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Articles by Ning Mao
Editorial for “Combined Cerebral Blood Flow and Cerebrovascular Reactivity MRI for Multivariate Classification of Clinically Defined Mild Cognitive Impairment”
No abstract is available for this article. References 1, , , , , and , “Mild Cognitive Impairment: Clinical Characterization and Outcome,” Archives of Neurology 56, no. 3 (1999): 303–308. 2, , , and , “Systematic Review of Different Neuroimaging Correlates in Mild Cognitive Impairment and Alzheimer's Disease,” Clinical Neuroradiology 31, no. 4 (2021): 953–967.
Correlation between pathogens of chronic suppurative otitis media and nasopharyngeal colonization in the Taklamakan Desert region
Abstract This study investigated the potential nasopharyngeal reservoir of infection in chronic suppurative otitis media (CSOM), for which comprehensive local data on concurrent middle ear pathogen profiles, antimicrobial resistance, and nasopharyngeal colonization are lacking. A total of 189 CSOM patients and 136 healthy volunteers were enrolled.
Metabolic reprogramming in Oocystis borgei drives the biosynthesis of gold nanoparticles
Abstract Microalgae-mediated biosynthesis of gold nanoparticles (AuNPs) offers a sustainable alternative for nanomaterial synthesis; however the metabolic mechanisms underlying the reduction of HAuCl4 and the formation of AuNPs remain unclear. In this study, the green microalga Oocystis borgei was employed to synthesize AuNPs, and associated cellular metabolic alterations were systematically examined using transmission electron microscopy (TEM) and untargeted LC-MS-based metabolomics.
Tunable symmetry breaking in a hexagonal-stacked moiré magnet
Abstract Symmetry plays a central role in defining magnetic phases, making tunable symmetry breaking across magnetic transitions highly desirable for discovering non-trivial magnetism. Magnetic moiré superlattices, formed by twisting two-dimensional magnetic crystals, have been theoretically proposed and experimentally explored as platforms for unconventional magnetic states.
Optimizing sustainable fishery resource allocation in China: an improved adaptive NSGA-III approach under multi-dimensional rigid constraints
Abstract Introduction: Multi-dimensional fishery resource allocation presents a complex and highly nonlinear optimization challenge under the converging pressures of ecological redlines and industrial transformation. Existing allocation approaches often struggle to coordinate production, processing, and marketing under rigid ecological and capacity constraints, thereby limiting the sustainable transition of China’s fishery sector.
Interpretation of Crystal Energy Landscapes with Kolmogorov–Arnold Networks Click to copy article link Article link copied!
Abstract Click to copy section linkSection link copied! Characterizing crystalline energy landscapes is essential to predicting thermodynamic stability, electronic structure, and functional behavior. While machine learning (ML) enables rapid property predictions, the “black-box” nature of most models limits their utility for generating new scientific insights. Here, we introduce Kolmogorov–Arnold Networks (KANs) as an interpretable framework to bridge this gap.
Universal giant spin Hall effect in moiré metal - npj Computational Materials
Abstract While moiré phenomena have been extensively studied in low-carrier-density systems such as semiconductors, their implications for metallic systems with large Fermi surfaces remain largely unexplored. Using GPU-accelerated large-scale ab-initio quantum transport simulations, we investigate spin transport in two distinct platforms: twisted bilayer MoTe2 (semiconductor) and NbX2 (X = S, Se; metals).
Intra- and peritumoral radiomics for predicting equivocal HER2 status of breast cancer on contrast-enhanced mammography
Abstract Objective: Identification of Human epidermal growth factor receptor 2 (HER2) status is significant for the treatment and prognosis of breast cancer patients. The study aimed to evaluate the equivocal HER2 (IHC 2+) status of breast cancer using intra- and peritumoral radiomics features of contrast-enhanced mammography (CEM).
Editorial for “Intratumoral Spatial Heterogeneity at Dynamic Contrast‐Enhanced MRI for Assessing Tertiary Lymphoid Structures in Hepatocellular Carcinoma”
No abstract is available for this article. References 1 and , “Tertiary Lymphoid Structures in Cancer,” Science 375 (2022): eabf9419. 2, , , et al., “Intra-Tumoral Tertiary Lymphoid Structures Are Associated With a Low Risk of Early Recurrence of Hepatocellular Carcinoma,” Journal of Hepatology 70 (2019): 58–65. 3 and , “Tumour Heterogeneity and Resistance to Cancer Therapies,” Nature Reviews. Clinical Oncology 15 (2018): 81–94.
A multifunctional MRI model based on IVIM and DKI predicts HIF-1α, Ki-67, and VEGF status in breast carcinoma
Introduction Breast carcinoma is currently recognized as a leading malignancy and primary contributor to cancer-related mortality in women. Moreover, recent trends indicate a growing incidence of breast cancer diagnoses among younger individuals (1). From a molecular viewpoint, breast carcinoma is a highly heterogeneous tumor type, posing considerable challenges for the accurate evaluation and implementation of personalized medicine into clinical practice (2).
Layer dependent topological phases and transitions in TaRhTe4: From monolayer and bilayer to bulk
The recently synthesized ternary quasi-2D material TaRhTe4 is a bulk Weyl semimetal with an intrinsically layered structure, which poses the question of how the topology of its electronic structure depends on layer separations. Experimentally, these separations may be changed for instance by intercalation of the bulk, or by exfoliation, to reach monolayer or few-layer structures.
Development and validation of an MRI spatiotemporal interaction model for early noninvasive prediction of neoadjuvant chemotherapy response in breast cancer: a multicentre study
Keywords Deep learning Early prediction Breast cancer Neoadjuvant chemotherapy Pathological complete response Longitudinal MRI Evidence before this study We searched for the terms (“deep learning” OR “radiomics” OR “artificial intelligence”) AND (“breast cancer” OR “breast tumor”) AND (“neoadjuvant chemotherapy”) AND (“pathological complete response”) AND (“MRI”) without date or language restrictions on PubMed.
Bridging plastic recycling and clean energy production: hydrogen-free catalytic pyrolysis of polyethylene over CuMgAlOx for high-yield diesel fuel generation
Bridging plastic recycling and clean energy production: hydrogen-free catalytic pyrolysis of polyethylene over CuMgAlOx for high-yield diesel fuel generation† The increasing annual production of plastic waste, particularly polyolefins, underscores the critical need to valorize these waste polyolefin plastics by converting them into high-value products.
A multimodal and fully automated system for prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer
Abstract Accurately predicting pathological complete response (pCR) before neoadjuvant chemotherapy (NAC) is crucial for patients with breast cancer. In this study, we developed a multimodal integrated fully automated pipeline system (MIFAPS) in forecasting pCR to NAC, using a multicenter and prospective dataset of 1004 patients with locally advanced breast cancer, incorporating pretreatment magnetic resonance imaging, whole slide image, and clinical risk factors.
A Multi-Resolution Sequence Method with Strong Constraints for Marine Gravity Matching Navigation
1. Introduction The marine gravity field reflects information about Earth’s internal structure, material migration, density distribution, etc. The magnitude of the gravity value establishes a nonlinear functional relationship with a geospatial location (longitude, latitude, and altitude) and is stable on the milligal scale (1 mGal = 1 × 10−5 m/s2), so the marine gravity field is a continuous and stable fundamental physical field [1,2,3].
Deep Learning Model for the Differential Diagnosis of Nasal Polyps and Inverted Papilloma by CT Images: A Multicenter Study
Key Words Computed tomography Deep learning Inverted papilloma Nasal polyps Proteomic Get full text access Log in, subscribe or purchase for full access. REFERENCES 1. Anari, S. ∙ Carrie, S. Sinonasal inverted papilloma: narrative review J Laryngol Otol. 2010; 124:705-715 2. Hedman, J. ∙ Kaprio, J. ∙ Poussa, T. ... Prevalence of asthma, aspirin intolerance, nasal polyposis and chronic obstructive pulmonary disease in a population-based study Int J Epidemiol. 1999; 28:717-722 3.
Application of Machine Learning Models to Multi-Parameter Maximum Magnitude Prediction
4. Results 4.1. Evaluation of Model Performance Table 3 and Table 4 present the MAE, MSE, and RMSE values of different machine learning models under various training and testing split strategies (i.e., 7:3 and 8:2). The results indicate that the LSTM model consistently achieves the lowest errors under both split ratios, outperforming other models. Specifically, with a 7:3 split, the LSTM model’s MAE is 0.58, its MSE is 0.44, and its RMSE is 0.67.
Giant Topological Hall Effect and Colossal Magnetoresistance in Heusler Ferromagnet near Room Temperature
1 Introduction Colossal magnetoresistance (CMR) represents a striking phenomenon observed in certain materials, particularly manganites, where the application of a magnetic field has been shown to dramatically reduce electrical resistance.[1-3] This property has garnered significant interest due to its potential applications in magnetic sensors, data storage devices, and spintronic technologies.
Forecasting Motor Vehicle Ownership and Energy Demand Considering Electric Vehicle Penetration
1. Introduction Energy is the key material foundation supporting national economic development, while transportation is a pillar sustaining the growth of the national economy. The development of transportation and that of energy supply are closely intertwined. The transportation industry is one of the three major high-carbon emission sectors in China, and achieving carbon neutrality in the transportation system is crucial for realizing the country’s “dual carbon” goals [1].
Monthly Maximum Magnitude Prediction in the North-South Seismic Belt of China Based on Deep Learning
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Research on Machine Learning-Based Method for Predicting Industrial Park Electric Vehicle Charging Load
1. Introduction In recent years, driven by the national “dual-carbon” policy, the electric vehicle (EV) industry in China has been flourishing. A large number of EVs have been integrated into the power grid, but this has also brought new challenges to the stable and secure operation of the grid. In industrial parks with high EV penetration rates, the charging behavior of EVs during peak electricity consumption periods has increased the peak load on the grid.
Two New Species of Hymenogaster (Hymenogastraceae, Agaricales) from China Based on Morphological and Molecular Markers
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Fast Prediction and Optimization of Building Wind Environment Using CFD and Deep Learning Method
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Five New Species of the Genus Hymenogaster (Hymenogastraceae, Agaricales) from Northern China
1. Introduction Hymenogaster (Hymenogastraceae, Agaricales), established by Carolo Vittadini based on eight species found in Europe [1], is one of the most species-rich genera of false truffles [2,3,4]. Hymenogaster citrinus was designated as the type species [5].
Interactions between Noctiluca scintillans and Three Co-Occurring Microalgae in Response to Varying Nutrient Levels
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Quantum oscillations revealing topological band in kagome metal ${\mathrm{ScV}}_{6}{\mathrm{Sn}}_{6}$
Compounds with kagome lattice structure are known to exhibit Dirac cones, flatbands, and van Hove singularities, which host numerous versatile quantum phenomena. Inspired by these intriguing properties, we investigate the temperature and magnetic field-dependent electrical transports along with the theoretical calculations of ScV6Sn6, a nonmagnetic charge-density wave (CDW) compound.
Topology-Engineered Orbital Hall Effect in Two-Dimensional Ferromagnets
Download Hi-Res ImageDownload to MS-PowerPointCite This:Nano Lett. 2024, XXXX, XXX Terms & Conditions Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses).
Adaptive Evolution of Marine Organisms: A Bibliometric Analysis Based on CiteSpace
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Ferry Scheduling Optimization Considering Arrival Time Uncertainty and In-Place Time Differences
4.1. Research on Algorithm Parameters In Section 3, a multi-parameter configurable GA was designed to effectively and quickly solve the model. This section studies the range of values for population size, iteration times and sample size. Firstly, population size is an important indicator that affects the duration of a single iteration. In a single iteration, the larger the population size, the larger the search space of the algorithm.
Remote Sensing | Free Full-Text | Application of Model-Based Time Series Prediction of Infrared Long-Wave Radiation Data for Exploring the Precursory Patterns Associated with the 2021 Madoi Earthquake
4. Results 4.1. Model Performance After determining the optimal parameters for each method, we compared the performance of the different methods. presents the prediction performance of each model for 25 grid OLR time series. As shown in , there were significant differences between the different prediction models.
Ferroelectric heterobilayer with tunable first- and higher-order topological states
As conceptual milestones of nontrivial phenomenon, Z2 topological insulators (TIs) and higher-order TIs (HOTIs) have greatly reshaped the landscape of fundamental physics and materials. However, despite the exciting progress, a tunable topological phase transition between Z2 TIs and HOTIs remains elusive.
Two Scenario-Based Heuristics for Stochastic Shift Design Problem with Task-Based Demand
1. Introduction General workforce scheduling aims at balancing supply and demand for labor. The process of workforce scheduling can be decomposed into the following seven main steps [1]: Forecasting Demand, Determining Staffing Requirements, Shift Design [2], Rostering [3], Staff Management or Tour Scheduling [4,5], Task Assignment [6] or Staff Scheduling [7], and Re-scheduling [8,9,10,11].
Magnetic resonance imaging based deep-learning model: a rapid, high-performance, automated tool for testicular volume measurements
Introduction The testis is an important organ for male spermatogenesis and testosterone synthesis (1–3). As the seminiferous tubules account for approximately 80–90% of the testicular mass, the testicular volume (TV) reflects sperm and hormonal status (1, 2, 4–7). In clinical practice, the TV is an essential parameter for monitoring testicular functions and pathologies (2).
Whole-tumor histogram analysis of apparent diffusion coefficients for predicting lymphovascular space invasion in stage IB-IIA cervical cancer
1 Introduction Cervical cancer is the most common malignancy in women, with approximately 600,000 new cases worldwide each year, second only to breast, colorectal, and lung cancer. It is also the fourth leading cause of cancer-related deaths in women worldwide (1). Lymphovascular space invasion (LVSI), defined as the presence of one or more cancer cell clusters in the lymphatic lumen or vasculature, is an independent risk factor for postoperative recurrence and poor prognosis (2, 3).
An Instruction-Driven Batch-Based High-Performance Resource-Efficient LSTM Accelerator on FPGA
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A Parameterized Parallel Design Approach to Efficient Mapping of CNNs onto FPGA
Abstract : In recent years, Convolution Neural Networks (CNNs) have been widely applied to some artificial intelligence (AI) systems such as computer vision. Among many existing hardware accelerators, FPGA is regarded as a suitable platform for the implementation of CNNs because of its high energy efficiency and flexible reconfigurability.
Optimal Design and Experiment of Corn-Overlapped Strip Fertilizer Spreader
Abstract : As the complex terrain in hilly areas is not conducive to corn mid-tillage precision fertilization, a corn-overlapped strip fertilizer spreader was designed without an external power source. By configuring a passive overlapping spreading method with a three-branch split chamber structure, the uniform spreading of fertilizer in strips was achieved.
Ferroelectric higher-order topological insulator in two dimensions
Abstract The interplay between ferroelectricity and band topology can give rise to a wide range of both fundamental and applied research. Here, we map out the emergence of nontrivial corner states in two-dimensional ferroelectrics and, remarkably, demonstrate that ferroelectricity and corner states are coupled together by crystallographic symmetry to realize the electric control of higher-order topology.
Integrative interaction of emotional speech in audio-visual modality
Introduction Our senses enable us to receive information about our surroundings, and they also have the ability to perceive specific modalities. Sometimes we may be able to make accurate judgments and responses to the surroundings through information from only one modality, but more often we need the assistance of the integrated multi-sensory information, and our cognition of the world is often multimodal. Therefore, our sensory organs are not isolated from each other.
Doubled quantum spin Hall effect with high-spin Chern number in $\ensuremath{\alpha}$-antimonene and $\ensuremath{\alpha}$-bismuthene
COVID-19 has impacted many institutions and organizations around the world, disrupting the progress of research. Through this difficult time APS and the Physical Review editorial office are fully equipped and actively working to support researchers by continuing to carry out all editorial and peer-review functions and publish research in the journals as well as minimizing disruption to journal access.
Dissect Relationships Between Gene Co-expression and Functional Connectivity in Human Brain
Introduction Functional connectivity calculated from functional magnetic resonance imaging (fMRI) has been widely used to characterize intrinsic low-frequency synchronization of brain activity at rest between anatomically distinct brain regions (Ogawa et al., 1992). Regions and connections are organized into brain functional networks responsible for such distinct functions as vision, audition, motion, attention, memory, and emotion.
Engineering antiferromagnetic topological insulators in two-dimensional NaMnBi
Engineering antiferromagnetic topological insulators in two-dimensional NaMnBi† Antiferromagnetic (AFM) topological insulators (TIs) have recently attracted extensive attention as a platform for exploring prominent physical phenomena and innovative design of topological spintronic devices. Here, we theoretically demonstrate a topological switch between the normal insulator and AFM TI in two-dimensional NaMnBi quintuple layers.
Mammography-based radiomics for predicting the risk of breast cancer recurrence: a multicenter study | The British Journal of Radiology
1. Siegel RL, , Miller KD, , Jemal A. Cancer statistics, 2019. CA Cancer J Clin 2019; 69: 7–34. doi: https://doi.org/10.3322/caac.21551 http://www.ncbi.nlm.nih.gov/pubmed/30620402 2. Boyages J, , Taylor R, , Chua B, , Ung O, , Bilous M, , Salisbury E, , et al.. A risk index for early node-negative breast cancer. Br J Surg 2006; 93: 564–71. doi: https://doi.org/10.1002/bjs.5207 3. Paik S, , Shak S, , Tang G, , Kim C, , Baker J, , Cronin M, , et al..
Antiferromagnetic Topological Insulator with Nonsymmorphic Protection in Two Dimensions
Abstract The recent demonstration of topological states in antiferromagnets (AFMs) provides an exciting platform for exploring prominent physical phenomena and applications of antiferromagnetic spintronics. A famous example is the AFM topological insulator (TI) state, which, however, was still not observed in two dimensions.
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