Structural Patterns Research Articles

Automatic identification of crystal structures and interfaces via artificial-intelligence-based electron microscopy

Characterizing crystal structures and interfaces down to the atomic level is an important step for designing advanced materials. Modern electron microscopy routinely achieves atomic resolution and is capable to resolve complex arrangements of atoms with picometer precision. Here, we present AI-STEM, an automatic, artificial-intelligence based method, for accurately identifying key characteristics from atomic-resolution scanning transmission electron microscopy (STEM) images of polycrystalline materials. The method is based on a Bayesian convolutional neural network (BNN) that is trained only on simulated images. AI-STEM automatically and accurately identifies crystal structure, lattice orientation, and location of interface regions in synthetic and experimental images. The model is trained on cubic and hexagonal crystal structures, yielding classifications and uncertainty estimates, while no explicit information on structural patterns at the interfaces is included during training. This work combines principles from probabilistic modeling, deep learning, and information theory, enabling automatic analysis of experimental, atomic-resolution images.

Failure Analysis of Resistance Spot-Welded Structure Using XFEM: Lifetime Assessment

Due to their effective and affordable joining capabilities, resistance spot-welded (RSW) structures are widely used in many industries, including the automotive, aerospace, and manufacturing sectors. Because spot-welded structures are frequently subjected to cyclic stress conditions while in service, fatigue failure is a serious concern. It is essential to comprehend and predict their fatigue behavior in order to guarantee the dependability and durability of the relevant engineering products. The analysis of fatigue failure in spot-welded structures is the main topic of this paper, along with the prediction of fatigue life (Nf) and identification of failure mechanisms. Also, the effects of parameters such as the amount of cyclic load applied, the load ratio, and size of the spot-welding on the Nf were investigated. To achieve this, the fatigue performance of spot-welded joints was simulated using the extended finite element method (XFEM). The XFEM method is particularly suited for capturing intricate crack patterns in spot-welded structures because it allows for the modeling of crack propagation without the need for remeshing. It was observed that when the cycling load was decreased by 20%, Nf increased by around 250%. On the other hand, the fatigue life of the structure, and, hence, the crack propagation rate, was significantly affected by the load ratio and diameter of the spot-welding. This paper presents the details of the novel approach to studying spot-weld fatigue characterization using XFEMs to simulate crack propagation.

Temporal and structural patterns of hepatitis B virus integrations in hepatocellular carcinoma.

Chronic infection of hepatitis B virus (HBV) is the major cause of hepatocellular carcinoma (HCC). Notably, 90% of HBV-positive HCC cases exhibit detectable HBV integrations, hinting at the potential early entanglement of these viral integrations in tumorigenesis and their subsequent oncogenic implications. Nevertheless, the precise chronology of integration events during HCC tumorigenesis, alongside their sequential structural patterns, has remained elusive thus far. In this study, we applied whole-genome sequencing to multiple biopsies extracted from six HBV-positive HCC cases. Through this approach, we identified point mutations and viral integrations, offering a blueprint for the intricate tumor phylogeny of these samples. The emergent narrative paints a rich tapestry of diverse evolutionary trajectories characterizing the analyzed tumors. We uncovered oncogenic integration events in some samples that appear to happen before and during the initiation stage of tumor development based on their locations in reconstituted trajectories. Furthermore, we conducted additional long-read sequencing of selected samples and unveiled integration-bridged chromosome rearrangements and tandem repeats of the HBV sequence within integrations. In summary, this study revealed premalignant oncogenic and sequential complex integrations and highlighted the contributions of HBV integrations to HCC development and genome instability.

A number balance approach for estimation of microcapsules surface affinity for fabrics: Implications towards sustainable use of microcapsules in consumer care and specialty chemicals

This study proposes a novel number balance approach for evaluating the affinity of microcapsules for a target substrate (e.g., cotton and polyester fabric). Using single particle optical sizing (SPOS) technique, the affinity of polyurea and silica microcapsules was studied by quantifying the capsules present in the dispersions before and after exposure to the fabric. Silica and polyurea microcapsules with encapsulated silicone oil were successfully synthesized and used as model capsules for affinity studies. Accuracy and reproducibility of the data generated from the SPOS were evaluated by relative standard deviation. Results of the affinity experiments revealed that, under the test conditions, not more than one-third of the capsules was deposited on the fabrics with silica capsules showing the highest affinity of 34.4% towards the polyester fabric. The observed affinity trends were explained by surface charge and the structural pattern of the fabrics, with capsules having a greater affinity for oppositely charged fabrics. We also found that the polyester fabric, which inherently contains bigger pores and higher exposed surface area, deposited more capsules than the cotton fabric. We demonstrated that while the microscopic techniques, such as scanning electron microscopy, can only confirm the deposition of capsules on the fabrics, alternative techniques such as SPOS provides an accurate measure of number of capsules, thereby determining the surface affinity of the capsules for the fabric.

2D Joint Inversion of Gravity and Magnetic Data to Evaluate a Geological Structure in Tanimbar Island

The need for hydrocarbon energy, especially oil and gas, requires continuous exploration of hydrocarbon reserves, especially in eastern Indonesia. Tanimbar Islands, Maluku was chosen to be the research area because of its complex subsurface geology and is located on the fold thrust belt resulting from tectonic evolution. In this research, an innovation is carried out using joint inversion modeling by correlating physical parameters from two different geophysical data, which are gravity and geomagnetic. The purpose of this research is to determine the subsurface mapping of the research area, determine the density and susceptibility values of rocks, and determine the structural patterns that exist in the subsurface. The results of subsurface mapping of the Tanimbar Islands based on the results of Joint Inversion modelling have found a geological structure pattern in the form of a fold thrust belt due to the Banda Arc subduction zone. In section A-A', there is a sequence of fold thrust belt with 10 structural patterns, including 6 structures in the northwest-southeast direction and 4 structures in the northeast-southwest direction. In section B-B' there are 9 structural patterns in the northeast-southwest direction. High anomalies obtained density values ranging from 2.77 - 2.81 gr/cm3 and susceptibility ranging from 0.00125 - 0.0013 SI are thought to be caused by high basement in the form of volcanic rocks, while low anomalies obtained density values ranging from 2.45 - 2.49 gr/cm3 and susceptibility ranging from 0.0008 - 0.00085 SI are thought to be caused by thick sedimentary layers of the Batimafudi Formation.

Structural but not functional resistance of frugivore-plant interaction networks to the defaunation process

Defaunation is the process of sequential loss of larger animal species caused by anthropogenic activities such as deforestation and hunting. This phenomenon has potential to disrupt the ecosystem stability, as well as their functional performance through the disruption of trophic interactions. We evaluated the effect of defaunation on structure and function in frugivore-plant interaction networks. We characterized interaction networks in two areas in northern Colombia and used a simulation model of species extinction in three different scenarios. The first scenario eliminated species based on body size, measured by body mass, according to the progressive effect of non-random species loss (defaunation); the second scenario eliminated species according to their contribution to network structure (CNS); and finally, the third scenario eliminated species according to their seed dispersal potential (SDP). Based on these simulations we evaluated the effect of species loss on the structural patterns (nestedness and modularity) and the functional diversity of the frugivore community, through the indexes of functional richness (FRic) and functional evenness (FEve). The loss of species with larger body sizes increased nestedness and did not affect modularity, whereas in the CNS scenario both patterns were affected. The FRic index decreased in the first stages of extinction by defaunation and by SDP, while the FEve index did not suffer significant variations in any scenario. The combination of interaction network analysis with functional diversity indices allows direct quantification of the robustness of network structural patterns and the vulnerability of the functional capacity of frugivore communities in the face of defaunation.

Combining eugenol and dihydroeugenol with a piperazine moiety to create new antimicrobial agents that are effective against resistant species

Historically, the piperazine moiety has been demonstrated to possess pharmacophoric properties, and has subsequently been incorporated in many drugs that have antitumor, antimalarial, antiviral, antibacterial and antifungal properties. Derivatives of eugenol and dihydroeugenol have also been reported as being bioactive compounds.This study reports the synthesis of a range of eugenol/dihydroeugenol - piperazine derivatives which have been tested as antimicrobial compounds against Gram positive, Gram negative and rapid-growing mycobacteria (RGM). The rationale employed in the design of the structural pattern of these new derivatives, provides useful insights into the structure-activity relationships (SAR) of the series.Antimicrobial activity tests were extremely encouraging, with the majority of the synthesised compounds being more active than eugenol and dihydroeugenol starting materials. The antimicrobial potential was most notable against the Gram-negative species K. pneumoniae and P. aeruginosa, but there was also significant performance against the Gram-positive strains S. epidermidis and S. aureus and the Rapidly Growing Mycobacteria (RGM) strains tested. Tests using the synthesised compounds against multidrug-resistance clinical (MDR) isolates also showed high activity. The biofilm inhibition tests using M. fortuitum showed that all evaluated derivatives were able to inhibit biofilm formation even at low concentrations.In terms of structural-activity relationships; the results generated by this study demonstrate that the compounds with bulky substituents on the piperazine subunit were much more active than those with less bulky groups, or no groups. Importantly, the derivatives with a sulfonamide side chain were the most potent compounds. A further observation was that those compounds with a para-substituted benzenesulfonamide ring stand out, regardless of whether this substituent is a donor or an electron-withdrawing group.

Effect of Knitting Pattern of PP Mesh on the Flexural Properties of Heat-cured PMMA Denture Base Resin

Heat-cured polymethyl methacrylate is (PMMA) is the most common denture base material and some mechanical properties such as flexural strength and impact resistance etc. may lead to fail, besides its excellent properties. Polypropylene (PP) hernia mesh is a commercially available medical textile used in surgical repair of different types of hernia. It was aimed to investigate the effect of two different knitting patterns of PP meshes on the flexural properties of the PMMA denture base resin when they are used as reinforcement and compare with glass fiber mesh reinforced and no mesh used resins. Knitting patterns of the PP mesh structures were hexagonal honeycomb pattern and square pattern and these were used as single or double layer as reinforcement. 6 groups were established in the study: control group with no mesh and 5 reinforced groups with meshes (glass fiber mesh, single layer honeycomb patterned PP mesh, double layer honeycomb patterned PP mesh, single layer square patterned PP mesh, double layer square patterned PP mesh). A total of 60 samples with the dimensions of 65x10x3 mm, n=10 in each group were fabricated. The flexural strength, maximum deformation, and flexural modulus were determined by three-point bending test. Fracture surfaces were evaluated by scanning electron microscopy. The obtained data were statistically analyzed by two-way ANOVA test with Bonferroni corrections. The single layer square patterned PP mesh group exhibited the highest (76.67 ± 7.64 MPa), and the control group showed the lowest (63.49 ± 7.18 MPa) flexural strength values. The single layer glass fiber mesh group showed the highest (7.13 ± 0.55 mm) and the control group showed the lowest (4.72 ± 0.81 mm) maximum deformation values. The single layer glass fiber mesh group exhibited the highest (2131.87 ± 205.76 MPa), and the control group exhibited the lowest (1582.26 ± 98.63 MPa) flexural modulus values. Significant increase in flexural strength was observed in all polypropylene mesh-reinforced groups compared to the control group except double layer honeycomb patterned PP mesh group (p < 0.05). Using PP fiber mesh for reinforcement provide a very favorable aesthetic view and PP fiber mesh is concluded to be a promising material for reinforcement of heat-cured PMMA denture base resins.

Structural, developmental and functional analyses of leaf salt glands of mangrove recretohalophyte Aegiceras corniculatum.

Salt secretion is an important strategy used by the mangrove plant Aegiceras corniculatum to adapt to the coastal intertidal environment. However, the structural, developmental and functional analyses on the leaf salt glands, particularly the salt secretion mechanism, are not well documented. In this study, we investigated the structural, developmental and degenerative characteristics and the salt secretion mechanisms of salt glands to further elucidate the mechanisms of salt tolerance of A. corniculatum. The results showed that the salt gland cells have a large number of mitochondria and vesicles, and plenty of plasmodesmata as well, while chloroplasts were found in the collecting cells. The salt glands developed early and began to differentiate at the leaf primordium stage. We observed and defined three stages of salt gland degradation for the first time in A. corniculatum, where the secretory cells gradually twisted and wrinkled inward and collapsed downward as the salt gland degeneration increased and the intensity of salt gland autofluorescence gradually diminished. In addition, we found that the salt secretion rate of the salt glands increased when the treated concentration of NaCl increased, reaching the maximum at 400mM NaCl. The salt-secreting capacity of the salt glands of the adaxial epidermis is significantly greater than that of the abaxial epidermis. The real-time quantitative PCR results indicate that SAD2, TTG1, GL2 and RBR1 may be involved in regulating the development of the salt glands of A. corniculatum. Moreover, Na+/H+ antiporter, H+-ATPase, K+ channel and Cl- channel may play important roles in the salt secretion of salt glands. In sum mary, this study strengthens the understanding of the structural, developmental and degenerative patterns of salt glands and salt secretion mechanisms in mangrove recretohalophyte A. corniculatum, providing an important reference for further studies at the molecular level.

Enhanced structural properties of electrochemically synthesised NiFeS using 500 keV carbon C++ ions irradiation

ABSTRACT An electrochemical approach was used to synthesise nickel iron sulphide (NiFeS) materials in this work. The prepared NiFeS underwent a thorough investigation, which included analyses of its optical, electrical, structural, morphological, elemental, and functional group properties. Cubic crystal formations with prominent peaks were visible from the structural pattern. Nanoflakes and pebbles were visible, and their elements were determined through elemental dispersive X-ray diffractometer (EDX) spectrum. The film’s crystallinity increased after incorporating carbon ions and its optical properties improved, with energy band gap values ranging from 1.50 eV to 1.15 eV as the peaks became more distinct. The materials produced could be utilised in the production of solar cells and optoelectronic devices. The electrical conductivity diminishes with increasing thickness. Carbon ion radiation increases carrier concentration, which increases electrical conductivity.

An illustrated atlas of the vertebral morphology of extant non-caenophidian snakes, with special emphasis on the cloacal and caudal portions of the column

AbstractWe here present a thorough documentation of the vertebral morphology and intracolumnar variation across non-caenophidian snakes. Our studied sample of multiple individuals covers a large number of genera (67) and species (120), pertaining to almost all extant non-caenophidian families. Detailed figuring of multiple vertebrae across the trunk, cloacal, and caudal series for many different individuals / taxa documents the intracolumnar, intraspecific, and interspecific variation. An emphasis is given in the trunk-to-caudal transition and the pattern of the subcentral structures in that region of the column. Extant non-caenophidian snakes show an astonishing diversity of vertebral morphologies. Diagnostic vertebral features for extant families and many genera are given, though admittedly vertebral distinction among genera in certain groups remains a difficult task. A massive compilation of vertebral counts for 270 species, pertaining to 78 different genera (i.e., almost all known valid genera) and encompassing all extant non-caenophidian families, is provided based on our observations as well as an extensive literature overview. More particularly, for many taxa, detailed vertebral counts are explicitly given for the trunk, cloacal, and caudal portions of the column. Extant non-caenophidian snakes witness an extremely wide range of counts of vertebrae, ranging from 115 up to 546. A discussion on the diagnostic taxonomic utility and potential phylogenetic value of certain vertebral structures is provided. Comparisons of the subcentral structures of the cloacal and caudal vertebral series are also made with caenophidian lineages. We anticipate that this illustrative guide will set the stage for more vertebral descriptions in herpetological works but will also be of significant aid for taxonomic identifications in ophidian palaeontology and archaeozoology.

3D-Printed Biomimetic Structural Colors.

Resolution control and expansibility have always been challenges to the fabrication of structural color materials. Here, a facile strategy to print cholesteric liquid crystal elastomers (CLCEs) into complex structural color patterns with variable resolution and enhanced expansibility is reported. A volatile solvent is introduced into the synthesized CLC oligomers, modifying its rheological properties and allowing direct-ink-writing (DIW) under mild conditions. The combination of printing shear flow and anisotropic deswelling of ink drives the CLC molecules into an ordered cholesteric arrangement. The authors meticulously investigate the influence of printing parameters to achieve resolution control over a wide range, allowing for the printing of multi-sized 1D or 2D patterns with constant quality. Furthermore, such solvent-cast direct-ink-writing (DIW) strategy is highly expandable and can be integrated easily into the DIW of bionic robots. Multi-responsive bionic butterfly and flower are printed with biomimetic in both locomotion and coloration. Such designs dramatically reduced the processing difficulty of precise full-color printing and expanded the capability of structural color materials to collaborate with other systems.

Hierarchical Transformer with Spatio-temporal Context Aggregation for Next Point-of-interest Recommendation

Next point-of-interest (POI) recommendation is a critical task in location-based social networks, yet remains challenging due to a high degree of variation and personalization exhibited in user movements. In this work, we explore the latent hierarchical structure composed of multi-granularity short-term structural patterns in user check-in sequences. We propose a Spatio-Temporal context AggRegated Hierarchical Transformer (STAR-HiT) for next POI recommendation, which employs stacked hierarchical encoders to recursively encode the spatio-temporal context and explicitly locate subsequences of different granularities. More specifically, in each encoder, the global attention layer captures the spatio-temporal context of the sequence, while the local attention layer performed within each subsequence enhances subsequence modeling using the local context. The sequence partition layer infers positions and lengths of subsequences from the global context adaptively, such that semantics in subsequences can be well preserved. Finally, the subsequence aggregation layer fuses representations within each subsequence to form the corresponding subsequence representation, thereby generating a new sequence of higher-level granularity. The stacking of hierarchical encoders captures the latent hierarchical structure of the check-in sequence, which is used to predict the next visiting POI. Extensive experiments on three public datasets demonstrate that the proposed model achieves superior performance while providing explanations for recommendations.

Influence of Nonlinear Analysis Technology on Damage Analysis of Asphalt Pavement Structure

As a means of predicting the damage pattern and design life of asphalt pavement structures, the reliability of damage analysis is highly dependent on the calculation accuracy of the pavement mechanical responses under wheel load. The nonlinear analysis, on its part, can practically describe the stress dependence of the modulus of granular materials and fine-grained soils, so that the mechanical responses of the wheel-loaded asphalt pavement structure can be obtained more accurately. Therefore, the correct application of nonlinear analysis technology is essential to obtain reliable damage analysis results. For this reason, computer program KENLAYER was utilized to explore the effects of stress adjustment methods and core parameters of nonlinear iterative analysis on the damage analysis results. According to the calculation results, this paper explains the reasons why the stress adjustment Methods 2 and 3 are not applicable to the structural analysis of pavements containing nonlinear granular materials in the case of thin surface layers, illustrates the effects of improper selection of the adjustment methods and each iteration parameter on the dominant damage pattern, finds out the reasons for unreliable calculation results due to improper selection of the iteration parameters, and makes corresponding suggestions for carrying out damage analysis accurately.

Influence of pyrophosphate (PPi) and adenosine 5`-triphosphate (ATP) on the conformational stability and ultrastructure of silver carp myofibrillar proteins at low salinity

The effect of pyrophosphate (PPi) in comparison with adenosine 5`-triphosphate (ATP) on the thermal and ultrastructural properties of silver carp myofibrillar protein (SMf) was studied. The temperatures for 50 % denaturation (T1/2) of PPi-treated myosin and actin were 38 °C and 41 °C, respectively, lower than those for control SMf (43 °C and 48 °C, respectively). In comparison, T1/2 of myosin in ATP-treated SMf was 42 °C, while T1/2 of actin cannot be detected because no changes in actin digestion pattern. The ultrastructural change of PPi-treated and control SMf differed considerably from that of ATP-treated SMf in which the typical striated structural pattern disappeared, replaced by an aggregated form. In contrast, PPi-treated SMf retained the striated structure with lengthened sarcomere. Therefore, while both PPi and ATP can dissociate actomyosin, the presence of ATP hinders the chymotryptic digestion of actin.

PbPDCB16-mediated callose deposition affects the plasmodesmata blockage and reduces lignification in pear fruit

Stone cell, a type of lignified cell, is a unique trait in pear and one of the key factors affects pear fruit quality and economic value. The transmissibility of cell lignification process has been proven to exist, however the effects of callose on the permeability of plasmodesmata (PD) and how to influence cell lignification processes are still unknown. In this study, the genome-wide analysis of PD callose binding proteins (PDCB) gene family in pear genome was performed, and 25 PbPDCB genes were identified and divided into four branches. Similar intron/exon structural patterns were observed in the same branch, strongly supporting their close evolutionary relationship. The expression of PbPDCB16 was negatively correlated with lignin accumulation through qRT-PCR analysis. With transient expression in pear fruit and stable expression in pear calli, the increased callose content accompanied by decreased lignin content was further observed. Besides, compared with wild type Arabidopsis, the transgenic plants grew slowly, and cell walls in the stem were thinner, while fewer PDs were observed on the cell walls, and the interspore filaments were also blocked in transgenic Arabidopsis through the transmission electron microscope (TEM). In summary, overexpression of PbPDCB16 could promote accumulation of callose at PD to affect the PD-mediated intercellular connectivity, and inhibit the intercellular communication. This study will provide new insight in reducing the lignin content through callose deposition, and also provide the theoretical basis for further exploration of lignin metabolism and cell wall lignification to form stone cells in pear fruit.

PreHom-PCLM: protein remote homology detection by combing motifs and protein cubic language model.

Protein remote homology detection is essential for structure prediction, function prediction, disease mechanism understanding, etc. The remote homology relationship depends on multiple protein properties, such as structural information and local sequence patterns. Previous studies have shown the challenges for predicting remote homology relationship by protein features at sequence level (e.g. position-specific score matrix). Protein motifs have been used in structure and function analysis due to their unique sequence patterns and implied structural information. Therefore, designing a usable architecture to fuse multiple protein properties based on motifs is urgently needed to improve protein remote homology detection performance. To make full use of the characteristics of motifs, we employed the language model called the protein cubic language model (PCLM). It combines multiple properties by constructing a motif-based neural network. Based on the PCLM, we proposed a predictor called PreHom-PCLM by extracting and fusing multiple motif features for protein remote homology detection. PreHom-PCLM outperforms the other state-of-the-art methods on the test set and independent test set. Experimental results further prove the effectiveness of multiple features fused by PreHom-PCLM for remote homology detection. Furthermore, the protein features derived from the PreHom-PCLM show strong discriminative power for proteins from different structural classes in the high-dimensional space. Availability and Implementation: http://bliulab.net/PreHom-PCLM.

Analyzing and Forecasting Pediatric Fever Clinic Visits in High Frequency Using Ensemble Time-Series Methods After the COVID-19 Pandemic in Hangzhou, China: Retrospective Study.

The COVID-19 pandemic has significantly altered the global health and medical landscape. In response to the outbreak, Chinese hospitals have established 24-hour fever clinics to serve patients with COVID-19. The emergence of these clinics and the impact of successive epidemics have led to a surge in visits, placing pressure on hospital resource allocation and scheduling. Therefore, accurate prediction of outpatient visits is essential for informed decision-making in hospital management. Hourly visits to fever clinics can be characterized as a long-sequence time series in high frequency, which also exhibits distinct patterns due to the particularity of pediatric treatment behavior in an epidemic context. This study aimed to build models to forecast fever clinic visit with outstanding prediction accuracy and robust generalization in forecast horizons. In addition, this study hopes to provide a research paradigm for time-series forecasting problems, which involves an exploratory analysis revealing data patterns before model development. An exploratory analysis, including graphical analysis, autocorrelation analysis, and seasonal-trend decomposition, was conducted to reveal the seasonality and structural patterns of the retrospective fever clinic visit data. The data were found to exhibit multiseasonality and nonlinearity. On the basis of these results, an ensemble of time-series analysis methods, including individual models and their combinations, was validated on the data set. Root mean square error and mean absolute error were used as accuracy metrics, with the cross-validation of rolling forecasting origin conducted across different forecast horizons. Hybrid models generally outperformed individual models across most forecast horizons. A novel model combination, the hybrid neural network autoregressive (NNAR)-seasonal and trend decomposition using Loess forecasting (STLF), was identified as the optimal model for our forecasting task, with the best performance in all accuracy metrics (root mean square error=20.1, mean absolute error=14.3) for the 15-days-ahead forecasts and an overall advantage for forecast horizons that were 1 to 30 days ahead. Although forecast accuracy tends to decline with an increasing forecast horizon, the hybrid NNAR-STLF model is applicable for short-, medium-, and long-term forecasts owing to its ability to fit multiseasonality (captured by the STLF component) and nonlinearity (captured by the NNAR component). The model identified in this study is also applicable to hospitals in other regions with similar epidemic outpatient configurations or forecasting tasks whose data conform to long-sequence time series in high frequency exhibiting multiseasonal and nonlinear patterns. However, as external variables and disruptive events were not accounted for, the model performance declined slightly following changes in the COVID-19 containment policy in China. Future work may seek to improve accuracy by incorporating external variables that characterize moving events or other factors as well as by adding data from different organizations to enhance algorithm generalization.

Food access in Kalamazoo, Michigan: A spatial analysis

Healthy and affordable food is a universal human need. In the U.S., food access is often limited in low-income areas as opposed to medium- and high-income areas. To address disparities in the availability of healthy foods, the dispersion of food access points needs to be quantified and docu­mented. Nutritional quality and consistency of availability vary across different types of food access points, including permanent grocery stores, farmers markets, community gardens, food pan­tries, and convenience stores. Accessibility is also determined by the means of transportation avail­able or required to get to food access points (public transit, driving, or walking). In this geographic information systems (GIS)-based analysis, we iden­tify differences in accessibility to distinct types of food access points—reliable, seasonal, and lower quality—between low-income and higher-income tracts in the City of Kalamazoo, Michigan. We found that all full-service grocery stores are acces­sible via bus routes in the City of Kalamazoo; however, 11% of people reside in low-income areas with low access to these grocery stores—beyond the 0.25-mile walkable distance to bus routes. We then asked whether the addition of community gardens, food pantries, and farmers markets, on the “plus” side, or convenience and dollar stores, on the “minus” side, changes the food access landscape in this community. We found that the “positive” access points served areas that already had access to grocers, while “negative” access points filled the access gap in lower income areas. More than twice as many low-income residents had walkable access to convenience stores—which provide lower-quality and highly processed food—with 81% of them being located within low-income tracts. Geographical analysis of low food access and low-quality food access is important to identify structural patterns, but it needs to be paired with interview-based community assessments to ascertain how residents actually procure their food.

Laboratory investigation of scale effects in bursting failure of quasi-brittle materials

Understanding the scale effect in the behavior of solid materials is important when small-scale models are used to predict the behavior of real structures. Tremendous efforts have been devoted to investigating the scale effect in the strength of quasi-brittle materials. However, limited studies have focused on the whether there is a scale effect in bursting failure, which is a typical failure pattern of quasi-brittle structures. Here, we conduct a series of unconfined compression tests on coal samples using a specialized designed loading machine to produce bursting failure in the laboratory. We use cubic coal samples with a large range of sizes from 50 to 300 mm to investigate the scale effect in bursting failure of quasi-brittle materials. We use acoustic emission technology to monitor microcreaking within the samples and a high-speed camera to capture the bursting failure process. We demonstrate that there is a strong scale effect in bursting failure of quasi-brittle materials in terms of mechanical properties including compressive strength and deformability, strain energy density, bursting severity, and precursor time. We found that ejection of localized pieces from the skin of the structure is a precursor of catastrophic bursting failure of quasi-brittle materials. We conclude that the relationship between the precursor time (T) and structure size (M) of bursting failure is logarithmic and can be described as logT = a + bM where a and b are constants. This relationship provides a guideline when models obtained from laboratory tests are used to predict strength and behavior at the intermediate (mines and rock slopes) and large scales (earthquakes).