High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: a comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development

BACKGROUND: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). RESULTS: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. CONCLUSION: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.

Profiling ellagic acid content: The importance of form and ascorbic acid levels

As the importance of plant-based antioxidants to human health becomes clearer there is a rapidly expanding search for rich sources of these compounds. Much attention is currently focussed on the antioxidant potential of ellagic acid (EA). Making assessment difficult is that EA occurs in different forms: free EA, EA glycosides and polymeric ellagitannins. The overall structure of these forms has a pronounced effect on their antioxidant efficiency and is responsible for widely differing reactivity, solubility and hence bioavailability properties. Often associated with EA is vitamin C which also contributes to the plant foods total antioxidant activity. Previous studies have suggested that ascorbic acid may have protective effects on the polyphenol content of plants. With a view to gaining evidence that the bioactive forms of vitamin C influence EA content, several fruits with a range of EA and vitamin C contents were examined. To facilitate a more detailed assessment of the selected fruits antioxidant potential the relative proportions of EA forms were also determined. In strawberries and boysenberries EA content was predominantly in the polymeric form (21% and 12% free EA plus EA glycoside vs total EA levels for strawberry and boysenberry respectively), while in Kakadu plum it was mainly in the free form (70% of total EA). An increasing percentage of dehydroascorbic acid (9 to 14% of total vitamin C) indicating enhanced transformation of ascorbic acid to its oxidative degradation product together with stable free EA levels (≈ 950 mg/100 g DW) over the 4 month frozen storage period for the Kakadu plum samples are consistent with a possible protective effect of EA by ascorbic acid.

Towards automated content analysis of discussion transcripts: A cognitive presence case

In this paper, we present the results of an exploratory study that examined the problem of automating content analysis of student online discussion transcripts. We looked at the problem of coding discussion transcripts for the levels of cognitive presence, one of the three main constructs in the Community of Inquiry (CoI) model of distance education. Using Coh-Metrix and LIWC features, together with a set of custom features developed to capture discussion context, we developed a random forest classification system that achieved 70.3% classification accuracy and 0.63 Cohen's kappa, which is significantly higher than values reported in the previous studies. Besides improvement in classification accuracy, the developed system is also less sensitive to overfitting as it uses only 205 classification features, which is around 100 times less features than in similar systems based on bag-of-words features. We also provide an overview of the classification features most indicative of the different phases of cognitive presence that gives an additional insights into the nature of cognitive presence learning cycle. Overall, our results show great potential of the proposed approach, with an added benefit of providing further characterization of the cognitive presence coding scheme.

High-Throughput Prediction of Acacia and Eucalypt Lignin Syringyl/Guaiacyl Content Using FT-Raman Spectroscopy and Partial Least Squares Modeling

High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials.

Engine wear and used oil analysis - comparative study in high speed diesel engines

The operational life and reliability of I.C. engines are limited to a certain extent by the break down of the engine components due to wear. It is advantageous to know the condition of an engine and its components without disassembling for detailed measurements. This paper describes the possibility of employing chemical analysis of the used crank case oil to predict the wear of engine components. It is concluded that the acidity and carbon contents of the crank case oil play a significant role in assessing the wear of copper-lead bearings used for the big end of the connecting rod.

Letter to K.K.S.I. from Moses and Simon Content, August 19, 1828

Digital image

Efficient Content-based Routing, Mobility-aware Topologies, and Temporal Subspace Matching

Event-based systems are seen as good candidates for supporting distributed applications in dynamic and ubiquitous environments because they support decoupled and asynchronous many-to-many information dissemination. Event systems are widely used, because asynchronous messaging provides a flexible alternative to RPC (Remote Procedure Call). They are typically implemented using an overlay network of routers. A content-based router forwards event messages based on filters that are installed by subscribers and other routers. The filters are organized into a routing table in order to forward incoming events to proper subscribers and neighbouring routers. This thesis addresses the optimization of content-based routing tables organized using the covering relation and presents novel data structures and configurations for improving local and distributed operation. Data structures are needed for organizing filters into a routing table that supports efficient matching and runtime operation. We present novel results on dynamic filter merging and the integration of filter merging with content-based routing tables. In addition, the thesis examines the cost of client mobility using different protocols and routing topologies. We also present a new matching technique called temporal subspace matching. The technique combines two new features. The first feature, temporal operation, supports notifications, or content profiles, that persist in time. The second feature, subspace matching, allows more expressive semantics, because notifications may contain intervals and be defined as subspaces of the content space. We also present an application of temporal subspace matching pertaining to metadata-based continuous collection and object tracking.

Offloading content routing cost from routers

The publish/subscribe paradigm has lately received much attention. In publish/subscribe systems, a specialized event-based middleware delivers notifications of events created by producers (publishers) to consumers (subscribers) interested in that particular event. It is considered a good approach for implementing Internet-wide distributed systems as it provides full decoupling of the communicating parties in time, space and synchronization. One flavor of the paradigm is content-based publish/subscribe which allows the subscribers to express their interests very accurately. In order to implement a content-based publish/subscribe middleware in way suitable for Internet scale, its underlying architecture must be organized as a peer-to-peer network of content-based routers that take care of forwarding the event notifications to all interested subscribers. A communication infrastructure that provides such service is called a content-based network. A content-based network is an application-level overlay network. Unfortunately, the expressiveness of the content-based interaction scheme comes with a price - compiling and maintaining the content-based forwarding and routing tables is very expensive when the amount of nodes in the network is large. The routing tables are usually partially-ordered set (poset) -based data structures. In this work, we present an algorithm that aims to improve scalability in content-based networks by reducing the workload of content-based routers by offloading some of their content routing cost to clients. We also provide experimental results of the performance of the algorithm. Additionally, we give an introduction to the publish/subscribe paradigm and content-based networking and discuss alternative ways of improving scalability in content-based networks. ACM Computing Classification System (CCS): C.2.4 [Computer-Communication Networks]: Distributed Systems - Distributed applications

Using Big Data to manage safety-related risk in the upstream oil and gas industry: A research agenda

Despite considerable effort and a broad range of new approaches to safety management over the years, the upstream oil & gas industry has been frustrated by the sector’s stubbornly high rate of injuries and fatalities. This short communication points out, however, that the industry may be in a position to make considerable progress by applying “Big Data” analytical tools to the large volumes of safety-related data that have been collected by these organizations. Toward making this case, we examine existing safety-related information management practices in the upstream oil & gas industry, and specifically note that data in this sector often tends to be highly customized, difficult to analyze using conventional quantitative tools, and frequently ignored. We then contend that the application of new Big Data kinds of analytical techniques could potentially reveal patterns and trends that have been hidden or unknown thus far, and argue that these tools could help the upstream oil & gas sector to improve its injury and fatality statistics. Finally, we offer a research agenda toward accelerating the rate at which Big Data and new analytical capabilities could play a material role in helping the industry to improve its health and safety performance.

Water activity of poultry litter: Relationship to moisture content during a grow-out

Poultry grown on litter floors are in contact with their own waste products. The waste material needs to be carefully managed to reduce food safety risks and to provide conditions that are comfortable and safe for the birds. Water activity (Aw) is an important thermodynamic property that has been shown to be more closely related to microbial, chemical and physical properties of natural products than moisture content. In poultry litter, Aw is relevant for understanding microbial activity; litter handling and rheological properties; and relationships between in-shed relative humidity and litter moisture content. We measured the Aw of poultry litter collected throughout a meat chicken grow-out (from fresh pine shavings bedding material to day 52) and over a range of litter moisture content (10–60%). The Aw increased non-linearly from 0.71 to 1.0, and reached a value of 0.95 when litter moisture content was only 22–33%. Accumulation of manure during the grow-out reduced Aw for the same moisture content. These results are relevant for making decisions regarding litter re-use in multiple grow-outs as well as setting targets for litter moisture content to minimise odour, microbial risks and to ensure necessary litter physical conditions are maintained during a grow-out. Methods to predict Aw in poultry litter from moisture content are proposed.

Evaluation of chlorothalonil and paraffinic oil alone and in combinations with registered fungicides for the control of yellow Sigatoka (Mycosphaerella musicola) of bananas in Northern Queensland, Australia

The efficacy of chlorothalonil and paraffinic oil alone and in combinations with the registered fungicides propiconazole, tebuconazole, difenoconazole, epoxiconazole and pyrimethanil was evaluated in a field experiment over two cropping cycles in 2013 and 2014 in Northern Queensland, Australia, for control of yellow Sigatoka (caused by Mycosphaerella musicola) of banana. The predominantly applied by the banana industry treatment mancozeb with paraffinic oil was included for comparison. The results from the two cropping cycles suggested that all chemicals used with paraffinic oil were as effective or more effective than when applied with chlorothalonil, and chlorothalonil alone. Difenoconazole and epoxiconazole with paraffinic oil followed by propiconazole with paraffinic oil were the most effective treatments. Pyrimethanil and tebuconazole plus chlorothalonil were the least effective treatments. None of the chemical treatments was phytotoxic or reduced yield.

Engine wear and used oil analysis-A comparative study in high speed diesel engines

The operational life and reliability of I.C. engines are limited to a certain extent by the break down of the engine components due to wear. It is advantageous to know the condition of an engine and its components without disassembling for detailed measurements. This paper describes the possibility of employing chemical analysis of the used crank case oil to predict the wear of engine components. It is concluded that the acidity and carbon contents of the crank case oil play a significant role in assessing the wear of copper-lead bearings used for the big end of the connecting rod.

Clustering Users of Online Content Service

Online content services can greatly benefit from personalisation features that enable delivery of content that is suited to each user's specific interests. This thesis presents a system that applies text analysis and user modeling techniques in an online news service for the purpose of personalisation and user interest analysis. The system creates a detailed thematic profile for each content item and observes user's actions towards content items to learn user's preferences. A handcrafted taxonomy of concepts, or ontology, is used in profile formation to extract relevant concepts from the text. User preference learning is automatic and there is no need for explicit preference settings or ratings from the user. Learned user profiles are segmented into interest groups using clustering techniques with the objective of providing a source of information for the service provider. Some theoretical background for chosen techniques is presented while the main focus is in finding practical solutions to some of the current information needs, which are not optimally served with traditional techniques.

A noticeboard in "both worlds" unsurprising interfaces supporting easy bi-cultural content publication

We describe the design of a digital noticeboard to support communication within a remote Aboriginal community whose aspiration is to live in "both worlds", nurturing and extending their Aboriginal culture and actively participating in Western society and economy. Three bi-cultural aspects have emerged and are presented here: the need for a bi-lingual noticeboard to span both oral and written language traditions, the tension between perfunctory information exchange and social, embodied protocols of telling in person and the different ways in which time is represented in both cultures. The design approach, developed iteratively through consultation, demonstration and testing led to an "unsurprising interface", aimed at maximizing use and appropriation across cultures by unifying visual, text and spoken contents in both passive and interactive displays in a modeless manner.

Measuring the impact of burn scarring on health-related quality of life: Development and preliminary content validation of the Brisbane Burn Scar Impact Profile (BBSIP) for children and adults

INTRODUCTION No burn-scar specific, health-related quality of life (HRQOL) measure exists. This study aimed to develop a patient-reported, evaluative HRQOL measure to assess the impact of burn scarring in children and adults. METHOD Semi-structured interviews, content validation surveys, and cognitive interviews were used to develop and test content validity of a new measure - the Brisbane Burn Scar Impact Profile (BBSIP). RESULTS Participants comprised Australian adults (n=23) and children (n=19) with burn scarring; caregivers of children with burn scarring (n=28); and international scar management experts (n=14). Items distinct from other burn scar measures emerged. Four versions of the BBSIP were developed; one for children aged 8-18 years, one for adults, one for caregivers (as proxies for children aged less than 8-years), and one for caregivers of children aged 8-18 years. Preliminary content validity of the BBSIP was supported. Final items covered physical and sensory symptoms; emotional reactions; impact on social functioning and daily activities; impact of treatment; and environmental factors. CONCLUSION The BBSIP was developed to assess burn-scar specific HRQOL and will be available at http://www.coolburns.com.au under a creative commons license. Further testing is underway.