Initial design and physical characterization of a polymeric device for osmosis-driven delayed burst delivery of vaccines

Achieving the combination of delayed and immediate release of a vaccine from a delivery device without applying external triggers remains elusive in implementing single administration vaccination strategies. Here a means of vaccine delivery is presented, which exploits osmosis to trigger delayed burst release of an active compound. Poly(-caprolactone) capsules of 2 mm diameter were prepared by dip-coating, and their burst pressure and release characteristics were evaluated. Burst pressures (in bar) increased with wall thickness (t in mm) following Pburst = 131.t + 3.4 (R2 = 0.93). Upon immersion in PBS, glucose solution-filled capsules burst after 8.7 ± 2.9 days. Copolymers of hydrophobic  -caprolactone and hydrophilic polyethylene glycol were synthesized and their physico-chemical properties were assessed. With increasing hydrophilic content, the copolymer capsules showed increased water uptake rates and maximum weight increase, while the burst release was earlier: 5.6 ± 2.0 days and 1.9 ± 0.2 days for 5 and 10 wt% polyethylene glycol, respectively. The presented approach enables the reproducible preparation of capsules with high versatility in materials and properties, while these vaccine delivery vehicles can be prepared separately from, and independently of the active compound.

A new approach to the cloud-based heterogeneous MapReduce placement problem

Guaranteeing Quality of Service (QoS) with minimum computation cost is the most important objective of cloud-based MapReduce computations. Minimizing the total computation cost of cloud-based MapReduce computations is done through MapReduce placement optimization. MapReduce placement optimization approaches can be classified into two categories: homogeneous MapReduce placement optimization and heterogeneous MapReduce placement optimization. It is generally believed that heterogeneous MapReduce placement optimization is more effective than homogeneous MapReduce placement optimization in reducing the total running cost of cloud-based MapReduce computations. This paper proposes a new approach to the heterogeneous MapReduce placement optimization problem. In this new approach, the heterogeneous MapReduce placement optimization problem is transformed into a constrained combinatorial optimization problem and is solved by an innovative constructive algorithm. Experimental results show that the running cost of the cloud-based MapReduce computation platform using this new approach is 24:3%-44:0% lower than that using the most popular homogeneous MapReduce placement approach, and 2:0%-36:2% lower than that using the heterogeneous MapReduce placement approach not considering the spare resources from the existing MapReduce computations. The experimental results have also demonstrated the good scalability of this new approach.

Raman and infrared spectroscopic characterization of the arsenate-bearing mineral tangdanite– and in comparison with the discredited mineral clinotyrolite

The minerals clinotyrolite and fuxiaotuite are discredited in terms of the mineral tangdanite. The mixed anion mineral tangdanite Ca2Cu9(AsO4)4(SO4)0.5(OH)9 9H2O has been studied using a combination of Raman and infrared spectroscopy. Characteristic bands associated with arsenate, sulphate and hydroxyl units are identified. Broad bands in the OH stretching region are observed and are resolved into component bands. These bands are assigned to water and hydroxyl stretching vibrations. Two intense Raman bands at 837 and approximately 734 cm−1 are assigned to the ν1 (AsO4)3− symmetric stretching and ν3 (AsO4)3− antisymmetric stretching modes. Infrared bands at 1023 cm−1 are assigned to the (SO4)2− ν1 symmetric stretching mode, and infrared bands at 1052, 1110 and 1132 cm−1 assigned to (SO4)2− ν3 antisymmetric stretching modes, confirming the presence of the sulphate anion in the tangdanite structure. Raman bands at 593 and 628 cm−1 are attributed to the (SO4)2− ν4 bending modes. Low-intensity Raman bands found at 457 and 472 cm−1 are assigned to the (AsO4)3− ν2 bending modes. A comparison is made with the previously obtained spectral data on the discredited mineral clinotyrolite.

Infrared and Raman spectroscopic characterization of the carbonate bearing silicate mineral aerinite – Implications for the molecular structure

The mineral aerinite is an interesting mineral because it contains both silicate and carbonate units which is unusual. It is also a highly colored mineral being bright blue/purple. We have studied aerinite using a combination of techniques which included scanning electron microscopy, energy dispersive X-ray analysis, Raman and infrared spectroscopy. Raman bands at 1049 and 1072 cm−1 are assigned to the carbonate symmetric stretching mode. This observation supports the concept of the non-equivalence of the carbonate units in the structure of aerinite. Multiple infrared bands at 1354, 1390 and 1450 cm−1 supports this concept. Raman bands at 933 and 974 cm−1 are assigned to silicon–oxygen stretching vibrations. Multiple hydroxyl stretching and bending vibrations show that water is in different molecular environments in the aerinite structure.

Ageing Australian unions and the ‘youth problem’

Trade union membership, both in aggregate numbers and in density, has declined in the majority of advanced economies globally over recent decades (Blanchflower, 2007). In Australia, the decline in the 1990s was somewhat more precipitate than in most countries (Peetz, 1998). As discussed in Chapter 1, reasons for the decline are multifactorial, including a more hostile environment to unionism created by employers and the state, difficulties ·with workplace union organisation, and structural change in the economy (Bryson and Gomez, 2005; Bryson et a!., 2011; Ebbinghaus et al., 2011; Payne, 1989; Waddington and Kerr, 2002; Waddington and Whitson, 1997). Our purpose in this chapter is to look beyond aggregate Australian union density data, to examine how age relates to membership decline, and how different age groups, particularly younger workers, are located in the story of union decline. The practical implications of this research are that understanding how unions relate to workers of different age groups, and to workers of different genders amongst those age groups, may lead to improved recruitment and better union organisation.

Raman and infrared spectroscopic characterization of the silicate mineral lamprophyllite

The mineral lamprophyllite is fundamentally a silicate based upon tetrahedral siloxane units with extensive substitution in the formula. Lamprophyllite is a complex group of sorosilicates with general chemical formula given as A2B4C2Si2O7(X)4, where the site A can be occupied by strontium, barium, sodium, and potassium; the B site is occupied by sodium, titanium, iron, manganese, magnesium, and calcium. The site C is mainly occupied by titanium or ferric iron and X includes the anions fluoride, hydroxyl, and oxide. Chemical composition shows a homogeneous phase, composed of Si, Na, Ti, and Fe. This complexity of formula is reflected in the complexity of both the Raman and infrared spectra. The Raman spectrum is characterized by intense bands at 918 and 940 cm−1. Other intense Raman bands are found at 576, 671, and 707 cm−1. These bands are assigned to the stretching and bending modes of the tetrahedral siloxane units.

Synthesis, characterization and applications of graphene oxide-polymer nanocomposites

Graphene has emerged as one of the most exciting materials of the 21st century due to its unique properties which have demonstrated great potential for applications in energy storage, flexible electronics and multifunctional composites. This thesis has established a new technique for investigating the structure-property relationship of graphene-polymer nanocomposites at micro and nanoscales. The outcomes can help gain a fundamental understanding of the toughening mechanism in these novel nanocomposites and benefit the development of broad graphene based materials and devices.

A survey: Particle Swarm Optimization based algorithms to solve premature convergence problem

Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method based on the social behaviors of birds flocking or fish schooling. Although, PSO is represented in solving many well-known numerical test problems, but it suffers from the premature convergence. A number of basic variations have been developed due to solve the premature convergence problem and improve quality of solution founded by the PSO. This study presents a comprehensive survey of the various PSO-based algorithms. As part of this survey, the authors have included a classification of the approaches and they have identify the main features of each proposal. In the last part of the study, some of the topics within this field that are considered as promising areas of future research are listed.

A robust optimization approach for index tracking problem

Index tracking is an investment approach where the primary objective is to keep portfolio return as close as possible to a target index without purchasing all index components. The main purpose is to minimize the tracking error between the returns of the selected portfolio and a benchmark. In this paper, quadratic as well as linear models are presented for minimizing the tracking error. The uncertainty is considered in the input data using a tractable robust framework that controls the level of conservatism while maintaining linearity. The linearity of the proposed robust optimization models allows a simple implementation of an ordinary optimization software package to find the optimal robust solution. The proposed model of this paper employs Morgan Stanley Capital International Index as the target index and the results are reported for six national indices including Japan, the USA, the UK, Germany, Switzerland and France. The performance of the proposed models is evaluated using several financial criteria e.g. information ratio, market ratio, Sharpe ratio and Treynor ratio. The preliminary results demonstrate that the proposed model lowers the amount of tracking error while raising values of portfolio performance measures.

Expression and characterization of digestive enzyme genes from hepatopancreatic transcripts from redclaw crayfish (Cherax quadricarinatus)

Redclaw crayfish, Cherax quadricarinatus, possess a number of biological and commercial attributes that make them ideal for commercial aquaculture. While some studies have investigated digestive enzyme activity and nutritional requirements of this species, little information exists about the expression of digestive enzyme genes and their role in regulating digestive capacity. The current study therefore sequenced and annotated a RNASeq library constructed from a redclaw hepatopancreas to identify genes involved in digestive enzyme production. We observed that most of the transcripts that were annotated as digestive enzyme genes are associated with carbohydrate metabolism, thus confirming that redclaw have an innate capacity to digest a range of carbohydrate substrates. While endoglucanases were the most abundant group of digestive enzymes found, a number of novel transcripts were also detected. Here, we provide the first report for the presence and expression of endo-b-mannanase in freshwater crayfish. This novel gene showed significant alignment with a GH5 family protein from marine Limnoriids, wood borers that do not possess symbiotic microbes in their gut system. Overall, the data generated here provide an important resource to better understand the suite of digestive enzymes in redclaw that are very useful to fully utilize the species’ digestive capacity and will assist development of specific artificial feeds.

Characterization of alluvial formation by stochastic modelling of paleo-fluvial processes: The concept and method

Modelling fluvial processes is an effective way to reproduce basin evolution and to recreate riverbed morphology. However, due to the complexity of alluvial environments, deterministic modelling of fluvial processes is often impossible. To address the related uncertainties, we derive a stochastic fluvial process model on the basis of the convective Exner equation that uses the statistics (mean and variance) of river velocity as input parameters. These statistics allow for quantifying the uncertainty in riverbed topography, river discharge and position of the river channel. In order to couple the velocity statistics and the fluvial process model, the perturbation method is employed with a non-stationary spectral approach to develop the Exner equation as two separate equations: the first one is the mean equation, which yields the mean sediment thickness, and the second one is the perturbation equation, which yields the variance of sediment thickness. The resulting solutions offer an effective tool to characterize alluvial aquifers resulting from fluvial processes, which allows incorporating the stochasticity of the paleoflow velocity.

Post-quantum key exchange for the TLS protocol from the ring learning with errors problem

Lattice-based cryptographic primitives are believed to offer resilience against attacks by quantum computers. We demonstrate the practicality of post-quantum key exchange by constructing cipher suites for the Transport Layer Security (TLS) protocol that provide key exchange based on the ring learning with errors (R-LWE) problem, we accompany these cipher suites with a rigorous proof of security. Our approach ties lattice-based key exchange together with traditional authentication using RSA or elliptic curve digital signatures: the post-quantum key exchange provides forward secrecy against future quantum attackers, while authentication can be provided using RSA keys that are issued by today's commercial certificate authorities, smoothing the path to adoption. Our cryptographically secure implementation, aimed at the 128-bit security level, reveals that the performance price when switching from non-quantum-safe key exchange is not too high. With our R-LWE cipher suites integrated into the Open SSL library and using the Apache web server on a 2-core desktop computer, we could serve 506 RLWE-ECDSA-AES128-GCM-SHA256 HTTPS connections per second for a 10 KiB payload. Compared to elliptic curve Diffie-Hellman, this means an 8 KiB increased handshake size and a reduction in throughput of only 21%. This demonstrates that provably secure post-quantum key-exchange can already be considered practical.

Development and characterization of microsatellite markers in the sea squirt, Halocynthia roretzi

We characterized nine new microsatellite markers isolated from (GT) n and (CT) n microsatellite- enriched genomic libraries of the sea squirt ( Halocynthia roretzi ). All markers were polymorphic in 92 individuals from a single natural population with 2–21 (mean 9.22) alleles per locus. The observed and expected heterozy-gosity of these markers were 0.086–0.886 and 0.102–0.870, respectively.One marker (Hr2004) significantly deviated from Hardy–Weinberg equilibrium. These new microsat-ellite markers should be useful for assessing the genetic diversity and population structure in H. roretzi.

Characterization of novel microsatellite markers derived from Korean rose bitterling (Rhodeus uyekii) genomic library

Korean rose bitterling (Rhodeus uyekii) is a freshwater fish endemic to Korea. Natural populations of this species have experienced severe declines as a result of habitat fragmentation and water pollution. To conserve and restore R. uyekii, the genetic diversity of this species needs to be assessed at the population level. Eighteen novel polymorphic microsatellite loci for R. uyekii were developed using an enriched partial genomic library. Polymorphisms at these loci were studied in 150 individuals collected from three populations. The number of alleles at each locus ranged from 3 to 47 (mean = 17.1). Within the populations, the observed heterozygosity ranged from 0.032 to 1.000, expected heterozygosity from 0.082 to 0.967, and polymorphism information content from 0.078 to 0.950. Six loci showed significant deviation from Hardy-Weinberg equilibrium after Bonferroni’s correction, and no significant linkage disequilibrium was detected between most locus pairs, except in three cases. These highly informative microsatellite markers should be useful for genetic population structure analyses of R. uyekii.

A penalty-based genetic algorithm for the migration cost-aware virtual machine placement problem in cloud data centers

In the past few years, the virtual machine (VM) placement problem has been studied intensively and many algorithms for the VM placement problem have been proposed. However, those proposed VM placement algorithms have not been widely used in today's cloud data centers as they do not consider the migration cost from current VM placement to the new optimal VM placement. As a result, the gain from optimizing VM placement may be less than the loss of the migration cost from current VM placement to the new VM placement. To address this issue, this paper presents a penalty-based genetic algorithm (GA) for the VM placement problem that considers the migration cost in addition to the energy-consumption of the new VM placement and the total inter-VM traffic flow in the new VM placement. The GA has been implemented and evaluated by experiments, and the experimental results show that the GA outperforms two well known algorithms for the VM placement problem.