bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ion Coupling, Bonding, and Transfer in Narrow Carbon Nanotubes
Authors: Neklyudov Vadim , Freger Viatcheslav 
Published: June 2024

AbstractNarrow carbon nanotubes (nCNT) are unique mimics of biological channels with water‐ion selectivity attractive for applications such as water purification and osmotic energy harvesting, yet their understanding is still incomplete. Here, an ab initio computation is employed to develop the full picture of ion transfer in nCNT including specificity and coupling between ions. The thermodynamic costs of ion transfer are computed for single ions and ion pairs and used to evaluate different local coupling scenarios including strong (pairing) and weak (free‐ion) coupling as well as “electroneutrality breakdown” (EB), possible for cations only due to their chemisorption‐like interaction with nCNT. The results also indicate that nCNT behaves as a highly polarizable metal‐like shell, which eliminates the dielectric energy when CNT accommodates coupled cation and anion. This allows facile computation and comparison of the full transfer costs, including translation entropy, for different ions in different coupling modes to identify the dominant regime. EB transfer appears most favorable for K+, while anions strongly favor transfer as pairs, except for chloride which favors weak coupling and, at neutral pH, transfers as a trace ion coupled to both cation and OH−. The results demonstrate that, in general, observed ion permeation and conduction in nCNT, especially for anions, reflect a complex ion‐specific and composition‐dependent interplay between different ions.
Oriented Metal Stripping for Highly Reversible Zinc Anode
Authors: Zhang Shimeng , Wu Yu , Gao Jianxiong , Song Yanyun , Jin Bowen , Shao Mingfei 
Published: June 2024

AbstractAqueous zinc metal batteries are a viable candidate for next‐generation energy storage systems, but suffer from poor cycling efficiency of the Zn anode. Emerging approaches aim to regulate zinc plating behavior to suppress uncontrolled dendrites, while the stripping process is seldom considered. Herein, an oriented metal stripping strategy is demonstrated to stabilize the Zn anode by removing high‐index facets for exposing the (002) plane through the addition of anionic additive sodium citrate (SC). Consequently, high‐index facets that coordinate strongly with SC are preferentially stripped out due to a reduced stripping barrier, rendering stable (002) facet preponderant in epitaxial plating. After repeat stripping/plating, the ultra‐high proportion of 93% for (002) and large‐size grains of ≈100 µm (six times larger than before) can be obtained. Zn anode shows continuous 25 000 cycles with low overpotential at 100 mA cm−2 in symmetric cells and more than 70 h of stable operation even at an ultra‐high depth of discharge of 92.3%. Moreover, an extremely long lifespan of 12 000 cycles at 10 A g−1 with a high capacity retention of 89% is achieved by the assembled Zn//I2 battery. This work provides a distinctive approach to improving the stripping process to design highly efficient zinc anodes for promising aqueous zinc metal batteries.
A Sunlight‐Driven Self‐Cleaning CuCo‐MOF Composite Membrane for Highly Efficient Emulsion Separation and Water Purification
Authors: He Xuanting , Wu Zixuan , Lu Jihan , Liu Jiaxiang , Li Boyu , Liu Xiaohui , Tao Wenquan , Li Zhuo 
Published: June 2024

AbstractThe fouling phenomenon of membranes has hindered the rapid development of separation technology in wastewater treatment. The integration of materials into membranes with both excellent separation performance and self‐cleaning properties still pose challenges. Here, a self‐assembled composite membrane with solar‐driven self‐cleaning performance is reported for the treatment of complex oil‐water emulsions. The mechanical robustness of the composite membrane is enhanced by the electrostatic attraction between chitosan and metal–organic frameworks (MOF) CuCo‐HHTP as well as the crosslinking effect of glutaraldehyde. Molecular dynamics (MD) simulations also revealed the hydrogen bonding interaction between chitosan and CuCo‐HHTP. The composite membrane of CuCo‐HHTP‐5@CS/MPVDF exhibits a high flux ranging from 700.6 to 2350.6 L∙m−2∙h−1∙bar−1 and excellent separation efficiency (>99.0%) for various oil–water emulsions, including crude oil, kerosene, and other light oils. The addition of CuCo‐HHTP shows remarkable photothermal effects, thus demonstrating excellent solar‐driven self‐cleaning capability and antibacterial performance (with an efficiency of ≈100%). Furthermore, CuCo‐HHTP‐5@CS/MPVDF can activate peroxomonosulfate (PMS) under sunlight, quickly removing oil‐fouling and dyes. Density functional theory (DFT) calculations indicate that the bimetallic sites of Cu and Co in CuCo‐HHTP effectively promoted the activation of PMS. This study provides distinctive insights into the multifaceted applications of MOFs‐derived photothermal anti‐fouling composite membranes.
In Situ Electrochemical Polymerization of Cathode Electrolyte Interphase Enabling High‐Performance Lithium Metal Batteries
Authors: Sun Shipeng , Yu Jiangtao , Ma Xinyu , Fang Pengda , Yang Mingchen , Yang Jinhua , Wu Mingzhu , Hu Yin , Yan Feng 
Published: June 2024

AbstractLithium metal batteries (LMBs) with high‐voltage nickel‐rich cathodes show great potential as energy storage devices due to their exceptional capacity and power density. However, the detrimental parasitic side reactions at the cathode electrolyte interface result in rapid capacity decay. Herein, a polymerizable electrolyte additive, pyrrole‐1‐propionic acid (PA), which can be in situ electrochemically polymerized on the cathode surface and involved in forming cathode electrolyte interphase (CEI) film during cycling is proposed. The formed CEI film prevents the formation of microcracks in LiNi0.8Co0.1Mn0.1O2 (NCM811) secondary particles and mitigates parasitic reactions. Additionally, the COO− anions of PA promote the acceleration of Li+ transport from cathode particles and increase charging rates. The Li||NCM811 batteries with PA in the electrolyte exhibit a high capacity retention of 83.83% after 200 cycles at 4.3 V, and maintain 80.88% capacity after 150 cycles at 4.6 V. This work provides an effective strategy for enhancing interface stability of high‐voltage nickel‐rich cathodes by forming stable CEI film.
In Situ Construction of Highly Dispersed Pd on Cobalt Nanoparticle on Hollow Functional Cubic Graphene by Double Framework for ORR
Authors: Fei Shiyuan , He Zejin , Yang Shuai , Li Ji , Li Xuewen , Zhao Hongbin , Xu Qing , Liu Xiaosong , Jiang Zheng 
Published: June 2024

AbstractDeveloping advanced functional carbon materials is essential for electrocatalysis, caused by their vast merits for boosting many key energy conversion reactions. Herein, the covalent organic frameworks (COFs) is utilized on metal–organic frameworks (MOFs) as the template, under the controllable metal atoms thermal migration process successfully in situ constructs Pd–Co alloy nanoparticles on hollow cubic graphene. The electrocatalytic oxygen reduction reaction (ORR) evaluation showed excellent performances with a half‐wave potential of 0.866 V, and a limited current density of 4.975 mA cm−2, that superior to the commercial Pt/C and Co nanoparticles. The contrast experiments and X‐ray absorption spectrum demonstrated the aggregated electrons at highly dispersed Pd atoms on Co nanoparticle that promoted the main activities. This work not only enlightens the novel carbon materials designing strategies but also suggests heterogeneous electrocatalysis.
Optimizing Surface State Electrons of Topological Semi‐Metal by Atomic Doping for Enhanced Hydrogen Evolution Reaction
Authors: Su Meixia , Zhang Yuhao , Liu Guo , Jiang Haiqing , Lin Yuan , Ding Yan , Wu Qingfeng , Wei Wei , Wang Xinge , Wu Tianyu , Tao Kun , Chen Changcheng , Xie Erqing , Zhang Zhenxing 
Published: June 2024

AbstractTopological materials carrying topological surface states (TSSs) have extraordinary carrier mobility and robustness, which provide a new platform for searching for efficient hydrogen evolution reaction (HER) electrocatalysts. However, the majority of these TSSs originate from the sp band of topological quantum catalysts rather than the d band. Here, based on the density functional theory calculation, it is reported a topological semimetal Pd3Sn carrying TSSs mainly derived from d orbital and proposed that optimizing surface state electrons of Pd3Sn by introduction heteroatoms (Ni) can promote hybridization between hydrogen atoms and electrons, thereby reducing the Gibbs free energy (ΔGH) of adsorbed hydrogen and improving its HER performance. Moreover, this is well verified by electrocatalytic experiment results, the Ni‐doped Pd3Sn (Ni0.1Pd2.9Sn) show much lower overpotential (−29 mV vs RHE) and Tafel slope (17 mV dec−1) than Pd3Sn (−39 mV vs RHE, 25 mV dec−1) at a current density of 10 mA cm−2. Significantly, the Ni0.1Pd2.9Sn nanoparticles exhibit excellent stability for HER. The electrocatalytic activity of Ni0.1Pd2.9Sn nanoparticles is superior to that of commercial Pt. This work provides an accurate guide for manipulating surface state electrons to improve the HER performance of catalysts.
Conclusion
Authors: Tokdoğan Nagehan 
Published: June 2024

AbstractIn the concluding part, I wrap up the discussion of this book and argue that, due to the Neo-Ottomanist symbolic politics, ‘Turks remembered the Ottomans again’. The emphasis on Islam as a major constituent of Turkish national identity has arisen as ‘the return of the repressed’ through the Neo-Ottomanist narrative. I argue that one of the reasons for the endurance of the AKP and its politics of emotions centred around this narrative, is its undeniable appeal to the emotional needs of some segments of society. Nevertheless, I argue that, given the current conditions of the country, this way of conducting politics for the AKP is no longer sustainable, and that the country is experiencing an identity crisis under Erdoğan’s autocratic regime.
The Wave-Memory Interpretation of Quantum Mechanics
Authors: Castro Paulo 
Published: June 2024

AbstractPresent quantum mechanics has been a source of puzzlement since its inception in 1927. The theory has been undoubtedly successful predicting results in a large number of experimental situations. However, its heavy epistemological legacy, coming from the initial ideas of Niels Bohr about complementarity and about the possibility for physical description, has turned quantum mechanics in a kind of ontological black box. This work is an attempt to overcome such epistemological opacity, proposing an interpretation that will present Bohrian quantum mechanics formalism and the pilot-wave framework as two complementary and mutually non-exclusive theoretical descriptions of quantum phenomena. The two theories will, hopefully, become the foundations of a new and more complete approach to quantum reality. One that will, simultaneously, serve as a highly efficient predictive formalism and also as an intelligible description about quantum phenomena in four-dimensional spacetime. I will start from the pilot-wave framework, proposing that quantum waves are memory carrying structures that encode probabilistic distributions of the fundamental behaviors of corpuscles. This nomological information, as I will call it, will have a necessitarian weight upon all corpuscles behaviors, in the sense that the only behaviors allowed in Nature are the ones that can be encoded or have been encoded in the quantum wave carriers. Such a picture of quantum physics will imply that corpuscles exchange nomological information with the carrier waves, by means of the guidage or pilot-wave effect. Secondly, I will suggest that the actual Bohrian quantum mechanics formalism, the one used in the Copenhagen School interpretation, describes not the actual states and properties of quantum corpuscular entities, but the nomological information about those states and properties. As such Bohrian quantum mechanics is a description about not the actual physical observable dynamics, but about the dynamics of the nomological information encoded in the carrier quantum waves. The adoption and consistent interplay of both theoretical descriptions, pilot-wave mode and Bohrian mode, will serve epistemological completeness in the study of quantum phenomena.
Introduction
Authors: Chircop Aldo , Goerlandt Floris , Aporta Claudio , Pelot Ronald 
Published: June 2024

AbstractThis chapter introduces area-based management (ABM) in shipping against the historical and policy backdrop of control of international navigation in defined areas of ocean space, culminating with the development of the international law of the sea in the twentieth century. The problematique of ABM in shipping is set out as a deliberate and scientifically supported exercise guided by multiple factors, including how risks posed by ships and risks posed to ships are scientifically assessed and perceived by regulators, rightsholders, stakeholders, and the public at large. Finally, the chapter describes the book’s purposes, approach, research context, structure, and chapters.
Addressing the Cumulative Effects of Marine Shipping Through Area-Based Management Approaches
Authors: Doucette Paula , Mansfield Samuel 
Published: June 2024

AbstractCanada’s Oceans Protection Plan (OPP) is a comprehensive initiative launched by the Government of Canada to enhance marine safety, protect marine ecosystems, engage with coastal communities, and improve evidence-based decision-making. The OPP focuses on safeguarding Canadian coasts and waterways by implementing measures to prevent and respond to marine incidents, supporting research and innovation, and establishing stronger Indigenous partnerships to address maritime concerns and promote sustainable marine practices. Under the Oceans Protection Plan, Transport Canada’s Cumulative Effects of Marine Shipping (CEMS) initiative has been working in seven regions of Canada to assess and address the regional cumulative effects of marine shipping, in partnership with Indigenous peoples and guided by the principles of reconciliation. The goal of this chapter is to showcase how area-based management (ABM) is applied in the CEMS initiative by first providing background on the CEMS initiative from a broad perspective and then examining linkages between the initiative and ABM approaches. A case study is described from one regional CEMS assessment being conducted along a section of the Northwest Passage in southern Victoria Island, Nunavut, which resulted in the development of a voluntary measure using an ABM approach to mitigate the impacts of icebreaking activities on caribou migration and hunter safety.
Risk Analysis for Vessel Accident Prevention in Marine Areas: An Accident-Theoretic Perspective on Spatial Aspects of Risk
Authors: Goerlandt Floris 
Published: June 2024

AbstractArea-based marine management approaches aim to mitigate the risks and impacts of shipping on human safety at sea and on ecosystems in marine and coastal environments. Through various regulatory initiatives and policy practices, risk assessment has been established as an important element to support decision-making for area-based marine management. This chapter focuses on the use of risk assessment for supporting decisions to manage navigational risks through risk control measures such as the design of vessel traffic separation schemes, the selection and positioning of aids to navigation, and the definition of operational requirements from a vessel traffic management perspective. To facilitate further developments in this domain, this chapter provides a brief overview of risk analysis techniques currently promoted at the international level, and selected approaches proposed in the academic literature are outlined. A discussion is provided on these selected techniques, through the lens of accident causation theories, focusing on how aspects related to the marine space are conceptualized in these techniques. Finally, directions for future research and development are outlined.
Assessing the impacts of EU agricultural policies on the sustainability of the livestock sector: a review of the recent literature
Authors: Adams Nina , Sans Ariane , Trier Kreutzfeldt Karen-Emilie , Arias Escobar Maria Alejandra , Oudshoorn Frank Willem , Bolduc Nathalie , Aubert Pierre-Marie , Smith Laurence Graham 
Published: June 2024

Abstract
How do agricultural policies in the EU need to change to increase the sustainability of livestock production, and what measures could encourage sustainable practices whilst minimising trade-offs? Addressing such questions is crucial to ensure progress towards proclaimed targets whilst moving production levels to planetary boundaries. However, a lack of available evidence on the impacts of recent policies hinders developments in this direction. In this review, we address this knowledge gap, by collating and evaluating recent policy analyses, using three complementary frameworks. The review highlights that recent policy reforms, and especially those of the Common Agricultural Policy, have had a large impact on the sustainability of the livestock sector by contributing to intensification and simplification. This has often resulted in negative impacts (e.g. on greenhouse gas emissions and animal welfare) and while financial support has enabled production, it can also lead to a culture of dependency that limits innovation. At the same time, a lack of regulation and concrete targets, and low levels of stakeholder engagement in policy design have led to delays in the delivery of sustainability objectives. Future policies could take on-board more innovative thinking that addresses the interrelatedness of society, animals, and the environment, to deliver effective targets and support.
An effective multiclass skin cancer classification approach based on deep convolutional neural network
Authors: Houssein Essam H. , Abdelkareem Doaa A. , Hu Gang , Hameed Mohamed Abdel , Ibrahim Ibrahim A. , Younan Mina 
Published: June 2024

AbstractSkin cancer is one of the most dangerous types of cancer due to its immediate appearance and the possibility of rapid spread. It arises from uncontrollably growing cells, rapidly dividing cells in one area of the body, invading other bodily tissues, and spreading throughout the body. Early detection helps prevent cancer progress from reaching critical levels, reducing the risk of complications and the need for more aggressive treatment options. Convolutional neural networks (CNNs) revolutionize skin cancer diagnosis by extracting intricate features from images, enabling an accurate classification of lesions. Their role extends to early detection, providing a powerful tool for dermatologists to identify abnormalities in their nascent stages, ultimately improving patient outcomes. This study proposes a novel deep convolutional neural network (DCNN) approach to classifying skin cancer lesions. The proposed DCNN model is evaluated using two unbalanced datasets, namely HAM10000 and ISIC-2019. The DCNN model is compared with other transfer learning models, including VGG16, VGG19, DenseNet121, DenseNet201, and MobileNetV2. Its performance is assessed using four widely used evaluation metrics: accuracy, recall, precision, F1-score, specificity, and AUC. The experimental results demonstrate that the proposed DCNN model outperforms other deep learning (DL) models that utilized these datasets. The proposed DCNN model achieved the highest accuracy with the HAM10000 and ISIC-2019 datasets, reaching $$98.5\%$$

98.5
%

and $$97.1\%$$

97.1
%

, respectively. These experimental results show how competitive and successful the DCNN model is in overcoming the problems caused by class imbalance and raising skin cancer classification accuracy. Furthermore, the proposed model demonstrates superior performance, particularly excelling in terms of accuracy, compared to other recent studies that utilize the same datasets, which highlights the robustness and effectiveness of the proposed DCNN.
Scrutinizing different predictive modeling validation methodologies and data-partitioning strategies: new insights using groundwater modeling case study
Authors: Lal Alvin , Sharan Ashneel , Sharma Krishneel , Ram Arishma , Roy Dilip Kumar , Datta Bithin 
Published: June 2024

AbstractGroundwater salinity is a critical factor affecting water quality and ecosystem health, with implications for various sectors including agriculture, industry, and public health. Hence, the reliability and accuracy of groundwater salinity predictive models are paramount for effective decision-making in managing groundwater resources. This pioneering study presents the validation of a predictive model aimed at forecasting groundwater salinity levels using three different validation methods and various data partitioning strategies. This study tests three different data validation methodologies with different data-partitioning strategies while developing a group method of data handling (GMDH)-based model for predicting groundwater salinity concentrations in a coastal aquifer system. The three different methods are the hold-out strategy (last and random selection), k-fold cross-validation, and the leave-one-out method. In addition, various combinations of data-partitioning strategies are also used while using these three validation methodologies. The prediction model’s validation results are assessed using various statistical indices such as root mean square error (RMSE), means squared error (MSE), and coefficient of determination (R2). The results indicate that for monitoring wells 1, 2, and 3, the hold-out (random) with 40% data partitioning strategy gave the most accurate predictive model in terms of RMSE statistical indices. Also, the results suggested that the GMDH-based models behave differently with different validation methodologies and data-partitioning strategies giving better salinity predictive capabilities. In general, the results justify that various model validation methodologies and data-partitioning strategies yield different results due to their inherent differences in how they partition the data, assess model performance, and handle sources of bias and variance. Therefore, it is important to use them in conjunction to obtain a comprehensive understanding of the groundwater salinity prediction model's behavior and performance.
Curvature-constrained Steiner networks with three terminals
Authors: Grossman Peter A. , Kirszenblat David , Brazil Marcus , Rubinstein J. Hyam , Thomas Doreen A. 
Published: June 2024

AbstractA procedure is presented for finding the shortest network connecting three given undirected points, subject to a curvature constraint on both the path joining two of the points and the path that connects to the third point. The problem is a generalisation of the Fermat–Torricelli problem and is related to a shortest curvature-constrained path problem that was solved by Dubins. The procedure has the potential to be applied to the optimal design of decline networks in underground mines.