Triple-Helix Structured Model Based on Problem-Knowledge-Solution Co-evolution for Innovative Product Design Process

A design problem with deficient information is generally described as wicked or ill-defined.The information insufficiency leaves designers with loose settings,free environments,and a lack of strict boundaries,which provides them with more opportunities to facilitate innovation.Therefore,to capture the opportunity behind the uncertainty of a design problem,this study models an innovative design as a composite solving process,where the problem is clarified and resolved from fuzziness to satisfying solutions by interplay among design problems,knowledge,and solutions.Additionally,a triple-helix structured model for the innovative product design process is proposed based on the co-evolution of the problem,solution,and knowledge spaces,to provide designers with a distinct design strategy and method for innovative design.The three spaces interact and co-evolve through iterative mappings,including problem structuring,knowledge expansion,and solution generation.The mappings carry the information processing and decision-making activities of the design,and create the path to satisfying solutions.Finally,a case study of a reactor coolant flow distribution device is presented to demonstrate the practicability of this model and the method for innovative product design.

Adaptive co-evolution of strategies and network leading to optimal cooperation level in spatial prisoner's dilemma game

We study evolutionary prisoner＇s dilemma game on adaptive networks where a population of players co-evolves with their interaction networks. During the co-evolution process, interacted players with opposite strategies either rewire the link between them with probability p or update their strategies with probability 1 - p depending on their payoffs. Numerical simulation shows that the final network is either split into some disconnected communities whose players share the same strategy within each community or forms a single connected network in which all nodes are in the same strategy. Interestingly, the density of cooperators in the final state can be maximised in an intermediate range of p via the competition between time scale of the network dynamics and that of the node dynamics. Finally, the mean-field analysis helps to understand the results of numerical simulation. Our results may provide some insight into understanding the emergence of cooperation in the real situation where the individuals＇ behaviour and their relationship adaptively co-evolve.

Adaptive Co-evolution Model for Multi-agent System

It is important to harmonize effectively the behaviors of the agents in the multi-agent system (MAS) to complete the solution process. The co-evolution computing techniques, inspired by natural selection and genetics, are usually used to solve these problems. Based on learning and evolution mechanisms of the biological systems, an adaptive co-evolution model was proposed in this paper. Inner-population, inter-population, and community learning operators were presented. The adaptive co-evolution algorithm (ACEA) was designed in detail. Some simulation experiments were done to evaluate the performance of the ACEA. The results show that the ACEA is more effective and feasible than the genetic algorithm to solve the optimization problems.

A Co-Evolution Model for Dynamic Social Network and Behavior

Individual behaviors, such as drinking, smoking, screen time, and physical activity, can be strongly influenced by the behavior of friends. At the same time, the choice of friends can be influenced by shared behavioral preferences. The actor-based stochastic models (ABSM) are developed to study the interdependence of social networks and behavior. These methods are efficient and useful for analysis of discrete behaviors, such as drinking and smoking;however, since the behavior evolution function is in an exponential format, the ABSM can generate inconsistent and unrealistic results when the behavior variable is continuous or has a large range, such as hours of television watched or body mass index. To more realistically model continuous behavior variables, we propose a co-evolution process based on a linear model which is consistent over time and has an intuitive interpretation. In the simulation study, we applied the expectation maximization (EM) and Markov chain Monte Carlo (MCMC) algorithms to find the maximum likelihood estimate (MLE) of parameter values. Additionally, we show that our assumptions are reasonable using data from the National Longitudinal Study of Adolescent Health (Add Health).

Hybrid Support Vector Regression with Parallel Co-Evolution Algorithm Based on GA and PSO for Forecasting Monthly Rainfall

Accurate and timely monthly rainfall forecasting is a major challenge for the scientific community in hydrological research such as river management project and design of flood warning systems. Support Vector Regression (SVR) is a very useful precipitation prediction model. In this paper, a novel parallel co-evolution algorithm is presented to determine the appropriate parameters of the SVR in rainfall prediction based on parallel co-evolution by hybrid Genetic Algorithm and Particle Swarm Optimization algorithm, namely SVRGAPSO, for monthly rainfall prediction. The framework of the parallel co-evolutionary algorithm is to iterate two GA and PSO populations simultaneously, which is a mechanism for information exchange between GA and PSO populations to overcome premature local optimum. Our methodology adopts a hybrid PSO and GA for the optimal parameters of SVR by parallel co-evolving. The proposed technique is applied over rainfall forecasting to test its generalization capability as well as to make comparative evaluations with the several competing techniques, such as the other alternative methods, namely SVRPSO (SVR with PSO), SVRGA (SVR with GA), and SVR model. The empirical results indicate that the SVRGAPSO results have a superior generalization capability with the lowest prediction error values in rainfall forecasting. The SVRGAPSO can significantly improve the rainfall forecasting accuracy. Therefore, the SVRGAPSO model is a promising alternative for rainfall forecasting.

Pocket Modification of x-Amine Transaminase AtATA for Overcoming the Trade-Off Between Activity and Stability Toward 1-Acetonaphthone

Amine transaminases(ATAs)catalyze the asymmetric amination of prochiral ketones or aldehydes to their corresponding chiral amines.However,the trade-off between activity and stability in enzyme engineering represents a major obstacle to the practical application of ATAs.Overcoming this trade-off is important for developing robustly engineered enzymes and a universal approach for ATAs.Herein,we modified the binding pocket of co-ATA from Aspergillus terreus(AtATA)to identify the key amino acid residues controlling the activity and stability of AtATA toward 1-acetonaphthone.We discovered a structural switch comprising four key amino acid sites(R128,V149,L182,and L187),as well as the"best"mutant(AtATAD224K/V149A/L182 F/L187F;termed M4).Compared to the parent enzyme AtATAD224K(AtATAPa),M4 increased the catalytic efficiency(k_(cat)/K_(m)^(1-acetonaphthone),where kcatis the constant of catalytic activities and is 10.1 min^(-1),K_(m)^(1-acetonaphthoneis) Michaelis-Menten constant and is 1.7 mmol·L^(-1))and half-life(t1/2)by 59-fold to 5.9 L·min^(-1)·mmol-1and by 1.6-fold to 46.9 min,respectively.Moreover,using M4 as the biocatalyst,we converted a 20 mmol·L^(-1)aliquot of 1-acetonaphthone in a 50 mL scaled-up system to the desired product,(R)-(+)-1(1-naphthyl)ethylamine((R)-NEA),with 78%yield and high enantiomeric purity(R>99.5%)within 10 h.M4 also displayed significantly enhanced activity toward various 1-acetonaphthone analogs.The related structural properties derived by analyzing structure and sequence information of robust ATAs illustrated their enhanced activity and thermostability.Strengthening of intramolecular interactions and expansion of the angle between the substratebinding pocket and the pyridoxal 5’-phosphate(PLP)-binding pocket contributed to synchronous enhancement of ATA thermostability and activity.Moreover,this pocket engineering strategy successfully transferred enhanced activity and thermostability to three other ATAs,which exhibited 8%-22%sequence similarity with AtATA.This research has important implications for overcoming the trade-off between ATA activity and thermostability.

Helicobacter pylori in human health and disease:Mechanisms for local gastric and systemic effects

Helicobacter pylori(H. pylori) is present in roughly 50% of the human population worldwide and infection levels reach over 70% in developing countries. The infection has classically been associated with different gastro-intestinal diseases, but also with extra gastric diseases. Despite such associations, the bacterium frequently persists in the human host without inducing disease, and it has been suggested that H. pylori may also play a beneficial role in health. To understand how H. pylori can produce such diverse effects in the human host, several studies have focused on understanding the local and systemic effects triggered by this bacterium. One of the main mechanisms by which H. pylori is thought to damage the host is by inducing local and systemic inflammation. However, more recently, studies are beginning to focus on the effects of H. pylori and its metabolism on the gastric and intestinal microbiome. The objective of this review is to discuss how H. pylori has co-evolved with humans, how H. pylori presence is associated with positive and negative effects in human health and how inflammation and/or changes in the microbiome are associated with the observed outcomes.

The arms race between Magnaporthe oryzae and rice: Diversity and interaction of Avr and R genes

Rice blast disease, caused by Magnaporthe oryzae, threatens global food security. The rice blast pathosystem is a longstanding model system for understanding plant-microbe interactions. In order to elucidate the coevolution of the host and pathogen, and provide the appropriate methods for preventing or controlling rice blast disease, researchers have focused on the evolution of virulence factors and resistance genes. Thus far, more than 30 rice blast resistance（R） genes and 12 avirulence（Avr） genes have been cloned. This review summarizes the cloned rice blast R genes, cloned Avr genes of M. oryzae and the interaction between them. This discussion also considers some of the major unanswered questions concerning this pathosystem and the opportunities for future investigations.

A Hybrid Differential Evolution Algorithm Integrated with Particle Swarm Optimization

To implement self-adaptive control parameters,a hybrid differential evolution algorithm integrated with particle swarm optimization( PSODE) is proposed. In the PSODE, control parameters are encoded to be a symbiotic individual of original individual,and each original individual has its own symbiotic individual. Differential evolution( DE) operators are used to evolve the original population. And,particle swarm optimization( PSO) is applied to co-evolving the symbiotic population. Thus,with the evolution of the original population in PSODE, the symbiotic population is dynamically and self-adaptively adjusted and the realtime optimum control parameters are obtained. The proposed algorithm is compared with some DE variants on nine functions. The results show that the average performance of PSODE is the best.

Predicting residue contacts for protein-protein interactions by integration of multiple information

Detailed knowledge of interfacial region between interacting proteins is not only helpful in annotating function for proteins, but also very important for structure-based drug design and disease treatment. However, this is one of the most difficult tasks and current methods are constrained by some factors. In this study, we developed a new method to predict residue-residue contacts of two interacting protein domains by integrating information about evolutionary couplings andamino acid pairwise contact potentials, as well as domain-domain interaction interfaces. The experimental results showed that our proposed method outperformed the previous method with the same datasets. Moreover, the method promises an improvement in the source of template-based protein docking.

Strategic Ecological Network Competition in Emerging Markets:Theory and Case Analysis of A GPS Vehicle Navigation Firm

Using the case study methodology, firm＇s competition behavior in strategic network and strategic ecosystems are analyzed. With the ecology view, there is consistency between strategic network and strategic ecosystem. Enterprise should pursue for suitable ecological niche to hold a strategic competitive power.

Demand-side Response Strategy of Multi-microgrids Based on an Improved Co-evolution Algorithm

An effective modeling and optimization method,which takes into account source-load-storage coordination,and full-time collaborative optimization within and outside micro-grids,is introduced.Considering the operational conditions of various resources and their interactions,an energy management model for microgrids is proposed aiming at maximization of renewable energy utilization and minimization of overall system costs.The model is suitable for both real-time pricing and time-of-use mechanisms.In microgrids,demand response and economic energy storage dispatch are introduced to enhance selfcoordination and self-balancing ability among different resources.Depending on whether there is still an imbalance between supply and demand after coordination within a niicrogrid,trade between it and external microgrids are optimized in a orderly manner by considering different transaction prices and usage rights.Finally,three different schemes are designed,where the Lagrangian multiplier method as well as a co-evolution algorithm are used to solve and analyze different examples,verifying the reliability and validity of the method proposed in this paper.

Co-evolution:A New Perspective for Business Model Innovation

This paper combines the perspective of co-evolution with studies in the area of business model, reveals the phenomenon of business model co-evolution and explores the business model coevolution mechanism between firms through a case study. Findings and what other companies can learn from this study are as follows. Firstly, companies, be it leaders or not, can act as enablers for other party’s business model innovation. Secondly, companies can enable each other’s business model innovation by taking the perspective of business model co-evolution; Thirdly, the interdependence of the business model co-evolution process can be explained by the four levers named novelty, lock-in,complementarity and efficiency. Companies can select novelty, lock-in, complementarity, efficiency or the combination of the four as mediators to achieve business model co-evolution.

The Piks allele of the NLR immune receptor Pik breaks the recognition of AvrPik effectors of rice blast fungus

Arms race co-evolution of plant–pathogen interactions evolved sophisticated recognition mechanisms between host immune receptors and pathogen effectors. Different allelic haplotypes of an immune receptor in the host mount distinct recognition against sequence or non-sequence related effectors in pathogens. We report the molecular characterization of the Piks allele of the rice immune receptor Pik against rice blast pathogen, which requires two head-to-head arrayed nucleotide-binding sites and leucine-rich repeat proteins. Like other Pik alleles, both Piks-1 and Piks-2 are necessary and sufficient for mediating resistance. However, unlike other Pik alleles, Piks does not recognize any known AvrPik variants of Magnaporthe oryzae. Sequence analysis of the genome of an avirulent isolate V86010 further revealed that its cognate avirulence(Avr) gene most likely has no significant sequence similarity to known AvrPik variants. Piks-1 and Pikm-1 have only two amino acid differences within the integrated heavy metal-associated(HMA) domain. Pikm-HMA interacts with AvrPik-A,-D, and-E in vitro and in vivo,whereas Piks-HMA does not bind any AvrPik variants. Characterization of two amino acid residues differing Piks-1 from Pikm-1 reveal that Piks-E229Q derived from the exchange of Glu229 to Gln229 in Piks-1 gains recognition specificity against AvrPik-D but not AvrPik-A or-E, indicating that Piks-E229Q partially restores the Pikm spectrum. By contrast,Piks-A261V derived from the exchange of Ala261 to Val261 in Piks-1 retains Piks recognition specificity.We conclude that Glu229 in Piks-1 is critical for Piks breaking the canonical Pik/AvrPik recognition pattern. Intriguingly, binding activity and ectopic cell death induction is maintained between Piks-A261V and AvrPik-D, implying that positive outcomes from ectopic assays might be insufficient to deduce its immune activity against the relevant effectors in rice and rice blast interaction.

Salinity variation and hydrographic dynamics in the early Cambrian Nanhua Basin(South China)

Despite intensive study of the early Cambrian Nanhua Basin(ECNB)in South China,its degree of connectedness to the open ocean remains uncertain,impeding analysis of contemporaneous oceanic redox evolution and its role in the Cambrian Explosion.We analyzed bulk-shale B/Ga,a newly proposed proxy for watermass salinity in ancient depositional systems,for three sections(Daotuo,Yuanjia,and Zhalagou)representing a range of water depths in the ECNB and spanning early Cambrian Stages 2 and 3.The B/Ga proxy records a salinity gradient in the basin,with increasing salinity from shallow-to deep-water areas,particularly during the deposition of black shales of the lower Jiumenchong/Niutitang/Zhalagou Formation.The gradient was probably due to the mixing of freshwater from adjacent landmasses with marine waters within a moderately restricted basin.All three study sections exhibit a monotonic rise in salinity over the~9-Myr study interval,reflecting increased watermass exchange with the open ocean due to regional tectonic and/or global sea-level changes.The improved watermass exchange may have weakened water-column stratification and reduced deep-water anoxia in the ECNB,contributing the enhanced oceanic oxygenation along with global environmental controls and further modulating the expression of the Cambrian Explosion recorded in Lower Cambrian sections of South China.Our study thus highlights the need for comprehensive analyses of hydrographic dynamics in marginal-marine settings that are used to explore co-evolutionary relationships between early animals and environmental oxygen levels.

Resilience in action: The bottom up! architecture festival in Turin (Italy)

This article describes the practice of co-evolutionary and transformative resilience through a case study con-ducted in Turin(Italy).According to a broad definition,resilience includes performing actions of urban design and planning,innovating community-based project procedures,and creating positive financial outcomes that are assessable because of the monitoring process of short-and long-term outcomes and impacts.Through the Turin-based case of the Bottom Up!Architecture Festival,this article observes processes in which resilience is in action in metropolitan areas,feeding urban projects and practices of self-organization of the social and financial actors involved.By applying the definition of community projects,the festival manages to take territorial problems and crises(the pandemic,inequality,etc.)and view them as an opportunity to change the system,recommending in-tegrated action on the natural,cultural,financial,and social capital,innovating practices and holding society and institutions more accountable.The transformation of spaces relies on collaborations between social and institu-tional actors,operating spatially concentrated transformations in the city of Turin,and using flexible governance tools based on co-planning and crowdfunding for project design and financing.

Mycobacteriaceae Phenome Atlas(MPA):A Standardized Atlas for the Mycobacteriaceae Phenome Based on Heterogeneous Sources

The bacterial family Mycobacteriaceae includes pathogenic and nonpathogenic bacteria,and systematic research on their genome and phenome can give comprehensive perspectives for exploring their disease mechanism.In this study,the pheno-types of Mycobacteriaceae were inferred from available phenomic data,and 82 microbial phenotypic traits were recruited as data elements of the microbial phenome.This Mycobacteriaceae phenome contains five categories and 20 subcategories of polyphasic phenotypes,and three categories and eight subcategories of functional phenotypes,all of which are complemen-tary to the existing data standards of microbial phenotypes.The phenomic data of Mycobacteriaceae strains were compiled by literature mining,third-party database integration,and bioinformatics annotation.The phenotypes were searchable and comparable from the website of the Mycobacteriaceae Phenome Atlas(MPA,https://www.biosi no.org/mpa/).A topological data analysis of MPA revealed the co-evolution between Mycobacterium tuberculosis and virulence factors,and uncovered potential pathogenicity-associated phenotypes.Two hundred and sixty potential pathogen-enriched pathways were found by Fisher's exact test.The application of MPA may provide novel insights into the pathogenicity mechanism and antimicrobial targets of Mycobacteriaceae.

Italian perspective on the planned preventive conservation of architectural heritage

This paper tells us a complex story on the historic evolution of preventive conser vation of architectural heritage in Italy.Firstly,it introduces Cesare Brandi's Theory of Resto ration,pointing out the peculiar sense of the word Restoration in Brandi's system other than the common sense in the international discourse,the limits of Brandi's theory to architectural conservation and his prophecy on preventive restoration.Then it talks about the differentframework and practices of preventive conservation in the field of built heritage compared to the museum sector,the milestone of Giovanni Urbani's pilot project on programmed conser.vation and the leading role of the Risk Map of Cultural Heritage.Finally,based on the discus-sions of the durable change in the architectural conservation field after the Venice Charter,including the teaching in Milan School,the debate and re-definition of architectural conserva-tion and the advance definitions of conservation,prevention,maintenance and restoration in the 2004 National Code of Cultural Heritage and Landscape,it gives us an agenda for futuretrends of planned conservation with aims to conserve the material authenticity and promote.the co-evolutional strategy.

A structural and data-driven approach to engineering a plant cytochrome P450 enzyme

Functional manipulation of biosynthetic enzymes such as cytochrome P450 s(or P450 s) has attracted great interest in metabolic engineering of plant natural products.Cucurbitacins and mogrosides are plant triterpenoids that share the same backbone but display contrasting bioactivities.This structural and functional diversity of the two metabolites can be manipulated by engineering P450 s.However,the functional redesign of P450 s through directed evolution(DE) or structure-guided protein engineering is time consuming and challenging,often because of a lack of high-throughput screening methods and crystal structures of P450 s.In this study,we used an integrated approach combining computational protein design,evolutionary information,and experimental data-driven optimization to alter the substrate specificity of a multifunctional P450(CYP87 D20)from cucumber.After three rounds of iterative design and evaluation of 96 protein variants,CYP87 D20,which is involved in the cucurbitacin C biosynthetic pathway,was successfully transformed into a P450 mono-oxygenase that performs a single specific hydroxylation at C11 of cucurbitadienol.This integrated P450-engineering approach can be further applied to create a de novo pathway to produce mogrol,the precursor of the natural sweetener mogroside,or to alter the structural diversity of plant triterpenoids by functionally manipulating other P450 s.

Strategic flight assignment approach based on multi-objective parallel evolution algorithm with dynamic migration interval

The continuous growth of air traffic has led to acute airspace congestion and severe delays, which threatens operation safety and cause enormous economic loss. Flight assignment is an economical and effective strategic plan to reduce the flight delay and airspace congestion by rea- sonably regulating the air traffic flow of China. However, it is a large-scale combinatorial optimiza- tion problem which is difficult to solve. In order to improve the quality of solutions, an effective multi-objective parallel evolution algorithm （MPEA） framework with dynamic migration interval strategy is presented in this work. Firstly, multiple evolution populations are constructed to solve the problem simultaneously to enhance the optimization capability. Then a new strategy is pro- posed to dynamically change the migration interval among different evolution populations to improve the efficiency of the cooperation of populations. Finally, the cooperative co-evolution （CC） algorithm combined with non-dominated sorting genetic algorithm II （NSGA-II） is intro- duced for each population. Empirical studies using the real air traffic data of the Chinese air route network and daily flight plans show that our method outperforms the existing approaches, multi- objective genetic algorithm （MOGA）, multi-objective evolutionary algorithm based on decom- position （MOEA/D）, CC-based multi-objective algorithm （CCMA） as well as other two MPEAs with different migration interval strategies.