Article
Multidisciplinary Sciences
Utku Emre Ali, Gaurav Modi, Ritesh Agarwal, Harish Bhaskaran
Summary: Phase-change materials have the ability to permanently and reversibly switch between amorphous and crystalline states. In this study, nanowires were used as active nanoelectromechanical systems to overcome limitations in suspended thin-film configurations. By exploiting a dislocation-based route for amorphization, the researchers achieved active modulation of Young's modulus in GeTe nanowires. These nanowires enabled power-free tuning of resonance frequency and demonstrated real-time frequency tuning in a frequency-hopping spread spectrum radio prototype.
NATURE COMMUNICATIONS
(2022)
Article
Environmental Sciences
Hancheng Guo, Yanyu Wang, Jie Yu, Lina Yi, Zhou Shi, Fumin Wang
Summary: Understanding terrestrial ecosystem dynamics requires a comprehensive examination of vegetation changes. Remote sensing technology has been established as an effective approach to comprehensively assess vegetation change. In this study, a novel framework integrating short-term disturbance detection and long-term trend analysis was proposed and applied to characterize vegetation changes in Zhejiang Province from 1990 to 2020. The results showed a browning trend in the plains and a greening trend in the mountains, with an overall greening of the vegetation during the study period.
ENVIRONMENTAL RESEARCH
(2023)
Article
Environmental Sciences
Dainius Masiliunas, Nandin-Erdene Tsendbazar, Martin Herold, Jan Verbesselt
Summary: BFAST Lite is an improved unsupervised time series change detection algorithm derived from the original BFAST algorithm, offering increased speed and flexibility. It has similar accuracy to BFAST but is significantly faster and more flexible, with the ability to handle missing values and provide the best balance between user's and producer's accuracy. It serves as a useful addition to aid in global land cover change detection.
Article
Environmental Sciences
Zhiying Li, Steven M. Quiring
Summary: This study predicts future streamflow changes in 889 watersheds in the contiguous United States based on projected climate and land use changes. The results show that the random forest model can explain over 85% of the variance in most watersheds. The study also found that relative cumulative moisture surplus, forest coverage, crop land, and urban land are the most important variables affecting the time-varying omega.
WATER RESOURCES RESEARCH
(2022)
Article
Multidisciplinary Sciences
Fuxiao Li, Mengli Hao, Lijuan Yang
Summary: This study introduces two test statistics for change-point detection in health care data, which are the standardized efficient score vector and the quadratic form of the efficient score vector with a weight function. The research shows that the two methods perform differently at various change-point positions, with consistency and robustness.
Article
Engineering, Electrical & Electronic
Chandrabali Karmakar, Corneliu Octavian Dumitru, Nick Hughes, Mihai Datcu
Summary: This article presents a novel framework to model and understand image dynamics in Openly available satellite image time series (SITS). The framework utilizes visualizations and domain knowledge to efficiently integrate machine learning pipelines in the absence of ground truth data. The framework is validated through a case study in a Polar region, where limited ground truth data is extended to discover temporal evolution at the image patch level.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Business
Donncha Kavanagh, Geoff Lightfoot, Simon Lilley
Summary: The paper challenges the assertion that social change is proceeding at hyper-speed and argues that millennial Americans are not living in a particularly rapid period of social change, especially when compared to 1900-1950. The analysis suggests that a punctuated equilibrium model of change is more supported by the data than significant variation occurring in long wave-like cycles.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Article
Surgery
Andrea Pietrabissa, Patricia Sylla
Summary: The operating room is a significant source of pollution due to various factors like energy consumption, consumables procurement and disposal, and water waste. Taking action to reduce the environmental impact of surgery and slow down climate change has become a priority. The collaboration between SAGES and EAES aims to raise awareness, provide recommendations, and share good practices regarding sustainable and environmentally-friendly surgical techniques.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2023)
Article
Psychology, Multidisciplinary
L. Alison Phillips, Kimberly R. R. More
Summary: Researchers conducted a secondary analysis of a 4-week experiment on young women and found that intentions and self-efficacy predicted initial behavioral engagement, while habit strength was a significant predictor of behavioral frequency.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Geochemistry & Geophysics
Shane R. Cloude
Summary: This letter presents a new approach to analyze polarimetric radar time series by focusing on the changes in the full coherency matrix of the scene. The method involves forming matrix differences over time to obtain physical coherency matrix, and it was applied to study agricultural changes over a two-year period using L-band POLSAR data from the NASA-JPL UAVSAR system.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Environmental Sciences
Daniele Marinelli, Michele Dalponte, Lorenzo Frizzera, Erik Naesset, Damiano Gianelle
Summary: Forest disturbances have a significant impact on ecosystem dynamics and it is important to gather objective information about their location, nature, and timing. Existing methods focus more on detecting stand replacing disturbances (SRD) and less on non-stand replacing disturbances (NSRD). In this study, a method for automated detection of both SRD and NSRD is proposed, using a two-dimensional grid-like structure to analyze the sequence of images. The method has been tested and achieved high accuracy for detecting disturbed areas.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Construction & Building Technology
Ebrahim Farrokh
Summary: This paper discusses common methodologies used in the prediction of cutter change time and cutter consumption, and proposes new models based on statistical analysis to improve accuracy.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2021)
Article
Environmental Sciences
Ekbal Hussain, Alessandro Novellino, Colm Jordan, Luke Bateson
Summary: Traditional applications of InSAR data involve inverting interferograms to determine average displacement, but fitting a line through the time series results in loss of information. Thanks to regular acquisitions by the Sentinel-1 satellite constellation, opportunities for near-real time deformation monitoring are now available. A statistical approach is presented for detecting offsets and gradient changes in InSAR time series, utilizing 5 years of Sentinel-1 data to calculate population standard deviation. Detection of statistically significant peaks in differences series and movements in derivative series are key components of the method. Exploiting the high spatial resolution and spatial continuity of Sentinel-1 data allows for filtering out false positive detections and potential detection of ground deformation associated with geophysical phenomena.
Article
Mathematics, Interdisciplinary Applications
Hongyu Qin, Xiaoli Chen, Boya Zhou
Summary: This paper presents a finite difference method for solving fractional differential equations numerically. The numerical schemes are developed based on change in variable and piecewise interpolations. Error analysis of the numerical schemes is obtained using a Gronwall-type inequality. Numerical examples are provided to validate the theoretical results.
FRACTAL AND FRACTIONAL
(2023)
Article
Environmental Sciences
Annarosa Quarello, Olivier Bock, Emilie Lebarbier
Summary: This paper presents a novel segmentation method called segfunc for analyzing GNSS Integrated Water Vapour data. By estimating the variance and change points, this method homogenizes the data to improve the usage of observational data for climate analysis. The performance of the method has been verified through numerical simulation experiments and achieved a high hit rate when applied to real data.
