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Origins of perturbations in dayside equatorial ground magnetograms

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Earth and Planetary Physics 2024年第1期8卷 215-221页

作者： Syau-Yun W.hsieh David G.Sibeck The Johns Hopkins University Applied Physics Laboratory LaurelMarylandUSA NASA Goddard Space Flight Center GreenbeltMarylandUSA

To determine the cause(s)of perturbations seen in dayside equatorial ground magnetograms,we conducted a systematic survey of simultaneous ground-based and geosynchronous satellite-based observations during the 90-day period from December 1,2020 to February 28,*** examined Huancayo ground magnetometer observations from 14:00:00 to 20:00:00 UT each day,during which Huancayo passed through local *** those data we chose perturbation events selected on the basis of large(>20 nT)event amplitude and classified the selected events as responding primarily to solar wind pressure,or to variations in the north/south component of the interplanetary magnetic field(IMF Bz),or perhaps in part to *** results show that an equivalent number of events were identified for each model during this 90-day *** in the lagged solar wind dynamic pressure routinely correspond to nearly simultaneous sudden impulses recorded at both geosynchronous orbit and on the *** in IMF Bz produce erosion signatures at geosynchronous orbit and can correspond to ground events if lag times for reconnection to enhance convection in the magnetosphere are taken into account.

关键词： dayside magnetosphere dayside equatorial ionosphere geosynchronous magnetic field

Management of retroperitoneal high-grade serous carcinoma of unknown origin:A case report

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World Journal of Clinical Cases 2024年第6期12卷 1190-1195页

作者： Wen-Lin hsieh Dah-Ching Ding Department of Obstetrics and Gynecology Hualien Tzu Chi HospitalBuddhist Tzu Chi Medical FoundationTzu Chi UniversityHualien 970Taiwan Institute of Medical Sciences Tzu Chi UniversityHualien 970TaiwanTaiwan

BACKGROUND Retroperitoneal high-grade serous carcinoma(HGSC)of unknown origin is a sporadic tumor that can originate from ovarian ***,we report the case of a woman with retroperitoneal HGSC of unknown origin and describe how she was diagnosed and *** SUMMARY A 71-year-old female presented with the tumor marker CA125 elevated to 1041.9 U/mL upon a regular health *** tomography revealed retroperitoneal lymph node ***,positron emission tomography scanning revealed lesions with increased F-18 fluorodeoxyglucose uptake at the *** a result,she underwent laparoscopic lymph node resection,and pathology revealed metastatic adenocarcinoma with CK7(+),PAX8(+),WT1(+),PR(-),and p53 mutational loss of expression,indicating that the origin may be from the *** patient was admitted to our ward and underwent laparoscopic staging;however,the pathological results were *** the suspicion of retroperitoneal HGSC of unknown origin,chemotherapy and targeted therapy were *** marker levels decreased after *** We present a case of HGSC of unknown origin managed using retroperitoneal lymphadenectomy,staging surgery,chemotherapy,and targeted therapy.

关键词： High-grade serous carcinoma Retroperitoneum Origin Chemotherapy Lymph node Case report

Automated and miniaturized screening of antibiotic combinations via robotic-printed combinatorial droplet platform

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Acta Pharmaceutica Sinica B 2024年第4期14卷 1801-1813页

作者： Fangchi Shao Hui Li Kuangwen hsieh Pengfei Zhang Sixuan Li Tza-Huei Wang Department of Biomedical Engineering Johns Hopkins UniversityBaltimoreMD 21218USA Department of Mechanical Engineering Johns Hopkins UniversityBaltimoreMD 21218USA

Antimicrobial resistance(AMR)has become a global health crisis in need of novel *** this end,antibiotic combination therapies,which combine multiple antibiotics for treatment,have at-tracted significant attention as a potential approach for combating *** facilitate advances in anti-biotic combination therapies,most notably in investigating antibiotic interactions and identifying synergistic antibiotic combinations however,there remains a need for automated high-throughput plat-forms that can create and examine antibiotic combinations on-demand,at scale,and with minimal reagent *** address these challenges,we have developed a Robotic-Printed Combinatorial Droplet(RoboDrop)platform by integrating a programmable droplet microfuidic device that generates antibiotic combinations in nanoliter droplets in automation,a robotic arm that arranges the droplets in an array,and a camera that images the array of thousands of droplets in *** further implement a resazurin-based bacterial viability assay to accelerate our antibiotic combination *** a demonstration,we use RoboDrop to corroborate two pairs of antibiotics with known interactions and subsequently identify a new synergistic combination of cefsulodin,penicillin,and oxacillin against a model *** *** therefore envision RoboDrop becoming a useful tool to efficiently identify new synergistic antibiotic combinations toward combating AMR.

关键词： Droplet microfluidics Antimicrobial resistance Antibiotic combinatorial screening Contact printing Robotics Pharmaceutical analysis High-throughput Antibiotic interactions

Adaptive Fourier Decomposition of the First Three SARS-CoV-2 Infection Waves with Epidemic Intervention—London,UK,2020-2022

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China CDC weekly 2024年第21期6卷 478-486,I0006-I0008页

作者： Zige Liu Guibin Lu Cheokieng Vong Zhiqi Zeng Wei He Zhijie Lin Cuiyun Lin Kaichin hsieh Zifeng Yang Arlindo L.Oliveira Chitin Hon Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao SARChina Queen Ethelburga’s Collegiate Thorpe Underwood EstateYorkUK State Key Laboratory of Respiratory Disease National Clinical Research Center for Respiratory DiseaseGuangzhou Institute of Respiratory HealthThe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou CityGuangdong ProvinceChina Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications Department of Engineering ScienceFaculty of Innovation EngineeringMacao University of Science and TechnologyMacao SARChina Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases KingMed School of Laboratory MedicineGuangzhou Medical UniversityGuangzhou CityGuangdong ProvinceChina Faculty of Innovation Engineering School of Computer Science and EngineeringMacao University of Science and TechnologyMacao SARChina University College London UCL Faculty of Engineering SciencesLondonUK Guangzhou Laboratory Guangzhou CityGuangdong ProvinceChina Instituto de Engenharia de Sistemas e Computadores:Investigação e Desenvolvimento em Lisboa LisboaPortugal Instituto Superior Técnico Universidade de LisboaLisboaPortugal

Background:This study provides a detailed analysis of the daily fluctuations in coronavirus disease 2019(COVID-19)case numbers in London from January 31,2020 to February 24,*** primary objective was to enhance understanding of the interactions among government pandemic responses,viral mutations,and the subsequent changes in COVID-19 case ***:We employed the adaptive Fourier decomposition(AFD)method to analyze diurnal changes and further segmented the AFD into novel multi-component groups consisting of one to three *** restructured components were rigorously evaluated using Pearson correlation,and their effectiveness was compared with other signal analysis *** study introduced a novel approach to differentiate individual components across various time-frequency scales using basis decomposition ***:Analysis of London’s daily COVID-19 data using AFD revealed a strong correlation between the“stay at home”directive and high-frequency components during the first epidemic *** indicates the need for sustained implementation of vaccination policies to maintain their ***:The AFD component method provides a comprehensive analysis of the immediate and prolonged impact of governmental policies on the spread of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).This robust tool has proven invaluable for analyzing COVID-19 pandemic data,offering critical insights that guide the formulation of future preventive and public health strategies.

关键词： offering sustained London

Interpenetrated Structures for Enhancing Ion Diffusion Kinetics in Electrochemical Energy Storage Devices

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Nano-Micro Letters 2024年第11期16卷 718-728页

作者： Xinzhe Xue Longsheng Feng Qiu Ren Cassidy Tran Samuel Eisenberg Anica Pinongcos Logan Valdovinos Cathleen hsieh Tae Wook Heo Marcus A.Worsley Cheng Zhu Yat Li Department of Chemistry and Biochemistry University of California1156 High StreetSanta CruzCA 95064USA Lawrence Livermore National Laboratory 7000 East AvenueLivermoreCA 94550USA

The architectural design of electrodes offers new opportunities for next-generation electrochemical energy storage devices(EESDs)by increasing surface area,thickness,and active materials mass loading while maintaining good ion diffusion through optimized electrode ***,conventional thick electrodes increase ion diffusion length and cause larger ion concentration gradients,limiting reaction *** demonstrate a strategy for building interpenetrated structures that shortens ion diffusion length and reduces ion concentration *** free-standing device structure also avoids short-circuiting without needing a *** feature size and number of interpenetrated units can be adjusted during printing to balance surface area and ion *** with a 3D-printed interpenetrated polymer substrate,we metallize it to make it *** substrate has two individually addressable electrodes,allowing selective electrodeposition of energy storage *** a Zn//MnO_(2) battery as a model system,the interpenetrated device outperforms conventional separate electrode configurations,improving volumetric energy density by 221%and exhibiting a higher capacity retention rate of 49%compared to 35%at temperatures from 20 to 0℃.Our study introduces a new EESD architecture applicable to Li-ion,Na-ion batteries,supercapacitors,etc.

关键词： Interpenetrated structure 3D printing Electrochemical energy storage Ion diffusion length Inter-electrode distance

Generic Interpretable Reaction Condition Predictions with Open Reaction Condition Datasets and Unsupervised Learning of Reaction Center

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Research 2024年第2期2023卷 773-794页

作者： Xiaorui Wang Chang-Yu hsieh Xiaodan yin Jike Wang Yuquan Li Yafeng Deng Dejun Jiang Zhenxing Wu Hongyan Du Hongming Chen Yun Li Huanxiang Liu Yuwei Wang Pei Luo Tingjun Hou Xiaojun Yao Dr.Neher's Biophysics Laboratory for lnnovative Drug Discovery State Key Laboratory of Quality Research in Chinese MedicineMacao Institute for Applied Research in Medicine and HealthMacao University of Science and TechnologyMacao999078China innovation Institute for Artificial Intelligence in Medicine of Zhejiang University College of Pharmaceutical SciencesZhejiang UniversityHangzhou310058China Faculty of Applied Sciences Macao Polytechnic UniversityMacao999078China College of Chemistry and Chemical Engineering Lanzhou UniversityLanzhou730000China Carbon Silicon AI Technology Co. LtdHangzhouZhejiang 310018China Center of Chemistry and Chemical Biology Guangzhou Regenerative Medicine and Health Guangdong LaboratoryGuangzhou 510530China College of Pharmacy Shaanxi University of Chinese MedicineXianyangShaanxi712044China

Effective synthesis planning powered by deep learning(DL)can significantly accelerate the discovery of new drugs and ***,most DL-assisted synthesis planning methods offer either none or very limited capability to recommend suitable reaction conditions(RCs)for their reaction ***,the prediction of RCs with a DL framework is hindered by several factors,including:(a)lack of a standardized dataset for benchmarking,(b)lack of a general prediction model with powerful representation,and(c)lack of *** address these issues,we first created 2 standardized RC datasets covering a broad range of reaction classes and then proposed a powerful and interpretable Transformer-based RC predictor named *** careful design of the model architecture,pretraining method,and training strategy,Parrot improved the overall top-3 prediction accuracy on catalysis,solvents,and other reagents by as much as 13.44%,compared to the best previous model on a newly curated ***,the mean absolute error of the predicted temperatures was reduced by about 4℃.Furthermore,Parrot manifests strong generalization capacity with superior cross-chemical-space prediction *** analysis indicates that Parrot effectively captures crucial chemical information and exhibits a high level of interpretability in the prediction of *** proposed model Parrot exemplifies how modern neural network architecture when appropriately pretrained can be versatile in making reliable,generalizable,and interpretable recommendation for RCs even when the underlying training dataset may still be limited in diversity.

关键词： versatile absolute generalization

Enhancing Generic Reaction yield Prediction through Reaction Condition-Based Contrastive Learning

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Research 2024年第3期 685-702页

作者： Xiaodan yin Chang-Yu hsieh Xiaorui Wang Zhenxing Wu Qing Ye Honglei Bao Yafeng Deng Hongming Chen Pei Luo Huanxiang Liu Tingjun Hou Xiaojun Yao Dr.Neher’s Biophysics Laboratory for Innovative Drug Discovery State Key Laboratory of Quality Research in Chinese MedicineMacao Institute for Applied Research in Medicine and HealthMacao University of Science and TechnologyMacao 999078China Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University College of Pharmaceutical SciencesZhejiang UniversityHangzhou 310058China. Faculty of Applied Sciences Macao Polytechnic UniversityMacao 999078China. CarbonSilicon AI Technology Co.Ltd HangzhouZhejiang 310018China Center of Chemistry and Chemical Biology Guangzhou Regenerative Medicine and Health Guangdong LaboratoryGuangzhou 510530China.

Deep learning(DL)-driven efficient synthesis planning may profoundly transform the paradigm for designing novel pharmaceuticals and ***,the progress of many DL-assisted synthesis planning(DASP)algorithms has suffered from the lack of reliable automated pathway evaluation *** a critical metric for evaluating chemical reactions,accurate prediction of reaction yields helps improve the practicality of DASP algorithms in the real-world ***,accurately predicting yields of interesting reactions still faces numerous challenges,mainly including the absence of high-quality generic reaction yield datasets and robust generic yield *** compensate for the limitations of high-throughput yield datasets,we curated a generic reaction yield dataset containing 12 reaction categories and rich reaction condition ***,by utilizing 2 pretraining tasks based on chemical reaction masked language modeling and contrastive learning,we proposed a powerful bidirectional encoder representations from transformers(BERT)-based reaction yield predictor named *** achieved comparable or even superior performance to the best previous models on 4 benchmark datasets and established state-of-the-art performance on the newly curated *** found that reaction-condition-based contrastive learning enhances the model’s sensitivity to reaction conditions,and Egret is capable of capturing subtle differences between reactions involving identical reactants and products but different reaction ***,we proposed a new scoring function that incorporated Egret into the evaluation of multistep synthesis *** results showed that yield-incorporated scoring facilitated the prioritization of literature-supported high-yield reaction pathways for target *** addition,through meta-learning strategy,we further improved the reliability of the model’s prediction for reaction types with limited data and lower data *** r

关键词： synthesis generic holds

Programming nonlinear propagation for efficient optical learning machines

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Advanced Photonics 2024年第1期6卷 73-83页

作者： Ilker Oguz Jih-Liang hsieh Niyazi Ulas Dinc Ugur Tegin Mustafa yildirim Carlo Gigli Christophe Moser Demetri Psaltis École Polytechnique Fédérale de Lausanne Institute of Electrical and Micro EngineeringEcublensSwitzerland Koc University Department of Electrical and Electronics EngineeringIstanbulTurkey

The ever-increasing demand for training and inferring with larger machine-learning models requires more efficient hardware solutions due to limitations such as power dissipation and *** is a promising contender for providing lower power computation,since light propagation through a nonabsorbing medium is a lossless ***,to carry out useful and efficient computations with light,generating and controlling nonlinearity optically is a necessity that is still *** fibers(MMFs)have been shown that they can provide nonlinear effects with microwatts of average power while maintaining parallelism and low *** propose an optical neural network architecture that performs nonlinear optical computation by controlling the propagation of ultrashort pulses in MMF by wavefront *** a surrogate model,optimal sets of parameters are found to program this optical computer for different tasks with minimal utilization of an electronic *** show a remarkable decrease of 97%in the number of model parameters,which leads to an overall 99%digital operation reduction compared to an equivalently performing digital neural *** further demonstrate that a fully optical implementation can also be performed with competitive accuracies.

关键词： neural networks nonlinear optics fiber optics surrogate optimization neuromorphic computing wavefront shaping

Aqueous self-assembly and surface-functionalized nanodots for live cell imaging and labeling

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Nano Research 2014年第8期7卷 1164-1176页

作者： Mei-lang Kung Pei-ying Lin Chiung-Wen hsieh Shuchen hsieh Department of Chemistry and Center for Nanoscience and Nanotechnology 'National Sun Yat-sen University' Kaohsiung 80424 School of Pharmacy College of Pharmacy Kaohsiung Medical University Kaohsiung 80707

Nanoparticles have enormous potential for bioimaging and biolabeling applications, in which conventional organically based fluorescent labels degrade and fail to provide long-term tracking. Thus, the development of approaches to make fluorescent probes water soluble and label cells efficient is desirable for most biological applications. Here, we report on the fabrication and charac- terization of self-assembled nanodots （SANDs） from 3-aminopropyltriethoxysilane （APTES） as a probe for protein labeling. We show that fluorescent SAND probes exhibit both bright photoluminescence and biocompatibility in an aqueous environment. Selective in vitro imaging using protein and carbohydrate labeling of hepatoma cell lines are demonstrated using biocompatible SANDs conjugated with avidin and galactose, respectively. Cytotoxicity tests show that conjugated SAND particles have negligible effects on cell proliferation. Unlike other synthetic systems that require multistep treatments to achieve robust surface functionalization and to develop flexible bioconjugation strategies, our results demonstrate the versatility of this one-step SAND fabrication method for creating multicolor fluorescent probes with the tailored functionalities, effident emission, as well as excellent biocompatibility, required for broad biological use.

关键词： atomic force microscop hydrophilicity molecular imaging self-assembly silane