Effect of zinc and silica solubilizing bacteria and their consortia on paddy was studied under field conditions at Agricultural Research Station, Janagamaheswarapuram, Andhra Pradesh. Thirteen ...treatments were assessed for availability of nutrients viz., Nitrogen, Phosphorus, Potassium, Zinc and Silica in soil and concentration of Nitrogen, Phosphorus and Potassium in plant at 45, 90 and 120 days after sowing (DAS).Significantly highest nitrogen (198.9, 262.3 and 240.2 kg ha-1), available phosphorus (36.7, 64.7 and 40.6 kg ha-1), potassium (221.4, 349.6 and 263.5 kg ha-1), zinc (0.86, 1.14 and 0.98 ppm) and silica (66.8, 98.9 and 84.8 ppm) were recorded in T13 (RDF + ZnKJJ-4 & ZnPGG-1 + SiKPP-1 & SiPYY-3) at 45, 90 and 120DAS, respectively. In the plant, nitrogen (0.89, 1.10 and 0.98 %), phosphorus (0.46, 0.67 and 0.58 %) and potassium (1.87, 2.29 and 1.98 %) were significantly highest at 45, 90 and 120DAS, respectively, in T13. There was increase in the available nutrient content upto90 DAS which then decreased at 120DAS. It is inferred that consortia of two zinc solubilizing and two silica solubilizing microorganisms (T13) is useful for increased availability of Nitrogen, Phosphorus, Potassium, Zinc and Silica in soil and increased uptake of NPK by rice plant, which in turn reduce exogenous chemical fertilizers.
Metal-organic framework-derived materials are now considered potential next-generation electrode materials for supercapacitors. In this present investigation, Co
3
O
4
@MnO
2
nanosheets are ...synthesized using ZIF-67, which is used as a sacrificial template through a facile hydrothermal method. The unique vertically grown nanosheets provide an effective pathway for rapidly transporting electrons and ions. As a result, the ZIF-67 derived Co
3
O
4
@MnO
2
-3 electrode material shows a high specific capacitance of 768 C g
−1
at 1 A g
−1
current density with outstanding cycling stability (86% retention after 5000 cycles) and the porous structure of the material has a good BET surface area of 160.8 m
2
g
−1
. As a hybrid supercapacitor, Co
3
O
4
@MnO
2
-3//activated carbon exhibits a high specific capacitance (82.9 C g
−1
) and long cycle life (85.5% retention after 5000 cycles). Moreover, a high energy density of 60.17 W h kg
−1
and power density of 2674.37 W kg
−1
has been achieved. This attractive performance reveals that Co
3
O
4
@MnO
2
nanosheets could find potential applications as an electrode material for high-performance hybrid supercapacitors.
Metal-organic framework-derived materials are now considered potential next-generation electrode materials for supercapacitors.
By exchanging safety-related messages, the Internet of Vehicles (IoV) technology can reduce traffic collisions. With the help of the internet, vehicles can communicate and exchange information about ...location and speed with other cars and with roadside devices. False alarms, improper vehicle placement, and other forms of assault become commonplace in the automotive network. Message authentication is a difficult operation since it requires distinguishing between legitimate message packets and attack message packets. This study employs a deep learning method based on binary classification to distinguish benign from malicious data packets. Starting with the publidy available KDD99 and CICIDS 2018 datasets, the training dataset is constructed, including 1,20,223 network packets and 41 features. First, an autoencoder is used to weed out any extraneous information from the one-dimensional network data. After training the model using structured deep neural networks, the Softmax classifier, and the ReLU activation functions are included into the mix, leaving just the most relevant 23 characteristics. In order to train and evaluate the proposed Intrusion Prevention model, google Colab, an open platform cloud service, and the open-source tensor flow are used. In order to ensure the suggested preventive classifier model is accurate, it was tested on a dataset created by network simulation. The experimental findings demonstrate an accuracy of 99.57%, which is better than any other RNN- or CNN-based model currently available. To further enhance the model's efficacy and accuracy, it may be trained in the future on more datasets.
Considering the role of matrix metalloproteinase-3 (MMP-3) and tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) in the pathogenesis of periodontitis, the present study is to estimate the ...levels of MMP-3 and TIMP-1 in gingival crevicular fluid (GCF) in periodontal health, disease and to evaluate the effect of periodontal therapy on MMP-3 and TIMP-1 concentrations in GCF.
A periodontal examination and collection of GCF by extra-crevicular method was performed in 30 subjects selected randomly and categorized into 3 groups. Group I consists of 10 subjects Group II consists of 20 patients and Group III consists of 20 patients of Group II. Non surgical periodontal therapy was performed, and GCF was collected after 8 weeks from the same site of 20 chronic periodontitis patients who are considered as Group III. MMP- 3 and TIMP-1 levels were estimated in GCF-samples by using enzyme-linked immunosorbent assay. The findings were analyzed using the software and descriptive statistical methods such as Mann- Whitney U-test and Kruskal-Wallis test. P value < 0.001 was considered significant.
MMP-3 and TIMP-1 was detected in all samples. Highest mean MMP-3 concentrations in GCF were obtained for Group II (7.490 ng/ml) while the lowest concentrations were seen in Group I (0.344 ng/ml) and Group III (2.129 ng/ml). This suggests that MMP-3 levels in GCF increases proportionally with the progression of periodontal disease and decreases after treatment. Lowest mean TIMP-1 concentrations in GCF were obtained for Group-II (1.592 ng/ml), while the highest concentrations were seen in Group-I (8.78 ng/ml) and Group-III (6.40 ng/ml). This suggests that TIMP-1 levels in GCF decreases proportionally with progression of periodontal disease and increases after treatment.
There is a substantial increase in the concentrations of MMP-3 and decrease in TIMP-1 as periodontal disease progress. Since MMP-3 and TIMP-1 levels in GCF are positively correlated with gingival index, probing pocket depth, and clinical attachment loss, MMP-3, and TIMP-1 may be considered as a Novel Biomarkers in periodontal disease. However, controlled, longitudinal studies are needed to confirm this possibility.
Friction stir welding is a method used to weld together materials considered challenging by fusion welding. FSW is primarily a solid phase method that has been proven efficient due to its ability to ...manufacture low-cost, low-distortion welds. The quality of weld and stresses can be determined by calculating the amount of heat transferred. Recently, many researchers have developed algorithms to optimize manufacturing techniques. These machine learning techniques have been applied to FSW, which allows it to predict the defect before its occurrence. ML methods such as the adaptive neurofuzzy interference system, regression model, support vector machine, and artificial neural networks were studied to predict the error percentage for the friction stir welding technique. This article examines machine learning applications in FSW by utilizing an artificial neural network (ANN) to control fracture failure and a convolutional neural network (CNN) to detect faults. The ultimate tensile strength is predicted using a regression and classification model, a decision tree model, a support vector machine for defecting classification, and Gaussian process regression (UTS). Machine learning implementation mainly promotes uniformity in the process and precision and maximally averts human error and involvement.
Cloud computing offers service delivery models that facilitate users during development, execution and deployment of workflows. In this Big-data era, Organizations require value out of big data. For ...this they need not have to deploy complex infrastructure, but can use services that provide value. As such there is a need for a flexible and scalable service called Predictive Analytics as a Service (PAaaS). Predictive analytics can forecast trends, determines statistical probabilities and to act upon fraud and security threats for big data applications such as business trading, fraud detection, crime investigation, banking, insurance, enterprise security, government, healthcare, e-commerce, and telecommunications Prediction algorithms can be supervised or unsupervised with different configurations, and the optimal one may be different for each kind of data. This paper summarizes existing service frameworks for big data and proposes PAaaS framework that can be used by business to deal with prediction in big data. This proposed framework is based upon ensemble model that uses best out of prediction algorithms such as Artificial Neural Networks (ANN), Auto Regression algorithm (ARX) and Gaussian process (GP).
The bioassay-guided chemical examination of the rhizomes of
R. emodi resulted in the isolation of two new oxanthrone esters, revandchinone-1, revandchinone-2, a new anthraquinone ether ...revandchinone-3 and a new oxanthrone ether, revandchinone-4. Their structures were established based on spectroscopic and degradative evidence. Occurrence of oxanthrone ether is reported for the first time. The anti bacterial and anti fungal activity of the isolates is studied.
The bioassay-guided fractionation of the rhizomes of
Rheum emodi afforded two oxanthrone esters, revandchinone-1 (
1), revandchinone-2 (
2), an anthraquinone ether, revandchinone-3 (
3) and an oxanthrone ether, revandchinone-4 (
4). The anti bacterial and anti fungal properties of the new compounds were established.
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