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Predictive factors for percutaneous nephrolithotomy bleeding risks

Asian Journal of urology 2024年第1期11卷 105-109页

作者： u Phun Loo Chun Hou Yong Guan Chou Teh urology Department Sarawak General HospitalKuchingMalaysia

Objective:This study aimed to identify predictive factors for percutaneous nephrolithotomy(PCNL)bleeding *** better risk stratification,bleeding in high-risk patient can be anticipated and facilitates early ***:A prospective observational study of PCNL performed at our institution was *** adults with radio-opaque renal stones planned for PCNL were included except those with coagulopathy,planned for additional *** including gender,co-morbidities,body mass index,stone burden,puncture site,tract dilatation size,operative position,surgeon's seniority,and operative duration were studied using stepwise multivariate regression analysis to identify the predictive factors associated with higher estimated hemoglobin(Hb)***:Overall,4.86%patients(n=7)received packed cells *** mean estimated Hb deficiency was 1.3(range 0-6.5)g/dL and the median was 1.0 g/*** multivariate regression analysis revealed that absence of hypertension(p=0.024),puncture site(p=0.027),and operative duration(p=0.023)were significantly associated with higher estimated Hb ***,the effect sizes are rather small with partial eta-squared of 0.037,0.066,and 0.038,*** power obtained was 0.621,0.722,and 0.625,*** factors studied did not correlate with Hb ***:Hypertension,puncture site,and operative duration have significant impact on estimated Hb deficiency during ***,the effect size is rather small despite adequate study power ***,operative position(supine or prone),puncture number,or tract dilatation size did not correlate with Hb *** mainstay of reducing bleeding in PCNL is still meticulous operative *** study findings also suggest that PCNL can be safely done by urology trainees under supervision in suitably selected patient,without increasing risk of bleeding.

关键词： Percutaneous nephrolithotomy Predictive factor Risk factor Bleeding Blood loss

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How the Flat space Cosmology Model Correlates the Recombination CMB Temperature of 3000 K with a Redshift of 1100

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Journal of Modern Physics 2024年第2期15卷 174-178页

作者： Eugene Terry Tatum u. V. s. seshavatharam Independent Researcher Bowling Green Kentucky USA I-sERVE Hitech City Hyderabad India

This paper shows how the Flat space Cosmology model correlates the recom-bination epoch CMB temperature of 3000 K with a cosmological redshift of 1100. This proof is given in support of the recent publication that the Tatum and seshavatharam Hubble temperature formulae can be derived using the stephan-Boltzmann dispersion law. Thus, as explained herein, the era of high precision Planck scale quantum cosmology has arrived.

关键词： Hubble Constant Cosmic Microwave Background Quantum Cosmology stephan-Boltzmann upsilon Coupling Constant Flat space Cosmology ΛCDM Cosmology

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Estimating the subsolar magnetopause position from soft X-ray images using a low-pass image filter

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Earth and Planetary Physics 2024年第1期8卷 173-183页

作者： Hyangpyo Kim Hyunju K.Connor Jaewoong Jung Brian M.Walsh David sibeck Kip D.Kuntz Frederick s.Porter Catriana K.Paw u Rousseau A.Nutter Ramiz Qudsi Rumi Nakamura Michael Collier space Research Institute Austrian Academy of Sciences8042 GrazAustria Geophysical Institute University of Alaska FairbanksFairbanksAlaska 99775USA National Aeronautics and space Administration(NAsA)Goddard space Flight Center GreenbeltMaryland 20771USA Astronomy Department University of Maryland College ParkCollege ParkMaryland 20742USA Center for space Physics Boston UniversityBostonMassachusetts 02215USA Department of Physics and Astronomy Johns Hopkins UniversityBaltimoreMaryland 21218USA Howard university WashingtonDC 20059USA

The Lunar Environment heliospheric X-ray Imager(LEXI)and solar wind Magnetosphere Ionosphere Link Explorer(sMILE)missions will image the Earth’s dayside magneto pause and cusps in soft X-rays after their respective launches in the near future,to specify glo bal magnetic reconnection modes for varying solar wind *** suppo rt the success of these scientific missions,it is critical to develop techniques that extract the magnetopause locations from the observed soft X-ray *** this research,we introduce a new geometric equation that calculates the subsolar magnetopause position(Rs)from a satellite position,the look direction of the instrument,and the angle at which the X-ray emission is *** assumptions are used in this method:(1)The look direction where soft X-ray emissions are maximized lies tangent to the magnetopause,and(2)the magnetopause surface near the subsolar point is almost spherical and thus Rsis nea rly equal to the radius of the magneto pause *** create synthetic soft X-ray images by using the Open Geospace General Circulation Model(OpenGGCM)global magnetohydrodynamic model,the galactic background,the instrument point spread function,and Poisson *** then apply the fast Fourier transform and Gaussian low-pass filte rs to the synthetic images to re move noise and obtain accurate look angles for the soft X-ray pea *** the filte red images,we calculate Rs and its accuracy for different LEXI locations,look directions,and solar wind densities by using the OpenGGCM subsolar magnetopause location as ground *** method estimates Rs with an accuracy ofsolar wind density exceeds>10 *** accuracy improves for greater solar wind densities and during southward interplanetary magnetic *** method ca ptures the magnetopause motion during southwa rd interplaneta ry magnetic field ***,the technique will enable quantitative analysis of the magnetopause motion and help reveal the daysi

关键词： soft X-ray magnetopause reconnection low-pass filter LEXI sMILE

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Protein-activated atomic layer deposition for robust crude-oil-repellent hierarchical nano-armored membranes

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science Bulletin 2024年第2期69卷 218-226页

作者： Xiaobin Yang Pan sun Yajie Wen Anil u.Mane Jeffrey W.Elam Jun Ma shaomin Liu seth B.Darling Lu shao MIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and storage State Key Laboratory of Urban Water Resource and EnvironmentSchool of Chemistry and Chemical EngineeringHarbin Institute of TechnologyHarbin 150001China Chemical sciences and Engineering Division Argonne National LaboratoryLemont IL 60439USA Applied Materials Division Argonne National LaboratoryLemont IL 60439USA Advanced Materials for Energy-Water systems Energy Frontier Research Center Argonne National LaboratoryLemont IL 60439USA Pritzker school of Molecular Engineering University of ChicagoChicago IL 60637USA Department of Physics University of Ilinois at ChicagoChicago IL 60607USA school of Environment Harbin Institute of TechnologyHarbin 150090China WA school of Mines:Minerals Energy and Chemical EngineeringCurtin UniversityPerth WA 6845Australia

Atomic layer deposition(ALD)offers unique capabilities to fabricate atomically engineered porous materials with precise pore tuning and multi-functionalization for diverse applications like advanced membrane separations towards sustainable energy-water ***,current ALD technique is inhibited on most non-polar polymeric membranes due to lack of accessible nucleation ***,we report a facile method to efficiently promote ALD coating on hydrophobic surface of polymeric membranes via novel protein activation/*** a proof of concept,TiO2 ALD-coated membranes activated by bovine serum albumin exhibit remarkable superhydrophilicity,ultralow underwater crude oil adhesion,and robust tolerance to rigorous environments including acid,alkali,saline,and *** importantly,excellent cyclable crude oil-in-water emulsion separation performance can be *** mechanism for activation/sensitization is rooted in reactivity for a particular set of amino ***,the universality of protein-sensitized ALD is demonstrated using common egg white,promising numerous potential usages in biomedical engineering,environmental remediation,lowcarbon manufacturing,catalysis,and beyond.

关键词： Membrane separation Atomic layer deposition Water treatment Antifouling

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Quantized autoencoder(QAE)intrusion detection system for anomaly detection in resource-constrained loT devices using RT-loT2022 dataset

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Cybersecurity 2024年第2期7卷 13-27页

作者： B s sharmila Rohini Nagapadma Depatment of Electronics and Communication Engineering The National Institute of EngineeringMysoreKarnataka 570008India

In recent years,many researchers focused on unsupervised learning for network anomaly detection in edge devices to identify *** deployment of the unsupervised autoencoder model is computationally expensive in resource-constrained edge *** study proposes quantized autoencoder(QAE)model for intrusion detection systems to detect *** is an optimization model derived from autoencoders that incorporate pruning,clustering,and integer quantization *** autoencoder uint8(QAE-u8)and quantized autoencoder float16(QAE-f16)are two variants of QAE built to deploy computationally expensive Al models into Edge ***,we have generated a Real-Time Internet of Things 2022 dataset for normal and attack *** autoencoder model operates on normal traffic during the training *** same model is then used to reconstruct anomaly traffic under the assumption that the reconstruction error(RE)of the anomaly will be high,which helps to identify the ***,we study the performance of the autoencoders,QAE-u8,and QAE-f16 using accuracy,precision,recall,and F1 score through an extensive experimental *** showed that QAE-u8 outperforms all other models with a reduction of 70.01%in average memory utilization,92.23%in memory size compression,and 27.94%in peak CPu ***,the proposed QAE-u8 model is more suitable for deployment on resource-constrained IoT edge devices.

关键词： IoT constrained system

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Refining aquifer heterogeneity and understanding groundwater recharge sources in an intensively exploited agrarian dominated region of the Ganga Plain

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Geoscience Frontiers 2024年第4期15卷 134-147页

作者： Abhinav Patel shive Prakash Rai Nijesh Puthiyottil Abhinesh Kumar singh Jacob Noble Rajesh singh Dharmappa Hagare u.D.saravana Kumar Nachiketa Rai Kossitse Venyo Akpataku Department of Geology Institute of ScienceBanaras Hindu UniversityVaranasiUttar Pradesh 221005India Isotope and Radiation Application Division Bhabha Atomic Research CentreTrombayMumbai 400085India Environmental Hydrology Division National Institute of HydrologyRoorkeeUttarakhand 247667India school of Engineering Design and Built EnvironmentWestern Sydney UniversityAustralia Isotope Hydrology section Division of Physical and Chemical SciencesInternational Atomic Energy Agency(IAEA)ViennaAustria Department of Earth sciences Indian Institute of TechnologyRoorkeeUttarakhand 247667India Laboratory of Organic Chemistry and Environmental science Department of ChemistryUniversity of KaraPO Box 404KaraTogo

Densely populated region of Ganga Plain is facing aquifer vulnerability through waterborne pollutants and groundwater stress due to indiscriminate abstraction,causing environmental and socio-economic *** address long-term groundwater resilience,it is crucial to understand aquifer heterogeneity and connectivity,groundwater recharge sources,effects of groundwater abstraction *** this con-text,present study aims to understand factors responsible for vertical and spatial variability of groundwater chemistry and to identify groundwater recharge sources in an intensively exploited agrarian region of the Ganga *** of chemometric,statistical,and isotopic analysis categorises the alluvial aquifer into zone 1(G1;ground surface to 100 m)and zone 2(G2;>100 m-210 m).The group G1 samples are characterized by a wide variation in hydrochemical species,noted with pockets of F-and NO3-rich groundwater,and fresh to more evolved water types,while group G2 groundwater is characterized by a sharp increase in freshwater types and limited variation in their isotopic and hydrochemical *** G1 groundwater chemistry is governed by soil mineralogy,local anthropogenic inputs(sO42-,Cl-,and NO3-),and manifested by multiple recharge sources(local precipitation,river,canal water,pond).The G2 group is dominated by geogenic processes and mainly recharged by the local *** signatures confirm more evolved water type for group G1 in northwestern region,while fresh-water type covers the rest of the study *** rich groundwater is attributed to sodic water under alkaline conditions and enrichedδ18O values emphasizing role of evaporation in F-mobilization from micas and amphiboles abundant in the *** findings provide insight into potential groundwater vulnerability towards inorganic contaminants,and ground water recharge *** outcome of this study will help to develop aquifer resilience towards indiscriminate groundwater extrac

关键词： stable isotopes Hydrogeochemical attributes Groundwater recharge sources Ganga Plain

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Battery health management-a perspective of design,optimization,manufacturing,fault detection,and recycling

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Energy storage and saving 2024年第3期3卷 190-208页

作者： Pavel M.Roy Harsh H.sawant Pratik P.shelar Prashil u.sarode s.H.Gawande Industrial Tribology Laboratory Department of Mechanical EngineeringM.E.S.College of EngineeringSavitribai Phule Pune UniversityPune411007India

This paper explores the key aspects of battery technology,focusing on lithium-ion,lead-acid,and nickel metal hydride(NiMH)*** delves into manufacturing processes and highlighting their significance in optimizing battery *** addition,the study investigates battery fault detection,emphasizing the importance of early diagnosis using artificial intellignece(AI)and machine learning(ML)*** paper also addresses battery recycling techniques,discussing methods such as pyrometallurgy,hydrometallurgy,mechanical separation,and electrodialysis,considering their environmental *** comprehensive analysis sheds light on the evolution of battery technology and its role in sustainable energy systems.

关键词： Battery health Manufacturing Fault detection Recycling

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Explainable Conformer Network for Detection of COVID-19 Pneumonia from Chest CT scan: From Concepts toward Clinical Explainability

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Computers, Materials & Continua 2024年第1期78卷 1171-1187页

作者： Mohamed Abdel-Basset Hossam Hawash Mohamed Abouhawwash s.s.Askar Alshaimaa A.Tantawy Faculty of Computers and Informatics Zagazig UniversityZagazig44519Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of statistics and Operations Research College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT *** study aims to investigate the indispensable need for precise and interpretable diagnostic tools for improving clinical decision-making for COVID-19 *** paper proposes a novel deep learning approach,called Conformer Network,for explainable discrimination of viral pneumonia depending on the lung Region of Infections(ROI)within a single modality radiographic CT ***,an efficient u-shaped transformer network is integrated for lung image ***,a robust transfer learning technique is introduced to design a robust feature extractor based on pre-trained lightweight Big Transfer(BiT-L)and finetuned on medical data to effectively learn the patterns of infection in the input ***,this work presents a visual explanation method to guarantee clinical explainability for decisions made by Conformer *** evaluation of real-world CT data demonstrated that the diagnostic accuracy of ourmodel outperforms cutting-edge studies with statistical *** Conformer Network achieves 97.40% of detection accuracy under cross-validation *** model not only achieves high sensitivity and specificity but also affords visualizations of salient features contributing to each classification decision,enhancing the overall transparency and trustworthiness of our *** findings provide obvious implications for the ability of our model to empower clinical staff by generating transparent intuitions about the features driving diagnostic decisions.

关键词： Deep learning COVID-19 multi-modal medical image fusion diagnostic image fusion

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Emotion Detection using ECG signals and a Lightweight CNN Model

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Computer systems science & Engineering 2024年第5期48卷 1193-1211页

作者： Amita u.Dessai Hassanali G.Virani Department of Electronics and Telecommunication Engineering Goa College of EngineeringGoa UniversityPonda403401India

Emotion recognition is a growing field that has numerous applications in smart healthcare systems and Human-Computer Interaction(HCI).However,physical methods of emotion recognition such as facial expressions,voice,and text data,do not always indicate true emotions,as users can falsify *** the physiological methods of emotion detection,Electrocardiogram(ECG)is a reliable and efficient way of detecting ***-enabled smart bands have proven effective in collecting emotional data in uncontrolled *** use deep machine learning techniques for emotion recognition using ECG signals,but there is a need to develop efficient models by tuning the ***,most researchers focus on detecting emotions in individual settings,but there is a need to extend this research to group settings aswell since most of the emotions are experienced in *** this study,we have developed a novel lightweight one dimensional(1D)Convolutional Neural Network(CNN)model by reducing the number of convolution,max pooling,and classification *** optimization has led to more efficient emotion classification using *** tested the proposed model’s performance using ECG data from the AMIGOs(A Dataset for Affect,Personality and Mood Research on Individuals andGroups)dataset for both individual and group *** results showed that themodel achieved an accuracy of 82.21%and 85.62%for valence and arousal classification,respectively,in individual *** group settings,the accuracy was even higher,at 99.56%and 99.68%for valence and arousal classification,*** reducing the number of layers,the lightweight CNNmodel can process data more quickly and with less complexity in the hardware,making it suitable for the implementation on the mobile phone devices to detect emotions with improved accuracy and speed.

关键词： Emotions AMIGOs ECG lightweight 1D CNN

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u. s. Academic Medical Centers under the Managed Health Care Environment

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Biomedical and Environmental sciences 1999年第2期12卷 81-87页

作者： KRIsTINA GuO (school of Policy and Managment, Florida International university,North Miami, FL 33181, u. s. A.) Florida International university 美国

This research investigates the impact of managed health care on academic medical centers in the united states. Academic medical centers hold a unique position in the u. s. health care system through their missions of conducting cutting-edge biomedical researeh, pursuing clinical and technological innovations, Providing state-of-the-art medical care and producing highly qualified health professionals. However, policies to control costs through the use of managed care and limiting resources are detrimental to academic medical centers and impede the advancement of medical sciTo survive the threats of managed care in the health care environment, acadendc medical centers must rely on their upper level managers to derive successful strategies. The methods used in this study include qualitative approaches in the form of key informants and case studies. In addition, a survey questionnaire was sent to 1h8 CEOs in all the academic medical centers in the u. s. The findings revealed that managers who perform the liaison, monitor, entrepreneur and resource allocator roles are crucial to ensure the survival of academic medical centers, so that academic medical centers can continue their missions to serve the general public and promote their well-being.

关键词： Academic Medical Centers Cost Control Health Policy Humans Managed Care Programs Organizational Innovation united states

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