A New Approach of Clustering Feedback Sessions for Inferring User Search Goals

Internet information is growing every day exponentially. In order to find out the exact required information from this web search engines has become absolutely necessary tool for the web users. It has also become more difficult to provide user the required information. When Different users provide an ambiguous query to a search engine, they might be having different search goals. Therefore, it is required to find and analyze user search goals to improve the performance of a search engine and user experience. By representing the results in cluster we find out different user search goals for a query. It has advantages in improving search engine relevance and user experience. It extends the delivery and quality of internet information services to the end user. It also improves performance of Web server system. Query classification, search result reorganization and session boundary detection are the approaches attempt to find out user search goals. But the mentioned approaches has many limitations. A new approach has been implemented that overcomes the limitations and analyze, discover user search goals using feedback sessions. This approach first takes the user search query. For each single result of the search query pseudo-documents are generated. Using K-means++ clustering algorithm, these pseudo-documents are clustered. Each cluster can be considered as one user search goal. Finally in restructured result is given to the user where each URL is categorized into a cluster centered by the inferred search goals. Then depending upon user click through, results are restructured and represented to the user in order to satisfy the information need. DOI: 10.17762/ijritcc2321-8169.15071

Survey on the Use of Feedback Sessions for Inferring User Search Goals

Largest source of web traffic are search engines. Search engines are being used by different kind of users for different purpose. When users are searching something they have a different search goal in mind. Thus the queries are mostly ambiguous one. In order to improve search engine relevance and thus user experience inference and analysis of user search is required. To get the best results it is needful to capture different user search goals. This paper first talks about the different ways of inferring user search goals. Then insights of new approach has been discussed. A new algorithm firstly specifies a framework to analyze user search goals by clustering feedback sessions. There should be a proper way to represent these feedback sessions. In the second step of this algorithm pseudo-documents are prepared to represent feedback sessions. With this original results are restructured. This in turn is used to select optimal user search goals

D-4F, an apoA-1 mimetic, decreases airway hyperresponsiveness, inflammation, and oxidative stress in a murine model of asthma

Asthma is characterized by oxidative stress and inflammation of the airways. Although proinflammatory lipids are involved in asthma, therapies targeting them remain lacking. Ac-DWFKAFYDKVAEKFKEAFNH2 (4F) is an apolipoprotein (apo)A-I mimetic that has been shown to preferentially bind oxidized lipids and improve HDL function. The objective of the present study was to determine the effects of 4F on oxidative stress, inflammation, and airway resistance in an established murine model of asthma. We show here that ovalbumin (OVA) -sensitization increased airway hyperresponsiveness, eosinophil recruitment, and collagen deposition in lungs of C57BL/6J mice by a mechanism that could be reduced by 4F. OVA sensitization induced marked increases in transforming growth factor (TGF)β-1, fibroblast specific protein (FSP)-1, anti-T15 autoantibody staining, and modest increases in 4-hydroxynonenal (4-HNE) Michael\u27s adducts in lungs of OVA-sensitized mice. 4F decreased TGFβ-1, FSP-1, anti-T15 autoantibody, and 4-HNE adducts in the lungs of the OVA-sensitized mice. Eosinophil peroxidase (EPO) activity in bronchial alveolar lavage fluid (BALF), peripheral eosinophil counts, total IgE, and proinflammatory HDL (p-HDL) were all increased in OVA-sensitized mice. 4F decreased BALF EPO activity, eosinophil counts, total IgE, and p-HDL in these mice. These data indicate that 4F reduces pulmonary inflammation and airway resistance in an experimental murine model of asthma by decreasing oxidative stress

Energetics and atomic mechanisms of dislocation nucleation in strained epitaxial layers

We study numerically the energetics and atomic mechanisms of misfit dislocation nucleation and stress relaxation in a two-dimensional atomistic model of strained epitaxial layers on a substrate with lattice misfit. Relaxation processes from coherent to incoherent states for different transition paths are studied using interatomic potentials of Lennard-Jones type and a systematic saddle point and transition path search method. The method is based on a combination of repulsive potential minimization and the Nudged Elastic Band method. For a final state with a single misfit dislocation, the minimum energy path and the corresponding activation barrier are obtained for different misfits and interatomic potentials. We find that the energy barrier decreases strongly with misfit. In contrast to continuous elastic theory, a strong tensile-compressive asymmetry is observed. This asymmetry can be understood as manifestation of asymmetry between repulsive and attractive branches of pair potential and it is found to depend sensitively on the form of the potential.Comment: 11 pages, 9 figures, to appear in Phys. Rev.

Head-down tilt bed rest with or without artificial gravity is not associated with motor unit remodeling

© 2020, The Author(s). Purpose: The objective of this study was to assess whether artificial gravity attenuates any long-duration head-down 60 bed rest (HDBR)-induced alterations in motor unit (MU) properties. Methods: Twenty-four healthy participants (16 men; 8 women; 26–54 years) underwent 60-day HDBR with (n = 16) or without (n = 8) 30 min artificial gravity daily induced by whole-body centrifugation. Compound muscle action potential (CMAP), MU number (MUNIX) and MU size (MUSIX) were estimated using the method of Motor Unit Number Index in the Abductor digiti minimi and tibialis anterior muscles 5 days before (BDC-5), and during day 4 (HDT4) and 59 (HDT59) of HDBR. Results: The CMAP, MUNIX, and MUSIX at baseline did not change significantly in either muscle, irrespective of the intervention (p > 0.05). Across groups, there were no significant differences in any variable during HDBR, compared to BDC-5. Conclusion: Sixty days of HDBR with or without artificial gravity does not induce alterations in motor unit number and size in the ADM or TA muscles in healthy individuals

Assessment of the reliability of the motor unit size index (MUSIX) in single subject “round-robin” and multi-centre settings

Objective The motor unit size index (MUSIX) is incorporated into the motor unit number index (MUNIX). Our objective was to assess the intra-/inter-rater reliability of MUSIX in healthy volunteers across single subject “round robin” and multi-centre settings. Methods Data were obtained from i). a round-robin assessment in which 12 raters (6 with prior experience and 6 without) assessed six muscles (abductor pollicis brevis, abductor digiti minimi, biceps brachii, tibialis anterior, extensor digitorum brevis and abductor hallucis) and ii). a multi-centre study with 6 centres studying the same muscles in 66 healthy volunteers. Intra/inter-rater data were provided by 5 centres, 1 centre provided only intra-rater data. Intra/inter-rater variability was assessed using the coefficient of variation (COV), Bland-Altman plots, bias and 95% limits of agreement. Results In the round-robin assessment intra-rater COVs for MUSIX ranged from 7.8% to 28.4%. Inter-rater variability was between 7.8% and 16.2%. Prior experience did not impact on MUSIX values. In the multi-centre study MUSIX was more consistent than the MUNIX. Abductor hallucis was the least reliable muscle. Conclusions The MUSIX is a reliable neurophysiological biomarker of reinnervation. Significance MUSIX could provide insights into the pathophysiology of a range of neuromuscular disorders, providing a quantitative biomarker of reinnervation

Fuzzy min-max neural networks for categorical data: application to missing data imputation

The fuzzy min–max neural network classifier is a supervised learning method. This classifier takes the hybrid neural networks and fuzzy systems approach. All input variables in the network are required to correspond to continuously valued variables, and this can be a significant constraint in many real-world situations where there are not only quantitative but also categorical data. The usual way of dealing with this type of variables is to replace the categorical by numerical values and treat them as if they were continuously valued. But this method, implicitly defines a possibly unsuitable metric for the categories. A number of different procedures have been proposed to tackle the problem. In this article, we present a new method. The procedure extends the fuzzy min–max neural network input to categorical variables by introducing new fuzzy sets, a new operation, and a new architecture. This provides for greater flexibility and wider application. The proposed method is then applied to missing data imputation in voting intention polls. The micro data—the set of the respondents’ individual answers to the questions—of this type of poll are especially suited for evaluating the method since they include a large number of numerical and categorical attributes

Techniques of EMG signal analysis: detection, processing, classification and applications

Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications

Follicular fluid content and oocyte quality: from single biochemical markers to metabolomics

The assessment of oocyte quality in human in vitro fertilization (IVF) is getting increasing attention from embryologists. Oocyte selection and the identification of the best oocytes, in fact, would help to limit embryo overproduction and to improve the results of oocyte cryostorage programs. Follicular fluid (FF) is easily available during oocyte pick-up and theorically represents an optimal source on non-invasive biochemical predictors of oocyte quality. Unfortunately, however, the studies aiming to find a good molecular predictor of oocyte quality in FF were not able to identify substances that could be used as reliable markers of oocyte competence to fertilization, embryo development and pregnancy. In the last years, a well definite trend toward passing from the research of single molecular markers to more complex techniques that study all metabolites of FF has been observed. The metabolomic approach is a powerful tool to study biochemical predictors of oocyte quality in FF, but its application in this area is still at the beginning. This review provides an overview of the current knowledge about the biochemical predictors of oocyte quality in FF, describing both the results coming from studies on single biochemical markers and those deriving from the most recent studies of metabolomic