Climate models without pre-industrial volcanic forcing underestimate historical ocean thermal expansion

Episodic explosive volcanic eruptions are a natural part of the climate system but are often omitted from atmosphere-ocean general circulation model (AOGCM) preindustrial spin-up and control experiments. This omission imposes a negative bias on ocean heat uptake in simulations of the historical period. In models of a range of complexity, we find that global-mean sea level rise due to thermal expansion during the last ∼ 150 years is consequently underestimated by 5–30 mm, which is a substantial proportion of the model mean of 50 mm in Coupled Model Intercomparison Project Phase 3 AOGCMs with anthropogenic forcing only, and is therefore important in accounting for 20th century sea level rise. We test and recommend a procedure for removing the bias.

Which factors drive rental depreciation rates for office and industrial properties?

As new buildings are constructed in response to changes in technology or user requirements, the value of the existing stock will decline in relative terms. This is termed economic depreciation and it may be influenced by the age and quality of buildings, amount and timing of expenditure, and wider market and economic conditions. This study tests why individual assets experience different depreciation rates, applying panel regression techniques to 375 UK office and industrial assets. Results suggest that rental value depreciation rates reduce as buildings get older, while a composite measure of age and quality provides more explanation of depreciation than age alone. Furthermore, economic and local real estate market conditions are significant in explaining how depreciation rates change over time.

Volatile profile of Spanish Cistus plants as sources of antimicrobials for industrial applications

Cistus is a plant genus traditionally used in folk medicine as remedy for several microbial disorders and infections. The abundance of Cistus spp. in the Iberian Peninsula together with their ability to renew after wildfire contribute to their profitability as suppliers of functional ingredients. The aim of this study was to provide a comprehensive characterization of the volatile profile of different Cistus plants grown in Spain:Cistus ladanifer L., Cistus albidus L., Cistus salviifolius L., and Cistus clusii Dunal (the latter has not been studied before). A system combining headspace solid-phase microextraction and gas chromatography coupled to mass spectrometry (HS-SPME-GC–MS) was implemented; thereby, the volatile compounds were extracted and analyzed in a fast, reliable and environment-friendly way. A total of 111 volatile compounds were identified, 28 of which were reported in Cistus for the first time. The most abundant components of the samples (mono and sesquiterpenes) have been previously reported as potent antimicrobial agents. Therefore, this work reveals the potential use of the Cistus spp. studied as natural sources of antimicrobial compounds for industrial production of cosmeceuticals, among other applications.

Geoadditive models for regional count data: an application to industrial location

We propose a geoadditive negative binomial model (Geo-NB-GAM) for regional count data that allows us to address simultaneously some important methodological issues, such as spatial clustering, nonlinearities, and overdispersion. This model is applied to the study of location determinants of inward greenfield investments that occurred during 2003–2007 in 249 European regions. After presenting the data set and showing the presence of overdispersion and spatial clustering, we review the theoretical framework that motivates the choice of the location determinants included in the empirical model, and we highlight some reasons why the relationship between some of the covariates and the dependent variable might be nonlinear. The subsequent section first describes the solutions proposed by previous literature to tackle spatial clustering, nonlinearities, and overdispersion, and then presents the Geo-NB-GAM. The empirical analysis shows the good performance of Geo-NB-GAM. Notably, the inclusion of a geoadditive component (a smooth spatial trend surface) permits us to control for spatial unobserved heterogeneity that induces spatial clustering. Allowing for nonlinearities reveals, in keeping with theoretical predictions, that the positive effect of agglomeration economies fades as the density of economic activities reaches some threshold value. However, no matter how dense the economic activity becomes, our results suggest that congestion costs never overcome positive agglomeration externalities.

Draft genome sequence of Pseudomonas corrugata, a phytopathogenic bacterium with potential industrial applications

Pseudomonas corrugata was first described as the causal agent of a tomato disease called ‘pith necrosis’ yet it is considered as a biological resource in various fields such as biocontrol of plant diseases and production of industrially promising microbial biopolymers (mcl-PHA). Here we report the first draft genome sequence of this species.

Accuracy of Periapical Radiography and Cone-Beam Computed Tomography Scans in Diagnosing Apical Periodontitis Using Histopathological Findings as a Gold Standard

Introduction: The aim of this study was to evaluate the accuracy of two imaging methods in diagnosing apical periodontitis (AP) using histopathological findings as a gold standard. Methods: The periapex of 83 treated or untreated roots of dogs` teeth was examined using periapical radiography (PR), cone-beam computed tomography (CBCT) scans, and histology. Sensitivity, specificity, predictive values, and accuracy of PR and CBCT diagnosis were calculated. Results: PR detected AP in 71% of roots, a CBCT scan detected AP in 84%, and AP was histologically diagnosed in 93% (p = 0.001). Overall, sensitivity was 0.77 and 0.91 for PR and CBCT, respectively. Specificity was 1 for both. Negative predictive value was 0.25 and 0.46 for PR and CBCT, respectively. Positive predictive value was 1 for both. Diagnostic accuracy (true positives + true negatives) was 0.78 and 0.92 for PR and CBCT (p = 0.028), respectively. Conclusion: A CBCT scan was more sensitive in detecting AP compared with PR, which was more likely to miss AP when it was still present. (J Endod 2009;35:1009-1012)

Outcome of Root Canal Treatment in Dogs Determined by Periapical Radiography and Cone-Beam Computed Tomography Scans

The purpose of this study was to compare the favorable outcome of root canal treatment determined by periapical radiographs (PRs) and cone beam computed tomography (CBCT) scans. Ninety-six roots of dogs` teeth were used to form four groups (n = 24). In group 1, root canal treatments were performed in healthy teeth. Root canals in groups 2 through 4 were infected until apical periodontitis (AP) was radiographically confirmed. Roots with AP were treated by one-visit therapy in group 2, by two-visit therapy in group 3, and left untreated in group 4. The radiolucent area in the PRs and the volume of CBCT-scanned periapical lesions were measured before and 6 months after the treatment. In groups 1, 2, and 3, a favorable outcome (lesions absent or reduced) was shown in 57 (79%) roots using PRs but only in 25 (35%) roots using CBCT scans (p = 0.0001). Unfavorable outcomes occurred more frequently after one-visit therapy than two-visit therapy when determined by CBCT scans (p = 0.023). (J Endod 2009; 35:723-726)

Genotoxic effects of X-rays on keratinized mucosa cells during panoramic dental radiography

Objectives: The aim of this study was to evaluate the genotoxic effects of X-rays on epithelial gingival cells during panoramic dental radiography using a differentiated protocol for the micronucleus test. Methods: 40 healthy individuals who underwent this procedure for diagnostic purposes on request from their dentists agreed to participate in this study. All of them answered a questionnaire before the examination. Epithelial gingival cells were obtained from the keratinized mucosa of the upper dental arcade by gentle scraping with a cervical brush immediately before exposure and 10 days later. Cytological preparations were stained according to the Feulgen-Rossenbeck reaction, counterstained with fast green 1% for 1 min and analysed under a light microscope. Micronuclei, nuclear projections (broken eggs) and degenerative nuclear alterations (pyknosis, karyolysis, karyorrhexis and condensed chromatin) were scored. Results: The frequency of micronuclei was significantly higher after exposure (P < 0.05), as were frequencies of nuclear alterations indicate of apoptosis (P < 0.001). Conclusions: These results indicate that X-ray radiation emitted during panoramic dental radiography induces a genotoxic effect on epithelial gingival cells that increases the frequency of chromosomal damage and nuclear alterations indicative of apoptosis.

Valorization of an Industrial Organosolv-Sugarcane Bagasse Lignin: Characterization and Use as a Matrix in Biobased Composites Reinforced With Sisal Fibers

In the present study, the main focus was the characterization and application of the by-product lignin isolated through an industrial organosolv acid hydrolysis process from sugarcane bagasse, aiming at the production of bioethanol. The sugarcane lignin was characterized and used to prepare phenolic-type resins. The analysis confirmed that the industrial sugarcane lignin is of HGS type, with a high proportion of the less substituted aromatic ring p-hydroxyphenyl units, which favors further reaction with formaldehyde. The lignin-formaldehyde resins were used to produce biobased composites reinforced with different proportions of randomly distributed sisal fibers. The presence of lignin moieties in both the fiber and matrix increases their mutual affinity, as confirmed by SEM images, which showed good adhesion at the biocomposite fiber/matrix interface. This in turn allowed good load transference from the matrix to the fiber, leading to biobased composites with good impact strength (near 500 J m(-1) for a 40 wt% sisal fiber-reinforced composite). The study demonstrates that sugarcane bagasse lignin obtained from a bioethanol plant can be used without excessive purification in the preparation of lignocellulosic fiber-reinforced biobased composites displaying high mechanical properties. Biotechnol. Bioeng. 2010;107: 612-621. (C) 2010 Wiley Periodicals, Inc.

Agro-Based Biocomposites for Industrial Applications

Leaf fibers are fibers that run lengthwise through the leaves of most monocotyledonous plants such as pineapple, banana, etc. Pineapple (Ananas comosus) and Banana (Musa indica) are emerging fiber having a very large potential to be used for composite materials. Over 150,000 ha of pineapple and over 100,000 ha of banana plantations are available in Brazil for the fruit production and enormous amount of agricultural waste is produced. This residual waste represents one of the single largest sources of cellulose fibers available at almost no cost. The potential consumers for this fiber are pulp and paper, chemical feedstock, textiles and composites for the automotive, furniture and civil construction industry.

Industrial IT - Att certifiera produktinformation på ABB

Detta examensarbete genomfördes på ABB Power Technologies AB i Ludvika. ABB vill överbrygga gapet mellan industri och informationsteknologi för att få de båda delarna att arbeta integrerat. ABB kallar detta koncept för Industrial IT (IIT). Ett krav från koncernledningen är att alla produkter ska vara certifierade enligt nivå 0, som är det första steget i IIT: s certifieringsprocess. Målet var att utföra en kravspecifikation på ett system som ska kunna leverera certifierad produktinformation enligt IIT-standard. Målet var även att, med kravspecifikationen som underlag, ge förslag på en lösning för att ABB ska kunna skapa och bifoga denna produktinformation till sina kunder.Det akademiska syftet var att beskriva hur man kan gå till väga för att certifiera produktinformationen enligt IIT nivå 0 på en produkt i ABB: s verksamhet. Syftet var även att öka förståelsen för IIT-konceptet.Genom hela arbetet har Gatemodellen använts. Denna projektstyrningsmodell är framtagen speciellt för informationssystem-projekt inom ABB och alla projekt som utförs inom ABB ska följa den. För att uppfylla målet med en utförd kravspecifikation har relevanta delar ur Directmodellen använts. För att få information om hur verksamheten fungerar och få insikt i problematiken har intervjuer genomförts som grundar sig på litteraturstudier.Vi föreslår att ett tidigare utgivet system vid namn Aspect Object Builder (AOB) används som grund i det här projektet. AOB: n har använts i liknande projekt inom ABB och fungerat bra. Det finns ingen standardkoppling mellan AOB: n och de system där produktinformationen finns eftersom det finns så många olika typer av filservrar, PDM- och ERP-system, där informationen lagras. Därför måste ett unikt gränssnitt göras för just detta projekt, som hjälper AOB: n att samla in data. Ett förslag till ett gränssnitt presenteras i uppsatsen.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.

Energy Analysis within Industrial Hydraulics and Correspondent Solar PV System Design

Energy efficiency and renewable energy use are two main priorities leading to industrial sustainability nowadays according to European Steel Technology Platform (ESTP). Modernization efforts can be done by industries to improve energy consumptions of the production lines. These days, steel making industrial applications are energy and emission intensive. It was estimated that over the past years, energy consumption and corresponding CO2 generation has increased steadily reaching approximately 338.15 parts per million in august 2010 [1]. These kinds of facts and statistics have introduced a lot of room for improvement in energy efficiency for industrial applications through modernization and use of renewable energy sources such as solar Photovoltaic Systems (PV).The purpose of this thesis work is to make a preliminary design and simulation of the solar photovoltaic system which would attempt to cover the energy demand of the initial part of the pickling line hydraulic system at the SSAB steel plant. For this purpose, the energy consumptions of this hydraulic system would be studied and evaluated and a general analysis of the hydraulic and control components performance would be done which would yield a proper set of guidelines contributing towards future energy savings. The results of the energy efficiency analysis showed that the initial part of the pickling line hydraulic system worked with a low efficiency of 3.3%. Results of general analysis showed that hydraulic accumulators of 650 liter size should be used by the initial part pickling line system in combination with a one pump delivery of 100 l/min. Based on this, one PV system can deliver energy to an AC motor-pump set covering 17.6% of total energy and another PV system can supply a DC hydraulic pump substituting 26.7% of the demand. The first system used 290 m2 area of the roof and was sized as 40 kWp, the second used 109 m2 and was sized as 15.2 kWp. It was concluded that the reason for the low efficiency was the oversized design of the system. Incremental modernization efforts could help to improve the hydraulic system energy efficiency and make the design of the solar photovoltaic system realistically possible. Two types of PV systems where analyzed in the thesis work. A method was found calculating the load simulation sequence based on the energy efficiency studies to help in the PV system simulations. Hydraulic accumulators integrated into the pickling line worked as energy storage when being charged by the PV system as well.