Polybrominated diphenyl ethers and polychlorinated dibenzo-p-dioxins and dibenzofurans in surface dust at an E-waste processing site in Southeast China

Surface dust collected from printed circuit board recycling workshop floors, roads, a schoolyard, and an outdoor food market in Guiyu, China, a village intensely involved in e-waste processing, were investigated for levels of polybrominated diphenyl ethers (PBDEs) and polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs). PBDE concentrations in dust from workshop-floors (14,800 ± 5130 ng/g) and on adjacent roads to the workshops (24,900 ± 31,600 ng/g) were highest among the study sites whereas PCDD/F concentrations were highest at the schoolyard (1316 pg/g) and in a workshop (1264 pg/g). Analyses of <2 mm and <53 μm dust particle sizes did not show any significant differences in PBDE concentrations. The cytotoxicity was investigated using two bioassays: 7-ethoxyresorufin O-deethylase (EROD-TEQ) and MTT. EROD-TEQ values ranged from 260 to 432 pg/g, with the highest in dust collected from a street lined with workshops. Using the MTT assay, cytoxicity of dust from the plastic chips drying district in Guiyu was higher than dust from the other sites investigated. This study showed that the primitive recycling of e-waste introduced toxic pollutants into the environment which are potentially harmful to the health of e-waste workers and local residents, especially children, and warrants an urgent investigation into POPs related health impacts.     

Using genetic algorithms and linear regression analysis for private housing demand forecast

An accurate prediction of prospective construction supply and demand, especially the private residential market, is paramount important to policy makers, as it could help formulate strategies to cultivate/stabilize the economy and satisfy the social needs (at macro level). Despite that, a realistic prediction of future private residential demand is never an easy task, as it is governed by a number of social and economic factors. In this paper, four leading indicator models are developed and compared for directly forecasting Hong Kong private sector residential demand. These comprise a (i) Linear Regression Analysis (LRA) model, (ii) Genetic Algorithms (GA) model, (iii) GA-LRA model, where LRA is used to select the indicator variables; and (iv) GA-LRA model with Adaptive Mutation Rate (AMR) to reduce the likelihood of local optima. The findings indicate that the GA-LRA model with AMR provides the most accurate forecasts and over a longer time horizon. In providing a range of possible forecasts, the model also provides an opportunity for the decision-maker to exercise judgment in selecting the most appropriate forecasts.     

Parallel algorithms for bipartite matching problems on distributed memory computers

We present a new parallel algorithm for computing a maximum cardinality matching in a bipartite graph suitable for distributed memory computers.The presented algorithm is based on the Push-Relabel algorithm which is known to be one of the fastest algorithms for the bipartite matching problem. Previous attempts at developing parallel implementations of it have focused on shared memory computers using only a limited number of processors.We first present a straightforward adaptation of these shared memory algorithms to distributed memory computers. However, this is not a viable approach as it requires too much communication. We then develop our new algorithm by modifying the previous approach through a sequence of steps with the main goal being to reduce the amount of communication and to increase load balance. The first goal is achieved by changing the algorithm so that many push and relabel operations can be performed locally between communication rounds and also by selecting augmenting paths that cross processor boundaries infrequently. To achieve good load balance, we limit the speed at which global relabelings traverse the graph. In several experiments on a large number of instances, we study weak and strong scalability of our algorithm using up to 128 processors.The algorithm can also be used to find ?-approximate matchings quickly.     

Nanoparticles Targeted to Fibroblast Activation Protein Outperform PSMA for MRI Delineation of Primary Prostate Tumors

Accurate delineation of gross tumor volumes remains a barrier to radiotherapy dose escalation and boost dosing in the treatment of solid tumors, such as prostate cancer. Magnetic resonance imaging (MRI) of tumor targets has the power to enable focal dose boosting, particularly when combined with technological advances such as MRI-linear accelerator. Fibroblast activation protein (FAP) is overexpressed in stromal components of >90% of epithelial carcinomas. Herein, the authors compare targeted MRI of prostate specific membrane antigen (PSMA) with FAP in the delineation of orthotopic prostate tumors. Control, FAP, and PSMA-targeting iron oxide nanoparticles were prepared with modification of a lymphotropic MRI agent (FerroTrace, Ferronova). Mice with orthotopic LNCaP tumors underwent MRI 24 h after intravenous injection of nanoparticles. FAP and PSMA nanoparticles produced contrast enhancement on MRI when compared to control nanoparticles. FAP-targeted MRI increased the proportion of tumor contrast-enhancing black pixels by 13%, compared to PSMA. Analysis of changes in R2 values between healthy prostates and LNCaP tumors indicated an increase in contrast-enhancing pixels in the tumor border of 15% when targeting FAP, compared to PSMA. This study demonstrates the preclinical feasibility of PSMA and FAP-targeted MRI which can enable targeted image-guided focal therapy of localized prostate cancer.     

RECODE: an image‐based collision detection algorithm

Object interactions are ubiquitous in interactive computer graphics, 3D object motion simulations, virtual reality and robotics applications. Most collision detection algorithms are based on geometrical object‐space interference tests. Some algorithms have employed an image‐space approach to the collision detection problem. In this paper we demonstrate an image‐space collision detection process that allows substantial computational savings during the image‐space interference test. This approach makes efficient use of the graphics rendering hardware for real‐time complex object interactions. Copyright © 1999 John Wiley & Sons, Ltd.