bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding condensation halo growth on superhydrophobic surfaces: Insights from a vapor diffusive model
Authors: Shang Yuhe , Li Dong , Liu Haozheng
Published: August 2024

Anti-icing technologies are vital across various sectors, from transportation to energy systems. In this study, we investigate the formation of condensation halos during the process of condensation–freezing on superhydrophobic surfaces. Experimental tests were conducted on metallic nanostructured superhydrophobic surfaces, where droplet icing was induced and observed under controlled conditions. The formation of condensation halos, characterized by the sudden appearance and subsequent vanishing of microdroplets around the freezing droplets, was captured and analyzed. A vapor diffusive model coupled with heterogeneous nucleation theory was developed to understand and quantify the growth of condensation halos. The model considers vapor diffusion around the icing droplet and the critical vapor pressure required for nucleation. Experimental observations and theoretical predictions demonstrated a strong dependence of condensation halo size on the icing droplet radius. The study sheds light on the mechanisms underlying condensation halo formation and provides insights into the intricate interplay between droplet size, surface properties, and environmental conditions in condensation–freezing phenomena, offering valuable perspectives for the development of effective anti-icing strategies.
Broadband and efficient terahertz helicity inversion by a reconfigurable reflective metasurface based on vanadium dioxide
Authors: Inokuma Akira , Takano Keisuke , Nakanishi Toshihiro , Miyamaru Fumiaki , Okimura Kunio , Sanada Atsushi , Nakata Yosuke
Published: August 2024

We experimentally demonstrate the broadband and highly efficient inversion of the rotation direction of the terahertz circular polarization achieved by a dynamic metasurface with vanadium dioxide (VO2). This metasurface converts linear polarization into circular polarization. The rotational direction of the output circular polarization can be reversed based on the VO2 phase transition. The VO2 state can be dynamically switched by injecting direct current into an on-chip circuit. To improve the terahertz-wave utilization efficiency, the metasurface is operated at an incident angle of 45°, thereby eliminating the beam splitter typically used to separate the outgoing wave from the incident wave at normal incidence. To achieve broadband operation, we employ a dispersion-cancelation strategy that cancels the dispersive phase responses between orthogonal linear polarizations. This strategy was previously developed for static metasurfaces; we have applied it to the design of dynamic metasurfaces. At a center frequency of 0.99 THz, the experimental evaluation demonstrated helicity switching with conversion efficiencies of 92% and 87% for the insulating and metallic states of VO2, respectively. Dispersion cancelation is simultaneously achieved for the insulating and metallic states of VO2, resulting in a relative bandwidth of 0.26, which is 3.2 times broader than that of a previously developed efficient dynamic metasurface.
Uncovering quantum characteristics of incipient evolutions at the photosynthetic oxygen evolving complex
Authors: Huo Pei-Ying , Jiang Wei-Zhou , Yang Rong-Yao , Zhang Xiu-Rong
Published: August 2024

Water oxidation of photosynthesis at the oxygen evolving complex (OEC) is driven by the polarization field induced by the photoelectric hole. By highlighting the role of the polarization field in reshaping the spin and orbit potentials, we reveal in this work the characteristics and underlying mechanism in the relatively simpler OEC evolutions within the states S0–S2 prior to the water oxidation. The characteristic shifts of the density of states (DOS) of the electron donor Mn atom are observed in the vicinity of the Fermi surface to occur with the spin flips of Mn atoms and the change in the Mn oxidation states during the electron transfer. Notably, the spin flips of Mn atoms point to the resulting spin configuration of the next states. It is found that the electron transfer tends to stabilize the catalyst OEC itself, whereas the proton transfer pushes the evolution forward by preparing a new electron donor, demonstrating the proton-coupled electron transfer. Meanwhile, it shows that the Mn–O bonds around the candidate Mn atom of the electron donor undergo characteristic changes in the bond lengths during the electron transfer. These concomitant phenomena uncovered in first-principle calculations characterize the essential equilibrium of the OEC between the state evolution and stability that forms the groundwork of the dynamic OEC cycles. In particular, the characteristic undulation of the DOS around the Fermi level occurring at the proton-coupled electron transfer can be used to reveal crucial processes in a wide range of realistic systems.
Theory of electrotuneable mechanical force of solid–liquid interfaces: A self-consistent treatment of short-range van der Waals forces and long-range electrostatic forces
Authors: Chen Hai-Na , Yang Le , Huang Jun , Song Wei-Li , Chen Hao-Sen
Published: August 2024

Elucidating the mechanical forces between two solid surfaces immersed in a communal liquid environment is crucial for understanding and controlling adhesion, friction, and electrochemistry in many technologies. Although traditional models can adequately describe long-range mechanical forces, they require substantial modifications in the nanometric region where electronic effects become important. A hybrid quantum–classical model is employed herein to investigate the separation-dependent disjoining pressure between two metal surfaces immersed in an electrolyte solution under potential control. We find that the pressure between surfaces transits from a long-range electrostatic interaction, attractive or repulsive depending on the charging conditions of surfaces, to a strong short-range van der Waals attraction and then an even strong Pauli repulsion due to the redistribution of electrons. The underlying mechanism of the transition, especially the attractive–repulsive one in the short-range region, is elucidated. This work contributes to the understanding of electrotunable friction and lubrication in a liquid environment.
Organic heterojunction memristors with enhanced tunable resistive states for artificial synapses
Authors: Li Wen , Zhou Jia , Xu Yechen , Tao Kui , Ling Haifeng , Shi Wei , Huang Wei , Yi Mingdong
Published: August 2024

Tunable and uniform evolution of conductance is the key performance metric for neuromorphic computing leveraging memristors. Nonetheless, the stochastic conductance update associated with limited material composition and uncontrollable filament distribution has restricted the tunability that can be customized for targeted synaptic properties. Here, we introduce organic heterojunction memristors utilizing the C60/P3HT bilayer, demonstrating analog switching characteristics with multilevel conductance states. We demonstrate that both conventional bipolar and unipolar voltages can achieve synaptic plasticity modulation for potentiation and depression, offering enhanced tunability. Through in situ Raman spectroscopy and impedance spectroscopy, we directly observe the dynamic alterations within the active layers during switching processes. The reversible migration of ions diminishes the barrier within the polymer layer, leading to highly uniform resistive switching behavior. The C60 layer functions as a confined transport medium, mitigating critical current variability issues. Moreover, we introduce a shunt resistor approach, furnishing analog memristors with selectively adjustable uniformity, enhanced linearity, and expanded dynamic conductance range, providing a general solution adaptable to various memristive hardware architectures.
Forced vibration of liquid-filled composite laminated shell container considering fluid–structure interaction by the scaled boundary finite element method
Authors: Liu Jun , Zhang Wen-Qiang , Ye Wen-Bin , Gan Lei , Qin Lei , Zang Quan-Sheng , Wang Hai-Bo
Published: August 2024

In this paper, the scaled boundary finite element method (SBFEM) is first applied to the forced vibration analysis of partially liquid-filled composite laminated shell structure considering fluid–structure interaction. In comparison with the finite element method, the SBFEM only requires discretization of the boundary of the solution domain, which can reduce the spatial dimension of the problem by one and provide the radial analytical expressions for the variables within the solution domain. The structure consists of a multi-layered fiber-reinforced composite laminated shell and incompressible, inviscid, and irrotational liquid. After separately describing the basic expressions for the fluid and composite laminated shell, which includes the transformation of three coordinate systems and the establishment of the constitutive equations for the shell, the governing equations for the fluid and shell structure using the scaled boundary finite element method and modified SBFEM based on scaling surface transformation are formulated, respectively. Meanwhile, the Newmark method and synchronous solution algorithm are employed for the fluid–structure interaction analysis. Subsequently, two validation cases are conducted to assess the accuracy and convergence of the model. Finally, two numerical examples are employed to perform a parameter analysis on the model, involving the response of the system to ground horizontal harmonic excitation and seismic load. The results indicate that the SBFEM, as a semi-analytical high-precision numerical method, can be effectively used to simulate fluid–structure interaction problem of partially liquid-filled laminated composite shell structures.
Modulating conductive filaments via thermally stable bilayer organic memristor
Authors: Zheng Yiming , Guo Xiangyu , Jiang Jiandong , Fu Yujun , Wang Qi , He Deyan
Published: August 2024

The basic unit of information in conductive bridge random access memory based on the redox mechanism of metal ions is physically stored in a conductive filament (CF). Therefore, the overall performance of the device is indissolubly related to the properties of such CFs, as unreliable performance often originates from unstable CFs behavior. However, accurately controlling the dissolution of CFs during device operation can be challenging due to their non-uniformity. This paper proposes a type of memristor based on a solid polymer electrolyte with a polyvinylpyrrolidone/polyvinyl alcohol composite layer structure. The properties of the composite layer are employed to regulate the number of CFs and the growth/fracture location, while the damage to the device by Joule heat is prevented. The device exhibits low operating voltage (0.5 V), stable switching conditions (2000 cycles), and a long holdup time (>3 × 104 s).
A parallelized environmental-sensing and multi-tasks model for intelligent marine structure control in ocean waves coupling deep reinforcement learning and computational fluid dynamics
Authors: Qin Hao , Liang Hongjian , Su Haowen , Wen Zhixuan
Published: August 2024

In addressing the active control challenges of marine structures in ocean waves, a coupling model is proposed combining computational fluid dynamics (CFD) and deep reinforcement learning (DRL). Following the Markov decision process (MDP), the proposed DRL-CFD model treats the wave fields and simplified marine structures as the environment and the agent, respectively. The CFD component utilizes the PIMPLE algorithm to solve the Navier–Stokes equations, in which the free surface is reconstructed using the volume of fluid method. The DRL component utilizes the Soft Actor-Critic algorithm to realize the MDP between marine structures and the wave fields. Three simulation cases with different control purposes are conducted to show the effectiveness of the DRL–CFD coupling model, including the active controls for wave energy absorption, attenuation, and structure heave compensation. Comparative analyses with passive (resistive) control are performed, demonstrating the advantages of the DRL–CFD coupling model. The results confirm that the proposed coupling model enables the marine structure to observe the wave environment and generate effective active control strategies for different purposes. This suggests that the model has the potential to address various active control challenges of marine structures in ocean waves, while being capable of environmental sensing and handling multiple tasks simultaneously.
A physical constraint-based machine learning model for shale oil production prediction
Authors: Wang Yuhan , Lei Zhengdong , Zhou Qiang , Liu Yishan , Xu Zhenhua , Wang Yanwei , Liu Pengcheng
Published: August 2024

Shale oil has become a crucial unconventional resource, bolstering energy supply security, and it is important to accurately predict shale oil production dynamics. However, traditional prediction methods are faced with the challenges of large data fluctuations and numerous interference factors, which make accurate prediction difficult. This paper introduces a deep learning approach, specifically a physical constraint-based convolutional neural network combined with long short-term memory and attention mechanism (CNN-LSTM-AM), to predict shale oil production dynamics. Initially, the correlation analysis method is used to analyze the correlation strengths of features with the prediction target, and the data that are most strongly correlated with the daily oil production are screened out and preprocessed. Key features are then extracted; that is, the CNN layer's output is fed into the LSTM layer, the output of which informs a fully connected layer for time-series production predictions. The model integrates an AM to concentrate on vital data aspects. In the “five-linear flow” formula, the imbibition is hard-coded into the shale oil production prediction model. Physical constraints are introduced into the model. Data driven and empirical formulas are used to introduce a loss function as a constraint condition in the training process of a machine learning model to improve the interpretability and predictive ability of the model. During the tuning phase, Bayesian optimization is used to fine-tune the model's hyperparameters. Shapley additive explanation and accumulated local effects analyses are used to further assess and quantify the significance of the essential parameters, thus optimizing the prediction effectiveness.
Scalable transfer printing approach to heterogeneous integration of InP lasers on silicon-on-insulator waveguide platform
Authors: Ghosh Samir , O'Callaghan James , Moynihan Owen , Huang Duanni , Frish Harel , Rong Haisheng , Thomas Kevin , Pelucchi Emanuele , Corbett Brian
Published: August 2024

InP-based edge-emitting O-band lasers are integrated onto silicon photonics circuit employing micro-transfer printing technology. Blocks of unpatterned InP gain material of typical size 1000 × 60 μ m2 are first transferred onto 400 nm thick silicon rib waveguides with the fabrication steps performed on the target wafer to realize the final lasers. As a result, the InP ridge waveguides are aligned with lithographic accuracy to the underlying Si waveguides resulting in an approach free from any misalignment stemming from the transfer printing process. The fabricated Distributed Bragg Reflector laser shows lasing around 100 mA current injection with minimum 1 mW of output power coupled to a single mode fiber. This integration method paves a reliable route toward scaling-up the integration of active devices such as lasers, modulators, and detectors on 300-mm diameter silicon wafers, which requires high-uniformity across the wafer.
Robust control of charged particles position in a homogeneous isotropic turbulence using an electric field
Authors: Motamedi Ehsan , Moosaie Amin , Rahmani Behrooz
Published: August 2024

This research investigates the position control of spherical charged particles suspended in a directly simulated homogeneous isotropic turbulence, which has the potential to improve the efficiency of the electrostatic precipitators (ESPs) in removing gaseous pollutants. To do this, the electric field used in ESPs is controlled by the sliding mode control method to steer the particles toward their desired positions. The particles are charged using the field charging method, which leads to electrical interactions between them. Employing the linked-list method reduces the computational cost related to these interaction forces. The dynamics of particles is simulated using the Maxey–Riley equation including the control force. Coupling the direct numerical simulation solver with the proposed control method and the linked-list scheme, along with solving the particle dynamics, complicates the problem from a control theory point of view. The robustness of the proposed model-free control method leads to overcoming disturbances and uncertainties in the simulation due to turbulence and repulsive electric forces. Hence, steering a large number of charged particles to places with more pollution concentration or increasing the duration of exposure of the particles to gaseous pollutants becomes possible. The findings of the present research are pertinent to improving the performance of air purification equipment.
Vortex-shedding modes of a pair of side-by-side thin pitching plates
Authors: Sarkar Sandip , De Arnab Kumar
Published: August 2024

We have conducted three-dimensional (3D) direct numerical simulations to analyze vortex-shedding modes past vertically arranged, side-by-side 3D pitching plates, considering cases where the plates are in the same, opposite, and different phases. The simulations are performed at a Reynolds number Re=1000, with a dimensionless pitching frequency St=1, and a maximum pitching angle θmax=15°. The vortex-shedding modes reveal horseshoe vortices transforming into distorted hairpin-like structures in the far wake for in-phase plates. Opposite phase plates exhibit helical distortion and core bifurcation, while different phase angles produce meridionally twisted, entangled hairpins. We observe a reverse von Kármán vortex street for in- and different-phase plates, while the opposite shows a reverse Kármán vortex street for the upper plate and a Kármán vortex street for the lower plate. The streakline visualizations reveal wake compression and spoke-like structures symmetrically emanating from the shear layer extremities around the plates' central region. We find leapfrog-like cross-stream vortex interaction when the plates are in phase. The line-time diagram reveals alternating patches of low-intensity cells, switching between negative and positive, alongside continuous bands of both positive and negative cells. Both plates produce similar thrust for the parameters examined in this study.
Australian medical practitioners: trends in demographics and regions of work 2013–2022
Authors: Cortie Colin H. , Garne David , Parker-Newlyn Lyndal , Ivers Rowena G. , Mullan Judy , Mansfield Kylie J. , Bonney Andrew
Published: August 2024

Objective This study aimed to examine changes in the demographics and regions of work of Australian doctors over a period of 9 years. Methods A retrospective study of Australian Health Practitioner Regulation Agency (AHPRA) registration data was performed. Data were sourced from the Health Workforce Dataset Online Data Tool which was derived from annual registration data from AHPRA for 2013–2022. The demographic factors analysed were gender, age, and origin of qualification. Regions of work were defined using the Modified Monash (MM) model. Results The number of registered doctors increased from 82,408 in 2013 to 111,908 in 2022 but mean hours worked per week decreased from 41 to 39 leading up to 2020. Trends in age and origin of qualification remained stable, but the proportion of female workers increased from 38.5% in 2013 to 44.5% in 2022. While female hours per week (~37) were consistent from 2013 to 2020, male hours per week decreased from 43 to 41. The number of registrations and total full-time equivalent (FTE) outcomes increased consistently in metropolitan (MM1) and rural (MM2–5) regions but did not increase for remote and very remote (MM6–7) regions. Conclusion The Australian medical workforce both grew and changed between 2013 and 2022. An overall decrease in mean hours worked appears to be driven by a decline in hours worked by male workers and the increased proportion of female workers. While increased gender parity and a decrease in hours worked per week were positive outcomes, a lack of growth in the medical workforce was noted in remote and very remote regions of Australia.
Consumer involvement in health service research: a cross-sectional survey of staff in an Australian public hospital and health service
Authors: Ryan Laura , Hattingh Laetitia , Carlini Joan , Weir Kelly A. , Shapiro Margaret , Baglot Noela , Cardona Magnolia , Tobiano Georgia , Muir Rachel , Roberts Shelley , Sargeant Sally , Wenke Rachel
Published: August 2024

Objective Consumer involvement is when patients (their families, friends, and caregivers) work with researchers on research projects. While health services are expected to support consumer–researcher collaborations, conducive environments still need to be developed, with limited research into how Australian health services support this practice. This study explores current consumer involvement in research activity and staff perceptions at an Australian tertiary hospital and health service. Methods Research-active employees at a health service were invited to participate in an online cross-sectional survey. It assessed experience with and confidence in involving consumers in research, the perceived value of consumer involvement, and considerations related to challenges, facilitators, and solutions to enhance consumer involvement in health service research. Results Among 83 respondents, including medical, nursing, and allied health professionals, 54 completed the survey. Approximately half had experience with involving consumers in research. Over 80% recognised that involving consumers enhanced research relevance. Identified barriers included challenges in finding (46.6%) and compensating (59.3%) consumers, as well as deficiencies in researcher skills, knowledge (32.2%), and time constraints (39%). Facilitators comprised access to experienced researchers and educational opportunities. Moreover, 87% advocated for increased support to involve consumers within health services, with the appointment of a designated consumer involvement officer deemed the most beneficial solution by 92.5% of respondents. Conclusions While individual barriers inhibit consumer involvement in research, more prominent institutional factors such as financial and technical support may determine successful and meaningful collaborations. As health services evolve towards co-design models in research, the outcomes of this study will guide initiatives aimed at enhancing consumer involvement in the research process within Australian health services.
Type I interferon signaling pathway enhances immune-checkpoint inhibition in KRAS mutant lung tumors
Authors: Fernández-García Fernando , Fernández-Rodríguez Ana , Fustero-Torre Coral , Piñeiro-Yáñez Elena , Wang Haiyun , Lechuga Carmen G. , Callejas Sergio , Álvarez Rebeca , López-García Alejandra , Esteban-Burgos Laura , Salmón Marina , San Román Marta , Guerra Carmen , Ambrogio Chiara , Drosten Matthias , Santamaría David , Al-Shahrour Fátima , Dopazo Ana , Barbacid Mariano , Musteanu Monica
Published: August 2024

Lung cancer is the leading cause of cancer mortality worldwide. KRAS oncogenes are responsible for at least a quarter of lung adenocarcinomas, the main subtype of lung cancer. After four decades of intense research, selective inhibitors of KRAS oncoproteins are finally reaching the clinic. Yet, their effect on overall survival is limited due to the rapid appearance of drug resistance, a likely consequence of the high intratumoral heterogeneity characteristic of these tumors. In this study, we have attempted to identify those functional alterations that result from KRAS oncoprotein expression during the earliest stages of tumor development. Such functional changes are likely to be maintained during the entire process of tumor progression regardless of additional co-occurring mutations. Single-cell RNA sequencing analysis of murine alveolar type 2 cells expressing a residentKrasoncogene revealed impairment of the type I interferon pathway, a feature maintained throughout tumor progression. This alteration was also present in advanced murine and human tumors harboring additional mutations in the p53 or LKB1 tumor suppressors. Restoration of type I interferon (IFN) signaling by IFN-β or constitutive active stimulator of interferon genes (STING) expression had a profound influence on the tumor microenvironment, switching them from immunologically “cold” to immunologically “hot” tumors. Therefore, enhancement of the type I IFN pathway predisposes KRAS mutant lung tumors to immunotherapy treatments, regardless of co-occurring mutations in p53 or LKB1.
Role making in translational contexts
Authors: Hohl Zürcher Franziska , Griebel Cornelia
Published: August 2024

This study examines the roles of intercept interpreters/translators (IITs) in covert communication surveillance.
Despite their increasing importance in global criminal investigations, their roles remain underexplored in academic research.
Utilizing sociological theories of role taking and role making, three distinct IIT roles emerge: “distant service providers,”
“deputy police officers,” and “masters of balance.” Each role reflects unique approaches influenced by professional identity and
self-defined involvement in police investigations. At the same time, the research highlights the relevance of police trust in
IITs. According to our study, role making functions as a negotiation between all stakeholders involved, challenging dichotomous
perspectives on norms and expectations. The study advocates for a nuanced approach to IIT roles that integrates
forensic-criminalistic considerations into translation practices. It also urges criminal justice authorities to rethink
interpreting and translation methods by prioritizing meaningful translations that align with ethical standards and forensic
principles.
Real-time methods in JT/SYK holography
Authors: Arias Raúl , Botta-Cantcheff Marcelo , Martinez Pedro J
Published: August 2024

We study the conventional holographic recipes and its real-time extensions in the context of the correspondence between Sachdev–Ye–Kitaev quantum mechanics and JT gravity. We first observe that only closed contours are allowed to have a 2d space-time holographic dual and standard holographic formulas. Thus, in a real-time formulation of the duality, the boundaries of a classical connected geometry are a set of closed curves, parameterized by a complex time contour as in the Schwinger–Keldysh framework. In this context, a consistent extension of the standard holographic formulas can be proposed, describing the (real-time) correspondence between gravity and boundary quantum models that include averaging on the coupling constants. We investigate the proposed prescription in different AdS

1
+
1

solutions with Schwinger–Keldysh boundary condition, dual to a boundary quantum theory at finite temperature defined on a complex time contour, and consider also classical, asymptotically AdS solutions (wormholes) with two disconnected boundaries. In doing this, we revisit the so-called factorization problem, and its resolution in conventional holography by virtue of some (non-local) coupling between disconnected boundaries, and we show how in specific contexts, the averaging proposal by-passes the paradox as well, since it induces a similar effective coupling.
The motion of twisted particles in a stellar gravitational field
Authors: Lian Dan-Dan , Zhang Peng-Ming
Published: August 2024

In this work, we explore the motion of a twisted particle possessing intrinsic orbital angular momentum (OAM) as it traverses a weak stellar gravitational field, which we approximate using a polytropic model. We disregard the spin characteristic of the twisted particle, modeling it as a massless complex twisted scalar wave packet to simplify its interaction with gravitational fields. Building on this simplification, we determine the trajectory of this twisted particle by using the center of its energy density and investigate the gravitational birefringence induced by its OAM. In a weak field approximation, we find the gravitational birefringence-OAM relationship parallels that with spin, as described by the Mathisson-Papapetrou-Dixon equations. This indicates that the gravitational birefringence induced by OAM can potentially exceed that induced by spin by several orders of magnitude, significantly enhancing its detectability. To broaden our analysis, we introduce a nonminimal coupling term,

λ
R

|

ϕ

|
2

, into the Lagrangian, resulting in the modified expression

L

=
−

1
2

∇
ρ

ϕ

∇
ρ

ϕ
∗

−

1
2

λ
R

|

ϕ

|
2

. This adjustment is necessitated by the quantization of the scalar field in curved spacetime. We then explore the effects of this term on the motion of the twisted particle. Our findings show that the trajectory of the twisted particle under nonminimal coupling (λ ≠ 0) differs from that in the minimal coupling scenario (λ = 0). Specifically, for a positive nonminimal coupling constant λ, the trajectory of the twisted particle is expected to deviate away from the stellar center, compared to the minimal coupling scenario.
A new 2+1 coherent spin-foam vertex for quantum gravity
Authors: Simão J D
Published: August 2024

We propose an explicit spin-foam amplitude for Lorentzian gravity in three dimensions, allowing for both space- and time-like boundaries. The model is based on two main requirements: that it should be structurally similar to its well-known Euclidean analog, and that geometricity should be recovered in the semiclassical regime. To this end we introduce new coherent states for space-like boundary edges, derived from the continuous series of unitary

SU

(
1
,
1
)

representations. We show that the relevant objects in the amplitude can be written in terms of the defining representation of the group, just as so happens in the Euclidean case. We derive an expression for the semiclassical amplitude at large spins, showing it relates to the Lorentzian Regge action.
Shadow of rotating black holes surrounded by dark fluid with Chaplygin-like equation of state and constraints from EHT results
Authors: Zahid Muhammad , Sarikulov Furkat , Shen Chao , Ahmedov Saidmuhammad , Rayimbaev Javlon
Published: August 2024

In this work, we mainly focus on testing the spacetime properties around black holes surrounded by a dark fluid, which are potential candidates for dark energy described by the Chaplygin-like equation of state through its shadow. To do this, we first study the black hole’s horizon structure and shadow for the non-rotating case. Then, we obtain a rotating black hole solution in the presence of a dark fluid using the generalized Newman–Janis algorithm and study the effects of the black hole spin and the fluid parameters on the black hole horizons. Also, we obtained the shadow cast of the rotating black hole using celestial coordinates and showed that the presence of the dark fluid causes an increase in shadow size. Moreover, we use the shadow size of supermassive black holes Sagittarius A* and M87* from Event Horizon Telescope observations to obtain constraints on the spin, black hole charge, and dark fluid parameters. Lastly, we investigate the energy emission rate of a charged black hole surrounded by a Chaplygin-like dark fluid, comparing it to both rotating and non-rotating cases.
A perspective on reducing stabilizing pressure for high-temperature superconductivity in hydrides
Authors: Jiang Qiwen , Chen Ling , Du Mingyang , Duan Defang
Published: August 2024

The theoretical predictions and experimental syntheses of hydrogen sulfide (H3S) have ignited a surge of research interest in hydride superconductors. Over the past two decades, extensive investigations have been conducted on hydrides with the ultimate goal of achieving room-temperature superconductivity under ambient conditions. In this review, we present a comprehensive summary of the current strategies and progress towards this goal in hydride materials. We conclude their electronic characteristics, hydrogen atom aggregation forms, stability mechanisms, and more. While providing a real-time snapshot of the research landscape, our aim is to offer deeper insights into reducing the stabilizing pressure for high-temperature superconductors in hydrides. This involves defining key long-term theoretical and experimental opportunities and challenges. Although achieving high critical temperatures for hydrogen-based superconductors still requires high pressure, we remain confident in the potential of hydrides as candidates for room-temperature superconductors at ambient pressure.
Use of real-time electronic extremity dosimeters for monitoring and optimisation of radiopharmacy technique
Authors: Cournane S , McCavana J , Maguire D , Tutty L , Harris L , Lucey J , Kenneally C
Published: August 2024

Radiopharmacy staff members are subject to extremity radiation doses, particularly to the fingertips. Dosemeters, such as, thermoluminescent detectors (TLDs) are currently used for monitoring fingertip doses. This study aimed to use real-time dosemeters to monitor radiopharmacy extremity doses to identify specific procedural steps associated with higher fingertip doses and, subsequently, reduce dose through promotion of optimised radiation protection practises. Five radiopharmacy operators were monitored using an ED3 active extremity dosemeter with a detector attached to each tip of the index fingers. Dose rate and accumulated dose data were matched to the handled radioactivity data, of 99mTc-labelled radiopharmaceuticals only, with the dose per activity (μSv MBq−1) calculated for each step. Once baseline dose data was established, an educational session identified technique adjustments toward improved radiation protection. A subsequent monitored session was undertaken with the dose data compared to quantify changes in operator doses. Radiopharmacy steps which significantly contributed to extremity doses were identified. The average accumulated dose per activity across all procedural steps for the 99mTc-labelled radiopharmaceuticals for all operators before the educational session was 0.042 ± 0.045 μSv MBq−1 and 0.042 ± 0.041 μSv MBq−1 (n = 89) for non-dominant and dominant index fingertips, respectively, and 0.030 ± 0.044 μSv MBq−1 and 0.031 ± 0.032 μSv MBq−1 (n = 97), respectively, afterwards. Overall, there was an average 40.7% reduction in the total extremity dose received after the educational session. Real-time electronic extremity dosemeters for monitoring radiopharmacy extremity dose presented as a useful tool for incorporation into radiation protection education and training, towards optimised radiopharmacy technique.
Multi-scale receptive field grouped and split attention network for real-time detection of hazardous chemical gas leaks in infrared images
Authors: Chen Yan , Wang Kehong , Wang Xiaofeng , Huai Shibao , Xu Lixiang , Zhang Chen , Wang Mingtao
Published: August 2024

The petrochemical industry faces frequent hazardous gas leaks, which demand precise and timely detection to avert severe consequences. Existing computer vision approaches encounter challenges due to limitations in gas characteristics and scene features. To address these issues, we propose a multiscale receptive field grouped and split attention network, GAS-YOLO, that integrates infrared imaging technology. Within GAS-YOLO, we design a novel module, multi-scale receptive field grouped convolution (MRFGConv), to preserve fine-grained information, preventing detail loss and addressing spatial attention feature-sharing issues. An innovative split convolution attention (SCA) mechanism in the C2f module effectively couples multi-scale features, balancing performance and efficiency. Additionally, the asymptotic feature pyramid network (AFPN) facilitates the mutual interaction of information between non-adjacent levels, enabling advanced feature fusion. Using benchmark InfraGasLeakDataset, GAS-YOLO surpasses YOLOv8-n by 5.8% mAP50, with SCA outperforming state-of-the-art attention models. Experiment results validate the effectiveness and feasibility of our proposed approaches, providing valuable insights into hazardous chemical gas leak detection.
LDVI-SLAM: a lightweight monocular visual-inertial SLAM system for dynamic environments based on motion constraints
Authors: Wang Fenghua , Zhao Lengrui , Xu Zhicheng , Liang Hong , Zhang Qian
Published: August 2024

Traditional simultaneous localization and mapping (SLAM) systems are typically based on the assumption of a static environment. However, in practical applications, the presence of moving objects significantly reduces localization accuracy, limiting the system’s versatility. To address the challenges of SLAM systems in dynamic environments, the academic community often employs computationally intensive methods such as deep learning, and some algorithms rely on expensive sensors (e.g. LiDAR or RGB-D cameras) to obtain depth information. These factors increase computational complexity or hardware costs, complicating practical deployment. To improve localization accuracy and adaptability of SLAM systems in dynamic scenarios while maintaining low deployment costs, this paper proposes a dynamic environment robust monocular inertial SLAM system named LDVI-SLAM. The system uses more cost-effective sensors—monocular cameras and inertial measurement unit (IMU)—along with lightweight computational methods. In LDVI-SLAM, first, the reliability of IMU data is verified. Then, using the ego-motion information provided by the IMU, along with epipolar constraint and an improved rotation-aware flow vector bound (R-FVB) constraint, dynamic feature points are eliminated. Additionally, this paper proposes a continuous tracking across interval frames method to enhance the distinction between static and dynamic feature points. Experimental results demonstrate that LDVI-SLAM performs effectively in dynamic environments and is easy to deploy. On the Visual-Inertial Odometry in Dynamic Environments dataset, experimental results show that compared to the deep learning-based DynaSLAM, this method reduces the root mean square error of absolute trajectory error by 10.3%. Moreover, in terms of speed, under the same computing power, the single-frame processing speed of this method is comparable to ORB-SLAM3 and is two orders of magnitude faster than DynaSLAM, significantly outperforming deep learning-based SLAM algorithms. Experiments on the Oxford Multimotion Dataset further prove that this method effectively avoids the risk of semantic classification errors, demonstrating better robustness and generality.
Experiment and industrial application of dust concentration measurement method using image transmittance characteristic
Authors: Ye Fangping , Wang Daibing , Xu Xianjin , Fang Chaoyang , Nie Lei
Published: August 2024

To prevent the harm of respirable dust and dust explosions, it is necessary to detect the concentration of dust generated in the process of bulk materials to help dust suppression. In this investigation, a dust concentration measurement method is proposed based on the eigenvalue calculation of image transmittance. The method is combined with the dark channel prior theory into the computer system and calibrated in the laboratory to calculate the transmittance of dust images. Furthermore, a dust concentration online measurement experimental platform is established to verify the correctness and reliability. Moreover, the industrial application is also carried out. The average relative error of dust concentration is 4.53%, and the relative error is less than 10% of the dust concentration measured by online measurement experimental platforms and industrial applications, which satisfied the measurement requirements. It is concluded that the measurement method has high applicability and can be practically applied to dust concentration measurements.
Research on a semi-supervised soft sensor modelling method for complex chemical processes based on INGO-VMD-ESN
Authors: Wang Qinghong , Li Longhao , Li Naiqing , Sun Fengpeng , Liu Xuefeng , Wang Shuang
Published: August 2024

The dynamic and non-linear nature of complex chemical processes often leads to low prediction accuracy of key quality variables by traditional soft sensors, thus affecting the overall system control accuracy and operational efficiency. Therefore, this paper proposes a semi-supervised soft sensor modelling method based on improved the northern goshawk optimization (INGO)-variable mode decomposition (VMD)-echo state network (ESN). Firstly, a new semi-supervised fusion method is proposed to address the problem of model training difficulty due to the scarcity of labelled samples and process dynamics, which reconstructs the sample dataset by fusing labelled and unlabelled samples into more representative new samples, improving the model’s generalization ability. Secondly, for the noise interference present in the reconstructed data, the input data is denoised using the VMD method to improve the quality of data. Then, a soft sensor model is built based on ESN. Additionally, the denoising and prediction performance of VMD and ESN is significantly affected by parameters, therefore the paper utilizes the INGO algorithm to achieve parameter rectification for VMD and ESN. Finally, the method is validated based on actual sulphur recovery data from a refinery. The results demonstrate that the method effectively mitigates the impact of dynamics and nonlinearity in the complex chemical process which enhances prediction accuracy.
Refining penalty parameter selection in whole-body PET image reconstruction for lung cancer patients using the cross-validation log-likelihood method
Authors: Wang Qian , Abdelhafez Yasser G , Nalbant Hande , Spencer Benjamin A , Bayerlein Reimund , Qi Jinyi , Cherry Simon R , Nardo Lorenzo , Badawi Ramsey D
Published: August 2024

Objective. Penalty parameters in penalized likelihood positron emission tomography (PET) reconstruction are typically determined empirically. The cross-validation log-likelihood (CVLL) method has been introduced to optimize these parameters by maximizing a CVLL function, which assesses the likelihood of reconstructed images using one subset of a list-mode dataset based on another subset. This study aims to validate the efficacy of the CVLL method in whole-body imaging for cancer patients using a conventional clinical PET scanner. Approach. Fifteen lung cancer patients were injected with 243.7 ± 23.8 MBq of [18F]FDG and underwent a 22 min PET scan on a Biograph mCT PET/CT scanner, starting at 60 ± 5 min post-injection. The PET list-mode data were partitioned by subsampling without replacement, with 20 minutes of data for image reconstruction using an in-house ordered subset expectation maximization algorithm and the remaining 2 minutes of data for cross-validation. Two penalty parameters, penalty strength β and Fair penalty function parameter δ, were subjected to optimization. Whole-body images were reconstructed, and CVLL values were computed across various penalty parameter combinations. The optimal image corresponding to the maximum CVLL value was selected by a grid search for each patient. Main results. The δ value required to maximize the CVLL value was notably small (⩽10−6 in this study). The influences of voxel size and scan duration on image optimization were investigated. A correlation analysis revealed a significant inverse relationship between optimal β and scan count level, with a correlation coefficient of −0.68 (p-value = 3.5 × 10−5). The optimal images selected by the CVLL method were compared with those chosen by two radiologists based on their diagnostic preferences. Differences were observed in the selection of optimal images. Significance. This study demonstrates the feasibility of incorporating the CVLL method into routine imaging protocols, potentially allowing for a wide range of combinations of injected radioactivity amounts and scan durations in modern PET imaging.
SBL-LCGL: sparse Bayesian learning based on Laplace distribution for robust cone-beam x-ray luminescence computed tomography
Authors: Wang Yifan , Wang Haoyu , Zhu Qiuquan , Chen Yi , Su Linzhi , Yi Huangjian , Gao Chengyi , Cao Xin
Published: August 2024

Objective. To address the quality and accuracy issues in the distribution of nanophosphors (NPs) using Cone-beam x-ray luminescence computed tomography (CB-XLCT) by proposing a novel reconstruction strategy. Approach. This paper introduces a sparse Bayesian learning reconstruction method termed SBL-LCGL, which is grounded in the Lipschitz continuous gradient condition and the Laplace prior to overcome the ill-posed inverse problem inherent in CB-XLCT. Main results. The SBL-LCGL method has demonstrated its effectiveness in capturing the sparse features of NPs and mitigating the computational complexity associated with matrix inversion. Both numerical simulation and in vivo experiments confirm that the method yields satisfactory imaging results regarding the position and shape of the targets. Significance. The advancements presented in this work are expected to enhance the clinical applicability of CB-XLCT, contributing to its broader adoption in medical imaging and diagnostics.
A sectional nonlinear wideband piezoelectric-magnetic coupled energy collector for collecting multi-directional vibrational energy
Authors: Zhu Yuancheng , Zhu Yongqiang , Zou Longhua , Chi Han , Zhuang Huyue , Zhang Pingxia
Published: August 2024

The classic vibration energy collector has functional restrictions, and it can only collect vibration energy in one or two dimensions. At the same time, it has issues with low output power in the low-frequency vibration region and a limited reaction frequency range. This research proposes a segmented nonlinear broadband piezoelectric–magnetic coupled energy collector capable of collecting vibration energy in different directions. The collector is equivalent to current state-of-the-art research in that it can collect vibration energy in three dimensions while also having a wide collection frequency and a high power density. The collection consists of a hemispherical support structure and four fundamental piezoelectric beam collision components. The rationality of the collision segmentation nonlinear principle is first clarified through theoretical calculation and analysis, and then the collision design is applied between the ends of different cantilever beams to broaden the captured energy frequency band, while parallel piezoelectric beams use a 45° tilt treatment to fully utilize the geometrical properties of the tilted beams for multidirectional energy collection. In addition, the collector introduces a magnetic coupling effect to create a bistable structure via magnetic contact. Comsol 5.6 software is used to model and simulate the planned 45° tilted beam structure, which clarifies the piezoelectric beam’s linear intrinsic frequency characteristics and multi-directional geometric aspects. To further verify the collector’s validity, a physical model is built and a vibration experiment apparatus is created. The experimental results demonstrate that the collector’s effective bandwidth range is up to 6.3 Hz under 1 g acceleration excitation, representing a 125.0% increase in bandwidth when compared to the cantilever beam with a linear array. At 14 Hz frequency, the collector produces a maximum total output power of 19.52 mW and a power density of up to 3211uW cm−3 when excitation is provided in the Z-direction.