‘Dying Irish’: eulogising the Irish in Scotland in Glasgow Observer obituaries

The Glasgow Observer newspaper, founded in 1885 by and for the Irish community in Scotland regularly published both lengthy and brief funereal and elegiac obituaries of the Irish in Scotland in the nineteenth and early twentieth centuries. They marshal an impressive, emotive and oftentimes contradictory body of evidence and anecdote of immigrant lives of the kind utilised, and as often passed over, by historians of the Irish in Britain. They contain, however, a unique perspective on the march of a migrant people bespoke of their experiences and, perhaps more importantly, the perception of their experiences in passage, in the host society and ultimately in death. Moreover, the changing sense of Victorian sensibilities over the solemnity, purpose and ritual of death into the Edwardian era finds a moot reflection in the key staples of Irish immigrant obsequies with their stress on thrift, endeavour, piety, charity and gratitude. This article explores Glasgow Observer obituaries from the 1880s to the 1920s to see what they say about the immigrants, their lives, work and culture, the Scots, migration itself, the wider relations between Britain and Ireland, and the place where Irish and British attitudes to death meet in this period. It does so by drawing upon recent sociological perspectives on obituaries and their relationship with the formation and articulation of collective memory

Kinetic parameters for nutrient enhanced crude oil biodegradation in intertidal marine sediments

Availability of inorganic nutrients, particularly nitrogen and phosphorous, is often a primary control on crude oil hydrocarbon degradation in marine systems. Many studies have empirically determined optimum levels of inorganic N and P for stimulation of hydrocarbon degradation. Nevertheless, there is a paucity of information on fundamental kinetic parameters for nutrient enhanced crude oil biodegradation that can be used to model the fate of crude oil in bioremediation programmes that use inorganic nutrient addition to stimulate oil biodegradation. Here we report fundamental kinetic parameters (Ks and qmax) for nitrate-and phosphate-stimulated crude oil biodegradation under nutrient limited conditions and with respect to crude oil, under conditions where N and P are not limiting. In the marine sediments studied, crude oil degradation was limited by both N and P availability. In sediments treated with 12.5 mg/g of oil but with no addition of N and P, hydrocarbon degradation rates, assessed on the basis of CO2 production, were 1.10 ± 0.03 μmol CO2/g wet sediment/day which were comparable to rates of CO2 production in sediments to which no oil was added (1.05 ± 0.27 μmol CO2/g wet sediment/day). When inorganic nitrogen was added alone maximum rates of CO2 production measured were 4.25 ± 0.91 μmol CO2/g wet sediment/day. However, when the same levels of inorganic nitrogen were added in the presence of 0.5% P w/w of oil (1.6 μmol P/g wet sediment) maximum rates of measured CO2 production increased more than four-fold to 18.40 ± 1.04 μmol CO2/g wet sediment/day. Ks and qmax estimates for inorganic N (in the form of sodium nitrate) when P was not limiting were 1.99 ± 0.86 μmol/g wet sediment and 16.16 ± 1.28 μmol CO2/g wet sediment/day respectively. The corresponding values for P were 63 ± 95 nmol/g wet sediment and 12.05 ± 1.31 μmol CO2/g wet sediment/day. The qmax values with respect to N and P were not significantly different (P < 0.05). When N and P were not limiting Ks and qmax for crude oil were 4.52 ± 1.51 mg oil/g wet sediment and 16.89 ± 1.25 μmol CO2/g wet sediment/day. At concentrations of inorganic N above 45 μmol/g wet sediment inhibition of CO2 production from hydrocarbon degradation was evident. Analysis of bacterial 16S rRNA genes indicated that Alcanivorax spp. were selected in these marine sediments with increasing inorganic nutrient concentration, whereas Cycloclasticus spp. were more prevalent at lower inorganic nutrient concentrations. These data suggest that simple empirical estimates of the proportion of nutrients added relative to crude oil concentrations may not be sufficient to guarantee successful crude oil bioremediation in oxic beach sediments. The data we present also help define the maximum rates and hence timescales required for bioremediation of beach sediments

Skin texture and colour predict perceived health in Asian faces

Facial skin texture and colour play an important role in observers' judgments of apparent health and have been linked to aspects of physiological health, including fitness, immunity and fertility. However, most studies have focused on Caucasian populations. Here, we report two studies that investigate the contribution of skin texture and colour to the apparent health ofMalaysian Chinese faces. In Study 1, homogenous skin texture, as measured by wavelet analysis, was found to positively predict ratings of apparent health of Asian faces. In study 2, homogenous skin texture and increased skin yellowness positively predicted rated health of Malaysian Chinese faces. This finding suggests that skin condition serves as an important cue for subjective judgements of health in Malaysian Chinese faces

Simulation-Based Finite-Sample Tests for Heteroskedasticity and ARCH Effects

A wide range of tests for heteroskedasticity have been proposed in the econometric and statistics literature. Although a few exact homoskedasticity tests are available, the commonly employed procedures are quite generally based on asymptotic approximations which may not provide good size control in finite samples. There has been a number of recent studies that seek to improve the reliability of common heteroskedasticity tests using Edgeworth, Bartlett, jackknife and bootstrap methods. Yet the latter remain approximate. In this paper, we describe a solution to the problem of controlling the size of homoskedasticity tests in linear regression contexts. We study procedures based on the standard test statistics [e.g., the Goldfeld-Quandt, Glejser, Bartlett, Cochran, Hartley, Breusch-Pagan-Godfrey, White and Szroeter criteria] as well as tests for autoregressive conditional heteroskedasticity (ARCH-type models). We also suggest several extensions of the existing procedures (sup-type of combined test statistics) to allow for unknown breakpoints in the error variance. We exploit the technique of Monte Carlo tests to obtain provably exact p-values, for both the standard and the new tests suggested. We show that the MC test procedure conveniently solves the intractable null distribution problem, in particular those raised by the sup-type and combined test statistics as well as (when relevant) unidentified nuisance parameter problems under the null hypothesis. The method proposed works in exactly the same way with both Gaussian and non-Gaussian disturbance distributions [such as heavy-tailed or stable distributions]. The performance of the procedures is examined by simulation. The Monte Carlo experiments conducted focus on : (1) ARCH, GARCH, and ARCH-in-mean alternatives; (2) the case where the variance increases monotonically with : (i) one exogenous variable, and (ii) the mean of the dependent variable; (3) grouped heteroskedasticity; (4) breaks in variance at unknown points. We find that the proposed tests achieve perfect size control and have good power.Un grand éventail de tests d'hétéroscédasticité a été proposé en économétrie et en statistique. Bien qu'il existe quelques tests d'homoscédasticité exacts, les procédures couramment utilisées sont généralement fondées sur des approximations asymptotiques qui ne procurent pas un bon contrôle du niveau dans les échantillons finis. Plusieurs études récentes ont tenté d'améliorer la fiabilité des tests d'hétéroscédasticité usuels, sur base de méthodes de type Edgeworth, Bartlett, jackknife et bootstrap. Cependant, ces méthodes demeurent approximatives. Dans cet article, nous décrivons une solution au problème de contrôle du niveau des tests d'homoscédasticité dans les modèles de régression linéaire. Nous étudions des procédures basées sur les critères de test standard [e.g., les critères de Goldfeld-Quandt, Glejser, Bartlett, Cochran, Hartley, Breusch-Pagan-Godfrey, White et Szroeter], de même que des tests pour l'hétéroscédasticité autorégressive conditionnelle (les modèles de type ARCH). Nous suggérons plusieurs extensions des procédures usuelles (les statistiques de type-sup ou combinées) pour tenir compte de points de ruptures inconnus dans la variance des erreurs. Nous appliquons la technique des tests de Monte Carlo (MC) de façon à obtenir des seuils de signification marginaux (les valeurs-p) exacts pour les tests usuels et les nouveaux tests que nous proposons. Nous démontrons que la procédure de MC permet de résoudre les problèmes des distributions compliquées sous l'hypothèse nulle, en particulier ceux associés aux statistiques de type-sup, aux statistiques combinées et aux paramètres de nuisance non-identifiés sous l'hypothèse nulle. La méthode proposée fonctionne exactement de la même manière en présence de lois Gaussiennes et non Gaussiennes [comme par exemple les lois aux queues épaisses ou les lois stables]. Nous évaluons la performance des procédures proposées par simulation. Les expériences de Monte Carlo que nous effectuons portent sur : (1) les alternatives de type ARCH, GARCH et ARCH-en-moyenne; (2) le cas où la variance augmente de manière monotone en fonction : (i) d'une variable exogène, et (ii) de la moyenne de la variable dépendante; (3) l'hétéroscédasticité groupée; (4) les ruptures en variance à des points inconnus. Nos résultats montrent que les tests proposés permettent de contrôler parfaitement le niveau et ont une bonne puissance

The impact of endemic and epidemic malaria on the risk of stillbirth in two areas of Tanzania with different malaria transmission patterns

BACKGROUND: The impact of malaria on the risk of stillbirth is still under debate. The aim of the present analysis was to determine comparative changes in stillbirth prevalence between two areas of Tanzania with different malaria transmission patterns in order to estimate the malaria attributable component. METHODS: A retrospective analysis was completed of stillbirth differences between primigravidae and multigravidae in relation to malaria cases and transmission patterns for two different areas of Tanzania with a focus on the effects of the El Niño southern climatic oscillation (ENSO). One area, Kagera, experiences outbreaks of malaria, and the other area, Morogoro, is holoendemic. Delivery and malaria data were collected over a six year period from records of the two district hospitals in these locations. RESULTS: There was a significantly higher prevalence of low birthweight in primigravidae compared to multigravidae for both data sets. Low birthweight and stillbirth prevalence (17.5% and 4.8%) were significantly higher in Kilosa compared to Ndolage (11.9% and 2.4%). There was a significant difference in stillbirth prevalence between Ndolage and Kilosa between malaria seasons (2.4% and 5.6% respectively, p < 0.001) and during malaria seasons (1.9% and 5.9% respectively, p < 0.001). During ENSO there was no difference (4.1% and 4.9%, respectively). There was a significant difference in low birthweight prevalence between Ndolage and Kilosa between malaria seasons (14.4% and 23.0% respectively, p < 0.001) and in relation to malaria seasons (13.9% and 25.2% respectively, p < 0.001). During ENSO there was no difference (22.2% and 19.8%, respectively). Increased low birthweight risk occurred approximately five months following peak malaria prevalence, but stillbirth risk increased at the time of malaria peaks. CONCLUSION: Malaria exposure during pregnancy has a delayed effect on birthweight outcomes, but a more acute effect on stillbirth risk

A review of laser engineered net shaping (LENS) build and process parameters of metallic parts

Purpose: This paper aims to present a comprehensive review of the laser engineered net shaping (LENS) process in an attempt to provide the reader with a deep understanding of the controllable and fixed build parameters of metallic parts. The authors discuss the effect and interplay between process parameters, including: laser power, scan speed and powder feed rate. Further, the authors show the interplay between process parameters is pivotal in achieving the desired microstructure, macrostructure, geometrical accuracy and mechanical properties. Design/methodology/approach: In this manuscript, the authors review current research examining the process inputs and their influences on the final product when manufacturing with the LENS process. The authors also discuss how these parameters relate to important build aspects such as melt-pool dimensions, the volume of porosity and geometry accuracy. Findings: The authors conclude that studies have greatly enriched the understanding of the LENS build process, however, much studies remains to be done. Importantly, the authors reveal that to date there are a number of detailed theoretical models that predict the end properties of deposition, however, much more study is necessary to allow for reasonable prediction of the build process for standard industrial parts, based on the synchronistic behavior of the input parameters. Originality/value: This paper intends to raise questions about the possible research areas that could potentially promote the effectiveness of this LENS technology.</div

Simulation-Based Finite-Sample Tests for Heteroskedasticity and ARCH Effects

A wide range of tests for heteroskedasticity have been proposed in the econometric and statistics literatures. Although a few exact homoskedasticity tests are available, the commonly employed procedures are quite generally based on asymptotic approximations which may not provide good size control in finite samples. There has been a number of recent studies that seek to improve the reliability of common heteroskedasticity tests using Edgeworth, Bartlett, jackknife and bootstrap methods. Yet the latter remain approximate. In this paper, we describe a solution to the problem of controlling the size of homoskedasticity tests in linear regression contexts. We study procedures based on the standard test statistics [e.g., the Goldfeld-Quandt, Glejser, Bartlett, Cochran, Hartley, Breusch-Pagan-Godfrey, White and Szroeter criteria] as well as tests for autoregressive conditional heteroskedasticity (ARCH-type models). We also suggest several extensions of the existing procedures (sup-type or combined test statistics) to allow for unknown breakpoints in the error variance. We exploit the technique of Monte Carlo tests to obtain provably exact p-values, for both the standard and the new tests suggested. We show that the MC test procedure conveniently solves the intractable null distribution problem, in particular those raised by the sup-type and combined test statistics as well as (when relevant) unidentified nuisance parameter problems under the null hypothesis. The method proposed works in exactly the same way with both Gaussian and non-Gaussian disturbance distributions [such as heavy-tailed or stable distributions]. The performance of the procedures is examined by simulation. The Monte Carlo experiments conducted focus on: (1) ARCH, GARCH and ARCH-in-mean alternatives; (2) the case where the variance increases monotonically with: (i) one exogenous variable, and (ii) the mean of the dependent variable; (3) grouped heteroskedasticity; (4) breaks in variance at unknown points. We find that the proposed tests achieve perfect size control and have good power. Un grand éventail de tests d'hétéroskédasticité a été proposé en économétrie et en statistique. Bien qu'il existe quelques tests d'homoskédasticité exacts, les procédures couramment utilisées sont généralement fondées sur des approximations asymptotiques qui ne procurent pas un bon contrôle du niveau dans les échantillons finis. Plusieurs études récentes ont tenté d'améliorer la fiabilité des tests d'hétéroskédasticité usuels, sur base de méthodes de type Edgeworth, Bartlett, jackknife et bootstrap. Cependant, ces méthodes demeurent approximatives. Dans cet article, nous décrivons une solution au problème de contrôle du niveau des tests d'homoskédasticité dans les modèles de régression linéaire. Nous étudions des procédures basées sur les critères de test standards [e.g., les critères de Goldfeld-Quandt, Glejser, Bartlett, Cochran, Hartley, Breusch-Pagan-Godfrey, White et Szroeter], de même que des tests pour l'hétéroskédasticité autorégressive conditionnelle (les modèles de type ARCH). Nous suggérons plusieurs extensions des procédures usuelles (les statistiques de type-sup ou combinées) pour tenir compte de points de ruptures inconnus dans la variance des erreurs. Nous appliquons la technique des tests de Monte Carlo (MC) de façon à obtenir des seuils de signification marginaux (les valeurs-p) exacts, pour les test usuels et les nouveaux tests que nous proposons. Nous démontrons que la procédure de MC permet de résoudre les problèmes des distributions compliquées sous l'hypothèse nulle, en particulier ceux associés aux statistiques de type-sup, aux statistiques combinées et aux paramètres de nuisance non-identifiés sous l'hypothèse nulle. La méthode proposée fonctionne exactement de la même manière en présence de lois Gaussiennes et non-Gaussiennes [comme par exemple les lois aux queues épaisses ou les lois stables]. Nous évaluons la performance des procédures proposées par simulation. Les expériences de Monte Carlo que nous effectuons portent sur: (1) les alternatives de type ARCH, GARCH and ARCH-en-moyenne; (2) le cas où la variance augmente de manière monotone en fonction: (i) d'une variable exogène, et (ii) de la moyenne de la variable dépendante; (3) l'hétéroskédasticité groupée; (4) les ruptures en variance à des points inconnus. Nos résultats montrent que les tests proposés permettent de contrôler parfaitement le niveau et ont une bonne puissance.Heteroskedasticity, homoskedasticity, linear regression, Monte Carlo test, exact test, finite-sample test, specification test, ARCH, GARCH, ARCH in mean, stable distribution, structural stability, hétéroskédasticité, homoskédasticité, régression linéaire, test de Monte Carlo, test exact, test valide en échantillon fini, test de spécification, ARCH, GARCH, ARCH-en-moyenne, distribution stable, stabilité structurelle