Mortality from neurodegenerative disease and exposure to extremely low-frequency magnetic fields: 31 years of observations on Swiss railway employees

AIMS: The objective of the present study was to investigate the relationship between extremely low-frequency magnetic field (ELF-MF) exposure and mortality from several neurodegenerative conditions in Swiss railway employees. METHODS: We studied a cohort of 20,141 Swiss railway employees with 464,129 person-years of follow-up between 1972 and 2002. For each individual, cumulative exposure was calculated from on-site measurements and modelling of past exposure. We compared cause-specific mortality in highly exposed train drivers (mean exposure: 21 microT) with less exposed occupational groups (for example station masters: 1 microT). RESULTS: The hazard ratio for train drivers compared to station masters was 1.96 [95% confidence interval (CI) = 0.98-3.92] for senile dementia and 3.15 (95% CI = 0.90-11.04) for Alzheimer's disease. For every 10 microT years of cumulative exposure senile dementia mortality increased by 5.7% (95% CI = 1.3-10.4), Alzheimer's disease by 9.4% (95% CI = 2.7-16.4) and amyotrophic lateral sclerosis by 2.1% (95% CI = -6.8 to 11.7). There was no evidence for an increase in mortality from Parkinson's disease and multiple sclerosis. CONCLUSIONS: This study suggests a link between exposure to ELF-MF and Alzheimer's disease and indicates that ELF-MF might act in later stages of the disease process.

Leukaemia, brain tumours and exposure to extremely low frequency magnetic fields: cohort study of Swiss railway employees

AIMS: To investigate the relationship between extremely low frequency magnetic field (ELF-MF) exposure and mortality from leukaemia and brain tumour in a cohort of Swiss railway workers. METHODS: 20,141 Swiss railway employees with 464,129 person-years of follow-up between 1972 and 2002 were studied. Mortality rates for leukaemia and brain tumour of highly exposed train drivers (21 muT average annual exposure) were compared with medium and low exposed occupational groups (i.e. station masters with an average exposure of 1 muT). In addition, individual cumulative exposure was calculated from on-site measurements and modelling of past exposures. RESULTS: The hazard ratio (HR) for leukaemia mortality of train drivers was 1.43 (95% CI 0.74 to 2.77) compared with station masters. For myeloid leukaemia the HR of train drivers was 4.74 (95% CI 1.04 to 21.60) and for Hodgkin's disease 3.29 (95% CI 0.69 to 15.63). Lymphoid leukaemia, non-Hodgkin's disease and brain tumour mortality were not associated with magnetic field exposure. Concordant results were obtained from analyses based on individual cumulative exposure. CONCLUSIONS: Some evidence of an exposure-response association was found for myeloid leukaemia and Hodgkin's disease, but not for other haematopoietic and lymphatic malignancies and brain tumours.

Cardiovascular mortality and exposure to extremely low frequency magnetic fields: a cohort study of Swiss railway workers

BACKGROUND: Exposure to intermittent magnetic fields of 16 Hz has been shown to reduce heart rate variability, and decreased heart rate variability predicts cardiovascular mortality. We examined mortality from cardiovascular causes in railway workers exposed to varying degrees to intermittent 16.7 Hz magnetic fields. METHODS: We studied a cohort of 20,141 Swiss railway employees between 1972 and 2002, including highly exposed train drivers (median lifetime exposure 120.5 muT-years), and less or little exposed shunting yard engineers (42.1 muT-years), train attendants (13.3 muT-years) and station masters (5.7 muT-years). During 464,129 person-years of follow up, 5,413 deaths were recorded and 3,594 deaths were attributed to cardio-vascular diseases. We analyzed data using Cox proportional hazards models. RESULTS: For all cardiovascular mortality the hazard ratio compared to station masters was 0.99 (95%CI: 0.91, 1.08) in train drivers, 1.13 (95%CI: 0.98, 1.30) in shunting yard engineers, and 1.09 (95%CI: 1.00, 1.19) in train attendants. Corresponding hazard ratios for arrhythmia related deaths were 1.04 (95%CI: 0.68, 1.59), 0.58 (95%CI: 0.24, 1.37) and 10 (95%CI: 0.87, 1.93) and for acute myocardial infarction 1.00 (95%CI: 0.73, 1.36), 1.56 (95%CI: 1.04, 2.32), and 1.14 (95%CI: 0.85, 1.53). The hazard ratio for arrhythmia related deaths per 100 muT-years of cumulative exposure was 0.94 (95%CI: 0.71, 1.24) and 0.91 (95%CI: 0.75, 1.11) for acute myocardial infarction. CONCLUSION: This study provides evidence against an association between long-term occupational exposure to intermittent 16.7 Hz magnetic fields and cardiovascular mortality.

DESIGN AND IMPLEMENT DYNAMIC PROGRAMMING BASED DISCRETE POWER LEVEL SMART HOME SCHEDULING USING FPGA

With the development and capabilities of the Smart Home system, people today are entering an era in which household appliances are no longer just controlled by people, but also operated by a Smart System. This results in a more efficient, convenient, comfortable, and environmentally friendly living environment. A critical part of the Smart Home system is Home Automation, which means that there is a Micro-Controller Unit (MCU) to control all the household appliances and schedule their operating times. This reduces electricity bills by shifting amounts of power consumption from the on-peak hour consumption to the off-peak hour consumption, in terms of different “hour price”. In this paper, we propose an algorithm for scheduling multi-user power consumption and implement it on an FPGA board, using it as the MCU. This algorithm for discrete power level tasks scheduling is based on dynamic programming, which could find a scheduling solution close to the optimal one. We chose FPGA as our system’s controller because FPGA has low complexity, parallel processing capability, a large amount of I/O interface for further development and is programmable on both software and hardware. In conclusion, it costs little time running on FPGA board and the solution obtained is good enough for the consumers.

A continuous-time MILP model for short-term scheduling of make-and-pack production processes

In process industries, make-and-pack production is used to produce food and beverages, chemicals, and metal products, among others. This type of production process allows the fabrication of a wide range of products in relatively small amounts using the same equipment. In this article, we consider a real-world production process (cf. Honkomp et al. 2000. The curse of reality – why process scheduling optimization problems are diffcult in practice. Computers & Chemical Engineering, 24, 323–328.) comprising sequence-dependent changeover times, multipurpose storage units with limited capacities, quarantine times, batch splitting, partial equipment connectivity, and transfer times. The planning problem consists of computing a production schedule such that a given demand of packed products is fulfilled, all technological constraints are satisfied, and the production makespan is minimised. None of the models in the literature covers all of the technological constraints that occur in such make-and-pack production processes. To close this gap, we develop an efficient mixed-integer linear programming model that is based on a continuous time domain and general-precedence variables. We propose novel types of symmetry-breaking constraints and a preprocessing procedure to improve the model performance. In an experimental analysis, we show that small- and moderate-sized instances can be solved to optimality within short CPU times.