Concurrent Behavior Research Articles

Non-linear communication via graded modal session types

Session types provide guarantees about concurrent behaviour and can be understood through their correspondence with linear logic, with propositions as sessions and proofs as processes. However, a strictly linear setting is somewhat limiting since there exist various useful patterns of communication that rely on non-linear behaviours. For example, shared channels provide a way to repeatedly spawn a process with binary communication along a fresh linear session-typed channel. Non-linearity can be introduced in a controlled way in programming through the general concept of graded modal types, which are a framework encompassing various kinds of coeffect typing (describing how computations make demands on their context). This paper shows how graded modal types can be leveraged alongside session types to enable various well-known non-linear concurrency behaviours to be re-introduced in a precise manner in a type system with a linear basis. The ideas here are demonstrated using Granule, a functional programming language with linear, indexed, and graded modal types. We then define a core calculus capturing the requisite type features and our new graded modal session-typed primitives. We give an operational model and establish key properties following from the typing.

Curiosity and Digital Stories: Exploring Preschoolers’ Behaviors

<p style="text-align:justify">Given curiosity’s fundamental role in motivation and learning and considering the widespread use of digital stories as educational tools from the preschool age, we pursued measuring preschoolers’ curiosity when interacting with digital stories. Using 129 toddlers and preschoolers as a sample, three groups (one for each class) were given different versions of the same digital story to listen to: interactive, non-interactive, and animated. Toddlers' verbal and nonverbal behaviors were utilized to quantify curiosity as a condition brought on by the app. The participants' verbal and nonverbal behaviors were recorded during the digital reading aloud. Every child's data was encoded at one-minute intervals to examine concurrent behavior, and the results were then compiled. The findings show that interactive presentation formats encourage more touching and language use but less noise production and that interaction and the creative use of hot spots in digital illustrations are key elements in piquing viewers' curiosity while contributing to the strengthening of the engagement to the activity and the cultivation of critical thinking, creativity, and imagination.</p>

Ferromagnetic quantum critical point protected by nonsymmorphic symmetry in a Kondo metal

Quantum critical points (QCPs), zero-temperature phase transitions, are windows to fundamental quantum-mechanical phenomena associated with universal behaviour. Magnetic QCPs have been extensively investigated in the vicinity of antiferromagnetic order. However, QCPs are rare in metallic ferromagnets due to the coupling of the order parameter to electronic soft modes. Recently, antisymmetric spin-orbit coupling in noncentrosymmetric systems was suggested to protect ferromagnetic QCPs. Nonetheless, multiple centrosymmetric materials host FM QCPs, suggesting a more general mechanism behind their protection. In this context, CeSi2-δ, a dense Kondo lattice crystallising in a centrosymmetric structure, exhibits ferromagnetic order when Si is replaced with Ag. We report that the Ag-substitution to CeSi1.97 linearly suppresses the ferromagnetic order towards a QCP, accompanied by concurrent strange-metal behaviour. Herein, we suggest that, despite the centrosymmetric structure, spin-orbit coupling arising from the local noncentrosymmetric structure, in combination with nonsymmorphic symmetry, can protect ferromagnetic QCPs. Our findings offer a general guideline for discovering new ferromagnetic QCPs and highlight one new family of materials within which the interplay of topology and quantum phase transitions can be investigated in the context of strongly correlated systems.

Modeling the effect of material heterogeneity on the thermo-mechanical behavior of concrete using mesoscale and stochastic field approaches

The adverse impact of high temperatures on concrete is a well-recognized issue that can lead to significant mechanical deterioration and structural integrity loss. Factors such as aggregate type, cement composition, temperature, duration of exposure, and moisture content can substantially influence the fire resistance of concrete. To simulate and better understand the effects arising from the heterogeneity of concrete in a fire situation, a mesoscale approach is proposed, using the Mesh Fragmentation Technique (MFT) to assess the complex thermo-mechanical behavior of concrete. The MFT introduces high aspect ratio interface elements to model crack propagation and interfacial transition zones by means of an appropriated tensile damage constitutive law. In this extended framework, a fully-coupled thermo-mechanical model is proposed. The modeling approach includes considerations of both macroscopic and mesoscopic scales, in which the coarse aggregate, mortar matrix and interfacial transition zones are represented. Besides, a stochastic distribution is assumed for the material properties to account for the lower scale heterogeneity. The main novelty proposed in this study consists in the synergy of mesoscale and stochastic approaches that are herein combined to model the effect of heterogeneity on the concurrent macro-mesoscale thermo-mechanical behavior of concrete. To validate the numerical model’s capabilities in capturing thermally induced cracks, benchmark cases and a simulation of a bending beam exposed to elevated temperatures are presented. The results demonstrate the potential of the proposed approach in predicting the behavior of concrete subjected to thermal loading and the role played by heterogeneity in the thermally induced cracking.

Spectral-switching analysis reveals real-time neuronal network representations of concurrent spontaneous naturalistic behaviors in human brain.

Despite abundant evidence of functional networks in the human brain, their neuronal underpinnings, and relationships to real-time behavior have been challenging to resolve. Analyzing brain-wide intracranial-EEG recordings with video monitoring, acquired in awake subjects during clinical epilepsy evaluation, we discovered the tendency of each brain region to switch back and forth between 2 distinct power spectral densities (PSDs 2-55Hz). We further recognized that this 'spectral switching' occurs synchronously between distant sites, even between regions with differing baseline PSDs, revealing long-range functional networks that would be obscured in analysis of individual frequency bands. Moreover, the real-time PSD-switching dynamics of specific networks exhibited striking alignment with activities such as conversation and hand movements, revealing a multi-threaded functional network representation of concurrent naturalistic behaviors. Network structures and their relationships to behaviors were stable across days, but were altered during N3 sleep. Our results provide a new framework for understanding real-time, brain-wide neural-network dynamics.

The Relationship between Lifestyle Behaviors and Mental Illness in Women in College.

Women, particularly those in college, have the highest prevalence of any mental illness (MI), which negatively impacts social connection, academic performance, and health. Research into alternative treatment methods suggests that lifestyle behaviors are safer and more effective than medication at reducing MI symptoms. This study explores the relationship between lifestyle behaviors and MI in college women through an online survey. The survey included a food frequency questionnaire (Diet History Questionnaire II) and questions about lifestyle behaviors, symptoms of MI, and sociodemographic information. Diet quality was calculated using the Healthy Eating Index (HEI), and MI was assessed using the Depression, Anxiety, and Stress Scale-21. Independent sample t-tests, ANOVA, and chi-square analyses were conducted. A total of 222 women completed the survey. Overall, diet quality was poor, with a mean HEI of 62.6 ± 10.4. No significant differences or associations were found between MI groups for total HEI score, sleep, or tobacco use. However, alcohol use was significantly associated with MI (p = 0.049). Individuals with fewer concurrent unhealthy lifestyle behaviors had less severe symptoms of depression (p = 0.009) and anxiety (p < 0.001) compared to those with more unhealthy lifestyle behaviors. In this study, alcohol use was the only independent lifestyle behavior associated with symptoms of MI. We also found an association between the number of concurrent unhealthy lifestyle behaviors and depression and anxiety symptoms. Future research should explore the benefits of a healthy lifestyle on MI in a more diverse sample of women.

Multidimensional profiles of head start preschoolers' moral self-concept predict subsequent, but not concurrent, aggression.

The moral self-concept (MSC) describes how children view themselves as moral agents. Research suggests that the MSC may relate to moral behavior, yet little is known about how MSC relates to moral behavior in preschoolers. One hundred six low-income children (M age = 52.78 months, SD = 6.61 months) and their teachers participated in this study. In the fall, children completed a MSC puppet task measure. In the fall and spring, teachers reported via children's survey prosocial behavior and aggressive behavior. We used a person-centered approach to identify profiles of MSC, which revealed two profiles of behavior: comforting prosocials and helpful aggressors. Comforting prosocials showed a moderate preference for comforting, a slight preference for helping, and a slight preference for avoiding aggression. Helpful aggressors had a moderate aversion to comforting, a strong preference for helping, and a slight preference for aggressive behavior. Subsequent analysis of covariance analysis revealed that MSC profiles did not differ in concurrent behavior but did differ in behavior 6 months later. The comforting prosocial group participated in more aggression than the helpful aggressors. Additionally, analysis of covariance analysis of change in aggression scores over time showed that comforting prosocials aggression increased, while helpful aggressors aggression decreased. Both groups over time decreased in prosocial behavior, but to different degrees. Overall, findings reveal that the MSC in preschoolers may relate to future not concurrent moral behavior.

Enhancing Resilience in Biometric Research: Generation of 3D Synthetic Face Data Using Advanced 3D Character Creation Techniques from High-Fidelity Video Games and Animation.

Biometric authentication plays a vital role in various everyday applications with increasing demands for reliability and security. However, the use of real biometric data for research raises privacy concerns and data scarcity issues. A promising approach using synthetic biometric data to address the resulting unbalanced representation and bias, as well as the limited availability of diverse datasets for the development and evaluation of biometric systems, has emerged. Methods for a parameterized generation of highly realistic synthetic data are emerging and the necessary quality metrics to prove that synthetic data can compare to real data are open research tasks. The generation of 3D synthetic face data using game engines' capabilities of generating varied realistic virtual characters is explored as a possible alternative for generating synthetic face data while maintaining reproducibility and ground truth, as opposed to other creation methods. While synthetic data offer several benefits, including improved resilience against data privacy concerns, the limitations and challenges associated with their usage are addressed. Our work shows concurrent behavior in comparing semi-synthetic data as a digital representation of a real identity with their real datasets. Despite slight asymmetrical performance in comparison with a larger database of real samples, a promising performance in face data authentication is shown, which lays the foundation for further investigations with digital avatars and the creation and analysis of fully synthetic data. Future directions for improving synthetic biometric data generation and their impact on advancing biometrics research are discussed.

Dependability model of automated intelligent regenerative life support system for space missions

Long-duration human space missions require intelligent regenerative life support systems that can recycle resources and automatically manage failures. This paper explores using Petri nets to model the reliability and complex interactions of such closed-loop systems. An architecture consisting of primary systems, backups, and consumable reserves is outlined. The automation system that controls everything is described. Petri nets can capture concurrency, failure modes, redundancy, and dynamic behavior. A modular modeling methodology is presented to develop hierarchical Petri net models that scale in fidelity. Elementary fragments represent failures and redundancy. Subsystem modules can be substituted for more detailed models. Analysis and simulation assess system reliability and failure response. This supports designing ultra-reliable systems to safely sustain human life in space.

Identifying Concurrent Behaviours in Erlang Legacy Systems

In Erlang, behaviours are special forms of design patterns. There are many benefits to using behaviours. For example, behaviours can help abstract away the most common parts when solving similar problems. Design pattern recognition may help understand the source code of the software. It can provide structured information about the purpose of specific parts and the design decisions behind the implementation. For object-oriented languages, several tools exist that use different approaches and methods to identify design patterns. We present a method for identifying source code fragments in legacy Erlang systems amenable to transforming into client-server Erlang design patterns. In our analysis, we identify the base set of server candidates using concurrent process analysis and narrow down the result using further static analysis knowledge using the RefactorErl framework.

Co-occurrence of habit-forming risk behaviors and their socio-demographic, health status and lifestyle determinants: a population-based cross-sectional study

BackgroundAlthough habit-forming risk behaviors frequently co-occur, determinants of concurrent risk behaviors have rarely been investigated. The aim of the present study was to investigate socio-demographic, health status, and lifestyle determinants of single versus concurrent risk behaviors in general-population adults.MethodsWe analyzed data from 32,622 participants (74.5% female; mean age = 57.9 ± 14.2 years) of the NutriNet-Santé cohort who completed the Alcohol Use Disorders Identification Test, the 12-item Cigarette Dependence Scale, the modified Yale Food Addiction Scale 2.0, and the Internet Addiction Test in 2021–2022. Using established cutoffs, participants were first split into 2 groups (presence versus absence) for each risk variable (alcohol use disorders, nicotine dependence, food addiction, Internet addiction) and were then divided into 3 groups (no risk behavior, 1 risk behavior (reference), and ≥ 2 risk behaviors). The association between socio-demographic, health status, and lifestyle exposures and individual/concurrent risk behaviors were investigated with polytomous logistic regression.ResultsYounger age (Odds Ratio (OR) = 2.04; 95% Confidence Interval (CI: 1.62–2.56), current financial difficulties (OR = 1.29; CI: 1.08–1.54), self-perceived poor health (OR = 1.70; CI: 1.32–2.20), overall poor dietary quality (OR = 2.88; CI: 2.06–4.02), being underweight (OR = 1.46; CI: 1.05–2.04), having obesity (OR = 1.62; CI: 1.31–1.99), lack of affection during childhood (OR = 1.41; CI: 1.18–1.69), and a lifetime prevalence or medication use for a mental disorder (OR = 1.46; CI: 1.24–1.73) were positively associated with having ≥ 2 versus 1 risk behavior (all p < 0.05). The comparison of none versus 1 risk behavior revealed the same determinants in addition to having a higher education, being physically active at work, and being overweight.ConclusionsWe investigated determinants of concurrent habit-forming risk behaviors among adults in a large, population-based study. The findings could serve as impetus for future research in this domain and ultimately help guide addiction prevention efforts.

Reusable formal models for concurrency and communication in custom real-time operating systems

In embedded systems, the execution semantics of the real-time operating system (RTOS), which is responsible for scheduling and timely execution of concurrent processes, is crucial for the correctness of the overall system. However, existing approaches for the formal verification of embedded systems typically abstract from the RTOS completely, or provide a detailed and synthesizable formal model of the RTOS. While the former may lead to unsafe systems, the latter is not compatible with industrial design processes. In this paper, we present an approach for reusable abstract formal models that can be configured for custom RTOS. Our key idea is to formally capture common execution mechanisms of RTOS like preemptive scheduling, event synchronization, and communication abstractly in configurable timed automata models. These abstract formal models can be configured for a concrete custom RTOS, and they can be combined into a formal system model together with a concrete application. Our reusable models significantly reduce the manual effort of defining a formal model that captures concurrency and real-time behavior, together with the functionality of an application. The resulting formal model enables analysis, verification, and graphical simulation. We validate our approach by formalizing and analyzing a rescue robot application running the custom open source RTOS EV3RT.

Sibling and pet relationships: links with adversity and adjustment in pre-adolescence

Although children view pets (i.e. companion animals) as family members, child-pet relationships are rarely studied alongside other family relationships. In a socially diverse sample of 77 British families with pre-adolescent children (M age = 12.14 years, SD = 0.29 years), we examine how the quality of children’s relationships with their pets and siblings vary in the context of adversity, and controlling for parent-child relationship quality, predict their behavioral adjustment. Children reported on the quality of their relationships and mothers rated child adjustment. Mother, child, and researcher ratings were combined to construct a multi-informant index of adversity. Child-pet positivity differed by adversity level for girls (but not boys) and, in low adversity contexts, was associated with greater concurrent prosocial behavior. Sibling positivity was unrelated to adversity, but had a buffering effect, in that adversity only predicted increases in problem behaviors over 12 months for those with low sibling positivity.

"Load-Unload" Effect of Manganese Oxides on Phosphorus in Surface Water of the Pearl River Estuary

Phosphorus (P) conveyed by surface runoff plays an essential role in regulating nutrient balance and primary production in estuarine waters. In this study, basic physiochemical properties, total phosphorus (TP, including speciation), particulate iron (PFe), particulate manganese (PMn), and particulate aluminum (PAl) of the surface water in the Pearl River Estuary (PRE) in different seasons were determined to investigate the spatiotemporal distribution characteristics of P and to identify the crucial factor controlling P migration and transformation in the freshwater-saltwater interaction zone. TP concentrations (28.88-233.68 μg·L-1) decreased with increasing salinity gradient owing to deposition and dilution. The proportions of P speciation followed a decreasing order as dissolved inorganic phosphorus (DIP, 37.3%) &gt; particulate inorganic phosphorus (PIP, 22.7%) &gt; dissolved organic phosphorus (DOP, 21.0%) &gt; particulate organic phosphorus (POP, 19.0%). PIP was positively related to PFe, PMn, and PAl (P &lt; 0.05), confirming their concurrent migration behaviors. In addition, the increase in salinity promoted the desorption of phosphate on the suspended particulate matters, which mainly took place near the freshwater-saltwater interface. A significant positive correlation (P &lt; 0.001) between the solid-liquid phase partitioning coefficient (Kd) of phosphate and salinity indicated that PIP was present mainly in more stable forms in the brackish water. Most importantly, a better relationship between Kd and PMn (P &lt; 0.01) supported our scientific hypothesis of the "load-unload" effect of Mn oxides on P:particulate-carrying phosphates transported from the freshwater zone tend to be desorbed and released into the brackish water.

Bounded model checking for interval probabilistic timed graph transformation systems against properties of probabilistic metric temporal graph logic

Cyber-physical systems often encompass complex concurrent behavior with timing constraints and probabilistic failures on demand. The analysis whether such systems with probabilistic timed behavior adhere to a given specification is essential. The formalism of Interval Probabilistic Timed Graph Transformation Systems (IPTGTSs) is often a suitable choice to model cyber-physical systems because (a) its rule-based approach to graph transformation can capture a wide range of system's structure dynamics when the states of the system can be represented by graphs while (b) it employs interval specifications for probabilistic behavior as well as lower and upper bounds on delays of steps to support systems where precise probabilities and delays are not known or may change during the runtime of the system. Probabilistic Metric Temporal Graph Logic (PMTGL) has been introduced as a powerful specification language to express worst-case/best-case probabilistic timed requirements such as actor-based soft deadlines using (a) path properties relying on its Metric Temporal Graph Logic fragment to track individual graph elements and (b) an operator inherited from Probabilistic Timed Computation Tree Logic to express worst-case/best-case probabilistic requirements identifying worst-case/best-case resolutions of non-determinism. Bounded Model Checking (BMC) support for Probabilistic Timed Graph Transformation Systems (PTGTSs) w.r.t. properties specified using PMTGL has been already presented. However, for IPTGTSs no analysis support w.r.t. PMTGL properties has been developed for stating metric temporal properties on identified subgraphs and their structural changes over time.In this paper, we adapt the BMC approach developed for PTGTSs to the case of IPTGTSs extending modeling and analysis support to the usage of probability intervals more appropriately covering cyber-physical systems where probabilistic effects cannot be specified precisely and need to be approximated instead. In our evaluation, we apply an implementation of our BMC approach in AutoGraph to a novel running example demonstrating the effect of using probability intervals instead of precise probability values.

Teachers' proactive behaviour: Interactions with job characteristics and professional competence in a longitudinal study.

In times of accelerating changes, teachers who proactively engage in activities towards school improvement and innovation are increasingly needed. Still, studies on factors that affect teachers' proactive behaviour are rare. Integrating previous research on proactive behaviour within the Job Demand-Resources (JD-R) Model, this paper investigates how job characteristics (time pressure, bureaucratic structures, participative climate, personal initiative of the team) and aspects of teachers' professional competence (self-efficacy, self-regulation skills and knowledge) contribute to and interact with their proactive behaviour. A total of 130 German secondary school teachers (M(SD)age = 44.05 (11.36), 65% female) participated in this study. We employed a full two-wave panel design, with measurement points 5 months apart. The data were analysed with (moderated) single indicator modelling and a cross-lagged panel model. While teachers' self-efficacy in implementing change and self-regulation skills predicted their concurrent proactive behaviour, job characteristics and teachers' knowledge had no such cross-sectional effects. In addition, we found an interaction effect of time pressure and teachers' self-efficacy on proactive behaviour. Including the second measurement point, data indicated no cross-lagged effects of the job and personal factors on proactive behaviour. However, cross-lagged analysis revealed that teachers' proactive behaviour predicted their later self-efficacy in implementing change and the time pressure they perceive. Examining both cross-sectional and longitudinal effects, this study highlights the importance of measurements over time when analysing factors that influence teachers' proactive behaviour: While aspects of professional competence appear to be trainable concurrent resources, time pressure can limit their effect. Finally, cross-lagged effects of teachers' proactive behaviour on their later self-efficacy and time pressure appear as influential in the long run.

A spatial dependence approach to assessing the impacts of Sustainable Forestry Initiative’s Fiber Sourcing certification on forestry Best Management Practices in Georgia, United States

Understanding the effectiveness of the Sustainable Forestry Initiative Fiber Sourcing (SFI-FS) standard in increasing/sustaining a high forestry Best Management Practices (BMP) implementation rate is critical for the overall sustainability of southern forestlands. We analyze the impacts of SFI-FS standard on the forestry BMP implementation rate in Georgia, United States, by considering the locations of certified and non-certified mills between 2002 and 2019. The results show each increasing non-certified sourcing area overlap reduces BMP rates by 0.15%, while the same rate goes up by 0.08% overall with each increasing certified sourcing overlap. Moreover, the results of the spatial analyses indicate that neighbors' certified overlaps have a negative effect on average forestry BMP rates associated with a sourcing mill, even though the overall effect is positive. An increase in own harvesting area and mill size reduces BMP rates by 0.056%, but an increase for neighboring sourcing mills increases them by 0.063%, showing an overall positive effect of these two variables. These findings reflect the supply chain inefficiency brought on by concurrent contracting behavior between small mills and their larger certified neighbors. BMP rates are higher in the mill sourcing area by 0.023%, with each increase in the presence of perennial streams, further indicating that loggers are adequately following BMPs in areas that have perennial streams. Our overall results show that spatial dependence is an essential mechanism for ascertaining the effectiveness of SFI-FS standard at large spatial scales.

Supervisory control of business processes with resources, parallel and mutually exclusive branches, loops, and uncertainty

A recent direction in Business Process Management studied methodologies to control the execution of Business Processes under several sources of uncertainty in order to always get to the end by satisfying all constraints. Current approaches encode business processes into temporal constraint networks or timed game automata in order to exploit their related strategy synthesis algorithms. However, the proposed encodings can only synthesize single-strategies and fail to handle loops. To overcome these limits we propose an approach based on supervisory control. We consider structured business processes with resources, parallel and mutually exclusive branches, loops, and uncertainty. We provide an encoding into finite state automata and prove that their concurrent behavior models exactly all possible executions of the process. After that, we introduce tentative commitment constraints as a new class of constraints restricting the executions of a process. We define a tree decomposition of the process that plays a central role in modular supervisory control, and we prove that this modular approach is equivalent to the monolithic one. We provide an algorithm to compute the finest tree decomposition to reduce the computational effort of synthesizing supervisors.

Modeling and analysis of switching max-plus linear systems with discrete-event feedback

AbstractSwitching max-plus linear system (SMPLS) models are an apt formalism for performance analysis of discrete-event systems. SMPLS analysis is more scalable than analysis through other formalisms such as timed automata, because SMPLS abstract pieces of determinate concurrent system behavior into atomic modes with fixed timing. We consider discrete-event systems that are decomposed into a plant and a Supervisory Controller (SC) that controls the plant. The SC needs to react to events, concerning e.g. the successful completion or failure of an action, to determine the future behavior of the system, for example, to initiate a retrial of the action. To specify and analyze such system behavior and the impact of feedback on timing properties, we introduce an extension to SMPLS with discrete-event feedback. In this extension, we model the plant behavior with system modes and capture the timing of discrete-event feedback emission from plant to SC in the mode matrices. Furthermore, we use I/O automata to capture how the SC responds to discrete-event feedback with corresponding mode sequences of the SMPLS. We define the semantics of SMPLS with events using new state-space equations that are akin to classical SMPLS with dynamic state-vector sizes. To analyze the extended models, we formulate a transformation from SMPLS with events to classical SMPLS with equivalent semantics and properties such that performance properties can be analyzed using existing techniques. Our approach enables the specification of discrete-event feedback from the plant to the SC and its performance analysis. We demonstrate our approach by specifying and analyzing the makespan of a flexible manufacturing system.

Conjugated two-dimensional covalent organic frameworks as the high-performance anode for lithium-ion batteries: Mechanism and prediction

It is significant in developing high-performance carbonaceous materials (CMs) for lithium-ion batteries (LIBs). The conjugated covalent organic frameworks (CCOFs), one subset of CMs, have spurred great research interest and possess great potential in the realm of negative electrode applications for LIBs. Many CMs and CCOFs are reported with highly anodic capacities outstripping that of graphite, and the underlying mechanism warrants further investigation. Herein, the mechanism of such high capacities is studied on an experimentally synthesized conjugated covalent organic framework (CCOF) by combing the first-principles calculation and electrochemical analysis. By probing the spatial and electronic interactions in the model CCOF during the lithiation process, the mechanism for the dense lithium arraying and concurrent lithiation behavior in CCOFs is revealed. And the microscopic origin of some electrochemical phenomena of CCOFs, such as the high capacity, lacking charging/discharging plateaus, etc., are vividly comprehended. In addition, four analogous CCOFs are designed, and their electrochemical performances are briefly studied to verify the universality of the summarized mechanism. The critical factors of developing high-performance anodic CCOFs are predicted.