bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficient Cryogenic Nonlinear Conversion Processes in Periodically‐Poled Thin‐Film Lithium Niobate Waveguides
Authors: Cheng Yujie , Li Xiaoting , Feng Lantian , Li Haochuan , Sun Wenzhao , Song Xinyu , Ding Yuyang , Guo Guangcan , Wang Cheng , Ren Xifeng 
Published: November 2024

AbstractPeriodically poled thin‐film lithium niobate (TFLN) waveguides, which enable efficient quadratic nonlinear processes, serve as crucial foundation for classical and quantum signal processing. To expand their application scope, the first investigation of nonlinear conversion processes in periodically poled TFLN waveguides at cryogenic conditions (7 K) is provided. Through systematic experimental characterization, it is found that the periodically poled TFLN waveguide retains its high conversion efficiency at both cryogenic and room temperatures for both classical second‐harmonic generation and quantum photon‐pair generation processes. Particularly, the photon‐pair source at cryogenic conditions shows high brightness (≈8 MHz µW−1) and broad bandwidth (>100 THz). These results demonstrate the significant potential of TFLN wavelength conversion devices for cryogenic applications and foster future scalable quantum photonic systems.
Surface Involvement in the Boosting of Chiral Organocatalysts for Efficient Asymmetric Catalysis
Authors: Mou Qi , Wang Donghui , Li Shuang , Li Xin , Wang Jiahao , Chen Changpin , Huo Yanping , Mu Yingxiao , Huang Zhegang 
Published: November 2024

AbstractNanostructures with curved surfaces and chiral‐directing residues are highly desirable in the synthesis of asymmetric chemicals, but they remain challenging to synthesize without using unique templates due to the disfavored torsion energy of twisted architectures toward chiral centers. Here, a strategy for the facile fabrication of highly cured capsule‐shaped catalysts with chiral interiors by the amplification of molecular chirality via the irreversible cross‐linking of 2D asymmetric laminates is presented. The key to the success of these irregular 2D layers is the use of hierarchical assembly of chiral macrocycles, which can exactly regulate the cured nanostructures as well as asymmetric catalysis. The cross‐linking of 2D laminates from the assembly of hexameric macrocycles with one proline edge gave rise to rarely curled capsules with a diameter of 200–400 nm and excellent enantioselectivities as well as diastereoselectivities for asymmetric aldol reactions (94% ee and 1:13 dr). The tetrameric macrocycles decorated with the chiral block produced further curled porous structures, giving an outstanding enantioselectivities (up to 98% ee and 1:17 dr). The strategy of mechanical surface folding will provide a new insight related to increasing the enantioselectivity of chiral organocatalysts.
Randomized Controlled Trial of Transcranial Direct Current Stimulation over the Supplementary Motor Area in Tourette Syndrome
Authors: Mahjoub Yasamin , Szejko Natalia , Gan Liu Shi , Adeoti Janet Adesewa , Nitsche Michael A. , Vicario Carmelo M. , Pringsheim Tamara M. , Martino Davide 
Published: November 2024

ABSTRACTBackgroundTranscranial direct current stimulation (tDCS) over the supplementary motor area (SMA) has shown promise in Tourette syndrome (TS), but previous studies were limited in size and stimulation duration.ObjectiveThe aim was to explore the efficacy and safety of multiple sessions of cathodal tDCS over the bilateral SMA on tic severity in TS.MethodsA double‐blind, randomized, sham‐controlled trial 1 mA cathodal tDCS over bilateral SMA was performed in participants with TS older than 16 years. The intervention involved two 20‐min periods of stimulation with either sham or active tDCS per day, over 5 consecutive days, during which participants actively suppressed tics. Tic severity was measured using the Yale Global Tic Severity Scale Total Tic Severity (YGTSS‐TTS, primary outcome) score at baseline, day 5 (visit 5), and 1 week later (visit 6). Questionnaires focusing on comorbidities were performed at baseline and visit 6.ResultsTwenty‐four participants were randomly assigned (12 active, 12 sham; 8 women; median age: 26). We observed a significant effect of visit on YGTSS‐TSS, but no significant effect of treatment or treatment × visit interaction emerged. In contrast, a statistically significant effect of the treatment × visit interaction was observed for the motor tic subscore, with significantly larger improvement in the active arm. Furthermore, we detected a significantly larger decrease in premonitory urge intensity at visit 6 after active stimulation. No effect was detected on severity of comorbidities.ConclusionsThis preliminary study suggests that bilateral tDCS over the SMA provides small, but significant benefits in reducing motor tic severity in TS.
Self‐supervised learning improves robustness of deep learning lung tumor segmentation models to CT imaging differences
Authors: Jiang Jue , Rangnekar Aneesh , Veeraraghavan Harini 
Published: December 2024

AbstractBackgroundSelf‐supervised learning (SSL) is an approach to extract useful feature representations from unlabeled data, and enable fine‐tuning on downstream tasks with limited labeled examples. Self‐pretraining is a SSL approach that uses curated downstream task dataset for both pretraining and fine‐tuning. Availability of large, diverse, and uncurated public medical image sets presents the opportunity to potentially create foundation models by applying SSL in the “wild” that are robust to imaging variations. However, the benefit of wild‐ versus self‐pretraining has not been studied for medical image analysis.PurposeCompare robustness of wild versus self‐pretrained models created using convolutional neural network (CNN) and transformer (vision transformer [ViT] and hierarchical shifted window [Swin]) models for non‐small cell lung cancer (NSCLC) segmentation from 3D computed tomography (CT) scans.MethodsCNN, ViT, and Swin models were wild‐pretrained using unlabeled 10,412 3D CTs sourced from the cancer imaging archive and internal datasets. Self‐pretraining was applied to same networks using a curated public downstream task dataset (n = 377) of patients with NSCLC. Pretext tasks introduced in self‐distilled masked image transformer were used for both pretraining approaches. All models were fine‐tuned to segment NSCLC (n = 377 training dataset) and tested on two separate datasets containing early (public n = 156) and advanced stage (internal n = 196) NSCLC. Models were evaluated in terms of: (a) accuracy, (b) robustness to image differences from contrast, slice thickness, and reconstruction kernels, and (c) impact of pretext tasks for pretraining. Feature reuse was evaluated using centered kernel alignment.ResultsWild‐pretrained Swin models resulted in higher feature reuse at earlier level layers and increased feature differentiation close to output. Wild‐pretrained Swin outperformed self‐pretrained models for analyzed imaging acquisitions. Neither ViT nor CNN showed a clear benefit of wild‐pretraining compared to self‐pretraining. Masked image prediction pretext task that forces networks to learn the local structure resulted in higher accuracy compared to contrastive task that models global image information.ConclusionWild‐pretrained Swin networks were more robust to analyzed CT imaging differences for lung tumor segmentation than self‐pretrained methods. ViT and CNN models did not show a clear benefit for wild‐pretraining over self‐pretraining.
Automatic segmentation of pericardial adipose tissue from cardiac MR images via semi‐supervised method with difference‐guided consistency
Authors: Zhang Xinru , Zhou Shoujun , Li Bohan , Wang Yuanquan , Lu Ke , Liu Weipeng , Wang Zhida 
Published: December 2024

AbstractBackgroundAccurate and automatic segmentation of pericardial adipose tissue (PEAT) in cardiac magnetic resonance (MR) images is essential for the diagnosis and treatment of cardiovascular diseases. Precise segmentation is challenging due to high costs and the need for specialized knowledge, as a large amount of accurately annotated data is required, demanding significant time and medical resources.PurposeIn order to reduce the burden of data annotation while maintaining the high accuracy of segmentation tasks, this paper introduces a semi‐supervised learning method to solve the limitations of current PEAT segmentation methods.MethodsIn this paper, we propose a difference‐guided collaborative mean teacher (DCMT) semi‐supervised method, designed for the segmentation of PEAT from DCMT consists of two main components: a semi‐supervised framework with a difference fusion strategy and a backbone network MCM‐UNet using Mamba‐CNN mixture (MCM) blocks. The differential fusion strategy effectively utilizes the uncertain areas in unlabeled data, encouraging the model to reach a consensus in predictions across these difficult‐to‐segment yet information‐rich areas. In addition, considering the sparse and scattered distribution of PEAT in cardiac MR images, which makes it challenging to segment, we propose MCM‐UNet as the backbone network in our semi‐supervised framework. This not only enhances the processing ability of global information, but also accurately captures the detailed local features of the image, which greatly improves the accuracy of PEAT segmentation.ResultsOur experiments conducted on the MRPEAT dataset show that our DCMT method outperforms existing state‐of‐the‐art semi‐supervised methods in terms of segmentation accuracy. These findings underscore the effectiveness of our approach in handling the specific challenges associated with PEAT segmentation.ConclusionsThe DCMT method significantly improves the accuracy of PEAT segmentation in cardiac MR images. By effectively utilizing uncertain areas in the data and enhancing feature capture with the MCM‐UNet, our approach demonstrates superior performance and offers a promising solution for semi‐supervised learning in medical image segmentation. This method can alleviate the extensive annotation requirements typically necessary for training accurate segmentation models in medical imaging.
Strain and damage monitoring of optical fiber sensor‐embedded carbon fiber reinforced polymer confined cracked pipes
Authors: Shi Jiajun , Kong Deao , Li Chenggao , Guo Rui , Xian Guijun , Liu Haibo , Tan Xiaolin 
Published: December 2024

AbstractPipelines for water, oil, or gas transportation are prone to cracking damage due to severe service conditions. Carbon fiber reinforced polymer (CFRP) composites have been applied to repair cracked pipelines. In the present paper, fiber Bragg grating (FBG) and Brillouin optical time domain analysis (BOTDA) technology were applied to monitor the circumferential strains of the steel pipes and CFRP confined seamless/cracked steel pipes in hydrostatic testing. The finite element model (FEM), and the mechanical model were used to verify and analyze monitored strains. The results showed that FBG achieved real‐time and high‐precision strain monitoring with an error of less than 9.3%, better than BOTDA (less than 22.0%). Compared with FBG, the strain of FEM showed that the error of seamless pipe is less than 6%, and the error of cracked pipe is less than 15%. FEM strain field analysis revealed the failure mode of the confined cracked pipe in tensile fracture of structural adhesive between CFRP and steel substrate. The debonding was identified by the sudden strain drops (4.3%–26.2%) in the cracked area. The leakage was identified by a sudden drop (53.0%) in the slope significantly and fluctuations from the curve of strain and hydrostatic pressure after failure.Highlights
Sensor‐embedded CFRP confined cracked pipes prevent leakage and monitor strain.
Multiple FBG sensors are more accurate to monitoring the pipe strain than BOTDA.
Debonding of CFRP confined cracked pipes is monitored by the sudden strain drop.
Leakage of CFRP confined cracked pipes is detected by strain fluctuations.
Interconnected expanded graphite/stearic acid networks for self‐lubricating PA6 composites with excellent heat dissipation performance
Authors: Feng Wenkai , Liang Bo , Li Haorong , Chen Jing , Gao Xiping , Yao Dahu , Lu Chang , Pang Xinchang 
Published: November 2024

AbstractThe improvement in social production efficiency demands increasingly faster mechanical operation speeds. However, under high‐speed friction conditions, the frictional heat generated by nylon 6 (PA6) components is difficult to dissipate efficiently, leading to severe wear and subsequently threatening the safe operation of the equipment. In this work, interconnected expanded graphite/stearic acid (EG/SA) networks in PA6 composites were constructed to achieve fast frictional heat dissipation and self‐lubricating properties by a simple hot‐pressing method. The synergistic lubrication of EG and SA results in PA6 composites with a low coefficient of friction (COF) of 0.12, a 74.5% reduction compared to pure PA6. The low COF reduces the generation of frictional heat, while the conduction and absorption of frictional heat by the EG/SA network accelerates the dissipation of frictional heat, ultimately lowering the contact temperature from 106.9°C to 40.6°C. The specific wear rate of the PA6 composite is as low as 1.7 × 10−5 mm3 N−1 m−1, which is 90.1% lower than that of pure PA6. This study provides a new solution for the rapid dissipation of frictional heat in polymer composites under harsh operating conditions and broadens the application range of wear‐resistant polymer composites.Highlights
Expanded graphite (EG) prevents stearic acid from leaking through adsorption.
The interconnected EG network transfers frictional heat to stearic acid.
The phase transition of stearic acid can absorb heat and promote lubrication.
The low COF and high heat dissipation make PA6 composites highly wear‐resistant.
Prediction and Computational Analysis of Annular Photonic Crystal Based Multifunctional Directional Coupler Quantum Device for Optical Networks
Authors: Doss M Pradeep , Jeyachitra R. K. 
Published: November 2024

AbstractIn this research article, a novel all‐optical directional coupler switch is designed with multifunctionality for various optical network applications. The analog Silicon (Si) and Silicon Dioxide (SiO2) based annular crystal nano‐resonator in photonic crystal (PC) platform is used to realize the 2 × 2 structure and is further explored. The proposed structure dimensions are predicted by using Machine Learning (ML) based random forest regression model, design and numerical analysis is carried out using Finite‐Difference‐Time‐Domain (FDTD) method. Dataset records are collected by varying the input launch type, operating wavelength, and annular photonic crystal (APC) dimensions, the electric field and normalized power values in all ports are calculated. Optical network devices with high‐performance is realized, such as an optical coupler switch, wavelength selective switches (WSS), slow light device, and an optical multiplexer. Hence, the reported photonics platform with a compact size of 98.96 µm2, fast response time, and high extinction ratio providing multifunctional operation with quantum computing is more appropriate for microwave photonics, optical interconnects, and quantum computing.
Microbial inocula enhance effects of biochar amendments on crop productivity, soil health, and microbial communities: A meta‐analysis
Authors: Ross Aysha Tapp , Emery Sarah M. 
Published: December 2024

AbstractBiochar as a soil amendment can increase soil carbon sequestration, soil microbial diversity, overall yields, and general soil functioning. To accelerate these effects, biochar is often activated with beneficial soil microbes such as arbuscular mycorrhizal fungi or plant growth promoting bacteria via microbial inocula. However, there has been no comprehensive review of the effects of microbial inoculum additions for biochar amendments. We conducted a meta‐analysis to quantify the crop and soil effects of adding biochar alone compared to adding biochar with a microbial inoculum. The meta‐analysis included 56 studies and examined whether the effects depended on the source of inoculum, inoculum type, or experiment type. We found that microbial inocula increased soil N and soil organic carbon concentrations and crop productivity compared to adding biochar alone. However, these effects were limited to locally sourced and research‐grade inocula, while commercial inoculum products only slightly increased soil P. Fungal inocula had stronger effects than bacterial inocula. Inoculum effects were the strongest in greenhouse studies, increasing N, plant productivity, and fungal abundance, while field studies only increased plant productivity, suggesting that biochar activation with inoculum in on‐farm settings may not provide intended positive effects, and thus alternative methods for biochar activation may be needed.
Advancing Sustainable Development Goal 15: The Role of Corporate Governance Structures and Environmental Regulations in Emerging Economies
Authors: Saeed Ummar Faruk , Ning Wu , Agyemang Andrew Osei 
Published: December 2024

ABSTRACTThis study advances the literature on sustainable development, corporate governance, and environmental management by examining the interplay between governance structures (GS) and biodiversity disclosure (BD) in alignment with Sustainable Development Goal 15. Grounded in institutional, legitimacy, and stakeholder theories, we investigate how various GS influence firms' commitment to biodiversity reporting in sub‐Saharan Africa, while also considering the moderating role of environmental regulations. Utilizing panel data from 386 environmentally sensitive manufacturing firms between 2010 and 2022, we employ the two‐step system generalized method of moments (GMM) modeling, as proposed by Blundell and Bond and addressed potential endogeneity issues through instrumental variable two‐stage least squares (IV‐2SLS), propensity score matching, and lagged effect estimations. Our findings reveal that board diversity, particularly gender diversity and the presence of foreign nationals, positively impacts BD. Additionally, structural attributes such as board size and independence enhance BD, while CEO duality negatively affects this outcome. Furthermore, a positive relationship is observed between the frequency of board meetings and BD, yet a negative association exists with meeting attendance. Notably, environmental regulations not only increase BD, but significantly enhance the effect of GS on BD. These findings provide valuable insights for policymakers and stakeholders, contributing to the discourse on Sustainable Development Goal 15 by advocating for stronger governance frameworks to bolster biodiversity conservation and environmental stewardship in emerging economies.
Theoretical reevaluation and machine learning analysis on the concrete confinement effect of square reinforced concrete columns
Authors: Lai Bing‐Lin , Zhou Xiang , Zheng Xiao‐Feng , Li Shan , Venkateshwaran Akshay 
Published: December 2024

AbstractConcrete confinement effect plays a pivotal role in augmenting the strength and ductility of concrete structures. However, traditional models are often proven to be time‐consuming and occasionally yield unreliable predictions. In this paper, the evaluation of traditional models is performed by deconstructing the derivation process into critical steps: determination of confining pressure, calculation of confinement effectiveness coefficient, and the assessment of confined strength and strain. Each step undergoes rigorous scrutiny with the predictions being compared against experimental results and numerical simulations. Subsequently, data‐driven analysis is conducted leveraging a database comprising 466 specimens spanning across a wide spectrum of material strengths and geometric configurations. The power of six machine learning (ML) models is harnessed to unveil the correlations between input parameters and the confinement degree. After that, the interpretability analysis is undertaken to further evaluate the feasibility of the trained ML models. In comparison to traditional semi‐empirical models, ML techniques present a promising alternative for quantifying the confinement effect rapidly and efficiently, opening new avenues for advancing concrete structural analysis.
X‐Ray Fluorescence Determination of the Chemical Composition and Coating Thickness of Artifact Surfaces Using the Intensity Ratio of α‐ and β‐Lines
Authors: Tsvetyansky A. L. , Revenko A. G. 
Published: November 2024

ABSTRACTThe potential capabilities of the x‐ray spectral analysis method and the efforts of many researchers have ensured its widespread use in industry and scientific research. X‐ray fluorescence analysis (XRF) is one of the non‐destructive methods widely used to determine the chemical composition of automobile catalysts, solar panels, coins, jewelry, and so forth. In recent years, the problems of studying gold and silver objects of artistic value have attracted great interest. This paper presents a review of work on determining the chemical composition and thickness of single‐layer and multi‐layer coatings of artifacts and other objects of study with surfaces of complex configuration using the ratio of the intensities of characteristic x‐ray radiation of α‐ and β‐lines.
Forest Damage
Authors: Hantula Jarkko , Elfstrand Malin , Hekkala Anne-Maarit , Hietala Ari M. , Honkaniemi Juha , Klapwijk Maartje , Koivula Matti , Matala Juho , Rönnberg Jonas , Siitonen Juha , Widemo Fredrik 
Published: December 2024

Abstract

Heterobasidion root and butt rot pose a greater risk in continuous cover forestry (CCF) than in rotation forestry (RF) in conifer-dominated forests, regardless of whether selective, gap or shelterwood cutting is used.

Damage from wind, snow, spruce bark beetle, and large pine weevil are likely to be less severe in CCF than in RF. However, the conversion of RF to CCF may briefly expose stands to windthrow.

Browsing by large herbivores on saplings may limit regeneration of tree species other than spruce in continuous cover forestry and reduce tree species diversity, but alternative silvicultural practices may also increase forage availability in the field and shrub layer. Browsing damage outcomes for saplings in CCF are difficult to predict.

For many types of damage in CCF, substantial knowledge gaps complicate the assessment of damage risk.
Reasons for Hope, Reasons to Doubt
Authors: Laws Ben 
Published: November 2024

AbstractThis final chapter assesses the future of nonreligious claims, highlighting the role of NGOs in raising awareness and supporting nonreligious claimants. It discusses recent policy developments and questions the precedent set by apparent successes. The chapter aims to provide a comprehensive introduction to the challenges and opportunities faced by nonreligious claimants, while also acknowledging the significant human toll experienced by asylum case officers. It calls for continued advocacy, research, and policy reform to better address the needs of nonreligious asylum seekers, ensuring that their rights and identities are adequately recognised and protected within the asylum framework.