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316 Austenitic stainless steel (AusSS) is extensively utilized in high‐temperature industrial applications such as boiler tubes and nuclear reactor pressure vessels. These components commonly experience failure under high‐temperature and high‐pressure conditions, attributed to either creep or fatigue. Existing classical models for creep and fatigue life prediction focus on a singular failure mode (either creep or fatigue) and consider physical features only. This study aims to develop a unified life prediction model for both creep and fatigue phenomena. It synthesizes information from 12 additional unexplored chemical and microstructural features from the National Institute of Materials Science (NIMS), Japan database, and previously published literature. Machine learning (such as decision tree, random forest, and XGBoost) and deep learning (like deep neural network) algorithms are employed in the modeling process. The trained models have been cross‐validated against unseen creep and fatigue life data, demonstrating superior prediction accuracy of 96.1% for deep neural network compared with classical models. Highlights: Unified prediction model for both creep and fatigue life prediction.Investigated the effect of up to 20 physical, chemical, and microstructural features.Multiple ML and DL prediction models were developed and compared with classical ones. [ABSTRACT FROM AUTHOR]

Recognizing patient activity in real‐time from video or images collected by a CCTV camera available in the hospital during a Covid‐19 situation has proven challenging. The dilemma of patient activity recognition is identifying and recognizing a patient's various actions in a series of videos. The process presented in our paper needs to achieve unrestricted, generic behavior in videos. Detecting events in any video is often difficult because we use Bidirectional ConvLSTM to create a robust patient in the sense behaviors (PSB) framework capable of eliminating certain barriers. To begin this paper by proposing a new Bidirectional ConvLSTM for establishing a stable PSB scheme. Our proposed model is capable of accurately predicting patient's behaviors like seated, standing, and so on. Using Bidirectional ConvLSTM, learning information from a pre‐trained model is an excellent place to start for rapidly developing a new PSB system using a current PSB database, as both the source and target datasets are critical. All parameters are frozen in a pre‐trained PSB device. Then, using the UCI and HMDB51 dataset to train the model, variables and local relations are progressively fixed. A novel PSB framework is developed using the target dataset. Relevant tests are conducted using commonly used research indices to assess prediction precision accuracy. They acknowledge six patient's behavior with a weighted accuracy rate of 92%. For recognizing novel activity, laying, the precision of a corresponding prediction is the best, 91%, of all six test results. The proposed work uses bidirectional ConvLSTM with modified activation layers to sense the patients' behavior. This article may be a patient activity recognition system to identify an individual. It takes a clip of COVID‐19 patients as input and looks for matches inside the hold‐on images. [ABSTRACT FROM AUTHOR]

Image Incorporation concerns, including background confusion, uneven population distribution, and variations in scale and familiarity, can make group counting difficult. Pre-existing information and multi-level contextual representations are required to handle these problems effectively with deep neural networks and Mask-RCNN. Numerous studies on crowd counting use density maps without segmentation, which treat a group of individuals as a single entity. This article offers a hybrid method for crowd counting that combines Mask-RCNN (MRCNN) and a bidirectional convolutional long-term memory network (ConvLSTM), dubbed (CC: MRCNN-biCLSTM). The CC: MRCNN-biCLSTM is based on the Mask-RCN; it first segments instances and generates density maps, which are passed into adversarial learning during the training phase. Finally, the bidirectional convolutional LSTM is being used to return metrics and counts for individuals within a group of individuals. Following that, the suggested activity detection technique based on the Bayesian non-linear filter AD-BNF is used to identify a person's activity. Additionally, the suggested approach resolves human grouping and enhances metric performance. Extensive studies demonstrate that the suggested method outperforms more sophisticated techniques on four frequently used difficult criteria for density map precision and quality. [ABSTRACT FROM AUTHOR]

Due to environmental issues and high cost of synthetic fibers, natural or cellulosic fibers have emerged as a promising reinforcement for polymer composites. The hybridization of natural fiber with synthetic fiber is a useful technique to improve the mechanical properties instead of using the natural fibers alone. This research aims to evaluate the influence of glass fiber hybridization on the mechanical properties of continuous, unidirectional, alkali (NaOH)‐treated kenaf‐epoxy composites. At first, the effect of treatment of various concentrations (3, 5, 7, and 9% w/v) of NaOH on the structure of single kenaf fiber was characterized using XRD, SEM, FTIR, and tensile testing. At the optimum 5% alkali concentration the tensile strength, modulus, and %elongation of the kenaf fibers were enhanced by 81%, 114%, and 42%, respectively. The effect of hybridization of 5% NaOH treated kenaf along with glass fiber on the improvement in tensile, flexural, and impact properties for hand laid kenaf‐glass‐epoxy hybrid composite laminates was established. The overall matrix to fiber weight ratio of five different layup sequence laminates was maintained constant at 70:30. It can be concluded from the obtained results that the 15% glass and 15% kenaf fiber hybridized composites exhibited the maximum increment in tensile strength and modulus (68.5% and 19.5%, respectively) in comparison to the unhybridized composites. Further, the flexural strength and modulus were also improved by 21% and 67%, respectively, and the impact strength by 153%. The SEM fractography proved that alkali treatment of fibers improved the fiber‐matrix interfacial bonding whereas fiber breakage, fiber pull‐out and debonding were established as the main fracture mechanisms of hybrid composites. The findings of the present investigation on kenaf‐glass hybrid composites corroborate that they are suitable for secondary structural applications in construction and automobile sectors. [ABSTRACT FROM AUTHOR]

Porous scaffolds assisted bone tissue engineering is a viable alternative for reconstruction of large segmental bone defects caused by bone pathologies or trauma. In the current study, we intend to develop trabecular bone scaffolds using gyroid architecture. An interactive modeling framework is developed for the design of three-dimensional gyroid scaffolds using advanced generative tools including K3DSurf, MeshLab, and Netfabb. The suggested modeling approach resulted in uniform and interconnected pores. Subsequently, fused deposition modeling 3D-printing is employed to fabricate the scaffolds using poly lactic acid material. The pores interconnectivity, porosity, and surface finish of the fabricated scaffolds are characterized using micro-computer tomography and scanning electron microscopy. Additionally, to assess the performance of scaffolds as a bone substitute, compression, and in-vitro biocompatibility tests on sterilized scaffolds are conducted. Compression tests reveal mechanical strength in the range of native bone while human adipose-derived mesenchymal stem cells show high proliferation after 72 h of incubation. Based on these results, the fabricated gyroid scaffolds can be said to possess favorable properties for trabecular bone scaffold. [ABSTRACT FROM AUTHOR]

Overall long-term success of metallic bone implant is mainly governed by the two key factors osseointegration and antibacterial function. Bioceramic hopeite coatings have been proven effective for getting strong osseointegration and antibacterial character. However, deterioration of hopeite coatings during the implantation period can adversely affect their overall biological performance. To overcome this issue, the present research work recommends an innovative process route of laser rapid manufacturing (LRM) for depositing hopeite coatings with good metallurgical bonding. Microstructure, phase composition, microhardness, antibacterial efficacy, and bioactivity were evaluated through Scanning Electron Microscopy (SEM), X-ray diffraction (XRD), a Vickers microhardness tester, Fluorescence-Activated Cell Sorting (FACS) technique, and a Simulated Body Fluid (SBF) immersion test respectively. The promising results obtained from these characterisations and testing establishes the new process route LRM as an effective alternative to deposit multifunctional hopeite coatings on metallic prosthetic-orthopaedic implants. [ABSTRACT FROM AUTHOR]

Orthopaedic metallic implant's long-term success strongly depends upon the two main factors: osseointegration and antibacterial character. Bioceramic (hydroxyapatite and hopeite) coatings have been proven effective for getting strong osseointegration and antibacterial character. However, deterioration of bioceramic coatings during the implantation period can adversely affect its overall biological performance. To conquer this issue, this research work recommends an innovative process route of laser rapid manufacturing for depositing bioceramic (hydroxyapatite and hopeite) coatings with metallurgical bonding. Microstructure, phase composition, antibacterial efficacy and bioactivity were evaluated using scanning electron microscopy, X-ray diffraction, fluorescence-activated cell sorting technique and simulated body fluid immersion test. The promising results obtained from these characterizations and testing establish the new process route laser rapid manufacturing as an effective alternative to deposit multifunctional bioceramic (hydroxyapatite and hopeite) coatings on metallic prosthetic-orthopaedic implants. [ABSTRACT FROM AUTHOR]

Coating of hydroxyapatite using the pulsed laser deposition technique, on medical grade UNS S31254 stainless steel (254SS), to yield a biomaterial for potential orthopedic implant applications, is unreported so far in the literature. In this paper, the pulsed laser deposition process was used to improve the physiological response of 254SS. The surface morphology of the deposited hydroxyapatite coatings was characterized using scanning electron microscopy and atomic force microscopy, while the phase composition of the deposited hydroxyapatite coatings was determined using the X-ray diffraction method. The thickness and adhesive strength of the hydroxyapatite coatings were determined using an ellipsometer and a tensometer, respectively. The antibacterial efficacy of the deposited hydroxyapatite coatings was confirmed using the modern technique of fluorescence-activated cell sorting. Finally, the bioactivity of hydroxyapatite coatings was investigated by conducting immersion test in simulated body fluid environment. The scanning electron microscopy and atomic force microscopy results revealed higher (∼8 nm) average surface roughness, which is likely to facilitate better osseointegration. X-ray diffraction analysis confirmed that postdeposition annealing is essential to achieve the desired crystallinity and uniformity of coatings. Tensile pull-out tests confirmed adhesive strength of hydroxyapatite coatings beyond the standard expected values. Immersion tests inferred high bioactivity of pulsed laser deposition hydroxyapatite coatings. The promising results obtained in this research signify the potential application of hydroxyapatite coatings in orthopedic implants. [ABSTRACT FROM AUTHOR]

This study is aimed at producing biofilms by reinforcement of Magnesium Oxide (MgO) nanoparticles in polylactic acid (PLA) biopolymer using the solvent casting method. In this study MgO nanoparticles (up to 4 wt%) were reinforced in PLA biopolymer and their key mechanical, barrier, thermal and antibacterial properties were investigated for food packaging applications. Among the prepared biocomposite films, the 2 wt% reinforced PLA films showed the maximum improvement in tensile strength and oxygen barrier properties (up to 29% and 25% respectively) in comparison to pristine PLA films. However, the water vapor barrier properties decreased by nearly 25% due to interfacial behavior and presence of free volumes near MgO nanoparticles. PLA/MgO films also exhibited superior antibacterial efficacy. The 2 wt% biofilms caused progressive damage and death of nearly 46% of E. coli bacterial culture after 12 h treatment. The produced films are transparent, capable of screening UV radiations and exhibit superior antibacterial efficacy making them an excellent food packaging material. [ABSTRACT FROM AUTHOR]

Carbon nanotubes have been proposed as an ideal reinforcement for the fabrication of nanocomposites. However, because of their chemical inertness, carbon nanotubes have to be functionalized in order to acquire superior properties. In the present paper, we examine the effect of functionalization of single-, double-, and triple-walled carbon nanotubes with ethylene-di-amine, analyzing their elastic properties. Condensed-phase optimized molecular potentials for atomistic simulations studies force field is used to model the interatomic interactions for armchair (5,5), (9,0), and (10,10) configuration carbon nanotubes. Molecular dynamics simulations for carbon nanotubes with various densities of the attached ethylene-di-amine molecules have been performed. This study quantitatively investigates the effect of amine functionalization (up to 12 numbers of ethylene-di-amine groups) on the Young's, bulk, and shear moduli and tensile strengths of different carbon nanotube structures. [ABSTRACT FROM AUTHOR]

Napier grass is a high-productivity perennial grass that is a very important forage for animals in the tropics. In this research work, fiber strands from Napier grass were extracted and the effect of acetic acid treatment on their chemical composition, morphological and structural changes, and tensile and thermal properties was studied. The acid treatment was carried out using glacial acetic acid solution at three different concentrations (5, 10, and 15%) for 2 h. Chemical analysis indicated lowering of amorphous hemicellulose content on acid treatment. FT-IR spectroscopic studies revealed variation of functional groups on acid treatment. Scanning electron micrographs indicated roughening of the surface of the fiber strands due to the removal of the hemicellulose layer on acid treatment. X-ray diffraction analysis indicated an increase in crystallinity of the fiber strands on acid treatment. The thermal stability and tensile properties of the fiber strands increased on acid treatment. This fiber has competitive advantages when evaluated with other natural fibers and can be developed further as a potential reinforcement in polymer matrix composites. [ABSTRACT FROM PUBLISHER]

Napier grass fiber strands were used as reinforcement to obtain composites with epoxy resin as matrix. To improve the surface, these fiber strands were treated with alkali solution. The composites were prepared by means of hand lay-up molding, then the effects of Napier grass fiber strand loading on mechanical properties such as tensile, flexural and impact, interfacial bonding, and chemical resistance were investigated. The composite with 20 wt.% Napier grass fiber strands gives excellent mechanical properties and chemical resistance, showing that it has the best bonding and adhesion of the composites. SEM micrographs of fractured and worn surfaces clearly demonstrate the interfacial adhesion between fiber and matrix. Alkali-treated Napier grass fiber strand–reinforced composites have better resistance to water and chemicals than the untreated fiber strand composites. [ABSTRACT FROM AUTHOR]