User Perspectives On Adoption Of A Hybrid Tagging System: A Case Of Topic Structure Of Zhihu Knowledge Community

Social tagging system has been prevalent thanks to its user-centric and flexible features. However, it suffers from its uncontrolled vocabulary and loose connection between tags. To overcome their drawbacks, a hybrid tagging system, which combines the ideas of the traditional taxonomy and social tagging, is adopting by some online knowledge communities. The top layers of the hybrid tagging system are determined by the website designer, while the bottom layers are constructed by users under certain restrictions. Due to the absence of sufficient research on user acceptance of this hybrid tagging system, cognitive factors affecting user adoption of the system is explored in this paper with topic structure of Zhihu, the famous Chinese knowledge community. An integrated model is proposed based on technology acceptance model and social cognitive theory. A survey will be conducted to empirically verify relationships between proposed constructs and actual usage. The research is expected to provide guidance for incremental improvement on a hybrid tagging system or development on new tagging systems

A Three-Party Case Study: Exploring the Value of Student Work in Co-creation in Teaching and Learning

In the context of a large first-year business course, we explore the value of student contributors, the former students from this course, working with faculty to improve the learning experience of the students enrolled in the course. By describing our study of the roles, impacts, benefits, and challenges of the student contributors’ involvement in creating supplemental resources, such as videos and practice problems, intended to augment the teaching process of the faculty and the learning process of the student learners, we contribute to the understanding of this three-party experience. Our study included interviews, survey questions, and resource-engagement analytics. We found that because student contributors can provide unique perspectives, greater inclusivity, and diverse approaches to teaching, there are benefits to the instructors, the student contributors, and the student learners

The non-gibberellic acid-responsive semi-dwarfing gene uzu affects Fusarium crown rot resistance in barley

BACKGROUND: Studies in Arabidopsis show that DELLA genes may differentially affect responses to biotrophic and necrophic pathogens. A recent report based on the study of DELLA-producing reduced height (Rht) genes in wheat and barley also hypothesized that DELLA genes likely increased susceptibility to necrotrophs but increased resistance to biotrophs. RESULTS: Effects of uzu, a non-GA (gibberellic acid)-responsive semi-dwarfing gene, on Fusarium crown rot (FCR) resistance in barley were investigated. Fifteen pairs of near isogenic lines for this gene were generated and assessed under two different temperature regimes. Similar to its impacts on plant height, the semi-dwarfing gene uzu also showed larger effects on FCR severity in the high temperature regime when compared with that in the low temperature regime. CONCLUSIONS: Results from this study add to the growing evidence showing that the effects of plant height on Fusarium resistances are unlikely related to DELLA genes but due to direct or indirect effects of height difference per se. The interaction between these two characteristics highlights the importance of understanding relationships between resistance and other traits of agronomic importance as the value of a resistance gene could be compromised if it dramatically affects plant development and morphology

Genome-Wide Association Study Reveals Novel Genomic Regions Associated With High Grain Protein Content in Wheat Lines Derived From Wild Emmer Wheat

Grain protein content (GPC) and yield are of two important traits in wheat, but their negative correlation has hampered their simultaneous improvement in conventional breeding. Wild emmer wheat (Triticum turgidum ssp. dicoccoides) is an important genetic resource for wheat quality improvement. In this study, we report a genome-wide association study (GWAS) using 13116 DArT-seq markers to characterize GPC in 161 wheat lines derived from wild emmer. Using a general linear model, we identified 141 markers that were significantly associated with GPC, and grouped into 48 QTL regions. Using both general linear model and mixed linear model, we identified four significant markers that were grouped into two novel QTL regions on chromosomes 2BS (QGpc.cd1-2B.1) and 7BL (QGpc.cd1-7B.2). The two QTLs have no negative effects on thousand kernel weight (TKW) and should be useful for simultaneous improvement of GPC and TKW in wheat breeding. Searches of public databases revealed 61 putative candidate/flanking genes related to GPC. The putative proteins of interest were grouped in four main categories: enzymes, kinase proteins, metal transport-related proteins, and disease resistance proteins. The linked markers and associated candidate genes provide essential information for cloning genes related to high GPC and performing marker-assisted breeding in wheat

CT-based radiomic phenotypes of lung adenocarcinoma: a preliminary comparative analysis with targeted next-generation sequencing

ObjectivesThis study aimed to explore the relationship between computed tomography (CT)-based radiomic phenotypes and genomic profiles, including expression of programmed cell death-ligand 1 (PD-L1) and the 10 major genes, such as epidermal growth factor receptor (EGFR), tumor protein 53 (TP53), and Kirsten rat sarcoma viral oncogene (KRAS), in patients with lung adenocarcinoma (LUAD).MethodsIn total, 288 consecutive patients with pathologically confirmed LUAD were enrolled in this retrospective study. Radiomic features were extracted from preoperative CT images, and targeted genomic data were profiled through next-generation sequencing. PD-L1 expression was assessed by immunohistochemistry staining (chi-square test or Fisher's exact test for categorical data and the Kruskal–Wallis test for continuous data). A total of 1,013 radiomic features were obtained from each patient's CT images. Consensus clustering was used to cluster patients on the basis of radiomic features.ResultsThe 288 patients were classified according to consensus clustering into four radiomic phenotypes: Cluster 1 (n = 11) involving mainly large solid masses with a maximum diameter of 5.1 ± 2.0 cm; Clusters 2 and 3 involving mainly part-solid and solid masses with maximum diameters of 2.1 ± 1.4 cm and 2.1 ± 0.9 cm, respectively; and Cluster 4 involving mostly small ground-glass opacity lesions with a maximum diameter of 1.0 ± 0.9 cm. Differences in maximum diameter, PD-L1 expression, and TP53, EGFR, BRAF, ROS1, and ERBB2 mutations among the four clusters were statistically significant. Regarding targeted therapy and immunotherapy, EGFR mutations were highest in Cluster 2 (73.1%); PD-L1 expression was highest in Cluster 1 (45.5%).ConclusionOur findings provide evidence that CT-based radiomic phenotypes could non-invasively identify LUADs with different molecular characteristics, showing the potential to provide personalized treatment decision-making support for LUAD patients

AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors in Agents

Autonomous agents empowered by Large Language Models (LLMs) have undergone significant improvements, enabling them to generalize across a broad spectrum of tasks. However, in real-world scenarios, cooperation among individuals is often required to enhance the efficiency and effectiveness of task accomplishment. Hence, inspired by human group dynamics, we propose a multi-agent framework \framework that can collaboratively and dynamically adjust its composition as a greater-than-the-sum-of-its-parts system. Our experiments demonstrate that \framework framework can effectively deploy multi-agent groups that outperform a single agent. Furthermore, we delve into the emergence of social behaviors among individual agents within a group during collaborative task accomplishment. In view of these behaviors, we discuss some possible strategies to leverage positive ones and mitigate negative ones for improving the collaborative potential of multi-agent groups. Our codes for \framework will soon be released at \url{https://github.com/OpenBMB/AgentVerse}.Comment: Work in progres

Uncovering the dispersion history, adaptive evolution and selection of wheat in China

Wheat was introduced to China approximately 4500 years ago, where it adapted over a span of time to various environments in agro-ecological growing zones. We investigated 717 Chinese and 14 Iranian/Turkish geographically diverse, locally adapted wheat landraces with 27,933 DArTseq (for 717 landraces) and 312,831 Wheat660K (for a subset of 285 landraces) markers. This study highlights the adaptive evolutionary history of wheat cultivation in China. Environmental stresses and independent selection efforts have resulted in considerable genome-wide divergence at the population level in Chinese wheat landraces. In total, 148 regions of the wheat genome show signs of selection in at least one geographic area. Our data show adaptive events across geographic areas, from the xeric northwest to the mesic south, along and among homoeologous chromosomes, with fewer variations in the D genome than in the A and B genomes. Multiple variations in interdependent functional genes, such as regulatory and metabolic genes controlling germination and flowering time were characterized, showing clear allelic frequency changes corresponding to the dispersion of wheat in China. Population structure and selection data reveal that Chinese wheat spread from the northwestern Caspian Sea region to south China, adapting during its agricultural trajectory to increasingly mesic and warm climatic areas