“Qualitative Air Flow Modelling And Analysis Of Data Centre Air Conditioning As Multiple Jet Array

In the present study the effect of hot air recirculation is studied with suitable assumptions. It identifies that, the pressure drop across the tile is a dominant parameter which governs the recirculation. The rack suction pressure of the hardware along with the pressure drop across the tile determines the point of recirculation in the cold aisle. The positioning of hardware in the racks play an important role in controlling the recirculation point. The present study is thus helpful in the design of data centre air flow, based on the theory of jets. The air flow can be modelled both quantitatively and qualitatively based on the results

Assessment of Energy Conservation in Indian Cement Industry and Forecasting of Co2 Emissions

Cement industry ranks 2nd in energy consumption among the industries in India. It is one of the major emitter of CO2, due to combustion of fossil fuel and calcination process. As the huge amount of CO2 emissions cause severe environment problems, the efficient and effective utilization of energy is a major concern in Indian cement industry. The main objective of the research work is to assess the energy cosumption and energy conservation of the Indian cement industry and to predict future trends in cement production and reduction of CO2 emissions. In order to achieve this objective, a detailed energy and exergy analysis of a typical cement plant in Kerala was carried out. The data on fuel usage, electricity consumption, amount of clinker and cement production were also collected from a few selected cement industries in India for the period 2001 - 2010 and the CO2 emissions were estimated. A complete decomposition method was used for the analysis of change in CO2 emissions during the period 2001 - 2010 by categorising the cement industries according to the specific thermal energy consumption. A basic forecasting model for the cement production trend was developed by using the system dynamic approach and the model was validated with the data collected from the selected cement industries. The cement production and CO2 emissions from the industries were also predicted with the base year as 2010. The sensitivity analysis of the forecasting model was conducted and found satisfactory. The model was then modified for the total cement production in India to predict the cement production and CO2 emissions for the next 21 years under three different scenarios. The parmeters that influence CO2 emissions like population and GDP growth rate, demand of cement and its production, clinker consumption and energy utilization are incorporated in these scenarios. The existing growth rate of the population and cement production in the year 2010 were used in the baseline scenario. In the scenario-1 (S1) the growth rate of population was assumed to be gradually decreasing and finally reach zero by the year 2030, while in scenario-2 (S2) a faster decline in the growth rate was assumed such that zero growth rate is achieved in the year 2020. The mitigation strategiesfor the reduction of CO2 emissions from the cement production were identified and analyzed in the energy management scenarioThe energy and exergy analysis of the raw mill of the cement plant revealed that the exergy utilization was worse than energy utilization. The energy analysis of the kiln system showed that around 38% of heat energy is wasted through exhaust gases of the preheater and cooler of the kiln sysetm. This could be recovered by the waste heat recovery system. A secondary insulation shell was also recommended for the kiln in the plant in order to prevent heat loss and enhance the efficiency of the plant. The decomposition analysis of the change in CO2 emissions during 2001- 2010 showed that the activity effect was the main factor for CO2 emissions for the cement industries since it is directly dependent on economic growth of the country. The forecasting model showed that 15.22% and 29.44% of CO2 emissions reduction can be achieved by the year 2030 in scenario- (S1) and scenario-2 (S2) respectively. In analysing the energy management scenario, it was assumed that 25% of electrical energy supply to the cement plants is replaced by renewable energy. The analysis revealed that the recovery of waste heat and the use of renewable energy could lead to decline in CO2 emissions 7.1% for baseline scenario, 10.9 % in scenario-1 (S1) and 11.16% in scenario-2 (S2) in 2030. The combined scenario considering population stabilization by the year 2020, 25% of contribution from renewable energy sources of the cement industry and 38% thermal energy from the waste heat streams shows that CO2 emissions from Indian cement industry could be reduced by nearly 37% in the year 2030. This would reduce a substantial level of greenhouse gas load to the environment. The cement industry will remain one of the critical sectors for India to meet its CO2 emissions reduction target. India’s cement production will continue to grow in the near future due to its GDP growth. The control of population, improvement in plant efficiency and use of renewable energy are the important options for the mitigation of CO2 emissions from Indian cement industries

Characterization of Bacteriocins from Bacillus licheniformis strain BTHT8 and Bacillus subtilis strain BTFK101 isolated from marine sediment

Pathogenic microorganisms such as Bacillus cereus, Listeria Monocytogenes and Staphylococcus sp have caused serious diseases, and consequently contributed to considerable economic loss in the food and agricultural industries. Antibiotics have been practically used to treat these pathogens since penicillin G was discovered more than half a century ago. Many different types of antibiotics have been discovered or synthesized to control pathogenic microorganisms. Repetitive use and misuse of antibiotics by the agricultural and pharmaceutical industries have caused the emergence of multidrug-resistant microorganisms, even to the strongest antibiotics currently available; therefore, the rapid development of more effective antimicrobial compounds is required to keep pace with demand. Bacteria were isolated from marine water and sediment samples collected from various locations off the coast of Cochin and salt pans of Tuticorin using pour plate technique. One hundred and twelve isolates were obtained. Seventeen isolates exhibiting antimicrobial activity were segregated after primary screening. The secondary screening which was aimed at selection of bacteria that produce proteinaceous inhibitory compounds, helped to select five strains viz. BTFK101, BTHT8, BTKM4, BTEK16 and BTSB22. The five isolates inhibited the growth of six Gram positive test organisms viz. B. cereus, B. circulans, B. coagulans, B. pumilus, Staphylococcus aureus and Clostridium perfringens. After quantitative estimation of the bacteriocin production, the two strains BTFK101 and BTHT8 were selected for further study.

Utilization of aquatic macrophyte Spirodela polyrhiza as phytotoxicological assessment and phytoremediation tool in selected polluted wetland sites in Ernakulam district

One of the objectives of the current investigation was to evaluate the effectiveness of Spirodela polyrhiza to remove heavy metals and other contaminants from the water samples collected from wetland sites of Eloor and Kannamaly under controlled conditions .The results obtained from the current study suggest that the test material S. polyrrhiza should be used in the biomonitoring and phytoremediation of municipal, agricultural and industrial effluents because of their simplicity, sensitivity and cost-effectiveness. The study throws light on the potential of this plant which can be used as an assessment tool in two diverse wetland in Ernakulum district. The results show the usefulness of combining physicochemical analysis with bioassays as such approach ensures better understanding of the toxicity of chemical pollutants and their influence on plant health. The results shows the suitability of Spirodela plant for surface water quality assessment as all selected parameters showed consistency with respect to water samples collected over a 3-monitoring periods. Similarly the relationship between the change in exposure period (2, 4 and 8 days) with the parameters were also studied in detail. Spirodela are consistent test material as they are homogeneous plant material; due to predominantly vegetative reproduction. New fronds are formed by clonal propagation thus, producing a population of genetically homogeneous plants. The result is small variability between treated individuals. It has been observed that phytoremediation of water samples collected from Eloor and Kannamaly using the floating plant system is a predominant method which is economic to construct, requires little maintenance and eco friendly.

From Market- to Development Orientation - The Trade Aspect of Food Security and Agriculture

Trade rules are suggested to be one of the reasons for the hunger in the world and environmental damage. As current trade rules encourage market orientation and therefore specialization and industrialization of agriculture, which has as side effects rural hunger and environmental damage, there is room for improvement in the international trade regime. One main finding of Nexus Foundations' work in Geneva is a possible new orientation for agricultural and food markets – an orientation on development, rather than purely on markets. This development orientation consists of several elements from development of soil fertility to local markets and consumer relatedness. Since the Bali Ministerial in 2013, the WTO has set up a four year work programme on the issue of food security related to food reserves. This opens the chance to discuss broader food security issues in the realm of trade negotiations.

BioJADE: A Design and Simulation Tool for Synthetic Biological Systems

The next generations of both biological engineering and computer engineering demand that control be exerted at the molecular level. Creating, characterizing and controlling synthetic biological systems may provide us with the ability to build cells that are capable of a plethora of activities, from computation to synthesizing nanostructures. To develop these systems, we must have a set of tools not only for synthesizing systems, but also designing and simulating them. The BioJADE project provides a comprehensive, extensible design and simulation platform for synthetic biology. BioJADE is a graphical design tool built in Java, utilizing a database back end, and supports a range of simulations using an XML communication protocol. BioJADE currently supports a library of over 100 parts with which it can compile designs into actual DNA, and then generate synthesis instructions to build the physical parts. The BioJADE project contributes several tools to Synthetic Biology. BioJADE in itself is a powerful tool for synthetic biology designers. Additionally, we developed and now make use of a centralized BioBricks repository, which enables the sharing of BioBrick components between researchers, and vastly reduces the barriers to entry for aspiring Synthetic Biologists.

The Wrong Kind of Lean: Over-Commitment and Under-Represented Skills on Technology Teams

This paper reports on results from five companies in the aerospace and automotive industries to show that over-commitment of technical professionals and under-representation of key skills on technology development and transition teams seriously impairs team performance. The research finds that 40 percent of the projects studied were inadequately staffed, resulting in weaker team communications and alignment. Most importantly, the weak staffing on these teams is found to be associated with a doubling of project failure rate to reach full production. Those weakly staffed teams that did successfully insert technology into production systems were also much more likely than other teams to have development delays and late engineering changes. The conclusion suggests that the expense of project failure, delay and late engineering changes in these companies must greatly out-weigh the savings gained from reduced staffing costs, and that this problem is likely going to be found in other technology-intensive firms intent on seeing project budgets as a cost to be minimized rather than an investment to be maximized.

Data-Driven Text Generation using Neural Networks & Provenance is Complicated and Boring — Is there a solution?

Title: Data-Driven Text Generation using Neural Networks Speaker: Pavlos Vougiouklis, University of Southampton Abstract: Recent work on neural networks shows their great potential at tackling a wide variety of Natural Language Processing (NLP) tasks. This talk will focus on the Natural Language Generation (NLG) problem and, more specifically, on the extend to which neural network language models could be employed for context-sensitive and data-driven text generation. In addition, a neural network architecture for response generation in social media along with the training methods that enable it to capture contextual information and effectively participate in public conversations will be discussed. Speaker Bio: Pavlos Vougiouklis obtained his 5-year Diploma in Electrical and Computer Engineering from the Aristotle University of Thessaloniki in 2013. He was awarded an MSc degree in Software Engineering from the University of Southampton in 2014. In 2015, he joined the Web and Internet Science (WAIS) research group of the University of Southampton and he is currently working towards the acquisition of his PhD degree in the field of Neural Network Approaches for Natural Language Processing. Title: Provenance is Complicated and Boring — Is there a solution? Speaker: Darren Richardson, University of Southampton Abstract: Paper trails, auditing, and accountability — arguably not the sexiest terms in computer science. But then you discover that you've possibly been eating horse-meat, and the importance of provenance becomes almost palpable. Having accepted that we should be creating provenance-enabled systems, the challenge of then communicating that provenance to casual users is not trivial: users should not have to have a detailed working knowledge of your system, and they certainly shouldn't be expected to understand the data model. So how, then, do you give users an insight into the provenance, without having to build a bespoke system for each and every different provenance installation? Speaker Bio: Darren is a final year Computer Science PhD student. He completed his undergraduate degree in Electronic Engineering at Southampton in 2012.

Natural resources, redistribution and Human capital formation

How do resource booms affect human capital accumulation? We exploit time and spatial variation generated by the commodity boom across local governments in Peru to measure the effect of natural resources on human capital formation. We explore the effect of both mining production and tax revenues on test scores, finding a substantial and statistically significant effect for the latter. Transfers to local governments from mining tax revenues are linked to an increase in math test scores of around 0.23 standard deviations. We find that the hiring of permanent teachers as well as the increases in parental employment and improvements in health outcomes of adults and children are plausible mechanisms for such large effect on learning. These findings suggest that redistributive policies could facilitate the accumulation of human capital in resource abundant developing countries as a way to avoid the natural resources curse.

Crop yield reduction in the tropics under climate change: Processes and uncertainties

Many modelling studies examine the impacts of climate change on crop yield, but few explore either the underlying bio-physical processes, or the uncertainty inherent in the parameterisation of crop growth and development. We used a perturbed-parameter crop modelling method together with a regional climate model (PRECIS) driven by the 2071-2100 SRES A2 emissions scenario in order to examine processes and uncertainties in yield simulation. Crop simulations used the groundnut (i.e. peanut; Arachis hypogaea L.) version of the General Large-Area Model for annual crops (GLAM). Two sets of GLAM simulations were carried out: control simulations and fixed-duration simulations, where the impact of mean temperature on crop development rate was removed. Model results were compared to sensitivity tests using two other crop models of differing levels of complexity: CROPGRO, and the groundnut model of Hammer et al. [Hammer, G.L., Sinclair, T.R., Boote, K.J., Wright, G.C., Meinke, H., and Bell, M.J., 1995, A peanut simulation model: I. Model development and testing. Agron. J. 87, 1085-1093]. GLAM simulations were particularly sensitive to two processes. First, elevated vapour pressure deficit (VPD) consistently reduced yield. The same result was seen in some simulations using both other crop models. Second, GLAM crop duration was longer, and yield greater, when the optimal temperature for the rate of development was exceeded. Yield increases were also seen in one other crop model. Overall, the models differed in their response to super-optimal temperatures, and that difference increased with mean temperature; percentage changes in yield between current and future climates were as diverse as -50% and over +30% for the same input data. The first process has been observed in many crop experiments, whilst the second has not. Thus, we conclude that there is a need for: (i) more process-based modelling studies of the impact of VPD on assimilation, and (ii) more experimental studies at super-optimal temperatures. Using the GLAM results, central values and uncertainty ranges were projected for mean 2071-2100 crop yields in India. In the fixed-duration simulations, ensemble mean yields mostly rose by 10-30%. The full ensemble range was greater than this mean change (20-60% over most of India). In the control simulations, yield stimulation by elevated CO2 was more than offset by other processes-principally accelerated crop development rates at elevated, but sub-optimal, mean temperatures. Hence, the quantification of uncertainty can facilitate relatively robust indications of the likely sign of crop yield changes in future climates. (C) 2007 Elsevier B.V. All rights reserved.

Field trials to assess the uptake of arsenic by vegetables from contaminated soils and soil remediation with iron oxides

The uptake of arsenic (As) by plants from contaminated soils presents a health hazard that may affect the use of agricultural and former industrial land. Methods for limiting the hazard are desirable. A proposed remediation treatment comprises the precipitation of iron (Fe) oxides in the contaminated soil by adding ferrous sulfate and lime. The effects on As bioavailability were assessed using a range of vegetable crops grown in the field. Four UK locations were used, where soil was contaminated by As from different sources. At the most contaminated site, a clay loam containing a mean of 748 mg As kg(-1) soil, beetroot, calabrese, cauliflower, lettuce, potato, radish and spinach were grown. For all crops except spinach, ferrous sulfate treatment caused a significant reduction in the bioavailability of As in some part of the crop. Application of ferrous sulfate in solution, providing 0.2% Fe oxides in the soil (0-10 cm), reduced As uptake by a mean of 22%. Solid ferrous sulfate was applied to give concentrations of 0.5% and 1% Fe oxides: the 0.5% concentration reduced As uptake by a mean of 32% and the 1% concentration gave no significant additional benefit. On a sandy loam containing 65 mg As kg(-1) soil, there was tentative evidence that ferrous sulfate treatment up to 2% Fe oxides caused a significant reduction in lettuce As, but calabrese did not respond. At the other two sites, the effects of ferrous sulfate treatment were not significant, but the uptake of soil As was low in treated and untreated soils. Differences between sites in the bioavailable fraction of soil As may be related to the soil texture or the source of As. The highest bioavailability was found on the soil which had been contaminated by aerial deposition and had a high sand content. (C) 2003 Elsevier Science B.V. All rights reserved.

Rainfall and runoff water quality of the Pang and Lambourn, tributaries of the River Thames, south-eastern England

The water quality of rainfall and runoff is described for two catchments of two tributaries of the River Thames, the Pang and Lambourn. Rainfall chemistry is variable and concentrations of most determinands decrease with increasing volume of catch probably due to 'wash out' processes. Two rainfall sites have been monitored, one for each catchment. The rainfall site on the Lambourn shows higher chemical concentrations than the one for the Pang which probably reflects higher amounts of local inputs from agricultural activity, Rainfall quality data at a long-term rainfall site on the Pang (UK National Air Quality Archive) shows chemistries similar to that for the Lambourn site. but with some clear differences. Rainfall chemistries show considerable variation on an event-to-event basis. Average water quality concentrations and flow-weighted concentrations as well as fluxes vary across the sites, typically by about 30%. Stream chemistry is much less variable due to the main Source of water coming from aquifer sources of high storage. The relationship between rainfall and runoff chemistry at the catchment outlet is described in terms of the relative proportions of atmospheric and within-catchment sources. Remarkably, in view of the quantity of agricultural and sewage inputs to the streams, the catchments appear to be retaining both P and N.

Remote estimation of thermal inertia and soil heat flux for bare soil

A method is presented which allows thermal inertia (the soil heat capacity times the square root of the soil thermal diffusivity, C(h)rootD(h)), to be estimated remotely from micrometeorological observations. The method uses the drop in surface temperature, T-s, between sunset and sunrise, and the average night-time net radiation during that period, for clear, still nights. A Fourier series analysis was applied to analyse the time series of T-s . The Fourier series constants, together with the remote estimate of thermal inertia, were used in an analytical expression to calculate diurnal estimates of the soil heat flux, G. These remote estimates of C(h)rootD(h) and G compared well with values derived from in situ sensors. The remote and in situ estimates of C(h)rootD(h) both correlated well with topsoil moisture content. This method potentially allows area-average estimates of thermal inertia and soil heat flux to be derived from remote sensing, e.g. METEOSAT Second Generation, where the area is determined by the sensor's height and viewing angle. (C) 2003 Elsevier B.V. All rights reserved.