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Structural,optical and dielectric investigations on RECr_(0.85)Mn_(0.15)O_(3)(RE=Ho,Gd and Pr) nanoparticles

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Journal of Rare Earths 2024年第2期42卷 399-408,I0006页

作者： Komal Kanwar Sonali Pradhan S.Satapathy Yugandhar Bitla neeraj Panwar Department of Physics Central University of Rajasthan BandarsindrAjmer305817RajasthanIndia Laser Material Section HBNIRaja Ramanna Centre for Advanced TechnologyIndore452013India

We hereby report the room-temperature structural and optical characterization of RECr_(0.85)Mn_(0.15)O_(3)(RECMO,RE=Ho,Gd and Pr) compounds synthesized by the auto-combustion sol-gel *** low temperature dielectric properties are also *** RECMO compounds crystallize in an orthorhombic Pbnm symmetry with an average grain size range of 51-80 *** analysis reveals an increase in the structural distortion compared to that of the undoped bulk *** measurements exhibit a significant reduction in bandgap values for RECMO nanoparticles when compared with their undoped bulk ***,from the absorbance measurements various optical parameters such as skin depth,extinction coefficient,refractive index and optical conductivity were also *** dielectric analysis confirms the lower values of the dielectric permittivity and dielectric loss than those of their corresponding bulk *** conductivity versus frequency and temperature data are fitted according to the Jonscher's power law and Arrhenius law,*** small polaron hopping is responsible for the electric conduction in these *** tunability of the optical and dielectric properties as a result of substitution and particle size reduction makes these materials useful for various potential applications in photocatalysis,optoelectronics and low permittivity dielectrics.

关键词： Rare-earth orthochromites Nanoparticles Optical properties Dispersion parameters Dielectric properties Small polaron hopping

Optimizing sampling frequency of surface and downhole measurements for efficient stick-slip vibration detection

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Petroleum 2024年第1期10卷 30-38页

作者： Saket srivastava Aditya Sharma Catalin Teodoriu Mewbourne School of Petroleum and Geological Engineering The University of Oklahoma

Drilling vibrations significantly impact drilling operations with high costs due to early downhole equipment failure and loss of productive time. Stick-slip vibrations, a severe form of torsional vibrations,is known to be present up to 50% of total drilling time, making it a topic of immense concern and research. An ongoing discussion in the industry is regarding the reliability of surface measurements for early detection of severe downhole bit sticking. Moreover, most surface measurements are sampled at lower frequency rates closer to 1 Hz. Recently, the implementation of advanced data acquisition modules in downhole subs has greatly improved our understanding of drilling vibrations through high resolution data, sampled up to 10 kHz. However, with a wide range of sampling frequency to choose from different available tools, a critical question remains unanswered. What is an optimal and adequate sampling frequency for early detection of downhole vibrations using both surface and downhole measurements?The paper addresses the question with a focus on stick-slip vibrations through an experimental investigation. Stick slip tests are repeated for different sampling frequencies of surface and downhole measurements and the stick slip index for each case is calculated. The stick-slip index varies for different sampling frequency even though the vibration tests remain completely identical. It was inferred that sampling frequency of measurements greatly impact the detection of downhole vibrations. Even though stick-slip vibrations are characteristically low frequency vibrations(≤2Hz), a minimum of 10Hz sampling frequency is recommended for detection of stick-slip vibrations. Moreover, all characteristics of stick-slip vibrations including bit sticking, bit RPM peaks and negative bit RPMs are clearly observed at a minimum of 100Hz sampling rate.

关键词： Stick-slip

A Deep Learning Approach for Landmines Detection Based on Airborne Magnetometry Imaging and Edge Computing

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 2117-2137页

作者： Ahmed Barnawi Krishan Kumar neeraj Kumar Bander Alzahrani Amal Almansour Faculty of Computing and Information Technology King Abdulaziz UniversityJeddahSaudi Arabia Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyDeemed to be UniversityPatialaIndia

Landmines continue to pose an ongoing threat in various regions around the world,with countless buried landmines affecting numerous human *** detonation of these landmines results in thousands of casualties reported worldwide ***,there is a pressing need to employ diverse landmine detection techniques for their *** effective approach for landmine detection is UAV(Unmanned Aerial Vehicle)based AirborneMagnetometry,which identifies magnetic anomalies in the local terrestrial magnetic *** can generate a contour plot or heat map that visually represents the magnetic field *** the effectiveness of this approach,landmine removal remains a challenging and resource-intensive task,fraughtwith *** computing,on the other hand,can play a crucial role in critical drone monitoring applications like landmine *** processing data locally on a nearby edge server,edge computing can reduce communication latency and bandwidth requirements,allowing real-time analysis of magnetic field *** enables faster decision-making and more efficient landmine detection,potentially saving lives and minimizing the risks involved in the ***,edge computing can provide enhanced security and privacy by keeping sensitive data close to the source,reducing the chances of data exposure during *** paper introduces the MAGnetometry Imaging based Classification System(MAGICS),a fully automated UAV-based system designed for landmine and buried object detection and *** have developed an efficient deep learning-based strategy for automatic image classification using magnetometry dataset *** simulating the proposal in various network scenarios,we have successfully detected landmine signatures present in themagnetometry *** trained models exhibit significant performance improvements,achieving a maximum mean average precision value of 97.8%.

关键词： CNN deep learning landmine detection magnetometer mean average precision UAV

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 *** forms of CVD,such as stroke and heart attack,are more common among patients with certain *** development is a major factor underlying cardiovascular events,such as heart attack and stroke,and its early detection may prevent such *** 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 ***,we propose an automated method for classification of high-risk atherosclerotic plaque ultrasound *** 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 *** enhance model interpretability,output gradient-weighted convolutional activation maps(GradCAMs)were generated and overlayed on original *** A series of indices,including accuracy,sensitivity,specificity,F1-score,Cohen-kappa index,and area under the curve values,were calculated to evaluate model *** output images allowed visualization of the most significant ultrasound image *** GoogLeNet model yielded the highest accuracy(98.20%).Conclusion ML models may be also suitable for applications requiring low computational ***,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

Trace fossil evidences of an Early Miocene paleoseismic event and depositional regime change from the Kutch(Kachchh) Basin

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Journal of Palaeogeography 2024年第1期13卷 165-180页

作者： Ayush srivastava Sudipta Dasgupta Krishanu Chatterjee Mohuli Das Bombay Ichnos Research Group Department of Earth SciencesIndian Institute of Technology Bombay(lIT Bombay)PowaiMumbaiMaharashtra400076India

Unconsolidated siliciclastic sediments can undergo post-burial deformation, which leads to the formation of distinctive sedimentary structures, known as soft-sediment deformation structures(SSDS). The presence of a series of sand volcanoes confined to a particular lithostratigraphic horizon can represent a paleoseismic activity and, thereby, exemplifies the concept of “seismite”. The Kutch Basin has been a tectonically active region since the initiation of eastern Gondwana rifting followed by a tectonic inversion during the Cenozoic due to the collision of the Indian and Eurasian plates. A stratum-bound series of sand volcanoes belonging to the Khari Nadi Formation(KNF) is exposed along the banks of Khari River. They separate the shallow marine deposits below and non-marine deposits above with their characteristic marine and paleosol trace fossil suites, respectively. Although a seismogenic origin has been much debated for the SSDS,the ichnofabric analysis of the sand-volcano-bearing stratum unequivocally points toward such an origin under a shallow seafloor condition. In addition to the sedimentary regime change from an open shallow-marine setting to a continental depositional environment concomitant with basinal uplift, the behavior of the burrowing crustaceans testifies to a syn-depositional development of a fault network associated with the fluidization, sand volcanism, and the resilience of the trace-producers in surviving those processes until the sedimentary regime change in the overlying strata. Although the ichno-sedimentological evidence apparently differs from the previous works that proposed a continuous base-level rise from the beginning of deposition of the Khari Nadi Formation up to the middle part of the overlying Chhasra Formation, the paleoseismic activity,its ichnologic signature, and the depositional regime change refer to a higher-resolution(i.e., lower-order)sequence-stratigraphic change causing a short-duration regression within a longer-durat

关键词： Sand volcano Seismite Ichnology Khari Nadi Formation Kutch Basin Kachchh Basin

IDS-INT:Intrusion detection system using transformer-based transfer learning for imbalanced network traffic

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Digital Communications and Networks 2024年第1期10卷 190-204页

作者： Farhan Ullah Shamsher Ullah Gautam srivastava Jerry Chun-Wei Lin School of Software Northwestern Polytechnical UniversityXian710072ShaanxiChina Knowledge Unit of Systems and Technology University of Management and TechnologySialkot 51040Pakistan Department of Math and Computer Science Brandon UniversityBrandonMB R7A 6A9Canada Department of Computer Science and Math Lebanese American UniversityBeirut1102Lebanon Western Norway University of Applied Sciences BergenNorway Research Centre for Interneural Computing China Medical UniversityTaichungTaiwanChina

A network intrusion detection system is critical for cyber security against llegitimate *** terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a subcategory of attack,host information,malicious scripts,*** terms of network perspectives,network traffic may contain an imbalanced number of harmful attacks when compared to normal *** is challenging to identify a specific attack due to complex features and data imbalance *** address these issues,this paper proposes an Intrusion Detection System using transformer-based transfer learning for Imbalanced Network Traffic(IDS-INT).IDS-INT uses transformer-based transfer learning to learn feature interactions in both network feature representation and imbalanced ***,detailed information about each type of attack is gathered from network interaction descriptions,which include network nodes,attack type,reference,host information,***,the transformer-based transfer learning approach is developed to learn detailed feature representation using their semantic ***,the Synthetic Minority Oversampling Technique(SMOTE)is implemented to balance abnormal traffic and detect minority ***,the Convolution Neural Network(CNN)model is designed to extract deep features from the balanced network ***,the hybrid approach of the CNN-Long Short-Term Memory(CNN-LSTM)model is developed to detect different types of attacks from the deep *** experiments are conducted to test the proposed approach using three standard datasets,i.e.,UNsWNB15,CIC-IDS2017,and *** explainable AI approach is implemented to interpret the proposed method and develop a trustable model.

关键词： Network intrusion detection Transfer learning Features extraction Imbalance data Explainable AI Cybersecurity

Modern internet search analytics and thyroidectomy:What are patients asking?

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World Journal of Otorhinolaryngology-Head and Neck Surgery 2024年第1期10卷 49-58页

作者： neeraj Suresh Christian Fritz Emma De Ravin Karthik Rajasekaran Department of Otorhinolaryngology–Head&Neck Surgery University of PennsylvaniaPhiladelphiaPennsylvaniaUSA Perelman School of Medicine at the University of Pennsylvania PhiladelphiaPennsylvaniaUSA Leonard Davis Institute of Health Economics University of PennsylvaniaPhiladelphiaPennsylvaniaUSA

Objectives:Thyroidectomy is among the most commonly performed head and neck surgeries,however,limited existing information is available on topics of interest and concern to *** Design:***:***:A search engine optimization tool was utilized to extract metadata on Google‐suggested questions that“People Also Ask”(PAA)pertaining to“thyroidectomy”and“thyroid surgery.”These questions were categorized by Rothwell criteria and topics of *** Journal of the American Medical Association(JAMA)benchmark criteria enabled quality ***:A total of 250 PAA questions were ***‐oriented PAA questions describing what to expect during and after the surgery on topics such as postoperative management,risks or complications of surgery,and technical details were significantly less popular among the“thyroid surgery”group(P<0.001,P=0.005,and P<0.001,respectively).PAA questions about scarring and hypocalcemia were nearly threefold more popular than those related to pain(335 and 319 vs.113 combined search engine response page count,respectively).The overall JAMA quality score remained low(2.50±1.07),despite an increasing number of patients searching for“thyroidectomy”(r(77)=0.30,P=0.007).Conclusions:Patients searching for the nonspecific term“thyroid surgery”received a curated collection of PAA questions that were significantly less likely to educate them on what to expect during and after surgery,as compared to patients with higher health literacy who search with the term“thyroidectomy.”This suggests that the content of PAA questions differs based on the presumed health literacy of the internet user.

关键词： information quality online health education search analytics thyroid surgery thyroidectomy

Machine learning for predicting the outcome of terminal ballistics events

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Defence Technology（防务技术） 2024年第1期31卷 14-26页

作者： Shannon Ryan neeraj Mohan Sushma Arun Kumar AV Julian Berk Tahrima Hashem Santu Rana Svetha Venkatesh Applied Artificial Intelligence Institute(A2I2) Deakin University75 Pigdons RdWaurn PondsVIC3216Australia

Machine learning(ML) is well suited for the prediction of high-complexity,high-dimensional problems such as those encountered in terminal *** evaluate the performance of four popular ML-based regression models,extreme gradient boosting(XGBoost),artificial neural network(ANN),support vector regression(SVR),and Gaussian process regression(GP),on two common terminal ballistics’ problems:(a)predicting the V50ballistic limit of monolithic metallic armour impacted by small and medium calibre projectiles and fragments,and(b) predicting the depth to which a projectile will penetrate a target of semi-infinite *** achieve this we utilise two datasets,each consisting of approximately 1000samples,collated from public release *** demonstrate that all four model types provide similarly excellent agreement when interpolating within the training data and diverge when extrapolating outside this *** extrapolation is not advisable for ML-based regression models,for applications such as lethality/survivability analysis,such capability is *** circumvent this,we implement expert knowledge and physics-based models via enforced monotonicity,as a Gaussian prior mean,and through a modified loss *** physics-informed models demonstrate improved performance over both classical physics-based models and the basic ML regression models,providing an ability to accurately fit experimental data when it is available and then revert to the physics-based model when *** resulting models demonstrate high levels of predictive accuracy over a very wide range of projectile types,target materials and thicknesses,and impact conditions significantly more diverse than that achievable from any existing analytical *** with numerical analysis tools such as finite element solvers the ML models run orders of magnitude *** provide some general guidelines throughout for the development,application,and reporting of ML models in terminal ballist

关键词： Machine learning Artificial intelligence Physics-informed machine learning Terminal ballistics Armour

Disease clearance in ulcerative colitis:A new therapeutic target for the future

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World Journal of Gastroenterology 2024年第13期30卷 1801-1809页

作者： Syed Adeel Hassan neeraj Kapur Fahad Sheikh Anam Fahad Somia Jamal Division of Digestive Disease and Nutrition University of KentuckyLexingtonKY 40536United States Department of Pathology and Laboratory Medicine Montefiore Medical CenterAlbert Einstein College of MedicineNew YorkNY 10461United States Division of Primary Care Essen HealthcareNew YorkNY 10457United States Department of Internal Medicine Karachi Medical and Dental CollegeKarachi 74700SindhPakistan

Advancements in murine modeling systems for ulcerative colitis have diversified our understanding of the pathophysiological factors involved in disease onset and *** has fueled the identification of molecular targets,resulting in a rapidly expanding therapeutic ***,management strategies have evolved from symptomatic resolution to well-defined objective endpoints,including clinical remission,endoscopic remission and mucosal *** the incorporation of these assessment modalities has permitted targeted intervention in the context of a natural disease history and the prevention of complications,studies have consistently depicted discrepancies associated with ascertaining disease status through clinical and endoscopic *** recommendations lack consideration of histological *** simultaneous achievement of clinical,endoscopic,and histologic remission has not been fully *** has laid the groundwork for a novel therapeutic outcome termed disease clearance(DC).This article summarizes the concept of DC and its current evidence.

关键词： Inflammatory bowel disease Ulcerative colitis Clinical remission Endoscopic remission Histological remission Mucosal healing Disease clearance