Academic literature on the topic 'TVPMDI'
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Journal articles on the topic "TVPMDI"
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Soroosh, Mehravar, Amani Meisam, Moghimi Armin, et al. "Temperature-Vegetation-soil Moisture-Precipitation Drought Index (TVMPDI); 21-year drought monitoring in Iran using satellite imagery within Google Earth Engine." Advances in Space Research 68, no. 11 (2021): 4573–93. https://doi.org/10.5281/zenodo.6517351.
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Remote Sensing (RS) offers efficient tools for drought monitoring, especially in countries with a lack of reliable and consistent in-situ multi-temporal datasets. In this study, a novel RS-based Drought Index (RSDI) named Temperature-Vegetation-soil MoisturePrecipitation Drought Index (TVMPDI) was proposed. To the best of our knowledge, TVMPDI is the first RSDI using four different drought indicators in its formulation. TVMPDI was then validated and compared with six conventional RSDIs including VCI, TCI, VHI, TVDI, MPDI and TVMDI. To this end, precipitation and soil temperature in-situ data have been used. Different time scales of meteorological Standardized Precipitation Index (SPI) index have also been used for the validation of the RSDIs. TVMPDI was highly correlated with the monthly precipitation and soil temperature in-situ data at 0.76 and 0.81 values respectively. The correlation coefficients between the RSDIs and 3-month SPI ranged from 0.07 to 0.28, identifying the TVMPDI as the most suitable index for subsequent analyses. Since the proposed TVMPDI could considerably outperform the other selected RSDIs, all spatiotemporal drought monitoring analyses in Iran were conducted by TVMPDI over the past 21 years. In this study, different products of the Moderate Resolution Imaging Spectrometer (MODIS), Tropical Rainfall Measuring Mission (TRMM), and Global Precipitation Measurement (GPM) datasets containing 15,206 images were used on the Google Earth Engine (GEE) cloud computing platform. According to the results, Iran experienced the most severe drought in 2000 with a 0.715 TVMPDI value lasting for almost two years. Conversely, the TVMPDI showed a minimum value equal to 0.6781 in 2019 as the lowest annual drought level. The drought severity and trend in the 31 provinces of Iran have also been mapped. Consequently, various levels of decrease over the 21 years were found for different provinces, while Isfahan and Gilan were the only provinces showing an ascending drought trend (with a 0.004% and 0.002% trendline slope respectively). Khuzestan also faced a worrying drought prevalence that occurred in several years. In summary, this study provides updated information about
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Soroosh, Mehravar, Amani Meisam, Moghimi Armin, et al. "Temperature-Vegetation-soil Moisture-Precipitation Drought Index (TVMPDI); 21-year drought monitoring in Iran using satellite imagery within Google Earth Engine." Advances in Space Research 68, no. 11 (2021): 4573–93. https://doi.org/10.5281/zenodo.6137154.
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Remote Sensing (RS) offers efficient tools for drought monitoring, especially in countries with a lack of reliable and consistent <em>in-situ</em> multi-temporal datasets. In this study, a novel RS-based Drought Index (RSDI) named Temperature-Vegetation-soil Moisture-Precipitation Drought Index (TVMPDI) was proposed. To the best of our knowledge, TVMPDI is the first RSDI using four different drought indicators in its formulation. TVMPDI was then validated and compared with six conventional RSDIs including VCI, TCI, VHI, TVDI, MPDI and TVMDI. To this end, precipitation and soil temperature <em>in-situ</em> data have been used. Different time scales of meteorological Standardized Precipitation Index (SPI) index have also been used for the validation of the RSDIs. TVMPDI was highly correlated with the monthly precipitation and soil temperature in-situ data at 0.76 and 0.81 values respectively. The correlation coefficients between the RSDIs and 3-month SPI ranged from 0.07 to 0.28, identifying the TVMPDI as the most suitable index for subsequent analyses. Since the proposed TVMPDI could considerably outperform the other selected RSDIs, all spatiotemporal drought monitoring analyses in Iran were conducted by TVMPDI over the past 21 years. In this study, different products of the Moderate Resolution Imaging Spectrometer (MODIS), Tropical Rainfall Measuring Mission (TRMM), and Global Precipitation Measurement (GPM) datasets containing 15,206 images were used on the Google Earth Engine (GEE) cloud computing platform. According to the results, Iran experienced the most severe drought in 2000 with a 0.715 TVMPDI value lasting for almost two years. Conversely, the TVMPDI showed a minimum value equal to 0.6781 in 2019 as the lowest annual drought level. The drought severity and trend in the 31 provinces of Iran have also been mapped. Consequently, various levels of decrease over the 21 years were found for different provinces, while Isfahan and Gilan were the only provinces showing an ascending drought trend (with a 0.004% and 0.002% trendline slope respectively). Khuzestan also faced a worrying drought prevalence that occurred in several years. In summary, this study provides updated information about drought trends in Iran using an advanced and efficient RSDI implemented in the cloud computing GEE platform. These results are beneficial for decision-makers and officials responsible for environmental sustainability, agriculture and the effects of climate change.
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Wang, Ziyu, Zegen Wang, Junnan Xiong, Wen He, Zhiwei Yong, and Xin Wang. "Responses of the Remote Sensing Drought Index with Soil Information to Meteorological and Agricultural Droughts in Southeastern Tibet." Remote Sensing 14, no. 23 (2022): 6125. http://dx.doi.org/10.3390/rs14236125.
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The Temperature–Vegetation–Precipitation–Drought Index (TVPDI) has a good performance in drought monitoring in China. However, different regions have different responses to droughts due to terrain differences. In southeastern Tibet, the drought monitoring capacity of some drought indices without soil information has to be assessed on account of the poor sensitivity between temperature and soil humidity. Therefore, soil moisture was added to calculate a new drought index based on TVPDI in southeastern Tibet, named the Temperature–Vegetation–Soil-Moisture–Precipitation–Drought Index (TVMPDI). Then, the TVMPDI was validated by using the Standardized Precipitation Evapotranspiration Index (SPEI) and other remote sensing drought indices, including the Vegetation Health Index (VHI) and Scale Drought Conditions Index (SDCI), during the growing seasons of 2003–2018. The Standardized Precipitation Index (SPI) and SPEI were used to represent meteorological drought and Gross Primary Productivity (GPP) was used to represent agricultural drought. The relation between TVMPDI and these drought indices was compared. Finally, the time trends of TVMPDI were also analyzed. The relation coefficients of TVMPDI and SPEI were above 0.5. The correlations between TVMPDI and drought indices, including the Vegetation Health Index (VHI) and Scale Drought Conditions Index (SDCI), also had a good performance. The correlation between the meteorological drought indices (SPI and SPEI) and TVMPDI were not as good as for the TVPDI, but the temporal correlation between the TVMPDI and GPP was greater than that between the TVPDI and GPP. This indicates that the TVMPDI is more suitable for monitoring agricultural drought than the TVPDI. In addition, historical drought monitoring had values that were consistent with those of the actual situation. The trend of the TVMPDI showed that drought in the study area was alleviated from 2003 to 2018. Furthermore, GPP was negatively correlated with SPEI (r = −0.4) and positively correlated with Soil Moisture (SM) drought index (TVMPDI, SMCI) (r = 0.4) in the eastern part of the study area, which suggests that SM, rather than precipitation, could promote the growth of vegetation in the region. A correct understanding of the role of soil information in drought comprehensive indices may monitor meteorological drought and agricultural drought more accurately.
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Makino, Koji, Mia Mudge, Chelsea Zaunmayr, and Dom Tilden. "PP41 Using Medicare Claims Data To Support Reimbursement Of A Novel Leadless Pacing System For The Management Of Bradycardia." International Journal of Technology Assessment in Health Care 39, S1 (2023): S63. http://dx.doi.org/10.1017/s0266462323001897.
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IntroductionThe Micra Transcatheter Pacing System (Micra TPS) is a single-chamber transcatheter leadless pacemaker (LPM). LPMs do not require leads or a subcutaneous pocket, which represent the primary sources of device-related complications with conventional transvenous pacemakers (TVPMs). Complications such as infections and lead dislodgements cause significant patient burden, which have significant economic consequences. Running a randomized controlled trial (RCT) to estimate risk differences of infrequent events requires large sample sizes and long follow-up periods. Real-world observational data, while informative, requires an appropriate study design and statistical adjustments to control for potential biases.MethodsThe Micra Coverage with Evidence Development (CED) study was a cohort study of LPM versus TVPM based on US Medicare claims data of 16,431 patients with 2-year follow up (LPM: n=6,219; TVPM: n=10,212). Propensity score matching (PSM) was applied to account for differences in baseline characteristics. As no RCT was identified in the literature, this study was presented to the Australian payer as the primary source of clinical evidence, upon which a cost-utility analysis was conducted.ResultsAfter PSM, the CED study demonstrated significantly more complications with TVPM versus LPM with adjusted rates of 6.5 percent and 4.6 percent (p<0.001). Significant differences favoring LPM (p<0.01) were observed in device breakdown (1.4% vs 2.0%), dislodgment (0.4% vs 1.2%) and infection (<0.1% vs 0.6%). Based on these findings, a claim of superior safety was accepted by Medical Services Advisory Committee (MSAC) to support reimbursement. In making this decision, MSAC considered that the large sample size and propensity weighting overcame some of the potential biases and the magnitude of the benefit supported cost-effectiveness relative to TVPM.ConclusionsThe lack of a sufficiently powered RCT with an extended follow-up period can mean the impact and benefits of new technologies that reduce clinically important adverse events of relative infrequency are not formally incorporated into payer decision making, particularly where RCTs are a requirement. A well-designed observational study can provide valuable, real-world evidence to support a HTA for reimbursement decisions.
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Ren, Jie, Hexiang Zheng, Jun Wang, et al. "Assessment of Soil Moisture in Vegetation Regions of Mu Us Sandy Land Using Several Aridity Indicators." Atmosphere 15, no. 11 (2024): 1329. http://dx.doi.org/10.3390/atmos15111329.
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Drought, a significant calamity in the natural domain, has extensive worldwide repercussions. Drought, primarily characterized by reduced soil moisture (SM), presents a significant risk to both the world environment and human existence. Various drought indicators have been suggested to accurately represent the changing pattern of SM. The study examines various indices related to the Drought Severity Index (DSI), Evaporation Stress Index(ESI), Vegetation Supply Water Index(VSWI), Temperature-Vegetation Dryness Index(TVDI), Temperature Vegetation Precipitation Dryness Index(TVPDI), Vegetation Health Index(VHI), and Temperature Condition Index (TCI). An evaluation was conducted to assess the effectiveness of seven drought indicators, such as DSI, ESI, TVPDI, VSWI, etc., in capturing the changes in SM in Mu Us Sandy Land. The research results indicated that DSI and ESI had the highest accuracy, while TVDI and VSWI showed relatively lower accuracy. However, their smaller fluctuations in the time series demonstrated stronger adaptability to different regions. Additionally, the delayed impact of aridity indices on soil moisture, variable attributes, temperature, and vegetation coverage in sandy land and grassland areas with low, medium, and high coverage all contributed to the effectiveness of the four aridity indices (DSI, ESI, VSWI, and TVPDI) in capturing the dynamics of soil moisture. The primary element that affects the effectiveness of TVDI is the divergence of the relationship curve between Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI), which is a kind of deterioration. This paper presents a very efficient approach for monitoring soil moisture dynamics in dry and semi-arid regions. It also analyzes the patterns of soil moisture changes, offering valuable scientific insights for environmental monitoring and ecological enhancement.
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Wei, Wei, Sufei Pang, Xufeng Wang, et al. "Temperature Vegetation Precipitation Dryness Index (TVPDI)-based dryness-wetness monitoring in China." Remote Sensing of Environment 248 (October 2020): 111957. http://dx.doi.org/10.1016/j.rse.2020.111957.
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Sun, Minxuan, Zhengxin Ji, Xin Jiao, Fei Lun, Qiangqiang Sun, and Danfeng Sun. "Mapping Grassland Based on Bio-Climate Probability and Intra-Annual Time-Series Abundance Data of Vegetation Habitats." Remote Sensing 15, no. 19 (2023): 4723. http://dx.doi.org/10.3390/rs15194723.
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Accurate inventories of grasslands are important for studies of greenhouse gas (GHG) dynamics, as grasslands store about one-third of the global terrestrial carbon stocks. This paper develops a framework for large-area grassland mapping based on the probability of grassland occurrence and the interactive pathways of fractional vegetation and soil-related endmember nexuses. In this study, grassland occurrence probability maps were produced based on data on bio-climate factors obtained from MODIS/Terra Land Surface Temperature (MOD11A2), MODIS/Terra Vegetation Indices (MOD13A3), and Tropical Rainfall Measuring Mission (TRMM 3B43) using the random forests (RF) method. Time series of 8-day fractional vegetation-related endmembers (green vegetation, non-photosynthetic vegetation, sand land, saline land, and dark surfaces) were generated using linear spectral mixture analysis (LSMA) based on MODIS/Terra Surface Reflectance data (MOD09A1). Time-series endmember fraction maps and grassland occurrence probabilities were employed to map grassland distribution using an RF model. This approach improved the accuracy by 5% compared to using endmember fractions alone. Additionally, based on the grassland occurrence probability maps, we identified extensive ecologically sensitive regions, encompassing 1.54 (104 km2) of desert-to-steppe (D-S) and 2.34 (104 km2) of steppe-to-meadow (S-M) transition regions. Among these, the D-S area is located near the threshold of 310 mm/yr in precipitation, an annual temperature of 10.16 °C, and a surface comprehensive drought index (TVPDI) of 0.59. The S-M area is situated close to the line of 437 mm/yr in precipitation, an annual temperature of 5.49 °C, and a TVPDI of 0.83.
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Takasaki, Kenji, Carey D. Balaban, Isamu Sando, and Makoto Miura. "Functional Anatomy of the Tensor Veli Palatini Muscle and Ostmann's Fatty Tissue." Annals of Otology, Rhinology & Laryngology 111, no. 11 (2002): 1045–49. http://dx.doi.org/10.1177/000348940211101117.
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This study examined morphological features of the tensor veli palatini muscle (TVPM) and Ostmann's fatty tissue that may be important for eustachian tube (ET) ventilation. Histologic sections through the midcartilaginous ET from 17 human temporal bone-ET specimens (age range, 3 months to 88 years) were used to assess 1) the presence or absence of attachment of the TVPM fibers to either the perichondrium of the ET cartilage lateral lamina (LL) or a tendinous membrane along the medial margin of the TVPM, 2) the angular relationship between the TVPM fibers and the vertical axis of the ET lumen, and 3) the location of the TVPM and Ostmann's fatty tissue. The TVPM fibers were attached to the LL perichondrium in 14 cases; an attachment was absent in 3 cases because of fatty atrophy of the TVPM. However, the TVPM fibers were inserted into the tendonlike membrane in all cases. The angle of insertion of TVPM fibers into the membrane was significantly more acute (relative to the vertical ET axis) in the inferior aspect than in the superior aspect of the membrane both in young children (3 months to 4 years; mean ± SD, 39.0° ± 15.1° superiorly to 23.8° ± 17.0° inferiorly) and in older subjects (8 to 88 years, 30.4° ± 11.6° superiorly to 15.7° ± 11.2° inferiorly; t-test, p < .001). The location of Ostmann's fatty tissue accompanied the TVPM throughout the cartilaginous ET. These data suggest that contraction of the TVPM moves the LL inferolaterally to open the superior aspect more than the inferior aspect of the lumen and that Ostmann's fatty tissue will limit the opening of the ET lumen, especially that of its inferior aspect.
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Rivera, Joao, Franz Franchetti, and Markus Püschel. "Floating-Point TVPI Abstract Domain." Proceedings of the ACM on Programming Languages 8, PLDI (2024): 442–66. http://dx.doi.org/10.1145/3656395.
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Floating-point arithmetic is natively supported in hardware and the preferred choice when implementing numerical software in scientific or engineering applications. However, such programs are notoriously hard to analyze due to round-off errors and the frequent use of elementary functions such as log, arctan, or sqrt. In this work, we present the Two Variables per Inequality Floating-Point (TVPI-FP) domain, a numerical and constraint-based abstract domain designed for the analysis of floating-point programs. TVPI-FP supports all features of real-world floating-point programs including conditional branches, loops, and elementary functions and it is efficient asymptotically and in practice. Thus it overcomes limitations of prior tools that often are restricted to straight-line programs or require the use of expensive solvers. The key idea is the consistent use of interval arithmetic in inequalities and an associated redesign of all operators. Our extensive experiments show that TVPI-FP is often orders of magnitudes faster than more expressive tools at competitive, or better precision while also providing broader support for realistic programs with loops and conditionals.
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Orita, Yorihisa, Makoto Miura, Isamu Sando, and Seishi Hasebe. "Postnatal Changes in the Connective Tissue in the Region Lateral to the Eustachian Tube: Possible Relationship to Tube Function." Annals of Otology, Rhinology & Laryngology 112, no. 8 (2003): 716–21. http://dx.doi.org/10.1177/000348940311200812.
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In order to delineate the possible role of connective tissue (CT) in the region lateral to the eustachian tube (ET) between the ET lumen and the tensor veli palatini muscle (TVPM), we studied the postnatal changes in the CT in histologic sections of human ET. In fetuses and neonates, the lateral region was filled with mesenchyme. Loose collagenous CT appeared first at 2 weeks of age, and in subjects older than 4 years of age, the collagen formed dense, meshlike structures attaching to both the subepithelial CT layer of the ET and the tendonlike membrane of the TVPM. Along the long axis of the ET, those attachments were distributed mainly in the region at the posterior part of the cartilaginous portion of the ET. Attachments to the subepithelial CT layer of the ET were distributed mainly in the upper half of the region. The dense, meshlike collagenous CT might help the ET to be opened by drawing the lateral wall of the ET lumen through inferolateral movement of the tendonlike membrane of the TVPM when the TVPM contracts. It may work to open mainly the parts that include the narrowest portion of the ET, and also the upper aspect of the ET lumen. Incomplete development of this structure in infants may be one of the factors associated with dysfunction in ET opening.
Book chapters on the topic "TVPMDI"
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"The TVPI Abstract Domain." In Value-Range Analysis of C Programs. Springer London, 2008. http://dx.doi.org/10.1007/978-1-84800-017-9_8.
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"The Integral TVPI Domain." In Value-Range Analysis of C Programs. Springer London, 2008. http://dx.doi.org/10.1007/978-1-84800-017-9_9.
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"Total-Value-to-Paid-in-Capital (TVPI)." In The Palgrave Encyclopedia of Private Equity. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-81653-6_301072.
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Gilligan, John, and Mike Wright. "Measuring Private Equity Performance." In Private Equity Demystified. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198866961.003.0003.
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This chapter explains how to measure private equity performance. One of the key distinctions to be focused on is the gross versus net performance of a fund or investor. Gross returns are the returns earned by the private equity fund before fees are paid to the manager. Meanwhile, net returns are the returns earned by the investors in the fund after the fees of the manager have been deducted. Various measures are applied to monitor and adjust for the timing differences between total return and receipt of cash flows. DPI measures distribution as a percentage of paid-in capital, while TVPI measures total value as a percentage of paid-in capital. However, the most commonly used measure is the Internal Rate of Return (IRR). IRR is a cash flow measure that allows for the timing of cash flows. The chapter then highlights the importance of understanding both the overall industry returns and their variance and volatility over time. The variation in returns between the most successful and least successful fund managers is a key statistic to understand the performance and risks of the industry.
Conference papers on the topic "TVPMDI"
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Wan, Xin, Xinfang Zhang, Liang Chen, and Hao Jin. "TVPDc: A Model for Secure Managing Virtual Infrastructure in IaaS Cloud." In 2012 Eighth International Conference on Computational Intelligence and Security (CIS). IEEE, 2012. http://dx.doi.org/10.1109/cis.2012.38.
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