Great Wall Research Articles

Non-destructive testing research on the surface damage faced by the Shanhaiguan Great Wall based on machine learning

The Shanhaiguan Great Wall is a section of the Great Wall of the Ming Dynasty, which is a UNESCO World Heritage Site. Both sides of its basic structure are composed of rammed earth and gray bricks. The surface gray bricks sustain damage from environmental factors, resulting in a decline in their structural quality and even a threat to their safety. Traditional surface damage detection methods rely primarily on manual identification or manual identification following unmanned aerial vehicle (UAV) aerial photography, which is labor-intensive. This paper applies the YOLOv4 machine learning model to the gray surface bricks of the Plain Great Wall of Shanhaiguan as an illustration. By slicing and labeling the photos, creating a training set, and then training the model, the proposed approach automatically detects four types of damage (chalking, plants, ubiquinol, and cracking) on the surface of the Great Wall. This eliminates the need to expend costly human resources for manual identification following aerial photography, thereby accelerating the work. Through research, it is found that 1) compared with manual detection, this method can quickly and efficiently monitor a large number of wall samples in a short period of time and improve the efficiency of brick wall detection in ancient buildings. 2) Compared with previous approaches, the accuracy of the current method is improved. The identifiable types are increased to include chalking and ubiquinol, and the accuracy rate increases by 0.17% (from 85.70% before to 85.87% now). 3) This method can quickly identify the damaged parts of the wall without damaging the appearance of the historical building structure, enabling timely repair measures.

Ho’oleilana: An Individual Baryon Acoustic Oscillation?

Theory of the physics of the early hot universe leads to a prediction of baryon acoustic oscillations (BAOs) that has received confirmation from the pairwise separations of galaxies in samples of hundreds of thousands of objects. Evidence is presented here for the discovery of a remarkably strong individual contribution to the BAO signal at z = 0.068, an entity that is given the name Ho’oleilana. The radius of the 3D structure is Mpc. At its core is the Boötes supercluster. The Sloan Great Wall, Center for Astrophysics Great Wall, and Hercules complex all lie within the BAO shell. The interpretation of Ho’oleilana as a BAO structure with our preferred analysis implies a value of the Hubble constant of

Exploring The Symbiotic Economic Benefits Between Farmers and Herders to Promote Peaceful Coexistence in Taraba State Nigeria

This paper explored the symbiotic economic benefits between farmers and herders in Taraba State to promote peaceful coexistence. Taraba State is one of the states in the North East region of Nigeria that is mainly affected by the farmers-herders crisis. The paper illustrated the causes of the farmers-herders crisis which include the growing population, abandonment of the grazing reserve system, and proliferation of small arms and light weapons among others. Although the Federal and State Governments have responded in several ways, among which the creation of grazing reserves in 1965, the establishment of the National Commission for Nomadic Education (NCNE) in 1989, the use of the Armed Forces to curb internal security caused by farmers-herders crisis, proposed National Grazing Reserve Bill 2016, proposed Cattle Ranching System 2018, legislation prohibiting open grazing and the Great Green Wall Agency of the Federal Government. All these efforts by the Federal Government and various State Governments could not bring the desired peaceful coexistence between farmers and herders. The crisis still lingered in Taraba State and many other states. Therefore, the paper explored the symbiotic economic benefits that could be enjoyed by farmers and herders leading to peaceful coexistence. Some of the symbiotic economic benefits capable of stimulating peaceful coexistence are; after harvesting crops on their farm, they usually allow cattle to graze on the leftovers, during which excrement from the cows provide manure for the farm, use of yam and cassava peels for preparation of animal feeds, use of rice, guinea corn, maize, and millet chaff for animal feeds and use of animal waste as fertilizer. The author concluded that exploring the symbiotic economic benefits explicated in this paper can bring about peaceful coexistence between farmers and herders which will also result in a peaceful Taraba State. It was suggested that government and private individuals should establish ranches within farming communities in such a manner that herders can get animal feeds from farmers while the farmers get manure from the herders’ farms.

An Analysis of the Causes and Effects of the Out-of-Control Merger and Acquisition of Subsidiaries—A Case Study of the Great Wall of Culture Company

The phenomenon of out-of-control of subsidiaries after mergers and acquisitions is becoming more and more prominent. Effective control of subsidiaries is the most important issue that needs to be paid attention to. How to reasonably and effectively control subsidiaries has become the focus of theoretical and practical research. Taking the acquisition of Jade Education by Great Wall of Culture as an example, this paper analyzes the causes of losing control after the acquisition and analyzes the impact of losing control subsidiaries on the enterprise by means of event research and financial index analysis. The study found that the main reasons for the out-of-control of subsidiaries are unreasonable performance commitment, excessive decentralization caused by cross-border mergers and acquisitions, and out-of-control caused by blind mergers and acquisitions. Moreover, the out-of-control subsidiaries are no longer included in the scope of consolidated statements, which has a significant impact on the operating conditions of enterprises. In order to prevent the subsidiaries from losing control, it is suggested to carefully select the target for merger and acquisition, conduct due diligence on the target enterprise before merger and acquisition, reasonably delegate decision-making power and enrich and improve the performance commitment agreement.

Abandon the idea of ‘great green walls’

Abandon the idea of ‘great green walls’

A boundary optimization model of instance segmentation combined with wavelet transform on Buildings

Data driven deep learning methods have become the mainstream method of building extraction from remote sensing images. In this paper, deep learning algorithm is used to classify and extract buildings from remote sensing images of rural areas around the Great Wall in the suburbs of Beijing captured by unmanned aerial vehicles. Aiming at the shortcomings of the current mainstream instance segmentation algorithm Mask R-CNN in feature fusion and poor prediction of instance mask boundaries, this paper proposes a boundary optimization algorithm for building instance segmentation based on discrete wavelet transform. Firstly, the discrete wavelet transform is introduced into the segmentation task branch of Mask R-CNN algorithm to extract the low-frequency and high-frequency information of the real mask, in which the high-frequency information includes the boundary information. Secondly, the pixel by pixel prediction of the mask turns into the learning of the low-frequency and high-frequency information of the real mask. The learning of the high-frequency information helps the segmentation network to learn the boundary features better. Finally, using the reversibility of discrete wavelet transform, the low-frequency and high-frequency information of the learned mask is inversely transformed to reconstruct the final mask. The improved algorithm is evaluated on the dataset COCO, and applied to the automatic extraction of buildings. The DWT Mask R-CNN algorithm model achieved 70.2% segmentation accuracy and 71.4% detection accuracy, which were improved by 1% and 0.7% respectively compared with the Mask R-CNN and Cascade Mask R-CNN models. The experimental results show that the instance segmentation edge optimization algorithm combined with wavelet transform has achieved better results on the segmentation boundary, improved the poor effect of mask edge detection and achieved higher detection accuracy, and can accurately extract village buildings.

Mitogenome analysis reveals predominantly ancient Yellow River origin of population inhabiting Datong agro-pastoral ecotone along Great Wall.

The Datong Basin was an important arena for population movement and admixture between the Yellow River Valley and Eastern Steppe. In historical materials, the region was often the setting for a tug-of-war between Han farmers and non-Han nomads. The genetic makeup and population history of this Datong population has, however, remained uncertain. In this study, we analysed 289 mitogenomes from Datong individuals. Our primary findings were: (1) population summary statistics analysis revealed a high level of genetic diversity and strong signals of population expansion in the Datong population; (2) inter-population comparisons (PCA and Fst heatmap) exhibited a close clustering between the Datong population and Northern Han, especially northern frontier groups, such as the Inner Mongolia Han, Heilongjiang Han, Liaoning Han and Tianjin Han; (3) phylogeographic analysis of complete mitogenomes revealed the presence of different components in the maternal gene pools of Datong population-the northern East Asian component was dominant (66.44%), whereas the southern East Asians were the second largest component with 31.49%. We also observed a much reduced west Eurasian (2.07%) component; (4) direct comparisons with ancient groups showed closer relationship between Datong and Yellow River farmers than Eastern Steppe nomads. Despite, therefore, centuries of Eastern Steppe nomadic control over the Datong area, Yellow River farmers had a much more significant impact on the Datong population.

Aeolian disaster risk evaluation in the African Sahel

The Sahel is facing a serious environmental crisis due to aeolian disaster that has seriously affected the local development and survival of residents. Thus, evaluating the aeolian disaster risk levels and their variation in the Sahel is important. This study established an optimal model by evaluating the applicability of different models in the aeolian disaster risk determination in the Sahel. Using this model, the spatiotemporal changes in the risk subsystem of aeolian disaster (hazard, sensitivity, vulnerability, and restorability) and the aeolian disaster risk in the Sahel from 2000 to 2020 were analyzed. Based on this analysis, the impact of climate change and human activities on the aeolian disaster risk in the Sahel was evaluated. Results revealed that the variable fuzzy recognition (VFR) based on the aeolian disaster risk index (ADRI) model had the highest accuracy, reaching 89.72 %. The middle of the Sahel, located in the desert-grassland transition zone, exhibited a high hazard, sensitivity, and vulnerability, rendering it highly susceptible to aeolian disaster. The proportion of areas with very low and very high aeolian disaster risk levels decreased from 2000 to 2020, while those with low and high levels increased, and the change in moderate risk level areas remained relatively stable. Areas of low, moderate, and high risk are more sensitive to climate change and human activities and are subjected to greater pressure for change. Human activities were the main factor for the change of ADRI in the Sahel, accounting for 69.74 and 58.19 % of the increased and decreased areas of ADRI, respectively. This study evaluated the level of aeolian disaster risk in the Sahel and identified the main driving factors, providing a reference for Sahel countries to better implement the Green Great Wall (GGW) program in Africa, thereby mitigating the adverse effects of aeolian disaster.

Understanding the world heritage sites’ brand diffusion and formation via social media: a mixed-method study

PurposeBuilding on social media and destination brand-related literature, this study aims to explore World Heritage Sites’ (WHSs) brand diffusion and formation process from long-term and short-term perspectives, which includes brand diffusion, user-generated content (UGC), opinion leaders and brand events’ impact.Design/methodology/approachThis study uses a mixed-method including text mining, keyword analysis and social network analysis to explore the brand formation process of four popular WHSs in Beijing, namely, the Palace Museum, Great Wall, Summer Palace and Temple of Heaven and more than 10,000,000 users’ data on Sina Weibo has been implemented to uncover the underlying social media branding mechanism.FindingsThe results show that the number of postings keeps in a stable range in most months, but, in general, there are no common rules for changing trends among the four WHSs; long-term high-frequency keywords related to history and culture account for a higher percentage; different kinds of accounts have varying impacts on information diffusion, in which media accounts lead to a bigger influence. However, more followers do not necessarily mean more interactions and most of the interaction ratio is much lower than 0.01000; brand events facilitate brand dissemination and have an impact on the creation of UGC.Practical implicationsThis study is valuable for destination marketers to deeper understand brand diffusion and formation and provides valuable insights for developing effective destination marketing strategies.Originality/valueUnlike previous studies that only concern a few parts of destination brand formation via social media (e.g. brand diffusion, brand events or opinion leaders’ impact), this study takes a more comprehensive perspective by systematically analyzing the brand formation process of WHSs on social media. By considering both long-term diffusion and short-term representative events, this study provides a more holistic understanding of the branding mechanism.

Great Wall Construction Algorithm: A novel meta-heuristic algorithm for engineer problems

In recent years, the optimization community has witnessed a surge in the popularity of population-based optimization methods. However, many of these methods suffer from various shortcomings, including unclear performance characteristics, incomplete validation, excessive reliance on metaphors, inadequate exploration and exploitation components, and compromised trade-offs between exploration and exploitation in real-world scenarios. As a result, users often find themselves needing to extensively modify and fine-tune these methods to achieve faster convergence, stable balance, and high-quality results. To shift the optimization community’s focus towards performance rather than metaphorical changes, we propose a general population-based optimization technique called the Great Wall Construction Algorithm (GWCA). This study presents GWCA as a simple yet robust method with competitive performance for efficiently solving constrained and unconstrained problems. GWCA draws inspiration from the competition and elimination mechanisms observed among workers during the construction of the ancient Great Wall. It introduces a mathematical model of the labor movement to simulate the algorithm’s dynamics. Unlike other methods that employ multiple models to generate new solutions, GWCA randomly assigns a single predefined motion model to each worker in every iteration. This unique approach showcases GWCA’s dynamic nature, simple structure, high convergence performance, and ability to deliver satisfactory solution quality, thus outperforming existing optimization methods in terms of efficiency. To validate GWCA, we conduct extensive comparisons with popular and advanced algorithms on the IEEE CEC 2017 benchmark suite across different dimensions (D = 10, 30, 50, 100). Additionally, GWCA is applied to solve 16 constrained engineering problems and 6 NP-Hard problems, demonstrating its applicability in handling constrained and complex nonlinear problems. Finally, we compare GWCA’s optimized solutions with those obtained from 33 advanced meta-heuristic algorithms, including the winner of CEC 2017. The results confirm the effectiveness of the proposed optimizer in solving a wide range of single-objective problems, surpassing popular base optimizers, advanced variants of existing methods, and several CEC winners. We present GWCA as an open-source population-based method that can serve as a standard optimization tool across various domains of artificial intelligence and machine learning. It exhibits a range of exploratory and exploitative features, offering high performance and optimization capabilities. The method is highly flexible, scalable, and can be further extended in terms of structure and application to accommodate diverse forms of optimization scenarios. https://github.com/guangian/Great-Wall-Construction-Algorithm-a-novel-meta-heuristic-algorithm-for-global-optimization.

『사기』로 본 고대의 요동

The location of the Liaodong (遼東) in ancient China was different from that of today. The Liaodong at the time was a major indicator of the western boundary of Old Joseon (古朝鮮), the first Korean nation. According to literature including Sagi (史記), Liaodong in ancient was a place name first used to point to the Far East of China. However, over time, it has also apply to name of the administrative district and princely states in China. Example of the former both includes Liadong-gun (遼東郡), an administrative district established after the Yan (燕) defeated Dongho (東胡) and Old Joseon, built their Great Wall, and is Liaodong-gun, an administrative district established during the Qin (秦) and Western Han (西漢) period. Example of the latter was Liaodong-guk (遼東國), an princely states established by dividing the land of the former Yan in the early Han Dynasty.
 The Liaodong before invasion Dongho and Old Joseon by Jingae (秦蓋) (approximately BC 300) seem to have pointed to outside the eastern border of the Yan, that is, the area between the Chisu (治水) River (currently Yeongjeongha 永定河) and the Gosu 沽水) River (currently Jobaekha 潮白河). After the invasion of Jingae, it went beyond the region and pointed to the east part of Yusu (濡水) River (currently Nanha 灤河). The Liaodong-gun which was established during the Jingae period, the Liaodong-gun which was established during the Qin Dynasty, and Liaodong-guk which was established during the Western Han were geographically overlapped on the same region. Therefore, we argue that the Liaodong from the ancient Yan to the Western Han period was a region limited to the east part of the lower stream of Yusu (濡水) River (currently Nanha 灤河).

Beyond climate change: The effects of deforestation on food security in the Lake Chad region

Deforestation of the Lake Chad region (LCR) has led to the loss of vegetation and biodiversity in the area. This situation has not only exacerbated the adverse effects of rising aridity in the region but has resulted in its desertification. Agricultural activities are endangered as a result of this unhealthy practice. Extant studies have largely focused on the nexus between climate change and food insecurity in the LCR without adequate attention on the impact of deforestation. The study examined how deforestation in concert with climate change has affected food security in the LCR. Data were generated from secondary sources and analysed using qualitative descriptive method. The theory of Anthropogenic Global Warming was adopted. The study found, among others, that the increasing deforestation of the LCR’s vegetation is implicated in food insecurity menacing the area. It recommended, inter alia, an effective implementation of the African Union’s Great Green Wall initiative aimed at ensuring strategic reforestation of the region in order to attenuate the adverse effects of climate change and restore the region’s viability for agricultural production.

The long‐run effects of the imperial bureaucracy: Two tales along the Great Wall of Ming China

AbstractThis article examines the long‐term effects of the administrative system using the Great Wall as a geographical discontinuity. Using town‐level nighttime light luminosity per capita as a measure of economic development, we find that today, luminosity per capita is significantly and robustly higher in towns south of the Great Wall than in those north of it. The holding of resource allocation authority by the administrative hierarchy and the uniform enforcement of justice by hierarchy officials were advantageous for city building and judicial cross‐territory enforceability on the south side of the great wall, which had a long‐term impact on the imperial bureaucracy.

Research on the Revitalization of the Defensive Fortress of the Great Wall Based on the Adversarial Interpretive-Structure Model

This article aims to formulate a revitalization strategy for the affiliated fortress of the Ming Great Wall. The Adversarial Interpretive-Structure Model (AISM) extracts the opposite hierarchical rules and obtains a pair of simplified hierarchical topology graphs. The directed line segments in the adversarial hierarchical topology graph represent the interrelationships between the elements, which are presented in a topological hierarchy and can easily compare the advantages and disadvantages of the revitalization factors, which provides a basis for subsequent revitalization strategy formulation. The adversarial hierarchical topology graph provides a new method for conserving and reusing architectural heritage. Key Words: adversarial hierarchical topology graph, fortress, architectural heritage, conservation and reuse

Primary leiomyoma of the great saphenous vein using multimodal imaging

A 28-year-old man had presented with a complaint of a mass in the left lower limb that had been present for 10 years. The mass had increased slowly, with aggravated pain during the most recent week. On physical examination, a soft mass was present in the front of left lower limb with poor activity, and preserved sensation and palpable arterial pulses within the distal extremity. Ultrasound revealed a hypoechoic lesion without a shape change after compression around the distal great saphenous vein. The lesion measured 1.9 × 1.3 × 2.1 cm, with a well-circumscribed boundary that seemed to be a continuation of the venous wall (A). Some dot-like blood flow signals were detected inside the lesion with a pulsatile arterial spectrum. The great saphenous vein was patent with intact intima (B/Cover). Magnetic resonance imaging was further performed, which revealed an equal T1-weighted signal and an equal or a long T2-weighted signal, similar to that for muscle tissue, for the mass. Continuous and intact adventitia was observed, which confirmed that the mass was localized to the vascular wall (C). A tentative preoperative diagnosis was a muscle-derived benign tumor of the great saphenous vein wall. The possibility of malignancy was excluded by the slow progression, clear boundary, and no invasiveness. The patient subsequently underwent resection of the mass without vascular reconstruction, and the excised mass displayed a fish-flesh cut surface. Postoperative pathologic examination revealed the mass was composed of benign spindle cells with a reticular or parallel arrangement and was positive for smooth muscle actin and desmin (D). Ultimately, the definite diagnosis was a primary leiomyoma of the great saphenous vein. The patient recovered uneventfully without complications. The patient provided written informed consent for the report of his case details and imaging studies.

Study on the spatial regularity of rammed pits of the Ming Great Wall using 3D scanning technique and Random Forest algorithm

In Northwestern China, the Ming Great Wall generally involves multiple layers of rammed earth, and rammed pits with regular spatial characteristics are always distributed on the horizontal interfaces between rammed layers. Obviously, the spatial regularity of rammed pits cannot only reflect the level of ramming technique in the Ming dynasty, but also control the geotechnical properties of rammed layer interfaces (RLIs). Hence, in the present study, one typical RLI with visible rammed pits was obtained from the Ming Great Wall in Yongchang County, Northwestern China, and the corresponding point cloud data were collected by 3D scanning technique. Then, this RLI was reconstructed using numerous micro slopes in ArcGIS, and the distribution maps of micro-slope heights, angles, plan curvatures and profile curvatures were produced as well. Based on these distribution maps and Random Forest (RF) algorithm, those micro slopes which can reflect the true rammed pit morphology (called the representative micro slopes) were identified, and ten zones where the representative micro slopes concentrate were selected as effective analysis domains. Furthermore, within effective analysis domains, the contour lines were generated to show the outline features of rammed pits, and the values of micro-slope heights, angles, plan curvatures and profile curvatures were statistically analyzed to reveal the surface features of rammed pits. Moreover, the distribution features of rammed pits were exhibited by their centroid positions, which can be calculated by the corresponding contour line shapes. Ultimately, this study indicates that rammed pits of the Ming Great Wall show more regularity than randomness in terms of geometric shapes and spatial distribution. Concretely, the outlines of most rammed pits approximate the circular or elliptical shapes. All the rammed pit surfaces are rough rather than smooth, and most of them can be mathematically expressed by quadratic polynomial equations. As for the distribution features, rammed pits are overall distributed in the triangular shapes, and distances between the equivalent centroids of adjacent rammed pits range from 8.95 cm to 17.86 cm. These findings prove that standardized ramming technique was applied in the Ming dynasty, resulting in high-quality construction of the Great Wall. Meanwhile, the rammers used to compact earthen materials possess rounded heads. However, the imperfect polishing of rammers and the inevitable operational errors could also lead to slight spatial randomness of rammed pits.

Analysis of Financial Strategy and Operation Strategy of BYD, Changan Automobile, and Great Wall Motor

With the increasing emphasis on environmental protection energy in global development, new energy vehicles have attracted the attention of automobile manufacturers. At present, the market has a great development prospect and there is no obvious oligopoly. Therefore, taking China's domestic automobile market as the target, this paper selects three representative automobile enterprises with different development priorities to conduct financial analysis, industry analysis, and SWOT analysis on the three companies. Based on the data of these three companies, the overall domestic automobile market in China is roughly evaluated, and the future development of China's new energy automobile market is speculated. This study found that the influence of new energy automobile enterprises in the automobile manufacturing industry has gradually increased, but it still cannot affect the position of traditional automobile manufacturing companies. At present, there is no oligopoly in China's domestic new energy market. Even BYD, which already has the first-mover advantage, does not fully grasp the majority of the domestic market, and it is still possible to be surpassed by later companies (such as Changan Automobile and Great Wall Automobile).

Comparative Study of Roman Empire and Qin Dynasty

Rome is a great empire centered on the Mediterranean Sea and spanning Europe, Asia, and Africa. After the republic system collapsed, the political and economic markets of the Roman Empire underwent various changes, while the cultural and foreign policies remained unchanged. The Qin Dynasty, the representative of the eastern empire, was the first unified feudal dynasty in ancient China. This paper presents a comparative study of Rome and the Qin Dynasty from the aspect of politics, economy, culture, and foreign policies. Romans political power was concentrated and spread out, as the power was controlled by the Senate and the Roman emperor. Meanwhile, the power within the Qin dynasty was highly concentrated in the hands of the emperor. Roman Culture is centered around religion, while the culture of the Qin dynasty is quite different. The mainstream thought was legalism, so the influence of religion was very tiny in the Qin Empire. Roman had a diverse economy, but the Qin dynasty implemented land nationalization, controlled commercial activities, and unified market management. Romes foreign policy was complex, and they used multiple tactics to deal with different nations, while the Qin Dynastys foreign policy aimed to resist foreign enemies. For example, the Qin Dynasty built the Great Wall, whose primary function was to resist the Huns.

From the Great Wall to the Great Firewall: A Historical Analysis of Surveillance

This article delves into the historical development of surveillance practices in China, tracing their roots from the construction of the Great Wall to the contemporary cyber surveillance system known as the Great Firewall. The study explores the strategic importance of the Great Wall as an early warning system and its significance in shaping China's modern national security strategies. Additionally, the article examines the evolution of surveillance techniques throughout China's dynastic history, the impact of Western influences, and the emergence of a modern surveillance state under the People's Republic of China. The analysis then shifts its focus to the development, implementation, and objectives of the Great Firewall, highlighting its role in both domestic control and international cyber warfare. Lastly, the article addresses the ethical debates surrounding surveillance and privacy in China, along with the future implications of emerging technologies and trends in the country's national security strategy. Through this historical lens, the article aims to provide a comprehensive understanding of China's long-standing relationship with surveillance and its crucial role in national security, while also shedding light on potential future developments and global implications. Keywords: Chinese national security, Cyber surveillance, Cyber surveillance, Great Wall of China, History of surveillance in China. Jel Codes: F50, H56, H56, P25, P37.

Integrating an In‐Plane Electron‐Conductive Separator to Enable Short‐Circuit Warning in Lithium–Sulfur Batteries

AbstractLithium–sulfur (Li–S) batteries are one of the most competitive candidates for high‐energy‐density batteries. However, the high energy density and high reactivity of the lithium anode and sulfur cathode make the safety issues of Li–S batteries particularly prominent. Herein, an early warning strategy for the short circuits in Li–S batteries is explored by integrating an in‐plane electron‐conductive separator. The internal short circuits caused by lithium dendrites or manufacturing defects can be quickly and accurately predicted before catastrophic thermal runaway, with enough time to take rescue measures. The separator with high thermal conductivity also facilitates the heat dissipation of the cell, thus reducing the risk of thermal runaway under abuse. The fast and reliable early warning strategy based on the in‐plane electron‐conductive separator builds the Great Wall of active defense against inherently unsafe Li–S batteries.