Assessing the long-term urban heat island in San Antonio, Texas based on moderate resolution imaging spectroradiometer/Aqua Data

Urban environmental conditions are strongly dependent on the land use and land cover properties. Urban and rural areas normally exhibit obvious difference in land surface temperature (LST). The Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua (PM satellite) MYD11A1 temperature products (daily and 1 km spatial resolution) for the period from June 1 to September 30 between 2002 and 2008 were used to screen the existence of urban heat island (UHI) phenomena for the city of San Antonio, TX. 8-day MYD11A2 temperature products between 2002 and 2008 were also retrieved to map the temperature climatology at the 1:30 a.m. for the region. The UHI effect was detected in both satellite surface- temperature and meteorological station air- temperature record. The existence of an UHI of the San Antonio downtown area was clearly shown in about 90% of the available cloud- free (or cloudless) data from June 1-September 30 each year. It is especially prevalent in the night- time imagery due to less cloud contamination. During nighttime, the heat island (HI) is about 4 - 5 degrees K (6 - 8 degrees F) higher than the average temperature of the study area and 6 7 degrees K (8 - 12 degrees F) higher than the rural area. Surprisingly, the HI phenomenon is found not only in the downtown area, but also several other small areas in the northern corner. Finally, the long- term UHI effect of San Antonio and its relationship with normalized difference vegetation index (NDVI) were discussed. USGS rainfall data were also used to discuss the possible connections between the UHI and several local storm events

Surface flooding of Antarctic summer sea ice

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ackley, S. F., Perovich, D. K., Maksym, T., Weissling, B., & Xie, H. Surface flooding of Antarctic summer sea ice. Annals of Glaciology, 61(82), (2020): 117-126, doi:10.1017/aog.2020.22.The surface flooding of Antarctic sea ice in summer covers 50% or more of the sea-ice area in the major summer ice packs, the western Weddell and the Bellingshausen-Amundsen Seas. Two CRREL ice mass-balance buoys were deployed on the Amundsen Sea pack in late December 2010 from the icebreaker Oden, bridging the summer period (January–February 2011). Temperature records from thermistors embedded vertically in the snow and ice showed progressive increases in the depth of the flooded layer (up to 0.3–0.35 m) on the ice cover during January and February. While the snow depth was relatively unchanged from accumulation (<10 cm), ice thickness decreased by up to a meter from bottom melting during this period. Contemporaneous with the high bottom melting, under-ice water temperatures up to 1°C above the freezing point were found. The high temperature arises from solar heating of the upper mixed layer which can occur when ice concentration in the local area falls and lower albedo ocean water is exposed to radiative heating. The higher proportion of snow ice found in the Amundsen Sea pack ice therefore results from both winter snowfall and summer ice bottom melt found here that can lead to extensive surface flooding.This work was supported by the National Science Foundation grant to UTSA, ANT-0839053-Sea Ice System in Antarctic Summer (S.F. Ackley, H. Xie and B. Weissling), and to WHOI, ANT-1341513 (T. Maksym), and by the NASA Center for Advanced Measurements in Extreme Environments or NASA-CAMEE at UTSA, NASA #80NSSC19M0194 (S.F. Ackley, H. Xie, B.Weissling)

An Automatic Tool for Partial Discharge De-noising via Short Time Fourier Transform and Matrix Factorization

This paper develops a fully automatic tool for the denoising of partial discharge (PD) signals occurring in electrical power networks and recorded in on-site measurements. The proposed method is based on the spectral decomposition of the PD measured signal via the joint application of the short-time Fourier transform and the singular value decomposition. The estimated noiseless signal is reconstructed via a clever selection of the dominant contributions, which allows us to filter out the different spurious components, including the white noise and the discrete spectrum noise. The method offers a viable solution which can be easily integrated within the measurement apparatus, with unavoidable beneficial effects in the detection of important parameters of the signal for PD localization. The performance of the proposed tool is first demonstrated on a synthetic test signal and then it is applied to real measured data. A cross comparison of the proposed method and other state-of-the-art alternatives is included in the study

MEMD-ABSA: A Multi-Element Multi-Domain Dataset for Aspect-Based Sentiment Analysis

Aspect-based sentiment analysis is a long-standing research interest in the field of opinion mining, and in recent years, researchers have gradually shifted their focus from simple ABSA subtasks to end-to-end multi-element ABSA tasks. However, the datasets currently used in the research are limited to individual elements of specific tasks, usually focusing on in-domain settings, ignoring implicit aspects and opinions, and with a small data scale. To address these issues, we propose a large-scale Multi-Element Multi-Domain dataset (MEMD) that covers the four elements across five domains, including nearly 20,000 review sentences and 30,000 quadruples annotated with explicit and implicit aspects and opinions for ABSA research. Meanwhile, we evaluate generative and non-generative baselines on multiple ABSA subtasks under the open domain setting, and the results show that open domain ABSA as well as mining implicit aspects and opinions remain ongoing challenges to be addressed. The datasets are publicly released at \url{https://github.com/NUSTM/MEMD-ABSA}