bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modelling of surface brightness fluctuation measurements
Authors: Rodríguez-Beltrán P. , Cerviño M. , Vazdekis A. , Beasley M. A. 
Published: March 2024

Aims. The goal of this work is to scrutinise the surface brightness fluctuation (SBF) calculation methodology. We analysed the SBF derivation procedure, measured the accuracy of the fitted SBF under controlled conditions, retrieved the uncertainty associated with the variability of a system that is inherently stochastic, and studied the SBF reliability under a wide range of conditions. Additionally, we address the possibility of an SBF gradient detection. We also examine the problems related with biased measurements of the SBF and low luminosity sources. All of this information allows us to put forward guidelines to ensure a valid SBF retrieval.
Methods. To perform all the experiments described above, we carried out Monte Carlo simulations of mock galaxies as an ideal laboratory. Knowing its underlying properties, we attempted to retrieve SBFs under different conditions. The uncertainty was evaluated through the accuracy, the precision, and the standard deviation of the fitting.
Results. We demonstrate how the usual mathematical approximations taken in the SBF theoretical derivation have a negligible impact on the results and how modelling the instrumental noise reduces the uncertainty. We conducted various studies where we varied the size of the mask applied over the image, the surface and fluctuation brightness of the galaxy, its size and profile, its point spread function, and the sky background. It is worth highlighting that we find a strong correlation between having a high number of pixels within the studied mask and retrieving a low uncertainty result. We address how the standard deviation of the fitting underestimates the actual uncertainty of the measurement. Lastly, we find that, when studying SBF gradients, the result is a pixel-weighted average of all the SBFs present within the studied region. Retrieving an SBF gradient requires high-quality data and a sufficient difference in the fluctuation value through the different radii. We show how the SBF uncertainty can be obtained and we present a collection of qualitative recommendations for a safe SBF retrieval.
Conclusions. Our main findings are as follows. It is important to model the instrumental noise, rather than fitting it. The target galaxies must be observed under appropriate observational conditions. In a traditional SBF derivation, one should avoid pixels with fluxes lower than ten times the SBF estimate to prevent biased results. The uncertainty associated with the intrinsic variability of the system can be obtained using sets of Monte Carlo mock galaxy simulations. We offer our computational implementation in the form of a simple code designed to estimate the uncertainty of the SBF measurement. This code can be used to predict the quality of future observations or to evaluate the reliability of those already conducted.
Damped kink motions in a system of two solar coronal tubes with elliptic cross sections
Authors: Shi Mijie , Li Bo , Chen Shaoxia , Yu Hui , Guo Mingzhe 
Published: March 2024

Aims. This study is motivated by observations of coordinated transverse displacements in neighboring solar active region loops, addressing specifically how the behavior of kink motions in straight two-tube equilibria is impacted by tube interactions and tube cross-sectional shapes.
Methods. We worked with linear, ideal, pressureless magnetohydrodynamics. Axially standing kink motions were examined as an initial value problem for transversely structured equilibria involving two identical, field-aligned, density-enhanced tubes with elliptic cross sections (elliptic tubes). Continuously nonuniform layers were implemented around both tube boundaries. We numerically followed the system response to external velocity drivers, largely focusing on the quasi-mode stage of internal flows to derive the pertinent periods and damping times.
Results. The periods and damping times that we derive for two-circular-tube setups justify the available modal results found with the T-matrix approach. Regardless of cross-sectional shapes, our nonuniform layers feature the development of small-scale shears and energy accumulation around Alfvén resonances, indicative of resonant absorption and phase mixing. As with two-circular-tube systems, our configurational symmetries still make it possible to classify lower-order kink motions by the polarization and symmetric properties of the internal flows; hence, such motions are labeled as S​x and Ax. However, the periods and damping times for two-elliptic-tube setups further depend on cross-sectional aspect ratios, with Ax motions occasionally damped less rapidly than S​x motions. We find uncertainties up to ∼20% (∼50%) for the axial Alfvén time (the inhomogeneity lengthscale) if the periods (damping times) computed for two-elliptic-tube setups are seismologically inverted with canonical theories for isolated circular tubes.
Conclusions. The effects of loop interactions and cross-sectional shapes need to be considered when the periods, and in particular the damping times, are seismologically exploited for coordinated transverse displacements in adjacent coronal loops.
Towards the epitaxial growth of Au thin films on MgO substrates for plasmonic applications
Authors: Celebrano Michele , Savoini Matteo , Biagioni Paolo , Della Valle Giuseppe , Pellegrini Giovanni , Cantoni Matteo , Rinaldi Christian , Cattoni Andrea , Petti Daniela , Bertacco Riccardo , Duò Lamberto , Finazzi Marco 
Published: March 2024

Surface Plasmon Polaritons (SPPs) in Au thin films are nowadays intensively exploited for sensing applications that leverage the strong optical field confinement at the metal/dielectric interface and the easy functionalization of the Au surface. Moreover, Au thin films represent one of the common starting points for the top-down nanofabrication of plasmonic nanostructures supporting localized resonances. In this framework, strategies for the growth of high-quality Au films on transparent substrates are crucial and not yet fully established. In this study, we exploit MgO(001) substrates for the growth of thin (about 45 nm) Au films, also including an additional buffer layer of Fe. We successfully demonstrate Au samples with reduced roughness and presenting Low-Energy Electron Diffraction (LEED) features, indicating a high degree of crystalline ordering. This is supported by the experimental evidence of an increased (by almost a factor of 3) propagation length compared to a reference Au sample grown on standard glass slides, which is however still significantly lower than the one expected from first principles.
Lessons Learnt from Imaging Review of Interval Breast Cancers in a Single Center in the UK National Breast Screening Program
Authors: Lee Jia Mang , Jantarang Palida , Rengabashyam Bhavani 
Published: March 2024

AbstractFalse-negative mammograms are a part of any screening program and the National Breast Screening Program in the United Kingdom is no exception. Every year, 2.5 million women have screening mammograms in the United Kingdom. Around 8 per 1,000 women screened are diagnosed with a breast cancer and 3 per 1,000 women will present with an interval breast cancer following a negative screening mammogram and before their next mammogram.Robust quality standards have to be adhered to at every stage in the screening pathway in order to maintain the fine balance between detecting cancers early and avoiding unnecessary false-positive results. As part of this process, there is a mandatory requirement for screening units to review all breast cancers. We present a pictorial illustration of the lessons learnt from such a review in this essay. The cases described here are from one large breast screening unit in the North of England. In this unit, 30,000 to 40,000 women have a screening mammogram each year and these are all double read by human readers. All cases requiring recall and those where there is a disagreement between the first and second human reader go through a consensus/arbitration process involving a minimum of two human readers. Interval cancers are identified through a consistent process outlined by the screening program and are then subjected to a review by a minimum of two reviewers. In this process, the reviewers have access to the false-negative mammograms along with all priors that were available at the time of initial read. The reviewers make a decision on whether the initial mammogram is normal or abnormal without seeing the diagnostic mammogram with the interval cancer. They also categorize the density of the breast and describe the mammographic abnormality if there is any on a standardized interval cancer data collection form. Finally, they categorize the interval cancer into one of three types—“satisfactory,” “satisfactory with learning points,” or “unsatisfactory.”
Ensemble forecasting of Persian leopard (Panthera pardus saxicolor) distribution and habitat suitability in south-western Iran
Authors: Jamali Fatemeh , Amininasab Seyed Mehdi , Taleshi Hamid , Madadi Hossein 
Published: March 2024

Context Habitat loss and fragmentation are major threats to global biodiversity, especially for wide-ranging apex carnivores. The Persian leopard (Panthera pardus saxicolor) is an endangered species. Although populations of Persian leopards are declining, the species remains widely distributed across large areas of Iran. Aims This study aimed to determine habitat suitability for Persian leopards in the Khaeiz and Sorkh protected area of south-western Iran and to identify the most significant factors influencing their habitat use/selection and spatial distribution. Methods We performed species distribution modelling in two stages: First, we ran the model with three abiotic predictors: slope; aspect; and distance from water resources. In the second stage, modelling was conducted using three ecological predictors: caracal distribution; wild goat distribution; and livestock distribution. Ensemble modelling was applied based on five replicates of eight SDMs (species distribution models; GLM, CTA, FDA, GBM, ANN, MARS, RF and MaxEnt). Key results We observed only minor differences in habitat suitability between the abiotic and ecological models. Habitat suitability for Persian leopards was higher in steeper areas, close to water resources and near the distribution of caracals, livestock and wild goats. The ecological model predicted 2.03% (329 ha) more suitable habitat than the abiotic model did. Conclusions Most habitat suitability models focus on abiotic variables, but we found that ecological variables offer similar predictive power for determining the habitat suitability of Persian leopards. Implications Habitat suitability models for Persian leopards can be used to guide conservation and management decisions. They are also useful indicating where conflicts between predators and humans may occur.
Accelerating Asteroidal Period and Pole Inversion from Multiple Lightcurves Using Parallel Differential Evolution and Cellinoid Shape Model
Authors: Zhang Yong-Xiong , Guo Wen-Xiu , Lu Xiao-Ping , Zheng Hua , Zhao Hai-Bin , Tian Jun , Wang Wei-Lin 
Published: March 2024

Abstract
Determining asteroid properties provides valuable physical insights but inverting them from photometric lightcurves remains computationally intensive. This paper presents a new approach that combines a simplified Cellinoid shape model with the Parallel Differential Evolution (PDE) algorithm to accelerate inversion. The PDE algorithm is more efficient than the Differential Evolution algorithm, achieving an extraordinary speedup of 37.983 with 64 workers on multicore CPUs. The PDE algorithm accurately derives period and pole values from simulated data. The analysis of real asteroid lightcurves validates the method’s reliability: in comparison with results published elsewhere, the PDE algorithm accurately recovers the rotational periods and, given adequate viewing geometries, closely matches the pole orientations. The PDE approach converges to solutions within 20,000 iterations and under one hour, demonstrating its potential for large-scale data analysis. This work provides a promising new tool for unveiling asteroid physical properties by overcoming key computational bottlenecks.
The multi-peak point phenomenon of broadband microwave reflection caused by inhomogeneous plasma
Authors: YANG 杨 Min 敏 , QI 齐 Kaixuan 凯旋 , YANG 杨 Jiuwen 玖文 , JIA 贾 Sa 飒 , LIU 刘 Haoyan 浩岩 , CHEN 陈 Yanyang 燕扬 , LI 李 Jin 瑾 , (李小平) Xiaoping LI 
Published: March 2024

Abstract
During spacecraft re-entry, the challenge of measuring plasma sheath parameters directly contributes to difficulties in addressing communication blackout. In this work, we have discovered a phenomenon of multiple peaks in reflection data caused by the inhomogeneous plasma. Simulation results show that the multi-peak points fade away as the characteristic frequency is approached, resembling a series of gradually decreasing peaks. The positions and quantities of these points are positively correlated with electron density, yet they show no relation to collision frequency. This phenomenon is of significant reference value for future studies on the spatial distribution of plasmas, particularly for using microwave reflection signals in diagnosing the plasma sheath.
Incorporating network diffusion and peak location information for better single-cell ATAC-seq data analysis
Authors: Yu Jiating , Leng Jiacheng , Hou Zhichao , Sun Duanchen , Wu Ling-Yun 
Published: March 2024

Abstract
Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) data provided new insights into the understanding of epigenetic heterogeneity and transcriptional regulation. With the increasing abundance of dataset resources, there is an urgent need to extract more useful information through high-quality data analysis methods specifically designed for scATAC-seq. However, analyzing scATAC-seq data poses challenges due to its near binarization, high sparsity and ultra-high dimensionality properties. Here, we proposed a novel network diffusion–based computational method to comprehensively analyze scATAC-seq data, named Single-Cell ATAC-seq Analysis via Network Refinement with Peaks Location Information (SCARP). SCARP formulates the Network Refinement diffusion method under the graph theory framework to aggregate information from different network orders, effectively compensating for missing signals in the scATAC-seq data. By incorporating distance information between adjacent peaks on the genome, SCARP also contributes to depicting the co-accessibility of peaks. These two innovations empower SCARP to obtain lower-dimensional representations for both cells and peaks more effectively. We have demonstrated through sufficient experiments that SCARP facilitated superior analyses of scATAC-seq data. Specifically, SCARP exhibited outstanding cell clustering performance, enabling better elucidation of cell heterogeneity and the discovery of new biologically significant cell subpopulations. Additionally, SCARP was also instrumental in portraying co-accessibility relationships of accessible regions and providing new insight into transcriptional regulation. Consequently, SCARP identified genes that were involved in key Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to diseases and predicted reliable cis-regulatory interactions. To sum up, our studies suggested that SCARP is a promising tool to comprehensively analyze the scATAC-seq data.
Benchmarking multi-omics integration algorithms across single-cell RNA and ATAC data
Authors: Xiao Chuxi , Chen Yixin , Meng Qiuchen , Wei Lei , Zhang Xuegong 
Published: March 2024

Abstract
Recent advancements in single-cell sequencing technologies have generated extensive omics data in various modalities and revolutionized cell research, especially in the single-cell RNA and ATAC data. The joint analysis across scRNA-seq data and scATAC-seq data has paved the way to comprehending the cellular heterogeneity and complex cellular regulatory networks. Multi-omics integration is gaining attention as an important step in joint analysis, and the number of computational tools in this field is growing rapidly. In this paper, we benchmarked 12 multi-omics integration methods on three integration tasks via qualitative visualization and quantitative metrics, considering six main aspects that matter in multi-omics data analysis. Overall, we found that different methods have their own advantages on different aspects, while some methods outperformed other methods in most aspects. We therefore provided guidelines for selecting appropriate methods for specific scenarios and tasks to help obtain meaningful insights from multi-omics data integration.
scENCORE: leveraging single-cell epigenetic data to predict chromatin conformation using graph embedding
Authors: Duan Ziheng , Xu Siwei , Sai Srinivasan Shushrruth , Hwang Ahyeon , Lee Che Yu , Yue Feng , Gerstein Mark , Luan Yu , Girgenti Matthew , Zhang Jing 
Published: March 2024

Abstract
Dynamic compartmentalization of eukaryotic DNA into active and repressed states enables diverse transcriptional programs to arise from a single genetic blueprint, whereas its dysregulation can be strongly linked to a broad spectrum of diseases. While single-cell Hi-C experiments allow for chromosome conformation profiling across many cells, they are still expensive and not widely available for most labs. Here, we propose an alternate approach, scENCORE, to computationally reconstruct chromatin compartments from the more affordable and widely accessible single-cell epigenetic data. First, scENCORE constructs a long-range epigenetic correlation graph to mimic chromatin interaction frequencies, where nodes and edges represent genome bins and their correlations. Then, it learns the node embeddings to cluster genome regions into A/B compartments and aligns different graphs to quantify chromatin conformation changes across conditions. Benchmarking using cell-type-matched Hi-C experiments demonstrates that scENCORE can robustly reconstruct A/B compartments in a cell-type-specific manner. Furthermore, our chromatin confirmation switching studies highlight substantial compartment-switching events that may introduce substantial regulatory and transcriptional changes in psychiatric disease. In summary, scENCORE allows accurate and cost-effective A/B compartment reconstruction to delineate higher-order chromatin structure heterogeneity in complex tissues.
FusionNW, a potential clinical impact assessment of kinases in pan-cancer fusion gene network
Authors: Yang Chengyuan , Kumar Himansu , Kim Pora 
Published: March 2024

AbstractKinase fusion genes are the most active fusion gene group in human cancer fusion genes. To help choose the clinically significant kinase so that the cancer patients that have fusion genes can be better diagnosed, we need a metric to infer the assessment of kinases in pan-cancer fusion genes rather than relying on the sample frequency expressed fusion genes. Most of all, multiple studies assessed human kinases as the drug targets using multiple types of genomic and clinical information, but none used the kinase fusion genes in their study. The assessment studies of kinase without kinase fusion gene events can miss the effect of one of the mechanisms that enhance the kinase function in cancer. To fill this gap, in this study, we suggest a novel way of assessing genes using a network propagation approach to infer how likely individual kinases influence the kinase fusion gene network composed of ~5K kinase fusion gene pairs. To select a better seed of propagation, we chose the top genes via dimensionality reduction like a principal component or latent layer information of six features of individual genes in pan-cancer fusion genes. Our approach may provide a novel way to assess of human kinases in cancer.
Translational bioinformatics and data science for biomarker discovery in mental health: an analytical review
Authors: Bhuvaneshwar Krithika , Gusev Yuriy 
Published: March 2024

Abstract
Translational bioinformatics and data science play a crucial role in biomarker discovery as it enables translational research and helps to bridge the gap between the bench research and the bedside clinical applications. Thanks to newer and faster molecular profiling technologies and reducing costs, there are many opportunities for researchers to explore the molecular and physiological mechanisms of diseases. Biomarker discovery enables researchers to better characterize patients, enables early detection and intervention/prevention and predicts treatment responses. Due to increasing prevalence and rising treatment costs, mental health (MH) disorders have become an important venue for biomarker discovery with the goal of improved patient diagnostics, treatment and care. Exploration of underlying biological mechanisms is the key to the understanding of pathogenesis and pathophysiology of MH disorders. In an effort to better understand the underlying mechanisms of MH disorders, we reviewed the major accomplishments in the MH space from a bioinformatics and data science perspective, summarized existing knowledge derived from molecular and cellular data and described challenges and areas of opportunities in this space.
Development and Validation of a New Reversed Phase HPLC Method for the Quantitation of Azithromycin and Rifampicin in a Capsule Formulation
Authors: Patel Foram , Kotadiya Rajendra , Patel Rashmin , Patel Mrunali 
Published: March 2024

Abstract
This research aimed to develop a new method for simultaneously estimating the presence of azithromycin (AZT) and rifampicin (RIF) in a capsule formulation using reverse-phase high-performance liquid chromatography. The developed method utilized a Gemini column with a 60:40% v/v acetonitrile and potassium dihydrogen phosphate mobile phase, a flow rate of 1 mL/min, and an injection volume of 20 μL. The detection wavelengths of 210 and 254 nm for AZT and RIF, respectively, were used. Validation ensures specificity with a peak purity index &gt; 0.99999 for AZT and &gt;0.99995 for RIF, affirming unambiguous analyte detection. The system suitability test, within acceptable limits, validates method reliability. Linearity calibration curves (R2 = 0.998) cover a 25–150% target concentration range. Accuracy studies employing the standard addition method yield recovery values between 96.6 and 103.9% for both drugs, confirming method accuracy. Precision studies reveal % relative standard deviation values consistently below 2%, highlighting reproducibility. Robustness testing supports method reliability under varying conditions. Application to a pharmaceutical capsule formulation demonstrates the method’s practicality, accurately quantifying AZT (98.30%) and RIF (99.37%). This study provides a validated analytical approach for simultaneous quantification in commercial pharmaceutical products containing both drugs, enhancing pharmaceutical quality control for critical antibiotics in complex formulations.