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In most Internet of Things (IoT) systems, Quality of service (QoS) must be confirmed with respect to the requirement of implementation domain. The dynamic nature of the IoT surroundings shapes it to complicate the fulfilment of these commitments. A wide range of unpredictable events endanger the quality of service. While execution the self-adaptive schemes handle with system's unpredictable. In IoT-based Wireless Sensor Networks (WSNs), the significant self-management objectives are self-configuration (SC) and self-healing (SH). In this paper, Self-Configuration and Self-healing Framework using an extreme gradient boosting (XGBoost) Classifier are proposed. In this framework, the IoT traffic classes are categorized as several types under XGBoost classifier. In SC phase, the IoT devices are self-configured by allocating various transmission slots, contention access period (CAPs) on the basis of its categories with priorities. In SH phase, the source node cardinally establishes a confined route retrieval method if the residual power in-between node is truncated or the node has displaced far away. The proposed framework is executed in NS-2 and the results exhibit that the proposed framework has higher packet delivery ratio with reduced packet drops and computational cost. Therefore, the proposed approach has attained 24.7%, 28.9%, 12.75% higher PDR, and 16.8%, 19.87%, and 13.7% higher residual energy than the existing methods like Self-Healing and Seamless Connectivity using Kalman Filter among IoT Networks (SH-SC-KF-IoT), Provenance aware run-time verification mechanism for self-healing IoT (PA-RVM-SH-IoT), and Fully Anonymous Routing Protocol and Self-healing Capacity in Unbalanced Sensor Networks (FARP-SC-USN) methods, respectively. [ABSTRACT FROM AUTHOR]

In our paper, we primarily concentrate on the existence and controllability results for fractional evolution inclusions of order 1 < r < 2 with Clarke's subdifferential type. By applying the facts related to the measure of noncompactness, fractional calculus, and fixed‐point technique, the principal results are proved. Initially, we are concentrating the existence and continue to prove the controllability of the fractional evolution system. In the end, we present an example to demonstrate the theory. [ABSTRACT FROM AUTHOR]

• Study of spin dynamics in Ta/NiFe/FeMn/CoFeB multilayer by varying NiFe thickness. • Two distinct FMR modes are found for the NiFe and CoFeB layers. • The separation between the resonance fields shows reconfigurable phenomena. • Parallel mode spin-to-charge conversion is explored using the ISHE technique. • NiFe layer significantly contributes to spin-to-charge conversion. The precise engineering of microwave absorption frequencies is of paramount importance in the advancement of spintronic-based RF devices. In the pursuit of this objective, magnetic thin films demonstrate unrivaled efficacy in enabling external modulation of their microwave responses in a reconfigurable manner. Here, we demonstrate dual-frequency ferromagnetic resonance modes and corresponding spin-to-charge conversion efficiency in thin film structures comprising Ta/NiFe/FeMn/CoFeB multilayer. A systematic thickness variation of the NiFe layer (i.e., 4–20 nm) has been undertaken to elucidate the impact on both static and dynamic properties across the multilayer structure. The presence of two distinct magnetic layers manifests in the emergence of two-step magnetic hysteresis loops, which are incorporated with unique resonant modes. The separation between the resonant fields shows tunable properties with excitation frequencies, thereby offering a wide range of reconfigurable operating parameters. The effective damping parameter has shown a decrement with increasing thickness of the NiFe layers. The effective spin mixing conductance for the NiFe layer was found to be 7.4 ± 0.6 nm−2. The spin-to-charge conversion within these structures has been demonstrated through measurements of the inverse spin Hall effect. Systematic thickness variation revealed that the prominent voltage drop was observed in the NiFe layer compared to the CoFeB layer. Considering the opposite spin Hall angles of Ta and FeMn layer, the direction of the spin flow and spin-to-charge conversion efficiency are summarized. [ABSTRACT FROM AUTHOR]

Bone illnesses arise at a young age itself, so bone age assessment (BAA) is primarily utilized in paediatrics to identify their growth. Several BAA-related methods are employed to determine bone maturity; however, they do not give accuracy and the rate of error increases. To overcome this issue, in this manuscript, TW3-based Region of Interest (ROI) identification and classification with Chaotic ANN (CANN), as well as Deep Neural Network optimized with Evolved Gradient Direction optimizer (EVGO) architecture, is proposed for an Automated BAA classification. In this, Hand X-Ray images are taken from the Digital Hand Atlas (DHA) dataset and the Radiological Society of North America (RSNA) database. Here, Tanner-Whitehouse (TW3) and Shallow convolution neural network (SCNN) is utilized for extracting the ROI regions such as radius, ulna, and short bones (RUS) from the wrist region of the left hand. After that, the extracted ROI feature data are given to CANN for predicting BAA. Then, the predicted data are classified using the DNN-EVGO network. The bone age evaluation is then classified depending on maturity phases. The proposed approach is activated in MATLAB. Simulation outcomes of TW3- SCNN- CANN- DNN-EVGO- BAA methods for DHA database attain higher accuracy of 45.75%, 37.64%, 24.64% when analysed to the existing models, such as Faster Region-Convolutional Neural network oriented feature learning with optimal trained Recurrent Neural Network for BAA for paediatrics (TW3-F-R-CNN-AF-SFO), Multi-objective segmentation approach for BAA under parameter tuning- U-net architecture, and TW3-based fully automated bone age assessment system using deep neural networks (TW3-F-R-CNN-VGGNet-CNN-BAA). [ABSTRACT FROM AUTHOR]

Thin films of FePtCo ternary alloy with 100 nm thickness have been deposited on an Si substrate using a DC magnetron sputtering system by co-sputtering of Co metal target and Fe40Pt60 alloy target in three different conditions, i.e. as-deposited at room temperature, annealed at 400 °C ${}_{}^ \circ C$ ∘ C , and deposited on the seed- layer. The effects of target sputtering power, leading to different compositions and various deposition conditions on surface roughness of films and magnetic properties, were studied. The average surface roughness of the as-deposited films decreases with the increase in the sputtering power of the Co target. For the annealed and seed-layered films, an increase in Co sputtering power resulted in an increased in roughness. Moreover, the annealed films possess smallerlower roughness due to an increase in the surface mobility. On the other hand, the Cu seed- layer decreases the roughness by preventing the diffusion of the film into the substrate. The room -temperature M-H measurement shows that the films exhibit soft ferromagnetism with coercivity in the order of ${10^3}$ 10 3 A/m and large saturation magnetizationmagnetisation of the order ${10^6}$ 10 6 A/m. The saturation magnetizationmagnetisation decreases with the increase in the sputtering power and is not influenced by the film surface roughness. On the other hand, riseincrease in surface roughness leads to decrease in coercivity of the films. HIGHLIGHTS: Thin films of FePtCo ternary alloy have been deposited by co-sputtering of Co metal target and Fe40Pt60 alloy target. The effects of surface roughness of films on magnetic properties were studied. The room-temperature M-H measurement shows that the films exhibit soft ferromagnetism. The saturation magnetisation decreases with sputtering power and is not influenced by the film surface roughness. On the other hand, increase in surface roughness leads to decrease in coercivity of the films. [ABSTRACT FROM AUTHOR]

In the current project the samarium substituted strontium hexaferrites with general formula SrSm x Fe 12-x O 19 (where x = 0, 0.1, 0.2, 0.3, 0.4, and 0.5) nanocrystalline powder have been successfully synthesized employing sol-gel auto-combustion route. The fabricated samples have been sintered at 1200 °C for 2 h. The structural, functional group, morphological, elemental, optical, magnetic, dielectric and electrochemical properties have been studied by X-Ray diffractometer, Fourier transformer infrared spectroscopy, scanning electron microscopy, Energy dispersive X-Ray, UV–visible, vibrating sample magnetometer, Inductor capacitor and resistor meter and cyclic voltammetry, galvanostatic charging discharging respectively. The structural analysis confirms the formation of the single-phase Magnetoplumbite structure of all the samples. The crystallite size decreases with increasing Sm+3 ions concentration. The characteristic bands of hexagonal structure present in the range of 400–660 cm−1 which correspond to metal–oxygen (M − O) stretching and vibrational bonds. The bandgap increases from 4.21 to 4.86 eV. The magnetic properties reveal the clear ferromagnetic M − H curve in which the value of coercivity increases and saturation magnetization decreases. The dielectric constant and tangential loss of the material both decrease with increasing frequency. Conversely, the ac conductivity of the material increases with increasing applied frequency. This is the natural behavior of ferrites. This behavior can be attributed to the polarization and orientation of the dipoles within the material in response to the applied electric field. The observed increase in σ at higher frequencies suggests that the material may be useful in applications where high-frequency electrical properties are desired such as in the development of high-speed electronic devices. The specific capacitance increases monotonically up to 1020 F g −1 with increasing Sm+3 concentration. The samarium substituted hexaferrites are recommended to fabricate the high energy density charge storage devices such as supercapacitors. [ABSTRACT FROM AUTHOR]

There are fewer studies on Trichoderma diversity in agricultural fields. The rhizosphere of 16 crops was analyzed for Trichoderma species in 7 districts of Rajasthan state of India. Based on DNA sequence of translation elongation factor 1α (tef-1α), and morphological characteristics, 60 isolates were identified as 11 species: Trichoderma brevicompactum, species in Harzianum clade identified as T. afroharzianum, T. inhamatum, T. lentiforme, T. camerunense, T. asperellum, T. asperelloides, T. erinaceum, T. atroviride, T. ghanense, and T. longibrachiatum. T. brevicompactum is the most commonly occurring strain followed by T. afroharzianum. No new species were described in this study. T. lentiforme, showed its first occurrence outside the South American continent. The morphological and cultural characteristics of the major species were observed, described, and illustrated in detail. The isolates were tested for their antagonistic effect against three soilborne plant pathogens fungi: Sclerotium rolfsii, Rhizoctonia solani, and Fusarium verticillioides in plate culture assays. One of the most potent strains was T. afroharzianum BThr29 having a maximum in vitro inhibition of S. rolfsii (76.6%), R. solani (84.8%), and F. verticillioides (85.7%). The potential strain T. afroharzianum BThr29 was also found to be efficient antagonists against soil borne pathogens in in vivo experiment. Such information on crop selectivity, antagonistic properties, and geographic distribution of Trichoderma species will be beneficial for developing efficient Trichoderma-based biocontrol agents. [ABSTRACT FROM AUTHOR]

Test data volume (TDV) is the main issue for lessening the test data volume for system-on-a-chip (SoC), lessening test time, average power, and peak power. Several optimization algorithms have been presented previously to decrease the TDV, but none of the algorithm provides sufficient results. To overcome these issues, a novel test data compression technique for CSA using hosted cuckoo optimization algorithm is proposed in this manuscript for lessening the test data volume during fault analysis. The conflicting bits volume is decreased to achieve the ratio of better compression with reduced test application time (TAT) including test data volume. The proposed algorithm achieves fast global searching capability. Hosted cuckoo optimization (HCOA) algorithm is used to find the optimal solution for the constrained problems. The proposed method is executed in MATLAB. The proposed method attains 23.84%, 27.94%, 32.84% higher compression ratio compared with the existing methods. [ABSTRACT FROM AUTHOR]

We have looked at a very interesting class of Heusler alloy that has received a lot of theoretical research but a very little experimental attention. Mn2TiSi Heusler alloy was synthesized by a conventional vacuum arc remelting process. The formation of Heusler phase along with the secondary phases was observed after annealing it at 773 K for 120 h. The X-ray diffraction pattern illustrates the presence of cubic B2 disordered phase along with a secondary phase with a lattice parameter of 5.82 Å. The microstructure and compositional analysis of Mn2TiSi alloy shows the presence of distribution of Mn, Ti, and Si elements according to their stoichiometric ratio. The magnetic measurements show a ferromagnetic nature with Curie temperature (TC) around 203 K. With low magnetic moment and coercivity, Mn2TiSi can be used for switching applications because of its fast magnetization reversal. So, Mn2TiSi becomes the greatest choice for use in spintronics due to its low magnetic moment and low coercivity. [ABSTRACT FROM AUTHOR]

Ataxia telangiectasia, one of the rare human autosomal recessive disorders, results from a mutation in the Ataxia telangiectasia mutated kinase (ATM) gene, leading to high radiosensitivity, immunodeficiency, and predisposition to cancer. The eukaryotic DNA is a complex component that undergoes a lot of damage due to several endogenous and exogenous stimuli. These stimuli can cause DNA damage regularly, and the human system does repair mechanisms through a range of signal pathways to overcome. DNA double-strand breaks are effectively repaired through ATM-mediated mechanisms like homologous recombination and non-homologous end-joining. Due to replication stress, cancer cells are prone to DNA damage, making them targets for pharmacological intervention to hinder tumor growth. ATM inhibitors, crucial for disrupting DNA damage response pathways in cancer cells, are clinically significant for cancer mitigation. Integrating artificial intelligence (AI) in healthcare can potentially alleviate the workload of healthcare professionals. Detailed discussions delve into the use of machine learning and deep learning programs for the initial screening and monitoring of ataxia and its types. With this focus, the review discusses basic and advanced analytical and AI techniques used to estimate ATM inhibitors and ataxia diseases. • Ataxia telangiectasia mutated kinase gene heightens radiosensitivity and cancer risk. • Understanding DNA damage repair pathways using ataxia telangiectasia is crucial. • Ataxia telangiectasia mutated kinase inhibition promises in cancer therapy. • Artificial intelligence is helpful to healthcare in ataxia screening and monitoring. [ABSTRACT FROM AUTHOR]

This manuscript proposes an optimization method for direct torque control for an induction motor drive with an open-end winding. The proposed method is the Cheetah Optimization Algorithm (COA). The proposed method’s primary goal is to maximize system efficiency and reduce power losses. The COA reduces power loss in the IM by optimizing the control factors such as the inductance of the rotor, the stator resistance, and so forth. This study provides an improvised loss analysis for an OEWIM drive with three levels of dual-inverter feeding and direct torque control (DTC), and comparative loss analysis for decoupled and alternative systems is examined. There are two types of pulse-width modulation schemes: space vector and discontinuous, both based on inverter switching and varying with modulation index. The proposed technique is implemented on the MATLAB platform and compared with current methods. The THD value of proposed technique is 0.99%, and the efficiency is 99.8%, compared with other existing techniques, such as gray wolf optimization, particle swarm optimization, and Capuchin Search Algorithm, the Total Harmonic Distortion (THD) of proposed approach is low. The simulation outcomes indicate that the proposed approach outperforms the existing ones in terms of performance. [ABSTRACT FROM AUTHOR]

Magnetostrictive bimorphs consisting of positive and negative magnetostrictive materials such as FeGa and Ni respectively were made in the form of (a) multilayers containing Si/Ni/FeGa and (b) stacking consisting of Ni/Si/FeGa by sputtering technique on Si substrates. While the thickness of the FeGa film was maintained at 200 nm for all the films, Ni films were grown with two different thicknesses, viz., 100 and 200 nm. Magnetostrictive response of these bimorphs was compared with FeGa unimorph deposited on Si. Structural studies indicated FCC and BCC structure for Ni and FeGa films respectively. Magnetization studies showed a decrease in saturation magnetization with increase in Ni content owing to the lower magnetization of Ni when compared to FeGa. Considerable enhancement in tip deflection has been observed in the bimorph structure when compared with pure FeGa film. [ABSTRACT FROM AUTHOR]

• A reproducible BPCA quantification procedure for deep-sea sediments. • Black carbon derived BPCA exhibit a notable prevalence in marine sediments. • Using BPCA isotopes to trace the origin of black carbon in marine sediments. • Sedimentary black carbon results from both marine and pyrogenic sources. Methodologies based on benzene polycarboxylic acids (BPCA) selectively target the polymeric aromatic fraction of black carbon (BC) and are considered adequate to quantify pyrogenic inputs in environmental samples such as soils, lakes, and marine dissolved organic carbon. However, the usefulness of these methodologies to quantify BPCA-derived BC in deep-sea sediments has not been fully evaluated. In this manuscript we describe and validate a procedure to quantify BPCAs in deep oceanic sediments with very low organic carbon content. The resulting analytical procedure has produced reproducible quantitative data for BPCAs over a period of 10 months (coefficient of variation, CV = 6.4 − 6.6%). The stable carbon isotopes (δ13C) of BC_BPCA have been characterized using an LC Isolink™-irMS system with an accuracy better than 0.5‰. The quantitative and isotopic composition of several marine sediments has been characterized to investigate the relative contributions of marine/diagenetic and continental/pyrogenic sources to the BC accumulated in oceanic sediments from different contexts, ranging from upwelling systems to remote oceanic locations. Overall, a significant fraction of the sedimentary BC is of marine origin and should be considered in inventories of pyrogenic materials accumulated in the world oceans. However, the continental/pyrogenic sources can be largely dominant in marine settings with large inputs of pyrogenic materials. [ABSTRACT FROM AUTHOR]

Radiation-based gauges have been widely utilized in the industry as a dependable, non-destructive method of measuring metal layer thickness. It is only possible to trust the conventional radiation thickness meter when the material's composition is known in advance. Thickness measurement errors are to be anticipated in contexts like rolled metal factories, where the real component of the material could diverge greatly from the stated composition. An X-ray-based device was suggested in this study to measure aluminum sheet thickness and identify the type of its alloys. Transmission and backscattered X-ray energy were recorded using two sodium iodide detectors while a 150 kV X-ray tube in the described detection system was operated. Aluminum layers of varying thicknesses (2–45 mm) and alloys (1050, 3105, 5052, and 6061) were simulated to be placed between the X-ray source and the transmission detector. The development of radiation-based systems used the MCNP code as a very powerful framework to imitate the detecting architecture and the spectra acquired by the detectors. The recorded signals were transferred to the frequency domain using the Fourier transform, and the frequency characteristics were extracted from them. Two GMDH neural networks were trained using these characteristics: one to identify the alloy type and another to determine the aluminum layer's thickness. The classifier network had a 92.2% success rate in identifying the alloy type, while the predictive network had a 1.9% error rate in determining the thickness of the aluminum layer. By extracting important characteristics and using powerful neural networks, this study was able to improve the precision with which aluminum layer thickness was measured and correctly identify the alloy type. The suggested method is used to determine the thickness of aluminum and its alloy sheets and may also be applied to other metals. • An X-ray-based device was suggested to measure aluminum sheet thickness and identify the type of its alloys. • Transmission and backscattered X-ray energy were recorded using two NaI detectors. • The recorded signals were transferred to the frequency domain using the Fourier transform. • Two trained GMDH neural networks determined the alloy type and the aluminum layer's thickness. [ABSTRACT FROM AUTHOR]

Handling of agricultural residues is a major concern today, since they pose a serious threat to the environment. Pyrolysis is one among the different techniques explored across the globe towards the effective conversion of these crop residues into various useful products. In this work, the degradation behaviour of corn husk loaded with tin oxide nanoparticles and raw corn husk are characterized separately by employing thermogravimetric analyzer (TGA). From the thermograms obtained, the energy required for facilitating the degradation process with the aid of the catalyst is found to be 98.48 kJ/mol. Further, the corn husk loaded with prepared tin oxide nanoparticles (0.1 g& 0.2 g) is subjected to pyrolytic degradation at different temperature ranges from 400 °C to 550 °C and compared with thermal pyrolysis. The biochar retained from the pyrolysis process is investigated for its efficacy as an energy storage material after coating them over graphite sheet. Electrochemical analysis reveals the fabricated SnO2/biochar nanocomposite have excellent energy storage characteristics (205 F/g at a scan rate of 10 mV/s) which was attributed to the presence of facile architecture with porous surface area. The outcomes of the present study open fresh gateways for the innovative electrodes in energy domain. [ABSTRACT FROM AUTHOR]

Multiphase fluids are common in many industries, such as oil and petrochemical, and volume fraction measurement of their phases is a vital subject. Hence, there are lots of scientists and researchers who have introduced many methods and equipment in this regard, for example, photon attenuation sensors, capacitance-based sensors, and so on. These approaches are non-invasive and for this reason, are very popular and widely used. In addition, nowadays, artificial neural networks (ANN) are very attractive in a lot of fields and this is because of their accuracy. Therefore, in this paper, to estimate volume proportion of a three-phase homogeneous fluid, a new system is proposed that contains an MLP ANN, standing for multilayer perceptron artificial neural network, a capacitance-based sensor, and a photon attenuation sensor. Through computational methods, capacities and mass attenuation coefficients are obtained, which act as inputs for the proposed network. All of these inputs were divided randomly in two main groups to train and test the presented model. To opt for a suitable network with the lowest rate of mean absolute error (MAE), a number of architectures with different factors were tested in MATLAB software R2023b. After receiving MAEs equal to 0.29, 1.60, and 1.67 for the water, gas, and oil phases, respectively, the network was chosen to be presented in the paper. Hence, based on outcomes, the proposed approach's novelty is being able to predict all phases of a homogeneous flow with very low error. [ABSTRACT FROM AUTHOR]

In this paper, we report a systematic study on effect of film thickness and substrate temperature on structural and magnetic behaviour of Fe-Ga films with Cu buffer layer, deposited on Si and Si/SiO2 substrates at room and high substrate temperatures. Grazing incidence X-ray diffraction studies reveal that all the films are crystalline with disordered alpha-Fe phase, which is BCC A2 phase. At 300 °C of substrate temperature, films deposited on Si/SiO2 substrate found to nucleate L12 phase from matrix of A2 phase, which is not seen in Si based films. Irrespective of substrate material, Fe-Ga films found to exist in dual phases at 500 °C substrate temperature. Lattice strains of the films were calculated from X-ray diffraction patterns, using Williamson-Hall method. From X- ray reflectivity analysis of all the films, film density, thickness and roughness of Fe-Ga layer and buffer layer were obtained after fitting the reflectivity data. Presence of an oxide layer is also evident from reflectivity fitting analysis. From magnetization studies it is clear that, all the films exhibited strong in-plane anisotropy. Saturation magnetization of films was found to vary with change in film density and oxide layer thickness of films. Saturation magnetization of films deposited on Si substrates found to decrease with decrease in film density. Coercivity of films found to vary with change in crystallite size, interface roughness and lattice strain of films. Films deposited on Si substrates are sensitive to strain with change in film thickness and films deposited on Si/SiO2 substrates are sensitive to strain with change in deposition temperature. Coercivity in films found to decrease with decrease in film roughness, increase in crystallite size and lowering the tensile lattice strain. [ABSTRACT FROM AUTHOR]

This paper portrays the effect of growth rate on the structural, magnetic, and electrical properties of sputtered Ni thin films. Seventy-five nanometer thick Ni films were grown on Si <100> substrates at room temperature by high power impulse magnetron sputtering with varying growth rates such as 0.27, 0.57, 1.01, 2.18, and 2.65 Å/s. All the films crystallized in a single FCC type structure devoid of any impurity phase. With an increase in the growth rate, the density of the Ni films was found to increase. The surface roughness and the stresses developed in Ni films were found to decrease with an increase in the growth rate. Microstructural investigations indicated an island of surface morphology for all the films. An increase in growth rate was also found to affect the magnetic properties of Ni thin films considerably. Saturation magnetization increased with an increase in growth rate both along the in-plane and out-of-direction owing to the increase in the density of the film and reduction in stresses and surface roughness. Further, the in-plane magnetization studies also showed an increase in in-plane magnetic anisotropy in Ni films with an increase in growth rate. Evidences for improvement in the in-plane magnetic anisotropy were derived from the increase in the in-plane coercivity and remanence. Temperature variation of electrical resistivity in Ni films indicated a metallic behavior. Films grown at higher growth rates exhibited high-temperature co-efficient of resistance suitable for resistance temperature detector applications. [ABSTRACT FROM AUTHOR]

• Ni 0.5 Co 0.5 Gd 0.025 Tb 0.025 Dy 0.025 Ho 0.025 Fe 1.99 O 4 was prepared by sol–gel method. • All four rare earth elements at B-site with low doping equi molar concentration. • Structural & magnetic behavior due to multi RE doping to Ni 0.5 Co 0.5 Fe 2 O 4 was given. • NC-4R showed good strain sensitivity at lower magnetic field. In this work the impact of multi rare earth (RE) doping (especially four RE elements as dopants at B-site in equi molar concentration) on properties of Ni 0.5 Co 0.5 Fe 2 O 4 was discussed. Ni-Co spinel ferrite with four RE elements at B-site i.e. Ni 0.5 Co 0.5 Gd 0.025 Tb 0.025 Dy 0.025 Ho 0.025 Fe 1.99 O 4 (NC-4R) was successfully synthesized by sol–gel process. From XRD and Raman data FCC spinel structure with Fd-3m space group was observed. Both experimental and theoretical data showed good agreement in Rietveld refinement. Five Raman modes with shoulder like peaks confirm the cubic and mixed spinel structure. Magnetization behaviour with magnetic field and temperature are discussed. NC-4R showed good strain sensitivity i.e. 0.5x10-9 A-1m at lower magnetic field i.e. 1350 Oe which is helpful in energy harvesting applications. [ABSTRACT FROM AUTHOR]

[Display omitted] • Cefadroxil sulfoxide (CDSO) was synthesized and characterized by FT-IR, FT-Raman and UV–Visible spectroscopic technique. • Chemical reactivity and electronic properties were evaluated for the different solvents. • Electronic states DOS, TDOS and COOP analyses were estimated. • Topology analyses viz., ELF, LOL, RDG and electron hole were evaluated. • Molecular docking study and ADME properties were investigated for the anti-microbial targets. The cefadroxil sulfoxide (CDSO) para -hydroxy derivative, derived from cefadroxil, has enormous significance in pharmaceutical applications. The cefadroxil sulfoxide (CDSO) compound was synthesized and characterized by spectroscopic (FT-IR, FT-Raman, and UV–Visible) assessments. Computational investigations have been carried out concurrently with a B3LYP-6-311++G(d,p) basis set and density functional theory (DFT). The molecular vibrational assignments, chemical reactivity, electronic properties, and optical activities are calculated using gas and different solvent phases. The stable ground state configuration of the given molecular compound is investigated using PES analysis. Furthermore, the chemical behavior of the CDSO was thoroughly investigated for different solvent aspects through HOMO-LUMO, MEP, UV–Visible and electron-hole excitation analyses. The molecular occupancy, virtual occupancy, and overlapping bonding energies are investigated by TDOS, PDOS, and COOP spectrum studies. Fukui function and dual descriptor investigations extend to the chemical reactivity of individual atomic sites. The intra-molecular analysis provided a deeper understanding of the molecular interactions performed by natural bond orbitals (NBO) and non-linear optics (NLO), which provided optical activity for the title compound. Additionally, electron localization function (ELF), localized orbital locator (LOL), and reduced density gradient (RDG) analyses were also accomplished to provide insight into the delocalized orbitals in the header composite. The molecular docking was achieved, and the ligand with 4EVM protein is providing the potential antimicrobial biological activity (binding energy −7.12 kcal/mol) of the CDSO compound. [ABSTRACT FROM AUTHOR]

The electrochemical performance of ternary metal oxide electrodes exhibiting faradic battery-type characteristics, represents a promising and desirable solution for addressing the ongoing energy crisis. In the current investigation, we present the optimized solution-combustion synthesis of Co 0.03 Ni 0.97 Fe γ Mn 2-γ O 4 nanoparticles, with varying Fe concentrations (γ=0.01, 0.05, 0.10 %), specifically tailored for application in supercapacitors. The Styrofoam-natured (CNMFO:1) exhibited outstanding specific capacitance, reaching 489.12 Fg−1 at a scan rate of 50 mVs−1. Moreover, validation through galvanostatic charge-discharge (GCD) investigations substantiated a notable specific capacitance of 391.41 Fg−1, achieved at a current density of 1Ag−1. In addition, the CNMFO:1 electrode demonstrated remarkable cyclic stability, retaining 83.87 % of its initial performance over 6000 cycles. Similarly, the fabricated asymmetric device of (CNMFO:1||AC) also demonstrated a maximum specific capacitance of 33.86 Fg−1 under a current density of 1Ag−1, which exhibits good energy and power density of 10.52 Wh Kg−1 and 749.34 W Kg−1 respectively. From the overall observation, the CNMFO:1 electrode exhibited notable cyclic stability and electrochemical reversibility. This research recommends that CNMFO:1 nanocomposite have an extraordinary potential for evolution of active electrode materials forthcoming supercapacitors in energy storage system. • Synthesis: Co 0.03 Ni 0.97 Mn 2-γ O 4 (γ=Fe:0.01, 0.05, 0.10 %) nanoparticle using solution-combustion route. • Characterization confirms the successful formation of the Styrofoam natured of the CNMFO:1 electrode. • The prepared CNMFO:1 electrode exhibits an excellent specific capacitance of 489.12 Fg−1 at 50 mV−1. • The CNMFO:1 electrode showcased prolonged cyclic stability. • The developed ASC device delivers an impressive energy and power density of 10.52 Wh Kg−1 and 749.34 W Kg−1 [ABSTRACT FROM AUTHOR]

The importance of flow monitoring in the oil industry has expanded due to the global need for fossil fuels. This has led to the emergence of a new subset of the flowmeter market. The goal of this study is to use a Radial Basis Function (RBF) neural network developed through Simulated Annealing (SA) to pick features of the signals generated by gamma-based flowmeters in order to determined volumetric fractions. The volumetric detection system presented in this article consists of a137Cs isotope as gamma emitter, two NaI detectors for collecting the photons, and a glass pipe in between them. Monte Carlo N-Particle (MCNP) was used to model the above-mentioned geometry. Fifteen wavelet, frequency, and time characteristics were extracted from the raw data captured by both detectors. First, the SA optimization algorithm was used to identify the suitable attributes. Five useful features were presented as a consequence of this procedure, and they were fed into the RBF network in order to estimate volumetric percentages. This study is innovative in that it combines the RBF neural network with the SA algorithm to pick effective features. The outcome is as follows: (1) Outlining five appropriate characteristics for use in determining percentages of volume. (2) Predicting the volume fraction of materials in two-phase flow with a root mean square error of less than 0.22. (3) By recognizing suitable inputs using the method based on the SA algorithm, the artificial neural network can determine the target output with less computational load. • This research employs an RBF created using SA to identify characteristics in flowmeter data for volumetric determination. • The volumetric detection system uses a137Cs gamma generator and two NaI detectors. • Fifteen wavelet, frequency, and time characteristics were extracted from both detectors. • The SA optimization method identified appropriate characteristics. • Two-phase flow volume fraction was determined with an RMSE of <0.22. [ABSTRACT FROM AUTHOR]

Compared to single-phase multiferroic materials, multiferroic (MF)-magnetoelectric (ME) composites, which combine magnetic and ferroelectric materials, show improved (many orders of magnitude) ME coupling and a higher operating temperature (beyond room temperature). In the present study, lead-free multiferroic Ni0.5Co0.5Fe2O4/BaTiO3 (NCFO/BTO) composites with different weight percentages were prepared through the solid-state reaction approach. The phase purity and structural confirmation were carried out using X-ray diffractograms. The XRD peak shifting in the composites has been observed, and it is attributed to the formation of residual stresses/strains during the sample’s grinding, heating, and freezing processes. Fourier-transformative infrared spectroscopy confirmed the presence of metal-oxygen bonds in spinel NCFO and Ti-O and Ba-O bonds in perovskite BaTiO3. UV-vis spectra disclose the energy gap values of the magnetoelectric composites. It has been found that the energy gap values for pure ferrite are 1.53 eV, the pure ferroelectric phase is 2.99 eV, and the composites possess the Eg values of 1.78 eV, 2.33 eV, 2.77 eV with decreasing ferrite concentration. The M-H hysteresis loops reveal the ferromagnetic nature of pure ferrite as well as the presence of ferromagnetism in composites. The magnetic moment of the NCFO has been found as 2.26 µB and it further decreased to 0.59 µB for the 0.25NCFO-0.75BTO compound. The magneto crystalline anisotropy has been calculated using the law of approach (LA) method and the details are discussed in the paper. [ABSTRACT FROM AUTHOR]

• Molecular geometrical parameters were calculated for the synthesised compound in the gas phase. • Spectroscopic characterizations (FT-IR,FT-RAMAN and UV–Vis) were performed and compared the interpretations with the simulated data. • HOMO-LUMO energies, MEP map, electron-hole distribution analysis was carried out for the different solvents. • ELF, LOL and RDG were estimated for the different solvents. • Drug-likeness and ADMET properties evaluation were discussed. • Docking analysis was performed for various targeted protein inhibitors. Chalcones are a significant class of naturally occurring chemical substances and their derivatives are extremely influential in the field of biological industries. In the current study, the title composite,4 - Chlorochalcone has undergone extensive investigation to understand its spectral properties using a combination of experimental and theoretical calculations. Fourier transform (FT-IR) infrared and FT-Raman characterizations provided valuable insights into the vibrational assignments (functional groups) in the header molecule, while ultraviolet–visible (UV–Vis) spectroscopy explored its electronic transitions and absorbance characteristics. The electronic properties were studied for the solvents viz., ethanol, methanol, DMSO, acetonitrile and benzene through theoretical-computational DFT calculations, revealing details about their molecular orbitals, electronic energies, and other energy parameters. Additionally, the NBO- natural bond orbital analysis shed light on the chemical bonding and electron distributions by donor and acceptor atoms. Furthermore, MEP- molecular electrostatic potential was analyzed for the various solvents and the calculated energy parameters were obtained. A drug-likeness evaluation was performed to assess its potential as a drug candidate based on its molecular properties. Moreover, the topological analysis and electron-hole distributions, contributed to a comprehensive understanding of electron density and localization within the molecule for the solvents viz., ethanol, methanol, DMSO, acetonitrile and benzene. Molecular docking investigations, as well as the Ramchandran plots, revealed that substituents targeting amino acids contribute to the antiviral action of the header compound. The potential of 4′-Chlorochalcone (ligand) as an antiviral agent offers promising prospects for further exploration and development in various therapeutic areas within the field of medicinal chemistry. [ABSTRACT FROM AUTHOR]

Scaling oil pipelines over time leads to issues including diminished flow rates, wasted energy, and decreased efficiency. In order to take preventative measures in a timely manner and avoid the aforementioned issues, it is crucial to get a precise gauge of the scale within the pipe. Non-invasive gamma attenuation systems are one of the most accurate detection methods. In this investigation, he Monte Carlo N Particle (MCNP) technique was used to model a scale thickness measuring system including a test pipe, two sodium iodide detectors, and a dual-energy gamma source. The three-phase flow was created by simulating water, gas and oil in a homogenous flow regime in the test pipe. Additionally, a scale of varying thicknesses was installed inside the conduit. The photon intensity on the opposite side of the pipe was measured by detectors when gamma rays shone through it. Photopeaks of 241 Am and 133 Ba of the transmission detector and the total count of the scattering detector were derived from the signal received by the detectors. Since there are different variables such as scale layer and volume fractions in the present study, it is not possible to use regular known attenuation formulas for calculating the thickness. So, in this paper, RBF was implemented to solve this issue. By training and optimizing a RBF network, we were able to predict the thickness of a scale with an RMSE of 0.057. Having such a small margin for error confirms the validity of the suggested technology and its practical use in the petroleum and petrochemical industries. • This system measure thickness of scale within the pipe using gamma attenuation. • A dual-energy source and 2 NaI detectors are the main components of this system. • After a large number of simulations, they were used as inputs of RBF network. • RBF was implemented to solve this complex issue with different variables. • This system can predict the thickness of a scale with an RMSE of 0.057. [ABSTRACT FROM AUTHOR]