bluuebunny/crossref_metadata_2025_split huggingface dataset:
A hybrid Prairie INFO fission naked algorithm with stagnation mechanism for the parametric estimation of solar photovoltaic systems
Authors: Sharma Pankaj , Salgotra Rohit , Raju Saravanakumar , Abouhawwash Mohamed , Askar S. S. 
Published: February 2025

Abstract
This paper presents a study to enhance the performance of a recently introduced naked mole-rat algorithm (NMRA), by local optima avoidance, and better exploration as well as exploitation properties. A new set of algorithms, namely Prairie dog optimization algorithm, INFO, and Fission fusion optimization algorithm (FuFiO) are included in the fundamental framework of NMRA to enhance the exploration operation. The proposed algorithm is a hybrid algorithm based on four algorithms: Prairie Dog, INFO, Fission Fusion and Naked mole-rat (PIFN) algorithm. Five new mutation operators/inertia weights are exploited to make the algorithm self-adaptive in nature. Apart from that, a new stagnation phase is added for local optima avoidance. The proposed algorithm is tested for variable population, dimension size, and efficient set of parameters is analysed to make the algorithm self-adaptive in nature. Friedman as well as Wilcoxon rank-sum tests are performed to determine the effectiveness of the PIFN algorithm. On the basis of a comparison of outcomes, the PIFN algorithm is more effective and robust than the other optimization techniques evaluated by prior researchers to address standard benchmark functions (classical benchmarks, CEC 2017, and CEC-2019) and complex engineering design challenges. Furthermore, the effectiveness as well as reliability of the PIFN algorithm is demonstrated by testing using various PV modules, namely the RTC France Solar Cell (SDM, and DDM), Photowatt-PWP201, STM6- 40/36, and STP6-120/36 module. The results obtained from the PIFN algorithm are compared with various MH algorithms reported in the existing literature. The PIFN algorithm achieved the lowest root-mean-square error value, for RTC France Solar Cell (SDM) is 7.72E−04, RTC France Solar Cell (DDM) is 7.59E−04, STP6-120/36 module is 1.44E−02, STM6-40/36 module is 1.723E−03, and Photowatt-PWP201 module is 2.06E−03, respectively. In order to enhance the accuracy of the obtained results of parameter estimation of solar photovoltaic systems, we integrated the Newton-Raphson approach with the PIFN algorithm. Experimental and statistical results further prove the significance of the PIFN algorithm with respect to other algorithms.
Fully automated CFD simulation system research based on design scheme tree
Authors: Liu Zijun 
Published: February 2025

Abstract
Compared with the remarkable achievements of computer-aided drug discovery systems for drug discovery, the role of computational fluid dynamics (CFD) in flow channel design requires further development. While CFD has undergone rapid evolution, the absence of integrated geometry and mesh processing hinders the potential development of advanced applications of this technology. To overcome this limitation, in this paper, the JIACFD toolset is presented, and a fully automated CFD simulation system is established. The simulation system is also constructed on a design scheme tree, which is more in accordance with engineering logic. The control parameter trend analysis method is introduced to select appropriate candidates from the design scheme tree. Additionally, the control parameter trend assumption, which is proven via the Spearman method, is proposed to improve the efficiency of the system. During the verification process for the study case, two independent control parameters exhibit correlating trends, and one control parameter converges when the number of meshes increases, indicating a lack of trend sensitivity. The design scheme tree and trend curve are subsequently utilized to effectively analyze the flow field characteristics of different schemes. Finally, the control parameter trend analysis method is employed to rank the design scheme tree and verify that the ranking of candidates is not dependent on the number of meshes. This paper investigates and verifies the presented system, method, and assumption and explores the possibility of an established system playing a more critical role in performance design work.
Tracking metal pollution from illegal gold mining: a health risk assessment in Edfu, Egypt
Authors: AbdelMaksoud Kholoud M. , Al-Metwaly Wael M. , Hathout Heba M. R. 
Published: February 2025

Abstract
Over the past decade, there has been an increase in small-scale gold mining in the arid southern region of Egypt. Miners extract ore from the Eastern Desert and transport it to Nile Valley farms, where ample water facilitates the processing. In Edfu, Egypt, the lack of economic opportunities prompted resource-constrained farmers to transform their agricultural lands into gold mines. The study utilized a multifaceted approach that integrated various methodologies, including remote sensing technologies, field surveys, chemical analyses, and statistical methods. The study aimed to assess the concentrations of carcinogenic agents and determine the potential human health risks associated with these agents in soil and fish samples collected within the city boundaries. The study examined correlations between various heavy metals (HMs), such as Ni, Pb, Cd, Cr, Cu, and Hg, in Soilsamples collected in 2020 and 2022. The results revealed direct proportional relationships among specific HMs. The Index of Geoaccumulation (Igeo) and Pollution Load Index (PLI) revealed significantly elevated values in both years, indicating potential environmental degradation. Although no carcinogenic hazards were identified, non-carcinogenic risks related to ingestion were observed for both adults and children exposed to mercury (Hg), copper (Cu), and arsenic (As). Contamination Factor (CF) values were also significantly high. Ecological risks were observed in both Soiland water, as well as in Nile Tilapia samples. Hazard Quotients (HQ) calculated for Nile Tilapia indicated potential risks for both adults and children, particularly associated with elevated arsenic (As) levels. This transformation elicited concerns regarding environmental and health implications, leading us to undertake a thorough investigation.
High-Precision computational solutions for nonlinear evolution models in graphene sheets
Authors: Khater Mostafa M. A. , Alfalqi Suleman H. , Vokhmintsev Aleksander 
Published: February 2025

Abstract
This study investigates the analytical solutions of a nonlinear evolution model governing the dynamics of graphene sheets, a material renowned for its exceptional electronic properties and versatile applications in nanotechnology. Three advanced analytical approaches-the Khater II (Khat II) method, the Khater III (Khat III) method, and the Generalized Rational (GRat) approach-are employed to derive exact solutions for this model with high precision. The accuracy and reliability of these solutions are validated by comparing them to numerical results obtained via He’s Variational Iteration (HVI) method, which serves as a benchmark for numerical verification. The analysis reveals a remarkable agreement between the analytical and numerical solutions, highlighting the robustness and effectiveness of the proposed methodologies. Furthermore, this study provides new insights into the nonlinear dynamics and physical properties of graphene sheets, while also identifying connections to other prominent nonlinear evolution equations. The innovative use of these analytical techniques offers practical frameworks for addressing complex nonlinear models in mathematical physics, thus advancing solution methodologies for such equations. This research contributes significantly to applied mathematics, material science, and nanotechnology by delivering accurate solutions and enhancing our understanding of graphene’s nonlinear behavior. Finally, the findings have far-reaching implications, offering potential applications in designing advanced materials with tailored properties to support technological advancements, thereby pushing the boundaries of nanotechnology and materials engineering.
Assessing hazard prediction and risk calibration skills in experienced and novice e-scooter riders
Authors: Ventsislavova Petya , Harrison Lydia , Baguley Thom 
Published: February 2025

Abstract
Less experienced e-scooter riders often exhibit risky riding behaviours. Despite this, no studies have examined how riders calibrate risk, respond to hazardous situations, and the impact of riding experience on these skills. To address this, this study assessed hazard prediction and risk calibration in e-scooter riders via bespoke video-based tests featuring real e-scooter footage filmed from the rider’s perspective. The first experiment assessed the ability of e-scooter riders to predict hazardous riding scenarios. The second experiment evaluated their proneness to engage in risky riding situations. The results indicated that increased riding experience did not improve riders’ hazard prediction skills or reduced their proneness to engage in risky riding. In fact, a higher riding frequency was linked to an increased tendency to engage in risky behaviour in certain scenarios. The results highlight that the typically short duration of e-scooter trips may limit riders’ exposure to a variety of hazards, hindering their ability to develop effective risk calibration skills. The observed high propensity to engage in risky riding scenarios, combined with average hazard prediction scores, emphasizes the need for targeted rider training focused on vigilance and risk awareness.
Exploring potential biomarkers for acute myocardial infarction by combining circadian rhythm gene expression and immune cell infiltration
Authors: Yu Xiao , Zhang Xiaopeng , Bilal Hazrat , Shi Chang , Sun Lei 
Published: February 2025

Abstract
Current diagnostic biomarkers for acute myocardial infarction (AMI), such as troponins, often lack specificity, leading to false positives under non-cardiac conditions. Recent studies have implicated circadian rhythm and immune infiltration in the pathogenesis of AMI. This study hypothesizes that analyzing the interplay between circadian rhythm-related gene expression and immune infiltration identify highly specific diagnostic biomarkers for AMI. Our results demonstrated differential expression of 15 circadian rhythm-related genes (CRGs) between AMI patients and healthy individuals, with five key genes—JUN, NAMPT, S100A8, SERPINA1, and VCAN identified as key contributors to this process. Functional enrichment analyses suggest these genes significantly influence cytokine and chemokine production in immune responses. Immune infiltration assessments using ssGSEA indicated elevated levels of neutrophils, macrophages, and eosinophils in AMI patients. Additionally, we identified potential therapeutic implications with 13 pivotal miRNAs and 10 candidate drugs targeting these genes. The Benjamini–Hochberg method was employed to adjust for multiple testing, and the results retained statistical significance. RT-qPCR analysis further confirmed the upregulation of these five genes under hypoxic conditions, compared to controls. Collectively, our findings highlight the critical role of CRGs in AMI, providing a foundation for improved diagnostic approaches and novel therapeutic targets.
Human activity recognition: A review of deep learning‐based methods
Authors: Dutta Sanjay Jyoti , Boongoen Tossapon , Zwiggelaar Reyer 
Published: February 2025

AbstractHuman Activity Recognition (HAR) covers methods for automatically identifying human activities from a stream of data. End‐users of HAR methods cover a range of sectors, including health, self‐care, amusement, safety and monitoring. In this survey, the authors provide a thorough overview of deep learning based and detailed analysis of work that was performed between 2018 and 2023 in a variety of fields related to HAR with a focus on device‐free solutions. It also presents the categorisation and taxonomy of the covered publication and an overview of publicly available datasets. To complete this review, the limitations of existing approaches and potential future research directions are discussed.
Structural optimisation of oil immersed transformer winding block washers based on WOA‐DRBF surrogate model optimisation strategy
Authors: Dong Yufei , Gao Chenglong , Xiang Wenxin , Liu Gang , Liu Yunpeng , Liu Yang , Du Zhenbin 
Published: February 2025

AbstractIn order to reduce the transformer winding hot spot temperature (HST), a dynamic radial basis function surrogate model optimisation strategy is proposed to optimise the structure of the forced oil circulation transformer winding's block washers in this paper. The whale optimisation algorithm (WOA) is introduced to obtain the optimal hyperparameter, and the WOA‐DRBF surrogate model optimisation strategy is used to improve the fitting and optimisation ability. After optimisation, the HST corresponding to the size of the block washers decreased by 3.67°C, and the maximal temperature rise decreased by 12.93%, effectively ameliorating the phenomenon of excessive local temperature rise within each partition. Comparing the above optimisation results with those of the WOA‐RBF static surrogate model and the genetic algorithm (GA), the proposed method shows superior performance in both optimisation search capability and efficiency. Comparing the optimisation efficiencies of the three methods, the number of model calls for the WOA‐DRBF method is 23.89% of the WOA‐RBF method and 1.77% of the GA method, respectively. The proposed method significantly enhances optimisation efficiency while improving global optimisation search capability. It offers a feasible solution for efficiently and accurately solving the optimisation problem of the transformer winding's block washer.
Multi-wavelength Study for Gamma-Ray Nova V1405 Cas
Authors: Ou Zi-Wei , Tam Pak-Hin Thomas , Wang Hui-Hui , Pei Song-Peng , Huang Wen-Jun 
Published: February 2025

Abstract
Novae are found to have GeV to TeV γ-ray emission, which reveals the shock acceleration from the white dwarfs. Recently, V1405 Cas was reported to radiate suspicious γ-ray by Fermi-LAT with low significance (4.1σ) after the optical maximum. Radio observations reveal that it is one of the five brightest novae surrounded by low-density ionized gas columns. Here we report a continuous search for GeV γ-ray from Fermi-LAT. No γ-ray was found. For V1405 Cas the flux level is lower than other well-studied Fermi novae, and the γ-ray maximum appears at t
0 + 145 days. γ-ray of V1405 Cas is used to search potential γ-ray periodicity. No γ-ray periodicity was found during the time of observation. By comparing multi-wavelength data, the γ-ray upper limit to optical flux ratio with a value at around 10−4 is obtained to constrain the shock acceleration. Long-term analysis from Swift-XRT gets X-ray spectral in the post-shock phase, which indicates that V1405 Cas became a super-soft source. The best-fit black body temperature at the super soft state is 0.11–0.19 keV.
Long-period Double-lined Eclipsing Binaries: The System V454 Aur with the Secondary Eclipse Caused by the Occultation of the Hotter Component
Authors: Kniazev Alexei Y. , Malkov Oleg , Gorda Stanislav , Berdnikov Leonid N. , Katkov Ivan Y. 
Published: February 2025

Abstract
We present the results of our study of the long-period eclipsing binary star V454 Aur. The results are based on spectroscopic data obtained with the UFES échelle spectrograph and photometric observations from Transiting Exoplanet Survey Satellite (TESS). The derived radial velocity curve is based on 17 spectra obtained between 2021 and 2023, covering all orbital phases of this binary system. The orbital period determined from TESS data, P = 27.019803 ± 0.000003 days, agrees within uncertainties with the period established in previous studies. The model constructed for the TESS photometric light curve achieves a precision of 0.01%. The effective temperatures of both components, as well as the system metallicity, were directly derived from the spectra and are T
eff,A = 6250 ± 50 K, T
eff,B = 5855 ± 50 K, and [Fe/H] = −0.10 ± 0.08, respectively. Our analysis of the photometric and spectroscopic data allowed us to directly compute the luminosities of the components, L
A = 1.82 L
⊙ and L
B = 1.07 L
⊙, their radii, R
A = 1.15 R
⊙ and R
B = 1.00 R
⊙, and their masses, M
A = 1.137 M
⊙ and M
B = 1.023 M
⊙, with uncertainties below 1%. Comparison with evolutionary tracks indicates that the system’s age is 1.18 ± 0.10 Gyr, and both components are still on the main sequence. The V454 Aur system is particularly interesting due to the partial eclipse of the primary component, which results in the “inversion” of the primary and secondary minima in the photometric light curve.
Constraints on Baryon Density from the Effective Optical Depth of High-redshift Quasars
Authors: Liu Wen-Fei , Xie Yuan-Bo , Liu Zhi-E , Qin Jin , Jiao Kang , Zhao Dong-Yao , Zhang 张 Tong-Jie 同杰 
Published: February 2025

Abstract
We present constraints on the baryonic matter density parameter, Ω
b
, within the framework of the ΛCDM model. Our analysis utilizes observational data on the effective optical depth from high-redshift quasars. To parameterize the photoionization rate Γ−12, we employ a Bézier polynomial. Additionally, we approximate the Hubble parameter at high redshifts as

H
(
z
)
≈
100
h

Ω

m

1
/
2

(
1
+
z
)

3
/
2

km s−1 Mpc−1. Confidence regions are obtained with h = 0.701 ± 0.013 and Ω
m
= 0.315, optimized by the Planck mission. The best-fit values are

Ω

b

=
0.04

3

−
0.006

+
0.005

and

Ω

b

=
0.04

5

−
0.006

+
0.004

, corresponding to an old data set and a new data set, respectively. We test the non-parametric form of Γ−12, obtaining

Ω

b

=
0.04

8

−
0.003

+
0.001

. These results are consistent with the findings of Planck at the 1σ confidence level. Our findings underscore the effectiveness of quasar data sets in constraining Ω
b
, eliminating the need for independent photoionization rate data. This approach provides detailed cosmic information about baryon density and the photoionization history of the intergalactic medium.
Tests of X-ray Image Reconstruction: A New Index for Assessing Image Quality
Authors: Li Zhentong , YU Wenhui , Su Yang , Chen Wei , Gan Weiqun 
Published: February 2025

Abstract
Indirect X-ray modulation imaging has been adopted in a number of solar missions and provided reconstructed X-ray images of solar flares that are of great scientific importance. However, the assessment of the image quality of the reconstruction is still difficult which is particularly useful for scheme design of X-ray imaging systems, testing and improvement of imaging algorithms, and scientific research of X-ray sources. Currently, there is no specified method to quantitatively evaluate the quality of X-ray image reconstruction and the point spread function (PSF) of an X-ray imager. In this paper, we propose percentage proximity degree (PPD) by considering the imaging characteristics of X-ray image reconstruction and in particular, sidelobes and their effects on imaging quality. After testing a variety of imaging quality assessments in six aspects, we utilized the technique for order preference by similarity to ideal solution to the indices that meet the requirements. Then we develop the final quality index for X-ray image reconstruction, QuIX, which consists of the selected indices and the new PPD. QuIX performs well in a series of tests, including assessment of instrument PSF and simulation tests under different grid configurations, and imaging tests with RHESSI data. It is also a useful tool for testing of imaging algorithms, and determination of imaging parameters for both RHESSI and ASO-S/HXI, such as field of view (FOV), beam width factor, and detector selection.
Seedling size affects the strategy of dune seedlings responding to rainfall variation
Authors: Shen-Tu Xiao-Lu , Hu Yu-Kun , Shea Katriona , Gascoigne Samuel JL , Wei Qing , Tang Li-Chen , Li Dan-Dan , Li Shou-Li 
Published: February 2025

Abstract

Background and Aims
Climate change poses a growing threat to population maintenance in harsh desert habitats with high precipitation variability. Desert seeds may germinate at different times as a bet-hedging strategy to cope with increased rainfall fluctuation. As a result, a population may consist of seedlings of various sizes. However, it remains unknown how the variation in seedling sizes affects their capacity to cope with different rainfall scenarios, thus impairing our capacity to manage population under climate change.

Methods
To fill this gap in knowledge, we examined how seedling size (large seedlings with an average height of 14.30 cm vs. small seedlings with an average height of 5.85 cm) affects the strategy seedlings use to cope with a gradient of rainfall treatments (-75%, -50%, -25%, 0%, +25%, +50%, +75%) for Artemisia ordosica Krasch., a dominant shrub widely used for ecological restoration in the Mu Us Sandland.

Key Results
We found that seedling performance was affected both by rainfall intensity and seedling size. Seedling survival and growth declined with reduction in rainfall. Moreover, large seedlings allocated more biomass to roots, thus increasing their capacity for water absorption, resulting in relatively less reduction in their total biomass under water stress. In contrast, small seedlings invested more in aboveground growth, likely to compete for light.

Conclusions
Our study demonstrates that seedling size may strongly affect the responses of seedlings to rainfall variation. As a result, populations having recruitment of seedlings with different sizes may better spread mortality risk under variable rainfall conditions. Therefore, our results suggest that species with flexible germination time may be highly suitable for desert vegetation restoration under climate change.
Instagram Vs. Reality: Assessment of the Representation of Lip Aesthetic Subtypes on Social Media Using the Lip Classification of Tubercles System
Authors: Harris Steven , Castellari Fabrizio , Orlovska Madara , Othoro Don , Bran Greg 
Published: February 2025

Abstract

Background
Social media platforms, particularly Instagram appear to be influencing contemporary beauty standards, especially concerning lip enhancements. Understanding the prevalent lip types showcased can offer valuable insights into evolving aesthetic ideals to inform both patients and practitioners.

Objectives
This study aims to analyse lip types associated with minimally invasive lip enhancements on Instagram (Meta, Menlo Park, CA) and compare these findings with classifications from a patient clinic using the Lip Classification of Tubercles (LCT) system.

Methods
A within-subjects design was employed to examine 120 "Before and After" images from four trending Instagram hashtags related to lip enhancements. Four expert examiners performed the classification, and inter-rater reliability was assessed. Data from a previous study involving patients from an aesthetic clinic (N = 214) were incorporated to compare the frequencies of lip types in the clinic and on Instagram.

Results
The inter-rater reliability for lip classification on Instagram was very good (Fleiss’ Kappa: pre-treatment k = 0.817; post-treatment k = 0.837). The most common lip type pre-treatment was 1A, which dramatically shifted to type 3A post-treatment. The comparison with the patient clinic revealed that while type 1A was the most prevalent in both datasets, Instagram exhibited lower variability, with only 10 unique types identified pre-treatment and a predominant type 3A post-treatment.

Conclusions
The representations of lip enhancements on Instagram reflect a narrower range of lip types compared to clinical findings, including a dramatic shift toward a type 3A lip shape. This standardisation of beauty ideal highlights the need for further exploration of social media's influence on lip enhancement preferences and the associated risks, as well as how these trends shape patient expectations in aesthetic practices.