Slope Of Trend Research Articles

Trends in gastric cancer mortality 1990-2019 in 36 countries worldwide, with predictions to 2025, and incidence, overall and by subtype.

Gastric cancer (GC) incidence is declining heterogeneously worldwide. We aimed to calculate updated mortality trends for GC. We investigated time trends for selected countries using the World Health Organization database. We computed age-standardized mortality rates (ASMR) per 100,000 persons over the 1990-2019 period. We reported rates for the 2010-2014 and 2015-19 calendar periods, and the corresponding percent changes. We used joinpoint regression analysis to identify changes in the slope of mortality trends, and predict the number of deaths and rates for 2025. We also reported 2008-2012 incidence rates of cardia and noncardia GC. Mortality trends from GC have been favorable since 1990 for all countries analyzed and the European Union (EU 27), in both sexes and all ages. GC mortality is predicted to decline in all countries for both sexes, except for French and US women aged 35-64 years, and Canadian men aged 35-64. The highest proportions of cardia GC were observed in Northern and Central Europe while the lowest ones in Southern and Eastern Europe. Elsewhere, the highest proportions were registered in countries with low incidence and mortality rates, whereas high-mortality countries showed lower proportions of cardia GC. Observed and predicted GC mortality trends declined in most countries in both sexes, with few exceptions, likely due to the control of GC risk factors, in particular Hp infection.

Continuous monitoring and sub-annual change detection in high-latitude forests using Harmonized Landsat Sentinel-2 data

Spatially and temporally precise monitoring of forest resources is becoming increasingly vital in rapidly changing environmental and economic conditions. However, recent developments in moderate resolution satellite imagery have led to spectrally consistent and temporally dense datasets capable of capturing both seasonal variation and long-term trajectories. Previous studies have demonstrated the ability of continuous monitoring algorithms to detect transitional changes such as timber harvesting at sub-annual scales. However, less is known about the ability to use these algorithms in areas such as high-latitude forests which have large data gaps over winter due to prolonged snow cover. This study investigated the use of a time series of 7-day Harmonized Landsat Sentinel-2 (HLS) composites along with the Bayesian Estimator of Abrupt Change, Seasonality, and Trend (BEAST) algorithm for change detection and monitoring in two managed forest areas in Canada. On average, both sites had no data periods (over winter) lasting ∼200 days. Despite this, BEAST successfully detected change, with overall accuracies of 88.7% and 97.3% for both sites when compared to an independent validation dataset derived from visual interpretation of PlanetScope images. A simulation of change detection in near-real time revealed that approximately 75% of changes were detected within 7 and 11 valid images for each site. Furthermore, monitoring the trend slope of the spectral index showed that areas with a new declining slope were typically about twice as likely to occur in photointerpreted polygons of non-stand replacing disturbance, indicating that such a technique could be used as an early warning signal of fine-scale changes such as those due to insect defoliation or drought. Overall, this study demonstrated the efficacy of a continuous change detection and monitoring framework, which could be used to provide insights at previously unavailable temporal and spatial scales, thereby allowing forest managers the ability to quickly react to changes in uncertain future conditions.

Deterrence effect of penalties upon adolescent cannabis use.

Penalties are used in an effort to curtail drug use by citizens in most societies. There are growing calls for a reduction or elimination of such penalties. Deterrence theory suggests that use should increase if penalties reduce and vice versa. We sought to examine the relationship between changes to penalties for drug possession and adolescent cannabis use. Ten instances of penalty change occurred in Europe between 2000 and 2014, seven of which involved penalty reduction and three involved penalty increase. We conducted a secondary analysis of a series of cross-sectional surveys of 15-16-year-old school children, the ESPAD surveys, which are conducted every four years. We focused on past month cannabis use. We anticipated that an eight-year time span before and after each penalty change would yield two data points either side of the change. A simple trend line was fitted to the data points for each country. In eight cases, the trend slope in past month cannabis use was in the direction predicted by deterrence theory, the two exceptions being the UK policy changes. Using the principals of binomial distributions, the likelihood of this happening by chance is 56/1024 = 0.05. The median change in the baseline prevalence rate was by 21%. The science seems far from settled on this issue. There remains a distinct possibility that reducing penalties could contribute to small increases in adolescent cannabis use and consequently increase cannabis-related harms. This possibility should be considered in any political decision-making influencing drug policy changes.

Long‐Term Density Trend in the Mesosphere and Lower Thermosphere From Occultations of the Crab Nebula With X‐Ray Astronomy Satellites

AbstractWe present long‐term density trends of the Earth's upper atmosphere at altitudes between 71 and 116 km, based on atmospheric occultations of the Crab Nebula observed with X‐ray astronomy satellites, ASCA, RXTE, Suzaku, NuSTAR, and Hitomi. The combination of the five satellites provides a time period of 28 years from 1994 to 2022. To suppress seasonal and latitudinal variations, we concentrate on the data taken in autumn (49 < doy < 111) and spring (235 < doy < 297) in the northern hemisphere with latitudes of 0°–40°. With this constraint, local times are automatically limited either around noon or midnight. We obtain four sets (two seasons × two local times) of density trends at each altitude layer. We take into account variations due to a linear trend and the 11‐year solar cycle using linear regression techniques. Because we do not see significant differences among the four trends, we combine them to provide a single vertical profile of trend slopes. We find a negative density trend of roughly −5%/decade at every altitude. This is in reasonable agreement with inferences from settling rate of the upper atmosphere. In the 100–110‐km altitude, we found an exceptionally high density decline of about −12%/decade. This peak may be the first observational evidence for strong cooling due to water vapor and ozone near 110 km, which was first identified in a numerical simulation by Akmaev et al. (2006, https://doi.org/10.1016/j.jastp.2006.03.008). Further observations and numerical simulations with suitable input parameters are needed to establish this feature.

Degradation of Typical Reverse Sand-Mudstone Interbedded Bank Slope Based on Multi-Source Field Experiments.

The bank slopes in the Three Gorges Reservoir area (TGRA) have experienced obvious deterioration under the action of the periodic fluctuations in the reservoir water level. Generally, laboratory tests have been used to reveal the evolution trend of the slope banks. However, this method has a certain degree of cross-scale problem, especially for the mechanical state in a complex environment. Therefore, in this study, we took the Yangjiaping bank slope in the TGRA as an example and proposed a comprehensive on-site detection method to further reveal the rock mass degradation phenomenon of this typical reverse sand-mudstone interbedded bank slope. Specifically, multi-scale laser scanning, cross-hole acoustic wave detection, and inclination measurements were performed to analyze the fractures, quality, and deformation of rocky banks. The results showed that the deterioration of the bank slope manifested as the expansion, deepening, and widening of the cracks, as well as the peeling off and loosening of rocky banks. Large-scale laser scanning revealed that the deterioration zone was deformed along large fracture zones and layers. Unlike limestone slopes, the intact sandstone underground might be degraded by changes in water. There are few inclinometers and no deformation or weak deformation, which requires long-term monitoring. The relevant research methods provide an important reference for determining the instability and failure trend of the reservoir bank slopes.

Trend patterns of HBsAg kinetics in chronic hepatitis B patients during nucleos(t)ide analogue therapy based on ARMA models

BackgroundTrend pattern analysis are lacking for hepatitis B surface antigen (HBsAg) kinetics in chronic hepatitis B (CHB) patients during nucleos(t)ide analogue (Nuc) therapy. We evaluated the trend patterns of HBsAg kinetics by time series analysis and forecasting times to HBsAg seroclearance accordingly. MethodsA total of 116 CHB patients with documented three-month HBsAg levels during the previous more than five years of Nuc therapy were included. The piecewise linear trends of the autoregressive-moving average (ARMA) model were used for time series analysis of HBsAg kinetics trends. Best fitted models were created for each patient using HBsAg datasets with backtracking capability. Predicted time to HBsAg seroclearance was calculated accordingly. ResultsFour trend patterns of HBsAg kinetics were found: no trend (n = 22, 19.0%), single trend (n = 16, 13.8%), biphasic trend with rapid-slow decline (n = 56, 48.2%) and biphasic trend with rise-decline (n = 22, 19.0%). Except for no-trend patients, the trend became slow reduction as HBsAg declined. Only 6.1% of patients continued rapid decline when the initial HBsAg of the last trend reached <100 IU/mL. Last trend slopes < −10 and rise-decline patterns indicate greater chances of achieving HBsAg seroclearance within two years. ConclusionBest fitted ARMA models of HBsAg kinetics can be created individually for patients during Nuc therapy. About 67.2% patients have biphasic trend patterns, suggesting the dynamic nature of HBsAg kinetics over time. Trend patterns and last trend slopes predict individual times to HBsAg seroclearance.

Evaluating the (F)utility of Mandatory Minimum Sentencing Laws in Pennsylvania

In the current criminal justice policy sphere mandatory minimum sentencing serves two important purposes 1) they are used as a punitive response to immediate crime concerns and 2) their removal is viewed as a tool to conserve resources, decarcerate, and promote fairness in sentencing. Though much research explores how the passage of these laws relates to crime, the literature has not focused on the public safety implications of removing mandatory minimum sentences. Using a comparative interrupted time-series approach, the present work investigates whether a Pennsylvania Supreme Court decision that invalidated several mandatory minimum sentencing provisions impacted the state’s crime rate. We find little to no evidence of a discrete shift in overall or type-disaggregated crime rates, or changes in the slope of any crime trend when the state reduced their use of mandatory minimums. These findings tentatively suggest that many mandatory minimums can be repealed without risking public safety.

Deformation Monitoring and Trend Analysis of Reservoir Bank Landslides by Combining Time-Series InSAR and Hurst Index

Landslides along the Three Gorges Reservoir in China pose a threat to coastal residents and waterway safety. To reduce false positive misjudgments caused by a sudden local change in the landslide deformation curve, in this paper, we propose an effective method for predicting the deformation trend of reservoir bank landslides. We take reservoir bank landslides in the Wanzhou District of the Three Gorges Reservoir area as the research object. The Time-Series Interferometric Synthetic Aperture Radar (InSAR) method and 62 Sentinel-1A images from 2018 to 2022 were selected for landslide deformation monitoring, and the Hurst index was calculated to characterize the deformation trend. Furthermore, we propose a method for predicting the deformation trend based on the statistical distribution of deformation rates and the physical significance of the Hurst index. After the field survey and Global Positioning System (GPS) verification, the Time-Series InSAR results are shown to be reliable. We take the Sifangbei landslide as a representative case to analyze the validation results. It is found that the determined Sifangbei landslide deformation trend is consistent with the conclusions for the region. In addition, the deformation trend of a reservoir bank slope has obvious spatial and temporal differences. Changes in the reservoir water level and concentrated rainfall play roles similar to those of catalysts. The proposed method, involving the combination of Time-Series InSAR and the Hurst index, can effectively monitor deformation and predict the stability trend of reservoir bank landslides. The presented research results provide new ideas and solutions for landslide prevention and risk mitigation in reservoir areas.

Delayed response of net primary productivity with climate change in the Yiluo River basin

Climatic factors are the main drivers that change net primary productivity (NPP). We chose the Yiluo River Basin as the study area to investigate the response of NPP to climatic factors in the Yellow River’s middle reaches. The temporal and spatial distribution of net primary productivity and the trend change of slope in the basin from 2000 to 2020 are analyzed. In addition, we analyzed the correlation between the NPP and climatic factors (precipitation and temperature) and the time-lag effect. The results show that 1) the annual average NPP in the basin is 556.4 gC/m2/a, the maximum value that occurred in 2019. Most of the NPP’s mutation points in the basin’s forest appeared in 2004, while the NPP’s mutation points in arable land mostly appeared in 2008 and 2009. 2) The slope trend analysis result of NPP from 2000 to 2020 shows that the NPP in 67.88% of the basin shows a significant increasing trend, 3.8% of the basin shows a significant decrease, and the other area show no significant change. 3) The correlation analysis between NPP and climatic factors shows a positive correlation between precipitation and NPP in 62.3% of the basin and a positive correlation between air temperature and NPP in 62.5%. The response of NPP to precipitation and temperature in the basin has different degrees of a time-lag effect. The NPP has a time-lag effect on precipitation in 44.8% of the basin, and its mean lag time is 8 days. NPP has a time-lag effect on temperature in 55.7% of the basin, and its mean lag time is 1 day. This study is beneficial to understanding the influence of climatic factor change on vegetation activities in the Yiluo River Basin. Our study illustrates the significance of time lag in analyzing the relationship between NPP and climatic factors. Furthermore, it provides support for scientific vegetation regulation and allocation, as well as adaptation to climate change in areas similar to the Loess Plateau, based on the lag time distribution corresponding to different vegetation types in different regions of the Yiluo River Basin. After that, these areas’ water resources will be fully utilized by vegetation, and ecological restoration could be accelerated.

石羊河流域水分利用效率及其对饱和水汽压差的响应

PDF HTML阅读 XML下载 导出引用 引用提醒 石羊河流域水分利用效率及其对饱和水汽压差的响应 DOI: 10.5846/stxb202111243322 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学青年基金项目(41705062,32071606); 甘肃省气象局研究型业务重点项目(ZD2021-02); 云南省教育厅项目"云南省高校山地实景点云数据处理及应用重点实验室" Spatial-temporal dynamics of water use efficiency and responding to vapor pressure deficit in Shiyang River Basin, northwestern China Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:水分利用效率(WUE)是叶片通过光合作用调节水分生理过程的指标,是联系生态系统碳循环与水循环关系的关键,反映了植被生态系统对立地环境快速调整和资源的变化适应策略。基于卫星遥感和地面观测数据,利用光能利用率模型和蒸散发经验估算模型,模拟石羊河流域2000-2019年植被总初级生产力(GPP)和蒸散发(ET)数据,估算2000-2019年不同植被类型的WUE空间分布特征,研究GPP/ET/WUE与饱和水汽压差(VPD)的相关性,探讨干旱区不同类型植被对水分利用及胁迫的适应策略。结果表明:(1) 2000-2019年石羊河流域植被WUE、GPP和ET的平均值分别为0.80 gC m-2 mm-1、256.52 gC/m2和302.52 mm,其三者的空间分布特征表现为"南高北低",即由流域源头至下游逐渐减少的空间分布。(2) 近20年内,流域内WUE、GPP和ET的变化率的平均值分别为0.017 gC m-2 mm-1 a-1,6.99 gC m-2 a-1和3.80 mm/a,流域总体呈现波动上升的趋势,但城区和民勤耕地-荒漠交接区呈不同程度的减少趋势。(3) 流域内不同类型植被的WUE平均值关系为:森林>农作物>草地>灌丛>荒漠植被>湿地植被,WUE增加速度的平均值关系为:农作物>森林>草地>灌丛>荒漠植被>湿地植被,与GPP基本一致,其中ET在灌丛、荒漠植被、湿地植被地区呈现降低趋势。(4) 研究区内GPP/ET/WUE与VPD相关性的空间分布特征与石羊河径流方向具有高度一致性,WUE与VPD相关性分布特征受土地利用以及径流方向影响显著。WUE与VPD呈正相关的区域主要分布在河西走廊绿洲东部和荒漠区东部,呈负相关区域主要分布在祁连山高海拔地区、河西走廊绿洲中部和荒漠区西部。因此,正确揭示内陆河植被GPP/ET/WUE的空间分异以及变化趋势及其对驱动因素VPD的响应,是了解流域尺度中干旱区植被对全球干旱加剧的适应性策略前提,进而为生态保护提供决策服务。 Abstract:Water use efficiency (WUE) is the regulation index of leaf photosynthesis on the water physiological process, as the key to link the relationship between the ecosystem carbon cycle and the water cycle, and directly reflects the rapid adjustment of the ecosystem to the site environment and the adaptation strategy of resource changes. The Gross primary production (GPP) temporal and spatial characteristics derived from the data of MODIS-NDVI by the Light Energy Utilization Model, and the Evapotranspiration (ET) temporal and spatial characteristics derived from the meteorological data by the Thornthwaite Evapotranspiration Model during 2000-2019 in Shiyang River Basin (SRB). In this research, we estimated the spatial pattern and temporal variations of the GPP, ET and WUE in different vegetation types from 2000 to 2019, investigated the co-relationship between GPP/ET/WUE and Vapor pressure deficit (VPD), and discussed the response of adaptation strategies for water utilization and stress in the arid area among the different vegetation. The results show that: (1) from 2000 to 2019, the average annual value of total WUE, GPP, and ET in SRB were 0.80 gC m-2 mm-1, 256.52 gC/m2, and 302.52 mm, respectively; The spatial patterns of average annual WUE, GPP and ET in the SRB's vegetated areas varied widely, and the values decreased from upstream on the south side of the Qilian Mountains and middle to downstream on the north side of the desert. (2) During the 20 years, the average slope of WUE, GPP, and ET showed an obvious upward trend in almost whole basin, with the rate of 0.017 gC m-2 mm-1 a-1, 6.99 gC m-2 a-1 and 3.80 mm/a. The change rates of WUE, GPP and ET within the basin exhibited an upward trend, except for Liangzhou and the areas surrounding Minqin cropland according to the urbanization and industrial adjustment. (3) The WUE, GPP and ET annual average values, and slope of trends among the different land use types also varied significantly. Among various vegetation types, the highest values of WUE, GPP and ET appeared in forests, and the lowest values presented in wetlands; the highest change rate of different vegetation was forest, and the lowest one was the wetland. (4) Correlation analysis and statistical results indicated that the correlation distribution characteristics of GPP/ET/WUE and VPD in the study area were highly consistent with the runoff direction of the SRB. As the WUE was determined by GPP and ET, the correlation distribution between WUE and VPD had obviously spatial heterogeneity with the land-use and SRB runoff direction. The positive correlation was distributed in the eastern part of the Hexi Corridor oasis and the eastern desert area, and the negative correlation was distributed in the high-altitude areas of the Qilian Mountains, the middle of the Hexi Corridor oasis and the western part of the desert area. Overall, correctly revealing the spatial differentiation and changing trend of GPP/ET/WUE of inland river vegetation and its response to the driving factor VPD was the premise of understanding the adaptive strategy of vegetation in arid areas at the watershed scale to the intensification of global drought, to provide decision-making services for ecological protection. 参考文献 相似文献 引证文献

Trends in river runoff in Latvia for the period 1951-2020

A time series of monthly, seasonal and annual mean specific runoff of rivers in Latvia are analysed in order to detect trends for the period 1951–2020. Trend analysis is performed by applying the Mann-Kendall test and the trend slope is calculated using Sen’s method. There were significant seasonal changes in the time series of specific runoff measured at 32 stations during the study period. In all hydrological regions, the trend values obtained for the winter season are statistically significant, but they are relatively weaker in the Eastern region. At the same time, river runoff in April and May has notably decreased, indicating a shift of the runoff maximum to an earlier time. Long-term changes in specific runoff are statistically significant in April in all hydrological regions, and only in May for the Eastern region. Generally, statistically insignificant trends in specific runoff are observed for the summer and autumn months. Annual mean specific runoff has not revealed any strong trends in spite of the increased precipitation and temperature. Clear seasonal changes have been found in several earlier studies in the Baltic countries, and they are confirmed by the current one.

Ellenberg‐type indicator values for European vascular plant species

AbstractAimsEllenberg‐type indicator values are expert‐based rankings of plant species according to their ecological optima on main environmental gradients. Here we extend the indicator‐value system proposed by Heinz Ellenberg and co‐authors for Central Europe by incorporating other systems of Ellenberg‐type indicator values (i.e., those using scales compatible with Ellenberg values) developed for other European regions. Our aim is to create a harmonized data set of Ellenberg‐type indicator values applicable at the European scale.MethodsWe collected European data sets of indicator values for vascular plants and selected 13 data sets that used the nine‐, ten‐ or twelve‐degree scales defined by Ellenberg for light, temperature, moisture, reaction, nutrients and salinity. We compared these values with the original Ellenberg values and used those that showed consistent trends in regression slope and coefficient of determination. We calculated the average value for each combination of species and indicator values from these data sets. Based on species’ co‐occurrences in European vegetation plots, we also calculated new values for species that were not assigned an indicator value.ResultsWe provide a new data set of Ellenberg‐type indicator values for 8908 European vascular plant species (8168 for light, 7400 for temperature, 8030 for moisture, 7282 for reaction, 7193 for nutrients, and 7507 for salinity), of which 398 species have been newly assigned to at least one indicator value.ConclusionsThe newly introduced indicator values are compatible with the original Ellenberg values. They can be used for large‐scale studies of the European flora and vegetation or for gap‐filling in regional data sets. The European indicator values and the original and taxonomically harmonized regional data sets of Ellenberg‐type indicator values are available in the Supporting Information and the Zenodo repository.

高填方边坡研究热点及发展趋势可视化分析

高填方边坡研究热点及发展趋势可视化分析

Rainfall Trend analysis using Mann-Kendall and Sen’s slope test estimation - A case study

In order to analyze the changing pattern of rainfall in one of the important district in Kerala, this study concentrated on a crucial meteorological variable: precipitation. Agriculture in this region depends on rain, but because it occurs erratically and without warning, it has an adverse impact on the cropping system and the availability of natural water resources. Non-parametric analysis was used to determine the monthly, seasonal, and annual rainfall variability (trend and slope magnitude) from rainfall data spanning 30 years (1989-2018) on a monthly basis. To determine the strength of a trend for time series data, the Mann-Kendall (MK) Test for monotonic analysis of trend and non-parametric Sen's Slope Estimator were utilized. The past 30 years have been used to create monthly, seasonal, and yearly precipitation trends. The 30-year monthly data was used to generate monthly, seasonal, and yearly precipitation trends. The results of the statistical analysis of the entire reference time series data shows that the trend appears to be primarily positive (growing), both on an annual and seasonal scale. There was a decreasing tendency in the spring, pre-monsoon, and post-monsoon seasons. Individually, the seven months of January through February show a growing tendency, whereas the remaining five months of March through December show a declining trend with 99% and 95% confidence levels, respectively, the annual total rainfall and monsoon seasons demonstrated a positive significant increasing trend.

Climate change in the Debrecen area in the last 50 years and its impact on maize production

The average yield of maize is significantly dependent on the meteorological conditions of the growing year. Both the most favorable weather conditions and the weather anomalies that tend to cause damage depend on the given phenophase. The aim of this research is to analyze the climatic changes that are important in maize production in the Hajdúság region. For the climatological study of the area, homogenized temperature and precipitation data from the Hungarian Meteorological Service was used for the Debrecen region, which are freely available for download from the data repository of the institution. Trend analysis was performed for the last 50-year (1973–2022) and 30-year (1993–2022) periods. In total, 40 meteorological data series matching the study objective were analyzed. Linear regression calculations were performed using the SPSS 27 statistical software. For the non-parametric procedure, the MAKESENS Excel application was used, based on the Mann-Kendall (MK) test and Sen's slope estimation. This research shows that the choice of the length of the study period affects the results of trend analysis. The numerical values of the trend slope for the 30-year vs. 50-year period differ, and for some parameters there are also substantial differences (e.g., trend sign). The results of the parametric and non-parametric trend analyses differed only marginally for the temperature variables included. Also, for precipitation data that do not follow a normal distribution (e.g., monthly), there were only a few significant differences. The trend in mean annual temperature shows an increase of 0.39 and 0.52 °C in 10 years, and an increase of around 2 °C in 50 years and 1.5 °C in 30 years. There is a significant warming in both the summer and winter half-years, with the summer half-year showing a steeper upward trend in the 50-year data series and the winter half-year in the 30-year data series. There is a clear pattern of large, highly significant warming in the summer months and less significant changes in the two spring and two autumn months that were observed. A negative, non-significant trend in annual precipitation is observed. The decreases of 17 mm and 24 mm/10 years obtained for the 50- and 30-year time series are not negligible from a practical point of view. For the summer half-year, the precipitation amount is decreasing, with a slope of -27 mm/10 years for the last 30 years, but even this value is not significant due to the high variability. There is no significant change in the amount of precipitation in the winter half-year over the last decades. Significant trends cannot be detected from monthly or even semi-annual or annual precipitation data. The Mann-Kendall test showed a trend decrease only in the 30-year April data series at the p=0.1 significance level. Overall, the changes are negative for maize production. It should be highlighted that the obvious warming, combined with a slight decrease in precipitation, is leading to a deterioration in crop water availability and a reduction in crop yields. The impact of the identified adverse climatic changes can be compensated to a significant extent by the proposed agrotechnical responses.

A New Density Peak Clustering Algorithm With Adaptive Clustering Center Based on Differential Privacy

A new density peak clustering (DPC) algorithm with adaptive clustering center based on differential privacy was proposed to solve the problems of poor adaptability of high-dimensional data, inability to automatically determine clustering centers, and privacy problems in clustering analysis. First, to solve the problem of poor adaptability of high-dimensional data, cosine distance was used to measure the similarity between high-dimensional datasets. Then, aiming at the subjective problem of clustering center selection, from the perspective of ranking graph, the weight <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$(i-1)/i$ </tex-math></inline-formula> was introduced creatively, the slope trend of ranking graph was redefined to realize the adaptive clustering center. Finally, aiming at the privacy problem, the Laplacian noise of appropriate privacy budget was added to the core statistic (local density) of the algorithm to achieve the balance between privacy protection and algorithm effectiveness. Experimental results on both the synthetic and UCI datasets show that this algorithm can not only realize the automatic selection of clustering center, but also solve the privacy problem in clustering analysis, and improve the clustering evaluation index greatly, which proves the effectiveness of the algorithm.

Analysis of Temperature Data Using the Innovative Trend Pivot Analysis Method and Trend Polygon Star Concept: A Case Study of Soan River Basin, Potohar, Pakistan

The trend analysis approach is used to estimate changing climate and its impact on the environment, agriculture and water resources. Innovative polygonal trend analyses are qualitative methods applied to detect changes in the environment. In this study, the Innovative Trend Pivot Analysis Method (ITPAM) and Trend Polygon Star Concept Method were applied for temperature trend detection in Soan River Basin (SRB), Potohar region, Pakistan. The average monthly temperature data (1995–2020) for 11 stations were used to create polygon graphics. Trend length and slope were calculated separately for arithmetic mean and standard deviation. The innovative methods produced useful scientific information, with the identification of monthly shifts and trend behaviors of temperature data at different stations. Some stations showed an increasing trend and others showed decreasing behavior. This increasing and decreasing variability is the result of climate change. The winter season temperature is increasing, and the months of December to February are getting warmer. Summer is expanding and pushing autumn towards winter, swallowing the early period of the cold season. The monthly polygonal trends with risk graphs depicted a clear picture of climate change in the Potohar region of Pakistan. The phenomena of observed average temperature changes, indicated by both qualitative methods, are interesting and have the potential to aid water managers’ understanding of the cropping system of the Potohar region.

Investigating the impact of multi-dimensional urbanization and FDI on carbon emissions in the belt and road initiative region: Direct and spillover effects

The climate ambition led by the net zero goal has prompted growing concern among international organizations about the carbon emissions effects of urbanization and foreign direct investment (FDI) in the Belt and Road Initiative (BRI) region. Due to the limited data experiments, the direction and externalities of the impact of urbanization and FDI on carbon emissions in the BRI region remain largely unclear, and accounting for urbanization is also isolated. To address this knowledge gap, this study quantified the direct and spillover effects of multi-dimensional urbanization and FDI on carbon emissions using multiple remote sensing data from 2000 to 2018. The study explored the spatial distribution, evolutionary trends, bivariate evolutionary relationships, and influence mechanisms of carbon emissions with multi-dimensional urbanization and FDI by combining temporal trend (Slope), bivariate spatial autocorrelation, spatial Durbin model (SDM), and other methods. The results indicate that from 2000 to 2018, the total BRI carbon emissions added 253 million tons at an average annual growth rate of 3.68%; since 2013, the average annual growth rate has dropped sharply to 1.34%. East and South Asian countries (especially China and India) posted the highest increase in carbon emissions and had faster growth rates in multi-dimensional urbanization and FDI. Only some European countries, such as France and Germany, achieved overall carbon reduction. The results highlight the adaptability of the “Environmental Kuznets Curve” hypothesis. The “Low-Low” was the main cluster type of the evolutionary trends of carbon emissions associated with each variable. Multi-dimensional urbanization and FDI directly contributed to local carbon emissions, but the effects have gradually weakened over time (except for land urbanization). After controlling for the direct effects, we found a widespread consistently enhanced positive effects of population urbanization and land urbanization on carbon emissions in adjacent areas (especially after the BRI implementation), while FDI reduced the direct impact and strengthened the gain effect on carbon reduction in adjacent regions. Our findings confirm the importance of integrating policies to reduce emissions in population, economy, land, and foreign investment and provide strong evidence for joint governance of carbon emissions among BRI countries.

733: IMPACT OF ELECTRONIC SEPSIS ALERT ON PEDIATRIC SEPSIS OUTCOMES: AN INTERRUPTED TIME SERIES ANALYSIS

Introduction: Pediatric sepsis is a significant cause of morbidity and mortality in children; guidelines now recommend a systematic screening tool to enhance early recognition of children with sepsis. However, it is unknown whether a screening tool that uses electronic clinical data to alert clinicians about a concern for sepsis can impact outcomes. We hypothesized that an electronic sepsis alert would decrease mortality, ICU admission, vasoactive use, and organ dysfunction at day 3 and day 7. Methods: This was a single-center, retrospective study of emergency department sepsis episodes from January 20, 2011 to May 20, 2021. Sepsis episodes were identified by a validated computational algorithm which reflects presence of infection with organ dysfunction (cardiac, respiratory, hematologic or renal) using data in the electronic health record. The sepsis alert was positive with elevated pulse rate or hypotension, concern for infection, and at least one of the following: abnormal capillary refill, abnormal mental status, or high-risk condition. We performed an interrupted time series analysis to compare outcomes before and after implementation of the electronic sepsis alert in March 2014. Interrupted time series analysis is a quasi-experimental design which can assess a level change (difference between predicted vs observed outcomes immediately post-intervention) as well as changes in trends (slope) before and after intervention. Outcomes included mortality, ICU admission, vasoactive use, and organ dysfunction at day 3 and day 7. Results: Of 3,269 total sepsis episodes, 770 occurred prior to and 2,429 occurred after sepsis alert implementation (70 missing alert status). After adjusting for season, there was no change in mortality (p=0.30), ICU admission (p=0.39) or vasoactive use (p=0.10). Sepsis alert implementation was associated with a significant change in organ dysfunction at day 3 (p=0.03) and day 7 (p< 0.0001). Specifically, there was an increasing slope of organ dysfunction prior to sepsis alert, which was stabilized after alert implementation. Conclusions: Using electronic clinical health data, implementation of a sepsis alert may impact rate of day 3 and day 7 organ dysfunction, though did not impact mortality, ICU admission or vasoactive use in our single center.

Joint lensing–dynamics constraint on the elliptical galaxy mass profile from the largest galaxy–galaxy lens sample

AbstractFrom various lensing and non-lensing observations, the total density profile in elliptical galaxies is well approximated by a power law mass distribution. However, as neither the dark matter nor the baryons individually follow the power law, this observational result has been referred to as the “bulge–halo conspiracy”. We investigate the consistency of this conspiracy with higher precision than previous studies with the largest ever sample of galaxy–galaxy lenses assembled from archival Hubble Space Telescope (HST) data. By performing lens modelling with power law profiles and combining them with stellar dynamics using the mass-sheet transformation, we can constrain the profile’s deviation from the power law model over a redshift range of 0.1 to 0.8. To uniformly model such a large sample of lens models, we use the automated modelling pipeline dolphin. We also investigate the evolutionary trend of the total mass density slope of the lensing galaxies.