Miracle-dz/UniFAR-FTUs huggingface dataset:
STRENGTHEN AND UPGRADE REGIONAL CAPABILITIES (REGIONAL UNIVERSITY KNOWLEDGE CENTRE PROGRAMME IN HUNGARY)

The emerging vision of the modern, innovative Hungarian economy, which can compete successfully in the global arena, made it absolutely necessary to encourage business firms to be innovation-oriented and to encourage universities to develop, beyond their traditional teaching mission, also their research performance and their capabilities to transfer research results and new knowledge to convert them into commercially relevant innovations. The role of government was to create a suitable legal environment and proper incentives to stimulate and support change and to enable collaborations between Public and Private Sector actors. Despite all efforts in launching relevant programmes, the competency and attractiveness of universities for strategic research partnerships with the private sector remained heterogeneous and partially unsatisfactory because of shortcomings in their knowledge base and their capability to act as well-performing research partners in collaborative projects. In 2004 Hungary established a new complementary programme which addressed particularly these shortcomings, the Pazmany Peter – Regional University Knowledge Centre programme. This paper describes shortly the programme and then investigates the experiences of two initial calls. This Public-Private-Partnership model, where the state is not the single supporter of the programme, the participating Private Sector actors provide complementary funding. In addition, the centres can also attract external funding from various other sources. In addition, Private Sector enterprises make advanced technical equipment available for use by members and non-members. By the first experiences this programme is a good frame to support overcoming on one of the failure of the system, weak knowledge distribution capability. This initiative, the Pazmany Peter programme provides a potentially transferable example for other countries with shortcomings similar to those of Hungary’s National Science and Innovation System. It was the first policy measure which has attracted a large number of actors and united them in joint regional research activities. This form of Public Sector - Private Sector research collaborations is crucial for the flow of knowledge, the seamless transfer of research results to commercially relevant innovation and for feedback loops in development. The centres offer a stimulating environment for innovators and potential innovators, thus contributing to make the Hungarian economy more competitive.
D C ] 1 9 M ar 2 01 6 On the Space Complexity of Renaming

We study the space complexity of implementing long-lived an o e-shot adaptive renaming from multi-reader multi-writer registers, in an asynchron ous distributed system with n processes. As a result of anf -adaptive renaming algorithmeach participating process gets a distinct name in the range {1, . , f (k)} providedk processes participate. Let f : {1, . ,n}→N be a non-decreasing function satisfying f (1)≤ n−1 and letd=max{x | f (x)≤ n− 1}. We show that any non-deterministic solo-terminating long -lived f -adaptive renaming object requiresd+ 1 registers. This implies a lower bound of n− c registers for long-lived(k+ c)-adaptive renaming, which we observe is tight. We also prove a lower bound of ⌊2(n−c) c+2 ⌋ registers for implementing any non-deterministic soloterminating one-shot (k+c)-adaptive renaming. We provide two one-shot renaming algor ithms: a waitfree algorithm and an obstruction-free algorithm. Each alg orithm employs a parameter to depict the tradeoff between space and adaptivity. When these paramete rs ar chosen appropriately, this results in a wait-free one-shot (3k 2 2 )-adaptive renaming algorithm from⌈ √ n⌉+1 registers, and an obstruction-free one-shotf -adaptive renaming algorithm from only min { ,x | f (x)≥ 2n}+1 registers. 1mhelmikh@ucalgary.ca, +1 403 210-9416 2higham@ucalgary.ca, +1 403 220-7696 3woelfel@ucalgary.ca, +1 403 220-7259
Scaling limits for the transient phase of local Metropolis–Hastings algorithms

Summary. The paper considers high dimensional Metropolis and Langevin algorithms in their initial transient phase. In stationarity, these algorithms are well understood and it is now well known how to scale their proposal distribution variances. For the random‐walk Metropolis algorithm, convergence during the transient phase is extremely regular—to the extent that the algo‐rithm's sample path actually resembles a deterministic trajectory. In contrast, the Langevin algorithm with variance scaled to be optimal for stationarity performs rather erratically. We give weak convergence results which explain both of these types of behaviour and practical guidance on implementation based on our theory.
New ASIC/FPGA Cost Estimates for SHA-1 Collisions

SHA-1 remains, till date, the most widely used hash function, in spite of several successful cryptanalytic attacks against it. These attacks, however, remain impractical due to high computation complexity and associated cost. We endeavor to do cost-time product estimation for an attack by the aid of application-specific hardware acceleration. This work proposes an Application-Specific Instruction-set Processor (ASIP), named Cracken. Cracken is aimed to efficiently realize near collision attack on SHA-1. The estimations of the physical attack complexity is done using 65nm standard CMOS technology and commercial FPGA devices. It is estimated, with post-layout simulations, that Stevens' differential attack with an estimated complexity of 257.5, can be executed in 46 days using 4096 Cracken cores at a cost of €15m. Estimation for real collision with complexity 261 is also done. Our cost-time estimates reveal that an FPGA-based attack is more efficient compared to ASIC. Previously reported SHA-1 attacks based on ASIC and cloud computing platforms are also compiled and benchmarked for reference.
Dramatic response in the dependency to transfusion after low doses of lenalidomide treatment in a 5q-syndrome patient: a case report

5q-syndrome is a special subgroup of myelodysplastic syndrome in terms of follow-up and treatment. Lenalidomide is an immunomodulatory drug that is frequently used in the treatment of multiple myeloma. Some clinical studies have shown that lenalidomide treatment is effective in 5q syndrome and significantly decreases the transfusion dependency in these patients. In this paper, we would like to share a dramatic response of lowered transfusion dependency after treatment with low-dose lenalidomide in a patient who received myelodysplastic syndrome diagnosis and isolated 5q anomaly in our clinic.
A Novel Mouse Segmentation Method Based on Dynamic Contrast Enhanced Micro-CT Images

With the development of hybrid imaging scanners, micro-CT is widely used in locating abnormalities, studying drug metabolism, and providing structural priors to aid image reconstruction in functional imaging. Due to the low contrast of soft tissues, segmentation of soft tissue organs from mouse micro-CT images is a challenging problem. In this paper, we propose a mouse segmentation scheme based on dynamic contrast enhanced micro-CT images. With a homemade fast scanning micro-CT scanner, dynamic contrast enhanced images were acquired before and after injection of non-ionic iodinated contrast agents (iohexol). Then the feature vector of each voxel was extracted from the signal intensities at different time points. Based on these features, the heart, liver, spleen, lung, and kidney could be classified into different categories and extracted from separate categories by morphological processing. The bone structure was segmented using a thresholding method. Our method was validated on seven BALB/c mice using two different classifiers: a support vector machine classifier with a radial basis function kernel and a random forest classifier. The results were compared to manual segmentation, and the performance was assessed using the Dice similarity coefficient, false positive ratio, and false negative ratio. The results showed high accuracy with the Dice similarity coefficient ranging from 0.709 ± 0.078 for the spleen to 0.929 ± 0.006 for the kidney.
Dielectric Resonator Antennas for Polarization Diversity in Base Station Array Applications

Dielectric resonator antennas (DRA) are mostly investigated for frequencies above approx. 5 GHz, but in this paper they are suggested for use in the mobile communication standard UMTS (1.92 -2.17 GHz) base stations, because they can provide a denser aperture since they can be drastically reduced in size through proper selection of the materials dielectric constant. In this paper the main aspect will be the investigation of dual polarized resonators and the buildup of arrays. The goal is to provide a solution which can compete with the commercial market and additionally offer new possibilities.
Activation and repression functions of an SR splicing regulator depend on exonic versus intronic-binding position

SR proteins and related factors play widespread roles in alternative pre-mRNA splicing and are known to promote splice site recognition through their Arg–Ser-rich effector domains. However, binding of SR regulators to some targets results in repression of splice sites through a distinct mechanism. Here, we investigate how activated and repressed targets of the Drosophila SR regulator Transformer2 elicit its differing effects on splicing. We find that, like activation, repression affects early steps in the recognition of splice sites and spliceosome assembly. Repositioning of regulatory elements reveals that Tra2 complexes that normally repress splicing from intronic positions activate splicing when located in an exon. Protein tethering experiments demonstrate that this position dependence is an intrinsic property of Tra2 and further show that repression and activation are mediated by separate effector domains of this protein. When other Drosophila SR factors (SF2 and Rbp1) that activate splicing from exonic positions were tethered intronically they failed to either activate or repress splicing. Interestingly, both activities of Tra2 favor the exonic identity of the RNA sequences that encompass its binding sites. This suggests a model in which these two opposite functions act in concert to define both the position and extent of alternatively spliced exons.
User-weighted sentiment analysis for financial community on Twitter

Sentiment analysis is a popular research area in computer science. It aims to determine the attitude of a person with respect to some topic, such as his mood or opinion from textual documents generated by the person. With the proliferation of social micro-blogging sites, opinion text has become available in digital forms, thus enabling research on sentiment analysis to both deepen and broaden in different sociological fields, particularly in the finance field. In this paper, we propose a novel sentiment analysis method which added new user metrics to classical Naive Bayes based sentiment analysis method and applies it to the finance field. We also analyze the correlation between the mood of the financial community and the behavior of the stock exchange of Turkey, namely BIST 100 using Spearman's rank correlation coefficient (SRCC) method. Our empirical studies show that the proposed sentiment analysis method (SRCC value 0.5634) computes a moderate positive correlation between stock market behavior and the sentiment polarity of financial community.
Comparison of DFIG and Synchronous Machine for Storage Hydro-Power Generation

Among the alternative methods for energy storage , using the potential energy of water stored in different heights has be en considered by human for ages. Storage pumping plants have been invented for this purpose and are considered as one of the most reliable and effective methods of s the electrical energy. Factors such as having appropriate static and dynam ic stability, high efficiency, suitable steady state and transient performance, th e least cost of manufacturing, utilities and etc. can play a major role in choosin g the type of machines for energy- making. Therefore, advantages and capabilities of variable speed storage -pumping plants, compared with conventional synchronous one s, have drawn into consideration in this paper. Different viewpoints s uch as structure and steady state behavior are focused for comparing the application of Doubly Fed Induction Generators (DFIG) and synchronous ones in storage hydro plants. Dynamic stimulations are also used to evaluate the perform ance of variable-speed versus synchronous fixed-speed generation units.
On the Construction of E cient MultilevelCoded Modulations

Abstract We have recently proposed a class of high-rate binary linear codes based on low-density generator matrices (LDGM). With iterative decoding algorithm based on the belief propagation principle, these codes are shown to approach the capacity for the binary input Gaussian channel. In this paper, we shall apply these codes to M -ary signaling schemes by multilevel coding methods. The equivalent channel capacities for individual partition levels used in the multilevel coding systems are rst computed. Partition rules other than Ungerboeck's maximum intra-set distance criterion are examined. LDGM codes for individual levels are then selected according to the corresponding equivalent capacities. We shall show this approach can be used to devise systems that (1) achieve near channel capacity performances and (2) are able to provide unequal error protection. (Most of our results are summarized in Fig. 1.)
The correlation of the Lyman α forest in close pairs and groups of high-redshift quasars: clustering of matter on scales of 1–5 Mpc

We study the clustering of matter in the intergalactic medium from the Lyman a forests seen in the spectra of pairs or groups of z ∼ 2 quasars observed with FORS2 and UVES at the VLT-UT2 Kueyen ESO telescope. The sample consists of five pairs with separation of 0.6, 1, 2.1, 2.6 and 4.4 arcmin and a group of four quasars with separations from 2 up to 10 arcmin. This unprecedented data set allows us to measure the transverse flux correlation function for a range of angular scales. Correlations are clearly detectable at separations smaller than 3 arcmin. The shape and correlation length of the transverse correlation function on these scales are in good agreement with those expected from absorption by the photoionized warm intergalactic medium associated with the filamentary and sheet-like structures predicted in cold dark matter-like models for structure formation. At larger separation no significant correlation is detected. Assuming that the absorbing structures are randomly orientated with respect to the line of sight, the comparison of transverse and longitudinal correlation lengths constrains the cosmological parameters (as a modified version of the Alcock & Paczynski test). The present sample is too small to have significant constraints. Using N-body simulations, we investigate the possibility of constraining Ω A from future larger samples of quasistellar object pairs with similar separations. The observation of a sample of 30 pairs at 2, 4.5 and 7.5 arcmin should constrain the value of Ω A at ′15 per cent (2σ level). We also use the observed spectra of the group of four quasars to search for underdense regions in the intergalactic medium. We find a quasi-spherical structure of reduced absorption with radius 12.5 h - 1 Mpc, which we identify as an underdense region.
A video broadcast architecture utilizing the locality properties

We proposes a hybrid architecture MTreeTV which combines the use of P2P networks with dedicated streaming servers, and was proposed to build on the advantages of both P2P and CDN paradigms. MTreeTV uses a novel locality-aware overlay construction and scheduling algorithm to assure the effectiveness of P2P overlay. We also study the placement of the servers with constraints on the client to server paths and evaluate the effect of the server parameters. Through analysis and simulation, we show that MTreeTV supports fast channel switching (<4s).
Anagram generation using sentence probabilities

An anagram is a word or phrase made by transposing the letters of another word or phrase, and is a popular kind of puzzle. Finding anagrams for a word or a phrase is a difficult task due to the huge number of possible permutations of the letters, and using computers for anagram generation has been increasingly popular. This paper presents an attempt on constructing an automatic anagram generator based on sentence probabilities. Using a relatively small corpus of one million words, a simple implementation using bigram probabilities proved to yield quite satisfactory results but is too inclusive due to the limited context recorded in bigrams. A trigram based version produces much less incorrect results but would need a larger corpus since it is much more exclusive.
Income Convergence and Inflation in Central and Eastern Europe

This study investigates the process of price convergence in the ten new EU countries of Central and Eastern Europe. The analyses are based on panel data from 1995 to 2008 of the common currency price relative to the EU15 average. The lagged income level exhibits little explanatory power toward relative inflation, but the lagged price level has some explanatory power. In the long term, the relative income and price levels are closely correlated, implying concurrent real and nominal convergence. Deviations from the long-term relation between income and price levels are gradually decreased by changes in relative inflation and gross domestic product growth, but the process of convergence appears to be rather slow. In the short term, the capital inflows associated with current account deficits put substantial upward pressure on relative price inflation, but the Balassa-Samuelson effect appears to be subdued.
Cross-modal effects on learning: a seismic stimulus improves color discrimination learning in a jumping spider

SUMMARY The production of multimodal signals during animal displays is extremely common, and the function of such complex signaling has received much attention. Currently, the most frequently explored hypotheses regarding the evolution and function of complex signaling focus on the signal and/or signaler, or the signaling environment, while much less attention has been placed on the receivers. However, recent studies using vertebrates suggest that receiver psychology (e.g. learning and memory) may play a large role in the evolution of complex signaling. To date, the influence of multimodal cues on receiver learning and/or memory has not been studied in invertebrates. Here, we test the hypothesis that the presence of a seismic (vibratory) stimulus improves color discrimination learning in the jumping spider Habronattus dossenus. Using a heat-aversion learning experiment, we found evidence for a cross-modal effect on color learning. Over a series of training trials, individuals exposed to a seismic stimulus jumped onto the heated color less frequently and remained there for less time than did individuals not exposed to a seismic stimulus. In addition, in a final no-heat test trial, individuals from the seismic-present treatment were more likely to avoid the previously heated color than were individuals from the seismic-absent treatment. This is the first study to demonstrate a cross-modal influence on learning in an invertebrate.
Prognostic value of baseline human immunodeficiency virus type 1 DNA measurement for disease progression in patients receiving nucleoside therapy.

Human immunodeficiency virus (HIV) type 1 DNA assay data were obtained at baseline from 111 HIV-1-positive subjects who were treated with nucleosides. Higher baseline DNA level, HIV-1 RNA level, and infectious titer were comparably associated with an increased hazard of disease progression (each P<.03). Only DNA level was significantly associated with survival (adjusted hazard ratio for 1 log(10) higher level, 3.99; 95% confidence interval, 1.44-11.09; P=. 008).
ISO/IEC 18000-7 based on RFID multi-hop relay system

In this paper, we analyze the ISO/IEC 18000-7 active RFID system. In order to improve the coverage in sensor networks, which includes a large number of active RFID tags, we propose RFID multi-hop relay system using active RFID relay tags. To compare the performance of the existing ISO/IEC 18000-7 with that of the proposed RFID multi-hop relay system, we introduce new system efficiency and sensitivity-based measures of the achieved coverage. Also, we analyze the performance of the proposed system and compare it with that of the existing system through the analyses of minimum coupling loss (MCL) and system level simulation (SLS).
Relative in vitro wood decay resistance of sapwood from landscape trees of southern temperate regions

The development of wood decay caused by 12 major root-rot and trunk-rot fungi was investigated in vitro with sapwood extracted from nine ornamental and landscape hardwood and conifer species native to southern temperate regions of North America, Europe, and the lower Mississippi Delta. Wood decay rates based on dry weight loss for 108 host tree-wood decay fungi combinations were compared at 21 8C over 1-year and 2-year incubation periods in the absence of tree-resistance mechanisms. Strains of Armillaria mellea, Ganoderma lucidum, and Heterobasidion annosum exhibited the highest decay potential in most tree species tested. The order of fungi causing the greatest decay varied over time as a result of temporal changes in decay-rate curves. Relative wood durability or resistance to decay generally was greater in gymnosperm than in angiosperm wood types. Quercus nuttallii, Fraxinus pennsylvanica, and Quercus lyrata sustained the highest levels of decay by all fungi. Northern white cedar (Thuja occidentalis) sapwood was most resistant to decay by all rot-fungi tested, sustaining only limited weight loss after 1 and 2 years of decay, although sapwood of Pinus taeda, Liquidambar styraciflua, and Platanus occidentalis had relatively low levels of decay after 2 years. These results in combination with data from portable decay-detection devices provide useful information for the management of tree breakages or failures resulting from wood decay fungi in hazardous landscape trees. Some potential landscaping applications for tree evaluations, risk assessments, and selections for tree-replacement plantings are discussed.
An Efficient Silent Data Corruption Detection Method with Error-Feedback Control and Even Sampling for HPC Applications

The silent data corruption (SDC) problem is attracting more and more attentions because it is expected to have a great impact on exascale HPC applications. SDC faults are hazardous in that they pass unnoticed by hardware and can lead to wrong computation results. In this work, we formulate SDC detection as a runtime one-step-ahead prediction method, leveraging multiple linear prediction methods in order to improve the detection results. The contributions are twofold: (1) we propose an error feedback control model that can reduce the prediction errors for different linear prediction methods, and (2) we propose a spatial-data-based even-sampling method to minimize the detection overheads (including memory and computation cost). We implement our algorithms in the fault tolerance interface, a fault tolerance library with multiple checkpoint levels, such that users can conveniently protect their HPC applications against both SDC errors and fail-stop errors. We evaluate our approach by using large-scale traces from well-known, large-scale HPC applications, as well as by running those HPC applications on a real cluster environment. Experiments show that our error feedback control model can improve detection sensitivity by 34-189% for bit-flip memory errors injected with the bit positions in the range [20,30], without any degradation on detection accuracy. Furthermore, memory size can be reduced by 33% with our spatial-data even-sampling method, with only a slight and graceful degradation in the detection sensitivity.