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Chemistry-driven mass spectrometry for structural lipidomics at the C=C bond isomer level

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Chinese Chemical Letters 2025年第1期36卷 225-233页

作者： Junmeng Luo Qiongqiong Wan Suming Chen The institute for Advanced studies Wuhan UniversityWuhan 430072China

As more and more studies have shown that lipid molecules play an important role in the whole biology,in-depth analysis of lipid structure has become particularly important in *** spectrometry(MS),as the preferred tool for lipid analysis,has greatly promoted the development of this ***,the existing MS methods still face many difficulties in the in-depth or even comprehensive analysis of lipid *** this review,we discuss recent advances in MS methods based on double bond-specific chemistries for the resolving of C=C location and geometry isomers of *** progress has greatly advanced the lipidomics analysis to a deeper structural level and facilitated the development of structural lipid biology.

关键词： Mass spectrometry Structural lipidomics Lipid isomers Double bond location Double bond configuration Chemical derivatization

An Enhanced Lung Cancer Detection Approach Using Dual-Model Deep Learning Technique

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 835-867页

作者： Sumaia Mohamed Elhassan Saad Mohamed Darwish Saleh Mesbah Elkaffas Department of Information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandria21526Egypt College of Computing and Information Technology Arab Academy for ScienceTechnology and Maritime TransportAlexandriaP.O.Box 1029Egypt

Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic *** detection of lung tumors significantly increases the chances of successful treatment and ***,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung ***-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate ***,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor *** overcome these disadvantages,dual-model or multi-model approaches can be *** research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of *** automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung ***8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single *** is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to ***,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive *** combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applicati

关键词： Lung cancer detection dual-model deep learning technique data augmentation CNN YOLOv8

Improving Model Chain Approaches for Probabilistic Solar Energy Forecasting through Post-processing and Machine Learning

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Advances in Atmospheric Sciences 2025年第2期42卷 297-312页

作者： Nina HORAT Sina KLERINGS Sebastian LERCH institute of Statistics Karlsruhe Institute of TechnologyKarlsruhe 76185Germany Heidelberg institute for Theoretical studies Heidelberg 69118Germany

Weather forecasts from numerical weather prediction models play a central role in solar energy forecasting,where a cascade of physics-based models is used in a model chain approach to convert forecasts of solar irradiance to solar power *** simulations from such weather models aim to quantify uncertainty in the future development of the weather,and can be used to propagate this uncertainty through the model chain to generate probabilistic solar energy ***,ensemble prediction systems are known to exhibit systematic errors,and thus require post-processing to obtain accurate and reliable probabilistic *** overarching aim of our study is to systematically evaluate different strategies to apply post-processing in model chain approaches with a specific focus on solar energy:not applying any post-processing at all;post-processing only the irradiance predictions before the conversion;post-processing only the solar power predictions obtained from the model chain;or applying post-processing in both *** a case study based on a benchmark dataset for the Jacumba solar plant in the U.S.,we develop statistical and machine learning methods for postprocessing ensemble predictions of global horizontal irradiance(GHI)and solar power ***,we propose a neural-network-based model for direct solar power forecasting that bypasses the model *** results indicate that postprocessing substantially improves the solar power generation forecasts,in particular when post-processing is applied to the power *** machine learning methods for post-processing slightly outperform the statistical methods,and the direct forecasting approach performs comparably to the post-processing strategies.

关键词： solar forecasting post-processing probabilistic forecasting machine learning model chain

Distribution and mapping of temperate savanna in the sandy lands of eastern China

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Science China Earth Sciences 2025年第1期68卷 128-141页

作者： Xiaoya LI Feng WANG Tao DUAN Kaijie YANG Bin YANG Chunmei WANG Xin TIAN Qi LU institute of Ecological Conservation and Restoration Institute of Desertification StudiesChinese Academy of ForestryBeijing100091China institute of Desertification Institute of Desertification StudiesChinese Academy of ForestryBeijing100091China institute of Great Green Wall Bayan Nur015200China Satellite Application Centre for Ecology and Environment MEEBeijing100094China institute of Microelectronics Chinese Academy of SciencesBeijing100029China Aerospace Information Research institute Chinese Academy of SciencesBeijing100094China institute of Forest Resource Information Techniques Chinese Academy of ForestryBeijing100091China

Savannas are distributed globally across various *** perform a significant socioeconomic role in regulating net primary productivity and the terrestrial carbon *** to the high spatial heterogeneity induced by the mixed distribution of trees and grasses,current global land-cover classification maps often classify savannas as forests or grasslands Temperate savannas in China cover a vast area,yet their spatial patterns and extent remain poorly *** study developed a novel remote sensing temperate savannas mapping method by integrating very high-resolution(VHR)unmanned aerial vehicle(UAV)and GF-6 satellite imagery based on the vegetation structure characteristics of temperate savannas using the FAO definition of *** and validation datasets were collected from VHR UAV imagery covering the main temperate savannah types with a ground area of 1818 *** fractional woody vegetation cover(FWVC)and fractional herbaceous vegetation cover(FHVC)in temperate savannas were estimated by integrating Classification and Regression Tree and Random Forest *** current distribution of temperate savannas in the Horqin and Otindag Sandy Lands of Eastern China was mapped to a unit area of 0.5 *** root-mean-square error(RMSE)values for the FWVC and FHVC models were 10.69%and 11.67%,and the R^(2)values were 0.66 and 0.63,*** assessment indicated that the new temperate savanna map had high identification accuracy,with a Kappa coefficient of 0.70,overall accuracy of 0.88,and average accuracy of *** savannas in the sandy lands of eastern China were primarily distributed in the northern Horqin Sandy Land the central and eastern regions of the Otindag Sandy Land,and the transition zone from the southern slopes of the Greater Khingan Mountains to the plains,covering a total area of 3.27×10^(6)*** main savannah types were elm,oak/maple,and shrub *** savannas were widely distributed in the Otindag Sandy Land a

关键词： Temperate savanna UAV imagery GF-6 Fractional woody vegetation cover Fractional herbaceous vegetation cover Machine learning

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Finite-Time Stability of Impulsive and Switched Hybrid Systems With Delay-Dependent Impulses

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 466-468页

作者： Taixiang Zhang Jinde Cao Mahmoud Abdel-Aty Ardak Kashkynbayev the School of Mathematics Southeast University IEEE the Deanship of graduate studies and Scientific Research Ahlia University the Jadara Research Center Jadara University the Department of Mathematics Nazarbayev University

Dear Editor,This letter studies finite-time stability (FTS) of impulsive and switched hybrid systems with delay-dependent impulses. Some conditions, based on Lyapunov method, are proposed for ensuring FTS and estimating settling-time function (STF) of the hybrid *** switching dynamics are FTS and impulsive dynamics involve destabilizing delay-dependent impulses, the FTS is retained if the impulses occur infrequently.

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Nickel-catalyzed ligand-controlled switchable skeletal rearrangements:divergent synthesis of isoquinoline-1,3-diones,cyclohexenols,cycloheptenols,and 2-benzazepin-5-ones

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Science China Chemistry 2025年

作者： Yongli Liu Yuanyuan Ping Wangqing Kong The institute for Advanced studies (IAS) Wuhan University

Skeleton diversity is an important feature of compound libraries and plays a key role in the success of biological ***-controlled divergent synthesis can transform the same substrate into different molecular skeletons, which not only can endow compound libraries with diverse biological activities but also reveal new catalytic modes, and therefore has received extensive attention. Herein, we disclose a Ni-catalyzed, ligand-controlled switchable skeletal rearrangement reaction of acryloyl o-bromobenzamides and activated alkenes. In this protocol, modification of the ligand backbone allows the conversion of the same starting material into four structurally distinct scaffolds of pharmacological importance. Specifically, the use of terpyridine ligand favors the 6-exo cyclization and subsequent 1,2-acyl/Ni dyotropic rearrangement to generate highly functionalized cyclohexenols, while the sterically hinderediPrPDI ligand facilitates the 6-exo cyclization and subsequent 1,2-aryl/Ni dyotropic rearrangement to form highly functionalized cycloheptenols. Furthermore, isoquinoline-1,3-diones were obtained through alkene diarylation in the absence of additional activated alkenes. More strikingly, the bidentate ligand promotes nucleophilic addition of the aryl halides to the amide carbonyl, followed by 1,4-acyl transfer and cross-coupling to afford 2-benzazepin-5-ones.

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Liquid metal catalyst for ammonia synthesis at low pressure

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Science China Materials 2025年第2期68卷 681-682页

作者： Ziyue Zeng Chenyang Wang Lei Fu College of Chemistry and Molecular Sciences Wuhan UniversityWuhan 430072China The institute for Advanced studies Wuhan UniversityWuhan 430072China

Liquid metal(LM)has attracted immense interest as a novel catalyst in the past few years for its distinctive physicochemical properties,encompassing superior electrical and thermal conductivities,as well as exceptional fluidity characteristics at low temperatures[1].In contrast to conventional solid heterogeneous catalysts,the fluidic characteristics of liquid metal catalysts enhance the interaction between catalysts and reactants,boosting mass transfer at the reaction interface.

关键词： catalyst ammonia synthesis

In vivo direct neuronal conversion as a therapeutic strategy for ischemic stroke

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Neural Regeneration Research 2025年第8期20卷 2309-2310页

作者： Takashi Irie Taito Matsuda Department of Stem Cell Biology and Medicine Graduate School of Medical SciencesKyushu UniversityFukuokaJapan Department of Neurology Neurological InstituteGraduate School of Medical SciencesKyushu UniversityFukuokaJapan

Stroke causes neuronal loss,which ultimately results in persistent neurological ***,stroke was the third-leading cause of death and disability combined in all ages in 2019,after neonatal disorders and ischemic heart *** that year,there were 12.2 million incident strokes,101 million prevalent strokes,and 143 million disability-adjusted life-years due to stroke.

关键词： neonatal death therapeutic

Relativistic two-fluid hydrodynamics with quantized vorticity from the nonlinear Klein–Gordon equation

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Communications in Theoretical Physics 2025年第2期77卷 161-171页

作者： Chi Xiong Kerson Huang Minjiang Collaborative Center for Theoretical Physics Minjiang University institute of Advanced studies & School of Physical and Mathematical Science Nanyang Technological University Physics Department Massachusetts Institute of Technology Cambridge

We consider a relativistic two-fluid model of superfluidity, in which the superfluid is described by an order parameter that is a complex scalar field satisfying the nonlinear Klein–Gordon equation(NLKG). The coupling to the normal fluid is introduced via a covariant current–current interaction, which results in the addition of an effective potential, whose imaginary part describes particle transfer between superfluid and normal fluid. Quantized vorticity arises in a class of singular solutions and the related vortex dynamics is incorporated in the modified NLKG,facilitating numerical analysis which is usually very complicated in the phenomenology of vortex filaments. The dual transformation to a string theory description(Kalb–Ramond) of quantum vorticity, the Magnus force, and the mutual friction between quantized vortices and normal fluid are also studied.

关键词： relativistic superfluidity nonlinear Klein-Gordon field theory quantized vortices two-fluid model Kalb-Ramond field global string