Miracle-dz/UniFAR-FTUs huggingface dataset:
Text for " Realistic Impulsive Noise Model "

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Outcome of kidneys in patients treated for vesicoureteral reflux (VUR) during childhood.

BACKGROUND Outcome of renal function and blood pressure (BP) at early middle age was clarified in patients treated for vesicoureteral reflux (VUR) during childhood. METHODS Information of renal function was available from 147 (55%) of 267 patients treated for non-obstructive VUR of any grade. Twelve patients had died of kidney-related conditions and eight had gone into terminal uraemia. A total of 127 patients participated in the study. RESULTS The mean age of the participants was 41 years. No signs of renal scars were detected by ultrasound examination in 53 (42%) subjects. Unilateral scarring was seen in 44 (35%) and bilateral in 30 (24%) subjects. Glomerular filtration rate (GFR) showed moderate or severe renal insufficiency in four (3%) participants, all with bilateral scars. Normal GFR was found in one-third of the patients. Twenty-five (83%) subjects with bilateral scars and 60 (62%) of the other participants had abnormal GFR values (P < 0.05). Proteinuria was found in 12 (9%) and albuminuria in 30 (24%) participants. Hypertension was diagnosed earlier in 14 (11%) patients, eight having bilateral scarring (P < 0.01). Diastolic BP was significantly lower in subjects without scars compared with those having scars in one or both kidneys (P < 0.05). CONCLUSIONS Renal function was slightly lowered in more than half of the participants. Findings of the participants with unilateral scarring or unscarred kidneys were similar, except for the increased tendency for hypertension in subjects with scars. A total of 83% of the patients with bilateral kidney scars had lowered kidney function, a quarter presented with proteinuria and a half with hypertension. Long-term follow-up for all the patients with earlier VUR is emphasized.
Ministers and Parliament: Accountability in Theory and Practice

I: THE CONVENTION OF INDIVIDUAL MINISTERIAL RESPONSIBILITY II: RESIGNATIONS AND NON-RESIGNATIONS: THE OPERATION OF INDIVIDUAL MINISTERIAL RESPONSIBILITY IN THE 1980S AND 1990S III: CHANGES AFFECTING THE OPERATION OF INDIVIDUAL MINISTERIAL RESPONSIBILITY
Linguistic Modifiers to Improve the Accuracy-Interpretability Trade-Off in Multi-Objective Genetic Design of Fuzzy Rule Based Classifier Systems

In the last few years a number of studies have focused on the design of fuzzy rule-based systems which are interpretable (i.e. simple and easy to read), while maintaining quite a high level of accuracy. Therefore, a new tendency in the fuzzy modeling that looks for a good balance between interpretability and accuracy is increasing in importance. In fact, recently multi-objective evolutionary algorithms have been applied to improve the difficult trade-off between interpretability and accuracy. In this paper, we focus both on rule learning and fuzzy memberships tuning proposing a technique based on a multi-objective genetic algorithm (MOGA) to design deep-tuned Fuzzy Rule Based Classifier Systems (FRBCSs) from examples. Our technique generates a FRBCS which includes certain operators (known as linguistic hedges or modifiers) able to improve accuracy without losses in interpretability. In our proposal the MOGA is used to learn the FRBCS and to set the operators in order to optimize both model accuracy and metrics of interpretability, compactness and transparency in a single algorithm. The resulting Multi-Objective Genetic Fuzzy System (MOGFS) is evaluated through comparative examples based on well-known data sets in the pattern classification field.
ully coupled methods for multiphase morphodynamics

We present numerical methods for a system of equations consisting of the two dimensional Saint– Venant shallow water equations (SWEs) fully coupled to a completely generalized Exner formulation of hydrodynamically driven sediment discharge. This formulation is implemented by way of a discontinuous Galerkin (DG) finite element method, using a Roe Flux for the advective components and the unified form for the dissipative components. We implement a number of Runge–Kutta time integrators, including a family of strong stability preserving (SSP) schemes, and Runge–Kutta Chebyshev (RKC) methods. A brief discussion is provided regarding implementational details for generalizable computer algebra tokenization using arbitrary algebraic fluxes. We then run numerical experiments to show standard convergence rates, and discuss important mathematical and numerical nuances that arise due to prominent features in the coupled system, such as the emergence of nondifferentiable and sharp zero crossing functions, radii of convergence in manufactured solutions, and nonconservative product (NCP) formalisms. Finally we present a challenging application model concerning hydrothermal venting across metalliferous muds in the presence of chemical reactions occurring in low pH environments.
Realizing Simple Petri Net Models for Complex and Large Scheduling Problems: An Approach Based Activity-Oriented Petri Nets

This work presents a new Petri nets based approach for modeling discrete event systems in which activities compete for common resources. The new approach is known as Activity-Oriented Petri Net (AOPN). AOPN allows modelers to concentrate on modeling activities, and the resources are left to be managed by the underlying system; this approach allows compact and much simpler models even for large and complex systems that involve many resources. General Purpose Petri Net Simulator (GPenSIM) is a toolbox of functions realizing AOPN approach on MATLAB platform. In this paper, an application example is also presented to demonstrate how efficiently a resource scheduling problem can be modeled and simulated with AOPN approach.
Phrase Search over Encrypted Data with Symmetric Encryption Scheme

We study the case of searching over encrypted data from a remote server. In order to retrieve the encrypted documents that satisfy a client's criteria, a special index must be built and sent by the client together with encrypted documents. A trapdoor will also be produced to offer the privilege to search on the index. In the area of searchable encryption, many works mainly focused on search criteria consisting of a single keyword or conjunctive keywords. Up until now, searching of the exact documents that contain a phrase, or consecutive keywords still remains an unsolved problem. We first define the model of phrase search over encrypted data with symmetric encryption and its security definition based on the latest security definition raised by R. Curtmola. Then we propose a construction for phrase search with symmetric encryption (PSSE), which meets the functionality of searching a phrase over encrypted documents securely and efficiently. The computing complexity of our scheme when performing a query is linear in the size of the phrase, and at a moderate communication cost between server and client as well. In addition, we prove that our scheme achieves non-adaptive security.
Evaluating Feature Selection Techniques in Simulated Soccer Multi Agents System

Since the quality of data affects the success rate ofdata mining and learning algorithms, it is always attempted to identify and remove the irrelevant and redundant information in a dataset. Robotic soccer is a multi-agent system in which agents play in real-time, dynamic, complex and noisy environment. Many parameters affect the result of shooting toward the goal and agents must response to variations in soccer field rapidly. Therefore it is impossible to use all features in scoring behavior. This paper selects dataset for effective features of scoring behavior simulated soccer agents, then compares the size of the trees and accuracy produced by each feature selection scheme against the size of the trees and accuracy produced by C4.5 with no feature selection method. Experimental results have shown that dimensionality reductions lead to operate faster and more effective learning algorithm in real-time simulated soccer agent.
Expressing and Validating OCL Constraints using Graphs

The definition of the semantics of visual languages, in particular Unified Modeling Language (UML) diagrams, using graph formalism has known a wide success, since graphs fit the multi-dimensional nature of this kind of language. However, constraints written in Object Constraint Language (OCL) and defined on these models are still not well integrated within this graph-based semantics. In this chapter, the authors propose an integrated semantics of OCL constraints within class diagrams, using graph transformation systems. Their contribution is divided into two parts. In the first part, they introduce graph constraint patterns, as the translation into graphs of a subset of OCL expressions. These patterns are validated with experimental examples using the GROOVE toolset. In the second part, the authors define the relation between OCL and UML models within their graph transformation system.
Previously Published Works Uc Irvine Regulation of ␣7 Nicotinic Acetylcholine Receptors in Mouse Somatosensory Cortex following Whisker Removal at Birth

A University of California author or department has made this article openly available. Thanks to the Academic Senate's Open Access Policy, a great many UC-authored scholarly publications will now be freely available on this site. Let us know how this access is important for you. We want to hear your story! Title: Regulation of alpha7 nicotinic acetylcholine receptors in mouse somatosensory cortex following whisker removal at birth. Local Identifier: 9671275 eScholarship provides open access, scholarly publishing services to the University of California and delivers a dynamic research platform to scholars worldwide. Abstract: Previous studies in postnatal mouse demonstrating high levels of alpha7 nicotinic acetylcholine receptors on layer IV somatosensory cortical neurons coincident with the onset of functional synaptic transmission led us to investigate whether the number and/or the localization of these receptors could be regulated by activity. Accordingly, we examined alpha-bungarotoxin binding in mouse somatosensory cortex following removal of all of the vibrissae on one side of the face, either by vibrissal follicle cauterization or daily plucking beginning on the day of birth. Following vibrissa plucking, the levels of [125I]alpha-bungarotoxin binding on postnatal day 6 were significantly higher (23 +/-7%) in the denervated cortex (contralateral to the peripheral manipulation) than the intact cortex. Cauterization also resulted in significantly higher (14 +/-3%) [125I]alpha-bungarotoxin binding in the contralateral vs. the ipsilateral cortex. In contrast, there was no difference in [125I]alpha-bungarotoxin binding in the left and right cortices of unoperated control animals. At postnatal day 14, levels of [125I]alpha-bungarotoxin binding in layer IV were very low in control animals as well as in animals subjected to whisker plucking or cautery. These findings suggest that reducing activity in the somatosensory pathway regulates the density of alpha7 nicotinic acetylcholine receptors during the first postnatal week. However, the normal decrease in receptor density that is seen during the second postnatal week of development proceeds despite altered sensory activity. ABSTRACT Previous studies in postnatal mouse demonstrating high levels of ␣7 nicotinic acetylcho-line receptors on layer IV somatosensory cortical neurons coincident with the onset of functional synaptic transmission led us to investigate whether the number and/or the localization of these receptors could be regulated by activity. Accordingly, we examined ␣-bungarotoxin binding in mouse somatosensory cortex following removal of all of the vibrissae on one side of the face, either by vibrissal follicle cauterization or daily plucking beginning on the day of birth. Following vibrissa plucking, the levels of …
Feature Selection Using Euclidean Distance and Cosine Similarity for Intrusion Detection Model

Nowadays, data mining plays an important role in many sciences, including intrusion detection system (IDS). However, one of the essential steps of data mining is feature selection, because feature selection can help improve the efficiency of prediction rate. The previous researches, selecting features in the raw data, are difficult to implement. This paper proposes feature selection based on Euclidean Distance and Cosine Similarity which ease to implement. The experiment results show that the proposed approach can select a robust feature subset to build models for detecting known and unknown attack patterns of computer network connections. This proposed approach can improve the performance of a true positive intrusion detection rate.
Voices from the coast : drawing on family funds of knowledge to build ocean literacy and home school partnerships

approved: ____________________________________________________ Kathryn M. Ciechanowski In this qualitative study, ethnographic methods were used to identify parent funds of knowledge related to ocean literacy in a rural, coastal context. Participants included 16 parents of students in the teacher-researcher’s third-grade classroom. Interactions between parent-child, parent-parent, and parent and the teacher-researcher were studied in order to determine factors that influence home-school partnership. Data collection occurred through (1) artifacts resulting from parent-child activities during three Ocean Literacy Family Nights, (2) parent study groups, and (3) in-depth interviews with six focal parents. Grounded theory methods were used to code and analyze the data. Study findings suggest that a funds of knowledge approach to building ocean literacy is an effective means of building home-school partnership as well as a sense of community among parents of diverse backgrounds. This is supported by parent response to (1) the process of accessing parent funds of knowledge related to ocean literacy, (2) their shared experience in a different kind of family night, and (3) exploration of the interactions that occurred through study activities. Implications for future research using a funds of knowledge approach and for humanizing home-school partnership are presented. ©Copyright by Susan Merwin Roebber September 5, 2013 All Rights Reserved Voices from the Coast: Drawing on Family Funds of Knowledge to Build Ocean Literacy and Home School Partnerships by Susan Merwin Roebber
A Hybrid Differential Dynamic Programming Algorithm for Robust Low-Thrust Optimization

Low-thrust propulsion is becoming increasingly considered for future space missions, but optimization of the resulting trajectories is very challenging. To solve such complex problems, differential dynamic programming is a proven technique based on Bellman’s Principle of Optimality and successive minimization of quadratic approximations. In this paper, we build upon previous and existing optimization strategies to present an alternative hybrid variant of differential dynamic programming for robust low-thrust optimization. It uses first- and second-order state transition matrices to take advantage of an efficient discretization scheme and obtain the partial derivatives needed to perform the minimization. Unlike the traditional formulation, the state transition approach provides valuable constraint sensitivities and furthermore is naturally amenable to parallel computation. The method includes also a smoothing strategy to improve robustness of convergence when starting far from the optimum, as well as the capability to handle efficiently both soft and hard constraints. Procedures to drastically reduce the computation cost are mentioned. Preliminary numerical results are presented and compared to existing algorithms to illustrate the performance and the accuracy of our approach.
BLAS: Block-level adaptive striping for solid-state drives

Increasing the degree of parallelism and reducing the overhead of garbage collection (GC overhead) are the two keys to enhancing the performance of solid-state drives (SSDs). SSDs employ multichannel architectures, and a data placement scheme in an SSD determines how the data are striped to the channels. Without considering the data access pattern, existing fixed and device-level data placement schemes may have either high GC overhead or poor I/O parallelism, resulting in degraded performance. In this article, an adaptive block-level data placement scheme called BLAS is proposed to maximize the I/O parallelism while simultaneously minimizing the GC overhead. In contrast to existing device-level schemes, BLAS allows different data placement policies for blocks with different access patterns. Pages in read-intensive blocks are scattered over various channels to maximize the degree of read parallelism, while pages in each of the remaining blocks are attempted to be gathered in the same physical block to minimize the GC overhead. Moreover, BLAS allows the placement policy for a logical block to be changed dynamically according to the access pattern changes of that block. Finally, a parallelism-aware write buffer management approach is adopted in BLAS to maximize the degree of write parallelism. Performance results show that BLAS yields a significant improvement in the SSD response time when compared to existing device-level schemes. In particular, BLAS outperforms device-level page striping and device-level block striping by factors of up to 8.75 and 7.41, respectively. Moreover, BLAS achieves low GC overhead and is effective in adapting to workload changes.
An analog signal conditioning circuit for thermocouple temperature sensor employing thermistor for cold junction compensation

Thermocouples are widely used as temperature sensors in industrial as well as laboratory settings owing to their low cost, usability and stability over a wide range of temperatures. However limitations arise in the form of cold junction compensation and non-linearity of the thermocouple emf. The present paper proposes an analog signal conditioning circuit that performs the dual task of cold junction compensation and linearization. Cold junction compensation is done using a thermistor based circuit to emulate the output voltages of the thermocouple at different ambient temperatures with respect to 0°C, and linearization is performed by employing a temperature-compensated dual-input logarithmic amplifier. Optimum circuit parameters have been found by standard optimizations methods, and simulations have been performed using a circuit simulation software `PSpice' by considering the characteristics of a 5kΩ thermistor and a T-type Copper Constantan Thermocouple. Nonlinearity errors and variation of output voltage of the signal conditioning circuit with ambient temperature are investigated from the simulation results.
Using a Neural Network Controller to Control Chaos in the Rossler System

The complex dynamics behaviors of the Rossler reaction systems are studied in the paper. By applying bifurcation diagram and phase diagram are presented to analyze periodic oscillation state and chaos motions. Periodic and chaotic motions of the system can be distinguished by Lyapunov exponent method. The chaotic motion of the system is controlled using neural network controller. We obtain the steady periodic orbit of the system under effectively controlling. It is concluded the hyperbolic tangent function is the best candidate as the threshold function of NNC for controlling the Rossler reaction system. By studying numerical simulations, it is possible to provide reliable theory and effective numerical method for other systems.
The Emotion Mouse

One goal of human computer interaction (HCI) is to make an adaptive, smart computer system. This type of project could possibly include gesture recognition, facial recognition, eye tracking, speech recognition, etc. Another non-invasive way to obtain information about a person is through touch. People use their computers to obtain, store and manipulate data using their computer. In order to start creating smart computers, the computer must start gaining information about the user.
Growth and Poverty Reduction in Developing Countries : Is Growth in Democracies More Pro-Poor than in Non-Democracies?

Economists today agree that growth is fundamental in reducing poverty. But the strength of the relationship between the two has been debated, and there is a lack of satisfactory explanations to why the growth elasticity of poverty differs between countries. Solid democratic institutions have been mentioned as a means to ensure that growth is shared by the poor, but this proposition has not been assessed empirically. Using a data set including 157 intervals from 57 developing countries I estimate the elasticity of poverty to growth. I also use two different democracy indices to test the hypothesis that growth in democracies is more poverty-reducing than in non-democracies. Several other macroeconomic variables are also included in the model to analyze the determinants of the growth elasticity of poverty. Using several measures of growth and poverty, I find strong support that poverty is reduced by economic growth, with the elasticity estimated to be around -2. I do not, however, find any robustly significant determinants of the impact of growth on poverty. The results give some indication that the growth elasticity of poverty is higher in partly free countries than in nonfree countries. However, contrary to the hypothesis, there is stronger evidence that growth in fully democratic countries reduces poverty less than it does in partly free countries. None of the other macroeconomic variables are found to have a significant impact on how poverty responds to growth.
Finding group shilling in recommendation system

In the age of information explosion, recommendation system has been proved effective to cope with information overload in e-commerce area. However, unscrupulous producers shill the systems in many ways to make profit, and it makes the system imprecise and unreliable in a long term. Among many shilling behaviors, a new form of attack, called group shilling, appears and does great harm to the system. Because group shilling users are now well organized and become more hidden among various normal users, it is hard to find them by traditional methods. However, these group shilling users are similar to some extent, for they both shill the target items. We bring out a similarity spreading algorithm to find these group shilling users and protect recommendation system from unfair ratings. In our algorithm, we try to find these cunning group shilling users through propagating similarities from items to users iteratively. The experiment shows our similarity spreading algorithm improves the precision of the system and provides the system a reliable protection.