Spot Model Research Articles

The GAPS programme at TNG

Context. The intrinsic variability due to the magnetic activity of young active stars is one of the main challenges in detecting and characterising exoplanets. The stellar activity is responsible for jitter effects observed both in photometric and spectroscopic observations that can impact our planetary detection sensitivity. Aims. We present a method able to model the stellar photosphere and its surface inhomogeneities (starspots) in young, active, and fast-rotating stars based on the cross-correlation function (CCF) technique, and we extract information about the spot configuration of the star. Methods. We developed Spot CCF, a tool able to model the deformation of the CCF profile due to the presence of multiple spots on the stellar surface. Within the Global Architecture of Planetary Systems (GAPS) Project at the Telescopio Nazionale Galileo, we analysed more than 300 spectra of the young planet-hosting star V1298 Tau provided by the HARPS-N high-resolution spectrograph. By applying the SpotCCF model to the CCFs, we extracted the spot configuration (latitude, longitude, and projected filling factor) of this star, and provide a new radial velocity (RV) time series for this target. Results. We find that the features identified in the CCF profiles of V1298 Tau are modulated by the stellar rotation, supporting our assumption that they are caused by starspots. The analysis suggests a differential rotation velocity of the star with lower rotation at higher latitudes. Also, we find that SpotCCF provides an improvement in RV extraction, with a significantly lower dispersion with respect to the commonly used pipelines. This allows mitigation of the stellar activity contribution modulated with stellar rotation. A detection sensitivity test, involving the direct injection of a planetary signal into the data, confirms that the SpotCCF model improves the sensitivity and ability to recover planetary signals. Conclusions. Our method enables us to model the stellar photosphere and extract the spot configuration of young, active, and rapidly rotating stars. It also allows the extraction of optimised RV time series, thereby enhancing our detection capabilities for new exoplanets and advancing our understanding of stellar activity.

Probing valence quark width of the proton in deeply virtual Compton scattering at high energies* *Supported by the National Natural Science Foundation of China (12165004), the Basic and Applied Basic Research Project of Guangzhou Science and Technology Bureau (202201011324), the Education Department of Guizhou Province, China (QJJ[2022]016) and the National Key Research and Development Program of China (2018YFE0104700, CCNU18ZDPY04)

We use the refined hot spot model to study the valence quark shape of the proton with the deeply virtual Compton scattering at high energies in the color glass condensate framework. To investigate the individual valence quark shape, a novel treatment of the valence quark width is employed. We calculate the cross-sections for coherent and incoherent deeply virtual Compton scattering using, for the first time, different widths ( and ) for the profile density distributions of the up and down quarks instead of using the same width as in the literature. We find that the cross-sections calculated with at each collision energy are consistent with each other, which is in agreement with theoretical expectations, whereas those computed with show some discrepancies. This outcome implies that the up quark might emit more gluons than the down quark, leading to at high energy. The impact of energy on the outcome is estimated. Our results show that as the collision energy increases, the aforementioned discrepancies are not only significantly broadened, but also shift to a relatively smaller momentum transfer range at the future Electron-Ion Collider (EIC) and Large Hadron Electron Collider (LHeC) energies, which indicates that the EIC and LHeC can provide an unprecedented chance to access the shape of the valence quark of the proton.

Development and tuning of models for accurate simulation of CT spatial resolution using CatSim.

Objective. We sought to systematically evaluate CatSim's ability to accurately simulate the spatial resolution produced by a typical 64-detector-row clinical CT scanner in the projection and image domains, over the range of clinically used x-ray techniques.Approach.Using a 64-detector-row clinical scanner, we scanned two phantoms designed to evaluate spatial resolution in the projection and image domains. These empirical scans were performed over the standard clinically used range of x-ray techniques (kV, and mA). We extracted projection data from the scanner, and we reconstructed images. For the CatSim simulations, we developed digital phantoms to represent the phantoms used in the empirical scans. We developed a new, realistic model for the x-ray source focal spot, and we empirically tuned a published model for the x-ray detector temporal response. We applied these phantoms and models to simulate scans equivalent to the empirical scans, and we reconstructed the simulated projections using the same methods used for the empirical scans. For the empirical and simulated scans, we qualitatively and quantitatively compared the projection-domain and image-domain point-spread functions (PSFs) as well as the image-domain modulation transfer functions. We reported four quantitative metrics and the percent error between the empirical and simulated results.Main Results.Qualitatively, the PSFs matched well in both the projection and image domains. Quantitatively, all four metrics generally agreed well, with most of the average errors substantially less than 5% for all x-ray techniques. Although the errors tended to increase with decreasing kV, we found that the CatSim simulations agreed with the empirical scans within limits required for the anticipated applications of CatSim.Significance.The new focal spot model and the new detector temporal response model are significant contributions to CatSim because they enabled achieving the desired level of agreement between empirical and simulated results. With these new models and this validation, CatSim users can be confident that the spatial resolution represented by simulations faithfully represents results that would be obtained by a real scanner, within reasonable, known limits. Furthermore, users of CatSim can vary parameters including but not limited to system geometry, focal spot size/shape and detector parameters, beyond the values available in physical scanners, and be confident in the results. Therefore, CatSim can be used to explore new hardware designs as well as new scanning and reconstruction methods, thus enabling acceleration of improved CT scan capabilities.

Investigation into the mechanism of surface atom emission from an individual cathode spot using molecular dynamics simulation

Contact erosion on the cathode of a vacuum arc is determined by the behaviours of the cathode spots, where the plasma–surface interactions take place. A comprehensive model of a single cathode spot is developed in this work based on the molecular dynamics method, where an atomic copper substrate in the size of nanometres is built and the contributions to the development of cathode spot from leftover plasma ions, surface electron emission, surface atom emission, back ions, Nottingham heating and Joule heating are integrated. Defined based on the surface temperature distribution, a cathode spot is observed in the simulation results. The surface atom emission, which is the origin of mass loss, can be directly detected by the atoms being isolated from the surface. Two routes of surface atom emission are observed as the sources of mass loss, including evaporation, and atom sputtering or splashing. It is found that in the high-temperature region, atom sputtering or splashing dominates the surface atom emission, which leads to considerable mass losses. The simulation results are consistent with previous experimental and other simulation findings, providing fundamental insights into the cathode spot formation mechanism from a microscopic perspective.

Business decision-making of power generators in competitive electricity market

This paper presents a theoretical framework for the business decision-making process of the power generators as price takers when considering the participation of energy storage. The framework assesses rational valuation, optimal sales strategies, and hedging options for power plants with and without a gross sales constraint. The valuation and optimal sales strategy problems are analyzed using a risk-neutral pricing approach, dynamic programming principles, and the trinomial tree model suitable for the regime switching model. The formulation of a price risk hedging scheme flexible and widely used over-the-counter electricity derivative, the electricity contract for difference, as a tool for hedging electricity spot price risk. The minimum variance hedge ratio and its corresponding hedging efficiency formula are derived. In the section of numerical simulations, we first use the EM algorithm to calibrate the electricity spot model based on electricity spot price data of Nord Pool. Numerical simulations are then conducted on the operational decision-making of power generators under three different forms of energy storage. The results of the simulations provide a basis for power generators to evaluate the real-time value of power plants, to select optimal real-time power sales, and to determine the optimal timing of power plant transfer and storage methods.

Parameter-based analysis of clinical efficacy of combined bed nucleus of the stria terminalis-nucleus accumbens deep brain stimulation for treatment-resistant depression.

Treatment-resistant depression (TRD) is a severely disabling psychiatric condition that responds poorly to conventional treatments. Deep brain stimulation (DBS) has been proposed for the treatment of patients with TRD in numerous studies. Several deep brain nuclei are considered as potential targets for TRD-DBS, but their clinical efficacy needs further validation. This study carried out dual-target combined stimulation of the bed nucleus of the stria terminalis (BNST) and nucleus accumbens (NAc) to investigate the effectiveness of the treatment for TRD patients. An 8-contact DBS electrode was used in the study with a surgical path that crossed the BNST and NAc targets. Stimulation parameters and the corresponding severity of symptoms evaluated by the 17-item Hamilton Depression Rating Scale (HAMD-17) and other scales were obtained at each follow-up. The accuracy of electrode positions, the effect of combined stimulation, and the corresponding stimulation parameters were evaluated. Sweet spot prediction models were used to assess the effective stimulation sites in the treatment. The study included 23 TRD patients undergoing DBS at a single center from March 2021 to May 2023. At the last follow-up (range 4-24 months), 14 patients had responded to the treatment (HAMD-17 score improved ≥ 50%), 7 of whom had achieved clinical remission (HAMD-17 score ≤ 7). Electrode position analysis suggested that the BNST may be more important for the improvement of depressive symptoms than the NAc. Overlapped volumes of volume of tissue activated (VTA) and BNST were significantly correlated with absolute (ρleft = -0.377, p < 0.001; ρright = -0.251, p < 0.001) and percent (ρleft = -0.249, p < 0.001; ρright = -0.098, p = 0.102) changes in HAMD-17 score. The sweet spot model of HAMD-17 improvement also suggested that the VTA overlap with the dorsal side of BNST was associated with the impact on depressive symptoms (t = -4.10, p < 0.05). Combined BNST-NAc stimulation of TRD can effectively improve depressive symptoms, in which the BNST seems to have a dominant therapeutic effect. The results of this study not only help to optimize the DBS programming parameters, but also offer an opportunity to further understand the differences between the two targets. In the future, larger prospective cohorts are needed to verify the results of combined BNST-NAc DBS.

Thermal Runaway in Thin Film PV: temperature profile modeling

Thermal runaway is a well known phenomena in degradation analysis of the CdS/CdTe thin film solar cells. The thin thickness of such devices can be deteriorated by the temperature fluctuations after a long enough time. We modeled the temperature profile of thin film devices considering the uniform and nonuniform distribution for temperature of the glass substrate and current flowing through TCO layer. In addition, the temperature profile of a hot spot at the edge of the device has been formulated and compared with the real data and fitting functions represented in a few literature. All the above modeling was based on the heat transfer equation considering the importance of thermal resistances. The convection and conduction resistances were introduced in the considered Biot number optimized for PV applications. The modeling presented in this paper can be extended to other solar cell structures or large scale modules. The current study suggests that the thickness and temperature dependencies of the thermal conductivity, convection and conduction resistance might be taken into account and be optimized in thermal runaway issues of thin film devices. The hot spot modeling suggests that the current flowing across the TCO layer can assist the thermal runaway and deformation of neighboring area.

Bringing 2D Eclipse Mapping out of the Shadows with Leave-one-out Cross Validation

Eclipse mapping is a technique for inferring 2D brightness maps of transiting exoplanets from the shape of an eclipse light curve. With JWST’s unmatched precision, eclipse mapping is now possible for a large number of exoplanets. However, eclipse mapping has only been applied to two planets, and the nuances of fitting eclipse maps are not yet fully understood. Here, we use Leave-one-out Cross Validation (LOO-CV) to investigate eclipse mapping, with application to a JWST NIRISS/SOSS observation of the ultrahot Jupiter WASP-18b. LOO-CV is a technique that provides insight into the out-of-sample predictive power of models on a data-point-by-data-point basis. We show that constraints on planetary brightness patterns behave as expected, with large-scale variations driven by the phase-curve variation in the light curve and smaller-scale structures constrained by the eclipse ingress and egress. For WASP-18b we show that the need for higher model complexity (smaller-scale features) is driven exclusively by the shape of the eclipse ingress and egress. We use LOO-CV to investigate the relationship between planetary brightness map components when mapping under a positive-flux constraint to better understand the need for complex models. Finally, we use LOO-CV to understand the degeneracy between the competing “hot spot” and “plateau” brightness map models of WASP-18b, showing that the plateau model is driven by the ingress shape and the hot spot model is driven by the egress shape, but preference for neither model is due to outliers or unmodeled signals. Based on this analysis, we make recommendations for the use of LOO-CV in future eclipse-mapping studies.

Micro-Expression Spotting Based on VoVNet, Driven by Multi-Scale Features

Micro-expressions are a type of real emotional expression, which are unconscious and difficult to hide. Identifying these expressions has great potential applications in areas such as civil aviation security, criminal interrogation, and clinical medicine. However, because of their characteristics such as short duration, low intensity, and sparse action units, this makes micro-expression spotting difficult. To address this problem and inspired by object detection methods, we propose a VoVNet-based micro-expression spotting model, driven by multi-scale features. Firstly, VoVNet is used to achieve the extraction and reuse of different scale perceptual field features to improve the feature extraction capability. Secondly, multi-scale features are extracted and fused using the Feature Pyramid Network module, incorporating optical flow features, and by realizing the interactive fusion of fine-grained feature information and semantic feature information. Finally, the model is trained and optimized on CAS(ME)2 and SAMM Long Video. The experimental results show that the F1 score of the proposed model is improved by 0.1963 and 0.2441 on the two datasets compared with the baseline method, which outperforms the most popular spotting methods.

Optical and X-Ray Studies of Marginal Contact Binary RW Dor Using TESS and XMM-Newton Observatories

Marginal short-period contact binaries are important to understand as they pose a different physical scenario than the predicted theoretical model based on the thermal relaxation oscillation mechanism due to their shallow degree of contact. Here we present the optical and X-ray studies of a contact binary source RW Dor using the Transiting Exoplanet Survey Satellite (TESS) and XMM-Newton telescopes. For the first time we report the varying O’Connell effect and explain the asymmetry with a spot model. Based on the new times of minima, we make a robust estimate of the orbital period of the third body at 47.01 ∼ 0.52 yr with an eccentricity e = 0.21. We show that the period-decreasing trend observed in O − C variation can be explained by both conservative mass transfer from primary to secondary and AML via stellar wind. The X-ray luminosity exhibited by RW Dor did not vary significantly on three different occasions and was found to be about 3.34 × 1029 erg s−1. Assuming that the quiescent X-ray emission is emitted from an undisturbed loop structure, the loop size is estimated to be 0.6–1 × 1010 cm which is ≤Alfvén radius r A ∼ 8 × 1010 cm.

Exploring the network effects of deep brain stimulation for rapid eye movement sleep behavior disorder in Parkinson's disease.

The research findings on the effects of subthalamic nucleus (STN) deep brain stimulation (DBS) in Parkinson's disease (PD) with Rapid Eye Movement Sleep Behavior Disorder (RBD) are inconsistent, and there is a lack of research on DBS electrode sites and their network effects for the explanation of the differences. Our objective is to explore the optimal stimulation sites (that is the sweet spot) and the brain network effects of STN-DBS for RBD in PD. In this study, among the 50 PD patients who underwent STN-DBS treatment, 24 PD patients with RBD were screened. According to clinical scores and imaging data, the sweet spot of STN-DBS was analyzed in PD patients with RBD, and the optimal structure and functional network models of subthalamic stimulation were constructed. Bilateral STN-DBS can effectively improve the symptoms of RBD and other non-motor symptoms in 24 PD patients with RBD. RBD Questionnaire-Hong Kong (RBDQ-HK) score was 41.33 ± 17.45 at baseline and 30.83 ± 15.83 at 1-year follow-up, with statistical significance between them (P < 0.01). However, the MoCA score was an exception with a baseline of 22.04 ± 4.28 and a 1-year follow-up of 21.58 ± 4.33, showing no statistical significance (P = 0.12). The sweet spot and optimal network connectivity models for RBD improvement have been validated as effective. Bilateral STN-DBS can improve the symptoms of RBD in PD. There exist the sweet spot and brain network effects of bilateral STN-DBS in the treatment of PD with RBD. Our study also demonstrates that RBD is a brain network disease.

Images of Betelgeuse with VLTI/MATISSE across the Great Dimming

ABSTRACT From Nov. 2019 to May 2020, the red supergiant star Betelgeuse experienced an unprecedented drop of brightness in the visible domain called the Great Dimming event (GDE). Large atmospheric dust clouds and large photospheric convective features are suspected to be responsible for it. To better understand the dimming event, we used mid-infrared long-baseline spectro-interferometric measurements of Betelgeuse taken with the Very Large Telescope Interferometer/Multi AperTure mid-Infrared SpectroScopic Experiment (VLTI/MATISSE) instrument before (Dec. 2018), during (Feb. 2020), and after (Dec. 2020) the GDE. We present data in the 3.98–4.15 µm range to cover SiO spectral features molecules as well as adjacent continuum. We have employed geometrical models, image reconstruction, as well as radiative transfer models to monitor the spatial distribution of SiO over the stellar surface. We find a strongly inhomogeneous spatial distribution of SiO that appears to be looking very different between our observing epochs, indicative of a vigorous activity in the stellar atmosphere. The contrast of our images is small in the pseudo-continuum for all epochs, implying that our MATISSE observations support both cold spot and dust cloud model.

A novel mathematical approach for gravity-driven granular flows in block caving

This study presents a novel mathematical model aimed at elucidating the distinctive behavior observed in the flow of flat-bottom silos. A scheme analogous to the spot model proposed by Bazant is adopted, in which groups of particles move in relation to a static medium. However, we assume that the movement of the particles is driven by the local change in the tensional state instead of the increment of interstitial space through the diffusion of spots. We propose that the tensional state and gravity might induce a driving force with a larger magnitude than the friction exerted at the boundary of the group of mobilized particles. Thus, the dynamics of the flow is controlled by the driving and frictional force. Finally, we have introduced a dimensionless number (Y) corresponding to the ratio of driving to frictional force to characterize the movement of particles. By assuming that frictional force at the interface has a viscous component proportional to the relative speed of the mobilized particles, we have writen an equation analogous to Darcy's law for the flow of a Bingham fluid in a porous medium. The finite element method is utilized to solve the model, and the numerical findings demonstrate a strong correspondence with experimental results achieved in flat-bottom silos featuring one or two openings. Comparatively, the results of the kinematic model are surpassed, with a notable enhancement in the depiction of the velocity field.

A Spatio-Temporal Spotting Network with Sliding Windows for Micro-Expression Detection

Micro-expressions reveal underlying emotions and are widely applied in political psychology, lie detection, law enforcement and medical care. Micro-expression spotting aims to detect the temporal locations of facial expressions from video sequences and is a crucial task in micro-expression recognition. In this study, the problem of micro-expression spotting is formulated as micro-expression classification per frame. We propose an effective spotting model with sliding windows called the spatio-temporal spotting network. The method involves a sliding window detection mechanism, combines the spatial features from the local key frames and the global temporal features and performs micro-expression spotting. The experiments are conducted on the CAS(ME)2 database and the SAMM Long Videos database, and the results demonstrate that the proposed method outperforms the state-of-the-art method by 30.58% for the CAS(ME)2 and 23.98% for the SAMM Long Videos according to overall F-scores.

NY Bootes: An Active Deep and Low-mass-ratio Contact Binary with a Cool Companion in a Hierarchical Triple System

The first detailed photometric and spectroscopic study of G-type short-period binary NY Boo is presented. The radial velocity curve was obtained by the cross-correlation function (CCF) method based on LAMOST and SDSS spectra, which derived its mass ratio as q = 0.139(1/7.2). The CCF profiles of the SDSS spectra clearly show the existence of a cool third component, which is supported by the results of the orbital period investigation. The period study based on the O-C analysis indicates that besides a long-term decrease, the orbital period has a periodic oscillation due to the light-travel time effect caused by a third body. When the third light contribution is consistent with the CCF results, the orbit of the third body and the inner pair are non-coplanar with m 3 = 0.31 M ⊙. Combining with the TESS light curves, it is found that the target is a deep and low-mass-ratio contact binary (DLMRCB) with a fill-out factor of f = 73%. The notable asymmetry in light curves was detected and explained by the spot model very well. The spectroscopic profiles, the cyclic variation in the O-C diagram, and the radial velocity curve and light-curve solutions all suggest that NY Boo is a hierarchical triple system with a cool tertiary component orbiting around an active DLMRCB. With the orbital period shrinking, the binary may eventually merge. The period of NY Boo decreases faster than other shrinking DLMRCB, together with active inner pair and non-coplanar tertiary component, making NY Boo an important target for studying the late evolution of binaries.

Center TextSpotter: A Novel Text Spotter for Autonomous Unmanned Vehicles

Automatic text spotting can help unmanned vehicles read human texts, thus improving the safety and reliability of autonomous driving. Some existing text spotting models use inefficient region proposal networks or modules based on the recurrent neural network. Region proposal networks produce redundant anchors. Recurrent neural networks cannot perform parallel operations well. The existence of these inefficient modules prevents these models from applying in autonomous unmanned vehicles. In this paper, we propose an end-to-end two-stage text spotting model named Center TextSpotter, which is a convolution model that does not involve region proposal networks and recurrent neural network. Moreover, we develop a weakly supervised training method and a feature fusion module. The weakly supervised training method adjusts the loss by weighting the predicted labels to improve the performance of text recognition. The feature fusion module fuses the features of the proposal with the features of the proposal-context to enhance the overall performance. Our model follows the modular design principle. So it can be easily extended and modified. This paper presents an extension scheme based on graph neural network. By adding the graph neural network before the fully connected layer, the model learns better features. Experiments demonstrate that Center TextSpotter can complete the task of text spotting for autonomous unmanned vehicles commendably.

Tectonic evolution of Southeast Asia documented by two periods of high-grade metamorphism in the Kon Tum Massif, Central Vietnam

The Kon Tum Massif in the eastern Indochina Block (ICB) contains extensive Ordo-Silurian and Permo-Triassic metamorphic rocks. These two episodes of metamorphism not only affected the Kon Tum Massif, but were also widely developed in the whole of Southeast and East Asia, including the South China Block (SCB). Comparisons of the metamorphic characteristics among these blocks can reveal the crustal evolution and their affinity in supercontinents. Two gneiss samples in the eastern part of the Kan Nack Complex of the Kon Tum Massif have similar peak metamorphic ages of 488–482 Ma and mineral assemblages of garnet + plagioclase + K-feldspar + biotite + sillimanite + ilmenite + quartz. P-T calculations and thermodynamic modelling constrain a pressure peak (M1) at 770–820 °C and ∼1.1–1.2 GPa, and a temperature peak (M2) at 790–850 °C and 0.85–0.98 GPa, suggesting a near-isothermal decompression. The post-peak M3 assemblage developed at 650–760 °C and 0.48–0.74 GPa. The clockwise P-T-t path with medium and variable geothermal gradients probably reflects an orogeny process from compression to extension, which was triggered by the closure of the Tam Ky-Phuoc Son Ocean in the northern flank of the Kon Tum Massif. The P-T-t path and tectonic setting of this period of metamorphism in the Kon Tum Massif is similar to that in the SCB, but occurred a little earlier than that in the SCB, suggesting that the ICB and the SCB were adjacent on the northern margin of East Gondwana and together experienced a diachronous early Paleozoic orogeny.A granulite sample from the western Kan Nack Complex contains garnet + orthopyroxene + plagioclase + quartz + ilmenite ± K-feldspar. Decomposition of garnet to plagioclase and orthopyroxene suggests a decompression process. Coupled with features of a gneiss sampled at the same spot, P-T calculations and thermodynamic modelling indicate a pressure peak of 885–960 °C and 0.83–0.95 GPa and a temperature peak at 890–970 °C and 0.61–0.73 GPa, corresponding to ultrahigh-temperature (UHT) metamorphism. LA-ICP-MS monazite U-Th-Pb dating constrains a peak metamorphic age of 254 Ma, and Sm-Nd mineral isochrons date the retrograde stage at 243–236 Ma. This UHT metamorphism with a clockwise P-T-t path probably resulted from the excess heat supplied by asthenospheric upwelling following the break-off of the subducting slab of the Paleo-Tethyan Ocean. The Permo-Triassic metamorphism and other geological records in the ICB are significantly different from those in the SCB, implying that the geological processes in the two blocks were controlled by different geodynamic regimes during Late Permian to Early Triassic.

A Method of Star Spot Center-of-Mass Localization Algorithm for Star Sensor Under Highly Dynamic Conditions

The starlight guidance system calculates the vehicle attitude information by observing the stars position through the star sensor. When the star sensor operates under high dynamic conditions, the motion blur phenomenon exists in the images taken by it, which seriously affects the computational accuracy of attitude solution. In this paper, based on the motion characteristics of the vehicle under high dynamic conditions, we study and derive the imaging model of the blurred star spot under high dynamic conditions. On this basis, we use the least squares method combined with simulated annealing algorithm to fit the trajectory of the corresponding star spot. The trajectory fitting is based on the information of multiple star streaks in the star field image. And finally, we calculate the center-of-mass coordinates of the star spot. Simulations and experiments demonstrate the feasibility and effectiveness of the method. The fitting error is less than 0.3 pixels for the angular velocity vector [10°/s,0°/s,10°/s] and exposure time 200ms, which is an improvement of at least 0.1 pixel compared to previous studies.

The dusty circumstellar environment of Betelgeuse during the Great Dimming as seen by VLTI/MATISSE

Context. The ‘Great Dimming’ of the prototypical red supergiant Betelgeuse, which occurred between December 2019 and April 2020, gives us unprecedented insight into the processes occurring on the stellar surface and in the inner wind of this type of star. In particular it may bring further understanding of their dust nucleation and mass-loss processes. Aims. Here, we present and analyse VLTI/MATISSE observations in the N band (8–13 µm) taken near the brightness minimum in order to assess the status of the dusty circumstellar environment. Methods. We explored the compatibility of a dust clump obscuring the star with our mid-infrared interferometric observations using continuum 3D radiative transfer modelling, and probed the effect of adding multiple clumps close to the star on the observables. We also tested the viability of a large cool spot on the stellar surface without dust present in the ambient medium. Results. Using the visibility data, we derived a uniform disk diameter of 59.02 ± 0.64 mas in the spectral range 8–8.75 µm. We find that both the dust clump and the cool spot models are compatible with the data. Further to this, we note that the extinction and emission of our localised dust clump in the line of sight of the star directly compensate for each other, making the clump undetectable in the spectral energy distribution and visibilities. The lack of infrared brightening during the Great Dimming therefore does not exclude extinction due to a dust clump as one of the possible mechanisms. The visibilities can be reproduced by a spherical wind with dust condensing at 13 stellar radii and a dust mass-loss rate of (2.1–4.9) × 10−10 M⊙ yr−1; however, in order to reproduce the complexity of the observed closure phases, additional surface features or dust clumps would be needed.

A novel scenic spots assessment and recommendation method based on network attention: augmented mining model using probabilistic linguistic term set combined with VIKOR

PurposeThe purpose is to provide decision support for tourists recommending scenic spots and corresponding suggestions for the management of scenic spots.Design/methodology/approachBased on the Baidu index data generated, this paper analyzes the temporal and spatial characteristics of network attention of 5A scenic spots in Sichuan Province. The online comment data are used to build the assessment model of scenic spots based on network attention, and the comment information of tourists is mined and analyzed through statistical analysis. At the same time, the key attributes of scenic spots from the perspective of network attention are evaluated and analyzed by using the probabilistic linguistic term set. Finally, this paper further constructs a recommendation model based on the key attribute set of scenic spots.FindingsThis paper uses different types of tourism network information, integrates multi-types of data and methods, fully excavates the value information of tourism network information, constructs the research framework of “scenic spot assessment + scenic spot recommendation” from the perspective of network attention, analyzes the network attention characteristics of scenic spots, evaluates the performance of scenic spots, and implements scenic spot recommendation.Originality/valueThis paper integrates multi-source data and multidisciplinary theoretical methods to form a scenic spot research framework of “assessment + recommendation” from the perspective of network attention.