Population balance models for the thermal degradation of PMMA

A widely accepted view of the thermal degradation of polymers such as PMMA is that an initiation reaction produces radical fragments that undergo rapid depropagation and are also converted back to molecules by a termination reaction. This mechanism is applied to a population of linear molecules and radicals and the evolution of the population is modelled by appropriate discrete sets of ordinary differential equations. In particular, end-chain and random initiation reactions with first-order termination are analysed and compared with experimental data. We find on comparison with TG data for PMMA that the initiation reaction is important in dictating the qualitative behaviour of the overall rate of thermal degradation. Furthermore, the behaviour of degradation rate with initial degree of polymerisation is also investigated and interpreted within the framework of the model.     

Population shift bias in tests of space–time interaction

Common to all tests of space–time interaction is the assumption that the population underlying the events of interest exhibits a trajectory of growth that is consistent through time and across space. In practice, however, this assumption is often untenable and, when violated, can introduce population shift bias into the results of these tests. While this problem is widely recognized, more work remains to compare its effect across tests and to determine the extent to which it is a problem for study short periods. This paper quantifies and compares the population shift bias present in the results of the Knox, Mantel, and Jacquez tests of space–time interaction. A simulation study is carried out which quantifies the bias present in each test across a variety of population movement scenarios. Results show a positive relationship between population shift bias and the heterogeneity in population growth across all the tests. They also demonstrate variability in the size of the bias across the three tests for space–time interaction considered. Finally, the results illustrate that population shift bias can be a serious problem for short study periods. Collectively, these findings suggest that an unbiased approach to assessing the significance of space–time interaction test results is needed whenever spatially heterogeneous population change is identified within a study area.     

人口与车辆交通地理信息库的建立模式探讨

人口和车辆是城市交通管理和规划的重点对象和考虑因素，通过对城市机动车辆数据和人口数据进行分区处理。生成人口与车辆地理信息库系统，为城市交通管理者在做有关城市交通管理和规划方面提供决策数据。本文探讨运用数据仓库与地理信息系统相结合技术，利用现有的信息资源，建立人口与车辆分布分析的数据库系统。     

Modelling population responses to flow: The development of a generic fish population model

Many fish species are dependent upon flows to trigger breeding, facilitate high recruitment of offspring, and to maintain adult survival rates. Understanding how fish populations respond to different flow regimes is important in regulated waterways as subtle changes in regimes have the potential to influence both fish breeding and survival. In this paper, we describe an age-structured population response model that explores how quantitative changes in the flow regime can lead to changes in fish population size and structure through time. We use three large bodied fish species (golden perch, Murray cod and the invasive common carp) from the mid Murray River near Barmah-Millewa Forest to explore the possible responses to the observed flow regime over a 30-year period. The model links flow volumes, seasonality, temperature and rates of fall to the fecundity and survival rates for the different fish species to project population change through time.     

Uncertainty analysis and evaluation of a complex,multi-specific weed dynamics model with diverse and incomplete data sets

Weed dynamics models are needed to test prospective cropping systems but are rarely evaluated with independent data (“validated”). Here, we evaluated the FlorSys model which quantifies the effects of cropping systems and pedoclimate on multispecific weed dynamics with a daily time step. We adapted existing validation methodologies and uncertainty analyses to account for multi-specific, multi-annual and diverse outputs, focusing on missing input data, incomplete and imprecise weed time series. Field data ranged from entirely monitored cropping system trials to annual snapshots recorded on farm fields by the French Biovigilance-Flore network. FlorSys satisfactorily predicted weed seed bank, plant densities and crop yields, at daily and multi-annual scales, at well monitored sites. It overestimated plant biomass and underestimated total flora density. Missing processes (photoperiod dependency in flowering, crop:weed competition for nitrogen) and inadequately predicted scenarios (weed dynamics in untilled fields, floras with summer-emerging species) were identified. Guidelines for model use were proposed.     

Microsatellite markers for Rhyzopertha dominica (Coleoptera: Bostrichidae)

Rhyzopertha dominica (F.) is a destructive insect pest of stored products. Due to this pest's broad host range, short life cycle, and high reproductive capacity, it has rapidly spread throughout the world. Understanding the population structuring of this important pest is vital for developing and implementing an effective integrated pest management strategy. In this study, we isolated 19 novel polymorphic microsatellite loci from an enriched genomic library based on a biotin/streptavidin capture protocol. The genetic parameters were estimated based on 80 individual R. dominica from two natural populations. The numbers of alleles ranged from 3 to 10, and sixteen loci exhibited polymorphic information contents (PICs) greater than 0.5. The observed (H_O) and expected (H_E) heterozygosities ranged from 0.033 to 0.900 and 0.310 to 0.882, respectively. Six locus/population combinations significantly deviated from Hardy–Weinberg equilibrium (HWE). These microsatellite markers will provide a valuable resource for studying the population genetic structure of this species.     

Patch-Levy-based initialization algorithm for Bees Algorithm

The Bees Algorithm (BA) is a population-based metaheuristic algorithm inspired by the foraging behavior of honeybees. This algorithm has been successfully used as an optimization tool in combinatorial and functional optimization fields. In addition, its behavior very closely mimics the actual behavior that occurs in nature, and it is very simple and easy to implement. However, its convergence speed to the optimal solution still needs further improvement and it also needs a mechanism to obviate getting trapped in local optima. In this paper, a novel initialization algorithm based on the patch concept and Levy flight distribution is proposed to initialize the population of bees in BA. Consequently, we incorporate this initialization procedure into a proposed enhanced BA variant. The proposed variant is more natural than conventional variants of BA. It mimics the patch environment in nature and Levy flight, which is believed to characterize the foraging patterns of bees in nature. The results of experiments conducted on several widely used high-dimensional benchmarks indicate that our proposed enhanced BA variant significantly outperforms other BA variants and state-of-the-art variants of the Artificial Bee Colony (ABC) algorithm in terms of solution quality, convergence speed, and success rate. In addition, the results of experimental analyses conducted indicate that our proposed enhanced BA is very stable, has the ability to deal with differences in search ranges, and rapidly converges without getting stuck in local optima.     

Simulation of a Bubble Column by Computational Fluid Dynamics and Population Balance Equation Using the Cell Average Method

An axisymmetric computational fluid dynamics (CFD) simulation coupled with a population balance equation (PBE) has been applied in simulating the gas‐liquid flow in a bubble column with an in‐house code. The novel feature of this simulation is the application of the cell average method in a CFD‐PBE coupled model for the first time. The predicted results by this method are compared with those by the traditional fixed pivot method and experimental data. For both methods, the simulated results are in reasonable agreement with the reported experimentally measured values. However, the bubble size distributions determined by the cell average method are slightly better than those found by means of the fixed pivot method, i.e., the latter provides a smaller peak value and a wider bubble size distribution, and the probability density function of large bubbles is higher.     

Development of microsatellite markers and a preliminary assessment of population structuring in the rice weevil,Sitophilus oryzae (L.)

The rice weevil, Sitophilus oryzae is one of the primary pests of stored grains worldwide. To develop and implement an effective integrated pest management strategy, an understanding of the population structuring of this destructive pest is vital. In this study we used Illumina paired-end sequencing to develop S. oryzae species-specific microsatellite markers, and used these markers to conduct a preliminary assessment of population structuring in four populations of S. oryzae from three countries (Australia, China, and USA). 7,635,996 raw sequencing reads were produced, with 11,794 microsatellites detected and 214,257 primer options designed. 48 microsatellite markers were selected for further validation, with 10 markers amplifying consistently across the four S. oryzae populations. These markers displayed a high level of polymorphism overall (6.67 alleles/locus), though this was slightly lower within populations (3.10–4.88 alleles/locus). We used the markers to conduct a preliminary assessment of genetic structuring among the four S. oryzae populations: three laboratory cultures (New South Wales, Queensland, and Santai) and a field collected population from Kansas. Analyses suggest high levels of genetic differentiation between the sample locations, with a global F_ST of 0.239, and pairwise F_ST values ranging from 0.100 to 0.395. Bayesian clustering analyses suggest these four populations formed four distinct clusters, with a similar pattern identified by Principal Coordinate Analysis. These microsatellite markers, together with our preliminary population genetic analyses, will provide a valuable resource for population genetic research, and contribute to effective integrated pest management strategies in the future.     

Numerical simulation of froth formation in aerated slurry coupled with population balance modelling

A computational fluid dynamic (CFD) model has been developed to incorporate pulp and froth zones into one model. In the present research, froth was considered as a separate phase comprised of a mixture of gas, liquid and solids. Considering the froth phase as a separate phase, allowed the incorporation of pulp and froth zones into one model by tracking the formation and destruction of the froth phase due to mass exchange between the pulp and froth. Bubble break-up and coalescence were taken into account in the pulp zone, by employing user functions, written using FORTRAN. The effect of bubble coalescence process due to ?lm rupture was considered in the froth phase. The variation in the concentration of attached particles due to attachment and detachment processes were also taken into account. The CFD model predicted the height of froth layer, the concentration of different bubble sizes in both pulp and froth zones, and finally the multiphase ?ow phenomena in the slurry column. Froth height was found to increase with the increase of gas flow rate while increasing solid concentration decreased froth height.