Ms. Na Fan
· Teaching Assistant ProfessorUniversity of North Carolina at Chapel Hill · Asian Studies
Active 2003–2022
About
Ms. Na Fan, originally hailing from Beijing, China, earned her B.A. in Business Law from Nihon University in Tokyo, Japan. She completed an M.A. in Teaching Chinese as a Second Language at Peking University and has experience teaching Chinese to international students at Xi'an International Studies University. In the United States, she has served as a Japanese language instructor for a prominent Japanese automotive corporation and worked as a patent clerk at a Washington, D.C.-based patent law firm. Since joining the Department of Asian and Middle Eastern Studies at the University of North Carolina in 2019, she has been involved in teaching a diverse range of Chinese language courses, including those tailored for heritage learners. Her research interests focus on Content-Based Instruction (CBI) methods and language instruction for Chinese heritage students.
Research topics
- Biology
- Genetics
- Endocrinology
- Neuroscience
- Zoology
- Botany
- Evolutionary biology
Selected publications
Chemical looping-based energy transformation via lattice oxygen modulated selective oxidation
Progress in Energy and Combustion Science · 2023 · 128 citations
- Chemistry
- Chemical engineering
- Organic chemistry
Toward Fast, Flexible, and Robust Low-Light Image Enhancement
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · 2022 · 937 citations
- Computer Science
- Artificial Intelligence
- Computer Science
Existing low-light image enhancement techniques are mostly not only difficult to deal with both visual quality and computational efficiency but also commonly invalid in unknown complex scenarios. In this paper, we develop a new Self-Calibrated Illumination (SCI) learning framework for fast, flexible, and robust brightening images in real-world low-light scenarios. To be specific, we establish a cascaded illumination learning process with weight sharing to handle this task. Considering the computational burden of the cascaded pattern, we construct the self-calibrated module which realizes the convergence between results of each stage, producing the gains that only use the single basic block for inference (yet has not been exploited in previous works), which drastically diminishes computation cost. We then define the unsupervised training loss to elevate the model capability that can adapt general scenes. Further, we make comprehensive explorations to excavate SCI's inherent properties (lacking in existing works) including operation-insensitive adaptability (acquiring stable performance under the settings of different simple operations) and model-irrelevant generality (can be applied to illumination-based existing works to improve performance). Finally, plenty of experiments and ablation studies fully indicate our superiority in both quality and efficiency. Applications on low-light face detection and nighttime semantic segmentation fully reveal the latent practical values for SCI. The source code is available at https://github.com/vis-opt-group/SCI.
BMC Zoology · 2022 · 17 citations
1st authorCorresponding- Biology
- Zoology
- Endocrinology
BACKGROUND: The ricefield eel is a freshwater protogynous hermaphrodite fish and has become an important aquaculture species in China. The sex change of ricefield eel is impeding its aquaculture practice, particularly the large-scale artificial breeding. Many studies including transcriptomes of mixed gonadal samples from different individuals have been aimed to elucidate mechanisms underlying the sex change. However, the key physiological factors involved in the initiation of sex change remain to be identified. RESULTS: The present study performed transcriptomic analysis on gonadal samples of different sexual stages obtained through biopsy from the same fish undergoing sex change. A total of 539,764,816 high-quality reads were generated from twelve cDNA libraries of gonadal tissues at female (F), early intersexual (EI), mid-intersexual (MI), and late intersexual (LI) stages of three individual sex-changing fish. Pairwise comparisons between EI and F, MI and EI, and LI and MI identified 886, 319, and 10,767 differentially expressed genes (DEGs), respectively. Realtime quantitative PCR analysis of 12 representative DEGs showed similar expression profiles to those inferred from transcriptome data, suggesting the reliability of RNA-seq data for gene expression analysis. The expression of apoeb, csl2, and enpp2 was dramatically increased and peaked at EI while that of cyp19a1a, wnt4a, fgf16, and foxl2a significantly downregulated from F to EI and remained at very low levels during subsequent development until LI, which suggests that apoeb, csl2, enpp2, cyp19a1a, wnt4a, fgf16, and foxl2a may be closely associated with the initiation of sex change of ricefield eels. CONCLUSIONS: Collectively, results of the present study confirmed that the down-regulation of female-related genes, such as cyp19a1a, wnt4a, fgf16, and foxl2a, is important for the sex change of ricefield eels. More importantly, some novel genes, including apoeb, csl2, and enpp2, were shown to be expressed with peak values at EI, which are potentially involved in the initiation of sex change. The present transcriptomic data may provide an important research resource for further unraveling the mechanisms underlying the sex change and testicular development in ricefield eels as well as other teleosts.
Physical Review Letters · 2022 · 94 citations
- Physics
- Particle physics
- Nuclear physics
Branching fraction and effective lifetime measurements of the rare decay B 0 s -and searches for the decays B 0 -and B 0 s - are reported using proton-proton collision data collected with the LHCb detector at center-of-mass energies of 7, 8, and 13 TeV, corresponding to a luminosity of 9 fb -1 . The branching fraction BB 0 s - 3.09 0.460.15 -0.43-0.11 10 -9 and the effective lifetime B 0 s - 2.07 AE 0.29 AE 0.03 ps are measured, where the first uncertainty is statistical and the second systematic. No significant signal for B 0 -and B 0 s - decays is found and upper limits BB 0 - < 2.6 10 -10 and BB 0 s - < 2.0 10 -9 at the 95% C.L. are determined, where the latter is limited to the range m > 4.9 GeV=c 2 . The results are in agreement with the standard model expectations.
JAMA · 2022 · 315 citations
- Medicine
- Internal medicine
- Endocrinology
Importance: The effect of glucocorticoids on major kidney outcomes and adverse events in IgA nephropathy has been uncertain. Objective: To evaluate the efficacy and adverse effects of methylprednisolone in patients with IgA nephropathy at high risk of kidney function decline. Design, Setting, and Participants: An international, multicenter, double-blind, randomized clinical trial that enrolled 503 participants with IgA nephropathy, proteinuria greater than or equal to 1 g per day, and estimated glomerular filtration rate (eGFR) of 20 to 120 mL/min/1.73 m2 after at least 3 months of optimized background care from 67 centers in Australia, Canada, China, India, and Malaysia between May 2012 and November 2019, with follow-up until June 2021. Interventions: Participants were randomized in a 1:1 ratio to receive oral methylprednisolone (initially 0.6-0.8 mg/kg/d, maximum 48 mg/d, weaning by 8 mg/d/mo; n = 136) or placebo (n = 126). After 262 participants were randomized, an excess of serious infections was identified, leading to dose reduction (0.4 mg/kg/d, maximum 32 mg/d, weaning by 4 mg/d/mo) and addition of antibiotic prophylaxis for pneumocystis pneumonia for subsequent participants (121 in the oral methylprednisolone group and 120 in the placebo group). Main Outcomes And Measures: The primary end point was a composite of 40% decline in eGFR, kidney failure (dialysis, transplant), or death due to kidney disease. There were 11 secondary outcomes, including kidney failure. Results: Among 503 randomized patients (mean age, 38 years; 198 [39%] women; mean eGFR, 61.5 mL/min/1.73 m2; mean proteinuria, 2.46 g/d), 493 (98%) completed the trial. Over a mean of 4.2 years of follow-up, the primary outcome occurred in 74 participants (28.8%) in the methylprednisolone group compared with 106 (43.1%) in the placebo group (hazard ratio [HR], 0.53 [95% CI, 0.39-0.72]; P < .001; absolute annual event rate difference, -4.8% per year [95% CI, -8.0% to -1.6%]). The effect on the primary outcome was seen across each dose compared with the relevant participants in the placebo group recruited to each regimen (P for heterogeneity = .11): full-dose HR, 0.58 (95% CI, 0.41-0.81); reduced-dose HR, 0.27 (95% CI, 0.11-0.65). Of the 11 prespecified secondary end points, 9 showed significant differences in favor of the intervention, including kidney failure (50 [19.5%] vs 67 [27.2%]; HR, 0.59 [95% CI, 0.40-0.87]; P = .008; annual event rate difference, -2.9% per year [95% CI, -5.4% to -0.3%]). Serious adverse events were more frequent with methylprednisolone vs placebo (28 [10.9%] vs 7 [2.8%] patients with serious adverse events), primarily with full-dose therapy compared with its matching placebo (22 [16.2%] vs 4 [3.2%]). Conclusions and Relevance: Among patients with IgA nephropathy at high risk of progression, treatment with oral methylprednisolone for 6 to 9 months, compared with placebo, significantly reduced the risk of the composite outcome of kidney function decline, kidney failure, or death due to kidney disease. However, the incidence of serious adverse events was increased with oral methylprednisolone, mainly with high-dose therapy. Trial Registration: ClinicalTrials.gov Identifier: NCT01560052.
Journal of Nanobiotechnology · 2022 · 116 citations
- Chemistry
- Cancer research
- Nanotechnology
Cancer remains a serious threat to human health owing to the lack of effective treatments. Photodynamic therapy (PDT) has emerged as a promising non-invasive cancer treatment that consists of three main elements: photosensitizers (PSs), light and oxygen. However, some traditional PSs are prone to aggregation-caused quenching (ACQ), leading to reduced reactive oxygen species (ROS) generation capacity. Aggregation-induced emission (AIE)-PSs, due to their distorted structure, suppress the strong molecular interactions, making them more photosensitive in the aggregated state instead. Activated by light, they can efficiently produce ROS and induce cell death. PS is one of the core factors of efficient PDT, so proceeding from the design and preparation of AIE-PSs, including how to manipulate the electron donor (D) and receptor (A) in the PSs configuration, introduce heavy atoms or metal complexes, design of Type I AIE-PSs, polymerization-enhanced photosensitization and nano-engineering approaches. Then, the preclinical experiments of AIE-PSs in treating different types of tumors, such as ovarian cancer, cervical cancer, lung cancer, breast cancer, and its great potential clinical applications are discussed. In addition, some perspectives on the further development of AIE-PSs are presented. This review hopes to stimulate the interest of researchers in different fields such as chemistry, materials science, biology, and medicine, and promote the clinical translation of AIE-PSs.
Nature Biomedical Engineering · 2021 · 307 citations
- Medicine
- Internal medicine
- Ophthalmology
A Selective Overview of Deep Learning
Statistical Science · 2021 · 130 citations
- Artificial Intelligence
- Artificial Intelligence
- Computer Science
Deep learning has achieved tremendous success in recent years. In simple words, deep learning uses the composition of many nonlinear functions to model the complex dependency between input features and labels. While neural networks have a long history, recent advances have greatly improved their performance in computer vision, natural language processing, etc. From the statistical and scientific perspective, it is natural to ask: What is deep learning? What are the new characteristics of deep learning, compared with classical methods? What are the theoretical foundations of deep learning? To answer these questions, we introduce common neural network models (e.g., convolutional neural nets, recurrent neural nets, generative adversarial nets) and training techniques (e.g., stochastic gradient descent, dropout, batch normalization) from a statistical point of view. Along the way, we highlight new characteristics of deep learning (including depth and over-parametrization) and explain their practical and theoretical benefits. We also sample recent results on theories of deep learning, many of which are only suggestive. While a complete understanding of deep learning remains elusive, we hope that our perspectives and discussions serve as a stimulus for new statistical research.
European Heart Journal · 2021 · 120 citations
- Medicine
- Internal medicine
- Intensive care medicine
AIMS: Mortality rates from chronic kidney disease (CKD) have increased in the last decade. In this pre-specified analysis of the DAPA-CKD trial, we determined the effects of dapagliflozin on cardiovascular and non-cardiovascular causes of death. METHODS AND RESULTS: DAPA-CKD was an international, randomized, placebo-controlled trial with a median of 2.4 years of follow-up. Eligible participants were adult patients with CKD, defined as a urinary albumin-to-creatinine ratio (UACR) 200-5000 mg/g and an estimated glomerular filtration rate (eGFR) 25-75 mL/min/1.73 m2. All-cause mortality was a key secondary endpoint. Cardiovascular and non-cardiovascular death was adjudicated by an independent clinical events committee. The DAPA-CKD trial randomized participants to dapagliflozin 10 mg/day (n = 2152) or placebo (n = 2152). The mean age was 62 years, 33% were women, the mean eGFR was 43.1 mL/min/1.73 m2, and the median UACR was 949 mg/g. During follow-up, 247 (5.7%) patients died, of whom 91 (36.8%) died due to cardiovascular causes, 102 (41.3%) due to non-cardiovascular causes, and in 54 (21.9%) patients, the cause of death was undetermined. The relative risk reduction for all-cause mortality with dapagliflozin (31%, hazard ratio [HR] [95% confidence interval (CI)] 0.69 [0.53, 0.88]; P = 0.003) was consistent across pre-specified subgroups. The effect on all-cause mortality was driven largely by a 46% relative risk reduction of non-cardiovascular death (HR [95% CI] 0.54 [0.36, 0.82]). Deaths due to infections and malignancies were the most frequently occurring causes of non-cardiovascular deaths and were reduced with dapagliflozin vs. placebo. CONCLUSION: In patients with CKD, dapagliflozin prolonged survival irrespective of baseline patient characteristics. The benefits were driven largely by reductions in non-cardiovascular death.
Reporting guidelines for human microbiome research: the STORMS checklist
Nature Medicine · 2021 · 452 citations
- Computer Science
- Medicine
- Data science
The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.
Frequent coauthors
- 48 shared
Wei Yang
Changchun University of Chinese Medicine
- 15 shared
Lihong Zhang
Xi'an Medical University
- 8 shared
Weimin Zhang
Hainan University
- 4 shared
Jingjing Wang
Nanjing University of Chinese Medicine
- 4 shared
Hongjun Chen
Hangzhou Center for Disease Control and Prevention
- 4 shared
Jitong Xue
Zhejiang University
- 4 shared
Ming Chen
Zhejiang University
- 4 shared
Xue Li
Capital Medical University
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