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This work describes the use of urea as fuel and a simple solution-based approach technique for both the pure and Ce-doped ZnMn2O4. The magnetic, structural, optical, morphological, vibrational spectroscopy and solar cell analysis were performed on the resultant materials. By increasing the Ce doping, the grain size shrank. On the other hand, the average crystallite size of pure and Ce-doped ZnMn2O4 represents 29–21 nm. The results of vibrational spectroscopy revealed that the absorption bands 450–900 cm−1 and 950–1050 cm−1 both exhibit spinal manganite formation. The morphologies of the highly uniformly distributed nanoparticles in each sample varied according to the preparation. To reach the Ce doping level, the band gap energy (1.4–2.2 eV) was lowered from the bulk to the nanoscale. M-H loops, the composites showed that cations were paramagnetic to ferromagnetic, were occupied by octahedral and tetrahedral structures. Additionally, the impact of doping on the optical and structural characteristics of various blends was investigated. This advancement suggests the application of prepared blends in various optoelectronic, electrochemical, storage devices, and solar cell applications. [ABSTRACT FROM AUTHOR]

Specifically, biocatalyst coupled semiconductor photocatalysts have great potential towards the eco-friendly decomposition of toxic organic dyes that contaminate water bodies. This study reports the synthesis of vermiwash activated molybdenum doped tin oxide (Mo:SnO2) nanomaterial, for the photocatalytic degradation of a representative cationic dye - methylene blue (MB). The photocatalytic performance of the synthesized nanoparticles was evaluated using UV-visible (UV-vis) spectroscopy and the degrading efficiency of MB dye was quantified. The addition of vermiwash resulted in a marked improvement in the photocatalytic activity of Mo:SnO2 nanoparticles, with a degradation efficiency of 96% achieved after 75 min of irradiation. The nanoparticles were characterized using XRD, SEM-EDX, TEM, FTIR, XPS and UV-vis to confirm the crystal structure, morphology, functional groups, elemental analysis and bandgap energy by using Tauc's plot. The study demonstrates the potential of vermiwash as a green and efficient bio co-catalyst for improving the photocatalytic activity of Mo:SnO2 nanoparticles regarding the degradation of textile effluents. Thus, this study paves a way for new eco-friendly approach for the synthesis of cost-effective, biocatalyst coupled semiconductor photocatalyst. [ABSTRACT FROM AUTHOR]

Hydrothermal reduction was used to synthesise NiCo2S4 nanoparticles anchored on reduced graphene oxide (NiCo2S4@RGO), which were then employed as the counter electrode (CE) in dye-sensitised solar cells (DSSC), as detailed in this paper. Graphene nanosheets have a highly scattered distribution of NiCo2S4 nanoparticles, as seen by scanning electron microscopy and transmission electron microscopy. The iodide/triiodide redox reaction shows great promise when this novel nanostructure is used to enhance electrocatalytic performance via a synergistic impact. Researchers found that the electrocatalytic activity of NiCo2S4 nanostructures was enhanced by the synergistic interaction of nickel and cobalt ions with the highly electrically conductive RGO networks. The enhanced conductivity of rGO and the increased number of octahedral catalytic active sites of Co3+ in NiCo2S4 inverse spinel crystal structure are likely the causes of their synergistic action. A dye-sensitised solar cell utilising a NiCo2S4@RGO composite counter electrode achieves a conversion efficiency of 8.5% when exposed to AM 1.5 simulated solar light (100 mWcm−2), an efficiency that is on par with that of a cell based on a Pt electrode (7.1%) and significantly higher than devices utilising NiCo2S4 (7.3%) and RGO (3.1%). The recently created NiCo2S4 counter electrodes are formidable competitors for potential dye-sensitised solar cell uses due to their novel production method, reasonable price, and outstanding electrocatalytic properties. [ABSTRACT FROM AUTHOR]

The present article addresses the influence of surface mechanical attrition treatment (SMAT) parameters such as a size of the balls (2, 5 and 8 mm ∅ 316L stainless steel (SS) balls) and treatment time (15, 30, 45 and 60 min) on the microstructural features, deformation characteristics, surface roughness and compressive residual stress induced on EN 8 steel. The effective deformation is ~ 25 μm from the top surface along with elongated grains in the near subsurface region. The decrease in crystallite size and an increase in micro-strain become more pronounced during SMAT using balls with a larger diameter and for a longer treatment time. A similar trend is observed in surface roughness. This is mainly attributed to the involvement of higher kinetic energy imposed by SMAT on EN 8 steel. The residual stress induced during SMAT of EN 8 steel measured by x-ray diffraction (XRD) measurements is higher when treated using 2 mm ∅ SS balls when compared to those treated using 5 and 8 mm ∅ SS balls for a similar time duration. Irrespective of the size of the balls, an increase in treatment time has led to a decrease in the residual stress of EN8 steel. Over working of EN8 steel that creates surface cracking has been considered responsible for the decrease in residual stress of EN8 steel treated using 5 and 8 mm ∅ SS balls for any given time duration as well as with an increase in treatment time for a given size of the balls. The development surface cone cracks and material removal from the surface evidenced from the microstructure validates such as an occurrence. When the duration of SMAT is limited to 15 min, a large difference in residual stress values is observed for the EN8 steel treated using 2, 5 and 8 mm ∅ balls, whereas with a further increase in treatment time, the difference between them becomes marginal. Hence, in order to achieve better mechanical properties, the treatment time employed for SMAT of carbon steels should be carefully optimized. The other option available is to choose lower size balls for SMAT. The change in residual stress of EN8 steel as a function of process parameters employed for SMAT and the correlation between the ball size and treatment time with the residual stress are discussed. [ABSTRACT FROM AUTHOR]

In the current study, the co-precipitation technique was employed for the synthesis of Cadmium oxide (CdO) and Copper‒doped Cadmium oxide (Cu‒CdO) nanoparticles. The synthesized samples were subjected to powder X-Ray diffraction (P-XRD), Field emission scanning electron microscopy (FE-SEM), Energy-dispersive X-ray (EDX), Fourier transforms Infrared (FT-IR), UV–Vis spectroscopy, photoluminescence (PL), laser-induced fluorescence spectroscopy and antibacterial investigations. According to the P-XRD analysis, both the samples were simple cubic in structure and have average grain sizes of 54 and 28 nm, respectively. FE-SEM was deployed to explore the surface textures of the samples. EDX technique was used to look at the elemental compositions of the samples. The technique of FT-IR was employed to identify the vibrational modes. UV–Vis spectra in diffuse reflectance mode were obtained and the optical bandgaps of the CdO and Cu‒CdO samples were obtained as 4.52 eV and 2.83 eV, respectively. The photoluminescence studies were conducted at an excitation wavelength of 300 nm and emission peaks were red-shifted in both samples. Fluorescence spectroscopy was applied to explore the lifetimes of synthesized nanoparticles. The technique of Agar-well diffusion was applied to assess the antibacterial performance of the generated nanoparticles against Micrococcus Luteus (gram-positive) and Escherichia coli (gram-negative) bacterium at variable concentrations. Both samples in the current study are significantly effective against both bacterial strains. [ABSTRACT FROM AUTHOR]

Hydrogen is the new age alternative energy source to combat energy demand and climate change. Storage of hydrogen is vital for a nation's growth. Works of literature provide different methods for storing the produced hydrogen, and the rational selection of a viable method is crucial for promoting sustainability and green practices. Typically, hydrogen storage is associated with diverse sustainable and circular economy (SCE) criteria. As a result, the authors consider the situation a multi-criteria decision-making (MCDM) problem. Studies infer that previous models for hydrogen storage method (HSM) selection (i) do not consider preferences in the natural language form; (ii) weights of experts are not methodically determined; (iii) hesitation of experts during criteria weight assessment is not effectively explored; and (iv) three-stage solution of a suitable selection of HSM is unexplored. Driven by these gaps, in this paper, authors put forward a new integrated framework, which considers double hierarchy linguistic information for rating, criteria importance through inter-criteria correlation (CRITIC) for expert weight calculation, evidence-based Bayesian method for criteria weight estimation, and combined compromise solution (CoCoSo) for ranking HSMs. The applicability of the developed framework is testified by using a case example of HSM selection in India. Sensitivity and comparative analysis reveal the merits and limitations of the developed framework. [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]

In this study, vermiwash derived—enzyme enriched ZnO NPs co-doped with copper and nitrogen were synthesized using soft chemical method for cost-effective and eco-friendly photocatalytic dye degradation. Undoped and copper (cationic), nitrogen (anionic) and copper + nitrogen (cationic + anionic) doped ZnO NPs were synthesized separately and compared with their vermiwash derived—enzyme enriched counterparts. Vermiwash—an aqueous liquid obtained from vermi reactor of Eudrilus eugineae earthworm—was used as a reducing agent along with NaOH for the synthesis process. The presence of four enzymes viz. phosphatase, urease, protease and amylase was confirmed through enzymes activity studies. The enzymes quantitative study clearly showed that the enzymes prevalent in the vermiwash are inherited by the vermiwash activated nanoparticles as well as by the photocatalytically treated water. The photocatalytic dye degradation efficiency of the ZnO:Cu:N:vermi nanopowder against the methylene blue dye was found to be 99% which is the best among all the other synthesized counterparts. The photocatalytic dye degradation efficiencies of the enzyme enriched samples were in the order: ZnO:vermi < ZnO:N:vermi < ZnO:Cu:vermi < ZnO:Cu:N:vermi. The same order is observed in the bare samples also: ZnO < ZnO:N < ZnO:Cu < ZnO:Cu:N. The mechanism lying behind the enhanced photocatalytic ability of the vermiwash activated ZnO:Cu:N NPs is illustrated in the paper. The results obtained from the X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), photoluminescence (PL) and enzyme quantitative studies were correlated with the proposed dye degradation mechanism of the vermiwash activated ZnO:Cu:N nanomaterial. The synthesized nanomaterials have good reproducibility and stability. The results showed that the synthesized vermiwash activated ZnO:Cu:N NPs have great potential for the effective degradation of various toxic organic dyes. [ABSTRACT FROM AUTHOR]

Introduction: Temporomandibular Joint Disorder (TMJD) is a debilitating condition that affects the quality of a person's life. However, its aetiology remains controversial. Understanding the signs and symptoms associated with this condition is crucial for better comprehension. Determining the prevalence of TMJD can emphasise the importance of routine Temporomandibular Joint (TMJ) examinations and the implementation of preventive measures. Aim: To determine the prevalence of TMJ pain among patients who reported to the dental Outpatient Department (OPD) between January 2015 and December 2019. Additionally, the study sought to identify potential predisposing factors for TMJ pain. Materials and Methods: A cross-sectional study was conducted in the Dental Department at Pondicherry Institute of Medical Sciences, Pondicherry, India. The study duration was six months, from December 2021 to May 2022. The study was done by examining the medical records of all patients who reported TMJ pain during the specified period. A total of 32,094 patients' records were reviewed, and 322 patients reported pain in the TMJ region. The patients' reported signs and symptoms were extracted from their case records and evaluated. Pearson's Chi-square/Fisher's-exact test was utilised to determine associations between the factors. Results: The mean age of the participants was 35.4±13.2 years. Out of the 32,094 patients who attended the dental OPD, 327 (1.02%; 95% CI: 0.91-1.13) reported TMJ pain. Among these patients, 207 (63.3%) were females. Joint sounds were the most common symptom, observed in 243 (74.3%) patients, followed by emotional stress or tension, reported by 205 (62.7%) patients. Most symptoms were more prevalent in females than males. Parafunctional habits and stress/tension showed a statistically significant association (p<0.001) with male gender. Additionally, occlusal variation, joint sound, missing teeth, chewing with one side, parafunctional habits, and stress showed associations with age. Conclusion: The TMJ pain was more frequently reported by women than men in the studied population. The most common symptoms reported were pain and joint sounds. The highest number of patients fell within the 30 years-55 years age group. Although the prevalence identified was 1.02%, routine TMJ examination should be conducted as a standard part of oral and maxillofacial examinations to identify any predisposing factors that may lead to TMJD in the future. [ABSTRACT FROM AUTHOR]

In this present work, the leaf extract of Ocimum sanctum (O. sanctum) stabilized biofabrication of ceria nanoparticles (CeO2 NPs) were achieved. The XRD pattern of CeO2 NPs reveals the cubic structure. The bandgap energy (Eg) of the as-prepared and annealed CeO2 NPs observed were 2.65 and 2.63 eV, respectively. The XRD pattern confirms the face-centered cubic structure of the nanoparticles. The FTIR study reveals the presence of Ce-O stretching frequency at 400 cm−1. The HRTEM images confirm the spherical shape particles. The photodegradation of methylene blue (MB) dye under UV-Visible irradiation by biosynthesized CeO2 NPs was studied. The MB degradation of as-prepared and annealed NPs was 90 and 60 min, respectively. Antibacterial activity of biofabricated CeO2 NPs was studied. The cytotoxic effects of NPs against A431 human skin cancer cells compared to normal cells revealed the possible use of these NPs as an anticancer agent. [ABSTRACT FROM AUTHOR]

The considerable improvement of technology produced for various applications has resulted in a growth in data sizes, such as healthcare data, which is renowned for having a large number of variables and data samples. Artificial neural networks (ANN) have demonstrated adaptability and effectiveness in classification, regression, and function approximation tasks. ANN is used extensively in function approximation, prediction, and classification. Irrespective of the task, ANN learns from the data by adjusting the edge weights to minimize the error between the actual and predicted values. Back Propagation is the most frequent learning technique that is used to learn the weights of ANN. However, this approach is prone to the problem of sluggish convergence, which is especially problematic in the case of Big Data. In this paper, we propose a Distributed Genetic Algorithm based ANN Learning Algorithm for addressing challenges associated with ANN learning for Big data. Genetic Algorithm is one of the well-utilized bio-inspired combinatorial optimization methods. Also, it is possible to parallelize it at multiple stages, and this may be done in an extremely effective manner for the distributed learning process. The proposed model is tested with various datasets to evaluate its realizability and efficiency. The results obtained from the experiments show that after a specific volume of data, the proposed learning method outperformed the traditional methods in terms of convergence time and accuracy. The proposed model outperformed the traditional model by almost 80% improvement in computational time. [ABSTRACT FROM AUTHOR]

Here, we present the synthesis of a novel porosity core-shell oriented NiS2@C-rGO hybrid network for high-performance supercapacitors using a simple hydrothermal method. The NiS2@C-rGO nanocomposite is a three-dimensional material made up of clusters of NiS2 nanoparticles coated in carbon and rGO nanosheets. To achieve fast ion and electron transportation and a phenomenal specific surface area, NiS2@C-rGO particles are uniformly distributed and intercalated between rGO nanosheets to create a 3D carbon matrix. In a 1 M H2SO4 electrolyte, the cyclic voltammetry and galvanostatic charge-discharge method have been used to thoroughly examine the physicochemical features and electrochemical properties. NiS2 and NiS2@C-rGO were reported to have capacitances of 565 Fg−1 (1 Ag−1) and 1297 Fg−1 at 1 Ag−1, respectively, with 95.3% capacitance retention after 10,000 cycles at 1 Ag−1. The NiS2@C-rGO is utilized as a positive electrode, and activated carbon (AC) is employed as a negative electrode to fabricate a supercapattery, which exhibits a wide operating potential window of 1.6 V, a high energy density of 44.1 Whkg−1 at 755 Wkg−1, and even 10 Whkg−1 at an elevated power density of 7650 Wkg−1. Hence, the fabricated ASC device confirmed that the NiS2@C-rGO composite could be used as energy storage electrode materials for supercapacitor applications. [ABSTRACT FROM AUTHOR]

Purpose: To assess the negative predictive value of PSMA PET scan for lymph node staging in patients undergoing robotic radical prostatectomy and pelvic lymph node dissection. Materials and methods: A retrospective analysis of patients who underwent robotic-assisted radical prostatectomy with pelvic lymph node dissection and had a preoperative negative PSMA PET scan for metastasis was performed. The documented pre-operative variables studied included age, BMI, PSA at diagnosis, Gleason score, and biopsy ISUP grades. Patients were categorised as low, intermediate and high risk according to the D Amico classification. The post-op variables included were number of lymph nodes harvested, number of positive nodes, positivity rate, size of the node metastasis, T staging and ISUP grading. Results: The overall negative predictive value of PSMA PET scan was 71.6%. Further sub-classification according to risk stratification demonstrated a NPV of 58.02%, 92.7% and 90% for high, intermediate and low risk, respectively. Conclusion: Pelvic lymph node dissection cannot be excluded based on a negative preop PSMA PET/CT scan. [ABSTRACT FROM AUTHOR]

The present study reports the development of multi-functional coatings on titanium for orthopaedic implant applications. The multi-functional coating approach involves the development of TiO2 nanotubes by anodization followed by dip coating of polycaprolactone (PCL) in which the polymer matrix is incorporated with bioglass (BG), Ag doped bioglass (AgBG), Ag doped bioglass-graphene oxide (AgBG-GO), Ag doped bioglass-reduced graphene oxide (AgBG-rGO) and bioglass-silver functionalized reduced graphene oxide (BG-AgrGO). The structural and morphological characteristics, bioactivity and antibacterial activity of the multi-functional coatings were evaluated. The AgBG-GO/PCL and BG-AgrGO/PCL composite coatings exhibit better antibacterial activity than the AgBG/PCL and AgBG-rGO/PCL composite coatings. Among them, the BG-AgrGO/PCL composite coating with higher loading and slow release of silver ions is suitable for long term antibiotic delivery. The BG-AgrGO/PCL composite coating shows a Ca/P ratio of 1.53. The formation of Ca-deficient apatite of this composite coating suggests that the AgrGO did not hinder the bioactivity. Further, rGO nanosheets enable a higher loading of Ag and the persistence of 0.98 at% of Ag even after 10 days of immersion reveals sustained release of antibiotics in the physiological medium. The retention of coarse BG particles and the lower number of oxygen functional groups of rGO and AgrGO could have limited the dissolution of BG particles in the AgBG-rGO/PCL and BG-AgrGO/PCL composite coatings even after 14 days of immersion in HBSS. With a higher loading, slow release of antibiotics and having adequate bioactivity, the BG-AgrGO/PCL composite coating can be considered as a potential candidate for biomedical implant materials. [ABSTRACT FROM AUTHOR]

Polycrystalline SbAs nanorods were synthesized by the simple solvothermal method. X-ray diffraction analysis of prepared SbAs confirmed the formation of rhombohedral structure and the average crystallite size of ~9 nm. Nanorods shaped morphology of SbAs polycrystalline was studied using high-resolution scanning electron microscopy analysis. The optical bandgap energy of 3.58 eV was determined from UV–visible spectrum with absorption maximum at 226 nm. An uncommon and fascinating potential-induced semiconductor to insulator-like transition is determined within the frequency-dependent real and imaginary part of impedance, dielectric plot and modulus plot. The direct bandgap of prepared SbAs nanorods made it applicable in opto-electronic devices. [ABSTRACT FROM AUTHOR]

Heusler alloy-based materials have been experimentally and theoretically explored owing to the growing features, determining interests, and capacities in spintronics. In the present work, the structural, morphological, thermal, thermoelectric, and magnetic properties of inverse Heuser alloy Cr2NiAl have been investigated. Mechanical alloying was used to prepare the inverse Heusler alloy to produce homogeneity and nanocrystalline nature. The structure and magnetization effects on the size of the nanoparticles were investigated. Structural analysis reveals face-centered cubic with XA or Xα structure. A high-resolution scanning electron microscope study discloses that the particles have aggregated morphology. Thermoelectric measurement endorses metallic to semiconducting-like nature. Room-temperature magnetization measurement suggests soft ferromagnetic nature. Enhanced magnetic properties such as magnetic saturation, coercivity, and retentivity are observed with an increase in annealing temperature. [ABSTRACT FROM AUTHOR]

Co2MnAl Heusler alloy nanoparticle was synthesized by a facile solid-state reaction method. The structural, morphological, thermal, thermoelectrical, and magnetic properties of Co2MnAl full Heusler alloy have been investigated. The X-ray diffraction data indicates the alloy particles are polycrystalline in nature with a cubic crystal structure. The prepared alloy was thermally stable up to 705 °C, and it is confirmed through thermogravimetric analysis and differential thermal analysis. The temperature-dependent Seebeck coefficient and Hall measurement exhibit the negative carrier concentration; it shows the prepared alloy was an n-type semiconducting nature. The vibrating sample magnetometer data indicated that the alloy particle exhibits soft ferromagnetic nature with low coercivity and a high Curie temperature of 736 K. The Co2MnAl full Heusler alloy will be suitable for spintronics device applications, as it shows high magnetic moment with low coercivity. These results unambiguously indicate that it possesses great advantage for implementation into giant magnetoresistance or tunneling magnetoresistance for next-generation spintronics device application. [ABSTRACT FROM AUTHOR]

In this work, an attempt to augment the photocatalytic dye degrading ability of zinc oxide thin films by suitably doping strontium + molybdenum(Sr + Mo). The ZnO:Sr:Mo film were coated onto glass substrates via automatic nebulizer spray pyrolysis method. The photocatalytic studies were done by degrading two dyes viz methyl orange (MO) and methylene blue (MB) and the efficiency of the prepared films was tested at different pH levels. A 97% and 84% decomposition are observed for MB and MO dyes, respectively, in 60 min. The kinetics and reusability of the catalyst were studied. The results indicated that the catalysts exhibit considerable reusability and high photocatalytic efficiency. A possible mechanism for the improved degradation has been elaborated with the support of characterization studies. [ABSTRACT FROM AUTHOR]

Industry 4.0 and the emergence of the circular economy have inspired industries to rigorously concentrate on digital technologies (DTs). There is an excellent appetite for DTs in developing countries like India, and initiatives such as Digital India have transformed business to a more sustainable dimension. Encouraged to adopt DTs, industries identify practical barriers at the social, environmental and economic levels. Although the literature provides discussion on these barriers, a rational prioritization is lacking. To circumvent the problem, a fuzzy decision model is put forward. Firstly, the barriers affecting DT adoption are reviewed and industry experts can rate the barriers after that. Owing to the diversification/heterogeneity of the experts, biased weights are determined by the fuzzy-attitudinal-CRiteria Importance Through Inter-criteria Correlation (CRITIC) technique. Furthermore, the barriers are prioritized by proposing the interactive COomplex PRoportional ASsessment (COPRAS) algorithm. Finally, a case example from the food industry is exemplified so as to understand the usefulness of the model, and a comparison with the other models is made so as to realize the benefits and the shortcomings. [ABSTRACT FROM AUTHOR]

Suitable management and treatment of healthcare waste (HCW) have become a key issue due to its potential risk to human health and the environment, predominantly in emerging nations. The selection of an optimal HCW treatment (HCWT) option is a complicated multicriteria decision-making (MCDM) problem that includes several incompatible qualitative and quantitative attributes. This article presents an extended MCDM methodology for assessing and choosing the HCWT options using Pythagorean fuzzy stepwise weight assessment ratio analysis (PF-SWARA) and additive ratio assessment (PF-ARAS) approaches. To do this, attribute weights are estimated by the SWARA model and the ARAS framework decides the preference order of the options on Pythagorean fuzzy sets (PFSs). Furthermore, a selection problem of HCWT options in India is presented within PFSs to illustrate the efficiency and practicality of the introduced framework. Comparative discussions and sensitivity analysis are presented to demonstrate the rationality and stability of the developed approach for prioritizing HCWT options. [ABSTRACT FROM AUTHOR]

The role of cloud services in the data-intensive industry is indispensable. Cision recently reported that the cloud market would grow to 55 billion USD, with an active contribution of the cloud to healthcare around 2025. Inspired by the report, cloud vendors expand their market and the quality of services to seek growth globally. The rapid growth of the cloud sector in the healthcare industry imposes a challenge: making a rational choice of a cloud vendor (CV) out of a diverse set of vendors. Typically, the healthcare industry 4.0 sees the issue as a large-scale group decision-making problem. Previous studies on a CV selection face certain challenges, such as (i) a lack of the ability to handle multiple users' views, as well as experts'/users' complex linguistic views; (ii) the confidence level associated with a view is not considered; (iii) the transformation of multiple users' views into holistic data is lacking; and (iv) the systematic prioritization of CVs with minimum human intervention is a crucial task. Motivated by these challenges and circumventing them, a new big data-driven decision model is put forward in this paper. Initially, the data in the form of complex expressions are collected from multiple cloud users and are further transformed into a holistic decision matrix by adopting probabilistic linguistic information (PLI). PLI represents complex linguistic expressions along with the associated confidence levels. Later, a holistic decision matrix is formed with the missing values imputed by proposing an imputation algorithm. Furthermore, the criteria weights are determined by using a newly proposed mathematical model and partial information. Finally, the evaluation based on the distance from average solution (EDAS) approach is extended to PLI for the rational ranking of CVs. A real-time example of a CV selection for a healthcare center in India is exemplified so as to demonstrate the usefulness of the model, and the comparison reveals the merits and limitations of the model. [ABSTRACT FROM AUTHOR]

This paper presents a new interpretive structural modeling (ISM) technique based on linguistic term sets. In the proposed approach, the linguistic terms will replace binary numbers 0 and 1, representing one attribute's influence on another. The main objective is to introduce the concept of linguistic term sets to the ISM and develop a linguistic interpretive structural modeling (LISM), where the decision-makers (DM) would use linguistic terms such as very high (VH), high (H), low (L), very low (VL) and, no influence (N) to measure the strength of the impact of an attribute on other attributes. Since the linguistic terms are closer to the human cognitive process, it is more convenient and realistic for the decision-makers to use linguistic terms instead of binary numbers to express the pairwise relationship between different attributes. The integration of fuzzy linguistic terms and the ISM would enhance the consistency level and reduce the uncertainty inherent in the decision-maker's choice. The proposed LISM has been demonstrated by identifying the inter-relationships among the key attributes of business analytics methodology (BAM) acceptance in the industry settings. [ABSTRACT FROM AUTHOR]

Introduction: Enteric fever continues to be endemic in the Indian subcontinent carrying with it significant morbidity, despite available antibiotics. With changing trends in antibiotic use, concern for emerging resistance to many common pathogens is very common. Taking enteric fever, as a case in point, there is evidence of increased use of azithromycin and thirdgeneration cephalosporins. Documenting evidence of increasing concentrations of antibiotics, required to inhibit the organism, is necessary to alter the prescribing practice and to adopt course correction. This is required to modify antibiotic policies in health care setups both for the management of antibiotic susceptible and resistant cases of enteric fever. Aim: To document the rising Minimum Inhibitory Concentration (MIC) of azithromycin among Salmonella isolates. Materials and Methods: A cross-sectional study was conducted in Pondicherry Institute of Medical Sciences for a period of seven years (January 2014 to December 2020). A total of 168 clinical isolates from enteric fever cases were tested for drug resistance to azithromycin by disk diffusion as per Clinical and Laboratory Standards Institute (CLSI) guidelines. MIC was estimated using the Epsilometer test. Results were interpreted as per CLSI 2020 guidelines. Spearman's rank correlation coefficient (r) and twotailed p-values were estimated to note the trend. Results: Out of 168 Salmonella isolates, 65 were Salmonella Typhi and 103 were Salmonella Paratyphi A. MIC of these isolates ranged from 1.5-64 µg/mL and three isolates were resistant to azithromycin with MIC =32 µg/mL and nine isolates had a high level of MIC of 24 µg/mL. Disc diffusion test results were consistent with MIC of azithromycin against Salmonella isolates from enteric fever. Regression coefficient for MIC for the given value of zone diameter for 65 Salmonella Typhi isolates was -0.579 (p<0.001, considered highly significant) and -0.475 (p<0.01, considered as significant) for Salmonella Paratyphi A isolates. Rising MIC to azithromycin was observed among Salmonella isolates over a period of seven years. Conclusion: There is a need to monitor the rising trend of MIC, which may pose a therapeutic challenge for treating enteric fever cases in near future. Regular MIC estimation can pre-empt overt resistance. Hence, MIC testing should be routinely done where facilities are available than doing only disk diffusion testing for enteric fever isolates. [ABSTRACT FROM AUTHOR]

Employing enzymes as co-catalysts with semiconducting oxides is one of the cost-effective and nature-friendly ways for photocatalytic decomposition of toxic organic dye molecules. In the present study, enzyme-powered zinc oxide nanomaterial was prepared using vermiwash derived from the earthworm (Endrilus eugeniae) culturing unit. Two sets of samples were prepared via a simple soft-chemical method by applying heat (i) during the stirring stage of synthesis and (ii) as post-synthesis heat treatment. The effect of this heat treatment on the photocatalytic efficiency of the synthesized nanoproduct has been studied. The study on the activity of enzymes present in the nanoproduct, structural studies through X-ray diffraction, scanning electron microscopy, transmission electron microscopy and photocatalytic degradation studies are fitly correlated among them to address the observed enhancement in the photocatalytic activity. The results provide strong evidence to support the potential use of vermiwash for synthesising nano-sized photocatalysts that can be used to treat toxic organic pollutants, such as methylene blue. [ABSTRACT FROM AUTHOR]

This paper proposes a novel ranking model under probabilistic hesitant fuzzy set (PHFS) by extending the idea of evidence theory (ET). PHFS is a strong variant of hesitant fuzzy set that associates occurrence probabilities to multiple membership grades. This offers flexibility to experts during preference elicitation and aids proper handling of uncertainty. Evidence theory is also a powerful concept for managing uncertainty/hesitation. By integrating Bayesian approximation with ET, a flexible ranking model is developed that complements ET. Due to the partial availability of evidences for decision-making under uncertainty, an approximation strategy is combined. Previous studies on PHFS have not handled hesitation of experts better and to alleviate the issue, a new regret-rejoice approach is put forward that calculates weights of criteria by handling hesitation efficiently. Ranking values from each expert are obtained that are further fused by the Maclaurin operator to get the final ranking order. These approaches are integrated into a framework and its usefulness is exemplified using renewable energy technology selection for Tamil Nadu. Finally, comparative analysis with other approaches reveals the strengths and weaknesses of the proposed work. [ABSTRACT FROM AUTHOR]

In the title compound [systematic name: 1-(3-methyl-2,6-diphenylpiperidin-1-yl)ethanone], C20H23NO, the piperidine ring adopts a distorted boat conformation, while the phenyl rings subtend a dihedral angle 65.1 (2)°. In the crystal, molecules are linked by C--H⋯O hydrogen bonds into chains extending along the b-axis direction. The DFT/B3LYP/6-311 G(d,p) method was used to determine the HOMO-LUMO energy levels. A Hirshfeld surface analysis was conducted to verify the contributions of the different intermolecular inter-actions, indicating that the important contributions to the crystal packing are from H⋯H (73.2%), C⋯H (18.4%) and O⋯H (8.4%) interactions. [ABSTRACT FROM AUTHOR]

This study examines the impact of the COVID-19 pandemic on the determinants of FinTech Peer-to-Peer (P2P) lending. The issue is significant because P2P lending platforms have attracted borrowers with little to no access to the credit facilities offered by conventional banks during the pandemic. Although many banks and financial institutions have offered online loan application services during the COVID-19 pandemic, few have developed verification of loan applications submitted online. The results of this study show that the COVID-19 has brought a drastic change in the key determinants of P2P lending. The results imply that FinTech P2P lending has become the most viable alternative credit option available to borrowers. The findings are significant and likely to be of interest to borrowers, investors, practitioners, academics, and policymakers because they highlight the usefulness of P2P lending platforms and their potential to augment or replace lending provided by traditional or conventional banking institutions. [ABSTRACT FROM AUTHOR]

The Cr2FeAl inverse-based Heusler alloy nanoparticle was synthesized using mechanical alloy method. The as-prepared sample was annealed at various temperatures (700 °C, 800 °C, and 900 °C) in nitrogen gas for 5 h. The nanoparticles were annealed at varying temperatures in order to investigate the influence of annealing on crystal structure and magnetic properties. The structure, morphology, and magnetic properties were determined from X-ray diffraction (XRD), high-resolution scanning electron microscopy, and vibrating sample magnetometer. XRD analysis shows that the samples are having XA or Xα structure disordered phase. The grain size of 24-h ball-milled XA structure of Cr2FeAl Heusler alloy phase, calculated by analyzing the XRD peak broadening using Williamson and Hall approach, was 29 nm. The magnetic properties of Cr2FeAl Heusler alloy nanoparticles were studied, showing ferromagnetic behavior and low coercivity of soft magnetic nature. The Cr2FeAl Heusler alloy nanoparticles can be potential materials for use in spin polarized based spin sensors, spin devices, magnetic sensors, and magneto-electronic device applications. [ABSTRACT FROM AUTHOR]

Green supplier selection (GSS) is a crucial issue in green supply chain management. CAPS indicate that industries spend yearly USD 25 million per procurement, which is a huge amount that necessitates a systematic GSS to avoid financial catastrophes. Literatures on GSS reveal that researchers have not addressed the issue of missing preferences, consistency of decision matrices, and repairing inconsistencies. Moreover, handling of complex linguistic expressions is another open challenge in GSS. Motivated by these research gaps, a two-stage decision framework was proposed. From the analysis of different linguistic models, it is clear that a double-hierarchy linguistic model is flexible for handling complex expressions. In the preprocessing stage, preferences were imputed using the case-based method. Later, consistency of matrices was determined using the Cronbach's coefficient, and inconsistent matrices were repaired using the iterative method. In the next stage, new mathematical models were formulated to calculate weights of experts and criteria. Preferences were sensibly aggregated by using the Maclaurin symmetric mean operator, which captures the criteria interrelationship. Green suppliers were prioritized by using the TODIM method. Finally, the practicality, strengths, and weaknesses of the proposed framework were realized by demonstrating a case study of GSS and comparison with other methods. Results infer that the proposed framework (i) is consistent with the existing models, and the values are 0.60, 0.86, and 0.75, respectively; (ii) is robust with 100% rank-order stability even after adequate weight alterations; and (iii) finally can better discriminate suppliers with a broad deviation range of 0.34–0.35. [ABSTRACT FROM AUTHOR]

The paper aims to present an integrated approach to solve the decision-making problem under the probabilistic hesitant fuzzy information (PHFI) features, which is an extension of the hesitant fuzzy set. The considered PHFI not only allows multiple opinions, but also associates occurrence probability to each opinion, which increases the reliability of the information. Motivated by these features of PHFI, an approach is presented to solve the decision problem with partial known information about the attribute and expert weights. In addition, an algorithm for finding some missing values in the preference information is presented and stated their properties. Afterward, the Hamy mean operator has been used to aggregate the different collective information into a single one. Also, we presented a COPRAS method to the PHFI for ranking the given alternatives. The presented algorithm has been demonstrated through a case study of cloud vendor selection and its validity has been revealed by comparing the approach results with the several existing algorithm results. [ABSTRACT FROM AUTHOR]

India is endowed with a variety of coastal wetlands viz., mangroves, seagrasses, saltmarshes, coral reefs, lagoons and tidal flats, and the country is also a signatory to the Ramsar Convention on Wetlands and the Convention of Biological Diversity, besides having a robust framework of laws and policies, governing the wetland conservation. However, the conservation strategies can better be improved in the context of increasing pressures and threats and limited success of restoration/rehabilitation. Land conversion and ecological degradation of coastal wetlands are the stressors, associated with rapid coastal developmental activities and climate change. The coastal wetlands require desired habitat niche and hence, the conversion of coastal wetlands to other land uses (including agricultural and urban lands) may lead to permanent loss, whereas ecologically degraded coastal wetlands may be resilient if supported by effective protection measures. Preventing the habitat conversion and maximizing the adaptive potential (viz., the ability of populations or species to adapt to rapid environmental change with minimal disruption) by preserving the ecological health are the need of the hour to safeguard the existing coastal wetlands and sustain the provisional ecosystem services offered by them rather than short-term increase in area by unproductive restoration/rehabilitation efforts. Since coastal wetlands are flow through ecosystems, preserving the hydrological connectivity, facilitating the connectivity between adjacent ecosystems and protection of natural corridors are potential strategies that are required to enhance the adaptive potential of coastal wetlands. This analysis calls for site-specific, long-term and integrated ecosystem-based protection, management and rehabilitation strategies based on scientific principles and enforcing the effective legislative measures to regularize the coastal developmental activities in India. [ABSTRACT FROM AUTHOR]

Strontium doped Cerium oxide (Ce1-0.25Sr0.25O2 nanocrystals were synthesized by combustion technique. The synthesized (Ce1-xSrxO2, x = 0.25, 0.5) nanocrystals were annealed at 500° C for 2hr. The phase formation, surface morphology and elemental composition analysis have been studied using XRD, HRSEM and EDXS. XRD and HRSEM measurements revealed that the synthesized nanocrystals were in single phase with face-centered cubic (fcc) structure and that the nano-grains had different sizes. Chemical composition was confirmed using EDXS. The UV-Vis spectroscopic studies revealed that as the Sr doping level increases, the band gap width increases from Eg = 2.9 eV to 2.95 eV. At the same time, the wavelength of maximum absorbance shifts from λabs = 285 to 300 nm. Further, PL studies were performed with excitation wavelength λ = 350 nm and two main emission peaks were observed at 415 and 437 nm respectively. TGA, DTA and DSC measurements were carried out to check the weight loss and the occurrence of endothermic/exothermic reactions. [ABSTRACT FROM AUTHOR]

This study describes how video conferencing saves a person profits and time, reduces travel costs, and stimulates its participation everywhere. These Video conferencing is a technique for visual correspondence in which eye-to-eye and direct contact takes place without any traffic. It shows the behavioral development of social events, workshops, and instructional courses by exchanging these ongoing communications with the help of the website. Furthermore, it provides cost reduction and profitability and safe living for long-distance travelers and enables its service to run smoothly without any hindrance. With the development of this information technology, it has become very important for various activities such as online video conferences. At the same time, the method of video conferencing has been safely developed without giving place to online crimes. There is a huge gap between basic security and its impacts on society, and gaps need to be analyzed to improve the situation. Accordingly, when 243 samples were taken to explore the primary video conferencing type of security and explored through the Kruskel-Wallis test, various advantages emerged. This research method shows separate box plots regarding primary video conferencing security. Various companies are making HD video calls from their favorite gadgets that can be connected to the Internet from anywhere and run in minutes with safe operations explore its applications through this amazingly advanced cloud video conferencing. [ABSTRACT FROM AUTHOR]

Objective: To determine breastmilk sodium changes in the first 72 hours after birth and to correlate maternal and neonatal variables with maternal breastmilk sodium. Methods: We enrolled 245 mothers and their exclusively breast-fed neonates in this prospective cohort study. Singleton, inborn babies of greater than 34 weeks gestation, who were exclusively breastfed for the first 72 hours were included. Babies who required neonatal intensive care unit (NICU) admission, top up feeds or discharged before 72 hours were excluded. Study outcomes were changes in breast milk sodium in the first 72 hours and association of high maternal breast milk sodium with various maternal and neonatal variables. Results: Mean (SD) breastmilk sodium steadily declined over the first 72 hours [53.5 (19.2), 38.5 (19.0) and 22.2 (10.6) mmol/L at 24, 48, 72 hours, respectively]. Breastfeeding ≤8 times per 24 hours in the first three days was the only factor significantly associated with high breastmilk sodium (P=0.008). Maternal age, gravida, mode of delivery, significant neonatal weight loss, hypernatremia, neonatal morbidities like fever, irritability, lethargy and poor suck had no significant correlation with high breastmilk sodium. Conclusion: Breastmilk sodium shows a steady decline in the first 72 hours after delivery. Feeding ≤8 times per day is associated high breastmilk sodium at 72 hours of age. [ABSTRACT FROM AUTHOR]

Cloud vendors (CVs) play an indispensable role in the development of IT sectors and industry 4.0. Many CVs evolve every day, and a systematic selection of these is becoming substantial for organizations. Literature studies have shown that multicriteria decision‐making (MCDM) is a powerful tool for systematic selection. However, the major issue with the state‐of‐the‐art models is that they do not effectively represent uncertainty. Moreover, the personalized selection of CVs based on user queries is not prominent in an MCDM context. In this paper, to circumvent these issues, a new decision framework is proposed that utilizes a generalized preference style called interval‐valued probabilistic linguistic term set (IVPLTS). This preference style considers occurring probability values as interval numbers instead of a single precise value, which provides flexibility during preference elicitation. Initially, missing values are imputed systematically by using a case‐based method. Then, the consistency of these preferences is checked using Cronbach's alpha coefficient, and the inconsistent preferences are repaired rationally by using an iterative method. A programming model is proposed for determining the weights of the evaluation criteria. Furthermore, Maclaurin symmetric mean (MSM) is extended to IVPLTS for aggregating preferences from each expert. The interval‐valued probabilistic linguistic comprehensive (IVPLC) method is proposed for prioritizing CVs in a personalized manner. Finally, the framework's practicality is validated by using a case study of CV selection for an academic institution; strengths and weaknesses of the framework are conferred by comparison with extant CV selection models. [ABSTRACT FROM AUTHOR]

As a promising option, Hydrogen as a clean energy alternative has been acknowledged for emissions alleviation and environmental safety. Life cycle sustainability evaluation of hydrogen can help the experts choose the desirable sustainable methodology for hydrogen production in life cycle standard over various options. This paper proposes a sustainable approach for selecting apt hydrogen production methodologies by integrating life cycle sustainability evaluation and an uncertain linguistic multi-attribute decision-making approach. As a useful extension to linguistic models, probabilistic uncertain linguistic term sets (PULTSs) have attracted many scholars. Elicitation of precise occurring probability value for each uncertain linguistic term is an interesting and open challenge. Occurring probability values are considered interval numbers with lower and upper limits associated with each uncertain linguistic term to form interval-valued probabilistic uncertain linguistic term sets (IVPULTSs). Various operations and axioms of the IVPULTS concept are discussed. Next, a novel aggregation operator is proposed under the IVPULTS context for aggregating decision expert's preferences. Criteria weights are computed using the extended statistical variance approach on the IVPULTS environment, and the popular VIKOR method is extended on IVPULTSs for the best hydrogen production methodology selection. Here, four hydrogen production methodologies are chosen viz., coal gasification, steam reformation of methane, biomass gasification, and water electrolysis to realize the developed framework's applicability. Biomass Gasification is considered a viable option in this study. Finally, the strengths and weaknesses of the introduced approach are discussed by comparing it with other approaches. [ABSTRACT FROM AUTHOR]

With growing hesitation in human perception, hesitant fuzzy set, an important extension of fuzzy set, has gained much attention from the research community. The concept of HFS gives decision makers the ability to provide multiple preferences for the same instance. However, the chance of these preferences occurring is assumed to be equal, which is unreasonable in practice. To circumvent this issue, probabilistic hesitant fuzzy set (PHFS) is adopted in this work, which is an extension of hesitant fuzzy set with associated probability values. Based on the literature review on PHFS, it is evident that (i) occurrence probability of each element was not methodically calculated; (ii) hesitation was not properly captured during criteria weight calculation; (iii) interrelationship among criteria was not captured during aggregation; and (iv) broad/rational ranking of alternatives with compromise solution was lacking. Motivated by these challenges and to alleviate the same, a systematic procedure is proposed in this paper to estimate these probabilities. Additionally, in this procedure, decision makers' preferences are aggregated using the newly proposed probabilistic hesitant fuzzy generalized Maclaurin symmetric mean operator and criteria weights are calculated using the proposed statistical variance method in the context of PHFS. A new ranking method is also proposed that extends a well-known VIKOR method to the PHFS context. Further, the practical use of the proposed decision framework is demonstrated by two examples viz., selecting a suitable coordinator for a research and development project and selection of a doctoral candidate for the supervisor position. Finally, the strength and weakness of the proposed decision framework are realized by comparing it with state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The single layers of TiN, TiAlN and TiN/TiAlN multilayer coatings were deposited on 316L SS bipolar plate by physical vapor deposition technique. The X-ray diffraction studies revealed that the formed coatings exhibited single-phase cubic structure. The low surface roughness and high contact angles of the TiAlN and TiN/TiAlN coatings governed the better water management in the fuel cell. Nyquist and Bode-impedance studies of TiN/TiAlN coating ensured higher electrochemical impedance behavior. The polarization results revealed that the current densities (icorr) of TiN/TiAlN coating were below 1 µA/cm2 in the PEMFC environments, which satisfied the U.S. Department of Energy's 2020 target. The contact resistance of the TiN/TiAlN-coated 316L SS was the lowest and fulfilled the requirements of bipolar plate (≤ 10 mΩ cm2) in PEMFC environment. Surface morphology results revealed that the surface of 316L SS is well protected by multilayer TiN/TiAlN coating. Inductive coupled plasma-optical emission spectroscopy results are in good agreement with electrochemical studies revealing the TiN/TiAlN coating significantly reduced the metal ions dissolution. [ABSTRACT FROM AUTHOR]

Introduction: Ultrasonography (USG) guided supraclavicular block is an excellent choice for upper limb surgeries. It not only allows smaller volumes of local anaesthetic usage but also provides optimal tourniquet coverage. Ropivacaine is structurally related to bupivacaine with reduced potential for toxicity and improved sensory and motor blocking profiles. Nalbuphine acquired a significant place in pain control but its efficacy as a local anaesthetic adjuvant is yet to be proved in peripheral nerve blockades. Aim: To evaluate the efficacy of adding nalbuphine to ropivacaine in supraclavicular brachial plexus blockade and to assess the quality of block for patients undergoing ambulatory forearm and hand surgeries. Materials and Methods: Seventy American Society of Anesthesiologists (ASA) grade 1 and 2 patients were randomised into two groups of 35 each. Group A (n=35): received 24 mL of 0.5% of ropivacaine + 1 mL of nalbuphine (10 mg) and Group B (n=35): received 24 mL of 0.5% of ropivacaine + 1 mL of normal saline. The parameters observed were duration of analgesia, onset of sensory and motor blockade, duration of motor blockade and haemodynamic changes during the procedure. Categorical variables were analysed using the Pearson's Chi-square test. Continuous variables were analysed using the independent sample t-test and p<0.05 was considered as statistically significant. Results: The onset of sensory and motor blockades were faster in the nalbuphine group compared to the control group (p<0.001). The duration of sensory and motor blockades was similarly longer in nalbuphine group (p<0.001). Also, the mean duration of analgesia was significantly longer with nalbuphine group (p<0.001). Conclusion: Nalbuphine significantly prolonged the duration of analgesia and duration of block while accelerating the onset of blockade thereby improving the overall quality of blockade. [ABSTRACT FROM AUTHOR]

This study focuses on the preparation of enzyme-activated zinc oxide nanomaterial using vermiwash via a simple soft chemical method. This vermiwash––an aqueous extract obtained from vermin reactor––is produced using earthworm, Eudrilus eugeniae, cow dung and leaf litter. The prepared nanoproduct was used to decompose toxic dye molecules through photocatalysis. The enzymes present in the vermiwash (like amylase, phosphatase, urease and protease) are found to be inherited by the prepared nanoproduct as well as the photocatalytically treated water. The quantitative study of enzymes shows that the quantity of enzymes present in the nanoproduct as well as in the photocatalytically treated water increases as the proportion of vermiwash used in the starting solution increases. This increase in the quantity of enzymes causes an increase in the photocatalytic efficiency of the nanoproduct. The photocatalytically treated water which consists of enzymes can be used as a potential candidate for effective irrigation. Thus, the vermiwash-activated ZnO nanopowder prepared in this study shows a two linear cascading applications. The results of the studies on enzymes, photocatalysis, XRD, SEM and FTIR are appropriately correlated with one another to address the enhancement in the photocatalytic activity of the prepared nanomaterials and the underlying mechanism. [ABSTRACT FROM AUTHOR]

With the proliferation in demand for navigation systems for reconnaissance, surveillance, and other day-to-day activities, the development of efficient and robust path planning algorithm is an open challenge. The uncertain and dynamic nature of the real-time scenario imposes a challenge for the autonomous systems to navigate in the environment, avoiding collision with the moving obstacles without compromising on the energy-time trade-off. Motivated by this challenge, an efficient gain-based dynamic green ant colony optimization (GDGACO) metaheuristic has been proposed in this paper. The energy consumption while path planning in a dynamic scenario will be humongous owing to its nature. The proposed algorithm reduces the total energy consumed during path planning through an efficient gain function-based pheromone enhancement mechanism. The memory efficiency of Octrees is incorporated for workspace representation because of its ability to map large 3D environments to limited memory. Comprehensive simulation experiments are conducted to demonstrate the efficacy of GDGACO. Results are analysed through comparison with other methods in terms of path length, computation time, and energy consumed. Also, the results are verified for statistical significance. [ABSTRACT FROM AUTHOR]

The intelligent healthcare management is of great concern to mobilize the enthusiasm of individuals and groups, and effectively use limited resources to achieve maximum health improvement by AI technology. When considering the intelligent healthcare management evaluation, the primary issues involve many uncertainties. Interval-valued fuzzy soft set, depicted by membership degree with interval form, is a more resultful means for capturing uncertainty. In this paper, the comparison issue in interval-valued fuzzy soft environment is disposed of by proposing novel score function. Later, some new properties for interval-valued fuzzy soft matrix are investigated in detail. Moreover, the objective weight is calculated by CRITIC (Criteria Importance Through Inter-criteria Correlation) method. Meanwhile, the combined weight is determined by reflecting both subjective weight and the objective weight. Then, interval-valued fuzzy soft decision-making algorithm-based CoCoSo (Combined Compromise Solution) is developed. Lastly, the validity of algorithm is expounded by the healthcare management industry evaluation issue, along with their sensitivity analysis. The main characteristics of the presented algorithm are: (1) without counterintuitive phenomena; (2) no division by zero problem; (3) have strong ability to distinguish alternatives. [ABSTRACT FROM AUTHOR]

BiSb nanoparticles were synthesized by solvothermal method. The synthesized material having a trigonal structure with space group R3m was confirmed through X-ray diffraction pattern. The Williamson-Hall method was employed to analyze the lattice stress and micro-strain produced in the BiSb nanoparticles. On the prepared material surface morphology studies were carried out using HR-SEM with EDXA. UV-visible absorption spectrum shows a wide absorption peak at 287 nm and the estimated band gap value is at Eg = 1.6 eV (from Tauc plot). The values of remanent polarization Pr = 0.156 μC/cm2, saturation polarization Ps = 0.253 μC/cm2, and coercive electric field Ec = 13.5 kV/cm obtained from the loop were close to the value. The BiSb nanoparticles exhibit semi-metallic-reported characteristics. This material is useful for thermoelectric power generation applications. [ABSTRACT FROM AUTHOR]

Group decision-making (GDM) is a complex process. The diversity, discrimination, and inevitable uncertainty due to human intervention characterize such problems that add to this complexity. To circumvent this challenge, there is an urge for an appropriate knowledge representation and decision-making approaches. The present paper is concerned with a prescriptive approach to GDM that can aid a group of decision-makers (DMs) to arrive at a decision. To this end, the recent concept of probabilistic linguistic term set is utilized. The discrimination among the alternatives, as in the real world, are mimicked using an integrated framework that adopts CRITIC and variance methods for attribute weight calculation, Gini index for calculating the weights of DMs, Maclaurin symmetric mean for aggregating preferences, and weighted distance-based approximation for prioritization of alternatives. A real-world problem on electric bike selection illustrates the usefulness of the proposed work. Finally, comparative analysis with extant methods demonstrates the technical results, and it is inferred that the proposed work is (i) highly consistent (from Spearman correlation) and (ii) produces broad rank values (from standard deviation) that could be efficiently discriminated for rational decision-making and backup management during critical situations. [ABSTRACT FROM AUTHOR]