Miracle-dz/UniFAR-FTUs huggingface dataset:
An Analysis of Factors Influencing Asset Writedowns

This study investigates the magnitude of total asset writedowns for a random sample of Australian industrial companies. We adopt an income strategy approach in operationalising our magnitude of writedowns construct to consider the set of accounting policies and negative accruals potentially available to managers. Our focus is on the incentives for and constraints on management to make asset writedowns. We find that the magnitude of writedowns observed are associated with managers incentives to writedown impaired assets that have declined in value, as well as the firm's capacity to absorb the financial statement effects of the writedown. The number of senior management changes found to be associated with greater writedowns in prior studies is also supported in this study when only writedowns taken to the income statement are considered. The quality of corporate governance mechanisms does not vary systematically with the magnitude of writedowns.
Data Development for Implementing Integrated Land-use and Transportation Forecasting Models in Medium-sized Metropolitan Planning Organizations

Abstract Integrated land-use and transportation forecasting models require large amounts of data to calibrate and estimate. Obtaining reliable datasets for these models can be one of the most cost-prohibitive and time-consuming stages of such an endeavor. The purpose of this paper is to present a case-study data development program that was able to successfully provide all of the needed data for the estimation and calibration of an integrated land-use and transportation forecasting model. The recently developed Cube Land model was implemented in the Montgomery (Alabama) Area Metropolitan Planning Organization with funding from the Alabama Department of Transportation. The data development program was fiscally and temporally constrained and replicates typical model development conditions in medium-sized metropolitan planning organizations. This case study presents findings demonstrating that in the US locally developed datasets combined with national data sources and ‘off-the-shelf’, relatively low-cost but high-quality, purchasable datasets can be obtained in a relatively short amount of time and are sufficient to estimate and calibrate an integrated land-use and transportation forecasting model.
Two distinct promoter elements in the human rRNA gene identified by linker scanning mutagenesis

A cell-free RNA polymerase I transcription system was used to evaluate the transcription efficiency of 21 linker scanning mutations that span the human rRNA gene promoter. Our analysis revealed the presence of two major control elements, designated the core and upstream elements, that affect the level of transcription initiation. The core element extends from -45 to +18 relative to the RNA start site, and transcription is severely affected (up to 100-fold) by linker scanning mutations in this region. Linker scanning and deletion mutations in the upstream element, located between nucleotides -156 and -107, cause a three- to fivefold reduction in transcription. Under certain reaction conditions, such as the presence of a high ratio of protein to template or supplementation of the reaction with partially purified protein fractions, sequences upstream of the core element can have an even greater effect (20- to 50-fold) on RNA polymerase I transcription. Primer extension analysis showed that RNA synthesized from all of these mutant templates is initiated at the correct in vivo start site. To examine the functional relationship between the core and the upstream region, mutant promoters were constructed that alter the orientation, distance, or multiplicity of these control elements relative to each other. The upstream control element appears to function in only one orientation, and its position relative to the core is constrained within a fairly narrow region. Moreover, multiple core elements in close proximity to each other have an inhibitory effect on transcription.
A Quantitative Model for Decomposing & Assessing the Value for the Customer

The research presented in this paper proposes a novel quantitative model for decomposing and assessing the Value for the Customer. The proposed approach builds on the different dimensions of the Value Network analysis proposed by Verna Allee having as background the concept of Value for the Customer proposed by Woodall. In this context, the Value for the Customer is modelled as a relationship established between the exchanged deliverables and a combination of tangible and intangible assets projected into their endogenous or exogenous dimensions. The Value Network Analysis of the deliverables exchange enables an in-depth understanding of this frontier and the implicit modelling of co-creation scenarios. The proposed Conceptual Model for Decomposing Value for the Customer combines several concepts: from the marketing area we have the concept of Value for the Customer; from the area of intellectual capital the concept of Value Network Analysis; from the collaborative networks area we have the perspective of the enterprise life cycle and the endogenous and exogenous perspectives; at last, the proposed model is supported by a mathematical formal description that stems from the area of Multi-Criteria Decision Making. The whole concept is illustrated in the context of a case study of an enterprise in the footwear industry (Pontechem). The merits of this approach seem evident from the contact with Pontechem as it provides a structured approach for the enterprises to assess the adequacy of their value proposition to the client/customer needs and how these relate to their endogenous and/or exogenous tangible or intangible assets. The proposed model, as a tool, may therefore be a useful instrument in supporting the commercialisation of new products and/or services.
A Theory of 'Oil'igopoly: Cournot Equilibrium in Exhaustible Resource Markets with Fixed Supplies

The emergence of an effective and powerful cartel in the international petroleum market has stimulated considerable effort among economists to develop models of pricing and supply behavior for this industry.2 This modeling task poses two basic difficulties. First, as in the standard oligopoly problem, one must characterize the behavior of several sellers in a market, aware of each other and of their effect on market price. Second, there is here the added difficulty of treating the explicitly intertemporal nature of suppliers' decision, wherein a limited stock must be optimally allocated over time. This paper studies the implications of the simplest non-trivial postulates about these two aspects of the problem. It is assumed that suppliers are non-cooperative Cournot-Nash players, each of whom is imagined to select an optimal supply strategy taking as given the strategies of the others. Moreover, it is hypothesized that the feasible strategies are limited to open loop paths, chosen at the initial date to maximize the present value of profits in light of the paths of supply which the others have chosen.3 These basic postulates, together with a few technical assumptions concerning the structure of resource demand, permit one to demonstrate the existence of at least one non-cooperative equilibrium. Concerning thisequilibrium we show that: (1) the average and marginal return on resource stocks is inversely related to the size of a player's initial endowment; (2) aggregate production decreases over time until all stocks are exhausted, while firms with smaller stocks exhaust their supplies no later than firms with larger stocks do; (3) the present value of price net of extraction cost declines over time; (4) industry production maximizes a weighted average of intertemporal consumer's surplus and producers' profits;
Stock Return Seasonalities in Asia Pacific Markets

This study documents the existence of strong day-of-the-week effects for most of the Asia Pacific markets. There are also more day-of-the-week variations in the non-January months than in January and there is also a ‘Rogalski’ effect for returns on Monday, Tuesday, Friday and Saturday. Moreover, some turn-of-the-lunar-year effects are found for some markets. Unlike the industrialized markets, month-of-the-year variations are not consistent with the tax-loss selling hypothesis in most of the Asia Pacific markets. This study also finds it hard to reject the hypothesis that day-of-the-week variations of Asia Pacific markets are similar to that of the U.S. market after adjustments for time zone differences, especially for smaller markets.
Increasing Influence of Party Identification on Perceived Scientific Agreement and Support for Government Action on Climate Change in the United States, 2006-12

AbstractSince the mid-2000s, U.S. conservative leaders and Republican politicians have stepped up efforts to challenge the reality and seriousness of anthropogenic climate change (ACC). Especially with the rise of the Tea Party in 2009, ACC denial has become something of a litmus test for Republican politicians to prove their conservative bona fides. Two recent studies find that misperception of scientific agreement on ACC is associated with lower levels of support for government action to deal with ACC. Using nationally representative survey data from 2006 and 2012, the analytical model developed in those two studies was applied to investigate whether the effect of political orientation on perceived scientific agreement and support for government action to reduce emissions has increased since the heightened ACC denial by Republican politicians beginning in 2009. The results indicated that political ideology and party identification are moderately strong predictors of perceived scientific agreement; belie.
Strategic application of outbound open innovation

Purpose – This paper aims to examine the strategic dimension of outbound open innovation (OOI) with a focus on identifying strategic objectives for exploiting knowledge externally. It reviews the literature, presents a list of strategic objectives, and introduces a novel categorization.Design/methodology/approach – A literature review of works combining strategy, and OOI lead to conceptualizing an array of strategic benefits including novel concepts. The review focuses on the empirical observations reported by previous research.Findings – This paper presents the most comprehensive description of strategic objectives that may be pursued by OOI, with several case examples. Objectives are classified to six categories: gaining access to new knowledge, multiplication of own technologies, learning from knowledge transfer, controlling technological trajectories, external exploitation as a core business model and exerting control over the market environment.Research limitations/implications – The paper limits its.
Processing an Offline Insertion-Query Sequence with Applications

In this paper, we present techniques and algorithms for processing an offline sequence of insertion and query operations and for related problems. Most problems we consider are solved optimally in linear time by our algorithms, which are based on a new geometric modeling and interesting techniques. We also discuss some applications to which our algorithms and techniques can be applied to yield efficient solutions.
Subregular Complexity and Deep Learning

This paper argues that the judicial use of formal language theory and grammatical inference are invaluable tools in understanding how deep neural networks can and cannot represent and learn long-term dependencies in temporal sequences. Learning experiments were conducted with two types of Recurrent Neural Networks (RNNs) on six formal languages drawn from the Strictly Local (SL) and Strictly Piecewise (SP) classes. The networks were Simple RNNs (s-RNNs) and Long Short-Term Memory RNNs (LSTMs) of varying sizes. The SL and SP classes are among the simplest in a mathematically well-understood hierarchy of subregular classes. They encode local and long-term dependencies, respectively. The grammatical inference algorithm Regular Positive and Negative Inference (RPNI) provided a baseline. According to earlier research, the LSTM architecture should be capable of learning long-term dependencies and should outperform s-RNNs. The results of these experiments challenge this narrative. First, the LSTMs' performance was generally worse in the SP experiments than in the SL ones. Second, the s-RNNs out-performed the LSTMs on the most complex SP experiment and performed comparably to them on the others.
Stochastic Volatility Models with Application in Option Pricing

In this paper, we develop a new method for pricing derivatives under stochastic volatility models by viewing the call price as an expected value of a truncated lognormal distribution under the risk neutral measure. We also obtain the formula for the estimate of the variance of the call price with the stochastic volatility. Using return data, we estimate the mean and variance of the stochastic volatility of the Black-Scholes model. An extensive empirical analysis of the European call option valuation for S & P 100 Index shows: (i) our method outperforms other compelling stochastic volatility pricing models, (ii) the pricing errors when using our method are quite small even though our estimation procedure is based only on historical return data. Formulas for option pricing and variances derivation for Heston’s (1993) continuous time stochastic volatility model and for Taylor’s (1973) discrete time stochastic volatility model are also discussed in some detail.
Non-Linear Price Transmission between Biofuels, Fuels and Food Commodities

For the biofuel markets and related commodities, we study their price transmission, which is in fact equivalent to studying price cross-elasticities. Importantly, we focus on the price dependence of the price transmission mechanism. Several methodological caveats are discussed. Specifically, we combine the memory robust feasible generalized least squares estimation with two-stage least squares to control for endogeneity bias and inconsistency. We find that both ethanol and biodiesel prices are responsive to their production factors (ethanol to corn, and biodiesel to German diesel). The strength of transmission between both significant pairs increased remarkably during the food crisis of 2007/2008. Causality tests further show that price changes in production factors lead the changes in biofuels even after controlling for price effects.
Nodal promotes the generation of M2‐like macrophages and downregulates the expression of IL‐12

Nodal, a member of the TGF‐β superfamily, is an embryonic morphogen that is upregulated in different types of tumors. Nodal increases the tumorigenesis by inducing angiogenesis and promoting metastasis. Importantly, Nodal inhibition suppresses the growth and invasion of tumor. Since tumor‐associated macrophages (TAMs) are the major infiltrating leukocytes in most cancers, we investigated whether Nodal is involved in the differentiation of TAMs. Our results revealed that Nodal inhibition in tumor microenvironment upregulated the production of IL‐12 in macrophages and reversed TAMs to classically activated macrophage phenotype. In contrast, treatment with recombinant Nodal (rNodal) decreased the expression of IL‐12 in murine macrophages. Furthermore, rNodal promoted macrophage polarization to an alternatively activated macrophage‐like/TAM phenotype and modulated its function. These results suggest that Nodal may play an important role in macrophage polarization and downregulation of IL‐12. The rescued antitumor function of TAMs via the inhibition of Nodal expression could be a new therapeutic strategy for cancer treatment.
Economic fluctuations and health outcome: a panel analysis of Asia-Pacific countries

The purpose of this study is to assess the effects of economic fluctuations on health outcome. By using data obtained from eight Asia-Pacific countries over the period 1976 to 2003 and a fixed-effects model to conduct the regression analysis, the results of this study indicate that unemployment rate is negatively and significantly correlated with total mortality and mortality rates from cardiovascular diseases, motor vehicle accidents and infant mortality. These findings are consistent with the view that health may improve during economic downturns. In addition, suicide is found to move countercyclically with economic fluctuations. Socioeconomic factors such as age and gender also play important roles in affecting the mortality rates. The results also show that unemployment has a stronger immediate and contemporaneous, rather than a sustained, effect on mortality rates. Finally, this study concludes that the effects of economic fluctuations on health outcome tend to lead to erroneous conclusions if the fixed-effects problems are neglected. The findings of this study shed some light on the link between economic fluctuations and health outcome and provide further international evidence on this issue.
Targeting Assay To Study the cis Functions of Human Telomeric Proteins: Evidence for Inhibition of Telomerase by TRF1 and for Activation of Telomere Degradation by TRF2

ABSTRACT We investigated the control of telomere length by the human telomeric proteins TRF1 and TRF2. To this end, we established telomerase-positive cell lines in which the targeting of these telomeric proteins to specific telomeres could be induced. We demonstrate that their targeting leads to telomere shortening. This indicates that these proteins act in cis to repress telomere elongation. Inhibition of telomerase activity by a modified oligonucleotide did not further increase the pace of telomere erosion caused by TRF1 targeting, suggesting that telomerase itself is the target of TRF1 regulation. In contrast, TRF2 targeting and telomerase inhibition have additive effects. The possibility that TRF2 can activate a telomeric degradation pathway was directly tested in human primary cells that do not express telomerase. In these cells, overexpression of full-length TRF2 leads to an increased rate of telomere shortening.
Compiling and Using a Shareable Parallel Corpus for Machine Translation Evaluation

TECMATE is a dynamic TEchnical Corpus for MAchine Translation Evaluation currently being compiled and used at the University of Leeds. A purpose-built corpus for machine translation (MT) evaluation differs in terms of size and content from corpora used for other kinds of linguistic analysis. For example, our research in automated MT evaluation requires source texts with human and machine translations as well as the scores for these translations given by human judges. These scores will allow us to test the reliability of experimental automated evaluation methods. Furthermore, a representative sample of machine translations annotated with fluency errors is also required to guide our research into automated error detection. In this paper, we summarise our rationale for corpus design and describe the different stages of corpus development. We provide an example of the content for one language pair and present findings from our recent evaluations of MT output using texts from the French-English sub-corpus. TECMATE will shortly be available online for research.
Enabling iterative software architecture derivation using early non-functional property evaluation

The structure of a software architecture strongly influences the architecture's ability to prescribe systems satisfying functional requirements, non functional requirements, and overall qualities such as maintainability, reusability, and performance. Achieving an acceptable architecture requires an iterative derivation and evaluation process that allows refinement based on a series of tradeoffs. Researchers at the University of Texas at Austin are developing a suite of processes and supporting tools to guide architecture derivation from requirements acquisition through system design. The various types of decisions needed for concurrent derivation and evaluation demand a synthesis of evaluation techniques, because no single technique is suitable for all concerns of interest. Two tools in this suite, RARE and ARCADE, cooperate to enable iterative architecture derivation and architecture property evaluation. RARE guides derivation by employing a heuristics knowledge base, and evaluates the resulting architecture by applying static property evaluation based on structural metrics. ARCADE provides dynamic property evaluation leveraging simulation and model-checking. This paper presents a study whereby RARE and ARCADE were employed in the early stages of an industrial project to derive a Domain Reference Architecture (DRA), a high-level architecture capturing domain functionality, data, and timing. The discussion emphasizes early evaluation of performance qualities, and illustrates how ARCADE and RARE cooperate to enable iterative derivation and evaluation. These evaluations influenced DRA refinement as well as subsequent design decisions involving application implementation and computing platform selection.
Effects of caffeine ingestion on rating of perceived exertion during and after exercise: a meta‐analysis

The purpose of this study was to use the meta‐analytic approach to examine the effects of caffeine ingestion on ratings of perceived exertion (RPE). Twenty‐one studies with 109 effect sizes (ESs) met the inclusion criteria. Coding incorporated RPE scores obtained both during constant load exercise (n=89) and upon termination of exhausting exercise (n=20). In addition, when reported, the exercise performance ES was also computed (n=16). In comparison to placebo, caffeine reduced RPE during exercise by 5.6% (95% CI (confidence interval), −4.5% to −6.7%), with an equivalent RPE ES of −0.47 (95% CI, −0.35 to −0.59). These values were significantly greater (P<0.05) than RPE obtained at the end of exercise (RPE % change, 0.01%; 95% CI, −1.9 to 2.0%; RPE ES, 0.00, 95% CI, −0.17 to 0.17). In addition, caffeine improved exercise performance by 11.2% (95% CI; 4.6–17.8%). Regression analysis revealed that RPE obtained during exercise could account for ∼29% of the variance in the improvement in exercise performance. The results demonstrate that caffeine reduces RPE during exercise and this may partly explain the subsequent ergogenic effects of caffeine on performance.
Analysis and Design of Graphene-Based Surface Plasmon Waveguide Switch at Long-Wavelength Infrared Frequencies

A graphene-based surface plasmon (SP) waveguide switch is designed at near infrared frequencies. First, graphene is modeled in electronic and electromagnetic solvers, in order to use graphene strips for designing the waveguide. Because of finite size of these strips, propagating surface plasmon polaritons (SPPs) along them exhibit spatial dispersion. By considering this and shifting interband losses to higher frequencies (by doping the graphene strips), the waveguide switch is designed to operate at 30 THz. In this paper, chemical potential in the graphene strips is controlled through applying back and top gate voltages which provide a reconfigurable waveguide switch and the chemical potentials of the strips are changed so that ultra-confinement and extremely low-loss propagation are achieved. The designed switch provides extremely low return loss and ultra-bandwidth in 30--40 THz frequency range. Due to the spatial dispersion in the graphene strips, new procedures are proposed to calculate the return and insertion losses of the switch and also absorbed power in the graphene strips.