Welfare and Revenue Guarantees for Competitive Bundling Equilibrium

We study equilibria of markets with $m$ heterogeneous indivisible goods and $n$ consumers with combinatorial preferences. It is well known that a competitive equilibrium is not guaranteed to exist when valuations are not gross substitutes. Given the widespread use of bundling in real-life markets, we study its role as a stabilizing and coordinating device by considering the notion of \emph{competitive bundling equilibrium}: a competitive equilibrium over the market induced by partitioning the goods for sale into fixed bundles. Compared to other equilibrium concepts involving bundles, this notion has the advantage of simulatneous succinctness ($O(m)$ prices) and market clearance. Our first set of results concern welfare guarantees. We show that in markets where consumers care only about the number of goods they receive (known as multi-unit or homogeneous markets), even in the presence of complementarities, there always exists a competitive bundling equilibrium that guarantees a logarithmic fraction of the optimal welfare, and this guarantee is tight. We also establish non-trivial welfare guarantees for general markets, two-consumer markets, and markets where the consumer valuations are additive up to a fixed budget (budget-additive). Our second set of results concern revenue guarantees. Motivated by the fact that the revenue extracted in a standard competitive equilibrium may be zero (even with simple unit-demand consumers), we show that for natural subclasses of gross substitutes valuations, there always exists a competitive bundling equilibrium that extracts a logarithmic fraction of the optimal welfare, and this guarantee is tight. The notion of competitive bundling equilibrium can thus be useful even in markets which possess a standard competitive equilibrium

Comparison of physics-based, semi-empirical and neural network-based models for model-based combustion control in a 3.0 L diesel engine

A comparison of four different control-oriented models has been carried out in this paper for the simulation of the main combustion metrics in diesel engines, i.e., combustion phasing, peak firing pressure, and brake mean effective pressure. The aim of the investigation has been to understand the potential of each approach in view of their implementation in the engine control unit (ECU) for onboard combustion control applications. The four developed control-oriented models, namely the baseline physics-based model, the artificial neural network (ANN) physics-based model, the semi-empirical model, and direct ANN model, have been assessed and compared under steady-state conditions and over the Worldwide Harmonized Heavy-duty Transient Cycle (WHTC) for a Euro VI FPT F1C 3.0 L diesel engine. Moreover, a new procedure has been introduced for the selection of the input parameters. The direct ANN model has shown the best accuracy in the estimation of the combustion metrics under both steady-state/transient operating conditions, since the root mean square errors are of the order of 0.25/1.1 deg, 0.85/9.6 bar, and 0.071/0.7 bar for combustion phasing, peak firing pressure, and brake mean effective pressure, respectively. Moreover, it requires the least computational time, that is, less than 50 µs when the model is run on a rapid prototyping device. Therefore, it can be considered the best candidate for model-based combustion control applications

Intraneuronal Aβ detection in 5xFAD mice by a new Aβ-specific antibody

<p>Abstract</p> <p>Background</p> <p>The form(s) of amyloid-β peptide (Aβ) associated with the pathology characteristic of Alzheimer's disease (AD) remains unclear. In particular, the neurotoxicity of intraneuronal Aβ accumulation is an issue of considerable controversy; even the existence of Aβ deposits within neurons has recently been challenged by Winton and co-workers. These authors purport that it is actually intraneuronal APP that is being detected by antibodies thought to be specific for Aβ. To further address this issue, an anti-Aβ antibody was developed (MOAB-2) that specifically detects Aβ, but not APP. This antibody allows for the further evaluation of the early accumulation of intraneuronal Aβ in transgenic mice with increased levels of human Aβ in 5xFAD and 3xTg mice.</p> <p>Results</p> <p>MOAB-2 (mouse IgG_2b) is a pan-specific, high-titer antibody to Aβ residues 1-4 as demonstrated by biochemical and immunohistochemical analyses (IHC), particularly compared to 6E10 (a commonly used commercial antibody to Aβ residues 3-8). MOAB-2 did not detect APP or APP-CTFs in cell culture media/lysates (HEK-APP_Sweor HEK-APP_Swe/BACE1) or in brain homogenates from transgenic mice expressing 5 familial AD (FAD) mutation (5xFAD mice). Using IHC on 5xFAD brain tissue, MOAB-2 immunoreactivity co-localized with C-terminal antibodies specific for Aβ40 and Aβ42. MOAB-2 did not co-localize with either N- or C-terminal antibodies to APP. In addition, no MOAB-2-immunreactivity was observed in the brains of 5xFAD/BACE^-/-mice, although significant amounts of APP were detected by N- and C-terminal antibodies to APP, as well as by 6E10. In both 5xFAD and 3xTg mouse brain tissue, MOAB-2 co-localized with cathepsin-D, a marker for acidic organelles, further evidence for intraneuronal Aβ, distinct from Aβ associated with the cell membrane. MOAB-2 demonstrated strong intraneuronal and extra-cellular immunoreactivity in 5xFAD and 3xTg mouse brain tissues.</p> <p>Conclusions</p> <p>Both intraneuronal Aβ accumulation and extracellular Aβ deposition was demonstrated in 5xFAD mice and 3xTg mice with MOAB-2, an antibody that will help differentiate intracellular Aβ from APP. However, further investigation is required to determine whether a molecular mechanism links the presence of intraneuronal Aβ with neurotoxicity. As well, understanding the relevance of these observations to human AD patients is critical.</p

Observation of Top Quark Production in Proton-Nucleus Collisions

Peer reviewe

Application of Technological Control Measures on Vehicle Pollution: A Cost-Benefit Analysis in China

For the past two decades, China has experienced strong, continuous economic growth. At the same time, the number of motor vehicles in China has rapidly increased. As a direct result of such a phenomenon, China has been registering significant increases in air pollution. In spite of recent advances in air pollution control, it remains a serious problem for Chinas major cities, and constitutes an important issue in the agenda of its policy makers. The object of this paper is to explore the use of cost-benefit analysis (CBA) to evaluate and rank alternative policy scenarios regarding the control of air pollution emitted by motor vehicles. The empirical analysis carried out relates specifically to the Chinese context, over a twenty year period, from 2001 to 2020, and focuses on emission changes of the following three principal pollutants: CO, HC and NOx