Numerical simulation of explosive fracturing with smoothed particle hydrodynamics

In this paper we study explosive fracturing with smoothed particle hydrodynamics (SPH). As a particle based Lagrangian method, SPH is particularly suited to the analysis of fracture due to its full Lagrangian frame and capacity to model large deformation. We adopt the Jones-Wilkins-Lee equation as equation of state of the trinitrotoluene (TNT) explosive and a continuum elasto-damage model to predict the fracture of the rock. We predict the evolution of damage using the strain history of each particle. To strengthen the interaction of coupling interfaces we use a penalty function to avoid penetration between different material particles

Modulating Notochordal Differentiation of Human Induced Pluripotent Stem Cells using Natural Nucleus Pulposus Tissue Matrix

Human induced pluripotent stem cells (hiPSCs) can differentiate into notochordal cell (NC)-like cells when cultured in the presence of natural porcine nucleus pulposus (NP) tissue matrix. The method promises massive production of high-quality, functional cells to treat degenerative intervertebral discs (IVDs). Based on our previous work, we further examined the effect of cell-NP matrix contact and culture medium on the differentiation, and further assessed the functional differentiation ability of the generated NC-like. The study showed that direct contact between hiPSCs and NP matrix can promote the differentiation yield, whilst both the contact and non-contact cultures can generate functional NC-like cells. The generated NC-like cells are highly homogenous regarding the expression of notochordal marker genes. A culture medium containing a cocktail of growth factors (FGF, EGF, VEGF and IGF-1) also supported the notochordal differentiation in the presence of NP matrix. The NC-like cells showed excellent functional differentiation ability to generate NP-like tissue which was rich in aggrecan and collagen type II; and particularly, the proteoglycan to collagen content ratio was as high as 12.5-17.5 which represents a phenotype close to NP rather than hyaline cartilage. Collectively, the present study confirmed the effectiveness and flexibility of using natural NP tissue matrix to direct notochordal differentiation of hiPSCs, and the potential of using the generated NC-like cells for treating IVD degeneration

A micromechanics-informed phase field model for brittle fracture accounting for the unilateral constraint

We propose a new direction-dependent model for the unilateral constraint involved in the phase field approach to fracture and also in the continuous damage mechanics models. The construction of this phase field model is informed by micromechanical modeling through the homogenization theory, where the representative volume element (RVE) has a planar crack in the center. The proposed model is made closely match the response of the RVE, including the frictionless self-contact condition. This homogenization approach allows to identify a direction-dependent phase field model with the tension-compression split obtained from cracked microstructures. One important feature of the proposed model is that unlike most other models, the material degradation is consistently determined without artificial assumptions or ad hoc parameters with no physical interpretation, thus, a more realistic modeling is resulted. With standard tests such as uniaxial loadings, three-point bending, simple shear, and through-crack tests, the proposed model predicts reasonable crack paths. Moreover, with the RVE response as a benchmark, the proposed model gives rise to an accurate stress-strain curve under shear loads, more accurate than most existing models

Fiber Optic Vibration Sensor Based on the Tilted Fiber Bragg Grating

A temperature-insensitive fiber optic vibration sensor based on the tilted fiber Bragg grating (TFBG) is presented. The sensing head is formed by insertion of a small section of MMF between a single-mode fiber and the TFBG. The reflection light from this tilted fiber Bragg grating includes two parts: the reflected Bragg mode and the cladding modes. The cladding modes were coupled back into the core mode as a function of the multimode fiber. The power of the cladding modes is sensitive to vibration, so the external vibration measurement can be obtained through the cladding mode average output power. Experiment results show that the root mean square (RMS) of the detection error of the average power was 0.01 μW within the temperature range from 20 to 70°C, so it is proved to be temperature independent; its frequency response has been tested to 1 KHz

Magnetic γ-Fe2O3-Loaded Attapulgite Sorbent for Hg0 Removal in Coal-Fired Flue Gas

A magnetically recoverable composite mercury removal sorbent was produced by introducing magnetic γ-Fe2O3 into attapulgite (ATT) (xFe1ATT) via the co-precipitation method and used to remove Hg0 in the simulated coal-fired power plant flue gas. The as-prepared 0.5Fe1ATT sorbent was characterized by X-ray diffraction, Brunauer–Emmett–Teller, transmission electron microscopy, vibrating sample magnetometer, X-ray photoelectron spectroscopy, and Fourier transform infrared spectroscopy analyses. The results showed that the Hg0 removal performance of the composite of γ-Fe2O3 and ATT was significantly promoted in comparison to pure γ-Fe2O3 and ATT individually. A relatively high magnetization value and good Hg0 removal performance were obtained by the sample of 0.5Fe1ATT. O2 could enhance Hg0 removal activity via the Mars–Maessen mechanism. NO displayed a significant promotion effect on Hg0 removal as a result of the formation of active species, such as NO2 and NO+. SO2 inhibited the removal of Hg0 as a result of its competition adsorption against Hg0 for the active sites and the sulfation of the sorbent. However, the introduction of NO could obviously alleviate the adverse effect of SO2 on the Hg0 removal capability. H2O showed a prohibitive effect on Hg0 removal as a result of its competition with Hg0 for the active sites. The findings of this study are of fundamental importance to the development of efficient and economic magnetic mercury sorbents for Hg0 removal from coal-fired boiler flue gases

Rewritable and sustainable 2D barcode for traceability application in smart IoT based fault-tolerant mechanism.

With the development of the Internet of Things (IoT) technology, two-dimensional (2D) barcodes are widely used in smart IoT applications as a perception portal. In industries with many circulations and testing links like traceability, since the existing 2D barcode cannot be changed once it is printed, it can only be replaced with more expensive radio frequency identification (RFID) labels or new 2D barcodes, causing a waste of human resources and costs. For better circulation efficiency and resource utilization, we propose a new design of the rewritable and sustainable 2D barcode based on the fault-tolerance mechanism. The ability to add new information in the 2D barcode can be achieved through data encryption and the insertion of a rewritable layer. It means the message of 2D barcodes could be changed, and increases the flexibility and liquidity of the 2D barcode application. Besides, the encoding and decoding method of the proposed 2D barcode is presented. Experimental results have illustrated the superiority of rewritable and sustainable 2D barcodes in the traceability of herbal medicine compared with the conventional 2D barcodes, and demonstrated the feasibility of the design. The findings show the potential for significant application in the field of traceability in smart IoT, as well as in the manufacturing industry and logistics

Combination of machine learning-based bulk and single-cell genomics reveals necroptosis-related molecular subtypes and immunological features in autism spectrum disorder

BackgroundNecroptosis is a novel form of controlled cell death that contributes to the progression of various illnesses. Nonetheless, the function and significance of necroptosis in autism spectrum disorders (ASD) remain unknown and require further investigation.MethodsWe utilized single-nucleus RNA sequencing (snRNA-seq) data to assess the expression patterns of necroptosis in children with autism spectrum disorder (ASD) based on 159 necroptosis-related genes. We identified differentially expressed NRGs and used an unsupervised clustering approach to divide ASD children into distinct molecular subgroups. We also evaluated immunological infiltrations and immune checkpoints using the CIBERSORT algorithm. Characteristic NRGs, identified by the LASSO, RF, and SVM-RFE algorithms, were utilized to construct a risk model. Moreover, functional enrichment, immune infiltration, and CMap analysis were further explored. Additionally, external validation was performed using RT-PCR analysis.ResultsBoth snRNA-seq and bulk transcriptome data demonstrated a greater necroptosis score in ASD children. Among these cell subtypes, excitatory neurons, inhibitory neurons, and endothelials displayed the highest activity of necroptosis. Children with ASD were categorized into two subtypes of necroptosis, and subtype2 exhibited higher immune activity. Four characteristic NRGs (TICAM1, CASP1, CAPN1, and CHMP4A) identified using three machine learning algorithms could predict the onset of ASD. Nomograms, calibration curves, and decision curve analysis (DCA) based on 3-NRG have been shown to have clinical benefit in children with ASD. Furthermore, necroptosis-based riskScore was found to be positively associated with immune activation. Finally, RT-PCR demonstrated differentially expressed of these four NRGs in human peripheral blood samples.ConclusionA comprehensive identification of necroptosis may shed light on the underlying pathogenic process driving ASD onset. The classification of necroptosis subtypes and construction of a necroptosis-related risk model may yield significant insights for the individualized treatment of children with ASD