Miracle-dz/UniFAR-FTUs huggingface dataset:
Flux calculation using CARIBIC DOAS aircraft measurements: SO2 emission of Norilsk

[1] Based on a case-study of the nickel smelter in Norilsk (Siberia), the retrieval of trace gas fluxes using airborne remote sensing is discussed. A DOAS system onboard an Airbus 340 detected large amounts of SO2 and NO2 near Norilsk during a regular passenger flight within the CARIBIC project. The remote sensing data were combined with ECMWF wind data to estimate the SO2 output of the Norilsk industrial complex to be around 1 Mt per year, which is in agreement with independent estimates. This value is compared to results using data from satellite remote sensing (GOME, OMI). The validity of the assumptions underlying our estimate is discussed, including the adaptation of this method to other gases and sources like the NO2 emissions of large industries or cities.
The 4 th International Conference FITAT 2011 GeoSocialDM : A Framework for Mining Location-based Online Social Networks

Location-based Social Networking (LBSN) are playing crucial role in adding a spatial dimension to the social interactions. However, it still needs a sophisticated model to provide its intended services. In this paper we propose GeoSocialDM a framework for mining LBSN. In essence we introduce its basic modules along with research challenges facing it.
Robust multi-view stereo without matching

This paper proposes a robust algorithm that finds a proxy surface from a series of calibrated pictures of an object without assuming any of its reflectance properties. This proxy is optimized to reduce view interpolation errors by globally minimizing the frequency criterion proposed in. The generality of this setting makes robustness particularly difficult to achieve since no model from which to identify outliers or noise is available. Unfortunately, failing to achieve robustness results in unusable proxy for most of the datasets presented. The traditional method of identifying outliers by their discrepency from photoconsistency must somehow be replaced by a global analysis involving all viewpoints. The major contribution of this paper is to meet this requirement by proposing a robust estimation of the minimizer of the frequency criterion as well as a novel framework for merging the multiple depth hypotheses obtained. View interpolation results and proxies are shown for challenging datasets, both Lambertian and not.
Extended Endoscopic Endonasal Approaches for Cerebral Aneurysms: Anatomical, Virtual Reality and Morphometric Study

Introduction. The purpose of the present contribution is to perform a detailed anatomic and virtual reality three-dimensional stereoscopic study in order to test the effectiveness of the extended endoscopic endonasal approaches for selected anterior and posterior circulation aneurysms. Methods. The study was divided in two main steps: (1) simulation step, using a dedicated Virtual Reality System (Dextroscope, Volume Interactions); (2) dissection step, in which the feasibility to reach specific vascular territory via the nose was verified in the anatomical laboratory. Results. Good visualization and proximal and distal vascular control of the main midline anterior and posterior circulation territory were achieved during the simulation step as well as in the dissection step (anterior communicating complex, internal carotid, ophthalmic, superior hypophyseal, posterior cerebral and posterior communicating, basilar, superior cerebellar, anterior inferior cerebellar, vertebral, and posterior inferior cerebellar arteries). Conclusion. The present contribution is intended as strictly anatomic study in which we highlighted some specific anterior and posterior circulation aneurysms that can be reached via the nose. For clinical applications of these approaches, some relevant complications, mainly related to the endonasal route, such as proximal and distal vascular control, major arterial bleeding, postoperative cerebrospinal fluid leak, and olfactory disturbances must be considered.
The Flipped Classroom Method: Lessons Learned from Flipping Two Programming Courses

The flipped classroom teaching method, which emphasizes independent learning of theory and practical, in-depth exercises in the classroom, is gaining foothold in teaching. The method is increasingly being applied at university level. It has been implemented with varying approaches and guidelines, and a single unified process has not been described. In this article we compare existing literature to two case studies where flipped classroom was introduced to teaching. We discuss the lessons learned in these cases and present recommendations based on our experiences. Flipping the classroom has been found to be more efficient than traditional lecture-exercises method and the findings in this study support this. Therefore we recommend teachers to explore the possibility of utilizing the flipped classroom method in their courses.
High Dimensional Pattern Recognition using Diffusion Maps and Earth Mover's Distance

We propose a new method for matching, comparing, and discriminating datasets consisting of high-dimensional data (e.g., signals and images ). Our approach first performs dimension reduction and feature extraction of training datasets using the diffusion maps developed by Coifman and Lafon [1, 2]. This leads to a compact representation of the given classes in the so-called “diffusion space” whose dimension is much lower than the original ambient space. In fact, each class in the diffus ion space is represented as a set of cluster centroids called “signatures”. Dimension r eduction via diffusion maps offers the advantage of preserving the underlying geometry in the data. To classify an unlabeled test dataset, we extend (or embed) that dataset into the diffusion space constructed during the training stage, construct its signatur e, and then measure the “closeness” or similarity between the test signature and the class signatures using the Earth Mover’s Distance (EMD) [3, 4], which is more robust than othe r measures. Finally, we will demonstrate the usefulness of our method using two practical real applications and compare the performance of the dimension reduction capability of our method with that of the standard Principal Component Analysis.
A significance-driven programming framework for energy-constrained approximate computing

Approximate execution is a viable technique for energy-constrained environments, provided that applications have the mechanisms to produce outputs of the highest possible quality within the given energy budget. We introduce a framework for energy-constrained execution with controlled and graceful quality loss. A simple programming model allows users to express the relative importance of computations for the quality of the end result, as well as minimum quality requirements. The significance-aware runtime system uses an application-specific analytical energy model to identify the degree of concurrency and approximation that maximizes quality while meeting user-specified energy constraints. Evaluation on a dual-socket 8-core server shows that the proposed framework predicts the optimal configuration with high accuracy, enabling energy-constrained executions that result in significantly higher quality compared to loop perforation, a compiler approximation technique.
CONSISTENT SOLAR EVOLUTION MODEL INCLUDING DIFFUSIONAND RADIATIVE ACCELERATION EFFECTSTurcotte

The solar evolution has been calculated including all the eeects of the diiusion of helium and heavy elements. Monochromatic opacities are used to calculate radiative accelerations and Rosseland opacities at each evolution time step taking into account the local abundance changes of all important (21) chemical elements. The OPAL monochromatic data are used for the opacities and the radiative accelerations. The Opacity Project data are needed to calculate how chemical species and electrons share the momentum absorbed from the radiation ux. A detailed evaluation of the impact of atomic diiusion on solar models is presented. On some elements thermal diiusion adds approximately 50 % to the gravitational settling velocity. While gravitational settling had been included in previous solar models, this is the rst time that the impact of radiative accelerations is considered. Radiative accelerations can be up to 40 % of gravity below the solar convection zone and thus aaect signiicantly chemical element diiusion contrary to current belief. Up to the solar age, the abundances of most metals change by 7.5 % if complete ionization is assumed, but by 8.5 to 10 % if detailed ionization of each species is taken into account. If radiative accelerations are included, intermediate values are obtained. Diiusion leads to a change of up to 8 % in the Rosseland opacities if one compares to those of the original mixture. Most of this eeect can be taken into account by using tables with several values of Z. If one isolates the eeects of radiative accelerations, the abundance changes they cause alter the Rosseland opacity by up to 0.5 %; the density is aaected by up to 0.2 %; the sound speed is aaected by at most 0.06 %. The inclusion of radiative accelerations { 2 { leads to a reduction of 3 % of neutrino uxes measured with 37 Cl detectors and 1 % with 71 Ga detectors. The partial transformation of C and O into N by nuclear reactions in the core causes a 1 % change in the opacities which cannot be modeled by a change in Z alone. The evolution is allowed to proceed to 10 10 yr in order to determine the impact at the end of the main sequence life of solar type stars. It is found that immediately below the convection zone, the radiative acceleration on some iron peak elements is within a few percents of gravity. The abundance …
Rheumatoid arthritis and the role of oral bacteria

Abstract Rheumatoid arthritis (RA) and periodontal disease (PD) have shown similar physiopathologic mechanisms such as chronic inflammation with adjacent bone resorption in an immunogenetically susceptible host; however, PD has a well-recognized bacterial etiology while the cause of RA is unclear. Some reports have indicated that an infectious agent in a susceptible host could be one possible trigger factor for RA, and it has been suggested that oral microorganisms, specialty periodontal bacteria could be the infectious agent (mainly Porphyromonas gingivalis). It has been reported that PD is more frequent and more severe in patients with RA, suggesting a positive association between both diseases. There have been reports regarding the detection of antibodies against periodontal bacteria while other studies have identified periodontal bacterial DNA in serum and synovial fluid of RA patients and have explored the possible pathways of transport of periodontal bacterial DNA. In conclusion, there is no question that RA and PD have pathologic features in common and there is strong evidence of an association between both diseases, but further studies, including experimental models, are needed to demonstrate the arthritogenicity of oral microorganisms.
Assessment of VANET multi-hop routing over an experimental platform

Experimental evaluation of Vehicular Ad-hoc Networks (VANETs) is still a remaining issue for most researchers. Some works carry out performance tests to evaluate the communication channel according to physical and MAC conditions. Only a few works deal with multi-hop experimentation, but practically none use routing protocols. In this paper an integral VANET testbed is evaluated, using 802.11b and a multi-hop network managed by the Optimised Link State Routing (OLSR) protocol. Up to four vehicles are used to study the VANET performance over different traffic environments and different metrics are considered to analyse the results, including a deeper analysis to track the routes followed by packets end to end. Results differ from traditional one-hop and static-route tests, presenting a more realistic study.
Reduced variation in transgene expression from a binary vector with selectable markers at the right and left T-DNA borders

Summary A new binary vector for Agrobacterium-mediated plant transformation was constructed, in which two selectable markers, for kanamycin and hygromycin resistance, were placed next to the right and left T-DNA borders, respectively, and a CaMV 35S promoter-driven ~glucuronidase (GUS) gene was placed between these markers as a reporter gene (transgene). Using double antibiotic selection, all transgenic tobacco plants carrying at least one intact copy of the T-DNA expressed the transgene, and this population exhibited reduced variability in transgene expression as compared with that obtained from the parent vector pBI121. Absence of the intact transgene was the major reason for transgenic plants with little or no transgene expression. Integration of truncated T-DNAs was also observed among transgenic plants that expressed the transgene and carried multiple T-DNA inserts. The copy number of fully integrated T-DNAs was positively associated with transgene expression levels in R0 plants and R1 progeny populations. Variability due to position effect was determined among 17 plants carrying a single T-DNA insert. The coefficient of variability among these plants was only 35.5%, indicating a minor role for position effects in causing transgene variability. The new binary vector reported here can therefore be used to obtain transgenic populations with reduced variability in transgene expression.
Pothole Detection and Warning System: Infrastructure Support and System Design

a Many on-going projects in the field of vehicular networks are working in the direction of providing driver with relevant information about roads and traffic movements. In this paper, we propose a novelWi-Fi based architecture for Pothole Detection and Warning System which assists the driver in avoiding potholes on the roads by giving prior warnings. The system consists of access points placed on the roadsides for broadcasting data, which can be received byte Wi-Fi enabled vehicles as they enter the area covered by the influence of the access points. The mobile nodes can also broadcast their response as feedback which when received by access point can beutilized for backend server processing.The pothole detection application proposed in this paper enables the driver to receive information of the potholes on the roads in the vicinity of the moving vehicle. The application can be integrated in the vehicle so as to alarm the driver in the form of a visual signal, audio signal or even trigger the braking system. Simulations demonstrate the advantages of using our approach for constructing pothole detection systems. Many such similar applications can be deployed over the framework provided by the system to assist navigation on roads.
Mixed-script query labelling using supervised learning and ad hoc retrieval using sub word indexing

Much of the user generated content on the internet is written in their transliterated form instead of in their indigenous script. Due to this search engines receive a large number of transliterated search queries. This paper presents our approach to handle labelling of queries and ad hoc retrieval of documents based on these queries, as part of the FIRE2014 shared task on transliterated search. The content of each document is written in either the native Devanagari script or its transliterated form in Roman script or a combination of both. The queries to retrieve these documents can also be in mixed script. The task is challenging primarily due to the spelling variations that occur in the transliterated form of search queries. This particular problem is addressed by using back transliteration to reduce spelling variations, and a set of hand-tailored rules for consonant mapping. Sub-word indexing is done to take care of breaking and joining of transliterated words. Implementation of query labelling of the mixed script content was done using a supervised learning approach where an SVM classifier was trained using character n-grams as features for language identification. A Naïve Bayes classifier was used for classifying transliterated words that can belong to both Hindi and English when looked at individually. The 2 runs submitted by our team (BITS-Lipyantaran) performs best across all metrics for Subtask 2 among all the teams that participated, with a MRR score of 0.8171 and MAP score of 0.6421.
Toward online hybrid systems model checking of cyber-physical systems' time-bounded short-run behavior

Many Cyber-Physical Systems (CPS) are highly nondeterministic. This often makes it impractical to model and predict the complete system behavior. To address this problem, we propose that instead of offline modeling and verification, many CPS systems should be modeled and verified online, and we shall focus on the system's time-bounded behavior in short-run future, which is more describable and predictable. Meanwhile, as the system model is generated/updated online, the verification has to be fast. It is meaningless to tell an online model is unsafe when it is already out-dated. To demonstrate the feasibility of our proposal, we study two cases of our ongoing projects, one on the modeling and verification of a train control system, and the other on a Medical Device Plug-and-Play (MDPnP) application. Both cases are about safety-critical CPS systems. Through these two cases, we exemplify how to build online models that describe the time-bounded short-run behavior of CPS systems; and we show that fast online modeling and verification is possible.
Sampling limitations in using tourists’ mobile phones for GPS-based visitor monitoring

Abstract This study examined sampling limitations when tourists’ own mobile phones are used for visitor monitoring in a protected area. In Nikko National Park, Japan, we collected GPS tracking information from respondents’ mobile phones and investigated sociodemographic attributes of participants and nonparticipants in the survey. The participation rate for GPS data collection was low (15%). A major reason not to participate was technical unfamiliarity in using their own mobile phones as a tracking tool. Meanwhile, participants were biased toward visitors who were younger, more technology friendly, staying longer, coming from a greater distance, and being first-time or group visitors. A practical challenge for GPS data collection was the diversity of mobile phones. We conclude that further development of user-friendly tracking applications compatible with a wide variety of mobile phones could ease visitors’ technical concerns, make it easier to use GPS tracking, increase participation rates, and reduce data bias.
Urban traffic congestion prediction based on routes information

Traffic congestion represents an important problem in crowded urban areas. It leads to travel delays, increased fuel consumption and higher level of pollution. This paper proposes a technique for congestion prediction in urban traffic. It uses event based routes selection and relies on information collected by a sensor network. Simulation experiments with more than 50 traffic patterns over eight crowded intersections demonstrate promising results.
( MUC 5 AC and MUC 2 ) in Human Gastric Carcinomas Immunohistochemical Study of the Expression of MUC 6 Mucin and Co-expression of Other Secreted

http://jhc.sagepub. com/content/48/3/377 The online version of this article can be found at: DOI: 10.1177/002215540004800307 2000 48: 377 J Histochem Cytochem and Manuel Sobrinho-Simões Celso A. Reis, Leonor David, Filipa Carvalho, Ulla Mandel, Carme de Bolós, Ekaterina Mirgorodskaya, Henrik Clausen Mucins (MUC5AC and MUC2) in Human Gastric Carcinomas Immunohistochemical Study of the Expression of MUC6 Mucin and Co-expression of Other Secreted
DNA Copy Number Selection Using Robust Structured Sparsity-Inducing Norms

Array comparative genomic hybridization (aCGH) is a newly introduced method for the detection of copy number abnormalities associated with human diseases with special focus on cancer. Specific patterns in DNA copy number variations (CNVs) can be associated with certain disease types and can facilitate prognosis and progress monitoring of the disease. Machine learning techniques have been used to model the problem of tissue typing as a classification problem. Feature selection is an important part of the classification process, because many biological features are not related to the diseases and confuse the classification tasks. Multiple feature selection methods have been proposed in the different domains where classification has been applied. In this work, we will present a new feature selection method based on structured sparsity-inducing norms to identify the informative aCGH biomarkers which can help us classify different disease subtypes. To validate the performance of the proposed method, we experimentally compare it with existing feature selection methods on four publicly available aCGH data sets. In all empirical results, the proposed sparse learning based feature selection method consistently outperforms other related approaches. More important, we carefully investigate the aCGH biomarkers selected by our method, and the biological evidences in literature strongly support our results.
Rethinking materialism : a question of judgements and enactments of power

This thesis traces the etymology of 'materialism' using a Foucauldian discourse analysis to bring to the fore the word’s use as discursive mode of power. Through examining over 5000 texts, spanning across 400 years, I trace a line from the origins of materialism in philosophical thought of the Renaissance and Enlightenment eras to its uptake in American rhetoric and integration into the consumer behaviour literature. This approach leads to a reconceptualization of materialism. Commonly viewed in consumer studies as a measurable value, trait, or motive inherent in the consumer, I situate materialism as external to the consumer. The word’s history, especially in consumer studies, demonstrates that it embodies moral condemnations. I find that accusations of materialism rise in discourses during moments of intense social dislocations. It is wielded by social groups as part of a play for status. In this analysis, concepts of power as per Foucault and social distinctions as per Bourdieu, are used to explain the motives residing behind the use of the word. These motives, which reflect sociocultural dynamics and geo-political agendas, manifest in the meanings attributed to 'materialism', and the directionality of the allegation. Thus I argue that 'materialism', at its essence, is an epithet used to advance or demobilise a set of interests. This is what I term, delegitimizing discourse—words used to debase other social groups. Studying 'materialism' as a case in point, I note that groups use delegitimizing discourse either an assimilative measure—rhetoric geared towards indoctrination—or as a defensive mechanism—rhetoric used to debase threatening elements and behaviours. It is hoped that this new perspective will encourage academics to be rethink their approach to studying materialism, or in the least, to be aware of what is being measured, and what moral judgements and interests they are perpetuating through their continued studies.
Virtual keyboard BCI using Eye blinks in EEG

A Brain Computer Interface (BCI) provides a new communication channel between human brain and the computer. This paper is concentrated on developing a BCI system, a Virtual Keyboard using the LabVIEW platform. The Electroencephalogram (EEG) signal contains the technical artifacts (noise from the electric power source, amplitude artifact, etc.) and biological artifacts (eye artifacts, ECG and EMG artifacts). Eye blink is one of the main artifacts in the EEG signal. But in this context the Eye blinks are not artifacts and are control signals to select the blocks/characters in the Virtual Keyboard. The kurtosis coefficient and amplitude characteristics of the eye blink signals are used to detect the control signals.