Hazard Analysis and Criteria for Software Safety in Electrotechnics

2006 ◽  
Author(s):  
A.V. Krumov
Keyword(s):  
Hazard Analysis ◽  
Software Safety

Hazard Analysis and Validation Metrics Framework for System of Systems Software Safety

2010 ◽  
Vol 4 (2) ◽  
pp. 186-197 ◽  
Author(s):  
James Bret Michael ◽  
Man-Tak Shing ◽  
Kristian John Cruickshank ◽  
Patrick James Redmond
Keyword(s):  
Hazard Analysis ◽  
System Of Systems ◽  
Software Safety ◽  
Validation Metrics ◽  
Systems Software

Food Safety Security: A new Concept for Enhancing Food Safety Measures

2012 ◽  
Vol 82 (3) ◽  
pp. 216-222 ◽  
Author(s):  
Venkatesh Iyengar ◽  
Ibrahim Elmadfa
Keyword(s):  
Food Safety ◽  
Hazard Analysis ◽  
Warning System ◽  
Shared Responsibility ◽  
Fine Tuning ◽  
Strategic Action ◽  
Surveillance Network ◽  
Measurement Systems ◽  
Critical Control Points ◽  
The Impact

The food safety security (FSS) concept is perceived as an early warning system for minimizing food safety (FS) breaches, and it functions in conjunction with existing FS measures. Essentially, the function of FS and FSS measures can be visualized in two parts: (i) the FS preventive measures as actions taken at the stem level, and (ii) the FSS interventions as actions taken at the root level, to enhance the impact of the implemented safety steps. In practice, along with FS, FSS also draws its support from (i) legislative directives and regulatory measures for enforcing verifiable, timely, and effective compliance; (ii) measurement systems in place for sustained quality assurance; and (iii) shared responsibility to ensure cohesion among all the stakeholders namely, policy makers, regulators, food producers, processors and distributors, and consumers. However, the functional framework of FSS differs from that of FS by way of: (i) retooling the vulnerable segments of the preventive features of existing FS measures; (ii) fine-tuning response systems to efficiently preempt the FS breaches; (iii) building a long-term nutrient and toxicant surveillance network based on validated measurement systems functioning in real time; (iv) focusing on crisp, clear, and correct communication that resonates among all the stakeholders; and (v) developing inter-disciplinary human resources to meet ever-increasing FS challenges. Important determinants of FSS include: (i) strengthening international dialogue for refining regulatory reforms and addressing emerging risks; (ii) developing innovative and strategic action points for intervention {in addition to Hazard Analysis and Critical Control Points (HACCP) procedures]; and (iii) introducing additional science-based tools such as metrology-based measurement systems.

PEMETAAN DAERAH RENTAN GEMPA BUMI SEBAGAI DASAR PERENCANAAN TATA RUANG DAN WILAYAH DI PROVINSI SULAWESI BARAT

KURVATEK ◽  
2017 ◽  
Vol 1 (2) ◽  
pp. 41-47
Author(s):  
Marinda noor Eva
Keyword(s):  
Seismic Hazard ◽  
Hazard Analysis ◽  
Probabilistic Seismic Hazard Analysis ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard

Penelitian mengenai daerah rawan gempa bumi ini menggunakan Metode Probabilistic Seismic Hazard Analysis (PSHA) di Provinsi Sulawesi Barat, dengan tujuan untuk memetakan tingkat kerawanan bahaya gempa bumi di Kabupaten Mamasa. Penelitian ini menggunakan data kejadian gempa bumi di Pulau Sulawesi dan sekitarnya dari tahun 1900 – 2015. Hasil pengolahan PSHA menggunakan Software Ez-Frisk 7.52 yang menghasilkan nilai hazard di batuan dasar pada kondisi PGA (T = 0,0 sekon), dengan periode ulang 500 tahun dan 2500 tahun berkisar antara (149,54 – 439,45) gal dan (287,18 – 762,81) gal. Nilai hazard di batuan dasar dengan kondisi spektra T = 0,2 sekon untuk periode ulang 500 tahun dan 2500 tahun adalah (307,04 – 1010,90) gal dan (569,48 – 1849,78) gal. Nilai hazard di batuan dasar dengan kondisi spektra T = 1,0 sekon untuk periode ulang 500 tahun dan 2500 tahun diperoleh nilai (118,01 – 265,75) gal dan (223,74 – 510,92) gal. Berdasarkan analisis PSHA, nilai PGA di Provinsi Sulawesi Barat dominan dipengaruhi oleh sumber gempa sesar.

Agent-based approach for process hazard analysis

2014 ◽  
Author(s):  
Dong Gao ◽  
Xin Xu ◽  
Beike Zhang ◽  
Xin Ma
Keyword(s):  
Hazard Analysis ◽  
Agent Based

Oct1 regulates cell growth of LNCaP cells and is a prognostic factor for prostate cancer

2020 ◽  
Author(s):  
Lungwani Muungo
Keyword(s):  
Prostate Cancer ◽  
Prognostic Factor ◽  
Hazard Analysis ◽  
Critical Role ◽  
Immunohistochemical Analysis ◽  
Lncap Cells ◽  
Cancer Specific Survival ◽  
High Gleason Score ◽  
Castrate Resistant ◽  
Transcription Factor 1

The androgen receptor (AR) plays a critical role in the development and the progression of prostate cancer. Alterations in theexpression of AR coregulators lead to AR hypersensitivity, which is one of the mechanisms underlying the progression ofprostate cancer into a castrate-resistant state. Octamer transcription factor 1 (Oct1) is a ubiquitous member of the POUhomeodomainfamily that functions as a coregulator of AR. In our study, the contribution of Oct1 to prostate cancerdevelopment was examined. Immunocytochemistry analysis showed that Oct1 is expressed in the nuclei of LNCaP cells.siRNA-mediated silencing of Oct1 expression inhibited LNCaP cell proliferation. Immunohistochemical analysis of Oct1expression in tumor specimens obtained from 102 patients with prostate cancer showed a positive correlation of Oct1immunoreactivity with a high Gleason score and AR immunoreactivity (p 5 0.0042 and p < 0.0001, respectively). Moreover,patients with high immunoreactivity of Oct1 showed a low cancer-specific survival rate, and those patients with highimmunoreactivities of both Oct1 and AR exhibited poorer cancer-specific prognosis. Multivariate hazard analysis revealed asignificant correlation between high Oct1 immunoreactivity and poor cancer-specific survival (p 5 0.012). These resultsdemonstrate that Oct1 can be a prognostic factor in prostate cancer as a coregulator of AR and may lead to the developmentof a new therapeutic intervention for prostate cancer.

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