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With the frequent occurrence of black swan events, global energy security situation has become increasingly complex and severe. Assessing the resilience of the international oil trade network (iOTN) is crucial for evaluating its ability to withstand extreme shocks and recover thereafter, ensuring energy security. We overcomes the limitations of discrete historical data by developing a simulation model for extreme event shock-recovery in the iOTNs. We introduce network efficiency indicator to measure oil resource allocation efficiency and evaluate network performance. Then, construct a resilience index to explore the resilience of the iOTNs from dimensions of resistance and recoverability. Our findings indicate that extreme events can lead to sharp declines in performance of the iOTNs, especially when economies with significant trading positions and relations suffer shocks. The upward trend in recoverability and resilience reflects the self-organizing nature of the iOTNs, demonstrating its capacity for optimizing its own structure and functionality. Unlike traditional energy security research based solely on discrete historical data or resistance indicators, our model evaluates resilience from multiple dimensions, offering insights for global energy governance systems while providing diverse perspectives for various economies to mitigate risks and uphold energy security.

PSR J1012+5307 is a millisecond pulsar with an extremely low-mass (ELM) white dwarf (WD) companion in an orbit of 14.5 hours. Magnetic braking (MB) plays an important role in influencing the orbital evolution of binary systems with a low-mass ($\lt 1-2~M_{\odot}$) donor star. At present, there exist several different MB descriptions. In this paper, we investigate the formation of PSR J1012+5307 as a probe to test the plausible MB model. Employing a detailed stellar evolution model by the MESA code, we find that the Convection And Rotation Boosted MB and the 'Intermediate' MB models can reproduce the WD mass, WD radius, WD surface gravity, neutron-star mass, and orbital period observed in PSR J1012+5307. However, our simulated WD has higher effective temperature than the observation. Other three MB mechanisms including the standard MB model are too weak to account for the observed orbital period in a Hubble time. A long cooling timescale caused by H-shell flashes of the WD may alleviate the discrepancy between the simulated effective temperature and the observed value., Comment: 12 pages, 4 figures, 1 table; ApJ in press

The source 2A 1822-371 is an eclipsing low-mass X-ray binary (LMXB) consisting of a neutron star (NS) and a $\sim0.5~M_{\odot}$ donor star in an orbit of 5.57 hr. Based on timing of the eclipse arrival times, this source was found to be experiencing a rapid orbital expansion with an orbital-period derivative as $\dot{P}_{\rm orb}=(1.51\pm0.05)\times10^{-10}~\rm s\, s^{-1}$, implying that the mass-transfer rate should be higher than at least three times the Eddington accretion rate. The standard magnetic braking (MB) model cannot produce such a high mass-transfer rate. The modified MB model derived by Van \& Ivanova (2019) can produce a high mass-transfer rate, resulting in a high $\dot{P}_{\rm orb}$. This work proposes an alternative model to account for the anomalously high mass-transfer rate and $\dot{P}_{\rm orb}$ of 2A 1822-371. During the mass transfer, a tiny fraction of the transferred material is thought to form a circumbinary (CB) disk around the LMXB, which can efficiently extract orbital angular momentum from the system by the interaction between the CB disk and the binary. We use the MESA code to model the formation and evolution of 2A 1822-371 for different CB-disk masses. When the CB-disk mass is $2.3\times10^{-8}~ M_{\odot}$, the simulation can reproduce the observed donor-star mass, orbital period, and orbital-period derivative. Such a CB disk can accelerate the evolution of the binary and produce a high mass transfer rate of $1.9\times10^{-7}~ M_\odot\,\rm yr^{-1}$, driving the binary to evolve toward a wide-orbit system. Therefore, we propose that CB disks may be responsible for the rapid orbital changes observed in some LMXBs., Comment: 8 pages, 8 figures, Astronomy and Astrophysics in press

Energy security and energy trade are the cornerstones of global economic and social development. The structural robustness of the international oil trade network (iOTN) plays an important role in the global economy. We integrate the machine learning optimization algorithm, game theory, and utility theory for learning an oil trade decision-making model which contains the benefit endowment and cost endowment of economies in international oil trades. We have reconstructed the network degree, clustering coefficient, and closeness of the iOTN well to verify the effectiveness of the model. In the end, policy simulations based on game theory and agent-based model are carried out in a more realistic environment. We find that the export-oriented economies are more vulnerable to be affected than import-oriented economies after receiving external shocks. Moreover, the impact of the increase and decrease of trade friction costs on the international oil trade is asymmetrical and there are significant differences between international organizations., Comment: 14 pages, 5 figures

Propelled by the omnipresence of versatile data capture, communication, and computing technologies, physical sensing has revolutionized the avenue for decisively interpreting the real world. However, various limitations hinder physical sensing's effectiveness in critical scenarios such as disaster response and urban anomaly detection. Meanwhile, social sensing is contriving as a pervasive sensing paradigm leveraging observations from human participants equipped with portable devices and ubiquitous Internet connectivity to perceive the environment. Despite its virtues, social sensing also inherently suffers from a few drawbacks (e.g., inconsistent reliability and uncertain data provenance). Motivated by the complementary strengths of the two sensing modes, social-physical sensing (SPS) is protruding as an emerging sensing paradigm that explores the collective intelligence of humans and machines to reconstruct the "state of the world", both physically and socially. While a good number of interesting SPS applications have been studied, several critical unsolved challenges still exist in SPS. In this paper, we provide a comprehensive survey of SPS, emphasizing its definition, key enablers, state-of-the-art applications, potential research challenges, and roadmap for future work. This paper intends to bridge the knowledge gap of existing sensing-focused survey papers by thoroughly examining the various aspects of SPS crucial for building potent SPS systems., Comment: Accepted for publication at ACM Collective Intelligence

As a vital strategic resource, oil has an essential influence on the world economy, diplomacy and military development. Using oil trade data to dynamically monitor and warn about international trade risks is an urgent need. Based on the UN Comtrade data from 1988 to 2017, we construct unweighted and weighted global oil trade networks (OTNs). Complex network theories have some advantages in analyzing global oil trade as a system with numerous economies and complicated relationships. This paper establishes a trading-based network model for global oil trade to study the evolving efficiency, criticality and robustness of economies and the relationships between oil trade partners. The results show that for unweighted OTNs, the efficiency of oil flows gradually increases with growing complexity of the OTNs, and the weighted efficiency indicators are more capable of highlighting the impact of major events on the OTNs. The identified critical economies and trade relationships have more important strategic significance in the real market. The simulated deliberate attacks corresponding to national bankruptcy, trade blockade, and economic sanctions have a more significant impact on the robustness than random attacks. When the economies are promoting high-quality economic development, and continuously enhancing positions in the OTN, more attention needs be paid to the identified critical economies and trade relationships. To conclude, some suggestions for application are given according to the results., Comment: 19 pages, 9 figures

We propose a three-dimensional nonlinear diffusion method to implement the similar autofocusing function of multiple micro-objects and simultaneously remove the defocused images, which can distinguish the locations of certain sized scattering particles that are overlapping along z-axis. It is applied to all of the reconstruction slices that are generated from the captured hologram after each back propagation. For certain small sized particles, the maxima of maximum gradient magnitude of each reconstruction slice appears at the ground truth z position after applying the proposed scheme when the reconstruction range along z-axis is sufficiently long and the reconstruction depth spacing is sufficiently fine. Therefore, the reconstructed image at ground truth z position is remained, while the defocused images are diffused out. The results demonstrated that the proposed scheme can diffuse out the defocused images which are 20 um away from the ground truth z position in spite of that several scattering particles with different diameters are completely overlapping along z-axis with a distance of 800 um when the hologram pixel pitch is 2 um. It also demonstrated that the sparsity distribution of the ground truth z slice cannot be affected by the sparsity distribution of corresponding defocused images when the diameter of the particle is not more than 35um and the reconstruction depth spacing is not less than 20 um., Comment: no

Let $G_1\sq G_2$ denote the graph obtained from $G_1+G_2$ by adding new edges from each vertex of $G_1$ to every vertex of $G_2$. In this paper, the critical groups of the graphs $K_m\sq P_n$$(n\geq4)$ and $P_m\sq P_n$$(m\geq4,n\geq5)$ are determined.