Inorganic-organic hybrids of the p,p'-diphenylmethylenediphosphinate ligand with bivalent metals: a new 2D-layered phenylphosphinate zinc(II) complex

By reaction of Zn(CH₃COO)₂ with p,p′-diphenylmethylenediphosphinic acid in water a new inorganic–organic polymeric hybrid of formula [Zn(CH₂(P(Ph)O₂)₂)] has been synthesized and completely characterized. The X-ray analysis established that the structure consists of 2D-layered polymeric array, the 2D-sheets being built up through strong covalent linkages between the zinc metal and the oxygen donors of the phenylphosphinate ligand. The 2D-layers, which are featuring a mesh-net fashion, present voids of various dimensionality, up to 24-membered rings. The organic parts of the hybrid ligand, namely the phenyl rings, are shielding the inorganic skeleton of the layers, preventing the propagation of the polymer in the third dimension. No water molecules are present in the lattice, both of coordination and crystallization. Crystal data are: monoclinic, P2₁Ic, a=11.840(2), b=9.646(9), c=12.516(5) Å, β=95.03(2), V=1423.9(15) ų, Z=4. The solid material has been characterized by ³¹P MAS NMR spectroscopy and thermogravimetric analysis.

Earthquake-controlled event deposits and its tectonic significance from the Middle Permian Wandrawandian Siltstone in the Sydney Basin, Australia

The Sydney-Bowen basin in eastern Australia is an elongate back arc-converted foreland basin system situated between the Lachlan Fold Belt in the west and the New England Fold Belt in the east. The Middle Permian Wandrawandian Siltstone at Warden Head near Ulladulla in the southern Sydney Basin is dominated by fossiliferous siltstone and mudstone, with a large amount of dropstones and minor pebbly sandstone beds. Two general types of deposits are recognized from the siltstone unit in view of the timing and mechanism of formation. One is represented by the primary deposits from offshore to subtidal environments with abundant dropstones of glacial marine origin. The second type is distinguished by secondary, soft-sediment deformational deposits and structures, and comprises three layers of mudstone dykes of seismic origin. In the latter type, metre scale, laterally extensive syn-depositional slump deformation structures occur in the middle part of the Wandrawandian Siltstone. The deformation structures vary in morphol-ogy and pattern, including large-scale complex-type folds, flexural stratification, concave-up structures, faulting of small displacements accompanied by folding and brecciation. The slumps and associated syn-sedimentary structures are attributed to penecontemporaneous deformations of soft sediments (mostly silty mud) formed as a result of mass movement of unconsolidated and/or semi-consolidated substrate following an earthquake event. The occurrence of the earthquake event deposits supports the current view that the Sydney Basin was located in a back-arc setting near the New England magmatic arc on an active continental margin during the Middle Permian.

Layered fragment architecture for situational methodology engineering

Many organizations make use of information system development methodologies to guide their staff in developing computerised information systems. This thesis contributes to methodology engineering research by introducing a number of important innovations in methodology fragment architectures.

A layered security approach for cloud computing infrastructure

This paper introduces a practical security model based on key security considerations by looking at a number of infrastructure aspects of Cloud Computing such as SaaS, Utility, Web, Platform and Managed Services, Service commerce platforms and Internet Integration which was introduced with a concise literature review. The purpose of this paper is to offer a macro level solution for identified common infrastructure security requirements. This model with a number of emerged patterns can be applied to infrastructure aspect of Cloud Computing as a proposed shared security approach in system development life cycle focusing on the plan-built-run scope.

Transparent uv-shielding films from organic small molecule-intercalated layered double hydroxide nanoplatelets/polymer composite

In this study, layered double hydroxide (LDH) with nitrate as the interlayer anion has been partially exfoliated in dimethyl sulfoxide (DMSO). Atomic force microscopy (AFM) images showed that both the lateral size and the thickness of the LDH nanoplatelets were decreased after DMSO treatment. Formation of transparent LDH suspension in DMSO was observed. Taking this advantage, we have prepared transparent LDH/ethylene-vinyl alcohol copolymer (EVOH) nanocomposite films using DMSO as the processing solvent. Organic small molecules, UV absorbers, were intercalated into the LDH interlayers to incorporate the UV-shielding property into the transparent composite films. The thermal stability of UV absorbers was considerably improved after intercalation, which was attributed to the electrostatic interaction between the guest UV absorbers and the host LDH layers. The prepared composite films were flexible and exhibited excellent UV-shielding capability, but had transmittance as high as 90% in the visible region. The effect of LDH filler on thermal and mechanical properties of the composite films was also examined.

Visible transparent, UV-blocking polymer nanocomposite films containing nano-sized organic-LDH (Layered Double Hydroxide) hybrid

A nano-sized Mg2Al layered double hydroxide (LDH) was used for encapsulating an organic UV absorber, 2-hydroxy-4- methoxybenzeophenone-5-sulfonic acid (HMBS), to produce HMBS@LDH hybrid nano-platelets. Upon dispersing this organic-inorganic hybrid LDH into ethylene-vinyl alcohol copolymer (EVOH) for film casting, a thin polymer
nanocomposite film that is UV opaque but highly transparent to visible light (higher than 90%) was formed. Thermogravimetry (TG) analysis confirmed that the intercalation of HMBS into LDH considerably increased the thermal stability of HMBS. Such an improvement was attributed to the strong guest-host interaction between the HMBS anions and the LDH layers. Also, the nanocomposite films were flexible and had good mechanical properties.

Partial exfoliation of layered double hydroxides in DMSO : a route to transparent polymer nanocomposites

Layered double hydroxides (LDHs), either having nitrate counter anions or intercalated with organic molecules, have been for the first time partially exfoliated in dimethyl sulfoxide (DMSO) to form a transparent suspension. Atomic force microscopy (AFM) images showed that both the lateral size and the thickness of the LDH nanoplatelets were decreased after the exfoliation. The organic-LDHs maintained their intercalation characteristics, i.e. the thermal stability improvement of the incorporated organic anions, after the exfoliation in DMSO. Transparent ethylene-vinyl alcohol copolymer (EVOH) nanocomposite films containing partially exfoliated LDHs intercalated with UV absorbers were prepared using DMSO as the processing solvent. As the first reported example of a highly transparent LDH/polymer composite, the obtained composite film had a visible light transmittance of 90% (comparable to that of the pure matrix), was flexible and exhibited an excellent UV-shielding capability and thermal stability.

Semantic and layered protein function prediction from PPI networks

Background The past few years have seen a rapid development in novel high-throughput technologies that have created large-scale data on protein-protein interactions (PPI) across human and most model species. This data is commonly represented as networks, with nodes representing proteins and edges representing the PPIs. A fundamental challenge to bioinformatics is how to interpret this wealth of data to elucidate the interaction of patterns and the biological characteristics of the proteins. One significant purpose of this interpretation is to predict unknown protein functions. Although many approaches have been proposed in recent years, the challenge still remains how to reasonably and precisely measure the functional similarities between proteins to improve the prediction effectiveness.

Results We used a Semantic and Layered Protein Function Prediction (SLPFP) framework to more effectively predict unknown protein functions at different functional levels. The framework relies on a new protein similarity measurement and a clustering-based protein function prediction algorithm. The new protein similarity measurement incorporates the topological structure of the PPI network, as well as the protein's semantic information in terms of known protein functions at different functional layers. Experiments on real PPI datasets were conducted to evaluate the effectiveness of the proposed framework in predicting unknown protein functions.

Conclusion The proposed framework has a higher prediction accuracy compared with other similar approaches. The prediction results are stable even for a large number of proteins. Furthermore, the framework is able to predict unknown functions at different functional layers within the Munich Information Center for Protein Sequence (MIPS) hierarchical functional scheme. The experimental results demonstrated that the new protein similarity measurement reflects more reasonably and precisely relationships between proteins.

Occupant interaction with interior environment in Greek dwellings during summer

User behaviour significantly affects energy consumption simulation estimates, which can consequently influence architectural design decisions at an early stage. Different regional behavioural patterns could, therefore, hinder the applicability of certain architectural and environmental strategies. Through questionnaires analysis and field studies, this study investigates the pattern use of manual control of windows, shading and air condition units, in residential buildings in Greece, during summer. Initial findings of the analysis indicate significant interaction of Greek residents with the building shell, in their effort to maintain comfort.

Layered dynamic probabilistic networks for spatio-temporal modelling

In applications such as tracking and surveillance in large spatial environments, there is a need for representing dynamic and noisy data and at the same time dealing with them at different levels of detail. In the spatial domain, there has been work dealing with these two issues separately, however, there is no existing common framework for dealing with both of them. In this paper, we propose a new representation framework called the Layered Dynamic Probabilistic Network (LDPN), a special type of Dynamic Probabilistic Network (DPN), capable of handling uncertainty and representing spatial data at various levels of detail. The framework is thus particularly suited to applications in wide-area environments which are characterised by large region size, complex spatial layout and multiple sensors/cameras. For example, a building has three levels: entry/exit to the building, entry/exit between rooms and moving within rooms. To avoid the problem of a relatively large state space associated with a large spatial environment, the LDPN explicitly encodes the hierarchy of connected spatial locations, making it scalable to the size of the environment being modelled. There are three main advantages of the LDPN. First, the reduction in state space makes it suitable for dealing with wide area surveillance involving multiple sensors. Second, it offers a hierarchy of intervals for indexing temporal data. Lastly, the explicit representation of intermediate sub-goals allows for the extension of the framework to easily represent group interactions by allowing coupling between sub-goal layers of different individuals or objects. We describe an adaptation of the likelihood sampling inference scheme for the LDPN, and illustrate its use in a hypothetical surveillance scenario.