Miracle-dz/UniFAR-FTUs huggingface dataset:
Caloric restriction induces energy-sparing alterations in skeletal muscle contraction, fiber composition and local thyroid hormone metabolism that persist during catch-up fat upon refeeding

Weight regain after caloric restriction results in accelerated fat storage in adipose tissue. This catch-up fat phenomenon is postulated to result partly from suppressed skeletal muscle thermogenesis, but the underlying mechanisms are elusive. We investigated whether the reduced rate of skeletal muscle contraction-relaxation cycle that occurs after caloric restriction persists during weight recovery and could contribute to catch-up fat. Using a rat model of semistarvation-refeeding, in which fat recovery is driven by suppressed thermogenesis, we show that contraction and relaxation of leg muscles are slower after both semistarvation and refeeding. These effects are associated with (i) higher expression of muscle deiodinase type 3 (DIO3), which inactivates tri-iodothyronine (T3), and lower expression of T3-activating enzyme, deiodinase type 2 (DIO2), (ii) slower net formation of T3 from its T4 precursor in muscles, and (iii) accumulation of slow fibers at the expense of fast fibers. These semistarvation-induced changes persisted during recovery and correlated with impaired expression of transcription factors involved in slow-twitch muscle development. We conclude that diminished muscle thermogenesis following caloric restriction results from reduced muscle T3 levels, alteration in muscle-specific transcription factors, and fast-to-slow fiber shift causing slower contractility. These energy-sparing effects persist during weight recovery and contribute to catch-up fat.
Dopamine Receptors and Groups I and II mGluRs Cooperate for Long-Term Depression Induction in Rat Prefrontal Cortex through Converging Postsynaptic Activation of MAP Kinases

Tetanic stimuli to layer I–II afferents in rat prefrontal cortex induced long-term depression (LTD) of layer I–II to layer V pyramidal neuron glutamatergic synapses when tetani were coupled to bath application of dopamine. This LTD was blocked by the following metabotropic glutamate receptor (mGluR) antagonists coapplied with dopamine: (S)-α-methyl-4-carboxyphenylglycine (MCPG; group I and II antagonist), (RS)-1-aminoindan-1,5-dicarboxylic acid (AIDA; group I antagonist), or (RS)-α-methylserine-O-phosphate monophenyl ester (MSOPPE; group II antagonist). This suggests that the dopamine-facilitated LTD requires synaptic activation of groups I and II mGluRs during tetanus. LTD could also be induced by coupling tetani to bath application of groups I and II mGluR agonist (1S,3R)-1-aminocyclopentane-1,3-dicarboxylic acid (1S,3R-ACPD). In the next series of experiments, coapplication of dopamine and 1S,3R-ACPD, but not application of either drug alone, consistently induced LTD without tetani or even single test stimuli during drug application, suggesting that coactivation of dopamine receptors and the mGluRs is sufficient for LTD induction. Immunoblot analyses with anti-active mitogen-activated protein kinases (MAP-Ks) revealed that D1 receptors, D2 receptors, group I mGluRs, and group II mGluRs all contribute to MAP-K activation in prefrontal cortex, and that combined activation of dopamine receptors and mGluRs synergistically or additively activate MAP-Ks. Consistently, LTD by dopamine + 1S,3R-ACPD coapplication, as well as the two other forms of LTD (LTD by dopamine + tetani and LTD by 1S,3R-ACPD + tetani), was blocked by bath application of MAP-K kinase inhibitor PD98059. LTD by dopamine + 1S,3R-ACPD coapplication was also blocked by postsynaptic injection of synthetic MAP-K substrate peptide. Our results suggest that dopamine receptors and groups I and II mGluRs cooperate to induce LTD through converging postsynaptic activation of MAP-Ks.
Livestock and livelihoods: Development goals and indicators applied to Senegal

In this report, we present a series of empirical techniques to examine linkage between livestock and livelihood, using data from Senegal, a West African economy with high levels of smallholder poverty and livestock dependence. Our results for this country show that livestock dependent populations are more likely to be poor and the severity of their poverty is greater, yet the same reliance on livestock also offers a way to mitigate their adversity. By analyzing market linkages and supply chains in the livestock sector, we find that rural household producers capture only a small fraction of the ultimate value of their products. Moreover, we find that generalist agricultural promotion policies may be of limited value to them because most of the value created by these policies can be captured by downstream market participants. Our primary conclusion is that livestock holds substantial potential for poverty alleviation, but that carefully targeted policies are required to realize this potential.
Financial Modelling with Jump Processes

WINNER of a Riskbook.com Best of 2004 Book Award! During the last decade, financial models based on jump processes have acquired increasing popularity in risk management and option pricing. Much has been published on the subject, but the technical nature of most papers makes them difficult for nonspecialists to understand, and the mathematical tools required for applications can be intimidating. Potential users often get the impression that jump and Levy processes are beyond their reach.Financial Modelling with Jump Processes shows that this is not so. It provides a self-contained overview of the theoretical, numerical, and empirical aspects involved in using jump processes in financial modelling, and it does so in terms within the grasp of nonspecialists. The introduction of new mathematical tools is motivated by their use in the modelling process, and precise mathematical statements of results are accompanied by intuitive explanations.Topics covered in this book include: jump-diffusion models, Levy processes, stochastic calculus for jump processes, pricing and hedging in incomplete markets, implied volatility smiles, time-inhomogeneous jump processes and stochastic volatility models with jumps. The authors illustrate the mathematical concepts with many numerical and empirical examples and provide the details of numerical implementation of pricing and calibration algorithms.This book demonstrates that the concepts and tools necessary for understanding and implementing models with jumps can be more intuitive that those involved in the Black Scholes and diffusion models. If you have even a basic familiarity with quantitative methods in finance, Financial Modelling with Jump Processes will give you a valuable new set of tools for modelling market fluctuations.
How to Use Not-Always-Reliable Binding Site Information in Protein-Protein Docking Prediction

In many protein-protein docking algorithms, binding site information is used to help predicting the protein complex structures. Using correct and accurate binding site information can increase protein-protein docking success rate significantly. On the other hand, using wrong binding sites information should lead to a failed prediction, or, at least decrease the success rate. Recently, various successful theoretical methods have been proposed to predict the binding sites of proteins. However, the predicted binding site information is not always reliable, sometimes wrong binding site information could be given. Hence there is a high risk to use the predicted binding site information in current docking algorithms. In this paper, a softly restricting method (SRM) is developed to solve this problem. By utilizing predicted binding site information in a proper way, the SRM algorithm is sensitive to the correct binding site information but insensitive to wrong information, which decreases the risk of using predicted binding site information. This SRM is tested on benchmark 3.0 using purely predicted binding site information. The result shows that when the predicted information is correct, SRM increases the success rate significantly; however, even if the predicted information is completely wrong, SRM only decreases success rate slightly, which indicates that the SRM is suitable for utilizing predicted binding site information.
Trusted Computing Dynamic Attestation by Using Static Analysis Based Behavior Model

Current technology of trusted computing can not comply with the requirement of trusted behavior. One method for trusted computing dynamic attestation was proposed in this paper. This method uses the behavior model based on static analysis of binary code. One same source code may have several different binary versions, this paper proposed one method of building almost the same core function model for different binary versions. This paper also overcame the difficulty that some dynamic behaviors can not be obtained by static analysis. The paper also gave out some solutions of dynamic attestation for some complex programs, such as recursion program, library link program and multi threads program.
Principle and Realization of a Permanent Magnet Motor Running with a Higher Harmonic Airgap Wave for a BLDC Drive Application

A straightforward industrial development process of customized variable speed drive systems is today preferably assisted by efficient numerical calculation tools. Hence, the interaction of different electronic circuit designs of power stacks controlled by modern algorithms with innovative motor topologies based on higher space harmonics can be investigated with respect to the complete drive system. Fortunately, different case studies on various drives can be carried in advance.
Evaluating the impact of different document types on the performance of web cache replacement schemes

In this paper, we present a comprehensive performance study of least recently used and least frequently used with dynamic aging as traditional replacement schemes as well as for the newly proposed schemes greedy dual size and greedy dual. The goal of our study constitutes the understanding how these replacement schemes deal with different web document types. Using trace-driven simulation, we present curves plotting the hit rate and byte hit rate broken down for image, HTML, multi media, and application documents. The presented results show for the first workload that under the packet cost model Greedy Dual outperforms the other schemes both in terms of hit rate and byte hit rate for image, HTML, and multi media documents. However, the advantages of Greedy Dual diminish when the workload contains more distinct multi media documents and a larger number of requests to multi media documents.
Are Male and Female Avatars Perceived Equally in 3D Virtual Worlds?

Virtual worlds are three-dimensional, computer-generated worlds in which users take the form of avatars and use those avatars to interact with objects and other avatars in the virtual world. Virtual worlds are growing in importance in both educational institutions and businesses. Educational institutions have adopted virtual worlds as a medium for instructional delivery whereas businesses are using virtual worlds for recruitment, training, collaboration, and marketing. Given these emerging phenomena, a better understanding of behavioral and perceptual issues in virtual worlds is warranted. We propose a research model to study the interaction effects of gender stereotypicality of male and female avatars and gender typicality of tasks on trust perceptions. Gender stereotypes have been widely studied in the real world along with their effects on trust perceptions. An experiment is proposed to examine the effects of gender stereotypes on trust perceptions in virtual worlds. Implications and expected contributions are also discussed.
Ironing Out the Flat Tax

One of the major claims of the promoters of the Flat Tax is that it would be simple to administer. Yet to date, no details of the design have been offered, which makes evaluation of the administrative costs difficult. This paper attempts to fill in the gap by considering the design issues presented by the Flat Tax. A wide variety of issues are considered, including the Flat Tax taxation of financial transactions, business formations and reorganizations, small businesses, accounting methods, and international transactions. The major finding of this paper is that there would be significant administrative difficulties in implementing the regime. Even with significant administrative difficulties, however, the regime would most likely be simpler than current law in many respects.
Sentence compression by structural conversion of parse tree

Sentence compression is the task of generating a grammatical short sentence from an original sentence, retaining important information. The existing methods of only removing the constituents in the parse tree of an original sentence cannot emulate human compression that changes structures of the parse tree. This paper proposes a method to remove recursive structures, one example of such structural conversions, and generate a grammatical short sentence. In order to remove a recursive structure, our method detects the constituents forming the structure and removes them as a unit. Compression experiments have shown that our method generates more grammatical compressed sentences than the previous method.
Personal Name Extraction from Japanese Historical Documents Using Machine Learning

In this poster, we propose a method for extracting persons' real names and aliases from Japanese historical documents. In this method, we extract personal names and aliases by applying a named entity extraction technique based on machine learning using characters as the unit of analysis. One of the features of this method is that it uses already attached annotations to named entities in order to find undiscovered ones. Experimental results showed that our proposed method was able to extract personal names and aliases from "Yakusha-Hyoban-Ki", a collection of review documents of Kabuki actors in Edo Era (1603-1868) in Japan, with approximately 0.91 in F-measure.
The NO/ONOO-Cycle as the Central Cause of Heart Failure

The NO/ONOO-cycle is a primarily local, biochemical vicious cycle mechanism, centered on elevated peroxynitrite and oxidative stress, but also involving 10 additional elements: NF-κB, inflammatory cytokines, iNOS, nitric oxide (NO), superoxide, mitochondrial dysfunction (lowered energy charge, ATP), NMDA activity, intracellular Ca2+, TRP receptors and tetrahydrobiopterin depletion. All 12 of these elements have causal roles in heart failure (HF) and each is linked through a total of 87 studies to specific correlates of HF. Two apparent causal factors of HF, RhoA and endothelin-1, each act as tissue-limited cycle elements. Nineteen stressors that initiate cases of HF, each act to raise multiple cycle elements, potentially initiating the cycle in this way. Different types of HF, left vs. right ventricular HF, with or without arrhythmia, etc., may differ from one another in the regions of the myocardium most impacted by the cycle. None of the elements of the cycle or the mechanisms linking them are original, but they collectively produce the robust nature of the NO/ONOO-cycle which creates a major challenge for treatment of HF or other proposed NO/ONOO-cycle diseases. Elevated peroxynitrite/NO ratio and consequent oxidative stress are essential to both HF and the NO/ONOO-cycle.
A role for hydrophobicity in a Diels–Alder reaction catalyzed by pyridyl-modified RNA

New classes of RNA enzymes or ribozymes have been obtained by in vitro evolution and selection of RNA molecules. Incorporation of modified nucleotides into the RNA sequence has been proposed to enhance function. DA22 is a modified RNA containing 5-(4-pyridylmethyl) carboxamide uridines, which has been selected for its ability to promote a Diels–Alder cycloaddition reaction. Here, we show that DA_TR96, the most active member of the DA22 RNA sequence family, which was selected with pyridyl-modified nucleotides, accelerates a cycloaddition reaction between anthracene and maleimide derivatives with high turnover. These widely used reactants were not used in the original selection for DA22 and yet here they provide the first demonstration of DA_TR96 as a true multiple-turnover catalyst. In addition, the absence of a structural or essential kinetic role for Cu2+, as initially postulated, and nonsequence-specific hydrophobic interactions with the anthracene substrate have led to a reevaluation of the pyridine modification's role. These findings broaden the catalytic repertoire of the DA22 family of pyridyl-modified RNAs and suggest a key role for the hydrophobic effect in the catalytic mechanism.
STUDY OF MAXIMUM A POSTERIORI SPEAKER ADAPTATION FOR AUTOMATIC SPEECH RECOGNITION OF PATHOLOGICAL SPEECH

This paper shows the results achieved by the Maximum A Posteriori (MAP) speaker adaptation method in a task of isolated word Automatic Speech Recognition (ASR) system for 6 young speakers with different types of speech pathologies. In this work, the influence of two important variables in speech recognition and speaker adaptation are studied. On one hand, the performance of the ASR system depending on the acustic unit used by the system (word level unit and context-dependent unit) is analized. On the other hand, how the size of the training set influences the results when using MAP adaptation is studied. The results of this work with the first subset of the Alborada-GTC corpus show that context-dependent units are the most reliable acoustic unit to use, while the use of 2 utterances of the vocabulary recorded in the corpus is enough for getting the best results in speaker adaptation.
Saliency detection by non-linear intensity mapping in images

Visually saliency detection provides an filternative methodology to image description in many applications such as adaptive content delivery and image retrieval. In this paper, we propose a novel computational method to model visual saliency in nature images. To efficiently eliminate high contrast noise regions in the background, we propose a constructive approach of non-linear intensity mapping for rendering an image based on local and global context information. Therefore, the most salient region can be easily selected as the one which is globally most isolated and has locally distinctive characteristics. The proposed approach intrinsically provides an filternative methodology to model attention with low implementation complexity. Experiments show that our approach achieves much better performance than that from the existing state-of-art.
Global Social Change Leadership: A Framework For Business

This article posits a framework for thinking about the role business leaders can play in creating global social change. The qualitative, grounded theory research study rests on the assumption that alternative paradigms exist compared to our predominant, profitmaximizing corporate model. The study seeks to understand how 39 formal and informal leaders consciously act within business contexts in order to create forms of wealth that include, but are not limited to, financial profits. The framework’s four propositions characterize attitudes and values espoused by the snowball sample of individuals. Implications are hypothesized for the influence relationships created within our larger global society as a result of interconnection actions occurring at individual and local levels.
Korean Version of a Model to Estimate Survival in Ambulatory Patients with Hepatocellular Carcinoma (K-MESIAH)

Background and Aim A model to estimate survival in ambulatory hepatocellular carcinoma patients (MESIAH) is useful for estimating patient prognosis but needs improvement for Korean patients, most of whom have a hepatitis B virus. We aimed to modify the MESIAH for better prognostication through enhancing calibration for Korean patient population (K-MESIAH). Methods Utilizing a cohort of 1,969 hepatocellular carcinoma (HCC) patients from the National Cancer Center of Korea between 2004 and 2009, a survival prediction model was developed using the Cox proportional hazards model. The model’s performance was evaluated using C-statistical and χ2-statistical analyses. External validation was performed using an independent cohort of 328 patients from the Seoul National University Bundang Hospital. Results To develop the K-MESIAH, etiology was added to the original risk factors (age, Model for Endstage Liver Disease, albumin, size of the largest nodule, number of tumor nodules, vascular invasion, metastasis, and alpha fetoprotein) in the MESIAH. From the internal validation study, the C-statistics and χ2-statistics for one-, three-, and five-years of survival were 0.83 (95% Confidence Interval: 0.82−0.85), 49.07; 0.81 (95% Confidence Interval: 0.79−0.82), 28.95; and 0.80 (95% Confidence Interval: 0.79−0.81), 20.93, respectively. The K-MESIAH also showed a high prediction ability for the external validation cohort. Conclusions A survival prediction model for Korean HCC patients was developed and validated to have a high level of performance. This K-MESIAH may be more useful in clinical practice and personalized care in a hepatitis B virus endemic area.
An automatically‐tuned sorting library

We present ATSL, an automatically‐tuned sorting library. ATSL generates a sorting routine optimized to the target machine for a specific data type. ATSL finds a high‐performance sorting routine by searching an algorithmic space that we have defined. The search space includes basic sorting algorithms and automatically‐generated compositions of sorting algorithms. Performance measurements are used both for ranking candidate algorithms and for characterizing the behavior of candidates in specific settings (e.g. ranges of input sizes). These characterizations allow ATSL to generate hybrid algorithms that intelligently exploit the strengths of particular algorithms, such as high speed at specific input‐size ranges. Many sorting algorithms can be tuned using numeric parameters and ATSL searches these parameter spaces to find values that yield high performance on the target machine. The building blocks from which ATSL synthesizes sorting algorithms include adaptations of many of the most effective hand‐tuned sorting routines, including several that are tuned for cache efficiency. An extensive experimental evaluation shows that ATSL generates high‐performance codes that are well tuned for the target machine and data type. The experiments were conducted on six different machines, of several architectures, and with three different compilers. The algorithms that are generated are fast; in particular, they beat the hand‐tuned building blocks and the compiler's C++ built‐in sorting routine. The algorithms that ATSL generates on different machines and using different compilers are different from each other. Copyright © 2007 John Wiley & Sons, Ltd.