bluuebunny/crossref_metadata_2025_split huggingface dataset:
Niclosamide targets the dynamic progression of macrophages for the resolution of endometriosis in a mouse model
Authors: Zhao Liang , Shi Mingxin , Winuthayanon Sarayut , MacLean James A. , Hayashi Kanako 
Published: November 2022

AbstractDue to the vital roles of macrophages in the pathogenesis of endometriosis, targeting macrophages could be a promising therapeutic direction. Here, we investigated the efficacy of niclosamide for the resolution of a perturbed microenvironment caused by dysregulated macrophages in a mouse model of endometriosis. Single-cell transcriptomic analysis revealed the heterogeneity of macrophages including three intermediate subtypes with sharing characteristics of traditional “small” or “large” peritoneal macrophages (SPMs and LPMs) in the peritoneal cavity. Endometriosis-like lesions (ELL) enhanced the differentiation of recruited macrophages, promoted the replenishment of resident LPMs, and increased the ablation of embryo-derived LPMs, which were stepwise suppressed by niclosamide. In addition, niclosamide restored intercellular communications between macrophages and B cells. Therefore, niclosamide rescued the perturbed microenvironment in endometriosis through its fine regulations on the dynamic progression of macrophages. Validation of similar macrophage pathogenesis in patients will further promote the clinical usage of niclosamide for endometriosis treatment.
GPR55 in B cells limits atherosclerosis development and regulates plasma cell maturation
Authors: Guillamat-Prats Raquel , Hering Daniel , Derle Abhishek , Rami Martina , Härdtner Carmen , Santovito Donato , Rinne Petteri , Bindila Laura , Hristov Michael , Pagano Sabrina , Vuilleumier Nicolas , Schmid Sofie , Janjic Aleksandar , Enard Wolfgang , Weber Christian , Maegdefessel Lars , Faussner Alexander , Hilgendorf Ingo , Steffens Sabine 
Published: November 2022

AbstractDissecting the pathways regulating the adaptive immune response in atherosclerosis is of particular therapeutic interest. Here we report that the lipid G-protein-coupled receptor GPR55 is highly expressed by splenic plasma cells (PCs), upregulated in mouse spleens during atherogenesis and human unstable or ruptured compared to stable plaques.Gpr55-deficient mice developed larger atherosclerotic plaques with increased necrotic core size compared to their corresponding controls. Lack of GPR55 hyperactivated B cells, disturbed PC maturation and resulted in IgG overproduction. B-cell-specificGpr55depletion or adoptive transfer ofGpr55-deficient B cells was sufficient to promote plaque development and elevated IgG titers. In vitro, the endogenous GPR55 ligand lysophsophatidylinositol (LPI) enhanced PC proliferation, whereas GPR55 antagonism blocked PC maturation and increased their mitochondrial content. Collectively, these discoveries provide previously undefined evidence for GPR55 in B cells as a key modulator of the adaptive immune response in atherosclerosis.
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.
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.
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.
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.
Remote actuation based on magnetically responsive pillar arrays
Authors: Jiang Wei , Wang Lanlan , Chen Bangdao , Liu Hongzhong 
Published: November 2022

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.
A positioning correction method for turbine blade film cooling holes
Authors: Li Pengfei , Guo Jianmei , Cai Yanhua , Wu Dongbo , Liang Jiawei , Wang Hui , Han Xiao 
Published: November 2022

Abstract
It is significant to improve the machining accuracy of film cooling holes on aero-engine turbine blades. This paper presents a method to correct the position of film cooling holes on turbine blades. In this method, the pre-positioning algorithm and the precise positioning algorithm are proposed. The pre-positioning algorithm introduces the blade structure information. In the precise positioning algorithm, 3D coordinate transformation, ∠B and ∠C of 5-axis machine tool updating, iteration points creating based on the normal vector are designed. The operation of the gas film cooling hole correcting by the method is given. Experiment shows that, after 7 iterations, the error is reduced to 0.0344mm, achieving high-precision positioning of turbine blades. Furthermore, the coordinates are corrected to realize the high-precision machining of the film cooling holes, which can improve the cooling performance of turbine blades.