Development of marine environmental protection curricula for cadets at the Arab Academy for Science and Technology and Maritime Transport

Marine environmental protection is becoming, increasingly, a world-wide demand. Marine accidental and operational pollution due to shipping activities, though contributing by a relatively small percentage of the annual global inputs into the seas, is characterized by massive releases of oil or hazardous substances causing acute pollution, which enjoys media coverage and public concem. The human factor has always been behind most accidental and operational marine pollution from shipping activities The IMO emphasised the role of the human factor in the effective and efficient implementation of international regulations, including marine pollutin prevention, through the revised STCW 1978, as amended in 1995. _Consequently, the Arab Academy for Science and Technology and Maritime Transport (AAST&MT) in Egypt, as a regional maritime institute, has taken a commitment to work on promoting competence standard requirements of intemational regulations including marine pollution prevention. In order to achieve the objectives of the AAST&MT, conducting an assessment of the standards of maritime education and training conceming marine environmental protection was necessary. The Maritime Basic Studies Program (MBSP), a two-year academic common program for prospective officers in the AAST&MT, has been chosen in this dissertation to be reviewed, examined and evaluated. The methodology of standards assessment was followed at two levels: 1. Reviewing and analysing the curricular system of the MBSP evaluating adequacy and relevance of the subject areas concerning marine environmental protection. 2. Conducting a survey in the form of a questionnaire to evaluate the standards of environmental awareness of cadets in the AAST&M\u27I‘_ Consequently, ma.rine enviromnental protection curricula were prepared for the MBSP on basis of three major axis: 1. Deficiencies in the subject areas concerning marine environmental protection in the MBSP. 2. Standards of environmental awareness of cadets in the AAST&MT. 3. The competence and standard of knowledge requirements of the revised STCW 1978, as amended in 1995, concerning marine pollution prevention and antipollution procedures. The syllabuses were prepared to promote environmental culture by providing baseline marine environmental information. They cover international preventive regulations (prevention, mitigation and control), curative regulations (response and clean-up), liability and compensation in cases of oil pollution damage. UNCLOS 1982, which provides the international legal framework of enforcement of environmental legislation, was also covered

Early Diagnosis and Its Benefits in Sepsis Blood Purification Treatment

Abstract—Sepsis is a progressive medical condition charac-terized as an uncontrolled inflammatory response, which is the leading cause of death in non-coronary intensive care units in the United States. In sepsis treatment, accurate and timely diagnosis is essential for allowing physicians to design appropriate therapeutic strategies at early stages, when therapies are usually the most effective and the least costly. To make an adequate diagnosis, physicians usually rely on manual inspection of a large amount of complex, high-dimensional longitudinal data. We use our recently published data mining method for extracting patterns from such data and show that these patterns can be used to assist physicians in providing early diagnosis. In conducted experiments, we showed that combination of early diagnosis and blood purification therapy can rescue more patients (52%) than standard approach for blood purification therapy (32%). We also propose a hybrid therapy model that combines strengths of early and standard approaches and further improves the percentage of rescued patients. Finally, by correctly classifying 98 % of patients who didn’t need treatment, MSD method provides opportunity to reduce the total cost of treatments. I

A proposed protocol for GMP-BoK implementation gap analysis - case study at AASTMT

Purpose: Maritime Education and Training (MET) plays a crucial role in maintaining the safety and sustainability of the maritime industry. However, it remains behind the industry expectations to fulfill the gap regarding the required level of maritime capacities to safely control efficient new technology and keep them sustainable and effective during the industrial revolution era. The International Association of Maritime Universities (IAMU) developed the Global Maritime Professional Body of Knowledge (GMP-BoK) to address the current gap between the maritime industry expectations and the delivered Maritime Education and Training (MET) programs. Design/methodology/approach: This paper briefly introduces the GMP-BoK and proposes a protocol for a new analogous instrument to efficiently implement the GMP-BoK via a user-friendly method developed at the Arab Academy for Science, Technology and Maritime Transport (AASTMT). The developed analogous instrument helps maritime universities and institutes to digitalize and develop an integrated curriculum framework that is based on robust evaluation and data analysis to develop strategic plans to improve seafarer capabilities. Moreover, the paper suggests a protocol for mapping and analysis of maritime programs and courses, enabling educators to reliably perform gap analysis and identify repetitions within delivered courses and programs based on the GMP-BoK recommended practices. As a case study, the proposed protocol was validated utilizing the Maritime Engineering Technology Program (METP). Findings: The findings of this study revealed that the examined METP includes 30% repetition and focuses on the cognitive and psychomotor methods of education, with little focus on the affective technique

Islet Autoimmunity and HLA Markers of Presymptomatic and Clinical Type 1 Diabetes: Joint Analyses of Prospective Cohort Studies in Finland, Germany, Sweden, and the US

OBJECTIVETo combine prospective cohort studies, by including HLA harmonization, and estimate risk of islet autoimmunity and progression to clinical diabetes.RESEARCH DESIGN AND METHODSFor prospective cohorts in Finland, Germany, Sweden, and the U.S., 24,662 children at increased genetic risk for development of islet autoantibodies and type 1 diabetes have been followed. Following harmonization, the outcomes were analyzed in 16,709 infants-toddlers enrolled by age 2.5 years.RESULTSIn the infant-toddler cohort, 1,413 (8.5%) developed at least one autoantibody confirmed at two or more consecutive visits (seroconversion), 865 (5%) developed multiple autoantibodies, and 655 (4%) progressed to diabetes. The 15-year cumulative incidence of diabetes varied in children with one, two, or three autoantibodies at seroconversion: 45% (95% CI 40–52), 85% (78–90), and 92% (85–97), respectively. Among those with a single autoantibody, status 2 years after seroconversion predicted diabetes risk: 12% (10–25) if reverting to autoantibody negative, 30% (20–40) if retaining a single autoantibody, and 82% (80–95) if developing multiple autoantibodies. HLA-DR-DQ affected the risk of confirmed seroconversion and progression to diabetes in children with stable single-autoantibody status. Their 15-year diabetes incidence for higher- versus lower-risk genotypes was 40% (28–50) vs. 12% (5–38). The rate of progression to diabetes was inversely related to age at development of multiple autoantibodies, ranging from 20% per year to 6% per year in children developing multipositivity in ≤2 years or >7.4 years, respectively.CONCLUSIONSThe number of islet autoantibodies at seroconversion reliably predicts 15-year type 1 diabetes risk. In children retaining a single autoantibody, HLA-DR-DQ genotypes can further refine risk of progression.</div

Continuous Conditional Dependency Network for Structured Regression

Structured regression on graphs aims to predict response variables from multiple nodes by discovering and exploiting the dependency structure among response variables. This problem is challenging since dependencies among response variables are always unknown, and the associated prior knowledge is non-symmetric. In previous studies, various promising solutions were proposed to improve structured regression by utilizing symmetric prior knowledge, learning sparse dependency structure among response variables, or learning representations of attributes of multiple nodes. However, none of them are capable of efficiently learning dependency structure while incorporating non-symmetric prior knowledge. To achieve these objectives, we proposed Continuous Conditional Dependency Network (CCDN) for structured regression. The intuitive idea behind this model is that each response variable is not only dependent on attributes from the same node, but also on response variables from all other nodes. This results in a joint modeling of local conditional probabilities. The parameter learning is formulated as a convex optimization problem and an effective sampling algorithm is proposed for inference. CCDN is flexible in absorbing non-symmetric prior knowledge. The performance of CCDN on multiple datasets provides evidence of its structure recovery ability and superior effectiveness and efficiency as compared to the state-of-the-art alternatives