cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/ppkr-vf58
title: Corona Virus (COVID-19) Geolocation-based Sentiment Data

description: This dataset contains the geolocation-based sentiment analysis data. The data is generated by an on-going project deployed at https://live.rlamsal.com.np. The geolocation is extracted from the tweets which mention anything about "corona", "covid-19", "coronavirus" or the variants of "sars-cov-2". The longitude and latitude shared in this dataset are the exact ones. That means the user has shared his/her precise location while tweeting. The data is available in four formats: CSV, JSON, SQL and XML. I am sharing this data after receiving an enormous amount of requests from non-technical researchers. If you are someone who is quite comfortable with python and databases, then use "COVID-19 Tweets Dataset" and hydrate the IDs, and add the following condition within your streaming file.if data["coordinates"]:longitude, latitude = data["coordinates"]["coordinates"]
DOI: 10.5281/zenodo.3767047
title: Example DWI Dataset including minimally preprocessed and co-registered data

description: Includes minimally preprocessed and co-registered dataset for example subject containing both diffusion weighted and T1 weighted MR images, both in BIDS format. The dataset in the root directory (i.e. starting with /sub-) should be used as input to many end-to-end pipelines. The dataset in the preprocessed directory (i.e. starting with /derivatives/preproc/) should be used as input to modelling pipelines such as tractometry or connectivity analysis.
description: {"references": ["http://fcon_1000.projects.nitrc.org/indi/enhanced/data.html"]}
DOI: 10.5281/zenodo.3767048
title: Example DWI Dataset including minimally preprocessed and co-registered data

description: Includes minimally preprocessed and co-registered dataset for example subject containing both diffusion weighted and T1 weighted MR images, both in BIDS format. The dataset in the root directory (i.e. starting with /sub-) should be used as input to many end-to-end pipelines. The dataset in the preprocessed directory (i.e. starting with /derivatives/preproc/) should be used as input to modelling pipelines such as tractometry or connectivity analysis.
description: {"references": ["http://fcon_1000.projects.nitrc.org/indi/enhanced/data.html"]}
DOI: 10.14457/mu.the.2016.310
title: Isolation and characterization of biocatalyst digesting stevioside
DOI: 10.14457/mu.the.2016.311
title: Commissioning and validation of compass system for vmat patient specific quality assurance
DOI: 10.14457/mu.the.2016.312
title: Determination of output factor for 6 MV small photon beam : Comparison between monte carlo simulation techaique and micro Diamond detector
DOI: 10.14457/mu.the.2016.313
title: Factors related to quality of life among patients with chronic hepatitis B
DOI: 10.3886/e119144
title: An Antiviral Formulation with RNA Dependent RNA Polymerase and Viral DNA Gyrase Suppressive Features for The Treatment of Coronaviral & Adenoviral Infections

description: <br>The invention relates to a composition for antiviral use. <br><br>State of the Art <br><br>Antiviral agents are the pharmacological agents used against the virus infections. They are used in order to control or destroy the viral infection. Currently existing antiviral therapies are the methods for temporarily suppressing the symptoms caused by the virus, rather than the virus itself, by way of suppression of the enzymes that regulate the capabilities of the viruses to self-replicate and to synthesize DNA from RNA. These components may not provide a permanent solution and they also become ineffective due to the tolerance developed by the virus to these agents in the medium term. The invention no. EP19990203128 entitled “Antiviral compositions” relates to the pharmaceutical compositions of the antiviral compounds that may be administered to a mammal, particularly to a human with viral infection. These compositions include the particles, which may be obtained by melt-extruding a mixture containing one or more antiviral compound and one or more suitable water-soluble polymer and then milling said melt-extruded mixture. As a result, the presence of the need for a composition for antiviral use and the inadequacy of the existing solutions have made it necessary to perform an improvement in the relevant art. <br> <br> Object of the Invention <br><br> In order to eliminate the disadvantages of the state of the art, an object of the invention is to cause permanent destruction in the structure and the function of the virus itself, owing to the tissue-selective increase in the production of nitric oxide (particularly in the tissues exposed to viral infection). Another object of the invention is to effectively inhibit the DNA synthesis capability of the viruses and also the ability of the viruses to transfer the DNA they synthesize into the healthy cells that they have not yet invaded. Another object of the invention is to support intracellular immunity by enhancing the TH1 immune reaction. In order to achieve the aforesaid advantages, the invention is a composition for antiviral use, said composition being obtained by the components selected from the group comprising 1-protopanaxatriol, methylpanaxadiol, methylprotobioside that are used individually or in combinations. The structural and characteristic features and all the advantages of the invention will become more clearly understood from the detailed description provided below and therefore, the evaluation must be made taking this detailed description into consideration.
DOI: 10.3886/e119144v1
title: An Antiviral Formulation with RNA Dependent RNA Polymerase and Viral DNA Gyrase Suppressive Features for The Treatment of Coronaviral & Adenoviral Infections

description: <br>The invention relates to a composition for antiviral use. <br><br>State of the Art <br><br>Antiviral agents are the pharmacological agents used against the virus infections. They are used in order to control or destroy the viral infection. Currently existing antiviral therapies are the methods for temporarily suppressing the symptoms caused by the virus, rather than the virus itself, by way of suppression of the enzymes that regulate the capabilities of the viruses to self-replicate and to synthesize DNA from RNA. These components may not provide a permanent solution and they also become ineffective due to the tolerance developed by the virus to these agents in the medium term. The invention no. EP19990203128 entitled “Antiviral compositions” relates to the pharmaceutical compositions of the antiviral compounds that may be administered to a mammal, particularly to a human with viral infection. These compositions include the particles, which may be obtained by melt-extruding a mixture containing one or more antiviral compound and one or more suitable water-soluble polymer and then milling said melt-extruded mixture. As a result, the presence of the need for a composition for antiviral use and the inadequacy of the existing solutions have made it necessary to perform an improvement in the relevant art. <br> <br> Object of the Invention <br><br> In order to eliminate the disadvantages of the state of the art, an object of the invention is to cause permanent destruction in the structure and the function of the virus itself, owing to the tissue-selective increase in the production of nitric oxide (particularly in the tissues exposed to viral infection). Another object of the invention is to effectively inhibit the DNA synthesis capability of the viruses and also the ability of the viruses to transfer the DNA they synthesize into the healthy cells that they have not yet invaded. Another object of the invention is to support intracellular immunity by enhancing the TH1 immune reaction. In order to achieve the aforesaid advantages, the invention is a composition for antiviral use, said composition being obtained by the components selected from the group comprising 1-protopanaxatriol, methylpanaxadiol, methylprotobioside that are used individually or in combinations. The structural and characteristic features and all the advantages of the invention will become more clearly understood from the detailed description provided below and therefore, the evaluation must be made taking this detailed description into consideration.
DOI: 10.5281/zenodo.3767054
title: Trialstreamer PubMed RCTs 2020-04-24

description: Trialstreamer annotated collection of RCTs 2020-04-24
DOI: 10.14457/cu.res.2000.7
title: ความน่าเชื่อถือในการออกแบบระเบิดหินและการควบคุมผลกระทบต่อสิ่งแวดล้อม
DOI: 10.14457/cu.res.2001.16
title: การประเมินความเสี่ยงและความเชื่อถือได้ของเสถียรภาพของงานการขุดเจาะบนพื้นผิวดินและใต้ผิวดิน
DOI: 10.14457/cu.res.2002.29
title: การพัฒนาออกแบบสร้างโวลเตจดิไวเดอร์สำหรับวัดแรงดันอิมพัลส์หน้าคลื่นชัน
DOI: 10.14457/mu.the.2016.314
title: A content analysis of music therapy interventions to support a good death concept in thai palliative care patients with cancer
DOI: 10.14457/mu.the.2016.315
title: The quality of work-life for nurse practitioners:a case study of intensive care units
DOI: 10.14457/mu.the.2016.316
title: Applying business intelligence in internet traffic analysis: a case study of information and communication technology Silpakorn university
DOI: 10.14457/mu.the.2016.317
title: Factors related to quality of life among patients with HIV/AIDS
DOI: 10.21227/4q7y-3952
title: Corona Virus (COVID-19) Geolocation-based Sentiment Data

description: This dataset contains the geolocation-based sentiment analysis data. The data is generated by an on-going project deployed at https://live.rlamsal.com.np. The geolocation is extracted from the tweets which mention anything about "corona", "covid-19", "coronavirus" or the variants of "sars-cov-2". The longitude and latitude shared in this dataset are the exact ones. That means the user has shared his/her precise location while tweeting.I'll be sharing new files every day, and the files will be named period-wise. For example, april25-april27.* will contain longitude, latitude and sentiment data of the tweets that were tweeted between April 25, 2020, and April 27, 2020. Learn more about Twitter geo objects from here. The data is available in four formats: CSV, JSON, SQL and XML. I am sharing this data after receiving an enormous amount of requests from non-technical researchers. If you are someone who is quite comfortable with programming, JSON and databases, then use "Corona Virus (COVID-19) Tweets Dataset" and hydrate the IDs, and add the following condition within your streaming file.if data["coordinates"] is true; then use longitude, latitude = data["coordinates"]["coordinates"]
DOI: 10.21227/ph6j-ej08
title: Corona Virus (COVID-19) Geolocation-based Sentiment Data

description: This dataset contains the geolocation-based sentiment analysis data. The data is generated by an on-going project deployed at https://live.rlamsal.com.np. The geolocation is extracted from the tweets which mention anything about "corona", "covid-19", "coronavirus" or the variants of "sars-cov-2". The longitude and latitude shared in this dataset are the exact ones. That means the user has shared his/her precise location while tweeting.I'll be sharing new files every day, and the files will be named period-wise. For example, april25-april27.* will contain longitude, latitude and sentiment data of the tweets that were tweeted between April 25, 2020, and April 27, 2020. Learn more about Twitter geo objects from here. The data is available in four formats: CSV, JSON, SQL and XML. I am sharing this data after receiving an enormous amount of requests from non-technical researchers. If you are someone who is quite comfortable with programming, JSON and databases, then use "Corona Virus (COVID-19) Tweets Dataset" and hydrate the IDs, and add the following condition within your streaming file.if data["coordinates"] is true; then use longitude, latitude = data["coordinates"]["coordinates"]
DOI: 10.14457/cu.res.1995.2
title: การประเมินเสถียรภาพของเหมืองเปิดและอุโมงค์ใต้ดิน
DOI: 10.14457/cu.res.2011.77
title: ผลกระทบของการปรับปรุงสิ่งอำนวยความสะดวกทางการค้า ตามข้อตกลงประชาคมอาเซียนที่มีต่อการขนส่งสินค้าข้ามแดนและ การค้าผ่านแดน
DOI: 10.14457/cu.res.2012.106
title: ประกอบสร้างความรู้เรื่องอยุธยาตอนปลาย
DOI: 10.14457/cu.res.2015.45
title: โครงการ การจัดทำแผนที่นำทางการวิจัยประเด็นวิจัยยุทธศาสตร์ เรื่อง "การเปลี่ยนแปลงภูมิอากาศ น้ำ ที่ดิน และ การจัดการสิ่งแวดล้อม"
DOI: 10.14457/cu.res.2016.32
title: การวิจัยเพื่อศึกษาแนวทางการพัฒนาโครงการที่อยู่อาศัยของภาครัฐโดยใช้เกณฑ์ Ecovillag
DOI: 10.14457/cu.res.2016.33
title: การจัดการแผงเซลล์แสงอาทิตย์ที่หมดความคุ้มค่าในการผลิตไฟฟ้า
DOI: 10.14457/mu.the.2016.318
title: The happiness at work of staffs in one of tertiary hospitals
DOI: 10.14457/mu.the.2016.319
title: Lesion detectability in tomographic imaging of radioiodine-131
DOI: 10.14457/mu.the.2016.320
title: Factors related to functional status among patients with ischemic stroke
DOI: 10.14457/mu.the.2017.89
title: In silico approach for differentiation of hypochromic microcytic anemia and dyslipidemia
DOI: 10.14457/cu.res.2015.46
title: การพัฒนาระบบบริหารจัดการเงินสงเคราะห์ (CESS) เพื่อเพิ่มประสิทธิภาพการแข่งขันของอุตสาหกรรมยางพาราของประเทศไทย
DOI: 10.14457/cu.res.2017.7
title: ผลกระทบของการลงทุนโดยตรงขาออกในต่างประเทศต่อการส่งออกและมูลค่าเพิ่มที่ส่งผ่านไปยังเศรษฐกิจไทย
DOI: 10.14457/mu.the.2016.321
title: An assessment of existing and potential ecotourism boat routes at bueng borapet, Nakhon Sawan province,thailand
DOI: 10.14457/mu.the.2016.322
title: The development of thai-psychological capital inventory computerized version
DOI: 10.14457/mu.the.2016.323
title: Factors related to quality of life among patients with asthma
DOI: 10.14457/mu.the.2017.90
title: Criminal charge and punishment identification system using elements of crime
DOI: 10.5281/zenodo.3767055
title: Network-based Drug Repurposing for Human Coronavirus

description: Datasets from a study in which network-based methodologies were used to identify potential repurposable drugs and drug combinations for successfully targeting the 2019 novel coronavirus.
description: 2019-nCoV-master file gives the network proximity result for 2938 drugs against pan-human coronavirus (CoV) and individual CoVs as well as gene set enrichment analysis for the drugs using three CoV transcriptome data set. GPSnet-master file gives the network proximity framework for the dataset.
DOI: 10.5281/zenodo.3767056
title: Network-based Drug Repurposing for Human Coronavirus

description: Datasets from a study in which network-based methodologies were used to identify potential repurposable drugs and drug combinations for successfully targeting the 2019 novel coronavirus.
description: 2019-nCoV-master file gives the network proximity result for 2938 drugs against pan-human coronavirus (CoV) and individual CoVs as well as gene set enrichment analysis for the drugs using three CoV transcriptome data set. GPSnet-master file gives the network proximity framework for the dataset.
DOI: 10.5281/zenodo.3767066
title: Trialstreamer PubMed RCTs 2020-04-26

description: Trialstreamer annotated collection of RCTs 2020-04-26
DOI: 10.14457/cu.res.2017.10
title: ยุทธศาสตร์การพัฒนาสถาบันอุดมศึกษา (มหาวิทยาลัย) สู่การเป็นสถาบันการเรียนรู้ตลอดชีวิต
DOI: 10.14457/cu.res.2017.11
title: ทางเลือกข้อเสนอภาพฉายอนาคตการลดการปล่อยก๊าซเรือนกระจกของอุตสาหกรรมปิโตรเคมี และการพัฒนาศูนย์ความเชี่ยวชาญด้านระบบการตรวจวัด การรายงาน และการทวนสอบกิจกรรมการลดก๊าซเรือนกระจกในภาคอุตสาหกรรม
DOI: 10.14457/cu.res.2017.8
title: กฎหมายแข่งขันทางการค้า / ป้องกันการผูกขาด ในประชาคมเศรษฐกิจอาเซียน (กฎหมายแข่งขันทางการค้าของประเทศสมาชิกอาเซียน)
DOI: 10.14457/cu.res.2017.9
title: การพัฒนาชุดตรวจสอบจุลชีววิทยาอย่างรวดเร็วเเพื่อการเฝ้าระวังความเสี่ยงของเนื้อสุกรในกรุงเทพมหานคร
DOI: 10.14457/cu.res.2018.7
title: ผลของดีแอมิเดชั่นด้วยเอนไซม์ protein-glutaminase ต่อสมบัติการจับกลิ่นรสของโปรตีนมะพร้าว
DOI: 10.14457/mu.the.2016.324
title: Comparison of build-up region doses in oblique tangential 6 MV photon beams calculated by AAA and CCC algorithms in breast rando phantom
DOI: 10.14457/mu.the.2016.325
title: Economic liberalisation,political space and the role of trade unions in vietnam
DOI: 10.14457/mu.the.2016.326
title: Factors related to quality of life among patients with end stage renal disease receiving hemodialysis
DOI: 10.14457/mu.the.2017.91
title: Applying cloud storage and search engine in the thesis management system
DOI: 10.21227/7naj-r029
title: Corona Virus (COVID-19) Tweets Dataset

description: This dataset includes CSV files which contain the tweet IDs. The tweets have been collected by the model deployed here at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for corona virus-related tweets, using filters: language “en”, and keywords “corona”, "coronavirus", "covid", "covid19" and variants of "sarscov2". As per the Twitter Developer Policy, it is not possible for me to provide information other than the Tweet IDs (this dataset has been completely re-designed on March 20, 2020, to comply with data sharing policies set by Twitter). Note: This dataset should be solely used for non-commercial research purpose (ignore every other LICENSE category given in this page).If you're looking for geolocation-based COVID-19 sentiment data: http://dx.doi.org/10.21227/fpsb-jz61 +--------------------------------+
DOI: 10.21227/dy0k-ky76
title: Corona Virus (COVID-19) Tweets Dataset

description: This dataset includes CSV files which contain the tweet IDs. The tweets have been collected by the model deployed here at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for corona virus-related tweets, using filters: language “en”, and keywords “corona”, "coronavirus", "covid", "covid19" and variants of "sarscov2". As per the Twitter Developer Policy, it is not possible for me to provide information other than the Tweet IDs (this dataset has been completely re-designed on March 20, 2020, to comply with data sharing policies set by Twitter). Note: This dataset should be solely used for non-commercial research purpose (ignore every other LICENSE category given in this page).If you're looking for geolocation-based COVID-19 sentiment data: http://dx.doi.org/10.21227/fpsb-jz61 +-------------------------------+
DOI: 10.21227/kr35-vy39
title: Corona Virus (COVID-19) Geolocation-based Sentiment Data

description: This dataset contains the geolocation-based sentiment analysis data. The data is generated by an on-going project deployed at https://live.rlamsal.com.np. The geolocation is extracted from the tweets which mention anything about "corona", "covid-19", "coronavirus" or the variants of "sars-cov-2". The longitude and latitude shared in this dataset are the exact ones. That means the user has shared his/her precise location while tweeting.I'll be sharing new files every day, and the files will be named period-wise. For example, april25-april27.* will contain longitude, latitude and sentiment data of the tweets that were tweeted between April 25, 2020, and April 27, 2020. Learn more about Twitter geo objects from here. The data is available in four formats: CSV, JSON, SQL and XML. I am sharing this data after receiving an enormous amount of requests from non-technical researchers. If you are someone who is quite comfortable with programming, JSON and databases, then use "Corona Virus (COVID-19) Tweets Dataset" and hydrate the IDs, and add the following condition within your streaming file.if data["coordinates"] is true; then use longitude, latitude = data["coordinates"]["coordinates"]
DOI: 10.14457/cu.res.2009.129
title: โครงการการจัดการความรู้และสร้างศักยภาพศาลยุติธรรม ในศาลชํานัญพิเศษ
DOI: 10.14457/cu.res.2014.92
title: การศึกษาสถานภาพเทคโนโลยีเครื่องปฏิกรณ์นิวเคลียร์ขนาดเล็กแบบโมดูลาร์
DOI: 10.14457/cu.res.2015.47
title: การค้นหาโปรตีนชนิดใหม่ของเชื้อเลปโตสไปราสายพันธุ์ก่อโรคที่จับ Factor H complement regulator เพื่อนำมาพัฒนาเป็นวัคซีนสำหรับโรคเลปโตสไปโรซิส
DOI: 10.14457/cu.res.2015.48
title: รูปแบบการสอนทักษะการปฎิบัติในงานตัดเย็บด้วยกิจกรรมหมอนแฟนซีสำหรับนักเรียนชั้นประถมศึกษาตอนปลาย
DOI: 10.14457/mu.the.2016.327
title: Identifying factors that influence intention to adopt qr code among firms in thailand
DOI: 10.14457/mu.the.2016.328
title: Factors related to the functional status among patients with rheumatoid arthritis
DOI: 10.14457/mu.the.2017.92
title: Theoretical and performance analysis of selected 19th-century and 20th-century original tuba compositions by Casterede, Plau and Danielsson
DOI: 10.21227/1dfk-vc18
title: Corona Virus (COVID-19) Geolocation-based Sentiment Data

description: This dataset contains the geolocation-based sentiment analysis data. The data is generated by an on-going project deployed at https://live.rlamsal.com.np. The geolocation is extracted from the tweets which mention anything about "corona", "covid-19", "coronavirus" or the variants of "sars-cov-2". The longitude and latitude shared in this dataset are the exact ones. That means the user has shared his/her precise location while tweeting.I'll be sharing new files every day, and the files will be named period-wise. For example, april25-april27.* will contain longitude, latitude and sentiment data of the tweets that were tweeted between April 25, 2020, and April 27, 2020. Learn more about Twitter geo objects from here. The data is available in four formats: CSV, JSON, SQL and XML. I am sharing this data after receiving an enormous amount of requests from non-technical researchers. If you are someone who is quite comfortable with programming, JSON and databases, then use "Corona Virus (COVID-19) Tweets Dataset" and hydrate the IDs, and add the following condition within your streaming file.if data["coordinates"] is true; then use longitude, latitude = data["coordinates"]["coordinates"]
DOI: 10.21227/2yyb-yz24
title: Twitter Sentiment Analysis Data

description: Each database (*.db) contain three columns. First column: date and time of the tweet, second column: tweet, third column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.If you're looking for geolocation-based COVID-19 sentiment data:http://dx.doi.org/10.21227/fpsb-jz61The tweets have been collected by the LSTM model deployed here at sentiment.live[1]. The last column, viz. sentiment score, is not the score estimated by the model. The LSTM model is still in the pre-alpha phase. Therefore, to make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [2] has been appended as the last column. The sentiment scores produced by our model will be made public after the project is completely open-sourced.References:[1]https://sentiment.live/ [2]https://textblob.readthedocs.io/en/dev/
DOI: 10.21227/8bww-2c91
title: Corona Virus (COVID-19) Geolocation-based Sentiment Data

description: This dataset contains the geolocation-based sentiment analysis data. The data is generated by an on-going project deployed at https://live.rlamsal.com.np. The geolocation is extracted from the tweets which mention anything about "corona", "covid-19", "coronavirus" or the variants of "sars-cov-2". The longitude and latitude shared in this dataset are the exact ones. That means the user has shared his/her precise location while tweeting.I'll be sharing new files every day, and the files will be named period-wise. For example, april25-april27.* will contain longitude, latitude and sentiment data of the tweets that were tweeted between April 25, 2020, and April 27, 2020. Learn more about Twitter geo objects from here. The data is available in four formats: CSV, JSON, SQL and XML. I am sharing this data after receiving an enormous amount of requests from non-technical researchers. If you are someone who is quite comfortable with programming, JSON and databases, then use "Corona Virus (COVID-19) Tweets Dataset" and hydrate the IDs, and add the following condition within your streaming file.if data["coordinates"] is true; then use longitude, latitude = data["coordinates"]["coordinates"]