In this paper we consider the problem of efficient estimation in conditional quantile models with time series data. Our first result is to derive the semiparametric efficiency bound in time series models of conditional quantiles; this is a nontrivial extension of a large body of work on efficient estimation, which has traditionally focused on models with independent and identically distributed data. In particular, we generalize the bound derived by New and Powell (1990) to the case where the data is weakly dependent and heterogeneous. We then proceed by constructing an M-estimator which achieves the semiparametric efficiency bound. Our efficient M-estimator is obtained by minimizing an objective function which depends on a nonparametric estimator of the conditional distribution of the variable of interest rather than its density.

Purpose: The purpose of this study was to evaluate the shear bond strength (SBS) of various restorative materials – pure glass ionomer cement (GIC), resin-modified glass ionomer (RMGI), and resin composite to artificial carious dentin treated with silver diamine fluoride (SDF).Methods: Extracted human permanent molars were sectioned and put in demineralizing solution to create artificial carious lesions and subsequently treated with SDF and exposed to human saliva. Various restorative materials, consisting of GIC, RMGI, and composite, were placed and analyzed for differences in shear bond strengths. Statistical analysis was performed using ANOVA and a post-hoc Tukey HSD test (P<0.05). Results: ANOVA revealed statistically significant differences in the mean shear bond strengths (mean ± SD MPa) of the three groups (GIC, RMGI, composite) (P=0.020). GIC exhibited the highest shear bond strengths in MPa (11.6 ± 4.1) followed by composite (9.2 ± 3.7) and RMGI (7.7 ± 3.9). Statistically significant differences were found between mean bond strengths of GIC and RMGI (P=0.016). Failure mode analysis revealed 100% adhesive failures in the RMGI and Composite groups. GIC exhibited 53% adhesive and 47% mixed failure modes. Conclusions: Glass ionomer cement shows higher shear bond strength to SDF-treated artificial carious dentin compared to composite and resin-modified glass ionomer.

Agricultural food crop production must increase 100-110% by 2050 in order to meet the predicted global population and production demands. In order to meet the increasing food demands from the growing population, as a society we are looking for ways to increase food yield without needing to further exploit land and water resources. Plant breeders look to solve this problem by breeding novel high-yielding crop varieties that can produce quality fruit in extreme weather and limited water conditions. This includes crossbreeding commercially available cultivars with wild types shown to react favorably in times of drought and heat stress in nature. The two key components in breeding commercial crop cultivars are quantifying genotypic and phenotypic data.Prior to second generation sequencing, the bottleneck in producing commercial crop varieties was the inability to accurately and efficiently sequence a crop genome. The second generation of sequencing has simplified the process of genome mapping and allows for the identification of candidate genetic markers to utilize marker assisted selection (MAS). With these developments, the current bottleneck in producing new crop varieties is now phenotyping plant traits in in-field breeding trials. There is an increased need for higher throughput in relating genetic material to phenotypes. Current in-field phenotyping methods rely on humans to go into the breeding fields to detect these phenotypes. These current methods are time consuming, labor intensive, and subjective. These phenotyping trials rely on repetition of genetic material in a study to maximize time and space and reduce the amount of human labor is needed. In order to meet current and future food demands, we need to look at new methods of high-throughput phenotyping to help plant breeders create new crops more efficiently. In this study we look at three aspects of high-throughput phenotyping: developing and deploying a multi-camera and multi-sensor in-field phenotyping system for Solanaceae crops, developing algorithms to use with the phenotyping system to detect phenotypes in tomatoes, and exploring new sensor technology to develop low-cost methods of detecting green fruit. A high-throughput phenotyping (HTTP) system was developed to be a high clearance tractor fitted with 9 color DSLR cameras, 9 pseudo-NDVI cameras, 2 Time of Flight cameras, 2 temperature sensors, 8 custom LED modules, with infrared and broad-spectrum white LEDs, 1 RTK-GPS, 1 National Instruments High Speed Controller, 1 Dell desktop computer, and 1 National Instruments USB controller. The system was used in 2018 and 2019 to collect multi-sensor data in a processing pepper and tomato breeding trial in Davis, CA. Images from a single camera from the HTPP system was used to develop algorithms for object detection in tomatoes throughout the growing season. The algorithm utilized Mask R-CNN for object detection of flowers, green fruit, ripe fruit, and sunburnt fruit with an average mAP of 21.1% on a validation set. The number of ripe fruit and green fruit on the last date were used to predict the weight of ripe fruit and green fruit from manual phenotyping at harvest, the R values were 0.407 and 0.201 in 2018 and 0.202, and 0.142 in 2019 respectively. A pseudo-NDVI camera was used to test if adding non-visible wavelengths to imaging would impact the detection of green fruit. DSLR cameras were modified to allow infrared and near-infrared wavelengths to be imaged, in hopes that this would be a low-cost method for incorporating multi-spectral imaging in the HTPP system. An infrared camera and color camera were compared for green fruit detection in 2019. 85% of the plant-plots imaged had more green fruit detected in the color images than the infrared camera, which could imply double counting in the color images. More testing and ground truth data needs to be done to get conclusive answers about the green fruit detection in infrared. In conclusion, this dissertation focuses on developing high-throughput phenotyping methods that rely on 2D imaging of in-field plants. The ability to quickly process quantitative phenotypic data is important for the development of new crops as the current bottleneck in plant breeding is phenotyping. This dissertation shows that there are new and old technologies and techniques that can be applied to high-throughput phenotyping for in-field phenotyping.

Despite a national vaccination effort prioritizing frontline healthcare workers, COVID-19 vaccination rates among nurses have been lower than necessary to protect workforce and patient health. Historically, nurses have been more vaccine hesitant than other healthcare workers. To assess the vaccine attitudes and COVID-19 vaccine intent of California’s registered nurses, we conducted a statewide cross-sectional survey among 603 licensed RNs working in direct patient care. Of 167 respondents (27.7%), 111 met inclusion criteria. Their mean score of 3.01 on a 6-point rating scale on the Vaccine Attitudes Examination scale measuring general vaccine hesitancy was comparable to previous findings among U.S. West Coast adults. Greater vaccine hesitancy was significantly associated with lower COVID-19 vaccine intent, after controlling for relevant confounders. Since nurses make up the largest portion of the healthcare workforce, it is crucial to specifically address this group’s vaccine hesitancy.

Cellular proliferation and differentiation are critical events in normal development and cancer. Despite decades of research, much remains to be learned about how cells transition between the two states. To decipher one aspect of this switch, we focused on the transcription factor, Hepatocyte Nuclear Factor (HNF) 4 alpha. HNF4a is a nuclear receptor that is important in development and in maintaining the homoeostasis of the adult liver and colon. There are multiple isoforms of the HNF4a that are generated by alterative promoter (P1 and P2) usage and 3' splicing events in different tissues. Both P1 and P2-HNF4a isoforms are expressed in the adult colon, while the P1-HNF4a is expressed in the adult liver. Others have shown that P1-HNF4a is downregulated in cancer, whereas P2-HNF4a is upregulated in hepatocellular carcinoma and colorectal cancer. This would suggest that P1-HNF4a is tumor suppressive, while P2-HNF4a may act as an oncogene although a mechanism has not been elucidated. One potential mechanism could be through a differential interplay with the Wnt/beta-catenin/TCF pathway, which is activated in many cancers including liver and colon. To determine whether HNF4a and TCF4 cross-talk to control the switch between proliferation and differentiation and to elucidate the role of the HNF4a isoforms in early development and cancer, we generated Tet-On inducible systems that express either HNF4a2 (P1) or HNF4a8 (P2) under the control of doxycycline in human colon cancer and mouse embryonic stem cells. We characterized the lines to look for morphological and functional differences between the isoforms. We performed RNA-Seq and ChIP-Seq on the HCT116 inducible lines to identify any changes in gene expression and regulation and compared the HNF4a2 and HNF4a8 lines to determine functional differences. Although we found some functional redundancy, there are discrete differences. HNF4a2 suppresses tumor growth, inhibits cellular proliferation, and competes with TCF4 for regulation of target genes more effectively than HNF4a8. Similarly, we also found that HNF4a2 decreases cell numbers more than HNF4a8 in the mES inducible lines. Our findings provide insight into the distinct role of the P1- and P2-HNF4a in cancer and normal development.

Aluminum Nitride (Al-N) is a white, hydrophilic, thermally-conducting, high-band-gap ceramic with low visible-light-spectrum emissivity. Aluminum Nitride being hydrophilic makes it capable of utilizing capillary action, which means it can be used as a material for wicking. Here we report on the light-induced evaporation of saltwater through a capillary wick composed of drop-cast, loosely bonded Al-N microparticles. With 405-nm LED light illuminating the wick, water evaporation rates are increased to levels above equivalent-energy thermal evaporation rates. We checked for the effect of humidity and crystallization on the trials, and showed how both act as inevitable inhibitors to the evaporation process. Oscillations in the evaporation rate occur as well, caused by a dominance in either crystallization or dissolution in the pores. Our observations point to the potential of a novel solar non-thermal desalination approach.

Alternative splicing produces mRNA isoforms of distinct structure and function from the same gene. Neuronal polarization has been shown to be regulated by alternative splicing in the brain. Loss of neuronal enriched splicing factor PTBP2 causes deleterious effects in neuronal maturation and regulates genes involved in axon formation. We identify microtubule associated protein involved in axon formation, Trim46 as a PTBP2-specific target through multi-pronged approaches. We further show that non-sense mediated mRNA decay pathway (NMD) degrades transcripts containing premature termination codons (PTCs) of Trim46 isoform to control its steady-state expression. We used gene editing tool CRISPR/Cas9 to ablate alternative splicing and NMD control of Trim46 in mouse embryonic stem cells (mESC). Differentiation of mutant mESCS into neurons show defects of AnkG localization in the axon initial segment, demonstrating the essential roles of alternative splicing and NMD control during axon formation. We further performed gain and loss of function analysis to show that the long and short TRIM46 isoforms affect microtubule stability differently. In summary, alternative splicing and NMD control of Trim46 isoforms regulates formation of the axon initial segment.