Aerothermodynamic cycle analysis of a dual-spool, separate-exhaust turbofan engine with an interstage turbine burner

This study focuses on a specific engine, i.e., a dual-spool, separate-flow turbofan engine with an Interstage Turbine Burner (ITB). This conventional turbofan engine has been modified to include a secondary isobaric burner, i.e., ITB, in a transition duct between the high-pressure turbine and the low-pressure turbine. The preliminary design phase for this modified engine starts with the aerothermodynamics cycle analysis is consisting of parametric (i.e., on-design) and performance (i.e., off-design) cycle analyses. In parametric analysis, the modified engine performance parameters are evaluated and compared with baseline engine in terms of design limitation (maximum turbine inlet temperature), flight conditions (such as flight Mach condition, ambient temperature and pressure), and design choices (such as compressor pressure ratio, fan pressure ratio, fan bypass ratio etc.). A turbine cooling model is also included to account for the effect of cooling air on engine performance. The results from the on-design analysis confirmed the advantage of using ITB, i.e., higher specific thrust with small increases in thrust specific fuel consumption, less cooling air, and less NOx production, provided that the main burner exit temperature and ITB exit temperature are properly specified. It is also important to identify the critical ITB temperature, beyond which the ITB is turned off and has no advantage at all. With the encouraging results from parametric cycle analysis, a detailed performance cycle analysis of the identical engine is also conducted for steady-stateengine performance prediction. The results from off-design cycle analysis show that the ITB engine at full throttle setting has enhanced performance over baseline engine. Furthermore, ITB engine operating at partial throttle settings will exhibit higher thrust at lower specific fuel consumption and improved thermal efficiency over the baseline engine. A mission analysis is also presented to predict the fuel consumptions in certain mission phases. Excel macrocode, Visual Basic for Application, and Excel neuron cells are combined to facilitate Excel software to perform these cycle analyses. These user-friendly programs compute and plot the data sequentially without forcing users to open other types of post-processing programs.

Semiotic Analysis in the Study of Social Work

Research and professional practices have the joint aim of re-structuring the preconceived notions of reality. They both want to gain the understanding about social reality. Social workers use their professional competence in order to grasp the reality of their clients, while researchers’ pursuit is to open the secrecies of the research material. Development and research are now so intertwined and inherent in almost all professional practices that making distinctions between practising, developing and researching has become difficult and in many aspects irrelevant. Moving towards research-based practices is possible and it is easily applied within the framework of the qualitative research approach (Dominelli 2005, 235; Humphries 2005, 280). Social work can be understood as acts and speech acts crisscrossing between social workers and clients. When trying to catch the verbal and non-verbal hints of each others’ behaviour, the actors have to do a lot of interpretations in a more or less uncertain mental landscape. Our point of departure is the idea that the study of social work practices requires tools which effectively reveal the internal complexity of social work (see, for example, Adams & Dominelli & Payne 2005, 294 – 295). The boom of qualitative research methodologies in recent decades is associated with much profound the rupture in humanities, which is called the linguistic turn (Rorty 1967). The idea that language is not transparently mediating our perceptions and thoughts about reality, but on the contrary it constitutes it was new and even confusing to many social scientists. Nowadays we have got used to read research reports which have applied different branches of discursive analyses or narratologic or semiotic approaches. Although differences are sophisticated between those orientations they share the idea of the predominance of language. Despite the lively research work of today’s social work and the research-minded atmosphere of social work practice, semiotics has rarely applied in social work research. However, social work as a communicative practice concerns symbols, metaphors and all kinds of the representative structures of language. Those items are at the core of semiotics, the science of signs, and the science which examines people using signs in their mutual interaction and their endeavours to make the sense of the world they live in, their semiosis. When thinking of the practice of social work and doing the research of it, a number of interpretational levels ought to be passed before reaching the research phase in social work. First of all, social workers have to interpret their clients’ situations, which will be recorded in the files. In some very rare cases those past situations will be reflected in discussions or perhaps interviews or put under the scrutiny of some researcher in the future. Each and every new observation adds its own flavour to the mixture of meanings. Social workers have combined their observations with previous experience and professional knowledge, furthermore, the situation on hand also influences the reactions. In addition, the interpretations made by social workers over the course of their daily working routines are never limited to being part of the personal process of the social worker, but are also always inherently cultural. The work aiming at social change is defined by the presence of an initial situation, a specific goal, and the means and ways of achieving it, which are – or which should be – agreed upon by the social worker and the client in situation which is unique and at the same time socially-driven. Because of the inherent plot-based nature of social work, the practices related to it can be analysed as stories (see Dominelli 2005, 234), given, of course, that they are signifying and told by someone. The research of the practices is concentrating on impressions, perceptions, judgements, accounts, documents etc. All these multifarious elements can be scrutinized as textual corpora, but not whatever textual material. In semiotic analysis, the material studied is characterised as verbal or textual and loaded with meanings. We present a contribution of research methodology, semiotic analysis, which has to our mind at least implicitly references to the social work practices. Our examples of semiotic interpretation have been picked up from our dissertations (Laine 2005; Saurama 2002). The data are official documents from the archives of a child welfare agency and transcriptions of the interviews of shelter employees. These data can be defined as stories told by the social workers of what they have seen and felt. The official documents present only fragmentations and they are often written in passive form. (Saurama 2002, 70.) The interviews carried out in the shelters can be described as stories where the narrators are more familiar and known. The material is characterised by the interaction between the interviewer and interviewee. The levels of the story and the telling of the story become apparent when interviews or documents are examined with the use of semiotic tools. The roots of semiotic interpretation can be found in three different branches; the American pragmatism, Saussurean linguistics in Paris and the so called formalism in Moscow and Tartu; however in this paper we are engaged with the so called Parisian School of semiology which prominent figure was A. J. Greimas. The Finnish sociologists Pekka Sulkunen and Jukka Törrönen (1997a; 1997b) have further developed the ideas of Greimas in their studies on socio-semiotics, and we lean on their ideas. In semiotics social reality is conceived as a relationship between subjects, observations, and interpretations and it is seen mediated by natural language which is the most common sign system among human beings (Mounin 1985; de Saussure 2006; Sebeok 1986). Signification is an act of associating an abstract context (signified) to some physical instrument (signifier). These two elements together form the basic concept, the “sign”, which never constitutes any kind of meaning alone. The meaning will be comprised in a distinction process where signs are being related to other signs. In this chain of signs, the meaning becomes diverged from reality. (Greimas 1980, 28; Potter 1996, 70; de Saussure 2006, 46-48.) One interpretative tool is to think of speech as a surface under which deep structures – i.e. values and norms – exist (Greimas & Courtes 1982; Greimas 1987). To our mind semiotics is very much about playing with two different levels of text: the syntagmatic surface which is more or less faithful to the grammar, and the paradigmatic, semantic structure of values and norms hidden in the deeper meanings of interpretations. Semiotic analysis deals precisely with the level of meaning which exists under the surface, but the only way to reach those meanings is through the textual level, the written or spoken text. That is why the tools are needed. In our studies, we have used the semiotic square and the actant analysis. The former is based on the distinctions and the categorisations of meanings, and the latter on opening the plotting of narratives in order to reach the value structures.

Meta-Analysis of Long-Term Land Management Effect on Soil Organic Carbon (SOC) in Ethiopia

The role of Soil Organic Carbon (SOC) in mitigating climate change, indicating soil quality and ecosystem function has created research interested to know the nature of SOC at landscape level. The objective of this study was to examine variation and distribution of SOC in a long-term land management at a watershed and plot level. This study was based on meta-analysis of three case studies and 128 surface soil samples from Ethiopia. Three sites (Gununo, Anjeni and Maybar) were compared after considering two Land Management Categories (LMC) and three types of land uses (LUT) in quasi-experimental design. Shapiro-Wilk tests showed non-normal distribution (p = 0.002, a = 0.05) of the data. SOC median value showed the effect of long-term land management with values of 2.29 and 2.38 g kg-1 for less and better-managed watersheds, respectively. SOC values were 1.7, 2.8 and 2.6 g kg-1 for Crop (CLU), Grass (GLU) and Forest Land Use (FLU), respectively. The rank order for SOC variability was FLU>GLU>CLU. Mann-Whitney U and Kruskal-Wallis test showed a significant difference in the medians and distribution of SOC among the LUT, between soil profiles (p<0.05, confidence interval 95%, a = 0.05) while it is not significant (p>0.05) for LMC. The mean and sum rank of Mann Whitney U and Kruskal Wallis test also showed the difference at watershed and plot level. Using SOC as a predictor, cross-validated correct classification with discriminant analysis showed 46 and 49% for LUT and LMC, respectively. The study showed how to categorize landscapes using SOC with respect to land management for decision-makers.

Analysis of spatial microbial properties from experimental plots of the Jena experiment (September 2010)

The study was carried out on the main plots (Main Experiment) of a large grassland biodiversity experiment, the Jena Experiment. In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. This data set consists of standard deviation (SD), mean and stability (stab) of soil microbial basal respiration (µl O2/h/g dry soil) and microbial biomass carbon (µg C/g dry soil). Data were derived by taking soil samples and measuring basal and substrate-induced microbial respiration with an oxygen-consumption apparatus. Samples for calculating the spatial stability of soil microbial properties were taken on the 20th of September in 2010. Oxygen consumption of soil microorganisms in fresh soil equivalent to 3.5 g dry weight was measured at 22°C over a period of 24 h. Basal respiration (µlO2/g dry soil/h) was calculated as mean of the oxygen consumption rates of hours 14 to 24 after the start of measurements. Substrate- induced respiration was determined by adding D-glucose to saturate catabolic enzymes of microorganisms according to preliminary studies (4 mg g-1 dry soil solved in 400 µl deionized water). Maximum initial respiratory response (µl O2/g dry soil/ h) was calculated as mean of the lowest three oxygen consumption values within the first 10 h after glucose addition. Microbial biomass carbon (µg C/g dry soil) was calculated as 38 × Maximum initial respiratory response according to prelimiray studies.

Analysis of temporal microbial properties from experimental plots of the Jena experiment (2003-2014)

The study was carried out on the main plots (Main Experiment) of a large grassland biodiversity experiment, the Jena Experiment. In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. This data set consists of standard deviation (SD), mean and stability (stab) of soil microbial basal respiration (µl O2/h/g dry soil) and microbial biomass carbon (µg C/g dry soil). Data were derived by taking soil samples and measuring basal and substrate-induced microbial respiration with an oxygen-consumption apparatus. Samples for calculating the temporal stability were taken every year in May/June from 2003 to 2014, except in 2005. Oxygen consumption of soil microorganisms in fresh soil equivalent to 3.5 g dry weight was measured at 22°C over a period of 24 h. Basal respiration (µlO2/g dry soil/h) was calculated as mean of the oxygen consumption rates of hours 14 to 24 after the start of measurements. Substrate- induced respiration was determined by adding D-glucose to saturate catabolic enzymes of microorganisms according to preliminary studies (4 mg g-1 dry soil solved in 400 µl deionized water). Maximum initial respiratory response (µl O2/g dry soil/h) was calculated as mean of the lowest three oxygen consumption values within the first 10 h after glucose addition. Microbial biomass carbon (µg C/g dry soil) was calculated as 38 × Maximum initial respiratory response according to prelimiray studies.

Nitrous oxide emissions from European agriculture - an analysis of variability and drivers of emissions from field experiments

Nitrous oxide emissions from a network of agricultural experiments in Europe were used to explore the relative importance of site and management controls of emissions. At each site, a selection of management interventions were compared within replicated experimental designs in plot-based experiments. Arable experiments were conducted at Beano in Italy, El Encin in Spain, Foulum in Denmark, Logarden in Sweden, Maulde in Belgium CE1, Paulinenaue in Germany, and Tulloch in the UK. Grassland experiments were conducted at Crichton, Nafferton and Peaknaze in the UK, Godollo in Hungary, Rzecin in Poland, Zarnekow in Germany and Theix in France. Nitrous oxide emissions were measured at each site over a period of at least two years using static chambers. Emissions varied widely between sites and as a result of manipulation treatments. Average site emissions (throughout the study period) varied between 0.04 and 21.21 kg N2O-N ha−1yr−1, with the largest fluxes and variability associated with the grassland sites. Total nitrogen addition was found to be the single most important deter- minant of emissions, accounting for 15 % of the variance (using linear regression) in the data from the arable sites (p<0.0001), and 77 % in the grassland sites. The annual emissions from arable sites were significantly greater than those that would be predicted by IPCC default emission fac- tors. Variability of N2O emissions within sites that occurred as a result of manipulation treatments was greater than that resulting from site-to-site and year-to-year variation, highlighting the importance of management interventions in contributing to greenhouse gas mitigation

From snapshot to movie: φ analysis of protein folding transition states taken one step further

Kinetic anomalies in protein folding can result from changes of the kinetic ground states (D, I, and N), changes of the protein folding transition state, or both. The 102-residue protein U1A has a symmetrically curved chevron plot which seems to result mainly from changes of the transition state. At low concentrations of denaturant the transition state occurs early in the folding reaction, whereas at high denaturant concentration it moves close to the native structure. In this study we use this movement to follow continuously the formation and growth of U1A's folding nucleus by φ analysis. Although U1A's transition state structure is generally delocalized and displays a typical nucleation–condensation pattern, we can still resolve a sequence of folding events. However, these events are sufficiently coupled to start almost simultaneously throughout the transition state structure.

Comparative analysis of the gene-dense ACHE/TFR2 region on human chromosome 7q22 with the orthologous region on mouse chromosome 5

Chromosome 7q22 has been the focus of many cytogenetic and molecular studies aimed at delineating regions commonly deleted in myeloid leukemias and myelodysplastic syndromes. We have compared a gene-dense, GC-rich sub-region of 7q22 with the orthologous region on mouse chromosome 5. A physical map of 640 kb of genomic DNA from mouse chromosome 5 was derived from a series of overlapping bacterial artificial chromosomes. A 296 kb segment from the physical map, spanning Ache to Tfr2, was compared with 267 kb of human sequence. We identified a conserved linkage of 12 genes including an open reading frame flanked by Ache and Asr2, a novel cation-chloride cotransporter interacting protein Cip1, Ephb4, Zan and Perq1. While some of these genes have been previously described, in each case we present new data derived from our comparative sequence analysis. Adjacent unfinished sequence data from the mouse contains an orthologous block of 10 additional genes including three novel cDNA sequences that we subsequently mapped to human 7q22. Methods for displaying comparative genomic information, including unfinished sequence data, are becoming increasingly important. We supplement our printed comparative analysis with a new, Web-based program called Laj (local alignments with java). Laj provides interactive access to archived pairwise sequence alignments via the WWW. It displays synchronized views of a dot-plot, a percent identity plot, a nucleotide-level local alignment and a variety of relevant annotations. Our mouse–human comparison can be viewed at http://web.uvic.ca/~bioweb/laj.html. Laj is available at http://bio.cse.psu.edu/, along with online documentation and additional examples of annotated genomic regions.

A Spatial Analysis of Agricultural Land Prices in Bavaria. Factor Markets Working Document No. 50, June 2013

This paper empirically analyses a dataset of more than 7,300 agricultural land sales transactions from 2001 and 2007 to identify the factors influencing agricultural land prices in Bavaria. We use a general spatial model, which combines a spatial lag and a spatial error model, and in addition account for endogeneity introduced by the spatially lagged dependent variable as well as other explanatory variables. Our findings confirm the strong influence of agricultural factors such as land productivity, of variables describing the regional land market structure, and of non-agricultural factors such as urban pressure on agricultural land prices. Moreover, the involvement of public authorities as a seller or buyer increases sales prices in Bavaria. We find a significant capitalisation of government support payments into agricultural land, where a decrease of direct payments by 1% would decrease land prices in 2007 and 2001 by 0.27% and 0.06%, respectively. In addition, we confirm strong spatial relationships in our dataset. Neglecting this leads to biased estimates, especially if aggregated data is used. We find that the price of a specific plot increases by 0.24% when sales prices in surrounding areas increase by 1%.

Comparative Analysis of Structural and Morphological Properties of Large-Pore Periodic Mesoporous Organosilicas and Pure Silicas

A systematic study on the structural properties and external morphologies of large-pore mesoporous organosilicas synthesized using triblock copolymer EO20PO70EO20 as a template under low-acid conditions was carried out. By employing the characterization techniques of SAXS, FE-SEM, and physical adsorption of N-2 in combination with alpha(s)-plot method, the structural properties and external morphologies of large-pore mesoporous organosilicas were critically examined and compared with that of their pure-silica counterparts synthesized under similar conditions. It has been observed that unlike mesoporous pure silicas, the structural and morphological properties of mesoporous organosilicas are highly acid-sensitive. High-quality mesoporous organosilicas can only be obtained from synthesis gels with the molar ratios of HCl/H2O between 7.08 x 10(-4) and 6.33 x 10(-3), whereas mesoporous pure silicas with well-ordered structure can be obtained in a wider range of acid concentration. Simply by adjusting the HCl/H2O molar ratios, the micro-, meso-, and macroporosities of the organosilica materials can be finely tuned without obvious effect on their structural order. Such a behavior is closely related to their acid-controlled morphological evolution: from necklacelike fibers to cobweb-supported pearl-like particles and to nanosized particulates.

A contour plot approach that uses data accumulated during routine monitoring to obtain insights into lagoon behaviour

Regular monitoring of wastewater characteristics is undertaken on most wastewater treatment plants. The data acquired during this process are usually filed and forgotten. However, systematic analysis of these data can provide useful insights into plant behaviour. Conventional graphical techniques are inadequate to give a good overall picture of how wastewater characteristics vary, with time and along the lagoon system. An approach based on the use of contour plots was devised that largely overcomes this problem. Superimposition of contour plots for different parameters can be used to gain a qualitative understanding of the nature and strength of relationships between the parameters. This is illustrated in an analysis of monitoring data for lagoon 115 East at the Western Treatment Plant, near Melbourne, Australia. In this illustrative analysis, relationships between ammonia removal rates and parameters such as chlorophyll a level and temperature are explored using a contour plot superimposition approach. It is concluded that this approach can help improve our understanding, not only of lagoon systems, but of other wastewater treatment systems as well.

Quantifying the pathology of neurodegenerative disorders:Quantitative measurements, sampling strategies and data analysis

The use of quantitative methods has become increasingly important in the study of neurodegenerative disease. Disorders such as Alzheimer's disease (AD) are characterized by the formation of discrete, microscopic, pathological lesions which play an important role in pathological diagnosis. This article reviews the advantages and limitations of the different methods of quantifying the abundance of pathological lesions in histological sections, including estimates of density, frequency, coverage, and the use of semiquantitative scores. The major sampling methods by which these quantitative measures can be obtained from histological sections, including plot or quadrat sampling, transect sampling, and point-quarter sampling, are also described. In addition, the data analysis methods commonly used to analyse quantitative data in neuropathology, including analyses of variance (ANOVA) and principal components analysis (PCA), are discussed. These methods are illustrated with reference to particular problems in the pathological diagnosis of AD and dementia with Lewy bodies (DLB).

The application of analysis of variance (ANOVA) to different experimental designs in optometry

Analysis of variance (ANOVA) is the most efficient method available for the analysis of experimental data. Analysis of variance is a method of considerable complexity and subtlety, with many different variations, each of which applies in a particular experimental context. Hence, it is possible to apply the wrong type of ANOVA to data and, therefore, to draw an erroneous conclusion from an experiment. This article reviews the types of ANOVA most likely to arise in clinical experiments in optometry including the one-way ANOVA ('fixed' and 'random effect' models), two-way ANOVA in randomised blocks, three-way ANOVA, and factorial experimental designs (including the varieties known as 'split-plot' and 'repeated measures'). For each ANOVA, the appropriate experimental design is described, a statistical model is formulated, and the advantages and limitations of each type of design discussed. In addition, the problems of non-conformity to the statistical model and determination of the number of replications are considered. © 2002 The College of Optometrists.

Analysis of spatial patterns in histological sections of brain tissue using a method based on regression

A method of determining the spatial pattern of any histological feature in sections of brain tissue which can be measured quantitatively is described and compared with a previously described method. A measurement of a histological feature such as density, area, amount or load is obtained for a series of contiguous sample fields. The regression coefficient (β) is calculated from the measurements taken in pairs, first in pairs of adjacent samples and then in pairs of samples taken at increasing degrees of separation between them, i.e. separated by 2, 3, 4,..., n units. A plot of β versus the degree of separation between the pairs of sample fields reveals whether the histological feature is distributed randomly, uniformly or in clusters. If the feature is clustered, the analysis determines whether the clusters are randomly or regularly distributed, the mean size of the clusters and the spacing of the clusters. The method is simple to apply and interpret and is illustrated using simulated data and studies of the spatial patterns of blood vessels in the cerebral cortex of normal brain, the degree of vacuolation of the cortex in patients with Creutzfeldt-Jacob disease (CJD) and the characteristic lesions present in Alzheimer's disease (AD). Copyright (C) 2000 Elsevier Science B.V.

Analysis of spatial patterns in histological sections of brain tissue

A method is described which enables the spatial pattern of discrete objects in histological sections of brain tissue to be determined. The method can be applied to cell bodies, sections of blood vessels or the characteristic lesions which develop in the brain of patients with neurodegenerative disorders. The density of the histological feature under study is measured in a series of contiguous sample fields arranged in a grid or transect. Data from adjacent sample fields are added together to provide density data for larger field sizes. A plot of the variance/mean ratio (V/M) of the data versus field size reveals whether the objects are distributed randomly, uniformly or in clusters. If the objects are clustered, the analysis determines whether the clusters are randomly or regularly distributed and the mean size of the clusters. In addition, if two different histological features are clustered, the analysis can determine whether their clusters are in phase, out of phase or unrelated to each other. To illustrate the method, the spatial patterns of senile plaques and neurofibrillary tangles were studied in histological sections of brain tissue from patients with Alzheimer's disease.