bluuebunny/crossref_metadata_2025_split huggingface dataset:
Textured Asymmetric Membrane Electrode Assemblies of Piezoelectric Phosphorene and Ti3C2Tx MXene Heterostructures for Enhanced Electrochemical Stability and Kinetics in LIBs
Authors: Li Yihui , Xie Juan , Wang Ruofei , Min Shugang , Xu Zewen , Ding Yangjian , Su Pengcheng , Zhang Xingmin , Wei Liyu , Li Jing-Feng , Chu Zhaoqiang , Sun Jingyu , Huang Cheng 
Published: January 2024

AbstractBlack phosphorus with a superior theoretical capacity (2596 mAh g−1) and high conductivity is regarded as one of the powerful candidates for lithium-ion battery (LIB) anode materials, whereas the severe volume expansion and sluggish kinetics still impede its applications in LIBs. By contrast, the exfoliated two-dimensional phosphorene owns negligible volume variation, and its intrinsic piezoelectricity is considered to be beneficial to the Li-ion transfer kinetics, while its positive influence has not been discussed yet. Herein, a phosphorene/MXene heterostructure-textured nanopiezocomposite is proposed with even phosphorene distribution and enhanced piezo-electrochemical coupling as an applicable free-standing asymmetric membrane electrode beyond the skin effect for enhanced Li-ion storage. The experimental and simulation analysis reveals that the embedded phosphorene nanosheets not only provide abundant active sites for Li-ions, but also endow the nanocomposite with favorable piezoelectricity, thus promoting the Li-ion transfer kinetics by generating the piezoelectric field serving as an extra accelerator. By waltzing with the MXene framework, the optimized electrode exhibits enhanced kinetics and stability, achieving stable cycling performances for 1,000 cycles at 2 A g−1, and delivering a high reversible capacity of 524 mAh g−1 at − 20 ℃, indicating the positive influence of the structural merits of self-assembled nanopiezocomposites on promoting stability and kinetics.
Thermal Analysis of Ductile Iron: A New Way to Predict the Mechanical Properties
Authors: Schüssler J. , Bührig-Polaczek A. 
Published: January 2024

AbstractThermal analysis is characterized by the recording and evaluation of the temperature curve over time. Due to the correlation between transformation temperatures and chemical composition, thermal analysis is used to determine the carbon and silicon content. Furthermore, the aim is to be able to predict mechanical properties by thermal analysis. However, all current prediction methods refer to the cooling conditions in the investigated casting area and do not allow any transfer to other cooling conditions. There is a lack of a direct and automatic prediction of the mechanical properties from the thermal analysis before casting and transfer to other cooling conditions. For this study, cooling curves from the last 10 years at the Foundry Institute at RWTH Aachen University were evaluated and correlated with the mechanical properties from castings with three different thermal modules. The results of this empirical regression analysis are equations for the investigated mechanical parameters, which can be automatically filled with the characteristic times and temperatures of a thermal analysis in the casting process and the thermal modulus from the casting. For this modulus, the user can insert a corresponding value of the structural casting part that is relevant to the quality requirements in the foundry.
3D simulation of pulsatile bubbly flow resembling decompression sickness conditions inside a realistic human artery
Authors: Evgenidis Sotiris P. , Karapantsios Thodoris D. 
Published: January 2024

AbstractI-VED (In-Vivo Embolic Detector) is a novel diagnostic tool for non-invasive, real-time detection of bubbles in humans. Bubbles are precursors of decompression sickness (DCS), which can be encountered in astronauts, scuba divers, etc. I-VED exploits an EU patented electrical impedance spectroscopy technology, developed under the umbrella of a European Space Agency project. So far, I-VED has been calibrated and validated in vitro. In view of the forthcoming in-vivo trials, it needs to be configured for sensing bubbles in the bloodstream. For this, 3D computational fluid dynamics simulation is performed to investigate axial and radial variation of void fraction (α) and flow velocity (U) in a pulsatile bubbly flow inside a realistic human artery (diameter: 5–20 mm, implying vessel dilatation or contraction), where liquid velocity, bubble size, and void fraction resemble DCS conditions. Results show that U and α show a core-peaking profile despite the variation of artery diameter, while 3D sharp turns yield U and α non-uniformities in the angular direction that do not affect mean void fraction across the artery. Obtained knowledge allows deeper insight on the physics and spatial characteristics of bubbly flow in a real artery, which is useful in the design of measuring volume and tuning of I-VED.
A GMEE-WFED System: Optimizing Wind Turbine Distribution for Enhanced Renewable Energy Generation in the Future
Authors: Salman Mahdi Abed , Mahdi Muhammed Abaid , Al-Janabi Samaher 
Published: January 2024

AbstractThis paper presents the Generation Max Electrical Energy from Wind Friendly Environment Database (GMEE-WFED) system, a groundbreaking innovation aimed at enhancement the performance and energy output of wind power generation stations. The GMEE-WFED system has been meticulously designed to provide precise wind power forecasting within distributed turbine systems, facilitating the seamless integration of renewable energy into the grid. This forecasting is enabled by the utilization of the Spatial Dynamic Wind Power Forecasting (SDWPF) dataset, which takes into account the spatial distribution and dynamic characteristics of wind turbines. The GMEE-WFED system comprises five layers, each offering unique advantages. The first layer, referred to as the "Best Distribution of Turbines Based on DOA (BDT-DOA)," is designed to achieve the following objectives: (a) increase power generation, (b) determine the optimal coordinates (x, y) for each turbine, and (c) distribute turbines based on the best locations. The second layer, named the "Effect Features Layer (EF)," focuses on: (a) identifying the impact of features on wind power generation, (b) streamlining implementation time, and (c) reducing computational demands. The third layer, denoted as the "Average and Shifting up Target Layer (AEH-SUV)," serves the purposes of: (a) enhancing accuracy by calculating feature averages, and (b) predicting future active power through target shifting at different intervals (ranging from 1 to 6 h). Meanwhile, the fourth layer is associated with the development of a prediction model based on a deep learning technique known as "Deep Learning-Long Short-Term Memory (DL-LSTM) Layer," which is utilized for: (a) forecasting future energy production, (b) evaluating model accuracy at varying intervals, and (c) assessing overall model effectiveness. The final layer is also dedicated to constructing a prediction model, but it leverages a different deep learning technique called "Deep Learning Gate Recurrent Unit (DL-GRU)." These models contribute to accurate wind power predictions at various intervals and ensure the overall effectiveness of the system. Experimental results have shown that DL-GRU outperforms DL-LSTM in all shifting cases, underscoring the system's effectiveness in predicting future wind power generation and forecasting accuracy. As a result, the GMEE-WFED system is a pioneering approach that enhances wind DC-power generation forecasting. The GMEE-WFED system, with its intricate layers and advanced modeling techniques, represents a significant leap forward in harnessing the potential of wind energy for a more sustainable future.
Variations in Hospital Admissions of Non-Communicable Disease Patients Before and During The COVID-19 Pandemic (A Tertiary Care Setting, January 2018–June 2021)
Authors: Kara Seyma Aliye , Cakir Banu 
Published: January 2024

Abstract
Background
This study aimed to analyze the variations (if any) in hospital admissions of patients with any of the five common non-communicable diseases (NCDs), based on secondary analysis of electronic health records of patients admitted to Hacettepe University Hospitals at least once, from January 1, 2018 through June 15, 2021.

Design
Data were recruited from hospital’s electronic health records on patients with diagnoses of ischemic heart disease, hypertension, diabetes, cancer, and chronic obstructive pulmonary disease, using relevant ICD-10 codes.

Results
Compared to the corresponding time span in the pre-pandemic period, the number of hospital admissions of patients with selected five NCDs significantly decreased during the pandemic, with an official start in Turkey on March 11, 2020. Number of total-, out-patient-, and in-patient admissions of NCD patients were significantly lower in the pandemic period compared to the expected values in time series analysis, controlling for patient characteristics, and seasonality.

Conclusions
Study findings suggest that there has been a prominent impediment in NCD patients’ access to, and/or use of health care services over the pandemic, which might evolve to higher admission rates, severity and fatality of such patients in the upcoming years. Further studies are warranted for confirmation of our findings in other care settings, with individual-based data on care compensation through settings other than regular admission sites (if any), and/or the reasons for under-use of services.
Consumer Willingness to Pay for Visually Imperfect Organic Kale
Authors: Behler Shane , de Figueiredo Silva Felipe , Vassalos Michael , Ureta Joan U. 
Published: January 2024

AbstractCosmetic standards implemented by grocery stores are a substantial barrier to farmers who want to market visually imperfect (VI) produce. However, in recent years, efforts to market VI produce grocery stores have increased. In this study, we estimate the willingness to pay (WTP) for VI organic kale in the Southeastern U.S. using a payment card approach. The results indicate that WTP does not increase when additional information is provided, decreases when areas of imperfections are highlighted, and it is impacted by several consumer characteristics. A profitability case study for a large organic kale producer is also presented.
Disturbance observer-based fixed-time control for hypersonic morphing vehicles with uncertainties
Authors: Zhang H. , Wang P. , Tang G. , Bao W. 
Published: January 2024

AbstractThe attitude-tracking problem of hypersonic morphing vehicles (HMVs) is investigated in this research. After introducing variable-span wings, the optimal aerodynamic shape is available throughout the entire flight mission. However, the morphing wings cause significant changes in aerodynamic coefficients and mass distribution, challenging the attitude control. Therefore, a complete design procedure for the flight control system is proposed to address the issue. Firstly, the original model and the control-oriented model of HMVs are built. Secondly, in order to eliminate the influence caused by the multisource uncertainties, an adaptive fixed-time disturbance observer combined with fuzzy control theory is established. Thirdly, the fixed-time control method is developed to stabilise hypersonic morphing vehicles based on a multivariable sliding mode manifold. The control input can be obtained directly. Finally, the effectiveness of the proposed method is proved with the help of the Lyapunov theory and simulation results.
Would consumers accept CRISPR fruit crops if the benefit has health implications? An application to cranberry products
Authors: Ma Xueying , Gallardo Rosa Karina , Canales Elizabeth , Atucha Amaya , Zalapa Juan , Iorizzo Massimo 
Published: January 2024

AbstractCranberry products are perceived as healthy due to their high antioxidant content yet adding sugars to increase their palatability deters consumption. Plant breeding technologies such as gene editing, specifically the clustered regularly interspaced palindromic repeats (CRISPR), offer a plausible alternative to develop cranberries with desired traits (e.g., lower acidity and increased sweetness). We estimated consumers’ willingness to pay for sugar content, CRISPR, and cranberry flavor intensity for two cranberry products under different health-related information treatments. Respondents stated a discount for regular sugar content favoring reduced sugar products, for CRISPR compared to conventional breeding, and for weak/bland compared to full/intense cranberry flavor. Compensated valuation analysis of products with different attribute levels indicates that consumers were willing to pay a premium for cranberry products with reduced sugar content, CRISPR-bred, and full/intense cranberry flavor relative to products with regular sugar content, conventionally bred, and weak/bland flavor. Information treatments highlighting cranberries’ health benefits and recommendations to limit sugar intake increased consumers’ discounts for regular sugar content, surpassing the discount for CRISPR. This research underscores the importance of the conditions under which breeding technologies might gain public acceptance. This information will benefit the scientific community and industry seeking to use CRISPR to develop improved cranberry cultivars.
Provable observation noise robustness for neural network control systems
Authors: Krish Veena , Mata Andrew , Bak Stanley , Hobbs Kerianne , Rahmati Amir 
Published: January 2024

Abstract
Neural networks are vulnerable to adversarial perturbations: slight changes to inputs that can result in unexpected outputs. In neural network control systems, these inputs are often noisy sensor readings. In such settings, natural sensor noise – or an adversary who can manipulate them – may cause the system to fail. In this paper, we introduce the first technique to provably compute the minimum magnitude of sensor noise that can cause a neural network control system to violate a safety property from a given initial state. Our algorithm constructs a tree of possible successors with increasing noise until a specification is violated. We build on open-loop neural network verification methods to determine the least amount of noise that could change actions at each step of a closed-loop execution. We prove that this method identifies the unsafe trajectory with the least noise that leads to a safety violation. We evaluate our method on four systems: the Cart Pole and LunarLander environments from OpenAI gym, an aircraft collision avoidance system based on a neural network compression of ACAS Xu, and the SafeRL Aircraft Rejoin scenario. Our analysis produces unsafe trajectories where deviations under

$1{\rm{\% }}$

of the sensor noise range make the systems behave erroneously.
Hypercontractivity on the symmetric group
Authors: Filmus Yuval , Kindler Guy , Lifshitz Noam , Minzer Dor 
Published: January 2024

AbstractThe hypercontractive inequality is a fundamental result in analysis, with many applications throughout discrete mathematics, theoretical computer science, combinatorics and more. So far, variants of this inequality have been proved mainly for product spaces, which raises the question of whether analogous results hold over non-product domains.We consider the symmetric group,$S_n$, one of the most basic non-product domains, and establish hypercontractive inequalities on it. Our inequalities are most effective for the class ofglobal functionson$S_n$, which are functions whose$2$-norm remains small when restricting$O(1)$coordinates of the input, and assert that low-degree, global functions have smallq-norms, for$q>2$.As applications, we show the following:1.An analog of the level-dinequality on the hypercube, asserting that the mass of a global function on low degrees is very small. We also show how to use this inequality to bound the size of global, product-free sets in the alternating group$A_n$.2.Isoperimetric inequalities on the transposition Cayley graph of$S_n$for global functions that are analogous to the KKL theorem and to the small-set expansion property in the Boolean hypercube.3.Hypercontractive inequalities on the multi-slice and stability versions of the Kruskal–Katona Theorem in some regimes of parameters.
The INHABIT (synergIstic effect of aNtHocyAnin and proBIoTics in) Inflammatory Bowel Disease trial: a study protocol for a double-blind, randomised, controlled, multi-arm trial
Authors: Cosier Denelle , Lambert Kelly , Batterham Marijka , Sanderson-Smith Martina , Mansfield Kylie J , Charlton Karen 
Published: January 2024

Abstract
Ulcerative Colitis (UC), a type of Inflammatory Bowel Disease (IBD), is a chronic, relapsing gastrointestinal condition with increasing global prevalence. The gut microbiome profile of people living with UC differs from healthy controls and this may play a role in the pathogenesis and clinical management of UC. Probiotics have been shown to induce remission in UC; however, their impact on the gut microbiome and inflammation is less clear. Anthocyanins, a flavonoid subclass, have shown anti-inflammatory and microbiota-modulating properties; however, this evidence is largely preclinical. To explore the combined effect and clinical significance of anthocyanins and a multi-strain probiotic, a 3-month randomised controlled trial will be conducted in 100 adults with UC. Participants will be randomly assigned to one of four groups: anthocyanins (blackcurrant powder) + placebo probiotic, probiotic + placebo fruit powder, anthocyanin + probiotic, or double placebo. The primary outcome is a clinically significant change in the health-related quality-of-life measured with the Inflammatory Bowel Disease Questionnaire-32. Secondary outcomes include shotgun metagenomic sequencing of the faecal microbiota, faecal calprotectin, symptom severity, and mood and cognitive tests. This research will identify the role of adjuvant anti-inflammatory dietary treatments in adults with UC and elucidate the relationship between the gut microbiome and inflammatory biomarkers in this disease, to help identify targeted individualised microbial therapies. ANZCTR registration ACTRN12623000630617.
Slave labor productivity and wine output: Stellenbosch, 1680–1828
Authors: Fourie Johan , Greyling Jan 
Published: January 2024

AbstractThis paper examines wine output and slave labor productivity in the Dutch and British Cape Colony, leveraging annual tax censuses. We document a substantial increase in wine production, but, despite substantial institutional changes over more than a century, we find surprisingly stable median wine yields. Exploiting the farm-level nature of our data, we observe increasing heterogeneity in wine yields, suggesting that some farmers were able to realize productivity increases. We show that efficient slave labor utilization was a critical driver of productivity enhancement, largely unaffected by external factors.
Displays of anger in Turkish political discourse: a hard choice between cultural norms and political performance of anger
Authors: Akkaraca Kose Melike , Breeze Ruth 
Published: January 2024

AbstractThis paper examines the influence of cultural display rules on how high-status individuals, such as political leaders, publicly express anger. Specifically, it focuses on Recep Tayyip Erdoğan, who has been the Turkish leader since 2003. The study aims to understand the extent to which Erdoğan’s expression of anger is influenced by cultural display rules, the religious context stemming from his conservative electoral support, and his position as a long-term populist political leader. Using extended conceptual metaphor theory (ECMT) supported by corpus-assisted discourse analysis, the paper seeks to identify the contextual factors that shape anger expressions (both direct and metaphorical) in the political discourse of a populist leader in a collectivist culture. By comparing the conceptualization of ascribed anger and inscribed anger expressions, the analysis reveals that Erdoğan’s discourse presents two distinct scenarios for expressing anger toward ‘us’ and ‘others’. Additionally, it demonstrates how anger is strategically employed in culture-specific ways to navigate the challenges posed by conflicting contextual factors.
Divided Attitudes Toward Rectifying Injustice: How Preferences for Indigenous Policies Differ Between the Indigenous and Majority Populations of Norway and Sweden
Authors: Bergmann Fabian 
Published: January 2024

AbstractMost states acknowledge the significance of Indigenous rights to rectify past injustices. Yet, on the domestic level, the realization of these rights depends on national policies. For democratic societies, questions about public opinion toward Indigenous policies are thus of great interest but remain largely unstudied. To what extent does the ethnic majority support policies conducive to Indigenous rights realization? And how different are the Indigenous population’s policy preferences? I use original experimental data from a vignette study to investigate these questions in the case of the Sámi people in Norway and Sweden. I hypothesize that groups’ attitudes are shaped by policies’ potential to alter the social status hierarchy between the majority and Indigenous populations. The results provide a nuanced picture. The ethnic majority shows significantly less support for policies facilitating Sámi linguistic, self-governance, and territorial rights. While the Sámi have, in general, more positive attitudes toward such policies, their support seems to be less pronounced than the majority’s resistance. Moreover, as attitudes are surprisingly similar when compared between Norway and Sweden, a country’s existing policy context does not appear to be crucial in the formation of these preferences.
Evaluating the Minority Candidate Penalty with a Regression Discontinuity Approach
Authors: White Ariel , Shah Paru , Juenke Eric Gonzalez , Fraga Bernard L. 
Published: January 2024

AbstractDo parties face an electoral penalty when they nominate candidates of colour? We employ a regression discontinuity design using state legislative election data from 2018, 2019, and 2020 to isolate the effect of nominating a candidate of colour on a party's general election performance. Utilising this approach with real-world data heightens external validity relative to existing racial penalty studies, largely supported by surveys and experiments. We find no evidence that candidates of colour are disadvantaged in state legislative general elections relative to narrowly nominated white candidates from the same party. These findings challenge the leading explanations for the underrepresentation of racial/ethnic minority groups, with implications for candidate selection across the United States.