Miracle-dz/UniFAR-FTUs huggingface dataset:
Peroxisome Proliferator-activated Receptor-γ Co-activator 1α-mediated Metabolic Remodeling of Skeletal Myocytes Mimics Exercise Training and Reverses Lipid-induced Mitochondrial Inefficiency*

Peroxisome proliferator-activated receptor-γ co-activator 1α (PGC1α) is a promiscuous co-activator that plays a key role in regulating mitochondrial biogenesis and fuel homeostasis. Emergent evidence links decreased skeletal muscle PGC1α activity and coincident impairments in mitochondrial performance to the development of insulin resistance in humans. Here we used rodent models to demonstrate that muscle mitochondrial efficiency is compromised by diet-induced obesity and is subsequently rescued by exercise training. Chronic high fat feeding caused accelerated rates of incomplete fatty acid oxidation and accumulation of β-oxidative intermediates. The capacity of muscle mitochondria to fully oxidize a heavy influx of fatty acid depended on factors such as fiber type and exercise training and was positively correlated with expression levels of PGC1α. Likewise, an efficient lipid-induced substrate switch in cultured myocytes depended on adenovirus-mediated increases in PGC1α expression. Our results supported a novel paradigm in which a high lipid supply, occurring under conditions of low PGC1α, provokes a disconnect between mitochondrial β-oxidation and tricarboxylic acid cycle activity. Conversely, the metabolic remodeling that occurred in response to PGC1α overexpression favored a shift from incomplete to complete β-oxidation. We proposed that PGC1α enables muscle mitochondria to better cope with a high lipid load, possibly reflecting a fundamental metabolic benefit of exercise training.
Bewelcome.org - a non-profit democratic hospex service set up for growth

This paper presents an extensive data-based analysis of the non-profit democratic hospitality exchange service bewelcome.org. We hereby pursuit the goal of determining the factors influencing its growth. It also provides general insights on internet-based hospitality exchange services. The other investigated services are hospitalityclub.org and couchsurfing.org. Communities using the three services are interconnected -- comparing their data provides additional information.
Libor Market Model and Gaussian HJM Explicit Approaches to Option on Composition

The twin brothers Libor Market and Gaussian HJM models are investigated. A simple exotic option, floor on composition, is studied. The same explicit approach is used for both models. Using an approximation the LLM price is obtained without Monte Carlo simulation. The results of the approximation are very good, with an error well below the uncertainty due to the simulation. The appendices proves the existence of the (modified) normal and shifted log-normal LLM used in the pricing. The link of the latter with the Ho and Lee continuous time model is described.
An Extension of the Regression of Offspring on Mid‐Parent to Test for Association and Estimate Locus‐Specific Heritability: The Revised ROMP Method

The Regression of Offspring on Mid‐Parent (ROMP) method is a test of association between a quantitative trait and a candidate locus. ROMP estimates the trait heritability and the heritability attributable to a locus and requires genotyping the offspring only. In this study, the theory underlying ROMP was revised (ROMPrev) and extended. Computer simulations were used to determine the type I error and power of the test of association, and the accuracy of the locus‐specific heritability estimate. The ROMPrev test had good power at the 5% significance level with properly controlled type I error. Locus‐specific heritability estimates were, on average, close to simulated values. For non‐zero locus‐specific heritability, the proposed standard error was downwardly biased, yielding reduced coverage of 95% confidence intervals. A bootstrap approach with proper coverage is suggested as a second step for loci of interest.
Dendritic Cell Vaccines Antigen-Presenting Functions and Antitumor Activity of Inhibits the β Transforming Growth Factor Updated

Dendritic cell (DC)-based vaccines have exhibited minimal effectiveness in treating established tumors, likely because of factors present in the tumor microenvironment. One such factor is transforming growth factor (TGF), a cytokine that is produced by numerous tumor types and has been demonstrated to impair DC functions in vitro. We have evaluated the effect of TGFon the immunostimulatory activities of DCs. We demonstrate that TGFexposure inhibits the ability of DCs to present antigen, stimulate tumor-sensitized T lymphocytes, and migrate to draining lymph nodes. Neutralization of TGFusing the TGF-neutralizing monoclonal antibody 2G7 enhanced the ability of DC vaccines to inhibit the growth of established 4T1 murine mammary tumors. Treatment of 4T1 tumors transduced with the antisense TGFtransgene (4T1-asT) with the combination of DC and 2G7 monoclonal antibody inhibited tumor growth and resulted in complete regression of tumors in 40% of the mice. These results demonstrate that neutralization of TGFin tumor-bearing mice enhances the efficacy of DC-based vaccines.
Meltdown: The End of the Age of Greed

Meltdown is a gripping account of the financial collapse that destroyed the West's investment banks, brought the global economy to its knees, and undermined three decades of neoliberal orthodoxy. Covering the development of the crisis from the economic front line, Paul Mason explores the roots of the US and UK's financial hubris, documenting the real-world causes and consequences from the Ford factory, to Wall Street, to the City of London. In this fully updated new edition, he recounts how the credit crunch became a full-blown financial crisis, and explores the impact of this development on capitalist ideology and politics.
Topic Discovery in Research Literature Based on Non-negative Matrix Factorization and Testor Theory

The paper proposes a new way of comprising the Non-negative matrix factorization (NMF) and Testor theory to make topic discovery. NMF method is good at dealing with high dimensional documents and clustering, while Testor theory is used to find the topic of each cluster. By an example of ten abstracts of Chinese science literature from magazines relative to environmental science, the whole process is described in detail. In the end, a case study about automatic classification of a conference proceeding (in Chinese) is given. The result shows the effectiveness of the whole method.
The Classification Method Study of Two-Dimension Iteration Transductive Support Vector Machine

Because of the restriction caused by the practical application, the semi-supervised learning is generally adopted in pattern recognition. The paper proposed the method, which takes the Support Vector Machine (SVM) as a basic tool with absorbing the transductive inference to make the full use of concerned training sample information so that high-quality separating hyperplane of transductive sample set can be generated. The method is composed of two transductive inferences that 1) based on time-varied separating hyperplane the number of labeled transductive samples is increased while the samples in the training set is simultaneously deleted, so-called y-dimension iteration transduction and 2) labeled training sample subsets are offered the gradually increasing punishment factor coefficients as well as the punishment factor of training set is decreased by steps, the so-called x-dimension iteration transduction. During the period x-dimension iteration transductions are nested in y-dimension iteration transductions, which end at the time when the training set is empty. Simulation proves the method has the higher accuracy and stronger robust than correlation knowledge induction SVM and prior knowledge induction SVM in the situation where the label of training set is unavailable, such as remote sensing thermal imaging cognition.
GFC or KFC?: How Standard Setters Were Battered and Fried

The Global Financial Crisis (GFC) has exposed the fragility of both the alleged independence of the International Accounting Standards Board (IASB) and the Financial Accounting Standards Board (FASB) and their agreement to work together on major projects such as accounting for financial instruments. This paper outlines the events that have dogged the IASB and FASB in their attempts to respond to the GFC and explores the implications of the recent political pressures on accounting standard setting for the likelihood of ultimately achieving one global set of accounting standards.
Optimal designs for random effect models with correlated errors with applications in population phar

We consider the problem of constructing optimal designs for population pharmacokinetics which use random effect models. It is common practice in the design of experiments in such studies to assume uncorrelated errors for each subject. In the present paper a new approach is introduced to determine efficient designs for nonlinear least squares estimation which addresses the problem of correlation between observations corresponding to the same subject. We use asymptotic arguments to derive optimal design densities, and the designs for finite sample sizes are constructed from the quantiles of the corresponding optimal distribution function. It is demonstrated that compared to the optimal exact designs, whose determination is a hard numerical problem, these designs are very efficient. Alternatively, the designs derived from asymptotic theory could be used as starting designs for the numerical computation of exact optimal designs. Several examples of linear and nonlinear models are presented in order to illustrate the methodology. In particular, it is demonstrated that naively chosen equally spaced designs may lead to less accurate estimation.
Classification of movement intention by spatially filtered electromagnetic inverse solutions

We couple standardized low-resolution electromagnetic tomography, an inverse solution for electroencephalography (EEG) and the common spatial pattern, which is here conceived as a data-driven beamformer, to classify the benchmark BCI (brain–computer interface) competition 2003, data set IV. The data set is from an experiment where a subject performed a self-paced left and right finger tapping task. Available for analysis are 314 training trials whereas 100 unlabelled test trials have to be classified. The EEG data from 28 electrodes comprise the recording of the 500 ms before the actual finger movements, hence represent uniquely the left and right finger movement intention. Despite our use of an untrained classifier, and our extraction of only one attribute per class, our method yields accuracy similar to the winners of the competition for this data set. The distinct advantages of the approach presented here are the use of an untrained classifier and the processing speed, which make the method suitable for actual BCI applications. The proposed method is favourable over existing classification methods based on an EEG inverse solution, which rely either on iterative algorithms for single-trial independent component analysis or on trained classifiers.
A Novel k-out-of-n Oblivious Transfer Protocol from Bilinear Pairing

Oblivious transfer (OT) protocols mainly contain three categories: 1-out-of-2 OT, 1-out-of-n OT, and k-out-of-n OT. In most cases, they are treated as cryptographic primitives and are usually executed without consideration of possible attacks that might frequently occur in an open network, such as an impersonation, replaying, or man-in-the-middle attack. Therefore, when used in certain applications, such as mental poker games and fair contract signings, some extra mechanisms must be combined to ensure the security of the protocol. However, after a combination, we found that very few of the resulting schemes are efficient enough in terms of communicational cost, which is a significant concern for generic commercial transactions. Therefore, we propose a novel k-out-of-n oblivious transfer protocol based on bilinear pairing, which not only satisfies the requirements of a k-out-of-n OT protocol, but also provides mutual authentication to resist malicious attacks. Meanwhile, it is efficient in terms of communication cost.
A New Algorithm for Shape Reconstruction by the Computational Geometry Approach

The shape reconstruction problem is one of important and most applied problems in many branches of computer science. In this paper a new method is introduced which a graph as output and work on boundary samples as input, in the plan. The proposed method starts reconstruction from the random polygon production on input points and by calculating the Euclidean distance between points, it produces a set of new points. By adding produced points to the initial points and implementation of algorithm on a set of final point, this approach performs the shape reconstruction process. This method reduces reconstruction error compared to the initial shape and improves the process of shape reconstruction.
Mining noisy tagging from multi-label space

In this paper we study the problem of mining noisy tagging. Most of the existing discriminative classification methods to this problem only consider one tag at a time as the classification target, and completely ignore the rest of the given tags at the same time. In this paper we argue that all the given multiple tags can be utilized simultaneously as an additional feature and the information contained in the multi-label space can be taken advantage of to improve the performance of the classification. We first propose a novel distance measure to compute the distance between instances in the multi-label space. Then we propose several novel methods to incorporate the information of the multi-label space into the discriminative classification methods in one view learning or in two views learning to solve a general multi-label classification problem and to mitigate the influence of the noise in the classification. We apply the proposed solutions to the problem with a more specific context - noisy image annotation, and evaluate the proposed methods on a standard dataset from the related literature. Experiments show that they are superior to the peer methods in the existing literature on solving the problem of mining noisy tagging.
Resampling Process of the Scalable High Efficiency Video Coding

SHVC is the scalable extension of the latest video coding standard High Efficiency Video Coding (HEVC) and spatial resampling process is inevitable module to support spatial scalability. This paper describes in details the resampling process, including both texture and motion data resampling in SHVC, and using experimental evidence, demonstrate their benefits in terms of coding efficiency.
Mutual Fund Advisory Fees: The Cost of Conflicts of Interest

In the early 1970's, America's mutual fund industry was suffering net redemptions, meaning it was contracting in size. Fund marketing efforts were in disarray, thus prompting the Securities and Exchange Commission (SEC) to embark on a special study analyzing the problems then plaguing the industry. From that starting point, the SEC moved to loosen restrictions on fund marketing in order to foster a more competitive environment. One consequence of this loosening was the explosive growth in mutual funds. Today's industry boasts more than 10,000 funds, with assets exceeding $7 trillion, an average annual asset growth rate since 1974 exceeding twenty percent. A consequence of this staggering growth is that fund sponsors, the SEC, fund investors, and the courts must now confront a new wave of challenges. Despite its phenomenal marketing success, the fund industry now finds aspects of its conduct under attack from various quarters. The popular press and a prominent regulator, Eliot Spitzer, are focusing attention on the industry's fee structure and the perceived inadequacy of mutual fund governance, including the gap between prices charged funds for advisory services versus prices fetched elsewhere in the economy for those same services. This article examines whether the chief product that shareholders buy when they invest in mutual funds - professional investment advice - is being systematically over-priced by fund managers. The emphasis is on advisory fees imposed on equity mutual funds. Part II explains how the industry's unique management structure accounts for the alleged lack of price competition in the delivery of management advice perceived by the industry's detractors. Part III examines two questions related to economies of scale in the fund industry. First, do economies of scale exist for the delivery of investment management services to equity fund shareholders? Second, if so, are those economies being shared fairly with the funds' owners by the funds' agents, the investment advisors? Part IV studies causes for the status quo, including the industry's statutory scheme, the quality of the SEC's regulatory efforts, and the reception given fund critics by the courts. The Article concludes with a set of proposals for changing the present competitive environment in which fund advisory fees are set, disclosed, and evaluated.
Trust-Region Interior-Point SQP Algorithms for a Class of Nonlinear Programming Problems

In this paper, a family of trust-region interior-point sequential quadratic programming (SQP) algorithms for the solution of a class of minimization problems with nonlinear equality constraints and simple bounds on some of the variables is described and analyzed. Such nonlinear programs arise, e.g., from the discretization of optimal control problems. The algorithms treat states and controls as independent variables. They are designed to take advantage of the structure of the problem. In particular they do not rely on matrix factorizations of the linearized constraints but use solutions of the linearized state equation and the adjoint equation. They are well suited for large scale problems arising from optimal control problems governed by partial differential equations. The algorithms keep strict feasibility with respect to the bound constraints by using an affine scaling method proposed, for a different class of problems, by Coleman and Li [SIAM J. Optim. , 6 (1996), pp. 418--445] and they exploit trust-region techniques for equality-constrained optimization. Thus, they allow the computation of the steps using a variety of methods, including many iterative techniques. Global convergence of these algorithms to a first-order Karush--Kuhn--Tucker (KKT) limit point is proved under very mild conditions on the trial steps. Under reasonable, but more stringent, conditions on the quadratic model and on the trial steps, the sequence of iterates generated by the algorithms is shown to have a limit point satisfying the second-order necessary KKT conditions. The local rate of convergence to a nondegenerate strict local minimizer is q-quadratic. The results given here include, as special cases, current results for only equality constraints and for only simple bounds. Numerical results for the solution of an optimal control problem governed by a nonlinear heat equation are reported.
Cellular-based machine-to-machine: overload control

One of the most important problems posed by cellular-based machine type communications is congestion. Congestion concerns all the parts of the network, both the radio and the core network impacting both the user data plane and the control plane. In this article, we address the problem of congestion in machine type communications. We propose a congestion-aware admission control solution that selectively rejects signaling messages from MTC devices at the radio access network following a probability that is set based on a proportional integrative derivative controller reflecting the congestion level of a relevant core network node. We evaluate the performance of our proposed solution using computer simulations. The obtained results are encouraging. In fact, we succeed in reducing the amount of signaling while maintaining a target utilization ratio of resources in the core network.
Topography and Areal Organization of Mouse Visual Cortex

To guide future experiments aimed at understanding the mouse visual system, it is essential that we have a solid handle on the global topography of visual cortical areas. Ideally, the method used to measure cortical topography is objective, robust, and simple enough to guide subsequent targeting of visual areas in each subject. We developed an automated method that uses retinotopic maps of mouse visual cortex obtained with intrinsic signal imaging (Schuett et al., 2002; Kalatsky and Stryker, 2003; Marshel et al., 2011) and applies an algorithm to automatically identify cortical regions that satisfy a set of quantifiable criteria for what constitutes a visual area. This approach facilitated detailed parcellation of mouse visual cortex, delineating nine known areas (primary visual cortex, lateromedial area, anterolateral area, rostrolateral area, anteromedial area, posteromedial area, laterointermediate area, posterior area, and postrhinal area), and revealing two additional areas that have not been previously described as visuotopically mapped in mice (laterolateral anterior area and medial area). Using the topographic maps and defined area boundaries from each animal, we characterized several features of map organization, including variability in area position, area size, visual field coverage, and cortical magnification. We demonstrate that higher areas in mice often have representations that are incomplete or biased toward particular regions of visual space, suggestive of specializations for processing specific types of information about the environment. This work provides a comprehensive description of mouse visuotopic organization and describes essential tools for accurate functional localization of visual areas.
Die Rentenversicherung unter Reformdruck: Ein Drama in drei Akten

Der vorliegende Beitrag soll zeigen, dass die von der sogenannten Rurup-Kommission eingebrachten Vorschlage durchaus einen Weg in Richtung Nachhaltigkeit der Rentenversicherung darstellen konnen. Darunter fallen v.a. zwei Masnahmen, namlich die Anhebung der Altersgrenze fur Regelaltersrenten von 65 auf 67 Jahre und die Integration eines sogenannten Nachhaltigkeitsfaktors in die aktuelle Rentenformel. Auf die in der wissenschaftlichen Diskussion seit langem geforderte Einfuhrung von hoheren Abschlagen bei Fruhverrentung hat man verzichtet. Dennoch wird auch diese Masnahme zusammen mit den vorgeschlagenen mittels der Methode der Generationenbilanzierung im Hinblick auf ihre fiskalische Wirkung uberpruft. Dazu erfolgt im ersten Akt zunachst eine kurze Einfuhrung in die Methodik der Generationenbilanzierung. Im zweiten Akt werden die bestehenden Probleme der GRV aufgezeigt und verdeutlicht. Die Analyse der unterschiedlichen Reformideen und Losungsvorschlage im Vergleich zum Status quo ist Gegenstand des dritten Akts. Der Epilog fasst den Beitrag zusammen und schliest mit einem Ausblick auf die politischen Realisierungschancen der Reformkonzepte.