An official website of the United States government
The brevity of the instrumental record limits our knowledge of tropical cyclone activity on multidecadal to longer timescales and hampers our ability to diagnose climatic controls. Sedimentary archives containing event beds provide essential data on tropical cyclone activity over centuries and millennia. This review highlights the advantages and limitations of this approach and how these reconstructions have illuminated patterns of tropical cyclone activity and potential climate drivers over the last millennium. Key elements to developing high-quality reconstructions include confident attribution of event beds to tropical cyclones, assessing the potential role of other mechanisms, and evaluating the potential influence of geomorphic changes, sea-level variations, and sediment supply on a settings’ susceptibility to event bed deposition. Millennium-long histories of severe tropical cyclone occurrence are now available from many locations in the western North Atlantic and western North Pacific, revealing clear regional shifts in activity likely related to intervals of large-scale ocean-atmosphere reorganization.▪Prior to significant human influence in Earth's climate, natural climate variability dramatically altered patterns of tropical cyclone activity.▪For some regions (e.g., The Bahamas and the Marshall Islands), earlier intervals of tropical cyclone activity exceeded what humans have experienced during the recent period of instrumental measurements (∼1850 CE–present).▪Risk assessments based on the short instrumental record likely underestimate the threat posed by tropical cyclones in many regions.▪Changes in atmospheric and oceanic circulation associated with the Little Ice Age (∼1400–1800 CE) resulted in significant regional changes in tropical cyclone activity.▪Given the past sensitivity of tropical cyclone activity to climate change, we should anticipate regional shifts in tropical cyclone activity in response to ongoing anthropogenic warming of the planet.
more »
« less
This content will become publicly available on April 11, 2026
Domain-Informed Label Fusion Surpasses LLMs in Free-Living Activity Classification (Student Abstract)
FuSE-MET addresses critical challenges in deploying human activity recognition (HAR) systems in uncontrolled environments by effectively managing noisy labels, sparse data, and undefined activity vocabularies. By integrating BERT-based word embeddings with domain-specific knowledge (i.e., MET values), FuSE-MET optimizes label merging, reducing label complexity and improving classification accuracy. Our approach outperforms the state-of-the-art techniques, including ChatGPT-4, by balancing semantic meaning and physical intensity.
more »
« less
- Award ID(s):
- 2227002
- PAR ID:
- 10588892
- Publisher / Repository:
- AAAI
- Date Published:
- Journal Name:
- Proceedings of the AAAI Conference on Artificial Intelligence
- Volume:
- 39
- Issue:
- 28
- ISSN:
- 2159-5399
- Page Range / eLocation ID:
- 29495 to 29497
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Within the CSCL community and in computing and computational making more broadly, issues of equity continue to be under-researched and undertheorized. Here, we examine how FUSE Studios – a set of in-school, choice-based, STEAM learning environments, based around a set of digital and tangible making challenges – supports equitable access to and participation in making and computing. Drawing on web-log data and video-ethnographic data, we argue that four characteristics of FUSE support equity: the design of the challenges; the diverse ways of knowing and doing supported by the activity system; the specific interactions encouraged by the activity system; and the program’s placement inside school. We focus, here, on gender equity, but also discuss implications and planned research on other aspects of equity.more » « less
-
Many applications are designed to perform traversals ontree-likedata structures. Fusing and parallelizing these traversals enhance the performance of applications. Fusing multiple traversals improves the locality of the application. The runtime of an application can be significantly reduced by extracting parallelism and utilizing multi-threading. Prior frameworks have tried to fuse and parallelize tree traversals using coarse-grained approaches, leading to missed fine-grained opportunities for improving performance. Other frameworks have successfully supported fine-grained fusion on heterogeneous tree types but fall short regarding parallelization. We introduce a new frameworkOrchardbuilt on top ofGrafter.Orchard’s novelty lies in allowing the programmer to transform tree traversal applications by automatically applyingfine-grainedfusion and extractingheterogeneousparallelism.Orchardallows the programmer to write general tree traversal applications in a simple and elegant embedded Domain-Specific Language (eDSL). We show that the combination of fine-grained fusion and heterogeneous parallelism performs better than each alone when the conditions are met.more » « less
-
The rapid development of micro/nanomanipulation technologies has opened unprecedented opportunities for the sorting, assembly, and actuation of biological and inorganic entities for applications ranging from live‐cell separation, drug screening, biosensing to micro/nanomachines and nanorobots. To this end, remarkable progress has been made in the development of efficient, precise, and versatile nanomanipulation techniques based on individual or combined chemical and physical fields. Among them, techniques that fuse light stimuli with electric (E) fields, have achieved impressive performance in the versatility, reconfigurability, and throughput in the manipulation of both biological and inorganic micro/nanoscale objects compared to those of many other manipulation techniques, by leveraging the strong optoelectric coupling effect of semiconductor materials. This work provides a review of various types of light‐gated electric manipulation systems – the working principles, experimental setups, limitations, applications, and future perspectives.more » « less
-
Background Research has shown the feasibility of human activity recognition using wearable accelerometer devices. Different studies have used varying numbers and placements for data collection using sensors. Objective This study aims to compare accuracy performance between multiple and variable placements of accelerometer devices in categorizing the type of physical activity and corresponding energy expenditure in older adults. Methods In total, 93 participants (mean age 72.2 years, SD 7.1) completed a total of 32 activities of daily life in a laboratory setting. Activities were classified as sedentary versus nonsedentary, locomotion versus nonlocomotion, and lifestyle versus nonlifestyle activities (eg, leisure walk vs computer work). A portable metabolic unit was worn during each activity to measure metabolic equivalents (METs). Accelerometers were placed on 5 different body positions: wrist, hip, ankle, upper arm, and thigh. Accelerometer data from each body position and combinations of positions were used to develop random forest models to assess activity category recognition accuracy and MET estimation. Results Model performance for both MET estimation and activity category recognition were strengthened with the use of additional accelerometer devices. However, a single accelerometer on the ankle, upper arm, hip, thigh, or wrist had only a 0.03-0.09 MET increase in prediction error compared with wearing all 5 devices. Balanced accuracy showed similar trends with slight decreases in balanced accuracy for the detection of locomotion (balanced accuracy decrease range 0-0.01), sedentary (balanced accuracy decrease range 0.05-0.13), and lifestyle activities (balanced accuracy decrease range 0.04-0.08) compared with all 5 placements. The accuracy of recognizing activity categories increased with additional placements (accuracy decrease range 0.15-0.29). Notably, the hip was the best single body position for MET estimation and activity category recognition. Conclusions Additional accelerometer devices slightly enhance activity recognition accuracy and MET estimation in older adults. However, given the extra burden of wearing additional devices, single accelerometers with appropriate placement appear to be sufficient for estimating energy expenditure and activity category recognition in older adults.more » « less
