bluuebunny/crossref_metadata_2025_split huggingface dataset:
Overcoming the Friction between the “Right to be Forgotten” and Blockchain Technology through a New Approach
Authors: Severino F. , Sposini L. 
Published: November 2024

Objective: this paper explores the challenges arising from the conflict between blockchain technology and the “right to be forgotten” as provided by the European data protection framework.Methods: in the First Section, the author provides a brief description of the evolution of blockchain technology and the most pressing issues between traditional blockchain models and UE’s legislations. Among the latter, the author analyzes the specific issue concerning the clash between the traditional blockchains (both private and public models), typically immutable, and the individual’s right to cancellation or modification of own personal data. This section emphasizes the importance of personal data protection, which has always been one of the main tasks for supranational legislators. The legal regulation of data protection and the relevant judicial practice of the European Court of Human Rights is analyzed. The author raises the problem of expressing the free self-determination of an individual in the form of controlling their personal data on the Internet. The Second Section of this contribution is dedicated to the study of probable ways to solve the existing incompatibility and to make the distributed ledger system compatible with the European data protection legislation. An emphasis is made on the model provided by “Traent” company, which ensures the right to data cancellation or modification. The capability of this model to solve the said contradiction is analyzed.Results: the study delves into the peculiar features of the new model to understand how it strategically utilizes the advantages of public and private blockchains guaranteeing not only the validity and authenticity of the chain where the transaction was performed, but, most importantly, the modification and granular cancellation of client’s personal data. This innovative solution offers a potential path forward for navigating the complex intersection of data privacy and blockchain innovation in the European context.Scientific novelty: Traent has implemented a “hybrid” model blockchain that, incorporating both public and private components, to achieve an effective compliance with the European Union regulations, especially those concerning data protection and privacy.Practical significance: the obtained conclusions and proposals can be taken into consideration in improving the compliance of blockchain technologies with the European Union General Data Protection Regulation.
Using Artificial Intelligence for Competitive Procurements: Legal Regulation Issues
Authors: Kazantsev D. A. , Dohnal P. , Dohnal Jr. P. 
Published: November 2024

Objective: to substantiate the promising directions of legal regulation of relations in the use of artificial intelligence technologies in competitive (commercial and public) procurement.Methods: the study was conducted using induction, synthesis, analogy, decomposition of problems and generalization of conclusions. The reasoning was based on the experience of a complex procurement of high-tech equipment. This real-life example was considered as an experimental model for the study and subsequent prediction of the potential use of artificial intelligence technologies in competitive procurement procedures.Results: advantages and potential risks of using artificial intelligence technologies in procurement work were formulated; recommendations on regulating such use were given. The authors highlighted recommendations of general legal nature concerning the legal personality and delictual capacity of artificial intelligence and proposed the wordings for new norms and options for regulating the use of new procurement tools. It was proved that artificial intelligence technologies, if used thoughtfully, may not only improve the work quality and significantly reduce organizational costs, but also help to develop the basic principles of regulated procurement: transparency of procedures, development of competition for contracts between qualified suppliers, reasonableness of decisions, and economic efficiency of the customer’s expenditures.Scientific novelty: despite a large number of works devoted to both the problems of artificial intelligence in general and its use in procurement in particular, the article considers this topic on the basis of mainly inductive reasoning, built on handling a particular case and experience of complex procurement for knowledge-intensive research, refracted through the prism of essential correlation between the basic concepts of “digitalization”, “automation”, “robotization” and so on.Practical significance: the directions of using artificial intelligence described in this paper can be implemented by corporate and, in the future, by public customers to improve the quality of their procurement. At the same time, the recommendations on the normative regulation of such innovation seem to be in demand both at the legislative and local levels.
Violation of the Airspace of Countries by Unmanned Aerial Vehicles (Drones) from the Perspective of International Law
Authors: Kamijani M. K. 
Published: November 2024

Objective: to illustrate the challenges to international law and the shortcomings of current regulation caused by the rapid development of drone technology, by the example of using unmanned aerial vehicles (drones) in airspace.Methods: the study is based primarily on a set of methods for interpreting the provisions of international law, which allow analyzing the provisions in the field of using unmanned aerial vehicles (drones). Results: based on international air law and humanitarian law, the article examines the issues of unmanned aerial vehicles (drones) using airspace. The main sources of law in this area are analyzed, including the provisions of international air law, especially the Paris, Madrid, Havana and Chicago Conventions. An attempt is made to answer the questions arising from the development of unmanned technologies as to which rules of international law apply to their use and whether existing international law is capable of responding effectively to them. The article shows the current understanding of the legal status of airspace over the territory of a state. The author puts forward the question whether the sphere of unmanned aerial vehicles, automatic and autonomous weapons, which combines scientific and military achievements with new technologies, is exceptional. In this regard, the problem of using unmanned aerial vehicles as a universal weapon in international conflicts is touched upon. A conclusion is made that the use of intelligent, guided and robotic weapons capable of automatic decision-making, such as drones, requires the revision of existing conventions or the establishment of new legal standards for these weapons. It is proposed to consider such drones as military aircraft of a special type.Scientific novelty: international legal responsibility of states for the military use of drones has not received an unambiguous assessment in the doctrine. However, much in this issue depends on the legal interpretation of the most important international legal categories. Further development of this issue is directly related to the issues of international responsibility and the concept of state sovereignty over airspace.Practical significance: the development of unmanned aviation at the present stage demonstrates the imperfection of the existing legal framework, which is designed to regulate these relations. With regard to the study of the global trend in the current international law, the identification of the shortcomings in the provisions of the latter is important primarily for their further modernization, taking into account modern scientific achievements and the development of the concept of a state sovereignty over its airspace.
Neurorights, Neurotechnologies and Personal Data: Review of the Challenges of Mental Autonomy
Authors: Cornejo Y. 
Published: November 2024

Objective: to present the results of a systematic review of research on the impact of neurotechnology on legal concepts and regulatory frameworks, addressing ethical and social issues related to the protection of individual rights, privacy and mental autonomy.Methods: The systematic literature review was based on the methodology proposed by a renowned British scholar, a professor emerita of computer science at Keele University Barbara Kitchenham, chosen for its flexibility and effectiveness in obtaining results for publication. Thorough searches were carried out with the search terms “neurotechnology”, “personal data”, “mental privacy”, “neuro-rights”, “neurotechnological interventions”, and “neurotechnological discrimination” on both English and Spanish sites, using search engines like Google Scholar and Redib as well as databases including Scielo, Dialnet, Redalyc, Lilacs, Scopus, Medline, and Pubmed. The focus of this research is bibliometric data and its design is non-experimental with a cross-sectional and descriptive, using content analysis based on PRISMA model.Results: the study emphasizes the need to establish clear ethical principles to protect individual rights and promote responsible use of neurotechnologies; a number of problems of mental autonomy were identified, such as improper handling of information, lack of legal security guarantees, violation of rights and freedoms in the medical sphere. The author shows the need to adapt the existing regulatory legal framework to address the ethical and social problems arising from the new neurotechnologies. It is noted that a broad study of neurotechnology issues will contribute to the protection of human rights.Scientific novelty: an expanded understanding of the five neurorights within the Universal Declaration of Human Rights is proposed; neurorights are viewed as a new category of rights aimed at protecting mental integrity against the misuse of neurotechnologies. The author justifies the adoption of such technocratic principles as personal identity, free will, mental privacy, equal access and protection against bias.Practical significance: the obtained results are relevant for understanding modern legal concepts related to neurorights and for adapting the existing normative legal acts to solve ethical and social problems arising from the emergence of new technologies, protection of human neurorights and liability for their violation. The study of these issues is key for provision of further responsible development and use of neurotechnologies.
When superfluidity meets superconductivity - extraction of 3He isotope from liquid helium
Authors: Kempiński Wojciech , Banat Piotr , Kempiński Mateusz , Trybuła Zbigniew , Niechciał Jakub , Chorowski Maciej , Poliński Jarosław , Chołast Katarzyna 
Published: November 2024

Abstract

The world needs clean energy. One of the most promising ways of producing it in large amounts is the helium3–deuterium (3He-D) fusion reaction. Although there are numerous sources of 3He on Earth, most of them are either difficult to access or unprofitable to operate, which results in its deep shortage1. As a matter of great importance, this problem was reported to American Congress2 where, among other possibilities, the extraction of the 3He from the liquid helium was considered. The main problem underlying the shortage of 3He is the lack of an effective method of obtaining this isotope. Here we report the results of quantum filtration of 3He from liquid helium in a superfluid state (below the l-transition), with the use of an entropy filter made of a high-temperature superconductor YBCO-123. During operation of the so-called fountain effect generated with this filter, unlike the other filters, we observed a strong increase of 3He concentration downstream, where only pure 4He was expected. This effect occurred due to the unique combination of two quantum phenomena – superfluidity and superconductivity, leading to the observation of a low-temperature rectification-like process. This process would be considerably more economical than filtration, as rectification could be operated above the
l-transition. Moreover, micro-superconductors could be applied also to the extraction of deuterium, thus allowing the same method to be used for both crucial components of the 3He-D fusion. This method should be easy to upscale and could be used in space (with less energy input) as 3He, the crucial isotope for future energy, is also sought beyond the Earth3,4.
Lake chlorophyll-a linked to upstream nutrients across the CONUS
Authors: Dietrich Matthew , Golden Heather E. , Christensen Jay R. , Lane Charles R. , Dumelle Michael 
Published: November 2024

Abstract

Chlorophyll-a (Chl-a) is a commonly used proxy for algal biomass within surface waters, which can be indicative of harmful algal blooms. Excess nutrients, such as nitrogen or phosphorus, promote Chl-a production, often leading to eutrophication. However, little research exists on river nutrients-to-downstream lake Chl-a linkages at large watershed scales and across disparate climatic and physiographic regions. We found a significant positive relationship between measured total nitrogen (TN) and total phosphorous (TP) concentrations in upstream rivers and Chl-a concentrations in downstream lakes at the watershed scale (average area = 99.8 km2 [35.8-628.6 km2], n = 254 watersheds) throughout the conterminous United States (CONUS). Additionally, through spatial logistic regression models, we demonstrate that a small number of explanatory variables (2–3 per model) can accurately predict (77%-86% accuracy, AUC = 0.83–0.91) classifications of high or low riverine TN, TP, or lake Chl-a concentrations throughout the CONUS at the watershed scale. The predictive variables included vegetation type, runoff, tile drainage, temperature, and nitrogen inputs. This work supports the hypothesis that rivers supply nutrients that enhance Chl-a concentrations in downstream lakes and demonstrates the power of parsimonious models combined with spatial autocorrelation to accurately predict classifications of nutrient concentrations and Chl-a across the CONUS. Synopsis River nutrient concentrations are positively correlated with downstream lake chlorophyll-a and both are effectively predicted by parsimonious models that incorporate spatial autocorrelation.
Heavy metals concentrations in commercial organic fertilizers and the potential risk of fertilization into soils
Authors: Su Kunjie , Zhang Qingliang , Chen Anjing , Wang Xiaoqin , Zhan Lingling , Rao Qiang , Wang Jinxia , Yang Hongjun 
Published: November 2024

Abstract

Inductively coupled plasma mass spectrometry (ICP-MS) was used to detect heavy metals in 74 typical and representative commercial organic fertilizers (COFs) collected in major COF production areas in China. The potential risk of fertilization into soils was evaluated. The concentrations of heavy metals (mg kg− 1) in these COFs were 1.55–36.95 (As), 0.04–2.32 (Hg), 1.43–78.05 (Pb), 0.15–7.49 (Cd), 11.03–212.90 (Cr), 7.74-555.11 (Cu), 21.46-2705.68 (Zn), and 5.62-244.47 (Ni), respectively. Based on China’s Organic Fertilizer Standard (2021), COFs with excessive heavy metals accounted for 45.95% (As), 1.35% (Hg), 2.70% (Pb), 8.11% (Cd), and 6.76% (Cr). According to the European Union standard (2019), the rate of COFs with excessive heavy metals was 32.43% for Cu, 75.68% for Zn, and 85.14% for Ni. Estimated by applying 3854 kg hectare− 1 (dry bass) of fertilizer per hectare per year, to guarantee the safe use of organic fertilizer, the risk monitoring of Cd in soil should be emphasized. China should formulate appropriate standards for the limits of Cu, Zn, and Ni in organic fertilizer as soon as possible and should pay great attention to heavy metal pollution of soils.
Multilayer Perception and Multivariate Time Series Intelligent Lithofacies Identification Method for Tight Sandstone Reservoirs
Authors: Mu Zihao , Li Chunsheng , Liu Zongbao , Liu Tao , Zhang Kejia , Mu Haiwei , Yang Yuchen , Xu Cuiyun , Zhang Ruixue 
Published: November 2024

Abstract

Lithofacies classification and identification are of great significance in the exploration and evaluation of tight sandstone reservoirs. Existing methods of lithofacies identification in tight sandstone reservoirs face issues such as lengthy manual classification, strong subjectivity of identification, and insufficient sample datasets, which make it challenging to analyze the lithofacies characteristics of these reservoirs during oil and gas exploration. In this paper, the Fuyu oil formation in the Songliao Basin is selected as the target area, and an intelligent method for recognizing the lithophysics reservoirs in tight sandstone based on hybrid multilayer perceptron (MLP) and multivariate time series (MTS-Mixers) is proposed. Firstly, appropriate logging curve parameters are selected based on the contribution rate as the basis of the lithofacies intelligent discrimination. Second, preprocessing operations are performed on the logging dataset to ensure the quality of the experimental data. Finally, the MLP-MTS hybrid intelligent model is constructed by combining the powerful information extraction and classification recognition capabilities of the MLP and MTS models to complete the intelligent recognition of the petrography of tight sandstone reservoirs. The experimental results demonstrate that the recognition efficiency of MLP-MTS model for all kinds of lithofacies phases is more than 90%, which verifies the good applicability of deep learning model in solving the process of lithofacies phase recognition in reservoirs.
Dual-View Embedding for Hyper-relational Knowledge Graphs with Hierarchical Structure
Authors: Liu Shuang , Xu Liangyang , Liu Yiying , Kolmani Simon 
Published: November 2024

Abstract

This study proposes a dual-view hyper-relational knowledge graph embedding model aimed at addressing the challenges of embedding complex relationships in knowledge graphs. Traditional methods primarily handle simple triplet relations and struggle with the complexity of hyper-relations. By integrating instance view and ontology view, our model, DVHE, captures hierarchical structural information between entities and is applied to link prediction tasks. Experimental results show that DVHE significantly outperforms existing single-view and dual-view models across multiple benchmark datasets, particularly in handling complex hyper-relations and hierarchical information. Ablation studies further validate the effectiveness of the model’s components, providing new insights for the development of knowledge graph embeddings.
Preparation and mechanical performance of fluorite tailings geopolymer precursor under alkaline heat activation
Authors: Qiu Hao , Su Hongtao , Liu Hengyuan , Guo Zhijian , Zhang Huifang , Ma Juntao , Wang Xiao 
Published: November 2024

Abstract

As one of the bulk solid wastes in the Yellow River basin in China, fluorite tailings urgently need to be utilized as resources. In this paper, NaOH and Na2CO3 were used for alkali thermal activation of ground fluorite tailings under different temperature conditions, and the reactivity was analyzed by XRD, SEM and compressive strength after hydration, so as to evaluate the feasibility of fluorite tailings as geopolymer precursor. The results show that the fluorite tailings can exhibit certain reactivity under alkaline heat excitation, and significant amorphous glass phase can be detected. The better heat excitation temperature is 1000℃, while there is not enough amorphous glass phase for hydration reaction at the lower or higher temperature. The compressive strength of the tailings harden paste can reach 7.2MPa at 28d after excitation with 50%NaOH at 1000℃, which is expected to be used as geopolymer precursor after excitation.
Advancing Biodiesel Production from Waste Cooking Oil: Optimization and Characterization of Manganese-Based Catalysts
Authors: Alahmar Nashwa Mohammed , Azelee Nur Izyan Binti Wan , Toemen Susilawati 
Published: November 2024

Abstract

Biodiesel stands as a non-toxic, biodegradable, and environmentally friendly substitute for conventional petroleum-based fuels. In recent years, the production of biodiesel has garnered significant attention from both industries and researchers globally. Waste cooking oil (WCO) has emerged as a promising feedstock for biodiesel production, drawing the interest of researchers. Utilizing WCO in biodiesel production is not only cost-effective but also addresses the disposal challenges associated with this waste cooking oil. The aim of the present study is to synthesis Ce/Mn(10:90)/γ-Al2O3 using incipient wetness impregnation (IWI) methods, with the goal of facilitating the biodiesel production from WCO. Various preparation parameters, comprising calcination temperatures and based loadings as well as various reaction conditions for the transesterification reaction such as catalyst loading, methanol to oil molar ratio, reaction temperature and time were optimized. From the results, the maximum conversion of triglyceride achieved was 97% for Ce/Mn(10:90)/γ-Al2O3 catalyst calcined at 800oC. The optimum reaction conditions were 10 wt% of catalyst loading and 1:24 of methanol to oil ratio at 65°C of reaction temperature for 3 hrs. This outstanding performance can be attributed to the catalyst's high surface area of 143. m2/g, large pore size of 8.75 nm, and smaller particle size of 0.462 nm, collectively enhancing its catalytic efficiency.
A systematic review and meta-analysis of breastfeeding rates and practices in the United Arab Emirates (UAE)
Authors: O'CONNELL MAEVE ANNE , Meedya Shahla , Baqali Jenan Al , Alraeesi Kadeeja , Leahy-Warren Patricia 
Published: November 2024

Abstract

Objectives
The primary objectives of this study were to estimate breastfeeding rates, identify factors influencing breastfeeding, and explore breastfeeding practices among women in the United Arab Emirates (UAE).
Study Design
Systematic review and meta-analysis.
Methods
A systematic review and meta-analysis of relevant published peer-reviewed literature in the MEDLINE (Ovid), Cumulative Index of Nursing and Allied Health Literature (CINAHL) databases from 2013 to 1st August 2023. When statistical pooling was not possible, results were synthesized narratively.
Results
Twelve studies were included. Pooled data from five studies (n=2009) indicated that 62% of women initiated breastfeeding within the first hour after birth (95% CI: [0.45 - 0.78], I2 = 98.3%). At three months, pooled data from three studies (n=851) showed that 73% of these women were still breastfeeding (95% CI: [0.42 - 0.96], I2 = 98.7%). At six months, the rate of exclusive breastfeeding, based on pooled data from three studies (n=1121), was 29.5% (95% CI: [0.14 - 0.477], I2 = 97.5%). Significant heterogeneity was observed, suggesting that the results should be interpreted with caution. Three key themes emerged from the analysis: (1) balancing supportive factors with traditional practices, (2) the role of health service provision in breastfeeding, and (3) the influence of socioeconomic factors.
Conclusions
This review highlights the importance of integrating cultural competence into healthcare strategies to better support breastfeeding mothers. Additionally, a national infant feeding survey is recommended to address the existing knowledge gaps in the UAE.