Pathwidth Research Articles

Study on the Mechanism of Agricultural Greenhouse Gas Emission Reduction Under Macro Emission Reduction Measures

Clarifying the impact of macro emission reduction measures on the mechanism of agricultural greenhouse gas emission reduction is of great significance in promoting climate change governance and the construction of a carbon emission reduction policy system. This paper explores the mechanism of important macro emission reduction measures based on a multi-level progressive factor decomposition perspective and designs a coupled model of computable general equilibrium and structural path decomposition to identify the key emission reduction paths of major macro emission reduction measures and to decompose the drivers that promote emission reduction in each path. This study found that: (1) The emission reduction effect of the combination of carbon tax, carbon sink and carbon capture, utilization, and storage macro emission reduction measures is dominated by the indirect emission reduction triggered by the industrial chain, accounting for 95.67% of the total agricultural GHG emission reduction, and the emission reduction effect is gradually weakened with the increase in the production level. (2) The emission intensity effect and the industrial structure effect are the main drivers of the macro emission reduction portfolio measures to promote emission reduction, but there are differences in the roles of the different drivers on the various production levels and different emission reduction pathways. (3) Vegetables, fertilizers, the light industry, and other key industries are the main agricultural greenhouse gas emission reduction contributing industries, of which the emission reduction contribution from citizen consumption is the largest, and the emission reduction is mainly achieved by influencing the demand path of the vegetable industry and the light industry to the upstream high-energy-consuming or high-emission industries. Therefore, there is a need to fully utilize the mechanisms that drive emission reduction at different production levels and pathways by each key factor and to take targeted measures to promote synergistic emission reduction among industries. In the short term, focus on enhancing the role of the emission intensity effect, while in the medium and long term, pay much attention to the positive role of the industrial structure effect on agricultural greenhouse gas emissions.

Factors and structural paths of the changes in carbon emissions in China's provincial construction industries

The changes in the carbon emissions in China's provincial construction industries are of high complexity. It is essential to understand the changes in the construction carbon emissions (CCEs) in China on the provincial scale. This study evaluates the factors and structural paths of the changes in provincial CCEs in China between 2012 and 2017 using the structural path decomposition analysis. The results show that the emission intensity effect and production structure effect contributed greatly to the reduction of CCEs across various regions, while the final demand effect had contrary impacts. The local nonmetallic mineral products industry (c13), metal smelting and pressing industry (c14), and electricity industry (c24) generally contributed significantly to the emission intensity effect, production structure effect, and final demand effect across most regions. The consumption of local c13, c14, and c24 by the construction industry (c27), namely “local c13→c27”, “local c14→c27”, and “local c24→c27” were generally the important structural paths of the CCEs changes across various regions. Nonlocal industries such as Hebei c14 and nonlocal structural paths such as “Hebei c14→c27” contributed substantially to the CCEs changes in many regions such as Beijing. The emission intensity effect, first-order production structure effect, and final demand effect typically dominated the effects of the critical structural paths of the CCEs changes across various regions. This study can help policymakers better understand the changes in China's provincial CCEs to formulate region-specific emission reduction measures and provide a comprehensive reference for related research.

Conductivity Prediction Method of Solid Electrolyte Materials Based on Pearson Coefficient Method and Ensemble Learning

In order to screen solid electrolytic materials with high ionic conductivity more quickly and accurately, a conductivity prediction method for solid electrolyte materials based on logistic regression model and random forest regression model is constructed. The method first selects 20 characteristic descriptors related to ionic conductivity from material library according to four dimensions: structural stability, metal stability, electronic conductivity and oxidative decomposition stability. The enumeration method and feature selection method are used to combine different features. Then, the dimension reduction of the feature combinations is carried out by Pearson coefficient method, so as to screen the optimal feature combinations. Finally, according to the optimal feature combination and data subset, the constructed random forest ensemble learning model is utilized to predict the ionic conductivity of other solid-state electrolyte materials in the material library, in order to find the solid-state electrolyte materials that can meet the high conductivity. The results indicate that as the number of features in the combination increases, the prediction performance of the model shows a trend of first increasing and then decreasing. When the feature descriptor in the combination is 7, the maximum AUC (Accuracy) value is reached, and the optimal feature in this case contains 7 optimal feature subsets corresponding to feature descriptors, namely the standard deviation of the average adjacency number of Li atoms, the standard deviation of Li-X ion bonds, the average electronegativity of the straight path, the average width of the straight path, the average atomic volume, the average Li-Li bond, and the filling fraction of the sublattice. On the basis of the optimal feature screening, the average prediction accuracy of the logistic regression model is 87.13%, which has a high accuracy. Using the random forest regression model for prediction, the average absolute error and root mean square error obtained are only 0.237 and 0.134, and compared with classical classification methods such as KNN, SVM and Adaboost, they are smaller, which can better predict the ionic conductivity of solid electrolyte materials. This proves that the constructed method can quickly and accurately produce high ionic conductivity materials in solid electrolyte materials, which is worthy of further research and promotion.

Transitive path decompositions of Cartesian products of complete graphs

An H-decomposition of a graph Γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Gamma $$\\end{document} is a partition of its edge set into subgraphs isomorphic to H. A transitive decomposition is a special kind of H-decomposition that is highly symmetrical in the sense that the subgraphs (copies of H) are preserved and transitively permuted by a group of automorphisms of Γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Gamma $$\\end{document}. This paper concerns transitive H-decompositions of the graph Kn□Kn\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$K_n \\Box K_n$$\\end{document} where H is a path. When n is an odd prime, we present a construction for a transitive path decomposition where the paths in the decomposition are considerably large compared to the number of vertices. Our main result supports well-known Gallai’s conjecture and an extended version of Ringel’s conjecture.

A study on landscape feature and emotional perception evaluation of waterfront greenway

Waterfront greenway is important spatial carriers for urban residents to engage in walking tours and fitness activities. Improving the quality of its walking spaces can have a positive impact on the mental well-being of pedestrians. This enhancement is a crucial aspect of building healthy cities. This study focused on urban waterfront greenway landscapes. Field surveys combined with questionnaire scales were used to assess pedestrians’ emotional perceptions, while concurrently collecting image data of waterfront greenway walking spaces. Semantic segmentation was employed to identify elements, and landscape metrics were calculated using relevant formulas. Correlation analysis was used to investigate the relationship between landscape metric features and emotional perceptions. And established a multiple regression model of pedestrian spatial perception on waterfront greenways to investigate the influence mechanisms of emotional perception and landscape metrics. The study indicates that greenness, proportion of water area, and vegetation diversity positively impact emotional perception of waterfront leisure greenway walking spaces, whereas path width negatively affects emotional perception. Specifically, the magnitude of influence is ranked as follows: greenness (0.491), proportion of water area (0.356), proportion of trails (−0.272), and vegetation diversity (0.130). The design guidelines for urban waterfront greenway spaces were proposed, guided by quantitative studies on landscape elements of waterfront greenway spaces and based on the measurement features of these elements. Moreover, the environmental experience of the waterfront green walking spaces was further enhanced, satisfying the public’s visual perception and psychological needs. The contribution of this study is to lay the foundation for the development of spatial control items for urban waterfront greenway.

Feasibility of using electrodermal activity responses to assess level of crowdedness of pedestrian paths

As urban populations grow, it's imperative to evaluate and enhance the quality of pedestrian paths from the user's perspective. Crowdedness, associated with discomfort and safety, is crucial in determining the overall walking quality and user experience. Previously utilized methods for measuring crowdedness, such as travel diaries and floating population surveys, were limited to collecting perceptual data from sporadic surveys with restricted spatial coverage. Similarly, methods based on CCTV or mobile service data have been used but present issues with blind spots and fail to consider pedestrian perspectives. Against this background, this study explores the feasibility of assessing crowdedness levels by measuring subjects' physiological responses in a laboratory setting based on visual images of real and virtual environments. This study hypothesizes that the amount of people or vehicles passing by affects the electrodermal activity (EDA) of pedestrians, indicating the comfort level of using the environment. Experimental EDA data were measured using a wearable device while the subjects were watching videos showing different pedestrian traffic flows. Representative EDA signal features (e.g., skin conductance responses) were extracted after data pre-processing. Noticeable changes in EDA responses are observed when subjects countered specific environmental variations, such as differing volumes of passing people, on pedestrian paths. The findings suggest that EDA data can be instrumental in differentiating crowdedness levels on pedestrian paths. This study contributes to the body of knowledge by demonstrating the potential of EDA data to characterize the crowdedness experienced by pedestrians. This aids in the development of a novel, quantitative method to gauge pedestrian path crowdedness and to discern contributing factors, such as path width.

Investigation of the Effects of the Number of Shells, Raster Angle, Extrusion Ratio, and Path Width on Printed Polylactic Acid Parts with Fused Deposition Modeling 3D Printer

Investigation of the Effects of the Number of Shells, Raster Angle, Extrusion Ratio, and Path Width on Printed Polylactic Acid Parts with Fused Deposition Modeling 3D Printer

Path decompositions of 5-regular graphs

Path decompositions of 5-regular graphs

Predicting fatigue life with the IMWCW under complex loading

The Integration Modified Wöhler Curve Method (IMWCW), a novel approach for predicting fatigue life under complex strain-based non-proportional loading paths is introduced in this research. This method integrates concepts from the Modified Wöhler Curve Method (MWCW) with the principle of damage incremental integration to provide a more nuanced prediction of material fatigue. Besides two established E-N curves (strain-number of cycles) for uniaxial tension and torsion, a new fundamental E-N curve that characterizes the strain-life relationship under complete non-proportional loading paths is introduced. A novel strain path decomposition technique is presented, which dissects an infinite number of instantaneous micro-elements along any loading path into components parallel and perpendicular to the proportional loading direction. It is assumed that each instant will cause fatigue damage to the material. A concurrent model for the incremental integration of damage is formulated, allowing for the calculation of cumulative damage. The model is further expanded to provide analytical expressions for proportional loading and non-proportional loading, linking them to three fundamental E-N curve, so as to calibrate the parameters required for the integration model. The empirical validity of the model is confirmed through experimental testing on 7 different metallic materials under 20 loading conditions, with 391 data points analyzed. The results demonstrate that 91% of the model's predictions fall within a scatter band of 2, confirming its robustness and reliability in forecasting fatigue life in complex, real-world scenarios.

Microscopic simulation of bicycle traffic flow incorporating cyclists’ heterogeneous dynamics and non-lane-based movement strategies

Cycling as a mode of transport is on an upward trend as a low-emission alternative to driving in urbanized areas nowadays. With the increasing number of cyclists, it is of great importance to assess the capacity of cycling infrastructure in practice. Simulation models are useful tools to investigate bicycle flow performance considering cyclists’ distinct moving behaviors. However, existing bicycle simulation models are restricted by either space discretization, lane-based setup, adaptation from models for car traffic, or complicated calibration requirement in a force-based environment. In addition, cyclists’ decision-making ability in the operational-level cycling behavior are not well-captured in these models. This paper proposes a comprehensible microscopic bicycle simulation model which includes a detailed decision-making process and the ability to simulate continuous-space lateral movement. The model consists of three levels, maneuver decision, movement planning, and physical acceleration. It is able to simulate bicycle flow dynamics in undersaturated traffic conditions on an exclusive bike path. As we do not intend to show the empirical validity of the proposed model, the simulation experiment aims at verifying the model and exploring bicycle flow performance in various scenarios by estimating the fundamental diagrams (FDs). The effect of different path widths on bicycle flow capacity is first explored. Other behavioral factors, including desired speed heterogeneity, overtaking incentive, and safety region size perceived by cyclists, which can potentially influence the shape of the FD are also tested. The model can be further extended to simulate relatively complex cycling behavior with cooperative and anticipative strategies and investigate bicycle flow characteristics in congested traffic conditions.

How older adults maintain lateral balance while walking on narrowing paths

BackgroundOlder adults have difficulty maintaining side-to-side balance while navigating daily environments. Losing balance in such circumstances can lead to falls. We need to better understand how older adults adapt lateral balance to navigate environment-imposed task constraints. Research QuestionHow do older adults adjust mediolateral balance while walking along continually-narrowing paths, and what are the stability implications of these adjustments? MethodsEighteen older (71.6±6.0 years) and twenty younger (21.7±2.6 years) healthy adults traversed 25 m-long paths that gradually narrowed from 45 cm to 5 cm. Participants switched onto an adjacent path when they chose. We quantified participants’ lateral center-of-mass dynamics and lateral Margins of Stability (MoSL) as paths narrowed. We quantified lateral Probability of Instability (PoIL) as the probability that participants would take a laterally unstable (MoSL<0) step as they walked. We also extracted these outcomes where participants switched paths. ResultsAs paths narrowed, all participants exhibited progressively smaller average MoSL and increasingly larger PoIL. However, their MoSL variability was largest at both the narrowest and widest path sections. Older adults exhibited consistently both larger average and more variable MoSL across path widths. Taken into account together, these resulted in either comparable or somewhat larger PoIL as paths narrowed. Older adults left the narrowing paths sooner, on average, than younger. As they did so, older adults exhibited significantly larger average and more variable MoSL, but somewhat smaller PoIL than younger. SignificanceOur results directly challenge the predominant interpretation that larger average MoSL indicate “greater stability”, which we argue is inconsistent with the principles underlying its derivation. In contrast, analyzing step-to-step gait dynamics, together with estimating PoIL allows one to properly quantify instability risk. Furthermore, the adaptive strategies uncovered using these methods suggest potential targets for future interventions to reduce falls in older adults.

The North-South industrial transfer of manufacturing and the pattern of carbon emissions in China

In recent years, the gap between the north and the south of China has been expanding, showing a decreasing proportion of value-added and an increasing proportion of carbon emissions in the north of China, and vice versa in the south of China. Based on the most recent inter-provincial input-output table of China in 2012 and 2017, this paper focused on the North-South industrial transfer of manufacturing, quantified its impact on regional carbon emissions, and decomposed the path of impacts. The results suggest that the North-South industrial transfers of China during 2012-2017 indeed aggravated the imbalance of carbon emissions in the north and the south of China. Further explorations of path decompositions show that the spillover effect through production linkages is the major path where industrial transfer influences regional carbon emissions, particularly in the north of China. The results provide insightful policy implications for the achievement of carbon emissions reduction targets in China as well as the globe.

ANALYSIS OF PEDESTRIAN PATH WIDTH REQUIREMENTS IN THE MANUKAN LOR ROAD AREA, SURABAYA CITY

The commercial area on Manukan Lor street is one of the places in the city of Surabaya that currently has quite heavy traffic. The problem in this area is that there is no special pedestrian/pedestrian route available so it can endanger pedestrians, apart from that it can also disrupt the activity of traffic vehicles. The aim of this thesis refers to the formulation of the problem and the existing background, including: Determining the characteristics of pedestrians in the Manukan Lor Street area of Surabaya, determining the width requirements for pedestrian/pedestrian lanes in the Manukan Lor Street area, and to determine the performance results in Manukan Lor road section after and before the sidewalk. Guidelines used in planning pedestrian paths in the area "Sidewalk Planning Guidebook Number.007/T/BNKT/1990 Directorate General of Highways", "Guidebook for Building Construction Materials and Civil Engineering Ministry of PUPR Number.02/SE/M/2018 regarding technical planning of pedestrian facilities", and "Indonesian Road Capacity Guidebook 2023 (PKJI 2023)". The results of the analysis of the required width of the pedestrian path on the Manukan Lor road are 1.5 m wide with the level of service obtained is category A, and includes low-level side obstacles, with an average increase in the degree of saturation (Dj) of 0.026 but still in service level category C with a stable flow the speed can be controlled by traffic. Keywords: Pedestrian Width; Characteristics; Road Performance.

Direct visualization and measurement of the plantar aponeurosis behavior in foot arch deformation via the windlass mechanism.

The plantar aponeurosis (PA) is an elastic longitudinal band that contributes to the generation of a propulsive force in the push-off phase during walking and running through the windlass mechanism. However, the dynamic behavior of the PA remains unclear owing to the lack of direct measurement of the strain it generates. Therefore, this study aimed to visualize and quantify the PA behavior during two distinct foot postures: (i) neutral posture and (ii) windlass posture with midtarsal joint plantarflexion and metatarsophalangeal joint dorsiflexion, using computed tomography scans. Six healthy adult males participated in the experiment, and three-dimensional reconstruction of the PA was conducted to calculate its path length, width, thickness, and cross-sectional area. This study successfully visualized and quantified the morphological changes in the PA induced by the windlass mechanism, providing a precise reference for biomechanical modeling. This study also highlighted the interindividual variability in the PA morphology and stretching patterns. Although the windlass posture was not identical to that observed in the push-off phase during walking, the observed PA behavior provides valuable insights into its mechanics and potential implications for foot disorders.

A computational method for calculating the electrical and thermal conductivity of random composites

In the present work, for the first time, the electrical–thermal conductivity of a composite random material is correlated with the number of conductive paths, the mean path length, and the mean effective path width measured in a representative surface element (RSE) by Monte Carlo sampling. This work is organized in two parts. The theoretical calculation takes place in the first part for the correlation of conductive paths by adopting three approaches (incremental with respect to accuracy and complexity) based on: (i) one-component straight paths; (ii) one-component non-straight paths; (iii) multi-component non-straight paths. In the second part, a novel numerical methodology for the calculation of the conductance of the RSE through the conductive paths, mean path length and the mean effective path is developed for the general model of multi-component non-straight line paths based on Ohm’s law. In addition, a methodology that reduces the calculated conductivity from the microscale to the macroscale is proposed, that takes into account the probability of percolation for finite sizes and the average value of the conductivity from the samples in which percolation occurs. After the necessary consistency steps and verification of the method and its implementation on random binary material systems, it is further applied to solve synthetic continuous percolation problems at the microscale and macroscale. The results and the accuracy of the calculations are in close agreement with existing models. The electrical Direct Current (DC) and thermal conductivity follow the same scaling relation and the proposed methodology can be applied at the same stage without additional cost. In a random binary medium the simulations showed that a scaling law of conductivity is followed by an exponent value close to 1.3. In addition, the number of conductive paths, the average length of the paths, and the effective width follow scaling laws with exponents 1.44±0.01 , −0.25±0.01 and −0.39±0.01, respectively.

Evaluation of Adhesive Joints Using Ultrasonic Rayleigh Waves.

Adhesive joints are non-separable connections that are used in numerous ways in vehicle construction, particularly in buses. The widespread use of adhesive joints makes it necessary to assess their quality, especially under production conditions. The main goal of this study was to develop a mathematical model to estimate the width of the adhesive path in a plywood-adhesive-closed-profile joint based on selected parameters of the ultrasonic surface wave. A digital ultrasonic flaw detector and Rayleigh wave probes were applied. The test involved evaluating different widths of hybrid adhesive and two-component epoxy adhesive. The tests were conducted on a steel profile from a bus construction. The attenuation of the ultrasonic waves on the steel profile (0.026 db/mm) and the adhesive (0.264 dB/mm) was determined. A one-size-fits-all model for estimating adhesive path width for specific conditions is proposed.

Equitable path decomposition of graphs

A decomposition of a graph is a collection of its edge — disjoint subgraphs whose union equals the edge set of the graph. A decomposition all of whose members are paths is called a path decomposition. In this paper, we introduce and initiate a study of a new variation of decomposition namely equitable path decomposition of a graph [Formula: see text] which is defined to be a decomposition in which all the members are paths and the lengths of any two paths are differ by at most one in [Formula: see text]. In this paper, we initiate a study on this parameter.

PERFORMANCE ANALYSIS OF PEDESTRIAN PATHS IN THE COLONIAL HISTORICAL AREA OF KOTA LAMA CIREBON

Pedestrian path conditions are one of the factors that affect willingness to walk and play an important role in supporting historical tourism activities. This study analyzes the performance of pedestrian paths expressed by Pedestrian Level of Service (PLOS) in the colonial historical area of Kota Lama Cirebon. The method used in this study was to conduct a geometric survey of pedestrian paths, pedestrian flow surveys, and pedestrian travel time surveys in 10 segments scattered throughout the study area. The survey results were analyzed regarding the 1985 Highway Capacity Manual (HCM) and PLOS values generated based on available walking space. The study shows that in terms of walking space availability, most of the segments in the study area have a PLOS A score, which means they are performing well. In comparison, some segments have poor PLOS, such as Merdeka Street, Yos Sudarso Street, TJ Street, and Kebumen Street, due to the unavailability of sufficient walking paths to serve pedestrians or the presence of side obstacles that reduce the effective width of the pedestrian path. To overcome these problems, several things need to be done, such as: 1) issue a policy prohibiting selling on pedestrian paths to reduce side obstacles so that the effective width of the pedestrian path can increase; 2) widen the pedestrian path at least according to the applicable standards; and 3) provide pedestrian paths on segments that do not yet have pedestrian paths.

Simulation of the Hydraulic Model HEC-RAS Coupled with GIS and Remote Sensing to Study the Effect of River Cross-section Width in Detecting Flood-prone Areas

Abstract Flooding is one of the extreme hydrological phenomena. It is a recurring natural disaster that causes loss of life and property in many parts of the world, particularly during the monsoon season. It is important to address such issues for local government and policymakers to manage the flood properly. One such flood management activity is to develop a flood-prone area that depicts the spatial and temporal extent of flood accurately. The integration of the Hydrologic Engineering Centre - River Analysis System (HEC-RAS) model and geospatial tools have emerged as a crucial approach for identifying and mapping flood-prone areas. The successful application of the HEC-RAS model generally depends on the topographical data, which represents the channel and floodplain geometry. In floodplain geometry, discrete cross-sections play a vital role to develop the floodplain map, particularly in the flat topographical region. To extract these data it needs a high-quality digital elevation model (DEM), such as light detection and ranging (LiDAR). However, due to a lack of high-resolution topographical data, flood hazard mapping in developing countries is rare. In common practice, the centerline of the river is considered the flow path for the channel. The orientation of the cross-sections is perpendicular to this line and extends to reach the limits of the floodplain. But, it is difficult to define the limits and it may depend on the magnitude of the flood. Hence, in this study, the HEC RAS model coupled with ArcGIS has been applied to the Ganga River, which traverses through the Bihar state of India to study the effect of cross-sectional width to define the floodplain. The Bihar state is facing substantial hardships from annual flooding events with approximately 16.5% of India’s flood-prone area. The extreme flood values for 5, 10, and 25 years of return period have been determined and the influence of the three different cross-sectional widths to mapping the floodplain has been investigated. This novel perspective adds dimension to the understanding of flood dynamics and its implications for flood risk assessment. In this analysis, it has been observed that, with an increase in the width of the cross-section, the floodplain area also getting increased. In this topographical region, keeping a fixed flow path will underestimate the flood-prone area. The width of the flow path depends on the topography of the region and the river flow. The outcomes of this analysis provide valuable insights into the flood-inundated areas for the specified return periods, enabling the identification and prioritization of flood-prone zones.

Layer thickness and path width setting in 3D printing of pre-impregnated continuous carbon, glass fibers and their hybrid composites

3D printing has been successfully applied in the manufacturing of variety continuous fiber and hybrid fiber reinforced composites. The process parameters have a significant impact on the overall performance of the printed parts. This paper investigates the effects of layer thickness and path width on the bending strength and surface roughness of printed pre-impregnated continuous carbon fiber, glass fiber, and their hybrid composites. Additionally, the microstructures of the fracture surfaces of the printed parts were analyzed. The results indicate that the optimal combination of bending strength and surface accuracy for printed single fiber parts is achieved when the printing layer thickness is set to 30%–40% of the fiber filament diameters. Furthermore, finely matched path width settings significantly improve the surface accuracy of printed hybrid carbon/glass fiber composites. Notably, the bending strength of printed interlayer hybrid fiber composite specimens increased by 35% compared to the specimens uniformly set according to the carbon fiber path width.