Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum effects near a point mass in (2+1)-dimensional gravity.

We investigate the behavior of classical and quantum fields in the conical space-time associated with a point mass in 2 + 1 dimensions. We show that the presence of conical boundary conditions alters the electrostatic field of a point charge leading to the presence of a finite self-force on the charge from the direction of the point mass exactly as if the point mass itself were charged. The conical space-time geometry also affects the zero-point fluctuations of a quantum scalar field leading to the existence of a vacuum polarization $〈{T}_{\ensuremath{\mu}\ensuremath{\nu}}〉$ in the (2 + 1)-dimensional analogue of the Schwarzschild metric. The resulting linearized semiclassical Einstein equations ${G}_{\ensuremath{\mu}\ensuremath{\nu}}=8\ensuremath{\pi}G〈{T}_{\ensuremath{\mu}\ensuremath{\nu}}〉$ possess a well-defined Newtonian limit, in marked contrast to the classical case for which no Newtonian limit is known to exist. An elegant reformulation of our results in terms of the method of images is also presented. Our analysis also covers the nonstatic de Sitter-Schwarzschild metric in 2 + 1 dimensions, in which in addition to the vacuum polarization, a nonzero vacuum flux of energy $〈{T}_{\mathrm{rt}}〉$ is also found to exist. As part of this analysis, we evaluate the scalar field propagator in an $n$-dimensional de Sitter space; as a result some novel features of quantum field theory in odd dimensions are seen to emerge.
From acquisition to modelisation of a form base to retrieve information

This article deals with the description of a module for information structure extraction. This module is applied to forms which are used by the CAF, the French National Family Allowance Department, Caisse d'Allocations Familiales. The aim of this module is to create a base of information structures (models) defining their forms and their content so as to be able to deal with them automatically. The module deals with the various stages of form treatment, from acquisition to modelisation. It is composed of three different stages. The first corresponds to low-level processing-i.e., binarisation, skew correction. The second extracts the informative features contained in the forms. The last one organises the different features to obtain form modelisation thanks to a hierarchical structure. The creation of this base of information structures will be used for a second module for type form identification based on the comparison of these information structures.
Antimicrobial Susceptibility Testing of Carbapenems: Multicenter Validity Testing and Accuracy Levels of Five Antimicrobial Test Methods for Detecting Resistance in Enterobacteriaceae and Pseudomonas aeruginosa Isolates

ABSTRACT From January 1996 to May 1999, Project ICARE (Intensive Care Antimicrobial Resistance Epidemiology) received 448 nonduplicate clinical isolates of Enterobacteriaceae and Pseudomonas aeruginosa that were reported to be imipenem intermediate or resistant. However, broth microdilution (BMD) confirmatory testing at the Project ICARE central laboratory confirmed this result in only 11 of 123 (8.9%) Enterobacteriaceae isolates and 241 of 325 (74.2%) P. aeruginosa isolates. To investigate this overdetection of imipenem resistance, we tested 204 selected isolates from the Project ICARE collection plus five imipenem-resistant challenge strains at the Centers for Disease Control and Prevention against imipenem and meropenem by agar dilution, disk diffusion, Etest (AB BIODISK North America, Inc., Piscataway, N.J.), two MicroScan WalkAway conventional panels (Neg MIC Plus 3 and Neg Urine Combo 3) (Dade MicroScan, Inc., West Sacramento, Calif.), and two Vitek cards (GNS-116 containing meropenem and GNS-F7 containing imipenem) (bioMérieux Vitek, Inc., Durham, N.C.). The results of each test method were compared to the results of BMD testing using in-house-prepared panels. Seven imipenem-resistant and five meropenem-resistant isolates of Enterobacteriaceae and 43 imipenem-resistant and 21 meropenem-resistant isolates of P. aeruginosa were identified by BMD. For Enterobacteriaceae, the imipenem and meropenem test methods produced low numbers of very major and major errors. All test systems in the study produced low numbers of very major and major errors when P. aeruginosa was tested against imipenem and meropenem, except for Vitek testing (major error rate for imipenem, 20%). Further testing conducted in 11 of the participating ICARE hospital laboratories failed to pinpoint the factors responsible for the initial overdetection of imipenem resistance. However, this study demonstrated that carbapenem testing difficulties do exist and that laboratories should consider using a second, independent antimicrobial susceptibility testing method to validate carbapenem-intermediate and -resistant results.
Purchase Prediction and Item Suggestion based on HTTP sessions in absence of User Information

In this paper, the task is to determine whether an HTTP session buys an item, or not, and if so, which items will be purchased. An HTTP session is a series of item clicks. A session has type buy, if it buys at least one item, or non-buy otherwise. Accordingly, data is in (session, item, time) format, which tells us when an item is clicked or purchased during an HTTP session. The main challenge comes from the fact that (1) user information is not available for clicked or purchased items, which are merely tagged with anonymous sessions, and (2) suggestions are highly temporal as they are suggested to sessions instead of users. In other words, users which are stable and identified are replaced with sessions which are temporal and anonymous. In this work, we propose a feature-based system that predicts the type of a session, and determines which items are going to be purchased. As the main contribution, we have modeled sessions separated by the number of unique items, prioritized item-features based on the number of clicks, and utilized cumulative statistics of similar items to attenuate the sparsity problem.
Monitoring of collagen shrinkage by use of second harmonic generation microscopy

Thermal treatment induced collagen shrinkage has a great number of applications in medical practice. Clinically, the there is lack of reliable non-invasive methods to quantify the shrinkage. Overt treatment by heat application can lead to devastating results. We investigate the serial changes of collagen shrinkage by thermal treatment of rat tail tendons. The change in length is correlated with the finding in second harmonic generation microscopy and histology. Rat tail tendon shortens progressively during initial thermal treatment. After a certain point in time, the length then remains almost constant despite further thermal treatment. The intensity of second harmonic generation signals also progressively decreases initially and then remains merely detectable upon further thermal treatment. It prompts us to develop a mathematic model to quantify the dependence of collagen shrinkage on changes of SHG intensity. Our results show that SHG intensity can be used to predict the degree of collagen shrinkage during thermal treatment for biomedical applications.
Role of DnaJ G/F-rich Domain in Conformational Recognition and Binding of Protein Substrates*

DnaJ from Escherichia coli is a Type I Hsp40 that functions as a cochaperone of DnaK (Hsp70), stimulating its ATPase activity and delivering protein substrates. How DnaJ binds protein substrates is still poorly understood. Here we have studied the role of DnaJ G/F-rich domain in binding of several substrates with different conformational properties (folded, partially (un)folded and unfolded). Using partial proteolysis we find that RepE, a folded substrate, contacts a wide DnaJ area that involves part of the G/F-rich region and Zn-binding domain. Deletion of G/F-rich region hampers binding of native RepE and reduced the affinity for partially (un)folded substrates. However, binding of completely unfolded substrates is independent on the G/F-rich region. These data indicate that DnaJ distinguishes the substrate conformation and is able to adapt the use of the G/F-rich region to form stable substrate complexes.
A unified deep neural network for speaker and language recognition

Learned feature representations and sub-phoneme posteriors from Deep Neural Networks (DNNs) have been used separately to produce significant performance gains for speaker and language recognition tasks. In this work we show how these gains are possible using a single DNN for both speaker and language recognition. The unified DNN approach is shown to yield substantial performance improvements on the the 2013 Domain Adaptation Challenge speaker recognition task (55% reduction in EER for the out-of-domain condition) and on the NIST 2011 Language Recognition Evaluation (48% reduction in EER for the 30s test condition).
Spectral Analysis of High-Frequency Finance by Yuqing Zhang

Popular across a wide range of fields, spectral analysis is a powerful technique for studying the behavior of complex systems. It decomposes a signal into many different periodic components, each associated with a specific cycle length. We argue that the application of spectral analysis to finance leads to natural interpretations in terms of horizon-specific behaviors. A spectral framework provides a few main advantages over conventional time domain approaches to financial analysis: (1) improved computational efficiency for the evaluation of behaviors across a spectrum of time horizons, (2) reduced vulnerability to aliasing effects, and (3) more convenient representations of inherently cyclic dynamics, e.g. business cycles, credit cycles, liquidity cycles, etc. In this paper we first present a set of spectral techniques, including a frequencyspecific correlation and a frequency decomposition of trading strategy profits. Then, we demonstrate the application of these techniques in an empirical analysis of highfrequency dynamics over the years 1995-2014. Our results consist of three parts: (1) an analysis of individual stock returns and various portfolio returns, (2) an analysis of contrarian trading strategies and the introduction of a novel technique for managing frequency exposures of general strategies, and (3) a case analysis of recent market shocks. The great extent to which our empirical results align with financial intuition attests to the practicality of spectral approaches to financial analysis. It demonstrates that many real phenomena can be captured through a spectral lens. Thesis Supervisor: Andrew W. Lo Title: Charles E. and Susan T. Harris Professor
Does the Macaque Monkey Provide a Good Model for Studying Human Executive Control? A Comparative Behavioral Study of Task Switching

The ability to swiftly and smoothly switch from one task set to another is central to intelligent behavior, because it allows an organism to flexibly adapt to ever changing environmental conditions and internal needs. For this reason, researchers interested in executive control processes have often relied on task-switching paradigms as powerful tools to uncover the underlying cognitive and brain architecture. In order to gather fundamental information at the single-cell level, it would be greatly helpful to demonstrate that non-human primates, especially the macaque monkey, share with us similar behavioral manifestations of task-switching and therefore, in all likelihood, similar underlying brain mechanisms. Unfortunately, prior attempts have provided negative results (e.g., Stoet & Snyder, 2003b), in that it was reported that macaques do not show the typical signature of task-switching operations at the behavioral level, represented by switch costs. If confirmed, this would indicate that the macaque cannot be used as a model approach to explore human executive control mechanisms by means of task-switching paradigms. We have therefore decided to re-explore this issue, by conducting a comparative experiment on a group of human participants and two macaque monkeys, whereby we measured and compared performance costs linked to task switching and resistance to interference across the two species. Contrary to what previously reported, we found that both species display robust task switching costs, thus supporting the claim that macaque monkeys provide an exquisitely suitable model to study the brain mechanisms responsible for maintaining and switching task sets.
Frontostriatal Contribution to the Interplay of Flexibility and Stability in Serial Prediction

Surprising events may be relevant or irrelevant for behavior, requiring either flexible adjustment or stabilization of our model of the world and according response strategies. Cognitive flexibility and stability in response to environmental demands have been described as separable cognitive states, associated with activity of striatal and lateral prefrontal regions, respectively. It so far remains unclear, however, whether these two states act in an antagonistic fashion and which neural mechanisms mediate the selection of respective responses, on the one hand, and a transition between these states, on the other. In this study, we tested whether the functional dichotomy between striatal and prefrontal activity applies for the separate functions of updating (in response to changes in the environment, i.e., switches) and shielding (in response to chance occurrences of events violating expectations, i.e., drifts) of current predictions. We measured brain activity using fMRI while 20 healthy participants performed a task that required to serially predict upcoming items. Switches between predictable sequences had to be indicated via button press while sequence omissions (drifts) had to be ignored. We further varied the probability of switches and drifts to assess the neural network supporting the transition between flexible and stable cognitive states as a function of recent performance history in response to environmental demands. Flexible switching between models was associated with activation in medial pFC (BA 9 and BA 10), whereas stable maintenance of the internal model corresponded to activation in the lateral pFC (BA 6 and inferior frontal gyrus). Our findings extend previous studies on the interplay of flexibility and stability, suggesting that different prefrontal regions are activated by different types of prediction errors, dependent on their behavioral requirements. Furthermore, we found that striatal activation in response to switches and drifts was modulated by participants' successful behavior toward these events, suggesting the striatum to be responsible for response selections following unpredicted stimuli. Finally, we observed that the dopaminergic midbrain modulates the transition between different cognitive states, thresholded by participants' individual performance history in response to temporal environmental demands.
A Genetic-Algorithm Approach to Scheduling Communications for Embedded Parallel Space-Time Adaptive Processing Algorithms

Computational efficiency is of great significance for high-performance embedded applications. The work here develops and evaluates a genetic-algorithm-based (GA-based) optimization technique for the scheduling of messages for a class of parallel embedded signal processing techniques known as space-time adaptive processing (STAP). The GA-based optimization is performed off-line, resulting in static schedules for the compute nodes of the parallel system. These static schedules are utilized for the on-line implementation of the parallel STAP application. The primary motivation and justification for devoting significant off-line effort to solving the formulated scheduling problem is the resulting reduction of hardware resources required for the actual on-line implementation. Numerical studies illustrate that reductions in hardware requirements of around 50% can be achieved by employing the results of the proposed scheduling techniques. This reduction in hardware requirement is of critical importance for STAP, which is typically an airborne application in which the size, weight, and power consumption of the computational platform are severely constrained.
Dyslexia research at the turn of the 21st century: behavioural, neuroimaging and genetic findings

Behavioural studies have shown that dyslexics are a heterogeneous population and between-group comparisons are thus inadequate. Some subjects do not develop dyslexia despite having a deficit implicated in this disorder, which points to protective factors. Dyslexia co-occurs with ADHD, DCD, SLI, and SSD, so that future behavioural studies will need to screen and/or statistically control for other disorders. Studies of multiple cases of DPs with other developmental disorders are necessary. Neuroimaging findings show structural and/or functional brain abnormalities in language areas, V5/MT and the cerebellum. Future neuroimaging studies need to investigate the whole reading network and multiple cases. Six dyslexia risk genes have been found, mostly involved in neural migration, which may suggest dyslexia is a deficit of neuronal migration. However, it is not clear how these genes can restrict migration to specific brain areas. As a complex and heterogeneous disorder, dyslexia is likely to be associated with several mutated genes. ADHD and SSD are characterised by genetic risk factors which are partially shared with dyslexia, resulting in comorbidity. Future genetic studies need to focus on identifying other risk genes and pleiotropic genes involved in comorbidities, and linking genotypes implicated in dyslexia with brain structure. Any theory of dyslexia needs to take into account a multitude of risk and protective factors across behavioural, neural and genetic domains.
Taxonomic Relationships among Turkish Water Frogs as Revealed by Phylogenetic Analyses using mtDNA Gene Sequences

We assessed taxonomic relationships among Turkish water frogs through estimation of phylogenetic relationships among 62 adult specimens from 44 distinct populations inhabiting seven main geographical regions of Turkey using 2897 bp sequences of the mitochondrial Cytb, 12S rRNA and 16S rRNA genes with equally-weighted parsimony, likelihood, and Bayesian methods of inference. Monophyletic clade (Clade A) of the northwesternmost (Thrace) samples is identified as Pelophylax ridibundus. The other clade (Clade B) consisted of two monophyletic subclades. One of these contains specimens from southernmost populations that are regarded as an unnamed species. The other subclade consists of two lineages, of which one corresponds to P. caralitanus and another to P. bedriagae. Taxonomic relationships of these two species are discussed and recognition of P. caralitanus as a subspecies of P. bedriagae is proposed.
Minimal Residual Approaches for Policy Evaluation in Large Sparse Markov Chains

We consider the problem of policy evaluation in a special class of Markov Decision Processes (MDPs) where the underlying Markov chains are large and sparse . We start from a stationary model equation that the limit of Temporal Difference (TD) learning satisﬁes, and develop a Robbins-Monro method consistently estimating its coefﬁcients. Then we introduce the minimal residual approaches, which solve an approximate version of the stationary model equation. Incremental Least-squares temporal difference (iLSTD) is shown to be a special form of minimal residual approaches. We also develop a new algorithm called minimal residual (MR) algo-rithm whose step-size can be computed on line. We introduce the Compressed Sparse Row (CSR) format and reduce the complexity of MR to near that of TD. The advantages of the MR algorithm are that it has comparable data efﬁciency and computational efﬁciency to iLSTD, but does not require manual selection of step-size.
Anaerobic growth of Neisseria gonorrhoeae coupled to nitrite reduction

A total of 204 Neisseria gonorrhoeae strains, including 39 penicillinase-producing strains, representing 64 distinct auxotype and serovar classes were tested for their ability to grow anaerobically with nitrite as a terminal electron acceptor. All strains grew anaerobically with subtoxic concentrations of nitrite, and all penicillinase-producing strains produced beta-lactamase when grown anaerobically. Nitrite reductase was produced constitutively under aerobic conditions in the absence of nitrite, and cytochrome oxidase was produced constitutively under anaerobic conditions. Strains could not grow anaerobically with sulfite as a terminal electron acceptor. Strain NRL 905 grew anaerobically in broth medium containing nitrite at a rate comparable to its growth rate under aerobic conditions. The feasibility and significance of in vivo anaerobic growth of N. gonorrhoeae is discussed.
Atomistic Simulations of Dislocation Nucleation

The objective of this research is to use atomistic simulations to investigate dislocation nucleationfrom asymmetric tilt grain boundaries in FCC copper and aluminum. We use a 3D periodicbicrystal configuration to investigate how grain boundary degrees of freedom impact both theboundary structure and dislocation nucleation in symmetric and asymmetric tilt boundaries.Simulation results show that dislocation nucleation from asymmetric tilt grain boundaries requiresunderstanding of the structure and faceting of these boundaries. Deformation simulations of singlecrystals and grain boundaries under uniaxial tension and compression show entirely differentnucleation mechanisms, i.e., nucleation of full dislocations in copper from the grain boundaryunder compression. Analysis of the resolved stresses shows that the resolved stress normal to theslip plane on which the dislocation nucleates plays an integral role in dislocation nucleation forboth single crystals and interfaces.
Transcript and protein expression profiles of the NCI-60 cancer cell panel: an integromic microarray study

To evaluate the utility of transcript profiling for prediction of protein expression levels, we compared profiles across the NCI-60 cancer cell panel, which represents nine tissues of origin. For that analysis, we present here two new NCI-60 transcript profile data sets (A based on Affymetrix HG-U95 and HG-U133A chips; Affymetrix, Santa Clara, CA) and one new protein profile data set (based on reverse-phase protein lysate arrays). The data sets are available online at http://discover.nci. nih.gov in the CellMiner program package. Using the new transcript data in combination with our previously published cDNA array and Affymetrix HU6800 data sets, we first developed a “consensus set” of transcript profiles based on the four different microarray platforms. Using that set, we found that 65% of the genes showed statistically significant transcript-protein correlation, and the correlations were generally higher than those reported previously for panels of mammalian cells. Using the predictive analysis of microarray nearest shrunken centroid algorithm for functional prediction of tissue of origin, we then found that (a) the consensus mRNA set did better than did data from any of the individual mRNA platforms and (b) the protein data seemed to do somewhat better (P = 0.027) on a gene-for-gene basis in this particular study than did the consensus mRNA data, but both did well. Analysis based on the Gene Ontology showed protein levels of structure-related genes to be well predicted by mRNA levels (mean r = 0.71). Because the transcript-based technologies are more mature and are currently able to assess larger numbers of genes at one time, they continue to be useful, even when the ultimate aim is information about proteins. [Mol Cancer Ther 2007;6(3):820–32]