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Industries of low batches or one-off manufacturing aim for automation that is competitive enough to adapt to new or modified products daily through in-house knowledge. A knowledge that focuses on manufacturing processes, not on machine function programming. To solve this a complete set of actions that utilize seamless data transfer from product design to a Plug & Produce automation concept is proposed together with a generic structure for the integration of standard industrial robots into agents. This structure enables agents to handle their local reference coordinate systems and locations relative to a global perspective. Seamless utilization of data from product designs to Plug & Produce will simplify and shorten the time of digital development through concurrently usable text-based and graphical configuration tools of a configurable multi-agent system. Needed data extracts directly from the product design as requirements of operational goals. Extraction of data from the product design, sequence of goals, and process plans, which are recipes of how to solve goals, can by this concept be configured by in-house knowledge that has the process knowledge but not necessarily programming competence.

This article presents a framework for Plug & Produce that makes it possible to use configurations rather than programming to adapt a manufacturing system for new resources and parts. This is solved by defining skills on resources, and goals for parts. To reach these goals, process plans are defined with a sequence of skills to be utilized without specifying specific resources. This makes it possible to separate the physical world from the process plans. When a process plan requires a skill, e.g., grip with a gripper resource, then that skill may require further skills, e.g., move with a robot resource. This creates a tree of connected resources that are not defined in the process plan. Physical and logical compatibility between resources in this tree is checked by comparing several parameters defined on the resources and the part. This article presents an algorithm together with a multiagent system framework that handles the search and matching required for selecting the correct resources.

Serotonin, or 5-hydroxytryptamine (5-HT), is an important neurotransmitter1,2 that activates the largest subtype family of G-protein-coupled receptors3. Drugs that target 5-HT1A, 5-HT1D, 5-HT1E and other 5-HT receptors are used to treat numerous disorders4. 5-HT receptors have high levels of basal activity and are subject to regulation by lipids, but the structural basis for the lipid regulation and basal activation of these receptors and the pan-agonism of 5-HT remains unclear. Here we report five structures of 5-HT receptor–G-protein complexes: 5-HT1A in the apo state, bound to 5-HT or bound to the antipsychotic drug aripiprazole; 5-HT1D bound to 5-HT; and 5-HT1E in complex with a 5-HT1E- and 5-HT1F-selective agonist, BRL-54443. Notably, the phospholipid phosphatidylinositol 4-phosphate is present at the G-protein–5-HT1A interface, and is able to increase 5-HT1A-mediated G-protein activity. The receptor transmembrane domain is surrounded by cholesterol molecules—particularly in the case of 5-HT1A, in which cholesterol molecules are directly involved in shaping the ligand-binding pocket that determines the specificity for aripiprazol. Within the ligand-binding pocket of apo-5-HT1A are structured water molecules that mimic 5-HT to activate the receptor. Together, our results address a long-standing question of how lipids and water molecules regulate G-protein-coupled receptors, reveal how 5-HT acts as a pan-agonist, and identify the determinants of drug recognition in 5-HT receptors. Cryo-electron microscopy structures of three different serotonin receptors in complex with serotonin and other agonists provide insights into the role of lipids in regulating these receptors and the structural basis of ligand recognition.

Multi-agent technology, used for implementing Plug & Produce systems have many proposed benefits for fast adaption of manufacturing systems. However, still today multi-agent technology is not ready for the industry, due to the lack of mature supporting tools and guidelines. The result is that today, multi-agent systems are more complicated and time-consuming to use than traditional approaches. This hides their true benefits. In this paper, a new method for configuring agents is presented that includes automated deployment to manufacturing systems and by its flexible design opens the possibility to connect many other supporting tools when needed. A configuration tool is also designed that works with the proposed method by connecting to an agent configuration database. The overall aim of the method is to simplify the steps taken for adapting a manufacturing system for new parts and resources.

Mass customization has become more attractive but requires a transformation towards more flexible solutions in contrast to dedicated manufacturing systems. Flexibility includes complex tasks such as the introduction of new products or new manufacturing processes as well as to efficiently handle daily balancing. The main challenge when it comes to flexibility in manufacturing is to be able to handle the technical aspects and still be competitive. In this article we consider the cost for flexibility to include two main things; (1) setup time, e.g., time for planning, design, programming and configuration, installation, ramp-up, scrapping of old equipment, preparation of facility, hardware installation, and (2) need of competence, inhouse knowledge, external competence, or external expert competence.

Today, multi-agent systems are still uncommon in the industry because they require more time to be implemented than traditional manufacturing systems. In this paper, a conceptual model and guidelines are defined for communication and negotiation between agents for Plug & Produce systems. Standards for agent communication exists today, such as the FIPA collection of specifications. However, FIPA is a broad and general standard for any kind of system and leaves a lot of room for interpretation. This paper presents a new conceptual model and guidelines on how to simplify the implementation phase by limiting the choices an engineer must make when implementing a multi-agent system for a manufacturing system.

Ligand‐based virtual screening of large compound collections, combined with fast bioactivity determination, facilitate the discovery of bioactive molecules with desired properties. Here, chemical similarity based machine learning and label‐free differential scanning fluorimetry were used to rapidly identify new ligands of the anticancer target Pim‐1 kinase. The three‐dimensional crystal structure complex of human Pim‐1 with ligand bound revealed an ATP‐competitive binding mode. Generative de novo design with a recurrent neural network additionally suggested innovative molecular scaffolds. Results corroborate the validity of the chemical similarity principle for rapid ligand prototyping, suggesting the complementarity of similarity‐based and generative computational approaches., Fast computational compound screening led to the discovery of a novel inhibitor of human Pim‐1 kinase, an important anticancer drug target. Chemical ensemble‐based machine‐learning and de novo molecular design with artificial intelligence resulted in innovative chemical scaffolds. This approach might provide a universal template for efficient hit and lead discovery in medicinal and biological chemistry.

This paper describes a method together with an implementation for automating the detection, identification and configuration of newly added resources and parts in a Plug and Produce system using OP ...

This paper presents a method for automating the generation, verification and deployment of robot programs used in prefabrication of walls for family houses. The making of robot programs is today pe ...

This article investigates multi-objective optimization of the robot trajectories and position-based operation-coordination of complex multi-robot systems, such as press lines, to improve the production rate and obtaining smooth motions to avoid excessive wear of the robots' components. Different functions for handling the multiple objectives are evaluated on real-world press lines, including both scalarizing single-objective functions and Pareto-based multi-objective functions. Additionally, the Multi-Objective Constructive Cooperative Coevolutionary (moC(3)) algorithm is proposed, for Pareto-based optimization, which uses a novel constructive initialization of the subpopulations in a co-adaptive fashion. It was found that Pareto-based optimization performs better than the scalarizing single-objective functions. Furthermore, C-mo(3) gives substantially better results compared to manual online tuning, as currently used in the industry. Optimizing robot trajectories and operation-coordination of complex multi-robot systems using the proposed method with C-mo(3) significantly improves productivity and reduces maintenance. This article hereby addresses the lack of systematic methods for effectively improving the productivity of press lines.

Optimisation of the control function for multiple automated interacting production stations is a complex problem, even for skilled and experienced operators or process planners. When using mathematical optimisation techniques, it often becomes necessary to use simulation models to represent the problem because of the high complexity (i.e. simulation-based optimisation). Standard optimisation techniques are likely to either exceed the practical time frame or under-perform compared to the manual tuning by the operators or process planners. This paper presents the Constructive cooperative coevolutionary (C3) algorithm, which objective is to enable effective simulation-based optimisation for the control of automated interacting production stations within a practical time frame. C3 is inspired by an existing cooperative coevolutionary algorithm. Thereby, it embeds an algorithm that optimises subproblems separately. C3 also incorporates a novel constructive heuristic to find good initial solutions and thereby expedite the optimisation. In this work, two industrial optimisation problems, involving interaction production stations, with different sizes are used to evaluate C3. The results illustrate that with C3, it is possible to optimise these problems within a practical time frame and obtain a better solution compared to manual tuning.

A current trend in production is to reduce energy consumption where possible not only to lower the cost but also to be a more energy efficient entity. This paper presents an energy model to estimate the electrical energy consumption of 2D-belt robots used for material handling in multi-stage sheet metal press lines. An estimation of the energy consumption is computed by the proposed energy model based on the robot components' specifications, the robot path and trajectory. The proposed model can predict the energy consumption offline by simulation, and thus, before installation, avoiding the need for physical experiments. It is demonstrated that it can be used for predicting potential energy reductions achieved by optimising the motion planning. Additionally, it is also shown how to investigate the energy saving achieved by using mechanical brakes when the robot is idle. This effectively illustrates the usefulness of the proposed energy model. [Submitted 01 March 2018; Accepted 18 March 2019]

Automated manufacturing processes such as automotive tandem press lines include time dependent complex control functions. All motions and critical interactions between moving parts must be synchronised to avoid collisions and reach high production rate. It is even for a skilled operator hard to optimise these processes on-line. Therefore, a hardware-in-the-loop simulation including real industrial control systems and its control code establish an essential tool for optimisation. Additionally, an efficient optimisation algorithm is required to reach a useful simulation-based optimisation method. This paper proposes a new optimisation algorithm starting with the Lipschitzian algorithm DIRECT as global search and then switches over to the Nelder-Mead simplex algorithm for local convergence. During the switch over, the new algorithm determines all local candidates of the set of points evaluated by DIRECT and starts multiple Nelder-Mead local searches in each of these. An optimisation study for an automotive press line shows that the proposed algorithm combines the benefits of the Lipschitzian and the simplex algorithms in an efficient way. The importance of multiple local searches from all local candidates found is also shown in the study. Based on the same number of function evaluations, it is also shown that this algorithm reaches improved press line performances compared to the stochastic differential evolution algorithm.

This article describes and analyses the process in which the establishment of a Christmas market led to an attempt to establish a regional destination brand named "Delightful Christmas". Our focus ...

Environmental, social and economic sustainability is an important topic of today’s decision makers in tourism. This book, Harald Pechlaner, Peter Keller, Sabine Pichler and Klaus Weiermair, provides profound insights into current concepts and challenges of sustainable tourism development – with particular regard to mountain destinations worldwide.

This paper presents an off-line process parameter tuning method, focussing on complex control functions for automated manufacturing systems. The proposed method is based on a combination of simulation-based optimisation and time-synchronised hardware-in-the-loop simulation. Real industrial control systems, e.g., PLCs, are included in the simulation, executing the unchanged control code from the manufacturing plant. This approach allows all plant control functions to be included, even time-critical feedback loops and vendor secret blocks such as motion control. Consequently, the method suggested manages the problems identified in previously presented simulation-based approaches. Furthermore, a case study of an automotive sheet-metal press line has been performed to verify the proposed method, with successful results.

Simulation-based programmable logic controller (PLC) code verification is a part of virtual commissioning, where the control code is verified against a virtual prototype of an application. With today's general OPC interface, it is easy to connect a PLC to a simulation tool for, e.g., verification purposes. However, there are some problems with this approach that can lead to an unreliable verification result. In this paper, four major problems with the OPC interface are described, and two possible solutions to the problems are presented: a general IEC 61131-3-based software solution, and a new OPC standard solution.

Consolidated tourism destinations should expand their market share by focusing on tourism spending instead of number of travellers. This strategy emphasises satisfying the preferences and needs of tourists more dynamically in terms of their expenditure patterns. The purpose of this paper consists of evaluating the usefulness of an expenditure-based segmentation as a relevant instrument of tourism policy in order to increase the economic benefits from travellers to Andalusia. More specifically, by means of decision trees and linear regression statistical techniques, heavy spenders are identified as well as exploring which variables might be considered as the best predictors of travel expenditure. Finally, the implications of the results are discussed, as they may provide practical guidance for tourism practitioners at similar destinations.

Serine proteases of the S1 family have maintained a common structure over an evolutionary span of more than one billion years, and evolved a variety of substrate specificities and diverse biological roles, involving digestion and degradation, blood clotting, fibrinolysis and epithelial homeostasis. We here show that a wide range of C-terminal peptide sequences of serine proteases, particularly from the coagulation and kallikrein systems, share characteristics common with classical antimicrobial peptides of innate immunity. Under physiological conditions, these peptides exert antimicrobial effects as well as immunomodulatory functions by inhibiting macrophage responses to bacterial lipopolysaccharide. In mice, selected peptides are protective against lipopolysaccharide-induced shock. Moreover, these S1-derived host defense peptides exhibit helical structures upon binding to lipopolysaccharide and also permeabilize liposomes. The results uncover new and fundamental aspects on host defense functions of serine proteases present particularly in blood and epithelia, and provide tools for the identification of host defense molecules of therapeutic interest.

Obsidian is a domain specific language for data-parallel programming on graphics processors (GPUs). It is em- bedded in the functional programming language Haskell. The user writes code using constructs familiar from Haskell (like map and reduce), recursion and some specially designed combinators for combining GPU programs. NVIDIA CUDA code is generated from these high level descriptions, and passed to the nvcc compiler [1]. Currently, we consider only the generation of single kernels, and not their coordination. This paper is focussed on how the user should work with Obsidian, starting with an obviously correct (or well- tested) description of the required function, and refining it by the introduction of constructs to give finer control of the computation on the GPU. For some combinators, this approach results in CUDA code with satisfactory performance, promising increased productivity, as the high level descriptions are short and uncluttered. But for other combinators, the performance of generated code is not yet satisfactory. Ways to tackle this problem and plans to integrate Obsidian with another higher-level embedded language for GPU programming in Haskell are briefly discussed.

A strategy that combines virtual screening and structure-guided selection of fragments was used to identify three unexplored classes of human DHODH inhibitor compounds: 4-hydroxycoumarins, fenamic acids, and N-(alkylcarbonyl)anthranilic acids. Structure-guided selection of fragments targeting the inner subsite of the DHODH ubiquinone binding site made these findings possible with screening of fewer than 300 fragments in a DHODH assay. Fragments from the three inhibitor classes identified were subsequently chemically expanded to target an additional subsite of hydrophobic character. All three classes were found to exhibit distinct structure-activity relationships upon expansion. The novel N-(alkylcarbonyl)anthranilic acid class shows the most promising potency against human DHODH, with IC(50) values in the low nanomolar range. The structure of human DHODH in complex with an inhibitor of this class is presented.

The anaphylatoxin C3a and its inactivated derivative C3adesArg, generated during complement activation, exert direct antimicrobial effects, mediated via its C-terminal region [Nordahl et al. (2004) Proc. Natl. Acad. Sci. U.S.A. 101, 16879-16884]. During evolution, this region of C3a displays subtle changes in net charge, while preserving a moderate but variable amphipathicity [Pasupuleti et al. (2007) J. Biol. Chem. 282, 2520-2528]. In this study, we mimic these evolutionary changes, employing a design approach utilizing selected amino acid substitutions at strategic and structurally relevant positions in the original human C3a peptide CNYITELRRQHARASHLGLA, followed by structure-activity studies incorporating sequence-dependent QSAR models as tools for generation of C3a peptide variants with enhanced effects. While the native peptide and related amphipathic analogues of moderate positive net charge were active against the Gram-negative Escherichia coli, activity against the Gram-positive Staphylococcus aureus was primarily observed for peptides characterized by a combination of a relatively high net charge (+6-7) and a propensity to adopt an alpha-helical conformation with amphipathic character. Such increased helicity and charge also conferred activity against the fungus Candida albicans. A central histidine residue (H11), evolutionarily conserved among vertebrates, conferred high selectivity toward microbes, while substitutions with leucine rendered the peptides hemolytic. Selected C3a analogues retained their specificity against staphylococci in the presence of human plasma, while showing low cytotoxicity. The work illustrates structure-activity relationships underlying the function and specificity of antimicrobial C3a and related analogues and provides insights into the forces that drive evolution of antimicrobial peptides.

The aminopropyltransferase spermidine synthase (SpdS) is a promising drug target in cancer and in protozoan diseases including malaria. Plasmodium falciparum SpdS (PfSpdS) transfers the aminopropyl group of decarboxylated S-adenosylmethionine (dcAdoMet) to putrescine or to spermidine to form spermidine or spermine, respectively. In an effort to understand why efficient inhibitors of PfSpdS have been elusive, the present study uses enzyme activity assays and isothermal titration calorimetry with verified or predicted inhibitors of PfSpdS to analyze the relationship between binding affinity as assessed by KD and inhibitory activity as assessed by IC50. The results show that some predicted inhibitors bind to the enzyme with high affinity but are poor inhibitors. Binding studies with PfSpdS substrates and products strongly support an ordered sequential mechanism in which the aminopropyl donor (dcAdoMet) site must be occupied before the aminopropyl acceptor (putrescine) site can be occupied. Analysis of the results also shows that the ordered sequential mechanism adequately accounts for the complex relationship between IC50 and KD and may explain the limited success of previous efforts at structure-based inhibitor design for PfSpdS. Based on PfSpdS active-site occupancy, we suggest a classification of ligands that can help to predict the KD−IC50 relations in future design of new inhibitors. The present findings may be relevant for other drug targets that follow an ordered sequential mechanism.

This article explores the impact of governance on destination development, focusing on public–private relationships, plus formal and informal networks and resource dependencies. The empirical contribution is based on a single case study of the Swedish ski resort of Åre. In the concluding section, some of the results are developed into suggestions concerning if and how the governance structure matters in terms of performance. The results indicate that public–private relationships built on trust, joint risk taking, informal structures and strategic consensus do have a positive impact on the level of growth at a tourist destination.

The Differential Evolution (DE) algorithm is widely used for real-world global optimisation problems in many different domains. To improve DE's performance on large-scale optimisation problems, it has been combined with the Cooperative Coevolution (CCDE) algorithm. CCDE adopts a divide-and-conquer strategy to optimise smaller subcomponents separately instead of tackling the large-scale problem at once. DE then evolves a separate subpopulation for each subcomponent but there is cooperation between the subpopulations to co-adapt the individuals of the subpopulations with each other. The Constructive Cooperative Coevolution (C3DE) algorithm, previously proposed by the authors, is an extended version of CCDE that has a better performance on large-scale problems, interestingly also on non-separable problems. This paper proposes a new version, called the Improved Constructive Cooperative Coevolutionary Differential Evolution (C3iDE), which removes several limitations with the previous version. A novel element of C3iDE is the advanced initialisation of the subpopulations. C3iDE initially optimises the subpopulations in a partially co-adaptive fashion. During the initial optimisation of a subpopulation, only a subset of the other subcomponents is considered for the co-adaptation. This subset increases stepwise until all subcomponents are considered. The experimental evaluation of C3iDE on 36 high-dimensional benchmark functions (up to 1000 dimensions) shows an improved solution quality on large-scale global optimisation problems compared to CCDE and DE. The greediness of the co-adaptation with C3iDE is also investigated in this paper.

5-Chloro-N-ethyl-1,2-dihydro-4-hydroxy-1-methyl-2-oxo-N-phenyl-3-quinolinecarboxamide (laquinimod, 2) is an oral drug in clinical trials for the treatment of multiple sclerosis. The final step in the synthesis of 2 is a high-yielding aminolysis reaction of ester 1 with N-ethylaniline. An equilibrium exists between 1 and 2, and removal of formed methanol during the reaction is a prerequisite for obtaining high yields of 2 from 1. The reactivity of 1 and 2 is explained by a mechanistic model that involves a transfer of the enol proton to the exocyclic carbonyl substituent with concomitant formation of ketene 3. This proton transfer is especially facilitated for 2 because the intramolecular hydrogen bond to the carbonyl oxygen is weakened due to steric interactions. Both 1 and 2 undergo solvolosis reactions that obey first-order reaction kinetics, further supporting the theory that these two molecules are able to decompose unimolecularly into ketene 3. The solvent-dependent spectroscopic features of 2 indicate that the molecule mainly resides in two conformations. One conformation is favored in nonpolar solvents and is likely the result of intramolecular hydrogen bonding. The other conformation is favored in polar solvents and probably exhibits less intramolecular hydrogen bonding.

In this work, X-ray crystallography was used to examine ligand complexes of spermidine synthase from the malaria parasite Plasmodium falciparum (PfSpdS)., The enzymes of the polyamine-biosynthesis pathway have been proposed to be promising drug targets in the treatment of malaria. Spermidine synthase (SpdS; putrescine aminopropyltransferase) catalyzes the transfer of the aminopropyl moiety from decarboxylated S-adenosylmethionine to putrescine, leading to the formation of spermidine and 5′-methylthio­adenosine (MTA). In this work, X-ray crystallography was used to examine ligand complexes of SpdS from the malaria parasite Plasmodium falciparum (PfSpdS). Five crystal structures were determined of PfSpdS in complex with MTA and the substrate putrescine, with MTA and spermidine, which was obtained as a result of the enzymatic reaction taking place within the crystals, with dcAdoMet and the inhibitor 4-methylaniline, with MTA and 4-aminomethyl­aniline, and with a compound predicted in earlier in silico screening to bind to the active site of the enzyme, benzimidazol-(2-yl)pentan-1-amine (BIPA). In contrast to the other inhibitors tested, the complex with BIPA was obtained without any ligand bound to the dcAdoMet-binding site of the enzyme. The complexes with the aniline compounds and BIPA revealed a new mode of ligand binding to PfSpdS. The observed binding mode of the ligands, and the interplay between the two substrate-binding sites and the flexible gatekeeper loop, can be used in the design of new approaches in the search for new inhibitors of SpdS.

Simulation-based optimisation carries the burden of computationally expensive fitness calculations. It is very often used to tackle large-scale optimisation problems with a relatively high level of complexity. Therefore, it is of interest to have optimisation techniques dedicated to simulation-based optimisation. This paper proposes a simulation-based optimisation approach, called Constructive Cooperative Coevolutionary (C3) search procedure, to optimise the control of interacting production stations. An optimisation algorithm is embedded in the C3 search procedure to optimise subproblems separately. It includes a novel constructive heuristic that creates a feasible solution for the considered problem efficiently. It also incorporates an extended version of the existing cooperative coevolutionary method that can handle large-scale optimisation problems. Furthermore, this paper presents a case study considering a sheet metal press line as an example of interacting production stations. In this case study, the performance of the proposed C3 search procedure is evaluated and compared with other optimisation algorithms. This shows that the C3 search procedure is able to successfully optimise the press line within a given number of fitness calculations, outperforming existing algorithms. Also, it is shown that C3 can be embedded with either stochastic or deterministic optimisation algorithms, without sacrificing performance.

We present a new algorithm for Reverse Monte Carlo (RMC) simulations of liquids. During the simulations, we calculate energy, excess chemical potentials, bond-angle distributions and three-body correlations. This allows us to test the quality and physical meaning of RMC-generated results and its limitations. It also indicates the possibility to explore orientational correlations from simple scattering experiments. The new technique has been applied to bulk hard-sphere and Lennard-Jones systems and compared to standard Metropolis Monte Carlo results.