bluuebunny/crossref_metadata_2025_split huggingface dataset:
A general unsteady Fourier solution for orthotropic heat transfer in 2D functionally graded cylinders
Authors: Delouei Amin Amiri , Emamian Amin , Ghorbani Saeed , He Fuli 
Published: December 2023

In the present research, an analytical solution is presented for unsteady heat transfer in a two‐dimensional finite cylinder made of functionally graded Materials (FGM). The governing equation, as an unsteady partial differential equation (PDE), is solved with general boundary conditions (BCs). The thermal conductivity coefficients are considered as a power function of the radius, both in the longitudinal and radial directions of the FGM cylinder. The presence of non‐constant coefficients and general BCs will confront us with the challenge of solving an unsteady problem with high complexity. A combination of Laplace transform, Fourier transform, and meromorphic functions are utilized to deal with this complex PDE. The Laplace transform was applied to transform to the frequency domain, the Sturm–Liouville equation was used to extract the orthogonal basis Fourier series, and the meromorphic function was deployed to transform back from the frequency domain to the time domain. Results were well verified against previous research works. Results showed that the proposed analytical solution could well predict the temperature distribution. The current analytical solution is useful to better understand unsteady heat transfer in FGMs.
Preparation and characterization of shear thickening fluid/carbon nanotubes/Kevlar composite materials
Authors: Lu Chunrui , Li Siqi , Lu Xue , Ma Ji , Ma Wenlong , Wang Xiaodong , Ba Shuhong 
Published: December 2023

AbstractShear thickening fluid (STF), carbon nanotubes (CNTs) are both promising in body protection and anti‐impact for the drastic viscosity change of STF and the extremely high tensile strength and elongation of CNTs. The excellent performance of the above two combined with traditional Kevlar fabrics can significantly improve the mechanical properties and reduce the number of layers used for body protection. This work reports a new method to prepare STF/CNTs/Kevlar with excellent tensile properties and anti‐impact performance by spraying method with 1 wt% polyvinyl alcohol (PVA) solution as a binder for better integration between CNTs and Kevlar. Surface morphology changes in the preparation process indicate the combined structure of PVA binder, CNTs, and STF, presenting a uniform macroscopic and nonuniform microscopic surface of STF/CNTs/Kevlar composite. The tensile strength and anti‐impact properties including punch residual velocity and energy absorbed were studied and results for STF/CNTs/Kevlar composite are 669.8 ± 18.1 MPa, 1.602 ± 0.045 m/s, and 21.683 ± 1.182 J in 12 ms, increased by 46.4%, 23.0%, and 240.2%, respectively, compared with neat Kevlar, owing to the improved tight bonding and friction between fabrics yarns caused by PVA adhesive and tangled CNTs, accompanied with the enhanced viscosity of STF under forces.Highlights
Composites were made by spraying PVA, CNTs, and STF onto Kevlar fabrics;
The tensile strength of the composite was 46.4% higher than Kevlar;
The energy absorbed in 12 ms in anti‐impact tests was improved by 240.2%;
Tight bonding and friction between yarns are reasons to improve properties;
The raised viscosity of STF under forces is useful for mechanical properties.
Study on the temperature field distribution of the interface and process parameter optimization for material extrusion of PLA
Authors: Wang Yanqing , Tang Mengke , Zhou Zheng , Wang Caijuan 
Published: December 2023

AbstractDespite the significant development and wide application of 3D printing technology, there are rarely reports on the influence of the build plate temperature upon the manufactured products. By conducting transient thermal analysis and 3D printing experiments, researchers optimized the build plate temperature for reducing defects in printed samples formed through material extrusion (MEX). The temperature distribution near the bottom interface was analyzed using ANSYS parametric design language (APDL) numerical calculation, and the temperature variation at the key monitoring node was examined for different build plate temperatures. Standard samples were then prepared to study warping and tensile properties. The results indicated that sagging would occur when the key monitoring node's temperature exceeded the glass state temperature of the PLA filament, particularly at build plate temperatures of 55 and 60°C. This conclusion was verified through MEX experiments. Ultimately, without sagging, an optimal build plate temperature of 50°C was determined based on APDL calculations, warping measurements (0.42 mm), and tensile yield strength (39.63 MPa). Thus, research on this parameter of temperature field distribution will contribute to the realization of high‐quality and high‐precision 3D printing.Highlights
Optimized the build plate temperature to reduce defects of MEX.
The temperature distribution of the interface near the bottom was analyzed by APDL and monitored.
Optimal temperature was discussed by combining the results of APDL and experiment data.
Integrative analysis of transcriptome and proteome profiles in primary and recurrent glioblastoma
Authors: Zhang Jiajie , Wang Guowei , Yan Bo , Yang Ge , Yang Qianqian , Hu Yaqin , Guo Jiuru , Zhao Ningning , Wang Liang , Wang Huijuan 
Published: December 2023

AbstractPurposeGlioblastoma (GBM) is the most common and aggressive primary brain tumor characterized by poor prognosis and high recurrence. The underlying molecular mechanism that drives tumor progression and recurrence is unclear. This study is intended to look for molecular and biological changes that play a key role in GBM recurrence.Experimental designAn integrative transcriptomic and proteomic analysis was performed on three primary GBM and three recurrent GBM tissues. Omics analyses were conducted using label‐free quantitative proteomics and whole transcriptome sequencing.ResultsA significant difference was found between primary GBM and recurrent GBM at the transcriptional level. Similar to other omics studies of cancer, a weak overlap was observed between transcriptome and proteome, and Procollagen C‐Endopeptidase Enhancer 2 (PCOLCE2) was observed to be upregulated at mRNA and protein levels. Analysis of public cancer database revealed that high expression of PCOLCE2 is associated with poor prognosis of patients with GBM and that it may be a potential prognostic indicator. Functional and environmental enrichment analyses revealed significantly altered signaling pathways related to energy metabolism, including mitochondrial ATP synthesis‐coupled electron transport and oxidative phosphorylation.Conclusions and clinical relevanceThis study provides new insights into the recurrence process of GBM through combined transcriptomic and proteomic analyses, complementing the existing GBM transcriptomic and proteomic data and suggesting that integrated multi‐omics analyses may reveal new disease features of GBM.
A Cleaner Approach for Controllable Synthesis of Au/TiO2 Nanocomposite as an Efficient Catalyst for 4‐Nitrophenol Reduction
Authors: Guzmán‐Cruz Andrés , Pal Mou , Paraguay‐Delgado Francisco , Vázquez‐Lepe Milton , Pal Umapada 
Published: December 2023

AbstractSupported metal catalysts have attracted considerable attention because of their remarkably high catalytic activity and thermal stability. In this work, we report a facile and eco‐friendly method to synthesize porous Au/TiO2 nanocomposites with tunable size and different loading of Au nanoparticles. Porous TiO2 particles with average size of 20 nm were obtained using deep eutectic solvent‐assisted solvothermal method, in which Au NPs were immobilized by citrate reduction process. By adjusting the molar ratio of citrate and gold precursor, the size and loading of Au particles could be effectively controlled. The optimized nanocomposite with maximum Au loading and smallest particle size of 9 nm manifested the best catalytic activity in the 4‐nitrophenol reduction and excellent reusability. The superior catalytic performance can be ascribed to the strong interfacial interaction between small Au NPs and porous TiO2 support together with the high concentration of active sites at the interface.
Adsorption of Carbon Dioxide on Shirasu‐based Materials
Authors: Umegaki Tetsuo , Noguchi Daisuke , Fukumoto Tsubasa 
Published: December 2023

AbstractThis work investigated adsorption of carbon dioxide on Shirasu‐based materials with various pretreatment procedures. A Shirasu‐based material pretreated via calcination procedure followed by treatment in aqueous ammonia solution adsorbed significantly high amount of carbon dioxide compared with pristine Shirasu‐based material and the Shirasu‐based material pretreated via only solution treatment in aqueous ammonia solution. The ability improved through addition of appropriate amount of water before the adsorption process of carbon dioxide, and exhibited comparative adsorption amount of carbon dioxide with high performance materials previously reported.
Phase transition in von Neumann entropy from replica symmetry breaking
Authors: Jian Shao-Kai , Swingle Brian 
Published: December 2023

Abstract
We study the entanglement transition in monitored Brownian SYK chains in the large-N limit. Without measurement the steady state n-th Rényi entropy is obtained by summing over a class of solutions, and is found to saturate to the Page value in the n → 1 limit. In the presence of measurements, the analytical continuation n → 1 is performed using the cyclic symmetric solution. The result shows that as the monitoring rate increases, a continuous von Neumann entanglement entropy transition from volume-law to area-law occurs at the point of replica symmetry unbreaking.
Krylov complexity of open quantum systems: from hard spheres to black holes
Authors: Mohan Vyshnav 
Published: December 2023

Abstract
We examine the complexity of quasi-static chaotic open quantum systems. As a prototypical example, we analytically compute the Krylov complexity of a slowly leaking hard-sphere gas using Berry’s conjecture. We then connect it to the holographic complexity of a d + 1-dimensional evaporating black hole using the Complexity=Volume proposal. We model the black hole spacetime by stitching together a sequence of static Schwarzschild patches across incoming negative energy null shock waves. Under certain identification of parameters, we find the late time complexity growth rate during each quasi-static equilibrium to be the same in both systems.
Axion-de Sitter wormholes
Authors: Aguilar-Gutierrez Sergio E. , Hertog Thomas , Tielemans Rob , van der Schaar Jan Pieter , Van Riet Thomas 
Published: December 2023

Abstract
We construct wormholes supported by axion flux in the presence of a positive cosmological constant. The solutions describe compact, one-handle bodies colloquially known as kettlebell geometries. The wormholes are perturbatively stable, but regularity of the Euclidean geometry implies an upper bound on the axion flux. Viewed as no-boundary saddle points, wormholes are suppressed relative to the round sphere. The symmetric kettlebell with maximal axion density has vanishing Euclidean action. Continuing into the Lorentzian across the equator, the solutions describe two expanding branches of de Sitter space filled with an axion field that rapidly dilutes and which are connected by a quantum bounce across which the arrow of time reverses.
Liouville theory and the Weil-Petersson geometry of moduli space
Authors: Harrison Sarah M. , Maloney Alexander , Numasawa Tokiro 
Published: December 2023

Abstract
Liouville theory describes the dynamics of surfaces with constant negative curvature and can be used to study the Weil-Petersson geometry of the moduli space of Riemann surfaces. This leads to an efficient algorithm to compute the Weil-Petersson metric to arbitrary accuracy using Zamolodchikov’s recursion relation for conformal blocks. For example, we compute the metric on $$ \mathcal{M} $$
M
0,4 numerically to high accuracy by considering Liouville theory on a sphere with four punctures. We numerically compute the eigenvalues of the Weil-Petersson Laplacian, and find evidence that the obey the statistics of a random matrix in the Gaussian Orthogonal Ensemble.
Resonant drivings in global AdS
Authors: Mas Javier , Mayo David Travieso 
Published: December 2023

Abstract
We revisit the case of a real scalar field in global AdS4 subject to a periodic driving. We address the issue of adiabatic preparation and deformation of a time-periodic solution dual to a Floquet condensate. Then we carefully study the case of driving close to the normal mode resonant frequencies. We examine different slow protocols that adiabatically change the amplitude and/or the frequency of the driving. Traversing a normal mode frequency has very different results depending upon the sense of the frequency modulation. Generally, in the growing sense, the geometry reaches a periodically-modulated state, whereas in the opposite one, it collapses into a black hole. We study the suppression points. These are periodic solutions that are dual to a scalar field with vanishing v.e.v., 〈ϕ〉 = 0, instead of vanishing source. We also investigate quasi-periodic solutions that are prepared by driving with a combination of two normal resonant frequencies. We observe that, while the driving is on, the non-linear cascading towards higher frequencies is strongly suppressed. However, once the driving is switched off, the cascading takes over again, and in some cases, it eventually brings the solution to a collapse. Finally, we study the driving by a non-coherent thermal ensemble of resonant drivings that model stochastic noise. Our numerical results suggest the existence of stable regular solutions at sufficiently low temperature and a transition to collapse above some threshold.
Calculating composite-particle spectra in Hamiltonian formalism and demonstration in 2-flavor QED1+1d
Authors: Itou Etsuko , Matsumoto Akira , Tanizaki Yuya 
Published: December 2023

Abstract
We consider three distinct methods to compute the mass spectrum of gauge theories in the Hamiltonian formalism: (1) correlation-function scheme, (2) one-point-function scheme, and (3) dispersion-relation scheme. The first one examines spatial correlation functions as we do in the conventional Euclidean Monte Carlo simulations. The second one uses the boundary effect to efficiently compute the mass spectrum. The third one constructs the excited states and fits their energy using the dispersion relation with selecting quantum numbers. Each method has its pros and cons, and we clarify such properties in their applications to the mass spectrum for the 2-flavor massive Schwinger model at m/g = 0.1 and θ = 0 using the density-matrix renormalization group (DMRG). We note that the multi-flavor Schwinger model at small mass m is a strongly coupled field theory even after the bosonizations, and thus it deserves to perform the first-principles numerical calculations. All these methods mostly agree and identify the stable particles, pions πa (JPG = 1−+), sigma meson σ (JPG = 0++), and eta meson η (JPG = 0−−). In particular, we find that the mass of σ meson is lighter than twice the pion mass, and thus σ is stable against the decay process, σ → ππ. This is consistent with the analytic prediction using the WKB approximation, and, remarkably, our numerical results are so close to the WKB-based formula between the pion and sigma-meson masses, Mσ/Mπ = $$ \sqrt{3} $$

3

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Dreams of Declassification: The Early Cold War Quest for Nuclear Knowledge in The Netherlands and Norway
Authors: Kleemans Machiel 
Published: December 2023

AbstractThis article seeks to explore the relation between nuclear physics and secrecy in early Cold War Europe. After World War II, nuclear physics re-emerged from the Manhattan Project as a largely classified field. Over time, the boundary between secret and unclassified information set by the United States moved due to both political and scientific developments. This shifting boundary of secrecy is taken as a place to investigate power relations in the context of Cold War Science. The Netherlands and Norway are two countries with early nuclear programs that tried to move this boundary, in part by building a joint reactor in 1951. Whereas they requested classified information from the US in 1946, their programs developed to a point where the US made requests to classify nuclear information in Europe by 1960. Between 1954 and 1960, the joint reactor program became the site of a multilateral intelligence operation. Secrecy was used as an intelligence tool to spread nuclear disinformation to the Soviet Union. This history shows how (de)classification opened and closed windows of opportunity and sheds light on the effectiveness of classification.
Weather, weekday, and vacation effects on webcam recorded daily visitor numbers in the alpine winter season
Authors: Kloos Simon , Bigalke Carina , Neumair Matthias , Menzel Annette 
Published: December 2023

AbstractWinter tourism is an important economic factor in the European Alps, which could be exposed to severely changing meteorological conditions due to climate change in the future. The extent to which meteorology influences winter tourism figures has so far been analyzed mainly based on monthly or seasonal data and in relation to skier numbers. Therefore, we record for the first time daily visitor numbers at five Bavarian winter tourism destinations based on 1518 webcam images using object detection and link them to meteorological and time-related variables. Our results show that parameters such as temperature, cloud cover or sunshine duration, precipitation, snow depth, wind speed, and relative humidity play a role especially at locations that include other forms of winter tourism in addition to skiing. In the ski resorts studied, on the other hand, skiing is mostly independent of current weather conditions, which can be attributed mainly to artificial snowmaking. Moreover, at the webcam sites studied, weekends and vacation periods had an equal or even stronger influence on daily visitor numbers than the current weather conditions. The extent to which weather impacts the (future) visitor numbers of a winter tourism destination must therefore be investigated individually and with the inclusion of non-meteorological variables influencing human behavior.
Data-driven decadal climate forecasting using Wasserstein time-series generative adversarial networks
Authors: Bouteska Ahmed , Seranto Marco Lavazza , Hajek Petr , Abedin Mohammad Zoynul 
Published: December 2023

AbstractRecent trends in global climate modeling, coupled with the availability of more fine-scale datasets, have opened up opportunities for deep learning-based climate prediction to improve the accuracy of predictions over traditional physics-based models. For this, however, large ensembles of data are needed. Generative models have recently proven to be a suitable solution to this problem. For a sound generative model for time-series forecasting, it is essential that temporal dynamics are preserved in that the generated data obey the original data distributions over time. Existing forecasting methods aided by generative models are not adequate for capturing such temporal relationships. Recently, generative models have been proposed that generate realistic time-series data by exploiting the combinations of unsupervised and supervised learning. However, these models suffer from instable learning and mode collapse problems. To overcome these issues, here we propose Wasserstein Time-Series Generative Adversarial Network (WTGAN), a new forecasting model that effectively imitates the dynamics of the original data by generating realistic synthetic time-series data. To validate the proposed forecasting model, we evaluate it by backtesting the challenging decadal climate forecasting problem. We show that the proposed forecasting model outperforms state-of-the- art generative models. Another advantage of the proposed model is that once WTGAN is tuned, generating time-series data is very fast, whereas standard simulators consume considerable computer time. Thus, a large amount of climate data can be generated, which can substantially improve existing data-driven climate forecasting models.
Association of clinicopathologic and molecular factors with the occurrence of positive margins in breast cancer
Authors: Praveen Kumar Anupama , Vicente Diego , Liu Jianfang , Raj-Kumar Praveen-Kumar , Deyarmin Brenda , Lin Xiaoying , Shriver Craig D. , Hu Hai 
Published: December 2023

AbstractPurposeTo explore the association of clinicopathologic and molecular factors with the occurrence of positive margins after first surgery in breast cancer.MethodsThe clinical and RNA-Seq data for 951 (75 positive and 876 negative margins) primary breast cancer patients from The Cancer Genome Atlas (TCGA) were used. The role of each clinicopathologic factor for margin prediction and also their impact on survival were evaluated using logistic regression, Fisher’s exact test, and Cox proportional hazards regression models. In addition, differential expression analysis on a matched dataset (71 positive and 71 negative margins) was performed using Deseq2 and LASSO regression.ResultsAssociation studies showed that higher stage, larger tumor size (T), positive lymph nodes (N), and presence of distant metastasis (M) significantly contributed (p ≤ 0.05) to positive surgical margins. In case of surgery, lumpectomy was significantly associated with positive margin compared to mastectomy. Moreover, PAM50 Luminal A subtype had higher chance of positive margin resection compared to Basal-like subtype. Survival models demonstrated that positive margin status along with higher stage, higher TNM, and negative hormone receptor status was significant for disease progression. We also found that margin status might be a surrogate of tumor stage. In addition, 29 genes that could be potential positive margin predictors and 8 pathways were identified from molecular data analysis.ConclusionThe occurrence of positive margins after surgery was associated with various clinical factors, similar to the findings reported in earlier studies. In addition, we found that the PAM50 intrinsic subtype Luminal A has more chance of obtaining positive margins compared to Basal type. As the first effort to pursue molecular understanding of the margin status, a gene panel of 29 genes including 17 protein-coding genes was also identified for potential prediction of the margin status which needs to be validated using a larger sample set.
Harms and the Illegal Wildlife Trade: Political Ecology, Green Criminology and the European Eel
Authors: Gutierrez Laura , Duffy Rosaleen 
Published: December 2023

AbstractThis paper integrates political ecology and green criminology to examine the critical endangerment of the European eel. Using a harms-based approach, our research suggests that the identification of organised crime networks as the central perpetrators of illegal wildlife trade (IWT) and of IWT itself as the main threat to eels, neglects a myriad of practices—many of which are related to legal businesses and activities—that significantly contribute to the endangerment of the species. We suggest that, in order to better protect the European eel, we need more holistic conservation measures that go beyond a focus on fisheries and IWT.