4-Bromo-1-[2,6-dichloro-4-(trifluoro­meth­yl)phen­yl]-5-(4-methoxy­benzyl­ideneamino)-1H-pyrazole-3-carbonitrile

The title compound, C19H10BrCl2F3N4O, is an imine with an overall Y shape. The dihedral angles between the pyrazole ring and the methoxy- and trifluoromethyl-substituted benzene ring planes are 88.4 (2) and 65.8 (2)°, respectively

Use of Structural Equation Modelling and Neural Network to Analyse Shared Parking Choice Behaviour

The shared parking mode represents a feasible solution to the persistent problem of parking scarcity in urban areas. This paper aims to examine the shared parking choice behaviours using a combination of structural equation modelling (SEM) and neural network, taking into account both the parking location characteristics and the travellers’ characteristics. Data were collected from a commercial district in Nanjing, China, through an online questionnaire survey covering 11 factors affecting shared parking choice. The method involved two steps: firstly, SEM was applied to examine the influence of these factors on shared parking choice. Following this, the seven factors with the strongest correlation to shared parking choice were used to train a neural network model for shared parking prediction. This SEM-informed model was found to outperform a neural network model trained on all eleven factors across precision, recall, accuracy, F1 and AUC metrics. The research concluded that the selected factors significantly influence shared parking choice, reinforcing the hypothesis regarding the importance of parking location and traveller characteristics. These findings provide valuable insights to support the effective implementation and promotion of shared parking

Hierarchical Prompting Assists Large Language Model on Web Navigation

Large language models (LLMs) struggle on processing complicated observations in interactive decision making tasks. To alleviate this issue, we propose a simple hierarchical prompting approach. Diverging from previous prompting approaches that always put the full observation (e.g. a web page) to the prompt, we propose to first construct an action-aware observation which is more condensed and relevant with a dedicated SUMMARIZER prompt. The ACTOR prompt then predicts the next action based on the summarized observation. While our method has broad applicability, we particularly demonstrate its efficacy in the complex domain of web navigation where a full observation often contains redundant and irrelevant information. Our approach outperforms the previous state-of-the-art prompting mechanics by 6.2% on task success rate, demonstrating its potential on interactive decision making tasks with long observation traces.Comment: EMNLP 2023 Findings; Natural Language Reasoning and Structured Explanations Workshop at ACL 202

Targeting UDP-α-D-glucose 6-dehydrogenase inhibits glioblastoma growth and migration

UDP-glucose 6-dehydrogenase (UGDH) produces UDP-α-D-glucuronic acid, the precursors for glycosaminoglycans (GAGs) and proteoglycans of the extracellular matrix. Elevated GAG formation has been implicated in a variety of human diseases, including glioblastoma (GBM). In our previous study, we found that Krüppel-like factor 4 (KLF4) promotes GBM cell migration by binding to methylated DNA, mainly methylated CpGs (mCpG) and transactivating gene expression. We identified UDGH as one of the downstream targets of KLF4-mCpG binding activity. In this study, we show that KLF4 upregulates UGDH expression in a mCpG-dependent manner, and UGDH is required for KLF4-induced cell migration in vitro. UGDH knockdown decreases GAG abundance in GBM cells, as well as cell proliferation and migration in vitro. In intracranial xenografts, reduced UGDH inhibits tumor growth and migration, accompanied by a decrease in the expression of extracellular matrix proteins such as tenascin C, brevican. Our studies demonstrate a novel DNA methylation-dependent UGDH upregulation by KLF4. Developing UGDH antagonists to decrease the synthesis of extracellular matrix components will be a useful strategy for GBM therapy

Study on Yield Stress and Thixotropy of Hydroxypropyl Distarch Phosphate Paste

In order to study the yield stress and thixotropic behavior of the hydroxypropyl distarch phosphate (HPDSP) paste, HPDSP respectively derived from corn starch (CS) and waxy corn starch (WS) with different ratios of amylopectin were investigated. The critical mass fractions, yield stress, and thixotropic behavior of HPDSP pastes under various temperatures were studied. The results showed that, the critical mass fractions for the transition of the HPDSP solution at 5 ℃ from dilute to semi-dilute, and from semi-dilute to concentrated were 3wt% and 6wt%, respectively. The yield stress of 5wt% corn starch-hydroxypropyl distarch phosphate (CS-HPDSP) and waxy corn starch-hydroxypropyl distarch phosphate (WS-HPDSP) paste both showed weak correlations with temperature. However, at 6wt% concentration, the yield stress significantly decreased (P<0.05) by 69.52% and 77.95% respectively at 85 ℃. Additionally, the thixotropic behavior of HPDSP was influenced by both mass fraction and temperature. At 5 ℃, 5wt% CS-HPDSP and WS-HPDSP showed limited thixotropy, while at 6wt% of mass fraction, the areas of thixotropic loops of CS-HPDSP and WS-HPDSP were 163.49 and 85.00 Pa/s, respectively, and decreased by 86.38% and 92.18% at 85 ℃, respectively. WS-HPDSP exhibited less thixotropic behavior than CS-HPDSP, and showed better stability in three interval thixotropy test (3iTT). In conclusion, WS-HPDSP showed less yield stress and thixotropy compared with CS-HPDSP. This study provides theoretical supports for practical application of HPDSP as thickening agents in food products

Polyploidy events shaped the expansion of transcription factors in Cucurbitaceae and exploitation of genes for tendril development

Cucurbitaceae is one of the most important plant families distributed worldwide. Transcription factors (TFs) regulate plant growth at the transcription level. Here, we performed a systematic analysis of 42 641 TFs from 63 families in 14 Cucurbitaceae and 10 non-cucurbit species. Whole-genome duplication (WGD) was the dominant event type in almost all Cucurbitaceae plants. The TF families were divided into 1 210 orthogroups (OGs), of which, 112 were unique to Cucurbitaceae. Although the loss of several gene families was detected in Cucurbitaceae, the gene families expanded in five species that experienced a WGD event comparing with grape. Our findings revealed that the recent WGD events that had occurred in Cucurbitaceae played important roles in the expansion of most TF families. The functional enrichment analysis of the genes that significantly expanded or contracted uncovered five gene families, AUX/IAA, NAC, NBS, HB, and NF-YB. Finally, we conducted a comprehensive analysis of the TCP gene family and identified 16 tendril-related (TEN) genes in 11 Cucurbitaceae species. Interestingly, the characteristic sequence changed from CNNFYFP to CNNFYLP in the TEN gene (Bhi06M000087) of Benincasa hispida. Furthermore, we identified a new characteristic sequence, YNN, which could be used for TEN gene exploitation in Cucurbitaceae. In conclusion, this study will serve as a reference for studying the relationship between gene family evolution and genome duplication. Moreover, it will provide rich genetic resources for functional Cucurbitaceae studies in the future

WebArena: A Realistic Web Environment for Building Autonomous Agents

With advances in generative AI, there is now potential for autonomous agents to manage daily tasks via natural language commands. However, current agents are primarily created and tested in simplified synthetic environments, leading to a disconnect with real-world scenarios. In this paper, we build an environment for language-guided agents that is highly realistic and reproducible. Specifically, we focus on agents that perform tasks on the web, and create an environment with fully functional websites from four common domains: e-commerce, social forum discussions, collaborative software development, and content management. Our environment is enriched with tools (e.g., a map) and external knowledge bases (e.g., user manuals) to encourage human-like task-solving. Building upon our environment, we release a set of benchmark tasks focusing on evaluating the functional correctness of task completions. The tasks in our benchmark are diverse, long-horizon, and designed to emulate tasks that humans routinely perform on the internet. We experiment with several baseline agents, integrating recent techniques such as reasoning before acting. The results demonstrate that solving complex tasks is challenging: our best GPT-4-based agent only achieves an end-to-end task success rate of 14.41%, significantly lower than the human performance of 78.24%. These results highlight the need for further development of robust agents, that current state-of-the-art large language models are far from perfect performance in these real-life tasks, and that WebArena can be used to measure such progress.Comment: Our code, data, environment reproduction resources, and video demonstrations are publicly available at https://webarena.dev

High-sensitivity magnetic sensor based on the evanescent scattering by a magnetorheological film

We present a simple concept to implement a magnetic sensor that uses evanescent scattering by a suspended magnetorheological (MR) film above a planar waveguide. The soft MR film embedded with ferromagnetic particles is to induce scattering on the evanescent field of a planar waveguide at a proximity distance. This distance can be controlled precisely by a magnetic field. Consequently, the waveguide output power changes in response to the magnetic intensity. Two sensor prototypes of different film thicknesses were designed and tested showing a trade-off between the sensitivity and dynamic sensing range. A maximum sensitivity of ∼2.62dB/mT was obtained. Compared to optical micro-electromechanical systems, the presented sensors feature a simple design, easy fabrication, low cost, and the potential for large-scale production and miniaturization to be integrated into portable devices

High-quality ice plant reference genome analysis provides insights into genome evolution and allows exploration of genes involved in the transition from C3 to CAM pathways

Ice plant (Mesembryanthemum crystallinum), a member of the Aizoaceae family, is a typical halophyte crop and a model plant for studying the mechanism of transition from C3 photosynthesis to crassulacean acid metabolism (CAM). Here, we report a high-quality chromosome-level ice plant genome sequence. This 98.05% genome sequence is anchored to nine chromosomes, with a total length of 377.97 Mb and an N50 scaffold of 40.45 Mb. Almost half of the genome (48.04%) is composed of repetitive sequences, and 24 234 genes have been annotated. Subsequent to the ancient whole-genome triplication (WGT) that occurred in eudicots, there has been no recent whole-genome duplication (WGD) or WGT in ice plants. However, we detected a novel WGT event that occurred in the same order in Simmondsia chinensis, which was previously overlooked. Our findings revealed that ice plants have undergone chromosome rearrangements and gene removal during evolution. Combined with transcriptome and comparative genomic data and expression verification, we identified several key genes involved in the CAM pathway and constructed a comprehensive network. As the first genome of the Aizoaceae family to be released, this report will provide a rich data resource for comparative and functional genomic studies of Aizoaceae, especially for studies on salt tolerance and C3-to-CAM transitions to improve crop yield and resistance