SISTEM PENDUKUNG KEPUTUSAN POLA OLAHRAGA BERDASARKAN HASIL YANG INGIN DICAPAI MENGGUNAKAN FUZZY DATABASE MODEL TAHANI

Pada saat ini, perkembangan di dunia kesehatan telah berkembang secara cepat sehingga mendorong para ahli untuk merancang sebuah teknologi yang dapat mengambil keputusan didalam bidang kesehatan. Kesehatan merupakan hal sangat mahal dan sangat penting bagi keberlangsungan hidup manusia. Untuk mendapatkan tubuh yang sehat tentunya di butuhkan olahraga yang teratur. Olahraga dilakukan juga harus dengan porsi yang dibutuhkan oleh tubuh. Ketidaktahuan akan porsi olahraga yang dibutuhkan oleh tubuh manusia ini yang menjadi masalah bagi kebanyakan orang. Penelitian ini menggunakan metode studi literature dalam pengumpulan data serta fuzzy database model tahani. Pengembangan sistemnya menggunakan metode waterfall. Pemodelan analisis dan desain menggunakan bahasa pemograman PHP dan database server MySQL. Metode pengujian menggunakan pengujian white box.  Hasil penelitian ini adalah sebuah sistem pendukung keputusan pola olahraga berbasis website yang dapat memudahkan pengguna dalam menentukan pola olahraga yang cocok dilakukan sesuai data kriteria yaitu umur, berat badan dan tinggi badan

Elution of gentamicin and vancomycin from polymethylmethacrylate beads and hip spacers in vivo

Background and purpose Late infections after total hip arthroplasty are still a problem. Treatment procedures include resection arthroplasty with implantation of antibiotic-loaded beads or implantation of an antibiotic-impreganted spacer. However, little is known about antibiotic elution from bone cement beyond the first 2–3 postoperative days in humans

ICoVeR - an interactive visualization tool for verification and refinement of metagenomic bins.

BACKGROUND: Recent advances in high-throughput sequencing allow for much deeper exploitation of natural and engineered microbial communities, and to unravel so-called "microbial dark matter" (microbes that until now have evaded cultivation). Metagenomic analyses result in a large number of genomic fragments (contigs) that need to be grouped (binned) in order to reconstruct draft microbial genomes. While several contig binning algorithms have been developed in the past 2 years, they often lack consensus. Furthermore, these software tools typically lack a provision for the visualization of data and bin characteristics. RESULTS: We present ICoVeR, the Interactive Contig-bin Verification and Refinement tool, which allows the visualization of genome bins. More specifically, ICoVeR allows curation of bin assignments based on multiple binning algorithms. Its visualization window is composed of two connected and interactive main views, including a parallel coordinates view and a dimensionality reduction plot. To demonstrate ICoVeR's utility, we used it to refine disparate genome bins automatically generated using MetaBAT, CONCOCT and MyCC for an anaerobic digestion metagenomic (AD microbiome) dataset. Out of 31 refined genome bins, 23 were characterized with higher completeness and lower contamination in comparison to their respective, automatically generated, genome bins. Additionally, to benchmark ICoVeR against a previously validated dataset, we used Sharon's dataset representing an infant gut metagenome. CONCLUSIONS: ICoVeR is an open source software package that allows curation of disparate genome bins generated with automatic binning algorithms. It is freely available under the GPLv3 license at https://git.list.lu/eScience/ICoVeR . The data management and analytical functions of ICoVeR are implemented in R, therefore the software can be easily installed on any system for which R is available. Installation and usage guide together with the example files ready to be visualized are also provided via the project wiki. ICoVeR running instance preloaded with AD microbiome and Sharon's datasets can be accessed via the website

A 16S rRNA gene Illumina–based barcoded assay design for high throughput characterisation of microbial communities from anaerobic digesters

High throughput sequencing of 16S/18S rRNA gene is becoming an indispensable tool to explore microbial community ecology. To date, most of the studies using next generation amplicon sequencing of microorganisms involved in the anaerobic digestion process (AD) are based on the 454 pyrosequencing. However, the cost per read obtained with the Illumina technology is currently less than 1/100 of that for the 454 pyrosequencing, thus enabling throughout sequencing and larger number of samples to be analysed per study (e.g. given the current Miseq output, around 100 000 reads per sample can be expected for a pool of 96 libraries). Moreover, the Illumina technology is less biased by the GC content of the template and currently allows for a relatively long sequence read of 600 bp (2 x 300bp). This consideration is particularly important, since longer sequences permit for more accurate assignment to a taxonomic group. Here, we designed and optimized an Illumina–based 16S rRNA amplicon approach for a high throughput characterization of microbial communities from different AD

Educating the Future Educators: the quest for professionalism in early childhood education

This article examines the implications of recent and proposed changes to the college-based training of practitioners in early childhood education (ECE). These changes will change the length of courses by shortening them and, therefore, the depth of teaching that students will experience on a college-based course. The links between level of education and improved outcomes for children are discussed. This colloquium explores how these changes may impact on the professionalization of the early childhood workforce. Definitions of professionalism found in the early childhood literature and the notion of the professional ECE student are explored. The current barriers to viewing ECE as a profession and the ongoing professionalism of the field are discussed, as are possible solutions to removing the barriers

A year of monitoring 20 mesophilic full-scale bioreactors reveals the existence of stable but different core microbiomes in bio-waste and wastewater anaerobic digestion systems

Abstract Background Anaerobic digestion (AD) is a microbe-driven process of biomass decomposition to CH4 and CO2. In addition to renewable and cost-effective energy production, AD has emerged in the European Union as an environmentally friendly model of bio-waste valorisation and nutrient recycling. Nevertheless, due to the high diversity of uncharacterised microbes, a typical AD microbiome is still considered as “dark matter”. Results Using the high-throughput sequencing of small rRNA gene, and a monthly monitoring of the physicochemical parameters for 20 different mesophilic full-scale bioreactors over 1 year, we generated a detailed view of AD microbial ecology towards a better understanding of factors that influence and shape these communities. By studying the broadly distributed OTUs present in over 80% of analysed samples, we identified putatively important core bacteria and archaea to the AD process that accounted for over 70% of the whole microbial community relative abundances. AD reactors localised at the wastewater treatment plants were shown to operate with distinct core microbiomes than the agricultural and bio-waste treating biogas units. We also showed that both the core microbiomes were composed of low (with average community abundance ≤ 1%) and highly abundant microbial populations; the vast majority of which remains yet uncharacterised, e.g. abundant candidate Cloacimonetes. Using non-metric multidimensional scaling, we observed microorganisms grouping into clusters that well reflected the origin of the samples, e.g. wastewater versus agricultural and bio-waste treating biogas units. The calculated diversity patterns differed markedly between the different community clusters, mainly due to the presence of highly diverse and dynamic transient species. Core microbial communities appeared relatively stable over the monitoring period. Conclusions In this study, we characterised microbial communities in different AD systems that were monitored over a 1-year period. Evidences were shown to support the concept of a core community driving the AD process, whereas the vast majority of dominant microorganisms remain yet to be characterised

ICoVeR – an interactive visualization tool for verification and refinement of metagenomic bins

Abstract Background Recent advances in high-throughput sequencing allow for much deeper exploitation of natural and engineered microbial communities, and to unravel so-called “microbial dark matter” (microbes that until now have evaded cultivation). Metagenomic analyses result in a large number of genomic fragments (contigs) that need to be grouped (binned) in order to reconstruct draft microbial genomes. While several contig binning algorithms have been developed in the past 2 years, they often lack consensus. Furthermore, these software tools typically lack a provision for the visualization of data and bin characteristics. Results We present ICoVeR, the Interactive Contig-bin Verification and Refinement tool, which allows the visualization of genome bins. More specifically, ICoVeR allows curation of bin assignments based on multiple binning algorithms. Its visualization window is composed of two connected and interactive main views, including a parallel coordinates view and a dimensionality reduction plot. To demonstrate ICoVeR’s utility, we used it to refine disparate genome bins automatically generated using MetaBAT, CONCOCT and MyCC for an anaerobic digestion metagenomic (AD microbiome) dataset. Out of 31 refined genome bins, 23 were characterized with higher completeness and lower contamination in comparison to their respective, automatically generated, genome bins. Additionally, to benchmark ICoVeR against a previously validated dataset, we used Sharon’s dataset representing an infant gut metagenome. Conclusions ICoVeR is an open source software package that allows curation of disparate genome bins generated with automatic binning algorithms. It is freely available under the GPLv3 license at https://git.list.lu/eScience/ICoVeR . The data management and analytical functions of ICoVeR are implemented in R, therefore the software can be easily installed on any system for which R is available. Installation and usage guide together with the example files ready to be visualized are also provided via the project wiki. ICoVeR running instance preloaded with AD microbiome and Sharon’s datasets can be accessed via the website