Prospective randomized controlled pilot study on the effects of almond consumption on skin lipids and wrinkles.

ObjectiveAlmonds are a rich source of fatty acids and antioxidants, and their supplementation is known to significantly modulate serum lipids. The effects of almond on the skin's lipid barrier and the appearance of wrinkles have not yet been elucidated. The aim of this study was to investigate the effects of almond consumption on facial sebum production and wrinkles.MethodsThis was a prospective, investigator-blinded, randomized controlled trial in which subjects consumed 20% of their daily energy consumption in either almonds or a calorie-matched snack for 16 weeks. This study was completed at the UC Davis Dermatology clinic. Participants were a volunteer sample of generally healthy postmenopausal females with Fitzpatrick skin types 1 and 2. A facial photograph and image analysis system was used to obtain standardized photographs and information on wrinkle width and severity at 0, 8, and 16 weeks. Measurements of transepidermal water loss and sebum production were also completed at 0, 8, and 16 weeks.ResultsFifty healthy postmenopausal females were recruited, 31 participants were enrolled, and 28 completed the study. Under photographic analysis, the almond group had significantly decreased wrinkle severity and width compared with the control group at 16 weeks (p < .02). Changes in skin barrier function were nonsignificant, measured by the transepidermal water loss (p = .65) between the almond and control groups relative to baseline after 16 weeks. No adverse effects were reported.ConclusionOur study demonstrates that daily almond consumption may reduce wrinkle severity in postmenopausal females to potentially have natural antiaging benefits

Integration of Remote Sensing and Proximal Sensing for Improvement of Field Scale Water Management

Water is one of the most precious natural resources, and sustainable water resources development ‎‎is a significant challenge facing water managers over the coming decades. Accurate estimation of ‎‎the different components of the hydrologic cycle is key for water managers and planners in order ‎‎to achieve sustainable water resources development. The primary goal of this dissertation was to ‎investigate techniques to combine datasets acquired by remote and proximal sensing and in-situ ‎sensors for the improvement of monitoring near surface water fluxes. This dissertation is ‎separated into three site-specific case studies. First study, investigated the feasibility of using ‎inverse vadose zone modeling for field actual evapotranspiration (ETa) estimation. Results show ‎reasonable estimates of ETa, both daily and annually, from soil water content (SWC) sensors and ‎Cosmic-Ray Neutron Probes (CRNPs). Second study, combined remote and proximal sensing ‎methods to explore the spatial correlation between hydrological state variables and ET flux. ‎Comparison of the datasets reveal that SWC and ETa were linearly correlated but the correlation ‎between depth to the water table and ETa was weak. A simple multivariate linear regression ‎model was used to estimate ETa. The estimated ETa values were then compared to the time ETa ‎integration spline method. The comparison indicates similar seasonal ETa between the two ‎methods in 2015 ‎‎(wet) but a 20% reduction in 2016 (dry). The study highlights the challenge of ‎connecting hydrologic state variables with hydrologic flux estimates. Third study, evaluated the ‎functionality of automatically calibrated Earth Engine Evapotranspiration Flux (EEFlux) to the ‎existing mapping evapotranspiration at high resolution with internalized calibration (METRIC) ‎images in different locations. The comparison results showed that EEFlux is able to calculate ‎Reference evapotranspiration Fraction (ETrF) and ETa in agricultural areas comparable ‎‎(RMSE=0.13) to the ones from trained expert METRIC users. However, the EEFlux algorithm ‎needs to be improved to calculate ETrF and ETa in non-agricultural areas (RMSE=0.21). Given ‎the paucity of in-situ data across much of the globe the field of remote sensing offers an ‎alternative but requires users to be cautious and realistic about associated errors and uncertainty ‎on using such information to help construct a hydrologic budget.‎ Advisor: Trenton E. Franz and Ayse Kili

Integrating a Heterogeneous Graph with Entity-aware Self-attention using Relative Position Labels for Reading Comprehension Model

Despite the significant progress made by transformer models in machine reading comprehension tasks, they still fall short in handling complex reasoning tasks due to the absence of explicit knowledge in the input sequence. To address this limitation, many recent works have proposed injecting external knowledge into the model. However, selecting relevant external knowledge, ensuring its availability, and requiring additional processing steps remain challenging. In this paper, we introduce a novel attention pattern that integrates reasoning knowledge derived from a heterogeneous graph into the transformer architecture without relying on external knowledge. The proposed attention pattern comprises three key elements: global-local attention for word tokens, graph attention for entity tokens that exhibit strong attention towards tokens connected in the graph as opposed to those unconnected, and the consideration of the type of relationship between each entity token and word token. This results in optimized attention between the two if a relationship exists. The pattern is coupled with special relative position labels, allowing it to integrate with LUKE's entity-aware self-attention mechanism. The experimental findings corroborate that our model outperforms both the cutting-edge LUKE-Graph and the baseline LUKE model on the ReCoRD dataset that focuses on commonsense reasoning.Comment: submitted for Knowledge-Based Systems Journa

Genome Mapping and Molecular Breeding of Tomato

The cultivated tomato, Lycopersicon esculentum, is the second most consumed vegetable worldwide and a well-studied crop species in terms of genetics, genomics, and breeding. It is one of the earliest crop plants for which a genetic linkage map was constructed, and currently there are several molecular maps based on crosses between the cultivated and various wild species of tomato. The high-density molecular map, developed based on an L. esculentum × L. pennellii cross, includes more than 2200 markers with an average marker distance of less than 1 cM and an average of 750 kbp per cM. Different types of molecular markers such as RFLPs, AFLPs, SSRs, CAPS, RGAs, ESTs, and COSs have been developed and mapped onto the 12 tomato chromosomes. Markers have been used extensively for identification and mapping of genes and QTLs for many biologically and agriculturally important traits and occasionally for germplasm screening, fingerprinting, and marker-assisted breeding. The utility of MAS in tomato breeding has been restricted largely due to limited marker polymorphism within the cultivated species and economical reasons. Also, when used, MAS has been employed mainly for improving simply-inherited traits and not much for improving complex traits. The latter has been due to unavailability of reliable PCR-based markers and problems with linkage drag. Efforts are being made to develop high-throughput markers with greater resolution, including SNPs. The expanding tomato EST database, which currently includes ∼214 000 sequences, the new microarray DNA chips, and the ongoing sequencing project are expected to aid development of more practical markers. Several BAC libraries have been developed that facilitate map-based cloning of genes and QTLs. Sequencing of the euchromatic portions of the tomato genome is paving the way for comparative and functional analysis of important genes and QTLs

LUKE-Graph: A Transformer-based Approach with Gated Relational Graph Attention for Cloze-style Reading Comprehension

Incorporating prior knowledge can improve existing pre-training models in cloze-style machine reading and has become a new trend in recent studies. Notably, most of the existing models have integrated external knowledge graphs (KG) and transformer-based models, such as BERT into a unified data structure. However, selecting the most relevant ambiguous entities in KG and extracting the best subgraph remains a challenge. In this paper, we propose the LUKE-Graph, a model that builds a heterogeneous graph based on the intuitive relationships between entities in a document without using any external KG. We then use a Relational Graph Attention (RGAT) network to fuse the graph's reasoning information and the contextual representation encoded by the pre-trained LUKE model. In this way, we can take advantage of LUKE, to derive an entity-aware representation; and a graph model - to exploit relation-aware representation. Moreover, we propose Gated-RGAT by augmenting RGAT with a gating mechanism that regulates the question information for the graph convolution operation. This is very similar to human reasoning processing because they always choose the best entity candidate based on the question information. Experimental results demonstrate that the LUKE-Graph achieves state-of-the-art performance on the ReCoRD dataset with commonsense reasoning.Comment: submitted for neurocomputing journa

Identifying Molecular Markers Suitable For Frl Selection in Tomato Breeding

Modern plant breeding heavily relies on the use of molecular markers. In recent years, next generation sequencing (NGS) emerged as a powerful technology to discover DNA sequence polymorphisms and generate molecular markers very rapidly and cost effectively, accelerating the plant breeding programmes. A single dominant locus, Frl, in tomato provides resistance to the fungal pathogen Fusarium oxysporum f. sp. radicis-lycopersici (FORL), causative agent of Fusarium crown and root rot. In this study, we describe the generation of molecular markers associated with the Frl locus. An F2 mapping population between an FORL resistant and a susceptible cultivar was generated. NGS technology was then used to sequence the genomes of a susceptible and a resistant parent as well the genomes of bulked resistant and susceptible F2 lines. We zoomed into the Frl locus and mapped the locus to a 900 kb interval on chromosome 9. Polymorphic single-nucleotide polymorphisms (SNPs) within the interval were identified and markers co-segregating with the resistant phenotype were generated. Some of these markers were tested successfully with commercial tomato varieties indicating that they can be used for marker-assisted selection in large-scale breeding programmes

A new resonant-based sensor for non-invasive measurement of blood glucose levels

This paper presents a rapidly developed non-invasive microstrip sensor for measuring blood glucose levels (BGLs). The sensor features a microstrip closed-loop square resonator integrated with an interdigital capacitor (IDC), creating a sensitive area for glucose detection when a patient’s finger is placed on it. Using odd and even mode analytical methods and transmission line theory, we analyzed the sensor’s performance. Results indicate that the second even mode demonstrates significant changes across a standard glucose concentration range. The sensor was designed and simulated in ANSYS high frequency structure simulator (HFSS), showing a resonance frequency shift of up to 24.9 MHz at 1.94 GHz and a sensitivity of 110 kHz per mg/dL over a detection range of 0 to 216 mg/dL. Additionally, the frequency shift exhibits a high linear correlation (0.9485). In summary, the proposed sensor shows significant promise for achieving precise measurements of BGLs

Recent Advances in Multi-Choice Machine Reading Comprehension: A Survey on Methods and Datasets

This paper provides a thorough examination of recent developments in the field of multi-choice Machine Reading Comprehension (MRC). Focused on benchmark datasets, methodologies, challenges, and future trajectories, our goal is to offer researchers a comprehensive overview of the current landscape in multi-choice MRC. The analysis delves into 30 existing cloze-style and multiple-choice MRC benchmark datasets, employing a refined classification method based on attributes such as corpus style, domain, complexity, context style, question style, and answer style. This classification system enhances our understanding of each dataset's diverse attributes and categorizes them based on their complexity. Furthermore, the paper categorizes recent methodologies into Fine-tuned and Prompt-tuned methods. Fine-tuned methods involve adapting pre-trained language models (PLMs) to a specific task through retraining on domain-specific datasets, while prompt-tuned methods use prompts to guide PLM response generation, presenting potential applications in zero-shot or few-shot learning scenarios. By contributing to ongoing discussions, inspiring future research directions, and fostering innovations, this paper aims to propel multi-choice MRC towards new frontiers of achievement

Common QTL Affect the Rate of Tomato Seed Germination under Different Stress and Nonstress Conditions

The purpose of this study was to determine whether the rates of tomato seed germination under different stress and nonstress conditions were under common genetic controls by examining quantitative trait loci (QTL) affecting such traits. Seeds of BC1 progeny of a cross between a slow-germinating tomato breeding line and a rapid-germinating tomato wild accession were evaluated for germination under nonstress as well as cold, salt, and drought stress conditions. In each treatment, the most rapidly-germinating seeds were selected, grown to maturity, and subjected to molecular marker analysis. A selective genotyping approach detected between 6 and 9 QTL affecting germination rate under each of the four conditions, with a total of 14 QTL identified. Ten QTL affected germination rate under 2 or 3 conditions, which were considered germination-related common QTL. Four QTL affected germination rate only in one treatment, which were considered germination-related, condition-specific QTL . The results indicated that mostly the same QTL affected seed germination under different stress and nonstress conditions, supporting a previous suggestion that similar physiological mechanisms contribute to rapid seed germination under different conditions. Marker-assisted selection for the common QTL may result in progeny with rapid seed germinability under different conditions