Miracle-dz/UniFAR-FTUs huggingface dataset:
The Core of Games on Distributive Lattices

Cooperative games under precedence constraints have been introduced by Faigle and Kern [1] , [4] as a generalization of classical cooperative games. An important notion in cooperative game theory is the core of the game, as it contains the rational imputations for players. We propose two definitions for the core of a distributive game, the first one is called the precore and is a direct generalization of the classical definition. It contains the set of imputations and may be unbounded, which makes its application questionable. A second definition is proposed, imposing normalization at each stage, causing the core to be a convex bounded set. We study its properties, introducing balancedness and marginal worth vectors, and defining the Weber set and the pre-Weber set. We show that the classical properties of inclusion of the (pre)core into the (pre)-Weber set as well as their coincidence in the convex case remain valid.
High Content Screening Identifies Decaprenyl-Phosphoribose 2′ Epimerase as a Target for Intracellular Antimycobacterial Inhibitors

A critical feature of Mycobacterium tuberculosis, the causative agent of human tuberculosis (TB), is its ability to survive and multiply within macrophages, making these host cells an ideal niche for persisting microbes. Killing the intracellular tubercle bacilli is a key requirement for efficient tuberculosis treatment, yet identifying potent inhibitors has been hampered by labor-intensive techniques and lack of validated targets. Here, we present the development of a phenotypic cell-based assay that uses automated confocal fluorescence microscopy for high throughput screening of chemicals that interfere with the replication of M. tuberculosis within macrophages. Screening a library of 57,000 small molecules led to the identification of 135 active compounds with potent intracellular anti-mycobacterial efficacy and no host cell toxicity. Among these, the dinitrobenzamide derivatives (DNB) showed high activity against M. tuberculosis, including extensively drug resistant (XDR) strains. More importantly, we demonstrate that incubation of M. tuberculosis with DNB inhibited the formation of both lipoarabinomannan and arabinogalactan, attributable to the inhibition of decaprenyl-phospho-arabinose synthesis catalyzed by the decaprenyl-phosphoribose 2′ epimerase DprE1/DprE2. Inhibition of this new target will likely contribute to new therapeutic solutions against emerging XDR-TB. Beyond validating the high throughput/content screening approach, our results open new avenues for finding the next generation of antimicrobials.
Dynamical and chemical properties of the "starless" core L1014

Spitzer Space Telescope observations of a point-like source, L1014-IRS, close to the dust peak of the low-mass dense core L1014, have raised questions about its starless nature. These show the presence of an object with colors expected for an embedded protostar with the implication that L1014-IRS would be the lowest luminosity isolated protostar known, and an ideal target with which to test star formation theories at the low mass end. In order to study its molecular content and to search for the presence of a molecular outflow, we mapped L1014 in at least one transition of 12 CO, N2H + ,H CO + , CS, and of their isotopologues 13 CO, C 18 O, C 17 O, N2D + ,a nd H 13 CO + , using the Five College Radio Astronomy Observatory (FCRAO), the IRAM 30 m antenna, and the Caltech Submillimeter Observatory (CSO). The data show physical and chemical properties in L1014 typical of moderately evolved dense cores: i.e. H2 central density of a few 10 5 molecules cm −3 , estimated mass of ∼2 M� , CO integrated depletion factor less than 10, N(N2H + ) � 6 × 10 12 cm −2 , N(N2D + )/N(N2H + ) equal to 10%, and relatively broad N2H + and N2D + lines (0.35 km s −1 ). Infall signatures and significant velocity shifts between optically thick and optically thin tracers are not observed in the line profiles. No classical signatures of molecular outflow are found in the 12 CO and 13 CO FCRAO observations. In particular, no high velocity wings are found, and no well-defined blue-red lobes of 12 CO emission are seen in the channel maps. Sensitive, higher resolution observations will clarify the presence of a molecular outflow on a smaller scale than that probed by our observations.
Reliable Multipath Provisioning for High-Capacity Backbone Mesh Networks

We investigate reliable multipath provisioning of traffic in high-capacity backbone mesh networks, e.g., next-generation SONET/SDH networks supporting virtual concatenation (VCAT). VCAT enables a connection to be inversely multiplexed on to multiple paths, a feature that may lead to significantly improved performance over conventional single-path provisioning. Other mesh networks such as those employing optical wavelength-division multiplexing (WDM) and multiprotocol label switching (MPLS) can also benefit from this multipath provisioning approach. We propose effective multipath bandwidth as the metric to provision a connection while satisfying its reliability requirements (measured in terms of availability). We demonstrate that effective multipath bandwidth provides more flexibility and lower blocking probability without the cost and the complexity associated with traditional protection schemes developed for optical WDM and MPLS networks. We also investigate the practical problem of provisioning effective multipath bandwidth with cost constraints. We analyze the tractability of the problem and present a heuristic which results in significantly reduced number of blocked connections due to cost constraints.
Empirical evidence that algorithm animation promotes understanding of distributed algorithms

Previous studies of program visualization have generally failed to provide convincing support for the benefits of algorithm animation in promoting the understanding of computations. This paper presents a study in which the use of program visualization resulted in significantly better understanding of a distributed computation. Understanding was measured in terms of the number of correct responses to questions about the algorithm. The environment used in this study differs from that of previous studies in a number of aspects: it combines the use of distributed algorithm visualization, 3D visualization, and legends. In addition, the design of both the experiment and animation focuses on reducing cognitive noise.
An integrative model of pediatric medical traumatic stress.

OBJECTIVE To guide assessment and intervention for patients and families, a model for assessing and treating pediatric medical traumatic stress (PMTS) is presented that integrates the literature across pediatric conditions. METHODS A model with three general phases is outlined--I, peritrauma; II, early, ongoing, and evolving responses; and III, longer-term PMTS. Relevant literature for each is reviewed and discussed with respect to implications for intervention for patients and families. RESULTS Commonalities across conditions, the range of normative responses to potentially traumatic events (PTEs), the importance of preexisting psychological well-being, developmental considerations, and a social ecological orientation are highlighted. CONCLUSIONS Growing empirical support exists to guide the development of assessment and intervention related to PMTS for patients with pediatric illness and their parents. The need for interventions across the course of pediatric illness and injury that target patients, families, and/or healthcare teams is apparent. The model provides a basis for further development of evidence-based treatments.
Genetic Factors in the Pathogenesis of Nonalcoholic Fatty Liver and Steatohepatitis

Liver fat accumulation generally related to systemic insulin resistance characterizes nonalcoholic fatty liver disease (NAFLD), which in the presence of nonalcoholic steatohepatitis (NASH) can progress towards cirrhosis and hepatocellular carcinoma. Due to the epidemic of obesity, NAFLD is now the most frequent liver disease in Western countries. Epidemiological, familial, and twin studies provide evidence for a strong genetic component of NAFLD susceptibility. Recently, genome-wide association studies led to the identification of the major inherited determinants of hepatic fat accumulation: patatin-like phospholipase domain-containing 3 (PNPLA3) I148M gene and transmembrane 6 superfamily member 2 (TM6SF2) E167K gene variants, involved in lipid droplets remodelling and very low-density lipoproteins secretion, are the major determinants of interindividual differences in liver steatosis, and susceptibility to progressive NASH. In this review, we aimed to provide an overview of recent insights into the genetics of hepatic fat accumulation and steatohepatitis.
Slovak Unit-Selection Speech Synthesis: Creating a New Slovak Voice within a Czech TTS System ARTIC

ARTIC (Artificial Talker in Czech) is a corpus- based text-to-speech (TTS) system that enables to synthesise an arbitrary text, mainly for the Czech language. Basically, two versions of ARTIC are available—a single unit instance system (also known as fixed-inventory synthesis) with the quality of resulting speech limited by the fixed inventory, and multiple unit instance system with the quality profitting from employing a unit-selection algorithm to select the longest suitable sequence of phonetic units from many units available. In this paper, a process of building a new Slovak voice for the unit-selection version of ARTIC is presented. All steps in the design, from the preparation of a suitable speech corpus to the creation of an acoustic unit inventory of the new Slovak voice and its use in the ARTIC system will be described. Text processing module, including automatic phonetic transcription and symbolic prosodic description of an arbitrary Slovak text, will be detailed. Finally, speech production module based on the unit selection algorithm will be mentioned as well.
INTEGRAL observations of six AGN in the Galactic Plane

We present results on approximately one year of INTEGRAL observations of six AGN detected during the regular scans of the Galactic Plane. The sample is composed by five Seyfert 2 objects (MCG –05–23–16, NGC 4945, the Circinus galaxy, NGC 6300, ESO 103–G35) and the radio galaxy Centaurus A. The continuum emission of each of these sources is well represented by a highly absorbed ($N_{\rm H}>10^{22} \, \rm cm^{-2}$) power law, with average spectral index $\Gamma = 1.9 \pm 0.3$. A high energy exponential cut-off at $E_{\rm c} \sim 50 \rm \,~keV$ is required to fit the spectrum of the Circinus galaxy, whereas a lower limit of 130 keV has been found for NGC 4945 and no cut-off has been detected for NGC 6300 in the energy range covered by these INTEGRAL data. The flux of Centaurus A was found to vary by a factor of ~2 in 10 months, showing a spectral change between the high and low state, which can be modelled equally well by a change in the absorption ( N H from 17 to $33 \times 10^{22} \rm \, cm^{-2}$) or by the presence of a cut-off at $\ga$120 keV in the low state spectrum. A comparison with recently reprocessed BeppoSAX /PDS data shows a general agreement with INTEGRAL results. The high energy cut-off in the hard X-ray spectra appears to be a common but not universal characteristic of Seyfert 2 and to span a wide range of energies.
Artificial Affective Listening towards a Machine Learning Tool for Sound-Based Emotion Therapy and Control

We are extending our work in EEG-based emotion detection for automated expressive performances of algorithmically composed music for affective communication and induction. This new system will involve music composed and expressively performed in real-time to induce specific affective states, based on the detection of affective state in a human listener. Machine learning algorithms will learn: (1) how to use EEG and other biosensors to detect the user’s current emotional state; and (2) how to use algorithmic performance and composition to induce certain affective trajectories. In other words the system will attempt to adapt so that it can – in real-time turn a certain user from depressed to happy, or from stressed to relaxed, or (if they like horror movies! ) from relaxed to fearful. As part of this we have developed a test-bed involving an artificial listening affective agent to examine key issues and test potential solutions. As well as giving a project overview, prototype design and first experiments with this artificial agent are presented here.
Learning to Predict Opinion Share in Social Networks

We address the problem of predicting the expected opinion share over a social network at a target time from the opinion diffusion data under the value-weighted voter model with multiple opinions. The value update algorithm ensures that it converges to a correct solution and the share prediction results outperform a simple linear extrapolation approximation when the available data is limited. We further show in an extreme case of complete network that the opinion with the highest value eventually takes over, and the expected share prediction problem with uniform opinion value is not well-defined and any opinion can win.
In Macrophages, Caspase-1 Activation by SopE and the Type III Secretion System-1 of S. Typhimurium Can Proceed in the Absence of Flagellin

The innate immune system is of vital importance for protection against infectious pathogens. Inflammasome mediated caspase-1 activation and subsequent release of pro-inflammatory cytokines like IL-1β and IL-18 is an important arm of the innate immune system. Salmonella enterica subspecies 1 serovar Typhimurium (S. Typhimurium, SL1344) is an enteropathogenic bacterium causing diarrheal diseases. Different reports have shown that in macrophages, S. Typhimurium may activate caspase-1 by at least three different types of stimuli: flagellin, the type III secretion system 1 (T1) and the T1 effector protein SopE. However, the relative importance and interdependence of the different factors in caspase-1 activation is still a matter of debate. Here, we have analyzed their relative contributions to caspase-1 activation in LPS-pretreated RAW264.7 macrophages. Using flagellar mutants (fliGHI, flgK) and centrifugation to mediate pathogen-host cell contact, we show that flagellins account for a small part of the caspase-1 activation in RAW264.7 cells. In addition, functional flagella are of key importance for motility and host cell attachment which is a prerequisite for mediating caspase-1 activation via these three stimuli. Using site directed mutants lacking several T1 effector proteins and flagellin expression, we found that SopE elicits caspase-1 activation even when flagellins are absent. In contrast, disruption of essential genes of the T1 protein injection system (invG, sipB) completely abolished caspase-1 activation. However, a robust level of caspase-1 activation is retained by the T1 system (or unidentified T1 effectors) in the absence of flagellin and SopE. T1-mediated inflammasome activation is in line with recent work by others and suggests that the T1 system itself may represent the basic caspase-1 activating stimulus in RAW264.7 macrophages which is further enhanced independently by SopE and/or flagellin.
Throughput-Lifetime Trade-Offs in Multihop Wireless Networks under an SINR-Based Interference Model

High throughput and lifetime are both crucial design objectives for a number of multihop wireless network applications. As these two objectives are often in conflict with each other, it naturally becomes important to identify the trade-offs between them. Several works in the literature have focused on improving one or the other, but investigating the trade-off between throughput and lifetime has received relatively less attention. We study this trade-off between the network throughput and lifetime for the case of fixed wireless networks, where link transmissions are coordinated to be conflict-free. We employ a realistic interference model based on the Signal-to-Interference-and-Noise Ratio (SINR), which is usually considered statistically sufficient to infer success or failure of wireless transmissions. Our analytical and numerical results provide several insights into the interplay between throughput, lifetime, and transmit power. Specifically, we find that with a fixed throughput requirement, lifetime is not monotonic with power-neither very low power nor very high power result in the best lifetime. We also find that, for a fixed transmit power, relaxing the throughput requirement may result in a more than proportional improvement in the lifetime for small enough relaxation factors. Taken together, our insights call for a careful balancing of objectives when designing a wireless network for high throughput and lifetime.
Efficiently Generalizing Ultra-Cold Atomic Simulations via Inhomogeneous Dynamical Mean-Field Theory from Two- to Three-Dimensions

We describe techniques that we are implementing to move inhomogeneous dynamical mean-field theory simulations from two-to three-dimensions. Two-dimensional simulations typically run on 2,000 -- 10,000 lattice sites, while three-dimensional simulations typically need to run on 1,000,000 or more lattice sites. The inhomogeneous dynamical mean-field theory requires the diagonal of the inverse of many sparse matrices with the same sparsity pattern, and a dimension equal to the number of lattice-sites. For two-dimensional systems, we have employed general dense LAPACK routines since the matrices are small enough. For three-dimensional systems, we need to employ sparse matrix techniques. Here, we present one possible strategy for the sparse matrix routine, based on the well-known Lanczos technique, with a long run of the algorithm and (partial) reorthogonalization. This approach is about two-times faster than the LAPACK routines with identical accuracy, and hence will become the standard we use on the two-dimensional problems. We illustrate this approach on the problem of increasing the efficiency for pre-forming dipolar molecules in K-Rb mixtures on a lattice. We compare the local density approximation to inhomogeneous dynamical mean-field theory to illustrate how the local density approximation fails at low-temperature, and to illustrate the benefits of the new algorithms. For a three-dimensional problem, a speed-up of 1,000 or more times is needed. We end by discussing some options that are promising toward reaching this goal.
Using Tariff Indices to Evaluate Preferential Trading Arrangements : An Application to Chile *

A tariff index that, combined with a simple general equilibrium model, can be used to calculate more accurately how preferential tariff reductions affect sectoral output, factor prices, average tariff rates, and general welfare. Summary findings Bond presents a tariff index that uses constant-elasticity-of-substitution aggregators of tariff line data to calculate how preferential tariff reductions affect both prices and average tariff rates. A simple general-equilibrium model with sector-specific factors of production can be combined with the tariff indices to calculate how a preferential trade arrangement affects sectoral output, factor prices, and general welfare. The general equilibrium model is simple enough that it can be calculated on an Excel spreadsheet, and is flexible enough to be used with different ranges of available domestic data. Bond presents an example of the model, simulating the effects of free trade agreements between Chile and MERCOSUR countries and between Chile and NAFTA countries. Calculations for the case of Chile show that the index is simple to calculate because of its recursive structure, which allows large amounts of detailed tariff line data to be aggregated for use with domestic production data that is available only at a more aggregated level. Bond finds that results using the tariff aggregators may differ substantially from those derived using simple averages of tariff reductions. Reductions in import prices using the index were 10 to 30 percent larger than those calculated using a simple average of tariffs. Ignoring the information available in tariff line data could lead to a substantial overestimate of the average tariff rate on imports after a preferential reduction. The tariff index could be extended to incorporate the role of quantitative restructions. The general equilibrium model could be used to consider the effects on domestic production of allowing reallocation of capital between industries over time. The Policy Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Foreword As regional trading arrangements (RTAs) have spread, enlarged and deepened over the last decade, …
Applicability of feature selection on multivariate time series data for robotic discovery

Open ended robotic discovery aims at enabling robots to autonomously design and execute sophisticated experiments for gaining conceptual insight about real world. Such experiments are planned activities rather than innate motor commands and thus each single experiment results in a multivariate time series. In such a scenario, reducing the number of features in order to allow a symbolic learner to build a correct conceptual model of underlying phenomena is a fundamental task. Only few feature selection approaches deal with finding relevant features in multivariate time series, which is just what the robot receives through its sensors. In this paper, we present results of applicability of a range of feature selection and time series analysis approaches on a novel real world scenario for autonomous robotic discovery. We found that even sophisticated representations and state of the art techniques, which perform very well on other benchmarks, do not show significant results in context of open ended discovery.
Combining multiple features for text-independent writer identification and verification

In recent years, we proposed a number of new and very effective features for automatic writer identification and verification. They are probability distribution functions (PDFs) extracted from the handwriting images and characterize writer individuality independently of the textual content of the written samples. In this paper, we perform an extensive analysis of feature combinations. In our fusion scheme, the final unique distance between two handwritten samples is computed as the average of the distances due to the individual features participating in the combination. Obtained on a large dataset containing 900 writers, our results show that fusing multiple features (directional, grapheme, run-length PDFs) yields increased writer identification and verification performance.