Modelling Cohesive-Frictional Particulate Solids for Bulk Handling Applications

Many powders and particulate solids are cohesive in nature and the strength often exhibits dependence on the consolidation stress. As a result, the stress history in the material leading up to a handling scenario needs to be considered when evaluating its handleability. This paper outlines the development of a DEM contact model accounting for plasticity and adhesion force, which is shown to be suitable for modelling the stress history dependent cohesive strength. The model was used to simulate the confined consolidation and the subsequent unconfined loading of iron ore fines with particle sizes up to 1.18mm. The predicted flow function was found to be comparable to the experimental results. 

Handling Sequential Observations in Intelligent Surveillance

Demand for intelligent surveillance in public transport systems is growing due to the increased threats of terrorist attack, vandalism and litigation. The aim of intelligent surveillance is in-time reaction to information received from various monitoring devices, especially CCTV systems. However, video analytic algorithms can only provide static assertions, whilst in reality, many related events happen in sequence and hence should be modeled sequentially. Moreover, analytic algorithms are error-prone, hence how to correct the sequential analytic results based on new evidence (external information or later sensing discovery) becomes an interesting issue. In this paper, we introduce a high-level sequential observation modeling framework which can support revision and update on new evidence. This framework adapts the situation calculus to deal with uncertainty from analytic results. The output of the framework can serve as a foundation for event composition. We demonstrate the significance and usefulness of our framework with a case study of a bus surveillance project.

ALEA: Fine-Grain Energy Profiling with Basic Block Sampling

Energy efficiency is an essential requirement for all contemporary computing systems. We thus need tools to measure the energy consumption of computing systems and to understand how workloads affect it. Significant recent research effort has targeted direct power measurements on production computing systems using on-board sensors or external instruments. These direct methods have in turn guided studies of software techniques to reduce energy consumption via workload allocation and scaling. Unfortunately, direct energy measurements are hampered by the low power sampling frequency of power sensors. The coarse granularity of power sensing limits our understanding of how power is allocated in systems and our ability to optimize energy efficiency via workload allocation.
We present ALEA, a tool to measure power and energy consumption at the granularity of basic blocks, using a probabilistic approach. ALEA provides fine-grained energy profiling via sta- tistical sampling, which overcomes the limitations of power sens- ing instruments. Compared to state-of-the-art energy measurement tools, ALEA provides finer granularity without sacrificing accuracy. ALEA achieves low overhead energy measurements with mean error rates between 1.4% and 3.5% in 14 sequential and paral- lel benchmarks tested on both Intel and ARM platforms. The sampling method caps execution time overhead at approximately 1%. ALEA is thus suitable for online energy monitoring and optimization. Finally, ALEA is a user-space tool with a portable, machine-independent sampling method. We demonstrate two use cases of ALEA, where we reduce the energy consumption of a k-means computational kernel by 37% and an ocean modelling code by 33%, compared to high-performance execution baselines, by varying the power optimization strategy between basic blocks.

A design strategy of large grain lithium-rich layered oxides for lithium-ion batteries cathode

Li-rich materials are considered the most promising for Li-ion battery cathodes, as high capacity can be achieved. However, poor cycling stability is a critical drawback that leads to poor capacity retention. Here a strategy is used to synthesize a large-grain lithium-rich layered oxides to overcome this difficulty without sacrificing rate capability. This material is designed with micron scale grain with a width of about 300 nm and length of 1-3 μm. This unique structure has a better ability to overcome stress-induced structural collapse caused by Li-ion insertion/extraction and reduce the dissolution of Mn ions, which enable a reversible and stable capacity. As a result, this cathode material delivered a highest discharge capacity of around 308 mAh g^-1 at a current density of 30 mA g^-1 with retention of 88.3% (according to the highest discharge capacity) after 100 cycles, 190 mAh g^-1 at a current density of 300 mA g^-1 and almost no capacity fading after 100 cycles. Therefore, Lithium-rich material of large-grain structure is a promising cathode candidate in Lithium-ion batteries with high capacity and high cycle stability for application. This strategy of large grain may furthermore open the door to synthesize the other complex architectures for various applications.

Silicon, the silver bullet for mitigating biotic and abiotic stress, and improving grain quality, in rice?

Adequate silicon fertilization greatly boosts rice yield and mitigates biotic and abiotic stress, and improves grain quality through lowering the content of cadmium and inorganic arsenic. This review on silicon dynamics in rice considers recent advances in our understanding of the role of silicon in rice, and the challenges of maintaining adequate silicon fertility within rice paddy systems. Silicon is increasingly considered as an element required for optimal plant performance, particularly in rice. Plants can survive with very low silicon under laboratory/glasshouse conditions, but this is highly artificial and, thus, silicon can be considered as essential for proper plant function in its environment. Silicon is incorporated into structural components of rice cell walls were it increases cell and tissue rigidity in the plant. Structural silicon provides physical protection to plants against microbial infection and insect attack as well as reducing the quality of the tissue to the predating organisms. The abiotic benefits are due to silicon's effect on overall organ strength. This helps protect against lodging, drought stress, high temperature (through efficient maintenance of transpiration), and photosynthesis by protecting against high UV. Furthermore, silicon also protects the plant from saline stress and against a range of toxic metal stresses (arsenic, cadmium, chromium, copper, nickel and zinc). Added to this, silicon application decreases grain concentrations of various human carcinogens, in particular arsenic, antimony and cadmium. As rice is efficient at stripping bioavailable silicon from the soil, recycling of silicon rich rice straw biomass or addition of inorganic silicon fertilizer, primarily obtained from iron and steel slag, needs careful management. Silicon in the soil may be lost if the silicon-cycle, traditionally achieved via composting of rice straw and returning it to the land, is being broken. As composting of rice straw and incorporation of composted or non-composted straw back to land are resource intensive activities, these activities are declining due to population shifts from the countryside to cities. Processes that accelerate rice straw composting, therefore, need to be identified to aid more efficient use of this resource. In addition, rice genetics may help address declining available silicon in paddy soils: for example by selecting for characteristics during breeding that lead to an increased ability of roots to access recalcitrant silicon sources from soil and/or via selection for traits that aid the maintenance of a high silicon status in shoots. Recent advances in understanding the genetic regulation of silicon uptake and transport by rice plants will aid these goals.

Genetic mapping of the rice ionome in leaves and grain:Identification of QTLs for 17 elements including arsenic, cadmium, iron and selenium

Research into the composition of cereal grains is motivated by increased interest in food quality. Here multi-element analysis is conducted on leaves and grain of the Bala x Azucena rice mapping population grown in the field. Quantitative trait loci (QTLs) for the concentration of 17 elements were detected, revealing 36 QTLs for leaves and 41 for grains. Epistasis was detected for most elements. There was very little correlation between leaf and grain element concentrations. For selenium, lead, phosphorus and magnesium QTLs were detected in the same location for both tissues. In general, there were no major QTL clusters, suggesting separate regulation of each element. QTLs for grain iron, zinc, molybdenum and selenium are potential targets for marker assisted selection to improve seed nutritional quality. An epistatic interaction for grain arsenic also looks promising to decrease the concentration of this carcinogenic element. © Springer Science+Business Media B.V. 2009.

Differential efficiency of the endocytic machinery in tonic and phasic synapses

Efficient synaptic vesicle membrane recycling is one of the key factors required to sustain neurotransmission. We investigated potential differences in the compensatory endocytic machineries in two glutamatergic synapses with phasic and tonic patterns of activity in the lamprey spinal cord. Post-embedding immunocytochemistry demonstrated that proteins involved in synaptic vesicle recycling, including dynamin, intersectin, and synapsin, occur at higher levels (labeling per vesicle) in tonic dorsal column synapses than in phasic reticulospinal synapses. Synaptic vesicle protein 2 occurred at similar levels in the two types of synapse. After challenging the synapses with high potassium stimulation for 30 min the vesicle pool in the tonic synapse was maintained at a normal level, while that in the phasic synapse was partly depleted along with expansion of the plasma membrane and accumulation of clathrin-coated intermediates at the periactive zone. Thus, our results indicate that an increased efficiency of the endocytic machinery in a synapse may be one of the factors underlying the ability to sustain neurotransmission at high rates.

Determination of the Mycotoxin Content in Distiller's Dried Grain with Solubles Using a Multianalyte UHPLC-MS/MS Method

There are more than 300 potential mycotoxins that can contaminate food and feed and cause adverse effects in humans and animals. The data on the co-occurrence of mycotoxins in novel animal feed materials, such as distiller's dried grain with solubles (DDGS), are limited. Thus, a UHPLC-MS/MS method for the quantitation of 77 mycotoxins and other fungal metabolites was used to analyze 169 DDGS samples produced from wheat, maize, and barley and 61 grain samples. All DDGS samples analyzed were contaminated with 13-34 different mycotoxins. Fumonisins were present in all 52 maize DDGS samples (81.0-6890 μg/kg for fumonisin B1), and deoxynivalenol was present in all 99 wheat DDGS samples (39.3-1120 μg/kg). A number of co-occurring mycotoxins were also identified. Due to the high co-occurrence of mycotoxins, routine screening of the animal feed ingredients is highly recommended to allow the highlighted risks to be effectively managed.

Availability and transfer to grain of As, Cd, Cu, Ni, Pb and Zn in a barley agri-system: Impact of biochar, organic and mineral fertilizers

With biochar becoming an emerging soil amendment and a tool to mitigate climate change, there are only a few studies documenting its effects on trace element cycling in agriculture. Zn and Cu are deficient in many human diets, whilst exposures to As, Pb and Cd need to be decreased. Biochar has been shown to affect many of them mainly at a bench or greenhouse scale, but field research is not available. In our experiment we studied the impact of biochar, as well as its interactions with organic (compost and sewage sludge) and mineral fertilisers (NPK and nitrosulfate), on trace element mobility in a Mediterranean agricultural field (east of Madrid, Spain) cropped with barley. At harvesting time, we analysed the soluble fraction, the available fraction (assessed with the diffusive gradients in thin gels technique, DGT) and the concentration of trace elements in barley grain. No treatment was able to significantly increase Zn, Cu or Ni concentration in barley grain, limiting the application for cereal fortification. Biochar helped to reduce Cd and Pb in grain, whereas As concentration slightly increased. Overall biochar amendments demonstrated a potential to decrease Cd uptake in cereals, a substantial pathway of exposure in the Spanish population, whereas mineral fertilisation and sewage sludge increased grain Cd and Pb. In the soil, biochar helped to stabilise Pb and Cd, while marginally increasing As release/mobilisation. Some of the fertilisation practises or treatments increased toxic metals and As solubility in soil, but never to an extent high enough to be considered an environmental risk. Future research may try to fortify Zn, Cu and Ni using other combinations of organic amendments and different parent biomass to produce enriched biochars.