bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structural and electrical properties of Ni-doped MnZn ferrite synthesized via solid state reaction
Authors: Mendoza JC , Arcangel M , Nucum JA , Cervera RB 
Published: November 2024

Abstract
MnZn ferrite is commonly studied due to its exceptional magnetic, electric, and catalytic properties, making it a promising material for hyperthermia applications, magnetic fluid, memory storage devices, drug delivery, virus detection, and photocatalysis. It was identified that divalent nickel cation substitution increases the ferrite conductivity and dielectric constant. This study targets to synthesize Ni-doped MnZn ferrite by a simpler, more convenient, and economic solid state reaction, and to investigate its influence on the structural and electrical properties of MnZn ferrite. Mn0.5-xNixZn0.5Fe2O4 (x=0.1 and 0.2) was synthesized via solid state reaction with calcination and sintering temperature at 1000 °C and 1200 °C, respectively. The structural and electrical properties of the resulting pellet were characterized by x-ray diffraction (XRD), scanning electron microscopy (SEM), and electrochemical impedance spectroscopy (EIS). The XRD profile, indexed as cubic spinel, indicated good crystallinity and no impurity peaks were detected. As Ni2+ dopant concentration increases, a decrease in lattice parameter and an increase in theoretical and apparent densities were observed. This is attributed to the smaller ionic radius and greater mass of Ni2+ relative to Mn2+. Varying Ni2+ concentration significantly modified the morphology of the ferrite. At higher Ni2+, less uniformity in shape and size was evident in the SEM micrograph since Ni promotes aggregation at the surface. An increase in dielectric constant was also observed with increasing Ni2+ molar concentration. Since Ni2+ presents a high tendency to occupy B sites, its substitution promotes Fe2+ migration to A sites, augmenting Fe2+/Fe3+ hopping resulting in an increase in polarization and dielectric constant.
Comparison of single-vs dual-chamber microbial electrolysis cells performance for biohydrogen production
Authors: Isla-Cabaraban M T , Paclijan S , Logico N P , Dalagan J M , Gonzales F A , Cabaraban G M S , Tan N P 
Published: November 2024

Abstract
In this study, fed batch single- and dual-chamber microbial electrolysis cells (MECs) were operated to compare differences in the electrohydrogenesis performance at 0.8 V applied voltage and hydraulic retention time (HRT) of 48 h. Results showed that current intensity, current density, COD removal efficiency, and H2 production rate were higher in the dual-chamber MEC than in the single-chamber configuration. Electromethanogenesis and homoacetogenesis scavenged the H2 from electrohydrogenesis thus reducing H2 generation, as demonstrated by cathodic efficiencies less than 10%. It appears that homoacetogenesis overshadowed H2 production in the dual-chamber MEC, as reflected by a coulombic efficiency greater than 100%, likely induced by a high H2 partial pressure. These results portray MECs as an energy-efficient scheme for bioH2 production in addition to removal of pollutants (COD). This study presented valuable information when deciding on suitable reactors and optimizing reactor design.
Generation mechanism and anti-friction effect evaluation of continuous micro-groove texture machined by ball-end milling process
Authors: Huang Weimin , Huang Yuchao , Li Anbang , Zhou Xiangyuan , Wan Cong , Wang Guijie 
Published: November 2024

Abstract
Based on ball-end milling cutter characteristics, it takes advantage of the flexibility and controllability of its tool path during processing. The aim of this research is to process continuous microgroove textured surfaces by using ball-end milling cutters. Evaluation of the anti-friction effect of continuous microgroove texture by combining simulation and friction tests. The results indicate that, the surface topography of continuous microgrooves can be obtained by combining small feed per tooth and large radial cutting depth. The radial depth of cut and tool radius affect aspect ratio of microgrooves. The bearing capacity of the oil film shows an increasing and then decreasing trend with the increase of radial depth of cut and orientation angle. The radial depth of cut increased from 0.1 mm to 0.3 mm, resulting in a maximum 4.87% increase in the bearing capacity of oil film because of the enhanced wedge effect. However, further increase in radial depth of cut leads to increased vortex, weakening the wedge effect. The oil film bearing capacity is reduced so that the friction coefficient increases by a maximum of 510%. Moreover, as the orientation angle increases from 10° to 20°, the bearing capacity of the oil film increases by 22.7%. The minimum friction coefficient currently is 0.0215. However, when the microgroove orientation angle is further increased, the countercurrent effect is enhanced and the dynamic pressure effect is weakened, which finally leads to a decrease in the bearing capacity of the oil film. The friction coefficient has increased by 30.2% maximum. This study is of great significance which provides a new method for guiding the friction reduction on the die surface.
Development of age-specific population-based paediatric computational phantoms for image-based data mining and other radiotherapy applications
Authors: Ahmad Reem , Cantwell Jessica , Borrelli Carolina , Lim Pei , D’Souza Derek , Gaze Mark N , Moinuddin Syed , Gains Jennifer , Veiga Catarina 
Published: November 2024

Abstract

Objective. Computational anatomical models have many applications in paediatric radiotherapy. Age-specific computational anatomical models were historically developed to represent average and/or healthy individuals, where cancer patients may present with anatomical variations caused by the disease and/or treatment effects. We developed RT-PAL, a library of computational age-specific voxelized anatomical models tailored to represent the paediatric radiotherapy population. Approach. Data from patients undergoing craniospinal irradiation (CSI) were used (n = 74, median age 7.3y, range: 1–17y). The RT-PAL phantoms were generated using groupwise deformable image registration to spatially normalize and average a sub-set of twenty clinical CTs and contours (n = 74, median age 7.7y, range: 3–14 y). To assess their anatomical and age-dependency plausibility, the RT-PAL models were compared against clinical cancer patient data and two healthy population based libraries of phantoms: the International Commission on Radiological Protection (ICRP) pediatric reference computational phantoms (n = 8, median age 7.5y, range: 1–15y) and a range of 4D paediatric extended cardiac torso (XCAT) phantoms (n = 75, median age 9.1y, range: 1–18y). For each dataset, nineteen organs were segmented on all age models to determine their volume. Each set was evaluated through a linear fit of organ volume with age, where comparisons were made relative to the linear fit of the clinical data. Main Results. Overall good anatomical plausibility was found for the RT-PAL phantoms. The age-dependency reported was comparable to both the clinical data and other phantoms, demonstrating their efficacy as a library of age-specific phantoms. Larger discrepancies with the clinical, ICRP and XCAT organ data were attributable to differences in organ filling, segmentation strategy and age distribution of the datasets, limitations of RT-PAL generation methodology, and/or possible anatomical differences between healthy and cancer populations. Significance. The RT-PAL models showed potential in representing the paediatric radiotherapy cohort, who are most likely to benefit from dedicated, age-specific anatomical phantoms.
Computer-aided diagnosis of early-stage Retinopathy of Prematurity in neonatal fundus images using artificial intelligence
Authors: Raja Sankari V M , Umapathy Snekhalatha 
Published: November 2024

Abstract
Retinopathy of Prematurity (ROP) is a retinal disorder affecting preterm babies, which can lead to permanent blindness without treatment. Early-stage ROP diagnosis is vital in providing optimal therapy for the neonates. The proposed study predicts early-stage ROP from neonatal fundus images using Machine Learning (ML) classifiers and Convolutional Neural Networks (CNN) based pre-trained networks. The characteristic demarcation lines and ridges in early stage ROP are segmented utilising a novel Swin U-Net. 2000 Scale Invariant Feature Transform (SIFT) descriptors were extracted from the segmented ridges and are dimensionally reduced to 50 features using Principal Component Analysis (PCA). Seven ROP-specific features, including six Gray Level Co-occurrence Matrix (GLCM) and ridge length features, are extracted from the segmented image and are fused with the PCA reduced 50 SIFT features. Finally, three ML classifiers, such as Support Vector Machine (SVM), Random Forest (RF), and k- Nearest Neighbor (k-NN), are used to classify the 50 features to predict the early-stage ROP from Normal images. On the other hand, the raw retinal images are classified directly into normal and early-stage ROP using six pre-trained classifiers, namely ResNet50, ShuffleNet V2, EfficientNet, MobileNet, VGG16, and DarkNet19. It is seen that the ResNet50 network outperformed all other networks in predicting early-stage ROP with 89.5% accuracy, 87.5% sensitivity, 91.5% specificity, 91.1% precision, 88% NPV and an Area Under the Curve (AUC) of 0.92. Swin U-Net Convolutional Neural Networks (CNN) segmented the ridges and demarcation lines with an accuracy of 89.7% with 80.5% precision, 92.6% recall, 75.76% IoU, and 0.86 as the Dice coefficient. The SVM classifier using the 57 features from the segmented images achieved a classification accuracy of 88.75%, sensitivity of 90%, specificity of 87.5%, and an AUC of 0.91. The system can be utilised as a point-of-care diagnostic tool for ROP diagnosis of neonates in remote areas.
Numerical study of runaway current impact on sawtooth oscillations in tokamaks
Authors: MA 马 Ruirui 瑞瑞 , ZHAO 赵 Chen 忱 , ZHOU 周 Yao 尧 , LIU 刘 Chang 畅 
Published: November 2024

Abstract
This study investigates the influence of runaway current in runaway plasmas on the dynamics of sawtooth oscillations and resultant loss of runaway electrons (RE) using the 3D magnetohydrodynamic (MHD) code M3D-C

(Jardin et al 2012 J. Comput. Sci. Discovery
6 014002). Using an HL-2A-like equilibrium, we confirm that in the linear phase, the impact of REs on resistive internal kink instabilities is consistent with previous research. In the nonlinear phase, as the runaway current fully replaces the plasmas current, we observe a significant suppression of sawtooth oscillations, with the first sawtooth cycle occurring earlier compared to the case without runaway current. Following the first sawtooth collapse, plasma current density, runaway current density, and safety factor (

) flatten within the

surface, albeit displaying fine structures. Subsequently, the growing high torodial (

) and poloidal (

) mode number modes disrupt the magnetic surfaces, leading to the loss of REs outside the

surface, while minimally affecting the majority of REs well-confined within it. Thus, in the current model, the physical processes associated with the presence of sawtooth oscillations do not effectively dissipate runaway current, as REs are assumed to be collisionless. In addition, the final profile of runaway current density exhibits increased steepening near the

surface in contrast to the initial profile, displaying a distinctive corrugated inhomogeneity influenced by the growing fluctuation of the

component. Finally, detailed convergence tests are conducted to validate the numerical simulations.
Unlocking mode programming with multi-plane light conversion using computer-generated hologram optimisation
Authors: Rothe Stefan , Barbosa Fabio A , Czarske Jürgen W , Ferreira Filipe M 
Published: November 2024

Abstract
Programmable optical devices provide performance enhancement and flexibility to spatial multiplexing systems enabling transmission of tributaries in high-order eigenmodes of spatially-diverse transmission media, like multimode fibre (MMF). Wavefront shaping with spatial light modulators (SLMs) facilitates scalability of the transmission media by allowing for channel diagonalization and quasi-single-input single-output operation. Programmable mode multiplexing configurations like multi-plane light conversion (MPLC) utilise the SLM and offer the potential to simultaneously launch an arbitrary subset of spatial tributaries in any N-mode MMF. Such programmable optical processor would enable the throughput of space-division multiplexing systems to be progressively increased by addressing a growing number of tributaries over one MMF and in this way meet a growing traffic demand—similarly to the wavelength-division multiplexing evolution path. Conventionally, MPLC phasemasks are calculated using the wavefront matching algorithm (WMA). However, this method does not exploit the full potential of programmable mode multiplexers. We show, that computer-generated hologram algorithms like direct search enable significant improvement compared to the traditional WMA-approach. Such gains are enabled by tailored cost functions with dynamic constraints concerning insertion loss as well as mode extinction ratio. We show that average mode extinction ratio can be greatly improved by as much as

≈

15

dB

at the expense of insertion loss deterioration of less than

3

dB

. One particular feature of programmable mode multiplexers is the adaptability to optimised transmission functions. Besides conventional linearly polarized modes transmission, we employ our approach on Schmidt modes, which are spatial eigenchannels with minimum crosstalk derived from a measured transmission matrix.
Advanced multi-nozzle electrohydrodynamic printing: mechanism, processing, and diverse applications at micro/nano-scale
Authors: Li Yin , Zhang Guangming , Zhang Jinrun , Song Daosen , Guo Chenxu , Zhou Wei , Fu Zhiguo , Zhu Xiaoyang , Wang Fei , Duan Yongqing , Dong Jingyan , Lan Hongbo 
Published: November 2024

Abstract
Electrohydrodynamic (EHD) jet printing represents a novel micro/nano-scale additive manufacturing process that utilises a high-voltage induced electric field between the nozzle and the substrate to print micro/nanoscale structures. EHD printing is particularly advantageous for the fabrication on flexible or non-flat substrates and of large aspect ratio micro/nanostructures and composite multi-material structures. Despite this, EHD printing has yet to be fully industrialised due to its low throughput, which is primarily caused by the limitations of serial additive printing technology. The parallel multi-nozzle array-based process has become the most promising option for EHD printing to achieve large-scale printing by increasing the number of nozzles to realise multichannel parallel printing. This paper reviews the recent development of multi-nozzle EHD printing technology, analyses jet motion with multi-nozzle, explains the origins of the electric field crosstalk effect under multi-nozzle and discusses several widely used methods for overcoming it. This work also summarises the impact of different process parameters on multi-nozzle EHD printing and describes the current manufacturing process using multi-nozzle as well as the method by which they can be realised independently. In addition, it presents an additional significant utilisation of multi-nozzle printing aside from enhancing single-nozzle production efficiency, which is the production of composite phase change materials through multi-nozzle. Finally, the future direction of multi-nozzle EHD printing development is discussed and envisioned.
Fabrication of 3D-printed coiled PCL microfibrous bundles using alginate-based biocomposites for bone tissue engineering applications
Authors: Pei Mohan , Hwangbo Hanjun , Kim GeunHyung 
Published: November 2024

Abstract
Biomedical scaffold fabrication has seen advancements in mimicking the native extracellular matrix through intricate three-dimensional (3D) structures conducive to tissue regeneration. Coiled fibrous scaffolds have emerged as promising substrates owing to their ability to provide unique topographical cues. In this study, coiled poly (ϵ-caprolactone) (PCL) fibrous bundles were fabricated using an alginate-based composite system, and processed with 3D printing. The unique structure was obtained through the die-swell phenomenon related to the release of residual stresses from the printed strut, thereby transforming aligned PCL fibers into coiled structures. The effects of printing parameters, such as pneumatic pressure and nozzle moving speed, on fiber morphology were investigated to ensure a consistent formation of coiled PCL fibers. The resulting coiled PCL fibrous scaffold demonstrated higher activation of mechanotransduction signaling as well as upregulation of osteogenic-related genes in human adipose stem cells (hASCs), supporting its potential in bone tissue engineering.
Optimal balanced-norm error estimate of the LDG method for reaction-diffusion problems II: The two-dimensional case with layer-upwind flux
Authors: Cheng Yao , Wang Xuesong , Stynes Martin 
Published: November 2024

A singularly perturbed reaction-diffusion problem posed on the unit square in

R

2

\mathbb {R}^2

is solved numerically by a local discontinuous Galerkin (LDG) finite element method. Typical solutions of this class of 2D problems exhibit boundary layers along the sides of the domain; these layers generally cause difficulties for numerical methods. Our LDG method handles the boundary layers by using a Shishkin mesh and also introducing the new concept of a “layer-upwind flux”—a discrete flux whose values are chosen on the fine mesh (which lies inside the boundary layers) in the direction where the layer weakens. On the coarse mesh, one can use a standard central flux. No penalty terms are needed with these fluxes, unlike many other variants of the LDG method. Our choice of discrete flux makes it feasible to derive an optimal-order error analysis in a balanced norm; this norm is stronger than the usual energy norm and is a more appropriate measure for errors in computed solutions for singularly perturbed reaction-diffusion problems. It will be proved that the LDG method is usually convergent of order

O
(
(

N

−
1

ln
⁡
N

)

k
+
1

)

O((N^{-1}\ln N)^{k+1})

in the balanced norm, where

N
N

is the number of mesh intervals in each coordinate direction and tensor-product piecewise polynomials of degree

k
k

in each coordinate variable are used in the LDG method. This result is the first of its kind for the LDG method applied to this class of problem and is optimal for convergence on a Shishkin mesh. Its sharpness is confirmed by numerical experiments.
Science of Science
Authors: Krauss Alexander 
Published: November 2024

AbstractHow do we drive new knowledge and science? What are their present boundaries? And how can we improve science? We still do not understand these essential questions about science well, even though science is at the foundation of modern society. The field of science of science can provide answers to these foundational questions. The central challenge of the field is integrating the different empirical and theoretical knowledge across disciplines into a holistic field and uncovering the general mechanism driving science across fields. This is the first book to offer an integrated framework for the science of science and thus aims to provide a comprehensive understanding of the foundations and limits of science. The book integrates 14 scientific fields and illustrates how our evolved mind (that enables us to observe, experiment and solve problems) makes doing science possible but also shapes what and how we observe. Our scientific methods and instruments (such as statistics and telescopes) enable us to study a much larger range of phenomena but also have constraints to how we measure them. Institutions and funding shape what knowledge we produce and how we evaluate our evidence, among other influences. By integrating the fields together, we are able to identify the common mechanism that underpins the different factors studied across all these fields: our powerful scientific methods and instruments. The book explains how the sophisticated scientific tools we develop are the main driving force for creating new knowledge and advancing science. This methodological toolbox of ours sets the scope and present limits of what we can know and what is possible in science—while economic, social and historical influences help shape what we study within that scope and those limits. The book offers a unifying theory for the field of science of science—the new-methods-drive-science theory. By better understanding the foundations of science we will also show how we can reduce the constraints and biases that we and our scientific methods and instruments face to advance science and push its present boundaries. This book is written in an easily accessible way for readers interested in understanding how science works.
Describing Science of Science
Authors: Krauss Alexander 
Published: November 2024

AbstractHere we describe the existing landscape of the 14 disparate fields studying science and outline what an integrated science of science can look like by providing a framework for the field. Science of science involves scientists doing science to understand science. When studying science itself, we thus practice the activity being studied. We use scientific evidence to explain what science is and how it works. Different researchers studying science use a different method and unit of analysis and thus study different features of science, including publications and citations, paradigm shifts in scientific theories, criteria for evaluating scientific theories, the social practices of scientists, and so on. Disciplinary isolation has led to simplified and at times contradictory views. Here we illustrate a unified field, without disciplinary divisions, which can be defined as: the field of science of science is the study of science, and especially the foundations, limits and advancement of science and scientific methods, that integrates methods and evidence from across the natural, behavioural and social sciences.
Biology of Science
Authors: Krauss Alexander 
Published: November 2024

AbstractWhat are the evolutionary origins of science and how can they help us understand how we do science today? This chapter illustrates that, like other animals, our ancestors evolved abilities for vision and other senses that enable us to perceive the world. Species like ours require making observations and acquiring knowledge about the world to be able to survive and meet basic needs. Using tools to solve problems, human and non-human animals have a toolkit that they acquire through social learning and experimenting. Our evolution lays the basis for our methodological abilities that we use to be able to do science.
Archaeology of Science
Authors: Krauss Alexander 
Published: November 2024

AbstractArchaeological artefacts that include increasingly sophisticated tools developed by early humans provide evidence for the origin of science. They offer historical evidence of the evolution of our methodological abilities to reason and acquire knowledge that are needed to construct those artefacts and to do science today. We humans have evolved abilities to observe, solve problems, experiment, categorise, reason causally and test ideas or hypotheses. These, together, account for our methodological abilities of the mind we use to be able to develop knowledge and make sense of the world around us. Using these abilities, early humans such as Homo erectus and Neanderthals created complex tools such as hand axes, and early humans also later developed fire-hardened spears and controlled fire, which required making mental representations, inferences and predictions. These evolved human abilities have enabled us to start science and are commonly used in contemporary scientific practice.