Irregular Distribution Research Articles

Repeat-based holocentromeres of the woodrush Luzula sylvatica reveal insights into the evolutionary transition to holocentricity

In most studied eukaryotes, chromosomes are monocentric, with centromere activity confined to a single region. However, the rush family (Juncaceae) includes species with both monocentric (Juncus) and holocentric (Luzula) chromosomes, where centromere activity is distributed along the entire chromosome length. Here, we combine chromosome-scale genome assembly, epigenetic analysis, immuno-FISH and super-resolution microscopy to study the transition to holocentricity in Luzula sylvatica. We report repeat-based holocentromeres with an irregular distribution of features along the chromosomes. Luzula sylvatica holocentromeres are predominantly associated with two satellite DNA repeats (Lusy1 and Lusy2), while CENH3 also binds satellite-free gene-poor regions. Comparative repeat analysis suggests that Lusy1 plays a crucial role in centromere function across most Luzula species. Furthermore, synteny analysis between L. sylvatica (n = 6) and Juncus effusus (n = 21) suggests that holocentric chromosomes in Luzula could have arisen from chromosome fusions of ancestral monocentric chromosomes, accompanied by the expansion of CENH3-associated satellite repeats.

Enhancing high-resolution reconstruction of flow fields using physics-informed diffusion model with probability flow sampling

The application of artificial intelligence (AI) technology in fluid dynamics is becoming increasingly prevalent, particularly in accelerating the solution of partial differential equations and predicting complex flow fields. Researchers have extensively explored deep learning algorithms for flow field super-resolution reconstruction. However, purely data-driven deep learning models in this domain face numerous challenges. These include susceptibility to variations in data distribution during model training and a lack of physical and mathematical interpretability in the predictions. These issues significantly impact the effectiveness of the models in practical applications, especially when input data exhibit irregular distributions and noise. In recent years, the rapid development of generative artificial intelligence and physics-informed deep learning algorithms has created significant opportunities for complex physical simulations. This paper proposes a novel approach that combines diffusion models with physical constraint information. By integrating physical equation constraints into the training process of diffusion models, this method achieves high-fidelity flow field reconstruction from low-resolution inputs. Thus, it not only leverages the advantages of diffusion models but also enhances the interpretability of the models. Experimental results demonstrate that, compared to traditional methods, our approach excels in generating high-resolution flow fields with enhanced detail and physical consistency. This advancement provides new insights into developing more accurate and generalized flow field reconstruction models.

A Strip Steel Surface Defect Salient Object Detection Based on Channel, Spatial and Self-Attention Mechanisms

Strip steel is extensively utilized in industries such as automotive manufacturing and aerospace due to its superior machinability, economic benefits, and adaptability. However, defects on the surface of steel strips, such as inclusions, patches, and scratches, significantly affect the performance and service life of the product. Therefore, the salient object detection of surface defects on strip steel is crucial to ensure the quality of the final product. Many factors, such as the low contrast of surface defects on strip steel, the diversity of defect types, complex texture structures, and irregular defect distribution, hinder existing detection technologies from accurately identifying and segmenting defect areas against complex backgrounds. To address the above problems, we propose a novel detector called S3D-SOD for the salient object detection of strip steel surface defects. For the encoding stage, a residual self-attention block is proposed to explore semantic information cues of high-level features to locate and guide low-level feature information. In addition, we apply a general residual channel and spatial attention to low-level features, enabling the model to adaptively focus on the key channels and spatial areas of feature maps with high resolutions, thereby enhancing the encoder features and accelerating the convergence of the model. For the decoding stage, a simple residual decoder block with an upsampling operation is proposed to realize the integration and interaction of feature information between different layers. Here, the simple residual decoder block is used for feature integration due to the following observation: backbone networks like ResNet and the Swin Transformer, after being pretrained on the large dataset ImageNet and then fine-tuned on a smaller dataset for strip steel surface defects, are capable of extracting feature maps that contain both general image features and the specific characteristics required for the salient object detection of strip steel surface defects. The experimental results on the SD-saliency-900 dataset show that S3D-SOD is better than advanced methods, and it has strong generalization ability and robustness.

Synthesis and characterization of bacterial cellulose composite with graphite and TiO2-ZnO: structural and functional analysis

This research aims to synthesize and characterize a bacterial cellulose (BC)-based composite with graphite and TiO2-ZnO as reinforcement materials using ex-situ synthesis with CTAB as a surfactant. FTIR and SEM-EDS analysis revealed interactions between the matrix and the reinforcement materials, as well as irregular particle distribution in the BC/G-TiO2-ZnO composite. The addition of graphite to BC significantly increased the conductivity of the composite, while the addition of TiO2-ZnO had the opposite effect. The mechanical properties of the composite exhibited an inverse relationship with the conductivity parameter. Swelling tests indicated that pH and the addition of CTAB influenced the swelling behavior of the BC-based composite. The results of this study provide a strong foundation for the development of potential applications in the fields of electronics and pollutant filtration. The synthesis of this composite aims to harness the unique properties of BC, graphite, and TiO2-ZnO, creating a multifunctional material with potential uses in flexible electronics, sensors, biocompatible conductive materials, and advanced filtration systems.

Characterizing southeast Greenland fjord surface ice and freshwater flux to support biological applications

Abstract. Southeast Greenland (SEG) is characterized by complex morphology and environmental processes that create dynamic habitats for top marine predators. Active glaciers producing solid-ice discharge, freshwater flux, offshore sea ice transport, and seasonal landfast-ice formation all contribute to a variable, transient environment within SEG fjord systems. Here, we investigate a selection of physical processes in SEG to provide a regional characterization that reveals physical system processes and supports biological research. SEG fjords exhibit high fjord-to-fjord variability regarding bathymetry, size, shape, and glacial setting, influencing some processes more than others. For example, during fall, the timing of offshore sea ice formation near SEG fjords progresses temporally when moving southward across latitudes, while the timing of offshore sea ice disappearance is less dependent on latitude. The rates of annual freshwater flux into fjords, however, are highly variable across SEG, with annual average input values ranging from ∼ 1 × 108 to ∼ 1.25 × 1010 m3 (∼ 0.1–12.5 Gt) for individual fjords. Similarly, the rates of solid-ice discharge in SEG fjords vary widely – partly due to the irregular distribution of active glaciers across the study area (60–70° N). Landfast sea ice, assessed for eight focus fjords, is seasonal and has a spatial distribution highly dependent on individual fjord topography. Conversely, glacial ice is deposited into fjord systems year-round, with the spatial distribution of glacier-derived ice depending on the location of glacier termini. As climate change continues to affect SEG, the evolution of these metrics will vary individually in their response, and next steps should include moving from characterization to system projection. Due to the projected regional ice sheet persistence that will continue to feed glacial ice into fjords, it is possible that SEG could remain a long-term refugium for polar bears and other ice-dependent species on a centennial to millennial scale, demonstrating a need for continued research into the SEG physical environment.

Effects of weed management on soil metagenomic composition in cultivated chickpea fields

Abstract Non-chemical methods, including mechanical and manual weed management are important for improving crop yields and preserving soil microbial diversity. In Tunisia, chickpea cultivation uses a combination of these methods to suppress weeds. This study aimed to evaluate the impact of weeding practices on chickpea (Cicer arietinum L. cultivar REBHA) yield and soil microbial diversity. Field experiments were conducted at the Technical Center for Biological Agriculture in Essaida, Tunisia, using six plots with manual and no weeding treatments. Chickpea yield was measured, and soil samples were collected for metagenomic analysis. Floristic surveys identified 13 weed species, with Chenopodium album L., Rumex acetosa L., and Urtica dioica L. being the most dominant. Seed yield ranged from 23.2 to 26.2 qls/ha in non-weeded plots and from 25.1 to 30.1 qls/ha in weeded plots, showing an increase in yield (11.75%) with manual weeding.
Soil metagenomics revealed changes in bacterial community composition between the two treatments. The dominant phylum was Pseudomonadota, whose relative abundance increased from 24.88% in non-weeded plots to 34.76% in weeded plots. Alpha diversity indices showed lower species richness and diversity in weeded soils, with 62000 OTUs in weeded plots compared to 43202 OTUs in non-weeded plots. Betaproteobacteria and Alphaproteobacteria exhibited higher OTU counts in weeded soils. The Simpson diversity index was lower in non-weeded soils (0.025) than in weeded soils (0.075), indicating a more irregular microbial distribution in non-weeded plots. Thus, manual weeding improved chickpea yield and altered the soil bacterial community, increasing diversity in key microbial taxa. This study highlights the complex interaction between weed management practices and soil microbial ecosystems, which may influence crop productivity.

CytoNet: an efficient dual attention based automatic prediction of cancer sub types in cytology studies

Computer-assisted diagnosis (CAD) plays a key role in cancer diagnosis or screening. Whereas, current CAD performs poorly on whole slide image (WSI) analysis, and thus fails to generalize well. This research aims to develop an automatic classification system to distinguish between different types of carcinomas. Obtaining rich deep features in multi-class classification while achieving high accuracy is still a challenging problem. The detection and classification of cancerous cells in WSI are quite challenging due to the misclassification of normal lumps and cancerous cells. This is due to cluttering, occlusion, and irregular cell distribution. Researchers in the past mostly obtained the hand-crafted features while neglecting the above-mentioned challenges which led to a reduction of the classification accuracy. To mitigate this problem we proposed an efficient dual attention-based network (CytoNet). The proposed network is composed of two main modules (i) Efficient-Net and (ii) Dual Attention Module (DAM). Efficient-Net is capable of obtaining higher accuracy and enhancing efficiency as compared to existing Convolutional Neural Networks (CNNs). It is also useful to obtain the most generic features as it has been trained on ImageNet. Whereas DAM is very robust in obtaining attention and targeted features while negating the background. In this way, the combination of an efficient and attention module is useful to obtain the robust, and intrinsic features to obtain comparable performance. Further, we evaluated the proposed network on two well-known datasets (i) Our generated thyroid dataset (ii) Mendeley Cervical dataset (Hussain in Data Brief, 2019) with enhanced performance compared to their counterparts. CytoNet demonstrated a 99% accuracy rate on the thyroid dataset in comparison to its counterpart. The precision, recall, and F1-score values achieved on the Mendeley Cervical dataset are 0.992, 0.985, and 0.977, respectively. The code implementation is available on GitHub. https://github.com/naveedilyas/CytoNet-An-Efficient-Dual-Attention-based-Automatic-Prediction-of-Cancer-Sub-types-in-Cytol.

Impact of Various High Intensity Earthquake Characteristics on the Inelastic Seismic Response of Irregular Medium-Rise Buildings

In the twenty-first century, the seismic design of buildings seems to have become a fully recognized topic. There are guidelines and standards which should be taken into account by designers in seismic areas. Designers using modern international guidelines have ascertained that the behavior of structures is not as expected. New challenges in the construction industry result in the construction of structures with new, unusual shapes. These are structures that do not meet the assumptions of safe construction in seismic areas. Contemporary buildings are also characterized by their irregular distribution of structural elements. Such solutions are not beneficial from the point of view of seismic engineering and can lead to reduced dynamic resistance and damage in such structures. In this paper, a five-storey, irregular-shaped reinforced concrete (RC) building model was subjected to different earthquakes with varying magnitudes, PGA (peak ground acceleration) and PGV (peak ground velocity) values, and durations of the intense shock phase. Once the model was verified using previous in situ measurements, the building model was subjected to five earthquakes. A numerical nonlinear analysis of the building was performed using a verified FEA (finite element analysis) model in the time domain through non-linear time history analysis with the Broyden–Fletcher–Goldfarb–Shanno (BFGS) method. The building’s dynamic properties were measured using various methods of excitation. The model was influenced, among others, by two far-field representative events caused by the last earthquake in Turkey, which resulted in strong ground motion. The analysis results identified the locations of structural damage and allowed for the assessment of the structure’s dynamic resistance. The results of the calculations prove that the duration of the intensive phase of extortion is one of the reasons for building damage in earthquake-prone areas. Building damage occurs with earthquakes that are characterized by an intensive phase of excitation with a long duration and high values of velocity in the earthquake components. The article highlights the inadequate dynamic resistance of the building, leading to excessive displacements and unfavorable structural solutions. Damage to buildings at this earthquake intensity caused damage to the load-bearing structure, which was not designed for such intensities. This paper is a research report with a specific case study of medium-rise irregular RC buildings.

Vegetative Index Intercalibration Between PlanetScope and Sentinel-2 Through a SkySat Classification in the Context of “Riserva San Massimo” Rice Farm in Northern Italy

Rice farming in Italy accounts for about 50% of the EU’s rice area and production. Precision agriculture has entered the scene to enhance sustainability, cut pollution, and ensure food security. Various studies have used remote sensing tools like satellites and drones for multispectral imaging. While Sentinel-2 is highly regarded for precision agriculture, it falls short for specific applications, like at the “Riserva San Massimo” (Gropello Cairoli, Lombardia, Northern Italy) rice farm, where irregularly shaped crops need higher resolution and frequent revisits to deal with cloud cover. A prior study that compared Sentinel-2 and the higher-resolution PlanetScope constellation for vegetative indices found a seasonal miscalibration in the Normalized Difference Vegetation Index (NDVI) and in the Normalized Difference Red Edge Index (NDRE). Dr. Agr. G.N. Rognoni, a seasoned agronomist working with this farm, stresses the importance of studying the radiometric intercalibration between the PlanetScope and Sentinel-2 vegetative indices to leverage the knowledge gained from Sentinel-2 for him to apply variable rate application (VRA). A high-resolution SkySat image, taken almost simultaneously with a pair of Sentinel-2 and PlanetScope images, offered a chance to examine if the irregular distribution of vegetation and barren land within rice fields might be a factor in the observed miscalibration. Using an unsupervised pixel-based image classification technique on SkySat imagery, it is feasible to split rice into two subclasses and intercalibrate them separately. The results indicated that combining histograms and agronomists’ expertise could confirm SkySat classification. Moreover, the uneven spatial distribution of rice does not affect the seasonal miscalibration object of past studies, which can be adjusted using the methods described here, even with images taken four days apart: the first method emphasizes accuracy using linear regression, histogram shifting, and histogram matching; whereas the second method is faster and utilizes only histogram matching.

Emerging roles of cancer-associated histone mutations in genomic instabilities.

Epigenetic mechanisms often fuel the quick evolution of cancer cells from normal cells. Mutations or aberrant expressions in the enzymes of DNA methylation, histone post-translational modifications, and chromatin remodellers have been extensively investigated in cancer pathogenesis; however, cancer-associated histone mutants have gained momentum in recent decades. Next-generation sequencing of cancer cells has identified somatic recurrent mutations in all the histones (H3, H4, H2A, H2B, and H1) with different frequencies for various tumour types. Importantly, the well-characterised H3K27M, H3G34R/V, and H3K36M mutations are termed as oncohistone mutants because of their wide roles, from defects in cellular differentiation, transcriptional dysregulation, and perturbed epigenomic profiles to genomic instabilities. Mechanistically, these histone mutants impart their effects on histone modifications and/or on irregular distributions of chromatin complexes. Recent studies have identified the crucial roles of the H3K27M and H3G34R/V mutants in the DNA damage response pathway, but their impacts on chemotherapy and tumour progression remain elusive. In this review, we summarise the recent developments in their functions toward genomic instabilities and tumour progression. Finally, we discuss how such a mechanistic understanding can be harnessed toward the potential treatment of tumours harbouring the H3K27M, H3G34R/V, and H3K36M mutations.

Bio-mechanical analysis of porous Ti-6Al-4V scaffold: a comprehensive review on unit cell structures in orthopaedic application.

A scaffold is a three-dimensional porous structure that is used as a template to provide structural support for cell adhesion and the formation of new cells. Metallic cellular scaffolds are a good choice as a replacement for human bones in orthopaedic implants, which enhances the quality and longevity of human life. In contrast to conventional methods that produce irregular pore distributions, 3D printing, or additive manufacturing, is characterized by high precision and controlled manufacturing processes. AM processes can precisely control the scaffold's porosity, which makes it possible to produce patient specific implants and achieve regular pore distribution. This review paper explores the potential of Ti-6Al-4V scaffolds produced via the SLM method as a bone substitute. A state-of-the-art review on the effect of design parameters, material, and surface modification on biological and mechanical properties is presented. The desired features of the human tibia and femur bones are compared to bulk and porous Ti6Al4V scaffold. Furthermore, the properties of various porous scaffolds with varying unit cell structures and design parameters are compared to find out the designs that can mimic human bone properties. Porosity up to 65% and pore size of 600 μm was found to give optimum trade-off between mechanical and biological properties. Current manufacturing constraints, biocompatibility of Ti-6Al-4V material, influence of various factors on bio-mechanical properties, and complex interrelation between design parameters are discussed herein. Finally, the most appropriate combination of design parameters that offers a good trade-off between mechanical strength and cell ingrowth are summarized.

Synergistic impact of lanthanum and cerium co-doping ZnO for improved photocatalytic rhodamine B degradation efficiency under UV light

In this study, the influence of different La and Ce co-doping amounts on the structural, morphological, optical, and photodegradation properties of ZnO nanostructures was evaluated. Zn1-2xLaxCexO nanoparticles (NPs) were prepared using sol-gel auto-ignition process, where x = 0.00 (pure ZnO), 0.01 (LC1), 0.03 (LC3), and 0.05 (LC5). The X-ray diffraction (XRD) and Raman results revealed that the prepared ZnO NPs crystallize in the hexagonal wurtzite structure. The size of crystallites is affected by the increment of La and Ce and it decreased from 24.29 nm to 10.40 nm with the increase in the concentration of La and Ce. Transmission electron microscopy (TEM) showed that the samples exhibit an irregular distribution of NPs with a dominant spherical shape morphology. The simultaneous incorporation of La and Ce in ZnO NPs led to a slight variation in the absorption edge and a slight shift in the values of the band gap energy from 3.20 to 3.24 eV. Furthermore, a reduction in the recombination rate of photogenerated charge carriers and the creation of fewer additional defects upon the appropriate insertion of Ce and La ions are highlighted by the analysis of photoluminescence spectra, Nyquist plots, and transient photocurrent measurements. The photocatalytic activity of samples was evaluated against rhodamine B organic dye under UV light irradiation. The analysis showed that LC1 sample exhibited superior photocatalytic performance with 99.1% degradation efficiency and a degradation rate constant of 0.0762 min-1. This enhancement has been ascribed to the surface defects and the optimized crystallite size achieved, which help to generate reactive entities such as •OH and O2•− in addition to the great role of holes (h+) and impede the recombination of charge carriers e-/h+.

A novel process approach of a circular economy practice in the production of hydroxyapatite from phosphogypsum

Phosphogypsum (PG), a by-product of phosphate fertilizer industry, is chemically impure gypsum (CaSO4 · 2 H2O) containing phosphate residues. Provided by the calcium and phosphorus content, PG can be considered as a precursor for synthetic hydroxyapatite (s-HAp) production. This study proposes a two-step alkali route for s-HAp production from PG. Resulting samples were characterized by ICP-OES, SEM, XRD and FT-IR analyses in comparison with bone ash (BA) sample. Ca/P ratio (wt%) was determined as 2.46 and 2.78 for s-HAp and BA samples, respectively. SEM analysis showed the uniform distribution of spherical shaped particles in BA samples; however s-HAp particles showed irregular distribution of nearly spherical-like particles agglomerated as platelets on the surface. XRD analysis indicated that s-HAp particles possessed low crystallinity and ICDD references showed the appearance of apatite-CaOH phases. FT-IR spectrum showed the vibration bands of PO4 3− bands in the range of 1018–601 cm−1. According to characterization analyses, s-HAp samples show lower Ca/P ratio, irregular morphology, and low crystallinity due to possible impurities. Thus, further downstream operations regarding to impurity removal should be employed to develop a promising route to synthetic HAp production and employ a CE approach on industrial scale to evaluate s-HAp samples as a commercial substitute to BA.

Ambiguous landscapes: A framework for assessing robustness and uncertainties in archaeological point pattern analysis.

Landscape research in archaeology has greatly benefited from the increasing application of computational methods over the last decades. Spatial statistical methods such as point pattern analysis have been particularly revolutionary. Archaeologists have used point pattern analysis to explore spatial arrangements and relations between 'points' (e.g., locations of artefacts or archaeological sites). However, the results obtained from these techniques can be greatly affected by the uncertainty coming from the fragmentary nature of archaeological data, their irregular distribution in the landscape, and the working methods used to study them. Furthermore, the quantification of uncertainty in spatial data coming from non-systematic surveys has never been fully addressed. To overcome this challenge, archaeologists have increasingly relied on applying advanced methods from statistics, data science, and geography. While the application of advanced methods from formal sciences will provide robustness to models based on uncertain datasets, as with uncertainty, robustness must be assessed in relation to the case study, the regional context, and the methods used. These issues are of great importance when the models from advanced methods are directly used to create narratives about past landscapes. In this paper, we gather previous research on uncertainty quantification in archaeology and formalize its best practices into a framework to assess robustness and uncertainty in spatial statistical models, particularly focusing on one commonly used in the discipline, i.e., the Pair Correlation Function. This framework allows us to understand better how incomplete data affect a model, quantify the model uncertainties, and assess the robustness of the results achieved with spatial point processes.

World-class amethyst-agate geodes from Los Catalanes, Northern Uruguay: genetic implications from fluid inclusions and stable isotopes

AbstractThe amethyst and agate geodes from the Los Catalanes Gemmological District in Uruguay represent one of the main deposits of its kind worldwide. The geometry of the deposit is horizontal, with an irregular distribution of amethyst geodes within the upper level of the basalt lava flows and shows strong variations in their abundance, as well as quality, geometry, and shape. Reliable exploration guides are scarce, and the limited knowledge of the geological parameters controlling its occurrence makes exploration unpredictable, leading to inaccurate reserve estimation. Based on cutting-edge methods including nucleation-assisted microthermometry of one-phase fluid inclusions and determination of triple oxygen isotope in silicates and carbonates, as well as analysis of geode-hosted water and groundwater, we estimate the crystallisation temperatures in the range between 15 and 60 °C. These low temperatures point to amethyst crystallisation after the emplacement of the complete basalt pile. The mineralising fluid shows isotopic signatures consistent with meteoric water and very low salinities from pure water up to rarely over 3 wt% NaCl-eq., likely sourced from the groundwater hosted in the aquifers in the basaltic sequence and underlying units. Based on the insights provided by the new data, we propose the combination of open- and closed-system crystallisation inside pre-existing cavities due to the episodic infiltration of meteoric water in a rather stable geological context.

Swarm Investigation of Ultra-Low-Frequency (ULF) Pulsation and Plasma Irregularity Signatures Potentially Associated with Geophysical Activity

Launched on 22 November 2013, Swarm is the fourth in a series of pioneering Earth Explorer missions and also the European Space Agency’s (ESA’s) first constellation to advance our understanding of the Earth’s magnetic field and the near-Earth electromagnetic environment. Swarm provides an ideal platform in the topside ionosphere for observing ultra-low-frequency (ULF) waves, as well as equatorial spread-F (ESF) events or plasma bubbles, and, thus, offers an excellent opportunity for space weather studies. For this purpose, a specialized time–frequency analysis (TFA) toolbox has been developed for deriving continuous pulsations (Pc), namely Pc1 (0.2–5 Hz) and Pc3 (22–100 mHz), as well as ionospheric plasma irregularity distribution maps. In this methodological paper, we focus on the ULF pulsation and ESF activity observed by Swarm satellites during a time interval centered around the occurrence of the 24 August 2016 Central Italy M6 earthquake. Due to the Swarm orbit’s proximity to the earthquake epicenter, i.e., a few hours before the earthquake occurred, data from the mission may offer a variety of interesting observations around the time of the earthquake event. These observations could be associated with the occurrence of this geophysical event. Most notably, we observed an electron density perturbation occurring 6 h prior to the earthquake. This perturbation was detected when the satellites were flying above Italy.

Full-scale field test of early-age behaviour of partially continuous reinforced concrete pavement

To address the damage characteristics and deficiencies of the existing continuously reinforced concrete pavement (CRCP), which are the high construction cost and irregular crack distribution patterns, a concrete pavement structure called partially continuous reinforced concrete pavement (PCRCP) is proposed. In this paper, the early-age (28 days, without traffic) behaviour of PCRCP subjected to environmental loading is investigated. To this end, full-scale field tests were carried out in Xiangjiagou Tunnel, Shanxi Province, China. Testing results showed that the PCRCP test section with the partial continuous reinforcement length of 100 cm and active crack spacing of 5 m can provide better early-age performance and lower initial construction cost in this study. The PCRCP test section with the active crack control method has a uniform crack distribution pattern with narrow width compared to the CRCP test section. The results of this study would provide data support and reference for the rational design of PCRCP.

Impact of Regular and Irregular Pore Distributions on the Elasticity of Porous Materials: A Microstructure-Free Finite Element Study.

Conventional analytical formulas for predicting the effective Young's modulus of porous materials often rely on simplifying assumptions and do not explicitly incorporate microstructural information. This study investigates the impact of regular versus irregular pore distributions on the stiffness of porous materials using microstructure-free finite element modeling (MF-FEM). After conducting a convergence study, MF-FEM predictions were validated against experimental data and used to assess the accuracy of commonly employed analytical models. The results demonstrate that materials with irregular microstructures exhibit a rapid decrease in Young's modulus, approaching zero at porosities slightly greater than 50%. In contrast, regular microstructures show a more gradual decline, maintaining significant stiffness until the porosity exceeds 90%. Additionally, the study reveals that some analytical formulas align better with irregular microstructures while others are more suited to regular ones, attributable to the underlying assumptions of these models. These findings underscore the necessity of considering pore distribution patterns in modeling to accurately predict the mechanical behavior of porous materials.

Efficient separation of coal gasification fine slag from Texaco gasifier and microstructures and elemental characteristics of separated components

ABSTRACT Coal gasification fine slag (CGFS) is one of the by-products of coal gasification process, which is mainly composed of inorganic minerals and residual carbon. The key to realize the high-value utilization of CGFS is separating the residual carbon and mineral in CGS effectively. Owing to irregular distribution of carbon in different size of CGFS, which could not be enriched by simple grinding and screening for component enrichment. In this paper, the enrichment of CGFS was carried out by the float-sink method, which is low-cost and does not result in the loss of raw materials. The carbon-rich particles (CRP, ash: 27.89%) and mineral-rich particles (MRP, ash: 78.01%) were obtained, where CRP contains a large amount of amorphous carbon with rich porous structure, while MRP is a heterogeneous material containing not only inorganic minerals but also organic carbon with low porosity. The mineral particles exist as aluminosilicates with a high degree of polymerization. The results of this paper will provide theoretical and technical support for the high-value utilization of CGFS.

Seismic performance of skewed bridges with uniform and non-uniform scour

Seismic safety of highway bridges is one of the critical issues for the functionality of transportation lifelines after severe earthquakes. Skewed highway bridges are found to be more vulnerable due to the irregular distribution of seismic demands on the bridge components. Moreover, scour induced loss of soil material and hence reduction in lateral support around the foundation piles can amplify the seismic effects on the structural components of water crossing bridges. A numerical study was conducted to investigate the seismic performance of skewed and straight highway bridges with varying scour depths and two different scouring types around the bridge piles. Analytical models of straight (0°) and 45° skewed bridges were created using the OpenSees program and a series of nonlinear response history analysis was carried out under the effect of recorded strong ground motions. In the first scouring type which was called as Case-1, scour depth was assumed the same around all piles and varied uniformly. In Case 2, two different non-uniform scouring types with linearly varying scour depth around the piles were investigated. The uncertainty in the earthquake ground motion excitation direction of the two horizontal components was also studied by considering the variable incidence angle of ground motion pairs. The maximum seismic demands of the members at different ground motion incidence angles were evaluated and compared to the demands obtained for the critical ground motion incidence angles suggested by Caltrans. Superstructure displacement, curvature demands of bridge column and shear force demands of pile elements are the seismic demand parameters examined within the scope of the study and were compared for each scour condition for both straight (0°) and 45° skewed bridge.