Time Span Of Observations Research Articles

An investigation of ocean mass budget in the East China Sea during the GRACE era

The Gravity Recovery and Climate Experiment (GRACE) mission provides uniquely high-precision observations for monitoring ocean mass changes (OMC), allowing for the establishment and evaluation of the ocean mass budget in conjunction with satellite altimetry and temperature and salinity observations. However, it is challenging to perform OMC closed-loop validation in the East China Sea (ECS) due to potential biases in the individual model and the lack of certain data processing. In this study, we comprehensively analyze the ocean mass budget in the ECS during the GRACE era (2005–2015) by utilizing multiple datasets, mainly consisting of three official GRACE RL06 solutions, three altimetry products, and four ocean reanalysis products. The effect of ocean bottom deformation, neglected in previous studies, is −0.38 ± 0.06 mm/yr, and we estimate a more accurate ensemble sea level change to be 4.05 ± 1.50 mm/yr in the ECS from the altimetry products. There are discrepancies between leakage-corrected GRACE OMC observations and steric-corrected altimeter OMC estimations in both the seasonal signals and the long-term trends (e.g., 6.25 mm/yr vs. 4.22 mm/yr). These discrepancies are strongly correlated with sediment runoff from the Yangtze River and in-situ sediment observations, suggesting that ocean sediment accumulation should be considered in the ocean mass budget in the ECS. Since in-situ sediment data are estimated over ∼100 years, we employ an empirical estimation method to determine the corresponding data during the period 2005–2015, to avoid potential biases caused by inconsistencies in observational timespans. The results show that sediment mass changes can explain about 96 % of residual trends. Our results emphasize the significant impact of sediment on improving the ocean mass budget in the ECS, offering a novel perspective for estimating ocean mass changes in other coastal regions.

Analysis Of The Influence Of Domestic Investment, Foreign Direct Investment, Popu-lation, Crime Rate, And Unemployment Rate On Economic Growth In Deli Serdang Regency: ARDL Model Approach

The aim of development in a country or region is to improve the welfare and prosperity of society in a fair and equitable manner, one of which is by increasing sustainable economic growth. The main objective of this study is to analyze the effect of domestic investment, foreign investment, population, crime and unemployment on economic growth in Deli Serdang Regency. The data analysis method used is the Autoregressive Distributed Lag (ARDL) approach in the time series data model and the observation time span of this study starts from 2010 to 2021 where data interpolation will be carried out in quarterly. According to the results of the analysis, the variables domestic investment and foreign direct investment have a positive significant effect on economic growth. Meanwhile, the variables of population, crime and unemployment have a negative significant impact on economic growth in the long run. However, in the short run, the variables of direct investment, foreign investment, population and crime have a positive significant impact on economic growth. On the other hand, only the number of unemployed has a negative significant effect on economic growth. Based on the results of this study, it is appropriate for the Government of Deli Serdang Regency to optimize programs that are oriented towards increasing investment both domestic and foreign, suppressing the rate of population growth and the number of unemployed and maintaining regional security in the Deli Serdang Regency area.

A Scaling Relation for Core Heating by Giant Impacts and Implications for Dynamo Onset

AbstractAccretional heating of Earth's interior during formation is pivotal to its subsequent thermal and chemical evolution. In particular, impact heating of Earth's core is expected, but its amplitude and radial distribution within the core is unknown and could influence the onset of the geodynamo. The uncertainty is due, in part, to the lack of constraints on the temperature of the interior following formation due to the difficulty of preserving a record of such a high energy environment, and the assertion that super‐heating during formation would be rapidly lost through magma ocean cooling. Here we systematically investigate core heating due to giant impacts using a Smoothed Particle Hydrodynamics (SPH) code with simulations spanning a range of impact angles, velocities, and masses. From these simulations we derive a scaling relation for core heating that depends on the impact parameters and predicts the radial core temperature profile following the impact. Our findings show that a significant amount of heat is deposited into the core, with a canonical impact scenario resulting in an average core temperature increase of about 3000 K, approximately 500 K higher than that of the overlying mantle. In this case the heat distribution within the core produces a strong thermal stratification. We use a parameterized cooling model to estimate that the core could have cooled to an adiabatic state ∼290 Myr after a canonical impact, which is consistent with the observed time span between the age of the Moon and evidence for an active geodynamo.

Unveiling hidden companions in post-common-envelope binaries: A robust strategy and uncertainty exploration

Context. Some post-common-envelope binaries (PCEBs) are binary stars with short periods that exhibit significant period variations over long observational time spans. These eclipse timing variations (ETVs) are most likely to be accounted for by the presence of an unseen massive companion, potentially of planetary or substellar nature, and the light-travel time (LTT) effect. The existence of such companions challenges our current understanding of planetary formation and stellar evolution. Aims. In this study, our main objective is to describe the diversity of compatible nontransit companions around PCEBs and explore the robustness of the solutions by employing tools for uncertainty estimation. We select the controversial data of the QS Vir binary star, which previous studies have suggested hosts a planet. Methods. We employ a minimizing strategy, using genetic algorithms to explore the global parameter space followed by refinement of the solution using the simplex method. We evaluate errors through the classical Markov chain Monte Carlo (MCMC) approach and discuss the error range for parameters, considering the 1σ values obtained from the minimization. Results. Our results highlight the strong dependence of ETV models for close binaries on the dataset used, which leads to relatively loose constraints on the parameters of the unseen companion. We find that the shape of the O – C curve is influenced by the dataset employed. We propose an alternative method to evaluate errors on the orbital fits based on a grid search surrounding the best-fit values, obtaining a wider range of plausible solutions that are compatible with goodness-of-fit statistics. We also analyze how the parameter solutions are affected by the choice of the dataset, and find that this system continuously changes the compatible solutions as new data are obtained from eclipses. Conclusions. The best-fit parameters for QS Vir correspond to a low-mass stellar companion (57.71 Mjup ranging from ~40 to ~64 Mjup) on an eccentric orbit (e = 0.91−0.17+0.07) with a variety of potential periods (P = 16.69−0.42+0.47 yr.). Most solutions within 1σ exhibit regular orbits, despite their high eccentricity. Additional observations are required to accurately determine the period and other parameters of the unseen companion. In this context, we propose that a fourth body should not be modeled to fit the data, unless new observations considerably modify the computed orbital parameters. This methodology can be applied to other evolved binary stars suspected of hosting companions.

Observing Temporally Varying Synoptic‐Scale Total Alkalinity and Dissolved Inorganic Carbon in the Arctic Ocean

AbstractThe long‐term absorption by the oceans of atmospheric carbon dioxide is leading to the slow decline of ocean pH, a process termed ocean acidification (OA). The Arctic is a challenging region to gather enough data to examine the changes in carbonate chemistry over sufficient scales. However, algorithms that calculate carbonate chemistry parameters from more frequently measured parameters, such as temperature and salinity, can be used to fill in data gaps. Here, these published algorithms were evaluated against in situ measurements using different data input types (data from satellites or in situ re‐analysis climatologies) across the Arctic Ocean. With the lowest uncertainties in the Atlantic influenced Seas (AiS), where re‐analysis inputs achieved total alkalinity estimates with Root Mean Squared Deviation (RMSD) of 21 μmol kg−1 and a bias of 2 μmol kg−1 (n = 162) and dissolved inorganic carbon RMSD of 24 μmol kg−1 and bias of −14 μmol kg−1 (n = 262). AiS results using satellite observation inputs show similar bias but larger RMSD, although due to the shorter time span of available satellite observations, more contemporary in situ data would provide further assessment and improvement. Synoptic‐scale observations of surface water carbonate conditions in the Arctic are now possible to monitor OA, but targeted in situ data collection is needed to enable the full exploitation of satellite observation‐based approaches.

Oral anticoagulation in heart failure complicated by atrial fibrillation: a nationwide routine data study

Abstract Background/Introduction Heart failure (HF) is frequently complicated by atrial fibrillation (AF). The co-occurrence of both conditions worsens the overall patient prognosis (1). To reduce the risk of thromboembolic complications, current guidelines highly recommend an oral anticoagulant (OAC) therapy in the majority of patients affected (2). Purpose Aim of this study was to evaluate whether a permanent OAC therapy in patients with HF and AF leads to favourable outcomes. Additional benefits of new oral anticoagulants (NOACs), compared to vitamin K antagonists (VKA), were further assessed. Methods Anonymous routine data of patients who were medically insured at the largest German health insurance provider and had a claims record for hospitalisation with the main diagnosis of HF and AF (2017-2019) were included. Admission due to HF in the previous year, incomplete medication data within 90 days after hospital stay as well as the diagnoses of congenital anomaly, transplantation, asthma, and age under 30 years were exclusion criteria. The endpoints of mortality and readmission rate for all-cause and stroke/intracranial bleeding (ICB) 91-365 days after the index hospitalisation were analysed. For this, information about the medications was taken from the pharmacy database. Kaplan-Meier survival curves and multivariable Cox regression models were used to evaluate the impact of medication on outcome. Adjusted hazard ratios (HRs) and 95% confidence intervals (95% CIs) were calculated. Patient age, sex, and comorbidities were evaluated as independent factors, including all variables of the CHA2DS2-VASc score. Results We included n = 180,316 cases (see figure 1). The median age was 81 years (interquartile range of 76-86) with 55.6% of the patients being female. 96.81% had a CHA2DS2-VASc score of ≥ 2. We found OAC prescription in 80.6% (VKA: 21.7%; direct factor Xa inhibitors (FXaI): 60.0%; direct thrombin inhibitors (DTI): 3.4%). In 8,087 cases, more than one OAC was prescribed. The mortality rate was 19.1%, readmission rate was 29.9% and stroke/ICB occurred in 1.9% during the observed time span. As presented in figure 2, the risk of death was lower with any OAC (HR 0.77, 95% CI 0.75-0.79) but without significant differences in OAC type (VKA: HR 0.73, 95% CI 0.71-0.76; FXaI: HR 0.77, 95% CI 0.75-0.78; DTI: HR 0.71, 95% CI 0.66-0.77). The total readmission rate (HR 0.97, 95% CI 0.94-0.99) and readmission for stroke/ICB (HR 0.71, 95% CI 0.65-0.77) was likewise lower with OAC use. Conclusion(s) Routine data confirm the beneficial outcome of OAC therapy in patients with HF complicated by AF regarding mortality and readmission for all-cause as well as for stroke/ICB. No additional benefits were visible with the use of NOACs.Figure 1.Patient selection criteria.Figure 2.Kaplan-Meier survival (OAC).

Quality and physiological evaluation of tomato subjected to different supplemental lighting systems

Light is a crucial mediator in plants of growth and development, secondary metabolism, and signaling of potentially beneficial phytochemicals. The present study investigated three indoor supplemental light treatments, HPS, LED, and LED+IR, applied during tomato cultivation, in which non-destructive and destructive analyses were performed at two time points to record the physiological responses and effects of these artificial lights on the growth and quality of the produce. An infrared thermometer and thermal cameras were used throughout the experiment to record temperature changes under each growing condition. LED+IR supplemented light showed a decrease in photosynthetic pigments, such as chlorophyll a, b, and carotenoids but induced an increased number of flowers, heavier tomato fruits, enhanced anthocyanins, phenolic index, lipid peroxidation, titratable acidity, and reduced nitrate accumulation. Moreover, higher generated temperatures under LED+IR helped tomato plants to reduce white fly infestation, but suppressed plant height. HPS light performed better than both LED and LED+IR in terms of total sugar accumulation, total carotenoids, water content, plant height, and leaf lipid peroxidation at harvest. Lycopene, ß-carotene, brix index were remarkable under HPS lighting but under the same conditions the number of whiteflies, however, was the highest in HPS among all the tested light treatments. In terms of fruit color analysis, maximum redness (a*), reduced hue angle, and chroma were observed under LED+IR while LED lighting in brightness (L*), and HPS in yellowness (b*) were prominent. However, LED in particular was insufficiently effective in acquiring any possible physiological and qualitative characteristics of tomato plants and fruits for the observed time span of the experiment. Hence, LED+IR has been shown to boost the accumulation of bioactive chemicals, improve fruit quality, promote more rapid and early flowering in tomato plants, and can serve as an efficient replacement for traditional indoor illumination.

An advanced multipole model of the (130) Elektra quadruple system

Context. The Ch-type asteroid (130) Elektra is orbited by three moons, making it the first quadruple system in the main asteroid belt. Aims. We aim to characterise the irregular shape of Elektra and construct a complete orbital model of its unique moon system. Methods. We applied the All-Data Asteroid Modelling (ADAM) algorithm to 60 light curves of Elektra, including our new measurements, 46 adaptive-optics (AO) images obtained by the VLT/SPHERE and Keck/Nirc2 instruments, and two stellar occultation profiles. For the orbital model, we used an advanced N-body integrator, which includes a multipole expansion of the central body (with terms up to the order ℓ = 6), mutual perturbations, internal tides, and the external tide of the Sun acting on the orbits. We fitted the astrometry measured with respect to the central body and also relatively, with respect to the moons themselves. Results. We obtained a revised shape model of Elektra with the volume-equivalent diameter (201 ± 2) km. Of two possible pole solutions, (λ,β) = (189; −88) deg is preferred, because the other one leads to an incorrect orbital evolution of the moons. We also identified the true orbital period of the third moon S/2014 (130) 2 as P2 = (1.642112 ± 0.000400) days, which is in between the other periods, P1 ≃ 1.212days, P3 = 5.300 days, of S/2014 (130) 1 and S/2003 (130) 1, respectively. The resulting mass of Elektra, (6.606-0.013+0.007) ×1018 kg, is precisely constrained by all three orbits. Its bulk density is then (1.536 ± 0.038) g cm−3. The expansion with the assumption of homogeneous interior leads to the oblateness J2 = −C20 ≃ 0.16. However, the best-fit precession rates indicate a slightly higher value, ≃0.18. The number of nodal precession cycles over the observation time span 2014–2019 is 14, 7, and 0.5 for the inner, middle, and outer orbits. Conclusions. Future astrometric or interferometric observations of Elektra’s moons should constrain these precession rates even more precisely, allowing the identification of possible inhomogeneities in primitive asteroids.

Moon Imaging Performance of FAST Radio Telescope in Bistatic Configuration with Other Radars

Ground-based radar has been used for Moon imaging for more than 60 years. Five-hundred-meter Aperture Spherical radio Telescope (FAST), as the largest radio telescope on Earth, holds significant potential for celestial imaging missions with its exceptional sensitivity. A bistatic Synthetic Aperture Radar (SAR) Moon imaging model that incorporates FAST and other transmitting radars is presented. The objective of this paper is to design the imaging parameters of this bistatic configuration based on the required resolution, and to estimate the resolution performance based on a given bistatic system capability. Considering the ultra-far range and the ultra-long observation time between the radars and the Moon, the geometric relationship involved in this bistatic configuration is significantly distinct from the bistatic configuration of airborne and spaceborne radars. Therefore, this paper accurately derives the two-dimensional resolution on the Moon’s surface. First of all, the models of the Earth’s surface and the Moon’s surface, and the celestial motion of the Earth and Moon are established using WGS-84 and JPL-DE421, given by STK. Secondly, the bistatic range history within the observation time is calculated in terms of continuous celestial motion instead of the popular ‘stop-and-go’ assumption. Thirdly, no approximation is used in the resolution derivation process, and, in addition to the two-dimensional resolutions, the incident angle and the included angle are also given to describe the imaging performance. This method can also be extended to other bistatic-station and single-station celestial imaging, providing support for radar location and parameters design, for observation time span selection, for observation area selection, and for imaging performance estimation. The echo generation and imaging for point targets set on the Moon are shown. The simulation results prove the validity and accuracy of the proposed method in the paper.

Effects of non-tidal loading applied in VLBI-only terrestrial reference frames

We investigate the impact of the reduction of non-tidal loading (NTL) in the computation of secular terrestrial reference frames (TRFs) from Very Long Baseline Interferometry (VLBI) observations. There are no conventional models for NTL in the geodetic community yet, but the Global Geophysical Fluid Center prepared a set of corresponding site displacements for the 2020 realizations of the International Terrestrial Reference System. We make use of these data, which comprise the total NTL consisting of non-tidal atmospheric, oceanic, and hydrological loading. The displacement series contain linear trends (i.e., offsets plus drifts), and since these affect the estimated linear station positions and the realized geodetic datum in a secular TRF, we remove the trends before reducing the NTL in our computations. The displacements are applied at two different levels of the parameter estimation process: the observation and the normal equation level. This way, we can analyze whether the latter offers a suitable approximation if the original observations have not been reduced by NTL. We find that the TRF statistics are hardly affected by the NTL. The largest impact is given for the secular motion of antennas with short observation time spans. The application level is basically irrelevant for the linear antenna positions, but it leads to differences in the rates of the jointly estimated Earth orientation parameters (EOPs). Secular TRF solutions and session solutions deviate with respect to the parameterization of the antenna coordinates, and thus also with respect to the correlations between the estimated antenna parameters and the EOPs. Due to this, the consistently estimated EOP series also show differences. However, for both solution types the reduction of the NTL leads to a change of the annual signal in the EOP series.

The 95 per cent confidence interval for the mean sea-level change rate derived from tide gauge data

SUMMARYTide gauge (TG) data are crucial for assessing global sea-level and climate changes, coastal subsidence and inundation. Mean sea-level (MSL) time-series derived from TG data are autocorrelated. The conventional ordinary least-squares regression method provides reasonable estimates of relative sea-level (RSL) change rates (linear trends) but underestimates their uncertainties. In order to cope with the autocorrelation issue, we propose an approach that uses an ‘effective sample size’ (${N}_{\mathrm{ eff}}$) to estimate the uncertainties (±95 per cent confidence interval, or 95 per cent CI for short). The method involves decomposing the monthly MSL time-series into three components: a linear trend, a periodic component and a noise time-series. The ${N}_{\mathrm{ eff}}$ is calculated according to the autocorrelation function (ACF) of the noise time-series. We present an empirical model that fits an inverse power-law relationship between 95 per cent CI and time span (T) based on 1160 TG data sets globally distributed, where $95\ \mathrm{ per}\ \mathrm{ cent}\,\mathrm{ CI} = 179.8{T}^{ - 1.29}$. This model provides a valuable tool for projecting the optimal observational time span needed for the desired uncertainty in sea-level rise rate or coastal subsidence rate from TG data. It suggests that a 20-yr TG time-series may result in a 3–5 mm yr−1 uncertainty (95 per cent CI) for the RSL change rate, while a 30-yr data set may achieve about 2 mm yr−1 uncertainty. To achieve a submillimetre per year (< 1 mm yr−1) uncertainty, approximately 60 yr of TG observations are needed. We also present a Python module (TG_Rate_95CI.py) for implementing the methodology. The Python module and the empirical model have broad applications in global sea-level rise and climate change studies, and coastal environmental and infrastructure planning, as well as Earth science education.

Detection of seven 2+2 doubly eclipsing quadruple systems

In this work, we study a heterogeneous group of seven stellar systems for the first time. Despite their different distances or spectral types, all of them belong to a very rare group of quadruple systems of 2+2 architecture, where both of the inner pairs harbor eclipsing binaries. These systems are: ASASSN-V J102911.57−522413.6 (inner periods 0.57272, and 3.79027 days), V1037 Her (0.78758 and 5.80348 days), WISE J181904.2+241243 (0.36713 and 0.41942 days), V2894 Cyg (2.57434 and 1.30579 days), NSVS 5725040 (1.79368 and 0.76794 days), WISE J210230.8+610816 (1.84324 and 0.57159 days), and ZTF J220518.78+592642.1 (2.79572 and 3.34615 days). Their outer mutual periods are: 9.3, 25.4, 18.7, 27.5, 2.6, 2.2, and 14.0 yr, respectively. These outer periodicities were derived using longer time span of photometric observations of these systems and analysing their period changes of both inner pairs via ETVs (eclipse-timing variations). Most of these studied systems are detached, as evidenced by the proper modelling of their light curves. A few of them show significant eccentric orbits with apsidal motion (e.g., V2894 Cyg, and NSVS 5725040). Further spectroscopic follow-up observations would offer a better characterization of the component star’s parameters (for e.g., NSVS 5725040), as well as a potential interferometric detection of the systems as real doubles on their mutual orbits (for e.g., V1037 Her). A rather interesting excess of systems close to a 3:2 mean motion resonance is seen only for early spectral-type stars with higher temperatures.

Analytical and Computational Modeling for Multi-Degree of Freedom Systems: Estimating the Likelihood of an FOWT Structural Failure

Wind turbines and their associated parts are subjected to cyclical loads, such as bending, torque, longitudinal stresses, and twisting moments. The novel spatiotemporal reliability technique described in this research is especially useful for high-dimensional structural systems that are either measured or numerically simulated during representative observational time span. As this study demonstrates, it is possible to predict risks of dynamic system failure or damage given the in situ environmental load pattern. As an engineering example for this reliability, the authors have chosen 10-MW floating wind turbines and their dynamic responses, under environmental loadings, caused by wind and waves. The aim of this study was to benchmark a state-of-the-art approach suitable for the reliable study of offshore wind turbines. Existing reliability methods do not easily cope with dynamic system high dimensionality. The advocated reliability technique enables accurate and efficient assessment of dynamic system failure probability, accounting for system nonlinearities and high dimensionality as well as cross-correlations between different system components.

Correlation between activity indicators: Hα and Ca II lines in M-dwarf stars

Context. Different approaches have been adopted to study both short- and long-term stellar magnetic activity, and although the mechanisms by which low-mass stars generate large-scale magnetic fields are not well understood, it is known that stellar rotation plays a key role. Aims. There are stars that show a cyclical behaviour in their activity studied on the blue side of the visible spectrum, which can be explained by solar dynamo or αΩ dynamo models. However, when studying late-type dwarf stars, they become redder and it is necessary to implement other indicators to analyse their magnetic activity. In the present work, we perform a comparative study between the best-known activity indicators so far defined from the Ca II and Hα lines to analyse M-dwarf stars. Methods. We studied a sample of 29 M stars with different chromospheric activity levels and spectral classes ranging from dM0 to dM6. To do so, we employed 1796 spectra from different instruments with a median time span of observations of 21 yr. The spectra have a wide spectral range that allowed us to compute the chrosmospheric activity indicators based on Ca II and Hα. In addition, we complemented our data with photometric observations from the TESS space mission for better stellar characterisation and short-term analysis. Results. We obtained a good and significant correlation (ρ = 0.91) between the indexes defined from the two lines for the whole set of stars in the sample. However, we found that there is a deviation for faster rotators (with Prot < 4 days) and higher flare activity (at least one flare per day). For the individual analysis, we found that the indexes computed individually for each star correlate independently of the level of chromospheric emission and the rotation period. Conclusions. There is an overall positive correlation between Ca II and Hα emission in dM stars, except during flare events. In particular, we found that low-energy high-frequency flares could be responsible for the deviation in the linear trend in fast-rotator M dwarfs. This implies that the rotation period could be a fundamental parameter to study the stellar activity and that the rotation could drive the magnetic dynamo in low-mass active stars.

A lower bound on intergalactic magnetic fields from time variability of 1ES 0229+200 from MAGIC and Fermi/LAT observations

Context. Extended and delayed emission around distant TeV sources induced by the effects of propagation of γ ray s through the intergalactic medium can be used for the measurement of the intergalactic magnetic field (IGMF). Aims. We search for delayed GeV emission from the hard-spectrum TeV γ-ray emitting blazar 1ES 0229+200, with the goal of detecting or constraining the IGMF-dependent secondary flux generated during the propagation of TeV γ rays through the intergalactic medium. Methods. We analysed the most recent MAGIC observations over a 5 year time span, and complemented them with historic data of the H.E.S.S. and VERITAS telescopes, along with a 12-year-long exposure of the Fermi/LAT telescope. We used them to trace source evolution in the GeV–TeV band over a decade and a half. We used Monte Carlo simulations to predict the delayed secondary γ-ray flux, modulated by the source variability, as revealed by TeV-band observations. We then compared these predictions for various assumed IGMF strengths to all available measurements of the γ-ray flux evolution. Results. We find that the source flux in the energy range above 200 GeV experiences variations around its average on the 14-year time span of observations. No evidence for the flux variability is found in the 1 − 100 GeV energy range accessible to Fermi/LAT. The non-detection of variability due to delayed emission from electromagnetic cascade developing in the intergalactic medium imposes a lower bound of B > 1.8 × 10−17 G for the long-correlation-length IGMF and B > 10−14 G for an IGMF of cosmological origin. Though weaker than the one previously derived from the analysis of Fermi/LAT data, this bound is more robust, being based on a conservative intrinsic source spectrum estimate and accounting for the details of source variability in the TeV energy band. We discuss implications of this bound for cosmological magnetic fields that might explain the baryon asymmetry of the Universe.

KOBEsim: A Bayesian observing strategy algorithm for planet detection in radial velocity blind-search surveys

Context. Ground-based observing time is precious in the era of exoplanet follow-up and characterization, especially in high-precision radial velocity instruments. Blind-search radial velocity surveys thus require a dedicated observational strategy in order to optimize the observing time, which is particularly crucial for the detection of small rocky worlds at large orbital periods. Aims. We developed an algorithm with the purpose of improving the efficiency of radial velocity observations in the context of exoplanet searches, and we applied it to the K-dwarfs Orbited By habitable Exoplanets experiment. Our aim is to accelerate exoplanet confirmations or, alternatively, reject false signals as early as possible in order to save telescope time and increase the efficiency of both blind-search surveys and follow-up of transiting candidates. Methods. Once a minimum initial number of radial velocity datapoints is reached in such a way that a periodicity starts to emerge according to generalized Lomb-Scargle periodograms, that period is targeted with the proposed algorithm, named KOBEsim. The algorithm selects the next observing date that maximizes the Bayesian evidence for this periodicity in comparison with a model with no Keplerian orbits. Results. By means of simulated data, we proved that the algorithm accelerates the exoplanet detection, needing 29-33% fewer observations and a 41–47% smaller time span of the full dataset for low-mass planets (mp < 10 M⊕) in comparison with a conventional monotonic cadence strategy. For 20 M⊕ planets we found a 16% enhancement in the number of datapoints. We also tested KOBEsim with real data for a particular KOBE target and for the confirmed planet HD 102365 b. These two tests demonstrate that the strategy is capable of speeding up the detection by up to a factor of 2 (i.e., reducing both the time span and number of observations by half).

Precise dynamical masses of new directly imaged companions from combining relative astrometry, radial velocities, and HIPPARCOS-Gaia eDR3 accelerations

Aims. With an observing time span of more than 20 yr, the CORALIE radial-velocity survey is able to detect long-term trends in data corresponding to companions with masses and separations accessible to direct imaging. Combining exoplanet detection techniques, such as radial velocities from the CORALIE survey, astrometric accelerations from HIPPARCOS and Gaia eDR3, and relative astrometry from direct imaging, removes the degeneracy of unknown orbital parameters. This allows precise model-independent masses of detected companions to be derived, which provides a powerful tool to test models of stellar and substellar mass-luminosity relations. Methods. Long-term precise Doppler measurements with the CORALIE spectrograph reveal radial-velocity signatures of companions on long-period orbits. The long baseline of radial-velocity data allows the detectability of the companion candidates to be assessed with direct imaging. We combine long-period radial-velocity data with absolute astrometry from HIPPARCOS and Gaia eDR3 and relative astrometry derived from new direct imaging detections with VLT/SPHERE to fit orbital parameters and derive precise dynamical masses of these companions. Results. In this paper we report the discovery of new companions orbiting HD 142234, HD 143616, and HIP 22059, as well as the first direct detection of HD 92987 B, and update the dynamical masses of two previously directly imaged companions: HD 157338 B and HD 195010 B. The companions span a period range of 32–279 yr and are all very low-mass stellar companions, ranging from 218 to 487 MJup. We compare the derived dynamical masses to mass-luminosity relations of very low-mass stars (<0.5 M⊙), and discuss the importance of using precursor radial-velocity and astrometric information to inform the future of high-contrast imaging of exoplanets and brown dwarfs.

Sea Surface Salinity Inversion Model for Changjiang Estuary and Adjoining Sea Area with SMAP and MODIS Data Based on Machine Learning and Preliminary Application

Sea surface salinity (SSS) is one of the most important basic parameters for studying the oceanographic processes and is of great significance in identifying oceanic currents. However, for a long time, the salinity observation in the estuary and coastal waters has not been well resolved due to the technology limitation. In this study, the SSS inversion models for the Changjiang Estuary and the adjacent sea waters were established based on machine learning methods, using SMAP (Soil Moisture Active and Passive) salinity data combined with the specific bands and bands ratios of MODIS (Moderate Resolution Imaging Spectroradiometer). The performance of the three machine learning methods (Random Forest, Particle Swarm Optimization Support Vector Regression (PSO-SVR) and Automatic Machine Learning (TPOT)) are compared with accuracy verification by the in-situ measured SSS. Random Forest is proven to be effective for the SSS inversion in flood season, whereas TPOP performs the best for the dry season. The machine learning-based models effectively solve the problem of insufficient time span of SSS observation from salinity satellites. At the same time, an empirical algorithm was established for the SSS inversion for the sea areas with low salinity (<30 psu) where the machine learning based model fails with great errors. The average deviation of the complex SSS inversion models is −0.86 psu, validated with Copernicus Global Ocean Reanalysis Data. The long term series SSS dataset of March and August from 2003 to 2020 was then constructed to observe the salinity distribution characteristics of the flood season and the dry season, respectively. It is indicated that the distribution pattern of CDW can be divided into three categories: northeast-oriented expansion pattern, multi direction isotropic expansion pattern, and a turn pattern of which CDW shows changing direction, namely the northeast-southeast expansion pattern. The pattern of CDW expansion is indicated to be the comprehensive effect of the interaction of different currents. In addition, it is noteworthy that CDW shows increasing expansion with decreasing SSS in the front plume, especially in the flood season. This study not only gives a feasible solution for effective SSS observation, but also provides a dataset of basic oceanographic parameters for studying the coastal biogeochemical processes, evolution of land-sea interaction, and changing trend of material and energy transport by the CDW in the west Pacific boundary.

Model Makro-Ekonometrika Postur Anggaran Pendapatan dan Belanja Negara (APBN) Indonesia

This research aims to develop a Macro-Econometric Model of State Budget Posture and its Application for Impact Analysis of Fiscal and Monetary Policy. The approach used is the Macro-Econometric model, also known as the Indonesian State Budget Posture model. The time span of the data series observation is from 1990–2019. The Macro-Econometric Model which is used for APBN Posture is a system of simultaneous equations which is estimated of using two stages least squares (2SLS) method, while the solution to solve the system of equations used the Newton method. The results of the analysis show that economic growth is 2.11 percent, but under the pessimistic scenario, the contraction growth is -2.94%, while in the moderate scenario the contraction is -1.88 percent in 2020. The budget deficit in 2020 is estimated at 6.41 percent of GDP. A budget deficit of below 3 percent of GDP is expected to be achieved in 2023. For the 2020-2024 period, the primary balance is negative, which indicates that the government does not have funds to finance debt interest, so the new debt is also used to pay debt interest. It is more appropriate to finance the budget deficit from domestic sources of funds in order to avoid fluctuations in rupiah exchange rate fluctuations.

Earthquake size: An example of a statistical distribution that lacks a well-defined mean

Power-law distributions are observed to describe many physical phenomena with remarkable accuracy. In some cases, the distribution gives no indication of a cutoff in the tail, which poses interesting theoretical problems, because its average is then infinite. It is also known that the averages of samples of such data do not approach a normal distribution, even if the sample size increases. These problems have previously been studied in the context of random walks. Here, we present another example in which the sample average increases with the sample size. In the Gutenberg–Richter law for earthquakes, we show that the cumulative energy released by earthquakes grows faster than linearly with time. Here, increasing the time span of observation corresponds to increasing the sample size. While the mean of released energy is not well defined, its distribution obeys a non-trivial scaling law.