cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2674k5
title: CCDC 2032656: Experimental Crystal Structure Determination

description: Related Article: Chad H. Michael, Matthias Zeller, Curtis M. Zaleski|2021|J.Chem.Cryst.|51|562|doi:10.1007/s10870-021-00880-7
DOI: 10.5517/ccdc.csd.cc2674l6
title: CCDC 2032657: Experimental Crystal Structure Determination

description: Related Article: Chad H. Michael, Matthias Zeller, Curtis M. Zaleski|2021|J.Chem.Cryst.|51|562|doi:10.1007/s10870-021-00880-7
DOI: 10.5517/ccdc.csd.cc26vdr7
title: CCDC 2051169: Experimental Crystal Structure Determination

description: Related Article: Mohit Kumar, Raziullah, Ashfaq Ahmad, Himangsu Sekhar Dutta, Afsar Ali Khan, Anushka Rastogi, Ruchir Kant, Dipankar Koley|2021|J.Org.Chem.|86|15185|doi:10.1021/acs.joc.1c01811
DOI: 10.5517/ccdc.csd.cc2674m7
title: CCDC 2032658: Experimental Crystal Structure Determination

description: Related Article: Chad H. Michael, Matthias Zeller, Curtis M. Zaleski|2021|J.Chem.Cryst.|51|562|doi:10.1007/s10870-021-00880-7
DOI: 10.5517/ccdc.csd.cc26ytvv
title: CCDC 2054458: Experimental Crystal Structure Determination

description: Related Article: Gao-Liang Zheng, Chenxi Lu, Jin-Pei Cheng, Xin Li|2021|Org.Lett.|23|8499|doi:10.1021/acs.orglett.1c03221
DOI: 10.5517/ccdc.csd.cc26z6v8
title: CCDC 2054830: Experimental Crystal Structure Determination

description: Related Article: Lei Zhao, Xiao Meng, Yifeng Zou, Junsong Zhao, Lili Wang, Lanlan Zhang, Chao Wang|2021|Org.Lett.|23|8516|doi:10.1021/acs.orglett.1c03210
DOI: 10.5517/ccdc.csd.cc27nl4n
title: CCDC 2075361: Experimental Crystal Structure Determination

description: Related Article: Fei Chen|2021|CSD Communication|||
description: Related Article: Yang Zheng, Qing-Yun Yang, Lu-Yan Wu, Xin-Yue Zhu, Ming-Jing Ge, Hao Yang, Shi-Yu Liu, Fei Chen|2021|Org.Lett.|23|8533|doi:10.1021/acs.orglett.1c03196
DOI: 10.5517/ccdc.csd.cc27y8k1
title: CCDC 2083713: Experimental Crystal Structure Determination

description: Related Article: Gianpiero Cera, Margherita Bazzoni, Leonardo Andreoni, Federica Cester Bonati, Chiara Massera, Serena Silvi, Alberto Credi, Andrea Secchi, Arturo Arduini|2021|Eur.J.Org.Chem.|2021|5788|doi:10.1002/ejoc.202101080
DOI: 10.5517/ccdc.csd.cc283tcl
title: CCDC 2089039: Experimental Crystal Structure Determination

description: Related Article: Lei Zhao, Xiao Meng, Yifeng Zou, Junsong Zhao, Lili Wang, Lanlan Zhang, Chao Wang|2021|Org.Lett.|23|8516|doi:10.1021/acs.orglett.1c03210
DOI: 10.5517/ccdc.csd.cc283tdm
title: CCDC 2089040: Experimental Crystal Structure Determination

description: Related Article: Lei Zhao, Xiao Meng, Yifeng Zou, Junsong Zhao, Lili Wang, Lanlan Zhang, Chao Wang|2021|Org.Lett.|23|8516|doi:10.1021/acs.orglett.1c03210
DOI: 10.5517/ccdc.csd.cc28924t
title: CCDC 2094085: Experimental Crystal Structure Determination

description: Related Article: Kate A. Jesse, Sophie W. Anferov, Kelsey A. Collins, Juan A. Valdez-Moreira, Maia E. Czaikowski, Alexander S. Filatov, John S. Anderson|2021|J.Am.Chem.Soc.|143|18121|doi:10.1021/jacs.1c06911
DOI: 10.5517/ccdc.csd.cc289zrb
title: CCDC 2094972: Experimental Crystal Structure Determination

description: Related Article: Juan A. Valdez-Moreira, Daniel M. Beagan, Hao Yang, Joshua Telser, Brian M. Hoffman, Maren Pink, Veronica Carta, Jeremy M. Smith|2021|ACS Cent.Sci.|7|1751|doi:10.1021/acscentsci.1c00890
DOI: 10.5517/ccdc.csd.cc289zsc
title: CCDC 2094973: Experimental Crystal Structure Determination

description: Related Article: Juan A. Valdez-Moreira, Daniel M. Beagan, Hao Yang, Joshua Telser, Brian M. Hoffman, Maren Pink, Veronica Carta, Jeremy M. Smith|2021|ACS Cent.Sci.|7|1751|doi:10.1021/acscentsci.1c00890
DOI: 10.5517/ccdc.csd.cc28bs2h
title: CCDC 2095726: Experimental Crystal Structure Determination

description: Related Article: Guofeng Zhao, Yi Wu, Hai-Hong Wu, Junfeng Yang, Junliang Zhang|2021|J.Am.Chem.Soc.|143|17983|doi:10.1021/jacs.1c09742
DOI: 10.5517/ccdc.csd.cc28bs3j
title: CCDC 2095727: Experimental Crystal Structure Determination

description: Related Article: Guofeng Zhao, Yi Wu, Hai-Hong Wu, Junfeng Yang, Junliang Zhang|2021|J.Am.Chem.Soc.|143|17983|doi:10.1021/jacs.1c09742
DOI: 10.5517/ccdc.csd.cc28c6d8
title: CCDC 2096139: Experimental Crystal Structure Determination

description: Related Article: Kota Koshino, Rei Kinjo|2021|J.Am.Chem.Soc.|143|18172|doi:10.1021/jacs.1c07389
DOI: 10.5517/ccdc.csd.cc28c6f9
title: CCDC 2096140: Experimental Crystal Structure Determination

description: Related Article: Kota Koshino, Rei Kinjo|2021|J.Am.Chem.Soc.|143|18172|doi:10.1021/jacs.1c07389
DOI: 10.5517/ccdc.csd.cc28c6gb
title: CCDC 2096141: Experimental Crystal Structure Determination

description: Related Article: Kota Koshino, Rei Kinjo|2021|J.Am.Chem.Soc.|143|18172|doi:10.1021/jacs.1c07389
DOI: 10.25912/rdf_1619745028901
title: Sensing Science and Engineering Centre (SEC) Structural Data

description: Sixteen vibrating wire strain gauges mounted on sister bars to the steel reinforcement in the pile column. Twelve vibrating sensors report strain in four sides (North, South, East and West) at Vertical, North-South and East-West alignments, and the remaining four are mounted on the level above on four sides (North, South, East and West) at Vertical alignment. Sixteen strain gauges mounted on sister bars are also monitoring strain as a comparison to the vibrating wires. The sensors are mounted on both the upper and lower column and upper and lower slab in four sides (North, South, East and West). All data is logged to a central server at one sample per second and logged. Vibrating wire sensors are connected to National Instruments NI-9205 and sampled at 1Hz. Strain gauge sensors are connected to National Instruments NI-9237 and sampled at 1Hz. Software has been specifically written to collect, organise and store data onto QUT's storage systems. Time stamped strain data from a structural column in the basement car park of the Science and Engineering Centre building on the Gardens Point Campus of Queensland University of Technology. Files are stored in Comma Separated Values (.csv).
DOI: 10.14457/tu.the.2018.1693
title: กลยุทธ์การตั้งราคาห้องพักธุรกิจโรงแรม

description: การค้นคว้าอิสระนี้มุ่งศึกษากลยุทธ์การตั้งราคาห้องพักของธุรกิจโรงแรมเซ็นทาราแกรนด์แอทเซ็นทรัลเวิลด์ที่ส่งผลต่อประสิทธิผลของธุรกิจ และผลต่อความพึงพอใจของลูกค้าของโรงแรมเซ็นทาราแกรนด์แอทเซ็นทรัลเวิลด์ โดยนำข้อมูลทุติยภูมิจาก Smith Travel Research (STR) และจากบริษัท ReviewPro สำคัญ 4 ส่วน คือ อัตราราคาห้องพักเฉลี่ย (Average Room Rate: ARR) อัตราการเข้าพักเฉลี่ย (Occupancy Rate: OCC) อัตราเฉลี่ยของรายได้ต่อจำนวนห้องพักทั้งหมด (Revenue Per Available Room: REVPAR) และ ความพึงพอใจของลูกค้า (Guest Satisfaction Surveys: GSS) มาใช้ในการเปรียบเทียบกลยุทธ์การตั้งราคาห้องพักสูงหรือต่ำกว่าคู่แข่ง จากการที่โรงแรมเซ็นทาราแกรนด์แอทเซ็นทรัลเวิลด์เป็นโรงแรมที่มีเป้าหมายมุ่งเน้นไปยังกลุ่มนักท่องเที่ยวเชิงธุรกิจการจัดประชุมสัมมนาโดยมีทำเลที่ตั้งอยู่ใจกลางแหล่งห้างสรรพสินค้าและย่านธุรกิจของกรุงเทพมหานคร ผลการศึกษานึ้จึงพบว่า การใช้กลยุทธ์การตั้งราคาสูงกว่าคู่แข่งส่งผลต่อประสิทธิผลธุรกิจโรงแรมด้านอัตราเฉลี่ยของรายได้ต่อจำนวนห้องพักทั้งหมด (REVPAR) ให้มีค่าสูงขึ้น โดยเฉพาะกลยุทธ์การตั้งราคาสูงกว่าคู่แข่งมากกว่าร้อยละ 20 เป็นกลยุทธ์ที่ทำให้อัตราเฉลี่ยของรายได้ต่อจำนวนห้องพักทั้งหมด (REVPAR) สูงสุด และกลยุทธ์การตั้งราคาสูงกว่าคู่แข่งไม่มีผลทำให้ความพึงพอใจลดลงนัก อย่างไรก็ตามในการวางกลยุทธ์ราคา โรงแรมก็ควรคำนึงถึงองค์ประกอบต่าง ๆ ของโรงแรม โดยเฉพาะมาตรฐานการบริการด้วย
DOI: 10.25912/rdf_1619745461144
title: Sensing Science and Engineering Centre (SEC) Vibration Data

description: Two structural columns host the sensors (named A3 and A8) and sensors are mounted on the ceiling slabs of every second floor, i.e. levels 3,5,7 and 9 for both columns. Most locations measure three axes of acceleration, except for Level 3 Column A8 and Level 7 Column A8 which only measure x axis. Two additional sites are instrumented, a footbridge leading out of the building and a site to monitor the vibration under a Transmission Electron Microscope (TEM). The footbridge has a total of 8 axes simultaneously measured with addition to two Acoustic Emmisions (AE) sensors monitoring the bridge support and mid span. The TEM has a three-axis accelerometer mounted under the concrete and rubber slab the microscope is mounted to and monitors the vibration the microscope is exposed to. Samples are simultaneously sampled at each location and different sample sites are triggered via a central location to minimise clock drift. Data is sampled at 2000 samples per second per axis 24 hours a day, 7 days a week and logged into csv files. In total there are 31 Axes of data collected throughout the building. Data is uploaded from the data collection server to the storage server in 30 minute intervals. Data is stored in "g's". National Instruments NI-9234 module acquiring data at 2KHz, anti-aliasing filter at 900Hz. Software specifically written to collect, organise and store data onto QUT's storage systems. Time stamped vibration data from multiple locations throughout the Science and Engineering Centre building on the Gardens Point campus of Queensland University of Technology. Files are stored in Comma Separated Values (.csv). At approximately 90MB/hour/channel, software is required that can handle large datasets such as Mathworks MATLAB or National Instruments DIAdem.
DOI: 10.25912/rdf_1619745351201
title: Sensing Science and Engineering Centre (SEC) Subsurface Data

description: This data consists of time stamped strain and extensometer data from the foundations of the Science and Engineering Centre (SEC) building on the Gardens Point campus of Queensland University of Technology. Twelve vibrating wire strain guages are mounted on sister bars to the steel reinforcement in the pile column report strain in four orientations (North, South, East and West) over three heights (Upper, Middle and Lower). This data is logged to a central server at 1 sample per second and logged. Extensometer data is logged with six rod type multiple borehole extensometers monitoring the stability and movement of the foundation of the building. Data is collected from these sensors at 1 sample per second. Two three-axis accelerometers collect vibration data at two locations. One location is the pile that the strain measurements are taken, and the other is a reference sensor mounted to the earth. This data is logged to a central server at 2000 sample per second and logged. All sensors are connected to National Instruments NI-9205 and sampled at 2KHz, with down sampling applied to the strain and extensometers. Software is specifically written to collect, organise and store data onto QUT's storage systems. Files are stored in Comma Separated Values (.csv).
DOI: 10.6084/m9.figshare.14685432
title: CT_Configuration_Comparison

description: The experimental datasets corresponding to the manuscript [manuscript in preparation] (invited). <br><br>Contains two datasets of potassium ion beam transients extracted from the LPSC 14 GHz Phoenix-type Charge Breeder Electron Cyclotron Resonance Ion Source, each dataset corresponding to a different operating condition of the source (described in more detail in the measurement legends and in the manuscript).<br><br>Data is readily analyzed by means of the Consecutive Transients analysis code, which is publicly available at the URL: https://github.com/misapema-jyfl/popTauPy<br>The CT-method was first described in: J Angot <em>et al</em> 2020 <em>Plasma Sources Sci. Technol.</em> <b>30</b> 03501818(https://doi.org/10.1088/1361-6595/abe611)<br>
DOI: 10.6084/m9.figshare.14685432.v1
title: CT_Configuration_Comparison

description: The experimental datasets corresponding to the manuscript [manuscript in preparation] (invited). <br><br>Contains two datasets of potassium ion beam transients extracted from the LPSC 14 GHz Phoenix-type Charge Breeder Electron Cyclotron Resonance Ion Source, each dataset corresponding to a different operating condition of the source (described in more detail in the measurement legends and in the manuscript).<br><br>Data is readily analyzed by means of the Consecutive Transients analysis code, which is publicly available at the URL: https://github.com/misapema-jyfl/popTauPy<br>The CT-method was first described in: J Angot <em>et al</em> 2020 <em>Plasma Sources Sci. Technol.</em> <b>30</b> 03501818(https://doi.org/10.1088/1361-6595/abe611)<br>
DOI: 10.6084/m9.figshare.12026433
title: Development of the MobQoL patient reported outcome measure for mobility-related quality of life

description: To examine how mobility and mobility impairment affect quality of life; to develop a descriptive system (i.e., questions and answers) for a novel mobility-related quality of life outcome measure. Data were collected through semi-structured interviews. Participants were recruited predominantly from NHS posture and mobility services. Qualitative framework analysis was used to analyse data. In the first stage of analysis the key dimensions of mobility-related quality of life were defined, and in the second stage a novel descriptive system was developed from the identified dimensions. Forty-six interviews were conducted with 37 participants (aged 20–94 years). Participants had a wide range of conditions and disabilities which impaired their mobility, including cerebral palsy, multiple sclerosis, and arthritis. Eleven dimensions of mobility-related quality of life were identified: accessibility, safety, relationships, social inclusion, participation, personal care, pain and discomfort, independence, energy, self-esteem, and mental-wellbeing. A new outcome measure, known as MobQoL, was developed. Mobility and mobility impairment can have significant impacts on quality of life. MobQoL is the first outcome measure designed specifically to measure the impact of mobility on quality of life, and therefore has utility in research and practice to measure patient outcomes related to rehabilitation.Implications for RehabilitationMobility impairment affects many different aspects of health and quality of life.The impact of mobility impairment on quality of life is related to processes of physical, emotional, and behavioural adaptation.MobQoL is the first patient-reported outcome measure designed specifically to measure the quality of life impacts of mobility impairment and assistive mobility technology use.MobQoL has potential to be used by rehabilitation professionals to measure and monitor mobility-related quality of life as part of routine clinical practice. Mobility impairment affects many different aspects of health and quality of life. The impact of mobility impairment on quality of life is related to processes of physical, emotional, and behavioural adaptation. MobQoL is the first patient-reported outcome measure designed specifically to measure the quality of life impacts of mobility impairment and assistive mobility technology use. MobQoL has potential to be used by rehabilitation professionals to measure and monitor mobility-related quality of life as part of routine clinical practice.
DOI: 10.6084/m9.figshare.12006486.v1
title: Identifying barriers and facilitators to physical activity for people with scleroderma: a nominal group technique study

description: People with systemic sclerosis (scleroderma) face difficulties being physically active. This study identified physical activity barriers and facilitators experienced by people with scleroderma. We conducted nominal group technique sessions with scleroderma patients who shared physical activity barriers, barrier-specific facilitators, and general facilitators. Participants rated importance of barriers and likelihood of using facilitators from 0 to 10, and indicated whether they had tried facilitators. Barriers and facilitators across sessions were merged to eliminate overlap; edited by investigators, patient advisors, and clinicians; and categorized using qualitative content analysis. We conducted 9 sessions (<i>n</i> = 41 participants) and initially generated 181 barriers, 457 barrier-specific facilitators, and 20 general facilitators. The number of consolidated barriers (barrier-specific facilitators in parentheses) per category were: 14 (61) for health and medical; 4 (23) for social and personal; 1 (3) for time, work, and lifestyle; and 1 (4) for environmental. There were 12 consolidated general facilitators. The consolidated items with ≥1/3 of participants’ ratings ≥8 were: 15 barriers, 69 barrier-specific facilitators, and 9 general facilitators. Scleroderma patients reported many barriers related to health and medical aspects of scleroderma and several barriers in other categories. They reported facilitators to remain physically active despite the barriers.Implications for RehabilitationPeople with scleroderma experience difficulty being physically active due to the diverse and often severe manifestations of the disease, including involvement of the skin, musculoskeletal system, and internal organs.In addition to regular care of scleroderma-related symptoms, patients overcome many exercise challenges by selecting physical activities that are comfortable for them, adjusting the intensity and duration of activities, adapting activities, and using adapted equipment or other materials to reduce discomfort.Rehabilitation professionals should help people with scleroderma to tailor activity options to their capacity and needs when providing care and advice to promote physical activity. People with scleroderma experience difficulty being physically active due to the diverse and often severe manifestations of the disease, including involvement of the skin, musculoskeletal system, and internal organs. In addition to regular care of scleroderma-related symptoms, patients overcome many exercise challenges by selecting physical activities that are comfortable for them, adjusting the intensity and duration of activities, adapting activities, and using adapted equipment or other materials to reduce discomfort. Rehabilitation professionals should help people with scleroderma to tailor activity options to their capacity and needs when providing care and advice to promote physical activity.
DOI: 10.6084/m9.figshare.12006486
title: Identifying barriers and facilitators to physical activity for people with scleroderma: a nominal group technique study

description: People with systemic sclerosis (scleroderma) face difficulties being physically active. This study identified physical activity barriers and facilitators experienced by people with scleroderma. We conducted nominal group technique sessions with scleroderma patients who shared physical activity barriers, barrier-specific facilitators, and general facilitators. Participants rated importance of barriers and likelihood of using facilitators from 0 to 10, and indicated whether they had tried facilitators. Barriers and facilitators across sessions were merged to eliminate overlap; edited by investigators, patient advisors, and clinicians; and categorized using qualitative content analysis. We conducted 9 sessions (<i>n</i> = 41 participants) and initially generated 181 barriers, 457 barrier-specific facilitators, and 20 general facilitators. The number of consolidated barriers (barrier-specific facilitators in parentheses) per category were: 14 (61) for health and medical; 4 (23) for social and personal; 1 (3) for time, work, and lifestyle; and 1 (4) for environmental. There were 12 consolidated general facilitators. The consolidated items with ≥1/3 of participants’ ratings ≥8 were: 15 barriers, 69 barrier-specific facilitators, and 9 general facilitators. Scleroderma patients reported many barriers related to health and medical aspects of scleroderma and several barriers in other categories. They reported facilitators to remain physically active despite the barriers.Implications for RehabilitationPeople with scleroderma experience difficulty being physically active due to the diverse and often severe manifestations of the disease, including involvement of the skin, musculoskeletal system, and internal organs.In addition to regular care of scleroderma-related symptoms, patients overcome many exercise challenges by selecting physical activities that are comfortable for them, adjusting the intensity and duration of activities, adapting activities, and using adapted equipment or other materials to reduce discomfort.Rehabilitation professionals should help people with scleroderma to tailor activity options to their capacity and needs when providing care and advice to promote physical activity. People with scleroderma experience difficulty being physically active due to the diverse and often severe manifestations of the disease, including involvement of the skin, musculoskeletal system, and internal organs. In addition to regular care of scleroderma-related symptoms, patients overcome many exercise challenges by selecting physical activities that are comfortable for them, adjusting the intensity and duration of activities, adapting activities, and using adapted equipment or other materials to reduce discomfort. Rehabilitation professionals should help people with scleroderma to tailor activity options to their capacity and needs when providing care and advice to promote physical activity.
DOI: 10.6084/m9.figshare.12026433.v1
title: Development of the MobQoL patient reported outcome measure for mobility-related quality of life

description: To examine how mobility and mobility impairment affect quality of life; to develop a descriptive system (i.e., questions and answers) for a novel mobility-related quality of life outcome measure. Data were collected through semi-structured interviews. Participants were recruited predominantly from NHS posture and mobility services. Qualitative framework analysis was used to analyse data. In the first stage of analysis the key dimensions of mobility-related quality of life were defined, and in the second stage a novel descriptive system was developed from the identified dimensions. Forty-six interviews were conducted with 37 participants (aged 20–94 years). Participants had a wide range of conditions and disabilities which impaired their mobility, including cerebral palsy, multiple sclerosis, and arthritis. Eleven dimensions of mobility-related quality of life were identified: accessibility, safety, relationships, social inclusion, participation, personal care, pain and discomfort, independence, energy, self-esteem, and mental-wellbeing. A new outcome measure, known as MobQoL, was developed. Mobility and mobility impairment can have significant impacts on quality of life. MobQoL is the first outcome measure designed specifically to measure the impact of mobility on quality of life, and therefore has utility in research and practice to measure patient outcomes related to rehabilitation.Implications for RehabilitationMobility impairment affects many different aspects of health and quality of life.The impact of mobility impairment on quality of life is related to processes of physical, emotional, and behavioural adaptation.MobQoL is the first patient-reported outcome measure designed specifically to measure the quality of life impacts of mobility impairment and assistive mobility technology use.MobQoL has potential to be used by rehabilitation professionals to measure and monitor mobility-related quality of life as part of routine clinical practice. Mobility impairment affects many different aspects of health and quality of life. The impact of mobility impairment on quality of life is related to processes of physical, emotional, and behavioural adaptation. MobQoL is the first patient-reported outcome measure designed specifically to measure the quality of life impacts of mobility impairment and assistive mobility technology use. MobQoL has potential to be used by rehabilitation professionals to measure and monitor mobility-related quality of life as part of routine clinical practice.
DOI: 10.6084/m9.figshare.14864769.v1
title: clean_data

description: This item contains fish swimming speed (ucrit) and morphological measurement datasets.
DOI: 10.5517/ccdc.csd.cc28c6jd
title: CCDC 2096143: Experimental Crystal Structure Determination

description: Related Article: Kota Koshino, Rei Kinjo|2021|J.Am.Chem.Soc.|143|18172|doi:10.1021/jacs.1c07389