Activation of Cyclin-Dependent Kinase 5 Is a Consequence of Cell Death

Cyclin-dependent kinase 5 (Cdk5) is similar to other Cdks but is activated during cell differentiation and cell death rather than cell division. Since activation of Cdk5 has been reported in many situations leading to cell death, we attempted to determine if it was required for any form of cell death. We found that Cdk5 is activated during apoptotic deaths and that the activation can be detected even when the cells continue to secondary necrosis. This activation can occur in the absence of Bim, calpain, or neutral cathepsins. The kinase is typically activated by p25, derived from p35 by calpain-mediated cleavage, but inhibition of calpain does not affect cell death or the activation of Cdk5. Likewise, RNAi-forced suppression of the synthesis of Cdk5 does not affect the incidence or kinetics of cell death. We conclude that Cdk5 is activated as a consequence of metabolic changes that are common to many forms of cell death. Thus its activation suggests processes during cell death that will be interesting or important to understand, but activation of Cdk5 is not necessary for cells to die

Applications of two neuro-based metaheuristic techniques in evaluating ground vibration resulting from tunnel blasting

Peak particle velocity (PPV) caused by blasting is an unfavorable environmental issue that can damage neighboring structures or equipment. Hence, a reliable prediction and minimization of PPV are essential for a blasting site. To estimate PPV caused by tunnel blasting, this paper proposes two neuro-based metaheuristic models: neuro-imperialism and neuro-swarm. The prediction was made based on extensive observation and data collecting from a tunnelling project that was concerned about the presence of a temple near the blasting operations and tunnel site. A detailed modeling procedure was conducted to estimate PPV values using both empirical methods and intelligence techniques. As a fair comparison, a base model considered a benchmark in intelligent modeling, artificial neural network (ANN), was also built to predict the same output. The developed models were evaluated using several calculated statistical indices, such as variance account for (VAF) and a-20 index. The empirical equation findings revealed that there is still room for improvement by implementing other techniques. This paper demonstrated this improvement by proposing the neuro-swarm, neuro-imperialism, and ANN models. The neuro-swarm model outperforms the others in terms of accuracy. VAF values of 90.318% and 90.606% and a-20 index values of 0.374 and 0.355 for training and testing sets, respectively, were obtained for the neuro-swarm model to predict PPV induced by blasting. The proposed neuro-based metaheuristic models in this investigation can be utilized to predict PPV values with an acceptable level of accuracy within the site conditions and input ranges used in this study

Multi-material topology optimisation of micro-composites with reduced stress concentration for optimal functional performance

This study develops a new multi-material topology optimisation framework for design of periodic micro-composites with optimal functional performance and reduced stress concentration. First, multi-material topology optimisation is developed based on the alternating active phase algorithm and inverse homogenisation method with the sensitivity analysis derived for specific property objective i.e., negative Poisson's ratio (NPR) or maximum effective bulk modulus (EBM) and (p-norm macroscopic) stress objective. Then, the effects of initial material distribution and weight ratio (w1, w2 assigned to the property and stress objectives, respectively) are investigated, and the evaluation indices are also developed to obtain the optimal solution. Further, two cases related to the design of micro-composites for maximised either NPR or EBM with reduced maximum stress are performed. The results show that when designing the multi-material NPR micro-composites, the decrease of w1/w2 contributes to a general decease of both NPR and maximum stress. While in designing the maximum EBM, decreasing w1/w2 leads to the reduced maximum stress and simultaneously reduced EBM; hereby, a decision-making method as well as the proposed evaluation index are both applied and compared for acquiring the optimal result. This study provides new methods and solutions to multi-material micro-composites design for future industrial applications

High velocity impact responses of sandwich panels with metal fibre laminate skins and aluminium foam core

In this paper, high velocity impact responses of newly designed sandwich panels with aluminium (AL) foam core and metal fibre laminate (FML) skins, which are comprised of aluminium sheets and plain woven E glass fibre composite plies are investigated. Gas gun impact tests were conducted to investigate the high velocity impact response of the panels subjected to the impact from a steel ball bearing at an impact velocity of around 210 m/s. The effect of the thickness of the foam core and FML skin on the impact resistance of the panels is also investigated via experimental study. A finite element model is developed for effective numerical modelling of the impact behaviour of the sandwich panels using the commercially finite element software ANSYS LS-DYNA for more extensive study of the impact response of the sandwich panels. The simplified Johnson Cook material model, the composite damage material model based on the Chang-Chang criteria, and the crushable foam material model are used to model the aluminium sheets, composite plies and the AL foam respectively. Three types of contact algorithms, i.e. the erosion contact type, the tie-break contact type and the general 3D contact type are employed to define the various contacts during the impact and to model the delamination between the FML layers and debonding between the FML skin and the AL foam. The finite element model is validated by comparing the simulated impact behaviour to that from experimental for a sandwich panel subjected to high speed impact and demonstrated to be effective and accurate. The effect of the shape of projectile and impact angle on the impact behaviour of the sandwich panels is studied using the developed finite element model. The research findings are summarized and concluded finally

Artificial neural network based mechanical and electrical property prediction of engineered cementitious composites

Engineered cementitious composite (ECC) is a type of cement-based material fabricated with a variety of add-in functional fillers, featuring superior properties of strain-hardening, ductility and energy absorption. Proper composition is essential for designing ECC material, which may lead to different mechanical and electrical properties. However the design for ECC is still a complex process on the basis of micro-mechanism followed by numerical and experimental analyses, and there is no simple model yet for practical engineering application. This study presents the prediction of mechanical and electrical properties of ECC based on the artificial neural network (ANN) technique with the aim of providing a gateway for a more efficient and effective approach in ECC design. Specifically, neural network models were developed for ECCs reinforced with polyvinyl alcohol (PVA) fibre or steel fibre (SF) with experimental data collected from other researchers for training. The development, training and validation of the proposed models were discussed. To assess the capability of well-trained ANN models for property prediction, experimental studies were conducted, including compression test, four-point bending test, tensile test and electrical resistance measurement for ECCs of various composition. Excellent consistency between the predicted and tested results is obtained, demonstrating the feasibility of ANN models for property prediction of ECCs

[In Press] A multi-material topology optimization with temperature-dependent thermoelastic properties

This is a study on the development of a novel multi-material topology optimization scheme considering temperature-dependent thermoelastic properties for engineering structure design. Two cases, a three-point-bending beam under a uniform temperature field and a cantilever beam under a non-uniform temperature field, are investigated for the effects of thermoelastic properties on topology optimization. The proposed optimization scheme is compared with two existing topology optimization approaches: conventional topology optimization and thermoelastic topology optimization. The results show that the temperature-dependent elastic modulus dominantly influences the design optimization outcomes, in terms of material distribution, structural shape and compliance, while the temperature-dependent thermal expansion coefficient has a much more crucial impact on determining the material distribution and structural geometry than on compliance. Taken together, the findings demonstrate that the developed topology optimization scheme can be used to design thermally sensitive multi-materials in industrial applications, e.g. aerospace structures under high temperature and polymers in additive manufacturing

Compression behaviours of 3D-printed CF/PA metamaterials : experiment and modelling

This study characterises the compressive behaviours of 3D-printed carbon fibre (CF) reinforced polyamide (PA) composite metamaterials with negative Poisson's ratio (NPR) or enhanced effective elastic modulus (EEEM), which were designed via a multidisciplinary approach and additively manufactured with fused filament fabrication. The continuous carbon reinforced PA (CCF/PA) metamaterials are compared to those made of short carbon fibre reinforced PA (SCF/PA) when subjected to in-plane compression. A numerical model based on continuum damage mechanics is developed to describe the response and failure of the 3D-printed CCF/PA composites while another one based an elastic-plastic model is developed for the 3D-printed SCF/PA parts. For metamaterials with NPR, the stiffness, peak force, energy absorption (EA) and specific energy absorption (SEA) of CCF/PA metamaterials are respectively 152.1%, 90%, 107.6% and 86%, respectively, larger than those of SCF/PA, while the SCF/PA metamaterials can reach a greater NPR (about −0.3) than CCF/PA (−0.2 ~ −0.1). For composites with EEEM, the stiffness, peak force, EA and SEA of CCF/PA are significantly improved by 433.3%, 183.3%, 228.7% and 208.2%, respectively, in comparison to those of SCF/PA. Based on experimental observation and numerical simulation, matrix failure is found to be predominant for CCF/PA NPR and EEEM composites

3D printed carbon-fibre reinforced composite lattice structures with good thermal-dimensional stability

A good dimensional stability is a crucial property of any base-platform structure for the attachment of high precision optical or mechanical devices, such as imaging equipment, satellite antennas, thermal sensors, etc., where the surrounding temperature may fluctuate substantially. The present study demonstrates how such a base-platform in a form of a dual-composite, planar-lattice structure can be designed and rapidly, and conveniently, manufactured using 3D printing via fused filament fabrication (FFF). Specifically, the planar-lattice consists of a central cross-lattice manufactured using a continuous carbon-fibre reinforced polyamide (CCF/PA) composite with four interlocking outer-strips manufactured using a short carbon-fibre reinforced polyamide (SCF/PA) composite. Numerical finite-element analyses of the planar-lattices are developed, and validated by experimental results, with respect to their thermal-deformation behaviour. This numerical analysis is then used to study the effects of various types of fibre architecture for the composites that might be used to manufacture the planar-lattice. The results demonstrate, for the first time, the ability of 3D printing, using FFF, to manufacture base-platform structures which use dual-composite materials, based upon carbon-fibre reinforced polyamide materials, in order to achieve a very good thermal-dimensional stability

Mechanical behaviours of green hybrid fibre-reinforced cementitious composites

New green cementitious composites reinforced with bagasse fibre and steel fibre with ultra-high volume of fly ash are developed in this paper. The mechanical properties of bagasse fibre such as the tensile strength, Young's modulus and stress-strain relationship are determined via conducting single fibre tensile test. Mechanical behaviours of the new composites, including compressive strength, Young's modulus, bending behaviour and uniaxial tensile behaviour, are investigated experimentally. The influence of the content of bagasse fibres and fly ash on the mechanical behaviour of the composites is also evaluated. The obtained results show that the compressive strength, Young's modulus, modulus of rupture and tensile strength of the composites decrease with the deduction of the content of the fly ash and bagasse fibre, but the bending toughness and tensile ductility of the material increase with fly ash content and peak as fly ash to cement ratio achieves 2.0. It is found that the mechanical properties of the composites are comparable to those of conventional concrete and are very promising green and sustainable construction and building materials and have strong potential to be used in engineering practice

Experiment and prediction of in-plane localised crushing responses of CF/EP composite sandwich panels under a semicircular indenter

This study investigates the in-plane localised crushing responses of carbon fibre reinforced epoxy (CF/EP) composite sandwich panels under a semi-circular indenter subjected to both quasi-static and dynamic loadings. The in-plane localised crushing behaviours of the CF/EP composite sandwich panels were investigated. It was found that the specimens were prone to lamina bending under quasi-static compression, whilst the specimens failed mostly with fronds fracturing under dynamic crushing. The specific energy absorption (SEA) of the panels under dynamic impact is 25.5% lower than that under quasi-static compression. An energy balance model was adopted to analyse failure mechanisms and energy dissipation. To the model, the geometry of the debris wedge was predicted using an inverse calculation with experimental validation. The results showed that the crush energy was mainly consumed by friction work and bending