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Bow shock, where the solar wind first encounters the Martian environment, reflects the complex interplay between the solar wind and Martian upper atmosphere and crustal fields. However, a comprehensive understanding of Martian bow shock dynamics remains elusive due to limited multi-spacecraft observations. Here, leveraging the joint observations from China’s Tianwen-1 and NASA’s Mars Atmosphere and Volatile EvolutioN (MAVEN), we reveal Martian bow shock oscillations with a temporal scale of minutes and spatial extents of hundreds of kilometers during weakly disturbed solar wind. Our analysis of the observations along with three-dimensional simulations suggests that magnetosonic Mach number is the most sensitive parameter influencing the bow shock, and a slow solar wind stream that favors low Mach numbers may lead to the large-scale bow shock oscillations and the whole Martian space environment. This finding advances our understanding of the interactions between the solar wind and non-magnetized planets. Mars’ bow shock, where the solar wind meets the planet’s plasma environment, responds dynamically to solar wind conditions. Here, the authors show that even under relatively calm solar wind, it globally oscillates within minutes and shifts by hundreds of kilometers.

A novel Gram-negative bacterium, designated strain SN16T, was isolated from a harmful algal bloom (HAB). Strain SN16T exhibited potent, broad-spectrum algicidal activity against the colony-forming alga Phaeocystis globosa and eight other HAB-causing species, highlighting its potential as a promising candidate for the biological control of HABs. A phylogenetic analysis of 16S rRNA gene sequences placed strain SN16T within the genus Flagellimonas. The average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) values between strain SN16T and its relatives were 75.4–91.4% and 19.3–44.0%, respectively. These values fall below the established thresholds for species delineation, confirming that SN16T represents a novel species. A chemotaxonomic analysis revealed its dominant cellular fatty acids to be iso-C15:0 and iso-C15:1 G. The major polar lipid was phosphatidylethanolamine, and the primary respiratory quinone was menaquinone-6. Genome mining identified 11 biosynthetic gene clusters (BGCs), including those encoding for terpenes, ribosomal peptide synthetases, and non-ribosomal peptide synthetases. By integrating BGC analysis with the observed algicidal activities, we predicted that pentalenolactone and xiamycin analogues are the likely causative compounds. Based on this polyphasic evidence, strain SN16T is proposed as a novel species of the genus Flagellimonas, named Flagellimonas algicida sp. nov. This is the first report of Flagellimonas species exhibiting broad-spectrum algicidal activity, including activity against the colonial form of P. globosa—a key ecological challenge in HAB mitigation.

Quantifying the rate at which the large-scale solar-wind structure evolves is important for both understanding the physical processes occurring in the corona and for space-weather forecast improvement. Models of the global corona and heliosphere typically assume that the ambient solar-wind structure is steady and corotates with the Sun, which is generally expected to be more valid at solar minimum than solar maximum, but this has not been well tested. Similarly, assimilation of solar-wind observations into models requires quantitative knowledge of how the reliability of the observations changes with age. In this study we examine 25 years of near-Earth in situ solar-wind observations and 45 years of observation-constrained solar-wind simulations to determine how much the 1-AU solar-wind speed, V , and radial magnetic-field component, B R , vary between consecutive Carrington rotations (CRs). For the in situ spacecraft observations, we find the rate of change of V and B R is similar during solar maximum and minimum, particularly when transient interplanetary coronal mass ejections are removed from the data. This is somewhat counter to expectations. Conversely, the rate of change in V and B R obtained from global heliospheric simulations is strongly correlated with the solar cycle, with the corona and heliosphere being more variable at solar maximum, as expected. Limiting the analysis of the simulations to the solar equatorial region, however, strongly reduces the difference between solar maximum and minimum, bringing the result into close agreement with the in situ observations. This latitudinal sensitivity is explained in terms of the global solar-wind structure over the solar cycle. For the purposes of assimilating in-ecliptic solar-wind observations, we suggest the uncertainty in V should increase by around 3 km s −1 per day since the observation was made and 0.1 nT per day for B R . For observations made at higher latitude, the effect of observation age will be solar-cycle dependent.

The Martian bow shock stands as the first defense against the solar wind and shapes the Martian magnetosphere. Previous studies showed the correlation between the Martian bow shock location and solar wind parameters. Here we present direct evidence of solar wind effects on the Martian bow shock by analyzing Tianwen‐1 and MAVEN data. We examined three cases where Tianwen‐1 data show rapid oscillations of the bow shock, while MAVEN data record changes in solar wind plasma and magnetic field. The results indicate that the bow shock is rapidly compressed and then expanded during the dynamic pressure pulse in the solar wind, and is also oscillated during the IMF rotation. The superposition of variations in multiple solar wind parameters leads to more intensive bow shock oscillation. This study emphasizes the importance of joint observations by Tianwen‐1 and MAVEN for studying the real‐time response of the Martian magnetosphere to the solar wind. Plain Language Summary The Martian bow shock is a standing shock wave that forms ahead of Mars due to the interaction with the solar wind, where the supersonic solar wind flow drops sharply to subsonic. The bow shock plays a crucial role in shaping the Martian magnetosphere and controlling the energy, mass, and momentum exchange between the solar wind and the Martian atmosphere. Previous research has shown that the position of Mars' bow shock is related to the solar wind. This research presents two‐spacecraft observations of how the solar wind affects the Martian bow shock. By analyzing data obtained by two orbiters, Tianwen‐1 and MAVEN, we find that the bow shock quickly contracts when the solar wind dynamic pressure rises or when the interplanetary magnetic field direction turns radial. When there are multiple changes in the solar wind at the same time, the bow shock moves around even more. This study shows how important it is to look at data from Tianwen‐1 and MAVEN at the same time to understand how Mars' magnetosphere reacts to the solar wind. Key Points First observations of the real‐time response of the Martian bow shock to changes in the upstream solar wind Direct evidence of the compression of the Martian bow shock under increased solar wind dynamic pressure Direct evidence of motion of the Martian bow shock caused by the rotation of the interplanetary magnetic field

When a CME arrives at the Earth, it will interact with the magnetosphere, sometimes causing hazardous space weather events. Thus, the study of CMEs which arrived at Earth (hereinafter, Earth-impacting CMEs) has attracted much attention in the space weather and space physics communities. Previous results have suggested that the three-dimensional parameters of CMEs play a crucial role in deciding whether and when they reach Earth. In this work, we use observations from the Solar TErrestrial RElations Observatory (STEREO) to study the three-dimensional parameters of 71 Earth-impacting CMEs from the middle of 2008 to the end of 2012. We find that the majority Earth-impacting CMEs originate from the region of [30S,30N] × [40E,40W] on the solar disk; Earth-impacting CMEs are more likely to have a central propagation angle (CPA) no larger than half-angular width, a negative correlation between velocity and acceleration, and propagation time is inversely related to velocity. Based on our findings, we develop an empirical statistical model to forecast the arrival time of the Earth-impacting CME. Also included is a comparison between our model and the aerodynamic drag model.

We establish a catalog of interplanetary coronal mass ejections (ICMEs) during the period from 1995 to 2015 using the in-situ observations from the Wind and ACE spacecraft. Based on this catalog, we extend the statistical properties of ICMEs to the maximum phase of Solar Cycle 24. We confirm previous results that the yearly occurrence frequencies of ICMEs and shocks, the ratios of ICMEs driving shocks are correlated with the sunspot numbers. For the magnetic cloud (MC), we confirm that the yearly occurrence frequencies of MCs do not show any correlation with sunspot numbers. The highest MC ratio of ICME occurred near the solar minimum. In addition, we analyzed the yearly variation of the ICME parameters. We found that the ICME velocities, the magnetic-field strength, and their related parameters are varied in pace with solar-cycle variation. At the solar maximum, ICMEs move faster and carry a stronger magnetic field. By comparing the parameters between MCs and non-MC ejecta, we confirm the result that the magnetic-field intensities of MC are higher than those in non-MC ejecta. Furthermore, we also discuss the forward shocks driven by ICMEs. We find that one half of the ICMEs have upstream shocks and ICMEs with shocks have faster speed and higher magnetic-field strength than the ICMEs without shocks. The magnetic-field parameters and solar-wind plasma parameters in the shock sheath regions are higher than those in the ejecta regions of ICMEs from a statistical point of view.

Mars lacks an intrinsic global magnetic field but possesses crustal magnetic anomalies and an atmosphere. Mars' ionosphere, resulted from interactions between Mars' atmosphere and solar radiation, directly interacts with solar wind and interplanetary magnetic field (IMF). However, the mechanisms governing ion acceleration and escape from Mars' ionosphere remain incompletely understood. By analyzing simultaneous observations from MAVEN and Tianwen‐1 missions, we present observational evidence of magnetic reconnection events in Mars' dayside upper ionosphere above weak crustal field region during IMF rotation, accompanied by acceleration of ionospheric ions. The explosive escape flux exceeds the average plume and tailward escape flux by an order of magnitude and is comparable to that of reconnection processes above strong crustal field regions. Our results provide evidence that IMF rotation‐triggered magnetic reconnection constitutes a significant pathway for ion escape from Mars, offering new insights into planet's atmospheric evolution and potential mechanisms for early water loss on Mars.

The research on exoskeleton robots has been widely carried out for many years around the world, especially the development of new-style lower limb exoskeletons for rehabilitation and assistance is one of the key research directions. The focus on the control system of lower limb exoskeletons for rehabilitation is discussed. Based on the public literature in recent years, it is summarized from three aspects, i.e., movement mode switching, human gait recognition and human-exoskeleton interaction control. Finally, the technical issues of the current lower limb rehabilitation exoskeleton control strategy are discussed. The future development prospects and research directions of the lower limb rehabilitation exoskeleton are prospected, and some suggestions on how to achieve a more efficient and accurate control are given.

To understand the weaker geomagnetic activity in Solar Cycle 24, we present comparisons of interplanetary coronal mass ejections (ICMEs) fittings and in situ observation parameters in Solar Cycles 23 and 24. According to their in situ features, ICMEs are separated into two categories: isolated ICMEs (I-ICMEs) and multiple ICMEs (M-ICMEs). The number of I-ICMEs in Solar Cycles 23 and 24 does not show a strong difference, while the number of M-ICMEs, which have a high probability of causing intense geomagnetic storms, declines proportionally to the sunspot number in Solar Cycle 24. Despite no obvious variation in their distribution, the geoeffective ICMEs in Solar Cycle 23 have a larger average total magnetic field strength and a larger southern magnetic field than those of Solar Cycle 24. Since the average solar wind velocities of the two solar cycles differ, the geoeffective ICMEs in Solar Cycle 23 have a higher velocity and distinct speed distributions from those in Solar Cycle 24. The total magnetic flux and radius of I-ICMEs in Solar Cycle 23 are larger than those in Solar Cycle 24, while the axial magnetic field intensity is basically the same. We propose that geomagnetic activity in Solar Cycle 24 is lower than that of Solar Cycle 23, due to the smaller M-ICME number, the slower ICME speed, and absence of ICME events with significant southward magnetic field.

The Disturbance Storm Time (Dst) Index stands as a crucial geomagnetic metric, serving to quantify the intensity of geomagnetic disturbances. The accurate prediction of the Dst index plays a pivotal role in mitigating the detrimental effects caused by severe space-weather events. Therefore, Dst prediction has been a long-standing focal point within the realms of space physics and space-weather forecasting. In this study, a Temporal Convolutional Network (TCN) is deployed in tandem with the Integrated Gradient (IG) algorithm to predict the Dst index and scrutinize its associated physical processes. With these two components, our model can give the contribution of each input parameter to the outcome along with the forecast. The TCN component of our model utilizes interplanetary observational data, encompassing the vector magnetic field, solar-wind velocity, proton temperature, proton density, interplanetary electric field, and other relevant parameters for forecasting Dst indices. Despite the disparity in test sets, our model’s forecast accuracy approximates the error levels of the prior models. Remarkably, the prediction error of these machine-learning models has become comparable to the inherent error between the Dst index itself and the actual ring-current strength. To understand the physical process behind the forecasting model, the IG algorithm was applied in our prediction model, in an attempt to analyze the underlying physical process of the machine-learning black box. In the temporal dimension, it is evident that the more recent the time, the more substantial the influence on the final prediction. Regarding the physical parameters, besides the historical Dst index itself, the flow pressure, the z -component of the magnetic field, and the proton density all significantly contribute to the final prediction. Additionally, IG attributions were analyzed for subsets of data, including different Dst-index ranges, different observation times, and different interplanetary structures. Most of the subsets exhibit an IG matrix with deviations from the mean distribution, which indicates a complex nonlinear system and sensitivity of the prediction to input values. These analyses align with physical reasoning and are in good agreement with previous research. The results affirm that the TCN+IG technique not only enhances space-weather forecast accuracy but also advances our comprehension of the underlying physical processes in space weather.