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Multi-Step Clustering of Smart Meters Time Series:Application to Demand Flexibility Characterization of SME Customers

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 869-907页

作者： Santiago Bañales Raquel Dormido Natividad Duro Department of Computer Sciences and Automatic Control Universidad Nacional de Educación a Distancia(UNED)Madrid28040Spain iberdrola innovation middle east Doha210177Qatar

Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’participation in the energy *** study proposes an innovative multi-step clustering procedure to segment customers based on load-shape patterns at the daily and intra-daily time *** meter data is split between daily and hourly normalized time series to assess monthly,weekly,daily,and hourly seasonality patterns *** dimensionality reduction implicit in the splitting allows a direct approach to clustering raw daily energy time series *** intraday clustering procedure sequentially identifies representative hourly day-unit profiles for each customer and the entire *** the first time,a step function approach is applied to reduce time series *** attributes embedded in surveys are employed to build external clustering validation metrics using Cramer’s V correlation factors and to identify statistically significant determinants of load-shape in energy *** addition,a time series features engineering approach is used to extract 16 relevant demand flexibility indicators that characterize customers and corresponding clusters along four different axes:available Energy(E),Temporal patterns(T),Consistency(C),and Variability(V).The methodology is implemented on a real-world electricity consumption dataset of 325 Small and Medium-sized Enterprise(SME)customers,identifying 4 daily and 6 hourly easy-to-interpret,well-defined *** application of the methodology includes selecting key parameters via grid search and a thorough comparison of clustering distances and methods to ensure the robustness of the *** research can test the scalability of the methodology to larger datasets from various customer segments(households and large commercial)and locations with different weather and socioeconomic conditio

关键词： Electric load clustering load profiling smart meters machine learning data mining demand flexibility demand response

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ImSpiRE: image feature-aided spatial resolution enhancement method

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Science China Life Sciences 2025年第1期68卷 272-283页

作者： Yuwei Hua Yizhi Zhang Zhenming Guo Shan Bian Yong Zhang State Key Laboratory of Cardiovascular Diseases and Medical innovation Center Institute for Regenerative MedicineDepartment of NeurosurgeryShanghai East HospitalShanghai Key Laboratory of Signaling and Disease ResearchFrontier Science Center for Stem Cell ResearchSchool of Life Sciences and TechnologyTongji University

The resolution of most spatially resolved transcriptomic technologies usually cannot attain the single-cell level, limiting their applications in biological discoveries. Here, we introduce ImSpiRE, an image feature-aided spatial resolution enhancement method for in situ capturing spatial transcriptome. Taking the information stored in histological images, ImSpiRE solves an optimal transport problem to redistribute the expression profiles of spots to construct new transcriptional profiles with enhanced resolution, together with extending the gene expression profiles into unmeasured regions. Applications to multiple datasets confirm that ImSpiRE can enhance spatial resolution to the subspot level while contributing to the discovery of tissue domains, signaling communication patterns, and spatiotemporal characterization.

关键词： spatial transcriptome histological images spatial resolution enhancement

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Smart Gas Sensors:Recent Developments and Future Prospective

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Nano-Micro Letters 2025年第3期17卷 55-86页

作者： Boyang Zong Shufang Wu Yuehong Yang Qiuju Li Tian Tao Shun Mao College of Environmental Science and Engineering Biomedical Multidisciplinary Innovation Research InstituteShanghai East HospitalState Key Laboratory of Pollution Control and Resource ReuseTongji University1239 Siping RoadShanghai 200092People’s Republic of China Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092People’s Republic of China Microbiome Medicine Center Department of Laboratory MedicineZhujiang HospitalSouthern Medical UniversityGuangzhou 510280People’s Republic of China

Gas sensor is an indispensable part of modern society withwide applications in environmental monitoring,healthcare,food industry,public safety,*** the development of sensor technology,wireless communication,smart monitoring terminal,cloud storage/computing technology,and artificial intelligence,smart gas sensors represent the future of gassensing due to their merits of real-time multifunctional monitoring,earlywarning function,and intelligent and automated *** electronicand optoelectronic gas sensors have been developed for high-performancesmart gas *** the development of smart terminals and the maturityof integrated technology,flexible and wearable gas sensors play an increasingrole in gas *** review highlights recent advances of smart gassensors in diverse *** structural components and fundamentalprinciples of electronic and optoelectronic gas sensors are described,andflexible and wearable gas sensor devices are ***,sensorarray with artificial intelligence algorithms and smart gas sensors in“Internet of Things”paradigm are ***,the challengesand perspectives of smart gas sensors are discussed regarding the future need of gas sensors for smart city and healthy living.

关键词： Smart gas sensor Electronic sensor Optoelectronic sensor Flexible and wearable sensor Artificial intelligence

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Sequence-activated chemiluminescence probes: programmable illumination for high-contrast in vivo sensing and imaging

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Science China Chemistry 2025年第1期68卷 26-34页

作者： Yutao Zhang Juan Li Wei-Hong Zhu Zhiqian Guo Shanghai Key Laboratory of Functional Materials Chemistry Joint International Research Laboratory of Precision Chemistry and Molecular Engineering Institute of Fine Chemicals School of Chemistry and Molecular Engineering East China University of Science and Technology State Key Laboratory of Bioreactor Engineering Shanghai Frontier Science Research Base of Optogenetic Techniques for Cell MetabolismEast China University of Science & Technology

Sequence-activated chemiluminescence(CL) technique offers a unique approach to detecting specific biomolecules or cellular events with high sensitivity and spatial resolution. The fundamental principle behind sequence-activated CL probes involves tailoring highly-controllable CL signals in response to specific sequences or events of interest, thus enabling high-contrast signals under complex physiological conditions. This sequential activation could be triggered by enzymes, reactive oxygen species(ROS), biothiols or changes in the microenvironment. These unique sequence-activated CL probes bestow several advantages, including minimal background, deep-tissue penetration, and the ability of non-invasive or minimally invasive detection. The sequence-activated CL techniques represent a significant advancement in molecular imaging and diagnostics. In this mini-review, we focus on the latest developments in sequential CL probes, addressing the technical challenges and discussing the future trajectory by harnessing CL signaling and molecular recognition.

关键词： chemiluminescnece sequence-activation in-vivo bioimaging cyclic peroxide

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Impregnating photo-stable gold precursor onto uncalcined TS-1 to boost catalytic hydro-oxidation of propane

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Science China Chemistry 2025年

作者： Zhihua Zhang Erchuan Yang Fan Liu Kesheng Xu Yuxia Zhong Jinwei Sun Shudong Shi Xuezhi Duan Xinggui Zhou State Key Laboratory of Chemical Engineering East China University of Science and Technology

Immobilizing highly dispersed Au nanoparticles onto titanium silicalite-1 (TS-1) by a simple impregnation method under light is still a challenging *** this work,a high photostable Au precursor protected by thiol ligands was firstly synthesized,and the as-prepared Au precursor displayed excellent stability under light for over 30 days,while the Au precursor without thiol ligands formed precipitates after just 2 h under ***,the Au precursor protected by thiol ligands was immobilized on the external surface of uncalcined TS-1 (i.e.,TS-1-B) by the incipient wetness impregnation method (IWI method) to prepare Au/TS-1-B *** activity of as-prepared Au/TS-1-B catalyst in the hydro-oxidation of propane to acetone was 1.4 times higher than that of the catalyst prepared by the deposition-precipitation urea method (DPU method).The structures of the Au/TS-1-B catalysts prepared by different methods were analyzed by multiple *** to the Au/TS-1-B catalyst prepared by the DPU method,the Au/TS-1-B catalyst synthesized by the IWI method exhibited a narrower size distribution of Au nanoparticles and had more small Au particles (<2 nm),which is the main reason for its superior ***,the effects of gold loadings,reaction temperature and Si/Ti molar ratio on the catalytic performance of the Au/TS-1-B catalyst prepared by the IWI method were also *** addition,the Au/TS-1-B catalyst prepared by the IWI method also exhibited excellent stability for over 140 h.

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Single-cell technologies: current and near future

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Science China Life Sciences 2025年第1期68卷 1-4页

作者： Chenfei Wang Qi Liu Xiaohui Fan Tieliu Shi Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration Ministry of EducationOrthopedics DepartmentTongji HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji University Frontier Science Center for Stem Cells School of Life Sciences and TechnologyTongji University Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine Shanghai East HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji University Research Institute of Intelligent Computing Zhejiang Lab Pharmaceutical Informatics Institute College of Pharmaceutical SciencesZhejiang University National Key Laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River DeltaZhejiang University Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal University Key Laboratory of Advanced Theory and Application in Statistics and Data Science (MOE) School of StatisticsEast China Normal University

Single-cell technologies enable the indepth exploration of multiple biological hierarchies at the scale of individual cells,which have deepened our knowledge of cellular diversity, tissue organization, and overall organism function(Sun et al.,2024). In 2009, single-cell RNA sequencing(sc RNA-seq) was first developed as a powerful tool to dissect gene expression and uncover transcriptional *** the rapid advancement of technology, single-cell approaches have expanded to encompass other omics, such as genomics, epigenomics, proteomics,and metabolomics.

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Domain generalization with semi-supervised learning for people-centric activity recognition

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Science China(Information Sciences) 2025年第1期68卷 171-188页

作者： Jing LIU Wei ZHU Di LI Xing HU Liang SONG Academy for Engineering & Technology Fudan University Shanghai east-bund Research Institute on Networking Systems of AI School of Optoelectronic Information and Computer Engineering University of Shanghai for Science & Technology

People-centric activity recognition is one of the most critical technologies in a wide range of real-world applications,including intelligent transportation systems, healthcare services, and brain-computer interfaces. Large-scale data collection and annotation make the application of machine learning algorithms prohibitively expensive when adapting to new tasks. One way of circumventing this limitation is to train the model in a semi-supervised learning manner that utilizes a percentage of unlabeled data to reduce the labeling burden in prediction tasks. Despite their appeal, these models often assume that labeled and unlabeled data come from similar distributions, which leads to the domain shift problem caused by the presence of distribution gaps. To address these limitations, we propose herein a novel method for people-centric activity recognition,called domain generalization with semi-supervised learning(DGSSL), that effectively enhances the representation learning and domain alignment capabilities of a model. We first design a new autoregressive discriminator for adversarial training between unlabeled and labeled source domains, extracting domain-specific features to reduce the distribution gaps. Second, we introduce two reconstruction tasks to capture the task-specific features to avoid losing information related to representation learning while maintaining task-specific consistency. Finally, benefiting from the collaborative optimization of these two tasks, the model can accurately predict both the domain and category labels of the source domains for the classification task. We conduct extensive experiments on three real-world sensing datasets. The experimental results show that DGSSL surpasses the three state-of-the-art methods with better performance and generalization.

关键词： activity recognition deep learning domain generalization semi-supervised learning adversarial training

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Mainchain conformation ordering self-assembly tailored room temperature phosphorescence emission

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Science China Chemistry 2025年第1期68卷 329-336页

作者： Yuzhu Li Yumeng Gao Feng Tian Yu Wang Yuan Yao Shaoliang Lin Xiang Ma Binbin Xu Shanghai Key Laboratory of Advanced Polymeric Materials Key Laboratory for Ultrafine Materials of Ministry of Education School of Materials Science and Engineering East China University of Science and Technology Shanghai Synchrotron Radiation Facility Shanghai Advanced Research Institute Chinese Academy of Sciences Key Laboratory for Advance Materials and Feringa Noble Prize Scientist Joint Research Centre Frontiers Science for Materiobiology and Dynamic Chemistry School of Chemistry and Molecular Engineering East China University of Science & Technology

Developing organic room-temperature phosphorescence （RTP） materials with a wide range of tunable-emission is significant in expanding the applications of RTP ***,we rationally designed amphiphilic alternating copolymers poly(1,2-bis（4-alkoxyphenyl）ethane-1,2-dione-alt-（ethylene glycol）x)(P（Bz-alt-EGx）) that combined the advantage of alternating benzil and EGxskeleton,and tunable mainchain *** a mainchain conformation ordering assembly （COA） process,P（Bz-alt-EGx） self-assembled into well-defined platelets,and such assemblies emitted blue RTP at ca.425 nm due to the ordered folded-chain conformation and confined *** contrast,traditional self-assembly （TA） of P（Bz-alt-EGx） obtained less ordered aggregates,such as asymmetric worms,vesicles,and rod-like *** resultant less ordered aggregates exhibited yellow-green RTP at ca.550 *** wide-tuning RTP emission in solution （between blue and yellow-green,over125 nm） is realized using the P（Bz-alt-EGx） alternating copolymers under the treatment of different self-assembly *** study uncovers a new strategy to tailor the RTP emission through different self-assembly pathways and holds great promise for the fabrication of advanced optical materials.

关键词： self-assembly conformation ordering alternating copolymer phosphorescence emission

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Leveraging ROTI map derived from Indonesian GNSS receiver network for advancing study of Equatorial Plasma Bubble in Southeast/east Asia

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Earth and Planetary Physics 2025年第1期9卷 101-116页

作者： Prayitno Abadi Ihsan N.Muafiry Teguh N.Pratama Angga Y.Putra Suraina Gatot H.Pramono Sidik T.Wibowo Febrylian F.Chabibi Umar A.Ahmad Wildan P.Tresna Asnawi Research Center for Climate and Atmosphere Indonesian National Research and Innovation Agency(BRIN)BandungIndonesia School of Electrical Engineering Telkom UniversityBandungIndonesia Directorate of Laboratory Management Facilities and Science and Technology Park Indonesian National Research and Innovation Agency(BRIN)PontianakIndonesia Geophysics Laboratory Master Program in PhysicsUniversitas Gadjah Mada(UGM)YogyakartaIndonesia Research Center for Space Indonesian National Research and Innovation Agency(BRIN)BandungIndonesia Indonesian Geospatial Information Agency(BIG) JakartaIndonesia Research Center for Photonics Indonesian National Research and Innovation Agency(BRIN)Tangerang SelatanIndonesia Department of Earth and Planetary Sciences Hokkaido UniversitySapporoJapan

This paper highlights the crucial role of Indonesia’s GNSS receiver network in advancing Equatorial Plasma Bubble(EPB)studies in Southeast and east Asia,as ionospheric irregularities within EPB can disrupt GNSS signals and degrade positioning *** by the Indonesian Geospatial Information Agency(BIG),the Indonesia Continuously Operating Reference Station(Ina-CORS)network comprises over 300 GNSS receivers spanning equatorial to southern low-latitude ***-CORS is uniquely situated to monitor EPB generation,zonal drift,and dissipation across Southeast *** provide a practical tool for EPB research,by sharing two-dimensional rate of Total Electron Content(TEC)change index(ROTI)derived from this *** generate ROTI maps with a 10-minute resolution,and samples from May 2024 are publicly available for further scientific *** preliminary findings from the ROTI maps of Ina-CORS are ***,the Ina-CORS ROTI maps reveal that the irregularities within a broader EPB structure persist longer,increasing the potential for these irregularities to migrate farther ***,we demonstrate that combined ROTI maps from Ina-CORS and GNSS receivers in east Asia and Australia can be used to monitor the development of ionospheric irregularities in Southeast and east *** have demonstrated the combined ROTI maps to capture the development of ionospheric irregularities in the Southeast/east Asian sector during the G5 Geomagnetic Storm on May 11,*** observed simultaneous ionospheric irregularities in Japan and Australia,respectively propagating northwestward and southwestward,before midnight,whereas Southeast Asia’s equatorial and low-latitude regions exhibited irregularities *** sharing ROTI maps from Indonesia and integrating them with regional GNSS networks,researchers can conduct comprehensive EPB studies,enhancing the understanding of EPB behavior across Southeast and east Asia and contributing significantly to ionosphe

关键词： Equatorial Plasma Bubble(EPB) GNSS receivers’network Indonesia Continuously Operating Reference Station(Ina-CORS) ionospheric map Rate of TEC change index(ROTI)map

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A robust statistical prediction model for late-summer heavy precipitation days in North China

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Science China Earth Sciences 2025年第1期68卷 158-171页

作者： Shunli JIANG Tingting HAN Xin ZHOU Huijun WANG Zhicong YIN Xiaolei SONG Collaborative innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education Nanjing University for Information Science and Technology Nansen-Zhu International Research Centre Institute of Atmospheric Physics Chinese Academy of Sciences Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)

Recently, heavy precipitation(HP) events have occurred frequently in North China(NC), causing devastating economic losses and human fatalities. However, the short-term climate prediction of HP is quite limited. Combining year-to-year increment(DY) method and sliding correlations, we developed a robust seasonal prediction model for late-summer HP days(HPDs) in NC during 1982–2022, utilizing three independent predictors—February sea surface temperature(SST) in the Indian Ocean(SST＿IO), February snow depth over North Asia(SDE＿NA), and May melted snow depth in NC(MSDE＿NC). The SST＿IO anomalies affect NC's precipitation through the Pacific-Japan pattern. The SDE＿NA anomalies are associated with east Asian anomalous anticyclone by southeastern propagation of Rossby wave at Eurasia. The MSDE＿NC anomalies are followed by vertical motion and moisture anomalies in situ and thereby cause precipitation anomalies. This prediction model can well simulate the variations of the HPDs, with a correlation coefficient(CC) of 0.81(0.65) between the observed and predicted HPDs＿DY(HPDs＿anomaly). The percentage with the same sign for 15 extreme HPDs＿anomaly years(PSSE) is 100%.Moreover, in the cross-validation test during 1982–2022, the PSSE for HPDs＿anomaly is as high as 100%, along with a low rootmean-square error of 1.14. For independent hindcasts during 2013–2022, the CC between the observed and predicted HPDs＿DY(HPDs＿anomaly) is 0.93(0.83), together with high Nash-Sutcliffe efficiency(0.82) and agreement index(0.89). Specifically, the predictions are broadly consistent with the observations for 2015, 2016, 2017, 2021, and 2022, reflecting excellent performance of this prediction model of HPDs in NC.

关键词： Heavy precipitation at North China Year-to-year increment approach Robust seasonal prediction Sea surface temperature Snow depth

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