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"Ivanov, Dmitry"
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Handbook of ripple effects in the supply chain
This book offers an introduction to the ripple effect in the supply chain for a broad audience comprising recent developments. The chapters of this handbook are written by leading experts in supply chain risk management and resilience. For the first time, the chapters present in their synergy a multiple-faceted view of the ripple effect in supply chains, while considering organization, optimization, and informatics perspectives. Ripple effect describes the impact of a disruption propagation on supply chain performance, structural designs and operational parameters. The ripple effect manifests when the impact of a disruption cannot be localized and cascades along the supply chain. The resulting structural dynamics can lead to capacity and demand fulfilment downscaling and negatively influence the firm's financial and operational performance. The book delineates major features of the ripple effect and methodologies to mitigate the adverse impact of supply chain disruption propagation and to recover in case of severe disruptions. The book provides fresh insights for supply chain management and engineering regarding the following questions: - In what circumstance does one failure cause other failures? - Which structures of the supply chain are especially susceptible to the ripple effect? - What are the typical ripple effect scenarios and what are the most efficient ways to respond them? Distinctive Features: It considers ripple effect in the supply chain from an multi-disciplinary perspective It offers an introduction to ripple effect mitigation and recovery policies in the framework of disruption risk management in supply chains for a broad audience It integrates management and engineering perspectives on disruption risk management in the supply chain It presents innovative optimization and simulation models for real-life management problems It considers examples from both industrial and service supply chains It reveals decision-making recommendations for tackling disruption risks in the supply chain in proactive and reactive domains.
Book
Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic
Viability is the ability of a supply chain (SC) to maintain itself and survive in a changing environment through a redesign of structures and replanning of performance with long-term impacts. In this paper, we theorize a new notion—the viable supply chain (VSC). In our approach, viability is considered as an underlying SC property spanning three perspectives, i.e., agility, resilience, and sustainability. The principal ideas of the VSC model are adaptable structural SC designs for supply–demand allocations and, most importantly, establishment and control of adaptive mechanisms for transitions between the structural designs. Further, we demonstrate how the VSC components can be categorized across organizational, informational, process-functional, technological, and financial structures. Moreover, our study offers a VSC framework within an SC ecosystem. We discuss the relations between resilience and viability. Through the lens and guidance of dynamic systems theory, we illustrate the VSC model at the technical level. The VSC model can be of value for decision-makers to design SCs that can react adaptively to both positive changes (i.e., the agility angle) and be able to absorb negative disturbances, recover and survive during short-term disruptions and long-term, global shocks with societal and economical transformations (i.e., the resilience and sustainability angles). The VSC model can help firms in guiding their decisions on recovery and re-building of their SCs after global, long-term crises such as the COVID-19 pandemic. We emphasize that resilience is the central perspective in the VSC guaranteeing viability of the SCs of the future. Emerging directions in VSC research are discussed.
Journal Article
Notch Signaling-Induced Oscillatory Gene Expression May Drive Neurogenesis in the Developing Retina
After integrating classic and cutting-edge research, we proposed a unified model that attempts to explain the key steps of mammalian retinal neurogenesis. We proposed that the Notch signaling-induced lateral inhibition mechanism promotes oscillatory expression of Hes1. Oscillating Hes1 inhibitory activity as a result leads to oscillatory expression of Notch signaling inhibitors, activators/inhibitors of retinal neuronal phenotypes, and cell cycle-promoting genes all within a retinal progenitor cell (RPC). We provided a mechanism explaining not only how oscillatory expression prevents the progenitor-to-precursor transition, but also how this transition happens. Our proposal of the mechanism posits that the levels of the above factors not only oscillate but also rise (with the exception of Hes1) as the factors accumulate within a progenitor. Depending on which factors accumulate fastest and reach the required supra-threshold levels (cell cycle activators or Notch signaling inhibitors), the progenitor either proliferates or begins to differentiate without any further proliferation when Notch signaling ceases. Thus, oscillatory gene expression may regulate an RPC's decision to proliferate or differentiate. Meanwhile, a post-mitotic precursor's selection of one retinal neuronal phenotype over many others depends on the expression level of key transcription factors (activators) required for each of these retinal neuronal phenotypes. Because the events described above are stochastic due to oscillatory gene expression and gene product inheritance from a mother RPC after its division, an RPC or precursor's decision requires the assignment of probabilities to specific outcomes in the selection process. While low and sustained (non-oscillatory) Notch signaling activity is required to promote the transition of retinal progenitors into various retinal neuronal phenotypes, we propose that the lateral inhibition mechanism, combined with high expression of the BMP signaling-induced Inhibitor of Differentiation (ID) protein family, promotes high and sustained (non-oscillatory) Hes1 and Hes5 expression. These events facilitate the transition of an RPC into the Müller glia (MG) phenotype at the late stage of retinal development.
Journal Article
Dihadron production at the LHC: full next-to-leading BFKL calculation
The study of the inclusive production of a pair of charged light hadrons (a “dihadron” system) featuring high transverse momenta and well separated in rapidity represents a clear channel for the test of the BFKL dynamics at the Large Hadron Collider (LHC). This process has much in common with the well-known Mueller–Navelet jet production; however, hadrons can be detected at much smaller values of the transverse momentum than jets, thus allowing to explore an additional kinematic range, supplementary to the one studied with Mueller–Navelet jets. Furthermore, it makes it possible to constrain not only the parton densities (PDFs) for the initial proton, but also the parton fragmentation functions (FFs) describing the detected hadron in the final state. Here, we present the first full NLA BFKL analysis for cross sections and azimuthal angle correlations for dihadrons produced in the LHC kinematic ranges. We make use of the Brodsky–Lapage–Mackenzie optimization method to set the values of the renormalization scale and study the effect of choosing different values for the factorization scale. We also gauge the uncertainty coming from the use of different PDF and FF parametrizations.
Journal Article
Neuromorphic artificial intelligence systems
Modern AI systems, based on von Neumann architecture and classical neural networks, have a number of fundamental limitations in comparison with the brain. This article discusses such limitations and the ways they can be mitigated. Next, it presents an overview of currently available neuromorphic AI projects in which these limitations are overcome by bringing some brain features into the functioning and organization of computing systems (TrueNorth, Loihi, Tianjic, SpiNNaker, BrainScaleS, NeuronFlow, DYNAP, Akida). Also, the article presents the principle of classifying neuromorphic AI systems by the brain features they use (neural networks, parallelism and asynchrony, impulse nature of information transfer, local learning, sparsity, analog and in-memory computing). In addition to new architectural approaches used in neuromorphic devices based on existing silicon microelectronics technologies, the article also discusses the prospects of using a new memristor element base. Examples of recent advances in the use of memristors in neuromorphic applications are also given.
Journal Article
Exiting the COVID-19 pandemic: after-shock risks and avoidance of disruption tails in supply chains
Entering the COVID-19 pandemic wreaked havoc on supply chains. Reacting to the pandemic and adaptation in the “new normal” have been challenging tasks. Exiting the pandemic can lead to some after-shock effects such as “disruption tails.” While the research community has undertaken considerable efforts to predict the pandemic’s impacts and examine supply chain adaptive behaviors during the pandemic, little is known about supply chain management in the course of pandemic elimination and post-disruption recovery. If capacity and inventory management are unaware of the after-shock risks, this can result in highly destabilized production–inventory dynamics and decreased performance in the post-disruption period causing product deficits in the markets and high inventory costs in the supply chains. In this paper, we use a discrete-event simulation model to investigate some exit strategies for a supply chain in the context of the COVID-19 pandemic. Our model can inform managers about the existence and risk of disruption tails in their supply chains and guide the selection of post-pandemic recovery strategies. Our results show that supply chains with postponed demand and shutdown capacity during the COVID-19 pandemic are particularly prone to disruption tails. We then developed and examined two strategies to avoid these disruption tails. First, we observed a conjunction of recovery and supply chain coordination which mitigates the impact of disruption tails by demand smoothing over time in the post-disruption period. Second, we found a gradual capacity ramp-up prior to expected peaks of postponed demand to be an effective strategy for disruption tail control.
Journal Article
Hadron-jet correlations in high-energy hadronic collisions at the LHC
The inclusive production at the LHC of a charged light hadron and of a jet, featuring a wide separation in rapidity, is suggested as a new probe process for the investigation of the BFKL mechanism of resummation of energy logarithms in the QCD perturbative series. We present some predictions, tailored on the CMS and CASTOR acceptances, for the cross section averaged over the azimuthal angle between the identified jet and hadron and for azimuthal correlations.
Journal Article
High-energy resummed distributions for the inclusive Higgs-plus-jet production at the LHC
The inclusive hadroproduction of a Higgs boson and of a jet, featuring large transverse momenta and well separated in rapidity, is proposed as a novel probe channel for the manifestation of the Balitsky–Fadin–Kuraev–Lipatov (BFKL) dynamics. Using the standard BFKL approach, with partial inclusion of next-to-leading order effects, predictions are presented for azimuthal Higgs-jet correlations and other observables, to be possibly compared with experimental analyses at the LHC and with theoretical predictions obtained in different schemes.
Journal Article
Lean resilience: AURA (Active Usage of Resilience Assets) framework for post-COVID-19 supply chain management
PurposeSupply chain resilience capabilities are usually considered in light of some anticipated events and are as passive assets, which are “waiting” for use in case of an emergency. This, however, can be inefficient. Moreover, the current COVID-19 pandemic has revealed difficulties in the timely deployments of resilience assets and their utilization for value creation. We present a framework that consolidates different angles of efficient resilience and renders utilization of resilience capabilities for creation of value.Design/methodology/approachWe conceptualise the design of the AURA (Active Usage of Resilience Assets) framework for post-COVID-19 supply chain management through collating the extant literature on value creation-oriented resilience and practical examples and complementing our analysis with a discussion of practical implementations.FindingsBuilding upon and integrating the existing frameworks of VSC (Viable Supply Chain), RSC (Reconfigurable Supply Chain) and LCNSC (Low-Certainty-Need Supply Chain), we elaborate on a new idea in the AURA approach – to consider resilience as an inherent, active and value-creating component of operations management decisions, rather than as a passive “shield” to protect against rare, severe events. We identify 10 future research areas for lean resilience integrating management and digital platforms and technology.Practical implicationsThe outcomes of our study can be used by supply chain and operations managers to improve the efficiency and effectiveness by turning resilience from passive, cost-driving assets into a value-creating, inclusive decision-making paradigm.Originality/valueWe propose a novel approach to bring more dynamics to the notion of supply chain resilience. We name our approach AURA and articulate its two major advantages as follows: (1) reduction of disruption prediction efforts and (2) value creation from resilience assets. We offer a discussion on ten future research directions towards a lean resilience.
Journal Article
Fundamentals of ultrafast laser–material interaction
Short pulse laser irradiation has the ability to bring a material into a state of strong electronic, thermal, phase, and mechanical nonequilibrium and trigger a sequence of structural transformations leading to the generation of complex multiscale surface morphologies, unusual metastable phases, and microstructures that cannot be produced by any other means. In this article, we provide an overview of recent advancements and existing challenges in the understanding of the fundamental mechanisms of short pulse laser interaction with materials, including the material response to strong electronic excitation, ultrafast redistribution and partitioning of the deposited laser energy, the peculiarities of phase transformations occurring under conditions of strong superheating/undercooling, as well as laser-induced generation of crystal defects and modification of surface microstructure.
Journal Article