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machine learning approach to assess the association between anthropometric,metabolic,and nutritional status and semen parameters

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Asian Journal of Andrology 2024年第4期26卷 349-355页

作者： Guillaume Bachelot Antonin Lamaziere Sebastien Czernichow Celine faure Chrystelle Racine Rachel Levy Charlotte Dupont Nutrition and Fertility(ALIFeRT)Group Author Information Sorbonne University School of medicine Saint-Antoine Research CenterINSERM UMR 93827 rue ChalignyParis 75012France Reproductive Biology Department-CeCOS Tenon HospitalAP-HP.Sorbonne UniversityParis 75020France Clinical metabolomics Department Saint-Antoine HospitalAP-HP27 rue ChalignyParis 75012France Nutrition Department Obesity Specialist CentreGeorges Pompidou European HospitalAP-HPParis 75015France 不详

many lifestyle factors,such as nutritional imbalance leading to obesity,metabolic disorders,and nutritional deficiency,have been identified as potential risk factors for male *** aim of this study was to evaluate the relationship between semen parameters and anthropometric,metabolic and nutritional *** was first assessed individually,then after the application of a previously constructed and validated machine learning score that allows their ***,metabolic,antioxidant,micronutrient,and sperm parameters from 75 men suffering from idiopathic infertility from four infertility centers in France(Jean-Verdier ART Center Hospital,Bondy;North Hospital ART Center,Saint-Étienne;Navarre Polyclinic ART Center,Pau;and Cochin Hospital ART Center,Paris)between September 2009 and December 2013 were *** assessing standard correlation analysis,a previously built machine learning model,providing a score ranging from 0(the poorest)to 1(the most favorable),was calculated for each man in the study *** machine learning model,which separates infertile/fertile men with unexplained infertility on the basis of their bioclinical signature,provides a more holistic evaluation of the influence of the considered markers(anthropometric,metabolic,and oxidative status).We observed a significant correlation of some anthropometric,metabolic,and nutritional disorders with some sperm ***,an unfavorable machine learning score was associated with a high level of sperm DNA *** anthropometric,metabolic,and oxidative patterns,which may reflect an appropriate lifestyle,appear to positively impact overall health,in particular reproductive *** study,consistent with previous publications,suggests that beyond semen quality parameters,in an essential assessment of male fertility,other key factors should be taken into *** this regard,the application of emerging artificial intelligence t

关键词： lifestyle machine learning metabolism nutrition sperm DNA fragmentation

enhanced quantum resources via two distant atom-cavity systems under the influence of atomic dissipation

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Communications in Theoretical Physics 2024年第2期76卷 62-73页

作者： m Setodeh Kheirabady m K Tavassoly m Rafeie e Ghasemian Laser and Optics Group Faculty of PhysicsYazd UniversityYazd 89195-741Iran Department of electrical engineering Faculty of Intelligent Systems Engineering and Data SciencePersian Gulf UniversityBushehrIran

Quantum resources such as entanglement and coherence are the holy grail for modern quantum technologies. Although the unwanted environmental effects tackle quantum information processing tasks, suprisingly these key quantum resources may be protected and even enhanced by the implementation of some special hybrid open quantum systems. Here, we aim to show how a dissipative atom-cavity-system can be accomplished to generate enhanced quantum *** do so, we consider a couple of dissipative cavities, where each one contains two effective two-level atoms interacting with a single-mode cavity field. In practical applications, a classical laser field may be applied to drive each atomic subsystem. After driving the system, a Bell-state measurement is performed on the output of the system to quantify the entanglement and coherence. The obtained results reveal that the remote entanglement and coherence between the atoms existing inside the two distant cavities are not only enhanced, but can be stabilized, even under the action of dissipation. In contrast, the local entanglement between two atoms inside each dissipative cavity attenuates due to the presence of unwanted environmental ***, the local coherence may show the same behavior as the remote ***, the system provides the steady state entanglement in various interaction regimes,particularly in the strong atom-cavity coupling and with relatively large detuning. more interestingly, our numerical analyses demonstrate that the system may show a memory effect due to the fact that the death and revival of the entanglement take place during the interaction. Our proposed model may find potential applications for the implementation of long distance quantum networks. In particular, it facilitates the distribution of quantum resources between the nodes of large-scale quantum networks for secure communication.

关键词： remote entanglement and coherence atomic dissipation steady state entanglement Bell-statemeasurement

Novel Framework for an Intrusion Detection System Using multiple Feature Selection methods Based on Deep Learning

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Tsinghua Science and Technology 2024年第4期29卷 948-958页

作者： A.e.m.eljialy mohammed Yousuf Uddin Sultan Ahmad Department of Information Systems College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabiaand also with University Center for Research and Development(UCRD)Department of Computer Science and EngineeringChandigarh UniversityPunjabIndia

Intrusion detection systems (IDSs) are deployed to detect anomalies in real time. They classify a network’s incoming traffic as benign or anomalous (attack). An efficient and robust IDS in software-defined networks is an inevitable component of network security. The main challenges of such an IDS are achieving zero or extremely low false positive rates and high detection rates. Internet of Things (IoT) networks run by using devices with minimal resources. This situation makes deploying traditional IDSs in IoT networks unfeasible. machine learning (mL) techniques are extensively applied to build robust IDSs. many researchers have utilized different mL methods and techniques to address the above challenges. The development of an efficient IDS starts with a good feature selection process to avoid overfitting the mL model. This work proposes a multiple feature selection process followed by classification. In this study, the Software-defined networking (SDN) dataset is used to train and test the proposed model. This model applies multiple feature selection techniques to select high-scoring features from a set of features. Highly relevant features for anomaly detection are selected on the basis of their scores to generate the candidate dataset. multiple classification algorithms are applied to the candidate dataset to build models. The proposed model exhibits considerable improvement in the detection of attacks with high accuracy and low false positive rates, even with a few features selected.

关键词： random forest feature selection decision tree software-defined network logistic regression intrusion detection system XGB classifier AdaBoost

Beyond p-y method:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

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Journal of Rock mechanics and Geotechnical engineering 2024年第9期16卷 3812-3840页

作者： m.e.Al-Atroush A.e.Aboelela ezz el-Din Hemdan Civil and environmental engineering Program Engineering Management DepartmentCollege of EngineeringPrince Sultan UniversityRiyadhSaudi Arabia Department of Structural engineering Faculty of EngineeringAin Shams UniversityCairoEgypt Structure and materials Research Lab Prince Sultan UniversityRiyadhSaudi Arabia Computer Science and engineering Department Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt

In 2023,pivotal advancements in artificial intelligence(AI)have significantly *** that in mind,traditional methodologies,notably the p-y approach,have struggled to accurately model the complex,nonlinear soil-structure interactions of laterally loaded large-diameter drilled *** study undertakes a rigorous evaluation of machine learning(mL)and deep learning(DL)techniques,offering a comprehensive review of their application in addressing this geotechnical challenge.A thorough review and comparative analysis have been carried out to investigate various AI models such as artificial neural networks(ANNs),relevance vector machines(RVms),and least squares support vector machines(LSSVms).It was found that despite mL approaches outperforming classic methods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach made their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the mathematical equations derived from these ***,the research identified a gap in the availability of drilled shaft datasets,limiting the extendibility of current findings to large-diameter *** extensive dataset,compiled from a series of lateral loading tests on free-head drilled shaft with varying properties and geometries,was introduced to bridge this *** paper concluded with a direction for future research,proposes the integration of physics-informed neural networks(PINNs),combining data-driven models with fundamental geotechnical principles to improve both the interpretability and predictive accuracy of AI applications in geotechnical engineering,marking a novel contribution to the field.

关键词： Laterally loaded drilled shaft load transfer and failure mechanisms Physics-informed neural networks(PINNs) P-y curves Artificial intelligence(AI) Dataset

evaluation of the seismic behavior of reinforced concrete structures with flat slab-column gravity frame and shear walls through nonlinear analysis methods

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earthquake engineering and engineering Vibration 2024年第3期23卷 713-726页

作者： m.A.Najafgholipour S.Heidarian Radbakhsh e.erfani Department of Civil and environmental engineering Shiraz University of TechnologyShiraz ***Iran Department of Building Civiland Environmental EngineeringConcordia UniversityMontréal H3G 1M8Canada

This paper presents an investigation of the seismic behavior of reinforced concrete(RC)structures in which shear walls are the main lateral load-resisting elements and the participation of flat slab floor systems is not considered in the seismic design *** this regard,the behavior of six prototype structures(with different heights and plan layouts)is investigated through nonlinear static and time history analyses,implemented in the OpenSees *** results of the analyses are presented in terms of the behavior of the slab-column connections and their mode of failure at different loading ***,the global response of the buildings is discussed in terms of some parameters,such as lateral overstrength due to the gravity flat slab-column *** to the nonlinear static analyses,in structures in which the slab-column connections were designed only for gravity loads,the slab-column connections exhibited a punching mode of failure even in the early stages of ***,the punching failure was eliminated in structures in which a minimum transverse reinforcement recommended in ACI 318(2019)was provided in the slabs at joint ***,despite neglecting the contribution of gravity flat slab-column frames in the lateral load resistance of the structures,a relatively significant overstrength was imposed on the structures by the gravity frames.

关键词： RC flat slab-column frames seismic behavior nonlinear analysis time history analysis

Converting TRex-RGB green-channel data to 557.7 nm auroral intensity:methodology and initial results

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earth and Planetary Physics 2024年第1期8卷 258-274页

作者： Jun Liang D.m.Gillies e.Spanswick e.F.Donovan University of Calgary CalgaryT2N 1N4Canada

The recently deployed Transition Region explorer(TRex)-RGB(red-green-blue)all-sky imager(ASI)is designed to capture“true color”images of the aurora and *** the 557.7 nm green line is usually the brightest emission line in visible auroras,the green channel of a TRex-RGB camera is usually dominated by the 557.7 nm *** this rationale,the TRex mission does not include a specific 557.7 nm imager and is designed to use the RGB green-channel data as a proxy for the 557.7 nm *** this study,we present an initial effort to establish the conversion ratio or formula linking the RGB green-channel data to the absolute intensity of 557.7 nm auroras,which is crucial for quantitative uses of the RGB *** illustrate two approaches:(1)through a comparison with the collocated measurement of green-line auroras from the TRex spectrograph,and(2)through a comparison with the modeled green-line intensity according to realistic electron precipitation flux measurements from low-earth-orbit satellites,with the aid of an auroral transport *** demonstrate the procedures and provide initial results for the TRex-RGB ASIs at the Rabbit Lake and Lucky Lake *** RGB response is found to be *** conversion ratios or formulas between RGB green-channel data and the green-line auroral intensity are given and can be applied immediately by TRex-RGB data *** methodology established in this study will also be applicable to the upcoming SmILe ASI mission,which will adopt a similar RGB camera system in its deployment.

关键词： TRex RGB green-line aurora auroral transport model

Fuel cell stack design and modelling with a double-stage boost converter coupled to a single-phase inverter

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Clean energy 2024年第1期8卷 188-196页

作者： Basem e.elnagi Ahmed m.Ismaiel Hany S.e.mansour m.N.Abd-Alwahab electrical engineering Department Faculty of EngineeringSuez Canal UniversityIsmailia 41522Egypt

A comprehensive proton-exchange membrane fuel cell stack model was developed and integrated with a two-stage DC/DC boost *** was directly coupled to a single-phase(two levels-four pulses)inverter without a *** pulse-width modu-lation signal was used to independently regulate every converter *** converter was modelled using a mATLAB®/Simulink®environment and an appropriate voltage control *** analysis features of the suggested circuit were created and,through established experiments,the simulation results were verified.A single-phase(two levels-four pulses)inverter control circuit was tested and it produced a pure sinusoidal waveform with voltage *** matches the voltage of the network in terms of amplitude and frequency.A sinusoidal pulse-width modulation approach was performed using a single-phase(two levels-four pulses)pulse-width modulation *** results demonstrated an enhancement in the standard of the output wave and tuned the dead time with a reduction of 63μs compared with 180μs in conventional techniques.

关键词： Pem fuel cell pulse-width modulation single-phase inverter and double-stage DC/DC boost converter

The multi-impurity system in CdSe nanoplatelets:electronic structure and thermodynamic properties

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Communications in Theoretical Physics 2024年第3期76卷 165-173页

作者： D A Baghdasaryan V A Harutynyan e m Kazaryan H A Sarkisyan Russian-Armenian University H Emin 1230051YerevanArmenia Institute of Applied Problems of Physics 25 Nersisyan St0014YerevanArmenia

This paper theoretically studies the impurity states and the effects of impurity concentration and configuration on the optical,electrical,and statistical properties of CdSe nanoplatelets(NPLs).An image charge-based model of electron-impurity interaction is *** charge-carrier energy spectra and corresponding wave functions depending on the impurity number and configuration are *** electron binding energies are calculated for different NPL *** is shown that the image charge-based interaction potential that arises due to the dielectric constants mismatch is much stronger than the interaction potential that does not take such a mismatch into ***,it is demonstrated that the binding energies are increasing with the number of *** calculate the canonical partition function using the energy levels of the electron,which in turn is used to obtain the mean energy,heat capacity,and entropy of the non-interacting electron *** thermodynamic properties of the non-interacting electron gas that depend on the geometric parameters of the NPL,impurity number,configuration,and temperature are studied.

关键词： nanoplateletes thermodynamic properties impurity states

mitochondrial recruitment in myelin:an anchor for myelin dynamics and plasticity?

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Neural Regeneration Research 2024年第7期19卷 1401-1402页

作者： Jean-David m.Gothié Timothy e.Kennedy Department of Neurology and Neurosurgery Montreal Neurological InstituteMcGill UniversityMontrealQCCanada

Optimal propagation of neuronal electrical impulses depends on the insulation of axons by myelin,produced in the central nervous system by *** is an extension of the oligodendrocyte plasma membrane,which wraps around an axon to form a compact multi-layered *** is composed of a substantially higher proportion of lipids compared to other biological membranes and enriched in a small number of specialized proteins.

关键词： plasticity insulation dynamics