Solving digital image correlation with neural networks constrained by strain-displacement relations.

The use of supervised neural networks is a new approach to solving digital image correlation (DIC) problems, but the existing methods solely adopt the black-box neural network, i.e., the mapping from speckle image pair (reference image and deformed image) to multiple deformation fields (displacement fields and strain fields) is directly established without considering the physical constraints between the fields, causing a low level of accuracy that is even inferior to that of Subset-DIC. In this work, we proposed a deep learning model by introducing strain-displacement relations into a neural network, in which the effect of errors both in displacement and strain are considered in the network training. The back-propagation process of the proposed model is derived, and the solution scheme is implemented by Python. The performance of the proposed model is evaluated by simulation and real DIC experiments, and the results show that adding physical constraints to the neural network can significantly improve prediction accuracy.

AMF Inoculum Enhances Crop Yields of Zea mays L. 'Chenghai No. 618' and Glycine max L. 'Zhonghuang No. 17' without Disturbing Native Fugal Communities in Coal Mine Dump.

For the agricultural development of dumps, increase in land use efficiency and protection of food security, to verify the safety, efficacy and sustainability of field-applied arbuscular mycorrhizal fungi (AMF) inoculum, and to exclude the risk of potential biological invasion, in this study, we determined the effect of AMF inoculation and intercropping patterns (maize-soybean) on the temporal dynamics of soil parameters, native AMF communities and crop yields. AMF communities were analyzed using Illumina MiSeq. A total of 448 AMF operational taxonomic units (OTUs) belonging to six genera and nine families were identified. AMF inoculation treatment significantly improved the yield of intercropping maize and increased the content of available phosphorus. AMF diversity was significantly influenced by cropping pattern and growth stage, but not by the inoculation treatment. Inoculation altered the AMF community composition in the early growth stage and facilitated a more complex AMF network in the early and late growth stages. These results indicate that AMF inoculation affects native AMF only in the early stage, and its impact on yield may be the consequence of cumulative effects due to the advantages of plant growth and nutrient uptake in the early stage.

Combined inoculation with dark septate endophytes and arbuscular mycorrhizal fungi: synergistic or competitive growth effects on maize?

BACKGROUND: Effects on maize were assessed of dual inoculation with arbuscular mycorrhizal fungi (AMF) and dark septate endophytes (DSE) isolated from other plant species. METHODS: Suspensions of DSE isolated from Stipa krylovii were prepared at different densities (2, 4, and 8 × 105 CFU mL- 1) and inoculated separately (AMF or DSE) or together (AMF + DSE), to explore their effects on maize growth. RESULTS: Inoculation with AMF or medium and high densities of DSE and combined inoculation (AMF + DSE) increased plant above-ground growth and altered root morphology. Differences in plant growth were attributable to differences in DSE density, with negative DSE inoculation responsiveness at low density. AMF promoted plant above-ground growth more than DSE and the high density of DSE promoted root development more than AMF. Combined inoculation might lead to synergistic growth effects on maize at low density of DSE and competitive effects at medium and high DSE densities. CONCLUSIONS: AMF and DSE co-colonized maize roots and they had positive effects on the host plants depending on DSE density. These findings indicate the optimum maize growth-promoting combination of AMF and DSE density and provide a foundation for further exploration of potentially synergistic mechanisms between AMF and DSE in physiological and ecological effects on host plants.

Shifts in composition and function of soil fungal communities and edaphic properties during the reclamation chronosequence of an open-cast coal mining dump.

The diversity, composition and ecological guilds of soil fungal communities in relation to revegetation were assessed during an open-cast mining dump reclamation chronosequence of the soil <1, 5, 10, 15 and 20 years after the start of reclamation. Soil pH and electrical conductivity, total nitrogen (TN), soil organic carbon (SOC), available potassium (AK), and available phosphorus (AP) contents, and soil phosphatase (Pha), urease (U) and invertase (INV) activities were measured. Using high-throughput sequence analysis on internal transcribed spacer (ITS) sequences, 1059 soil fungal operational taxonomic units (OTUs) were identified belonging to 64 orders and these were further categorized by ecological guild. Soil fungal diversity indices were significantly different between the early (<1 year) and later reclamation communities. Nonmetric multidimensional scaling (NMDS) analysis indicates that the composition and ecological guilds of soil fungal communities were significantly different early in the process and at the end of reclamation (P < 0.05). Co-occurrence network and structural equation model analyses show that soil fungal community structure and ecological guilds were correlated with edaphic properties and had an indirect effect on soil available nutrients through direct action on soil enzymes. Overall, the data suggest that soil fungal community composition and function within an open-cast coal mining dump reclamation chronosequence changed during the period following artificial re-vegetation, with interactions between edaphic properties and soil fungal communities associated with these changes.

Heat Transfer and Temperature Characteristics of a Working Digital Camera.

Digital cameras represented by industrial cameras are widely used as image acquisition sensors in the field of image-based mechanics measurement, and their thermal effect inevitably induces thermal-induced errors of the mechanics measurement. To deeply understand the errors, the research for digital camera's thermal effect is necessary. This study systematically investigated the heat transfer processes and temperature characteristics of a working digital camera. Concretely, based on the temperature distribution of a typical working digital camera, the heat transfer of the working digital camera was investigated, and a model describing the temperature variation and distribution was presented and verified experimentally. With this model, the thermal equilibrium time and thermal equilibrium temperature of the camera system were calculated. Then, the influences of thermal parameters of digital camera and environmental temperature on the temperature characteristics of working digital camera were simulated and experimentally investigated. The theory analysis and experimental results demonstrate that the presented model can accurately describe the temperature characteristics and further calculate the thermal equilibrium state of working digital camera, all of which contribute to guiding mechanics measurement and thermal design based on such camera sensors.

Dissecting Collective Cell Behavior in Polarization and Alignment on Micropatterned Substrates.

Pattern-dependent collective behaviors of cells have recently raised intensive attention. However, the underlying mechanisms that regulate these behaviors are largely elusive. Here, we report a quantitative study, combining experiment and modeling, on cell polarization and arrangement on a micropatterned substrate. We show that cells exhibit position-dependent collective behaviors that can be regulated by geometry and stiffness of the patterned substrate. We find that the driving force for these collective behaviors is the in-plane maximum shear stress in the cell layer that directs the arrangement of cells. The larger the shear stress, the more the cells preferentially align and polarize along the direction of the maximum principal stress. We also find that the aspect ratio of cell polarization shape and the degree to which cells preferentially align along the direction of maximum principal stress exhibit a biphasic dependence on substrate rigidity, corresponding to our quantitative predictions that the magnitude of the maximum shear stress is biphasically dependent on the stiffness of the substrate. As such, the driving force of these cell collective behaviors can be quantified using the maximum shear stress.

Experimental investigation of the systematic error on photomechanic methods induced by camera self-heating.

The systematic error for photomechanic methods caused by self-heating induced image expansion when using a digital camera was systematically studied, and a new physical model to explain the mechanism has been proposed and verified. The experimental results showed that the thermal expansion of the camera outer case and lens mount, instead of mechanical components within the camera, were the main reason for image expansion. The corresponding systematic error for both image analysis and fringe analysis based photomechanic methods were analyzed and measured, then error compensation techniques were proposed and verified.

Full-field measurement of nonuniform stresses of thin films at high temperature.

Coherent gradient sensing (CGS), a shear interferometry method, is developed to measure the full-field curvatures of a film/substrate system at high temperature. We obtain the relationship between an interferogram phase and specimen topography, accounting for temperature effect. The self-interference of CGS combined with designed setup can reduce the air effect. The full-field phases can be extracted by fast Fourier transform. Both nonuniform thin-film stresses and interfacial stresses are obtained by the extended Stoney's formula. The evolution of thermo-stresses verifies the feasibility of the proposed interferometry method and implies the "nonlocal" effect featured by the experimental results.