bluuebunny/crossref_metadata_2025 huggingface dataset:
Stellar evolution models with overshooting based on 3-equation non-local theories
Authors: Kupka F. , Ahlborn F. , Weiss A.
Published: November 2022

Context.Mixing by convective overshooting has long been suggested to play an important role in the amount of hydrogen available for nuclear burning in convective cores of stars. The best way to model this effect is still debated.

Aims.We suggest an improved model for the computation of the dissipation rate of turbulent kinetic energy which can be used in non-local models of stellar convection and can readily be implemented and self-consistently used in 1D stellar evolution calculations.

Methods.We review the physics underlying various models to compute the dissipation rate of turbulent kinetic energy,ϵ, in local models of convection in stellar astrophysics and particularly in non-local ones. The different contributions to the dissipation rate and their dependence on local stratification and on non-local transport are analysed and a new method to account for at least some of these physical mechanisms is suggested.

Results.We show how the new approach influences predictions of stellar models of intermediate-mass main-sequence stars and how these changes differ from other modifications of the non-local convection model that focus on the ratio of horizontal to vertical (turbulent) kinetic energy.

Conclusions.The new model is shown to allow for a physically more complete description of convective overshooting and mixing in massive stars. Dissipation by buoyancy waves is found to be a key ingredient which has to be accounted for in non-local models of turbulent convection.
Photometric redshift estimation of strongly lensed galaxies
Authors: Langeroodi Danial , Sonnenfeld Alessandro , Hoekstra Henk , Agnello Adriano
Published: November 2022

Context.Around 105strongly lensed galaxies are expected to be discovered with upcoming wide-field surveys such asEuclidand the LSST. Utilising these large samples to study the inner structure of lens galaxies requires source redshifts, which are needed to turn lens models into mass measurements. However, obtaining spectroscopic source redshifts for large samples of strong lenses is prohibitive with the current capacity of spectroscopic facilities.

Aims.As an alternative to spectroscopy, we study the possibility of obtaining source photometric redshifts (photo-zs) for large samples of strong lenses. We pay particular attention to the problem of blending between the lens and the source light.

Methods.Our strategy consists of deblending the source and lens light by simultaneously modelling the lens galaxy and the background source in all available photometric bands, and then feeding the derived source colours to a template-fitting photo-zalgorithm. We describe the lens and the source light with a Sérsic profile, and the lens mass with a singular isothermal ellipsoid. We first test our approach on a simulated sample of lenses. Then, we apply it to 23 real systems with broad-band photometry from the Hyper Suprime-Cam survey.

Results.We identify the deviations of the lens light from a Sérsic profile and the contrast between the lens and source image as the main drivers of the source colour measurement error. Although the former is challenging to measure directly for real lenses, we find the latter to be sufficient for evaluating the accuracy of a measured source colour. We split the real sample based on the ratio Λ of the lens to source surface brightness measured at the image locations. In the Λ < 1 regime, the photo-zoutlier fraction is 20%, and the accuracy of photo-zestimation is limited by the performance of the template-fitting process. In the opposite regime, the photo-zoutlier fraction is 75%, and the errors from the source colour measurements dominate the photo-zuncertainty.

Conclusions.Measuring source photo-zs for lenses with Λ < 1 poses no particular challenges compared to the isolated galaxy case. For systems with significant lens light contamination, however, improvements in the description of the surface brightness distribution of the lens are required: a single Sérsic model is not sufficiently accurate.
Differences between two sequential uncemented stem sizes in total hip arthroplasty: A comparative biomechanical study and potential clinical implications
Authors: Wang Katherine , Kenanidis Eustathios , Suleman Khurram , Miodownik Mark , Avadi Mahsa , Horne David , Thompson Jonathan , Tsiridis Eleftherios , Moazen Mehran
Published: November 2022

Background: Early failure of uncemented femoral stems associated with incorrect sizing is a known postoperative complication. Surgeons are often faced with the question of whether an uncemented stem of adequate stability or a larger-sized stem should be implanted, especially when the proximal femoral cancellous bone is adequate. The biomechanical effect of sub-optimal stem sizing in the femur remains unclear. This study investigated the mechanical behaviour of two sequential sized uncemented stems of the same type. Methods: Six laboratory models of synthetic non-osteoporotic femora were randomly divided into two groups and implanted with either a nominal or oversized uncemented hydroxyapatite-coated nonporous titanium collarless stem. Stiffness, uniaxial strain, and pattern of strain distribution were measured under an anatomical one-legged stance. Results: Oversized stems demonstrated a higher overall stiffness compared to nominal; however, this was not statistically significant. The nominal stem showed a higher strain in the neck and the proximal medial diaphyseal region. The oversized stem showed higher strains in the distal region around the implant tip. Conclusion: Opting to use a larger stem may potentially increase primary stability, thus allowing safer early mobility. However, higher stiffness may lead to stress shielding, bone loss, and thigh pain in the long term. In addition, strains in the diaphysis and the tip of the stem may predispose to periprosthetic fractures, especially in osteoporotic bones, making this a relatable aspect for users and biomechanical loading. Given the wide range of complex factors that need to be considered when choosing stem size in uncemented THA surgery, this study’s results should be interpreted cautiously.
Noninvasive thermal sensors measure skin physiology
Authors: Piccone Ashley
Published: November 2022

Sensing technology provides quantitative characterization of blood flow, hydration, perfusion, skin temperature, and thermal transport properties.
Magnetic nanobubbles could zap away brain cancer
Authors: Johnson-Groh Mara
Published: November 2022

A specific design of magnetic nanobubbles has shown promise in treating glioblastoma through hyperthermia.
Stability and convergence of dynamical decoupling with finite amplitude controls
Authors: Burgarth Daniel , Facchi Paolo , Hillier Robin
Published: November 2022

Dynamical decoupling is a key method to mitigate errors in a quantum mechanical system, and we studied it in a series of papers dealing, in particular, with the problems arising from unbounded Hamiltonians. The standard bangbang model of dynamical decoupling, which we also used in those papers, requires decoupling operations with infinite amplitude, which is, strictly speaking, unrealistic from a physical point of view. In this paper, we look at decoupling operations of finite amplitude, discuss under what assumptions dynamical decoupling works with such finite amplitude operations, and show how the bangbang description arises as a limit, hence justifying it as a reasonable approximation.
Mass-resolved ion measurement by particle counting analysis for characterizing relativistic ion beams driven by lasers
Authors: Minami T. , Tokiyasu A. O. , Kohri H. , Abe Y. , Iwasaki K. , Taguchi T. , Oda K. , Suzuki S. , Asai T. , Tanaka S. J. , Isayama S. , Kanasaki M. , Kodaira S. , Fukuda Y. , Kuramitsu Y.
Published: November 2022

Particle counting analysis is a possible way to characterize GeV-scale, multi-species ions produced in laser-driven experiments. We present a multi-layered scintillation detector to differentiate multi-species ions of different masses and energies. The proposed detector concept offers potential advantages over conventional diagnostics in terms of (1) high sensitivity to GeV ions, (2) realtime analysis, and (3) the ability to differentiate ions with the same charge-to-mass ratio. A novel choice of multiple scintillators with different ion stopping powers results in a significant difference in energy deposition between the scintillators, allowing accurate particle identification in the GeV range. Here, we report a successful demonstration of particle identification for heavy ions, performed at the Heavy Ion Medical Accelerator in Chiba. In the experiment, the proposed detector setup showed the ability to differentiate particles with similar atomic numbers, such as C6+ and O8+ ions, and provided an excellent energy resolution of 0.41%–1.2% (including relativistic effect, 0.51%--1.6%).
Adaptive segmentation method in radiographic testing for turbine blades based on spatial entropy
Authors: Shang Zhongyu , Li Bing , Chen Lei , Zhang Lei
Published: November 2022

During the radiographic testing with multiple voltage exposures, the problem of image redundancy has serious influences on the speed of analysis. In this paper, by the calculation of spatial entropy and the extraction of microtopography features, a new segmentation method for an unpredictable free-form surface in turbine blades is presented to reduce the testing redundancy. First, the entropy calculation is applied to a set of radiography images of the target object. The optimized image for surface segmentation is determined according to global entropy values and exposure parameters. Then, the obtained image is set as the reference image for the segmentation process. Through the spatial entropy calculation, the reference radiographic image is divided into several regions by geometric features of the tested object. The different thickness range of free-form surfaces is indicated by those regions through the analysis of spatial entropy distribution in the reference image. By the statistical advantage of entropy calculation, the selected region is self-adaptive to the unpredictable free-form surface in the blade. A nickel-based alloy turbine blade is used to validate the segmentation method in the radiographic testing. The processed image quality is assessed by using the American Society for Testing and Materials image quality indicator to address its capability for the detection of defects, where the resolution of the image is not affected by the down-sampled effect of entropy calculation. The experimental results show that the image redundancy in the multiple exposure testing is reduced to less than 30% during the inline testing, while the dynamic range in each extracted region with an optimal image is significantly improved.
The MagneDyn beamline at the FERMI free electron laser
Authors: Malvestuto Marco , Caretta Antonio , Bhardwaj Richa , Laterza Simone , Parmigiani Fulvio , Gessini Alessandro , Zamolo Matteo , Galassi Fabio , Sergo Rudi , Cautero Giuseppe , Danailov Miltcho B. , Demidovic Alexander , Sigalotti Paolo , Lonza Marco , Borghes Roberto , Contillo Adriano , Simoncig Alberto , Manfredda Michele , Raimondi Lorenzo , Zangrando Marco
Published: November 2022

The scope of this paper is to outline the main marks and performances of the MagneDyn beamline, which was designed and built to perform ultrafast magnetodynamic studies in solids. Open to users since 2019, MagneDyn operates with variable circular and linear polarized femtosecond pulses delivered by the externally laser-seeded FERMI free-electron laser (FEL). The very high degree of polarization, the high pulse-to-pulse stability, and the photon energy tunability in the 50–300 eV range allow performing advanced time-resolved magnetic dichroic experiments at the K-edge of light elements, e.g., carbon and at the M- and N-edge of the 3d-transition-metals and rare earth elements, respectively. To this end, two experimental end-stations are available. The first is equipped with an in situ dedicated electromagnet, a cryostat, and an extreme ultraviolet Wollaston-like polarimeter. The second, designed for carry-in user instruments, hosts also a spectrometer for pump-probe resonant x-ray emission and inelastic spectroscopy experiments with a sub-eV energy resolution. A Kirkpatrick-Baez active optics system provides a minimum focus of ∼20×20μm2 FWHM at the sample. A pump laser setup, synchronized with the FEL-laser seeding system, delivers sub-picosecond pulses with photon energies ranging from the mid-IR to near-UV for optical pump-FEL probe experiments with a minimal pump-probe jitter of few femtoseconds. The overall combination of these features renders MagneDyn a unique state-of-the-art tool for studying ultrafast magnetic and resonant emission phenomena in solids.
Spontaneous exchange bias and large dielectric constant in Bi0.8Tb0.2Fe0.8Mn0.2O3 multiferroic
Authors: Kumari Seema , Anand Khyati , Alam Mohd , Ghosh Labanya , Ghosh Swayangsiddha , Gupta Prince , Singh Rahul , Jain A. K. , Yusuf S. M. , Ghosh Anup K. , Mohan Anita , Chatterjee Sandip
Published: November 2022

The structural, dielectric, and magnetic properties of Bi0.8Tb0.2Fe0.8Mn0.2O3 have been studied in detail. A structural shift from rhombohedral (space group R3c) to orthorhombic (space group Pn21a + Pnma) phase is observed with doping. The substitution of Mn and Tb gives a very large value of the dielectric constant. It has been demonstrated that the observed spontaneous exchange bias is larger than the conventional exchange bias at room temperature. Moreover, doping reduces the Neel temperature from 643 to 521 K and magnetization increases. Thermoremanent magnetization studies at room temperature show that the system is composed of an interfacial layer of an antiferromagnetic core and a two-dimensional diluted antiferromagnet shell with a net magnetization under the field. Furthermore, the system's reasonable HEB and HC values at room temperature make it intriguing and appealing for a variety of multifunctional devices.
Continuous wave operation of terahertz metasurface quantum-cascade VECSEL with a long intra-cryostat cavity
Authors: Wu Yu , Curwen Christopher A. , Hayton Darren J. , Reno John L. , Williams Benjamin S.
Published: November 2022

We report continuous wave (cw) operation of a terahertz quantum-cascade vertical-external-cavity surface-emitting laser with an external cavity length of approximately 30 mm, benefited by an intra-cryostat focusing cavity. Compared to previous plano–plano cavities, an off-axis paraboloid mirror is introduced into the external cavity as a focusing element to reduce the diffraction loss and to enable cw lasing using small-area metasurfaces and long cavity lengths. The device shows lasing operation in the cw mode up to 111 K, and cw output power up to 11.5 mW at 77 K (0.5% wall-plug efficiency). A circular, directive beam pattern is collected, and free-running linewidths on the order of tens of kHz are measured over tens of seconds.
0.342 nW Class-AB enhanced flipped source follower low pass filter for biomedical applications
Authors: Thakur Diksha , Sharma Kulbhushan
Published: November 2022

Owing to the impact of process voltage and temperature variations, the design of low-power low-pass filters (LPFs) with improved linearity is still one of the most challenging tasks for effective biological signal processing. This paper presents the design of a fourth-order Class-AB enhanced flipped source follower (EFSF) LPF circuit aimed at the detection of electroencephalography signals. The simulated results attained using complementary metal–oxide–semiconductor 180 nm technology node in Cadence Analog Design Environment demonstrate that the EFSF LPF emulates a DC-gain of −88 mdB with a bandwidth of 100 Hz and consumes 0.342 nW power from a supply voltage of 0.5 V. The calculated figure of merit for the proposed filter is 5.983 × 10−15 J with a dynamic range (DR) of 43.54 dB and input-referred noise of 91 µVrms. It consumes an area of 0.0458 mm2. To check the robustness of the proposed filter circuit, we performed Monte Carlo simulations with 200 runs. The statistical results achieved for the DC-gain, DR, and total harmonic distortion of the proposed filter show mean values of −188.09 mdB, 43.10 dB, and −41.85 dB along with standard deviation values of 285.21 mdB, 718.72 mdB, and 4.52 dB, respectively. The proposed Class-AB EFSF LPF can be used to achieve high power efficiency in future low-voltage and low-power biological systems.
Deep convolutional neural networks for generating atomistic configurations of multi-component macromolecules from coarse-grained models
Authors: Christofi Eleftherios , Chazirakis Antonis , Chrysostomou Charalambos , Nicolaou Mihalis A. , Li Wei , Doxastakis Manolis , Harmandaris Vagelis A.
Published: November 2022

Despite the modern advances in the available computational resources, the length and time scales of the physical systems that can be studied in full atomic detail, via molecular simulations, are still limited. To overcome such limitations, coarse-grained (CG) models have been developed to reduce the dimensionality of the physical system under study. However, to study such systems at the atomic level, it is necessary to re-introduce the atomistic details into the CG description. Such an ill-posed mathematical problem is typically treated via numerical algorithms, which need to balance accuracy, efficiency, and general applicability. Here, we introduce an efficient and versatile method for backmapping multi-component CG macromolecules of arbitrary microstructures. By utilizing deep learning algorithms, we train a convolutional neural network to learn structural correlations between polymer configurations at the atomistic and their corresponding CG descriptions, obtained from atomistic simulations. The trained model is then utilized to get predictions of atomistic structures from input CG configurations. As an illustrative example, we apply the convolutional neural network to polybutadiene copolymers of various microstructures, in which each monomer microstructure (i.e., cis-1,4, trans-1,4, and vinyl-1,2) is represented as a different CG particle type. The proposed methodology is transferable over molecular weight and various microstructures. Moreover, starting from a specific single CG configuration with a given microstructure, we show that by modifying its chemistry (i.e., CG particle types), we are able to obtain a set of well equilibrated polymer configurations of different microstructures (chemistry) than the one of the original CG configuration.
Simulation of liquid jet atomization and droplet breakup via a Volume-of-Fluid Lagrangian–Eulerian strategy
Authors: Kuo Chia-Wei , Trujillo Mario F.
Published: November 2022

The hybrid Volume-of-Fluid and Lagrangian–Eulerian (VoFLE) strategy is an attractive approach for reducing the computational cost of spray simulations while retaining a reasonable amount of fidelity. It is based on the concept of transitioning small liquid bodies or droplets to a Lagrangian–Eulerian (LE) representation, alleviating the burden of maintaining high resolution for small droplets. This hybrid VoFLE methodology is extended in the present work by incorporating a hydrodynamic breakup model based on maximum entropy formalism (MEF). This approach is particularly suitable for realistic spray conditions, such as high-pressure fuel injectors, where adequate numerical resolution of the smallest droplets is extremely difficult. The first step in the present VoFLE treatment is the identification of unresolved liquid structures targeted for LE transition. This step is followed by the application of the MEF breakup model for those structures that are hydrodynamically unstable, resulting in the assignment of secondary drop sizes and velocities. The model is evaluated statistically and tested against experimental data from the Engine Combustion Network and the breakup of a water jet. Relatively favorable results are encountered in these tests.
Confinement of Bose–Einstein magnon condensates in adjustable complex magnetization landscapes
Authors: Schweizer Matthias R. , Kreil Alexander J. E. , von Freymann Georg , Hillebrands Burkard , Serga Alexander A.
Published: November 2022

Coherent wave states such as Bose–Einstein condensates (BECs), which spontaneously form in an overpopulated magnon gas even at room temperature, have considerable potential for wave-based computing and information processing at microwave frequencies. The ability to control the transport properties of magnon BECs plays an essential role in their practical use. Here, we demonstrate the spatiotemporal control of the BEC density distribution through the excitation of magnon supercurrents in an inhomogeneously magnetized yttrium iron garnet film. The BEC is created by microwave parametric pumping and probed by Brillouin light scattering spectroscopy. The desired magnetization profile is prepared by heating the film with optical patterns projected onto its surface using a phase-based wavefront modulation technique. Specifically, we observe a pronounced spatially localized magnon accumulation caused by magnon supercurrents flowing toward each other originating in two heated regions. This accumulation effect increases the BEC lifetime due to the constant influx of condensed magnons into the confinement region. The shown approach to manipulate coherent waves provides an opportunity to extend the lifetime of freely evolving magnon BECs, create dynamic magnon textures, and study the interaction of magnon condensates formed in different regions of the sample.
A tunable microwave circulator based on a magnetized plasma as an active gyrotropic element
Authors: Mehrpour Bernety Hossein , Houriez Luc S. , Rodríguez Jesse A. , Wang Benjamin , Cappelli Mark A.
Published: November 2022

We present a theoretical analysis and experimental demonstration of a microwave circulator that uses a magnetized plasma as the gyrotropic element. Unlike traditional circulators that exploit the anisotropic permeability of ferrite, here, we exploit the anisotropic dielectric constant of a magnetized plasma to achieve non-reciprocity. The advantage of a plasma-loaded circulator is that it allows for tunability, and modulation that is limited in speed by the ionization/recombination time of the plasma. The theoretical analysis treats the problem of electromagnetic scattering from a heterogeneous gyrotropic plasma rod to confirm scattering behavior and to guide in defining the design parameter space covered by more detailed computational simulations. Proof-of-concept experiments are carried out using a custom-fabricated low-frequency gas discharge tube as the plasma element. Here, we confirm the plasma-frequency dependent tunability predicted by the simulations, demonstrating this tunability in the experiments by varying the applied discharge voltage. These initial experiments suggest that isolation in excess of 25 dB is achievable, in reasonable agreement with the theory and simulations for studies in the S and C ranges of the microwave spectrum.
Physico-chemical elucidation of the mechanism involved in optical lithography: Micro-fabrication of 2D and 3D platforms
Authors: Philipp N. , Angriman S. , Burne S. , Caral P. , Gómez Florenciano I. , Rapagnani N. , Gabriel M. , Estrada L. C.
Published: November 2022

Direct laser lithography has attracted much attention as a convenient micro-fabrication method to develop rapid, free-form, and low-cost microstructures. In this work, different microdevices were fabricated using a home-made two-photon excitation microscope and a commercial negative UV photoresin. The mechanism involved during the fabrication of the devices as well as the effects of the irradiation intensity and removal time on micro-patterns was investigated by optical microscopy. For the characterization of the microstructures, scanning electron microscopy, atomic force microscopy, Nuclear Magnetic Resonance (1H-NMR), and Fourier transform infrared spectroscopy were used. High-resolution optical characterization shows an enormous uniformity and high reproducibility of fabricated platforms in two and three dimensions. These results prompted us to propose a different mechanism not compatible with a polymerization reaction as the triggering mechanism for the interaction between light and the photoresin. We demonstrate the coexistence of an allylic photo-induced reaction with a photo-induced polymerization effect during the fabrication process. We studied the influence of these mechanisms by fabricating micro-patterns in two conditions, with and without the presence of a polymerization initiator [azobisisobutyronitrile (AIBN)], which boots the polymerization reaction. Even though the two mechanisms are present during the fabrication process, the polymerization is dominant in the presence of a photo-initiator as AIBN. Finally, we discuss the applications of our microdevices as suitable platforms for industry and biomedical applications.
Measurement method of aero-engine rotor concentricity and perpendicularity based on deep belief neural network
Authors: Sun Chuanzhi , Liu Wentao , Cheng Hanwen , Liu Yongmeng , Tan Jiubin
Published: November 2022

When implementing the traditional assembly method, the rotor is affected by machining errors. The morphology of the rotor is complex, and the machining error of the rotors at all levels are transmitted step by step through the stop mating surface, which affects the performance and service life of the aero-engine. The evaluation of machining error of single-stage rotor is the basis of assembly quality of multi-stage rotor. In order to improve the current situation of complicated and time-consuming rotor machining error evaluation, this paper proposes to establish a deep belief neural network (DBNN) to replace the traditional procedure of depolarization. The network takes the relative evaluation error of the rotor profile data without depolarization as the input and takes the machining error of the rotors obtained after depolarization as the output. First, the evaluation mechanism of the rotor’s machining error is analyzed, and the corresponding machining error influence source is selected as the input source of the deep belief neural network. Second, as DBNN is trained, and the appropriate weight initialization method and the optimization algorithm of the prediction network are selected to ensure the optimization of the whole network for feature mapping extraction of the training set. Finally, the assembly of multi-stage rotors is simulated and analyzed. It is shown in the experiments that after the iteration, the prediction network, with good training effects, has converged, and its prediction results tend to be consistent with the real values. The mean prediction error of the concentricity is 0.09 µm while the mean difference of angle of concentricity error value is 0.77°, and the mean difference of perpendicularity error value is 0.21 µm while the mean difference of angle of perpendicularity error value is 1.4°, the corresponding R2 determination coefficients were 0.99, 0.98, 0.91, and 0.94, respectively. It meets the requirements of field assembly and fully embodies the effectiveness of the procedure of depolarization based on deep confidence neural network.
Transition-metal ions in β-Ga2O3 crystals: Identification of Ni acceptors
Authors: Gustafson T. D. , Giles N. C. , Holloway B. C. , Jesenovec J. , Dutton B. L. , McCloy J. S. , McCluskey M. D. , Halliburton L. E.
Published: November 2022

Transition-metal ions (Ni, Cu, and Zn) in β-Ga2O3 crystals form deep acceptor levels in the lower half of the bandgap. In the present study, we characterize the Ni acceptors in a Czochralski-grown crystal and find that their (0/−) level is approximately 1.40 eV above the maximum of the valence band. Both Ni2+ (3d8) and Ni3+ (3d7) acceptors are present in the as-grown crystal. Also present are unintentional Ir3+ (5d6) and Ir4+ (5d5) donors. The neutral Ni3+ acceptors have a low-spin S = 1/2 ground state and are easily monitored with electron paramagnetic resonance (EPR). Principal values of the g matrix for these acceptors are 2.131, 2.138, and 2.233. Although paramagnetic, the singly ionized Ni2+ acceptors are not seen with EPR at X band (9.4 GHz). The Ir4+ donors are monitored with EPR and with infrared absorption spectroscopy. Exposing the Ni-doped β-Ga2O3 crystal to 275 nm light at room temperature increases the concentration of Ni3+ ions and reduces the concentration of Ir4+ ions as electrons move from the acceptors to the donors. After illumination, heating the crystal above 375 °C restores the initial concentrations of the Ni3+ and Ir4+ ions. Broad optical absorption bands peaking near 303 and 442 nm are attributed to the Ni3+ acceptors.
Laminar–turbulent intermittency in pipe flow for an Herschel–Bulkley fluid: Radial receptivity to finite-amplitude perturbations
Authors: Charles Antoine , Romanò Francesco , Ribeiro Thierry , Azimi Sam , Rocher Vincent , Baudez Jean-Christophe , Bahrani S. Amir
Published: November 2022

We investigate the laminar-to-turbulent transition for non-Newtonian Herschel–Bulkley fluids that exhibit either a shear-thinning or shear-thickening behavior. The reduced-order model developed in this study also includes the effect of yield-stress for the fluid. Within our model framework, we investigate how the Newtonian dynamics change when significant non-Newtonian effects are considered either via the flow index n or the yield-stress τ0 or both. We find that an increase in τ0 as well as a decrease in n lead to a delayed transition if a perturbation of the given turbulent intensity is injected at various radial locations. As the radial position of the injection for the perturbation is varied in this study, our reduced-order model allows for the investigation of the flow receptivity to the finite-amplitude perturbations and to their radial position of inception. We observe that, for a given mean flow profile, the same perturbation becomes more prone to induce turbulence the closer it approaches the wall because of its initial amplitude being relatively higher with respect to the local mean flow. An opposite trend is found when the perturbation amplitude is rescaled on the local mean flow.
Evaluation of feed efficiency traits in different Hereford populations and their effect on variance component estimation
Authors: Pravia Maria Isabel , Navajas Elly Ana , Aguilar Ignacio , Ravagnolo Olga
Published: November 2022

Context Residual feed intake is a relevant trait for beef cattle, given the positive impact on reducing feeding costs and greenhouse gas emissions. The lack of large databases is a restriction when estimating accurate genetic parameters for dry matter intake (DMI) and residual feed intake (RFI), and combining different data sets could be an alternative to increase the amount of data and achieve better estimations. Aim The main objective was to compare Uruguayan data (URY; 780 bulls) and Canadian data (CAN; 1597 bulls), and to assess the adequacy of pooling both data sets (ALL) for the estimation of genetic parameters for DMI and RFI. Methods Feed intake and growth traits phenotypes in both data sets were measured following the same protocols established by the Beef Improvement Federation. Pedigree connections among data sets existed, but were weak. Performance data were analysed for each data set, and individual partial regression coefficients for each energy sink on DMI were obtained and compared. Univariate and multivariate variance components were estimated by the restricted maximum likelihood (REML) for DMI, RFI and their energy sinks traits (average daily gain, metabolic mid weight and back fat thickness). Key results There were some differences in phenotypic performance among data (P < 0.01); however, no differences (P > 0.1) were observed for phenotypic values of RFI between sets. Heritability estimates for DMI were 0.42 (URY), 0.41 (CAN) and 0.45 for ALL data, whereas heritability estimates for RFI were 0.34 (URY), 0.20 (CAN) and 0.25 for ALL data. The results obtained indicate selection on reducing RFI could lead to a decrease in DMI, without compromising other performance traits, as genetic correlations between RFI, growth and liveweight were low or close to 0 (−0.12–0.07). Conclusions As genetic parameters were similar between national data sets (URY, CAN), pooling data (ALL) provided more accurate parameter estimations, as they presented smaller standard deviations, especially in multivariate analysis. Implications Parameters estimated here may be used in international or national genetic evaluation programs.
It is time for a more targeted approach to prediabetes in primary care in Aotearoa New Zealand
Authors: Barthow Christine , Pullon Sue , McKinlay Eileen , Krebs Jeremy
Published: November 2022

Type 2 diabetes (T2DM), its related morbidities and entrenched diabetes‐related inequities pose significant challenges for health care delivery systems in Aotearoa New Zealand (NZ). Primary care services undertake the majority of diabetes prevention work by initially detecting and managing those with prediabetes. In this viewpoint, we present available NZ data to highlight NZ trends in prediabetes and consider the current NZ clinical guidelines and the prediabetes care pathway. Multiple areas for improvement are identified to optimise diabetes prevention, potentially reduce T2DM inequities, and sustain more effective prediabetes management in primary care in NZ.
Australian sexually transmitted infection (STI) management guidelines for use in primary care 2022 update
Authors: Ong Jason J. , Bourne Christopher , Dean Judith A. , Ryder Nathan , Cornelisse Vincent J. , Murray Sally , Kenchington Penny , Moten Amy , Gibbs Courtney , Maunsell Sarah , Davis Tyler , Michaels Jessica , Medland Nicholas A.
Published: November 2022

The ‘Australian Sexually Transmitted Infection (STI) Management Guidelines For Use In Primary Care’ (www.sti.guidelines.org.au) provide evidence-based, up-to-date guidance targeted at use in primary care settings. A major review of the guidelines was undertaken in 2020–22. All content was reviewed and updated by a multi-disciplinary group of clinical and non-clinical experts, and assessed for appropriateness of recommendations for key affected populations and organisational and jurisdictional suitability. The guidelines are divided into six main sections: (1) standard asymptomatic check-up; (2) sexual history; (3) contact tracing; (4) STIs and infections associated with sex; (5) STI syndromes; and (6) populations and situations. This paper highlights important aspects of the guidelines and provides the rationale for significant changes made during this major review process.
A plant-specific bridging adaptor for amphisome biogenesis
Authors: Koestel Jérôme , Batoko Henri
Published: November 2022

The fusion of autophagosomes with endocytic compartments to form amphisomes has only been described in metazoans. In this issue, Zhao et al. (2022. J. Cell Biol.https://doi.org/10.1083/jcb.202203139) demonstrate the existence of amphisomes in the plant cell and identify a plant-specific adaptor protein, CFS1, that mediates their biogenesis.
Remote actuation based on magnetically responsive pillar arrays
Authors: Jiang Wei , Wang Lanlan , Chen Bangdao , Liu Hongzhong
Published: November 2022

Smart actuators, integrated with high aspect-ratio structures and stimuli-responsive materials, can take more diverse tasks skillfully. Although great advances have been achieved over the past few years, it is still difficult in manipulating the small objects such as the transporting and grasping them under the remote untethered condition. Inspired by the ciliary structures on biological organs, a magnetically responsive actuator with hierarchical pillars on the surface of the film is designed and proposed, which allows active, fast, and dynamic manipulation over the force and speed of a small object by taking an external magnetic field. Magnetic pillars of different morphologies were fabricated by a modified soft lithographic method involving inking and imprinting processes. The magnetic-force conversion unit was constructed by magnetically responsive pillar arrays. Upon applying an external magnetic field, these pillars can rhythmically bend and recover in a controlled manner, and the generated force can be used to drive the small object to move or capture the small object. All these was further addressed from experimental and theoretical perspectives. This magnetically responsive actuator demonstrates reliable actuating performance with instant field responses. No complex mechanical and electrical control systems are required. Thus, the combined use of high aspect-ratio structures and stimuli-responsive materials will facilitate many other applications such as surface engineering, soft actuators and robotics in the future.
Photothermal investigation for optimizing a lattice strain relaxation condition of InGaAs/GaAsP superlattice photovoltaic structures from a nonradiative transition point of view
Authors: Fukuyama Atsuhiko , Yamamoto Naoki , Furukawa Ryo , Sugiyama Masakazu , Ikari Tetsuo
Published: November 2022

The carrier collection efficiencies of InGaAs/GaAsP superlattice (SL) photovoltaic structures were optimized by choosing adequate manufacturing parameters, such as the composition and thickness of the quantum wells (QWs) and barrier layers. However, no insights have been observed from the viewpoint of the nonradiative transition of photoexcited carriers. In this study, piezoelectric photothermal (PPT) and photoluminescence (PL) measurements were performed as a function of temperature from 100 to 340 K. Using a piezoelectric transducer, the PPT signal detected the heat generated by nonradiative recombination (NR). The indium composition of the QW layer was fixed at 0.3, and the phosphorus composition x[P] in the barrier layer was changed from 0.4 to 0.6. The observed temperature dependences of the PPT and PL signal intensities were analyzed using a rate equation for the photoexcited carriers in e1 and hh1 quantized levels. Four carrier dissipating processes, namely, radiative recombination, NR, thermal escape from the QW thermal excitation (TE), and tunneling after thermal excitation (TATE), were considered for both electrons and holes. Thermal activation energies were included in the NR, TE, and TATE processes. Because nonradiative and radiative transition components cause PPT and PL signals, curve fitting of the temperature behavior enabled us to determine the activation energies. We then found that the activation energy of the NR process reached a maximum at x[P] = 0.45. No such maxima were observed for the TE and TATE process. This result was explained by a trade-off between the strain valance condition over the entire range of the SL structure and the local residual strain at the interfaces between the QW, interlayer, and barrier layer when x[P] increased. Because no software can theoretically calculate the activation energy of the NR process, we demonstrated the usefulness of the present PPT experimental methodology for investigating carrier transport properties.
Adaptive progressive learning stochastic resonance for weak signal detection
Authors: Zong Ping , Men Yubo , An Ran , Wang Hongyu
Published: November 2022

Stochastic resonance (SR) can enhance signals by using noise. This has attracted more attention in the field of weak signal detection. In practical applications, owing to the non-adjustability of noisy signals, SR is required to adjust the system parameters adaptively to satisfy the conditions of the SR phenomenon. In this paper, an adaptive progressive learning SR method is proposed to improve the detection ability for weak signal, and the SR phenomenon is quantitatively defined. A theoretical learning framework is established with an improved reinforcement learning model by mapping the nonlinear system parameter space to a progressive learning set. By selecting a proper learning layer within a determined constraint range, the matching system parameters can be quickly and accurately searched to generate a desired optimal output. Numerical simulation results show that the signal energy and the output signal-to-noise ratio (SNR) can be enhanced significantly, which reflects an excellent weak signal detection performance especially for low SNR conditions. Finally, a diagnosis of the outer race fault signals of a rolling bearing confirms that the proposed method can effectively detect fault characteristics.
Support vector machine fault diagnosis based on sparse scaling convex hull
Authors: Renwang Song , Baiqian Yu , Hui Shi , Lei Yang , Zengshou Dong
Published: November 2022

In solving the problems encountered when implementing support vector machine (SVM) fault diagnosis, the convex-hull-covering model of the dataset cannot reflect the effective distribution of the samples, and the fault identification accuracy of the original high-dimensional feature set is low. A sparse scaling convex-hull based SVM classification method is proposed and applied to the fault diagnosis of roller bearings. The dimensionality reduction of the features of the sample set is carried out by the random forest (RF) algorithm. First, the optimized sample subsets are obtained by sparse approximation, and the reduction coefficient of the convex hull of the optimized sample set is adjusted, hence the convex hulls of various sample sets are linearly separable. Second, to solve the problem of low fault recognition accuracy of the original high-dimensional feature set, the importance of features is evaluated by RF, and some redundant features are removed. Finally, the SVM model is constructed by the closest points between the convex hulls. Through fault diagnosis on two different bearing datasets, the experimental results and related theories show that the proposed method has high performance in bearing fault diagnosis.
A multi-channel data-based fault diagnosis method integrating deep learning strategy for aircraft sensor system
Authors: Jia Zhen , Li Yang , Wang Shengdong , Liu Zhenbao
Published: November 2022

The effectiveness and safety of an aircraft’s flight depend heavily on the flight control system. Since the attitude sensor is the weakest link, identifying its failure modes is crucial. To overcome the shortcomings of a single diagnosis model and a single input signal, this paper proposes a hybrid deep fault diagnosis model based on multi-data fusion. First, the normal and fault models of the sensor are established, and the residual timing signals of the sensor in different fault states are obtained. The frequency domain and timefrequency domain representations of the original timing signals are collected by means of fast Fourier transform and S-transform, and they are used as the input of the hybrid deep diagnosis model. The deep model is designed for the three inputs to mine the characteristics of the input data. These three deep features are concatenated and dimensionally reduced to obtain more comprehensive and representative features. Finally, the classifier is used to classify and obtain the diagnosis results. Through experiments, the advantages of the proposed method are verified by comparing it with several other methods.
Experimental characterization of a commercial TEG device under mimicked operating conditions
Authors: Bottega Andrea , Campagnoli Elena , Dongiovanni Claudio , Giaretto Valter
Published: November 2022

A long-standing zT = 1 barrier is still present in commercial thermoelectric generator devices (TEG) and is typically not overcome. Although it is possible to accept the current limits of such devices, the performances reported on the datasheets are frequently not obtainable when these thermoelectric devices are arranged for use in the actual operating conditions. Despite this, the current primary energy prices and ongoing climate change make their use attractive for many industrial sectors. An experimental investigation is here proposed on a single type of TEG available on the market; the temperature relationships of the electrical resistivity, Seebeck coefficient, and thermal conductivity in a thermostatic chamber were first determined. A piece of apparatus was assembled to mimic the operating conditions of the TEG device and verify its performance, but some critical issues were highlighted regarding the heat transfer and its ability to maintain an adequate contact pressure on the hot and cold sides of the module. In order to extend the recovery of waste heat to a non-excessively high temperature in the hot forging process, the maximum temperature attained on the hot side of the TEG in the performed experiments was not allowed to exceed 180 °C. With temperatures of around 160 °C on the hot side and just over 40 °C on the cold side, the conversion efficiency was close to 3%. Considering this conversion efficiency and the operating conditions, the estimated order of magnitude of the electricity that could be produced by recovering heat waste in the Italian hot forging sector could be in the region of some hundreds of MWh per year.
Effect of particle shape on packing fraction and velocity profiles at outlet of a silo
Authors: Gao Qing-Qing , Chen Yu-Chao , Hu Lin
Published: November 2022

Many studies on how the particle shape affects the discharge flow mainly focus on discharge rates and avalanche statistics. In this study, the effect of the particle shape on the packing fraction and velocities of particles in the silo discharge flow are investigated by using the discrete element method. The time-averaged packing fraction and velocity profiles through the aperture are systematically measured for superelliptical particles with different blockinesses. Increasing the particle blockiness is found to increase resistance to flow and reduce the flow rate. At an identical outlet size, larger particle blockiness leads to lower velocity and packing fraction at the outlet. The packing fraction profiles display evidently the self-similar feature that can be appropriately adjusted by fractional power law. The velocity profiles for particles with different shapes obey a uniform self-similar law that is in accord with previous experimental results, which is compatible with the hypothesis of free fall arch. To further investigate the origin of flow behaviors, the packing fraction and velocity field in the region above the orifice are computed. Based on these observations, the flow rate of superelliptical particles is calculated and in agreement with the simulated data.
Performance optimization on finite-time quantum Carnot engines and refrigerators based on spin-1/2 systems driven by a squeezed reservoir
Authors: Liu Haoguang , He Jizhou , Wang Jianhui
Published: November 2022

We investigate the finite-time performance of a quantum endoreversible Carnot engine cycle and its inverse operation — Carnot refrigeration cycle, employing a spin-1/2 system as the working substance. The thermal machine is alternatively driven by a hot boson bath of inverse temperature β
h and a cold boson bath at inverse temperature β
c (>β
h). While for the engine model the hot bath is constructed to be squeezed, in the refrigeration cycle the cold bath is established to be squeezed, with squeezing parameter r. We obtain the analytical expressions for both efficiency and power in heat engines and for coefficient of performance and cooling rate in refrigerators. We find that, in the high-temperature limit, the efficiency at maximum power is bounded by the analytical value

η
+

=
1
−

sech
(
2
r
)
(
1
−

η
C

)

, and the coefficient of performance at the maximum figure of merit is limited by

ε
+

=

sech
(
2
r
)
(
1
+

ε
C

)

sech
(
2
r
)
(
1
+

ε
C

)
−

ε
C

−
1

, where η
C = 1 – β
h/β
c and ε
C = β
h/(β
c – β
h) are the respective Carnot values of the engines and refrigerators. These analytical results are identical to those obtained from the Carnot engines based on harmonic systems, indicating that the efficiency at maximum power and coefficient at maximum figure of merit are independent of the working substance.