Miracle-dz/UniFAR-FTUs huggingface dataset:
An Empirical Analysis of Trade and Economic Growth in Libya

ABSTRACT This research is an empirical analysis of trade led growth of Libya during 1963-2008. Overall objective of this research is to investigate the role of international trade on Libya’s economy through reviewing various phases of economic growth in Libya starting from 1963. During this period, Libyan economy has undergone various structural changes. Not only has oil been one of its main exporting commodities, but also earnings from this sector of the Libyan economy have been credited with high growth rates experienced in the country. The research comprise of five specific objectives of which four require empirical justification. The non-empirical objective of the research is to obtain a trade profile of Libya. The empirical objectives include the analysis of relationship between trade and economic growth of Libya with and without incorporating the role of trade partners and the development of import demand in Libya with and without incorporating expenditure component. Results of the research showed that Libya is significantly dependent on international trade with countries of European Union; however, feedback effect from these countries is low. Mostly, Libya depends on the trade partners to cover the import demand. Import demand of the country is determined via price level instead of the income of the country. The only expenditure in Libya out of household consumption, government consumption, and investment, investment has sing incant effect on the price level. Therefore, for Libya to receive tread led growth, the country should employ such policies that favour total investment.
Academic Language Instruction for Students in Grades 4 Through 8: A Literature Synthesis

Abstract Academic language, which is characterized by the words and structure of the language of schooling, is an important teachable component of academic achievement. When compared to other strong predictors of academic achievement (e.g., decoding, fluency, vocabulary, comprehension), academic language is not as well understood or explicitly taught in schools. The purpose of this literature synthesis is to identify the instructional practices that currently have the best evidence to improve academic language and broader academic achievement outcomes. The most prolific study of academic language instruction occurs with English learner samples. In the current study, we sought high-quality empirical intervention studies conducted with English learners. We describe the components of instruction that explicitly address academic language skills, and we describe the impact on outcomes for English learner students as well as their English-only peers.
The Ravenscar profile for high-integrity Java programs?

The Ravenscar Profile was a major output of the 8th International Real-Time Ada Workshop. The profile defines a subset of the Ada95 tasking constructs that matches the requirements of Safety Critical, High Integrity and Hard Real-Time systems by eliminating constructs with high overhead or non-deterministic behavior (semantically or temporally) whilst retaining those elements that form the basic building blocks for constructing analyzable real-time systems.The recent explosion in interest and use of the Java&trade; platform for embedded devices has exposed basic flaws in the semantics of its real-time constructs, and this has led to initiatives to extend the language to address these weaknesses. Key personnel involved in the definition of the Real-Time Annex for Ada95 and the Ravenscar Profile also influenced the design of the real-time extensions to Java&trade;, and so it is not surprising that these extensions follow closely the experiences learned from Ada.This paper describes the proposed set of extensions to Java&trade; to support real-time and high integrity systems, drawing parallels with the Ravenscar Profile definition. It suggests the possibility of co-existence and interoperability of Ravenscar-compliant Ada and RT-Java partitions within a high integrity or safety critical system.
Embedded Predictive Control on an FPGA using the Fast Gradient Method

Model predictive control (MPC) in resource-constrained embedded platforms requires faster, cheaper and more power-efficient solvers for convex programs than is currently offered by software-based solutions. In this paper we present the first field programmable gate array (FPGA) implementation of a fast gradient solver for linear-quadratic MPC problems with input constraints. We use fixed-point arithmetic to exploit the characteristics of the computing platform and provide analytical guarantees ensuring no overflow errors occur during operation. We further prove that the arithmetic errors due to round-off can lead only to reduced accuracy, but not instability, of the fast gradient method. The results are demonstrated on a model of an industrial atomic force microscope (AFM) where we show that, on a low-end FPGA, satisfactory control performance at a sample rate beyond 1 MHz is achievable, opening up new possibilities for the application of MPC.
Getting by with a Little Help from the Crowd: Practical Approaches to Social Image Labeling

Validating user tags helps to refine them, making them more useful for finding images. In the case of interpretation-sensitive tags, however, automatic (i.e., pixel-based) approaches cannot be expected to deliver optimal results. Instead, human input is the key. This paper studies how crowdsourcing-based approaches to image tag validation can achieve parsimony in their use of human input from the crowd, in the form of votes collected from workers on a crowdsourcing platform. Experiments in the domain of social fashion images are carried out using the dataset published by the Crowdsourcing Task of the Mediaeval 2013 Multimedia Benchmark. Experimental results reveal that when a larger number of crowd-contributed votes are available, it is difficult to beat a majority vote. However, additional information sources, i.e., crowdworker history and visual image features, allow us to maintain similar validation performance while making use of less crowd-contributed input. Further, investing in "expensive" experts who collaborate to create definitions of interpretation-sensitive concepts does not necessarily pay off. Instead, experts can cause interpretations of concepts to drift away from conventional wisdom. In short, validation of interpretation-sensitive user tags for social images is possible, with "just a little help from the crowd".
Title: Differential Activity-dependent, Homeostatic Plasticity of Two Neocortical Inhibitory Circuits Running Head: Differential Activity-dependent Plasticity of Inhibitory Circuits

Chronic changes in neuronal activity homeostatically regulate excitatory circuitry. However, little is known about how activity regulates inhibitory circuits or specific inhibitory neuron types. Here, we examined the activity-dependent regulation of two neocortical inhibitory circuits – parvalbumin-positive (Parv+) and somatostatin-positive (Som+) – using paired recordings of synaptically coupled neurons. Action potentials were blocked for 5 days in slice culture, and unitary synaptic connections among inhibitory/excitatory neuron pairs were examined. Chronic activity blockade caused similar and distinct changes between the two inhibitory circuits. First, increases in intrinsic membrane excitability and excitatory synaptic drive in both inhibitory subtypes were consistent with the homeostatic regulation of firing rate of these neurons. On the other hand, inhibitory synapses originating from these two subtypes were differentially regulated by activity blockade. Parv+ unitary IPSC (uIPSC) strength was decreased while Som+ uIPSC strength was unchanged. Using short duration stimulus trains, short-term plasticity for both uEPSCs and uIPSCs was unchanged in Parv+ circuitry while distinctively altered in Som+ circuitry uEPSCs became less facilitating and uIPSCs became more depressing. In the context of recurrent inhibition, these changes would result in a frequency-dependent shift in the relative influence of each circuit. The functional changes at both types of inhibitory connections appear to be mediated by increases in presynaptic release probability and decreases in synapse number. Interestingly, these opposing changes result in decreased Parv+ mediated uIPSCs, but balance out to maintain normal Som+ mediated uIPSCs. In summary, these results reveal that inhibitory circuitry is not uniformly regulated by activity levels and may provide insight into the mechanisms of both normal and pathological neocortical plasticity.
An incremental local-first community detection method for dynamic graphs

Community detections for large-scale real world networks have been more popular in social analytics. In particular, dynamically growing network analyses become important to find long-term trends and detect anomalies. In order to analyze such networks, we need to obtain many snapshots and apply same analytic methods to them. However, it is inefficient to extract communities from these whole newly generated networks with little differences every time, and then it is impossible to follow the network growths in the real time. We proposed an incremental community detection algorithm for high-volume graph streams. It is based on the top of a well-known batch-oriented algorithm named DEMON [1]. We also evaluated performance and precisions of our proposed incremental algorithm with real-world big networks with up to 410,236 vertices and 2,439,437 edges and computed in less than one second to detect communities in an incremental fashion — which achieves up to 107 times faster than the original algorithm without sacrificing accuracies.
Strategic communication in exponential bandit problems

We generalize Keller, Rady and Cripps’s [2005] model of strategic experimentation by assuming that transfers of information between players are costly. We introduce costly communication in three different ways. First, we consider the Paying to exchange information game: the exchange of information between players occurs if and only if both payed the communication cost. Second, we consider the Paying to buy information case, where players pay the cost to observe their opponent’s action. Finally, we study the Paying to give information case, where players pay the communication cost to display their actions and outcomes. We study the existence and the structure of equilibria in each setting. We show that making communication costly is efficient, in the sense that it decreases free-riding, and increases the speed of learning at equilibrium.
Sunk Costs and Risk-Based Barriers to Entry

In merger analysis and other antitrust settings, risk is often cited as a potential barrier to entry. But there is little consensus as to the kinds of risk that matter - systematic versus non-systematic and industry-wide versus firm-specific - and the mechanisms through which they affect entry. I show how and to what extent different kinds of risk magnify the deterrent effect of exogenous sunk costs of entry, and thereby affect industry dynamics, concentration, and equilibrium market prices. To do this, I develop a measure of the "full," i.e., risk-adjusted, sunk cost of entry. I show that for reasonable parameter values, the full sunk cost is far larger than the direct measure of sunk cost typically used to analyze markets.
Generalist diurnal pollination provides greater fitness in a plant with nocturnal pollination syndrome: assessing the effects of a Silene Hadena interaction

Nursery pollination in Caryophyllaceae species by Hadena and Perizoma moths has been extensively described in the last few decades. Evidence across multiple pairs of species shows that such pollination systems constitute relatively specialized interactions, shifting between parasitism and mutualism depending on the presence of effective co-pollinators. In this work, we describe a new specific Silene-Hadena interaction, the Silene ciliataHadena consparcatoides system. Although S. ciliata presents a typical nocturnal pollination syndrome, diurnal flower visitors have also been recorded, which motivated us to evaluate the costs and benefits of this nursery moth pollination to the plant. We experimentally induced two pollination regimes at non-overlapping day-night periods in a natural population of S. ciliata , and compared their effects on plant reproductive success from flower to seedling stages. Flower scent composition of S. ciliata and antennal responses of H. consparcatoides to this scent were recorded to evaluate the specificity of olfactory signals in this interaction system. In accordance with its nocturnal pollination syndrome, S. ciliata emitted a greater amount of flower scent compounds during the night. Some of the predominant scent compounds, such as benzaldehyde, benzyl acetate and methyl salicylate elicited signals in the antennae of H. consparcatoides . Diurnal pollination produced more fruits per flower than nocturnal pollination, but the latter produced higher brood size resulting in similar overall fecundity. However, seeds generated from diurnal pollination were heavier and germinated better. We conclude that despite its nocturnal pollination syndrome, S. ciliata achieved similar reproductive success and higher offspring vigour under the diurnal pollinator regime. Although H. consparcatoides is specialized in S. ciliata , its shortage or absence would not jeopardize the reproductive success of its host plant. On the contrary, the seed predation exerted by this nursery pollinator shifts the interaction towards parasitism.
The Different Physical Mechanisms that Drive the Star-Formation Histories of Giant and Dwarf Galaxies

We present an analysis of star formation and nuclear activity in galaxies as a function of both luminosity and environment in the fourth data release of the Sloan Digital Sky Survey. Using a sample of 27 753 galaxies in the redshift range 0.005 < z < 0.037 that is ≥90 per cent complete to M r = -18.0, we find that the Ha equivalent width, EW(Hα), distribution is strongly bimodal, allowing galaxies to be robustly separated into passively evolving and star-forming populations about a value EW(Ha) = 2 A. In high-density regions ∼70 per cent of galaxies are passively evolving independent of luminosity. In the rarefied field, however, the fraction of passively evolving galaxies is a strong function of luminosity, dropping from 50 per cent for M r ≤ -21 to zero by M r ∼ -18. Indeed for the lowest luminosity range covered (-18 < M r < -16) none of the ∼600 galaxies in the lowest-density quartile is passively evolving. The few passively evolving dwarf galaxies in field regions appear as satellites to bright (≥ L*) galaxies. We find a systematic reduction of ∼30 per cent in the Ha emission from dwarf (-19 < M r < - 18) star-forming galaxies in high-density regions with respect to field values, implying that the bulk of star-forming dwarf galaxies in groups and clusters are currently in the process of being slowly transformed into passive galaxies. The fraction of galaxies with the optical signatures of an active galactic nucleus (AGN) decreases steadily from ∼50 per cent at M r ∼ -21 to ∼0 per cent by M r ∼ -18 closely mirroring the luminosity dependence of the passive galaxy fraction in low-density environments. This result reflects the increasing importance of AGN feedback with galaxy mass for their evolution, such that the star formation histories of massive galaxies are primarily determined by their past merger history. In contrast, the complete absence of passively evolving dwarf galaxies more than ∼2 virial radii from the nearest massive halo (i.e. cluster, group or massive galaxy) indicates that internal processes, such as merging, AGN feedback or gas consumption through star formation, are not responsible for terminating star formation in dwarf galaxies. Instead the evolution of dwarf galaxies is primarily driven by the mass of their host halo, probably through the combined effects of tidal forces and ram-pressure stripping.
Does the inferior frontal sulcus play a functional role in deception? A neuronavigated theta-burst transcranial magnetic stimulation study

By definition, lying involves withholding the truth. Response inhibition may therefore be the cognitive function at the heart of deception. Neuroimaging research has shown that the same brain region that is activated during response inhibition tasks, namely the inferior frontal region, is also activated during deception paradigms. This led to the hypothesis that the inferior frontal region is the neural substrate critically involved in withholding the truth. In the present study, we critically examine the functional necessity of the inferior frontal region in withholding the truth during deception. We experimentally manipulated the neural activity level in right inferior frontal sulcus (IFS) by means of neuronavigated continuous theta-burst stimulation (cTBS). Individual structural magnetic resonance brain images (MRI) were used to allow precise stimulation in each participant. Twenty-six participants answered autobiographical questions truthfully or deceptively before and after sham and real cTBS. Deception was reliably associated with more errors, longer and more variable response times than truth telling. Despite the potential role of IFS in deception as suggested by neuroimaging data, the cTBS-induced disruption of right IFS did not affect response times or error rates, when compared to sham stimulation. The present findings do not support the hypothesis that the right IFS is critically involved in deception.
On the use of traffic monitoring and measurements for improving networking

Several recent traffic monitoring studies proved that traffic is highly variable (sometimes not stationary), and in any cases exhibiting many disruptions in its throughput, that of course are damaging for providing a stable QoS. If some of these disruptions can be legitimate variations of traffic (because a user suddenly generates a big flow or because of a flash crowd), others may be due to DoS attacks. This paper presents the use of monitoring and measurement techniques for improving networking. In particular, it gives examples on how to operate TCP/IP level traffic engineering mechanisms, and how to use monitoring as a countermeasure for DoS attacks. All contribute to the provision and maintenance of end-to-end QoS in the presence of traffic disruptions, due to user demand (normal or abnormal) or to malicious behaviour.
Comparison of iterative sparse recovery algorithms

Most signals can be represented sparsely in a basis. Recently, Compressive Sensing Theorem which offers convex optimization algorithms based on ℓ1-minimization for sparse signal recovery is often being used. In this paper, some of the iterative signal recovery algorithms alternative to ℓ1-minimization solution which are Orthogonal Matching Pursuit (OMP), Compressive Sampling Matching Pursuit (CoSaMP), Iterative Hard Thresholding (IHT) and Lipschitz Iterative Hard Theresholding (LIHT) are compared in noisy and noiseless conditions with various tests. Iterative algorithms alternative to the ℓ1 optimization method with similar performance are verified. OMP algorithm that works at higher true reconstruction rates in noisy and noiseless conditions can be preferred instead of convex optimization methods.
Automated diagnosis of software misconfigurations based on static analysis

Software configuration settings are an effective way to customize applications. However, inconsistencies or mistakes in option values can result in a system crash and need huge time and effort to diagnose. We present a technique to identify the root causes of configuration errors. It uses static program analysis to link the misconfiguration of an application to a specific configuration option. Our technique has two prominent characteristics compared to existing approaches: it relies only on static analysis, and it does not need profiles of the application with correct configuration. Based on the proposed techniques, we developed a tool called ConfDebugger. We evaluated its effectiveness on 8 configuration errors in the Java program JChord. ConfDebugger successfully diagnosed 7 out of 8 errors. For 5 of them, root cause was exactly pinpointed without a false positive, and in total, the average number of false positives was only 0.5. This is better than two state-of-the-art methods, with average numbers of false positives of 1.7 and 5.7, respectively.
Incremental Tree Induction

Analyzing data streams has in the recent years gained significant interest. This is mainly powered by the need to be able to classify over a continuos flow of data, for example for credit card fraud detection or human behaviour monitoring. This requires a high speed algorithm in order to be able to keep up with the data. While this is already a hard task, the task becomes more challenging since the underlying logic that generates the stream of data usually isn’t static. For example people their behaviour might change over times, such flexibility in the data is know as ’concept drifting’. In this article i describe a technique i have implemented that tackles both challenge successfully. The technique works on the basis of a Genetic Algorithm, this is remarkable since GAs are commonly thought of to be slow.
Reorganization of genera in the families Rickettsiaceae and Anaplasmataceae in the order Rickettsiales: unification of some species of Ehrlichia with Anaplasma, Cowdria with Ehrlichia and Ehrlichia with Neorickettsia, descriptions of six new species combinations and designation of Ehrlichia equi and

The genera Anaplasma, Ehrlichia, Cowdria, Neorickettsia and Wolbachia encompass a group of obligate intracellular bacteria that reside in vacuoles of eukaryotic cells and were previously placed in taxa based upon morphological, ecological, epidemiological and clinical characteristics. Recent genetic analyses of 16S rRNA genes, groESL and surface protein genes have indicated that the existing taxa designations are flawed. All 16S rRNA gene and groESL sequences deposited in GenBank prior to 2000 and selected sequences deposited thereafter were aligned and phylogenetic trees and bootstrap values were calculated using the neighbour-joining method and compared with trees generated with maximum-probability, maximum-likelihood, majority-rule consensus and parsimony methods. Supported by bootstrap probabilities of at least 54%, 16S rRNA gene comparisons consistently clustered to yield four distinct clades characterized roughly as Anaplasma (including the Ehrlichia phagocytophila group, Ehrlichia platys and Ehrlichia bovis) with a minimum of 96.1% similarity, Ehrlichia (including Cowdria ruminantium) with a minimum of 97.7% similarity, Wolbachia with a minimum of 95.6% similarity and Neorickettsia (including Ehrlichia sennetsu and Ehrlichia risticii) with a minimum of 94.9% similarity. Maximum similarity between clades ranged from 87.1 to 94.9%. Insufficient differences existed among E. phagocytophila, Ehrlichia equi and the human granulocytic ehrlichiosis (HGE) agent to support separate species designations, and this group was at least 98.2% similar to any Anaplasma species. These 16S rRNA gene analyses are strongly supported by similar groESL clades, as well as biological and antigenic characteristics. It is proposed that all members of the tribes Ehrlichieae and Wolbachieae be transferred to the family Anaplasmataceae and that the tribe structure of the family Rickettsiaceae be eliminated. The genus Anaplasma should be emended to include Anaplasma (Ehrlichia) phagocytophila comb. nov. (which also encompasses the former E. equi and the HGE agent), Anaplasma (Ehrlichia) bovis comb. nov. and Anaplasma (Ehrlichia) platys comb. nov., the genus Ehrlichia should be emended to include Ehrlichia (Cowdria) ruminantium comb. nov. and the genus Neorickettsia should be emended to include Neorickettsia (Ehrlichia) risticii comb. nov. and Neorickettsia (Ehrlichia) sennetsu comb. nov.