cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13145/bacdive142198.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142199.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142201.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142202.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142203.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142204.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142205.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142207.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142209.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142210.20241212.9.2
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142220.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142228.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142233.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15468/dl.t3p66e
title: Occurrence Download

description: A dataset containing 108 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Germany",
 "GadmGid is DEU.3_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Candelariella aurella (Hoffm.) Zahlbr."
 ]
}

 The dataset includes 108 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010499-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13145/bacdive142234.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142237.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142238.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142239.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142241.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142242.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive142243.20240916.9.1
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.5281/zenodo.18054481
title: MLOps Pipeline Generation for Reinforcement Learning: A Low-Code Approach Using Large Language Models: Replication Package

description: Title: MLOps Pipeline Generation for Reinforcement Learning: A Low-Code Approach Using Large Language Models: Replication Package

Authors: Stephen John Warnett; Evangelos Ntentos; Uwe Zdun

About: This is the replication package artefact for the paper entitled "MLOps Pipeline Generation for Reinforcement Learning: A Low-Code Approach Using Large Language Models".

Paper Abstract: MLOps (Machine Learning Operations) and its application to Reinforcement Learning (RL) involve various challenges when integrating Machine Learning and RL models into production systems, entailing considerable expertise and manual effort, which can be error-prone and obstruct scalability and rapid deployment. We propose a new approach to address these challenges in generating MLOps pipelines. We present a low-code, template-based approach leveraging Large Language Models (LLMs) to automate RL pipeline generation, validation and deployment. In our approach, the Pipes and Filters pattern allows for the fine-grained generation of MLOps pipeline configuration files. Built-in error detection and correction help maintain high-quality output standards.    To empirically evaluate our solution, we assess the correctness of pipelines generated with seven LLMs for three open-source RL projects. Our initial approach achieved an average error rate of 0.187 across all seven LLMs. OpenAI GPT-4o performed the best with an error rate of just 0.09, followed by Qwen2.5 Coder with an error rate of 0.15. We implemented a single round of improvements to our implementation and low-code template. We reevaluated our solution on the best-performing LLM from the initial evaluation, achieving perfect results with an overall error rate of zero for OpenAI GPT-4o. Our findings indicate that pipelines generated by our approach have low error rates, potentially enabling rapid scaling and deployment of reliable MLOps for RL pipelines, particularly for practitioners lacking advanced software engineering or DevOps skills. Our approach contributes towards demonstrating increased reliability and trustworthiness in LLM-based solutions, despite the uncertainty hitherto associated with LLMs.
DOI: 10.5281/zenodo.18054482
title: MLOps Pipeline Generation for Reinforcement Learning: A Low-Code Approach Using Large Language Models: Replication Package

description: Title: MLOps Pipeline Generation for Reinforcement Learning: A Low-Code Approach Using Large Language Models: Replication Package

Authors: Stephen John Warnett; Evangelos Ntentos; Uwe Zdun

About: This is the replication package artefact for the paper entitled "MLOps Pipeline Generation for Reinforcement Learning: A Low-Code Approach Using Large Language Models".

Paper Abstract: MLOps (Machine Learning Operations) and its application to Reinforcement Learning (RL) involve various challenges when integrating Machine Learning and RL models into production systems, entailing considerable expertise and manual effort, which can be error-prone and obstruct scalability and rapid deployment. We propose a new approach to address these challenges in generating MLOps pipelines. We present a low-code, template-based approach leveraging Large Language Models (LLMs) to automate RL pipeline generation, validation and deployment. In our approach, the Pipes and Filters pattern allows for the fine-grained generation of MLOps pipeline configuration files. Built-in error detection and correction help maintain high-quality output standards.    To empirically evaluate our solution, we assess the correctness of pipelines generated with seven LLMs for three open-source RL projects. Our initial approach achieved an average error rate of 0.187 across all seven LLMs. OpenAI GPT-4o performed the best with an error rate of just 0.09, followed by Qwen2.5 Coder with an error rate of 0.15. We implemented a single round of improvements to our implementation and low-code template. We reevaluated our solution on the best-performing LLM from the initial evaluation, achieving perfect results with an overall error rate of zero for OpenAI GPT-4o. Our findings indicate that pipelines generated by our approach have low error rates, potentially enabling rapid scaling and deployment of reliable MLOps for RL pipelines, particularly for practitioners lacking advanced software engineering or DevOps skills. Our approach contributes towards demonstrating increased reliability and trustworthiness in LLM-based solutions, despite the uncertainty hitherto associated with LLMs.
DOI: 10.5281/zenodo.18133862
title: XRP/ETH Multi-Path Arbitrage Dataset (Binance Exchange, 2025)

description: This dataset contains minute-level price data for three cryptocurrency trading pairs from Binance exchange, used in the study "Applying Modigliani-Miller Theorem to Cryptocurrency Multi-Path Arbitrage: A Theoretical Framework and Empirical Evidence from XRP/ETH Markets."


The dataset includes:

1. xrp_usdt_data.csv: XRP/USDT trading pair data

2. xrp_eth_data.csv: XRP/ETH trading pair data  

3. eth_usdt_data.csv: ETH/USDT trading pair data


Each CSV file contains the following columns:

- date: Timestamp in YYYY-MM-DD HH:MM:SS format

- close: Closing price (in USDT or ETH)

- volume: Trading volume (in base asset units, e.g., XRP or ETH)

- amount: Trading amount (in quote currency units, e.g., USDT)


Data period: January 1, 2025 - October 15, 2025

Data frequency: 1-minute intervals

Data source: Binance Exchange (https://www.binance.com/)


This dataset supports research on cryptocurrency arbitrage strategies, mean reversion analysis, and the application of classical finance theory (Modigliani-Miller theorem) to digital asset markets.
DOI: 10.5281/zenodo.18133861
title: XRP/ETH Multi-Path Arbitrage Dataset (Binance Exchange, 2025)

description: This dataset contains minute-level price data for three cryptocurrency trading pairs from Binance exchange, used in the study "Applying Modigliani-Miller Theorem to Cryptocurrency Multi-Path Arbitrage: A Theoretical Framework and Empirical Evidence from XRP/ETH Markets."


The dataset includes:

1. xrp_usdt_data.csv: XRP/USDT trading pair data

2. xrp_eth_data.csv: XRP/ETH trading pair data  

3. eth_usdt_data.csv: ETH/USDT trading pair data


Each CSV file contains the following columns:

- date: Timestamp in YYYY-MM-DD HH:MM:SS format

- close: Closing price (in USDT or ETH)

- volume: Trading volume (in base asset units, e.g., XRP or ETH)

- amount: Trading amount (in quote currency units, e.g., USDT)


Data period: January 1, 2025 - October 15, 2025

Data frequency: 1-minute intervals

Data source: Binance Exchange (https://www.binance.com/)


This dataset supports research on cryptocurrency arbitrage strategies, mean reversion analysis, and the application of classical finance theory (Modigliani-Miller theorem) to digital asset markets.
DOI: 10.6084/m9.figshare.30988328.v1
title: From bench to brain: novel thieno-oxazine hybrids as potent pleiotropic anti-Alzheimer’s agents with <i>in vivo</i>/<i>in vitro</i> validation and <i>in silico</i> insights

description: Due to their various pharmacological effects, several substituted sulphur heterocycles containing thiophene have recently attracted a great deal of attention. A novel 2,3-diaryl-2,3,5,6,7,8-hexahydro-4<i>H</i>-benzo[4,5]thieno[3,2-<i>e</i>][1,3]oxazin-4-one <b>(9–14)</b> was synthesised starting from cyclohexa[<i>b</i>]thiophene. Compounds <b>9</b> and <b>10</b> showed the greatest gene expression downregulation of BAX by 75.1% and 79.7%, and upregulation of Bcl-2 gene expression by 8.1 folds for each. It also decreased the level of AChE by 70.2 and 75%; respectively. Compounds <b>9</b> and <b>10</b> significantly increased Wnt3a levels by 5.8 and 6.6 folds, and β-Catenin levels by 10.1 and 10.5 folds, respectively, compared to donepezil. They significantly downregulated 5-GSK3β gene expression by 77.1%, and 78.7%, respectively. Even though all compounds exhibited potent inhibition of AChE, all synthesised compounds, except for compounds <b>5</b> and <b>11</b> demonstrated higher selectivity towards BChE (SI &lt; 1). <i>In-silico</i> ADMET calculations as well as molecular docking have been performed for synthetic compounds.
DOI: 10.6084/m9.figshare.30988328
title: From bench to brain: novel thieno-oxazine hybrids as potent pleiotropic anti-Alzheimer’s agents with <i>in vivo</i>/<i>in vitro</i> validation and <i>in silico</i> insights

description: Due to their various pharmacological effects, several substituted sulphur heterocycles containing thiophene have recently attracted a great deal of attention. A novel 2,3-diaryl-2,3,5,6,7,8-hexahydro-4<i>H</i>-benzo[4,5]thieno[3,2-<i>e</i>][1,3]oxazin-4-one <b>(9–14)</b> was synthesised starting from cyclohexa[<i>b</i>]thiophene. Compounds <b>9</b> and <b>10</b> showed the greatest gene expression downregulation of BAX by 75.1% and 79.7%, and upregulation of Bcl-2 gene expression by 8.1 folds for each. It also decreased the level of AChE by 70.2 and 75%; respectively. Compounds <b>9</b> and <b>10</b> significantly increased Wnt3a levels by 5.8 and 6.6 folds, and β-Catenin levels by 10.1 and 10.5 folds, respectively, compared to donepezil. They significantly downregulated 5-GSK3β gene expression by 77.1%, and 78.7%, respectively. Even though all compounds exhibited potent inhibition of AChE, all synthesised compounds, except for compounds <b>5</b> and <b>11</b> demonstrated higher selectivity towards BChE (SI &lt; 1). <i>In-silico</i> ADMET calculations as well as molecular docking have been performed for synthetic compounds.
DOI: 10.6084/m9.figshare.24658095
title: Compensation payment for fisherfolk during closed-season fishing: Lessons from small-scale fisherfolk in Ghana

description: This study contributes to the literature on marine conservation, fisheries management, and coastal development. The study investigated the distribution mechanism of government -led compensation payment schemes for small-scale coastal fisherfolk in Ghana during the closed season. We also sought to explore the perception of fisherfolk concerning equity and fairness in the distribution of the compensation scheme. The empirical data consisted of 220 household surveys and 20 in-depth interviews with relevant stakeholders from the Central Region of Ghana. The findings from our study indicate that significant controversies exist about the selection of beneficiaries for compensation payment. There is a lack of transparency in the compensation schemes targeting criteria. The distribution process was widely perceived to be unfair. The results from the study show that there are high levels of politics and nepotism in compensation distribution. Access to compensation packages is largely influenced by political party affiliation. A more transparent and precisely targeted scheme may go a long way to improving perceptions of fairness and compliance. The paper calls for the introduction of alternative livelihoods for fishing households during the closed season.
DOI: 10.6084/m9.figshare.24658095.v1
title: Compensation payment for fisherfolk during closed-season fishing: Lessons from small-scale fisherfolk in Ghana

description: This study contributes to the literature on marine conservation, fisheries management, and coastal development. The study investigated the distribution mechanism of government -led compensation payment schemes for small-scale coastal fisherfolk in Ghana during the closed season. We also sought to explore the perception of fisherfolk concerning equity and fairness in the distribution of the compensation scheme. The empirical data consisted of 220 household surveys and 20 in-depth interviews with relevant stakeholders from the Central Region of Ghana. The findings from our study indicate that significant controversies exist about the selection of beneficiaries for compensation payment. There is a lack of transparency in the compensation schemes targeting criteria. The distribution process was widely perceived to be unfair. The results from the study show that there are high levels of politics and nepotism in compensation distribution. Access to compensation packages is largely influenced by political party affiliation. A more transparent and precisely targeted scheme may go a long way to improving perceptions of fairness and compliance. The paper calls for the introduction of alternative livelihoods for fishing households during the closed season.
DOI: 10.6084/m9.figshare.24628372
title: Inner-city development experiences of Germany: Lessons for Pakistan, Ghana, Kenya, and Rwanda in urban development

description: Inner-city development is a key part of urban development strategies in Germany for sustainable urban development. Using comparative urbanism as a methodological and theoretical lens, this review paper reflects on Germany’s experiences with inner-city development. It contextualizes the experiences as “potential lessons” for four developing countries in Asia and Africa—Pakistan, Ghana, Kenya, and Rwanda—taking into account the intricacies of inner-city development in these countries. The study identifies the principles (in the light of challenges) of inner-city development in Germany and argues that they can be spearheaded in Pakistan, Ghana, Kenya, and Rwanda for sustainable urban development. However, there must be strong commitment and firmness in planning and policy direction, grounded by sensitivity to the context realities that shape urban planning and policy analysis. The study contributes to the emerging discourse on the nexus between inner city and urban planning in developing countries and grounds future studies on inclusive urban planning interventions in the focal countries.
DOI: 10.6084/m9.figshare.24628372.v1
title: Inner-city development experiences of Germany: Lessons for Pakistan, Ghana, Kenya, and Rwanda in urban development

description: Inner-city development is a key part of urban development strategies in Germany for sustainable urban development. Using comparative urbanism as a methodological and theoretical lens, this review paper reflects on Germany’s experiences with inner-city development. It contextualizes the experiences as “potential lessons” for four developing countries in Asia and Africa—Pakistan, Ghana, Kenya, and Rwanda—taking into account the intricacies of inner-city development in these countries. The study identifies the principles (in the light of challenges) of inner-city development in Germany and argues that they can be spearheaded in Pakistan, Ghana, Kenya, and Rwanda for sustainable urban development. However, there must be strong commitment and firmness in planning and policy direction, grounded by sensitivity to the context realities that shape urban planning and policy analysis. The study contributes to the emerging discourse on the nexus between inner city and urban planning in developing countries and grounds future studies on inclusive urban planning interventions in the focal countries.
DOI: 10.6084/m9.figshare.24793820
title: Profiling terrorist organizations capable of high impact attacks

description: Terrorist attacks aim to maximize human fatalities and related damages to instill fear within the community. Such attacks are considered High Impact Attacks (HIAs) and orchestrating them requires considerable organizational setup and resources. This study extends the implementation of the Iterative Outlier Analysis (IOA) heuristics developed earlier to each region reported in the Global Terrorism Database (GTD). It reinforces and generalizes the finding that the “nkill” attribute resulted in richer sets of HIAs in regions where terrorism is prolific compared to the composite measure Global Terrorism Index—Impact Score (GTI-IS). HIA dataset of each region facilitates the identification and ranking of the Most Active Organizations (MAOs). Moreover, this study proposes a consistency and intensity code (CIC) to classify terrorist organizations capable of HIAs using four color categories. K-Means validate the number of clusters. The frequency of MAOs rank follows distinct probability distribution in each CIC category. Finally, this research identified the most virulent consistent and intense terrorist organizations (CITO) capable of perpetrating attacks in multiple regions. Regional counterterrorism policymakers can use such a classification method. A non-parametric hypothesis test confirmed that the contribution of ideologies varies significantly by region.
DOI: 10.6084/m9.figshare.24793820.v1
title: Profiling terrorist organizations capable of high impact attacks

description: Terrorist attacks aim to maximize human fatalities and related damages to instill fear within the community. Such attacks are considered High Impact Attacks (HIAs) and orchestrating them requires considerable organizational setup and resources. This study extends the implementation of the Iterative Outlier Analysis (IOA) heuristics developed earlier to each region reported in the Global Terrorism Database (GTD). It reinforces and generalizes the finding that the “nkill” attribute resulted in richer sets of HIAs in regions where terrorism is prolific compared to the composite measure Global Terrorism Index—Impact Score (GTI-IS). HIA dataset of each region facilitates the identification and ranking of the Most Active Organizations (MAOs). Moreover, this study proposes a consistency and intensity code (CIC) to classify terrorist organizations capable of HIAs using four color categories. K-Means validate the number of clusters. The frequency of MAOs rank follows distinct probability distribution in each CIC category. Finally, this research identified the most virulent consistent and intense terrorist organizations (CITO) capable of perpetrating attacks in multiple regions. Regional counterterrorism policymakers can use such a classification method. A non-parametric hypothesis test confirmed that the contribution of ideologies varies significantly by region.