•A newly improved under-load cascading failure model are established.•The method to assess the network robustness and resilience are proposed.•The threshold of key parameter to protect global energy ...and food security is obtained.•There is no positive correlation between network robustness and resilience.•We should pay more attention to the little and countries to handle the risk.
The Russian- Ukraine War has and further influence the global energy and food security. However, the detailed influence degree, key weak points and influence process is still unclear in the current. Therefore, this study established a newly improved under-load cascading failure model with consideration of overload limitation, and used it to evaluate influence of Russian- Ukraine War on the global energy and food security. This study also proposed a method to assess the network structure characteristic including robustness and resilience through model simulation under different scenarios. The main results include: The upper limitation of node load has the dominant function on the global energy and food security, while the influence of lower limitation parameter of node load has limited function. All of the networks have relative consistent recover and anti-damage ability against Russian and Ukraine War and the global panic except barley network. A key phenomenon we should concern is that the largest trade flow amounts are not occurred in the failure nodes. The failure nodes are always the countries with low economic scale and political status. The results tell us that we should further strengthen the importance of enhance production ability and energy types to resist the risk of Russian and Ukraine War. The global international organizations are also required to strengthen the function of balance the global security demand of energy and food between big countries and small countries. We should pay more attention to the little countries in the Africa and Asia to handle the risk.
Sub‐freezing temperature presents a significant challenge to the survival of current Li‐ion batteries (LIBs) as it leads to low capacity retention and poor cell rechargeability. The electrolyte in ...commercial LIBs relies too heavily on ethylene carbonate (EC) to produce a stable solid electrolyte interphase (SEI) on graphite (Gr) anodes, but its high melting point (36.4 °C) severely restricts ion transport below 0 °C, causing energy loss and Li plating. Here, a class of EC‐free electrolytes that exhibits remarkable low‐temperature performance without compromising cell lifespan is reported. It is found that at sub‐zero temperatures, EC forms highly resistive SEI that seriously impedes electrode kinetics, whereas EC‐free electrolytes create a highly stable, low‐impedance SEI through anion decomposition, which boosts capacity retention and eliminates Li plating during charging. Pouch‐type LiCoO2 (LCO)|Gr cells with EC‐free electrolytes sustain 900 cycles at 25 °C with 1 C charge/discharge, and LiNi0.85Co0.10Al0.05O2 (NCA)|Gr cells last 300 cycles at −15 °C with 0.3 C charge, both among the best‐performing in the literature under comparable conditions. Even at −50 °C, the NCA|Gr cell with EC‐free electrolytes still delivers 76% of its room‐temperature capacity, outperforming EC‐based electrolytes.
A new class of ethylene carbonate (EC)‐free electrolytes, based on methyl acetate and fluorinated ethers, is proposed for Li‐ion batteries operating at sub‐freezing temperatures. The EC‐free electrolyte demonstrates all‐round performance advantages over the traditional EC‐based electrolyte and presents a viable solution to improve the capacity retention and rechargeability of metal‐ion batteries in cold climates.
Drawing on the theoretical framework of functional translation, this study presents a multifaceted exploration of university English translation through functional, constructive, evolutionary, and ...cultural lenses. Positioned within a cross-cultural context, the paper categorizes university English translation into three primary attributes: the frontier nature of translation, linguistic and cultural divergences, and the professionalism required in translation activities. Utilizing Super Decision software, these attributes serve as input variables to construct a Network Hierarchical Analysis model. This model is further integrated with the Interpretive Structural Modeling (ISM) recursive structure to assess the influence of various factors on translation quality. The study employs a multidimensional approach to dissect the impact of cultural and professional variances on the quality of university English translation. The results reveal that 54 out of 65 cultural dimensions (83.08%) significantly affect translation quality. In the realm of professional characteristics, four out of six dimensions (66.67%) are found to have a considerable influence on translation quality. Based on these comprehensive findings, the paper proposes four strategic optimizations aimed at enhancing the quality of university English translation, thereby offering valuable insights and practical recommendations for the field.
Interpreting the geometric structure of artworks enhances our intuitive grasp of their deeper meanings. This study employs a Capsule network model, incorporating a dynamic routing algorithm to ...correlate high and low-level geometric structural features of artworks. Additionally, an attention mechanism is introduced, forming a spatial attention capsule to capture the spatial context of the artwork’s geometric structure. To obtain images, a fixed-focus camera is utilized, followed by median filtering for image preprocessing and threshold segmentation using the maximum inter-class variance method to optimize recognition accuracy. The efficacy of the geometric structure recognition model, grounded in the Capsule network, is confirmed using a dataset of collected artwork images. The model achieves stability after 380 epochs, exhibiting an impressive accuracy of approximately 99.7% and a minimal loss of 0.025. Removing the attention mechanism results in a 4.06 percentage point decrease in model accuracy, whereas incorporating a dynamic routing algorithm boosts efficiency by 7.36%. Thus, the Capsule model proves highly effective in precisely recognizing and interpreting the geometric structures of artworks.
Coronavirus disease 2019 (COVID-19) is a respiratory infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Droplets and contacts serve as the main route of ...transmission of SARS-CoV-2. The characteristic of the disease is rather heterogeneous, ranging from no symptoms to critical illness. The factors associated with the outcome of COVID-19 have not been completely characterized to date. Inspired by previous studies on the relevance of infectious diseases, viral and host factors related to clinical outcomes have been identified. The severity of COVID-19 is mainly related to host factors, especially cellular immune responses in patients. Patients with mild COVID-19 and improved patients with severe COVID-19 exhibit a normal immune response to effectively eliminate the virus. The immune response in patients with fatal severe COVID-19 includes three stages: normal or hypofunction, hyperactivation, and anergy. Eventually, the patients were unable to resist viral infection and died. Based on our understanding of the kinetics of immune responses during COVID-19, we suggest that type I interferon (IFN) could be administered to patients with severe COVID-19 in the hypofunctional stage, intravenous immunoglobulin (IVIG) and glucocorticoid therapy could be administered in the immune hyperactivation stage. In addition, low molecular weight heparin (LMWH) anticoagulation therapy and anti-infective therapy with antibiotics are recommended in the hyperactivation stage.
Heavy metal contamination in soils has worsened with rapid economic development. The combined method with principal component analysis/absolute principal component scores) and random forest models ...successfully reveals the total sources contribution structure and the specific influence process of industrial activities on heavy metals concentration in soils of the three urban agglomerations. Through statistical analysis, Cd in the Jing-Jin-Ji Metropolitan Region, Pb, Cu, Hg, Cd and As in the Yangtze River Delta, and Hg, As, Cd, Cu and Pb in the Pearl River Delta had relatively high mean concentrations and coefficient of variation (CV), which indicates that the contamination may be caused by human activities. Through PCA/APCS analysis, industrial activities contributed more than 60% of the Cd, Hg and Pb concentrations in soils in JJJ, YRD and PRD. A random forest simulation revealed that heavy metal pollution in soils is the combined result of natural processes and human activities in the three urban agglomerations. The heavy metals concentration in JJJ is mainly caused by industrial activities through land-based emission. The industrial activities presented more significant impact on heavy metals concentration in the soil of YRD compared with other two urban agglomerations. The elevation variation controlled the pattern of heavy metal concentration through influencing the spatial clustering feature of industrial activities. The distance from the sample location to the nearest industrial enterprise is the most important factor in determining the heavy metal concentration. The number of enterprises within a 5 km radius of the sample locations makes a greater contribution to the amount of Hg pollution than other heavy metals. The results of this study could provide support for better management of soil pollution prevention practices such as specific industrial governance and layout optimization.
Linking water to research on coupled human and natural systems (CHANS) has attracted wide interest as a means of supporting human-natural sustainability. However, most current research does not focus ...on water environmental properties; instead, it is at the stage of holistic status assessment and measures adjustment from the point of view of the whole study region without revealing the dynamic interaction between human activities and natural processes. This paper establishes an integrated model that combines a System Dynamics model, a Cell Automaton model and a Multiagent Systems model and exploits the potential of the combined model to reveal regions' human-water interaction status during the process of urban evolution, identify the main pollution sources and spatial units, and provide the explicit space-time measurements needed to enhance local human-natural sustainability. The successful application of the integrated model in the case study of Changzhou City, China reveals the following. (1) As the city's development has progressed, the water environment status in some spatial units is still unsatisfactory and may even become more serious, especially in the urban areas of the Urban District and Liyang County. The concentration of Chemical Oxygen Demand (COD) in monitoring section 157 of the Urban District has increased from 36.90 mg/l to 40.84 mg/l. The main source of this increase is the increase in secondary industry. (2) With the application of the spatially explicit measures of the sewage treatment ratio improvement and new sewage plant construction, the water quality in the urban area has significantly improved and now satisfies the water quality standards. The measure of livestock manure utilization enhancement is adopted to improve the spatial units in which livestock is the main pollution source and achieve the goal of water quality improvement. The model can be used to support the sustainable status assessment of human-water interaction and to identify effective measures that can be used to realize human-water sustainability along with social-economic development.
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•An integrated model has been established for human-water simulation.•It could reveal human-water dynamic change along with urban evolution.•It realizes pollution sources structure analysis for a specific monitoring section.•It could support for spatial explicit adjustment for human-water sustainability.
A spatially explicit approach is proposed to reveal human-water dynamic change and support human-water sustainable management.
There is increasing evidence that the existence of systemic inflammation response is correlated with poor prognosis in several solid tumors. The aim of this retrospective study was to investigate the ...association between systemic immune-inflammation index (SII) and therapy response and overall survival in patients with stage III non-small cell lung cancer (NSCLC). The prognostic values of neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and prognostic nutritional index (PNI) were also evaluated.
In total, 332 patients with new diagnosis of stage III NSCLC were included in this retrospective analysis. SII was defined as platelet counts × neutrophil counts/lymphocyte counts. Receiver operating characteristic (ROC) curve was used to evaluate the optimal cut-off value for SII, NLR, PLR and PNI. Univariate and multivariate survival analysis were performed to identify the factors correlated with overall survival.
Applying cut-offs of ≥ 660 (SII), ≥ 3.57 (NLR), ≥ 147 (PLR), ≤ 52.95 (PNI), SII ≥ 660 was significantly correlated with worse ECOG PS (< 0.001), higher T stage (< 0.001), advanced clinical stage (p = 0.019), and lower response rate (p = 0.018). In univariate analysis, SII ≥ 660, NLR ≥ 3.57, PLR ≥ 147, and PNI ≤ 52.95 were significantly associated with worse overall survival (p
< 0.001). Patients with SII ≥ 660 had a median overall survival of 10 months, and patients with SII < 660 showed a median overall survival of 30 months. In multivariate analysis only ECOG PS (HR, 1.744; 95% CI 1.158-2.626; p = 0.008), T stage (HR, 1.332; 95% CI 1.032-1.718; p = 0.028), N stage (HR, 1.848; 95% CI 1.113-3.068; p = 0.018), SII (HR, 2.105; 95% CI 1.481-2.741; p < 0.001) and NLR ≥ 3.57 (HR, 1.934; 95% CI 1.448-2.585; p < 0.001) were independently correlated with overall survival.
This study demonstrates that the SII is an independent prognostic indicator of poor outcomes for patients with stage III NSCLC and is superior to other inflammation-based factors in terms of prognostic ability.
Oral cancer is one of the most common malignant tumors of the head and neck, and it continues to represent a serious public health problem. Recent reports show the involvement of H19 long noncoding ...RNA (LncRNA) in oncogenesis but its mechanism associated with oral cancer remains unclear. Here, we identify an H19 transcript variant that lacks exon 4 in oral cancer specimens and carcinoma‐derived cells. Depletion of H19 by short hairpin RNAs (shRNAs) targeting exon 1 but not exon 4 significantly inhibited oral cancer iCell‐h120 cells growth and invasion in vitro and tumorigenesis of these cells in vivo. Through binding the ZEB1 mRNA, the variant H19 transcript without exon 4 promotes the expression of ZEB1 protein during epithelial–mesenchymal transition (EMT). Thus, these data reveal the role of a splicing events of H19LncRNA in oral tumorigenesis, and indicate that the splicing event of H19 can be served as potential therapeutic targets for oral cancer.
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