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Experimental demonstration of SnO_(2) nanofiber-based memristors and their data-driven modeling for nanoelectronic applications

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Chip 2023年第4期2卷 142-153页

作者： Soumi Saha Madadi Chetan Kodand Reddy tati sai nikhil Kaushik Burugupally Sanghamitra DebRoy Akshay Salimath Venkat Mattela Surya Shankar Dan Parikshit Sahatiya Department of Electrical&Electronics Engineering Birla Institute of Technology and Science PilaniHyderabad CampusHyderabad 500078India Department of Computer Science and Information Systems Birla Institute of Technology and Science PilaniHyderabad CampusHyderabad 500078India Nanomagnetic Division Ceremorphic India Pvt LtdIndia Ceremorphic Inc.San JoseCA 95131USA

This paper demonstrated the fabrication,characterization,datadriven modeling,and practical application of a 1D SnO_(2)nanofiber-based memristor,in which a 1D SnO_(2)active layer wassandwiched between silver(Ag)and aluminum(Al)electrodes.Thisdevice yielded a very high ROFF:RON of~104(ION:IOFF of~105)with an excellent activation slope of 10 mV/dec,low set voltage ofVSET~1.14 V and good repeatability.This paper physically explained the conduction mechanism in the layered SnO_(2)nanofiber-basedmemristor.The conductive network was composed of nanofibersthat play a vital role in the memristive action,since more conductive paths could facilitate the hopping of electron carriers.Energyband structures experimentally extracted with the adoption of ultraviolet photoelectron spectroscopy strongly support the claimsreported in this paper.An machine learning(ML)–assisted,datadriven model of the fabricated memristor was also developedemploying different popular algorithms such as polynomialregression,support vector regression,k nearest neighbors,andartificial neural network(ANN)to model the data of the fabricateddevice.We have proposed two types of ANN models(type I andtype II)algorithms,illustrated with a detailed flowchart,to modelthe fabricated memristor.Benchmarking with standard ML techniques shows that the type II ANN algorithm provides the bestmean absolute percentage error of 0.0175 with a 98%R^(2)score.The proposed data-driven model was further validated with the characterization results of similar new memristors fabricated adoptingthe same fabrication recipe,which gave satisfactory predictions.Lastly,the ANN type II model was applied to design and implementsimple AND&OR logic functionalities adopting the fabricatedmemristors with expected,near-ideal characteristics.

关键词： Nanofiber-based memristors Data-driven modeling Artificial neural network(ANN) SnO_(2)

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Hepatocellular carcinoma immune microenvironment and check point inhibitors-current status

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World Journal of Hepatology 2024年第3期16卷 353-365页

作者： Tarana Gupta nikhil sai Jarpula Division of Hepatology Department of MedicinePandit Bhagwat Dayal Sharma Post Graduate Institute of Medical SciencesRohtak 124001HaryanaIndia

Hepatocellular carcinoma(HCC)is the most common primary tumor of the liver and has a high mortality rate.The Barcelona Clinic Liver Cancer staging system in addition to tumor staging also links the modality of treatment available to a particular stage.The recent description of the tumor microenvironment(TME)in HCC has provided a new concept of immunogenicity within the HCC.Virusrelated HCC has been shown to be more immunogenic with higher expression of cytotoxic T lymphocytes and decreased elements for immunosuppression such as regulatory T cells.This immunogenic milieu provides a better response to immunotherapy especially immune checkpoint inhibitors(ICIs).In addition,the recent data on combining locoregional therapies and other strategies may convert the less immunogenic state of the TME towards higher immunogenicity.Therefore,data are emerging on the use of combinations of locoregional therapy and ICIs in unresectable or advanced HCC and has shown better survival outcomes in this difficult population.

关键词： Hepatocellular carcinoma Tumor immune microenvironment Immune checkpoint inhibitor Atezolizumab Bevacizumab Pembrolizumab

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In-hospital outcomes in COVID-19 patients with non-alcoholic fatty liver disease by severity of obesity:Insights from national inpatient sample 2020

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World Journal of Hepatology 2024年第6期16卷 912-919页

作者： Sashwath Srikanth Vibhor Garg Lakshmi Subramanian Jyoti Verma Hansika Sharma Harroop Singh Klair Shrenil A Kavathia Jithin Kolli Teja nikhil sai Vasireddy Kumar Anmol Dhanush Kolli Shruti Sanjay Bodhankar Sobya Hashmi Shaylika Chauhan Rupak Desai Department of Medicine ECU Health Medical CenterGreenvilleNC 27834United States Department of Medicine Jacobi Medical Center/Albert Einstein College of MedicineBronxNY 10461United States Department of Medicine North Alabama Medical CentreFlorenceAL 35630United States Department of General Medicine Gandhi Medical CollegeSecunderabad 500003TelanganaIndia Department of Medicine Government Medical CollegePatiala 147001PunjabIndia Department of Medicine B.J.Medical CollegeAhmedabad 380016GujaratIndia Department of Medicine JSS Medical CollegeMysore 570015KarnatakaIndia Department of Internal Medicine Gandhi Medical CollegeSecunderabad 500003TelanganaIndia Department of Medicine Kasturba Medical CollegeManipal 575001KarnatakaIndia Clinical Extern Department of Internal MedicineBeaumont HospitalDearbornMI 48124United States Department of Internal Medicine Geisinger Health SystemWilkes-BarrePA 18702United States Independent Researcher AtlantaGA 30079United States

BACKGROUND Non-alcoholic fatty liver disease(NAFLD)increases the risk of cardiovascular diseases independently of other risk factors.However,data on its effect on cardiovascular outcomes in coronavirus disease 2019(COVID-19)hospitalizations with varied obesity levels is scarce.Clinical management and patient care depend on understanding COVID-19 admission results in NAFLD patients with varying obesity levels.AIM To study the in-hospital outcomes in COVID-19 patients with NAFLD by severity of obesity.METHODS COVID-19 hospitalizations with NAFLD were identified using International Classification of Disease-10 CM codes in the 2020 National Inpatient Sample database.Overweight and Obesity Classes Ⅰ,Ⅱ,and Ⅲ(body mass index 30-40)were compared.Major adverse cardiac and cerebrovascular events(MACCE)(all-cause mortality,acute myocardial infarction,cardiac arrest,and stroke)were compared between groups.Multivariable regression analyses adjusted for sociodemographic,hospitalization features,and comorbidities.RESULTS Our analysis comprised 13260 hospitalizations,7.3% of which were overweight,24.3% Class Ⅰ,24.1% Class Ⅱ,and 44.3% Class Ⅲ.Class Ⅲ obesity includes younger patients,blacks,females,diabetics,and hypertensive patients.On multivariable logistic analysis,Class Ⅲ obese patients had higher risks of MACCE,inpatient mortality,and respiratory failure than Class Ⅰ obese patients.Class Ⅱ obesity showed increased risks of MACCE,inpatient mortality,and respiratory failure than Class I,but not significantly.All obesity classes had non-significant risks of MACCE,inpatient mortality,and respiratory failure compared to the overweight group.CONCLUSION Class Ⅲ obese NAFLD COVID-19 patients had a greater risk of adverse outcomes than class Ⅰ.Using the overweight group as the reference,unfavorable outcomes were not significantly different.Morbid obesity had a greater risk of MACCE regardless of the referent group(overweight or Class Ⅰ obese)compared to overweight NAFLD patients admitted with COVID-19.

关键词： Non-alcoholic fatty liver disease Obesity Obese Body mass index Major adverse cardiac and cerebrovascular events Mortality Acute myocardial infarction Cardiac arrest Stroke

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Artificial intelligence powered glucose monitoring and controlling system:Pumping module

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World Journal of Experimental Medicine 2024年第1期14卷 100-112页

作者： Sravani Medanki nikhil Dommati Hema Harshitha Bodapati Venkata Naga sai Kowsik Katru Gollapalli Moses Abhishek Komaraju Nanda sai Donepudi Dhanya Yalamanchili Jasti Sateesh Pratap Turimerla Department of Electronics and Communication Engineering Velagapudi Ramakrishna Siddhartha Engineering CollegeVijayawada 520007Andhra PradeshIndia Department of General Medicine Siddhartha Government Medical CollegeVijayawada 520008Andhra PradeshIndia

BACKGROUND Diabetes,a globally escalating health concern,necessitates innovative solutions for efficient detection and management.Blood glucose control is an essential aspect of managing diabetes and finding the most effective ways to control it.The latest findings suggest that a basal insulin administration rate and a single,highconcentration injection before a meal may not be sufficient to maintain healthy blood glucose levels.While the basal insulin rate treatment can stabilize blood glucose levels over the long term,it may not be enough to bring the levels below the post-meal limit after 60 min.The short-term impacts of meals can be greatly reduced by high-concentration injections,which can help stabilize blood glucose levels.Unfortunately,they cannot provide long-term stability to satisfy the postmeal or pre-meal restrictions.However,proportional-integral-derivative(PID)control with basal dose maintains the blood glucose levels within the range for a longer period.AIM To develop a closed-loop electronic system to pump required insulin into the patient's body automatically in synchronization with glucose sensor readings.METHODS The proposed system integrates a glucose sensor,decision unit,and pumping module to specifically address the pumping of insulin and enhance system effectiveness.Serving as the intelligence hub,the decision unit analyzes data from the glucose sensor to determine the optimal insulin dosage,guided by a pre-existing glucose and insulin level table.The artificial intelligence detection block processes this information,providing decision instructions to the pumping module.Equipped with communication antennas,the glucose sensor and micropump operate in a feedback loop,creating a closed-loop system that eliminates the need for manual intervention.RESULTS The incorporation of a PID controller to assess and regulate blood glucose and insulin levels in individuals with diabetes introduces a sophisticated and dynamic element to diabetes management.The simulation not only allows visualization of ho

关键词： Diabetes Hyperglycemia Insulin Micropump Closed loop systems Artificial intelligence automation

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Claroideoglomus etunicatum and Pantoea dispersa significantly enhance growth and nutrition of broom grass

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Studies in Fungi 2021年第1期6卷 327-333页

作者： nikhil sai N Ashwin R Bagyaraj DJVenugopala Rao R Centre for Natural Biological Resources and Community Development(CNBRCD) 41 RBI ColonyAnand NagarBangalore 560024KarnatakaIndia Laya Resource Centre YendadaVisakhapatnam 530045Andhra PradeshIndia

Broom grass(Thysanolaena maxima)is an evergreen non-timber forest produce species.This grass is now domesticated for cultivation by farmers.It is a multi-purpose grass providing mainly inflorescence used as brooms for cleaning every household and also fodder for cattle,fuel wood for cooking and thus enhance farmers income.An earlier pot culture study brought out that Claroideoglomus etunicatum as the best arbuscular mycorrhizal fungus(AMF)and Pantoea dispersa as the best plant growth promoting rhizobacteria(PGPR)for inoculating broom grass.In the present investigation,a pot culture experiment was conducted in glasshouse to study the effect of individual and combined inoculation of C.etunicatum and P.dispersa on the growth of broom grass.The plant height,stem girth,biovolume index,plant dry weight,major and minor nutrient concentrations were significantly higher in plants inoculated with C.etunicatum+P.dispersa compared to inoculation with either of them.It was concluded that dual inoculation with the two selected beneficial microorganisms is best for enhancing the growth and yield of broom grass which in turn will improve the livelihood of the farmers.

关键词： Microbial consortia Mycorrhiza symbiosis Thysanolaena maxima

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Impact of Autonomous Vehicles on Parking Spaces

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Journal of Architectural Environment & Structural Engineering Research 2020年第1期3卷 17-23页

作者： nikhil sai Yekollu Kasim A Korkmaz Construction Management Eastern Michigan UniversityYpsilantiMIUnited States School of Visual and Built Environment Eastern Michigan UniversityUnited States

The United States has an enormous supply of parking and with the appropriation of Autonomous vehicles,the interest for these spaces could change drastically.Parking is among the most pervasive land utilizes involving up to 31%of urban territory.With completely automated vehicles expected on the customer advertise by 2020,the$30 billion leaving industry will encounter gigantic changes as autos develop.The purpose of this paper is to analyse how the parking and garage spaces can be utilized after the implementation of automated vehicles in every household.Analysis has been conducted about different households in Ypsilanti Township using Zillow application which includes the address,area of the house,parking area and year in which it is built.Results are based on the analysis conducted on the houses and the impact of the autonomous vehicles on their parking space.

关键词： Structure Garage Household Transit

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