Labor Market Density and Increasing Returns to Scale: How Strong is the Evidence?

Models of economic geography posit that the density of economic activity has two e¤ects that oppose each other in equilibrium: decreasing returns to productive activities due to congestion e¤ects and increasing returns that result from information spillovers and local demand externalities. In an in�uential paper, Ciccone and Hall (1996) looked at the effect of county level labor market concentration on per-worker Gross State Product in a cross section of US States, and observed that on net, the increasing returns/agglomeration effect dominates. We extend their analysis and re-examine the relationship between density and productivity across industries and over both states and time. Through careful identi�cation of the source and nature of productivity shocks, we show that the evidence for agglomeration effects is indeed quite robust, even within industries, providing evidence for the presence of Marshallian externalities. As for the balance of agglomeration and congestion e¤ects found in previous literature, what we call �net increasing returns to scale", the evidence is much weaker.

Unsupervised Bilingual POS Tagging with Markov Random Fields

In this paper, we give a treatment to the problem of bilingual part-of-speech induction with parallel data. We demonstrate that naïve optimization of log-likelihood with joint MRFs suffers from a severe problem of local maxima, and suggest an alternative – using contrastive estimation for estimation of the parameters. Our experiments show that estimating the parameters this way, using overlapping features with joint MRFs performs better than previous work on the 1984 dataset.

A Dynamin-3 Spliced Variant Modulates the Actin/Cortactin-Dependent Morphogenesis of Dendritic Spines

Immature dendrites extend many actin-rich filopodial structures that can be replaced by synapse-containing dendritic spines as the neuron matures. The large GTPase dynamin-3 (Dyn3) is a component of the postsynapse in hippocampal neurons but its function is undefined. Here, we demonstrate that a specific Dyn3 variant (Dyn3baa) promotes the formation of immature dendritic filopodia in cultured neurons. This effect is dependent upon Dyn3 GTPase activity and a direct interaction with the F-actin-binding protein cortactin. Consistent with these findings, Dyn3baa binds to cortactin with a 200% higher affinity than Dyn3aaa, a near identical isoform that does not induce dendritic filopodia when expressed in cultured neurons. Finally, levels of Dyn3baa-encoding mRNA are tightly regulated during neuronal maturation and are markedly upregulated during synaptogenesis. Together, these findings provide the first evidence that an enhanced interaction between a specific Dyn3 splice variant and cortactin modulate actin-membrane dynamics in developing neurons to regulate the morphogenesis of dendritic spines. Supplementary material available online at http://jcs.biologists.org/cgi/content/full/118/6/1279/DC

Dynamic Social Balance and Convergent Appraisals via Homophily and Influence Mechanisms

Social balance theory describes allowable and forbidden configurations of the topologies of signed directed social appraisal networks. In this paper, we propose two discrete-time dynamical systems that explain how an appraisal network \textcolor{blue}{converges to} social balance from an initially unbalanced configuration. These two models are based on two different socio-psychological mechanisms respectively: the homophily mechanism and the influence mechanism. Our main theoretical contribution is a comprehensive analysis for both models in three steps. First, we establish the well-posedness and bounded evolution of the interpersonal appraisals. Second, we fully characterize the set of equilibrium points; for both models, each equilibrium network is composed by an arbitrary number of complete subgraphs satisfying structural balance. Third, we establish the equivalence among three distinct properties: non-vanishing appraisals, convergence to all-to-all appraisal networks, and finite-time achievement of social balance. In addition to theoretical analysis, Monte Carlo validations illustrates how the non-vanishing appraisal condition holds for generic initial conditions in both models. Moreover, numerical comparison between the two models indicate that the homophily-based model might be a more universal explanation for the formation of social balance. Finally, adopting the homophily-based model, we present numerical results on the mediation and globalization of local conflicts, the competition for allies, and the asymptotic formation of a single versus two factions

Estimation of Zero-Inflated Population Mean: A Bootstrapping Approach

A mixture model was adopted from the maximum pseudo-likelihood approach under complex sampling designs to estimate the mean of zero-inflated population. To overcome the complexity and assumptions of asymptotic distribution, the maximum pseudo-likelihood function was used, but a bootstrapping procedure was proposed as an alternative. Bootstrap confidence intervals consistently capture the true means of zero-inflated populations of the simulation studies

Optical depth to reionization from perturbative 21cm clustering

The optical depth $\tau$ is the least well determined parameter in the standard model of cosmology, and one whose precise value is important for both understanding reionization and for inferring fundamental physics from cosmological measurements. We forecast how well future epoch of reionization experiments could constraint $\tau$ using a symmetries-based bias expansion that highlights the special role played by anisotropies in the power spectrum on large scales. Given a parametric model for the ionization evolution inspired by the physical behavior of more detailed reionization simulations, we find that future 21cm experiments could place tight constraints on the timing and duration of reionization and hence constraints on $\tau$ that are competitive with proposed, space-based CMB missions provided they can measure $k\approx 0.1\,h\,\text{Mpc}^{-1}$ with a clean foreground wedge across redshifts spanning the most active periods of reionization, corresponding to ionization fractions $0.2 \lesssim x \lesssim 0.8$. Significantly improving upon existing CMB-based measurements with next-generation 21cm surveys would require substantially longer observations ($\sim5$ years) than standard $\mathcal{O}(1000 \,\,\text{hour})$ integration times. Precise measurements of smaller scales will not improve constraints on $\tau$ until a better understanding of the astrophysics of reionization is achieved. In the presence of noise and foregrounds even future 21cm experiments will struggle to constrain $\tau$ if the ionization evolution deviates significantly from simple parametric forms.Comment: published in JCA

Multiple mechanisms for processing reward uncertainty in the primate basal forebrain

UNLABELLED: The ability to use information about the uncertainty of future outcomes is critical for adaptive behavior in an uncertain world. We show that the basal forebrain (BF) contains at least two distinct neural-coding strategies to support this capacity. The dorsal-lateral BF, including the ventral pallidum (VP), contains reward-sensitive neurons, some of which are selectively suppressed by uncertain-reward predictions (U(-)). In contrast, the medial BF (mBF) contains reward-sensitive neurons, some of which are selectively enhanced (U(+)) by uncertain-reward predictions. In a two-alternative choice-task, U(-) neurons were selectively suppressed while monkeys chose uncertain options over certain options. During the same choice-epoch, U(+) neurons signaled the subjective reward value of the choice options. Additionally, after the choice was reported, U(+) neurons signaled reward uncertainty until the choice outcome. We suggest that uncertainty-related suppression of VP may participate in the mediation of uncertainty-seeking actions, whereas uncertainty-related enhancement of the mBF may direct cognitive resources to monitor and learn from uncertain-outcomes. SIGNIFICANCE STATEMENT: To survive in an uncertain world, we must approach uncertainty and learn from it. Here we provide evidence for two mostly distinct mechanisms for processing uncertainty about rewards within different subregions of the primate basal forebrain (BF). We found that uncertainty suppressed the representation of certain (or safe) reward values by some neurons in the dorsal-lateral BF, in regions occupied by the ventral pallidum. This uncertainty-related suppression was evident as monkeys made risky choices. We also found that uncertainty-enhanced the activity of many medial BF neurons, most prominently after the monkeys\u27 choices were completed (as they awaited uncertain outcomes). Based on these findings, we propose that different subregions of the BF could support action and learning under uncertainty in distinct but complimentary manners

HID-1 controls formation of large dense core vesicles by influencing cargo sorting and trans-Golgi network acidification

Large dense core vesicles (LDCVs) mediate the regulated release of neuropeptides and peptide hormones. They form at the trans-Golgi network (TGN), where their soluble content aggregates to form a dense core, but the mechanisms controlling biogenesis are still not completely understood. Recent studies have implicated the peripheral membrane protein HID-1 in neuropeptide sorting and insulin secretion. Using CRISPR/Cas9, we generated HID-1 KO rat neuroendocrine cells, and we show that the absence of HID-1 results in specific defects in peptide hormone and monoamine storage and regulated secretion. Loss of HID-1 causes a reduction in the number of LDCVs and affects their morphology and biochemical properties, due to impaired cargo sorting and dense core formation. HID-1 KO cells also exhibit defects in TGN acidification together with mislocalization of the Golgi-enriched vacuolar H+-ATPase subunit isoform a2. We propose that HID-1 influences early steps in LDCV formation by controlling dense core formation at the TGN.</jats:p