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Bibliografias temáticas / Retrieval Depth

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Literatura científica selecionada sobre o tema "Retrieval Depth"

Autor: Grafiati

Publicado: 7 de junho de 2025

Última modificação: 2 de agosto de 2025

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Artigos de revistas sobre o assunto "Retrieval Depth"

1

Evans, K. Franklin, Alexander Marshak, and Tamás Várnai. "The Potential for Improved Boundary Layer Cloud Optical Depth Retrievals from the Multiple Directions of MISR." Journal of the Atmospheric Sciences 65, no. 10 (2008): 3179–96. http://dx.doi.org/10.1175/2008jas2627.1.

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The Multiangle Imaging Spectroradiometer (MISR) views the earth with nine cameras, ranging from a 70° zenith angle viewing forward through nadir to 70° viewing aft. MISR does not have an operational cloud optical depth retrieval algorithm, but previous research has hinted that solar reflection measured in multiple directions might improve cloud optical depth retrievals. This study explores the optical depth information content of MISR’s multiple angles using a retrieval simulation approach. Hundreds of realistic boundary-layer cloud fields are generated with large-eddy simulation (LES) models

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2

Stein, Thorwald H. M., Julien Delanoë, and Robin J. Hogan. "A Comparison among Four Different Retrieval Methods for Ice-Cloud Properties Using Data from CloudSat, CALIPSO, and MODIS." Journal of Applied Meteorology and Climatology 50, no. 9 (2011): 1952–69. http://dx.doi.org/10.1175/2011jamc2646.1.

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AbstractThe A-Train constellation of satellites provides a new capability to measure vertical cloud profiles that leads to more detailed information on ice-cloud microphysical properties than has been possible up to now. A variational radar–lidar ice-cloud retrieval algorithm (VarCloud) takes advantage of the complementary nature of the CloudSat radar and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar to provide a seamless retrieval of ice water content, effective radius, and extinction coefficient from the thinnest cirrus (seen only by the lidar) to the thi

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3

Zhang, H., R. M. Hoff, S. Kondragunta, I. Laszlo, and A. Lyapustin. "Aerosol Optical Depth (AOD) retrieval using simultaneous GOES-East and GOES-West reflected radiances over the Western US." Atmospheric Measurement Techniques Discussions 5, no. 5 (2012): 7945–81. http://dx.doi.org/10.5194/amtd-5-7945-2012.

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Abstract. Aerosol Optical Depth (AOD) in the Western United States is observed independently by both the GOES-East and GOES-West imagers. The GASP (GOES Aerosol/Smoke Product) aerosol optical depth retrieval algorithm treats each satellite as a unique sensor and thus NOAA obtains two separate aerosol optical depth values at the same time for the same location. The TOA radiances and the associated derived optical depths can be quite different due to the different viewing geometries with large difference in solar-scattering angles. In order to fully exploit the simultaneous observations and gene

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4

Tu, Jinsheng, Haohan Wei, Rui Zhang, et al. "GNSS-IR Snow Depth Retrieval from Multi-GNSS and Multi-Frequency Data." Remote Sensing 13, no. 21 (2021): 4311. http://dx.doi.org/10.3390/rs13214311.

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Global navigation satellite system interferometric reflectometry (GNSS-IR) represents an extra method to detect snow depth for climate research and water cycle managing. However, using a single frequency of GNSS-IR for snow depth retrieval is often found to be challenging when attempting to achieve a high spatial and temporal sensitivity. To evaluate both the capability of the GNSS-IR snow depth retrieved by the multi-GNSS system and multi-frequency from signal-to-noise ratio (SNR) data, the accuracy of snow depth retrieval by different frequency signals from the multi-GNSS system is analyzed,

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5

Holz, Robert E., Steve Ackerman, Paolo Antonelli, et al. "An Improvement to the High-Spectral-Resolution CO2-Slicing Cloud-Top Altitude Retrieval." Journal of Atmospheric and Oceanic Technology 23, no. 5 (2006): 653–70. http://dx.doi.org/10.1175/jtech1877.1.

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Abstract An improvement to high-spectral-resolution infrared cloud-top altitude retrievals is compared to existing retrieval methods and cloud lidar measurements. The new method, CO2 sorting, determines optimal channel pairs to which the CO2 slicing retrieval will be applied. The new retrieval is applied to aircraft Scanning High-Resolution Interferometer Sounder (S-HIS) measurements. The results are compared to existing passive retrieval methods and coincident Cloud Physics Lidar (CPL) measurements. It is demonstrated that when CO2 sorting is used to select channel pairs for CO2 slicing there

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6

Garrett, T. J., and C. Zhao. "Ground-based remote sensing of thin clouds in the Arctic." Atmospheric Measurement Techniques Discussions 5, no. 6 (2012): 8653–99. http://dx.doi.org/10.5194/amtd-5-8653-2012.

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Abstract. This paper describes a method for using interferometer measurements of downwelling thermal radiation to retrieve the properties of single-layer clouds. Cloud phase is determined from ratios of thermal emission in three "micro-windows" where absorption by water vapor is particularly small. Cloud microphysical and optical properties are retrieved from thermal emission in two micro-windows, constrained by the transmission through clouds of stratospheric ozone emission. Assuming a cloud does not approximate a blackbody, the estimated 95% confidence retrieval errors in effective radius, v

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7

Lipponen, Antti, Tero Mielonen, Mikko R. A. Pitkänen, et al. "Bayesian aerosol retrieval algorithm for MODIS AOD retrieval over land." Atmospheric Measurement Techniques 11, no. 3 (2018): 1529–47. http://dx.doi.org/10.5194/amt-11-1529-2018.

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Abstract. We have developed a Bayesian aerosol retrieval (BAR) algorithm for the retrieval of aerosol optical depth (AOD) over land from the Moderate Resolution Imaging Spectroradiometer (MODIS). In the BAR algorithm, we simultaneously retrieve all dark land pixels in a granule, utilize spatial correlation models for the unknown aerosol parameters, use a statistical prior model for the surface reflectance, and take into account the uncertainties due to fixed aerosol models. The retrieved parameters are total AOD at 0.55 µm, fine-mode fraction (FMF), and surface reflectances at four different w

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Zheng, Jianyu, Zhibo Zhang, Hongbin Yu, et al. "Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations." Atmospheric Chemistry and Physics 23, no. 14 (2023): 8271–304. http://dx.doi.org/10.5194/acp-23-8271-2023.

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Abstract. In this study, we developed a novel algorithm based on the collocated Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared (TIR) observations and dust vertical profiles from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) to simultaneously retrieve dust aerosol optical depth at 10 µm (DAOD10 µm) and the coarse-mode dust effective diameter (Deff) over global oceans. The accuracy of the Deff retrieval is assessed by comparing the dust lognormal volume particle size distribution (PSD) corresponding to retrieved Deff with the in situ-measured dust PSDs fro

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9

Zhang, H., R. M. Hoff, S. Kondragunta, I. Laszlo, and A. Lyapustin. "Aerosol optical depth (AOD) retrieval using simultaneous GOES-East and GOES-West reflected radiances over the western United States." Atmospheric Measurement Techniques 6, no. 2 (2013): 471–86. http://dx.doi.org/10.5194/amt-6-471-2013.

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Abstract. Aerosol optical depth (AOD) in the western United States is observed independently by both the (Geostationary Operational Environmental Satellites) GOES-East and GOES-West imagers. The GASP (GOES Aerosol/Smoke Product) aerosol optical depth retrieval algorithm treats each satellite as a unique sensor and thus obtains two separate aerosol optical depth values at the same time for the same location. The TOA (the top of the atmosphere) radiances and the associated derived optical depths can be quite different due to the different viewing geometries with large difference in solar-scatter

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10

Yang, Yuekui, Alexander Marshak, J. Christine Chiu, et al. "Retrievals of Thick Cloud Optical Depth from the Geoscience Laser Altimeter System (GLAS) by Calibration of Solar Background Signal." Journal of the Atmospheric Sciences 65, no. 11 (2008): 3513–26. http://dx.doi.org/10.1175/2008jas2744.1.

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Abstract Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other spaceborne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (&lt; about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so one must first calibrate the reflected solar radiation received by the photon-counting detectors of the GLAS

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Teses / dissertações sobre o assunto "Retrieval Depth"

1

Vonk, Jennifer. "Attentional, instructional, and depth effects on retrieval estimates." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0002/MQ30256.pdf.

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2

Dombrock, Ryan M. "Automating the shadow method for aerosol optical depth retrieval." Thesis, Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion.exe/07Mar%5FDombrock.pdf.

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3

Broomhall, Mark Anthony. "A time-series method for MODIS aerosol optical depth retrieval." Thesis, Curtin University, 2014. http://hdl.handle.net/20.500.11937/23.

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Aerosol Optical Depth [AOD] is an important input for the atmospheric correction of satellite-derived Earth Observation data, and remains the most difficult variable to properly quantify. The Reflectance Change method utilises time-series data from a Bidirectional Reflectance Distribution Model to estimate the surface reflectance which is used as an input into the AOD retrieval model. This approach moves away from previous methods that use band ratio techniques, which are problematic over characteristically arid Australian landscapes.

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4

Cimbora, Brett D. "A Verification Of Aerosol Optical Depth Retrieval Using The Terra Satellite." Thesis, Monterey, California. Naval Postgraduate School, 2012. http://hdl.handle.net/10945/7321.

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A method for sensing retrieval of Aerosol Optical Depth (AOD) was investigated by Vincent (2006). This technique is known as the Shadow Method. Using high-resolution commercial satellite imagery, Vincent was able to calculate AOD values by measuring the radiance of a scene in and out of a shadow. Over the last five years, several advancements have been made to validate the Shadow Method. Using the MODerate resolution Imaging Spectrometer (MODIS), scenes were analyzed over desert regions to exploit shadows generated by clouds and terrain. The results were quickly compiled using MATLAB. Results

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5

Brown, Brady A. "Aerosol optical depth retrieval by NPS model modified for SeaWiFS input." Thesis, Monterey, California. Naval Postgraduate School, 2002. http://hdl.handle.net/10945/6091.

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Approved for public release, distribution is unlimited<br>Using visible wavelength radiance data obtained from the spaceborne Sea-viewing Wide Field-of-view Sensor (SeaWiFS), during the Aerosol Characterization Experiment-Asia (ACE-Asia), an analysis of aerosol optical depth (AOD) was completed by modification to the NPS AOD Model previously compiled for NOAA geosynchronous- and polar-orbiting satellites. The objective of the analysis was to calibrate the linearized, single-scatter algorithm, estimated bi-directional surface reflectance, and phase function parameters. The intent of the study w

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6

Rasure, James O. "Aerosol optical depth retrieval with AVIRIS data : a test Of Tafkaa." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2002. http://library.nps.navy.mil/uhtbin/hyperion-image/02sep%5FRasure.pdf.

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Thesis (M.S. in Meteorology and Physical Oceanography)--Naval Postgraduate School, September 2002.<br>Thesis advisor(s): Philip A. Durkee, Kurt E. Nielsen. Includes bibliographical references (p. 39-40). Also available online.

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7

Clifford, Mary B. "Effects of water vapor and anisotropic scattering on aerosol optical depth retrieval." Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/28152.

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8

Ibarra, Castanedo Clémente. "Quantitative subsurface defect evaluation by pulsed phase thermography: depth retrieval with the phase." Thesis, Université Laval, 2005. http://www.theses.ulaval.ca/2005/23016/23016.pdf.

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La Thermographie de Phase Pulsée (TPP) est une technique d’Évaluation Non-Destructive basée sur la Transformée de Fourier pouvant être considérée comme étant le lien entre la Thermographie Pulsée, pour laquelle l’acquisition de données est rapide, et la Thermographie Modulée, pour laquelle l’extraction de la profondeur est directe. Une nouvelle technique d’inversion de la profondeur reposant sur l’équation de la longueur de diffusion thermique : μ=(α /πf)½, est proposée. Le problème se résume alors à la détermination de la fréquence de borne fb, c à d, la fréquence à laquelle un défaut à une p

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9

Ibarra, Castanedo Clemente. "Quantitative subsurface defect evaluation by pulsed phase thermography: depth retrieval with the phase." Doctoral thesis, Université Laval, 2005. http://hdl.handle.net/20.500.11794/18116.

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La Thermographie de Phase Pulsée (TPP) est une technique d’Évaluation Non-Destructive basée sur la Transformée de Fourier pouvant être considérée comme étant le lien entre la Thermographie Pulsée, pour laquelle l’acquisition de données est rapide, et la Thermographie Modulée, pour laquelle l’extraction de la profondeur est directe. Une nouvelle technique d’inversion de la profondeur reposant sur l’équation de la longueur de diffusion thermique : μ=(α /πf)½, est proposée. Le problème se résume alors à la détermination de la fréquence de borne fb, c à d, la fréquence à laquelle un défaut à une p

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10

Wang, Tianyang. "A Novel Image Retrieval Strategy Based on VPD and Depth with Pre-Processing." OpenSIUC, 2015. https://opensiuc.lib.siu.edu/dissertations/1054.

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This dissertation proposes a comprehensive working flow for image retrieval. It contains four components: denoising, restoration, color features extraction, and depth feature extraction. We propose a visual perceptual descriptor (VPD) to extract color features from an image. Gradient direction is calculated at each pixel, and the VPD is moved over the entire image to locate regions with similar gradient direction. Color features are extracted only at these pixels. Experiments demonstrate that VPD is an effective and reliable descriptor in image retrieval. We propose a novel depth feature for i

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Livros sobre o assunto "Retrieval Depth"

1

Clifford, Mary B. Effects of water vapor and anisotropic scattering on aerosol optical depth retrieval. Naval Postgraduate School, 1991.

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2

Kaufman, Howard H., ed. Pediatric Brain Death and Organ/Tissue Retrieval. Springer US, 1989. http://dx.doi.org/10.1007/978-1-4684-5532-8.

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3

H, Kaufman Howard, ed. Pediatric brain death and organ/tissue retrieval: Medical, ethical, and legal aspects. Plenum Medical Book Co., 1989.

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4

Office, General Accounting. Records management: Retrieval of State Department's political appointee files : report to Congressional requesters. The Office, 1994.

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5

Hawaii. Legislature. Office of the Legislative Auditor. Study of the development of the Department of Education's financial management system and student information and program management system: A report to the Governor and the Legislature of the State of Hawaii. The Auditor, 1991.

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6

Division, Montana Legislature Legislative Audit. Consolidated environmental data access and retrieval system: Verification of data accuracy and integrity, Department of Environmental Quality : information systems audit. Legislative Audit Division, 2009.

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7

Montana. Legislature. Legislative Audit Division. Consolidated environmental data access and retrieval system: Verification of data accuracy and integrity, Department of Environmental Quality : information systems audit. Legislative Audit Division, 2009.

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8

Office, General Accounting. Data management: DOD should redirect its efforts to automate technical data repositories : report to the chairman, Committee on Government Operations, House of Representatives. The Office, 1986.

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9

United States. General Accounting Office., ed. U.S. Department of Agriculture: Restructuring will impact farm service agencies' automation plans and programs : statement for the record by JayEtta Z. Hecker, Director, Resources, Community, and Economic Development Information Systems, Information Management and Technology Division, before the Committee on Agriculture, House of Representatives. The Office, 1992.

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10

United States. General Accounting Office. Accounting and Information Management Division. Navy's TAC-4 procurement. The Office, 1993.

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Capítulos de livros sobre o assunto "Retrieval Depth"

1

Rüger, Stefan. "Content-based Retrieval in Depth." In Multimedia Information Retrieval. Springer International Publishing, 2010. http://dx.doi.org/10.1007/978-3-031-02269-2_3.

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2

Hasanain, Maram, Tamer Elsayed, and Walid Magdy. "Improving Tweet Timeline Generation by Predicting Optimal Retrieval Depth." In Information Retrieval Technology. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-28940-3_11.

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3

Yu, Hai-Tao, Adam Jatowt, Roi Blanco, et al. "An In-Depth Study of Implicit Search Result Diversification." In Information Retrieval Technology. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48051-0_29.

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4

Czúni, László, and Dezsö Csordás. "Depth-Based Indexing and Retrieval of Photographic Images." In Visual Content Processing and Representation. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39798-4_12.

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5

Lin, Jun-Yang, May-Fang She, Ming-Han Tsai, I.-Chen Lin, Yo-Chung Lau, and Hsu-Hang Liu. "3D Articulated Model Retrieval Using Depth Image Input." In Communications in Computer and Information Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26756-8_2.

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6

Seth, Amit, and Vandana Dixit Kaushik. "Optimized Depth-Wise Separable Convolution Neural Network for Lung and Colon Cancer Detection." In Cyber Intelligence and Information Retrieval. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3594-5_26.

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7

Magliani, Federico, Tomaso Fontanini, and Andrea Prati. "A Dense-Depth Representation for VLAD Descriptors in Content-Based Image Retrieval." In Advances in Visual Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03801-4_58.

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8

Li, Haitao, You Chen, Zhekai Ge, et al. "Towards an In-Depth Comprehension of Case Relevance for Better Legal Retrieval." In New Frontiers in Artificial Intelligence. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3076-6_15.

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9

Muhammad, Dafa Faris, Subashkumar Rajanayagam, and Stefan Twieg. "Semi-Autonomous Object Retrieval with Robot Arm and Depth Camera for Quadruped Robots." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-89296-7_20.

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10

Wang, Yi, Jie Xiang, and Zeming Zhou. "Retrieval of Atmospheric Aerosol Optical Depth with an Improved Algorithm Over East China Sea." In Geo-Informatics in Resource Management and Sustainable Ecosystem. Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49155-3_37.

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Trabalhos de conferências sobre o assunto "Retrieval Depth"

1

Hilmarsen, Henrik, Nicholas Dalhaug, Trym Anthonsen Nygård, Edmund Førland Brekke, Rudolf Mester, and Annette Stahl. "Maritime Tracking-By-Detection with Object Mask Depth Retrieval Through Stereo Vision and Lidar*." In 2024 27th International Conference on Information Fusion (FUSION). IEEE, 2024. http://dx.doi.org/10.23919/fusion59988.2024.10706307.

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2

Webber, William, Praveen Chandar, and Ben Carterette. "Alternative assessor disagreement and retrieval depth." In the 21st ACM international conference. ACM Press, 2012. http://dx.doi.org/10.1145/2396761.2396781.

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3

Makarov, Ilya, Alisa Korinevskaya, and Vladimir Aliev. "Fast Semi-dense Depth Map Estimation." In ICMR '18: International Conference on Multimedia Retrieval. ACM, 2018. http://dx.doi.org/10.1145/3210499.3210529.

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4

Li, Pengzhi, Yikang Ding, Linge Li, Jingwei Guan, and Zhiheng Li. "Towards Practical Consistent Video Depth Estimation." In ICMR '23: International Conference on Multimedia Retrieval. ACM, 2023. http://dx.doi.org/10.1145/3591106.3592264.

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5

Xu, Xiaolan, Simon Yueh, Rashmi Shah, and Akiko Hayashi. "Vegetation Optical Depth Retrieval from CYGNSS Data." In IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021. http://dx.doi.org/10.1109/igarss47720.2021.9553251.

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6

Vajramushti, N., I. A. Kakadiaris, T. Theoharis, and G. Papaioannou. "Efficient 3D object retrieval using depth images." In the 6th ACM SIGMM international workshop. ACM Press, 2004. http://dx.doi.org/10.1145/1026711.1026743.

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7

Guo, Jianping, Huadong Xiao, Chunxiang Cao, et al. "Fast Aerosol Optical Depth Retrieval from MODIS." In IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2008. http://dx.doi.org/10.1109/igarss.2008.4779502.

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8

Chaouch, Mohamed, and Anne Verroust-Blondet. "3D Model Retrieval Based on Depth Line Descriptor." In Multimedia and Expo, 2007 IEEE International Conference on. IEEE, 2007. http://dx.doi.org/10.1109/icme.2007.4284721.

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9

Downs, Brandi, Andrew O'Brien, Mary Morris, and Cinzia Zuffada. "Water Depth Retrieval in the Everglades Using Cygnss." In IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021. http://dx.doi.org/10.1109/igarss47720.2021.9553584.

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10

Jalal, Khairunnisa Abd, Arnis Asmat, and Noordin Ahmad. "Aerosol Optical Depth (AOD) retrieval method using MODIS." In 2015 International Conference on Space Science and Communication (IconSpace). IEEE, 2015. http://dx.doi.org/10.1109/iconspace.2015.7283802.

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Relatórios de organizações sobre o assunto "Retrieval Depth"

1

Desrochers, Paul R. Cloud Optical Depth Retrieval from Cloud Radar and Microwave Radiometer Measurements. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada443401.

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2

Pradhan, Nawa Raj. Estimating growing-season root zone soil moisture from vegetation index-based evapotranspiration fraction and soil properties in the Northwest Mountain region, USA. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42128.

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A soil moisture retrieval method is proposed, in the absence of ground-based auxiliary measurements, by deriving the soil moisture content relationship from the satellite vegetation index-based evapotranspiration fraction and soil moisture physical properties of a soil type. A temperature–vegetation dryness index threshold value is also proposed to identify water bodies and underlying saturated areas. Verification of the retrieved growing season soil moisture was performed by comparative analysis of soil moisture obtained by observed conventional in situ point measurements at the 239-km2 Reyno

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3

Trishchenko, A. P., Z. Li, and F. L. Chang. Cloud optical depths and TOA fluxes: Comparison between satellite and surface retrievals from multiple platforms. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2001. http://dx.doi.org/10.4095/219748.

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Lo, C., JM Comstock, and C. Flynn. An Atmospheric Radiation Measurement Value-Added Product to Retrieve Optically Thin Cloud Visible Optical Depth using Micropulse Lidar. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/1019412.

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Yang, Ying, Xiangting Huang, Yuge Wang, and Lan Chen. The impact of Triglyceride-Glucose Index on Ischemic Stroke: a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.11.0145.

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Review question / Objective: This Systematic review, describes two issues. 1. in the general population, a high TyG index predicts the risk of ischaemic stroke (IS) P: the general population without ischaemic stroke. I: higher TyG index. C: lower TyG index. O: first ischaemic stroke occurrence. S: Observational study. 2.In the ischaemic stroke(IS) population, a high tyg index predicts poor prognostic outcome. P: ischaemic stroke patient population. I: higher TyG index. C: lower TyG index O: death, stroke recurrence, poor functional outcome, deterioration in neurological function. S: Observatio

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Deng, Chun, Zhenyu Zhang, Zhi Guo, et al. Assessment of intraoperative use of indocyanine green fluorescence imaging on the number of lymph node dissection during minimally invasive gastrectomy: a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.11.0062.

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Review question / Objective: Whether is indocyanine green fluorescence imaging-guided lymphadenectomy feasible to improve the number of lymph node dissections during radical gastrectomy in patients with gastric cancer undergoing curative resection? Condition being studied: Gastric cancer was the sixth most common malignant tumor and the fourth leading cause of cancer-related death in the world. Radical lymphadenectomy was a standard procedure in radical gastrectomy for gastric cancer. The retrieval of more lymph nodes was beneficial for improving the accuracy of tumor staging and the long-term

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Letcher, Theodore, Kent Sparrow, and Sandra LeGrand. Establishing a series of dust event case studies for East Asia. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/47824.

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Dust aerosols have a wide range of effects on air quality, health, land-management decisions, aircraft operations, and sensor data interpretations. Therefore, the accurate simulation of dust plume initiation and transport is a priority for operational weather centers. Recent advancements have improved the performance of dust prediction models, but substantial capability gaps remain when forecasting the specific location and timing of individual dust events, especially extreme dust outbreaks. Operational weather forecasters and US Army Engineer Research and Development Center (ERDC) researchers

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Fourqurean, James, Johannes Krause, Juan González-Corredor, Tom Frankovich, and Justin Campbell. Caricas Partner's Practical Field and Laboratory Guide. Florida International University, 2024. http://dx.doi.org/10.25148/merc_fac.2024.32.

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This field and laboratory guide describes the field and laboratory methods used to characterize blue carbon in seagrass meadows. It was developed for the Caribbean Carbon Accounting in Seagrass project and describes the protocols and methods used by the network. In brief, at each project site, seagrass abundance, species composition, canopy height, and sediment type were assessed at sixteen 0.25 m2 quadrats placed at random locations within the site. Eight 20 cm diameter cores were taken to assess seagrass biomass, shoot density, and to provide the material for assessing seagrass carbon and nu

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Rosen, Michael, C. Matthew Stewart, Hadi Kharrazi, et al. Potential Harms Resulting From Patient-Clinician Real-Time Clinical Encounters Using Video-based Telehealth: A Rapid Evidence Review. Agency for Healthcare Research and Quality (AHRQ), 2023. http://dx.doi.org/10.23970/ahrqepc_mhs4telehealth.

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Objectives. To review the evidence on harms associated with patient-clinician real time encounters using video-based telehealth and determine the effectiveness of any related patient safety practices (PSPs). PSPs are interventions, strategies, or approaches intended to prevent or mitigate unintended consequences of healthcare delivery and improve patient safety. This review provides information that clinicians and health system leaders need to determine how to minimize harms from increasing real-time use of telehealth. Methods. We followed rapid review processes of the Agency for Healthcare Re

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The Islamic State's Real Estate Department: Documents and Analysis. George Washington University, 2020. http://dx.doi.org/10.4079/poe.06.2020.04.

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Drawing on documents retrieved from northern Iraq as part of The ISIS Files project and other sources, this paper examines in-depth the Islamic State’s Diwan al-Aqarat wa al-Kharaj (Real Estate and Land Tax Department), exploring how the Islamic State came to acquire ‘real estate’ and the functions of the department within the context of the group’s larger governance project.

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