Miracle-dz/UniFAR-FTUs huggingface dataset:
Priori-Information Aided Iterative Hard Threshold: A Low-Complexity High-Accuracy Compressive Sensing Based Channel Estimation for TDS-OFDM

This paper develops a low-complexity channel estimation (CE) scheme based on compressive sensing (CS) for time-domain synchronous (TDS) orthogonal frequency-division multiplexing (OFDM) to overcome the performance loss under doubly selective fading channels. Specifically, an overlap-add method of the time-domain training sequence is first proposed to obtain the coarse estimates of the channel length, path delays, and path gains of the wireless channel, by exploiting the channel's temporal correlation to improve the robustness of the coarse CE under the severe fading channel with long delay spread. We then propose the priori-information aided (PA) iterative hard threshold (IHT) algorithm, which utilizes the priori information of the acquired coarse estimate for the wireless channel and therefore is capable of obtaining an accurate channel estimate of the doubly selective fading channel. Compared with the classical IHT algorithm whose convergence requires the l2 norm of the measurement matrix being less than 1, the proposed PA-IHT algorithm exploits the priori information acquired to remove such a limitation and to reduce the number of required iterations. Compared with the existing CS-based CE method for TDS-OFDM, the proposed PA-IHT algorithm significantly reduces the computational complexity of CE and enhances the CE accuracy. Simulation results demonstrate that, without sacrificing spectral efficiency and changing the current TDS-OFDM signal structure, the proposed scheme performs better than the existing CE schemes for TDS-OFDM in various scenarios, particularly under severely doubly selective fading channels.
A data mining method to predict transcriptional regulatory sites based on differentially expressed genes in human genome

Very large-scale gene expression analysis, i.e., UniGene and dbEST, are provided to find those genes with significantly differential expression in specific tissues. The differentially expressed genes in a specific tissue are potentially regulated concurrently by a combination of transcription factors. This study attempts to mine putative binding sites on how combinations of the known regulatory sites homologs and over-represented repetitive elements are distributed in the promoter regions of considered groups of differentially expressed genes. We propose a data mining approach to statistically discover the significantly tissue-specific combinations of known site homologs and over-represented repetitive sequences, which are distributed in the promoter regions of differential gene groups. The association rules mined would facilitate to predict putative regulatory elements and identify genes potentially co-regulated by the putative regulatory elements.
GENOMIC SEQUENCE SEARCHES AND PHYLOGENETIC TREES

The past decade has seen a remarkable explosion in our knowledge of the size and diversity of the myosin superfamily. Since these actin-based motors are candidates to provide the molecular basis for many cellular movements, it is essential that motility researchers be aware of the complete set of myosins in a given organism. The availability of cDNA and/or draft genomic sequences from humans, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana, Saccharomyces cerevisiae, Schizosaccharomyces pombe, and Dictyostelium discoideum has allowed us to tentatively define and compare the sets of myosin genes in these organisms. This analysis has also led to the identification of several putative myosin genes that may be of general interest. In humans, for example, we find a total of 40 known or predicted myosin genes including two new myosins-I, three new class II (conventional) myosins, a second member of the class III/ninaC myosins, a gene similar to the class XV deafness myosin, and a novel myosin sharing at most 33% identity with other members of the superfamily. These myosins are in addition to the recently discovered class XVI myosin with N-terminal ankyrin repeats and two human genes with similarity to the class XVIII PDZ-myosin from mouse. We briefly describe these newly recognized myosins and extend our previous phylogenetic analysis of the myosin superfamily to include a comparison of the complete or nearly complete inventories of myosin genes from several experimentally important organisms.
Relativizing an incompressible number and an incompressible function through subrecursive extensions of Turing machines

We show in this article that uncomputability is also a relative property of subrecursive classes built on a recursive relative incompressible function, which acts as a higher-order "yardstick" of irreducible information for the respective subrecursive class. We define the concept of a Turing submachine, and a recursive relative version for the Busy Beaver function and for the halting probability (or Chaitin's constant) Omega; respectively the Busy Beaver Plus (BBP) function and a time-bounded halting probability. Therefore, we prove that the computable BBP function defined on any Turing submachine is neither computable nor compressible by any program running on this submachine. In addition, we build a Turing submachine that can use lower approximations to its own time-bounded halting probability to calculate the values of its Busy Beaver Plus function, in the "same" manner that universal Turing machines use approximations to Omega to calculate Busy Beaver values. Thus, the algorithmic information carried by the BBP function is relatively incompressible (and uncomputable) at the same time that it still is occasionally reached by submachines. We point that this phenomenon enriches the research on the relativization and simulation of uncomputability and irreducible information.
Fast ADMM Algorithm for Distributed Optimization with Adaptive Penalty

We propose new methods to speed up convergence of the Alternating Direction Method of Multipliers (ADMM), a common optimization tool in the context of large scale and distributed learning. The proposed method accelerates the speed of convergence by automatically deciding the constraint penalty needed for parameter consensus in each iteration. In addition, we also propose an extension of the method that adaptively determines the maximum number of iterations to update the penalty. We show that this approach effectively leads to an adaptive, dynamic network topology underlying the distributed optimization. The utility of the new penalty update schemes is demonstrated on both synthetic and real data, including an instance of the probabilistic matrix factorization task known as the structure from motion problem.
Behçet’s Disease: an Insight from a Cardiologist’s Point of View

Behçet's disease (BD) is an enigmatic inflammatory disorder, with vasculitis (perivasculitis) underlying pathophysiology of its multisystemic affections. Venous pathology and thrombotic complications are hallmarks of BD. However, it has been increasingly recognized that cardiac involvement and arterial complications (aneurysms, pseudoaneurysms, rupture and thrombosis) are important part of the course of BD. Pericarditis, myocardial (diastolic and/or systolic dysfunction), valvular and coronary (thrombosis, aneurysms, rupture) involvement, intracardiac thrombi (predominantly right-sided) are, probably, the most frequent cardiac manifestations. Treatment of cardiovascular involvement in BD is largely empirical and aimed at suppression of vasculitis. The most challenging seems to be the treatment of arterial aneurysms and thromboses due to the associated risk of bleedings. Cardiologists should always bear in mind potential threats of (a)symptomatic cardiovascular involvement in BD.
Event-Based Distributed $H_{\infty }$ Filtering Networks of 2-DOF Quarter-Car Suspension Systems

This paper is concerned with the problem of vertical attitude estimation of a two-degree-of-freedom quarter-car suspension system by designing a distributed filtering network, where several distributed filters estimate vehicle heave motion cooperatively under consideration of external disturbance, network channel noises, and measurement error. The sampled data are transmitted through wireless networks. In order to reduce network traffic load and save communication resources, a novel periodic event-triggered sampling scheme is proposed, under which data are transmitted only when the proposed triggering condition is violated. Codesign of event-triggered and distributed filters is derived to guarantee well $H_{\infty }$ robustness to the system noises considered above. Finally, the experiments are given to show the effectiveness of the proposed filtering system.
Determining a Robust, Pareto Optimal Geometry for a Welded Joint

Multi-criteria optimization problems are known to give rise to a set of Pareto optimal solutions where one solution cannot be regarded as being superior to another. It is often stated that the selection of a particular solution from this set should be based on additional criteria. In this paper a methodology has been proposed that allows a robust design to be selected from the Pareto optimal set. This methodology has been used to determine a robust geometry for a welded joint. It has been shown that the robust geometry is dependent on the variability of the geometric parameters.
Short-Term Generation Asset Valuation: A Real Options Approach

This paper discusses using real options to value power plants with unit commitment constraints over a short-term period. We formulate the problem as a multistage stochastic problem and propose a solution procedure that integrates forward-moving Monte Carlo simulation with backward-moving dynamic programming. We assume that the power plant operator maximizes expected profit by deciding in each hour whether or not to run the unit, that a certain lead time for commitment and decommitment decisions is necessary to start up and shut down a unit, and that these commitment decisions, once made, are subject to physical constraints such as minimum uptime and downtime. We also account for the costs associated with starting up and shutting down a unit. Last, we assume that there are hourly markets for both electricity and the fuel used by the generator and that their prices follow Ito processes. Using numerical simulation, we show that failure to consider physical constraints may significantly overvalue a power plant.
The ASCH superfamily: novel domains with a fold related to the PUA domain and a potential role in RNA metabolism

Several studies show that transcription coactivators are often bi-functional ribonucleoprotein complexes that also regulate pre-mRNA processing and splicing decisions. Using sensitive sequence profile searches and structural comparisons we show that the C-terminal domain of the human coactivator protein ASC-1 defines a novel superfamily, the ASC-1 homology (ASCH) domain. The approximately 110 amino acid long ASCH domains are widely represented in all the three superkingdoms of life and several prokaryotic viruses. We show that the ASCH superfamily adopts a beta-barrel fold similar to the PUA domain superfamily. Using multiple lines of evidence, we suggest that members of the ASCH superfamily are likely to function as RNA-binding domains in contexts related to coactivation, RNA-processing and possibly prokaryotic translation regulation. Structural analysis of ASCH domains reveals the presence of a potential RNA-binding cleft associated with a conserved sequence motif, which is characteristic of this superfamily. Despite their similar structure, the ASCH and PUA domains appear to occupy distinct functional niches, with the former domains typically occurring in a standalone form in polypeptides, and the latter domains showing fusions to a variety of RNA-modifying enzymes.
The Dead Cryptographers Society Problem

This paper defines The Dead Cryptographers Society Problem - DCS (where several great cryptographers created many polynomial-time Deterministic Turing Machines (DTMs) of a specific type, ran them on their proper descriptions concatenated with some arbitrary strings, deleted them and left only the results from those running, after they died: if those DTMs only permute and sometimes invert the bits on input, is it possible to decide the language formed by such resulting strings within polynomial time? ), proves some facts about its computational complexity, and discusses some possible uses on Cryptography, such as into distance keys distribution, online reverse auction and secure communication.
A new plastics material for engineering applications based on polyethylene terephthalate

Polyethylene terephthalate (PETP) forms the basis of a new plastics material, Hostadur®, which is suitable for mouldings in engineering applications which are subject to mechanical stress. The crystallisation behaviour of PETP is discussed as this is an important factor if economic processing by injection moulding is to be obtained. Short-term properties of the material such as stiffness, strength and toughness were found to be good. Creep rupture strength, and fatigue strength under alternating stress, as well as other long-term properties, were found to be better than with other thermoplastics such as polyamides and polyacetals.
The Effects of Interaction on Spoken Discourse

Near-term spoken language systems will likely be limited in their interactive capabilities. To design them, we shall need to model how the presence or absence of speaker interaction influences spoken discourse patterns in different types of tasks. In this research, a comprehensive examination is provided of the discourse structure and performance efficiency of both interactive and noninteractive spontaneous speech in a seriated assembly task. More specifically, telephone dialogues and audiotape monologues are compared, which represent opposites in terms of the opportunity for confirmation feedback and clarification subdialogues. Keyboard communication patterns, upon which most natural language heuristics and algorithms have been based, also are contrasted with patterns observed in the two speech modalities. Finally, implications are discussed for the design of near-term limited-interaction spoken language systems.
Downregulation of fibroblast growth factor receptor 2 and its isoforms correlates with a high proliferation rate and poor prognosis in high-grade glioma.

Fibroblast growth factor receptor 2 (FGFR-2) contributes to the progression of numerous types of cancers; however, its role in glioma has yet to be determined. We investigated the expression of FGFR-2 and its predominant isoforms, FGFR-2 IIIb and FGFR-2 IIIc, in gliomas of all histological grades. Using immunohistochemistry, we demonstrated that FGFR-2, FGFR-2 IIIb and FGFR-2 IIIc were expressed in the astrocytes of normal human brains. The percentages of cells expressing FGFR-2, FGFR-2 IIIb and FGFR-2 IIIc and the intensities of their staining in glioblastomas (grade IV) were significantly reduced when compared to these parameters in the low-grade tumors (grade I, II and III; P<0.05). A high MIB-1 index, indicated by Ki-67 expression in >20% of the cells, was also associated with low expression of each FGFR-2 protein. Lower expression of FGFR-2 and FGFR-2 IIIc was correlated with a reduced survival rate (P=0.02 and 0.0253, respectively). Quantitative PCR analysis confirmed that the mRNA levels of FGFR-2 IIIb and FGFR-2 IIIc in a high-grade glioma-derived cell line (YKG-1) were lower than levels in a low-grade glioma-derived cell line (KG-1-C). These findings suggest that the decrease or loss of FGFR-2, FGFR-2 IIIb and FGFR-2 III in high-grade gliomas correlates with poor prognosis, which we attribute to the high proliferation rate of the tumor.
Phenolic compounds and sensorial characterization of wines aged with alternative to barrel products made of Spanish oak wood (Quercus pyrenaica Willd.)

Wood of Quercus pyrenaica has suitable properties for the wine ageing process. However, the forest available for the barrel making from this particular type of tree is very limited. Nevertheless, it is highly advisable to use this kind of wood in order to manufacture alternative oak products. This study presents the results of ageing the same red wine using different pieces of wood (chips and staves) of Spanish oak (Q. pyrenaica), American oak (Quercus alba) and French oak (Quercus petraea) in conjunction with small, controlled amounts of oxygen. In addition, the phenolic parameters, colour and sensory analysis point out that wines aged with Q. pyrenaica pieces have similar enological characteristics to those aged with American or French oak pieces of wood (chips and staves). Furthermore, the total oxygen consumed and its relation with sensory properties also has been studied in this article in order to know how the oxygen behaves in these processes. Besides, it is going to put forward the fact that chips and staves from Q. pyrenaica oak are suitable for the ageing of red wines and better considered than American or French ones, showing higher aromatic intensity, complexity, woody, balsamic and cocoa. Finally, the tasters valued highly the wines with staves, pointing out its flavour and roundness in mouth.
Numerical Drape Behavior of Circular Fabric Sheets Over Circular Pedestals

Draping of circular fabric sheets over a circular pedestal is a typical large displacement/ rotation post-buckling deformation problem. Different deformed shapes or drape patterns may appear when repeating the same draping experiment for the same piece of fabric. This paper explores the possibility of using numerical techniques to reproduce this complicated but interesting fabric drape behavior. A recently developed geometrically nonlinear finite-volume method is deployed here in the numerical simulation. An initially flat circular fabric sheet is first subdivided into a number of structured finite volumes (or control volumes) by mesh lines along the warp and weft directions, resulting in rectan gular internal volumes and triangular or quadrilateral boundary volumes. Each control volume contains one grid node. The strains and curvatures and hence the out-of-plane bending and in-plane membrane strain energies of a typical volume can be evaluated using the global coordinates of its grid node and several neighbors surrounding it. The equi librium equations of the fabric sheet are derived by employing the principle of stationary total potential energy. The full Newton-Raphson iteration method with line searches is used to solve the nonlinear algebraic equations resulting from the formulation. Numerical results of two circular fabric pieces of different sizes and materials are presented. The predicted symmetrically deformed shape of the first fabric sheet is compared with existing experimental results, demonstrating good agreement between the two approaches. Several other asymmetrical drape patterns for each fabric sheet are presented, demonstrating that the proposed finite-volume method is capable of predicting not only the basic deformed shape of a circular fabric sheet, but also other possible drape patterns in a real experiment.
An information-theoretic approach to the correspondence-free AX=XB sensor calibration problem

For the case of an exact set of compatible A's and B's with known correspondence, the AX=XB problem was solved decades ago. However, in many applications, data streams containing the A's and B's will often have different sampling rates or will be asynchronous. For these reasons and the fact that each stream may contain gaps in information, methods that require minimal a priori knowledge of the correspondence between A's and B's would be superior to the existing algorithms that require exact correspondence. We present an information-theoretic algorithm for recovering X from a set of A's and a set of B's that does not require a priori knowledge of correspondences. The algorithm views the problem in terms of distributions on the group SE(3), and minimizing the Kullback-Leibler divergence of these distributions with respect to the unknown X. This minimization is performed by an efficient numerical procedure that reliably recovers an unknown X.
Influence of microenvironment on engraftment of transplanted β-cells

Abstract Pancreatic islet transplantation into the liver provides a possibility to treat selected patients with brittle type 1 diabetes mellitus. However, massive early β-cell death increases the number of islets needed to restore glucose homeostasis. Moreover, late dysfunction and death contribute to the poor long-term results of islet transplantation on insulin independence. Studies in recent years have identified early and late challenges for transplanted pancreatic islets, including an instant blood-mediated inflammatory reaction when exposing human islets to the blood microenvironment in the portal vein and the low oxygenated milieu of islets transplanted into the liver. Poor revascularization of remaining intact islets combined with severe changes in the gene expression of islets transplanted into the liver contributes to late dysfunction. Strategies to overcome these hurdles have been developed, and some of these interventions are now even tested in clinical trials providing a hope to improve results in clinical islet transplantation. In parallel, experimental and clinical studies have, based on the identified problems with the liver site, evaluated the possibility of change of implantation organ in order to improve the results. Site-specific differences clearly exist in the engraftment of transplanted islets, and a more thorough characterization of alternative locations is needed. New strategies with modifications of islet microenvironment with cells and growth factors adhered to the islet surface or in a surrounding matrix could be designed to intervene with site-specific hurdles and provide possibilities to improve future results of islet transplantation.
Cosmological perturbations from an inhomogeneous phase transition

A mechanism for generating metric perturbations in inflationary models is considered. Long-wavelength inhomogeneities of light scalar fields in a decoupled sector may give rise to superhorizon fluctuations of couplings and masses in the low-energy effective action. Cosmological phase transitions may then occur that are not simultaneous in space, but occur with time lags in different Hubble patches that arise from the long-wavelength inhomogeneities. Here an interesting model in which cosmological perturbations may be created at the electroweak phase transition is considered. The results show that phase transitions may be a generic source of non-Gaussianity.
Mining causality graph for automatic web-based service diagnosis

It is crucial for Internet company to provide highly reliable web-based services. The web-based services always have many components running in the large-scale infrastructure with complex interactions. As an indispensable part of high reliability, the diagnosis remains to be a thorny problem. With the growth of system scale and complexity, it becomes even more difficult. In this paper, we propose an automatic diagnosis system based on causality graph to help system operators find the root causes. The causality graph is mainly extracted from the historical data of the monitoring system, and the method consists of four steps. 1) It utilizes a data mining method to extract the initial causality graph. 2) Once a failure happens, it lists top-k suspects with a ranking algorithm based on the causality graph. 3) Then system operators check the suspects and label them either right or wrong. 4) A supervised learning algorithm takes the labels as the input to tune the causality graph, in order to improve the diagnosis accuracy on step 2 iteratively. This method requires neither knowledge about the design and implementation details of the web-based service, nor instrumenting the services' source code. Our controlled experiments show that the root causes can be ranked in top 3 with 100% accuracy after countable learning iterations.