bluuebunny/crossref_metadata_2025_split huggingface dataset:
Femtosecond laser-assisted corneal transplantation with a low-energy, liquid-interface system
Authors: Liu Yu-Chi , Morales-Wong Fernando , Patil Moushmi , Han Sang Beom , Lwin Nyein C. , Teo Ericia Pei Wen , Ang Heng Pei , Yussof Nur Zah M. , Mehta Jodhbir S. 
Published: April 2022

AbstractFemtosecond laser-assisted keratoplasty has been proposed as a treatment option for corneal transplantation. In this study, we investigated and compared the outcomes of Ziemer Z8 femtosecond laser (FSL)-assisted penetrating keratoplasty (PK) using a liquid interface versus flat interface. Thirty fresh porcine eyes underwent FSL-assisted PK with the Z8 using different levels of energies (30%, 90% or 150%) and different interfaces (liquid or flat). The real-time intraocular pressure (IOP) changes, incision geometry, corneal endothelial damage, as well as the accuracy of laser cutting and tissue reaction, were performed and compared. We found that the overall average IOP at all laser trephination stages was significantly higher with the flat interface, regardless of the energy used (68.9 ± 15.0 mmHg versus 46.1 ± 16.6 mmHg; P < 0.001). The overall mean laser-cut angle was 86.2º ± 6.5º and 88.2º ± 1.0º, for the liquid and flat platform respectively, indicating minimal deviation from the programmed angle of 90º. When high energy (150%) was used, the endothelial denuded area was significantly greater with the flat interface than with liquid interface (386.1 ± 53.6 mm2 versus 139.0 ± 10.4 mm2P = 0.02). The FSL cutting did not cause obvious tissue reaction alongside the laser cut on histological evaluation. The results indicated a liquid interface is the preferable choice in FSL-assisted corneal transplantation.
The relationship between ecosystem services and human modification displays decoupling across global delta systems
Authors: Reader Martin Oliver , Eppinga Maarten B. , de Boer Hugo Jan , Damm Alexander , Petchey Owen L. , Santos Maria J. 
Published: April 2022

AbstractThe ties between a society and its local ecosystem can decouple as societies develop and replace ecosystem services such as food or water regulation via trade and technology. River deltas have developed into important, yet threatened, urban, agricultural and industrial centres. Here, we use global spatial datasets to explore how 49 ecosystem services respond to four human modification indicators, e.g. population density, across 235 large deltas. We formed bundles of statistically correlated ecosystem services and examined if their relationship with modification changed. Decoupling of all robust ecosystem service bundles from at least one modification indicator was indicated in 34% of deltas, while 53% displayed decoupling for at least one bundle. Food-related ecosystem services increased with modification, while the other bundles declined. Our findings suggest two developmental pathways for deltas: as coupled agricultural systems risking irreversible local biodiversity loss; and as decoupled urban centres externalising the impact of their growing demands.
Cavitation recognition of axial piston pumps in noisy environment based on Grad‐CAM visualization technique
Authors: Chao Qun , Wei Xiaoliang , Tao Jianfeng , Liu Chengliang , Wang Yuanhang 
Published: April 2022

AbstractThe cavitation in axial piston pumps threatens the reliability and safety of the overall hydraulic system. Vibration signal can reflect the cavitation conditions in axial piston pumps and it has been combined with machine learning to detect the pump cavitation. However, the vibration signal usually contains noise in real working conditions, which raises concerns about accurate recognition of cavitation in noisy environment. This paper presents an intelligent method to recognise the cavitation in axial piston pumps in noisy environment. First, we train a convolutional neural network (CNN) using the spectrogram images transformed from raw vibration data under different cavitation conditions. Second, we employ the technique of gradient‐weighted class activation mapping (Grad‐CAM) to visualise class‐discriminative regions in the spectrogram image. Finally, we propose a novel image processing method based on Grad‐CAM heatmap to automatically remove entrained noise and enhance class features in the spectrogram image. The experimental results show that the proposed method greatly improves the diagnostic performance of the CNN model in noisy environments. The classification accuracy of cavitation conditions increases from 0.50 to 0.89 and from 0.80 to 0.92 at signal‐to‐noise ratios of 4 and 6 dB, respectively.
Joint range and velocity estimation for orthogonal frequency division multiplexing‐based high‐speed integrated radar and communications system
Authors: Wang Xiaojiang , Zhang Zhenkai 
Published: April 2022

AbstractThe integrated radar and communications (IRC) waveform can simultaneously estimate the range and velocity of other targets while communicating with other facilities. In high‐speed scenarios, the IRC echo signal based on orthogonal frequency division multiplexing (OFDM) needs to consider the intra‐symbol and inter‐subcarrier Doppler effects. This paper first builds a receiving model of the integrated echo signal by including the intra‐symbol and inter‐subcarrier Doppler effects. On this basis, we propose a two‐step joint range and velocity estimation method, where rough estimation is performed by an improved estimating the signal parameters via the rotational invariance technique (ESPRIT), and a least‐square weighted (LSW) method is applied for fine estimation. The Cramer‐Rao lower bound (CRLB) of the receiving model is also provided, and the computational complexity of the proposed method is analyzed. Simulation results demonstrate the superiority of the proposed method.
Person Re‐identification Based on Feature Erasure and Diverse Feature Learning
Authors: Peng Lu , Jidong Zhang , Zhen Zhang , Wei Wang , Yamei Dou 
Published: April 2022

AbstractRobust and comprehensive modelling of targets is the key to successful person re‐identification. However, some useful information may be ignored, since CNNs tend to learn from the most distinctive feature region of the human body. In the present study, a multi‐branch lightweight network structure that can enhance the ability of diverse feature retrieval is introduced. The proposed network consists of three branches. In the feature erasure branch, a drop block model is added to remove the horizontal region with the highest activation degree from feature vectors so as to allow the network to learn relatively low discrimination features. The global branch is used as an essential supplement to the feature erasure branch. A unified horizontal segmentation strategy is adopted in the local branch to avoid the influence of feature dislocation. Finally, diverse feature learning is achieved through the branch network structure. The proposed method can achieve state‐of‐the‐art results on Market‐1501, CUHK03 and DukeMTMC‐Reid data sets, thereby demonstrating the effectiveness of the method.
Cinnamaldehyde and indocyanine green loaded lipid nanoparticles induced intracellular oxidative/thermal stress damage for effective cervical cancer therapy
Authors: Yan Qiong‐Qiong , Li Bing‐Lin 
Published: April 2022

AbstractThe redox and thermal balances in cancer have been considered two fundamental bases for cancer progression. As a result, the development of novel action ways to disrupt these balances can therefore give potential anticancer benefits. Herein, cinnamaldehyde (CA) as a plant‐derived drug which could accelerate the H2O2 generation and elevate the reactive oxygen species (ROS) level in cancer cells, is employed to elevate the ROS level of cancer cells while the indocyanine green (ICG) as a photothermal agent was co‐delivered to induce oxidative/thermal stress damage to cells that provide a novel but effective way for effective cancer therapy. The CA and ICG were loaded in lipid nanoparticles to be a drug delivery system (DDS) for safe and effective drug delivery to tumour. The HeLa (human cervical cancer cell line) cells were employed as model and showed promising effects both in vitro and in vivo.
Time-domain self-broadened and air-broadened nitrogen S-branch Raman linewidths at 80–200 K recorded in an underexpanded jet
Authors: Retter Jonathan E. , Koll Matthew , Richardson Daniel R. , Kearney Sean P. 
Published: April 2022

We report pure-rotational N2–N2, N2–air, and O2–air S-branch linewidths for temperatures of 80–200 K by measuring the time-dependent decay of rotational Raman coherences in an isentropic free-jet expansion from a sonic nozzle. We recorded pure-rotational hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering (fs/ps CARS) spectra along the axial centerline of the underexpanded jet, within the barrel shock region upstream of the Mach disk. The dephasing of the pure-rotational Raman coherence was monitored using probe-time-delay scans at different axial positions in the jet, corresponding to varying local temperatures and pressures. The local temperature was obtained by fitting CARS spectra acquired at zero probe time delay, where the impact of collisions was minimal. The measured decay of each available Raman transition was fit to a dephasing constant and corrected for the local pressure, which was obtained from the CARS-measured static temperature and thermodynamic relationships for isentropic expansion from the known stagnation state. Nitrogen self-broadened transitions decayed more rapidly than those broadened in air for all temperatures, corresponding to higher Raman linewidths. In general, the measured S-branch linewidths deviated significantly in absolute and relative magnitudes from those predicted by extrapolating the modified exponential gap model to low temperatures. The temperature dependence of the Raman linewidth for each measured rotational state of nitrogen (J ≤ 10) and oxygen (N ≤ 11) was fit to a temperature-dependent power law over the measurable temperature domain (80–200 K) and extrapolated to both higher rotational states and room temperature. The measured and modeled low-temperature linewidth data provided here will aid low temperature gas-phase pressure measurements with fs/ps CARS.
Small-world connectivity dictates collective endothelial cell signaling
Authors: Lee Matthew D. , Buckley Charlotte , Zhang Xun , Louhivuori Lauri , Uhlén Per , Wilson Calum , McCarron John G. 
Published: April 2022

SignificanceThe endothelium is the single layer of cells lining all blood vessels and acts as a central control hub to regulate multiple cardiovascular functions in response to hundreds of physiological stimuli. The detection of various physiological stimuli is distributed in spatially separated sites across the endothelium. Distributed sensing is difficult to reconcile with the requirement for coordinated cell activity across large regions of the endothelium. Here, we show that the endothelium resolves the issue by using a network with scale-free and small-world properties. The organization confers a high signal-propagation speed and a high degree of synchronizability across the endothelium. The network organization also explains the robust nature of endothelial communication and its resistance to damage or failure.
SIM key comparison in pneumatic gauge pressure for high accuracy pressure balances up to 120 kPa (SIM.M.P-K6)
Authors: Torres-Guzman J C , Aranzolo-Suarez J , Flores-Martinez F J , Cruz L de la , Olson D A , Forastieri J , Solano A , Neira C , Couto P R G , Palma J , Garcia S 
Published: April 2022

Main text
This report describes the results of a pneumatic pressure standards key comparison among eleven SIM National Metrology Institutes to determine their degree of equivalence in the pressure range from 10 kPa to 120 kPa in gauge mode. The pilot laboratory was the Centro Nacional de Metrología (CENAM, Mexico). All participating institutes used pneumatic pressure balances as their pressure standard. The transfer standard was a complete system including a pressure balance with a free-deformation piston-cylinder assembly and a set of masses. Eleven participants completed their measurements and reported the pressure-dependent effective areas of the transfer standard at specified pressures with the associated uncertainties. NRC/Canada and BSJ/Jamaica withdrew the comparison by not sending their measurements. To link the results of the nine laboratories that sent their results to the CCM.P- NIST, the USA provided the reference values. To evaluate the compatibility of the results of the participants their relative deviations from those obtained by NIST results were analyzed. The results of six participating NMIs agree with the NIST reference values within their expanded uncertainties (k = 2) in the entire pressure range from 10 kPa to 120 kPa according to the normalized error equation method.
To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.
The final report has been peer-reviewed and approved for publication by the CCM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
Determining damping terms in fractional wave equations
Authors: Kaltenbacher Barbara , Rundell William 
Published: April 2022

Abstract
This paper deals with the inverse problem of recovering an arbitrary number of fractional damping terms in a wave equation. We develop several approaches on uniqueness and reconstruction, some of them relying on Tauberian theorems that provide relations between the asymptotic behaviour of solutions in time and Laplace domains. The possibility of additionally recovering space-dependent coefficients or initial data is discussed. The resulting methods for reconstructing coefficients and fractional orders in these terms are tested numerically. In addition, we provide an analysis of the forward problem consisting of a multiterm fractional wave equation.
A novel MEMS inertial switch with frictional electrode
Authors: Du Liqun , Yang Xiaochen , Guo Bingjiang , Dong Yakun , Yuan Bowen , Zhao Jian , Liu Junshan 
Published: April 2022

Abstract
This paper presents a frictional MEMS inertial switch with aiming to solve the problems of short contact time and bounce. According to contact principle in MEMS inertial switch, a new enhanced contact method by friction is proposed and a frictional switch is designed. To compare the frictional switch with common rigid switch and flexible switch, three switches were fabricated by micro electroforming technology and tested by a standard dropping hammer system. The tested results show that the contact time of rigid switch, flexible switch and frictional switch is 13 μs, 85 μs and 620 μs, respectively. Both rigid switch and flexible switch have bounce problem, while frictional switch is closed stably without bounce phenomenon. Frictional MEMS inertial switch has great advantages in enhancing contact.
Decoupling method for four-degree-of-freedom automatic centering and tilting worktable
Authors: Shao Chunyu , Liu Yongmeng , Li Ruirui , Mei Yingjie , Tan Jiubin 
Published: April 2022

Abstract
The ultra-precise measurement of aero-engine rotor geometry error is the basis of its assembly, and adjusting the rotor coaxially with the measurement rotation axis is the key to ensure the measurement accuracy. As a typical adjustment device for rotor alignment, the traditional method of applying a four-degree-of-freedom centering and tilting table for adjustment does not take into account the coupling effect caused by the position of each adjustment motor not being perfectly perpendicular to each other, this paper gives the calibration method of the angle between each adjustment motor and the starting position of the angle grating, analyzes the principle of eccentricity and tilt adjustment and deduces the coupling solution method. Subsequently, the size of the coupling between the two adjustments is analyzed and an efficient adjustment method is given for its mechanical structure characteristics. The experimental results show that the platform can effectively decouple and quickly converge to the setting values of 0.3 µm and 0.5′′ for different initial eccentric distance and tilt angle. With the same adjustment accuracy, the number of adjustments is reduced by more than 50% and more than 37.5%, respectively, compared with the non-decoupled method.
Stability and bifurcation phenomena in asymptotically Hamiltonian systems
Authors: Sultanov Oskar A 
Published: April 2022

Abstract
The influence of time-dependent perturbations on an autonomous Hamiltonian system with an equilibrium of center type is considered. It is assumed that the perturbations decay at infinity in time and vanish at the equilibrium. In this case the stability and the long-term behaviour of trajectories depend on nonlinear and non-autonomous terms of equations. The paper investigates bifurcations associated with a change of Lyapunov stability of the equilibrium and the emergence of new attracting or repelling states in the perturbed non-autonomous system. The dependence of bifurcations on the structure of perturbations is discussed.
Improving small animal cone beam CT resolution by mitigating x-ray focal spot induced blurring via deconvolution
Authors: Hu Xiaoyu , Zhong Yuncheng , Huang Yanqi , Shen Chenyang , Jia Xun 
Published: April 2022

Abstract

Objective. Modern preclinical small animal radiation platforms utilize cone beam computerized tomography (CBCT) for image guidance and experiment planning purposes. The resolution of CBCT images is of particular importance for visualizing fine animal anatomical structures. One major cause of spatial resolution reduction is the finite size of the x-ray focal spot. In this work, we proposed a simple method to measure x-ray focal spot intensity map and a CBCT image domain deblurring model to mitigate the effect of focal spot-induced image blurring. Approach. We measured a projection image of a tungsten ball bearing using the flat panel detector of the CBCT platform. We built a forward blurring model of the projection image and derived the spot intensity map by deconvolving the measured projection image. Based on the measured spot intensity map, we derived a CBCT image domain blurring model for images reconstructed by the filtered backprojection algorithm. Based on this model, we computed image domain blurring kernel and improved the CBCT image resolution by deconvolving the CBCT image. Main results. We successfully measured the x-ray focal spot intensity map. The spot size characterized by full width at half maximum was ∼0.75 × 0.55 mm2 at 40 kVp. We computed image domain convolution kernels caused by the x-ray focal spot. A simulation study on noiseless projections was performed to evaluate the spatial resolution improvement exclusively by the focal spot kernel, and the modulation transfer function (MTF) at 50% was increased from 1.40 to 1.65 mm−1 for in-plane images and 1.05–1.32 mm−1 for cross-plane images. Experimental studies on a CT insert phantom and a plastinated mouse phantom demonstrated improved spatial resolution after image domain deconvolution, as indicated by visually improved resolution of fine structures. MTF at 50% was improved from 1.00 to 1.12 mm−1 for in-plane direction and from 0.72 to 0.84 mm−1 for cross-plane direction. Significance. The proposed method to mitigate blurring caused by finite x-ray spot size and improve CBCT image resolution is simple and effective.
Real-time liver tumor localization via a single x-ray projection using deep graph neural network-assisted biomechanical modeling
Authors: Shao Hua-Chieh , Wang Jing , Bai Ti , Chun Jaehee , Park Justin C , Jiang Steve , Zhang You 
Published: April 2022

Abstract

Objective. Real-time imaging is highly desirable in image-guided radiotherapy, as it provides instantaneous knowledge of patients’ anatomy and motion during treatments and enables online treatment adaptation to achieve the highest tumor targeting accuracy. Due to extremely limited acquisition time, only one or few x-ray projections can be acquired for real-time imaging, which poses a substantial challenge to localize the tumor from the scarce projections. For liver radiotherapy, such a challenge is further exacerbated by the diminished contrast between the tumor and the surrounding normal liver tissues. Here, we propose a framework combining graph neural network-based deep learning and biomechanical modeling to track liver tumor in real-time from a single onboard x-ray projection. Approach. Liver tumor tracking is achieved in two steps. First, a deep learning network is developed to predict the liver surface deformation using image features learned from the x-ray projection. Second, the intra-liver deformation is estimated through biomechanical modeling, using the liver surface deformation as the boundary condition to solve tumor motion by finite element analysis. The accuracy of the proposed framework was evaluated using a dataset of 10 patients with liver cancer. Main results. The results show accurate liver surface registration from the graph neural network-based deep learning model, which translates into accurate, fiducial-less liver tumor localization after biomechanical modeling (<1.2 (±1.2) mm average localization error). Significance. The method demonstrates its potentiality towards intra-treatment and real-time 3D liver tumor monitoring and localization. It could be applied to facilitate 4D dose accumulation, multi-leaf collimator tracking and real-time plan adaptation. The method can be adapted to other anatomical sites as well.
Partially observable Szilárd engines
Authors: Still Susanne , Daimer Dorian 
Published: April 2022

Abstract
Almost a century ago, Leo Szilárd replaced Maxwell’s ‘demon’ by machinery. The resulting information engine concept laid the foundation for studying the physical nature of information. Szilárd reduced the demon’s role to mapping an observable onto a work extraction protocol, thereby creating and utilizing a meta-stable memory. While Szilárd demonstrated that this map can be implemented mechanistically, it was not chosen automatically by the demon, or ‘observer’, but rather given a priori. This choice implements the demon’s intelligence. In Szilárd’s original setup, the choice is trivial, but we show here that nontrivial data representations emerge for generalized, partially observable Szilárd engines. Partial observability is pervasive in real world systems with limited sensor types and information acquisition bandwidths. Generalized information engines may run work extraction at a higher temperature than memory formation, which enables the combined treatment of heat- and information engines. To date, Szilárd’s (fully observable) information engine still serves as a canonical example. Implications of partial observability are under-explored, despite their ubiquitous nature. We provide here the first physical characterization of observer memories that result in minimal engine dissipation. We introduce a new canonical model, simple yet physically rich: a minor change to Szilárd’s engine—inserting the divider at an angle—results in partially observable engines. We demonstrate how the demon’s intelligence can be automated. For each angle and for each temperature ratio, an optimal memory is found algorithmically, enabling the engine to run with minimal dissipation. While naive coarse graining is sufficient for the special case of full observability, in general, minimally dissipative observers use probabilistic memories. We propose a simple model for an implementation of these memories, and construct a nontrivial physical codebook. We characterize the performance of engines with minimally dissipative memories, and compare their quality to that of engines using an optimized coarse graining of the observable.