Cultural Studies in the Mandarin-English Dual Immersion Classroom: A Case Study

This thesis uses a Mandarin-English dual immersion program at a Southern California public elementary school as a case study to examine how culture is taught and learned in the dual immersion setting. Based on classroom observations and interviews with students, staff, and parents, this thesis argues that concepts of “China” and “Chinese culture” are conveyed, constructed, and negotiated by students as well as teachers, both implicitly and explicitly

MSIQ: Joint Modeling of Multiple RNA-seq Samples for Accurate Isoform Quantification

Next-generation RNA sequencing (RNA-seq) technology has been widely used to assess full-length RNA isoform abundance in a high-throughput manner. RNA-seq data offer insight into gene expression levels and transcriptome structures, enabling us to better understand the regulation of gene expression and fundamental biological processes. Accurate isoform quantification from RNA-seq data is challenging due to the information loss in sequencing experiments. A recent accumulation of multiple RNA-seq data sets from the same tissue or cell type provides new opportunities to improve the accuracy of isoform quantification. However, existing statistical or computational methods for multiple RNA-seq samples either pool the samples into one sample or assign equal weights to the samples when estimating isoform abundance. These methods ignore the possible heterogeneity in the quality of different samples and could result in biased and unrobust estimates. In this article, we develop a method, which we call "joint modeling of multiple RNA-seq samples for accurate isoform quantification" (MSIQ), for more accurate and robust isoform quantification by integrating multiple RNA-seq samples under a Bayesian framework. Our method aims to (1) identify a consistent group of samples with homogeneous quality and (2) improve isoform quantification accuracy by jointly modeling multiple RNA-seq samples by allowing for higher weights on the consistent group. We show that MSIQ provides a consistent estimator of isoform abundance, and we demonstrate the accuracy and effectiveness of MSIQ compared with alternative methods through simulation studies on D. melanogaster genes. We justify MSIQ's advantages over existing approaches via application studies on real RNA-seq data from human embryonic stem cells, brain tissues, and the HepG2 immortalized cell line

Immuno-Anti-Infective Drug Design Using BioAI

According to the World Health Organization, antibiotic resistance is one of the biggest threats to global health, food security, and development today. A growing number of infections, like Methicillin-resistant Staphylococcus aureus, are becoming harder to treat as the antibiotics used to treat them become less effective. As a result, the primary concern for infections in the hospital setting is due to the S. aureus’s growing resistance to antibiotics. Therefore, in response to this global health threat, our project focuses on furthering the research in developing a drug that S. aureus will not develop resistance to. In this paper, we assess NPY-Y2 as a potential immuno-anti-infective drug target to prevent the activation of Sortase A on S. aureus. We have shown that NPY-Y2 is a potential drug target; however, further invasion assay experiments need to be conducted for more reliable verification. In a larger scheme, our hope is that the approach of this research will allow for the development of other anti-infective drugs for other bacteria

EpiAlign: an alignment-based bioinformatic tool for comparing chromatin state sequences.

The availability of genome-wide epigenomic datasets enables in-depth studies of epigenetic modifications and their relationships with chromatin structures and gene expression. Various alignment tools have been developed to align nucleotide or protein sequences in order to identify structurally similar regions. However, there are currently no alignment methods specifically designed for comparing multi-track epigenomic signals and detecting common patterns that may explain functional or evolutionary similarities. We propose a new local alignment algorithm, EpiAlign, designed to compare chromatin state sequences learned from multi-track epigenomic signals and to identify locally aligned chromatin regions. EpiAlign is a dynamic programming algorithm that novelly incorporates varying lengths and frequencies of chromatin states. We demonstrate the efficacy of EpiAlign through extensive simulations and studies on the real data from the NIH Roadmap Epigenomics project. EpiAlign is able to extract recurrent chromatin state patterns along a single epigenome, and many of these patterns carry cell-type-specific characteristics. EpiAlign can also detect common chromatin state patterns across multiple epigenomes, and it will serve as a useful tool to group and distinguish epigenomic samples based on genome-wide or local chromatin state patterns

Cosmological inference from the EFTofLSS: the eBOSS QSO full-shape analysis

We present cosmological results inferred from the effective-field theory (EFT) analysis of the full-shape of eBOSS quasars (QSO) power spectrum. We validate our analysis pipeline against simulations, and find overall good agreement between the analyses in Fourier and configuration space. Keeping the baryon abundance and the spectral tilt fixed, we reconstruct at $68\%$ CL the fractional matter abundance $\Omega_m$, the reduced Hubble constant $h$, and the clustering amplitude $\sigma_8$, to respectively $\Omega_m=0.327\pm 0.035$, $h=0.655\pm 0.034$, and $\sigma_8=0.880\pm 0.083$ from eBOSS QSO alone. These constraints are consistent at $\lesssim 1.8\sigma$ with the ones from Planck and from the EFT analysis of BOSS full-shape. Interestingly $S_8$ reconstructed from eBOSS QSO is slightly higher than that deduced from Planck and BOSS, although statistically consistent. In combination with the EFT likelihood of BOSS, supernovae from Pantheon, and BAO from lyman-$\alpha$ and 6dF/MGS, constraints improve to $\Omega_m = 0.2985\pm 0.0069$ and $h = 0.6803\pm 0.0075$, in agreement with Planck and with similar precision. We also explore one-parameter extensions to $\Lambda$CDM and find that results are consistent with flat $\Lambda$CDM at $\lesssim 1.1\sigma$. We obtain competitive constraints on the curvature density fraction $\Omega_k=-0.039\pm 0.029$, the dark energy equation of state $w_0=-1.038\pm 0.041$, the effective number of relativistic species $N_{\rm eff}=3.44^{+0.44}_{-0.91}$ at $68\%$ CL, and the sum of neutrino masses $\sum m_\nu<0.274e$V at $95\%$ CL, without Planck data. Including Planck data, contraints significantly improve thanks to the large lever arm in redshift between LSS and CMB measurements. In particular, we obtain the stringent constraint $\sum m_\nu<0.093e$V, competitive with recent lyman-$\alpha$ forest power spectrum bound.Comment: 33 + 13 pages, 8 figures. Comments welcome

Moderate lifelong overexpression of tuberous sclerosis complex 1 (TSC1) improves health and survival in mice

The tuberous sclerosis complex 1/2 (TSC1/2) is an endogenous regulator of the mechanistic target of rapamycin (mTOR). While mTOR has been shown to play an important role in health and aging, the role of TSC1/2 in aging has not been fully investigated. In the current study, a constitutive TSC1 transgenic (Tsc1tg) mouse model was generated and characterized. mTORC1 signaling was reduced in majority of the tissues, except the brain. In contrast, mTORC2 signaling was enhanced in Tsc1tg mice. Tsc1tg mice are more tolerant to exhaustive exercises and less susceptible to isoproterenol-induced cardiac hypertrophy at both young and advanced ages. Tsc1tg mice have less fibrosis and inflammation in aged as well as isoproterenol-challenged heart than age-matched wild type mice. The female Tsc1tg mice exhibit a higher fat to lean mass ratio at advanced ages than age-matched wild type mice. More importantly, the lifespan increased significantly in female Tsc1tg mice, but not in male Tsc1tg mice. Collectively, our data demonstrated that moderate increase of TSC1 expression can enhance overall health, particularly cardiovascular health, and improve survival in a gender-specific manner.ISSN:2045-232

Evaluating NLG Evaluation Metrics: A Measurement Theory Perspective

We address the fundamental challenge in Natural Language Generation (NLG) model evaluation, the design and validation of evaluation metrics. Recognizing the limitations of existing metrics and issues with human judgment, we propose using measurement theory, the foundation of test design, as a framework for conceptualizing and evaluating the validity and reliability of NLG evaluation metrics. This approach offers a systematic method for defining "good" metrics, developing robust metrics, and assessing metric performance. In this paper, we introduce core concepts in measurement theory in the context of NLG evaluation and key methods to evaluate the performance of NLG metrics. Through this framework, we aim to promote the design, evaluation, and interpretation of valid and reliable metrics, ultimately contributing to the advancement of robust and effective NLG models in real-world settings

Consistency of effective field theory analyses of the BOSS power spectrum

We assess the robustness of $\Lambda$CDM results from the full-shape analysis of BOSS power spectrum using the one-loop prediction of the Effective Field Theory of Large-Scale Structure (EFTofLSS). The public likelihoods PyBird and CLASS-PT lead to results in agreement only at the $1\sigma$ level, despite the fact that they are derived from the same BOSS dataset and theory model. We perform a thorough comparison of the various analyses choices made between the two pipelines, and identify that the differences come from the choice of prior on the EFT parameters, dubbed "West-coast" (WC) and "East-coast" (EC) prior, respectively associated to PyBird and CLASS-PT. In particular, because posteriors are non-Gaussian, projection effects from the marginalization over the EFT parameters shift the posterior mean of the cosmological parameters with respect to the best-fit up to $1\sigma$ in the WC prior and up to $2\sigma$ in the EC prior. We quantify that best-fit cosmological parameters extracted from BOSS given the two prior choices are consistent at $\sim 1\sigma$. The consistency improves to $\sim 0.5\sigma$ when doubling the prior widths. While this reveals that current EFT analyses are subject to prior effects, we show that cosmological results obtained in combination with CMB, or from forthcoming large-volume data, are less sensitive to those effects. In addition, we investigate differences between BOSS measurements. We find broad agreements across all pre-reconstructed measurements considered ($<0.6\sigma$), but the two available BOSS post-reconstructed measurements in Fourier space, once combined with the EFT full-shape analysis, lead to discrepant Hubble parameter $H_0$ at $\sim 0.9\sigma$. Given the various effects we discuss, we argue that the clustering amplitude $\sigma_8$ measured with BOSS is not in statistical tension with that inferred from Planck under $\Lambda$CDM.Comment: 17+6 pages, 10 figures. Comments welcome

Optimization of treatment planning workflow and tumor coverage during daily adaptive magnetic resonance image guided radiation therapy (MR-IGRT) of pancreatic cancer

Abstract Background To simplify the adaptive treatment planning workflow while achieving the optimal tumor-dose coverage in pancreatic cancer patients undergoing daily adaptive magnetic resonance image guided radiation therapy (MR-IGRT). Methods In daily adaptive MR-IGRT, the plan objective function constructed during simulation is used for plan re-optimization throughout the course of treatment. In this study, we have constructed the initial objective functions using two methods for 16 pancreatic cancer patients treated with the ViewRay™ MR-IGRT system: 1) the conventional method that handles the stomach, duodenum, small bowel, and large bowel as separate organs at risk (OARs) and 2) the OAR grouping method. Using OAR grouping, a combined OAR structure that encompasses the portions of these four primary OARs within 3 cm of the planning target volume (PTV) is created. OAR grouping simulation plans were optimized such that the target coverage was comparable to the clinical simulation plan constructed in the conventional manner. In both cases, the initial objective function was then applied to each successive treatment fraction and the plan was re-optimized based on the patient’s daily anatomy. OAR grouping plans were compared to conventional plans at each fraction in terms of coverage of the PTV and the optimized PTV (PTV OPT), which is the result of the subtraction of overlapping OAR volumes with an additional margin from the PTV. Results Plan performance was enhanced across a majority of fractions using OAR grouping. The percentage of the volume of the PTV covered by 95% of the prescribed dose (D95) was improved by an average of 3.87 ± 4.29% while D95 coverage of the PTV OPT increased by 3.98 ± 4.97%. Finally, D100 coverage of the PTV demonstrated an average increase of 6.47 ± 7.16% and a maximum improvement of 20.19%. Conclusions In this study, our proposed OAR grouping plans generally outperformed conventional plans, especially when the conventional simulation plan favored or disregarded an OAR through the assignment of distinct weighting parameters relative to the other critical structures. OAR grouping simplifies the MR-IGRT adaptive treatment planning workflow at simulation while demonstrating improved coverage compared to delivered pancreatic cancer treatment plans in daily adaptive radiation therapy

Synchronizing Rural Students’ Cognition:An International Case Study about Rural Education Gap in China

This primary qualitative study examines the impacts of curricular and non-curricular social learning experiences on rural middle and high school students in China, regarding their cognition about the world, themselves, and their missions. Through eight-week focus field interviews including students in rural schools and the ones studying in urban schools but had rural school experience, this study provides unusual insight to Chinese rural education from learner’s perspective in a comparison model, which has rarely been done. The differences found about rural students’ cognition suggest that “distance” to their learning “models”, and limited access to learning recourses are the major issues with theoretical interpretations. Consistent visiting teaching programs from city and new information technologies are effective tools to help synchronizing the cognition of rural students in the current social context.  This study involves further examination of the major learning theories: Social Learning Theory and Social Cognitive Theory. Keywords: Social learning, cognitive learning behavior, student’s cognition, rural educatio