Fluctuation trend of the mean temperature index. by Chengyuan Hao (21615653)

“…This article takes Jiaozuo City, Henan Province, China as the research area. Based on daily maximum, minimum and mean temperatures from seven meteorological stations for the period 1961<b>–</b>2021, the comprehensive indications of temperature changes were analyzed using the linear tendency estimation, Mann-Kendall test, and levels fluctuation. …”

Variation curve of the mean temperature index. by Chengyuan Hao (21615653)

“…This article takes Jiaozuo City, Henan Province, China as the research area. Based on daily maximum, minimum and mean temperatures from seven meteorological stations for the period 1961<b>–</b>2021, the comprehensive indications of temperature changes were analyzed using the linear tendency estimation, Mann-Kendall test, and levels fluctuation. …”

Parameter estimates of linear mixed effects models for juvenile <i>M</i>. <i>mercenaria</i>, juvenile <i>M</i>. <i>arenaria</i> and juvenile <i>A</i>. <i>islandica</i> mean shell c... by Teagan McMahon (20108036)

Mann-Kendall test for the mean temperature index. by Chengyuan Hao (21615653)

“…This article takes Jiaozuo City, Henan Province, China as the research area. Based on daily maximum, minimum and mean temperatures from seven meteorological stations for the period 1961<b>–</b>2021, the comprehensive indications of temperature changes were analyzed using the linear tendency estimation, Mann-Kendall test, and levels fluctuation. …”

COVID19 effect on essential services. by Admas Abera (11821659)

“…The difference in the trends of services before and during COVID-19 was compared using linear-by-linear tests and the difference of magnitude across the indicators was compared using Autoregressive Integrated Moving Average (ARIMA) interrupted time series analysis at a 5% significance level.…”

Means scores of CAM and CAM-MYCS. by Senay Yildirim-Kahriman (22693464)

The Date. by Chengyuan Hao (21615653)

“…This article takes Jiaozuo City, Henan Province, China as the research area. Based on daily maximum, minimum and mean temperatures from seven meteorological stations for the period 1961<b>–</b>2021, the comprehensive indications of temperature changes were analyzed using the linear tendency estimation, Mann-Kendall test, and levels fluctuation. …”

Variation curve of the extreme temperature index. by Chengyuan Hao (21615653)

“…This article takes Jiaozuo City, Henan Province, China as the research area. Based on daily maximum, minimum and mean temperatures from seven meteorological stations for the period 1961<b>–</b>2021, the comprehensive indications of temperature changes were analyzed using the linear tendency estimation, Mann-Kendall test, and levels fluctuation. …”

Achieving Improved Ion Swarm Shaping Based on Ion Leakage Control in Ion Mobility Spectrometry by Jiyao Wang (2121157)

Study-related adverse events. by Benjamin R. Lewis (22279166)

“…We recorded 12 study-related, Grade 1–2 AEs and no serious AEs. In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”

Study flow chart. by Benjamin R. Lewis (22279166)

“…We recorded 12 study-related, Grade 1–2 AEs and no serious AEs. In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”

Study CONSORT diagram. by Benjamin R. Lewis (22279166)

“…We recorded 12 study-related, Grade 1–2 AEs and no serious AEs. In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”

Mean parameter values for the selected crops. by Gourab Saha (8987405)

“…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”

Scaling of overall health burden with yearly expenditure growth. by Margherita Molaro (17803989)

Fig 6 - by Torsten Schober (20485754)

Detailed information of the observation datasets. by Weidong Ji (129916)

“…On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”

General technical specification for GW154/6700. by Weidong Ji (129916)

“…On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”

Droplet-based microfluidics can be used to model clustered bacterial growth. by Justin Greene (306625)

Gating strategy of experiment using 30 min EdU pulses experiments in mOr2-Piwi1 juvenile polyps. by Eudald Pascual-Carreras (12115380)

Block diagram for IoT-based irrigation system. by Gourab Saha (8987405)

“…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”