Miracle-dz/UniFAR-FTUs huggingface dataset:
17beta‐estradiol protects oligodendrocytes from cytotoxicity induced cell death

During pregnancy, changes in circulating levels of hormones, including estrogens, correlates with a significant decrease in the relapse incidence in women with Multiple Sclerosis (MS). In the present study, we demonstrate that both primary and cell line cultures of rat oligodendrocytes express the estrogen receptor (ER)‐α and ERβ estrogen receptors in the cytosol and nucleus, and that nuclear compartmentalization becomes more pronounced as the cells mature. Moreover, 17β‐estradiol significantly decreases the cytotoxic effects of the peroxynitrite generator 3‐(4‐morpholinyl)‐sydnonimine (SIN‐1) in both immature and mature oligodendrocytes in a dose dependent manner. This protective mechanism requires pretreatment with 17β‐estradiol and is blocked by ICI 182,780, a selective ERα/ERβ antagonist. These results strongly suggest that 17β‐estradiol protects oligodendrocytes against SIN‐1 mediated cytotoxicity through the activation of the estrogen receptors and provides new insights into the roles of the estrogen signaling pathways in myelin forming cells that are lost in demyelinating disorders.
Variations in nicotine yields between single cigarettes.

INTRODUCTION AND AIMS It is beyond any doubt that nicotine yield in cigarettes as determined using standard ISO method bears almost no relation to smokers' actual intake. However, the ISO method is still in use in many countries where the government is responsible for controlling and monitoring cigarette quality. The aim of the study was to measure the nicotine yield in single cigarettes and to evaluate their statistical distribution among the same brand. MATERIALS AND METHODS Nicotine yields were measured according to the ISO method in single cigarettes of the twenty most popular Polish brands of cigarettes. RESULTS Relative standard deviation of nicotine yields in single cigarettes of the same brands varied from 16% to 34%. Relative differences between nicotine yields in a single cigarette of a particular brand and the mean value varied from -65% to +76%. DISCUSSION AND CONCLUSIONS The results indicate high variation in nicotine yields between cigarettes of the same brand. Such variation might affect compensatory smoking. This provides another reason why yields estimated using the standard ISO method are potentially misleading to smokers. Further studies are needed to better understand the implications of within-brand variability in yields for tobacco product regulation.
Dividend taxation and household dividend portfolio decisions: evidence from the U.S. Jobs and Growth Tax Relief Reconciliation Act of 2003

ABSTRACT This study examines the dividend clientele hypothesis by focusing on the preferential tax treatment of qualified dividends provided by the 2003 Jobs and Growth Tax Relief Reconciliation Act (JGTRRA) in the United States. Using the Public Use Tax File data, the author finds that the ratios of dividends to long-term capital gains before the 2003 tax act significantly declined with household tax rate differentials between dividends and long-term capital gains, but such a negative tax effect on the ratios disappears afterwards. This seemingly tax-inefficient composition of dividends and long-term capital gains after the tax act arises from households’ ability to reduce their tax burdens on stocks by exploiting the new preferential tax treatments on qualified dividends under JGTRRA. That is, households in the upper tax bracket hold significantly greater shares of qualified dividends relative to ordinary dividends after the tax act.
Career Paths in Institutional Business Elites: Finnish Family Firms from 1762–2010

This article analyzes the career paths of family business executives in institutional business elites in Finland using an empirical database based on a Bourdieusian prosopographical approach. The results indicate that career paths became more complex but shortened in length toward the beginning of the twenty-first century. The early career paths of family executives changed from positions as assistants and salesmen in the eighteenth and nineteenth centuries to governance, chief executive officer (CEO), and management positions in the twentieth and twenty-first centuries. Compared with the founder generation, next-generation family members benefited from more rapid institutional business elite career paths. The complexity of the career paths in the institutional business elite increased in subsequent generations. However, although there were few family executives with a third- or fourth-generation background in family businesses, founder-generation family executives existed in each cohort, apart from the pioneering generation.
Persistence in the price-to-dividend ratio and its macroeconomic fundamentals

Persistent variations in the log price-to-dividend ratio (PtDR) have triggered a lively discussion in the literature. This paper proposes a present value model incorporating this persistence through a time-varying steady state of the PtDR. Log-likelihood statistics confirm that the time-varying state model outperforms its counterpart with a constant steady state. It is shown that the steady state of the PtDR is jointly influenced by consumption risk, risking sharing, and the demographic structure. Among those consumption risk is the dominating factor in shaping the variations in the steady state of the PtDR throughout the entire last century.
Stacked low-power field-programmable antifuse memories for RFID on plastic

We demonstrate a stacked antifuse-based field-programmable memory utilizing organic materials on plastic to enable applications such as the encoding of low-cost RFID tags. We demonstrate 2 stacked levels with 100 bits/level, delivering excellent read margins and disturb immunity. These devices show high-speed programming capability (25ns) and ultra-low programming energy requirements of <1nW/bit. This technology is therefore extremely promising for plastic electronics applications
The development and researching of lightweight pseudorandom number generators

The paper is devoted to the development and quality assessment of lightweight pseudo-random number generators (PNRG). The design principles of lightweight PRNG (LW-PNRG) are described. The requirements for LW-PNRG quality are formulated. This paper gives an example of the transformation of a classical generator into LW-PNRG by means of modifying the function of feedback (OFB). We propose methods of assessing the quality of pseudo-random numbers formed by lightweight generator. The results of statistical tests of the developed LW-PNRG are also given.
Precoding for Uplink Distributed Antenna Systems With Transmit Correlation in Rician Fading Channels

In this paper, we develop an optimal precoder and a suboptimal precoder for uplink distributed antenna systems with transmit correlation over Rician channels. The objective is to minimize a pairwise error probability (PEP) with constrained transmit power. The optimal scheme uses an efficient projection-based steepest descent algorithm to obtain the Gram matrix of the precoder, while the suboptimal scheme exploits the eigen-structure of the Gram matrix to obtain its unitary matrix (beamforming) and eigenvalues (power control). For a given beamforming (BF), an efficient power adaptation based on a fuzzy signal-to-noise ratio (SNR) is developed. The PEP analysis at low SNR is used to obtain a suboptimal BF. The derived BF and the fuzzy power adaptation have closed-form expressions that make the suboptimal scheme computationally efficient in comparison with existing methods. The BF can be re-optimized via the Riemannian steepest descent method to further reduce the PEP. Simulation results show that the proposed optimal scheme not only gives the performance the same as the existing optimal scheme when the latter can converge, but it also has lower computational complexity and faster convergence. Moreover, the suboptimal scheme can give a nearly optimal error rate.
Advances in Smartphone-Based Point-of-Care Diagnostics

Point-of-care (POC) diagnostics is playing an increasingly important role in public health, environmental monitoring, and food safety analysis. Smartphones, alone or in conjunction with add-on devices, have shown great capability of data collection, analysis, display, and transmission, making them popular in POC diagnostics. In this article, the state-of-the-art advances in smartphone-based POC diagnostic technologies and their applications in the past few years are outlined, ranging from in vivo tests that use smartphone's built-in/external sensors to detect biological signals to in vitro tests that involves complicated biochemical reactions. Novel techniques are illustrated by a number of attractive examples, followed by a brief discussion of the smartphone's role in telemedicine. The challenges and perspectives of smartphone-based POC diagnostics are also provided.
Outcome in Two Groups of Patients with Allograft-Prosthetic Reconstruction of Pelvic Tumor Defects

To predict the outcomes obtained with allograft-implant composite reconstruction of pelvic defects after bone tumor resection better, a retrospective review of a prospectively collected database was done and two groups of patients were identified. These groups were compared with respect to oncologic and functional outcomes in this investigation. Group 1 included 21 patients with allograft total hip replacement reconstruction for pelvic bone tumors that required Type I and II or Type I, II, and III pelvic resections. Group 2 included five patients who required an acetabular allograft in combination with proximal femoral replacement for reconstruction of Type II pelvic resections done to treat proximal femoral bone sarcomas that invaded or surrounded the hip joint. Functional assessment was measured with three instruments (Toronto Extremity Salvage Score, Musculoskeletal Tumor Society 1987, and the Musculoskeletal Tumor Society 1993 scores). In Group 1, nine of 19 evaluable patients (two patients died in the immediate postoperative period) either retained the allograft until their death or were still alive at last followup with their allograft in place. An additional patient had revision surgery to an allograft-saddle composite that remains intact. The functional results in Group 1 were influenced heavily by the occurrence of deep infection. Nine of 19 evaluable patients developed infection, with seven patients requiring either removal of the graft (three patients) or hindquarter amputation (four patients). Two patients retained their infected allografts with long-term antibiotic suppression. In 10 Group 1 patients who did not develop infection, reasonable functional results were obtained. Group 2 patients had no infections and better functional results. Level of Evidence: Therapeutic study, Level IV-1 (case series). See the Guidelines for Authors for a complete description of levels of evidence.
Smart interface for reshaping photos in 3D

In this work we present an interactive prototype for an interface that supports the interaction with virtual objects integrated in a real life scenario. The user can reshape or re-design a real space with virtual objects using several pictures of the desired space. The images are analyzed for known features such as surfaces, edges, floor location and room orientation. Using these elements, it is possible to devise an augmented reality system where the user can add virtual objects to the scenario. The smart interface attaches the objects to the scene elements (e.g., floor) automatically. The current demo loads images from user files or takes a snapshot directly from the camera. The high-level features are automatically detected, but can be manually adjusted. A use-case example of an augmented reality application is presented.
A neural network that explains as well as predicts financial market behavior

When a neural network makes a financial prediction, the user may benefit from knowing which previous time periods are illustrative of the current time period. The authors describe a high-performance neural network that in addition to predicting stock market direction, allows the user to visualize the relationship between current conditions and previous conditions that led to similar predictions. Visualization is accomplished by forming a gated multi-expert network using funnel-shaped multilayer dimensionality reduction networks. The neck of the funnel is a two-neuron layer that displays the training data and the decision boundaries in a two-dimensional space. This architecture facilitates a) interactive design of the decision functions and b) explanation of the relevance of past decisions from the training set to the current decision. They describe a stock market prediction system whose design incorporates a visual neural network for prediction, wavelet transforms and tapped delay lines for feature extraction, and a genetic algorithm for feature selection. This system shows that the visual neural network provides the low error rates (i.e., accurate predictions) of multi-expert networks along with the visual explanatory power of nonlinear dimensionality reduction.
Predictive Ability Of Alternative Performance Measurement Models

The variance data generated by a traditional standard cost system are thought to provide useful measures of performance for a variety of purposes [5, 19]. However, there are alternative methods of computing variances so that management is faced with the problem of choosing an optimum method. In making a choice, the issue of operational' selection criteria naturally arises. At a conceptual level, we should select that alternative which results in the highest possible goal attainment for the firm. Unfortunately, operational use of this criterion requires explicit knowledge of the firm's goals and decision processes. Because neither is explicitly known, we must evaluate managerial accounting alternatives with a set of surrogate evaluators. One such surrogate, predictive ability, is used in this paper to assess three alternative costing models that management may use-direct costing, absorption costing, and an ex post optimum model.
Synergies and differences in mathematical and computational thinking: implications for integrated instruction

ABSTRACT A key debate in computer science education is whether and how computational thinking (CT) is used within disciplines other than computer science. Broad definitions provide many avenues for developing integrated instruction, as practices within existing activities can simply be reframed in terms of CT. But such general use of the term CT may confuse its meaning and dilute its power as a tool for bringing CS to all. In this paper, we take the viewpoint that mathematical thinking and computational thinking share common practices, such as using repetition to accomplish tasks, but these shared ideas may develop differently in mathematics and computer science. We use document analysis to analyze the K-5 Common Core State Standards for Mathematics for the presence of these common practices and describe the specific ways they develop in mathematics. We compare these elements of mathematical thinking to related elements of CT to identify synergies and differences between CT and mathematical thinking. We argue that these synergies and differences have implications for the development of integrated instruction designed to bring CS to all.
Politics and environmental policy: theory and evidence from U.S. states

We develop a two dimensional political agency model, which is in the spirit of the political agency literature. A politician, who faces peridic elections, has to decide on the level of public spending and an environmental regulation. We introduce a term limit into this model and develop the predictions of the model for the differences in envrionmental policy between years in which the politician does and does not face a binding term limit. These predictions are tested on panel data on environmental policy choices of US governors for the years 1960-98.
Discriminant Analysis, Classification Results, and Financially Distressed P-L Insurers

Several recent insurance studies [3, 8, 21, 24] have employed multiple discriminant analysis in an attempt to identify important predictor variables and to reclassify the original observations into one of two known groups. The purpose of this paper is to examine the impact of three separate factors influencing classification results obtained from discriminant analysis-multivariate normality, equality of the variance/covariance matrices and misclassification error rates. In order to focus on the potential impact of these three factors, the authors assume that the priori probabilities of group membership are equal as are the costs of misclassification, and that the specific predictor variables have already been determined. ' Data from the previous Trieschmann-Pinches (T-P) study [24] are analyzed to illustrate the impact of these three factors on the classification results. The important objectives of this paper are twofold: first, to illustrate that it is possible to get many different classification results from the same discriminant model, and second, to provide a review of the present knowledge available on the impact of non-multivariate normality, unequal covariance matrices, and different misclassification error rates on classification results obtained when multiple discriminant analysis is employed.
Application of Nonparametric Quantile Regression to Estimating Value at Risk.

LI, WANYING. Application of Nonparametric Quantile Regression to Estimating Value at Risk. (Under the direction of Peter Bloomfield.) Value-at-Risk (VaR), a widely used measure in risk management and portfolio valuation in many financial institutions, is the conditional quantile of the return distribution given the past information. Because financial time series data usually have a non-Gaussian conditional distribution, quantile regression has become very popular in VaR estimation due to its advantage of being distribution free. Especially since the CAViaR model introduced by Engle and Manganelli (2004), it has attracted much attention because the model takes a recursive fashion like GARCH model: instead of recursively regressing on volatilities, it regresses on implicit quantile functions. My work suggests to use additive smoothing splines / regression splines to approximate the unknown quantile functions. In fact, my model can also be considered as a generalized form of a class of well-studied models, e.g. TS-GARCH. Under certain assumptions, the estimation can be obtained by a two-stage procedure, including solving a modified nonparametric quantile regression problem and optimizing a nonlinear function over Rn space (usually n = 1). On selecting the best smoothing parameter, we suggest to use SIC as the criterion for our model by a simulation study, because SIC can perform almost as well as Gold Criterion (defined as minimum expected prediction error) at 5% level and relatively better than improved-AIC at both 5% and 1% levels. The proposed models are implemented on S&P 500 and IBM stock prices to estimate 5% and 1% VaR and the performance of the estimations are especially satisfactory with recursive smoothing splines. c © Copyright 2011 by Wanying Li All Rights Reserved Application of Nonparametric Quantile Regression to Estimating Value at Risk
MARKET-BASED EMPIRICAL-RESEARCH IN ACCOUNTING - A REVIEW, INTERPRETATION, AND EXTENSION

A decade and a half of the most concerted and ambitious research effort in accounting history is evaluated here. It is the search into the relationship between publicly disclosed accounting information and the consequences of the use of this information by the major group of usersequity investors-as such consequences are reflected in characteristics of common stocks traded in major exchanges. This research effort, known as "market-based accounting research" (MBAR), obtained its impetus from major developments in finance theory during the late 1950s and early 1960s. These were the portfolio selection theory and its offspring, the capital asset pricing model (CAPM); and the concept of informationally efficient capital markets (ECM). Subsequent developments in information economics, agency theory, and optimal incentive-signaling models were quickly incorporated into MBAR. While the impetus to this line of research came from other disciplines, accounting was not only a beneficiary but also, to a modest extent, a benefactor. MBAR is relevant to the study of capital market efficiency, the CAPM, information economics, and regulation. This contribution distinguishes MBAR from most accounting areas, whose contributions to other disciplines are negligible. In
Networks in the Disaster Response and Global Health Domain: A case study of The Partnership for Quality Medical Donation's response to the 2010 Haitian Earthquake

The 2010 Haitian earthquake underscored the fact that disaster response is increasingly complex, multi-sectoral and multi-faceted in character. Nonetheless, disaster relief operations both globally and nationally tend to operate within a highly fragmented context in which potentially overwhelming human and infrastructure needs must be served by limited material and financial aid delivered by disparate humanitarian actors specializing in varying functional domains. Such a chaotic environment demands highly effective communication, collaboration and coordination among a variety of humanitarian actors if relief efforts are to be successful. Even though the coordination mechanisms of multi-organizational actors during disaster response have been studied in a variety of contexts, much less attention has been paid to how international non-governmental (INGOs) and private sector actors may be able to operate collaboratively in disaster settings. This dissertation provides a case analysis of the efforts of one set of cross-sectoral humanitarian actors that worked through a network in response to the 2010 Haitian earthquake. This mixed methods case study incorporates interview, personal observation, and survey data from INGO field staff, headquarters personnel, and corporate donor representatives, all of whom were members of the cross-sectoral Partnership for Quality Medical Donation (PQMD) that responded to the 2010 Haitian earthquake. The inquiry explores what the coordination-related challenges to disaster response are for network members and then examines whether and in what ways a cross-sector network, PQMD in this instance, can effectively mitigate or overcome those obstacles. This study contributes to the body of disaster coordination and cross-sector network scholarship in two ways. First, the analysis reviews prevailing trends within the cross-sector network and disaster coordination-related literature concerning the requisites and challenges of coordination in humanitarian relief emergencies. Second, this study augments existing understanding of the extremely complex processes involved in coordinating INGO-business disaster response as part of efforts to mobilize multi-sectoral humanitarian action. This research suggests that efforts to develop cross-sector networks prior to disaster events can build communication, collaboration and coordination pathways that later enhance coordinated INGO-business disaster response to crises. It argues that current theoretical horizons in both network and disaster coordination studies need to be broadened. Specifically, this inquiry highlights the importance of incorporating cross-sector networks (i.e., INGO and corporate actors) into all planning efforts aimed at enhancing collaboration and coordination practices in disaster relief.