Miracle-dz/UniFAR-FTUs huggingface dataset:
Entropy of near-extremal black holes in AdS_5

We construct the microstates of near-extremal black holes in AdS_5 x S5 as gases of defects distributed in heavy BPS operators in the dual SU(N) Yang-Mills theory. These defects describe open strings on spherical D3-branes in the S5, and we show that they dominate the entropy by directly enumerating them and comparing the results with a partition sum calculation. We display new decoupling limits in which the field theory of the lightest open strings on the D-branes becomes dual to a near-horizon region of the black hole geometry. In the single-charge black hole we find evidence for an infrared duality between SU(N) Yang-Mills theories that exchanges the rank of the gauge group with an R-charge. In the two-charge case (where pairs of branes intersect on a line), the decoupled geometry includes an AdS_3 factor with a two-dimensional CFT dual. The degeneracy in this CFT accounts for the black hole entropy. In the three-charge case (where triples of branes intersect at a point), the decoupled geometry contains an AdS_2 factor. Below a certain critical mass, the two-charge system displays solutions with naked timelike singularities even though they do not violate a BPS bound. We suggest a string theoretic resolution of these singularities.
A toolset for supporting UML static and dynamic model checking

The Unified Modeling Language has become widely accepted as a standard in software development. Several tools have been produced to support UML model validation. However most of them support either static or dynamic model checking; and no tools support to check both static and dynamic aspects of a UML model. But a UML model should include the static and dynamic aspects of a software system. Furthermore, these UML tools translate a UML model into a validation language such as PROMELA. But they have some shortcomings: there is no proof of correctness (with respect to the UML semantics) for these tools. In order to overcome these shortcomings, we present a toolset which can validate both static and dynamic aspects of a model; and this toolset is based on the semantic model using Abstract State Machines. Since the toolset is derived from the semantic model, the toolset is correct with respect to the semantic model.
Enabling Language Resources to Expose Translations as Linked Data on the Web

Language resources, such as multilingual lexica and multilingual electronic dictionaries, contain collections of lexical entries in several languages. Having access to the corresponding explicit or implicit translation relations between such entries might be of great interest for many NLP-based applications. By using Semantic Web-based techniques, translations can be available on the Web to be consumed by other (semantic enabled) resources in a direct manner, not relying on application-specific formats. To that end, in this paper we propose a model for representing translations as linked data, as an extension of the lemon model. Our translation module represents some core information associated to term translations and does not commit to specific views or translation theories. As a proof of concept, we have extracted the translations of the terms contained in Terminesp, a multilingual terminological database, and represented them as linked data. We have made them accessible on the Web both for humans (via a Web interface) and software agents (with a SPARQL endpoint).
Modeling for Wind Farm Control

Wind turbines are typically operated to maximize their own performance without considering the impact of wake effects on nearby turbines. There is the potential to increase total power and reduce structural loads by properly coordinating the individual turbines in a wind farm. The effective design and analysis of such coordinated controllers requires turbine wake models of sufficient accuracy but low computational complexity. First, we formulate a coordinated control problem for a two-turbine array. Next, we review several simulation tools that range from low-fidelity, quasi-static models to high-fidelity, computational fluid dynamic models. These tools are compared by evaluating the power, loads, and flow characteristics for the coordinated two-turbine array. The results highlight the advantages and disadvantages of existing wake models for design and analysis of coordinated wind farm controllers. Finally, a dynamic medium fidelity wake model is constructed and compared to experimental results obtained from LiDAR wake measurements of the Clipper Turbine in UMore Park, Rosemount, MN.
Color Doppler assessment of mitral regurgitation with orthogonal planes.

We evaluated 147 patients with adequate color Doppler and angiographic studies for mitral regurgitation. Sixty-five patients had no mitral regurgitation by both color Doppler and angiography and 82 patients had mitral regurgitation by both techniques. Thus the sensitivity and specificity of color Doppler for the detection of mitral regurgitation was 100%. Three two-dimensional echocardiographic planes (parasternal long and short axis, apical four-chamber view) were used to analyze variables of the mitral regurgitant jet signals in the left atrium. The best correlation with angiography was obtained when the regurgitant jet area (RJA) (maximum or average from three planes) expressed as a percentage of the left atrial area (LAA) obtained in the same plane as the maximum regurgitant area was considered. The maximum RJA/LAA was under 20% in 34 of 36 patients with angiographic grade I mitral regurgitation, between 20% and 40% in 17 of 18 patients with grade II mitral regurgitation, and over 40% in 26 of 28 patients with severe mitral regurgitation. Maximum RJA/LAA also correlated with angiographic regurgitant fractions (r = .78) obtained in 21 of 40 patients in normal sinus rhythm and with no evidence of associated aortic regurgitation. Other variables of the regurgitant jet such as maximal linear and transverse dimensions, maximal area, or maximal area expressed as a percentage of the LAA in one or two planes correlated less well with angiography. Color Doppler is a useful noninvasive technique that is not only highly sensitive and specific in the identification of mitral regurgitation but also provides accurate estimation of its severity.
Análise de células satélite em diferentes modelos murinos para distrofias musculares

RIBEIRO JUNIOR, Antonio Fernando. Satellite Cells Analysis in Different Murine Models for Muscular Dystrophies. 2018. 65f. M.S. Dissertation (Genetics) Instituto de Biociências, Universidade de São Paulo, São Paulo, 2018. Muscle tissue has a high regeneration capacity after injury, which is directly linked to satellite cells (SCs). These cells are the main stem cells of the muscle and also have a key role in muscle development in embryogenesis. Although quiescent in normal adult muscles, SCs can be activated by specific signals upon muscle injury. In diseases characterized by chronic degeneration process, such as muscular dystrophies, the SCs are constantly activated, leading to depletion of the SC pool and consequent failure of the regenerative process. We studied muscle SCs in the mouse dystrophic strains DMD mdx , Large myd , DMD mdx /Large myd , comparing to wild-type mice, with the main objective to evaluate SCs behavior in dystrophic muscles with different degrees of histopathological degeneration. Gene and protein expression of transcription factors related to SCs were studied in the muscle, and the results were compared to regenerating and degenerating histopathologic pattern and proliferative state of muscle cells. Our results showed that the dystrophic muscle retains its satellite cells pool, expressing PAX7, an important muscle factor for self-renewal of the SCs pool, at similar levels in all dystrophic strains and wild-type. Dystrophic muscle single cells presented a higher proportion of proliferating cells, as observed by the analysis of cell cycle markers in dissociated gastrocnemius muscle, with a greater number of cells in the G2/M phase. The cascade of regeneration genes is activated in the dystrophic muscle, with high levels of expression of muscle regenerating factors, such as MYOD and Myogenin. Dystrophic muscle retains the ability to form new fibers, as observed by a significant number of new fibers expressing dMHC in all dystrophic strains. However, these new fibers show incomplete maturation characteristics, such as small size and no variation in fiber caliber, which could be determinant for its dysfunction. Muscle degeneration is intense in spite of regeneration, with significant more connective tissue infiltration in dystrophic mice than wild-type mice. In conclusion, our findings suggest that dystrophic muscles, independently of the degree of degeneration, retain the pool of satellite cells with proliferating capacity and
Towards an automated deduction system for first‐order possibilistic logic programming with fuzzy constants

In this article, we present a first‐order logic programming language for fuzzy reasoning under possibilistic uncertainty and poorly known information. Formulas are represented by a pair (φ, α), in which φ is a first‐order Horn clause or a query with fuzzy constants and regular predicates, and α ∈ [0, 1] is a lower bound on the belief on φ in terms of necessity measures. Since fuzzy constants can occur in the logic component of formulas, the truth value of formulas is many‐valued instead of Boolean. Moreover, since we have to reason about the possibilistic uncertainty of formulas with fuzzy constants, belief states are modeled by normalized possibility distributions on a set of many‐valued interpretations. In this framework, (1) we define a syntax and a semantics of the underlying logic; (2) we give a sound modus ponens‐style calculus by derivation based on a semantic unification pattern of fuzzy constants; (3) we develop a directional fuzzy unification algorithm based on the distinction between general and specific object constants; and (4) we describe a backward first‐order proof procedure oriented to queries that is based on the calculus of the language and the computation of the unification degree between fuzzy constants in terms of a necessity measure for fuzzy events. © 2002 Wiley Periodicals, Inc.
The imprints of contemporary mass redistribution on regional sea
level and vertical land motion observations

Abstract. We derive trends and monthly anomalies in global and regional sea-level and solid-earth deformation that result from mass redistribution observed by GRACE and an ensemble of GIA models. With this ensemble, we do not only compute mean changes, but we also derive uncertainty estimates of all quantities. We find that over the GRACE era, the trend in land mass change has led to a sea-level trend of 1.28–1.82 mm/yr, which is driven by ice mass loss, while terrestrial water storage has increased over the GRACE period, causing a sea-level drop of 0.11–0.47 mm/yr. This redistribution of mass causes sea-level and deformation patterns that do not only vary in space, but also in time. The temporal variations affect GNSS-derived vertical land motion (VLM) observations, which are now commonly used to correct tide-gauge observations. We find that for many GNSS stations, including GNSS stations in coastal locations, solid-earth deformation resulting from present-day mass redistribution causes trends in the order of 1 mm/yr or higher. Since GNSS records often only span a few years, these trends are generally not representative for the tide-gauge records, which often span multiple decades, and extrapolating them backwards in time could cause substantial biases. To avoid this possible bias, we computed trends and associated uncertainties for 8228 GNSS stations after removing deformation due to GIA and present-day mass redistribution. With this separation, we are able to explain a large fraction of the discrepancy between observed sea-level trends at multiple long tide-gauge records and the reconstructed global-mean sea-level trend from recent reconstructions.
Optical flow field estimation of nature scene images

Covered-uncovered problem and noise interference are key problems in optical flow estimation of nature scene images. In this paper, the visible scene areas are labeled by visible matrix and the distribution of noise is approximately described with normal probability distribution. The arithmetic expressions of optical flow field in visible scene areas are deduced in the Bayes framework. The results of simulation experiments show that the method is effective.
Seasonal Export of Dissolved Organic Matter from a New England Salt Marsh

ABSTRACT Schiebel, H.N. ; Gardner, G.B. ; Wang, X. ; Peri, F. , and Chen, R.F. , 2018. Seasonal export of dissolved organic matter from a New England salt marsh. The seasonality of dissolved organic matter (DOM) export from a New England salt marsh was investigated using multiple estuary transects along with laboratory plant leaching experiments. From 2001 through 2013, 35 transects of the Neponset Estuary in Boston, Massachusetts, were conducted to measure high-resolution in situ chromophoric dissolved organic matter (CDOM) fluorescence, along with other standard oceanographic parameters, via sensors incorporated into an undulating depressor wing known as the mini-shuttle. Water samples were collected during each cruise for discrete dissolved organic carbon (DOC) and CDOM fluorescence analyses. Seasonal salt marsh DOC export rates ranged from 1.1 × 107 to 15 × 107 mol C season−1 (10–140 mol C m−2 season−1). The total export was found to be 23 ± 17 × 107 mol C y−1 (210 mol C m−2 y−1) with river discharge, temperature, and day length significantly affecting this rate. Results from seasonal salt marsh vegetation (Spartina alterniflora, Spartina patens, and Phragmites australis) incubation experiments showed that the leaching of DOC and CDOM from plant biomass was a rapid process occurring over several days. Sunlight exposure, biomass type (above- versus belowground biomass), and microbial activity had significant effects on DOC leaching rates from plant matter. These incubations, in conjunction with the cruise data, support the fall dump hypothesis, in which a pulse of DOC leaches from plants during the fall as marsh plants begin to senesce for winter. The long-term trend in salt marsh DOM contributions to the estuary suggested a decrease in the in situ inputs from the marsh to the estuary during the length of this study.
Efficient edit distance based string similarity search using deletion neighborhoods

This paper serves as a report for the participation of Special Interest Group In Data (SIGDATA), Indian Institute of Technology, Kanpur in the String Similarity Workshop, EDBT, 2013. We present a novel technique to efficiently process edit distance based string similarity queries. Our technique draws upon some previously conducted works in the field and introduces new methods to tackle the issues therein. We focus on achieving minimum possible execution time while being rather liberal with memory consumption. We propose and support the use of deletion neighborhoods for fast edit distance lookups in dictionaries. Our work emphasizes the power of deletion neighborhoods over other popular finger print based schemes for similarity search queries. Furthermore, we establish that it is possible to reduce the large space requirement of a deletion neighborhood based finger print scheme using simple hashing techniques, thereby making the scheme suitable for practical application. We compare our implementation with the state of the art libraries (Flamingo) and report speed ups of up to an order of magnitude.
Coordination and Risk Analysis of VMI Supply Chains With RFID Technology

RFID technology is an important tool in modern supply chain management. This paper analytically studies the use of RFID in a two-echelon single-manufacturer single-retailer supply chain with the vendor managed inventory (VMI) scheme. First, the supply chain models under a retail replenishment problem with and without RFID are constructed. Second, both the levels of risk and the expected profits of the supply chains are explored. Third, measures which can coordinate the supply chains with and without RFID are proposed. Fourth, comparisons between the cases with and without RFID are made. This paper analytically illustrates several important managerial insights which include: (i) when the RFID tag cost is very small, employing the RFID technology yields an improved supply chain with both larger expected profit and smaller risk; (ii) there exist multiple return policies which can coordinate the supply chain with RFID and the respective upper and lower bounds are identified; (iii) it is beneficial for the manufacturer to take the initiative to share the retailer's cost of RFID implementation, and this action not only can help coordinate the supply chain but also lower the manufacturer's risk; and (iv) compared to the case without RFID, the return rate under the coordinating return policy for the case with RFID can be lower if the RFID tag cost is appropriately shared between the retailer and the manufacturer. These insights are important for both industrialists and academicians.
Myxoma Virus and the Leporipoxviruses: An Evolutionary Paradigm

Myxoma virus (MYXV) is the type species of the Leporipoxviruses, a genus of Chordopoxvirinae, double stranded DNA viruses, whose members infect leporids and squirrels, inducing cutaneous fibromas from which virus is mechanically transmitted by biting arthropods. However, in the European rabbit (Oryctolagus cuniculus), MYXV causes the lethal disease myxomatosis. The release of MYXV as a biological control for the wild European rabbit population in Australia, initiated one of the great experiments in evolution. The subsequent coevolution of MYXV and rabbits is a classic example of natural selection acting on virulence as a pathogen adapts to a novel host species. Slightly attenuated mutants of the progenitor virus were more readily transmitted by the mosquito vector because the infected rabbit survived longer, while highly attenuated viruses could be controlled by the rabbit immune response. As a consequence, moderately attenuated viruses came to dominate. This evolution of the virus was accompanied by selection for genetic resistance in the wild rabbit population, which may have created an ongoing co-evolutionary dynamic between resistance and virulence for efficient transmission. This natural experiment was repeated on a continental scale with the release of a separate strain of MYXV in France and its subsequent spread throughout Europe. The selection of attenuated strains of virus and resistant rabbits mirrored the experience in Australia in a very different environment, albeit with somewhat different rates. Genome sequencing of the progenitor virus and the early radiation, as well as those from the 1990s in Australia and Europe, has shown that although MYXV evolved at high rates there was no conserved route to attenuation or back to virulence. In contrast, it seems that these relatively large viral genomes have the flexibility for multiple pathways that converge on a similar phenotype.
Using active learning in intrusion detection

Intrusion detection systems (IDSs) have become an important part of operational computer security. They are the last line of defense against malicious hackers and help detect ongoing attacks as well as mitigate their damage. However, intrusion detection systems are not turnkey solutions but are heavily dependent on expensive and scarce security experts for successful operation. By emphasizing self-learning algorithms, we can reduce dependence on the domain expert but instead require massive amounts of labeled training data, another scarce resource in intrusion detection. In this paper, we investigate whether an active learning algorithm can perform on a par with a traditional self-learning algorithm in terms of detection accuracy but using significantly less labeled data. Our preliminary findings indicate that the active learning algorithm generally performs better than the traditional learning algorithm given the same amount of training data. Moreover, the reduction of labeled data needed can be as much as 80 times, shown by comparing an active learner with a traditional learner with similar detection accuracy. Thus, active learning algorithms seem promising in that they can reduce the dependence on security experts in the development of new detection rules by better leveraging the knowledge and time of the expert.
Pupal Cuticle Protein is Abundant During Early Adult Diapause in the Mosquito Culex pipiens

ABSTRACT Using a proteomics approach, we identified 13 differentially abundant proteins in heads of nondiapause, early, and mid-diapause Culex pipiens L. adult females. Three proteins that were more abundant during early diapause showed highest identities to pupal cuticle protein (PCP). The majority of less abundant proteins were involved in energy metabolism and cytoskeletonal reorganization. The increase of PCP in early diapause may be involved in enhancing stress resistance in the cuticle, a response akin to the general enhancement of stress resistance associated with overwintering insects. PCP also may have utility as a biomarker for early diapause in this species.
FPGA Implementation of Reservoir Computing with Online Learning

Reservoir Computing is a bio-inspired computing paradigm for processing time dependent signals. The performance of its analogue implementation are comparable to, and sometimes surpass, other state of the art algorithms for tasks such as speech recognition or chaotic time series prediction. However, these implementation present several issues, which we address here by using programmable dedicated electronics in place of a personal computer. We demonstrate a standalone reservoir computer programmed onto a FPGA board and apply it to the real-world task of equalisation of a nonlinear communication channel. The training of the RC is carried out online, as this learning method, on top of being simple to implement, allows the RC to adapt itself to a changing environment, as we show here by equalising a variable communication channel.
Sub-second pencil beam dose calculation on GPU for adaptive proton therapy

Although proton therapy delivered using scanned pencil beams has the potential to produce better dose conformity than conventional radiotherapy, the created dose distributions are more sensitive to anatomical changes and patient motion. Therefore, the introduction of adaptive treatment techniques where the dose can be monitored as it is being delivered is highly desirable. We present a GPU-based dose calculation engine relying on the widely used pencil beam algorithm, developed for on-line dose calculation. The calculation engine was implemented from scratch, with each step of the algorithm parallelized and adapted to run efficiently on the GPU architecture. To ensure fast calculation, it employs several application-specific modifications and simplifications, and a fast scatter-based implementation of the computationally expensive kernel superposition step. The calculation time for a skull base treatment plan using two beam directions was 0.22 s on an Nvidia Tesla K40 GPU, whereas a test case of a cubic target in water from the literature took 0.14 s to calculate. The accuracy of the patient dose distributions was assessed by calculating the γ-index with respect to a gold standard Monte Carlo simulation. The passing rates were 99.2% and 96.7%, respectively, for the 3%/3 mm and 2%/2 mm criteria, matching those produced by a clinical treatment planning system.
Classification of the quantum deformations of the superalgebra gl(1|1)

We present a classification of the possible quantum deformations of the supergroup and its Lie superalgebra . In each case, the (super)commutation relations and the Hopf structures are explicitly computed. For each R-matrix, one finds two inequivalent co-products whether one chooses an unbraided or a braided framework while the corresponding structures are isomorphic as algebras. In the braided case, one recovers the classical algebra for suitable limits of the deformation parameters but this is no longer true in the unbraided case.