Aromatic Borozene

Based on our comprehensive theoretical investigation and known experimental results for small boron clusters, we predict the existence of a novel aromatic inorganic molecule, B₁₂H₆. This molecule, which we refer to as borozene, has remarkably similar properties to the well-known benzene. Borozene is planar, possesses a large first excitation energy, D _3h symmetry, and more importantly is aromatic. Furthermore, the calculated anisotropy of the magnetic susceptibility of borozene is three times larger in absolute value than for benzene. Finally, we show that borozene molecules may be fused together to give larger aromatic compounds with even larger anisotropic susceptibilities.     

An algorithm for the recognition of levels of congestion in road traffic problems

Detection and recognition of the level of congestion at an intersection is a very important problem and a valuable source of information in traffic management. Although it is just one of all the aspects that make up a traffic management system, it seems to be a crucial point for gathering information. In this paper, we present a technique based on a k-means clustering algorithm for classification, which has been already successfully used in a number of pattern recognition problems, namely: as an algorithm for face recognition problems and in a number of medical diagnosis problems and it compares very well with the state of the art techniques.     

In search of a relational theory.

The author searched for empirically based theories and models with an interpersonal and relational focus. This search was conducted in spite of academic and professional psychology’s general avoidance of theory building coupled with an exaggerated reliance on empirical evidence, producing a chaotic proliferation of models unrelated to each other. Requirements for any theory are verifiability, applicability, redundancy, and fruitfulness. Many two-factor relational theories and models derive from the two assumptions of space and time. From these models and theories two stand out: attachment theory and relational competence theory (RCT). Both theories attempt to link heretofore separate fields: research and practice. The major asset of attachment theory has been a multitude of studies in the English-speaking world. The major shortcoming of RCT is that research to support the validity of its models has been conducted only in Italy. However, many test instruments, enrichment programs, and interactive practice exercises for some models of RCT are available in English. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Automating mode detection for travel behaviour analysis by using global positioning systemsenabled mobile phones and neural networks

Travel surveys collect trip data such as origin, destination, mode, duration, distance and purpose of trips, as well as socioeconomic and demographic data for analysis. Transportation planners, policymakers, state departments of transportation, metropolitan planning organisations, industry professionals and academic researchers use survey data to better understand the current demand and performance of the transportation infrastructure, and to plan in preparation for future growth. Next-generation travel surveys will utilise global positioning systems (GPS) to collect trip data with minimal input from survey participants. Owing to their ubiquity, GPS-enabled mobile phones are developing into a promising survey tool. TRAC-IT is a mobile phone application that collects real-time GPS data and requires minimal input from the user for data such as trip purpose, mode and vehicle occupancy. To ease survey burden on participants and enable real-time, modespecific location-based services, new techniques must be explored to derive more information directly from GPS data. As part of travel survey collection, TRAC-IT is able to passively determine trip mode using GPSenabled mobile phones and neural networks. The mode detection technique presented in this article can be optimised using a critical point, pre-processing algorithm to reduce the size of required GPS datasets obtained from GPS-enabled mobile phones, thus reducing data collection costs while conserving precious mobile phone resources such as battery life.     

Pheromone-based trapping of West Indian sugarcane weevil in a sugarcane plantation

Attraction of Metamasius hemipterus (Oliver) to gallon and bamboo traps baited with insecticide-treated sugarcane, the male-produced pheromone, 4-methyl-5-nonanol, and 2-methyl-4-heptanol is more efficient if ethyl acetate is added. The optimal traps are ground-level gallon traps baited with insecticide-laced sugarcane, pheromone, and ethyl acetate. Capture rates of ground-level gallon traps are doubled by placing an insecticide-laced pad under the trap, but significantly decreased by placing the trap on a stick above ground. The efficiency of ground-level gallon traps is the same as ground level ramp traps. Mass-trapping M. hemipterus in newly planted sugarcane using ground level bamboo traps baited with insecticide-laced sugarcane and pheromone over six months revealed populations were low for the first two months, became maximum at five months, and declined thereafter. Capture rates of traps bordering newly planted and mature sugarcane were not significantly different from capture rates of traps in the interior of the plots. Capture rates of bamboo traps containing only insecticide-laced sugarcane and deployed at 30 traps/ha averaged 6 weevils/trap/week compared with 66 weevils/trap/week for traps additionally containing pheromone lures and deployed at 5 traps/ha. Capture rates for bamboo traps baited with insecticide-laced sugarcane and pheromone and deployed at 10 and 15 traps/ha were 43 and 38 weevils/trap/week, respectively. Total captures were higher in those plots with a higher density of insecticide-laden sugarcane and pheromone baited traps, and the differences were approximately proportional to trap density in the range of 5–15 traps/ha. Capture rates of traps containing insecticide-laced sugarcane and pheromone were always higher than of traps containing only insecticide-laced sugarcane, but in the first two months after planting the differences were much greater than in months 3–6 after planting.     

Control of a Robotic Wheelchair Using Recurrent Networks

This paper describes an adaptive neural control system for governing the movements of a robotic wheelchair. It presents a new model of recurrent neural network based on a RBF architecture and combining in its architecture local recurrence and synaptic connections with FIR filters. This model is used in two different control architectures to command the movements of a robotic wheelchair. The training equations and the stability conditions of the control system are obtained. Practical tests show that the results achieved using the proposed method are better than those obtained using PID controllers or other recurrent neural networks models