cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/nkxjhw8dbc.1
title: The Role of Organizational Justice in Predicting Job Satisfaction and Turnover Intention: Evidence from Indonesian Banks

description: Purpose: This study examines the connection between organizational justice, job satisfaction, and turnover intention in the Indonesian banking sector and emphasizes the impact of flexible work arrangements (FWAs).
Design/methodology/approach: This study is using a quantitative cross-sectional design, this research applies Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze survey data from 204 respondents in the Jabodetabek area. The study is grounded in Social Exchange Theory (SET) to examine how distributive, procedural, and interactional justice affect job satisfaction and turnover intentions.
Findings: The findings of this study indicate that higher levels of perceived organizational justice are associated with greater job satisfaction, which subsequently leads to lower turnover intention. However, flexible work arrangements did not significantly influence the relationship between job satisfaction and turnover intention. 
Research limitations/implications: This study is confined to the Indonesian banking sector, which limits its applicability to other industries or regions. Unfortunately, to successfully retain talent, organizations should emphasize the establishment of a fair and just work environment. Considering the changes in work environments due to the pandemic and the growing demand for flexibility, organizations must be prepared to adapt to new work models.
Originality/value: This study is the first to examine the moderating effect of flexible work arrangements (FWAs) in the Indonesian banking context.
Keywords: organizational justice, job satisfaction, turnover intention, Flexible Work Arrangements (FWAs), banking sector
DOI: 10.17632/d9g2242swc.1
title: Privacy in IoV

description: This dataset is associated with the journal article Privacy Concerns in the Disclosure of IoV Personal Driving Data
DOI: 10.17632/ff4bxnxp8j
title: The Role of Organizational Justice in Predicting Job Satisfaction and Turnover Intention: Evidence from Indonesian Banks

description: Purpose: This study examines the connection between organizational justice, job satisfaction, and turnover intention in the Indonesian banking sector and emphasizes the impact of flexible work arrangements (FWAs).
Design/methodology/approach: This study is using a quantitative cross-sectional design, this research applies Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze survey data from 204 respondents in the Jabodetabek area. The study is grounded in Social Exchange Theory (SET) to examine how distributive, procedural, and interactional justice affect job satisfaction and turnover intentions.
Findings: The findings of this study indicate that higher levels of perceived organizational justice are associated with greater job satisfaction, which subsequently leads to lower turnover intention. However, flexible work arrangements did not significantly influence the relationship between job satisfaction and turnover intention. 
Research limitations/implications: This study is confined to the Indonesian banking sector, which limits its applicability to other industries or regions. Unfortunately, to successfully retain talent, organizations should emphasize the establishment of a fair and just work environment. Considering the changes in work environments due to the pandemic and the growing demand for flexibility, organizations must be prepared to adapt to new work models.
Originality/value: This study is the first to examine the moderating effect of flexible work arrangements (FWAs) in the Indonesian banking context.
Keywords: organizational justice, job satisfaction, turnover intention, Flexible Work Arrangements (FWAs), banking sector
DOI: 10.17632/ff4bxnxp8j.1
title: The Role of Organizational Justice in Predicting Job Satisfaction and Turnover Intention: Evidence from Indonesian Banks

description: Purpose: This study examines the connection between organizational justice, job satisfaction, and turnover intention in the Indonesian banking sector and emphasizes the impact of flexible work arrangements (FWAs).
Design/methodology/approach: This study is using a quantitative cross-sectional design, this research applies Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze survey data from 204 respondents in the Jabodetabek area. The study is grounded in Social Exchange Theory (SET) to examine how distributive, procedural, and interactional justice affect job satisfaction and turnover intentions.
Findings: The findings of this study indicate that higher levels of perceived organizational justice are associated with greater job satisfaction, which subsequently leads to lower turnover intention. However, flexible work arrangements did not significantly influence the relationship between job satisfaction and turnover intention. 
Research limitations/implications: This study is confined to the Indonesian banking sector, which limits its applicability to other industries or regions. Unfortunately, to successfully retain talent, organizations should emphasize the establishment of a fair and just work environment. Considering the changes in work environments due to the pandemic and the growing demand for flexibility, organizations must be prepared to adapt to new work models.
Originality/value: This study is the first to examine the moderating effect of flexible work arrangements (FWAs) in the Indonesian banking context.
Keywords: organizational justice, job satisfaction, turnover intention, Flexible Work Arrangements (FWAs), banking sector
DOI: 10.21233/a8b8-ng61
title: Tannersville Bog testate amoebae surface sample dataset

description: Raw data for the Tannersville Bog testate amoebae surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/t1mm-8g73
title: Gorno-Slinkino village 2 testate amoebae surface sample dataset

description: Raw data for the Gorno-Slinkino village 2 testate amoebae surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.17632/9ry6mj4dw8
title: UNORGANIZED-LIDAR POINT CLOUD-DATASET

description: Pavement planar coefficients are critical for a wide range of civil engineering applications, including 3D city modeling, extraction of pavement design parameters, and assessment of pavement conditions. Existing plane fitting methods, however, often struggle to maintain accuracy and stability in complex road environments, particularly when the point cloud is affected by non-pavement objects such as trees, curbstones, pedestrians, and vehicles.

REoPC is proposed as a robust two-stage estimation method based on road point clouds acquired using a hybrid solid-state LiDAR. The method consists of two main parts: coarse estimation and refined estimation. The first stage employs a dual-plane sliding window to remove major outliers and extract an initial surface. The second stage introduces a new cost function based on the Geman-McClure estimator to further suppress residual noise and reduce fitting instability caused by outlier influence and algorithmic randomness.

Evaluation is conducted on both synthetic and real-world datasets collected using a custom mobile LiDAR scanning system across three urban road scenarios—flat, crowned, and traffic-interfered segments. Each scenario includes 100 frames of road point clouds, with approximately 35,000 points per frame, offering a diverse and challenging benchmark. REoPC consistently outperforms existing methods in terms of accuracy and robustness and exhibits low sensitivity to parameter tuning, demonstrating strong applicability in varied real-world conditions.
DOI: 10.17632/9ry6mj4dw8.1
title: UNORGANIZED-LIDAR POINT CLOUD-DATASET

description: Pavement planar coefficients are critical for a wide range of civil engineering applications, including 3D city modeling, extraction of pavement design parameters, and assessment of pavement conditions. Existing plane fitting methods, however, often struggle to maintain accuracy and stability in complex road environments, particularly when the point cloud is affected by non-pavement objects such as trees, curbstones, pedestrians, and vehicles.

REoPC is proposed as a robust two-stage estimation method based on road point clouds acquired using a hybrid solid-state LiDAR. The method consists of two main parts: coarse estimation and refined estimation. The first stage employs a dual-plane sliding window to remove major outliers and extract an initial surface. The second stage introduces a new cost function based on the Geman-McClure estimator to further suppress residual noise and reduce fitting instability caused by outlier influence and algorithmic randomness.

Evaluation is conducted on both synthetic and real-world datasets collected using a custom mobile LiDAR scanning system across three urban road scenarios—flat, crowned, and traffic-interfered segments. Each scenario includes 100 frames of road point clouds, with approximately 35,000 points per frame, offering a diverse and challenging benchmark. REoPC consistently outperforms existing methods in terms of accuracy and robustness and exhibits low sensitivity to parameter tuning, demonstrating strong applicability in varied real-world conditions.
DOI: 10.17632/znvw6hr4px.1
title: The Role of Organizational Justice in Predicting Job Satisfaction and Turnover Intention: Evidence from Indonesian Banks

description: The data supporting this study were collected from a survey of 204 respondents and comprise six variables: procedural justice, interactional justice, distributive justice, job satisfaction, turnover intention, and flexible work arrangements (FWAs) to support this research: "The Role of Organizational Justice in Predicting Job Satisfaction and Turnover Intention: Evidence from Indonesian Banks".
DOI: 10.21233/ky0g-qy20
title: KNGC14 pollen surface sample dataset

description: Raw data for the KNGC14 pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/vf5h-b912
title: Roy Lake diatom surface sample dataset

description: Raw data for the Roy Lake diatom surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.17632/kgdr3jhyfx.1
title: Dupilumab and Lichen Planus

description: The purpose of this systematic review was to assess the potential of dupilumab as a treatment for recalcitrant LP and to explore the clinical characteristics of dupilumab-induced LP.
DOI: 10.17632/m9g8xcwdb4.1
title: Data for: Evaluating fluvial source-sink system change in a context of millennial-scale climate change from Tarim River Basin to Lop Nur Salt Lake:

description: Carbon content of Lop Nur Salt Lake
DOI: 10.17632/6v9h6gjh8f
title: Evaluation of H 2 O 2 electrogeneration and tebuthiuron degradation by photo-electro-Fenton from a carbon-based gas diffusion electrode modified with Zn-zeolitic imidazolate framework
DOI: 10.17632/6v9h6gjh8f.1
title: Evaluation of H 2 O 2 electrogeneration and tebuthiuron degradation by photo-electro-Fenton from a carbon-based gas diffusion electrode modified with Zn-zeolitic imidazolate framework
DOI: 10.21233/jjd2-wc58
title: Shabotik River water chemistry dataset

description: Raw data for the Shabotik River water chemistry dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.17632/zgph46p46f.1
title: Good and Bad Classification of Chickpea(Cicer arietinum L)

description: Use of biotechnology and precision agriculture

Promoting chickpea consumption through awareness
DOI: 10.17632/zgph46p46f.2
title: Good and Bad Classification of Chickpea(Cicer arietinum L)

description: Title: Good and Bad Classification of Chickpea (Cicer arietinum L.)

Abstract:
Chickpea (Cicer arietinum L.) is a major legume crop valued for its high protein content and adaptability to diverse agro-climatic conditions. Classifying chickpea into good and bad categories involves evaluating several parameters, including morphological characteristics, agronomic traits, quality attributes, and resistance to biotic and abiotic stresses. This paper discusses the criteria for classifying chickpea cultivars as good or bad and presents recent advancements in breeding and selection practices.

Introduction:
Chickpea, commonly known as garbanzo bean, is one of the most important pulse crops globally. Its nutritional profile, comprising high protein, fiber, and essential minerals, makes it a staple in many diets. Despite its significance, chickpea productivity is often challenged by environmental stresses and diseases. Classifying chickpea varieties as good or bad is crucial for breeding, cultivation, and consumption purposes.

Criteria for Classification:
2.1 Morphological Characteristics:
Good chickpea cultivars typically exhibit uniform plant height, robust branching, and optimal pod setting. Bad cultivars may show irregular growth patterns, weak stems, and low pod production.

2.2 Agronomic Performance:
Yield potential, drought tolerance, and nutrient efficiency are key agronomic parameters. Good cultivars demonstrate consistent yields across variable conditions, while poor cultivars suffer from yield instability.

2.3 Quality Parameters:
Seed size, protein content, cooking quality, and market value define good quality chickpea. Poor quality chickpeas often have small, shriveled seeds, low protein, and prolonged cooking time.

2.4 Resistance to Biotic and Abiotic Stresses:
Good chickpea cultivars show resistance to diseases like Ascochyta blight and Fusarium wilt, as well as tolerance to drought and salinity. Susceptible cultivars face high crop loss and reduced market value.

Methods for Classification:

Phenotypic Evaluation

Molecular Markers

Field Trials

Genetic Mapping

Recent Advancements:

Marker-Assisted Selection (MAS)

Genomic Selection (GS)

Integrative Breeding Approaches

Conclusion:
Classifying chickpea varieties based on comprehensive criteria ensures the selection of superior cultivars for sustainable agriculture. Ongoing research in genetic improvement continues to enhance the resilience and productivity of chickpea.
DOI: 10.17632/sp2bvhmmj6.1
title: Investigating the prevalence of tobacco or other substance use (TOSU) and factors associated among the medical students: a nationwide cross-sectional survey from Bangladesh

description: Investigating the prevalence of tobacco or other substance use (TOSU) and factors associated among the medical students: a nationwide cross-sectional survey from Bangladesh
DOI: 10.21233/ykmf-w360
title: Mile 94, Granite Rapids pollen surface sample dataset

description: Raw data for the Mile 94, Granite Rapids pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/5r86-ft63
title: Esche stroom pollen dataset

description: Raw data for the Esche stroom pollen dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/1p3d-5b64
title: Hubbs Creek ostracode surface sample dataset

description: Raw data for the Hubbs Creek ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/x34k-x198
title: Cookson [34CK12] macroinvertebrate dataset

description: Raw data for the Cookson [34CK12] macroinvertebrate dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/7a4k-g412
title: ALASK 21 pollen surface sample dataset

description: Raw data for the ALASK 21 pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.15468/dl.enzats
title: Occurrence Download

description: A dataset containing 133 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-99 18,-81.5 18,-81.5 31,-99 31,-99 18))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ulva Linnaeus, 1753",
 "Year 2010-2020"
 ]
}

 The dataset includes 133 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022326-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21233/1yw3-ng78
title: Dry Creek Reservoir water chemistry dataset

description: Raw data for the Dry Creek Reservoir water chemistry dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/ac6s-kn52
title: Tannersville Bog testate amoebae surface sample dataset

description: Raw data for the Tannersville Bog testate amoebae surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/sje6-6x15
title: B9416 pollen surface sample dataset

description: Raw data for the B9416 pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/hh19-a634
title: LDDsite2380 ostracode surface sample dataset

description: Raw data for the LDDsite2380 ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/pwdq-2w15
title: OXBO401 pollen surface sample dataset

description: Raw data for the OXBO401 pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/xkcx-j942
title: Chief Joseph Dam Site 45OK2 vertebrate fauna dataset

description: Raw data for the Chief Joseph Dam Site 45OK2 vertebrate fauna dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/ashc-9r74
title: LDDsite10 ostracode surface sample dataset

description: Raw data for the LDDsite10 ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/g99x-qw27
title: Palmer Meadows Lake diatom surface sample dataset

description: Raw data for the Palmer Meadows Lake diatom surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/gq6m-c174
title: Watson Lake water chemistry dataset

description: Raw data for the Watson Lake water chemistry dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/x46y-ts77
title: Morris Reservoir diatom bottom sample dataset

description: Raw data for the Morris Reservoir diatom bottom sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/h5xm-1z90
title: Sugar Camp water chemistry dataset

description: Raw data for the Sugar Camp water chemistry dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/xnzr-dv37
title: Lenora Lake ostracode surface sample dataset

description: Raw data for the Lenora Lake ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.