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Optimal life insurance and annuity decisions under money illusion
No full textThis paper investigates the optimal consumption, investment, and life insurance/annuity decisions for a family in an inflationary economy under money illusion. The family can invest in a financial market that consists of nominal bonds, inflation-linked bonds, and a stock index. The breadwinner can also purchase life insurance or annuities that are available continuously. The family's objective is to maximize the expected utility of a mixture of nominal and real consumption, as they partially overlook inflation and tend to think in terms of nominal rather than real monetary values. We formulate this life-cycle problem as a random horizon utility maximization problem and derive the optimal strategy. We calibrate our model to the U.S. data and demonstrate that money illusion increases life insurance demand for young adults and reduces annuity demand for retirees. Our findings indicate that the money illusion contributes to the annuity puzzle and highlight the role of financial literacy in an inflationary environment.</p
Assessing historical snowfall patterns in Seoul from 1625 to 1907 CE in relation to the Grand Solar Minima
No full textThe Sun is the primary energy source driving the Earth's climate system. A prevailing hypothesis suggests that even minor variations in solar activity, when amplified by climate system feedback mechanisms, can induce significant climatic changes on decadal to centennial timescales. However, the limited availability of historical winter climate proxies has impeded consensus on how solar variability influences the long-term winter climate in Northeast Asia, particularly during Grand Solar Minima (GMs). In this study, we analyzed daily-resolution snowfall records in Seoul from 1625 to 1907 CE, derived from the Korean official historical chronicle Seungjeongweon Ilgi. This period encompasses both the Maunder Minimum (1645–1715 CE) and the Dalton Minimum (1790–1830 CE) of solar activity. Our findings indicate that during the GMs, the first date of annual snowfall (FDS) was delayed by approximately 10 days, and the average annual snowfall frequency (ASF) was reduced by half compared to non-GM periods. Additionally, while an 11-year solar cycle was evident in the ASF during non-GM periods, this cycle was replaced by a shortened 8- to 9-year cycle during the GMs. These variations suggest a differential regional climatic response to prolonged changes in solar activity, and provide historical insights that enhance our understanding of the potential impact of low solar activity on the winter climate in Northeast Asia
A Survey of Reasoning with Foundation Models: Concepts, Methodologies, and Outlook
No full textReasoning, a crucial ability for complex problem-solving, plays a pivotal role in various real-world settings such as negotiation, medical diagnosis, and criminal investigation. It serves as a fundamental methodology in the field of Artificial General Intelligence (AGI). With the ongoing development of foundation models, there is a growing interest in exploring their abilities in reasoning tasks. In this article, we introduce seminal foundation models proposed or adaptable for reasoning, highlighting the latest advancements in various reasoning tasks, methods, and benchmarks. We then delve into the potential future directions behind the emergence of reasoning abilities within foundation models. We also discuss the relevance of multimodal learning, autonomous agents, and super alignment in the context of reasoning. By discussing these future research directions, we hope to inspire researchers in their exploration of this field, stimulate further advancements in reasoning with foundation models, e.g., Large Language Models (LLMs), and contribute to the development of AGI.</p
GigaTok: Scaling Visual Tokenizers to 3 Billion Parameters for Autoregressive Image Generation
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Exploring the pathways linking fasting insulin to coronary artery disease: a proteome-wide Mendelian randomization study
No full textBackground: Insulin is known to be associated with a higher risk of coronary artery disease (CAD), but molecular mechanisms remain unclear. This study aimed to explore protein-mediated pathways linking fasting insulin to CAD using Mendelian randomization (MR). Methods: This MR study examined the association between fasting insulin and CAD using genome-wide association study (GWAS) data from MAGIC and CARDIoGRAMplusC4D. To investigate underlying mechanisms, a two-step proteome-wide MR analysis was conducted. First, associations of fasting insulin with 2940 circulating proteins were assessed using GWAS of proteomics from UKB-PPP. Proteins affected by insulin were then analyzed for their association with CAD risk. Proteins selected in both steps were considered as potential mediators. Sensitivity analyses to test whether associations are robust to pleiotropy and replication using other GWAS data, including GWAS of proteomics from deCODE and GWAS of CAD from FinnGen Biobank, were performed. Results: Genetically predicted insulin was associated with a higher risk of CAD (odds ratio 1.79, 95% confidence interval 1.34 to 2.40). At a false discovery rate of 0.05, insulin affected 355 proteins, ten of which were both increased by insulin and linked to a higher risk of CAD. After sensitivity and replication analyses, PLA2G7, GZMA, LDLR, AGRP, and HHEX were identified as reliable mediators. Mediation analyses using non-pleiotropic instruments showed that PLA2G7, GZMA, LDLR, and AGRP explained 19.50%, 6.91%, 19.31%, and 29.66% of insulin’s total effect on CAD, respectively. Conclusions: This study identified five protein mediators linking insulin to CAD. These proteins could be considered as potential targets to mitigate insulin-related cardiovascular risk, providing novel insights for drug repurposing
Profit-sensitive generative design for high-rise building morphologies: innovations in 3D form generation and cost-revenue assessment
No full textGenerative design has been applied to facilitate architectural exploration and augment designers’ ability to consider building profits. However, the take-up of generative design instruments is slow due to the lack of considering practical needs. This paper reports a novel generative design methodology that meets the practical needs of profit-aware morphology for high-rise buildings. It follows a generation–evaluation–optimization workflow but is enriched with a novel shape generator; an evaluator estimating construction cost and selling revenue; and an optimizer using genetic algorithms. The methodology is prototyped in Grasshopper with Python programs embedded and then tested in two real cases in Hong Kong. We find that the methodology is effective in generating complex yet plausible morphologies for high-rises, evaluating their costs and revenues, and deriving profit-optimal buildings. This research contributes to the growing literature on generative design and could lead to a practical design tool that bridges designers and surveying professions.</p
Design of teaching main line for robot engineering major directed by new engineering education
No full textNew engineering education (NEE) proposes new challenges for traditional engineering education. The paper defines the teaching main line of undergraduate major under the NEE framework, elaborates on the hierarchical structure division method of the teaching main line from both vertical and horizontal perspectives, and explores the setting and evaluation indicators of the teaching main line. Taking the three courses of Robot Modeling and Control, Embedded Systems and Robots, and ROSs (Robot Operating Systems) in the field of robotics engineering as examples, the teaching main line is set up by reverse decomposition of the overall objectives of the new engineering. The teaching knowledge points of the courses are effectively grasped to evaluate the execution effect of the teaching main line, and feedback is provided to improve the setting of the teaching main line and the execution of the teaching process. The relevant research methods and experiences have important reference significance for the integration of NEE in engineering universities/colleges, especially in the field of robotics engineering courses.</p
