Miracle-dz/UniFAR-FTUs huggingface dataset:
Sparsifying network topologies for application guidance

Topology managers expose network information to applications to improve application-level resource management. An example for various ongoing standardization activities is Application-Layer Traffic Optimization (ALTO). Due to privacy and security constraints, exposed network information has to be filtered according to policies. As part of such policies, distance information can be abstracted by presenting coarser distances over pairs of clustered nodes rather than the precise distances between all node pairs. We refer to this process as distance sparsification. The contribution of this paper is two-fold, the first being a new policy system to enforce abstraction. The second and the main contribution addresses the algorithmic challenge. For the latter, we consider two types of distance sparsification algorithms. The first variant takes as input a matrix of pairwise distances. The sparsification algorithm produces a smaller distance matrix by clustering the nodes into clusters. The second variant instead collapses an edge-weighted graph. We measure the performance of the algorithms by the accuracy of the resulting sparsified distances, and we show that matrix sparsification outperforms graph sparsification. We further observe the trade-off between the accuracy and the size of the sparsified representation. In addition, we also extend our algorithms to handle labeled data, i. e. , abstraction policies explicitly mark a number of destinations as reference points. Such additional information can improve the distance sparsification.
CpxR Activates MexAB-OprM Efflux Pump Expression and Enhances Antibiotic Resistance in Both Laboratory and Clinical nalB-Type Isolates of Pseudomonas aeruginosa

Resistance-Nodulation-Division (RND) efflux pumps are responsible for multidrug resistance in Pseudomonas aeruginosa. In this study, we demonstrate that CpxR, previously identified as a regulator of the cell envelope stress response in Escherichia coli, is directly involved in activation of expression of RND efflux pump MexAB-OprM in P. aeruginosa. A conserved CpxR binding site was identified upstream of the mexA promoter in all genome-sequenced P. aeruginosa strains. CpxR is required to enhance mexAB-oprM expression and drug resistance, in the absence of repressor MexR, in P. aeruginosa strains PA14. As defective mexR is a genetic trait associated with the clinical emergence of nalB-type multidrug resistance in P. aeruginosa during antibiotic treatment, we investigated the involvement of CpxR in regulating multidrug resistance among resistant isolates generated in the laboratory via antibiotic treatment and collected in clinical settings. CpxR is required to activate expression of mexAB-oprM and enhances drug resistance, in the absence or presence of MexR, in ofloxacin-cefsulodin-resistant isolates generated in the laboratory. Furthermore, CpxR was also important in the mexR-defective clinical isolates. The newly identified regulatory linkage between CpxR and the MexAB-OprM efflux pump highlights the presence of a complex regulatory network modulating multidrug resistance in P. aeruginosa.
An Anatomy of Rating Through the Cycle

Using an asset-based model of default, I derive rating characteristics if ratings are meant to look 'through the cycle' as opposed to being based on the borrowers' current condition. The through-the-cycle method, which is employed by most rating agencies, requires a separation of permanent and cyclical components of default risk. In a time series setting, this can be done through the Kalman filter. The analysis shows that many empirical irregularities of agency ratings could be the consequence of such a rating method. The stability of through-the-cycle ratings is higher than that of their current-condition counterparts, and their correlation with actual default probabilities is relatively low. Though not predictable in the usual sense, rating changes exhibit several properties which call for a reconsideration of the existing evidence.
An AHP-Based Analysis of the Cost of ERP Modification

The modification of ERP systems and adaptation of business processes is widely recognized as complicated and expensive during implementation and post implementation. While there is research focusing on the classification and impact of different ERP modification strategies, research addressing the cost implication of ERP modifications is still lacking. In this paper, we look at existing literature to classify ERP modification strategies, and then we focus on the issue of evaluating the relative cost of different strategies. We gather the opinion of experts in ERP implementations about the relative cost of alternative strategies using an AHP-based online questionnaire. Based on the results of the data collection, we build cost functions to compare the relative cost of alternative strategies. Our approach represents a first step in quantifying the relative cost of different ERP implementation strategies and can be exploited in decision-making problems related to ERP change and evolution.
An algorithm to retrieve Land Surface Temperature using Landsat-8 Dataset

Soil moisture, surface temperature, and vegetation are variables that play an important role in our environment which in turn increases the demand for accurate estimation of certain geophysical parameters such as weather, flooding, and land classification. However, for accurate Land Surface Temperature (LST) estimation, remotely sensed data of key environmental forms were considered and applied in this research. The goal of this study was to apply a suitable algorithm for LST estimation from the Landsat-8 dataset that gives a great accuracy when compared with in-situ observations. Spatial and temporal Landsat-8 data were acquired which provided the analytical structure for linking specific data successfully due to fine resolutions. The data were then applied to determine brightness temperatures, vegetation cover, and surface emissivity which demonstrated the effectiveness of the Split-Window Algorithm as an optimum method for LST retrieval from satellite. The results show temperature variation over a long period of time can be used in observing varying temperature values based on terrain i.e. High temperatures in fully built up areas and low temperatures in the well-vegetated regions. Finally, accurate LST estimation is important for land classification, energy budget estimations as well as agricultural production. Keywords: Emissivity, Landsat, Land Surface Temperature, Split-Window, Vegetation
Mixed symbolic representations for model checking software programs

We present an efficient symbolic search algorithm for software model checking. The algorithm combines multiple symbolic representations to efficiently represent the transition relation and reachable states and uses a combination of decision procedures for Boolean and integer representations. Our main contributions include: (1) mixed symbolic representations to model C programs with rich data types and complex expressions; and (2) new symbolic search strategies and optimization techniques specific to sequential programs that can significantly improve the scalability of model checking algorithms. Our controlled experiments on real-world software programs show that the new symbolic search algorithm can achieve several orders-of-magnitude improvements over existing methods. The proposed techniques are extremely competitive in handling sequential models of non-trivial sizes, and also compare favorably to popular Boolean-level model checking algorithms based on BDDs and SAT
A New Characterization of Probabilities in Bayesian Networks

We characterize probabilities in Bayesian networks in terms of algebraic expressions called quasi-probabilities. These are arrived at by casting Bayesian networks as noisy AND-OR-NOT networks, and viewing the subnetworks that lead to a node as arguments for or against a node. Quasi-probabilities are in a sense the "natural" algebra of Bayesian networks: we can easily compute the marginal quasi-probability of any node recursively, in a compact form; and we can obtain the joint quasi-probability of any set of nodes by multiplying their marginals (using an idempotent product operator). Quasi-probabilities are easily manipulated to improve the efficiency of probabilistic inference. They also turn out to be representable as square-wave pulse trains, and joint and marginal distributions can be computed by multiplication and complementation of pulse trains.
Leukotrienes in patients with clinically active multiple sclerosis

Objectives– The role of leukotrienes (LTs) in the pathophysiology of multiple sclerosis (MS) has been controversially discussed in the past. Studies of LTs in the cerebrospinal fluid (CSF) revealed different results mainly because of analytical difficulties. Material and methods– In the present study we used highly sensitive and specific analytical methods for measuring LTs in the CSF as well as in urine samples from 20 patients with active MS and 20 control patients with noninflammatory neurological disorders. Results– LTB4 concentrations in CSF were almost twice as high in MS patients compared with controls (P < 0.001). CSF concentrations of the cysteinyl‐LTs (LTC4, LTD4 and LTE4) as well as urinary LTE4 showed no significant differences compared with controls (P > 0.05). In addition, there was no significant association between CSF pleocytosis, clinical severity or time of disease onset. Conclusions– The increased concentration of LTB4 in the CSF of MS patients may indicate a biological importance for this mediator in MS.
Ear-phone: an end-to-end participatory urban noise mapping system

A noise map facilitates monitoring of environmental noise pollution in urban areas. It can raise citizen awareness of noise pollution levels, and aid in the development of mitigation strategies to cope with the adverse effects. However, state-of-the-art techniques for rendering noise maps in urban areas are expensive and rarely updated (months or even years), as they rely on population and traffic models rather than on real data. Participatory urban sensing can be leveraged to create an open and inexpensive platform for rendering up-to-date noise maps. In this paper, we present the design, implementation and performance evaluation of an end-to-end participatory urban noise mapping system called Ear-Phone. Ear-Phone, for the first time, leverages Compressive Sensing to address the fundamental problem of recovering the noise map from incomplete and random samples obtained by crowdsourcing data collection. Ear-Phone, implemented on Nokia N95 and HP iPAQ mobile devices, also addresses the challenge of collecting accurate noise pollution readings at a mobile device. Extensive simulations and outdoor experiments demonstrate that Ear-Phone is a feasible platform to assess noise pollution, incurring reasonable system resource consumption at mobile devices and providing high reconstruction accuracy of the noise map.
Improved Outcomes of Cardiopulmonary Resuscitation in Rats Treated With Vagus Nerve Stimulation and Its Potential Mechanism

ABSTRACT Studies have demonstrated that vagus nerve stimulation (VNS) reduces ischemia/reperfusion injury. In this study, we investigated the protective effects of VNS in a rat model of cardiopulmonary resuscitation (CPR). We further investigated whether the beneficial effects of VNS were dependent on the alpha 7 nicotinic acetylcholine receptor (&agr;7nAChR). Forty animals were randomized into four groups and all underwent CPR (n = 10 each): CPR alone (control); VNS during CPR; &agr;7nAChR antagonist methyllycaconitine citrate (MLA) with VNS; &agr;7nAChR agonist 3-(2, 4-dimethoxybenzylidene) anabaseine (GTS-21 dihydrochloride) without VNS. The right vagus nerve was exteriorized in all animals. Ventricular fibrillation was induced and untreated for 8 min. Defibrillation was attempted after 8 min of CPR. VNS was initiated at the beginning of precordial chest compressions and continued for 4 h after return of spontaneous circulation (ROSC) in both the VNS and MLA groups. Hemodynamic measurements and myocardial function, including ejection fraction and myocardial performance index, were assessed at baseline, 1 and 4 h after ROSC. The neurological deficit score was measured at 24-h intervals for a total of 72 h. The heart rate was reduced in the VNS and MLA groups, while no difference was found in mean arterial pressure between the four groups. Better post-resuscitation myocardial and cerebral function and longer duration of survival were observed in the VNS-treated animals. The protective effects of VNS could be abolished by MLA and imitated by GTS-21. In addition, VNS decreased the number of electrical shocks and the duration of CPR required. VNS improves multiple outcomes after CPR.
Fast and Slow Slip Events Emerge Due to Fault Geometrical Complexity

Active faults release elastic strain energy via a whole continuum of modes of slip, ranging from devastating earthquakes to slow slip events (SSEs) and persistent creep. Understanding the mechanisms controlling the occurrence of rapid, dynamic slip radiating seismic waves (i.e., earthquakes) or slow, silent slip (i.e., SSEs) is a fundamental point in the estimation of seismic hazard along subduction zones. Using the numerical implementation of a simple rate‐weakening fault model, we show that the simplest of fault geometrical complexities with uniform rate‐weakening friction properties give rise to both SSEs and fast earthquakes without appealing to complex rheologies or mechanisms. We argue that the spontaneous occurrence, the characteristics and the scaling relationship of SSEs and earthquakes emerge from geometrical complexities. The geometry of active faults should be considered as a complementary mechanism to current numerical models of SSEs and fast earthquakes.
On the Identifiability of the Post-Nonlinear Causal Model

By taking into account the nonlinear effect of the cause, the inner noise effect, and the measurement distortion effect in the observed variables, the post-nonlinear (PNL) causal model has demonstrated its excellent performance in distinguishing the cause from effect. However, its identifiability has not been properly addressed, and how to apply it in the case of more than two variables is also a problem. In this paper, we conduct a systematic investigation on its identifiability in the two-variable case. We show that this model is identifiable in most cases; by enumerating all possible situations in which the model is not identifiable, we provide sufficient conditions for its identifiability. Simulations are given to support the theoretical results. Moreover, in the case of more than two variables, we show that the whole causal structure can be found by applying the PNL causal model to each structure in the Markov equivalent class and testing if the disturbance is independent of the direct causes for each variable. In this way the exhaustive search over all possible causal structures is avoided.
A Flexible and Extensible Contract Aggregation Framework (CAF) for Financial Data Stream Analytics

The paper presents the Contract Aggregation Framework (CAF) for the modeling and analysis of data streams representing arbitrary financial contracts, ranging from privately negotiated deals to exchange-traded securities. We discuss the need for a flexible and extensible data model and provide an exemplar representing trading in corporate equities and bonds. Using a measure of Market volume, we review several analytical methods to explore the data. Initial observations support the benefits of the framework to integrate and analyze disparate sources of data.
Temporal Variation of Bacterial Community Structure in the Sea Surface Microlayer at Nearshore and Offshore Sites in the Northern Yellow Sea

: Sea surface microlayers (SSM) are specific microbial habitats that are critical to global biochemical process. In this study, bacterial populations inhabiting the SSM from two types of coastal sites (nearshore vs. offshore) were investigated by culturing and DNA fingerprinting methods, and were compared with those of subsurface layer (SUB). Bacterial samples from the SSM were collected using a glass plate method during March, August, October and January in the Northern Yellow Sea. The total number of bacterial and culturable bacterial exhibited an obvious spatial distribution, with more abundant in the nearshore sites than the offshore sites, and they showed an obvious enrichment effect in the surface microlayer. DGGE and sequencing revealed a close relationship between the bacterial community in the surface microlayer and subsurface layer, with high similarities between the two dominant bacterial communities, Proteobacteria and Bacteroidetes. The bacterial abundance and diversity in the surface microlayer are obviously superior to those in the subsurface layer. It is more likely for bacterial communities to show significant differences with spatial and temporal changes.
Social Phobia in an Outpatient Alcohol and Drug Treatment Sample

Objective: To examine characteristics of patients with social phobia (SP) in alcohol and drug treatment settings and to identify features distinguishing this group from patients with and without other psychiatric conditions. Method: A random sample of 105 patients completing an initial assessment at two outpatient alcohol and drug treatment services were assessed and agreed to a 9 month follow-up interview, completed by n=102 (97%). At baseline the Composite International Diagnostic Interview (CIDI) was administered. Current diagnoses at baseline were used to separate the sample into those with SP (n=33), other current psychiatric disorders (OPD, n=40), and those with no current psychiatric diagnosis other than a substance use disorder (NPD, n=29). The novel methodology used in this study compared the SP group first to the NPD group to see if SP was associated with a different presentation, and then compared the SP group to the OPD group to see if any identified differences were associated with SP per se or psychopathology generally. The three groups were compared on demographic, current clinical, and past treatment utilization variables at baseline, while follow-up data were used to compare the groups on treatment outcome and treatment utilization. Results: The SP group did not differ from either group in a systematic way. What differences did emerge tended to show a difference between OPD and NPD, with SP intermediate between the two, or that SP and OPD together were different from NPD. Conclusions: Despite the relatively small sample size, these findings suggest that in substance use disorder treatment settings, patients with coexisting SP do not represent a distinctly high-needs or at-risk group in the broader context of patient populations, for which coexisting psychiatric diagnoses are the norm rather than the exception.
A Performance Modeling Scheme for Multistage Switch Networks With Phase-Type and Bursty Traffic

Existing analytical methods to model multistage switch networks cannot be applied to the performance modeling of switch networks with phase-type and bursty traffic because of the problem of state-space explosion and unrealistic assumptions, e.g., uniform traffic and independent destination (UTID). This paper presents an approximate scheme to model and analyze such networks. First, a traffic aggregation technique is proposed to deal with phase-type and bursty traffic, including splitting and merging. For the aggregation of two bursty traffic, a closed-form solution is obtained for buffer state probabilities. For the aggregation of more bursty traffic, a recursive algorithm is derived in terms of the buffer size and number of inputs of a switch. Second, a switch decomposition technique is developed, by which the crossbar of a switch is decomposed from its preceding and succeeding buffers. In this way, a switch network of N inputs and outputs is converted to N tandem queues, for which the performance can be easily evaluated. Our extensive numerical and simulation examples have shown that the proposed scheme achieves satisfied accuracy and computational efficiency.
Watson-Crick automata: determinism and state complexity

Watson-Crick automata are flnite state automata working on double-stranded tapes, introduced to investigate the potential of DNA molecules for computing. In this paper, we continue the investigation of de- scriptional complexity of Watson-Crick automata initiated in (9). In particular, we show that any flnite language as well as any unary regular language can be recognized by a Watson-Crick automaton with only two and respectively three states. Also, we formally deflne the notion of determinism for these systems. Contrary to the case of non-deterministic Watson-Crick automata, we show that for deterministic ones, the complementarity relation plays a major role in the acceptance power of these systems.
Estimating the Effect of Rotor Diameter on the Physical Properties of NACA0015 Airfoil-Based Vertical-Axis Wind Turbine

This study combines aerodynamic and structural analyses on a vertical-axis wind turbine (VAWT) built using NACA0015 airfoil-based blades. Aerodynamic analyses consist of velocity and pressure profiles as well as the drag behaviour. Structural investigations have included stress and displacement of the blade to the airflow pressure. This study has highlighted the effect of the diameter variation on VAWT physical performance. The results have showed a positive effect of the rotor diameter on the laminar flow and Von Karman vortex street. The drag coefficient behaviour was reduced with the diameter increase due to the reduction of the wake within the thin layers of the laminar behind the streamlined airfoils. Also, the structural stress and displacement were negatively affected by the diameter increase.
Direct and Indirect Consequences of Dominant Plants in Arid Environments

In arid environments, dominant woody plants such as shrubs or trees, usually facilitate a high density of species in their understories. This phenomemon is composed by a series of direct and indirect effects from the dominant plant to the understory species, and among understory species. The aim of this project was to determine these direct and indirect consequences of dominant plant-plant facilitation in a collection of field sites along the coastal Atacama Desert. The following objectives and hypotheses were examined in this project: (1) to summarize and contextualize the breadth of research on indirect interactions in terrestrial plant communities; (2) that the positive effects of dominant plants on understory communities are spatiotemporally scale dependent, from microto broad-scale spatial effects, and from within-seasonal to among-year temporal effects; (3) that dominant plants via their different traits determine the outcome of plantplant interactions; (4) that dominant plants determine the outcome of interactions amongst understory species and that their responses are species-specific; and (5) that facilitation by dominant plants generates sufficiently different micro-environmental conditions that lead to consistent differences in seeds traits of understory plants. Overall, we found that multiple factors determine the outcome of plant-plant interactions along the field sites studied in this project. These factors impact both the direct and indirect effects of dominant woody plants on their understory communities and include species-specific traits of both the dominant and understory species, and the spatial and temporal environmental gradients that manifest their effects at different scales. Dominant plants usually facilitate increased species richness and density of plants in