Search

Individual-based networks provide the building blocks for community-level networks. However, network studies of bats and their parasites have focused only on the species level. Intrapopulation variation may allow certain host individuals to play important roles in the dynamics of the parasites. Therefore, we evaluated how the variation in host sex, body size, ectoparasite abundance and co-occurrence configure individual-based networks of the lesser bulldog bat Noctilio albiventris and bat flies. We expected bat individuals with greater body mass and forearms acting as the core in the network. We also expected males to play a more important role in the network. We sampled a network of N. albiventris bat individuals and their bat flies to describe the structure of an antagonistic individual-based network. We aimed to identify the most relevant bat individuals in the network, focusing on the implications inherent to each of the following approaches: (i) core-periphery organization; (ii) modularity; (iii) species level metrics; and (iv) the main ecological driver of bat individual roles in the network, using niche-based predictors (body mass, forearm and sex). We showed that a network of N. albiventris individuals and their bat flies had low modularity containing a persistent nucleus of individuals and bat flies with well-established interactions. Male individuals with greater body mass played an important role in the network, while for females neither mass nor forearm length were important predictors of their role in the network. Finally, individuals with a high abundance of Paradyschiria parvula played a core role. These results provide an alternative perspective to understand the patterns and mechanisms of interspecific interactions between parasites on the host, as well as sex-biased parasitism.

The current travel demand in railways requires the adoption of novel approaches and technologies in order to increase network capacity. Virtual Coupling is considered one of the most innovative solutions to increase railway capacity by drastically reducing train headway. The aim of this paper is to provide an approach to investigate the potential of Virtual Coupling in railways by composing stochastic activity networks model templates. The paper starts describing the Virtual Coupling paradigm with a focus on standard European railway traffic controllers. Based on stochastic activity network model templates, we provide an approach to perform quantitative evaluation of capacity increase in reference Virtual Coupling scenarios. The approach can be used to estimate system capacity over a modelled track portion, accounting for the scheduled service as well as possible failures. Due to its modularity, the approach can be extended towards the inclusion of safety model components. The contribution of this paper is a preliminary result of the PERFORMINGRAIL (PERformance-based Formal modelling and Optimal tRaffic Management for movING-block RAILway signalling) project funded by the European Shift2Rail Joint Undertaking.

Individual behaviour and local context can influence the evolution of ecological interactions and how they structure into networks. In trophic interactions, consumers can increase their fitness by actively choosing resources that they are more likely to explore successfully. Mathematical modelling is often employed in theoretical studies to understand the coevolutionary dynamics between consumers and resources. However, they often disregard the individual consumer behaviour since the complexity of these systems usually requires simplifying assumptions about interaction details. Using an individual-based model, we model a community of several species that interact antagonistically. Each individual has a trait (attack or defence) that is explicitly modelled and the probability of the interaction to occur successfully increases with increased trait-matching. In addition, consumers can actively choose resources that guarantee greater fitness. We show that active consumer choice can generate coevolutionary units over time. It means that the traits of both consumers and resources converge into multiple groups with similar traits and the species interactions stay restricted to these groups over time. We also observed that network structure is more dependent on the parameter that delimits active consumer choice than on the intensity of selective pressure. Thus, our results support the idea that consumer active choice behaviour plays an important role in the ecological and evolutionary processes that structure interacting communities.

The “puzzle” of emotional plasticity concerns making sense of two conflicting bodies of evidence: evidence that emotions often appear modular in key respects, and evidence that our emotions also of...

Difunctionalization of strained cyclic alkynes presents a powerful strategy to build richly functionalized cyclic alkenes in an expedient fashion. Herein we disclose an efficient and flexible approach to achieve carbohalogenation, dicarbofunctionalization, aminohalogenation and aminocarbonation of readily available cyclohexenyl triflates. We have demonstrated the novel use of zincate base/nucleophile system for effective formation of key cyclohexyne intermediates and selective addition of various carbon and nitrogen nucleophiles. Importantly, leveraging the resulting organozincates enables the incorporation of a broad range of electrophilic partners to deliver structurally diverse cyclohexene motifs. The importance and utility of this method is also exemplified by the modularity of this approach and the ease in which even highly complex polycyclic scaffolds can be accessed in one step.

In this article, we develop a modular design method of decentralized controllers for linear dynamical network systems, where multiple subcontroller designers aim at individually regulating their local control performance with accessibility only to their respective subsystem models. First, we derive a constrained version of the Youla parameterization that characterizes all retrofit controllers for a single subcontroller, defined as an add-on-type subcontroller that manages a subsystem. The resultant feedback system is kept robustly stable for any variation in the neighboring subsystems, other than the subsystem of interest, provided that the original system is stable prior to implementing the retrofit control. Subsequently, we find out a unique internal structure of the retrofit controllers, assuming that the interaction input signal from the neighboring subsystems is measurable. Furthermore, we show that the simultaneous implementation of multiple retrofit controllers, designed by individual subcontroller designers, can improve the upper bound of the overall control performance. Finally, the practical significance of the method is demonstrated via an illustrative example of frequency regulation using the IEEE 68-bus power system model.

To what degree are individual structural elements within proteins modular such that similar structures from unrelated proteins can be interchanged? We study subdomain modularity by creating 20 chimeras of an enzyme, Escherichia coli dihydrofolate reductase (DHFR), in which a catalytically important, 10-residue α-helical sequence is replaced by α-helical sequences from a diverse set of proteins. The chimeras stably fold but have a range of diminished thermal stabilities and catalytic activities. Evolutionary coupling analysis indicates that the residues of this α-helix are under selection pressure to maintain catalytic activity in DHFR. Reversion to phenylalanine at key position 31 was found to partially restore catalytic activity, which could be explained by evolutionary coupling values. We performed molecular dynamics simulations using replica exchange with solute tempering. Chimeras with low catalytic activity exhibit nonhelical conformations that block the binding site and disrupt the positioning of the catalytically essential residue D27. Simulation observables and in vitro measurements of thermal stability and substrate-binding affinity are strongly correlated. Several E. coli strains with chromosomally integrated chimeric DHFRs can grow, with growth rates that follow predictions from a kinetic flux model that depends on the intracellular abundance and catalytic activity of DHFR. Our findings show that although α-helices are not universally substitutable, the molecular and fitness effects of modular segments can be predicted by the biophysical compatibility of the replacement segment.

Bistability is intrinsically connected to various decision making processes in living systems. The operating principles of a bistable switch, generated from a positive feedback loop, are well understood both in natural and synthetic settings. However, the fate of dynamic modularity of a positive feedback loop is unknown when it is connected to another dynamically modular signaling motif. In order to address this, here we investigate feed-forward signaling of a positive feedback loop to determine the fate of a bistable switch under such signaling. Using the potential energy based high-throughput bifurcation analysis method, we uncover that in addition to the conventional bistability the hybrid motifs generate various emergent bistable switches, namely mushroom and isola switches, which are not produced by the individual motifs. Using random parameter sampling, network perturbation, and phase plane analysis, we establish the design principles of such emergent behaviors. Incoherent feed-forward signaling of a positive feedback loop with distinct regulatory thresholds of the two arms of the feed-forward loop are the key requirements for such emergent behaviors. Our calculations show that the specific types of atypical bistable responses depend on the logic gate configuration of the signals. However, the emergent bistable behaviors of the hybrid networks do not depend on the nature of the positive feedback loop.

Maasai and other Maa-speaking pastoralists in Kenya and Tanzania have a risk-pooling system that they refer to by their word for the umbilical cord (osotua). Gifts from one osotua partner to another are contingent on the recipient’s need and do not create any debt. We refer to such gifts as need-based transfers. Maa-speakers also have a system of debt-based transfers (esile) in which gifts must be repaid. We designed an agent-based model to compare the impacts on herd survival of need-based and debt-based transfers on networks of varying topologies and sizes and with different degrees of temporal correlation of shocks felt by the agents. We found that the use of need-based rather than debt-based transfers, greater network modularity, greater network size, and decreased correlation among shocks were associated with increased rates of survival.

Although the individual cortical areas in the brain support very diverse functions, their anatomical organizations are very similar, given by collections of cortical blocks with nearly the same structure. This character suggests that statistical dynamics in the brain may be modeled much efficiently if interactions between the cortical blocks and learning in them are described through effective reduction. This paper introduces a neural network model based on the cortical modularity. Specifically, in building the model, we postulate on how cortical blocks function and interact with each other and adopt the formalism of path-integral-based interactions and free-energy-based learning. We apply the model to explain the characteristics observed in early visual systems.

The potential of artificial selection to dramatically impact phenotypic diversity is well known. Large-scale morphological changes in domestic species, emerging over short timescales, offer an accelerated perspective on evolutionary processes. The domestic horse (Equus caballus) provides a striking example of rapid evolution, with major changes in morphology and size likely stemming from artificial selection. However, the microevolutionary mechanisms allowing to generate this variation in a short time interval remain little known. Here, we use 3D geometric morphometrics to quantify skull morphological diversity in the horse, and investigate modularity and integration patterns to understand how morphological associations contribute to cranial evolvability in this taxon. We find that changes in the magnitude of cranial integration contribute to the diversification of the skull morphology in horse breeds. Our results demonstrate that a conserved pattern of modularity does not constrain large-scale morphological variations in horses and that artificial selection has impacted mechanisms underlying phenotypic diversity to facilitate rapid shape changes. More broadly, this study demonstrates that studying microevolutionary processes in domestic species produces important insights into extant phenotypic diversity. Introduction Material and methods - Material - Acquisition of data - Shape analyses - Integration and modularity -- Modular patterning -- Covariation patterns -- Magnitude of morphological integration Results - Size and shape variation - Allometry‑free shape variation - Allometry‑free shape variation of the modules - Modularity and integration Discussion - Cranial shape variation in the horse: the role of allometry and artificial selection in the morphological diversification - Cranial modularity and shape diversification -- Stasis in patterns, changes in magnitude -- Influence of morphological integration on shape variance - The role of function and development in integration patterns -- Anterior region -- Posterior region Conclusion

Demonstrations, strikes, direct actions, and acts of civil disobedience are just a few examples of the broad set of protest tactics potentially available to citizens in order to raise their demands and call the public’s attention to unjust situations. Each of these forms of claim-making can be more or less modular. Modularity, a concept originally introduced by Sidney Tarrow (1993) and popularized by Charles Tilly (1993, 1995), refers to the adaptability or degree of transferability of protest forms to different circumstances of contention. A protest form is strongly modular when it belongs to the regular repertoire of diverse actors and is employed for the defense of varied issues, against distinct targets, and in different places. Nonetheless, despite the considerable popularity of the concept for theoretical elaboration, its empirical operationalization has so far remained underdeveloped. In this article, building upon the conceptual bases set up by Wada (2012), we lay out a new perspective for the evaluation of the modularity of protest forms. Drawing upon social network analysis, we propose to analyze contingency tables generated from protest event catalogs as two-mode networks, measuring tactical transferability as weighted degree centrality (Opsahl et al. 2010). To demonstrate the usefulness of our proposed operationalization, we examine a large original dataset of protest events, applying our measure in order to evaluate repertoire change in the Basque Country over the last four decades, tracing the evolution of ten different protest forms in terms of actor transferability. Results show a relatively rigid repertoire in which demonstrations appear as dominant, at the same time that symbolic protests have gradually increased its modularity in recent years, at the expense of civil disobedience and violent direct action, which used to be significantly more relevant during the 80s and 90s. In comparison with Wada’s original proposal, the new measure of modularity proposed in this article derives from a more intuitive operationalization and offers an easily interpretable visual representation of the data. These advantages could eventually encourage more empirical research comparing the varying modularity of forms of contention across diverse contexts and periods. Manifestaciones, huelgas, acciones directas, o actos de desobediencia civil forman parte de un amplio abanico de tácticas de protesta mediante las cuales la población plantea demandas a pie de calle. Cada una de estas formas de acción reivindicativa puede ser más o menos modular. La modularidad, concepto introducido originalmente por Sidney Tarrow (1993) y popularizado por Charles Tilly (1993, 1995), hace referencia a la capacidad de adaptación, o grado de transferibilidad, de cada forma de protesta a diferentes contextos. Es decir, un modo de protesta presenta una alta modularidad si forma parte del repertorio habitual de diversos actores y es utilizado para diferentes causas, contra distintos destinatarios y en múltiples lugares. Sin embargo, el amplio desarrollo teórico del concepto no ha ido acompañado de un desarrollo similar en su operacionalización empírica. En este trabajo, partiendo de la base conceptual desarrollada por Wada (2012), planteamos una nueva perspectiva desde la que evaluar la modularidad de las formas de protesta. Así, a través del análisis de redes sociales, proponemos analizar las tablas de contingencia generadas a partir de catálogos de eventos de protesta como redes bimodales de afiliaciones, midiendo la transferibilidad de las diferentes tácticas como la centralidad de grado ponderada (Opsahl et al. 2010). Para ilustrar la utilidad de nuestra propuesta de operacionalización, utilizamos una base de datos original de eventos de protesta, aplicando nuestra medida para describir los principales cambios en el repertorio vasco de contienda durante las últimas cuatro décadas, siguiendo la evolución de la transferibilidad entre actores de diez formas de protesta diferentes. Los resultados del estudio revelan un repertorio relativamente rígido dominado por las manifestaciones y en el que la protesta simbólica ha ido adquiriendo progresivamente una mayor modularidad, a costa de la desobediencia civil y la acción directa violenta, que gozaban de mayor relevancia en los años 80 y 90. En conclusión, la nueva medida propuesta en este artículo ofrece una operacionalización más intuitiva y fácilmente representable visualmente respecto a la propuesta inicial de Wada, lo que podría incentivar la realización de más investigaciones empíricas que comparen las características de los repertorios de contienda en diferentes contextos políticos y/o periodos históricos.

Network design problems, such as flexibility design, are ubiquitous in modern marketplaces where firms constantly innovate new ways to match supply and demand. We develop a primal-dual based approach to analyze the flexibility design problem, i.e., allocating subsets of limited resources to each of multiple demand classes, and establish that the problem possesses a novel structural property. The property, which we call cover modularity, can be interpreted as an approximate form of submodularity, in the sense that local changes in the objective function can be used to bound global changes. We use this structure to analyze a class of greedy heuristics and establish the first constant factor approximation guarantee for solving the general flexibility design problem. Further, we identify a significant practical byproduct of our primal-dual analysis: the dual solutions we construct can be used as surrogates to guide the heuristics, leading to order of magnitude gains in computational efficiency, without loss of optimization performance. Finally, we extend our analysis by demonstrating the presence of cover modularity in a general class of linear programming formulations, indicating applicability of our approach to a wide range of network design problems distinct from flexibility design.

The ability to tune RNA and gene expression dynamics is greatly needed for biotechnological applications. Native RNA stabilizers or engineered 5' stability hairpins have been used to regulate transcript half-life to control recombinant protein expression. However, these methods have been mostly ad hoc and hence lack predictability and modularity. Here, we report a library of RNA modules called degradation-tuning RNAs (dtRNAs) that can increase or decrease transcript stability in vivo and in vitro. dtRNAs enable modulation of transcript stability over a 40-fold dynamic range in Escherichia coli with minimal influence on translation initiation. We harness dtRNAs in messenger RNAs and noncoding RNAs to tune gene circuit dynamics and enhance CRISPR interference in vivo. Use of stabilizing dtRNAs in cell-free transcription-translation reactions also tunes gene and RNA aptamer production. Finally, we combine dtRNAs with toehold switch sensors to enhance the performance of paper-based norovirus diagnostics, illustrating the potential of dtRNAs for biotechnological applications.

PurposeHow to determine the appropriate contractual structure for an outsourcing relationship has been a major theme in the business process outsourcing (BPO) literature. Drawing on transaction cost economics, this study aims to examine how anticipated coordination and adaptation costs in a BPO relationship affect the choice of contract types. Specifically, this research categorizes contracts types (fixed-price, time and materials and hybrid contracts) based on levels of contract design comprehensiveness and flexibility to change.Design/methodology/approachThe research setting is the BPO for a focal firm, involving a contractor. Data from 153 US companies are collected using a structured questionnaire on senior executives of functional areas of marketing, IT and finance. Hypotheses were tested using ordered probit model.FindingsThe results show that maturity is negatively associated with anticipated adaptation costs, while modularity and IT detachability are negatively related to anticipated coordination costs. Furthermore, adaptation costs have a direct impact on the choice, whereas the anticipated coordination costs do not have a significant direct impact on contract choice. The strength of adaptation costs' impact, however, is significantly reduced when coordination costs are high.Originality/valueThis study explicitly examines the role of anticipated coordination and adaptation costs in shaping the strategic choice of contract types in the BPO market. By differentiating the two types of anticipated transaction costs, this research enables a better understanding of the dynamics between transaction characteristics, anticipated transaction costs and contract types in complicated relationships such as BPO relationships.

Development has intrigued humanity since ancient times. Today, the main paradigm in developmental biology and evolutionary developmental biology (evo-devo) is the genetic program, in which development is explained by the interplay and interaction of genes, that is, by the action of gene regulatory networks (GRNs). However, it is not even clear that a GRN, no matter how complex, can be translated into a form. Therefore, the fundamental enigma of development still remains: how is a complex organism formed from a single cell? This question unfolded the historical drama and the dialectical tension between preformation and epigenesis. In order to shed light on these issues, I studied the development of crabs (infraorder Brachyura), as representative of the subphylum Crustacea, using network theory. The external morphology of the different phases of brachyuran metamorphosis were modeled as networks and their main characteristics analyzed. As one could expect, the parameters usually regarded as indicative of network complexity, such as modularity and hierarchy, increased during development. However, when more sophisticated complexity measures were tested, it was evidenced that whereas a group of complexity measures increased during development, another group decreased. This led to consider that two kinds of complexities were being measured. I called them intensive and extensive complexity. In view of these results, I propose that crab development involves a passage from an intensive to an extensive complexity. In other words, crab development can be interpreted as a process of unfolding of an intensive, preexistent complexity., Facultad de Ciencias Naturales y Museo

Studies of human mitochondrial (mt) genome variation may be undertaken to investigate the human history and natural selection. By analyzing nucleotide co-occurrence over the entire human mt-genome, we have developed a network model to describe human evolutionary patterns. Using 7,424 unique polymorphic sites, we found evidence that mutation biases at second codon position and RNA genes were critical to producing continental-level heterogeneity among human subpopulations. Further, the analysis highlighted richer co-mutation regions of the mt-genome and thus provided evidence of epistasis. Specifically, a large portion of COX genes co-mutate in Asian and American populations whereas, in African, European and Oceanic populations, there was greater epistasis in hypervariable regions. Very interestingly, this study demonstrated hierarchical modularity as a crucial agent for a nucleotide co-occurrence network make-up. More profoundly, our ancestry-based nucleotide module analyses showed that nucleotide co-changes cluster preferentially in known mitochondrial haplogroups. It was also conceived that contemporary human mt-genome nucleotides most closely resembled the ancestral state and very few of them were ancestral-variants. Overall, these results demonstrated that subpopulation based factors such as intra-species evolution do exert selection on mitochondrial genes by favoring specific epistatic genetic variants.

CRISPR–Cas activator (CRISPRa) systems that selectively turn on transcription of a target gene are a potentially transformative technology for programming cellular function. While in eukaryotes versatile CRISPRa systems exist, in bacteria these systems suffer from a limited ability to activate different genes due to strict distance-dependent requirements of functional target binding sites, and require greater customization to optimize performance in different genetic and cellular contexts. To address this, we apply a rational protein engineering approach to create a new CRISPRa platform that is highly modular to allow for easy customization and has increased targeting flexibility through harnessing engineered Cas proteins. We first demonstrate that transcription activation domains can be recruited by CRISPR–Cas through noncovalent protein-protein interactions, which allows each component to be encoded on separate and easily interchangeable plasmid elements. We then exploit this modularity to rapidly screen a library of different activation domains, creating new systems with distinct regulatory properties. Furthermore, we demonstrate that by harnessing a library of circularly permuted Cas proteins, we can create CRISPRa systems that have different target binding site requirements, which together, allow for expanded target range.

Growing evidence reveals strong overlap between microbiomes of flowers and bees, suggesting that flowers are hubs of microbial transmission. Whether floral transmission is the main driver of bee microbiome assembly, and whether functional importance of florally sourced microbes shapes bee foraging decisions are intriguing questions that remain unanswered. We suggest that interaction network properties, such as nestedness, connectedness, and modularity, as well as specialization patterns can predict potential transmission routes of microbes between hosts. Yet microbial filtering by plant and bee hosts determines realized microbial niches. Functionally, shared floral microbes can provide benefits for bees by enhancing nutritional quality, detoxification, and disintegration of pollen. Flower microbes can also alter the attractiveness of floral resources. Together, these mechanisms may affect the structure of the flower-bee interaction network.

Evolution of gait rehabilitation robotic devices for stroke survivors has aimed at providing transparency to user's efforts and implementing 'assist-as-needed' paradigm. Alteration of muscle activity and synergies recruitment has been noticed in trials involving healthy subjects but no analytic tool has been proposed to understand root causes. In this paper, a simplified neuro-mechanical model is introduced for simulating lower limbs' muscle activity during unrestrained and device-constrained gait, taking into consideration exoskeleton-plus-treadmill and end-effector categories. Muscle control is based on the key hypothesis that optimality criterion pursues co-occurrence between effort minimisation and modularity during regular gait. Results highlight that modelised motion constraints on lower body raise additional redundancies which alter muscle activity and increase intervention external to unrestrained gait synergies. Accordingly, the developed simulations help to identify the inherent limitations of current technology: further degree of freedom addition to exoskeleton-plus-treadmill device could be useful but impractical, while end-effector devices would benefit significantly from an improved interaction management.

Plant–animal interaction science repeatedly finds that plant species differ by orders of magnitude in the number of interactions they support. The identification of plant species that play key structural roles in plant–animal networks is a global conservation priority; however, in hyperdiverse systems such as tropical forests, empirical datasets are scarce. Plant species with longer reproductive seasons are posited to support more interactions compared to plant species with shorter reproductive seasons but this hypothesis has not been evaluated for plant species with the longest reproductive season possible at the individual plant level, the continuous reproductive phenology. Resource predictability is also associated with promoting specialization, and therefore, continuous reproduction may instead favor specialist interactions. Here, we use quantitative pollinating insect–plant networks constructed from countryside habitat of the Tropical Wet forest Life Zone and modularity analysis to test whether plant species that share the trait of continuous flowering hold core roles in mutualistic networks. With a few exceptions, most plant species sampled within our network were assigned to the role of peripheral. All but one network had significantly high modularity scores and each continuous flowering plant species was in a different module. Our work reveals that the continuous flowering plant species differed in some networks in their topological role, and that more evidence was found for the phenology to support specialized subsets of interactions. Our findings suggest that the conservation of Neotropical pollinating insect communities may require planting species from each module rather than identifying and conserving network hubs., Plant species with longer reproductive seasons are posited to support more interactions compared to plant species with shorter reproductive seasons but this hypothesis has not been evaluated for plant species with the longest reproductive season possible at the individual plant level, the continuous reproductive phenology. Here, we use a quantitative pollinating insect–plant network constructed in tropical lowland wet forest and modularity analysis to test whether species that share the trait of continuous flowering hold core roles in mutualistic networks. Our work reveals that the continuous flowering plant species differed in some networks in their topological role, supporting specialized subsets of interactions more commonly, and that conservation of pollinating insect communities may require planting species from each module rather than identifying and conserving network hubs.

A plants’ water and nutrients are primarily absorbed through roots, which in a natural setting is highly dependent on the 3-dimensional configuration of the root system, collectively known as root system architecture (RSA). RSA is difficult to study due to a variety of factors, accordingly, an arsenal of methods have been developed to address the challenges of both growing root systems for imaging, and the imaging methods themselves, although there is no ‘best’ method as each has its own spectrum of trade-offs. Here, we describe several methods for plant growth or imaging. Then, we introduce the adaptation and integration of three complementary methods, root mesocosms, photogrammetry, and electrical resistance tomography (ERT). Mesocosms can allow for unconstrained root growth, excavation and preservation of 3-dimensional RSA, and modularity that facilitates the use of a variety of sensors. The recovered root system can be digitally reconstructed through photogrammetry, which is an inexpensive method requiring only an appropriate studio space and a digital camera. Lastly, we demonstrate how 3-dimensional water availability can be measured using ERT inside of root mesocosms.

Adaptive radiations are often stereotypical, as populations repeatedly specialize along conserved environmental axes. Phenotypic plasticity may be similarly stereotypical, as individuals respond to environmental cues. These parallel patterns of variation, which are often consistent across traits, have led researchers to propose that plasticity can facilitate predictable patterns of evolution along environmental gradients. This "flexible stem" model of evolution raises questions about the genetic nature of plasticity, including how complex is the genetic basis for plasticity? Is plasticity across traits mediated by many distinct loci, or few "global" regulators? To address these questions, we reared a hybrid cichlid mapping population on alternate diet regimes mimicking an important environmental axis. We show that plasticity across an array of ecologically relevant traits is generally morphologically integrated, such that traits respond in a coordinated manner, especially those with overlapping function. Our genetic data are more ambiguous. While our mapping experiment provides little evidence for global genetic regulators of plasticity, these data do contain a genetic signal for the integration of plasticity across traits. Overall, our data suggest a compromise between genetic modularity, whereby plasticity may evolve independently across traits, and low level but widespread genetic integration, establishing the potential for plasticity to experience coordinated evolution.

Research Summary: Digitalization has three fundamental characteristics, reprogrammability infrastructural elementality, and intangibility Based on these characteristics, it is transforming how firms organize for value creation, delivery, and capture Its intangibility and infrastructural character largely free economic and business activities from the constraints of physical geography like those imposed by transportation and collocation Digital communication technologies typically reinforce the centrifugal forces that favor dispersing the firm's high knowledge activities Digital in situ technologies strengthen the centripetal forces toward concentrating the firm's low knowledge activities Location dependence and product modularity are crucial moderators for tangible products, while institutional barriers are important for intangible ones Finally, digital technologies increase the resilience of firms during disruptive events that impose restrictions on the movements of people and goods, as during the COVID-19 pandemic Managerial Summary: Digitalization is a general purpose technology on the scale of the steam engine and electricity, and affects every aspect of business and society It is transforming how firms organize for value creation, delivery, and capture Freeing businesses from the constraints of transportation and collocation, it increases their resiliency in the face of global disruptions like those associated with the COVID-19 pandemic Digital communication technologies typically reinforce the centrifugal forces that favor dispersing the firm's high knowledge activities Digital in situ technologies like advanced robotics strengthen the centripetal forces toward concentrating the firm's low knowledge activities Location dependence and product modularity are crucial moderators for tangible products, while institutional barriers are important for intangible ones © 2021 Strategic Management Society

Photocatalytic hydrogen production from water has the potential to fulfil future energy needs by producing a clean and storable fuel. In recent years polymer photocatalysts have attracted significant interest in an attempt to address these challenges. One reason organic photocatalysts have been considered an attractive target is their synthetic modularity, therefore, the ability to tune their opto-electronic properties by incorporating different building blocks. A wide range of factors has been investigated and in particular nano-sized particles have found to be highly efficient due to the size effect resulting from the ability of these to increase the number of charges reaching catalytic sites.

There are a vast number of cloud service providers, which offer virtual machines (VMs) with different configurations. From the companies perspective, an appropriate selection of VMs is an important issue, as the proper service selection leads to improved productivity, higher efficiency, and lower cost. An effective service selection cannot be done without a systematic approach due to the modularity of requests, the conflicts between requirements, and the impact of network parameters. In this paper, we introduce an innovative framework, called PCA, to solve service selection problem in the hybrid environment of peer-assisted, public, and private clouds. PCA detects the conflicts between the requests and enterprises policies, finds proper services based on the requirements, and reduces VMs rent and end-to-end network costs. PCA selects the services from multiple clouds to utilize resources and reduce the total cost. Our proposed framework utilizes set theory, B+ tree, and greedy algorithms to meet its goals. The simulation results show that PCA can reduce up to 30 percent of cloud-related costs and can achieve answers at least seven times faster in comparison to recent studies.

Cognitive abilities of the human brain, including language, have expanded dramatically in the course of our recent evolution from nonhuman primates, despite only minor apparent changes at the gene level. The hypothesis we propose for this paradox relies upon fundamental features of human brain connectivity, which contribute to a characteristic anatomical, functional, and computational neural phenotype, offering a parsimonious framework for connectomic changes taking place upon the human-specific evolution of the genome. Many human connectomic features might be accounted for by substantially increased brain size within the global neural architecture of the primate brain, resulting in a larger number of neurons and areas and the sparsification, increased modularity, and laminar differentiation of cortical connections. The combination of these features with the developmental expansion of upper cortical layers, prolonged postnatal brain development, and multiplied nongenetic interactions with the physical, social, and cultural environment gives rise to categorically human-specific cognitive abilities including the recursivity of language. Thus, a small set of genetic regulatory events affecting quantitative gene expression may plausibly account for the origins of human brain connectivity and cognition.

Modularization, an important trend in innovation markets, allows for recombination of product components into multiple end-product configurations. Although modularization has consequences for how firms manage their relationships with upstream component suppliers, the governance implications of modularity for innovation sourcing relationships have not been adequately examined in the prior literature. We intend to bridge this gap. We argue that (i) buyer firms employ governance mechanisms (monitoring and socialization) to cope with the strategic hazards of innovation sourcing relationships (knowledge specificity, knowledge asymmetry, and knowledge spillover) and (ii) the consequences of deploying these mechanisms in response to the strategic hazards on relationship performance are contingent upon the degree of modularity of the system in which they are deployed. We provide empirical support for the developed moderated mediation model through an analysis of 194 innovation projects. The developed theory and findings contribute to the governance and modularity literatures. In addition, our findings may help change managers’ behaviors: we observe that managers do not consider modularity when selecting governance mechanisms, while our model findings suggest they should.

Catastrophic forgetting occurs when learning algorithms change connections used to encode previously acquired skills to learn a new skill. Recently, a modular approach for neural networks was deemed necessary as learning problems grow in scale and complexity since it intuitively should reduce learning interference by separating functionality into physically distinct network modules. However, an algorithmic approach is difficult in practice since it involves expert design and trial and error. Kashtan et al. finds that evolution under an environment that changes in a modular fashion leads to the spontaneous evolution of a modular network structure. In this paper, we aim to solve the reverse problem of modularly varying goal (MVG) to obtain a highly modular structure that can mitigate catastrophic forgetting so that it can also apply to realistic data. First, we confirm that a configuration with a highly modular structure exists by applying an MVG against a realistic dataset and confirm that this neural network can mitigate catastrophic forgetting. Next, we solve the reverse problem, that is, we propose a method that can obtain a highly modular structure able to mitigate catastrophic forgetting. Since the MVG-obtained neural network can relatively maintain the intra-module elements while leaving the inter-module elements relatively variable, we propose a method to restrict the inter-module weight elements so that they can be relatively variable against the intra-module ones. From the results, the obtained neural network has a highly modular structure and can learn an unlearned goal faster than without this method.

The transcription regulatory network inside a eukaryotic cell is defined by the combinatorial actions of transcription factors (TFs). However, TF binding studies in plants are too few in number to produce a general picture of this complex network. In this study, we use large-scale ChIP-seq to reconstruct it in the maize leaf, and train machine-learning models to predict TF binding and co-localization. The resulting network covers 77% of the expressed genes, and shows a scale-free topology and functional modularity like a real-world network. TF binding sequence preferences are conserved within family, while co-binding could be key for their binding specificity. Cross-species comparison shows that core network nodes at the top of the transmission of information being more conserved than those at the bottom. This study reveals the complex and redundant nature of the plant transcription regulatory network, and sheds light on its architecture, organizing principle and evolutionary trajectory., Transcriptional factors (TFs) bind in a combinatorial fashion to specify the on-and-off states of genes in a complex and redundant regulatory network. Here, the authors construct the transcription regulatory network in maize leaf using 104 TFs ChIP-seq data and train machine learning models to predict TF binding and colocalization.

Ecosystem modelling based on membrane computing is emerging as a powerful way to study the dynamics of (real) ecological populations. *ese models, providing distributed parallel devices, have shown a great potential to imitate the rich features observed in the behaviour of species and their interactions and key elements to understand and model ecosystems. Compared with differential equations, membrane computing models, also known as P systems, can model more complex biological phenomena due to their modularity and their ability to enclose the evolution of different environments and simulate, in parallel, different interrelated processes. In this paper, a comprehensive survey of membrane computing models for ecosystems is given, taking a giant panda ecosystem as an example to assess the model performance. *is work aims at modelling a number of species using P systems with different membrane structure types to predict the number of individuals depending on parameters such as reproductive rate, mortality rate, and involving processes as rescue or release. Firstly, the computing models are introduced conceptually, describing the main elements constituting the syntax of these systems and explaining the semantics of the rules involved. Next, various modelled species (including endangered animals, plants, and bacteria) are summarized, and some computer tools are presented. *en, a discussion follows on the use of P systems for ecosystem modelling. Finally, a case study on giant pandas in Chengdu Base is analysed, concluding that the study in this field by using PDP systems can provide a valuable tool to deepen into the knowledge about the evolution of the population. *is could ultimately help in the decision-making processes of the managers of the ecosystem to increase the species diversity and modify the adaptability. Besides, the impacts of natural disasters on the population dynamics of the species should also be considered. *e analysis performed throughout the paper has taken into consideration this fact in order to increase the reliability of the prospects making use of the models designed. Ministerio de Economía, Industria y Competitividad TIN2017-89842-P (MABICAP)

Hyperscanning—the simultaneous recording of hemodynamic or neuroelectric activity of the brain——is the new technology to directly observe the brain communication between individuals. Since the publication of the first hyperscanning study in 2002, it has developed rapidly in the past decade. Brain-to-brain coupling (BBC) technology of human interaction was widely used in the research of action coordination, cooperative game, classroom teaching and other interactive tasks, which involved the use of functional magnetic resonance imaging (fMRI), Electroencephalogram (EEG), magnetoencephalography (MEG), functional near-infrared spectroscopy (fNIRS) and other neuroimaging technologies. In addition, hyperscanning research experienced a leap from pseudo-interaction to real interaction, a leap from a strictly controlled laboratory paradigm to the “field research” paradigm in nature situations. Based on the differentiation and analysis of the core concepts such as coupling and synchronization, taking the development of time and technology as the main line, this paper reviewed the common BBC indicators and their application conditions, introduced the related theories and forecasted the future research direction of BBC. In hyperscanning study, BBC refers to the interaction and influence of two or more brains, or between two or more brain regions within a single brain, while the inter-brain synchronization (IBS) refers to the consistency (relative stability) in frequency, phase, and other characteristics of signals from different brain or different regions of the brain. Thus, the similarities and differences between hyperscanning, BBC and IBS can be summarized as follows: Hyperscanning is the technique of recording the neural activity of two or more brains simultaneously. BBC refers to the interaction or interaction between two or more brains. BBC sometimes manifests as IBS, the degree of IBS can represent the strength of BBC in this case, but BBC is not the same as IBS: (1) In addition to IBS, BBC can also be manifested as functional connections and interactions between the brains; (2) due to the possibility of pseudo-synchronization, the occurrence of IBS does not mean that there must be BBC. In the field of physics and electronic engineering, the characteristics of a signal can be described by multiple indicators such as amplitude, period, frequency and phase. Accordingly, neurologic studies have found that brain activity induced by external events may take the form of phase response, frequency response, amplitude response, and production of new components. Therefore, it is not surprising that many different indicators are used to characterize the strength of BBC in existing hyperscanning studies. These indicators including the circular correlation coefficient (CCorr), wavelet transform coherence (WTC), directed coherence, phase-locking value (PLV), the coupling indexes based on the event-related potentials (ERP) such as the latency difference and the amplitude difference, the coupling indexes based on the Graph Theory such as the shortest path length, global efficiency, local efficiency, divisibility, modularity, small-word network. Through the review, we found the following three issues deserve the attention of the future hyperscanning research. Firstly, as different coupling indicators have different characteristics and applicable conditions, we suggest that the selection of indicators should be based on specific research methods, technical equipment and research problems. There are no best indicators, only the most suitable ones. Secondly, the existing theory of BBC is not complete, integrating existing theories and proposing theories with stronger explanatory power should be the focus of future hyperscanning theory research. Thirdly, there are many forms of coupling in neural processing, and the meaning of coupling is different in different forms. Therefore, it is necessary to take into account the comprehensive consideration of the specific research task type, interactive mode and other factors when discussing the significance of coupling.

Armaments are characterized by groups of technical and operational characteristics, each of which is divided into separate indicators. These include effectiveness, ranges of use; combat capability, reliability, operational safety. Under the effectiveness of the missile’s warhead it shall be understood the amount of damage that can cause an explosion in combat environment. The aim of the work is to evaluate the effectiveness of the blast-fragmentation warhead by modeling and analyzing the damaging of injurious effects. Primary blast-fragmentation warhead effects are a shock wave, which is characterized by a specific air pressure on its front and a specific impulse, as well as fragments that move at high speed. Determining the effectiveness of target neutralization by the fragmentation effect of the warhead is described by a set of positions of the j units, each of which is characterized by the fractional volume, the angle of inclination, the type of losses. Due to the independent impact on the target of several effects, their whole impact can be estimated by the total probability of individual injurious effects. The effectiveness of warhead is assessed by the probability of hitting the target. It is most rational to achieve the goal by reducing the distance to the explosion while increasing accuracy. This is a global development trend. Other ways are either to increase its explosive power or structurally - the number of fragments. It is necessary to indicate experimental data on the number of holes per unit area for a given distance and characteristics of the warhead of the missile. Assessing the probability of the debris impact requires clarification of the characteristics of the warhead, the characteristics of the vulnerable spots of the target and the angle of the missile approach. It is advisable to make the trajectory of the missile approach guided, taking into account the modularity of the configuration. This reduces ammunition consumption and increases the efficiency of the warhead.

Recent trends in manufacturing require the use of reconfigurable equipment that facilitates rapid and cost-effective change of functionality through modular design, which supports fast integration. Intelligent devices (e.g., sensors, actuators) with integrated computation and communication capabilities enable high-level modularity, not only with the respect to hardware components but also in terms of control functionality; this can be achieved by distributing control to different network-connected devices. Thus, to enable fast and reliable system reconfigurations, in this brief, we introduce a method for distribution of control tasks and generation of control code for the devices in the control network. Our approach is based on the control interpreted Petri nets (CIPNs) formalism. We start from a CIPN capturing the centralized (overall) control system, and the mapping of input and output signals to local controllers (LCs) (i.e., smart devices) that have direct physical access to system sensors and actuators. From these, our method automatically designs distributed control tasks for LCs in the network, as well as generates control code for each LC. The applicability of the proposed method is experimentally verified on two real-world case studies.

Different models have tried to find an answer to the organization of the bilingual language organization. Connectionist Models, e.g. BIA, BIA+, postulate an integrated network and a language non-selective access to the bilinguals’ mental lexicon. Accordingly, a language conflict appears in bilinguals when accessing words. The language conflict predicts slower reaction times of bilinguals on interlingual homographs. Here, German-English bilinguals, German-English high proficient users of English and German-English low proficient users of English performed a general lexical decision task on interlingual homographs, non-words, English and German control words. Group’s reaction times showed no significant differences. The results cannot account for BIA or BIA+ but for the also discussed modularity hypothesis. In addition, attention to the participants’ language skills needs to be taken in future research.

Discovery and selection of the potential targets are some of the important issues in pharmacology. Even when all the reactions and the proteins in a biological network are known, how does one choose the optimal target? Here, we review and discuss the application of the computational methods to address this problem using the blood coagulation cascade as an example. The problem of correct antithrombotic targeting is critical for this system because, although several anticoagulants are currently available, all of them are associated with bleeding risks. The advantages and the drawbacks of different sensitivity analysis strategies are considered, focusing on the approaches that emphasize: 1) the functional modularity and the multi-tasking nature of this biological network; and 2) the need to normalize hemostasis during the anticoagulation therapy rather than completely suppress it. To illustrate this effect, we show the possibility of the differential regulation of lag time and endogenous thrombin potential in the thrombin generation. These methods allow to identify the elements in the blood coagulation cascade that may serve as the targets for the differential regulation of this system.

Within the context of Greece promising a success story in the fight against the disease, this paper proposes a novel method for studying the evolution of the Greek COVID-19 infection curve in relation to the anti-COVID-19 policies applied to control the pandemic. Based on the ongoing spread of COVID-19 and the insufficient data for applying classic time-series approaches, the analysis builds on the visibility graph algorithm to study the Greek COVID-19 infection curve as a complex network. By using the modularity optimization algorithm, the generated visibility graph is divided into communities defining periods of different connectivity in the time-series body. These periods reveal a sequence of different typologies in the evolution of the disease, starting with a power pattern, where a second order polynomial (U-shaped) pattern intermediates, being followed by a couple of exponential patterns, and ending up with a current logarithmic pattern revealing that the evolution of the Greek COVID-19 infection curve tends towards saturation. In terms of Gaussian modeling, this successive compression of the COVID-19 infection curve into five parts implies that the pandemic in Greece is about to reach the second (decline) half of the bell-shaped distribution. The network analysis also illustrates stability of hubs and instability of medium and low-degree nodes, implying a low probability of meeting maximum (infection) values in the future and high uncertainty in the variability of other values below the average. The overall approach contributes to the scientific research by proposing a novel method for the structural decomposition of a time-series into periods, which allows removing from the series the disconnected past-data facilitating better forecasting, and provides insights of good policy and decision-making practices and management that may help other countries improve their performance in the war against COVID-19.

This paper describes a new modification of fuzzy cognitive maps (FCMs) for the modeling of autonomous entities that make decisions in a dynamic environment. The paper offers a general design for an FCM adjusted for the decision-making of autonomous agents through the categorization of its concepts into three different classes according to their purpose in the map: Needs, Activities, and States (FCM-NAS). The classification enables features supporting decision-making, such as the easy processing of input from sensors, faster system reactions, the modeling of inner needs, the adjustable frequency of computations in a simulation, and self-evaluation of the FCM-NAS that supports unsupervised evolutionary learning. This paper presents two use cases of the proposed extension to demonstrate its abilities. It was implemented into an agent-based artificial life model, where it took advantage of all the above features in the competition for resources, natural selection, and evolution. Then, it was used as decision-making for human activity simulation in an ambient intelligence model, where it is combined with scenario-oriented mechanism proving its modularity.

Genitalia are multitasking structures whose development is mediated by numerous regulatory pathways. This multifactorial nature provides an avenue for multiple sources of selection. As a result, genitalia tend to evolve as modular systems comprising semi-independent subsets of structures, yet the processes that give rise to those patterns are still poorly understood. Here, we ask what are the relative roles of development and function in shaping modular patterns of genitalia within populations and across species of stink-bugs. We found that male genitalia are less integrated, more modular, and primarily shaped by functional demands. In contrast, females show higher integration, lower modularity, and a predominant role of developmental processes. Further, interactions among parts of each sex are more determinant to modularity than those between the sexes, and patterns of modularity are equivalent between and within species. Our results strongly indicate that genitalia have been subjected to sex-specific selection, although male and female genitalia are homologous and functionally associated. Moreover, modular patterns are seemingly constant in the evolutionary history of stink-bugs, suggesting a scenario of multivariate stabilizing selection within each sex. Our study demonstrates that interactions among genital parts of the same sex may be more fundamental to genital evolution than previously thought.

Natural proteins traverse complex free energy landscapes to assemble into hierarchically organized structures, often through stimuli-directed kinetic pathways in response to relevant biological cues. Bioinspired strategies have sought to emulate the complexity, dynamicity, and modularity exhibited in these natural processes with synthetic analogues. However, these efforts are limited by many factors that complicate the rational design and predictable assembly of synthetic constructs, especially in aqueous environments. Herein, a model discotic amphiphile gelator is described that undergoes pathway-dependent structural maturation when exposed to varying application rates of a pH stimulus, investigated by electron microscopy, spectroscopy, and X-ray scattering techniques. Under the direction of a slowly changing pH stimulus, complex hierarchical assemblies result, characterized by mesoscale elongated "superstructure" bundles embedded in a percolated mesh of narrow nanofibers. In contrast, the assembly under a rapidly applied pH stimulus is characterized by homogeneous structures that are reminiscent of the superstructures arising from the more deliberate path, except with significantly reduced scale and concomitantly large increases in bulk rheological properties. This synthetic system bears resemblance to the pathway complexity and hierarchical ordering observed for native structures, such as collagen, and points to fundamental design principles that might be applied toward enhanced control of the properties of supramolecular self-assembly across length scales.

Performance tradeoffs are ubiquitous in both ecological and evolutionary modeling, yet they are usually postulated and built into fitness and ecological landscapes. However, tradeoffs depend on genetic background and evolutionary history and can themselves evolve. We present a simple model capable of capturing the key feedback loop: evolutionary history shapes tradeoff strength, which, in turn, shapes evolutionary future. One consequence of this feedback is that genomes with identical fitness can have different evolutionary properties shaped by prior environmental exposure. Another is that, generically, the best adaptations to one environment may evolve in another. Our simple framework bridges the gap between the phenotypic Fisher’s Geometric Model and the genotypic properties, such as modularity and evolvability, and can serve as a rich playground for investigating evolution in multiple or changing environments.

The design of controllable artificial microbial consortia has attracted considerable interest in recent years to capitalize on the inherent advantages in comparison to monocultures such as the distribution of the metabolic burden by division of labor, the modularity and the ability to convert complex substrates. One promising approach to control the consortia composition, function and stability is the provision of defined ecological niches fitted to the specific needs of the consortium members. In this review, we discuss recent examples for the creation of metabolic niches by biological engineering of resource partitioning and syntrophic interactions. Moreover, we introduce a complementing process engineering approach to provide defined spatial niches with differing abiotic conditions (e.g. O-2, T, light) in stirred tank reactors harboring biofilms. This enables the co-cultivation of microorganisms with non-overlapping abiotic requirements and the control of the strain ratio in consortia characterized by substrate competition.

Corporate governance has a significant impact not only on the behavior and performance of a corporation but also on the functioning of other corporations, entrepreneurialism in the economy, and the working of capital markets. One way of looking at the effects of corporate governance on company performance is to study the contributions of the corporate board of directors. In this article, we explore the network of the director boards for the top Indian corporations to better understand the effects of the interlocking of management boards when the financial performance is considered. To study the corporate networks, we collected and analyzed relevant data set of the top 150 Indian companies on the basis of the maximum revenue generation. We find that the debt-to-equity ratio (D/E), on average, tends to decrease as the measure of the degree centrality of certain corporations increases. Furthermore, we study a modularity maximization-based community structure of the network of director boards to better comprehend the interconnections of the Indian corporates. Moreover, the underlying relationship between the modularity and the corporate performance is also analyzed, and it can be observed that most of the top Indian corporations, with low net current asset value per share, belong to the larger communities.

Large numbers of quantitative trait loci (QTLs) for blood pressure (BP) exist and have long been thought to function by accumulating their individual miniscule effects. Recent experimental evidence in the functional biology of BP control has tested this intuitive assumption. A new paradigm has emerged that BP is biologically determined in modularity by multiple QTLs. Functionally, when a master regulator is taken out, distinct epistatic modules organize biological 'blocks' into a genetic architecture, and serve as basic functional cores from which numerous QTLs act together to physiologically formulate BP. An epistatic module refers to the grouping of QTLs that perform their functions epistatically to one another and influence BP as a group. The modularity mechanism framework indicates that BP as a quantitatively-measured trait is not cumulatively determined and implies that the QTLs in the same epistatic module may participate in the same pathway leading to the BP control, and the QTLs from separate epistatic modules may act in divergent but parallel pathways. This mechanistic conceptualization and subsequent validations synergize with anticipated demands from current human epidemiological studies, since the outcome from them primarily implicates single nucleotide polymorphisms with unknown functions. Eventually, functional understandings of the human results have to be realized by their pathogenic directionality and mechanisms biologically controlling BP.

PurposeThe purpose of this paper is to offer novel and complementary insights into the relationship between product modularity and product innovation by investigating the mediating role of module suppliers' relationship-specific investments which include both property-based relationship-specific investment (PRSI) and knowledge-based relationship-specific investment (KRSI).Design/methodology/approachThis paper is an empirical study based on structural equation modelling, with a sample of 121 core firms of high-tech modular cooperation in China.FindingsThe findings indicated that product modularity had a significant positive effect on product innovation; product modularity was positively related to module suppliers' PRSI; module suppliers’ KRSI had a direct effect on product innovation while PRSI had an indirect effect on product innovation through KRSI; the relationship between product modularity and product innovation was serially multi-mediated by module suppliers’ PRSI and KRSI.Practical implicationsModular product design and modular cooperation governance guidance for core firms and cooperative investment strategies guidance for module suppliers were provided.Originality/valueThis study is the first attempt to analyse how product modularity affects product innovation in the context of inter-firm modular cooperation by revealing the mediating role of module suppliers' relationship-specific investments.

The evolution of semi-independent modules is hypothesized to underlie the functional diversification of serially repeating (metameric) structures. The mammal vertebral column is a classic example of a metameric structure that is both modular, with well-defined morphological regions, and functionally differentiated. How the evolution of regions is related to their functional differentiation in the forerunners of mammals remains unclear. Here we gathered morphometric and biomechanical data on the presacral vertebrae of two extant species that bracket the synapsid–mammal transition and use the relationship between form and function to predict functional differentiation in extinct non-mammalian synapsids. The origin of vertebral functional diversity does not correlate with the evolution of new regions but appears late in synapsid evolution. This decoupling of regions from functional diversity implies that an adaptive trigger is needed to exploit existing modularity. We propose that the release of axial respiratory constraints, combined with selection for novel mammalian behaviours in Late Triassic cynodonts, drove the functional divergence of pre-existing morphological regions. Applying vertebral form–function relationships derived from extant animals to the synapsid fossil record indicates evolution of vertebral regions is decoupled from their functional exploitation.

A major goal in post-synthesis evolutionary biology has been to better understand how complex interactions between traits drive movement along and facilitate the formation of distinct evolutionary pathways. I present analyses of a character matrix sampled across the haplorrhine skeleton that revealed several modules of characters displaying distinct patterns in macroevolutionary disparity. Comparison of these patterns to those in neurological development showed that early ape evolution was characterized by an intense regime of evolutionary and developmental flexibility. Shifting and reduced constraint in apes was met with episodic bursts in phenotypic innovation that built a wide array of functional diversity over a foundation of shared developmental and anatomical structure. Shifts in modularity drove dramatic evolutionary changes across the ape body plan in two distinct ways: 1) an episode of relaxed integration early in hominoid evolution coincided with bursts in evolutionary rate across multiple character suites; 2) the formation of two new trait modules along the branch leading to chimps and humans preceded rapid and dramatic evolutionary shifts in the carpus and pelvis. Changes to the structure of evolutionary mosaicism may correspond to enhanced evolvability that has a ‘preadaptive’ effect by catalyzing later episodes of dramatic morphological remodeling.

Product modularity can be considered as a product design strategy. It provides many benefits for companies that adapt it. However, there is little empirical evidence to support such an expectation. This study aims to measure the effects of product modularity on the efficiency and productivity of the product engineering area of a bus manufacturer. To reach the proposed objective, a longitudinal case study was conducted on the product engineering department of a company covering a period of three consecutive years. We used Data Envelopment Analysis (DEA) combined with Mann–Whitney U test and Malmquist index. The results show an increase of 18.40% in the efficiency indexes of the company’s products engineering. In addition, positive changes can be observed, that is, there was a 63.50% increase in Total Factor Productivity Index (TFPI). The improvements are attributed to the implementation of product modularity in the organization under study. In this sense, the main contribution of this paper to the field is to present the increment of productivity with the insertion of the product modularity in the product engineering in a bus manufacturing company. Thus, product modularity can be considered a technology that increases the Total Factor Productivity Index (TPFI) of the companies that use it.

This paper proposes a dynamic state-of-charge (SOC) balance control strategy for the modular super capacitor energy storage system (ESS). The strategy takes SOC information as the droop variable and introduces the SOC of each module into its independent current closed loop by inverse droop control, so that the system can adjust the average operating current of each sub-module according to its SOC in the system dynamic charging and discharging process. Moreover, a concise unified current compensation method is proposed to minimize system current deviation caused by the balance algorithm. Compared with the traditional control strategies, the proposed strategy does not need to exchange SOC information between sub-modules, thus effectively reduces system communication data. In addition, the proposed strategy not only has favorable voltage control ability and stability, but also has a concise control structure. The proposed balance control strategy can further improve the modularity and reliability of the modular ESS, which is helpful to promote the application of the system in medium and high voltage applications.

The paper suggests a novel workflow to solving adaptively the automated guided vehicle (AGV) fleet management problem with the key objective to serve production flawlessly. Departing from a material flow network model it is shown how an analysis using recent notions and methods of network science can detect the hidden structure of the overall problem. Once uncovered, this modularity-based structuring is exploited when balancing the expected load of vehicles and dynamically deciding their final dispatching. The paper presents stages of the workflow and the merits of its application on a series of comparative simulation studies taken from industrial experience.