The quality of life in England and Wales

Local amenities play an important role in determining where we choose to live and our overall quality of life. In many cases, however, amenities do not have prices and will therefore be underprovided by the market. In this paper, we use county level data for England and Wales to estimate implicit amenity prices and to calculate an index of quality of life for each county. Among our findings is a large negative price on air pollution. The range in quality of life across counties is estimated to be in excess of two thousand pounds per year. Keywords; quality of life index, amenities, hedonic prices JEL classification: I31, R1

The case of the missing productivity growth: or, does information technology explain why productivity accelerated in the United States but not the United Kingdom?

Solow's paradox has disappeared in the United States but remains alive and well in the United Kingdom. In particular, the U.K. experienced an information and communications technology (ICT) investment boom in the 1990s in parallel with the U.S., but measured total factor productivity has decelerated rather than accelerated in recent years. We ask whether ICT can explain the divergent TFP performance in the two countries. Stories of ICT as a 'general purpose technology' suggest that measured TFP should rise in ICT-using sectors (reflecting either unobserved accumulation of intangible organizational capital; spillovers; or both), but perhaps with long lags. Contemporaneously, investments in ICT may in fact be associated with lower TFP as resources are diverted to reorganization and learning. ; In both the U.S. and U.K., we find a strong correlation between ICT use and industry TFP growth. The U.S. results are consistent with GPT stories: the acceleration after the mid-1990s was broadbased-located primarily in ICT-using industries rather than ICT-producing industries. Furthermore, industry TFP growth is positively correlated with industry ICT capital growth in the 1980s and early 1990s. Indeed, as GPT stories would suggest, controlling for past ICT growth, industry TFP growth appears negatively correlated with increases in ICT usage in the late 1990s. A somewhat different picture emerges for the U.K. TFP growth does not appear correlated with lagged ICT investment. But TFP growth in the 1990s is strongly and positively associated with the growth of ICT capital services, while being strongly and negatively associated with the growth of ICT investment. If, as we argue, unmeasured investment in complementary capital is correlated with ICT investment, then this finding too is consistent with the GPT story. However, comparing the first and second halves of the 1990s, the net effect of ICT is positive, suggesting that ICT cannot explain the observed TFP slowdown. On the other hand, our results do suggest, albeit tentatively, that the U.K. could see an acceleration in TFP growth over the next decade.Information technology ; Labor productivity ; Productivity

The Case of the Missing Productivity Growth: Or, Does Information technology explain why productivity accelerated in the United States but not the United Kingdom?

We argue that unmeasured investments in intangible organizational capital—associated with the role of information and communications technology (ICT) as a ‘general purpose technology’—can explain the divergent U. S. and U. K. TFP performance after 1995. GPT stories suggest that measured TFP should rise in ICT-using sectors, perhaps with long lags. Contemporaneously, investments in ICT may in fact be associated with lower TFP as resources are diverted to reorganization and learning. In both the U. S. and U. K. , we find a strong correlation between ICT use and industry TFP growth. The U. S. results, in particular, are consistent with GPT stories: the TFP acceleration was located primarily in ICT-using industries and is positively correlated with industry ICT capital growth from the 1980s and early 1990s. Indeed, as GPT stories suggest, controlling for past ICT growth, industry TFP growth appears negatively correlated with increases in ICT capital services in the late 1990s. A somewhat different picture emerges for the U. K. TFP growth does not appear correlated with lagged ICT capital growth. But TFP growth in the late 1990s is strongly and positively associated with the growth of ICT capital services, while being strongly and negatively associated with the growth of ICT investment.

The effect of scaffold physical properties on endothelial cell function

Thesis: Ph. D. in Materials Science and Medical Engineering, Harvard-MIT Program in Health Sciences and Technology, February 2010.Cataloged from PDF version of thesis.Includes bibliographical references (pages 135-139).Endothelial cells (EC) are ubiquitous - as vascular epithelial cells they line the inner surface of all vessels and are the contact surface with flowing blood. Macrovascular EC are the first line barrier between flowing blood and mural structures. The microvasculature includes EC-lined vessels that contact virtually every cell in the body. These EC are potent bioregulatory cells, modulating thrombosis, inflammation and control over mural smooth muscle cells and vascular health. The biochemical roles of EC can be retained when cells are embedded within three-dimensional matrices without recapitulation of the full vessel architecture. Within these matrices, surface and structural properties impose a set of forces on the embedded EC. Indeed, substrata pore size and modulus have profound effects on phenotype and function of a range of cell types. In the first part of this work, we examined the effect of pore size, matrix relative density and modulus on matrix-embedded EC growth and secretion and found a greater biological dependence on modulus than pore size or density. In the second part of this work, we examined the effect of isolated changes in modulus on BC growth, secretion of growth regulators, and modulation of smooth muscle cell growth. EC growth is maximal at intermediate moduli over a range from 50 Pa- 1500 Pa. Secretion of heparan sulfate proteoglycans (HSPGs), which inhibit smooth muscle cell growth, is maximal at low moduli and flat at high moduli. Secretion of growth factors such as FGF2 and PDGF-BB were also modulus responsive. Inhibition of smooth muscle cell growth rose as modulus decreased from 510 Pa to 50 Pa and was the result of a balance between increased HSPG secretion and reduced secretion of vasoactive growth factors. Changes in endothelial function correlated with extracellular matrix gene and integrin aP 3 and c41 expression. Changes in the forces experienced by the cell - a change in substrate modulus - cause the cell to alter its ECM and integrin expression in an effort to return the force balance to normal, leading to downstream effects on cell function. While growth stimulatory function largely conserved, growth inhibitory function was altered to a much larger degree. In the final part of this work, we examined the effect of scaffold modulus on EC response to inflammatory stimuli, and attempted to correlate it to changes in smooth muscle cell regulation and integrin expression. While cytokine secretion was independent of modulus, surface expression of ICAM- 1 and VCAM-1, and induction of CD4' T cell proliferation followed a similar pattern to smooth muscle cell inhibition, suggesting that similar mechanisms may be involved in their regulation by substrate modulus. Alteration of scaffold modulus has a profound impact on EC function including growth regulation and inflammatory response. The model offered in this thesis - wherein EC attempt to neutralize changes in environmental force balance by altering ECM and integrin expression, leading to changes in downstream function - offers insight into how environmental changes effect functional changes in ECs.by Sylaja Murikipudi.Ph. D. in Materials Science and Medical Engineerin

Indian Manufacturing Industry: Elephant or Tiger? New Evidence on the Asian Miracle

We estimate the rate of total factor productivity growth in Indian manufacturing industry for the period 1973-1992, and compare the results to those obtained by Young for the East Asian Tigers. We then interpret our results in light of Krugman's hypothesis that, because the Asian Miracle was driven by capital formation under diminishing marginal returns, it is not sustainable. We suggest a reinterpretation of the sustainability problem that recognizes the true role of TFP as a motive force in output growth. Past studies have compared the TFP residual to the growth rate of output and used this ratio as a measure of the importance of TFP as a source of growth. We argue that this is an erroneous way of assessing the role of TFP, because it ignores the additional capital formation made possible by an increase in productivity and therefore understates productivity's true importance. Our estimates suggest that the understatement may be quite large, and that one might better ask if the growth rate of TFP, rather than capital growth, is sustainable.

DEM simulation of effect of confining pressure on ballast behaviour

In this paper, an attempt has been made to investigate the influence of confining pressure on deformation and degradation behaviourof railway ballast using the Discrete Element Method (DEM). A novel approach has been employed to model the two dimensionalprojection of field size ballast particles as cluster of bonded particles. Bonded particles are held together by a bond, and debonding isconsidered as particle breakage. A series of cyclic loading simulations using DEM were carried out on an assembly of angular ballast particles at different confining pressures (10 kPa to 240 kPa). The results highlight that the development of axial strain during cyclicloading as a function of initial confining pressure and number of cycles. Very high axial strain and breakage of particles have been observed at low confining pressure (\u3c 30 kPa) owing to dilative volumetric strain behaviour. In terms of particle breakage, there existsan optimum range of confining pressures where breakage is minimal. In addition, the evolution of particle displacement vectors explains the breakage mechanism and associated deformations during cyclic loading

A rare midbrain infarction presenting with plus-minus lid syndrome with ataxia: a case report

<p>Abstract</p> <p>Introduction</p> <p>We present the case of a patient with midbrain infarction with an unusual clinical presentation, where clinical diagnosis and anatomical localization were valuable tools in deciding treatment.</p> <p>Case presentation</p> <p>Our patient was a 59-year-old, right-handed Caucasian man with hypertension who presented to our facility with acute diplopia that persisted until he developed complete right-sided ptosis. He also had difficulty walking and coordinating movements of his upper extremities bilaterally, but this was worse on his left side.</p> <p>Conclusions</p> <p>Plus-minus lid syndrome with ataxia is a rare presentation of midbrain infarction with a unique localization and anatomical description. This case highlights the importance of clinical skills for making a diagnosis in the absence of imaging to confirm the findings.</p

Double deflation: theory and practice

Real GDP measured from the output side, GDP(O), should equal real GDP measured from the expenditure side, GDP(E), just as corresponding two approaches to measuring GDP in current prices are necessarily equal. But this is only the case even in theory if real value added in each industry is measured by double deflation. We set out the theory of double deflation using a matrix algebra treatment based on the framework of the Supply and Use Tables. The context is the UK’s national accounts which measures volume growth by chained Laspeyres indices and which currently use single not double deflation. Initially we use simplified assumptions about prices. Later we introduce more realistic assumptions. We analyse the conditions on prices under which real GDP(O) equals real GDP(E). We consider three alternative methods of implementing double deflation. The preferred method makes use of all the price indices which the Office for National Statistics currently collects: Producer Price Indices, Services Producer Price Indices, Consumer Price Indices, Export Price Indices and Import Price Indices. We implement a simplified version of double deflation, using the same data as in the latest vintage of the national accounts, and compare our estimates with the official ones. In this version the same price index is used for each product regardless of whether the product is an output or an input. We find that double-deflated industry growth rates are consistently lower than the official single-deflated ones and also considerably more variable year-to-year. We interpret this finding as reinforcing the case for careful selection of the set of deflators to use for double deflation

AutoML accurately predicts endovascular mechanical thrombectomy in acute large vessel ischemic stroke

Background and objectiveAutomated machine learning or autoML has been widely deployed in various industries. However, their adoption in healthcare, especially in clinical settings is constrained due to a lack of clear understanding and explainability. The aim of this study is to utilize autoML for the prediction of functional outcomes in patients who underwent mechanical thrombectomy and compare it with traditional ML models with a focus on the explainability of the trained models.MethodsA total of 156 patients of acute ischemic stroke with Large Vessel Occlusion (LVO) who underwent mechanical thrombectomy within 24 h of stroke onset were included in the study. A total of 34 treatment variables including clinical, demographic, imaging, and procedure-related data were extracted. Various conventional machine learning models such as decision tree classifier, logistic regression, random forest, kNN, and SVM as well as various autoML models such as AutoGluon, MLJAR, Auto-Sklearn, TPOT, and H2O were used to predict the modified Rankin score (mRS) at the time of patient discharge and 3 months follow-up. The sensitivity, specificity, accuracy, and AUC for traditional ML and autoML models were compared.ResultsThe autoML models outperformed the traditional ML models. For the prediction of mRS at discharge, the highest testing accuracy obtained by traditional ML models for the decision tree classifier was 74.11%, whereas for autoML which was obtained through AutoGluon, it showed an accuracy of 88.23%. Similarly, for mRS at 3 months, the highest testing accuracy of traditional ML was that of the SVM classifier at 76.5%, whereas that of autoML was 85.18% obtained through MLJAR. The 24-h ASPECTS score was the most important predictor for mRS at discharge whereas for prediction of mRS at 3 months, the most important factor was mRS at discharge.ConclusionAutomated machine learning models based on multiple treatment variables can predict the functional outcome in patients more accurately than traditional ML models. The ease of clinical coding and deployment can assist clinicians in the critical decision-making process. We have developed a demo application which can be accessed at https://mrs-score-calculator.onrender.com/