Miracle-dz/UniFAR-FTUs huggingface dataset:
Terminated and Tailbiting Spatially Coupled Codes With Optimized Bit Mappings for Spectrally Efficient Fiber-Optical Systems

We study the design of spectrally efficient fiber-optical communication systems based on different spatially coupled (SC) forward error correction (FEC) schemes. In particular, we optimize the allocation of the coded bits from the FEC encoder to the modulation bits of the signal constellation. Two SC code classes are considered. The codes in the first class are protograph-based low-density parity-check (LDPC) codes which are decoded using iterative soft-decision decoding. The codes in the second class are generalized LDPC codes which are decoded using iterative hard-decision decoding. For both code classes, the bit allocation is optimized for the terminated and tailbiting SC cases based on a density evolution analysis. An optimized bit allocation can significantly improve the performance of tailbiting SC codes over the baseline sequential allocation, up to the point where they have a comparable gap to capacity as their terminated counterparts, at a lower FEC overhead. For the considered terminated SC codes, the optimization only results in marginal performance improvements, suggesting that in this case a sequential allocation is close to optimal.
Body size evolution in South American Liolaemus lizards of the boulengeri clade: a contrasting reassessment

Bergmann's rule predicts larger body sizes in species living in higher latitudes and altitudes. This rule appears to be valid for endotherms, but its relevance to ectotherm vertebrates has largely been debated. In squamate reptiles (lizards and snakes), only one study, based on Liolaemus species of the boulengeri clade, has provided phylogenetic evidence in favour of Bergmann's clines. We reassessed this model in the same lizard clade, using a more representative measure of species body size and including a larger number of taxa in the sample. We found no evidence to support Bergmann's rule in this lineage. However, these non‐significant results appear to be explained only by the inclusion of further species rather than by a different estimation of body size. Analyses conducted on the 16 species included in the previous study always revealed significant relationships between body size and latitude–altitude, whereas, the enlarged sample always rejected the pattern predicted by Bergmann's rule.
Cesar-FD: An Effective Stateful Fault Detection Mechanism in Drug Discovery Grid

Workflow management system is widely accepted and used in the wide area network environment, especially in the e-Science application scenarios, to coordinate the operation of different functional components and to provide more powerful functions. The error-prone nature of the wide area network environment makes the fault-tolerance requirements of workflow management become more and more urgent. In this paper, we propose Cesar-FD, a stateful fault detection mechanism, which builds up states related to the runtime and external environments of workflow management system by aggregating multiple messages and provides more accurate notifications asynchronously. We demonstrate the use of this mechanism in the Drug Discovery Grid environment by two use cases. We also show that it can be used to detect faulty situations more accurately.
Improving deep neural networks based multi-accent Mandarin speech recognition using i-vectors and accent-specific top layer

In this paper, we propose a method that use i-vectors and model adaptation techniques to improve the performance of deep neural networks(DNNs) based multi-accent Mandarin speech recognition. I-vectors which are speaker-speciﬁc features have been proved to be effective when used in accent identiﬁcation. They can be used in company with conventional spectral features as the input features of DNNs to improve the discrimination for different accents. Meanwhile, we adapt DNNs to different accents by using an accent-speciﬁc top layer and shared hidden layers. The accent-speciﬁc top layer is used to adap-t to different accents while the share hidden layers which can be seen as feature extractors can extract discriminative high-level features between different accents. These two techniques are complementary and can be easily combined together. Our experiments on the 400-hours Intel Accented Mandarin Speech Recognition Corpus show that our proposed method can signiﬁ-cantly improve the performance of DNNs-based accented Mandarin speech recognition.
Cryptanalysis of the CHES 2009/2010 Random Delay Countermeasure

Inserting random delays in cryptographic implementations is often used as a countermeasure against side-channel attacks. Most previ- ous works on the topic focus on improving the statistical distribution of these delays. For example, ecient random delay generation algorithms have been proposed at CHES 2009/2010. These solutions increase se- curity against attacks that solve the lack of synchronization between dierent leakage traces by integrating them. In this paper, we demon- strate that integration may not be the best tool to evaluate random delay insertions. For this purpose, we rst describe dierent attacks exploiting pattern recognition techniques and Hidden Markov Models. Using these tools, we succeed in cryptanalyzing a (straightforward) implementation of the CHES 2009/2010 proposal in an Atmel microcontroller, with the same data complexity as an unprotected implementation of the AES Ri- jndael. In other words, we completely cancel the countermeasure in this case. Next, we show that our cryptanalysis tools are remarkably robust to attack improved variants of the countermeasure, e.g. with additional noise or irregular dummy operations. We also exhibit that the attacks remain applicable in a non-proled adversarial scenario. Overall, these results suggest that the use of random delays may not be eective for pro- tecting small embedded devices against side-channel leakage. They also conrm the need of worst-case analysis in physical security evaluations.
On Pattern Preserving Graph Generation

Real datasets always play an essential role in graph mining and analysis. However, nowadays most available real datasets only support millions of nodes. Therefore, the literature on Big Data analysis utilizes statistical graph generators to generate a massive graph (e.g., billions of nodes) for evaluating the scalability of an algorithm. Nevertheless, current popular statistical graph generators are properly designed to preserve only the statistical metrics, such as the degree distribution, diameter, and clustering coefficient of the original social graphs. Recently, the importance of frequent graph patterns has been recognized in the various works on graph mining, but unfortunately this crucial criterion has not been noticed in the existing graph generators. To address this important need, we make the first attempt to design a Pattern Preserving Graph Generation (PPGG) algorithm to generate a graph including all frequent patterns and three most popular statistical parameters: degree distribution, clustering coefficient, and average vertex degree. The experimental results show that PPGG, which we have released as a free download, is efficient and able to generate a billion-node graph in approximately 10 minutes, much faster than the existing graph generators.
Helicobacter pylori: A Possible Risk Factor for Bone Health

Background Helicobacter pylori (H. pylori) infection may cause systemic inflammation and increase the production of tumor necrosis factor-α, interleukin-1, and interleukin-6. Unfortunately, bone mineral density also may be affected by these cytokines. This study aimed to evaluate the association between bone mineral density and H. pylori infection. Methods A cross-sectional study evaluated 1,126 men undergoing a comprehensive health screening in a private Korean screening center. Subjects' sera were tested for H. pylori antibodies (immunoglobulin G) using an enzyme-linked immunosorbent assay, and bone mineral densities (g/cm2) of the lumbar spine, femoral neck, and total femur were obtained using dual-energy X-ray absorptiometry. To evaluate the difference in bone mineral density according to H. pylori infection status, the adjusted mean bone mineral densities at each site were compared after adjusting for potential confounders, including age, sex, body mass index, smoking, alcohol consumption, and exercise. Results H. pylori infection was associated with a significant decrease in mean lumbar bone mineral density (H. pylori-positive, 1.190 g/cm2; H. pylori-negative, 1.219 g/cm2; P=0.006), which was greatest among men who were ≥50 years old (H. pylori-positive, 1.193 g/cm2; H. pylori-negative, 1.233 g/cm2; P=0.006). However, no significant association was observed in the bone mineral densities of the total femur and femoral neck. Conclusion In men, H. pylori infection was negatively associated with lumbar bone mineral density. This association may be useful in the early detection, prevention, and management of male osteoporosis.
Abstracts. Symposium on Heavy Metals in the Environment

Background: The translational efficiency of an mRNA can be modulated by upstream open reading frames (uORFs) present in certain genes. A uORF can attenuate translation of the main ORF by interfering with translational reinitiation at the main start codon. uORFs also occur by chance in the genome, in which case they do not have a regulatory role. Since the sequence determinants for functional uORFs are not understood, it is difficult to discriminate functional from spurious uORFs by sequence analysis. Results: We have used comparative genomics to identify novel uORFs in yeast with a high likelihood of having a translational regulatory role. We examined uORFs, previously shown to play a role in regulation of translation in Saccharomyces cerevisiae, for evolutionary conservation within seven Saccharomyces species. Inspection of the set of conserved uORFs yielded the following three characteristics useful for discrimination of functional from spurious uORFs: a length between 4 and 6 codons, a distance from the start of the main ORF between 50 and 150 nucleotides, and finally a lack of overlap with, and clear separation from, neighbouring uORFs. These derived rules are inherently associated with uORFs with properties similar to the GCN4 locus, and may not detect most uORFs of other types. uORFs with high scores based on these rules showed a much higher evolutionary conservation than randomly selected uORFs. In a genome-wide scan in S. cerevisiae, we found 34 conserved uORFs from 32 genes that we predict to be functional; subsequent analysis showed the majority of these to be located within transcripts. A total of 252 genes were found containing conserved uORFs with properties indicative of a functional role; all but 7 are novel. Functional content analysis of this set identified an overrepresentation of genes involved in transcriptional control and development. Conclusion: Evolutionary conservation of uORFs in yeasts can be traced up to 100 million years of separation. The conserved uORFs have certain characteristics with respect to length, distance from each other and from the main start codon, and folding energy of the sequence. These newly found characteristics can be used to facilitate detection of other conserved uORFs. Published: 8 August 2007 BMC Bioinformatics 2007, 8:295 doi:10.1186/1471-2105-8-295 Received: 8 June 2007 Accepted: 8 August 2007 This article is available from: http://www.biomedcentral. com/1471-2105/8/295 © 2007 Cvijović et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Defected ground structure for bandwidth improvement of artificial magnetic conductor-based microwave absorber

In this paper, the bandwidth improvement technique applied for microwave absorber is numerically investigated. The proposed technique is carried out by defecting or making some structure on the ground surface of microwave absorber, thus it is known as defected ground structure (DGS). The absorber that is constructed based on artificial magnetic conductor (AMC) concept has narrow bandwidth due to the characteristic of AMC structure. There are 3 kinds of DGS pattern utilized in the proposed technique. Each pattern will be investigated and analyzed through the unit cell of AMC structure. From the result, it shows that the bandwidth of microwave absorber with DGS pattern and PEC boundary condition is improved up to 6% compared to the bandwidth of microwave absorber without DGS. The utilization of DGS pattern is also lowering the resonance frequency of microwave absorber from 3.62 GHz to 2.98 GHz for PEC boundary condition. In addition, the incorporation of external resistors with particular resistance value put between adjacent patches in parallel to the incoming wave has shown the significant contribution to increase the absorption rate of microwave absorber.
An overview of MechBass: A four string robotic bass guitar

Traditional robotic guitar-like stringed instruments have lacked sufficient degrees of freedom and responsivity required to emulate even an average human guitar player. We seek to address this in the design and construction of a modular four-string robotic bass guitar, MechBass. This paper describes the various components of each module and the system-level operation of MechBass. The result is an instrument that can outperform (in terms of capability and consistency) even a highly skilled human guitar player.
Face detection based on AdaBoost algorithm with differential images

Recently, a powerful face detection method based on AdaBoost algorithm is drawing attention to various applications. This method provides face detection systems with a good detection rate, although a considerable number of weak classifiers are needed. This paper introduces weak classifiers which can not be or can be less influenced by gradual brightness changes in face regions or changes in lighting condition. Using a simple mathematical model for these changes, we have found that a second-order differentiation, e.g. Laplacian Operator, is very useful to cope with these changes. In order to show the effectiveness, we have compared the classification results for original and differential images with and without normalization. As a result, the second-order differentiation is found to be very effective, regardless of normalization of images. This result suggests the number of weak classifiers may be reduced to a great extent, while preserving equal detection capability.
Use of the growing environment as a source of variation to identify the quantitative trait transcripts and modules of co-expressed genes that determine chlorogenic acid accumulation

Developing Coffea arabica seeds accumulate large amounts of chlorogenic acids (CGAs) as a storage form of phenylpropanoid derivatives, making coffee a valuable model to investigate the metabolism of these widespread plant phenolics. However, developmental and environmental regulations of CGA metabolism are poorly understood. In the present work, the expression of selected phenylpropanoid genes, together with CGA isomer profiles, was monitored throughout seed development across a wide set of contrasted natural environments. Although CGA metabolism was controlled by major developmental factors, the mean temperature during seed development had a direct impact on the time-window of CGA biosynthesis, as well as on final CGA isomer composition through subtle transcriptional regulations. We provide evidence that the variability induced by the environment is a useful tool to test whether CGA accumulation is quantitatively modulated at the transcriptional level, hence enabling detection of rate-limiting transcriptional steps [quantitative trait transcripts (QTTs)] for CGA biosynthesis. Variations induced by the environment also enabled a better description of the phenylpropanoid gene transcriptional network throughout seed development, as well as the detection of three temporally distinct modules of quantitatively co-expressed genes. Finally, analysis of metabolite-to-metabolite relationships revealed new biochemical characteristics of the isomerization steps that remain uncharacterized at the gene level.
Clinical Biomarkers and Pathogenic-Related Cytokines in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a common autoimmune disease with unknown etiology and pathogenesis. Although major therapeutic advances have been made in recent years, there is no cure for the disease. Current medications mainly reduce inflammation in order to relieve pain and slow joint damage, but many have potentially serious side effects. Therefore, to find specific biomarkers will benefit both RA patients to find relief from the disease and physicians to monitor the disease development. A number of biomarkers have been discovered and used clinically, and others are still under investigation. The autoantibodies, which are widely used in diagnosis and prognosis, novel biomarkers, which reflect clinical disease activity, and newly found biomarkers and pathogenic-related cytokines are discussed in this review.
White light from an electroluminescent diode made from poly[3(4‐octylphenyl)‐2,2′‐bithiophene] and an oxadiazole derivative

We report on an electroluminescent diode emitting red, green, and blue light simultaneously. The device is based on a thin polymer layer, poly[3‐(4‐octylphenyl)‐2,2’‐bithiophene] and a thick molecular layer, 2‐(4‐biphenylyl)‐5‐(4‐tertbutyl‐phenyl)1,3,5‐oxadiazole. The quantum efficiency for light conversion is 0.3% and the turn‐on voltage for light emission is 7 V. In this article we present electric and spectroscopic characterizations. A mechanism for the light emission, based on electron and hole recombination between the two organic layers, is proposed.
Stochastic wire length sampling for cycle time estimation

Cycle time models perform an a-priori calculation of local signal delays by estimating the lengths of wires connecting different levels of synchronously clocked logic elements. Typically, a signal will have to pass through approximately 15-25 layers of logic during a single clock cycle and it is has been assumed that this number is sufficiently large to allow average wire lengths to be used. This paper investigates the accuracy of this mean value assumption by comparing cycle times calculating using average wire lengths with cycle times calculated using wires sampled from an estimate of the wire length distribution in each wiring layer. The sampling algorithm provides a more accurate calculation of the cycle time and also an estimate of its variation due to the inherently stochastic nature of the layout process. Results for a benchmark netlist, implemented in 0.25 μm technology, indicate that for a logic depth of 25 the mean value assumption is satisfactory and that clock rate has a standard deviation of approximately 5% of this mean value due to the inherently stochastic nature of the layout process.
Design And Application Of A Gradient-Weighted Moving Finite Element Code, Part I, In 1-D

This paper reports on the design of a robust and versatile gradient-weighted Moving Finite Element code in 1-D and its application to a variety of diicult PDE's and PDE systems. A companion paper, Part II, will do the same for the 2-D case. These moving node methods are especially suited to problems which develop sharp moving fronts, especially problems where one needs to resolve the ne-scale structure of the fronts. Brief explanations are given of the variational interpretation of GWMFE, the geometrical-mechanical interpretation, simpliied regularization terms, and the treatment of PDE systems. There are many possible pitfalls in the design of GWMFE codes; Section 5 discusses special features of the implicit 1-D and 2-D codes which contribute greatly to their robustness and eeciency. Section 6 uses a few simple examples to illustrate the workings of the method, some diiculties, and reasons for the standard choices of the internodal viscosity regularization coeecient. Section 7 reports numerical trials on several more diicult PDE systems. Section 8 discusses the failure of the method on certain steady-state convection problems. Section 9 describes a simple nonlinear \Krylov subspace" accelerator for Newton's method, a routine which greatly decreases the number of Jacobian evaluations required for our stii ODE solver.
Value proposition and social proof in online deals: an exploratory study of Groupon.com

In this paper, we examine the role of value proposition and social proof on the success of localized online deals that are made available in coupon form. We develop a model to understand what factors affect coupon sales of a deal and conduct an empirical validation study on Groupon.com, the leading localized daily deal website. We find that both the value proposition and the level of social proof play an important role in demand generation for deals, and that our model can successfully predict future coupon sales. Based on our findings, we describe the managerial implications and directions for future research.
Matching game for green uplink in hyper dense LTE HeTNets

In this paper, we aim to improve the energy efficiency of cellular users located in hyper-dense co-channel deployments of LTE small cell Networks (SCNs), randomly distributed within LTE macro cell networks (MCNs). Avoiding the severe cross-tier interferences at the small base stations (SBSs) levels caused by the uplink transmissions between the macro indoor users (which are inside the SBS coverage area) and the macro base station (MBS), ensuring load balancing, and improving energy efficiency are critical technical challenges in hyper-dense co-channel LTE SCNs deployments. As a solution, we formulate our problem as a matching game, then we propose the deferred acceptance algorithm to compute the optimal stable matching consisting of assigning each macro indoor user to the most suitable SBS and vice versa. Simulation results validate our solution, and show how it can effectively improve the energy efficiency of cellular users in hyper-dense LTE HetNets compared to the default Max-SINR association scheme.
Bayesian Mixed Membership Models for Soft Classification 1

The paper describes and applies a fully Bayesian approach to soft classification using mixed membership models. Our model structure has assumptions on four levels: population, subject, latent variable, and sampling scheme. Population level assumptions describe the general structure of the population that is common to all subjects. Subject level assumptions specify the distribution of observable responses given individual membership scores. Membership scores are usually unknown and hence we can also view them as latent variables, treating them as either fixed or random in the model. Finally, the last level of assumptions specifies the number of distinct observed characteristics and the number of replications for each characteristic. We illustrate the flexibility and utility of the general model through two applications using data from: (i) the National Long Term Care Survey where we explore disability classifications; (ii) semantic decompositions of abstracts and bibliographies from articles published in The Proceedings of the National Academy of Sciences. In the first application we use a Monte Carlo Markov chain implementation for sampling from the posterior distribution. In the second application, because of the size and complexity of the data base, we use a variational approximation to the posterior. We also include a guide to other applications of mixed membership modeling.