bluuebunny/crossref_metadata_2025_split huggingface dataset:
Determination of the partial and total pressures of the mixed gases in atomic vapor cells by optical absorption
Authors: Peng Jinpeng , Liu Zhanchao , Yin Kaifeng , Zou Sheng , Yuan Heng 
Published: May 2022

Abstract
We study the partial and total pressures of the mixed gases in a Rb vapor cell from its absorption spectrum under the influence of natural broadening, self-broadening, pressure broadening, the pressure shift, and Doppler broadening. A comprehensive model of the absorption coefficient on the Rb D2 line is developed, which takes into account the influence of multiple gas species. The importance of light intensity selection and frequency calibration to obtain accurate experimental results are discussed. Accurate abundances are deduced from the experimentally measured absorption spectra of vacuum cells and are used to optimize the abundance parameters in our model. We fit the experimentally measured absorption spectrum of a gas-filled cell to the optimized model and obtain a root mean square error better than 0.1%. The extracted partial pressures indicate that the mixture ratio agrees well with the designed value, while the total pressure has an increment of about 17% of its nominal value. We further estimate the amount of helium leakage in a cell to be 89.1 Torr for 6 months. Moreover, using a series of absorption spectra generated by our model as benchmarks, we evaluate the effectiveness of the commonly used single and double Lorentzian fitting models and give some suggestions for using the double Lorentzian model. This study provides a reference for designing the appropriate gas mixture for comagnetometer systems.
Generalization of deep recurrent optical flow estimation for particle-image velocimetry data
Authors: Lagemann Christian , Lagemann Kai , Mukherjee Sach , Schröder Wolfgang 
Published: May 2022

Abstract
Particle-image velocimetry (PIV) is one of the key techniques in modern experimental fluid mechanics to determine the velocity components of flow fields in a wide range of complex engineering problems. Current PIV processing tools are mainly handcrafted models based on cross-correlations computed across interrogation windows. Although widely used, these existing tools have a number of well-known shortcomings, including limited spatial output resolution and peak-locking biases. Recently, new approaches for PIV processing leveraging a novel neural network architecture for optical flow estimation called recurrent all-pairs field transforms (RAFT) have been developed. These have matched or exceeded the performance of classical, handcrafted models. While the RAFT-PIV method is a promising approach, it is important for the broader fluids community to more completely understand its empirical behavior and performance. To this end, in this study, we thoroughly investigate the performance of RAFT-PIV under varying image and lighting conditions. We consider applications spanning synthetic and experimental data, with a breadth and depth going far beyond currently available empirical results. The results for the wide variation of experiments shed new light on the capabilities of deep learning for PIV processing.
Collaborative detection and on-line monitoring of pipeline stress in oil and gas stations
Authors: Zhao Jianhua , Liao Kexi , Li Xiaoxiao , He Guoxi , Xia Feng , Zeng Qiang 
Published: May 2022

Abstract
The types of pipeline used in oil and gas stations is diverse, and it is difficult to comprehensively and accurately measure pipeline stress using a single detection method. Non-contact pipeline magnetic detection (NPMD), metal magnetic memory, ultrasonic stress measurement (USM) and ultrasonic thickness measurement (UTM)constitute a collaborative detection strategy for station pipelines. The pipeline magnetic abnormal evaluation parameter N is derived according to the sensor arrangement in NPMD devices. The magnetic field distribution based on different extraction heights is determined by the magnetic charge model and the experimental results, and a feature parameter E is constructed that can characterize the degree of stress concentration. The pipeline stress concentration points can be quickly determined in accordance with N and E. Reference stress values can be measured using USM and UTM. Monitoring is implemented at the stress concentration points, and the true stress values at the stress concentration points of the pipeline are established by combining the stress detection results. The collaborative detection method is applied to an oil and gas station, and two stress concentrations of 186.7 and 211.6 MPa are identified, respectively. The stress at the excavation pit is confirmed to be 196 MPa based on the monitoring data. Based on collaborative detection and on-line monitoring, fast and efficient collaborative detection and real-time mastering of station pipeline stress are achieved.
Pi-induced in-situ aggregation of sevelamer nanoparticles for vascular embolization
Authors: Bi Qiu-chen , Li Yan-shu , Luo Rong-guang , Chen Hong , Lv Yang-feng , Liu Zhi-Xing , Liang Qing-rong , Chen Li , Xu Bao-hua , Tang Qun 
Published: May 2022

Abstract
Decades have witnessed rapid progress of polymeric materials for vascular embolic or chemoembolic applications. Commercially available polymeric embolics range from gelatin foam to synthetic polymers such as poly(vinyl alcohol). Current systems under investigation include tunable, bioresorbable microspheres composed of chitosan or poly(ethylene glycol) derivatives, in situ gelling liquid embolics with improved safety profiles, and radiopaque embolics that are trackable in vivo. In this paper, we proposed a concept of ‘responsive embolization’. Sevelamer, clinically proved as an inorganic phosphate binder, was ground into nanoparticles. Sevelamer nanoparticle is highly mobile and capable of swelling and aggregating in the presence of endogenous inorganic phosphate, thereby effectively occluding blood flow in the vessel as it was administered as an embolic agent for interventional therapy. Moreover, citrated sevelamer nanoparticles delayed the aggregation, preferable to penetrate deeply into the capillary system. On the rabbit VX2 liver cancer model, both sevelamer particles aggregates occlude the tumor feeding artery, but backflow was found for the pristine one, thereby citrate passivation of sevelamer nanoparticles endows it have potential from ‘bench to bedside’ as a new type of vascular embolic.
Multi-label classification of reduced-lead ECGs using an interpretable deep convolutional neural network
Authors: Wickramasinghe Nima L , Athif Mohamed 
Published: May 2022

Abstract

Objective. We propose a model that can perform multi-label classification on 26 cardiac abnormalities from reduced lead Electrocardiograms (ECGs) and interpret the model. Approach. PhysioNet/computing in cardiology (CinC) challenge 2021 datasets are used to train the model. All recordings shorter than 20 s are preprocessed by normalizing, resampling, and zero-padding. The frequency domains of the recordings are obtained by applying fast Fourier transform. The time domain and frequency domain of the signals are fed into two separate deep convolutional neural networks. The outputs of these networks are then concatenated and passed through a fully connected layer that outputs the probabilities of 26 classes. Data imbalance is addressed by using a threshold of 0.13 to the sigmoid output. The 2-lead model is tested under noise contamination based on the quality of the signal and interpreted using SHapley Additive exPlanations (SHAP). Main results. The proposed method obtained a challenge score of 0.55, 0.51, 0.56, 0.55, and 0.56, ranking 2nd, 5th, 3rd, 3rd, and 3rd out of 39 officially ranked teams on 12-lead, 6-lead, 4-lead, 3-lead, and 2-lead hidden test datasets, respectively, in the PhysioNet/CinC challenge 2021. The model performs well under noise contamination with mean F1 scores of 0.53, 0.56 and 0.56 for the excellent, barely acceptable and unacceptable signals respectively. Analysis of the SHAP values of the 2-lead model verifies the performance of the model while providing insight into labeling inconsistencies and reasons for the poor performance of the model in some classes. Significance. We have proposed a model that can accurately identify 26 cardiac abnormalities using reduced lead ECGs that performs comparably with 12-lead ECGs and interpreted the model behavior. We demonstrate that the proposed model using only the limb leads performs with accuracy comparable to that using all 12 leads.
Quantum many-body scars and Hilbert space fragmentation: a review of exact results
Authors: Moudgalya Sanjay , Bernevig B Andrei , Regnault Nicolas 
Published: May 2022

Abstract
The discovery of quantum many-body scars (QMBS) both in Rydberg atom simulators and in the Affleck–Kennedy–Lieb–Tasaki spin-1 chain model, have shown that a weak violation of ergodicity can still lead to rich experimental and theoretical physics. In this review, we provide a pedagogical introduction to and an overview of the exact results on weak ergodicity breaking via QMBS in isolated quantum systems with the help of simple examples such as the fermionic Hubbard model. We also discuss various mechanisms and unifying formalisms that have been proposed to encompass the plethora of systems exhibiting QMBS. We cover examples of equally-spaced towers that lead to exact revivals for particular initial states, as well as isolated examples of QMBS. Finally, we review Hilbert space fragmentation, a related phenomenon where systems exhibit a richer variety of ergodic and non-ergodic behaviors, and discuss its connections to QMBS.
Manipulation of breather waves with split-dispersion cascaded fibers
Authors: Deng Zhixiang , Zhang Jin , Fan Dianyuan , Zhang Lifu 
Published: May 2022

Abstract
A stabilization scheme is proposed for the dynamics of breather waves induced by the coherent-seed modulation instability based on manipulation of phase-space trajectory. Theoretical and numerical analysis show that carefully dispersion- and nonlinearity-managed cascades of fiber configuration allows the system evolution to be stabilized around an elliptic center point, forming stable pulse trains with ultrahigh contrast efficiently. We also demonstrate that the scheme proposed works equally well for near-separatrix dynamics. Our results provide an alternative means to control the unsteady nonlinear waves by abruptly changing the waveguide properties.
Design and simulation of a gas sensitive junctionless FinFET based on conducting polymer as the gate material
Authors: Mehrdad Farzad , Ahangari Zahra 
Published: May 2022

Abstract
In this study, we demonstrate a multi-gas sensing device utilizing junctionless Fin-shaped Field Effect Transistor (FinFET) with conducting polymer as the gate material. The higher gas response is explained based on workfunction modulation of the conducting polymer gate, Poly(p-phenylene), upon gas molecule absorption. By definition, threshold voltage and off-state current variation before and after gas absorption are considered as two different measures for assessing the responsivity and sensitivity of the sensor. Basically, the main focus of this paper is designing a low power device, in which the change in the electrical characteristics of the device under gas exposure can be detected even in the absence of the gate bias. The high sensitivity of the proposed FinFET device as a gas sensor is mainly attributed to the large surface area of the 3D structure. We optimize the gas-sensing properties by investigating impact of critical physical and structural design parameters on the responsivity and selectivity of the sensor. In addition, statistical analysis is carried out to calculate coefficient of variation (CV) measure, for assessing the change in the responsivity of the gas sensor based on variation of main design parameters. Our results provide a route to design a low power CMOS compatible gas sensor that has fast response with high distinguishing selectivity and can be scaled down to nanoscale regime.
Fishing activities of Kinh people1 in the Southwest Sea: Ethnic knowledge approach
Authors: Thu H N , Loc D H 
Published: May 2022

Abstract
Ethnic knowledge is accumulated based on the practical experience of that ethnic group in a specific ecological and cultural environment and is transmitted from generation to generation. Ethnic knowledge is cognitive and affects behaviour in people’s lives. Based on previous studies on Vietnamese fishermen in the Southwest Sea, ethnic knowledge is essential in fishing activities. The fishermen have accumulated and thoroughly applied this knowledge system to forecast the weather and classify marine resources to exploit the fish populations in the best way. By primary data collected in the community for two years, from 2019 to 2020, the article describes this particular knowledge system to realise its importance in the fishing activities of Kinh fishermen.
The SLIQ Approach to Sustainable Tourism Development: Case Study of Hai Tac Islands
Authors: Nghia L H 
Published: May 2022

Abstract
Island tourism has always been one of the most attractive kinds of tourism globally. However, it is challenging to analyze tourist development on an island since it is a dynamic entity with unique characteristics. In recent years, island tourism development has faced some challenges, such as climate change, environmental degradation, economic downturns, cultural erosion, and diseases like the COVID-19 pandemic. Thus, sustainable development is key to ensuring the destination can keep up with demand. The author opted for the SLIQ concept as a new approach while seeking innovative ways to tackle old problems. The paper selected Hai Tac Islands, Vietnam, as a case study, using qualitative research and conducting in-depth interviews with six residents. The findings showed that local authorities should govern the island as living entity requiring a distinct way of thinking because island destinations are susceptible to economic perils and environmental issues. The paper also confirmed that sustainable economic growth, environmental protection, and human fairness should be the three goals of public policy when it comes to planning and managing inclusive tourism island development.
Accuracy assessment of land use land cover LULC 2020 (ESRI) data in Con Dao island, Ba Ria – Vung Tau province, Vietnam
Authors: Huan V D 
Published: May 2022

Abstract
Managing land use in an efficient way results in food security and economic development. Recently, the Environmental Systems Research Institute (ESRI) announced a new product, LULC 2020 (ESRI), that has been produced by the classification with Artificial Intelligence (AI) technique of satellite data at 10-meter resolution. This data has global coverage and is freely available on the internet, but the questions are how good the data is and how to apply it to local practice and land use system. This study aims to answer those questions by emphasizing the accuracy assessment of the LULC 2020 (ESRI) data. The systematic samples of 281 test sites and the Geographic Information Systems (GIS) analysis have been conducted by using the Confusion matrix method in comparison with the visualization of high-resolution data from Google Earth images and field survey data. Topographic information data such as Digital Elevation Model (DEM) and slope data have been integrated for achieving better data accuracy, with overall accuracy increasing from 79.72% (Overall Kappa Statistic 0.421) to 84.34% (Overall Kappa Statistic 0.589). The improved land use types are hilly non-forest, other agricultural, and flat unused types that are typical for the local land use classification system. The study provides a new data processing method to apply LULC 2020 (ESRI) for land use mapping in Con Dao island, Ba Ria - Vung Tau province in the East Sea of Vietnam.
Bilayer silk fibroin/sodium alginate scaffold promotes vascularization and advances inflammation stage in full-thickness wound
Authors: Shen Ying , Wang Xinyu , Wang Yiyu , Guo Xiaodong , Yu Keda , Dong Kuo , Guo Yajin , Cai Cuiling , Li Binbin 
Published: May 2022

Abstract
An ideal wound dressing for full-thickness wound regeneration should offer desirable biocompatibility, adequate mechanical properties, barrier function, and cellular regulation. Here, a bilayer scaffold resembling the hierarchical structure of human skin was developed using silk fibroin and sodium alginate. The upper membrane was prepared through casting and functioned as the epidermis, whereas the lower porous scaffold was prepared by freeze-drying and mimicked extracellular matrix structures. The membrane had nonporous structure, desirable mechanical properties, moderate hydrophilic surface, and suitable water vapor transmission rate, whereas the porous scaffold revealed 157.61 ± 41.67 µm pore size, 86.10 ± 3.60% porosity, and capability of stimulating fibroblast proliferation. The combination of the two structures reinforced the tensile strength by five-fold and provided protection from wound dehydration. A suitable degradation rate reduced potential administration frequency. Furthermore, an in vivo rabbit full-thickness wound healing test demonstrated that the bilayer scaffold facilitated wound closure, granulation tissue formation, re-epithelialization and skin component transition towards normal skin by providing a moist wound environment, advancing the inflammation stage, and stimulating angiogenesis. Collectively, as an off-the-shelf and cell-free wound dressing with single topical administration, the bilayer scaffold is a promising wound dressing for full-thickness wound regeneration.
On the dynamic wear behavior of misaligned journal bearing with profile modification under mixed lubrication
Authors: Guo Juan , Xiang Guo , Wang Jiaxu , Song Yankui , Cai Jianlin , Dai Haiming 
Published: May 2022

Abstract
In this paper, we introduce a method of one-side profile modification for the misaligned journal bearing to reduce the edge wear caused by the journal defection under the external load. To predict the bearing wear behavior, a dynamic wear model considering mixed lubrication based on friction fatigue mechanism is applied. The positive role of the one-side profile modification in mitigating the negative effects caused by journal misalignment is confirmed by numerical calculations. The optimal modification parameter setting is determined with the calculation results, and the dependence of the optimal modification parameters on the different operating conditions, including external force and shaft length, are explored. The results indicate that the reasonable design of one-sided profile modification can effectively increase the minimum film thickness at the edge of the bearing and reduce the rough contact, thereby improve the anti-wear performance of the misaligned journal bearing under mixed lubrication. The present study could provide an engineering approach for the anti-wear optimal design in misaligned journal bearing applications.
Plasma jet printing of metallic patterns in zero gravity
Authors: Gutierrez Daniel H , Doshi Pranay , Nordlund Dennis , Gandhiraman Ram P 
Published: May 2022

Abstract
Printing of metallic, semiconducting and other materials is a key step in printed and flexible electronics. Plasma jet printing is emerging as an alternative to inkjet, aerosol and other competing printing techniques since it is a single step process that does not require post-thermal annealing to obtain consolidated printed films with good adhesion. Here, we provide results for printing metallic films and patterns from flight tests with varying gravity from 0 to 2 G. The conductivity of the as-printed silver film without any post-sintering was 12% of the bulk value for silver. As expected, the absence of gravity has no adverse impact on the print quality since the ink content along with the plasma is forcefully ejected by the applied electric field towards the substrate, while the successful flight test itself attests to the robustness of the printer and the printing technique.
Electron transport tuning of graphene by helium ion irradiation
Authors: Nakaharai Shu , Iwasaki Takuya , Morita Yoshifumi , Moriyama Satoshi , Ogawa Shinichi 
Published: May 2022

Abstract
This article reviews charge carrier transport phenomena in single-layer graphene, in which crystalline defects are generated by helium-ion-beam irradiation using a helium-ion microscope. Crystalline defects work as electron scatterers, and the conductivity drastically decays as ion dose increases. Moreover, real-time conductivity monitoring during ion beam scans over the graphene surface is demonstrated. In cryogenic measurements under magnetic fields, defective graphene exhibits negative magnetoresistance, suggesting that strong localization occurred in this two-dimensional electron system, which survived even at room temperature. The localized state contributes to inducing a transport gap around the Dirac point, where the density of states is at its minimum, and it enables field-effect control of the carrier transport by tuning the carrier density. The fabrication and operation of field-effect transistors with defective graphene channels are demonstrated.
Explaining Public Organization Adaptation to Climate Change: Configurations of Macro- and Meso-Level Institutional Logics
Authors: Zhang Fengxiu , Welch Eric W 
Published: May 2022

AbstractClimate change can bring about large-scale irreversible physical impacts and systemic changes in the operating environment of public organizations. Research on preconditions for organizational adaptation to climate change has produced two parallel lines of inquiry, one focusing on macro-level norms, rules, and expectations and the other on meso-level culture, design, and structure within the organization. Drawing on the meta-theory of institutional logics, this study proposes a configurational approach to link institutionally aware top managers with the combination and reconciliation of macro- and meso-level logics. We identify government authority, professionalism, and market as macro-level institutional logics, and risk-based logic and capacity-based logic as critical meso-level institutional logics. Our theory proposes that (1) the macro- and meso-level institutional logics co-exist in systematic ways as to produce identifiable configurations, (2) the configurations are differentially associated with climate adaptation, and (3) the effects of each logic differ across the configurations. Using a 2019 national survey on approximately 1000 top managers in the largest U.S. transit agencies, we apply latent profile analysis to identify three distinct clusters: forerunner, complacent, and market-oriented. Only the forerunner cluster is adaptive to climate change, whereas the two others are maladaptive. Findings from the multigroup structural equation model also demonstrate varied effects of each institutional logic on adaptation across the clusters, confirming institutional work at play to reconcile and integrate co-existing and potential contradictory logics.