Horizontal Mergers of Online Firms: Structural Estimation and Competitive Effects

This paper (1) presents a general model of online price competition, (2) shows how to structurally estimate the underlying parameters of the model when the number of competing firms is unknown or in dispute, (3) estimates these parameters based on UK data for personal digital assistants, and (4) uses these estimates to simulate the competitive effects of horizontal mergers. Our results suggest that competitive effects in this online market are more closely aligned with the simple homogeneous product Bertrand model than might be expected given the observed price dispersion and number of firms. Our estimates indicate that so long as two firms remain in the market post merger, the average transaction price is roughly unaffected by horizontal mergers. However, there are potential distributional effects; our estimates indicate that a three-to-two merger raises the average transaction price paid by price sensitive "shoppers" by 2.88 percent, while lowering the average transaction price paid by consumers "loyal" to a particular firm by 1.37 percent.

Astrocytic LRP1 mediates brain Aβ clearance and impacts amyloid deposition

Accumulation and deposition of amyloid-β (Aβ) in the brain represent an early and perhaps necessary step in the pathogenesis of Alzheimer's disease (AD). Aβ accumulation leads to the formation of Aβ aggregates, which may directly and indirectly lead to eventual neurodegeneration. While Aβ production is accelerated in many familial forms of early-onset AD, increasing evidence indicates that impaired clearance of Aβ is more evident in late-onset AD. To uncover the mechanisms underlying impaired Aβ clearance in AD, we examined the role of low-density lipoprotein receptor-related protein 1 (LRP1) in astrocytes. Although LRP1 has been shown to play critical roles in brain Aβ metabolism in neurons and vascular mural cells, its role in astrocytes, the most abundant cell type in the brain responsible for maintaining neuronal homeostasis, remains unclear. Here, we show that astrocytic LRP1 plays a critical role in brain Aβ clearance. LRP1 knockdown in primary astrocytes resulted in decreased cellular Aβ uptake and degradation. In addition, silencing of LRP1 in astrocytes led to downregulation of several major Aβ-degrading enzymes, including matrix metalloproteases MMP2, MMP9, and insulin-degrading enzyme. More important, conditional knock-out of theLrp1gene in astrocytes in the background of APP/PS1 mice impaired brain Aβ clearance, exacerbated Aβ accumulation, and accelerated amyloid plaque deposition without affecting its production. Together, our results demonstrate that astrocytic LRP1 plays an important role in Aβ metabolism and that restoring LRP1 expression and function in the brain could be an effective strategy to facilitate Aβ clearance and counter amyloid pathology in AD.SIGNIFICANCE STATEMENTAstrocytes represent a major cell type regulating brain homeostasis; however, their roles in brain clearance of amyloid-β (Aβ) and underlying mechanism are not clear. In this study, we used both cellular models and conditional knock-out mouse models to address the role of a critical Aβ receptor, the low-density lipoprotein receptor-related protein 1 (LRP1) in astrocytes. We found that LRP1 in astrocytes plays a critical role in brain Aβ clearance by modulating several Aβ-degrading enzymes and cellular degradation pathways. Our results establish a critical role of astrocytic LRP1 in brain Aβ clearance and shed light on specific Aβ clearance pathways that may help to establish new targets for AD prevention and therapy.</jats:p

Controlled epitaxial graphene growth within amorphous carbon corrals

Structured growth of high quality graphene is necessary for technological development of carbon based electronics. Specifically, control of the bunching and placement of surface steps under epitaxial graphene on SiC is an important consideration for graphene device production. We demonstrate lithographically patterned evaporated amorphous carbon corrals as a method to pin SiC surface steps. Evaporated amorphous carbon is an ideal step-flow barrier on SiC due to its chemical compatibility with graphene growth and its structural stability at high temperatures, as well as its patternability. The amorphous carbon is deposited in vacuum on SiC prior to graphene growth. In the graphene furnace at temperatures above 1200$^\circ$C, mobile SiC steps accumulate at these amorphous carbon barriers, forming an aligned step free region for graphene growth at temperatures above 1330$^\circ$C. AFM imaging and Raman spectroscopy support the formation of quality step-free graphene sheets grown on SiC with the step morphology aligned to the carbon grid

Proteomic analyses reveal misregulation of LIN28 expression and delayed timing of glial differentiation in human iPS cells with MECP2 loss-of-function.

Rett syndrome (RTT) is a pervasive developmental disorder caused by mutations in MECP2. Complete loss of MECP2 function in males causes congenital encephalopathy, neurodevelopmental arrest, and early lethality. Induced pluripotent stem cell (iPSC) lines from male patients harboring mutations in MECP2, along with control lines from their unaffected fathers, give us an opportunity to identify some of the earliest cellular and molecular changes associated with MECP2 loss-of-function (LOF). We differentiated iPSC-derived neural progenitor cells (NPCs) using retinoic acid (RA) and found that astrocyte differentiation is perturbed in iPSC lines derived from two different patients. Using highly stringent quantitative proteomic analyses, we found that LIN28, a gene important for cell fate regulation and developmental timing, is upregulated in mutant NPCs compared to WT controls. Overexpression of LIN28 protein in control NPCs suppressed astrocyte differentiation and reduced neuronal synapse density, whereas downregulation of LIN28 expression in mutant NPCs partially rescued this synaptic deficiency. These results indicate that the pathophysiology of RTT may be caused in part by misregulation of developmental timing in neural progenitors, and the subsequent consequences of this disruption on neuronal and glial differentiation

Chebyshev polynomial filtered subspace iteration in the Discontinuous Galerkin method for large-scale electronic structure calculations

The Discontinuous Galerkin (DG) electronic structure method employs an adaptive local basis (ALB) set to solve the Kohn-Sham equations of density functional theory (DFT) in a discontinuous Galerkin framework. The adaptive local basis is generated on-the-fly to capture the local material physics, and can systematically attain chemical accuracy with only a few tens of degrees of freedom per atom. A central issue for large-scale calculations, however, is the computation of the electron density (and subsequently, ground state properties) from the discretized Hamiltonian in an efficient and scalable manner. We show in this work how Chebyshev polynomial filtered subspace iteration (CheFSI) can be used to address this issue and push the envelope in large-scale materials simulations in a discontinuous Galerkin framework. We describe how the subspace filtering steps can be performed in an efficient and scalable manner using a two-dimensional parallelization scheme, thanks to the orthogonality of the DG basis set and block-sparse structure of the DG Hamiltonian matrix. The on-the-fly nature of the ALBs requires additional care in carrying out the subspace iterations. We demonstrate the parallel scalability of the DG-CheFSI approach in calculations of large-scale two-dimensional graphene sheets and bulk three-dimensional lithium-ion electrolyte systems. Employing 55,296 computational cores, the time per self-consistent field iteration for a sample of the bulk 3D electrolyte containing 8,586 atoms is 90 seconds, and the time for a graphene sheet containing 11,520 atoms is 75 seconds.Comment: Submitted to The Journal of Chemical Physic

Identification and Estimation of Online Price Competition With an Unknown Number of Firms

This paper considers identification and estimation of a general model for online price competition. We show that when the number of competing firms is unknown the underlying parameters of the model can still be identified and estimated employing recently developed results on measurement errors. We illustrate our methodology using UK data for personal digital assistants and employ the estimates to simulate competitive effects. Our results reveal that heightened competition has differential effects on the prices paid by different consumer segments

Dopamine promotes instrumental motivation, but reduces reward-related vigour.

We can be motivated when reward depends on performance, or merely by the prospect of a guaranteed reward. Performance-dependent (contingent) reward is instrumental, relying on an internal action-outcome model, whereas motivation by guaranteed reward may minimise opportunity cost in reward-rich environments. Competing theories propose that each type of motivation should be dependent on dopaminergic activity. We contrasted these two types of motivation with a rewarded saccade task, in patients with Parkinson's disease (PD). When PD patients were ON dopamine, they had greater response vigour (peak saccadic velocity residuals) for contingent rewards, whereas when PD patients were OFF medication, they had greater vigour for guaranteed rewards. These results support the view that reward expectation and contingency drive distinct motivational processes, and can be dissociated by manipulating dopaminergic activity. We posit that dopamine promotes goal-directed motivation, but dampens reward-driven vigour, contradictory to the prediction that increased tonic dopamine amplifies reward expectation