Fractal Dimension Research Articles

Dendritic copper nanostructures for ultrasensitive detection of rhodamine 6G and Congo red

Surface-Enhanced Raman Scattering (SERS) is a fast-responding and non-destructive ultra-sensitive detection technique that can replace traditional chromatographic and spectroscopic analysis techniques. In this experiment, dendritic copper nanostructures were prepared by the solid-state ionics method and the vacuum hot evaporation process with an applied current of I=9μA. Using them as a SERS substrate, Raman detection was performed on the dye molecules Rhodamine 6G (R6G) and Congo Red (CR) to determine SERS enhancement performance. It is found that the growth of the prepared copper nanostructures has a top-end dominant phenomenon. The fractal dimension of the copper nanostructure was calculated using fractal theory, and it was revealed to be 1.560. Scanning electron microscopy (SEM) results showed that a large number of 60-80 nm regularly arranged copper nanoparticles were attached to the surface of the dendritic copper nanostructure. This is beneficial to increase the surface roughness of the substrate and improve the detection level of dye molecules. Subsequently, copper nanostructures can sensitively detect R6G and CR solutions as low as 1×10-13 mol/L and 1×10-7 mol/L, reaching single-molecule levels. The Raman mapping experiment showed that the mean relative standard deviation (RSD) values of R6G and CR were 12.3% and 12.9%, indicating high uniformity and reproducibility of the structure. This structure effectively achieves the fusion of uniformity, repeatability, and sensitivity, and shows broad application prospects in food detection.

A model characterising the fractal supercritical adsorption behaviour of methane in shale: Incorporating principles, methods, and applications

The pore structure of shale is patently heterogeneous, with a conventional adsorption model being difficult to characterise the complex adsorption behavior of methane in shale. Therefore, a model is being proposed to characterise the fractal supercritical adsorption behavior of methane in shale. The principles and derivation of the model have been described in detail. The results showed that the adsorption characteristic parameters relating to different scale pores were affected by temperature and fractal dimension to different degrees. In addition, the relationship between isosteric heat of adsorption (qst) and adsorption capacity of different samples revealed different trends. The absolute values of ΔS of FC-66 and FC-72 decreased linearly. This might have been because of the fact that the adsorption saturation’s inflection point, which caused a fall in the absolute value of the entropy change (ΔS), was not reached. Compared with traditional adsorption models, the proposed model could reflect menthane’s adsorption in shale more accurately. The research results provide theoretical support for the evaluation of deep shale gas reserves, including the optimisation of exploitation strategies.

Evolution of pore structure and cement composition during weathering of conglomerate at Mogao Grottoes in alkaline and arid regions, NW China

Numerous conglomerate grottoes have been excavated and preserved in the arid and alkaline regions of NW China. After millennia of weathering, these conglomerate grottoes have suffered from various weathering issues (such as seepage and collapse) that are internally governed by the distribution of pore networks and the degree of cementation. However, studies on conglomerate weathering have mostly been reported in humid and tropical climates, where intensive chemical weathering occurs. Additionally, characterizations of pore evolution during conglomerate weathering have been restricted due to limitations in detecting pore size and pore type using a single pore characterization method. To fill this gap, this study jointly used mercury intrusion porosimetry (MIP) and computed tomography (CT) to characterize the pore evolution process during conglomerate weathering at Mogao Grottoes, a world heritage site in NW China. Mineralogical, hydrological, mechanical and microscopic characterization were also conducted to understand the changes in compositions of bulk samples and cements during weathering. Results revealed that the majority of pores in conglomerate are concentrated in macropores > 5 μm, followed by mesopores and micropores. During weathering, volume fraction of macropores significantly increases and that of micropores decreases, with median/average pore diameters experiencing an 8- to 10-fold increase. Permeability, porosity and fractal dimension exhibited strong positive linear correlations with median/average pore diameters. Throughout weathering, the abundances of calcite and clay minerals show notable decrease, particularly in cements, resulting in an enrichment of feldspars. Frequently occurring sand-carrying wind activities and salt weathering in arid regions are inferred to be responsible for the major cement loss and porosity generation through physical processes. Our combined MIP-CT method for pore network characterization is also applicable to other lithologies with a wide range of pore sizes. The proposed mechanism of pore evolution and cementation failure provides a scientific base for protecting stone heritages in arid zones.

Fabrication and characterization of foam ceramics from recycled waste concrete powder and waste glass powder

Incorporating multi-solid wastes to prepare foam ceramics has attracted widespread attention due to its excellent characteristics and environmental protection. In this study, foam ceramics were prepared by sintering method using recycled waste concrete powder (RWCP) and waste glass power (WGP) as the major material, Na2CO3 as foaming agent and borax as fluxing agent. The effect of sintering temperature on the physical properties and pore structure of foam ceramics were studied. The phase transformation and reaction mechanism were also discussed. The results reveal that when the RWCP content was 40%, the WGP content was 60% and the sintering temperature was 890 °C, the foam ceramics showed the best overall performance. The compressive strength, bulk density, water absorption and porosity were 2.39MPa, 0.83g/cm3, 8.27% and 66.68%, respectively. At this time, the pore size distribution was optimal, and mesopore occupied the vast majority. The fractal dimension of pore reached the minimum of 1.09. In addition, The XRD results showed that WGP and RWCP gradually depolymerized and reconstructed under the action of flux. Then the foam ceramics with mullite, pyroxene and wollastonite as the main phases were formed. The experimental results showed that it was feasible to prepare foam ceramics using RWCP. This study can provide a new train of thought for the reuse of RWCP.

Modulating the Electrical Transport in Superconducting NbC Crystals by Fractal Morphology.

The self-similar fractal morphology mediated by nonequilibrium processes is widely observed in low-dimensional materials grown by various techniques. Understanding how these fractal geometries affect the physical and chemical properties of materials and devices is crucial for both fundamental studies and various applications. In particular, the interplay between superconducting phase fluctuations and disorder can give rise to intriguing phenomena depending on the dimensionality. However, current experimental studies on low-dimensional superconductors are limited to two- and one-dimensional systems, leaving fractional dimensional systems largely unexplored. Here, we use chemical vapor deposition to successfully synthesize ultrathin NbC crystals with a well-defined fractal geometry at the nanoscale. By performing electrical transport measurements, we find that both the superconducting and normal-state properties are strongly affected in the fractal samples, where the intrinsic and geometric disorder is induced. In contrast to the 2D crystal, the fractal NbC crystals show a significant low-temperature resistive upturn before the onset of superconducting transition, which can be attributed to the disorder-enhanced electron-electron interaction effect. From transport data analysis, we demonstrate that the superconducting transition in NbC is correlated to the strength of disorder and the fractional dimensions, revealing that nanoscale fractal structures can significantly modify the electronic properties of low-dimensional superconductors. Our work paves the way for the explorations of mesoscopic transport and intriguing superconducting phenomena in fractional dimensions.

Utilizing unsupervised machine learning to uncover novel phenogroups within the broad QRS complex

Abstract Background Conduction disease can manifest as a broad QRS complex on the ECG. Broad QRS is conventionally categorised as left bundle branch block (LBBB) and right bundle branch block (RBBB) or non-specific intraventricular conduction delay (IVCD), based on QRS morphology. These subgroups were coined over a century ago and have been relevant for heart failure with reduced ejection fraction and cardiac resynchronization therapy (CRT). However, there may be more precise phenogroups underlying broad QRS complexes. Purpose Using unsupervised machine learning to define novel broad QRS phenogroups and characterise them using clinical variables and disease outcomes. Methods We extracted 51 relevant features using a Variational Autoencoder from 47,456 median-beat ECGs with broad QRS intervals (QRS ≥ 130ms) from a secondary care cohort. These were input into Discriminative Dimensionality Reduction via Learning a Tree (DDRTree), a clustering method that models the continuum of heterogeneity by projecting the underlying distribution as a tree structure in a low-dimensional space, while assigning distinct branch/cluster labels. Results Six distinct phenogroups were identified within broad QRS morphologies (Figure-1). Two branches were RBBB dominant (Branch 1: more males, high-comorbidity; Branch 6: low-comorbidity/healthy-RBBB). Two branches were LBBB dominant (Branch 4: mixed IVCD with CHB burden; Branch 5: more females, CRT responders). Two branches were IVCD/mixed-phenotype (Branch 2: IVCD-dominant, high risk of future cardiovascular events; Branch 3: average/core branch). Within LBBB, Branch 4 and 5 showed similar trends with improving echocardiography profiles and CRT response when adjusted for covariates, each compared against the core branch. Branch 5 was distinct due its high risk of future HF (HR 1.19 [1.07-1.33] p < 0.01), cardiovascular death (HR 1.35 [1.20-1.50] p < 0.0001), all-cause mortality (HR 1.08 [1.01-1.16] p < 0.05) and CHB (HR 1.35 [1.16-1.56] p < 0.0001) (Figure-2). Conversely within RBBB, Branch 1 and 6 showed stark differences across various traits. Branch 1 captured a high-risk profile associated to higher risk of cardiovascular death (HR 1.37 [1.24-1.52] p < 0.0001), all-cause mortality (HR 1.20 [1.12-1.29] p < 0.0001) and CHB (HR 1.15 [1.01-1.32] p < 0.05) (Figure-2), while Branch 6 retained a low-risk phenotype. The tree dimensions also revealed relevant trends in cardiac anatomy and valvular dysfunction; the top-left region in Figure-1 associated with higher left ventricular ejection fraction and lower left ventricular end-diastolic dimension, lower left ventricular end-systolic dimension and a greater CRT response. Conclusion Through unsupervised methods we have identified conduction disease phenogroups with additive value for disease prognosis and CRT response prediction beyond traditional LBBB and RBBB labels. These novel phenogroups may help guide precision care for patients with a broad QRS complex.Figure-1Figure-2

Predictors for mitral regurgitation improvement in patients with pure severe aortic regurgitation undergoing transcatheter aortic valve replacement: when can kill two birds with one stone?

Abstract Objective Transcatheter aortic valve replacement (TAVR) has been recognized as a significant treatment for pure severe aortic regurgitation (PSAR). Part of patients with PSAR concurrently suffer from functional mitral regurgitation (FMR). Whether TAVR could improve FMR in patients with PSAR and the predictors have not yet been clarified. This study aims to explore predictors of FMR improvement in patients with PSAR undergoing TAVR and subsequently provide evidence for further clinical therapy. Method Patients with PSAR and FMR who underwent TAVR at Zhongshan Hospital Affiliated with Fudan University were enrolled from June 2021 to August 2023. Depending on whether FMR improved one month post-TAVR, they were divided into groups with or without FMR improvement. The baseline data, imaging results, and follow-up data of the patients were collected. Result This study included 75 patients, among whom 38 patients had improved FMR and 37 patients did not. Compared to patients without FMR improvement, more patients in the FMR-improved group were diagnosed with renal insufficiency (10.8% vs. 0%, p=0.018), left bundle branch block (8.1% vs. 0%, p= 0.037), and less right bundle branch block (0% vs. 10.5%, p=0.017). The transthoracic ultrasound examination showed that patients with FMR improvement were prone to have lower left ventricular ejection fraction (LVEF) and larger left ventricle end dimension diastole (LVEDd). A higher proportion of patients in the FMR-improved group were found to have had more moderate to severe FMR (28.9% vs. 2.7%, P=0.029). In both groups, the degree of aortic regurgitation was significantly improved during the 1-day and 1-month follow-ups post-TAVR (p<0.001). No significant differences were found in the incidence of postoperative adverse events between the two groups during the short-term follow-up. Conclusion FMR improvement is observed in approximately half of PSAR patients undergoing TAVR. A higher FMR degree, lower LVEF, and hypertension before TAVR are independent predictors of FMR improvement.Figure 1 AR and MR post TAVRTable 1 Logistic regression

Genetic and phenotypic architecture of biventricular trabeculation

Abstract Introduction Cardiac trabeculae form a network of muscular strands that line the inner surfaces of the heart, and their development involves molecular pathways that regulate structural complexity. Excessive or hypertrabeculation occurs as part of normal variation in apparently healthy individuals, as an adaptation to altered loading conditions, and is observed in patients with cardiomyopathies (CMs) and heart failure (HF). Purpose In adults, trabeculation is not a prognostic factor independent of the underlying myocardial disease but may play a role in the natural history of ventricular remodelling. We sought to (i) understand the genetic and non-genetic determinants of trabeculation, (ii) understand its role in the causality of disease, and (iii) evaluate trabeculation as a biomarker for diagnosis and stratification. Methods We report genes with a burden of rare variants and novel common variant associations across the allele frequency spectrum for biventricular trabecular morphology in 47,803 participants of the UK Biobank using fractal dimension analysis of cardiac imaging (Figure 1). We assessed environmental modifiers of trabecular morphology, correlation with cardiac traits, phenome-wide association studies, and the relationship with the progression of CMs and HF. Results We identified a burden of trabeculation-associated rare variants in genes that regulate myocardial contractility and cardiac development and GWAS identified novel loci near genes implicated in CMs, conduction traits, and signalling pathways that define the early development of trabeculation. For example, we identified 56 genes with a burden of rare variants and 68 novel loci from GWAS (e.g., CASQ2, CACNA1C, MYBPC3, MYH7, NKX2-5, NOTCH1, TBX20) for the left ventricle. The strongest imaging relationships with trabeculation were with measures of volume and strain. Modifiers of trabeculation included African ancestry, alcohol intake, and physical activity. Carriers of CM-associated pathogenic variants had increased trabeculation. Of participants with CM reported after imaging, 25% had hypertrabeculation on imaging and hypertrabeculation was a risk factor for a subsequent diagnosis of HF (HR=1.3), mitral valve disorders (HR=1.4), bundle branch block (HR=1.2). Comparisons of biventricular trabeculation showed similarities in trabeculation across the ventricles in CM. Reduced right ventricular trabeculation and end-diastolic volume associated with Type-2 diabetes. Conclusions These data provide new insights into the mechanisms that regulate structural complexity in the heart. Changes in trabeculation may occur early in the pathogenesis of heart disease, can be modified by genes regulating pathways outside the sarcomere, and causality depends on the underlying cardiomyopathic substrate. Trabeculation progresses with cardiovascular disease, is a useful marker of remodelling, and identifies novel genetic modifiers of ventricular complexity.Figure 1

Predictive and Explainable Artificial Intelligence for Neuroimaging Applications

Background: The aim of this review is to highlight the new advance of predictive and explainable artificial intelligence for neuroimaging applications. Methods: Data came from 30 original studies in PubMed with the following search terms: “neuroimaging” (title) together with “machine learning” (title) or ”deep learning” (title). The 30 original studies were eligible according to the following criteria: the participants with the dependent variable of brain image or associated disease; the interventions/comparisons of artificial intelligence; the outcomes of accuracy, the area under the curve (AUC), and/or variable importance; the publication year of 2019 or later; and the publication language of English. Results: The performance outcomes reported were within 58–96 for accuracy (%), 66–97 for sensitivity (%), 76–98 for specificity (%), and 70–98 for the AUC (%). The support vector machine and the convolutional neural network registered the best performance (AUC 98%) for the classifications of low- vs. high-grade glioma and brain conditions, respectively. Likewise, the random forest delivered the best performance (root mean square error 1) for the regression of brain conditions. The following factors were discovered to be major predictors of brain image or associated disease: (demographic) age, education, sex; (health-related) alpha desynchronization, Alzheimer’s disease stage, CD4, depression, distress, mild behavioral impairment, RNA sequencing; (neuroimaging) abnormal amyloid-β, amplitude of low-frequency fluctuation, cortical thickness, functional connectivity, fractal dimension measure, gray matter volume, left amygdala activity, left hippocampal volume, plasma neurofilament light, right cerebellum, regional homogeneity, right middle occipital gyrus, surface area, sub-cortical volume. Conclusion: Predictive and explainable artificial intelligence provide an effective, non-invasive decision support system for neuroimaging applications.

Artificial Intelligence-Based Segmentation and Classification of Plant Images with Missing Parts and Fractal Dimension Estimation

Existing research on image-based plant classification has demonstrated high performance using artificial intelligence algorithms. However, limited camera viewing angles can cause parts of the plant to be invisible in the acquired images, leading to an inaccurate classification. However, this issue has not been addressed by previous research. Hence, our study aims to introduce a method to improve classification performance by taking these limitations into account; specifically, we incorporated both segmentation and classification networks structured as shallow networks to expedite the processing times. The proposed shallow plant segmentation network (Shal-PSN) performs adversarial learning based on a discriminator network; and a shallow plant classification network (Shal-PCN) with applied residual connections was also implemented. Moreover, the fractal dimension estimation is used in this study for analyzing the segmentation results. Additionally, this study evaluated the performance of the proposed Shal-PSN that achieved the dice scores (DSs) of 87.43% and 85.71% with PlantVillage and open leaf image (OLID-I) open datasets, respectively, in instances where 40–60% of plant parts were missing. Moreover, the results demonstrate that the proposed method increased the classification accuracy from 41.16% to 90.51% in the same instances. Overall, our approach achieved superior performance compared to the existing state-of-the-art classification methods.

Hybrid Geopolymer Composites Based on Fly Ash Reinforced with Glass and Flax Fibers

This article’s aim is to analyze physical, mechanical, and fracture properties as well as the thermal investigation of geopolymer composites reinforced with flax, glass fiber, and also the hybrid combination of fibers. Two types of matrices were considered as composites matrices. The first composition was based on fly ash and river sand. The second matrix composition contained fly ash and glass spheres. The content of reinforcement was 1% by mass. Compressive strength and three-point bending fracture tests were performed. The values of fracture toughness and fracture energy were determined. The resonance method was used to verify the dynamic characteristics, such as the dynamic modulus of elasticity and the dynamic Poisson ratio. The results show that single-type fibers in composites based on fly ash and glass spheres did not affect compressive strength. However, introducing hybrid reinforcement increased compressive strength by about 10% compared to the reference specimens. Flax fibers and hybrid reinforcement ensured higher fracture toughness and energy. The results also revealed great potential for glass sphere application to geopolymer materials in terms of fracture mechanics and thermal properties. Despite the lower strength properties in relation to geopolymers based on sand aggregate, applying reinforced fibers into the composite with glass spheres enhanced the compressive strength compared to other materials. Materials modified with glass spheres have a thermal conductivity twice as low as that of materials containing river sand.

ScatterX： A software for fast processing of high-throughput small-angle scattering data

Abstract Scattering experiments become increasingly popular in modern scientific research, including the areas of materials, biology, chemistry, physics, etc. Besides, various types of scattering facilities have been developed recently, such as lab-based X-ray scattering equipment, national synchrotron facilities and large neutron facilities. These above-mentioned trends bring up fast-increasing data amounts of scattering data, as well as different scattering types (X-ray, neutron, laser and even microwaves). This struggles with data analysis software of the last generation, where data are usually analyzed assuming certain first-principle models and given data formats. To help researchers process and analyze scattering data more efficiently, we developed a general and model-free scattering data analysis software based on matrix operation, which has the unique advantage of high throughput scattering data processing, analysis and visualization. To maximize generality and efficiency, data processing is performed based on a three-dimensional matrix, where scattering curves are saved as matrices or vectors, rather than the traditional definition of paired values. It can not only realize image batch processing, background subtraction and correction, but also analyze data according to scattering theory and model, such as radius of gyration, fractal dimension and other physical quantities. In the aspect of visualization, the software allows the modify the color maps of two-dimensional scattering images and the gradual color variation of one-dimensional curves to suit efficient data communications. In all, this new software can work as a standalone platform for researchers to process, analyze and visualize scattering data from different research facilities without considering different file types or formats. All codes in this manuscript are open-sourced and can be easily implemented in matrix-based software, such as MATLAB, Python and Igor.

Fractional quantum mechanics meets quantum gravity phenomenology

Abstract This letter extends previous findings on the modified Schrödinger evolution inspired by quantum gravity phenomenology. By establishing a connection between this approach and fractional quantum mechanics, we provide insights into a potential deep infrared regime of quantum gravity, characterized by the emergence of fractal dimensions, similar to behaviors observed in the deep ultraviolet regime. Additionally, we explore the experimental investigations of this regime using Bose-Einstein condensates. Notably, our analysis reveals a direct implication of this analogy: general experiments probing fractional quantum mechanics may serve as equivalent models of quantum gravity. We identify instances of nonlocal behavior in such systems, suggesting an analogous phenomenon of nonlocality in quantum gravity.

Microvascular changes in eyes with non-proliferative diabetic retinopathy with or without macular microaneurysms: an OCT-angiography study.

To evaluate different quantitative non-invasive retinal biomarkers of microvascular impairment and neurodegeneration in patients affected by mild and moderate non proliferative diabetic retinopathy (NPDR) with or without macular microaneurysms (MAs). A cross-sectional case-control study. Ninety-seven eyes with NPDR, 49 with no central MAs and 48 with central MAs, underwent color fundus photography and optical coherence tomography (OCT)/OCT-angiography (OCT-A). Thickness of central macula, retinal nerve fiber layer (NFL), ganglion cell layer (GCL+) and NFL + GCL + was evaluated on OCT. FAZ metrics (ImageJ), perfusion and vessel density (PD/VD), and fractal dimension (FD) (MATLAB) were evaluated on 3 × 3 OCT-A slabs of both superficial and deep capillary plexuses (SCP/DCP). All evaluations were performed on the full image and after subdivision in 4 quadrants. In the MA group, 77 MAs were detected (45.5% in the DCP). The MA group showed: increased FAZ area and perimeter in the SCP (p < 0.01) and DCP (p = 0.02), and reduced circularity index in the SCP (p = 0.03); reduced VD in the SCP (p < 0.01) and reduced PD, VD (p < 0.01) and FD (p = 0.02) in the DCP; decreased VD and FD in the SCP (p = 0.02 and p = 0.05), and in VD and FD in the DCP in the inferior quadrant (p = 0.04 and p = 0.03); a decrease in VD in the SCP in the nasal quadrant (p = 0.05). No differences have been detected in OCT parameters. Our results suggest that the presence of central MAs in patients with NPDR may correlate with more pronounced macular microvascular impairment, particularly during the mild and moderate stages of the disease.

Study on the morphological characteristics of coal particle flocs under fractal theory

Based on fractal theory, the geometric size, surface morphology, and spatial structure of flocs in the hydrophobic flocculation process of coal particles were examined via particle size distribution detection, image analysis technology, and numerical simulation. The floc size distribution curve was classified and discussed via the dual-domain fractal rule, and the variation law of the composition and distribution of the coarse- and fine-grained coal particle flocs with the flocculation process was clarified. The various levels and characteristics of the floc growth geometry were explained by the analysis of the fractal dimension of the individual floc surface and the multiple spectra of the floc groups in the metallographic microscopy image. The hydrophobic flocculation process of coal particles was simulated via the diffusion-limited cluster aggregation model. The gyration fractal dimension was used to examine floc fragmentation and reconstruction and clarify the growth law of the floc spatial structure during the hydrophobic flocculation process.

An advanced closed-loop geothermal system to substantially enhance heat production

Heat production through conventional closed-loop geothermal systems is constrained by the limited contact area for heat exchange between rock formations and the wellbore. To address this challenge, an advanced closed-loop geothermal system (ACGS) is proposed to enhance heat production in this research. The ACGS incorporates a hydraulic fracture, partitioned by a horizontal insulator for vertical zonal isolation of fluid flow in the fracture, into the closed-loop system’s fluid circulation. To assess heat production from the ACGS, a three-dimensional ACGS numerical model is established and validated, utilized to simulate heat production through the ACGS under conditions of different fracture dimensions and structures, tubing materials, and fluid heat capacities. Performances of complicated fracture structures, including a branched fracture and a multiple-wing fracture, in improving heat production are evaluated. It is found that due to the incorporation of a double-wing fracture, the cumulative extracted heat of a closed-loop system over 20 years is enhanced by 162.94 %. Increasing fracture half-length and fracture height both enhances the heat production of the ACGS considerably. Polyurethane foam proves an excellent tubing material for the ACGS due to its low cost and outstanding adiabatic functionality. Compared with a multiple-wing fracture, a branched fracture results in better heat production through the ACGS, with more fracture branches leading to higher heat production. A branched fracture can improve the cumulative extracted heat from a closed-loop system over 20 years by 321.77 %, and increasing the inter-branch angle further enhances heat production. Working fluid with smaller heat capacity yields considerably higher outlet temperature.

Study on the evolution rules of coal deformation and failure characteristics caused by multiple mining disturbances

During coal mining operations, the coal will be deformed and damaged due to multiple mining disturbances (MMD), often resulting in disasters, like rock burst. To understand the evolution rules of coal deformation under MMD and its final fracture characteristics after impact dynamic load loading, reduce the adverse effects of mining disturbances, and improve disaster prevention and control capabilities, quasi-static uniaxial cyclic loading-unloading (L-U) and dynamic axial compression tests were conducted on large-sized coal-like samples. During the tests, three-dimensional (3D) laser scanning and acoustic emission (AE) monitoring technology were utilized to accurately capture the full-field deformation and AE response data, facilitating a systematic analysis of deformation and fracture characteristics. The results show that: (1) Under the cyclic L-U effect induced by MMD, each loading cycle causes compression deformation with partial recovery during unloading, presenting an overall “wavy” variation trend. (2) The maximum load is the most critical factor affecting the damaged coal deformation, with smaller load resulting in less overall sample deformation. (3) After the impact dynamic loading, the damaged samples suffered large-scale impact splitting failure, with the compressive-shear layer failure mainly occurred inside the holes. (4) Lower loading during cyclic L-U process correlate with reduced damage degree, and smaller debris particles with a higher fractal dimension when impact failure occurs, indicating a more severe impact failure. (5) With multiple cycles of L-U, the cracks inside the sample gradually extend and expand from around the hole to the outside. The greater the load and the number of cycles, the more serious the crack damage will be. (6) In the practical mining process, it is crucial to reinforce roadway interiors while minimizing low-loading cyclic disturbances induced by MMD. The study has obtained the deformation evolution rules and failure characteristics of coal under MMD, providing a theoretical basis for the prevention and control of corresponding engineering disasters.

Comparison of destructive and non-destructive fracture toughness measurements for Q235 steel butt-welded joint

As a critical component of a welded structure, the integrity of the welded joint significantly affects the safety and reliability of the structure in service. Therefore, it is essential to investigate the integrity of welded joints. However, given the harshness of standard measurements renders them unsuitable for application to small volume zones, welded structures or in-service structures. In this study, the fracture properties of a Q235 steel butt-welded joint was evaluated by boundary effect modelling (BEM) method and the ball indentation (BI) method. The results demonstrate that the fracture toughness distribution obtained by the two methods are consistent, with the highest fracture toughness in the weld metal, followed by the heat-affected zone and the base metal, and the lowest fracture toughness in the fusion zone, which is in agreement with the results of the metallographic testing. Furthermore, the relative errors of the zones obtained by the ball indentation method and the boundary effect modelling method ranging from 10.16 to 19.05%, which indicates safety margin ought to be considered for employing the BI method to determine fracture properties of in-service structures.

Fractal Strategy for Improving Characterization of N2 Adsorption–Desorption in Mesopores

The current studies primarily analyze the heterogeneity and complexity of mesopore structures based on low-temperature nitrogen (N2) adsorption curves and the Frenkel–Halsey–Hill (FHH) fractal model. However, these studies ignore the fact that the low-temperature N2 desorption curve can also reflect the desorption performance of the mesopore structure. In this research, novel fractal indicators for characterizing the adsorption–desorption performance of mesopores based on the fractal dimension from the N2 adsorption curves and N2 desorption curves are proposed. The novel fractal indicators I1 and I2 are applied to evaluate the adsorption–desorption performance of mesopores with pore size 2–5 nm and pore size 5–50 nm, respectively. The fractal indicator I1 shows an increasing trend with coalification, reflecting that the gas adsorption performance of 2–5 nm mesopores is enhanced with coalification. The fractal indicator I2 exhibits a trend of first increasing and then decreasing with coalification, indicating the gas desorption performance of mesopores with pore size 5–50 nm decreases first and then increases. The proposed indicators provide novel analytical parameters for further understanding the gas adsorption–desorption mechanism of porous coal-based or carbon-based materials.

Evaluation of cyst treatment technique, cyst type, size differences and healing by fractal analysis

AimThe aim of the study was to evaluate the trabeculation increase of treated mandibular cysts.Material and methodThe study included 26 female and 33 male patients (age mean: 38,4 years) with cysts larger than 3 cm in the posterior region of the mandible who were admitted to the same center. Two groups in treatment technique: marsupialization (n = 29) and enucleation (n = 30). Four groups in cyst types: dentigerous cyst (n = 21), keratocyst (n = 19), radicular cyst (n = 15) and residual cyst (n = 4). Cyst size was divided into two categories: smaller than 5.5 cm (n = 31) and larger than 5.5 cm (n = 28). Panoramic radiographs (PR) of the patients were analyzed at the beginning, 6. month and 12. month.ResultAt the end of the treatment, there was no statistically significant difference in terms of Fractal Analysis (FA) between patients treated with marsupialization and enucleation, but considering that the cysts in the marsupialization group were larger in size, a faster increase in FA was observed in the marsupialization group. When the cysts were grouped according to their size, it was observed that healing tissues in cysts smaller than 5.5 cm reached normal FA values faster, while healing in the middle of cysts larger than 5.5 cm took more time.ConclusionsFA is a reproducible and reliable method. In large cysts, marsupialization results in a faster recovery, but FA values at the end of treatment are similar to the enucleation group. Cysts larger than 5.5 cm show a more rapid increase in Fractal Dimension (FD). The centre of the cysts is the area that heals the latest. Studies with larger sample sizes are needed to evaluate the difference in healing between cyst types.Clinical trial numberClinical trial number: Not applicable