Miracle-dz/UniFAR-FTUs huggingface dataset:
2 IS THERE AN AID LAFFER CURVE ?

Comparing aid flows in the 1990s with those from the 1970s make it clear that there are now many more countries receiving what may be termed "high aid" (say in excess of 30 per cent of GNP) and that there has emerged a group of countries receiving very high aid. Whilst never formally considered in the literature, there is a feeling that such high aid may do more harm than good, a notion which may be captured in an aid Laffer curve. This paper presents an endogenous growth model which exhibits negative returns to aid at high aid levels, and offer some additional reasons as to why such a phenomenon may exist. Finally, empirical evidence is provided from cross-country regressions which confirms the existence of an aid Laffer curve.
Stochastic System with Colored Noise and Absorbing States: Path Integral Solution

The behavior of the most probable values of the order parameter $x$ and the amplitude $\phi$ of conjugate force fluctuations is studied for a stochastic system with a colored multiplicative noise with absorbing states. The phase diagrams introduced as dependencies the noise self-correlation time vs temperature and noise growth velocity are defined. It is shown that phase half-plane $(x,\phi)$ can be split into isolated domains of large, intermediate, and small values of $x$. System behavior in these domains is studied by the probability represented as path integral. In the region $x\ll 1$, the trajectories converge to the point $x = \phi = 0$ for $0 < a < 1/2$ and to $x = 0$, $\phi\to\infty$ for $1/2 < a \le 1$. In the former case, the probability of realization of trajectories is finite, while in the latter case it is vanishingly small, and an absorbing state can be formed.
Proteomics in Neuroscience: From Protein to Network

Proteomic tools offer a new platform for studies of complex biological functions involving large numbers and networks of proteins. Intracellular networks of proteins perform key functions in neurons and glia. The unicellular eukaryote Saccharomyces cerevisiae has been the prototype for eukaryotic proteomic studies, and when combined with genomics, microarrays, genetics, and pharmacology, new insights into the integrated function of the cell emerge. The anatomical complexity of the nervous system both in cell types and in the vast number of synapses introduces novel technical and biological issues regarding the subcellular organization of protein networks. Here we will discuss the technology of proteomics and its applications to the nervous system.
ECONOMIC FORCES IN THE LONDON STOCK MARKET

Empirical tests of APT have relied on factor analysis to estimate the risk factors. Here the authors propose a diff erent two-stage iterative methodology that relates risk factors to ex plicit economic variables. In the first stage, portfolio returns are regressed over time against these variables. In the second stage, a c ross-section regression is run across portfolios obtained in the firs t stage. The method is applied to 76 portfolios constructed from 760 securities traded on the London Stock Exchange between October 1977 a nd December 1983. Although experimental, four risk factors are identi fied: inflation, money supply, raw material prices, and interest rate s. Copyright 1988 by Blackwell Publishing Ltd
An Immune Recognition Based Algorithm for Finding Non-Dominated Set in Multi-Objective Optimization

An immune recognition based algorithm is proposed for finding the non-dominated set in multi-objective optimization. In this paper, non-dominated solution is comprehended from a new point of view. Then extra-optimal solution and infra-extra-optimal solution are defined and proved to be non-dominated solutions. After that, flowchart of the algorithm is outlined clearly, correctness of the algorithm is proved in detail, and computational complexity of the algorithm is analyzed theoretically. Compared with the algorithms which have the lowest computational complexity up to the present, experimental results show that when there are less objectives, the efficiency of the method based on immune recognition is almost the same as the method based on arenapsilas principle, and it is much better in the condition of more objectives.
CRISP: coarse-grain reconfigurable image signal processor for digital still cameras

This paper presents a novel preview-based coarse-grain reconfigurable image signal processor (CRISP) for digital still cameras (DSCs). The two modes in DSCs, which have quite different hardware considerations, make traditional implementation methods inefficient. One is preview mode, which needs realtime constraints and the other one is picture-taking mode, which requires high flexibility and capability for various algorithms in it. Low cost design of CRISP considers simpler image pipelines in preview mode and extends flexibility required in picture-taking mode with proper hardware resources devotion. Algorithmic similarity in image pipelines and successful hardware classification lead it to a combination of low cost and high efficiency. Coarse-grain modules connected by reconfigurable interconnection make it a good compromise between dedicated hardware and DSPs, which are suitable for only one, not all of two modes in DSCs respectively. The experimental results show that the total gate count of it is 38.6K with 5.8K byte memory. It can save more than 75% area from high end DSP, such as Trimedia TM1300. Besides, CRISP reduces execution cycle number of image pipeline tasks, such as 2-D filters to only 0.17% of that required by TM1300
Fuzzy adaptive control for pneumatic muscle actuator with simulated annealing tuning

Pneumatic artificial muscles - based robotic systems usually necessitate the use various nonlinear control techniques in order to improve their performance. Moreover, their robustness to parameter variation, which is generally hardly predictable, should also be tested. Here a fast hybrid adaptive control is proposed, where a conventional PD controller is placed into the feedforward branch and a fuzzy controller is placed into the adaptation branch. The fuzzy controller compensates for the actions of PD controller under conditions of inertia moment variation. The design of fuzzy controller is based on the results of optimization using simulated annealing algorithm. The results confirm fast action of the control scheme as well as its robustness to changes in inertia moment variation.
research paper series Globalisation , Productivity and Technology Research Paper 2006 / 22 Multinationals ’ productivity advantage : Scale or technology ?

The first aim of this paper is to decompose the productivity advantage of foreign multinationals into two components: the technology and scale effect. The second aim is to analyse the causal relationship between foreign ownership and these two components of productivity growth. We do so by analyzing the effects of an acquisition of a domestic establishment by a foreign multinational enterprise, using a combined propensity score matching and difference-indifferences estimation. Our empirical analysis is based on plant level data for the UK. From our econometric investigation three broad patterns emerge: (i) any positive impact of ownership change is predominantly due to change in technical efficiency, not scale effects (ii) the preacquisition TFP level of the erstwhile domestic plants play a role positive or negative – in mediating the rate of technology transfer from the MNE parent companies, (iii) the productivity growth effects are not confined to the year of acquisition, and tend to persist through time. JEL classification: F23, L22
An effective pansharpening method based on guided filtering

Pansharpening is an important tool in remote sensing applications. It transforms a set of low-spatial-resolution multispectral images to high-spatial-resolution images by fusing with a co-registered high-spatial-resolution panchromatic image. To deal with the increasing high resolution satellite images, wide varieties of pansharpening techniques have been developed. In this paper, we present an effective pansharpening method based on guided filtering. The method takes advantage of the guided filter to refine the blocking edges in the upscaled multispectral images and extract sufficient high frequency details from the panchromatic image. Moreover, it can be implemented to sharpen multispectral imagery in a convenient band-by-band manner. The experimental evaluations are carried out on QuickBird satellite images. Subjective and objective evaluations show that our proposed method can achieve high spectral and spatial quality and outperforms some existing methods.
Virtual object handling to assist people with limited mobility

Interaction with appliances present in an environment can be difficult for people who have mobility problems (such as the elderly or moving out of a wheelchair). This paper presents an approach based on the use of an Inertial Measurement Unit which identifies human movements from two points of view: on the one hand, the user can specify the object with which it wants to interact by simply pointing it with his arm, from the other he can pass a command to the object indicated by an appropriate gesture of the arm. The paper describes the operating modes of the approach, the Hw/Sw architecture used and the underlying mathematical analysis.
Two-dimensional Analytical Modelling of a Direct Methanol Fuel Cell

Direct methanol fuel cells are regarded nowadays as promising energy sources for portable electronic devices. Numerical models can be very useful for addressing the exploration of the fuel cell performance, without the development of many prototypes, which can be very expensive due to the presence of rear materials. Analytical models are particularly suited for investigating the cell performance with limited computing costs. In this work, a two-dimensional model for assessing the performance of an active-feed direct methanol fuel cell is presented, accounting for electrochemical reactions, mass and heat transfer.
OpenStack networking for humans: Symbolic execution to the rescue

Neutron is the OpenStack component that implements networking and it has been mocked and derided the weakest line in OpenStack [11]. We propose to use network symbolic execution to improve Neutron's ability to correctly implement tenant policies and to provide tenant traffic isolation. We propose to apply symbolic execution on two different OpenStack layers: the tenant view of the network and the actual deployment. Analyzing the tenant view is useful in many ways; first, it helps the tenant better understand its configuration's behavior before deployment. Secondly, its outputs can be compared to the analysis of the deployment to check if they are equivalent. We have built a prototype implementation and conducted preliminary evaluation, finding that we can verify our department's OpenStack deployment in seconds and detect certain common Neutron problems.
Addressing Time Series Modelling, Analysis and Forecasting in e-Learning Environments

It is well known that a distributed e-learning environment can only be an effective tool if both the trainers' and the students' requirements are fulfilled. This paper presents various aspects concerning the design of graphical user interface, the most suited interaction techniques, the e-content structuring and the effective learning assessment in the field of time series modelling, analysis and forecasting. Details on functionalities, web programming techniques, software simulation design, software testing and validation are all considered to obtain a high quality e-Learning system called e-TJMES.
Vehicle detection and counting based on color space model

Detecting moving objects in videos is an important task in many computer vision applications, including human interaction, traffic monitoring and Structural Health Monitoring. When having a stationary camera, a basic method to detect the objects of interest is background subtraction. However, precise moving object detection using such a method is an extremely difficult task in a varying environment. This paper introduces a new technique for detecting and counting the vehicles based on color space model. This model uses each pixel's color distortion and brightness distortion to detect the vehicle foreground pixels. In this work filtering methods are used to eliminate the noise. The proposed algorithm is tested with different videos and results clearly show the efficiency of the algorithm.
II . Prior Studies 2 . 1 Prior Studies on Customer Classification and Response Modeling

Conventional Support Vector Machines (SVMs) have been utilized as classifiers for binary classification problems. However, certain real world problems, including corporate bond rating, cannot be addressed by binary classifiers because these are multi-class problems. For this reason, numerous studies have attempted to transform the original SVM into a multiclass classifier. These studies, however, have only considered nominal classification problems. Thus, these approaches have been limited by the existence of multiclass classification problems where classes are not nominal but ordinal in real world, such as corporate bond rating and multiclass customer classification. In this study, we adopt a novel multiclass SVM which can address ordinal classification problems using ordinal pairwise partitioning (OPP). The proposed model in our study may use fewer classifiers, but it classifies more accurately because it considers the characteristics of the order of the classes. Although it can be applied to all kinds of ordinal multiclass classification problems, most prior studies have applied it to finance area like bond rating. Thus, this study applies it to a real world customer level classification case for implementing customer relationship management. The result shows that the ordinal multiclass SVM model may also be effective for customer level classification.
A Reversed Stackelberg Approach to Electronic Commerce Logistics Based on Supernetwork Theory

Electronic commerce (E-commerce) logistics has become one of the most hot-debated issues with the boom of modern information technologies. Different models have been introduced during the recent years. In this paper, a reversed stackelberg approach to E-commerce logistics market based on the supernetwork theory is proposed. In such a hierarchical market model, we take into account the profits, risks, as well as the credits as the elements of participant's utility function. A sequence-dependent gaming process in the secondary market is formulated and the equilibrium is obtained as a cooperation contract between the leader and the follower in every transaction. Furthermore, we formulate a reversed stackelberg solution with which an ordered, robust logistics market could be maintained. Analysis shows that the proposed approach has great contribution in improving both the cooperation among different participants, and the robustness of the entire E-commerce logistics market.
Ventral Striatum, but Not Cortical Volume Loss, Is Related to Cognitive Dysfunction in Type 1 Diabetic Patients With and Without Microangiopathy

OBJECTIVE Patients with longstanding type 1 diabetes may develop microangiopathy due to high cumulative glucose exposure. Also, chronic hyperglycemia is related to cerebral alterations and cognitive dysfunction. Whether the presence of microangiopathy is conditional to the development of hyperglycemia-related cerebral compromise is unclear. Since subcortical, rather than cortical, volume loss was previously related to cognitive dysfunction in other populations, we measured these brain correlates and cognitive functions in patients with longstanding type 1 diabetes with and without microangiopathy. RESEARCH DESIGN AND METHODS We evaluated differences in subcortical volume and cortical thickness and volume in type 1 diabetic patients with (n = 51) and without (n = 53) proliferative retinopathy and 49 control subjects and related volume differences to cognitive dysfunction. Analyses were corrected for age, sex, systolic blood pressure, and A1C. RESULTS Putamen and right thalamic volume loss was noted in both patients with and without proliferative retinopathy compared with control subjects (all P < 0.05). Additionally, in patients with proliferative retinopathy relative to control subjects, volume loss of the bilateral nucleus accumbens was found (all P < 0.05). No differences were observed between the two patient groups. Cortical thickness and volume were not different between groups. In pooled analyses, lower left nucleus accumbens volume was associated with cognitive dysfunction (P < 0.035). CONCLUSIONS This study shows subcortical, but not cortical, volume loss in relation to cognitive dysfunction in patients with longstanding type 1 diabetes, irrespective of microangiopathy. The time course, pathophysiology, and clinical relevance of these findings need to be established in longitudinal and mechanistic studies.
Analyzing software reviews for software quality-based ranking

Software comparison reviews from users who have experience with the software are important information for software ranking. Software reviews may contain information in terms of software quality comparison such as, “Software A is better than the other in quality Q”. This information can be used for software quality ranking. This research presents an approach for software ranking from user reviews which composed of 3 main phases: user reviews gathering, user reviews analysis and software ranking. After user reviews gathering, a collection of user review is constructed and analyzed. The analysis consists of comparative relation extraction, quality classification and sentiment classification. We use keyword and grammatical relation to extract comparative relation. Keyword is also used for 5 types of quality classification; performance, reliability, security, usability and maintainability. Information from comparative relation is used for sentiment classification. Then, the ranking method is performed. From our experiment, we achieve a high value of f-measure for comparative relation extraction and quality classification. We also improve the accuracy of sentiment classification. Our proposed ranking result is statistically correlated to the expert judgment with 0.935 Pearson's correlation coefficient.
In Silico Single-Molecule Manipulation of DNA with Rigid Body Dynamics

We develop a new powerful method to reproduce in silico single-molecule manipulation experiments. We demonstrate that flexible polymers such as DNA can be simulated using rigid body dynamics thanks to an original implementation of Langevin dynamics in an open source library called Open Dynamics Engine. We moreover implement a global thermostat which accelerates the simulation sampling by two orders of magnitude. We reproduce force-extension as well as rotation-extension curves of reference experimental studies. Finally, we extend the model to simulations where the control parameter is no longer the torsional strain but instead the torque, and predict the expected behavior for this case which is particularly challenging theoretically and experimentally.
Measuring the Accuracy of Minimum Width Transistor Area in Estimating FPGA Layout Area

Integrating reconfigurable fabrics in SOCs require an accurate estimation of the layout area of the reconfigurable fabrics in order to properly accommodate early floor-planning. This work examines the accuracy of using minimum width transistor area, a widely used area model in many previous FPGA architectural studies, in assisting floor-planning process. In particular, the layout areas of LUT multiplexers are used as a case study. We found that comparing to the minimum width transistor area, the traditional metal area based stick diagrams can provide much more accurate layout area estimations. In particular, minimum width transistor area can underestimate the layout area of LUT multiplexers by as much as a factor of 3-4 while stick diagrams can achieve over 80 percent accuracy in layout area estimation.
A New Threshold Blind Signature Scheme from Pairings

Threshold digital signature and blind signature are playing important roles in crypto- graphy as well as in practical applications such as e-cash and e-voting systems, etc. In this paper, we present a new threshold blind digital signature based on pairings without the third party. Our scheme operates on Gap Deffie-Hellman (GDH) group, where Computational Diffie-Hellman problem is hard but Decision Diffie-Hellman problem is easy. For example, we use pairings that could be built from Weil pairing or Tate pairing. We also analyze security and efficiency of the scheme.
Block Entropy Analysis of Heart Rate Variability Signals

In this paper we present a novel approach to the analysis of Heat Rate Variability (HRV) data, by coarse-graining analysis using the estimation of Block Entropies with the technique of lumping. HRV time series are generated from long recordings of Electrocardiograms (ECGs) and are then filtered in order to produce a coarse-grained symbolic dynamics. Block Entropy analysis is applied to these dynamics in order to examine its coarse-grained statistics. Our data set is comprised of two subsets, one of healthy subjects and another of Coronary Artery Disease (CAD) patients. It is found that Entropy analysis provides a quick and efficient tool for the differentiation of these series according to subject category. Healthy subjects provided more complex statistics compared to patients; specifically, the healthy data files provided higher values of block Entropies compared to patient ones. We also compare these results with the Correlation Dimension Estimation in order to establish coherency. We believe that this analysis may provide a useful statistical method towards the better understanding of the human cardiac system.