Miracle-dz/UniFAR-FTUs huggingface dataset:
Toluene Detection in Aqueous Phase by Optical Fiber Sensors Integrated with Single-Walled Carbon Nanotubes~!2008-04-21~!2008-05-19~!2008-06-11~!

Recent preliminary studies have demonstrated the feasibility of using Single-Walled Carbon Nanotubes (SWCNTs) as sensitive coatings of optical fiber sensors for the detection of chemical traces in water at room temperature. A low- finesse extrinsic Fabry-Perot configuration was adopted as sensing scheme and Langmuir-Blodgett thin SWCNT films have been integrated to form the sensing optical cavity. This contribution reports on the improvement of the per- formance of such SWCNTs-based chemo-optic transducers based on a proper choice of the number of carbon nanotube monolayers. The results here shown reveal a strong enhancement in term of sensor sensitivity of more than one order of magnitude, combined with a significant reduction of the response times. The achieved sub-ppm resolution, the response rapidity, and the complete and fast recovery of the initial output signal corresponding to the condition of uncontaminated water reveal the potentiality of the improved version of the sensor to be applied for water monitoring applications.
Symmetry based 3D reconstruction of repeated cylinders

First, we describe how 360°-rotational symmetry may be used for three dimensional reconstruction of repeated cylinders from a single perspective image. In our experiments, we consider translational and affine repetition of cylinders with vertical and random orientations. Later, we create a virtual camera configuration for retrieving pose and location of repeated cylinders. The combination of 360°-rotational symmetry and camera center is used to identify two orthogonal planes called axis plane and orthogonal axis plane. These two planes are the basis for the proposed reconstruction framework and virtual camera configuration. Furthermore, we discuss possible extension of our method in vision tasks based on motion analysis.
An overlay scheme to provide loose QoS for wireless nodes

The diffusion of wireless technologies is rapidly growing, and they are increasingly employed to provide connectivity on the road. Wireless systems are widely deployed to allow cheap devices to communicate, to provide local networking capabilities to even more demanding customers, e. g. for short range on-line gaming. One of the key problems is related to provide some Quality of Service (QoS) mechanisms in order to partition and control the underlying physical resource. Even if mechanisms for supporting QoS are becoming available also at the Medium Access Control (MAC) layer, this paper introduces an approach independent of the MAC, called PRIMUS (PRoviding QoS Independently of MAC UserS). The proposed scheme is based on a peer-to-peer (p2p) framework and it exploits an overlay network model in order to be fully decoupled from the underlying physical technology.
ARTWare: A Component Library for Building Domain-Oriented Authoring Environments

Building interactive systems using multimedia objects requires a wide range of knowledge including knowledge about 3D objects, graphics, movies, sound, and how to design user interface. We have built ARTWare, a library of components for building domain-oriented multimedia authoring environments. ARTWare consists of interactive components, such as various types of movie viewers and 3D spaces for positioning multimedia objects. We argue that in order for such a library to be useful it has to provide components that are (1) well designed based on theories of Human-Computer Interaction and (2) well integrated by synchronizing behavior of objects across different components. Interactive multimedia systems using ARTWare illustrate how ARTWare helps the development of interactive multimedia application systems in different domains.
Nucleotide variation at the methionine synthase locus in an endangered tree species, Fokienia hodginsii (Cupressaceae) in Vietnam

Nucleotide variation at the methionine synthase (MetE) locus within and among populations of an endangered forest tree Fokienia hodginsii in Vietnam was investigated in the present study. A total of 12 populations were sampled across Vietnam. The length of the sequenced locus varied from 1567 to 1559 bp. A total of 42 polymorphic sites were detected among samples. Overall, nucleotide diversity was estimated to be 0.00499 and 0.00692 at the total (ð tot ) and silent sites (ð silent ) in the pool, respectively. Nucleotide diversity within populations varied from 0.00300 to 0.00521 at the total and 0.00357 to 0.00666 at silent sites. The estimates of nucleotide diversity were lower in the 4 populations located in central and southern Vietnam (0.00300 to 0.00380) in comparison with the northern populations (ranging from 0.00399 to 0.00543). Overall estimates of genetic differentiation among 12 populations were low (F ST = 0.093 and K ST * = 0.078), even though both values were highly significant (P < 0.001). Pairwise analysis among 12 populations showed significant genetic differentiation as evaluated by F ST and Snn but not significant as evaluated by K ST *. Analysis of genetic clustering using BAPS provided the best support for all 144 sequences belonging to the same genetic cluster. The implication of the results revealed in this study in the genetic conservation of F. hodginsii was discussed. Key words: Population genetics, conservation, forest, methionine synthase (MetE), structure.
HOT SAX: efficiently finding the most unusual time series subsequence

In this work, we introduce the new problem of finding time series discords. Time series discords are subsequences of a longer time series that are maximally different to all the rest of the time series subsequences. They thus capture the sense of the most unusual subsequence within a time series. Time series discords have many uses for data mining, including improving the quality of clustering, data cleaning, summarization, and anomaly detection. Discords are particularly attractive as anomaly detectors because they only require one intuitive parameter (the length of the subsequence) unlike most anomaly detection algorithms that typically require many parameters. We evaluate our work with a comprehensive set of experiments. In particular, we demonstrate the utility of discords with objective experiments on domains as diverse as Space Shuttle telemetry monitoring, medicine, surveillance, and industry, and we demonstrate the effectiveness of our discord discovery algorithm with more than one million experiments, on 82 different datasets from diverse domains.
Encoding and retrieval of landmark‐related spatial cues during navigation: An fMRI study

To successfully navigate, humans can use different cues from their surroundings. Learning locations in an environment can be supported by parallel subsystems in the hippocampus and the striatum. We used fMRI to look at differences in the use of object‐related spatial cues while 47 participants actively navigated in an open‐field virtual environment. In each trial, participants navigated toward a target object. During encoding, three positional cues (columns) with directional cues (shadows) were available. During retrieval, the removed target had to be replaced while either two objects without shadows (objects trial) or one object with a shadow (shadow trial) were available. Participants were informed in blocks about which type of retrieval trial was most likely to occur, thereby modulating expectations of having to rely on a single landmark or on a configuration of landmarks. How the spatial learning systems in the hippocampus and caudate nucleus were involved in these landmark‐based encoding and retrieval processes were investigated. Landmark configurations can create a geometry similar to boundaries in an environment. It was found that the hippocampus was involved in encoding when relying on configurations of landmarks, whereas the caudate nucleus was involved in encoding when relying on single landmarks. This might suggest that the observed hippocampal activation for configurations of objects is linked to a spatial representation observed with environmental boundaries. Retrieval based on configurations of landmarks activated regions associated with the spatial updation of object locations for reorientation. When only a single landmark was available during retrieval, regions associated with updating the location of oneself were activated. There was also evidence that good between‐participant performance was predicted by right hippocampal activation. This study therefore sheds light on how the brain deals with changing demands on spatial processing related purely to landmarks. © 2014 Wiley Periodicals, Inc.
Pregnancy complicated by focal nodular hyperplasia: a case report of one woman over two consecutive courses of pregnancy

We encountered a woman with a preexisting large focal nodular hyperplasia (FNH) of the liver, persisting during two separate pregnancies. FNH size was not affected by either pregnancy. Her elevated serum γ‐glutamyltransferase and alkaline phosphatase levels before pregnancy were reduced during both pregnancies, but returned to prepregnancy levels after delivery.
Comparing Trace Visualizations for Program Comprehension through Controlled Experiments

For efficient and effective program comprehension, it is essential to provide software engineers with appropriate visualizations of the program's execution traces. Empirical studies, such as controlled experiments, are required to assess the effectiveness and efficiency of proposed visualization techniques. We present controlled experiments to compare the trace visualization tools Extravis and Explor Viz in typical program comprehension tasks. We replicate the first controlled experiment with a second one targeting a differently sized software system. In addition to a thorough analysis of the strategies chosen by the participants, we report on common challenges comparing trace visualization techniques. Besides our own replication of the first experiment, we provide a package containing all our experimental data to facilitate the verifiability, reproducibility and further extensibility of our presented results. Although subjects spent similar time on program comprehension tasks with both tools for a small-sized system, analyzing a larger software system resulted in a significant efficiency advantage of 28 percent less time spent by using Explor Viz. Concerning the effectiveness (correct solutions for program comprehension tasks), we observed a significant improvement of correctness for both object system sizes of 39 and 61 percent with Explor Viz.
doRiNA: a database of RNA interactions in post-transcriptional regulation

In animals, RNA binding proteins (RBPs) and microRNAs (miRNAs) post-transcriptionally regulate the expression of virtually all genes by binding to RNA. Recent advances in experimental and computational methods facilitate transcriptome-wide mapping of these interactions. It is thought that the combinatorial action of RBPs and miRNAs on target mRNAs form a post-transcriptional regulatory code. We provide a database that supports the quest for deciphering this regulatory code. Within doRiNA, we are systematically curating, storing and integrating binding site data for RBPs and miRNAs. Users are free to take a target (mRNA) or regulator (RBP and/or miRNA) centric view on the data. We have implemented a database framework with short query response times for complex searches (e.g. asking for all targets of a particular combination of regulators). All search results can be browsed, inspected and analyzed in conjunction with a huge selection of other genome-wide data, because our database is directly linked to a local copy of the UCSC genome browser. At the time of writing, doRiNA encompasses RBP data for the human, mouse and worm genomes. For computational miRNA target site predictions, we provide an update of PicTar predictions.
Isolation and Characterization of Bacteria Colonizing Acartia tonsa Copepod Eggs and Displaying Antagonist Effects against Vibrio anguillarum, Vibrio alginolyticus and Other Pathogenic Strains

Copepods represent a major source of food for many aquatic species of commercial interest for aquaculture such as mysis shrimp and early stages of fishes. For the purpose of this study, the culturable mesophilic bacterial flora colonizing Acartia tonsa copepod eggs was isolated and identified. A total of 175 isolates were characterized based on their morphological and biochemical traits. The majority of these isolates (70%) were Gram-negative bacteria. Matrix-assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI-TOF-MS) was used for rapid identification of bacterial isolates. Here, 58% of isolates were successfully identified at the genus level and among them, 54% were identified at the species level. These isolates belong to 12 different genera and 29 species. Five strains, identified as Bacillus pumilus, named 18 COPS, 35A COPS, 35R COPS, 38 COPS, and 40A COPS, showed strong antagonisms against several potential fish pathogens including Vibrio alginolyticus, V. anguillarum, Listeria monocytogenes, and Staphylococcus aureus. Furthermore, using a differential approach, we show that the antimicrobial activity of the 35R COPS strain is linked primarily to the production of antimicrobial compounds of the amicoumacin family, as demonstrated by the specific UV-absorbance and the MS/MS fragmentation patterns of these compounds.
Studies on Foam Flow in the Porous Media in the Last Decade: A Review

Foam has been used for several decades to decrease the mobility of drive gas or steam, thereby increasing the reservoir sweep efficiency and enhancing the oil recovery. The optimization of the operations requires a thorough understanding of the physical aspects involved in foam flow through porous media. The present paper aims mainly at reviewing experimental and modeling studies on foam flow in porous media particularly during the last decade, to stress the new achievements and highlight the areas that are less understood. X-ray computed tomography (CT) is a useful tool to study in-situ foam behaviors in porous media and new findings were obtained through this technology. The population-balance model was improved in different forms by researchers.
Distributed data gathering scheduling protocol for wireless sensor actor and actuator networks

This paper presents a cross-layer distributed scheduling protocol for sensor data gathering transmission in wireless sensor actor and actuator networks. We propose the parent-dominant decision scheduling with collision free (PDDS-CF) algorithm to adapt the dynamics of links in a realistic low-power wireless network. In addition, the protocol has a light-weight mechanism to maintain the conflict links. We have evaluated the protocol and implementation in TinyOS and Telosb hardware. The experiment shows that our protocol has robustness to the topology changes and it has significant improvements to reduce the traffic load in realistic wireless networks.
Protection against Code Obfuscation Attacks Based on Control Dependencies in Android Systems

In Android systems, an attacker can obfuscate an application code to leak sensitive information. TaintDroid is an information flow tracking system that protects private data in smartphones. But, TainDroid cannot detect control flows. Thus, it can be circumvented by an obfuscated code attack based on control dependencies. In this paper, we present a collection of obfuscated code attacks on TaintDroid system. We propose a technical solution based on a hybrid approach that combines static and dynamic analysis. We formally specify our solution based on two propagation rules. Finally, we evaluate our approach and show that we can avoid the obfuscated code attacks based on control dependencies by using these propagation rules.
Strategies for data and learning analytics informed national education policies: the case of Uruguay

This work provides an overview of an education and technology monitoring system developed at Plan Ceibal, a nationwide initiative created to enable technology enhanced learning in Uruguay. Plan Ceibal currently offers one-to-one access to technology and connectivity to every student and teacher (from primary and secondary education) as well as a comprehensive set of educational software platforms. All these resources generate massive amounts of data about the progress and style of students learning. This work introduces the conceptual framework, design and preliminary results of the Big Data Center for learning analytics currently being developed at Plan Ceibal. This initiative is focused on exploiting these datasets and conducting advanced analytics to support the educational system. To this aim, a 360 degrees profile will be built including information characterizing the user's online behavior as well as a set of technology enhanced learning factors. These profiles will be studied both at user (e.g., student or teacher) and larger scale levels (e.g., per school or school system), addressing both the need of understanding how technology is being used for learning as well as to provide accurate feedback to support evidence based educational policies.
Direct Mining of Closed Tree Patterns With Subtree Constraint

Two critical bottle necks in mining frequent tree patterns from tree databases are the exponential number of mined patterns and the lack of user focus on the mining process. We propose, in this paper, an algorithm that solves the problems for unordered attribute trees by mining only the compact representation of tree patterns, i.e. closed tree patterns, and allows users to mine only trees of their interest by specifying subtree constraints. The experimental results show the efficiency of our algorithm.
Imputation Methods to Improve Inference in Snp Association Studies

Missing single nucleotide polymorphisms (SNPs) are quite common in genetic association studies. Subjects with missing SNPs are often discarded in analyses, which may seriously undermine the inference of SNP-disease association. In this article, we develop two haplotype-based imputation approaches and one tree-based imputation approach for association studies. The emphasis is to evaluate the impact of imputation on parameter estimation, compared to the standard practice of ignoring missing data. Haplotype-based approaches build on haplotype reconstruction by the expectation-maximization (EM) algorithm or a weighted EM (WEM) algorithm, depending on whether case-control status is taken into account. The tree-based approach uses a Gibbs sampler to iteratively sample from a full conditional distribution, which is obtained from the classification and regression tree (CART) algorithm. We employ a standard multiple imputation procedure to account for the uncertainty of imputation. We apply the methods to simulated data as well as a case-control study on developmental dyslexia. Our results suggest that imputation generally improves efficiency over the standard practice of ignoring missing data. The tree-based approach performs comparably well as haplotype-based approaches, but the former has a computational advantage. The WEM approach yields the smallest bias at a price of increased variance.
Use of Generalized Regression Neural Network in Authorship

Identification of authorship of writings of unknown authorship is a special type of problems in the field of Stylometry. In this paper, the classification of articles of ambiguous authorship to the articles written by contemporary Tamil scholars of the same period, namely Mahakavi Bharathiar (MB), Subramaniya Iyer (SI), and T. V. Kalyanasundaram (TVK) is discussed. During the preindependence period, these three popular scholars had written number of articles on India’s Freedom Movement in the magazine called, India. Initially, all the three writers contributed their articles by attributing their names. Later, all the three patriots wrote articles on the same theme for anonymous publications without mentioning their names due to the oppressive attitude of the then British regime. Over the last two decades, the application of Artificial Neural Network models has increased considerably in areas of pattern classification and recognition problems in the field of Stylometry. In the present research, an attempt is made to apply the Generalised Regression Neural Network to the problem of authorship attribution for articles of ambiguous authorship and to assign them to the contemporary writers of the same period. Different sets of variables such as morphology and function words are made use of for classification purposes. Subsequently, results of authorship attribution are discussed.
Effect of Sustainable and Composite Materials on the Mechanical Behavior of Sandwich Panels under Edgewise Compressive Loading

Effect of Sustainable and Composite Materials on the Mechanical Behavior of Sandwich Panels under Edgewise Compressive Loading Justin A. Tafoya Over the last three decades, the aerospace industry has gradually shifted from metals to composites in many different applications due to the lightweight properties of composite materials. Some benefits of composites include higher strength-to-weight ratio and corrosion resistance. At this point in time, the composite industry researchers are focusing on renewable and sustainable materials (bio-composites). By understanding the structural capabilities of bio-composites that have been used for centuries, new developments of sustainable materials will spark more interest throughout the industry. Bio-composites include fibers such as hemp, bamboo, flax, etc. The high demand for bio-composites in composite structures can also reduce raw material costs. This study investigated, through experimental and numerical analysis, the mechanical behavior of sandwich panels under edgewise compressive loading. The first task of the study was to use four different facesheet materials and the same Nomex honeycomb core. The number of facesheet layers consecutively increased from one layer to four layers on each side of the core for each material. The facesheet materials used were Hexply AGP280-5H Carbon Fiber Pre-Preg, B601 Plain Weave Hemp, D118DKBR Split Herringbone Weave Hemp, and NB308T 7725 Texalium Fiberglass Pre-Preg. The sandwich panels were cured using a composite heat press and followed the recommended cure cycle for the material’s resin matrix. The variation of the facesheet materials while keeping the core consistent showed how the edgewise strength and displacement of the composite sandwiches were affected under compressive loading. The second task of the study was to try and create a multifunctional hybrid composite sandwich with two different facesheet materials; using one hemp material and one pre-preg material. The goal of this task was to try and minimize
Electrospray deposition of titanium dioxide (TiO2) nanoparticles

Deposition of titanium dioxide (TiO2) nanoparticles was conducted by using eletrospray method. 0.05wt% of titanium dioxide suspension was prepared and characterized by using Malvern Zetasizer prior to the experiment. From Zetasizer results, stable suspension condition was obtained which is at pH 2 with zeta potential value of ±29.0 mV. In this electrospraying, the suspension was pumped at flowrate of 5 ml/hr by using syringe pump. The input voltage of 2.1 kV was applied at the nozzle tip and counter electrode. Electrosprayed particles were collected on the grounded aluminium plate substrate which was placed at 10–20 cm from counter electrode. Particles were then characterized using FESEM and average size of electrosprayed particles obtained. Initial droplet size was calculated by scaling law and compared with FE-SEM results in order to prove droplet fission occur during electrospray. Due to the results obtained, as the working distance increase from 10–20 cm the deposited TiO2 droplet size decrease from 247–116 nm to show droplet fission occur during the experiment.