The healthy immigrant effect: Patterns and evidence from four countries

The existence of a healthy immigrant effect—where immigrants are on average healthier than the native born—is a widely cited phenomenon across a multitude of literatures including epidemiology and the social sciences. There are many competing explanations. The goals of this paper are twofold: first, to provide further evidence on the presence of the healthy immigrant effect across source and destination country using a set of consistently defined measures of health; and second, to evaluate the role of selectivity as a potential explanation for the existence of the phenomenon. Utilizing data from four major immigrant recipient countries, USA, Canada, UK, and Australia allows us to compare the health of migrants from each with the respective native born who choose not to migrate. This represents a much more appropriate counterfactual than the native born of the immigrant recipient country and yields new insights into the importance of observable selection effects. The analysis finds strong support for the healthy immigrant effect across all four destination countries and that selectivity plays an important role in the observed better health of migrants vis a vis those who stay behind in their country of origin.

Complementary surface-enhanced resonance raman spectroscopic biodetection of mixed protein solutions by chitosan- and silica-coated plasmon-tuned silver nanoparticles

Silver nanoparticles with identical plasmonic properties but different surface functionalities are synthesized and tested as chemically selective surface-enhanced resonance Raman (SERR) amplifiers in a two-component protein solution. The surface plasmon resonances of the particles are tuned to 413 nm to match the molecular resonance of protein heme cofactors. Biocompatible functionalization of the nanoparticles with a thin film of chitosan yields selective SERR enhancement of the anionic protein cytochrome b5, whereas functionalization with SiO2 amplifies only the spectra of the cationic protein cytochrome c. As a result, subsequent addition of the two differently functionalized particles yields complementary information on the same mixed protein sample solution. Finally, the applicability of chitosan-coated Ag nanoparticles for protein separation was tested by in situ resonance Raman spectroscopy.

Alliances in the shadow of conflict

Victorious alliances often fight about the spoils of war. This article presents an experiment on the determinants of whether alliances break up and fight internally after having defeated a joint enemy. First, if peaceful sharing yields an asymmetric rent distribution, this increases the likelihood of fighting. In turn, anticipation of the higher likelihood of internal fight reduces the alliance’s ability to succeed against the outside enemy. Second, the option to make nonbinding nonaggression declarations between alliance members does not make peaceful settlement within the alliance more likely. Third, higher differences in the alliance players’ contributions to alliance effort lead to more internal conflict and more intense fighting.

Evaluation of features for leaf classification in challenging conditions

Fine-grained leaf classification has concentrated on the use of traditional shape and statistical features to classify ideal images. In this paper we evaluate the effectiveness of traditional hand-crafted features and propose the use of deep convolutional neural network (ConvNet) features. We introduce a range of condition variations to explore the robustness of these features, including: translation, scaling, rotation, shading and occlusion. Evaluations on the Flavia dataset demonstrate that in ideal imaging conditions, combining traditional and ConvNet features yields state-of-theart performance with an average accuracy of 97:3%�0:6% compared to traditional features which obtain an average accuracy of 91:2%�1:6%. Further experiments show that this combined classification approach consistently outperforms the best set of traditional features by an average of 5:7% for all of the evaluated condition variations.

A reduction of diffusion in PVA Fricke hydrogels

A modification to the PVA-FX hydrogel whereby the chelating agent, xylenol orange, was partially bonded to the gelling agent, poly-vinyl alcohol, resulted in an 8% reduction in the post irradiation Fe3+ diffusion, adding approximately 1 hour to the useful timespan between irradiation and readout. This xylenol orange functionalised poly-vinyl alcohol hydrogel had an OD dose sensitivity of 0.014 Gy−1 and a diffusion rate of 0.133 mm2 h−1. As this partial bond yields only incremental improvement, it is proposed that more efficient methods of bonding xylenol orange to poly-vinyl alcohol be investigated to further reduce the diffusion in Fricke gels.

Facile dearomatisation of porphyrins using palladium-catalysed hydrazination: the 5,15-diiminoporphodimethenes and their redox products

The synthesis, electronic absorption and 1H NMR spectra of a suite of novel porphyrinoids derived from meso-bromoporphyrins by palladium-catalysed aminations using ethyl and tert-butylcarbazates are reported. Instead of the expected carbazate-substituted porphyrins, a facile oxidative dearomatisation of the porphyrin ring occurs in high yield, especially for the nickel(II) complexes, resulting in high yields of 5,15-diiminoporphodimethenes (DIPDs). The analogous zinc(II) and free base DIPDs were also characterised, the former by X-ray crystallography. The oxidation and reduction reactions of DIPDs and their precursor carbazate porphyrins were studied. Density Functional Theory (DFT) was used to calculate the optimised geometries and frontier molecular orbitals of DIPD Ni8c and bis(azocarboxylate) 19c, and Time Dependent DFT calculations allowed the prediction of electronic absorption spectra, whose characteristics corresponded well with those of the observed solution spectra. In the latter case, the calculated low-energy absorptions were unlike those of a typical porphyrin, due to the near-degeneracy of the highest filled frontier orbitals, and the wide energy separation between the unfilled orbitals. This feature was present in the observed spectrum.

Model-based analysis and optimization of bioreactor for hematopoietic stem cell cultivation

One of the problems to be solved in attaining the full potentials of hematopoietic stem cell (HSC) applications is the limited availability of the cells. Growing HSCs in a bioreactor offers an alternative solution to this problem. Besides, it also offers the advantages of eliminating labour intensive process as well as the possible contamination involved in the periodic nutrient replenishments in the traditional T-flask stem cell cultivation. In spite of this, the optimization of HSC cultivation in a bioreactor has been barely explored. This manuscript discusses the development of a mathematical model to describe the dynamics in nutrient distribution and cell concentration of an ex vivo HSC cultivation in a microchannel perfusion bioreactor. The model was further used to optimize the cultivation by proposing three alternative feeding strategies in order to prevent the occurrence of nutrient limitation in the bioreactor. The evaluation of these strategies, the periodic step change increase in the inlet oxygen concentration, the periodic step change increase in the media inflow, and the feedback control of media inflow, shows that these strategies can successfully improve the cell yield of the bioreactor. In general, the developed model is useful for the design and optimization of bioreactor operation.

Breaking the DNA-vaccine bottleneck

Monash University in Australia has developed a new approach towards DNA vaccine development that has the potential to cut the time it takes to produce a vaccine from up to nine months to four weeks or less. The university has designed and filed a patent on a commercially viable, single-stage technology for manufacturing DNA molecules. The technology was used to produce malaria and measles DNA vaccines, which were tested to be homogeneous supercoiled DNA, free from RNA and protein contaminations and meeting FDA regulatory standards for DNA vaccines. The technique is based on customized, smart, polymeric, monolithic adsorbents that can purify DNA very rapidly. The design criteria of solid-phase adsorbent include rapid adsorption and desorption kinetics, physical composition, and adequate selectivity , capacity and recovery. The new show technology significantly improved binding capacities, higher recovery, drastically reduced use of buffers and processing time, less clogging, and higher yields of DNA.

Development of a pilot-scale bacterial fermentation for plasmid-based biopharmaceutical production using a stoichiometric medium

The recognition of the potential efficacy of plasmid DNA (pDNA) molecules as vectors in the treatment and prevention of emerging diseases has birthed the confidence to combat global pandemics. This is due to the close-to-zero safety concern associated with pDNA vectors compared to viral vectors in cell transfection and targeting. Considerable attention has been paid to the potential of pDNA vectors but comparatively less thought has been given to the practical challenges in producing large quantities to meet current rising demands. A pilot-scale fermentation scheme was developed by employing a stoichiometrically-designed growth medium whose exceptional plasmid yield performance was attested in a shake flask environment for pUC19 and pEGFP-N1 transformed into E. coliDH5α and E. coliJM109, respectively. Batch fermentation of E. coliDH5α-pUC19 employing the stoichiometric medium displayed a maximum plasmid volumetric and specific yield of 62.6 mg/L and 17.1 mg/g (mg plasmid/g dry cell weight), respectively. Fed-batch fermentation of E. coliDH5α-pUC19 on a glycerol substrate demonstrated one of the highest ever reported pilot-scale plasmid specific yield of 48.98 mg/g and a volumetric yield of 0.53 g/L. The attainment of high plasmid specific yields constitutes a decrease in plasmid manufacturing cost and enhances the effectiveness of downstream processes by reducing the proportion of intracellular impurities. The effect of step-rise temperature induction was also considered to maximize ColE1-origin plasmid replication.

Affinity purification of plasmid DNA directly from crude bacterial cell lysates

We have shown previously that a sequence-specific DNA-binding protein based on the Lac repressor protein can isolate pre-purified DNA efficiently from simple buffer solution but our attempts to purify plasmids directly from crude starting materials were disappointing with unpractically low DNA yields. We have optimized tbe procedure and present a simple affinity methodology whereby plasmid DNA is purified directly by mixing two crude cell lysates, one cell lysate containing the plasmid and the other the protein affinity ligand, without the need for treatment by RNaseA. After IMAC chromatography, high purity supercoiled DNA is recovered in good yields of 100-150 μg plasmid per 200 mL shake flask culture. Moreover, the resulting DNA is free from linear or open-circular plasmid DNA, genomic DNA, RNA, and protein, to the limits of our detection. Furthermore, we show that lyophilized affinity ligand can be stored at room temperature and re-hydrated for use when required.

Growth medium selection and its economic impact on plasmid DNA production

Current developments in gene medicine and vaccination studies are utilizing plasmid DNA (pDNA) as the vector. For this reason, there has been an increasing trend towards larger and larger doses of pDNA utilized in human trials: from 100-1000 μg in 2002 to 500-5000 μg in 2005. The increasing demand of pDNA has created the need to revolutionalize current production levels under optimum economy. In this work, different standard media (LB, TB and SOC) for culturing recombinant Escherichia coli DH5α harbouring pUC19 were compared to a medium optimised for pDNA production. Lab scale fermentations using the standard media showed that the highest pDNA volumetric and specific yields were for TB (11.4 μg/ml and 6.3 μg/mg dry cell mass respectively) and the lowest was for LB (2.8 μg/ml and 3.3 μg/mg dry cell mass respectively). A fourth medium, PDMR, designed by modifying a stoichiometrically-formulated medium with an optimised carbon source concentration and carbon to nitrogen ratio displayed pDNA volumetric and specific yields of 23.8 μg/ml and 11.2 μg/mg dry cell mass respectively. However, it is the economic advantages of the optimised medium that makes it so attractive. Keeping all variables constant except medium and using LB as a base scenario (100 medium cost [MC] units/mg pDNA), the optimised PDMR medium yielded pDNA at a cost of only 27 MC units/mg pDNA. These results show that greater amounts of pDNA can be obtained more economically with minimal extra effort simply by using a medium optimised for pDNA production.

How Gordon Ramsay appeals to consumers : effects of self-concept clarity and celebrity meaning on celebrity endorsements

How do celebrities like Gordon Ramsay appeal to consumers? This article examines one explanation. We study how celebrities appeal to consumers in the context of celebrity chefs. We examine how a consumer's self-concept clarity (SCC) interacts with their perception of the meaning that a celebrity endorser possesses. An experiment comparing fictional ads endorsed by different celebrity chefs yields the surprising result that consumers with a clear sense of who they are (high-SCC consumers) are more influenced by an ad featuring a celebrity high in meaning (Ramsay), whereas low-SCC consumers are influenced to slightly higher levels by a celebrity with lower levels of celebrity meaning.

Supervised latent dirichlet allocation models for efficient activity representation

Local spatio-temporal features with a Bag-of-visual words model is a popular approach used in human action recognition. Bag-of-features methods suffer from several challenges such as extracting appropriate appearance and motion features from videos, converting extracted features appropriate for classification and designing a suitable classification framework. In this paper we address the problem of efficiently representing the extracted features for classification to improve the overall performance. We introduce two generative supervised topic models, maximum entropy discrimination LDA (MedLDA) and class- specific simplex LDA (css-LDA), to encode the raw features suitable for discriminative SVM based classification. Unsupervised LDA models disconnect topic discovery from the classification task, hence yield poor results compared to the baseline Bag-of-words framework. On the other hand supervised LDA techniques learn the topic structure by considering the class labels and improve the recognition accuracy significantly. MedLDA maximizes likelihood and within class margins using max-margin techniques and yields a sparse highly discriminative topic structure; while in css-LDA separate class specific topics are learned instead of common set of topics across the entire dataset. In our representation first topics are learned and then each video is represented as a topic proportion vector, i.e. it can be comparable to a histogram of topics. Finally SVM classification is done on the learned topic proportion vector. We demonstrate the efficiency of the above two representation techniques through the experiments carried out in two popular datasets. Experimental results demonstrate significantly improved performance compared to the baseline Bag-of-features framework which uses kmeans to construct histogram of words from the feature vectors.

Limitations of a laboratory scale model in predicting optimal pilot scale conditions for dilute acid pretreatment of sugarcane bagasse

Pilot and industrial scale dilute acid pretreatment data can be difficult to obtain due to the significant infrastructure investment required. Consequently, models of dilute acid pretreatment by necessity use laboratory scale data to determine kinetic parameters and make predictions about optimal pretreatment conditions at larger scales. In order for these recommendations to be meaningful, the ability of laboratory scale models to predict pilot and industrial scale yields must be investigated. A mathematical model of the dilute acid pretreatment of sugarcane bagasse has previously been developed by the authors. This model was able to successfully reproduce the experimental yields of xylose and short chain xylooligomers obtained at the laboratory scale. In this paper, the ability of the model to reproduce pilot scale yield and composition data is examined. It was found that in general the model over predicted the pilot scale reactor yields by a significant margin. Models that appear very promising at the laboratory scale may have limitations when predicting yields on a pilot or industrial scale. It is difficult to comment whether there are any consistent trends in optimal operating conditions between reactor scale and laboratory scale hydrolysis due to the limited reactor datasets available. Further investigation is needed to determine whether the model has some efficacy when the kinetic parameters are re-evaluated by parameter fitting to reactor scale data, however, this requires the compilation of larger datasets. Alternatively, laboratory scale mathematical models may have enhanced utility for predicting larger scale reactor performance if bulk mass transport and fluid flow considerations are incorporated into the fibre scale equations. This work reinforces the need for appropriate attention to be paid to pilot scale experimental development when moving from laboratory to pilot and industrial scales for new technologies.

Frequency independence of ultrasound transit time spectroscopy

Recent studies have shown that ultrasound transit time spectroscopy (UTTS) is an alternative method to describe ultrasound wave propagation through complex samples as an array of parallel sonic rays. This technique has the potential to characterize bone properties including volume fraction and may be implemented in clinical systems to predict osteoporotic fracture risk. In contrast to broadband ultrasound attenuation, which is highly frequency dependent, we hypothesise that UTTS is frequency independent. This study measured 1 MHz and 5 MHz broadband ultrasound signals through a set of acrylic step-wedge samples. Digital deconvolution of the signals through water and each sample was applied to derive a transit time spectrum. The resulting spectra at both 1 MHz and 5 MHz were compared to the predicted transit time values. Linear regression analysis yields agreement (R2) of 99.23% and 99.74% at 1 MHz and 5 MHz respectively indicating frequency independence of transit time spectra.