cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.ejyg4e
title: Occurrence Download

description: A dataset containing 1119 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pinus rigida Mill.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 1119 records from 121 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009239-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/95fb84nzcd.3
title: Nairobi Securities Exchange Prices 2008-2012 for 6 selected stocks

description: Stock market prediction remains active research in a quest to inform investors on how to trade (buy/sell) at the most opportune time. The prevalent methods used by stock market players in trying to predict the likely future trade prices are either technical, fundamental or time series analysis. This research wanted to try out machine learning methods, in contrast to the existing prevalent methods. Artificial neural networks (ANNs) tend to be the preferred machine learning method for this type of application. However, ANNs require some historical data to learn from, in order to do predictions. The research used an ANN model to test the hypothesis that the next day price (prediction) can be determined from the stock prices of the immediate last five days. The final ANN model used for the tests was a feedforward multi-layer perceptron (MLP) with error backpropagation, using sigmoid activation function, with network configuration 5:21:21:1. The data period used was a 5-year dataset (2008 to 2012), with 80% of the data (4-year data) used for training and the balance 20% used for testing (last 1-year data). The original raw data for Nairobi Securities Exchange (NSE) was scrapped from a publicly available and accessible website of a stock market analysis company in Kenya (Synergy, 2020). This daily prices data was first exported to a spreadsheet, then cleaned off headers and other redundant information, leaving only the data with stock name, date of trade and the related data such as volumes, low prices, high prices and adjusted prices. The data was further sorted by the stock names and then the trading dates. The data dimension was finally reduced to only what was needed for the research, which was the stock name, the date of trade and the adjusted price (average trade price). This final dataset was in CSV format, as hereby presented. The research tested three NSE stocks with the mean absolute percentage error (MAPE) ranging between 0.77% to 1.91%, over the 3-month testing period, while the root mean squared error (RMSE) ranged between 1.83 and 3.07. This raw data can be used to train and test any machine learning model that requires training and testing data. The data can also be used to validate and reproduce the results already presented in this research. There could be slight variance between what is obtained when reproducing the results, due to the differences in the final exact weights that the trained ANN model eventually achieves. However, these differences should not be significant. List of data files on this dataset: stock01_NSE_01jan2008_to_31dec2012_Kakuzi.csv stock02_NSE_01jan2008_to_31dec2012_StandardBank.csv stock03_NSE_01jan2008_to_31dec2012_KenyaAirways.csv stock04_NSE_01jan2008_to_31dec2012_BamburiCement.csv stock05_NSE_01jan2008_to_31dec2012_Kengen.csv stock06_NSE_01jan2008_to_31dec2012_BAT.csv References: Synergy Systems Ltd. (2020). MyStocks. Retrieved March 9, 2020, from http://live.mystocks.co.ke/
DOI: 10.17632/rdwn4bs5ky.2
title: BANSpEmo: A Bangla Language Emotional Speech Recognition Dataset

description: For languages with low resources like the Bangla language, BANSpEmo is the third audio dataset for emotional speech recognition (SER). BANSpEmo consists of 792 utterance recordings of six basic emotional reactions of two sets of sentences. Each set has six sentences. Speakers are explained the emotional states and utterances are recorded in a more realistic way than just reading the sentences. These emotional states are Disgust (বিতৃষ্ণা),  Happy (খুশি),  Sad (দুঃখজনক), Surprised (বিস্মিত), Anger (রাগ), Fear (ভয়). The produced corpus includes voice recordings from 22 unprofessional speakers, 11 of whom are male and 11 of whom are female. The audio recording was for two sets of sentences.
DOI: 10.17632/vcfsgryyb4.2
title: The Effect of Institutional Factors on Financial Deepening:  Evidence from 50 African Countries

description: This paper investigates the impact of institutional factors on financial deepening and its implications on bank credit in Africa. The paper employs different panel econometric models to examine the heterogeneity of 50 African countries from 2000 to 2019. The estimators include panel corrected standard errors, system generalized method of moments, quantile and threshold regressions. The results show that rule of law, regulatory quality, government effectiveness, voice and accountability, control of corruption, and political stability significantly influence financial deepening in Africa. However, government effectiveness has a higher effect on middle- and high-income countries, while other indicators have a high impact on low-income countries. All institutional indicators have stronger effects, almost double, at higher financial levels than for countries with lower levels. Government effectiveness and regulatory quality impact financial deepening more for countries with strong institutions than weak ones. Thus, the relationship between institutional qualities and credit provided by banks is non-monotonic. The findings suggest that strengthening appropriate institutional factors based on country heterogeneity may effectively stimulate debt financing in Africa, the primary source of financing for small and medium-sized enterprises and entrepreneurs. The novelty of this paper is that previous studies did not sufficiently scrutinize the heterogeneity of the structure of African economies – i.e. differences in institution, credit and income levels.
DOI: 10.17632/v4kp9c947k.1
title: chatgpt self-study experimental data

description: The shared data is part of a research project that assessed the influences of ChatGPT on the learning success of university students. We carried out experiments in two separate subjects to compare the learning success (measured via a test) of ChatGPT self-study against traditional lectures. 
The data file consists of 3 sheets. 
Learning duration: depicts the duration of each student for developing learning contents with ChatGPT. It is divided into two subjects and a consolidated table. 
Course 1: contains scores (result points) per student in the lecture and the ChatGPT group incl. the gender for the PI experiment. 
Course 2: contains scores (result points) per student in the lecture and the ChatGPT group incl. the gender for the HRM experiment.
DOI: 10.17632/bmfh63cc74.1
title: Geospatial datasets of energy consumption drivers in the Ecuador's residential sector

description: The geospatial datasets presented here provides high-resolution gridded data respect to Population, Gross Domestic Product (GDP), GDP per capita (GDPpc), Human Development Index (HDI) and four residential energy demands for Ecuador, between 2010 and 2020. Each variable follows a specific method and uses other available data to end with the calculated datasets. Gridded population dataset primarily uses data from the Center for International Earth Science Information Network, which is calibrated using Ecuadorian official data provided by the National Institute of Statistics and Censuses (INEC). Gridded GDP uses data provided by the Central Bank of Ecuador (BCE), whereas GDPpc is the relationship between GDP and the previously calculated population counts. The HDI is a combination of data provided by INEC, BCE, Minister of Education and Secretary of Higher Education. The four gridded energy demand datasets for the residential sector are (i) space heating, (ii) space cooling, (iii) water heating, and (iv) total energy demand. To end with these demands, the approach combines datasets from NASA temperature with population and energy balances by the Agency for the Regulation and Control of Energy and Non-Renewable Natural Resources. These datasets provide high-profile information for long-term energy policy and planning for national and local government. These datasets are also important for the research community and enterprises to prioritize energy research and development.
DOI: 10.17632/jgcg2y64sw.1
title: Data for: The impacts of government ideology on innovation: What are the main implications?

description: see detailed in data file
DOI: 10.17632/t6w796prvt.2
title: Supplemental Table 1: Types of treatment for primary, non-metastatic cutaneous squamous cell carcinomas that developed poor outcomes

description: This table details the types of curative therapy used to treat each primary, non-metastatic cutaneous squamous cell carcinoma that led to poor outcomes (n=782) in this multi-center, multinational dataset of over 23,000 CSCCs from 12 institutions within the United States, Spain, and Brazil.
DOI: 10.17632/snp7sbkb36.1
title: Delhi's ambient PM2.5 concentrations data for 2006-2018

description: This dataset presents Delhi's ambient PM2.5 data in the raw format at 15-minute interval for the period of 2006 to 2018. The data is obtained from the online open repository operated and maintained by the Central Pollution Control Board (CPCB), India. https://app.cpcbccr.com/ccr/#/caaqm-dashboard-all/caaqm-landing (last accessed August 21st, 2020). Use the advance search option to download. The data request conditions vary by pollutant, time step, and total time period. The data was filtered for nulls, negatives, and unexplainable feeds for quality control. Cleaned composite concentrations file for all of Delhi includes hourly averages, monthly averages, annual averages, number of operating stations by year, and data availability as % of 15-minute data points in a year
DOI: 10.17632/jfwttjcxvz.1
title: THE STRUCTURE AND PRACTICE OF THE ROSARY: A DETAILED EXAMINATION OF ITS ROLE IN ADDICTION RECOVERY AND MINDFULNESS IN DAILY LIFE

description: This article provides an in-depth examination of the Rosary’s structure and practice, with a focus on its role in addiction recovery and mindfulness. As a central element of Catholic devotion, the Rosary integrates repetitive prayer with meditation on key events from Christ’s life, known as the Mysteries. The study explores the Rosary’s alignment with Catholic doctrines of healing and transformation, highlighting its capacity to promote mindfulness, emotional balance, and spiritual resilience. The repetitive nature of the prayers fosters mental discipline, which is crucial in addiction recovery, while the meditative reflection on the Mysteries encourages personal spiritual growth. Additionally, Marian devotion, an essential part of the Rosary, provides comfort and inspiration to individuals in recovery, 
promoting virtues such as faith, humility, and perseverance. This analysis positions the Rosary as a valuable spiritual tool, bridging the gap between faith and healing, supporting both individual recovery and long-term emotional well-being.
DOI: 10.17632/vb4xmyknvj.1
title: Dataset on Financial Technology and Customer Satisfaction in Systemically Important Banks in Kaduna State, Nigeria

description: • The data provides empirical insights into the effectiveness of fintech in enhancing customer satisfaction, which can inform policy decisions aimed at improving financial inclusion and banking services in Nigeria.
• Banks can use the data to develop customer retention and service improvement strategies, leveraging fintech solutions to enhance their competitive edge. 
• This data can assists the United Nations in evaluating progress toward achieving SDGs 9 and identifying areas needing additional attention.
DOI: 10.17632/jnyfw3xzrk.1
title: AGRICULTURAL CROP RESIDUES: ITS POTENTIAL AS NUTRIENT MEDIA IN IN-VITRO CULTURE OF OYSTER MUSHROOM (Pleurotus Ostreatus)

description: The disposal of agri-waste is one of the most pressing problems facing the Philippines today. Farmers have chosen to burn agricultural waste as a disposal method, which pollutes the environment and leads to climate change. A study was conducted to determine the potential of different crop residues as agar-based nutrient media for the in-vitro culture of Oyster Mushroom (Pleurotus ostreatus). The study was lay-outed using Completely Randomized Design (CRD) replicated three times with 7 treatments include Water Hyacinth Agar (WHA), 50% Banana Leaves and 50% Bracts Agar (BLBA), 50% Rice Straw and 50% Hull Agar (RSHA), Palm Oil Empty Bunch Agar (POEBA), 50% Corn Cobs and 50% Husk Agar (CCHA), Coconut Coir Agar (CCA) with Potato Dextrose Agar (PDA) as control. The different media were prepared aseptically in the laboratory, and isolation and data collection took place 7-14 days later. Results showed that crop residues from Water Hyacinth, Banana Leaves and Bracts, Rice Straw and Hull, Palm Oil Empty Bunch, and Coco Coir were found to be a good substitute media for oyster mushroom development, as the substrate promotes oyster mushroom growth and colonization in in-vitro culture. However, since it colonized the media in such a short time, Palm Oil empty bunch may be one of the best alternatives for PDA.
DOI: 10.17632/sd554hbbjb.1
title: Efficacy and safety of the oral Janus kinase inhibitor baricitinib in the treatment of adults with alopecia areata: Phase 2 results from a randomized controlled study - Supplement

description: Supplemental material for manuscript published in the Journal for the American Academy of Dermatology. https://doi.org/10.1016/j.jaad.2021.05.050
DOI: 10.17632/4r8hp2hmb4.5
title: Electroencephalogram (EEG) dataset with porn addiction and healthy teenagers under rest and executive function task

description: A set of electroencephalogram (EEG) signals data obtained from Yayasan Kita Dan Buah Hati (YKBH), Jakarta, Indonesia. The data was collected using a BrainMaker EEG machine with 19 channels. The sampling rate of the machine is 250Hz. There are 14 participants (girl = 5, boy = 9) join the data collection. A psychologist has verified 7 of them are an addiction, and 7 of them are healthy children. The EEG data were recorded through one protocol with five tasks for 10 minutes. The five tasks are baseline, emotional state, memorize task, executive task, and recall task. The obtained data is used for analyzing the pattern of pornography addiction among children. Further analysis of pre-processing, feature extraction, and classification will be applied to the data.
DOI: 10.17632/kv38x5dxtj.1
title: Dataset on The Sustainable Smart City Development in Indonesia

description: mart city movements are growing all over the world. The un-dertaking is expected to solve a plethora of problems arising from urbanization. Indonesia is one of the countries who march toward the development of sustainable smart cities. However, before the government can start a smart city project, they need to assess the readiness of each target city. Data in this article illustrate the readiness of six major cities in Indonesia, which are Semarang, Makassar, Jakarta, Samarinda, Medan, and Surabaya. They repre-sent the four biggest islands in Indonesia. The readiness assess-ment was based on three main elements and six Smart City Pillars taken from Smart City Master Plan Preparation Guidance Book prepared by Ministry of Communication and Information Tech-nology of the Republic of Indonesia. Those elements serve as a checklist to determine the readiness of the cities. Data for quali-tative analysis were gathered through interviews and triangulated through secondary sources, such as publication from Statistics Indonesia and the assessment reports. The dataset contains in-formation on the readiness assessment is presented in this article. The indices of the six region's readiness assessment are presented in percentages.
DOI: 10.17632/hxh8kd3snj.1
title: Acoustic Signal Dataset: Tall Coconut Fruit Species

description: The dataset contains the extracted acoustic signal features of tall Philippine coconut fruits. There are a total of 129 coconut samples that were tapped uniformly on their three side ridges. Acoustic signals acquired from each ridge are recorded, having a total of 387 acoustic signals.
The coconut_acoustic signals.csv shows the acoustic features of coconuts. The dataset is divided into three sheets: ‘Ridge A’, ‘Ridge B’, and ‘Ridge C’. Acoustic signals in each sheet are labeled with their corresponding sample number and their maturity level classification. There are three maturity levels used with their respective maturity level code (im: ‘premature’, m: ‘mature’, om: ‘overmature’). There are 8, 36, and 85 coconut samples per maturity level, respectively.
The dataset can be used for machine learning procedures and the classification of coconuts according to their maturity levels based on their acoustic features.
DOI: 10.17632/xxxcsknt9f.1
title: Large International Corporate Bonds: Investor Behavior and Firm Responses

description: Included are the readme file and the do file needed to reproduce the paper "Large International Corporate Bonds: Investor Behavior and Firm Responses," by Charles W. Calomiris, Mauricio Larrain, Sergio L. Schmukler, and Tomas Williams, published at the Journal of International Economics.
DOI: 10.17632/zj9g4s8psf.2
title: Bebagai Macam Jenis Merek Obat Aborsi dan Obat Penggugur Kandungan Di Apotek yang Dijual Bebas Tanpa Resep Dokter ( Misoprostol 200 mcg & Cytotec 400 mg )

description: Apa Itu Misoprostol? Obat Aborsi Cytotec, Kegunaan, Dosis & Cara Kerja serta Efek Sampingnya

seputar informasi tentang aborsi 085377157715 anda semua bisa menggakses melalui situs kami untuk mendapatkan obat cytotec misoprostol FDA USA original alodokter.weebly.com alasan perempuan melakukan aborsi

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DOI: 10.17632/tt3tnrs3rz.1
title: Data for Tax Threshold

description: The dataset captures different aspects of taxation in sub-Saharan African countries.
DOI: 10.17632/89g9r6w2sz.1
title: 8. Packed-Bed Methanation Reactor in CHEMCAD Linked to Mathematica.

description: The Sabatier reaction is receiving renewed attention because of the promising concept of large-scale recycling of carbon dioxide in power plants.[1] The reaction, also known as CO₂ methanation, can be written for the methanation of CO₂ with hydrogen, as:

CO₂(g) + 4 H₂(g) ⇌ CH₄(g) + 2 H₂O(g)

The reaction is exothermic and reversible, and is catalyzed by supported metals such as nickel on magnesia.[10] The supported metal catalysts can be configured into a packed bed. The reaction can also be accomplished in fluidized-bed or biological reactors, but those are not considered here. In this study, we consider supported-nickel catalyst pellets poured into pipes in a shell-and-tube configuration. 

Various commercial applications can be studied by incorporation of the reactor design equations into process simulator software, but this software does not generally contain built-in packed bed reactors. This type of reactor needs to be added by the user. CHEMCAD is one commonly used chemical process simulator and we have shown previously that it can be used in tandem with Mathematica for real-time solutions of advanced mathematical problems.[2-8] Our previous work showed application to algebraic solutions. That is, the membrane and flash models in those studies involved solutions of systems of algebraic equations. This study extends the method to systems of differential equations solved numerically. Specifically, this paper demonstrates the simultaneous solution of the two equations dP/dW=F₁ and dX/dW=F₂, where X is conversion of CO₂, P is pressure in the reactor, and W is catalyst mass[9], in Mathematica coupled to CHEMCAD. Kinetic models used are gas-phase with simultaneous adsorption-desorption on the solid catalyst, with kinetic rate laws and thermochemical properties taken from the literature [10,11].
DOI: 10.17632/45f952y38r.3
title: KU-HAR: An Open Dataset for Human Activity Recognition

description: Human Activity Recognition (HAR) refers to the capacity of machines to perceive human actions. This dataset contains information on 18 different activities collected from 90 participants (75 male and 15 female) using smartphone sensors (Accelerometer and Gyroscope). It has 1945 raw activity samples collected directly from the participants, and 9185 subsamples extracted from them. The activities are: Stand➞ Standing still (1 min) Sit➞ Sitting still (1 min) Talk-sit➞ Talking with hand movements while sitting (1 min) Talk-stand➞ Talking with hand movements while standing or walking(1 min) Stand-sit➞ Repeatedly standing up and sitting down (5 times) Lay➞ Laying still (1 min) Lay-stand➞ Repeatedly standing up and laying down (5 times) Pick➞ Picking up an object from the floor (10 times) Jump➞ Jumping repeatedly (10 times) Push-up➞ Performing full push-ups (5 times) Sit-up➞ Performing sit-ups (5 times) Walk➞ Walking 20 meters (≈12 s) Walk-backward➞ Walking backward for 20 meters (≈20 s) Walk-circle➞ Walking along a circular path (≈ 20 s) Run➞ Running 20 meters (≈7 s) Stair-up➞ Ascending on a set of stairs (≈1 min) Stair-down➞ Descending from a set of stairs (≈50 s) Table-tennis➞ Playing table tennis (1 min) Contents of the attached .zip files are: 1.Raw_time_domian_data.zip➞ Originally collected 1945 time-domain samples in separate .csv files. The arrangement of information in each .csv file is: Column 1, 5➞ exact time (elapsed since the start) when the Accelerometer & Gyro output was recorded (in ms) Col. 2, 3, 4➞ Acceleration along X,Y,Z axes (in m/s^2) Col. 6, 7, 8➞ Rate of rotation around X,Y,Z axes (in rad/s) 2.Trimmed_raw_data.zip➞ Samples of the previous file after certain parts of the signals that contained no information on the corresponding activity were trimmed. 3.Time_domain_subsamples.zip➞ 9185 subsamples extracted from the 1945 collected samples in a single .csv file. Arrangement of information: Col. 1–1500, 1501–3000, 3001–4500➞ Acc.meter X, Y, Z axes readings Col. 4501–6000, 6001–7500, 7501–9000➞ Gyro X, Y, Z axes readings Col. 9001➞ Class ID (0 to 17, in the order mentioned above) Col. 9002➞ length of the subsample (each signal begins from the starting column and runs its course, the remaining columns are padded with zeros) Col. 9003➞ serial no. of the subsample 4.Frequency_features.zip➞ The 1500-point DFT output of each signal of 9185 subsamples in a single .csv file. The arrangement of information is the same as above. Samples were collected at 100 Hz, gravity acceleration was omitted from the Acc.meter data, and no filter was applied to remove noise. The dataset is free to download, modify, and use. More information is provided in the data paper which is currently submitted: N. Sikder, A.-A. Nahid, KU-HAR: An open dataset for heterogeneous human activity recognition, Pattern Recognit. Lett. (submitted). A preprint will be available soon. Backup: drive(dot)google.com/drive/folders/1cS29tHwlu9MGM9OYq8ApInz0eDnuyPFs