bluuebunny/crossref_metadata_2025_split huggingface dataset:
Scaling of self-compression of near-IR femtosecond pulses in hollow-core fibers down to the single-cycle limit
Authors: Dey Pritha , Vijayan C , Krishnan Sivarama 
Published: February 2022

Abstract
We numerically investigate the scaling of self-compression processes with experimental parameters for near-infrared ultrashort pulses (30 fs) in gas-filled hollow-core fiber (HCF). These simulations over a wide-range of input pulse energies as well as filling gas pressures reveal a remarkable scaling of the self-compression process and dynamics. As a function of soliton order N, we identify the relation between the propagation distance after which self-compression in the HCF begins and the subsequent propagation length up to which the pulse remains maximally compressed; both these length scales decrease with an increase in N, the soliton order. Although previous investigations revealed pulse compression scaling laws which provide a good approximation for input pulse-widths ∼100 fs down to the limit where soliton fission begins to dominate the dynamics, these are not sufficiently accurate to describe the entire scaling dynamics. Instead, we identify a more generalized set of scaling laws by taking both third-order dispersion and the saturation of the compression factor due to soliton fission into account. These conclusions about scaling are robust: our simulations were carried out over a wide range of realistic input pulse energies and gas pressures as implemented in laboratories taking into account higher-order dispersive properties of the gaseous propagating medium. Therefore, given that these numerical investigations consider conditions typically applied in practice in laboratories, this work provides elegant design principles and guideposts relevant to realizing systems capable of achieving self-compression at substantially high pulse energies down to the few-cycle limit; they are of paramount importance in generating single as well as trains of attosecond pulses and acceleration strategies for electrons and ions in intense laser pulses.
The surface waves propagating along the contact between the layer with the constant gradient of refractive index and photorefractive crystal
Authors: Savotchenko Sergey 
Published: February 2022

Abstract
We consider the photorefractive crystal with diffusion nonlinearity mechanism contacting with the linearly graded-index medium. The new types of the surface waves propagating along the contact are found and their properties are described. The transition between two types of the surface waves can be controlled by the waveguide temperature. The light field penetrates into the photorefractive crystal much deeper than into the graded-index medium. The maxima intensity monotonically increase with an increase in the propagation constant, and monotonically decrease with an increase in the temperature. The localization length of the surface waves decreases with an increase in the characteristic distance the graded-index medium and with a decrease in the propagation constant and the temperature. The discrete spectrum of the propagation constant for the special waveguide mode corresponding to the case of exponential damping of intensity maxima of the surface waves with an increasing temperature is obtained. It is shown that the intensity maxima in the photorefractive crystal depend parabolic on the temperature at low temperature waveguide mode.
Effect of ceramic surface texture on the tribological property of ceramics and carbon fiber reinforced silicon carbide ceramic matrix composite (C/SiC)
Authors: Wei Jinhua , Wang Jie , Pei Tianhe , Yan Weidong , Hu Zhiyuan , Li Awen , Sui Tianyi , Wang Haoji , Lin Bin 
Published: February 2022

Abstract
Three processing methods including grinding, polishing, laser engraving were used on ZrO2 and Si3N4 surfaces. Two types of surface textures were obtained including micro dimples and micro grooves through the laser engraving. Therefore, the friction experiments of the eight surfaces mated with C/SiC were conducted under a dry condition at ambient temperature. The results indicated that surface texture does not necessarily have a positive effect on the tribological properties which are largely influenced by the countrpart materials and the texture type. Ground ZrO2-C/SiC and Si3N4 with micro dimples-C/SiC have a better tribological property, and the former shows the best performance during the tests. The formation and the falling off of wear debris are accompanied with the whole friction process while C/SiC rubbing against Si3N4 disc with micro dimples thus resulting in a worse result.
Effect of shear stress and compressive stress deformation on LPSO phase kink behavior of Mg-Gd-Y-Zn-Zr alloy
Authors: Wu Yaojin , Meng Yingze , Yu Huisheng , He Yayun , Yu Jianmin , Wang Zhen , Zhang Zhimin 
Published: February 2022

Abstract
Using torsion and compression experiments, the kink behavior of the long period stacking ordered (LPSO) phase under different stress deformation of the Mg-13Gd-4Y-2Zn-0.5Zr alloy were studied. The results show that different stress states have different effects on the kink of LPSO phase. The grain deformation of the shear stress deformed (SSD) alloy is relatively weak, where LPSO phases are mostly C-shaped or S-shaped kinks. The kink forms can be divided into parallel kinks and angular kinks. The grains of compressive stress deformed (CSD) alloy are significantly elongated and perpendicular to the compression direction, in which occur more Z-shaped zigzag kinks. The kink angle and kink times of the shear stress deformed alloy are small, while the relative kink width is larger. There are large number kink bands during compressive stress deformation, almost all of which are distributed in perpendicular to the compression direction. The difference in the kink behavior is due to the non-basal slip of SSD is easy to active, while in the CSD alloy, the non-basal slip is relatively difficult to active, resulting in more dislocation pile-up. Different forms of kinks can release stress concentration, and all of kinks make the grains deflect in the direction with higher non-basal slip schmid factor.
Matched Sampling Methodology Reconsidered: The Role of Trust in Studying Remittance Transfers Between Ghanaian Immigrants in the UK and their Relatives in Ghana
Authors: Ampah Geraldine Asiwome 
Published: February 2022

Abstract
Matched sampling methodology (MSM) has been used in remittance studies to understand remittance transfers. However, a detailed examination of the role of trust as a central element in producing reliable and valid research conclusions when a matched sample methodology is used has been missing in the literature. This paper fills this lacuna by arguing that cultivating trust in matched sampling research on remittance transfers, a sensitive subject matter, between African immigrants and their relatives presents a more nuanced narrative of remittance transfers. This approach shows that not only do African immigrants in the ‘Global North’ send remittances back home, but immigrants also receive remittances (reverse remittances) from their relatives on the continent. Using remittance research conducted among Ghanaian immigrants in the UK and their relatives in Ghana, this article identifies three ‘avenues of trust’—‘public avenues of trust’, ‘intermediate avenues of trust’, and ‘private avenues of trust’—to highlight the processes and challenges that researchers encounter while establishing contact with research participants and the role that trust plays in gathering accurate information. Focusing on the role of trust in MSM is in line with recent theoretical paradigms of remittance research that call for soliciting information from both origin and destination countries.
Measurement Error Affecting Web- and Paper-Based Dietary Assessment Instruments: Insights From the Multi-Cohort Eating and Activity Study for Understanding Reporting Error
Authors: Kirkpatrick Sharon I , Troiano Richard P , Barrett Brian , Cunningham Christopher , Subar Amy F , Park Yikyung , Bowles Heather R , Freedman Laurence S , Kipnis Victor , Rimm Eric B , Willett Walter C , Potischman Nancy , Spielgelman Donna , Baer David J , Schoeller Dale A , Dodd Kevin W 
Published: February 2022

Abstract
Few biomarker-based validation studies have examined error in online self-report dietary assessment instruments, and food records (FRs) have been considered less than food frequency questionnaires (FFQs) and 24-hour recalls (24HRs). We investigated measurement error in online and paper-based FFQs, online 24HRs, and paper-based FRs in 3 samples drawn primarily from 3 cohorts, comprising 1,393 women and 1,455 men aged 45–86 years. Data collection occurred from January 2011 to October 2013. Attenuation factors and correlation coefficients between reported and true usual intake for energy, protein, sodium, potassium, and respective densities were estimated using recovery biomarkers. Across studies, average attenuation factors for energy were 0.07, 0.07, and 0.19 for a single FFQ, 24HR, and FR, respectively. Correlation coefficients for energy were 0.24, 0.23, and 0.40, respectively. Excluding energy, the average attenuation factors across nutrients and studies were 0.22 for a single FFQ, 0.22 for a single 24HR, and 0.51 for a single FR. Corresponding correlation coefficients were 0.31, 0.34, and 0.53, respectively. For densities (nutrient expressed relative to energy), the average attenuation factors across studies were 0.37, 0.17, and 0.50, respectively. The findings support prior research suggesting different instruments have unique strengths that should be leveraged in epidemiologic research.
Impact of the Timing of Stay-at-Home Orders and Mobility Reductions on First-Wave COVID-19 Deaths in US Counties
Authors: Audirac Michelle , Tec Mauricio , Meyers Lauren Ancel , Fox Spencer , Zigler Cory 
Published: February 2022

Abstract
As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission continues to evolve, understanding the contribution of location-specific variations in nonpharmaceutical interventions and behaviors to disease transmission during the initial epidemic wave will be key for future control strategies. We offer a rigorous statistical analysis of the relative effectiveness of the timing of both official stay-at-home orders and population mobility reductions during the initial stage of the US coronavirus disease 2019 (COVID-19) epidemic. We used a Bayesian hierarchical regression to fit county-level mortality data from the first case on January 21, 2020, through April 20, 2020, and quantify associations between the timing of stay-at-home orders and population mobility with epidemic control. We found that among 882 counties with an early local epidemic, a 10-day delay in the enactment of stay-at-home orders would have been associated with 14,700 additional deaths by April 20 (95% credible interval: 9,100, 21,500), whereas shifting orders 10 days earlier would have been associated with nearly 15,700 fewer lives lost (95% credible interval: 11,350, 18,950). Analogous estimates are available for reductions in mobility—which typically occurred before stay-at-home orders—and are also stratified by county urbanicity, showing significant heterogeneity. Results underscore the importance of timely policy and behavioral action for early-stage epidemic control.
PIPENN: protein interface prediction from sequence with an ensemble of neural nets
Authors: Stringer Bas , de Ferrante Hans , Abeln Sanne , Heringa Jaap , Feenstra K Anton , Haydarlou Reza 
Published: February 2022

AbstractMotivationThe interactions between proteins and other molecules are essential to many biological and cellular processes. Experimental identification of interface residues is a time-consuming, costly and challenging task, while protein sequence data are ubiquitous. Consequently, many computational and machine learning approaches have been developed over the years to predict such interface residues from sequence. However, the effectiveness of different Deep Learning (DL) architectures and learning strategies for protein–protein, protein–nucleotide and protein–small molecule interface prediction has not yet been investigated in great detail. Therefore, we here explore the prediction of protein interface residues using six DL architectures and various learning strategies with sequence-derived input features.ResultsWe constructed a large dataset dubbed BioDL, comprising protein–protein interactions from the PDB, and DNA/RNA and small molecule interactions from the BioLip database. We also constructed six DL architectures, and evaluated them on the BioDL benchmarks. This shows that no single architecture performs best on all instances. An ensemble architecture, which combines all six architectures, does consistently achieve peak prediction accuracy. We confirmed these results on the published benchmark set by Zhang and Kurgan (ZK448), and on our own existing curated homo- and heteromeric protein interaction dataset. Our PIPENN sequence-based ensemble predictor outperforms current state-of-the-art sequence-based protein interface predictors on ZK448 on all interaction types, achieving an AUC-ROC of 0.718 for protein–protein, 0.823 for protein–nucleotide and 0.842 for protein–small molecule.Availability and implementationSource code and datasets are available at https://github.com/ibivu/pipenn/.Supplementary informationSupplementary data are available at Bioinformatics online.
Evolutionary dynamics of climatic niche influenced the current geographical distribution of Viperidae (Reptilia: Squamata) worldwide
Authors: Esparza-Estrada Citlalli Edith , Terribile Levi Carina , Rojas-Soto Octavio , Yáñez-Arenas Carlos , Villalobos Fabricio 
Published: February 2022

AbstractAn understanding of patterns of climatic niche evolution has important implications for ecological and evolutionary theory and conservation planning. However, despite considerable testing, niche evolution studies continue to focus on clade-wide, homogeneous patterns, without considering the potentially complex dynamics (i.e. phylogenetic non-stationarity) along the evolutionary history of a clade. Here, we examine the dynamics of climatic niche evolution in vipers and discuss its implication for their current patterns of diversity and distribution. We use comparative phylogenetic methods and global-scale datasets, including 210 viper species with phylogenetic and climatic data. We find that climatic niche evolution in Viperidae shows an overall pattern of phylogenetic conservatism, but with different dynamics depending on the niche feature (niche breadth or niche position) and the evolutionary history of particular lineages within the family, thus resulting in phylogenetic non-stationarity. Indeed, we find several shifts in niche breadth evolution that were probably influenced by the main geological and environmental changes experienced during the evolutionary history of the family. These results highlight the importance of considering complex patterns of climatic niche evolution and their role in shaping patterns of diversity and distribution.
Semiparametric Bayesian inference for optimal dynamic treatment regimes via dynamic marginal structural models
Authors: Rodriguez Duque Daniel , Stephens David A , Moodie Erica E M , Klein Marina B 
Published: February 2022

SummaryConsiderable statistical work done on dynamic treatment regimes (DTRs) is in the frequentist paradigm, but Bayesian methods may have much to offer in this setting as they allow for the appropriate representation and propagation of uncertainty, including at the individual level. In this work, we extend the use of recently developed Bayesian methods for Marginal Structural Models to arrive at inference of DTRs. We do this (i) by linking the observational world with a world in which all patients are randomized to a DTR, thereby allowing for causal inference and then (ii) by maximizing a posterior predictive utility, where the posterior distribution has been obtained from nonparametric prior assumptions on the observational world data-generating process. Our approach relies on Bayesian semiparametric inference, where inference about a finite-dimensional parameter is made all while working within an infinite-dimensional space of distributions. We further study Bayesian inference of DTRs in the double robust setting by using posterior predictive inference and the nonparametric Bayesian bootstrap. The proposed methods allow for uncertainty quantification at the individual level, thereby enabling personalized decision-making. We examine the performance of these methods via simulation and demonstrate their utility by exploring whether to adapt HIV therapy to a measure of patients’ liver health, in order to minimize liver scarring.
Cause-specific mortality and life years lost in people with epilepsy: a Danish cohort study
Authors: Dreier Julie Werenberg , Laursen Thomas Munk , Tomson Torbjörn , Plana-Ripoll Oleguer , Christensen Jakob 
Published: February 2022

AbstractMortality rates are two to three times higher in people with epilepsy than in the general population. This study aimed to quantify how this increased mortality translates into reduced life expectancy and to identify the underlying causes of deaths, thereby offering suggestions for how to reduce mortality associated with epilepsy.In this population-based cohort study, we included all individuals aged 0–94 years who were living in Denmark between 2000 and 2015. Using the nationwide registers, we identified people diagnosed with epilepsy and estimated the excess of life years lost due to 13 overall and nine specific causes of death.Among 6 022 160 people, we identified 129 598 with epilepsy (52.6% males), with a mean age of epilepsy onset of 36.5 years (standard deviation = 26.3 years). During the 16 years of follow-up, 851 087 individuals died, and of these 36 923 had been diagnosed with epilepsy. The average reduction in life expectancy in people with epilepsy was 11.84 years in males (95% confidence interval: 11.66–12.00) and 10.91 years in females (95% confidence interval: 10.70–11.11) compared to the general population. Life expectancy was reduced irrespective of epilepsy aetiology (symptomatic ∼14 years; idiopathic ∼8–10 years), and in particular in people with epilepsy and psychiatric comorbidity (∼13–16 years). Excess mortality was evident across all causes of death including cardiovascular disorders, accidents, and suicide.People with epilepsy experience a substantial reduction in lifespan that can only partly be explained by underlying conditions. Prevention of epilepsy-related deaths should focus on the consequences of psychiatric comorbidity and on modifiable risk factors associated with preventable causes of death such as accidents and neurological and cardiovascular disorders.
Widespread white matter oedema in subacute COVID-19 patients with neurological symptoms
Authors: Rau Alexander , Schroeter Nils , Blazhenets Ganna , Dressing Andrea , Walter Lea I , Kellner Elias , Bormann Tobias , Mast Hansjörg , Wagner Dirk , Urbach Horst , Weiller Cornelius , Meyer Philipp T , Reisert Marco , Hosp Jonas A 
Published: February 2022

Abstract
While neuropathological examinations in patients who died from COVID-19 revealed inflammatory changes in cerebral white matter, cerebral MRI frequently fails to detect abnormalities even in the presence of neurological symptoms. Application of multi-compartment diffusion microstructure imaging (DMI), that detects even small volume shifts between the compartments (intra-axonal, extra-axonal and free water/CSF) of a white matter model, is a promising approach to overcome this discrepancy.
In this monocentric prospective study, a cohort of 20 COVID-19 inpatients (57.3 ± 17.1 years) with neurological symptoms (e.g. delirium, cranial nerve palsies) and cognitive impairments measured by the Montreal Cognitive Assessment (MoCA test; 22.4 ± 4.9; 70% below the cut-off value &lt;26/30 points) underwent DMI in the subacute stage of the disease (29.3 ± 14.8 days after positive PCR). A comparison of whole-brain white matter DMI parameters with a matched healthy control group (n = 35) revealed a volume shift from the intra- and extra-axonal space into the free water fraction (V-CSF). This widespread COVID-related V-CSF increase affected the entire supratentorial white matter with maxima in frontal and parietal regions. Streamline-wise comparisons between COVID-19 patients and controls further revealed a network of most affected white matter fibres connecting widespread cortical regions in all cerebral lobes. The magnitude of these white matter changes (V-CSF) was associated with cognitive impairment measured by the MoCA test (r = −0.64, P = 0.006) but not with olfactory performance (r = 0.29, P = 0.12). Furthermore, a non-significant trend for an association between V-CSF and interleukin-6 emerged (r = 0.48, P = 0.068), a prominent marker of the COVID-19 related inflammatory response. In 14/20 patients who also received cerebral 18F-FDG PET, V-CSF increase was associated with the expression of the previously defined COVID-19-related metabolic spatial covariance pattern (r = 0.57; P = 0.039). In addition, the frontoparietal-dominant pattern of neocortical glucose hypometabolism matched well to the frontal and parietal focus of V-CSF increase.
In summary, DMI in subacute COVID-19 patients revealed widespread volume shifts compatible with vasogenic oedema, affecting various supratentorial white matter tracts. These changes were associated with cognitive impairment and COVID-19 related changes in 18F-FDG PET imaging.