Web News Timeline Generation with Extended Task Prompting

The creation of news timeline is essential for a comprehensive and contextual understanding of events as they unfold over time. This approach aids in discerning patterns and trends that might be obscured when news is viewed in isolation. By organizing news in a chronological sequence, it becomes easier to track the development of stories, understand the interrelation of events, and grasp the broader implications of news items. This is particularly helpful in sectors like finance and insurance, where timely understanding of the event development-ranging from extreme weather to political upheavals and health crises-is indispensable for effective risk management. While traditional natural language processing (NLP) techniques have had some success, they often fail to capture the news with nuanced relevance that are readily apparent to domain experts, hindering broader industry integration. The advance of Large Language Models (LLMs) offers a renewed opportunity to tackle this challenge. However, direct prompting LLMs for this task is often ineffective. Our study investigates the application of an extended task prompting technique to assess past news relevance. We demonstrate that enhancing conventional prompts with additional tasks boosts their effectiveness on various news dataset, rendering news timeline generation practical for professional use. This work has been deployed as a publicly accessible browser extension which is adopted within our network.Comment: 4 page

The role of echocardiography in prognosis for dysfunction and abandonment of radiocephalic arteriovenous fistula in elderly Chinese patients on hemodialysis

The objective of this study was to examine the impact of cardiac structure and function at baseline on the outcomes associated with arteriovenous fistula (AVF) in patients on hemodialysis (HD). Patients who initiated HD aged ≥70 years and received a mature AVF creation were included retrospectively. Echocardiographic parameters measured within 1 week before AVF creation were acquired. The observational period for each patient was from the point of AVF creation to the last time of follow‐up unless AVF abandonment or death occurred. Kaplan‐Meier and Cox proportional hazard regression analyses were conducted. A total of 82 elderly Chinese HD patients with mature radiocephalic AVF (RCAVF) and EF ≥50% were analyzed. During the median study period of 26.8 (12‐40) months, 42 (51.2%) experienced RCAVF dysfunction and 34 (41.5%) progressed to abandonment. Primary and cumulative patencies at 6, 12, 24, and 36 months were 81%, 73%, 48%, 38%, and 84%, 81%, 68%, 55%, respectively. Left ventricle end‐diastolic volume (LVEDV) ≤103.5 mL (HR = 2.5, P = .019) and the right side of RCAVF (HR = 3.59, P = .003) significantly predicted RCAVF dysfunction. The main pulmonary artery internal diameter (MPAID) ≤21.5 mm (HR = 4.3, P = .001) as well as the right side (HR = 2.95, P = .047) were the independent predictors for RCAVF abandonment. In conclusion, LVEDV, MPAID assessed by echocardiography and the right side of RCAVF, showed significant predictive implications for the outcomes of RCAVF. Disparities among nationalities in the areas of utilization and patency of AVFs necessitate additional studies.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156158/2/sdi12871.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156158/1/sdi12871_am.pd

Dynamic reliability sensitivity analysis for inter-story isolation structure under stochastic excitations

Considering the uncertainties of seismic excitation and stochastic parameters of the Inter-story Isolation Structure, the implicit structural response function is transformed into an explicit one by the Stochastic Response Surface Method (SRSM), combined with a probabilistic collocation method based on the linear independence principle. By using the reliability analysis method based on the first-passage failure, the reliability of isolation structure is analyzed and the sensitivity of the reliability of each sub-structure is further analyzed. The results show that conducting sensitivity research based on reliability analysis can provide an important theoretical basis for an optimized and robust design of a random vibration system. The changes of the stiffness and damping ratio of the Isolation Layer have a great influence on the reliability of the system and have different effects on the reliability of different parts of the system. The analysis results of reliability sensitivity could provide system reliability indexes to rank stochastic parameters by their importance, thus improving the efficiency of the structure reliability analysis and optimization design

Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives

Thanks to the augmented convenience, safety advantages, and potential commercial value, Intelligent vehicles (IVs) have attracted wide attention throughout the world. Although a few autonomous driving unicorns assert that IVs will be commercially deployable by 2025, their implementation is still restricted to small-scale validation due to various issues, among which precise computation of control commands or trajectories by planning methods remains a prerequisite for IVs. This paper aims to review state-of-the-art planning methods, including pipeline planning and end-to-end planning methods. In terms of pipeline methods, a survey of selecting algorithms is provided along with a discussion of the expansion and optimization mechanisms, whereas in end-to-end methods, the training approaches and verification scenarios of driving tasks are points of concern. Experimental platforms are reviewed to facilitate readers in selecting suitable training and validation methods. Finally, the current challenges and future directions are discussed. The side-by-side comparison presented in this survey not only helps to gain insights into the strengths and limitations of the reviewed methods but also assists with system-level design choices.Comment: 20 pages, 14 figures and 5 table

Zn⁺-O⁻ dual-spin surface states formation by modification of ZnO nanoparticles with diboron compounds

ZnO semiconductor oxides are versatile functional materials that are used in photoelectronics, catalysis, sensing, etc. The Zn⁺–O⁻ surface electronic states of semiconductor oxides were formed on the ZnO surface by Zn 4s and O 2p orbital coupling with the diboron compound’s B 2p orbitals. The formation of spin-coupled surface states was based on the spin–orbit interaction on the interface, which has not been reported before. This shows that the semiconductor oxide’s spin surface states can be modulated by regulating surface orbital energy. The Zn⁺–O⁻ surface electronic states were confirmed by electron spin resonance results, which may help in expanding the fundamental research on spintronics modulation and quantum transport

A versatile route to fabricate single atom catalysts with high chemoselectivity

Preparation of single atom catalysts (SACs) is of broad interest to materials scientists and chemists but remains a formidable challenge. Herein, we develop an efficient approach to synthesize SACs via a precursor-dilution strategy, in which metalloporphyrin (MTPP) with target metals are co-polymerized with diluents (tetraphenylporphyrin, TPP), followed by pyrolysis to N-doped porous carbon supported SACs (M1/N-C). Twenty-four different SACs, including noble metals and non-noble metals, are successfully prepared. In addition, the synthesis of a series of catalysts with different surface atom densities, bi-metallic sites, and metal aggregation states are achieved. This approach shows remarkable adjustability and generality, providing sufficient freedom to design catalysts at atomic-scale and explore the unique catalytic properties of SACs. As an example, we show that the prepared Pt1/N-C exhibits superior chemoselectivity and regioselectivity in hydrogenation. It only converts terminal alkynes to alkenes while keeping other reducible functional groups such as alkenyl, nitro group, and even internal alkyne intact