Explore the vast range of titles available.

Erastin was initially discovered as a small molecule compound that selectively kills tumor cells expressing ST and RASV12 and was later widely investigated as an inducer of ferroptosis. Ferroptosis is a recently discovered form of cell death caused by peroxidation induced by the accumulation of intracellular lipid reactive oxygen species (L-ROS) in an iron-dependent manner. Erastin can mediate ferroptosis through a variety of molecules including the cystine-glutamate transport receptor (system XC -), the voltage-dependent anion channel (VDAC), and p53. Erastin is able to enhance the sensitivity of chemotherapy and radiotherapy, suggesting a promising future in cancer therapy. We hope that this review will help to better understand the role of erastin in ferroptosis and lay the foundation for further research and the development of erastin-based cancer therapies in the future.Erastin was initially discovered as a small molecule compound that selectively kills tumor cells expressing ST and RASV12 and was later widely investigated as an inducer of ferroptosis. Ferroptosis is a recently discovered form of cell death caused by peroxidation induced by the accumulation of intracellular lipid reactive oxygen species (L-ROS) in an iron-dependent manner. Erastin can mediate ferroptosis through a variety of molecules including the cystine-glutamate transport receptor (system XC -), the voltage-dependent anion channel (VDAC), and p53. Erastin is able to enhance the sensitivity of chemotherapy and radiotherapy, suggesting a promising future in cancer therapy. We hope that this review will help to better understand the role of erastin in ferroptosis and lay the foundation for further research and the development of erastin-based cancer therapies in the future.

Electrochemical reduction of CO 2 to multi-carbon fuels and chemical feedstocks is an appealing approach to mitigate excessive CO 2 emissions. However, the reported catalysts always show either a low Faradaic efficiency of the C 2+ product or poor long-term stability. Herein, we report a facile and scalable anodic corrosion method to synthesize oxygen-rich ultrathin CuO nanoplate arrays, which form Cu/Cu 2 O heterogeneous interfaces through self-evolution during electrocatalysis. The catalyst exhibits a high C 2 H 4 Faradaic efficiency of 84.5%, stable electrolysis for ~55 h in a flow cell using a neutral KCl electrolyte, and a full-cell ethylene energy efficiency of 27.6% at 200 mA cm −2 in a membrane electrode assembly electrolyzer. Mechanism analyses reveal that the stable nanostructures, stable Cu/Cu 2 O interfaces, and enhanced adsorption of the *OCCOH intermediate preserve selective and prolonged C 2 H 4 production. The robust and scalable produced catalyst coupled with mild electrolytic conditions facilitates the practical application of electrochemical CO 2 reduction. Oxide-derived copper has been extensively studied as catalysts for CO 2 electroreduction but its catalytic stability and selectivity still need to be improved. Here, the authors report ultrathin CuO nanoplate arrays for CO 2 reduction with high ethylene selectivity and enhanced long-term stability.

With the widespread application of machine learning techniques in time series analysis, the interpretability of models trained on time series data has attracted increasing attention. Most existing explanation methods are based on time-domain features, making it difficult to reveal how complex models focus on time–frequency information. To address this, this paper proposes a time–frequency domain-based time series interpretation method aimed at enhancing the interpretability of models at the time–frequency domain. This method extends the traditional LIME algorithm by combining the ideas of short-time Fourier transform (STFT), inverse STFT, and local interpretable model-agnostic explanations (LIME), and introduces a self-designed TFHS (time–frequency homogeneous segmentation) algorithm. The TFHS algorithm achieves precise homogeneous segmentation of the time–frequency matrix through peak detection and clustering analysis, incorporating the distribution characteristics of signals in both frequency and time dimensions. The experiment verified the effectiveness of the TFHS algorithm on Synthetic Dataset 1 and the effectiveness of the TF-LIME algorithm on Synthetic Dataset 2, and then further evaluated the interpretability performance on the MIT-BIH dataset. The results demonstrate that the proposed method significantly improves the interpretability of time-series models in the time–frequency domain, exhibiting strong generalization capabilities and promising application prospects.

Sate of charge (SOC) accurate estimation is one of the most important functions in a battery management system for battery packs used in electrical vehicles. This paper focuses on battery SOC estimation and its issues and challenges by exploring different existing estimation methodologies. The key technologies of lithium-ion battery state estimation methodologies of the electrical vehicles categorized under five groups, such as the conventional method, adaptive filter algorithm, learning algorithm, nonlinear observer, and the hybrid method, are explored in an in-depth analysis. Lithium-ion battery characteristic, battery model, estimation algorithm, and cell unbalancing are the most important factors that affect the accuracy and robustness of SOC estimation. Finally, this paper concludes with the challenges of SOC estimation and suggests other directions for possible research efforts.

Open circuit voltage (OCV) is an important characteristic parameter of lithium-ion batteries, which is used to analyze the changes of electronic energy in electrode materials, and to estimate battery state of charge (SOC) and manage the battery pack. Therefore, accurate OCV modeling is a great significance for lithium-ion battery management. In this paper, the characteristics of high-capacity lithium-ion batteries at different temperatures were considered, and the OCV-SOC characteristic curves at different temperatures were studied by modeling, exponential, polynomial, sum of sin functions, and Gaussian model fitting method with pulse test data. The parameters of fitting OCV-SOC curves by exponential model (n = 2), polynomial model (n = 3~7), sum of sin functions model (n = 3), and Gaussian model (n = 4) at temperatures of 45 °C, 25 °C, 0 °C, and −20°C are obtained, and the errors are analyzed. The experimental results show that the operating temperature of the battery influences the OCV-SOC characteristic significantly. Therefore, these factors need to be considered in order to increase the accuracy of the model and improve the accuracy of battery state estimation.

The Linhe Depression is the largest tectonic unit in the Hetao Basin. The recently discovered commercial oil flow in the structural trap of wells JH2X and S5 has proved that the Meso-Cenozoic strata in the Linhe Depression have great exploration potential. Research on the kinematic model for the Mesozoic–Cenozoic Linhe Depression is important for analysing the geological conditions of hydrocarbon accumulation. In this study, field observations, seismic interpretation and scaled analogue modelling are performed. The results prove that the Linhe Depression experienced different stages of tectonic evolution, such as compressional depression (K1l), conversion from contraction to uniform subsidence (K1g), extensional rifting (E2–N2) and strike-slip deformation (Q), during the Mesozoic–Cenozoic eras. The kinematic model of negative inverted basins was first established with the early differential compression superimposed by the late extension. The seismic interpretation and analogue modelling results show that Jilantai Sag in the southern part of the Linhe Depression was subjected to compression from the Bayanwulashan fold–thrust belt on the NW side and the Helanshan fold–thrust belt on the SE side during Early Cretaceous time. Meanwhile, the Hanghou Sag in the northern part of the Linhe Depression was only compressed by the Langshan fold–thrust belt from the NW direction. The rifted structure generated by the extension from the SE direction during the Cenozoic Era resulted in the negative inversion of the pre-existing thrusts in different patterns. The intensity of negative inversion is controlled by several key factors, such as dip angle and the patterns of thrust faults, along with different basement textures. The morphological changes in the forebulge zone developed during Early Cretaceous time are responsible for the development of the segmented Central fault zones in the Hanghou Sag.

Let ( X, ϕ ) be a nonautonomous dynamical system. In this paper, we introduce the notions of packing topological entropy and measure-theoretical upper entropy for nonautonomous dynamical systems. Moreover, we establish the variational principle between the packing topological entropy and the measure-theoretical upper entropy.

The Eastern Depression in the Bayanhaote Basin in western Inner Mongolia has experienced multi-stage Meso-Cenozoic tectonic events and possesses considerable exploration potential. However, structural deformation patterns, sequences and the genesis of oil-bearing structures in the basin are still poorly understood. In this study, based on high-quality 2D seismic data and drilling and well-logging data, we elucidate the activities and structural styles of faults, the tectonic evolution and the distribution characteristics of styles, as well as assessing potential petroleum traps in the Eastern Depression. Five types of faults that were active at different stages of the Meso-Cenozoic faults have been recognized: long-lived normal faults active since the late Middle Jurassic; reverse faults and strike-slip faults active in the late Late Jurassic; normal faults active in the Early Cretaceous; normal faults active in the Oligocene; and negative inverted faults active in the Early Cretaceous and Oligocene. These faults constituted 12 geometric styles in NE-trending belts at various stratigraphic levels, and were formed by compression, strike-slip, extension and inversion. The temporal development of structural styles promoted the formation and reconstruction and finalization of structural traps, while regional unconformities and open reverse and strike-slip faults provided migration pathways for petroleum to fill the traps. In general, potential traps that formed by compressional movement and strike-slip movement in the late Late Jurassic are primarily faulted anticlines. Those traps developed in Carboniferous rocks and are located in the southwestern region of the Eastern Depression, being controlled by NNE-NE-striking reverse and transpressive faults.

Due to increased concerns regarding air pollutants emitted from shipping, feasible technology for the surveillance of these pollutants is in high demand. Here, we present shore-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of SO2 and NO2 emitted from ships under different traffic conditions in China's ship emission control areas (ECAs) in Shanghai and Shenzhen, China. Three typical measurement sites were selected in these two regions to represent the following emission scenarios: ships docked at berth, ships navigating in an inland waterway and inbound/outbound ships in a deep-water port. Using 2-D scanning, the observations show that SO2 and NO2 hot spots can be quickly and easily located from multiple berths. Although MAX-DOAS measurements can not distinguish plumes from specific ships in the busy shipping lanes of the inland waterway area, they certify that variations in the SO2 and NO2 levels are mainly impacted by the ship traffic density and the atmospheric dispersion conditions. In the open water area, which has a lower vessel density, MAX-DOAS measurements can capture the pulse signal of ship-emitted SO2 and NO2 very well; they can also characterize the peak's altitude and the insistent duration of the individual ship plumes. Combined with the ship activity data, information on the rated power of the engine and the fuel sulfur content, it was found that the SO2∕NO2 ratio in a single plume is usually low (< 1.5) for inbound vessels due to the usage of the auxiliary engine, which has less power and uses “clean” fuel with a low sulfur content. Thus, an unexpectedly high SO2∕NO2 ratio implies the use of fuel with a sulfur content exceeding the regulation limits. Therefore, the observed SO2∕NO2 ratio in the plume of a single ship can be used as an index to indicate compliance (or noncompliance) with respect to the fuel sulfur content, and the suspicious ship can then be flagged for further enforcement. Combining the ship emissions estimated by actual operation parameters and the logical sulfur content, shore-based MAX-DOAS measurements will provide a fast and more accurate way to surveil ship emissions.

Traditional tumour‐dynamic therapy still inevitably faces the critical challenge of limited reactive oxygen species (ROS)‐generating efficiency due to tumour hypoxia, extreme pH condition for Fenton reaction, and unsustainable mono‐catalytic reaction. To fight against these issues, we skilfully develop a tumour‐microenvironment‐driven yolk‐shell nanoreactor to realize the high‐efficiency persistent dynamic therapy via cascade‐responsive dual cycling amplification of •SO4−/•OH radicals. The nanoreactor with an ultrahigh payload of free radical initiator is designed by encapsulating the Na2S2O8 nanocrystals into hollow tetra‐sulphide‐introduced mesoporous silica (HTSMS) and afterward enclosed by epigallocatechin gallate (EG)‐Fe(II) cross‐linking. Within the tumour microenvironment, the intracellular glutathione (GSH) can trigger the tetra‐sulphide cleavage of nanoreactors to explosively release Na+/S2O82−/Fe2+ and EG. Then a sequence of cascade reactions will be activated to efficiently generate •SO4− (Fe2+‐catalyzed S2O82− oxidation), proton (•SO4−‐catalyzed H2O decomposition), and •OH (proton‐intensified Fenton oxidation). Synchronously, the oxidation‐generated Fe3+ will be in turn recovered into Fe2+ by excessive EG to circularly amplify •SO4−/•OH radicals. The nanoreactors can also disrupt the intracellular osmolarity homeostasis by Na+ overload and weaken the ROS‐scavenging systems by GSH exhaustion to further amplify oxidative stress. Our yolk–shell nanoreactors can efficiently eradicate tumours via multiple oxidative stress amplification, which will provide a perspective to explore dynamic therapy. Traditional tumour‐dynamic therapy still inevitably faces the critical challenge of limited reative oxygen species (ROS)‐generating efficiency due to tumour hypoxia, strict Fenton reaction conditions, and un‐sustainable mono‐catalytic reaction. To fight against these issues, a tumour–microenvironment‐responsive yolk–shell nanoreactor is developed to realize the high‐efficiency, selective, and sustainable dynamic therapy via cascade‐responsive dual cycling amplification of •SO4−/•OH radicals.