TRANSFORMATION AND CLASSIFICATION OF ORDINAL SURVEY DATA

Currently, Machine Learning is being significantly used in almost all of the research domains. However, its applicability in survey research is still in its infancy. We in this paper, attempt to highlight the applicability of Machine Learning in survey research while working on two different aspects in parallel. First, we introduce a pattern-based transformation method for ordinal survey data. Our purpose behind developing such a transformation method is twofold. Our transformation facilitates easy interpretation of ordinal survey data and provides convenience while applying standard Machine Learning approaches. Second, we demonstrate the application of various classification techniques over real and transformed ordinal survey data and interpret their results in terms of their suitability in survey research. Our experimental results suggest that Machine Learning coupled with the Pattern Recognition paradigm has a tremendous scope in survey research

A Literature Study of Wind Analysis on High Rise Building

Recently modern architecture means something regularity and irregularity in geometry. Everyone wants to win the race of designing beautiful and complex structures and with issue of scarcity of land it is today\u27s necessity to go higher and higher vertical and construct high rise structures. But as we go higher wind excitation becomes one of the most precarious force acting on the surface of the structure and if the plan geometry is irregular it can induce torsion which can be life-threatening to the structure, so it is essential to analyze and understand such forces during designing. In this study the behavior of high rise building against the wind force in wind zone 2nd, L shape is studied and analyzed for specific heights.Also direction of wind plays very vital role in behavior of structure

Alginate Oligosaccharides modify hyphal infiltration of Candida albicans in an in vitro model of invasive Human Candidosis

AIMS: A novel alginate oligomer (OligoG CF-5/20) has been shown to potentiate antifungal therapy against a range of fungal pathogens. The current study assessed the effect of this oligomer on in vitro virulence factor expression and epithelial invasion by Candida species. METHODS AND RESULTS: Plate substrate assays and epithelial models were used to assess Candida albicans (CCUG 39343 and ATCC 90028) invasion, in conjunction with confocal laser scanning microscopy and histochemistry. Expression of candidal virulence factors was determined biochemically and by quantitative PCR (qPCR). Changes in surface charge of C. albicans following OligoG treatment were analysed using electrophoretic light scattering. OligoG induced marked alterations in hyphal formation in the substrate assays and reduced invasion in the epithelial model (P 0·05), qPCR demonstrated a reduction in phospholipase B (PLB2) and SAPs (SAP4 and SAP6) expression. CONCLUSION: OligoG CF-5/20 reduced in vitro virulence factor expression and invasion by C. albicans. SIGNIFICANCE AND IMPACT OF THE STUDY: These results, and the previously described potentiation of antifungal activity, define a potential therapeutic opportunity in the treatment of invasive candidal infections

Bio-enrichment of phenolics and antioxidant activity of combination of Oryza sativa and Lablab purpureus fermented with GRAS filamentous fungi

Cereal and legumes meet a considerable requirement of protein and carbohydrate of the local population. Most of the foods are cereal based but some cereal/legume or legume based foods are also common in many countries of Asia and Africa. In present study, the effect of fermentation on total phenolics, antioxidant activity and α-amylase enzyme activity of ethanolic extracts of each of seeds and flours combination (1:1) of Oryza sativa (rice) and Lablab purpureus (seim) was determined. The percentage inhibition of free radicals formation by DPPH and ABTS assays was found maximum i.e. 80.66 ± 0.21, 97.67 ± 0.35 on 4th day of incubation of combined sample of rice and seim seeds fermented with Aspergillus oryzae and Aspergillus awamori, respectively. The increased percentage inhibition of free radical formation of fermented samples was found greater than the non-fermented samples (65.88 ± 0.15, 42.00 ± 0.63). The TPC of substrate i.e. rice:seim seeds (1:1) was also found maximum i.e. 47.53 ± 0.20 on 5th day of fermentation with A. awamori. α-amylase activity of fermented samples was also found higher than that of non fermented samples. Almost similar results were obtained in combined flour extract of both the substrates. Increase in level of α-amylase enzyme during SSF indicates that enzymes produced by microorganisms were responsible for release of bound phenolics which may be responsible for increase in antoxidant activity of extracts of fermented seeds and flour combination a cereal and a legume

Recent advances in production of lignocellulolytic enzymes by solid-state fermentation of agro-industrial wastes

Agricultural, forestry, and food industries produce large amounts of lignocellulosic wastes every year. Land disposal of these residues without proper treatment leads to environmental pollution and negative health effects. The recent advances in valorization of agro-industrial wastes by the production of lignocellulolytic enzymes under solid-state fermentation (SSF) are reviewed. SSF is a promising technology to produce lignocellulolytic enzymes. However, the large-scale feasibility is the main challenge of SSF being the control of operational parameters and adequate reactor design the first locks. The current and future trends of SSF bioreactors for lignocellulolytic enzyme production are summarized. SSF allows the production of lignocellulolytic enzymes with high stability at different temperatures and pH, improving their applicability in different industrial settings.This work was supported by the project ‘Development of innovative sustainable protein and omega-3 rich feedstuffs for aquafeeds, from local agroindustrial by-products,’ reference POCI-01-0145-FEDER-030377, funded by European Regional Development Fund (ERDF). JMS was supported by contract from this project. This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2019 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. PL was supported by the PhD grant (SFRH/BD/114777/2016) funded by FCT. DS was supported by the doctoral programme ‘Agricultural Production Chains e from fork to farm’ (PD/ 00122/2012). HF was supported by the PhD grant SFRH/BD/131219/2017, and MF was funded by SFRH/BD/143614/2019, both funded by FCT. MG and DF were supported by project InovFeed (ref. MAR-02.01.01-FEAMP0111; Mar2020).info:eu-repo/semantics/publishedVersio

Alginate Oligosaccharide-Induced Modification of the lasI-lasR and rhlI-rhlR Quorum Sensing Systems in Pseudomonas aeruginosa

Pseudomonas aeruginosa plays a major role in many chronic infections. Its ability to readily form biofilms contributes to its success as an opportunistic pathogen and its resistance/tolerance to antimicrobial/antibiotic therapy. A low-molecular-weight alginate oligomer (OligoG CF-5/20) derived from marine algae has previously been shown to impair motility in P. aeruginosa biofilms and disrupt pseudomonal biofilm assembly. As these bacterial phenotypes are regulated by quorum sensing (QS), we hypothesized that OligoG CF-5/20 may induce alterations in QS signaling in P. aeruginosa. QS regulation was studied by using Chromobacterium violaceum CV026 biosensor assays that showed a significant reduction in acyl homoserine lactone (AHL) production following OligoG CF-5/20 treatment (≥2%; P < 0.05). This effect was confirmed by liquid chromatography-mass spectrometry analysis of C4-AHL and 3-oxo-C12-AHL production (≥2%; P < 0.05). Moreover, quantitative PCR showed that reduced expression of both the las and rhl systems was induced following 24 h of treatment with OligoG CF-5/20 (≥0.2%; P < 0.05). Circular dichroism spectroscopy indicated that these alterations were not due to steric interaction between the AHL and OligoG CF-5/20. Confocal laser scanning microscopy (CLSM) and COMSTAT image analysis demonstrated that OligoG CF-5/20-treated biofilms had a dose-dependent decrease in biomass that was associated with inhibition of extracellular DNA synthesis (≥0.5%; P < 0.05). These changes correlated with alterations in the extracellular production of the pseudomonal virulence factors pyocyanin, rhamnolipids, elastase, and total protease (P < 0.05). The ability of OligoG CF-5/20 to modify QS signaling in P. aeruginosa PAO1 may influence critical downstream functions such as virulence factor production and biofilm formation

Performance of some estimators in covariance structure models with nonnormal data

Maximum likelihood (ML) and generalized least squares (GLS) methods are frequently used in CSM. ML and GLS estimators assume that data are multivariate normally distributed. However, the assumption of multivariate normality is often violated in practice and Monte Carlo studies (e.g., Harlow, 1985) have shown that normal theory estimators are often not robust for non-normal distributions. Three approaches to dealing with the problem of non-normal data in CSM have been to (a) develop estimators (e.g., ADF) based on less restrictive distributional assumptions, (b) correct the relevant statistics obtained from normal theory estimators, and (c) investigate conditions where normal theory methods are robust. A simulation was conducted to examine the performance of the three approaches at a sample size of 500 for 6-variable, 15-variable, and 16-variable confirmatory factor analysis (CFA) models for multivariate and/or moderately non-normal data. For multivariate normal data, ML, GLS, and ADF estimators did fairly well with respect to the parameter estimates, standard errors, and goodness of fit statistics for the 6-variable CFA model at a sample size of 500. In contrast, the ADF goodness of fit statistic completely broke down for the larger models (15 or 16-variables) at a sample size of 500. However, ML and GLS goodness of fit statistics performed well for the 15 and 16-variable models and multivariate normal data. For moderately non-normal data, the ADF estimator outperformed ML and GLS estimators for the 6 variable model and a sample size of 500. In addition, corrected ML and GLS (ROBUST) standard errors outperformed uncorrected ML and GLS standard errors for moderately non-normal data

Skills Availability in the Jordanian Educational Process Outputs Compared with the Local Labor Market Needs

Skills Availability in the Jordanian Educational Process Outputs Compared with the Local Labor Market NeedsAbstractThe aim of this study is to measure the level of soft skills obtaining among Jordanian public and private university undergraduates. This paper focused on studying four skills; Communication, Technology Skills, Initiative and Creativity, and Foreign Languages skills. Two hundreds and twenty eight students (120 males and 108 females) from public and private Jordanian universities in the academic year 2007/2008 participated in this study. Data for this study was collected through answering developed questionnaire.    The results of the study showed that both public and private university undergraduate students in Jordan acquire soft skills to a large extent. The study also showed that there were some variation in the level of skills acquired based on gender, type of major, as well as university. This comes because of the attempt of the Jordanian higher education policy makers to improve the quality of the higher education sector and make it more responsive to the economy. The study ended up with some recommendation and suggestions