bluuebunny/crossref_metadata_2025_split huggingface dataset:
An investigation of the surface topography of wire tool and the modelling of wire electro-spark machined Ti-alloy using ANN
Authors: Sharma Vikas , Misra Joy Prakash , Singhal Sandeep 
Published: November 2024

Abstract
Titanium and its alloys are in demand in the field of biomedical and aerospace engineering because of its high strength-to-weight ratio and anti-corrosive properties. WESM emerged as a processing method as traditional methods could not process because of strain hardening and low material conductivity; however, wire tool consumption contributes to high costs while processing with WESM. The current Article investigates the effect of input factors on wire consumption and their significance level on wire consumption. 81 experimental runs were conducted while taking input factors Spark on, Spark off time, peak current and servo voltage at three levels, each using a full factorial approach. Experimental results were analysed using ANOVA and MLR (Multi-Linear regression). Moreover, ANN modelling is done to model the wire consumption using a 4-10-1 architecture that increased the coefficient of correlation (R2) up to 0.991. Lastly, after processing, the wire tool surface is evaluated using a scanning electron microscope to assess the effect of various input energy levels and find input combinations for minimum wire consumption.
DGTNet:dynamic graph attention transformer network for traffic flow forecasting
Authors: Chen Jing , Li Wuzhi , Chen Shuixuan , Zhang Guowei 
Published: November 2024

Abstract
Graph-based traffic flow prediction plays a crucial role in urban traffic management and planning. In this paper, we propose a novel Dynamic Graph Attention Transformer Network (DGTNet), which is designed to address the issue of inadequate integration of temporal and spatial dimensions in traditional models. DGTNet maintains temporal continuity while revealing the complex dynamic relationships between key nodes in the urban traffic system, capturing the periodic changes in the rhythm of city life. Specifically, this study adopts adaptive signal decomposition technology to decompose traffic data into multiple Intrinsic Mode Functions (IMFs), effectively capturing the dynamic changes in traffic flow. This decomposition method is key to the implementation of DGTNet’s dynamic graph construction, enabling the analysis of traffic flow at different time scales, thereby providing a new perspective for traffic flow prediction research. In the traffic prediction module, we comprehensively consider node, edge, and graph structural information, adopting a multi-head self-attention mechanism to achieve direct cross-modeling in both temporal and spatial dimensions. Finally, we introduce a position-wise feedforward network layer to integrate different types of data and capture nonlinear relationships. The experimental results, based on public transportation network datasets METR_LA, PEMS_BAY, PEMS03, and PEMS07, demonstrate that DGTNet exhibits notable enhancements in three evaluation indicators, namely the Mean Absolute Percentage Error (MAPE), the Root Mean Square Error (RMSE), and the Mean Absolute Error (MAE). The pertinent code has been made available for public access at https://github.com/chenjing0616/DGTNet.
Micromechanical study of core barrel drilling for rotary drilling rigs based on the discrete element method
Authors: Zhao Lei , Chen Liangyu , Yuan Fei , Ma Jiaocheng 
Published: November 2024

Abstract
This study developed a gravel soil granular bed model using the discrete element method, elaborating on the core barrel drilling process by integrating bond-breaking and particle flow patterns. A quantitative description of the drilling process is achieved by defining bond-breaking efficiency. The results indicate that the force on particles near the drill tooth is the greatest, and this force increases with the core barrel feed rate, which enhances drilling efficiency and exacerbates wear on the drill tooth and guide bars. An increase in rotational speed raises the force on the particles in the boundary region, leading to deeper wear of the guide bar; however, the enlargement of particle voids near the drill tooth mitigates wear. Additionally, a coupled discrete element method and finite element method are developed to analyse the effects of drilling parameters on drill tooth deformation, revealing that the design of the open hole at the top of the drill can effectively reduce the maximum equivalent stress and wear depth. The conclusions drawn contribute to understanding particle mechanics, the particle bonding damage mechanism, and drilling mechanical behavior, providing a reference for optimizing drilling operations and drill design.
Investigation of burnout effect in turbine blade tip leakage at transonic conditions: a numerical study
Authors: Boopalan Vignesh , R Jishnu Chandran , Arumugam Senthil Kumar , P Rajesh Kanna 
Published: November 2024

Abstract
In the aviation industry, turbine blade tip leakage significantly impacts the economy due to aerodynamic losses in the turbine. The tip leakage flow increases when the tip surface is exposed to high heat loads from the burnout effect, contributing to nearly 30% of the total loss in the turbine stage. This study numerically investigates two-dimensional flat tip and burnt-out tip models under different flow accelerations at transonic conditions. Variations in the discharge coefficient are examined for different pressure ratios across the tip gap. Flow and shockwave patterns for various blade tip geometries are obtained and analyzed. The burnt-out tip notably increases tip leakage, and a significant decrease in turbine efficiency is observed beyond a critical burnout limit. The quantified losses at different stages of blade tip burnout are used to predict the effective operational life of the blade. A correlation is developed to relate the non-dimensional tip-leakage flow parameters to the normalized blade-tip geometry.
High-speed voltage level-up shifter with wide range conversion for system-on-chip applications
Authors: Sudhakar M Venkata 
Published: November 2024

Abstract
The purpose of this investigation is to demonstrate a level shifter circuit that enhances voltage switching capacity while simultaneously reducing latency by employing a cascaded current mirror, input, and output inverters. We improved our design using multi-threshold complementary metal-oxide semi-conductor (MTCMOS) technology by adding stackable transistors, super-cutoff mechanisms, and cascaded techniques. The level shifting between voltage ranges of 0.3 V and 2.0 V is accomplished by the proposed level shifter. Our design has been fine-tuned to meet the needs of system-on-chip applications by meticulously optimizing performance characteristics like energy usage, latency, and space utilization. The proposed level shifter has an area of 6.936 μm2 and a power consumption of 17 nW, with a delay of 90.64 ps. The proposed work has been done on the Cadence Virtuoso Tool using 45 nm technology. Our suggested level shifter is more effective than earlier methods in terms of latency and conversion range. In addition to delivering considerable reductions in space and power consumption, the suggested design promises a 50-fold increase in operating speed.
The mechanical properties of aged PA-12 FS3300PA powder: influence of layer thickness, sintering orientations, and laser power
Authors: Rosley Mohd Idain Fahmy , Mat Nuri Nur Rashid , Mohammad Nasir Mohd Zakaria , Omar Mohamad Rafi , Mamat Mohd Fauzi 
Published: November 2024

Abstract
This research investigates the influence of layer thickness, laser power, and sintering orientation on the mechanical properties of aged Polyamide-12 (PA-12) FS3300PA using the Selective Laser Sintering (SLS) 3D printing method. Specimens were sintered with three different layer thicknesses, laser powers, and sintering orientations using SLS. The study also aimed to examine the resulting powder morphology, mechanical properties, and tensile fracture behaviors of the aged (more than eight continuously sintering cycles) and virgin FS3300PA powders. The specimens divided into ten groups: nine groups of aged powder and one group of virgin powder as a benchmark. The nine groups of aged powder were sintered with three different layer thicknesses (0.07 mm, 0.12 mm, and 0.15 mm), laser powers (65 W, 70 W, and 75 W), and orientations (YZY 0°, YZY 90°, and XYY 0°). The selections of these laser power and layer thickness values for the sintering setting are due to machine and material parameter limitation. The results from these parameters then compared with those of the virgin powder, which sintered using the parameters provided by the manufacturer, in terms of powder morphology, mechanical properties, and tensile fracture behaviours. Observation made using scanning electron microscope (SEM) revealed that there were not many changes in shape, size, and distribution between the virgin and aged powder, but slightly larger sizes and the presence of cracks found in the aged powder. The tensile strength, elongation at break value, and Young’s modulus all shared a similar trend, increasing with higher laser power but decreasing with increased layer thickness. Regarding the fracture morphologies, the number of pores and dimples decreased with increased laser power but increased with thicker layer thickness. There was also the occurrence of un-molten powder, especially in specimens sintered at the YZY 90° orientation with lower laser power and thicker layer thickness.
Impact of nano cerium oxide addition with pyrolysis waste plastic oil on combustion, performance and emission characteristics of CRDI diesel engine
Authors: D M Madhuvanesan , J M Babu 
Published: November 2024

Abstract
This investigation examined the effect of incorporating cerium oxide (CeO2) nanoparticle into diesel and waste plastic oil (WPO) blends on the combustion, performance and emission characteristics of the diesel engine. The WPO was extracted from low density polyethylene using plastic pyrolysis. The blending of diesel and WPO with combination of D70:WPO30 and D50:WPO50 was prepared to evaluate the engine operation. Additionally, the spherical sized CeO2 with 50 mg l−1 and 100 mg l−1 was added with this blend. The various blends named as Diesel, D-WPO30, D-WPO30+Ce50, D-WPO30+Ce100, D-WPO50, D-WPO50+Ce50 and D-WPO50+Ce100 were used in this investigation to operate the engine under various load conditions. The experiment was performed using water cooled common rail direct injection (CRDI) diesel engine with prepared D-WPO blend. Different characteristics such as In-cylinder pressure (CP), heat release rate (HRR), ignition delay time (IDT), brake thermal efficiency (BTE), brake specific fuel consumption (BSFC) and exhaust gas temperature (EGT), carbon monoxide (CO), hydrocarbon (HC), nitrogen oxide (NOx) and smoke opacity emission are studied with respect to the effect of different blends and applied load used. It was observed that increasing of CeO2 nanoparticles in blend improved the overall performance and emission of the engine. Form the results, D-WPO30+Ce100 blend showed enhanced brake thermal efficiency (BTE), brake specific fuel consumption (BSFC) and exhaust has temperature (EGT) are 28.2%, 3% and 465 °C respectively. Similarly, reduced emission of CO, NOx, HC and smoke opacity was observed in the CeO2 added blends particularly at 100 mg l−1. It was concluded that among all blends prepared, the D70:WPO30 with 100 mg l−1 of CeO2 showed improved combustion, performance and emission characteristics in proposed diesel engine.
Focus on synthesis, characterization and applications of low dimensional nanomaterials
Authors: Kumar Arun , Kumar Pramod , Di Bartolomeo Antonio 
Published: November 2024

Abstract
This Editorial summarizes the content of a focus collection on the synthesis, characterization and applications of low dimensional materials. The collection groups original research and review articles providing recent results and prospects in the field, with particular attention on optoelectronic applications, dielectric and magnetic properties, and electrochemical and biological performances.
Curbing the crises, gauging the gap: measuring the nexus between gender and the environment
Authors: Duerto-Valero Sara , Kaul Sneha , Billi Lauren , Encarnacion Jessamyn , Olofsson Sofia 
Published: November 2024

Abstract
Women and men interact with the environment differently. Although data on the gender and environment nexus is only recently starting to become more widely available, existing evidence shows that, in many countries, women and men’s livelihoods, roles at home, and decision-making actions are widely different, and thus so are their contributions to environmental conservation and degradation. Similarly, climate change, pollution and biodiversity loss affect women and men in different ways, but the limited availability of related data still prevents a full understanding of the multiplicity of ways in which these differences manifest. In recent years, numerous methodological advancements have taken place, which are enabling the production of gender and environment statistics to better understand these connections. From dedicated surveys to uses of non-conventional data sources, empirical evidence on this topic is increasingly available. Still, substantial efforts are needed to fill existing data gaps and gain a thorough understanding of the connections. This paper showcases available evidence on various aspects of the gender-environment nexus and highlights possible solutions to fill remaining data gaps.
Theory of shifts, shocks, and the intimate connections to 𝐿²-type A posteriori error analysis of numerical schemes for hyperbolic problems
Authors: Giesselmann Jan , Krupa Sam 
Published: November 2024

In this paper, we develop reliable a posteriori error estimates for numerical approximations of scalar hyperbolic conservation laws in one space dimension.

Our methods have no inherent small-data limitations and are a step towards error control of numerical schemes for systems. We are careful not to appeal to the Kruzhkov theory for scalar conservation laws. Instead, we derive novel quantitative stability estimates that extend the theory of shifts, and in particular, the framework for proving stability first developed by the second author and Vasseur. This is the first time this methodology has been used for quantitative estimates.

We work entirely within the context of the theory of shifts and

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a

-contraction, techniques which adapt well to systems. In fact, the stability framework by the second author and Vasseur has itself recently been pushed to systems (see G. Chen, S. G. Krupa, and A. F. Vasseur [Arch. Ration. Mech. Anal. 246 (2022), pp. 299–332]).

Our theoretical findings are complemented by a numerical implementation in MATLAB and numerical experiments.
Anthropology of Science
Authors: Krauss Alexander 
Published: November 2024

AbstractAnthropology of science is the cross-cultural study of humanity which retraces how we have developed science, from the past to the present. So how did we get from being hunters and gatherers using axes, basic observation and numerical reasoning, to being scientists hunting explanations and gathering data using systematic controls and mathematical methods? How did we get from being nomads running in the savannahs and conducting trial and error, to being scientists running sophisticated experiments and conducting statistical analysis? Here we trace the history of how our species has reasoned more complexly over time. This ranges from how hunter-gatherer groups developed plant-based medicines and controlled parts of their environment through agriculture and livestock, to the ancient Chinese who developed, as the first or independently, effective immunisation techniques, magnetic compasses, negative numbers, astronomical observations of novae, seismographs and quantitative cartography, as well as papermaking and printing that fostered the spread of knowledge. Such innovations required complex understanding of causal relationships and making predictions. What made the work of 17th-century scientists possible is a cumulative process of greater technological advances and greater awareness of the methods already widely used for such advancements, namely more systematic observation, measurement and experimentation to create increasingly sophisticated technologies.
Philosophy of Science
Authors: Krauss Alexander 
Published: November 2024

AbstractWhat science is and its foundation have been explored by philosophers for centuries, including Bacon, Hume and Popper, and what knowledge is and its foundation for over two and a half millennia, including Plato, Aristotle and Wittgenstein. Philosophers have addressed central questions of science of science longer than researchers in any other subfield of science of science. Major debates that have dominated philosophy of science include paradigm shifts, justification, induction, demarcation and realism. Paradigm shifts refer to fundamental changes in the theories of a scientific field. Justification deals with principles such as falsification and verification to justify our theories of the world. Induction addresses the question of whether observations we make can or cannot justify generalising about the observations in other contexts or in the future. Demarcation involves defining criteria for what is and is not science. Realism concerns whether scientific theories provide a reliable approximation and true description of reality, for observable and not directly observable phenomena. We can also better understand science by comprehending the metaphysical aspects underlying science: causal and mechanistic explanations, measurement of causes, the nature of scientific regularities and laws, and the metaphysical assumptions of science inherent in research, namely in methods, definitions, concepts and theories.
Science of Science: An Integrated Field Grounded in the New-Methods-Drive-Science Theory
Authors: Krauss Alexander 
Published: November 2024

AbstractEstablishing the field of science of science requires providing not only an empirical foundation but also a theoretical foundation for understanding science. The new-methods-drive-science theory presented here can offer a unifying theory and foundation for the field that is grounded in the powerful role of scientific methods which is the common thread among this scientific community. The theory can integrate and unify the disparate fields studying science as our methods and instruments are connected to all features of science. Our evolved methodological abilities of the mind and sophisticated methods and instruments we develop using our mind (such as novel statistical techniques and telescopes) are the main mechanism that directly enables us to develop knowledge and science, by expanding our present cognitive, sensory and methodological reach to the world. The theory describes how our methods and tools have driven the origins, foundations and present limits of science.
Deciphering lineage-relevant gene regulatory networks during endoderm formation by InPheRNo-ChIP
Authors: Su Chen , Pastor William A , Emad Amin 
Published: November 2024

Abstract
Deciphering the underlying gene regulatory networks (GRNs) that govern early human embryogenesis is critical for understanding developmental mechanisms yet remains challenging due to limited sample availability and the inherent complexity of the biological processes involved. To address this, we developed InPheRNo-ChIP, a computational framework that integrates multimodal data, including RNA-seq, transcription factor (TF)–specific ChIP-seq, and phenotypic labels, to reconstruct phenotype-relevant GRNs associated with endoderm development. The core of this method is a probabilistic graphical model that models the simultaneous effect of TFs on their putative target genes to influence a particular phenotypic outcome. Unlike the majority of existing GRN inference methods that are agnostic to the phenotypic outcomes, InPheRNo-ChIP directly incorporates phenotypic information during GRN inference, enabling the distinction between lineage-specific and general regulatory interactions. We integrated data from three experimental studies and applied InPheRNo-ChIP to infer the GRN governing the differentiation of human embryonic stem cells into definitive endoderm. Benchmarking against a scRNA-seq CRISPRi study demonstrated InPheRNo-ChIP’s ability to identify regulatory interactions involving endoderm markers FOXA2, SMAD2, and SOX17, outperforming other methods. This highlights the importance of incorporating the phenotypic context during network inference. Furthermore, an ablation study confirms the synergistic contribution of ChIP-seq, RNA-seq, and phenotypic data, highlighting the value of multimodal integration for accurate phenotype-relevant GRN reconstruction.
mxfda: a comprehensive toolkit for functional data analysis of single-cell spatial data
Authors: Wrobel Julia , Soupir Alex C , Hayes Mitchell T , Peres Lauren C , Vu Thao , Leroux Andrew , Fridley Brooke L 
Published: November 2024

Abstract

Summary
Technologies that produce spatial single-cell (SC) data have revolutionized the study of tissue microstructures and promise to advance personalized treatment of cancer by revealing new insights about the tumor microenvironment. Functional data analysis (FDA) is an ideal analytic framework for connecting cell spatial relationships to patient outcomes, but can be challenging to implement. To address this need, we present mxfda, an R package for end-to-end analysis of SC spatial data using FDA. mxfda implements a suite of methods to facilitate spatial analysis of SC imaging data using FDA techniques.

Availability and implementation
The mxfda R package is freely available at https://cran.r-project.org/package=mxfda and has detailed documentation, including four vignettes, available at http://juliawrobel.com/mxfda/.
Conditional flux balance analysis toolbox for python: application to research metabolism in cyclic environments
Authors: Páez-Watson Timothy , Hernández Medina Ricardo , Vellekoop Loek , van Loosdrecht Mark C M , Wahl S Aljoscha 
Published: November 2024

Abstract

Summary
We present py_cFBA, a Python-based toolbox for conditional flux balance analysis (cFBA). Our toolbox allows for an easy implementation of cFBA models using a well-documented and modular approach and supports the generation of Systems Biology Markup Language models. The toolbox is designed to be user-friendly, versatile, and freely available to non-commercial users, serving as a valuable resource for researchers predicting metabolic behaviour with resource allocation in dynamic-cyclic environments.

Availability and implementation
Extensive documentation, installation steps, tutorials, and examples are available at https://tp-watson-python-cfba.readthedocs.io/en/. The py_cFBA python package is available at https://pypi.org/project/py-cfba/.