bluuebunny/crossref_metadata_2025_split huggingface dataset:
Waving the same flag? Government legislation and obstructionism during the COVID-19 crisis in Italy
Authors: Gambacciani Paolo , Pedrazzani Andrea , Pinto Luca 
Published: January 2025

Abstract
This study examines the amendatory activities of the majority and opposition parties in the Italian 18th legislature (2018–2022) in response to the COVID-19 pandemic crisis. Following the rally around the flag hypothesis, we test whether both sides exhibited similar legislative behaviour during emergencies. We exploit an original database covering amendments tabled by Italian legislators on bills converting decree-laws. Results reveal that the COVID-19 pandemic affected amendment activities without aligning majority and opposition behaviours. In other words, the opposition did not pull in the same direction of the government legislation. This can be explained by contingent factors and pre-existing party polarization.
Global drag reduction and local flow statistics in Taylor–Couette turbulence with dilute polymer additives
Authors: Zhang Yi-Bao , Fan Yaning , Su Jinghong , Xi Heng-Dong , Sun Chao 
Published: January 2025

We present an experimental study on the drag reduction by polymers in Taylor–Couette turbulence at Reynolds numbers (

$Re$

) ranging from

$4\times 10^3$

to

$2.5\times 10^4$

. In this

$Re$

regime, the Taylor vortex is present and accounts for more than 50 % of the total angular velocity flux. Polyacrylamide polymers with two different average molecular weights are used. It is found that the drag reduction rate increases with polymer concentration and approaches the maximum drag reduction (MDR) limit. At MDR, the friction factor follows the

$-0.58$

scaling, i.e.

$C_f \sim Re^{-0.58}$

, similar to channel/pipe flows. However, the drag reduction rate is about

$20\,\%$

at MDR, which is much lower than that in channel/pipe flows at comparable

$Re$

. We also find that the Reynolds shear stress does not vanish and the slope of the mean azimuthal velocity profile in the logarithmic layer remains unchanged at MDR. These behaviours are reminiscent of the low drag reduction regime reported in channel flow (Warholic et al., Exp. Fluids, vol. 27, no. 5, 1999, pp. 461–472). We reveal that the lower drag reduction rate originates from the fact that polymers strongly suppress the turbulent flow while only slightly weaken the mean Taylor vortex. We further show that polymers steady the velocity boundary layer and suppress the small-scale Görtler vortices in the near-wall region. The former effect reduces the emission rate of both intense fast and slow plumes detached from the boundary layer, resulting in less flux transport from the inner cylinder to the outer one and reduces energy input into the bulk turbulent flow. Our results suggest that in turbulent flows, where secondary flow structures are statistically persistent and dominate the global transport properties of the system, the drag reduction efficiency of polymer additives is significantly diminished.
SRMR for Models with Covariates
Authors: McNeish Daniel , Matta Tyler H. 
Published: January 2025

Abstract
The standardized root mean squared residual (SRMR) is commonly reported to evaluate approximate fit of latent variable models. As traditionally defined, SRMR summarizes the discrepancy between observed covariance elements and implied covariance elements. However, current applications of latent variable models often include additional features like overidentified mean structures and covariates, to which the traditional SRMR definition is not applicable. To date, SRMR extensions for models with covariates have received limited attention. Nonetheless, mainstream software provide SRMR for models with covariates, but values differ based on model specification and differ across programs. The goal of this paper is to formalize SRMR definitions for models with covariates. We develop possible SRMR definitions corresponding to different model specifications with covariates, discussing the advantages and disadvantages of each. Importantly, some SRMR definitions are susceptible to confounding misfit and model size such that SRMR values systematically decrease and suggest better fit when covariates are present, even if covariates have null effects. The primary conclusion is that there may not be a single unifying SRMR definition for covariates, but practically, researchers reporting SRMR with covariates should be aware (a) which definition is being used and (b) which information is and is not included in the particular definition.
PKLM: A Flexible MCAR Test Using Classification
Authors: Spohn Meta-Lina , Näf Jeffrey , Michel Loris , Meinshausen Nicolai 
Published: January 2025

Abstract
We develop a fully nonparametric, easy-to-use, and powerful test for the missing completely at random (MCAR) assumption on the missingness mechanism of a dataset. The test compares distributions of different missing patterns on random projections in the variable space of the data. The distributional differences are measured with the Kullback-Leibler Divergence, using probability Random Forests (Malley et al., 2011). We thus refer to it as “Projected Kullback–Leibler MCAR” (PKLM) test. The use of random projections makes it applicable even if very few or no fully observed observations are available or if the number of dimensions is large. An efficient permutation approach guarantees the level for any finite sample size, resolving a major shortcoming of most other available tests. Moreover, the test can be used on both discrete and continuous data. We show empirically on a range of simulated data distributions and real datasets that our test has consistently high power and is able to avoid inflated type-I errors. Finally, we provide an R-package PKLMtest with an implementation of our test.
An Overall Test of Pairwise Mean Conditional Covariances in IRT
Authors: Ellis Jules L. , van der Ark L. Andries , Sijtsma Klaas 
Published: January 2025

Abstract
We study how the Conditioning on Added Regression Predictions (CARP) statistics from different item pairs can be aggregated into a single overall test of monotone homogeneity. As a pairwise statistic, we use the mean conditional covariance (MCC) or its standardized value (

$Z$

). We use three different estimates of the covariance matrix of the pairwise test statistics: (1) the covariance matrix of the MCCs, based on the sample moments; (2) the covariance matrix of the MCCs or

$Z$

s, based on bootstrapping; and (3) the covariance matrix of the

$Z$

s, equated to the identity matrix. We consider various aggregation methods, including (a) the chi-bar-square statistic; (b) the preselected standardized partial sum of pairwise statistics; (c) the product of preselected

$p$

-values; (d) the minimum of preselected

$p$

-values; and (e–h) the same statistics, but now conditioned on post-selecting only the negative values in the test sample. We study the Type 1 error rate and power of the ensuing 20 tests based on simulations. The tests with the highest power among the tests that control the Type I error rate are based on

$Z$

-statistics with the identity matrix: the conditional likelihood ratio test, the conditionalized product of

$p$

-values, the conditionalized sum of Z-values, and the preselected product of

$p$

-values.
State-Dependent Missingness in Hidden Markov Models, with an Application to Drop-Out in a Clinical Trial
Authors: Speekenbrink Maarten , Visser Ingmar 
Published: January 2025

Abstract
Establishing the effectiveness of treatments for psychopathology requires accurate models of its progression over time and the factors that impact it. Longitudinal data is however fraught with missingness, hindering accurate modeling. We re-analyse data on schizophrenia severity in a clinical trial using hidden Markov models (HMMs). We consider missing data in HMMs with a focus on situations where data is missing not at random (MNAR) and missingness depends on the latent states, allowing symptom severity to indirectly impact probability of missingness. In simulations, we show that including a submodel for state-dependent missingness reduces bias when data is MNAR and state-dependent, whilst not reducing accuracy when data is missing-at-random (MAR). When missingness depends on time, a model that allows missingness to be both state- and time-dependent is unbiased. Overall, these results show that modelling missingness as state-dependent and including relevant covariates is a useful strategy in applications of HMMs to time-series with missing data. Applying the model to data from a clinical trial, we find that drop-out is more likely for patients with less severe symptoms, which may lead to a biased assessment of treatment effectiveness.
Infinitesimal Jackknife Estimates of Standard Errors for Rotated Estimates of Redundancy Analysis: Applications to Two Real Examples
Authors: Gu Fei , Jarukasemthawee Somboon , Pisitsungkagarn Kullaya , van Dam Ynte K. 
Published: January 2025

Abstract
In redundancy analysis (RA), the redundancy variates are interpreted in terms of the predictor variables that have the prominent redundancy loadings. Israels (1986) advocated the rotation of redundancy loadings to facilitate the interpretation of the rotated redundancy variates. In this paper, the purpose is to obtain the standard error estimates for rotated redundancy loadings that can facilitate the interpretation of the rotated redundancy variates. To this end, we modify the original RA-L model (Gu et al., 2023) and specify two modified RA-L models for orthogonal and oblique rotations, separately. On the basis of the modified RA-L models, we describe the infinitesimal jackknife (IJ) method that can produce the standard error estimates for rotated RA estimates. A simulation study is conducted to validate the standard error estimates from the IJ method, and two real examples are used to demonstrate the use of the standard error estimates for rotated redundancy loadings. Finally, we summarize the paper and provide additional remarks regarding the rotation methods and the use of numeric derivatives in the implementation of the IJ method.
Association between composite dietary antioxidant index and chronic obstructive pulmonary disease in adults: results of NHANES 2015–2020 and Mendelian randomisation study
Authors: Xiang Zhiyi , Wang Heng 
Published: January 2025

Abstract
Oxidative stress is present in chronic obstructive pulmonary disease (COPD); however, the effect of increased dietary antioxidants on reducing COPD risk remains unclear. The aim of this study was to investigate the association of the composite dietary antioxidant index (CDAI) with COPD in adults. This study conducted a cross-sectional investigation using data from the National Health and Nutrition Examination Survey (NHANES) spanning from 2015 to March 2020 to explore the association between CDAI and COPD in adults. This study included 9295 participants. Three logistic regression models (crude model, partially adjusted model and fully adjusted model) and restricted cubic spline (RCS) curves were utilised to assess the association between CDAI levels and COPD risk. Subsequently, a two-sample Mendelian randomisation (MR) was employed to analyse the causal impact of antioxidant levels within CDAI on the occurrence of COPD. CDAI levels were inversely associated with COPD after adjusting for confounders (OR = 0·97, 95 % CI 0·95, 1·00), and the association was linear (P < 0·001), and the results of the RCS showed that CDAI was linearly correlated with COPD occurrence (P < 0·001). MR analysis revealed a causal relationship between vitamin C and COPD occurrence (OR = 0·99, 95 % CI 0·98, 1·00, P < 0·05). Our study indicates that dietary sources of antioxidants may reduce the risk of COPD occurrence, and the results of the MR analysis further show that vitamin C is causally associated with a reduced risk of COPD occurrence. However, further exploration is needed to understand how antioxidants prevent COPD.
Pre-diagnostic 25-hydroxyvitamin D levels and subsite-specific colorectal cancer risk: a nested case–control study from the Norwegian Women and Cancer Study (NOWAC)
Authors: Paulsen Elise Marlen , Braaten Tonje Bjørndal , Urbarova Ilona , Brustad Magritt 
Published: January 2025

Abstract
Colorectal cancer (CRC), the third most common cancer globally, causes over 900 000 deaths annually. Although vitamin D is observed to have potential anti-carcinogenic properties, research findings on its preventable effect against CRC remain inconclusive. Notably, different subsites within the colon and rectum may be associated with distinct risk factors. While some studies have explored this relationship with circulating 25-hydroxyvitamin D (25(OH)D), the results remain contradictory. Our study employed a nested case–control design, involving 775 CRC cases matched with 775 cancer-free controls based on age, region of living and the time of blood sampling. The study was conducted within the Norwegian Women and Cancer post-genome cohort, which comprises approximately 50 000 women. We measured pre-diagnostic circulating plasma 25(OH)D status 5–13 years before diagnosis. Adjustment variables were based on self-administered questionnaires and included BMI, physical activity level, smoking, intake of processed meat, calcium, alcohol and fibre. An increase of 5 nmol/l in 25(OH)D reduced the risk of proximal colon cancer by 6 % (OR = 0·94, 95 % CI 0·89, 0·99). Furthermore, a sensitivity analysis revealed a 62 % increased risk among the women with 25(OH)D levels below 50 nmol/l compared with sufficient levels, ≥ 50 to < 75 nmol/l (OR = 1·62, 95 % CI 1·01, 2·61). No association was found with CRC, colon or distal colon cancer. We observed a subsite-specific association between 25(OH)D and CRC, highlighting the need for further investigation to elucidate the potential underlying mechanisms and clinical implications.
Human‐Induced Climate Change Intensifies Extreme Precipitation Events in Central China's Urban Areas
Authors: Chen Yufan , Zhang Shuyu , Wang Hong , Chen Deliang , Liu Junguo 
Published: January 2025

AbstractUnderstanding the drivers behind extreme precipitation is crucial for predicting and mitigating the impacts of climate change globally, yet it remains little known how anthropogenic factors contribute to these phenomena. This study investigates the impact of human‐induced climate change on circulation patterns conducive to extreme precipitation over the Central Plains Urban Agglomeration in China, a region frequently experiencing severe flooding and home to a dense population with significant economic and agricultural activities. Using advanced techniques such as deep learning and optimal fingerprinting, this study identifies and analyzes the physical mechanisms behind the extreme precipitation. The findings reveal that greenhouse gas emissions play a pivotal role in altering atmospheric circulation patterns, specifically promoting the westward extension of western North Pacific subtropical high and northwestward shift of South Asian High, along with tropical cyclones. These changes enhance moisture transport and convective activity, leading to more frequent and intense precipitation events.
Resonant Scattering of Sub‐keV Electrons by Beam‐Driven Electron Cyclotron Harmonic Waves
Authors: Zhang Xu , Artemyev Anton , Angelopoulos Vassilis , Zhang Xiao‐Jia , Ma Qianli , An Xin , Jia Ying‐dong 
Published: January 2025

AbstractElectron cyclotron harmonic waves (ECH) play a key role in scattering and precipitation of plasma sheet electrons. Previous analysis on the resonant interaction between ECH waves and electrons assumed that these waves are generated by a loss cone distribution and propagate nearly perpendicular to the background magnetic field. Recent spacecraft observations, however, have demonstrated that such waves can also be generated by low energy electron beams and propagate at moderately oblique angles . To quantify the effects of this newly observed ECH wave mode on electron dynamics in Earth's magnetosphere, we use quasi‐linear theory to calculate the associated electron pitch angle diffusion coefficient. Utilizing THEMIS spacecraft measurements, we analyze in detail a few representative events of beam‐driven ECH waves in the plasma sheet and the outer radiation belt. Based on the observed wave properties and the hot plasma dispersion relation of these waves, we calculate their bounce‐averaged pitch angle, momentum and mixed diffusion coefficients. We find that these waves most efficiently scatter low‐energy electrons (10–500 eV) toward larger pitch angles, on time scales of to seconds. In contrast, loss‐cone‐driven ECH waves most efficiently scatter higher‐energy electrons (500 eV–5 keV) toward lower pitch‐angles. Importantly, beam‐driven ECH waves can effectively scatter ionospheric electron outflows out of the loss cone near the magnetic equator. As a result, these outflows become trapped in the magnetosphere, forming a near‐field‐aligned anisotropic electron population. Our work highlights the importance of ECH waves, particularly beam‐driven modes, in regulating magnetosphere‐ionosphere particle and energy coupling.
A Durable Electron Density Profile Near the Inner Edge of the Io Torus
Authors: Kurth W. S. , Hospodarsky G. B. , Faden J. B. , Menietti J. D. , Sulaiman A. H. , Elliott S. S. , Bagenal F. , Nerney E. G. , Connerney J. E. P. , Allegrini F. , Bolton S. J. 
Published: January 2025

AbstractThe Juno Waves instrument can be used to accurately determine the electron density inside Io's orbit, the inner Io torus. These observations have revealed a local peak in the electron density just inside M = 5 and at centrifugal latitudes above about 10 that is likely the ’cold torus' as identified in Earth‐based observations of emissions. This peak or “finger” is separated from the more dense Io torus by a local minimum or ’trough’ at M 5. The electron densities are inferred by identifying characteristic frequencies of the plasma such as the low‐frequency cutoff of Z‐mode radiation at and the low‐frequency cutoff of ordinary mode radiation at that depend on the electron density. The “finger” density ranges from about 0.2 to 65 and decreases with increasing centrifugal latitude. The “trough” densities range from 0.05 to 10 . This pattern of a density “trough” followed by the “finger” closer to Jupiter is found on repeated passes through the inner Io torus over a range of centrifugal latitudes. Using a simple model for the electron densities measured above about 10 centrifugal latitude, we've estimated the scale height of the “finger” densities as about 1.17 with respect to the centrifugal equator, which is somewhat surprising given the expected cold temperature of the cold torus. The larger scale height suggests a population of light ions, such as protons, is elevated off the centrifugal equator. This is confirmed by a multi‐species diffusive equilibrium model.
The Retard‐Boost Effect of Fragmentation in Rock Avalanches
Authors: Jiang Hui , Feng Ye‐Nan , Zhou Yuan‐De , Wang Jin‐Ting , Du Xiu‐Li 
Published: January 2025

AbstractThis study presents a micro‐mechanical numerical investigation of the fundamental aspects of progressive fragmentation and its effects on rock avalanche dynamics. The simulations involve breakable rock assemblies that are released along an inclined plane and subsequently collide onto a horizontal surface. A discrete‐continuous numerical model is adopted to effectively capture progressive particle breakage and complex interparticle interactions. By incorporating variations in fracture mechanics parameters, the model systematically evaluates the influence of progressive grain fragmentation on rock avalanche dynamics. A multi‐layer analysis method and the interlayer transmitting coefficient are proposed to analyze the temporal and spatial kinematics, stress distribution and the ongoing particle size reduction process. The results indicate that grain fragmentation significantly influences rock avalanche motion, identified as the “retard‐boost” effect in this study. At low fragmentation degrees, densely packed rock particles exhibit an interlayer transmitting effect, with kinematic energy dissipation primarily resulting from grain breakage. Conversely, full mobilization of rock fragmentation from the base upwards enhances flow mobility by reducing basal friction through the agitation of fragments. The findings indicate a competition between positive feedback, which enhances rock avalanche mobility at high fragmentation levels, and negative feedback, which results in energy dissipation at low fragmentation levels, with the predominance of these effects varying according to the degree of fragmentation.
One-sided device-independent random number generation through fiber channels
Authors: Zhang Jinfang , Li Yi , Zhao Mengyu , Han Dongmei , Liu Jun , Wang Meihong , Gong Qihuang , Xiang Yu , He Qiongyi , Su Xiaolong 
Published: January 2025

AbstractRandomness is an essential resource and plays important roles in various applications ranging from cryptography to simulation of complex systems. Certified randomness from quantum process is ensured to have the element of privacy but usually relies on the device’s behavior. To certify randomness without the characterization for device, it is crucial to realize the one-sided device-independent random number generation based on quantum steering, which guarantees security of randomness and relaxes the demands of one party’s device. Here, we distribute quantum steering between two distant users through a 2 km fiber channel and generate quantum random numbers at the remote station with untrustworthy device. We certify the steering-based randomness by reconstructing covariance matrix of the Gaussian entangled state shared between distant parties. Then, the quantum random numbers with a generation rate of 7.06 Mbits/s are extracted from the measured amplitude quadrature fluctuation of the state owned by the remote party. Our results demonstrate the first realization of steering-based random numbers extraction in a practical fiber channel, which paves the way to the quantum random numbers generation in asymmetric networks.
Beyond visible: giant bulk photovoltaic effect for broadband neuromodulation
Authors: Chai Xueping , Sun Zhipei 
Published: January 2025

AbstractThe giant bulk photovoltaic effect in tellurene nanomaterials has been harnessed to enable broadband infrared neuromodulation, expanding the potential for safe, non-invasive neural stimulation and highlighting the importance of material innovation in advancing infrared photonic applications.
High-integrated photonic tensor core utilizing high-dimensional lightwave and microwave multidomain multiplexing
Authors: Meng Xiangyan , Shi Nuannuan , Zhang Guojie , Li Junshen , Jin Ye , Sun Shiyou , Shen Yichen , Li Wei , Zhu Ninghua , Li Ming 
Published: January 2025

AbstractThe burgeoning volume of parameters in artificial neural network models has posed substantial challenges to conventional tensor computing hardware. Benefiting from the available optical multidimensional information entropy, optical intelligent computing is used as an alternative solution to address the emerging challenges of electrical computing. These limitations, in terms of device size and photonic integration scale, have hindered the performance of optical chips. Herein, an ultrahigh computing density optical tensor processing unit (OTPU), which is grounded in an individual microring resonator (MRR), is introduced to respond to these challenges. Through the independent tuning of multiwavelength lasers, the operational capabilities of an MRR are orchestrated, culminating in the formation of an optical tensor core. This design facilitates the execution of tensor convolution operations via the lightwave and microwave multidomain hybrid multiplexing in terms of the time, wavelength, and frequency of microwaves. The experimental results for the MRR-based OTPU show an extraordinary computing density of 34.04 TOPS/mm2. Additionally, the achieved accuracy rate in recognizing MNIST handwritten digits was 96.41%. These outcomes signify a significant advancement toward the realization of high-performance optical tensor processing chips.