Improved adaptive gray wolf genetic algorithm for photovoltaic intelligent edge terminal optimal configuration

Photovoltaic (PV) intelligent edge terminals (IETs) integrate data acquisition, processing, storage and upload functions for intelligent operations of PV power stations. However, the cost of installing a PV IET at one PV station is relatively high. In order to achieve the goal of multiple distributed PV stations sharing one PV IET on the premise of ensuring reliability, the paper proposes a method for the optimal configuration of PV IETs. First of all, considering the economy and reliability of optimizing configuration of PV IET, a two-layer optimization model is established. After that, to solve the nonlinearity of the proposed model, an improved adaptive genetic algorithm and gray wolf optimization (IAGA-GWO) is proposed. Finally, through two application cases of PV IETs, it is proved that the optimized configuration method in this paper can reduce the cost under the premise of ensuring the reliability

PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts

The increasing reliance on Large Language Models (LLMs) across academia and industry necessitates a comprehensive understanding of their robustness to prompts. In response to this vital need, we introduce PromptBench, a robustness benchmark designed to measure LLMs' resilience to adversarial prompts. This study uses a plethora of adversarial textual attacks targeting prompts across multiple levels: character, word, sentence, and semantic. These prompts are then employed in diverse tasks, such as sentiment analysis, natural language inference, reading comprehension, machine translation, and math problem-solving. Our study generates 4,032 adversarial prompts, meticulously evaluated over 8 tasks and 13 datasets, with 567,084 test samples in total. Our findings demonstrate that contemporary LLMs are vulnerable to adversarial prompts. Furthermore, we present comprehensive analysis to understand the mystery behind prompt robustness and its transferability. We then offer insightful robustness analysis and pragmatic recommendations for prompt composition, beneficial to both researchers and everyday users. We make our code, prompts, and methodologies to generate adversarial prompts publicly accessible, thereby enabling and encouraging collaborative exploration in this pivotal field: https://github.com/microsoft/promptbench.Comment: Technical report; 23 pages; code is at: https://github.com/microsoft/promptbenc

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Characterization of the Key Aroma Compounds in Marselan Wine by Gas Chromatography-Olfactometry, Quantitative Measurements, Aroma Recombination, and Omission Tests

Key odorants of red wine made from the hybrid grapes of Marselan (Vitis vinifera L.) were isolated by solid-phase extraction (SPE) and explored by gas chromatography-olfactometry (GC-O) analysis. Application of aroma extract dilution analysis (AEDA) revealed 43 odor-active compounds, and 31 odorants among them were detected with flavor dilution (FD) factors ranging from 9 to 2187. Comprehensive two-dimensional gas chromatography and time-of-flight mass spectrometry (GC × GC-TOF-MS) were exploited to quantitate the aroma-active compounds with FD ≥9. The identification indicated β-damascenone as having the highest FD factors, followed by eugenol, 2,3-butanedione, citronellol, 4-hydroxy-2,5-dimethyl-3(2H)-furanone, phenethyl acetate, guaiacol, and 2-methoxy-4-vinylphenol. A total of 21 compounds were found to have odor activity values (OAVs) >1.0. Aroma reconstitution validation experiments showed a good similarity of blackberry, green pepper, honey, raspberry, caramel, smoky, and cinnamon aroma attributes between the original Marselan wine and the reconstructed wine. In addition, omission tests were carried out to further determine the contribution of odorants to the overall aroma

Sedimentary characteristics and controlling factors of the Ba 66 fan in Bayindulan Sag

Based on the data of core, thin sections, logging and 3D seismic, the sedimentary characteristics, controlling factors and sedimentary model of Ba 66 fan are studied systematically to determine the types and characteristics of the fan.The study shows that Ba 66 fan is a fan delta rapidly deposited by torrent after short-distance transport, and the hydrodynamic force of the fan is mainly driven by gravity.The extension distance of the fan is short on the plane.The fan is lobate as a whole and has the facies feature of " large plain, small front".The main characteristics of the fan are as follows: the maturity of the rock is low, and the disorderly massive glutenite is the typical lithofacies; The fan has the logging characteristics of high amplitude, odonation and abrupt contact.The fan bodies can be divided into plain, front (including proximal, middle and distal), pre-delta or lacustrine facies according to the characteristics of seismic facies, such as random hills, front accumulations, and sheets.The analysis shows that the development of fan delta in the slope belt is mainly controlled by the background environment of the depression and paleogeomorphology: ①The background conditions such as source of uplift area, narrow lake basin (no gentle slope) and wide lake surface ensure the supply of source and short-distance transportation conditions for the formation of fan delta; ②Grooves provide space for sand body development. The slope break changes the slope, divides the accommodation space, and controls the distribution of facies, and the low bulge under the water affects the plane distribution of the fan.Finally, the deposition model of Ba 66 fan is constructed

Inkjet-printed patch antenna emitter for wireless communication application

This research focuses on exploring low-cost and rapid production solutions for fabricating emitters for patch antennas for wireless communication applications. Additive manufacturing technique is employed to fabricate two patch antennas using silver nanoparticle ink on FR4 substrate. Finite-element simulation software, HFSS is used to analyse and predict the theoretical performance of the antenna designs for 2.4 GHz MIMO and 6 GHz wireless data transmission. The fabricated antennas have resonant frequencies closely matching the design values. The work provides a viable solution for fabricating emitters and finally antennas commercially using inkjet printing platform, thus overall reducing the cost and simplifying the process.National Research Foundation (NRF)Accepted versionThis work was supported under the grant by National Research Foundation (NRF)

DNA Computation-Modulated Self-Assembly of Stimuli-Responsive Plasmonic Nanogap Antennas for Correlated Multiplexed Molecular Imaging

Nanogap antennas with strong electromagnetic fields of the “hot spot” in the gap region of two adjacent particles that can significantly improve the optical properties of fluorophores hold great potential for ultrasensitive bioanalysis. Herein, a DNA computation-mediated self-assembly of Au NBP dimer-based plasmonic nanogap antennas was designed for imaging of intracellular correlated dual disease biomarkers. It is worth noting that with the benefit from the electromagnetic fields of the “hot spot” in the gap region and strand displacement amplification, the fluorescence intensity can be enhanced ∼14.7-fold by Au NBP dimer-based plasmonic nanogap antennas. In addition, the AND-gate sensing mechanism was confirmed through monitoring the response of three designed nAP-PH1, m-PH1, and PH1 probes, the fluorescence recovery in different cell lines (Hela and L02), and inhibitor-treated cells, respectively. Furthermore, thanks to the “dual keys” activation design, such an “AND-gate” sensing manner can be used for ultrasensitive correlated multiplexed molecular imaging, demonstrating its feasible prospect in correlated multiplexed molecular imaging