Miracle-dz/UniFAR-FTUs huggingface dataset:
An Approach of Vector Space Model to Link Concrete Concepts with Wiki Entities

Entity Linking (EL) search and labeling are important research topics with various web applications. The challenge is to find and link the important concepts from web text to online encyclopedia databases instead of simple personal and place names. This paper presents a new approach to link concrete concepts from English texts with Wiki entities. Using part-of-speech tagging to detect concrete concepts, Vector Space Model has been applied to perform the disambiguation and selection of Wiki entities. Comparing to existing method, the proposed framework, named UnBWiki VSM, achieved satisfactory result and was adjusted with the Wikilinks database of 2.8 million entities and 18 million words. As for a case study, five web texts from the British Royal Family History were analyzed manually. The results obtained using UnBWiki VSM were satisfactory, with recall of 73.5% for the five selected texts. This process shows the perspective for the automatic Entity Linking (EL) from web pages.
Implementing Stream-Processing Applications on FPGAs: A DSL-Based Approach

We introduce CAPH, a new domain-specific language (DSL) suited to the implementation of stream-processing applications on field programmable gate arrays (FPGA). \caph relies upon the actor/dataflow model of computation. Applications are described as networks of purely dataflow actors exchanging tokens through unidirectional channels. The behavior of each actor is defined as a set of transition rules using pattern matching. The \caph suite of tools currently comprises a reference interpreter and a compiler producing both SystemC and synthetizable VHDL code. We describe the implementation with a preliminary version of the compiler, of a simple real-time motion detection application on a FPGA-based smart camera platform. The language reference manual and a prototype compiler are available from http://wwwlasmea.univ-bpclermont.fr/Personnel/Jocelyn.Serot/caph.html.
Study of 3D Geological Structure Modeling and Visualization Application Based on Computer Technology

The paper takes Yinchuan plain as a research object, and basically investigated the quaternary geology and the spatial distribution and structure characteristics of groundwater system. The method of virtualizing boreholes is used to increase borehole data in accordance with the well-developed geological structures, the complex strata and lithology, the multiple geomorphologic units, the large area and the unevenly distributed boreholes. Based on the platform of geostatistics and Groundwater Modeling System (GMS), the three-dimensional geological structure model has been set up which reflects the hydrogeological conditions in the study area and the visualization of hydrogeological structure has been realized. All of these provide the foundation for exactly evaluating groundwater aquifer and rationally developing and utilizing groundwater.
Intelligent integration of multi-sensor data for risk assessment in transport corridor environments

Roads and railways are founded on earthwork structures such as embankments, which can be susceptible to slope instability and failure, with serious economic and safety implications. Existing approaches to earthwork condition appraisal are labour-intensive and hazardous. While the increasing availability of high resolution geospatial data offers improved opportunities for remote and efficient slope stability assessment, there remains a gap between the availability of such data, and the subsequent extraction of intelligent information. In this research, high resolution lidar data and multispectral aerial imagery are supporting the extraction of the key stability controls of slope gradient, aspect, soil moisture and vegetation type. The influence of these parameters has been established through numerical modelling under existing and future climate scenarios, enabling stability to be quantified and mapped in a spatially continuous manner. The research has been applied to a test site located at Haltwhistle in northern England. Results highlight the challenges associated with establishing a suitable spatial resolution for parameter extraction and risk assessment in a GIS environment, with degradation in resolution from 20 to 0.5 points / m required in order to overcome micro-topographic effects. A topographic wetness index (TWI), derived from the lidar DTM, was used to characterise soil moisture across the test site. Initial concerns over whether the restricted lidar coverage would be sufficient to capture broader-scale flow routing were allayed following investigations using a larger-scale DTM, which was found to produce results which were in good agreement with the lidar-derived TWI. * Corresponding author.
Recognition of facial expressions in presence of partial occlusion

Nowadays, both computer vision researchers and psychology experts show an increased interest for human facial expression analysis. Despite the huge amount of research that has been dedicated to this area, almost all of them concern data recorded in controlled laboratory conditions, which does not always reflect the real world environment in which the human face is partially occluded. Six basic facial expressions are investigated in that case, i.e.when the eyes and eyebrows or the mouth regions are left out. We are interested in finding which part of the face comprised sufficient information with respect to the entire face, in order to correctly classify these six expressions. Each image from the two databases used is convolved with a set of Gabor filters having various orientations and frequencies. The new feature vectors are classified using a maximum correlation classifier and the cosine similarity measure approaches. Overall, the method provides robustness against partial occlusion.
A novel fuzzy multi-objective framework to construct optimal prediction intervals for wind power forecast

The forecasting behavior of the high volatile and unpredictable wind power energy has always been a challenging issue in the power engineering area. In this regard, this paper proposes a new multi-objective framework based on fuzzy idea to construct optimal prediction intervals (Pis) to forecast wind power generation more sufficiently. The proposed method makes it possible to satisfy both the PI coverage probability (PICP) and PI normalized average width (PINAW), simultaneously. In order to model the stochastic and nonlinear behavior of the wind power samples, the idea of lower upper bound estimation (LUBE) method is used here. Regarding the optimization tool, an improved version of particle swam optimization (PSO) is proposed. In order to see the feasibility and satisfying performance of the proposed method, the practical data of a wind farm in Australia is used as the case study.
c-Src Is Required for Glial Cell Line-Derived Neurotrophic Factor (GDNF) Family Ligand-Mediated Neuronal Survival via a Phosphatidylinositol-3 Kinase (PI-3K)-Dependent Pathway

The glial cell line-derived neurotrophic factor (GDNF) family ligands (GFLs), consisting of GDNF, neurturin, persephin, and artemin, signal via a multicomponent complex composed of Ret tyrosine kinase and the glycosyl-phosphatidylinositol (GPI)-anchored coreceptors GFRα1–α4. In previous work we have demonstrated that the localization of Ret to membrane microdomains known as lipid rafts is essential for GDNF-induced downstream signaling, differentiation, and neuronal survival. Moreover, we have found that Ret interacts with members of the Src family kinases (SFK) only when it is localized to these microdomains. In the present work we show by pharmacological and genetic approaches that Src activity was necessary to elicit optimal GDNF-mediated signaling, neurite outgrowth, and survival. In particular, p60Src, but not the other ubiquitous SFKs, Fyn and Yes, was responsible for the observed effects. Moreover, Src appeared to promote neuronal survival via a phosphatidylinositol-3 kinase (PI-3K)-dependent pathway because the PI-3K inhibitor LY294002 prevented GFL-mediated neuronal survival and prevented activated Src-mediated neuronal survival. In contrast, the inhibition of Src activity had no effects on NGF-mediated survival, indicating that the requirement for Src was selective for GFL-mediated neuronal survival. These data confirm the importance of protein–protein interactions between Ret and raft-associated proteins in the signaling pathways elicited by GDNF, and the data implicate Src as one of the major signaling molecules involved in GDNF-mediated bioactivity.
A root-music algorithm for high resolution ISAR imaging

Inverse Synthetic Aperture Radar (ISAR) is used to image objects such as aircrafts and ships by the virtue of their rotation. The high resolution in range is obtained by large bandwidth pulses and similarly in the azimuth, by the rotational motion of the object. The rotational motion produces a Doppler shift, measured by the phase shift produced on a sequence of coherent pulses. Hence the azimuth resolution is determined by the Doppler discrimination using spectral analysis. In this paper, we propose an analysis technique for classification of ships, based on root-Multiple Signal Classification (MUSIC) algorithm, which betters the performance provided by the conventional Fast Fourier Transform (FFT) technique for ISAR imaging. This technique belongs to a class of super-resolution algorithms which also provides a resolution improved target classification.
Efficient Facial Expression and Face Recognition using Ranking Method

Expression detection is useful as a non-invasive method of lie detection and behaviour prediction. However, these facial expressions may be difficult to detect to the untrained eye. In this paper we implements facial expression recognition techniques using Ranking Method. The human face plays an important role in our social interaction, conveying people's identity. Using human face as a key to security, the biometrics face recognition technology has received significant attention in the past several years. Experiments are performed using standard database like surprise, sad and happiness. The universally accepted three principal emotions to be recognized are: surprise, sad and happiness along with neutral.
Robust classification of protein variation using structural modelling and large-scale data integration

Existing methods for interpreting protein variation focus on annotating mutation pathogenicity rather than detailed interpretation of variant deleteriousness and frequently use only sequence-based or structure-based information. We present VIPUR, a computational framework that seamlessly integrates sequence analysis and structural modeling (using the Rosetta protein modeling suite) to identify and interpret deleterious protein variants. To train VIPUR, we collected 9,477 protein variants with known effects on protein function from multiple organisms and curated structural models for each variant from crystal structures and homology models. VIPUR can be applied to mutations in any organism’s proteome with improved generalized accuracy (AUROC .83) and interpretability (AUPR .87) compared to other methods. We demonstrate that VIPUR‘s predictions of deleteriousness match the biological phenotypes in ClinVar and provide a clear ranking of prediction confidence. We use VIPUR to interpret known mutations associated with inflammation and diabetes, demonstrating the structural diversity of disrupted functional sites and improved interpretation of mutations associated with human diseases. Lastly we demonstrate VIPUR‘s ability to highlight candidate genes associated with human diseases by applying VIPUR to de novo variants associated with autism spectrum disorders.
Peer review of online learning and teaching: Harnessing collective intelligence to address emerging challenges

In 1983 Donald Schon argued for the development of "an epistemology of practice which places technical problem-solving within a broader context of reflective inquiry" (Schon, 1983, p. 69) in response to the complexity, uncertainty and instability of professional knowledge. This paper reports on a collaborative project led by the University of South Australia, which designed and developed a comprehensive, integrated peer review system that harnesses the power of the collaborative web to engage academic staff in the development or redevelopment of their own courses through the kind of reflective processes Schon (1983) advocated. The project builds on extensive work that has been undertaken both within Australia and overseas to support and stimulate the scholarship of online learning and teaching, and it has the capacity to demonstrate quality learning and teaching through course development, evaluation, improvement and interactive learning. Evidence produced through such processes can be used by academic staff as evidence to support claims for recognition and reward. The project has evolved in response to changing technologies and recognition of the need for a more adaptable system that enables academics to play a significant role in the creation of criteria and in contributing their own exemplars using a Web 2.0 approach. A major feature of the approach is its educative dimension, which is responsive to supporting online teaching and learning at a time when new Web 2.0 and 3D virtual learning technologies are presenting new challenges for educators. This paper describes the project and argues that online learning and teaching in this changing landscape is an emerging area of scholarship which needs to be supported and encouraged.
Expression Profiling of Selected Glutathione Transferase Genes in Zea mays (L.) Seedlings Infested with Cereal Aphids

The purpose of this report was to evaluate the expression patterns of selected glutathione transferase genes (gst1, gst18, gst23 and gst24) in the tissues of two maize (Zea mays L.) varieties (relatively resistant Ambrozja and susceptible Tasty Sweet) that were colonized with oligophagous bird cherry-oat aphid (Rhopalosiphum padi L.) or monophagous grain aphid (Sitobion avenae L.). Simultaneously, insect-triggered generation of superoxide anion radicals (O2 •−) in infested Z. mays plants was monitored. Quantified parameters were measured at 1, 2, 4, 8, 24, 48 and 72 h post-initial aphid infestation (hpi) in relation to the non-infested control seedlings. Significant increases in gst transcript amounts were recorded in aphid-stressed plants in comparison to the control seedlings. Maximal enhancement in the expression of the gst genes in aphid-attacked maize plants was found at 8 hpi (gst23) or 24 hpi (gst1, gst18 and gst24) compared to the control. Investigated Z. mays cultivars formed excessive superoxide anion radicals in response to insect treatments, and the highest overproduction of O2 •− was noted 4 or 8 h after infestation, depending on the aphid treatment and maize genotype. Importantly, the Ambrozja variety could be characterized as having more profound increments in the levels of gst transcript abundance and O2 •− generation in comparison with the Tasty Sweet genotype.
Important discoveries from analysing bacterial phenotypes

The ability to test hundreds to thousands of cellular phenotypes in a single experiment has opened up new avenues of investigation and exploration and led to important discoveries in very diverse applications of microbiological research and development. The information provided by global phenotyping is complementary to, and often more easily interpretable than information provided by global molecular analytical methods such as gene chips and proteomics. This report summarizes advances presented by scientists brought together to share their experiences and knowledge gained with high‐throughput phenotyping.
A novel stream-weight method for the multi-stream speech recognition system

A multi-stream speech recognition system is based on the combination of multiple complementary feature streams. Utilizing the fusion scheme of multi-stream, better performance was achieved in speech recognition system. The stream-weight method plays a very important role in the fusion collaborative scheme. The stream weights should be selected to be proportional to the feature stream reliability and informativeness. The posterior probability estimate is a measure of reliability, and the classification error is a measure of informativeness. The larger separation between class distributions in a given stream implies better discriminative power. The intra-class distances are an estimate of the class variance. The inter- and intra-class distances are combined to yield and estimate of the misclassification error for each stream. An unsupervised stream weight estimation method for multi-stream speech recognition system based on the computation of intra-and inter-class distances in each stream is proposed here. Experiments are conducted using Chinese Academy of Science speech database. Applying the new stream-weigh algorithm, we achieve better fusion performance compared with some traditional fusion methods, and the word error rate was decreased by 6%.
A Meningococcal Outer Membrane Vesicle Vaccine Incorporating Genetically Attenuated Endotoxin Dissociates Inflammation from Immunogenicity

Background Group B Neisseria meningitidis, an endotoxin-producing Gram-negative bacterium, causes the highest incidence of group B meningococcus (MenB) disease in the first year of life. The Bexsero vaccine is indicated in Europe from 8 weeks of age. Endotoxin components of outer membrane vesicles (OMVs) or soluble lipopolysaccharide (LPS) represent a potential source of inflammation and residual reactogenicity. The purpose of this study was to compare novel candidate MenB vaccine formulations with licensed vaccines, including Bexsero, using age-specific human in vitro culture systems. Methods OMVs from wild type- and inactivated lpxL1 gene mutant-N. meningitidis strains were characterized in human neonatal and adult in vitro whole blood assays and dendritic cell (DC) arrays. OMVs were benchmarked against licensed vaccines, including Bexsero and whole cell pertussis formulations, with respect to Th-polarizing cytokine and prostaglandin E2 production, as well as cell surface activation markers (HLA-DR, CD86, and CCR7). OMV immunogenicity was assessed in mice. Results ΔlpxLI native OMVs (nOMVs) demonstrated significantly less cytokine induction in human blood and DCs than Bexsero and most of the other pediatric vaccines (e.g., PedvaxHib, EasyFive, and bacillus Calmette–Guérin) tested. Despite a much lower inflammatory profile in vitro than Bexsero, ΔlpxLI nOMVs still had moderate DC maturing ability and induced robust anti-N. meningitidis antibody responses after murine immunization. Conclusion A meningococcal vaccine comprised of attenuated LPS-based OMVs with a limited inflammatory profile in vitro induces robust antigen-specific immunogenicity in vivo.
A spatial decision support system for guiding focal indoor residual spraying interventions in a malaria elimination zone

A customized geographical information system (GIS) has been developed to support focal indoor residual spraying (IRS) operations as part of a scaled-up campaign to progressively eliminate malaria in Vanuatu. The aims of the GISbased spatial decision support system (SDSS) were to guide the planning, implementation and assessment of IRS at the household level. Additional aims of this study were to evaluate the user acceptability of a SDSS guiding IRS interventions. IRS was conducted on Tanna Island, Republic of Vanuatu between 26 October and 5 December 2009. Geo-referenced household information provided a baseline within the SDSS. An interactive mapping interface was used to delineate operation areas, extract relevant data to support IRS field teams. In addition, it was used as a monitoring tool to assess overall intervention coverage. Surveys and group discussions were conducted during the operations to ascertain user acceptability. Twenty-one operation areas, comprising a total of 187 settlements and 3,422 households were identified and mapped. A total of 3,230 households and 12,156 household structures were sprayed, covering a population of 13,512 individuals, achieving coverage of 94.4% of the households and 95.7% of the population. Village status maps were produced to visualize the distribution of IRS at the sub-village level. One hundred percent of survey respondents declared the SDSS a useful and effective tool to support IRS. The GIS-based SDSS adopted in Tanna empowered programme managers at the provincial level to implement and asses the IRS intervention with the degree of detail required for malaria elimination. Since completion, SDSS applications have expanded to additional provinces in Vanuatu and the neighbouring Solomon Islands supporting not only specific malaria elimination and control interventions, but also the broader public health sector in general.
Stochastic Bisimulation for MDPs Using Reachability Analysis

This paper presents how to improve model reduction, a technique that receives an MDP and returns a stochastic bisimulation, which is an equivalence relation represented as a partition of the MDP set of states. In this work, we use the initial state information to do a reachability analysis before the stochastic bisimulation computation. This combination enables to compute a model reduction over the reachable states from a given initial state and then solve a smaller MDP problem. We show that with such reduction we can have exact solutions of larger MDP problems of domains with sparse transition function.
The Effect of Overhead Energy to the Lifetime in Wireless Sensor Networks

Although the transmitter energy is one of the major factors of total energy dissipation in a sensor node, neglecting the overhead energy in energy aware routing decisions could result in suboptimal energy usage. Routing algorithms should be concerned about the overhead energy which is wasted at each hop of data transfer. When only the transmission energy is considered as the communication cost, using shorter multi-hop links seems to be more advantageous. However, due to other energy consuming activities on the sensor nodes, such as reception of relayed messages, sensing and computation tasks, a considerable overhead energy might be dissipated while forwarding a message. Therefore, multi-hopping becomes not always advantageous in wireless sensor networks. In this work, we investigate the use of multi-hop communication links and compare the amount of energy gain acquired by correct routing energy calculations. We show that neglecting the overhead energy and overemphasizing the importance of power adjustable transmitter circuitry could result in considerable energy loss.
Diversity of Streptomyces spp. in Eastern Himalayan region – computational RNomics approach to phylogeny

Isolation and characterization of actinomycetes from soil samples from altitudinal gradient of North-East India were investigated for computational RNomics based phylogeny. A total of 52 diverse isolates of Streptomyces from the soil samples were isolated on four different media and from these 6 isolates were selected on the basis of cultural characteristics, microscopic and biochemical studies. Sequencing of 16S rDNA of the selected isolates identified them to belong to six different species of Streptomyces. The molecular morphometric and physico-kinetic analysis of 16S rRNA sequences were performed to predict the diversity of the genus. The computational RNomics study revealed the significance of the structural RNA based phylogenetic analysis in a relatively diverse group of Streptomyces.