Local Intensity Research Articles

Looking for undocumented earthquake effects: a probabilistic analysis of Italian macroseismic data

Abstract. A methodology to detect local incompleteness of macroseismic intensity data at the local scale is presented. In particular, the probability that undocumented effects actually occurred at a site is determined by considering intensity prediction equations (in their probabilistic form) integrated by observations relative to known events documented at surrounding sites. The outcomes of this analysis can be used to investigate how representative and known the seismic histories of localities are (i.e., the list of documented effects through time). The proposed approach is applied to the Italian area. The analysis shows that, at most of the considered sites, the effects of intensity ≥ 6 should most probably have occurred at least once, but they are not contained in the current version of the Italian macroseismic databases. In a few cases, instead, the lack of data may concern higher intensity levels (i.e., ≥ 8). The geographical distribution of potentially lost information reflects the heterogeneity of the seismic activity over the Italian territory.

Local intensity of artisanal gold mining drives mercury accumulation in neotropical oxbow lake fishes

Driven by surges in global gold prices and additional socio-economic factors, artisanal small-scale gold mining (ASGM) in the Global South is increasing and driving emissions of significant quantities of mercury (Hg) into the air and freshwater. Hg can be toxic to animal and human populations and exacerbate the degradation of neotropical freshwater ecosystems. We examined drivers of Hg accumulation in fish that inhabit oxbow lakes of Peru's Madre de Dios, a region with high biodiversity value and increasing human populations that depend on ASGM. We hypothesized that fish Hg levels would be driven by local ASGM activities, by environmental Hg exposure, by water quality, and by fish trophic level. We sampled fish in 20 oxbow lakes spanning protected areas and areas subject to ASGM during the dry season. Consistent with previous findings, Hg levels were positively associated with ASGM activities, and were higher in larger, carnivorous fish and where water had lower dissolved oxygen levels. In addition, we found a negative relationship between fish mercury levels associated with ASGM and the occurrence of the piscivorous giant otter. The link between fine-scale quantification of spatial ASGM activity and Hg accumulation, as indicated by the result that in the lotic environment, localized effects of gold mining activities are stronger drivers (77 % model support) of Hg accumulation than environmental exposure (23 %) constitutes a novel contribution to a growing body of literature on Hg contamination. Our findings provide additional evidence of high Hg exposure risks to neotropical human and top carnivore populations subject to the impacts of ASGM, which depend on freshwater ecosystems undergoing gradual degradation. The documented spatial variation in Hg accumulation and increased Hg levels in carnivorous fish should serve as a warning to human communities in Madre de Dios to avoid the proximity of high-intensity gold mining areas and minimize local carnivorous fish consumption.

Modeling Earthen Treatments for Climate Change Effects

Adobe has been used globally for millennia. In the US Southwest, cultural heritage sites made of adobe materials have lasted hundreds of years in an arid/semi-arid environment. A common prediction across multiple climate change models, however, is that rainfall intensity will increase in the US Southwest. This increased erosivity threatens the long-term protection and preservation of these sites, and thus resource managers are faced with selecting effective conservation practices. For this reason, modeling tools are needed to predict climate change impacts and plan for adaptation strategies. Many existing strategies, including patching damaged areas, building protective caps and shelter coating walls are already commonly utilized. In this study, we modeled adobe block construction, subjected extant walls to a local 100-year return interval rainfall intensity, and tested earthen-coat-based strategies to minimize the deterioration of earthen fabric. Findings from the resultant linear models indicate that the patching of earthen architecture alone will not prevent substantial damage, while un-amended encapsulation coats and caps provide similar, and significantly greater protection than patching. The use of this model will enable local heritage resource managers to better target preservation methods for a return on investment of the material and labor costs, resulting in better preservation overall and the retention of culturally valuable resources.

Subcritical multitype Markov branching processes with immigration generated by Poisson random measures

We investigate multitype subcritical Markov branching processes with immigration driven by Poisson random measures. Limiting distributions are established for various rates of the Poisson measures when they are asymptotically equivalent to exponential or regularly varying functions. Results analogous to a strong LLN are proved, and limiting normal distributions are obtained when the local intensity of the Poisson measure increases with time. When it decreases, conditional limiting distributions are established. When the intensity converges to a constant, a stationary limiting distribution is obtained. The asymptotic behavior of the first and second moments of the processes is also investigated.

The critical role of digital technology in sustainable development goals: A two-stage analysis of the spatial spillover effect of carbon intensity

In order to achieve sustainable development goals, China has further increased its goal of reducing carbon intensity and has made digitalization an important support for sustainable development. However, the impact of digitalization on carbon intensity reduction is still unclear. In this context, this paper first evaluates the digitalization level of 30 provincial regions in China and then constructs a spatial Durbin model for two stages, 2012–2015 and 2016–2019, so as to explore the spatial spillover effects of carbon intensity in different stages and the important roles of digital infrastructure and digital inputs in carbon intensity reduction. The main findings are as follows: (1) the current digitization level of each province in China is widely disparate, with the region showing a high level in the east and a low level in the west; (2) carbon intensity reduction has a significant spatial spillover effect, as shown by a 1% reduction in local carbon intensity and a 0.21% reduction in neighboring regions; and (3) digitalization has a more significant positive impact on the reduction in carbon intensity in stage 2. The research results are strong demonstration that digitalization drives sustainable development.

Поддержка обрабатывающей промышленности Уральского экономического района в условиях санкций

The main feature of modern economic realities, which Russia faced in 2014, is the sanctions pressure applied on the country by leading economic powers. The import substitution policy will ensure the resilience of the domestic economy to the external environment, and one of its sectors that must be supported within the framework of such a policy is the manufacturing industry. This article shows that in order to make a particular sector of the economy independent of import will allow the acceleration of the annual dynamics of investment in fixed capital, for which it is advisable for the authorities to continue to develop special economic zones. It is noted that, at present, there is a lack of these zones on the territory of Ural economic region. By calculating three indicators, namely the localization coefficient in terms of output, the localization coefficient in terms of the number of employees, and the localization intensity coefficient, it was found that Kurgan and Orenburg regions, Perm Krai, and Udmurt Republic need them. And if the Orenburg region and the Perm region have already moved off the dead center, then in the Kurgan region and the Udmurt Republic, such an event did not take place. Based on the situation observed in these regions, it was stated that the status of special economic zones should be assigned to industrial parks located on their territory. This will provide companies that are currently residents of these parks with new tax preferences, which will become a trigger for annual dynamics growth of the volume of investments in fixed assets, and, consequently, for the implementation of the import substitution policy.

Effective first flush volumes in experimental household-scale rainwater catchment systems

Abstract Rainwater collection systems often include a first flush system to divert contaminants away from collected and stored rainwater. These have traditionally been designed for a set volume, to capture and divert the first 1–2 mL of rain deposited onto a roof. However, environmental and collection system parameters can vary the volume of the first flush necessary to effectively divert contaminants. Using a test-scale rainwater collection system in Amherst, Massachusetts (USA), a series of experiments were conducted to assess the quality of rainwater in the system per collection volume and time. This included a tracer study of an ideal contaminant, and water quality measurements of atmospheric rain, fractionated first flush, and the collection tank during rain events. First flush samples contained elevated dissolved organic carbon (DOC) concentrations up to 40 mg/L, with high variability between the rain events. UV 254, DOC, and conductivity all trended together indicating a uniform wash-off of contaminants. Higher intensity storms increased roof wash-off deposition and environmental conditions affected the necessary first flush volumes. The majority of contaminants likely originated from roof wet and dry deposition. The design of first flush in rainwater harvesting systems needs to account for local precipitation patterns, storm intensity, and canopy conditions.

The impact of vertical fiscal asymmetry on carbon emissions in China.

Facing the double pressure of promoting economic growth and achieving the goal of "emission peak" by 2030, China must cut down the carbon emission intensity. Focusing on the typical characteristics of China's financial system arrangement, we theoretically analyze the mechanism of vertical fiscal asymmetry affecting carbon emission intensity and use a panel data from 30 Chinese provinces to conduct an empirical examination. The results show that (1) vertical fiscal asymmetry significantly increases the local carbon emission intensity. After a series of robust tests, such as replacement variables and sample data, the conclusion is still valid. (2) The analysis of regional heterogeneity shows that the influence of vertical fiscal asymmetry in carbon emission intensity is the largest in the central area of China, followed by the eastern provinces, and not evident in the western area. The rise in carbon emission intensity brought on by vertical fiscal asymmetry can be successfully reduced by the central transfer payment. The impact of vertical fiscal asymmetry on carbon emission intensity will be greatly lessened when the central transfer payment surpasses the threshold. (3) The mechanism test shows that vertical fiscal asymmetry increases the carbon emissions intensity by three paths: reducing the intensity of environmental regulation, strengthening local governments' dependence on land finance, and local government competition. The above analysis further enriches the relevant research on how China's vertical fiscal asymmetry system affects carbon emission intensity through land finance and local government competition while pointing out the role of transfer payment, and it can help to provide new ideas and empirical evidence for further improving the financial system and promoting the green development of the economy.

Merging precipitation scheme design for improving the accuracy of regional precipitation products by machine learning and geographical deviation correction

Global satellite precipitation products (SPPs) effectively obtain spatial precipitation information but frequently fail to meet application requirements in small-scale areas due to low accuracy. This study aims to design a merging precipitation scheme based on remote sensing and surface parameters to address the inaccuracy of regional precipitation. The scheme data are based on daily IMERG-FR, CHIRPS, and PDIR-Now satellite precipitation products from 2011 to 2018, combined with WorldClim model climate data and 39 rain gauge observations. The scheme generates merged precipitation with high-accuracy and high-resolution (0.04°) through the streamlined operation of multiple methods in the Songhua River basin in northeast China. First, the stacking algorithm was employed to perform preliminary merging of SPPs and decrease data noise errors (mean absolute error and standard deviation were reduced by 13.80% and 14.44%, respectively). Second, the correlation of merged and observed precipitation was improved by 1.18%–4.46% in different seasons after geographically weighted regression. Finally, the merged data were subjected to local intensity scaling, which reduced the precipitation error by an average of 3.14%. When compared to the original SPPs, the final merged precipitation (FMP) improved the correlation (increased by 0.19) and reduced the errors (root mean square error and relative error decreased by 1.71 mm and 0.08 mm, respectively). FMP performed well under precipitation event cases, with an average difference of 0.24 mm from observed precipitation. The study realized the merging analysis of remote sensing precipitation data with varying precision and spatial resolution. Furthermore, a systematic merging precipitation scheme coupled with multiple algorithms of machine learning, geographic regression, and mathematical statistics was formed. This study provides a reference for merging precipitation at a regional scale, which can be applied to other study areas as a process-oriented scheme.

Alterations in gonadotropin, prolactin, androgen and estrogen receptor and steroidogenesis-associated gene expression in gander testes in relation to the annual period

Physiological mechanisms of seasonal changes in testicular function in birds are not fully elucidated. The balance between androgens and estrogens and testis sensitivity for gonadotropin and gonadal steroids are still unclear. The aim of the study was to examine: (1) the changes in circulating and intra-testicular steroid hormone levels and their relationship; (2) the mRNA expression of testicular gonadotropin, prolactin (PRL), progesterone (P4), androgen, and estrogen receptors, and (3) key steroidogenesis processes-related genes with immunofluorescent localization of aromatase in gander testes during the annual period. Testes from ganders (n = 25) in the first reproduction season were obtained at five breeding stages, i.e., prebreeding (PrB), peak of reproduction (PR), postbreeding (PoB), nonbreeding (NB), and onset of reproduction (OR). Males were kept under breeding conditions. It was found that plasma P4 levels decreased at the PoB and NB stages, whereas intra-testicular P4 was the highest in the NB stage. Intra-testicular estradiol (E2) levels were higher at the PoB and NB stages than the other stages, whereas testosterone (T) levels showed a nearly opposite pattern. The plasma estradiol–to–testosterone ratios were higher at the PrB, PoB and NB stages compared to other stages. The transcript abundances for luteinizing hormone receptor (LHR), PRL receptor (PRLR), estrogen receptor alpha (ERα), and estrogen receptor beta (ERβ) also change in testicular tissue during the annual period. Moreover, StAR mRNA expression was upregulated at the PoB and NB stages, and CYP11A1 transcript level was the highest at the PoB stage. Stage-dependent changes in the CYP19A1 mRNA and aromatase protein levels with higher abundances of transcript at PoB and NB stages and protein at the NB stage were observed. Localization and immunofluorescent signal intensity for aromatase also differed in relation to the examined stages. It may be suggested that differential E2 levels, as well as aromatase expression and localization across annual stages are responsible for the seasonal activation/inactivation stages of testis spermatogenesis in domestic ganders. These data strongly suggest a role of aromatase in the control of gander steroidogenesis as changes in this enzyme level are associated with alternation in gonadal steroid hormones. In addition, joint action with others hormones, like PRL and LH, seems to be important in the final effect of seasonal reproduction potential.

The spatial distribution and temporal trends of livestock damages caused by wolves in Europe

Wolf populations are recovering and expanding across Europe, causing conflicts with livestock owners. Here we compiled incident-based livestock damage data across 21 countries for the years 2018, 2019 and 2020, during which 39,262 wolf-caused incidents were reported from 470 administrative regions. We found substantial regional variation in all aspects of the data, including the primary target species, the density of damages, their seasonal distribution, and their temporal trend. More than half of the variation in damage densities across regions was explained by the area of extensively cultivated habitats occupied by wolves, namely natural grasslands and broad-leaved forests. Regional variation in husbandry practices and damage prevention, while difficult to quantify at a continental scale, appear important factors to further modulate these incidents. As illustrated with detailed data from Germany, a relationship between the number of wolf units and damages diminished over time, suggesting some adaptation of livestock owners and local authorities to their presence, for example by increasing prevention efforts. As we argue, temporal trends of damage incidents, which are robust to variation in data collection across regions, are thus informative about the local intensity of the wolf-human conflict. We estimated increasing trends for the majority of regions, reflecting the current expansion of wolves across the continent. Nonetheless, many of these increases were moderate and for more than one third of all regions, trends were negative despite growing wolf populations, thus indicating that wolf-livestock conflicts can be successfully mitigated with proper management.

A Fully Convolutional Network with Waterfall Atrous Spatial Pooling and Localized Active Contour Loss for Fish Segmentation

Accurate measurements and statistics of fish data are important for sustainable development of aqua-enviroment and marine fisheries. For data measurements and statistics, automatic segmentation of fish is one of key tasks. The fish segmentation however is a challenging task due to arterfacts in underwater images. In this study, we introduce a deep-learning approach, namely FCN-WRN-WASP for automatic fish segmentation from the underwater images. In particular, we introduce a computational-efficient variation called Waterfall Atrous Spatial Pooling (WASP) module into a Fully convolutional network with Wide ResNet baseline. We also proposed a loss function inspired from active contour approach that can exploit the local intensity information from the input image. The approach has been validated on the DeepFish data and the SIUM data set. The results are promissing for fish segmentation, with higher Intersection over Union (IoU) scores compared to state of the arts. The evaluation results showed that the incorporation of the image based active contour loss helps increase the segmentation performance. In addition, the use of the WASP in the architecture is effective especially for forground fish segmentation.

A microstructure-sensitive analytical solution for short fatigue crack growth rate in metallic materials

Short fatigue crack growth in engineering alloys is among the most prominent challenges in mechanics of materials. Owing to its microstructural sensitivity, advanced and computationally expensive numerical methods are required to solve for crack growth rate. A novel mechanistic analytical model is presented, which adopts a stored energy density fracture criterion. Full-field implementation of the model in polycrystalline materials is achieved using a crystallographic crack-path prediction method based on a local stress intensity factor term. The model is applied to a range of Zircaloy-4 microstructures and demonstrates strong agreement with experimental rates and crack paths. Growth rate fluctuations across individual grains and substantial texture sensitivity are captured using the model. More broadly, this work demonstrates the benefits of mechanistic analytical modelling over conventional fracture mechanics and recent numerical approaches for accurate material performance predictions and design. Additionally, it offers a significant computer processing time reduction compared with state-of-the-art numerical methods.

Invisible economy, performance assessment of local governments, and environmental regulation in China.

Currently, environmental regulation in China is characterized by partial improvement and overall deterioration of the environment. To investigate the impact of China's environmental regulation on the country's environment, we consider the invisible economy by constructing a Stackelberg game model between local governments and polluting enterprises based on the Chinese institutional structure. We derive the following findings: (1) Increasing the invisible economic production scale causes the enterprise to reduce the pollution control level, resulting in increasing total pollutant emissions. Increasing the invisible economy production scale increases the enterprise's profit but undermines the utility of the local government. (2) The higher the proportion of environmental performance in the performance assessment of the local government is, the greater is the incentive for the local government to regulate the environment, which can force the enterprise to improve the pollution control level. However, there is an inefficient range for the proportion of environmental performance. (3) The lenient the pollutant emissions limit is, the weaker is the local government's environmental regulation intensity and the enterprise's pollution control level. (4) The higher the unit fine levied on the enterprise for excessive emissions is, the lower is the environmental regulation intensity of the local government, which can bring about improvement in the enterprise's pollution control level and reduction in total pollutant emissions. The results of the study have positive effects on sustainable environmental regulation in China under the invisible economy.

Improvement on Plasma Intensity Uniformity in Rectangular DC Magnetron Sputter by Optimizing Structures of Substrate Electrode

DC magnetron sputtering is widely used for thin film deposition in the field of displays. By adding magnet arrays to a large rectangular magnetron sputtering system, while the ionization and deposition rate are increased, the film properties can be nonuniform, and the local target erosion rate can be increased. Film properties strongly depend on uniform plasma density and energy. Although the ferromagnetic shield has been used to decrease the magnetic field locally, the plasma remains nonuniform at the corners of the rectangular shape target. In this study, a plasma simulation was conducted to analyze the plasma distribution in a DC magnetron sputtering system. The plasma uniformity was improved by optimizing the thickness and shape of the substrate electrode, carefully controlling the distance between the target and substrate electrode based on Paschen’s law, leading to the reduction of local high plasma intensity.

An Integrated Amplification-Free Digital CRISPR/Cas-Assisted Assay for Single Molecule Detection of RNA.

Conventional nucleic acid detection technologies usually rely on amplification to improve sensitivity, which has drawbacks, such as amplification bias, complicated operation, high requirements for complex instruments, and aerosol pollution. To address these concerns, we developed an integrated assay for the enrichment and single molecule digital detection of nucleic acid based on a CRISPR/Cas13a and microwell array. In our design, magnetic beads capture and concentrate the target from a large volume of sample, which is 100 times larger than reported earlier. The target-induced CRISPR/Cas13a cutting reaction was then dispersed and limited to a million individual femtoliter-sized microwells, thereby enhancing the local signal intensity to achieve single-molecule detection. The limit of this assay for amplification-free detection of SARS-CoV-2 is 2 aM. The implementation of this study will establish a "sample-in-answer-out" single-RNA detection technology without amplification and improve the sensitivity and specificity while shortening the detection time. This research has broad prospects in clinical application.

Uncertainty parameter weighted entropy-based fuzzy c-means algorithm using complemented membership functions for noisy volumetric brain MR image segmentation

In this paper, we propose an uncertainty parameter weighted entropy-based fuzzy c-means clustering algorithm for noisy volumetric (3D) brain MR image segmentation using complemented global and spatially constraint local membership functions. Due to inherent noise and intensity inhomogeneity (IIH), the acquired MR images have blurry tissue boundaries. This leads to a situation where uncertainty arises while labeling a pixel/voxel into its proper tissue region. Further, it magnifies in the regions of different tissue boundaries. The proposed algorithm addresses this issue by introducing a class-level uncertainty parameter for each voxel and weightedly incorporating in the fuzzy objective function using complemented global and spatially constraint local fuzzy membership functions. It also incorporates total uncertainties in the 3D image domain by means of Shannon entropy. The complemented local fuzzy membership function estimates the degree of non-association, constraint by the local region-level intensity distribution. This framework allows the algorithm to utilize the spatial intensity distribution both in locally and globally within the image domain and produce more accurate cluster prototypes. We validate the proposed algorithm qualitatively and quantitatively with 10 3D simulated brain MR images, contaminated by noise and intensity inhomogeneity, 4 volumes of clinical real patient 3D brain MR images and a synthetic 3D image with added Rician noise. The simulation results in several evaluation indices indicate its superiority over state-of-the-art algorithms developed in recent past.

Carbon-Free, Binder-Free MnO2@Mn Catalyst for Oxygen Reduction Reaction

Reasonable design and feasible preparation of low-cost and stable oxygen reduction reaction (ORR) catalysts with excellent performance play a key role in the development of fuel cells and metal-air batteries. A 3D porous superimposed nanosheet catalyst composed of metal manganese covered with MnO2 nanofilms (P-NS-MnO2@Mn) was designed and synthesized by rotating disk electrodes (RDEs) through one-step electrodeposition. The catalyst contains no carbon material. Therefore, the oxidation and corrosion of the carbon material during use can be avoided, resulting in excellent stability. The structural and composition characterizations indicate that the nanosheets with sharp edges exist on the surface of the wall surrounding the macropore (diameter ∼ 5.07 μm) and they connect tightly. Both the nanosheets and the wall of the macropore are composed of metal manganese covered completely with MnO2 film with a thickness of less than 5 nm. The half-wave potential of the synthesized P-NS-MnO2@Mn catalyst is 0.86 V. Besides, the catalyst exhibits good stability with almost no decay after a 30 h chronoamperometric test. Finite element analysis (FEA) simulation reveals the high local electric field intensity surrounding the sharp edges of the nanosheets. Density functional theory (DFT) calculations reveal that the novel nanosheet structure composed of MnO2 nanofilms covered on the surface of the Mn matrix accelerates the electronic transfer of the MnO2 nanofilms during the ORR process. The high local electric field intensity near the sharp edge of the nanosheets effectively promotes the orbital hybridization and strengthens the adsorbing Mn-O bond between the active site Mn in the nanosheets and the intermediate OOH* during the ORR process. This study provides a new strategy for preparing transition metal oxide catalysts and a novel idea about the key factors affecting the catalytic activity of transition metal oxides for the ORR.

High-Resolution Ultrasound Characterization of Local Scattering in Cancer Tissue.

Ultrasound (US) has afforded an approach to tissue characterization for more than a decade. The challenge is to reveal hidden patterns in the US data that describe tissue function and pathology that cannot be seen in conventional US images. Our group has developed a high-resolution analysis technique for tissue characterization termed H-scan US, an imaging method used to interpret the relative size of acoustic scatterers. In the present study, the objective was to compare local H-scan US image intensity with registered histologic measurements made directly at the cellular level. Human breast cancer cells (MDA-MB 231, American Type Culture Collection, Manassas, VA, USA) were orthotopically implanted into female mice (N=5). Tumors were allowed to grow for approximately 4 wk before the study started. In vivo imaging of tumor tissue was performed using a US system (Vantage 256, Verasonics Inc., Kirkland, WA, USA) equipped with a broadband capacitive micromachined ultrasonic linear array transducer (Kolo Medical, San Jose, CA, USA). A 15-MHz center frequency was used for plane wave imaging with five angles for spatial compounding. H-scan US image reconstruction involved use of parallel convolution filters to measure the relative strength of backscattered US signals. Color codes were applied to filter outputs to form the final H-scan US image display. For histologic processing, US imaging cross-sections were carefully marked on the tumor surface, and tumors were excised and sliced along the same plane. By use of optical microscopy, whole tumor tissue sections were scanned and digitized after nuclear staining. US images were interpolated to have the same number of pixels as the histology images and then spatially aligned. Each nucleus from the histologic sections was automatically segmented using custom MATLAB software (The MathWorks Inc., Natick, MA, USA). Nuclear size and spacing from the histology images were then compared with local H-scan US image features. Overall, local H-scan US image intensity exhibited a significant correlation with both cancer cell nuclear size (R2 > 0.27, p < 0.001) and the inverse relationship with nuclear spacing (R2 > 0.17, p < 0.001).

Local percolation of non-spherical particles in moving bed waste heat recovery unit for hydrogen production by methanol steam reforming

To study the local percolation of non-spherical particles in a moving bed waste heat recovery unit (MBWHRU) for hydrogen production, the discrete element method (DEM) was applied to simulate the discharge. A local method was applied to determine the location and local intensity of percolation. The percolation maps were presented. Moreover, the effects of structural parameters of MBWHRU, fine particle parameters, and friction parameters on local percolation were also considered. Percolation mainly occurs at the bottom, flow mechanism transition region, and near the vertical segment wall. Among them, percolation above the orifice is the most intense. The velocity gradient (or shear) is not the only condition under which percolation occurs. Percolation is closely related to changes in multiple parameters. The effects of fine particle parameters and friction parameters relative to structural parameters on percolation are significant. Percolation can be effectively avoided by increasing the mass percentage and particle size of fine particles, which is beneficial to hydrogen production. Especially, for the particle size ratio of fine particles to coarse particles greater than 0.5, percolation is no longer evident. The percolation near the vertical segment wall is particularly sensitive to particle-wall friction (>0.45). Reducing particle-particle friction and wall roughness is also beneficial to hydrogen production.