Energy-efficient scheduling of flexible flow shop of composite recycling

Composite recycling technologies have been developed to tackle the increasing use of composites in industry and as a result of restrictions placed on landfill disposal. Mechanical, thermal and chemical approaches are the existing main recycling techniques to recover the fibres. Some optimisation work for reducing energy consumed by above processes has also been developed. However, the resource efficiency of recycling composites at the workshop level has never been considered before. Considering the current trend of designing and optimising a system in parallel and the future needs of the composite recycling business, a flexible flow shop for carbon fibre reinforced composite recycling is modelled. Optimisation approaches based on non-dominated sorting genetic algorithm II (NSGA-II) have been developed to reduce the time and energy consumed for processing composite wastes by searching for the optimal sub-lot splitting and resource scheduling plans. Case studies on different composite recycling scenarios have been conducted to prove the feasibility of the model and the developed algorithm

Convergence acceleration for multiobjective sparse reconstruction via knowledge transfer

© Springer Nature Switzerland AG 2019. Multiobjective sparse reconstruction (MOSR) methods can potentially obtain superior reconstruction performance. However, they suffer from high computational cost, especially in high-dimensional reconstruction. Furthermore, they are generally implemented independently without reusing prior knowledge from past experiences, leading to unnecessary computational consumption due to the re-exploration of similar search spaces. To address these problems, we propose a sparse-constraint knowledge transfer operator to accelerate the convergence of MOSR solvers by reusing the knowledge from past problem-solving experiences. Firstly, we introduce the deep nonlinear feature coding method to extract the feature mapping between the search of the current problem and a previously solved MOSR problem. Through this mapping, we learn a set of knowledge-induced solutions which contain the search experience of the past problem. Thereafter, we develop and apply a sparse-constraint strategy to refine these learned solutions to guarantee their sparse characteristics. Finally, we inject the refined solutions into the iteration of the current problem to facilitate the convergence. To validate the efficiency of the proposed operator, comprehensive studies on extensive simulated signal reconstruction are conducted

A Suite of Computationally Expensive Shape Optimisation Problems Using Computational Fluid Dynamics

This is the author accepted manuscript. The final version is available from Springer via the DOI in this record.PPSN2018: 15th International Conference on Parallel Problem Solving from Nature, 8-12 September 2018, Coimbra, PortugalIn many product design and development applications, Computational Fluid Dynamics (CFD) has become a useful tool for analysis. This is particularly because of the accuracy of CFD simulations in predicting the important flow attributes for a given design. On occasions when design optimisation is applied to real-world engineering problems using CFD, the implementation may not be available for examination. As such, in both the CFD and optimisation communities, there is a need for a set of computationally expensive benchmark test problems for design optimisation using CFD. In this paper, we present a suite of three computationally expensive real-world problems observed in different fields of engineering. We have developed Python software capable of automatically constructing geometries from a given decision vector, running appropriate simulations using the CFD code OpenFOAM, and returning the computed objective values. Thus, users may easily evaluate a decision vector and perform optimisation of these design problems using their optimisation methods without developing custom CFD code. For comparison, we provide the objective values for the base geometries and typical computation times for the test cases presented here.This work was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) grant (reference number: EP/M017915/1)

Surfactant protein D modulates HIV infection of both T-cells and dendritic cells

Surfactant Protein D (SP-D) is an oligomerized C-type lectin molecule with immunomodulatory properties and involvement in lung surfactant homeostasis in the respiratory tract. SP-D binds to the enveloped viruses, influenza A virus and respiratory syncytial virus and inhibits their replication in vitro and in vivo. SP-D has been shown to bind to HIV via the HIV envelope protein gp120 and inhibit infectivity in vitro. Here we show that SP-D binds to different strains of HIV (BaL and IIIB) and the binding occurs at both pH 7.4 and 5.0 resembling physiological relevant pH values found in the body and the female urogenital tract, respectively. The binding of SP-D to HIV particles and gp120 was inhibited by the presence of several hexoses with mannose found to be the strongest inhibitor. Competition studies showed that soluble CD4 and CVN did not interfere with the interaction between SP-D and gp120. However, soluble recombinant DC-SIGN was shown to inhibit the binding between SP-D and gp120. SP-D agglutinated HIV and gp120 in a calcium dependent manner. SP-D inhibited the infectivity of HIV strains at both pH values of 7.4 and 5.0 in a concentration dependent manner. The inhibition of the infectivity was abolished by the presence of mannose. SP-D enhanced the binding of HIV to immature monocyte derived dendritic cells (iMDDCs) and was also found to enhance HIV capture and transfer to the T-cell like line PM1. These results suggest that SP-D can bind to and inhibit direct infection of T-cells by HIV but also enhance the transfer of infectious HIV particles from DCs to T-cells in vivo

Development and validation of an improved algorithm for overlaying flexible molecules

A program for overlaying multiple flexible molecules has been developed. Candidate overlays are generated by a novel fingerprint algorithm, scored on three objective functions (union volume, hydrogen-bond match, and hydrophobic match), and ranked by constrained Pareto ranking. A diverse subset of the best ranked solutions is chosen using an overlay-dissimilarity metric. If necessary, the solutions can be optimised. A multi-objective genetic algorithm can be used to find additional overlays with a given mapping of chemical features but different ligand conformations. The fingerprint algorithm may also be used to produce constrained overlays, in which user-specified chemical groups are forced to be superimposed. The program has been tested on several sets of ligands, for each of which the true overlay is known from protein–ligand crystal structures. Both objective and subjective success criteria indicate that good results are obtained on the majority of these sets

The sudden change phenomenon of quantum discord

Even if the parameters determining a system's state are varied smoothly, the behavior of quantum correlations alike to quantum discord, and of its classical counterparts, can be very peculiar, with the appearance of non-analyticities in its rate of change. Here we review this sudden change phenomenon (SCP) discussing some important points related to it: Its uncovering, interpretations, and experimental verifications, its use in the context of the emergence of the pointer basis in a quantum measurement process, its appearance and universality under Markovian and non-Markovian dynamics, its theoretical and experimental investigation in some other physical scenarios, and the related phenomenon of double sudden change of trace distance discord. Several open questions are identified, and we envisage that in answering them we will gain significant further insight about the relation between the SCP and the symmetry-geometric aspects of the quantum state space.Comment: Lectures on General Quantum Correlations and their Applications, F. F. Fanchini, D. O. Soares Pinto, and G. Adesso (Eds.), Springer (2017), pp 309-33

Assessing Specific Cognitive Deficits Associated with Dementia in Older Adults with Down Syndrome: Use and Validity of the Arizona Cognitive Test Battery (ACTB)

BACKGROUND: Down syndrome is associated with specific cognitive deficits. Alongside this, older adults with Down syndrome are a high risk group for dementia. The Arizona Cognitive Test Battery (ACTB), a cognitive assessment battery specifically developed for use with individuals with Down syndrome, has been proposed for use as outcome measures for clinical trials in this population. It has not been validated in older adults with Down syndrome. This study aims to assess the use and validity of the ACTB in older adults with Down syndrome. METHODS: Participants with Down syndrome aged 45 and over were assessed using the ACTB, standard tabletop tests and informant ratings. RESULTS: Assessment outcomes of 49 participants were analysed. Of these, 19 (39%) had a diagnosis of dementia or possible dementia. Most participants were able to attempt most of the tasks, although some tasks had high floor effects (including CANTAB Intra-Extra Dimensional shift stages completed and Modified Dots Task). Of the ACTB tasks, statistically significant differences were observed between the dementia and no dementia groups on CANTAB Simple Reaction Time median latency, NEPSY Visuomotor Precision-Car and Motorbike and CANTAB Paired Associates Learning stages completed. No significant differences were observed for CANTAB Intra-Extra Dimensional Shift, Modified Dots Task, Finger Sequencing, NEPSY Visuomotor precision-Train and Car and CANTAB Paired Associates Learning first trial memory score. Several of the tasks in the ACTB can be used in older adults with Down syndrome and have mild to moderate concurrent validity when compared to tabletop tests and informant ratings, although this varies on a test by test basis. CONCLUSIONS: Overall, scores for a number of tests in the ACTB were similar when comparing dementia and no dementia groups of older adults with Down syndrome, suggesting that it would not be an appropriate outcome measure of cognitive function for clinical trials of dementia treatments without further modification and validation

Readthrough of Premature Termination Codons in the Adenomatous Polyposis Coli Gene Restores Its Biological Activity in Human Cancer Cells

The APC tumor suppressor gene is frequently mutated in human colorectal cancer, with nonsense mutations accounting for 30% of all mutations in this gene. Reintroduction of the WT APC gene into cancer cells generally reduces tumorigenicity or induces apoptosis. In this study, we explored the possibility of using drugs to induce premature termination codon (PTC) readthrough (aminoglycosides, negamycin), as a means of reactivating endogenous APC. By quantifying the readthrough of 11 nonsense mutations in APC, we were able to identify those giving the highest levels of readthrough after treatment. For these mutations, we demonstrated that aminoglycoside or negamycin treatment led to a recovery of the biological activity of APC in cancer cell lines, and showed that the level of APC activity was proportional to the level of induced readthrough. These findings show that treatment with readthrough inducers should be considered as a potential strategy for treating cancers caused by nonsense mutations APC gene. They also provide a rational basis for identifying mutations responsive to readthrough inducers