Miracle-dz/UniFAR-FTUs huggingface dataset:
Alternative Markov Properties for Chain Graphs

Graphical Markov models use graphs to represent possible dependences among statistical variables. Lauritzen, Wermuth, and Frydenberg (LWF) introduced a Markov property for chain graphs (CG): graphs that can be used to represent both structural and associative dependences simultaneously and that include both undirected graphs (UG) and acyclic directed graphs (ADG) as special cases. Here an alternative Markov property (AMP) for CGs is introduced and shown to be the Markov property satisfied by a block‐recursive linear system with multivariate normal errors. This model can be decomposed into a collection of conditional normal models, each of which combines the features of multivariate linear regression models and covariance selection models, facilitating the estimation of its parameters. In the general case, necessary and sufficient conditions are given for the equivalence of the LWF and AMP Markov properties of a CG, for the AMP Markov equivalence of two CGs, for the AMP Markov equivalence of a CG to some ADG or decomposable UG, and for other equivalences. For CGs, in some ways the AMP property is a more direct extension of the ADG Markov property than is the LWF property.
Non-linearity effects and predistortion in optical OFDM wireless transmission using LEDs

Orthogonal frequency division multiplexing (OFDM) is a promising technique to realise high-speed indoor optical wireless (OW) links through the exploitation of the high peak-to-average power ratio (PAPR) for intensity modulation (IM). However, the non-linear characteristic of a light emitting diode (LED) imposes limitations on the performance. In this paper, the impact of the non-linear characteristic on bit-error performance is analysed using a commercially available LED (OSRAM, SFH 4230). Also, the paper proposes a predistorter to overcome the non-linearities. The performance without compensation and after compensation is analysed via simulations in an additive white Gaussian noise (AWGN) environment. In this context, the bit-error performance is determined for different bias points and power back-off values applied to the OFDM signal modulating the LED intensity. It is shown that LED non-linearity can significantly degrade the performance. It is also demonstrated that this degradation can greatly be mitigated by using the proposed predistortion technique.
Performance models for desktop grids

Main characteristics of desktop grids are the large number of nodes and their heterogeneity. Application speedup on a large-scale desktop grid is limited by the heterogeneous computational capabilities of each node, which increase the synchronization overhead, and by the large number of nodes, that results in the serial fraction dominating performance. In this paper we present an innovative technique which may outperform the throughput of traditional grid applications by merging job partitioning and job replication. We utilize ordered statistics analytical models for the performance analysis of desktop–based grid applications. The models describe the effects of resource heterogeneity, serial fraction and synchronization overheads on the application– level performance. Using the models we show how the proposed policies can be tuned with respect to the size of the grid in order to optimize the grid throughput.
A Fresh Look at Modeling Distributed Reactive Systems

Scalable, distributed reactive systems require a scalable control infrastructure. Being able to model such an infrastructure is a prerequisite for putting it into place. In current systems, finite state machine based approaches are prevailing. They are, however, limited by their nature and hamper further improvements. Extensions like state charts have emerged to alleviate those shortcomings. Despite all this work, the proposed improvements do not live up to the requirements of continuously operating distributed systems. Therefore we look for alternatives that break with the underlying state-based model. Workflow systems recently became mature enough to be considered for use cases going beyond small-scale business applications. The concept on which they build is promising to scale to large systems. This paper compares various modeling technologies using the real-world scenario of distributed data acquisition systems as we find them in currently operating high-energy physics installations at the Large Hadron Collider at CERN. The outcome of our qualitative evaluation will show that current finite state machine compared to workflow based approaches have a bigger gap between specification and executed processes. Consequently workflow based approaches are better suited for the use case at hand and require less custom software extensions to reduce the remaining gap.
RESUBMITTED TO IEEE SUMMER MEETING-96 ON MAY 30,1996. TOWARD IMPROVED USES OF THE CONJUGATE GRADIENT METHOD FOR POWER SYSTEM APPLICATIONS

The conjugate gradient method has been suggested as a better alternative to direct methods for the solution of certain large sparse linear systems Ax = b, where A is symmetric and positive de nite. E ciency considerations often require that the conjugate gradient method be accelerated by preconditioning (a linear transformation of A). One of the most widely used preconditioners is based on the incomplete LU factors of A. Positive de nite preconditioner matrices assure convergence. However, the incomplete factorization for a symmetric and positive de nite matrix is not necessarily positive de nite. This paper provides signi cant theoretical insights into the conjugate gradient method for matrices arising from several classes of power systems problems. The paper also presents a new preconditioner (based on a one-time complete factorization) that is guaranteed to be positive de nite.
Parallelism in Bubba

Bubba is a parallel computer system for data intensive applications under design at MCC. Bubba is intended as a replacement for mainframe systems providing scalable, continuous, high-performance-per-dollar access to large amounts of shared data for a large number of concurrent application types. To meet these ambitious goals, we adopted a data-driven, message passing army of ants approach. In this talk I provide a brief rationale for this choice. I then discuss some implications. Next I describe a number of the mechanisms used to enable and manage parallelism in Bubba. I conclude with an outline of the research methodology used.
Temperature-Dependent lnduction of Salicylic Acid and Its Conjugates during the Resistance Response to Tobacco Mosaic Virus lnfection

lncreases in endogenous salicylic acid (SA) levels and induction of several families of pathogenesis-related genes (PR-1 through PR-5) occur during the resistance response of tobacco to tobacco mosaic virus infection. We found that at temperatures that prevent the induction of PR genes and resistance, the increases in SA levels were eliminated. The addition of exogenous SA to infected plants at these temperatures was sufficient to induce the PR genes but not the hypersensitive response. However, when the resistance response was restored by shifting infected plants to permissive temperatures, SA levels increased dramatically and preceded PR-1 gene expression and necrotic lesion formation associated with resistance. SA was also found in a conjugated form whose levels increased in parallel with the free SA levels. The majority of the conjugates appeared to be SA glucosides. The same glucoside was formed when plants were supplied with exogenous SA. These results provide further evidence that endogenous SA signals the induction of certain defense responses and suggests additional complexity in the modulation of this signal.
3 D WILDFIRE SIMULATION SYSTEM

The increase in the number of forest fires in the last few years has forced governments to take precautions. Besides prevention, early intervention is also very important in fire fighting. If the fire-fighters know where the fire will be in some time, it would be easier for them to stop the fire. Therefore a big need for simulating the fire behaviour exists. In this paper we are proposing a system which can simulate the propagation of fire in time. Also this system can visualize the propagation of fire in any 3D-GIS environment that accepts KMZ as a file format. Besides, the system supports the visualization of a large number of output data from the simulations, according to the user needs. This facilitates fire planning by fire-fighters. 3D visualization at 3D screens is also supported. Therefore, a better understanding of the terrain can be obtained.
Aliskiren Attenuates Steatohepatitis and Increases Turnover of Hepatic Fat in Mice Fed with a Methionine and Choline Deficient Diet

Background & Aims Activation of the renin-angiotensin-system is known to play a role in nonalcoholic steatohepatitis. Renin knockout mice manifest decreased hepatic steatosis. Aliskiren is the first direct renin inhibitor to be approved for clinical use. Our study aims to evaluate the possible therapeutic effects and mechanism of the chronic administration of aliskiren in a dietary steatohepatitis murine model. Methods Male C57BL/6 mice were fed with a methionine and choline-deficient (MCD) diet to induce steatohepatitis. After 8 weeks of feeding, the injured mice were randomly assigned to receive aliskiren (50 mg·kg-1 per day) or vehicle administration for 4 weeks. Normal controls were also administered aliskiren (50 mg·kg-1 per day) or a vehicle for 4 weeks. Results In the MCD mice, aliskiren attenuated hepatic steatosis, inflammation and fibrosis. Aliskiren did not change expression of lipogenic genes but increase turnover of hepatic fat by up-regulating peroxisome proliferator-activated receptor α, carnitine palmitoyltransferase 1a, cytochrome P450-4A14 and phosphorylated AMP-activated protein kinase. Furthermore, aliskiren decreased the hepatic expression of angiotensin II and nuclear factor κB. The levels of oxidative stress, hepatocyte apoptosis, activation of Kupffer cells and hepatic stellate cells, and pro-fibrotic markers were also reduced in the livers of the MCD mice receiving aliskiren. Conclusions Aliskiren attenuates steatohepatitis and fibrosis in mice fed with a MCD diet. Thus, the noted therapeutic effects might come from not only the reduction of angiotensin II but also the up-regulation of fatty acid oxidation-related genes.
COSMIC Approximate Sizing Using a Fuzzy Logic Approach: A Quantitative Case Study with Industry Data

In software engineering, the standards for functional size measurement require that the functionality to be measured be fully known for accurate measurement results. Therefore, in the early phases of software development, when there is a lack of detail, approximate sizing approaches must be used instead of the standards themselves. Approximate sizing techniques are typically based on the analysis of historical data of the functional size of a number of completed projects within an organization. For organizations without historical data on the functional size of their completed projects, this paper proposes a fuzzy logic model to approximate functional size early in the software development process. It also reports on a quantitative case study of this approximation technique from industry, and compares its performance with the Equal Size Band approximation approach.
Using Galvanic Skin Response (GSR) to Measure Trust and Cognitive Load in the Text-Chat Environment

Exchanging text messages via software on smart phones and computers has recently become one of the most popular ways for people to communicate and accomplish their tasks. However, there are negative aspects to using this kind of software, for example, it has been found that people communicating in the text-chat environment may experience a lack of trust and may face different levels of cognitive load [1, 11]. This study examines a novel way to measure interpersonal trust and cognitive load when they overlap with each other in the text-chat environment. We used Galvanic Skin Response (GSR), a physiological measurement, to collect data from twenty-eight subjects at four gradients and overlapping conditions between trust and cognitive load. The findings show that the GSR signals were significantly affected by both trust and cognitive load and provide promising evidence that GSR can be used as a tool for measuring interpersonal trust when cognitive load is low and also for measuring cognitive load when trust is high.
Efficient quantum algorithm for preparing molecular-system-like states on a quantum computer

We present an efficient quantum algorithm for preparing a pure state on a quantum computer, where the quantum state corresponds to that of a molecular system with a given number $m$ of electrons occupying a given number $n$ of spin orbitals. Each spin orbital is mapped to a qubit: the states $| 1 >$ and $| 0>$ of the qubit represent, respectively, whether the spin orbital is occupied by an electron or not. To prepare a general state in the full Hilbert space of $n$ qubits, which is of dimension $2^{n}$%, $O(2^{n})$ controlled-NOT gates are needed, i.e., the number of gates scales \emph{exponentially} with the number of qubits. We make use of the fact that the state to be prepared lies in a smaller Hilbert space, and we find an algorithm that requires at most $O(2^{m+1} n^{m}/{m! })$ gates, i.e., scales \emph{polynomially} with the number of qubits $n$, provided $n\gg m$. The algorithm is simulated numerically for the cases of the hydrogen molecule and the water molecule. The numerical simulations show that when additional symmetries of the system are considered, the number of gates to prepare the state can be drastically reduced, in the examples considered in this paper, by several orders of magnitude, from the above estimate.
A characterization of broadband user behavior and their e-business activities

This paper presents a characterization of broadband user behavior from an Internet Service Provider standpoint. Users are broken into two major categories: residential and Small-Office/Home-Office (SOHO). For each user category, the characterization is performed along four criteria: (i) session arrival process, (ii) session duration, (iii) number of bytes transferred within a session and (iv) user request patterns.Our results show that both residential and SOHO session inter-arrival times are exponentially distributed. Whereas residential session arrival rates remain relatively high during the day, SOHO session arrival rates vary much more significantly during the day. On the other hand, a typical SOHO user session is longer and transfers a larger volume of data. Furthermore, our analysis uncovers two main groups of session request patterns within each user category. The first group consists of user sessions that use traditional Internet services, such as e-mail, instant messenger and, mostly, www services. On the other hand, sessions from the second group, a smaller group, use typically peer-to-peer file sharing applications, remain active for longer periods and transfer a large amount of data. Looking further into the e-business services most commonly accessed, we found that subscription-based and advertising services account for the vast majority of user HTTP requests in both residential and SOHO workloads. Understanding these user behavior patterns is important to the development of more efficient applications for broadband users.
SNViz : Analysis-oriented Visualization for the Internet of Things

The Internet is evolving from a network of computers to a network of devices, e.g., phones, smart meters, traffic cameras, and air quality sensors. In this Internet of Things, large amounts of data generated by everyday objects can often be organized into data streams, where each data stream is a time series of sensor values sampled together. Visualization is an easy-to-use, efficient, and effective method to present this heterogeneous data to large and diverse audiences, and enable its analysis by users without programming background. Although general data-storage and sharing systems for the Internet of Things, like Pachube and Sensor.Network, offer some basic visualizations, they do little to help users understand relations and patterns hidden in the data, nor do they support live updates to the underlying data streams. Other systems, like Biketastic and the Copenhagen Wheel, feature more complex visualizations but are tailored for a specific application domain and do not address heterogeneous data streams. In this paper, we present SNViz, a Web browser-based AJAX application built using Protovis for visual analysis of large, heterogeneous, and live data streams in the Internet of Things. Besides offering panning and zooming for a detailed look at smaller data subsets, SNViz offers brush-andlinking across multiple visualizations. The latter is invaluable in helping users understand and analyze relationships and patterns hidden in the data. Although SNViz currently works by accessing JSON representations of data streams from Sensor.Network over HTTP, it can be extended to work with other data sources (e.g., wireless sensor network devices or smartphones) and even customized for specific applications.
Character Strengths of Airline Pilots: Explaining Life and Job Satisfaction and Predicting CRM Performance

The associations of character strengths with job satisfaction and work performance have recently been studied. However, the questions whether different professions are characterized by different strengths, and whether different strengths explain desired outcomes in different professions remain unresolved. The present study sought to identify the character strengths most highly endorsed by airline pilots and most highly used in a typical pilot’s workday. The study also aimed to determine which strengths are most highly associated with pilots’ life and job satisfaction, and most predictive of specific work performance. Israeli airline pilots (N = 177) completed measures of strengths endorsement, strengths use, life satisfaction, and job satisfaction. Participants’ crew resource management (CRM) behaviors were assessed to reflect actual job performance. Findings pointed to various character strength profiles related to the examined personal and work aspects. These findings highlight the contribution of specific strengths to satisfaction and performance of airline pilots. Implications regarding the potential interaction between organization culture and personal strengths are addressed.
The effect of changes in natural and anthropogenic deposition on modelling recovery from acidification.

Abstract. The multi-layer dynamic soil chemistry SAFE model was used to study the dynamics of recovery in the F1 catchment at Lake Gardsjon, Sweden. The influence of (1) sulphate adsorption, and (2) changes in marine deposition, on model predictions of recovery was studied. Sulphate adsorption/desorption in SAFE is modeled by an isotherm in which sulphate adsorption is dependent on both the sulphate concentration and the pH in the soil solution. This isotherm was parameterised for the B-horizon of F1 for the sulphate concentration range 10–260 m mol-1 and the pH range 3.8–5.0. Sulphate adsorption/desorption as the only soil process involving sulphate is adequate to predict sulphate in run-off at F1. Adding the process caused time-delays in sulphate concentration in run-off of only 1-2 years, which was much shorter than previously seen in the adjacent G1 catchment. The location of Lake Gardsjon, approximately 15 km inland from the Swedish west coast, ensures that the marine deposition to the area is high. Model output showed that the temporal variation in marine deposition has a considerable impact on the run-off chemistry. Such changes in marine deposition are difficult to foresee and their influence on modelled run-off chemistry can be large when soils start to recover as the previously high concentrations of anthropogenic sulphate in the soil solution decrease. Keywords: climate change, dynamic modelling, run-off chemistry, sea-salt effect, soil and water acidification, sulphate adsorption
Collaborating in Social Networks : The Problem Solving Activity Leading to Interaction-‘ Struggle ’ Analysis Framework ( SAF )

This paper examines the effect of problem solving activity during computersupported collaborative problem solving in digital social networks and introduces the ‘Struggle Analysis Framework (SAF)’, for analyzing interactions in these networks; interactions will be called ‘struggle’. A study of collaborative modeling has been contacted in the frame of an authentic educational activity among students in a secondary school and in a university, using Facebook social network. The students involved were separated into two groups. Students peer interaction analysis revealed that, according to our expectations, the group provided with an activity appeared to have much more struggle than the group that had nothing special to do. They were more active, they exchanged more messages and documents, they were involved in deeper discussions, they achieved mentor/tutor roles and they collaborated more. The reported findings as well as the SAF model, can have implications to various settings of collaboration in social networks.
Towards Robust Overlay Networks : Enhancing Adaptivity Mechanisms with Byzantine-Resilience

Adaptive measurement-based overlay networks offer increased performance and resilience to benign failures for end-to-end communication by using aggressive adaptivity mechanisms. These mechanisms dynamically optimize applicationcentric metrics such as latency, jitter, bandwidth, and loss rate. However, end-systems are more vulnerable than core routers, making overlay networks susceptible to malicious attacks coming from untrusted outsiders, and especially from trusted (but compromised) members of the overlay. Unlike outsider attacks, insider (or Byzantine) attacks can not be prevented by simply deploying cryptographic authentication mechanisms. In this work, we identify and classify insider attacks against adaptivity mechanisms in overlay networks and demonstrate several of them against the ESM/Narada multicast overlay system. The attacks target the overlay network construction, maintenance, and availability and allow malicious nodes to control significant traffic in the network, facilitating further attacks such as selective forwarding and traffic analysis. We believe this work is the first to classify insider attacks against adaptivity mechanisms in distributed systems and the first to propose techniques to enhance the adaptivity mechanisms with Byzantine-resilience. We demonstrate the effectiveness of the newly proposed techniques through real-life deployments and emulations conducted on the PlanetLab and DETER testbeds, respectively.