Assessing the combined effect of asbestos exposure and smoking on lung cancer: a Bayesian approach

We review the literature on the combined association between lung cancer and two environmental exposures, asbestos exposure and smoking, and explore a Bayesian approach to assess evidence of interaction between the exposures. The meta-analysis combines separate indices of additive and multiplicative relationships and multivariate relative risk estimates. By making inferences on posterior probabilities we can explore both the form and strength of interaction. This analysis may be more informative than providing evidence to support one relation over another on the basis of statistical significance. Overall, we find evidence for a more than additive and less than multiplicative relation.

Damage assessment of structures with uncertainty by using mode-shape curvatures and fuzzy logic

Uncertainties associated with the structural model and measured vibration data may lead to unreliable damage detection. In this paper, we show that geometric and measurement uncertainty cause considerable problem in damage assessment which can be alleviated by using a fuzzy logic-based approach for damage detection. Curvature damage factor (CDF) of a tapered cantilever beam are used as damage indicators. Monte Carlo simulation (MCS) is used to study the changes in the damage indicator due to uncertainty in the geometric properties of the beam. Variation in these CDF measures due to randomness in structural parameter, further contaminated with measurement noise, are used for developing and testing a fuzzy logic system (FLS). Results show that the method correctly identifies both single and multiple damages in the structure. For example, the FLS detects damage with an average accuracy of about 95 percent in a beam having geometric uncertainty of 1 percent COV and measurement noise of 10 percent in single damage scenario. For multiple damage case, the FLS identifies damages in the beam with an average accuracy of about 94 percent in the presence of above mentioned uncertainties. The paper brings together the disparate areas of probabilistic analysis and fuzzy logic to address uncertainty in structural damage detection.

Prediction of masonry compressive behaviour using a damage mechanics inspired modelling method

Masonry under compression is affected by the properties of its constituents and their interfaces. In spite of extensive investigations of the behaviour of masonry under compression, the information in the literature cannot be regarded as comprehensive due to ongoing inventions of new generation products – for example, polymer modified thin layer mortared masonry and drystack masonry. As comprehensive experimental studies are very expensive, an analytical model inspired by damage mechanics is developed and applied to the prediction of the compressive behaviour of masonry in this paper. The model incorporates a parabolic progressively softening stress-strain curve for the units and a progressively stiffening stress-strain curve until a threshold strain for the combined mortar and the unit-mortar interfaces is reached. The model simulates the mutual constraints imposed by each of these constituents through their respective tensile and compressive behaviour and volumetric changes. The advantage of the model is that it requires only the properties of the constituents and considers masonry as a continuum and computes the average properties of the composite masonry prisms/wallettes; it does not require discretisation of prism or wallette similar to the finite element methods. The capability of the model in capturing the phenomenological behaviour of masonry with appropriate elastic response, stiffness degradation and post peak softening is presented through numerical examples. The fitting of the experimental data to the model parameters is demonstrated through calibration of some selected test data on units and mortar from the literature; the calibrated model is shown to predict the responses of the experimentally determined masonry built using the corresponding units and mortar quite well. Through a series of sensitivity studies, the model is also shown to predict the masonry strength appropriately for changes to the properties of the units and mortar, the mortar joint thickness and the ratio of the height of unit to mortar joint thickness. The unit strength is shown to affect the masonry strength significantly. Although the mortar strength has only a marginal effect, reduction in mortar joint thickness is shown to have a profound effect on the masonry strength. The results obtained from the model are compared with the various provisions in the Australian Masonry Structures Standard AS3700 (2011) and Eurocode 6.

Post-head-emergence frost in wheat and barley: defining the problem, assessing the damage, and identifying resistance

Radiant frost is a significant production constraint to wheat (Triticum aestivum) and barley (Hordeum vulgare), particularly in regions where spring-habit cereals are grown through winter, maturing in spring. However, damage to winter-habit cereals in reproductive stages is also reported. Crops are particularly susceptible to frost once awns or spikes emerge from the protection of the flag leaf sheath. Post-head-emergence frost (PHEF) is a problem distinct from other cold-mediated production constraints. To date, useful increased PHEF resistance in cereals has not been identified. Given the renewed interest in reproductive frost damage in cereals, it is timely to review the problem. Here we update the extent and impacts of PHEF and document current management options to combat this challenge. We clarify terminology useful for discussing PHEF in relation to chilling and other freezing stresses. We discuss problems characterizing radiant frost, the environmental conditions leading to PHEF damage, and the effects of frost at different growth stages. PHEF resistant cultivars would be highly desirable, to both reduce the incidence of direct frost damage and to allow the timing of crop maturity to be managed to maximize yield potential. A framework of potential adaptation mechanisms is outlined. Clarification of these critical issues will sharpen research focus, improving opportunities to identify genetic sources for improved PHEF resistance.

Post-head-emergence frost in wheat and barley: defining the problem, assessing the damage, and identifying resistance

Radiant frost is a significant production constraint to wheat (Triticum aestivum) and barley (Hordeum vulgare), particularly in regions where spring-habit cereals are grown through winter, maturing in spring. However, damage to winter-habit cereals in reproductive stages is also reported. Crops are particularly susceptible to frost once awns or spikes emerge from the protection of the flag leaf sheath. Post-head-emergence frost (PHEF) is a problem distinct from other cold-mediated production constraints. To date, useful increased PHEF resistance in cereals has not been identified. Given the renewed interest in reproductive frost damage in cereals, it is timely to review the problem. Here we update the extent and impacts of PHEF and document current management options to combat this challenge. We clarify terminology useful for discussing PHEF in relation to chilling and other freezing stresses. We discuss problems characterizing radiant frost, the environmental conditions leading to PHEF damage, and the effects of frost at different growth stages. PHEF resistant cultivars would be highly desirable, to both reduce the incidence of direct frost damage and to allow the timing of crop maturity to be managed to maximize yield potential. A framework of potential adaptation mechanisms is outlined. Clarification of these critical issues will sharpen research focus, improving opportunities to identify genetic sources for improved PHEF resistance.

Automating Crop Damage Assessments with Unmanned Aerial Systems and Machine Learning

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 methodology 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 this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling 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 clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.

Development of a transient gradient enhanced non local continuum damage mechanics model for masonry

Due to the advent of varied types of masonry systems a comprehensive failure mechanism of masonry essential for the understanding of its behaviour is impossible to be determined from experimental testing. As masonry is predominantly used in wall structures a biaxial stress state dominates its failure mechanism. Biaxial testing will therefore be necessary for each type of masonry, which is expensive and time consuming. A computational method would be advantageous; however masonry is complex to model which requires advanced computational modelling methods. This thesis has formulated a damage mechanics inspired modelling method and has shown that the method effectively determines the failure mechanisms and deformation characteristics of masonry under biaxial states of loading.

Microarrays in Lung Cancer Research: From Comparative Analyses to Verified Findings

Keuhkosyöpä on yleisimpiä syöpätauteja. Se jaetaan kahteen päätyyppiin: pienisoluiseen ja ei-pienisoluiseen keuhkosyöpään. Ei-pienisoluinen keuhkosyöpä jaetaan lisäksi alatyyppeihin, joista suurimmat ovat levyepiteeli-, adeno- ja suurisoluinen karsinooma. Keuhkosyövän tärkein riskitekijä on tupakointi, mutta muutkin työ- ja elinympäristön altisteet, kuten asbesti, voivat johtaa syöpään. Väitöstyössä tutkittiin kahdenlaisten keuhkosyöpäryhmien erityispiirteitä. Työssä kartoitettiin, onko löydettävissä muutoksia, jotka erottavat asbestikeuhkosyövät muista syövistä sekä luuytimeen varhaisessa vaiheessa leviävät keuhkosyövät leviämättömistä syövistä. Tutkimusten ensimmäisessä vaiheessa käytettiin mikrosirupohjaisia menetelmiä, jotka mahdollistavat jopa kaikkien geenien tarkastelun yhden kokeen avulla. Vertailevien mikrosirututkimusten avulla on mahdollista paikantaa geenejä tai kromosomialueita, joiden muutokset erottelevat ryhmät toisistaan. Asbestiin liittyvissä tutkimuksissa paikannettiin kuusi kromosomialuetta, joissa geenien kopiolukumäärän sekä ilmenemistason muutokset erottelivat potilaat altistushistorian mukaan. Riippumattomilla laboratoriomenetelmillä tehtyjen jatkoanalyysien avulla pystyttiin varmistamaan, että 19p-alueen häviämä oli yhteydessä asbestialtistukseen. Työssä osoitettiin myös, että 19p-alueen muutoksia voidaan indusoida altistamalla soluja asbestille in vitro. Tutkimuksessa saatiin lisäksi viitteitä asbestispesifisistä muutoksista signaalinvälitysreiteissä, sillä yhdessä toimivien geenien ilmentymisessä havaittiin eroja asbestille altistuneiden ja altistumattomien välillä. Vertailemalla luuytimeen syövän aikaisessa vaiheessa levinneiden ja leviämättömien keuhkoadenokarsinoomien muutosprofiileita toisiinsa, paikannettiin viisi aluetta, joilla geenien kopiolukumäärä- sekä ilmenemistason muutokset erottelivat ryhmät toisistaan. Jatkoanalyyseissä havaittiin, että 4q-alueen häviämää esiintyi adenokarsinoomien lisäksi levyepiteelikarsinoomiin, jotka olivat levinneet luuytimeen. Myös keuhkosyöpien aivometastaaseissa alue oli toistuvasti hävinnyt. Väitöstyön tutkimukset osoittavat, että vertailevien mikrosiruanalyysien avulla saadaan tietoa syöpäryhmien erityispiirteistä. Työssä saadut tulokset osoittavat, että 19p-alueen muutokset ovat tyypillisiä asbestikeuhkosyöville ja 4q-alueen muutokset luuytimeen aikaisessa vaiheessa leviäville keuhkosyöville.

Acoustic emission source location and damage detection in a metallic structure using a graph-theory-based geodesic pproach

A geodesic-based approach using Lamb waves is proposed to locate the acoustic emission (AE) source and damage in an isotropic metallic structure. In the case of the AE (passive) technique, the elastic waves take the shortest path from the source to the sensor array distributed in the structure. The geodesics are computed on the meshed surface of the structure using graph theory based on Dijkstra's algorithm. By propagating the waves in reverse virtually from these sensors along the geodesic path and by locating the first intersection point of these waves, one can get the AE source location. The same approach is extended for detection of damage in a structure. The wave response matrix of the given sensor configuration for the healthy and the damaged structure is obtained experimentally. The healthy and damage response matrix is compared and their difference gives the information about the reflection of waves from the damage. These waves are backpropagated from the sensors and the above method is used to locate the damage by finding the point where intersection of geodesics occurs. In this work, the geodesic approach is shown to be suitable to obtain a practicable source location solution in a more general set-up on any arbitrary surface containing finite discontinuities. Experiments were conducted on aluminum specimens of simple and complex geometry to validate this new method.

Exposure-related human cancer: Molecular changes in sinonasal cancer and lung cancer, with focus on TP53 mutations

Cancer is a leading cause of death worldwide and the total number of cancer cases continues to increase. Many cancers, for example sinonasal cancer and lung cancer, have clear external risk factors and so are potentially preventable. The occurrence of sinonasal cancer is strongly associated with wood dust exposure and the main risk factor for lung cancer is tobacco smoking. Although the molecular mechanisms involved in lung carcinogenesis have been widely studied, very little is known about the molecular changes leading to sinonasal cancer. In this work, mutations in the tumour suppressor TP53 gene in cases of sinonasal cancer and lung cancer and the associations of these mutations with exposure factors were studied. In addition, another important mechanism in many cancers, inflammation, was explored by analyzing the expression of the inflammation related enzyme, COX-2, in sinonasal cancer. The results demonstrate that TP53 mutations are frequent in sinonasal cancer and lung cancer and in both cancers they are associated with exposure. In sinonasal cancer, the occurrence of TP53 mutation significantly increased in relation to long duration and high level of exposure to wood dust. Smoking was not associated with the overall occurrence of the TP53 mutation in sinonasal cancer, but was associated with multiple TP53 mutations. Furthermore, inflammation appears to play a part in sinonasal carcinogenesis as indicated by our results showing that the expression of COX-2 was associated with adenocarcinoma type of tumours, wood dust exposure and non-smoking. In lung cancer, we detected statistically significant associations between TP53 mutations and duration of smoking, gender and histology. We also found that patients with a tumour carrying a G to T transversion, a mutation commonly found in association with tobacco smoking, had a high level of smoking-related bulky DNA adducts in their non-tumorous lung tissue. Altogether, the information on molecular changes in exposure induced cancers adds to the observations from epidemiological studies and helps to understand the role and impact of different etiological factors, which in turn can be beneficial for risk assessment and prevention.