Miracle-dz/UniFAR-FTUs huggingface dataset:
Consequences of Employment Protection? The Case of the Americans with Disabilities Act

The Americans with Disabilities Act (ADA) requires employers to accommodate disabled workers and outlaws discrimination against the disabled in hiring, firing, and pay. Although the ADA was meant to increase the employment of the disabled, the net theoretical effects are ambiguous. For men of all working ages and women under 40, Current Population Survey data show a sharp drop in the employment of disabled workers after the ADA went into effect. Although the number of disabled individuals receiving disability transfers increased at the same time, the decline in employment of the disabled does not appear to be explained by increasing transfers alone, leaving the ADA as a likely cause. Consistent with this view, the effects of the ADA appear larger in medium‐size firms, possibly because small firms were exempt from the ADA. The effects are also larger in states with more ADA‐related discrimination charges.
Testing for Common Breaks in a Multiple Equations System

The issue addressed in this paper is that of testing for common breaks across or within equations of a multivariate system. Our framework is very general and allows integrated regressors and trends as well as stationary regressors. The null hypothesis is that breaks in different parameters occur at common locations and are separated by some positive fraction of the sample size unless they occur across different equations. Under the alternative hypothesis, the break dates across parameters are not the same and also need not be separated by a positive fraction of the sample size whether within or across equations. The test considered is the quasi-likelihood ratio test assuming normal errors, though as usual the limit distribution of the test remains valid with non-normal errors. Of independent interest, we provide results about the rate of convergence of the estimates when searching over all possible partitions subject only to the requirement that each regime contains at least as many observations as some positive fraction of the sample size, allowing break dates not separated by a positive fraction of the sample size across equations. Simulations show that the test has good finite sample properties. We also provide an application to issues related to level shifts and persistence for various measures of inflation to illustrate its usefulness.
Java client ahead-of-time compiler for embedded systems

The performance of embedded Java virtual machine can be improved by ahead-of-time compiler (AOTC), which translates bytecode into machine code in the server and installs the machine code on the client device. Although AOTC is more advantageous than just-in-time compiler (JITC) due to its absence of the translation overhead, AOTC cannot be applicable to dynamically downloaded classes at runtime. This paper proposes client-AOTC (c-AOTC) which performs AOTC on the client device using the JITC module installed on the device, complementing the server-AOTC. The machine code of a method translated by JITC is cached on a persistent memory of the device, and when the method is invoked again in a later run of the program, the machine code is loaded and executed directly without the translation and interpretation overhead. One of major issues in c-AOTC is relocation because some of the addresses used by the cached machine code are not correct when the machine code is loaded and used in a different run; those addresses should be corrected before they are used. Constant pool resolution and inlining complicate the relocation problem and we propose our solutions. We developed a c-AOTC on Sun's CDC VM reference implementation (RI) and our evaluation results indicate that c-AOTC can improve the performance significantly, as much as an average of 12%. We also experiment with the issue of reducing the number of c-AOTC methods to be cached when the persistent space is tight, with a graceful degradation of performance.
Simvastatin Potentiates the Antihyperglycemic, Antidyslipidimic and Antioxidative Effect of Glibenclamide on Alloxan-Induced Diabetic Rats

The aim of the current study is to investigate the effect of combination of glibenclamide; an antidiabetic drug and simvastatin; a HMG-CoA reductase inhibitor on long-term (four weeks) alloxan-induced diabetes rats (ADRs). Methods: Alloxan (120 mg/kg body weight, BW) was injected intra-peritonially (i.p.) in rats. At first alloxan (120 mg/kg BW) induced diabetic rats were treated with single dose of glibenclamide (1.2 mg/70kg BW) and simvastatin (10 mg/70kg BW) for two weeks. Then fixed dose combinations of glibenclamide (0.6 mg/70kg BW) and simvastatin (5 mg/70kg BW) were injected along with those of two drugs for four weeks. Results: At first it was found that glibenclamide reduced significant amount of glucose in blood, but it had no significant effect on lipid profile on short term (two weeks) ADRs. In contrast, simvastatin had no effect on blood glucose level, whereas it significantly reduced total cholesterol (TC), triglycerides (TG) and low density lipoprotein cholesterol (LDL-C) and increased significant amount of high density lipoprotein cholesterol (HDL-C). However, pathological changes of pancreas’s Islets of Langerhans were observed only after long-term (four weeks) induction of alloxan in rats. The inhibitory effect of combination therapy on blood glucose, TC, TG and LDL-C level was higher than those of monotherapy alone on long term ADRs. In addition, treatment with combination therapy on long term ADRs showed higher amount of HDL-C level and super oxide dismutase and catalase enzyme activity than those with monotherapy. They also decreased serum glutamic pyruvic transaminase (SGPT) and Serum glutamic oxaloacetic transaminase (SGOT) level. Administration of simvastatin recovered Langerhans cells from shrinkage whereas glibenclamide displayed slight recovery. But the combination therapy showed complete recovery of Langerhans cells as compared with diabetic rats. Conclusion: Our present findings suggest that treatment of glibenclamide in combination with simvastatin may be more effective than mono-therapy for preventing diabetes in rats. It may also suggest that this combination may have some beneficial effects on reducing cardiovascular risks from long term diabetes in rats.
On the Asymptotic Performance of Bit-Wise Decoders for Coded Modulation

Two decoder structures for coded modulation over the Gaussian channel are studied: 1) the maximum likelihood symbol-wise decoder and 2) the (suboptimal) bit-wise decoder based on the bit-interleaved coded modulation paradigm. We consider a 16-ary quadrature amplitude constellation labeled with a Gray labeling. It is shown that the asymptotic loss in terms of pairwise error probability, for any two codewords caused by the bit-wise decoder, is bounded by 1.25 dB. The analysis also shows that the asymptotic loss is zero for a wide range of linear codes, including all rate-1/2 convolutional codes.
Designing Future Warehouse-Scale Computers for Sirius, an End-to-End Voice and Vision Personal Assistant

As user demand scales for intelligent personal assistants (IPAs) such as Apple’s Siri, Google’s Google Now, and Microsoft’s Cortana, we are approaching the computational limits of current datacenter (DC) architectures. It is an open question how future server architectures should evolve to enable this emerging class of applications, and the lack of an open-source IPA workload is an obstacle in addressing this question. In this article, we present the design of Sirius, an open end-to-end IPA Web-service application that accepts queries in the form of voice and images, and responds with natural language. We then use this workload to investigate the implications of four points in the design space of future accelerator-based server architectures spanning traditional CPUs, GPUs, manycore throughput co-processors, and FPGAs. To investigate future server designs for Sirius, we decompose Sirius into a suite of eight benchmarks (Sirius Suite) comprising the computationally intensive bottlenecks of Sirius. We port Sirius Suite to a spectrum of accelerator platforms and use the performance and power trade-offs across these platforms to perform a total cost of ownership (TCO) analysis of various server design points. In our study, we find that accelerators are critical for the future scalability of IPA services. Our results show that GPU- and FPGA-accelerated servers improve the query latency on average by 8.5× and 15×, respectively. For a given throughput, GPU- and FPGA-accelerated servers can reduce the TCO of DCs by 2.3× and 1.3×, respectively.
Intention-Based Decision Making via Intention Recognition and its Applications

In this chapter we present an intention-based decision making system. We exhibit a coherent combination of two Logic Programming based implemented systems, Evolution Prospection and Intention Recognition. The Evolution Prospection system has proven to be a powerful system for decision making, designing and implementing several kinds of preferences and useful environment-triggering constructs. It is here enhanced with an ability to recognize intentions of other agents—an important aspect not well explored so far. The usage and usefulness of the combined system are illustrated with several extended examples in different application domains, including Moral Reasoning, Ambient Intelligence, Elder Care, and Game Theory.
A Versatile Framework for Speaker Separation Using a Model-Based Speaker Localization Approach

We build upon our speaker localization framework developed in a previous work (N. Madhu and R. Martin, A scalable framework for multiple speaker localization and tracking,” in Proc. Int. Workshop Acoustic Echo Noise Control (IWAENC), Sep. 2008) to perform source separation. The proposed approach, exploiting the supplementary information from the mixture of Gaussians-based localization model, allows for the incorporation of a wide class of separation algorithms, from the nonlinear time-frequency mask-based approaches to a fully adaptive beamformer in the generalized sidelobe canceller (GSC) structure. We propose, in addition, a generalized estimation of the blocking matrix based on subspace projectors. The adaptive beamformer realized as proposed is insensitive to gain mismatches among the sensors, obviating the need for magnitude calibration of the microphones. It is also demonstrated that the proposed linear approach has a performance comparable to that of an optimal (oracle) GSC implementation. In comparison to ICA-based approaches, another advantage of the separation framework described herein is its robustness to ambient noise and scenarios with an unknown number of sources.
Bioactives of Artemisia dracunculus L. Mitigate the Role of Ceramides in Attenuating Insulin Signaling in Rat Skeletal Muscle Cells

Ectopic lipids in peripheral tissues have been implicated in attenuating insulin action in vivo. The botanical extract of Artemisia dracunculus L. (PMI 5011) improves insulin action, yet the precise mechanism is not known. We sought to determine whether the mechanism by which PMI 5011 improves insulin signaling is through regulation of lipid metabolism. After differentiation, cells were separately preincubated with free fatty acids (FFAs) and ceramide C2, and the effects on glycogen content, insulin signaling, and ceramide profiles were determined. The effect of PMI 5011 on ceramide accumulation and ceramide-induced inhibition of insulin signaling was evaluated. FFAs resulted in increased levels of total ceramides and ceramide species in L6 myotubes. Saturated FFAs and ceramide C2 inhibited insulin-stimulated phosphorylation of protein kinase B/Akt and reduced glycogen content. PMI 5011 had no effect on ceramide formation or accumulation but increased insulin sensitivity via restoration of Akt phosphorylation. PMI 5011 also attenuated the FFA-induced upregulation of a negative inhibitor of insulin signaling, i.e., protein tyrosine phosphatase 1B (PTP1B), and increased phosphorylation of PTP1B. PMI 5011 attenuates the reduction in insulin signaling induced by ceramide accumulation, but the mechanism of improved insulin signaling is independent of ceramide formation.
The Information Content of Stock Markets: Why Do Emerging Markets Have So Little Firm-Specific Risk?

Stock prices in emerging economies move in step much more than in advanced economies. Emerging markets' prices capitalize less firm specific information, and appear subject to more economy-wide fluctuations. Measures of this consonance of stock returns are positively correlated with indicators of poor property rights protection, inefficient legal systems and corrupt government. Lax accounting standards strengthen these correlations, but do not have an independent effect. We argue that property rights, judicial efficiency, clean government and meaningful accounting information let stock markets process information and allocate capital better, and thus contribute to economic growth. The absence of these factors may discourage informed trading and foster noise trading.
Comparative Label-Free Mass Spectrometric Analysis of Mildly versus Severely Affected mdx Mouse Skeletal Muscles Identifies Annexin, Lamin, and Vimentin as Universal Dystrophic Markers

The primary deficiency in the membrane cytoskeletal protein dystrophin results in complex changes in dystrophic muscles. In order to compare the degree of secondary alterations in differently affected subtypes of skeletal muscles, we have conducted a global analysis of proteome-wide changes in various dystrophin-deficient muscles. In contrast to the highly degenerative mdx diaphragm muscle, which showed considerable alterations in 35 distinct proteins, the spectrum of mildly to moderately dystrophic skeletal muscles, including interosseus, flexor digitorum brevis, soleus, and extensor digitorum longus muscle, exhibited a smaller number of changed proteins. Compensatory mechanisms and/or cellular variances may be responsible for differing secondary changes in individual mdx muscles. Label-free mass spectrometry established altered expression levels for diaphragm proteins associated with contraction, energy metabolism, the cytoskeleton, the extracellular matrix and the cellular stress response. Comparative immunoblotting verified the differences in the degree of secondary changes in dystrophin-deficient muscles and showed that the up-regulation of molecular chaperones, the compensatory increase in proteins of the intermediate filaments, the fibrosis-related increase in collagen levels and the pathophysiological decrease in calcium binding proteins is more pronounced in mdx diaphragm as compared to the less severely affected mdx leg muscles. Annexin, lamin, and vimentin were identified as universal dystrophic markers.
Managed Floats to Damp World-Wide Exchange Rate Liquidity Shocks Like 1982-5, 2006-9: Field and Laboratory Evidence for the Benefits of a Single World Currency

This paper's field evidence is: (1) in reality a major exchange rate change devastates an economy, i.e. the widespread academic faith that exchange rate changes are either beneficial or harmless is a false faith that contributes to needless world-wide economic havoc; (2) the 1982-85 exchange rate liquidity crisis sent much of the third world into unmanageable debt levels and was so devastating for the first world that in 1985 the G5 instituted managed cooperating floats; (3) nearly all economists in the official sector and in academe rapidly forgot the devastation and reverted to advocating what caused that devastation, namely a closed economy clean floats exchange rate perspective; and (4) the 2006-2008/9 exchange rate liquidity shock would have been far more drastic but for central bank currency swaps yet the role of these swaps in averting unmanageable exchange rate mayhem that would have precluded the September 2008 rescue of the world financial system, has been ignored. The field evidence thus decisively favours stabilizing managed floats, or better a single world currency, and a means of preventing economists in official sectors and in academe forgetting the devastation and dangers of multiple currencies. This field evidence is bolstered by a laboratory experiment. The experiment incorporates more aspects of real world complexity and more different sorts of official and private sector agents than other investigations and employs a new central bank cooperation-conflict model of exchange rate determination. The experiment allows an interpretation within an umbrella theory of Pope, namely SKAT, the Stages of Knowledge Ahead Theory.
Estimating Effective Connectivity from fMRI Data Using Factor-based Subspace Autoregressive Models

We consider the problem of identifying large-scale effective connectivity of brain networks from fMRI data. Standard vector autoregressive (VAR) models fail to estimate reliably networks with large number of nodes. We propose a new method based on factor modeling for reliable and efficient high-dimensional VAR analysis of large networks. We develop a subspace VAR (SVAR) model from a factor model (FM), where observations are driven by a lower-dimensional subspace of common latent factors with an AR dynamics. We consider two variants of principal components (PC) methods that provide consistent estimates for the FM hence the implied SVAR model, even of large dimensions. Information criterion is used to select the optimal subspace dimension. We established asymptotic normality and convergence rates for the estimated SVAR coefficients matrix. Evaluation on simulated resting-state fMRI shows that the SVAR models are more robust and produce better connectivity estimates than the classical model for a moderately-large network analysis. Results on real data by varying the subspace dimensions identify strong connections in the default mode network and reveal hierarchical connectivity of resting-state networks with distinct functional relevance.
How Non-Verbal Power Communication Increases Frustration and Aggressive Encounters Within the Public Task Domain

Despite specially designed training programmes, violence and aggression against individuals with a public task (e.g. ambulance, police, railway guard, bus drivers or security) is occurring on a daily basis. This study investigates the possible influence of non-verbal cues or behaviours on the development of aggressive feelings of the opponent in dyadic interactions. The development of aggressive behaviour is explained with the Frustration – Anger Theory of Dollard and colleagues (1939), the interpersonal power model of Schmid Mast (2010) and the approach inhibition theory of power of Keltner, Gruenfeld, and Anderson (2003). Further the importance of non-verbal communication and justice within the public tasks is explained. Non-verbal power communication and procedural justice were manipulated in an experimental study. Participants (N=92) took part in a short experiment where they read a scenario and saw an interaction (in Virtual Reality) with a police officer displaying high non-verbal power communication or neutral non-verbal power communication. Overall this study adds information about the influence of non-verbal power communication on the development of feelings of aggression
Worst-case computational complexity analysis for embedded MPC based on dual gradient method

In this paper we analyze the computational complexity of a linear model predictive control (MPC) scheme for embedded systems based on the dual gradient algorithm. We recast our MPC problem as a linearly constrained convex problem. When it is difficult to project on the primal feasible set described by linear constraints, we use the Lagrangian relaxation to handle the complicated constraints and then we apply the dual gradient algorithm for solving the corresponding dual. We give a full convergence rate analysis for dual gradient algorithm: we provide sublinear or linear estimates on the primal suboptimality and feasibility violation of the generated approximate primal solutions. Our analysis relies on the Lipschitz property of the dual function or an error bound property. Furthermore, the iteration complexity analysis is based on an approximate primal solution given by the last primal iterate sequence. We also discuss implementation aspects of the proposed algorithm on constrained linear MPC for embedded systems.
SELF CONCEPTS OF CHILDREN AND THEIR INTELLIGENCE , ACHIEVEMENT , INTERESTS , AND ANXIETY 1 . 2

This is a study of the self concepts of 4th and 6th grade boys and girls in relation to their intelligence, academic achievement, interests, and manifest anxiety. METHOD From a random sample of 27 J 4th and 6th grade boys and girls from 4 schools in Clarke County, Georgia, the scores on the following instruments-as measures of the above traits-were used in the present study: (a) A Self Concept Scale consisting of a checklist of 30 trait-descriptive adjectives which the subject checked as characteristic of himself "nearly always," "about half the time," or "just now and then. " The scale was slightly modified from Lipsitt's adaptation (6) of Bills' Index of Adjustment (2). The scale as adapted assigned scores of 3,2, or I points for each item, reversing the values for the five "negative" traits-lazy, mean, selfish, etc. The higher score, then, indicates higher self-esteem. (b) California Test of Mental Maturity. (c) California Achievement Tests. (d) What-l-Like-to-Do Inventory (4). (e) The McCandless and Castaneda adaptation (7) of the Taylor Manifest Anxiety Scale (9), consisting of 53 items such as "1 blush easily. " RESULTS The self-concept scores (SC) are presented in Table J. There was no appreciable difference between the SC of boys in the two grades, or of girls in the two grades. But the girls in both grades scored significantly higher (at the .01 level) than the boys in the corresponding grades. Table 1 presents also correlations between SC and the other measures. Relationships with intelligence were mostly low to moderately positive. But whereas the correlations for boys were significant and positive, ranging from . 278 to . 42J for total IQ, for girls they were not significant. under the tide of "Self-concepts of elementary school children in relation to their academic achievement, intelligence, interests, and manifest anxiety. " 2The research reported herein was performed pursuant to a contract with the
When are artificial intelligence versus human agents faulted for wrongdoing? Moral attributions after individual and joint decisions

ABSTRACT Artificial intelligence (AI) agents make decisions that affect individuals and society which can produce outcomes traditionally considered moral violations if performed by humans. Do people attribute the same moral permissibility and fault to AIs and humans when each produces the same moral violation outcome? Additionally, how do people attribute morality when the AI and human are jointly making the decision which produces that violation? We investigate these questions with an experiment that manipulates written descriptions of four real-world scenarios where, originally, a violation outcome was produced by an AI. Our decision-making structures include individual decision-making – either AIs or humans – and joint decision-making – either humans monitoring AIs or AIs recommending to humans. We find that the decision-making structure has little effect on morally faulting AIs, but that humans who monitor AIs are faulted less than solo humans and humans receiving recommendations. Furthermore, people attribute more permission and less fault to AIs compared to humans for the violation in both joint decision-making structures. The blame for joint AI-human wrongdoing suggests the potential for strategic scapegoating of AIs for human moral failings and the need for future research on AI-human teams.