cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/wt7nd5jv6s.1
title: globalcovid19cases6thseptember2020

description: Data In this study the data sources are WHO, CDC, ECDC, NHC, DXY, 1point3acres, Worldometers.info, BNO, the COVID Tracking Project (testing and hospitalizations), State and National Government Health Departments, and local media reports. A layer in the package ArcGis(Arc Gis 2020) was created and maintained by the Center for Systems Science and Engineering (CSSE) at the John Hopkins University (CSSE 2020). This feature layer is supported by ESRI Living Atlas team, JHU APL and JHU Data Services. This layer is opened to the public and free to share. The cases data set was downloaded from that repository on the 6th of September, 2020, and includes the following attributes: Country Name, Deaths(D), Recovered(R) and Active(A) patients. Note that the second and the third are cumulative figures until that day and the last one is the value available on that day. For each frequency (Deaths, Recovered, Active) proportions of the population were calculated in the acomp scale, entries with null values were converted to Below Detection Limits (BDL). The original attributes will now be named in the acomp scale: PD: cumulative relative frequency of deaths PR: cumulative relative frequency of recovered PA: relative frequency of active* Pc: frequency (cumulative and 6th of September) of confirmed cases** *People still being treated **People that caught the Covid-19 Table I Absolute frequencies per country on the 6th September 2020 source: John Hopkins University(JHU) – Center for Systems Science and Engineering (CSSE) link: https://github.com/CSSEGISandData/COVID-19 G – Gray: Active dominant and Recovery subdominant Y – Yellow: Recovery Dominant and Active subdominant B – Black: Recovery Dominant and Deaths subdominant or Active Dominant and Deaths subdominant (just two samples fall into this cathegory) Table II Closure with c=1, acomp scale PD: deaths PR: recovered PA: active
DOI: 10.17632/pcmnjy69gv.1
title: Extreme weather events AMY weather file

description: Building performance simulation in extreme conditions is crucial for improving the resilience of buildings to withstand climate change-induced weather events. Using Actual Meteorological Year weather files instead of Typical Meteorological Year files allows for accurate estimation of building performance during such extreme conditions, enabling the assessment of vulnerabilities and areas that require improvement. The approach applies to both existing buildings needing climate change-resilient retrofits and new building designs that must be compatible with future climatic conditions. The intensification and frequency increase of these extreme weather events make developing adaptation and resilient-building measures imperative, involving understanding potential losses households may experience due to the intensification of extreme events. Addressing the knowledge gap caused by the absence of an AMY weather file dataset is essential for accurate BPS during past extreme climate change-induced weather events. This article introduces a comprehensive .epw format weather file dataset focusing on historical extreme weather events in Canada, encompassing a diverse array of past occurrences in various locations, allowing for better estimation of thermal performance.
DOI: 10.17632/2g67vckxgz.1
title: Data for: Why do people share their travel experiences on social media?

description: Tourism practices and destination decisions are more and more affected by the opinions of trusted friends channeled through social media, and it is therefore of great interest to explore the role that this plays in the travel context. It is also valuable to understand the behaviour of people commonly known as “lurkers”, who travel but do not share their experiences with others. We draw on social influence theory and its three constructs – identification, internalization, and compliance, as well as the users’ personality, to investigate these issues. Based on 381 responses, findings reveal two dominant reasons: first, perceived enjoyment was the most important motive for travellers to share their travel experiences on online networks and travel websites. Second, security and privacy issues are the top latent reasons. This study extends the tourism literature by combining all online behaviours into one single model. We also provide suggestions for further research.
DOI: 10.17632/sj93bbhdcw.2
title: Persistent and Transitory Components of Firm Characteristics

description: Code for Dataset for replicating Persistent and Transitory Components of Firm Characteristics
DOI: 10.17632/7c6dry9hps.1
title: financial literacy

description: Docente Investigadora Universitaria RENACYT.
DOI: 10.17632/pkyn5x4tfy.1
title: Data for: The role of bank funding in risk transmission among Australian banks

description: We use a dataset of 420 weekly observations ranging from 31/03/2004 to 30/06/2017 over eight Australian banks. The balance sheet data are collected from the Australian Prudential Regulation Authority (APRA Monthly Banking Statistics [2017]). APRA requires deposit-taking banks to be locally incorporated and to report their accounts monthly. From these we collect total loans, total deposits, household (mortgage) and financial intermediaries loans, and resident assets. The historical, continuously compounding, return series are computed using daily closing prices and aggregated to monthly returns. All returns data are collected from Bloomberg. We use a ten year Australian bond yield (GACGB10Y), S&P ASX Australia for the market (S&P ASX index) and a trade weighted effective exchange rate index (ATWI Index).
DOI: 10.17632/257mshmtz6.1
title: Data for: A Novel Conjugal Donor Strain for Improved DNA transfer into Clostridium spp.
DOI: 10.17632/ptk9bdbf6w.1
title: Targeted deletion of Fibroblast Growth Factor-23 in adipocytes rescues metabolic dysregulation of diet-induced obesity in female mice

description: Supplemental Data: Supplemental Table 1 and Supplemental Figure 1
DOI: 10.17632/n2fdtbwrxb.2
title: Practice and Knowledge DS Indonesian Adult

description: Raw Data:
1. Data 541 Analysis contains raw data of this study
2. Erratum Data 541 Analysis contains correction on coding variables, all started from 0.

Supplementary file contains:
1. Survey instrument
2. Differences between DS consumption practice of respondents with health-related background and non-health-related background
DOI: 10.15468/dl.jrvyfe
title: Occurrence Download

description: A dataset containing 2912 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Brazil",
 "TaxonKey is Bombus Latreille, 1802",
 "Year 2000-2024"
 ]
}

 The dataset includes 2912 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009250-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/4mm6kdj4xg.1
title: China's Overseas Lending - loan-level dataset and country debt stock estimates

description: Data and replication files for Horn, Reinhart and Trebesch (2021) China's Overseas Lending, forthcoming in the Journal of International Economics. 

Our database contains estimates of debt owed to China by more than 100 developing and emerging market governments for each year 2000-2017. The zip file also contains the underlying micro-level  “consensus” database covering 4900 loans and grants from Chinese official creditors 1949 to 2017. 

The Stata Do file "DebtStockEstimation" uses the micro-level loan data to produce our country-level debt stock estimates. The additional Stata and Excel files allow replicating all figures and main results of Horn, Reinhart and Trebesch (2021).
DOI: 10.17632/x8ygrw87jw.1
title: Data for: A hybrid machine learning approach to cerebral stroke prediction based on imbalanced medical-datasets

description: basic dataset of stroke prediction
DOI: 10.17632/jf79ty994d.1
title: Data for: Endovascular treatment of tracheo-innominate artery fistula: case report and literature review with pooled cohort analysis

description: The data file includes extracted data from historical case reports on tracheoinnominate artery fistulization with surgical or interventional treatments or no treatment.
DOI: 10.17632/3k8rtyfrt6
title: Data Availability

description: This file is the basic data about the “Unraveling Bacterial Catabolism-Induced Modifications in the Molecular Composition of Dissolved Organic Matter” .
DOI: 10.17632/364p44vtj2.1
title: Data:Short Circuit 72Ah Li-Ion Battery & Battery Management Controller

description: This dataset is in support of my research.

I had earlier got remark by someone- If this is my work or stolen or copied paste or other ... remark, from some graduate/pg/plagiarised phd degree holder.

As I wont later entertain any question/remark and I will stop replying lateron (which may start to happen next week or next year). I have uploaded this for free download on this open-access myself.
DOI: 10.17632/br82d4xkj7.1
title: Mental Health dataset based on DASS-21

description: Coding category: 
Q 1.1 Age

Q 1.2 Gender
1. Male 
2. Female

Q 1.3 Marital status 
0. No
1. Yes

Q 1.4 Educational Status
1. Illiterate 
2. Primary
3. SSC
4. HSC
5. Graduation and above

Q 1.5 Occupational Status
1. Housewife 
2. Service 
3. Business 
4. Student
5. Day labor 
6. Unemployed

Q 1.6 Sleeping problem
0. No
1. Yes

Q 3.1 – 3.7 (Stress), 
Q 3.8 – 3.14 (Anxiety), 
Q 3.15 – 3.21 (Depression) 


0. Did not apply to me at all – NEVER
1. Applied to me to some degree, or some of the time – SOMETIMES
2. Applied to me to a considerable degree, or a good part of time – OFTEN
3. Applied to me very much, or most of the time - ALMOST ALWAYS
DOI: 10.17632/hf9fy55wbp.1
title: Tidak Ada Paksaan Dalam Agama - Saeful Karim : Kritikal Review Yan Nurcahya

description: Abstract: Syaiful Karim or Saeful Karim and also known as Father Guru Saiful Karim is an ustaz whose studies often go viral on social media, especially on TikTok. Even though he is known as a preacher, academically, Syaiful Karim is a physics lecturer at the Indonesian University of Education (UPI). The circulation of videos of misleading religious lectures from Syaiful Karim which are widely circulated on TIK Tok has caused inflammation to the Chairman of Barisan Kesatria Nusantara BKN center Muhammad Rofi’I Mukhlis. How could this video not be very misleading? This Critical Review of Cerahamh, from Saeful Karim provides corrections for inaccuracies in the meaning and information regarding his lecture on There is No Compulsion in Religion. In the modern era, humans are sophisticated today. When there is a YouTuber, or a name that is famous and excited at that time. It will influence the YouTuber to check the ongoing information and of course will mislead the YouTuber when the information/lecture delivered is not true.

Keywords: Saiful Karim, Prayer, No Coercion, Religion

Abstrak: Syaiful Karim atau Saeful Karim dan biasa juga dipanggil dengan Ayahanda Guru Saiful Karim merupakan seorang ustaz yang kajiannya kerap viral di media sosial, khususnya di TikTok. Meski dikenal sebagai seorang pendakwah, namun secara akademik, Syaiful Karim merupakan dosen fisika di Universitas Pendidikan Indonesia (UPI). Beredarnya video ceramah agama yang menyesatkan dari Syaiful Karim yang banyak beredar di TIK Tok membuat radang Ketua Barisan Kesatria Nusantara BKN pusat Muhammad Rofi’I Mukhlis. Bagaimana tidak video itu sangat menyesatkan. Kritikal Review Cerahamh, dari Saeful Karim ini menyampaikan koreksi dari ketidaktepatan dengan makna dan informasi mengenai ceramahnya tentang Tidak ada Paksaan Dalam Agama. Di era modern, manusia canggih saat ini. Ketika ada youtuber, atau nama yang terkenal dan heboh pada saat tersebut. Akan mempengaruhi youtuber untuk mengecek info yang berlangsung tersebut  dan tentunya akan menyesatkan youtuber tersebut ketika informasi/ceramah yang disampaikan memang tidak benar.

Kata Kunci: Saiful Karim, Solat, Tidak ada Paksaan, Agama
DOI: 10.17632/hngpw44b8z.1
title: National Culture and the Demand for Physical Money During the First Year of the COVID-19 Pandemic

description: This dataset contains data used in the paper titled "National Culture and the Demand for Physical Money During the First Year of the COVID-19 Pandemic." In it I searched if "national culture" variables had significant impacts on the money demand during the first year of the COVID-19 pandemic.

The main file of this dataset is the "20220923_final_dataset.xlsx" spreadsheet. Sheet "trimed_dataset_final" contains all the data used in the final regressions presented in the paper. In sheet "full_dataset_active", partial data on countries that did not make it into final analyses due to data gaps is also presented. Sheets "CiC", "GDP", "CPI'", "IR", "SI," and "NC" hold all the data on dependent and independent variables I have managed to collect. The origin of each data point is presented in the "data_sources_table." It should be noted that all data in this spreadsheet underwent transformation as described in the paper. However, all raw data is also included in this dataset (folder 'raw_data').

Data on CiC were primarily gathered from the IMF International Financial Statistics database (henceforth: IMF IFS; database: FASMBC_XDC), but for some countries the data were supplemented with the data from National Central Banks’.

Data on NC was taken from the Hofstede Insights consultancy (https://www.hofstede-insights.com/).

Data on GDP was primarily obtained from the IMF IFS (database: NGDP_XDC). Data gaps in this area were filled, if possible, directly from the National Statistical Offices’ (NSOs’) datasets. Because the study is based on monthly data, all quarterly data obtained was temporally disaggregated using the Denton-Cholette method (without an indicator series).

Data on CPI was obtained primarily from Bank for International Settlements (BIS) datasets (https://www.bis.org/statistics/cp.htm) and IMF IFS databases (database: PCPI_IX) [BIS data had precedence]. Data gaps in this area were filled, if possible, directly from the National Statistical Offices’ datasets.

Data on IR was obtained primarily from Bank for International Settlements (BIS) datasets (https://www.bis.org/statistics/cbpol.htm) and IMF IFS databases (databases: FPOLM_PA, FIMM_PA, and FIDR_PA) [BIS data had precedence]. Data gaps in this area were filled, if possible, directly from the National Central Banks’ datasets. Furthermore, data on IR were compiled using hierarchy suggested by the monetary transmission mechanism's: 'central bank policy rates' were given precedence; if those were unavailable,'money market rates' were used; and if those were also unavailable, data on 'deposit rates' were collected.

Data on SI was taken directly from the COVID-19 Government Response Tracker (https://www.bsg.ox.ac.uk/research/research-projects/covid-19-government-response-tracker or https://github.com/OxCGRT/covid-policy-tracker/tree/master/data).
DOI: 10.17632/5jk24v47zp.4
title: Secondary school teachers' and students' perceptions of teaching-learning activities used in biology classrooms

description: The data on teachers' and students' perceptions of teaching-learning activities used in Zambian secondary school biology classrooms were collected between February and May 2022 using two separate survey questionnaires administered to 57 secondary school biology teachers selected from 16 secondary schools and students (469) selected from eight secondary schools. Both instruments were five-point Likert-scale questionnaires measuring participants' perceptions of teaching-learning activities used in biology classrooms. The data includes respondents' gender and their responses to statements on teaching-learning activities used in biology classrooms. Furthermore, students' data on grade level and age were also collected. Respondents (subjects) indicated the degree to which they agreed with 26 teaching-learning activities related to (a) students' prior knowledge and misconceptions, (b) making teaching-learning easy, (c) biology curriculum, (d) teaching strategies, and (d) representations and analogies. The responses ranged from strongly disagree (1), representing disagreement/negative perception, to strongly agree (5), representing agreement/positive perception. Therefore, 1 and 2 represent disagreement/negative perception, 3 represents neutral perception, while 4 and 5 represent agreement/positive perception. The dataset is accompanied by an Excel file named "Dateset on teachers’ and students’ perceptions of biology teaching-learning activities" with five sheets: Sheet 1 (Teaching-learning activities), Sheet 2 (Raw data for teachers), Sheet 3 (Raw data for students), Sheet 4 (Combined raw data) and Sheet 5 (Analysed data). The data were analysed using SPSS version 25, and the results suggest significant differences between teachers' and students' perceptions about teaching-learning activities used in biology classrooms.
DOI: 10.17632/m7bzjsx557.1
title: Latvian Real Estate Announcements Monitoring in 2019

description: This data set represents real estate market announcements monitoring data in Latvia in 2019. The data was collected from online ads site ss.com. The database contains 206,4 thousand ads and consists of 24 groups of data (type of deal, price, characteristics and address of real estate, etc.). The data reflects the dynamics of price changes by months (at the beginning of the month) in 2019. Monitoring continued in 2019 was started in 2018. 2018 year dataset is available in Skribans, Dr.oec. V. (Riga Technical University) (2019): Latvian Real Estate Announcements Monitoring in 2018. DANS. https://doi.org/10.17026/dans-2z3-fx28
DOI: 10.17632/74dg25shnt.1
title: Intermediary Equity Term Structure_Replication Files

description: This file contains the replication code for “Intermediary-Based Equity Term Structure ”, published in the Journal of Financial Economics.
DOI: 10.17632/jb25b25ndf.1
title: Inflation, default and sovereign debt: The role of denomination and ownership

description: Replication files for results in "Inflation, default and sovereign debt: The role of denomination and ownership"
DOI: 10.17632/929mtp3fyr.1
title: Dataset on Water Quality Monitoring Parameters from Various Monitoring Stations in Johor, Malaysia

description: The dataset comprises water quality monitoring data from 39 stations across Johor, Malaysia, collected periodically throughout the year 2020 to capture seasonal variations and long-term trends. The dataset includes 2 (TWO) sheets: one detailing the water quality parameters ("2020") and another providing geographical coordinates and station identifiers ("LATITUDE LONGITUDE").

The "2020" sheet contains the water quality parameters measured at these stations. The parameters include physical measurements such as suspended solids (SS) in mg/l, water temperature (TEMP) in degrees Celsius, conductivity (COND) in milli Siemens per centimeter, and turbidity (TUR) in Nephelometric Turbidity Units. Chemical parameters include concentrations of ammonia nitrogen (NH3-N) in mg/l, chloride (Cl) in mg/l, phosphate (PO4) in mg/l, arsenic (As) in mg/l, and iron (Fe) in mg/l. Additional data points include the frequency of data collection, the date and time of sample collection, and the names of the rivers where the stations are located, such as Sungai Semangar and Sungai Segamat.

The "LATITUDE LONGITUDE" sheet provides essential geographical information for each monitoring station. This includes the state (JOHOR), the basin (e.g., JOHOR, MUAR), latitude and longitude coordinates, and both old (2016) and new station identifiers.
DOI: 10.17632/3dy6tjmzvt.1
title: Date for: How Climate Risk Drives Corporate Green Innovation: Evidence from China

description: This dataset is utilized for the empirical analysis in our study, with CRP and CRP_OPP being focal variables.
DOI: 10.17632/69fmdb25xm.1
title: Mexican Sign Language's Dactylology and Ten First Numbers -Raw videos. From person #8 to #10

description: The following data set has 10 raw recordings of 3 people each (People were anonymously classified from person 8 to 10) performing Sign Language and the First Ten Numbers of Mexican Sign Language. It is worth mentioning that, for each person, 5 recordings were made with the right hand and 5 with the left hand.
DOI: 10.17632/9sb65dzs63.1
title: Abis Lines MF Promises Replication Packet

description: The code in this replication package constructs the tables and figures in Abis and Lines (2024, Journal of Financial Economics) "Broken Promises, Competition, and Capital Allocation in the Mutual Fund Industry". Dummy data are provided in lieu of proprietary and embargoed data.
DOI: 10.17632/c27jz8y4wx.1
title: The impact of social media use on student engagement and acculturative stress among international students in China.

description: The impact of social media use on student engagement and acculturative stress among international students in China.
DOI: 10.17632/hb74ynkjcn.1
title: A Database of Leaf Images: Practice towards Plant Conservation with Plant Pathology

description: The relationship between the plants and the environment is multitudinous and complex. They help in nourishing the atmosphere with diverse elements. Plants are also a substantial element in regulating carbon emission and climate change. But in the past, we have destroyed them without hesitation. For the reason that not only we have lost a number of species located in them, but also a severe result has also been encountered in the form of climate change. However, if we choose to give them time and space, plants have an astonishing ability to recover and re-cloth the earth with varied plant and species that we have, so recently, stormed. Therefore, a contribution has been made in this work towards the study of plant leaf for their identification, detection, disease diagnosis, etc. Twelve economically and environmentally beneficial plants named as Mango, Arjun, Alstonia Scholaris, Guava, Bael, Jamun, Jatropha, Pongamia Pinnata, Basil, Pomegranate, Lemon, and Chinar have been selected for this purpose. Leaf images of these plants in healthy and diseased condition have been acquired and alienated among two separate modules. Principally, the complete set of images have been classified among two classes i.e. healthy and diseased. First, the acquired images are classified and labeled conferring to the plants. The plants were named ranging from P0 to P11. Then the entire dataset has been divided among 22 subject categories ranging from 0000 to 0022. The classes labeled with 0000 to 0011 were marked as a healthy class and ranging from 0012 to 0022 were labeled diseased class. We have collected about 4503 images of which contains 2278 images of healthy leaf and 2225 images of the diseased leaf. All the leaf images were collected from the Shri Mata Vaishno Devi University, Katra. This process has been carried out form the month of March to May in the year 2019. The images are captured in a closed environment. This acquisition process was completely wi-fi enabled. All the images are captured using a Nikon D5300 camera inbuilt with performance timing for shooting JPEG in single shot mode (seconds/frame, max resolution) = 0.58 and for RAW+JPEG = 0.63. The images were in .jpg format captured with 18-55mm lens with sRGB color representation, 24-bit depth, 2 resolution unit, 1000-ISO, and no flash. Further, we hope that this study can be beneficial for researchers and academicians in developing methods for plant identification, plant classification, plant growth monitoring, leave disease diagnosis, etc. Finally, the anticipated impression is towards a better understanding of the plants to be planted and their suitable management.