[
    {
        "id": "authors:mgdxg-dad78",
        "collection": "authors",
        "collection_id": "mgdxg-dad78",
        "cite_using_url": "https://authors.library.caltech.edu/records/mgdxg-dad78",
        "type": "article",
        "title": "Permanent fluidic magnets for liquid bioelectronics",
        "author": [
            {
                "family_name": "Zhao",
                "given_name": "Xun",
                "orcid": "0000-0001-5543-0081",
                "clpid": "Zhao-Xun"
            },
            {
                "family_name": "Zhou",
                "given_name": "Yihao",
                "orcid": "0000-0002-7299-5911",
                "clpid": "Zhou-Yihao"
            },
            {
                "family_name": "Song",
                "given_name": "Yang",
                "orcid": "0000-0001-8026-9293",
                "clpid": "Song-Yang"
            },
            {
                "family_name": "Xu",
                "given_name": "Jing",
                "clpid": "Xu-Jing"
            },
            {
                "family_name": "Li",
                "given_name": "Justin",
                "clpid": "Li-Justin"
            },
            {
                "family_name": "Tat",
                "given_name": "Trinny",
                "orcid": "0000-0002-9068-8325",
                "clpid": "Tat-Trinny"
            },
            {
                "family_name": "Chen",
                "given_name": "Guorui",
                "clpid": "Chen-Guorui"
            },
            {
                "family_name": "Li",
                "given_name": "Song",
                "orcid": "0000-0002-4760-8828",
                "clpid": "Li-Song"
            },
            {
                "family_name": "Chen",
                "given_name": "Jun",
                "orcid": "0000-0002-3439-0495",
                "clpid": "Chen-Jun"
            }
        ],
        "abstract": "<div class=\"c-article-section\">\n<div class=\"c-article-section__content\">\n<p>Brownian motion allows microscopically dispersed nanoparticles to be stable in ferrofluids, as well as causes magnetization relaxation and prohibits permanent magnetism. Here we decoupled the particle Brownian motion from colloidal stability to achieve a permanent fluidic magnet with high magnetization, flowability and reconfigurability. The key to create such permanent fluidic magnets is to maintain a stable magnetic colloidal fluid by using non-Brownian magnetic particles to self-assemble a three-dimensional oriented and ramified magnetic network structure in the carrier fluid. This structure has high coercivity and permanent magnetization, with long-term magnetization stability. We establish a scaling theory model to decipher the permanent fluid magnet formation criteria and formulate a general assembly guideline. Further, we develop injectable and retrievable permanent-fluidic-magnet-based liquid bioelectronics for highly sensitive, self-powered wireless cardiovascular monitoring. Overall, our findings highlight the potential of permanent fluidic magnets as an ultrasoft material for liquid devices and systems, from bioelectronics to robotics.</p>\n</div>\n</div>",
        "doi": "10.1038/s41563-024-01802-6",
        "issn": "1476-1122",
        "publisher": "Nature Publishing Group",
        "publication": "Nature Materials",
        "publication_date": "2024-05",
        "series_number": "5",
        "volume": "23",
        "issue": "5",
        "pages": "703-710"
    },
    {
        "id": "authors:8gchc-jax79",
        "collection": "authors",
        "collection_id": "8gchc-jax79",
        "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20211202-191325598",
        "type": "article",
        "title": "3-Dimensional electrical impedance spectroscopy for in situ endoluminal mapping of metabolically active plaques",
        "author": [
            {
                "family_name": "Abiri",
                "given_name": "Parinaz",
                "orcid": "0000-0002-0520-6863",
                "clpid": "Abiri-Parinaz"
            },
            {
                "family_name": "Luo",
                "given_name": "Yuan",
                "clpid": "Luo-Yuan"
            },
            {
                "family_name": "Huang",
                "given_name": "Zi-Yu",
                "clpid": "Huang-Zi-Yu"
            },
            {
                "family_name": "Cui",
                "given_name": "Qingyu",
                "clpid": "Cui-Qingyu"
            },
            {
                "family_name": "Duarte-Vogel",
                "given_name": "Sandra",
                "clpid": "Duarte-Vogel-Sandra"
            },
            {
                "family_name": "Roustaei",
                "given_name": "Mehrdad",
                "clpid": "Roustaei-Mehrdad"
            },
            {
                "family_name": "Chang",
                "given_name": "Chih-Chiang",
                "clpid": "Chang-Chih-Chiang"
            },
            {
                "family_name": "Xiao",
                "given_name": "Xiao",
                "clpid": "Xiao-Xiao"
            },
            {
                "family_name": "Packard",
                "given_name": "Rene",
                "orcid": "0000-0002-8520-5843",
                "clpid": "Packard-Ren\u00e9-Rupen-Sevag"
            },
            {
                "family_name": "Cavallero",
                "given_name": "Susana",
                "orcid": "0000-0001-5402-8840",
                "clpid": "Cavallero-Susana"
            },
            {
                "family_name": "Ebrahimi",
                "given_name": "Ramin",
                "clpid": "Ebrahimi-Ramin"
            },
            {
                "family_name": "Benharash",
                "given_name": "Peyman",
                "clpid": "Benharash-Peynam"
            },
            {
                "family_name": "Chen",
                "given_name": "Jun",
                "clpid": "Chen-Jun"
            },
            {
                "family_name": "Tai",
                "given_name": "Yu-Chong",
                "orcid": "0000-0001-8529-106X",
                "clpid": "Tai-Yu-Chong"
            },
            {
                "family_name": "Hsiai",
                "given_name": "Tzung K.",
                "orcid": "0000-0003-1734-0792",
                "clpid": "Hsiai-Tzung-K"
            }
        ],
        "abstract": "Electrical impedance spectroscopy (EIS) has been recognized to characterize oxidized low-density lipoprotein (oxLDL) in the metabolically active plaque. However, intravascular deployment of 3-D EIS-derived electrical impedance tomography (EIT) for endoluminal mapping of oxLDL-laden arterial walls remains an unmet clinical challenge. To this end, we designed the 6-point microelectrode arrays that were circumferentially configurated onto the balloon catheter for 15 intravascular EIS permutations. In parallel, we created the metabolically active plaques by performing partial ligation of right carotid artery in Yorkshire mini-pigs (n = 6 males), followed by demonstrating the plaque progression at baseline, 8 weeks, and 16 weeks of high-fat diet via computed tomography (CT) angiogram. Next, we deployed the 3-D EIS sensors to the right and left carotid arteries, and we demonstrated 3-D EIS mapping of metabolically active endolumen in the right but not left carotid arteries as evidenced by the positive E06 immunostaining for oxLDL-laden regions. By considering electrical conductivity (\u03c3) and permittivity (\u03b5) properties of collagen, lipid, and smooth muscle presence in the arterial wall, we further validated the 3-D EIS-derived EIT by reconstructing the histology of right and left carotid arteries for the finite element modeling of the oxLDL-laden endolumen, and we accurately predicted 3-D EIS mapping. Thus, we establish the capability of 3-D EIS-derived EIT to detect oxLDL-laden arterial walls with translational implication to predict metabolically active plaques prone to acute coronary syndromes or stroke.",
        "doi": "10.1016/j.snb.2021.131152",
        "issn": "0925-4005",
        "publisher": "Elsevier",
        "publication": "Sensors and Actuators B: Chemical",
        "publication_date": "2022-03-01",
        "volume": "354",
        "pages": "Art. No. 131152"
    },
    {
        "id": "authors:qhqv3-3eh17",
        "collection": "authors",
        "collection_id": "qhqv3-3eh17",
        "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20210203-135928428",
        "type": "article",
        "title": "In Vivo Intravascular Pacing Using a Wireless Microscale Stimulator",
        "author": [
            {
                "family_name": "Abiri",
                "given_name": "Parinaz",
                "orcid": "0000-0002-0520-6863",
                "clpid": "Abiri-Parinaz"
            },
            {
                "family_name": "Duarte-Vogel",
                "given_name": "Sandra",
                "clpid": "Duarte-Vogel-Sandra"
            },
            {
                "family_name": "Chou",
                "given_name": "Tzu-Chieh",
                "orcid": "0000-0002-6074-8286",
                "clpid": "Chou-Tzu-Chieh"
            },
            {
                "family_name": "Abiri",
                "given_name": "Arash",
                "clpid": "Abiri-Arash"
            },
            {
                "family_name": "Gudapati",
                "given_name": "Varun",
                "orcid": "0000-0003-0134-7236",
                "clpid": "Gudapati-Varun"
            },
            {
                "family_name": "Yousefi",
                "given_name": "Alireza",
                "orcid": "0000-0002-6814-4452",
                "clpid": "Yousefi-Alireza"
            },
            {
                "family_name": "Roustaei",
                "given_name": "Mehrdad",
                "clpid": "Roustaei-Mehrdad"
            },
            {
                "family_name": "Chang",
                "given_name": "Chih-Chiang",
                "clpid": "Chang-Chih-Chiang"
            },
            {
                "family_name": "Cui",
                "given_name": "Qingyu",
                "clpid": "Cui-Qingyu"
            },
            {
                "family_name": "Hsu",
                "given_name": "Jeffrey J.",
                "orcid": "0000-0002-9971-5916",
                "clpid": "Hsu-Jeffrey-J"
            },
            {
                "family_name": "Bersohn",
                "given_name": "Malcolm",
                "clpid": "Bersohn-Malcolm"
            },
            {
                "family_name": "Markovic",
                "given_name": "Dejan",
                "clpid": "Markovic-Dejan"
            },
            {
                "family_name": "Chen",
                "given_name": "Jun",
                "clpid": "Chen-Jun"
            },
            {
                "family_name": "Tai",
                "given_name": "Yu-Chong",
                "orcid": "0000-0001-8529-106X",
                "clpid": "Tai-Yu-Chong"
            },
            {
                "family_name": "Hsiai",
                "given_name": "Tzung K.",
                "orcid": "0000-0003-1734-0792",
                "clpid": "Hsiai-Tzung-K"
            }
        ],
        "abstract": "Millions of patients worldwide are implanted with permanent pacemakers for the treatment of cardiac arrhythmias and conduction disorders. The increased use of these devices has established a growing clinical need to mitigate associated complications. Pacemaker leads, in particular, present the primary risks in most implants. While wireless power transfer holds great promise in eliminating implantable device leads, anatomical constraints limit efficient wireless transmission over the necessary operational range. We thereby developed a transmitter-centered control system for wireless power transfer with sufficient power for continuous cardiac pacing. Device safety was validated using a computational model of the system within an MRI-based anatomical model. The pacer was then fabricated to meet the acute constraints of the anterior cardiac vein (ACV) to enable intravascular deployment while maintaining power efficiency. Our computational model revealed the wireless system to operate at &gt;\u200950 times below the tissue energy absorption safety criteria. We further demonstrated the capacity for ex vivo pacing of pig hearts at 60 beats per minute (BPM) and in vivo pacing at 120 BPM following pacer deployment in the ACV. This work thus established the capacity for wireless intravascular pacing with the potential to eliminate complications associated with current lead-based deep tissue implants.",
        "doi": "10.1007/s10439-021-02729-8",
        "issn": "0090-6964",
        "publisher": "Springer",
        "publication": "Annals of Biomedical Engineering",
        "publication_date": "2021-09",
        "series_number": "9",
        "volume": "49",
        "issue": "9",
        "pages": "2094-2102"
    },
    {
        "id": "authors:9xshm-4hg97",
        "collection": "authors",
        "collection_id": "9xshm-4hg97",
        "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20210506-101710133",
        "type": "article",
        "title": "Short-term load forecasting of industrial customers based on SVMD and XGBoost",
        "author": [
            {
                "family_name": "Wang",
                "given_name": "Yuanyuan",
                "orcid": "0000-0002-9575-3712",
                "clpid": "Wang-Yuanyuan"
            },
            {
                "family_name": "Sun",
                "given_name": "Shanfeng",
                "orcid": "0000-0002-9120-357X",
                "clpid": "Sun-Shanfeng"
            },
            {
                "family_name": "Chen",
                "given_name": "Xiaoqiao",
                "orcid": "0000-0003-4685-3466",
                "clpid": "Chen-Xiaoqiao"
            },
            {
                "family_name": "Zeng",
                "given_name": "Xiangjun",
                "clpid": "Zeng-Xiangjun"
            },
            {
                "family_name": "Kong",
                "given_name": "Yang",
                "orcid": "0000-0002-3817-9785",
                "clpid": "Kong-Yang"
            },
            {
                "family_name": "Chen",
                "given_name": "Jun",
                "clpid": "Chen-Jun"
            },
            {
                "family_name": "Guo",
                "given_name": "Yongsheng",
                "orcid": "0000-0003-4235-9807",
                "clpid": "Guo-Yongsheng"
            },
            {
                "family_name": "Wang",
                "given_name": "Tingyuan",
                "clpid": "Wang-Tingyuan"
            }
        ],
        "abstract": "The electricity consumption by industrial customers in the society accounts for a significant proportion of the total electrical energy. Thus, it is of great significance for demand-side electrical energy management to develop an accurate method for short-term load forecasting for industrial customers. Unlike traditional load forecasting on system-level, the load forecasting of individual industrial customer is more challenging due to its significant volatility and uncertainty. We propose an adaptive decomposition method based on VMD and SampEn (SVMD) to decompose the raw load data into a trend series and a set of fluctuation sub-series, and then establish the corresponding prediction model (line regression model for the trend series and XGBoost regression model for each fluctuation sub-series). The hyper-parameters of XGBoost are optimized by bayesian optimization algorithm (BOA). Furthermore, relevant factors that affect the electricity consumption behavior of industrial customers are considered in order to further improve the accuracy of the hybrid method. The proposed method is tested in multiple scenarios with different industrial customers of China and Irish. The results show that the proposed model has significantly improved performance over the contrast models in state-of-the-art load forecasting.",
        "doi": "10.1016/j.ijepes.2021.106830",
        "issn": "0142-0615",
        "publisher": "Elsevier",
        "publication": "International Journal of Electrical Power and Energy Systems",
        "publication_date": "2021-07",
        "volume": "129",
        "pages": "Art. No. 106830"
    },
    {
        "id": "authors:pdx78-8ax02",
        "collection": "authors",
        "collection_id": "pdx78-8ax02",
        "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20210519-141319478",
        "type": "article",
        "title": "Coal fly ash is a major carbon flux in the Chang Jiang (Yangtze River) basin",
        "author": [
            {
                "family_name": "Li",
                "given_name": "Gen K.",
                "orcid": "0000-0002-6300-3570",
                "clpid": "Li-Gen-K"
            },
            {
                "family_name": "Fischer",
                "given_name": "Woodward W.",
                "orcid": "0000-0002-8836-3054",
                "clpid": "Fischer-W-W"
            },
            {
                "family_name": "Lamb",
                "given_name": "Michael P.",
                "orcid": "0000-0002-5701-0504",
                "clpid": "Lamb-M-P"
            },
            {
                "family_name": "West",
                "given_name": "A. Joshua",
                "orcid": "0000-0001-6909-1471",
                "clpid": "West-A-Joshua"
            },
            {
                "family_name": "Zhang",
                "given_name": "Ting",
                "clpid": "Zhang-Ting"
            },
            {
                "family_name": "Galy",
                "given_name": "Valier",
                "orcid": "0000-0003-0385-8443",
                "clpid": "Galy-Valier"
            },
            {
                "family_name": "Wang",
                "given_name": "Xingchen Tony",
                "orcid": "0000-0001-5316-789X",
                "clpid": "Wang-Xingchen-Tony"
            },
            {
                "family_name": "Li",
                "given_name": "Shilei",
                "orcid": "0000-0001-7053-2828",
                "clpid": "Li-Shilei"
            },
            {
                "family_name": "Qiu",
                "given_name": "Hongrui",
                "orcid": "0000-0002-4219-0039",
                "clpid": "Qiu-Hongrui"
            },
            {
                "family_name": "Li",
                "given_name": "Gaojun",
                "orcid": "0000-0002-2463-0774",
                "clpid": "Li-Gaojun"
            },
            {
                "family_name": "Zhao",
                "given_name": "Liang",
                "clpid": "Zhao-Liang"
            },
            {
                "family_name": "Chen",
                "given_name": "Jun",
                "orcid": "0000-0002-3480-5961",
                "clpid": "Chen-Jun"
            },
            {
                "family_name": "Ji",
                "given_name": "Junfeng",
                "clpid": "Ji-Junfeng"
            }
        ],
        "abstract": "Fly ash\u2014the residuum of coal burning\u2014contains a considerable amount of fossilized particulate organic carbon (FOC_(ash)) that remains after high-temperature combustion. Fly ash leaks into natural environments and participates in the contemporary carbon cycle, but its reactivity and flux remained poorly understood. We characterized FOC_(ash) in the Chang Jiang (Yangtze River) basin, China, and quantified the riverine FOC_(ash) fluxes. Using Raman spectral analysis, ramped pyrolysis oxidation, and chemical oxidation, we found that FOC_(ash) is highly recalcitrant and unreactive, whereas shale-derived FOC (FOC_(rock)) was much more labile and easily oxidized. By combining mass balance calculations and other estimates of fly ash input to rivers, we estimated that the flux of FOCash carried by the Chang Jiang was 0.21 to 0.42 Mt C\u22c5y\u207b\u00b9 in 2007 to 2008\u2014an amount equivalent to 37 to 72% of the total riverine FOC export. We attributed such high flux to the combination of increasing coal combustion that enhances FOCash production and the massive construction of dams in the basin that reduces the flux of FOC_(rock) eroded from upstream mountainous areas. Using global ash data, a first-order estimate suggests that FOC_(ash) makes up to 16% of the present-day global riverine FOC flux to the oceans. This reflects a substantial impact of anthropogenic activities on the fluxes and burial of fossil organic carbon that has been made less reactive than the rocks from which it was derived.",
        "doi": "10.1073/pnas.1921544118",
        "pmcid": "PMC8166106",
        "issn": "0027-8424",
        "publisher": "National Academy of Sciences",
        "publication": "Proceedings of the National Academy of Sciences of the United States of America",
        "publication_date": "2021-05-25",
        "series_number": "21",
        "volume": "118",
        "issue": "21",
        "pages": "Art. No. e1921544118"
    },
    {
        "id": "authors:p17n6-54p35",
        "collection": "authors",
        "collection_id": "p17n6-54p35",
        "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20201008-083808624",
        "type": "article",
        "title": "Short-Term Load Forecasting for Industrial Customers Based on TCN-LightGBM",
        "author": [
            {
                "family_name": "Wang",
                "given_name": "Yuanyuan",
                "orcid": "0000-0002-9575-3712",
                "clpid": "Wang-Yuanyuan"
            },
            {
                "family_name": "Chen",
                "given_name": "Jun",
                "orcid": "0000-0001-7095-5142",
                "clpid": "Chen-Jun"
            },
            {
                "family_name": "Chen",
                "given_name": "Xiaoqiao",
                "orcid": "0000-0003-4685-3466",
                "clpid": "Chen-Xiaoqiao"
            },
            {
                "family_name": "Zeng",
                "given_name": "Xiangjun",
                "clpid": "Zeng-Xiangjun"
            },
            {
                "family_name": "Kong",
                "given_name": "Yang",
                "orcid": "0000-0002-3817-9785",
                "clpid": "Kong-Yang"
            },
            {
                "family_name": "Sun",
                "given_name": "Shanfeng",
                "orcid": "0000-0002-9120-357X",
                "clpid": "Sun-Shanfeng"
            },
            {
                "family_name": "Guo",
                "given_name": "Yongsheng",
                "orcid": "0000-0003-4235-9807",
                "clpid": "Guo-Yongsheng"
            },
            {
                "family_name": "Liu",
                "given_name": "Ying",
                "clpid": "Liu-Ying"
            }
        ],
        "abstract": "Accurate and rapid load forecasting for industrial customers has been playing a crucial role in modern power systems. Due to the variability of industrial customers' activities, individual industrial loads are usually too volatile to forecast accurately. In this paper, a short-term load forecasting model for industrial customers based on the Temporal Convolutional Network (TCN) and Light Gradient Boosting Machine (LightGBM) is proposed. Firstly, a fixed-length sliding time window method is adopted to reconstruct the electrical features. Next, the TCN is utilized to extract the hidden information and long-term temporal relationships in the input features including electrical features, a meteorological feature and date features. Further, a state-of-the-art LightGBM capable of forecasting industrial customers' loads is adopted. The effectiveness of the proposed model is demonstrated by using datasets from different industries in China, Australia and Ireland. Multiple experiments and comparisons with existing models show that the proposed model provides accurate load forecasting results.",
        "doi": "10.1109/TPWRS.2020.3028133",
        "issn": "0885-8950",
        "publisher": "IEEE",
        "publication": "IEEE Transactions on Power Systems",
        "publication_date": "2021-05",
        "series_number": "3",
        "volume": "36",
        "issue": "3",
        "pages": "1984-1997"
    },
    {
        "id": "authors:a1csm-3yn27",
        "collection": "authors",
        "collection_id": "a1csm-3yn27",
        "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20210401-080618288",
        "type": "article",
        "title": "Microbially Induced Magnesium Carbonate Precipitation and its Potential Application in Combating Desertification",
        "author": [
            {
                "family_name": "Zhang",
                "given_name": "Menglong",
                "orcid": "0000-0001-6345-9781",
                "clpid": "Zhang-Menglong"
            },
            {
                "family_name": "Zhao",
                "given_name": "Liang",
                "clpid": "Zhao-Liang"
            },
            {
                "family_name": "Li",
                "given_name": "Gen K.",
                "orcid": "0000-0002-6300-3570",
                "clpid": "Li-Gen-K"
            },
            {
                "family_name": "Zhu",
                "given_name": "Chen",
                "clpid": "Zhu-Chen"
            },
            {
                "family_name": "Dong",
                "given_name": "Sijia",
                "orcid": "0000-0002-5811-9333",
                "clpid": "Dong-Sijia-S"
            },
            {
                "family_name": "Li",
                "given_name": "Zibo",
                "orcid": "0000-0002-1234-2230",
                "clpid": "Li-Zibo"
            },
            {
                "family_name": "Tang",
                "given_name": "Chaosheng",
                "clpid": "Tang-Chaosheng"
            },
            {
                "family_name": "Ji",
                "given_name": "Junfeng",
                "clpid": "Ji-Junfeng"
            },
            {
                "family_name": "Chen",
                "given_name": "Jun",
                "clpid": "Chen-Jun"
            }
        ],
        "abstract": "This study investigated the reaction processes of microbially induced magnesium carbonate precipitation (MIMP) with Sporosarcina pasteurii (ATCC 11859) and evaluated its feasibility for controlling desertification in the desert areas in Northwest China. We explored systematically bacterial growth curves, mineralogy of precipitates, and relative chemical conversion efficiencies of the reaction using magnesium carbonate and bacterial urea hydrolysis with Sporosarcina pasteurii. We also compared the results of MIMP with the previously, well-studied microbially induced calcium carbonate precipitation (MICP). Our results indicate that excess Mg\u00b2\u207a motivated bacterial growth slightly. Magnesium carbonate precipitates appeared as nesquehonite, Mg-amorphous calcium carbonate, and Mg-rich calcite. The relative chemical conversion efficiency was higher in Mg medium than in Ca medium. We next evaluated the potential of using MIMP to mitigate desertification. We validated our results using the Mg-rich solution obtained by dissolving abandoned Mg salts that formed from the potassium salt plants nearby salt lakes. MIMP could potentially overcome shortcomings of traditional sand fixing methods, and was particularly suitable for controlling desertification in desert areas in Northwest China where there are abundant Mg resources. If MIMP works at field scales, this approach would further benefit ecosystem reconstruction because MIMP has main products of organic nutrients and ammonia, which would facilitate the development of biomass and soils. Overall, this work provides new insights into MIMP and its geoengineering potential in controlling desertification.",
        "doi": "10.1080/01490451.2021.1900461",
        "issn": "0149-0451",
        "publisher": "Taylor & Francis",
        "publication": "Geomicrobiology Journal",
        "publication_date": "2021-03-22",
        "series_number": "6",
        "volume": "38",
        "issue": "6",
        "pages": "549-560"
    },
    {
        "id": "authors:zgcf4-jmj97",
        "collection": "authors",
        "collection_id": "zgcf4-jmj97",
        "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20200911-084739596",
        "type": "article",
        "title": "Short-Term Industrial Load Forecasting Based on Ensemble Hidden Markov Model",
        "author": [
            {
                "family_name": "Wang",
                "given_name": "Yuanyuan",
                "orcid": "0000-0002-9575-3712",
                "clpid": "Wang-Yuanyuan"
            },
            {
                "family_name": "Kong",
                "given_name": "Yang",
                "orcid": "0000-0002-3817-9785",
                "clpid": "Kong-Yang"
            },
            {
                "family_name": "Tang",
                "given_name": "Xiafei",
                "clpid": "Tang-Xiafei"
            },
            {
                "family_name": "Chen",
                "given_name": "Xiaoqiao",
                "clpid": "Chen-Xiaoqiao"
            },
            {
                "family_name": "Xu",
                "given_name": "Yao",
                "clpid": "Xu-Yao"
            },
            {
                "family_name": "Chen",
                "given_name": "Jun",
                "orcid": "0000-0001-7095-5142",
                "clpid": "Chen-Jun"
            },
            {
                "family_name": "Sun",
                "given_name": "Shanfeng",
                "orcid": "0000-0002-9120-357X",
                "clpid": "Sun-Shanfeng"
            },
            {
                "family_name": "Guo",
                "given_name": "Yongsheng",
                "orcid": "0000-0003-4235-9807",
                "clpid": "Guo-Yongsheng"
            },
            {
                "family_name": "Chen",
                "given_name": "Yuhao",
                "clpid": "Chen-Yuhao"
            }
        ],
        "abstract": "Short-term load forecasting (STLF) for industrial customers has been an essential task to reduce the cost of energy transaction and promote the stable operation of smart grid throughout the development of the modern power system. Traditional STLF methods commonly focus on establishing the non-linear relationship between loads and features, but ignore the temporal relationship between them. In this paper, an STLF method based on ensemble hidden Markov model (e-HMM) is proposed to track and learn the dynamic characteristics of industrial customer's consumption patterns in correlated multivariate time series, thereby improving the prediction accuracy. Specifically, a novel similarity measurement strategy of log-likelihood space is designed to calculate the log-likelihood value of the multivariate time series in sliding time windows, which can effectively help the hidden Markov model (HMM) to capture the dynamic temporal characteristics from multiple historical sequences in similar patterns, so that the prediction accuracy is greatly improved. In order to improve the generalization ability and stability of a single HMM, we further adopt the framework of Bagging ensemble learning algorithm to reduce the prediction errors of a single model. The experimental study is implemented on a real dataset from a company in Hunan Province, China. We test the model in different forecasting periods. The results of multiple experiments and comparison with several state-of-the-art models show that the proposed approach has higher prediction accuracy.",
        "doi": "10.1109/access.2020.3020799",
        "issn": "2169-3536",
        "publisher": "IEEE",
        "publication": "IEEE Access",
        "publication_date": "2020-09-01",
        "volume": "8",
        "pages": "160858-160870"
    },
    {
        "id": "authors:3z98b-a2864",
        "collection": "authors",
        "collection_id": "3z98b-a2864",
        "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20200417-134621813",
        "type": "book_section",
        "title": "Short-Term Load Forecasting for Industrial Enterprises Based on Long Short-Term Memory Network",
        "book_title": "2019 IEEE 3rd Conference on Energy Internet and Energy System Integration (EI2)",
        "author": [
            {
                "family_name": "Wang",
                "given_name": "Tingyuan",
                "clpid": "Wang-Tingyuan"
            },
            {
                "family_name": "Chen",
                "given_name": "Xiaoqiao",
                "clpid": "Chen-Xiaoqiao"
            },
            {
                "family_name": "Wang",
                "given_name": "Yuanyuan",
                "clpid": "Wang-Yuanyuan"
            },
            {
                "family_name": "Chen",
                "given_name": "Yuhao",
                "clpid": "Chen-Yuhao"
            },
            {
                "family_name": "Chen",
                "given_name": "Jun",
                "clpid": "Chen-Jun"
            },
            {
                "family_name": "Sun",
                "given_name": "Shanfeng",
                "clpid": "Sun-Shanfeng"
            }
        ],
        "abstract": "In China, industrial enterprises develop rapidly, and industrial electricity consumption account for 70% of social electricity consumption. However, the charging mode of industrial electricity is very complicated which can be divided into two basic modes, one mode is to pay according to transformer capacity and other mode is to pay according to maximum demand. In both modes, the complex charging type involving seasonal factors and national economic growth. Once a company chooses the wrong mode to buy electricity, it has to change it three months later. In this case, it not only increases the cost of electricity but also wastes resources. Therefore, it is important to predict the future load data according to the energy consumption characteristics of enterprises. In the context of big data, the electricity data of Chinese enterprises will be developed and utilized gradually. In this paper, the long short-term memory (LSTM) model is built to carry out load forecasting of the international dairy companies which called Ausnutria. The simulation results show that LSTM network is feasible in the field of load prediction, and the method can ensure the accuracy.",
        "doi": "10.1109/ei247390.2019.9061773",
        "isbn": "9781728131375",
        "publisher": "IEEE",
        "place_of_publication": "Piscataway, NJ",
        "publication_date": "2019-11",
        "pages": "1759-1764"
    },
    {
        "id": "authors:t7fq9-zan06",
        "collection": "authors",
        "collection_id": "t7fq9-zan06",
        "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20180130-140046897",
        "type": "article",
        "title": "Mineralogical evidence of reduced East Asian summer monsoon rainfall on the Chinese loess plateau during the early Pleistocene interglacials",
        "author": [
            {
                "family_name": "Meng",
                "given_name": "Xianqiang",
                "clpid": "Meng-Xianqiang"
            },
            {
                "family_name": "Liu",
                "given_name": "Lianwen",
                "clpid": "Liu-Lianwen"
            },
            {
                "family_name": "Wang",
                "given_name": "Xingchen T.",
                "clpid": "Wang-Xingchen-T"
            },
            {
                "family_name": "Balsam",
                "given_name": "William",
                "clpid": "Balsam-W"
            },
            {
                "family_name": "Chen",
                "given_name": "Jun",
                "clpid": "Chen-Jun"
            },
            {
                "family_name": "Ji",
                "given_name": "Junfeng",
                "clpid": "Ji-Junfeng"
            }
        ],
        "abstract": "The East Asian summer monsoon (EASM) is an important component of the global climate system. A better understanding of EASM rainfall variability in the past can help constrain climate models and better predict the response of EASM to ongoing global warming. The warm early Pleistocene, a potential analog of future climate, is an important period to study EASM dynamics. However, existing monsoon proxies for reconstruction of EASM rainfall during the early Pleistocene fail to disentangle monsoon rainfall changes from temperature variations, complicating the comparison of these monsoon records with climate models. Here, we present three 2.6 million-year-long EASM rainfall records from the Chinese Loess Plateau (CLP) based on carbonate dissolution, a novel proxy for rainfall intensity. These records show that the interglacial rainfall on the CLP was lower during the early Pleistocene and then gradually increased with global cooling during the middle and late Pleistocene. These results are contrary to previous suggestions that a warmer climate leads to higher monsoon rainfall on tectonic timescales. We propose that the lower interglacial EASM rainfall during the early Pleistocene was caused by reduced sea surface temperature gradients across the equatorial Pacific, providing a testable hypothesis for climate models.",
        "doi": "10.1016/j.epsl.2017.12.048",
        "issn": "0012-821X",
        "publisher": "Elsevier",
        "publication": "Earth and Planetary Science Letters",
        "publication_date": "2018-03-15",
        "volume": "486",
        "pages": "61-69"
    },
    {
        "id": "authors:mcx9f-49432",
        "collection": "authors",
        "collection_id": "mcx9f-49432",
        "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20150323-091451806",
        "type": "article",
        "title": "Two particles' repelling random walks on the complete graph",
        "author": [
            {
                "family_name": "Chen",
                "given_name": "Jun",
                "clpid": "Chen-Jun"
            }
        ],
        "abstract": "We consider two particles' repelling random walks on complete graphs. In this model, each particle has higher probability to visit the vertices which have been seldom visited by the other one. By a dynamical approach we prove that the two particles' occupation measure asymptotically has small joint support almost surely if the repulsion is strong enough.",
        "doi": "10.1214/EJP.v19-2669",
        "issn": "1083-6489",
        "publisher": "Institute of Mathematical Statistics",
        "publication": "Electronic Journal of Probability",
        "publication_date": "2014-12-12",
        "volume": "19",
        "pages": "Art. No. 113"
    },
    {
        "id": "authors:sj255-xnf43",
        "collection": "authors",
        "collection_id": "sj255-xnf43",
        "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20150115-130415690",
        "type": "article",
        "title": "A generalized P\u00f3lya's urn with graph based interactions: convergence at linearity",
        "author": [
            {
                "family_name": "Chen",
                "given_name": "Jun",
                "clpid": "Chen-Jun"
            },
            {
                "family_name": "Lucas",
                "given_name": "Cyrille",
                "clpid": "Lucas-C"
            }
        ],
        "abstract": "We consider a special case of the generalized Polya's urn model introduced in 3]. Given a finite connected graph G, place a bin at each vertex. Two bins are called a pair if they share an edge of G. At discrete times, a ball is added to each pair of bins. In a pair of bins, one of the bins gets the ball with probability proportional to its current number of balls. A question of essential interest for the model is to understand the limiting behavior of the proportion of balls in the bins for different graphs G. In this paper, we present two results regarding this question. If G is not balanced-bipartite, we prove that the proportion of balls converges to some deterministic point v = v (G) almost surely. If G is regular bipartite, we prove that the proportion of balls converges to a point in some explicit interval almost surely. The question of convergence remains open in the case when G is non-regular balanced-bipartite.",
        "doi": "10.1214/ECP.v19-3094",
        "issn": "1083-589X",
        "publisher": "Institute of Mathematical Statistics",
        "publication": "Electronic Communications in Probability",
        "publication_date": "2014-10-03",
        "volume": "19",
        "pages": "1-13"
    }
]