bluuebunny/crossref_metadata_2025 huggingface dataset:
Simultaneous measurements of temporal evolutions of the voltage and the current on the load of the Seoul National University X-pinch device using the optics-based systems
Authors: Choi Seongmin , Ham Seunggi , Ryu Jonghyeon , Park Sungbin , Kim Jung-Hwa , Choi YeongHwan , Cha Muhyeop , Bong Seungmin , Chung Kyoung-Jae , Hwang Y. S. , Ghim Y.-c.
Published: July 2024

Optics-based measurement systems have been developed to measure the voltage and the current on a load of the Seoul National University X-pinch device [Ryu et al., Rev. Sci. Instrum. 92, 053533 (2021)]. A lithium niobate crystal that changes the polarization state of the propagating laser beam due to the Pockels effect induced by the electric field across the crystal, thus capable of measuring the voltage, is located next to the load. For the current measurement, an optic fiber is wound around the load to detect the change in the polarization state of the propagating laser beam due to the Faraday rotation induced by the magnetic field. As both voltage and current measurement systems utilize optical effects, the sensors, i.e., the lithium niobate crystal and the optic fiber, do not require any electrical grounds, in contrast to circuit-based probes, such as voltage dividers or Rogowski grooves. This facilitates an easy access to shield other required electronic devices, such as lasers and photodetectors, from the electromagnetic interference generated by the X-pinch power system. In addition, the sensors can be placed in close proximity to the load with fewer concerns on the electrical insulation. Temporal evolutions of the simultaneously measured voltage and current on the load of the X-pinch are successfully obtained and discussed.
Breakdown mechanisms induced by stationary crossflow vortices in hypersonic three-dimensional boundary layers
Authors: Su Caihong , Li Gen , Han Yufeng
Published: July 2024

This study investigates the crossflow breakdown of a Mach 6 flow over a swept flat plate by direct numerical simulation (DNS) considering three cases with different spanwise wavenumbers of stationary vortices. Transition in these cases is initiated by the linear and nonlinear evolution of these vortices, followed by secondary instabilities and breakdown due to type-I, type-II modes, and wall blowing/suction perturbations, respectively. The results showed that amplified secondary instabilities significantly distort the mean flow, causing a steep rise in the wall friction coefficient. Fourier analysis shows that, in this fast-varying flow region, the low-frequency disturbances undergo significantly greater amplifications than high-frequency disturbances. Moreover, the stability characteristics of the time- and spanwise-averaged mean flow were examined to elucidate the breakdown mechanisms. It was found that the unstable region initially contracts to a lower frequency band and then expands significantly in the spanwise wavenumber range at low frequencies. This suggests the significant amplifications of low-frequency disturbances, consistent with the observations from DNS. These amplified low-frequency disturbances, in turn, modify the mean flow, leading to the final breakdown. The presented mechanisms, highlighting the critical role of low-frequency disturbances in the breakdown process, are likely to be universally relevant across various parameter regimes.
Identification and prediction method for acoustic emission and electromagnetic radiation signals of rock burst based on deep learning
Authors: Yang Hengze , Wang Enyuan , Song Yue , Chen Dong , Wang Xiaoran , Wang Dongming , Li Jingye
Published: July 2024

With the deep development of underground rock engineering, the threat of rock burst disasters is increasing. At present, the identification and prediction of rock burst mostly rely on the experience of field staff to determine the critical value and development trend, and there is a lack of efficient and intelligent methods for the utilization of massive data. Therefore, this paper constructs a rock burst signal recognition and prediction model based on deep learning methods to solve the above problems. In this paper, the acoustic emission (AE) and electromagnetic radiation (EMR) data of the site are first marked and input into the long-short-term memory-fully connected neural network model to realize the identification of rock burst danger signals. Then, the graph data of the AE and EMR sensor monitoring networks are constructed and input into the spatiotemporal graph convolutional network signal prediction model to predict future monitoring data. Finally, this paper uses the same dataset to compare and analyze several other commonly used deep learning models. The results show that the model constructed in this paper has the best performance in the identification and prediction of AE and EMR signals with rockburst risk. This study can provide theoretical reference for intelligent monitoring and early warning of rock burst in underground rock engineering.
Electric field-induced volume change in pyro-vanadate-phosphates: Toward an alternative actuator architecture
Authors: Takada K. , Shibutani J. , Yagi K. , Ikawa F. , Yokoyama Y. , Hirai D. , Okamoto Y. , Katayama N. , Umena Y. , Chavas L. M. G. H. , Hatano T. , Fujita A. , Takenaka K.
Published: July 2024

We discovered large electric-field-induced strain in pyro-vanadate-phosphate Cu2−xZnxV1.8P0.2O7. Distinct from conventionally used piezoelectric materials including lead-zirconate-titanate, this material expands almost isotropically at room temperature when an electric field is applied. This volume change, exceeding 1000 ppm under the field of E = 3900 V/cm, is of the largest class induced by an electric field. The strain is phenomenologically interpreted as electrostriction because it is symmetric about E = 0 and because it obeys a higher term than E-linear such as E squared. The present x-ray diffraction experiments suggest that the applied electric field distorts the crystal lattice, although there is no structural phase transition. This material performs a volume-change-driven actuator function that is distinct from the strain-driven counterpart of piezoelectric materials. The discovery of actuator functionality in a material system with a non-perovskite structure, unlike the actuator materials developed to date, is a major breakthrough for future actuator engineering.
Thermally developing streaming potential-mediated pressure-driven flow of Phan–Thien–Tanner fluid in a microchannel
Authors: Kumbalpuri Tripti , Sarkar Sandip
Published: July 2024

In this study, we have conducted a semi-analytical investigation into the streaming potential-mediated pressure-driven flow of hydrodynamically fully developed and thermally developing viscoelastic fluid in a parallel plate microchannel. We have utilized a simplified Phan–Thien–Tanner model to describe the rheology of the viscoelastic fluid. Our approach delved into the full Poisson–Boltzmann equation, deriving exact analytical solutions for the electrostatic potential distribution and velocity profile. Furthermore, we concurrently derived semi-analytical solutions for the temperature distribution and Nusselt number, accounting for the effects of heat generation from viscous dissipation and Joule heating in thermally developing flows. We have demonstrated that an increase in the degree of surface charge triggers the streaming potential field, while the volumetric flow rate escalates with the viscoelastic parameter εWik¯2. Moreover, we have observed that the magnitude of the dimensionless temperature decreases with increasing values of the effective Joule heating parameter Speff. Our analysis reveals that the streaming potential effect hampers fluid flow, resulting in an increase in the bulk fluid temperature and consequently reducing the heat transfer rate. We observe that the magnitude of the Nusselt number decreases with increasing Speff. The entropy generation analysis reveals that increasing the Peclet number amplifies flow and temperature gradients, leading to higher fluid irreversibility in microchannels. The Bejan number experiences a significant decrease across the channel, reaching its minimum at a specific axial location before stabilizing further downstream. We find that heat transfer irreversibility predominantly influences system irreversibility, except for the Brinkmann number Br = 0.01, where convective heat transfer dominates at the entrance region, transitioning to friction losses beyond the thermal entry zone.
Prominent phonon transmission across aperiodic superlattice through coherent mode-conversion
Authors: Maranets Theodore , Wang Yan
Published: July 2024

In both particle and wave descriptions of phonons, the dense, aperiodically arranged interfaces in aperiodic superlattices are expected to strongly attenuate thermal transport due to phonon-interface scattering or broken long-range coherence. However, non-trivial thermal conductivity is still observed in these structures. In this study, we reveal that incoherent modes propagating in the aperiodic superlattice can be converted, through interference, into coherent modes defined by an approximate dispersion relation. This conversion leads to high transmission across the aperiodic superlattice structure, which contains hundreds of interfaces, ultimately resulting in non-trivial thermal conductivity. Such incoherent-to-coherent mode-conversion behavior is extensively observed in periodic superlattices. This work suggests an effective strategy to manipulate the phonon dispersion relation through layer patterning or material choice, enabling precise control of phonon transmission across aperiodic superlattices.
Triple decomposition and sparse representation for noisy pressure-sensitive paint data
Authors: Kubota Koyo , Takagi Makoto , Ikami Tsubasa , Egami Yasuhiro , Nagai Hiroki , Kashikawa Takahiro , Kimura Koichi , Matsuda Yu
Published: July 2024

Triple decomposition is a powerful analytical method for a deep understanding of the flow structure by extracting the mean value, organized coherent motion, and stochastic part from a fluctuating quantity. Here, we perform the triple decomposition of the spatial two-dimensional data, especially pressure-sensitive paint (PSP) data, since the PSP method is widely used to measure the pressure distribution on a surface in wind tunnel testing. However, the PSP data measuring near atmospheric pressure contain significant noise, and this makes it difficult to conduct the decomposition. To construct phase-averaged data representing an organized coherent motion, we propose a relatively simple method based on a multi-dimensional scaling plot of the cosine similarity between each PSP datum. Then, the stochastic part is extracted by selecting phase-averaged data with an appropriate phase angle based on the similarity between the measurement and phase-averaged data, and the PSP data are successfully decomposed. Moreover, we consider sparse optimal sensor positions, in which the data are effectively represented, based on the stochastic part as a data-driven approach. The optimal sensor positions are determined as a combinatorial optimization problem and estimated using Fujitsu computing as a service digital annealer. We reconstruct the pressure distribution from the pressure data at the optimal sensor positions using the mean value, organized coherent motion, and stochastic part obtained from the triple decomposition. The root mean square error between the pressure measured by a pressure transducer and the reconstructed pressure obtained by the proposed method is small, even when the number of modes and sensor points is small. The application of PSP measurement is expected to expand further, and the framework for calculating triple decomposition and sparse representation based on the decomposition will be useful for detailed flow analysis.
Domain partition leads to a manifold increase of heat transport in Rayleigh–Bénard convection at low Prandtl number
Authors: Smith Joel , Zikanov Oleg
Published: July 2024

Results of an exploratory numerical study of Rayleigh–Bénard convection of a low-Pr fluid in a cylinder with a vertical partition are reported. It is shown that a partition may lead to a many-fold increase in the rate of convection heat transfer. The effect is associated with the formation of coherent hot and cold streams separated by the partition. The heat transfer enhancement is particularly strong in tall cylinders and requires that the partition penetrates into the thermal boundary layers near the top and bottom walls.
Threatened stick-nest rats preferentially eat invasive boxthorn rather than native vegetation on Australia’s Reevesby Island
Authors: Kraehe Annie A. , Weisbecker Vera , Hill Robert R. , Hill Kathryn E.
Published: July 2024

Context The incorporation of invasive plants into novel ecosystems often has negative effects, but it can also sometimes enhance ecosystem function. The threatened native rodent species Leporillus conditor (greater stick-nest rat) is extinct on the Australian mainland and now lives primarily on small islands off the coast of southern Australia. Many of these are degraded novel ecosystems invaded by African boxthorn (Lycium ferocissimum), a weed of national significance. However, L. conditor does not appear to be negatively affected by the presence of boxthorn, raising the question of how the two species co-exist. Aims To understand how L. conditor uses African boxthorn, we evaluated dietary composition of L. conditor on parts of Reevesby Island by comparing consumption of invasive boxthorn with that of native vegetation. Methods We identified three key vegetation types on the centre of the island and used point-intercept vegetation surveys to estimate relative availability of plant species in each. We then used micro-histological faecal analysis to estimate the proportions of each species in the diet of L. conditor, and quantified plant species selection by using selection ratios (use/availability). Key results Qualitative evidence of L. conditor activity suggested that it was mostly confined to vegetation with greater abundance of boxthorn than the other vegetation types (13.5%, compared with 5.7% total sampled vegetation). Furthermore, 51.7% of the faecal plant content and 11.8% of total sampled vegetation was African boxthorn, resulting in a selection ration for boxthorn of 4.4. Native species that appeared to be favoured food sources of L. conditor included Olearia axillaris, Myoporum insulare and Enchylaena tomentosa. Conclusions Stick-nest rats of Reevesby Island demonstrate a clear selection for African boxthorn, both in terms of diet (tested quantitatively) and nesting (from previous research and our field observations). Implications The strong selection of stick-nest rats for a declared noxious weed as its main food source and persistence of stick-nest rats on Reevesby Island require consideration with regards to vegetation management on islands where L. conditor occurs. More broadly, it highlights that some elements of novel ecosystems may have unexpected positive impacts on parts of original ecosystems.
GABA
A
receptor subunit composition regulates circadian rhythms in rest–wake and synchrony among cells in the suprachiasmatic nucleus
Authors: Granados-Fuentes Daniel , Lambert Peter , Simon Tatiana , Mennerick Steven , Herzog Erik D.
Published: July 2024

The mammalian circadian clock located in the suprachiasmatic nucleus (SCN) produces robust daily rhythms including rest–wake. SCN neurons synthesize and respond to γ-aminobutyric acid (GABA), but its role remains unresolved. We tested the hypothesis that γ2- and δ-subunits of the GABA
A
receptor in the SCN differ in their regulation of synchrony among circadian cells. We used two approaches: 1) shRNA to knock-down (KD) the expression of either γ2 or δ subunits in the SCN or 2) knock-in mice harboring a point mutation in the M2 domains of the endogenous GABA
A
γ2 or δ subunits. KD of either γ2 or δ subunits in the SCN increased daytime running and reduced nocturnal running by reducing their circadian amplitude by a third. Similarly, δ subunit knock-in mice showed decreased circadian amplitude, increased duration of daily activity, and decreased total daily activity. Reduction, or mutation of either γ2 or δ subunits halved the synchrony among, and amplitude of, circadian SCN cells as measured by firing rate or expression of the PERIOD2 protein, in vitro. Surprisingly, overexpression of the γ2 subunit rescued these phenotypes following KD or mutation of the δ subunit, and overexpression of the δ subunit rescued deficiencies due to γ2 subunit KD or mutation. We conclude that γ2 and δ GABA
A
receptor subunits play similar roles in maintaining circadian synchrony in the SCN and amplitude of daily rest–wake rhythms, but that modulation of their relative densities can change the duration and amplitude of daily activities.
Proton radiation boosts the efficacy of mesothelin-targeting chimeric antigen receptor T cell therapy in pancreatic cancer
Authors: Amit Uri , Uslu Ugur , Verginadis Ioannis I. , Kim Michele M. , Motlagh Seyyedeh Azar Oliaei , Diffenderfer Eric S. , Assenmacher Charles-Antoine , Bicher Sandra , Atoche Sebastian J. , Ben-Josef Edgar , Young Regina M. , June Carl H. , Koumenis Constantinos
Published: July 2024

Pancreatic ductal adenocarcinoma (PDAC) represents a challenge in oncology, with limited treatment options for advanced-stage patients. Chimeric antigen receptor T cell (CAR T) therapy targeting mesothelin (MSLN) shows promise, but challenges such as the hostile immunosuppressive tumor microenvironment (TME) hinder its efficacy. This study explores the synergistic potential of combining proton radiation therapy (RT) with MSLN-targeting CAR T therapy in a syngeneic PDAC model. Proton RT significantly increased MSLN expression in tumor cells and caused a significant increase in CAR T cell infiltration into tumors. The combination therapy reshaped the immunosuppressive TME, promoting antitumorigenic M1 polarized macrophages and reducing myeloid-derived suppressor cells (MDSC). In a flank PDAC model, the combination therapy demonstrated superior attenuation of tumor growth and improved survival compared to individual treatments alone. In an orthotopic PDAC model treated with image-guided proton RT, tumor growth was significantly reduced in the combination group compared to the RT treatment alone. Further, the combination therapy induced an abscopal effect in a dual-flank tumor model, with increased serum interferon-γ levels and enhanced proliferation of extratumoral CAR T cells. In conclusion, combining proton RT with MSLN-targeting CAR T therapy proves effective in modulating the TME, enhancing CAR T cell trafficking, and exerting systemic antitumor effects. Thus, this combinatorial approach could present a promising strategy for improving outcomes in unresectable PDAC.
Overlooked significance of iodic acid in new particle formation in the continental atmosphere
Authors: Ning An , Shen Jiewen , Zhao Bin , Wang Shuxiao , Cai Runlong , Jiang Jingkun , Yan Chao , Fu Xiao , Zhang Yunhong , Li Jing , Ouyang Daiwei , Sun Yisheng , Saiz-Lopez Alfonso , Francisco Joseph S. , Zhang Xiuhui
Published: July 2024

New particle formation (NPF) substantially affects the global radiation balance and climate. Iodic acid (IA) is a key marine NPF driver that recently has also been detected inland. However, its impact on continental particle nucleation remains unclear. Here, we provide molecular-level evidence that IA greatly facilitates clustering of two typical land-based nucleating precursors: dimethylamine (DMA) and sulfuric acid (SA), thereby enhancing particle nucleation. Incorporating this mechanism into an atmospheric chemical transport model, we show that IA-induced enhancement could realize an increase of over 20% in the SA–DMA nucleation rate in iodine-rich regions of China. With declining anthropogenic pollution driven by carbon neutrality and clean air policies in China, IA could enhance nucleation rates by 1.5 to 50 times by 2060. Our results demonstrate the overlooked key role of IA in continental NPF nucleation and highlight the necessity for considering synergistic SA-IA-DMA nucleation in atmospheric modeling for correct representation of the climatic impacts of aerosols.
The Neuroprotective Potential of Polyphenols in Neurodegenerative Diseases
Authors: Wojciechowska Olga
Published: July 2024

Neurodegenerative diseases, which pose a significant challenge to ageing populations, are characterised by the progressive loss of neurons leading to a range of symptoms. Alzheimer's and Parkinson's disease, the most prevalent neurodegenerative disorders, share common pathological mechanisms such as protein aggregation, neuroinflammation, mitochondrial dysfunction and oxidative stress. Despite extensive research, effective treatments for these diseases remain elusive. However, polyphenols, natural compounds found abundantly in plants, have been receiving attention for their potential neuroprotective effects. This review explores the impact of selected polyphenols, including curcumin, resveratrol, ellagitannins, anthocyanins, quercetin and epigallocatechin gallate, on Alzheimer's and Parkinson's disease.
In vitro
and animal model studies have demonstrated promising outcomes, suggesting that polyphenols may modulate key pathways involved in neurodegeneration. However, there are limited data from human trials. Challenges such as bioavailability and optimal dosing hinder the translation of the results into clinical practice. Furthermore, multidisciplinary research teams and well-designed clinical trials are essential to unlock the full therapeutic potential of polyphenols in combating neurodegenerative diseases and improving patient outcomes.

Information

© The Author 2024
Pauli-type coupling of spinors and curved spacetime
Authors: Struckmeier J , Vasak D , Redelbach A , Stöcker H
Published: July 2024

In this study we prove that the Pauli interaction—which is associated with a length parameter—emerges when the minimal coupling recipe is applied to the non-degenerate version of the Dirac Lagrangian. The conventional Dirac Lagrangian is rendered non-degenerate if supplemented by a particular term quadratic in the derivatives of the spinors. For dimensional reasons, this non-degenerate Dirac Lagrangian is associated with a length parameter

ℓ

. It yields the standard free Dirac equation in Minkowski space. However, if the Dirac spinor is minimally coupled to gauge fields, then the length parameter

ℓ

becomes a physical coupling constant yielding novel interactions. For the U(1) symmetry the Pauli coupling of fermions to electromagnetic fields arises, modifying the fermion’s magnetic moment. We discuss the impact of these findings on electrodynamics, and estimate the upper bound of the length parameter

ℓ

from the yet existing discrepancy between the (SM) theory and measurement of the anomalous magnetic moment of light leptons. This, and also recent studies of the renormalization theory, suggest that the Pauli coupling of leptons to the electromagnetic field is a necessary ingredient in quantum electrodynamics (QED), supporting the notion of a fundamental nature of the non-degenerate Dirac Lagrangian. In a second step we then investigate how analogous ‘Pauli-type’ couplings of gravity and matter arise if fermions are embedded in curved spacetime. Minimal coupling of the Dirac field to the gauge field of gravity, the spin connection, leads to an anomalous spin-torsion interaction and a curvature-dependent mass correction. The relation of the latter to Mach’s Principle is discussed. Moreover, it is found for a totally anti-symmetric torsion that an upper limit for the ‘strength’ of the torsion exists in order for a solution to remain causal, while causality for a vector torsion requires a lower limit for its amplitude. We calculate the mass correction in the De Sitter geometry of vacuum with the cosmological constant Λ. Possible implications for the existence of effective non-zero rest masses of neutrinos are addressed. Finally, an outlook on the impact of mass correction on the physics of ‘Big Bang’ cosmology, black holes, and of neutron stars is provided.
CosmoFlow: Python package for cosmological correlators
Authors: Werth Denis , Pinol Lucas , Renaux-Petel Sébastien
Published: July 2024

Cosmological correlators hold the key to high-energy physics as they probe the earliest moments of our Universe, and conceal hidden mathematical structures. However, even at tree-level, perturbative calculations are limited by technical difficulties absent in flatspace Feynman diagrammatics. In this paper, we introduceCosmoFlow: a new accurate open source Python code that computes tree-level cosmological correlators by tracing their time flow. This code is specifically designed to offer a simple, intuitive and flexible coding environment to theorists, primordial and late-time cosmologists. It can typically serve to complement analytical computations, to provide physical intuition when studying various inflationary theories, and to obtain exact results in regimes that are analytically out of reach. This paper presents the basic structure ofCosmoFlow, leads the reader through an in-depth user-guide, and illustrates how it can be used with a series of worked examples. Our hope is that this first building block sets the stage for a bank of theoretical data, which can be nurtured and enhanced collaboratively by the community.CosmoFlowis publicly available onGitHub.
Investigation of the mechanism of carrier recombination in GaN-based blue laser diodes before lasing
Authors: Liang Feng , Huang Yujie , Yang Jing , Chen Ping , Liu Zongshun , Zhao Degang
Published: July 2024

The carrier recombination behavior of GaN-based blue laser diodes (LDs) is studied and analyzed by experiments and simulation calculations before lasing, with a particular focus on the role of Auger recombination. It is found that Auger recombination plays a crucial role in the decrease in differential efficiency and threshold current of GaN-based blue LDs. The theoretical calculation results show that a large Auger recombination rate may lead to a dominant recombination channel before lasing, which could exceed the radiation recombination and result in an obvious decrease in the differential efficiency. Such a high Auger recombination will dissipate a large number of carriers in the quantum well, resulting in deterioration of device performance, a higher threshold current and a lower efficiency. This work presents a method to evaluate Auger recombination through differential efficiency and also provides evidence that suppressing the Auger recombination rate is beneficial to improve the performance of blue LDs.
In-line monitoring and modelling of particle size reduction of hexagonal boron nitride (hBN) suspension in femtosecond laser processing
Authors: Muneoka Hitoshi , Koike Takeru , Ito Tsuyohito , Terashima Kazuo , Miura Eisuke
Published: July 2024

This study investigates the particle-size reduction of hexagonal boron nitride (hBN) suspensions under femtosecond-laser irradiation. We propose an in-line monitoring method that uses transmission spectroscopy (TS) in the visible wavelength region to evaluate the changes in particle-size distribution. The Ångström exponent (α), derived from the wavelength dependence of optical thickness, is employed as an indicator of particle-size reduction. The effectiveness of α is validated through comparison with particle-size distributions obtained by the particle tracking method. We demonstrate real-time monitoring of particle-size variation in a flow system using in-line TS measurements. The dependence of α on laser energy and hBN concentration is also investigated. Furthermore, we introduce an indicator, the average number of size-reduction events per particle (N
SR), and a model for estimating it under various experimental conditions. The N
SR indicator and the model for its derivation provide a unified understanding of the experimental results obtained under various conditions, such as treatment volume, laser energy, and hBN concentration, suggesting that they capture the essential aspects of laser propagation in the suspension and the particle-size reduction process. This study highlights the potential of α as an in-line process monitoring tool and the significance of the N
SR indicator and its model in understanding the underlying mechanisms of laser processing for particle-size reduction in suspensions.
Nuclear medium effects on the properties of Λ(1405)
Authors: Süngü J Y , Er N
Published: July 2024

We study the Λ(1405) resonance with I(J

P
) = 0(1/2−) in the context of the pentaquark hypothesis in the nuclear medium. To explore the influence of the nuclear medium on the physical parameters of Λ(1405), we propose a molecular-type structure involving admixtures of K
−
p and

K

¯

0

n

, correlated with the nuclear matter density. Our analysis reveals a substantial shift in mass and residue, approximately 20% and 38%, respectively. These findings have significant implications for experimental researchers aiming to identify in-medium characteristics of hyperon resonances.
Ward identities in a two-dimensional gravitational model: anomalous amplitude revisited using a completely regularization-independent mathematical strategy
Authors: Dallabona G , de Oliveira P G , Battistel O A
Published: July 2024

We present a detailed investigation of the anomalous gravitational amplitude in a simple two-dimensional model with Weyl fermions. We employ a mathematical strategy that completely avoids any regularization prescription for handling divergent perturbative amplitudes. This strategy relies solely on the validity of the linearity of the integration operation and avoids modifying the amplitudes during intermediate calculations, unlike studies using regularization methods. Additionally, we adopt arbitrary routings for internal loop momenta, representing the most general analysis scenario. As expected, we show that surface terms play a crucial role in both preserving the symmetry properties of the amplitude and ensuring the mathematical consistency of the results. Notably, our final perturbative amplitude can be converted into the form obtained using any specific regularization prescription. We consider three common scenarios, one of which recovers the traditional results for gravitational anomalies. However, we demonstrate that this scenario inevitably breaks the linearity of integration, leading to an undesirable mathematical situation. This clean and transparent conclusion, enabled by the general nature of our strategy, would not be apparent in similar studies using regularization techniques.
The role of defect charge, crystal chemistry, and crystal structure on positron lifetimes of vacancies in oxides
Authors: Lopez-Bezanilla Alejandro , Selim Farida A , Oskar Liedke Maciej , Uberuaga Blas P
Published: July 2024

Density functional theory based positron lifetime (PL) calculations for cation and oxygen monovacancies in a range of oxides—hematite, magnetite, hercynite, and alumina—have been conducted to compare the impact of defect chemistry and crystal structure on the predicted lifetimes. The role of defect charge state has also been examined. A comparison across the same type of crystalline structure but different composition shows that oxygen vacancies only induce a slight increase in the positron-electron overlap and thus barely modify the PL as compared to the bulk. A much more substantial increase of PL is observed for cation monovacancies, regardless of crystal structure or the elemental nature of the vacancy, which we ascribe to an enhanced localization of charge density around the vacant site. The structural and compositional richness of the oxide leads to longer defect PLs, with defected hercynite exhibiting the longest PLs. The charge state of cation monovacancies modifies only by a small percentage the positron localization, relegating to secondary importance the metal defect’s oxidation state in modifying the lifetime of positrons within vacancy traps.
Long-term comparison and performance study of consumer grade electronic radon integrating monitors
Authors: Daraktchieva Z , Howarth C B , Wasikiewicz J M , Miller C A , Wright D A
Published: July 2024

This study reports the performance of 7 types of consumer grade passive Electronic Radon Integrating Monitors, ERIM (AlphaE, AER Plus, Canary, Corentium Pro, Radon Scout Home, Ramon and Wave) and passive etched track radon detectors. All monitors and passive radon detectors were exposed side by side for 2 periods of 3 months under controlled conditions in the UKHSA radon chamber and in a stainless steel container to an average radon concentration of 4781 Bq m−3 and 166 Bq m−3, respectively. The performance of each individual monitor was compared with Atmos 12DPX and AlphaGUARD P30 reference instruments. The performance of the monitors was evaluated by estimating the biased, precision and measurement errors of each type. It was found that UKHSA passive radon detectors showed excellent performance (measurement error < 10%) at both higher and lower exposures. The AlphaE, Canary and Ramon showed excellent performance, with measurement error <10%, when they were exposed to radon concentrations between 4000 Bq m−3 and 6000 Bq m−3 in the UKHSA radon chamber. However, when the monitors were exposed to radon levels below the UK radon Action Level of 200 Bq m−3, the only ERIM which had a measurement error <10% was the Radon Scout Home. All other monitors showed a significant decrease in their performance with measurement errors ranging between 20% and 50%. The calibration factor, which is the ratio between the measured value (background is subtracted) and the reference value, was also studied. It was found that the calibration factors of individual monitors changed significantly. Calibration measurements in 2019 and in 2023 found that the percentage change varied between −46% and +63%. This shows the importance of initial and regular calibration, and maintenance of the monitors.
Numerical assessment of induced electric fields in a worker’s hand with commonly used metallic implants under exposure to low frequency magnetic fields
Authors: Schmid Gernot , Schneeweiss Pia , Hirtl Rene , Jhala Tobias , Samaras Theodoros
Published: July 2024

The European Union’s Workers’ Directive 2013/35/EU on the minimum health and safety requirements regarding the exposure of workers to electromagnetic fields specifies action levels (ALs) for external electric and magnetic fields, which should protect against induced tissue-internal electric field strength E
i above the exposure limit values, the latter being defined in order to prevent tissue stimulation at low frequencies. However, although 2013/35/EU explicitly calls for the protection of ‘workers at particular risk’ (including workers with metallic implants), the AL specified in the Directive have been derived under the assumption that there are no metallic parts present inside the body. Therefore, in the present work, we analysed the situation of a worker’s hand and forearm bearing metallic implants (Herbert screw and volar radius plate) used for osteosynthesis after the most common bone fractures of the hand/forearm, exposed to low frequency magnetic fields. The uniform exposure of the whole hand and forearm as well as the exposure to a specific and widely used device, a deactivator for single-use labels of acousto-magnetic electronic article surveillance systems, were considered based on numerical computations using a high-resolution anatomical hand and forearm model. The results obtained indicated that the maximum induced electric field strength averaged in a volume of 2 mm × 2 mm × 2 mm cube was higher in the presence of the metallic implants by a factor of up to 4.2 for bone tissue and 2.3 for soft tissue compared with the case without an implant. Hence, it is obvious that the local induced electric field strengths may be substantially increased by the implants. The extent of this increase, however, is highly dependent on the implant’s position inside the body, the implant’s geometry, and the field distribution and orientation with respect to the anatomical structure and the implant.
Parallel-beams magnetic actuator for in-situ transmission electron microscope observation of mechanical testing
Authors: Denoual Matthieu , Lobato-Dauzier Nicolas , Saluden Luis , Sato Takaaki , Jalabert Laurent , Fujita Hiroyuki
Published: July 2024

Understanding the microscopic mechanisms behind mechanical fractures is essential for enhancing material properties and increasing reliability through fatigue suppression. Conventional mechanical testing methods, such as indentation tests that press a sharp needle into a specimen or tensile tests using hydraulic pumps, are unable to capture nanoscale deformations under applied forces. As a result, the microscopic mechanisms that influence mechanical properties are often inferred indirectly, and material design largely depends on the engineer’s intuition and occasional serendipity. To overcome these challenges, in-situ observation techniques utilizing transmission electron microscopes (TEMs) have been developed to enable the observation of sample deformations at the nanoscale. However, despite their high resolution, conventional TEMs are limited by a small available space -often just a few millimeters- that restricts the application of sufficient force to fracture specimens. Traditional actuation methods, such as thermal expansion, electrostatic force, and piezoelectric actuators, fail to generate significant forces within such confined spaces. In response to these limitations, our research involved the development of a micromachine with multiple parallel beams. This device leverages the Laplace force generated by an electric current passing through the beams and the magnetic field of the TEM. We demonstrated the capability to produce significant force using the magnetic field from the microscope’s magnetic lens. The actuator developed in our study successfully generated forces exceeding 50 µN, marking a significant advancement in the in-situ observation capabilities for mechanical testing.
Hybrid algorithms in path planning for autonomous navigation of unmanned aerial vehicle: a comprehensive review
Authors: Tuyet Minh Dang , Ba Dung Nguyen
Published: July 2024

Path planning for unmanned aerial vehicle (UAV) is the process of determining the path that travels through each location of interest within a particular area. There are numerous algorithms proposed and described in the publications to address UAV path planning problems. However, in order to handle the complex and dynamic environment with different obstacles, it is critical to utilize the proper fusion algorithms in planning the UAV path. This paper reviews some hybrid algorithms used in finding the optimal route of UAVs that developed in the last ten years as well as their advantages and disadvantages. The UAV path planning methods were classified into categories of hybrid algorithms based on traditional, heuristic, machine learning approaches. Criteria used to evaluate algorithms include execution time, total cost, energy consumption, robustness, data, computation, obstacle avoidance, and environment. The results of this study provide reference resources for researchers in finding the path for UAVs.
Methods and research for deformation monitoring of earth and rock dams based on close-range photogrammetry
Authors: Wang Kui , Cheng Yang , Xiong Yong , Wang Qiuqi , Zhao Mingjie
Published: July 2024

Traditional means of monitoring deformation in earth and rock dams encounter challenges such as low monitoring efficiency and limited coverage. Despite the potential of emerging technologies such as GPS and three-dimensional laser scanning, their adoption is expensive and hard to promote. This paper presents a deformation monitoring method for earth and rock dams based on the close-range photogrammetry technique. The proposed approach focuses on analytical algorithm the design and deployment of monitoring points, photographic schemes, camera checking and calibration, as well as deformation analysis methods. Initially, based on the analysis of the parsing algorithms’ applicability, they are fused to address the shortcomings of common image parsing methods in meeting the requirements of high precision and multi-image processing for deformation monitoring of earth and rock dams. Subsequently, the fused algorithm is introduced to analyze the acquired image data for 3D reconstruction, and the deformation in earth and rock dams is assessed based on the generated dense point cloud model. The proposed deformation monitoring method is applied to Pine Bridge Reservoir Dam, and the results demonstrated its capacity to comprehensively analyze the deformation. Furthermore, the required equipment is simple and easy to operate, aligning with the requirements for deformation monitoring accuracy of earth and rock dams.
Dual temporal attention mechanism-based convolutional LSTM model for industrial dynamic soft sensor
Authors: Cui Jiarui , Shi Yuyu , Huang Jian , Yang Xu , Gao Jingjing , Li Qing
Published: July 2024

Deep learning is an appropriate methodology for modeling complex industrial data in the field of soft sensors, owing to its powerful feature representation capability. Given the nonlinear and dynamic nature of the process industry, the key challenge for soft sensor technology is to effectively mine dynamic information from long sequences and accurately extract features of relevance to quality. A dual temporal attention mechanism-based convolutional long short-term memory network (DTA-ConvLSTM) under an encoder-decoder framework is proposed as a soft sensor model to acquire quality-relevant dynamic features from serial data. Considering different influences of process variables for prediction at multiple time steps and various locations, ConvLSTM and temporal self-attention mechanism are utilized as the encoder to adaptively fuse spatiotemporal features and capture long-term dynamic properties of process in order to capture the trends of industrial variables. Furthermore, a quality-driven temporal attention mechanism is employed throughout the decoding process to dynamically select relevant features to more accurately track quality changes. The encoder-decoder model meticulously analyses the interactions between process and quality variables by incorporating dual-sequence dynamic information to improve the prediction performance. The validity and superiority of the DTA-ConvLSTM model was validated on two industrial case studies of the debutanizer column and sulfur recovery unit. Compared to the traditional LSTM model, the proposed model demonstrated a substantial improvement with the accuracy R2 up to 97.3% and 94.9% and the root mean square error reducing to 0.122 and 0.022.
Multi-modality hierarchical attention networks for defect identification in pipeline MFL detection
Authors: Wang Gang , Su Ying , Lu Mingfeng , Chen Rongsheng , Sun Xusheng
Published: July 2024

Magnetic flux leakage (MFL) testing is widely used for acquiring MFL signals to detect pipeline defects, and data-driven approaches have been effectively investigated for MFL defect identification. However, with the increasing complexity of pipeline defects, current methods are constrained by the incomplete information from single modal data, which fail to meet detection requirements. Moreover, the incorporation of multimodal MFL data results in feature redundancy. Therefore, the multi-modality hierarchical attention networks (MMHAN) are proposed for defect identification. Firstly, stacked residual blocks with cross-level attention module (CLAM) and multiscale 1D-CNNs with multiscale attention module are utilized to extract multiscale defect features. Secondly, the multi-modality feature enhancement attention module (MMFEAM) is developed to enhance critical defect features by leveraging correlations among multimodal features. Lastly, the multi-modality feature fusion attention module (MMFFAM) is designed to dynamically integrate multimodal features deeply, utilizing the consistency and complementarity of multimodal information. Extensive experiments were conducted on multimodal pipeline datasets to assess the proposed MMHAN. The experimental results demonstrate that MMHAN achieves a higher identification accuracy, validating its exceptional performance.
Noncontact measurement of rectangular splines shaft based on line-structured light
Authors: Liu Siyuan , Li Honglin , Wang Conghui , Lian Fenghui , Miao Jianwei , Hu Zhengyi
Published: July 2024

The rectangular spline shaft, a typical type of shaft-tooth component, plays a significant role in mechanical transmissions. Existing methods for detecting size and positional tolerance in spline shafts often rely on contact-based measurement techniques, including specialized gauges and coordinate measuring machines (CMMs). To enhance the measurement efficiency, this paper proposes a method for measuring based on line-structured light. Firstly, a classification algorithm for data points on major and minor cylindrical surfaces and keyway surface of spline shaft is established, contributing to the automatic measurement. Secondly, a coaxiality error measurement model is established based on the overall least squares method, improving the measurement accuracy. Finally, a measurement model for key width and positional tolerance is established through the rotation of the spline axis. In experiments, the size and positional tolerance of the spline shaft obtained using this method are compared with measurements by CMM, meeting the general machining accuracy requirements.
EFS-YOLO: a lightweight network based on steel strip surface defect detection
Authors: Chen Beilong , Wei Mingjun , Liu Jianuo , Li Hui , Dai Chenxu , Liu Jinyun , Ji Zhanlin
Published: July 2024

With the advancement of deep learning technologies, industrial intelligent detection algorithms are gradually being applied in practical steel surface defect detection. Addressing the issues of high computational resource consumption and poor detection performance faced by existing models in large-scale industrial production lines, this paper proposes an EFS-YOLO (Efficient-Fast-Shared-YOLO) model based on improved YOLOv8s architecture. Firstly, the EfficientViT is employed as the feature extraction network, effectively reducing the model’s parameters and calculations while enhancing its capability to represent defect features. Secondly, the designed lightweight C2f-Faster-EffectiveSE Block (CFE-Block) was integrated into the model neck, accelerating feature fusion and better preserving detailed defect features at lower levels. Finally, the model detection head was reconstructed using the concept of shared parameters to address the high computational cost of the original detection head. Experimental results on the NEU-DET and GC10-DET datasets demonstrate that compared to the baseline model, the proposed model achieves a reduction in parameters, calculations and size by 49.5%, 62.7% and 46.9% respectively. It also exhibits an improvement in accuracy by 2.4% and 2.3% on the two datasets. The EFS-YOLO model effectively enhances precision in steel surface defect detection while maintaining lightweight characteristics, offering superior performance.