Miracle-dz/UniFAR-FTUs huggingface dataset:
Glagov Remodeling of Atherosclerotic Arteries

When blood vessels undergo remodeling because of the buildup of atherosclerotic plaque, it is thought that they first undergo compensatory or outward remodeling, followed by inward remodeling: the lumen area stays roughly constant or increases slightly and then decreases rapidly. The second phase of remodeling is supposed to start after the plaque burden exceeds about 40%. These changes in the vessel were first observed by S. Glagov who examined cross-sections of coronary arteries with different disease burdens. In this paper, we use a mathematical model based on growth and elasticity theory to verify the main aspects of Glagov’s result. However, both our model and curve-fitting to the data suggest that the critical stenosis is around 20% rather than 40%. Our model and data from the PROSPECT trial also show that Glagov remodeling can be qualitatively different depending on whether measurements are taken ex-vivo or in-vivo . Our results suggest that care must be taken when infering how in-vivo vessels remodel from ex-vivo data.
Complexity of Inference in Latent Dirichlet Allocation

We consider the computational complexity of probabilistic inference in Latent Dirichlet Allocation (LDA). First, we study the problem of finding the maximum a posteriori (MAP) assignment of topics to words, where the document's topic distribution is integrated out. We show that, when the effective number of topics per document is small, exact inference takes polynomial time. In contrast, we show that, when a document has a large number of topics, finding the MAP assignment of topics to words in LDA is NP-hard. Next, we consider the problem of finding the MAP topic distribution for a document, where the topic-word assignments are integrated out. We show that this problem is also NP-hard. Finally, we briefly discuss the problem of sampling from the posterior, showing that this is NP-hard in one restricted setting, but leaving open the general question.
Externalizing Metaphors Therapy: Outcomes Related to a Three-Session Treatment Model for Anxiety and Depression

Although effective treatments exist for transitional-aged youth presenting with dysphoria, treatment protocols often take much longer than the typical psychotherapy that clients receive. The authors proposed a three-session treatment protocol with an emphasis on the process of externalizing and shifting problem-focused identities using concrete metaphors. Trained clinicians from four post-secondary student counseling centers in Ontario, Canada, implemented externalizing metaphors therapy (EMT) to 50 participants who presented with anxiety and/or depression. Participating clients completed two self-report measures of dysphoria (DASS-21, STAI) before beginning and at the end of treatment. The results were then compared to a small sample of participants who engaged in treatment as usual (TAU). Differences on the DASS-21 between baseline and post-intervention revealed significant reductions in self-reported stress, depression, and anxiety. Additionally, data showed a significant and large reduction in trait a.
STABILITY SWITCHES AND REVERSALS OF LINEAR SYSTEMS WITH COMMENSURATE DELAYS: A MATRIX PENCIL CHARACTERIZATION

Abstract This paper addresses the problem of asymptotic stability of linear time-delay systems including commensurate delays. More precisely we focus on the characterization of stability switches and reversals using a matrix pencil approach. The proposed approach makes use of the generalized eigenvalue distribution with respect to the unit circle of some appropriate finite-dimensional matrix pencils. Classical problems, as for example, hyperbolicity and delay-independent/delay-dependent stability characterizations are reconsidered, and simple computational conditions are derived.
Global Self-Organization of the Cellular Metabolic Structure

Background Over many years, it has been assumed that enzymes work either in an isolated way, or organized in small catalytic groups. Several studies performed using “metabolic networks models” are helping to understand the degree of functional complexity that characterizes enzymatic dynamic systems. In a previous work, we used “dissipative metabolic networks” (DMNs) to show that enzymes can present a self-organized global functional structure, in which several sets of enzymes are always in an active state, whereas the rest of molecular catalytic sets exhibit dynamics of on-off changing states. We suggested that this kind of global metabolic dynamics might be a genuine and universal functional configuration of the cellular metabolic structure, common to all living cells. Later, a different group has shown experimentally that this kind of functional structure does, indeed, exist in several microorganisms. Methodology/Principal Findings Here we have analyzed around 2.500. 000 different DMNs in order to investigate the underlying mechanism of this dynamic global configuration. The numerical analyses that we have performed show that this global configuration is an emergent property inherent to the cellular metabolic dynamics. Concretely, we have found that the existence of a high number of enzymatic subsystems belonging to the DMNs is the fundamental element for the spontaneous emergence of a functional reactive structure characterized by a metabolic core formed by several sets of enzymes always in an active state. Conclusions/Significance This self-organized dynamic structure seems to be an intrinsic characteristic of metabolism, common to all living cellular organisms. To better understand cellular functionality, it will be crucial to structurally characterize these enzymatic self-organized global structures.
Anytime Synthetic Projection: Maximizing the Probability of Goal Satisfaction

This paper presents a projection algorithm for incremental control rule synthesis. The algorithm synthesizes an initial set of goal-achieving control rules using a combination of situation probability and estimated remaining work as a search heuristic. This set of control rules has a certain probability of satisfying the given goal. The probability is incrementally increased by synthesizing additional control rules to handle "error" situations the execution system is likely to encounter when following the initial control rules. By using situation probabilities the algorithm achieves a computationally effective balance between the limited robustness of triangle tables and the absolute robustness of universal plans.
Simulating DYMO in OMNeT++

Mobile Ad Hoc Networks (MANETs) have evolved in the last years into standards in the communication world. By deﬁnition, they do not need any network infrastructure to ensure communication between the nodes. Therefore, they are dealing with new challenges in the context of ad hoc routing. This paper deals with our new implementation of the routing protocol Dynamic MANET On Demand (DYMO). DYMO oﬀers adaptation to changing network topology and determines unicast routes between nodes within the network on demand. We developed a simulation model of DYMO for the network simulation environment OMNeT++. Based on the developed model, we performed several simulation experiments to analyze its performance. The implementation of DYMO and the results of the simulation experiments are described in this report.
Understanding the Role of Creative Self-Efficacy and Power Distance Orientation for Examining the Consequences of Abusive Supervision on Employee Creativity: A Case Study from Nepal

The present study investigates the effect of abusive supervision on employee creativity. For this, a psychological cognitive factor such as creative self-efficacy and cultural value namely power distance orientation have been examined based on social cognitive theory. Results are gathered from a survey of 325 full-time employees from 17 companies covering six industries in the central and eastern development regions of Nepal. The results indicate that abusive supervision is negatively related to employee creativity and this relationship is fully mediated by creative self-efficacy. In addition, it is evident from our results that employees’ power distance orientation plays a moderating role. The direct effect of abusive supervision on creative self-efficacy and the mediating effect of creative self-efficacy are weaker when the power distance orientation is high rather than low. The implications of our study for both theory and practical are discussed.
An integrated color and hand gesture recognition approach for an autonomous mobile robot

The purpose of this paper is to develop a real-time human-robot interaction with hand gesture recognition which can be constructed combining color and shape cues. There are two major problems that need to be resolved in this study. Firstly, due to variation in the apparent color of targets under varying imaging conditions, we propose a color multithresholding method with thresholds self-tuning mechanism to overcome the variation of target color suitable for indoor and outdoor environments. Secondly, the feature of the hand gesture is determined through the boundary extraction algorithm and the Fourier descriptors without having the results being affected by the rotation or size of hand gestures. Subsequently, outline feature for the nonlinear non-separable type of data was classified by using the support vector machines. In this paper, the accuracy of hand gesture recognition for the robot vision system has been enhanced by processing of these two methods as described above, and the human-robot interaction control of the robot has been successfully implemented under varying lighting conditions.
Visual Odometry for Corobots

—Odometry plays a very important role in robotics for localization, mapping, navigation, SLAM. Traditional odometry approaches use encoders to measure distance traveled, stepper motors for precise movements by distance o visual odometry. Rochester Institute of Technology started corobtics project to inspire and aid students in learning computing fundamentals and robotics applications. Corobots uses encoders for odometry which face precision problems, since wheels slips and slides. Visual odometry is widely used technique in robotics to overcome this issue. Corobots have Kinect sensor which produces RGB image and depth data, which is used for visual odometry in this project.
Robust Adaptive SDRE Filter and Its Application to SINS/SAR Integration

This paper presents a new robust adaptive filter based on the state dependent Riccati equation (SDRE) technique for SINS/SAR (strap-down inertial navigation system/synthetic aperture radar) integrated navigation. This method adopts the state dependent coefficient (SDC) form to convert nonlinear system model into linear system for avoiding the errors caused by the traditional numerical linearization process. It also adopts the concepts of robust estimation and adaptive factor to construct reasonably the discriminant statistics and adaptive factor for resisting the disturbances of singular observations and kinematic model error. Experiment results and comparison analysis demonstrate that the proposed filtering method can not only effectively resist disturbances from nonlinear system state noise and observation noise, but it also can achieve higher accuracy than the extended Kalman filter and SDRE filter.
Dynamics of the solar tachocline. I. An incompressible study

Gough & McIntyre have suggested that the dynamics of the solar tachocline are dominated by the advection-diffusion balance between the differential rotation, a large-scale primordial field and baroclinicly driven meridional motions. This paper presents the first part of a study of the tachocline, in which a model of the rotation profile below the convection zone is constructed along the lines suggested by Gough & McIntyre and solved numerically. In this first part, a reduced model of the tachocline is derived in which the effects of compressibility and energy transport on the system are neglected; the meridional motions are driven instead by Ekman-Hartmann pumping. Through this simplification, the interaction of the fluid flow and the magnetic field can be isolated and is studied through non-linear numerical analysis for various field strengths and diffusivities. It is shown that there exists only a narrow range of magnetic field strengths for which the system can achieve a nearly uniform rotation. The results are discussed with respect to observations and to the limitations of this initial approach. A following paper combines the effects of realistic baroclinic driving and stratification with a model that closely follows the lines of work of Gough & McIntyre.
Personalization using Support Vector Machines

We describe a system for recommending news articles, called NewsPer, which learns news-reading preferences of its users and suggests recently published articles that may be of interest to specific readers based on their interest profiles. The underlying algorithm is based on representing articles by bags of words and named entities, and applying support vector machines to this representation. We present this algorithm and give initial empirical results. We also discuss broader issues in the news personalization and the challenges of performance evaluation based on historical data.
Classification of Vintages of Wine by an Artificial Nose with Neural Networks

Artificial neural networks have been used to analyze odour patterns and are showing promising results. In this paper, a pattern recognition system of an artificial nose with neural networks which implement temporal processing is presented. The results were compared to those obtained by a Multi-Layer Perceptron (MLP) neural network. The signals generated by an array of six conducting polymer sensors exposed to the odours of three different vintages of the same wine were analyzed. Experimental details of the training method are shown, as well as the results obtained for different numbers of hidden units in one-hidden-layer
Strings in gravimagnetic fields

We provide a complete solution of closed strings propagating in Nappi-Witten space. Based on the analysis of geodesics we construct the coherent wavefunctions which approximate as closely as possible the classical trajectories. We then present a new free field realization of the current algebra using the gamma, beta ghost system. Finally we construct the quantum vertex operators, for the tachyon, by representing the wavefunctions in terms of the free fields. This allows us to compute the three- and four-point amplitudes, and propose the general result for N-point tachyon scattering amplitude.
NORA: Network Oriented Resource Allocation for Data Intensive Applications in the Cloud Environment

Optimization of data intensive applications is affected greatly by the nature of the platform, the distributed file system, the co-location of data and programs, and the proximity of resources. Data intensive applications running on a public cloud have been shown to exhibit degraded performance compared to a private cluster. This performance degradation is as a result of the inefficient resource allocation adopted in a virtualized, volatile and multi-tenancy environment such as a cloud. The placement of virtual machines is critical for improving performance in geo-clouds environment. We address degradation in performance by designing a scheduling algorithm that dynamically distributes virtual machines based on the characteristics of the job, the network characteristics and the real time performance of the data centers. Our algorithm also finds the best node(s) to host virtual machines that will yield maximum resource utilization and minimize bandwidth consumption. Our results show that incorporating these characteristics in a resource scheduling algorithm increases the performance of data intensive application than known traditional scheduling.
Interactive BRDF Estimation for Mixed-Reality Applications

Recent methods in augmented reality allow simulating mutual light interactions between real and virtual objects. These methods are able to embed virtual objects in a more sophisticated way than previous methods. However, their main drawback is that they need a virtual representation of the real scene to be augmented in the form of geometry and material properties. In the past, this representation had to be modeled in advance, which is very time consuming and only allows for static scenes. We propose a method that reconstructs the surrounding environment and estimates its Bidirectional Reflectance Distribution Function (BRDF) properties at runtime without any preprocessing. By using the Microsoft Kinect sensor and an optimized hybrid CPU & GPU-based BRDF estimation method, we are able to achieve interactive frame rates. The proposed method was integrated into a differential instant radiosity rendering system to demonstrate its feasibility.
Learning to grasp unknown objects based on 3D edge information

In this work we refine an initial grasping behavior based on 3D edge information by learning. Based on a set of autonomously generated evaluated grasps and relations between the semi-global 3D edges, a prediction function is learned that computes a likelihood for the success of a grasp using either an offline or an online learning scheme. Both methods are implemented using a hybrid artificial neural network containing standard nodes with a sigmoid activation function and nodes with a radial basis function. We show that a significant performance improvement can be achieved.
Working Paper Series Global Social Interactions with Sequential Binary Decisions: the Case of Marriage, Divorce, and Stigma Global Social Interactions with Sequential Binary Decisions: the Case of Marriage, Divorce, and Stigma *

This paper studies global social interactions in a stylized model of marriage and divorce with complementarities across agents. The key point of departure from traditional models of social interactions is that actions are interrelated and sequential. We establish existence and uniqueness results akin to those in traditional models. In contrast to these models, however, we show that the presence of strategic complementarities is no longer sufficient to generate a social multiplier that exceeds one in this environment. Self-fulfilling conformity, whereby a greater desire to conform at the individual level leads to greater homogeneity of choices in the aggregate, is not retained either. Some empirical implications are also discussed. uniqueness under moderate social influence * We thank Larry Blume, David Easley, and Ted O'Donoghue for helpful comments on early versions of this paper. We have also received helpful comments and suggestions from Tom Light, seminar participants at Cornell and Towson University, and participants at the Latin American Meeting of the Econometric Society. Any remaining errors are ours.
CDN: Content Distribution Network

Internet evolves and operates largely without a central coordination, the lack of which was and is critically important to the rapid growth and evolution of Internet. However, the lack of management in turn makes it very difficult to guarantee proper performance and to deal systematically with performance problems. Meanwhile, the available network bandwidth and server capacity continue to be overwhelmed by the skyrocketing Internet utilization and the accelerating growth of bandwidth intensive content. As a result, Internet service quality perceived by customers is largely unpredictable and unsatisfactory. Content Distribution Network (CDN) is an effective approach to improve Internet service quality. CDN replicates the content from the place of origin to the replica servers scattered over the Internet and serves a request from a replica server close to where the request originates. In this paper, we first give an overview about CDN. We then present the critical issues involved in designing and implementing an effective CDN and survey the approaches proposed in literature to address these problems. An example of CDN is described to show how a real commercial CDN operates. After this, we present a scheme that provides fast service location for peer-to-peer systems, a special type of CDN with no infrastructure support. We conclude with a brief projection about CDN.
Particle swarm optimization of neural controller for tanker ship steering

This paper discussed the implementation of Particle Swarm Optimization (PSO) to optimize a Radial Basis Function (RBF) neural controller for tanker ship control. The RBF neural controller uses reinforcement learning strategy to achieve the heading regulation of tanker ship exposed to plant changes and disturbances. However, the tuning of the neural controller design parameters are considered to be difficult and tedious due to the high nonlinearity of the ship dynamic model and the external disturbances. It is shown that PSO can provide a very promising technique for its simplicity and ease of use. Moreover, Centroidal Voronoi Tessellation (CVT) is implemented to select the starting positions of the particles strategically. The promising results from the experiment provide direct evidence for the feasibility and effectiveness of PSO for the optimization of neural controller for tanker ship heading regulation.
Evaluation of Orthodontic Treatment Needs Using the Dental Aesthetic Index in Iranian Students

Background In the contemporary orthodontics, the number of people who demand orthodontic treatment to improve their psychosocial issues related to facial esthetic is constantly increasing. Even in treatment plans, appearance and esthetic gain more attention. Objectives The purpose of this study was to determine the need for orthodontic treatment on the basis of the dental aesthetic index (DAI) in the Iranian students of Ahvaz city. Material and Methods This cross sectional study was performed on 900 students aged between 11 - 14 years (450 boys, 450 girls). Schools were selected based on random cluster sampling from different parts of the city. Students\ who had or were having orthodontic treatment including those on interceptive orthodontics, were excluded from the study. Two questionnaires were used; the first one included different DAI criteria, and the second one included two questions about orthodontic treatment need and satisfaction of personal dental appearance. The results were analyzed by Chi-Square and T test. Results In 70.9% of the students, DAI score was 13 - 25, 19.2% of the samples had a DAI score of 26 - 30, the DAI score of 7.8% was 31 - 35, and in 2.1% the DAI score was greater than 35. The association between the DAI score and sex was not statistically significant (P = 0.778). In relation to orthodontic treatment need, 44.8% of students answered positively, while in 55.2% the answer was negative. In relation to satisfaction with appearance, 21% of the students were satisfied with their appearance, 59% were relatively satisfied, and 19.9% were not satisfied with their appearance. The association between DAI score and the need for orthodontic treatment and satisfaction of dental appearance was significant (P = 0.000). Conclusion In comparison to other studies, the students in Iran (Ahvaz) have a better dental appearance and less need for orthodontic treatment. Significantly positive correlations were found between the DAI and satisfaction of dental appearance, orthodontic treatment need and student’s perception.