Miracle-dz/UniFAR-FTUs huggingface dataset:
High fidelity synthetic aperture sonar products for target analysis

Synthetic aperture sonar (SAS) can produce images with centimetre-level resolution and area coverage of better than one square kilometer per hour. This makes SAS an ideal sensor for detection and classification of small targets over large areas. Fully automated target analysis allows improved autonomy when using autonomous underwater vehicles (AUVs) and saves a tedious manual analysis in post-mission analysis. Recognition of small targets in sonar imagery is, however, a difficult task. SAS imagery preserves wavenumber information. This gives the possibility for extra products in addition to high resolution imagery. We propose a two-stage processing where regions of interest are generated from reduced resolution SAS imagery and subsequently post processed images are used to generate relevant target analysis information. In this paper, we concentrate on the types of information available and their significance rather than the choice of intermediate resolution and initial detection methods. The extra processing products discussed in this paper are target-enhanced images by autofocus, shadow-enhanced images by fixed focusing, multi-aspect images, frequency-selective information and 3D shape from interferometry. We show examples of each of the additional products using data collected by the HISAS 1030 interferometric SAS carried by the HUGIN 1000-MR vehicle.
Shape-Based Averaging

A new method for averaging multidimensional images is presented, which is based on signed Euclidean distance maps computed for each of the pixel values. We refer to the algorithm as "shape-based averaging" (SBA) because of its similarity to Raya and Udupa's shape-based interpolation method. The new method does not introduce pixel intensities that were not present in the input data, which makes it suitable for averaging nonnumerical data such as label maps (segmentations). Using segmented human brain magnetic resonance images, SBA is compared to label voting for the purpose of averaging image segmentations in a multiclassifier fashion. SBA, on average, performed as well as label voting in terms of recognition rates of the averaged segmentations. SBA produced more regular and contiguous structures with less fragmentation than did label voting. SBA also was more robust for small numbers of atlases and for low atlas resolutions, in particular, when combined with shape-based interpolation. We conclude that SBA improves the contiguity and accuracy of averaged image segmentations
A Novel Capacity Outer Bound for the MIMO Gaussian Interference Channel and Application to Relay-Assisted Communications

A novel Genie-aided capacity outer bound is provided for MIMO Gaussian interference channels. Rather than requiring each side-informed receiver to cancel the interference from its received signal, it is suggested that each receiver views the interference as the useful signal undergoing a different channel, which we call an equivalent channel representation. Reflections on the existence and capacity enhancement of such equivalent channel representation are made. Subsequently, an application to relay-assisted communications is provided for which an achievable capacity region is determined. Finally, numerical examples are provided to demonstrate an increase of capacity owing to the proposed interference processing method.
The Social Future of Web Search: Modeling, Exploiting, and Searching Collaboratively Generated Content

Social, or collaboratively generated content (CGC) is transforming how we seek and find information online: it is now a prominent part of the web information ecosystem, and a powerful platform for information seeking. The resulting archives of both the content and the context of the interactions contain valuable information that is often not available elsewhere, and can be helpful for the development of novel ranking algorithms, and natural language processing, text mining, and information retrieval techniques. We review machine learning techniques for modeling CGC, focusing on tasks such as learning to estimate content quality, relevance, and searcher intent and satisfaction with the retrieved results. We describe how this information can be incorporated into learning-based ranking methods for searching social media, and how CGC could be used to improve performance on key text mining and search tasks.
The design and construction of the 50 million words KSUCCA

In this paper, we report the design and construction of King Saud University Corpus of Classical Arabic (KSUCCA), which is part of ongoing research that attempts to study the meanings of words used in the holy Quran, through analysis of their distributional semantics in contemporaneous texts. The holy Quranic text was revealed in pure Classical Arabic, which forms the basis of Arabic linguistic theory and which is well understood by the educated Arabic reader. Therefore, it is necessary to investigate the distributional lexical semantics of the Quran's words in the light of similar texts (corpus) that are written in pure Classical Arabic. To the best of our knowledge, there exist only two corpora of Classical Arabic; one is part of the King Abdulaziz City for Science and Technology Arabic Corpus (KACST Arabic Corpus) and the other is the Classical Arabic Corpus (CAC) (Elewa, 2009). However, neither of the two corpora is adequate for our research; the former does not cover many genres such as: Linguistics, Literature, Science, Sociology and Biography; and it only contains 17+ million words, so it is not very large. While the latter is even smaller with only 5 million words. Therefore, we made an effort to carefully design and compose our own corpus bearing in mind that it should be large enough, balanced, and representative so that any result obtained from it can be generalized for Classical Arabic. In addition, we tried to make the design general enough in order to make the corpus also appropriate for other research.
CounterMeasures: A game for teaching computer security

Computer security has become vital for protecting users, applications and data, yet the field still faces severe shortages in skilled professionals. Typical methods to teach security from textbooks and academic papers are not engaging and take considerable time. Our hypothesis is that a security game that closely emulates real-world systems can improve learning about computer security above and beyond just reading technical documents. Our security game, CounterMeasures, provides a game-type environment for learning and practicing security skills through a series of guided objectives. CounterMeasures uses a real, interactive shell for input and targets a real server for exploits to provide an environment resembling security systems currently deployed. Evaluation with 20 test subjects illustrates the merits and shows the potential of our approach.
Maximum likelihood detection in spatial multiplexing with FBMC

In FBMC transmission systems, the bit rate is maximized when OQAM modulation is employed. One of the characteristics of this modulation is that the received data symbols are accompanied by interference terms, which complicates the application of ML techniques in optimal decoders. Two approaches are proposed to cope with this situation. The first one exploits the MMSE estimation of the interference terms and it introduces no additional delay. In the second one, the interference terms are calculated from past, present and future data symbols, either already decided or estimated. The gains provided by these approaches, with respect to MMSE, are assessed and illustrated by simulation.
VEGF Spliced Variants: Possible Role of Anti-Angiogenesis Therapy

Angiogenesis has been targeted in retinopathies, psoriasis, and a variety of cancers (colon, breast, lung, and kidney). Among these tumour types, clear cell renal cell carcinomas (RCCs) are the most vascularized tumours due to mutations of the von Hippel Lindau gene resulting in HIF-1 alpha stabilisation and overexpression of Vascular Endothelial Growth Factor (VEGF). Surgical nephrectomy remains the most efficient curative treatment for patients with noninvasive disease, while VEGF targeting has resulted in varying degrees of success for treating metastatic disease. VEGF pre-mRNA undergoes alternative splicing generating pro-angiogenic isoforms. However, the recent identification of novel splice variants of VEGF with anti-angiogenic properties has provided some insight for the lack of current treatment efficacy. Here we discuss an explanation for the relapse to anti-angiogenesis treatment as being due to either an initial or acquired resistance to the therapy. We also discuss targeting angiogenesis via SR (serine/arginine-rich) proteins implicated in VEGF splicing.
Function-Based Access Control (FBAC): From Access Control Matrix to Access Control Tensor

The misuse of legitimate access to data is a serious information security concern for both organizations and individuals. From a security engineering viewpoint, this might be due to the failure of access control. Inspired by Functional Encryption, we introduce Function-Based Access Control (FBAC). From an abstract viewpoint, we suggest storing access authorizations as a three-dimensional tensor, or an Access Control Tensor (ACT) rather than the two-dimensional Access Control Matrix (ACM). In FBAC, applications do not give blind folded execution right and can only invoke commands that have been authorized for function defined data segments. So, one might be authorized to use a certain command on one object, while being forbidden to use the same command on another object. Such behavior can not be efficiently modeled using the classical access control matrix or achieved efficiently using cryptographic mechanisms. Here, we lay the theoretical foundations of FBAC and summarize our extended work on implementation and deployment recommendations.
A model for pricing data bundles based on minimax risks for estimation of a location parameter

Consider a situation involving many sources of finite-length data, with buyers potentially interested in purchasing data from any bundle (subset) of the sources. A principled way is presented to assign a price to each source, when the value of the data is measured in terms of how much information about an underlying location parameter can be extracted from it. Apart from the operational relevance to data pricing, these results also have relevance to sensor network theory.
Interaction Motivation Driven Virtual Human Emotion Modeling in Computer Engineering and Application

Affective computing had been widely used in computer engineering and applications fields. Emotion generation is an important research component in affective computing field and there were a lot of works had been put into generating lifelike emotion reaction and emotional behaviors [1-. OCC model is the most common used emotion model and can be integrated with other component to generate virtual humans emotion states. However
Reflection Modeling for Passive Stereo

Stereo reconstruction in presence of reality faces many challenges that still need to be addressed. This paper considers reflections, which introduce incorrect matches due to the observation violating the diffuse-world assumption underlying the majority of stereo techniques. Unlike most existing work, which employ regularization or robust data terms to suppress such errors, we derive two least squares models from first principles that generalize diffuse world stereo and explicitly take reflections into account. These models are parametrized by depth, orientation and material properties, resulting in a total of up to 5 parameters per pixel that have to be estimated. Additionally large non-local interactions between viewed and reflected surface have to be taken into account. These two properties make inference of the model appear prohibitive, but we present evidence that inference is actually possible using a variant of patch match stereo.
Transmission system congestion analysis based on a European electricity market and network simulation framework

The coupling of electricity markets and the increasing feed-in of renewable energy sources (RES) cause a rising number of congestions in the European transmission network. In order to ensure a secure network operation suitable measures for resolving these congestions need to be found. In this context, a methodology for analyzing congestions in transmission systems is presented in this paper. The methodology is based on a European electricity market and network simulation framework including internal congestion management by redispatch and control of high-voltage direct current (HVDC) links. In particular, the methodology enables to determine the frequency of occurrence, the causes as well as a ranking of existing congestions regarding their constraining effect on social welfare. The simulation results of a Europe 2030 case study underline that the introduced methodology offers a detailed insight into the system and can help to identify suitable network extension measures for avoiding overloads.
The robustness of NUMA memory management

The study of operating systems level memory management policies for nonuniform memory access time (NUMA) shared memory multiprocessors is an area of active research. Previous results have suggested that the best policy choice often depends on the application under consideration, while others have reported that the best policy depends on the particular architecture. Since both observations have merit, we explore the concept of policy tuning on an application/architecture basis.We introduce a highly tunable dynamic page placement policy for NUMA multiprocessors, and address issues related to the tuning of that policy to different architectures and applications. Experimental data acquired from our DUnX operating system running on two different NUMA multiprocessors are used to evaluate the usefulness, importance, and ease of policy tuning.Our results indicate that while varying some of the parameters can have dramatic effects on performance, it is easy to select a set of default parameter settings that result in good performance for each of our test applications on both architectures. This apparent robustness of our parameterized policy raises the possibility of machine-independent memory management for NUMA-class machines.
Twelve-month azathioprine as maintenance therapy in early diffuse systemic sclerosis patients treated for 1-year with low dose cyclophosphamide pulse therapy.

OBJECTIVE To investigate the role of azathioprine in maintaining improvement after 1-year low-dose IV pulse CYC therapy in patients with early diffuse Systemic Sclerosis (dcSSc). METHODS Thirteen patients with early dcSSc who had completed a year of treatment with low-dose IV pulse CYC underwent AZA treatment (100 mg/day) in a prospective 1-year study. Modified Rodnan skin score (mRss), Health Assessment Questionnaire-Disability Index (HAQ-DI), forced vital capacity (FVC), and diffusing lung capacity for CO (DLCO) were assessed as outcome measures. In addition, the nine organ/system Medsger et al. severity scores and the European Scleroderma Study Group (ESSG) activity index were evaluated. RESULTS The improvement from a year of CYC therapy was maintained by AZA treatment. No outcome measures deteriorated (mRss 8.23 +/- 2.9 vs. 6.38 +/- 3.4; HAQ-DI 0.38 +/- 0.4 vs. 0.32 +/- 0.3; FVC 89.5 +/- 13.2 vs. 89.4 +/- 15.9; DLCO 73.6 +/- 14.4 vs. 75.0 +/- 19.5), nor were there any increases in any organ/system severity scores or ESSG activity index detected. CONCLUSION This study suggests a role of AZA in maintaining the improvement induced by low dose pulse CYC in early dcSSc, making it possible a short duration of treatment at a low cumulative dose of the drug. These results, however, await confirmation in controlled studies.
M i -Edge Colorings of Graphs

An edge coloring of a graph G is called Mi-edge coloring if at most i colors appear at any vertex of G. Let Ki(G) denote the maximum number of colors used in an Mi-edge coloring of G. In this paper we determine the exact value of K2(G) for any graph G of maximum degree at most 3. Mathematics Subject Classification: 05C15, 05C38
Photopolymerizable polymer nanocomposites incorporated with hyperbranched polymer having ultrahigh index of refraction for holographic light manipulation

We report on the volume holographic grating formation in photopolymerizable polymer nanocomposites that incorporate new hyperbranched polymers (HBPs) acting as transporting organic nanoparticles. Since HBPs are easily dispersed to acrylate monomer without any aggregation and possesses ultrahigh index of refraction of the order of 1.8 in the green due to the inclusion of triazine and aromatic ring units, volume gratings with good optical quality and refractive index changes as large as 2.2 × 10−2 can be recorded. It is also shown that the out-of-plane thickness change due to polymerization shrinkage is reduced to 2% or lower by the HBP dispersion.
RANSAC-Based DARCES: A New Approach to Fast Automatic Registration of Partially Overlapping Range Images

In this paper, we propose a new method, the RANSAC-based DARCES method (data-aligned rigidity-constrained exhaustive search based on random sample consensus), which can solve the partially overlapping 3D registration problem without any initial estimation. For the noiseless case, the basic algorithm of our method can guarantee that the solution it finds is the true one, and its time complexity can be shown to be relatively low. An extra characteristic is that our method can be used even for the case that there are no local features in the 3D data sets.
Clone Mapper: An Online Suite of Tools for RNAi Experiments in Caenorhabditis elegans

RNA interference (RNAi), mediated by the introduction of a specific double-stranded RNA, is a powerful method to investigate gene function. It is widely used in the Caenorhabditis elegans research community. An expanding number of laboratories conduct genome-wide RNAi screens, using standard libraries of bacterial clones each designed to produce a specific double-stranded RNA. Proper interpretation of results from RNAi experiments requires a series of analytical steps, from the verification of the identity of bacterial clones, to the identification of the clones’ potential targets. Despite the popularity of the technique, no user-friendly set of tools allowing these steps to be carried out accurately, automatically, and at a large scale, is currently available. We report here the design and production of Clone Mapper, an online suite of tools specifically adapted to the analysis pipeline typical for RNAi experiments with C. elegans. We show that Clone Mapper overcomes the limitations of existing techniques and provide examples illustrating its potential for the identification of biologically relevant genes. The Clone Mapper tools are freely available via http://www.ciml. univ-mrs.fr/EWBANK_jonathan/software.html.
The atomistic structure of a Σ = 3, (111) grain boundary in NiAl, studied by quantitative high-resolution transmission electron microscopy

Abstract The atomistic structure of the Σ = 3, (111) gain boundary in NiAl has been determined by quantitative high-resolution transmission electron microscopy. In NiAl, which crystallizes in the B2 (CsCl) structure this grain boundary constitutes an 'incoherent twin boundary'. Using an atomic resolution microscope (JEM-ARM 130) we have obtained images of the grain-boundary structure at a point resolution of 0·105nm. To extract the atomistic structure quantitatively from these images we have applied a new method of digital image processing. This method yields the positions of Ni and Al columns in the grain-boundary core with a precision of 0·015 nm. The refined structure features Al atoms on the boundary plane. Compared with a geometric model the real boundary has an excess volume. Except for the region close to the boundary the atom configuration exhibits mirror symmetry with respect to the boundary plane. Near the boundary, however, lateral relaxations of atom positions break the mirror symmetry. The co.
Involvement of Arabidopsis thaliana ribosomal protein S27 in mRNA degradation triggered by genotoxic stress

A recessive Arabidopsis mutant with elevated sensitivity to DNA damaging treatments was identified in one out of 800 families generated by T‐DNA insertion mutagenesis. The T‐DNA generated a chromosomal deletion of 1287 bp in the promoter of one of three S27 ribosomal protein genes (ARS27A) preventing its expression. Seedlings of ars27A developed normally under standard growth conditions, suggesting wild‐type proficiency of translation. However, growth was strongly inhibited in media supplemented with methyl methane sulfate (MMS) at a concentration not affecting the wild type. This inhibition was accompanied by the formation of tumor–like structures instead of auxiliary roots. Wild‐type seedlings treated with increasing concentrations of MMS up to a lethal dose never displayed such a trait, neither was this phenotype observed in ars27A plants in the absence of MMS or under other stress conditions. Thus, the hypersensitivity and tumorous growth are mutant‐specific responses to the genotoxic MMS treatment. Another important feature of the mutant is its inability to perform rapid degradation of transcripts after UV treatment, as seen in wild‐type plants. Therefore, we propose that the ARS27A protein is dispensable for protein synthesis under standard conditions but is required for the elimination of possibly damaged mRNA after UV irradiation.
Recognition of pyrrolysine tRNA by the Desulfitobacterium hafniense pyrrolysyl-tRNA synthetase

Pyrrolysine (Pyl), the 22nd co-translationally inserted amino acid, is incorporated in response to a UAG amber stop codon. Pyrrolysyl-tRNA synthetase (PylRS) attaches Pyl to its cognate tRNA, the special amber suppressor tRNAPyl. The genes for tRNAPyl (pylT) and PylRS (pylS) are found in all members of the archaeal family Methanosarcinaceae, and in Desulfitobacterium hafniense. The activation and aminoacylation properties of D. hafniense PylRS and the nature of the tRNAPyl identity elements were determined by measuring the ability of 24 mutant tRNAPyl species to be aminoacylated with the pyrrolysine analog N-ε-cyclopentyloxycarbonyl-l-lysine. The discriminator base G73 and the first base pair (G1·C72) in the acceptor stem were found to be major identity elements. Footprinting analysis showed that PylRS binds tRNAPyl predominantly along the phosphate backbone of the T-loop, the D-stem and the acceptor stem. Significant contacts with the anticodon arm were not observed. The tRNAPyl structure contains the highly conserved T-loop contact U54·A58 and position 57 is conserved as a purine, but the canonical T- to D-loop contact between positions 18 and 56 was not present. Unlike most tRNAs, the tRNAPyl anticodon was shown not to be important for recognition by bacterial PylRS.