Gezhouba Explosive (China)

Explosive ordnance including landmines, improvised explosive devices and explosive remnants of war are known to contaminate at least fifty-eight countries, threatening the health of affected communities across generations. Despite the scale of this problem, mortality estimates pertaining to these weapons are limited in scope. This study addresses this knowledge gap by conducting a multi-country epidemiological study on explosive weapons casualties in low-resource settings. A retrospective analysis of secondary data was conducted with data sourced from mine action authorities and centres, and international non-government organisations from across 17 countries. Casualty information contained included demographics, mortality, injury data, and incident details. Univariate and multivariate logistic regression models were used to assess which characteristics were associated with mortality and survival. Here we show one of the largest epidemiological analyses, to date, of explosive weapons casualties. The overall case fatality rate was 38.8% and females have an elevated risk of fatal outcomes. Overall, children experience lower odds of death compared to adults; and, improvised explosive devices have the highest lethality of the weapons examined. This research highlights the lethality of explosive weapons among local casualties, with a case fatality rate significantly higher than that observed in high-resource civilian or military trauma systems, illustrating the deadliness and indiscriminate nature of these devices. The findings of this analysis can inform injury prevention and trauma care initiatives targeting preventable death and disability for casualties of explosive ordnance.

Deep fractured-porous carbonate reservoirs used for underground gas storage (UGS) experience simultaneous changes in temperature and effective stress during cyclic injection and withdrawal, so predicting permeability evolution is essential for evaluating long-term injectivity and deliverability. Using the Xiangguosi UGS as the engineering background, we measured steady-state gas permeability of three fractured-porous carbonate cores under representative conditions (20–80 °C; 15–35 MPa). Permeability decreases nonlinearly under coupled loading: changing temperature or effective stress alone typically reduces permeability by 30–70%, while the maximum reduction under concurrent increases in both variables exceeds 80% relative to the reference condition. An exponential model was fitted to quantify the decay parameter of permeability with effective stress (0.038–0.046 MPa−1) and with temperature (0.016–0.020 °C−1). In addition, the temperature-related exponential decay parameter decreases with increasing effective stress, because compliant fractures and larger pores are progressively pre-closed, weakening the permeability response to temperature. Finally, we propose a parsimonious separable exponential model that reproduces the measurements with a mean relative error below 12%, providing a practical constitutive relation for multiphysics simulations of UGS in fractured-porous carbonates.

Fractured rocks containing infill materials are frequently encountered in engineering applications, and an understanding of dynamic characteristics is crucial for assessing stability and preventing disasters in rock engineering projects. The novel feature of this paper is that a dynamic constitutive model of fractured rocks with fillings is proposed to reveal the mechanical response mechanism of such rocks under dynamic load impact. This model has been formulated to characterize the dynamic attributes of fractured brittle rocks, utilizing damage elements that adhere to the Weibull distribution and high‐frequency Maxwell elements. The precision of the model has been confirmed through impact testing data obtained from granite samples. In the case of fractured brittle rocks with infill, structural plane factors have been incorporated, leading to the proposal of a macro–micro coupled damage dynamic constitutive model. This model considers both the microscale damage within the rock and the macroscale damage associated with the structural planes. The model parameters have been ascertained through nonlinear fitting techniques, and the validity of the model has been established by comparing its predictions to impact testing data obtained from grouted reinforcement bodies. The ultimate findings indicate that the proposed macro–micro coupled damage dynamic constitutive model is capable of precisely depicting the stress–strain relationship of fractured brittle rocks with infill when subjected to dynamic loading and impact. This model serves as a valuable reference for investigating the dynamic mechanisms of such rocks.

Existing tools to evaluate surgical care and trauma systems in low-resource settings contain a large number of variables that may limit feasibility of their use in low-resource conflict settings (LRCS). Further, such tools do not emphasize damage control capabilities, which are particularly relevant for explosive ordnance casualties. To address these needs, we developed a revised version of the existing International Assessment of Capacity for Trauma (INTACT) tool, INTACT-Blast (INTACT-B). We then piloted this tool at regional health facilities in an LRCS in the Sahel. INTACT-B was developed by synthesizing expert opinion with a narrative review of existing LMIC trauma and surgical capacity assessment tools as well as U.S. Department of Defense Joint Trauma System Clinical Practice Guidelines. This instrument was then piloted across regional and district hospitals in Burkina Faso with functional surgical services. Thirty-six regional and district health facilities in Burkina Faso were included in the INTACT-B pilot, with required less than 15min for data entry. Both material (e.g., equipment and infrastructure) and training needs were identified. Only 30.6% of facilities reported the ability to perform damage control laparotomy, with differences between regional and district facilities (70.0% vs. 15.4%, respectively). Although 75.0% had blood banks, only 44.4% had access to tranexamic acid and 33.3% to tourniquets and hemostatic dressings. Imaging equipment was limited (38.5% of district facilities had a functioning X-ray machine). Fewer than half of facilities were capable of performing essential war surgery interventions, such as chest tube placement and amputation (both 47.2%) or fasciotomy (33.3%), with the most significant gaps at district facilities. No facilities either at the regional or district level reporting vascular repair capabilities including intravascular shunt. The INTACT-B tool provides a feasible instrument for evaluating trauma care capacity and capability in LRCS. Significant needs both with respect to material resources, infrastructure, and training were identified in the study setting. Information generated through use of the INTACT-B tool may help guide efforts to strengthen regional and district health facilities closer to point-of-injury, which holds potential to reduce preventable death among local casualties in LRCS.

The inversion of shallow underground vibration fields primarily relies on signals collected by numerous sensors deployed on the surface. However, the accuracy of inversion is affected by the spatial distribution of these sensors. Therefore, under limited measurement points, signal reconstruction at unknown locations remains a critical challenge. To address this problem, we developed an SC-Net-based self-supervised interpolation method for missing wavefield data in shallow subsurface applications. This study utilizes incomplete seismic data acquired in real-world scenarios to train a neural network for seismic data interpolation, thereby expanding the sampled signals required for inversion. Since available seismic data samples are often scarce in practice, we adopt a hybrid training strategy combining simulated and real data. Specifically, a large number of numerically simulated samples are jointly trained with a limited set of real-world measurements. Furthermore, to enhance the robustness of network outputs, we integrate the Mean Teacher model framework and propose a self-supervised learning approach for missing data. Additionally, to enable the network to effectively capture long-range dependencies in both frequency and spatial domains of seismic data, we introduce a dual-branch feature fusion network that jointly models channel-wise and spatial relationships. Finally, in our actual field explosion experiments conducted at the test site, we demonstrated improved accuracy of our method through comparative analysis with several typical interpolation neural networks. Three ablation studies are also designed to demonstrate the effectiveness of the proposed approach.

The authors have nothing to report.

Cooperative multi-agent reinforcement learning (MARL) has emerged as a powerful paradigm for addressing complex real-world challenges, including autonomous robot control, strategic decision-making, and decentralized coordination in unmanned swarm systems. However, it still faces challenges in learning proper coordination among multiple agents. The lack of effective knowledge sharing and experience interaction mechanisms among agents has led to substantial performance decline, especially in terms of low sampling efficiency and slow convergence rates, ultimately constraining the practical applicability of MARL. To address these challenges, this paper proposes a novel framework termed Reward redistribution and Experience reutilization based Coordination Optimization (RECO). This innovative approach employs a hierarchical experience pool mechanism that enhances exploration through strategic reward redistribution and experience reutilization. The RECO framework incorporates a sophisticated evaluation mechanism that assesses the quality of historical sampling data from individual agents and optimizes reward distribution by maximizing mutual information across hierarchical experience trajectories. Extensive comparative analyses of computational efficiency and performance metrics across diverse environments reveal that the proposed method not only enhances training efficiency in multi-agent gaming scenarios but also significantly strengthens algorithmic robustness and stability in dynamic environments.

Low Earth orbit (LEO) satellite communication offers significant advantages over terrestrial communications, characterized by its cost-effectiveness and extensive coverage. Nevertheless, the relative motion between LEO satellites and user terminals results in a larger frequency offset compared to terrestrial communications. Meanwhile, the maximum round-trip delay within the satellite communication beam is considerably greater. To address these challenges, this paper first proposes a novel preamble based on the Zadoff-Chu sequence and creatively utilizes Affine Frequency Division Multiplexing (AFDM) waveforms for the transmission of the preamble for the first time. Subsequently, to enhance the accuracy of timing advance (TA) detection, a detection algorithm is proposed to distinguish the first-path delay. Finally, the simulation results confirm that the AFDM based preamble outperforms the preambles based on Orthogonal Frequency Division Multiplexing (OFDM) in mitigating the impact of frequency offset in LEO satellite communication without the requirement of pre-compensation.