Miracle-dz/UniFAR-FTUs huggingface dataset:
A real-time cellular system architecture to experiment with UMTS/HSDPA in a laboratory

Nowadays wireless wide area networks (e.g. cellular networks) are also used to provide access to Internet and its services. However, protocols and applications not specifically designed for wireless links (e.g., TCP, VoIP) often require a deeper analysis when applied to such links. Performance analysis represents a valid method to evaluate such protocols and applications, modeling their behavior and then working on their improvement. An appropriate solution to support performance evaluation of a wireless system and its support to protocols and applications consists in building a close-to-real test environments. This paper presents MUSA, a testbed that allows experimentation of cellular networks in a laboratory. The presented testbed combines emulation components and real equipments in a single experimentation platform, with the flexibility, scalability and repeatability features of an emulated environment and the possibility of testing real equipments, e.g., real mobile terminals or UMTS/HSDPA wireless cards and base stations. The paper describes also the assessment and calibration of the testbed. It presents an extensive comparison with a commercial 3G network and discusses the unique properties of MUSA. Finally, the paper also presents two case studies in order to highlight the benefits of conducting experimental research in an in-lab fully controlled platform rather than in an operator-controlled network.
Research of Trajectory Planning for Mobility Assistance Robot Based on CKF

According to the problem on tracking planning of mobility assistance robot, a tracking planning method was presented using the kalman filter (KF). Based on known nonholonomic dynamic model of mobility assistance robot, the cubature kalman filter (CKF) was used to improve the influence of nonlinear system, and the autonomous navigation and control of mobility assistance robot was realized. The experimental results indicate that the method presented in this paper was excellent than extended kalman filter (EKF) and unscented kalman filter (UKF) in the stability, precision and computational complexity.
Improved facial expression recognition via uni-hyperplane classification

Large margin learning approaches, such as support vector machines (SVM), have been successfully applied to numerous classification tasks, especially for automatic facial expression recognition. The risk of such approaches however, is their sensitivity to large margin losses due to the influence from noisy training examples and outliers which is a common problem in the area of affective computing (i.e., manual coding at the frame level is tedious so coarse labels are normally assigned). In this paper, we leverage the relaxation of the parallel-hyperplanes constraint and propose the use of modified correlation filters (MCF). The MCF is similar in spirit to SVMs and correlation filters, but with the key difference of optimizing only a single hyperplane. We demonstrate the superiority of MCF over current techniques on a battery of experiments.
Comment on "Asymptotic Phase for Stochastic Oscillators"

In his Comment [arXiv:1501.02126 (2015)] on our recent paper [Phys. Rev. Lett. , v. 113, 254101 (2014)], Pikovsky compares two methods for defining the "phase" of a stochastic oscillator. We reply to his Comment by showing that neither method can unambiguously identify a unique system of isochrons, when multiple oscillations coexist in the same system.
How Do Business Regulations Affect Foreign Direct Investment?

Abstract In this study, we apply three sets of econometric models to examine the effects of business regulations on foreign direct investment (FDI) by using FDI statistics from 12 source countries to 64 host countries in 2000. Our log-linear results suggest that FDI inflows are strongly correlated with business regulatory costs in the FDI host countries. By using endogenous threshold models and the rolling-regression techniques, we find evidence of a nonlinear threshold effect in the relationship between FDI inflows and regulatory costs. When a host country's regulatory costs are sufficiently low, a further decrease in regulations may not stimulate and, in fact, may even decrease FDI inflows. On the other hand, beyond some threshold, FDI inflows significantly rise as the regulatory costs fall. In addition, we find that the marginal effect of business taxes on FDI depends on the level of regulatory costs; i.e., as regulatory costs rise, the marginal effect of taxes on FDI inflows falls. Our results suggest that the regulatory competition between FDI host countries may have different impacts on countries with different regulatory cost levels. While a fall in the costs can directly stimulate FDI inflows in heavily regulated countries such as Brazil and China, it might have no effect, or even a negative effect, on FDI inflows in low-cost countries such as Canada and the United States. In the low-regulatory-cost countries, tax incentives might be more effective to attract FDI than those in heavily regulated countries.
Investigation on the convergence of the evanescent model and the polynomial model including effective conducting path effect (ECPE): Applied to the submicronic SG FD SOI MOSFET

We are presenting a convergence study of the evanescent model and the polynomial model with and without the Effective Conduction Path Effect (ECPE). These analytic models of the electric potential in the channel are used to analyze the short channel effects for the submicronic Single Gate FD SOI MOSFET. Hereby, we figure out the 2D Poisson equation and we analytically write the surface potential, the threshold voltage, the DIBL and the sub-threshold slope. The results show a good agreement of the evanescent model and the polynomial model including the ECPE with measures done by simulation tools.
Non-orthogonal Range Searching

A common type of database query consists of searching according to a range of key values. Such queries are termed range queries, and the problem associated with this type of queries is known as range searching. Ranges are often defined in multiple dimensions; for example, a range query could be phrased: “Report all the people in the database who live no more than 1 km away from the market place, are between 40 and 60 years old, and whose names fall between John and Joseph in alphabetical order. This problem has a long history, and has been widely studied by the Computational Geometry community. Range searching has multiple applications on relational databases, Geographic Information Systems (GIS), Computer Graphics, networks and communication, and other areas, including other problems in Computational Geometry itself.
A variational perspective on noise-robust speech recognition

Model compensation methods for noise-robust speech recognition have shown good performance. Predictive linear transformations can approximate these methods to balance computational complexity and compensation accuracy. This paper examines both of these approaches from a variational perspective. Using a matched-pair approximation at the component level yields a number of standard forms of model compensation and predictive linear transformations. However, a tighter bound can be obtained by using variational approximations at the state level. Both model-based and predictive linear transform schemes can be implemented in this framework. Preliminary results show that the tighter bound obtained from the state-level variational approach can yield improved performance over standard schemes.
Smart routing mechanism for green ZigBee-based wireless sensor networks

Recent advances in communication networks have spurred interest on the definition of efficient self-configuration protocols. Such mechanisms are particularly of interest on the rapid deployment of wireless sensor networks whose nodes are characterized by their low computational and energy resources according to the green networking principles. In this paper, we introduce an adaptable fuzzy-logic assisted configuration mechanism for ZigBee networks; one of the most promising standards in the area of wireless sensor networks. Our results show that the use of fuzzy-logic principles can significantly improve the operation of tree-based routing mechanisms by reducing the set-up network time and the number of router nodes in the network, thus allowing a reduction in the energy consumed by nodes.
Affinity Propagation-Based Probability Neural Network Structure Optimization

The structure optimization of probabilistic neural network is still an unsolved and challenging problem. In this paper, a modified probabilistic neural network is proposed by using affinity propagation. Firstly, the basic probabilistic neural network is presented and the associated problems are analyzed. Then the affinity propagation clustering algorithm is adopted to optimize the structure of the probabilistic neural network. Finally, the proposed probabilistic neural network with affinity propagation is applied in the Iris data classification case. The simulation results show that the proposed method can shrink the number of pattern neurons and improve the accuracy rate of testing samples without the need of extra running time.
Relationship between visual field sensitivity loss and quadrantic macular thickness measured with Stratus-Optical coherence tomography in patients with chiasmal syndrome.

PURPOSE To correlate visual field sensitivity (VFS) loss on standard automated perimetry (SAP) and quadrantic macular thickness on optical coherence tomography (OCT) in patients with permanent temporal hemianopia from chiasmal compression. METHODS Forty eyes from 40 patients with chiasmal compression and 40 healthy eyes were submitted to standard automated perimetry and Stratus-OCT scanning. Raw data of the fast macular thickness scanning protocol were exported and macular thickness measurements were recorded and averaged for each quadrant and half of the central area. The correlation between visual field sensitivity loss and optical coherence tomography measurements was tested with Pearson's correlation coefficients and with linear regression analysis. RESULTS A significant association was found between each macular thickness parameter and the corresponding central VF mean sensitivity. The strongest association was observed between superonasal macular thickness and the inferotemporal mean defect measured both in decibel (R=0.47; p=0.001) and in 1/Lambert (R=0.59; p<0.0001) units. CONCLUSION Stratus-OCT-measured macular thickness was topographically related with visual field sensitivity loss in patients with temporal hemianopia from chiasmal compression. Such measurements could prove clinically useful in the diagnosis and follow-up of patients with chiasmal compression. ClinicalTrial.gov identifier number: NCT0039122.
Hippocampus Segmentation via active contour model

Since hippocampal volume measurement is often used in studying Alzheimer’s disease to assess disease progression, automatic hippocampus segmentation is an important task in clinical applications. However, it is a challenging task due to its small size, complex shape, fuzzy boundaries, partial volume effects, and anatomical variability. In this paper we propose a new segmentation method to segment the hippocampus from brain MRI images automatically.This proposed method presents a new region-based signed pressure force function, which can efficiently stop the contours at weak boundary. Experimental results show that the model can fast and effectively segment the intensity inhomogeneous images.
An MCL-Based Text Mining Approach for Namesake Disambiguation on the Web

In this paper, we propose a Markov Clustering (MCL) based text mining approach for namesake disambiguation on the Web. The novelty of the proposed technique lies in modeling the collection of web pages using a weighted graph structure and applying MCL to crystalize it into different clusters, each one containing the web pages related to a particular namesake individual. The proposed method focuses on three broad and realistic aspects to cluster web pages retrieved through search engines - content overlapping, structure overlapping, and local context overlapping. The efficacy of the proposed method is demonstrated through experimental evaluations on standard datasets.
On the role of the nouns in IR-based traceability recovery

The intensive human effort needed to manually manage traceability information has increased the interest in utilising semi-automated traceability recovery techniques. This paper presents a simple way to improve the accuracy of traceability recovery methods based on Information Retrieval techniques. The proposed method acts on the artefact indexing considering only the nouns contained in the artefact content to define the semantics of an artefact. The rationale behind such a choice is that the language used in software documents can be classified as a sectorial language, where the terms that provide more indication on the semantics of a document are the nouns. The results of a reported case study demonstrate that the proposed artefact indexing significantly improves the accuracy of traceability recovery methods based on the probabilistic or vector space based IR models.
miR-26a inhibits invasion and metastasis of nasopharyngeal cancer by targeting EZH2

Nasopharyngeal carcinoma (NPC) is a highly invasive and metastatic type of cancer that is widely prevalent in Southern China. Studies have shown that several microRNAs (miRNAs) are implicated in NPC metastasis. Our previous studies have demonstrated that miRNA miR-26a inhibits cell growth and tumorigenesis of NPC through the repression of enhancer of zeste homolog 2 (EZH2). However, the role of miR-26a in NPC metastasis remains unknown. In this study, we showed that ectopic expression of miR-26a inhibited the migratory and invasive capacities of NPC cells in vitro. Additionally, we used a murine model to investigate the role of miR-26a in NPC metastasis and results showed that miR-26a overexpression suppresses the metastatic behavior of NPC cells in vivo. Furthermore, the data demonstrated that miR-26a decreased the expression levels of EZH2 in vitro and in vivo, suggesting that the antimetastatic effect of miR-26a in NPC was mediated by regulating EZH2. Therefore, these findings indicate that miR-26a functions as an antimetastatic miRNA in NPC and that its antimetastatic effects are mediated mainly by repressing EZH2 expression.
Alterations of cellular bioenergetics in pulmonary artery endothelial cells

Idiopathic pulmonary arterial hypertension (IPAH) is pathogenetically related to low levels of the vasodilator nitric oxide (NO). Because NO regulates cellular respiration and mitochondrial biogenesis, we hypothesized that abnormalities of bioenergetics may be present in IPAH. Evaluation of pulmonary artery endothelial cells from IPAH and control lungs in vitro revealed that oxygen consumption of IPAH cells was decreased, especially in state 3 respiration with substrates glutamate-malate or succinate, and this decrease paralleled reduction in Complex IV activity and IPAH cellular NO synthesis. IPAH pulmonary artery endothelial cells had decreased mitochondrial dehydrogenase activity and lowered mitochondrial numbers per cell and mitochondrial DNA content, all of which increased after exposure to NO donors. Although IPAH/pulmonary artery endothelial cells' ATP content was similar to control under normoxia, cellular ATP did not change significantly in IPAH cells under hypoxia, whereas ATP decreased 35% in control cells, identifying a greater dependence on cellular respiration for energy in control cells. Evidence that glucose metabolism was subserving the primary role for energy requirements of IPAH cells was provided by the ≈3-fold greater glycolytic rate of IPAH cells. Positron emission tomography scan with [18F]fluoro-deoxy-d-glucose performed on IPAH patients and healthy controls revealed significantly higher uptake in IPAH lungs as compared with controls, confirming that the glycolytic rate was increased in vivo. Thus, there are substantial changes in bioenergetics of IPAH endothelial cells, which may have consequences for pulmonary hypertensive responses and potentially in development of novel imaging modalities for diagnosis and evaluation of treatment.
The Timing and Effort of Lexical Access in Natural and Degraded Speech

Understanding speech is effortless in ideal situations, and although adverse conditions, such as caused by hearing impairment, often render it an effortful task, they do not necessarily suspend speech comprehension. A prime example of this is speech perception by cochlear implant users, whose hearing prostheses transmit speech as a significantly degraded signal. It is yet unknown how mechanisms of speech processing deal with such degraded signals, and whether they are affected by effortful processing of speech. This paper compares the automatic process of lexical competition between natural and degraded speech, and combines gaze fixations, which capture the course of lexical disambiguation, with pupillometry, which quantifies the mental effort involved in processing speech. Listeners’ ocular responses were recorded during disambiguation of lexical embeddings with matching and mismatching durational cues. Durational cues were selected due to their substantial role in listeners’ quick limitation of the number of lexical candidates for lexical access in natural speech. Results showed that lexical competition increased mental effort in processing natural stimuli in particular in presence of mismatching cues. Signal degradation reduced listeners’ ability to quickly integrate durational cues in lexical selection, and delayed and prolonged lexical competition. The effort of processing degraded speech was increased overall, and because it had its sources at the pre-lexical level this effect can be attributed to listening to degraded speech rather than to lexical disambiguation. In sum, the course of lexical competition was largely comparable for natural and degraded speech, but showed crucial shifts in timing, and different sources of increased mental effort. We argue that well-timed progress of information from sensory to pre-lexical and lexical stages of processing, which is the result of perceptual adaptation during speech development, is the reason why in ideal situations speech is perceived as an undemanding task. Degradation of the signal or the receiver channel can quickly bring this well-adjusted timing out of balance and lead to increase in mental effort. Incomplete and effortful processing at the early pre-lexical stages has its consequences on lexical processing as it adds uncertainty to the forming and revising of lexical hypotheses.
Realization of power aware software prefetching as a multi-objective optimization problem

Software prefetching is a performance-oriented optimization technique, which is generally used to reduce the gap between processor speed and memory access speed. When software prefetching is applied to memory-intensive benchmark programs, the performance improves with higher power consumption. The present work provides a mechanism to transform a program with software prefetching to its power-aware equivalent. This is done by executing the software prefetching program at different voltage-frequency pairs. Besides reducing the power, the performance has been improved by adjusting the prefetch distance. XEEMU-Panalyzer simulator is used to evaluate the present work. Experimental results of the proposed scheme guarantees that performance improvement of software prefetching program is possible at the cost of less power consumption. The proposed work can enable a compiler to generate power aware software prefetching program.
The great divide: Exploring the attitudes of sociology and economics faculty toward certain aspects of economic globalization

The socioeconomic ramifications analysts attribute to modern economic globalization are highly varied and represent a subject of great controversy. With regard to the nature of this controversy, many analysts allege a divide exists between sociologists’ and economists’ perspectives. Using survey methodology, I explored this alleged disciplinary divide on a small scale by investigating the attitudes of sociology and economics faculty about the socioeconomic consequences of certain aspects of economic globalization – capital control reduction within international financial markets, the proliferation of transnational corporations, the implementation of NAFTA, and the functioning of international trade and financial institutions. My survey data revealed significant differences exist between the attitudes of sociology faculty and economics faculty in the sample toward the aforementioned aspects of economic globalization.
A Multiphase Routing Scheme in Irregular Mesh-Based NoCs

At present, typical application-specific NoC systems often integrate a number of heterogeneous components which have varied functions, sizes and communication requirements. Instead of regular topology networks, constructing irregular mesh topology network on chip (NoCs) becomes an attractive approach to building future NoC systems with irregular structure. Deadlock-free routing control algorithm is a promising problem for irregular mesh topology. The available routing algorithms from regular mesh are not suitable for irregular mesh network. So in this paper, we introduce a hybrid scheme multiphase routing algorithm for irregular mesh integrating oversized rectangle modules. The basic idea of the scheme is borrowed from the area of fault tolerant networks, where a network topology is rendered irregular due to fault regions. The proposed scheme only employs 2 virtual channels per physical channel with fast routing decisions. In the case that the proposed two-phase routing scheme does not keep connection between some pairs of nodes, certain healthy nodes are deactivated to guarantee its deadlock-freeness. A greedy method is presented to ensure that only the minimum nodes are deactivated.
New dimensions in regional integration: Regionalism and multilateralism: an overview

The question of ‘regionalism’, defined broadly as preferential trade agreements among a subset of nations, is a longstanding one. As with all great issues, economists have long been divided on the wisdom of such arrangements. So have policymakers. While this may not be evident to the many economists who are not inhibited by lack of comparative advantage from pronouncing on these matters, and whose pronouncements are a testimony to the enduring value of the theory of comparative advantage, preferential trade arrangements were debated by economists, as such, during the very formation of the General Agreement on Tariffs and Trade (GATT). The context, of course, was the difference between the British, led by Keynes, who were devoted to the continuation of the discrimination in Britain's favour through Imperial Preference, and the Americans, with Cordell Hull to the fore, who were strongly opposed, and embraced multilateralism and most favoured nation status (MFN) instead. Keynes, quite characteristically, at first denounced the American attachment to non-discrimination in trade and then later, when the British had virtually capitulated, celebrated its virtues with equal passion. I will juxtapose the two positions in Keynes’ inimitable words, quoted in Bhagwati (1991a): My strong reaction against the word ‘discrimination’ is the result of feeling so passionately that our hands must be free … [T]he word calls up and must call up … all the old lumber, most-favored-nation clause and all the rest which was a notorious failure and made such a hash of the old world. We know also that it won't work. It is the clutch of the dead, or at least the moribund, hand.