Green Noctiluca scintillans (NSG) is a mixotrophic dinoflagellate that frequently forms intense blooms in the north Indian Ocean, especially in the northeastern Arabian Sea during winter. This study investigates the conducive conditions and drivers associated with NSG blooms and proposes significant models for estimating NSG based on in situ (time-series) study during the bloom cycles. Two critical factors with regard to the blooms, i.e., phytoplankton abundance and sea surface temperature (SST), were examined. The first phase of heterotrophy dominance was when moderate blooms up to ~ 2.26 × 10 4 cells 1-1 occurred and, when NSG cells per unit chlorophyll-a (chl-a) increased, SST decreased up to ~ 24.5 ºC. The bloom intensity was proportional to the feed (diatoms/phytoplankton) availability and the degree of cooling (by the winter convection, i.e., nutrient enrichment). In the second phase of autotrophy dominance, intense blooms up to 1.9 × 10 5 cells l −1 occurred and NSG cells per unit chl-a fell, when the SST increased. During this period, bloom intensity was proportional to the degree of warming, i.e., nutrient and physiological stress. Phytoplankton are related to NSG by a single linear model through this SST cycle and is likely the NSG's essential biotic precursor. Attention is then focused on developing a remote sensing reflectance (R rs) model for efficient synoptic monitoring of NSG using ocean color satellites. The R rs band product ratio, a new metric, in combination with SST, notably modelled NSG abundance, which may be of potential routine application.
The increase in population has made it possible for better, more cost-effective vehicular services, which warrants good roadways. The sub-base that serves as a stress-transmitting media and distributes vehicle weight to resist shear and radial deformation is a critical component of the pavement structures. Developing novel techniques that can assess the sub-base soil's geotechnical characteristics and performance is an urgent need. Laterite soil abundantly available in the West Godavari area of India was employed for this research. Roads and highways construction takes a chunk of geotechnical investigation, particularly, California bearing ratio (CBR) of subgrade soils. Therefore, there is a need for intelligent tool to predict or analyze the CBR value without time-consuming and cumbersome laboratory tests. An integrated extreme learning machine-cooperation search optimizer (ELM-CSO) approach is used herein to predict the CBR values. The correlation coefficient is utilized as cost functions of the CSO to identify the optimal activation weights of the ELM. The statistical measures are separately considered, and best solutions are reported in this article. Comparisons are provided with the standard ELM to show the superiorities of the proposed integrated approach to predict the CBR values. Further, the impact of each input variable is studied separately, and reduced models are proposed with limited and inadequate input data without loss of prediction accuracy. When 70% training and 30% testing data are applied, the ELM-CSO outperforms the CSO with Pearson correlation coefficient (R), coefficient of determination (R 2), and root mean square error (RMSE) values of 0.98, 0.97, and 0.84, respectively. Therefore, based on the prediction findings, the newly built ELM-CSO can be considered an alternative method for predicting real-time engineering issues, including the lateritic soil properties.
The main aim of the study is to determine the effect of dissolving slag in water. Two mixing procedures were studied. Initially, a standard mixing procedure was adopted in which slag is mixed directly with the other concrete constituents. Secondly, a unique mixing process was adopted wherein slag is dissolved in water for a fixed period of time in prior to its addition with the other concrete constituents. The study was carried out using five percentages of slag—0%, 2.5%, 5%, 10%, 20%. Unique mixing process has shown a better performance as compared to the standard mixing method. Highest compressive strength of concrete was obtained at 2.5% slag replacement with 1 h immersion period. The optimum percentage of 2.5% slag replacement was fixed using unique mixing method and further substitution of cement was carried out using fly ash by adding directly. Fly ash percentages of 0%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% were used in the study. The final optimum mix which was obtained was compared with the control mix and the mix corresponding to the standard mixing mode of slag and fly ash. Unique mixing procedure has been studied to reduce the problem of carbonation which is due to increased slag content in concrete. Till date, standard mixing procedure has been adopted and is implemented in the field. The change in the mixing methodology was adopted to be beneficial in places where slag is available. Hence, the effect of unique mixing methodology has been studied on ternary blended concrete to reduce carbonation depth, carbon foot print and to maximize the mechanical strength of concrete with reduced slag content.
The studies were conducted for the release characteristics of matrix-based zinc sulphate-controlled release fertilizer (CRF). The parameters of the study were fractional fertilizer, fraction of binder, matrix particle size and pellet diameter. Results showed that the release period found to be more for higher fractional fertilizer, pellet diameter; smaller the matrix particle size, moderate amounts of binder release period increases. Based on Fick’s second law of diffusion, models were developed for predicting the mass transfer rates by diffusion methods. The experimental values were in good agreement with simulated data of the model. The data was studied in three regions-A, B and C regions. In region A, the dissolution rate is linear and for other regions, the rate can be expressed as equations of the developed models.
A facile, eco-friendly, and efficient approach for the multicomponent synthesis of 2-amino-pyran analogues (4a–j) is described that involves the reaction of substituted aldehydes, methyl cyanoacetate, and 1,3-cyclohexadione in a one-pot method using ruthenia-doped alumina (RuO2/Al2O3) as heterogeneous catalyst in a green solvent system. A simple wet-impregnation approach was used to prepare the catalyst material and was well-characterized using several analytical techniques like PXRD, TEM, SEM, SEM–EDX, and BET analysis. The key benefits of the current protocol are operational simplicity, economy, green reaction conditions, easy workup, short reaction time (10 min), higher product yields (94–98%), and no need for column chromatographic purification. The additional key advantage of this method is the recyclability and reusability of catalyst material up to eight runs through simple filtration without any significant loss of its catalytic activity.
Background: Polycystic ovarian syndrome (PCOS) is a neuroendocrine metabolic disorder characterized by an irregular menstrual cycle. Treatment for PCOS using synthetic drugs is effective. However, PCOS patients are attracted towards natural remedies due to the effective therapeutic outcomes with natural drugs and the limitations of allopathic medicines. In view of the significance of herbal remedies, herein, we discuss the role of different herbs in PCOS. Methods: By referring to the Scopus, PubMed, Google Scholar, Crossref and Hinari databases, a thorough literature search was conducted and data mining was performed pertaining to the effectiveness of herbal remedies against PCOS. Results: In this review, we discuss the significance of herbal remedies in the treatment of PCOS, and the chemical composition, mechanism of action and therapeutic application of selected herbal drugs against PCOS. Conclusions: The present review will be an excellent resource for researchers working on understanding the role of herbal medicine in PCOS.
The current work focuses on experimental studies using Mesua Ferrea biodiesel (BD20) and Cr2O3 nanoparticles in a diesel engine. In different concentrations, 60, 80, and 100 mg/L Cr2O3 nanoparticles were mixed. In addition, the dispersant (QPAN80) and surfactant (CTAB) were used to change the surface of the Cr2O3 nanoparticle (at a 1:1 ratio). The compression ratios were varied such as; 16.5:1, 17.5:1, and 18.5:1, respectively. Using a mechanical agitator and a probe sonicator, the nanofuel was produced by inserting the surface modified Cr2O3 nanoparticles into BD20. The combustion characteristics of nanoparticles added to BD20, such as cylinder pressure (CP) and net heat release rate (NHRR) have improved greatly over normal diesel. However, nanofuels improved performance in terms of brake specific fuel consumption (BSFC) and brake thermal efficiency (BTE). Together with NOx, the emission characteristics (CO, UHC, and smoke) were reduced momentously. Eventually, a good trend in performance, combustion, and emissions were seen as the compression ratio increased. The dispersant added nanoparticles in BD20 has shown good outcomes than the surfactant added nanoparticles and base nanoparticles. The BD20 + Cr2O3 80 mg/L + DSP 80 mg/L had the best results of all the test samples. At CR 18.5:1, the BTE, BSFC, CP, and NHRR were 34.52%, 0.342 kg/kWh, 65.52 bar, and 88.79 J/oCA, respectively, whereas CO, UHC, smoke opacity, and NOx were, 0.092%, 35 ppm, 20.26%, and 1249 ppm, respectively.
An efficient iodine-catalyzed cascade coupling protocol was developed for the synthesis of tetracyclic and pentacyclic pyrrolo[1,2-a] quinoxaline and indolo[1,2-a]quinoxaline derivatives via Iodine-mediated oxidative Pictet-Spengler reaction of 2-(1H-pyrrol-1-yl)aniline, 2-(1H-indol-1-yl)aniline with ninhydrin followed by spirocyclic ring-opening with alcohol/ water. The target compounds were obtained in good-to excellent yields with a broad substrate scope
A solution equilibria study of ternary systems containing Mn ²⁺ and Co ²⁺ with Azelaic acid dihydrazide (AZDH) as L and α-amino acids L - Proline and L - Lysine as X of type [M m L l X xH h ], was carried out with the help of potentiometric method for data acquisition followed by chemometric modelling studies, (where m = 1, 2; The SOPHD programme is used to generate relative simulation and titration curves. The speciation analysis and evaluation of formation constants (303K and 0.01M ionic strength) were computed with the MINIQUAD-75 computer software, and concentration distribution graphs were generated with the HySS programme. Various statistical parameters were considered to choose the best-fit chemical models. The ∆log K formulation was used to compare the stability of ternary compleyxes with binary complexes.
In this Paper the Flow-induced motion (FIM) and power conversion of triangular prism in cross-flow is numerically investigated using 2-Dimensional fluid domain with spring mounted oscillators and study the effects at wakes. Flow velocities between 0.05–0.15 m/sec, Reynolds number 2250–7500 and spring stiffness of 125 and 250 N/m are used for the simulation cases. The results show that in Vortex Induced Vibration (VIV) region the response of dynamic characteristics is high with a maximum amplitude and maximum power. The maximum amplitude of the oscillation, maximum co-efficient of lift force and displacement have been calculated mathematically for plotting a graph and theoretical and simulated efficiencies are compared for validation of the analysis.KeywordsDynamic characteristicsVortex Induced Vibration (VIV)Flow induced motion (FIM)Mounted oscillatorsNumerical analysis
Diabetic retinopathy (DR) is a diabetic ocular manifestation that leads to loss of visual impairment and blindness in people worldwide. Detecting and diagnosing the DR remains a major question in this task. This developed work uses a robust hybrid binocular Siamese with a deep learning approach to classify the DR image. Initially, a pre-processing stage is introduced to remove unwanted noises. To perform this cross guided bilateral filter (CGBF) approach is emphasized. After the pre-processing, the feature extraction stage is presented to extract the features from the processed image. A wavelet-based Chimp optimization algorithm (WBCOA) is established for the extraction of features. After feature extraction, segmentation of optical disc (OD) and blood vessel (BV) is done via open closed watershed management (OCWSM). For the classification, binocular Siamese based AlexNet and GoogleNet with the SVM model are proposed in this work. The segmented OD and BV are input to the proposed hybrid DL network. Finally, the extracted images are fused and classified using the Support Vector Machine (SVM) model. The proposed method is implemented in Python and tested on DIARETDB0 (DB0) and DIARETDB1 (DB1) datasets. The proposed hybrid DL network attained 94% and 94.83% accuracy on DB0 and DB1 datasets, respectively. Also, the proposed model’s outcomes are compared with various existing approaches. The proposed method conducted statistical analysis for the DR image based on mean and standard deviation (SD) to obtain an efficient output. These outcomes prove that the proposed hybrid DL system is accurate for early DR detection and deliver effective treatment of diabetes.
The levels of ten trace elements in the range Ca to As in the scalp hair of schizophrenics were analyzed using Particle Induced X-ray emission (PIXE) technique. Thirty males and females with a confirmed diagnosis of schizophrenia and an equal number of age-matched controls of both genders were chosen. The samples were excited with a proton beam of 2.5 MeV and spectra were scanned by a Si (Li) detector. The findings revealed a statistically significant difference in the concentration of six trace elements (Ca, Zn, Se, Mn, Fe, Ni, and Cu) in scalp hair of schizophrenia patients compared to controls, implying a disruption in the homeostasis of these elements. A plausible correlation of this imbalance with the etiology and pathology of schizophrenia is discussed.
We developed a novel one-pot strategy for synthesizing biologically important 1,2,4-triazole motifs from easily accessible 4-hydroxy phenylacetic acid, formamidine hydrochloride and hydrazine derivatives under mild conditions.
A series of degradation impurities of Flucloxacillin and Dicloxacillin were synthesised. The formation and a facile synthesis of each impurity were presented in detail, namely Penicilloic acids of Dicloxacillin (3) (Ph.Eur. Impurity‐A), Dicloxacillin glycine analog (4), Dicloxacillin Penilloic acids (5) (Ph.Eur. Impurity‐B), Dicloxacillin Pencillamide (6), N‐Acetylated penicilloic acid of Dicloxacillin (7), DCMICAA adduct of Dicloxacillin penicilloic acid (8), Flucloxacillin glycine analog (Ph.Eur. Impurity‐F) (9), Penicilloic acids of Flucloxacillin (10), Penilloic acids of Flucloxacillin (11), CFMICAA adduct of Flucloxacillin penicilloic acid (Flucloxacillin Ph.Eur. Impurity‐H) (12), Flucloxacillin Penicillamide (Flucloxacillin Ph.Eur. Impurity‐E) (13), and N‐Acetylated penicilloic acid of Flucloxacillin (14). These impurities are extensively characterized by various analytical techniques This article is protected by copyright. All rights reserved.
A strong magnet of Co0.5Cu0.5-xZnxFe2O4 (x = 0.0, 0.1, 0.2, 0.3, 0.4 and 0.5) was prepared by using the sol–gel auto-combustion technique. Using XRD, FESEM, HRTEM, FTIR, and VSM, the synthesized samples’ structural and functional group, and permeability, magnetic and DC electrical resistivity properties were studied. The structure was found to be cubic spinel. The average crystallite sizes were found to be 40–60 nm. With an increase in Zn2+ ion replacement, the lattice constant increases. Field effect scanning electron microscopy (FESEM) and HRTEM are both used to examine the surface morphology and crystalline nature. Two absorption bands around 600 and 400 cm−1 related to tetrahedral (A) and octahedral (B) interstitial sites by FTIR agree with the spinel lattice. All possible parameters are responsible for enhancing the magnetic quality identified and presented in this work. These are highly suitable for multi-layer ferrite chip inductor applications with a considerable enhancement in permeability. Magnetic properties have been explained on the basis of cation distribution. The sample’s hysteresis curves showed that the saturation magnetization and coercivity decreased after Zn2+ ions were replaced in the Co–Cu nanoferrites. The ferrite samples were semiconducting because the DC electrical resistivity decreased as temperature increased.
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