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Strong coupling and catenary field enhancement in the hybrid plasmonic metamaterial cavity and TmDC monolayers

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Opto-electronic Advances 2024年第5期7卷 20-32页

作者： Andergachew mekonnen Berhe Khalil As’ham Ibrahim Al-Ani Haroldo T.Hattori Andrey e.miroshnichenko School of engineering and Technology University of New South Wales at CanberraNorthcott DriveCanberra ACT 2610Australia

Strong coupling between resonantly matched surface plasmons of metals and excitons of quantum emitters results in the formation of new plasmon-exciton hybridized energy *** plasmon-exciton strong coupling,plasmonic nanocavities play a significant role due to their ability to confine light in an ultrasmall ***,two-dimensional transition metal dichalcogenides(TmDCs) have a significant exciton binding energy and remain stable at ambient conditions,making them an excellent alternative for investigating light-matter *** a result,strong plasmon-exciton coupling has been reported by introducing a single metallic ***,single nanoparticles have lower spatial confinement of electromagnetic fields and limited tunability to match the excitonic ***,we introduce the concept of catenary-shaped optical fields induced by plasmonic metamaterial cavities to scale the strength of plasmon-exciton *** demonstrated plasmon modes of metallic metamaterial cavities offer high confinement and tunability and can match with the excitons of TmDCs to exhibit a strong coupling regime by tuning either the size of the cavity gap or *** calculated Rabi splitting of Au-moSe_2 and Au-WSe_2 heterostructures strongly depends on the catenary-like field enhancement induced by the Au cavity,resulting in room-temperature Rabi splitting ranging between 77.86 and 320 me *** plasmonic metamaterial cavities can pave the way for manipulating excitons in TmDCs and operating active nanophotonic devices at ambient temperature.

关键词： catenary-shaped field enhancement strong coupling plasmon exciton Rabi splitting

Toward a Learnable Climate model in the Artificial Intelligence era

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Advances in Atmospheric Sciences 2024年第7期41卷 1281-1288页

作者： Gang HUANG Ya WANG Yoo-Geun ham Bin mU Weichen TAO Chaoyang XIe State key Laboratory of Numerical modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Laboratory for Regional Oceanography and Numerical modeling Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China University of Chinese Academy of Sciences Beijing 100049China Department of environmental Planning Graduate School of Environmental StudiesSeoul National UniversitySeoul 08826South Korea School of Software engineering Tongji UniversityShanghai 200092China

Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related *** this AI-driven transformation,the foundational role of physics in climate science has occasionally been *** perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”*** controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical ***,we provide illustrative examples to guide future assessments and constraints for AI *** AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online ***,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)*** a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal.

关键词： artificial intelligence deep learning learnable climate model

enhancement of vertical phase separation in sequentially deposited organic photovoltaics through the independent processing of additives

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Journal of energy Chemistry 2024年第7期94卷 768-777页

作者： Damin Lee Changwoo Park Gayoung ham Young Yong Kim Sung-Nam Kwon Junyeong Lee Sungjin Jo Seok-In Na Hyojung Cha Department of Hydrogen and Renewable energy Kyungpook National UniversityDaegu 41566Republic of Korea Department of energy Convergence and Climate Change Kyungpook National UniversityDaegu 41566Republic of Korea Pohang Accelerator Laboratory(PAL) Pohang University of Science and Technology(POSTECH)PohangGyeongbuk 37673Republic of Korea Department of Flexible and Printable electronics Jeonbuk National UniversityJeonju-siJeollabuk-do 54896Republic of Korea School of energy engineering Kyungpook National UniversityDaegu 41566Republic of Korea

Herein,the impact of the independent control of processing additives on vertical phase separation in sequentially deposited (SD) organic photovoltaics (OPVs) and its subsequent effects on charge carrier kinetics at the electron donor-acceptor interface are *** film morphology exhibits notable variations,significantly depending on the layer to which 1,8-diiodooctane (DIO) was *** incidence wide-angle X-ray scattering analysis reveals distinctly separated donor/acceptor phases and vertical crystallinity details in SD ***-of-flight secondary ion mass spectrometry analysis is employed to obtain component distributions in diverse vertical phase structures of SD films depending on additive *** addition,nanosecond transient absorption spectroscopy shows that DIO control significantly affects the dynamics of separated charges in SD *** SD OPVs,DIO appears to act through distinct mechanisms with minimal restriction,depending on the applied *** study emphasizes the significance of morphological optimization in improving device performance and underscores the importance of independent additive control in the advancement of OPV technology.

关键词： Sequential deposition Vertical phase separation Charge dynamics Organic photovoltaics Nonfullerene acceptors

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

Identification and molecular Docking mechanism of Novel Anti-Inflammatory Peptides from Lactobacillus paraplantarum Fermented Cannabis sativa L. (hemp) Seeds

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Food Science and Human Wellness 2024年

作者： LingYue Shan Akanksha Tyagi HunJu ham Deog Hwan Oh Department of Food Science and Biotechnology， College of Agriculture and Life Sciences， Kangwon National University Future F Biotech Co.， Ltd Department of Biological environment， College of Agriculture and Life Sciences， Kangwon National University

The inflammatory response is a crucial physiological process that can lead to tissue damage and is considered a causative factor for various chronic diseases， such as rheumatoid arthritis. Recent research has focused on exploring valuable nutrients derived from Cannabis sativa L. (hemp) seeds， particularly hemp seed proteins. Therefore， this study aimed to investigate the release of anti-inflammatory peptides from Lactobacillus paraplantarum-fermented hemp seed proteins. To confirm the complete hydrolysis of hemp seed proteins during the fermentation process， SDS-PAGe was employed. Further， the isolation and purification of peptides were achieved through ultrafiltration. The identity of peptides was nextly established using ultra-high-performance liquid chromatography coupled with hybrid quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-mS). The results revealed a total of 39 identified peptides in fermented hemp seeds， with 9 peptides selected based on their relative quantity. Notably， AAeLIGVP (P1)， AAVPYPQ (P2)， VFPeVAP (P4)， DVIGVPLG (P6)， and PVPKVL (P9) demonstrated strong anti-inflammatory abilities in LPS-induced Raw 264.7 macrophage cells. molecular docking was used to understand the potential anti-inflammatory mechanism of these five peptides， and in silico results indicated that P1， P2， P4， P6， and P9 could bind to the active sites of TLR-4， NF-kB， and IKK with higher binding energies. Overall， these findings indicate that hemp seeds have potential to be a source of bioactive peptides for functional foods with anti-inflammatory properties.

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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