Miracle-dz/UniFAR-FTUs huggingface dataset:
China’s Energy Economy: Reforms, Market Development, Factor Substitution and the Determinants of Energy Intensity

The ongoing transition of former communist countries from planned to market economies has been one of the most important economic phenomena in the last few decades. Among these, China is one of the largest and fastest growing emerging economies in the world since the reforms initiated in the late 1980s. China’s economic growth has been phenomenal. Therefore, understanding China’s energy economy is crucial in the new millennium for politicians, businessmen and energy economists. In particular, China’s energy policy directions will bring about both challenges and opportunities to the world in terms of an increasing share of primary energy consumption and investment in the energy industry. However, after surveying the literature, it is surprising to find that a few major areas of China’s energy economics are missing and the views on China’s energy economics are already out dated. Therefore, given the size and growth of its economy and the effect of its energy consumption on global energy markets, reviewing China’s energy situation and filling the missing literatures are essential for those who are interested in and concerned about China’s economic development in the new millennium. This study was motivated after conducting a survey of the literature on the study of China’s energy economy and reviewing China’s energy situation in the new millennium. The goal of the research is focused on providing readers the most important and the newest information on China’s energy economy. The study consists of three introductory sections and three core sections. The former includes a survey of literature, China’s energy situation in the new millennium, institutional evolution and changing energy
An Adaptation of Experimental Design to the Empirical Validation of Software Engineering Theories

This paper has two objectives. Firstly, it seeks to promote discussion and debate about the need to encourage experimentation of the claims in the field of software engineering. The software community’s lack of concern for the need for the aforesaid experimentation is slowing down adoption of new technology by organizations unfurnished with objective data that show the benefits of the new artifacts to be introduced. This situation is also leading the introduction of new software technology to be considered as a risk, because, as it has not been formally validated beforehand, its application can cause disasters in user organizations. The second objective is to present a formal method of experimentation in SE, based on the experimental design and analysis techniques used in other branches of science.
Gaussian Cardinality Restricted Boltzmann Machines

Restricted Boltzmann Machine (RBM) has been applied to a wide variety of tasks due to its advantage in feature extraction. Implementing sparsity constraint in the activated hidden units of RBM is an important improvement on RBM. The sparsity constraints in the existing methods are usually specified by users and are independent of the input data. However, the input data could be heterogeneous in content and thus naturally demand elastic and adaptive settings of the sparsity constraints. To solve this problem, we proposed a generalized model with adaptive sparsity constraint, named Gaussian Cardinality Restricted Boltzmann Machines (GC-RBM). In this model, the thresholds of hidden unit activations are decided by the input data and a given Gaussian distribution on the pre-training phase. We provide a principled method to train the GC-RBM with Gaussian prior. Experimental results on two real world data sets justify the effectiveness of the proposed method and its superiority over CaRBM in terms of classification accuracy.
Wie werden Kreditsicherheiten in der Praxis eingesetzt? … Ein Überblick über empirische Befunde

Der Beitrag gibt einen berblick ber den aktuellen Stand der empirischen Forschung zur Kreditbesicherung. Demnach werden umso eher Kreditsicherheiten gestellt, (a) je j nger und je kleiner das Kredit nachfragende Unternehmen ist, (b) je l nger die Kreditlaufzeit und je h her der Kreditbetrag sind, (c) je geringer der Wettbewerb am Bankenmarkt und je schlechter die gesamtwirtschaftliche Lage ist. Mehrere Studien zeigen, dass besicherte Kredite h here Zinss tze aufweisen. Hausbanken scheinen mehr Sicherheiten zu halten als andere Kreditgeber. Es werden offenbar deutlich h ufiger Sicherheiten aus dem Unternehmensals aus dem Privatverm gen gestellt. Noch nicht hinreichend gekl rt ist, ob eine substitutive oder komplement re Beziehung zwischen Sicherheiten aus dem Unternehmensverm gen oder anderem Verm gen besteht, z. B. aus dem Privatverm gen. Insgesamt st tzen die empirischen Ergebnisse nicht die These, dass Kreditsicherheiten dazu dienen, besser zwischen „guten“ und „schlechten“ Kreditnehmern unterscheiden zu k nnen (Sortierungsoder Selbstselektionsfunktion). Teilweise gest tzt wird die These, dass Sicherheiten die Anreize des Schuldners zur Bedienung des Kredits verbessern. Das l sst allerdings eher Sicherheiten aus dem Privatverm gen erwarten. Am ehesten l sst sich noch die These vertreten, dass Gl ubiger Sicherheiten aus dem Unternehmensverm gen bestellen, wenn sie Interessenkonflikte mit anderen Kreditgebern bef rchten.
Discriminative Estimation of f-Divergence

We propose an approach for estimating f divergences that exploits a new representation of an f -divergence as a weighted integral of cost-weighted Bayes risks. We are therefore able to reduce f -divergence estimation to a problem of a posterior conditional probability estimation. We provide both batch and online implementation of our approach and analyze their convergence. Empirically, we show our implementation compares favorably to other f -divergence estimators and demonstrate its application to an EEG dataset.
Biologically realistic neural networks and adaptive visual information processing

This work aims to review the basic concepts of biologically realistic neural networks when applied to visual pattern recognition. A new simple model of biologically realistic visual pattern recognition that adaptively learns by example through synaptic plasticity and changes in structure is also presented. This system uses a spiking neural network composed of integrate-and-fire neurons and Hebbian-based learning. The event driven approach used in the implementation optimizes processing speed in order to simulate networks with large number of neurons.
Regulation of NF-κB Oscillation by Nuclear Transport: Mechanisms Determining the Persistency and Frequency of Oscillation

The activated transcription factor NF-κB shuttles between the cytoplasm and the nucleus resulting in the oscillation of nuclear NF-κB (NF-κBn). The oscillation pattern of NF-κBn is implicated in the regulation of gene expression profiles. Using computational models, we previously reported that spatial parameters, such as the diffusion coefficient, nuclear to cytoplasmic volume ratio, transport through the nuclear envelope, and the loci of translation of IκB protein, modified the oscillation pattern of NF-κBn. In a subsequent report, we elucidated the importance of the “reset” of NF-κBn (returning of NF-κB to the original level) and of a “reservoir” of IκB in the cytoplasm. When the diffusion coefficient of IκB was large, IκB stored at a distant location from the nucleus diffused back to the nucleus and “reset” NF-κBn. Herein, we report mechanisms that regulate the persistency and frequency of NF-κBn oscillation by nuclear transport. Among the four parameters of nuclear transport tested in our spatio-temporal computational model, the export of IκB mRNA from the nucleus regulated the persistency of oscillation. The import of IκB to the nucleus regulated the frequency of oscillation. The remaining two parameters, import and export of NF-κB to and from the nucleus, had virtually no effect on the persistency or frequency. Our analyses revealed that lesser export of IκB mRNA allowed NF-κBn to transcript greater amounts of IκB mRNA, which was retained in the nucleus, and was subsequently exported to the cytoplasm, where large amounts of IκB were synthesized to “reset” NF-κBn and drove the persistent oscillation. On the other hand, import of greater amounts of IκB led to an increase in the influx and the efflux of NF-κB to and from the nucleus, resulting in an increase in the oscillation frequency. Our study revealed the importance of nuclear transport in regulating the oscillation pattern of NF-κBn.
Feature covariance for human action recognition

In this paper, we present a novel method for human action recognition using covariance features. Computationally efficient action features are extracted from the skeleton of the subject performing the action. They aim to capture relative positions of the joints and motion over time. These features are encoded into a compact representation using a covariance matrix. We evaluate the performance of the proposed method and demonstrate its superiority compared to related state-of-the-art methods on various datasets, including the MSR Action 3D, the MSR Daily Activity 3D and the UTKinect-Action dataset.
WISP-1, a novel angiogenic regulator of the CCN family, promotes oral squamous cell carcinoma angiogenesis through VEGF-A expression

Oral squamous cell carcinoma (OSCC), which accounts for nearly 90% of head and neck cancers, is characterized by poor prognosis and a low survival rate. VEGF-A is the most established angiogenic factor involved in the angiogenic-regulated tumor progression. WISP-1/CCN4 is an extracellular matrix-related protein that belongs to the Cyr61, CTGF, Nov (CCN) family and regulates many biological functions, such as angiogenesis. Previous studies indicated the role of WISP-1 in tumor progression. However, the angiogenic property of WISP-1 in the cancer microenvironment has never been discussed. Here, we provide novel insights regarding the role of WISP-1 in the angiogenesis through promoting VEGF-A expression. In this study, the correlation of WISP-1 and VEGF-A was confirmed by IHC staining of specimens from patients with OSCC. In vitro results indicated that WISP-1 induced VEGF-A expression via the integrin αvβ3/FAK/c-Src pathway, which transactivates the EGFR/ERK/HIF1-α signaling pathway in OSCC. This pathway in turn induces the recruitment of endothelial progenitor cells and triggers the neovascularization in the tumor microenvironment. Our in vivo data revealed that tumor-secreted WISP-1 promoted the angiogenesis through VRGF expression and increased angiogenesis-related tumor growth. Our study offers new information that highlights WISP-1 as a potential novel therapeutic target for OSCC.
Tall and Skinny QR Matrix Factorization Using Tile Algorithms on Multicore Architectures LAPACK Working Note-222

To exploit the potential of multicore architectures, recent dense linear algebra libraries have used tile algorithms, which consist in scheduling a Directed Acyclic Graph (DAG) of tasks of fine granularity where nodes represent tasks, either panel factorization or update of a block-column, and edges represent dependencies among them. Although past approaches already achieve high performance on moderate and large square matrices, their way of processing a panel in sequence leads to limited performance when factorizing tall and skinny matrices or small square matrices. We present a fully asynchronous method for computing a QR factorization on shared-memory multicore architectures that overcomes this bottleneck. Our contribution is to adapt an existing algorithm that performs a panel factorization in parallel (named CommunicationAvoiding QR and initially designed for distributed-memory machines), to the context of tile algorithms using asynchronous computations. An experimental study shows significant improvement (up to almost 10 times faster) compared to state-of-the-art approaches. We aim to eventually incorporate this work into the Parallel Linear Algebra for Scalable Multicore Architectures (PLASMA) library.
Is Error Term Residual?

Following Fama-French (1993), most researchers try to find new risk factors to complement the Fama-French three factors model. Most of them implement by ranking on the desirable risk factors or regression on the risk factors, and then check the beta or risk premium is significant from zero or not, and assess by the increment of the R2 or/and closer of alpha to zero. However, does adding new factors can really solve the puzzle? Unfortunately, this paper’s answers is no. By regression individual’s (or portfolio’s) excess return on the risk factors and rank the error term from the regression, then construct portfolios based on the ranking, you will get the result very similar to that you directly rank the average return of the portfolios. And by constructing portfolios with various kinds of strategies the result is unchanged and robust. That is similar error term have similar return, but this pattern isn’t persistent. When you rank on lag of (at least 1-12 is) error term or return this pattern disappears. This again, however, means no risk factors missing. This is because if there is missing factor, this pattern may survive when rank on lag due to the persistence of risk factor to some extent. Therefore, this pattern is like a puzzle.
Identification of Heavy Smokers through Their Intestinal Microbiota by Data Mining Analysis

The intestinal microbiota compositions of 92 Japanese men were identified following consumption of identical meals for 3 days, and collected feces were analyzed through terminal restriction fragment length polymorphism. The obtained operational taxonomic units and smoking habits of subjects were analyzed by a data mining software. The constructed decision tree was able to identify explicitly the groups of smokers and nonsmokers. In particular, 4 smokers, who smoked 20 cigarettes/day, i.e., heavy smokers, were gathered in the same group of the decision tree and were clearly identified. Related operational taxonomic unit were traced to understand the species of bacteria, but all were found to be uncultured bacteria.
On the Expressiveness of Distributed Leasing in Linda-like Coordination Languages

Distributed leasing is an emerging paradigm adopted in applications based on the client-server architecture. The basic idea is that, at the moment a client asks for a service, it also declares the (maximal) duration that service should be granted. This paradigm has been recently adopted by SUN Microsystems in the definition of JavaSpaces, a coordination middleware inspired by the shared dataspace model of Linda. In this paper we investigate the interplay between distributed leasing and the Linda coordination model. To this aim, the output operation of a Linda-like calculus is adapted to enrich the tuple with expiration time; the semantics of the resulting calculus is studied under both assumptions that there is one unique global clock or many local clocks. We prove that the introduction of distributed leasing strictly decreases the expressiveness of the Linda-like calculus, and that global time is stricly more expressive than local time.
A Two-Level Algorithm for Large-Scale Terrain Using Nested Regular Grids

We propose a two-level algorithm for large-scale terrain using nested regular grids. To avoid large computing cost by numerous low-resolution blocks, we merge these low- resolution blocks into one level, use nested regular grids to process the other level contains high-resolution blocks, and merge the two levels in GPU, while ensuring the rendering effects, significantly improve the frame rate. Additional, in accordance with the characteristics of the nested regular grid, this paper use a simple and effective strategy for data loading, and rationally organize the out-of-core data, which significantly reduce the real-time loading of the out-of-core data.
Search right and thou shalt find ... Using Web Queries for Learner Error Detection

We investigate the use of web search queries for detecting errors in non-native writing. Distinguishing a correct sequence of words from a sequence with a learner error is a baseline task that any error detection and correction system needs to address. Using a large corpus of error-annotated learner data, we investigate whether web search result counts can be used to distinguish correct from incorrect usage. In this investigation, we compare a variety of query formulation strategies and a number of web resources, including two major search engine APIs and a large web-based n-gram corpus.
Log-parabolic spectra and particle acceleration in blazars. II. The BeppoSAX wide band X-ray spectra of Mkn 501

We present the results of a spectral and temporal study of the complete set of BeppoSAX NFI (11) and WFC (71) observations of the BL Lac object Mkn 501. The WFC 2-28 keV data, reported here for the first time, were collected over a period of about five years, from September 1996 to October 2001. These observations, although not evenly distributed, show that Mkn 501, after going through a very active phase from spring 1997 to early 1999, remained in a low brightness state until late 2001. The data from the LECS, MECS and PDS instruments, covering the wide energy interval 0.1-150 keV, have been used to study in detail the spectral variability of the source. We show that the X-ray energy distribution of Mkn 501 is well described by a log-parabolic law in all luminosity states. This model allowed us to obtain good estimates of the SED synchrotron peak energy and of its associated power. The strong spectral variability observed, consisting of strictly correlated changes between the synchrotron peak energy and bolometric flux (Epeak ∝ F ∼1.4 b ), suggests that the main physical changes are not only due to variations of the maximum Lorentz factor of the emitting particles but that other quantities must be varying as well. During the 1997 flare the high energy part of the spectrum of Mkn 501 shows evidence of an excess above the best fit log-parabolic law suggesting the existence of a second emission component that may be responsible for most of the observed variability.
Magnitude of potential biases in a simulated case-control study of the effectiveness of influenza vaccination.

BACKGROUND Many influenza vaccine effectiveness estimates have been made using case-control methods. Although several forms of bias may distort estimates of vaccine effectiveness derived from case-control studies, there have been few attempts to quantify the magnitude of these biases. METHODS We estimated the magnitude of potential biases in influenza vaccine effectiveness values derived from case-control studies from several factors, including bias from differential use of diagnostic testing based on influenza vaccine status, imperfect diagnostic test characteristics, and confounding. A decision tree model was used to simulate an influenza vaccine effectiveness case-control study in children. Using probability distributions, we varied the value of factors that influence vaccine effectiveness estimates, including diagnostic test characteristics, vaccine coverage, likelihood of receiving a diagnostic test for influenza, likelihood that a child hospitalized with acute respiratory infection had influenza, and others. Bias was measured as the difference between the effectiveness observed in the simulated case-control study and a true underlying effectiveness value. RESULTS AND CONCLUSIONS We found an average difference between observed and true vaccine effectiveness of -11.9%. Observed vaccine effectiveness underestimated the true effectiveness in 88% of model iterations. Diagnostic test specificity exhibited the strongest association with observed vaccine effectiveness, followed by the likelihood of receiving a diagnostic test based on vaccination status and the likelihood that a child hospitalized with acute respiratory infection had influenza. Our findings suggest that the potential biases in case-control studies that we examined tend to result in underestimates of true influenza vaccine effects.
Conics Touching a Quartic Surface with 13 Nodes

Motivated by questions occuring in the construction of certain twistor spaces the parameter space of conics tangent to a given quartic is investigated. For a given real quartic surface in complex $\PP ^3$ that has exactly 13 ordinary nodes as singularities this parameter space is studied. In particular, its irreducible components are described.
FPGA IMPLEMENTATION OF SCALABLE BANDWIDTH SINGLE CARRIER FREQUENCY DOMAIN MULTIPLE ACCESS TRANSCEIVER FOR THE FOURTH GENERATION WIRELESS COMMUNICATION 1

In this paper, design and implementation of 4G SCFDMA transceiver on FPGA is done and explained. Long Term Evolution (LTE) is next generation mobile communication standard from 3GPP, it is based on OFDMA) in Downlink Transmission and SC-FDMA in upli nk Transmission. SC-FDMA is based on Frequency Division Multiple Access scheme. When com pared with other multiple access scheme, it deals with the multiple users in a shared communication s ystems. SC-FDMA is also called as linearly pre-code d OFDMA, in the sense it has the additional discrete tim Fourier transform (DFT) processing in SC-FDMA . The main advantage of SC-FDMA over OFDMA is low Pea k to average power ratio, so the power transmission is low when compared. This work propos es a run time reconfiguration architecture for the SCFDMA. Where the bandwidth and sub carrier mapping s chemes of SC-FDMA can be changed. Real time FPGA implementation results are captured in the Chi pscope Pro Embedded Logic analyzer.
Co-Precipitation of Dissolved Organic Matter by Calcium Carbonate in Pyramid Lake, Nevada

Our previous research has demonstrated that dissolved organic matter (DOM) influences calcium carbonate mineral formation in surface and ground water. To better understand DOM mediation of carbonate precipitation and DOM co-precipitation and/or incorporation with carbonate minerals, we characterized the content and speciation of DOM in carbonate minerals and in the lake water of Pyramid Lake, Nevada, USA. A 400-gram block of precipitated calcium carbonate from the Pyramid Lake shore was dissolved in 8 liters of 10% acetic acid. Particulate matter not dissolved by acetic acid was removed by centrifugation. DOM from the carbonate rock was fractionated into nine portions using evaporation, dialysis, resin adsorption, and selective precipitations to remove acetic acid and inorganic constituents. The calcium carbonate rock contained 0.23% DOM by weight. This DOM was enriched in polycarboxylic proteinaceous acids and hydroxy-acids in comparison with the present lake water. DOM in lake water was composed of aliphatic, alicyclic polycarboxylic acids. These compound classes were found in previous studies to inhibit calcium carbonate precipitation. DOM fractions from the carbonate rock were 14 C-age dated at about 3,100 to 3,500 years before present. The mechanism of DOM co-precipitation and/or physical incorporation in the calcium carbonate is believed to be due to formation of insoluble calcium