Large-volume methacrylate monolith for plasmid purification : process engineering approach to synthesis and application

The extent of exothermicity associated with the construction of large-volume methacrylate monolithic columns has somewhat obstructed the realisation of large-scale rapid biomolecule purification especially for plasmid-based products which have proven to herald future trends in biotechnology. A novel synthesis technique via a heat expulsion mechanism was employed to prepare a 40 mL methacrylate monolith with a homogeneous radial pore structure along its thickness. Radial temperature gradient was recorded to be only 1.8 °C. Maximum radial temperature recorded at the centre of the monolith was 62.3 °C, which was only 2.3 °C higher than the actual polymerisation temperature. Pore characterisation of the monolithic polymer showed unimodal pore size distributions at different radial positions with an identical modal pore size of 400 nm. Chromatographic characterisation of the polymer after functionalisation with amino groups displayed a persistent dynamic binding capacity of 15.5 mg of plasmid DNA/mL. The maximum pressure drop recorded was only 0.12 MPa at a flow rate of 10 mL/min. The polymer demonstrated rapid separation ability by fractionating Escherichia coli DH5α-pUC19 clarified lysate in only 3 min after loading. The plasmid sample collected after the fast purification process was tested to be a homogeneous supercoiled plasmid with DNA electrophoresis and restriction analysis.

Towards the design of a scalable and commercially viable technique for plasmid purification using a methacrylate monolithic stationary phase

A monolithic stationary phase was prepared via free radical co-polymerization of ethylene glycol dimethacrylate (EDMA) and glycidyl methacrylate (GMA) with pore diameter tailored specifically for plasmid binding, retention and elution. The polymer was functionalized. with 2-chloro-N,N-diethylethylamine hydrochloride (DEAE-Cl) for anion-exchange purification of plasmid DNA (pDNA) from clarified lysate obtained from E. coli DH5α-pUC19 culture in a ribonuclease/ protease-free environment. Characterization of the monolithic resin showed a porous material, with 68% of the pores existing in the matrix having diameters above 300 nm. The final product isolated from a single-stage 5 min anion-exchange purification was a pure and homogeneous supercoiled (SC) pDNA with no gDNA, RNA and protein contamination as confirmed by ethidium bromide agarose gel electrophoresis (EtBr-AGE), enzyme restriction analysis and sodium dodecyl sulfate-polyacrylamide gel electrophoresis. This non-toxic technique is cGMP compatible and highly scalable for production of pDNA on a commercial level.

Process engineering approach to large-volume methacrylate monolith synthesis for plasmid purification

The construction of large?volume methacrylate monolithic columns for preparative-scale plasmid purification is obstructed by the enormous release of exotherms, thus introducing structural heterogeneity in the monolith pore system. A remarkable radial temperature gradient develops along the monolith thickness, reaching a terminal temperature that supersedes the maximum temperature required for the preparation of a structurally homogeneous monolith. A novel heat expulsion technique is employed to overcome the heat build-up during the synthesis process. The enormous heat build-up is perceived to encompass the heat associated with initiator decomposition and the heat released from free radical-monomer and monomer-monomer interactions. The heat resulting from the initiator decomposition was expelled along with some gaseous fumes before commencing polymerisation in a gradual addition fashion. Characteristics of a 50 mL monolith synthesized using this technique showed an improved uniformity in the pore structure radially along the length on the monolith. Chromatographic characterization of this adsorbent displayed a persistent binding capacity of 14.5 mg pDNA/mL of the adsorbent. The adsorbent was able to fractionate a clarified bacteria lysate in only 3 min (after loading) into RNA, protein and pDNA respectively. The pDNA fraction obtained was analyzed to be a homogeneous supercoiled pDNA.

Electropolymerisation of catalytically active PEDOT from an ionic liquid on a flexible carbon cloth using a sandwich cell configuration

We report the electropolymerization of poly(3,4-ethylenedioxythiopene) (PEDOT) from an ionic liquid, butyl-methylpyrrolidinium bis(trifluoromethanesulfonyl)imide (C4mpyrTFSI) onto flexible carbon cloth electrodes. A continuous, homogeneous and well adhered coating of the individual cloth fibres is achieved by employing a sandwich cell arrangement where the carbon cloth which is soaked with electrolyte is placed between two indium tin oxide electrodes isolated from each other by a battery separator. The resultant PEDOT modified carbon cloth electrode demonstrates excellent activity for the oxygen reduction reaction which is due to the doping level, conductivity and morphology of the PEDOT layer and is also tolerant to the presence of methanol in the electrolyte. This simple approach therefore offers a route to fabricate flexible polymer electrodes that could be used in various electronic applications.

Automatic UAV forced landing site detection using machine learning

The commercialization of aerial image processing is highly dependent on the platforms such as UAVs (Unmanned Aerial Vehicles). However, the lack of an automated UAV forced landing site detection system has been identified as one of the main impediments to allow UAV flight over populated areas in civilian airspace. This article proposes a UAV forced landing site detection system that is based on machine learning approaches including the Gaussian Mixture Model and the Support Vector Machine. A range of learning parameters are analysed including the number of Guassian mixtures, support vector kernels including linear, radial basis function Kernel (RBF) and polynormial kernel (poly), and the order of RBF kernel and polynormial kernel. Moreover, a modified footprint operator is employed during feature extraction to better describe the geometric characteristics of the local area surrounding a pixel. The performance of the presented system is compared to a baseline UAV forced landing site detection system which uses edge features and an Artificial Neural Network (ANN) region type classifier. Experiments conducted on aerial image datasets captured over typical urban environments reveal improved landing site detection can be achieved with an SVM classifier with an RBF kernel using a combination of colour and texture features. Compared to the baseline system, the proposed system provides significant improvement in term of the chance to detect a safe landing area, and the performance is more stable than the baseline in the presence of changes to the UAV altitude.

Vibration based baseline updating method to localize crack formation and propagation in reinforced concrete members

Structural Health Monitoring (SHM) schemes are useful for proper management of the performance of structures and for preventing their catastrophic failures. Vibration based SHM schemes has gained popularity during the past two decades resulting in significant research. It is hence evitable that future SHM schemes will include robust and automated vibration based damage assessment techniques (VBDAT) to detect, localize and quantify damage. In this context, the Damage Index (DI) method which is classified as non-model or output based VBDAT, has the ability to automate the damage assessment process without using a computer or numerical model along with actual measurements. Although damage assessment using DI methods have been able to achieve reasonable success for structures made of homogeneous materials such as steel, the same success level has not been reported with respect to Reinforced Concrete (RC) structures. The complexity of flexural cracks is claimed to be the main reason to hinder the applicability of existing DI methods in RC structures. Past research also indicates that use of a constant baseline throughout the damage assessment process undermines the potential of the Modal Strain Energy based Damage Index (MSEDI). To address this situation, this paper presents a novel method that has been developed as part of a comprehensive research project carried out at Queensland University of Technology, Brisbane, Australia. This novel process, referred to as the baseline updating method, continuously updates the baseline and systematically tracks both crack formation and propagation with the ability to automate the damage assessment process using output only data. The proposed method is illustrated through examples and the results demonstrate the capability of the method to achieve the desired outcomes.

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.

A SEM, EDS and vibrational spectroscopic study of the tellurite mineral: Sonoraite Fe3+Te4+O3(OH)·H2O

We have undertaken a study of the tellurite mineral sonorite using electron microscopy with EDX combined with vibrational spectroscopy. Chemical analysis shows a homogeneous composition, with predominance of Te, Fe, Ce and In with minor amounts of S. Raman spectroscopy has been used to study the mineral sonoraite an examples of group A(XO3), with hydroxyl and water units in the mineral structure. The free tellurite ion has C3v symmetry and four modes, 2A1 and 2E. An intense Raman band at 734 cm−1 is assigned to the ν1 (TeO3)2− symmetric stretching mode. A band at 636 cm−1 is assigned to the ν3 (TeO3)2− antisymmetric stretching mode. Bands at 350 and 373 cm−1 and the two bands at 425 and 438 cm−1 are assigned to the (TeO3)2−ν2 (A1) bending mode and (TeO3)2−ν4 (E) bending modes. The sharp band at 3283 cm−1 assigned to the OH stretching vibration of the OH units is superimposed upon a broader spectral profile with Raman bands at 3215, 3302, 3349 and 3415 cm−1 are attributed to water stretching bands. The techniques of Raman and infrared spectroscopy are excellent for the study of tellurite minerals.

The inner quality of an article: Will time tell?

In this paper, we assess whether quality survives the test of time in academia by comparing up to 80 years of academic journal article citations from two top journals, Econometrica and the American Economic Review. The research setting under analysis is analogous to a controlled real world experiment in that it involves a homogeneous task (trying to publish in top journals) by individuals with a homogenous job profile (academics) in a specific research environment (economics and econometrics). Comparing articles published concurrently in the same outlet at the same time (same issue) indicates that symbolic capital or power due to institutional affiliation or connection does seem to boost citation success at the beginning, giving those educated at or affiliated with leading universities an initial comparative advantage. Such advantage, however, does not hold in the long run: at a later stage,the publications of other researchers become as or even more successful.

Transdimensional sequential Monte Carlo using variational Bayes — SMCVB

A new transdimensional Sequential Monte Carlo (SMC) algorithm called SM- CVB is proposed. In an SMC approach, a weighted sample of particles is generated from a sequence of probability distributions which ‘converge’ to the target distribution of interest, in this case a Bayesian posterior distri- bution. The approach is based on the use of variational Bayes to propose new particles at each iteration of the SMCVB algorithm in order to target the posterior more efficiently. The variational-Bayes-generated proposals are not limited to a fixed dimension. This means that the weighted particle sets that arise can have varying dimensions thereby allowing us the option to also estimate an appropriate dimension for the model. This novel algorithm is outlined within the context of finite mixture model estimation. This pro- vides a less computationally demanding alternative to using reversible jump Markov chain Monte Carlo kernels within an SMC approach. We illustrate these ideas in a simulated data analysis and in applications.

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.

Difficulties in distinguishing coherent from fragmental kimberlite: A case study of the Muskox pipe (Northern Slave Province, Nunavut, Canada)

Kimberlite drill core from the Muskox pipe (Northern Slave Province, Nunavut, Canada) highlights the difficulties in distinguishing coherent from fragmental kimberlite and assessing the volcanological implications of the apparent gradational contact between the two facies. Using field log data, petrography, and several methods to quantify crystal and xenolith sizes and abundances, the pipe is divided into two main facies, dark-coloured massive kimberlite (DMK) and light-coloured fragmental kimberlite (LFK). DMK is massive and homogeneous, containing country-rock lithic clasts (~ 10%) and olivine macrocrysts (~ 15%) set in a dark, typically well crystallised, interstitial medium containing abundant microphenocrysts of olivine (~ 15%), opaques and locally monticellite, all of which are enclosed by mostly serpentine. In general, LFK is also massive and structureless, containing ~ 20% country-rock lithic clasts and ~ 12% olivine macrocrysts. These framework components are supported in a matrix of serpentinized olivine microphenocrysts (10%), microlites of clinopyroxene, and phlogopite, all of which are enclosed by serpentine. The contact between DMK and LFK facies is rarely sharp, and more commonly is gradational (from 5 cm to ~ 10 m). The contact divides the pipe roughly in half and is sub-vertical with an irregular shape, locally placing DMK facies both above and below the fragmental rocks. Most features of DMK are consistent with a fragmental origin, particularly the crystal- and xenolith-rich nature (~ 55-65%), but there are some similarities with rocks described as coherent kimberlite in the literature. We discuss possible origins of gradational contacts and consider the significance for understanding the origin of the DMK facies, with an emphasis on the complications of alteration overprinting of primary textures.

Confirmatory factory analysis of the Neck Disability Index in a general problematic neck population indicates a one-factor model

BACKGROUND CONTEXT: The Neck Disability Index frequently is used to measure outcomes of the neck. The statistical rigor of the Neck Disability Index has been assessed with conflicting outcomes. To date, Confirmatory Factor Analysis of the Neck Disability Index has not been reported for a suitably large population study. Because the Neck Disability Index is not a condition-specific measure of neck function, initial Confirmatory Factor Analysis should consider problematic neck patients as a homogenous group. PURPOSE: We sought to analyze the factor structure of the Neck Disability Index through Confirmatory Factor Analysis in a symptomatic, homogeneous, neck population, with respect to pooled populations and gender subgroups. STUDY DESIGN: This was a secondary analysis of pooled data. PATIENT SAMPLE: A total of 1,278 symptomatic neck patients (67.5% female, median age 41 years), 803 nonspecific and 475 with whiplash-associated disorder. OUTCOME MEASURES: The Neck Disability Index was used to measure outcomes. METHODS: We analyzed pooled baseline data from six independent studies of patients with neck problems who completed Neck Disability Index questionnaires at baseline. The Confirmatory Factor Analysis was considered in three scenarios: the full sample and separate sexes. Models were compared empirically for best fit. RESULTS: Two-factor models have good psychometric properties across both the pooled and sex subgroups. However, according to these analyses, the one-factor solution is preferable from both a statistical perspective and parsimony. The two-factor model was close to significant for the male subgroup (p<.07) where questions separated into constructs of mental function (pain, reading headaches and concentration) and physical function (personal care, lifting, work, driving, sleep, and recreation). CONCLUSIONS: The Neck Disability Index demonstrated a one-factor structure when analyzed by Confirmatory Factor Analysis in a pooled, homogenous sample of neck problem patients. However, a two-factor model did approach significance for male subjects where questions separated into constructs of mental and physical function. Further investigations in different conditions, subgroup and sex-specific populations are warranted.

Hierarchical clustering of the genetic connectivity matrix reveals the network topology of gene action on brain microstructure: An N=531 twin study

Genetic correlation (rg) analysis determines how much of the correlation between two measures is due to common genetic influences. In an analysis of 4 Tesla diffusion tensor images (DTI) from 531 healthy young adult twins and their siblings, we generalized the concept of genetic correlation to determine common genetic influences on white matter integrity, measured by fractional anisotropy (FA), at all points of the brain, yielding an NxN genetic correlation matrix rg(x,y) between FA values at all pairs of voxels in the brain. With hierarchical clustering, we identified brain regions with relatively homogeneous genetic determinants, to boost the power to identify causal single nucleotide polymorphisms (SNP). We applied genome-wide association (GWA) to assess associations between 529,497 SNPs and FA in clusters defined by hubs of the clustered genetic correlation matrix. We identified a network of genes, with a scale-free topology, that influences white matter integrity over multiple brain regions.

A perfusion fMRI investigation of thematic and categorical context effects in the spoken production of object names

The context in which objects are presented influences the speed at which they are named. We employed the blocked cyclic naming paradigm and perfusion functional magnetic resonance imaging (fMRI) to investigate the mechanisms responsible for interference effects reported for thematicallyand categorically related compared to unrelated contexts. Naming objects in categorically homogeneous contexts induced a significant interference effect that accumulated from the second cycle onwards. This interference effect was associated with significant perfusion signal decreases in left middle and posterior lateral temporal cortex and the hippocampus. By contrast, thematically homogeneous contexts facilitated naming latencies significantly in the first cycle and did not differ from heterogeneous contexts thereafter, nor were they associated with any perfusion signal changes compared to heterogeneous contexts. These results are interpreted as being consistent with an account in which the interference effect both originates and has its locus at the lexical level, with an incremental learning mechanism adapting the activation levels of target lexical representations following access. We discuss the implications of these findings for accounts that assume thematic relations can be active lexical competitors or assume mandatory involvement of top-down control mechanisms in interference effects during naming.