Miracle-dz/UniFAR-FTUs huggingface dataset:
SUBCELLULAR DISTRIBUTION OF THE ENZYMES OF THE GLUTAMIC ACID, GLUTAMINE AND γ‐AMINOBUTYRIC ACID CYCLES IN RAT BRAIN *

RECENT studies have stressed the important physiological role of certain amino acids in the brain. Analytical determinations revealed high concentrations of glutamic and aspartic acids as well as of glutamine and N-acetylaspartate. y-Aminobutyric acid (GABA), is especially interesting, not only because of its high concentration, but also because of its exclusive presence in the CNS, particularly in grey matter. Numerous biochemical studies have been dedicated to the metabolic interrelationships existing among this group of amino acids and the glycolytic and tricarboxylic cycles, as well as with the mechanism of ammonia removal in brain. Some of these amino acids may serve as anions, making up for part of the inorganic anion deficit, or as important substrates in intermediary metabolism. Experimental observations have shown that these amino acids may have different physiological actions. Both glutamic and aspartic acids have a powerful excitatory action. On the contrary, GABA has a general depressant action on different neuronal responses while glutamine and N-acetylaspartic acid have no effect. It has been suggested that some of these amino acids are important in maintaining the normal excitability of neuronal membranes acting in a rather unspecific way, while others have suggested a synaptic role for them (see CURTIS, PHILLIS and WATKINS, 1959, 1960; CURTIS and WATKINS, 1960; FLOREY, 1964). The function of this group of amino acids seems to be related to the complex structure of the CNS and the existence of numerous compartments and metabolic pools. With radioisotope experiments it has been found that only a small fraction of the total glutamate is rapidly interchanged, while the rest remains rather inactive (BERL, TAKACAKI and PURPURA, 1961b). Similarly, only a small fraction of GABA appears to be active (BERL, LAJTHA and WAELSCH, 1961~). Furthermore some of these amino acids apparently can exchange across cell membranes, and this exchange is accelerated by stimulation of nerve cells (LUXORO, 1960).
Dried blood spots for the enzymatic diagnosis of lysosomal storage diseases in dogs and cats.

BACKGROUND In people, lysosomal storage diseases (LSD) can be diagnosed by assaying enzyme activities in dried blood spots (DBS). OBJECTIVE The aim of this study was to evaluate the feasibility of using DBS samples from dogs and cats to measure lysosomal enzymatic activities and diagnose LSD. METHODS Drops of fresh whole blood collected in EDTA from dogs and cats with known or suspected LSD and from clinically healthy dogs and cats were placed on neonatal screening cards, dried, and mailed to the Metabolic Laboratory, University Children's Hospital, Frankfurt, Germany. Activities of selected lysosomal enzymes were measured using fluorescent substrates in a 2-mm diameter disk (~2.6 μL blood) punched from the DBS. Results were expressed as nmol substrate hydrolyzed per mL of blood per minute or hour. RESULTS Reference values were established for several lysosomal enzyme activities in DBS from dogs and cats; for most enzymes, activities were higher than those published for human samples. Activities of β-glucuronidase, N-acetylglucosamine-4-sulfatase (arylsulfatase B), α-mannosidase, α-galactosidase, α-fucosidase, and hexosaminidase A were measureable in DBS from healthy cats and dogs; α-iduronidase activity was measureable only in cats. In samples from animals with LSD, markedly reduced activity of a specific enzyme was found. In contrast, in samples from cats affected with mucolipidosis II, activities of lysosomal enzymes were markedly increased. CONCLUSIONS Measurement of lysosomal enzyme activities in DBS provides an inexpensive, simple, and convenient method to screen animals for suspected LSD and requires only a small sample volume. For diseases in which the relevant enzyme activity can be measured in DBS, a specific diagnosis can be made.
COPINGWITH LANGUAGE DATA SPARSITY : SEMANTIC HEAD MAPPING OF COMPOUNDWORDS

In this paper we present a novel clustering technique for compound words. By mapping compounds onto their semantic heads, the technique is able to estimate n-gram probabilities for unseen compounds. We argue that compounds are well represented by their heads which allows the clustering of rare words and reduces the risk of overgeneralization. The semantic heads are obtained by a two-step process which consists of constituent generation and best head selection based on corpus statistics. Experiments on Dutch read speech show that our technique is capable of correctly identifying compounds and their semantic heads with a precision of 80.25% and a recall of 85.97%. A class-based language model with compound-head clusters achieves a significant reduction in both perplexity and WER.
EQUILIBRIUM IN THE EQUITY MARKET UNDER UNCERTAINTY

IN RECENT YEARS important contributions to a theory of the valuation of risk assets' have been made by Sharpe [15], Lintner [8,9] and Mossin [13]. Each of these authors has assumed that investors are risk averse, have homogeneous expectations,2 have utility functions definable over the first two moments of the probability distribution of portfolio rates of returns, have a given amount of their present wealth committed to investment in financial assets, have adequate funds for diversification, and can borrow and lend freely at the pure rate of interest. Given these assumptions they have developed analogous models of the relative price and/or yield structure of individual risk assets in equilibrium. Each of these authors treats the supply of risk assets as fixed and the rate of interest as exogenously determined. Sharpe's paper is essentially a verbal-diagrammatic presentation. He showed that through borrowing or lending, an investor may linearly alter the expected rate of return and standard deviation of the rate of return on his portfolio of financial assets. Since investors would prefer the portfolio or portfolios having the most favorable potential trade-off between expected rate of return and the standard deviation of the rate of return, he theorized that investors would purchase risk assets belonging to this (those) efficient portfolio (portfolios) and simultaneously sell others. The actions of investors would result in price revisions until every risk asset belonged to at least one efficient portfolio. Since portfolio diversification across securities enables investors to escape all but the risk resulting from swings in economic activity, he argued that only the responsiveness or proportionate change in the rate of return of an asset to changes in the level of economic activity is relevant in assessing its risk. He theorized that prices of individual risk assets would adjust until there is a linear relationship
Depth estimation of stereo matching based on microarray camera

Depth information affects greatly the accuracy of image measurement, 3D reconstruction and image recognition. In general, the methods of obtaining depth information are from 3D laser scanners, structured light, and depth cameras. The traditional method using binocular camera to obtain the depth information of images is based on the disparity between the left and right views, but it also brings some problems such as the occlusion area and mismatched points. To improve the accuracy, we proposed a novel method of depth estimation of stereo matching based on microarray camera. First, each lens in the camera is calibrated to compute the intrinsic and extrinsic parameters, which are used to rectify the captured images respectively. Then stereo matching between images is modeled by a Markov random field, and the energy cost function for the MRF is built and the minimization of it is solved with Graph-Cuts algorithm. Finally, the matching result is obtained with depth information simultaneously. In the minimization procedure, level division of depth is incorporated, and the gradient information of the reference image is utilized to refine the depth layers of the corresponding image. Experimental results showed the efficiency and accuracy of the proposed algorithm.
Methyl 4-benzyloxy-7-methoxy-1-methyl-1H-indole-2-carboxylate

There are two independent molecules in the asymmetric unit of the title compound, C19H19NO4. The indole unit in each molecule is essentially planar, with mean deviations of 0.017 (1) and 0.013 (1) Å and forms dihedral angles of 50.17 (7) and 26.05 (6)° with the phenyl ring. In the crystal, molecules are linked by weak C–H⋯π interactions.
A Primer on the Knowledge Economy

This primer is intended as a brief guide to the Knowledge Economy for people in business and government who need a succinct summary of its major features and implications. It draws on research undertaken at CSES over the last few years, on the work of the OECD and on a rapidly growing international literature, and aims to provide a synthesis. We address the following questions: - What is the knowledge economy? - What is new about the 'New Economy'? - What does it mean for Australia? - What might we do to meet the challenge?
Measuring T cell immunity to influenza vaccination in children after haemopoietic stem cell transplantation

Quantitative assessment of immunogen‐specific T cell responses may provide a meaningful surrogate marker of functional immunity in patients following haemopoietic stem cell transplantation (HSCT). We developed a flow‐cytometric assay to quantify antigen‐specific T cell immunity to influenza‐A and studied the T cell response to influenza vaccination in five children, 3–21 months post‐HSCT. All patients showed an increase in influenza‐A‐specific CD4+ immunity following vaccination while none had a detectable IgG response to the vaccine. This assay proved sufficiently sensitive to evaluate changes in T cell memory in immunocompromised individuals and could be used to better characterize post‐HSCT immune reconstitution.
The Impacts of Transportation Infrastructure on Property Values: A Higher-Order Spatial Econometrics Approach

We evaluate the impacts of enhanced transportation systems on property values for U.S. manufacturing firms, allowing for higher-order spatial error correlation. We use a state-level model of production cost and input demand that recognizes the productive contribution of public transportation infrastructure stocks. Our findings include significant impacts on property shadow values and input composition from both public highway and airport investment. We also find that these effects have a spatial dimension that depends on the proximity of the transport system; at least one and as many as three spatial error lags are significant in our estimating equations. Further, recognizing production growth from transportation system improvements augments the associated incentives for private capital investment.
Asset Pricing with Idiosyncratic Consumption Risk and Limited Participation

A growing body of literature suggests limited asset market participation as a plausible explanation of the empirical failure of the standard consumption capital asset pricing model (CCAPM). Correct identification of capital markets investors is, however, often impossible due to imperfection of available information on assetholding status. As a plausible solution to the problem of sample classification when available information is an imperfect sample separation indicator, we propose the CCAPM in which the pricing kernel is calculated as the weighted average of individual householdsi¯ marginal rate of substitution, with the weights being the probabilities of holding the asset in question. The asset holding probabilities are conditional on available sample separation information and estimated from a binary response model as a function of demographic and family characteristics of consumers simultaneously with the parameters of Euler equations. The CCAPM with probability-weighted agents is less susceptible to sample misclassification compared to when available imperfect information on asset holding status is used to separate assetholders from nonassetholders. Using data from the U.S. Consumer Expenditure Survey (CEX), we find that, in contrast to when the reported in the CEX financial information is regarded as a perfect sample separation indicator, the model with probability-weighted agents is not rejected statistically both under conventional normal and weak-identification asymptotics and yields precise and economically realistic estimates of the coefficient of relative risk aversion (RRA). The hypothesis that the householdsi¯ market participation behavior exhibits considerable persistence is not rejected statistically. Empirical evidence is that the decision to own assets is likely to be endogenous with respect to the consumption and savings decisions and that allowing for this fact is important for estimating risk aversion.
Ada/Mindstorms 3.0

The paper presents a computational environment built on the LEGO Minstorms RCX kit for introductory robotics and programming. The author describes the Ada/Mindstorms 3.0, a software environment for teaching using the LEGO Mindstorms RCX kit. He discusses the design choices made, the reasons for those decisions, and show examples of how the system works. Ada/Mindstorms has been used in computing classes at the US Air Force Academy and around the world and is freely available online.
Deep Convolutional Framelets: A General Deep Learning for Inverse Problems

Recently, deep learning approaches have achieved significant performance improvement in various imaging problems. However, it is still unclear why these deep learning architectures work. Moreover, the link between the deep learning and the classical signal processing approaches such as wavelet, non-local processing, compressed sensing, etc, is still not well understood, which often makes signal processors in deep troubles. To address these issues, here we show that the long-searched-for missing link is the convolutional framelets for representing a signal by convolving local and non-local bases. The convolutional framelets was originally developed to generalize the recent theory of low-rank Hankel matrix approaches, and this paper significantly extends the idea to derive a deep neural network using multi-layer convolutional framelets with perfect reconstruction (PR) under rectified linear unit (ReLU). Our analysis also shows that the popular deep network components such as residual block, redundant filter channels, and concatenated ReLU (CReLU) indeed help to achieve the PR, while the pooling and unpooling layers should be augmented with multi-resolution convolutional framelets to achieve PR condition. This discovery reveals the limitations of many existing deep learning architectures for inverse problems, and leads us to propose a novel deep convolutional framelets neural network. Using numerical experiments with sparse view x-ray computed tomography (CT), we demonstrated that our deep convolution framelets network shows consistent improvement. This discovery suggests that the success of deep learning is not from a magical power of a black-box, but rather comes from the power of a novel signal representation using non-local basis combined with data-driven local basis, which is indeed a natural extension of classical signal processing theory.
Recreational Housing and Community Development: A Triple Bottom Line Approach

In this study, we explore the impact of recreational housing on community development within a triple bottom line (economic, social, environmental) framework. We empirically assess the relationships between recreational housing and social, environmental, and economic conditions in nonmetropolitan counties and explicitly model spatial relationships, considering the potential for indirect spillover effects of recreational housing presence in one county to be associated with social, environmental, and economic conditions in neighboring counties. We employ a spatial Bayesian model averaging method to determine the set of control variables and find that higher concentrations of recreational homes are associated with lower levels of economic well-being, but somewhat higher levels of environmental quality.
Management Forecasts in Japan: An Empirical Study of Forecasts that are Effectively Mandated

ABSTRACT: We study management forecasts in Japan, where forecasts are effectively mandated but managers have considerable latitude over the numbers they release. We find that managers' initial earnings forecasts for a fiscal year are systematically upward‐biased but that they revise their forecasts downward during the fiscal year so that most earnings surprises are non‐negative. Managers' initial forecast optimism is inversely related to firm performance, and is more pronounced for firms with higher levels of insider ownership, smaller firms, and firms with a history of forecast optimism. The fact that managers' forecasts tend to be consistently optimistic suggests that reputation effects are insufficient to ensure managerial forecast accuracy. We also find that the information content of managers' forecasts is related to proxies for whether market participants view the forecasts as credible.
Desensitization therapy for allergic reactions to antituberculous drugs.

OBJECTIVE We retrospectively evaluated the clinical usefulness of desensitization therapy for many patients showing allergic reactions to anti-mycobacterial drugs (INH and RFP) according to the proposition reported by the Japanese Society for Tuberculosis (JST). METHODS Desensitization therapy for anti-mycobacterial drugs was performed according to the propositions of JST for forty-six patients with mycobacterial disease in several hospitals participating in the Chugoku-Shikoku Mycobacterial Disease Committee between January 1999 and December 2009. RESULTS Adverse reactions occurred as drug-induced skin eruptions in 23 patients, drug-induced fever in 16, and drug-induced fever plus eruption in 7. The causative drugs suggested by the clinical course or DLST were RFP in 30 patients and INH in 16. The clinical effects of desensitization therapy for individual drugs was good in 23 of 30 patients (77%) receiving RFP, and in 13 of 16 (81%) receiving INH. Ten patients showing failure of desensitization included 5 elderly patients and 2 patients with a history of drug allergies. The interval until initiation of desensitization therapy ranged from 5 to 30 days after the disappearance of adverse reactions and the interval until the appearance of adverse reactions during desensitization therapy ranged from 3 to 18 days. A comparative study between the patient group with successful desensitization therapy and that with failure of desensitization did not show any significant differences except for the interval until initiation of desensitization therapy. CONCLUSION We confirmed the clinical effectiveness of desensitization therapy for anti-mycobacterial drugs according to the propositions of JST in this multicenter study.
Hidden Flexibility: Institutions, Incentives, and the Margins of Selectivity in Fishing

The degree to which selectivity in fisheries is malleable to changes in incentive structures is critical for policy design. We examine data for a multispecies trawl fishery before and after a transition from management under common-pool quotas to a fishery cooperative and note a substantial shift in postcooperative catch from bycatch and toward valuable target species. We examine the margins used to affect catch composition, finding that large- and fine-scale spatial decision making and avoidance of night-fishing were critical. We argue that the poor incentives for selectivity in many systems may obscure significant flexibility in multispecies production technologies. (JEL Q22, Q28)
Limitations of Linear Programming Techniques for Bounded Color Matchings

Given a weighted graph G = (V,E,w), with weight function w : E → Q, a matching M is a set of pairwise non-adjacent edges. In the optimization setting, one seeks to find a matching of maximum weight. In the multi-criteria (or multi-budgeted) setting, we are also given ` length functions α1, . , α` assigning positive numbers to each edge and ` numbers β1, . , β` ∈ Q, each one associated with the corresponding length function. The goal is to find a maximum weight matching M (under function w) such that ∑ e∈M αi(e) ≤ βi, ∀i ∈ [`] (these are the budgets). In this paper we are interested in the case where each edge e ∈ E belongs to a unique budget, i.e., it has a unique color. In [30] an 1 2 -approximation algorithm was given based on rounding the natural linear programming relaxation of the problem, and this is optimal modulo the integrality gap of the formulation. The purpose of this paper is to study to what extend linear programming methods help us design algorithms with a better performance guarantee. We prove the following unconditional inapproximability result: even a large family of linear programs, generated by a logarithmic number of rounds of the Sherali-Adams hierarchy [29] or a linear number of rounds of the BCC operator [1], does not suffice to change the integrality gap even the slightest.
Food policy in India: the importance of electoral politics in policy implementation

This article discusses, compares and contrasts the politics of food policy implementation in two Indian States: Karnataka in South India and Bihar in North India. Both states are covered by the Public Distribution System (PDS), a major intervention in the Indian food economy intended to reduce food insecurity and improve welfare. As in most South Indian States, the PDS in Karnataka works reasonably well. Most poor people receive some subsidized foodgrains every month. Karnataka politicians see the scheme as important and use it to enhance their popularity and attract votes. By contrast, the impact of the PDS on the poor in Bihar is negligible. The foodgrains are coming every month, but more than 80 per cent is diverted to the open market. This raises the question as to why the populist politicians in Bihar are not making use of the PDS in the same way as their colleagues in Karnataka. Based on fieldwork in these two States, the article explores a number of explanations. It concludes that politicians in Bihar take a definite interest in the PDS, but as a result of the different features of the overall political processes in these two States, this leads to a different type of influence for them as well as different outcomes for the beneficiaries. Copyright © 1999 John Wiley & Sons, Ltd.
Economic Environmental Valuation: An Analysis of Limitations and Alternatives

The structure of this report is as follows. In Section 2 we introduce economic methods for environmental and biodiversity valuation, and in particular the total economic value model. Sections 3 through 7 will advance five distinct but related classes of criticisms of economic environmental valuation, and in each we will suggest the way in which alternative valuation methods contain the resources to help address those criticisms.