Context. Near-Earth asteroids (NEAs) that may evolve into impactors deserve detailed threat assessment studies. Early physical characterization of a would-be impactor may help in optimizing impact mitigation plans. We first detected NEA 2023 DZ₂ on 27 February 2023. After that, it was found to have a minimum orbit intersection distance (MOID) with Earth of 0.00005 au as well as an unusually high initial probability of becoming a near-term (in 2026) impactor. Aims. We perform a rapid but consistent dynamical and physical characterization of 2023 DZ₂ as an example of a key response to mitigating the consequences of a potential impact. Methods. We used a multi-pronged approach, drawing from various methods (observational-computational) and techniques (spectroscopy-photometry from multiple instruments), and bringing the data together to perform a rapid and robust threat assessment. Results. The visible reflectance spectrum of 2023 DZ₂ is consistent with that of an X-type asteroid. Light curves of this object obtained on two different nights give a rotation period P = 6.2743 ± 0.0005 min with an amplitude A = 0.57 ± 0.14 mag. We confirm that although its MOID is among the smallest known, 2023 DZ₂ will not impact Earth in the foreseeable future as a result of secular near-resonant behaviour. Conclusions. Our investigation shows that coordinated observation and interpretation of disparate data provides a robust approach from discovery to threat assessment when a virtual impactor is identified. We prove that critical information can be obtained within a few days after the announcement of the potential impactor.

This study examines the response of the Consumer Price Index (CPI) in local currency to the COVID-19 pandemic using monthly data (March 2020–February 2022), comparatively for six European countries. We have introduced a model of multivariate adaptive regression that considers the quasi-periodic effects of pandemic waves in combination with the global effect of the economic shock to model the variation in the price of crude oil at international levels and to compare the induced effect of the pandemic restriction as well and the oil price variation on each country’s CPI. The model was tested for the case of six emergent countries and developed European countries. The findings show that: (i) pandemic restrictions are driving a sharp rise in the CPI, and consequently inflation, in most European countries except Greece and Spain, and (ii) the emergent economies are more affected by the oil price and pandemic restriction than the developed ones.

The survey of the nearby space and continuous monitoring of the Near Earth Objects (NEOs) and especially Near Earth Asteroids (NEAs) are essential for the future of our planet and should represent a priority for our solar system research and nearby space exploration. More computing power and sophisticated digital tracking algorithms are needed to cope with the larger astronomy imaging cameras dedicated for survey telescopes. The paper presents the NEARBY platform that aims to experiment new algorithms for automatic image reduction, detection and validation of moving objects in astronomical surveys, specifically NEAs. The NEARBY platform has been developed and experimented through a collaborative research work between the Technical University of Cluj-Napoca (UTCN) and the University of Craiova, Romania, using observing infrastructure of the Instituto de Astrofisica de Canarias (IAC) and Isaac Newton Group (ING), La Palma, Spain. The NEARBY platform has been developed and deployed on the UTCN's cloud infrastructure and the acquired images are processed remotely by the astronomers who transfer it from ING through the web interface of the NEARBY platform. The paper analyzes and highlights the main aspects of the NEARBY platform development, and the results and conclusions on the EURONEAR surveys.

"The potential threat of Near Earth Objects (NEO) requires a constant survey of the night sky to discover potentially dangerous objects and assess their future impact odds. Several ongoing surveys relying on human operators or automated techniques exist. One such example is the EURONEAR blink mini-survey project which over time developed from a pure manual approach to detecting asteroids to semi-automatic methods (NEARBY) using image processing and service-oriented approaches. In this paper, we propose an extension of NEARBY based on an ensemble model comprising three state-of-art machine learning models, some used in similar approaches. The proposed model is designed for a binary classification problem where candidate images may contain an asteroid in their center. Validation on a real-life dataset comprising 11,000 images shows that our ensemble model is capable of recovering about 55% of the asteroids missed by the previous NEARBY automated process while at the same time having a 0.88 recall on the asteroids already detected by NEARBY. Used together with NEARBY our model increased the detection rate from 89% to 95%."

The study presents an approach based on highly accurate nonlinear models to predict the impact of the transition from manufacturing to tourism on sectoral inflation and labor costs. The dataset used is slightly outdated, reflecting the period 2011-20...