Global optimisation of cold-formed steel sections

In this thesis, standard algorithms are used to carry out the optimisation of cold-formed steel purlins such as zed, channel and sigma sections, which are assumed to be simply supported and subjected to a gravity load. For zed, channel and sigma section, the local buckling, distortional buckling and lateral-torsional buckling are considered respectively herein. Currently, the local buckling is based on the BS 5950-5:1998 and EN 1993-1-3:2006. The distortional buckling is calculated by the direct strength method employing the elastic distortional buckling which is calculated by three available approaches such as Hancock (1995), Schafer and Pekoz (1998), Yu (2005). In the optimisation program, the lateral-torsional buckling based on BS 5950-5:1998, AISI and analytical model of Li (2004) are investigated. For the optimisation program, the programming codes are written for optimisation of channel, zed and sigma beam. The full study has been coded into a computer-based analysis program (MATLAB)

Improving Pareto Front Learning via Multi-Sample Hypernetworks

Pareto Front Learning (PFL) was recently introduced as an effective approach to obtain a mapping function from a given trade-off vector to a solution on the Pareto front, which solves the multi-objective optimization (MOO) problem. Due to the inherent trade-off between conflicting objectives, PFL offers a flexible approach in many scenarios in which the decision makers can not specify the preference of one Pareto solution over another, and must switch between them depending on the situation. However, existing PFL methods ignore the relationship between the solutions during the optimization process, which hinders the quality of the obtained front. To overcome this issue, we propose a novel PFL framework namely PHN-HVI, which employs a hypernetwork to generate multiple solutions from a set of diverse trade-off preferences and enhance the quality of the Pareto front by maximizing the Hypervolume indicator defined by these solutions. The experimental results on several MOO machine learning tasks show that the proposed framework significantly outperforms the baselines in producing the trade-off Pareto front.Comment: Accepted to AAAI-2

A Framework for Controllable Pareto Front Learning with Completed Scalarization Functions and its Applications

Pareto Front Learning (PFL) was recently introduced as an efficient method for approximating the entire Pareto front, the set of all optimal solutions to a Multi-Objective Optimization (MOO) problem. In the previous work, the mapping between a preference vector and a Pareto optimal solution is still ambiguous, rendering its results. This study demonstrates the convergence and completion aspects of solving MOO with pseudoconvex scalarization functions and combines them into Hypernetwork in order to offer a comprehensive framework for PFL, called Controllable Pareto Front Learning. Extensive experiments demonstrate that our approach is highly accurate and significantly less computationally expensive than prior methods in term of inference time.Comment: Under Review at Neural Networks Journa

Coxiella burnetii Blocks Intracellular Interleukin-17 Signaling in Macrophages

Coxiella burnetii is an obligate intracellular bacterium and the etiological agent of Q fever. Successful host cell infection requires the Coxiella type IVB secretion system (T4BSS), which translocates bacterial effector proteins across the vacuole membrane into the host cytoplasm, where they manipulate a variety of cell processes. To identify host cell targets of Coxiella T4BSS effector proteins, we determined the transcriptome of murine alveolar macrophages infected with a Coxiella T4BSS effector mutant. We identified a set of inflammatory genes that are significantly upregulated in T4BSS mutant-infected cells compared to mock-infected cells or cells infected with wild-type (WT) bacteria, suggesting that Coxiella T4BSS effector proteins downregulate the expression of these genes. In addition, the interleukin-17 (IL-17) signaling pathway was identified as one of the top pathways affected by the bacteria. While previous studies demonstrated that IL-17 plays a protective role against several pathogens, the role of IL-17 during Coxiella infection is unknown. We found that IL-17 kills intracellular Coxiella in a dose-dependent manner, with the T4BSS mutant exhibiting significantly more sensitivity to IL-17 than WT bacteria. In addition, quantitative PCR confirmed the increased expression of IL-17 downstream signaling genes in T4BSS mutant-infected cells compared to WT- or mock-infected cells, including the proinflammatory cytokine genes Il1a, Il1b, and Tnfa, the chemokine genes Cxcl2 and Ccl5, and the antimicrobial protein gene Lcn2 We further confirmed that the Coxiella T4BSS downregulates macrophage CXCL2/macrophage inflammatory protein 2 and CCL5/RANTES protein levels following IL-17 stimulation. Together, these data suggest that Coxiella downregulates IL-17 signaling in a T4BSS-dependent manner in order to escape the macrophage immune response

Decoding the complexities of human malaria through systems immunology

The complexity of the Plasmodium parasite and its life cycle poses a challenge to our understanding of the host immune response against malaria. Studying human immune responses during natural and experimental Plasmodium infections can enhance our understanding of malaria-protective immunity and inform the design of disease-modifying adjunctive therapies and next-generation malaria vaccines. Systems immunology can complement conventional approaches to facilitate our understanding of the complex immune response to the highly dynamic malaria parasite. In this review, recent studies that used systems-based approaches to evaluate human immune responses during natural and experimental Plasmodium falciparum and Plasmodium vivax infections as well as during immunization with candidate malaria vaccines are summarized and related to each other. The potential for next-generation technologies to address the current limitations of systems-based studies of human malaria are discussed

Addressing multiple modifiable risks through structured community-based Learning Clubs to improve maternal and infant health and infant development in rural Vietnam: protocol for a parallel group cluster randomised controlled trial

Introduction: Optimal early childhood development is an international priority. Risks during pregnancy and early childhood have lasting effects because growth is rapid. We will test whether a complex intervention addressing multiple modifiable risks: maternal nutrition, mental health, parenting capabilities, infant health and development and gender-based violence, is effective in reducing deficient cognitive development among children aged two in rural Vietnam. Methods and analysis: The Learning Clubs intervention is a structured programme combining perinatal stage-specific information, learning activities and social support. It comprises 20 modules, in 19 accessible, facilitated groups for women at a community centre and one home visit. Evidence-informed content is from interventions to address each risk tested in randomised controlled trials in other resource-constrained settings. Content has been translated and culturally adapted for Vietnam and acceptability and feasibility established in pilot testing. We will conduct a two-arm parallel-group cluster-randomised controlled trial, with the commune as clustering unit. An independent statistician will select 84/112 communes in Ha Nam Province and randomly assign 42 to the control arm providing usual care and 42 to the intervention arm. In total, 1008 pregnant women (12 per commune) from 84 clusters are needed to detect a difference in the primary outcome (Bayley Scales of Infant and Toddler Development Cognitive Score \u3c1 SD below standardised norm for 2 years of age) of 15% in the control and 8% in the intervention arms, with 80% power, significance 0.05 and intracluster correlation coefficient 0.03. Ethics and dissemination: Monash University Human Research Ethics Committee (Certificate Number 20160683), Melbourne, Victoria, Australia and the Institutional Review Board of the Hanoi School of Public Health (Certificate Number 017-377IDD- YTCC), Hanoi, Vietnam have approved the trial. Results will be disseminated through a comprehensive multistranded dissemination strategy including peer-reviewed publications, national and international conference presentations, seminars and technical and lay language reports

Whole-blood transcriptomic signatures induced during immunization by chloroquine prophylaxis and Plasmodium falciparum sporozoites

A highly effective vaccine that confers sterile protection to malaria is urgently needed. Immunization under chemoprophylaxis with sporozoites (CPS) consistently confers high levels of protection in the Controlled Human Malaria infection (CHMI) model. To provide a broad, unbiased assessment of the composition and kinetics of direct ex vivo human immune responses to CPS, we profiled whole-blood transcriptomes by RNA-seq before and during CPS immunization and following CHMI challenge. Differential expression of genes enriched in modules related to T cells, NK cells, protein synthesis, and mitochondrial processes were detected in fully protected individuals four weeks after the first immunization. Non-protected individuals demonstrated transcriptomic changes after the third immunization and the day of treatment, with upregulation of interferon and innate inflammatory genes and downregulation of B-cell signatures. Protected individuals demonstrated more significant interactions between blood transcription modules compared to non-protected individuals several weeks after the second and third immunizations. These data provide insight into the molecular and cellular basis of CPS-induced immune protection from P. falciparum infection

A Schrödinger Equation for Evolutionary Dynamics

We establish an analogy between the Fokker–Planck equation describing evolutionary landscape dynamics and the Schrödinger equation which characterizes quantum mechanical particles, showing that a population with multiple genetic traits evolves analogously to a wavefunction under a multi-dimensional energy potential in imaginary time. Furthermore, we discover within this analogy that the stationary population distribution on the landscape corresponds exactly to the ground-state wavefunction. This mathematical equivalence grants entry to a wide range of analytical tools developed by the quantum mechanics community, such as the Rayleigh–Ritz variational method and the Rayleigh–Schrödinger perturbation theory, allowing us not only the conduct of reasonable quantitative assessments but also exploration of fundamental biological inquiries. We demonstrate the effectiveness of these tools by estimating the population success on landscapes where precise answers are elusive, and unveiling the ecological consequences of stress-induced mutagenesis—a prevalent evolutionary mechanism in pathogenic and neoplastic systems. We show that, even in an unchanging environment, a sharp mutational burst resulting from stress can always be advantageous, while a gradual increase only enhances population size when the number of relevant evolving traits is limited. Our interdisciplinary approach offers novel insights, opening up new avenues for deeper understanding and predictive capability regarding the complex dynamics of evolving populations

A Schr\"odinger Equation for Evolutionary Dynamics

We establish an analogy between the Fokker-Planck equation describing evolutionary landscape dynamics and the Schr\"{o}dinger equation which characterizes quantum mechanical particles, showing how a population with multiple genetic traits evolves analogously to a wavefunction under a multi-dimensional energy potential in imaginary time. Furthermore, we discover within this analogy that the stationary population distribution on the landscape corresponds exactly to the ground-state wavefunction. This mathematical equivalence grants entry to a wide range of analytical tools developed by the quantum mechanics community, such as the Rayleigh-Ritz variational method and the Rayleigh-Schr\"{o}dinger perturbation theory, allowing us to not only make reasonable quantitative assessments but also explore fundamental biological inquiries. We demonstrate the effectiveness of these tools by estimating the population success on landscapes where precise answers are elusive, and unveiling the ecological consequences of stress-induced mutagenesis -- a prevalent evolutionary mechanism in pathogenic and neoplastic systems. We show that, even in a unchanging environment, a sharp mutational burst resulting from stress can always be advantageous, while a gradual increase only enhances population size when the number of relevant evolving traits is limited. Our interdisciplinary approach offers novel insights, opening up new avenues for deeper understanding and predictive capability regarding the complex dynamics of evolving populations

Twisted graphene in graphite: Impact on surface potential and chemical stability

Abstract Highly-oriented pyrolytic graphite (HOPG), i.e., the 3D stack of sp2-hybridized carbon sheets, is an attractive material thanks to its high electrical conductivity, chemical inertness, thermal stability, atomic-scale flatness, and ease of exfoliation. Despite an apparently ideal and uniform material, freshly cleaved HOPG shows domains in Kelvin probe force microscopy (KPFM) with surface potential contrast over 30 mV. We systematically investigated these domains using an integrated approach, including time-dependent KPFM and hyperspectral Raman imaging. The observed time-evolving domains are attributed to locally different hydrocarbon adsorption from the environment, driven by structural defects likely related to rotational mismatch, i.e., twisted layers. These defects affect the interlayer coupling between topmost graphene and the underlying layers. Our hypothesis was supported by Raman spectroscopy results, showing domains with G peak shifts and 2D line shape compatible with bilayer graphene. We attribute the selective sensitivity of our Raman spectroscopy results to the top graphene layers as resonances due to van Hove singularities. Our results show that the chemical and electrical properties of HOPG are far more complex than what is generally believed due to the broken symmetry at the top surface, giving rise to graphene bilayer-like behavior