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This research develops a data-driven methodology for structural instability problems with highly nonlinear, difficult, noisy, and small data. A fast analysis and prediction (FAP) approach for instability problems of thin shells is first proposed. This approach contains two phases: the fast numerical analysis and the pure prediction utilizing artificial neural networks (ANNs) incorporated with the Bayesian regularization (B-R) algorithm as follows: (1) in Phase 1 (the fast numerical analysis), post-buckling analysis is conducted utilizing a minor amount of load steps. The load–displacement relation achieved from Phase 1 is not exact because of the small number of load steps utilized; (2) in Phase 2 (the prediction), the loads and deflections achieved from Phase 1 were employed as the data for training ANNs. The trained networks, including the load and displacement networks, were employed to fast predict loads and deflections at any step of the post-buckling analysis. After utilizing Phase 2, a smooth, complete and exact load–displacement curve was achieved. In Phase 1, the available formulation for post-buckling analysis of thin shells in the literature was utilized. Five popular types of instabilities chosen to confirm the effectiveness and exactness of the FAP were snap-through, snap-back, softening–hardening, kink instabilities, and delamination buckling and post-buckling of composites. The high exactness and effectiveness of the FAP were confirmed in the numerical verification section. The present approach saves a huge computation compared to the other ones. It was found that ANNs incorporated with the B-R algorithm have notable advantages compared to numerous neural networks. The proposed approach is applicable to simulations or experiments where data are “expensive”, highly nonlinear, difficult, and limited. Utilizing the proposed approach for these fields can dramatically save time and money.

Animal models have proven integral to broadening our understanding of complex cardiac diseases but have been hampered by significant species-dependent differences in cellular physiology. Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have shown great promise in the modelling of cardiac diseases despite limitations in functional and structural maturity. 3D stem cell-derived cardiac models represent a step towards mimicking the intricate microenvironment present in the heart as an in vitro model. Incorporation of non-myocyte cell types, such as cardiac fibroblasts, into engineered heart tissue models (EHTs) can help better recapitulate the cell-to-cell and cell-to-matrix interactions present in the human myocardium. Integration of human-induced pluripotent stem cell-derived cardiac fibroblasts (hiPSC-CFs) and hiPSC-CM into EHT models enables the generation of a genetically homogeneous modelling system capable of exploring the abstruse structural and electrophysiological interplay present in cardiac pathophysiology. Furthermore, the construction of more physiologically relevant 3D cardiac models offers great potential in the replacement of animals in heart disease research. Here we describe efficient and reproducible protocols for the differentiation of hiPSC-CMs and hiPSC-CFs and their subsequent assimilation into EHTs. The resultant EHT consists of longitudinally arranged iPSC-CMs, incorporated alongside hiPSC-CFs. EHTs with both hiPSC-CMs and hiPSC-CFs exhibit slower beating frequencies and enhanced contractile force compared to those composed of hiPSC-CMs alone. The modified protocol may help better characterise the interplay between different cell types in the myocardium and their contribution to structural remodelling and cardiac fibrosis.

Animal models have proven integral to broadening our understanding of complex cardiac diseases but have been hampered by significant species-dependent differences in cellular physiology. Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have shown great promise in the modelling of cardiac diseases despite limitations in functional and structural maturity. 3D stem cell-derived cardiac models represent a step towards mimicking the intricate microenvironment present in the heart as an in vitro model. Incorporation of non-myocyte cell types, such as cardiac fibroblasts, into engineered heart tissue models (EHTs) can help better recapitulate the cell-to-cell and cell-to-matrix interactions present in the human myocardium. Integration of human-induced pluripotent stem cell-derived cardiac fibroblasts (hiPSC-CFs) and hiPSC-CM into EHT models enables the generation of a genetically homogeneous modelling system capable of exploring the abstruse structural and electrophysiological interplay present in cardiac pathophysiology. Furthermore, the construction of more physiologically relevant 3D cardiac models offers great potential in the replacement of animals in heart disease research. Here we describe efficient and reproducible protocols for the differentiation of hiPSC-CMs and hiPSC-CFs and their subsequent assimilation into EHTs. The resultant EHT consists of longitudinally arranged iPSC-CMs, incorporated alongside hiPSC-CFs. EHTs with both hiPSC-CMs and hiPSC-CFs exhibit slower beating frequencies and enhanced contractile force compared to those composed of hiPSC-CMs alone. The modified protocol may help better characterise the interplay between different cell types in the myocardium and their contribution to structural remodelling and cardiac fibrosis.

Abstract Activation of cardiac fibroblasts and differentiation to myofibroblasts underlies development of pathological cardiac fibrosis, leading to arrhythmias and heart failure. Myofibroblasts are characterised by increased α-smooth muscle actin (α-SMA) fibre expression, secretion of collagens and changes in proliferation. Transforming growth factor-beta (TGF-β) and increased mechanical stress can initiate myofibroblast activation. Reversibility of the myofibroblast phenotype has been observed in murine cells but has not been explored in human cardiac fibroblasts. In this study, chronically activated adult primary human ventricular cardiac fibroblasts and human induced pluripotent stem cell derived cFbs (hiPSC-cFbs) were used to investigate the potential for reversal of the myofibroblast phenotype using either subculture on soft substrates or TGF-β receptor inhibition. Culture on softer plates (25 or 2 kPa Young’s modulus) did not alter proliferation or reduce expression of α-SMA and collagen 1. Similarly, culture of myofibroblasts in the presence of TGF-β inhibitor did not reverse myofibroblasts back to a quiescent phenotype. Chronically activated hiPSC-cFbs also showed attenuated response to TGF-β receptor inhibition and inability to reverse to quiescent fibroblast phenotype. Our data demonstrate substantial loss of TGF-β signalling plasticity as well as a loss of feedback from the surrounding mechanical environment in chronically activated human myofibroblasts.

Animal models have proven integral to broadening our understanding of complex cardiac diseases but have been hampered by significant species-dependent differences in cellular physiology. Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have shown great promise in the modelling of cardiac diseases despite limitations in functional and structural maturity. 3D stem cell-derived cardiac models represent a step towards mimicking the intricate microenvironment present in the heart as an in vitro model. Incorporation of non-myocyte cell types, such as cardiac fibroblasts, into engineered heart tissue models (EHTs) can help better recapitulate the cell-to-cell and cell-to-matrix interactions present in the human myocardium. Integration of human-induced pluripotent stem cell-derived cardiac fibroblasts (hiPSC-CFs) and hiPSC-CM into EHT models enables the generation of a genetically homogeneous modelling system capable of exploring the abstruse structural and electrophysiological interplay present in cardiac pathophysiology. Furthermore, the construction of more physiologically relevant 3D cardiac models offers great potential in the replacement of animals in heart disease research. Here we describe efficient and reproducible protocols for the differentiation of hiPSC-CMs and hiPSC-CFs and their subsequent assimilation into EHTs. The resultant EHT consists of longitudinally arranged iPSC-CMs, incorporated alongside hiPSC-CFs. EHTs with both hiPSC-CMs and hiPSC-CFs exhibit slower beating frequencies and enhanced contractile force compared to those composed of hiPSC-CMs alone. The modified protocol may help better characterise the interplay between different cell types in the myocardium and their contribution to structural remodelling and cardiac fibrosis.

Animal models have proven integral to broadening our understanding of complex cardiac diseases but have been hampered by significant species-dependent differences in cellular physiology. Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have shown great promise in the modelling of cardiac diseases despite limitations in functional and structural maturity. 3D stem cell-derived cardiac models represent a step towards mimicking the intricate microenvironment present in the heart as an in vitro model. Incorporation of non-myocyte cell types, such as cardiac fibroblasts, into engineered heart tissue models (EHTs) can help better recapitulate the cell-to-cell and cell-to-matrix interactions present in the human myocardium. Integration of human-induced pluripotent stem cell-derived cardiac fibroblasts (hiPSC-CFs) and hiPSC-CM into EHT models enables the generation of a genetically homogeneous modelling system capable of exploring the abstruse structural and electrophysiological interplay present in cardiac pathophysiology. Furthermore, the construction of more physiologically relevant 3D cardiac models offers great potential in the replacement of animals in heart disease research. Here we describe efficient and reproducible protocols for the differentiation of hiPSC-CMs and hiPSC-CFs and their subsequent assimilation into EHTs. The resultant EHT consists of longitudinally arranged iPSC-CMs, incorporated alongside hiPSC-CFs. EHTs with both hiPSC-CMs and hiPSC-CFs exhibit slower beating frequencies and enhanced contractile force compared to those composed of hiPSC-CMs alone. The modified protocol may help better characterise the interplay between different cell types in the myocardium and their contribution to structural remodelling and cardiac fibrosis.

For the first time, this paper introduces a Fast Analysis and Prediction (FAP) approach for geometrically nonlinear bending analysis of plates and shells. The proposed approach consists of two phases: fast analysis and prediction using artificial neural networks (ANNs) combined with the Bayesian regularization algorithm. In the first phase (fast analysis), geometrically nonlinear bending analysis of a structure is performed using only several load steps. This enables the efficient computation within a short period of time. In the second phase (prediction using ANNs), the deflections obtained in the first phase are utilized as the data for training the ANNs. The trained networks are then used to quickly predict deflections at any load step. The calculation process in the second phase is also very fast. For the analysis package in the first phase, the formulation of this paper is originated from the literature for geometrically nonlinear analysis of composite shells. High accuracy and efficiency of the FAP approach were demonstrated via solving nonlinear bending problems of plates and shells including an isotropic square plate, a composite cylinder subjected to internal pressure, a FG-CNTRC panel and a pinched cylinder with end diaphragms. The proposed approach offers significantly computational savings (up to 70%) compared to the conventional one. ANNs combined with the Bayesian regularization algorithm, which are proposed for the FAP approach in this work, possess the outstanding advantages compared to many existing neural networks. The FAP approach can be applied to simulations, observations, or experiments where nonlinear responses are present or data is limited. Applying the FAP approach to such areas can significantly save labor, time, and money. [ABSTRACT FROM AUTHOR]

Background. Asparagus root (Asparagus officinalis L.) is one of the herbaceous by-products with potential for making added-valued food products, due to its excellent nutritional properties and flavor/fragrance. In order to maintain its quality, several drying methods were investigated to select an advanced one that could be widely applied in the processing of dried vegetable products. Materials and methods. A thin layer at 40-90°C using a thin-layer drying oven was investigated to study the thermal degradation kinetic of bioactive compounds, including vitamin C, phenolic, flavonoid, saponin and antioxidant capacity of dried asparagus roots. Linear and non-linear regression analysis (zero-, first and second-order) was employed to assess the parameters, which helped select the optimal model that accurately characterizes an efficient drying process for asparagus roots. Results. The first-order model was described for vitamin C degradation and matched the experimental data well. The decomposition of phenolic, flavonoid, saponin and antioxidant capacity followed the second-order model with the highest coefficient of determination value (R² > 0.99) and the lowest root mean squared error (RMSE) value. Enhanced levels of bioactive compounds and antioxidant capacity notably slowed down the degradation of anthocyanins at a temperature of 70². Conclusion. This study reflected the thermal degradation kinetic for the drying process. The results could provide useful information for the optimizing the drying of asparagus roots with the aim being to obtain a product with high nutritive quality and bioactivity. [ABSTRACT FROM AUTHOR]

Inappropriate fertilizer application for rice crop resulted in the yield and soil fertility issues, then biochar and bioorganic utilization considered as the best solution for this situation. This study aimed to assess the combination of biochar and BOFs on growth and yield of lowland rice. The experiments were conducted at the field in Thua Thien Hue province, Central Vietnam in two crop seasons from 2023-2024. The completely randomized block experimental design involved three replications with five treatment combinations i.e., 100% NPK (control); 80% NPK + 5 t/ha BOF + 2 t/ha biochar; 80% CMOF + 5 t/ha BF + 2 t/ha biochar + 400 kg/ha lime; 70% CMOF + 5 t/ha BOF + 3 t/ha biochar + 400 kg/ha lime; 60% CMOF + 10 t/ha BOF + 3 t/ha biochar + 400 kg/ha lime. The effect of these treatments was analyzed using analysis of variance (ANOVA) and least significant difference (LSD) with a 95% confidence level (α=0.05). We found that the optimal combination is 80% NPK + 5 t/ha BOF + 2 t/ha biochar on rice plant height (98.67 cm), dry matter (12.43 g/plant) and economic yields (6.95 t/ha). The combination is capable of increasing the rice productivity according to rice performance and yield. [ABSTRACT FROM AUTHOR]

Objective: This study reports the mortality burden due to PM2.5 exposure among adults (age >25) living in Hanoi in 2017.Methods: We applied a health impact assessment methodology with the global exposure mortality model and a PM2.5 map with 3 × 3 km resolution derived from multiple data sources.Results: The annual average PM2.5 concentration for each grid ranged from 22.1 to 37.2 µg/m³. The district average concentration values ranged from 26.9 to 37.2 µg/m³, which means that none of the 30 districts had annual average values below the Vietnam Ambient National Standard of 25 µg/m3. Using the Vietnam Ambient National Standard as the reference standard, we estimated that 2,696 deaths (95% CI: 2,225 to 3,158) per year were attributable to exposure to elevated PM2.5 concentrations in Hanoi. Using the Interim Target 4 value of 10 µg/m3 as the reference standard, the number of excess deaths attributable to elevated PM2.5 exposure was 4,760 (95% CI: 3,958–5,534).Conclusion: A significant proportion of deaths in Hanoi could be avoided by reducing air pollution concentrations to a level consistent with the Vietnam Ambient National Standard.