Miracle-dz/UniFAR-FTUs huggingface dataset:
QUALITY-BIASED RETRIEVAL IN ONLINE FORUMS

This paper presents an ongoing research in utilizing content quality to enhance thread and post retrieval tasks in support oriented forums. First, we adapt the established information quality approach as a theoretical way to understand quality. Then, we outline research areas that help in quantifying quality. Lastly, we propose to use learning to rank method to weight quality parameters while ranking.
Forecasting and Uncertainty in Modeling the 2014-2015 Ebola Epidemic in West Africa

The Ebola epidemic in West Africa is the largest ever recorded, with over 27,000 cases and 11,000 deaths as of June 2015. The public health response was challenged by difficulties with disease surveillance, which impacted subsequent analysis and decision-making regarding optimal interventions. We developed a stage-structured model of Ebola virus disease (EVD). A key feature of the model is that it includes a generalized correction term accounting for factors such as the fraction of cases reported and fraction of the population at risk (e.g. due to contact patterns, interventions, spatiotemporal spread, pre-existing immunity, asymptomatic cases, etc.). We generated a range of short-term forecasts for Guinea, Liberia, and Sierra Leone, which we then validated using subsequent data. We also used the model to examine the uncertainty in the relative contributions to transmission by the different stages of infection (early, late, and funeral). We found that a wide range of forecasted trajectories fit approximately equally well to the early data. However, by including the correction factor term the best-fit models correctly forecasted EVD activity for all three countries, both individually and for all countries combined. In particular, the model correctly forecasted the slow-down in Liberia, as well as the continued exponential growth in Sierra Leone through November 2014. Parameter unidentifiability issues hindered estimation of the relative contributions of each stage of transmission from incidence and deaths data alone, which poses a challenge in determining optimal intervention strategies, and underscores the need for additional data collection. Even with these limited data, however, it is still possible to accurately capture and predict the epidemic dynamics by using a simplified correction term that approximately accounts for the complex underlying factors driving disease spread.
Movers and shakers of Canadian innovation policy — recognizing the influence of university vice-presidents as policy advocates

This paper examines the growing influence and impact of university Vice Presidents (VPs) Research on coordinating Canada’s innovation policy. As universities have become increasingly entrepreneurial, the institutional responsibilities go beyond policy implementation and have shifted towards shaping national level policy debates. By utilizing multi-level governance framework, the paper demonstrates how non-governmental stakeholders navigate the multi-level, multi-actor and multi-issue landscape of innovation policy. The findings provide evidence on the role of VPs Research in advocating and mediating complex inter-jurisdictional relationships between the private sector, and the federal and provincial governments. Policy coordination is viewed as an issue-driven functional process that assumes individual learning capacity and is influenced by the interdependence of stakeholder interests.
Mutual Insurance Networks and Unequal Resource Sharing in Communities , First Draft, February 2015

We study formation of mutual insurance networks in a model where agents who obtain more resources share a xed amount of resources with all directly linked agents that obtain fewer resources. We identify the pairwise stable networks and ecient networks in a basic model where agents are identical. Then, we introduce in the model two types of heterogeneity: an exogenous one, where agents diers in their income or in their preferences over the transfer scheme, and an endogenous heterogeneity where the costs of linking to an agent depends on the number of links the latter has already formed in the network. We examine the impact of these heterogeneities on stability and eciency.
Contraction Approach to Power Control, with Non-Monotonic Applications

In wireless networks, monotonic, strictly subhomogeneous functions have been used to analyze power control algorithms. We provide an alternative analysis based on the observation that such functions are shrinking with respect to certain metrics. These metrics are then used to analyze problems involving two classes of non-monotonic functions. The first class consists of normalized interference functions that can be used to compute the maximum achievable signal-to-interference ratio under power constraints. The second class consists of absolutely subhomogeneous functions that are used to approximate power control dynamics with outages. The eigensolutions of monotonic, strictly subhomogeneous functions are characterized as part of this development.
An access control framework for business processes for web services

Business Processes for Web Services are the new paradigm for the lightweight integration of business from different enterprises.Whereas the security and access control policies for basic web services and distributed systems are well studied and almost standardized, there is not yet a comprehensive proposal for an access control architecture for business processes. The major issue is that a business process describe complex services that cross organizational boundaries and are provided by entities that see each other as just partners and nothing else.This calls for a number of differences with traditional aspects of access control architectures such as• credential vs classical user-based access control,• interactive and partner-based vs one-server-gathers-all requests of credentials from clients,• controlled disclosure of information vs all-or-nothing access control decisions,• abducing missing credentials for fulfilling requests vs deducing entailment of valid requests from credentials in formal models,• "source-code" authorization processes vs data describing policies for communicating policies or for orchestrating the work of authorization servers.Looking at the access control field we find good approximation of most components but not their synthesis into one access control architecture for business processes for web services, which is the contribution of this paper.
Imperfect competition, technical progress and capital accumulation

This paper explores the consequences of imperfect competition on capital accumulation. The framework is an OLG growth model with altruistic agents. Two types of long run equilibria exist : egoistic or altruistic. We assume both competitive and non-competitive firms exist, the latter being endowed with more productive technology. They behave strategically on the labor market : they take into account the impact of their demand for labor on the equilibrium wage and on their profit. The effect of technical progress for a non-competitive firm depends on the initial productivity of the firm and on the type of steady state (egoistic or altruistic). An increase in the productivity of the most productive firm has a negative impact on capital accumulation in an egoistic steady state, and a positive one in an altruistic steady state. An increase in the productivity of the competitive sector can have various effects on capital accumulation. If the productivity levels of the non-competitive firms are close enough, capital accumulation increases in an egoistic steady state and decreases in an altruistic one. But, the impact of increasing productivity in the competitive sector can be reversed if the productivity of the less productive non-competitive firm is low enough.
A block-level flash memory management scheme for reducing write activities in PCM-based embedded systems

This paper targets at an embedded system with phase change memory (PCM) and NAND flash memory. Although PCM is a promising main memory alternative and is recently introduced to embedded system designs, its endurance keeps drifting down and greatly limits the lifetime of the whole system. Therefore, this paper presents a block-level flash memory management scheme, WAB-FTL, to effectively manage NAND flash memory while reducing write activities of the PCM-based embedded systems. The basic idea is to preserve each bit in flash mapping table hosted by PCM from being inverted frequently during the process of mapping table update. To achieve this, a new merge strategy is adopted in WAB-FTL to delay the mapping table update, and a tiny mapping buffer is used for caching frequently updated mapping records. Experimental results based on Android traces show that WAB-FTL can effectively reduce write activities when compared with the baseline scheme.
A 2D-3D Registration Tool Capable of Accurately Quantifying Flexion- Extension Positioning in the Cervical Spine

Flexion-extension x-rays are almost exclusively employed to analyze cervical spine kinematics. Yet, 2D radiographic measures of key vertebral metrics used to evaluate cervical stability are limited by x-ray source beam divergence, magnification errors and off-axis image acquisition. Three-dimensional CT images can be used to accurately measure these parameters, however flexion-extension CT scans are rarely acquired and do not provide information on the kinematics of the loaded cervical spine. This study evaluates the ability of an open source 2D-3D intensity-based image registration algorithm (xSePT) to create accurate flexion-extension 3D CT quality data from 2D flexion-extension radiographs and a single neutral 3D CT scan. Off axis 2D digitally rendered radiographs (DRRs) were generated from a set of 'gold standard' flexion-extension CT images of a single patient. The xSePT algorithm used the DRRs and a neutral CT to generate 3D flexion-extension CT images. Cervical vertebral metrics of subluxation, intervertebral disc height and interspinous process gap distance were compared between the 'gold standard' flexion-extension CT images, the 2D flexion-extension DRRs and the 3D output of the xSePT algorithm. The xSePT 2D-3D registration tool successfully aligned to the original flexion-extension CT data within 1° rotation and 0.5mm translation. The algorithm rapidly calculated values for the vertebral metrics equivalent to those based on the original flexion-extension CT data. Future evaluation of cervical pathology and kinematics under load may be possible through the application of this algorithm to generate 3D loaded flexion-extension data based on 2D standing flexion-extension x-rays and a single neutral unloaded CT scan.
Constraints-driven scheduling and resource assignment

This paper describes a new method for modeling and solving different scheduling and resource assignment problems that are common in high-level synthesis (HLS) and system-level synthesis. It addresses assignment of resources for operations and tasks as well as their static, off-line scheduling. Different heterogeneous constraints are considered for these problems. These constraints can be grouped into two classes: problem-specific constraints and design-oriented constraints. They are uniformly modeled, in our approach, by finite domain (FD) constraints and solved using related constrained programming (CP) techniques. This provides a way to improve quality of final solutions. We have developed in Java a constraint solver engine, JaCoP (Java Constraint Programming), to evaluate this approach. This solver and a related framework make it possible to model different resource assignment and scheduling problems, and handle them uniformly. The JaCoP prototype system has been extensively evaluated on a number of HLS and system-level synthesis benchmarks. We have been able to obtain optimal results together with related proofs of optimality for all HLS scheduling benchmarks and for all explored design styles (except one functional pipeline design). Many system-level benchmarks can also be solved optimally. For large randomly generated task graphs, we have used heuristic search methods and obtained results that are 1--3% worse than lower bounds or optimal results. These experiments have proved the feasibility of the presented approach.
Sampling scheme for better RBF network

Neural networks have been developed for machine learning and data mining tasks, and because data mining problems contain a large amount of data, sampling is a necessity for the success of the task. For this reason, this paper suggests an effective sampling technique that is based on a generated decision tree, where the trees are generated based on a fast and dirty tree generation algorithm. Experiments with several sample sizes and RBF network showed that the method is more effective with respect to accuracy than conventional random sampling method.
Neural Network Based Microcontroller Operated Intelligent Vehicle System

Today a fast real-time and robust automatic vehicle system is required to increase driving safety as the manned driving is getting extremely numbered, so are those of traffic jams, bad, dangerous and rough drivers and more importantly, accidents. Automatic recognition of traffic signs is also important for automated intelligent driving vehicle or driver assistance systems. This paper presents a new technique for object recognition and control the vehicle thereby. A combination of image processing and artificial neural network has been used for extraction and recognition of the boundaries in captured noisy images. A car is chosen to move towards some defined directions. Direction of the car in a certain moment is a subject of sensing. This sensing is fed to the car to implement image processing techniques and some matching principles by means of artificial neural network. The microcontroller operating the car receives the data via serial port and drives it by analyzing the data. Experimental results demonstrating the performance of the proposed technique are also presented. Performance analysis shows that the applied technique is able to execute well on a low performance CPU without requiring significant additional CPU resources. Keywords— Intelligent vehicle, Automatic control, Image processing, Artificial neural network, Microcontroller
Symmetric extension for two-channel quincunx filter banks

In the case of one-dimensional filter banks, symmetric extension is a commonly used technique for constructing nonexpansive transforms of finite-length sequences. In this paper, we show how symmetric extension can be extended to the case of two-dimensional filter banks based on quincunx sampling. In particular, we show how, for filter banks of this type, one can construct nonexpansive transforms for input sequences defined on arbitrary rectangular regions.
Loss of MeCP2 disrupts cell autonomous and autocrine BDNF signaling in mouse glutamatergic neurons

Mutations in the MECP2 gene cause the neurodevelopmental disorder Rett syndrome (RTT). Previous studies have shown that altered MeCP2 levels result in aberrant neurite outgrowth and glutamatergic synapse formation. However, causal molecular mechanisms are not well understood since MeCP2 is known to regulate transcription of a wide range of target genes. Here, we describe a key role for a constitutive BDNF feed forward signaling pathway in regulating synaptic response, general growth and differentiation of glutamatergic neurons. Chronic block of TrkB receptors mimics the MeCP2 deficiency in wildtype glutamatergic neurons, while re-expression of BDNF quantitatively rescues MeCP2 deficiency. We show that BDNF acts cell autonomous and autocrine, as wildtype neurons are not capable of rescuing growth deficits in neighboring MeCP2 deficient neurons in vitro and in vivo. These findings are relevant for understanding RTT pathophysiology, wherein wildtype and mutant neurons are intermixed throughout the nervous system. DOI: http://dx.doi. org/10.7554/eLife.19374. 001
Incentives for Participation and Abstention in Probabilistic Social Choice

Voting rules are powerful tools that allow multiple agents to aggregate their preferences in order to reach joint decisions. A common flaw of some voting rules, known as the no-show paradox, is that agents may obtain a more preferred outcome by abstaining an election. Whenever a rule does not suffer from this paradox, it is said to satisfy participation. In this paper, we initiate the study of participation in probabilistic social choice, i.e., for voting rules that yield probability distributions over alternatives. We consider three degrees of participation based on expected utility, the strongest of which even requires that an agent is strictly better off by participating at an election. While the latter condition is prohibitive in non-probabilistic social choice, we show that it can be met by reasonable probabilistic functions. More generally, we study to which extent participation and Pareto efficiency are compatible. To the best of our knowledge, this is the first work in this direction.
On latency in GPU throughput microarchitectures

Modern GPUs provide massive processing power (arithmetic throughput) as well as memory throughput. Presently, while it appears to be well understood how performance can be improved by increasing throughput, it is less clear what the effects of micro-architectural latencies are on the performance of throughput-oriented GPU architectures. In fact, little is publicly known about the values, behavior, and performance impact of microarchitecture latency components in modern GPUs. This work attempts to fill that gap by analyzing both the idle (static) as well as loaded (dynamic) latency behavior of GPU microarchitectural components. Our results show that GPUs are not as effective in latency hiding as commonly thought and based on that, we argue that latency should also be a GPU design consideration besides throughput.
Improving KNN based text classifications

In a variety of text classification algorithm, KNN is a competitive one with simple implementation and high efficiency. However, with the expansion of the size of the text, the runtime of KNN will grow rapidly that cannot be afford. In this paper, we improve the KNN by introducing the kd-tree storage structure and reducing the sample space through the sample clestering methods. And experiment shows that the runtime of improved KNN algorithm reduce apparently.
Specific gyrA gene mutations predict poor treatment outcome in MDR-TB

Objectives Mutations in the gyrase genes cause fluoroquinolone resistance in Mycobacterium tuberculosis. However, the predictive value of these markers for clinical outcomes in patients with MDR-TB is unknown to date. The objective of this study was to determine molecular markers and breakpoints predicting second-line treatment outcomes in M. tuberculosis patients treated with fourth-generation fluoroquinolones. Methods We analysed treatment outcome data in relation to the gyrA and gyrB sequences and MICs of ofloxacin, gatifloxacin and moxifloxacin for pretreatment M. tuberculosis isolates from 181 MDR-TB patients in Bangladesh whose isolates were susceptible to injectable drugs. Results The gyrA 90Val, 94Gly and 94Ala mutations were most frequent, with the highest resistance levels for 94Gly mutants. Increased pretreatment resistance levels (>2 mg/L), related to specific mutations, were associated with lower cure percentages, with no cure in patients whose isolates were resistant to gatifloxacin at 4 mg/L. Any gyrA 94 mutation, except 94Ala, predicted a significantly lower proportion of cure compared with all other gyrA mutations taken together (all non-94 mutants + 94Ala) [OR = 4.3 (95% CI 1.4–13.0)]. The difference in treatment outcome was not explained by resistance to the other drugs. Conclusions Our study suggests that gyrA mutations at position 94, other than Ala, predict high-level resistance to gatifloxacin and moxifloxacin, as well as poor treatment outcome, in MDR-TB patients in whom an injectable agent is still effective.
Compromised Photosynthetic Electron Flow and H2O2 Generation Correlate with Genotype-Specific Stomatal Dysfunctions during Resistance against Powdery Mildew in Oats

Stomatal dysfunction known as “locking” has been linked to the elicitation of a hypersensitive response (HR) following attack of fungal pathogens in cereals. We here assess how spatial and temporal patterns of different resistance mechanisms, such as HR and penetration resistance influence stomatal and photosynthetic parameters in oat (Avena sativa) and the possible involvement of hydrogen peroxide (H2O2) in the dysfunctions observed. Four oat cultivars with differential resistance responses (i.e., penetration resistance, early and late HR) to powdery mildew (Blumeria graminis f. sp. avenae, Bga) were used. Results demonstrated that stomatal dysfunctions were genotype but not response-type dependent since genotypes with similar resistance responses when assessed histologically showed very different locking patterns. Maximum quantum yield (Fv/Fm) of photosystem II were compromised in most Bga–oat interactions and photoinhibition increased. However, the extent of the photosynthetic alterations was not directly related to the extent of HR. H2O2 generation is triggered during the execution of resistance responses and can influence stomatal function. Artificially increasing H2O2 by exposing plants to increased light intensity further reduced Fv/Fm ratios and augmented the patterns of stomatal dysfunctions previously observed. The latter results suggest that the observed dysfunctions and hence a cost of resistance may be linked with oxidative stress occurring during defense induced photosynthetic disruption.
The Impact of Immigration on Natives in the Antebellum U . S . Labor Market , 1850-60

A negative effect of immigration on natives’ wages or incomes has been difficult to detect over the last twenty five years. Such an impact has been observed at the turn of the century, however. This difference could result either from a genuine change in the impact of immigration or from differences across studies in the impact and treatment of the location decisions of immigrants and the internal migration of natives. This study is prompted by these differences. It measures the impact of immigration in the years before the Civil War, in a setting in which it should be possible to detect an impact if ever there was one: the analysis covers a period when the immigration rate was more than twice as great as in the modern period, controls for immigrants’ location decisions, and examines both out-migrants and non-migrants among the native born. It finds that the impact of immigration on the income of natives was limited to skilled workers in the urban northeast. The largest impact on this group came from unskilled Irish immigrants. Though the results are not encouraging to those who seek a large impact from immigration today, they help explain both the reluctance of the U.S. to impose restrictions on immigrant entry in this period and some important political developments leading up to the Civil War.
A Large Corpus of Product Reviews in Portuguese: Tackling Out-Of-Vocabulary Words

Web 2.0 has allowed a never imagined communication boom. With the widespread use of computational and mobile devices, anyone, in practically any language, may post comments in the web. As such, formal language is not necessarily used. In fact, in these communicative situations, language is marked by the absence of more complex syntactic structures and the presence of internet slang, with missing diacritics, repetitions of vowels, and the use of chat-speak style abbreviations, emoticons and colloquial expressions. Such language use poses severe new challenges for Natural Language Processing (NLP) tools and applications, which, so far, have focused on well-written texts. In this work, we report the construction of a large web corpus of product reviews in Brazilian Portuguese and the analysis of its lexical phenomena, which support the development of a lexical normalization tool for, in future work, subsidizing the use of standard NLP products for web opinion mining and summarization purposes.