Seismic Microzonation: A Tool for Disaster Mitigation Planning

Seismic microzonation has generally been recognized as the most accepted tool in seismic hazard assessment and risk evaluation. In general, risk reduction can be done by reducing the hazard, the vulnerability or the value at risk. Since the earthquake hazard can not be reduced, one has to concentrate on vulnerability and value at risk. The vulnerability of an urban area / municipalities depends on the vulnerability of infrastructure and redundancies within the infrastructure. The earthquake risk is the damage to buildings along with number of people that are killed / hurt and the economic losses during the event due to an earthquake with a return period corresponding to this time period. The principal approaches one can follow to reduce these losses are to avoid, if possible, high hazard areas for the siting of buildings and infrastructure, and further ensure that the buildings and infrastructure are designed and constructed to resist expected earthquake loads. This can be done if one can assess the hazard at local scales. Seismic microzonation maps provide the basis for scientifically based decision-making to reduce earthquake risk for Govt./public agencies, private owners and the general public. Further, seismic microzonation carried out on an appropriate scale provides a valuable tool for disaster mitigation planning and emergency response planning for urban centers / municipalities. It provides the basis for the identification of the areas of the city / municipality which are most likely to experience serious damage in the event of an earthquake.

Evaluation of the AlgerBrush II rotating burr as a tool for inducing ocular surface failure in the New Zealand White rabbit

The New Zealand White rabbit has been widely used as a model of limbal stem cell deficiency (LSCD). Current techniques for experimental induction of LSCD utilize caustic chemicals, or organic solvents applied in conjunction with a surgical limbectomy. While generally successful in depleting epithelial progenitors, the depth and severity of injury is difficult to control using chemical-based methods. Moreover, the anterior chamber can be easily perforated while surgically excising the corneal limbus. In the interest of creating a safer and more defined LSCD model, we have therefore evaluated a mechanical debridement technique based upon use of the AlgerBrush II rotating burr. An initial comparison of debridement techniques was conducted in situ using 24 eyes in freshly acquired New Zealand White rabbit cadavers. Techniques for comparison (4 eyes each) included: (1) non-wounded control, (2) surgical limbectomy followed by treatment with 100% (v/v) n-heptanol to remove the corneal epithelium (1-2 minutes), (3) treatment of both limbus and cornea with n-heptanol alone, (4) treatment of both limbus and cornea with 20% (v/v) ethanol (2-3 minutes), (5) a 2.5-mm rounded burr applied to both the limbus and cornea, and (6) a 1-mm pointed burr applied to the limbus, followed by the 2.5-mm rounded burr applied to the cornea. All corneas were excised and processed for histology immediately following debridement. A panel of four assessors subsequently scored the degree of epithelial debridement within the cornea and limbus using masked slides. The 2.5-mm burr most consistently removed the corneal and limbal epithelia. Islands of limbal epithelial cells were occasionally retained following surgical limbectomy/heptanol treatment, or use of the 1-mm burr. Limbal epithelial cells were consistently retained following treatment with either ethanol or n-heptanol alone, with ethanol being the least effective treatment overall. The 2.5-mm burr method was subsequently evaluated in the right eye of 3 live rabbits by weekly clinical assessments (photography and slit lamp examination) for up to 5 weeks, followed by histological analyses (hematoxylin & eosin stain, periodic acid-Schiff stain and immunohistochemistry for keratin 3 and 13). All 3 eyes that had been completely debrided using the 2.5-mm burr displayed symptoms of ocular surface failure as defined by retention of a prominent epithelial defect (~40% of corneal surface at 5 weeks), corneal neovascularization (2 to 3 quadrants), reduced corneal transparency and conjunctivalization of the corneal surface (demonstrated by the presence of goblet cells and/or staining for keratin 13). In conclusion, our findings indicate that the AlgerBrush II rotating burr is an effective method for the establishment of ocular surface failure in New Zealand White rabbits. In particular, we recommend use of the 2.5-mm rotating burr for improved efficiency of epithelial debridement and safety compared to surgical limbectomy.

Correlative fluorescence and transmission electron microscopy: An elegant tool to study the actin cytoskeleton of whole-mount (breast) cancer cells

Elucidating the structure and dynamics of lamellipodia and filopodia in response to different stimuli is a topic of continuing interest in cancer cells as these structures may be attractive targets for therapeutic purposes. Interestingly, a close functional relationship between these actin-rich protrusions and specialized membrane domains has been recently demonstrated. The aim of this study was therefore to investigate the fine organization of these actin-rich structures and examine how they structurally may relate to detergent-resistant membrane (DRM) domains in the MTLn3 EGF/serum starvation model. For this reason, we designed a straightforward and alternative method to study cytoskeleton arrays and their associated structures by means of correlative fluorescence (/laser)- and electron microscopy (CFEM). CFEM on whole mounted breast cancer cells revealed that a lamellipodium is composed of an intricate filamentous actin web organized in various patterns after different treatments. Both actin dots and DRM's were resolved, and were closely interconnected with the surrounding cytoskeleton. Long actin filaments were repeatedly observed extending beyond the leading edge and their density and length varied after different treatments. Furthermore, CFEM also allowed us to demonstrate the close structural association of DRMs with the cytoskeleton in general and the filamentous/dot-like structural complexes in particular, suggesting that they are all functionally linked and consequently may regulate the cell's fingertip dynamics. Finally, electron tomographic modelling on the same CFEM samples confirmed that these extensions are clearly embedded within the cytoskeletal matrix of the lamellipodium.

Patient-Generated Subjective Global Assessment Short Form (PG-SGA SF) is a valid screening tool in chemotherapy outpatients

Purpose In the oncology population where malnutrition prevalence is high, more descriptive screening tools can provide further information to assist triaging and capture acute change. The Patient-Generated Subjective Global Assessment Short Form (PG-SGA SF) is a component of a nutritional assessment tool which could be used for descriptive nutrition screening. The purpose of this study was to conduct a secondary analysis of nutrition screening and assessment data to identify the most relevant information contributing to the PG-SGA SF to identify malnutrition risk with high sensitivity and specificity. Methods This was an observational, cross-sectional study of 300 consecutive adult patients receiving ambulatory anti-cancer treatment at an Australian tertiary hospital. Anthropometric and patient descriptive data were collected. The scored PG-SGA generated a score for nutritional risk (PG-SGA SF) and a global rating for nutrition status. Receiver operating characteristic curves (ROC) were generated to determine optimal cut-off scores for combinations of the PG-SGA SF boxes with the greatest sensitivity and specificity for predicting malnutrition according to scored PG-SGA global rating. Results The additive scores of boxes 1–3 had the highest sensitivity (90.2 %) while maintaining satisfactory specificity (67.5 %) and demonstrating high diagnostic value (AUC = 0.85, 95 % CI = 0.81–0.89). The inclusion of box 4 (PG-SGA SF) did not add further value as a screening tool (AUC = 0.85, 95 % CI = 0.80–0.89; sensitivity 80.4 %; specificity 72.3 %). Conclusions The validity of the PG-SGA SF in chemotherapy outpatients was confirmed. The present study however demonstrated that the functional capacity question (box 4) does not improve the overall discriminatory value of the PG-SGA SF.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.

Mixed pixel analysis for flood mapping using extended support vector machine

This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

A generic individual-based spatially explicit model as a novel tool for investigating insect-plant interactions: A case study of the behavioural ecology of frugivorous Tephritidae

Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM) strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies) were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly), Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies’ behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies’ movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by refinement of parameters based on targeted experiments.

Trial of the Primary Care Practice Improvement Tool: Building organisational performance in Australian general practice and primary health care

Objective: To nationally trial the Primary Care Practice Improvement Tool (PC-PIT), an organisational performance improvement tool previously co-created with Australian primary care practices to increase their focus on relevant quality improvement (QI) activities. Design: The study was conducted from March to December 2015 with volunteer general practices from a range of Australian primary care settings. We used a mixed-methods approach in two parts. Part 1 involved staff in Australian primary care practices assessing how they perceived their practice met (or did not meet) each of the 13 PC-PIT elements of high-performing practices, using a 1–5 Likert scale. In Part 2, two external raters conducted an independent practice visit to independently and objectively assess the subjective practice assessment from Part 1 against objective indicators for the 13 elements, using the same 1–5 Likert scale. Concordance between the raters was determined by comparing their ratings. In-depth interviews conducted during the independent practice visits explored practice managers’ experiences and perceived support and resource needs to undertake organisational improvement in practice. Results: Data were available for 34 general practices participating in Part 1. For Part 2, independent practice visits and the inter-rater comparison were conducted for a purposeful sample of 19 of the 34 practices. Overall concordance between the two raters for each of the assessed elements was excellent. Three practice types across a continuum of higher- to lower-scoring practices were identified, with each using the PC-PIT in a unique way. During the in-depth interviews, practice managers identified benefits of having additional QI tools that relate to the PC-PIT elements. Conclusions: The PC-PIT is an organisational performance tool that is acceptable, valid and relevant to our range of partners and the end users (general practices). Work is continuing with our partners and end users to embed the PC-PIT in existing organisational improvement programs.

Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.

Direct torque control schemes for split-phase induction machine

In this paper, direct torque control (DTC) algorithms for a split-phase induction machine (SPIM) are established. An SPIM has two sets of three-phase stator windings, with a shift of thirty electrical degrees between them. The significant contributions of this paper are: 1) two new methods of DTC technique for an SPIM are developed, called Resultant Flux Control Method and Individual Flux Control Method and 2) advantages and disadvantages of both methods are discussed. High torque ripple is a disadvantage for three-phase DTC. It is found that torque ripple in an SPIM can be significantly reduced without increasing the switching frequency.

Support vector machine approach for the switching transient peak overvoltages during line energization

At the time of restoration transmission line switching is one of the major causes, which creates transient overvoltages. Though detailed Electro Magnetic Transient studies are carried out extensively for the planning and design of transmission systems, such studies are not common in a day-today operation of power systems. However it is important for the operator to ensure during restoration of supply that peak overvoltages resulting from the switching operations are well within safe limits. This paper presents a support vector machine approach to classify the various cases of line energization in the category of safe or unsafe based upon the peak value of overvoltage at the receiving end of line. Operator can define the threshold value of voltage to assign the data pattern in either of the class. For illustration of proposed approach the power system used for switching transient peak overvoltages tests is a 400 kV equivalent system of an Indian southern gri

Machine recognition of online handwritten Devanagari characters

In this paper, we describe a system for the automatic recognition of isolated handwritten Devanagari characters obtained by linearizing consonant conjuncts. Owing to the large number of characters and resulting demands on data acquisition, we use structural recognition techniques to reduce some characters to others. The residual characters are then classified using the subspace method. Finally the results of structural recognition and feature-based matching are mapped to give final output. The proposed system Ifs evaluated for the writer dependent scenario.

Site characterization model using least-square support vector machine and relevance vector machine based on corrected SPT data (N-c)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N,), N values have been corrected (Ne) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three-dimensional site characterization model, the function N-c=N-c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N, value, is to be approximated in which N, value at any half-space point in Bangalore can be determined. The first algorithm uses least-square support vector machine (LSSVM), which is related to aridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel-based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright (C) 2009 John Wiley & Sons,Ltd.

Minimizing total weighted tardiness on a batch-processing machine with non-agreeable release times and due dates

This study considers the scheduling problem observed in the burn-in operation of semiconductor final testing, where jobs are associated with release times, due dates, processing times, sizes, and non-agreeable release times and due dates. The burn-in oven is modeled as a batch-processing machine which can process a batch of several jobs as long as the total sizes of the jobs do not exceed the machine capacity and the processing time of a batch is equal to the longest time among all the jobs in the batch. Due to the importance of on-time delivery in semiconductor manufacturing, the objective measure of this problem is to minimize total weighted tardiness. We have formulated the scheduling problem into an integer linear programming model and empirically show its computational intractability. Due to the computational intractability, we propose a few simple greedy heuristic algorithms and meta-heuristic algorithm, simulated annealing (SA). A series of computational experiments are conducted to evaluate the performance of the proposed heuristic algorithms in comparison with exact solution on various small-size problem instances and in comparison with estimated optimal solution on various real-life large size problem instances. The computational results show that the SA algorithm, with initial solution obtained using our own proposed greedy heuristic algorithm, consistently finds a robust solution in a reasonable amount of computation time.

Adhesion,Presence and Antifouling of Deinococcus geothermalis in Paper Machine Environment

This thesis has two items: biofouling and antifouling in paper industry. Biofouling means unwanted microbial accumulation on surfaces causing e.g. disturbances in industrial processes, contamination of medical devices or of water distribution networks. Antifouling focuses on preventing accumulation of the biofilms in undesired places. Deinococcus geothermalis is a pink-pigmented, thermophilic bacterium, and extremely resistant towards radiation, UV-light and desiccation and known as a biofouler of paper machines forming firm and biocide resistant biofilms on the stainless steel surfaces. The compact structure of biofilm microcolonies of D. geothermalis E50051 and the adhesion into abiotic surfaces were investigated by confocal laser scanning microscope combined with carbohydrate specific fluorescently labelled lectins. The extracellular polymeric substance in D. geothermalis microcolonies was found to be a composite of at least five different glycoconjugates contributing to adhesion, functioning as structural elements, putative storages for water, gliding motility and likely also to protection. The adhesion threads that D. geothermalis seems to use to adhere on an abiotic surface and to anchor itself to the neighbouring cells were shown to be protein. Four protein components of type IV pilin were identified. In addition, the lectin staining showed that the adhesion threads were covered with galactose containing glycoconjugates. The threads were not exposed on planktic cells indicating their primary role in adhesion and in biofilm formation. I investigated by quantitative real-time PCR the presence of D. geothermalis in biofilms, deposits, process waters and paper end products from 24 paper and board mills. The primers designed for doing this were targeted to the 16S rRNA gene of D. geothermalis. We found D. geothermalis DNA from 9 machines, in total 16 samples of the 120 mill samples searched for. The total bacterial content varied in those samples between 107 to 3 ×1010 16S rRNA gene copies g-1. The proportion of D. geothermalis in those same samples was minor, 0.03 1.3 % of the total bacterial content. Nevertheless D. geothermalis may endanger paper quality as its DNA was shown in an end product. As an antifouling method towards biofilms we studied the electrochemical polarization. Two novel instruments were designed for this work. The double biofilm analyzer was designed for search for a polarization program that would eradicate D. geothermalis biofilm or from stainless steel under conditions simulating paper mill environment. The Radbox instrument was designed to study the generation of reactive oxygen species during the polarization that was effective in antifouling of D. geothermalis. We found that cathodic character and a pulsed mode of polarization were required to achieve detaching D. geothermalis biofilm from stainless steel. We also found that the efficiency of polarization was good on submerged, and poor on splash area biofilms. By adding oxidative biocides, bromochloro-5,5-dimethylhydantoin, 2,2-dibromo-2-cyanodiacetamide or peracetic acid gave additive value with polarization, being active on splash area biofilms. We showed that the cathodically weighted pulsed polarization that was active in removing D. geothermalis was also effective in generation of reactive oxygen species. It is possible that the antifouling effect relied on the generation of ROS on the polarized steel surfaces. Antifouling method successful towards D. geothermalis that is a tenacious biofouler and possesses a high tolerance to oxidative stressors could be functional also towards other biofoulers and applicable in wet industrial processes elsewhere.