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This research paper examines the uncertainties associated with selecting the optimal location for mobile tower installation while adhering to environmental protection regulations. The harmful effects of mobile tower radiation on living organisms, including humans, birds, and bees, can be mitigated through the proper investigation of installing tower locations based on various scientific criteria. Additionally, implementing proper regulations and guidelines for the construction and maintenance of mobile towers can also help minimize the negative impact of radiation on the environment. However, the fulfillment of these regulations poses several challenges, such as ensuring safety in terms of structural integrity, fire hazards, and aviation regulations, addressing concerns regarding radiation exposure, maintaining appropriate dimensions and weight for tower design, considering the signal range based on the area of operation, and numerous other criteria. This paper determines the optimal selection of mobile locations in scenarios where radiation emissions are uncertain through Fermatean fuzzy sets (FFSs). FFSs address the inherent imprecision associated with determining the optimal location. To measure the distance between two FFSs, the normalized distance (Ed) and normalized Hamming distance (Hd) metrics are utilized. Decision experts identify the most suitable locations for placing mobile towers, such as forested regions, public spaces, residential areas, and educational and healthcare institutions, to maximize their positive impacts. By focusing on these potential positive impacts, this research paper aims to instill hope and optimism in the reader about the future of mobile tower installation.

Non isolated multilevel inverters (MLI) with reduced switch components are becoming more popular to attain higher voltage levels. However, this kind of MLI increases the number of DC sources and has some issues like higher charging current, a high peak VA rating of the switches, and a high capacitor ripple voltage. This manuscript presents a modified multicell based multilevel boost inverter with a multistage DC output. It has three sections namely Boost converter, level shifter and h-bridge inverter. The proposed circuit is powered by solar photovoltaic (PV); using the Perturb and Observe Maximum Power Point method. The suggested circuit working in asymmetric mode and produces a 31-level output waveform. This topology helps to reduce the Total Harmonic Distortion, increases the output voltage levels, and reduces the common mode voltage. This topology is compared with other multilevel inverters presented in recent literature and the analysis is presented. Simulation results for various irradiance values are presented with other key factors. The experimental prototype of a 1.5 kW, single phase, 31-level inverter is designed and verified and the proportional results are substantiated.

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Progress in wisdom medicine has been driven by advancements in big data, cloud computing, and artificial intelligence, enabling the accumulation of valuable information and insights. However, the increasing reliance on cloud-based storage and transmission of medical images has raised significant concerns regarding information security. The risk of unauthorized access to patients' private data poses a considerable obstacle to medical research advancement. Thus, safeguarding patient data in cloud environments is imperative. Color space-based scrambling algorithms (CSSA) are gaining traction for multimedia data encryption due to their compatibility with JPEG and reduced processing requirements. However, traditional CSSA methods rely on colorful images to optimize security, limiting their applicability in fields like medical image processing where color images may be scarce. This study seeks to integrate CSSA image encryption with Multilayer Perceptron (MLP)-based techniques for securing medical images. Additionally, a noise-based data augmentation method is developed to address data scarcity in medical image analysis. Security analysis and temporal complexity assessments are employed to evaluate the effectiveness of the proposed MLP-CSSA deep learning model in encrypting medical images. Results demonstrate robust security in encrypting both grayscale and color medical images, with the proposed MLP-CSSA method outperforming existing encryption techniques.

To bridge the critical implementation gap in Renewable and Thermal Energy Systems (RTES) sector, this study proposed a groundbreaking Integrated Energy Planning (IEP) framework. Existing policy analysis methods for RTES often fall short. This limitation was addressed by investigating the disconnect between policy vision and execution within intricate energy landscape. This analysis was extended beyond Pakistan, incorporating energy policies from leading developed and developing nations alongside a comprehensive existing energy modeling efforts for RTES. By leveraging these insights, the potential of IEP was demonstrated to account for trade-offs and seamlessly integrate diverse energy sources. This paves the way for a more sustainable, secure, and efficient RTES for future.

In this innovative work, the fillers obtained by grinding Samanea Saman flowers were utilized for the fabrication of PLA biocomposites. Melt compounding of SSF fillers and PLA with a co-rotating twin-screw extruder permits the simple production of biocomposites with a substantial stage of filler distribution. The elemental compositions and surface morphology of PLA/SSF biocomposite were analyzed using energy dispersive X-ray (EDX) and scanning electron microscopy (SEM) apparatus. The crystalline structure of the PLA/SSF

Evolving highly competent and economical electrocatalysts for alkaline water electrolysis is crucial in renewable hydrogen energy technologies. The slow hydrogen evolution reaction (HER)/oxygen evolution reaction (OER) kinetics under alkaline electrolytes, still, has troubled developments in high-performance green hydrogen production systems. Herein, we demonstrate the tailoring of the interface of earth-abundant transition-metal nanoclusters (MNCs), including iron (Fe), cobalt (Co), nickel (Ni), and copper (Cu) nanoclusters on nickel oxide nanosheets (M NCs|NiO NS) through metal–support interaction for enriched overall water splitting under an alkaline electrolyte. The strong metal–metal oxide interaction allows alteration of the binding capabilities of hydrogen ions (*H) and hydroxyl ions (*OH) on Ni electrodes. Specifically, the robust interaction between Fe and NiO reveals optimized binding of H* and OH* energies, facilitating the water-splitting reaction under an alkaline electrolyte. In addition, the improved HER/OER catalytic activity is attained with the Fe NCs|NiO NS with small overpotentials of ∼62.0 and ∼380.0 mV for the HER and OER, respectively, a high mass activity of ∼90.0 A g–1, a turnover frequency of ∼5.94 s–1, and long-lasting stability via offering abundant electrochemical active sites, three-dimensional (3D) morphologies, and high dispersion of nanoclusters that provide effective charge and mass transport processes. This study provides a promising strategy for the effective design of efficient bifunctional electrocatalysts based on earth-abundant materials for alkaline water electrolyzers.

ABSTRACTThe production of low-alloy advanced high-strength steels such as the dual-phase (DP) steel with ferritic-bainitic microstructure using a hot strip mill is challenging in terms of consistent mechanical properties-based DP steel without violating the hot strip mill rolling capacity. In the present study, the Artificial Neural Network (ANN) technique was employed to develop tensile strength, yield strength and %Elongation models which can cater to complex relationships between the DP steel mechanical properties as a function of steel composition and rolling parameters. Furthermore, ANN models were used to predict the Nb effect on the mechanical properties of the DP steel. Model prediction and validation confirmed that niobium has a notable influence on mechanical properties. Finally. Nb’s role during hot rolling was reviewed and justified.

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This study investigates a prospective alternative to counter electrodes (CEs) composed of noble metals for dye-sensitized solar cells (DSSCs). By adopting a simplistic acid-etching method and direct blending of MXene and Graphene, we fabricated a novel 2D–2D MXene–graphene (MX–GE CE) counter electrode (MX–GE CE). The formation of a 2D–2D MX–GE structure was confirmed by X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM), respectively. In addition, X-ray photoelectron spectroscopy (XPS) disclosed the interaction between MX and GE, resulting in a structure with pronounced electrocatalytic active sites that enabled outstanding catalytic performance with respect to the iodide/triiodide electrolyte. To determine the optimal weight ratio for device fabrication and to evaluate the stability of MX–GE, various distinct weight ratios of MX–GE were used. Using DFT, the computational band structure, electron density profile, and eigenstate values were analyzed. The results showed that the MX–GE composite with a 2:1 weight ratio had high eigenstate profiles and a larger energy spacing between electronic states, making it suitable as a Pt-free counter electrode in DSSCs. The MX–GE CE exhibited minimal resistance for charge transfer, accelerated kinetics of charge transfer, and efficient diffusion of electrons. The DSSC built using a photoanode loaded with N719 dye and MX–GE CE attained a notable power conversion efficiency (PCE) of 6.4%. Significantly, this PCE was comparable to a DSSC constructed with a conventional Pt CE (8%) under identical testing conditions. These results imply that the synthesized material as a counter electrode has considerable potential as a Pt substitute for DSSC counter electrodes.

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Periclimenes pittisp. nov.is described from the Pitti Islet, Lakshadweep, India. The new species can be distinguished from its congener P. affinis(Zehntner, 1894) by the number of rostrum teeth, presence of single spine on the distal margin of third segment of antennular peduncle, and second pair of pereiopods long and robust with 3 distinct teeth on the inner margin, tips of claw curved with tuft of setae on distal margins. In addition, we have documented the Laomenes tigrisMarin, 2009 associated with crinoid and Cuapetes seychellensis(Borradaile, 1915) from Lakshadweep. L. tigrisis reported for the first time from India and C. seychellensisis new to Lakshadweep.

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Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.

The enzymatic biosensors’ response can be monitored based on the results of nonlinear differential equations. The nonlinear reaction-diffusion equations proposed for this enzyme-based electrochemical biosensor include a nonlinear term associated with Michaelis–Menten kinetics. Herein, the system of nonlinear reaction-diffusion equations is solved using a modified homotopy perturbation method. For all values of the rate constants, the approximate analytical expressions for the concentration profiles, current, sensitivity, and gradient of biosensor have been determined. Performance factors of an enzymatic electrochemical biosensor, such as response time, sensitivity, accuracy, and resistance, are discussed. The analytical results and numerically simulated outcomes using Matlab software have been compared.

Mobile ad hoc networks (MANETs) are the future communication infrastructure for all devices that operate without the elaborate design found in wired infrastructure networks. Constructing a routing protocol that helps MANETs to achieve (QoS). It is quite challenging to achieve energy-efficient routing, due to its limited resources and node mobility concerns, which would impact node resource stability and lead to congestion and lower user QoS. A novel Trustworthy Energy Efficient AODV protocol has been proposed for improving path selection and locating trusted stations to maximize QoS. This approach employs location data, transmission speed, and directions to estimate the energy usage and trustworthiness of distinct nodes. The proposed TEE-AODV protocol includes two new control information namely Trust Request packet and Trust Reply. (T-RREP) AODV's packet includes a neighbor list and channel trustworthiness. The number of working neighbors in every path is counted, and this information is used to efficiently choose paths. The TEE-AODV calculates a QoS supporting metric for each detected route to identify a traffic-free path at any moment and determines whether it is a trusted route. The NS-2 simulator has been used to assess the suggested approach in terms of specific characteristics, including energy consumption (EC), (PDR), end-to-end delay (), and number of dead nodes. According to the experimental results, the suggested framework enhances reliable route selection while lowering e nd-to-end latency and improving energy efficiency. The experimental findings indicate that the suggested TEE-AODV protocol achieves high energy efficiency rate in the selection of trustworthy route and minimizing the $ {E_D} $ ED.

Routes discovery that can provide reliable data transmission in Mobile Ad-hoc Networks is challenging due to its wireless channel characteristics and dynamic transmission environment. Ad-hoc networks frequently experience link failure because nodes are mobile and their positions are not fixed. The cellular ad hoc community's dynamic nature makes it possible to analyze multi-route routing protocols specifically. One of the most trustworthy and environment-friendly routing methods is the Zone Routing Protocol used in Mobile Ad Hoc Networks. Offering timely and trustworthy communication services, however, depends critically on maintaining the Quality of Service, electricity performance, and outstanding resource management. In this research, we suggested an energy-efficient routing method for zone-based MANETs called enthalpy and net routing. First, a completely fuzzy quarter clustering based on an Energy guide is used to perform the clustering. With the help of fuzzy memberships, the AFCM set of rules permits the input of statistics for each elegance. In the second, the best route is selected using Enthalpy Ant Net Routing (EANR) while taking the following factors into account: community disconnection, channel error, buffer overflow, and contention at the link layer. The results of the experiment show that the collection of rules performs better than many existing algorithms in terms of community longevity, electricity consumption, and other metrics.

A dual flat-spherical indentation (DFSI) method is proposed for evaluating elastic-plastic properties of metallic materials under equi-biaxial residual stress (RS) state. DFSI consists of two indentation steps: (step I) performing flat indentation (FI) on a specimen having significant presence of residual stress, and (step II) performing spherical indentation (SI) at the center of residualimprint generated by the FI (step I). Indentation load-depth curve in conventional single spherical indentation (SSI) generallyvaries with RS, while the load-depth curves of SI step in DFSI are almost identicaleven under significant RS; this is attributed to stress redistributionduring the preceding FI step. A set of FE analyses are performed for a wide range of properties of general metals. Regression-based mapping functions are established for evaluating the elastic-plastic properties from the SI data of step II. Finally, the proposed method is validated by performing DFSI experiments on the mechanically stressed SM45C and SS400 specimens.

Propylene glycol (or) 1,2-propanediol (1,2-PD) is an important polyol widely used for pharmaceuticals, polyester resins, paints, cosmetics, antifreeze, etc. Sucrose has emerged as a promising feedstock to produce 1,2-PD, as indicated by recent research findings. Graphitic carbon nitride (g-C3N4/gCN) was synthesized by using different crucibles. Ni–Mo was loaded on different g-C3N4supports via the wetness impregnation method for sucrose hydrogenolysis. Effects of different g-C3N4supports were studied. Catalysts with varying Ni (x= 0–8 wt %) and Mo (y= 0–15 wt %) contents were characterized using XRD, BET, XPS, FE-SEM, Py-FTIR, HR-TEM, TPD (CO2)and Raman spectroscopy. An attempt was made on sucrose conversion into 1,2-PD using a Ni–Mo/g-C3N4catalyst. The catalyst containing 8% Ni and 10% Mo on Gr-gCN exhibited the best performance, achieving complete sucrose conversion with a 76% yield of 1,2-PD under mild reaction conditions. The presence of highly dispersed nanoparticles and the nature of graphitic carbon nitride help improve the reactions’ yield by allowing reactions at lower temperatures, reducing the occurrence of side reactions, and increasing recycling rates. A straightforward approach to material preparation, coupled with the exceptional dispersion of metal nanoparticles, paves the way for a novel platform for biomass conversion.

ABSTRACTThermoplastic materials’ properties like mouldability, thermal stability, impact strength and thermal conductivity have played vital role in the study of nanocomposites in various fields of high-performance applications. Currently, Polyphenylene sulphide (PPS) based nanocomposites have attracted special attention in various automotive applications including automotive parts, coolant and fuel injection systems. The present study is aimed at improving the thermal stability of PPS polymer using lower weight% addition of dichalcogenides nanofillers like Tungsten Disulfide (WS2) and Molybdenum Disulphide (MoS2), prepared through melt compounding process using microcompunder and injection moulding steps. Addition of impact modifier poly-ethylene glycidyl methacrylate (PEGM) was explored while preparing the nanocomposites to enhance the mouldability. The weight loss and crystalline behaviour studies were performed using Thermo-Gravimetric analysis (TGA) and Digital Scanning Calorimetry (DSC) techniques. From the characterisation data, it was observed that the addition of specific nanofillers like WS2has significant effect on the crystallization temperature(Tc), percentage of crystallinity(Xc) and degree of crystallinity(DOC). The PPS nanocomposite sample with 0.5 wt.% WS2, yielded results viz. Tc as 232 °C, 30% of Xc and 66% DOC. The key outcome of this work includes greater thermal stability of nanocomposites by using lower weight percentage additions of nano-scale WS2and MoS2.

This paper has proposed a hybrid seven-level inverter topology with a boosting capability three times that of conventional seven-level inverter topologies. It contains ten number of active switches and an internal flying capacitor unit that develops a composition like the combination of T-type and neutral point clamped (NPC) inverter topologies. The proposed inverter topology increases dc link voltage utilization and reduces the total standing voltages across the power switches. In addition, self-voltage balancing of the floating capacitor is achieved through a simple level shifted PWM modulation technique. The dc link requirement of the proposed inverter topology is reduced by 66% when compared to the conventional seven-level inverters, and it can be more useful in industrial applications, including grid-tied renewable generation units. The working methodology and steady state analysis of the topology are presented, and its operation is validated through the simulation results performed in both Matlab/Simulink and PSIM platforms. In addition, experimental results verify the proposed inverter topology.

Phytochemical substances in seaweeds have a wide range of pharmacological properties and are involved in a unique eco-friendly technique to produce stable, less harmful metal nanoparticles. The antioxidant-rich phytochemical elements in red seaweed Champia parvulaextract have garnered attention for their potential functions in the prevention of human diseases. This research explores the phytoconstituent contents of C. parvulaaqueous extract as well as its ability to synthesize silver nanoparticles, and its antioxidant, antimicrobial, and anticancer properties are investigated. The seaweed extract was analyzed for total phenols (2.02 ± 0.11 mg/g), flavonoids (1.72 ± 0.05 mg/g), tannins (1.55 ± mg/g), anthocyanin (0.79 ± 0.21 mg/g), and total chlorophyll (0.7 ± 0.04 mg/g) contents. The biosynthesized C. parvula-mediated silver nanoparticles (Cp-AgNPs) were characterized by various spectroscopic techniques. The surface plasmonic resonance (SPR) band of Cp-AgNPs was observed at 425 nm using UV spectroscopy. The face-centered cubic (FCC) and crystalline structure were identified by X-ray diffraction (XRD) analysis. Scanning electron microscopy (SEM) confirmed the morphology of Cp-AgNPs as round in shape with 79 nm size. The biomolecules in the algae extract and Cp-AgNPs were identified with the help of FT-IR analysis, which confirms the presence of phenolic, proteins and amine compounds. Zeta potential analysis proved that the biosynthesized Cp-AgNPs were extremely stable due to the surface charge of nanoparticles (− 35.2 mV). The Cp-AgNPs showed greater free radical scavenging ability due to the presence of bioactive molecules such as phenols, flavonoids, tannins, and anthocyanin in algae extract. Cp-AgNPs exhibited the highest antimicrobial activity against Streptococcus mutans, Staphylococcus aureus, and Candida albicansat 100 μg/mL. Furthermore, Cp-AgNPs demonstrated anticancer activity against human lung (A549) cancer and colon (HT-29) cancer cells. The half-maximal inhibitory for lung cancer was found at 21.54 μg/mL, and for colon cancer it was found at 42.36 μg/mL. These findings confirmed that the synthesized Cp-AgNPs have a wide range of pharmacological activities and might be used as target drug carriers.

Inversion analysis of transient absorption data to capture the photoexcited charge carrier population rate dynamics is a powerful technique for extracting realistic lifetimes and identifying recombination pathways. However, for highly scattering samples such as Cu2O nanoparticles (NPs) with associated dielectric Mie scattering, the scattering leads to an inaccurate measure of the excited photocarrier. This work studies methods to correct for the scattering to generalize the use of inversion analysis and provide secondary information about the nature of the scattering NPs. Scattering profiles of semitransparent disks containing Cu2O NPs with different shapes and sizes are measured to demonstrate that the inclusion of scattering in analysis reduces the photoexcited carrier density by 1 order of magnitude. It is found that the photocarrier density response is affected by shape rather than size. A Fourier transform of the scattering profiles produces a distribution of length scales within the sample characteristic of the mean separation of scatterers. This analysis reveals that NPs are forming clusters. Links are made between the scattering and carrier dynamics.

A systematic design and detailed circuit analysis of a solar-powered ROSEPIC (reduced order single ended primary inductance converter) converter for maximum power point tracking (MPPT) and load voltage regulation by cascading an adaptive neuro-fuzzy inference system (ANFIS)-based Bass Gura controller with particle swarm optimization for standalone DC nanogrid applications has been proposed. An accurate mathematical model is derived to evaluate the gains of the Bass Gura controller. The order of the transfer function is reduced by using the moment matching method. The performance of the proposed controller is compared with the conventional Bass Gura controller to show the effectiveness of the system. Also, to substantiate the simulation results, an experimental prototype model controlled by C2000 Piccolo TMS320F28035MCU digital controller is set up. The inferences arrived from the results are (a) the proposed ANFIS-based Bass Gura controller has the ability in tracking 81.48–99.42% of MPPT and load voltage simultaneously against various irradiation levels, temperatures, and loads and (b) the moment matching method eases the controller design by retaining only the dominant modes. Despite of its potential benefits, the ROSEPIC system is also subjected to partial shading conditions, and the results guaranteed that the proposed ANFIS-based Bass Gura controller is effective enough in tracking the MPPT as well as the load voltage.

Scaling up clean hydrogen production using renewable energy is essential for decarbonizing a range of sectors, including transportation, chemicals, and steel, where reducing emissions and achieving net‐zero targets have proven to be challenging. Advances in laser‐based manufacturing, particularly ultra‐high‐speed laser drilling, are crucial for economically producing and scaling up hydrogen components, including high‐temperature hydrogen electrolyzers (HTHE).

This paper is a consolidated sharing of different types of experiences in using the Internet for specific purposes that include online teaching, meetings, conferences, webinars, developing interactive internet-based sessions and discussion panels, writing e-books or connecting the unconnected. It is written by a diverse group of members of three committees sponsoring this paper: IEEE Control Systems Society (CSS) Technical Committee on Stochastic Systems and Control (SSC), IEEE Society for Social Implications of Technology (SSIT) Technical Activity on Universal Access of Technology (UAT) and IEEE Systems Council Committee on DEI. The paper is presented in the form of the collection of sections ending with open discussion on reflections and perspectives. The contributors represent seven different cultures on four continents. This diverse group of co-authors reflects beautifully and powerfully a multidisciplinary character of control as a field that spans all STEM fields.

The impact of seed priming treatment using biosynthesized zinc oxide nanoparticles from (Coriandrum sativumL.) leaves on seed germination and seedling vigour parameters in green gram was assessed at the Seed Centre, TNAU, Coimbatore, from 2020 to 2021. The green gram seeds were primed with various concentrations of biosynthesized zinc oxide nanoparticles (ZnO NPs), namely, 100 mg/lit, 200 mg/lit, 300 mg/lit, 400 mg/lit, 500 mg/lit, and 600 mg/lit, for 3 h. Regardless of the concentration, the ZnO NPs-primed seeds exhibited a significant positive effect on seed germination, seedling vigour, and dry matter production compared to unprimed control and hydro-primed seeds. Seed priming with ZnO NPs at a concentration of 500 mg/lit resulted in an enhanced water imbibition rate in seeds (25.8%), which promoted the synthesis of the hydrolytic enzyme α-amylase (14.73 mg maltose min−1) and the respiratory enzyme dehydrogenase (0.312 units g−1). The ZnO NPs-primed seeds at 500 mg/lit also demonstrated a pronounced effect on antioxidant enzyme activity, including catalase (2138 units g−1), peroxidase (0.342 mg g−1min−1), superoxide dismutase (2.86 mg protein−1min−1), and reduced lipid peroxidation value (0.105 units g−1) compared to hydro-primed and control seeds. The analysis of Zn content confirmed a higher concentration of Zn in the treated seeds, ranging from 52 to 104 ppm, and in growing seedlings from 103 to 357 ppm. These results indicate that ZnO NPs seed priming treatment enhances seed quality parameters by accelerating the hydrolytic enzyme and antioxidant defence system in green gram seeds.

Lithium Niobate (LiNbO3) is a CVD grown synthetic salt having a trigonal crystal structure consisting of niobium, lithium, and oxygen. Due to its variety of mechanical and optical properties, single crystal LiNbO3 finds end use applications in optical waveguides, piezoelectric sensors, optical modulators, and electronic oscillators.

Alumina-Alumina (OX-Ox)CMCs are a technical ceramic composed of alumina fibres in an alumina matrix, with a primary usage case in the aerospace industry. Ox-Ox CMCs offer the traditional benefits of high toughness and bending strength, along with resistance to oxidation and corrosion associated with monolithic alumina, coupled with low brittleness and crack arresting behaviour of fibre in matrix composites. Whilst these properties are highly desirable, CMCs present significant difficulties for conventional mechanical machining, with laser machining offering potential solutions providing the impetus to the work presented in this paper. This work presents a parametric study of the effects of frequency and pulse energy for 10mm deep laser percussion drilled holes and a response surface study for these two variables, using an industrially representative 20kW peak power laser. Results show that for an 800µm diameter hole, a taper angle of <1⁰ and average recast layer thickness of <40µm are achievable, while the response surface study highlights the importance of considering input variables as a complex system, particularly for recast layer thickness.

The state-of-the-art process for manufacturing electric machine laminations, die stamping, lacks flexibility and is only applicable for high-volume production, thus prototyping is often done via laser cutting or electrical discharge machining (EDM). The water jet guided laser (WJGL) is proposed as an alternative method for prototyping. This paper investigates the impact on magnetic characteristics of WJGL cutting electrical steel laminations. A 532 nm nanosecond laser with a maximum average power of 400 W was used to cut 0.2 mm thick non-grain oriented electrical steel (NO20-1200). WJGL process parameters were down-selected through experimental trials. Strips of the electrical steel containing slits were created using two sets of WJGL parameters to examine the effect on the material’s magnetic characteristics. The results indicate that using lower powers could minimise the impact on the relative permeability and core loss. With further development on scaling up, the WJGL has potential for rapid prototyping of laminations.

Laser beam welding is an essential metal joining method for magnesium and its alloys with their growing applications in automotive, aerospace, marine, etc. In this research paper, the experimental modelling for laser beam welding of ZE41 Mg alloy and the mechanical and metallurgical characterisation after welding are reported. The effects of weld scan speed and laser beam power on the weld geometry for bead on plates of ZE41 Mg alloy using a continuous-wave CO2laser system were analysed in this work. The microstructure, hardness, and radiography analysis were discussed. The results indicate the influence of laser parameters and the validity of the regression equations developed for the optimisation of process parameters.

In the current era, harnessing agricultural waste recycling for the production of high-value nutritional products not only addresses sustainability challenges but also holds immense potential for meeting the growing demand for nutritious food sources worldwide. In this investigation, we explored the economic viability of utilizing waste arecanut leaf sheath remnants, a byproduct of plate-making, as a substrate for the cultivation of the edible mushroom Pleurotus ostreatusspp. The study involved assessing various substrate combinations (T1, T2, T3, and T4): Paddy straw alone (T1), arecanut leaf sheath alone (T2), a 1:1 ratio of arecanut leaf sheath and paddy straw (T3), and a 2:1:1 ratio of arecanut, paddy straw, and orange peel (T4). Among the combinations experimented, T4 exhibited the most beneficial outcomes by displaying the rapid transformation of a pinhead into mature mushrooms, highest rate of primordial formation, highest average number of fruiting bodies, and greatest average weight of individual fruiting bodies. Consequently, T4 yielded the highest overall mushroom production. Importantly, T4 addressed the nutritional aspect of mushroom consumption, aligning with the goal of enhancing protein intake while maintaining a low-calorie diet. The T4 combination provided approximately 3.2 g of protein per 100 g of mushrooms, accompanied by an estimated 31.84 calories. These findings underscore the potential of utilizing arecanut leaf sheath and orange peel as sustainable and cost-effective substrates for P. ostreatuscultivation, offering both nutritional and economic benefits. This research contributes to the development of environmentally friendly practices in the field of edible mushroom cultivation.

Family Fellowship Society for Psychosocial Rehabilitation Services is an initiative of families of persons with mental illness and with psychiatric disabilities. It has been advocating self-help movement on the part of the families who have been on the lookout for alternative care services. This venture has been technically supported by the mental health professionals at National Institute of Mental Health and Neurosciences, Bangalore. It is a collaborative effort of families and professionals to address the needs that have been felt by the consumers and the professionals. It is the first of its kind in India. Over a period of 26 years, 150 + families have availed the alternative care for psychosocial rehabilitation services for their wards. In this context, an attempt was made to enlighten the psychosocial rehabilitation services at family fellowship society.

The United Nations has placed significant emphasis on diversity and inclusion, with gender equality now recognized as one of the Sustainable Development Goals. This focus is particularly crucial in developing countries like India, where traditional gender roles persist, often relegating women to roles primarily focused on childcare and elderly care. Despite growing awareness of gender equality, there remains a strong decline in the representation of women in mid-career and senior positions within the technology sector, largely attributed to lack of self-motivation and confidence. To address this disparity, initiatives such as the Returning Mothers Conference have emerged as pivotal interventions, offering skill development, mentorship, and acknowledgement. The conference aims to rebalance the scales by empowering women to recognize the significance of financial independence and encouraging them to take proactive steps towards re-joining the workforce. The impact of such initiatives is evident in the increasing willingness of employers to offer skill development programs and the rising number of female applicants engaging with these opportunities.

Big data analytics is a complex exploratory process to uncover hidden data information from vast collections of data. It often provides enormous information from diverse sources and the use of analytics provides confined knowledge from the collected noisy data. In the case of diabetes data, there exist a massive collection of patient data that relates to significant information on patient health and its critical nature. In order of validating and analysing the data to get desired information about a patient and their health risk from the vast collection of data, the study uses bigdata based deep learning analytics. This study uses a Deep Learning Model namely capsule network (CapsNet) is executed on a MapReduce framework. The CapsNet present in the MapReduce framework enables the classification of instances via proper regulations. This model after suitable training with the training dataset enables optimal classification of instances to detect the nature of the risk of a patient. The validation conducted on the test dataset shows that the proposed CapsNets-based MapReduce model obtains increased accuracy, recall, and F-score than the conventional MapReduce and deep learning models.

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Moulded elastomeric vibration isolators used in aerospace applications are studied for predicting transient vibration response to typical excitations. Vibration isolators used in the present study undergo non-linear static deformations followed by transient dynamic loads. Static deformation is imposed by the specified displacement during assembly of metallic steel parts of isolator, and a static inertial load is applied as the load rating of the isolators. Statically deformed state is obtained using total Lagrangian approach assuming Hookean material model for metallic parts and Yeoh material model for elastomers. Steel properties are used from the literature, and Yeoh material constants are obtained from uni-axial tension test data of elastomer specimen. For transient response study, dynamic elastomeric constants are obtained from test in a Dynamic Mechanical Analyzer as a frequency–dependant complex function. To account for the pre-deformed state of elastomers, the Yeoh material constants are modified which includes frequency–dependant material characteristics and damping in the range of interest using multiplicative non-separable variable law based on the methodology provided for Mooney–Rivlin model. The Finite Element formulation and experimental validation provided for frequency domain response in the previous work is modified to study the isolators for rectangular and trapezium pulse loads and sinusoidally varying loads. Numerical results are validated with experimental observations for rectangular pulse load.

Frequency deviations in microgrids (MGs) often arise due to load fluctuations, posing a challenge for maintaining grid stability. Traditional inverter control does not actively predict future system behavior causing reliability issues. This work resolves this issue by proposing a distributed Model Predictive Control (DMPC) for microgrid frequency regulation. The MG components such as solar photovoltaic system, battery energy storage system (BESS), and voltage source inverter (VSI) modeling are presented. This is followed by modeling and implementation of the proposed DMPC controller. The model is developed in MATLAB/Simulink for validation. The results of MG stability with and without the proposed control scheme are discussed. The proposed model performance is compared with benchmark works, bode plot, and dynamic frequency response analysis. It is found that DMPC-based VSI control optimizes the performance and limits voltage fluctuation. Due to this, during the validation with the base load case, the frequency oscillations are minimal, with a variation of 0.002 Hz around the nominal value. This represents a deviation of less than 0.005%, indicating high precision and stability.

The paper proposes a three-port non-isolated hybrid converter that supplies the load with grid and battery power. In a non-isolated hybrid converter, two input ports are connected to an AC grid and a battery, and an output port is connected to a resistive load. A diode bridge converter receives a single-phase AC grid signal and generates pulsing DC. This design allows for the integration of a battery with the grid as per the requirements of the load and ensures a stable output voltage of 400 V. This voltage range plays a crucial role in hybrid energy applications, particularly in applications like the fast charging of batteries. The converter utilizes five switches to regulate the power flow between the two input ports. The proposed system in Simulink MATLAB utilizes dual loop proportional-integral (PI) controllers to efficiently charge the Battery in Constant Current (CC) charging and ensure power factor correction (PFC). Furthermore, a fuzzy logic controller determines different operating modes according to load demands. The OPAL-RT 5700 is designed to test and validate the performance of real-time hardware in-loop (HIL) systems. The system fulfils the load demand under various load scenarios, efficiently manages power and assesses total harmonic distortion (THD).

Two novel redox conopeptides with proline residues outside and within the active site disulfide loop were derived from the venom duct transcriptome of the marine cone snails Conus frigidusand Conus amadis. Mature peptides with possible post-translational modification of 4-trans-hydroxylation of proline, namely, Fr874, Fr890[P1O], Fr890[P2O], Fr906, Am1038, and Am1054, have been chemically synthesized and characterized using mass spectrometry. The estimated reduction potential of cysteine disulfides of synthetic peptides varied from −298 to −328 mV, similar to the active site cysteine disulfide motifs of the redox family of proteins. Fr906/Am1054 exhibited pronounced catalytic activity and assisted in improving the yields of natively folded globular form α-conotoxin ImI. Three-dimensional (3D) structures of the redox conopeptides were optimized using computational methods and verified by 2D-ROESY NMR spectroscopy: C. frigiduspeptides adopt an N-terminal helical fold and C. amadispeptides adopt distinct structures based on the Phe4–Pro/Hyp5 peptide bond configuration. The shift in the cis–transconfiguration of the Phe4–Pro/Hyp5 peptide bond of Am1038/Am1054 was observed between reduced free thiol and oxidized disulfide forms of the optimized peptides. The report confirms the position-specific effect of hydroxyproline on the oxidative folding of conotoxins and sequence diversity of redox conopeptides in the venom duct of cone snails.

Grid frequency regulation is essential for a reliable power grid. Whilst in distributed energy sources, (DERs) power fluctuations arise from the imbalance of frequency. There are multiple conventional and recent advanced frequency regulation techniques to dissolve this issue. The existing techniques using conventional controllers in microgrid control are well suited for voltage regulation, but the frequency cannot be adequately controlled using conventional and linear controllers. Most of the advanced control methods use algorithms to manage the grid frequency stability. This review comprehensively discusses the advanced control techniques for frequency regulation in micro-grids namely model predictive control, adaptive control, sliding mode control, h-infinity control, back-stepping control, (Disturbance estimation technique) kalman state estimator-based strategies, and intelligent control methods. Each control method is briefly explained along with recent advancements and corresponding governing equations. At glace, these control techniques are comparatively studied by elaborating future requirements.

AbstractHuman corona viral infection leads to acute breathing disease and death if not diagnosed and treated properly in time. The disease can be treated with the help of simple natural compounds, which we use in day-to-day life. These natural compounds act against several diseases but their drug targeting mechanism needs to be improved for more efficient and promising applications. In the present study five compounds (gingerol, thymol, thymohydroquinone, cyclocurcumin, hydrazinocurcumin) from three Indian medicinal plants (ginger, black cumin, turmeric) and its hyaluronic acid (HA) conjugates were docked against initially deposited spike structural proteins (PDB ID 6WPT) and its mutant variant D-614G (PDB ID 6XS6). Docking study result reveals that all the HA conjugates showed the most effective inhibitor of S-protein of initially deposited and D-614G variant forms of SARS-CoV-2. The compounds like Gingerol, Thymol, Thymohydroquinone, Cyclocurcumin, Hydrazinocurcumin, Hydroxychloroquinone, and hyaluronic acid conjugates inhibit the viral protein of both wild-type and mutated S-protein of SARS-CoV-2. The molecular docking studies of phytocompounds with initial deposited and variant spike protein targets show superior binding affinity than with the commercial repurposed viral entry inhibitor hydroxychloroquine. Further, the docking result was modeled using MD simulation study shows excellent simulation trajectories between spike proteins and HA conjugates spices constituents than its free form. DFT analysis was carried out to affirm the reason behind the highest binding affinity of HA conjugates over its free form towards SARS-CoV-2 spike protein targets. Further HA conjugates synthesis and its evaluation against SARS-CoV-2 in vitrostudies are needed to prove our novel idea for an anti-viral drug.Communicated by Ramaswamy H. Sarma