Premature separation of centromere and aneuploidy: an indicator of high risk in unaffected individuals from familial breast cancer families?

OBJECTIVES: Injury is the leading cause of death in the male working population of Brazil. An important fraction of these deaths are work related. Very few cohort studies of steel workers, and none from developing countries, have reported on mortality from injuries. This paper analyses mortality from work and non-work related injuries among Brazilian steel workers. METHODS: Deaths during employment from 1 January 1977 to 30 November 1992 were analysed in a cohort of 21,816 male steel workers. Mortality rates specific for age and calendar year among the workers were compared with those of the male population of the state where the plant is located. Work related injuries were analysed by comparing the mortality rates for different subgroups of the cohort. RESULTS: The number of deaths (391) was less than half that expected based on death rates of the general population. Over 60% (242) of deaths were due to injuries. Mortality from most causes was substantially below that in the general population, but that from unintentional injury, was 50% above that of the general population. Standardised mortality ratios (SMRs) were highest for the youngest and the oldest employees and for labourers and clerical workers. Mortality from motor vehicle injury was twice that expected from population rates (SMR = 209, 95% confidence interval (95% CI) 176-244). There was a 67% fall in the age adjusted mortality from occupational injuries in the study period. CONCLUSION: The healthy worker effect in this cohort was greater than that commonly found in studies of occupational groups in developed countries, probably because of a greater socioeconomic gap between employed and unemployed populations in Brazil, and unequal distribution of health care resources. Mortality was especially high for motor vehicle injuries. The fall in mortality from occupational injuries during the study period was probably due to improvement in safety standards, increased automation, and better medical care. There is a need to investigate risk factors for unintentional injuries among steel workers, especially those due to motor vehicle injuries. Prevention of occupational and nonoccupational injuries should be a main priority in Brazil.     

Artificial intelligence techniques and their application in oil and gas industry

Artificial Intelligence Review - Data are being continuously generated from various operational steps in the oil and gas industry. The recordings of these data and their proper utilization have...     

MODELING AND PREDICTIVE CONTROL OF MIMO NONLINEAR SYSTEMS USING WIENER-LAGUERRE MODELS

In this work, a Weiner-type nonlinear black box model was developed for capturing dynamics of open loop stable MIMO nonlinear systems with deterministic inputs. The linear dynamic component of the model was parameterized using orthogonal Laguerre filters while the nonlinear state output map was constructed either using quadratic polynomial functions or artificial neural networks. The properties of the resulting model, such as open loop stability and steady-state behavior, are discussed in detail. The identified Weiner-Laguerre model was further used to formulate a nonlinear model predictive control (NMPC) scheme. The efficacy of the proposed modeling and control scheme was demonstrated using two benchmark control problems: (a) a simulation study involving control of a continuously operated fermenter at its optimum (singular) operating point and (b) experimental verification involving control of pH at the critical point of a neutralization process. It was observed that the proposed Weiner-Laguerre model is able to capture both the dynamic and steady-state characteristics of the continuous fermenter as well as the neutralization process reasonably accurately over wide operating ranges. The proposed NMPC scheme achieved a smooth transition from a suboptimal operating point to the optimum (singular) operating point of the fermenter without causing large variation in manipulated inputs. The proposed NMPC scheme was also found to be robust in the face of moderate perturbation in the unmeasured disturbances. In the case of experimental verification using the neutralization process, the proposed control scheme was found to achieve much faster transition to a set point close to the critical point when compared to a conventional gain-scheduled PID controller.     

Effect of marangoni stresses on the deformation and coalescence in compatibilized immiscible polymer blends

The effect of physical compatibilization on the deformation and coalescence of droplets in immiscible polymer blends is discussed. Evidence is provided for the existence of concentration gradients in block copolymers along the interface during deformation. This causes complex changes in droplet shapes during deformation and relaxation. These concentration gradients also result in Marangoni stresses, which stabilize the droplets against deformation and breakup. Coalescence experiments have been performed, varying both the compatibilizer concentration and the shear rate. Existing coalescence models have been evaluated. An empirical extension of Chesters' partially mobile interface model is presented, that treats the effects of Marangoni stresses on the coalescence process as a higher effective viscosity ratio.     

Production of agrochemical from waste polyesters

In this study, agrochemical was produced from waste polyesters. Reactions of waste polyesters [poly (ethylene terephthalate) (PET) and poly (butylene terephthalate) (PBT)] powder with ethylene glycol (EG) in the presence of tetrahydrofurane (THF) using 0.003 mol lead acetate as a catalyst were carried out in a batch reactor at 470 K and at atmospheric pressure conditions. Reactions were undertaken with various particle size ranges from 50 to 512.5 μm, and reaction time from 30 to 70 min for reactions of polyesters. Low molecular weight product of polyester was obtained during this process. In the next stage, hydroxylamine hydrochloride (HAHC), cyclohexylamine (CHA), and potasium hydroxide (KOH) solution were introduced to convert low molecular weight product of polyester into terephthalohydroxamic acid (TPHA) by introduction of HCl (Hydrochloric Acid) as per stoichiometric requirement. TPHA can be used as an agrochemical (insecticide) with appreciable efficiency. To increase the polyester conversion rate, external catalyst (0.003 mol lead acetate) was introduced during the reaction. The product was deposited on the surface of unreacted polyester, which was removed from the surface by introducing dimethyl sulfoxide (DMSO). To accelerate the reaction rate, DMSO, CHA, and THF were introduced during the reaction, which has an industrial significance. Depolymerization of polyester was proportional to the reaction time. Depolymerization of polyester was inversely proportional to the particle size of polyester. Analyses of value‐added product (TPHA) and byproducts [EG and BD (1,4‐butanediol)] as well as polyesters were undertaken. A kinetic model is developed, and experimental data simulated with it, which was consistent with the model. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 2504–2510, 2006     

Review:Mg and Its Alloy——Scope, Future Perspectives and Recent Advancements in Welding and Processing

镁/镁合金焊接与加工的最新进展与未来展望

Sachin Kumar,武传松

（山东大学 材料科学与工程学院,济南 250061）

中文说明：

该文非常详细地综述了镁及镁合金的生产、加工及焊接的研究现状。尤其是在镁合金焊接部分,作者比较详细地阐述了熔化焊、激光焊、固相焊及钎焊等方法在镁合金焊接中的研究现状、存在问题与发展动向。该文对于镁合金焊接研究人员具有重要的参考价值。

关键词：镁;镁合金;加工;焊接;连接;最新进展

     

A data mining approach to characterize road accident locations

Data mining has been proven as a reliable technique to analyze road accidents and provide productive results. Most of the road accident data analysis use data mining techniques, focusing on identifying factors that affect the severity of an accident. However, any damage resulting from road accidents is always unacceptable in terms of health, property damage and other economic factors. Sometimes, it is found that road accident occurrences are more frequent at certain specific locations. The analysis of these locations can help in identifying certain road accident features that make a road accident to occur frequently in these locations. Association rule mining is one of the popular data mining techniques that identify the correlation in various attributes of road accident. In this paper, we first applied k-means algorithm to group the accident locations into three categories, high-frequency, moderate-frequency and low-frequency accident locations. k-means algorithm takes accident frequency count as a parameter to cluster the locations. Then we used association rule mining to characterize these locations. The rules revealed different factors associated with road accidents at different locations with varying accident frequencies. The association rules for high-frequency accident location disclosed that intersections on highways are more dangerous for every type of accidents. High-frequency accident locations mostly involved two-wheeler accidents at hilly regions. In moderate-frequency accident locations, colonies near local roads and intersection on highway roads are found dangerous for pedestrian hit accidents. Low-frequency accident locations are scattered throughout the district and the most of the accidents at these locations were not critical. Although the data set was limited to some selected attributes, our approach extracted some useful hidden information from the data which can be utilized to take some preventive efforts in these locations.