Data Sheet 1_Emotional prompting amplifies disinformation generation in AI large language models.docx by Rasita Vinay (21006911)

“…Introduction<p>The emergence of artificial intelligence (AI) large language models (LLMs), which can produce text that closely resembles human-written content, presents both opportunities and risks. …”

Pearson’s correlation matrix among agronomic traits based on BLUEs. by Fatima Henkrar (17346528)

Feasibility of AI-powered assessment scoring: Can large language models replace human raters? by Michael Jaworski III (22156096)

Definitions of traits for association analyses. by Dai Nogimura (21445649)

“…<div><p>Decreased nitric oxide (NO) production from the vascular endothelium is a major factor for vascular aging. …”

Genetic correlations between sMRI traits and BMI. by Daniela Fusco (10027975)

Causes and consequences of long-term defaunation in multi-species aggregations: Species traits predict freshwater mussel declines and decreases in biogeochemical storage and recycl... by Jonathan Lopez (16993383)

Summary of subscales or questions utilized to define traits. by Dai Nogimura (21445649)

Genetic correlation between BMI and 435 sMRI traits. by Daniela Fusco (10027975)

Genes associated by SMR to both BMI and at least one sMRI trait. by Daniela Fusco (10027975)

A novel RNN architecture to improve the precision of ship trajectory predictions by Martha Dais Ferreira (18704596)

“…To solve these challenges, Recurrent Neural Network (RNN) models have been applied to STP to allow scalability for large data sets and to capture larger regions or anomalous vessels behavior. …”

(A) The expression of DCXR and HRSP12 was higher in the DN model; (B) The expression of DCXR and HRSP12 was decreased compared with the normal control after knockout; (C) CCK8 expe... by Hongmin Luo (2142307)

Identification of quantitative trait gene (QTG) for meat color lightness (L*) and redness (a*) in chickens. by Jiahong Sun (6497603)

AI KRegression by CHIN-CHENG CHU (20718575)

Principal component analysis of agronomic traits and genotypes. by Fatima Henkrar (17346528)

Presentation 1_Tracking priming-induced language recovery in aphasia with pre-trained language models.zip by Yan Cong (1491478)

Data Sheet 1_Tracking priming-induced language recovery in aphasia with pre-trained language models.zip by Yan Cong (1491478)

Estimates of genetic parameters correlations and phenotypic correlations between meat color traits in fast-growing white-feathered broilers. by Jiahong Sun (6497603)

Image 2_Identification of candidate genes for reproductive traits in Xinjiang sheep breeds based on genomic structural variation.tif by Jiaqi Li (220961)

“…In this study, we characterized genomic SVs and identified candidate genes related to germplasm traits in seven sheep breeds. Based on the genome sequences of 73 ewes, SVs were detected using Delly, Lumpy, and Manta software tools, and the results were integrated using SURVIVOR software, leading to the identification of 107,166 SVs. …”

Table 1_Identification of candidate genes for reproductive traits in Xinjiang sheep breeds based on genomic structural variation.xlsx by Jiaqi Li (220961)

“…In this study, we characterized genomic SVs and identified candidate genes related to germplasm traits in seven sheep breeds. Based on the genome sequences of 73 ewes, SVs were detected using Delly, Lumpy, and Manta software tools, and the results were integrated using SURVIVOR software, leading to the identification of 107,166 SVs. …”

Image 3_Identification of candidate genes for reproductive traits in Xinjiang sheep breeds based on genomic structural variation.tif by Jiaqi Li (220961)

“…In this study, we characterized genomic SVs and identified candidate genes related to germplasm traits in seven sheep breeds. Based on the genome sequences of 73 ewes, SVs were detected using Delly, Lumpy, and Manta software tools, and the results were integrated using SURVIVOR software, leading to the identification of 107,166 SVs. …”