Analisa Pengaruh Penggunaan Serat Serabut Kelapa dalam Presentase Tertentu pada Beton Mutu Tinggi

The use of additional material as ingredients in the manufacture of concrete mixes is increasingly growing. The material used is also increasingly varied, depending on the expected results. This research aims to know the influence of the addition of coconut fibres material with percentage of 1,5 %, 2 %, 2,5 %, and 3 % as an alternative to the strength of high-quality concrete. Research methods done by producing cylindrical and beam concrete samples for testing against the force then conducted concrete. Furthermore, the analysis has been done and the results of testing and comparing the respective strength of the composition of concrete produced. Based on the test results of data concrete cylinder compression strength and tensile strength concrete beams, it was concluded that the increasing of compressive strength up to 9% can be reached by use of additional material coconut fibers 1,5%and increasing of tensile strength up to 19,7% can be reached by use of additional coconut fiber 2%. Therefore, the additional coconut fibers on concrete mixture has strong relationship to increase tensile strength of high strength concrete

PEMANFAATAN KARBON AKTIF TEMPURUNG KENARI SEBAGAI ADSORBEN FENOL DAN KLOROFENOL DALAM PERAIRAN

Marina Chimica Acta 6(1) 2005Artikel ini menyajikan hasil investigasi yang dilakukan pada penghilangan fenol dan 4-klorofenol dari\ud lingkungan air dengan menggunakan karbon aktif tempurung kenari. adsorben dibuat dengan mengarangkan\ud tempurung kenari menggunakan sekam padi dan arang yang terbentuk dipanaskan pada temperatur 200 oC .\ud hasil yang diperoleh dengan ukuran 100 ??? 200 mesh diaktivasi pada suhu 500 oC. penentuan konsentrasi fenol\ud dan 4-klorofenol yang teradsorpsi pada waktu kesetimbangan adsorpsi dijadikan dasar untuk mempelajari\ud pengaruh ph dan konsentrasi awal terhadap efektivitas adsorpsi senyawa-senyawa fenol oleh karbon aktif\ud tempurung kenari. Persamaan Freundlich dan Langmuir digunakan untuk mempelajari isotermal adsorpsi.\ud hasil penelitian menunjukkan bahwa waktu optimum adsorpsi fenol dan 4-klorofenol oleh karbon aktif\ud berturut-turut adalah 135 dan 150 menit, adsorpsi kedua senyawa fenol memenuhi persamaan laju orde dua\ud semu dengan tetapan laju 0,082 dan 0,127 g mg-1 menit-1 berturut-turut untuk adsorpsi fenol dan 4-klorofenol.\ud isotermal adsorpsi kedua senyawa fenol memenuhi persamaan langmuir dan freundlich. kapasitas adsorpsi\ud fenol lebih besar dari kapasitas adsorpsi 4-klorofenol

Down-expression of inducible nitric oxide synthase (iNOS) and endothelial (Enos) proteins and mRNA iNOS in bronchiectasis in vivo

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Naturally occurring diacetyl and 2,3-pentanedione concentrations associated with roasting and grinding unflavored coffee beans in a commercial setting

AbstractOver the last decade, concerns have been raised about potential respiratory health effects associated with occupational exposure to the flavoring additives diacetyl and 2,3-pentanedione. Both of these diketones are also natural components of many foods and beverages, including roasted coffee. To date, there are no published studies characterizing workplace exposures to these diketones during commercial roasting and grinding of unflavored coffee beans. In this study, we measured naturally occurring diacetyl, 2,3-pentanedione, and respirable dust at a facility that roasts and grinds coffee beans with no added flavoring agents. Sampling was conducted over the course of three roasting batches and three grinding batches at varying distances from a commercial roaster and grinder. The three batches consisted of lightly roasted soft beans, lightly roasted hard beans, and dark roasted hard beans. Roasting occurred for 37 to 41min, and the grinding process took between 8 and 11min. Diacetyl, 2,3-pentanedione, and respirable dust concentrations measured during roasting ranged from less than the limit of detection (<LOD) to 0.0039ppm, <LOD to 0.018ppm, and <LOD to 0.31mg/m3, respectively. During grinding, diacetyl, 2,3-pentanedione, and respirable dust concentrations ranged from 0.018 to 0.39ppm, 0.0089 to 0.21ppm, and <LOD to 1.7mg/m3, respectively. For any given bean/roast combination and sample location, diketone concentrations during grinding were higher than those measured during roasting. During grinding, concentrations decreased with increased distance from the source. Measured concentrations of both diketones were higher during grinding of soft beans than hard beans. The results indicate that airborne concentrations of naturally occurring diacetyl and 2,3-pentanedione associated with unflavored coffee processing: (1) are similar to the concentrations that have been measured in food flavoring facilities; (2) are likely to exceed some recommended short-term occupational exposure limits, but; (3) based on previous analyses of exposure response relationships in animal studies, are far below the concentrations that are expected to cause even minimal responses in the human respiratory tract

A hybrid, auto-adaptive, and rule-based multi-agent approach using evolutionary algorithms for improved searching

Selecting the most appropriate heuristic for solving a specific problem is not easy, for many reasons. This article focuses on one of these reasons: traditionally, the solution search process has operated in a given manner regardless of the specific problem being solved, and the process has been the same regardless of the size, complexity and domain of the problem. To cope with this situation, search processes should mould the search into areas of the search space that are meaningful for the problem. This article builds on previous work in the development of a multi-agent paradigm using techniques derived from knowledge discovery (data-mining techniques) on databases of so-far visited solutions. The aim is to improve the search mechanisms, increase computational efficiency and use rules to enrich the formulation of optimization problems, while reducing the search space and catering to realistic problems.Izquierdo Sebastián, J.; Montalvo Arango, I.; Campbell, E.; Pérez García, R. (2015). A hybrid, auto-adaptive, and rule-based multi-agent approach using evolutionary algorithms for improved searching. Engineering Optimization. 1-13. doi:10.1080/0305215X.2015.1107434S113Becker, U., & Fahrmeir, L. (2001). Bump Hunting for Risk: a New Data Mining Tool and its Applications. Computational Statistics, 16(3), 373-386. doi:10.1007/s001800100073Bouguessa, M., & Shengrui Wang. (2009). Mining Projected Clusters in High-Dimensional Spaces. IEEE Transactions on Knowledge and Data Engineering, 21(4), 507-522. doi:10.1109/tkde.2008.162Chong, I.-G., & Jun, C.-H. (2005). Performance of some variable selection methods when multicollinearity is present. Chemometrics and Intelligent Laboratory Systems, 78(1-2), 103-112. doi:10.1016/j.chemolab.2004.12.011CHONG, I., & JUN, C. (2008). Flexible patient rule induction method for optimizing process variables in discrete type. Expert Systems with Applications, 34(4), 3014-3020. doi:10.1016/j.eswa.2007.05.047Cole, S. W., Galic, Z., & Zack, J. A. (2003). Controlling false-negative errors in microarray differential expression analysis: a PRIM approach. Bioinformatics, 19(14), 1808-1816. doi:10.1093/bioinformatics/btg242FRIEDMAN, J. H., & FISHER, N. I. (1999). Statistics and Computing, 9(2), 123-143. doi:10.1023/a:1008894516817Geem, Z. W. (2006). Optimal cost design of water distribution networks using harmony search. Engineering Optimization, 38(3), 259-277. doi:10.1080/03052150500467430Goncalves, L. B., Vellasco, M. M. B. R., Pacheco, M. A. C., & Flavio Joaquim de Souza. (2006). Inverted hierarchical neuro-fuzzy BSP system: a novel neuro-fuzzy model for pattern classification and rule extraction in databases. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 36(2), 236-248. doi:10.1109/tsmcc.2004.843220Hastie, T., Friedman, J., & Tibshirani, R. (2001). The Elements of Statistical Learning. Springer Series in Statistics. doi:10.1007/978-0-387-21606-5Chih-Ming Hsu, & Ming-Syan Chen. (2009). On the Design and Applicability of Distance Functions in High-Dimensional Data Space. IEEE Transactions on Knowledge and Data Engineering, 21(4), 523-536. doi:10.1109/tkde.2008.178Hwang, S.-F., & He, R.-S. (2006). A hybrid real-parameter genetic algorithm for function optimization. Advanced Engineering Informatics, 20(1), 7-21. doi:10.1016/j.aei.2005.09.001Izquierdo, J., Montalvo, I., Pérez, R., & Fuertes, V. S. (2008). Design optimization of wastewater collection networks by PSO. Computers & Mathematics with Applications, 56(3), 777-784. doi:10.1016/j.camwa.2008.02.007Javadi, A. A., Farmani, R., & Tan, T. P. (2005). A hybrid intelligent genetic algorithm. Advanced Engineering Informatics, 19(4), 255-262. doi:10.1016/j.aei.2005.07.003Jin, X., Zhang, J., Gao, J., & Wu, W. (2008). Multi-objective optimization of water supply network rehabilitation with non-dominated sorting Genetic Algorithm-II. Journal of Zhejiang University-SCIENCE A, 9(3), 391-400. doi:10.1631/jzus.a071448Johns, M. B., Keedwell, E., & Savic, D. (2014). Adaptive locally constrained genetic algorithm for least-cost water distribution network design. Journal of Hydroinformatics, 16(2), 288-301. doi:10.2166/hydro.2013.218Jourdan, L., Corne, D., Savic, D., & Walters, G. (2005). Preliminary Investigation of the ‘Learnable Evolution Model’ for Faster/Better Multiobjective Water Systems Design. Evolutionary Multi-Criterion Optimization, 841-855. doi:10.1007/978-3-540-31880-4_58Kamwa, I., Samantaray, S. R., & Joos, G. (2009). Development of Rule-Based Classifiers for Rapid Stability Assessment of Wide-Area Post-Disturbance Records. IEEE Transactions on Power Systems, 24(1), 258-270. doi:10.1109/tpwrs.2008.2009430Kang, D., & Lansey, K. (2012). Revisiting Optimal Water-Distribution System Design: Issues and a Heuristic Hierarchical Approach. Journal of Water Resources Planning and Management, 138(3), 208-217. doi:10.1061/(asce)wr.1943-5452.0000165Keedwell, E., & Khu, S.-T. (2005). A hybrid genetic algorithm for the design of water distribution networks. Engineering Applications of Artificial Intelligence, 18(4), 461-472. doi:10.1016/j.engappai.2004.10.001Kehl, V., & Ulm, K. (2006). Responder identification in clinical trials with censored data. Computational Statistics & Data Analysis, 50(5), 1338-1355. doi:10.1016/j.csda.2004.11.015Liu, X., Minin, V., Huang, Y., Seligson, D. B., & Horvath, S. (2004). Statistical Methods for Analyzing Tissue Microarray Data. Journal of Biopharmaceutical Statistics, 14(3), 671-685. doi:10.1081/bip-200025657Marchi, A., Dandy, G., Wilkins, A., & Rohrlach, H. (2014). Methodology for Comparing Evolutionary Algorithms for Optimization of Water Distribution Systems. Journal of Water Resources Planning and Management, 140(1), 22-31. doi:10.1061/(asce)wr.1943-5452.0000321Martínez-Rodríguez, J. B., Montalvo, I., Izquierdo, J., & Pérez-García, R. (2011). Reliability and Tolerance Comparison in Water Supply Networks. Water Resources Management, 25(5), 1437-1448. doi:10.1007/s11269-010-9753-2McClymont, K., Keedwell, E., Savić, D., & Randall-Smith, M. (2013). A general multi-objective hyper-heuristic for water distribution network design with discolouration risk. Journal of Hydroinformatics, 15(3), 700-716. doi:10.2166/hydro.2012.022McClymont, K., Keedwell, E. C., Savić, D., & Randall-Smith, M. (2014). Automated construction of evolutionary algorithm operators for the bi-objective water distribution network design problem using a genetic programming based hyper-heuristic approach. Journal of Hydroinformatics, 16(2), 302-318. doi:10.2166/hydro.2013.226Michalski, R. S. (2000). Machine Learning, 38(1/2), 9-40. doi:10.1023/a:1007677805582Montalvo, I., Izquierdo, J., Pérez-García, R., & Herrera, M. (2014). Water Distribution System Computer-Aided Design by Agent Swarm Optimization. Computer-Aided Civil and Infrastructure Engineering, 29(6), 433-448. doi:10.1111/mice.12062Montalvo, I., Izquierdo, J., Schwarze, S., & Pérez-García, R. (2010). Multi-objective particle swarm optimization applied to water distribution systems design: An approach with human interaction. Mathematical and Computer Modelling, 52(7-8), 1219-1227. doi:10.1016/j.mcm.2010.02.017Nguyen, V. V., Hartmann, D., & König, M. (2012). A distributed agent-based approach for simulation-based optimization. Advanced Engineering Informatics, 26(4), 814-832. doi:10.1016/j.aei.2012.06.001Nicklow, J., Reed, P., Savic, D., Dessalegne, T., Harrell, L., … Chan-Hilton, A. (2010). State of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management. Journal of Water Resources Planning and Management, 136(4), 412-432. doi:10.1061/(asce)wr.1943-5452.0000053Onwubolu, G. C., & Babu, B. V. (2004). New Optimization Techniques in Engineering. Studies in Fuzziness and Soft Computing. doi:10.1007/978-3-540-39930-8Pelikan, M., Goldberg, D. E., & Lobo, F. G. (2002). Computational Optimization and Applications, 21(1), 5-20. doi:10.1023/a:1013500812258Reed, P. M., Hadka, D., Herman, J. D., Kasprzyk, J. R., & Kollat, J. B. (2013). Evolutionary multiobjective optimization in water resources: The past, present, and future. Advances in Water Resources, 51, 438-456. doi:10.1016/j.advwatres.2012.01.005Shang, W., Zhao, S., & Shen, Y. (2009). A flexible tolerance genetic algorithm for optimal problems with nonlinear equality constraints. Advanced Engineering Informatics, 23(3), 253-264. doi:10.1016/j.aei.2008.09.001Vrugt, J. A., & Robinson, B. A. (2007). Improved evolutionary optimization from genetically adaptive multimethod search. 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R., & Zecchin, A. C. (2014). Coupled Binary Linear Programming–Differential Evolution Algorithm Approach for Water Distribution System Optimization. Journal of Water Resources Planning and Management, 140(5), 585-597. doi:10.1061/(asce)wr.1943-5452.000036

Identifying factors that affected student enrolment in Additional Mathematics for urban areas of Kuantan district

The skilful and qualified Science, Technology, Engineering and Mathematics (STEM) workforces are expected to be in high demand in the 21st digital economy. In Malaysia public education system, the principal key to STEM education is Additional Mathematics. However, the statistics depicted that the number of upper secondary students enrolled in Additional Mathematics have been severely delineated. Furthermore, the prerequisite to enrol in STEM and Technical and Vocational Education and Training (TVET) courses in tertiary education is achieving a minimum grade C for Additional Mathematics. Therefore, the principal objective of this article is to identify the significant factors that affected the upper secondary students enrolled in Additional Mathematics using Pearson's chi-square test without Yates continuity correction and unadjusted odds ratio (OR). A validated questionnaire comprised nine potential factors that affected enrolment in additional mathematics was distributed to 389 Form Four students' cohort 2020 from four selected urban government schools to pursue this objective. Based on the finding of this article, several initiatives might be taken by the policymakers, such as the teachers may enhancing and throughout the broad of STEM and TVET careers in the 21st digital economy era, while the students' parents can participate in schools in building the communicating and coordinating mechanism. Consequently, the number of upper secondary enrolled in STEM education might be increased to pipeline the future STEM and TVET human capitals in sustaining and stabilising the national economy in the digital era

Heritability and major gene effects on left ventricular mass in the Chinese population: a family study

BACKGROUND: Genetic components controlling for echocardiographically determined left ventricular (LV) mass are still unclear in the Chinese population. METHODS: We conducted a family study from the Chin-San community, Taiwan, and a total of 368 families, 1145 subjects, were recruited to undergo echocardiography to measure LV mass. Commingling analysis, familial correlation, and complex segregation analysis were applied to detect component distributions and the mode of inheritance. RESULTS: The two-component distribution model was the best-fitting model to describe the distribution of LV mass. The highest familial correlation coefficients were mother-son (0.379, P < .0001) and father-son (0.356, P < .0001). Genetic heritability (h(2)) of LV mass was estimated as 0.268 ± 0.061 (P < .0001); it decreased to 0.153 ± 0.052 (P = .0009) after systolic blood pressure adjustment. Major gene effects with polygenic components were the best-fitting model to explain the inheritance mode of LV mass. The estimated allele frequency of the gene was 0.089. CONCLUSION: There were significant familial correlations, heritability and a major gene effect on LV mass in the population-based families

Isotopic, geophysical and biogeochemical investigation of submarine groundwater discharge : IAEA-UNESCO intercomparison exercise at Mauritius Island

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Journal of Environmental Radioactivity 104 (2012): 24-45, doi:10.1016/j.jenvrad.2011.09.009.Submarine groundwater discharge (SGD) into a shallow lagoon on the west coast of Mauritius Island (Flic-en-Flac) was investigated using radioactive (3H, 222Rn, 223Ra, 224Ra, 226Ra, 228Ra) and stable (2H, 18O) isotopes and nutrients. SGD intercomparison exercises were carried out to validate the various approaches used to measure SGD including radium and radon measurements, seepage-rate measurements using manual and automated meters, sediment bulk conductivity and salinity surveys. SGD measurements using benthic chambers placed on the floor of the Flic-en-Flac Lagoon showed discharge rates up to 500 cm/day. Large variability in SGD was observed over distances of a few meters, which were attributed to different geomorphological features. Deployments of automated seepage meters captured the spatial and temporal variability of SGD with a mean seepage rate of 10 cm/day. The stable isotopic composition of submarine waters was characterized by significant variability and heavy isotope enrichment and was used to predict the contribution of fresh terrestrially derived groundwater to SGD (range from a few % to almost 100 %). The integrated SGD flux, estimated from seepage meters placed parallel to the shoreline, was 35 m3/m day, which was in a reasonable agreement with results obtained from hydrologic water balance calculation (26 m3/m day). SGD calculated from the radon inventory method using in situ radon measurements were between 5 and 56 m3/m per day. Low concentrations of radium isotopes observed in the lagoon water reflected the low abundance of U and Th in the basalt that makes up the island. High SGD rates contribute to high nutrients loading to the lagoon, potentially leading to eutrophication. Each of the applied methods yielded unique information about the character and magnitude of SGD. The results of the intercomparison studies have resulted a better understanding of groundwater-seawater interactions in coastal regions. Such information is an important pre-requisite for the protection management of coastal freshwater resources.The financial support provided by the IOC and IHP of UNESCO for travel arrangements, and by the IAEA’s Marine Environment Laboratories for logistics is highly acknowledged. MAC and MEG were supported in part by the US National Science Foundation (OCE-0425061 and OCE-0751525). PPP acknowledges a support provided by the EU Research & Development Operational Program funded by the ERDF (project No. 26240220004), and the Slovak Scientific Agency VEGA (grant No. 1/108/08). The International Atomic Energy Agency is grateful to the Government of the Principality of Monaco for support provided to its Marine Environment Laboratories