bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fabrication of broadband-emissive micro/nanostructures using two-photon lithography
Authors: Singh Gaurav Pratap , Jaiswal Arun , Joshi Sarika , Soni Himanshu , Saxena Sumit , Shukla Shobha 
Published: December 2024

Abstract
The development of broadband emissive micro/nanoscale structures has enabled unprecedented opportunities to innovate multifunctional devices with applications in lighting, display, sensing, biomedical, photovoltaics, and optical communication. Realization of these micro/nanostructures require multi-step processing, and depends on sophisticated, complex, time-consuming, expensive, and conventional nanofabrication techniques such as mask-based photolithography, electron beam lithography, reactive ion etching. Precise control over z-axis features with a subwavelength resolution for the fabrication of 3D features is a challenge using these methods. Thus, the traditional methods often fall short of meeting these requirements simultaneously. Fabrication of emissive structures demand techniques that offer material compatibility, high resolution, and structural complexity. Here, we report single-step fabrication of 1D, 2D, and 3D broadband emissive micro/nanostructures using two-photon lithography. The broadband emissive resin used for fabricating these structures is made by combining synthesized functionalized carbon quantum dots with a commercially available acrylate-based resin. The resulting structures demonstrate excellent broadband emissive properties in the visible range under UV-Vis excitation. We have observed consistent emission across the fabricated structures along with good thermal and optical stability. Furthermore, we can tune the emission properties of the micro/nanostructures by modifying the functionalization/doping of the quantum dots. These micro/nanostructures have the potential to be used as fundamental components in photonics, particularly in the fields of biophotonics, sensing, and optoelectronics, and could drive new innovations in these areas.
Impact of macrohemodynamic manipulations during cardiopulmonary bypass on finger microcirculation assessed by photoplethysmography signal components
Authors: Tusman Gerardo , Böhm Stephan H , Fuentes Nora , Acosta Cecilia M , Absi Daniel , Climente Carlos , Suarez Sipmann Fernando 
Published: December 2024

Abstract

Objective. Continuous monitoring of the hemodynamic coherence between macro and microcirculation is difficult at the bedside. We tested the role of photoplethysmography (PPG) to real-time assessment of microcirculation during extreme manipulation of macrohemodynamics induced by the cardiopulmonary bypass (CPB). Approach. We analyzed the alternating (AC) and direct (DC) components of the finger PPG in 12 patients undergoing cardiac surgery with CPB at five moments: (1) before-CPB; (2) CPB-start, at the transition from pulsatile to non-pulsatile blood flow; (3) CPB-aortic clamping, at a sudden decrease in pump blood flow and volemia.; (4) CPB-weaning, during step-wise 20% decreases in pump blood flow and opposite proportional increases in native pulsatile blood flow; and (5) after-CPB. Main results. Nine Caucasian men and three women were included for analysis. Macrohemodynamic changes during CPB had an immediate impact on the PPG at all studied moments. Before-CPB the AC signal amplitude showed a median and IQR values of 0.0023(0.0013). The AC signal completely disappeared at CPB-start and at CPB-aortic clamping. During CPB weaning its amplitude progressively increased but remained lower than before CPB, at 80% [0.0008 (0.0005); p < 0.001], 60% [0.0010(0.0006); p < 0.001], and 40% [0.0013(0.0009); p = 0.011] of CPB flow. The AC amplitude returned close to Before-CPB values at 20% of CPB flow [0.0015(0.0008); p = 0.081], when CPB was completely stopped [0.0019 (0.0009); p = 0.348], and at after-CPB [0.0021(0.0009); p = 0.687]. The DC signal Before-CPB [0.95(0.02)] did not differ statistically from CPB-start, CPB-weaning and After-CPB. However, at CPB-aortic clamping, at no flow and a sudden drop in volemia, the DC signal decreased from [0.96(0.01)] to [0.94(0.02); p = 0.002]. Significance. The macrohemodynamic alterations brought on by CPB were consistent with changes in the finger’s microcirculation. PPG described local pulsatile blood flow (AC) as well as non-pulsatile blood flow and volemia (DC) in the finger. These findings provide plausibility to the use of PPG in ongoing hemodynamic coherence monitoring.
pyPCG: a Python toolbox specialized for phonocardiography analysis
Authors: Müller Kristóf , Hatvani Janka , Koller Miklós , Goda Márton Áron 
Published: December 2024

Abstract

Objective. Phonocardiography has recently gained popularity in low-cost and remote monitoring, including passive fetal heart monitoring. The development of methods which analyze phonocardiographic data tries to capitalize on this opportunity, and in recent years a multitude of such algorithms and models have been published. In these approaches there is little to no standardization and multiple parts of these models have to be reimplemented on a case-by-case basis. Datasets containing heart sound recordings also lack standardization in both data storage and labeling, especially in fetal phonocardiography. Approach. We are presenting a toolbox that can serve as a basis for a future standard framework for heart sound analysis. This toolbox contains some of the most widely used processing steps and with these, complex analysis pipelines can be created. These functions can be tested individually. Main results. Due to the interdependence of the steps, we validated the current segmentation stage using two phonocardiogram (PCG) datasets, a fetal dataset comprising 50 one-minute abdominal PCG recordings, which include 6758 S1 and 6729 S2 labels and a filtered version of the dataset used in the 2022 PhysioNet Challenge, containing 413 records with 9795 S1 and 9761 S2 labels. Our results were compared to other common and publicly available segmentation methods, such as peak detection with the Neurokit2 library, and the hidden semi-Markov model by Springer et al. Our best model achieved a 96.1% F1 score and 11.7 ms mean absolute error for fetal S1 detection, and 81.3% F1 score and 50.5 ms mean absolute error for PhysioNet S1 detection. Significance. Our detection method outperformed all other tested methods on the fetal dataset and achieved results comparable to the state of the art on the PhysioNet dataset. Accurate segmentation of signals is critical for the calculation of accurate statistical measures and the creation of classification models. Our toolbox contains functions for both feature extraction and calculation of statistics which are compatible with the previous steps. All of our methods can be fine tuned for specific datasets. pyPCG is available on https://pypcg-toolbox.readthedocs.io/en/latest/.
Performance evaluation of gate engineered ferroelectric MIMOS for analog/electrical IC applications
Authors: Pathak Yash , Verma Kajal , Dhar Malhotra Bansi , Chaujar Rishu 
Published: December 2024

Abstract
This work examines various materials for gate electrode for enhancing the performance of M-Fe-MIMOS (Metal Ferroelectric Metal Insulator Metal Oxide Semiconductor Field Effect Transistor (MOSFET)). The device is analysed for different analog, electrical and RF parameters with gate materials such as chromium, tungsten and palladium. The gate stacked attached to MOSFET device consists ferroelectric layer sandwiched with insulator for focusing on reliability and stability of M-Fe-MIMOS. The palladium gate material for M-Fe-MIMOS(spacer) shows better analog parameters such as improvement in leakage current by 106 times that results 107 times higher switching ratio as compare to chromium. Also with higher threshold voltage by 428% and lower subthreshold swing by 340% as compare to chromium, M-Fe-MIMOS(spacer) shows better immunity towards various noise distortions. The electrical properties of the device are analysed in terms of electric field , electric potential and energy band structure.All the analysed results indicate that palladium as a gate material for the M-Fe-MIMOS shows most improved electrical performance and can further be used for various applications in nanoelectronic devices and integrated circuit (IC) design.
Model-independent reconstruction of UV luminosity function and reionization epoch
Authors: Adak Debabrata , Hazra Dhiraj Kumar , Mitra Sourav , Krishak Aditi 
Published: December 2024

Abstract
We conduct a first comprehensive study of the Luminosity Function (LF) using a non-parametric approach. We use Gaussian Process to fit available luminosity data between redshifts z ∼ 2-8. Our free-form LF in the non-parametric approach rules out the conventional Schechter function model to describe the abundance-magnitude relation at redshifts z=3 and 4. Hints of deviation from the Schechter function are also noticed at redshifts 2, 7 and 8 at lower statistical significance. Significant deviation starts for brighter ionizing sources at M
UV ≲ -21. The UV luminosity density data at different redshifts are then derived by integrating the LFs obtained from both methods with a truncation magnitude of -17. In our analysis, we also include the first 90 arcmin2 JWST/NIRCam data at z ∼ 9-12. Since at larger magnitudes, we do not find major deviations from the Schechter function, the integrated luminosity density differs marginally between the two methods. Finally, we obtain the history of reionization from a joint analysis of UV luminosity density data along with the ionization fraction data and Planck observation of Cosmic Microwave Background. The history of reionization is not affected by the deviation of LFs from Schechter function at lower magnitudes. We derive reionization optical depth to be τ
re = 0.0494+0.0007
-0.0006 and the duration between 10% and 90% completion of ionization process is found to be Δ z ∼ 1.627+0.059
-0.071.
Cosmic cartography: Bayesian reconstruction of the galaxy density informed by large-scale structure
Authors: Leyde Konstantin , Baker Tessa , Enzi Wolfgang 
Published: December 2024

Abstract
The dark sirens method combines gravitational waves and catalogs of galaxies to constrain
the cosmological expansion history, merger rates and mass distributions of compact objects, and
the laws of gravity. However, the incompleteness of galaxy catalogs means faint potential host
galaxies are unobserved, and must be modeled to avoid inducing a bias. The majority of dark sirens
analyses to date assume that the missing galaxies are distributed uniformly across the sky, which
is clearly unphysical. We introduce a new Bayesian approach to the reconstruction of galaxy
catalogs, which makes full use of our knowledge of large-scale structure. Our method quantifies
the uncertainties on the estimated true galaxy number count in each voxel, and is marginalized
over cosmological parameters and bias parameters. Crucially, our method further assesses the
(absolute) magnitude distribution of galaxies, which is not known from the galaxy catalog
itself. We present the details of our method and validate our approach on a galaxy catalog
associated to the Millennium Simulation. The tools developed here generate physically-informed and
robust host galaxy reconstructions, enabling more informative dark sirens analyses. Stage IV
galaxy surveys will display greater redshift overlap with GW observations, whilst remaining
incomplete — emphasizing the importance of our work.
CMB constraints on natural inflation with gauge field production
Authors: Alam Khursid , Dutta Koushik , Jaman Nur 
Published: December 2024

Abstract
The natural inflation model with a periodic cosine potential is ruled out by recent Planck 2018 data for the decay constant f ≲ 5.5 M
Pl. If the Planck data is combined with the BICEP Keck array and BAO data, the model is excluded (at 2-σ) for all values of f. In this context, we revisit the model when the pseudoscalar inflation ϕ is coupled with a gauge field via a coupling of the form α/fϕ
FF̃, where F(F̃) denotes the gauge field (dual) strength tensor, and α is the coupling constant. The back-reactions associated with the gauge field production during the later stages of inflation extend the duration of inflation. We numerically evaluate the dynamics of the fields while neglecting the effects due to the perturbations in the inflaton field. It allows us to determine the scalar and tensor power spectra leading to the calculations of observables at the Cosmic Microwave Background (CMB) scales. We find that the natural inflation model survives the test of the latest data only for a certain range of the coupling constant α. Our analysis shows that the latest constraints coming from the scalar spectral index are more stringent than the ones arising from the non-gaussianities and the running of the scalar spectrum. This leads to lower and upper bounds on ξ
*, the parameter that controls the growth of the gauge field.
Design and photophysical characterization of quasi-intrinsic fluorescent probes utilized in DNA sequencing
Authors: Zhang 张 Yaning 雅宁 , Lyu 吕 Yongkang 永康 , Cao 曹 Zhizheng 智正 , Chen 陈 Xiaolin 晓琳 , Meng 孟 Qingtian 庆田 , Zhang 张 Changzhe 常哲 
Published: December 2024

Abstract
To understand the gene-based biological processes in-depth, the single-molecule real-time sequencing has drawn increasing attention with promoted by the Human Genome Project. Herein, a set of newly designed canonical fluorescent bases (Ay, tC, Gb, Tp) are proposed for four-color DNA sequencing. These quasi-intrinsic probes are derived from the fluorophore replacement and ring expansion on natural bases, which still keep the pyrimidine or purine underlying skeleton and Watson–Crick hydrogen bonding face to allow minimal perturbation to the native DNA duplex. More importantly, these nucleobase analogues possess red-shifted absorption and efficient photoluminescence due to the enhanced π-conjugation in character. Meanwhile, the four analogues could generate distinct emission wavelength (Δλ ∼ 50 nm) for real-time sequencing. To assess the biological employment of the proposed biosensors, the effects of base pairing and linking deoxyribose are also considered.
Modeling a Relativistic Star in Multi-layered Settings
Authors: Lighuda Avirt S. , Mathias Alberto K. 
Published: December 2024

Abstract
This paper yields a new exact solution for dense stellar objects by employing the Einstein–Maxwell system of differential equations. The established model comprises three interior layers with distinguishable equations of state (EoSs): the polytropic EoS at the core layer, the quadratic EoS at the intermediate layer and the modified Van der Waals EoS at the envelope layer. The physical features indicate that the matter variables, metric functions and other physical conditions are viable with dense astrophysical objects. Excitingly, this model is an extension solution of the two-layered model generated by Sunzu and Lighuda. The layers are matched gently across the junctions with the care of the Reissner–Nordström exterior spacetime. Utilizing our model, star masses and radii compatible with observations and satisfactorily known objects are generated. The findings from this paper may be useful to describes purported strange stars such as SAX J1808.4-3658 and binary stars such as Vela X-1.
Preictal period optimization for deep learning-based epileptic seizure prediction
Authors: Koutsouvelis Petros , Chybowski Bartlomiej , Gonzalez-Sulser Alfredo , Abdullateef Shima , Escudero Javier 
Published: December 2024

Abstract

Objective. Accurate seizure prediction could prove critical for improving patient safety and quality of life in drug-resistant epilepsy. While deep learning-based approaches have shown promising performance using scalp electroencephalogram (EEG) signals, the incomplete understanding and variability of the preictal state imposes challenges in identifying the optimal preictal period (OPP) for labeling the EEG segments. This study introduces novel measures to capture model behavior under different preictal definitions and proposes a data-centric deep learning methodology to identify the OPP. Approach. We trained a competent subject-specific CNN-Transformer model to detect preictal EEG segments using the open-access CHB-MIT dataset. To capture the temporal dynamics of the model’s predictions, we fitted a sigmoidal curve to the model outputs obtained from uninterrupted multi-hour EEG recordings prior to seizure onset. From this fitted curve, we derived key performance measures reflecting the timing of predictions, including classifier convergence, average error, output stability, and the transition between interictal and preictal states. These measures were then combined to compute the Continuous Input–Output Performance Ratio, a novel metric designed to comprehensively compare model behavior across different preictal definitions (60, 45, 30, and 15 min) and suggest the OPP for each patient. Main results. The CNN-Transformer model achieved state-of-the-art performance (area under the curve of 99.35% and F1-score of 97.46%) using minimally pre-processed EEG signals. The 60-minute preictal definition was associated with earlier seizure prediction, lower error in the preictal state, and reduced output fluctuations, leading to significantly higher CIOPR scores (p < 0.001). Conventional accuracy-related metrics (sensitivity, specificity, F1-score) were less sensitive to varying preictal definitions and often discordant with CIOPR findings. Cross- and intra-patient heterogeneities in the prediction times were also observed, complicating the establishment of a global preictal interval. Significance. The newly developed metrics demonstrate that varying the preictal period significantly impacts the timing of predictions in ways not captured by conventional accuracy-related metrics. Understanding this impact and the inter-seizure heterogeneities is essential for developing intelligent systems tailored to individual patient needs and for underlining practical limitations in detecting the preictal period in real-world clinical applications.
The effect of ZnO nanoparticle mass from pineapple peel via green synthesis on degradation of methylene blue by photocatalytic activity
Authors: Setyarsih W , Ardiansyah F F , Ma’arif M S , Ferdianto S P , Rohmawati L 
Published: December 2024

Abstract
Water pollution due to the use of bright colors and patterns in the textile industry derived from hazardous chemicals can damage the environment. For this reason, special treatment is needed in waste processing to reduce water pollution, one of which is the photocatalytic method. ZnO nanoparticles have potential in photocatalyst applications for pollutant degradation because they are non-toxic, biocompatible, and cheap. This material can be obtained using the green synthesis method from pineapple peel extract used as a bioreduction. So, this research aims to determine the effect of ZnO nanoparticle catalyst mass on the degradation of methylene blue dye in photocatalytic activity under UV light irradiation. The results show that the size of the catalyst mass influences the ability to degrade methylene blue. In this case, 5, 8, and 12 mg catalyst masses could degrade dyes by 97.52%, 98.51%, and 99.82% within 180 minutes. Thus, ZnO nanoparticles effectively degrade methylene blue dye under UV irradiation.
Summer tropical Atlantic drives autumn North American Arctic warming through western Pacific Bridge
Authors: Lou Wei , Sun Cheng , Li Jianping 
Published: December 2024

Abstract
The Arctic climate system exhibits dramatic changes in autumn, yet its connection to the tropics remains unclear. This study leverages inter-basin/region teleconnectivity (IB(R)T) analysis to unveil the key teleconnected regions responsible for the connection between autumn Arctic temperature and tropical sea surface temperature (SST). A robust positive correlation is identified between North American Arctic (NAA) temperatures and North Tropical Atlantic (NTA) SST, with the NTA SST leading by one season. Observational evidence reveals that western Pacific (WP) subtropical high (WPSH) and SST play an intermediary role in this cross-seasonal tropical-Arctic connection. Summertime NTA warming triggers an intensification of the WPSH, subsequently inducing autumnal warming of WP SST via inter-basin interactions. This intensified WP convection generates a Rossby wave train propagating from the Northern WP eastward towards the NAA, ultimately leading to an anomalous high over the NAA. The increased atmospheric thickness and air temperature enhances downward longwave radiation, further contributing to surface warming over the NAA. The linear baroclinic model experiments, forced with thermal anomalies corresponding to WP SST warming, successfully reproduce the observed atmospheric circulation response and the associated air temperature changes over the NAA. Our findings provide insights into the role of inter-basin connections in Tropical-Arctic linkages.
Adapting crop production to water scarcity
Authors: Perez-Quesada Gabriela , Hendricks Nathan P , Tack Jesse , Steward David R 
Published: December 2024

Abstract
Rapidly growing global food demand requires increased crop production that is supported by groundwater irrigation in many agricultural regions. This pressure on water sources has led to groundwater depletion already and is likely to increase moving forward as producers seek adaptation mechanisms to mitigate climate change impacts. Here we utilize high-resolution data on crop production and groundwater levels to estimate the nonlinear impacts of groundwater levels for corn and wheat production across the High Plains Aquifer in the central United States. Our models extend previous approaches by directly accounting for producer adaptation and feedback effects in the coupled natural and human system. This analysis reveals that continuing the current path of depletion will decrease corn and wheat production in the region by 6.75% and 1.08% in 2050, with the impacts primarily arriving via reductions in irrigated acreage. We provide evidence of substantial spatial heterogeneity of these impacts, which is notable for a region that employs largely homogeneous technology and management practices throughout. The largest production losses are associated with the Central and Southern portion and are as large as 40% for corn production in the Texas portion of the aquifer. Overall, our findings highlight the importance of developing solutions that can conserve the aquifer while avoiding significant losses in current production.