A series of blue and blue‑green Ir(Ⅲ)complexes has been investigated theoretically to explore their electronic structures,photophysical properties,efficiency roll‑off effect,and thermal activation delayed fluorescenc...A series of blue and blue‑green Ir(Ⅲ)complexes has been investigated theoretically to explore their electronic structures,photophysical properties,efficiency roll‑off effect,and thermal activation delayed fluorescence(TADF)properties.All calculations were performed using density functional theory(DFT)and time‑dependent density functional theory(TDDFT).Calculations for electronic structures,frontier molecular orbital characteristics(which determine the efficiency roll‑off effect of the complexes),and photophysical properties were conducted using the Gaussian 09 software package.The calculation of spin‑orbit coupling matrix elements<T|HSOC|S>,which determine the TADF properties of the complexes,was performed using the ORCA software package.The calculation results show that the auxiliary ligand tetraphenylimidodiphosphinate(tpip),a strong electron‑withdrawing group,can mitigate the efficiency roll‑off effect of the complex.Furthermore,TADF is observed in one of the designed complexes,(F_(3)Phppy)_(2)Ir(tpip),where F_(3)Phppy=2‑[4‑(2,4,6‑trifluorophenyl)phenyl]pyridine.展开更多
Background:This study aims to investigate the underlying mechanisms between parental marital conflict and adolescent short video dependence by constructing a chain mediation model,focusing on the mediating roles of ex...Background:This study aims to investigate the underlying mechanisms between parental marital conflict and adolescent short video dependence by constructing a chain mediation model,focusing on the mediating roles of experiential avoidance and emotional disturbance(anxiety,depression,and stress).Methods:Conducted in January 2025,the research recruited 4125 adolescents from multiple Chinese provinces through convenience sampling;after data cleaning,3957 valid participants(1959 males,1998 females)were included.Using a cross-sectional design,measures included parental marital conflict,experiential avoidance,anxiety,depression,stress,and short video dependence.Results:Pearson correlation analysis revealed significant positive correlations among all variables.Mediation analysis using the SPSS PROCESS macro showed that parental marital conflict directly predicted short video dependence(β=0.269,p<0.001),and also significantly predicted experiential avoidance(β=0.519,p<0.001),anxiety(β=0.072,p<0.001),depression(β=0.067,p<0.001),and stress(β=0.048,p<0.05).Experiential avoidance further predicted anxiety(β=0.521,p<0.001),depression(β=0.489,p<0.001),stress(β=0.408,p<0.001),and short video dependence(β=0.244,p<0.001).While both anxiety(β=0.050,p<0.05)and depression(β=0.116,p<0.001)positively predicted short video dependence,stress did not(β=0.019,p=0.257).Overall,experiential avoidance,anxiety,depression,and stress significantly mediated the relationship between parental marital conflict and short video dependence.Conclusion:These findings confirm that parental marital conflict not only directly influences adolescent short video dependence but also operates through a chain mediation pathway involving experiential avoidance and emotional disturbance,highlighting central psychological mechanisms and providing theoretical support for integrated mental health and behavioral interventions.展开更多
Conglomerate rock's complex and heterogeneous microstructure significantly affects its mechanical properties,especially under dynamic loading.However,research on their dynamic behavior and fracture mechanisms is l...Conglomerate rock's complex and heterogeneous microstructure significantly affects its mechanical properties,especially under dynamic loading.However,research on their dynamic behavior and fracture mechanisms is limited.Through uniaxial compression tests and split Hopkinson pressure bar(SHPB)impact tests,the dynamic compressive mechanical properties and fracture mechanisms of conglomerate rock were studied.Nanoindentation and high-resolution X-ray computed tomography were employed to analyze the micro-mechanical behavior and internal structure of the conglomerate rock.Results indicate significant differences in mechanical properties between different gravel particles and cementing materials,with initial fractures primarily distributed at the gravel-cement interfaces.The dynamic mechanical properties of conglomerate rocks exhibit a clear strain rate dependency.Based on the stress−strain curves and failure characteristics,the dynamic compressive mechanical behavior can be categorized into two types using a critical strain rate.The dynamic compressive strength,peak strain,and toughness of conglomerate rock increased with the strain rate,with the strength at 54 s−1 being 2.6 times that at 6 s−1.The dynamic compressive fracture mechanism of conglomerate rock is related to the strain rate and microstructure;at low strain rates,gravel distribution is the key factor,whereas at high strain rates,gravel content becomes critical.展开更多
Objective:The aging population is growing rapidly,leading to a rise in chronic diseases and placing significant physical,emotional,and financial strain on caregivers.Managing chronic conditions alongside caregiving re...Objective:The aging population is growing rapidly,leading to a rise in chronic diseases and placing significant physical,emotional,and financial strain on caregivers.Managing chronic conditions alongside caregiving responsibilities often results in burnout,adding to the burden on caregivers.This issue also affects society and healthcare systems through increased costs and greater demands for support services.Understanding the factors contributing to caregiver burden is crucial for creating effective interventions to address these challenges.The aim of this study is to describe the extent of caregiver burden and identify some factors related to burden among caregivers of chronically ill elderly people.By gaining insight into these relationships,this study seeks to identify strategies to reduce the burden on caregivers.Methods:This study utilized a cross-sectional design to examine caregivers of the elderly with chronic diseases receiving treatment in the public healthcare facility.Data collection involved administering structured questionnaires that gathered information on the demographic characteristics of both the elderly and their caregivers,the level of social support received,the functional status of patients as measured by daily activity indices,and the level of caregiver burden.Description was used to elaborate the characteristics of participants.Mann-Whitney,Kruskal-Wallis,and Spearman's correlation test were applied to explore the relationship between variables.Statistical significance was determined at P value<0.05.Results:Caregivers of the elderly with chronic diseases had a moderate care burden score(22.62±11.24,CI:95%).The patients'level of dependence,relationship with the patients,and time spent as a caregiver were factors related to caregiver burden(P<0.05).Conclusions:Those who care for elderly people with chronic diseases suffered great burden.The finding had found a number of factors that influence the caregivers'weight loss.Healthcare providers should consider these relevant factors when developing intervention plans to reduce caregiver burden.展开更多
Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usu...Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usually involves complex procedures and extremely depends on unidirectional freezing technique.Herein,we propose a groundbreaking approach that leverages the assemblies of salting-out protein induced by ammonium metatungstate(AM)as the precursor,and then acquire directional three-dimensional carbon-based foams through simple pyrolysis.The electrostatic interaction between AM and protein ensures well dispersion of WC_(1−x)nanoparticles on carbon frameworks.The content of WC_(1−x)nanoparticles can be rationally regulated by AM dosage,and it also affects the electromagnetic(EM)properties of final carbon-based foams.The optimized foam exhibits exceptional EM absorption performance,achieving a remarkable minimum reflection loss of−72.0 dB and an effective absorption bandwidth of 6.3 GHz when EM wave propagates parallel to the directional pores.Such performance benefits from the synergistic effects of macroporous architecture and compositional design.Although there is a directional dependence of EM absorption,radar stealth simulation demonstrates that these foams can still promise considerable reduction in radar cross section with the change of incident angle.Moreover,COMSOL simulation further identifies their good performance in preventing EM interference among different electronic components.展开更多
Distributions of nuclear magnetic resonance(NMR)relaxation times provide detailed information about the water in wood.This study documents the water dynamics analysis of T_(2)and T_(1)distributions for saturated delig...Distributions of nuclear magnetic resonance(NMR)relaxation times provide detailed information about the water in wood.This study documents the water dynamics analysis of T_(2)and T_(1)distributions for saturated delignified sapwood(DSW),delignified heartwood(DHW)and lignocellulose(LC)samples at different temperatures.Results indicate that below the freezing point of bulk water,free water freezes,causing its signal to disappear from the distribution.Then,the low temperature distributions of the unfrozen bound water contain more information about its components,with DSW,DHW and LC containing two distinct states of bound water(OH bound water(B-water)and more freely bound water(C-water)).Furthermore,it was observed that within the temperature range of−3°C to−60°C,B-water in DSW,DHW and LC maintained a higher unfrozen water content(UWC)value than C-water,and the T_(1)/T_(2)ratios for B-water were consistently higher than that for C-water,indicating that B-water has a greater antifreeze capacity.T_(2)and T_(1)distributions offer different kinds of information about water components,and all peaks within the distribution have been assigned.展开更多
The coexistence of emerging containments,such as antibiotic resistant bacteria(ARB),antibiotic-resistant genes(ARGs)and antibiotics,potentially influence elimination efficiencies in UV light-emitting diode(UV-LED)alon...The coexistence of emerging containments,such as antibiotic resistant bacteria(ARB),antibiotic-resistant genes(ARGs)and antibiotics,potentially influence elimination efficiencies in UV light-emitting diode(UV-LED)alone and UV-LED/H_(2)O_(2) system as their complex interactions.Tetracycline(TC)degradation efficiency(kF)correlated closely with its UV molar absorbance(R^(2)=0.831)in UV-LED alone system and with·OH yield(R^(2)=0.999)in UV-LED/H_(2)O_(2) system across studied wavelengths(265,280 and 310 nm).The kF values for intracellular DNA(i-ARGs)also exhibited a high correlation with UV-LED wavelengths in both systems(R^(2)=0.997-0.999).The coexistence of TC and ARB/ARGs resulted in a mutual inhibition of their degradation efficiencies due to competition for photons and·OH,along with the consequent reduction in intracellular ROS within ARB,with their degradation efficiencies exhibiting marked dependence on wavelength in both systems.Notably,the UV-LED/H_(2)O_(2) system at 265 nm effectively achieved the simultaneous removal of TC,ARB and ARGs with minimal energy consumption,and successfully fragmented ARGs.The degradation pathway of TC was analyzed,and the biotoxicity of its degradation intermediates demonstrated the environmental friendliness and safety of UV-LED/H_(2)O_(2) technology.This study elucidated the competitive interactions between antibiotics and ARB/ARGs within UV-LED/H_(2)O_(2) system,providing a promising approach for their simultaneous removal while ensuring energy efficiency.展开更多
When performing English-to-Tamil Neural Machine Translation(NMT),end users face several challenges due to Tamil's rich morphology,free word order,and limited annotated corpora.Although available transformer-based ...When performing English-to-Tamil Neural Machine Translation(NMT),end users face several challenges due to Tamil's rich morphology,free word order,and limited annotated corpora.Although available transformer-based models offer strong baselines,they compromise syntactic awareness and the detection and man-agement of offensive content in cluttered,noisy,and informal text.In this paper,we present POSDEP-Offense-Trans,a multi-task NMT framework that combines Part-of-Speech(POS)and Dependency Parsing(DEP)methods with a robust offensive language classification module.Our architecture enriches the Transformer encoder with syntax-aware embeddings and provides syntax-guided attention mechanisms.The architecture incorporates a structure-aware contrastive loss that reinforces syntactic consistency and deploys auxiliary classification heads for POS tagging,dependency parsing,and multi-class offensive detection.The classifier for offensive words operates at both sentence and token levels and obtains guidance from syntactic features and formal finite automata rules that model offensive language structures-hate speech,profanity,sarcasm,and threats.Using this architecture,we construct a syntactically enriched,socially annotated corpus.Experimental results show improvements in translation quality,with a BLEU score of 33.5,UAS/LAS parsing accuracies of 92.4%and 90%,and a 4.5%Fl-score gain in offensive content detection compared with baseline POS+DEP+Offense models.Also,the proposed model achieved 92.3%in offensive content neutralization,as confirmed by ablation studies.This comprehensive English-Tamil NMT model that unifies syntactic modelling and ethical filtering-laying the groundwork for applications in social media moderation,hate speech mitigation,and policy-compliant multilingual content generation.展开更多
Early and accurate detection of bone cancer and marrow cell abnormalities is critical for timely intervention and improved patient outcomes.This paper proposes a novel hybrid deep learning framework that integrates a ...Early and accurate detection of bone cancer and marrow cell abnormalities is critical for timely intervention and improved patient outcomes.This paper proposes a novel hybrid deep learning framework that integrates a Convolutional Neural Network(CNN)with a Bidirectional Long Short-Term Memory(BiLSTM)architecture,optimized using the Firefly Optimization algorithm(FO).The proposed CNN-BiLSTM-FO model is tailored for structured biomedical data,capturing both local patterns and sequential dependencies in diagnostic features,while the Firefly Algorithm fine-tunes key hyperparameters to maximize predictive performance.The approach is evaluated on two benchmark biomedical datasets:one comprising diagnostic data for bone cancer detection and another for identifying marrow cell abnormalities.Experimental results demonstrate that the proposed method outperforms standard deep learning models,including CNN,LSTM,BiLSTM,and CNN-LSTM hybrids,significantly.The CNNBiLSTM-FO model achieves an accuracy of 98.55%for bone cancer detection and 96.04%for marrow abnormality classification.The paper also presents a detailed complexity analysis of the proposed algorithm and compares its performance across multiple evaluation metrics such as precision,recall,F1-score,and AUC.The results confirm the effectiveness of the firefly-based optimization strategy in improving classification accuracy and model robustness.This work introduces a scalable and accurate diagnostic solution that holds strong potential for integration into intelligent clinical decision-support systems.展开更多
Antibody dependant enhancement refers that viral infectivity was unexpectedly enhanced at low antibody concentration compared to when antibodies were absent,such as Dengue,Zika and influenza virus.To mathematically de...Antibody dependant enhancement refers that viral infectivity was unexpectedly enhanced at low antibody concentration compared to when antibodies were absent,such as Dengue,Zika and influenza virus.To mathematically describe switch from enhancement to neutralisation with increase of antibody concentration,one hyperbolic tangent variant is used as switching function in existed models.However,switching function with hyperbolic tangent contains four parameters,and does not always increase with antibody concentration.To address this problem,we proposed a monotonically increasing Logistical function variant as switching function,which only contains position parameter and magnitude parameter.Analysing influenza viral titre estimated from 21 focus reduction assay(FRA)datasets from neutralisation group(viral titre lower than negative control on all serial dilutions)and 20 FRA dataset from enhancement group(viral titre higher than negative control on high serial dilution),switching function with Logistic function performs better than existed model independent of both groups and exhibited different behaviour/character;specifically,magnitude parameter estimated from enhancement group is lower,but position parameter estimated from enhancement group is higher.A lower magnitude parameter refers that enhancement group more rapidly switches from enhancement to neutralisation with increase of antibody concentration,and a higher position parameter indicates that enhancement group provides a larger antibody concentration interval corresponding to enhancement.Integrating estimated neutralisation kinetics with viral replication,we demonstrated that antibody-induced bistable influenza kinetics exist independent of both groups.However,comparing with neutralisation group,enhancement group provides higher threshold value of antibody concentration corresponding to influenza infectivity.This explains the observed phenomenon that antibody dependent enhancement enhances susceptibility,severity,and mortality to influenza infection.On population level,antibody dependant enhancement can promote H1N1 and H3N2 influenza virus cooperate to sustain long-term circulation on human populations according to antigenic seniority theory.展开更多
Backfill is often employed in mining operations for ground support,with its positive impact on ground stability acknowledged in many underground mines.However,existing studies have predominantly focused only on the st...Backfill is often employed in mining operations for ground support,with its positive impact on ground stability acknowledged in many underground mines.However,existing studies have predominantly focused only on the stress development within the backfill material,leaving the influence of stope backfilling on stress distribution in surrounding rock mass and ground stability largely unexplored.Therefore,this paper presents numerical models in FLAC3D to investigate,for the first time,the time-dependent stress redistribution around a vertical backfilled stope and its implications on ground stability,considering the creep of surrounding rock mass.Using the Soft Soil constitutive model,the compressibility of backfill under large pressure was captured.It is found that the creep deformation of rock mass exercises compression on backfill and results in a less void ratio and increased modulus for fill material.The compacted backfill conversely influenced the stress distribution and ground stability of rock mass which was a combined effect of wall creep and compressibility of backfill.With the increase of time or/and creep deformation,the minimum principal stress in the rocks surrounding the backfilled stope increased towards the pre-mining stress state,while the deviatoric stress reduces leading to an increased factor of safety and improved ground stability.This improvement effect of backfill on ground stability increased with the increase of mine depth and stope height,while it is also more pronounced for the narrow stope,the backfill with a smaller compression index,and the soft rocks with a smaller viscosity coefficient.Furthermore,the results emphasize the importance of minimizing empty time and backfilling extracted stope as soon as possible for ground control.Reduction of filling gap height enhances the local stability around the roof of stope.展开更多
Existing Chinese named entity recognition(NER)research utilises 1D lexicon-based sequence labelling frameworks,which can only recognise flat entities.While lexicons serve as prior knowledge and enhance semantic inform...Existing Chinese named entity recognition(NER)research utilises 1D lexicon-based sequence labelling frameworks,which can only recognise flat entities.While lexicons serve as prior knowledge and enhance semantic information,they also pose completeness and resource requirements limitations.This paper proposes a template-based classification(TC)model to avoid lexicon issues and to identify nested entities.Template-based classification provides a template word for each entity type,which utilises contrastive learning to integrate the common characteristics among entities with the same category.Contrastive learning makes template words the centre points of their category in the vector space,thus improving generalisation ability.Additionally,TC presents a 2D tablefilling label scheme that classifies entities based on the attention distribution of template words.The proposed novel decoder algorithm enables TC recognition of both flat and nested entities simultaneously.Experimental results show that TC achieves the state-ofthe-art performance on five Chinese datasets.展开更多
Repetitive transcranial magnetic stimulation(rTMS)is a rapid and effective therapy for major depressive disorder;however,there is significant variability in therapeutic outcomes both within and across individuals,with...Repetitive transcranial magnetic stimulation(rTMS)is a rapid and effective therapy for major depressive disorder;however,there is significant variability in therapeutic outcomes both within and across individuals,with approximately 50% of patients showing no response to rTMS treatment.Many studies have personalized the stimulation parameters of rTMS(e.g.,location and intensity of stimulation)according to the anatomical and functional structure of the brain.In addition to these parameters,the internal states of the individual,such as circadian rhythm,behavior/cognition,neural oscillation,and neuroplasticity,also contribute to the variation in rTMS effects.In this review,we summarize the current literature on the interaction between rTMS and internal states.We propose two possible methods,multimodal treatment,and adaptive closed-loop treatment,to integrate patients'internal states to achieve better rTMS treatment for depression.展开更多
Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accu...Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.展开更多
Distributed Federated Learning(DFL)technology enables participants to cooperatively train a shared model while preserving the privacy of their local datasets,making it a desirable solution for decentralized and privac...Distributed Federated Learning(DFL)technology enables participants to cooperatively train a shared model while preserving the privacy of their local datasets,making it a desirable solution for decentralized and privacy-preserving Web3 scenarios.However,DFL faces incentive and security challenges in the decentralized framework.To address these issues,this paper presents a Hierarchical Blockchain-enabled DFL(HBDFL)system,which provides a generic solution framework for the DFL-related applications.The proposed system consists of four major components,including a model contribution-based reward mechanism,a Proof of Elapsed Time and Accuracy(PoETA)consensus algorithm,a Distributed Reputation-based Verification Mechanism(DRTM)and an Accuracy-Dependent Throughput Management(ADTM)mechanism.The model contribution-based rewarding mechanism incentivizes network nodes to train models with their local datasets,while the PoETA consensus algorithm optimizes the tradeoff between the shared model accuracy and system throughput.The DRTM improves the system efficiency in consensus,and the ADTM mechanism guarantees that the throughput performance remains within a predefined range while improving the shared model accuracy.The performance of the proposed HBDFL system is evaluated by numerical simulations,with the results showing that the system improves the accuracy of the shared model while maintaining high throughput and ensuring security.展开更多
Radio Frequency Fingerprint Identification(RFFI)technology provides a means of identifying spurious signals.This technology has been widely used in solving Automatic Dependent Surveillance–Broadcast(ADS-B)signal spoo...Radio Frequency Fingerprint Identification(RFFI)technology provides a means of identifying spurious signals.This technology has been widely used in solving Automatic Dependent Surveillance–Broadcast(ADS-B)signal spoofing problems.However,the effects of circuit changes over time often lead to a decline in identification accuracy within open-time set.This paper proposes an ADS-B transmitter identification method to solve the degradation of identification accuracy.First,a real-time data processing system is established to receive and store ADS-B signals to meet the conditions for open-time set.The system possesses the following functionalities:data collection,data parsing,feature extraction,and identity recognition.Subsequently,a two-dimensional TimeFrequency Feature Diagram(TFFD)is proposed as a signal pre-processing method.The TFFD is constructed from the received ADS-B signal and the reconstructed signal for input to the recognition model.Finally,incorporating a frequency offset layer into the Swin Transformer architecture,a novel recognition network framework is proposed.This integration can enhance the network recognition accuracy and robustness by tailoring to the specific characteristics of ADSB signals.Experimental results indicate that the proposed recognition architecture achieves recognition accuracy of 95.86%in closed-time set and 84.33%in open-time set,surpassing other algorithms.展开更多
Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)informati...Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)information.This paper proposes a security position verification technique based on Multilateration(MLAT)to detect false signals,ensuring UAV safety and reliable airspace operations.First,the proposed method estimates the current position of the UAV by calculating the Time Difference of Arrival(TDOA),Time Sum of Arrival(TSOA),and Angle of Arrival(AOA)information.Then,this estimated position is compared with the ADS-B message to eliminate false UAV signals.Furthermore,a localization model based on TDOA/TSOA/AOA is established by utilizing reliable reference sources for base station time synchronization.Additionally,an improved Chan-Taylor algorithm is developed,incorporating the Constrained Weighted Least Squares(CWLS)method to initialize UAV position calculations.Finally,a false signal detection method is proposed to distinguish between true and false positioning targets.Numerical simulation results indicate that,at a positioning error threshold of 150 m,the improved Chan-Taylor algorithm based on TDOA/TSOA/AOA achieves 100%accuracy coverage,significantly enhancing localization precision.And the proposed false signal detection method achieves a detection accuracy rate of at least 90%within a 50-meter error range.展开更多
Dear Editor,This letter addresses the formation control problem for constrained underactuated autonomous underwater vehicles (AUVs). The feasibility condition of the virtual control law is eliminated by introducing a ...Dear Editor,This letter addresses the formation control problem for constrained underactuated autonomous underwater vehicles (AUVs). The feasibility condition of the virtual control law is eliminated by introducing a nonlinear state dependence function (NSDF) that transforms the state of each AUV in the formation.展开更多
This paper purports to expound a special(technical)notion of paths.A neglected fundamental fact(especially under indeterminism)is that the path-dependent direction of any diachronic outcome is backward,i.e.,later step...This paper purports to expound a special(technical)notion of paths.A neglected fundamental fact(especially under indeterminism)is that the path-dependent direction of any diachronic outcome is backward,i.e.,later steps depend on earlier ones successively,despite the ineradicable chance in their respective formation.In this paper,a token-oriented retrospective approach is proposed to overcome the limitation of the type-oriented approach in explaining path-related phenomena.My argument for the validity and utility of this approach is largely based on the elements of(PD),a definitional schema for diachronic sequences subject to a recursive counterfactual formula.I explore certain aspects of path individuation that have so far not been discussed,despite(PD)’s formal congeniality with Lewis’s‘causal chain’.Two basic patterns of path generation are examined:the first is for distinguishing actual vs possible branching paths,while the second introduces a metaphysical theme regarding the retrospective grounding of the causal status of an upstream event by its downstream(joint)effect.A central example of the paper,viz.,the Gobang game,is used to illustrate how the token-oriented approach works for path individuation.展开更多
文摘A series of blue and blue‑green Ir(Ⅲ)complexes has been investigated theoretically to explore their electronic structures,photophysical properties,efficiency roll‑off effect,and thermal activation delayed fluorescence(TADF)properties.All calculations were performed using density functional theory(DFT)and time‑dependent density functional theory(TDDFT).Calculations for electronic structures,frontier molecular orbital characteristics(which determine the efficiency roll‑off effect of the complexes),and photophysical properties were conducted using the Gaussian 09 software package.The calculation of spin‑orbit coupling matrix elements<T|HSOC|S>,which determine the TADF properties of the complexes,was performed using the ORCA software package.The calculation results show that the auxiliary ligand tetraphenylimidodiphosphinate(tpip),a strong electron‑withdrawing group,can mitigate the efficiency roll‑off effect of the complex.Furthermore,TADF is observed in one of the designed complexes,(F_(3)Phppy)_(2)Ir(tpip),where F_(3)Phppy=2‑[4‑(2,4,6‑trifluorophenyl)phenyl]pyridine.
文摘Background:This study aims to investigate the underlying mechanisms between parental marital conflict and adolescent short video dependence by constructing a chain mediation model,focusing on the mediating roles of experiential avoidance and emotional disturbance(anxiety,depression,and stress).Methods:Conducted in January 2025,the research recruited 4125 adolescents from multiple Chinese provinces through convenience sampling;after data cleaning,3957 valid participants(1959 males,1998 females)were included.Using a cross-sectional design,measures included parental marital conflict,experiential avoidance,anxiety,depression,stress,and short video dependence.Results:Pearson correlation analysis revealed significant positive correlations among all variables.Mediation analysis using the SPSS PROCESS macro showed that parental marital conflict directly predicted short video dependence(β=0.269,p<0.001),and also significantly predicted experiential avoidance(β=0.519,p<0.001),anxiety(β=0.072,p<0.001),depression(β=0.067,p<0.001),and stress(β=0.048,p<0.05).Experiential avoidance further predicted anxiety(β=0.521,p<0.001),depression(β=0.489,p<0.001),stress(β=0.408,p<0.001),and short video dependence(β=0.244,p<0.001).While both anxiety(β=0.050,p<0.05)and depression(β=0.116,p<0.001)positively predicted short video dependence,stress did not(β=0.019,p=0.257).Overall,experiential avoidance,anxiety,depression,and stress significantly mediated the relationship between parental marital conflict and short video dependence.Conclusion:These findings confirm that parental marital conflict not only directly influences adolescent short video dependence but also operates through a chain mediation pathway involving experiential avoidance and emotional disturbance,highlighting central psychological mechanisms and providing theoretical support for integrated mental health and behavioral interventions.
基金Project(51978674)supported by the National Natural Science Foundation of China。
文摘Conglomerate rock's complex and heterogeneous microstructure significantly affects its mechanical properties,especially under dynamic loading.However,research on their dynamic behavior and fracture mechanisms is limited.Through uniaxial compression tests and split Hopkinson pressure bar(SHPB)impact tests,the dynamic compressive mechanical properties and fracture mechanisms of conglomerate rock were studied.Nanoindentation and high-resolution X-ray computed tomography were employed to analyze the micro-mechanical behavior and internal structure of the conglomerate rock.Results indicate significant differences in mechanical properties between different gravel particles and cementing materials,with initial fractures primarily distributed at the gravel-cement interfaces.The dynamic mechanical properties of conglomerate rocks exhibit a clear strain rate dependency.Based on the stress−strain curves and failure characteristics,the dynamic compressive mechanical behavior can be categorized into two types using a critical strain rate.The dynamic compressive strength,peak strain,and toughness of conglomerate rock increased with the strain rate,with the strength at 54 s−1 being 2.6 times that at 6 s−1.The dynamic compressive fracture mechanism of conglomerate rock is related to the strain rate and microstructure;at low strain rates,gravel distribution is the key factor,whereas at high strain rates,gravel content becomes critical.
基金Da Nang University of Medical Technology and PharmacyDa Nang C Hospital for the invaluable support they provided in facilitating this research。
文摘Objective:The aging population is growing rapidly,leading to a rise in chronic diseases and placing significant physical,emotional,and financial strain on caregivers.Managing chronic conditions alongside caregiving responsibilities often results in burnout,adding to the burden on caregivers.This issue also affects society and healthcare systems through increased costs and greater demands for support services.Understanding the factors contributing to caregiver burden is crucial for creating effective interventions to address these challenges.The aim of this study is to describe the extent of caregiver burden and identify some factors related to burden among caregivers of chronically ill elderly people.By gaining insight into these relationships,this study seeks to identify strategies to reduce the burden on caregivers.Methods:This study utilized a cross-sectional design to examine caregivers of the elderly with chronic diseases receiving treatment in the public healthcare facility.Data collection involved administering structured questionnaires that gathered information on the demographic characteristics of both the elderly and their caregivers,the level of social support received,the functional status of patients as measured by daily activity indices,and the level of caregiver burden.Description was used to elaborate the characteristics of participants.Mann-Whitney,Kruskal-Wallis,and Spearman's correlation test were applied to explore the relationship between variables.Statistical significance was determined at P value<0.05.Results:Caregivers of the elderly with chronic diseases had a moderate care burden score(22.62±11.24,CI:95%).The patients'level of dependence,relationship with the patients,and time spent as a caregiver were factors related to caregiver burden(P<0.05).Conclusions:Those who care for elderly people with chronic diseases suffered great burden.The finding had found a number of factors that influence the caregivers'weight loss.Healthcare providers should consider these relevant factors when developing intervention plans to reduce caregiver burden.
基金financially supported by the National Natural Science Foundation of China(Nos.22475057 and No.52373262).
文摘Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usually involves complex procedures and extremely depends on unidirectional freezing technique.Herein,we propose a groundbreaking approach that leverages the assemblies of salting-out protein induced by ammonium metatungstate(AM)as the precursor,and then acquire directional three-dimensional carbon-based foams through simple pyrolysis.The electrostatic interaction between AM and protein ensures well dispersion of WC_(1−x)nanoparticles on carbon frameworks.The content of WC_(1−x)nanoparticles can be rationally regulated by AM dosage,and it also affects the electromagnetic(EM)properties of final carbon-based foams.The optimized foam exhibits exceptional EM absorption performance,achieving a remarkable minimum reflection loss of−72.0 dB and an effective absorption bandwidth of 6.3 GHz when EM wave propagates parallel to the directional pores.Such performance benefits from the synergistic effects of macroporous architecture and compositional design.Although there is a directional dependence of EM absorption,radar stealth simulation demonstrates that these foams can still promise considerable reduction in radar cross section with the change of incident angle.Moreover,COMSOL simulation further identifies their good performance in preventing EM interference among different electronic components.
基金supported by Natural Science Foundation of Inner Mongolia Autonomous Region of China (2023MS03027)the National Natural Science Foundation of China (31860185 and 31160141)
文摘Distributions of nuclear magnetic resonance(NMR)relaxation times provide detailed information about the water in wood.This study documents the water dynamics analysis of T_(2)and T_(1)distributions for saturated delignified sapwood(DSW),delignified heartwood(DHW)and lignocellulose(LC)samples at different temperatures.Results indicate that below the freezing point of bulk water,free water freezes,causing its signal to disappear from the distribution.Then,the low temperature distributions of the unfrozen bound water contain more information about its components,with DSW,DHW and LC containing two distinct states of bound water(OH bound water(B-water)and more freely bound water(C-water)).Furthermore,it was observed that within the temperature range of−3°C to−60°C,B-water in DSW,DHW and LC maintained a higher unfrozen water content(UWC)value than C-water,and the T_(1)/T_(2)ratios for B-water were consistently higher than that for C-water,indicating that B-water has a greater antifreeze capacity.T_(2)and T_(1)distributions offer different kinds of information about water components,and all peaks within the distribution have been assigned.
基金supported by Major Scientific and Technological Innovation Project of Shandong Province(No.2020CXGC011204)Qingdao Natural Science Foundation(No.23-2-1-234-zyyd-jch).
文摘The coexistence of emerging containments,such as antibiotic resistant bacteria(ARB),antibiotic-resistant genes(ARGs)and antibiotics,potentially influence elimination efficiencies in UV light-emitting diode(UV-LED)alone and UV-LED/H_(2)O_(2) system as their complex interactions.Tetracycline(TC)degradation efficiency(kF)correlated closely with its UV molar absorbance(R^(2)=0.831)in UV-LED alone system and with·OH yield(R^(2)=0.999)in UV-LED/H_(2)O_(2) system across studied wavelengths(265,280 and 310 nm).The kF values for intracellular DNA(i-ARGs)also exhibited a high correlation with UV-LED wavelengths in both systems(R^(2)=0.997-0.999).The coexistence of TC and ARB/ARGs resulted in a mutual inhibition of their degradation efficiencies due to competition for photons and·OH,along with the consequent reduction in intracellular ROS within ARB,with their degradation efficiencies exhibiting marked dependence on wavelength in both systems.Notably,the UV-LED/H_(2)O_(2) system at 265 nm effectively achieved the simultaneous removal of TC,ARB and ARGs with minimal energy consumption,and successfully fragmented ARGs.The degradation pathway of TC was analyzed,and the biotoxicity of its degradation intermediates demonstrated the environmental friendliness and safety of UV-LED/H_(2)O_(2) technology.This study elucidated the competitive interactions between antibiotics and ARB/ARGs within UV-LED/H_(2)O_(2) system,providing a promising approach for their simultaneous removal while ensuring energy efficiency.
文摘When performing English-to-Tamil Neural Machine Translation(NMT),end users face several challenges due to Tamil's rich morphology,free word order,and limited annotated corpora.Although available transformer-based models offer strong baselines,they compromise syntactic awareness and the detection and man-agement of offensive content in cluttered,noisy,and informal text.In this paper,we present POSDEP-Offense-Trans,a multi-task NMT framework that combines Part-of-Speech(POS)and Dependency Parsing(DEP)methods with a robust offensive language classification module.Our architecture enriches the Transformer encoder with syntax-aware embeddings and provides syntax-guided attention mechanisms.The architecture incorporates a structure-aware contrastive loss that reinforces syntactic consistency and deploys auxiliary classification heads for POS tagging,dependency parsing,and multi-class offensive detection.The classifier for offensive words operates at both sentence and token levels and obtains guidance from syntactic features and formal finite automata rules that model offensive language structures-hate speech,profanity,sarcasm,and threats.Using this architecture,we construct a syntactically enriched,socially annotated corpus.Experimental results show improvements in translation quality,with a BLEU score of 33.5,UAS/LAS parsing accuracies of 92.4%and 90%,and a 4.5%Fl-score gain in offensive content detection compared with baseline POS+DEP+Offense models.Also,the proposed model achieved 92.3%in offensive content neutralization,as confirmed by ablation studies.This comprehensive English-Tamil NMT model that unifies syntactic modelling and ethical filtering-laying the groundwork for applications in social media moderation,hate speech mitigation,and policy-compliant multilingual content generation.
文摘Early and accurate detection of bone cancer and marrow cell abnormalities is critical for timely intervention and improved patient outcomes.This paper proposes a novel hybrid deep learning framework that integrates a Convolutional Neural Network(CNN)with a Bidirectional Long Short-Term Memory(BiLSTM)architecture,optimized using the Firefly Optimization algorithm(FO).The proposed CNN-BiLSTM-FO model is tailored for structured biomedical data,capturing both local patterns and sequential dependencies in diagnostic features,while the Firefly Algorithm fine-tunes key hyperparameters to maximize predictive performance.The approach is evaluated on two benchmark biomedical datasets:one comprising diagnostic data for bone cancer detection and another for identifying marrow cell abnormalities.Experimental results demonstrate that the proposed method outperforms standard deep learning models,including CNN,LSTM,BiLSTM,and CNN-LSTM hybrids,significantly.The CNNBiLSTM-FO model achieves an accuracy of 98.55%for bone cancer detection and 96.04%for marrow abnormality classification.The paper also presents a detailed complexity analysis of the proposed algorithm and compares its performance across multiple evaluation metrics such as precision,recall,F1-score,and AUC.The results confirm the effectiveness of the firefly-based optimization strategy in improving classification accuracy and model robustness.This work introduces a scalable and accurate diagnostic solution that holds strong potential for integration into intelligent clinical decision-support systems.
文摘Antibody dependant enhancement refers that viral infectivity was unexpectedly enhanced at low antibody concentration compared to when antibodies were absent,such as Dengue,Zika and influenza virus.To mathematically describe switch from enhancement to neutralisation with increase of antibody concentration,one hyperbolic tangent variant is used as switching function in existed models.However,switching function with hyperbolic tangent contains four parameters,and does not always increase with antibody concentration.To address this problem,we proposed a monotonically increasing Logistical function variant as switching function,which only contains position parameter and magnitude parameter.Analysing influenza viral titre estimated from 21 focus reduction assay(FRA)datasets from neutralisation group(viral titre lower than negative control on all serial dilutions)and 20 FRA dataset from enhancement group(viral titre higher than negative control on high serial dilution),switching function with Logistic function performs better than existed model independent of both groups and exhibited different behaviour/character;specifically,magnitude parameter estimated from enhancement group is lower,but position parameter estimated from enhancement group is higher.A lower magnitude parameter refers that enhancement group more rapidly switches from enhancement to neutralisation with increase of antibody concentration,and a higher position parameter indicates that enhancement group provides a larger antibody concentration interval corresponding to enhancement.Integrating estimated neutralisation kinetics with viral replication,we demonstrated that antibody-induced bistable influenza kinetics exist independent of both groups.However,comparing with neutralisation group,enhancement group provides higher threshold value of antibody concentration corresponding to influenza infectivity.This explains the observed phenomenon that antibody dependent enhancement enhances susceptibility,severity,and mortality to influenza infection.On population level,antibody dependant enhancement can promote H1N1 and H3N2 influenza virus cooperate to sustain long-term circulation on human populations according to antigenic seniority theory.
基金the funding support from the National Natural Science Foundation of China(Grant Nos.52304101 and 52004206)the China Postdoctoral Science Foundation(Grant No.2023MD734215)。
文摘Backfill is often employed in mining operations for ground support,with its positive impact on ground stability acknowledged in many underground mines.However,existing studies have predominantly focused only on the stress development within the backfill material,leaving the influence of stope backfilling on stress distribution in surrounding rock mass and ground stability largely unexplored.Therefore,this paper presents numerical models in FLAC3D to investigate,for the first time,the time-dependent stress redistribution around a vertical backfilled stope and its implications on ground stability,considering the creep of surrounding rock mass.Using the Soft Soil constitutive model,the compressibility of backfill under large pressure was captured.It is found that the creep deformation of rock mass exercises compression on backfill and results in a less void ratio and increased modulus for fill material.The compacted backfill conversely influenced the stress distribution and ground stability of rock mass which was a combined effect of wall creep and compressibility of backfill.With the increase of time or/and creep deformation,the minimum principal stress in the rocks surrounding the backfilled stope increased towards the pre-mining stress state,while the deviatoric stress reduces leading to an increased factor of safety and improved ground stability.This improvement effect of backfill on ground stability increased with the increase of mine depth and stope height,while it is also more pronounced for the narrow stope,the backfill with a smaller compression index,and the soft rocks with a smaller viscosity coefficient.Furthermore,the results emphasize the importance of minimizing empty time and backfilling extracted stope as soon as possible for ground control.Reduction of filling gap height enhances the local stability around the roof of stope.
基金Sichuan Provincial Science and Technology Support Program,Grant/Award Number:2023YFG0151National Natural Science Foundation of China,Grant/Award Numbers:U22B2061,U2336204。
文摘Existing Chinese named entity recognition(NER)research utilises 1D lexicon-based sequence labelling frameworks,which can only recognise flat entities.While lexicons serve as prior knowledge and enhance semantic information,they also pose completeness and resource requirements limitations.This paper proposes a template-based classification(TC)model to avoid lexicon issues and to identify nested entities.Template-based classification provides a template word for each entity type,which utilises contrastive learning to integrate the common characteristics among entities with the same category.Contrastive learning makes template words the centre points of their category in the vector space,thus improving generalisation ability.Additionally,TC presents a 2D tablefilling label scheme that classifies entities based on the attention distribution of template words.The proposed novel decoder algorithm enables TC recognition of both flat and nested entities simultaneously.Experimental results show that TC achieves the state-ofthe-art performance on five Chinese datasets.
基金supported by STI2030-Major Projects(2021ZD0204300 and 2021ZD0200800)the National Natural Science Foundation of China(82271528)the Fundamental Research Funds for the Central Universities(Peking University Medicine Fund for World's Leading Discipline or Discipline Cluster Development,BMU2022DJXK007).
文摘Repetitive transcranial magnetic stimulation(rTMS)is a rapid and effective therapy for major depressive disorder;however,there is significant variability in therapeutic outcomes both within and across individuals,with approximately 50% of patients showing no response to rTMS treatment.Many studies have personalized the stimulation parameters of rTMS(e.g.,location and intensity of stimulation)according to the anatomical and functional structure of the brain.In addition to these parameters,the internal states of the individual,such as circadian rhythm,behavior/cognition,neural oscillation,and neuroplasticity,also contribute to the variation in rTMS effects.In this review,we summarize the current literature on the interaction between rTMS and internal states.We propose two possible methods,multimodal treatment,and adaptive closed-loop treatment,to integrate patients'internal states to achieve better rTMS treatment for depression.
基金funded by the Youth Fund of the National Natural Science Foundation of China(Grant No.42261070).
文摘Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.
文摘Distributed Federated Learning(DFL)technology enables participants to cooperatively train a shared model while preserving the privacy of their local datasets,making it a desirable solution for decentralized and privacy-preserving Web3 scenarios.However,DFL faces incentive and security challenges in the decentralized framework.To address these issues,this paper presents a Hierarchical Blockchain-enabled DFL(HBDFL)system,which provides a generic solution framework for the DFL-related applications.The proposed system consists of four major components,including a model contribution-based reward mechanism,a Proof of Elapsed Time and Accuracy(PoETA)consensus algorithm,a Distributed Reputation-based Verification Mechanism(DRTM)and an Accuracy-Dependent Throughput Management(ADTM)mechanism.The model contribution-based rewarding mechanism incentivizes network nodes to train models with their local datasets,while the PoETA consensus algorithm optimizes the tradeoff between the shared model accuracy and system throughput.The DRTM improves the system efficiency in consensus,and the ADTM mechanism guarantees that the throughput performance remains within a predefined range while improving the shared model accuracy.The performance of the proposed HBDFL system is evaluated by numerical simulations,with the results showing that the system improves the accuracy of the shared model while maintaining high throughput and ensuring security.
基金supported by the National Key Research and Development Program of China(No.2022YFB4300902)。
文摘Radio Frequency Fingerprint Identification(RFFI)technology provides a means of identifying spurious signals.This technology has been widely used in solving Automatic Dependent Surveillance–Broadcast(ADS-B)signal spoofing problems.However,the effects of circuit changes over time often lead to a decline in identification accuracy within open-time set.This paper proposes an ADS-B transmitter identification method to solve the degradation of identification accuracy.First,a real-time data processing system is established to receive and store ADS-B signals to meet the conditions for open-time set.The system possesses the following functionalities:data collection,data parsing,feature extraction,and identity recognition.Subsequently,a two-dimensional TimeFrequency Feature Diagram(TFFD)is proposed as a signal pre-processing method.The TFFD is constructed from the received ADS-B signal and the reconstructed signal for input to the recognition model.Finally,incorporating a frequency offset layer into the Swin Transformer architecture,a novel recognition network framework is proposed.This integration can enhance the network recognition accuracy and robustness by tailoring to the specific characteristics of ADSB signals.Experimental results indicate that the proposed recognition architecture achieves recognition accuracy of 95.86%in closed-time set and 84.33%in open-time set,surpassing other algorithms.
基金supported by the National Natural Science Foundation of China(Nos.U2441250,62301380,and 62231027)Natural Science Basic Research Program of Shaanxi,China(2024JC-JCQN-63)+3 种基金the Key Research and Development Program of Shaanxi,China(No.2023-YBGY-249)the Guangxi Key Research and Development Program,China(No.2022AB46002)the China Postdoctoral Science Foundation(No.2022M722504 and 2024T170696)the Innovation Capability Support Program of Shaanxi,China(No.2024RS-CXTD-01).
文摘Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)information.This paper proposes a security position verification technique based on Multilateration(MLAT)to detect false signals,ensuring UAV safety and reliable airspace operations.First,the proposed method estimates the current position of the UAV by calculating the Time Difference of Arrival(TDOA),Time Sum of Arrival(TSOA),and Angle of Arrival(AOA)information.Then,this estimated position is compared with the ADS-B message to eliminate false UAV signals.Furthermore,a localization model based on TDOA/TSOA/AOA is established by utilizing reliable reference sources for base station time synchronization.Additionally,an improved Chan-Taylor algorithm is developed,incorporating the Constrained Weighted Least Squares(CWLS)method to initialize UAV position calculations.Finally,a false signal detection method is proposed to distinguish between true and false positioning targets.Numerical simulation results indicate that,at a positioning error threshold of 150 m,the improved Chan-Taylor algorithm based on TDOA/TSOA/AOA achieves 100%accuracy coverage,significantly enhancing localization precision.And the proposed false signal detection method achieves a detection accuracy rate of at least 90%within a 50-meter error range.
基金supported by the National Natural Science Foundation of China(62073094)the Fundamental Research Funds for the Central Universities(3072024GH0404)
文摘Dear Editor,This letter addresses the formation control problem for constrained underactuated autonomous underwater vehicles (AUVs). The feasibility condition of the virtual control law is eliminated by introducing a nonlinear state dependence function (NSDF) that transforms the state of each AUV in the formation.
文摘This paper purports to expound a special(technical)notion of paths.A neglected fundamental fact(especially under indeterminism)is that the path-dependent direction of any diachronic outcome is backward,i.e.,later steps depend on earlier ones successively,despite the ineradicable chance in their respective formation.In this paper,a token-oriented retrospective approach is proposed to overcome the limitation of the type-oriented approach in explaining path-related phenomena.My argument for the validity and utility of this approach is largely based on the elements of(PD),a definitional schema for diachronic sequences subject to a recursive counterfactual formula.I explore certain aspects of path individuation that have so far not been discussed,despite(PD)’s formal congeniality with Lewis’s‘causal chain’.Two basic patterns of path generation are examined:the first is for distinguishing actual vs possible branching paths,while the second introduces a metaphysical theme regarding the retrospective grounding of the causal status of an upstream event by its downstream(joint)effect.A central example of the paper,viz.,the Gobang game,is used to illustrate how the token-oriented approach works for path individuation.
