cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3383693
title: CUPAC - The Coventry University Public Road Data Set for Automated Cars

description: This article presents a dataset recorded with a sensor-equipped research vehicle on public roads in the city of Coventry in the United Kingdom. The sensor suite includes a monocular-, infrared- and smartphone-camera, as well as a LiDAR unit, GPS receiver, Smartphone sensors and vehicle CAN bus data logger. Data were collected by day and night in a variety of traffic, weather and road surface conditions with a focus on the correlation between vehicle dynamics and the environmental perception process of automated vehicles. Please have a look at attached readme file, where detailed information on the data structure and acquisition process are given.
DOI: 10.5281/zenodo.3471309
title: Urban Fabric Types in Osaka-Kobe Metropolitan Area

description: This upload provides the processed results of Multiple Fabric Assessment (Araldi and Fusco, 2019) performed on a hyper-urbanized region of 2,500 km<sup>2</sup> in Japan and including Osaka and Kobe municipalities. The scale of analysis are the areas surrounding urban streets at close distance, which are named proximity bands. Outputs are made available using a geospatial vector data format (GeoPackage - WGS 84/UTM zone 53N) in order to be visualized in a geographic information system software. Attribute data contain the Bayesian probability assignment of each proximity band for the nine urban fabric types that have been identified in the Osaka-Kobe metropolitan area, namely, (1) High-rise and discontinuous modern fabric (2) Discontinuous mid-to-high-rise fabric of mixed land use (3-4) Peripheral low-to-mid-rise discontinuous mixed fabric (5) Industrial and logistic techno-fabrics (6) Residential hyper-compact continuous fabric (7) Residential compact continuous fabric (8) suburban planned single-house residential fabric (9) ex-urban irregular fabric with natural spaces. “MostProb” variable provides the higher probability of each proximity band, which is the main output cross analyzed with field observations in Perez <em>et al.,</em> 2019. Results are based upon the processing of morphological indicators calculated using the following datasets: 2013/14 Zmap-TOWN II (ZENRIN Residential Maps) for building coverage and Digital Road Map Database extended version 2015. Perez J., Araldi A., Fusco G., Fuse T. (2019) “The Character of Urban Japan: Overview of Osaka-Kobe’s Cityscapes”, <em>Urban Science</em>, 3(105), pp 1-22. https://www.mdpi.com/2413-8851/3/4/105 Araldi A., Fusco G. (2019) “From the built environment along the street to the metropolitan region. Human perspective approach in urban fabric analysis<em>”. Environment and Planning B: Urban Analytics and City Science</em>, 46(7), pp. 1243-1263.
DOI: 10.5281/zenodo.3471310
title: Urban Fabric Types in Osaka-Kobe Metropolitan Area

description: This upload provides the processed results of Multiple Fabric Assessment (Araldi and Fusco, 2019) performed on a hyper-urbanized region of 2,500 km<sup>2</sup> in Japan and including Osaka and Kobe municipalities. The scale of analysis are the areas surrounding urban streets at close distance, which are named proximity bands. Outputs are made available using a geospatial vector data format (GeoPackage - WGS 84/UTM zone 53N) in order to be visualized in a geographic information system software. Attribute data contain the Bayesian probability assignment of each proximity band for the nine urban fabric types that have been identified in the Osaka-Kobe metropolitan area, namely, (1) High-rise and discontinuous modern fabric (2) Discontinuous mid-to-high-rise fabric of mixed land use (3-4) Peripheral low-to-mid-rise discontinuous mixed fabric (5) Industrial and logistic techno-fabrics (6) Residential hyper-compact continuous fabric (7) Residential compact continuous fabric (8) suburban planned single-house residential fabric (9) ex-urban irregular fabric with natural spaces. “MostProb” variable provides the higher probability of each proximity band, which is the main output cross analyzed with field observations in Perez <em>et al.,</em> 2019. Results are based upon the processing of morphological indicators calculated using the following datasets: 2013/14 Zmap-TOWN II (ZENRIN Residential Maps) for building coverage and Digital Road Map Database extended version 2015. Perez J., Araldi A., Fusco G., Fuse T. (2019) “The Character of Urban Japan: Overview of Osaka-Kobe’s Cityscapes”, <em>Urban Science</em>, 3(105), pp 1-22. https://www.mdpi.com/2413-8851/3/4/105 Araldi A., Fusco G. (2019) “From the built environment along the street to the metropolitan region. Human perspective approach in urban fabric analysis<em>”. Environment and Planning B: Urban Analytics and City Science</em>, 46(7), pp. 1243-1263.
DOI: 10.15784/601213
title: Antarctic topographic and subglacial lake geostatistical simulations

description: These data accompany the paper "Antarctic Topographic Realizations and Geostatistical Modeling Used to Map Subglacial Lakes" (MacKie et al., in review). This dataset contains 100 geostatistically generated subglacial topographic realizations for Antarctica. Data science techniques were used to calculate the probability of the occurrence of radar-detected lakes and altimetry-detected (active) lakes across the continent, using each topographic realization as a parameter. This generated 100 probability maps of the likelihood of radar-detected lake occurrence and 100 probability maps of active lake occurrence. Further statistics were used to generate 100 binary maps showing expected radar-detected lake locations. The ensemble of realizations can be used for uncertainty quantification.
DOI: 10.21227/nky8-tb05
title: Real-world DNS dataset (2016)

description: · We captured ten days real-world DNS traffic from campus network comprising of 4000 hosts in peak load hours.
DOI: 10.7910/dvn/8zfkw1/4bxtig
title: Bridge_l205.3_b-6.7_l205.3_b-6.7_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/aljwhs
title: Bridge_l223.0_b-5.4_l223.0_b-5.4_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/mob8bl
title: Bridge_l205.6_b-8.0_l205.6_b-8.0_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/oofexu
title: Bridge_l127.3_b13.7_l127.3_b13.7_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/rkxeag
title: Bridge_l214.2_b-17.5_l214.2_b-17.5_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/u4eyua
title: Bridge_l216.6_b-13.9_l216.6_b-13.9_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/wuwx5m
title: Bridge_l217.0_b-13.9_l217.0_b-13.9_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/1wsr3o
title: Bridge_l100.0_b14.8_l100.0_b14.8_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/7rh9e1
title: Bridge_l95.9_b8.1_l95.9_b8.1_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/d0b9vl
title: Bridge_l130.1_b13.8_l130.1_b13.8_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/d6c2k6
title: Bridge_l132.3_b13.2_l132.3_b13.2_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/fcfxzb
title: Bridge_l201.4_b-9.7_l201.4_b-9.7_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/hsxfh1
title: Bridge_l224.0_b-3.4_l224.0_b-3.4_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/i39xc8
title: Bridge_l96.9_b10.2_l96.9_b10.2_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/ydwwhn
title: Bridge_l150.4_b3.9_l150.4_b3.9_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/0oafp4
title: Bridge_l204.1_b-11.7_l204.1_b-11.7_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/2haook
title: Bridge_l92.4_b4.7_l92.4_b4.7_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/4unelq
title: Bridge_l157.1_b-11.9_l157.1_b-11.9_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/5g9jgd
title: Bridge_l178.8_b-6.6_l178.8_b-6.6_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/cmn9bz
title: Bridge_l93.5_b8.6_l93.5_b8.6_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/eqisn1
title: Bridge_l215.0_b-19.8_l215.0_b-19.8_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/fwaziv
title: Bridge_l203.3_b-11.1_l203.3_b-11.1_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/heptfa
title: Bridge_l214.2_b-17.5_l214.2_b-17.5_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/qtwrpc
title: Bridge_l215.0_b-16.8_l215.0_b-16.8_cornerplot_rvfloat.png

description: :unav
DOI: 10.14457/cu.the.2009.2086
title: ความสัมพันธ์ระหว่างภาวะผู้นำแบบผู้ให้บริการของหัวหน้าหอผู้ป่วย วัฒนธรรมองค์การแบบสร้างสรรค์ กับประสิทธิผลของหอผู้ป่วย ตามการรับรู้ของพยาบาลวิชาชีพ โรงพยาบาลศูนย์ สังกัดกระทรวงสาธารณสุข เขตภาคใต้

description: การวิจัยครั้งนี้มีวัตถุประสงค์เพื่อศึกษาความสัมพันธ์ระหว่างภาวะผู้นำแบบผู้ให้บริการของหัวหน้าหอผู้ป่วย วัฒนธรรมองค์การแบบสร้างสรรค์ กับประสิทธิผลของหอผู้ป่วย ตามการรับรู้ของพยาบาลวิชาชีพ โรงพยาบาลศูนย์ สังกัดกระทรวงสาธารณสุข เขตภาคใต้ กลุ่มตัวอย่างคือ พยาบาลวิชาชีพระดับปฏิบัติการที่ปฏิบัติงานตั้งแต่ 1 ปีขึ้นไปในโรงพยาบาลศูนย์ สังกัดกระทรวงสาธารณสุข เขตภาคใต้ จำนวน 349 คน ได้จากการสุ่มตัวอย่างแบบง่าย เครื่องมือที่ใช้ในการวิจัยประกอบด้วย แบบสอบถามภาวะผู้นำแบบผู้ให้บริการของหัวหน้าหอผู้ป่วย แบบสอบถามวัฒนธรรมองค์การแบบสร้างสรรค์ และแบบสอบถามประสิทธิผลของหอผู้ป่วย ผ่านการตรวจสอบความตรงตามเนื้อหา และวิเคราะห์ค่าความเที่ยงโดยทดสอบค่าสัมประสิทธิ์แอลฟ่าครอนบาค ได้ค่าความเที่ยงของแบบสอบถามเท่ากับ .84, .96 และ .94 ตามลำดับ วิเคราะห์ข้อมูลโดยการแจกแจงความถี่ ค่าร้อยละ ค่าเฉลี่ย ส่วนเบี่ยงเบนมาตรฐานและสัมประสิทธิ์สหสัมพันธ์เพียร์สัน ผลการวิจัยสรุปได้ดังนี้ 1. ประสิทธิผลของหอผู้ป่วย ภาวะผู้นำแบบผู้ให้บริการของหัวหน้าหอผู้ป่วยและวัฒนธรรมองค์การแบบสร้าง สรรค์ตามการรับรู้ของพยาบาลวิชาชีพ โรงพยาบาลศูนย์ สังกัดกระทรวงสาธารณสุข เขตภาคใต้ อยู่ในระดับสูง ( X= 3.63, 3.62, 3.73 ตามลำดับ) 2. ภาวะผู้นำแบบผู้ให้บริการของหัวหน้าหอผู้ป่วยและวัฒนธรรมองค์การแบบสร้างสรรค์ มีความสัมพันธ์ทางบวกในระดับปานกลางกับประสิทธิผลของหอผู้ป่วย โรงพยาบาลศูนย์ สังกัดกระทรวงสาธารณสุข เขตภาคใต้ อย่างมีนัยสำคัญทางสถิติที่ระดับ .05 (r =. .497 และ .631 ตามลำดับ)
DOI: 10.5281/zenodo.3471374
title: Herbaceous plants pollen dataset from automatic particle detector in Šiauliai

description: Dataset acquired from Rapid-E device by testing it with anemophilous herbaceous plant pollen collected in Lithuania. Data is sorted by pollen type. The sampling methodology can be found in publication "Automatic pollen recognition with the Rapid-E particle counter: the first-level procedure, experience and next steps", Sauliene Ingrida, et al. Atmospheric Measurement Techniques, 2019, 12.6: 3435-3452. https://doi.org/10.5194/amt-12-3435-2019 Please inform the authors at realtime@su.lt if you use this dataset.
description: This research has been supported by the European Social Fund (project no. 09.3.3-LMT-K-712-01-0066) under grant agreement with the Research Council of Lithuania (LMTLT).
DOI: 10.7910/dvn/8zfkw1/7bvklj
title: Bridge_l102.6_b15.3_l102.6_b15.3_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/83yvll
title: Bridge_l154.6_b2.7_l154.6_b2.7_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/aqloay
title: Bridge_l213.3_b-18.1_l213.3_b-18.1_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/hm0txb
title: Bridge_l217.2_b-12.3_l217.2_b-12.3_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/rvmlts
title: Bridge_l92.4_b4.7_l92.4_b4.7_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/th8xs0
title: Bridge_l178.8_b-6.6_l178.8_b-6.6_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/wplnz9
title: Bridge_l149.3_b3.1_l149.3_b3.1_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/yibesg
title: Bridge_l154.8_b-15.1_l154.8_b-15.1_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/ypaus2
title: Bridge_l142.1_b10.0_l142.1_b10.0_losplot_rvfloat.png

description: :unav
DOI: 10.21227/d4fy-px63
title: Real-world DNS dataset (2016)

description: · We captured ten days real-world DNS traffic from campus network comprising of 4000 hosts in peak load hours.
DOI: 10.7910/dvn/8zfkw1/4yyp9g
title: Bridge_l218.4_b-11.2_l218.4_b-11.2_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/9zjtd9
title: Bridge_l154.6_b2.7_l154.6_b2.7_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/bgdons
title: Bridge_l143.7_b10.1_l143.7_b10.1_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/ghph1a
title: Bridge_l205.3_b-5.9_l205.3_b-5.9_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/meezww
title: Bridge_l97.2_b9.9_l97.2_b9.9_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/txdsft
title: Bridge_l218.4_b-11.2_l218.4_b-11.2_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/vtmtnc
title: Bridge_l224.0_b-3.4_l224.0_b-3.4_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/w1vcwc
title: Bridge_l203.7_b-8.2_l203.7_b-8.2_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/gfyy0n
title: Bridge_l222.4_b-6.4_l222.4_b-6.4_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/ihqrrk
title: Bridge_l154.8_b-15.1_l154.8_b-15.1_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/iylzgr
title: Bridge_l158.6_b-12.1_l158.6_b-12.1_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/oqorms
title: Bridge_l156.0_b-14.3_l156.0_b-14.3_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/pmeyl0
title: Bridge_l205.3_b-6.7_l205.3_b-6.7_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/q93qyi
title: Bridge_l203.3_b-11.1_l203.3_b-11.1_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/qtvacp
title: Bridge_l172.3_b-8.0_l172.3_b-8.0_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/sin3ex
title: Bridge_l142.1_b10.0_l142.1_b10.0_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/gol9jz
title: Bridge_l127.3_b13.7_l127.3_b13.7_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/lauhe9
title: Bridge_l223.7_b-4.6_l223.7_b-4.6_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/nbz8bn
title: Bridge_l223.0_b-5.4_l223.0_b-5.4_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/q1aygl
title: Bridge_l215.0_b-16.8_l215.0_b-16.8_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/qfeduu
title: Bridge_l149.3_b3.1_l149.3_b3.1_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/t9fuvi
title: Bridge_l169.9_b-9.2_l169.9_b-9.2_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/vk9xxa
title: Bridge_l130.1_b13.8_l130.1_b13.8_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/wupk2h
title: Bridge_l157.1_b-11.9_l157.1_b-11.9_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/eg8tpy
title: Bridge_l222.4_b-6.4_l222.4_b-6.4_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/imrslk
title: Bridge_l224.1_b-3.9_l224.1_b-3.9_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/jfro91
title: Bridge_l93.5_b8.6_l93.5_b8.6_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/mzkgsu
title: Bridge_l202.0_b-10.9_l202.0_b-10.9_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/pfl4gx
title: Bridge_l132.3_b13.2_l132.3_b13.2_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/rrwtre
title: Bridge_l217.0_b-13.9_l217.0_b-13.9_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/uhabgl
title: Bridge_l96.9_b10.2_l96.9_b10.2_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/x2vfia
title: Bridge_l100.0_b14.8_l100.0_b14.8_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/b0gkeg
title: Bridge_l221.9_b-6.6_l221.9_b-6.6_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/bjfxcp
title: Bridge_l204.1_b-11.7_l204.1_b-11.7_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/bmrxaf
title: Bridge_l177.8_b-9.5_l177.8_b-9.5_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/citrsp
title: Bridge_l217.2_b-12.3_l217.2_b-12.3_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/df5xs3
title: Bridge_l95.7_b7.8_l95.7_b7.8_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/fisp8o
title: Bridge_l95.7_b7.8_l95.7_b7.8_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/jksvvh
title: Bridge_l216.6_b-15.5_l216.6_b-15.5_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/lsuun0
title: Bridge_l215.0_b-19.8_l215.0_b-19.8_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/wf9ida
title: Bridge_l205.3_b-5.9_l205.3_b-5.9_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/fugsrp
title: Bridge_l223.7_b-4.6_l223.7_b-4.6_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/on3o5r
title: Bridge_l201.4_b-9.7_l201.4_b-9.7_cornerplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/qomiqn
title: Bridge_l150.4_b3.9_l150.4_b3.9_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/qyd4gq
title: Bridge_l202.0_b-10.9_l202.0_b-10.9_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/s7sjzw
title: Bridge_l96.4_b10.3_l96.4_b10.3_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/sv6umu
title: Bridge_l169.9_b-9.2_l169.9_b-9.2_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/vzd4bq
title: Bridge_l222.8_b-6.0_l222.8_b-6.0_losplot_rvfloat.png

description: :unav
DOI: 10.7910/dvn/8zfkw1/wt3tqo
title: Bridge_l156.0_b-14.3_l156.0_b-14.3_losplot_rvfloat.png

description: :unav
DOI: 10.14457/cu.the.2010.1165
title: Indirect determination of melamine by atomic spectrometry of excess copper(II) Ion

description: The indirect atomic absorption spectrometric method was developed for the determination of melamine after forming complexes with excess copper(II) ions. The copper-melamine complex (Cu-Mel) was synthesized by constantly heating and stirring the solution of copper(II) and melamine. Parameters affecting the complex formation including types of copper salt, solvents, temperature, and curing time were investigated in order to optimize the conditions for analytical assay. The optimal conditions for the copper-melamine synthesis were the system of CuCl2 in methanol at 80 °C for 14 hours. The synthesized complex was characterized by X-Ray powder diffraction spectrometry, thermogravimetry, and Fourier transform infrared spectrometry. In addition, stoichiometric study by Job’s plot revealed 1:2 copper-melamine. The complexation reaction was first-order with respect to both copper and melamine, and the activation energy of the reaction estimated by Arrhenius equation was 19.60 kJ/mol. Flame atomic absorption spectrometry used for measuring the amount of copper remaining in the solution indicated that the amount of depleting copper was proportional to the amount of melamine. The calibration curve built between melamine concentration series and copper absorbance showed a linearity with the coefficient of 0.9943 and the limit of detection of 0.60 mM. The external standard and standard addition used for melamine determination in fish sample showed acceptable recoveries between 70-93% and 3.0-10% RSD.
DOI: 10.14457/cu.the.2010.1166
title: Prevalence and determinants of hypertension among Bhutanese monks in Tashi-Choe-Dzong, Thimphu, Bhutan

description: Hypertension or high blood pressure is one of the leading causes of mortality and morbidity in the World, as reported by the WHO in 2004 that 7.5 million deaths are solely attributable to the hypertension. Bhutan, a country of 0.7 million people, reported the current rate (prevalence) of hypertension at 310 per 10,000 population (AHB-2010). As a step towards assessing the prevalence of hypertension and risk factors associated with hypertension, 138 monks at the Tashi-Choe-Dzong, age 20 years and above were recruited to participate in this study. The clinical parameters, i.e. blood pressure measurement and BMI measurement were undertaken on the surveyed monks on this cross sectional study. Analysis of the data revealed that the prevalence rate was 10.2%. Age, number of years of monkhood, monthly income and earlier history of hypertension were found significantly associated with the development of high blood pressure with p-value at α &lt;0.05. Since majority of the studied subjects are in the age group between 20-30 years, the observed prevalence rate was quite low. Moreover the knowledge level of the studied subjects was found very low with 44.9% possessing poor knowledge and 55.1% possessing just fair knowledge on Hypertension
DOI: 10.5281/zenodo.3470301
title: Reflection Spectra Repository for Cool Giant Planets

description: Supplementary material for <em>Exploring H2O Prominence in Reflection Spectra of Cool Giant Planets</em> - ApJ 858, 69 (2018). This repository contains 65520 model reflection spectra of cool giant planets. The grid explores the influence of metallicity, gravity, effective temperature, and sedimentation efficiency on H<sub>2</sub>O absorption signatures in giant planet atmospheres. We also include two animations to visualise how the prominence of H<sub>2</sub>O absorption evolves over this parameter space. The included models range over: *m =&gt; 1-100 x solar (log(m) @ 0.0, 0.5, 1.0, 1.5, 1.7, 2.0 dex) &lt;-- log(m) = 1.7 new for V2 of the database.<br> *g =&gt; 1-100 m/s<sup>2</sup> (evenly over log(g) in steps of 0.1 dex)<br> *T<sub>eff</sub> =&gt; 150-400 K (linearly in steps of 10 K)<br> *f<sub>sed</sub> =&gt; 1-10 (linearly in steps of 1) (V 1.0, March 30th 2018): Initial release of the reflection spectra repository. (V 2.0, Oct 1st 2019): The cool giant reflection spectra grid has been re-computed using the latest version of the PICASO albedo code (doi: 10.3847/1538-4357/ab1b51). This fixes a few bugs and adds new model features (e.g. Raman scattering, see Batalha+2019). The new grid is packaged as a HDF5 file with an accompanying python script 'Open_Albedo_Database.py'. The python script is provided to show how to open the albedo database, plot the spectra, and save spectra as a .txt file. The user need only change 4 lines (specifying log(m), log(g), T<sub>eff</sub>, f<sub>sed</sub>) and run the python script to produce a plot of the albedo spectra (both with and without H<sub>2</sub>O absorption). <strong>NEW</strong>: (V 2.1, Oct 3rd 2019): Fixed a bug causing models with log(g) = 3.4 or 3.9 to not display cloud opacity.