The purpose of this study was to analyse the performance of competing teams in the Pro Kabaddi League and predict their chances of winning in the upcoming seasons. Pro Kabaddi League is a professional league played in India every year (except in 2020) since 2014. Kabaddi is a contact sport originated in India which is quite rigorous and tactical. Thus, there is a lot of scope for analytical research in this sport. This paper delivers a profound analysis of every team participating in the Pro Kabaddi League over the past seven seasons. To conduct this research all data and related statistics were gathered from the official website of the Pro Kabaddi League. The dataset is curated manually and contains more than 25 variables. This study develops a quantitative approach towards predefined tactics of attack and defence to expand our understanding of the strengths and weaknesses of each team. The analysis is expected to help alleviate the burden of the investors while also assisting them in choosing reasonable strategies for winning their matches. This paper leverages an ensemble of machine learning algorithms for forecasting the tournament result. The paper delivers multiple models to predict tournament winners. Logistic regression (LR), decision tree (DT), k-nearest neighbour (KNN), support vector machine kernel linear (svmKerLin) and kernel radial (svmKerRad) and neural network algorithms are included in this research. This will help in better prediction and more investments in the Pro Kabaddi tournament. Another purpose of this paper is to develop a model which helps in better prediction techniques, thereby serving as a stepping stone for deeper analysis in the future for similar problems. This research aims to find a correlation between pre-established hypotheses and the results achieved through decision-making algorithms to plot real-time winning predictions of the game.
This paper proposes a comparison of various time series forecasting models to forecast annual data on sugarcane production over 63 years from 1960 to 2022. In this research, the Mean Forecast Model, the Naive Model, the Simple Exponential Smoothing Model, Holt's model, and the Autoregressive Integrated Moving Average time series models have all been used to make effective and accurate predictions for sugarcane. Different scale‐dependent error forecasting techniques and residual analysis have been used to examine the forecasting accuracy of these time series models. Standard Error of Residuals, Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Akaike's Information Criterion (AIC) are used to analyze the forecast's accuracy. The best model has been selected based on the predictions with the lowest value, according to the three‐performance metrics of RMSE, MAE, and AIC. The estimated sugarcane production shows an increasing trend for the next 10 years and is projected to be 37763.38 million tonnes in the year 2032. Further, empirical results support the plan and execution of viable strategies to advance sugarcane production in India to fulfill the utilization need of the increasing population and further improve food security. This article is protected by copyright. All rights reserved.
Although India has a well-established and growing economy surrounding synthetic drug chemistry with an antibiotic base, a large part of the population, especially in forested villages and tribal belts, is relying solely on plant-derived drugs. This is due to a lower number of side effects, low chances of resistance development against pathogenic microorganisms, as well as the diversity and affordability of such drugs. In the Indian subcontinents, Euphorbia neriifolia Linn. (EN) is one of the valuable plants from the big family of Euphorbiaceae, which is usually found in rocky and hilly areas. E. neriifolia was found to be useful in curing tumors, abdominal swelling, bronchial infection, hydrophobia, earache, cough and cold, asthma, leprosy, gonorrhea, spleen enlargement, leucoderma, snake bites, scorpion stings, and causing appetite improvement, etc. Different in vitro and in vivo experimental studies were performed to determine the antioxidant, anti-diabetic, immunomodulatory, anti-inflammatory, anti-arthritic, wound healing, anti-atherosclerosis, radioprotective, anti-anxiety, anti-convulsant, anti-psychotic, anti-thrombotic, dermal irritation, hemolytic, analgesic, anti-fertility, diuretic, anti-microbial, anti-diarrheal, and anti-carcinogenic activities of the various parts of EN. Several bioactive compounds, such as euphol, nerifoliol, taraxerol, euphonerins A–G, lectin, etc., were isolated from E. neriifolia and need to be investigated further for various biological activities (cardiovascular and neuronal diseases). In the pharmaceutical sector, E. neriifolia was selected for the development of new drugs due to its broad pharmacological activities. Therefore, in the present review, distribution, classification, morphological and microscopical description, phytochemical investigation, pharmacological activities, medicinal uses, harmful effects, and their treatment were evaluated, especially against different lifestyle-related diseases.
Assuming the significance of sustainability, it is considered necessary to ensure the conservation of our natural resources, in addition to minimizing waste. To promote significant sustainable effects, factors including production, transportation, energy usage, product control management, etc., act as the chief supports of any modern supply chain model. The buyer performs the firsthand inspection and returns any defective items received from the customer to the vendor in a process that is known as first-level inspection. The vendor uses the policy of recovery product management to obtain greater profit. A concluding inspection is accomplished at the vendor’s end in order to distinguish the returned item as belonging to one of four specific categories, namely re-workable, reusable, recyclable, and disposable, a process that is known as second-level inspection. Then, it is observed that some defective items are suitable for a secondary market, while some are reusable, and some can be disassembled to shape new derived products, and leftovers can be scrapped at the disposal cost. This ensures that we can meet our target to promote a cleaner drive with a lower percentage of carbon emissions, reducing the adverse effects of landfills. The activity of both players in this model is presented briefly in the flowchart shown in the abstract. Thus, our aim of product restoration is to promote best practices while maintaining economic value, with the ultimate goal of removing the surrounding waste with minimum financial costs. In this regard, it is assumed that the demand rate is precise in nature. The learning effect and fuzzy environment are also considered in the present model. The proposed model studies the impacts of learning and carbon emissions on an integrated green supply chain model for defective items in fuzzy environment and shortage conditions. We optimized the integrated total fuzzy profit with respect to the order quantity and shortages. We described the vendor’s strategy and buyer’s strategy through flowcharts for the proposed integrated supply chain model, and here, in the flowchart, R-R-R stands for re-workable, reusable, and recyclable. The demand rate was treated as a triangular fuzzy number. In this paper, a numerical example, sensitivity analysis, limitations, future scope, and conclusion are presented for the validation of the proposed model.
Due to the rise in smartphone apps and increase in the usage of Android, there are a lot of security issues. Security issues need to be addressed in order to prevent vulnerabilities and identify them prior mishap. People who use smartphones are linked to a warning about the risks. Most people who use mobile phones do not have to think about a few negative possibilities when they install Android Package Kit (APK) files from different sources. It is important to have a system that can tell if the code in Android app is harmful. The first step in this work is to look at the Android APK datasets. Both good and bad APKs are analyzed, and the dataset is processed. The signatures that are hidden in the APKs are identified and extracted. This will make it easier to build a training dataset. Then, it is checked to see if each APK has the permissions it needs and how it affects the way it works. Once it’s been cleaned, a dataset is made so that the model can be trained to predict malware. To finish the predictive analytics, any APK outside of the APKs is chosen and used. That’s when it is possible to figure out how likely it is that the new APK will have corruptive code in it. Machine learning is used to track the results of different prediction measures, such as how long it takes, how accurate they are, and how much they cost. This article describes a machine learning technique to solve functional selection by safeguarding the selection and mutation operators of genetic algorithms. The proposed method is adaptable during population calculations in the training set. Furthermore, for various population sizes, it gives the best possible probability of resolving function selection difficulties during the training process. Furthermore, the work is combined with a better classifier in order to detect the different malware categories. The proposed approach is compared and validated with current techniques by using different datasets, wherein this approach shows elevated results in terms of accuracy.
Audio steganography is a technique which is used to transmit hidden data by intangibly altering a sound symbol. Audio information hiding is one of the best methods to secure the encrypted and compressed message. This paper deals with two stages. The first part gives the steps of embedding data into the carrier signal to position the data, and the next section gives the steps for retrieving the hidden data. After embedding the secret message, the modified speech file appears as the original carrier file and presents the stego files that retain their original size after evaluation of the proposed method. This scheme eliminates the host audio embedding distortion. This method helps to adjust the remaining bits to eliminate substantial discrepancies between the cover audio and the embedded audio. We evaluated the system using metrics such as peak signal-to-noise ratio and mean squared error.
Agriculture sustains the livelihoods of over 2.5 billion people worldwide. The growing nature of disasters, the systemic nature of risk, a more recent pandemic along with abiotic stress factors are endangering our entire food system. In these stressful environment, it is widely reprimanded that strategies should be encompassed to attain increased crop yield and economic returns which would alleviate food and nutritional scarcity in developing countries. To study the physiological responses to salt stress, Vigna radiata seedlings subjected to varying levels of salt stress (0, 25, 50, 100 and 200 mM NaCl) were evaluated by tracking changes in Chl a fluorescence, pigment content, free proline and carotenoids content by HPLC. The ability of plants to adapt to salt stress is related with the plasticity and resilience of photosynthesis. As salt concentration increased, chlorophyll fluorescence indices decreased and a reduction in the PSII linear electron transport rate was observed. Chlorophyll fluorescence parameters can be used for in vitro non-invasive monitoring of plants responses to salt stress. Overall, Vigna responded to salt stress by the changes in avoidance mechanism and protective systems. Chl fluorescence indices, enzymatic contents of POD, CAT and free proline were sensitive to salt stress. The study is significant to evaluate the tolerance mechanisms of plants to salt stress and may develop insights for breeding new salt-tolerant varieties.
L-Amino acid oxidase has significant values in different biotechnology sectors. In this study, Aspergillus terreus MZ769058 had been reported as new fungal isolate for production of this enzyme. It was partially purified using ammonium sulfate precipitation methodology with87.9 U/mg protein maximal specific activity and1.69 folds purification fold for 30–60% saturation. Ion-exchange chromatography was further applied for achieving high value of purification fold (2.55) and high specific activity as 132.5 U/mg.This purified enzyme showed homodimer nature with molecular weight of subunit as 90 kDa and 180 kDa by SDS electrophoresis and NATIVE PAGE respectively. The activity of enzyme was found as maximum 193.5 U/l at optimum value of pH 6.0.The enzyme was active throughout a wide range of temperatures and showed maximum activity (227.08U/l) at optimum temperature 30°C. The value of Michaelis parameters of K m and V max was estimated as 26 mM and 250 µmole/min/mg proteinsrespectively. The catalytic efficiency of this enzyme (K cat ) value was determined as 2.5 µmole/min/mg. Metal ions such as FeSO 4 (85.4 %), Na 2 MO 4 (81.2 %), and CuSO 4 had showed negative effect on the activity of LAAO enzyme. Metal ions like MgSO 4 , H 3 BO 3 , and ZnSO 4 had showed very little effect on activityof L-Amino acid oxidase. The activity of LAAO enzyme was strongly inhibited at a concentration of 10 mM CaCl 2 .This enzyme was strongly inhibited with α-napthol (34.4%), EDTA (34.2%), Glycine (39%) sodium azide (41.4%), and riboflavin (85.3%). Fourier transform infrared spectroscopyhad confirmed the presence of the amine and aldehyde groups with C-H stretch, C=O stretch, C-O stretch at peak of 2927.95, 1745.25, and 1078.64 cm ⁻¹ . This enzyme could be effectively used for effective therapeutic agent in pharmaceutical sector.
Cobalt based sulfides of compositional formula Co3A2S2 (A = Sn and In) are endowed with frustrated kagome lattice structure and a plethora of novel phenomena due to the topological band structure. We report on the detailed exploration of magnetic properties of single crystals of ferromagnetic Weyl semimetal Co3Sn2S2. A non-linear behaviour observed in the inverse susceptibility above the critical temperature TC in the paramagnetic state corroborates to the presence of short-range ferromagnetic clusters above TC in Co3Sn2S2. The upward deviation indicates the antiferromagnetic interactions between the nearest neighbouring magnetic clusters. The slow spin dynamics behaviour above TC in isothermal remanent magnetization provide another evidence of ferromagnetic clusters. The magnetic hysteresis loops represent the magnetization reversal which, in turn, also confirm the short range magnetic correlations. Further, non-linear isothermal magnetization curves and zero spontaneous magnetization derived from corresponding Arrott plots above TC prove the short range ferromagnetic clusters in Co3Sn2S2. Our experimental results emphasize an intuitive understanding of the complex nature of magnetism present in Co-based shandite systems.
The oxidation pond, also known as the stabilization pond, is a traditional method of wastewater treatment with a water purification mechanism in which microbial diversity plays a significant role in the degradation of organic pollutants in wastewater. The 16 S V3-V4 rRNA tool was used in this study to unveil the taxonomy of microflora present inside the oxidation pond, which aided in lowering the pollution level in domestic wastewater. The physicochemical parameters of water quality, which are important for its further reuse for irrigation, landscaping, or other purposes, have been analyzed alongside the microbial community. This system reduced nitrate and lead concentrations by 55.9 and 71.43%, respectively, with a treatment efficiency of 55.9 and 71.43%. COD, phosphorus, TDS, and BOD levels are also reduced by 41.18, 46.5, 23.4, and 47.44%, respectively. The metagenomic study found that bacteria dominated domestic wastewater, with archaea accounting for only 1% of the total. The bacterial diversity in the effluent was greater than in the influent. Mycobacterium was also found in higher concentrations in treated water, with immunotherapeutic properties against MDR-TB patients. Opitutus and Hydrodictyon reticulatum species contributed to nitrate and phosphate reduction in domestic wastewater, respectively. An antibiotic resistance genus Pedobacter was also discovered in domestic wastewater, and its abundance increased after treatment, posing a potential threat. The harmful pathogen Legionella pneumophila is abundant in oxidation pond-based treatment. Overall, the oxidation pond system was found remarkable approach for low-cost wastewater treatment for those areas where lands are easily available, and metagenomic study can be an attainable approach to monitor the microbial profile of treated and untreated water.
Correction for ‘Pd-Catalysed [3 + 2]-cycloaddition towards the generation of bioactive bis-heterocycles/identification of COX-2 inhibitors via in silico analysis’ by Elagandhula Sathish et al. , Org. Biomol. Chem. , 2022, 20 , 4746–4752, https://doi.org/10.1039/D2OB00467D.
Being sessile, plants’ exposure to various environmental stresses during their life cycle is inevitable which can affect their yield and productivity. This study investigates the protective effect of exogenous application of melatonin on 30-day-old tomato plants under NaCl and cadmium stress treatments. Plant growth, photosynthetic pigment, and antioxidant enzymes of plants exposed to NaCl, cadmium (Cd), and NaCl + Cd stress and melatonin treatment on them were analysed. The plants under NaCl- and Cd-induced stress produced an increased amount of ROS and lipid peroxidation, which were significantly reduced upon melatonin application. The maximum quantum energy (FV/FM) and performance index (PIABS) significantly improved in melatonin-treated plants under stress conditions. Redox homeostasis was maintained with a significant increase in superoxide dismutase, catalase, ascorbate peroxidase, and glutathione reductase. This study suggests that exogenous melatonin improves plants’ ability to overcome the combination stress caused by NaCl and Cd by increasing overall photosynthetic capacity and modulating redox balance.
A novel electrochemical cross-dehydrogenative C-S bond coupling of aryl thiols with 2H-indazole is reported. Thiol-functionalized 2H-indazoles were synthesized under catalyst-, oxidant-, and metal-free conditions with innocuous hydrogen as the sole byproduct at ambient temperature. Furthermore, continuous electrochemical flow conditions using a graphite/Ni flow cell were used to obtained 3-(arylthio)-2H-indazole compounds on a gram scale within the residence time of 39 min. Detailed mechanistic studies including control experiments and cyclic voltammetry are provided to support the radical-radical cross-coupling pathway.
India is one of the largest contributors to anthropogenic emissions during the recent decade associated with its rapid economic growth in India. Trace gases are important components in the climate change process and due to that climate change, there will be a change in their atmospheric concentrations as the climate is sensitive to Earth’s; therefore, proper assessment of trace gases is necessary for ongoing sudden changes in climate. In this study, we used remote-sensing datasets from the Atmospheric Infrared Sounder (AIRS) and Ozone Monitoring Instrument (OMI) to analyze the spatio-temporal variations of four trace gases, like methane (CH4), ozone (O3), carbon monoxide (CO), and nitrogen dioxide (NO2) over India region during 2006–2015 and taken four seasons (i.e., winter, spring, summer, and winter) to interpret the seasonal variation. The project focuses on the temporal pattern of pollutant trace gases i.e., monthly, seasonal, and annual mean variations of trace gases, trend analysis of trace gases, and a comparison of the seasonal behavior of the trace gases by trend analysis was assessed. Higher concentrations of CO show east-to-west, CH4 show north-to-south, and O3 south-to-north gradient, indicating the variations in trace gases due to the impact of emissions and local meteorology. On the other hand, due to immense population density, huge traffic emissions, tremendous, polluted air, and overgrown industrial activities, total NO2 concentrations shoot up over Delhi, Lucknow, and Kolkata. Now as a result of seasonal variation in the long-range transport of air parcels and biomass burning activities, all trace gases shown significant seasonal variations in the spring season and substantially reduced in the summer season. However, in the winter season, O3 concentration evaluates minimum due to less amount of heat on cold days which leads to the reduction of O3 formation. Due to trace gases, all are significant to get regional climate variability. In this study by taking 2006 as a base year and investigate the behaviors of gases for 2007–2015 years to exhibit the increment and decrements in four seasons of all trace gases by taking the most populated 11 different cities of India.
A new series of thieno nucleus embellished trinuclear (19, 20) and tetranuclear (21‐24) nitrogen heteroaryl have been synthesized by the Suzuki cross‐coupling reaction using bis‐(triphenylphosphine) palladium (ll) dichloride. All the synthesized compounds were characterized by IR, 1HNMR, 13CNMR and Mass spectral properties. In vitro antibacterial studies of the synthesized compound were conducted using broth microdilution assay employing gram‐positive and gram negative strains and half‐maximal inhibitory concentration (IC50) was determined. The result showed that compound 20 possess best antibacterial activity against S. aureus and E. coli with IC50 values of 60 μg mL–1 and 90 μg mL‐1. Further to determine the mode of antibacterial action, compounds 20 and 21 were examined for in vitro bacterial dehydrogenase inhibitory assay. To understand the binding affinity of the synthesized compounds, the docking study was performed in the bacterial dehydrogenase enzyme by AutoDock Vina software and structure was confirmed by Discovery Studio Visualizer. All the synthesized compounds were docked in a good manner within the active sites of the bacterial dehydrogenase enzyme and exhibited good binding energies.
We define an addition signed Cayley graph on a unitary addition Cayley graph Gn represented by Σn∧, and study several properties such as balancing, clusterability and sign compatibility of the addition signed Cayley graph Σn∧. We also study the characterization of canonical consistency of Σn∧, for some n.
Under ultrasound irradiation, 17 examples of 2-Amino-3-cyano-4H-chromene derivatives were prepared via one-pot three components domino Knoevenagel–Michael condensation reaction of aliphatic/aromatic/heterocyclic aldehydes, malononitrile, and α-naphthol/β–naphthol/resorcinol in the presence of Fe3O4‐supported sulfonated graphene oxide as a green and magnetically separable nanocatalyst in H2O: EtOH (1:1) solvent system. FT-IR, TGA, SEM, and XRD were used to evaluate the catalyst. The current protocol is appealing because of high atom economy (95%), excellent yields (88-95%), its short reaction time, waste-free conditions, cost-effectiveness, use of a nontoxic solvent, lack of high temperature for reflux, non-chromatographic purification of products, recyclability of catalyst, etc. In-silico studies were conducted on the selected proteins DNA gyrase (1KZN) and CYP51 (4WMZ) to study the docking interactions with highest docking scores 4h (−8.8 kcal/mol) and 4e (−10.1 kcal/mol), respectively. ADME and Toxicity analysis of docked compounds and reference drugs were also done. • Highlights • Room temperature and ultrasound assisted three-component synthesis • Synthesis of biological important 4H-chromene derivatives in H2O: EtOH (1:1) solvent • High yields of products (88–95%) within rapid reaction time (10–15 min). • High atom economy 95%. • Avoid of column chromatography • In-silico studies • Easy and fast work up • Magnetically separable and reusable catalyst.
Analyzing the multiple relevant documents returned in reply to an end-user request by an information retrieval system is challenging. It is very time-consuming and less efficient to find analogous web pages without applying the clustering. Clustering of web pages arranges a large number of web documents into relevant small clustered groups. In this paper, a novel similitude degree computation technique is proposed to provide the web documents related to the context in which multiple related web documents are the members of the same cluster. The clustering module results in web documents’ arrangement with their associated topic and corresponding computed similitude or similarity score. This provides the user clusters containing equivalent web documents related to the issue of desire. This context-based grouping of web documents reduces the time taken for searching relevant data and improves the results in response to a user request. Moreover, the comparison and analysis of the proposed technique are done with different existing similarity measures on the basis of performance metrics purity and entropy. It has shown the proposed scheme provides better results to the user.
The dichalcogenide ligated molecules in catalysis to produce molecular hydrogen through electroreduction of water are rarely explored. Here, a series of heterometallic [Ag4(S2PFc(OR)4] [where Fc = Fe(η5-C5H4)(η5-C5H5), R = Me, 1; Et, 2; nPr, 3; isoAmyl, 4] clusters were synthesized and characterized by IR, absorption spectroscopy, NMR (1H, 31P), and electrospray ionization mass spectrometry. The molecular structures of 1, 2, and 3 clusters were established by single-crystal X-ray crystallographic analysis. The structural elucidation shows that each triangular face of a tetrahedral silver(I) core is capped by a ferrocenyl dithiophosphonate ligand in a trimetallic triconnective (η3; μ2, μ1) pattern. A comparative electrocatalytic hydrogen evolution reaction of 1-5 (R = iPr, 5) was studied in order to demonstrate the potential of these clusters in water splitting activity. The experimental results reveal that catalytic performance decreases with increases in the length of the carbon chain and branching within the alkoxy (-OR) group of these clusters. Catalytic durability was found effective even after 8 h of a chronoamperometric stability test along with 1500 cycles of linear sweep voltammetry performance, and only 15 mV overpotential was increased at 5 mA/cm2 current density for cluster 1. A catalytic mechanism was proposed by applying density functional theory (DFT) on clusters 1 and 2 as a representative. Here, a μ1 coordinated S-site between Ag4 core and ligand was found a reaction center. The experimental results are also in good accordance with the DFT analysis.
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