Thermodynamically stable amorphous drug dispersions in amorphous hydrophilic polymers engineered by hot melt extrusion.

In this study thermodynamically stable dispersions of amorphous quinine, a model BCS class 2 therapeutic agent, within an amorphous polymeric platform (HPC), termed a solid-in-solid dispersion, were produced using hot melt extrusion. Characterisation of the pre-extrudates and extrudates was performed using hyper-differential scanning calorimetry (DSC), powder X-ray diffraction (PXRD) and Raman spectroscopy. Water uptake by the raw materials was determined using dynamic vapour sorption (DVS) analysis. Furthermore, the presence or absence of crystalline drug following storage at 25 °C/60% relative humidity and 40 °C/75% relative humidity in a sealed glass jar, and at 40 °C/75% relative humidity in an open glass jar for 3 months was determined using PXRD. Amorphous quinine was generated in situ during extrusion from both quinine base (5%, 10%, 20% w/w drug loading) and from quinine hydrochloride (5%, 10% w/w drug loading) and remained thermodynamically stable as a solid-in-solid dispersion within the HPC extrudates. When processed with HPC, quinine hydrochloride (20% w/w) was converted to amorphous quinine hydrochloride. Whilst stable for up to 3 months when stored under sealed conditions, this amorphous form was unstable, resulting in recrystallisation of the hydrochloride salt following storage for 1 month at 40 °C/75% relative humidity in an open glass jar. The behaviour of the amorphous quinine hydrochloride (20% w/w) HPC extrudate was related, at least in part, to the lower stability and the hygroscopic properties of this amorphous form.

Understanding Complete Oxidation of Methane on Spinel Oxides at Molecular Level

It is crucial to develop a catalyst made of earth-abundant elements highly active for a complete oxidation of methane at a relatively low temperature. NiCo₂O₄ consisting of earth-abundant elements which can completely oxidize methane in the temperature range of 350-550 °C. Being a cost-effective catalyst, NiCo₂O₄ exhibits activity higher than precious-metal-based catalysts. Here we report that the higher catalytic activity at the relatively low temperature results from the integration of nickel cations, cobalt cations and surface lattice oxygen atoms/oxygen vacancies at the atomic scale. In situ studies of complete oxidation of methane on NiCo₂O₄ and theoretical simulations show that methane dissociates to methyl on nickel cations and then couple with surface lattice oxygen atoms to form -CH₃O with a following dehydrogenation to -CH₂O; a following oxidative dehydrogenation forms CHO; CHO is transformed to product molecules through two different sub-pathways including dehydrogenation of OCHO and CO oxidation.

Concrete damage plasticity model for modeling FRP-to-concrete bond behavior

The technique of externally bonding fiber-reinforced polymer (FRP) composites has become very popular worldwide for retrofitting existing reinforced concrete (RC) structures. Debonding of FRP from the concrete substrate is a typical failure mode in such strengthened structures. The bond behavior between FRP and concrete thus plays a crucial role in these structures. The FRP-to-concrete bond behavior has been extensively investigated experimentally, commonly using a single or double shear test of the FRP-to-concrete bonded joint. Comparatively, much less research has been concerned with numerical simulation, chiefly due to difficulties in the accurate modeling of the complex behavior of concrete. This paper presents a simple but robust finite-element (FE) model for simulating the bond behavior in the entire debonding process for the single shear test. A concrete damage plasticity model is proposed to capture the concrete-to-FRP bond behavior. Numerical results are in close agreement with test data, validating the model. In addition to accuracy, the model has two further advantages: it only requires the basic material parameters (i.e., no arbitrary user-defined parameter such as the shear retention factor is required) and it can be directly implemented in the FE software ABAQUS.

Finite element modelling of FRP-to-concrete bond behaviour using the concrete damage plasticity theory combined with a plastic degradation model

The technique of externally bonding fibre reinforced polymer (FRP) composites has been becoming popular worldwide for retrofitting existing reinforced concrete (RC) structures. A major failure mode in such strengthened structures is the debonding of FRP from the concrete substrate. The bond behaviour between FRP and concrete thus plays a crucial role in these structures. The FRP-to-concrete bond behaviour has been extensively investigated experimentally, commonly using the pull-off test of FRP-to-concrete bonded joint. Comparatively, much less research has been concerned with the numerical simulation of this bond behaviour, chiefly due to difficulties in accurately modelling the complex behaviour of concrete. This paper proposes a robust finite element (FE) model for simulating the bond behaviour in the entire loading process in the pull-off test. A concrete damage plasticity model based on the plastic degradation theory is proposed to overcome the weakness of the elastic degradation theory which has been commonly adopted in previous studies. The model produces results in very close agreement with test data. © Tsinghua University Press, Beijing and Springer-Verlag Berlin Heidelberg 2011.

Issues in fe modelling of FRP strengthened masonry arch bridges

Externally bonding of FRP composites is an effective technique for retrofitting historical masonry arch structures. A major failure mode in such strengthened structures is the debonding of FRP from the masonry. The bond behaviour between FRP and masonry thus plays a crucial role in these structures. Major challenges exist in the finite element modelling of such structures, such as modelling of mixed Mode-I and Mode-II bond behaviour between the FRP and the curved masonry substrate, modelling of existing damages in the masonry arches, consideration of loading history in the unstrengthened and strengthened structure etc. This paper presents a rigorous FE model for simulating FRP strengthened masonry arch structures. A detailed solid model was developed for simulating the masonry and a mixed-mode interface model was used for simulating the FRP-to-masonry bond behaviour. The model produces results in very close agreement with test results.

A technique for reducing strain concentrations in FRP wrapped concrete columns

Existing studies have shown conclusively that the measured fibre reinforced polymer (FRP) rupture strain in FRP wrapped concrete columns is usually significantly smaller than the rupture strain obtained from flat coupon tests. One of the main causes for this phenomenon is the existence of geometrical discontinuities at both ends of the FRP sheets. This study proposes a new strengthening method in which continuous FRP spiral wrapping is used to eliminate strain concentrations due to the geometrical discontinuities and thus increase the FRP rupture strain at column failure. The effect of the spiral angle of FRP on the FRP rupture strain in FRP wrapped specimens was experimentally investigated. The test results indicate that the spiral wrapping with a small angle with respect to the column circumference can significantly increase the strain efficiency of FRP and thus enhance the axial compression capacity of the strengthened cylinders.

Efficient Processing of Spatial Group Keyword Queries

With the proliferation of geo-positioning and geo-tagging techniques, spatio-textual objects that possess both a geographical location and a textual description are gaining in prevalence, and spatial keyword queries that exploit both location and textual description are gaining in prominence. However, the queries studied so far generally focus on finding individual objects that each satisfy a query rather than finding groups of objects where the objects in a group together satisfy a query.

We define the problem of retrieving a group of spatio-textual objects such that the group's keywords cover the query's keywords and such that the objects are nearest to the query location and have the smallest inter-object distances. Specifically, we study three instantiations of this problem, all of which are NP-hard. We devise exact solutions as well as approximate solutions with provable approximation bounds to the problems. In addition, we solve the problems of retrieving top-k groups of three instantiations, and study a weighted version of the problem that incorporates object weights. We present empirical studies that offer insight into the efficiency of the solutions, as well as the accuracy of the approximate solutions.

Efficient Algorithms for Answering the m-Closest Keywords Query

As an important type of spatial keyword query, the m-closest keywords (mCK) query finds a group of objects such that they cover all query keywords and have the smallest diameter, which is defined as the largest distance between any pair of objects in the group. The query is useful in many applications such as detecting locations of web resources. However, the existing work does not study the intractability of this problem and only provides exact algorithms, which are computationally expensive.

In this paper, we prove that the problem of answering mCK queries is NP-hard. We first devise a greedy algorithm that has an approximation ratio of 2. Then, we observe that an mCK query can be approximately answered by finding the circle with the smallest diameter that encloses a group of objects together covering all query keywords. We prove that the group enclosed in the circle can answer the mCK query with an approximation ratio of 2 over 3. Based on this, we develop an algorithm for finding such a circle exactly, which has a high time complexity. To improve efficiency, we propose another two algorithms that find such a circle approximately, with a ratio of 2 over √3 + ε. Finally, we propose an exact algorithm that utilizes the group found by the 2 over √3 + ε)-approximation algorithm to obtain the optimal group. We conduct extensive experiments using real-life datasets. The experimental results offer insights into both efficiency and accuracy of the proposed approximation algorithms, and the results also demonstrate that our exact algorithm outperforms the best known algorithm by an order of magnitude.