1,181 research outputs found

    Online mechanism design for electric vehicle charging

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    The rapid increase in the popularity of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) is expected to place a considerable strain on the existing electricity grids, due to the high charging rates these vehicles require. In many places, the limited capacity of the local electricity distribution network will be exceeded if many such vehicles are plugged in and left to charge their batteries simultaneously. Thus, it will become increasingly important to schedule the charging of these vehicles, taking into account the vehicle owners’ preferences, and the local constraints on the network. In this paper, we address this setting using online mechanism design and develop a mechanism that incentivises agents (representing vehicle owners) to truthfully reveal their preferences, as well as when the vehicle is available for charging. Existing related online mechanisms assume that agent preferences can be described by a single parameter. However, this is not appropriate for our setting since agents are interested in acquiring multiple units of electricity and can have different preferences for these units, depending on factors such as their expected travel distance. To this end, we extend the state of the art in online mechanism design to multi-valued domains, where agents have non-increasing marginal valuations for each subsequent unit of electricity. Interestingly, we show that, in these domains, the mechanism occasionally requires leaving electricity unallocated to ensure truthfulness. We formally prove that the proposed mechanism is dominant-strategy incentive compatible, and furthermore, we empirically evaluate our mechanism using data from a real-world trial of electric vehicles in the UK. We show that our approach outperforms any fixed price mechanism in terms of allocation efficiency, while performing only slightly worse than a standard scheduling heuristic, which assumes non-strategic agents

    Untersuchung von Chloridtransportprozessen am Beispiel von ClC-2 und KCC2 Knockout Mäusen

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    In dieser Arbeit wurden die Funktion der beiden Chloridtransportproteine KCC2 und ClC–2 in Knockout Mausmodellen untersucht. Während ClC–2 ein ubiquitär exprimierter Chloridkanal ist (Thiemann et al., 1992), wird KCC2 ausschließlich in ZNS exprimiert (Payne et al., 1996). Von beiden untersuchten Chloridtransportern wurde erwartet, daß sie eine wichtige Rolle in der Regulation der intrazellulären Chloridkonzentration in Neuronen spielen. Für KCC2 konnte dies zum ersten Mal im physiologischen Zusammenhang bestätigt werden. In Clcn2-/- Tieren wurde jedoch keine neurologische Veränderung beobachtet. Eine eingehende Untersuchung der neuronale Funktion von ClC–2 steht jedoch noch aus, so daß eine subtile neuronale Funktion von ClC–2 nicht ausgeschlossen werden kann

    Hybrid bounds for twisted L-functions

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    The aim of this paper is to derive bounds on the critical line Rs 1/2 for L- functions attached to twists f circle times chi of a primitive cusp form f of level N and a primitive character modulo q that break convexity simultaneously in the s and q aspects. If f has trivial nebentypus, it is shown that L(f circle times chi, s) << (N vertical bar s vertical bar q)(epsilon) N-4/5(vertical bar s vertical bar q)(1/2-1/40), where the implied constant depends only on epsilon > 0 and the archimedean parameter of f. To this end, two independent methods are employed to show L(f circle times chi, s) << (N vertical bar s vertical bar q)(epsilon) N-1/2 vertical bar S vertical bar(1/2)q(3/8) and L(g,s) << D-2/3 vertical bar S vertical bar(5/12) for any primitive cusp form g of level D and arbitrary nebentypus (not necessarily a twist f circle times chi of level D vertical bar Nq(2))

    Antithrombotic therapy after myocardial reperfusion in acute myocardial infarction

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    AbstractThe problem of post-thrombolytic reocclusion can be approached in several ways. 1) Better thrombolytic agents with longer duration of effects and more powerful properties aimed at enhanced clot lysis and anticoagulation are under study. 2) The combination of high dose heparin and low dose aspirin is proposed for all patients with an acute myocardial infarction treated with thrombolytic agents. 3) Peptide inhibitors of thrombin and monoclonal antibodies against platelet glycoprotein receptors and adhesive macromolecules are potentially effective inhibitors of platelet aggregation and thrombus formation during or after thrombolytic therapy

    Two-sided online markets for electric vehicle charging

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    With the growing popularity of electric vehicles (EVs), the number of public charging stations is increasing rapidly, allowing drivers to charge their cars while parked away from home or en-route to their destination. However, as a full charge can take a significant amount of time, drivers may face queues and uncertainty over availability of charging facilities at different stations and times. In this paper, we address this problem by proposing a novel, two-sided market for advance reservations, in which agents, representing EV owners, report their preferences for time slots and charging locations, while charging stations report their availability and costs. In our model, both parties are rational, profit-maximising entities, and buyers enter the market dynamically over time. Given this, we apply techniques from online mechanism design to develop a pricing mechanism which is truthful on the buyer side (i.e., drivers have no incentive to misreport their preferences or to delay their reservations). For the seller side, we adapt three well-known pricing mechanisms and compare them both theoretically and empirically. Using realistic simulations, we demonstrate that two of our proposed mechanisms consistently achieve a high efficiency (90–95% of optimal), while offering a trade-off between stability and budget balance. Surprisingly, the third mechanism, a common payment mechanism that is truthful in simpler settings, achieves a significantly lower efficiency and runs a high deficit

    Neddylation regulates excitatory synaptic transmission and plasticity

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    Post-translational modifications, like phosphorylation, ubiquitylation, and sumoylation, have been shown to impact on synaptic neurotransmission by modifying pre- and postsynaptic proteins and therefore alter protein stability, localization, or protein-protein interactions. Previous studies showed that post-translational modifications are essential during the induction of synaptic plasticity, defined by a major reorganization of synaptic proteins. We demonstrated before that neddylation, a post-translational modification that covalently binds Nedd8 to lysine-residues, strongly affects neuronal maturation and spine stability. We now analysed the consequences of inhibiting neddylation on excitatory synaptic transmission and plasticity, which will help to narrow down possible targets, to make educated guesses, and test specific candidates. Here, we show that acute inhibition of neddylation impacts on synaptic neurotransmission before morphological changes occur. Our data indicate that pre- and postsynaptic proteins are neddylated since the inhibition of neddylation impacts on presynaptic release probability and postsynaptic receptor stabilization. In addition, blocking neddylation during the induction of long-term potentiation and long-term inhibition abolished both forms of synaptic plasticity. Therefore, this study shows the importance of identifying synaptic targets of the neddylation pathway to understand the regulation of synaptic transmission and plasticity.Fil: Brockmann, Marisa M.. Universitat Bonn; Alemania. Max Planck Institute Of Psychiatry; AlemaniaFil: Döngi, Michael. Universitat Bonn; AlemaniaFil: Einsfelder, Ulf. Universitat Bonn; AlemaniaFil: Körber, Nils. Universitat Bonn; AlemaniaFil: Refojo, Damian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; ArgentinaFil: Stein, Valentin. Universitat Bonn; Alemani

    Extreme tooth enlargement in a new Late Cretaceous rhabdodontid dinosaur from Southern France

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    International audienceRhabdodontidae is a successful clade of ornithopod dinosaurs, characteristic of Late Cretaceous continental faunas in Europe. A new rhabdodontid from the late Campanian, of southern France, Matheronodon provincialis gen. et sp. nov., is characterized by the extreme enlargement of both its maxillary and dentary teeth, correlated to a drastic reduction in the number of maxillary teeth (4 per generation in MMS/VBN-02-102). The interalveolar septa on the maxilla are alternately present or resorbed ventrally so as to be able to lodge such enlarged teeth. The rhabdodontid dentition and masticatory apparatus were adapted for producing a strict and powerful shearing action, resembling a pair of scissors. With their relatively simple dentition, contrasting with the sophisticated dental batteries in contemporary hadrosaurids, Matheronodon and other rhabdodontids are tentatively interpreted as specialized consumers of tough plant parts rich in sclerenchyma fibers, such as Sabalites and Pandanites

    Long-term changes of parvalbumin- and somatostatin-positive interneurons of the primary motor cortex after chronic social defeat stress depend on individual stress-vulnerability

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    Chronic stress is a major risk factor for developing mental illnesses and cognitive deficiencies although stress-susceptibility varies individually. In a recent study, we established the connection between chronic social defeat stress (CSDS) and impaired motor learning abilities accompanied by chronically disturbed structural neuroplasticity in the primary motor cortex (M1) of mice. In this study, we further investigated the long-term effects of CSDS exposure on M1, focusing on the interneuronal cell population. We used repeated CSDS to elicit effects across behavioral, endocrinological, and metabolic parameters in mice. Susceptible and resilient phenotypes were discriminated by symptom load and motor learning abilities were assessed on the rotarod. Structural changes in interneuronal circuits of M1 were studied by immunohistochemistry using parvalbumin (PV+) and somatostatin (SST+) markers. Stress-susceptible mice had a blunted stress hormone response and impaired motor learning skills. These mice presented reduced numbers of both interneuron populations in M1 with layer-dependent distribution, while alterations in cell size and immunoreactivity were found in both susceptible and resilient individuals. These results, together with our previous data, suggest that stress-induced cell loss and degeneration of the GABAergic interneuronal network of M1 could underlay impaired motor learning, due to their role in controlling the excitatory output and spine dynamics of principal neurons required for this task. Our study further highlights the importance of long-term outcomes of chronically stressed individuals which are translationally important due to the long timecourses of stress-induced neuropsychiatric disorders

    Online Mechanism Design for Vehicle-to-Grid Car Parks

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    Vehicle-to-grid (V2G) is a promising approach whereby electric vehicles (EVs) are used to store excess electricity supply (e.g., from renewable sources), which is sold back to the grid in times of scarcity. In this paper we consider the setting of a smart car park, where EVs come and go, and can be used for V2G while parked. We develop novel allocation and payment mechanisms which truthfully elicit the EV owners' preferences and constraints, including arrival, departure, required charge, as well as the costs of discharging due to loss of efficiency of the battery. The car park will schedule the charging and discharging of each EV, ensuring the constraints of the EVs are met, and taking into consideration predictions about future electricity prices. Optimally solving the global problem is intractable, and we present three novel heuristic online scheduling algorithms. We show that, under certain conditions, two of these satisfy monotonicity and are therefore truthful. We furthermore evaluate the algorithms using simulations, and we show that some of our algorithms benefit significantly from V2G, achieving positive benefit for the car park even when agents do not pay for using it

    Online Mechanism Design for Scheduling Non-Preemptive Jobs under Uncertain Supply and Demand

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    ABSTRACT We design new algorithms for the problem of allocating uncertain, flexible, and multi-unit demand online given uncertain supply, in order to maximise social welfare. The algorithms can be seen as extensions of the expectation and consensus algorithms from the domain of online scheduling. The problem is especially relevant to the future smart grid, where uncertain output from renewable generators and conventional supply need to be integrated and matched to flexible, non-preemptive demand. To deal with uncertain supply and demand, the algorithms generate multiple scenarios which can then be solved offline. Furthermore, we use a novel method of reweighting the scenarios based on their likelihood whenever new information about supply becomes available. An additional improvement allows the selection of multiple non-preemptive jobs at the same time. Finally, our main contribution is a novel online mechanism based on these extensions, where it is in the agents&apos; best interest to truthfully reveal their preferences. The experimental evaluation of the extended algorithms and different variants of the mechanism show that both achieve more than 85% of the offline optimal economic efficiency. Importantly, the mechanism yields comparable efficiency, while, in contrast to the algorithms, it allows for strategic agents
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