catalytic reduction technique was employed in the current test to reduce NOx emissions. The findings of this analysis indicate that the brake thermal efficiency of an insulated piston engine improved by 3.9%, and when JB 100 was chosen as the fuel, the insulated piston reduced brake-specific fuel consumption by 3.5% in comparison to the normal piston. In engines coated with SCR, hydrocarbon emissions were lowered by 20.1%, while carbon monoxide emissions were dropped by 13.4%. In comparison to the baseline engine, the oxide of nitrogen emissions were reduced by 39.1%.

Medical life-saving techniques include mechanical ventilation. During the COVID-19 epidemic, the lack of inexpensive, precise, and accessible mechanical ventilation equipment was the biggest challenge. The global need exploded, especially in developing nations. Global researchers and engineers are developing inexpensive, portable medical ventilators. A simpler mechanical ventilator system with a realistic lungs model is simulated in this work. A systematic ventilation study is done using the dynamic simulation of the model. Simulation findings of various medical disorders are compared to standard data. The maximum lung pressure (Pmax) was 15.78 cmH2O for healthy lungs, 17.72 for cardiogenic pulmonary edema, 16.05 for pneumonia, 19.74 for acute respiratory distress syndrome (ARDS), 17.1 for AECOPD, 19.64 for asthma, and 15.09 for acute intracranial illnesses and head traumas. All were below 30 cmH2O, the average maximum pressure. The computed maximum tidal volume (TDVmax) is 0.5849 l, substantially lower than that of the healthy lungs (0.700 l). The pneumonia measurement was 0.4256 l, substantially lower than the typical 0.798 l. TDVmax was 0.3333 l for ARDS, lower than the usual 0.497 l. The computed TDVmax for AECOPD was 0.6084 l, lower than the normal 0.700 l. Asthma had a TDVmax of 0.4729 l, lower than the typical 0.798 l. In individuals with acute cerebral diseases and head traumas, TDVmax is 0.3511 l, lower than the typical 0.700 l. The results show the viability of the model as it performs accurately to the presented medical condition parameters. Further clinical trials are needed to assess the safety and reliability of the simulation model.

Abstract Introduction There are limited data on family screening and genetic testing in pediatric cardiomyopathy from India. This study was conducted to describe the morphologic spectrum and identify potential familial and genetic causes of pediatric cardiomyopathies in this region. Methods From April 2018 to May 2020, all children from birth to 18 years of age with cardiomyopathy visiting a tertiary care hospital in North India were enrolled in this study. First-degree relatives of index patients were offered screening for cardiomyopathy; 260 clinically reported pathogenic/likely pathogenic variants in 17 genes were analyzed by a rapid genotyping method. Additionally, a subset of patients also underwent whole-exome sequencing. Results Of the 20 patients enrolled in this study (median age 42 months), 18 were clinically diagnosed with dilated cardiomyopathy. We observed a 44.4% mortality rate after a median follow-up of 15 months. 61.3% of the eligible first-degree relatives underwent screening, and one patient was identified to have familial cardiomyopathy. Multi-panel gene testing was performed on 18 patients, and none were found to have a pathogenic or likely pathogenic variant; 9 patients also underwent whole-exome sequencing, and pathogenic and likely pathogenic variants were identified in 50% (4/8) of them. Conclusion Dilated cardiomyopathy is the most common morphologic form of pediatric cardiomyopathy in India and has a high mortality rate. The prevalence of familial cardiomyopathy was low in this study. Future studies should evaluate the role of whole-exome sequencing in identifying genetic causes of cardiomyopathy in children.

Manufacturing has grown challenging because of the increased usage of harder materials, such as titanium alloys, in many industries, such as aerospace, automobiles, and marine. Conventional material removal procedures are not suitable for these tough materials due to their increased hardness and slow machinability. Wire Electrical discharge machining (WEDM) is a modern approach for material removal, particularly for harder materials, such as titanium alloys, nickel alloys, hard particle reinforced metal matrix composites, etc. The research design was performed by deeming the independent factors, such as duration of pulse and applied current. The removal rate of material, surface roughness of the machined region, dimensional deviation, and tolerance errors in form/orientation are considered performance metrics. Taguchi’s approach was engaged to assess the process variables, and the importance of the process factors was established using analysis of variance approach. The purpose of this research is to create an AI based decision making tool, which can be utilized to anticipate the various parameters that impact the WEDM material removal process. The discoveries of the present exploration allowing the manufacturers to make better-informed decisions with a developed model’s capability by demonstrating that the model’s predicted values were in close confirmation to the actual values.

Eight new functionalized spirooxindole-pyrrolizidine heterocyclic hybrids has been obtained from N-pyridinylmethyl-bisarylmethylidene-pyridinones, Isatin and L-Proline by a multi-component cycloaddition reaction. Such synthesized derivatives are being characterized systematically with the aid of instrumental facilities like FT-IR, NMR spectroscopy, and Mass spectrometry. Following this, all the compounds are tested for the anticancer potentials in vitro using HepG2 cells (cancer cells). The compound with no substitution on the aryl rings (phenyl rings), displayed the highest activity among the spirooxindole-pyrrolizidines. Further the most active heterocyclic hybrids are verified for toxicity effects against L929 cells (non-cancer cells; at 200 µg/mL for 24 h). Finally, the cell viability losses for these most active compounds (at its IC50 value) are addressed by assaying the activity of free radicals, apoptosis, and caspases.

This study presents animal fiber characterization and the influence of various fiber loadings on mechanical properties of sheep hair fiber-reinforced polymer (SHFRP) composites. The sheep hair fibers (SHF) characterization was carried out using X-ray diffraction (XRD), Fourier transform-infrared spectroscopy (FTIR), thermo-gravimetric analysis (TGA), scanning electron microscopy (SEM) and non-contact surface roughness machine. The functional group and chemical bond were analyzed using FTIR techniques. The crystallinity index and thermal stability of the SHF were characterized, using XRD and TGA techniques, respectively. The composites were fabricated using a compression molding technique and a varying weight percentage of 20, 30 and 40 fiber. The composite plates were cut into test samples according to ASTM standard methods for their mechanical (tensile, flexural and impact) behaviors to be extensively analyzed. The surface morphology of the fractured samples was examined with aid of an SEM. From the results obtained, it was evident that the SHFRP composite recorded a significantly increased tensile strength property when fiber loading was increased from 20 to 40 wt%. The optimum 40 wt% SHFRP composite sample recorded better flexural and impact strength, when compared with other counterparts. This was attributed to a better fiber-matrix interfacial adhesion, as established fromSEM micrographs.

The stem bark of Acacia caesia, or Senegalia caesia, richly available in the Western Ghats of Tamilnadu and Kerala, India, does potentially offer a ligno-cellulosic fiber, which was characterized in this work, studying its chemical composition, morphology, and thermal degradation. The as-received fibers, which were extracted as technical fibers with diameters ranging between 100 and 150 µm, had a density of 1200 kg/m3. Their composition included 37% cellulose, 20% hemicellulose and 18% lignin, not very dissimilar, among other fibers, from alfa esparto and particularly coir. Their thermal degradation onset was at 308°C, which suggested a potential in composite application with traditional oil-based matrices and possibly also in the long run on bio-based ones. However, their high roughness and easy splitting of the fibers suggested that possible use as the filler for composites would require fiber treatment, namely, to remove undesired loose parts, hence regularizing their geometry. This would also serve to reduce the likeliness of longitudinal splitting, which is a widely recognized occurrence during stripping of bark fibers.

The tensile strength of fibers extracted by retting from Acacia Caesia bark was measured and their fracture morphology was examined, with the idea to propose their potential use as the reinforcement in polymer composites. Four categories of fibers were investigated, namely untreated and treated with a concentration of 5, 10 and 15% sodium hydroxide (NaOH) for 24 hours at ambient temperature. The increase of alkali concentration resulted in a gradual reduction of hemicellulose, wax, and moisture, which on the other side increased the fiber density. Single fiber tensile tests were performed according to ASTM D3822 standard. The fracture surfaces of the fibers were observed using an optical microscope and scanning electron microscope (SEM). The tensile tests revealed that the 10% NaOH treatment sample showed the highest performance, namely an average tensile strength of 16.2 (±5.63) N with an ultimate elongation of 4.6 (± 1.0)%. SEM evidenced the different possible morphologies of Acacia Caesia bark fiber fractures, including sliding and tearing, splitting and torsion of fibrils.

In this study, composite materials were made from Carica papaya fibers (CPFs), as a reinforcing element in polypropylene (PP), polyester (P) and epoxy (E) matrices, using compression molding technique. Experiments were conducted to evaluate the input parameters with their output responses, specifically density and thickness. Various CPF reinforced PP, P, and E composite specimens with varied fiber orientations of 0°, 45°, and 90° as well as percentages of fiber contents of 10, 20, and 30 wt.% were prepared, according to the ASTM D 570 standard. From the results obtained, it was observed that CPF/E composites with fewer fraction of CPF and orientation of 90° exhibited less water absorption throughout the whole duration of immersion. Water saturated CPF/E composite specimen, designated as E8, with orientation of 0° and fiber content of 20 wt.% showed the highest tensile, flexural strengths, and Shore D Hardness of 119, 115 MPa, and 85, respectively. Also, CPF/E composite specimen (E7) with 90° and 10 wt.% recorded the lowest tensile strength of 32 MPa, and CPF/E composite (E3) with 90° and 30 wt.% showed the lowest flexural strength of 41 MPa. Hence, it was evident that optimum CPF reinforced polymeric composite can be used for some outdoor engineering applications.

This paper presents a study on extraction and characterization of the cellulose fiber from the bark of Erythrina variegate (EV) plant. Several tests were carried out on Erythrina variegata fibers (EVFs) to determine their properties. These included thermogravimetric analysis (TGA)/difference thermogravimetric (DTG), X-ray diffraction (XRD) analysis, Fourier transform infrared spectroscopy (FTIR) as well as morphological analysis, using scanning electron microscopy (SEM) and atomic force microscopy (AFM). From the results obtained, chemical composition of EVFs, such as cellulose, lignin, ash, and wax content of 70.60, 12.70, 8.60, and 0.24 wt.%, respectively, were recorded through standard chemical analysis. The maximum and average tensile strength of the EVFs were found as 6.06 ± 0.02MPa and 2.80 MPa, respectively. The thermogravimetric analysis on the fiber showed excellent stability with a char residue of 19.23% and a maximum degradation temperature of 349°C. The crystallinity index (CI) of 37.5% and crystalline size of 36.93 nm of EVFs were calculated through X-ray diffraction analysis. The morphological study established that EVFs possessed rough surface even in raw form. The density of EVF was obtained at 1412 kg/m3, which was higher than that of Grewia damine of 1378 kg/m3 and lower than that of jute of 1460 kg/m3.

Flower-like microstructured trigonal tellurium (t-Te) was prepared by a simple solution-based strategy with the reaction of 1,2,3,4,5-pentamethylcyclopentadiene (HCp*) and TeCl4 in tetrahydrofuran (THF) under reflux condition. Powder X-ray diffraction (XRD) and electron microscopy techniques confirmed the phase purity and morphology of the synthesized sample. X-ray photoelectron spectroscopy (XPS) analysis provides evidence for forming elemental Te, viz, Te (0). Also, XPS analysis indicates the presence of a higher oxidation state, i.e., Te(IV), which may be due to the formation of an ultrathin layer of TeO2 on the surface of the elemental t-Te microstructure. According to the synthetic strategy, higher oxidation is due to the surface oxidation of Te (0) to Te(IV) while washing the sample. Additionally, Fourier-transform infrared (FTIR) technique further supports the presence of Te–O bonds on the surface of t-Te. The semiconducting behavior of the prepared elemental t-Te microstructure was confirmed by obtaining a positive Hall coefficient (RH) value of 4.98 × 103 cm3 C−1. In addition, the resistivity (conductivity) value, i.e., 1.05 × 102 Ω cm (9.52 × 10−4 Ω−1 cm−1) is calculated using Hall-effect measurement.

The treatment of toxic organic pollutants is extremely important for the conservation of clean air, soil, and water. In this study, (reduced graphene oxide) NiCo _2 O _4 / rGO hybrid nanocomposite was prepared by a facile hydrothermal technique and employed for organic dye adsorption from wastewater. The synthesized NiCo _2 O _4 /rGO hybrid nanocomposite was studied using FTIR, XRD, SEM, TEM, BET, Raman spectroscopy, and UV–visible. The physical characterizations prove the deposition of NiCo _2 O _4 particles on the rGO surface. The transmission electron microscope image demonstrated that the NiCo _2 O _4 particles with an average size of ∼46 nm was dispersed on the rGO surface. The obtained nanoparticles show a higher specific surface area of 56.4 m ^2 g ^−1 . Adsorption dynamics as investigated by time and concentration variation show that the adsorption data follows pseudosecond order kinetics and the Langmuir isotherm model, with a maximum adsorption capacity of 106.2 mg g ^−1 , indicating homogeneous physiochemical adsorption of CR dye on the adsorbent surface. Besides, the catalytic effectiveness of synthesized nanocomposite towards Congo red (CR) dye reduction mediated by the electron (e ^− ) transfer route of BH _4 ^− ions was explained in detail. The electrostatic interaction used between the NiCo _2 O _4 /rGO hybrid composite and Congo red increased the adsorption ion effectiveness of the dye sample.

The recent advancement in the production of nanomaterials with novel architectures and functionality has allowed for the effective treatment of industrial wastewaters and contaminated soil and, in that view, the current study aimed to investigate the catalytic efficacy of biopolymer-loaded titanium nanocomposite. Therefore, Cerium (Ce)-titanium dioxide (TiO2) loaded chitosan nanocomposite was formed and studied its catalytic efficacy towards the degradation of an industrial dye pollutant. For the production of Ce-TiO2/chitosan nanocomposite, we followed the hydrothermal synthesis route and the formed nanocomposite was thoroughly analyzed for the crystallinity (using powdered X-ray diffraction, XRD), surface bonding, and nature (using Fourier transform infrared, FTIR spectroscopy), morphology (scanning electron microscopy, SEM), elemental composition (electron diffraction analysis by X-rays, EDAX), porosity (Brunauer–Emmett–Teller, BET), and particles size in powdered form (transmission electron microscopy, TEM). Then the efficiency of synthesized nanocomposite was tested towards the photocatalytic degradation of Rhodamine B (Rh B) dye by applying various parameters such as the irradiation time, solution pH, catalyst dosage, and the dye concentration. Further, the Langmuir–Hinshelwood model was employed to investigate the kinetics of RhB degradation and provided a conceivable photocatalytic mechanism. It was indicated based on the catalyst mechanism that the modification of TiO2 nanoparticles with Ce and loading onto chitosan biopolymer may have accelerated the photocurrent transport due to an increase in the number of electrons and holes generated by the photon’s irradiation. In this way, the study has witnessed the excellent photocatalytic performance of Ce-TiO2/chitosan with 95% Rh B degradation as against the pure TiO2 nanoparticles thus stressing the importance of developing novel composite photocatalysts.

This work explored the importance of quantitative observation through imaging methods of optical and electron microscopies on the mechanical properties of particulate polymeric composites. Egg shell powder (ESP) reinforced polypropylene carbonate (PPC) polymeric composites with different filler weight percentage (wt.%) from 1 to 5 wt.% were considered. A cost-effective Image Analysis Software (IAS) was developed to extract black particles from the original optical images. During this process, the optimal image can be reproduced based on its originality by controlling the threshold values from 0.1 to 0.6 in real time situation. Using one-dimensional (1D) Gaussian distribution analysis, the authentication of the particle distribution data was studied and linked to the tensile strength of the composites. The mean value of the particle area collected from the left and right side of the scattered curves has a significant effect on the tensile strength of the composites. The proposed model was validated by comparing the predicted statistical results with the measured tensile strength for different wt.% of ESP composites. From the results obtained, a close agreement of 99% accuracy was observed between the experimental results and the proposed model for the tensile strength of the composites. The innovative study provides more practical and quantitative knowledge on improved particulate polymeric composites, in addition to the detection of failure processes through optical/electron microscopic examination of images. Evidently, the proposed cost effective, accurate and less stressful model can be employed by several composite-based industries to correlate the tensile strengths of particulate polymeric composites with their morphological properties.

Due to the release of hazardous heavy metals from various industries, water pollution has become one of the biggest challenges for environmental scientists today. Mercury Hg(II) is regarded as one of the most toxic heavy metals due to its ability to cause cancer and other health issues. In this study, a tailor-made modern eco-friendly molecularly imprinted polymer (MIP)/nanoporous carbon (NC) nanocomposite was synthesized and examined for the uptake of Hg(II) using an aqueous solution. The fabrication of the MIP/NC nanocomposite occurred via bulk polymerization involving the complexation of the template, followed by polymerization and, finally, template removal. Thus, the formed nanocomposite underwent characterizations that included morphological, thermal degradation, functional, and surface area analyses. The MIP/NC nanocomposite, with a high specific surface area of 884.9 m2/g, was evaluated for its efficacy towards the adsorptive elimination of Hg(II) against the pH solution changes, the dosage of adsorbent, initial concentration, and interaction time. The analysis showed that a maximum Hg(II) adsorption effectiveness of 116 mg/g was attained at pH 4, while the Freundlich model fitted the equilibrium sorption result and was aligned with pseudo-second-order kinetics. Likewise, thermodynamic parameters like enthalpy, entropy, and Gibbs free energy indicated that the adsorption was consistent with spontaneous, favorable, and endothermic reactions. Furthermore, the adsorption efficiency of MIP/NC was also evaluated against a real sample of condensate from the oil and gas industry, showing an 87.4% recovery of Hg(II). Finally, the synthesized MIP/NC showed promise as a selective adsorbent of Hg(II) in polluted environments, suggesting that a variety of combined absorbents of different precursors is recommended to evaluate heavy metal and pharmaceutical removals.

Abstract TiCnp reinforced AA7150 nanocomposites were prepared through a novel fabrication process (a combination of Vortex/Two‐step Stir Casting/Ultrasonication). The effect of TiCnp (0.5, 1.0, 1.5, and 2.0 wt.%) and ultrasonication on both microstructure behavior as well as mechanical properties were investigated at room temperature. Microstructural studies were analyzed through optical and scanning electron microscopy for grain size refinement, nanoparticle distribution and failure analysis. Grain refinement and homogeneous distribution of nanoparticles were achieved due to the ultrasonication effect. The mechanical properties increase with the increase of TiCnp wt.%. The optimal peak value at 175 MPa in tensile strength, 177.05 HV in microhardness, and 41.07 µm in grain size reduction were achieved at 1.5 wt.% of TiCnp content, which was around 48.31% and 17.4% enhanced in strength, in microhardness and 52.37% in grain size reduction. These peculiar achievements resulted from the homogeneous dispersion of TiC nano‐particulates in the nanocomposite material through a novel fabrication process.

The reversible reduction and oxidation of protein thiols was first described as mechanism to control light/dark-dependent metabolic regulation in photosynthetic organisms. Today, it is recognized as an essential mechanism of regulation and signal transduction in all kingdoms of life. Proteins of the thioredoxin (Trx) family, Trxs and glutaredoxins (Grxs) in particular, catalyze thiol-disulfide exchange reactions and are vital players in the operation of thiol switches. Various Trx and Grx isoforms are present in all compartments of the cell. These proteins have a rather broad but at the same time distinct substrate specificity. Understanding the molecular basis of their target specificity is central to the understanding of physiological and pathological redox signaling. Electrostatic complementarity of the redoxins with their target proteins has been proposed as a major reason. Here, we analyzed the electrostatic similarity of all Arabidopsis thaliana Trxs, Grxs, and proteins containing such domains. Clustering of the redoxins based on this comparison suggests overlapping and also distant target specificities and thus functions of the different sub-classes including all Trx isoforms as well as the three classes of Grxs, i.e. CxxC-, CGFS-, and CC-type Grxs. Our analysis also provides a rationale for the tuned substrate specificities of both the ferredoxin- and NADPH-dependent Trx reductases.

This work addresses manufacture, testing and simulation of foot valve lever (FVL) for monoblock pump industry, using a cost-effective casting design process. The impact of different types of sands, such as air-set, dry and sodium silicate as well as gating designs, namely H-, U- and O-type, were studied with respect to surface roughness and porosity. The mold pattern was produced using additive manufacturing (AM) technology. Both experimental and numerical investigations were performed on the temperature distribution of molten metal at random locations for the different gating configurations or designs, considering mold filling and solidification. It was evident from the experimental investigation that contribution of air-set sand and O-type gating architecture showed limited consistency effects. Importantly, gating architecture was the most influential parameter to determine all specified quality outcomes, independent of sand mold. An order of O

Nanotechnology and materials science are highly developing sectors where several new materials are investigated. One area includes iron oxide nanoparticles with superparamagnetic behavior. Since nanomaterials are prone to be associated with high levels of intrinsic toxicity and can have adverse effects if not properly guided. So, toxic mechanisms associated with nanomaterials are like that of a therapeutic drug or any other toxic compound. In that way, by ignoring the general pathways of cell death followed by the nanomaterials, the present report covers the points to control the growth of cancer cells by employing engineered nanoparticles (NPs) to induce therapeutic toxicity. We discuss the pathways for the induction of toxicity to the cancer cells using the superparamagnetic iron oxide nanoparticles (SPIONs) with and without surface ligands, and the ligand efficiency towards controlling toxicity is covered. Also, the therapeutic means of controlling the cancer cells, such as generating heat and releasing anticancer drugs in an externally organized manner, are also discussed. Overall, the report links the physical properties of SPIONs related to their natural or therapeutical toxicity by connecting physicochemical and toxicology principles.

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.

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.

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.

A new hybrid fabrication technique was introduced to manufacture composite laminates made of glass fiber, carbon fiber, and acrylonitrile butadiene styrene (ABS) as the matrix. The fabrication process utilized two different techniques: fused deposition modeling and hot press molding. The composite laminates were produced using five layers of glass fibers to form glass fiber-reinforced composites (GF/ABS) and five layers of glass fiber and carbon fiber to form glass fiber, carbon fiber-reinforced hybrid composites (GF/CF/ABS), with three layers of glass fibers and two layers of carbon fibers. The fabricated composite laminates were subjected to wear testing at velocities of 2 m/s, 3 m/s, and 4 m/s and under loads of 5 N and 10 N. The results indicated that GF/ABS samples had the lowest wear loss at 5 N and a velocity of 4 m/s. Additionally, the GF/CF/ABS hybrid samples had the lowest coefficient of friction (COF) of 0.28 at 4 m/s. The GF/ABS samples also exhibited the lowest friction force of 1.7 at 5 N and a velocity of 4 m/s. The worn samples were analyzed using a scanning electron microscope to examine the fiber-to-matrix adhesion behavior. GF/ABS and GF/CF/ABS composites are widely used in various applications due to their high strength-to-weight ratio and resistance to wear. These materials could be used in automotive parts, sporting goods, and marine applications.

The present study deals with the adsorptive removal of Escherichia coli (E. coli) by making use of chitosan-silica/calcium carbonate (CS-SiO2/CaCO3) nanocomposites (NCs) where it was synthesized using the waste eggshells and rice husks occurred by natural sources. The bioadsorbent CS-SiO2/CaCO3 NCs were synthesized by incorporating eggshell-CaCO3 nanoparticles (NPs) and rice husk-SiO2 NPs in chitosan NPs solution. The adsorbents were characterized using HRTEM, BET, DLS, and TGA. The characterization of NCs revealed the formation of adsorbents in the range of 10–50 nm and some structural changes to the spectra of adsorbents before and after the adsorption of E. coli was revealed by the FTIR analysis. Moreover, the adsorption efficiency of E. coli over the adsorbents after 35 min of incubation was about 80% for CS-SiO2/CaCO3 NCs. Further, the kinetics of adsorption studies were observed to be well-fitted to the Langmuir isotherm model with an adsorption capacity of 3.18 × 101 (CFU E. coil per gram of CS-SiO2/CaCO3). From the analysis, the synthesized bioadsorbent demonstrated the potential for ameliorating the inherent risk of pathogens in water.