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Online social networks (OSNs) suffer from forged messages. Current studies have typically been focused on the detection of forged messages and do not provide the analysis of the behaviors of message publishers and network strategies to suppress forged messages. This paper carries out the analysis by taking a game theoretic approach, where infinitely repeated games are constructed to capture the interactions between a publisher and a network administrator and suppress forged messages in OSNs. Critical conditions, under which the publisher is disincentivized to publish any forged messages, are identified in the absence and presence of misclassification on genuine messages. Closed-form expressions are established for the maximum number of forged messages that a malicious publisher could publish. Confirmed by the numerical results, the proposed infinitely repeated games reveal that forged messages can be suppressed by improving the payoffs for genuine messages, increasing the cost of bots, and/or reducing the payoffs for forged messages. The increasing detection probability of forged messages or decreasing misclassification probability of genuine messages also has a strong impact on the suppression of forged messages. [ABSTRACT FROM AUTHOR]

The attribute-based encryption (ABE) has drawn a lot of attention for fine-grained access control in blockchains, especially in blockchain-enabled tampering-resistant Internet-of-Things (IoT) systems. However, its adoption has been severely hindered by the incompatibility between the immutability of typical blockchains and the attribute updates/revocations of ABE. In this article, we propose a new blockchain-based IoT system, which is compatible with the ABE technique, and fine-grained access control is implemented with the attribute update enabled by integrating Chameleon Hash algorithms into the blockchains. We design and implement a new verification scheme over a multilayer blockchain architecture to guarantee the tamper resistance against malicious and abusive tampering. The system can provide an update-oriented access control, where historical on-chain data can only be accessible to new members and inaccessible to the revoked members. This is distinctively different from existing solutions, which are threatened by data leakage toward the revoked members. We also provide analysis and simulations showing that our system outperforms other solutions in terms of overhead, searching complexity, security, and compatibility. [ABSTRACT FROM AUTHOR]

Abstract Soil erosion by water is a critical issue in the red soil regions of Southern China. Particularly, Changting County experiences severe erosion due to unreasonable human activities, high rainfall intensities, steep slopes, erodible parent material, and poor vegetation cover. In this study, a quantitative soil loss analysis and qualitative social surveys (data from 1999 to 2015) are integrated to identify the erosion vulnerable areas in Zhuxi watershed of Southern China. Using Zhuxi watershed as an example in the investigation of soil erosion problems, analytic hierarchy and entropy value methods are adopted to evaluate soil erosion vulnerability and determine the proportions of factors in an index system. The vulnerability of soil erosion is evaluated from the human–nature system coupling perspective, considering socio-economic factors, which are synthetically analyzed and evaluated for soil erosion exposure, sensitivity, and adaptive capacity. Results show that (1) vulnerability is low in the east and west and highest in the middle of the Zhuxi watershed. The vulnerability of low, mild, and moderate soil erosions show a patchy distribution, wide range of intensity, and severe soil erosion fragility. (2) The degree of soil erosion vulnerability gradually decreased from 1999 to 2015. Low levels of vulnerability were distributed from fragmentation to concentrated distribution, while high vulnerabilities presented the opposite trend. However, the high levels of soil erosion showed a gradual decrease in vulnerability from 1999 to 2015. This study provides important theoretical and practical information for constructing a safe soil erosion control and management system and accelerating the sustainable development of social economy in the watershed. Graphical abstract Spatial distribution of erosion evolution vulnerability grade in Zhuxi watershed from 1999 to 2015. Unlabelled Image Highlights • Soil erosion vulnerability is mainly used to predict the potential impacts and trends of soil erosion. • Soil erosion vulnerability is high in the middle part of the Zhuxi watershed and low in its eastern and western parts. • The vulnerability of soil erosion gradually decreased in 1999–2015. • The result is beneficial to identify and reduce the vulnerable areas of soil erosion. [ABSTRACT FROM AUTHOR]

Rainfall erosivity is one important factor that controls soil erosion. The interannual variability of rainfall erosivity in southeast China connected to the ENSO (El Niño-Southern Oscillation). Rainfall erosivity across southeast China was assessed using daily rainfall data from 60 meteorological stations during the period from 1980 to 2013. We determined that models of erosivity based on daily rainfall can accurately predict annual rainfall erosivity. This paper presents a study of the effects of Niño3.4 SST (Sea Surface Temperatures) anomalies, the SOI (Southern Oscillation Index) and the MEI (Multivariate El Niño–Southern Oscillation Index) on rainfall erosivity in the southeast of China. Results indicated that average rainfall erosivity is stronger during El Niño events and weaker during La Niña events. Correlation analyses were applied to rainfall erosivity and Niño3.4 SST anomalies, SOI, and MEI. The effects of Niño3.4 SST and SOI on rainfall erosivity are evident, as demonstrated by a statistically significant correlation (> 95% confidence level). MEI was the best indicator ( P < 0.01) for representing the state of the ENSO. Results further indicated that 45, 31, and 40 of the 60 meteorological stations showed a significant correlation ( P < 0.05) between rainfall erosivity and SST anomalies, SOI, and MEI, respectively. Most of these stations were located in western Fujian Province. The ENSO was determined to exert the strongest influence on rainfall erosivity. This information would be useful in the implementation of new soil conservation strategies. [ABSTRACT FROM AUTHOR]

Abstract: Various features extracted from raw signals usually contain a large amount of redundant information which may impede the practical applications of machine condition monitoring and fault diagnosis. Hence, as a solution, dimensionality reduction is vital for machine condition monitoring. This paper presents a new technique for dimensionality reduction called the discriminant diffusion maps analysis (DDMA), which is implemented by integrating a discriminant kernel scheme into the framework of the diffusion maps. The effectiveness and robustness of DDMA are verified in three different experiments, including a pneumatic pressure regulator experiment, a rolling element bearing test, and an artificial noisy nonlinear test system, with empirical comparisons with both the linear and nonlinear methods of dimensionality reduction, such as principle components analysis (PCA), independent components analysis (ICA), linear discriminant analysis (LDA), kernel PCA, self-organizing maps (SOM), ISOMAP, diffusion maps (DM), Laplacian eigenmaps (LE), locally linear embedding (LLE) analysis, Hessian-based LLE analysis, and local tangent space alignment analysis (LTSA). Results show that DDMA is capable of effectively representing the high-dimensional data in a lower dimensional space while retaining most useful information. In addition, the low-dimensional features generated by DDMA are much better than those generated by most of other state-of-the-art techniques in different situations. [Copyright &y& Elsevier]

This paper describes a new unified formal modeling framework based on generic place/transition nets (PTNs) for concurrent integrated design and planning of electromechanical assemblies. First, a generic PTN model is defined as an abstract (meta)class of all types of PTNs. Then, an integrated object modeling framework is proposed for capturing and representing information and knowledge in the assembly design and planning processes based on the defined generic PTN modeling language and formalisms. The proposed integrated assembly model with the generic PTNs can uniformly represent the causal relations at the assembly level, the operation level, and the feature-based single-part level through the data abstraction of components and connectors on various levels of integrated assembly design and planning. An assembly model compatible with the STandard for the Exchange of Product model data (STEP, officially ISO 10303) is also built with the generic PTNs. To validate the proposed modeling framework, a prototype system has been developed, and a case study on gearbox assembly design and planning is provided. [ABSTRACT FROM AUTHOR]

This paper presents the development of a web-enabled database system for MEMS design and manufacturing which can provide the networked design and manufacturing services over the Internet. Specifically, the data obtained from various sources for MEMS manufacturing processes/materials are organised as databases by using the relational database management systems (RDBMS), Microsoft Access and MySQL. The database system can be accessed from a Java application as well as an applet. The stand-alone Java application is created using JFC Swing, JDBC and SQL, and the Java applet is subsequently created to enable web functionality. The underlying database is open, extensible through a set of administrator tools or via the web, which gives commercial design and manufacturing facilities the ability to update their own materials, processes and rules. This plays a crucial role in the system for advisory MEMS manufacturing service and concurrent collaborative MEMS design and simulation. The developed database system, e-MEMS Designer @Database, which contains extensive manufacturing or fabrication processes and materials databases for MEMS and microelectronics, is easily incorporated as a sub-system into both the standalone system and the web-enabled MEMS design system, MEMS Designer, which is being developed. The database system can also be updated to create a comprehensive data warehouse and an advisory system for MEMS manufacturing processes/materials selection. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a knowledge-intensive support paradigm for platform-based product family design and development. The fundamental issues underlying the product family design and development, including product platform and product family modeling, product family generation and evolution, and product family evaluation for customization, are discussed. A module-based integrated design scheme is proposed with knowledge support for product family architecture modeling, product platform establishment, product family generation, and product variant assessment. A systematic methodology and the relevant technologies are investigated and developed for knowledge supported product family design process. The developed information and knowledge-modeling framework and prototype system can be used for platform product design knowledge capture, representation and management and offer on-line support for designers in the design process. The issues and requirements related to developing a knowledge-intensive support system for modular platform-based product family design are also addressed. [Copyright &y& Elsevier]

Contemporary design process requires the development of a new computational intelligence or soft computing methodology that involves intelligence integration and hybrid intelligent systems for design, analysis and evaluation, and optimization. This paper first presents a discussion of the need to incorporate “intelligence” into an automated design process and the various constraints that designers face when embarking on industrial design projects. Then, it presents the design problem as optimizing the design output against constraints and the use of soft computing and hybrid intelligent systems techniques. In this paper, a soft-computing-integrated intelligent design framework is developed. A hybrid dual cross-mapping neural network (HDCMNN) model is proposed using the hybrid soft computing technique based on “cross-mapping” between a back-propagation network (BPNN) and a recurrent Hopfield network (HNN) for supporting modeling, analysis and evaluation, and optimization tasks in the design process. The two networks perform different but complementary tasks—the BPNN “decides” if the design problem is a “type 0” (rational) or “type 1” (non-rational) problem, and the output layer weights are then used as the energy function for the HNN. The BPNN is used for representing design patterns, training classification boundaries, and outputting network weight values to the HNN, and then the HNN uses the calculated network weight values to evaluate and modify or re-design the design patterns. The developed system provides a unified soft-computing-integrated intelligent design framework with both symbolic and computational intelligence. The system has self-modifying and self-learning functions. Within the system, only one network training is needed for accomplishing the evaluation, rectification/modification, and optimization tasks in the design process. Finally, two case studies are provided to illustrate and validate the developed model and system. [ABSTRACT FROM AUTHOR]

E-Products, e-Manufacturing and e-Service are the goals of an enterprise to achieve. To achieve these goals, smart software and NetWare are needed to provide proactive maintenance capabilities such as performance degradation measurement, fault recovery, self-maintenance, and remote diagnostics. This paper reports the preliminary development of an Internet server controller based intelligent maintenance system for information appliance products (consumer appliances). The discussion also involves on how to develop products and manufacturing systems using Internet-based intelligent technologies and how to ensure product quality, coordinate activities, reduce costs and change maintenance practice from the breakdown reaction to prevention. In the paper, a hybrid intelligent approach using hardware and software agents (watchdog agent) is adopted. The server controller is web-enabled and its core is an embedded network model. The software agent is implemented through a package of Smart Prognostics Algorithms. The package consists of embedded computational prognostic algorithms including neural network based, time-series based, wavelet-based and hybrid joint time-frequency methods, etc. and a software toolbox for predicting degradation of devices and systems. The effectiveness of the proposed scheme is verified by developing a real system for the washing machine. [ABSTRACT FROM AUTHOR]

This paper reports the work of selecting suitable manufacturing processes and materials in concurrent design for manufacturing environment. In the paper, a fuzzy knowledge-based decision support method is proposed for multi-criteria decision-making in evaluating and selecting possible manufacturing process/material combinations in terms of the total production cost. Based on the proposed method, a prototype Web-based knowledge-intensive manufacturing consulting service system (WebMCSS) with the client-knowledge server architecture is developed to help designers/users find good processes and materials while still at the conceptual level of design. The system, as one of the important parts of an advanced design for manufacturing tool, is a concept level process and material selection tool that can be used as both a standalone application and a Java applet freely available via the Web. Interlinked with Web pages of tutorials, and reference pages explaining the facets, fabrication processes and material choices, the system performs reasoning and calculations using the process capability and material property data from the remote Web-based database and knowledge base that can be maintained and updated via the Internet. The use of the system is illustrated with an example. [ABSTRACT FROM AUTHOR]

In order to assist the designer in the design process, it is necessary to develop a new intelligent computational methodology that involves the integration of design, analysis and evaluation, and optimisation. In this paper, a hybrid crossmapping neural network model (HCMNN) is proposed to support design, analysis and evaluation, and optimisation in the design process, which integrates a back-propagation neural network (BPNN) and a Hopfield neural network (HNN). The BPNN is used for representing design patterns, training classification boundaries, and outputting the net weight values to the HNN, and then the HNN uses the calculated weight values to evaluate and modify or redesign the design patterns. The developed system provides a unified computational intelligent design framework. The system has self-modifying or self-learning functions. Within the system, only one network is needed to train for accomplishing design analysis and evaluation, rectification/modification and optimisation tasks in the design process. Finally, two case studies are provided to verify the proposed model. [ABSTRACT FROM AUTHOR]

An intensive knowledge engineering system is a large-scale knowledge framework that allows modeling and processing various types, different levels and multiple functionalities of knowledge in a process. The paper develops a knowledge intensive multi-agent system for cooperative/collaborative assembly modeling and process planning in a distributed design environment. In this paper, an AI protocol based knowledge intensive methodology is first developed for distributed collaborative design in facilitating concurrent integration and cooperation/collaboration of intelligent design agents. Then, unified class of knowledge intensive Petri nets is defined using an O-O knowledge-based Petri net approach and used an AI protocol for knowledge objects cooperation formalisms. Detailed cooperative/collaborative mechanisms and algorithms for handling integration and negotiation problems among intelligent agents are provided based on the knowledge objects cooperation formalisms. A research prototype system is implemented under the knowledge-intensive multi-agent framework with concurrent integration of multiple cooperative knowledge source and software tools/packages. Thus, assembly-oriented design could be carried out simultaneously and intelligently in distributed & integrated collaborative environment (DICE). [ABSTRACT FROM AUTHOR]

Planning of robot pose trajectory is a very complex task that plays a crucial role in design and application of robots in task space. This paper presents a unified approach to optimal pose trajectory planning for robot manipulators in Cartesian space through a genetic algorithm (GA) enhanced optimization of the pose ruled surface. The robot pose ruled surface is formed as a motion locus of its configuration vector. The unified treatment of the end-effector positions and orientations is based on the robot pose ruled surface concept and used in trajectory interpolations. The planning of robot pose trajectories is accomplished through the way of generating and optimizing robot pose ruled surfaces under the constraints of kinematics, dynamics and control performances. The optimization model is established based on functional analysis and dynamics planning, and instantiated by using high-order parametric space curves as position and orientation trajectories. A GA enhanced optimization method is used to choose the parameters (coefficients) of space curves such that the pose ruled surface and its area and area change ratios are optimized for achieving good kinematics and dynamics performances. With robot''s dynamics constraints taken into account, the optimized trajectories are realizable and robust for control. Two cases are studied to verify the feasibility of the proposed approach. [Copyright &y& Elsevier]

In recent years, the most widely distributed eukaryotic messenger RNA (mRNA) modification, N6-methyladenosine (m6A), has received a large amount of interest, in part due to the development and advances of high-throughput RNA sequencing. The effects of m6A mRNA on tumor progression have been the most widely studied, and large amounts of conflicting data have been reported due to differences in tumor contexts, cell types or cell states. The majority of these studies were related to the significance of m6A mRNA on tumor cells, including on proliferation, stemness, invasion capability, etc. However, it has been noted that tumorigenesis and tumor progression cannot occur without support from the tumor microenvironment (TME), which contains multiple types of stromal cells, such as infiltrating immune cells (IICs), vascular cells, mesenchymal stem cells (MSCs), cancer-associated fibroblasts (CAFs), and various environmental factors. Here, we summarized the contributions of abnormal m6A mRNA in stromal cells within the TME and described the effects of m6A mRNA on TME remodeling. [ABSTRACT FROM AUTHOR]

Introduces a series of articles on integrated and hybrid intelligent systems in product design and development. Methodology that involves the combined use of computer-aided engineering and artificial intelligence/knowledge intensive approach to bridge the gap for the full deployment of a computer aided/virtual design alternative; Neuro-fuzzy-based approximation approach for forecasting material-flow behavior in the offer phase; Proposed approach for integration and interoperation between a design house and a manufacturer that may or may not have prior relationship by developing semantic web services for business and engineering transactions.

Abstract: The development of efficient on-line data processing and decision support algorithms is one of future trends of expert systems for machine condition monitoring research. This paper contributes to a lean model for machine performance assessment by combining an efficient signal processing algorithm, an effective feature selection criterion, and an intelligent assessment method. In the proposed model, firstly, a second generation wavelet packet transform is used to project raw signals into the wavelet domain; secondly, the Fisher criterion is applied to reduce redundant dimensions; eventually, a fuzzy c-means clustering method is used to assess and classify the performance of mechanical systems. The vibration signals from a rolling element bearing experiment has been used to verify both efficiency and effectiveness of the lean model. Compared with conventional methods, the lean model can reduce the time consumption of feature extraction by 49.7% and storage space or data transfer load related to the feature dimensionality by 97.7%, which indicates a great improvement in efficiency. [Copyright &y& Elsevier]

Abstract: The efficiency of data processing is critical for the on-line monitoring applications of industrial components and systems, both from the viewpoints of the rapid adaptation to the non-stationary signals and the cost of information storage and transmission. In this paper, we propose an enhanced feature extraction model for machinery performance assessment, which is based on the lifting-based wavelet packet transform (WPT) and sampling-importance-resampling methods. The lifting-based WPT decomposes the signals. Then the sampling-importance-resampling procedure is applied in the wavelet domain to extract the distribution information and compose the feature vectors. Finally, a support vector machine is used to assess the normal or abnormal condition based on these extracted features. To validate the proposed new model, an endurance test of pressure regulators has been carried out. Compared to the traditional wavelet packet method, the new model can not only keep the precision level but also improve the efficiency by over 60%. [Copyright &y& Elsevier]

We designed a valveless micropump excited by a piezoelectric actuator for medical applications. The complete electric–fluid–solid coupling model is built upon using ANSYS software (Canonsburg, PA) to investigate the behaviors of the micropump. The effects of the geometrical dimensions on the micropump characteristics and its efficiency are analyzed. The simulation results show that there is an optimal thickness of the piezoelectric layer to obtain a large pump flow, and that this optimal thickness is affected by the material and the thickness of the pump membrane. To enhance the performance of the micropump, some important diffuser parameters, such as the diffuser length, the diffuser angle, and the neck width, should be optimized. However, the variations of the diffuser’s geometrical dimensions do not affect the optimal thickness of the piezoelectric layer. [ABSTRACT FROM AUTHOR]

Today, real-time measurement of dynamic power factor in resistance spot welding (RSW) is of increasing importance. On the basis of the welding transformer circuit model, a new method is proposed to measure the peak angle of the welding current and then calculate the dynamic power factor in each half-wave. The tailored sensing and computing system ensures that the measuring method possesses a real-time computational capacity with satisfying accuracy. Since the power factor cannot be represented via an explicit function with respect to measurable parameters, the traditional method(s) has to approximate the power factor angle with a constant phase lag angle and fails to detect its dynamic characteristics. An offline-trained embedded artificial neural network (ANN) successfully realizes the real-time implicit function calculation or estimation. A digital-signal-processor-based RSW monitoring system is developed to perform ANN computation. Experimental results indicate that the pro- posed method is applicable for measuring the dynamic power factor in single-phase half-wave controlled rectifier circuits. [ABSTRACT FROM AUTHOR]

The hilly red soil region of southern China suffers from severe soil erosion that has led to soil degradation and loss of soil nutrients. Estimating the content and spatial variability of soil organic carbon (SOC) and soil total nitrogen (STN) and assessing the influence of topography and land-use type on SOC and STN after years of soil erosion control are important for vegetation restoration and ecological reconstruction. A total of 375 topsoil samples were collected from Changting County, and their SOC and STN distributions were studied by using descriptive statistics and geostatistical methods. Elevation, slope, aspect and land-use type were selected to investigate the impacts of natural and human factors on the spatial heterogeneity of SOC and STN. The mean SOC and STN concentrations were 15.85 and 0.98 g kg-1 with moderate spatial variations, respectively. SOC and STN exhibited relatively uniform distributions that decreased gradually from the outside parts to the center of the study area. The SOC and STN contents in the study area were still at moderate and low levels after years of erosion control, which suggests that soil nutrient improvement is a slow process. The lowest SOC and STN values were at lower elevations in the center of Changting County. The results indicated that the SOC and STN contents increased most significantly with elevation and slope due to the influence of topography on the regional natural environment and soil erosion in the eroded hilly region. No significant variations were observed among different slope directions and land-use types. [ABSTRACT FROM AUTHOR]

• The evaluation system was constructed by comprehensively considering social and environmental factors. • The evaluation system facilitates decision-makers for partition management. • The ecological vulnerability of Fujian shows a trend of higher in the east and lower in the west. • The reliability of the evaluation results was validated by curve fitting. • The order weighted operator was used to simulate multiple situations for decision-makers. Evaluation of the ecological vulnerability facilitates ecological protection and management. We presented a well-organized and comprehensive evaluation system and analysis method of ecological vulnerability. We used Fujian Province, China, as a case study and validated the reliability of evaluation results. The details are as follows. Based on the framework of sensitivity-resilience-pressure (SRP) coupled with the "social-environmental" system (SES), this study selected 23 indicators and determined their weights by a combination of subjective and objective weighting methods to systematically construct the ecological vulnerability evaluation system. By establishing a fuzzy evaluation model, the indicator data were fuzzily mapped into evaluation scores for the calculation of the ecological vulnerability index (EVI). Following the calculation results, the spatial clustering analysis based on K-means, driving factor analysis based on GeoDetector and spatial autocorrelation analysis were conducted. Finally, an ecological vulnerability analysis under multiple decision-making attitudes was conducted based on the ordered weighted average (OWA) operators. The results were as follows. (1) The ecological vulnerability of Fujian Province showed a trend of higher in the east and lower in the west, and there is an obvious spatial aggregation effect. The high-high aggregation areas mainly distributed in the eastern coastal areas of Fujian Province, and the low-low aggregation areas mainly distributed in the western and central areas. (2) Landscape pattern sensitivity had the highest degree of explanation for the EVI. The main driving factors of the EVI in coastal cities were different from those of the EVI in inland cities. (3) We divided the study area into four categories: high-quality development areas, transformational development areas, ecological-economic synergy areas and ecological function areas. (4) With an increase in the decision-making risk coefficient, the ecological vulnerability of Fujian Province gradually increased. The results of the study provide important guidance for ecological protection and sustainable development in Fujian Province. Moreover, the study framework has reference value for related studies of regional ecological vulnerability evaluation. [ABSTRACT FROM AUTHOR]

Abstract: Taking into account the scarcity of feasible fertilizing rate feedback from on-board sensors and the limited computation power of controller mounted on the variable-rate granular fertilizer applicator, optimum control index chart is a good option for controller design to achieve accurate variable-rate fertilizing control. The index chart contains a list of optimum control parameters optimized to meet combined objectives: fertilizing accuracy, energy saving and fertilizing consistency. To generate such list, the probabilistic meta-model based on Gaussian Processes (GP) is firstly utilized to identify the variable-rate fertilizing process with the indoor experimental data. Consequently, the meta-model-based optimization process is presented with the given fertilizing rate, previous opening length and its adjusting direction. The optimal control parameters chart is obtained by the iterative multi-objectives optimization based on Genetic Algorithm (GA). Thus, the fertilizing prescription can be converted to the controller’s actions by searching the optimum control parameters chart. The well-trained GP models predict the fertilizing rate and the fertilizing coefficient of variation with limiting mean relative error to 0.014 and 0.089, respectively. Finally, by considering four main error sources, the verified fertilizing model improves the average fertilizing rate error to no more than 5% at given management zone scale in field test. [Copyright &y& Elsevier]

• Proanthocyanidin (PAC) inhibits ferroptosis in spinal cord injury (SCI). • PAC decreases iron contents and oxidative stress in SCI. • PAC increases GSH and GPX4 levels in SCI. • PAC rescues injuried tissues in SCI and improves recovery after SCI. • Proanthocyanidin promotes functional recovery of spinal cord injury via inhibiting ferroptosis. Improving the microenvironment of lesioned spinal cord to minimize the secondary injury is one important strategy to treat spinal cord injury (SCI). The ensuing hemorrhage after SCI has tight connection with ferroptosis. This study investigated the effects of proanthocyanidins (PACs) on SCI repair and the underlying mechanisms. Adult female mice were divided into four groups, including sham, SCI, PACs5 and PACs10 (i.p. 5 and 10 mg/kg PACs after SCI respectively). The impacts of SCI and PACs treatment on redox parameters (iron contents, TBARS, GSH, and GPX activities) and ferroptosis essential factors such as ACSL4, LPCAT3, Alox15B, Nrf2, HO-1, GPX4 were investigated. The results demonstrated that PACs treatment significantly decreased the levels of iron, TBARS, ACSL4, and Alox15B, while increased the levels of GSH, GPX4, Nrf2, and HO-1 in traumatic spinal cords. Above all, PACs improved the locomotive function of SCI mice. These results suggest that PACs might be potential therapeutics for SCI repair by inhibiting ferroptosis in SCI. [ABSTRACT FROM AUTHOR]