bluuebunny/crossref_metadata_2025 huggingface dataset:
Over-the-scope clip as first-line treatment of peptic ulcer bleeding: a multicenter randomized controlled trial (TOP Study)
Authors: Soriani Paola , Biancheri Paolo , Bonura Giuliano Francesco , Gabbani Tommaso , Rodriguez de Santiago Enrique , Dioscoridi Lorenzo , Andrisani Gianluca , Luigiano Carmelo , Deiana Simona , Rainer Joachim , Del Buono Mariagrazia , Amendolara Rocco , Marino Massimiliano , Hassan Cesare , Repici Alessandro , Manno Mauro
Published: April 2024

Background First-line over-the-scope (OTS) clip treatment has shown higher efficacy than standard endoscopic therapy in acute nonvariceal upper gastrointestinal bleeding (NVUGIB) from different causes. We compared OTS clips with through-the-scope (TTS) clips as first-line mechanical treatment in the specific setting of peptic ulcer bleeding.

Methods We conducted an international, multicenter randomized controlled trial on consecutive patients with suspected NVUGIB. Patients with Forrest Ia–IIb gastroduodenal peptic ulcer were randomized 1:1 to OTS clip or TTS clip treatment. The primary outcome was the rate of 30-day rebleeding after successful initial hemostasis. Secondary outcomes included the rates of successful initial hemostasis and overall clinical success, defined as the composite of successful initial hemostasis and no evidence of 30-day rebleeding.

Results 251 patients were screened and 112 patients were randomized to OTS (n = 61) or TTS (n = 51) clip treatment. The 30-day rebleeding rates were 1.6% (1/61) and 3.9% (2/51) in patients treated with OTS clips and TTS clips, respectively (Kaplan–Meier log-rank, P = 0.46). Successful initial hemostasis rates were 98.4% (60/61) in the OTS clip group and 78.4% (40/51) in the TTS clip group (P = 0.001). Overall clinical success rates were 96.7% (59/61) with OTS clips and 74.5% (38/51) with TTS clips (P = 0.001).

Conclusions Low rates of 30-day rebleeding were observed after first-line endoscopic treatment of acute peptic ulcer bleeding with either OTS or TTS clips. However, OTS clips showed higher efficacy than TTS clips in achieving successful initial hemostasis and overall clinical success.
A Rare Case of Primary Sarcoma Arising Within Free Muscle Transfer
Authors: Jain Anchal , Rafique Bilal , Durrani Amer J. , Abood Ahid
Published: April 2024

Soft tissue sarcomas are one of the rarest forms of cancer. We describe a unique case of a 35-year-old patient who sustained an open lower limb fracture requiring an intramedullary nail and free latissimus dorsi (LD) muscle flap reconstruction. He had a complex postoperative course including osteomyelitis, a refracture, and chronic pain. Eleven years following the injury, he presented with pain and localized swelling around the flap. Histological analysis confirmed a rhabdomyosarcoma within the LD muscle and he underwent a transfemoral amputation. He is now in remission and walks on a prosthesis pain-free.
Bryophyllum pinnatum Inhibits Oxytocin and Vasopressin Signaling in Myometrial Cells
Authors: Zurfluh Leonie , Duvaud Lauriane , Inci Nejla , Potterat Olivier , Simões-Wüst Ana Paula , Mosbacher Johannes
Published: April 2024

The medicinal plant Bryophyllum pinnatum was previously shown to block oxytocin (OT)-induced signals in myometrial cells, consistent with its tocolytic effect observed in patients. OT activates not only OT receptors but also V1A receptors, two receptors with high receptor homology that are both expressed in the myometrium and play a crucial role in myometrial contraction signaling. We aimed to study the molecular pharmacology of B. pinnatum herbal preparations using specific receptor ligands, the human myometrial cell line hTERT-C3, and cell lines expressing recombinant human OT and V1A receptors.

We found that press juice from B. pinnatum (BPJ) inhibits both OT- and vasopressin (AVP)-induced intracellular calcium increases in hTERT-C3 myometrial cells. In additional assays performed with cells expressing recombinant receptors, BPJ also inhibited OT and V1A receptor-mediated signals with a similar potency (IC50 about 0.5 mg/mL). We further studied endogenous OT- and AVP-sensitive receptors in hTERT-C3 cells and found that OT and AVP stimulated those receptors with similar potency (EC50 of ~ 1 nM), suggesting expression of both receptor subtypes. This interpretation was corroborated by the antagonist potencies of atosiban and relcovaptan that we found. However, using qPCR, we almost exclusively found expression of OT receptors suggesting a pharmacological difference between recombinant OT receptors and native receptors expressed in hTERT-C3 cells.

In conclusion, we show that B. pinnatum inhibits both OT and AVP signaling, which may point beyond its tocolytic effects to other indications involving a disbalance in the vasopressinergic system.
Approaches to the Management of Synkinesis: A Scoping Review
Authors: Zubler Cédric , Punreddy Ankit , Mayorga-Young Danielle , Leckenby Jonathan , Grobbelaar Adriaan O.
Published: April 2024

Postparalysis facial synkinesis (PPFS) can develop in any facial palsy and is associated with significant functional and psychosocial consequences for affected patients. While the prevention of synkinesis especially after Bell's palsy has been well examined, much less evidence exists regarding the management of patients with already established synkinesis. Therefore, the purpose of this review is to summarize the available literature and to provide an overview of the current therapeutic options for facial palsy patients with established synkinesis. A systematic literature review was undertaken, following the Preferred Reporting Items of Systematic Reviews and Meta-analyses 2020 guidelines. MEDLINE via PubMed and Cochrane Library were searched using the following strategy: ([facial palsy] OR [facial paralysis] OR [facial paresis]) AND (synkinesis) AND ([management] OR [guidelines] OR [treatment]). The initial search yielded 201 articles of which 36 original papers and 2 meta-analyses met the criteria for inclusion. Overall, the included articles provided original outcome data on 1,408 patients. Articles were divided into the following treatment categories: chemodenervation (12 studies, 536 patients), facial therapy (5 studies, 206 patients), surgical (10 studies, 389 patients), and combination therapy (9 studies, 278 patients). Results are analyzed and discussed accordingly. Significant heterogeneity in study population and design, lack of control groups, differences in postoperative follow-up, as well as the use of a variety of subjective and objective assessment tools to quantify synkinesis prevent direct comparison between treatment modalities. To date, there is no consensus on how PPFS is best treated. The lack of comparative studies and standardized outcome reporting hinder our understanding of this complex condition. Until higher quality scientific evidence is available, it remains a challenge best approached in an interdisciplinary team. An individualized multimodal therapeutic concept consisting of facial therapy, chemodenervation, and surgery should be tailored to meet the specific needs of the patient.
Linking Patient Encounters across Primary and Ancillary Electronic Health Record Systems: A Comparison of Two Approaches
Authors: Davila Marcos A. , Sholle Evan T. , Fuld Xiaobo , Israel Mark L. , Cole Curtis L. , Campion Thomas R.
Published: April 2024

Background To achieve scientific goals, researchers often require integration of data from a primary electronic health record (EHR) system and one or more ancillary EHR systems used during the same patient care encounter. Although studies have demonstrated approaches for linking patient identity records across different EHR systems, little is known about linking patient encounter records across primary and ancillary EHR systems.

Objectives We compared a patients-first approach versus an encounters-first approach for linking patient encounter records across multiple EHR systems.

Methods We conducted a retrospective observational study of 348,904 patients with 533,283 encounters from 2010 to 2020 across our institution's primary EHR system and an ancillary EHR system used in perioperative settings. For the patients-first approach and the encounters-first approach, we measured the number of patient and encounter links created as well as runtime.

Results While the patients-first approach linked 43% of patients and 49% of encounters, the encounters-first approach linked 98% of patients and 100% of encounters. The encounters-first approach was 20 times faster than the patients-first approach for linking patients and 33% slower for linking encounters.

Conclusion Findings suggest that common patient and encounter identifiers shared among EHR systems via automated interfaces may be clinically useful but not “research-ready” and thus require an encounters-first linkage approach to enable secondary use for scientific purposes. Based on our search, this study is among the first to demonstrate approaches for linking patient encounters across multiple EHR systems. Enterprise data warehouse for research efforts elsewhere may benefit from an encounters-first approach.
The reduction of effective feedback reception due to negative emotions in appeals
Authors: Zhang Peide , Peng Binbin , Mi Zhifu , Lin Zhongguo , Du Huibin , Cheng Lu , Zhou Xiafei , Cao Guozhi
Published: April 2024

Citizens’ daily appeals are generally accompanied by negative sentiment, yet little is known about the impact of negative emotions on official response behaviors in a closed online environment. This study analyzed over 2.6 million environmental appeals and their handling records from China’s closed complaint platform to explore how individual negative emotions affect department response behaviors. The results showed that negative emotions could cause departments to respond more rapidly and decrease the likelihood of the citizens receiving department assistance. Whether the appeal can be handled efficiently also depends on the oversight of the department and the respondent’s implementation. Negative emotion towards the department is more likely to lead to a failed handling of the appeal. In addition, when citizens face serious hazards, such as health risks, negative emotions are understandable. Negative emotional appeals concerning health risks receive more time and effective intervention by departments. This paper sheds light on the role of negative emotions in shaping feedback and provides suggestions for improving individual appeal expression and departmental response behavior.
A bibliometric analysis of knowledge mapping in Chinese education digitalization research from 2012 to 2022
Authors: Shi Rui , Wan XiuLan
Published: April 2024

The digital transformation of education should be continuously promoted to guarantee its sustainable development. Extensive research has been conducted in this field but has not comprehensively addressed Chinese education digitalization. To fill this research gap, discover the gaps between Chinese and international research on the digitization of education and provide well-founded, innovative ideas for future research, we perform a bibliometric analysis of knowledge mapping in Chinese education digitalization. WOS and CNKI databases were used to gather literature on Chinese education digitalization research from 2012 to 2022. CiteSpace was used to draw a knowledge map of Chinese education digitalization research through co-occurrence analysis of core authors, issuing institutions and regions and cluster analysis and burst terms analysis of keywords, combined with intensive manual studying of the literature. The results show the research status and hot spots of Chinese education digitalization research are divided into four dimensions: studies of lifelong education research in digital open universities and the online teaching transformation in higher education; studies of digital educational publications, the development and application of digital learning resources in vocational colleges and universities, and the equity of basic education resources in the digital context; studies on artificial intelligence technology empowering the digital transformation of education in China; and studies of digital integration of production and teaching in rural revitalization and improvement of digital literacy of university students and faculty. Future digital education research trends in China are likely to focus on the normalization of online education; the development of online education resources in the context of new infrastructure; “new technology plus education”; the impact of digital games on education; a more diversified digital divide in education; and digital rights, digital ethics, digital maturity and the Global Digital Education Development Index.
Spiderwebs in the physics classroom
Authors: Shapiro Maura
Published: April 2024

Students make rubber band spiderweb replicas to probe mechanical properties.
A feature extraction method of rub-impact based on adaptive stochastic resonance and Hjorth parameter
Authors: Yu Mingyue , Cong Haonan , Zhang Yi , Xi Jianhui , Li Zhaohua
Published: April 2024

The characteristic frequency of a rub-impact fault is usually very complex and may contain higher harmonics and subharmonics. Due to the uncertainty of harmonic components and the complexity of signal-to-noise ratio (SNR) operation, the general scale transformation stochastic resonance (GSTSR) has certain limitations in the identification of rub-impact faults. To solve this problem, the paper starts with complexity and proposes a rub-impact fault identification method combining a swarm intelligence optimized algorithm (SIOA) with Hjorth parameters and GSTSR. The complexity of vibration signals will change greatly before and after rub-impact faults. The complexity parameter in Hjorth parameters can effectively embody the complexity of signals and is invulnerable to noise interference. Therefore, the complexity parameter in the Hjorth parameters is taken as the objective function of SIOA and combined with GSTSR. Vibration signals from cases are taken as input to adaptive stochastic resonant (ASR) systems, and the system parameters are adaptively and synchronously adjusted to realize the maximal resonant effect. Finally, the spectrum analysis of signals obtained from ASR is used to extract failure features and recognize faults in the rotor–stator rub-impact. The proposed method is verified by comparing it with other schemes under different SIOAs and different operating conditions. The result of the comparison shows that the complexity parameter of the Hjorth parameters can be taken as the objective function of SIOA to accurately identify the rub-impact fault. Meanwhile, the proposed method, compared with the method of taking SNR as an objective function, has a better effect on reducing time costs and strengthening fault characteristics.
Wavelength-tuned transformation between photonic skyrmion and meron spin textures
Authors: Lin Min , Liu Qing , Duan Huigao , Du Luping , Yuan Xiaocong
Published: April 2024

Topological spin textures, among which skyrmions and merons are typical examples, have with their swirling vectorial structures triggered enormous interest in physical systems including elementary particles and magnetic materials. Manipulating their symmetry and topology is important for understanding the mechanisms that underlie their topological phase transformation as well as offering tunable degrees of freedom to encode information, which has already been demonstrated in magnetic materials. Recently, the photonic counterparts of skyrmions and merons were constructed in a 2D wave system with deep-subwavelength features promising for optical sensing, imaging, and information decoding. However, their experimental realization relied on stringent excitation conditions that only support a single spin texture type on a specific structure. Here, we demonstrate for the first time the transformation between photonic skyrmion and meron spin lattices on the same metallic meta-surface having a well-designed structural period. We show experimentally the wavelength-tuned symmetry transformation of the photonic spin lattices, which are also found to be robust against disorder in the structure to a certain degree. This work provides new insights into controlling the electromagnetic field symmetry and topology, as well as in developing applications in spin optics and topological photonics.
Representations of the affine ageing algebra agê(1)
Authors: Li Huaimin , Wang Qing
Published: April 2024

In this paper, we investigate the affine ageing algebra agê(1), which is a central extension of the loop algebra of the one-spatial ageing algebra age(1). Certain Verma-type modules including Verma modules and imaginary Verma modules of agê(1) are studied. Particularly, the simplicity of these modules are characterized and their irreducible quotient modules are determined. We also study the restricted modules of agê(1) which are also the modules of the affine vertex algebra arising from the one-spatial ageing algebra age(1). We present certain constructions of simple restricted agê(1)-modules and an explicit such example of simple restricted module via the Whittaker module of agê(1) is given.
An adaptive fully convolutional network for bearing fault diagnosis under noisy environments
Authors: Zhang Xinliang , Liu Guanlin , Zhou Yitian , Jia Lijie
Published: April 2024

Intelligent diagnostic algorithms based on convolutional neural networks (CNNs) have shown great potential in diagnosing various conditions. However, accurately and robustly diagnosing faults in noisy situations remains challenging. This study presents an adaptive fully convolutional network (AFCN) for identifying bearing defects in noisy environments. First, we use a novel large kernel convolution method for high-frequency noise reduction and wide-area temporal feature extraction. By utilizing a sequence of stacked residual adaptive convolution blocks, the AFCN achieves a selective emphasis on significant features and adaptive adjustment of feature weights at various convolution scales. The experimental results have shown that the AFCN achieves a diagnostic accuracy of over 90% for the faults in the CWRU dataset under the −8 dB noise and over 77% for the PU dataset in the case of −6 dB noise. The comparison results with five advanced baseline models have demonstrated the superiority of the AFCN in feature extraction, noise immunity, and robustness to the noise environment. The AFCN provides a better adaption to noise interference than conventional CNNs and other advanced adaptive networks.
Metallic barrier layer for Ag2S1−xSex inorganic ductile thermoelectric materials
Authors: Peng Liming , Xing Tong , Qiu Pengfei , Liao Jincheng , Gu Ming , Zhu Chenxi , Shi Xun
Published: April 2024

Metallic barrier layer is a key component in thermoelectric (TE) devices, but it is rarely investigated for the recently discovered inorganic ductile TE materials. In this work, we demonstrate that tungsten (W) is the excellent metallic barrier layer for Ag2S1−xSex ductile thermoelectric materials. The phase composition, microstructure, adhesive strength, and interfacial contact resistivity (ρC) of the W/Ag2S1−xSex joint have been systematically investigated. The sputtered W film has high adhesive strength and little interdiffusion/reaction with Ag2S1−xSex. The ρC decreases with increasing the Se content, which can be understood by the Thermionic-field Emission model. This work would guide the development of high-performance flexible TE devices based on ductile TE materials.
Large-amplitude density waves produced in ozone-mixed gas by ultraviolet laser irradiation
Authors: Michine Yurina , More Richard M. , Yoneda Hitoki
Published: April 2024

A remarkable large-amplitude density modulation has been observed in ozone-mixed oxygen gas at atmospheric density and temperature conditions following irradiation with a nanosecond pulse of ultraviolet laser radiation. This paper outlines the experimental findings and describes a hydrodynamic simulation that reproduces several quantitative aspects of this phenomenon. It is important to note that these density waves are not simple sound waves; instead, they are combined with another type of density modulation wave. These density modulation wave profiles are expected to have applications for new optical components using a gas medium.
An invariance constrained deep learning network for partial differential equation discovery
Authors: Chen Chao , Li Hui , Jin Xiaowei
Published: April 2024

The discovery of partial differential equations (PDEs) from datasets has attracted increased attention. However, the discovery of governing equations from sparse data with high noise is still very challenging due to the difficulty of derivatives computation and the disturbance of noise. Moreover, the selection principles for the candidate library to meet physical laws need to be further studied. The invariance is one of the fundamental laws for governing equations. In this study, we propose an invariance constrained deep learning network (ICNet) for the discovery of PDEs. Considering that temporal and spatial translation invariance (Galilean invariance) is a fundamental property of physical laws, we filter the candidates that cannot meet the requirement of the Galilean transformations. Subsequently, we embedded the fixed and possible terms into the loss function of neural network, significantly countering the effect of sparse data with high noise. Then, by filtering out redundant terms without fixing learnable parameters during the training process, the governing equations discovered by the ICNet method can effectively approximate the real governing equations. We select the one-dimensional (1D) Kuramoto–Sivashinsky equation, the two-dimensional (2D) Burgers equation, the equation of two-dimensional channel flow over an obstacle, and the equation of three-dimensional (3D) intracranial aneurysm as examples to verify the superiority of the ICNet for fluid mechanics. Furthermore, we extend similar invariance methods to the discovery of wave equation (Lorentz Invariance) and verify it through single and coupled Klein–Gordon equation. The results show that the ICNet method with physical constraints exhibits excellent performance in governing equations discovery from sparse and noisy data.
Toward neuromorphic computing using longitudinal pulses in a fluid near phase transition
Authors: Mussel Matan , Marcucci Giulia
Published: April 2024

Longitudinal waves propagate information about the stimulus in multiple dimensions, including the medium density and pressure. Pulses that reversibly cross a phase transition have a nonlinear response that resembles properties of neuronal signaling. This multidimensionality suggests that longitudinal pulses may be harnessed for in-materio computation, mimicking biological or artificial neural algorithms. To explore a feedforward physical neural network using longitudinal pulses, we demonstrate the implementation of (1) a complete set of logic gates, (2) classification of data, and (3) regression of a mathematical function. Our results illustrate the potential of harnessing nonlinear longitudinal waves—common in a plethora of materials—for the purpose of computation.
Assessing the accuracy of TD-DFT excited-state geometries through optimal tuning with GW energy levels
Authors: Knysh Iryna , Raimbault Denez , Duchemin Ivan , Blase Xavier , Jacquemin Denis
Published: April 2024

We study the accuracy of excited state (ES) geometries using optimally tuned LC-PBE functionals with tuning based on GW quasiparticle energies. We compare the results obtained with the PBE, PBE0, non-tuned, and tuned LC-PBE functionals with available high-level CC reference values as well as experimental data. First, we compare ES geometrical parameters obtained for three different types of systems: molecules composed of a few atoms, 4-(dimethylamino)benzonitrile (DMABN), and conjugated dyes. To this end, we used wave-function results as benchmarks. Next, we evaluate the accuracy of the theoretically simulated spectra as compared to the experimental ones for five large dyes. Our results show that, besides small compact molecules for which tuning LC-PBE does not allow obtaining geometries more accurate than those computed with standard functionals, tuned range-separated functionals are clearly to be favored, not only for ES geometries but also for 0–0 energies, band shapes, and intensities for absorption and emission spectra. In particular, the results indicate that GW-tuned LC-PBE functionals provide improved matching with experimental spectra as compared to conventionally tuned functionals. It is an open question whether TD-DFT with GW-tuned functionals can qualitatively mimic the actual many-body Bethe–Salpeter (BSE/GW) formalism for which analytic ionic gradients remain to be developed.
Exploring the interplay of excitatory and inhibitory interactions in the Kuramoto model on circle topologies
Authors: Díaz-Guilera Albert , Marinelli Dimitri , Pérez-Vicente Conrad J.
Published: April 2024

In the field of collective dynamics, the Kuramoto model serves as a benchmark for the investigation of synchronization phenomena. While mean-field approaches and complex networks have been widely studied, the simple topology of a circle is still relatively unexplored, especially in the context of excitatory and inhibitory interactions. In this work, we focus on the dynamics of the Kuramoto model on a circle with positive and negative connections paying attention to the existence of new attractors different from the synchronized state. Using analytical and computational methods, we find that even for identical oscillators, the introduction of inhibitory interactions modifies the structure of the attractors of the system. Our results extend the current understanding of synchronization in simple topologies and open new avenues for the study of collective dynamics in physical systems.
Uncovering the dual role of dimensionless radius in buckling of spherical shells with random geometric imperfections
Authors: Baizhikova Zheren , Ballarini Roberto , Le Jia-Liang
Published: April 2024

Localized deformation and randomly shaped imperfections are salient features of buckling-type instabilities in thin-walled load-bearing structures. However, it is generally agreed that their complex interactions in response to mechanical loading are not yet sufficiently understood, as evidenced by buckling-induced catastrophic failures which continue to today. This study investigates how the intimate coupling between localization mechanisms and geometric imperfections combine to determine the statistics of the pressure required to buckle (the illustrative example of) a hemispherical shell. The geometric imperfections, in the form of a surface, are defined by a random field generated over the nominally hemispherical shell geometry, and the probability distribution of the buckling pressure is computed via stochastic finite element analysis. Monte-Carlo simulations are performed for a wide range of the shell’s radius to thickness ratio, as well as the correlation length of the spatial distribution of the imperfection. The results show that over this range, the buckling pressure is captured by the Weibull distribution. In addition, the analyses of the deformation patterns observed during the simulations provide insights into the effects of certain characteristic lengths on the local buckling that triggers global instability. In light of the simulation results, a probabilistic model is developed for the statistics of the buckling load that reveals how the dimensionless radius plays a dual role which remained hidden in previous deterministic analyses. The implications of the present model for reliability-based design of shell structures are discussed.
Design of optical telescopes for laser field wavefront reconstruction in gravitational-wave detectors
Authors: Allocca A , Genin E , Mantovani M , Chiummo A
Published: April 2024

Pick-off beams in Interferometric Gravitational Wave Detectors are often used to derive information on the field circulating in the interferometer. In order to retrieve the wavefront of the field at some chosen location, an optical system has to be deployed so to image the desired field characteristics to an optical bench and ultimately to suitable sensors. In this paper, we detail the requirements in terms of Gouy Phase and ABCD matrix for such an optical system to provide the correct information. We show also that by designing the optical system with adequate Gouy Phase evolution, the same kind of transformation holds true not only for the fundamental Gaussian mode, but also for both even and odd Higher Order Modes (HOMs) of the main interferometer beam. This is important because these HOMs are excited by the aberrations of the optical elements in the interferometer, and carry the information one is interested to. Simulations with two tools (Finesse and Zemax OpticsStudio®) are provided to confirm the analytical results obtained using Gaussian modes expansion of a generic field.
Symmetry and instability of marginally outer trapped surfaces
Authors: Booth Ivan , Cox Graham , Margalef-Bentabol Juan
Published: April 2024

We consider an initial data set having a continuous symmetry and a marginally outer trapped surface (MOTS) that is not preserved by this symmetry. We show that such a MOTS is unstable except in an exceptional case. In non-rotating cases we provide a Courant-type lower bound on the number of unstable eigenvalues. These results are then used to prove the instability of a large class of exotic MOTSs that were recently observed in the Schwarzschild spacetime. We also discuss the implications for the apparent horizon in data sets with translational symmetry.
Faster than a speeding bullet—the 2023 Physics Nobel Prize
Authors: Vrakking Marc
Published: April 2024

Attosecond physics is a novel research field that pursues a better understanding of electron dynamics in atoms, molecules and condensed matter by means of pump-probe experiments where the motion of electrons are tracked with attosecond (1 as = 10−18 s) time resolution. The 2023 Physics Nobel Prize was awarded to three experimental pioneers of the field, who developed the key methods to generate and characterize attosecond pulses.
Remote sensing of high energy particle currents (HEC): towards HEC radiography
Authors: Zygmanski Piotr , Rajapakse Arith , Outwater Coral , Sajo Erno , Brivio Davide
Published: April 2024

High-energy charged particle current (HEC) originating in or passing through an object creates mirror currents in a system of electrodes surrounding it. The electrodes are not in an electrically conductive contact with the object; they can be placed at a distance from its surface. We employ this effect to probe the object by measuring HEC-radiographic signal for a megavoltage x-ray scanning beam and for a broad static beam. Unlike in standard radiography, where an external bank of detectors measures the emerging radiation from the object, the principle of the proposed HEC radiography relies on remotely sensing the current distribution inside the object. Thus, HEC radiography is capable of probing objects that absorb all or most of the primary incident beam and where transmitted radiation cannot be used for image formation or reconstruction. Potential applications of this technology include non-destructive imaging of radio-opaque objects andin-vivomonitoring of charged particle ranges or dose distribution during cancer radiotherapy.
Plasma emission spectroscopy and optical properties of reactive-sputtered silicon oxynitride films
Authors: Rodríguez-López R , Abundiz-Cisneros N , Sanginés R , Águila-Muñoz J , Machorro-Mejía R
Published: April 2024

Silicon oxynitride (SiO
x
N
y
) thin films were synthesized via reactive direct current magnetron sputtering under different reactive gas mass flow ratios (O2:N2) and discharge powers. The process was monitored by optical emission spectroscopy (OES), while spectroscopic ellipsometry was used to characterize the optical properties of the thin films and deposition rates. In this work, the plasma generated under different deposition parameters is analyzed by monitoring the emission lines of different species (Si I, Ar I, O2, and N2) and these results are then correlated with the corresponding target poisoning process and the optical properties of the grown thin films. According to the spectral analysis, the emission lines proved to be sensitive to the synthesis process as it was possible to differentiate deposition variations when other parameters remained unchanged. Furthermore, similar plasma conditions determined via the emission of different species were found to produce consistent thin film optical properties and vice versa. OES showed to be an effective method of monitoring and controlling the deposition of SiO
x
N
y
thin films with specific compositions.
Light-assisted thermochemical reduction of CuFe2O4 within a photo-thermogravimetric analyser for solar fuel production
Authors: Gai Zhongrui , Tang Sanli , Yang Tianlong , Zhang Jinrui , Rao Qiong , Li Yang , Li Peng , Pan Ying , Jin Hongguang
Published: April 2024

The solar thermochemical cycle has emerged as a promising clean energy technology that enables the splitting of water for solar fuel production. However, conventional two-step thermochemical cycles using single-metal oxides require high operating temperatures above 1000 °C, especially for the reduction step. Typical solar thermal systems struggle to meet such high temperature requirements, making it vital to reduce the operating temperature. To find a solution enabling lower temperature requirements, we propose a photo-thermochemical reduction (PTR) strategy, which employs light illumination as assistance, combining both thermally induced and photo-induced effects for more generation of oxygen vacancies (VOs), within the oxygen carrier copper ferrite (CuFe2O4). Experimental studies were performed in a specially-designed photo-thermogravimetric analyser (photo-TGA) that directly measures the weight change of solid reactants under direct light illumination. The results indicate that the PTR achieves a decrease of nearly 40 °C in temperature requirements, giving a higher oxygen release of 21% compared to that driven by pure thermal heating at 800 °C. We also measured an increase of 0.09 in the non-stoichiometry parameter δ in the photo-TGA. Additionally, we observed that oxygen release increases distinctly with the light intensity of incident illumination. From the viewpoint of spectral ranges, ultraviolet and visible light illumination give the primary boost to the generation of photo-induced VOs. These results demonstrate the effective assistance of concentrated solar energy to enhance the two-step thermochemical cycle for solar fuel production at lower temperatures.
Bearing fault diagnosis based on transfer learning with dual-flow manifold ResNet and improved CapsNet
Authors: Yao Linhu , Wang Hongwei , Tao Lei , Fang Zhiwen , Wang Haoran , Liu Yu , Wang Hongli
Published: April 2024

In intelligent fault diagnosis for rolling bearings, the variable operating conditions of rotating machinery lead to inconsistent distributions between training and testing data, inevitably decreasing fault diagnosis accuracy. To overcome this issue, we propose a bearing fault diagnosis method based on transfer learning with a dual-flow manifold residual network and improved capsule network (DMRCN). Firstly, we introduce a dual-flow manifold residual network structure consisting of continuous wide-kernel convolution, continuous narrow-kernel convolution, and manifold learning spatial information description blocks. This architecture is utilized to extract low-level features from the data. Then, we present a novel architecture of the capsule network with self-attention output. We incorporate a self-attention mechanism into the dynamic routing algorithm to transfer richer high-level features from the low-level capsule layer to the higher-level capsule layer. During training, we propose a loss function known as global-local distribution discrepancy loss to enhance the model’s generalization ability and accelerate model convergence. Finally, we validate the performance of DMRCN in cross-condition transfer fault diagnosis on both the Case Western Reserve University public dataset and a laboratory-built bearing experimental rig dataset. Experimental results demonstrate that DMRCN outperforms other commonly used deep transfer learning methods regarding fault diagnosis across different operating conditions.
Measurement method for large aperture angle incomplete spherical surface stitching based on confocal focusing
Authors: Wang Yun , Yang Zheng , Zhao Jiahao , Cui Jian , Qiu Lirong , Li Zhigang , Yang Shuai
Published: April 2024

In traditional stitching measurements, the central sub-aperture is usually used as the reference and is not suitable for incomplete spherical surfaces without central sub-aperture. The measurement of each sub-aperture requires manual readjusting the position and attitude of the measured component, resulting in low measurement accuracy and low measurement efficiency. In response to this issue, this study proposed a method based on confocal focusing for large aperture angle incomplete spherical surface stitching measurement. Automatically and accurately determine the position of the common focus through confocal focusing technology, the positioning accuracy of the measured component is improved. A sub-aperture stitching model was built, coordinate mapping rotation algorithm and overlapping area error compensation algorithm were applied to the surface shape of each sub-aperture, achieving stitching measurement of large aperture angle incomplete spherical surfaces. Finally, the confocal interference stitching measurement system was built to carry out stitching experiments of sphere and large aperture angle incomplete spherical surface. The stitching experimental results indicated that the method increases the measurement accuracy of PV by 2.2 times, increases the measurement accuracy of RMS by 2.3 times, and increases the measurement efficiency by 1.6 times. Therefore, this method provides a high-precision measurement method for detecting large aperture angle spherical surface shape.
Gas-insulated switch-gear mechanical fault detection based on acoustic feature analysis using a multi-state pre-trained neural network
Authors: Wang Zhihua , Zhang Zipeng , Shao Yuying , Qian Kun , Liu Houguang , Hu Bin , Schuller Björn W
Published: April 2024

The acoustic-based approach is a prevalent way for non-contact fault diagnosis on gas-insulated switch-gear (GIS). GIS always works under different voltages causing great diversity in acoustic frequency. However, based on the frequency principle, neural networks always focus on a specific frequency, which challenges robust fault detection on GIS. This paper introduces a novel multi-stage training method to improve the robustness of fault detection on GIS. The proposed method consists of three components: a multi-channel based frequency regressor (MCBFR), an audio spectrogram transformer auto-encoder (AST-AE), and a feature interaction module (FIM). MCBFR and AST-AE are optimised to extract specific features from acoustics during the pre-training stage. The FIM fuses components extracted by MCBFR and AST when training the model that can indicate the final result. Also, we apply a multi-stage training strategy during the training stage to reduce the cost of potential model retraining. The efficacy of the proposed method was validated using experimental data from a real GIS, and it shows competitive performance in fault detection compared to existing methods.
Cathodoluminescence emission and electron energy loss absorption from a 2D transition metal dichalcogenide in van der Waals heterostructures
Authors: Bonnet Noémie , Baaboura Jassem , Castioni Florian , Woo Steffi Y , Ho Ching-Hwa , Watanabe Kenji , Taniguchi Takashi , Tizei Luiz H G , Coenen Toon
Published: April 2024

Nanoscale variations of optical properties in transition metal dichalcogenide (TMD) monolayers can be explored with cathodoluminescence (CL) and electron energy loss spectroscopy (EELS) using electron microscopes. To increase the CL emission intensity from TMD monolayers, the MoSe2 flakes are encapsulated in hexagonal boron nitride (hBN), creating van der Waals (VdW) heterostructures. Until now, the studies have been exclusively focused on scanning transmission electron microscopy (STEM-CL) or scanning electron microscopy (SEM-CL), separately. Here, we present results, using both techniques on the same sample, thereby exploring a large acceleration voltage range. We correlate the CL measurements with STEM-EELS measurements acquired with different energy dispersions, to access both the low-loss region at ultra-high spectral resolution, and the core-loss region. This provides information about the weight of the various absorption phenomena including the direct TMD absorption, the hBN interband transitions, the hBN bulk plasmon, and the core losses of the atoms present in the heterostructure. The S(T)EM-CL measurements from the TMD monolayer only show emission from the A exciton. Combining the STEM-EELS and S(T)EM-CL measurements, we can reconstruct different decay pathways leading to the A exciton CL emission. The comparison with SEM-CL shows that this is also a good technique for TMD heterostructure characterization, where the reduced demands on sample preparation are appealing. To demonstrate the capabilities of SEM-CL imaging, we also measured on a SiO2/Si substrate, quintessential in the sample preparation of two-dimensional materials, which is electron-opaque and can only be measured in SEM-CL. The CL-emitting defects of SiO2 make this substrate challenging to use, but we demonstrate that this background can be suppressed by using lower electron energy.
Temperature-dependent excitonic emission characteristics of highly crystallized carbon nitride nanosheets
Authors: Wang Yue , Zhang Guodi , Zhao Min , Qi Hongbo , Gao Tianqi , An Limin , Sun Jianhui
Published: April 2024

Highly-crystallized carbon nitride (HCCN) nanosheets exhibit significant potential for advancements in the field of photoelectric conversion. However, to fully exploit their potential, a thorough understanding of the fundamental excitonic photophysical processes is crucial. Here, the temperature-dependent excitonic photoluminescence (PL) of HCCN nanosheets and amorphous polymeric carbon nitride (PCN) is investigated using steady-state and time-resolved PL spectroscopy. The exciton binding energy of HCCN is determined to be 109.26 meV, lower than that of PCN (207.39 meV), which is attributed to the ordered stacking structure of HCCN with a weaker Coulomb interaction between electrons and holes. As the temperature increases, a noticeable reduction in PL lifetime is observed on both the HCCN and PCN, which is ascribed to the thermal activation of carrier trapping by the enhanced electron–phonon coupling effect. The thermal activation energy of HCCN is determined to be 102.9 meV, close to the value of PCN, due to their same band structures. Through wavelength-dependent PL dynamics analysis, we have identified the PL emission of HCCN as deriving from the transitions: σ*–LP, π*–π, and π*–LP, where the π*–LP transition dominants the emission because of the high excited state density of the LP state. These results demonstrate the impact of high-crystallinity on the excitonic emission of HCCN materials, thereby expanding their potential applications in the field of photoelectric conversion.
Well-posedness for the surface quasi-geostrophic front equation
Authors: Ai Albert , Avadanei Ovidiu-Neculai
Published: April 2024

We consider the well-posedness of the surface quasi-geostrophic (SQG) front equation. Hunter–Shu–Zhang (2021 Pure Appl. Anal.
3 403–72) established well-posedness under a small data condition as well as a convergence condition on an expansion of the equation’s nonlinearity. In the present article, we establish unconditional large data local well-posedness of the SQG front equation, while also improving the low regularity threshold for the initial data. In addition, we establish global well-posedness theory in the rough data regime by using the testing by wave packet approach of Ifrim–Tataru.
Image denoising and model-independent parameterization for IVIM MRI
Authors: Sample Caleb , Wu Jonn , Clark Haley
Published: April 2024

Objective. To improve intravoxel incoherent motion imaging (IVIM) magnetic resonance Imaging quality using a new image denoising technique and model-independent parameterization of the signal versus b-value curve. Approach. IVIM images were acquired for 13 head-and-neck patients prior to radiotherapy. Post-radiotherapy scans were also acquired for five of these patients. Images were denoised prior to parameter fitting using neural blind deconvolution, a method of solving the ill-posed mathematical problem of blind deconvolution using neural networks. The signal decay curve was then quantified in terms of several area under the curve (AUC) parameters. Improvements in image quality were assessed using blind image quality metrics, total variation (TV), and the correlations between parameter changes in parotid glands with radiotherapy dose levels. The validity of blur kernel predictions was assessed by the testing the method's ability to recover artificial ‘pseudokernels’. AUC parameters were compared with monoexponential, biexponential, and triexponential model parameters in terms of their correlations with dose, contrast-to-noise (CNR) around parotid glands, and relative importance via principal component analysis. Main results. Image denoising improved blind image quality metrics, smoothed the signal versus b-value curve, and strengthened correlations between IVIM parameters and dose levels. Image TV was reduced and parameter CNRs generally increased following denoising. AUC parameters were more correlated with dose and had higher relative importance than exponential model parameters. Significance. IVIM parameters have high variability in the literature and perfusion-related parameters are difficult to interpret. Describing the signal versus b-value curve with model-independent parameters like the AUC and preprocessing images with denoising techniques could potentially benefit IVIM image parameterization in terms of reproducibility and functional utility.
DFUSNN: zero-shot dual-domain fusion unsupervised neural network for parallel MRI reconstruction
Authors: Chen Shengyi , Duan Jizhong , Ren Xinmin , Wang Junfeng , Liu Yu
Published: April 2024

Objective. Recently, deep learning models have been used to reconstruct parallel magnetic resonance (MR) images from undersampled k-space data. However, most existing approaches depend on large databases of fully sampled MR data for training, which can be challenging or sometimes infeasible to acquire in certain scenarios. The goal is to develop an effective alternative for improved reconstruction quality that does not rely on external training datasets. Approach. We introduce a novel zero-shot dual-domain fusion unsupervised neural network (DFUSNN) for parallel MR imaging reconstruction without any external training datasets. We employ the Noise2Noise (N2N) network for the reconstruction in the k-space domain, integrate phase and coil sensitivity smoothness priors into the k-space N2N network, and use an early stopping criterion to prevent overfitting. Additionally, we propose a dual-domain fusion method based on Bayesian optimization to enhance reconstruction quality efficiently. Results. Simulation experiments conducted on three datasets with different undersampling patterns showed that the DFUSNN outperforms all other competing unsupervised methods and the one-shot Hankel-k-space generative model (HKGM). The DFUSNN also achieves comparable results to the supervised Deep-SLR method. Significance. The novel DFUSNN model offers a viable solution for reconstructing high-quality MR images without the need for external training datasets, thereby overcoming a major hurdle in scenarios where acquiring fully sampled MR data is difficult.