Subsequent Path Research Articles

The gender gap in STEM: (Female) teenagers' ICT skills and subsequent career paths.

Skills shortage in the fields of Sciences, Technology, Engineering, and Mathematics (STEM) poses a significant challenge for industries globally. To overcome shortage of STEM talent, the selection into STEM fields must be fully understood. We contribute to existing research on the selection of STEM careers by analysing the interplay between teenagers' proficiency in Information and Communication Technology (ICT) and their career preferences in the STEM domain. Based on representative data for German teenagers, our study shows that female teenagers are less likely to choose a career in STEM unless they have strong ICT skills in secondary school. The relationship does not hold for male students. An increase in girls' ICT skills by 10 percentage points in ninth grade is associated with an increase in the probability to choose a STEM career by 2.95 percentage points. Our findings can be explained with evidence that teenagers sort into occupations they believe to be good at and that female teenagers rather underestimate their true potential. Using different empirical approaches, we also show that ICT skills act as a moderator and not as a mediator in the gender-specific choice of training upon graduating from secondary school. By addressing the interplay between gender, ICT skills, and educational choices, the present study uncovers an additional lever of how to mitigate skills shortage in STEM.

Multi-AGV multitask collaborative scheduling based on an improved ant colony algorithm

Research on multitask scheduling systems in factory environments is a popular topic in the field of intelligent manufacturing. Existing research mainly focuses on the optimization of automated guided vehicle (AGV) path planning and scheduling, emphasizing on the minimization of conflicts and deadlocks, multi-objective task scheduling, and metaheuristic algorithm optimization, while ignoring path stability and real-time path planning in dynamic environments. Therefore, this paper aims to address these issues to better handle dynamic changes in actual operating environments. This paper establishes a mathematical model with the optimization objective of minimizing the overall running time of material distribution tasks and proposes an improved ant colony algorithm to optimize the model. First, the concept of prior time is introduced to improve the traditional ant colony algorithm. The path of the ongoing task is introduced with a time calculation, and the occupancy time window of each grid point on the path is calculated. Based on this, the initial pheromone distribution on subsequent paths is altered dynamically, which accelerates the convergence of the ants to a collision-free path. Second, in the pheromone update stage, the method of calculating the pheromone increment in the traditional ant colony algorithm is modified. The original distance influence factor is changed to a time influence factor, which ensures that all tasks still have the minimum running time when calculating a collision-free path. Finally, through 30 sets of simulation experiments on material distribution tasks, it is shown that the proposed algorithm shortens the total running time by 15.14%, 12.87%, and 10.59% compared to two ant colony algorithms and one strategic multi-AGV scheduling algorithm, respectively, thus verifying the effectiveness of the proposed method.

Cross-level interaction mechanism for high growth among digital start–ups: an fsQCA analysis

Purpose In the field of digital entrepreneurship, achieving high growth in digital start-ups is crucial. This paper aims to explore how causal conditions at the individual, organizational and environmental levels interact in the growth process of digital start-ups. Furthermore, it uses a configurational approach to conduct a holistic analysis of the cross-level interaction mechanisms that enable digital start-ups to achieve high growth. Design/methodology/approach Based on a holistic perspective, the data collection included 57 representative cases of digital start-ups in China in the past decade (2014–2023). A fuzzy set qualitative comparative analysis was conducted to explore the cross-level interaction mechanism of the three-dimensional causal conditions of the environment, organization and individual entrepreneurs on high growth among digital start-ups. Findings This study found three models for digital start-ups to achieve high growth. These models − the resource network orchestration model, the innovation resource development model and the entrepreneurial spirit coherence model, respectively, reflect the multiple paths of high growth achieved by various digital start-ups based on their entrepreneurial environment, organizational capability and the personality of the founder. This reflects that digital start-ups face different conditions and entrepreneurial situations, with differing cross-level interaction mechanisms for achieving high growth. Practical implications First, digital start-ups should focus on strengthening their digital resource integration capabilities to lay the foundation for their subsequent high-growth path selection. Second, entrepreneurs need to adopt a holistic perspective to change or strengthen the causal conditions required to achieve high growth. Third, emphasis should be placed on the coherence between the entrepreneur’s need for achievement and the internal entrepreneurial culture. Originality/value First, this study contributes to the literature on high growth among digital start-ups by introducing a cross-level interaction mechanism comprising environmental, organizational and entrepreneurial causal conditions. Second, it reveals that individual factors at the environmental, organizational and entrepreneurial levels are not necessary conditions for high entrepreneurial growth and that digital resource integration capabilities play a more universal role in achieving high digital start-up growth. Finally, the study provides a cross-level holistic explanation of how digital start-ups can achieve high growth and reveals various configuration models conducive to high growth, thus offering practical insights for businesses.

The Relationship Between L2 Motivation and Epistemic Emotions of Boredom and Curiosity: A Study Among Adolescent Learners of English.

Motivational drivers and emotions that students experience play an important role in the process of learning a new language (L2). This has been recognised by researchers and educators, and extensive research has been conducted in recent decades to examine the psychological and emotional factors involved in L2 learning. However, two ubiquitous epistemic emotions, namely, boredom and curiosity, remain underexplored in the L2 research literature. This study addresses this gap. It performed a series of statistical tests to examine the relationship between these two epistemic emotions and L2 motivation. Specifically, it assessed whether epistemic curiosity plays a mediating role in the nexus of L2 motivation, epistemic curiosity, and epistemic boredom. Data were collected from adolescent learners of English in China (N = 312). The findings from the correlation analysis indicated that epistemic boredom had statistically significant negative relationships with epistemic curiosity and L2 motivation, except for the ought-to L2 self variable, where the relationship was not statistically significant. Conversely, epistemic curiosity had a positive and statistically significant relationship with L2 motivation, except for the ought-to L2 self variable, where the relationship was not statistically significant. Next, the path analysis examined the influence of L2 motivation on epistemic boredom without considering the mediating effect of epistemic curiosity. Its findings indicated that epistemic boredom had a statistically significant negative relationship with the general motivation/attitude and general motivation/effort variables. The subsequent path analysis, which focused solely on two goal-oriented L2 motivation constructs from the Gardnerian framework, detected the mediating role of epistemic curiosity. Some pedagogical implications are drawn from these findings.

Influence of subsequent path and pressure on pedestrian route choice in emergency evacuations

Route choice significantly impacts pedestrian evacuation efficiency. Previous studies have mainly focused on environmental or pedestrian conditions in single enclosed spaces, with limited consideration for the effects of successive paths, including both the current paths and subsequent paths beyond the room where pedestrians are located. In this study, we propose a new experimental setup with multiple subsequent paths. We carried out a series of single-person experiments to investigate the effect of different pressure levels on pedestrian route choice in multiple scenarios with different subsequent paths. The results indicate that path length is an important factor for the single person route choice, and the greater the length difference between alternative paths, the higher the proportion of pedestrians choosing the shorter path, reaching up to 100 %. Participants seem to have a short-term oriented behavior, when the total path length is the same, over 60 % of participants chose the shorter current path in all scenarios, and with a 21.67 % higher selection rate observed in high-pressure scenarios compared to low-pressure scenarios. The results of the logit regression analysis also significantly indicate the impact of pressure on pedestrian route choice, and the length of the current path has a greater influence on route choice than the length of the subsequent path. These results provide new evidence for future evacuation design and management in enclosed spaces.

Understanding the influence of children’s mental health, cognitive development, and environmental factors on learning outcomes in Chile

Mental health, cognitive development, and social background are related to educational success. While growing evidence is available in cultural settings other than Western countries, more knowledge is needed, especially regarding interactions among these dimensions. Rather than studying isolated factors, we propose an integrated approach to consider the diverse interrelated dimensions influencing children’s learning. Life course theory supports this approach underlying the role of early events in subsequent life paths and the multidisciplinary nature of these events. The sample consisted of 610 children (49.1% male) attending first grade. The children completed reading, mathematics, and visuospatial working memory (VWM) assessments. Parents completed the Strengths and Difficulties Questionnaire (SDQ-P) and reported their demographic information. A multilevel path model was estimated, including direct relationships between (i) children’s socioemotional behavior (SEB) and learning, (ii) VWM and learning, and (iii) SEB and VWM. The effects of sex and maternal education were also controlled. School and student level variances were modeled. At the school level, VWM, reading, and mathematics have variance, whereas SEB does not. At the student level, VWM, SEB, and maternal education have significant and differential effects on learning. Hyperactivity and peer problems were negatively related to reading and mathematics, while emotional problems were not, and conduct problems exhibited mixed results. These results reinforce developmental life course approaches, that is, from the beginning of schooling, promoting positive mental health can improve children’s learning outcomes.

An Automatic Mapping Method of Navigation Map for Outdoor Road Scenes

Abstract. In the process of autonomous navigation of outdoor mobile robots, four modules are involved: perception, localization, planning, and controlling. The perception module utilizes sensors such as cameras and radars based on various principles to analyze the robot's surroundings in real-time. The localization module uses GPS (Global Positioning System), IMU (Inertial Measurement Unit), and prior maps for real-time positioning analysis. The planning module plans optimal path based on the outputs of the first two modules, and the controlling module directs the robot's chassis to move along the planned optimal path. For the localization module, the accuracy of GPS positioning results heavily depends on weather conditions and GPS signal receptions. Even if the positioning results of imu are integrated, the positioning accuracy still cannot meet the needs of robot navigation. Therefore, using prior maps for repositioning can compensate for this accuracy deficiency. The planning module also requires path planning based on prior maps. If the a priori map storage is large, it will lead to difficulties in usage, maintenance, and updates. Therefore, it is crucial to research lightweight navigation map mapping methods. In this paper, an automatically mapping method of lightweight navigation maps is proposed, combining cameras and LiDAR (Light Detection and Ranging), including semantic informations necessary for outdoor navigation positioning, such as pole-like objects and traffic signs for robot longitudinal positioning, and lane line elements for robot lateral positioning. This method automatic generates robot navigation maps in Lanelet2 format, providing support for subsequent positioning and path planning modules.

In-process part tracking and shape measurement using vision-based motion capture for automated English wheeling

An English wheel is an exceedingly adaptable instrument in traditional metalworking. It is a manual manufacturing technique, enabling skilled craftsmen and blacksmiths to shape complex compound curves in sheet metal panels. Accurate measurements and precise adjustments are essential when operating an English wheel to ensure that the metal is shaped with the desired curvature. An automated method to form English wheeled panels through robot forming has recently been proposed. For such a method to be successful, accurate tracking of sheet information including positions, orientations, and deformation is important for error compensation and the design of the subsequent tool paths. In this study, a Vicon motion capture system is employed to monitor the position and shape of the sheet metal during the English wheeling process. The initial experimental results demonstrate the potential of such an in-process metrology system, along with possible avenues for future work.

Obtaining a PhD in Portugal. Determinants of Success and Subsequent Career Paths

Background Over the past three decades, Portugal has invested significantly in doctoral training. However, there is a lack of up-to-date information on the success of scholarship holders in obtaining the degree or on their subsequent career paths. Methods This study analysed four cohorts of scholarship holders funded by the Foundation for Science and Technology between 1995 and 2012. The professional situation at different points in time after the Ph.D. (5, 10, 15 and 20 years) was studied. Results The success rate for obtaining the degree was 88%, which is comparable to other European countries for doctorates completed with funding over a period of 3-4 years. The average time to obtain the degree was 5.06 years. The time to degree was influenced by the scientific field, the nationality of the scholarship holder, and the location of the institution awarding the degree (in Portugal or abroad). The gender or age range of the scholarship recipients did not influence the time required for graduation. The analysis of the career and sector of activity of these graduates at different points in time after obtaining the Ph.D. revealed that approximately 60% percent of the graduates were engaged in R&D activities at some point in their career paths, but this percentage diminished from the oldest to the most recent cohorts, suggesting difficulties in retaining recent graduates in academia and in the private sector. In 2020, 63% of the graduates were engaged in R&D activities, and almost half were employed in higher education as teachers, researchers, or scholarship holders. Conclusions This study confirmed the challenges faced by doctoral graduates in integrating into non-academic job markets. On the other hand, it has demonstrated an efficient use of public funds, with high success rates and a time to degree that is within the average of other European countries.

Integrating academic medical education into vocational general practitioner training: how do these combined training posts impact on subsequent career paths?

ABSTRACT Background In the UK, to encourage academic careers, extended education posts (EEPs) exist, where standard three-year, general practice vocational training is extended, offering trainees dedicated time to spend in another specialty such as medical education (Med Ed). Little is known about whether this impacts positively on their subsequent careers. Aims To explore general practitioners’ (GPs’) experiences and career trajectories after undertaking Med Ed EEPs. Method Twenty-eight GPs who completed a Med Ed EEP between 2013 and 2021 were invited to participate. Semi-structured interviews were held virtually. Transcripts were coded with NVivo software and underwent thematic analysis using Braun and Clarke’s six-phase framework to ensure a reiterative process of internal validation. Results Eight GPs took part. All were working as NHS GPs, alongside other roles. Four themes emerged: ‘growing as an academic educator’, ‘research can be interesting’, ‘the academic environment’ and ‘juggling multiple roles is stressful’. Most were still teaching, involved in research and had undertaken formal Med Ed training. Role models and immersion in academic teams were influential. Significant tensions and stresses were experienced when balancing multiple roles. The absence of ongoing academic training tracks contributed to this. Conclusion EEPs impact positively on academic career development and the acquisition of appropriate skills. However, managing multiple roles is challenging and stressful. Short-term university contracts, difficulties obtaining flexible working and resultant lack of partnership or salaried clinical work highlight an urgent need to explore fixed academic training pathways after vocational training, if sustainable recruitment into primary care academia is to be achieved.

A lung biopsy path planning algorithm based on the double spherical constraint Pareto and indicators’ importance-correlation degree

Lung cancer has the highest mortality rate among cancers. The commonly used clinical method for diagnosing lung cancer is the CT-guided percutaneous transthoracic lung biopsy (CT-PTLB), but this method requires a high level of clinical experience from doctors. In this work, an automatic path planning method for CT-PTLB is proposed to provide doctors with auxiliary advice on puncture paths. The proposed method comprises three steps: preprocessing, initial path selection, and path evaluation. During preprocessing, the chest organs required for subsequent path planning are segmented. During the initial path selection, a target point selection method for selecting biopsy samples according to biopsy sampling requirements is proposed, which includes a down-sampling algorithm suitable for different nodule shapes. Entry points are selected according to the selected target points and clinical constraints. During the path evaluation, the clinical needs of lung biopsy surgery are first quantified as path evaluation indicators and then divided according to their evaluation perspective into risk and execution indicators. Then, considering the impact of the correlation between indicators, a path scoring system based on the double spherical constraint Pareto and the importance-correlation degree of the indicators is proposed to evaluate the comprehensive performance of the planned paths. The proposed method is retrospectively tested on 6 CT images and prospectively tested on 25 CT images. The experimental results indicate that the method proposed in this work can be used to plan feasible puncture paths for different cases and can serve as an auxiliary tool for lung biopsy surgery.

Assembled Wood-Polyester Fabric-Hydrogel Janus Evaporator for Sustainable Seawater Desalination.

Solar-driven interfacial evaporation technology is a novel and efficient desalination process that helps alleviate the global shortage of freshwater resources. We developed a Janus evaporator assembled from cotton hydrogel, hydrophilic polyester fabric (PF), and Hydrophobic Wood (PW). By doping graphene oxide and TiO2 as light-absorbing materials within the hydrogel, we achieved a high absorptivity of over 90% across the entire solar spectrum. The hydrophilically modified PF, combined with the PW substrate, provided robust water transport and reduced thermal losses. Subsequent optical path simulations using TracePro74 software verified that the sawtooth light-trapping design of the wood substrate increased multiple light reflections and absorption (compared to a flat structure), enhancing light absorption capabilities. The sawtooth interface also enlarged the evaporation area, further boosting evaporation performance. The cleverly designed evaporator exhibited an evaporation rate of 1.722 kg m-2 h-1 and an efficiency of 83.1% under 1 sun irradiation. Additionally, after applying polydimethylsiloxane to the single surface of the photothermal hydrogel for low surface energy treatment, the resulting Janus structure demonstrated asymmetric wettability that prevented salt ions from accumulating on the irradiated interface. After 8 h of continuous evaporation in saline water (10 wt %), only slight salt crystallization occurred at the edges. The evaporator maintained long-term stability during a 15 day cyclic test, and the produced freshwater fully met the relevant drinking water standards. The components of the evaporator are characterized by simple fabrication, low cost, and eco-friendliness, offering significant application potential in the global context of energy conservation and emission reduction initiatives.

Students speak: Academic, career, and sociocultural experiences of African American college students

This manuscript presents the outcomes of a qualitative research investigation centered on the experiences of African American college students in terms of their preparation for high school, college, and careers within a Predominantly White Institution (PWI) situated in rural southeastern Wisconsin. At the time of this research, the comprehensive public university had an undergraduate enrollment of 10,196 students. Among these students, 82.1% self-identified as White, 7.8% as Hispanic or Latinx, 5.4% as African American, 3.2% as Asian or Southeast Asian, and 0.9% as American Indian or Alaskan Native. Using semi-structured interviews with willing student participants, the primary objectives of this study were twofold: (1) to recognize the sociocultural and institutional elements that influence the career trajectories of African American students attending the institution and (2) to effectively capture the educational and career viewpoints and voices of these students as they navigate the complex sociocultural and institutional landscape. Key findings from the research highlight the students’ perspectives on the substantial connections between their high school experiences, particularly those in and around a major urban center in the Midwest, and their subsequent college and career paths. Additionally, the study underscores the challenges these students encounter while navigating the physical and social spaces on a rural PWI campus. Recommendations are made for creating a more welcoming space for African American students and for supporting those engaged in the work.

Anisotropic mechanism of cold-rolled pure titanium plate during the two-step tensile process of the variable path

The effects of pre-deformation on the macro-mesoscopic deformation characteristics of the titanium plate during variable path tensile were studied by a two-step tensile test and electron backscatter diffraction (EBSD). The Schmid law, Kernel Average Misorientation (KAM), Taylor axis, and In-Grain Misorientation Axis (IGMA) were used to forecast and identify the types and change laws of the activated deformation modes under different loading conditions. The results demonstrated that dislocation slip is the primary cause of the evolution of the basal split texture components. The nucleation and de-twinning of {10–12}ET resulted in the sudden appearance and disappearance of the <0001>//RD texture. The pre-tensile causes a texture redirection that reduces the activability of both prismatic <a> slip and pyramidal <a> slip in the following variable path tensile. Among them, prismatic <a> slip is the dominant deformation mechanism that causes yield and hardening behavior during RD tensile and TD-RD tensile (rolling direction-RD, transeverse direction-TD). A portion of the prismatic <a> slip is preferentially activated in TD tensile and RD-TD tensile deformation, and the deformation is subsequently jointly controlled by the prismatic <a> slip and the pyramidal <a> slip. The pre-tensile along RD promotes nucleation of {10–12} extension twin (ET) during subsequent RD-TD variable path tensile, while tensile along TD-RD coordinates plastic deformation by consuming a significant quantity of {10–12}ET generated during pre-tensile along TD. The formation of slip-assisted twins in neighboring grains is facilitated by the dislocation pile-up at grain boundaries, and the de-twinning phenomenon also cause the local dislocation pile-up to weaken.

Three-Dimensional Path Planning for Post-Disaster Rescue UAV by Integrating Improved Grey Wolf Optimizer and Artificial Potential Field Method

The path planning of unmanned aerial vehicles (UAVs) is crucial in UAV search and rescue operations to ensure efficient and safe search activities. However, most existing path planning algorithms are not suitable for post-disaster mountain rescue mission scenarios. Therefore, this paper proposes the IGWO-IAPF algorithm based on the fusion of the improved grey wolf optimizer (GWO) and the improved artificial potential field (APF) algorithm. This algorithm builds upon the grey wolf optimizer and introduces several improvements. Firstly, a nonlinear adjustment strategy for control parameters is proposed to balance the global and local search capabilities of the algorithm. Secondly, an optimized individual position update strategy is employed to coordinate the algorithm’s search ability and reduce the probability of falling into local optima. Additionally, a waypoint attraction force is incorporated into the traditional artificial potential field algorithm based on the force field to fulfill the requirements of three-dimensional path planning and further reduce the probability of falling into local optima. The IGWO is used to generate an initial path, where each point is assigned an attraction force, and then the IAPF is utilized for subsequent path planning. The simulation results demonstrate that the improved IGWO exhibits approximately a 60% improvement in convergence compared to the conventional GWO. Furthermore, the integrated IGWO-IAPF algorithm shows an approximately 10% improvement in path planning effectiveness compared to other traditional algorithms. It possesses characteristics such as shorter flight distance and higher safety, making it suitable for meeting the requirements of post-disaster rescue missions.

A Multipath Process-Based Inherent Strain Method for Prediction of Deformation of Hull Plate for Integrated Heating and Mechanical Rolling Forming Process

Integrated heating and mechanical rolling forming (IHMRF) has recently been introduced for manufacturing complex curvature hull plates. It fabricates the target curved plate by sequential loading along the multipath. Accurate and efficient prediction of the deformation of the plate is the basis for developing the process planning and ensuring the quality of the forming. The inherent-strain method is ideal for this purpose, but its prediction accuracy needs to be improved. This paper proposes a multipath process-based inherent-strain method (MPISM), which considers the effect of the sequential loading process of the multipath on plate deformation. First, the effect of loading paths near the plate edge was investigated, which in turn clarified the rationale for obtaining the inherent strain only in the plate center. Secondly, a strain correction strategy was established by analyzing the variation pattern of the inherent strain caused by the crossing or proximity of the previous path and the subsequent path. This allowed the effects of the loading process to be taken into account in the elastic analysis. Based on the plate-and-shell theory, the idea of an equivalent inherent strain distribution is also presented. This makes the loading of inherent strains more accurate in the elastic finite-element model. MPISM predictions and experimental results show good agreement. Compared with the thermo-elastic–plastic finite element method, the MPISM substantially improves efficiency while maintaining accuracy. Compared with the original inherent-strain method, the MPISM is more accurate in terms of deformation magnitude prediction.

How is the path produced and sustained? Path-dependent college education expansion and underlying liberal rule in Korea

Abstract The conventional policy analyses with a path-dependent framework are featured by sequential causation composed of analytically two distinct phases: path production that occurs through a significant policy change at critical junctures and the subsequent path reproduction. This paper explores one policy area where the two-phase framework falls short in explaining path-making and maintenance – college education expansion in Korea. We argue that the shortcomings of the two-phase model can potentially be overcome by incorporating the underlying rule of the countries into the model. We identify the underlying rule relying on Esping-Andersen’s welfare regimes to highlight the political underpinnings of the countries. We show that the underlying liberal rule is a fundamental causal force behind the production and reproduction of college education expansion in Korea, using qualitative comparative analysis. Our framework based on the underlying rule provides a richer understanding of path dependency.

Trajectory optimization of unmanned surface vehicle based on improved minimum snap

To solve the problem of path discontinuity and tracking difficulty in unmanned surface vehicle path planning, this paper introduces the Minimum Snap algorithm to optimize the trajectory, and makes some improvements to the Minimum Snap algorithm to address the problem of imperfect paths caused by uneven time allocation. The concept of a safe corridor is introduced to optimize the Minimum Snap algorithm. In response to the problem of excessive deviation from the reference value in some areas of the optimized path, a guidance function is added to make the path closer to the original trajectory. In the simulation, the proposed improved Minimum Snap is compared with Bezier curve and B-spline curve, the results show that the improved Minimum Snap can enable unmanned surface vehicle to complete turns and other actions with minimal energy consumption while driving safely, without experiencing severe acceleration and Jerk, laying the foundation for subsequent path tracking control.

A multi-step attack path prediction method for oil & gas intelligence pipeline cyber physics system based on CPNE

Owing to the integration of the 5th Generation Mobile Communication Technology (5 G) and industrial internet construction, Oil & Gas intelligent pipeline network has witnessed accelerated construction and development. The Oil & Gas intelligent pipeline network proposed by China National Petroleum Corporation exhibits the advantages such as high integration, data unification, and intelligent decision-making, which helps to greatly reduce manual management costs, optimize risk decision-making by managers, and avoid risks such as human misuse. However, the highly integrated Cyber-physical system of the Internet and the Internet of Things faces various cyber security threats, and traditional intrusion detection systems exhibit drawbacks in the face of complex cyber-attack behaviors. In response to incomplete multi-step attack path prediction in traditional prediction methods, this paper proposes a multi-step attack path prediction method for Oil & Gas intelligence pipeline cyber physics system (CPS) based on Colored Petri nets and mixed strategy Nash equilibrium (CPNE). Taking into account the importance of assets and the dependency relationships between assets within the cyber-physical system of Oil & Gas intelligent pipeline network, CPNE constructs a node dependency model for the cyber-physical system of Oil & Gas intelligent pipeline network, simulates multi-step attack and defense games, calculates the probability of node failure triggering and transfer using mixed strategy Nash equilibrium, and extracts the risk of multi-step attack paths for different attack strategies. With the filtration and separation unit of a certain natural gas station as an example, this paper establishes a CPNE model to rank the risk of the first multi-step attack single attack source path and predict the risk of subsequent multi-step attack source paths, thus predicting multi-step attack paths. Taking three rounds of attacks as an example, compared to the paths predicted by traditional probability attack graph models, the proposed CPNE model is more advantageous in multi attack source path prediction, with a 2.33-fold increase in the relative coverage rate of path predictions.

Examining the relationship between car ownership, car use, and exercise: Role of the built environment

Although owning a car allows people to access distant fitness centers and may promote exercise, car use may encourage sedentary behavior and reduce exercise. There is no empirical evidence on the relationship between car ownership, car use, and exercise, and whether improving the built environment is useful to encourage exercise by affecting car ownership and usage. Through a survey of 1049 respondents in Shanghai and subsequent path analysis, we investigate the relationship between the built environment around residences and workplaces, car ownership, car usage for work and non-work trips, and the duration of exercise weekly. While car ownership directly fosters exercise, it indirectly reduces exercise due to increased car usage for work and non-work trips, and the negative effects outweigh the positive. Moreover, the built environment around residences and workplaces affects exercise through car ownership and usage. People living in dense and downtown neighborhoods conduct more exercise because of the fewer likelihood of owning and/or using cars. More intersections and transit stops around residences and mixed land use around workplaces reduce exercise by increasing car ownership and/or car usage. We conclude that reducing car ownership and usage can promote exercise, and built environment interventions are effective in enhancing public health outcomes.