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Development of Transferable Grapevine Nitrogen Retrieval Algorithm
No full textNitrogen (N) and nutrient management are central to sustainable grapevine production, supporting optimal yield, maximizing economic return, and reducing environmental pollution. Over the past two decades, remote sensing technologies have emerged as high potential tools for monitoring plant nutritional status. Unmanned aerial systems (UAS) and advances in computing capacity offer significant potential for nutrient management applications by enabling cost-effective acquisition of high-resolution imagery across large areas. Despite their growing popularity, traditional vegetation indices (VIs) and purely data-driven approaches face substantial limitations in generalizability, often failing to transfer across sensors, locations, and environmental conditions due to their empirical nature.This dissertation aims to develop generalizable, and interpretable methodologies for N and nutrient estimation in grapevines by leveraging physically based radiative transfer models (RTM) across multiple spatial scales. The first part of the study investigates leaf-level spectral dynamics using the PROSPECT model, evaluating the sensitivity of VIs and RTMs to biochemical and biophysical traits across different leaf ages. Comparative analysis reveals that data-driven methods achieved superior predictive performance (e.g., Gaussian Process Regression attained R² ≈ 0.78), whereas physically based models provided mechanistic interpretability grounded in biophysical parameters. A hybrid approach that combined physically based RTM-derived traits with a Random Forest Regressor yielded lower accuracy (R² ≈ 0.54) while reducing training data requirements by approximately 50%. Nevertheless, the accumulation of errors from RTM inversion and subsequent model training suggests that caution is warranted when applying the hybrid strategy.Building on these mechanistic insights, the second part of the dissertation scales the modeling framework to the canopy level through integration with the HELIOS 3D ray-tracing framework. A novel pipeline was developed in which synthetic multispectral imagery was generated under varying canopy structures, sun angles, and leaf optical properties to quantify how each factor influences overall canopy reflectance, and this imagery was used to train a deep learning model. A major milestone achieved in this study was the complete replacement of data-intensive imaging with synthetic multispectral data for model training, representing an efficient and scalable alternative to conventional data-driven approaches. The trained models demonstrated the ability to predict nutrient-related traits from real-world UAS imagery, generating spatial variability maps that identify zones requiring nutrient intervention. Although domain gaps between synthetic and real reflectance data persist the findings confirm the feasibility of using physically simulated data to train transferable models for field deployment.Collectively, this dissertation presents a hybrid modeling strategy that combines physics-based simulation and machine learning to address the fundamental trade-offs between accuracy, generalizability, and interpretability in nutrient monitoring. The resulting framework provides a strong foundation for advancing precision agriculture by enabling N estimation under physically based approach and supporting future standardization of remote sensing workflows using synthetic reference scenes
An Analysis of the Relationship Between School-Based Health Centers and Student Outcomes
Get PDFStudent health is essential to student academic success and emotional well-being. SchoolBased Health Centers (SBHCs) offer the opportunity to provide health care to students with the greatest barriers to access. This study describes the availability of SBHCs in California kindergarten through grade twelve (K-12) schools and analyzes the relationship between the presence of a SBHC and a wide variety of educational and health outcomes, including absenteeism, graduation and dropout rates, discipline rates, achievement, mental health, school connectedness, and alcohol or other drug (AOD) use. This study utilizes the National Assembly on School-Based Health Care framework, along with Bronfenbrenner’s bioecological theory and Maslow’s hierarchy of needs to place SBHCs in the context of the wider environment of student health influences. I use regression analysis and coarsened exact matching to estimate associations between SBHCs and school and student outcomes. Findings reveal that SBHCs are located more often in schools with higher densities of students with greater needs, such as low socioeconomic status and English learners. The correlation between the presence of a SBHC and outcomes is mixed, with some notable favorable outcomes for excused absences, graduation rates, mental health, and AOD use. Prior to 2025, funding school-based physical and mental health services was a political priority and California planned investment in this area. This analysis provides a pre-pandemic description of access and outcomes for California’s students. The findings from this study can help policymakers ensure that resources are being utilized to address students with the highest needs. This is particularly relevant given the recent focus on policies to support mental health and academic recovery post-pandemic
Analysis of Korean Dialect Obstruents in a Large Corpus Using Speech Recognition Technology
Get PDFThis study explores obstruent characteristics in Korean dialects, particularly distinctions between lax, tense, and aspirated sounds, using phone-level speech recognition on a 2,200-hour corpus. Using the AI-Hub senior dialect speech dataset, we analyzed Gyeongsang (1,203 hours) and Jeolla (1,015 hours) dialects. A G2P model and wav2vec 2.0 XLS-R speech recognition model compared canonical with actual phone sequences.
Gyeongsang dialect showed lax-tense confusion and lax-to-aspirated changes, while Jeolla dialect exhibited aspirated-to-lax changes. The lax-tense merger in Gyeongsang extends beyond previous /s/-/s*/ merger findings to general obstruents. Obstruent deletion in onset and coda positions in Gyeongsang represents a previously unreported phenomenon. The study demonstrates the effectiveness of large speech corpora for dialectal analysis, confirming known patterns while revealing new obstruent variations. Future research should examine how deletions vary by word position
The Phonological Analysis of Left Branch Extraction in Japanese
Get PDFBoskovic (2005) lays out five prerequisites for Left Branch Extraction (LBE): (i) scrambling; (ii) the absence of DP; (iii) NP-over-AP structure; (iv) the left-edge condition; and (v) agreement (see also Boskovic 2008, 2012, 2013). Japanese seems to satisfy the prerequisites (i)-(iv), but not (v) agreement. If agreement is a strict requirement for LBE, languages that lack φ-agreement, such as Japanese, are expected to disallow LBE. However, if agreement is merely a preferred or default option for LBE, it is plausible that languages without agreement may employ an alternative strategy to make LBE possible. We argue that Japanese, which lacks φ-agreement, actually employs an alternative strategy based on prosody to facilitate LBE. Specifically, we argue that the low acceptability of LBE in Japanese results from a phonological restriction on the relevant movement, showing that the phonological restriction can be alleviated or overridden by prosodic factors related to focus and topic
Children’s Sensitivity to the Island Effects in Japanese Cleft Constructions
Get PDFCleft constructions have been one of the central issues in the field of child language acquisition. In order to deepen our understanding of children’s knowledge about these constructions, this study conducted a new experiment to determine whether Japanese-speaking preschool children are sensitive to the island effects in cleft constructions. The results of our experiment, which were obtained from 43 children between the ages of four and six, suggest that these children conform to the island constraints in clefts, which in turn gives prominence to the view that child language acquisition is supported by an innate faculty of language
Co‐domestication of cold tolerance and female flower is determined by CsEIN2 in cucumber
Get PDFSurvive and successful reproduction at cold stress are critical for cucumber adaptation to environmental conditions in high-latitude regions. However, the molecular basis for the co-domestication of cold adaptation and reproductive success in cucumber remains unknown. Here, we demonstrate that CsEIN2 acts as an indispensable hub in regulating both cold tolerance and female flower percentage (FFP) in cucumber. Specifically, we discover that three completely linked natural variations at the C-terminus of CsEIN2, that is, the CsEIN2CTC and CsEIN2TCG haplotypes determine the differences in cold tolerance and FFP. These variations affect the interaction of CsEIN2 with the transcription factor CsEIN3, which activates the expression of target genes such as CsCBF2 and CsERF31 to regulate cold tolerance and FFP, respectively. Interestingly, the geographical distribution analyses show that the CsEIN2CTC haplotype, conferring higher cold tolerance and FFP, underwent artificial selection for adaptation to environmental conditions in high-latitude regions. Further, we find that CsEIN2 is the only sex determination gene for selection of both cold tolerance and FFP. Collectively, our findings not only establish CsEIN2 as a 'hub' regulator that enhances cold tolerance and FFP, but also provides target gene for breeding
Blood-brain barrier crossing biopolymer targeting c-Myc and anti-PD-1 activate primary brain lymphoma immunity: Artificial intelligence analysis
Get PDFPrimary Central Nervous System Lymphoma is an aggressive central nervous system neoplasm with poor response to pharmacological treatment, partially due to insufficient drug delivery across blood-brain barrier. In this study, we developed a novel therapy for this lymphoma by combining a targeted nanopolymer treatment with an immune checkpoint inhibitor antibody (anti-PD-1). A N-(2-hydroxypropyl)methacrylamide copolymer-based nanoconjugate was designed to block tumor cell c-Myc oncogene expression by antisense oligonucleotide. Angiopep-2 peptide was conjugated to the copolymer to facilitate nanodrug crossing of the blood-brain barrier. Systemically administered polymeric nanodrug, alone or in combination with immune checkpoint inhibitor antibody anti-PD-1, was tested in syngeneic mouse model of A20 intracranial brain lymphoma. There was no significant survival difference between saline- and free anti-PD-1-treated groups. However, significant survival advantage vs. saline was observed upon treatment with nanodrug bearing Angiopep-2, H6 (6 histidines for endosome escape), and c-Myc antisense alone and especially when it was combined with anti-PD-1 antibody. Animal survival after combined treatment was also significantly increased vs. free anti-PD-1. Artificial Intelligence-assisted analysis of gene expression database after RNA-seq of tumors was used to find novel immune pathways, molecular targets and the most effective multifunctional drugs together with future drug prediction for brain lymphoma in vivo model. Spectral flow cytometry and RNA-seq analysis revealed a robust activation of tumor infiltrating T lymphocytes with enhanced interferon γ signaling and polarization to M1-type macrophages in treated tumors, which was confirmed by immunofluorescence staining. In summary, a new effective blood-brain barrier crossing nano immuno therapeutic system was developed that effectively blocked tumor c-Myc acting in combination with immune checkpoint inhibitor anti-PD-1 to treat primary brain lymphoma. The treatment improved survival of tumor-bearing animals through activation of both the adaptive and innate immune responses
Identification of Chlamydia pneumoniae and NLRP3 inflammasome activation in Alzheimer's disease retina.
Get PDFEmerging evidence implicates bacterial infections, including Chlamydia pneumoniae (Cp), a gram-negative obligate intracellular bacterium responsible for community-acquired pneumonia, in Alzheimer's disease (AD) pathogenesis. However, the involvement of Cp in early and advanced AD in the retina is unknown. Here, we identified the existence and distribution of intracellular Cp inclusions and related NLRP3 inflammasome activation and neurodegeneration in postmortem retinas and brains from 95 human donors. Histological analysis in neuropathologically-confirmed MCI and AD patients compared with cognitively normal individuals (n=70), revealed 2.9-4.1-fold increases of Cp inclusions in AD retinas and brains, respectively, with no significant increases in MCI retinas or brains. Mass spectrometry-based proteomics in additional cohorts (n=30), revealed dysregulated brain and retinal bacterial infection-related proteins and inflammasome-associated pathways. Retinal Cp was strongly linked to Aβ 42 , caspase-1 and NLRP3-inflammasome activation components, as well as cleaved caspase-3 + apoptosis and cleaved gasdermin D pyroptotic cell death. Despite increased IBA1 + microgliosis in the AD retina, the Cp-associated microglial population was reduced by 62%, suggesting impaired microglial phagocytosis. Higher retinal Cp burden correlated with APOEε4 status, advanced Braak stage, and cognitive decline. Machine learning models revealed that retinal Cp or NLRP3, in combination with retinal Aβ 42 , effectively predicted AD diagnosis, Braak stage, and cognition. These findings suggest that Cp infection contributes to AD dementia but is unlikely to initiate AD pathological changes, whereas elevated retinal NLRP3 may serve as an early AD marker. These results underscore the need for future studies investigating Cp's role in AD dementia and testing early antibiotic or inflammasome-targeting therapies
Reactivation of an embryonic cardiac neural crest transcriptional profile during zebrafish heart regeneration
Get PDFDuring vertebrate development, the heart primarily arises from mesoderm, with crucial contributions from cardiac neural crest (CdNC) cells that migrate to the heart and form a variety of cardiovascular derivatives. Here, by integrating bulk and single cell RNA-seq with ATAC-seq, we identify a gene regulatory subcircuit specific to migratory cardiac crest cells composed of key transcription factors egr1, sox9a, tfap2a, and ets1. Notably, we show that cells expressing the canonical neural crest gene sox10 are essential for proper cardiac regeneration in adult zebrafish. Furthermore, expression of all transcription factors from the migratory cardiac crest gene subcircuit are reactivated after injury at the wound edge. Together, our results uncover a developmental gene regulatory network that is important for CdNC fate determination, with key factors of the program reexpressed during regeneration
