bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characteristics of the Dissimilar Turbulent Transport Processes of Heat and Momentum During Wind‐Wave Dynamical Interactions
Authors: Zhang Jinlong , Dong Yuhong , Shen Lian 
Published: November 2024

AbstractHeat and momentum transport processes are studied through direct numerical simulations of air‐water two‐phase flows with surface waves under wave‐wind couplings. Three wave age cases, sea state changing from wind sea to swell, are analyzed to investigate the roles of surface waves in the turbulent transport of heat and momentum, which are examined by decomposing the statistics into the plane‐averaged, wave‐coherent, and turbulent‐induced components. Under wind sea conditions, a dissimilarity in turbulent transfer between heat and momentum is observed in the near‐surface region. This discrepancy arises from the enhanced countergradient heat transport on the leeward side, which is caused by wave‐coherent structures. The surface waves induce phase‐dependent variations in the temperature and flow structures, reducing the scale of temperature structure. This reduction further results in a weaker contribution of ejections and sweeps to heat transfer. In contrast, momentum transport is predominantly downgradient on the leeward side due to the large‐scale flow structure. This difference in coherent structures leads to the dissimilar transport between heat and momentum. Under lower‐frequency swell conditions, surface waves induce an upward momentum that enhances the vortical structures near the wave surface. The transfer efficiency of turbulent momentum and heat gradually reaches equilibrium, after which both transport processes become more analogous.
Orbital (Hydro)Climate Variability in the Ice‐Free Early Eocene Arctic
Authors: Fokkema Chris D. , Brinkhuis Henk , Peterse Francien , Sluijs Appy 
Published: November 2024

AbstractEarly Eocene (∼56–48 Ma) climates are useful to investigate polar climate dynamics in the absence of ice. We explore early Eocene orbital variability of Arctic climate using sediments recovered by the Arctic Coring Expedition (ACEX). High resolution records of lipid biomarkers (GDGTs; 2‐kyr) and palynological assemblages (5‐kyr) in the ∼4 m interval below Eocene Thermal Maximum 2 (∼54 Ma) show cyclic signals related to ∼20‐kyr precession, ∼40‐kyr obliquity, and ∼100‐kyr eccentricity. Biomarkers indicate obliquity and precession variability representative of sea surface temperature (SST) variations up to ∼1.4 and ∼0.5°C, respectively. Peak SSTs coincide with an elevated supply of pollen and spores and increased marine productivity. This implies an orbital control on precipitation and terrestrial nutrient supply to the Arctic Basin. Assuming that SST maxima correspond to Arctic insolation maxima (precession minima/obliquity maxima), precipitation maxima also correspond to insolation maxima, implying regional hydrological processes as a forcing rather than variations in meridional water transport, contrasting Pleistocene Arctic hydrology. The relative amplitudes of precession and obliquity in the SST record match that of local insolation between spring and fall, corroborating a seasonal GDGT bias. The reconstructed complete orbital imprint refutes a bias to one end of the orbital variability. Eccentricity‐related SST variability was ∼0.8°C, ∼2–3 times higher than synchronous variability in the deep ocean, and 3–4 times higher than similar variations in the tropics. This confirms eccentricity‐forced global temperature variability and that this had pronounced polar amplification, despite the absence of ice‐albedo feedbacks.
Long COVID syndrome in children: neutrophilic granulocyte dysfunction and its correlation with disease severity
Authors: Kovács Fanni , Posvai Tamás , Zsáry Eszter , Kolonics Ferenc , Garai Réka , Herczeg Vivien , Czárán Domonkos , Takács Johanna , Szabó Attila József , Krivácsy Péter , Csépányi-Kömi Roland 
Published: November 2024

Abstract

Background
Many children suffer from lingering symptoms after COVID-19, known as long COVID syndrome (LCS), otherwise called Post COVID-19 Condition (PCC). Despite extensive research, the prevalence of symptoms, its impact on quality of life, and underlying mechanisms still need to be fully understood. As neutrophilic granulocytes play an essential role in COVID-19, and their prolonged disruption was found to cause immunological diseases, we hypothesized their ongoing disturbed functionality in LCS.

Methods
We studied 129 children with LCS, 32 convalescent children (CG+), and 8 uninfected children (CG−). Online questionnaires and in-person examinations assessed symptoms, quality of life, and functioning (QoL-F). Effector functions of neutrophilic granulocytes obtained from the venous blood of 29 LCS and 17 CG+ children were also investigated.

Results
Persistent fatigue was the most common symptom in children with LCS, while both control groups complained about anxiety most frequently. LCS children experienced significantly more symptoms, impairing their QoL-F compared to CG+. Neutrophilic granulocyte dysfunction was found in LCS children, with decreased superoxide-producing activity and phagocytosis compared to CG+. The number of complaints of children with LCS correlated significantly with altered neutrophil effector functions.

Conclusion
Neutrophil dysfunction in children with LCS may be part of the disease pathogenesis or a predisposing factor.

Impact

Using online questionnaires validated during in-person medical examinations and including two different control groups, our study compellingly supports and adds to previous clinical observations in the field.

Our study provides valuable insights into the prevalence and characteristics of pediatric LCS, highlighting the significant quality of life and functioning impairment compared to control groups.

By detecting neutrophilic granulocyte dysfunction in children with LCS, we shed light on a previously overlooked pathophysiological component of the condition.

We demonstrate a significant correlation between clinical symptoms and superoxide production, further enhancing our understanding of the underlying mechanisms of pediatric LCS.
Population genomics of Plasmodium ovale species in sub-Saharan Africa
Authors: Carey-Ewend Kelly , Popkin-Hall Zachary R. , Simkin Alfred , Muller Meredith , Hennelly Chris , He Wenqiao , Moser Kara A. , Gaither Claudia , Niaré Karamoko , Aghakanian Farhang , Feleke Sindew , Brhane Bokretsion G. , Phanzu Fernandine , Kashamuka Melchior Mwandagalirwa , Aydemir Ozkan , Sutherland Colin J. , Ishengoma Deus S. , Ali Innocent M. , Ngasala Billy , Kalonji Albert , Tshefu Antoinette , Parr Jonathan B. , Bailey Jeffrey A. , Juliano Jonathan J. , Lin Jessica T. 
Published: November 2024

AbstractPlasmodium ovale curtisi (Poc) and Plasmodium ovale wallikeri (Pow) are relapsing malaria parasites endemic to Africa and Asia that were previously thought to represent a single species. Amid increasing detection of ovale malaria in sub-Saharan Africa, we present a population genomic study of both species across the continent. We conducted whole-genome sequencing of 25 isolates from Central and East Africa and analyzed them alongside 20 previously published African genomes. Isolates are predominantly monoclonal (43/45), with their genetic similarity aligning with geography. Pow shows lower average nucleotide diversity (1.8×10−4) across the genome compared to Poc (3.0×10−4) (p < 0.0001). Signatures of selective sweeps involving the dihydrofolate reductase gene have been found in both species, as are signs of balancing selection at the merozoite surface protein 1 gene. Differences in the nucleotide diversity of Poc and Pow may reflect unique demographic history, even as similar selective forces facilitate their resilience to malaria control interventions.
Elastic and magnetic characteristics of nano-spinel ferrite Co0.5 MgxCu0.5−xFe2O4
Authors: Fakhry F. , Shaheen E. , El-Dosoky H. , Meaz T. M. , Mubark M. , El-Shater R. 
Published: November 2024

AbstractWet-chemical co-precipitation was used to create Co0.5MgxCu0.5−xFe2O4 nano-ferrites (x = 0.0, 0.2, 0.3, and 0.4). XRD, FT-IR, HRTEM, and EDX analyses were used to confirm each sample’s single-phase spinel cubic crystal structure. The crystallite size was calculated from the XRD data and determined to be between (11.1570 and 16.1457 nm), with a lattice constant between (8.359 to 8.387Å). The two absorption bands found in the FTIR data were utilized to show metal cation and oxygen bond stretching at tetrahedral and octahedral positions, as well as to calculate the elastic moduli. The elemental composition and structural behavior of every sample were examined using FE-SEM and EDS. The magnetic parameters were also estimated based on the VSM data, the contribution of magnetic anisotropy (K), and the magnetic interaction by Neel’s and Y-K-type magnetism modify as the Mg2+ ion substitution increases, thus we must consider how this variation in cation distribution affects all of these factors. As per the ferromagnet theory, ions originating from the magnetic tetrahedral A and octahedral B sites engage in super-exchange interactions with one another. Anti-ferromagnetic alignment occurs as a result (MB-MA). Magnetization occurs as a result.
Predicting executive functioning from walking features in Parkinson’s disease using machine learning
Authors: Piet Artur , Geritz Johanna , Garcia Pascal , Irsfeld Mona , Li Frédéric , Huang Xinyu , Irshad Muhammad Tausif , Welzel Julius , Hansen Clint , Maetzler Walter , Grzegorzek Marcin , Bunzeck Nico 
Published: November 2024

AbstractParkinson’s disease is characterized by motor and cognitive deficits. While previous work suggests a relationship between both, direct empirical evidence is scarce or inconclusive. Therefore, we examined the relationship between walking features and executive functioning in patients with Parkinson’s disease using state-of-the-art machine learning approaches. A dataset of 103 geriatric Parkinson inpatients, who performed four walking conditions with varying difficulty levels depending on single task walking and additional motor and cognitive demands, was analyzed. Walking features were quantified using an inertial measurement unit (IMU) system positioned at the patient’s lower back. The analyses included five imputation methods and four regression approaches to predict executive functioning, as measured using the Trail-Making Test (TMT). Multiple imputation by chained equations (MICE) in combination with support vector regression (SVR) reduce the mean absolute error by about 4.95% compared to baseline. Importantly, predictions solely based on walking features obtained with support vector regression mildly but significantly correlated with Δ−TMT values. Specifically, this effect was primarily driven by step time variability, double limb support time variability, and gait speed in the dual task condition with cognitive demands. Taken together, our data provide direct evidence for a link between executive functioning and specific walking features in Parkinson’s disease.
Bacteriorhodopsin of purple membrane reverses anisotropy outside the pH range of proton pumping based on logic gate realization
Authors: Mostafa Hamdy I. A. , Elfiki Abdo A. 
Published: November 2024

AbstractThe bacteriorhodopsin of purple membrane is the first discovered light-sensing protein among ion transporting microbial rhodopsins, some of which (e.g. Archaerhodopsin 3) could be broadly used as tools in optogenetics having wide potential of medical applications. Since its discovery as early as in 1971, bacteriorhodopsin has attracted wide interests in nano-biotechnology, particularly in optoelectronics devices. Therefore, the present work has been motivated due to two topics; firstly, anisotropy demand became indispensible in bioelectronics; secondly, the stationary level of electric response in bacteriorhodopsin within the pH range of proton pumping (pH 3 – pH 10) implies, in turn, raising here a question about whether the electric anisotropy is implicated for reducing (or switching off) such level beyond such pH range. Noteworthy is that the purple membrane converts to blue form upon acidification, while to reddish purple form upon alkalization. In the present study, the acidic and alkaline forms of bacteriorhodopsin have exhibited most probable state of reversal for the dielectric anisotropy around pH 2.5 and pH 10.5, respectively. This is underscored by proposing a correlation seemingly found between disassembly of the crystalline structure of bacteriorhodopsin and the reversal of dielectric anisotropy, at such acidic and alkaline reversal pH’s, in terms of the essence of the crystalline lattice. Most importantly, the results have substantiated dual frequency characteristics and logic gate-based dielectric anisotropy reversal to bacteriorhodopsin, which may implicate it for potential applications in bioelectronics.
Enhancing dysarthric speech recognition through SepFormer and hierarchical attention network models with multistage transfer learning
Authors: Vinotha R. , Hepsiba D. , Vijay Anand L. D. , Andrew J. , Jennifer Eunice R. 
Published: November 2024

AbstractDysarthria, a motor speech disorder that impacts articulation and speech clarity, presents significant challenges for Automatic Speech Recognition (ASR) systems. This study proposes a groundbreaking approach to enhance the accuracy of Dysarthric Speech Recognition (DSR). A primary innovation lies in the integration of the SepFormer-Speech Enhancement Generative Adversarial Network (S-SEGAN), an advanced generative adversarial network tailored for Dysarthric Speech Enhancement (DSE), as a front-end processing stage for DSR systems. The S-SEGAN integrates SEGAN’s adversarial learning with SepFormer speech separation capabilities, demonstrating significant improvements in performance. Furthermore, a multistage transfer learning approach is employed to assess the DSR models for both word-level and sentence-level DSR. These DSR models are first trained on a large speech dataset (LibriSpeech) and then fine-tuned on dysarthric speech data (both isolated and augmented). Evaluations demonstrate significant DSR accuracy improvements in DSE integration. The Dysarthric Speech (DS)-baseline models (without DSE), Transformer and Conformer achieved Word Recognition Accuracy (WRA) percentages of 68.60% and 69.87%, respectively. The introduction of Hierarchical Attention Network (HAN) with the Transformer and Conformer architectures resulted in improved performance, with T-HAN achieving a WRA of 71.07% and C-HAN reaching 73%. The Transformer model with DSE + DSR for isolated words achieves a WRA of 73.40%, while that of the Conformer model reaches 74.33%. Notably, the T-HAN and C-HAN models with DSE + DSR demonstrate even more substantial enhancements, with WRAs of 75.73% and 76.87%, respectively. Augmenting words further boosts model performance, with the Transformer and Conformer models achieving WRAs of 76.47% and 79.20%, respectively. Remarkably, the T-HAN and C-HAN models with DSE + DSR and augmented words exhibit WRAs of 82.13% and 84.07%, respectively, with C-HAN displaying the highest performance among all proposed models.
Metabolic reprogramming in saliva of mice treated with the environmental and tobacco carcinogen dibenzo[def, p]chrysene
Authors: Sun Yuan-Wan , Chen Kun-Ming , Aliaga Cesar , El-Bayoumy Karam 
Published: November 2024

AbstractThe goal of this study is to develop a non-invasive approach for early detection of oral squamous cell carcinoma (OSCC) using our established mouse model that faithfully recapitulates the human disease. We present for the first time a comparative metabolomic profiling of saliva samples of the tobacco smoke constituent, dibenzo[def, p]pyrene, (DB[a, l]P) vs. DMSO (control)-treated mice using an established and highly sensitive LC-MS/MS approach. DB[a, l]P was administered by topical application into the mouse oral cavity (25 µmol, 3x week for 6 weeks) and saliva was collected 24 h after the last dose of carcinogen administration. Using an untargeted metabolomics approach (negative and positive modes), we found that DB[a, l]P differentially altered several metabolites known to be involved in the carcinogenesis process when compared to DMSO. Of particular significance, we found that DB[a, l]P significantly enriched the levels of phosphatidic acid, known to bind and activate mTORC which can enhance proliferation and promote carcinogenesis. Pathway enrichment analysis revealed that DB[a, l]P altered two major lipid metabolism pathways (phospholipid biosynthesis and glycerolipid metabolism). Collectively, our results using saliva as a safe and non-invasive approach, provide additional mechanistic insights on DB[a, l]P-induced OSCC and potential biomarkers for early detection and an opportunity for cancer interception via reprogramming lipid metabolism.
The arms race of ray-finned fish against the derepression of LTR retroelements
Authors: Carotti Elisa , Tittarelli Edith , Carducci Federica , Barucca Marco , Canapa Adriana , Biscotti Maria Assunta 
Published: November 2024

AbstractTransposable elements (TEs) are dynamic components of eukaryotic genomes that are important in speciation. Evolutionary pressure has led to the evolution of silencing mechanisms, such as the involvement of Krüppel box-associated zinc finger proteins (KRAB-ZFPs) that regulate TE transcription via TRIM28-mediated NuRD complex recruitment in sarcopterygians. The transcriptional activity of genes that encode proteins of the NuRD complex was also detected in actinopterygians, even though genes encoding crucial proteins such as TRIM28 and KRAB-ZNF are missing in this evolutionary lineage. This study hypothesized that TRIM33 could serve as a replacement for TRIM28 in this lineage and suggested an evolutionary relationship between the sarcopterygian KRAB-ZFPs, the actinopterygian KRAB-like ZNFs and the fish N-terminal zinc-associated domain (FiNZ) ZNFs that are specific to cyprinids. Through coimmunoprecipitation analyses conducted in the basal teleost Anguilla marmorata and the cyprinid Danio rerio, we evaluated the interaction of TRIM33 with the KRAB-like and FiNZ ZFPs. Moreover, we explored the expression profiles of TEs and genes that encode proteins that are potentially involved in their silencing during zebrafish development. Our results may provide new evidence for more thoroughly understanding the evolutionary mechanisms underlying the adaptation of ray-finned fish.
Analysis of Nuclear Structure Properties and Stellar β-decay Rates of Even–Even 106–120Zr Isotopes
Authors: Kabir Abdul , Nabi Jameel-Un , Anmol Rida Syeda , Anwaar Izzah , Ain Raza Noor-Ul , Almujibah Hamad 
Published: November 2024

Abstract
The nuclear ground state properties of even–even 106–120Zr nuclei have been investigated within the framework of the relativistic mean field (RMF) approach. The RMF model with density-dependent DDME2 and DDPC1 interactions is utilized for the calculation of potential energy curves, the nuclear ground-state deformation parameters (β
2), neutron separation energies (S

n
and S
2n
) and neutron skin thickness (r

np
) of selected Zr isotopes. Later, the β-decay properties of Zr isotopes were studied using the proton-neutron quasi-particle random phase approximation (pn-QRPA) model. These include Gamow–Teller strength distributions, β-decay half-lives and stellar electron emission/positron capture rates. The β
2 values computed from the RMF model were employed in the pn-QRPA model as an input parameter for the calculations of β-decay properties for even–even 106–120Zr nuclei. The stellar rates were computed using the pn-QRPA framework with three different types of deformation parameters. Only at high temperature (T
9 ≥ 2) and low density (ρ
Y

e
≤ 107 g cm−3) values, the sum of electron emission and positron capture rates has a sizeable contribution (with positive exponents) to the stellar rates.
Analysis of optimal planting scheme based on the North China region
Authors: Liang Kun , Lei Jiaying , Wu Feiyang , Hu Zhenning , Zhou Yusong , Li Dandan , Gong Shiqin 
Published: November 2024

Abstract
This paper constructs a linear programming model for optimizing crop planting strategies in rural mountainous areas of North China by simulating data and predicting the planting scheme for each sample plot in the next six years. It sets decision variables as plot, year, season, and crop planting area, considering crop rotation and three-year legume planting restrictions. Applying an improved genetic algorithm for solving, which improves efficiency through multi-matrix chromosome coding and optimized crossover mutation operation, and deals with infeasible solutions through a rule-based repair mechanism to propose different optimal planting strategies. They are considering the fluctuating uncertainty of crop sales, yield, and planting cost based on the expected fluctuation range and reducing computational resources through orthogonal experimental design. A bi-objective robust optimization model was used to balance average profit maximization and profit minimization under different scenarios. This was solved by the improved NSGA-II algorithm. The final optimal planting scheme suggests increasing the planting proportion of vegetable crops and controlling the planting scale of crops with large cost fluctuations while guaranteeing grain crops like wheat and corn.
Memory-based fault detection for uncertain system with random sensor saturation
Authors: Zhang Yu , Wu Zhihui 
Published: November 2024

Abstract
This article tackles the memory-based fault detection (FD) issue for uncertain systems with sensor saturation. In order to improve the FD efficiency, a novel memory fault detection filter (MFDF) is established based on the historical state information of the filter. Sufficient criteria are given to ensure that the residual error system (RES) can achieve the expected performance. In addition, the MFDF parameters are obtained by solving matrix inequalities. Finally, a simulation is provided to verify the effectiveness of the developed memory-based FD algorithm.
Construction of indoor WiFi fingerprint map based on ray tracing and Gaussian process regression
Authors: Xu Jun , Fu Lin , Ma Jing 
Published: November 2024

Abstract
In traditional indoor robot positioning, SLAM sensors such as vision and lidar are commonly relied upon. However, achieving precise indoor Wireless Fidelity (WiFi) positioning and navigation for mobile robots, without the necessity of SLAM sensors, requires the construction of a high-precision wireless fingerprint map. To tackle this challenge, we suggest a technique for building indoor WiFi fingerprint maps using ray tracing and Gaussian process regression (GPR). This method involves simulating the propagation status of indoor WiFi signals using a ray tracing algorithm, resulting in a simulated WiFi fingerprint map. Additionally, we employ a mobile robot to collect real values of sparse WiFi fingerprints. These simulated and real-world data are then integrated through GPR to produce a comprehensive WiFi fingerprint map. To validate our approach, we evaluate it using three positioning algorithms in an indoor environment. Experimental results demonstrate that our method achieves a positioning accuracy of 69.30cm for indoor mobile robots, underscoring its effectiveness in constructing indoor WiFi fingerprint maps and paving the way for robot navigation in indoor environments. This research represents a significant advancement in the provision of high-precision WiFi fingerprint maps.