bluuebunny/crossref_metadata_2025_split huggingface dataset:
SYREN-HALOFIT: A fast, interpretable, high-precision formula for the ΛCDM nonlinear matter power spectrum
Authors: Bartlett Deaglan J. , Wandelt Benjamin D. , Zennaro Matteo , Ferreira Pedro G. , Desmond Harry 
Published: April 2024

Context.Rapid and accurate evaluation of the nonlinear matter power spectrum,P(k), as a function of cosmological parameters and redshift is of fundamental importance in cosmology. Analytic approximations provide an interpretable solution, yet current approximations are neither fast nor accurate relative to numerical emulators.Aims.We aim to accelerate symbolic approximations toP(k) by removing the requirement to perform integrals, instead using short symbolic expressions to compute all variables of interest. We also wish to make such expressions more accurate by re-optimising the parameters of these models (using a larger number of cosmologies and focussing on cosmological parameters of more interest for present-day studies) and providing correction terms.Methods.We use symbolic regression to obtain simple analytic approximations to the nonlinear scale,kσ, the effective spectral index,neff, and the curvature,C, which are required for theHALOFITmodel. We then re-optimise the coefficients ofHALOFITto fit a wide range of cosmologies and redshifts. We then again exploit symbolic regression to explore the space of analytic expressions to fit the residuals betweenP(k) and the optimised predictions ofHALOFIT. Our results are designed to match the predictions ofEUCLIDEMULATOR2, but we validate our methods againstN-body simulations.Results.We find symbolic expressions forkσ,neffandCwhich have root mean squared fractional errors of 0.8%, 0.2% and 0.3%, respectively, for redshifts below 3 and a wide range of cosmologies. We provide re-optimisedHALOFITparameters, which reduce the root mean squared fractional error (compared toEUCLIDEMULATOR2) from 3% to below 2% for wavenumbersk = 9 × 10−3 − 9 h Mpc−1. We introduceSYREN-HALOFIT(symbolic-regression-enhancedHALOFIT), an extension toHALOFITcontaining a short symbolic correction which improves this error to 1%. Our method is 2350 and 3170 times faster than currentHALOFITandHMCODEimplementations, respectively, and 2680 and 64 times faster thanEUCLIDEMULATOR2 (which requires runningCLASS) and theBACCOemulator. We obtain comparable accuracy toEUCLIDEMULATOR2 and theBACCOemulator when tested onN-body simulations.Conclusions.Our work greatly increases the speed and accuracy of symbolic approximations toP(k), making them significantly faster than their numerical counterparts without loss of accuracy.
Beneficial Effects of Echinacoside on Cognitive Impairment and
Diabetes in Type 2 Diabetic db/db Mice
Authors: Qin Fanglin , Yan Yiming , Yang Ningxi , Hao Yarong 
Published: April 2024

Abstract
Introduction Cognitive dysfunction is an important comorbidity of
diabetes. Insulin resistance may play a critical role in diabetes-related
cognitive impairment. Echinacoside (ECH), a natural phenylethanoid glycoside, is
the active component of anti-diabetes prescriptions in traditional Chinese
medicine. Its effect on modulating insulin resistance has been confirmed but
modulating neurodegenerative disease remains unclear.
Methods Db/db mice, a spontaneous type 2 diabetes mode, were
intragastrically administered ECH by 300 mg/kg or an equivalent volume of
saline. Weight, blood glucose, and insulin resistance index were measured.
Morris water maze test was performed to observe the compound effects on
cognition. Hippocampal lesions were observed by histochemical analysis.
Results In db/db mice, ECH alleviated diabetes symptoms, memory loss, and
hippocampal neuronal damage. Next, the expression of CD44 and phosphorylated tau
was upregulated in diabetic mice. In addition, the insulin receptor
substrate-1/phosphatidylinositol 3-kinase /protein kinase B signaling pathway
was dysregulated in diabetic mice. All these dysregulations could be reversed by
ECH.
Discussion This study provides theoretical support and experimental
evidence for the future application of ECH in diabetic cognition dysfunction
treatment, promoting the development of traditional medicines.
Blood Pressure Variability is Better Associated with Acute Relative
Hyperglycemia Than the Heart Rate Variability in Healthy Young
Adults
Authors: Prakash Kiran , Ranjan Navkiran , Malhotra Anita S. 
Published: April 2024

Abstract
Background Deranged cardiovascular autonomic functions are well-reported
complications of diabetes mellitus, where chronic hyperglycemia is an important
factor. The role of acute relative hyperglycemia on cardiovascular autonomic
functions, particularly on blood pressure variability in healthy subjects, has
been rarely explored. Therefore, this study aimed to examine the effect of acute
relative hyperglycemia on cardiovascular autonomic functions in healthy young
adults.
Methods Beat-to-beat blood pressure and electrocardiogram were recorded to
assess the heart rate variability and blood pressure variability in 42 young,
healthy subjects during fasting and relative hyperglycemic states. Recorded
cardiovascular parameters were analyzed in time and frequency domains.
Correlations among analyzed parameters of cardiovascular autonomic variabilities
were explored during fasting and relative hyperglycemic state.
Results A few of the systolic, mean, and diastolic
blood-pressure-variability parameters were significantly altered during acute
relative hyperglycemia when compared to the fasting state. However, no
significant changes were observed in any of the heart-rate-variability
parameters. Also, novel significant correlations were found among many of the
parameters of cardiovascular autonomic variabilities during fasting and relative
hyperglycemic states.
Conclusions The blood pressure variability is affected significantly
during acute relative hyperglycemia in healthy young adults; however, the heart
rate variability does not show such changes. Also, many blood pressure
variability parameters show significant correlations with heart rate variability
and baroreflex sensitivity. It may be hypothesized that although the
variabilities in heart rate and blood pressure assess cardiovascular autonomic
functions, blood pressure variability is a better indicator of cardiovascular
autonomic effects of acute relative hyperglycemia.
Effect of Perioperative Blood Transfusion on Postoperative Complications of Free-Flap Reconstruction for Oral Cancer: Analysis of Propensity Score-Matched Cohorts
Authors: Chen Yu , Lei Yinfu , Wu Hemei , Peng Xiaofeng , Gou Dengqun , Zhang Lu , Tao Ming 
Published: April 2024

Abstract
Background It has been confirmed in other fields that perioperative blood transfusion (PBT) will increase the incidence of complications after free-flap reconstruction and increase the risk of patients returning to the operating room within 48 hours after the initial operation. However, for head and neck tumors, whether PBT is related to postoperative complications is debatable. The aim of this study was to control the demographic and comorbidity characteristics of patients by propensity score matching (PSM) as well as to investigate the relationship between PBT and postoperative complications after oral cancer free-flap reconstruction.
Methods A total of 597 patients who underwent microvascular free tissue transfer in two top three hospitals in Southwest China from January 2015 to July 2023 were retrospectively reviewed. The study population was divided based on PBT within 24 hours of the start of the operation and to ensure homogeneity between groups by using the PSM. The primary outcomes were postoperative complications; secondary outcomes were to explore the intraoperative risk factors of PBT.
Results A total of 597 patients were included. Among them, 90 patients received a PBT. Those patients were successfully matched with 86 similar patients who did not receive a transfusion on a ratio of 1:1. This study did not find that patients receive a transfusion had a significantly higher risk of vascular pedicle thrombosis (p = 1.000), hematoma (p = 1.000), flap failure (p = 0.398), flap-related complications (p = 0.470), and other medical complications (p = 1.000). After controlling the preoperative confounding factors and adjusting the logistic regression model, it was concluded that the tumor location-mandible (odds ratio [OR] = 19.923, 95% confidence interval [CI]: 1.213–327.302, p = 0.036) and operation time (OR = 1.011, 95% CI: 1.008–1.014, p < 0.001) were the intraoperative risk factors for PBT.
Conclusion PBT is not associated with an increased probability of postoperative complications. Mandibular tumor may have a higher risk of PBT.
Artificial Intelligence and Machine Learning Applications in Critically Ill Brain Injured Patients
Authors: Vitt Jeffrey R. , Mainali Shraddha 
Published: April 2024

AbstractThe utilization of Artificial Intelligence (AI) and Machine Learning (ML) is paving the way for significant strides in patient diagnosis, treatment, and prognostication in neurocritical care. These technologies offer the potential to unravel complex patterns within vast datasets ranging from vast clinical data and EEG (electroencephalogram) readings to advanced cerebral imaging facilitating a more nuanced understanding of patient conditions. Despite their promise, the implementation of AI and ML faces substantial hurdles. Historical biases within training data, the challenge of interpreting multifaceted data streams, and the “black box” nature of ML algorithms present barriers to widespread clinical adoption. Moreover, ethical considerations around data privacy and the need for transparent, explainable models remain paramount to ensure trust and efficacy in clinical decision-making.This article reflects on the emergence of AI and ML as integral tools in neurocritical care, discussing their roles from the perspective of both their scientific promise and the associated challenges. We underscore the importance of extensive validation in diverse clinical settings to ensure the generalizability of ML models, particularly considering their potential to inform critical medical decisions such as withdrawal of life-sustaining therapies. Advancement in computational capabilities is essential for implementing ML in clinical settings, allowing for real-time analysis and decision support at the point of care. As AI and ML are poised to become commonplace in clinical practice, it is incumbent upon health care professionals to understand and oversee these technologies, ensuring they adhere to the highest safety standards and contribute to the realization of personalized medicine. This engagement will be pivotal in integrating AI and ML into patient care, optimizing outcomes in neurocritical care through informed and data-driven decision-making.
Acousto-optic holography for pseudo-two-dimensional dynamic light patterning
Authors: Akemann Walther , Bourdieu Laurent 
Published: April 2024

Optical systems use acousto-optic deflectors (AODs) mostly for fast angular scanning and spectral filtering of laser beams. However, AODs may transform laser light in much broader ways. When time-locked to the pulsing of low repetition rate laser amplifiers, AODs permit the holographic reconstruction of 1D and pseudo-two-dimensional (ps2D) intensity objects of rectangular shape by controlling the amplitude and phase of the light field at high (20–200 kHz) rates for microscopic light patterning. Using iterative Fourier transformations (IFTs), we searched for AOD-compatible holograms to reconstruct the given ps2D target patterns through either phase-only or complex light field modulation. We previously showed that phase-only holograms can adequately render grid-like patterns of diffraction-limited points with non-overlapping diffraction orders, while side lobes to the target pattern can be cured with an apodization mask. Dense target patterns, in contrast, are typically encumbered by apodization-resistant speckle noise. Here, we show the denoised rendering of dense ps2D objects by complex acousto-optic holograms deriving from simultaneous optimization of the amplitude and phase of the light field. Target patterns lacking ps2D symmetry, although not translatable into single holograms, were accessed by serial holography based on a segregation into ps2D-compatible components. The holograms retrieved under different regularizations were experimentally validated in an AOD random-access microscope. IFT regularizations characterized in this work extend the versatility of acousto-optic holography for fast dynamic light patterning.
A new car following model based on weighted average velocity field
Authors: Singh Nisha , Kumar Kranti 
Published: April 2024

Abstract
In real traffic, the motion status of forward moving vehicles play an important role in influencing the following vehicle’s motion behaviour. Nowadays, autonomous and electric vehicles have been incorporated with car-following mode when the control process is more complicated and more meaningful. As a result, researchers are studying car-following control strategies for vehicles to attain stability in traffic. Based on this, we propose a new car following model considering weighted average velocity field to describe the average effect of multi-vehicle interaction on the whole road. The weighted average velocity field can be regarded as the weighted average of velocities of finite number of vehicles preceding the objective vehicle with more weightage to more preceding vehicle. The stability condition is derived through stability analysis. Subsequently, the modified Korteweg–de Vries (mKdV) equation is formulated to unveil traffic congestion in the form of the kink-antikink density wave. Theoretical findings indicate that the weighted average velocity field yields larger stability regions compared to the average velocity field. Numerical simulations were conducted, and the results obtained demonstrate that the weighted average effect of multi-vehicle interactions play a crucial role in suppressing traffic jams faster than a simple average.
Thermalization and annihilation of dark matter in neutron stars
Authors: Bell Nicole F. , Busoni Giorgio , Robles Sandra , Virgato Michael 
Published: April 2024

Abstract
The capture of dark matter, and its subsequent annihilation, can heat old, isolated
neutron stars. In order for kinetic heating to be achieved, the captured dark matter must undergo
sufficient scattering to deposit its kinetic energy in the star. We find that this energy deposit
typically occurs quickly, for most of the relevant parameter space. In order for appreciable
annihilation heating to also be achieved, the dark matter must reach a state of
capture-annihilation equilibrium in the star. We show that this can be fulfilled for all types of
dark matter-baryon interactions. This includes cases where the scattering or annihilation cross
sections are momentum or velocity suppressed in the non-relativistic limit. Importantly, we find
that capture-annihilation equilibrium, and hence maximal annihilation heating, can be achieved
without complete thermalization of the captured dark matter. For scattering cross sections that
saturate the capture rate, we find that capture-annihilation equilibrium is typically reached on a
timescale of less than 1 year for vector interactions and 104 years for scalar interactions.
Generating a maximally entangled state via a pure global noise environment
Authors: Kong Fan-Zhen , Zhao Jun-Long 
Published: April 2024

Abstract
We studied the entangling power of two pure global noises, i.e. amplitude damping noise and classic noise. The entangling power of the two-qubit amplitude damping global noise periodically oscillates with time. Additionally, the entangling power of two-qubit global classical noise increases exponentially with time. The maximum entangling power of both of them exceeds that of the perfect entanglers. Based on this, we propose the conditions for generating a maximally entangled state with global noise acting on a two-qubit separable state. Only if the two-qubit composite system, which is initially in one of those product states:

1

2

(

|

0
⟩
±

|

1
⟩
)
⊗

1

2

(

|

0
⟩
±

|

1
⟩
)

,

|
10
⟩

and

|
01
⟩

suffers an amplitude damping global noise, can we prepare this system in the maximally entangled state by appropriately controlling the evolution time of amplitude damping. Finally, we investigate the disentanglement of the maximum entangled Bell state using these two types of global noise. The two global noises cannot completely disentangle the Bell states

Φ

±

. Under the influence of amplitude damping global noise, the entanglement of Bell state

Ψ
+

undergoes a cyclical variation, alternating between disappearance and recovery to reach maximum entanglement within one period. The entanglement of either Bell state

Ψ
+

or

Ψ
−

is completely independent of global classical noise. The entanglement of Bell state

Ψ
−

is also robust against amplitude damping global noise.
Metasurface CGH optimization for CTIS based on interior point method
Authors: Zhou Pengwei , Zhou Jiamin , Lv Yangfan 
Published: April 2024

Abstract
In the design of the Computed Tomographic Imaging Spectrometer (CTIS), in order to optimize the holographic grating and achieve better design performance, this paper proposes a novel optimization algorithm based on the Gerchberg–Saxton (GS) iterative algorithm. This algorithm combines the weighted GS algorithm with the interior point method (IPM). By introducing weight factors for phase and amplitude in the optimization process of the GS algorithm, and incorporating the actual diffraction characteristics of the holographic grating obtained from the Computer Simulation Technology Studio Suite into the IPM optimization process, a more optimized design performance is achieved. Using this algorithm, a metasurface holographic grating is designed, which can transform the input parallel light into a dispersion image of 25 diffraction orders on a focal plane array. The transmission efficiency exceeds 72%, and the root mean square error between different diffraction orders is less than 0.1. Among them, the optimization time is shortened by approximately 70% due to a significant reduction in the number of independent variables through symmetry. Through comparison, this method can further improve the uniformity of energy distribution based on the original algorithm, avoid being trapped in local extreme values, and thus enhance the overall design quality of the CTIS.
Evolutionary accessibility of random and structured fitness landscapes
Authors: Krug Joachim , Oros Daniel 
Published: April 2024

Abstract
Biological evolution can be conceptualized as a search process in the space of gene sequences guided by the fitness landscape, a mapping that assigns a measure of reproductive value to each genotype. Here, we discuss probabilistic models of fitness landscapes with a focus on their evolutionary accessibility, where a path in a fitness landscape is said to be accessible if the fitness values encountered along the path increase monotonically. For uncorrelated (random) landscapes with independent and identically distributed fitness values, the probability of existence of accessible paths between genotypes at a distance linear in the sequence length L becomes nonzero at a nontrivial threshold value of the fitness difference between the initial and final genotypes, which can be explicitly computed for large classes of genotype graphs. The behaviour of uncorrelated random landscapes is contrasted with landscape models that display additional, biologically motivated structural features. In particular, landscapes defined by a tradeoff between adaptation to environmental extremes have been found to display a combinatorially large number of accessible paths to all local fitness maxima. We show that this property is characteristic of a broad class of models that satisfy a certain global constraint, and provide further examples from this class.
3D bioprinting approaches for spinal cord injury repair
Authors: Jiu Jingwei , Liu Haifeng , Li Dijun , Li Jiarong , Liu Lu , Yang Wenjie , Yan Lei , Li Songyan , Zhang Jing , Li Xiaoke , Li Jiao Jiao , Wang Bin 
Published: April 2024

Abstract
Regenerative healing of spinal cord injury (SCI) poses an ongoing medical challenge by causing persistent neurological impairment and a significant socioeconomic burden. The complexity of spinal cord tissue presents hurdles to successful regeneration following injury, due to the difficulty of forming a biomimetic structure that faithfully replicates native tissue using conventional tissue engineering scaffolds. 3D bioprinting is a rapidly evolving technology with unmatched potential to create 3D biological tissues with complicated and hierarchical structure and composition. With the addition of biological additives such as cells and biomolecules, 3D bioprinting can fabricate preclinical implants, tissue or organ-like constructs, and in vitro models through precise control over the deposition of biomaterials and other building blocks. This review highlights the characteristics and advantages of 3D bioprinting for scaffold fabrication to enable SCI repair, including bottom–up manufacturing, mechanical customization, and spatial heterogeneity. This review also critically discusses the impact of various fabrication parameters on the efficacy of spinal cord repair using 3D bioprinted scaffolds, including the choice of printing method, scaffold shape, biomaterials, and biological supplements such as cells and growth factors. High-quality preclinical studies are required to accelerate the translation of 3D bioprinting into clinical practice for spinal cord repair. Meanwhile, other technological advances will continue to improve the regenerative capability of bioprinted scaffolds, such as the incorporation of nanoscale biological particles and the development of 4D printing.
3D printing processes in precise drug delivery for personalized medicine
Authors: Peng Haisheng , Han Bo , Tong Tianjian , Jin Xin , Peng Yanbo , Guo Meitong , Li Bian , Ding Jiaxin , Kong Qingfei , Wang Qun 
Published: April 2024

Abstract
With the advent of personalized medicine, the drug delivery system will be changed significantly. The development of personalized medicine needs the support of many technologies, among which three-dimensional printing (3DP) technology is a novel formulation-preparing process that creates 3D objects by depositing printing materials layer-by-layer based on the computer-aided design method. Compared with traditional pharmaceutical processes, 3DP produces complex drug combinations, personalized dosage, and flexible shape and structure of dosage forms (DFs) on demand. In the future, personalized 3DP drugs may supplement and even replace their traditional counterpart. We systematically introduce the applications of 3DP technologies in the pharmaceutical industry and summarize the virtues and shortcomings of each technique. The release behaviors and control mechanisms of the pharmaceutical DFs with desired structures are also analyzed. Finally, the benefits, challenges, and prospects of 3DP technology to the pharmaceutical industry are discussed.