Miracle-dz/UniFAR-FTUs huggingface dataset:
Synchronized Formation of Subgalactic Systems at Cosmological Reionization: Origin of Halo Globular Clusters

Gas-rich subgalactic halos with mass Mt ≤ 107.5 M☉, while incapable of forming stars because of a lack of adequate coolants, contain a large fraction of baryonic mass at cosmological reionization. We show that the reionization of the universe at z = 6-20 has an interesting physical effect on these halos. The external radiation field causes a synchronous inward propagation of an ionization front toward each halo, resulting in an inward, convergent shock. The resident gas of mass Mb ~ 104-107 M☉ in low-spin (initial dimensionless spin parameter λ ≤ 0.01) halos with a velocity dispersion of σv ≤ 11 km s-1 would be compressed by a factor of about 100 in radius and form self-gravitating baryonic systems. Under the assumption that such compressed gaseous systems fragment to form stars, the final stellar systems will have a size of about 2-40 pc, a velocity dispersion of about 1-10 km s-1, and a total stellar mass of M* ~ 103-106 M☉. The characteristics of these proposed systems seem to match the observed properties of halo globular clusters. The expected number density is consistent with the observed number density of halo globular clusters. The observed mass function of slope of about -2 at the high-mass end is predicted by the model. Strong correlation between velocity dispersion and luminosity (or surface brightness) and lack of correlation between velocity dispersion and size, in agreement with observations, are expected. Metallicity is, on average, expected to be low and should not correlate with any other quantities of globular clusters; however, a larger dispersion of metallicity among globular clusters is expected for larger galaxies. The observed trend of specific frequency with galaxy type may be produced in the model. We suggest that these stellar systems are seen as halo globular clusters today.
Cotranscriptional Recruitment of the Pseudouridylsynthetase Cbf5p and of the RNA Binding Protein Naf1p during H/ACA snoRNP Assembly

ABSTRACT H/ACA small nucleolar ribonucleoprotein particles (snoRNPs) are essential for the maturation and pseudouridylation of the precursor of rRNAs and other stable RNAs. Although the RNA and protein components of these RNPs have been identified, the mechanisms by which they are assembled in vivo are poorly understood. Here we show that the RNA binding protein Naf1p, which is required for H/ACA snoRNPs stability, associates with RNA polymerase II-associated proteins Spt16p, Tfg1p, and Sub1p and with H/ACA snoRNP proteins. Chromatin immunoprecipitation experiments show that Naf1p and the pseudouridylsynthetase Cbf5p cross-link specifically with the chromatin of H/ACA small nucleolar RNA (snoRNA) genes. Naf1p and Cbf5p cross-link predominantly with the 3′ end of these genes, in a pattern similar to that observed for transcription elongation factor Spt16p. Cross-linking of Naf1p to H/ACA snoRNA genes requires active transcription and intact H/ACA snoRNA sequences but does not require the RNA polymerase II CTD kinase Ctk1p. These results suggest that Naf1p and Cbf5p are recruited in a cotranscriptional manner during H/ACA snoRNP assembly, possibly by binding to the nascent H/ACA snoRNA transcript during elongation or termination of transcription of H/ACA snoRNA genes.
Development Tool for Service-Oriented Applications in Smart Homes

In this paper, we present a model-driven, domain-centric tool allowing the specification of service-oriented applications through abstract services composition. Executable applications, made of concrete services, are automatically generated and deployed. This tool can be customized with domain-specific knowledge. Our contributions in this paper are to slightly extend the tool to be used in the demanding home computing domain. An approach for modelling and implementing dynamic service composition is provided for satisfying the dynamic home environment. This work has been carried out in collaboration with Schneider Electric.
Inhibitor Complexes of the Pseudomonas Serine-carboxyl Proteinase †

Crystal structures of the serine-carboxyl proteinase from Pseudomonas sp. 101 (PSCP), complexed with a number of inhibitors, have been solved and refined at high-to atomic-level resolution. All of these inhibitors (tyrostatin, pseudo-tyrostatin, AcIPF, AcIAF, and chymostatin, as well as previously studied iodotyrostatin and pseudo-iodotyrostatin) make covalent bonds to the active site Ser287 through their aldehyde moieties, while their side chains occupy subsites S1-S4 of the enzyme. The mode of binding of the inhibitors is almost identical for their P1 and P2 side chains, while significant differences are observed for P3 and P4 (if present). Kinetic parameters for the binding of these nanomolar inhibitors to PSCP have been established and correlated with the observed mode of binding. The preferences of this enzyme for a larger side chain in P2 as well as Tyr or Phe in P1 are explained by the size, shape, and characteristics of the S2 and S1 regions of the protein structure, respectively. Networks of hydrogen bonds involving glutamic and aspartic acids have been analyzed for the atomic-resolution structure of the native enzyme. PSCP contains a calcium-binding site that consists of Asp328, Asp348, three amide carbonyl groups, and a water molecule, in almost perfect octahedral coordination. The presence of Ca 2+ cation is necessary for the activity of the enzyme. Serine-carboxyl proteinases belong to a recently characterized family of proteolytic enzymes that share their fold with subtilisin, but contain an active site with a unique catalytic triad, Ser-Glu-Asp (1, 2). This family was previously known as pepstatin-insensitive carboxyl proteinases (3-6), in view of the importance of a number of aspartic and glutamic acid residues for their catalytic activity; the current name was introduced after the structure of its first member was determined. Other related bacterial enzymes include Xanth-omonas sp. T-22 carboxyl proteinase (XSCP) (3), kumamol-ysin (KSCP), an enzyme isolated from a thermophilic bacterium Bacillus novosp. MN-32 (7), and alcohol-resistant proteinase J-4, isolated from Bacillus coagulans (8). An important member of this class of proteinases is CLN2, a mammalian tripeptidyl-peptidase I (9, 10), which, when mutated, leads to a fatal human neurodegenerative disease, classical late-infantile neuronal ceroid lipofuscinosis (11). Lys60 and Lys45, markers for late lysosomes in Amoeba proteus (12), are also putative members of this family. Our previous studies have resulted in the structure of the uninhibited enzyme solved and refined at 1 Å resolution, as well as in the 1.4 Å structure of a covalent complex of …
Automatic image annotation using SURF descriptors

In recent years there is an apparent shift in research from content based image retrieval (CBIR) to automatic image annotation in order to bridge the gap between low level features and high level semantics of images. Automatic Image Annotation (AIA) techniques facilitate extraction of high level semantic concepts from images by machine learning techniques. Many AIA techniques use feature analysis as the first step to identify the objects in the image. However, the high dimensional image features make the performance of the system worse. This paper describes and evaluates an automatic image annotation framework which uses SURF descriptors to select right number of features and right features for annotation. The proposed framework uses a hybrid approach in which k-means clustering is used in the training phase and fuzzy K-NN classification in the annotation phase. The performance of the system is evaluated using standard metrics.
KRASH: Reproducible CPU load generation on many-core machines

In this article we present KRASH, a tool for reproducible generation of system-level CPU load. This tool is intended for use in shared memory machines equipped with multiple CPU cores which are usually exploited concurrently by several users. The objective of KRASH is to enable parallel application developers to validate their resources use strategies on a partially loaded machine by replaying an observed load in concurrence with their application. To reach this objective, we present a method for CPU load generation which behaves as realistically as possible: the resulting load is similar to the load that would be produced by concurrent processes run by other users. Nevertheless, contrary to a simple run of a CPU-intensive application, KRASH is not sensitive to system scheduling decisions. The main benefit brought by KRASH is this reproducibility: no matter how many processes are present in the system the load generated by our tool strictly respects a given load profile. This last characteristic proves to be hard to achieve using simple methods because the system scheduler is supposed to share the resources fairly among running processes. Our first contribution is a method that cooperates with the system scheduler to produce a CPU load that conforms to a desired load profile. We argue that this cooperation with the system scheduler is mandatory in the generator to reach a good reproducibility, a high precision and a low intrusiveness. Taking advantage of Linux kernel capabilities, we implemented this method in KRASH (Kernel for Reproduction and Analysis of System Heterogeneity). We have run experiments that show that KRASH provides a precise reproduction of the desired load and that it induces a very low overhead on the system. Our second contribution is a qualitative and quantitative study that compares KRASH to other tools dealing with system-level CPU load generation. To our knowledge, KRASH is the only tool that implements the generation of a dynamic load profile (a load varying with time). When used to generate a constant load, KRASH result is among the most realistic ones. Furthermore, KRASH provides more flexibility than other tools.
Nitrogen Recycling and Flowering Time in Perennial Bioenergy Crops

Perennials have a number of traits important for profitability and sustainability of a biofuel crop. Perennialism is generally defined as the ability to grow and reproduce in multiple years. In temperate climates, many perennial plants enter dormancy during winter and recycle nutrients, such as nitrogen, to below ground structures for the next growing season. Nitrogen is expensive to produce and application of nitrogen increases the potent greenhouse gas NOx. Perennial bioenergy crops have been evaluated for biomass yields with nitrogen fertilization, location, year, and genotype as variables. Flowering time and dormancy are closely related to the N recycling program. Substantial variation for flowering time and dormancy has been identified in the switchgrass (Panicum virgatum L.) species, which provides a source to identify the genetic components of N recycling, and for use in breeding programs. Some studies have addressed recycling specifically, but flowering time and developmental differences were largely ignored, complicating interpretation of the results. Future studies on recycling need to appreciate plant developmental stage to allow comparison between experiments. A perennial/annual model(s) and more environmentally controlled experiments would be useful to determine the genetic components of nitrogen recycling. Increasing biomass yield per unit of nitrogen by maximizing recycling might mean the difference for profitability of a biofuel crop and has the added benefit of minimizing negative environmental effects from agriculture.
Serum ferritin level changes in children with sickle cell disease on chronic blood transfusion are nonlinear and are associated with iron load and liver injury.

Chronic blood transfusion is increasingly indicated in patients with sickle cell disease. Measuring resulting iron overload remains a challenge. Children without viral hepatitis enrolled in 2 trials for stroke prevention were examined for iron overload (STOP and STOP2; n = 271). Most received desferrioxamine chelation. Serum ferritin (SF) changes appeared nonlinear compared with prechelation estimated transfusion iron load (TIL) or with liver iron concentrations (LICs). Averaged correlation coefficient between SF and TIL (patients/observations, 26 of 164) was r = 0.70; between SF and LIC (patients/observations, 33 of 47) was r = 0.55. In mixed models, SF was associated with LIC (P = .006), alanine transaminase (P = .025), and weight (P = .026). Most patients with SF between 750 and 1500 ng/mL had a TIL between 25 and 100 mg/kg (72.8% +/- 5.9%; patients/observations, 24 of 50) or an LIC between 2.5 and 10 mg/g dry liver weight (75% +/- 0%; patients/observations, 8 of 9). Most patients with SF of 3000 ng/mL or greater had a TIL of 100 mg/kg or greater (95.3% +/- 6.7%; patients/observations, 7 of 16) or an LIC of 10 mg/g dry liver weight or greater (87.7% +/- 4.3%; patients/observations, 11 of 18). Although SF changes are nonlinear, levels less than 1500 ng/mL indicated mostly acceptable iron overload; levels of 3000 ng/mL or greater were specific for significant iron overload and were associated with liver injury. However, to determine accurately iron overload in patients with intermediately elevated SF levels, other methods are required. These trials are registered at www.clinicaltrials. gov as #NCT00000592 and #NCT00006182.
Learning to generalize to new compositions in image understanding

Recurrent neural networks have recently been used for learning to describe images using natural language. However, it has been observed that these models generalize poorly to scenes that were not observed during training, possibly depending too strongly on the statistics of the text in the training data. Here we propose to describe images using short structured representations, aiming to capture the crux of a description. These structured representations allow us to tease-out and evaluate separately two types of generalization: standard generalization to new images with similar scenes, and generalization to new combinations of known entities. We compare two learning approaches on the MS-COCO dataset: a state-of-the-art recurrent network based on an LSTM (Show, Attend and Tell), and a simple structured prediction model on top of a deep network. We find that the structured model generalizes to new compositions substantially better than the LSTM, ~7 times the accuracy of predicting structured representations. By providing a concrete method to quantify generalization for unseen combinations, we argue that structured representations and compositional splits are a useful benchmark for image captioning, and advocate compositional models that capture linguistic and visual structure.
Electrodynamic Structure of an Outer Gap Accelerator: Location of the Gap and the Gamma-Ray Emission from the Crab Pulsar

We investigate a stationary pair-production cascade in the outer magnetosphere of a spinning neutron star. The charge depletion due to global flows of charged particles causes a large electric field along the magnetic field lines. Migratory electrons and/or positrons are accelerated by this field to radiate curvature gamma rays, some of which collide with the X-rays to materialize as pairs in the gap. The replenished charges partially screen the electric field, which is self-consistently solved together with the distribution functions of particles and gamma rays. If no current is injected at either of the boundaries of the accelerator, the gap is located around the conventional null surface, where the local Goldreich-Julian charge density vanishes. However, we first find that the gap position shifts outward (or inward) when particles are injected at the inner (or outer) boundary. Applying the theory to the Crab pulsar, we demonstrate that the pulsed TeV flux does not exceed the observational upper limit for moderate infrared photon density and that the gap should be located near to or outside of the conventional null surface so that the observed spectrum of pulsed GeV fluxes may be emitted via a curvature process. Some implications of the existence of a solution for a super Goldreich-Julian current are discussed.
Data fusion for multiple mechanical fault diagnosis in induction motors at variable operating conditions

In this paper, data fusion based on multi-class support vector machines (SVM) is presented to detect and isolate three mechanical faults in induction motors. First, we construct the feature vector by using signatures created from frequency-domain characteristics. These signatures are obtained from mechanical vibration and line currents measurements. Then, the feature vector is used to feed SVM's to classify different motor conditions (normal, misalignment, unbalanced and bearing fault). Different experiments using a three phase induction motor were performed under variable operational conditions (motor speeds and load torque scenarios) in order to acquire training and validation data. The identified optimal parameters of the SVM's are reported. The SVM's are studied with two types of kernel functions, the radial basis and the polynomial functions. Data acquisition, feature extraction and SVM's computation were implemented by using LabView programming language. The experimental results show the effectiveness of the proposed approach in diagnosing the studied mechanical faults at different speeds and load conditions. In these experimental tests, the worst-case accuracy of the proposed method was 97.1%.
Business Intelligence: Concepts, Issues and Current Systems

During the last decade, the interest in Business Intelligence (BI) has been highly increased as a result of its widely used concept. Generally, the concept of BI is confusing, yet, it can be defined as the acquisition and utilization of fact-based knowledge to improve a business strategic and tactical advantage in marketplace. Based on this understanding, a lot of organizations have implemented BI systems within their firm and many others on the way to implement it as well. However, there are some challenges and drawbacks face organizations and prevent them from obtaining the optimal benefits from BI systems; perhaps the most obvious reason is organizations' readiness toward BI systems. This paper, discusses the term BI from different views, presents the concepts and ideas behind its applications and systems, and it gives more enlightening about the pros and cones of BI with a high focus on implementation challenges.
Hearing While Blinking: Multisensory Attentional Blink Revisited

It is well established that cognitive system overload is reflected in the attentional blink (AB), the failure to report a second target when it closely follows detection of a first target within a rapid series of stimuli. However, there is intense controversy concerning the effect of first-target detection in one modality on subsequent dynamics of attentional resources in other modalities. Mixed results were found using an audiovisual AB paradigm: depletion of resources in one modality either impaired performance in the other modality or had no effect. Here, we circumvent the need for task switching by measuring an event-related potential, the mismatch negativity, which reflects implicit auditory change detection without requiring task engagement and is present even for background sounds that participants ignore. Surprisingly, we find that during the visual AB, auditory processing is enhanced rather than inhibited, as would be expected by system overload. We suggest that multimodal attentional resources may be freed rather than engaged during the visual AB. Suppression of irrelevant input may require active control by a central executive, which is preoccupied during the visual AB, and/or there may be no reason to suppress other-modal input since the visual system will miss its second target anyway.
Effective color space representation for wavelet based compression of HDR images

Effective color image and video coding is usually exploited coupling a compression method with the most suitable color space representation. This work extends a previously proposed high dynamic range (HDR) image coding method, which combines a logarithmic color adaptation module with a JPEG2000 codec. Here we propose to change the original preprocessing stage with a more adequate one, based on the LogLuv color space representation, in order to take fully advantage of wavelet based coding. The experimental comparisons confirm that the proposed method improves the compression performances and simplify the overall coding scheme.
How (Not) To Minimize Events

When drawing conclusions about narratives, minimizing|to a reasonable extent|the occurrence of events is crucial. We argue that unguided minimization is insuucient in case events are causally connected, for it easily fails to distinguish unmotivated event occurrences from those that have a cause. Two solutions are ooered, the rst of which has the advantage of being straightforwardly realized but on the other hand has a restricted range of applicability. Our second solution overcomes these restrictions but requires two uncommon and novel features. First, event occurrences are identiied as uents, which allows to adapt a recent causality-oriented solution to the Ramiication Problem so that if an event is caused by another event then the former is obtained as indirect eeect of what caused the latter. Second, volitional actions and natural events which have no cause inside the reasoning context, are furnished with a special cause, namely, the reaching of the time-point at which they take place. We present both a high-level narrative description language and an axiomatization based on a novel Fluent Calculus in which is realized this solution to the event minimization problem.
Role of the CmeABC efflux pump in the emergence of fluoroquinolone-resistant Campylobacter under selection pressure.

OBJECTIVES The objective of this study was to determine the contribution of the CmeABC efflux pump to the emergence of fluoroquinolone (FQ)-resistant mutants in Campylobacter jejuni under various levels of selection pressure. METHODS The frequency of emergence of ciprofloxacin-resistant mutants was measured in wild-type C. jejuni NCTC 11168 and its isogenic cmeB mutant and cmeR mutant (overexpressing cmeABC) using plates containing various concentrations of ciprofloxacin. Representative ciprofloxacin-resistant mutants were selected for gyrA sequence analysis and MIC determination. Accumulation of ciprofloxacin in Campylobacter cells was measured using spectrofluorometry. RESULTS Mutation of cmeB drastically reduced the frequency of emergence of FQ-resistant mutants at 10x and 32x the MIC of ciprofloxacin, while the cmeR mutant displayed an approximately 17-fold increase in the frequency of emergence of the mutants at 32x the MIC when compared with the wild-type strain. Various point mutations occurred in gyrA in the FQ-resistant mutants selected at 5x and 10x the MIC, while the Thr-86-->Ile mutation was predominant in the mutants selected at 32x the MIC. The Thr-86-->Ile change conferred a high-level resistance to FQs, but other mutations only conferred an intermediate-level FQ resistance. In contrast, all types of gyrA mutations in the CmeABC-overexpressed background conferred high-level resistance to ciprofloxacin. Overexpression of cmeABC significantly reduced the amount of ciprofloxacin accumulated within bacterial cells. CONCLUSIONS CmeABC is not only important for maintaining high-level resistance to FQs but also contributes significantly to the emergence of FQ-resistant mutants. Inhibition of this efflux pump may prevent the emergence of clinically relevant FQ-resistant Campylobacter mutants.