cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/ngtpyv4zws.2
title: Maternal Health Service Coverage in India

description: Accessibility and availability of quality and essential health services and utilization of these services by a large proportion of the population amount towards the health service coverage in a country. Health service coverage in the area of maternal and child health is imperative from the development perspectives of the country. So that, India brings about a number of policies and schemes to increase the coverage of health services under the umbrella of Reproductive, Maternal, Newborn, Child Health (RMNCH). Maternal health is a prominent area of research concern about the health of a woman during the period of pregnancy, childbirth, and post-partum. Against this backdrop, the authors presented a dataset regarding the maternal health service coverage in India at the sub-national level for the three financial years from 2017 to 2020.
Based on the time in which the care has to be provided, the maternal health care services are categorized into three namely Antenatal/ prenatal care, intranatal/ intrapartum care, and postnatal/postpartum care. Antenatal care (ANC) refers to the systemic care and supervision recommended for women during their pregnancy while intranatal care is the systemic care during labour and delivery. Care providing after delivery conventionally for the first 42 days (6 weeks) is known as post-natal/post-partum care. 
The authors extracted data from the Health Management Information System (HMIS) portal, an initiative under the National Health Mission (NHM) by the Government of India. Followed by the extraction, the authors identified and shortlisted health indicators of maternal health service coverage in India at the sub-national level. HMIS is a web-based routine monitoring system of the vital Reproductive Maternal Newborn Child Health (RMNCH) data uploaded by the States and Union territories in India. 
The data for health indicators for the maternal health service coverage were identified and shortlisted based on the expert opinion and review of the literature. The study considered only those indicators for which the data is available in relative measure (in percentage). The selected Indicators are further classified under the domains of Antenatal care coverage (ANC), Intranatal Care Coverage (INC) and Postnatal Care coverage (PNC) based on various guidelines by the reputed national and international organizations. Furthermore, the authors classified the indicators under the domain of ANC into three sub-domains namely ANC registration & check-us, Supplementation & prophylaxis in pregnancy, and essential screening. The obtained data on the selected indicators were randomly chosen and rechecked for the errors in the data entry.
DOI: 10.17632/d3d4h5bvss.1
title: Physical disorder of streets in 264 Chinese cities (2015)

description: These compressed files contain data and Python code to replicate the paper “Measuring physical disorder in urban street spaces: A large-scale analysis using street view images and deep learning”. The data arise from a large-scale analysis of physical disorder in 264 major cities in China. The purpose is to use street view images and deep learning model to estimate the physical disorder score of each sampling point, street and city. 

MobileNetV3 code:
This is a PyTorch implementation of MobileNetV3 architecture as described in the paper. The trained models are also included in the code for prediction. Please see “README.md” for detailed procedures.

Training samples:
The image samples used to train the 15 physical disorder factors are included and can be used to train other machine learning models.

Virtual audit tool:
This tool is used to label images in a given directory, developed with a single Python script with GUI. Labeled images can be moved or copied into sub-directories, that are named with the assigned labels. Please see “README.md” for detailed procedures.

Physical disorder results:
The folder contains the results of the estimation of multi-scale physical disorder. The three shapefiles “china_cities.shp”, “china_streets.shp”, and “china_svipoints.shp” record physical disorder scores for 264 cities, 769,407 streets and 1,219,238 sampling points, respectively. The attributes of the data are explained below and detailed in “Metadata.doc”:

1.	china cities.shp
The attributes of this shapefile include: unique id of each city (ID), Chinese name of 264 cities (name), English name of 264 cities (nameEng), spatial distribution pattern of street physical disorder (mode), including: (a) scattered; (b) diffused along the urban expansion direction; (c) linear concentrated along arterial roads, and physical disorder value of each city (pdvalue), physical disorder value for each factor at each city (Field names are acronyms for factor names, e.g. "AB" is an acronym for abandoned buildings). See "Metadata.doc" for a cross-reference to factor names and their acronyms.

2.	china_streets.shp
The attributes of this shapefile include: unique id of each street (street_id), Chinese name of 264 cities (name), English name of 264 cities (nameEng), physical disorder value of each street (pdvalue), and physical disorder value for each factor at each street (Field names are acronyms for factor names, e.g. "AB" is an acronym for abandoned buildings). See "Metadata.doc" for a cross-reference to factor names and their acronyms.

3.	china_svipoints.shp
The attributes of this shapefile include: unique id of each sampling point (point_id), unique id of the street where it is located (street_id), physical disorder value of each point (pdvalue) and physical disorder value for each factor at each point (Field names are acronyms for factor names, e.g. "AB" is an acronym for abandoned buildings). See "Metadata.doc" for a cross-reference to factor names and their acronyms.
DOI: 10.17632/htkw5cnh2n.1
title: SV2A NEW dataset

description: The data are divided into three parts: (1) the first EXCEL table includes the clinical and demographic features of healthy controls (n=102), aMCI (n=91), AD (n=164), VaD (n=43), PDD (n=30) patients, and the serum results of indicators, and (2) the second EXCEL table includes the clinical and demographic of control (n=35), aMCI (n=14), AD (n=46), VaD (n=13), and PDD (n=13) patients,and the CSF results of indicators (3) The third EXCEL table includes the clinical and demographic features of cognitively normal APOE ε4 carriers (n=55) and non-carriers (n=60), and the serum results of indicators.
DOI: 10.17632/k6kcgz3ctb.1
title: Tracing subducted carbonates in the mantle using zinc and molybdenum isotopes

description: Data for Tracing subducted carbonates in the mantle using zinc and molybdenum isotopes
DOI: 10.17632/k6kcgz3ctb.2
title: Tracing subducted carbonates in Earth's mantle using zinc and molybdenum isotopes

description: Data for Tracing subducted carbonates in the mantle using zinc and molybdenum isotopes
DOI: 10.17632/k6kcgz3ctb.3
title: Tracing subducted carbonates in Earth's mantle using zinc and molybdenum isotopes

description: Data for Tracing subducted carbonates in Earth's mantle using zinc and molybdenum isotopes
DOI: 10.17632/k6kcgz3ctb.4
title: Tracing subducted carbonates in Earth's mantle using zinc and molybdenum isotopes

description: Data for Tracing subducted carbonates in Earth's mantle using zinc and molybdenum isotopes
DOI: 10.17632/spgf32p2gk.1
title: Melanoma Awareness in Jamaican Patients at the University Hospital of the West Indies: A Cross-Sectional Study [Knowledge Score Calculation]

description: Supplemental Table 1 Knowledge Score: Meaningful knowledge assigned to participants with a score ≥ 4.5: the minimum equivalent of a non-0 score in each category
*MK, meaningful knowledge
DOI: 10.17632/szwcwkhr9h.1
title: A 3D-Printable smartphone accessory for plant leaf chlorophyll measurement

description: Plant health and nutrition are universally inferred from leaf chlorophyll content. This research developed a 3D-printed accessory which attaches to a smartphone and estimates the concentration of chlorophyll in the leaves of six plant species. It unveils the 3D printing files and assembling details to allow the accessory to be built anywhere. The system uses a smartphone's ambient light sensor to measure the transmission of a 663 nm LED band through intact plant leaves. This band of light is absorbed by chlorophyll and allows its concentration to be measured. Absolute values of chlorophyll content are obtained by calibration against standard spectrophotometer measurements. This accessory is tested by comparing its readings to the universal spectrophotometric method and compared to a standard SPAD 502™ portable meter. This smartphone-connected system that has a 3D-printed body, lighting circuit, and common spare parts, measures chlorophyll in a way comparable to universally used standard systems. Due to the well-studied relationship between chlorophyll concentration and nutritional status of plants, and due to the ubiquitous presence of other sensors in smartphones today, the improvement and adoption of this smartphone accessory would ease the spread of precision farming and digital agronomy practices throughout the different scales of agriculture.
DOI: 10.17632/t436wdx87h.1
title: Figure BD

description: Figure of map study big data
DOI: 10.17632/7dxmwwnfb3.1
title: Table Big Data - CSE

description: List of research of Big data
DOI: 10.17632/43cd6wt97r.1
title: Ulna Length Predicts Height Measured by Stadiometer Among Adults in Ghana

description: The attached dataset (N = 402) consists of anthropometric and demographic information meant to evaluate the degree of agreement between the height estimated from the ulna length measurement and the height measured with a stadiometer.
DOI: 10.17632/mv9xf2jk84.1
title: Fritilaria karelinii (experimental data)

description: Uploaded experimental data for antioxidant activity  (FC, FRAP, DPPH) and figures rbcl, ITS phylogeny, field collection data map
DOI: 10.17632/mv9xf2jk84.2
title: Fritilaria karelinii (experimental data)

description: Uploaded experimental data for antioxidant activity (standard curves for FC, FRAP, DPPH methods) and figures of rbcl, ITS phylogeny, field collection data map
DOI: 10.17632/v7kkwgnyn5.1
title: Yamaguchi, Hatori et al., 2024

description: Numerical dataset for Yamaguchi, Hatori et al., 2024.
DOI: 10.17632/f4ky6ks248.1
title: Sen-2 LULC 

description: The "Sen-2 LULC Dataset" is a collection of 2,13,750+ pre-processed 10 m resolution images representing 7 distinct classes of Land Use Land Cover. The 7 classes are water, Dense forest, Sparse forest, Barren land, Built up, Agriculture land and Fallow land. Multiple classes are present in the  single image of the dataset. The Sentinel-2 images of Central India are taken from USGS (United States Geological Survey) EXPLORER  (https://earthexplorer.usgs.gov/) with cloud clover percentage ranging from 0 to 0.5. The images are combination of bands 3, 4 and 5 constituting the red, green and blue bands with spectral resolution of 10m. The images are taken within the months of March and April 2022. The images used in the dataset belongs to Sentinel-2 Level-2A product (https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-2-msi/product-types/level-2a#:~:text=The%20Level%2D2A%20product%20provides,(UTM%2FWGS84%20projection).). The dataset contains equal number of mask images. The dataset contains 6 folders with train, test and validate images and train, test and validate masks. This dataset can be used for Land Use Land Cover Classification (LULC) of Indian region to build the deep learning models. This dataset is beneficial for LULC classification research.
DOI: 10.17632/f4ky6ks248.2
title: Sen-2 LULC 

description: The "Sen-2 LULC Dataset" is a collection of 2,13,750+ pre-processed 10 m resolution images representing 7 distinct classes of Land Use Land Cover. The 7 classes are water, Dense forest, Sparse forest, Barren land, Built up, Agriculture land and Fallow land. Multiple classes are present in the  single image of the dataset. The Sentinel-2 images of Central India are taken from Copernicus Open Access Hub  (https://scihub.copernicus.eu/) with cloud clover percentage ranging from 0 to 0.5%. The images are combination of bands B4, B3 and B2 constituting the red, green and blue bands with spectral resolution of 10m. The images are taken within the months of February and March 2021. The images used in the dataset belongs to Sentinel-2 Level-2A product (https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-2-msi/product-types/level-2a#:~:text=The%20Level%2D2A%20product%20provides,(UTM%2FWGS84%20projection).). The dataset contains equal number of mask images. The dataset contains 6 folders with train, test and validate images and train, test and validate masks. This dataset can be used for Land Use Land Cover Classification (LULC) of Indian region to build the deep learning models. This dataset is beneficial for LULC classification research.
DOI: 10.17632/r6995krm6v.1
title: Marine geological data from the Roman Rock area in False Bay, South Africa

description: A 12 km2 area off Simon's Town in NW False Bay, South Africa, was surveyed using side-scan sonar and a single-beam echosounder, revealing six distinct patterns of acoustic reflectivity:

Facies 1 -- Outcrops of Cape Peninsula Granite characterized by irregular blocky patterns.
Facies 2 -- Stationary, long-crested wave ripples, oriented WSW-ENE.
Facies 3 -- Patchy veneer of calcareous sediment overlying quartzose sand.
Facies 4 -- Larger 'Cloud-like' and 'tongue-like' windows in the veneer of calcareous sediment revealing underlying rippled sand.
Facies 5 -- Rippled fine-grained quartzose sand in the deeper eastern area.
Facies 6 -- Medium-gray patches within Facies 5, possibly indicating weathered granite or calcareous sediment.

The Facies were ground-truthed using sediment sample data and diver observations. The sub-tidal environment is predominantly calm, with occasional high-energy conditions due to southeasterly gales influencing sediment movement. Analysis of sediment samples shows that the calcareous and quartzose sediments mix according to the Folk & Ward (1957) sediment-mixing model. Quartzose sands probably originate from Late Pleistocene regressive dunes reworked during the Holocene transgression. Modern calcareous sediments originate from carbonate-secreting organisms either attached to granite outcrops or unattached on the seafloor surface.

This repository contains spatial and sedimentological data from the survey and contextual data from other sources.
DOI: 10.17632/gfpfs4svg6.1
title: Protein Repeats Show Clade-Specific Volatility in Aves

description: Protein repeats are a source of rapid evolutionary and functional novelty. Repeats are crucial in development, neurogenesis, immunity, and disease. Repeat length variability and purity can alter the outcome of a pathway by altering the protein structure and affecting the protein−protein interaction affinity. Such rampant alterations can facilitate species to rapidly adapt to new environments or acquire various mor-phological/physiological features. With more than 11000 species, the avian clade is one of the most speciose vertebrate clades, with near-ubiquitous distribution globally. Explosive adaptive radiation and functional diversification facilitated the birds to occupy various habitats. High diversity in morphology, physiology, flight pattern, behavior, coloration, and life histories make birds ideal for studying protein repeats' role in evolutionary novelty. Our results demonstrate a similar repeat diversity and proportion of repeats across all the avian orders considered, implying an essential role of repeats in necessary pathways. We detected positively selected sites (PSS) in the polyQ repeat of RUNX2 in the avian clade; and considerable repeat length contraction in the Psittacopasserae. The repeats show a species-wide bias towards a contraction in Gal-loanseriformes. Interestingly, we detected the length contrast of polyS repeat in PCDH20 between Galli-formes and Anseriformes. We speculate the length variability of serine repeat and its interaction with β-cat-enin in the Wnt/β-catenin signaling pathway could have facilitated fowls to adapt to their respective environmental conditions. We believe our study emphasizes the role of protein repeats in functional/morphological diversification in birds. We also provide an extensive list of genes with considerable repeat length contrast to further explore the role of length volatility in evolutionary novelty and rapid functional diversification.
DOI: 10.6084/m9.figshare.24543736.v1
title: An innovative lightweight 1D-CNN model for efficient monitoring of large-scale forest composition: a case study of Heilongjiang Province, China

description: Large-scale forest composition mapping and change monitoring are essential for regional and national forest resource management, monitoring, and carbon stock assessment. However, the existing large-scale mapping methods are not effective enough in terms of efficiency and accuracy. To address this limitation, this study proposes a lightweight one-dimensional convolutional neural network (LW-CNN) model for forest composition mapping. The LW-CNN model is developed using Landsat imagery covering 470,700 km<sup>2</sup> obtained from Google Earth Engine (GEE) collected during two periods (2007 and 2018). The proposed LW-CNN is compared with a visual geometry group with 16 convolutional layers (VGG16), a residual network with 34 convolutional layers (Resnet34), and a residual network with 50 convolutional layers (Resnet50) in terms of model accuracy and efficiency. The factors influencing forest composition change are analyzed using the structural equation model (SEM). The results show that the proposed LW-CNN model can outperform the other three models in terms of model accuracy, achieving a mean overall accuracy (OA) of: 0.75 and efficiency of 7–22-fold. The changed forest composition from 2007 to 2018 accounts for 29.6% of the total forest area. The SEM results show that the climate factors have the most significant effect on the forest composition change. This study presents an innovative model for large-scale forest composition mapping, which is proven to be both efficient and accurate. This study also provides insights into the factors that affect the forest composition change, which could be valuable for forest resource management, monitoring, and carbon stock assessment.
DOI: 10.6084/m9.figshare.24543736
title: An innovative lightweight 1D-CNN model for efficient monitoring of large-scale forest composition: a case study of Heilongjiang Province, China

description: Large-scale forest composition mapping and change monitoring are essential for regional and national forest resource management, monitoring, and carbon stock assessment. However, the existing large-scale mapping methods are not effective enough in terms of efficiency and accuracy. To address this limitation, this study proposes a lightweight one-dimensional convolutional neural network (LW-CNN) model for forest composition mapping. The LW-CNN model is developed using Landsat imagery covering 470,700 km<sup>2</sup> obtained from Google Earth Engine (GEE) collected during two periods (2007 and 2018). The proposed LW-CNN is compared with a visual geometry group with 16 convolutional layers (VGG16), a residual network with 34 convolutional layers (Resnet34), and a residual network with 50 convolutional layers (Resnet50) in terms of model accuracy and efficiency. The factors influencing forest composition change are analyzed using the structural equation model (SEM). The results show that the proposed LW-CNN model can outperform the other three models in terms of model accuracy, achieving a mean overall accuracy (OA) of: 0.75 and efficiency of 7–22-fold. The changed forest composition from 2007 to 2018 accounts for 29.6% of the total forest area. The SEM results show that the climate factors have the most significant effect on the forest composition change. This study presents an innovative model for large-scale forest composition mapping, which is proven to be both efficient and accurate. This study also provides insights into the factors that affect the forest composition change, which could be valuable for forest resource management, monitoring, and carbon stock assessment.
DOI: 10.57693/zqr2zf/8rfqtf
title: 05_ETIEP_Data_EN_v1.0.tab

description: :unav
DOI: 10.57693/zqr2zf/bkv4yx
title: 05_ETIEP_Doc_Questionnaire_EN.pdf

description: :unav
DOI: 10.57693/zqr2zf
title: Ethnic Tensions, Institutional and Economic Performance in Bosnia and Herzegovina: What are (not) the Causal Links?

description: In the research the authors investigate the relationship between ethnic tensions, institutional and economic performance in Bosnia and Herzegovina (BiH), including a qualitative analysis of this issue for BiH and Macedonia. The research is conducted by a mixed methods approach, in which questionnaire surveys of the household and business sectors in BiH are supplemented by semi-structured interviews. We find that the both individual economic performance and individual ethnic tolerance in BiH are affected by the most important factors, such as: employment status, education and age; they both singly and in combination move individuals in BiH towards greater probability of being both prosperous and tolerant. The similar conclusions are supported by the qualitative analysis based on interviews conducted in BiH and Macedonia - the most important factors affecting ethnic tensions include: employment, education, and neighborhood. Finally, the empirical findings from the business survey in BiH suggest that the export performance of firms located in these communities are adversely affected by the ethnic tensions inherent in company's culture, formal institutions and firm's environment.
DOI: 10.17632/bs8w7h8m7p.1
title: Analisis Yuridis Keabsahan Perjanjian E-Commerce PT Tokopedia dalam Konteks Kepatuhan Terhadap Pasal 1320 KUHPerdata Tentang Syarat Sah Perjanjian

description: Pada zaman sekarang Kegiatan jual beli melalui internet ini dikenal dengan nama electronic commerce atau e commerce sangat menguasai pasar hampir 80 %. Hampir semua Penjualan barang dan jasa dipasarkan lewat online, e commerce sendiri mempunyai kelebihan dan kekurangan. Kelebihan dari e commerce yaitu dapat melakukan transaksi jual beli ke berbagai wilayah di Indonesia bahkan sampai ke luar negeri. Selain itu kekurangan e commerce sendiri yaitu tidak bertemunya penjual dan pembeli sehingga rawan terjadi penipuan. E commerce sama dengan perjanjian konvensional yang keabsahannya diatur didalam pasal 1320 KUH Perdata. Dimana ada empat (4) syarat sahnya perjanjian yaitu kesepakatan, kecakapan, obyek tertentu dan sebab yang halal. Kecakapan menjadi hal yang dipertanyakan karena pada saat transaksi terjadi para pihak tidak bertemu dan hanya melalui aplikasi. untuk kecakapan jg tidak bisa dipastikan sebab pihak yg membeli kadang anak yg berumur dibawah 18 tahun. Keabsahan perjanjian elektronik, pada prinsipnya keabsahan suatu perjanjian tidak ditentukan oleh bentuk fisik dari perjanjian tersebut. Baik cetak maupun elektronik, baik lisan maupun tulisan, akan dianggap sah menurut hukum jika memenuhi syarat Pasal 1320 KUH Perdata.
DOI: 10.17632/s4pj4gwthj.1
title: Replication Code/Pseudo Data for: "Collateral Eligibility of Corporate Debt in the Eurosystem"

description: The files contain replication codes and pseudo data for generating the tables and figures in the paper "Collateral Eligibility of Corporate Debt in the Eurosystem", by Loriana Pelizzon, Max Riedel, Zorka Simon, and Marti G. Subrahmanyam, Journal of Financial Economics, Forthcoming.
DOI: 10.17632/s4pj4gwthj.2
title: Replication Code/Pseudo Data for: "Collateral Eligibility of Corporate Debt in the Eurosystem"

description: The files contain replication codes and pseudo data for generating the tables and figures in the paper "Collateral Eligibility of Corporate Debt in the Eurosystem", by Loriana Pelizzon, Max Riedel, Zorka Simon, and Marti G. Subrahmanyam, Journal of Financial Economics, Forthcoming.