A Planetary Microlensing Event with an Unusually Red Source Star: MOA-2011-BLG-291

We present the analysis of planetary microlensing event MOA-2011-BLG-291, which has a mass ratio of $q=(3.8\pm0.7)\times10^{-4}$ and a source star that is redder (or brighter) than the bulge main sequence. This event is located at a low Galactic latitude in the survey area that is currently planned for NASA's WFIRST exoplanet microlensing survey. This unusual color for a microlensed source star implies that we cannot assume that the source star is in the Galactic bulge. The favored interpretation is that the source star is a lower main sequence star at a distance of $D_S=4.9\pm1.3\,$kpc in the Galactic disk. However, the source could also be a turn-off star on the far side of the bulge or a sub-giant in the far side of the Galactic disk if it experiences significantly more reddening than the bulge red clump stars. However, these possibilities have only a small effect on our mass estimates for the host star and planet. We find host star and planet masses of $M_{\rm host} =0.15^{+0.27}_{-0.10}M_\odot$ and $m_p=18^{+34}_{-12}M_\oplus$ from a Bayesian analysis with a standard Galactic model under the assumption that the planet hosting probability does not depend on the host mass or distance. However, if we attempt to measure the host and planet masses with host star brightness measurements from high angular resolution follow-up imaging, the implied masses will be sensitive to the host star distance. The WFIRST exoplanet microlensing survey is expected to use this method to determine the masses for many of the planetary systems that it discovers, so this issue has important design implications for the WFIRST exoplanet microlensing survey

OGLE-2014-BLG-0962 and a Comparison of Galactic Model Priors to Microlensing Data

OGLE-2014-BLG-0962 (OB140962) is a stellar binary microlensing event that was well covered by observations from the Spitzer satellite as well as ground-based surveys. Modeling yields a unique physical solution: a mid-M+M-dwarf binary with M_(prim) = 0.20 ± 0.01 M☉ and M_(sec) = 0.16 ± 0.01 M☉, with projected separation of 2.0 ± 0.3 au. The lens is only D_(LS) = 0.41 ± 0.06 kpc in front of the source, making OB140962 a bulge lens and the most distant Spitzer binary lens to date. In contrast, because the Einstein radius (θ_E = 0.143 ± 0.007 mas) is unusually small, a standard Bayesian analysis, conducted in the absence of parallax information, would predict a brown dwarf binary. We compare the results of Bayesian analysis using two commonly used Galactic model priors to the measured values for a set of Spitzer lenses. We find all models tested predict lens properties consistent with the Spitzer data. Furthermore, we illustrate the methodology for probing the Galactic distribution of planets by comparing the cumulative distance distribution of the Spitzer two-body lenses to that of the Spitzer single lenses

Impact of AlphaFold on Structure Prediction of Protein Complexes: The CASP15-CAPRI Experiment

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homo-dimers, 3 homo-trimers, 13 hetero-dimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their 5 best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% for the targets compared to 8% two years earlier, a remarkable improvement resulting from the wide use of the AlphaFold2 and AlphaFold-Multimer software. Creative use was made of the deep learning inference engines affording the sampling of a much larger number of models and enriching the multiple sequence alignments with sequences from various sources. Wide use was also made of the AlphaFold confidence metrics to rank models, permitting top performing groups to exceed the results of the public AlphaFold-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem

Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem

The Role of Crypto Trading in the Economy, Renewable Energy Consumption and Ecological Degradation

The rapid growth of information technology and industrial revolutions provoked digital transformation of all sectors, from the government to households. Moreover, digital transformations led to the development of cryptocurrency. However, crypto trading provokes a dilemma loop. On the one hand, crypto trading led to economic development, which allowed attracting additional resources to extending smart and green technologies for de-carbonising the economic growth. On the other hand, crypto trading led to intensifying energy sources, which provoked an increase in greenhouse gas emissions and environmental degradation. The paper aims to analyse the connections between crypto trading, economic development of the country, renewable energy consumption, and environmental degradation. The data for analysis were obtained from: Our World in Data, World Data Bank, Eurostat, Ukrstat, Crystal Blockchain, and KOF Globalisation Index. To check the hypothesis, the paper applied the Pedroni and Kao panel cointegration tests, FMOLS and DOLS panel cointegration models, and Vector Error Correction Models. The findings concluded that the increasing crypto trading led to enhanced GDP, real gross fixed capital formation, and globalisation. However, in the long run, the relationship between crypto trading and the share of renewable energies in total energy consumption was not confirmed by the empirical results. For further directions, it is necessary to analyse the impact of crypto trading on land and water pollution

Two new free-floating or wide-orbit planets from microlensing

Planet formation theories predict the existence of free-floating planets that have been ejected from their parent systems. Although they emit little or no light, they can be detected during gravitational microlensing events. Microlensing events caused by rogue planets are characterized by very short timescales tE (typically below two days) and small angular Einstein radii θE (up to several μas). Here we present the discovery and characterization of two ultra-short microlensing events identified in data from the Optical Gravitational Lensing Experiment (OGLE) survey, which may have been caused by free-floating or wide-orbit planets. OGLE-2012-BLG-1323 is one of the shortest events discovered thus far (tE = 0.155 ± 0.005 d, θE = 2.37 ± 0.10μas) and was caused by an Earth-mass object in the Galactic disk or a Neptune-mass planet in the Galactic bulge. OGLE-2017-BLG-0560 (tE = 0.905 ± 0.005 d, θE = 38.7 ± 1.6μas) was caused by a Jupiter-mass planet in the Galactic disk or a brown dwarf in the bulge. We rule out stellar companions up to a distance of 6.0 and 3.9 au, respectively. We suggest that the lensing objects, whether located on very wide orbits or free-floating, may originate from the same physical mechanism. Although the sample of ultrashort microlensing events is small, these detections are consistent with low-mass wide-orbit or unbound planets being more common than stars in the Milky Way