Miracle-dz/UniFAR-FTUs huggingface dataset:
Information Spreading in Expanding Wordnet Hypernymy Structure

The paper presents a wordnet expansion algorithm, which is based on lexicosemantic relations extracted from large text corpora. We do not assume that the extracted relation instances (i.e. word pairs) are described by probabilities. Thus, results produced by any method, including pattern-based and Distributional Semantics approaches can be used. The algorithm is based on a general spreading activation model. Support for word-to-word semantic associations is first mapped on the existing wordnet structure. Next, the support is spread over the wordnet network in order to find attachment areas for a new word. Evaluation and comparison with other approaches in experiments on Princeton WordNet 3.0 is presented.
Methods for performance evaluation of VBR video traffic models

Models for predicting the performance of multiplexed variable bit rate video sources are important for engineering a network. However, models of a single source are also important for parameter negotiations and call admittance algorithms. In this paper we propose to model a single video source as a Markov renewal process whose states represent different bit rates. We also propose two novel goodness-of-fit metrics which are directly related to the specific performance aspects that we want to predict from the model. The first is a leaky bucket contour plot which can be used to quantify the burstiness of any traffic type. The second measure applies only to video traffic and measures how well the model can predict the compressed video quality. >
Duffy Blood Group System and the malaria adaptation process in humans

Malaria is an acute infectious disease caused by the protozoa of the genus Plasmodium. The antigens of the Duffy Blood Group System, in addition to incompatibilities in transfusions and hemolytic disease of the newborn, are of great interest in medicine due to their association with the invasion of red blood cells by the parasite Plasmodium vivax. For invasions to occur an interaction between the parasites and antigens of the Duffy Blood Group System is necessary. In Caucasians six antigens are produced by the Duffy locus (Fya, Fyb, F3, F4, F5 and F6). It has been observed that Fy(a-b-) individuals are resistant to Plasmodium knowlesi and P. vivax infection, because the invasion requires at least one of these antigens. The P. vivax Duffy Binding Protein (PvDBP) is functionally important in the invasion process of these parasites in Duffy / DARC positive humans. The proteins or fractions may be considered, therefore, an important and potential inoculum to be used in immunization against malaria.
Dynamic Texture Synthesis Using Motion Distribution Statistics

In this paper we propose a motion based approach for synthesizing dynamic textures. Dynamic textures are natural phenomenon characterized by their distinctive motion patterns. Synthesis of these textures is thus considered as the regeneration of a motion pattern that has identical motion distribution of a source texture. In this paper we propose a synthesis technique where new textures are generated by computing their movement pattern from a known motion distribution followed by the generation of image frames. Experimental results demonstrate the ability of the proposed technique by producing visually promising dynamic textures.
The Impact of the Global Financial Crisis on The Economy of Sierra Leone

GLOBAL CRISIS AND POVERTY PREVENTION Most recent statistics indicate that the global financial crisis will cause a fall in export earnings in Sierra Leone of approximately fifteen percent in 2009 compared to 2008. A regression-based model estimates that this decline in exports earnings could result in a fall in national income of almost ten percent. Based on the income distribution in the 2003 household survey, a ten percent decline in national income would increase poverty by twelve percent of the population, or about 600,000 people. A fiscal stimulus of two percent of GDP could stabilise the economy at the level of 2008, preventing this disastrous increase in poverty. A stimulus package consisting of employment intensive public works programmes could be designed to return the economy to its pre-shock level with a reduction in poverty. (.)
Tourist Arrivals in India: How Important are Domestic Disorders

The Indian Tourism Industry has flourished in the past few years, significantly contributing to the nation's Gross Domestic Product, foreign exchange earning and employment. India with her enriched natural beauty is unambiguously one of the most viable candidates for promoting tourism. Since the past few years, Government of India has undertaken various measures to promote tourism; but its' benefits has not attained the maximum. This paper is an attempt to analyse empirically the determinants of international tourist arrivals in India using annual data from 1966 to 2000. The results document that socio-political factors, viz. communalism, terrorism and Indo-Pak tensions place serious threats to the tourism industry putting limits on the gains that could have been potentially realized.
Approximation-aware rewriting of AIGs for error tolerant applications

Approximation circuits offer superior performance (speed and area) compared to traditional circuits at the cost of computational accuracy. The accuracy of the results in approximation circuits is evaluated based on several error metrics such as worst-case error, bit-flip error, or error-rate. Several applications have varied requirements in error metrics, i.e., all the error criteria have to be met together at a time, or in combinations. Nevertheless, all applications benefit from improved delay and area. An automated synthesis approach with formal guarantees on error metrics is very helpful in generating circuits that meet these criteria. Furthermore, each of these metrics are independent quantities (value of one metric does not correlate with the other), and automated synthesis can discover opportunities to trade off one or more of the relaxed metrics with a strict requirement on the other, resulting in better performance. In this paper, we present an automatic synthesis approach using And-Inverter Graphs (AIGs) based rewriting that not only improves the performance but also guarantees the bounds of approximation errors introduced. Our synthesis approach is evaluated on a wide range of designs and standard benchmark circuits to show the usefulness and applicability. In particular, we show that our synthesis results are even comparable with the optimization achieved with hand crafted adhoc approximation circuits such as approximation adders in a case study on image compression.
The Data Complexity of Description Logic Ontologies

We analyze the data complexity of ontology-mediated querying where the ontologies are formulated in a description logic (DL) of the ALC family and queries are conjunctive queries, positive existential queries, or acyclic conjunctive queries. Our approach is non-uniform in the sense that we aim to understand the complexity of each single ontology instead of for all ontologies formulated in a certain language. While doing so, we quantify over the queries and are interested, for example, in the question whether all queries can be evaluated in polynomial time w.r. t. a given ontology. Our results include a PTime/coNP-dichotomy for ontologies of depth one in the description logic ALCFI, the equivalence of a PTime/coNP-dichotomy for ALC and ALCI-ontologies of unrestricted depth to the famous dichotomy conjecture for CSPs by Feder and Vardi, and the failure of PTime/coNP-dichotomy theorem for ALCF-ontologies. Regarding the latter DL, we also show that it is undecidable whether a given ontology admits PTime query evaluation.
A Taste for Bargains

There is a strong intuition among many people that consumers are attracted by bargains. However, a taste for bargains has been difficult to identify. The results of marketing experiments are consistent with consumers having such a taste, but their findings are not distinguished from behavior predicted by standard models in which consumers draw inferences from price. In the present study, I propose a conceptual framework that captures the psychological intuition of how bargains affect choice, and I implement two experiments that test for a taste for bargains in the absence of informational confounds. In the framework, individuals exhibiting a “taste for bargains” value not only the absolute attributes of a product but also the relative attractiveness of that product within a comparison set. Assuming that the comparison set contains objects that are similar in nature, the experiments test the following hypotheses: (1) that consumers attach positive value to bargains; and (2) that consumers attach negative value to bad deals, or ‘anti-bargains. ’ I induced bargains by varying the prices of comparable products. To eliminate any inference about product value, I announced in advance that all prices were selected at random. I found evidence for a bargain effect (although, not uniformly across experiments): that is, people are more likely to purchase a product when it appears next to a worse-looking alternative than when it sells alone. I also found evidence for an anti-bargain effect: that is, people are less likely to purchase a product when told of a counterfactual store selling a similar product at a randomly-assigned lower price. I estimate both effects to be moderately sized, increasing or decreasing demand by as much as 10% to 20%. ∗This paper was heavily influenced by the comments and suggestions of Matthew Rabin. I owe thanks to Stefano DellaVigna, Shachar Kariv, Botond Koszegi, Teck Ho, Miguel Villas-Boas, Kristine Brown, Raj Chetty, Ulrike Malmendier, and Dushyanth Reddivari for their many helpful suggestions. I am grateful to Institute of Business and Economic Research, the Berkeley Experimental Social Science Laboratory, the Program in Psychological Economics, and the Russell Sage Foundation for financial support.
Emergency (****); * (*): *-*

Ebola hemorrhagic fever (EHF) was first reported in 1976 with two concurrent outbreaks of acute viral hemorrhagic fever centered in Yambuku (near the Ebola River), Democratic Republic of Congo, and also in Nzara, Sudan. The current outbreak of the Ebola Virus was started by reporting the first case in March 2014 in the forest regions of southeastern Guinea. Due to raising infection rates of over 13,000% within a 6-month period, now is considered as a global public health emergency and in August 8, 2014 the World Health Organization (WHO) has declared the epidemic to be a Public Health Emergency of International Concern. With more than 5000 involved cases and also nearly 3000 deaths, this event has turned to the largest and most dangerous Ebola virus outbreak in all around the world. Based on above mentioned, the present article aimed to review the virologic characteristics, transmission, clinical manifestation, diagnosis, treatment, and prevention of Ebola virus disease.
Online Adaptation of Deep Architectures with Reinforcement Learning

Online learning has become crucial to many problems in machine learning. As more data is collected sequentially, quickly adapting to changes in the data distribution can offer several competitive advantages such as avoiding loss of prior knowledge and more efficient learning. However, adaptation to changes in the data distribution (also known as covariate shift) needs to be performed without compromising past knowledge already built in into the model to cope with voluminous and dynamic data. In this paper, we propose an online stacked Denoising Autoencoder whose structure is adapted through reinforcement learning. Our algorithm forces the network to exploit and explore favourable architectures employing an estimated utility function that maximises the accuracy of an unseen validation sequence. Different actions, such as Pool, Increment and Merge are available to modify the structure of the network. As we observe through a series of experiments, our approach is more responsive, robust, and principled than its counterparts for non-stationary as well as stationary data distributions. Experimental results indicate that our algorithm performs better at preserving gained prior knowledge and responding to changes in the data distribution.
A narrative review on haptic devices: relating the physiology and psychophysical properties of the hand to devices for rehabilitation in central nervous system disorders

Purpose: This article provides rehabilitation professionals and engineers with a theoretical and pragmatic rationale for the inclusion of haptic feedback in the rehabilitation of central nervous system disorders affecting the hand. Method: A narrative review of haptic devices used in sensorimotor hand rehabilitation was undertaken. Presented papers were selected to outline and clarify the underlying somatosensory mechanisms underpinning these technologies and provide exemplars of the evidence to date. Results: Haptic devices provide kinaesthetic and/or tactile stimulation. Kinaesthetic haptics are beginning to be incorporated in central nervous system rehabilitation; however, there has been limited development of tactile haptics. Clinical research in haptic rehabilitation of the hand is embryonic but initial findings indicate potential clinical benefit. Conclusions: Haptic rehabilitation offers the potential to advance sensorimotor hand rehabilitation but both scientific and pragmatic developments are needed to ensure that its potential is realized. Implications for Rehabilitation The current lack of emphasis on somatosensory rehabilitation may contribute to poor hand recovery in patients with central nervous system pathology. Haptic technologies have the potential to improve sensation and sensory motor integration in neurological conditions. An underlying theoretical rationale is provided for the design and clinical use of haptic technologies in neuro-rehabilitation of the hand.
Spatial Structure and Activity of Sedimentary Microbial Communities Underlying a Beggiatoa spp. Mat in a Gulf of Mexico Hydrocarbon Seep

Background Subsurface fluids from deep-sea hydrocarbon seeps undergo methane- and sulfur-cycling microbial transformations near the sediment surface. Hydrocarbon seep habitats are naturally patchy, with a mosaic of active seep sediments and non-seep sediments. Microbial community shifts and changing activity patterns on small spatial scales from seep to non-seep sediment remain to be examined in a comprehensive habitat study. Methodology/Principal Findings We conducted a transect of biogeochemical measurements and gene expression related to methane- and sulfur-cycling at different sediment depths across a broad Beggiatoa spp. mat at Mississippi Canyon 118 (MC118) in the Gulf of Mexico. High process rates within the mat (∼400 cm and ∼10 cm from the mat's edge) contrasted with sharply diminished activity at ∼50 cm outside the mat, as shown by sulfate and methane concentration profiles, radiotracer rates of sulfate reduction and methane oxidation, and stable carbon isotopes. Likewise, 16S ribosomal rRNA, dsrAB (dissimilatory sulfite reductase) and mcrA (methyl coenzyme M reductase) mRNA transcripts of sulfate-reducing bacteria (Desulfobacteraceae and Desulfobulbaceae) and methane-cycling archaea (ANME-1 and ANME-2) were prevalent at the sediment surface under the mat and at its edge. Outside the mat at the surface, 16S rRNA sequences indicated mostly aerobes commonly found in seawater. The seep-related communities persisted at 12–20 cm depth inside and outside the mat. 16S rRNA transcripts and V6-tags reveal that bacterial and archaeal diversity underneath the mat are similar to each other, in contrast to oxic or microoxic habitats that have higher bacterial diversity. Conclusions/Significance The visual patchiness of microbial mats reflects sharp discontinuities in microbial community structure and activity over sub-meter spatial scales; these discontinuities have to be taken into account in geochemical and microbiological inventories of seep environments. In contrast, 12–20 cm deep in the sediments microbial communities performing methane-cycling and sulfate reduction persist at lower metabolic rates regardless of mat cover, and may increase activity rapidly when subsurface flow changes.
The perception of time while perceiving dynamic emotional faces

Emotion plays an essential role in the perception of time such that time is perceived to “fly” when events are enjoyable, while unenjoyable moments are perceived to “drag. ” Previous studies have reported a time-drag effect when participants are presented with emotional facial expressions, regardless of the emotion presented. This effect can hardly be explained by induced emotion given the heterogeneous nature of emotional expressions. We conducted two experiments (n = 44 and n = 39) to examine the cognitive mechanism underlying this effect by presenting dynamic sequences of emotional expressions to participants. Each sequence started with a particular expression, then morphed to another. The presentation of dynamic facial expressions allows a comparison between the time-drag effect of homogeneous pairs of emotional expressions sharing similar valence and arousal to heterogeneous pairs. Sequences of seven durations (400, 600, 800, 1000, 1200, 1400, 1600 ms) were presented to participants, who were asked to judge whether the sequences were closer to 400 or 1600 ms in a two-alternative forced choice task. The data were then collated according to conditions and fit into cumulative Gaussian curves to estimate the point of subjective equivalence indicating the perceived duration of 1000 ms. Consistent with previous reports, a feeling of “time dragging” is induced regardless of the sequence presented, such that 1000 ms is perceived to be longer than 1000 ms. In addition, dynamic facial expressions exert a greater effect on perceived time drag than static expressions. The effect is most prominent when the dynamics involve an angry face or a change in valence. The significance of this sensitivity is discussed in terms of emotion perception and its evolutionary significance for our attention mechanism.
Urban traffic control structure based on hybrid Petri nets

An urban network of signalized intersections can be suitably modeled as a hybrid system, in which the vehicle flow behavior is described by means of a time-driven model and the traffic light dynamics are represented by a discrete event model. In this paper, a model of such a network via hybrid Petri nets is used to state and solve the problem of coordinating several traffic lights with the aim of improving the performance of some classes of special vehicles, i.e., public and emergency vehicles. The proposed model has been validated using real traffic data relevant to the city of Torino, Italy. Some relevant experimental results are reported and discussed.
GPGPU aided method for real-time systems

Guaranteeing real-time is required in the field of digital control. This is to start a task at a predetermined time, and complete the task before the predetermined deadline. However recently, it is getting difficult to guarantee such a completion. This is due to the fact that the amount of calculation within a period is increasing, and the period itself is being required to be shorter. As a method for parallel processing, GPGPU (General-Purpose computation on GPU) is recently attracting attention. However, tools to apply GPGPU to real-time system are not provided from the GPU vendor, and related research is not yet found. Therefore, this paper proposes and evaluates a method to operate GPGPU in real-time systems. From the experimental results, the proposed method dramatically reduced the jitter and the elapsed time comparing to the CPU itself, and also the conventional method. This shows that the proposed method improves the predictability of the completion time, and the GPU can be applied to real-time systems.
Biotic and abiotic factors influencing the development of N2 fixing symbioses between rhizobia and the woody legumes Acacia and Prosopis

Front cover: Root hairs of Acacia senegal stained with methylene blue. Oi maailma, elämä sä ihmeellinen! Mi on sun tarkoitukses? Mihin viimein? Se arvoituspa kauan askaretta on aatokseen tuonut.
Pose estimation for planar contact manipulation with manifold particle filters

We investigate the problem of using contact sensors to estimate the pose of an object during planar pushing by a fixed-shape hand. Contact sensors are unique because they inherently discriminate between “contact” and “no-contact” configurations. As a result, the set of object configurations that activates a sensor constitutes a lower-dimensional contact manifold in the configuration space of the object. This causes conventional state estimation methods, such as the particle filter, to perform poorly during periods of contact due to particle starvation. In this paper, we introduce the manifold particle filter as a principled way of solving the state estimation problem when the state moves between multiple manifolds of different dimensionality. The manifold particle filter avoids particle starvation during contact by adaptively sampling particles that reside on the contact manifold from the dual proposal distribution. We describe three techniques, one analytical and two sample-based, of sampling from the dual proposal distribution and compare their relative strengths and weaknesses. We present simulation results that show that all three techniques outperform the conventional particle filter in both speed and accuracy. In addition, we implement the manifold particle filter on a real robot and show that it successfully tracks the pose of a pushed object using commercially available tactile sensors.
Neurophysiological basis of rapid eye movement sleep behavior disorder: informing future drug development

Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia characterized by a history of recurrent nocturnal dream enactment behavior and loss of skeletal muscle atonia and increased phasic muscle activity during REM sleep: REM sleep without atonia. RBD and associated comorbidities have recently been identified as one of the most specific and potentially sensitive risk factors for later development of any of the alpha-synucleinopathies: Parkinson’s disease, dementia with Lewy bodies, and other atypical parkinsonian syndromes. Several other sleep-related abnormalities have recently been identified in patients with RBD/Parkinson’s disease who experience abnormalities in sleep electroencephalographic frequencies, sleep–wake transitions, wake and sleep stability, occurrence and morphology of sleep spindles, and electrooculography measures. These findings suggest a gradual involvement of the brainstem and other structures, which is in line with the gradual involvement known in these disorders. We propose that these findings may help identify biomarkers of individuals at high risk of subsequent conversion to parkinsonism.
Level-Crossing Rate and Average Duration of Fades of the Envelope of a Sum-of-Cisoids

For the modelling and simulation of mobile radio channels, one often uses a sum of complex sinusoids (cisoids). This paper analyses in detail the level-crossing rate (LCR), the average duration of the fades (ADF), and the cumulative distribution function (CDF) of the envelope of a sum-of-cisoids (SOC). For these statistical quantities, exact and simple approximate solutions are derived by taking into account that the inphase and quadrature components of SOC models are generally correlated. The correctness of all theoretical results is confirmed by simulations. The results are not only important for getting a better fundamental understanding of the statistical behaviour of SOC models, but also for the performance evaluation of SOC-based mobile radio channel simulators.