bluuebunny/crossref_metadata_2025_split huggingface dataset:
Negatively Charged Hydrophobic Carbon Nano‐Onion Interfacial Layer Enabling High‐Rate and Ultralong‐Life Zn‐Based Energy Storage
Authors: Peng Xinya , Li Yang , Kang Fulian , Li Xu , Zheng Zhiyuan , Dong Liubing 
Published: September 2023

AbstractZn‐based electrochemical energy storage (EES) systems are attracting more attention, whereas their large‐scale application is restricted by the dendrite and parasitic reaction‐caused unstable Zn anodes. Herein, a negatively charged hydrophobic carbon nano‐onion (CNO) interfacial layer is proposed to realize ultrastable and high‐rate Zn anodes, enabling high‐performance Zn‐based EES. For the CNO interfacial layer, its hydrophobicity not only blocks active water but also reduces the Zn2+ desolvation barrier, and meanwhile, the negatively‐charged CNO nanoparticles adsorb Zn2+ and repel SO42− to homogenize Zn2+ flux, accelerate Zn2+ desolvation and suppress the self‐corrosion of Zn anodes. Besides, the conductive CNO interfacial layer increases the surface area for the Zn deposition to reduce local current density. Consequently, under the modulation of the CNO interfacial layer, Zn plating/stripping exhibits impressive reversibility with an average Coulombic efficiency of 99.4% over 800 cycles, and Zn anodes present significantly enhanced electrochemical stability and rate performance, whose operation lifetime exceeds 2000 h at 1 mA cm−2 and 350 h even at 10 mA cm−2. Moreover, high‐rate and ultralong‐life Zn‐ion hybrid supercapacitors are achieved with the CNO interfacial layer‐modulated Zn anode and activated CNO cathode. This work provides new thinking in regulating the Zn deposition interface to realize high‐performance Zn‐based EES.
Transformation of SBUs and Synergy of MOF Host–Guest in Single Crystalline State: Ingenious Strategies for Modulating Third‐Order NLO Signals
Authors: Sun Yupei , Xu Wenjuan , Lang Feifan , Wang Huarui , Pan Fangfang , Hou Hongwei 
Published: September 2023

AbstractCentral metal exchange can innovatively open the cavity of metal‐organic frameworks (MOFs) by alternating the framework topology. Here, the single‐crystal‐to‐single‐crystal (SC‐SC) transformation is reported from a Co‐based MOF {[Co1.25(HL)0.5(Pz‐NH2)0.25(µ3‐O)0.25(µ2‐OH)0.25(H2O)]·0.125 Co·0.125 L·10.25H2O}n (Co‐MOF, L = 5,5'‐(1H‐2,3,5‐triazole‐1,4‐diyl)diisophthalic acid) into two novel MOF materials, {[Cu1.75L0.75(Pz‐NH2)0.125(µ3‐O)0.125(µ2‐OH)0.25(H2O)0.375]•3CH3CN}n (Cu‐MOF) and {[Zn1.75L0.625(Pz‐NH2)0.25(µ3‐O)0.25(µ2‐O)0.25(H2O)1.25]•4CH3CN}n (Zn‐MOF), through exchanging the Co2+ in the MOF into Cu2+ or Zn2+, respectively. The free Co2+ and L4− in the Co‐MOF channels fuse with the skeleton during the Co→Cu and Co→Zn exchange processes, leading to the expansion of the channel space and the transformation of the secondary building units (SBUs) to form an adjustable skeleton. The nonlinear optical response results show that the MOFs generated by the exchange of the central metal exhibit different saturable absorption and the self‐focusing effect. In addition, loading polypyrrole (PPy) into the MOFs can not only improve the stability of the MOFs but also further optimize the nonlinear optical behavior. This work suggests that SC‐SC central metal exchange and the introduction of polymer molecules can tune the nonlinear optical response, which provides a new perspective for the future study of nonlinear optical materials.
Perovskite Oxides Alleviate Microstrain and Anion Loss of Radially‐Aligned Ni‐Rich Ncm811 Cathodes under High‐Voltage Operations
Authors: Wang Zhihong , Wei Wu , Zhang Tao , Yu Haifeng , Li Chunzhong , Chen Ling , Jiang Hao 
Published: September 2023

AbstractThe energy density of Ni‐rich cathodes is expected to be further unlocked by increasing the cut‐off voltage to above 4.3 V, which nevertheless come with significantly increased irreversible phase transition and abundant side reactions. In this study, the perovskite oxides enhanced radial‐aligned LiNi0.8Co0.1Mn0.1O2(NCM811) cathodes are reported, in which the coherent‐growth La2[LiTM]O4clusters are evenly riveted into the crystals and the stable LaxCa1−x[TM]O3−xprotective layer is concurrently formed on the surface. The reciprocal interactions greatly reduce the lattice strain during de‐/lithiation. Meantime, the abundant oxygen vacancies of the coating layer are proved to reversibly capture (state of charge) and re‐release (state of discharge) the oxygen radicals, fully avoiding their correlative side reactions. The resultant NCM811 displays negligible O2and CO2emissions when charging to 4.5 V as well as a thinner CEI film, therefore delivering a large capacity of 225 mAh g−1at 0.1C in coin‐type half‐cells and a high retention of 88.3% after 1000 cycles at 1C in pouch‐type full‐cells within 2.7–4.5 V. The development of high‐voltage Ni‐rich cathodes exhibits a highly effective pathway to further increase their energy density.
Metallic 1T‐N‐WS2/WO3 Heterojunctions Featuring Interface‐Engineered Cu–S Configuration for Selective Electrochemical CO2 Reduction Reaction
Authors: Prasanna Murugesan , Logeshwaran Natarajan , Ramakrishnan Shanmugam , Yoo Dong Jin 
Published: September 2023

AbstractElectrocatalytic carbon‐dioxide reduction reactions (ECO2RR) are one of the most rational techniques to control one's carbon footprint. The desired product formation depends on deliberate reaction kinetics and a choice of electron–proton contribution. Herein the usage of novel CuS active centers decorated over stable 1T metallic N‐WS2/WO3 nanohybrids as an efficient selective formate conversion electrocatalyst with regard to ECO2RR is reported. The preferred reaction pathway is identified as *OCHO, which is reduced (by gaining H+ + e−) to HCOO− (HCOO− path) as the primary product. More significantly, at −1.3 V versus RHE yield of FEHCOO− is 55.6% ± 0.5 with a Jgeo of −125.05 mA cm−2 for CuS@1T‐N‐WS2/WO3 nanohybrids. In addition, predominant catalytic activity, selectivity, and stability properties are observed; further post‐mortem analysis demonstrates the choice of material importance. The present work describes an impressive approach to develop highly active electrocatalysts for selective ECO2RR applications.
Faster range minimum queries
Authors: Kowalski Tomasz M. , Grabowski Szymon 
Published: September 2023

SummaryRange minimum query is an important building brick of many compressed data structures and string matching algorithms. Although this problem is essentially solved in theory, with sophisticated data structures allowing for constant time queries, practical performance and construction time also matter. Additionally, there are offline scenarios in which the number of queries, ie, q, is rather small and given beforehand, which encourages to use a simpler approach. In this work, we present a simple data structure, with very fast construction, which allows to handle queries in constant time on average. This algorithm, however, requires access to the input data during queries (which is not the case of sophisticated range minimum query solutions). We subsequently refine our technique, combining it with one of the existing succinct solutions with O(1) worst‐case time queries and no access to the input array. The resulting hybrid is still a memory frugal data structure, spending usually up to about 3n bits and providing competitive query times, especially for wide ranges. We also show how to make our baseline data structure more compact. Experimental results demonstrate that the proposed block‐based sparse table (BbST) variants are competitive to existing solutions, also in the offline scenario.
Practice of Alibaba cloud on elastic resource provisioning for large‐scale microservices cluster
Authors: Xu Minxian , Yang Lei , Wang Yang , Gao Chengxi , Wen Linfeng , Xu Guoyao , Zhang Liping , Ye Kejiang , Xu Chengzhong 
Published: September 2023

SummaryCloud‐native architecture is becoming increasingly crucial for today's cloud computing environments due to the need for speed and flexibility in developing applications. It utilizes microservice technology to break down traditional monolithic applications into light‐weight and self‐contained microservice components. However, as microservices grow in scale and have dynamic inter‐dependencies, they also pose new challenges in resource provisioning that cannot be fully addressed by traditional resource scheduling approaches. The various microservices with different resource demands and latency requirements can create complex calling chains, making it difficult to provide fine‐grained and accurate resource allocation to each component while maintaining the overall quality of service in the chain. Alibaba Cloud has fully embraced cloud‐native and microservice technologies to drive its key business and scenarios, including Double 11 Shopping Festival. In this work, we aim to address the research problem on how to efficiently provision resources for the growing scale of microservice platform and ensure the performance of latency‐critical microservices. To address the problem, we present in‐depth analyses of Alibaba's microservice cluster and propose optimized resource provisioning algorithms to enhance resource utilization while ensuring the latency requirement. First, we analyze the distinct features of microservices in Alibaba's cluster compared to traditional applications. Then we present Alibaba's resource capacity provisioning workflow and framework to address challenges in resource provisioning for large‐scale and latency‐critical microservice clusters. Finally, we propose enhanced resource provisioning algorithms over Alibaba's current practice by making both proactive and reactive scheduling decisions based on different workloads patterns, which can improve resource usage by 10%–15% in Alibaba's clusters, while maintaining the necessary latency for microservices.
A methodology for parameter estimation in system dynamics models using artificial intelligence
Authors: Gadewadikar Jyotirmay , Marshall Jeremy 
Published: September 2023

AbstractMultiple tools exist for separately simulating and estimating the parameters of system dynamics models. Artificial intelligence (AI) has been increasingly used to estimate the parameters of system dynamics models. The development of modeling tools and advanced environments has resulted in great benefits to the community at large. The incorporation of AI tools into system dynamics presents opportunities for expanding on current decision‐making methods. As systems become complex, the need to incorporate evidence‐based data‐driven methods increases. By integrating system dynamics tools and facilitating AI and system dynamics simulation in an integrated environment, model parameters can be estimated with the latest data, and the integrity of the model can be retained effectively. This provides an advantage to the efficiency and capabilities of the system dynamics model and its analysis. This paper presents a general methodology to incorporate regression AI into system dynamics models for simulation and analysis. To demonstrate the validity of the methodology, a case study involving a susceptible‐infected‐recovered model and empirical data from the COVID‐19 pandemic is performed using support vector machines (SVMs), artificial neural networks (ANNs), and random forests.
Smart city maturity models: A multidimensional synthesized approach
Authors: Ghazinoory Sepehr , Roshandel Jinus , Parvin Fatemeh , Nasri Shohreh , Fatemi Mehdi 
Published: September 2023

AbstractSmart cities are one of the consequences of digital transformation, and there have been many attempts to assess the smartness of cities with various frameworks. Among these frameworks, smart city maturity models (SCMMs) evaluate the existing conditions of cities and provide guidelines for progressing through the subsequent stages of maturity. However, most maturity models follow the instructions of the first model, published by the International Data Corporation, and there are many similarities across the models. These maturity models have advantages and disadvantages, while previous studies have not addressed the differences. Therefore, this article fills this knowledge gap by systematically reviewing the existing SCMMs. The findings suggest that some trending topics, such as resiliency concerning global pandemics and cultural aspects are neglected in SCMMs. Moreover, the validation techniques of the models are not rational. Finally, given the theoretical nature of most models, they cannot be applied to multiple regions.This article is categorized under:
Fundamental Concepts of Data and Knowledge > Big Data Mining
Technologies > Artificial Intelligence
Technologies > Machine Learning
Exploring groundwater–climate change interactions: A critical review of Groundwater and Climate Change: Multi‐Level Law and Policy Perspectives by Philippe Cullet
Authors: Fatima Kulsum 
Published: September 2023

AbstractIn recent years, climate change has gained much attention worldwide, emphasizing the need to find sustainable solutions to protect the planet's resources. One of the primary resources affected by climate change is groundwater, a vital source of freshwater for agriculture and domestic use worldwide. In his book Groundwater and Climate Change: Multi‐Level Law and Policy Perspectives, Philippe Cullet discusses the complex relationship between groundwater and climate change and its legal and policy implications at various levels of interventions. Cullet's book provides comprehensive insights into the legal and governance frameworks needed to protect and sustainably manage groundwater in the face of climate change. This book review will examine the key arguments presented by Cullet, providing a critical analysis of the book's contribution to the field of environmental law and policy. It aims to provide a comprehensive analysis of the legal and policy framework related to groundwater management in the context of climate change with a special focus on interaction between climate change and groundwater lessons in Indian context.
Towards Memory-Efficient Training for Extremely Large Output Spaces – Learning with 670k Labels on a Single Commodity GPU
Authors: Schultheis Erik , Babbar Rohit 
Published: September 2023

AbstractIn classification problems with large output spaces (up to millions of labels), the last layer can require an enormous amount of memory. Using sparse connectivity would drastically reduce the memory requirements, but as we show below, applied naïvely it can result in much diminished predictive performance. Fortunately, we found that this can be mitigated by introducing an intermediate layer of intermediate size. We further demonstrate that one can constrain the connectivity of the sparse layer to be of constant fan-in, in the sense that each output neuron will have the exact same number of incoming connections, which allows for more efficient implementations, especially on GPU hardware. The CUDA implementation of our approach is provided at https://github.com/xmc-aalto/ecml23-sparse.
Probing the electroweak

final state in type I 2HDM at the LHC
Authors: Sanyal Prasenjit , Wang Daohan 
Published: September 2023

Abstract
Most of the experimental searches of the non-Standard Model Higgs boson(s) at the LHC rely on the QCD induced production modes. However, in some beyond Standard Model frameworks, the additional Higgs bosons can have fermiophobic behaviour. The type I two Higgs doublet model considered here is a perfect example where all the additional Higgs bosons exhibit fermiophobic nature over a large region of parameter space. Thus the electroweak productions of these new Higgs bosons are more dominant over the QCD induced processes. In scenarios with light pseuodoscalar (A) which is bound to decay dominantly to $$ b\overline{b} $$
b

b
¯

, even being fermiophobic, the 4b + W state via pp → H±A → (AW)A → 4b + W and followed by the leptonic decay of W boson can surpass the QCD initiated 4b final state. However, the signal gets overshadowed by large $$ t\overline{t} $$
t

t
¯

+jets background and hence constructing a suitable discriminator based on the signal hypothesis and signal topology is necessary. We devised a χ2 variable as the most suitable signal-background discrimintor to reduce the background by a sizable amount and showed the discovery reach (> 3σ) of the electroweak initiated "Image missing" final state at the LHC.
A coherent view of the quark-gluon plasma from energy correlators
Authors: Andres Carlota , Dominguez Fabio , Holguin Jack , Marquet Cyrille , Moult Ian 
Published: September 2023

AbstractThe ability to measure detailed aspects of the substructure of high-energy jets traversing the quark-gluon plasma (QGP) has provided a new window into its internal dynamics. However, drawing robust conclusions from traditional jet substructure observables has been difficult. In this manuscript we expand on a new approach to jet substructure in heavy-ion collisions based on the study of correlation functions of energy flow operators (energy correlators). We compute the two-point energy correlator of an in-medium massless quark jet and perform a detailed numerical analysis of the produced spectra. Our calculation incorporates vacuum radiation resummed at next-to-leading log accuracy together with the leading order contribution in medium-induced splittings evaluated through the BDMPS-Z multiple scattering and GLV single scattering formalisms for a static brick of QGP. Our analysis demonstrates how particular features of the modifications of in-medium splittings are imprinted in the correlator spectra, particularly showing how energy correlators may be used to extract the onset of colour coherence. We further present a comprehensive discussion on the accuracy and limitations of our study emphasizing how it can be systematically improved. This work sets the foundations for a rich program studying energy correlators in heavy-ion collisions.
Holographic entanglement as nonlocal magnetism
Authors: Gürsoy Umut , Pedraza Juan F. , Planas Guim Planella 
Published: September 2023

Abstract
The Ryu-Takayanagi prescription can be cast in terms of a set of microscopic threads that help visualize holographic entanglement in terms of distillation of EPR pairs. While this framework has been exploited for regions with a high degree of symmetry, we take the first steps towards understanding general entangling regions, focusing on AdS4. Inspired by simple constructions achieved for the case of disks and the half-plane, we reformulate bit threads in terms of a magnetic-like field generated by a current flowing through the boundary of the entangling region. The construction is possible for these highly symmetric settings, leading us to a modified Biot-Savart law in curved space that fully characterizes the entanglement structure of the state. For general entangling regions, the prescription breaks down as the corresponding modular Hamiltonians become inherently nonlocal. We develop a formalism for general shape deformations and derive a flow equation that accounts for these effects as a systematic expansion. We solve this equation for a complete set of small deformations and show that the structure of the expansion explicitly codifies the expected nonlocalities. Our findings are consistent with numerical results existing in the literature, and shed light on the fundamental nature of quantum entanglement as a nonlocal phenomenon.
An eight loop amplitude via antipodal duality
Authors: Dixon Lance J. , Liu Yu-Ting 
Published: September 2023

Abstract
We compute the six-particle maximally-helicity-violating (MHV) amplitude in planar $$ \mathcal{N} $$
N
= 4 super-Yang-Mills theory at eight loops, using antipodal duality and the recently computed eight-loop three-point form factor for the chiral stress energy tensor multiplet. Antipodal duality maps the form factor symbol to the amplitude symbol on a two-dimensional parity-preserving surface in the three-dimensional amplitude kinematics. There are remarkably few ambiguities in lifting from two to three dimensions, nor in promoting the symbol to a function. The amplitude passes many tests, including near-collinear, multi-Regge, factorization, self-crossing and origin limits. These checks also constitute a validation of antipodal duality at eight loops.
The Center of Distances of Central Cantor Sets
Authors: Banakiewicz Michał 
Published: September 2023

AbstractThe center of distances of central Cantor sets is investigated. Any central Cantor set is an achievement set of exactly one fast convergent sequence $$(a_n)$$

(

a
n

)

. We show that the center of distances of the central Cantor set is the union of all centers of distances of $$F_n$$

F
n

where $$F_n$$

F
n

is the set of all n-initial subsums of the series $$\sum a_n$$

∑

a
n

. Moreover, we give a necessary and sufficient condition for central Cantor sets to have not the minimal possible center of distances.
Characterizing lignins from various sources and treatment processes after optimized sample preparation techniques and analysis via ESI-HRMS and custom mass defect software tools
Authors: Letourneau Dane R. , Marzullo Bryan P. , Alexandridou Anastasia , Barrow Mark P. , O’Connor Peter B. , Volmer Dietrich A. 
Published: September 2023

AbstractSample preparation of complex, natural mixtures such as lignin prior to mass spectrometry analysis, however minimal, is a critical step in ensuring accurate and interference-free results. Modern shotgun-MS techniques, where samples are directly injected into a high-resolution mass spectrometer (HRMS) with no prior separation, usually still require basic sample pretreatment such as filtration and appropriate solvents for full dissolution and compatibility with atmospheric pressure ionization interfaces. In this study, sample preparation protocols have been established for a unique sample set consisting of a wide variety of degraded lignin samples from numerous sources and treatment processes. The samples were analyzed via electrospray (ESI)-HRMS in negative and positive ionization modes. The resulting information-rich HRMS datasets were then transformed into the mass defect space with custom R scripts as well as the open-source Constellation software as an effective way to visualize changes between the samples due to the sample preparation and ionization conditions as well as a starting point for comprehensive characterization of these varied sample sets. Optimized conditions for the four investigated lignins are proposed for ESI-HRMS analysis for the first time, giving an excellent starting point for future studies seeking to better characterize and understand these complex mixtures.
Graphical Abstract
The Geometry of the Space of Vortices on a Two-Sphere in the Bradlow Limit
Authors: Lara R. I. García , Speight J. M. 
Published: September 2023

AbstractIt is proved that the normalized$$L^2$$L2metric on the moduli space ofn-vortices on a two-sphere, endowed with any Riemannian metric, converges uniformly in the Bradlow limit to the Fubini–Study metric. This establishes, in a rigorous setting, a longstanding informal conjecture of Baptista and Manton.