bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Intrinsic Stable Layered Oxide Cathode for Practical Sodium‐Ion Battery: Solid Solution Reaction, Near‐Zero‐Strain and Marvelous Water Stability
Authors: Li Hong‐Wei , Li Jia‐Yang , Dong Hang‐Hang , Zhu Yan‐Fang , Su Yu , Wang Jing‐Qiang , Liu Ya‐Ning , Wen Chu‐Yao , Wang Zheng‐Jun , Chen Shuang‐Qiang , Zhang Zhi‐Jia , Wang Jia‐Zhao , Jiang Yong , Chou Shu‐Lei , Xiao Yao 
Published: November 2023

AbstractNon‐aqueous solvents, in particular N,N‐dimethylaniline (NMP), are widely applied for electrode fabrication since most sodium layered oxide cathode materials are readily damaged by water molecules. However, the expensive price and poisonousness of NMP unquestionably increase the cost of preparation and post‐processing. Therefore, developing an intrinsically stable cathode material that can implement the water‐soluble binder to fabricate an electrode is urgent. Herein, a stable nanosheet‐like Mn‐based cathode material is synthesized as a prototype to verify its practical applicability in sodium‐ion batteries (SIBs). The as‐prepared material displays excellent electrochemical performance and remarkable water stability, and it still maintains a satisfactory performance of 79.6% capacity retention after 500 cycles even after water treatment. The in situ X‐ray diffraction (XRD) demonstrates that the synthesized material shows an absolute solid‐solution reaction mechanism and near‐zero‐strain. Moreover, the electrochemical performance of the electrode fabricated with a water‐soluble binder shows excellent long‐cycling stability (67.9% capacity retention after 500 cycles). This work may offer new insights into the rational design of marvelous water stability cathode materials for practical SIBs.
Usefulness of open domain model for identifying missing software requirements concepts
Authors: Zhao Ziyan , Zhang Li , Lian Xiaoli 
Published: November 2023

SummaryDetecting missing requirements during software development is crucial to avoid unexpected consequences. However, this task is challenging due to limited domain knowledge of requirements analysts and the dynamic nature of software requirements. Previous studies have shown that requirement‐oriented domain models can help identify omissions in requirements, but they are often incomplete for many domains. Meanwhile, domain models constructed from other artifacts are available online. This raises the question: Can these domain models be useful in identifying missing functional information in requirement specifications? To address this question, we conducted a study to measure the overlap between entities in domain models and requirements. We analyzed the occurrence of overlapped entities, considering four distribution characteristics: the type of entities in the domain model, the distribution of mapped entities in the domain model, the family belonging of the mapped entities in the domain model, and the distribution of mapped entities in the requirements. Based on our findings, we proposed recommendations for missing requirements. Additionally, we performed experiments, including the use of the proposed metric “ancestors of the highest level with the most mapped entities” (AHME). The results showed significant improvements with gains of 146% and 223% in the two domains, highlighting the benefits of these distribution characteristics.
Evidenzlevel klinischer Interventionsstudien – Mind the biases
Authors: Deichsel Adrian , Günther Daniel , Mathis Dominic T. , Schüttler Karl F. , Wafaisade Arasch , Ackermann Jakob , Laky Brenda , Eggeling Lena , Kopf Sebastian , Herbst Elmar ,   Research-Komitee der Arbeitsgemeinschaft für Arthroskopie (AGA)
Published: November 2023

ZusammenfassungBei der Interpretation klinischer Studien sollten Verzerrungen (sog. Bias) berücksichtigt werden. Ein solcher Bias kann in sämtlichen klinischen Studien vorkommen und die Ergebnisse der Untersuchung auf relevante Art und Weise beeinflussen. Diese Verzerrungen können durch die Auswahl der Studienpatienten, die Untersucher, die Art sowie die Analyse der Daten auftreten. Das Ziel dieser Arbeit ist es, häufig auftretende Verzerrungen in klinischen Interventionsstudien zu beschreiben und Hinweise zu geben, wie diese erkannt werden können, um so die Bewertung von Literatur zu erleichtern.
The effect of high-pressure cutting fluid supply on the chip breakability of lead-free brass alloys
Authors: Müller Magdalena Susanne , Brans Kilian , Meurer Markus , Sørby Knut , Bergs Thomas 
Published: November 2023

AbstractTo improve machinability and in particular chip breakability, brass alloys are usually alloyed with small quantities of lead. Due to environmental and health concerns, the use of lead has been restricted in the last years. As lead-free brass alloys are progressively implemented in the industry, challenges arise due to their differing properties from traditional leaded brass alloys. One of the main challenges in automated continuous cutting processes is the worse chip breakability of lead-free brass alloys leading to longer and tangled chips. Hence, the impact of a high-pressure cutting fluid supply, as well as the impact of a chip-breaking geometry and the combined effect of both, has been investigated at different feeds. The three brass alloys CuZn37 (CW508L), CuZn38As (CW511L), and CuZn42 (CW510L) were studied at varying cutting fluid supply pressure levels and feed rates in a radial cutting operation. Cutting forces were measured, and chips were analyzed. No overall systematic impact of the cutting fluid supply pressure on the cutting forces was observed. In conclusion, increased pressure levels, a chip-breaking geometry, and an increased feed rate enhance the chip breakability of the investigated alloys.
Coherent Springer theory and the categorical Deligne-Langlands correspondence
Authors: Ben-Zvi David , Chen Harrison , Helm David , Nadler David 
Published: November 2023

AbstractKazhdan and Lusztig identified the affine Hecke algebra ℋ with an equivariant $K$
K
-group of the Steinberg variety, and applied this to prove the Deligne-Langlands conjecture, i.e., the local Langlands parametrization of irreducible representations of reductive groups over nonarchimedean local fields $F$
F
with an Iwahori-fixed vector. We apply techniques from derived algebraic geometry to pass from $K$
K
-theory to Hochschild homology and thereby identify ℋ with the endomorphisms of a coherent sheaf on the stack of unipotent Langlands parameters, the coherent Springer sheaf. As a result the derived category of ℋ-modules is realized as a full subcategory of coherent sheaves on this stack, confirming expectations from strong forms of the local Langlands correspondence (including recent conjectures of Fargues-Scholze, Hellmann and Zhu).In the case of the general linear group our result allows us to lift the local Langlands classification of irreducible representations to a categorical statement: we construct a full embedding of the derived category of smooth representations of $\mathrm{GL}_{n}(F)$

GL
n

(
F
)
into coherent sheaves on the stack of Langlands parameters.
Photovoltaic ZnO/SnSx heterostructures obtained by “electrochemical deposition-successive ionic layer adsorption and reaction” approach
Authors: Bogomazova Natalia V. , Kharytonau Dzmitry S. , Zharskii Ivan M. , Socha Robert P. 
Published: November 2023

AbstractIn this work, ZnO/SnS/indium tin oxide (ITO)/glass functional heterostructures have been developed using a combined approach of electrodeposition of a SnSx layer and successive ionic layer adsorption and reaction (SILAR) of the ZnO layer. The high-quality 400 nm-thick orthorhombic SnS0.9–0.95 films were formed on the ITO substrates with a thickness of 130 nm and an electrical conductivity of less than 40 Ω/□. Chemical deposition of ZnO thin films by the SILAR method allowed to deposit hexagonal films with a thickness of about 200 nm. The morphology, elemental and phase composition of the films were characterized by Scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, and X-ray diffraction. The band gap (1.4 eV for SnSx and 3.3 eV for ZnO), as well as the high light absorption coefficient of SnSx films (1–2) × 104 cm–1 were determined. The obtained ZnO/SnSx/ITO heterostructures formed by the electrodeposition–SILAR cycle showed a photoEMF value of 198 mV. These properties make ZnO/SnS heterostructure promising for low-cost solar cells based on affordable materials.
Die Genetik von Vorhofflimmern – auf dem Weg in die Präzisionsmedizin
Authors: Kany Shinwan , Schnabel Renate B. 
Published: November 2023

ZusammenfassungVorhofflimmern (VHF) ist eine verbreitete Herzkrankheit mit komplexer genetischer Grundlage. Trotz der Fortschritte in der Behandlung bleibt die Sterblichkeit bei VHF-Patienten hoch. Diese Übersichtsarbeit diskutiert die genetische Basis von VHF und ihre Auswirkungen auf Diagnose und Therapie. Während seit Langem eine hereditäre Komponente bei VHF bekannt war, wurden die ersten mit VHF assoziierten Gene in den frühen 2000er Jahren identifiziert. Mit Hilfe von genomweiten Assoziationsstudien (GWAS) wurden weitere Gene und zahlreiche genetische Varianten, die mit VHF in Verbindung stehen, identifiziert. Diese Studien haben fast 140 verschiedene, mit VHF assoziierte Regionen in der DNA aufgezeigt. Neben häufigen Varianten wurden auch seltene Varianten mit großen Auswirkungen identifiziert. Die Integration dieser genetischen Erkenntnisse in die klinische Praxis verspricht, die Diagnose und Behandlung von VHF zu verbessern und uns der Präzisionsmedizin näherzubringen. Es bleiben jedoch viele Herausforderungen, insbesondere besteht eine Diskrepanz für genetische Daten von Menschen mit nichteuropäischer Abstammung und an genetischen Analysen des therapeutischen Ansprechens.
Incorporating coarse and fine recycled aggregates into concrete mixes: mechanical characterization and environmental impact
Authors: Younes Ammar , Elbeltagi Emad , Diab Aboelkasim , Tarsi Giulia , Saeed Fam , Sangiorgi Cesare 
Published: November 2023

AbstractConcrete waste (CW) recycling stands as a promising strategy to promote sustainable construction practices. This research aims to assess the feasibility of using recycled concrete aggregates (RCA) as a surrogate for natural aggregates (NA) in concrete applications and reduce the environmental impact associated with the depletion of natural resources and landfill space. To achieve these objectives, CW was segregated from debris mixes of construction and demolition waste (CDW), collected, crushed, and graded to generate RCA. Thirty-two concrete samples were prepared and categorized into four distinct groups with 0% (reference), 50%, 75%, and 100% substitution levels for both coarse RCA (CRCA) and fine RCA (FRCA), all utilized simultaneously. Concurrently, the environmental impacts of producing 1 m3 of concrete were evaluated using a life cycle assessment (LCA) approach, (cradle-to-gate) covering three phases, the raw material supply (A1), transportation (A2) and concrete production (A3). At the 50% replacement level, the mechanical properties of recycled aggregate concrete (RAC) demonstrated a 20.0% increase in splitting tensile strength, accompanied by marginal decrease in workability (15.0%) and compressive strength (6.0%). In addition, at that percentage, the average environmental effects were reduced by 31.3%, with specific reductions of 34.7% for A1, 40.3% for A2, and no change in A3.
Implicit Sexual Cognitions in Women with Ambiphilic Sexual Attractions: A Comparison to Androphilic and Gynephilic Women
Authors: Snowden Robert J. , Gray Nicola S. , Uzzell Katie S. 
Published: November 2023

AbstractPrevious research using indirect cognitive measures (sometimes referred to as implicit measures) of sexual attraction have shown that women who are attracted to men (androphilic women) show category non-specific responses, whereas those who are attracted to women (gynephilic) show a category-specific bias to women. The purpose of the present study was to examine whether women who explicitly report approximately equal attraction to men and women (ambiphilic) would show similar non-category specific attraction at this implicit level or whether their responses would be more similar to those of gynephilic women. An implicit association task and a priming task were given to 169 women alongside measures of their self-labelled sexual orientation and an explicit measure of their sexual attraction to men and women. The results replicated previous findings of little bias towards either gender in androphilic women and of a strong bias towards females in gynephilic women. The ambiphilic women also showed a strong bias towards females. The findings clearly show that early automatic associations to sex are biased towards females in ambiphilic women and are not consistent with their explicit statements of preference.
Individual and area level factors associated with the breast cancer diagnostic-treatment interval in Queensland, Australia
Authors: Retell James D. , Cameron Jessica K. , Aitken Joanne F. , Youl Philippa , Pyke Chris , Dunn Jeff , Chambers Suzanne , Baade Peter D. 
Published: November 2023

Abstract
Background
Delays to breast cancer treatment can lead to more aggressive and extensive treatments, increased expenses, increased psychological distress, and poorer survival. We explored the individual and area level factors associated with the interval between diagnosis and first treatment in a population-based cohort in Queensland, Australia.

Methods
Data from 3216 Queensland women aged 20 to 79, diagnosed with invasive breast cancer (ICD-O-3 C50) between March 2010 and June 2013 were analysed. Diagnostic dates were sourced from the Queensland Cancer Registry and treatment dates were collected via self-report. Diagnostics-treatment intervals were modelled using flexible parametric survival methods.

Results
The median interval between breast cancer diagnosis and first treatment was 15 days, with an interquartile range of 9–26 days. Longer diagnostic-treatment intervals were associated with a lack of private health coverage, lower pre-diagnostic income, first treatments other than breast conserving surgery, and residence outside a major city. The model explained a modest 13.7% of the variance in the diagnostic-treatment interval $$\left( {R_{D}^{2} } \right)$$

R

D

2

. Sauerbrei’s D was 0.82, demonstrating low to moderate discrimination performance.

Conclusion
Whilst this study identified several individual- and area-level factors associated with the time between breast cancer diagnosis and first treatment, much of the variation remained unexplained. Increased socioeconomic disadvantage appears to predict longer diagnostic-treatment intervals. Though some of the differences are small, many of the same factors have also been linked to screening and diagnostic delay. Given the potential for accumulation of delay at multiple stages along the diagnostic and treatment pathway, identifying and applying effective strategies address barriers to timely health care faced by socioeconomically disadvantaged women remains a priority.
Investigating the moderating effects of social good and confidence on teachers' intention to prepare school students for artificial intelligence education
Authors: Sanusi Ismaila Temitayo , Ayanwale Musa Adekunle , Chiu Thomas K. F. 
Published: November 2023

AbstractArtificial Intelligence (AI) has triggered profound reforms across industries, including education. These developments necessitate the inclusion of AI as a subject in K-12 classrooms. However, the need for students to learn AI demands that educators pay increasing attention, believe in its relevance and intend to promote it among their students and colleagues. This paper aimed to explore teachers' perceptions of and behavioral intention to teach AI. We specifically considered the association of AI anxiety, perceived usefulness, attitude towards AI, AI relevance, AI readiness, and behavioral intention factors. This research further aims to examine the moderator effect of AI for social good and confidence on the relationship in our hypothesized research model. To address this purpose, a quantitative methodology with the use of structural equation modeling was utilized. Data were retrieved through an online questionnaire from 320 lower and upper secondary school in-service teachers, mostly in STEM-related fields. Our findings reveal that teacher perceptions of AI for social good and confidence will affect most relationships in the model. Teacher professional programs should include the benefits and risks of AI and good practice sharing.
Validation of detection efficiency-based corrections implemented in the k0-INRIM software
Authors: Di Luzio Marco , D’Agostino Giancarlo 
Published: November 2023

AbstractThe k0-INRIM is a software implemented at the Italian Metrology Institute (INRIM) to aid users elaborating data to obtain results including uncertainty budgets for Neutron Activation Analysis (NAA). The code relies on the efficiency evaluation based on an experimental characterization of the gamma detection system to calculate efficiency-based corrections. In order to validate the models adopted for these corrections in most demanding experimental conditions, an experiment is performed to collect data from point-like and extended-sources counted far from and near to the end-cap of two gamma detectors having different relative efficiency. The results comparing the experimentally evaluated and the calculated corrections are reported with detailed uncertainty estimation.
Balancing policy constraint and ensemble size in uncertainty-based offline reinforcement learning
Authors: Beeson Alex , Montana Giovanni 
Published: November 2023

AbstractOffline reinforcement learning agents seek optimal policies from fixed data sets. With environmental interaction prohibited, agents face significant challenges in preventing errors in value estimates from compounding and subsequently causing the learning process to collapse. Uncertainty estimation using ensembles compensates for this by penalising high-variance value estimates, allowing agents to learn robust policies based on data-driven actions. However, the requirement for large ensembles to facilitate sufficient penalisation results in significant computational overhead. In this work, we examine the role of policy constraints as a mechanism for regulating uncertainty, and the corresponding balance between level of constraint and ensemble size. By incorporating behavioural cloning into policy updates, we show empirically that sufficient penalisation can be achieved with a much smaller ensemble size, substantially reducing computational demand while retaining state-of-the-art performance on benchmarking tasks. Furthermore, we show how such an approach can facilitate stable online fine tuning, allowing for continued policy improvement while avoiding severe performance drops.
Pore Pressure Uncertainty Characterization Coupling Machine Learning and Geostatistical Modelling
Authors: Soares Amílcar , Nunes Rúben , Salvadoretti Paulo , Costa João Felipe , Martins Teresa , Santos Mario , Azevedo Leonardo 
Published: November 2023

AbstractPore pressure prediction is fundamental when drilling deep and geologically complex reservoirs. Even in relatively well-characterized hydrocarbon reservoir fields, with a considerable number of drilled wells, when located in challenging geological environments, poor prediction of abnormal pore pressure might result in catastrophic events that can cause harm to human lives and infrastructures. To better quantify drilling risks, the uncertainty associated with the pore pressure prediction should be integrated within the geo-modelling workflow. Leveraging a challenging real case from the Brazilian pre-salt, the work presented herein proposes a seismic-driven gradient pore pressure modelling workflow, which combines machine learning and geostatistical co-simulation to predict high-resolution gradient pore pressure volumes. First, existing angle-dependent seismic reflection data are inverted for P- and S-wave velocity and density. Then, K-nearest neighbor is used to create a regression model between pore pressure gradient and P- and S-wave velocity, density and depth based on the well log information. The trained model is applied to predict a three-dimensional gradient pore pressure model from the models obtained from geostatistical seismic inversion. This gradient pore pressure model is a smooth representation of the highly variable subsurface and is used as secondary variable in stochastic sequential co-simulation with joint probability distributions to generate multiple high-resolution realizations of gradient pore pressure. The ensemble of co-simulated models can be used to assess the spatial uncertainty about the gradient pore pressure predictions. The results of the application example show the ability of the method to reproduce the spatial patterns observed in the seismic data and to reproduce existing gradient pore pressure well logs at two blind well locations, which were not used to condition the gradient pore pressure predictions.
The semiclassical limit of a quantum Zeno dynamics
Authors: Cunden Fabio Deelan , Facchi Paolo , Ligabò Marilena 
Published: November 2023

AbstractMotivated by a quantum Zeno dynamics in a cavity quantum electrodynamics setting, we study the asymptotics of a family of symbols corresponding to a truncated momentum operator, in the semiclassical limit of vanishing Planck constant $$\hbar \rightarrow 0$$

ħ
→
0

and large quantum number $$N\rightarrow \infty $$

N
→
∞

, with $$\hbar N$$

ħ
N

kept fixed. In a suitable topology, the limit is the discontinuous symbol $$p\chi _D(x,p)$$

p

χ
D

(
x
,
p
)

where $$\chi _D$$

χ
D

is the characteristic function of the classically permitted region D in phase space. A refined analysis shows that the symbol is asymptotically close to the function $$p\chi _D^{(N)}(x,p)$$

p

χ
D

(
N
)

(
x
,
p
)

, where $$\chi _D^{(N)}$$

χ
D

(
N
)

is a smooth version of $$\chi _D$$

χ
D

related to the integrated Airy function. We also discuss the limit from a dynamical point of view.