bluuebunny/crossref_metadata_2025_split huggingface dataset:
Foliar characteristics of neotropical forest affect assemblages structure of parasitoid insects
Authors: Lara-Cetina Brandon , Ballina-Gómez Horacio , Bordera Santiago , Leirana-Alcocer Jorge , González-Moreno Alejandra 
Published: December 2024

Abstract
Several authors suggest that greater vegetation complexity provides more shelters, supporting higher parasitoid diversity. Additionally, it serves as visual cue in host searching. This study evaluates how visual stimuli and herbivore-induced vegetation changes affect parasitoid strategies and guilds in low deciduous forest [Yabucu], and Medium Semi-Evergreen forest [Noh-Bec]. We calculated the relative abundance of idiobiont and koinobiont life strategies for each vegetation type and constructed the range-abundance curves of these communities. Also, the relationship of guilds with the different types of damage from herbivory and leaf characteristics were described. The koinobiont:idiobiont (K:I) ratio was 6:1 (86.65% koinobionts and 13.35% idiobionts) in Yabucú and 1:2 (32.78% koinobionts and 67.22% idiobionts) in Noh-Bec. Some guilds were associated with vegetation: a negative correlation between fluctuating asymmetry seedlings (FAS) and parasitoids attacking larvae into the fruiting bodies of fungi was founded; the FAS is an indirect indicator of herbivory, nonetheless, the parasitoids found do not target phytophagous hosts, which makes an inverse relationship plausible and could potentially reduce intra-guild competition. Hyperparasitoids were positively associated with holes in adult plants (HA); with an association with herbivore parasitoids, which could be contributing to the recorded evidence of holes.
Not only infinity: Poverty and ‘minutiae’ in the philosophy of Giordano Bruno
Authors: Bassi Simonetta 
Published: December 2024

Abstract
This paper develops two perspectives. On the one hand, it analyzes and reconstructs the relationship between wealth and poverty as addressed by Giordano Bruno in the Expulsion of the Triumphant Beast, both against the backdrop of the new geographical discoveries and mercantilist theories and in relation to Bruno’s project of ethical, political, and religious renewal. On the other hand, it recovers Bruno’s passages on the ‘minuzzarie’ as a key concept to redress ‘ontological poverty’ by locating in every aspect of reality, even insignificant ones, a center of vital energy. At the beginning and at the end of the paper, mention is made of some Heideggerian writings that reveal some common assumption with Bruno’s ideas.
A multi-technique detection of an eccentric giant planet around the accelerating star HD 57625
Authors: Barbato D. , Mesa D. , D’Orazi V. , Desidera S. , Ruggieri A. , Farinato J. , Marafatto L. , Carolo E. , Vassallo D. , Ertel S. , Hom J. , Anche R. M. , Battaini F. , Becker A. , Bergomi M. , Biondi F. , Cardwell A. , Cerpelloni P. , Chauvin G. , Chinellato S. , Desgrange C. , Di Filippo S. , Dima M. , Machado T. S. Gomes , Gratton R. , Greggio D. , Henning Th. , Kenworthy M. , Laudisio F. , Lazzoni C. , Leisenring J. , Lessio L. , Lorenzetto A. , Mohr L. , Montoya M. , Rodeghiero G. , Patience J. , Power J. , Ricci D. , Santhakumari K. K. R. , Sozzetti A. , Umbriaco G. , Pallauta M. Vega , Viotto V. , Wagner K. 
Published: December 2024

Context. The synergy between different detection methods is a key asset in exoplanetology that allows the precise characterization of detected exoplanets and robust constraints even in the case of a non-detection. The interplay between imaging, radial velocities and astrometry has recently produced significant advancements in exoplanetary science.
Aims. We report a first result of an ongoing survey performed with SHARK-NIR, the new high-contrast near-infrared imaging camera at the Large Binocular Telescope, in parallel with LBTI/LMIRCam in order to detect planetary companions around stars with a significant proper motion anomaly. We focus on HD 57625, a F8 star for which we determine a 4.8−2.9+3.7 Ga age, exhibiting significant astrometric acceleration and for which archival radial velocities indicate a previously undetected massive long-period companion.
Methods. We analysed the imaging data we collected with SHARK-NIR and LMIRCam in synergy with the available public SOPHIE radial velocity time series and HIPPARCOS-Gaia proper motion anomaly. With this joint multi-technique analysis, we characterised the companion causing the astrometric and radial velocity signals.
Results. The imaging observations result in a non-detection, indicating the companion to be in the substellar regime. This is confirmed by the synergic analysis of archival radial velocity and astrometric measurements resulting in the detection of HD 57625 b, a 8.43−0.91+1.1 MJup planetary companion with an orbital separation of 5.70−0.13+0.14 au and an eccentricity of 0.52−0.03+0.04.
Conclusions. HD 57625 b joins the small but growing population of giant planets on outer orbits with a true mass determination provided by the synergic usage of multiple detection methods. This again proves the importance of a multi-technique analysis in providing a robust characterization of planetary companions.
Median nerve impairment in leprosy: how does it differ from the classic carpal tunnel syndrome?
Authors: Alves Pedro Henrique Sirotheau Corrêa , Cirino Fernanda de Oliveira , Garcia Leonardo Peixoto , Fernandes João Paulo Moreira , Luppi Andrea De Martino , Antunes Douglas Eulálio , Pereira Raquel Campos , Junior Wilson Marques , Goulart Isabela Maria Bernardes , Santos Diogo Fernandes dos 
Published: December 2024

Abstract
Background Carpal tunnel syndrome (CTS) has already been described as a possible form of neural leprosy presentation. However, the median nerve can be involved in this neuropathy in proximal segments and, sometimes, with an asymmetric impairment of the digital branches.
Objective To detail the pattern of median nerve impairment through nerve conduction study (NCS) and ultrasound evaluation.
Methods This cross-sectional study comprises 15 primary neural leprosy (PNL) patients and 14 patients with CTS who underwent peripheral nerve ultrasonography and NCS evaluation.
Results From the total, 92.8% of patients with CTS and 80% with PNL had bilateral impairment of the median nerve, with 27 nerves in each group. Considering the cross-sectional area (CSA) of the tunnel (Mt) segment, 63% of the nerves in the CTS and 74.1% in the PNL groups were found to be thickened, with an average CSA of 13.4 ± 4.4 and 12.4 ± 4.6, respectively (p = 0.18). The CSA of the proximal tunnel (Mpt) segment showed thickening in only 3.7% in the CTS group and 96.3% in the PNL (p < 0.0001), with an average of 6.6 ± 1.3 and 17.0 ± 6.7, respectively (p < 0.001). Finally, 88.9% of the nerves in the PNL group and only 7.4% in the CSA (p < 0.0001) showed a reduction in conduction velocity in the distal forearm, with an average of 41.0 ± 6.3 and 53.2 ± 5.2, respectively (p < 0.0001).
Conclusion The presence of neural thickening and demyelinating impairment in the segments proximal to the carpal tunnel favors the diagnosis of leprosy.
Controllable autofocusing circular Pearcey Airyprime beam
Authors: Yang Shuo , Yu Peixin , Wu Binyu , Ge Xiaolu , Chen Chidao , Man Zhongsheng , Zhang Liping 
Published: December 2024

Abstract
This paper introduces a novel type of abrupt autofocusing beam called the circular Pearcey Airyprime beam (CPApB). Theoretical investigations and experimental verification of the propagation dynamics of the CPApB are conducted. Our results indicate that the focusing intensity of the CPApB is significantly higher than that of the circular Pearcey Airy beam (CPAB), reaching about twice that of the CPAB. Therefore, the CPApB exhibits superior autofocusing capability compared to the CPAB under identical conditions. Furthermore, the influence of different decay factors and astigmatism factors on the self-focusing characteristics of the CPApB are investigated. By delving into the underlying principles governing the CPApB, our findings offer new insights and establish foundational theories, aiming to enhance the efficient and precise control of the beam. The superior autofocusing characteristics of the CPApB are expected to be applied to various media.
A high-precision calibration method for nonlinear error coefficients of accelerometer components
Authors: Lu Kewen , Wang Xinlong , Nie Guanghao , Ding Wei 
Published: December 2024

Abstract
With the continuous improvement of measurement accuracy requirements for inertial devices, how to accurately calibrate nonlinear error coefficients of accelerometer components has become an important factor affecting the accuracy of the inertial navigation system. Centrifuge calibration method can continuously provide a specific force greater than 1 g, which can fully excite the nonlinear errors of accelerometer components and is a commonly used method for calibrating nonlinear error coefficients. However, on the one hand, traditional centrifuge speeds are often selected based on empirical experience, lacking a scientific determination method. This can lead to a decrease in the calibration accuracy of nonlinear error coefficients. On the other hand, the inability to accurately model the highly complex and time-varying test errors during actual calibration further reduces the calibration accuracy. Therefore, a high-precision calibration method for nonlinear error coefficients is proposed. Firstly, by introducing G-optimal experimental design criterion to minimize the maximum scaled prediction variance of output prediction values, the optimal speed combination is designed to achieve the highest accuracy in estimating nonlinear error coefficients. Based on the idea of semi-parametric regression, system errors caused by calibration test errors are treated as parameters to be estimated, and a high-precision nonlinear error coefficient calibration model is established. Then the influence of calibration test errors is eliminated by estimating and compensating the system errors. Centrifuge calibration test results show compared with the traditional method, the ranges and standard deviations of the repeated calibration results of the proposed method are reduced by more than 80.37% and 63.01%. This indicates that the proposed method can effectively eliminate the influence of calibration test errors and achieve high-precision calibration of nonlinear error coefficients.
Improving the performance of quantum well solar cells with photonic crystal
Authors: Liu Weiye , Guo Jiaping , Ding Ding , Tan Xinhui , Xu Haonan , He Lingyu , Zhang Wei , Han Lili , Wang Zhaowei , Gong Weihua , Qi Jinyun , Tang Xiansheng 
Published: December 2024

Abstract
The fabrication of quantum well solar cells with surface photonic crystal (SPC) and embedded photonic crystal (EPC) structures has resulted in solar cells with improved properties. When compared to reference solar cells (RSCs), the photoluminescence (PL) intensities of SPC solar cells and EPC solar cells have been enhanced by 89% and 114%, respectively. This indicates improved light absorption and emission characteristics in the presence of the periodic patterns (PCs). The short-circuit current (Isc) of EPC solar cells is 31% higher than that of RSCs, suggesting improved light absorption and carrier generation. On the other hand, SPC solar cells exhibit a 6% higher Isc compared to RSCs, and the open-circuit voltage has increased simultaneously. The fill factors (FF) of the solar cells are 84% for RSCs, 86% for SPC solar cells, and 76% for EPC solar cells. The higher FF in SPC solar cells suggests improved charge carrier collection efficiency. In terms of photoelectric conversion efficiency, SPC solar cells demonstrate a 10.6% increase, while EPC solar cells show a 7.7% increase. These improvements indicate that the incorporation of PCs in the solar cells enhances their ability to convert light into electrical energy. These findings highlight the potential of photonic crystals engineering for enhancing the performance of solar cells.
Editorial for focus on emerging processes and applications of atomic and molecular layer deposition
Authors: Meng Xiangbo , Elam Jeffrey W , Barry Sean 
Published: December 2024

Abstract
This Focus aims to provide a platform for the latest research progress in atomic and molecular layer deposition (ALD and MLD), which collects 10 original research articles and 2 review papers. The original research articles present new precursors, new processes, and new applications. The review papers give a timely summary on the surface chemistry of metal ALD processes and flexible electronics resulting from ALD and MLD, respectively. This ensemble forms a valuable collection that advances our understanding and knowledge of ALD and MLD, and inspires the continued development of these valuable technologies.
Patterning and nanoribbon formation in graphene by hot punching
Authors: Abbaspourmani AmirAli , Shivayogimath Abhay , Petersen Ritika S , Lyksborg-Andersen Anton , Hansen Thomas W , Keller Stephan S , Booth Timothy J 
Published: December 2024

Abstract
Large area graphene patterning is critical for applications. Current graphene patterning techniques, such as electron beam lithography and nano imprint lithography, are time consuming and can scale unfavorably with sample size. Resist-based masking and subsequent dry plasma etching can lead to high roughness edges with no alignment to the underlying graphene crystal orientations. In this study, we present hot punching as a novel and feasible method for patterning of chemical vapor deposition (CVD) graphene sheets supported by a polyvinylalcohol (PVA) layer. Additionally, we observe the effect of such hot punching on graphene supported by PVA via optical microscopy, Raman spectroscopy, AFM, and TEM, including wrinkling, strain and the formation of nanoribbons with crystallographically aligned and smooth edges due to fracturing. We present hot punching as a facile technique for the production of arrays of such nanoribbons.
An efficient deep unrolling network for sparse-view CT reconstruction via alternating optimization of dense-view sinograms and images
Authors: Sun Chang , Liu Yitong , Yang Hongwen 
Published: December 2024

Abstract

Objective. Recently, there have been many advancements in deep unrolling methods for sparse-view computed tomography (SVCT) reconstruction. These methods combine model-based and deep learning-based reconstruction techniques, improving the interpretability and achieving significant results. However, they are often computationally expensive, particularly for clinical raw projection data with large sizes. This study aims to address this issue while maintaining the quality of the reconstructed image. Approach. The SVCT reconstruction task is decomposed into two subproblems using the proximal gradient method: optimizing dense-view sinograms and optimizing images. Then dense-view sinogram inpainting, image-residual learning, and image-refinement modules are performed at each iteration stage using deep neural networks. Unlike previous unrolling methods, the proposed method focuses on optimizing dense-view sinograms instead of full-view sinograms. This approach not only reduces computational resources and runtime but also minimizes the challenge for the network to perform sinogram inpainting when the sparse ratio is extremely small, thereby decreasing the propagation of estimation error from the sinogram domain to the image domain. Main results. The proposed method successfully reconstructs an image (512 × 512 pixels) from real-size (2304 × 736) projection data, with 3.39 M training parameters and an inference time of 0.09 s per slice on a GPU. The proposed method also achieves superior quantitative and qualitative results compared with state-of-the-art deep unrolling methods on datasets with sparse ratios of 1/12 and 1/18, especially in suppressing artifacts and preserving structural details. Additionally, results show that using dense-view sinogram inpainting not only accelerates the computational speed but also leads to faster network convergence and further improvements in reconstruction results. Significance. This research presents an efficient dual-domain deep unrolling technique that produces excellent results in SVCT reconstruction while requiring small computational resources. These findings have important implications for speeding up deep unrolling CT reconstruction methods and making them more practical for processing clinical CT projection data.
Impact of image formation factors on material discrimination in spectral CT
Authors: Rajagopal Jayasai , Zarei Mojtaba , Vrbaski Stevan , Pritchard William F , Abadi Ehsan , Jones Elizabeth C , Samei Ehsan 
Published: December 2024

Abstract

Objective. The accuracy of material decomposition in spectral computed tomography (CT) depends on the information quality captured in image acquisition, a factor that cannot be adequately assessed using conventional image quality metrologies due to the multi-energy nature of spectral CT. This work used metrologies specific to spectral CT to evaluate the impact of acquisition conditions on the quality of spectral CT images and accuracy of material decomposition techniques. Approach. Computational phantoms were created with cylindrical shapes and variable sizes (20–40 cm), containing inserts of iodine and gadolinium (1–8 mg ml−1). The phantoms were imaged using a validated CT simulator modeling a clinical photon-counting CT scanner. The acquisitions were done at different detector energy thresholds (50–90 keV) and tube currents (25–250 mAs). The images were used to develop and train a data-driven material identification and quantification algorithm. Two spectral metrologies, multivariate contrast-to-noise ratio (CNR) and separability index, were used to characterize the impact of energy threshold, tube current, phantom size, and material concentration on signal quality. The results were interpreted in terms of figures of merit of accuracy for classification and mean absolute error (MAE) and root mean squared error (RMSE) for regression. Main results. Signal quality for iodine and gadolinium was maximized with a low energy threshold, high tube current, and small phantom size. While conventional CNR terms predicted variable image quality for two-thirds of all conditions, multivariate CNR was above 10 for half of those. Separability index showed that for a phantom size greater than 30 cm, a minimum of 75–110 mAs is required to separate 2 mg ml−1 of iodine and gadolinium. For both classification and regression tasks, a random forest model with a local statistics dataset provided the best performance. Across conditions, classification performance was 0.66–0.99 for I accuracy, 0.72–0.99 for Gd accuracy. Regression performance was 0.02–0.91 mg ml−1 I and 0.02–0.59 mg ml−1 Gd for MAE and 0.11–1.08 mg ml−1 I and 0.07-0.76 mg ml−1 Gd for RMSE. Significance. Multivariate CNR and separability index metrologies can predict material decomposition performance. Theses metrics demonstrated that the decomposition of iodine and gadolinium have higher separability when the acquisition is done at a lower energy threshold, with a higher tube current, and when the imaged object has a smaller size. Object size had the largest impact on metrics and decomposition performance.
Wave-packet trajectory analysis of the self-interference and cross-interference mechanisms in double-slit interference involving single electrons
Authors: Pan Junheng , Liu Shaoran , Zhang Bozhou , Tang Qiang , Tang Jau 
Published: December 2024

Abstract
In Copenhagen’s interpretation, a self-interference mechanism is assumed for a wave function to split and to pass through the slits simultaneously, then recombine and collapse to generate a dot signal on a detector. Its use of a single wave function to describe a whole ensemble without accounting for a particle’s individuality is incomplete. To better understand the single-electron double-slit interference, we use a wave-packet trajectory approach to track each electron’s dynamics and calculate the time-dependent interference intensity. We analyze the self-interference and cross-interference mechanisms to illustrate how an electron’s coherence length affects the self-interference and how it dictates the wave packet overlaps between adjacent electrons for the cross-interference mechanism to be effective. To circumvent a conflicting dilemma between the electron’s indivisibility and its wave-packet split while passing through the slits, we consider an alternate mechanism involving slit-induced quantized momentum. This mechanism preserves the electron’s indivisibility and avoids the illusive split, recombination and mysterious collapse of a single particle’s wave function.
Multiple-model-based adaptive state fusion estimation of IWMD-EV using SSUKF
Authors: Dou Guowei , Li Zhongxing , Xu Xing , Chen Te 
Published: December 2024

Abstract
To improve the preciseness degree and adaptive adjustment ability of the state acquisition system under multiple operating conditions, a vehicle state fusion estimation strategy using strong-tracking suboptimal unscented Kalman filtering (SSUKF) algorithm and adaptive weights is proposed. The vehicle models were established by comprehensively characterizing the multi-parameter mapping relationship under the kinematic, dynamic, and electromechanical coupling driving relationship of in-wheel motor drive electric vehicle (IWMD-EV). To improve estimation performance of vehicle state estimation system in face of nonlinear factors such as noise and interference, a vehicle kinematic-based observer (KO) and a dynamic-based observer (DO) were developed based on the SSUKF algorithm. In addition, to enhance the overall preciseness degree and its adaptive adjustment ability for large-scale road conditions, a state fusion estimation method with adaptive weight is presented by combining redundant information of multiple model observers. The results demonstrated that the proposed method can significantly improve the estimation preciseness degree and the adaptive ability for complex working conditions.
A novel multi remote sensing image encryption scheme exploiting modified zigzag transformation and S-Box
Authors: Niu Tong , Liu Yi , Gao Lin 
Published: December 2024

Abstract
This paper proposed a novel multi-image remote sensing image encryption algorithm. The proposed algorithm leverages a novel fractional-order chaotic system, an enhanced Zigzag scanning technique, and a refined S-box for robust encryption. Initially, the plain remote sensing images are transformed into a one-dimensional sequence using an extended Zigzag transformation. Subsequently, chaotic sequence indices, generated by the advanced fractional-order chaotic system, are utilized for pixel position scrambling. During the diffusion phase, two differently ordered diffusions were performed to enhance the algorithm’s resistance to chosen-plaintext attacks after the S-box based encryption. To further augment the security of the proposed scheme, an XOR operation is executed on each color channel of the encrypted images. Additionally, to expand the key space and strengthen resistance to chosen-plaintext attacks, the initial values and parameters involved in the algorithm are intricately tied to the SHA3–512 hash value of the plaintext image. The experimental results show that the proposed algorithm not only meet the demand of efficiency, but also could resist commonly used security attacks.