bluuebunny/crossref_metadata_2025_split huggingface dataset:
Doping Regulation Stabilizing δ‐MnO2 Cathode for High‐Performance Aqueous Aluminium‐ion Batteries
Authors: Chen Shuimei , Kong Yueqi , Tang Cheng , Gadelhak Nashaat Ahmed , Nanjundan Ashok Kumar , Du Aijun , Yu Chengzhong , Huang Xiaodan 
Published: March 2024

Abstractδ‐MnO2 is a promising cathode material for aqueous aluminium‐ion batteries (AAIBs) for its layered crystalline structure with large interlayer spacing. However, the excellent Al ion storage performance of δ‐MnO2 cathode remains elusive due to the frustrating structural collapse during the intercalation of high ionic potential Al ion species. Here, it is discovered that introducing heterogeneous metal dopants with high bond dissociation energy when bonded to oxygen can significantly reinforce the structural stability of δ‐MnO2 frameworks. This reinforcement translates to stable cycling properties and high specific capacity in AAIBs. Vanadium‐doped δ‐MnO2 (V‐δ‐MnO2) can deliver a high specific capacity of 518 mAh g−1 at 200 mA g−1 with remarkable cycling stability for 400 cycles and improved rate capabilities (468, 339, and 285 mAh g−1 at 0.5, 1, and 2 A g−1, respectively), outperforming other doped δ‐MnO2 materials and the reported AAIB cathodes. Theoretical and experimental studies indicate that V doping can substantially improve the cohesive energy of δ‐MnO2 lattices, enhance their interaction with Al ion species, and increase electrical conductivity, collectively contributing to high ion storage performance. These findings provide inspiration for the development of high‐performance cathodes for battery applications.
Advances of Layered Double Hydroxide‐Based Materials for Tumor Imaging and Therapy
Authors: Ma Ke , Chen Ke‐Zheng , Qiao Sheng‐Lin 
Published: March 2024

AbstractLayered double hydroxides (LDH) are a class of functional anionic clays that typically consist of orthorhombic arrays of metal hydroxides with anions sandwiched between the layers. Due to their unique properties, including high chemical stability, good biocompatibility, controlled drug loading, and enhanced drug bioavailability, LDHs have many potential applications in the medical field. Especially in the fields of bioimaging and tumor therapy. This paper reviews the research progress of LDHs and their nanocomposites in the field of tumor imaging and therapy. First, the structure and advantages of LDH are discussed. Then, several commonly used methods for the preparation of LDH are presented, including co‐precipitation, hydrothermal and ion exchange methods. Subsequently, recent advances in layered hydroxides and their nanocomposites for cancer imaging and therapy are highlighted. Finally, based on current research, we summaries the prospects and challenges of layered hydroxides and nanocomposites for cancer diagnosis and therapy.
Multi‐Task Residential Short‐Term Load Prediction Based on Contrastive Learning
Authors: Zhang Wuqing , Li Jianbin , Wu Sixing , Guo Yiguo 
Published: March 2024

AbstractLoad forecasting is crucial for the operation and planning of electricity generation, transmission, and distribution. In the context of short‐term electricity load prediction for residential users, single‐task learning methods fail to consider the relationship among multiple residential users and have limited feature extraction capabilities for residential load data. It is challenging to obtain sufficient information from individual residential user load predictions, resulting in poor prediction performance. To address these issues, we propose a framework for multi‐task residential short‐term load prediction based on contrastive learning. Firstly, clustering techniques are used to select residential users with similar electricity consumption patterns. Secondly, contrastive learning is employed for pre‐training, extracting trend and seasonal feature representations of load sequences, thereby enhancing the feature extraction capability for residential load Feature. Lastly, a multi‐task learning prediction framework is utilized to learn shared information among multiple residential users' loads, enabling short‐term load prediction for multiple residences. The proposed load prediction framework has been implemented on two real‐world load data sets, and the experimental results demonstrate that it effectively reduces the prediction errors for residential load prediction. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.
The development of gait and mobility: Form and function in infant locomotion
Authors: Hospodar Christina M. , Adolph Karen E. 
Published: March 2024

AbstractThe development of locomotion can be described by its form (i.e., gait) and its function (i.e., mobility). Both aspects of locomotion improve with experience. Traditional treatises on infant locomotion focus on form by describing an orderly progression of postural and locomotor milestones en route to characteristic patterns of crawling and walking gait. We provide a traditional treatment of gait by describing developmental antecedents of and improvements in characteristic gait patterns, but we highlight important misconceptions inherent in the notion of “milestones”. Most critically, we argue that the prevailing focus on gait and milestones fails to capture the true essence of locomotion—functional mobility to engage with the world. Thus, we also describe the development of mobility, including the use of mobility aids for support and propulsion. We illustrate how infants find individual solutions for mobility and how the ability to move cascades into other domains of development. Finally, we show how an integration of gait and mobility provides insights into the psychological processes that make locomotion functional.This article is categorized under:
Psychology > Motor Skill and Performance
Psychology > Development and Aging
Magnetic modulation of lysosomes for cancer therapy
Authors: Li Yingze , Lv Cheng , Li Zhenguang , Chen Chang , Cheng Yu 
Published: March 2024

AbstractLysosomes play a central role in biochemical signal transduction and oxidative stress in cells. Inducing lysosome membrane penetration (LMP) to cause lysosomal‐dependent cell death (LCD) in tumor cells is an effective strategy for cancer therapy. Chemical drugs can destroy the stability of lysosomes by neutralizing protons within the lysosomes or enhancing the fragility of the lysosomal membranes. However, there remain several unsolved problems of traditional drugs in LMP induction due to insufficient lysosomal targeting, fast metabolism, and toxicity in normal cells. With the development of nanotechnology, magnetic nanoparticles have been demonstrated to target lysosomes naturally, providing a versatile tool for lysosomal modulation. Combined with excellent tissue penetration and spatiotemporal manipulability of magnetic fields, magnetic modulation of lysosomes progresses rapidly in inducing LMP and LCD for cancer therapy. This review comprehensively discussed the strategies of magnetic modulation of lysosomes for cancer therapy. The intrinsic mechanisms of LMP‐induced LCD were first introduced. Then, the modulation of lysosomes by diverse physical outputs of magnetic fields was emphatically discussed. Looking forward, this review will shed the light on the prospect of magnetic modulation of lysosomes, inspiring future research of magnetic modulation strategy in cancer therapy.This article is categorized under:
Therapeutic Approaches and Drug Discovery > Emerging Technologies
Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease
Nanotechnology Approaches to Biology > Nanoscale Systems in Biology
Reducing the Gap Between Theory and Applications in Algorithmic Bayesian Persuasion
Authors: Castiglioni Matteo 
Published: March 2024

AbstractThis work focuses on the following question: is it possible to influence the behavior of self-interested agents through the strategic provision of information? This ‘sweet talk’ is ubiquitous among all sorts of economics and non-economics activities. In this work, we model these multi-agent systems as games between an informed sender and one or multiple receivers. We study the computational problem faced by an informed sender that wants to use his information advantage to influence rational receivers with the partial disclosure of information. In particular, the sender faces an information structure design problem that amounts to deciding ‘who gets to know what’. Bayesian persuasion provides a formal framework to model these settings as asymmetric-information games. In recent years, much attention has been given to Bayesian persuasion in the economics and artificial intelligence communities due also to the applicability of this framework to a large class of scenarios like online advertising, voting, traffic routing, recommendation systems, security, and product marketing. However, there is still a large gap between the theoretical study of information in games and its applications in real-world scenarios. This work contributes to close this gap along two directions. First, we study the persuasion problem in real-world scenarios, focusing on voting, routing, and auctions. While the Bayesian persuasion framework can be applied to all these settings, the algorithmic problem of designing optimal information disclosure polices introduces computational challenges related to the specific problem under study. Our goal is to settle the complexity of computing optimal sender’s strategies, showing when an optimal strategy can be implemented efficiently. Then, we relax stringent assumptions that limit the applicability of the Bayesian persuasion framework in practice. In particular, the classical model assumes that the sender has perfect knowledge of the receiver’s utility. We remove this assumption initiating the study of an online version of the persuasion problem. This is the first step in designing adaptive information disclosure policies that deal with the uncertainty intrinsic in all real-world applications.
Modern High-Level Synthesis: Improving Productivity with a Multi-level Approach
Authors: Curzel Serena 
Published: March 2024

AbstractHigh-Level Synthesis (HLS) tools simplify the design of hardware accelerators by automatically generating Verilog/VHDL code starting from a general-purpose software programming language. Because of the mismatch between the requirements of hardware descriptions and the characteristics of input languages, HLS tools still require hardware design knowledge and non-trivial design space exploration, which might be an obstacle for domain scientists seeking to accelerate applications written, for example, in Python-based programming frameworks. This research proposes a modern approach based on multi-level compiler technologies to bridge the gap between HLS and high-level frameworks, and to use domain-specific abstractions to solve domain-specific problems. The key enabling technology is the Multi-Level Intermediate Representation (MLIR), a framework that supports building reusable compiler infrastructure. The proposed approach uses MLIR to introduce new optimizations at appropriate levels of abstraction outside the HLS tool while still relying on years of HLS research in the low-level hardware generation steps; users and developers of HLS tools can thus increase their productivity, obtain accelerators with higher performance, and not be limited by the features of a specific (possibly closed-source) backend. The presented tools and techniques were designed, implemented, and tested to synthesize machine learning algorithms, but they are broadly applicable to any input specification written in a language that has a translation to MLIR. Generated accelerators can be deployed on Field Programmable Gate Arrays or Application-Specific Integrated Circuits, and they can reach high energy efficiency without any manual optimization of the code.
Social Innovation and Co-design for Climate Neutrality: The NetZeroCities Project
Authors: Bresciani Sabrina , Rizzo Francesca , Mureddu Francesco 
Published: March 2024

AbstractThe complex and urgent challenge of reaching carbon neutrality requires systemic changes of our current systems. Starting from the acknowledgment that technological solutions alone are not enough to reach climate neutrality at the required speed, social innovation becomes a crucial lever for accelerating systemic transformation. Several projects and scientific evidence outline the benefits of a people-centred and co-design approaches to transitions. Yet, public administrators, policy makers and urban transition teams have limited guidance on how to embed social innovations in their cities’ action plans, and on how to assess the progresses, outcomes and impacts of social innovation initiatives at urban level. Based on the work developed within the EU-funded project NetZeroCities, the book presents a framework for categorization of social innovation solutions for climate neutrality at city level, and a clustered catalogue of indicators, which can be utilized by cities’ public administrators to monitor and evaluate social innovation action plans to support people-centred, collaborative solutions to lower carbon emissions.
Introduction: Studying the Relationship Between Parties and Democracy
Authors: Fink-Hafner Danica 
Published: March 2024

AbstractIn the current world, there are many empirical challenges to both parties and democracy. A long-term simplistic view of the party–democracy relationship helps neither in understanding the current challenges nor in the context-sensitive analysis of parties and party systems and their relationship with democracy. This book critically assesses early liberal political thought and the trends in political thought since the 1970s. The main thesis, the research questions and the methodological approach are presented using several puzzles from the real world and from political science on the relationship between parties, party systems and democracy, and the novel ideas of the book are explained.
An eikonal-inspired approach to the gravitational scattering waveform
Authors: Georgoudis Alessandro , Heissenberg Carlo , Russo Rodolfo 
Published: March 2024

Abstract
We revisit the amplitude-based derivation of gravitational waveform for the scattering of two scalar black holes at subleading post-Minkowskian (PM) order. We take an eikonal-inspired approach to the two-massive-particle cut needed in the KMOC framework, as highlighted in [1], and show that its effect is to implement a simple change of frame. This clarifies one of the points raised in [2] when comparing with the post-Newtonian (PN) results. We then provide an explicit PM expression for the waveform in the soft limit, ω → 0, including the first non-universal, ω log ω, contribution. Focusing on this regime, we show that the small-velocity limit of our result agrees with the soft limit of the PN waveform of [2], provided that the two quantities are written in the same asymptotic frame. Performing the BMS supertranslation that, as discussed in [3], is responsible for the $$\mathcal{O}$$(G) static contribution to the asymptotic field employed in the PN literature, we find agreement between the amplitude-based and the PN soft waveform up to and including G3/c5 order.
Weak chaos and mixed dynamics in the string S-matrix
Authors: Savić Nikola , Čubrović Mihailo 
Published: March 2024

Abstract
We investigate chaotic dynamics in tree-level S-matrices describing the scattering of tachyons, photons and gravitons on highly excited open and closed bosonic strings, motivated by the string/black hole complementarity. The eigenphase spacing distribution and other indicators of quantum chaotic scattering suggest that the dynamics is only weakly chaotic, consisting of both regular/Poisson and chaotic/Wigner-Dyson processes. Only for special values of momenta and (for photon scattering) scattering angles do we find strong chaos of random matrix type. These special values correspond to a crossover between two regimes of scattering, dominated by short versus long partitions of the total occupation number of the highly excited string; they also maximize the information entropy of the S-matrix. The lack of strong chaos suggests that perturbative dynamics of highly excited strings can never describe the universal properties and maximal chaos of black hole horizons.
The NADase CD38 is a central regulator in gouty inflammation and a novel druggable therapeutic target
Authors: Alabarse Paulo Gil , Oliveira Patricia , Qin Huaping , Yan Tiffany , Migaud Marie , Terkeltaub Robert , Liu-Bryan Ru 
Published: March 2024

Abstract
Objectives
Cellular NAD+ declines in inflammatory states associated with increased activity of the leukocyte-expressed NADase CD38. In this study, we tested the potential role of therapeutically targeting CD38 and NAD+ in gout.

Methods
We studied cultured mouse wild type and CD38 knockout (KO) murine bone marrow derived macrophages (BMDMs) stimulated by monosodium urate (MSU) crystals and used the air pouch gouty inflammation model.

Results
MSU crystals induced CD38 in BMDMs in vitro, associated with NAD+ depletion, and IL-1β and CXCL1 release, effects reversed by pharmacologic CD38 inhibitors (apigenin, 78c). Mouse air pouch inflammatory responses to MSU crystals were blunted by CD38 KO and apigenin. Pharmacologic CD38 inhibition suppressed MSU crystal-induced NLRP3 inflammasome activation and increased anti-inflammatory SIRT3–SOD2 activity in macrophages. BMDM RNA-seq analysis of differentially expressed genes (DEGs) revealed CD38 to control multiple MSU crystal-modulated inflammation pathways. Top DEGs included the circadian rhythm modulator GRP176, and the metalloreductase STEAP4 that mediates iron homeostasis, and promotes oxidative stress and NF-κB activation when it is overexpressed.

Conclusions
CD38 and NAD+ depletion are druggable targets controlling the MSU crystal- induced inflammation program. Targeting CD38 and NAD+ are potentially novel selective molecular approaches to limit gouty arthritis.
Neonatal GABAergic transmission primes vestibular gating of output for adult spatial navigation
Authors: Jiang Qiufen , Wu Kenneth Lap-Kei , Hu Xiao-Qian , Cheung Man-Him , Chen Wenqiang , Ma Chun-Wai , Shum Daisy Kwok-Yan , Chan Ying-Shing 
Published: March 2024

AbstractGABAergic interneurons are poised with the capacity to shape circuit output via inhibitory gating. How early in the development of medial vestibular nucleus (MVN) are GABAergic neurons recruited for feedforward shaping of outputs to higher centers for spatial navigation? The role of early GABAergic transmission in assembling vestibular circuits for spatial navigation was explored by neonatal perturbation. Immunohistochemistry and confocal imaging were utilized to reveal the expression of parvalbumin (PV)-expressing MVN neurons and their perineuronal nets. Whole-cell patch-clamp recording, coupled with optogenetics, was conducted in vitro to examine the synaptic function of MVN circuitry. Chemogenetic targeting strategy was also employed in vivo to manipulate neuronal activity during navigational tests. We found in rats a neonatal critical period before postnatal day (P) 8 in which competitive antagonization of GABAergic transmission in the MVN retarded maturation of inhibitory neurotransmission, as evidenced by deranged developmental trajectory for excitation/inhibition ratio and an extended period of critical period-like plasticity in GABAergic transmission. Despite increased number of PV-expressing GABAergic interneurons in the MVN, optogenetic-coupled patch-clamp recording indicated null-recruitment of these neurons in tuning outputs along the ascending vestibular pathway. Such perturbation not only offset output dynamics of ascending MVN output neurons, but was further accompanied by impaired vestibular-dependent navigation in adulthood. The same perturbations were however non-consequential when applied after P8. Results highlight neonatal GABAergic transmission as key to establishing feedforward output dynamics to higher brain centers for spatial cognition and navigation.
The Effects of Layer-Induced Elastic Anisotropy on Microseismic Monitoring Records in Underground Coal Mines
Authors: Malovichko Liliya 
Published: March 2024

AbstractReal-time microseismic observations are extensively used in underground hard rock mines. However, microseismic monitoring in coal mines is not common. In this study, the features of microseismic (MS) event waveforms were discussed under conditions of thin-layered sedimentary media. The possibility of source mechanism evaluation was considered for the MS event recorded in coal mine. Moment tensor (MT) inversion of the waveforms can be challenging due to influence of thin-layered medium structure. Splitting of shear SH- and SV-waves is one of the characteristic features that affect MS records in coal mines. The effect of splitting was demonstrated using real microseismic data collected by an underground seismic array installed in the Polosukhinskaya coal mine, Russia. Velocities of shear SH- and SV-waves were estimated from travel times. The results reveal significant variations in shear wave velocities composed of a radial anisotropy of 75%, thus confirming the importance of a thin-layered model for moment tensor inversion. The thin-layered model was built for geological conditions at the Polosukhinskaya coal mine and synthetic seismograms were generated using QSEIS (Pyrocko OS). A full moment tensor of a single typical event was found employing the layered 1D velocity model.
Asthma bronchiale und allergische Rhinitis – die Hautprobe offenbart eine schwerwiegende Systemerkrankung
Authors: Wölbing Priscila , Dugas-Breit Susanne , Hartschuh Wolfgang , Toberer Ferdinand 
Published: March 2024

ZusammenfassungVorgestellt wird eine 30-jährige Patientin, die seit Jahren an initial unspezifischen Symptomen, wie rezidivierenden, nicht allergischen und nicht infektiösen Sinusitiden, „late onset“ Asthma bronchiale und ausgeprägter Lymphadenopathie litt. Erst nach Auftreten erster Hauterscheinungen konnte durch die Entnahme einer Probebiopsie die Diagnose einer eosinophilen granulomatösen Polyangiitis (EGPA) gestellt werden. Die EGPA ist eine schwerwiegende Systemerkrankung, die unbehandelt multiple Organschäden verursachen und sogar einen tödlichen Verlauf nehmen kann. Mit der adäquaten Behandlung verläuft die Erkrankung in mehr als 90 % der Fälle milde und kann oft sogar vollständig in Remission gehen. Durch die richtige Diagnosestellung konnte die Patientin adäquat und erfolgreich behandelt und das Risiko für Spätmanifestationen und Folgeschäden mit potenziell tödlichem Verlauf vermindert werden.
No association between long-chain n-3 fatty acid intake during pregnancy and risk of type 1 diabetes in offspring in two large Scandinavian pregnancy cohorts
Authors: Lund-Blix Nicolai A. , Bjerregaard Anne A. , Tapia German , Størdal Ketil , Brantsæter Anne Lise , Strøm Marin , Halldorsson Thorhallur I. , Granstrøm Charlotta , Svensson Jannet , Joner Geir , Skrivarhaug Torild , Njølstad Pål R. , Olsen Sjurdur F. , Stene Lars C. 
Published: March 2024

Abstract
Aims/hypothesis
The aim of this study was to investigate whether higher dietary intake of marine n-3 fatty acids during pregnancy is associated with a lower risk of type 1 diabetes in children.

Methods
The Danish National Birth Cohort (DNBC) and the Norwegian Mother, Father and Child Cohort Study (MoBa) together include 153,843 mother–child pairs with prospectively collected data on eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) intake during pregnancy from validated food frequency questionnaires. Type 1 diabetes diagnosis in children (n=634) was ascertained from national diabetes registries.

Results
There was no association between the sum of EPA and DHA intake during pregnancy and risk of type 1 diabetes in offspring (pooled HR per g/day of intake: 1.00, 95% CI 0.88, 1.14), with consistent results for both the MoBa and the DNBC. Robustness analyses gave very similar results.

Conclusions/interpretation
Initiation of a trial of EPA and DHA during pregnancy to prevent type 1 diabetes in offspring should not be prioritised.

Graphical Abstract