cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/7tv6yscmn4.1
title: Experimental Examination of Audit Reporting Standards Data

description: We conducted an experimental investigation on the impact of a Disclosure requirement (publicly disclosing the auditors actual name) and Sign-Off requirement (requiring auditors to sign-off on the audit report) on auditor misreporting decisions. We used an experimental audit market based on the economic model in Magee and Tseng (1990). Markets were conducted via networked computers utilizing z-tree software (Fischbacher, 2007). In particular, two experimental sessions were conducted for each of the four experimental conditions and each session was conducted with two markets operating simultaneously. Consistent with prior research, participants were randomly reassigned to a different market group at the end of each market year (two trading periods) in order to help control reputational concerns among participants, and to remove market group confounds (Calegari, Schatzberg and Sevcik (1998); Schatzberg, Sevcik, Shapiro, Thorne and Wallace (2005); Blay, Gooden, Mellon and Stevens (2019a); Blay, Gooden, Mellon and Stevens (2019b).
All manipulations were administered on a between-subjects basis and all participants maintained their original randomly assigned role throughout the experiment. For a detailed description and discussion of the audit market setting, including equilibrium predictions see Blay et al. (2019b). We used the same experimental parameters as the audit markets described in Blay et al. (2019b), with three notable differences. 
First, we increased the penalty for misreporting from $0.05 to $0.25 in order for the economic penalty for misreporting to be consistent with Blay, Gooden, Mellon and Stevens (2019a). This enables us to better directly compare our results to prior research (Blay et al (2019a) and Schatzberg, Sevcik, Shapiro, Thorne and Wallace (2005)), while also allowing us to understand the interplay between economic penalties and the underlying theoretical mechanisms behind the observed reporting behavior. 
Second, we eliminated the pre-experimental quiz included in the instructions used in Blay et al. (2019b). Instead, we report the results of the Ethics Position Questionnaire (EPQ), Forsyth (1980), which can be used to measure individual differences in moral thought using its idealism and relativism scales.
Lastly, Blay et al. (2019b) presented a 3x1 between-participants experimental design in which disclosure is manipulated at three levels. In particular, Blay et al. (2019b) examined the impact no disclosure, disclosure only, and disclosure with sign-off on auditor misreporting. Instead, we utilized a 2 x 2 between-participants experimental design in which we examined following experimental conditions: No Sign-Off or Disclosure, Sign-Off Only, Disclosure Only, and Sign-Off with Disclosure. We believe that this design choice allows for a more direct comparison between the results of the two studies. In addition to the raw data from the study, the reported Excel file includes a tab with data descriptions.
DOI: 10.17632/7tv6yscmn4.2
title: Experimental Examination of Audit Reporting Standards Data

description: We conducted an experimental investigation on the impact of a Disclosure requirement (publicly disclosing the auditors actual name) and Sign-Off requirement (requiring auditors to sign-off on the audit report) on auditor misreporting decisions. We used an experimental audit market based on the economic model in Magee and Tseng (1990). Markets were conducted via networked computers utilizing z-tree software (Fischbacher, 2007) and student participants. Two experimental sessions were conducted for each of the four experimental conditions and each session was conducted with two markets operating simultaneously. Consistent with prior research, participants were randomly reassigned to a different market group at the end of each market year (two trading periods) in order to help control reputational concerns among participants, and to remove market group confounds (Calegari, Schatzberg and Sevcik (1998); Schatzberg, Sevcik, Shapiro, Thorne and Wallace (2005); Blay, Gooden, Mellon and Stevens (2019a); Blay, Gooden, Mellon and Stevens (2019b).
All manipulations were administered on a between-subjects basis and all participants maintained their original randomly assigned role throughout the experiment. For a detailed description and discussion of the audit market setting, including equilibrium predictions see Blay et al. (2019b). We used the same experimental parameters as the audit markets described in Blay et al. (2019b), with three notable differences. 
First, we increased the penalty for misreporting from $0.05 to $0.25 in order for the economic penalty for misreporting to be consistent with Blay, Gooden, Mellon and Stevens (2019a). This enables us to better directly compare our results to prior research (Blay et al (2019a) and Schatzberg, Sevcik, Shapiro, Thorne and Wallace (2005)), while also allowing us to understand the interplay between economic penalties and the underlying theoretical mechanisms behind the observed reporting behavior. 
Second, we eliminated the pre-experimental quiz included in the instructions used in Blay et al. (2019b). Instead, we report the results of the Ethics Position Questionnaire (EPQ), Forsyth (1980), which can be used to measure individual differences in moral thought using its idealism and relativism scales.
Lastly, Blay et al. (2019b) presented a 3x1 between-participants experimental design in which disclosure is manipulated at three levels. In particular, Blay et al. (2019b) examined the impact no disclosure, disclosure only, and disclosure with sign-off on auditor misreporting. Instead, we utilized a 2 x 2 between-participants experimental design in which we examined following experimental conditions: No Sign-Off or Disclosure, Sign-Off Only, Disclosure Only, and Sign-Off with Disclosure. We believe that this design choice allows for a more direct comparison between the results of the two studies. In addition to the raw data from the study, the reported Excel file includes a tab with data descriptions.
DOI: 10.5066/p953fo3i
title: Bottom dissolved oxygen measurements from Lake Erie's Central Basin, 2021

description: This data set, compiled by the USGS Lake Erie Biological Station, provides near-bottom measurements of temperature and dissolved oxygen for the Central Basin of Lake Erie. Data were recorded by self-contained environmental data loggers (PME, Inc., MiniDOT data loggers). The data loggers were deployed to collect data during mid-May 2021 through late October 2021 to better understand how hypoxia develops and influences fish habitat quality during lake stratification. The data loggers were deployed on acoustic telemetry receivers in a network designed to record tagged fish movements (Great Lakes Acoustic Telemetry Observation System, GLATOS). Additional years of data collection are planned, and data release will be updated as necessary.
DOI: 10.17632/3rtys2bzg4.1
title: Gender Perceptions and Role Attitudes of Turkish and Non-Turkish Citizen (Non-TC) Students: A Comparative Study

description: Research Description
This dataset was collected to assess the gender perceptions and gender role attitudes of Turkish and non-Turkish (Non-TC) students studying in the midwifery department of a university in Turkey. The study examines the impact of cultural differences on students' gender perceptions and attitudes towards gender roles.

Research Hypotheses:

There is a significant difference between the gender perceptions and role attitudes of Turkish students and Non-TC students.

Students raised in nuclear families have more egalitarian gender perceptions.

As class level increases, students' attitudes toward gender roles become more egalitarian.

Data Collection Process:
Data was collected through an online survey method between November 28, 2024, and February 28, 2024.
Participants were administered the “Gender Role Attitude Scale” and the “Gender Perception Scale.”
A total of 466 students participated in the study (263 Turkish citizens, 203 Non-TC students).

Noteworthy Findings:

Turkish students have more egalitarian gender perceptions and role attitudes compared to Non-TC students.

Students raised in nuclear families exhibit more favorable attitudes towards gender equality.

As class level increases, students' attitudes towards gender equality become more positive.

Interpretation and Use of Data:
This dataset can contribute to research examining the cultural influences on gender equality in higher education. The data can be used in fields such as sociology, education, gender studies, and psychology. When analyzing, the cultural context and the demographic characteristics of the participant group should be taken into account.

These data can serve as a guide for academic studies, policy-making, and the development of educational programs. Researchers utilizing these data should adhere to ethical guidelines and cite the source appropriately.
DOI: 10.17632/k7z85xf5sc
title: Basin-scale production of hyperacidic brines is critical for the formation of high-grade and large-tonnage uranium deposits in sedimentary basins

description: Including original open-source dataset of infrared hyperspectral logging data of the Athabasca Basin (Bosman and Percival, 2014; Percival et al., 2018). Use the link (https://publications.saskatchewan.ca/#/products/82130) for more information. Processed (40-m interval binning) hyperspectral logging data and compiled fluid inclusion data are incorporated within Supplementary Data.
DOI: 10.17632/k7z85xf5sc.1
title: Basin-scale production of hyperacidic brines is critical for the formation of high-grade and large-tonnage uranium deposits in sedimentary basins

description: Including original open-source dataset of infrared hyperspectral logging data of the Athabasca Basin (Bosman and Percival, 2014; Percival et al., 2018). Use the link (https://publications.saskatchewan.ca/#/products/82130) for more information. Processed (40-m interval binning) hyperspectral logging data and compiled fluid inclusion data are incorporated within Supplementary Data.
DOI: 10.5281/zenodo.15096718
title: Ben Johnston: String Quartet No. 8, 3rd movement: melodic structure of the 1st violin and list of intervals used

description: Table 1: The melody of the first violin is extremely complex and is based on that of the three “scurrying” passages in String Quartet No. 7.Table 2 lists the intervals occurring in the two violins and their frequency.
DOI: 10.5281/zenodo.15096719
title: Ben Johnston: String Quartet No. 8, 3rd movement: melodic structure of the 1st violin and list of intervals used

description: Table 1: The melody of the first violin is extremely complex and is based on that of the three “scurrying” passages in String Quartet No. 7.Table 2 lists the intervals occurring in the two violins and their frequency.
DOI: 10.17632/k37pdgw7ym.1
title: Data for More Predictive Spray/Wash Procedure

description: Supporting data for paper, J.E. Pickett, D. Yeager, O. Kuvshinnikova, More Predictive Spray/Wash Procedures for Xenon Arc Weathering, Journal of Testing and Evaluation, , in press (2025). https://doi.org/10.1520/JTE20240541
DOI: 10.15468/ke9zpe
title: The correct name for an Aquilegia (Ranunculaceae) hybrid of the parentage Aquilegia flavescens × A. formosa

description: This dataset contains the digitized treatments in Plazi based on the original journal article Cronk, Quentin C. B. (2023): The correct name for an Aquilegia (Ranunculaceae) hybrid of the parentage Aquilegia flavescens × A. formosa. PhytoKeys 220: 31-38, DOI: 10.3897/phytokeys.220.99170
DOI: 10.48579/pro/74cdkn
title: Campagne acoustique Brest Juin 2023

description: Le projet ACaPELA (ACoustique PELagique) est un projet porté par le MNHN (Station marine de Dinard) et réalisé en collaboration avec l’IRD (UMR LEMAR) et PatriNat (OFB-CNRS-MNHN). Ce projet R&D a pour objectif de développer et valider la méthodologie de surveillance DCSMM pour l’évaluation de l’état écologique des populations et peuplements de poissons et céphalopodes (PCs) des milieux pélagiques côtiers, c’est-à-dire les espèces pélagiques ou bentho-pélagiques fréquentant la colonne d’eau (le pelagos) dans les zones dont la bathymétrie est comprise entre 0 et 40 m (zones dites côtières). Les protocoles d’échantillonnages proposés consistent à combiner l’utilisation de deux technologies d’acoustiques actives complémentaires, orientées verticalement : un sondeur large bande (Simrad EK80, 70, 120 et 200 kHz) et un sonar multifaisceaux (Simrad M3, 500 kHz). Cette campagne a été réalisée dans le cadre du projet ACaPELA, en Juin 2023, à bord du bateau de station Albert Lucas. Cette campagne a permis de réaliser des radiales acoustiques en rade de Brest mais pas celles en baie de Douarnenez, pour des raisons de panne bateau. Ces enregistrements ont été complétés avec des enregistrements CTD (Conductivity-Depth-Temperature) à des points clefs identifiés au préalables.
DOI: 10.5281/zenodo.15096559
title: Ben Johnston: String Quartet No. 8, 2nd movement: Structural comparison of the prelude and postlude

description: The 2nd movement consists of a prelude, a fugue and a concluding postlude. The similarities between the prelude and postlude are so great that one can speak of an A - B - Aʹ form.
DOI: 10.5281/zenodo.15096560
title: Ben Johnston: String Quartet No. 8, 2nd movement: Structural comparison of the prelude and postlude

description: The 2nd movement consists of a prelude, a fugue and a concluding postlude. The similarities between the prelude and postlude are so great that one can speak of an A - B - Aʹ form.
DOI: 10.17632/d25ntjkwmz.1
title: Enhanced Quality of Life for Individuals in Early-stage Parkinson's Disease - A Three-month Customized Yoga Therapy Intervention.

description: Background: Parkinson's disease (PD) is a progressive neurodegeneration of happy hormone dopamine-producing neurons of the brain. This degeneration or absence of the dopamine neurons hinders the Activity of Daily Living (ADL) and Quality of Life (QoL), which results in a poor lifestyle and vice versa. The world also is confronted with so-called modern diseases, and nowadays, even minor stress can develop into a chronic neurological disorder that can affect everyday activities. The best method for boosting our entire life is to incorporate our traditional yoga practice in our daily life. Through yoga, regardless of the specific disease, we restore, rectify, and improve individuals who suffer from Parkinson’s Disease (PD) balance, quality of life, sleep, and motor functions. This interventional study aims to measure the efficacy of a customized yoga therapy method in improving QoL. 

Methods: A three-month yoga therapy intervention designed to improve the QoL of the PD population. Fifteen participants' random data from the study with one hour of yoga therapy five days a week for 3 months is given below. A three-month yoga therapy intervention was conducted on those living on the early stages scale, as per Hohen and Yahr of PD. Customized Yoga Therapy (CYT) interventions were provided daily to the participants' experimental group. Incorporating yoga knowledge into daily life requires more conscious effort and awareness, enabling safer choices and reducing the adverse effects of medications and the PD condition itself.

Outcomes: This clinical trial aims to improve the QoL, using the UPDRS III, PDQ-39, SCOPA to enhance sleep and the BBS (Berg Balance Scale) for daily activities.

Result : Yoga is a safe, affordable, healthy practice that can correct lifestyle and serve as a non-pharmacological strategy in treating Parkinson's Disease. This clinical trial of yoga experimentation among the Parkinson's disease population significantly enhanced the Quality of Life by improving overall health, balance, quality of life, sleep, and motor functions of individuals with early-stage Parkinsonism.
DOI: 10.5066/p1qrqwhr
title: Bottom dissolved oxygen measurements from Lake Erie's Central Basin, 2023

description: This data set, compiled by the USGS Lake Erie Biological Station, provides near-bottom measurements of temperature and dissolved oxygen for the Central Basin of Lake Erie. Data were recorded by self-contained environmental data loggers (PME, Inc., MiniDOT data loggers). The data loggers for 2023 were deployed to collect data during April 2023 through November 2023 to better understand how hypoxia develops and influences fish habitat quality during lake stratification. The data loggers were deployed on acoustic telemetry receivers in a network designed to record tagged fish movements (Great Lakes Acoustic Telemetry Observation System, GLATOS). Additional years of data collection are planned, and data release will be updated as necessary.
DOI: 10.15468/xhkve6
title: Morphology and multigene phylogeny revealed four new species of Geastrum (Geastrales, Basidiomycota) from China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Yang, Xin, Zhu, Yonggao, Duan, Songjing, Wu, Xingxing, Zhao, Changlin (2025): Morphology and multigene phylogeny revealed four new species of Geastrum (Geastrales, Basidiomycota) from China. MycoKeys 113: 73-100, DOI: 10.3897/mycokeys.113.139672, URL: https://mycokeys.pensoft.net/article/139672/download/xml/
DOI: 10.17632/d7bb7svhcz
title: Psicopatología: recorrido de conceptos básicos para el ejercicio de la clasificación

description: Es un recurso para el curso de psicopatología. El material de clase explica conceptos – definiciones implicadas en el ejercicio de la clasificación. Toma como referente los manuales diagnósticos de psicopatología DSM IV, V y CIE 10 al ser los manuales psicodiagnósticos más utilizados.
DOI: 10.17632/d7bb7svhcz.1
title: Psicopatología: recorrido de conceptos básicos para el ejercicio de la clasificación

description: Es un recurso para el curso de psicopatología. El material de clase explica conceptos – definiciones implicadas en el ejercicio de la clasificación. Toma como referente los manuales diagnósticos de psicopatología DSM IV, V y CIE 10 al ser los manuales psicodiagnósticos más utilizados.
DOI: 10.5281/zenodo.15095597
title: Ben Johnston: String Quartet No. 7, 3rd movement: List of used pitches

description: Johnston notates over 700 different pitches. If we consider this as a hypothetical scale, 500 intervals lie below the limit of two cents. The most frequently mentioned is clearly the schisma, the symbol of the threshold of hearing ((83 occurrences)). In the third movement of String Quartet No. 2, Johnston suggested the possibility of a sound continuum; now this is realized, for when the individual steps are no longer audible, the pitch movement becomes a glissando.
DOI: 10.5281/zenodo.15095598
title: Ben Johnston: String Quartet No. 7, 3rd movement: List of used pitches

description: Johnston notates over 700 different pitches. If we consider this as a hypothetical scale, 500 intervals lie below the limit of two cents. The most frequently mentioned is clearly the schisma, the symbol of the threshold of hearing ((83 occurrences)). In the third movement of String Quartet No. 2, Johnston suggested the possibility of a sound continuum; now this is realized, for when the individual steps are no longer audible, the pitch movement becomes a glissando.
DOI: 10.17632/35kb5f8hz2.1
title: Drivers of the Global Financial Cycle

description: Data and codes used in the paper "Drivers of the Global Financial Cycle"
DOI: 10.17632/35kb5f8hz2.2
title: Drivers of the Global Financial Cycle

description: Data and codes used in the paper "Drivers of the Global Financial Cycle"
DOI: 10.17632/5z3v8mgyzd.1
title: Artificial Intelligence for Chronic Kidney Disease Early Detection and Prognosis

description: Abstract: The integration of Artificial Intelligence (AI) in the early detection and prognosis of Chronic Kidney Disease (CKD) is revolutionizing nephrology by providing enhanced diagnostic accuracy and improved patient outcomes. This research explores the transformative role of AI, particularly machine learning (ML) and deep learning (DL), in predicting CKD progression and facilitating timely interventions. AI-driven models analyze diverse patient data, including imaging, laboratory results, and genetic information, to identify subtle patterns often overlooked by traditional methods. These technologies allow for earlier identification of kidney dysfunction, potentially slowing disease progression and increasing life expectancy. The study highlights the importance of using ensemble learning techniques and feature selection methods to refine AI models, improving their predictive capabilities. Furthermore, the research emphasizes the potential of AI to support clinical decision-making by offering objective, data-driven risk assessments, which are crucial in the personalized management of CKD. The use of convolutional neural networks (CNNs) in renal imaging has shown promise in detecting early-stage kidney damage, while support vector machines (SVM) and artificial neural networks (ANN) have demonstrated high accuracy in diagnosing CKD. The growing integration of AI into healthcare workflows is expected to reduce diagnostic delays, enhance prognostic evaluations, and optimize treatment strategies. This study also discusses the interdisciplinary collaboration between medicine, computer science, and engineering, which is essential for advancing AI applications in CKD. With the increasing availability of high-quality data and computational tools, AI is poised to play a central role in transforming CKD management, offering a proactive approach to care that can lead to better patient outcomes and healthcare resource efficiency.
Keyword: Artificial Intelligence (AI), Chronic Kidney Disease (CKD), Early Detection, Prognosis, Machine Learning, Diagnosis
DOI: 10.17632/5z3v8mgyzd.2
title: Artificial Intelligence for Chronic Kidney Disease Early Detection and Prognosis

description: Abstract: The integration of Artificial Intelligence (AI) in the early detection and prognosis of Chronic Kidney Disease (CKD) is revolutionizing nephrology by providing enhanced diagnostic accuracy and improved patient outcomes. This research explores the transformative role of AI, particularly machine learning (ML) and deep learning (DL), in predicting CKD progression and facilitating timely interventions. AI-driven models analyze diverse patient data, including imaging, laboratory results, and genetic information, to identify subtle patterns often overlooked by traditional methods. These technologies allow for earlier identification of kidney dysfunction, potentially slowing disease progression and increasing life expectancy. The study highlights the importance of using ensemble learning techniques and feature selection methods to refine AI models, improving their predictive capabilities. Furthermore, the research emphasizes the potential of AI to support clinical decision-making by offering objective, data-driven risk assessments, which are crucial in the personalized management of CKD. The use of convolutional neural networks (CNNs) in renal imaging has shown promise in detecting early-stage kidney damage, while support vector machines (SVM) and artificial neural networks (ANN) have demonstrated high accuracy in diagnosing CKD. The growing integration of AI into healthcare workflows is expected to reduce diagnostic delays, enhance prognostic evaluations, and optimize treatment strategies. This study also discusses the interdisciplinary collaboration between medicine, computer science, and engineering, which is essential for advancing AI applications in CKD. With the increasing availability of high-quality data and computational tools, AI is poised to play a central role in transforming CKD management, offering a proactive approach to care that can lead to better patient outcomes and healthcare resource efficiency.
Keyword: Artificial Intelligence (AI), Chronic Kidney Disease (CKD), Early Detection, Prognosis, Machine Learning, Diagnosis