Net Strain Research Articles

Strain rate controls alignment in growing bacterial monolayers.

Growing monolayers of rod-shaped bacteria exhibit local alignment similarly to extensile active nematics. When confined in a channel or growing inward from a ring, the local nematic order of these monolayers changes to a global ordering with cells throughout the monolayer orienting in the same direction. The mechanism behind this phenomenon is so far unclear, as previously proposed mechanisms fail to predict the correct alignment direction in one or more confinement geometries. We present a strain-based model relating net deformation of the growing monolayer to the cell-level deformation resulting from single-cell growth and rotation, producing predictions of cell orientation behavior based on the velocity field in the monolayer. This model correctly predicts the direction of preferential alignment in channel-confined, inward growing, and unconfined colonies. The model also quantitatively predicts orientational order when the velocity field has no net negative strain rate in any direction. We further test our model in simulations of expanding colonies confined to spherical surfaces. Our model and simulations agree that cells away from the origin cell orient radially relative to the colony's center. Additionally, our model's quantitative prediction of the orientational order agrees with the simulation results in the top half of the sphere but fails in the lower half where there is a net negative strain rate. The success of our model bridges the gap between previous works on cell alignment in disparate confinement geometries and provides insight into the underlying physical effects responsible for large-scale alignment.

Proteome-wide association study using cis and trans variants and applied to blood cell and lipid-related traits in the Women's Health Initiative study.

In most Proteome-Wide Association Studies (PWAS), variants near the protein-coding gene (±1 Mb), also known as cis single nucleotide polymorphisms(SNPs), are used to predict protein levels, which are then tested for association with phenotypes. However, proteins can be regulated through variants outside of the cis region. An intermediate GWAS step to identify protein quantitative trait loci (pQTL) allows for the inclusion of trans SNPs outside the cis region in protein-level prediction models. Here, we assess the prediction of 540 proteins in 1002 individuals from the Women's Health Initiative (WHI), split equally into a GWAS set, an elastic net training set, and a testing set. We compared the testing r2 between measured and predicted protein levels using this proposed approach, to the testing r2 using only cis SNPs. The two methods usually resulted in similar testing r2, but some proteins showed a significant increase in testing r2 with our method. For example, for cartilage acidic protein 1, the testing r2 increased from 0.101 to 0.351. We also demonstrate reproducible findings for predicted protein association with lipid and blood cell traits in WHI participants without proteomics data and in UK Biobank utilizing our PWAS weights.

Boosting the Output Performance of the MoS2 Monolayer-Based Piezoelectric Nanogenerator by Artificial Dual Strain Concentration.

Piezoelectric nanogenerators (PENGs) with molybdenum disulfide (MoS2) monolayers have been intensively studied owing to their superior mechanical durability and stability. However, the limited output performance resulting from a small active area and low strain levels continues to pose a significant challenge that should be overcome. Herein, we report a novel strategy for the epoch-making output performance of a PENG with a MoS2 monolayer by adopting the additive strain concentration concept. The simulation study indicates that strain in the MoS2 monolayer can be initially augmented by the wavy structure resulting from the prestretched poly(dimethylsiloxane) (PDMS) and is further increased through flexural deformation (i.e., bending). Based on these studies, we have developed concentrated strain-applied PENGs with MoS2 monolayers. The wavy structures effectively applied strain to the MoS2 monolayer and generated a piezoelectric output voltage and current of around 580 mV and 47.5 nA, respectively. Our innovative approach to enhancing the performance of PENGs with MoS2 monolayers through the artificial dual strain concept has led to groundbreaking results, achieving the highest recorded output voltage and current for PENGs based on two-dimensional (2D) materials, which provides unique opportunities for the 2D-based energy harvesting field and structural insight into how to improve the net strain on 2D materials.

Behavior of Inflatable Drop-Stitch Fabric Panels Subjected to Bending and Compression

In this paper, the mechanics of inflatable drop-stitch panels are investigated, including the impact of large shear deformations, nonlinearity due to wrinkling of the panel skin that occurs under net compressive strain, work done by the confined internal air, and the effect of the drop-stitch yarns on the panel skin stresses. A large deflection finite element (FE) analysis framework is presented that allows for a panel’s stability and post-buckling response to be quantified. The FE code is verified through comparison with available analytical solutions, and the impact of critical response drivers is examined. The FE models are then used to explore the capacity of panel walls when used as part of a shelter subject to realistic wind and snow loads and to assess the dependence of the capacity on the important design parameters of inflation pressure and panel depth. The analyses indicate that while the drop-stitch panel capacity is sensitive to the panel depth and inflation pressure, panels with reasonable cross-sectional dimensions are viable for use in structural applications where they must support significant compression and bending. Future work should focus on increasing the structural efficiency and capacity by increasing the panel shear stiffness and operational inflation pressure.

Magnesium-Induced Strain and Immobilized Radical Generation on the Boron Oxide Surface Enhances the Oxidation Rate of Boron Particles: A DFTB-MD Study.

Despite their high gravimetric and volumetric energy densities, boron (B) particles suffer from poor oxidative energy release rates as the boron oxide (B2O3) shell impedes the diffusivity of O2 to the particle interior. Recent experiemental studies have shown that the addition of metals with a lower free energy of oxidation, such as Mg, can reduce the oxide shell of B and enhance the energetic performance of B by ∼30-60%. However, the exact underlying mechanism behind the reactivity enhancement is unknown. Here, we performed DFTB-MD simulations to study the reaction of Mg vapor with a B2O3 surface. We found that the Mg becomes oxidized on the B2O3 surface, forming a MgBxOy phase, which induces a tensile strain in the B-O bond at the MgBxOy-B2O3 interface, simultaneously reducing the interfacial B and thereby developing dangling bonds. The interfacial bond straining creates an overall surface expansion, indicating the presence of a net tensile strain. The B with dangling bonds can act as active centers for gas-phase O2 adsorption, thereby increasing the adsorption rate, and the overall tensile strain on the surface will increase the diffusion flux of adsorbed O through the surface to the particle core. As the overall B particle oxidation rate is dependent on both the O adsorption and diffusion rates, the enhancement in both of these rates increases the overall reactivity of B particles.

Alternative Formulations of Decision Rule Learning from Neural Networks

This paper extends recent work on decision rule learning from neural networks for tabular data classification. We propose alternative formulations to trainable Boolean logic operators as neurons with continuous weights, including trainable NAND neurons. These alternative formulations provide uniform treatments to different trainable logic neurons so that they can be uniformly trained, which enables, for example, the direct application of existing sparsity-promoting neural net training techniques like reweighted L1 regularization to derive sparse networks that translate to simpler rules. In addition, we present an alternative network architecture based on trainable NAND neurons by applying De Morgan’s law to realize a NAND-NAND network instead of an AND-OR network, both of which can be readily mapped to decision rule sets. Our experimental results show that these alternative formulations can also generate accurate decision rule sets that achieve state-of-the-art performance in terms of accuracy in tabular learning applications.

Welding Groove Edge Detection Method Using Lightweight Fusion Model Based on Transfer Learning

Groove edge detection is the prerequisite for weld seam deviation identification. A welding groove edge detection method based on transfer learning is presented as a solution to the inaccuracy of the conventional image processing method for extracting the edge of the welding groove. DenseNet and MobileNetV2 are used as feature extractors for transfer learning. Dense-Mobile Net is constructed using the skip connections structure and depthwise separable convolution. The Dense-Mobile Net training procedure consists of two stages: pre-training and model fusion fine-tuning. Experiments demonstrate that the proposed model accurately detects groove edges in MAG welding images. Using MIG welding images and the Pascal VOC2012 dataset to evaluate the generalization ability of the model, the relevant indicators are greater than those of Support Vector Machine (SVM), Fully Convolutional Networks (FCN), and UNet. The average single-frame detection time of the proposed model is 0.14 s, which meets the requirements of industrial real-time performance.

Target detection for remote sensing based on the enhanced YOLOv4 with improved BiFPN

To solve problems for false detection, inadequate regression performance of anchor frames, and the inability to detect small targets in traditional multiscale target detection methods based on YOLOv4, we propose a novel target detection framework named as Enhanced YOLOv4. Firstly, our improved BiFPN replaced the original PANet as the feature fusion module, which can achieve multi-scale feature fusion by way of shared weights. Secondly, the channel attention mechanism (CAM) was embedded before the detection head to highlight the correlation between channels so that small targets can be get more attention. At last, to improve the anchor box regression effect and accelerate the training speed of YOLOv4, we improved the net training loss function, in which the original CIoU was replaced by CDIoU. The experimental results on the DOTA dataset validate our improvement. The mAP of our method is 90.88%, and the frame rate reached 58.76 FPS, at the same time, the speed of detection is not affected significantly.

Transfer Learning applied to a Classification Task: a Case Study in the Footwear Industry

Convolutional Neural Networks are a widely used method for image classification. They are part of the Deep Learning area, whose main advantage is the fact that they do not require an human support to extract features from the images. In the context of the footwear industry, they represent a useful computational resource, being applied for style classification problems, machine vision, among others. This article aims to evaluate the performance of transfer learning methods for the purpose of hierarchical classification of new items of footwear products. For this purpose, a dataset composed by 5,177 images of womens shoes was built. A pretrained architecture was selected to be refined, in order to produce a classification model. As a main result of this study, we confirm that the use of transfer learning speeds up deep neural nets training, allowing outstanding results through a VGG16 architecture. In terms of accuracy, the results achieved 99.97% and 98.42% for classifying respectively footwear categories and subcategories.

Effects of Obesity on Medial Tibiofemoral Cartilage Mechanics in Females—An Exploration Using Musculoskeletal Simulation and Probabilistic Cartilage Failure Modelling

This study examined the effects of obesity on cartilage mechanics and longitudinal failure probability at the medial tibiofemoral compartment, using combined musculoskeletal simulation and probabilistic failure modelling approaches. The current investigation examined twenty obese females (BMI > 30.0 kg/m2) and 20 healthy weight (BMI < 25.0 kg/m2) females. Walking kinematics were obtained via an 8-camera optoelectric system, and a force plate was used to collect ground reaction forces. Musculoskeletal simulation and probabilistic failure modelling were utilized to explore medial tibiofemoral forces and cartilage probability. Comparisons between groups were undertaken using linear mixed-effects models. Net peak cartilage forces, stress and strain were significantly larger in the obese group (force = 2013.92 N, stress = 3.03 MPa & strain = 0.25), compared to health weight (force = 1493.21 N, stress 2.26 MPa & strain = 0.19). In addition, medial tibiofemoral cartilage failure probability was also significantly larger in the obese group (42.98%) compared to healthy weight (11.63%). The findings from the current investigation show that obesity has a profoundly negative influence on longitudinal medial knee cartilage health and strongly advocates for the implementation of effective weight management programs into long-term musculoskeletal management strategies.

Learned Lifted Linearization Applied to Unstable Dynamic Systems Enabled by Koopman Direct Encoding

This paper presents a Koopman lifting linearization method that is applicable to nonlinear dynamical systems having both stable and unstable regions. It is known that DMD and other standard data-driven methods face a fundamental difficulty in constructing a Koopman model when applied to unstable systems. Here we solve the problem by incorporating knowledge about a nonlinear state equation with a learning method for finding an effective set of observables. In a lifted space, stable and unstable regions are separated into independent subspaces. Based on this property, we propose to find effective observables through neural net training where training data are separated into stable and unstable trajectories. The resultant learned observables are used for constructing a linear state transition matrix using method known as Direct Encoding, which transforms the nonlinear state equation to a state transition matrix through inner product computations with the observables. The proposed method shows a dramatic improvement over existing DMD and data-driven methods.

Non-thermal and thermal effects on mechanical strain in substrate-transferred wafer-scale hBN films

Wafer-scale thin films of hexagonal boron nitride have exceptional thermal and mechanical properties, which harness the potential use of these materials in two-dimensional electronic, device applications. Along with unavoidable defects, grains, and wrinkles, which develop during the growth process, underlying substrates influence the physical and mechanical properties of these films. Understanding the interactions of these large-scale films with different substrates is, thus, important for the implementation of this 2D system in device fabrication. MOVPE-grown 2 and 30 nm hBN/sapphire films of size 2 in. diameter are delaminated chemically and transferred on quartz, SiO2/Si, and sapphire substrates. The structural characteristics of these films are investigated by employing Raman spectroscopy. Our results suggest that not only the roughness but also the height modulation at the surface of the substrates play a pivotal role in determining substrate-mediated mechanical strain inhomogeneity in these films. The statistical analysis of the spectral parameters provides us with the overall characteristics of the films. Furthermore, a Stark difference in the thermal evolution of strain in these films depending on substrate materials is observed. It has been demonstrated that not only the differential thermal expansion coefficient of the substrates and the films, but also slippage of the latter during the thermal treatment determines the net strain in the films. The role of the slippage is significantly higher in 2 nm films than in 30 nm films. We believe that the observations provide crucial information on the structural characteristics of the substrate-coupled wafer-scale hBN films for their future use in technology.

An elastoplastic damage model of concrete under cyclic loading and its numerical implementation

A novel elastoplastic damage model describing the complex mechanical behaviors such as stiffness degradation and irreversible deformation of concrete under cyclic loading is constructed and the complete procedure for numerical implementation is presented. To solve the key problems including multi-axial stress states, asymmetry in tension and compression and conversion between tension and compression under cyclic loading, a series of approaches are put forward. A scalar equivalent strain based on the Hsieh-Ting-Chen strength criterion in the framework of strain space is used to convert the complex multiaxial stress state to the simple uniaxial one. Correspondingly, the equivalent strain obtained by the characteristic strength curve addresses the asymmetry in tension and compression, so that the stress–strain relationship in both uniaxial tension and uniaxial compression can be represented by the same curve, and a single damage scalar is available to characterize both tensile damage and compressive damage. To overcome the difficulty of conversion between tension and compression owing to the non-negative equivalent strain, a net equivalent strain is defined to keep the curve proceeding in the first quadrant under reverse loading. Meanwhile, a nominal damage variable is proposed to ensure that the reloading curve can return to the original stress–strain envelope. A new framework of the model with a concise mathematical form has been numerically implemented and is independent of the selection of fundamental governing equations. Typical experimental tests involving three-point bending test, mixed-mode bending test, cyclic uniaxial test, and reciprocating loading test are used for verification. The results calculated by the proposed model are all in good agreement with the tests. As a result, the correctness and reliability of the novel model are demonstrated.

Impact of stress triaxiality, strain rate, and temperature on the mechanical response and morphology of PVDF

Poly-vinylidene fluoride (PVDF) is a semi-crystalline thermoplastic featuring a high chemical resistance, good thermal stability, and high pressure resistance, rendering it attractive for a wide range of engineering applications. This study assesses the influence of temperature, strain rate, and stress triaxiality on the large-strain response of a commercial PVDF copolymer containing poly-ethylene (PE) particles.The thermo-viscoplastic response of the material was investigated at six temperatures ranging between −20°C and 100°C at a quasi-static strain rate ė of 0.005s−1, and three strain rates ė={0.005,0.1,1.0}s−1 at room temperature. To study the pressure sensitivity of the material, tensile tests using axisymmetric notched tensile specimens with three different notch radii as well as uniaxial compression tests were performed. The mechanical response was assessed in terms of net axial stress and volume strain vs. longitudinal strain, measured using digital image correlation (DIC). To gain insight into the interrelationship between the macroscopic volume strain and void morphology on the microscale, selected cross sections of deformed specimens were imaged employing scanning electron microscopy (SEM).The material exhibited a temperature- and strain-rate-dependent response as well as a pressure-sensitive flow stress. For ambient temperatures up to 60°C, pronounced plastic dilatancy was observed, promoted by increasing the stress triaxiality. The SEM study confirmed that the plastic dilatancy was a result of extensive void nucleation and growth on the microscale. Two sources of void nucleation were identified, namely particle–matrix interface separation as well as cavitation within the matrix material itself. In tests performed at ambient temperatures higher than 80°C, no plastic dilation was observed and no voids or PE particles were identified in the SEM images.Apart from an improved understanding of the material’s mechanical response, this study provides data and insights suitable for the development and calibration of constitutive models, aiding the design of robust and reliable structures using PVDF.

Intrinsic flexoelectricity of van der Waals epitaxial thin films

The direct measurement of flexoelectric coefficients in epitaxial thin films is an unresolved problem, due to the clamping effect of substrates which induces a net strain (and hence parasitic piezoelectricity) in addition to strain gradients and flexoelectricity. Herein, we propose and demonstrate the use of van der Waals epitaxy as a successful strategy for measuring the intrinsic (clamping-free = flexoelectric coefficients of epitaxial thin films. We have made, measured, and compared ${\mathrm{BaTiO}}_{3}$ and ${\mathrm{SrTiO}}_{3}$ thin film capacitor heterostructures grown both by conventional oxide-on-oxide epitaxy and by van der Waals oxide-on-mica epitaxy, and found that, whereas the former is dominated by parasitic piezoelectricity, the response of the latter is truly flexoelectric. The results are backed by theoretical calculations of the film-substrate mechanical interaction, as well as by direct measurements that confirm the strain-free state of the films. van der Waals epitaxy thus emerges as powerful new tool in the study of flexoelectricity and, in particular, they finally allow exploring flexoelectric phenomena at the nanoscale (where strain gradients are highest) with direct experimental knowledge of the actual flexoelectric coefficients of thin films.

On strain-based rupture criterion for ascending aortic aneurysm: The role of fiber waviness

We propose a new approach for constructing strain-based rupture criterion for ascending thoracic aortic aneurysm. The rupture metric is formulated using an effective strain, which is a measure of net strain that the collagen bundles experience after fiber uncrimping. The effective strain is a function of the total strain and the waviness properties of the collagen fibers. In the present work, the waviness properties are obtained from fitting biaxial response data to constitutive models that explicitly consider the collagen waviness and fiber recruitment. Inflation test data from 10 ascending thoracic aortic aneurysm specimens are analyzed. For each specimen, tension-strain data at ∼2300 material points are garnered. The effective strain fields in the configuration immediately before rupture are computed. It is found that the hotspots of the effective strain match the rupture sites very well in all 10 samples. More importantly, the values of effective strain at the hotsopts are closely clustered around 0.1, in contrast to a much wider distribution of the total strain. The study underscores the importance of considering the fiber recruitment in formulating strain-based rupture metric, and suggests that ϵ¯≈0.1, where ϵ¯ is the effective strain metric defined in this work, can be considered as a criterion for assessing the imminent rupture risk of ascending aortic aneurysms. Statement of significanceWe advocate to use effective strain in ATAA rupture assessment. The effective strain is a measure of net strain in the collagen network after waviness uncrimping. We analyzed bulge inflation data of ATAA samples. It was found that, while the total strains at rupture varied from sample to sample, the effective strains were closely clustered around 0.1. And the hotspots of effective strain matched the rupture sites well. The work underlines the importance of considering collagen fiber waviness and recruitment when evaluating the rupture risk using strain, and suggests a new direction for developing sharper rupture metrics.

Characterization of face-centered cubic structure and deformation mechanisms in high energy shot peening process of TC17

• The B-type face-centered cubic titanium (fcc-Ti) occurred in the severely deformed TC17. • The deformation twinning acted as a primary deformation mechanism for fcc-Ti. • The gliding of Shockley partials was responsible for different deformation twins in fcc-Ti. • The occurrence of fcc-Ti effectively promoted the grain refinement of TC17. The face-centered cubic structure (fcc) and its deformation behaviors, as well as the distinctive role of fcc-Ti in nanocrystallization in TC17 subjected to high energy shot peening (HESP), were investigated by using comprehensive high-resolution transmission electron microscopy (HRTEM). The results showed that there was a stress-induced fcc-Ti in TC17 with a lattice constant of 0.420–0.433 nm and the B-type orientation relationship between the hcp-Ti and the fcc-Ti as [2-1-10] hcp //[-110] fcc and (0001) hcp //(111) fcc , which was accomplished by the gliding of Shockley partial dislocations with Burgers vector of 1/3[01-10] on the basal plane. The deformation twinning dominated the subsequent deformation of fcc-Ti, producing two types of {111}<11-2> twins with different characteristics. Among them, the I-type twin with complete structure was generated by successive gliding of Shockley partial dislocations with the same Burgers vector of 1/6[11-2]. In contrast, the cooperative slip of three Shockley partials, whose sum of Burgers vectors was equal to zero, produced the II-type twin with zero net macroscopic strain. And then, the emission of Shockley partial with the Burgers vector of 1/6[11-2] on every three (111) fcc planes resulted in the formation of a 9R structure. Due to the dissociation effect of lamellar fcc-Ti and the superior deformation ability of fcc structure, the occurrence of fcc-Ti effectively promoted surface nanocrystallization of TC17.

Local norms describing the role of the state and the private provision of training

Apprenticeship systems are essentially based on the voluntary participation of firms that provide, and usually also finance, training positions, often incurring considerable net training costs. One potential, yet under-researched explanation for this behavior is that firms act in accordance with the norms and expectations they face in the local labor market in which they operate. In this paper, we focus on the Swiss apprenticeship system and ask whether local norms towards the private, rather than the public, provision of training influence firms’ decisions to offer apprenticeship positions. In line with this hypothesis, we find that the training incidence is higher in communities characterized by a stronger norm towards the private provision of training, which we measure using local results from two national-level plebiscites that explicitly dealt with the role of the state in the context of the apprenticeship system. This finding turns out to be robust to a series of alternative specifications and robustness checks.

Multi-objective optimization of heat sink with multi-cross-ribbed-fins for a motor controller

A novel multi-cross-ribbed-fin layout was proposed to supersede the original smooth fin to fulfill the lightweight requirement of the air-cooled heat sink for the electrical vehicle motor controller. The thermal design with multi-cross-ribbed-fins was optimized using the multi-objective optimization method to minimize the chip’s temperature rise and the weight of the heat sink simultaneously. The design variables are the number of multi-cross-ribbed-fins ranging from 12 to 24, the number of cross ribs on either side varying from 1 to 4, and cross rib height in the region of 1.00–2.50mm. The standard k-ε turbulence model was validated compared to the experimental data for the original heat sink with smooth fins. The Pareto front solution set was obtained by performing the mixed-level orthogonal design procedure with the numerical simulations, constructing the surrogated-based model with backpropagation neural net training, and implementing the genetic algorithm. The numerical results showed that the recommended optimal designs have the multi-cross-ribbed-fin number of 17–19, the number of cross ribs of 2–3, and a cross rib height of 2.13–2.50mm. The maximum decreases in the temperature rise and weight are 7.63% and 9.45%, respectively. For verifying the superiority of current optimal designs, one of the optimal designs of the heat sink, which yields comparative temperature rise of the chip but reduced weight, was selected to be experimentally tested and compared with the data for the original heat sink.

Cyclic flexural performance of RC beams with small circular openings in plastic hinge region

This paper describes the effect of a small circular web opening located in the plastic hinge region on the cyclic flexural performance of RC beams. The variable in the design of specimens is the diameter of the circular web openings installed in the plastic hinge region. Two rectangular beams scaled down to 67% of a practical RC beam were fabricated to have circular openings in the plastic hinge region with diameters 0.2 and 0.3 times the height of the beam. In another beam, in addition to the opening in the plastic hinge region, a web opening with a diameter of 0.3 times the height of the beam was installed at a location 180 mm from the center of the span. A total of four beams including a control beam were subjected to cyclic anti-symmetric moment. The cyclic flexural performance of the beams was evaluated in terms of hysteretic response, including strength, stiffness, ductility, and energy dissipation capacity. The neutral axis depth of the plastic hinge during the cyclic loading test was calculated using the linear distribution of strains of longitudinal reinforcing bars placed at the top and bottom of the openings. In addition, using the effective depth of the RC beams and the net tensile strain in the extreme tension reinforcement for tension-controlled sections, which are recommended by ACI 318–19, the maximum diameter of the circular web opening in the plastic hinge region was approximated and compared with the test results. Furthermore, with reference to the results of certain exiting studies, the ratio of the spacing between openings to the maximum diameter of the circular web opening was suggested by assuming the case of designing web openings to leap over major shear cracks expected to occur in a flexural RC beam undergoing shear-flexural failure.