Knowledge discovery for friction stir welding via data driven approaches: Part 2 – multiobjective modelling using fuzzy rule based systems

In this final part of this extensive study, a new systematic data-driven fuzzy modelling approach has been developed, taking into account both the modelling accuracy and its interpretability (transparency) as attributes. For the first time, a data-driven modelling framework has been proposed designed and implemented in order to model the intricate FSW behaviours relating to AA5083 aluminium alloy, consisting of the grain size, mechanical properties, as well as internal process properties. As a result, ‘Pareto-optimal’ predictive models have been successfully elicited which, through validations on real data for the aluminium alloy AA5083, have been shown to be accurate, transparent and generic despite the conservative number of data points used for model training and testing. Compared with analytically based methods, the proposed data-driven modelling approach provides a more effective way to construct prediction models for FSW when there is an apparent lack of fundamental process knowledge

ON THE EXPONENTIAL CHEBYSHEV APPROXIMATION IN UNBOUNDED DOMAINS: A COMPARISON STUDY FOR SOLVING HIGH-ORDER ORDINARY DIFFERENTIAL EQUATIONS

In this paper we investigate an improved scheme for exponential Chebyshev (EC) collocation method. The improved scheme of the EC functions is derived and introduced for solving high-order linear ordinary differential equations with variable coefficients in unbounded domain. This technique transforms the given differential equation and mixed conditions to matrix equation with unknown EC coefficients. These matrices together with the collocation method are utilized to reduce the solution of higher-order ordinary differential equations to the solution of a system of algebraic equations. The solution is obtained in terms of EC functions. Numerical examples are given to demonstrate the validity and applicability of the method. The obtained numerical results are compared with others existing methods and the exact solution where it shown to be very attractive with good accuracy

Supramolecular Assembly of Aminoethylene‐Lipopeptide PMO Conjugates into RNA Splice‐Switching Nanomicelles

Phosphorodiamidate morpholino oligomers (PMOs) are oligonucleotide analogs that can be used for therapeutic modulation of pre‐mRNA splicing. Similar to other classes of nucleic acid‐based therapeutics, PMOs require delivery systems for efficient transport to the intracellular target sites. Here, artificial peptides based on the oligo(ethylenamino) acid succinyl‐tetraethylenpentamine (Stp), hydrophobic modifications, and an azide group are presented, which are used for strain‐promoted azide‐alkyne cycloaddition conjugation with splice‐switching PMOs. By systematically varying the lead structure and formulation, it is determined that the type of contained fatty acid and supramolecular assembly have a critical impact on the delivery efficacy. A compound containing linolenic acid with three cis double bonds exhibits the highest splice‐switching activity and significantly increases functional protein expression in pLuc/705 reporter cells in vitro and after local administration in vivo. Structural and mechanistic studies reveal that the lipopeptide PMO conjugates form nanoparticles, which accelerate cellular uptake and that the content of unsaturated fatty acids enhances endosomal escape. In an in vitro Duchenne muscular dystrophy exon skipping model using H2K‐mdx52 dystrophic skeletal myotubes, the highly potent PMO conjugates mediate significant splice‐switching at very low nanomolar concentrations. The presented aminoethylene‐lipopeptides are thus a promising platform for the generation of PMO‐therapeutics with a favorable activity/toxicity profile

Synaptic convergence patterns onto retinal ganglion cells are preserved despite topographic variation in pre- and postsynaptic territories

Sensory processing can be tuned by a neuron’s integration area, the types of inputs, and the proportion and number of connections with those inputs. Integration areas often vary topographically to sample space differentially across regions. Here, we highlight two visual circuits in which topographic changes in the postsynaptic retinal ganglion cell (RGC) dendritic territories and their presynaptic bipolar cell (BC) axonal territories are either matched or unmatched. Despite this difference, in both circuits, the proportion of inputs from each BC type, i.e., synaptic convergence between specific BCs and RGCs, remained constant across varying dendritic territory sizes. Furthermore, synapse density between BCs and RGCs was invariant across topography. Our results demonstrate a wiring design, likely engaging homotypic axonal tiling of BCs, that ensures consistency in synaptic convergence between specific BC types onto their target RGCs while enabling independent regulation of pre- and postsynaptic territory sizes and synapse number between cell pairs

Tuning porosity in macroscopic monolithic metal-organic frameworks for exceptional natural gas storage.

Widespread access to greener energy is required in order to mitigate the effects of climate change. A significant barrier to cleaner natural gas usage lies in the safety/efficiency limitations of storage technology. Despite highly porous metal-organic frameworks (MOFs) demonstrating record-breaking gas-storage capacities, their conventionally powdered morphology renders them non-viable. Traditional powder shaping utilising high pressure or chemical binders collapses porosity or creates low-density structures with reduced volumetric adsorption capacity. Here, we report the engineering of one of the most stable MOFs, Zr-UiO-66, without applying pressure or binders. The process yields centimetre-sized monoliths, displaying high microporosity and bulk density. We report the inclusion of variable, narrow mesopore volumes to the monoliths' macrostructure and use this to optimise the pore-size distribution for gas uptake. The optimised mixed meso/microporous monoliths demonstrate Type II adsorption isotherms to achieve benchmark volumetric working capacities for methane and carbon dioxide. This represents a critical advance in the design of air-stable, conformed MOFs for commercial gas storage