This study examines the behavior of a micropolar nanofluidflowing over a sheet in the presence of a transverse magneticfield and thermal effects.In addition,chemical(first-order homogeneous)reactions are taken into accoun...This study examines the behavior of a micropolar nanofluidflowing over a sheet in the presence of a transverse magneticfield and thermal effects.In addition,chemical(first-order homogeneous)reactions are taken into account.A similarity transformation is used to reduce the system of governing coupled non-linear partial differ-ential equations(PDEs),which account for the transport of mass,momentum,angular momentum,energy and species,to a set of non-linear ordinary differential equations(ODEs).The Runge-Kutta method along with shoot-ing method is used to solve them.The impact of several parameters is evaluated.It is shown that the micro-rota-tional velocity of thefluid rises with the micropolar factor.Moreover,the radiation parameter can have a remarkable influence on theflow and temperature profiles and on the angular momentum distribution.展开更多
Objective:To screen different analogues of mangiferin pharmacologically for antipyretic activity. Methods:The naturally occurring xanthone glycoside mangiferin was isolated by column chromatography from the elhanolic ...Objective:To screen different analogues of mangiferin pharmacologically for antipyretic activity. Methods:The naturally occurring xanthone glycoside mangiferin was isolated by column chromatography from the elhanolic extract of stem bark of Mangifera indica.Mangiferin was further converted to 5-(N-phenylamino methyleno) mangiferin.5-(N-p-chlorophenylamino methyleno) mangiferin,5-(N-2-methyl phenylamino methyleno) mangiferin.5-(N-p-methoxy phenylamino methyleno) mangiferin.5-(N,N-diphenylamino methyleno) mangiferin,5-(N-α-napthylamino methyleno) mangiferin and 5-(N-4-methyl phenylamino methyleno) mangiferin analogues.The synthesized compounds were further screened for antipyretic activity along with mangiferin at a dose level of 100 and 200 tng/kg.Mangiferin and its analogues were characterized by melting point and R_f value determination and through spectral technique like UV,IR,and NMR spectral analysis.Results:The antipyretic activity of mangiferin as well as all analogues was found to be more significant in at higher dose ie.200 mg/kg which was depicted thmugh a decrease in rectal temperature up to 3 h.Conclusions:The antipyretic activity of mangiferin and its analogues may be attributed to inhibition in synthesis of TNF-αand anti-oxidant activity associated with amelioration of inflammatory actions of cytokines.展开更多
Diabetes mellitus is referred as common metabolic abnormalities characterized as hyperglycemia,mainly caused due to insufficient production of insulin at cellular level or/and defects in insulin action.Such an endocri...Diabetes mellitus is referred as common metabolic abnormalities characterized as hyperglycemia,mainly caused due to insufficient production of insulin at cellular level or/and defects in insulin action.Such an endocrine disorder is responsible for serious health problems and its worldwide prevalence is rapidly increasing.Common management of diabetes by oral administration of drugs without creating any side effects is still considered a challenging task and increasing cost of con-ventional medicine in developing countries is another matter of concern.To address these issues,traditional preparations of herbal plant extracts in the form of medicines already gained immense attention.Swertia chirayita is one among such plants which is known for its hypoglycemic potential.Numerous chemical constituents with promising pharmacological properties have been identified from such plant extracts but still,such compounds have not been well characterized,specifically against human application.Hence,more research efforts are necessitated to understand exact mechanism of such compounds and to develop overall safety of such plant formulations.Present review clearly represents antidiabetic properties of Swertia chirayita extract,strategies to be taken to strengthen its safety application on humans and biotechnological interventions that ensure conservation of such endangered species to promote its future application in modern medicine.展开更多
The influence of reduction in emissions on the inherent temporal characteristics of PMand NOconcentration time series in six urban cities of India is assessed by computing the Hurst exponent using Detrended Fluctuatio...The influence of reduction in emissions on the inherent temporal characteristics of PMand NOconcentration time series in six urban cities of India is assessed by computing the Hurst exponent using Detrended Fluctuation Analysis(DFA) during the lockdown period(March 24–April 20, 2020) and the corresponding period during the previous two years(i.e., 2018 and 2019). The analysis suggests the anticipated impact of confinement on the PMand NOconcentration in urban cities, causing low concentrations. It is observed that the original PMand NOconcentration time series is persistent but filtering the time series by fitting the autoregressive process of order 1 on the actual time series and subtracting it changes the persistence property significantly. It indicates the presence of linear correlations in the PMand NOconcentrations. Hurst exponent of the PMand NOconcentration during the lockdown period and previous two years shows that the inherent temporal characteristics of the short-term air pollutant concentrations(APCs) time series do not change even after withholding the emissions. The meteorological variations also do not change over the three time periods. The finding helps in developing the prediction models for future policy decisions to improve urban air quality across cities.展开更多
The effect of different concentrations of benzaldehyde on the electrodeposition of Ni–W alloy coatings on a mild steel substrate from a citrate electrolyte was investigated in this study. The electrolytic alkaline ba...The effect of different concentrations of benzaldehyde on the electrodeposition of Ni–W alloy coatings on a mild steel substrate from a citrate electrolyte was investigated in this study. The electrolytic alkaline bath(p H 8.0) contained stoichiometric amounts of nickel sulfate, sodium tungstate, and trisodium citrate as precursors. The corrosion resistance of the Ni–W-alloy-coated specimens in 0.2 mol/L H2SO4 was studied using various electrochemical techniques. Tafel polarization studies reveal that the alloy coatings obtained from the bath containing 50 ppm benzaldehyde exhibit a protection efficiency of 95.33%. The corrosion rate also decreases by 21.5 times compared with that of the blank. A higher charge-transfer resistance of 1159.40 ?·cm2 and a lower double-layer capacitance of 29.4 μF·cm-2 further confirm the better corrosion resistance of the alloy coating. X-ray diffraction studies reveal that the deposits on the mild steel surface are consisted of nanocrystals. A lower surface roughness value(Rmax) of the deposits is confirmed by atomic force microscopy.展开更多
Diabetic Retinopathy(DR)is an eye disease that mainly affects people with diabetes.People affected by DR start losing their vision from an early stage even though the symptoms are identified only at the later stage.On...Diabetic Retinopathy(DR)is an eye disease that mainly affects people with diabetes.People affected by DR start losing their vision from an early stage even though the symptoms are identified only at the later stage.Once the vision is lost,it cannot be regained but can be prevented from causing any further damage.Early diagnosis of DR is required for preventing vision loss,for which a trained ophthalmologist is required.The clinical practice is time-consuming and is not much successful in identifying DR at early stages.Hence,Computer-Aided Diagnosis(CAD)system is a suitable alternative for screening and grading of DR for a larger population.This paper addresses the different stages in CAD system and the challenges in identifying and grading of DR by analyzing various recently evolved techniques.The performance metrics used to evaluate the Computer-Aided Diagnosis system for clinical practice is also discussed.展开更多
<div style="text-align:justify;"> In the fast-moving world, it is noticed that every industry is developing gradually, but recently it is identified that the use of AI has become the talk of own. There...<div style="text-align:justify;"> In the fast-moving world, it is noticed that every industry is developing gradually, but recently it is identified that the use of AI has become the talk of own. Therefore, this study is focused on gathering data regarding the AI on how it has transformed the entire world’s corporate sector. The essential application AI in the business world helps the business to perform better in the corporate sector. In this paper, the critical role of artificial intelligence is to grow business in different sectors and also address its ethical and unethical issues. The paper has all the initial background and comprehensive literature regarding AI and machine learning. It is discovered how the technological world has been striving to take their business on to new heights, which requires updated technological changes in internal business activities. Companies can now effortlessly interact with their customers in making their application accessible for the end-users through implementing AI and machine learning. Companies are getting higher profitability and enhancing their performance and achieving economic advantages by integrated AI. Moreover, their technological developments will take human jobs in the future, so, it is suggested that humans should work on their skills and competencies so that they can deal with unemployment. </div>展开更多
This study explored the concurrent scheduling of machines, tools, and tool transporter(TT) with alternative machines in a multi-machine flexible manufacturing system(FMS), taking into mind the tool transfer durations ...This study explored the concurrent scheduling of machines, tools, and tool transporter(TT) with alternative machines in a multi-machine flexible manufacturing system(FMS), taking into mind the tool transfer durations for minimization of the makespan(MSN). When tools are expensive, just a single copy of every tool kind is made available for use in the FMS system. Because the tools are housed in a central tool magazine(CTM), which then distributes and delivers them to many machines, because there is no longer a need to duplicate the tools in each machine, the associated costs are avoided. Choosing alternative machines for job operations(jb-ons), assigning tools to jb-ons, sequencing jb-ons on machines, and arranging allied trip activities, together with the TT’s loaded trip times and deadheading periods, are all challenges that must be overcome to achieve the goal of minimizing MSN. In addition to a mixed nonlinear integer programming(MNLIP) formulation for this simultaneous scheduling problem, this paper suggests a symbiotic organisms search algorithm(SOSA) for the problem’s solution. This algorithm relies on organisms’ symbiotic interaction strategies to keep living in an ecosystem. The findings demonstrate that SOSA is superior to the Jaya algorithm in providing solutions and that using alternative machines for operations helps bring down MSN.展开更多
Cd1-xZnxSe films with different zinc contents are deposited by an electron beam evaporation technique onto glass substrates for applications in solid-state photovoltalc devices. The structural, optical and photoelectr...Cd1-xZnxSe films with different zinc contents are deposited by an electron beam evaporation technique onto glass substrates for applications in solid-state photovoltalc devices. The structural, optical and photoelectrochemical （PEC） properties of Cd1-xZnxSe films are studied. The host material Cd1-xZnxSe is prepared by the physical vapor deposition method of electron beam evaporation technique （PVD： EBE） under a pressure of 1 × 10^-5 mbar. The x-ray diffractogram indicates that these alloy films are polycrystalline in nature, hexagonal structure with strong preferential orientation of the crystallites along （002） direction. The optical properties shows that the band gap Eg varies from 2.08 to 2.84eV as zinc content varies from 0.2 to 0.8. A PEC cell of the configuration n-Cd1-xZnxSe/Na2S-S-NaOH is fabricated and the dynamic current-voltage characteristics in the dark atmosphere have been examined at room temperature. It has been found that both Voc and Iac decrease with the photoelectrode composition x. Efficiency η and fill factor （FF） also show similar variations. The material properties would be altered and excellently controlled by controlling the system composition x.展开更多
In the modern world,women now have tremendous success in every field.They can play,learn,and earn as much as men.But what about safety?Do they have the same secure environment that men and boys do?The answer is“NO”....In the modern world,women now have tremendous success in every field.They can play,learn,and earn as much as men.But what about safety?Do they have the same secure environment that men and boys do?The answer is“NO”.Women and girls have been subjected to numerous incidents,including acid throwing,rape,kidnapping,and harassment.It is common to read a lot of news like this in newspapers every day.These incidents make women feel unsafe in this society.Our freedom came a long time ago,but women still lack complete security in this society.All women cannot fight or shout all the time when some danger is happening to them.What can the physically challenged person and Children do?To make women feel safe,we designed“Wrist Band”using IoT for women safety.As the sensors sense information from the body,it will always update the information such as pulse,temperature,and vibration to the well-wishers through the Blynk app.展开更多
Facial emotion recognition(FER)has become a focal point of research due to its widespread applications,ranging from human-computer interaction to affective computing.While traditional FER techniques have relied on han...Facial emotion recognition(FER)has become a focal point of research due to its widespread applications,ranging from human-computer interaction to affective computing.While traditional FER techniques have relied on handcrafted features and classification models trained on image or video datasets,recent strides in artificial intelligence and deep learning(DL)have ushered in more sophisticated approaches.The research aims to develop a FER system using a Faster Region Convolutional Neural Network(FRCNN)and design a specialized FRCNN architecture tailored for facial emotion recognition,leveraging its ability to capture spatial hierarchies within localized regions of facial features.The proposed work enhances the accuracy and efficiency of facial emotion recognition.The proposed work comprises twomajor key components:Inception V3-based feature extraction and FRCNN-based emotion categorization.Extensive experimentation on Kaggle datasets validates the effectiveness of the proposed strategy,showcasing the FRCNN approach’s resilience and accuracy in identifying and categorizing facial expressions.The model’s overall performance metrics are compelling,with an accuracy of 98.4%,precision of 97.2%,and recall of 96.31%.This work introduces a perceptive deep learning-based FER method,contributing to the evolving landscape of emotion recognition technologies.The high accuracy and resilience demonstrated by the FRCNN approach underscore its potential for real-world applications.This research advances the field of FER and presents a compelling case for the practicality and efficacy of deep learning models in automating the understanding of facial emotions.展开更多
Surface chokes are widely utilized equipment installed on wellheads to control hydrocarbon flow rates.Several correlations have been suggested to model the multiphase flow of oil and gas via surface chokes.However,sub...Surface chokes are widely utilized equipment installed on wellheads to control hydrocarbon flow rates.Several correlations have been suggested to model the multiphase flow of oil and gas via surface chokes.However,substantial errors have been reported in empirical fitting models and correlations to estimate hydrocarbon flow because of the reservoir's heterogeneity,anisotropism,variance in reservoir fluid characteristics at diverse subsurface depths,which introduces complexity in production data.Therefore,the estimation of daily oil and gas production rates is still challenging for the petroleum industry.Recently,hybrid data-driven techniques have been reported to be effective for estimation problems in various aspects of the petroleum domain.This paper investigates hybrid ensemble data-driven approaches to forecast multiphase flow rates through the surface choke(viz.stacked generalization and voting architectures),followed by an assessment of the impact of input production control variables.Otherwise,machine learning models are also trained and tested individually on the production data of hydrocarbon wells located in North Sea.Feature engineering has been properly applied to select the most suitable contributing control variables for daily production rate forecasting.This study provides a chronological explanation of the data analytics required for the interpretation of production data.The test results reveal the estimation performance of the stacked generalization architecture has outperformed other significant paradigms considered for production forecasting.展开更多
Rice stands as a crucial staple food globally,with its enduring sustainability hinging on the prompt detection of rice leaf diseases.Hence,efficiently detecting diseases when they have already occurred holds paramount...Rice stands as a crucial staple food globally,with its enduring sustainability hinging on the prompt detection of rice leaf diseases.Hence,efficiently detecting diseases when they have already occurred holds paramount importance for solving the cost of manual visual identification and chemical testing.In the recent past,the identification of leaf pathologies in crops predominantly relies on manual methods using specialized equipment,which proves to be time-consuming and inefficient.This study offers a remedy by harnessing Deep Learning(DL)and transfer learning techniques to accurately identify and classify rice leaf diseases.A comprehensive dataset comprising 5932 self-generated images of rice leaves was assembled along with the benchmark datasets,categorized into 9 classes irrespective of the extent of disease spread across the leaves.These classes encompass diverse states including healthy leaves,mild and severe blight,mild and severe tungro,mild and severe blast,as well as mild and severe brown spot.Following meticulous manual labelling and dataset segmentation,which was validated by horticulture experts,data augmentation strategies were implemented to amplify the number of images.The datasets were subjected to evaluation using the proposed tailored Convolutional Neural Networks models.Their performance are scrutinized in conjunction with alternative transfer learning approaches like VGG16,Xception,ResNet50,DenseNet121,Inception ResnetV2,and Inception V3.The effectiveness of the proposed custom VGG16 model was gauged by its capacity to generalize to unseen images,yielding an exceptional accuracy of 99.94%,surpassing the benchmarks set by existing state-of-the-art models.Further,the layer wise feature extraction is also visualized as the interpretable AI.展开更多
The hot deformation behaviour of 7075 aluminium alloy reinforced with 10%of SiC particles was studied by employing both"processing maps"and microstructural observations.The composite was characterized by emp...The hot deformation behaviour of 7075 aluminium alloy reinforced with 10%of SiC particles was studied by employing both"processing maps"and microstructural observations.The composite was characterized by employing optical microscope to evaluate the microstructural transformations and instability phenomena.The material investigated was deformed by compression in the temperature and strain rate ranges of 300-500℃and 0.001-1.0 s-1,respectively.The deformation efficiency was calculated by strain rate sensitivity(m)values obtained by hot compression tests.The power dissipation efficiency and instability parameters were evaluated and processing maps were constructed for strain of 0.5.The optimum domains and instability zone were obtained for the composites.The optimum processing conditions are obtained in the strain rate range of 0.1-0.9 s-1and temperature range of 390-440 ℃with the efficiency of 30%.展开更多
The hot deformation behavior of as-cast ZE41A magnesium alloy was studied by employing both processing maps and microstructural observations. To obtain processing map, hot compression tests were performed over a range...The hot deformation behavior of as-cast ZE41A magnesium alloy was studied by employing both processing maps and microstructural observations. To obtain processing map, hot compression tests were performed over a range of strain rates (0.001-1.0 s-1) and temperatures (250-450 ℃). Power dissipation efficiency (η) and instability parameter [ξ (ε)] were evaluated and processing maps were developed for the strain of 0.5. The dynamic recrystallization (DRX) and instable zones were identified and validated through micrographs. The processing maps can be used to select optimum strain rates and temperatures for effective hot working of the material.展开更多
The mixed metal/metal sulphide(Ag@CoS)with reduced graphene oxide(rGO)nanocomposite(Ag@CoS/rGO)was synthesized for the possible electrode in supercapacitors.Ag@CoS was successfully deposited on the rGO nanosheets by h...The mixed metal/metal sulphide(Ag@CoS)with reduced graphene oxide(rGO)nanocomposite(Ag@CoS/rGO)was synthesized for the possible electrode in supercapacitors.Ag@CoS was successfully deposited on the rGO nanosheets by hydrothermal method,implying the growth of 2D Ag and CoS-based hexagonal-like structure on the rGO framework.The synthesized nanocomposite was subjected to structural,morphological and electrochemical studies.The XRD results show that the prepared nanocomposite material exhibits a combination of hexagonal and cubic phase due to the presence of CoS and Ag phases together.The band appearing at nearly 470.33 cm^−1 in FTIR spectra can be ascribed to the absorption of S—S bond in the Ag@CoS/rGO nanocomposite.The clear hexagonal structure was analysed by SEM and TEM with the grain sizes ranging from nanometer to micrometer.The electrode material exhibits excellent cyclic stability with a specific capacitance of 1580 F/g at a current density of 0.5 A/g without any loss of capacitive retention even after 1000 cycles.Based on the electrochemical performance,it can be inferred that the prepared novel nanocomposite material is very suitable for using as an electrode for electrochemical supercapacitor applications.展开更多
Multispectral images contain a large amount of spatial and spectral data which are effective in identifying change areas.Deep feature extraction is important for multispectral image classification and is evolving as a...Multispectral images contain a large amount of spatial and spectral data which are effective in identifying change areas.Deep feature extraction is important for multispectral image classification and is evolving as an interesting research area in change detection.However,many deep learning framework based approaches do not consider both spatial and textural details into account.In order to handle this issue,a Convolutional Neural Network(CNN)based multi-feature extraction and fusion is introduced which considers both spatial and textural features.This method uses CNN to extract the spatio-spectral features from individual channels and fuse them with the textural features.Then the fused image is classified into change and unchanged regions.The presence of mixed pixels in the bitemporal satellite images affect the classification accuracy due to the misclassification errors.The proposed method was compared with six state-of-theart change detection methods and analyzed.The main highlight of this method is that by taking into account the spatio-spectral and textural information in the input channels,the mixed pixel problem is solved.Experiments indicate the effectiveness of this method and demonstrate that it possesses low misclassification errors,higher overall accuracy and kappa coefficient.展开更多
In this communication we have used Bickley’s method for the construction of a sixth order spline function and apply it to solve the linear fifth order differential equations of the form yx(x)+g (x)y(x)= r(x) where g(...In this communication we have used Bickley’s method for the construction of a sixth order spline function and apply it to solve the linear fifth order differential equations of the form yx(x)+g (x)y(x)= r(x) where g(x) and r(x) are given functions with the two different problems of different boundary conditions. The method is illustrated by applying it to solve some problems to demonstrate the application of the methods discussed.展开更多
The objective of present work is to study the thermo diffusion effect on an unsteady simultaneous convective heat and mass transfer flow of an incompressible, electrically conducting, heat generating/absorbing fluid a...The objective of present work is to study the thermo diffusion effect on an unsteady simultaneous convective heat and mass transfer flow of an incompressible, electrically conducting, heat generating/absorbing fluid along a semi-infinite moving porous plate embedded in a porous medium with the presence of pressure gradient, thermal radiation field and chemical reaction. It is assumed that the permeable plate is embedded in a uniform porous medium and moves with a constant velocity in the flow direction in the presence of a transverse magnetic field. It is also assumed that the free stream consists of a mean velocity, temperature and concentration over which are super imposed an exponentially varying with time. The equations of continuity, momentum, energy and diffusion, which govern the flow field, are solved by using a regular perturbation method. The behavior of the velocity, temperature, concentration, Skin-friction, rate of heat transfer and rate of mass transfer has been discussed for variations in the physical parameters. An increase in both Pr and R results a decrease in thermal boundary layer thickness. However, concentration decreases as Kr, Sc increase but it increases with an increase in both So and δ.展开更多
The 12-lead ECG aids in the diagnosis of myocardial infarction and is helpful in the prediction of cardiovascular disease complications.It does,though,have certain drawbacks.For other electrocardiographic anomalies su...The 12-lead ECG aids in the diagnosis of myocardial infarction and is helpful in the prediction of cardiovascular disease complications.It does,though,have certain drawbacks.For other electrocardiographic anomalies such as Left Bundle Branch Block and Left Ventricular Hypertrophy syndrome,the ECG signal withMyocardial Infarction is difficult to interpret.These diseases cause variations in the ST portion of the ECG signal.It reduces the clarity of ECG signals,making itmore difficult to diagnose these diseases.As a result,the specialist is misled into making an erroneous diagnosis by using the incorrect therapeutic technique.Based on these concepts,this article reviews the different procedures involved in ECG signal pre-processing,feature extraction,feature selection,and classification techniques to diagnose heart disorders such as LeftVentricularHypertrophy,Bundle Branch Block,andMyocardial Infarction.It reveals the flaws and benefits in each segment,as well as recommendations for developing more advanced and robustmethods for diagnosing these diseases,which will increase the system’s accuracy.The current issues and prospective research directions are also addressed.展开更多
文摘This study examines the behavior of a micropolar nanofluidflowing over a sheet in the presence of a transverse magneticfield and thermal effects.In addition,chemical(first-order homogeneous)reactions are taken into account.A similarity transformation is used to reduce the system of governing coupled non-linear partial differ-ential equations(PDEs),which account for the transport of mass,momentum,angular momentum,energy and species,to a set of non-linear ordinary differential equations(ODEs).The Runge-Kutta method along with shoot-ing method is used to solve them.The impact of several parameters is evaluated.It is shown that the micro-rota-tional velocity of thefluid rises with the micropolar factor.Moreover,the radiation parameter can have a remarkable influence on theflow and temperature profiles and on the angular momentum distribution.
基金the University Grants Commission(UGC),New Delhi,India for the financial support to Mr.Shashi Kant Singh
文摘Objective:To screen different analogues of mangiferin pharmacologically for antipyretic activity. Methods:The naturally occurring xanthone glycoside mangiferin was isolated by column chromatography from the elhanolic extract of stem bark of Mangifera indica.Mangiferin was further converted to 5-(N-phenylamino methyleno) mangiferin.5-(N-p-chlorophenylamino methyleno) mangiferin,5-(N-2-methyl phenylamino methyleno) mangiferin.5-(N-p-methoxy phenylamino methyleno) mangiferin.5-(N,N-diphenylamino methyleno) mangiferin,5-(N-α-napthylamino methyleno) mangiferin and 5-(N-4-methyl phenylamino methyleno) mangiferin analogues.The synthesized compounds were further screened for antipyretic activity along with mangiferin at a dose level of 100 and 200 tng/kg.Mangiferin and its analogues were characterized by melting point and R_f value determination and through spectral technique like UV,IR,and NMR spectral analysis.Results:The antipyretic activity of mangiferin as well as all analogues was found to be more significant in at higher dose ie.200 mg/kg which was depicted thmugh a decrease in rectal temperature up to 3 h.Conclusions:The antipyretic activity of mangiferin and its analogues may be attributed to inhibition in synthesis of TNF-αand anti-oxidant activity associated with amelioration of inflammatory actions of cytokines.
文摘Diabetes mellitus is referred as common metabolic abnormalities characterized as hyperglycemia,mainly caused due to insufficient production of insulin at cellular level or/and defects in insulin action.Such an endocrine disorder is responsible for serious health problems and its worldwide prevalence is rapidly increasing.Common management of diabetes by oral administration of drugs without creating any side effects is still considered a challenging task and increasing cost of con-ventional medicine in developing countries is another matter of concern.To address these issues,traditional preparations of herbal plant extracts in the form of medicines already gained immense attention.Swertia chirayita is one among such plants which is known for its hypoglycemic potential.Numerous chemical constituents with promising pharmacological properties have been identified from such plant extracts but still,such compounds have not been well characterized,specifically against human application.Hence,more research efforts are necessitated to understand exact mechanism of such compounds and to develop overall safety of such plant formulations.Present review clearly represents antidiabetic properties of Swertia chirayita extract,strategies to be taken to strengthen its safety application on humans and biotechnological interventions that ensure conservation of such endangered species to promote its future application in modern medicine.
文摘The influence of reduction in emissions on the inherent temporal characteristics of PMand NOconcentration time series in six urban cities of India is assessed by computing the Hurst exponent using Detrended Fluctuation Analysis(DFA) during the lockdown period(March 24–April 20, 2020) and the corresponding period during the previous two years(i.e., 2018 and 2019). The analysis suggests the anticipated impact of confinement on the PMand NOconcentration in urban cities, causing low concentrations. It is observed that the original PMand NOconcentration time series is persistent but filtering the time series by fitting the autoregressive process of order 1 on the actual time series and subtracting it changes the persistence property significantly. It indicates the presence of linear correlations in the PMand NOconcentrations. Hurst exponent of the PMand NOconcentration during the lockdown period and previous two years shows that the inherent temporal characteristics of the short-term air pollutant concentrations(APCs) time series do not change even after withholding the emissions. The meteorological variations also do not change over the three time periods. The finding helps in developing the prediction models for future policy decisions to improve urban air quality across cities.
文摘The effect of different concentrations of benzaldehyde on the electrodeposition of Ni–W alloy coatings on a mild steel substrate from a citrate electrolyte was investigated in this study. The electrolytic alkaline bath(p H 8.0) contained stoichiometric amounts of nickel sulfate, sodium tungstate, and trisodium citrate as precursors. The corrosion resistance of the Ni–W-alloy-coated specimens in 0.2 mol/L H2SO4 was studied using various electrochemical techniques. Tafel polarization studies reveal that the alloy coatings obtained from the bath containing 50 ppm benzaldehyde exhibit a protection efficiency of 95.33%. The corrosion rate also decreases by 21.5 times compared with that of the blank. A higher charge-transfer resistance of 1159.40 ?·cm2 and a lower double-layer capacitance of 29.4 μF·cm-2 further confirm the better corrosion resistance of the alloy coating. X-ray diffraction studies reveal that the deposits on the mild steel surface are consisted of nanocrystals. A lower surface roughness value(Rmax) of the deposits is confirmed by atomic force microscopy.
文摘Diabetic Retinopathy(DR)is an eye disease that mainly affects people with diabetes.People affected by DR start losing their vision from an early stage even though the symptoms are identified only at the later stage.Once the vision is lost,it cannot be regained but can be prevented from causing any further damage.Early diagnosis of DR is required for preventing vision loss,for which a trained ophthalmologist is required.The clinical practice is time-consuming and is not much successful in identifying DR at early stages.Hence,Computer-Aided Diagnosis(CAD)system is a suitable alternative for screening and grading of DR for a larger population.This paper addresses the different stages in CAD system and the challenges in identifying and grading of DR by analyzing various recently evolved techniques.The performance metrics used to evaluate the Computer-Aided Diagnosis system for clinical practice is also discussed.
文摘<div style="text-align:justify;"> In the fast-moving world, it is noticed that every industry is developing gradually, but recently it is identified that the use of AI has become the talk of own. Therefore, this study is focused on gathering data regarding the AI on how it has transformed the entire world’s corporate sector. The essential application AI in the business world helps the business to perform better in the corporate sector. In this paper, the critical role of artificial intelligence is to grow business in different sectors and also address its ethical and unethical issues. The paper has all the initial background and comprehensive literature regarding AI and machine learning. It is discovered how the technological world has been striving to take their business on to new heights, which requires updated technological changes in internal business activities. Companies can now effortlessly interact with their customers in making their application accessible for the end-users through implementing AI and machine learning. Companies are getting higher profitability and enhancing their performance and achieving economic advantages by integrated AI. Moreover, their technological developments will take human jobs in the future, so, it is suggested that humans should work on their skills and competencies so that they can deal with unemployment. </div>
文摘This study explored the concurrent scheduling of machines, tools, and tool transporter(TT) with alternative machines in a multi-machine flexible manufacturing system(FMS), taking into mind the tool transfer durations for minimization of the makespan(MSN). When tools are expensive, just a single copy of every tool kind is made available for use in the FMS system. Because the tools are housed in a central tool magazine(CTM), which then distributes and delivers them to many machines, because there is no longer a need to duplicate the tools in each machine, the associated costs are avoided. Choosing alternative machines for job operations(jb-ons), assigning tools to jb-ons, sequencing jb-ons on machines, and arranging allied trip activities, together with the TT’s loaded trip times and deadheading periods, are all challenges that must be overcome to achieve the goal of minimizing MSN. In addition to a mixed nonlinear integer programming(MNLIP) formulation for this simultaneous scheduling problem, this paper suggests a symbiotic organisms search algorithm(SOSA) for the problem’s solution. This algorithm relies on organisms’ symbiotic interaction strategies to keep living in an ecosystem. The findings demonstrate that SOSA is superior to the Jaya algorithm in providing solutions and that using alternative machines for operations helps bring down MSN.
文摘Cd1-xZnxSe films with different zinc contents are deposited by an electron beam evaporation technique onto glass substrates for applications in solid-state photovoltalc devices. The structural, optical and photoelectrochemical （PEC） properties of Cd1-xZnxSe films are studied. The host material Cd1-xZnxSe is prepared by the physical vapor deposition method of electron beam evaporation technique （PVD： EBE） under a pressure of 1 × 10^-5 mbar. The x-ray diffractogram indicates that these alloy films are polycrystalline in nature, hexagonal structure with strong preferential orientation of the crystallites along （002） direction. The optical properties shows that the band gap Eg varies from 2.08 to 2.84eV as zinc content varies from 0.2 to 0.8. A PEC cell of the configuration n-Cd1-xZnxSe/Na2S-S-NaOH is fabricated and the dynamic current-voltage characteristics in the dark atmosphere have been examined at room temperature. It has been found that both Voc and Iac decrease with the photoelectrode composition x. Efficiency η and fill factor （FF） also show similar variations. The material properties would be altered and excellently controlled by controlling the system composition x.
文摘In the modern world,women now have tremendous success in every field.They can play,learn,and earn as much as men.But what about safety?Do they have the same secure environment that men and boys do?The answer is“NO”.Women and girls have been subjected to numerous incidents,including acid throwing,rape,kidnapping,and harassment.It is common to read a lot of news like this in newspapers every day.These incidents make women feel unsafe in this society.Our freedom came a long time ago,but women still lack complete security in this society.All women cannot fight or shout all the time when some danger is happening to them.What can the physically challenged person and Children do?To make women feel safe,we designed“Wrist Band”using IoT for women safety.As the sensors sense information from the body,it will always update the information such as pulse,temperature,and vibration to the well-wishers through the Blynk app.
文摘Facial emotion recognition(FER)has become a focal point of research due to its widespread applications,ranging from human-computer interaction to affective computing.While traditional FER techniques have relied on handcrafted features and classification models trained on image or video datasets,recent strides in artificial intelligence and deep learning(DL)have ushered in more sophisticated approaches.The research aims to develop a FER system using a Faster Region Convolutional Neural Network(FRCNN)and design a specialized FRCNN architecture tailored for facial emotion recognition,leveraging its ability to capture spatial hierarchies within localized regions of facial features.The proposed work enhances the accuracy and efficiency of facial emotion recognition.The proposed work comprises twomajor key components:Inception V3-based feature extraction and FRCNN-based emotion categorization.Extensive experimentation on Kaggle datasets validates the effectiveness of the proposed strategy,showcasing the FRCNN approach’s resilience and accuracy in identifying and categorizing facial expressions.The model’s overall performance metrics are compelling,with an accuracy of 98.4%,precision of 97.2%,and recall of 96.31%.This work introduces a perceptive deep learning-based FER method,contributing to the evolving landscape of emotion recognition technologies.The high accuracy and resilience demonstrated by the FRCNN approach underscore its potential for real-world applications.This research advances the field of FER and presents a compelling case for the practicality and efficacy of deep learning models in automating the understanding of facial emotions.
文摘Surface chokes are widely utilized equipment installed on wellheads to control hydrocarbon flow rates.Several correlations have been suggested to model the multiphase flow of oil and gas via surface chokes.However,substantial errors have been reported in empirical fitting models and correlations to estimate hydrocarbon flow because of the reservoir's heterogeneity,anisotropism,variance in reservoir fluid characteristics at diverse subsurface depths,which introduces complexity in production data.Therefore,the estimation of daily oil and gas production rates is still challenging for the petroleum industry.Recently,hybrid data-driven techniques have been reported to be effective for estimation problems in various aspects of the petroleum domain.This paper investigates hybrid ensemble data-driven approaches to forecast multiphase flow rates through the surface choke(viz.stacked generalization and voting architectures),followed by an assessment of the impact of input production control variables.Otherwise,machine learning models are also trained and tested individually on the production data of hydrocarbon wells located in North Sea.Feature engineering has been properly applied to select the most suitable contributing control variables for daily production rate forecasting.This study provides a chronological explanation of the data analytics required for the interpretation of production data.The test results reveal the estimation performance of the stacked generalization architecture has outperformed other significant paradigms considered for production forecasting.
文摘Rice stands as a crucial staple food globally,with its enduring sustainability hinging on the prompt detection of rice leaf diseases.Hence,efficiently detecting diseases when they have already occurred holds paramount importance for solving the cost of manual visual identification and chemical testing.In the recent past,the identification of leaf pathologies in crops predominantly relies on manual methods using specialized equipment,which proves to be time-consuming and inefficient.This study offers a remedy by harnessing Deep Learning(DL)and transfer learning techniques to accurately identify and classify rice leaf diseases.A comprehensive dataset comprising 5932 self-generated images of rice leaves was assembled along with the benchmark datasets,categorized into 9 classes irrespective of the extent of disease spread across the leaves.These classes encompass diverse states including healthy leaves,mild and severe blight,mild and severe tungro,mild and severe blast,as well as mild and severe brown spot.Following meticulous manual labelling and dataset segmentation,which was validated by horticulture experts,data augmentation strategies were implemented to amplify the number of images.The datasets were subjected to evaluation using the proposed tailored Convolutional Neural Networks models.Their performance are scrutinized in conjunction with alternative transfer learning approaches like VGG16,Xception,ResNet50,DenseNet121,Inception ResnetV2,and Inception V3.The effectiveness of the proposed custom VGG16 model was gauged by its capacity to generalize to unseen images,yielding an exceptional accuracy of 99.94%,surpassing the benchmarks set by existing state-of-the-art models.Further,the layer wise feature extraction is also visualized as the interpretable AI.
文摘The hot deformation behaviour of 7075 aluminium alloy reinforced with 10%of SiC particles was studied by employing both"processing maps"and microstructural observations.The composite was characterized by employing optical microscope to evaluate the microstructural transformations and instability phenomena.The material investigated was deformed by compression in the temperature and strain rate ranges of 300-500℃and 0.001-1.0 s-1,respectively.The deformation efficiency was calculated by strain rate sensitivity(m)values obtained by hot compression tests.The power dissipation efficiency and instability parameters were evaluated and processing maps were constructed for strain of 0.5.The optimum domains and instability zone were obtained for the composites.The optimum processing conditions are obtained in the strain rate range of 0.1-0.9 s-1and temperature range of 390-440 ℃with the efficiency of 30%.
文摘The hot deformation behavior of as-cast ZE41A magnesium alloy was studied by employing both processing maps and microstructural observations. To obtain processing map, hot compression tests were performed over a range of strain rates (0.001-1.0 s-1) and temperatures (250-450 ℃). Power dissipation efficiency (η) and instability parameter [ξ (ε)] were evaluated and processing maps were developed for the strain of 0.5. The dynamic recrystallization (DRX) and instable zones were identified and validated through micrographs. The processing maps can be used to select optimum strain rates and temperatures for effective hot working of the material.
文摘The mixed metal/metal sulphide(Ag@CoS)with reduced graphene oxide(rGO)nanocomposite(Ag@CoS/rGO)was synthesized for the possible electrode in supercapacitors.Ag@CoS was successfully deposited on the rGO nanosheets by hydrothermal method,implying the growth of 2D Ag and CoS-based hexagonal-like structure on the rGO framework.The synthesized nanocomposite was subjected to structural,morphological and electrochemical studies.The XRD results show that the prepared nanocomposite material exhibits a combination of hexagonal and cubic phase due to the presence of CoS and Ag phases together.The band appearing at nearly 470.33 cm^−1 in FTIR spectra can be ascribed to the absorption of S—S bond in the Ag@CoS/rGO nanocomposite.The clear hexagonal structure was analysed by SEM and TEM with the grain sizes ranging from nanometer to micrometer.The electrode material exhibits excellent cyclic stability with a specific capacitance of 1580 F/g at a current density of 0.5 A/g without any loss of capacitive retention even after 1000 cycles.Based on the electrochemical performance,it can be inferred that the prepared novel nanocomposite material is very suitable for using as an electrode for electrochemical supercapacitor applications.
文摘Multispectral images contain a large amount of spatial and spectral data which are effective in identifying change areas.Deep feature extraction is important for multispectral image classification and is evolving as an interesting research area in change detection.However,many deep learning framework based approaches do not consider both spatial and textural details into account.In order to handle this issue,a Convolutional Neural Network(CNN)based multi-feature extraction and fusion is introduced which considers both spatial and textural features.This method uses CNN to extract the spatio-spectral features from individual channels and fuse them with the textural features.Then the fused image is classified into change and unchanged regions.The presence of mixed pixels in the bitemporal satellite images affect the classification accuracy due to the misclassification errors.The proposed method was compared with six state-of-theart change detection methods and analyzed.The main highlight of this method is that by taking into account the spatio-spectral and textural information in the input channels,the mixed pixel problem is solved.Experiments indicate the effectiveness of this method and demonstrate that it possesses low misclassification errors,higher overall accuracy and kappa coefficient.
文摘In this communication we have used Bickley’s method for the construction of a sixth order spline function and apply it to solve the linear fifth order differential equations of the form yx(x)+g (x)y(x)= r(x) where g(x) and r(x) are given functions with the two different problems of different boundary conditions. The method is illustrated by applying it to solve some problems to demonstrate the application of the methods discussed.
文摘The objective of present work is to study the thermo diffusion effect on an unsteady simultaneous convective heat and mass transfer flow of an incompressible, electrically conducting, heat generating/absorbing fluid along a semi-infinite moving porous plate embedded in a porous medium with the presence of pressure gradient, thermal radiation field and chemical reaction. It is assumed that the permeable plate is embedded in a uniform porous medium and moves with a constant velocity in the flow direction in the presence of a transverse magnetic field. It is also assumed that the free stream consists of a mean velocity, temperature and concentration over which are super imposed an exponentially varying with time. The equations of continuity, momentum, energy and diffusion, which govern the flow field, are solved by using a regular perturbation method. The behavior of the velocity, temperature, concentration, Skin-friction, rate of heat transfer and rate of mass transfer has been discussed for variations in the physical parameters. An increase in both Pr and R results a decrease in thermal boundary layer thickness. However, concentration decreases as Kr, Sc increase but it increases with an increase in both So and δ.
文摘The 12-lead ECG aids in the diagnosis of myocardial infarction and is helpful in the prediction of cardiovascular disease complications.It does,though,have certain drawbacks.For other electrocardiographic anomalies such as Left Bundle Branch Block and Left Ventricular Hypertrophy syndrome,the ECG signal withMyocardial Infarction is difficult to interpret.These diseases cause variations in the ST portion of the ECG signal.It reduces the clarity of ECG signals,making itmore difficult to diagnose these diseases.As a result,the specialist is misled into making an erroneous diagnosis by using the incorrect therapeutic technique.Based on these concepts,this article reviews the different procedures involved in ECG signal pre-processing,feature extraction,feature selection,and classification techniques to diagnose heart disorders such as LeftVentricularHypertrophy,Bundle Branch Block,andMyocardial Infarction.It reveals the flaws and benefits in each segment,as well as recommendations for developing more advanced and robustmethods for diagnosing these diseases,which will increase the system’s accuracy.The current issues and prospective research directions are also addressed.
