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SpecRecFormer: Deep Learning-Driven Adaptive Component Identification of PAH Mixtures Based on Single-Component Raman Spectra

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Analytical Chemistry 2025年第18期97卷 9876-9883页

作者： Yu, Xinna Liu, Tianyuan Kong, Lili Lan, Tianshuo Sun, Qifang Qu, Fanhua Liu, Meichun Chen, Jie Huang, Meizhen School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Submarine Geoscience Shanghai Jiao Tong University Shanghai200240 China School of Mathematics Physics and Statistics Shanghai University of Engineering Science Shanghai201620 China College of Information Mechanical and Electrical Engineering Shanghai Normal University Shanghai201499 China

The identification of components in mixed spectra is a fundamental challenge in spectral analysis, complicated by factors such as spectral peak overlap due to structural similarities, shifts in characteristic peaks from molecular interactions, and interferences caused by matrix effects. While deep learning offers robust feature extraction capabilities and notable advantages in addressing these challenges, it still faces significant obstacles, including the limited availability of labeled spectral data for effective training and the difficulty of applying fixed-threshold predictive models to spectra containing uncertain components. This paper established a deep learning model, SpecRecFormer, for the rapid identification of individual components in mixed polycyclic aromatic hydrocarbons (PAHs) based on their Raman spectra. The model integrates a dual-channel convolutional neural network (CNN) for local feature extraction with a Transformer module for global representation. It is trained on a reference database composed of single-component spectra, with simulated mixed spectra generated through data augmentation to expand and diversify the training set. This architecture enables the model to evaluate the similarity between unknown mixed spectra and known single-component references. To further enhance recognition accuracy, an adaptive threshold strategy is introduced, dynamically adjusting decision thresholds based on spectral characteristics to retain only components exceeding the threshold as candidate predictions. Experimental results demonstrate that with training data derived from only four single-component reference spectra, the model generalizes effectively to three real-world PAH data sets, achieving accuracies of 93.75%, 89.21%, and 93.63%, respectively, significantly outperforming conventional neural network models. These findings present an innovative and highly effective approach to mixed spectral analysis, with substantial potential for advancing applicati

关键词： Feature Selection

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Causes of Differences in the Tropical Pacific SST Warming Pattern Projected by CMIP6 Models

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Advances in Atmospheric Sciences 2025年第06期 1077-1091页

作者： Jun YING Matthew COLLINS Robin CHADWICK Shangfeng CHEN Xiaoming HU Tao LIAN Shangmin LONG State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural Resources Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) Department of Mathematics and Statistics University of Exeter Met Office Hadley Centre Center for Monsoon System Research Institute of Atmospheric Physics Chinese Academy of Sciences School of Atmospheric Sciences Sun Yat-sen University School of Oceanography Shanghai Jiao Tong University Key Laboratory of Marine Hazards Forecasting Ministry of Natural Resources Hohai University College of Oceanography Hohai University

The inter-model difference in the tropical Pacific SST warming pattern is a big stumbling block for reliable projections of global climate change. Here by conducting an inter-model Empirical Orthogonal Function(EOF) analysis as well as an ocean mixed-layer heat budget, we find that the first two modes of inter-model difference in the SST warming pattern projected by 30 CMIP6 models, explaining more than three-quarters of the total inter-model variance, are both tied to different cloud–radiation feedbacks. The EOF1 mode that captures the different magnitudes of El Ni?o-like warming as well as the largest inter-model variance in the far eastern equatorial Pacific, is likely driven by highly diverse cloud–radiation feedbacks in the east and, to a lesser extent, by differing changes in the oceanic vertical temperature gradient. The EOF2 mode that mainly represents the different magnitudes of SST warming in the western equatorial Pacific, is associated with differing levels of negative cloud–radiation feedback over the central equatorial Pacific through a dynamic air–sea coupled process involving both the Bjerknes feedback and the wind–evaporation–SST *** in isolation the robust common model bias of a weak negative cloud–radiation feedback over the central equatorial Pacific, the projected SST warming in the western equatorial Pacific is likely to be smaller than the multi-model ensemble mean, thereby presenting a more weakeened zonal SST gradient than expected, implying the potential for more severe climate extremes under global warming.

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Monitoring of Fire-Affected Buildings and Air-Quality Assessment: A Remote-Sensing Study Using Ground-Based interferometric Radar and Google-Earth-Engine

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Rangeland Ecology and Management 2025年 101卷 28-42页

作者： Zhang, Hao Zheng, Xiangtian Ghaffar, Bushra Quddoos, Abdul Naz, Iram Aslam, Rana Waqar Fatima, Zoia Abdullah-Al-Wadud, M. Zulqarnain, Rana Muhammad China Academy of Safety Science and Technology Beijing 100012 China Nanjing Institute of Technology School of Computer Engineering Nanjing 211167 China Department of Environmental Science Faculty of Sciences International Islamic University Islamabad 44000 Pakistan State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (LIESMARS) Wuhan University Wuhan 430079 China Department of Software Engineering College of Computer and Information Sciences King Saud University Riyadh 11543 Saudi Arabia Department of Mathematics Saveetha School of Engineering SIMATS Thandalam Tamilnadu Chennai - 602105 India

This study investigates the environmental and structural impacts of crop and rangeland residue burning in Punjab during April and May 2023, utilizing ground-based interferometric radar alongside atmospheric and land use datasets. The radar system was employed to monitor structural deformations in buildings affected by fire, providing critical insights into the broader impacts of the fires on infrastructure. Multiple ground-based interferometric radars for distributed monitoring can effectively obtain the three-dimensional deformation components of structural targets in real fire scenes. The monitoring results conform to the displacement variation law of existing portal steel frame structures during fire deformation, and can provide effective data support for building structure collapse warning under fire. This approach offers a novel method for assessing the structural integrity of buildings during and after fire events, complementing traditional environmental monitoring. Environmental data show a marked increase in atmospheric pollutants such as NO₂, CH₄, and CO in May 2023, directly linked to the residue burning. Active fire data from FIRMS and MODIS revealed a 98% increase in fire events compared to April, while land surface temperature analysis showed a rise of 1.54%, with affected areas reaching up to 45.9°C. LULC analysis indicated a 23.3% decrease in cropland and rangeland areas, reflecting extensive land clearing. These findings highlight the urgent need for sustainable agricultural management and policies to mitigate the environmental and infrastructural damage caused by residue burning in Punjab. © 2025 The Society for Range Management

关键词： Agriculture Fire & Air Quality Distributed monitoring Google Earth Engine Ground-based interferometric radar Sentinel-2

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Security Performance Analysis for MIMO Systems: From Artificial Noise's Power and Dimension Perspective

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IEEE Transactions on Vehicular Technology 2025年

作者： Xu, Panpan Li, Zhenling Li, Chunguo Tan, Weijie Guizhou University School of Mathematics and Statistics Guiyang550025 China Southeast University School of Information Science and Engineering Nanjing210096 China Guizhou University State Key Laboratory of Public Big Data College of Computer Science and Technology Guiyang550025 China

This paper analyzes the influence of power and dimension of artificial noise (AN) on security performance of multiple-input multiple-output (MIMO) system with multiple randomly located eavesdroppers. We derive the closed-form expressions of the secrecy outage probability (SOP) and the optimal secrecy capacity by utilizing the irrelevance among transmission channels, and the orthogonality between AN and the basis vectors of the legitimate channel matrix's null space. We use the Poisson point process to determine the number and location of eavesdroppers, then analyze the security performance of the communication system under the 3D channel condition of probability-based line-of-sight (LoS) or non-line-of-sight (NLoS) channel. The simulation results show the following conclusions. When the AN dimension reaches 1/4 highest dimension (i.e., one quarter of the number of transmitting antennae less than one) and the power splitter factor (PSF) falls in the open interval (0.6, 0.9), we can achieve a trade-off between secrecy capacity and design complexity. © 1967-2012 IEEE.

关键词： Vector spaces

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Optimized thermoelectric generation for efficient low-medium temperature geothermal energy harvesting

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Renewable Energy 2025年 239卷

作者： Khan, Zafar Hayat Xie, Heping Sun, Licheng Yang, Wei Khan, Waqar A. Li, Bixiong Long, Xiting Wang, Jun Li, Cunbao Gao, Mingzhong Ruan, He Center for Applied Mathematics of Guangxi Nanning Normal University Nanning530100 China School of Mathematics and Statistics Nanning Normal University Nanning530100 China Guangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization Institute of Deep Earth Sciences and Green Energy College of Civil and Transportation Engineering Shenzhen University Shenzhen518060 China State Key Laboratory of Hydraulics and Mountain River Engineering College of Water Resource & Hydropower Sichuan University Chengdu610065 China Department of Mechanical Engineering College of Engineering Prince Mohammad Bin Fahd University Al Khobar31952 Saudi Arabia Key Laboratory of Deep Underground Science and Engineering for Ministry of Education Sichuan University Chengdu610065 China

This paper aims to design and evaluate a thermoelectric generation system optimized for low-to-medium temperature geothermal energy, focusing on maximizing power output and system efficiency. A one-dimensional mathematical model based on energy balance is employed for a single thermoelectric element and subsequently scaled to a 600 thermoelectric generators (TEGs) module. The Peltier, Fourier, and Joule heating effects are included in the analysis, whereas the radiation and convection effects are neglected. The impact of various 2D and 3D layouts of thermoelectric generators (TEGs) and temperature variations on power generation and performance is examined. An experiment is performed to observe the power capacity of a module consisting of five thermoelectric generators. These experimental observations validate the analytical model, and reference properties are adopted to predict more complex modules. This work aims to simulate the optimal design of a TEG module, utilizing the temperature difference to generate 1 kW of power. For this purpose, a module comprising of 600 TEGs is analyzed in various layouts. Based on experimental results for the temperature difference ΔT=96.4Co, it is proposed that a compact module consisting of 600 TEGs with a 3D design of 10 × 12 × 5 will be suitable and cost-effective to generate 1 kW power. © 2024 Elsevier Ltd

关键词： Geothermal Modeling Optimization Thermoelectric generator

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TVEG: Model Selection of the Time-Varying Exponential Family Distributions Graphical Models

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IEEE Transactions on Network Science and engineering 2025年

作者： Liu, Juan Mei, Guofeng Xia, Yuanqing Wu, Xiaoqun Lu, Jinhu Beijing Forestry University School of Technology Beijing100107 China Italy Zhongyuan University of Technology Henan 451191 China Wuhan University School of Mathematics and Statistics Wuhan430072 China Beihang University State Key Laboratory of Software Development Environment Beijing Advanced Innovation Center for Big Data and Brain Machine Intelligence School of Automation Science and Electrical Engineering Beijing100191 China

The undirected graphical model, a popular class of statistical model, offers a way to describe and explain the relationships among a set of variables. However, it remains a challenge to choose a certain graphical model to explain the relationships of variables adequately, especially when the relationships of variables are rewiring over time. This paper proposes the Time-Varying Exponential Family Distributions Graphical (TVEG) models, with time-varying structures and exponential family node-wise conditional distributions. TVEG models extend the scope of available graph models and can be applied to time-varying and exponential family distribution observation data in reality. We propose the Temporally Smoothed L1regularized exponential family graphical estimator (TSLEG), an estimator to infer the structure of TVEG from observations. We derive sufficient conditions for the TSLEG to recover the block partition and sparse pattern with high probability. We derive a message-passing optimization method to solve the TSLEG for time-varying Ising, Gaussian, exponential, and Poisson graphs based on the ADMM. The synthetic network simulations corroborate the theoretical analysis. Analysing of real data of stocks and the US Senate by the time-varying exponential model and Poisson model indicates the effectiveness and practicality of TVEG models. © 2025 IEEE. All rights reserved.

关键词： ADMM exponential family distributions Graphical model pseudo maximum likelihood estimation

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Delayed Pinning Control for Synchronization of Dynamical Networks

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IEEE Transactions on Automatic Control 2025年

作者： Zhu, Shuaibing Li, Feng Deng, Zhenhua Lü, Jinhu Hunan Normal University MOE-LCSM School of Mathematics and Statistics Changsha410081 China Anhui University of Technology School of Electrical and Information Engineering Ma'anshan243002 China Central South University School of Automation Changsha410075 China Beihang University School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing100083 China

Though pinning control of dynamical networks with or without delay has been well explored in the past two decades, little attention has been paid to the delay originated from pinning control itself. This paper investigates the delayed pinning control scheme for lag synchronization and lag quasi-synchronization of dynamical networks. Two pinning control schemes with uniform delay and nonuniform delays are proposed, which are more practical than the widely-used delay-free pinning control scheme. For the two pinning control schemes, criteria for lag synchronization and lag quasi-synchronization of dynamical networks are derived by proposing a system of functional differential inequalities, and in the meantime, an upper bound of tolerable delays that allows synchronization is given. In particular, the ultimate bound of the synchronization error is estimated for lag quasi-synchronization. Finally, the theoretical results are demonstrated by two numerical examples. © 1963-2012 IEEE.

关键词： Delay control systems

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Review and Prospect of the Uncertainties in Mathematical Models and Methods for Yellow River Ice

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Water (Switzerland) 2025年第9期17卷 1291-1291页

作者： Tan, Bing Li, Chunjiang Hu, Shengbo Li, Zhijun Ji, Honglan Deng, Yu Zhang, Limin School of Mathematics and Statistics Nanyang Normal University Nanyang473061 China School of Energy and Environment Inner Mongolia University of Science and Technology Baotou014010 China State Key Laboratory of Coastal and Offshore Engineering Dalian University of Technology Dalian116024 China College of Water Conservancy and Civil Engineering Inner Mongolia Agricultural University Hohhot010018 China Yellow River Institute of Hydraulic Research Zhengzhou450003 China

Mathematical models and methods serve as fundamental tools for studying ice-related phenomena in the Yellow River. River ice is driven and constrained by hydrometeorological and geographical conditions, creating a complex system. Regarding the Yellow River, there are some uncertainties that manifest in unique features in this context, including ice–water–sediment mixed transport processes and the distribution of sediment both within the ice and on its surface. These distinctive characteristics are considered to different degrees across different scales. Mathematical models for Yellow River ice developed over the past few decades not only encompass models for the large-scale deterministic evolution of river ice formation and melting, but also uncertainty parameter schemes for deterministic mathematical models reflecting the Yellow River’s particular ice-related characteristics. Moreover, there are modern mathematical results quantitatively describing these characteristics with uncertainty, allowing for a better understanding of the unique ice phenomena in the Yellow River. This review summarizes (a) universal equations established according to thermodynamic and hydrodynamic principles in river ice mathematical models, as well as (b) uncertainty sources caused by the river’s characteristics, ice properties, and hydrometeorological conditions, embedded in parametric schemes reflecting the Yellow River’s ice. The intractable uncertainty-related problems in space–sky–ground telemetric image segmentation and the current status of mathematical processing methods are reviewed. In particular, the current status and difficulties faced by various mathematical models in terms of predicting the freeze-up and break-up times, the formation of ice jams and dams, and the early warning of ice disasters are presented. This review discusses the prospects related to the uncertainties in research results regarding the simulation and prediction of Yellow River ice while also exploring pot

关键词： Analytical models

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Two-mode terms in Wigner transport equation elucidate anomalous thermal transport in amorphous silicon

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Physical Review B 2025年第9期111卷 094206-094206页

作者： Jin Yang Xueyan Zhu Alan J. H. McGaughey Yee Sin Ang Wee-Liat Ong ZJU-UIUC Institute College of Energy Engineering Zhejiang University Jiaxing Haining Zhejiang 314400 China China Academy of Engineering Physics Software Center for High Performance Numerical Simulation Beijing 100088 China Institute of Applied Physics and Computational Mathematics Beijing 100088 China Department of Mechanical Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 USA Science Mathematics and Technology Singapore University of Technology and Design 487372 Singapore State Key Laboratory of Clean Energy Utilization Zhejiang University Hangzhou Zhejiang 310027 China

Over the past decades, our understanding of thermal transport in amorphous materials has predominantly relied on the inherently harmonic Allen-Feldman theory, which has been found to be insufficient. In this study, the Wigner transport formalism is adopted to explicitly account for anharmonicity. In studying the thermal transport in amorphous silicon, the results highlight that amorphous materials are not generally computationally equivalent to crystals with disordered primitive cells. A method that leverages the properties of the two-mode terms in the Wigner transport formalism is proposed to predict the bulk thermal conductivity of amorphous materials using finite-size models. In doing so, the need for mode classification schemes required in the Allen-Feldman theory is eliminated, and similarities are discovered between the two-mode terms and the carriers commonly used to describe thermal transport in amorphous materials, i.e., propagons, diffusons, and locons. Two competing trends are identified that shed light on the recently discovered anomalous decrease in the high-temperature thermal conductivity in some amorphous materials.

关键词： Heat transfer

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Fractional Cattaneo heat equation in a semi-infinite medium

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Chinese Physics B 2013年第1期22卷 338-343页

作者：续焕英齐海涛蒋晓芸 School of Mathematics and Statistics Shandong University Weihai State Key Laboratory for Turbulence and Complex Systems and Department of Mechanics and Aerospace Engineering College of Engineering Peking University School of Mathematics Shandong University

To better describe the phenomenon of non-Fourier heat conduction, the fractional Cattaneo heat equation is introduced from the generalized Cattaneo model with two fractional derivatives of different orders. The anomalous heat conduction under the Neumann boundary condition in a semi-infinity medium is investigated. Exact solutions are obtained in series form of the H-function by using the Laplace transform method. Finally, numerical examples are presented graphically when different kinds of surface temperature gradient are given. The effects of fractional parameters are also discussed.

关键词： Caputo fractional derivative non-Fourier heat conduction Cattaneo equation H-function

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