Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing consensus Monte Carlo strategies for distributed Bayesian computation

Consensus Monte Carlo is an algorithm for conducting Monte Carlo based Bayesian inference on large data sets distributed across many worker machines in a data center. The algorithm operates by running a separate Monte Carlo algorithm on each worker machine, which only sees a portion of the full data set. The worker-level posterior samples are then combined to form a Monte Carlo approximation to the full posterior distribution based on the complete data set. We compare several methods of carrying out the combination, including a new method based on approximating worker-level simulations using a mixture of multivariate Gaussian distributions. We ﬁnd that resampling and kernel density based methods break down after 10 or sometimes fewer dimensions, while the new mixture-based approach works well, but the necessary mixture models take too long to ﬁt.
Decision Tree Based Algorithm for IPv6 Routing Table Lookup

The next generation Internet Protocol, IPv6, has attracted growing attention and has been deploying worldwide, especially in Europe, Asia, and North America. With 128-bit address, IPv6 provides an extremely large address space and poses a great challenge to the routing table lookup algorithms. The previous algorithms need reconsideration. An IPv6-specific longest prefix matching (LPM) scheme called DTLU (Decision Tree LookUp) is introduced is this paper. By dividing route prefixes into chunks, the scheme converts the IPv6 LPM problem to the multi-dimensional packet classification problem and then uses the decision tree to conquer the classification problem. Moreover observations are made on the real live IPv6 backbone BGP routing tables and on the converted classifiers. Then the observations are used to enhance the basic DTLU. DTLU supports incremental updates and only needs tens of kilobytes memory for the current real live IPv6 backbone BGP routing tables. The evaluation results show that the sample software implementation of DTLU can achieve more than 10 million lookups per second on a PC with Pentium4 2.4GHz CPU, 512M DDR333 memory, and Linux operating system.
Prise en compte de l'ionisation et du rayonnement dans la modélisation des écoulements de rentrée terrestre et martienne

Ce travail porte sur la simulation numerique des ecoulements de rentree martienne et terrestre. Parmi les phenomenes physico-chimiques complexes mis en jeu, les points abordes concernent plus particulierement l'ionisation du gaz dans la couche de choc et l'effet du rayonnement sur les flux thermiques parietaux. Le traitement de l'ionisation repose sur l'approche de Coquel-Marmignon permettant d’ecrire le systeme d’equations sous forme conservative. L'approche numerique est basee sur le schema de Roe et elle est validee sur trois cas d'epreuve pour des vitesses allant jusqu’a 11km/s. Un schema de relaxation, plus simple de mise en œuvre et mieux adapte, est egalement propose. Le traitement du rayonnement depend du cas d’application. Pour les applications terrestres, le modele de proprietes radiatives est de type raie-par-raie et la methode de resolution de l'equation de transfert radiatif est la methode des plans tangente. Les champs hydrodynamique et radiatif sont couples par une methode iterative. La comparaison avec les mesures en vol de la campagne FIRE II montre que l'approche est satisfaisante, excepte lorsque l'approximation liee aux plans tangente n’est plus valable (faible rayon de nez, loin de la region d’arret). Au point d’arret, le rayonnement participe jusqu'a 40% a l'echauffement parietal. Pour les applications martiennes, le modele de proprietes radiatives, limite aux contributions des especes CO et CO[indice 2] dans l'infrarouge, est de type statistique a bandes etroites et la methode numerique de type Monte Carlo. La methode de couplage hydrodynamique/rayonnement est similaire au cas terrestre. Les calculs, menes sur un vehicule generique typique de la mission Mars Premier, montrent qu’au niveau de l'arriere-corps, le rayonnement contribue de maniere signiﬁcative a l'echauffement parietal.
Assisted colonization as a climate change adaptation tool.

Assisted colonization is a form of conservation translocation which introduces species at risk from extinction to new habitats, beyond their current range, in anticipation of more suitable conditions. Identifying which species, communities and ecosystems may benefit most from assisted colonization in coming decades is a key goal for conservation. Climate change is expected to lead to the loss or movement of suitable habitat for a range of species and anticipating which can be effectively conserved through assisted colonization is critical. Here, we identify a series of scenarios that may predispose terrestrial species to the need for assisted colonization in order to reduce extinction risk resulting from anthropogenic climate change and assemble a list of traits commonly associated with at-risk species. These traits may help to provide broad-scale guidance on how to select species to target for assisted colonization as a conservation management response to climate change. We also identify six key themes associated with successful conservation translocations including recipient site selection and preparation, a clear understanding of species biology and ecology, and taking lessons from invasive species research.
Simulation of Shading Effects on the power output of solar modules for enhanced efficiency in photovoltaic energy generation

Shading Effects have a negative influence on the power output of solar cells. They reduce the efficiency of a module, which affects also other cells in the system. Main goal of this work is to have a structure that prevents the energy generation from such effects and bridge the affected modules. Therefor a simulation tool has been developed to compute whether a cell should be bridged or not. Input parameters are the illumination, temperature and the properties of the modules. It simulates the output power of the system and compares the values with and without the affected cells. The result is the decision if a module should be on or off. The MPP (maximum power point) voltage is a side product of this simulation. The goal is to have a retrofittable wireless sensor system which can be used to improve old structures. The simulation algorithm proposed here will be part of this system.
Activity of Selected Essential Oils against Candida spp. strains. Evaluation of New Aspects of their Specific Pharmacological Properties, with Special Reference to Lemon Balm

The aim was to investigate the antifungal effectiveness and some of pharmacological properties of essential oils (EOs), which had not yet been thoroughly studied in the planned scope. We first evaluated MIC/MFC of sixteen EOs against C. albicans ATCC 10231. Then, five most active EOs were tested, using 50 clinical Candida spp. strains and additional reference C. albicans ATCC 90028 strain. The time-kill curve, carryover, post-antifungal effects (PAFE), mutant prevention concentrations, the susceptibility of reference strains to the cell wall disrupting agents and tolerance to oxidative stress, were evaluated. For these detailed studies, we chose the following four essential oils. Clove oil, Geranium oil, Lemon balm and Citronella oil, with MICs of 0.097% (v/v), resulted concentration- and time-dependent killing and may be therapeutically safe, because they do not generate resistance. The best one was Lemon balm, which caused most extended PAFE, significantly reduced tolerance to oxidative stress and increased susceptibility to Calcofluor White, Congo Red and SDS. Phytochemical analysis of these four EOs has been performed and compared; looking for the reason that Lemon balm was the best.
Evaluation of Phosphatidylinositol-4-Kinase IIIα as a Hepatitis C Virus Drug Target

ABSTRACT Phosphatidylinositol-4-kinase IIIα (PI4KIIIα) is an essential host cell factor for hepatitis C virus (HCV) replication. An N-terminally truncated 130-kDa form was used to reconstitute an in vitro biochemical lipid kinase assay that was optimized for small-molecule compound screening and identified potent and specific inhibitors. Cell culture studies with PI4KIIIα inhibitors demonstrated that the kinase activity was essential for HCV RNA replication. Two PI4KIIIα inhibitors were used to select cell lines harboring HCV replicon mutants with a 20-fold loss in sensitivity to the compounds. Reverse genetic mapping isolated an NS4B-NS5A segment that rescued HCV RNA replication in PIK4IIIα-deficient cells. HCV RNA replication occurs on specialized membranous webs, and this study with PIK4IIIα inhibitor-resistant mutants provides a genetic link between NS4B/NS5A functions and PI4-phosphate lipid metabolism. A comprehensive assessment of PI4KIIIα as a drug target included its evaluation for pharmacologic intervention in vivo through conditional transgenic murine lines that mimic target-specific inhibition in adult mice. Homozygotes that induce a knockout of the kinase domain or knock in a single amino acid substitution, kinase-defective PI4KIIIα, displayed a lethal phenotype with a fairly widespread mucosal epithelial degeneration of the gastrointestinal tract. This essential host physiologic role raises doubt about the pursuit of PI4KIIIα inhibitors for treatment of chronic HCV infection.
The Mechanism of the Amidases

Background: A cysteine, a glutamic acid, and a lysine are the well known amidase catalytic residues. Results: Mutating the neighboring, structurally conserved Glu-142 inactivates the enzyme, but the active site cysteine still reacts with acrylamide via its double bond. Conclusion: Glu-142 positions the amide for productive nucleophilic attack by the cysteine. Significance: An intact catalytic tetrad is required for amidase activity. All known nitrilase superfamily amidase and carbamoylase structures have an additional glutamate that is hydrogen bonded to the catalytic lysine in addition to the Glu, Lys, Cys “catalytic triad. ” In the amidase from Geobacillus pallidus, mutating this glutamate (Glu-142) to a leucine or aspartate renders the enzyme inactive. X-ray crystal structure determination shows that the structural integrity of the enzyme is maintained despite the mutation with the catalytic cysteine (Cys-166), lysine (Lys-134), and glutamate (Glu-59) in positions similar to those of the wild-type enzyme. In the case of the E142L mutant, a chloride ion is located in the position occupied by Glu-142 Oϵ1 in the wild-type enzyme and interacts with the active site lysine. In the case of the E142D mutant, this site is occupied by Asp-142 Oδ1. In neither case is an atom located at the position of Glu-142 Oϵ2 in the wild-type enzyme. The active site cysteine of the E142L mutant was found to form a Michael adduct with acrylamide, which is a substrate of the wild-type enzyme, due to an interaction that places the double bond of the acrylamide rather than the amide carbonyl carbon adjacent to the active site cysteine. Our results demonstrate that in the wild-type active site a crucial role is played by the hydrogen bond between Glu-142 Oϵ2 and the substrate amino group in positioning the substrate with the correct stereoelectronic alignment to enable the nucleophilic attack on the carbonyl carbon by the catalytic cysteine.
Colored clock jitter model in audio continuous-time ΣΔ modulators

In this paper the effect of colored clock jitter on audio continuous-time ΣΔ modulators is studied. The results demonstrate the importance of using the correct model for the jitter on the clock signal, especially when it is generated by a phase-locked loop, as it is the case in most audio applications. The paper demonstrates that the popular clock signal model with white jitter noise spectrum leads to worse ΣΔ modulator performance than a more realistic model with colored jitter noise spectrum. Indeed, such a model allows the designer to obtain more reliable simulation results, in order to choose the most suitable architecture and size correctly the circuit components to achieve the desired design target, leading to power consumption and area optimization.
Strand-level proximity losses in PM machines designed for high-speed operation

The stator windings of surface PM synchronous machines with fractional-slot concentrated windings are vulnerable to high proximity losses when operated at high speeds due to their typically high pole numbers and resulting high electrical frequencies. The limitations of an existing 1-D flux density model are demonstrated and an improved 2-D analytical model is introduced for estimating flux densities and stand-level proximity losses inside the slots. The 2-D analytical model is shown to provide good matches with finite element analysis for the predicted flux densities and proximity losses inside a rectangular slot with a variable slot opening and electrical frequency.
Formalizing Langacker ’ s Notions of Nouns and Verbs Introduction

Nouns The final topic covered in chapter three is Langacker’s approach to abstract nouns . He treats abstract nouns as the linguistic handle referring to the result of a summary scan on a process . In our framework, an abstract noun like explosion would evoke theExplode x-schema, and then bind itself to the collection of states that the x-schema w nt through during the simulation of an Explode action.
Multilevel Annotation of Agreement and Disagreement in Italian News Blogs

In this paper, we present a corpus of news blog conversations in Italian annotated with gold standard agreement/disagreement relations at message and sentence levels. This is the first resource of this kind in Italian. From the analysis of ADRs at the two levels emerged that agreement annotated at message level is consistent and generally reflected at sentence level, moreover, the argumentation structure of disagreement is more complex than agreement. The manual error analysis revealed that this resource is useful not only for the analysis of argumentation, but also for the detection of irony/sarcasm in online debates. The corpus and annotation tool are available for research purposes on request.
Continuous versus inpatient prophylaxis of the first episode of spontaneous bacterial peritonitis with norfloxacin

Cirrhotic patients with ascites and low ascitic fluid total protein and/or high serum bilirubin levels are at high risk to develop the first episode of spontaneous bacterial peritonitis during long‐term follow‐up. The aim of the present study was to determine the efficacy of continuous long‐term selective intestinal decontamination with norfloxacin in the prevention of this complication. One hundred nine cirrhotic patients with ascites and ascitic fluid total protein levels of ⩽ 1 g/dL or serum bilirubin levels of > 2.5 mg/dL without previous spontaneous bacterial peritonitis were prospectively randomized into two groups: group 1 (n = 56) received norfloxacin, 400 mg daily administered orally, and group 2 (n = 53) was the long‐term control group, receiving norfloxacin only during hospitalization. During a mean follow‐up of 43 +/‐ 3 weeks, there was one spontaneous bacterial peritonitis (1.8%) in group 1 and 9 (16.9%) in group 2 (P < .01). The incidence of community‐acquired spontaneous bacterial peritonitis was lower in group 1 (1.8% vs. 13.2%, P < .05), whereas the incidence of nosocomial spontaneous bacterial peritonitis (0% vs. 3.7%) and the incidence of extraperitoneal infections (25% vs. 24.5%) were similar in both groups (P = NS). The actuarial probability of survival at 18 months was 75% in group 1 and 62% in group 2 (P = NS). Resistance to norfloxacin was observed in 9 of 10 (90%) Escherichia coli isolated in infections from group 1 and in 4 of 11 (36.3%) from group 2 (P < .05). The overall incidence of infections caused by norfloxacin‐resistant bacteria was higher in group 1 (19.6% vs. 15%), but it did not reach statistical significance. Continuous long‐term selective intestinal decontamination with norfloxacin is effective in preventing the first spontaneous bacterial peritonitis in cirrhotic patients at high risk. However, the emergence of infections caused by norfloxacin‐resistant bacteria must be weighed carefully against the benefits of continuous long‐term prophylaxis.
A minimal model of fire-vegetation feedbacks and disturbance stochasticity generates alternative stable states in grassland–shrubland–woodland systems

Altered disturbance regimes in the context of global change are likely to have profound consequences for ecosystems. Interactions between fire and vegetation are of particular interest, as fire is a major driver of vegetation change, and vegetation properties (e.g., amount, flammability) alter fire regimes. Mediterranean-type ecosystems (MTEs) constitute a paradigmatic example of temperate fire-prone vegetation. Although these ecosystems may be heavily impacted by global change, disturbance regime shifts and the implications of fire-vegetation feedbacks in the dynamics of such biomes are still poorly characterized. We developed a minimal modeling framework incorporating key aspects of fire ecology and successional processes to evaluate the relative influence of extrinsic and intrinsic factors on disturbance and vegetation dynamics in systems composed of grassland, shrubland, and woodland mosaics, which characterize many MTEs. In this theoretical investigation, we performed extensive simulations representing different background rates of vegetation succession and disturbance regime (fire frequency and severity) processes that reflect a broad range of MTE environmental conditions. Varying fire-vegetation feedbacks can lead to different critical points in underlying processes of disturbance and sudden shifts in the vegetation state of grassland–shrubland–woodland systems, despite gradual changes in ecosystem drivers as defined by the environment. Vegetation flammability and disturbance stochasticity effectively modify system behavior, determining its heterogeneity and the existence of alternative stable states in MTEs. Small variations in system flammability and fire recurrence induced by climate or vegetation changes may trigger sudden shifts in the state of such ecosystems. The existence of threshold dynamics, alternative stable states, and contrasting system responses to environmental change has broad implications for MTE management.
A parallel splitting-up method for partial differential equations and its applications to Navier-Stokes equations

La methode des pas fractionnaires est souhaitable pour le calcul sequentiel. Le pas, a une etape donnee, se calcule en fonction du pas a l'etape precedente. On propose ici, un nouveau schema de calcul, qui permet de determiner les pas fractionnaires independamment les uns des autres. On montre la convergence de la methode, et on donne une estimation du rang de convergence. Enfin on applique la methode proposee pour resoudre des problemes de Navier-Stokes en utilisant la methode des elements finis usuelle. On est amene alors a resoudre des systemes lineaires, a une dimension, independants, et qui peuvent etre traites par des processeurs en parallele
An improved particle swarm optimization algorithm for solving impulsive control problem

The particle swarm optimization (PSO), a newly developed method to the optimal impulse control, is an optimized algorithm with collective intelligence. The impulsive control problem has abrupt change of system states that make the problem of finding the global optimum difficult using any usual mathematical approaches. In this paper, an improved PSO algorithm is applied to obtain optimal numerical solutions to impulsive control problem. The operation strategy of ordered variables and Boolean variables is devised in such a way that the dynamic process inherent in the basic PSO is preserved. To demonstrate its efficiency and versatility, the proposed algorithm is applied and tested in two numerical experiments. Our results indicate that PSO algorithms can effectively find good enough solutions approximate to global optimum, although the solution algorithm is a population-based search one and is not suitable for the on-line implementation in real-time problems.
Adaptive intrusion detection algorithm based on learning algorithm

Signature based intrusion detection system (IDS), having stored rules for detecting intrusions at the library, judges whether new inputs are intrusion or not by matching them with the new inputs. However their policy has two restrictions generally. First, when they couldn't make rules against new intrusions, false negative (FN) errors may are taken place. Second, when they made a lot of rules for maintaining diversification, the amount of resources grows larger proportional to their amount. In this paper, we propose the learning algorithm which can evolve the competent of anomaly detectors having the ability to detect anomalous attacks by genetic algorithm. The anomaly detectors are the population be composed of by following the negative selection procedure of the biological immune system. To show the effectiveness of proposed system, we apply the learning algorithm to the artificial network environment, which is a computer security system.
Boundedness Properties For Time-Varying Nonlinear Systems

A Liapunov theorem guaranteeing uniform boundedness and uniform ultimate boundedness for a time-varying nonlinear system $\dot{x}(t) = f(x(t) , t)$ has been established. The study of uniform boundedness and uniform ultimate boundedness of particular classes of time-varying nonlinear systems $\dot{x} (t) =f(x(t) ,t )$ is reduced to the study of the corresponding time-invariant frozen systems $\dot{x} (t) = f(x(t) , \sigma )$ for all $\sigma \in \mathbb{R}$. This approach is illustrated for time-varying homogeneous systems with a positive order, for particular classes of time-varying nonhomogeneous systems and for time-varying Lotka--Volterra equations.