Miracle-dz/UniFAR-FTUs huggingface dataset:
Exchange Rate Policy and Exchange Rate Interventions: The Chilean Experience

In this paper we review Chile’s experience with exchange rate flexibility since the early 2000s. Since the abandonment of the target zone for the exchange rate at the end of the 1990s, the Central Bank of Chile has been strongly committed to exchange rate flexibility, allowing the exchange rate to fluctuate in response to different shocks. As a result, the floating regime in Chile has worked very well in different dimensions. In particular, we discuss how the credibility of the floating regime has significantly lowered the currency mismatch of assets and liabilities in the corporate sector and has enhanced the role played by exchange rate movements in adjusting the economy to financial and terms-of-trade shocks. In spite of its commitment to the floating regime, the Central Bank of Chile has intervened the exchange market on a few exceptional occasions. We review two of these interventions, which occurred in 2008 and 2011, discussing their mechanisms, effectiveness and potential drawbacks.Full publication: Market Volatility and Foreign Exchange Intervention in EMEs: What Has Changed?
CoFea: A Novel Approach to Spam Review Identification Based on Entropy and Co-Training

With the rapid development of electronic commerce, spam reviews are rapidly growing on the Internet to manipulate online customers’ opinions on goods being sold. This paper proposes a novel approach, called CoFea (Co-training by Features), to identify spam reviews, based on entropy and the co-training algorithm. After sorting all lexical terms of reviews by entropy, we produce two views on the reviews by dividing the lexical terms into two subsets. One subset contains odd-numbered terms and the other contains even-numbered terms. Using SVM (support vector machine) as the base classifier, we further propose two strategies, CoFea-T and CoFea-S, embedded with the CoFea approach. The CoFea-T strategy uses all terms in the subsets for spam review identification by SVM. The CoFea-S strategy uses a predefined number of terms with small entropy for spam review identification by SVM. The experiment results show that the CoFea-T strategy produces better accuracy than the CoFea-S strategy, while the CoFea-S strategy saves more computing time than the CoFea-T strategy with acceptable accuracy in spam review identification.
Reactive multi-agent based control of mobile robot chain formations

Abstract A Multi-agent based coordination scheme for chain formations of mobile robots, employing geometric constraint satisfaction rules, is presented. Applying this architecture on mobile robot swarms, snake-like real-time motion and reactive obstacle avoidance is achieved. A “Master – Slave” relationship is used, where a controller agent's motion is propagated to its two neighbouring ones in the chain formation and progressively further on towards the two chain endpoints. At each propagation step, a constraint preservation mechanism enforces the respect of minimum and maximum (minmax) distance constraint between agent pairs, and of minmax angular constraint among triplets of consecutive chain agents. The emergent behaviour of this multi-agent system is as if a moving part of the chain pushes or pulls the two subparts it divides the chain into. To allow replaning in case a slave part can't adapt to its master's motion, being trapped in obstacles or malfunctioning, the notion of a “Vetoable slave” behaviour is used, where the slave part can object (veto) to the motion of its master part.
Architectural practice and academic research

This paper examines one possible relationship of academic research and professional practice. It notes that this issue arises from particular national conditions that are not necessarily shared in different countries. As a result, this relationship is not equally visible or similarly understood, and hence models of research have national and even regional variations that threaten the transferability of architectural research across national boundaries, in contrast to established models of research from the sciences. The paper proposes a criterion-based response to this problem that seeks to identify common features of research and practice, thereby extending previous scholarship on the nature of academic research.
Estimating the Impact of Lygus hesperus on Cotton: The Insect, Plant, and Human Observer as Sources of Variability

Abstract Unexplained variation in the relationship between herbivore densities and the short-term appearance of crop damage is sometimes observed in pest management. Here we used a field survey of commercial cotton fields and a linked questionnaire for cooperating pest control advisors to document the existence of such unexplained variation in the impact of the western tarnished plant bug, Lygus hesperus, on upland cotton, Gossypium hirsutum. L. hesperus feeds preferentially on flower buds (“squares”), and the plant may respond to this damage with abscission of the square. We explored four classes of factors that might contribute to unexplained variation in square abscission. First, misperceptions by the human observer (i.e., sampling problems) may play a role, because commercial field scouts significantly underestimate densities of L. hesperus nymphs. Second, we found no support for the hypothesis that variable behavior expressed by L. hesperus contributes to unexplained variation in square abscission. L. hesperus seems to generate relatively predictable levels of square feeding damage; the variation that was observed was unrelated to grower categorization of fields as exhibiting normal versus unexpectedly high or low levels of square abscission. Third, variable plant responses to damage may instead be the key source of unexplained square abscission. Younger plants and plants with higher petiole phosphate concentrations expressed increased sensitivity to L. hesperus feeding; these correlations must, however, be tested experimentally before definitive conclusions are drawn. Fourth, another arthropod might be generating damage that was erroneously being attributed to L. hesperus. The omnivore Geocoris pallens was a candidate agent of cryptic damage to squares; however, an experiment showed that G. pallens generated only trivial square damage and no detectable increase in square abscission. Thus, this study has focused our attention away from the arthropod side of the interaction and toward the host plant as the primary source of greater than expected square abscission generated by L. hesperus.
M2DP: A novel 3D point cloud descriptor and its application in loop closure detection

In this paper, we present a novel global descriptor M2DP for 3D point clouds, and apply it to the problem of loop closure detection. In M2DP, we project a 3D point cloud to multiple 2D planes and generate a density signature for points for each of the planes. We then use the left and right singular vectors of these signatures as the descriptor of the 3D point cloud. Our experimental results show that the proposed algorithm outperforms state-of-the-art global 3D descriptors in both accuracy and efficiency.
Automatic semantic relation extraction from Portuguese texts

Nowadays we are facing a growing demand for semantic knowledge in computational applications, particularly in Natural Language Processing (NLP). However, there aren’t sufficient human resources to produce that knowledge at the same rate of its demand. Considering the Portuguese language, which has few resources in the semantic area, the situation is even more alarming. Aiming to solve that problem, this work investigates how some semantic relations can be automatically extracted from Portuguese texts. The two main approaches investigated here are based on (i) textual patterns and (ii) machine learning algorithms. Thus, this work investigates how and to which extent these two approaches can be applied to the automatic extraction of seven binary semantic relations (is-a, part-of, location-of, effect-of, property-of, made-of and used-for) in Portuguese texts. The results indicate that machine learning, in particular Support Vector Machines, is a promising technique for the task, although textual patterns presented better results for the used-for relation.
Treatment for Chronic Depression Using Schema Therapy

Schema therapy (ST) is an integrative treatment approach to chronic lifelong problems with an established effectiveness for treating personality disorders. This article describes the adaptation of ST to chronic depression by reviewing the literature on the underlying risk factors to chronic depression. A model of chronic depression is presented, describing the interplay between empirically supported risk factors to chronic depression (early adversity, cognitive factors, personality pathology, interpersonal factors). We provide a treatment protocol of ST for chronic depression describing techniques that can be used in ST to target these underlying risk factors. Based on the current body of empirical evidence for the underlying risk factors to chronic depression, ST appears to be a promising new treatment approach to chronic depression, as it directly targets these underlying risk factors. © 2013 American Psychological Association.
Significance of entropy correlation coefficient over symmetric uncertainty on FAST clustering feature selection algorithm

Feature selection is an essential method in which we identify a subset of most useful ones from the original set of features. On comparing results with original set and identified subset, we observe that the results are compatible. The feature selection algorithm is evaluated based on the components of efficiency and effectiveness, where the time required and the optimality of the subset of the feature is considered. Based on this, we are modifying the fast clustering feature selection algorithm, to check the impact of entropy correlation coefficient on it in this paper. In the algorithm, the correlation between the features is calculated using entropy correlation coefficient instead of symmetric uncertainty and then they are divided into clusters using clustering methods based on the graph. Then, the representative features i.e. those who are strongly related to the target class are selected from them. For ensuring the algorithm's efficiency, we have adopted the Kruskal minimum spanning tree (MST) clustering method. We have compared our proposed algorithm with FAST clustering feature selection algorithm on well-known classifier namely the probability-based Naive Bayes Classifier before and after feature selection. The results, on two publicly available real-world high dimensional text data, demonstrate that our proposed algorithm produces smaller and optimal features subset and also improves classifiers performance. The processing time required for the algorithm is far less than that of the FAST clustering algorithm.
Gene expression pattern Differential expression of neuropilin-1 and neuropilin-2 in arteries and veins

Neuropilin-1 (np1) and neuropilin-2 (np2) are receptors for class-3 semaphorins and for several isoforms of VEGF. We have cloned and characterized two chick isoforms of np2 cDNA. Expression patterns of np1, np2, and ephrin-B2 were compared in the developing vascular system of 24–72 h old chick embryos. We show for the first time that np2 is expressed in blood vessels in vivo from the earliest stages of their formation. In contrast to ephrin-B2, both np1 and np2 are expressed in blood islands of 24 h old chick embryos. At 48–72 h, np1 expression is localized preferentially in arteries with an expression pattern that resembles that of ephrin-B2. In contrast, np2 is expressed preferentially in veins. Thus, neuropilins may play a role in determining the arterial or venous identity of blood vessels. q 2001 Elsevier Science Ltd. All rights reserved.
KChIP2 is a core transcriptional regulator of cardiac excitability

Arrhythmogenesis from aberrant electrical remodeling is a primary cause of death among patients with heart disease. Amongst a multitude of remodeling events, reduced expression of the ion channel subunit KChIP2 is consistently observed in numerous cardiac pathologies. However, it remains unknown if KChIP2 loss is merely a symptom or involved in disease development. Using rat and human derived cardiomyocytes, we identify a previously unobserved transcriptional capacity for cardiac KChIP2 critical in maintaining electrical stability. Through interaction with genetic elements, KChIP2 transcriptionally repressed the miRNAs miR-34b and miR-34c, which subsequently targeted key depolarizing (INa) and repolarizing (Ito) currents altered in cardiac disease. Genetically maintaining KChIP2 expression or inhibiting miR-34 under pathologic conditions restored channel function and moreover, prevented the incidence of reentrant arrhythmias. This identifies the KChIP2/miR-34 axis as a central regulator in developing electrical dysfunction and reveals miR-34 as a therapeutic target for treating arrhythmogenesis in heart disease. DOI: http://dx.doi. org/10.7554/eLife.17304. 001
Receptor encoding of moving tactile stimuli in humans. I. Temporal pattern of discharge of individual low-threshold mechanoreceptors

The response of 70 cutaneous, low-threshold mechanoreceptors in the human median, radial and inferior alveolar nerves to well controlled brush stimuli moving across the receptive field was quantitatively studied. Microneurography was used to obtain the response of each to multiple velocities from 0.5 to 32 cm/sec in at least two opposing directions. A high degree of response consistency was observed from the slowly adapting receptors to replication of the same stimulus and to a lesser, but significant degree from the fast adapting receptors. The evoked discharge reflected up to three partially overlapping phases of the moving stimulus: skin compression, indentation, and stretch. Although the overall discharge rate increased with both stimulus velocity and force, the spatial discharge pattern was preserved to a high degrees. In contrast, the discharge patterns differed for opposing and orthogonal directions. Reducing the area of skin surrounding the receptive field that was contacted by the moving stimuli had little effect on the evoked response. Individual mechanoreceptors display highly reliable differences to brush stimuli moving at different velocities. to brush stimuli moving at different velocities. Moreover, different directions of movement evoke differences in the discharge that are consistently observed upon replication of the same stimuli. Despite the richness and consistency in the spatial discharge pattern displayed by individual receptors, it is argued that the details of the patterns are not likely used by the CNS to infer information about direction and velocity of movement across the skin. Rather, the intensity of discharge is proposed as a plausible information-bearing attribute of the stimulus-evoked response.
A novel chaotic neural network with Morlet-wavelet activation function

The new model can solve the 10-city traveling salesman problem more effectively because of Morlet wavelet being a kind of basic function. First, the chaotic dynamics of the neuron was analyzed, and the figures of the reversed bifurcation and the maximal Lyapunov exponents of single neural unit were given. Second, the new model was applied to solve function optimizations and the evolution figures of the energy function were plotted. Finally, 10-city traveling salesman problem was given and simultaneously a group of parameters for the network in solving the 10-city traveling salesman problem were proved to be efficient by the computer simulation. Seen from the simulation results, the new model is powerful.
Energy efficient Routing protocol using Clustering Technique

The past few years have witnessed increased interest in the potential use of wireless sensor networks (WSNs) in applications such as disaster management, combat field reconnaissance, border protection and security surveillance. Sensors in these applications are expected to be remotely deployed in large numbers and to operate autonomously in unattended environments. The sensor nodes deployed in wireless sensor networks are extremely power constrained, so maximizing the lifetime of the entire networks is mainly considered in the design. In this paper, we proposed An energy efficient clustering algorithm with optimum parameters is designed for reducing the energy consumption and prolonging the system lifetime. Using a wireless sensor network, variety applications are being developed. Clustering of a sensor nodes elect to cluster head from among the sensor nodes and cluster heads to the sink node is configured a clustering and cluster head changing depends upon the available energ. The clustering Algorithm is a kind of key technique used to reduce energy consumption. It can increase the scalability and lifetime of the network. Energy-efficient clustering protocols should be designed for the characteristic of heterogeneous wireless sensor
VM-tracking: Visual-motion sensing integration for real-time human tracking

Human tracking in video has many practical applications such as visual guided navigation, assisted living, etc. In such applications, it is necessary to accurately track multiple humans across multiple cameras, subject to real-time constraints. Despite recent advances in visual tracking research, the tracking systems purely relying on visual information fail to meet the accuracy and real-time requirements at the same time. In this paper, we present a novel accurate and real-time human tracking system called VM-Tracking. The system aggregates the information of motion (M) sensor on human, and integrates it with visual (V) data based on physical locations. The system has two key features, i.e. location-based VM fusion and appearance-free tracking, which significantly distinguish itself from other existing human tracking systems. We have implemented the VM-Tracking system and conducted comprehensive experiments on challenging scenarios.
Effect of Different pH on Canthaxanthin Degradation C

In this research, natural canthaxanthin as one of the most important carotenoids was extracted from Dietzia natronolimnaea HS-1. The changes of canthaxanthin enriched in oilin-water emulsions with vegetable oil (5 mg/ 100 mL), Arabic gum (5 mg/100 mL), and potassium sorbate (0.5 g/100 mL) was investigated. The effects of different pH (3, 5 and 7), as well as, time treatment (3, 18 and 33 days) in the environmental temperature (24°C) on the degradation were studied by response surface methodology (RSM). The Hunter values (L*, a*, and b*) and the concentration of canthaxanthin (C, mg/L) illustrated more degradation of this pigment at low pHs (pH≤ 4) by passing the time (days≥10) with R2 97.00%, 91.31%, 97.60%, and 99.54% for C, L*, a*, and b* respectively. The predicted model were found to be significant (p<0.05). Keywords—Degradation, Emulsion, Response Surface Methodology (RSM)
Simulation of energy consumption in a microgrid for demand side management by scheduling

Energy management systems (EMS) are necessary when smart grids and microgrids are considered. Simulation of energy consumption is very useful in planning and testing such systems. In this article we present the problems of simulating energy consumption and show concept of a very general load simulator. The simulator can generate time series of consumption from fixed profiles and also from the defined rules describing use of energy by the devices. The rules describe the probabilistic distribution of the device behaviour. The architecture of the implementation is also presented.
Model-Based Search for Statistical Machine Translation

I address the complexity problem of phrase-base translation model. I view the problem of machine translation as to find compact models having Minimum Description Length (MDL). Then I apply model merging on translation model to find compact models. This method uses the Joint-Probability Phrase-base Model as the initial model, and then gradually eliminates redundant translation entries according to the MDL principle. The size of result translation model is only 1% of the initial model, along with comparable performance.
Silence of NLRP3 Suppresses Atherosclerosis and Stabilizes Plaques in Apolipoprotein E-Deficient Mice

Objectives. The role of the NLRP3 inflammasome in atherosclerosis remains controversial. The aim of this study was to determine whether inhibition of NLRP3 signaling by lentivirus-mediated RNA interference could reduce atherosclerosis and stabilizes plaques. We also tried to explore the mechanisms of the impact of NLRP3 inflammasome on atherosclerosis. Methods. Apolipoprotein E-deficient mice aged 8 weeks were fed a high-fat diet and were injected with NLRP3 interfering or mock viral suspension after 4 weeks. Lentivirus transfer was repeated in 2 weeks. Four weeks after the first lentivirus injection, we evaluated the effects of NLRP3 gene silencing on plaque composition and stability and on cholesterol efflux and collagen metabolism, by histopathologic analyses and real-time PCR. Results. Gene silence of NLRP3 prevented plaques progression and inhibited inductions of proinflammatory cytokines. Moreover, this RNA interference reduced plaque content of macrophages and lipid, and increased plaque content of smooth muscle cells and collagen, leading to the stabilizing of atherosclerotic plaques. Conclusions. NLRP3 inflammasomes may play a vital role in atherosclerosis, and lentivirus-mediated NLRP3 silencing would be a new strategy to inhibit plaques progression and to reduce local inflammation.
Primer Master: a new program for the design and analysis of PCR primers

The polymerase chain reaction (PCR) is one of the most rapidly expanding methods in molecular biology. Although the range of applications of PCR is very broad, the key points for successful performance remain the careful selection of optimal primers and the proper determination of the temperature conditions of the reaction. The program presented here, 'Primer Master', has been developed to assist in solving these problems for two major types of PCR: the amplification of the appropriate fragments of several related, but not identical, sequences and the specific amplification of a certain fragment of only one nucleotide sequence where amplification of any other sequence needs to be prevented. Unlike other programs developed for the design of PCR primers, 'Primer Master' undertakes an automatic search and selection of the optimal primers and primer pairs for both types of reaction. The wide applicability of'Primer Master' is determined by two main automatic search regimes: 'Universal' and 'Specific'. The 'Universal' regime searches and selects primers and primer pairs which amplify the designated fragments of all required sequences (consensus primers) and allows a 'combined search', where the universal primers for a particular group of sequences must not amplify any sequence from another group. The number of sequences allowed is 2 to 100, with a maximum length of 65 000 nucleotides. The 'Specific' regime is designed to select the primers and primer pairs which amplify the fragment of a specific nucleotide sequence from all those the user wishes to consider. The total number of sequences to be tested is unlimited, and sequences up to 32000 nucleotides in length are allowed. 'Primer Master' also incorporates a number of special features designed to overcome problems common to PCR. Within the 'Specific' regime it may be necessary to find primers from one of several related sequences. However, if the sequences span different positions then there is the risk that the primers chosen may include regions absent from