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Development of a fluorescent scaffold by utilizing quercetin template for selective detection of Hg2+: Experimental and theoretical studies along with live cell imaging
Quercetin is an important antioxidant with high bioactivity and it has been used as SARS-CoV-2 inhibitor significantly. Quercetin, one of the most abundant flavonoids in nature, has been in the spot of numerous experimental and theoretical studies in the past decade due to its great biological and medicinal importance. But there have been limited instances of employing quercetin and its derivatives as a fluorescent framework for specific detection of various cations and anions in the chemosensing field. Therefore, we have developed a novel chemosensor based on quercetin coupled benzyl ethers (QBE) for selective detection of Hg2+ with naked-eye colorimetric and turn-on fluorometric response. Initially QBE itself exhibited very weak fluorescence with low quantum yield (? = 0.009) due to operating photoinduced electron transfer (PET) and inhibition of excited state intramolecular proton transfer (ESIPT) as well as intramolecular charge transfer (ICT) within the molecule. But in presence of Hg2+, QBE showed a sharp increase in fluorescence intensity by 18-fold at wavelength 444 nm with high quantum yield (? = 0.159) for the chelation-enhanced fluorescence (CHEF) with coordination of Hg2+, which hampers PET within the molecule. The strong binding affinity of QBE towards Hg2+ has been proved by lower detection limit at 8.47 M and high binding constant value as 2 104 M?1. The binding mechanism has been verified by DFT study, Cyclic voltammograms and Jobs plot analysis. For the practical application, the binding selectivity of QBE with Hg2+ has been capitalized in physiological medium to detect intracellular Hg2+ levels in living plant tissue by using green gram seeds. Thus, employing QBE as a fluorescent chemosensor for the specific identification of Hg2+ will pave the way for a novel approach to simplifying the creation of various chemosensors based on quercetin backbone for the precise detection of various biologically significant analytes. 2024 Elsevier B.V. -
Concentration-dependent luminescence characterization of terbium-doped strontium aluminate nanophosphors
The present investigation describes the synthesis of luminescent terbium-doped strontium aluminate nanoparticles emitting bright green light, which were synthesized through a solid-state reaction method assisted by microwave radiation. Various samples containing different concentrations of Tb were synthesized, and an analysis of their structural and morphological features was conducted using powder x-ray diffraction, Fourier transform infrared spectroscopy and field emission scanning electron microscopy. The band gaps of the samples were determined utilizing the KubelkaMunk method. The quenching mechanism observed was identified to be due to dipoledipole interaction using the Dexter theory. The optimized sample with a terbium concentration of 4at.% has a luminescence lifetime of 1.05 ms with 20.62% quantum efficiency. The results of this study indicate that the terbium-doped strontium aluminate fluorescent nanoparticles exhibit promising potential for a wide range of applications, including bioimaging, sensing and solid-state lighting. 2024 John Wiley & Sons Ltd. -
Coloring of Non-zero Component Graphs
The non-zero component graph of a finite dimensional vector space V over a finite field F is the graph G(V?) = (V, E), where vertices of G(V?) are the non-zero vectors in V, two of which are adjacent if they share at least one basis vector with non-zero coefficient in their basic representation. In this paper, we study the various types of colorings of non-zero component graph. (2024), (Universidad Catolica del Norte). All rights reserved. -
Climate Change inflicted Environmental Degradation leading to the Crumbling of Arctic Ecosystem
The Arctic and Antarctic regions serve as the air conditioners of planet Earth. The polar regions located thousands of miles away from us determine the climatic patterns of our geographical area. They maintain our planet at bearable temperatures which are ideal for the existence of diverse flora and fauna and to support different types of ecosystems all around the world. Apart from controlling the temperatures, they also regulate ocean currents which in turn have an effect on the monsoons, winds, hurricanes etc. The poles were pristine till a few decades back. Due to mans greed, the poles started deteriorating at an alarming scale. Climate change, biodiversity changes, oil drilling, seismic testing, toxin accumulation are a few of the challenges faced by the Arctic ecosystem having serious effects on its topography, terrestrial and marine life-forms and the whole ecosystem. Due to the alarming scale of global warming, there is also the danger of permafrost meltdown which can unleash a plethora of dangerous pathogens buried underneath and also let out the huge amounts of locked down carbon. The crumbling of the polar ecosystem is leading to rampant consequences not only in the poles but also elsewhere in the world thousands of miles away. Here, we attempt to discuss the repercussions of the crumbling Arctic ecosystem due to the physical, chemical and geological changes caused by such anthropogenic activities and look at the efforts being carried out to save the Arctic ecosystem in a frantic effort to save our planet. 2024, World Researchers Associations. All rights reserved. -
Prediction and modeling of mechanical properties of concrete modified with ceramic waste using artificial neural network and regression model
Over two centuries, concrete has been crucial to building. Thus, eco-friendly concrete is being developed. Emulating these tangible traits has recently gained popularity. Ceramic waste concretes mechanical properties were modeled in this study. Ceramic waste percentages ranged from 5 to 20%. Compressive and tensile concrete strengths were modeled. To predict concrete hardness, regression modeling and artificial neural network (ANN) were used. Model performance was evaluated using prediction coefficients and root-mean-square error (RMSE). ANN models outperformed linear prediction with a coefficient for determination (R2) of 0.97. ANN models achieved root-mean-square errors (RMSEs) of 1.22MPa, 1.21MPa, and 1.022MPa after 7, 14, and 28days of retraining, respectively. Linear regression model showed RMSE values of 1.21, 1.32, and 1.27MPa at 7, 14, and 28days, respectively. In determining the compressive and tensile strength, the R2 was 0.70, meanwhile the ANN model achieved 0.87. Given its accuracy in predicting the strength qualities of ceramics cement and structural stiffness, the ANN model presents a promising tool for representing various types of concrete. The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024. -
White Light Emission from Dy3+-Activated CaY2O4 Phosphor
Synthesis and characterization of a Dy3+-activated calcium yttrium oxide (CaY2O4) phosphor are reported. The CaY2O4:Dy3+ (1.5 mol%) phosphor is synthesized using a modified solid-state reaction technique for calcination and sintering. The cubic structure is revealed by the X-ray diffraction technique. The morphology and particle size distribution of the prepared phosphor are investigated by the FEGSEM technique. The chemical bonds and functional group analysis are confirmed by the FTIR. A photoluminescence analysis of the CaY2O4:Dy3+ phosphor shows dual excitation wavelengths at 285 and 348 nm, especially in the ultraviolet region. At 383 nm, three distinct emission peaks are found at the wavelengths 238, 485, and 571 nm. The spectroscopic parameters are calculated using the CIE chromaticity coordinates. The CIE coordinates of the Dysprosium ion-activated CaY2O4 phosphor (1.5 mol%) show an emission near the white light region of the chromaticity diagram, suggesting that it is suitable for W-LED applications. The Author(s), under exclusive licence to Springer Nature Switzlerland AG 2024. -
An optimized method for mulberry silkworm, Bombyx mori (Bombycidae:Lepidoptera) sex classification using TLBPSGA-RFEXGBoost
Silkworm seed production is vital for silk farming, requiring precise breeding techniques to optimize yields. In silkworm seed production, precise sex classification is crucial for optimizing breeding and boosting silk yields. A non-destructive approach for sex classification addresses these challenges, offering an efficient alternative that enhances both yield and environmental responsibility. Southern India is a hub for mulberry silk and cocoon farming, with the high-yielding double-hybrid varieties FC1 (foundation cross 1) and FC2 (foundation cross 2) being popular. Traditional methods of silkworm pupae sex classification involve manual sorting by experts, necessitating the cutting of cocoons a practice with a high risk of damaging the cocoon and affecting yield. To address this issue, this study introduces an accelerated histogram of oriented gradients (HOG) feature extraction technique that is enhanced by block-level dimensionality reduction. This non-destructive method allows for efficient and accurate silkworm pupae classification. The modified HOG features are then fused with weight features and processed through a machine learning classification model that incorporates recursive feature elimination (RFE). Performance evaluation shows that an RFE-hybridized XGBoost model attained the highest classification accuracy, achieving 97.2% for FC1 and 97.1% for FC2. The model further optimized with a novel teaching learning-based population selection genetic algorithm (TLBPSGA) achieved a remarkable accuracy of 98.5% for FC1 and 98.2% for FC2. These findings have far-reaching implications for improving both the ecological sustainability and economic efficiency of silkworm seed production. 2024. Published by The Company of Biologists Ltd. -
SIDNet: A SQL Injection Detection Network for Enhancing Cybersecurity
SQL (Structured Query Language) injection is one of the most prevalent and dangerous forms of cyber-attacks, posing significant threats to database management systems and the overall security of web applications. By exploiting vulnerabilities in web applications, attackers can execute malicious SQL statements, potentially compromising the integrity and confidentiality of critical data. To combat these threats, in this study, we introduce two novel CNN models, SIDNet-1 (SQL Injection-attack Detection Network-1) and SIDNet-2 (SQL Injection-attack Detection Network-2), specifically designed for the classification of SQL injection attacks to bolster web application security. Our comprehensive evaluation includes a comparison of the performance of these customized CNN models against traditional machine learning approaches, highlighting improvements in classification accuracy and reductions in false alarm rates. The proposed models have been experimented with two publicly available dataset SQLI (SQL-Injection) and SQLV2 (SQL-Injection version2). Specifically, SIDNet-1 achieves an impressive accuracy of 98.02% on the SQLI dataset, while SIDNet-2 closely follows with 97.54%. Furthermore, on the SQLIV2 dataset, SIDNet-1 attains 97.77%, and SIDNet-2 achieves 97.83% accuracy respectively. 2013 IEEE. -
Towards sustainable resource management: A short and long-run dynamics of mineral production on ecological footprint
The effect of mineral production on ecological footprint is examined in this study while controlling for economic growth, renewable energy consumption, and trade openness as additional determinants for Pakistan. On the empirical front, the study uses the Dynamic Autoregressive Distributed Lag (DYNARDL) simulations for the data collected between 1990 and 2021. The result portrays movement to the long-run equilibrium relationship when considering the ecological footprint as the outcome variable amidst mineral production, economic growth, renewable energy consumption, and trade openness as the covariates. Further, the finding shows temporal dynamics of mineral production on environmental quality with a short-term degradation versus long-term amelioration, which suggests that mineral production can be conducted more sustainably over time with an implication towards taking measures such as technological advancements, improved efficiency, and better waste management practices. Additionally, it failed to find evidence for the conventional Environmental Kuznets Curve, implying a need for policy reevaluation, reassessment of economic development models and accounting for environmental externalities in economic decision-making. Besides, as expected, the outcome demonstrates that using renewable energy lowers the ecological footprint both in long and short terms, which indicates that utilization of renewable energy sources reduces reliance on fossil fuels, resulting in decreased environmental degradation, thereby fostering the need for emphasis on the importance of continued technological innovation in renewable energy technologies to reduce the ecological footprint further. Moreover, it shows that trade openness improves the environmental quality in the short run (worsens it in the long run), thereby highlighting that trade openness may lead to short-term environmental benefits by promoting cleaner technologies and increasing resource efficiency. However, in the long term, trade openness can exacerbate environmental degradation due to economic priorities often taking precedence over environmental concerns. 2024 Elsevier Ltd -
Bifunctional Amorphous Transition-Metal Phospho-Boride Electrocatalysts for Selective Alkaline Seawater Splitting at a Current Density of 2Acm?2
Hydrogen production by direct seawater electrolysis is an alternative technology to conventional freshwater electrolysis, mainly owing to the vast abundance of seawater reserves on earth. However, the lack of robust, active, and selective electrocatalysts that can withstand the harsh and corrosive saline conditions of seawater greatly hinders its industrial viability. Herein, a series of amorphous transition-metal phospho-borides, namely Co-P-B, Ni-P-B, and Fe-P-B are prepared by simple chemical reduction method and screened for overall alkaline seawater electrolysis. Co-P-B is found to be the best of the lot, requiring low overpotentials of ?270mV for hydrogen evolution reaction (HER), ?410mV for oxygen evolution reaction (OER), and an overall voltage of 2.50V to reach a current density of 2Acm?2 in highly alkaline natural seawater. Furthermore, the optimized electrocatalyst shows formidable stability after 10,000 cycles and 30h of chronoamperometric measurements in alkaline natural seawater without any chlorine evolution, even at higher current densities. A detailed understanding of not only HER and OER but also chlorine evolution reaction (ClER) on the Co-P-B surface is obtained by computational analysis, which also sheds light on the selectivity and stability of the catalyst at high current densities. 2024 The Authors. Small Methods published by Wiley-VCH GmbH. -
Facile construction of gefitinib-loaded zeolitic imidazolate framework nanocomposites for the treatment of different lung cancer cells
Gefitinib (GET) is a revolutionary targeted treatment inhibiting the epidermal growth factor receptor's tyrosine kinase action by competitively inhibiting the ATP binding site. In preclinical trials, several lung cancer cell lines and xenografts have demonstrated potential activity with GET. Response rates neared 25% in preclinical trials for non-small cell lung cancer. Here, we describe the one-pot synthesis of GET@ZIF-8 nanocomposites (NCs) in pure water, encapsulating zeolitic imidazolate framework 8 (ZIF-8). This method developed NCs with consistent morphology and a loading efficiency of 9%, resulting in a loading capacity of 20wt%. Cell proliferation assay assessed the anticancer effect of GET@ZIF-8 NCs on A549 and H1299 cells. The different biochemical staining (Calcein-AM and PI and 4?,6-Diamidino-2-phenylindole nuclear staining) assays assessed the cell death and morphological examination. Additionally, the mode of apoptosis was evaluated by mitochondrial membrane potential (??m) and reactive oxygen species. Therefore, the study concludes that GET@ZIF-8 NCs are pledged to treat lung cancer cells. 2024 International Union of Biochemistry and Molecular Biology, Inc. -
Acute Leukemia Subtype Recognition in Blood Smear Images with Machine Learning
Acute leukemia is a swiftly progressing blood cancer affecting white blood cells which poses a significant threat to the immune system and often leads to fatal outcomes if not detected and treated promptly. The current manual diagnostic method, being time-consuming and prone to errors, necessitates an urgent shift toward a comprehensive automated system. This paper presents an innovative approach to automatically identify acute leukemia cells and their subtypes by analyzing microscopic blood smear images. The proposed methodology involves the segmentation of clustered lymphocytes, isolation of nuclei, and extraction of diverse features from each nucleus. A random forest classifier is then trained to categorize nuclei into healthy or cancerous, with further precision in classifying cancerous nuclei into specific subtypes. The method achieves an impressive 97% accuracy across all evaluations, holding profound implications for pathologists and medical practitioners in their decision-making processes. 2024, J.J. Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology. All rights reserved. -
Predicting energy source diversification in emerging Asia: The role of global supply chain pressure
This study investigates energy diversification trends in six Emerging Asian countries from 1998 to 2021 while exploring the predicting effects of the global supply chain pressure, total investment, innovation, economic growth, and globalisation on energy diversification. This study considers the Kernel-Based Regularized Least Squares (KRLS) estimations and prediction models (Adam and Stochastic Gradient Descent optimisers). The impacts of global supply chain pressure and total investment on energy diversification are positive. Innovation also emerges as crucial factor to enhance energy diversification. Deeper integration into the global economy (globalisation) and economic growth strengthen energy diversification. The study underscores the importance of tailored policies, advocating for investments in innovation, targeted total investment, and inclusive growth strategies to address energy diversification in emerging Asian countries. 2024 Elsevier B.V. -
Photophysical and In Vitro-In Silico Studies on Newly Synthesized Ethyl 3-((3-Methyl-1-phenyl-1H-pyrazol-5-yl)oxy)-2-methyleneheptanoate
Abstract: In the present work, the aryl-substituted pyrazolone derivative ethyl 3-((3-methyl-1-phenyl-1H-pyrazol-5-yl)oxy)-2-methyleneheptanoate (ETT) has been synthesized by the reaction of Baylis-Hillman acetate with pyrazolones and screened for their in vitro antifungal, antibacterial, and antioxidant properties. The molecule shows good in vitro antifungal and antibacterial activities due to the presence of pentane, which enhances the absorption rate by its increased lipid solubility and improves the pharmacological activity. It is also evident from the results obtained from structure-activity relationship (SAR) studies. In silico studies were conducted on the synthesized molecule, examining its interactions with DNA Gyrase, Lanosterol14 alpha demethylase, and KEAP1-NRF2 proteins. The results revealed strong binding interactions at specific sites. Further, the photophysical properties of synthesized compounds were theoretically estimated using the ab-intio technique. The ground state optimization, dipole moment, and HOMOLUMO energy levels are calculated using the DFT-B3LYP-6-31G(d) basis set. Using the theoretically estimated HOMOLUMO value, global chemical reactivity descriptor parameters are estimated, and the result shows the synthesised molecule has a highly electronegative and electrophilic index. NBO analysis proved the presence of intermolecular ON.H hydrogen bonds caused by the interaction of the lone pair of oxygen with the anti-bonding orbital. The results suggest that pentane-substituted pyrazolone derivatives show good photophysical and biological applications. Pleiades Publishing, Ltd. 2024. -
Adsorptive capacity of PANI/Bi2O3 composite through isotherm and kinetics studies on alizarin red
Adsorption offers numerous advantages for eliminating organic pollutants such as dyes, making it a valuable method for water treatment. Polyaniline/Bi2O3 (PANI/Bi2O3) nanocomposite is synthesized from aniline by the chemical oxidative polymerization method. The sample shows a high positive surface charge density as seen from zeta potential analysis. X-ray Diffraction analysis, FTIR analysis, UVvis spectroscopy technique, thermogravimetric analysis, BET N2 Adsorption-desorption analysis, DLS, and zeta potential analysis are the tools employed to characterize the PANI/Bi2O3 nanocomposite. The impact of PANI/Bi2O3 on the outcome of adsorption is confirmed by comparing the composite with pristine Bi2O3 and PANI. The effect of various factors like time, temperature, initial dye concentration, and varying pH on the adsorption efficiency is studied. A maximum adsorption efficiency of 95 % is observed when 100 mg of PANI/Bi2O3 nanocomposite is utilized for a duration of 100 min. The adsorption efficiency increases at higher temperatures, and a maximum adsorption efficiency is observed at a pH of 11.4. The adsorption isotherms proposed by Freundlich and Langmuir are examined to confirm the adsorption mechanism, which entails the creation of a single layer of dye molecules on the adsorbent's surface. Analysis of kinetic parameters indicates that the reaction follows pseudo-second-order adsorption kinetics. The composite produced demonstrates effectiveness as an adsorbent for removing harmful organic pollutants from water sources. 2024 Elsevier B.V. -
PEDOT-Doped Mesoporous Nanocarbon Electrodes for High Capacitive Aqueous Symmetric Supercapacitors
Poly(3,4-ethylenedioxythiophene) (PEDOT) and PEDOT-functionalized carbon nanoparticles (f-CNPs) were synthesized by in situ chemical oxidative polymerization and pyrolysis methods. f-CNP-PEDOT nanocomposites were prepared by varying the concentration of PEDOT from 1 to 20% by weight (i.e., 1, 2.5, 5, 10, and 20 wt%). Several characterization techniques, such as field-emission scanning electron microscopy (FESEM), attenuated total reflectance-Fourier transform infrared (ATR-FTIR), X-ray diffraction (XRD), N2 BrunauerEmmettTeller (BET) and BarrettJoynerHalenda (BJH) analyses, as well as cyclic voltammetry (CV), galvanostatic charge discharge (GCD), and electrochemical impedance spectroscopy (EIS), were applied to investigate the morphology, the crystalline structure, the N2 adsorption/desorption capability, as well as the electrochemical properties of these new synthesized nanocomposite materials. FESEM analysis showed that these nanocomposites have defined porous structures, and BET surface area analysis showed that the standalone f-CNP exhibited the largest surface area of 801.6 m2/g, whereas the f-CNP-PEDOT with 20 wt% exhibited the smallest surface area of 116 m2/g. The BJH method showed that the nanocomposites were predominantly mesoporous. CV, GCD, and EIS measurements showed that f-CNP functionalized with 5 wt% PEDOT had a higher capacitive performance compared to the individual f-CNPs and PEDOT constituents, exhibiting an extraordinary specific capacitance of 258.7 F/g, at a current density of 0.25 A/g, due to the combined advantage of enhanced electrochemical activity induced by PEDOT doping, and highly developed porosity of f-CNPs. Symmetric aqueous supercapacitor devices were fabricated using the optimized f-CNP-PEDOT doped with 5 wt% of PEDOT as active material, exhibiting a high capacitance of 96.7 F/g at 1.4 V, holding practically their full charge, after 10,000 chargedischarge cycles at 2 A/g, thus providing the highest electrical electrodes performance. Hereafter, this work paves the way for the potential use of f-CNP-PEDOT nanocomposites in the development of high-energy-density supercapacitors. 2024 by the authors. -
Synergistic Effect of Chemical and Physical Treatments on Azolla pinnata for Cadmium Ions Removal from Synthetic Wastewater Systems
Azolla pinnata, an aquatic fern has been utilized as an effective biofiltering and ad-sorbent agent to complement many convention-al treatment methods for the removal of environmental pollutants. This study is designed to develop an effective regime to treat metal pollutants of industrial and urban waste discharge using a novel strategy involving Azolla pinnata. In the present study, cell surface modification by physical treatments that include heating (muffle furnace), and mechanical waves (ultrasonication) and chemical treatments as sulphuric acid and ethanol were employed to enhance the adsorption of metal pollutants. Factors such as biosorbent dose, contact time, initial metal ion concentration, temperature, and solution pH were optimised in batch mode. The point of zero charge of the adsorbent was determined to be at 5.85 pH. The results of surface morphology, elemental analysis, crystallinity, recorded through SEM, FTIR and XRD confirmed the ad-sorptive properties in both modified and unmod-ified biomass. The intensity peaks linked to O-H, C-H, C-N, N-H and C=O stretching bands was intense in the treated A. pinnata groups indicat-ing the induction of the active groups. Out of the two chemical pre-treatments, the batch ad-sorption experiment with ethanol found to che-late Cd+2 metal ions to a higher extent (94.36%) in contrast to the results obtained from H2SO4 treated biomass. Whereas, the physical treat-ments exhibited the strong adsorption (83.28 and 96.920.55%) for ultrasonicated and muf-fle furnace pre-treated biomass respectively for the dosage of 0.25g. The adsorption efficiency of physically modified sorbent revealed the cent percent removal of Cd+2 ions from the aqueous phase with the dosage of 1.0g in 15min of con-tact time which is due to the incorporation of new binding sites. Moreover, these results proved that the highest rate of cadmium adsorption onto A. pinnata is in result of the modifications caused onto surface structure, porosity and the addition of functional groups on the surface of the treated biomass. 2024, Curr. Trends Biotechnol. Pharm. All rights reserved. -
Classroom mathematics learning: Association of joy of learning and school connectedness among high school students in India
Mathematics learning experiences can influence the overall academic and socio-emotional development of a child. The present study investigates the mediating effect of mathematics anxiety and emotional engagement on the relationships between teacherstudent interaction, the joy of learning, and school connectedness. Two mediation models were tested for the dependent variables: the joy of learning and school connectedness, using Hayes' process macro in SPSS on a sample of 774 eighth-standard students from Indian schools. The study's results indicate the presence of a serial mediation effect on the relationship between teacherstudent interaction and joy of learning, teacherstudent interaction, and school connectedness through mathematics anxiety and emotional engagement. The study emphasized the role of mathematics learning within the overall framework of joy of learning and school connectedness.. 2024 Wiley Periodicals LLC. -
Effectiveness of museum visits: attitude and learning of history
This quasi-experimental study investigates the effectiveness of museum visit on 6th-grade students attitude towards and learning of history. The study engaged 120 students in the museum visit intervention. That includes, 60 students in the experimental group and 60 students in the control group. The study design included pre-test and post-test measures. The study administered an achievement test and an attitude scale toward history. The study analyzed the data using the repeated measures analysis of variance (ANOVA) statistical test. The studys result revealed that the experimental group outperformed the control group in achievement test scores of histories. The museum-visit group expressed a more positive attitude towards history learning and engagement. These findings underscore museums potential as experiential learning environment, offering knowledge and fostering a positive attitude towards history. The study recommends the future researchers to conduct similar empirical studies in science subjects as a venue for place-based pedagogy in the Indian context. 2024, Institute of Advanced Engineering and Science. All rights reserved. -
A Stochastic Method for Optimizing Portfolios Using a Combined Monte Carlo and Markowitz Model: Approach on Python
The main of the study is to comprehend how the mean variance efficient frontier method may be used in conjunction with Markowitz portfolio theory to produce an optimal portfolio. The study uses daily observations 8 pharma companies closing price namely Auropharma, Granules, Glaxo, Lauruslabs, Pfizer, Sanofi and Torntpharma. Further, Nifty pharma index is considered as benchmark index to check the performance of the chosen companies. The study chosen the reference period from 2020 to 2023 and required data has been extracted from the National Stock Exchange (NSE). This research is based on implementing a stochastic method for efficient portfolio optimisation employing a blended Monte Carlo and Markowitz model. In order to forecast the price of these indices in the future and to determine the likelihood of profit or loss while investing in a portfolio of stocks representing the aforementioned indices, the study also uses Monte Carlo simulation. The study involves two algorithms, namely the deterministic optimisation algorithm, which uses Markowitz Portfolio Theory, and the probabilistic optimisation algorithm, which uses Monte Carlo simulation. The study employed correlation matrix to find the exist relationship between the chosen companies and benchmark index. Also, expected return and volatility has been identified with the help of standard deviation using Python. The study found that the NIFTY Pharma index offers a higher return of 14.35. In addition to this, NIFTY Pharma portfolio's volatility is considerably higher. The study concludes that the NIFTY pharma portfolio is more suitable for those investors who have an appetite for risk. 2024 R. Mallieswari et al., published by Sciendo.