Miracle-dz/UniFAR-FTUs huggingface dataset:
Concise review of the cytochrome P450s and their roles in toxicology.

The cytochrome P450s are hemoproteins that play critical roles in the bioactivation and detoxication of a wide variety of xenobiotic substances. The enzymes are encoded by a superfamily of genes. The term “cytochrome P450” originates from the observation that the reduced state of the proteins form complexes with carbon monoxide that exhibit absorbance maxima at 450 nm (Omura and Sato, 1964). The P450 enzymes are now referred to as heme-thiolate proteins. P450s have been characterized in many species of organisms, including bacteria, fungi, plants, fish, and mammalian systems (Nebert and McKinnon, 1994). In mammalian cells, P450s are localized predominantly in the smooth endoplasmic reticulum of the cell and are entirely distinct from the cytochrome proteins that comprise the mitochondrial electron-transport function. Currently, . 700 P450s have been characterized, inclusive of the many different species of organisms that have been studied (Nelson et al., 1996). Based primarily on sequence similarities, a standardized nomenclature has been adopted that categorizes the individual P450s into respective families and subfamilies. P450 proteins exhibiting . 40% similarity in protein sequence are classified within the same family; proteins exhibiting . 55% sequence similarity are grouped into the same subfamily (Nebert and McKinnon, 1994; Nelson et al., 1996). Although the catalog is updated regularly, the current P450 nomenclature and classification scheme was most recently reviewed in 1996 (Nelson et al., 1996). The purpose of this current review is to very briefly highlight some of the more important mammalian P450s with respect to their expression, inducibility and inhibition character, and substrate preferences, especially as they relate to human toxicology. Due to this limited scope, it is impossible to thoroughly reference all the important and relevant literature pertaining to this topic. The reader is referred to other recent reviews for more detailed information (Dogra et al., 1998; Meyer and Zanger, 1997; Pelkonen and Raunio, 1997; Rendic and Di-Carlo, 1997). Information from these and other references has been used as source material to compile the contents of Table 1, summarizing some of the salient features of several relevant P450s.
Executive Stock Option Plans and Incentives to Take Risk in Levered Firms : Equity Value or Firm Value Maximization ?

Financial leverage does not distort investment decisions if executives are paid to maximize total firm value rather than equity value. Existing models of this idea imply that stock-based incentives should be negatively related to firm leverage, a prediction that has little empirical support. We show that the distortions induced by financial leverage can be overcome without diluting effort incentives by adjusting the exercise price of executive stock options. We also show that the common practice of granting options at-the-money to a large degree implements this solution. We then empirically examine the risk incentives of executive stock option plans in a large sample of Canadian firms. We find evidence that executives’ stock options mitigate the risk-taking incentives of shareholders in levered firms. JEL Classification Numbers G32, D23, J33
120-GHz-band Low-noise Amplifier with 14-ps Group-delay Variation for 10-Gbit/s Data Transmission

This paper presents a 120-GHz-band low-noise amplifier (LNA) for a receiver microwave monolithic integrated circuit (MMIC), which is used for a 10-Gbit/s wireless link. The LNA was designed for low-noise performance, a high gain, and low group-delay variation. To achieve enough stability with low-noise performance and low group-delay variation, we introduce a new stabilizing circuit consisting of two coplanar-waveguide stubs. The LNA MMIC was fabricated using 0.1-mum-gate InP high-electron-mobility transistors (HEMTs). We integrated the LNA into a WR-8 (90-140 GHz) waveguide module and evaluated it. The LNA module achieved an averaged noise figure of 5.6 dB, a gain of >19.5 dB, and group-delay variation of <14 ps from 117.5 to 132.5 GHz.
ASR domain adaptation methods for low-resourced languages: Application to Romanian language

This study investigates the possibility of using statistical machine translation to create domain-specific language resources. We propose a methodology that aims to create a domain-specific automatic speech recognition system for a low-resourced language when in-domain text corpora are available only in a high-resourced language. We evaluate a new semi-supervised method and compare it with previously developed semi-supervised and unsupervised approaches. Moreover, in the effort of creating an out-of-domain language model for Romanian, we introduce and experiment an effective diacritics restoration algorithm.
Regulation Fe 65 localization to the nucleus by SGK 1 phosphorylation of its Ser 566 residue

Eun Jeoung Lee, Jaesun Chun, Sunghee Hyun, Hye Rim Ahn, Jae Myung Jeong, Soon-Kwang Hong, Jin Tae Hong, In Kyeong Chang, Hye Yeon Jeon, Yeon Soo Han, Chung-Kyoon Auh, Jae In Park & Sang Sun Kang* School of Science Education, Chungbuk National University, Cheongju, Department of Biological Education, Korea National University of Education, Cheongwon, Department of Premedicine, Eulji University School of Medicine, Daejeon, Division of Life Science, Myungji University, Yongin, Department of Pharmacy, Chungbuk National University, Cheongju, Department of Agricultural Biology, Chonnam National University, Gwangju, Division of Applied Biotechnology, Mokpo National University, Muan, Department of Forest Science, Chungbuk National University, Cheongju, Korea
Lévy Processes in Finance: Theory, Numerics, and Empirical Facts

Preface Lévy processes are an excellent tool for modelling price processes in mathematical finance. On the one hand, they are very flexible, since for any time increment ∆t any infinitely divisible distribution can be chosen as the increment distribution over periods of time ∆t. On the other hand, they have a simple structure in comparison with general semimartingales. Thus stochastic models based on Lévy processes often allow for analytically or numerically tractable formulas. This is a key factor for practical applications. This thesis is divided into two parts. The first, consisting of Chapters 1, 2, and 3, is devoted to the study of stock price models involving exponential Lévy processes. In the second part, we study term structure models driven by Lévy processes. This part is a continuation of the research that started with the author's diploma thesis Raible (1996) and the article Eberlein and Raible (1999). The content of the chapters is as follows. In Chapter 1, we study a general stock price model where the price of a single stock follows an exponential Lévy process. Chapter 2 is devoted to the study of the Lévy measure of infinitely divisible distributions, in particular of generalized hyperbolic distributions. This yields information about what changes in the distribution of a generalized hyperbolic Lévy motion can be achieved by a locally equivalent change of the underlying probability measure. Implications for option pricing are discussed. Chapter 3 examines the numerical calculation of option prices. Based on the observation that the pricing formulas for European options can be represented as convolutions, we derive a method to calculate option prices by fast Fourier transforms, making use of bilateral Laplace transformations. Chapter 4 examines the Lévy term structure model introduced in Eberlein and Raible (1999). Several new results related to the Markov property of the short-term interest rate are presented. Chapter 5 presents empirical results on the non-normality of the log returns distribution for zero bonds. In Chapter 6, we show that in the Lévy term structure model the martingale measure is unique. This is important for option pricing. Chapter 7 presents an extension of the Lévy term structure model to multivariate driving Lévy processes and stochastic volatility structures. In theory, this allows for a more realistic modelling of the term structure by addressing three key features: Non-normality of the returns , term structure movements that can only be explained by multiple stochastic factors, and stochastic …
Self-empowering to maintain and enhance personal identity as an older adult with depression

Australians have one of the longest life expectancies in the world, but up to 15% of older Australians living at home experience depression. Increasing attention is being paid to understanding the clinical aspects of depression in older age. However, less is known about how older Australians living in the community experience and self-manage depression, and the factors that influence these processes. The purpose of this qualitative grounded theory study was to explicate the self-management strategies used by older adults diagnosed with depression to optimise their well-being. Data collection and analysis were informed by Corbin and Strauss’ (2015) approach to grounded theory. Data were collected through 32 individual interviews, observations and questionnaires. The key conceptual findings of the study comprise a core problem, a core category and three related categories. The basic social psychological problem was conceptualised as Struggling to maintain personal identity as an older adult with depression. The core category, Self-empowering to maintain and enhance personal identity as an older adult with depression, was abstracted through simultaneous data collection and analysis, and constant comparison. This goal was achieved through the three interlinked strategies of Taking Stock, Accessing Support and Reclaiming Self-identity. Participants’ efforts were influenced by three contextual determinants: Perspectives on age and depression influencing help-seeking, Ability to navigate and access the health care system, and Individual capacity for self-management. When drawn together, these elements comprise a substantive theory that reflects a shift from a narrow biomedical discourse of depression in older age to a broader experiential focus on individuals as experts for managing long-term conditions. The findings of this study have implications relating to policy, professional practice, the portrayal of age and depression, older adults and their significant others, and future research.
A COMBINED FORECASTING METHOD OF WIND POWER CAPACITY WITH DIFFERENTIAL EVOLUTION ALGORITHM

As wind power is a mature and important renewable energy, wind power capacity forecasting plays an important role in renewable energy generation’s plan, investment and operation. Combined model is an effective load forecasting method; however, how to determine the weights is a hot issue. This paper proposed a combined model with differential evolution optimizing weights. The proposed model can improve the performance of each single forecasting model of regression, BPNN and SVM. In order to prove the effectiveness of the proposed model, an application of the China’s wind power capacity was evaluated from 2000 to 2010. The experiment results show that the proposed model gets the maximum mean absolute percentage error (MAPE) value 1.791%, which is better than the results of regression, BPNN and SVM.
Evaluating Machine Translation Utility via Propbank Annotation Semantics

We present the methodology that underlies mew metrics for semantic machine translation evaluation we are developing. Unlike widely-used lexical and n-gram based MT evaluation metrics, the aim of semantic MT evaluation is to measure the utility of translations. We discuss the design of empirical studies to evaluate the utility of machine translation output by assessing the accuracy for key semantic roles. These roles can be represented by the Propbank annotation (ARG0, ARG1, ., ARGM-ADV, ., etc.) by Palmer et al. (2005) and Xue and Palmer (2005). Recent work by Wu and Fung (2009b) introduced semantic role labeling into statistical machine translation to enhance the quality of MT output. However, this approach has so far only been evaluated using lexical and n-gram based SMT evaluation metrics like BLEU which are not aimed at evaluating the utility of MT output. Direct data analysis are still needed to understand how semantic models can be leveraged to evaluate the utility of MT output. In this paper, we discuss a new methodology for evaluating the utility of the machine translation output, by assessing the accuracy with which human readers are able to complete the Propbank annotation templates.
Fractional branes and wrapped branes

We discuss the ``fractional D-branes'' which arise in orbifold resolution. We argue that they arise as subsectors of the Coulomb branch of the quiver gauge theory used to describe both string theory D-brane and Matrix theory on an orbifold, and thus must form part of the full physical Hilbert space. We make further observations confirming their interpretation as wrapped membranes.
Prescribed Performance Adaptive Control for Multi-Input Multi-Output Affine in the Control Nonlinear Systems

We consider the tracking problem of unknown, robustly stabilizable, multi-input multi-output (MIMO), affine in the control, nonlinear systems with guaranteed prescribed performance. By prescribed performance we mean that the tracking error converges to a predefined arbitrarily small residual set, with convergence rate no less than a prespecified value, exhibiting maximum overshoot as well as undershoot less than some sufficiently small preassigned constants. Utilizing an output error transformation, we obtain a transformed system whose robust stabilization is proven necessary and sufficient to achieve prescribed performance guarantees for the output tracking error of the original system, provided that initially the transformed system is well defined. Consequently, a switching robust control Lyapunov function (RCLF)-based adaptive, state feedback controller is designed, to solve the stated problem. The proposed controller is continuous and successfully overcomes the problem of computing the control law when the approximation model becomes uncontrollable. Simulations illustrate the approach.
Power aware and high speed reconfigurable modified booth multiplier

Multiplier is one of the major arithmetic operations carried out in DSP applications. Multiplier architecture is reconfigured so as to enhance their performance and thereby improving the efficiency of the applications. This Reconfigurable multiplier is adapted at run time to satisfy multiple precision requirements of DSP applications. Power consumption of the multipliers is reduced with the introduction of power efficient scheme Dynamic Operand Interchange to the reconfigurable booth architecture. Implementation is done in Verilog and simulated using MODELSIM. Power and Timing analysis is done using Altera Quartus II tool (version 9.0)
Issues and Trends in Special Education: Implications for School Psychologists.

School psychologists' expertise and services have been important in student identification and program eligibility for students with disabilities. During the early 1990's, several factors, conditions, and trends luggest that special education will soon undergo seminal changes and psychologists must stand ready for this transformation. This paper identifies and analyzes selected conditions, controversies, and trends--in the field of special education and U.S. society as a whole--which will profoundly influence the future of special education in the nation's schools. Student enrollment in these programs has increased dramatically and with this expansion come issues of costs, defining at-risk students, the role of the Regular Education Initiative, and other importaut issues. Discussed with these conditions are the attendant changes in the roles and responsibilities of school psychologists along with recommentations on how they can become most effectively involved in special education's transitional period. Psychologists can help educators sort out many of the critical issues involving the complex relationsLips between students identified as having traditional disabilities and those students who do not qualify for special education sel.vices but who still are considered to be at risk. (Contains 36 references.) (LIM) *********************************************************************** * Reproductions supplied by EDRS are the best that can be made * * from the original document. * ************i. **********************************************************
Modeling and Verification of Space-Air-Ground Integrated Networks on Requirement Level Using STeC

This paper introduces a domain Spatio-Temporal Consistency (STeC) language for the application domain of space-air-ground integrated networks. The STeC language is taken as the foundation of modeling our systems, bacause it works well on specifying real-time systems concerning not only the time characteristic but also the location characteristic and the consistency between them. In this paper, a domain-STeC language is devised and applied to model satellite observation processes. We use two tools to check and verify this STeC model, the syntax and spatio-temporal consistency were checked in STeC tool, and after being transformed into timed automata model, some further verification can be finished in UPPAAL tool. It shows that the instantiated STeC approach is suitable for modeling and verifying space-air-ground integrated networks on the requirement level. This work helps to ensure the spatial-temporal consistency in that application domain, and increases the reliability and dependability of our system.
DESIGN OF PRE-PROCESSED CROSS LAYERED ADAPTIVE MODULATION FOR MIMO-OFDM RECEIVER ARCHITECTURE 1

Modern wireless communication applications are characterized by the need for advanced signal processing techniques such as Multiple-Input Multiple-Output (MIMO) technology for achieving high throughput and diversity and Orthogonal Frequency Division Multiplexing (OFDM) for achieving robustness to fading. This paper introduces techniques that increase the throughput, reduces preprocessing delay and thereby increases the overall spectral efficiency of any wireless communication system; including mobile adhoc networks and wireless sensor networks. An efficient preprocessed cross-layer adaptive modulation and coding (AMC) design for MIMO–OFDM systems, that combines the AMC at the physical layer with an automatic repeat request (ARQ) protocol at the data link layer, to maximize spectral efficiency under specified delay and packet error ratio (PER) constraints is developed and presented in this paper. We propose PLU channel decomposition replacing the widely used QR decomposition to achieve a better matching of the processing rate of MIMOOFDM receivers to the real-time processing deadlines imposed by the structure of the incoming data packets. The modulation and encoding techniques for each subcarrier derived from the result of preprocessing is updated frame-byframe to match the time-varying channel conditions. The proposed cross-layer AMC design is incorporated with preprocessing algorithm so as to further improve the system performance. In the event of occurrence of errors, the retransmission at the data link layer alleviates rigorous errorcontrol requirements at the physical layer and thereby allows higher data rate transmission. This results in a desirable tradeoff between spectral efficiency and delay in the MIMO– OFDM system achieved by only a smaller number of retransmissions.
Convergence behaviour of structural FSM traversal

We present a theoretical analysis of structural FSM traversal, which is the basis for the sequential equivalence checking algorithm Record & Play presented earlier [16]. We compare the convergence behaviour of exact and approximative structural FSM traversal with that of standard BDD-based FSM traversal. We show that for most circuits encountered in practice exact structural FSM traversal reaches the fixed point as fast as symbolic FSM traversal, while approximation can significantly reduce in the number of iterations needed. Our experiments confirm these results.
Cost optimization in cloud provisioning using Particle Swarm Optimization

A cloud technology has emerged as a prominent workflow computing infrastructure. The need arises to optimize the allocation of resources to cloud provider's customers. An appropriate number of VMs must be created along with the allocation of supporting resources. Moreover, commercial clouds may have many different purchasing options. Finding optimal provisioning solutions is thus an NP-hard problem. Currently, there are many research works discussing the cloud provisioning cost optimization. However, most of the works mainly concerned with task scheduling. In this paper, we proposed a new framework where number of purchased instance, instance type, purchasing options, and task scheduling are considered within an optimization process. In order to identify a solution in a reasonable amount of time, we studied the use of Particle Swarm Optimization (PSO) technique. The decoding scheme is also designed to convert real values in PSO's particles into an integer representing a solution. The initial results show a promising performance in both the perspectives of the total cost and fitness convergence. We believe that our system will be useful in purchasing options decision. Budget can also be accurately estimated for any specified workflow-based application. We believe that the work will benefit the on-demand provisioning of the virtualized resources as a service in the near future.
THE VALIDITY OF TRADITIONAL AND VALUE BASED MEASURES IN EXPLAINING EQUITY PRICES IN THE EMERGING STOCK MARKET OF SRI LANKA

Capital Market Based Accounting Researches (CMBAR) have been very much popular since late 60s. However,most of the studies were based on developed capital markets like US, UK and Australia. On the other hand, most of them were conducted on traditional accounting measures (TAMs) based valuation model like Ohlson (1995) model. However, the current researchers of accounting and finance field use TAMs as well as Value Based Measures (VBMs) such as Economic Value Added (EVA) and Market Value Added (MVA) for explaining Stock Prices(SPs). Thus this study addresses how far TAMs and VBMs are capable in explaining equity prices. The study contributes to the literature as the first widespread comprehensive study of the validity of TAMs and VBMs in determining stock prices in Sri Lanka. The main objective of the study is to compare the explanatory power of TAMs and VBMs. TAMs include Earnings per share (EPS), Cash Flows(CFs) and Book Value per Share (BVPS). VBMs include EVA and MVA in explaining stock prices (SPs). The study includes Manufacturing,Diversified holding and Beverage, Food and Tobacco companies listed in the Colombo Stock Exchange (CSE),selected on the basis of market capitalization and the data availability from 2003 to 2008. The Ordinary Least Square Regression (OLS) and Karl Pearson correlation coefficient were applied to analyze data. The study found that the OE is the most significant explanatary variable in explaining SP. Although the BVPS, Investing Cash Flows(ICF) and MVA are also significant variables for determining SPs as suggested by Stepwise regression, EVA is not a significant variable. The results indicate that the TAMs are still at the top in determining SPs. The standard setting bodies should streamline the format of financial statements to represent the investors’ information requirements. Key Words: Traditional Accounting Measures, Value Based Measures, Stock Prices