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Stock market prediction using deep learning algorithms

CAAI Transactions on Intelligence Technology 2023年第1期8卷 82-94页

作者： Somenath Mukherjee Bikash Sadhukhan Nairita Sarkar debajyoti roy Soumil De Nazrul Center of Social and Cultural Studies Kazi Nazrul UniversityAsansolIndia Department of Computer Science and Engineering Techno International New Town(Techno India College of Technology)KolkataIndia

The Stock Market is one of the most active research areas,and predicting its nature is an epic necessity nowadays.Predicting the Stock Market is quite challenging,and it requires intensive study of the pattern of data.Specific statistical models and artificially intelligent algorithms are needed to meet this challenge and arrive at an appropriate solution.Various machine learning and deep learning algorithms can make a firm prediction with minimised error possibilities.The Artificial Neural Network(ANN)or Deep Feedforward Neural Network and the Convolutional Neural Network(CNN)are the two network models that have been used extensively to predict the stock market prices.The models have been used to predict upcoming days'data values from the last few days'data values.This process keeps on repeating recursively as long as the dataset is valid.An endeavour has been taken to optimise this prediction using deep learning,and it has given substantial results.The ANN model achieved an accuracy of 97.66%,whereas the CNN model achieved an accuracy of 98.92%.The CNN model used 2-D histograms generated out of the quantised dataset within a particular time frame,and prediction is made on that data.This approach has not been implemented earlier for the analysis of such datasets.As a case study,the model has been tested on the recent COVID-19 pandemic,which caused a sudden downfall of the stock market.The results obtained from this study was decent enough as it produced an accuracy of 91%.

关键词： artificial neural network convolutional neural network nifty stock market

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Mechanism of Cu entry into the brain:many unanswered questions

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Neural Regeneration Research 2024年第11期19卷 2421-2429页

作者： Shubhrajit roy Svetlana Lutsenko Department of Physiology Johns Hopkins University School of MedicineBaltimoreMDUSA

Brain tissue requires high amounts of copper(Cu)for its key physiological processes,such as energy production,neurotransmitter synthesis,maturation of neuropeptides,myelination,synaptic plasticity,and radical scavenging.The requirements for Cu in the brain vary depending on specific brain regions,cell types,organism age,and nutritional status.Cu imbalances cause or contribute to several life-threatening neurologic disorders including Menkes disease,Wilson disease,Alzheimer’s disease,Parkinson’s disease,and others.Despite the well-established role of Cu homeostasis in brain development and function,the mechanisms that govern Cu delivery to the brain are not well defined.This review summarizes available information on Cu transfer through the brain barriers and discusses issues that require further research.

关键词： ATOX1 ATP7A ATP7B blood-brain barrier brain choroid plexus copper SLC31A1

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Structural,optical,electrical,and dielectric relaxation properties of rare earth containing sodium bismuth titanate Na_(0.5)Bi_(0.5)TiO_(3) perovskite:Effect of ionic radius

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Journal of Rare Earths 2024年第2期42卷 383-391,I0006页

作者： Rajdip roy Abhigyan Dutta Department of Physics The University of BurdwanBurdwan713104India

The main focus of this work is to study the effect of the ionic radius of different rare earth dopant cations RE^(3+)(RE=La,Sm,Dy,and Ho) on structural and various physical properties of sodium bismuth titanate(Na_(0.5)B_(0.5)TiO_(3),NBT) based perovskite nanomaterials.The X-ray diffraction data indicate the successful formation of the rhombohedral phase(space group R3c) of NBT nano perovskite incorporated with various rare earth ions in Bi-site.The lattice parameters were found to increase linearly with the ionic radius of the dopant cation.The ionic radii and atomic mass of rare earth dopants appear to be essential factors in the grain growth of the prepared compositions.The grain growth results in better crystallinity of the sample by reducing the microstrain with the increase of dopant ionic radius.Field emission scanning electron microscopy and energy-dispersive X-ray spectra confirm the prepared compositions' phase purity and stoichiometry.The UV-Vis spectra reveal that La-doped NBT composition exhibits the lowest optical band gap,which unfolds the application of NBT-based perovskite as photoactive material.The ac conductivity and complex impedance spectra unveil that the composition with the largest ionic radius,i.e.,La-doped NBT compound,exhibits the highest dc and bulk conductivity with the lowest activation energy.The frequency-dependent dielectric data follows Havriliak-Negami(HN) formalism and non-Debye type relaxation phenomena.Results also indicate that La-doped NBT composition exhibits the highest dielectric strength value.Thus,this study first elaborates that the increasing ionic radius of the rare earth dopant cation in the Bi-site of NBT perovskite improves its microstructural,optical,and electrical properties.

关键词： Rare earth doped NBT Microstructural analysis Optical band gap AC Conductivity Dielectric relaxation Rare earths

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Association between people’s attitudes towards human-elephant conflict and their locational,demographic,and socio-economic characteristics in Buxa Tiger Reserve and its adjoining area,India

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Regional Sustainability 2024年第1期5卷 11-25页

作者： Chiranjib NAD Tamal BASU-roy Department of Geography Raiganj UniversityRaiganj733134India

“Human-elephant conflict(HEC)”,the alarming issue,in present day context has attracted the attention of environmentalists and policy makers.The rising conflict between human beings and wild elephants is common in Buxa Tiger Reserve(BTR)and its adjoining area in West Bengal State,India,making the area volatile.People’s attitudes towards elephant conservation activity are very crucial to get rid of HEC,because people’s proximity with wild elephants’habitat can trigger the occurrence of HEC.The aim of this study is to conduct an in-depth investigation about the association of people’s attitudes towards HEC with their locational,demographic,and socio-economic characteristics in BTR and its adjoining area by using Pearson’s bivariate chi-square test and binary logistic regression analysis.BTR is one of the constituent parts of Eastern Doors Elephant Reserve(EDER).We interviewed 500 respondents to understand their perceptions to HEC and investigated their locational,demographic,and socio-economic characteristics including location of village,gender,age,ethnicity,religion,caste,poverty level,education level,primary occupation,secondary occupation,household type,and source of firewood.The results indicate that respondents who are living in enclave forest villages(EFVs),peripheral forest villages(PFVs),corridor village(CVs),or forest and corridor villages(FCVs),mainly males,at the age of 18–48 years old,engaged with agriculture occupation,and living in kancha and mixed houses,have more likelihood to witness HEC.Besides,respondents who are illiterate or at primary education level are more likely to regard elephant as a main problematic animal around their villages and refuse to participate in elephant conservation activity.For the sake of a sustainable environment for both human beings and wildlife,people’s attitudes towards elephants must be friendly in a more prudent way,so that the two communities can live in harmony.

关键词： Human-elephant conflict Elephant conservation Chi-square test statistics Binary logistic regression Demographic and socioeconomic characteristics Buxa Tiger Reserve

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Enhanced in-vitro degradation resistance and cytocompatibility of a thermomechanically processed novel Mg alloy:Insights into the role of microstructural attributes

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Journal of Magnesium and Alloys 2024年第2期12卷 700-725页

作者： Darothi Bairagi Santanu Mandal Mangal roy Manas Paliwal Sumantra Mandal Department of Metallurgical and Materials Engineering Indian Institute of TechnologyKharagpur 721302India

The role of microstructural features on in-vitro degradation and surface film development of a thermomechanically processed Mg-4Zn-0.5Ca-0.8Mn alloy has been investigated employing electrochemical studies,scanning electron microscopy and X-ray photoelectron spectroscopy.The specimen forged at 523 K temperature developed a coarse unimodal microstructure consisting of basal oriented grains,whereas the specimens forged at 623 K and 723 K temperatures exhibited bimodal microstructures containing randomly oriented fine grains and basal oriented coarse grains.The bimodal microstructures exerted higher resistance to corrosion compared to the unimodal microstructure in presence of a protective surface film.The optimum size distribution of fine and coarse grains as well as the prevalence of basal oriented grains led to the lowest anodic current density in the specimen forged at 623 K.The morphology of Ca_(2)Mg_(6)Zn_(3)precipitates governed the cathodic kinetics by controlling the anode to cathode surface area ratio.Despite the specimen forged at 723 K comprised comparatively lower fraction of precipitates than at 623 K,the mesh-like precipitate morphology increased the effective cathodic surface area,leading to enhanced localised corrosion in the former specimen.Optimal microstructural features developed at 623 K forging temperature formed a well-protective surface film with lower Mg(OH)_(2)to MgO ratio,exhibiting distinctly high polarization resistance and superior cytocompatibility in terms of cell-proliferation and cell-differentiation.

关键词： Magnesium alloy Microstructure Corrosion Electrochemical impedance spectroscopy X-ray photoelectron spectroscopy Cytotoxicity

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Atherosclerotic plaque classification in carotid ultrasound images using machine learning and explainable deep learning

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Intelligent Medicine 2024年第2期4卷 83-95页

作者： Soni Singh Pankaj K.Jain Neeraj Sharma Mausumi Pohit Sudipta roy School of Vocational Studies and Applied Sciences Gautam Buddha UniversityGreater NoidaUttar PradeshIndia Artificial Intelligence and Data Science Jio Institute Navi MumbaiMaharashtraIndia School of Biomedical Engineering Indian Institute of TechnologyVaranasiUttar PradeshIndia

Objective The incidence of cardiovascular diseases(CVD)is rising rapidly worldwide.Some forms of CVD,such as stroke and heart attack,are more common among patients with certain conditions.Atherosclerosis development is a major factor underlying cardiovascular events,such as heart attack and stroke,and its early detection may prevent such events.Ultrasound imaging of carotid arteries is a useful method for diagnosis of atherosclerotic plaques;however,an automated method to classify atherosclerotic plaques for evaluation of early-stage CVD is needed.Here,we propose an automated method for classification of high-risk atherosclerotic plaque ultrasound images.Methods Five deep learning(DL)models(VGG16,ResNet-50,GoogLeNet,XceptionNet,and SqueezeNet)were used for automated classification and the results compared with those of a machine learning(ML)-based technique,involving extraction of 23 texture features from ultrasound images and classification using a Support Vector Machine classifier.To enhance model interpretability,output gradient-weighted convolutional activation maps(GradCAMs)were generated and overlayed on original images.Results A series of indices,including accuracy,sensitivity,specificity,F1-score,Cohen-kappa index,and area under the curve values,were calculated to evaluate model performance.GradCAM output images allowed visualization of the most significant ultrasound image regions.The GoogLeNet model yielded the highest accuracy(98.20%).Conclusion ML models may be also suitable for applications requiring low computational resource.Further,DL models could be more completely automated than ML models.

关键词： Explainable deep learning Carotid artery Classification VGG 16 ResNet-50 GoogLeNet XceptionNet SqueezeNet

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Severe acute kidney injury due to oxalate crystal induced severe interstitial nephritis: A case report

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World Journal of Nephrology 2024年第2期13卷 24-30页

作者： Maulik K Lathiya Praveen Errabelli Sasmit roy Neeharik Mareedu Department of Emergency Medicine Mayo Clinic Health SystemEau ClaireWI 54703United States Department of Nephrology Mayo Clinic Health SystemEau ClaireWI 54703United States Department of Nephrology Centra Lynchburg General HospitalLynchburgVA 24551United States Department of Nephrology UPMC Western MarylandCumberlandMD 21502United States

BACKGROUND Acute kidney injury(AKI)due to interstitial nephritis is a known condition primarily attributed to various medications.While medication-induced interstitial nephritis is common,occurrences due to non-pharmacological factors are rare.This report presents a case of severe AKI triggered by intratubular oxalate crystal deposition,leading to interstitial nephritis.The aim is to outline the case and its management,emphasizing the significance of recognizing uncommon causes of interstitial nephritis.CASE SUMMARY A 71-year-old female presented with stroke-like symptoms,including weakness,speech difficulties,and cognitive impairment.Chronic hypertension had been managed with hydrochlorothiazide(HCTZ)for over two decades.Upon admis-sion,severe hypokalemia and AKI were noted,prompting discontinuation of HCTZ and initiation of prednisolone for acute interstitial nephritis.Further investigations,including kidney biopsy,confirmed severe acute interstitial nephritis with oxalate crystal deposits as the underlying cause.Despite treatment,initial renal function showed minimal improvement.However,with prednisolone therapy and supportive measures,her condition gradually improved,high-lighting the importance of comprehensive management.CONCLUSION This case underscores the importance of a thorough diagnostic approach in identifying and addressing uncommon causes of interstitial nephritis.The occurrence of interstitial nephritis due to oxalate crystal deposition,especially without typical risk factors,emphasizes the need for vigilance in clinical practice.

关键词： Acute kidney injury Interstitial nephritis Oxalate crystal Hydrochlorothiazide Hypokalemia Case report

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Appraisal of pollution and health risks associated with coal mine contaminated soil using multimodal statistical and Fuzzy-TOPSIS approaches

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Frontiers of Environmental Science & Engineering 2024年第5期18卷 101-115页

作者： Sumit Kumar Sonali Banerjee Saibal Ghosh Santanu Majumder Jajati Mandal Pankaj Kumar roy Pradip Bhattacharyya Agricultural and Ecological Research Unit Indian Statistical InstituteGiridih815301India Department of Life and Environmental Sciences Bournemouth University(Talbot Campus)Fern BarrowPooleBH12 5BBUK School of Sciences Engineering & EnvironmentUniversity of SalfordSalfordM5 4QJUK School of Water Resource Engineering Jadavpur UniversityKolkata700032India School of Environmental Studies Jadavpur UniversityKolkata700032India

The present study assesses the concentration,probabilistic risk,source classification,and dietary risk arising from heavy metal(HMs)pollution in agricultural soils affected by coal mining in eastern part of India.Analyses of soil and rice plant indicated significantly elevated levels of HMs beyond the permissible limit in the contaminated zones(zone 1:PbSoil:108.24±72.97,CuSoil:57.26±23.91,CdSoil:8.44±2.76,CrSoil:180.05±46.90,NiSoil:70.79±25.06 mg/kg;PbGrain:0.96±0.8,CuGrain:8.6±5.1,CdGrain:0.65±0.42,CrGrain:4.78±1.89,NiGrain:11.74±4.38 mg/kg.zone 2:PbSoil:139.56±69.46,CuSoil:69.89±19.86,CdSoil:8.95±2.57,CrSoil:245.46±70.66,NiSoil:95.46±22.89 mg/kg;PbGrain:1.27±0.84,CuGrain:7.9±4.57,CdGrain:0.76±0.43,CrGrain:8.6±1.58,NiGrain:11.50±2.46 mg/kg)compared to the uncontaminated zone(zone 3).Carcinogenic and non-carcinogenic health risks were computed based on the HMs concentration in the soil and rice grain,with Pb,Cr,and Ni identified as posing a high risk to human health.Monte Carlo simulation,the solubility-free ion activity model(FIAM),and severity adjusted margin of exposure(SAMOE)were employed to predict health risk.FIAM hazard quotient(HQ)values for Ni,Cr,Cd,and Pb were>1,indicating a significant non-carcinogenic risk.SAMOE(risk thermometer)results for contaminated zones ranged from low to moderate risk(CrSAMOE:0.05,and NiSAMOE:0.03).Fuzzy-TOPSIS and variable importance plots(from random forest)showed that Ni and Cr were mostly responsible for the toxicity in the rice plant,respectively.A self-organizing map for source classification revealed common origin for the studied HMs with zone 2 exhibiting the highest contamination.The positive matrix factorization model for the source apportionment identified coal mining and transportation as the predominant sources of HMs.Spatial distribution analysis indicated higher contamination near mining sites as compared to distant sampling sites.Consequently,this study will aid environmental scientists and policymakers controlling HM pollution in agricultural soils near coal m

关键词： Coal mine Free ion activity model Monto Carlo Simulation Pollution and Health risk Fuzzy-TOPSIS

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A hierarchical clustering approach for colorectal cancer molecular subtypes identification from gene expression data

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Intelligent Medicine 2024年第1期4卷 43-51页

作者： Shivangi Raghav Aastha Suri Deepika Kumar Aakansha Aakansha Muskan Rathore Sudipta roy Department of Computer Science&Engineering Bharati Vidyapeeth’s College of EngineeringNew DelhiIndia Artificial Intelligence&Data Science Jio InstituteNavi Mumbai410206India

Background Colorectal cancer(CRC)is the second leading cause of cancer fatalities and the third most common human disease.Identifying molecular subgroups of CRC and treating patients accordingly could result in better therapeutic success compared with treating all CRC patients similarly.Studies have highlighted the significance of CRC as a major cause of mortality worldwide and the potential benefits of identifying molecular subtypes to tailor treatment strategies and improve patient outcomes.Methods This study proposed an unsupervised learning approach using hierarchical clustering and feature selection to identify molecular subtypes and compares its performance with that of conventional methods.The proposed model contained gene expression data from CRC patients obtained from Kaggle and used dimension reduction techniques followed by Z-score-based outlier removal.Agglomerative hierarchy clustering was used to identify molecular subtypes,with a P-value-based approach for feature selection.The performance of the model was evaluated using various classifiers including multilayer perceptron(MLP).Results The proposed methodology outperformed conventional methods,with the MLP classifier achieving the highest accuracy of 89%after feature selection.The model successfully identified molecular subtypes of CRC and differentiated between different subtypes based on their gene expression profiles.Conclusion This method could aid in developing tailored therapeutic strategies for CRC patients,although there is a need for further validation and evaluation of its clinical significance.

关键词： Machine learning Colorectal cancer Feature selection Classification Clustering

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Fabrication and evaluation of carboxymethyl guar gum-chitosan interpenetrating polymer network (IPN) nanoparticles for controlled drug delivery

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Medicine in Novel Technology and Devices 2024年第2期22卷 73-79页

作者： Chandrani roy Arijit Gandhi Sreejan Manna Sougata Jana Department of Pharmaceutics Gupta College of Technological SciencesAshram MoreG.T.RoadAsansol713301West BengalIndia Department of Pharmaceutical Technology Brainware UniversityBarasatKolkataWest Bengal700125India Department of Health and Family Welfare Directorate of Health ServicesKolkataIndia

Guar gum(GG)has drawn more interest from researchers in the last several decades for the controlled delivery of drugs.The aim of the research is to fabricate and evaluate an interpenetrating polymer network(IPN)based nanocarriers system employing chemically modified GG to achieve controlled release of drug.In present study,we have reported the synthesis of carboxymethyl GG-chitosan IPN nanoparticles for controlled release of metformin hydrochloride.Carboxymethyl guar gum(CMGG)was synthesized and employed for developing IPN nanoparticles in combination with chitosan in varying polymeric ratios.A cross-linking agent,sodium tripolyphosphate(Na-TPP)was used for the synthesis of IPN colloidal suspension of nanoparticles which was lyophilized to obtain nanoparticles.The carboxymethylation of GG was confirmed through Fourier transform infra-red spectroscopy.The mean particle size was 440.6 nm indicating a polydispersity index of 0.528.The drug entrapment efficiency was found to vary between 67.461.64%to 88.232.02%.The differential scanning calorimetry study revealed the presence of amorphous metformin hydrochloride as a homogenous dispersion in nanoparticles(NPs)matrix.In vitro drug release study indicated controlled release ability of developed IPN matrix.A2 formulation(chitosan:CMGG-1:1)exhibited 78.110.27%release after 8 h.Antidiabetic evaluation performed in alloxan-treated diabetic rat model exhibited a prolonged hypoglycemic efficacy over 6 h,for A2 formulation treated group,compared to the group receiving only metformin HCl,which demonstrated a reduction in blood glucose levels for up to 4 h.The study findings demonstrated the efficacy of the CMGG-chitosan based IPN nanoparticulate system for sustained delivery of therapeutic agents.

关键词： Carboxymethyl guar gum Chitosan Interpenetrating polymer network Nanoparticles Controlled release Metformin hydrochloride

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