527 resultados para Synaptonemal complex failure


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A significant proportion of research in the field of human-computer interaction has been devoted to game design. Yet, a multitude of good ideas and enthusiastic game design initiatives exist, where the games never see the light of day. Unfortunately, the causes of these failures remain often unexplored and unpublished. The challenges faced by researchers and practitioners are particularly complex when designing games for special target groups, such as children, or for a serious purpose. The HCI community would benefit from a discussion on these issues in order to avoid researchers and practitioners to repeat mistakes. We want to learn from projects that started with a promising idea, but failed or faced severe challenges. This workshop will be the first at CHI focusing on 'failed game projects'. In particular, workshop participants are encouraged to discuss issues that typically received little attention in publications and hereby contribute to the discussion on failures in the design, development and evaluation of games for and or with children. As a result, the community will benefit from these insights and lessons-learned, which will enhance the design of future (serious) games with/for children.

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Post–disaster reconstruction projects are often considered ineffectual or unproductive because on many occasions in the past they have performed extremely poorly during post-contract occupation, or have failed altogether to deliver acceptable outcomes. In some cases, these projects have already failed even before their completion, leading many sponsor aid organisations to hold these projects up as examples of how not to deliver housing reconstruction. Research into some previous unsuccessful projects has revealed that often the lack of adequate knowledge regarding the context and complexity involved in the implementation of these projects is generally responsible for their failure. Post-disaster reconstruction projects are certainly very complex in nature, often very context-specific and they can vary widely in magnitude. Despite such complexity, reconstruction projects can still have a high likelihood of success if adequate consideration is given to the importance of factors which are known to positively influence reconstruction efforts. Good outcomes can be achieved when planners and practitioners ensure best practices are embedded in the design of reconstruction projects at the time reconstruction projects they are first instigated. This paper outlines and discusses factors that significantly contribute to the successful delivery of post-disaster housing reconstruction projects.

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Anisotropic damage distribution and evolution have a profound effect on borehole stress concentrations. Damage evolution is an irreversible process that is not adequately described within classical equilibrium thermodynamics. Therefore, we propose a constitutive model, based on non-equilibrium thermodynamics, that accounts for anisotropic damage distribution, anisotropic damage threshold and anisotropic damage evolution. We implemented this constitutive model numerically, using the finite element method, to calculate stress–strain curves and borehole stresses. The resulting stress–strain curves are distinctively different from linear elastic-brittle and linear elastic-ideal plastic constitutive models and realistically model experimental responses of brittle rocks. We show that the onset of damage evolution leads to an inhomogeneous redistribution of material properties and stresses along the borehole wall. The classical linear elastic-brittle approach to borehole stability analysis systematically overestimates the stress concentrations on the borehole wall, because dissipative strain-softening is underestimated. The proposed damage mechanics approach explicitly models dissipative behaviour and leads to non-conservative mud window estimations. Furthermore, anisotropic rocks with preferential planes of failure, like shales, can be addressed with our model.

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Completing a PhD on time is a complex process, influenced by many interacting factors. In this paper we take a Bayesian Network approach to analyzing the factors perceived to be important in achieving this aim. Focusing on a single research group in Mathematical Sciences, we develop a conceptual model to describe the factors considered to be important to students and then quantify the network based on five individual perspectives: the students, a supervisor and a university research students centre manager. The resultant network comprised 37 factors and 40 connections, with an overall probability of timely completion of between 0.6 and 0.8. Across all participants, the four factors that were considered to most directly influence timely completion were personal aspects, the research environment, the research project, and incoming skills.

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Light gauge steel frame wall systems are commonly used in industrial and commercial buildings, and there is a need for simple fire design rules to predict their load capacities and fire resistance ratings. During fire events, the light gauge steel frame wall studs are subjected to non-uniform temperature distributions that cause thermal bowing, neutral axis shift and magnification effects and thus resulting in a combined axial compression and bending action on the studs. In this research, a series of full-scale fire tests was conducted first to evaluate the performance of light gauge steel frame wall systems with eight different wall configurations under standard fire conditions. Finite element models of light gauge steel frame walls were then developed, analysed under transient and steady-state conditions and validated using full-scale fire tests. Using the results from fire tests and finite element analyses, a detailed investigation was undertaken into the prediction of axial compression strength and failure times of light gauge steel frame wall studs in standard fires using the available fire design rules based on Australian, American and European standards. The results from both fire tests and finite element analyses were used to investigate the ability of these fire design rules to include the complex effects of non-uniform temperature distributions and their accuracy in predicting the axial compression strength of wall studs and the failure times. Suitable modifications were then proposed to the fire design rules. This article presents the details of this investigation on the fire design rules of light gauge steel frame walls and the results.

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Recent fire research into the behaviour of light gauge steel frame (LSF) wall systems has devel-oped fire design rules based on Australian and European cold-formed steel design standards, AS/NZS 4600 and Eurocode 3 Part 1.3. However, these design rules are complex since the LSF wall studs are subjected to non-uniform elevated temperature distributions when the walls are exposed to fire from one side. Therefore this paper proposes an alternative design method for routine predictions of fire resistance rating of LSF walls. In this method, suitable equations are recommended first to predict the idealised stud time-temperature pro-files of eight different LSF wall configurations subject to standard fire conditions based on full scale fire test results. A new set of equations was then proposed to find the critical hot flange (failure) temperature for a giv-en load ratio for the same LSF wall configurations with varying steel grades and thickness. These equations were developed based on detailed finite element analyses that predicted the axial compression capacities and failure times of LSF wall studs subject to non-uniform temperature distributions with varying steel grades and thicknesses. This paper proposes a simple design method in which the two sets of equations developed for time-temperature profiles and critical hot flange temperatures are used to find the failure times of LSF walls. The proposed method was verified by comparing its predictions with the results from full scale fire tests and finite element analyses. This paper presents the details of this study including the finite element models of LSF wall studs, the results from relevant fire tests and finite element analyses, and the proposed equations.

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Ambiguity resolution plays a crucial role in real time kinematic GNSS positioning which gives centimetre precision positioning results if all the ambiguities in each epoch are correctly fixed to integers. However, the incorrectly fixed ambiguities can result in large positioning offset up to several meters without notice. Hence, ambiguity validation is essential to control the ambiguity resolution quality. Currently, the most popular ambiguity validation is ratio test. The criterion of ratio test is often empirically determined. Empirically determined criterion can be dangerous, because a fixed criterion cannot fit all scenarios and does not directly control the ambiguity resolution risk. In practice, depending on the underlying model strength, the ratio test criterion can be too conservative for some model and becomes too risky for others. A more rational test method is to determine the criterion according to the underlying model and user requirement. Miss-detected incorrect integers will lead to a hazardous result, which should be strictly controlled. In ambiguity resolution miss-detected rate is often known as failure rate. In this paper, a fixed failure rate ratio test method is presented and applied in analysis of GPS and Compass positioning scenarios. A fixed failure rate approach is derived from the integer aperture estimation theory, which is theoretically rigorous. The criteria table for ratio test is computed based on extensive data simulations in the approach. The real-time users can determine the ratio test criterion by looking up the criteria table. This method has been applied in medium distance GPS ambiguity resolution but multi-constellation and high dimensional scenarios haven't been discussed so far. In this paper, a general ambiguity validation model is derived based on hypothesis test theory, and fixed failure rate approach is introduced, especially the relationship between ratio test threshold and failure rate is examined. In the last, Factors that influence fixed failure rate approach ratio test threshold is discussed according to extensive data simulation. The result shows that fixed failure rate approach is a more reasonable ambiguity validation method with proper stochastic model.

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Here we report an ultrasensitive method for detecting bio-active compounds in biological samples by means of functionalised nanoparticles interrogated by surface enhanced Raman spectroscopy (SERS). This method is applicable to the recovery and detection of many diagnostically important peptidyl analytes such as insulin, human growth hormone, growth factors (IGFs) and erythropoietin (EPO), as well as many small molecule analytes and metabolites. Our method, developed to detect EPO, demonstrates its utility in a complex yet well defined biological system. Recombinant human EPO (rhEPO) and EPO analogues have successfully been used to treat anaemia in end-stage renal failure, chronic disorders and infections, cancer and AIDS. Current methods for EPO testing are lengthy, laborious and relatively insensitive to low concentrations. In our rapid screening methodology, gold nanoparticles were functionalised with anti-EPO antibodies to provide very high selectivity towards the EPO protein in urine. These “smart sensor” nanoparticles interact with and trap EPO. Subsequent SERS screening allows for the detection and quantisation of ultra trace amounts (<<10-15 M) of EPO in urine samples with minimal sample preparation. We present data showing that the SERS spectrum differentiates between human endogenous EPO and rhEPO in unpurified urine, and potentially distinguishes between purified EPO isoforms. The elimination of sample preparation and direct screening in biological fluids significantly reduces the time required by current methods. Antibody recognition against a variety of biological targets and the availability of portable commercial SERS analysers for rapid onsite testing suggest broad diagnostic applicability in a flexible analytical platform.

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Considerate amount of research has proposed optimization-based approaches employing various vibration parameters for structural damage diagnosis. The damage detection by these methods is in fact a result of updating the analytical structural model in line with the current physical model. The feasibility of these approaches has been proven. But most of the verification has been done on simple structures, such as beams or plates. In the application on a complex structure, like steel truss bridges, a traditional optimization process will cost massive computational resources and lengthy convergence. This study presents a multi-layer genetic algorithm (ML-GA) to overcome the problem. Unlike the tedious convergence process in a conventional damage optimization process, in each layer, the proposed algorithm divides the GA’s population into groups with a less number of damage candidates; then, the converged population in each group evolves as an initial population of the next layer, where the groups merge to larger groups. In a damage detection process featuring ML-GA, as parallel computation can be implemented, the optimization performance and computational efficiency can be enhanced. In order to assess the proposed algorithm, the modal strain energy correlation (MSEC) has been considered as the objective function. Several damage scenarios of a complex steel truss bridge’s finite element model have been employed to evaluate the effectiveness and performance of ML-GA, against a conventional GA. In both single- and multiple damage scenarios, the analytical and experimental study shows that the MSEC index has achieved excellent damage indication and efficiency using the proposed ML-GA, whereas the conventional GA only converges at a local solution.

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Business transformations are complex organisational change endeavours that result in a business performing current work differently, or performing different work. Information Technology (IT) is a key enabler of such initiatives, but comes with its challenges, as revamping the IT infrastructure in large-scale organisations implies high complexity, high risk, and often high failure rates. We view business transformations as a collection of management services that are demanded and enacted at a program level, defined as abstract resources that provide the managerial capabilities necessary for business transformations. In this research-in-progress, we explore what triggers the need for management services in response to the challenges in business transformation management. We analyse data from two exploratory case studies using the critical incident technique as our qualitative analysis method. Early findings indicate that management service triggers reside on either the strategic level, which may be internally or externally driven, or at the program management level, which may be situational, influential or reactional. We detail implications for our on-going research.

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One remaining difficulty in the Information Technology (IT) business value evaluation domain is the direct linkage between IT value and the underlying determinants of IT value or surrogates of IT value. This paper proposes a research that examines the interacting effects of the determinants of IT value, and their influences on IT value. The overarching research question is how those determinants interact with each other and affect the IT value at organizational value. To achieve this, this research embraces a multilevel, complex, and adaptive system view, where the IT value emerges from the interacting of underlying determinants. This research is theoretically grounded on three organizational theories – multilevel theory, complex adaptive systems theory, and adaptive structuration theory. By integrating those theoretical paradigms, this research proposes a conceptual model that focuses on the process where IT value is created from interactions of those determinants. To answer the research question, agent-based modeling technique is used in this research to build a computational representation based on the conceptual model. Computational experimentation will be conducted based on the computational representation. Validation procedures will be applied to consolidate the validity of this model. In the end, hypotheses will be tested using computational experimentation data.

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Human computer interaction and interaction design have recognised the need for participatory methods of co-design to contribute to designing human-centred interfaces, systems and services. Design thinking has recently developed as a set of strategies for human-centred co-design in product innovation, management and organisational transformation. Both developments place the designer in a new mediator role, requiring new skills than previously evident. This paper presents preliminary findings from a PhD case study of strategy and innovation consultancy Second Road to discuss these emerging roles of design lead, facilitator, teacher and director in action.

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Proper functioning of Insulated Rail Joints (IRJs) is essential for the safe operation of the railway signalling systems and broken rail identification circuitries. The Conventional IRJ (CIRJ) resembles structural butt joints consisting of two pieces of rails connected together through two joint bars on either side of their web and the assembly is held together through pre-tensioned bolts. As the IRJs should maintain electrical insulation between the two rails, a gap between the rail ends must be retained at all times and all metal contacting surfaces should be electrically isolated from each other using non-conductive material. At the gap, the rail ends lose longitudinal continuity and hence the vertical sections of the rail ends are often severely damaged, especially at the railhead, due to the passage of wheels compared to other continuously welded rail sections. Fundamentally, the reason for the severe damage can be related to the singularities of the wheel-rail contact pressure and the railhead stress. No new generation designs that have emerged in the market to date have focussed on this fundamental; they only have provided attention to either the higher strength materials or the thickness of the sections of various components of the IRJs. In this thesis a novel method of shape optimisation of the railhead is developed to eliminate the pressure and stress singularities through changes to the original sharp corner shaped railhead into an arc profile in the longitudinal direction. The optimal shape of the longitudinal railhead profile has been determined using three nongradient methods in search of accuracy and efficiency: (1) Grid Search Method; (2) Genetic Algorithm Method and (3) Hybrid Genetic Algorithm Method. All these methods have been coupled with a parametric finite element formulation for the evaluation of the objective function for each iteration or generation depending on the search algorithm employed. The optimal shape derived from these optimisation methods is termed as Stress Minimised Railhead (SMRH) in this thesis. This optimal SMRH design has exhibited significantly reduced stress concentration that remains well below the yield strength of the head hardened rail steels and has shifted the stress concentration location away from the critical zone of the railhead end. The reduction in the magnitude and the relocation of the stress concentration in the SMRH design has been validated through a full scale wheel – railhead interaction test rig; Railhead strains under the loaded wheels have been recorded using a non-contact digital image correlation method. Experimental study has confirmed the accuracy of the numerical predications. Although the SMRH shaped IRJs eliminate stress singularities, they can still fail due to joint bar or bolt hole cracking; therefore, another conceptual design, termed as Embedded IRJ (EIRJ) in this thesis, with no joint bars and pre-tensioned bolts has been developed using a multi-objective optimisation formulation based on the coupled genetic algorithm – parametric finite element method. To achieve the required structural stiffness for the safe passage of the loaded wheels, the rails were embedded into the concrete of the post tensioned sleepers; the optimal solutions for the design of the EIRJ is shown to simplify the design through the elimination of the complex interactions and failure modes of the various structural components of the CIRJ. The practical applicability of the optimal shapes SMRH and EIRJ is demonstrated through two illustrative examples, termed as improved designs (IMD1 & IMD2) in this thesis; IMD1 is a combination of the CIRJ and the SMRH designs, whilst IMD2 is a combination of the EIRJ and SMRH designs. These two improved designs have been simulated for two key operating (speed and wagon load) and design (wheel diameter) parameters that affect the wheel-rail contact; the effect of these parameters has been found to be negligible to the performance of the two improved designs and the improved designs are in turn found far superior to the current designs of the CIRJs in terms of stress singularities and deformation under the passage of the loaded wheels. Therefore, these improved designs are expected to provide longer service life in relation to the CIRJs.

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Travelling wave phenomena are observed in many biological applications. Mathematical theory of standard reaction-diffusion problems shows that simple partial differential equations exhibit travelling wave solutions with constant wavespeed and such models are used to describe, for example, waves of chemical concentrations, electrical signals, cell migration, waves of epidemics and population dynamics. However, as in the study of cell motion in complex spatial geometries, experimental data are often not consistent with constant wavespeed. Non-local spatial models have successfully been used to model anomalous diffusion and spatial heterogeneity in different physical contexts. In this paper, we develop a fractional model based on the Fisher-Kolmogoroff equation and analyse it for its wavespeed properties, attempting to relate the numerical results obtained from our simulations to experimental data describing enteric neural crest-derived cells migrating along the intact gut of mouse embryos. The model proposed essentially combines fractional and standard diffusion in different regions of the spatial domain and qualitatively reproduces the behaviour of neural crest-derived cells observed in the caecum and the hindgut of mouse embryos during in vivo experiments.

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NaAlH4 and LiBH4 are potential candidate materials for mobile hydrogen storage applications, yet they have the drawback of being highly stable and desorbing hydrogen only at elevated temperatures. In this letter, ab initio density functional theory calculations reveal how the stabilities of the AlH4 and BH4 complex anions will be affected by reducing net anionic charge. Tetrahedral AlH4 and BH4 complexes are found to be distorted with the decrease of negative charge. One H-H distance becomes smaller and the charge density will overlap between them at a small anion charge. The activation energies to release of H2 from AlH4 and BH4 complexes are thus greatly decreased. We demonstrate that point defects such as neutral Na vacancies or substitution of a Na atom with Ti on the NaAlH4(001) surface can potentially cause strong distortion of neighboring AlH4 complexes and even induce spontaneous dehydrogenation. Our results help to rationalize the conjecture that the suppression of charge transfer to AlH4 and BH4 anion as a consequence of surface defects should be very effective for improving the recycling performance of H2 in NaAlH4 and LiBH4. The understanding gained here will aid in the rational design and development of hydrogen storage materials based on these two systems.