Recent publications
Software development is based on explicit technical fundamentals and techniques. There are diverse phases executed to predict the defects in software, such as employing the data for input, pre-processing it, extracting the attributes, and classifying the defect. The given paper introduces an ensemble framework that comprises algorithms, namely Gaussian Naive Bayes (GNB), Bernoulli Naïve Bayes (BNB), Random Forest (RF), and Support Vector Machine (SVM), for predicting the software defects. This ensemble approach consists of Principal Component Analysis (PCA) or orthogonal linear transformation (OLT) with class balancing for feature selection. Python is executed for simulating the proposed model. In addition to this, the performance of the proposed work is validated and compared with existing recent studies based on evaluation metrics such as accuracy, precision and recall. The results show that the proposed framework outperforms the existing recent studies in terms of performance.
Code clones in software system are identical or similar pieces of code. The code is repeatedly generated by the copy and paste program. As a result, every duplicate contains a defect that was detected in one unit and the existing techniques are unable to achieve high accuracy for the code clone detection. In this research work, a hybrid deep learning model is proposed which comprises four phases namely pre-processing, feature set generation, feature set optimization and clone detection. We have utilized particle swarm optimization (PSO) and genetic algorithm (GA) for optimization along with convolutional neural network (CNN) and long short-term memory (LSTM) for clone detection. The proposed model is implemented in python and tested on several datasets in terms of accuracy (%), precision (%) and recall (%). In addition to this, the proposed model is compared with existing recent studies in terms of performance and the results show that the proposed hybrid model attains the highest accuracy (94.67%), highest precision (93.12%) and highest recall (93.13%) in case of big clone bench (BCB) dataset. Similarly, our model attains the highest accuracy (93.90%), highest precision (93.50%) and highest recall (93.52%) in case of Google code jam dataset while in case of Java dataset, accuracy, precision and recall are 93.78%, 92.67% and 92.66% respectively.
The present study reports the synthesis of Mangifera indica leaf extract mediated copper oxide nanoparticles (CuO NPs) via a biological method. CuO NPs are characterized for crystal structure and crystallite-size determination, absorption peak, particle size and morphological analysis, elemental composition, and functional groups’ identification using XRD, UV-visible spectroscopy, HRTEM, FESEM, EDX, and FTIR. CuO NPs show an absorption peak at a wavelength of 338 nm with a calculated band gap energy of 2.2 eV, using Tauc’s plot. XRD pattern depicts monoclinic phase ~18 nm average crystallite-size NPs. FESEM and HRTEM micrographs confirm the needle shaped CuO NPs with a 5:40 nm aspect ratio. The EDX spectrum, depicting the Cu and O peaks, shows that the particles are free from any type of impurity. FTIR analysis elucidates the role of bioactive chemicals in the extract in the successful formation of CuO NPs. The photoluminescence study reveals the existence of violet, green, orange, yellow and red emission bands. Additionally, CuO NPs exhibit an electrical conductivity of 1.37 × 10 ⁻⁷ Sm ⁻¹ and 5. 31 × 10 ⁻⁷ Sm ⁻¹ at 100 °C and 200 °C. Thus, environmentally friendly, non-toxic, green-synthesized CuO NPs hold significant potential for applications in resistive sensors, solar cells, and optoelectronics devices.
This study presents the fabrication and characterization of an Al(III) ion-selective electrode (ISE) using a novel BN@SnP composite. The composite, synthesized through a sol–gel process, integrates boron nitride (BN) nanoparticles into tin phosphate precipitates, exhibiting enhanced ion exchange capacity compared to individual inorganic counterparts. The resulting ion exchanger demonstrates selectivity towards Al (III) ions, forming the basis for constructing an ISE. The fabricated electrode exhibits a rapid response time of 10 s, a Nernstian slope of 22.05 mV decade−1, and a wide linear range spanning from 1.0 × 10⁻⁷ to 1.0 × 10−1 M. The electrode demonstrates a low limit of detection (LOD) of 7.5 × 10 −8M, highlighting its high sensitivity. The composite’s selectivity for Al (III) ions is confirmed through distribution coefficient studies, showcasing its preference over various metal ions. The chosen membrane for the electrode, M-3, exhibits optimal characteristics, including ideal thickness, high water content, and porosity. Comparative analysis with reported electrodes underscores the competitive performance of the proposed electrode. This research introduces a proficient ISE for Al (III) detection and sets the stage for future explorations in composite materials and their applications in biomedical monitoring, such as tracking aluminium levels in biological fluids for early diagnosis and management of neurological disorders, and environmental monitoring and analytical chemistry.
Citrus reticulata Blanco fruits experience significant fruit drop due to multiple environmental conditions that result in massive agricultural waste. The fruits can be used as source of bioactive components used as biofungicides in the agriculture sector which can replace synthetic fungicides having various side effects. The current study aimed to evaluate the antifungal efficacy of Citrus reticulata fruits dropped in the month of June against phytopathogenic fungi; Rhizoctonia solani and Drechslera oryzae causing sheath blight and brown spot disease in rice plants respectively. The methanol extract from the fruits was prepared by Soxhlet extraction followed by its fractionation using various polar and non-polar solvents. Among all the treatments, methanol extract exhibited maximum antifungal potential by in vitro studies against R. solani and D. oryzae with ED50 values as 510 and 580 µg/mL respectively. The methanol extract at 1500 µg/mL showed less disease incidence of sheath blight and brown spot disease than the untreated plants in rice cultivars (PR128 and PR124) respectively during kharif seasons (2021, 2022). The extract caused increase in cell components release in both fungi with shrunken and broken hyphae as revealed by SEM analysis. GC-MS analysis of extract showed the presence of 2-methoxy-4-vinylphenol, 3’,4’,5,6,7,8-Hexamethoxyflavone, 4’,5,6,7,8-Pentamethoxyflavone, quinic acid and 5-demethylnobiletin as major compounds and their molecular docking with cytochrome P450 14α-sterol demethylase (CYP51) revealed good docking scores (–6.9 to − 6.4 kcal mol–1). Hence, the dropped fruits can be used as botanical fungicides to control fungal diseases in rice as an effective strategy for biomass valorization.
Pesticides induce oxidative DNA damage and genotoxic effects such as DNA single-strand breaks (SSBs), double-strand breaks (DSBs), DNA adducts, chromosomal aberrations, and enhanced sister chromatid exchanges. Such DNA damage can be repaired by DNA repair mechanisms. In humans, single nucleotide polymorphisms (SNPs) are present in DNA repair genes involved in base excision repair (BER) ( OGG1 , XRCC1, and APE1), nucleotide excision repair (NER) ( XPC , XPD , XPF , XPG, and ERCC1 ), and double-strand break repair (DSBR) ( XRCC4 and RAD51 ). This systematic review intends to provide information about occupational pesticide exposure, genotoxic effects of pesticides as well as association of DNA repair gene polymorphisms with the risk of pesticide-induced DNA damage. Polymorphisms present in DNA repair genes may influence interindividual variation in DNA repair capacity (DRC) by altering the functional properties of DNA repair enzymes and thus modulate DNA damage. The mechanisms of oxidative damage and disrupted DNA repair caused by the pesticides explain the link between pesticide exposure and adverse health outcomes. These polymorphisms in DNA repair genes could be used as biomarkers of susceptibility for pesticide-induced DNA damage among agricultural workers. It could also be useful as a preventive measure by identifying the genetic susceptibility of agricultural workers to pesticide-induced oxidative stress as well as pesticide poisoning.
Significant participation on the stock exchange in India comes from Investors from other countries. Local institutional investors including mutual funds and corporate bodies also invest heavily in Indian stocks. Both FIIs and DIIs, the institutional investors nicknamed ‘elephants’ due to their significant financial strength. These key participants greatly influence how the stock market moves by the way they buy and sell. This research delves into the connection between large foreign, local players and gains in the stock markets over a 180-day timeframe. We analyze the potential impact of the recently introduced T+1 settlement phase on the Indian economy. The period between October 2022 and December 2022 represents the ‘pre-T+1’ phase, functioning under the previous T+2 settlement system. The timeframe following January 2023 marks the ‘T+1’ phase, reflecting the new settlement regulations. Data summarization, an enhanced Dickey-Fuller test, regression and correlation techniques could all be used in the study. According to the findings (considering a hypothetical scenario of T+1 settlement being implemented), the study would investigate whether the T+1 settlement phase has any significant effects on net purchase transactions undertaken by the large players. It would examine how sectoral indicators such as the Nifty 50 react to the introduction of T+1 settlement. The analysis would determine if the impact on the Nifty 50 Index Returns is significant and at what significance level. The study would assess how the T+1 settlement phase deepens its impact on sectoral indices except Nifty Public Sector Undertaking (PSU), Nifty Private Bank, and Nifty Reality (if the historical trends hold true). It would be interesting to see if the T+1 settlement disrupts any particular sector more than others. This research would help policymakers anticipate and mitigate the potential effects of the T+1 settlement phase on the market. By examining the impacts on different investor classes and sectoral indices, the study would provide valuable insights into how the market adjusts to this new settlement.
In simple words, cryptocurrencies are in the form of digital currencies that can be utilised to making purchase of goods and services just like fiat money can. However, from the beginning, it has largely caused controversy due to its decentralized nature. It functions without interference from any intermediaries like financial and banking institutions or the central government. The chapter comprises the cryptocurrency journey in India and its legal aspects. In India, the cryptocurrency journey has not been very long, but there have been many ups and downs in that short time. In 2013, the cryptocurrency trend began in India with the involvement of RBI and then the Supreme Court. It has come to the conclusion that banning of cryptocurrency is not a solution, but it should be regularized for the safety of investors. VDAs have received significant legal recognition in India, further legitimizing the sector. Anti-money laundering (AML) regulations have been expanded to encompass the fast growing virtual digital assets (VDAs) sector and enforcement actions under the current tax laws have been started. The coordinated global efforts of financial and regulatory agencies reflect the changing importance and recognition of the virtual and distributed economy. CERT (Indian Computer Emergency Response Team issued guidelines in relation to security practices, procedures, prevention and response, the VDAs income became taxable, instructions related to digital loans, and the Prevention of Money Laundering Act, 2002 was constituted by the NDA Govt. to prevent money laundering activities in the country. The chapter discusses these legal aspects concerning digital currencies in detail.
Biosurfactants are amphipathic, surface-active, nontoxic, and biodegradable compounds with wide applications in different industrial preparations. The present study was carried out to identify the biosurfactant-producing bacterial strains and surfactant production optimization with agro-industrial wastes. The potential biosurfactant-producing bacterial strain SS-1 was isolated from industrial effluent, and its surfactant-producing capabilities were determined via drop collapse assay, emulsification index, and reduction in surface tension. 16 S rRNA gene sequencing revealed 99% homology of isolate SS-1 with Alcaligenes sp. Agro-industrial wastes, namely, molasses, whey, and rapeseed cake, were optimized for biosurfactant production by the SS-1 strain, and maximum production was reported with molasses (4%). The present research has also documented an emulsification index of 93.26 ± 0.76% and surface tension reduction up to 35.26 ± 0.70 mN/m with an overall yield of biosurfactant approximately 2.38 g/L using 4% molasses at pH 7 and a temperature of 36 °C by Alcaligenes sp. FT-IR analysis revealed the presence of various functional groups, including O-H, N-H, C = O, C-H, and C-O-C, which suggest the lipopeptide nature of the biosurfactant. This was further validated by the distinctive resonance peaks observed in the NMR spectrum. The molecular mass of the biosurfactant was deduced to be 1382 Da via LC-MS. The partially purified biosurfactant was stable over a wide range of temperatures and pH values, with a maximum emulsification at pH 7 and a temperature of 30 °C.
This study investigates the synthesis and multifunctional applications of a cobalt-doped bismuth ferrite (Co@BFO) nanocomposite, emphasizing its efficacy in photocatalytic degradation of malachite green (MG) dye, antibacterial activity against foodborne pathogens, and antioxidant capacity. The Co@BFO nanocomposite was synthesized via a hydrothermal method, exhibiting a crystallite size of approximately 30 nm and a surface area of 16.2 m² g⁻¹. Under sunlight irradiation, the nanocomposite achieved a remarkable 97% degradation of MG dye at a concentration of 15 mg L⁻¹ within 120 minutes. The degradation kinetics followed a pseudo-first-order model with a rate constant of 0.0289 min⁻¹. The Co@BFO nanocomposite demonstrated significant antibacterial effects against Klebsiella pneumoniae and Bacillus cereus, achieving an MIC of 10 μg mL⁻¹. Additionally, it exhibited a DPPH radical scavenging activity ranging from 14.8% to 84.8% at concentrations between 2.5 to 15 mg L⁻¹, with an IC50 value of 11.13 mg L⁻¹. These results confirm that the Co@BFO nanocomposite not only effectively degrades organic pollutants, but also serves as a potent antimicrobial and antioxidant agent. This multifunctionality suggests its potential for diverse applications in environmental remediation and public health.
This study introduces CTAB-loaded Co₃O₄ nanoparticles (NPs) as a highly efficient solution for removing Brilliant Yellow (BY), Reactive Yellow (RY) and Methyl Orange (MO) dye from contaminated water. Synthesized via a co-precipitation and hydrothermal method, these NPs were characterized using UV-Vis, FTIR, XRD, TEM, and SEM. The Co₃O₄ NPs, with a crystallite size of 11.88 nm and an average particle size of 13 nm, achieved 100% photocatalytic degradation of BY dye (120 mg/L) within 140 min. Additionally, the NPs demonstrated promising photocatalytic activity against RY and MO dyes. The synergy between CTAB and Co₃O₄ NPs enhances dye degradation, positioning them as a cost-effective and efficient solution for wastewater treatment. This work highlights the environmental potential of CTAB/Co₃O₄ NPs in addressing water pollution challenges.
The authors of this paper (Jha et al. 2024) have tried to justify the uranium standards in drinking water (60 µg/L) of India adopted by the Atomic Energy Regulatory Board (AERB) based on radiological toxicity. All these authors belong to Bhabha Atomic Research Centre (BARC), Department of Atomic Energy (DAE), and they tried to justify the guidelines adopted by their sister organization under DAE with some ulterior motive. A careful reading of authors' paper reveals some contradictions which are so obvious, hence this rejoinder. In the abstract, authors state: "The detection of uranium in drinking water has ignited concerns among the public, regulators, and policymakers, particularly as around 1% of the 55,554 water samples in India have shown uranium levels surpassing the 60μg/L guideline established by the Atomic Energy Regulatory Board (AERB) based on radiological toxicity." But under section "Observations from nationwide survey ," the authors repeat a different story contradicting the abstract: "Out of 718 districts of the country, 403 districts in 23 States and 3 Union Territories are covered. Uranium and other water quality parameters have been measured in fifty-five thousand five hundred and fifty-four (55,554) sam-ples…..Uranium content in 98% of the samples was found to be less than 60 μg/L set by AERB, India. The pie-chart of the data is given in Fig. 6. From the figure, it can be observed that 93.9% and 97.8% of the data lie below the WHO guideline value of 30 μg/L and the AERB limit of 60 μg/L, respectively. It is observed that 2.2% of the samples had uranium concentrations > 60 μg/L in both pre-monsoon and post-monsoon seasons." My observation relates to this discrepancy in reporting the U content in water. Is it 1% or 2.2% above the AERB limit? The authors repeatedly point out to U content measured in 55,554 samples without giving reference to any source of their information. This is my second observation on the drawback of their paper. Our investigations based on U data generated under World Bank Project "Toward Managing Rural Drinking Water Quality in the State of Punjab, India" (World Bank 2020) reveal an entirely different scenario of U content in groundwater of Punjab. During 2009-2016, Punjab Water Supply and Sanitation Department (PWSSD) surveyed 7036 habitations (villages) in Punjab for various types of groundwater contaminants. Water samples were analyzed using state of art instrumentation (ICP-MS & IC-MS) in sophisticated laboratory of PWSSD in Mohali, near Chan-digarh. This laboratory is accredited by the National Board for Accreditation of Testing and Calibration Laboratories (NABL), India. U content was measured in 3608 water samples with a variation from 0.10 ppb (μg/L) to 2277 ppb (μg/L) and an average value of 31.38 ppb (μg/L), which is higher than the WHO limit of 30 ppb. Our investigations revealed that 1145 (31.7%) of water samples, analyzed in Punjab, contain U equal or higher than WHO limit (30 μg/L); and 786 (21.8 %) samples have U content equal or higher than AERB limit of 60 μg/L. In the case of Malwa belt districts, known as the cancer belt of Punjab, the U content values are higher than the AERB limit in almost 50% samples. However, the three Malwa districts of Barnala, Fazilka, and Moga record higher U content than AERB limit (60 μg/L) in 90%, 78.3%, and 61.4% samples, respectively (Virk 2017; 2019a, 2019b). Hence, the results of U content in water presented by the authors (1% above AERB limit) are highly doubtful and need to be rescrutinized. The authors have done an elaborate study of approaches to U content guideline values. In the section, "Global scenario on limit of uranium in drinking water," they refer to
This study investigated the effects of different treatments such as hot water blanching and potassium metabisulphite (KMS) treatment after blanching, along with various air-drying temperatures on pea processing waste. The drying process was conducted using a laboratory tray dryer at temperatures of 50 °C, 60 °C, and 70 °C, as well as their combinations, for various durations. The equilibrium moisture content decreased with increasing drying air temperature owing to higher moisture diffusivity. The Logarithmic model showed the best fit to the drying data, exhibiting R2 values ranging from 0.979 to 0.999. Chemical analysis of proximate composition, bioactive composition, chlorophyll content, and color (L*, a*, b*) was conducted to determine the optimal time-temperature combination. The results indicate that pea pods treated with KMS and dried at 60 °C for 5 h resulted in the highest retention of polyphenols (9%), ascorbic acid (20%), and chlorophyll content (17%) compared to blanched samples. Moreover, antioxidant content increased by 37–40% in pre-treated and dried pea pod powder relative to fresh pea pod. Additionally, pre-treatment process effectively preserved the color of pea pods, making it a desirable ingredient for various food products. This study contributes valuable insights into the optimization of pea processing waste utilization in the food industry.
The present study introduces Trigonella foenum-graecum (TFG, fenugreek)-mediated Co3O4 nanoparticles (NPs) as an innovative solution for eliminating industrial azo dyes from contaminated water. The novelty lies in their rapid, cost-effective synthesis and excellent photocatalytic and antimicrobial performance, which mark a significant advancement in environmental remediation. The NPs are synthesized using a co-precipitation method and characterized through advanced techniques. UV-visible absorption spectroscopy revealed two prominent direct bandgap transitions, surpassing previous reports and enhancing light absorption for efficient photocatalysis. FTIR analysis confirmed the successful incorporation of TFG phytochemicals, while XRD and SAED patterns indicated high crystallinity, a small crystallite size (1.6 nm), and ultrafine average particle size (5.5 nm) as observed by HRTEM. XPS analysis validated the synthesis with controlled oxidation states and defect sites featuring Co²⁺ and Co³⁺ ions. The optimized synthesis process led to outstanding photocatalytic performance, achieving 100% degradation of Congo red dye in just 60 minutes at a concentration of 120 mg L⁻¹. This efficiency underscores their capability to treat CR-contaminated water under specific conditions. The synergy between TFG phytochemicals and Co3O4 NPs demonstrates significant potential for water pollution remediation. Additionally, these NPs exhibit strong antimicrobial activity against Gram-negative and Gram-positive bacteria, highlighting their broader environmental significance and potential applications in various ecological fields.
Background
The rapid development of wireless communications and mobile computation has given rise to the novel Internet of Things (IoT) systems, which is causing considerable research attention and industrial development. However, the lack of synchronization between the timers of IoT devices compromises the network's security.
Aim
The purpose of this patent application is to present a technique for synchronizing the timepieces of IoT gadgets and establishing a secure channel for the transmission of data from source to destination.
Objective
This study proposes a Synchronization Selection Method (SSM) for IoT systems to enhance network security and reduce packet loss.
Methods
The method utilizes time-lay synchronization and RSA algorithm-based secure channel establishment. Time lay is a technique that was developed for IoT devices to achieve efficient clock synchronization of sensor nodes. Before synchronizing the sensor nodes' timings, the cluster leaders initiate the process. Utilizing a finite number of nodes, the proposed method was executed in MATLAB.
Results
Time-lay synchronization involves all network nodes synchronizing their clocks with a third-party clock. In the context of time-lay synchronization, the term “third-party clock” refers to a single specific point that contains the time signal that all nodes in the network use as a reference. This third-party clock is outside of the network nodes and acts as the standard for the precise and synchronized time within the network. Therefore, it can be deduced that each of the techniques possesses its advantages and disadvantages. Each of the synchronization techniques has the potential to significantly benefit the IoT by offering smart clock synchronization that is more secure. Experimental results demonstrate that the proposed method improves throughput and reduces packet loss compared to existing techniques.
Conclusion
The potential of this patent is highly significant for solving the synchronization problem of IoT devices and enhancing network security with decreased network packet loss.
Other
The SSM would be assessed using the parameters of packet loss and throughput.
In this investigation, the spatiotemporal distribution of cyanobacteria and their relationships with variations in water chemistry (physico-chemical parameters and heavy metal) of Sutlej River, Punjab (India) has been analyzed by employing multivariate statistical methods. Sutlej River exhibits a rich array of cyanobacterial diversity, comprising 28 species across 15 genera, distributed among 11 families and spanning 5 orders within the class Cyanophyceae. In terms of relative abundance, Microcystis aeruginosa (17.47%) was documented as the most abundant taxa followed by Microcystis robusta (16.55%), Merismopedia punctata (11.03%), Arthrospira fusiformis (6.67%) and Pseudanabaena galeata (3.68%). Significant variations were observed among sampling sites in most of the physico-chemical parameters. Principal Component Analysis delineated sampling sites into two discernible groups according to variations in water chemistry. River Pollution Index (RPI) showed that river water is under the unpolluted (RPI 1.5) to negligibly polluted category in the upstream sites, while moderately polluted (RPI 5.5) in the downstream sites. Heavy metal Pollution Index (HPI) revealed consistent heavy metal contamination at sites RWS7 and RWS8 across all seasons. Conversely, site RWS1 consistently exhibited lower HPI values throughout the three studied seasons. Further, Canonical Correspondence Analysis identified that pH, TDS, TA, NO3, Na, and NH4 are the key physicochemical parameters which affect the spatiotemporal distribution of cyanobacteria in the studied river system. Overall, this study will offer significant information for hydrologists, ecologists, and taxonomists to develop future holistic strategies for further monitoring of the Sutlej River and other similar habitats.
An effective therapeutic strategy to suppress Alzheimer's disease (AD) progression is to disrupt β‐sheet rich neurotoxic soluble amyloid‐β (Aβ) aggregates. Previously, we identified new pentapeptides (RVVPI and RIAPA) with notably enhanced ability to block Aβ42 aggregation as compared to Aβ42 C‐terminal derived peptide RIIGL using integrated computational protocol. In this work, the potential of RIIGL, RVVPI, and RIAPA for the structural destabilization of Aβ42 protofibril was assessed by molecular dynamics (MD) simulations and in vitro studies. The binding free energy analysis depicts that charged residues influence Aβ42 protofibril‐pentapeptide interactions. Notably, RVVPI displays a more pronounced destabilization effect than other peptides due to higher conformational fluctuations, and disruption of salt bridge (K28‐A42) interactions in Aβ42 protofibril. RVVPI exhibited highest inhibitory activity (Inhibition=66.2 %, IC50=5.57±0.83 μM) against Aβ42 aggregation consistent with computational results. Remarkably, RVVPI displayed ~4.5 fold lower IC50 value as compared to RIIGL. ThT and TEM studies highlighted the enhanced efficiency of RVVPI (62.4 %) in the disassembly of pre‐formed Aβ42 fibrils than RIIGL and RIAPA. The combined in silico and in vitro studies identified a new peptide, RVVPI, as an efficient inhibitor of Aβ42 fibrillation and disassembly of Aβ42 aggregates.
The construction of high-efficiency photocatalysts for photocatalytic disintegration of organic contaminants is a significant challenge. Herein, novel porous flower-like NiO/Mn3O4 heterojunction photocatalysts were successfully designed via a green synthesis route employing Tulsi leaf extract. The NiO/Mn3O4 heterojunction photocatalyst exhibited exceptional activity in the decomposition of thiamethoxam pesticide and crystal violet and rhodamine B dyes. The studied X-ray diffraction pattern established the existence of both NiO and Mn3O4 in the heterojunction photocatalyst. Field emission scanning electron microscopy micrographs substantiated the porous flower-like structure of the photocatalyst. Surface study demonstrated the surface area, micropore volume and mean pore diameter of the photocatalyst to be 119.93 m² g⁻¹, 0.1859 cm³ g⁻¹ and 3.78 nm, respectively, which are highly favourable for surface interactions. Photocatalytic experiments revealed that the heterojunction (NM-I) showed the highest photocatalytic efficiency for the degradation of thiamethoxam pesticide (93% in 90 min) and crystal violet (93.6% in 80 min) and rhodamine B (93.2% in 80 min) dyes with a rate constant of 0.0212, 0.0378 and 0.0355 min⁻¹, respectively. The performance of the NiO/Mn3O4 heterojunction was optimized by investigating the roles of certain variables, including pH, catalyst dosage, and scavengers, in degrading organic pollutants. Moreover, liquid chromatography–mass spectrometry was utilized to predict a tenable mechanism for thiamethoxam disintegration. In addition, the catalyst showed excellent stability and reusability, and was simple to extract from the solution. After five cycles, thiamethoxam, crystal violet and rhodamine B elimination efficiencies were 82%, 84%, and 87%, respectively.
Plant-mediated synthesis of nanoparticles (NPs) has emerged as an eco-friendly and cost-effective method, utilizing the reducing and capping properties of plant extracts for NPs fabrication. This review explores the influence of various plant parts such as leaves, seeds, roots, fruits, and flowers, on the morphology, size, and antibacterial activity of metal and metal-oxide NPs. Through comprehensive analysis of numerous studies, we elucidate how plant-derived carbohydrates and other phytochemicals impact the synthesis and characteristics of NPs. Nanoparticles synthesized with different parts of plants have successfully proved as antibacterial agents displaying significant zone of inhibition (ZOI). For instance, green tea leaf extract yields spherical silver NPs (15–33 nm) with potent antibacterial properties of ZOI of 11 mm and 10 mm toward S. aureus and K. pneumoniae, while Trigonella foenum-graecum seed extracts result in irregularly spherical zinc oxide (ZnO) NPs (70–90 nm) effective against bacterial strains. Moringa oleifera root extracts lead to the formation of hexagonal-shaped ZnO NPs (15–40 nm) with significant antibacterial activity with ZOI of 11.6 mm and 12.5 mm against B. subtilis and E. coli, and Myristica fragrans fruit extracts produce elliptical and spherical NPs (41.23 nm) effective against various bacterial strains such as E. coli (ZOI = 15 mm), S. aureus (ZOI = 21 mm), and K. pneumoniae (ZOI = 27 mm). Cassia auriculata flower extracts generate flake-structured NPs (41 nm) with potent antibacterial action against E. coli, S. aureus, K. pneumoniae, S. pneumoniae. This review highlights the innovative potential of plant-mediated nanoparticle synthesis and emphasizes the importance of selecting specific plant’s part by understanding the unique contributions of its phytochemicals to tailor NPs properties for diverse applications, particularly in the development of effective antibacterial formulations.
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