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[Display omitted] The novel promising materials of the transition metal carbonitrides, especially MXenes, have been attracting great attention, due to the extraordinary electrochemical and optoelectronic properties of their inorganic 2D layers. However, the potential properties of single-layered MXene nanoflakes, which are crucial, remain unexplored. Restacking of exfoliated MXene nanoflakes, driven by the strong van der Waals interactions, diminishes the surface area, leading to the reduction of ion transport, which results in low charge storage capacity below the theoretical value of 615 C·g−1 or 1200 F·g−1. In addition, the MXene surface with the most electronegative −F functional groups hinders the ionic transport of electrolytes. The synergistic combination of intrinsically conducting polymers, such as PANI, and the two-dimensional transition metal carbides, MXenes, which can store higher energy, offers better volumetric and areal capacitance resulting in superior pseudocapacitance. Due to the high energy density, exfoliation of polyaniline restricts the restacking of MXene layers, thereby improving the electrochemical performance of the energy storage electrode materials. This review addresses the preparation, and characterization of the MXene-PANI nanohybrids, and their electrochemical behavior as energy storage materials for supercapacitor applications. [ABSTRACT FROM AUTHOR]

In the recent era, RFID-tags enabled hallmark transparency potential (RFID-TEHTP) attributes, in addition to the hallmark transparency values in jewellery supply chain responsiveness (JSCR). Tanishq Jewellery's manufacturing and marketing business are based on 4P strategies, namely product innovation strategy, price strategy, place strategy, and promotion planning strategy. ISM approach is use to develop inter-relationships among transparency potential attributes and MICMAC analysis provides the precise analysis relationship among the driving and dependence power linkages ability in JSCM. AHP approach is use to evaluate the weight priority of RFID-TEHTP performance criterion in JSCR. The ranking sequence orders of jewellery RFID-TEHTP performance criterion weights are the following: cost-effectiveness (CE) > break-even tag price decision (BETPD) > effective lead-time reduction (ELTR) > efficient customer response (ECR) > SC visibility, and trust and traceability (SCV&T). Jewellery managers can benefit from overcoming financial losses such as reduction of operation handling costs, misplacement error reduction, inventory inaccuracy problems, etc.

Copper-based binary and ternary sulfides have attracted significant attention due to their excellent photophysical properties, making them highly promising for high-performance photovoltaic devices. This study focuses on the synthesis and structural characterization of an air-stable binuclear Cu-pyrazinethiolate-phosphine complex, which serves as an efficient single-source molecular precursor for the preparation of CuS nanoplatelets. Furthermore, the utility of this complex as a versatile molecular precursor for the preparation of copper-based ternary sulfides, such as CuInS2, Cu2SnS3, and CuSbS2, has been demonstrated. A plausible mechanism for the facile formation of these ternary materials is proposed based on the presence of disulfide (S–S) linkages in CuS. The crystal structure, phase purity, and compositions of the nanoparticles were confirmed using powder X-ray diffraction (PXRD), X-ray photoelectron spectroscopy (XPS), energy-dispersive X-ray spectroscopy (EDS), and area elemental mapping. Electron microscopic studies revealed the formation of a two-dimensional (2D) nanoplatelet morphology with varied shapes and sizes. Ultraviolet–visible (UV–vis) diffuse reflectance spectroscopy showed a slight blue shift in the band gap of the nanoparticles compared to their bulk counterparts, which can be attributed to quantum confinement or surface lattice distortion effects. The band gap and the pristine nanoparticles were found to be blue-shifted compared to the bulk material. Prototype photoelectrochemical cells, fabricated using pristine nanoparticles, exhibit nice photocurrent generation along with optimum photoswitching, which poses them as suitable materials for clean-energy applications.

The increased requirements for high-efficiency and low-cost energy storage devices have paced research nowadays. The present study explores the applications of reduced Graphene Oxide (rGO) and Polyaniline (Pani) composites (rGO-Pani) for supercapacitor devices. These composites offer improved electrical conductivity and high specific capacitance. The composites have been characterized for their optical, magnetic, and specific capacitance properties. The energy band gap and Urbach’s energy for the composites is observed to be lower than the pristine Pani sample. Three photoluminescence peaks have been observed for pristine Pani whose intensity increases with increasing concentration of rGO in the composite. The CIE coordinates also indicate the higher color temperature of the composites. The original samples of rGO and Polyaniline do not possess any magnetic properties, but the composites show slight retentivity and coercivity. Cyclic voltammetry and Galvanostatic Charge-Discharge techniques performed at different scan rates reveal higher specific capacitance for Polyaniline samples than the composites that may be attributed to the presence of defects or impurities as they can introduce additional energy levels within the band structure. Deep-level defects may trap charge carriers, which leads to reduced charge transport efficiency and lower electrochemical performance.

Groundwater is considered to be the most reliable source of fresh water. Groundwater supplies are under grave danger due to a number of factors, including an increasing population, urbanization, and industry. Finding groundwater with reasonable precision is frequently a difficult task. In this work, the groundwater potential zones (GWPZs) in the Bundelkhand Craton region of India are mapped out with the help of analytical hierarchy processes (AHP) that are based on Geographic Information Systems (GIS) and remote sensing (RS) techniques. Various groundwater affecting elements has been generated with the remote sensing data in GIS environment. The AHP method was used to determine the weights that should be allocated to each affecting elements and their sub-features as well. In order to determine the GWPZs of the research region, each of these thematic layers was combined on top of the previous one after the appropriate weights were assigned. As a result, the GWPZs that were acquired were divided into five distinct classes, which were respectively designated as “very low”, “low”, “moderate”, “high”, and “very high” GWPZs. The findings of this study showed that "very high" GWPZ comprises 1.42% (380.55 km2), "high" GWPZ comprises 12.48% (3340.63 km2), "moderate" GWPZ comprises 67.83% (18152.1 km2), "low" GWPZ comprises 17.26 (4619.64 km2), and "very low" GWPZ comprises 1% (267.85 Km2) of the overall studied region. The result that was achieved is verified with the assistance of well discharge rate data. Overall, this research provides a technique to delineate groundwater potentiality, which will be very helpful for managing groundwater resources.

ABSTRACTIn most of the manufacturing industries, the selection of optimal material among the finite available alternatives becomes more difficult with the more required performance criteria to satisfy certain objectives. In such scenarios, Multi-Criteria-Decision-Making (MCDM) techniques, such as hybrid AHP (Analytical hierarchy process) – TOPSIS (Technique for Order Preferences by Similarity to Ideal Solution) and others assist in quantitative decision-making by accounting for qualitative human judgments. The present work illustrates the application of a hybrid AHP-TOPSIS technique to the ranking of alloy composites. The properties defining data such as physical, mechanical, thermal, thermo-mechanical, etc. are weighted using the AHP technique; thereafter, relative weights are used to rank the alloy composite compositions by the TOPSIS method. The compositions comprise the AA2024 alloy as the matrix phase and the reinforcing phase consists of silicon carbide, silicon nitride and graphite particulates. The ranking analysis orders are consistent with subjective analysis.

This paper presents the individual and the combined impact of melt thermal treatment and artificial aging treatment on microstructure and mechanical properties of A356 alloy. Samples modified with and without strontium (Sr)-based master alloy are also prepared for comparison purposes. The as-cast results for melt thermal treatment processed alloys displayed the refinement of α-Al grains coupled with a drop in eutectic silicon length. Further treatment results of artificial aging treatment alter eutectic silicon morphology into a spherical shape, and distribution of α-Al and eutectic silicon phase improves significantly compared to as-cast A356 alloys. The best eutectic silicon modification in terms of aspect ratio and roundness is obtained in the case of aged A356 alloy processed through melt thermal treatment along with Sr modifier. Because of this improvement in eutectic Si characteristics, the ultimate tensile strength, elongation, and hardness of the aged A356 alloy treated through melt thermal treatment along with Sr modifier increased by 9.6%, 24.4%, and 10.1%, respectively, compared to the aged untreated alloy. DSC results show that a maximum shift in eutectic peak temperature is observed in the melt thermal treatment along with Sr modifier A356 alloy.

The Thermo physical behaviour of soil is the fundamental behaviour and plays significant position in its “utilization” as “electrical and heat insulation”. However, numerous “researchers have studied” thermo-physical properties of soil. Still, the study on the relationship between soil's properties and its cooling effect through evaporation has not been investigated in detail. In this analysis, soil samples and earthen pots were collected from four states of India: Haryana, Delhi, Rajasthan, and Uttar Pradesh. The performance parameters used to evaluate the cooling effect of the soil, and earthen pot samples are “water-holding capacity”, porosity, “thermal-conductivity”, texture, and particle and bulk density. The application of “high temperature” fluctuate the “internal microstructure” of clay/soil and subsequently disturbs its “physical and thermal properties”. The sand/clay is converted into an earthen pot by applying high temperatures in kilns. The pot samples collected are heated in kilns to bring them to the final form for the study. We are studying the properties after that treatment. In this paper, the impact of “firing temperature” (maximum 900°C) on the “thermo-physical properties” of earthen pots made up of soil of a similar kind as the soil samples collected and the impact of thermo-physical properties on the cooling of the earthen pots has been examined via experiments. The results specify that the “thermal conductivity” of soil/clay samples is less compared to earthen pot. The “porosity and water-holding capacity” of the soil are greater than earthen pots because pore space or pore volume has decreased due to the heating effect. From the experimental analysis, it was found that the soil of the Sohna location in Haryana state has a high water cooling capacity due to its high water-holding (49.28%) capacity and porosity (48.75%). The pot made out of clay, having higher porosity, and water-holding capacity, gives the maximum cooling temperature.

The use of synthetic fibers as reinforcement has been restricted as a result of enhanced ecological awareness and stringent laws and regulations by government agencies. Consequently, engineers and researchers are now developing sustainable composites using natural fibers. The goal of this experimental study is to develop sustainable biocomposites with improved structural, static, dynamic, mechanical, and dielectric characteristics using cashew nut shell biomass-based polymer and Bambusa tuldafiber. Fiber from Bambusa tuldahas been extracted and subjected to various NaOH solution concentrations (2 to 10% with an interval of 2 (w/v)). The composite has been developed with 30% fiber loaded differently treated bamboo fiber and characterized by performing XRD, FTIR, tensile testing, DMA, and different dielectric tests. The result revealed that chemical treatment increased the crystallinity index of the biocomposites. The maximum crystallinity index has been observed as 51.73% with 6% NaOH-treated bamboo fiber reinforced biocomposites. The maximum tensile strength and storage modulus have been reported as 132.91 MPa and 8378 MPa, respectively for 6% NaOH-treated fiber reinforced biocomposites (BFC_30_T6). BFC_30_T6 exhibits higher properties because of the increased crystallinity index of fiber and better interfacial interaction between fiber and polymer matrix after the chemical treatment. Chemical treatment with more than 6% NaOH concentration reduces the dielectric constant, dielectric loss, and ac conductivity of the composites. Conversely, treatment with 8 and 10% NaOH concentrations results in a quick increase in dielectric and conductivity values.

The food supply chain (FSC) is becoming more sustainable as companies aim to meet demand with lower waste and emissions. Big data analytics (BDA) can help achieve sustainability goals by extracting meaningful information from past data to help create sustainable strategies. However, in the sustainability literature, BDA's role in enabling sustainable FSC innovations is not explored. Thus, this study investigates how data‐driven analytics might improve FSC innovation by adopting creative tactics in every triple bottom line (TBL) component – green, corporate social responsibility (CSR), and financial – to gain a competitive edge. A resource‐based view (RBV) perspective was used to evaluate the links between supply chain (SC) innovation capabilities and competitive advantage (CA) in FSC innovation and sustainability. Indian food processing enterprises were surveyed using a questionnaire to collect data from 200 respondents. Adopting a structural equation modelling (SEM) approach, six hypotheses were evaluated for significance on the surveyed data using AMOS V.20. Since both goodness and badness fit indices were above cut‐off values, the measurement model was robustly evaluated and found to fit the survey data well. Structural model findings supported all study hypotheses. The results indicate that BDA strongly impacts food supply chain TBL and FSC innovation. Data‐driven innovative TBL methods were shown to boost FSC competitiveness. With the growing demand for value‐added innovation in FSC sustainable development, this study uniquely contributes to the current literature by linking BDA and TBL practice innovation to FSC CA.

Diabetic retinopathy (DR) is a diabetic condition that affects vision, despite the great success of supervised learning and Conventional Neural Networks (CNNs), it’s still challenging to detect the severity of DR at an early stage. The label-intensive nature of supervised learning and the limited scalability of CNNs inhibit exploiting tons of unlabeled medical images that can be useful for capturing rich domain-specific features. The local feature representations from CNNs and their inability to scale well with increased unlabeled data lead to indiscriminative representations not effective for the downstream task. Hence in this work, vision transformer-based paradigm for diabetic retinopathy (DR) severity detection is presented by undertaking a scalable learning approach for model building. Self-supervised learning (SSL) framework with transformer architecture is used to classify fundus images to one of the DR categories by pre-training the model on tons of unlabeled fundus images followed by supervised training on different fractions of labeled data. The performance of the proposed transformer based self-supervised DR detection models (DINO[ViT]DINO[ViT], MAE[ViT]MAE[ViT], MSN[ViT]MSN[ViT]) is analysed at different data regimes. The experimental results showcase that SSL with vision transformer achieves higher performance when pre-trained on large corpus of unlabeled data. One of the proposed DR classifiers (MAE[ViT]) pre-trained using Masked Autoencoder framework on unlabeled fundus images achieves kappa score of 0.9027 when trained on full data regime and achieves a significant performance of 0.8341 on lower data regime (trained on 50 samples of EyePACS training data). The best-performing model MAE[ViT]MAE[ViT]is also inspected for model explainabilityexplainabilityto infuse trust in the model predictions.

We have been using the brain, and all the marvellous systems, cells and structures within it, as the basis of a community outreach project using art to engage children and young people in science. Through this, we aim to show that communication within our brains and bodies, between our own close networks of friends and families, and across disparate groups the world over, depends upon the same principles of connectivity, diversity and feedback. Ultimately, we will use the project as a springboard to engage more community organizations, hospitals and schools around the UK and beyond to add to our network of budding scientist-artists.

AbstractBackground:The rapid and resource-intensive nature of acute ischemic stroke (AIS) treatment demands ongoing optimization. Simulation modeling offers an effective approach for investigating these complex systems by simulating care processes in a virtual environment, enabling outcomes evaluation without direct patient engagement. Objective:This systematic review identified and analyzed studies utilizing simulation modeling to optimize AIS treatment. We assessed the models and identified areas for improvement to inform future development of AIS care services simulation models. Methodology:The review spanned from 2012 to 2022 incorporating searches on PubMed, Medline, Google Scholar, and conducting a backward citation search. Data extraction included hospital information, care settings, data sources, inputs, outputs, simulation type, model type, and simulation features. Results:The review included 27 studies with 81.5% utilizing discrete-event simulation models. The primary focus was on service design (77.8%), optimizing care components across various stages: acute, stroke unit, rehabilitation, and post-acute. Cost analysis models (14.8%) showed benefits of strategies like expanding comprehensive stroke centers, centralizing thrombolysis facilities, and assessing thrombolysis use. Capacity planning models (7.4%) demonstrated advantages in bed increases and resource pooling between acute and rehabilitation settings. Although most studies transparently reported essential model elements, almost half did not report stakeholder and expert engagement. Nonetheless, the majority provided validation and verification details, aiding real-world implementation. Conclusions: 27 studies have used simulation modeling to optimize the AIS treatment workflow; however future studies should consider stringent reporting of model elements, enhanced stakeholder and expert engagement, reusable model development, and effective integration of model findings into real-world healthcare systems.

AbstractThe breast cancer susceptibility gene 1/2 (BRCA1/2) are the key regulators in maintaining the genomic integrity and mutations in these genes have been associated with development of breast and ovarian cancers. Also, synthetic lethality has been shown in BRCA1/2 deficient cancers, when the RAD52 gene is silenced by shRNA or small molecules aptamers, suggesting a role for RAD52 in the breast cancers pathogenesis. Thus, to find the potential inhibitors of RAD52, a collection of 21,000 compounds from the ChemBridge screening library was screened to conduct molecular docking and molecular dynamics simulation (MD) against RAD52. Further, the results were validated by a density functional theory (DFT) analysis and using post-dynamics free energy calculations. Out of all screened molecules, the docking study revealed five compounds were found to have promising activities against RAD52. Moreover, the catalytic amino acid residues of RAD52 developed stable contacts with compound 8758 and 10593, as anticipated by DFT calculation, MD simulation, and post dynamics MM-GBSA energy calculation. It appears that compound 8758 is the best inhibitor against RAD52 followed by 10593 compared to the other top hits, in terms of the HOMO orbital energy (-1.0966 eV and −1.2136 eV) from DFT and the post dynamics binding free energy calculation (-54.71 and −52.43 Kcal/mol). Furthermore, a drug-like properties of lead molecules (8758 and 10593) were also seen viaADMET analysis. Based on our computational analysis, we hypothesize that a small molecule 8758 and 10593 possess the therapeutic potential in the management for breast cancer patients with a BRCA mutation viatargeting RAD52.Communicated by Ramaswamy H. Sarma

Background: Pure neuritic leprosy (PNL) is uncommon form of leprosy involving peripheral nerves. Some isolated case reports have shown imaging changes in the central nervous system (CNS) and also impairment in visual evoked potential (VEP), somatosensory evoked potential (SSEP) and brain stem auditory-evoked potentials (BAEPs) parameters in PNL, but there is lack of large study. This prospective observational study evaluates impairment in these central conduction studies among PNL patients. Methods: We screened patients with leprosy presenting with features of neuropathy and/or thickened nerves. Patients with bacilli-positive nerve biopsies were included in the study and subjected to routine tests along with nerve conduction study (NCS), VEP, tibial SSEP and BAEPs. Parameters of these studies were analyzed based on data from previous studies. Results: Of 76 patients screened for PNL 49 had positive findings in biopsy. Most of patients were male and mean age group was 46.35 ± 15.35 years. Mononeuritis multiplex was most common NCS pattern in 46.93% (23/49) patients. We found abnormal VEP in 13 out of 35 patients (37.14%). Similarly abnormal SSEP and BAEPs among 42.85% and 40% patients respectively. Discussion: This study shows that in PNL significant number of patients have subclinical CNS involvement. Exact pathophysiology of CNS involvement is not known till now but study of VEP, SSEP and BAEPs parameter may help in early diagnosis of PNL.

This paper is devoted to the study of symmetry group classification, and optimal subalgebras of the three-dimensional Burgers equation, which describes nonlinear wave motion exhibits nonlinear effects and enhanced dispersion in the context of nonlinear dynamics. The equation undergoes a Painlevé analysis to assess its integrability properties to verify the possibility that it passes the Painlevé test, followed by the derivation of nonclassical symmetries. Utilizing the invariance property of Lie groups, desirable infinitesimal symmetries of Lie algebra have been outlined for the equation. Relying on the invariance characteristic of adjoint transformation along with the newly generated similarity variables, an intensive and systematically organized approach is employed to achieve a one-dimensional optimal system. The entire set of group invariant solutions for each of the associated subalgebras has been established. The dynamical behavior of derived exact solutions is examined using numerical simulations, and numerous intriguing occurrences are discovered, such as flat sheet, periodic wave, doubly soliton, multisoliton, bright-dark soliton, breather soliton, line soliton type, which offer valuable insights into the dynamics of the system and can predict the behavior of waves in real-world scenarios.

Immediate drug-induced hypersensitivity reactions (IDHSRs) have conventionally been attributed to an immunoglobulin E (IgE)–mediated mechanism. Nevertheless, it has now been acknowledged that IDHSRs can also occur independently of IgE involvement. Non–IgE-mediated IDHSRs encompass the activation of effector cells, both mast cell–dependent and –independent and the initiation of inflammatory pathways through immunogenic and nonimmunogenic mechanisms. The IDHSRs involve inflammatory mediators beyond histamine, including the platelet-activating factor, which activates multiple cell types, including smooth muscle, endothelium, and MC, and evidence supports its importance in IgE-mediated reactions in humans. Clinically, distinguishing IgE from non-IgE mechanisms is crucial for future treatment strategies, including drug(s) restriction, readministration approaches, and pretreatment considerations. However, this presents significant challenges because certain drugs can trigger both mechanisms, and their presentations can appear similarly, ranging from mild to life-threatening symptoms. Thus, history alone is often inadequate for differentiation, and skin tests lack a standardized approach. Moreover, drug-specific IgE immunoassays have favorable specificity but low sensitivity, and the usefulness of the basophil activation test remains debatable. Lastly, no biomarker reliably differentiates between both mechanisms. Whereas non–IgE-mediated mechanisms likely predominate in IDHSRs, reclassifying most drug-related IDHSRs as non–IgE-mediated, with suggested prevention through dose administration adjustments, is premature and risky. Therefore, continued research and validated diagnostic tests are crucial to improving our capacity to distinguish between these mechanisms, ultimately enhancing patient care.

In this investigation, aluminum alloy (AA7075) composites reinforced with titanium (Ti) particulates (0–2.0 wt.% @ step of 0.5%) were designed and fabricated via a high vacuum casting route. The composite specimens are then analyzed for their physical, mechanical, thermogravimetric analysis, thermomechanical, and sliding wear behavior as per standards. The Taguchi orthogonal array was used for designing sliding wear trials, parametric optimization, and knowing the order of significance of parameters that control the output response of wear. This follows surface morphology studies to understand the prevalent wear mechanism responsible for surface damage. Finally, the entropy-VIKOR method was used to rank the composites as per their performance merits. The range of voids content is 2.39–1.68 %, tensile strength is 190–426 MPa, flexural strength is 452–299.8 MPa, impact strength is 13–77 J, and Vickers hardness is 171–193 HV. The order of material stability is ATI-0 < ATI-2 < ATI-1.5 > ATI-1.0 >ATI-0.5. The order of storage modulus is ATI-1.5 > ATI-1.0> ATI-0 > ATI-0.5 > ATI-2, while loss modulus is ATI-0.5 > ATI-2> ATI-1 > ATI-0 > ATI-1.5, and damping capacity is ATI-0 > ATI-0.5 > ATI-1.0 > ATI-1.5> ATI-2, respectively. The alloy composites having 2 wt.% Ti particulates shown to have overall optimized performance merits and confirmed with the results of hybrid ENTROPY-VIKOR.

The paper presents the performance enhancement of band-pass filter-based M-class phasor estimation. The performance of the M-class phasor estimation using a band-pass FIR filter is enhanced with a magnitude correction factor for the off-nominal frequency range. The band-pass filter is implemented for the phasor estimation with various window functions Tukey, Rife Vincent class-I order-2 (RV2), Hamming, Hanning, Blackman, and Flat-top (FT) and its performance are evaluated under the steady and dynamic state tests prescribed by the standard. A rigorous performance analysis of enhanced phasor estimation using band-pass FIR filter with various window functions is presented with the accuracy indices of total vector error (TVE), frequency error (FE), and rate of change of frequency error (RFE). The result analysis reveals that the performance enhanced phasor estimation using band-pass FIR filter offers significantly less error than reported work at the low sampling rate. The design and performance analysis of the phasor estimation using the band-pass FIR filter is performed in the MATLAB platform.

All-solid-state fluoride-ion batteries (FIBs) have been considered next-generation energy storage devices because of their high theoretical energy density. However, previously reported metal/metal fluoride active materials suffer from severe degradation due to large volume expansion; consequentially, fluoride-ion-intercalating active materials fail to deliver a high capacity. Here, oxyfluorosulfide Sr2F2Fe2OS2(SFFOS) with a layer structure is reported as a topotactic fluoride-ion (de)intercalation host. This material delivers a high reversible capacity of more than 340 mAh g–1, which remains well maintained after 20 cycles. The intercalation reaction mechanism for this high and stable capacity is elucidated via X-ray diffraction and fine structure analysis. Wherein both Fe2+/Fe3+redox and sulfide ion redox are involved in charge compensation during charge/discharge processes, where the sulfide ion redox contributes to the whole voltage range of −1.5 to 1.5 V and Fe2+/Fe3+redox only contributes from the middle state of charge. Fluoride ions can not only insert into the Sr–S interstitial sites but also combine with Fe cations. Meanwhile, excessive fluoride-ion intercalation leads to the formation of S–S bonds in the SFFOS lattice. These results highlight the oxyfluorosulfides with layer structure as a new class of active materials for constructing high-performance FIBs.

In this current research work, magnesium AZ61 (Advancing Side) and aluminum 6061-T6 (Retreating Side) alloys were joined using the zinc interlayer friction stir welding technique at the optimum process parameters. The aim of this work is to propose an effective alternative to overcome issues related to aluminum/magnesium joints. This article investigates the effects of zinc foil (0.2 mm) on the weld surface (3 mm aluminum/magnesium plates), intermetallic compound characteristics, microstructure, fracture surface and strength of joint. The emergence and nature of intermetallic compounds during aluminum/magnesium and aluminum/zinc/magnesium friction stir welded joints were studied in detail. As can be seen from the findings, using zinc in aluminum/magnesium friction stir welded joints inhibits the emergence of brittle aluminum–magnesium intermetallic compounds and promotes the formation of magnesium–zinc intermetallic compounds in the stir zone by introducing the zinc interlayer, confirmed through X-ray diffraction analysis. Furthermore, the average tensile performance (181.33 MPa) of friction stir welded aluminum/zinc/magnesium joints was enhanced up to 18.26 % compared to aluminum/magnesium friction stir welded joints (153.33 MPa). The promising results of this research establish an alternative route with a cost-effective technique to enhance the aluminum/magnesium dissimilar joint strength.

Objective: Out-of-hospital mortality rates surged during the early COVID-19 pandemic. While expecting a return to pre-pandemic levels, the evolving patterns of out-of-hospital mortality in Canada remain uncertain. We investigated whether these rates returned to pre-pandemic levels. Methods: This retrospective study, employing linked administrative data, analyzed out-of-hospital mortality trends among adult residents in Ontario, Alberta, and Nova Scotia. Interrupted time series analysis assessed trends in age- and sex-standardized rates/100,000/quarter during pre-pandemic (April 2014–March 2020) and pandemic periods (April 2020–March 2022), while considering April to June 2020 as the pandemic onset period. Crude mortality rates were also examined, stratified by sex and age groups. Results: Pre-pandemic, Ontario’s standardized out-of-hospital mortality rates were rising, while Alberta’s and Nova Scotia’s remained stable. At the pandemic onset, all provinces experienced significant increases in standardized out-of-hospital mortality rates/100,000 (Ontario: β14.6, 95% CI [3.97, 25.22]; Alberta: 21.3, 95% CI [9.26, 33.34]; Nova Scotia: 10.5, 95% CI [1.06, 19.88]). During the pandemic, standardized out-of-hospital mortality rates/100,000/quarter remained above pre-pandemic levels, with no significant departure from the increased pandemic onset levels (Ontario: − 1.6, 95% CI [− 3.63, 0.52]; Alberta: 0.45, 95% CI [− 1.47, 2.36]; Nova Scotia: − 0.06, 95% CI [− 2.18, 2.06]). Crude out-of-hospital mortality rates increased most prominently among individuals aged 18 to 45 in Alberta and Ontario, and among males across all provinces. Conclusion: The sustained increase in out-of-hospital mortality, observed from the pandemic’s onset, spanning more than 2 years, potentially suggests its persistent direct and indirect effects on population health in Canada.

The study empirically examines whether increased supply chain (SC) flexibility correlates with improvements in an SC's ability to address a firm's sustainability performance (SP). In addition, we investigate how SC visibility impacts a firm's SP by way of enhancing SC agility in the model. SC flexibility plays a vital role in SC operations to achieve sustainability. However, there is a limited understanding of the effects of SC flexibility on SP. The study explores the moderating roles of SC flexibility and environmental uncertainty in the connections between SC visibility, SC agility, and SP within the research framework. We use the partial least squares structural equation modeling technique to validate both the measurement and structural models. Besides, the mediation analysis, moderation analysis, and multigroup analysis are employed to test the various effects in the model. The results indicate the positive and significant relationships among SC visibility, SC agility, and the organization's SP in the model. The significant moderating effects of SC flexibility on the relationships among SC visibility, SC agility, and the organization's SP are identified in this study. Our findings show that increasing SC flexibility could potentially pose challenges. We argue that increasing SC flexibility cannot always help an organization's SP, furthermore, firms with high SC flexibility may perform worse than firms with low SC flexibility in terms of a firm's SP. The study provides valuable insight into sustainable SC management and contingency management post-COVID-19 pandemic, especially drawing attention to SC flexibility.

Silver nanoparticles are gaining more attention day by day because of its antimicrobial properties. This study aims at assessing the antifungal properties of green-synthesized silver nanoparticles against human and plant pathogenic fungi. The aqueous extract of Chenopodium albumleaves were used to prepare silver nanoparticles (Cha-AgNPs) via green chemistry method. The effective synthesis of these nanoparticles was confirmed by using various characterization techniques like Fourier transform infrared spectroscopy, X-ray diffraction, energy-dispersive X-ray spectroscopy, and selected area electron diffraction. High-resolution electron microscopy and field emission scanning electron microscopy revealed that the diameter of these nanoparticles was ranging from 5.8 ± 0.28 to 17 ± 0.19 nm. The antifungal activity of green-synthesized nanoparticle was observed at 400 µg/ml against Candida albicansand Candida tropicalisand at 800 µg/ml against Fusarium oxysporum. Till date, Chenopodium albumhas not been explored for these antifungal properties using silver nanoparticles. Hence, the current investigation paves a way for better natural treatment to common human and plant pathogenic fungal diseases.

Sm3+excited vanadate-based Ca9La(VO4)7nanocrystalline material produced by solution combustion (SC) emits strong orange-red light. Irregularly shaped nanoparticles with R3c (161) space group and trigonal symmetry with an average diameter of 51 nm were prepared. Under UV stimulation, the luminescence spectrum produces an orange-red signal at wavenumber 16447 cm−1due to the 4G5/2→ 6H7/2electronic transition. The results of energy transfer are also well thought out. Diffuse reflectance measurements investigate energy band gaps of the host matrix and optimal system and a lower value of the latter confirms the existence of a better luminescence after the incorporation of Sm3+ions. The maximum brightness was observed at 10.0 mol% Sm3+fraction. Concentration quenching effects were also observed. The finest CIE points (0.5868, 0.4027) are in the orange-red region with a CCT value of 1715 K, finally confirming the potential of present nanophosphors in modern illumination applications.