bluuebunny/crossref_metadata_2025_split huggingface dataset:
The collapse of a sonoluminescent cavitation bubble imaged with X-ray free-electron laser pulses
Authors: Hoeppe Hannes P , Osterhoff Markus , Aghel Maleki Atiyeh , Rosselló Juan M , Vassholz Malte , Hagemann Johannes , Engler Thea , Schwarz Daniel , Rodriguez-Fernandez Angel , Boesenberg Ulrike , Möller Johannes , Shayduk Roman , Hallmann Jörg , Madsen Anders , Mettin Robert , Salditt Tim 
Published: February 2024

Abstract
Single bubble sonoluminescence (SBSL) is the phenomenon of synchronous light emission due to the violent collapse of a single spherical bubble in a liquid, driven by an ultrasonic field. During the bubble collapse, matter inside the bubble reaches extreme conditions of several gigapascals and temperatures on the order of 10000 K, leading to picosecond flashes of visible light. To this day, details regarding the energy focusing mechanism rely on simulations due to the fast dynamics of the bubble collapse and spatial scales below the optical resolution limit. In this work we present phase-contrast holographic imaging with single x-ray free-electron laser (XFEL) pulses of a SBSL cavitation bubble in water. X-rays probe the electron density structure and by that provide a uniquely new view on the bubble interior and its collapse dynamics. The involved fast time-scales are accessed by sub-100 fs XFEL pulses and a custom synchronization scheme for the bubble oscillator. We find that during the whole oscillation cycle the bubble’s density profile can be well described by a simple step-like structure, with the radius R following the dynamics of the Gilmore model. The quantitatively measured internal density and width of the boundary layer exhibit a large variance. Smallest reconstructed bubble sizes reach down to

R
≃
0.8
μ

m

, and are consistent with spherical symmetry. While we here achieved a spatial resolution of a few 100 nm, the visibility of the bubble and its internal structure is limited by the total x-ray phase shift which can be scaled with experimental parameters.
Designing of high performance MoS2@VZnS//AC hybrid battery supercapacitor device for the electrochemical energy storage and glucose detection
Authors: Imran Muhammad , Akhtar Nabila , Muzaffar Nimra , Afzal Amir Muhammad , Iqbal Muhammad Waqas , Safdar Samia , Bahajjaj Aboud Ahmed Awadh , Mumtaz Sohail , Ansari Mohd Zahid , Ahmad Zubair 
Published: February 2024

Abstract
Due to their high conductive properties and superior specific capacitance, metal sulfides exhibit remarkable electrical conductivity. Transition metal dichalcogenides (TMDs) are regarded ideal options for energy harvesting devices due to their unique 2D arrangement and remarkable electrochemical properties. In this work, the typical exfoliation method (tip sonication method) was used to synthesize the molybdenum disulfide (MoS2). By using the hydrothermal method, the vanadium zinc sulfide is synthesized. The composite was analyzed through SEM, XRD, and XPS techniques to investigate its morphological, structural, and compositional characteristics comprehensively. The MoS2@VZnS electrode achieved a specific capacity (Qs) of 1025 Cg−1 at 3 mVs−1 after being tested in 1 M KOH. In a two-electrode set-up, activated carbon is used as a negative electrode, and MoS2@VZnS is used as a positive electrode for the fabrication of a hybrid supercapacitor. The asymmetric device has demonstrated a Qs of 285.4 Cg−1 at 1.4 Ag−1. The fabricated asymmetric supercapacitor device has manifested an excellent energy density (Ed) of 39.5 Whkg−1 and power density (Pd) of 2462.35 Wkg−1. Furthermore, in the durability test of MoS2@VZnS//AC, it exhibited an impressive capacity retention of 91.32% after enduring 5,000 cycles. Besides this, an investigation was conducted on a glucose electrochemical sensor utilizing MoS2@VZnS, to enhance its performance. The device showed extraordinary performance and considerable sensitivity against glucose, even up to a very high value. The multifunctional MoS2@VZnS nanocomposite electrode material provides new opportunities to design hybrid devices in energy storage devices and biomedical applications.
Constraints on the proton fraction of cosmic rays at the highest energies and the consequences for cosmogenic neutrinos and photons
Authors: Ehlert Domenik , van Vliet Arjen , Oikonomou Foteini , Winter Walter 
Published: February 2024

Abstract
Over the last decade, observations have shown that the mean mass of ultra-high-energy cosmic rays (UHECRs) increases progressively toward the highest energies. However, the precise composition is still unknown and several theoretical studies hint at the existence of a subdominant proton component up to the highest energies.
Motivated by the exciting prospect of performing charged-particle astronomy with ultra-high-energy (UHE) protons we quantify the level of UHE-proton flux that is compatible with present multimessenger observations and the associated fluxes of neutral messengers produced in the interactions of the protons.
We study this scenario with numerical simulations of two independent populations of extragalactic sources and perform a fit to the combined UHECR energy spectrum and composition observables, constrained by diffuse gamma-ray and neutrino observations.
We find that up to of order 10% of the cosmic rays at the highest energies can be UHE protons, although the result depends critically on the selected hadronic interaction model for the air showers. Depending on the maximum proton energy (E
max
p) and the redshift evolution of sources, the associated flux of cosmogenic neutrinos and UHE gamma rays can significantly exceed the multimessenger signal of the mixed-mass cosmic rays. Moreover, if E
max
p is above the GZK limit, we predict a large flux of UHE neutrinos above EeV energies that is absent in alternate scenarios for the origin of UHECRs. We present the implications and opportunities afforded by these UHE proton, neutrino and photon fluxes for future multimessenger observations.
Comprehensive profile and areal calibration by additively manufactured material measures
Authors: Eifler Matthias , Hering-Stratemeier Julian , von Freymann Georg , Seewig Jörg 
Published: February 2024

Abstract
The calibration of surface texture measuring instruments is standardized with two distinct types of material measures. ISO 25178-70 categorizes material measures that feature a profile and an areal surface topography. The result is that different types of measuring instruments like profilers on the one hand and areal surface topography measuring instruments on the other hand may require different material measures whose scope of application may be limited to only one of the named instrument types. The reason is that most manufacturing principles allow either a linear or circular extrusion of a geometry limiting the possibilities to manufacture material measures that are suitable for both, profile and areal surface topography measuring instruments. Since a comparability is desired for as many different measuring instruments as possible, we examine to what degree profile and areal material measures of ISO 25178-70 can be adapted and combined to possibly allow a calibration of all types of surface topography measuring instruments. Additive manufacturing with direct laser writing (DLW) is characterized by a high degree of freedom in the design of material measures. An enhancement of structures that can be imaged either in multiple lateral directions or extruded to circular geometries is possible, allowing both, a profile sampling in different directions, just as well as an areal measurement. In the present publication, a modification of the ISO 25178-70 material measures is described including the design process, the manufacturing and the measurement with areal and profile surface topography measuring instruments to practically demonstrate the feasibility of a multifunctional calibration that considers the possible effects of directionality. We show that it is possible to combine different profile and areal geometries by linear and/or areal extrusion of the corresponding profile-based geometry. By aligning multiple material measures onto one sample, it can also be demonstrated that a comprehensive calibration of an optical profiler is enabled with only one measurement.
Modeling the intention and usage of organic pesticide control using value-belief-norm model
Authors: Yang Qing , Al Mamun Abdullah , Reza Mohammad Nurul Hassan , Naznen Farzana , Masud Muhammad Mehedi 
Published: February 2024

Abstract
The degradation of farming lands caused by excessive pesticide usage is a growing concern. One of the most effective strategies for preventing this disaster from worsening is to commence organic pesticide management at a mass level. Although farmers depend highly on synthetic pesticides and fertilizers to obtain higher yields and profitable returns, the adoption of these synthetic inputs have remained surprisingly low in many agricultural contexts, spanning both developing and developed countries. The goal of this study is to utilize the Value-Belief-Norm (VBN) theory as a framework for understanding the critical sociopsychological factors influencing farmers’ decision to use organic pesticides. Specifically, this study aims to introduce and assess the impact of a new construct, i.e., the social norm withing the VBN framework. Additionally, this study empirically evaluates the core components of VBN theory and their causal relationship. The data was collected from 322 farmers from Zhoukou, Henan province, China using a survey questionnaire. The findings show that farmers’ egoistic values significantly impact the ecological worldview, despite the fact that biospheric values had no discernible effect. The ecological worldview also profoundly influences the farmers’ awareness of consequences and their personal norms. Although the study finds awareness of consequences to have no significant effect on personal norms, it has a substantial positive impact on ascription of responsibility. In addition, ascription of responsibility significantly influences farmers’ personal norms, which substantially impacts the intention to use organic pesticides. The results also reveal that farmers’ intentions significantly impact the usage of organic pesticides. The study’s findings can help strengthen essential factors among farmers that can improve their perception of organic agricultural methods, create strategies for managing controlled agrochemicals, and successfully stop environmental degradation by toxic inputs.
Surface segregation in high-entropy alloys from alchemical machine learning
Authors: Mazitov Arslan , Springer Maximilian A , Lopanitsyna Nataliya , Fraux Guillaume , De Sandip , Ceriotti Michele 
Published: February 2024

Abstract
High-entropy alloys (HEAs), containing several metallic elements in near-equimolar proportions, have long been of interest for their unique mechanical properties. More recently, they have emerged as a promising platform for the development of novel heterogeneous catalysts, because of the large design space, and the synergistic effects between their components. In this work we use a machine-learning potential that can model simultaneously up to 25 transition metals to study the tendency of different elements to segregate at the surface of a HEA. We use as a starting point a potential that was previously developed using exclusively crystalline bulk phases, and show that, thanks to the physically-inspired functional form of the model, adding a much smaller number of defective configurations makes it capable of describing surface phenomena. We then present several computational studies of surface segregation, including both a simulation of a 25-element alloy, that provides a rough estimate of the relative surface propensity of the various elements, and targeted studies of CoCrFeMnNi and IrFeCoNiCu, which provide further validation of the model, and insights to guide the modeling and design of alloys for heterogeneous catalysis.
Comparison of neural network architectures for feature extraction from binary black hole merger waveforms
Authors: Gramaxo Freitas Osvaldo , Calderón Bustillo Juan , Font José A , Nunes Solange , Onofre Antonio , Torres-Forné Alejandro 
Published: February 2024

Abstract
We evaluate several neural-network architectures, both convolutional and recurrent, for gravitational-wave time-series feature extraction by performing point parameter estimation on noisy waveforms from binary-black-hole mergers. We build datasets of 100 000 elements for each of four different waveform models (or approximants) in order to test how approximant choice affects feature extraction. Our choices include SEOBNRv4P and IMRPhenomPv3, which contain only the dominant quadrupole emission mode, alongside IMRPhenomPv3HM and NRHybSur3dq8, which also account for high-order modes. Each dataset element is injected into detector noise corresponding to the third observing run of the LIGO-Virgo-KAGRA (LVK) collaboration. We identify the temporal convolutional network architecture as the overall best performer in terms of training and validation losses and absence of overfitting to data. Comparison of results between datasets shows that the choice of waveform approximant for the creation of a dataset conditions the feature extraction ability of a trained network. Hence, care should be taken when building a dataset for the training of neural networks, as certain approximants may result in better network convergence of evaluation metrics. However, this performance does not necessarily translate to data which is more faithful to numerical relativity simulations. We also apply this network on actual signals from LVK runs, finding that its feature-extracting performance can be effective on real data.
Multiple case study of processes used by hospitals to select performance indicators: do they align with best practices?
Authors: Heenan Michael A , Randall Glen E , Evans Jenna M , Reid Erin M 
Published: February 2024

Abstract
Several health policy institutes recommend reducing the number of indicators monitored by hospitals to better focus on indicators most relevant to local contexts. To determine which indicators are the most appropriate to eliminate, one must understand how indicator selection processes are undertaken. This study classifies hospital indicator selection processes and analyzes how they align with practices outlined in the 5-P Indicator Selection Process Framework. This qualitative, multiple case study examined indicator selection processes used by four large acute care hospitals in Ontario, Canada. Data were collected through 13 semistructured interviews and document analysis. A thematic analysis compared processes to the 5-P Indicator Selection Process Framework. Two types of hospital indicator selection processes were identified. Hospitals deployed most elements found within the 5-P Indicator Selection Process Framework including setting clear aims, having governance structures, considering indicators required by health agencies, and categorizing indicators into strategic themes. Framework elements largely absent included: adopting evidence-based selection criteria; incorporating finance and human resources indicators; considering if indicators measure structures, processes, or outcomes; and engaging a broader set of end users in the selection process. Hospitals have difficulty in balancing how to monitor government-mandated indicators with indicators more relevant to local operations. Hospitals often do not involve frontline managers in indicator selection processes. Not engaging frontline managers in selecting indicators may risk hospitals only choosing government-mandated indicators that are not reflective of frontline operations or valued by those managers accountable for improving unit-level performance.
Unveiling the Genetic Landscape of Feed Efficiency in Holstein Dairy Cows: Insights into Heritability, Genetic Markers, and Pathways via Meta-Analysis
Authors: Jiang Wentao , Mooney Mark H , Shirali Masoud 
Published: February 2024

Abstract
Improving the feeding efficiency of dairy cows is a key component to improve the utilization of land resources and meet the demand for high-quality protein. Advances in genomic methods and omics techniques have made it possible to breed more efficient dairy cows through genomic selection. The aim of this review is to obtain a comprehensive understanding of the biological background of feed efficiency (FE) complex traits in purebred Holstein dairy cows including heritability estimate, and genetic markers, genes, and pathways participating in FE regulation mechanism. Through a literature search, we systematically reviewed the heritability estimation, molecular genetic markers, genes, biomarkers, and pathways of traits related to feeding efficiency in Holstein dairy cows. A meta-analysis based on a random-effects model was performed to combine reported heritability estimates of FE complex. The heritability of residual feed intake, dry matter intake, and energy balance was 0.20, 0.34, and 0.22, respectively, which proved that it was reasonable to include the related traits in the selection breeding program. For molecular genetic markers, a total of 13 single-nucleotide polymorphisms and copy number variance loci, associated genes, and functions were reported to be significant across populations. A total of 169 reported candidate genes were summarized on a large scale, using a higher threshold (adjusted P value &lt; 0.05). Then, the subsequent pathway enrichment of these genes was performed. The important genes reported in the articles were included in a gene list and the gene list was enriched by gene ontology (GO):biological process (BP), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis. Three GO:BP terms and four KEGG terms were statistically significant, which mainly focused on adenosine triphosphate (ATP) synthesis, electron transport chain, and OXPHOS pathway. Among these pathways, involved genes such as ATP5MC2, NDUFA, COX7A2, UQCR, and MMP are particularly important as they were previously reported. Twenty-nine reported biological mechanisms along with involved genes were explained mainly by four biological pathways (insulin-like growth factor axis, lipid metabolism, oxidative phosphorylation pathways, tryptophan metabolism). The information from this study will be useful for future studies of genomic selection breeding and genetic structures influencing animal FE. A better understanding of the underlying biological mechanisms would be beneficial, particularly as it might address genetic antagonism.
Perspective on alternative therapeutic feeds to treat severe acute malnutrition in children aged between 6 and 59 months in sub-Saharan Africa: a narrative review
Authors: Nitschke Marie-Claire Charlotte , Smollich Martin 
Published: February 2024

Abstract
Worldwide, nearly 200 million children younger than 5 years old suffer from stunting and wasting, 2 different types of undernutrition. Moreover, 45% of deaths among children in that age group are associated with these conditions. Severe acute malnutrition (SAM) refers to children with a weight-for-height z score &lt; −3, a midupper arm circumference &lt; 115 mm, or the presence of bilateral edema, and is especially prevalent in low- and middle-income countries. Undernutrition in children can have a major impact on both their physical and cognitive development. It can lead to infections and death if it remains undetected or untreated. The use of therapeutic feeds is an important component in the management of SAM, which remains a challenge in poorly resourced countries. The aim of this review was to assess the alternatives to the standard therapeutic foods used to treat SAM and to summarize their advantages and disadvantages, providing an overview of current research. A literature search was performed from September to November 2022 using PubMed, the Trip medical database, and the German Institute for Medical Documentation and Information (DIMDI). This review includes 13 randomized controlled trials testing alternatives to the standard therapeutic foods used to treat SAM by using alternative ingredients or a reduced dosage. The results show that, while a few alternative ready-to-use therapeutic food formulas lead to recovery rates similar to those seen with the standard protocol, many alternatives were less effective in the affected children. Thus, the evidence is not yet strong enough to change the World Health Organization’s guidelines. The review identifies promising results of treatment alternatives related to treatment outcomes and costs. Additional research should focus on the interventions that positively impact the recovery process of severely malnourished children to facilitate the treatment and enable greater treatment coverage worldwide.
Effector Repertoire of the Sweetpotato Black Rot Fungal PathogenCeratocystis fimbriata
Authors: Parada-Rojas Camilo H. , Stahr Madison , Childs Kevin L. , Quesada-Ocampo Lina M. 
Published: February 2024

In 2015, sweetpotato producers in the United States experienced one of the worst outbreaks of black rot recorded in history, with up to 60% losses reported in the field and packing houses and at shipping ports. Host resistance remains the ideal management tool to decrease crop losses. Lack of knowledge of Ceratocystis fimbriata biology represents a critical barrier for the deployment of resistance to black rot in sweetpotato. In this study, we scanned the recent near chromosomal-level assembly for putative secreted effectors in the sweetpotato C. fimbriata isolate AS236 using a custom fungal effector annotation pipeline. We identified a set of 188 putative effectors on the basis of secretion signal and in silico prediction in EffectorP. We conducted a deep RNA time-course sequencing experiment to determine whether C. fimbriata modulates effectors in planta and to define a candidate list of effectors expressed during infection. We examined the expression profile of two C. fimbriata isolates, a pre-epidemic (1990s) isolate and a post-epidemic (2015) isolate. Our in planta expression profiling revealed clusters of co-expressed secreted effector candidates. Based on fold-change differences of putative effectors in both isolates and over the course of infection, we suggested prioritization of 31 effectors for functional characterization. Among this set, we identified several effectors that provide evidence for a marked biotrophic phase in C. fimbriata during infection of sweetpotato storage roots. Our study revealed a catalog of effector proteins that provide insight into C. fimbriata infection mechanisms and represent a core catalog to implement effector-assisted breeding in sweetpotato.[Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .