Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization in Economics and Finance: Some Advances in Non-Linear, Dynamic, Multi-Criteria and Stochastic Models

: Optimal Models for Economics and Finance. - Mathematics of Optimal Control. - Computing Optimal Control : The SCOM package. - Computing Optimal Growth and Development Models. - Modelling Financial Investment with Growth. - Modelling Sustainable Development. - Modelling and Computing a Stochastic Growth Model. - Optimization in Welfare Economics. - Transversality Conditions for Infinite Horizon. - Conclusions.
Analysis of Computer and Communication Systems with Uncertainties and Variabilities in Workload

A uniied approach to characterize workload parameters used t o m o del computer and communication systems with variabilities and uncertainties in workload is presented. The use of histograms is proposed and approaches to adapt existing analysis techniques to interval-based histogram arguments are discussed. The proposed method is demonstrated by application to existing analysis techniques for single class queueing network models. The analysis of computer systems requires eeective tools for predicting their performance and analyzing their behavior. Analytic techniques are often used for performance estimation because of their relatively low cost in comparison with simulations and benchmarks. A conventional analytic performance model accepts a set of single valued parameters such as service demands for diierent devices and produces a single point measure for each performance index of interest such as the mean response time and mean processor utilization. However, the exact value of every parameter for the system may not always be known to the performance analyst leading to uncertainties in the workload characterization WLC. For example systems are often subject to variabilities in the workload 2. Diierent phases in the operation of the system under study may lead to a diierent set of parameters that characterize each phase. Appropriate characterization of workload is required to capture any uncertainty o r v ariability associated with it. We propose to characterize the parameters D k of each aspect in the system that exhibits variability anddor uncertainty b y a histogram HD k. The histogram consists of a numb e r o f i n tervals and an associated probability of occurrence. Each i n terval is a range of values: the parameter lies in this given range uncertainty with the speciied probability of occurrence variability. A parameter X may be speciied through a histo-gram HX as follows: i=1 p i = 1. Each e n try in the deenition of X provided above i s a t wo-tuple, an interval x i ; x i and an associated probability p i , i.e. with probability p i the mean value of X lies between x i and x i. This general model can be used to represent uncertainties anddor variabilities: Uncertainties are characterized by the length of the interval, an interval of width zero thin interval" 13 represents no uncertainty. V ariability is described by the distribution of the probabilities p i , with m = 1 o b viously corresponding …
Semantic-Synaptic Web Mining: A Novel Model for Improving the Web Mining

Web mining is the application of data mining technique to automatically discover and gathered information from web documents and services which can be in structured, unstructured or semi-structured form. It is used to understand user behaviour, evaluate the effectiveness of a particular web and find out the relevant and efficient results from the web. Accuracy and relevance of information extracting from the web is the most significant issue of concern for the realization of web mining. The idea is to improve the accuracy and relevance of information extracting from the web. This paper proposes a novel model for improving the web mining, we hypothesize that web mining is Semantic-Synaptic web mining. Semantic-Synaptic web Mining interlinks the web of data to different data sources at low entropy (Information Theory). This paper combines the best ideas from the semantic web and synaptic web at low entropy and constructs the architecture of Semantic-Synaptic web mining.
Institutional framework of small community water supply systems in the United States : a review of experiences and lessons for developing countries

This paper examines rural water supply systems (RWS) in the United States and evaluates the relevance of findings for developing countries. It focuses on the institutional and regulatory framework that governs RWS in the U.S. by examining the organizational and procedural characteristics of national and regional institutions, such as the Farmers Home Administration (FmHA) and the Rural Water Association and its state affiliates. The working relationship between these institutions and community associations is also discussed and illustrated by data from field observations. Issues addressed include financial and technical management and extension and training services. The paper singles out the following as the most conspicuously effective features of the United States' RWS experience: 1) the local initiative and community mobilization required for the formation of a local RWS system for funding by the FmHA; and 2) the circuit-rider system for providing RWS systems with professional expertise, as developed and executed by the Oklahoma Rural Water Association. Insights gained from the United States' experience are then considered from a developing country perspective. The paper concludes by drawing on specific parallels and differences between the developed and developing country contexts to propose a model for a RWS demonstration program suited to a development setting.
Enterprise Architectures – Enabling Interoperability Between Organizations

Interoperability is central to any form of collaboration between organizations, as it enables information and knowledge sharing by cooperating entities within and across organizational boundaries. Interoperability is particularly important in the public sector where collaboration between public agencies is necessary to realize the notions of seamless services and one-stop government. Enterprise Architectures comprise models and tools to support decisionmaking and development particularly related to IT applications within an enterprise. This paper presents a survey of Enterprise Architectures focused on the question to what extent they support interoperability among organizations. The work has been carried out as part of a project to build a foundation for the development of an interoperability infrastructure for Electronic Government.
On-line structured subspace identification with application to switched linear systems

This article is concerned with the identification of switched linear multiple-inputs–multiple-outputs state-space systems in a recursive way. First, a structured subspace identification scheme for linear systems is presented which turns out to have many attractive features. More precisely, it does not require any singular value decomposition but is derived using orthogonal projection techniques; it allows a computationally appealing implementation and it is closely related to input–output models identification. Second, it is shown that this method can be implemented on-line to track both the range space of the extended observability matrix and its dimension and thereby, the system matrices. Third, by making use of an on-line switching times detection strategy, this method is applied to blindly identify switched systems and to label the obtained submodels. Simulation results on noisy data illustrate the abilities and the benefits of the proposed approach.
Facial muscle activity, Response Entropy, and State Entropy indices during noxious stimuli in propofol–nitrous oxide or propofol–nitrous oxide–remifentanil anaesthesia without neuromuscular block

Background Entropy™ is an anaesthetic EEG monitoring method, calculating two numerical parameters: State Entropy (SE, range 0–91) and Response Entropy (RE, range 0–100). Low Entropy numbers indicate unconsciousness. SE uses the frequency range 0.8–32 Hz, representing predominantly the EEG activity. RE is calculated at 0.8–47 Hz, consisting of both EEG and facial EMG. RE–SE difference (RE−SE) can indicate EMG, reflecting nociception. We studied RE−SE and EMG in patients anaesthetized without neuromuscular blockers. Methods Thirty-one women were studied in propofol–nitrous oxide (P) or propofol–nitrous oxide–remifentanil (PR) anaesthesia. Target SE value was 40–60. RE−SE was measured before and after endotracheal intubation, and before and after the commencement of surgery. The spectral content of the signal was analysed off-line. Appearance of EMG on EEG was verified visually. Results RE, SE, and RE−SE increased during intubation in both groups. Elevated RE was followed by increased SE values in most cases. In these patients, spectral analysis of the signal revealed increased activity starting from low (<20 Hz) frequency area up to the highest measured frequencies. This was associated with appearance of EMG in raw signal. No spectral alterations or EMG were seen in patients with stable Entropy values. Conclusions Increased RE is followed by increased SE at nociceptive stimuli in patients not receiving neuromuscular blockers. Owing to their overlapping power spectra, the contribution of EMG and EEG cannot be accurately separated with frequency analysis in the range of 10–40 Hz.
Skeletal Muscle Stem Cells from Animals I. Basic Cell Biology

Skeletal muscle stem cells from food-producing animals are of interest to agricultural life scientists seeking to develop a better understanding of the molecular regulation of lean tissue (skeletal muscle protein hypertrophy) and intramuscular fat (marbling) development. Enhanced understanding of muscle stem cell biology and function is essential for developing technologies and strategies to augment the metabolic efficiency and muscle hypertrophy of growing animals potentially leading to greater efficiency and reduced environmental impacts of animal production, while concomitantly improving product uniformity and consumer acceptance and enjoyment of muscle foods.
A common data manipulation language for nested data in heterogeneous environments

One key aspect of data-centric applications is the manipu- lation of persistent data repositories, which is moving fast from querying a centralized relational database to the ad- hoc combination of constellations of data sources. Query languages are being typefuly integrated in host, general purpose, languages in order to increase reasoning and optimizing capabilities of interpreters and compilers. However, not much is being done to integrate and orches- trate different and separate sources of data. We present a common data manipulation language, that abstracts the nature and localization of the data-sources. We define its semantics and a type directed compilation, query optimization, and query orchestration mechanism to be used in development tools for heterogeneous environments. We provide type safety and language integration. Our approach is also suitable for an interactive query construction environment by rich user interfaces that pro- vide immediate feedback on data manipulation operations. This approach is currently the base for the data layer of a development platform for mobile and web applications.
Invariant synthesis for verification of parameterized cyber-physical systems with applications to aerospace systems

In this paper, we describe a method for synthesizing inductive invariants for cyberphysical aerospace systems that are parameterized on the number of participants, such as the number of aircraft involved in a coordinated maneuver. The methodology is useful for automating the traditionally manual process of deductive verification of safety properties, such as collision avoidance, and establishes such properties regardless of the number of participants involved in a protocol. We illustrate the methodology using a simplified model of the landing protocol of the Small Aircraft Transportation System (SATS) as a case study. Each participant (aircraft) in the protocol is modeled as a hybrid automaton with both discrete and continuous states and potentially nondeterministic evolution thereof. Discrete states change instantaneously according to transitions and continuous states evolve according to rectangular differential inclusions. The invariant synthesis method enables a fully automatic verification of the main safety property of SATS, namely, safe separation of aircraft on approach to the runway. The method is implemented in a prototype verification tool called Passel. We present promising experimental results using the methodology, which has enabled a fully automatic proof of safe separation for the model of SATS.
THE PERFORMANCE OF THE SECURITIES EXCHANGE OF BARBADOS / LA PERFORMANCE DES MARCHÉS DE CAPITAUX DE BARBADE

This paper overviews the Securities Exchange of Barbados (SEB) and the aggre gate stock market indicators. It then tests the efficiency of the SEB using unit roots and cointegration techniques. Finally Granger causality is employed to examine the relationship between the stock market and the macroeconomy. The results indicate that the SEB is not efficient but stock returns can help predict the future direction of the Barbados economy. LA PERFORMANCE DES MARCHES DE CAPITAUX DE BARBADE
Woman as a Company Head

The female manager is a worldwide phenomenon in the development of private entrepreneurship. The American researchers R. Peterson and K. Weirmair have called this phenomenon a "quiet revolution on a world scale. "1 The intensity with which the "wave" of female entrepreneurship is spreading across the world, testifying to the opportunities for women to create their own businesses, raises the question of their contribution to the world economy.
Distribution of Faraday Rotation Measure in Jets from Active Galactic Nuclei. II. Prediction from Our Sweeping Magnetic Twist Model for the Wiggled Parts of Active Galactic Nucleus Jets and Tails

Distributions of Faraday rotation measure (FRM) and the projected magnetic field derived by a three-dimensional simulation of MHD jets are investigated based on our "sweeping magnetic twist model. " FRM and Stokes parameters were calculated to be compared with radio observations of large-scale wiggled AGN jets on kiloparsec scales. We propose that the FRM distribution can be used to discuss the three-dimensional structure of the magnetic field around jets and the validity of existing theoretical models, together with the projected magnetic field derived from Stokes parameters. In a previous paper we investigated the basic straight part of AGN jets by using the result of a two-dimensional axisymmetric simulation. The derived FRM distribution has a general tendency to have a gradient across the jet axis, which is due to the toroidal component of the magnetic field generated by the rotation of the accretion disk. In this paper we consider the wiggled structure of the AGN jets by using the result of a three-dimensional simulation. Our numerical results show that the distributions of FRM and the projected magnetic field have a clear correlation with the large-scale structure of the jet itself, namely, three-dimensional helix. Distributions, seeing the jet from a certain direction, show a good matching with those in a part of the 3C 449 jet. This suggests that the jet has a helical structure and that the magnetic field (especially the toroidal component) plays an important role in the dynamics of the wiggle formation because it is due to a current-driven helical kink instability in our model.
Unbiased Protein Interface Prediction Based on Ligand Diversity Quantification

Proteins interact with each other to perform essential functions in cells. Consequently, identification of their binding interfaces can provide key information for drug design. Here, we introduce Weighted Protein Interface Prediction (WePIP), an original framework which predicts protein interfaces from homologous complexes. WePIP takes advantage of a novel weighted score which is not only based on structural neighbours' information but, unlike current state-of-the-art methods, also takes into consideration the nature of their interaction partners. Experimental validation demonstrates that our weighted schema significantly improves prediction performance. In particular, we have established a major contribution to ligand diversity quantification. Moreover, application of our framework on a standard dataset shows WePIP performance compares favourably with other state of the art methods.
Surveillance capitalism and children’s data: the Internet of toys and things for children

This article discusses the positioning of children both as objects of economic activity as and subjects of market relations under surveillance capitalism. It looks briefly at the history of children’s engagement with the market economy from their engagement in the labour force during industrial revolution times; their disappearance from direct economic activity during the Romantic Movement; through to their emergence as both data sources and data consumers within a big data economy. It argues that this is the first time since children retreated from the paid labour force in the late 19th and early 20th centuries due to labour law reforms that their activities are of significant economic value, and that the emergence of Internet-connected toys and things for children will significantly amplify children’s position as data sources under surveillance capitalism.
Phase I Clinical Trials

Phase I trials are conducted to find a dose to use in subsequent trials. They provide data on the rate of adverse events at different dose levels and provide data for studying the pharmacokinetics and pharmacology of the drug. Dose-finding studies that involve therapies with little or no toxicity often enroll healthy volunteers and usually have a control group. Trials in oncology and other life threatening diseases such as HIV enroll patients because treatments are usually highly toxic and to enroll healthy volunteers would not be ethical. The primary outcome for phase I trials in oncology and HIV is typically dose limiting toxicity. Such studies require different design strategies. In section 1.2, we review dose-finding procedures used in healthy volunteers. In Section 1.3 we describe dose-finding procedures for trials with toxic outcomes enrolling patients. In Section 1.4, we list some other design problems in dose-finding.
Peak Luminosity-Spectral Lag Relation Caused by the Viewing Angle of the Collimated Gamma-Ray Bursts

We compute the kinematical dependence of the peak luminosity, the pulse width, and the spectral lag of the peak luminosity on the viewing angle θv of a jet. For appropriate model parameters we obtain a peak luminosity-spectral lag relation similar to the observed one including gamma-ray burst (GRB) 980425. A bright (dim) peak with short (long) spectral lag corresponds to a jet with small (large) viewing angle. This suggests that the viewing angle of the jet might cause various relations in GRBs such as the peak luminosity-variability relation and the luminosity-width relation. Our model also suggests that X-ray-rich GRBs (or X-ray flushes or fast X-ray transients) are typical GRBs observed from large θv with large spectral lag and low variability.
Distributed Intelligent Sensor Network for the Rehabilitation of Parkinson's Patients

The coordination between locomotion and respiration of Parkinson's disease (PD) patients is reduced or even absent. The degree of this disturbance is assumed to be associated with the disease severity [S. Schiermeier, D. Schäfer, T. Schäfer, W. Greulich, and M. E. Schläfke, “Breathing and locomotion in patients with Parkinson's disease,” Eur. J. Physiol. , vol. 443, No. 1, pp. 67-71, Jul. 2001]. To enable a long-term and online analysis of the locomotion-respiration coordination for scientific purpose, we have developed a distributed wireless communicating network. We aim to integrate biofeedback protocols with the real-time analysis of the locomotion-respiration coordination in the system to aid rehabilitation of PD patients. The network of sensor nodes is composed of intelligent network operating devices (iNODEs). The miniaturized iNODE contains a continuous data acquisition system based on microcontroller, local data storage, capability of on-sensor digital signal processing in real time, and wireless communication based on IEEE 802.15. 4. Force sensing resistors and respiratory inductive plethysmography are applied for motion and respiration sensing, respectively. A number of experiments have been undertaken in clinic and laboratory to test the system. It shall facilitate identification of therapeutic effects on PD, allowing to measure the patients' health status, and to aid in the rehabilitation of PD patients.
An Improved Mutual Information-Based Feature Selection Algorithm for Text Classification

Feature selection plays an important role in text classification, and contributes directly to the accuracy of the classification. In order to correct the defects, such as mutual information-Based feature selection method tends to select rare words and those words from small samples as features, and negative MI value. This paper proposes a new improved feature evaluation function for automatic text classification by taking word frequency, concentration rate between classes and dispersion within class into overall consideration. According to experimental results, the improved algorithm is well placed to remedy the defect that the original MI evaluation function is prone to select rare words, and can improve the performance of classification significantly.
Fuzzy predictive control of Tape Rectification

Tape Rectification is a highly nonlinear process. Conventional Model Predictive Control (MPC) may not be able to cope with such process. The Fuzzy Neural Network (FNN) methodology is proposed to realize the model of the nonlinear process. The measured data serve as samples to train the neural network. The prediction accuracy is guaranteed due to the interpolation ability of the feedforward network. Multidimensional searching technique is used to solve the nonlinear optimization problem. The optimization results are embedded into a BP neural network predictive controller. On-line computation of BP neural network can satisfy the real-time control demand. The experimental results have shown the effectiveness of the FNN predictive control.
Massive Type IIA Theory on K 3 1

In this paper we study K3 compactification of ten-dimensional massive type IIA theory with all possible Ramond-Ramond background fluxes turned on. The resulting sixdimensional theory is a new massive (gauged) supergravity with an action that is manifestly invariant under an O(4, 20)/O(4)× O(20) duality symmetry. We discover that this six-dimensional theory interpolates between vacua of ten-dimensional massive IIA supergravity and vacua of massless IIA supergravity with appropriate background fluxes turned on. This in turn suggests a new 11-dimensional interpretation for the massive type IIA theory. Work supported by: AvH – the Alexander von Humboldt foundation, DFG – the German Science Foundation, GIF – the German–Israeli Foundation for Scientific Research, DAAD – the German Academic Exchange Service. email: haack, j.louis, singh@physik.uni-halle.de