Mass Estimates Research Articles

Measurement of Dependence of Microlensing Planet Frequency on the Host Star Mass and Galactocentric Distance by Using a Galactic Model

We measure the dependence of planet frequency on host star mass, M L, and distance from the Galactic center, R L, using a sample of planets discovered by gravitational microlensing. We compare the two-dimensional distribution of the lens-source proper motion, μ rel, and the Einstein radius crossing time, t E, measured for 22 planetary events from Suzuki et al. with the distribution expected from Galactic model. Assuming that the planet-hosting probability of a star is proportional to MLmRLr , we calculate the likelihood distribution of (m,r). We estimate that r=0.10−0.37+0.51 and m=0.50−0.70+0.90 under the assumption that the planet-hosting probability is independent of the mass ratio. We also divide the planet sample into subsamples based on their mass ratio, q, and estimate that m=−0.08−0.65+0.95 for q < 10−3 and 1.25−1.14+1.07 for q > 10−3. Although uncertainties are still large, this result implies a possibility that, in orbits beyond the snowline, massive planets are more likely to exist around more massive stars whereas low-mass planets exist regardless of their host star mass.

An overlooked source of uncertainty in the mass of the Milky Way

ABSTRACT In the conventional approach to decomposing a rotation curve into a set of contributions from mass model components, the measurements of the rotation curve at different radii are taken to be independent. It is clear, however, that radial correlations are present in such data, for instance (but not only) because the orbital speed depends on the mass distribution at all (or, minimally, inner) radii. We adopt a very simple parametric form for a covariance matrix and constrain its parameters using Gaussian process regression. Applied to the rotation curve of the Milky Way, this suggests the presence of correlations between neighbouring rotation curve points with amplitudes of $\lt 10\, \mathrm{km}\, \mathrm{s}^{-1}$ over length scales of 1.5–$2.5\, \mathrm{kpc}$ regardless of the assumed dark halo component. We show that accounting for such covariance can result in a ∼50 per cent lower total mass estimate for the Milky Way than when it is neglected, and that the uncertainty in model parameters increases such that it seems more representative of the uncertainty in the rotation curve measurement. The statistical uncertainty associated with the covariance is comparable to or exceeds the total systematic uncertainty budget. Our findings motivate including more detailed treatment of rotation curve covariance in future analyses.

Estimating the Mass of Galactic Components Using Machine Learning Algorithms

The estimation of galactic component masses can be carried out through various approaches that involve a host of assumptions about baryon dynamics or the dark matter model. In contrast, this work introduces an alternative method for predicting the masses of the disk, bulge, stellar, and total mass using the k-nearest neighbours, linear regression, random forest, and neural network (NN) algorithms, reducing the dependence on any particular hypothesis. The ugriz photometric system was selected as the set of input features, and the training was performed using spiral galaxies in Guo’s mock catalogue from the Millennium simulation. In general, all of the algorithms provide good predictions for the galaxy’s mass from 109 M⊙ to 1011 M⊙, corresponding to the central region of the training domain. The NN algorithm showed the best performance. To validate the algorithm, we used the SDSS survey and found that the predictions of disk-dominant galaxies’ masses lie within a 99% confidence level, while galaxies with larger bulges are predicted at a 95% confidence level. The NN also reveals scaling relations between mass components and magnitudes. However, predictions for less luminous galaxies are biased due to observational limitations. Our study demonstrates the efficacy of these methods with the potential for further enhancement through the addition of observational data or galactic dynamics.

Body weight and composition endpoints in cancer cachexia clinical trials: Systematic Review 4 of the cachexia endpoints series.

Significant variation exists in the outcomes used in cancer cachexia trials, including measures of body composition, which are often selected as primary or secondary endpoints. To date, there has been no review of the most commonly selected measures or their potential sensitivity to detect changes resulting from the interventions being examined. The aim of this systematic review is to assess the frequency and diversity of body composition measures that have been used in cancer cachexia trials. MEDLINE, Embase and Cochrane Library databases were systematically searched between January 1990 and June 2021. Eligible trials examined adults (≥18years) who had received an intervention aiming to treat or attenuate the effects of cancer cachexia for >14days. Trials were also of a prospective controlled design and included body weight or at least one anthropometric, bioelectrical or radiological endpoint pertaining to body composition, irrespective of the modality of intervention (e.g., pharmacological, nutritional, physical exercise and behavioural) or comparator. Trials with a sample size of <40 patients were excluded. Data extraction used Covidence software, and reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidance. This review was prospectively registered (PROSPERO: CRD42022276710). A total of 84 clinical trials, comprising 13016 patients, were eligible for inclusion. Non-small-cell lung cancer and pancreatic cancer were studied most frequently. The majority of trial interventions were pharmacological (52%) or nutritional (34%) in nature. The most frequently reported endpoints were assessments of body weight (68 trials, n=11561) followed by bioimpedance analysis (BIA)-based estimates (23 trials, n=3140). Sixteen trials (n=3052) included dual-energy X-ray absorptiometry (DEXA)-based endpoints, and computed tomography (CT) body composition was included in eight trials (n=841). Discrepancies were evident when comparing the efficacy of interventions using BIA-based estimates of lean tissue mass against radiological assessment modalities. Body weight, BIA and DEXA-based endpoints have been most frequently used in cancer cachexia trials. Although the optimal endpoints cannot be determined from this review, body weight, alongside measurements from radiological body composition analysis, would seem appropriate. The choice of radiological modality is likely to be dependent on the trial setting, population and intervention in question. CT and magnetic resonance imaging, which have the ability to accurately discriminate tissue types, are likely to be more sensitive and provide greater detail. Endpoints are of particular importance when aligned with the intervention's mechanism of action and/or intended patient benefit.

Estimation of stellar mass and star formation rate based on galaxy images

ABSTRACT It is crucial for a deeper understanding of the formation and evolution of galaxies in the Universe to study stellar mass (M*) and star formation rate (SFR). Traditionally, astronomers infer the properties of galaxies from spectra, which are highly informative, but expensive and hard to be obtained. Fortunately, modern sky surveys obtained a vast amount of high-spatial-resolution photometric images. The photometric images are obtained relatively economically than spectra, and it is very helpful for related studies if M* and SFR can be estimated from photometric images. Therefore, this paper conducted some preliminary researches and explorations on this regard. We constructed a deep learning model named Galaxy Efficient Network (GalEffNet) for estimating integrated M* and specific star formation rate (sSFR) from Dark Energy Spectroscopic Instrument galaxy images. The GalEffNet primarily consists of a general feature extraction module and a parameter feature extractor. The research results indicate that the proposed GalEffNet exhibits good performance in estimating M* and sSFR, with σ reaching 0.218 and 0.410 dex. To further assess the robustness of the network, prediction uncertainty was performed. The results show that our model maintains good consistency within a reasonable bias range. We also compared the performance of various network architectures and further tested the proposed scheme using image sets with various resolutions and wavelength bands. Furthermore, we conducted applicability analysis on galaxies of various sizes, redshifts, and morphological types. The results indicate that our model performs well across galaxies with various characteristics and indicate its potentials of broad applicability.

Matrix effect correction in active neutron interrogation for residual fissile mass assessment in radioactive waste drums

Metallic waste in the form of shells and nozzles remains following the reprocessing of spent fuel at La Hague plant (France). Before the final disposal, drums containing the waste are transported to the compaction facility where its volume is reduced by a factor of 5. With the objective of controlling the criticality/safety levels, an active neutron interrogation system at the entrance of the facility is used to assess the residual fissile mass remaining in the waste, which relies on prompt fission neutron detection (known as the differential die-away technique, DDA). The measured signal is proportionally linked to the fissile mass by a calibration coefficient. However, two effects can produce an inaccurate prediction. The number of induced fissions for the same fissile mass varies according to the waste matrix composition, particularly the neutron slow-down and absorption ratio. Secondly, the presence of fissile clusters can impact the neutron interrogation due to an increase in self-shielding effect. This work presents a matrix effect correction method based on the use of internal flux monitors (sensitive to the neutron absorption ratio) and the transmission signal (sensitive to the slow-down ratio). It relies on a numerical model of the whole measurement cell developed with the Monte-Carlo N-Particle transport (MCNP) code. The calibration coefficient of 72 different matrices, representative of the waste produced at La Hague, were simulated and a statistical model using a multilinear regression was then established. This simulated-based approach provides a more robust and comprehensive estimation of the residual fissile mass without impacting accuracy thanks to the flux monitors and the transmission signals.

A 3D geometric morphometric analysis of the bovid distal humerus, with special reference to Rusingoryx atopocranion (Pleistocene, Eastern Africa).

The family Bovidae [Mammalia: Artiodactyla] is speciose and has extant representatives on every continent, forming key components of mammal communities. For these reasons, bovids are ideal candidates for studies of ecomorphology. In particular, the morphology of the bovid humerus has been identified as highly related to functional variables such as body mass and habitat. This study investigates the functional morphology of the bovid distal humerus in isolation due to its increased likelihood of preservation in the fossil record, and the resulting opportunity for a better understanding of the ecomorphology of extinct bovids. A landmark scheme of 30 landmarks was used to capture the 3D distal humerus morphology in 111 extant bovid specimens. We find that the distal humerus has identifiable morphologies associated with body mass, habitat preference and tribe affiliation and that some characteristics are shared between high body mass bovids and those living on hard, flat terrain which is likely due to the high stress on the bone in both cases. We directly apply our findings regarding extant bovids to the extinct alcelaphine bovid, Rusingoryx atopocranion from the mid to late Pleistocene (>33-45 ka) Lake Victoria region of Kenya. This species is known for some peculiar morphologies including a domed cranium with hollow nasal crests, and having small hooves for a bovid of its size. Another interesting aspect of Rusingoryx's skeletal morphology which has not been addressed is an unusual protrusion on the lateral epicondyle of the distal humerus. Despite considerable individual variation in the Rusingoryx specimens, we find evidence to support its historical assignment to the tribe Alcelaphini, and that it likely preferred open grassland habitats, which is consistent with independent reconstructions of the palaeoenvironment. We also provide the most accurate body mass estimate for Rusingoryx to date, based on distal humerus centroid size. Overall, we are able to conclude that the distal humerus in extant bovids is highly informative regarding body mass, habitat preference and tribe, and that this can be applied directly to a fossil taxon with promising results.

The black hole masses of high-redshift QSOs

ABSTRACT Observations of high-redshift quasars frequently promote suggestions of large black hole masses, whose presence so early in cosmic time is not easily explicable. I consider the parallel with ultraluminous X-ray sources (ULXs) – now known to be stellar-mass black hole (and neutron star) binaries apparently radiating far above their Eddington luminosities LEdd. The true luminosity in ULXs is actually only of order LEdd, for stellar-mass accretors, but has a very anisotropic (‘beamed’) component, plus a near-isotropic component of similar luminosity but much lower specific intensity. Observers viewing ULXs from within the beam but assuming spherical symmetry deduce a luminosity ≫LEdd. These features appear because the accretors are fed mass at highly super-Eddington rates, most of it expelled in high-speed (v &amp;gt; 0.2c) outflows from the accretion disc. I show that in similarly beamed AGN, emission-line properties would be essentially the same as in unbeamed sources, but standard virial mass indicators unusable because velocity widths are dominated by the outflows, not bound motions about the black holes. In an ensemble of this kind the apparently most luminous systems are always the most distant, but have the lowest black hole masses. Interpreting observations of this ensemble without knowing that they are beamed leads instead to very high black hole mass estimates. The analogy with ULXs therefore suggests that high-redshift quasars might actually have central black hole masses which could have grown from stellar values within the lookback time. I consider how one might test these ideas observationally.

Non-Contact Tilapia Mass Estimation Method Based on Underwater Binocular Vision

The non-destructive measurement of fish is an important link in intelligent aquaculture, and realizing the accurate estimation of fish mass is the key to the stable operation of this link. Taking tilapia as the object, this study proposes an underwater tilapia mass estimation method, which can accurately estimate the mass of free-swimming tilapia under non-contact conditions. First, image enhancement is performed on the original image, and the depth image is obtained by correcting and stereo matching the enhanced image using binocular stereo vision technology. And the fish body is segmented by an SAM model. Then, the segmented fish body is labeled with key points, thus realizing the 3D reconstruction of tilapia. Five mass estimation models are established based on the relationship between the body length and the mass of tilapia, so as to realize the mass estimation of tilapia. The results showed that the average relative errors of the method models were 5.34%~7.25%. The coefficient of determination of the final tilapia mass estimation with manual measurement was 0.99, and the average relative error was 5.90%. The improvement over existing deep learning methods is about 1.54%. This study will provide key technical support for the non-destructive measurement of tilapia, which is of great significance to the information management of aquaculture, the assessment of fish growth condition, and baiting control.

PSIV-A-2 Comparison of rising plate meter and total collection methods for forage mass determination of tall fescue

Abstract The objective was to compare estimates of forage mass (FM) determined with a rising plate meter (RPM) with forage mass determined by total collection method. Estimates of FM impact management decisions and give the producer a greater understanding of forage availability for their herd. Traditional methods of FM estimation using a forage ring or quadrat and total collection are labor intensive and time consuming. The RPM tool aims to provide a quicker method of FM estimation without sacrificing accuracy. The reliability of this tool can be impacted by season, species composition, plant growth state, and pasture management. Forage samples were collected from six random locations within both continuous and rotationally grazed systems. The predominant forage species was endophyte-infected tall fescue. A 0.25 m2 forage ring was randomly thrown, then two RPM (Jenquip Manual Platemeter) measurements were collected in the ring, followed by five measurements adjacent to the ring. The RPM determined the compressed sward height (CSH). Subsequently, forage within the ring was hand-clipped at ground level and collected. Samples were dried for 120 h at 55° C to determine forage availability (kg/ha). This process was repeated weekly for 6 wk. Rising plate meter FM was estimated using the equation: kg dry matter (DM)/ha = CSH × 158 + 200. Data were analyzed using the CORR procedure of SAS 9.4. Forage mass estimates from total ring collection method and RPM were weakly correlated in the rotational grazing system (r = 0.26; P = 0.13) and in the continuous grazing system (r = 0.20; P = 0.24). It is important to note that certain sample collection dates had stronger correlations than others. In the rotationally grazed paddocks, FM from RPM were strongly correlated (r ≥ 0.89, P ≤ 0.02) with FM from total ring collection on 6/23/23 and 7/26/23. In the continuously grazed paddocks, FM estimations from RPM were strongly correlated (r ≥ 0.73, P ≤ 0.10) with forage mass from total collection on 7/20/23 and 7/26/23. Variation among the seven RPM readings at each collection site could have contributed to variability. Coefficient of variation ranged from 9 to 48% and averaged 18% for all samples. The inconsistencies in relationship of forage mass determination methods suggests that more variables need to be considered when determining the accuracy of RPM-derived estimates of forage mass of tall fescue.

A novel hybrid-view technique for accurate mass estimation of kimchi cabbage using computer vision

This study addresses the accurate estimation of kimchi cabbage mass, as cabbage leaves exhibit size variability and complex leaf structures. Conventional mass estimation methods, which rely solely on external imaging, often overlook leaf gaps. To improve accuracy, we propose an innovative computer vision system utilizing hybrid-view images and detailed saturation analysis. Our system quantifies the impact of leaf gaps on mass using features from the saturation channel of images of bisected cabbage. Our proposed method can be easily integrated into existing workflows and has the potential to improve labor efficiency. Our approach outperforms the conventional method (R2 of 0.66 and relative error of 8.68%), achieving a 0.92 R2 value and lowering the relative error to 4.22%. This advancement offers a robust solution for the mass estimation of kimchi cabbage and suggests potential applications for other foods and crops with internal voids.

Dynamics of bridges during proof load tests and determination of mass-normalized mode shapes from OMA

Modal shapes derived from Operational Modal Analysis (OMA) lack normalization with respect to masses, hindering direct estimation of effective mass or modal participation factors. The mass-change method is suitable to solve this issue since it proposes an experimental derivation of scaling factors for modes based on OMA results in different load conditions. However, in the case of bridges, the method application is challenging, as significant static masses are required on the deck for OMA in loaded conditions. To address this challenge, trucks can be used as added masses during standard static proof load tests for bridges, making the mass-change method feasible. However, the presence of trucks introduces dynamic coupling effects among bridge and vehicles, potentially complicating the dynamic identification. This paper proposes a methodology to exploit data obtained from OMA on bridges loaded with stationed trucks within the framework of the mass-change method in order to get the modal scaling factors for the mass normalisation of mode shapes and taking into account possible effects of the dynamic coupling between the two systems. To this purpose, the bridge dynamics with added stationed trucks is studied by introducing a finite element model to address the bridge-vehicles dynamic coupling. Then, a simple but effective 2-degree of freedom system is introduced to develop a parametric investigation in a non-dimensional manner in order to provide a practical tool for engineers to account for the bridge-truck dynamic coupling effects. Finally, numerical applications are proposed to derive some conclusions about the effectiveness of the proposed procedure and its suitability in real applications.

Shielding mass estimation model for gas-cooled space nuclear reactors

The shielding is expected to be “mass-effective” for space nuclear power systems (SNPs) because it accounts for a significant portion of the total weight. Hence, the shield mass should be estimated rapidly but accurately especially in the early stage of SNPs’ design. In this paper, a simple mass estimation model was developed based on the preliminarily optimized shield design for the Jupiter Icy Moons Orbiter (JIMO) reactor. In the model, the reactor-induced 1 MeV equivalent silicon neutron fluence and photon absorbed dose at the unshielded payload were predicted by a circular surface source hypothesis at the core bottom, and the proportional coefficients were determined by the Monte Carlo calculation. Moreover, the attenuation factors of the shield were derived by solving the neutron/gamma coupled transport process within the shield body, and the correlations were established between the attenuation effect and the shield thicknesses. Afterwards, when given the radiation limits at the payload, the shield geometry and associated mass could be easily determined. Several detailed calculations corresponding to the variation of shield design were used to verify the estimation model. Those variations include the thickness of the Be-B4C layers, the effective density of the B4C and the number of the shielding layers. Additionally, the potential changes of the reactor such as the neutron energy spectrum and the structural materials in the core were also considered to evaluate the applicability of the model. Totally, the estimation model agrees with the detailed calculation within 15 % in a wide range, which suggests the model can be incorporated into the system code to help optimize the overall performance of the SNPs.

A Report on Stellar Companion Mass Estimates within Our Solar Neighborhood

We present mass estimates and companion demographics on stellar multiples within 25 pc, using a survey of stars of all spectral types done by Robo-AO and supplemented by Gaia. The survey combined direct imaging by Robo-AO, a robotic adaptive optics instrument for 2 m class telescopes, to detect tight companions (<4″ separation) and with Gaia astrometry to detect wider co-moving companions. We estimated the masses for 267 companions using empirical relations and, for a subset of 97, dynamical mass estimates. We utilized previous mass–magnitude models using contrasts measured from Gaia and Robo-AO to estimate the mass and also used the orvara python package, a Markov Chain Monte Carlo orbit fitter using the companion astrometry and Hipparcos-Gaia proper motion accelerations, to estimate dynamical masses. We compare agreements and discrepancies in mass estimates from these two methods.

The Present-day Mass Function of Star Clusters in the Solar Neighborhood

This work analyzes the present-day mass function (PDMF) of 93 star clusters utilizing Gaia Data Release 3 data, with membership determined by the StarGo machine-learning algorithm. The impact of unresolved binary systems on mass estimation is rigorously assessed, adopting three mass ratio profiles for correction. The PDMF is characterized by the power-law index, α, derived through a robust maximum likelihood method that avoids biases associated with data binning. The value of α for stars between the completeness limited mass of Gaia (with a mean 0.3 M ⊙ for our cluster samples) and 2 M ⊙ exhibits stability for clusters younger than 200 Myr, decreasing for older clusters, particularly when considering stars within the half-mass radius. The PDMF of these star clusters is consistent with a dynamically evolved Kroupa initial mass function via the loss of low-mass stars. Cluster morphology shows a correlation with α, as α values exhibit a decreasing trend from filamentary to tidal-tail clusters, mirroring the sequence of increasing cluster age. The dependence of α on the total cluster mass is weak, with a subtle increase for higher-mass clusters, especially outside the half-mass radius. We do not observe a correlation between α and the mean metallicity of the clusters. Younger clusters have lower metallicity compared to their older counterparts, which indicates that the older clusters might have migrated to the solar neighborhood from the inner disk. A comparison with numerical models incorporating a black hole population suggests the need for observations of distant, older, massive open clusters to determine whether or not they contain black holes.

Impact of α enhancement on the asteroseismic age determination of field stars

Aims. We investigated the theoretical biases affecting the asteroseismic grid-based estimates of stellar mass, radius, and age in the presence of a mismatch between the heavy element mixture of observed stars and stellar models. Methods. We performed a controlled simulation adopting a stellar effective temperature, [Fe/H], an average large frequency spacing, and a frequency of maximum oscillation power as observational constraints. Synthetic stars were sampled from grids of stellar models computed with different [α/Fe] values from 0.0 to 0.4. The mass, radius, and age of these objects were then estimated by adopting a grid of models with a fixed [α/Fe] value of 0.0. The experiment was repeated assuming different sets of observational uncertainties. In the reference scenario, we adopted an uncertainty of 1.5% in seismic parameters, 50 K in effective temperature, and 0.05 dex in [Fe/H]. A higher uncertainty in the atmospheric constraints was also adopted in order to explore the impact on the precision of the observations of the estimated stellar parameters. Results. Our Monte Carlo experiment showed that estimated parameters are biased up to 3% in mass, 1.5% in radius, and 4% in age when the reference uncertainty scenario was adopted. These values correspond to 45%, 48%, and 16% of the estimated uncertainty in the stellar parameters. These non-negligible biases in mass and radius disappear when adopting larger observational uncertainties because of the possibility of the fitting algorithm exploring a wider range of possible solutions. However, in this scenario, the age is significantly biased by −8%. Finally, we verified that the stellar mass, radius, and age can be estimated with a high accuracy by adopting a grid with the incorrect value of [α/Fe] if the metallicity [Fe/H] of the target is adjusted to match the Z in the fitting grid. In this scenario, the maximum bias in the age was reduced to 1.5%.

Measuring Body Composition and Functional Strength: Implications for the Clinical Assessment of Skeletal Muscle

Skeletal muscle represents the largest single component of the body, comprising up to 50% of total mass in healthy individuals. Body composition assessment has largely focused on overweight and obese individuals, but healthy skeletal muscle is also an important indicator of health and wellbeing. We hypothesized that estimates of lean body mass and empirical measures of functional strength should be directly correlated with one another. In the current study, we estimated body composition using two different field methods. Bioimpedance spectroscopy (BIS) employs 256 frequencies of low energy electrical current to estimate body composition. We used BIS (Impedimed SFB7) to determine percent body fat and fat free mass in physically active volunteers, ranging in age from 18 – 62 years. In addition, we used the Jackson and Pollock 3-site skin fold method to estimate these parameters from the same individuals. We also measured functional strength with a whole body dynamometer to determine mid-thigh pull strength, and a grip dynamometer to assess grip strength (Baseline Evaluation Instruments). Data collected from more than 75 men and women revealed significant correlations between fat-free mass (FFM) and both measures of functional strength. Interestingly, men and women fell along the same trend line, with women exhibiting similar strength for a given FFM. Moreover, functional strength standardized to FFM provides an objective measure of relative strength that was not different between men and women. The American Medical Association released a new policy statement about body mass index (BMI) in June of 2023, highlighting that BMI is an imprecise measure of body composition and recommending that alternative measures, such as more precise measurement of body composition, also be used. Indeed, we found that for individuals with a BMI of less than 30, there was direct relationship between FFM and functional strength. By contrast, percent body fat was not correlated with BMI within this range. We suggest that FFM and functional strength could be used to assess healthy weight, in conjunction with BMI. These measures could also be used to screen for sarcopenia, cachexia, and other conditions associated with significant muscle loss. Skeletal muscle represents an often underappreciated component of health and a more precise assessment of muscle mass and strength should be used as a measure of overall health. This work was supported by a Keenan Award at St. Bonaventure University. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

KMT-2023-BLG-1431Lb: A New q < 10−4 Microlensing Planet from a Subtle Signature

The current studies of microlensing planets are limited by small number statistics. Follow-up observations of high-magnification microlensing events can efficiently form a statistical planetary sample. Since 2020, the Korea Microlensing Telescope Network (KMTNet) and the Las Cumbres Observatory (LCO) global network have been conducting a follow-up program for high-magnification KMTNet events. Here, we report the detection and analysis of a microlensing planetary event, KMT-2023-BLG-1431, for which the subtle (0.05 mag) and short-lived (5 hr) planetary signature was characterized by the follow-up from KMTNet and LCO. A binary-lens single-source (2L1S) analysis reveals a planet/host mass ratio of q = (0.72 ± 0.07) × 10−4, and the single-lens binary-source (1L2S) model is excluded by Δχ 2 = 80. A Bayesian analysis using a Galactic model yields estimates of the host star mass of Mhost=0.57−0.29+0.33M⊙ , the planetary mass of Mplanet=13.5−6.8+8.1M⊕ , and the lens distance of DL=6.9−1.7+0.8 kpc. The projected planet-host separation of a⊥=2.3−0.5+0.5 au or a⊥=3.2−0.8+0.7 au, subject to the close/wide degeneracy. We also find that without the follow-up data, the survey-only data cannot break the degeneracy of central/resonant caustics and the degeneracy of 2L1S/1L2S models, showing the importance of follow-up observations for current microlensing surveys.

Transthoracic echocardiography is a simple tool for size matching in cardiac xenotransplantation.

Preoperative size matching is essential for both allogeneic and xenogeneic heart transplantation. In preclinical pig-to-baboon xenotransplantation experiments, porcine donor organs are usually matched to recipients by using indirect parameters, such as age and total body weight. For clinical use of xenotransplantation, a more precise method of size measurement would be desirable to guarantee a "perfect match." Here, we investigated the use of transthoracic echocardiography (TTE) and described a new method to estimate organ size prior to xenotransplantation. Hearts from n = 17 genetically modified piglets were analyzed by TTE and total heart weight (THW) was measured prior to xenotransplantation into baboons between March 2018 and April 2022. Left ventricular (LV) mass was calculated according to the previously published method by Devereux etal. and a newly adapted formula. Hearts from n = 5 sibling piglets served as controls for the determination of relative LV and right ventricular (RV) mass. After explantation, THW and LV and RV mass were measured. THW correlated significantly with donor age and total body weight. The strongest correlation was found between THW and LV mass calculated by TTE. Compared to necropsy data of the control piglets, the Devereux formula underestimated both absolute and relative LV mass, whereas the adapted formula yielded better results. Combining the adapted formula and the relative LV mass data, THW can be predicted with TTE. We demonstrate reliable LV mass estimation by TTE for size matching prior to xenotransplantation. An adapted formula provides more accurate results of LV mass estimation than the generally used Devereux formula in the xenotransplantation setting. TTE measurement of LV mass is superior for the prediction of porcine heart sizes compared to conventional parameters such as age and total body weight.

Mixed Learning- and Model-Based Mass Estimation of Heavy Vehicles

This research utilized long short-term memory (LSTM) to oversee an RLS-based mass estimator based on longitudinal vehicle dynamics for heavy-duty vehicles (HDVs) instead of using the predefined rules. A multilayer LSTM network that analyzed parameters such as vehicle speed, longitudinal acceleration, engine torque, engine speed, and estimated mass from the RLS mass estimator was employed as the supervision method. The supervisory LSTM network was trained offline to recognize when the vehicle was operated so that the RLS estimator gave an estimate with the desired accuracy and the network was used as a reliability flag. High-fidelity simulation software was employed to collect data used to train and test the network. A threshold on the error percentage of the RLS mass estimator was used by the network to check the reliability of the algorithm. The preliminary findings indicate that the reliability of the RLS mass estimator could be predicted by using the LSTM network.