In this paper, we obtain the finite-horizon and infinite-horizon ruin probability asymptotics for risk processes with claims of subexponential tails for non-stationary arrival processes that satisfy ...a large deviation principle. As a result, the arrival process can be dependent, non-stationary and non-renewal. We give three examples of non-stationary and non-renewal point processes: Hawkes process, Cox process with shot noise intensity and self-correcting point process. We also show some aggregate claims results for these three examples.
•Asymptotic ruin probabilities for risk processes with subexponential claims.•Some aggregate claims asymptotics are also studied.•Arrival process can be non-stationary and non-renewal.•The key assumption is arrival process satisfies a large deviation principle.•We apply our results to three examples of arrival processes.
The effective operation of time-critical Internet of things (IoT) applications requires real-time reporting of fresh status information of underlying physical processes. In this paper, a real-time ...IoT monitoring system is considered, in which the IoT devices sample a physical process with a sampling cost and send the status packet to a given destination with an updating cost. This joint status sampling and updating process is designed to minimize the average age of information (AoI) at the destination node under an average energy cost constraint at each device. This stochastic problem is formulated as an infinite horizon average cost constrained Markov decision process (CMDP) and transformed into an unconstrained Markov decision process (MDP) using a Lagrangian method. For the single IoT device case, the optimal policy for the CMDP is shown to be a randomized mixture of two deterministic policies for the unconstrained MDP, which is of threshold type. This reveals a fundamental tradeoff between the average AoI at the destination and the sampling and updating costs. Then, a structure-aware optimal algorithm to obtain the optimal policy of the CMDP is proposed and the impact of the wireless channel dynamics is studied while demonstrating that channels having a larger mean channel gain and less scattering can achieve better AoI performance. For the case of multiple IoT devices, a low-complexity semi-distributed suboptimal policy is proposed with the updating control at the destination and the sampling control at each IoT device. Then, an online learning algorithm is developed to obtain this policy, which can be implemented at each IoT device and requires only the local knowledge and small signaling from the destination. The proposed learning algorithm is shown to converge almost surely to the suboptimal policy. Simulation results show the structural properties of the optimal policy for the single IoT device case; and show that the proposed policy for multiple IoT devices outperforms a zero-wait baseline policy, with average AoI reductions reaching up to 33%.
Microglia are morphologically dynamic cells that rapidly extend their processes in response to various stimuli including extracellular ATP. In this study, we tested the hypothesis that stimulation of ...neuronal NMDARs trigger ATP release leading to communication with microglia. We used acute mouse hippocampal brain slices and two-photon laser scanning microscopy to study microglial dynamics and developed a novel protocol for fixation and immunolabeling of microglia processes. Similar to direct topical ATP application in vivo, short multiple applications of NMDA triggered transient microglia process outgrowth that was reversible and repeatable indicating that this was not due to excitotoxic damage. Stimulation of NMDAR was required as NMDAR antagonists, but not blockers of AMPA/kainate receptors or voltage-gated sodium channels, prevented microglial outgrowth. We report that ATP release, secondary to NMDAR activation, was the key mediator of this neuron-microglia communication as both blocking purinergic receptors and inhibiting hydrolysis of ATP to prevent locally generated gradients abolished outgrowth. Pharmacological and genetic analyses showed that the NMDA-triggered microglia process extension was independent of Pannexin 1, the ATP releasing channels, ATP release from astrocytes via connexins, and nitric oxide generation. Finally, using whole-cell patch clamping we demonstrate that activation of dendritic NMDAR on single neurons is sufficient to trigger microglia process outgrowth. Our results suggest that dendritic neuronal NMDAR activation triggers ATP release via a Pannexin 1-independent manner that induces outgrowth of microglia processes. This represents a novel uncharacterized form of neuron-microglial communication mediated by ATP.
•We analyzed the persistency in innovation behavior of firms, using a panel of Community Innovation Survey in Sweden, which spans over a decade.•We distinguish between product, process, ...organizational, and marketing innovations.•There is a variation in the degree of persistency among the four types of innovation.•Product Innovation shows the strongest persistency among all four types of innovation.•Marketing Innovation shows the least persistency.
This paper analyzes the persistency in innovation behavior of firms. Using five waves of the Community Innovation Survey in Sweden, we have traced the innovative behavior of firms over a ten-year period, i.e., between 2002 and 2012. We distinguish between four types of innovations: process, product, marketing, and organizational innovations. First, using transition probability matrix, we found evidence of (unconditional) state dependence in all types of innovation, with product innovators having the strongest persistent behavior. Second, using a dynamic probit model, we found evidence of “true” state dependency among all types of innovations, except marketing innovators. Once again, the strongest persistency was found for product innovators.
•Investment in digitalization increases employment of high-skilled people.•Investment in digitalization reduces employment of low-skilled people.•The job effects are driven by firms that employ ...machine-based digital technologies.•We do not find employment effects for non-machine-based digital technologies.
With the process of digitalization now in full swing, many are wondering how the adoption of new technologies influences job creation and destruction. Much hinges upon the specific tasks that machines take on and how many new tasks are created through the adoption of new digital technologies. Some argue that most tasks that are at risk of automation are those performed by rather low- to medium-skilled employees, while most new tasks that emerge from the adoption of digital technologies complement high-skilled labor. We present evidence derived from representative survey data from Switzerland that is consistent with this view. Specifically, we find that increased investment in digitalization is associated with increased employment of high-skilled workers and reduced employment of low-skilled workers, with a slightly positive net effect. The main effects are almost entirely driven by firms that employ machine-based digital technologies, e.g. robots, 3D printing or the Internet of Things. We do not find any significant employment effects when non-machine-based digital technologies are considered, e.g. ERP, e-commerce or cooperation support systems.
This volume explores the complexity, diversity and interwoven nature of taxonomic pursuits within the context of explorations of humans and related species. It also pays tribute to Professor Colin ...Groves, whose work has had an enormous impact on this field. Recent research into that somewhat unique species we call humankind, through the theoretical and conceptual approaches afforded by the discipline of biological anthropology, is showcased. The focus is on the evolution of the human species, the behaviour of primates and other species, and how humans affect the distribution and abundance of other species through anthropogenic impact. Weaving together these three key themes, through the considerable influence of Colin Groves, provides glimpses of how changes in taxonomic theory and methodology, including our fluctuating understanding of speciation, have recrafted the way in which we view animal behaviour, human evolution and conservation studies.
Abstract
Direct microstructure observations across three warm mesoscale eddies were conducted in the northern South China Sea during the field experiments in July 2007, December 2013, and January ...2014, respectively, along with finestructure measurements. An important finding was that turbulent mixing in the mixed layer was considerably elevated in the periphery of each of these eddies, with a mixing level 5–7 times higher than that in the eddy center. To explore the mechanism behind the high mixing level, this study carried out analyses of the horizontal wavenumber spectrum of velocities and spectral fluxes of kinetic energy. Spectral slopes showed a power law of
k
−2
in the eddy periphery and of
k
−3
in the eddy center, consistent with the result that the kinetic energy of submesoscale motion in the eddy periphery was more greatly energized than that in the center. Spectral fluxes of kinetic energy also revealed a forward energy cascade toward smaller scales at the wavelength of kilometers in the eddy periphery. This study illustrated a possible route for energy cascading from balanced mesoscale dynamics to unbalanced submesoscale behavior, which eventually furnished turbulent mixing in the upper ocean.
An autoregressive process with Markov regime is an autoregressive process for which the regression function at each time point is given by a nonobservable Markov chain. In this paper we consider the ...asymptotic properties of the maximum likelihood estimator in a possibly nonstationary process of this kind for which the hidden state space is compact but not necessarily finite. Consistency and asymptotic normality are shown to follow from uniform exponential forgetting of the initial distribution for the hidden Markov chain conditional on the observations.
During infection the SARS-CoV-2 virus fuses its viral envelope with cellular membranes of its human host. The viral spike (S) protein mediates both the initial contact with the host cell and the ...subsequent membrane fusion. Proteolytic cleavage of S at the S2′ site exposes its fusion peptide (FP) as the new N-terminus. By binding to the host membrane, the FP anchors the virus to the host cell. The reorganization of S2 between virus and host then pulls the two membranes together. Here we use molecular dynamics (MD) simulations to study the two core functions of the SARS-CoV-2 FP: to attach quickly to cellular membranes and to form an anchor strong enough to withstand the mechanical force during membrane fusion. In eight 10 μs long MD simulations of FP in proximity to endosomal and plasma membranes, we find that FP binds spontaneously to the membranes and that binding proceeds predominantly by insertion of two short amphipathic helices into the membrane interface. Connected via a flexible linker, the two helices can bind the membrane independently, yet binding of one promotes the binding of the other by tethering it close to the target membrane. By simulating mechanical pulling forces acting on the C-terminus of the FP, we then show that the bound FP can bear forces up to 250 pN before detaching from the membrane. This detachment force is more than 10-fold higher than an estimate of the force required to pull host and viral membranes together for fusion. We identify a fully conserved disulfide bridge in the FP as a major factor for the high mechanical stability of the FP membrane anchor. We conclude, first, that the sequential binding of two short amphipathic helices allows the SARS-CoV-2 FP to insert quickly into the target membrane, before the virion is swept away after shedding the S1 domain connecting it to the host cell receptor. Second, we conclude that the double attachment and the conserved disulfide bridge establish the strong anchoring required for subsequent membrane fusion. Multiple distinct membrane-anchoring elements ensure high avidity and high mechanical strength of FP–membrane binding.
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