5 research outputs found

    Analisis Strategi Penerapan Sistem Manajemen Keamanan Pangan HACCP (Hazard Analysis and Critical Control Points) Di PT. Sierad Produce Tbk. Parung

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    Quality and safety food products problem was usually after thought in the food industry development issues, accordance with the consumer\u27s desirability that understand the importance of product quality and food safety. Hazard Analysis and Critical Control Points (HACCP) certification is one way for company to implementing food safety. Sierad Produce Corp. at this moment has obtained HACCP certificate to produce chicken carcasses.But the implementation need to be controlled, as the case of foodborne illness and foodborne disease can occur easily if not properly controlled. The main objective of this research is to develop the best strategy to implement HACCP and to maintain the food safety quality system at Sierad Produce Corp. The information and data that has been collected within this research were covering both the primary and secondary data based on the date of September 2012 to December 2012. The methods used in this research are descriptive analysis, Internal Factor Evaluation (IFE), External Factor Evaluation (EFE), Internal External (IE), Strength Weakness Opportunity Threat (SWOT) and Analysis Hierarchy Process (AHP). Based on this research, the best strategy for implementing HACCP and sustain the system on Sierad Produce are Critical Control Points (CCP) evaluation and improvement of production room

    Experimental paradigm.

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    <p>Volunteers underwent Bispectral monitoring and EEG recording during each of the four experimental sessions: wakefulness, moderate sedation (OAA/S = 3), deep sedation (OAA/S = 1), and recovery (OAA/S = 5). Dexmedetomidine or propofol was administered intravenously and titrated to achieve the required sedation level.</p

    Changes in a raw EEG trace of dexmedetomidine sedation and propofol sedation from channel Fz.

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    <p>WA, wakefulness; MS, moderate sedation; DS, deep sedation; RS, recovery state (RS). During MS and DS, the EEG differences between the two agents are obvious.</p

    Spectral analysis of EEG from channel Fz for both dexmedetomidine sedation and propofol sedation.

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    <p>(A-B) Mean power spectra of WA (red), MS (green), DS (blue) and RS (black) for the two agents. (C-D) The green line represents the bootstrapped mean spectra of the difference between MS and WA for the two agents, and the gray space represents the bootstrapped 95% confidence interval bounds for the difference. (E-F) The blue line represents the bootstrapped mean spectra of the difference between DS and WA for the two agents, and the gray space represents the bootstrapped 95% confidence interval bounds for the difference. (G-H) The black line represents the bootstrapped mean spectra of the difference between RS and WA for the two agents, and the gray space represents the bootstrapped 95% confidence interval bounds for the difference. (I-J) The blue line represents the bootstrapped mean spectra of the difference between DS and MS for the two agents, and the gray space represents the bootstrapped 95% confidence interval bounds for the difference. The horizontal solid red lines represent the frequency ranges at which significant differences exist between each sedation state and WA, and the solid green lines represent the frequency ranges at which significant differences exist between DS and MS. WA, wakefulness; MS, moderate sedation; DS, deep sedation; RS, recovery state (RS).</p

    Bispectral (BIS) value during the dexmedetomidine/propofol sedation procedure.

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    <p>Data are shown as the mean ± standard deviation. *<i>P<</i> 0.05, ***<i>P <</i>0.001. WA, wakefulness; MS, moderate sedation; DS, deep sedation; RS, recovery state (RS).</p
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