Miracle-dz/UniFAR-FTUs huggingface dataset:
Conception d’un système de veille épidémiologique à base d’ontologies : application à la schistosomiase au Sénégal

Les systemes de veille epidemiologique sont utilises pour controler la propagation des maladies en proposant des plans d'action visant a prevenir les risques identifies. Dans ce domaine, la prediction des risques et la prise de decision sont fondees sur des analyses quantitatives. Ces approches quantitatives sont realisees par des simulations sur des modeles numeriques. Ces modeles, construits a l'issue d'enquetes epidemiologiques, permettent d'expliquer la dynamique de la propagation de la maladie et de valider des hypotheses. Cependant, ces modeles sont difficilement utilisables pour des predictions ou des decisions et requierent des donnees numeriques difficiles a acquerir en temps reel. Nous proposons une approche qualitative de modelisation des processus faisant abstraction de leurs details physiques. Elle permet une reproduction des comportements possibles d’un systeme a partir de la description abstraite de ses processus internes et des differents etats possibles. Ainsi, une simulation d’un modele qualitatif de processus permettra de predire des occurrences d’evenements ou des changements d’etats, ou de determiner la cause d’une observation (emergence ou propagation d'une maladie) en s’affranchissant de la necessite des donnees numeriques ou precises. L’approche qualitative adoptee pour la modelisation des processus est fondee sur les ontologies de processus. Par ailleurs, les activites de la veille epidemiologique exploitent des ressources (modeles de simulation, applications et donnees) potentiellement heterogenes et distribuees. De plus, les acteurs participant a l’analyse des risques et a la prise de decision peuvent avoir des profils heterogenes (epidemiologiste, biostatisticien, pathologiste, acteur politique, etc. ), et ainsi avoir des vocabulaires differents pour designer les memes concepts du domaine. Il est par consequent necessaire de construire une ontologie de domaine pour faciliter la communication, l’annotation des ressources utilisees, le partage de connaissances, l’integration des donnees et des applications. Nous proposons une methodologie et un cadre conceptuel de construction de telles ontologies pour le support de la veille d’une maladie en distinguant les composants ontologie de domaine et ontologie de processus. Nous montrons comment ces ontologies s'integrent dans les systemes de surveillance classiques et permettent de pallier leurs limites. L'approche adoptee est illustree dans le contexte de la veille de la schistosomiase au Senegal.
uCap: An Internet Data Management Tool For The Home

Internet Service Providers (ISPs) have introduced "data caps", or quotas on the amount of data that a customer can download during a billing cycle. Under this model, Internet users who reach a data cap can be subject to degraded performance, extra fees, or even temporary interruption of Internet service. For this reason, users need better visibility into and control over their Internet usage to help them understand what uses up data and control how these quotas are reached. In this paper, we present the design and implementation of a tool, called uCap, to help home users manage Internet data. We conducted a field trial of uCap in 21 home networks in three countries and performed an in-depth qualitative study of ten of these homes. We present the results of the evaluation and implications for the design of future Internet data management tools.
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Comparison of in vivo Adjuvanticity of Liposomal PO CpG ODN with Liposomal PS CpG ODN: Soluble Leishmania Antigens as a Model

Objective(s) CpG oligodeoxynucleotides (CpG ODNs) have been shown to have potent immunostimulatory adjuvant activity for a wide range of antigens. Due to susceptibility of phosphodiester CpG ODNs (PO CpG) to nuclease degradation, nuclease-resistant phosphorothioate CpG ODNs (PS CpG) were currently utilized in an in vivo model. In this study, according to some recently reported drawbacks with PS CpG, the adjuvant potential of liposomal PO CpG as a substitute for PS CpG was evaluated. Materials and Methods Soluble Leishmania antigens (SLA) as a model antigen and distearoylphosphatidylcoline (DSPC) as a neutral lipid were employed to prepare liposomes. Susceptible BALB/c mice received buffer, SLA, Lip-SLA, Lip-SLA-PS CpG, Lip-SLA-PO CpG, SLA+PS CpG, or SLA+PO CpG subcutaneously 3 times with 3 weeks intervals and then were challenged with Leishmania major’s live promastigotes. Blood and spleen samples were analyzed to determine the level and type of antibodies and cytokines. The number of live parasites in the spleen of immunized mice was determined. Moreover, the lesion size progress was assessed weekly by footpad swelling measurement. Results The results showed that mice immunized with Lip-SLA-PS CpG or Lip-SLA-PO CpG developed a significantly smaller footpad swelling, higher level of anti SLA IgG antibodies before and after challenge, and lower spleen parasite burden compared with the control groups. However, there was no significant difference between mice received Lip-SLA-PS CpG and those received Lip-SLA-PO CpG. Conclusion The results demonstrated that liposomal PO CpG ODN could be used instead of PS CpG ODN to overcome the possible drawbacks.
Insertion Operator for Bayesian Tree Substitution Grammars

We propose a model that incorporates an insertion operator in Bayesian tree substitution grammars (BTSG). Tree insertion is helpful for modeling syntax patterns accurately with fewer grammar rules than BTSG. The experimental parsing results show that our model outperforms a standard PCFG and BTSG for a small dataset. For a large dataset, our model obtains comparable results to BTSG, making the number of grammar rules much smaller than with BTSG.
Ego-centric Graphlets for Personality and Affective States Recognition

Do we tend to perceive ourselves more creative when surrounded by creative people? Or rather the opposite holds? Such information is very valuable to understand how to optimize work processes and boost people's productivity along with their happiness and satisfaction. Exploiting real-life data, collected over a period of six weeks in a research institution by means of wearable sensors, in this work we provide insights on human behavior dynamics in the workplace. We explore the use of graph lets, i.e. small induced sub graphs of a network, to encode the local structure of the interaction network of a subject, enriched with affective and personality states of his/her interaction partners. Our analysis shows that graph lets of increasing complexity, encoding non-trivial interaction patterns, are beneficial to affective and personality states recognition performance. We also find that different sensory channels, measuring proximity/co-location or face-to-face interactions, have different predictive power for distinct states.
Use of Immunostimulants in aquaculture disease management

A number microbial components and plant products such as polysaccharides, lentinan, levamisole, schizophyllan, oligosaccharides, muramyl dipeptide and yeast derivatives have been used as immunostimulants in aquaculture to stimulate the innate immune system of fish and shrimp. Among the all the immunostimulants examined, Betaglucans were found to be most promising immunostimulants, which are used in aquaculture to control diseases.
Ranking Significant Ubiquitous Computing Trails

Trails have been identified as a useful mechanism to provide navigational assistance in ubiquitous computing environments. Indeed, trails provide within a single framework an effective way to record, structure and represent interactions between users and physical or digital resources. Yet, this approach faces several challenges before it becomes practical at large scale since trailbased navigation requires considerable storage and computational resources when carried out naively. In this poster, we propose new methods and techniques that can effectively address these performance considerations and can support processing of large numbers of recorded trails. In particular, we present a stochastic model for the representation of trails and trail aggregates, and suitable data structures for efficient storage, filtering and retrieval which result in significantly improved performance. Furthermore, we propose algorithms and associated metrics that we use to rank trails and identify significant ones. Such significant trails can be subsequently used to guide search and navigation. We conclude by illustrating the use of these techniques in the context of three case studies.
Analysis on the 2-Dim Quantum Poincare Group at Roots of Unity

2--Dim quantum Poincar\'e Group Eq(1,1) at roots of unity, its dual Uq(e(1,1)) and some of its homogeneous spaces are introduced. Invariant integrals on Eq(1,1) and its invariant discrete subgroup E(1,1\mid p) are constructed. *--Representations of the quantum algebra Uq(e(1,1)) constructed in the homogeneous space SO(1,1\mid p) are integrated to the pseudo--unitary representations of Eq(1,1) by means of the universal T--matrix. Uq(e(1,1)) is realized on the quantum plane Eq(1,1) and the eigenfunctions of the complete set of observables are obtained in the angular momentum and momentum basis. The matrix elements of the pseudo--unitary irreducible representations are given in terms of the cut off q--exponential and q--Bessel functions whose properties we also investigate.
Improving semi-supervised fuzzy c-means classification of Breast Cancer data using feature selection

In previous work, six clinically novel and useful subgroups of breast cancer were identified using rules and clinicians' expertise to combine solutions from three different clustering algorithms on a database of biomarkers. The motivation for the present work is to reproduce this classification using a single clustering method. In the long term, we hope to produce a clinically useful classification using fewer features (biomarkers), reducing the time and cost of running complex and expensive clinical tests. Hence, the aim of this paper is to investigate the use of feature selection in combination with ssFCM to reduce the number of features while maintaining accuracy (defined as agreement with the previous classification), both on our breast cancer biomarker data and on other benchmark datasets. We show experimental results using four feature selection techniques, exploring with 10, 15 and 17 selected features out of the original 25 biomarkers for breast cancer. We experimented with varying amounts of labelled data (10% - 60% of the training data) and we evaluate classification accuracy using cross-validation. It was found that classification accuracy increased using 15 or 17 breast cancer biomarkers. Using SVM-RFE and CFS, improved classification accuracy was found on three UCI datasets, Arrhythmia, Cardiotocography and Yeast.
Exact numerical processing

A model of an exact arithmetic processing is presented. We describe a representation format that gives us a greater expressive capability and covers a wider numerical set. The rational numbers are represented by means of fractional notation and explicit codification of its periodic part. We also give a brief description of exact arithmetic operations on the proposed format. This model constitutes a good alternative for the symbolic arithmetic, in special when numerical exact values are required. As an example, we show an application of the exact numerical processing to calculate the perpendicular vector to another one for aerospace purposes.
The case for multipath multimedia transport over wireless ad hoc networks

Real-time multimedia transport has stringent bandwidth, delay, and loss requirements. Supporting this application in current wireless ad hoc networks is a challenge. Such networks are characterized with frequent link failures, as well as congestion. Consequently, data packets are dropped when a link fails or congestion occurs, resulting in low received quality. In addition, a realtime multimedia service may be unavailable when a particular server is unreachable. In this article, we make the case for using multipath transport for realtime multimedia services in wireless ad hoc networks, which provides a unified solution to the above problems. We review existing work on multipath multimedia transport, and discuss the advantages, as well as related issues, of using multipath transport for realtime multimedia transport.
Urban Air Pollution and Respiratory Emergency Visits at Pediatric Unit, Reggio Emilia, Italy

Short-term effects of air pollution on daily mortality and hospital admissions for respiratory causes are well documented. Few studies, however, explore the association between exposure to air pollution and daily emergency room visits for respiratory disorders, particularly in Italy and particularly among children as a susceptible population. A time-series analysis was conducted to explore the short-term association between air pollutants (PM10, total suspended particulates [TSP], NO2, SO2, CO, O3) and pediatric emergency room (ER) visits in a small city of northern Italy, Reggio Emilia, during the period 03/01/2001–03/31/2002. There were 1051 ER visits included in the study. Data were analyzed using generalized additive models (GAM), adjusting for various confounding variables, including temperature, humidity, and pollens (Graminaceae). The analyses were also stratified according to the nationality of children (Italians and foreigners). In single-pollutant models, the strongest associations were observed at lag 3 for a 10-μg/m3 increase of TSP (2.7% increase in ER, 95% CI 0.7–4.6) and PM10 (3.0% increase, 95% CI 0.4–5.7), and at lag 4 for a 10-μg/m3 increase of NO2 (11.0% increase in ER, 95% CI 3.6–18.8). At lag 3, the percentage increase in ER visits is similar for the 2 groups of children (Italians and foreigners) for TSP and PM10. The results of the study support the findings that air pollution is a relevant determinant of deterioration of respiratory health among children.
A robust and extendable framework towards fully automated diagnosis of nonmass lesions in breast DCE-MRI

Diagnosis of breast nonmass lesions, most notably ductal carcinoma in situ, is challenging. Recent studies show that dynamic contrast enhanced MRI achieves high sensitivity in diagnosis of nonmass lesions. Unlike successfully applied to diagnose mass lesions, particularly kinetic features are reported to be less effective in discriminating nonmass lesions. It is even difficult for human observers to differentiate nonmass lesions against the enhancing parenchymal or benign lesions due to their sometimes similar morphology and contrast kinetics. Towards an automated computer-aided diagnosis system of nonmass lesions, we implemented an extendable and completely automated framework that is efficient and modularized, aiming to discriminate detected suspicious regions into malignant and benign. The entire framework consists of five sequentially executed modules: motion correction, segmentation of breast regions, detection of suspicious regions, feature extraction, and knowledge-based analysis of suspicious regions. A preliminary test was performed on a data set collecting 162 nonmass lesions extracted from 67 patients, which achieved an area under ROC curve value of 0.74 for malignant lesions.
Study and Development of Anti-Islanding Control for Grid-Connected Inverters

This is a report on the development of anti-islanding control for grid-connected inverters from distributed generation sources. Islanding occurs when a distributed generation source continues to provide electricity to a portion of the utility grid after the utility experiences a disruption in service. Since the utility no longer controls this part of the distribution system, islanding can pose problems for utility personnel safety, power quality, equipment damage, and restoration of service. This report proposes a new family of anti-islanding schemes that meet IEEE 1547 interconnection standards, that can detect all disruptions in service, have minimum power-quality impact, require low-cost implementation, work for multiple distributed generators, and work for any multi-phase inverters. It also provides design guidelines for the schemes, and evaluates and validates the proposed schemes for practical applications.
Balancing bike sharing systems through customer cooperation - a case study on London's Barclays Cycle Hire

A growing number of cities worldwide have been installing public bike sharing systems, offering citizens a flexible and “green” alternative of mobility. In most bike sharing systems, customers rent and return bikes at different stations, without prior notification of the system operator. As a consequence, bike systems often become unbalanced, leaving some stations either empty or full. In such a case, customers either cannot pick up or return their bikes, resulting in a low service level. Typically, system operators employ staff to manually relocate bikes using trucks, leading to considerable operational cost. In this paper, we describe various methods to balance bike sharing systems by actively engaging customers in the balancing process. In particular, we show that by appropriately sending “control signals” to customers requesting them to slightly change their intended journeys, bike sharing systems can be balanced without using staffed trucks. Through extensive simulations based on historical data from London's Barclays Cycle Hire scheme, we show that simple control signals are sufficient to effectively balance the bike sharing system and offer service rates close to 100%.
Public Administration: Traditions of Inquiry and Philosophies of Knowledge

Introduction 1. Intellectual Heritage and Theoretical Developments: Is Public Administration an Art or a Science? 2. Searching for a Paradigm: Public Administration as a Postnormal Science 3. Identity Crises in the Social Sciences 4. Searching for Truth: The Logic of Inquiry in Public Administration 5. Theory Building through Qualitative Approaches 6. Theory Building through Quantitative Research 7. Theory Building through Mixed-Methods Research 8. Heterogeneity in Epistemic Traditions References Index
A constraint relaxation version of the interference leakage minimization algorithm in MIMO interference channels

This study explores the convergence property of the interference leakage minimization algorithm (ILMA) proposed by S. W. Peters and R. W. Heath Jr. Among the cooperative interference alignment (IA) schemes, we specialize the ILMA for its better feasibility in real applications than others. However, ILMA cannot converge to a global minimum because of its unitary constraints. As an iterative algorithm, no guarantee of global convergence means the tendency towards system instability. Up to the present, most efforts on cooperative IA are focused on pursuing high sum rate or low error floor. None of existing works looks into the convergence issue. In this paper, we explore the global convergence of ILMA. Specifically, we devise a constraint relaxation version of ILMA, named rILMA. Except that rILMA inherits the benefits from ILMA, mathematical proofs given in this paper also show that rILMA converges to a global minimum. This exploration directly results in the improvement of performance. Numerical simulations show that rILMA outperforms Max-SINR and ILMA in sum rate performance.
On the capacity of MIMO Rician broadcast channels

In this paper, a downlink communication system, in which a base station (BS) equipped with M antennas communicates with N (N Gt 1) single-antenna users, in a Rician fading environment is considered. The asymptotic (in terms of the number of users) sum-rate capacity of the system, as well as the capacity-achieving strategies, are derived. The main results of the paper are as follows: i) in the region of K = o(log N), where K denotes the Rician factor, the sum-rate capacity scales as M log(1 + P/Meta), where P denotes the SNR and eta =Delta log N/1+K, which is achieved by zero-forcing beam-forming (ZFBF) along with a low-complexity user selection algorithm that considers only the scattered component of the userspsila channels, ii) in the region K = omega(log N), in the case of co-located transmit antennas, the capacity scales as log(1+MP), which is achieved by time division multiple access (TDMA), iii) in the region K = omega(log N), in the case of isotropically-distributed specular components, the sum-rate capacity behaves as M log(1 + P), which is achieved by ZFBF, along with a user selection algorithm that considers only the specular component of the userspsila channels.
SEPIA: A Scalable Game Environment for Artificial Intelligence Teaching and Research

We describe a game environment we have developed that we call the Strategy Engine for Programming Intelligent Agents (SEPIA). SEPIA is based on real-time strategy games, but modified extensively to preferentially support the development of artificial agents rather than human play. Through flexible configuration options, SEPIA is designed to be pedagogically scalable: suitable for use at the undergraduate and graduate levels, and also as a research testbed. We also describe assignments and our experiences with this environment in undergraduate and graduate classes.
Impacts of rural development on Yellowstone wildlife: linking grizzly bear Ursus arctos demographics with projected residential growth

Exurban development is consuming wildlife habitat within the Greater Yellowstone Ecosystem with potential consequences to the long-term conservation of grizzly bears Ursus arctos. We assessed the impacts of alternative future land-use scenarios by linking an existing regression-based simulation model predicting rural development with a spatially explicit model that predicted bear survival. Using demographic criteria that predict population trajectory, we portioned habitats into either source or sink, and projected the loss of source habitat associated with four different build out (new home construction) scenarios through 2020. Under boom growth, we predicted that 12 km2 of source habitat were converted to sink habitat within the Grizzly Bear Recovery Zone (RZ), 189 km2 were converted within the current distribution of grizzly bears outside of the RZ, and 289 km2 were converted in the area outside the RZ identified as suitable grizzly bear habitat. Our findings showed that extremely low densities of residential development created sink habitats. We suggest that tools, such as those outlined in this article, in addition to zoning and subdivision regulation may prove more practical, and the most effective means of retaining large areas of undeveloped land and conserving grizzly bear source habitat will likely require a landscape-scale approach. We recommend a focus on land conservation efforts that retain open space (easements, purchases and trades) coupled with the implementation of ‘bear community programmes’ on an ecosystem wide basis in an effort to minimize human-bear conflicts, minimize management-related bear mortalities associated with preventable conflicts and to safeguard human communities. Our approach has application to other species and areas, and it has illustrated how spatially explicit demographic models can be combined with models predicting land-use change to help focus conservation priorities.