bluuebunny/crossref_metadata_2025_split huggingface dataset:
Grain-wise piezoelectric response of polycrystalline aluminum nitride thin films: an empirical investigation using piezo force microscopy
Authors: Sharma Neha , Kamparath Rajiv , Pal Suparna , Mukherjee C , Benerji N S 
Published: October 2024

Abstract
Local mapping of piezoelectric response across grains with different crystal planes is crucial to enhance the level of understanding of the piezoelectric behavior of wurtzite hexagonal (WH) AlN thin films. To investigate this phenomenon, polycrystalline WH-AlN thin films were deposited by pulsed-DC magnetron sputtering using a mixture of argon (Ar) and nitrogen (N2) with varying N2 content as 5%, 10%, and 20% in the form of the AlN/Ti/Si (100) heterostructure. Piezo force microscopy (PFM) was used to establish a correlation among piezo-response (PR) phase contrast, polarity, and crystal planes constituting the film surface. A phenomenological model is also presented to correlate the distribution of interface sheet charges with polar (0002)-, semi-polar (10

1
¯

1)-, and non-polar (10

1
¯

0)-planes present on the film surface. This interdependence eventually regulates the phase between piezoelectric oscillations and modulation voltage, which is ultimately translated into a grain-wise contrast obtained from PR-phase images.
Magnetic Monopole Phenomenology at Future Hadron Colliders
Authors: Ahmed Ijaz , Swalheen Sidra , Ur Rehman Mansoor , Tariq Rimsha 
Published: October 2024

AbstractIn the grand tapestry of Physics, the magnetic monopole (MM) is a holy grail. Therefore, numerous efforts are underway in search of this hypothetical particle at CMS, ATLAS, and MoEDAL experiments of Large Hadron Collider (LHC) by employing different production mechanisms. The cornerstone of our comprehension of monopoles lies in Dirac’s theory which outlines their characteristics and dynamics. Within this theoretical framework, an effectiveU(1) gauge field theory, derived from conventional models, delineates the interaction between spin magnetically-charged fields and ordinary photons under electric–magnetic dualization. The focus of this paper is the production of MMs through Drell–Yan (DY) and the Photon-Fusion (PF) mechanisms to generate velocity-dependent scalar, fermionic, and vector monopoles of spin angular momentum0,12,1respectively at LHC. A computational study compares the monopole pair-production cross-sections for both methods at various center-of-mass energies (s) with different magnetic dipole moments. The comparison of kinematic distributions of monopoles at Parton and reconstructed level are demonstrated for both DY and PF mechanisms. Extracted results showcase how modern machine-learning techniques can be used to study the production of MMs at the future proton-proton particle colliders at 100 TeV. We demonstrate the observability of MMs against the most relevant Standard Model background using multivariate methods such as Boosted Decision Trees, Likelihood, and Multilayer Perceptron. This study compares the performance of these classifiers with traditional cut-based and counting approaches, proving the superiority of our methods.
Cross-calibration and first vertical ECE measurement of electron energy distribution in the TCV tokamak
Authors: Tema Biwole A , Porte L , Fasoli A , Figini L , Decker J , Hoppe M , Cazabonne J , Votta L , Simonetto A , Coda S ,   the TCV Team
Published: October 2024

Abstract
This paper describes the first vertical electron cyclotron emission measurement of non-thermal electron distributions in the Tokamak à Configuration Variable. These measurements were conducted in runaway electron scenarios and in the presence of electron cyclotron current drive. Measured intensities of linearly polarized X- and O-mode radiation from fast electrons allow the analysis of the energy distribution. The measurements were made possible through the creation of an operational regime for the diagnostic that is free of thermal background radiation, in relaxed electron density operations. This operational regime notably enables the cross-calibration of the diagnostic system, relying on thermal plasma measurements and modeling with the ray-tracing code SPECE.
High peak power mini-array quantum cascade lasers operating in pulsed mode
Authors: Zhang 章 Yuhang 宇航 , Wang 王 Yupei 渝沛 , Luo 罗 Xiaoyue 晓玥 , Qian 钱 Chenhao 晨灏 , Cheng 程 Yang 洋 , Zhao 赵 Wu 武 , Sun 孙 Fangyuan 方圆 , Wang 王 Jun 俊 , Sun 孙 Zheng-Ming 正明 
Published: October 2024

Abstract
Broad area quantum cascade lasers (BA QCLs) have significant applications in many areas, but suffer from demanding pulse operating conditions and poor beam quality due to heat accumulation and generation of high order modes. A structure of mini-array is adopted to improve the heat dissipation capacity and beam quality of BA QCLs. The active region is etched to form a multi-emitter and the channels are filled with InP:Fe, which acts as a lateral heat dissipation channel to improve the lateral heat dissipation efficiency. A device with λ ∼ 4.8 μm, a peak output power of 122 W at 1.2% duty cycle with a pulse of 1.5 μs is obtained in room temperature, with far-field single-lobed distribution. This result allows BA QCLs to obtain high peak power at wider pump pulse widths and higher duty cycle conditions, promotes the application of the mid-infrared laser operating in pulsed mode in the field of standoff photoacoustic chemical detection, space optical communication, and so on.
Giant enhancement of negative friction by resonant coupling between localized surface phonon polaritons and graphene plasmonics
Authors: Liu 柳 Kaipeng 开鹏 , Zhou 周 Shuai 帅 , Dai 戴 Shiwei 士为 , Ge 葛 Lixin 力新 
Published: October 2024

Abstract
Negative friction refers to a frictional force that acts in the same direction as the motion of an object, which has been predicted in terahertz (THz) gain systems [Phys. Rev. B
108 045406 (2023)]. In this work, we investigate the enhancement of the negative friction experienced by nanospheres placed near a graphene substrate. We find that the magnitude of negative friction is related to the resonant coupling between the surface plasmon polaritons (SPPs) of the graphene and localized surface phonon polaritons (LSPhP) of nanospheres. We exam nanospheres consisted of several different materials, including SiO2, SiC, ZnSe, NaCl, lnSb. Our results suggest that the LSPhP of NaCl nanospheres match effectively with the amplified SPPs of graphene sheets. The negative friction for NaCl nanospheres can be enhanced about one-to-two orders of magnitude compared to that of silica (SiO2) nanospheres. At the resonant peak of negative friction, the required quasi-Fermi energy of graphene is lower for NaCl nanospheres. Our finds hold great prospects for the mechanical manipulations of nanoscale particles.
Comparison study on hyaline cartilage versus fibrocartilage formation in a pig model by using 3D-bioprinted hydrogel and hybrid constructs
Authors: Alizadeh Sardroud Hamed , Rosa Gustavo Dos Santos , Dust William , Cham Tat-Chuan , Roy Gwen , Bater Sarah , Chicoine Alan , Honaramooz Ali , Chen Xiongbiao , Eames B Frank 
Published: October 2024

Abstract
Cartilage tissue engineering (CTE) with the help of engineered constructs has shown promise for the regeneration of hyaline cartilage, where fibrocartilage may also be formed due to the biomechanical loading resulting from the host weight and movement. Previous studies have primarily reported on hyaline cartilage formation in vitro and/or in small animals, while leaving the fibrocartilage formation undiscovered. In this paper, we, at the first time, present a comparison study on hyaline cartilage versus fibrocartilage formation in a large animal model of pig by using two constructs (namely hydrogel and hybrid ones) engineered by means of three-dimensional (3D) bioprinting. Both hydrogel and hybrid constructs were printed from the bioink of alginate (2.5%) and ATDC5 cells (chondrogenic cells at a cell density of 5 × 106 cells ml−1), with the difference in that in the hybrid construct, there was a polycaprolactone (PCL) strand printed between every two bioink strands, which were strategically designed to shield the force imposed on the cells within the bioink strands. Both hydrogel and hybrid constructs were implanted into the chondral defects created in the articular cartilage of weight-bearing portions of pig stifle joints; the cartilage formation was examined at one- and three-months post-implantation, respectively, by means of Safranin O, Trichrome, immunofluorescent staining, and synchrotron radiation-based (SR) inline phase contrast imaging microcomputed tomography (inline-PCI-CT). Glycosaminoglycan (GAG) and collagen type II (Col II) secretion were used to evaluate the hyaline cartilage formation, while collagen type I (Col I) was used to indicate fibrocartilage given that Col I is low in hyaline cartilage but high in fibrocartilage. Our results revealed that cartilage formation was enhanced over time in both hydrogel and hybrid constructs; particularly, the hydrogel construct exhibited more cartilage formation at both one- and three-months post-implantation, while hybrid constructs tended to have less fibrocartilage formed in a long time period. Also, the result from the inline-PCI-CT revealed that the inline-PCI-CT was able to provide not only the information seen in other histology images, but also high-resolution details of biomaterials and regenerating cartilage. This would represent a significant advance toward the non-invasive assessment of cartilage formation regeneration within large animal models and eventually in human patients.
Estimating afforestation related forest cover change using data fusion and machine learning
Authors: Khan Kashif , Khan Junaid Aziz , Khokhar Muhammad Fahim , Khan Shahid Nawaz , Iqbal Javed 
Published: October 2024

Abstract
The rapid increase in population and changes in land use have led to the issue of climate change, which is threatening the overall human well-being in general, and particularly the forest resources. Recognizing the rapid decline in the forest cover and in adherence to the Bonn Challenge, Pakistan has initiated the Billion Tree Afforestation Project (BTAP) to restore forests. Hence, there is a need to analyze the spatio-temporal dynamics of forest cover to assess the efficacy of BTAP. The objectives of this study were: (1) to develop machine learning methods that combine Sentinel-1 and Sentinel-2 data to characterize forest cover; and (2) to characterize the forest cover dynamics in the study area during the study period. In the study area, the land cover was classified using two machine learning models: random forests (RF) and support vector machines (SVM). We then used the models to create forest cover maps for the period of 2016 to 2022. Based on the classifications of land cover, the study area was classified into forest and non-forest classes. Finally, the spatiotemporal distribution of the changes induced by afforestation was generated. The results demonstrate an increase of 3.7% in forest cover in the study area during the study period. The increase in forest cover was more prominent in the northern and central regions as compared to that of the southern region. In terms of species, the increase in broadleaved forests was more prominent. The results show that RF produces superior results as compared to the SVM, with overall accuracy and kappa coefficient of 94%–97% & 0.93–0.96 respectively. The overall accuracy and Kappa coefficient of the SVM model range from 92%–94% & 0.91–0.95. The techniques used in this study are cost-effective for accurately monitoring changes in forest cover.
Nano device fabrication for in-memory and in-sensor reservoir computing
Authors: Lin Yinan , Chen Xi , Zhang Qianyu , You Junqi , Xu Renjing , Wang Zhongrui , Sun Linfeng 
Published: October 2024

Abstract
Recurrent neural networks (RNNs) have proven to be indispensable for processing sequential and temporal data, with extensive applications in language modeling, text generation, machine translation, and time-series forecasting. Despite their versatility, RNNs are frequently beset by significant training expenses and slow convergence times, which impinge upon their deployment in edge AI applications. Reservoir computing (RC), a specialized RNN variant, is attracting increased attention as a cost-effective alternative for processing temporal and sequential data at the edge. RC’s distinctive advantage stems from its compatibility with emerging memristive hardware, which leverages the energy efficiency and reduced footprint of analog in-memory and in-sensor computing, offering a streamlined and energy-efficient solution. This review offers a comprehensive explanation of RC’s underlying principles, fabrication processes, and surveys recent progress in nano-memristive device based RC systems from the viewpoints of in-memory and in-sensor RC function. It covers a spectrum of memristive device, from established oxide-based memristive device to cutting-edge material science developments, providing readers with a lucid understanding of RC’s hardware implementation and fostering innovative designs for in-sensor RC systems. Lastly, we identify prevailing challenges and suggest viable solutions, paving the way for future advancements in in-sensor RC technology.
Constructing high-performance and versatile liquid–solid triboelectric nanogenerator with inflatable columnar units
Authors: Luo Lin , Liu Chao , Gu Rui , Chen Mingxia , Wang Yifei , Xu Nuo , Xiong Yao , Yang Jiahong , Huo Ziwei , Liu Yang , Wei Liang , Wang Zhong Lin , Sun Qijun 
Published: October 2024

Abstract
The use of water resources for energy generation has become increasingly prevalent, encompassing the conversion of kinetic energy from streams, tides, and waves into renewable electrical power. Water energy sources offer numerous benefits, including widespread availability, stability, and the absence of carbon dioxide and other greenhouse gas emissions, making them a clean and environmentally friendly form of energy. In this work, we develop a droplet-based liquid–solid triboelectric nanogenerator (LS-TENG) using sophisticatedly designed inflatable columnar structures with inner and outer dual-electrodes. This device can be utilized to harvest both the internal droplet-rolling mechanical energy and the external droplet-falling mechanical energy, capable of being assembled into various structures for versatile applications. The design incorporates a combined structure of both internal and external TENG to optimize output performance via multiple energy harvesting strategies. The internal structure features a dual-electrode columnar-shaped LS-TENG, designed to harvest fluid kinetic energy from water droplets. By leveraging the back-and-forth motion of a small amount of water within the air column, mechanical energy can be readily collected, achieving a maximum mass power density of 9.02 W·Kg−1 and an energy conversion efficiency of 10.358%. The external component is a droplet-based LS-TENG, which utilizes a double-layer capacitor switch effect elucidated with an equivalent circuit model. Remarkably, without the need for pre-charging, a single droplet can generate over 140 V of high voltage, achieving a maximum power density of 7.35 W·m−2 and an energy conversion efficiency of 22.058%. The combined LS-TENG with a sophisticated inflatable columnar structure can simultaneously collect multiple types of energy with high efficacy, exhibiting great significance in potential applications such as TENG aeration rollers, inflatable lifejacket, wind energy harvesting, TENG tents, and green houses.
Biofuel blends and nano-additives: a sustainable approach to diesel engine performance and emissions improvement
Authors: S Prakash Varma Potturi , Subbaiah K Venkata 
Published: October 2024

Abstract
The utilization of compression ignition (CI) diesel engines has seen a substantial increase in recent years owing to their numerous advantages. However, the widespread adoption of these engines has also significantly contributed to environmental pollution issues, with diesel engines being recognized as major global contributors to exhaust emissions-related pollution. To address this issue, comprehensive research has been carried out on both emissions from diesel exhaust pollutants and advanced after-treatment technologies for emission control. This study aims to evaluate the efficiency and emissions of diesel fuel mixed with various ratios of biofuel derived from Karanja seeds (B10, B15, and B20). Among the different blends examined, B20 demonstrated superior performance in terms of brake thermal efficiency (BTE) and brake-specific fuel consumption (BSFC), along with lower levels of hydrocarbon (HC) and carbon dioxide (CO2) emissions compared to pure diesel. Further, the impact of nanoadditives, specifically titanium dioxide (TiO2), at different concentrations (80 ppm, 100 ppm, and 120 ppm), on B20 blends was evaluated. The findings indicated that B20 blended with 100 ppm of TiO2 exhibited superior performance in terms of BTE, BSFC, and lower emissions of HC, CO2, nitrogen oxides (NOx), and carbon monoxide (CO). From the results, the BTE increases from 1% to 33%, illustrating enhanced thermal efficiency under similar conditions. The average BSFC across all loads and speeds in the table is approximately 0.89 kg kW−1h−1, while the average BTE stands at approximately 23.1%.
Dynamically customizable 4D printed shape memory polymer biomedical devices: a review
Authors: Xin Xiaozhou , Lin Cheng , Wang Xiaofei , Liu Fukai , Dong Lili , Liu Liwu , Liu Yanju , Leng Jinsong 
Published: October 2024

Abstract
There is an increased risk of complications and even surgical failures for various types of medical devices due to difficult to control configurations and performances, incomplete deployments, etc. Shape memory polymers (SMPs)-based 4D printing technology offers the opportunity to create dynamic, personalized, and accurately controllable biomedical devices with complex configurations. SMPs, typical representatives of intelligent materials, are capable of programmable deformation in response to stimuli and dynamic remodeling on demand. 4D printed SMP medical devices not only enable active control of configuration, performance and functionality, but also open the way for minimally invasive treatments and remote controllable deployment. Here, the shape memory mechanism, actuation methods, and printing strategies of active programmable SMPs are reviewed, and cutting-edge advances of 4D printed SMPs in the fields such as bone scaffolds, tracheal stents, cardiovascular stents, cell morphological regulation, and drug delivery are highlighted. In addition, promising and meaningful future research directions for 4D printed SMP biomedical devices are discussed. The development of 4D printed SMP medical devices is inseparable from the in-depth cooperation between doctors and engineers. The application of 4D printed SMP medical devices will facilitate the rapid realization of ‘smart medical care’ and accelerate the process of ‘intelligentization’ of medical devices.
Conclusion
Authors: Hewitt Martin 
Published: October 2024

Abstract
What we can learn about Darwinism in Britain from the various celebrations organised to mark the centenary of Darwin’s birth, and the 1909 half-centenary of the Origin? The sorts of layered multigenerational responses visible in the previous fifty years were still very much in evidence, complicated by the sense of the incipient emergence of a further, post-Edwardian generation. Reviewing the arguments of the rest of the book, the prosopographical basis of the conclusions are emphasised, conceding that exceptions to the generational pattern are numerous, that generational influences operate in a complex field of other positionalities of class, gender, race, and religion, but that these exceptions do not challenge the general pattern visible in the larger populations. Concluding reflections show the implications for understanding the nature of historical periodisation and change, and especially the importance of generational churn as a central dynamic of social and cultural change.
Dual-view jointly learning improves personalized drug synergy prediction
Authors: Li Xueliang , Shen Bihan , Feng Fangyoumin , Li Kunshi , Tang Zhixuan , Ma Liangxiao , Li Hong 
Published: October 2024

Abstract

Motivation
Accurate and robust estimation of the synergistic drug combination is important for medicine precision. Although some computational methods have been developed, some predictions are still unreliable especially for the cross-dataset predictions, due to the complex mechanism of drug combinations and heterogeneity of cancer samples.

Results
We have proposed JointSyn that utilizes dual-view jointly learning to predict sample-specific effects of drug combination from drug and cell features. JointSyn outperforms existing state-of-the-art methods in predictive accuracy and robustness across various benchmarks. Each view of JointSyn captures drug synergy-related characteristics and makes complementary contributes to the final prediction of the drug combination. Moreover, JointSyn with fine-tuning improves its generalization ability to predict a novel drug combination or cancer sample using a small number of experimental measurements. We also used JointSyn to generate an estimated atlas of drug synergy for pan-cancer and explored the differential pattern among cancers. These results demonstrate the potential of JointSyn to predict drug synergy, supporting the development of personalized combinatorial therapies.

Availability and implementation
Source code and data are available at https://github.com/LiHongCSBLab/JointSyn.
Circular RNA circASH1L(4,5) protects microRNA-129-5p from target-directed microRNA degradation in human skin wound healing
Authors: Wang Qizhang , Niu Guanglin , Liu Zhuang , Toma Maria A , Geara Jennifer , Bian Xiaowei , Zhang Letian , Piipponen Minna , Li Dongqing , Wang Aoxue , Sommar Pehr , Xu Landén Ning 
Published: October 2024

Abstract

Background
Skin wound healing involves a complex gene expression programme that remains largely undiscovered in humans. Circular RNAs (circRNAs) and microRNAs (miRNAs) are key players in this process.

Objectives
To understand the functions and potential interactions of circRNAs and miRNAs in human skin wound healing.

Methods
CircRNA, linear RNA and miRNA expression in human acute and chronic wounds were analysed with RNA sequencing and quantitative reverse transcription polymerase chain reaction. The roles of circASH1L(4,5) and miR-129-5p were studied in human primary keratinocytes (proliferation and migration assays, microarray analysis) and ex vivo wound models (histological analysis). The interaction between circASH1L(4,5) and miR-129-5p was examined using luciferase reporter and RNA pulldown assays.

Results
We identified circASH1L(4,5) and its interaction with miR-129-5p, both of which increased during human skin wound healing. Unlike typical miRNA sponging, circASH1L enhanced miR-129 stability and silencing activity by protecting it from target-directed degradation triggered by NR6A1 mRNA. Transforming growth factor-β signalling – crucial in wound healing – promoted circASH1L expression while suppressing NR6A1, thereby increasing the abundance of miR-129 at the post-transcriptional level. CircASH1L and miR-129 enhanced keratinocyte migration and proliferation, crucial processes for the re-epithelialization of human wounds.

Conclusions
Our study uncovered a novel role for circRNAs as protectors of miRNAs and highlights the importance of regulated miRNA degradation in skin wound healing.