Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploiting External Data for Training a Cancer Clause Classifier

Automatically detecting cancer-revealing clauses in a medical report can be helpful for medical experts in various tasks such as cancer staging. While the problem of detecting such clauses can be formulated as classifying individual clauses into cancer and non-cancer categories, standard classification algorithms suffer from the fact that the training data contains much more non-cancer clauses than cancer clauses in radiology reports. In order to alleviate the data imbalance and sparseness problems related to the radiology reports, we attempt to use cancer-related external data in term weighting at the training stage. Our experiment shows that this approach indeed changes term feature statistics and improve effectiveness of the classifier.
Dissonance and paradox in tourism planning - people first?

Dissonance turned my project on its head and this paper is one result. True to the brief of this volume, dissonance led me to face certain issues in tourism planning, namely the foregrounding of ‘locals’ in policy, planning, development, marketing and delivery of tourism as a sustainable development strategy. The philosophy underlying this foregrounding derives from a non-economic rationalist perspective and from a key aspect of sustainable development, the maintenance of local control. I argue that ‘locals’ have a right to set the parameters of development options, notwithstanding the (vested) interests of governments and private organisations, and a right to protect their own cultural interests, a right to consider the costs and benefits of tourism. The paradox? The contemporary literature on tourism planning, while asserting the need for community participation, tends to transform that participation into consultation, transform it from being potentially proactive to being simply reactive. In the language of power, the tourism development agenda is set elsewhere.
On the throughput of ARQ over multiple-access relay fading channels with queueing constraints

In this paper, the throughput under queuing constraints in multiple-access relay fading channels achieved by fixed-rate transmissions and a simple automatic repeat request (ARQ) protocol is investigated in the absence of channel side information (CSI) at the transmitters. Transmission is considered to be either in the ON or OFF state, depending on the reliability of the reception, and retransmissions are triggered by the ARQ protocol in the OFF state. The probabilities of these transmission states are identified. Through stability and queuing analysis, feasible set of system parameters is determined, and the maximum constant arrival rates at source nodes, which can be supported by the system under queuing constraints, are characterized in terms of the fixed transmission rates, state probabilities, and quality of service parameters.
Heterogeneous and Multitask Wireless Sensor Networks—Algorithms, Applications, and Challenges

Unlike traditional homogeneous single-task wireless sensor networks (WSNs), heterogeneous and multitask WSNs allow the cooperation among multiple heterogeneous devices dedicated to solving different signal processing tasks. Despite their heterogenous nature and the fact that each device may solve a different task, the devices could still benefit from a collaboration between them to achieve a superior performance. However, the design of such heterogeneous WSNs is very challenging and requires the design of scalable algorithms that maximize the performance of the devices without transmitting their raw sensor signals in an uncontrolled fashion. Towards this goal, novel techniques are needed both on the signal processing level and on the network-communication level. In this paper, we give an overview of applications in the field of heterogeneous and multitask WSNs with special focus on the signal processing aspects. Moreover, we provide a general overview of the existing algorithms for distributed node-specific estimation. Finally, we discuss the main challenges that have to be tackled for the design of heterogeneous multitask WSNs.
Heterogeneity in Perceptions of National Economic Conditions

Empirical findings concerning economic voting differ according to the level of analysis employed. A widely accepted explanation for the inconsistency between macroand microlevel evidence of economic voting is the high degree of random variation that plagues survey data. According to this explanation, aggregation purges individual-level "noise" from mass opinions on policy issues and outcomes. Building on the research of Bartels (1996), we debate the validity of this explanation by demonstrating that public evaluations of the national economy vary systematically with information, media exposure, political attitudes, personal experiences, and demographic characteristics. Furthermore, we show that these sources of subjective heterogeneity produce systematic biases when national economic evaluations are aggregated. These findings challenge a widely accepted notion that because "error" in individual-level measures (or expressions) of preferences is random, the aggregation of these individual measures ensures that they correctly represent the collective preference. mpirical findings concerning the influence of the economy on political behavior differ depending on the level of analysis employed. Using aggregate-level data, numerous studies have established a statistical relationship between economic conditions and election outcomes or executive popularity (e.g., Kramer 1971; MacKuen, Erikson, and Stimson 1992). On the basis of the macro-level evidence alone one would have little reason to doubt that the economy matters. In contrast, individual-level studies using survey data have produced only mixed evidence that voters consider economic conditions when evaluating the incumbent government and its leaders (e.g., Fiorina 1978, 1981; Kinder and Kiewiet 1979, 1981). Moreover, the strongest survey evidence of economic voting suggests that voters primarily care about national economic conditions not their personal financial situation. This finding contradicts the egocentric theory posited by early macro-level research that national economic indicators matter because they are correlated with personal financial circumstances. The micro-macro dichotomy in economic voting research reflects a similar dichotomy in research on voter sophistication and representation. Aggregate-level studies tend to indicate that voters are reasonably well informed about the economy and make forward-looking, rather sophisticated voting decisions (e.g., Alesina, Londregan, and Rosenthal 1993; Suzuki and Chappell 1996; Palmer and Whitten 1999). These studies infer that mass political decisions conform to rational expectations, or at least limited information rationality (e.g., MacKuen, Erikson, and Stimson 1992). In contrast to this macro-level image of the voter, individual-level survey research has shown that the public in general has low levels of political sophistication, lacking much knowledge of and interest in politics (e.g.,
Obstructive Sleep Apnea and Atrial Arrhythmogenesis

Atrial fibrillation (AF) is the most common sustained arrhythmia and is associated with relevant morbidity and mortality. Besides hypertension, valvular disease and cardiomyopathy, mainly ischemic and dilated, also other conditions like obesity, alcohol abusus, genetic factors and obstructive sleep apnea (OSA) are discussed to contribute to the progression from paroxysmal to persistent AF. The prevalence of OSA among patients with AF is 40-50%. OSA is characterized by periodic or complete cessation of effective breathing during sleep due to obstruction of the upper airways. Obstructive respiratory events result in acute intrathoracic pressure swings and profound changes in blood gases together leading to atrial stretch and acute sympatho-vagal dysbalance resulting in acute apnea related to electrophysiological and hemodynamic alterations. Additionally, repetitive obstructive events in patients with OSA may lead to sympathetic and neurohumoral activation and subsequent structural and functional changes in the atrium creating an arrhythmogenic substrate for AF in the long run. This review focuses on the acute and chronic effects of negative thoracic pressure swings, changes in blood pressure and sympatho-vagal dysbalance induced by obstructive respiratory events on atrial electrophysiology and atrial structure in patients with obstructive sleep apnea.
Analysing Monetary and Fiscal Policy Regimes using Deterministic and Stochastic Simulations

We wish to analyse the new rules in the European fiscal and monetary environment, and to investigate the effects of fiscal and monetary activism in Europe. The new European Central Bank has to decide on its monetary policy stance and we aim in this paper to contribute to the debate of the best overall policy rule for Euroland.
Local Weighted Semi-supervised Discriminant Analysis for Dimensionality Reduction

In this paper, we present a novel weighted version of semi-supervised discriminant analysis method by assigning weights to each labeled samples. The proposed within-class weight can detect the outliers and between-class weight can discover the support points in boundaries between different classes. In addition, our proposed method is robust to diverse-density classes and imbalanced boundaries. For high-dimensional dataset, our method can find a nice low-dimensional projection to preserve the discriminative information and manifold structure embedded in both labeled and unlabeled samples. It can also be easily kernelized to form a nonlinear method and do semi-supervised induction. The experiments show that our method can achieve very promising classification accuracies than other methods.
Time-Integration Schemes for the Finite Element Dynamic Signorini Problem

A large variety of discretizations have been proposed in the literature for the numerical solution of the dynamic Signorini problem. We classify the different discretizations into four groups. The first three groups correspond to different ways of enforcing the contact condition: exact enforcement, enforcement with penalty, and enforcement with contact condition in velocity. The fourth approach is based on a modification of the mass matrix. Numerical simulations on two one-dimensional benchmark problems with analytical solutions illustrate the properties of representative methods within each class, focusing first on spurious oscillations triggered by contact and then on energy behavior after multiple impacts. Selected schemes are also tested on a two-dimensional benchmark.
Dynamic Parameter Tuning for Hardware Prefetching Using Shadow Tagging

This paper presents a novel technique for dynamic selection of parameters for prefetching heuristics based on the use of shadow tag directories. Previous methods have been either static, made for a specific prefetching heuristic, or based on phase detection and tuning. The most flexible of these methods is phase detection and tuning. However, it has a serious drawback as it degrades performance while exploring the parameter space, as each configuration is tested on the running program. Our approach explores the parameter space using an extra structure called a shadow tag directory. This allows us to explore the parameter space without interfering with the running program, such that a larger parameter space can be explored without impacting performance. This paper examines the performance of this technique on tagged sequential prefetching, czone/delta correlation prefetching and reference prediction tables. In addition, we compare our results with a feedback directed approach. We show an overall 24% improvement over the best static sequential prefetcher and an 18% improvement versus feedback directed sequential prefetching on memory intensive SPEC benchmarks.
Sterol Regulatory Element-binding Protein-2- and Liver X Receptor-driven Dual Promoter Regulation of Hepatic ABC Transporter A1 Gene Expression

ABC transporter A1 (ABCA1) mediates and rate-limits biogenesis of high density lipoprotein (HDL), and hepatic ABCA1 plays a major role in regulating plasma HDL levels. HDL generation is also responsible for release of cellular cholesterol. In peripheral cells ABCA1 is up-regulated by the liver X receptor (LXR) system when cell cholesterol increases. However, cholesterol feeding has failed to show a significant increase in hepatic ABCA1 gene expression, and its expression is up-regulated by statins (3-hydroy-3-methylglutaryl-CoA reductase inhibitors), suggesting distinct regulation. In this study we investigated the mechanism of regulation of the rat hepatic ABCA1 gene and identified two major ABCA1 transcripts and two corresponding promoter regions. Compactin activated the novel liver-type promoter in rat hepatoma McARH7777 cells by binding the sterol regulatory element-binding protein-2 (SREBP-2). In contrast, compactin repressed the previously identified peripheral-type promoter in an LXR-responsive element-dependent but not E-box-dependent manner. Thus, compactin increased the liver-type transcript and decreased the peripheral-type transcript. The same two transcripts were also dominant in human and mouse livers, whereas the intestine contains only the peripheral-type transcript. Treatment of rats with pravastatin and a bile acid binding resin (colestimide), which is known to activate SREBP-2 in the liver, caused a reduction in the hepatic cholesterol level and the same differential responses in vivo, leading to increases in hepatic ABCA1 mRNA and protein and plasma HDL levels. We conclude that the dual promoter system driven by SREBP-2 and LXR regulates hepatic ABCA1 expression and may mediate the unique response of hepatic ABCA1 gene expression to cellular cholesterol status.
An Automatic Linguistics Approach for Persian Document Summarization

In this paper we propose a novel technique for summarizing a text based on the linguistics properties of text elements and semantic chains among them. In most summarization approaches, the major consideration is the statistical properties of text elements such as term frequency. Here we use centering theory which helps us to recognize semantic chains in a text, for proposing a new automatic single document summarization approach. For processing a text by centering theory and extracting a coherent summery, a processing pipeline should be constructed. This pipeline consists of several components such as co-reference resolution, semantic role labeling and POS [Part of speech] tagging.
Model Theory with Applications to Algebra and Analysis: Model theory for metric structures

A metric structure is a many-sorted structure with each sort a metric space, which for convenience is assumed to have finite diameter. Additionally there are functions (of several variables) between sorts, assumed to be uniformly continuous. Examples include metric spaces themselves, measure algebras (with the metric d(A,B) = μ(A∆B), where ∆ is symmetric difference), and structures based on Banach spaces (where one interprets the sorts as balls), including Banach lattices, C*algebras, etc.
A smart card based generic construction for anonymous authentication in mobile networks

The global mobility network can offer effective roaming services for a mobile wireless user between his home network and a visited network. For the sake of privacy, user anonymity has recently become an important security requirement for roaming services, and is a topic of concern in designing related protocols such as mutual authentication and key agreement. In this paper we present a generic construction, which converts any password authentication scheme based on the smart card into an anonymous authentication protocol for roaming services. Compared with the original password authentication scheme, the transformed protocol does not sacrifice authentication efficiency, and additionally, an agreed session key can be securely established between an anonymous mobile user and the foreign agent in charge of the network being visited.
A survey of interfaces using handheld devices to intuitively drive and show objects to a social robot.

Within this paper, we present three human-robot interfaces using handheld device as mediator object between the human and the robot: a virtual keyboard interface on the iPhone, a gesture based interface on the iPhone too and a Wiimote based interface. These interfaces allow to show particular objects to a robot. They were designed to be ease- of-use, specially by non-expert users, and to span different metaphors of interaction. In order to compare them and study the impact of the metaphor on the interaction, we designed a user-study based on two obstacle courses. Each of the 25 participants performed two courses with two different interfaces (total of 100 trials). Although the three interfaces were rather equally efﬁcient and all considered as satisfying by the participants, the iPhone gesture interface was largely preferred while the Wiimote was poorly chosen due to the impact of the chosen metaphor.
Neurosensory mechanotransduction through acid-sensing ion channels

Acid‐sensing ion channels (ASICs) are voltage‐insensitive cation channels responding to extracellular acidification. ASIC proteins have two transmembrane domains and a large extracellular domain. The molecular topology of ASICs is similar to that of the mechanosensory abnormality 4‐ or 10‐proteins expressed in touch receptor neurons and involved in neurosensory mechanotransduction in nematodes. The ASIC proteins are involved in neurosensory mechanotransduction in mammals. The ASIC isoforms are expressed in Merkel cell–neurite complexes, periodontal Ruffini endings and specialized nerve terminals of skin and muscle spindles, so they might participate in mechanosensation. In knockout mouse models, lacking an ASIC isoform produces defects in neurosensory mechanotransduction of tissue such as skin, stomach, colon, aortic arch, venoatrial junction and cochlea. The ASICs are thus implicated in touch, pain, digestive function, baroreception, blood volume control and hearing. However, the role of ASICs in mechanotransduction is still controversial, because we lack evidence that the channels are mechanically sensitive when expressed in heterologous cells. Thus, ASIC channels alone are not sufficient to reconstruct the path of transducing molecules of mechanically activated channels. The mechanotransducers associated with ASICs need further elucidation. In this review, we discuss the expression of ASICs in sensory afferents of mechanoreceptors, findings of knockout studies, technical issues concerning studies of neurosensory mechanotransduction and possible missing links. Also we propose a molecular model and a new approach to disclose the molecular mechanism underlying the neurosensory mechanotransduction.
Housing Quality Deficiencies and the Link to Income in the EU

the quality of housing is a key element of a person’s quality of life. this is particularly so in case of fundamental housing deficiencies, which are thus considered significant indicators of deprivation. if low housing quality is coupled with income poverty, it reinforces social disadvantage. although Western European countries have seen a great improvement in housing conditions in the last three decades, there is evidence that relative housing deprivation has increased recently (ranci, 2010).
iFoldRNA v2: folding RNA with constraints

UNLABELLED A key to understanding RNA function is to uncover its complex 3D structure. Experimental methods used for determining RNA 3D structures are technologically challenging and laborious, which makes the development of computational prediction methods of substantial interest. Previously, we developed the iFoldRNA server that allows accurate prediction of short (<50 nt) tertiary RNA structures starting from primary sequences. Here, we present a new version of the iFoldRNA server that permits the prediction of tertiary structure of RNAs as long as a few hundred nucleotides. This substantial increase in the server capacity is achieved by utilization of experimental information such as base-pairing and hydroxyl-radical probing. We demonstrate a significant benefit provided by integration of experimental data and computational methods. AVAILABILITY AND IMPLEMENTATION http://ifoldrna.dokhlab. org CONTACT dokh@unc.eu.
Structure Pattern Oriented Method for Service Composition

Improving dynamic feature of service composition is a vital and challenging stage in web service application. With the increasing of service number, it is hard to balance the flexibility and verification very well in dynamic and complex environment. The previous methods compare two services by their own features. These methods are useful and concise to find substitutes for unavailable services, but they might be too strict to find a solution on some occasions. We propose a novel method called SPACE to build and estimate service composition. The method uses six composite patterns as basic elements to organize services and it also measures impact of service replacement on these patterns in stead of pair of single ones. By using SPACE, we can find non-optimal solution for service selection and re-planning in service composition.
A Comparative Study on Key Phrase Extraction Methods in Automatic Web Site Summarization

Web Site Summarization is the process of automatically generating a concise and informative summary for a given Web site. It has gained more and more attention in recent years as eﬀective summarization could lead to enhanced Web information retrieval systems such as searching for Web sites. Extraction-based approaches to Web site summarization rely on the extraction of the most signiﬁcant sentences from the target Web site based on the density of a list of key phrases that best describe the entire Web site. In this work, we benchmark ﬁve alternative key phrase extraction methods, TFIDF, KEA, Keyword, Keyterm, and Mixture, in an automatic Web site summarization framework we previously developed. We investigate the performance of these underlying methods via a formal user study and demonstrate that Keyterm is the best choice for key phrase extraction while Mixture should be used to obtain key sentences. We also discuss why one method performs better than another and what could be done to further improve the summarization system.
On the Use of Air Quality Monitoring Networks for the Evaluation of Nitrogen Oxide Emission Inventories

The usefulness of ground based air quality monitoring data for diagnostics of uncertainties in gridded emission inventories is examined. A general probabilistic procedure for comparison of levels of uncertainties in different emission datasets is developed. It implies the evaluation of the agreement between modeling results obtained with these emission datasets and corresponding measurements. This procedure is applied to the evaluation of different datasets for European gridded nitrogen oxide (NOx) emissions by using the AirBase monitoring data and the CHIMERE chemistry-transport model. Numerical experiments are performed for two different types of spatial distributions of emission uncertainties and five different types of monitors. The results are also generalized for various levels of uncertainties in simulated and meas- ured data. It is found, in particular, that most informative, from the point of view of diagnostics of NOx emission uncer- tainties, are the measurements of NO2 at rural background sites and measurements of ozone at suburban sites situated in the vicinity of intensive sources of emissions. A more precise conclusion regarding the relative accuracy of two emission datasets can be drawn with a larger number of monitors in a network and a higher accuracy of the model and measure- ments. For example, with a network of 50 rural background NO2 monitors, the probability of choosing the more certain emission data set is more than 90 percent, if differences in uncertainty of two sets are more than 50 percent. Practical rec- ommendations for designing or evolving surface measurement networks, in light of the study results, are given.