The Demand for Green Cards

I estimate the demand curve for Legal Permanent Residence in the US, and the government revenues and migrant welfare gains that could be achieved by replacing all or parts of the current immigration system with a Uniform Price Auction. Willingness to pay and welfare are based on the net present value of the difference in income that people earn in the US compared to other countries. I obtain an equilibrium annual demand curve by modeling the dynamics of how pent-up demand for residence responds to the introduction of an auction for residence permits. I separately estimate the demand curves for each major source of demand for residence in the US, and combine them to find the total. I find that there are currently large inefficiencies in border controls, the Diversity Visa Lottery, and Removals of Noncriminal Aliens. A revenue-maximixing auction of LPR to the the population of workers who have historically entered illegally would generate $10.2 billion in revenues and$8.5 billion in gains to the migrants. Changing the Diversity Visa Lottery to an auction, while keeping the number of visas the same, would give the government $5 billion in revenue annually, while increasing migrant welfare by$2.3 billion. Expanding the annual sales to the revenue-maximizing quantity generates $6.8 billion in revenue, and$8.5 billion in gains for the migrants. Giving non-criminal aliens the chance to purchase LPR for $30,000 before being deported would generate$2.8 billion in revenues and $6.8 billion in gains for the migrants. If the government auctioned all green cards, at the current level of one million naturalizations per year, the price would be$35,000 and revenues would be $33 billion after processing costs. Migrant welfare would increase by$10.6 billion. The profit-maximizing quantity would be 845,000, resulting in a price of $42,000 and revenues of$34 billion. This extra billion in revenue would be obtained at a cost of $6.7 billion in lost migrant welfare

Mensch und Maschine im Spielraum: technische Praxis und ästhetische Erfahrung

Der Beitrag beschäftigt sich mit dem Verhältnis der Sphären des Technischen und des Ästhetischen. Technik und Ästhetik stehen sich spätestens seit der Industrialisierung diametral gegenüber, nicht weniger als Arbeit und Spiel. Eine vom Dualismus geprägte Denkweise stellt das Reich der Freiheit dem Reich der Notwendigkeit gegenüber, separiert eine ästhetische Welt von der technischen. Arbeit wird zur Technik gezählt. In deren Zweckorientierung und Determiniertheit sieht man - konträr zur Sphäre des Ästhetischen - in der ästhetischen Erziehung bzw. Bildung und darüber hinaus immer wieder die kreative Eigentätigkeit und damit die Freiheit des Menschen gefährdet - unabhängig davon, dass durch Technik der Mensch sich lebenserleichternde Maschinen und technische Systeme schafft. So werden schließlich die Künste und Spiel einerseits, Arbeit und Technik andererseits als sich prinzipiell ausschließende Tätigkeiten bewertet. Diese Ansicht gilt es jedoch zu überwinden, indem Mensch und Maschine in so genannten Spielräumen verortet werden. Die Ausführungen gliedern sich inhaltlich in zwei Abschnitte: In einem ersten Schritt wird das Verhältnis von Mensch und Maschine bzw. zwischen Spiel und Technik auf theoretischer Ebene erörtert. Dabei finden medien- und ingenieurswissenschaftliche (F. Rötzer), (technik-)soziologische (M. Weber, J. Baudrillard) und philosophische (H. Marcuse, G. Vattimo) Positionen Erwähnung. Im Anschluss folgt die Beschreibung von zwei Projekten der Gestaltung von Arbeit und Technik, in denen ein wechselseitiges Zusammenspiel zwischen Ästhetik und Technik angestrebt wird. So stellt die ästhetische Erziehung Spielräume in Form von Möglichkeitsräumen bereit. Sie erlauben ein Handeln auf Probe, was nichts anderes heißt als eine Praxis auf Gegenseitigkeit. Die erste Fallstudie umfasst die Computersimulation eines Containerhafens (1995). Bei dem zweiten Projekt handelt es sich um die Umsetzung eines 'Theaters der Maschinen' (1998-2000)

Long‐lived Snell dwarf mice display increased proteostatic mechanisms that are not dependent on decreased mTORC1 activity

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111144/1/acel12329.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/111144/2/acel12329-sup-0001-SuppInfo.pd

Deep Learning from Dual-Energy Information for Whole-Heart Segmentation in Dual-Energy and Single-Energy Non-Contrast-Enhanced Cardiac CT

Deep learning-based whole-heart segmentation in coronary CT angiography (CCTA) allows the extraction of quantitative imaging measures for cardiovascular risk prediction. Automatic extraction of these measures in patients undergoing only non-contrast-enhanced CT (NCCT) scanning would be valuable. In this work, we leverage information provided by a dual-layer detector CT scanner to obtain a reference standard in virtual non-contrast (VNC) CT images mimicking NCCT images, and train a 3D convolutional neural network (CNN) for the segmentation of VNC as well as NCCT images. Contrast-enhanced acquisitions on a dual-layer detector CT scanner were reconstructed into a CCTA and a perfectly aligned VNC image. In each CCTA image, manual reference segmentations of the left ventricular (LV) myocardium, LV cavity, right ventricle, left atrium, right atrium, ascending aorta, and pulmonary artery trunk were obtained and propagated to the corresponding VNC image. These VNC images and reference segmentations were used to train 3D CNNs for automatic segmentation in either VNC images or NCCT images. Automatic segmentations in VNC images showed good agreement with reference segmentations, with an average Dice similarity coefficient of 0.897 \pm 0.034 and an average symmetric surface distance of 1.42 \pm 0.45 mm. Volume differences [95% confidence interval] between automatic NCCT and reference CCTA segmentations were -19 [-67; 30] mL for LV myocardium, -25 [-78; 29] mL for LV cavity, -29 [-73; 14] mL for right ventricle, -20 [-62; 21] mL for left atrium, and -19 [-73; 34] mL for right atrium, respectively. In 214 (74%) NCCT images from an independent multi-vendor multi-center set, two observers agreed that the automatic segmentation was mostly accurate or better. This method might enable quantification of additional cardiac measures from NCCT images for improved cardiovascular risk prediction

Unimodality Problems in Ehrhart Theory

Ehrhart theory is the study of sequences recording the number of integer points in non-negative integral dilates of rational polytopes. For a given lattice polytope, this sequence is encoded in a finite vector called the Ehrhart $h^*$-vector. Ehrhart $h^*$-vectors have connections to many areas of mathematics, including commutative algebra and enumerative combinatorics. In this survey we discuss what is known about unimodality for Ehrhart $h^*$-vectors and highlight open questions and problems.Comment: Published in Recent Trends in Combinatorics, Beveridge, A., et al. (eds), Springer, 2016, pp 687-711, doi 10.1007/978-3-319-24298-9_27. This version updated October 2017 to correct an error in the original versio

Development of an invasively monitored porcine model of acetaminophen-induced acute liver failure

Background: The development of effective therapies for acute liver failure (ALF) is limited by our knowledge of the pathophysiology of this condition, and the lack of suitable large animal models of acetaminophen toxicity. Our aim was to develop a reproducible invasively-monitored porcine model of acetaminophen-induced ALF. Method: 35kg pigs were maintained under general anaesthesia and invasively monitored. Control pigs received a saline infusion, whereas ALF pigs received acetaminophen intravenously for 12 hours to maintain blood concentrations between 200-300 mg/l. Animals surviving 28 hours were euthanased. Results: Cytochrome p450 levels in phenobarbital pre-treated animals were significantly higher than non pre-treated animals (300 vs 100 pmol/mg protein). Control pigs (n=4) survived 28-hour anaesthesia without incident. Of nine pigs that received acetaminophen, four survived 20 hours and two survived 28 hours. Injured animals developed hypotension (mean arterial pressure; 40.8+/-5.9 vs 59+/-2.0 mmHg), increased cardiac output (7.26+/-1.86 vs 3.30+/-0.40 l/min) and decreased systemic vascular resistance (8.48+/-2.75 vs 16.2+/-1.76 mPa/s/m3). Dyspnoea developed as liver injury progressed and the increased pulmonary vascular resistance (636+/-95 vs 301+/-26.9 mPa/s/m3) observed may reflect the development of respiratory distress syndrome. Liver damage was confirmed by deterioration in pH (7.23+/-0.05 vs 7.45+/-0.02) and prothrombin time (36+/-2 vs 8.9+/-0.3 seconds) compared with controls. Factor V and VII levels were reduced to 9.3 and 15.5% of starting values in injured animals. A marked increase in serum AST (471.5+/-210 vs 42+/-8.14) coincided with a marked reduction in serum albumin (11.5+/-1.71 vs 25+/-1 g/dL) in injured animals. Animals displayed evidence of renal impairment; mean creatinine levels 280.2+/-36.5 vs 131.6+/-9.33 mumol/l. Liver histology revealed evidence of severe centrilobular necrosis with coagulative necrosis. Marked renal tubular necrosis was also seen. Methaemoglobin levels did not rise >5%. Intracranial hypertension was not seen (ICP monitoring), but there was biochemical evidence of encephalopathy by the reduction of Fischer's ratio from 5.6 +/- 1.1 to 0.45 +/- 0.06. Conclusion: We have developed a reproducible large animal model of acetaminophen-induced liver failure, which allows in-depth investigation of the pathophysiological basis of this condition. Furthermore, this represents an important large animal model for testing artificial liver support systems

LGP2 plays a critical role in sensitizing mda-5 to activation by double-stranded RNA.

The DExD/H box RNA helicases retinoic acid-inducible gene-I (RIG-I) and melanoma differentiation associated gene-5 (mda-5) sense viral RNA in the cytoplasm of infected cells and activate signal transduction pathways that trigger the production of type I interferons (IFNs). Laboratory of genetics and physiology 2 (LGP2) is thought to influence IFN production by regulating the activity of RIG-I and mda-5, although its mechanism of action is not known and its function is controversial. Here we show that expression of LGP2 potentiates IFN induction by polyinosinic-polycytidylic acid [poly(I:C)], commonly used as a synthetic mimic of viral dsRNA, and that this is particularly significant at limited levels of the inducer. The observed enhancement is mediated through co-operation with mda-5, which depends upon LGP2 for maximal activation in response to poly(I:C). This co-operation is dependent upon dsRNA binding by LGP2, and the presence of helicase domain IV, both of which are required for LGP2 to interact with mda-5. In contrast, although RIG-I can also be activated by poly(I:C), LGP2 does not have the ability to enhance IFN induction by RIG-I, and instead acts as an inhibitor of RIG-I-dependent poly(I:C) signaling. Thus the level of LGP2 expression is a critical factor in determining the cellular sensitivity to induction by dsRNA, and this may be important for rapid activation of the IFN response at early times post-infection when the levels of inducer are low

Achieving Sustainable Development Goals from a Water Perspective

Efforts to meet human water needs only at local scales may cause negative environmental externality and stress on the water system at regional and global scales. Hence, assessing SDG targets requires a broad and in-depth knowledge of the global to local dynamics of water availability and use. Further, Interconnection and trade-offs between different SDG targets may lead to sub-optimal or even adverse outcome if the set of actions are not properly pre-designed considering such interlinkages. Thus scientific research and evidence have a role to play in facilitating the implementation of SDGs through assessments and policy engagement from global to local scales. The paper addresses some of these challenges related to implementation and monitoring the targets of the Sustainable Development Goals from a water perspective, based on the key findings of a conference organised in 2015 with the focus on three essential aspects of SDGs- indicators, interlinkages and implementation. The paper discusses that indicators should not be too simple but ultimately deliver sustainability measures. The paper finds that remote sensing and earth observation technologies can play a key role in supporting the monitoring of water targets. It also recognises that implementing SDGs is a societal process of development, and there is need to link how SDGs relate to public benefits and communicate this to the broader public

Beyond ectomycorrhizal bipartite networks: projected networks demonstrate contrasted patterns between early- and late-successional plants in Corsica

International audienceThe ectomycorrhizal (ECM) symbiosis connects mutualistic plants and fungal species into bipartite networks. While links between one focal ECM plant and its fungal symbionts have been widely documented, systemic views of ECM networks are lacking, in particular, concerning the ability of fungal species to mediate indirect ecological interactions between ECM plant species (projected-ECM networks). We assembled a large dataset of plant–fungi associations at the species level and at the scale of Corsica using molecular data and unambiguously host-assigned records to: (i) examine the correlation between the number of fungal symbionts of a plant species and the average specialization of these fungal species, (ii) explore the structure of the plant–plant projected network and (iii) compare plant association patterns in regard to their position along the ecological succession. Our analysis reveals no trade-off between specialization of plants and specialization of their partners and a saturation of the plant projected network. Moreover, there is a significantly lower-than-expected sharing of partners between early- and late-successional plant species, with fewer fungal partners for early-successional ones and similar average specialization of symbionts of early- and late-successional plants. Our work paves the way for ecological readings of Mediterranean landscapes that include the astonishing diversity of below-ground interactions