Miracle-dz/UniFAR-FTUs huggingface dataset:
Building a Dataset of Multilingual Cognates for the Romanian Lexicon

Identifying cognates is an interesting task with applications in numerous research areas, such as historical and comparative linguistics, language acquisition, cross-lingual information retrieval, readability and machine translation. We propose a dictionary-based approach to identifying cognates based on etymology and etymons. We account for relationships between languages and we extract etymology-related information from electronic dictionaries. We employ the dataset of cognates that we obtain as a gold standard for evaluating to which extent orthographic methods can be used to detect cognate pairs. The question that arises is whether they are able to discriminate between cognates and non-cognates, given the orthographic changes undergone by foreign words when entering new languages. We investigate some orthographic approaches widely used in this research area and some original metrics as well. We run our experiments on the Romanian lexicon, but the method we propose is adaptable to any language, as far as resources are available.
Onebody: Remote Posture Guidance System using First Person View in Virtual Environment

We present Onebody, a virtual reality system for remote posture guidance during sports or physical activity training, such as martial arts, yoga or dance, using first person perspective. The system uses skeletal tracking of the instructor and the students, rendered as virtual avatars. Using a virtual reality headset, the student can visualise the movement of the instructor's avatar, rendered in place of their own body. Onebody provides a first person perspective of the movement instruction, allowing the student to step into the instructor's body. We conducted a study to compare the performance of Onebody in terms of posture matching accuracy and user's preference, with existing techniques of delivering movement instructions, including pre-recorded video, video conferencing and third person view virtual reality. The result indicated that Onebody offers better posture accuracy in delivering movement instructions.
Speech Enhancement and Recognition in Meetings With an Audio–Visual Sensor Array

This paper addresses the problem of distant speech acquisition in multiparty meetings, using multiple microphones and cameras. Microphone array beamforming techniques present a potential alternative to close-talking microphones by providing speech enhancement through spatial filtering. Beamforming techniques, however, rely on knowledge of the speaker location. In this paper, we present an integrated approach, in which an audio-visual multiperson tracker is used to track active speakers with high accuracy. Speech enhancement is then achieved using microphone array beamforming followed by a novel postfiltering stage. Finally, speech recognition is performed to evaluate the quality of the enhanced speech signal. The approach is evaluated on data recorded in a real meeting room for stationary speaker, moving speaker, and overlapping speech scenarios. The results show that the speech enhancement and recognition performance achieved using our approach are significantly better than a single table-top microphone and are comparable to a lapel microphone for some of the scenarios. The results also indicate that the audio-visual-based system performs significantly better than audio-only system, both in terms of enhancement and recognition. This reveals that the accurate speaker tracking provided by the audio-visual sensor array proved beneficial to improve the recognition performance in a microphone array-based speech recognition system.
Lattice-Based Array Contraction: From Theory to Practice

We build on prior work on intra-array memory reuse, for which a general theoretical framework was proposed based on lattice theory. Intra-array memory reuse is a way of reducing the size of a temporary array by folding, thanks to a(cid:14)ne mappings and modulo operations, reusing memory locations when they contain a value not used later. We describe the algorithms needed to implement such a strategy. Our implementation has two parts. The (cid:12)rst part, Bee, uses the source-to-source transformer ROSE to extract from the program all necessary information on the lifetime of array elements and to generate the code after memory reduction. The second part is a stand-alone mathematical tool dedicated to optimizations on polyhedra, in particular the computation of successive minima and the computation of good admissible lattices, which are the basis for lattice-based memory reuse. Both tools are developed in C++ and use linear programming and polyhedra manipulations. These tools can be used either for memory reduction in programs { e.g, to limit memory expansion introduced for parallelization { or for memory reduction in high-level synthesis { e.g., to design adequate memories between communicating hardware acceler-ators. Abstract We build on prior work on intra-array memory reuse, for which a general theoretical framework was proposed based on lattice theory. Intra-array memory reuse is a way of reducing the size of a temporary array by folding, thanks to a(cid:14)ne mappings and modulo operations, reusing memory locations when they contain a value not used later. We describe the algorithms needed to implement such a strategy. Our implementation has two parts. The (cid:12)rst part, Bee, uses the source-to-source transformer ROSE to extract from the program all necessary information on the lifetime of array elements and to generate the code after memory reduction. The second part is a stand-alone mathematical tool dedicated to optimizations on polyhedra, in particular the computation of successive minima and the computation of good admissible lattices, which are the basis for lattice-based memory reuse. Both tools are developed in C++ and use linear programming and polyhedra manipulations. These tools can be used either for memory reduction in programs { e.g, to limit memory expansion introduced for parallelization { or for memory reduction in high-level synthesis { e.g., to design adequate memories between communicating hardware accelerators.
ReNIC: Architectural extension to SR-IOV I/O virtualization for efficient replication

Virtualization is gaining popularity in cloud computing and has become the key enabling technology in cloud infrastructure. By replicating the virtual server state to multiple independent platforms, virtualization improves the reliability and availability of cloud systems. Unfortunately, existing Virtual Machine (VM) replication solutions were designed only for software virtualized I/O, which suffers from large performance and scalability overheads. Although hardware-assisted I/O virtualization (such as SR-IOV) can achieve close to native performance and very good scalability, they cannot be properly replicated across different physical machines due to architectural limitations (such as lack of efficient device state read/write, buffering outbound packets, etc.). In this paper, we address those architectural limitations, by proposing ReNIC, an architectural extension to SR-IOV I/O virtualization for efficient I/O replications. We have extended Xen hypervisor and the Remus rapid checkpoint solution to support this new architectural extension. We developed a system simulator on multi-core systems to extensively evaluate ReNIC. The experimental results demonstrate that ReNIC achieves up to 54% CPU usage reduction, compared to software based I/O virtualization at runtime, and up to 16.2% performance advantage over software based I/O virtualization in rapid checkpoint. During migration, ReNIC reduces service shutdown time by about 50%, compared to device emulation and paravirtualized I/O, and over 71% compared to teaming driver.
Pseudorandom Generator Based on Hard Lattice Problem

This paper studies how to construct a pseudorandom generator using hard lattice problems. We use a variation of the classical hard problem Inhomogeneous Small Integer Solution ISIS of lattice, say Inhomogeneous Subset Sum Solution ISSS. ISSS itself is a hash function. Proving the preimage sizes ISSS hash function images are almost the same, we construct a pseudorandom generator using the method in [GKL93]. Also, we construct a pseudoentropy generator using the method in [HILL99]. Most theoretical PRG constructions are not feasible in fact as they require rather long random bits as seeds. Our PRG construction only requires seed length to be O(n log2 n) which is feasible practically.
Protein Microarray Characterization of the S-Nitrosoproteome*

Nitric oxide (NO) mediates a substantial part of its physiologic functions via S-nitrosylation, however the cellular substrates for NO-mediated S-nitrosylation are largely unknown. Here we describe the S-nitrosoproteome using a high-density protein microarray chip containing 16,368 unique human proteins. We identified 834 potentially S-nitrosylated human proteins. Using a unique and highly specific labeling and affinity capture of S-nitrosylated proteins, 138 cysteine residues on 131 peptides in 95 proteins were determined, defining critical sites of NO's actions. Of these cysteine residues 113 are novel sites of S-nitrosylation. A consensus sequence motif from these 834 proteins for S-nitrosylation was identified, suggesting that the residues flanking the S-nitrosylated cysteine are likely to be the critical determinant of whether the cysteine is S-nitrosylated. We identify eight ubiquitin E3 ligases, RNF10, RNF11, RNF41, RNF141, RNF181, RNF208, WWP2, and UBE3A, whose activities are modulated by S-nitrosylation, providing a unique regulatory mechanism of the ubiquitin proteasome system. These results define a new and extensive set of proteins that are susceptible to NO regulation via S-nitrosylation. Similar approaches could be used to identify other post-translational modification proteomes.
Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion

Significance We know little about the nature of the evolved interaction networks that give rise to the rapid coordinated collective response exhibited by many group-living organisms. Here, we study collective evasion in schooling fish using computational techniques to reconstruct the scene from the perspective of the organisms themselves. This method allows us to establish how the complex social scene is translated into behavioral response at the level of individuals and to visualize, and analyze, the resulting complex communication network as behavioral change spreads rapidly through groups. Thus, we can map, for any moment in time, the extent to which each individual is socially influential during collective evasion and predict the magnitude of such behavioral epidemics before they actually occur. Coordination among social animals requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the communication network. Establishing the decision-making circuits and networks that give rise to individual behavior has been a central goal of neuroscience. However, the analogous problem of determining the structure of the communication network among organisms that gives rise to coordinated collective behavior, such as is exhibited by schooling fish and flocking birds, has remained almost entirely neglected. Here, we study collective evasion maneuvers, manifested through rapid waves, or cascades, of behavioral change (a ubiquitous behavior among taxa) in schooling fish (Notemigonus crysoleucas). We automatically track the positions and body postures, calculate visual fields of all individuals in schools of ∼150 fish, and determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals use simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates throughout groups are complex, being weighted, directed, and heterogeneous. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion and establish that individuals with relatively few, but strongly connected, neighbors are both most socially influential and most susceptible to social influence. Furthermore, we demonstrate that we can predict complex cascades of behavioral change at their moment of initiation, before they actually occur. Consequently, despite the intrinsic stochasticity of individual behavior, establishing the hidden communication networks in large self-organized groups facilitates a quantitative understanding of behavioral contagion.
Effects of Carnitine Isomers on Fatty Acid Metabolism in Ischemic Swine Hearts

We studied the hemodynamic and metabolic effects of treatments with the L- and DL- isomers of carnitine in four groups (n = 42) of intact working swine hearts rendered mildly ischemic (−46% reduction in global perfusion). In three groups (n = 34), free fatty acids (FFA) in the coronary perfusate were augmented with labeled palmitate (0.72 /μnol/ml). The inclusion of excess FFA per se (n = 11), as compared with nonsupplemented hearts, further and significantly depressed mechanical function (−40% and −55% declines in left ventricular (LV)-developed pressure and work), stimulated a 2-fold increase in FFA uptake (but without a corresponding increase in “CO2 production), raised fatty acyl-CoA levels in tissue (94 to 132 nmol/g dry), and shortened group survival. Treatments with both L- and DL-carnitine (serum values 6687 and 6398 nmol/ml) effected significant improvements in several parameters of mechanical function and survival. LV-developed pressure and work at end-ischemia were increased (+50% and +62% in L-treated hearts and +48% and +65% in DL-treated hearts). Myocardial oxygen consumption was similar to that of untreated FFA-supplemented hearts. During the middle to late portion of the perfusion trials in L-treated hearts (n = 9), FFA uptake and14CO2production were significantly reduced, and accumulation of tissue long-chain acyl-CoA was less (−44%, P < 0.05). Metabolic trends in DL-carnitine-treated hearts ranged between those in untreated and L- carnitine-treated hearts. These data suggest that carnitine reduces availability or incorporation of FFA intracellularly, and this benefits the heart mechanically during ischemic restrictions in coronary flow. The L-isomer appears to be the more biologically active.
Delivery of Acid Sphingomyelinase in Normal and Niemann-Pick Disease Mice Using Intercellular Adhesion Molecule-1-Targeted Polymer Nanocarriers

Type B Niemann-Pick disease (NPD) is a multiorgan system disorder caused by a genetic deficiency of acid sphingomyelinase (ASM), for which lung is an important and challenging therapeutic target. In this study, we designed and evaluated new delivery vehicles for enzyme replacement therapy of type B NPD, consisting of polystyrene and poly(lactic-coglycolic) acid polymer nanocarriers targeted to intercellular adhesion molecule (ICAM)-1, an endothelial surface protein up-regulated in many pathologies, including type B NPD. Real-time vascular imaging using intravital microscopy and postmortem imaging of mouse organs showed rapid, uniform, and efficient binding of fluorescently labeled ICAM-1-targeted ASM nanocarriers (anti-ICAM/ASM nanocarriers) to endothelium after i.v. injection in mice. Fluorescence microscopy of lung alveoli actin, tissue histology, and 125I-albumin blood-to-lung transport showed that anti-ICAM nanocarriers cause neither detectable lung injury, nor abnormal vascular permeability in animals. Radioisotope tracing showed rapid disappearance from the circulation and enhanced accumulation of anti-ICAM/125I-ASM nanocarriers over the nontargeted naked enzyme in kidney, heart, liver, spleen, and primarily lung, both in wild-type and ASM knockout mice. These data demonstrate that ICAM-1-targeted nanocarriers may enhance enzyme replacement therapy for type B NPD and perhaps other lysosomal storage disorders.
Exploiting Benchmark Patterns for Efficient Microarchitecture Simulation

The early stages of microarchitecture design rely heavily on simulation for evaluation.However, the complexity of modern processors and their associated software models, make simulation a very time consuming process. This is seen as amajor obstacle to a thorough exploration of the design space. We propose a sampling technique to greatly decrease simulation time without losing the effectiveness of a full benchmark simulation. Samples for simulation are determined by identifying the unique behavioral patterns in the benchmark. Simulation speed up is achieved by simulating only the regions associated with the unique patterns and skipping the regions exhibiting redundant behavior. Additionally we exploit the observation that for a few benchmarks, the unique patterns also occur in a smaller input-set of the benchmark, which further increases the potential for simulation speed up. Quantitative evaluation shows that the proposed technique results in a 72 times reduction in simulation time with an average sample induced error of 2.3% for the key processor
A superpixel based post-processing approach for segmenting dermoscopy images

Malignant melanoma is among the most rapidly increasing cancers in the world. Image border detection is often the first step to characterize skin lesion for the follow-up computer-aided diagnosis. As the existing segmentation techniques tend to find the sharpest pigment change in the dermoscopy images, the detected lesion borders are mostly contained inside the borders delineated manually by the dermatologists. Therefore, post-processing steps are needed to smooth and expand the segmented borders. In this paper, we propose a novel post-processing approach to enhance the accuracy of segmentation results, by merging superpixels which intersect with skin lesion area based on skin color consistency. The experimental results on the real dermoscopy image set show that the proposed method can improve the overall performance in terms of both accuracy and robustness.
WHAT CONTROLS THE Fe ii STRENGTH IN ACTIVE GALACTIC NUCLEI?

We used a large, homogeneous sample of 4178 z ⩽ 0.8 Seyfert 1 galaxies and QSOs selected from the Sloan Digital Sky Survey to investigate the strength of Fe ii emission and its correlation with other emission lines and physical parameters of active galactic nuclei. We find that the strongest correlations of almost all the emission-line intensity ratios and equivalent widths (EWs) are with the Eddington ratio (L/LEdd), rather than with the continuum luminosity at 5100 Å (L5100) or black hole mass (MBH); the only exception is the EW of ultraviolet Fe ii emission, which does not correlate at all with broad-line width, L5100, MBH, or L/LEdd. By contrast, the intensity ratios of both the ultraviolet and optical Fe ii emission to Mg ii λ2800 correlate quite strongly with L/LEdd. Interestingly, among all the emission lines in the near-UV and optical studied in this paper (including Mg ii λ2800, Hβ, and [O iii] λ5007), the EW of narrow optical Fe ii emission has the strongest correlation with L/LEdd. We hypothesize that the variation of the emission-line strength in active galaxies is regulated by L/LEdd because it governs the global distribution of the hydrogen column density of the clouds gravitationally bound in the line-emitting region, as well as its overall gas supply. The systematic dependence on L/LEdd must be corrected when using the Fe ii/Mg ii intensity ratio as a measure of the Fe/Mg abundance ratio to study the history of chemical evolution in QSO environments.
Top-Antitop Pair Production Close to Threshold Synopsis of Recent NNLO Results

Using non-relativistic effective theories, new next-to-next-to-leading order (NNLO) QCD corrections to the total $$t{\bar t}$$ production cross section at the Linear Collider have been calculated recently. In this article the NNLO calculations of several groups are compared and the remaining uncertainties are discussed. The theoretical prospects for an accurate determination of top quark mass parameters are discussed in detail. An outlook on possible future improvements is given.
Phenotypic Resistance and the Dynamics of Bacterial Escape from Phage Control

The canonical view of phage - bacterial interactions in dense, liquid cultures is that the phage will eliminate most of the sensitive cells; genetic resistance will then ascend to restore high bacterial densities. Yet there are various mechanisms by which bacteria may remain sensitive to phages but still attain high densities in their presence – because bacteria enter a transient state of reduced adsorption. Importantly, these mechanisms may be cryptic and inapparent prior to the addition of phage yet result in a rapid rebound of bacterial density after phage are introduced. We describe mathematical models of these processes and suggest how different types of this ‘phenotypic’ resistance may be elucidated. We offer preliminary in vitro studies of a previously characterized E. coli model system and Campylobacter jejuni illustrating apparent phenotypic resistance. As phenotypic resistance may be specific to the receptors used by phages, awareness of its mechanisms may identify ways of improving the choice of phages for therapy. Phenotypic resistance can also explain several enigmas in the ecology of phage-bacterial dynamics. Phenotypic resistance does not preclude the evolution of genetic resistance and may often be an intermediate step to genetic resistance.
Accelerate MapReduce on GPUs with multi-level reduction

With Graphics Processing Units (GPUs) becoming more and more popular in general purpose computing, more attentions have been paid on building a framework to provide convenient interfaces for GPU programming. MapReduce can greatly simplify the programming for data-parallel applications in cloud computing environment, and it is also naturally suitable for GPUs. However, there are some problems in recent reduction-based MapReduce implementation on GPUs. Its performance is dramatically degraded when handling massive distinct keys because the massive data cannot be stored in tiny shared memory entirely. A new MapReduce framework on GPUs, called Jupiter, is proposed with continuous reduction structure. Two improvements are supported in Jupiter, a multi-level reduction scheme tailored for GPU memory hierarchy and a frequency-based cache policy on key-value pairs in shared memory. Shared memories are utilized efficiently for various data-parallel applications whether involving little or abundant distinct keys. Experiments show that Jupiter can achieve up to 3x speedup over the original reduction-based GPU MapReduce framework on the applications with lots of distinct keys.
Learning Trigonometric Polynomials from Random Samples and Exponential Inequalities for Eigenvalues of Random Matrices

Motivated by problems arising in random sampling of trigonometric poly- nomials, we derive exponential inequalities for the operator norm of the dif- ference between the sample second moment matrix n 1 UU and its expec- tation where U is a complex random nD matrix with independent rows. These results immediately imply deviation inequalities for the largest (small- est) eigenvalues of the sample second moment matrix, which in turn lead to results on the condition number of the sample second moment matrix. We also show that trigonometric polynomials in several variables can be learned from constDlnD random samples.