Exploring the boundary between the siphon and barometer in a hypobaric chamber

Siphons have been used since ancient times, but exactly how they work is still a matter of debate. In order to elucidate the modus operandi of a siphon, a 1.5 m high siphon was set up in a hypobaric chamber to explore siphon behaviour in a low-pressure environment. When the pressure in the chamber was reduced to about 0.18 atmospheres, a curious waterfall-like feature appeared downstream from the apex of the siphon. A hypothesis is presented to explain the waterfall phenomenon. When the pressure was reduced further the siphon broke into two columns - in effect becoming two back-to-back barometers. This experiment demonstrates the role of atmospheric pressure in explaining the hydrostatic characteristics of a siphon and the role of molecular cohesion in explaining the hydrodynamic aspects.

Molecular structural studies of the amorphous mineral pitticite Fe, AsO4, SO4, H2O

Some minerals are colloidal and show no X-ray diffraction patterns. Vibrational spectroscopy offers one of the few methods for the assessment of the structure of these types of mineral. Among this group of minerals is pitticite simply described as Fe, AsO4, SO4, H2O. The objective of this research is to determine the molecular structure of the mineral pitticite using vibrational spectroscopy. Raman microscopy offers a useful method for the analysis of such colloidal minerals. Raman and infrared bands are attributed to the , and water stretching vibrations. The Raman spectrum is dominated by a very intense sharp band at 983 cm−1 assigned to the symmetric stretching mode. A strong Raman band at 1041 cm−1 is observed and is assigned to the antisymmetric stretching mode. Low intensity Raman bands at 757 and 808 cm−1 may be assigned to the antisymmetric and symmetric stretching modes. Raman bands observed at 432 and 465 cm−1 are attributable to the doubly degenerate ν2(SO4)2- bending mode.

Practical aspects of frequency-domain identification of dynamic models of marine structures from hydrodynamic data

The motion response of marine structures in waves can be studied using finite-dimensional linear-time-invariant approximating models. These models, obtained using system identification with data computed by hydrodynamic codes, find application in offshore training simulators, hardware-in-the-loop simulators for positioning control testing, and also in initial designs of wave-energy conversion devices. Different proposals have appeared in the literature to address the identification problem in both time and frequency domains, and recent work has highlighted the superiority of the frequency-domain methods. This paper summarises practical frequency-domain estimation algorithms that use constraints on model structure and parameters to refine the search of approximating parametric models. Practical issues associated with the identification are discussed, including the influence of radiation model accuracy in force-to-motion models, which are usually the ultimate modelling objective. The illustration examples in the paper are obtained using a freely available MATLAB toolbox developed by the authors, which implements the estimation algorithms described.

Molecular and structural basis of androgen receptor responses to dihydrotestosterone, medroxyprogesterone acetate and Δ4-tibolone

Medroxyprogesterone acetate (MPA) has widely been used in hormone replacement therapy (HRT), and is associated with an increased risk of breast cancer, possibly due to disruption of androgen receptor (AR) signaling. In contrast, the synthetic HRT Tibolone does not increase breast density, and is rapidly metabolized to estrogenic 3α-OH-tibolone and 3β-OH-tibolone, and a delta-4 isomer (Δ4-TIB) that has both androgenic and progestagenic properties. Here, we show that 5α-dihydrotestosterone (DHT) and Δ4-TIB, but not MPA, stabilize AR protein levels, initiate specific AR intramolecular interactions critical for AR transcriptional regulation, and increase proliferation of AR positive MDA-MB-453 breast cancer cells. Structural modeling and molecular dynamic simulation indicate that Δ4-TIB induces a more stable AR structure than does DHT, and MPA a less stable one. Microarray expression analyses confirms that the molecular actions of Δ4-TIB more closely resembles DHT in breast cancer cells than either ligand does to MPA.

Computational aspects of probabilistic assessment of UAS robust autonomy

As the level of autonomy in Unmanned Aircraft Systems (UAS) increases, there is an imperative need for developing methods to assess robust autonomy. This paper focuses on the computations that lead to a set of measures of robust autonomy. These measures are the probabilities that selected performance indices related to the mission requirements and airframe capabilities remain within regions of acceptable performance.

What aspects of demographic, personality, attitudes, and perceptions of law enforcement influence self-reported likelihood of drink driving?

The aim of the current study was to examine the associations between a number of individual factors (demographic factors (age and gender), personality factors, risk-taking propensity, attitudes towards drink driving, and perceived legitimacy of drink driving enforcement) and how they influence the self-reported likelihood of drink driving. The second aim of this study was to examine the potential of attitudes mediating the relationship between risk-taking and self-reported likelihood of drink driving. In total, 293 Queensland drivers volunteered to participate in an online survey that assessed their self-reported likelihood to drink drive in the next month, demographics, traffic-related demographics, personality factors, risk-taking propensity, attitudes towards drink driving, and perceived legitimacy of drink driving enforcement. An ordered logistic regression analysis was utilised to evaluate the first aim of the study; at the first step the demographic variables were entered; at step two the personality and risk-taking were entered; at the third step, the attitudes and perceptions of legitimacy variables were entered. Being a younger driver and having a high risk-taking propensity were related to self-reported likelihood of drink driving. However, when the attitudes variable was entered, these individual factors were no longer significant; with attitudes being the most important predictor of self-reported drink driving likelihood. A significant mediation model was found with the second aim of the study, such that attitudes mediated the relationship between risk-taking and self-reported likelihood of drink driving. Considerable effort and resources are utilised by traffic authorities to reducing drink driving on the Australian road network. Notwithstanding these efforts, some participants still had some positive attitudes towards drink driving and reported that they were likely to drink drive in the future. These findings suggest that more work is needed to address attitudes regarding the dangerousness of drink driving.

Quality aspects in service ecosystems : areas for exploitation and exploration

Service Science, Management, and Engineering (SSME) is a research area with significant relevance to research and practice. Networked systems of web services are a field of service science that enjoys growing interest from researchers. The complex and dynamic environment of these service ecosystems poses new requirements on quality management that are insufficiently addressed by current approaches that focus mainly on the technical aspects of quality. This focus is a severe limitation for the development of service networks because it neglects perceived service quality from the viewpoint of service consumers. In this paper we propose a reference model for quality management in service ecosystems. This reference model is linked in particular to innovation and new service development. Towards the end we propose premises for the implementation and outline a future research agenda.

Exercise alters the profile of phospholipid molecular species in rat skeletal muscle

We have determined the effect of two exercise-training intensities on the phospholipid profile of both glycolytic and oxidative muscle fibers of female Sprague-Dawley rats using electrospray-ionization mass spectrometry. Animals were randomly divided into three training groups: control, which performed no exercise training; low-intensity (8 m/min) treadmill running; or high-intensity (28 m/min) treadmill running. All exercise-trained rats ran 1,000 m/session for 4 days/wk for 4 wk and were killed 48 h after the last training bout. Exercise training was found to produce no novel phospholipid species but was associated with significant alterations in the relative abundance of a number of phospholipid molecular species. These changes were more prominent in glycolytic (white vastus lateralis) than in oxidative (red vastus lateralis) muscle fibers. The largest observed change was a decrease of ∼20% in the abundance of 1-stearoyl-2-docosahexaenoyl-phosphatidylethanolamine [PE(18:0/22:6); P < 0.001] ions in both the low- and high-intensity training regimes in glycolytic fibers. Increases in the abundance of 1-oleoyl-2-linoleoyl phopshatidic acid [PA(18:1/18:2); P < 0.001] and 1-alkenylpalmitoyl-2-linoleoyl phosphatidylethanolamine [plasmenyl PE (16:0/18:2); P < 0.005] ions were also observed for both training regimes in glycolytic fibers. We conclude that exercise training results in a remodeling of phospholipids in rat skeletal muscle. Even though little is known about the physiological or pathophysiological role of specific phospholipid molecular species in skeletal muscle, it is likely that this remodeling will have an impact on a range of cellular functions.

Random projections on manifolds of symmetric positive definite matrices for image classification

Recent advances suggest that encoding images through Symmetric Positive Definite (SPD) matrices and then interpreting such matrices as points on Riemannian manifolds can lead to increased classification performance. Taking into account manifold geometry is typically done via (1) embedding the manifolds in tangent spaces, or (2) embedding into Reproducing Kernel Hilbert Spaces (RKHS). While embedding into tangent spaces allows the use of existing Euclidean-based learning algorithms, manifold shape is only approximated which can cause loss of discriminatory information. The RKHS approach retains more of the manifold structure, but may require non-trivial effort to kernelise Euclidean-based learning algorithms. In contrast to the above approaches, in this paper we offer a novel solution that allows SPD matrices to be used with unmodified Euclidean-based learning algorithms, with the true manifold shape well-preserved. Specifically, we propose to project SPD matrices using a set of random projection hyperplanes over RKHS into a random projection space, which leads to representing each matrix as a vector of projection coefficients. Experiments on face recognition, person re-identification and texture classification show that the proposed approach outperforms several recent methods, such as Tensor Sparse Coding, Histogram Plus Epitome, Riemannian Locality Preserving Projection and Relational Divergence Classification.

Automatic classification of human epithelial type 2 cell indirect immunofluorescence images using cell pyramid matching

This paper describes a novel system for automatic classification of images obtained from Anti-Nuclear Antibody (ANA) pathology tests on Human Epithelial type 2 (HEp-2) cells using the Indirect Immunofluorescence (IIF) protocol. The IIF protocol on HEp-2 cells has been the hallmark method to identify the presence of ANAs, due to its high sensitivity and the large range of antigens that can be detected. However, it suffers from numerous shortcomings, such as being subjective as well as time and labour intensive. Computer Aided Diagnostic (CAD) systems have been developed to address these problems, which automatically classify a HEp-2 cell image into one of its known patterns (eg. speckled, homogeneous). Most of the existing CAD systems use handpicked features to represent a HEp-2 cell image, which may only work in limited scenarios. We propose a novel automatic cell image classification method termed Cell Pyramid Matching (CPM), which is comprised of regional histograms of visual words coupled with the Multiple Kernel Learning framework. We present a study of several variations of generating histograms and show the efficacy of the system on two publicly available datasets: the ICPR HEp-2 cell classification contest dataset and the SNPHEp-2 dataset.

Molecular sliding filament model for muscular contraction based on multiscale investigation

A multiscale approach that bridges the biophysics of the actin molecules at nanoscale and the biomechanics of actin filament at microscale level is developed and used to evaluate the mechanical performances of actin filament bundles. In order to investigate the contractile properties of skeletal muscle which is induced by the protein motor of myosin, a molecular model is proposed in the prediction of the dynamic behaviors of skeletal muscle based on classic sliding filament model. Randomly distributed myosin motors are applied on a 2.2 μm long sarcomere, whose principal components include actin and myosin filaments. It can be found that, the more myosin motors on the sarcomere, the faster the sarcomere contracts. The result demonstrates that the sarcomere shortening speed cannot increase infinitely by the modulation of myosin, thus providing insight into the self-protective properties of skeletal muscles. This molecular filament sliding model provides a theoretical way to evaluate the properties of skeletal muscles, and contributes to the understandings of the molecular mechanisms in the physiological phenomenon of muscular contraction.

Improved image set classification via joint sparse approximated nearest subspaces

Existing multi-model approaches for image set classification extract local models by clustering each image set individually only once, with fixed clusters used for matching with other image sets. However, this may result in the two closest clusters to represent different characteristics of an object, due to different undesirable environmental conditions (such as variations in illumination and pose). To address this problem, we propose to constrain the clustering of each query image set by forcing the clusters to have resemblance to the clusters in the gallery image sets. We first define a Frobenius norm distance between subspaces over Grassmann manifolds based on reconstruction error. We then extract local linear subspaces from a gallery image set via sparse representation. For each local linear subspace, we adaptively construct the corresponding closest subspace from the samples of a probe image set by joint sparse representation. We show that by minimising the sparse representation reconstruction error, we approach the nearest point on a Grassmann manifold. Experiments on Honda, ETH-80 and Cambridge-Gesture datasets show that the proposed method consistently outperforms several other recent techniques, such as Affine Hull based Image Set Distance (AHISD), Sparse Approximated Nearest Points (SANP) and Manifold Discriminant Analysis (MDA).

Molecular and cellular analysis of basement membrane invasion by human breast cancer cells in Matrigel-based in vitro assays

In vitro analyses of basement membrane invasiveness employing Matrigel (a murine tumor extract rich in basement membrane components) have been performed on human breast cancer model systems. Constitutive invasiveness of different human breast cancer (HBC) cell lines has been examined as well as regulation by steroid hormones, growth factors, and oncogenes. Carcinoma cells exhibiting a mesenchymal-like phenotype (vimentin expression, lack of cell border associated uvomorulin) show dramatically increased motility, invasiveness, and metastatic potential in nude mice. These findings support the hypothesis that epithelial to mesenchymal transition (EMT)-like events may be instrumental in the metastatic progression of human breast cancer. The MCF-7 subline MCF-7ADR appears to have undergone such a transition. The importance of such a transition may be reflected in the emergence of vimentin expression as an indicator of poor prognosis in HBC. Matrix degradation and laminin recognition are highlighted as potential targets for antimetastatic therapy, and analyses of laminin attachment and the matrix metalloproteinase (MMP) family in HBC cell lines are summarized. Matrigel-based assays have proved useful in the study of the molecular mechanisms of basement membrane invasiveness, their regulation in HBC cells, and their potential as targets for antimetastatic therapy.

Hormonal carcinogenesis in breast cancer : cellular and molecular studies of malignant progression

We have established and characterized a series of variant cell lines in which to identify the critical factors associated with E2-induced malignant progression, and the acquisition to tamoxifen resistance in human breast cancer. Sublines of the hormone-dependent MCF-7 cell line (MCF7/MIII and MCF7/LCC1) form stable, invasive, estrogen independent tumors in the mammary fat pads of ovariectomized athymic nude mice. These cells retain expression of both estrogen (ER) and progesterone receptors (PGR), but retain sensitivity to each of the major structural classes of antiestrogens. The tamoxifen-resistant MCF7/LCC2 cells retain sensitivity to the inhibitory effects of the steroidal antiestrogen ICI 182780. By comparing the parental hormone-dependent and variant hormone-independent cells, we have demonstrated an altered expression of some estrogen regulated genes (PGR, pS2, cathepsin D) in the hormone-independent variants. Other genes remain normally estrogen regulated (ER, laminin receptor, EGF-receptor). These data strongly implicate the altered regulation of a specific subset or network of estrogen regulated genes in the malignant progression of human breast cancer. Some of the primary response genes in this network may exhibit dose-response and induction kinetics similar to pS2, which is constitutively upregulated in the MCF7/MIII, MCF7/LCC1 and MCF7/LCC2 cells.

Paracrine interactions between LNCaP prostate cancer cells and bioengineered bone in 3D in vitro culture reflect molecular changes during bone metastasis

As microenvironmental factors such as three-dimensionality and cell–matrix interactions are increasingly being acknowledged by cancer biologists, more complex 3D in vitro models are being developed to study tumorigenesis and cancer progression. To better understand the pathophysiology of bone metastasis, we have established and validated a 3D indirect co-culture model to investigate the paracrine interactions between prostate cancer (PCa) cells and human osteoblasts. Co-culture of the human PCa, LNCaP cells embedded within polyethylene glycol hydrogels with human osteoblasts in the form of a tissue engineered bone construct (TEB), resulted in reduced proliferation of LNCaP cells. LNCaP cells in both monoculture and co-culture were responsive to the androgen analog, R1881, as indicated by an increase in the expression (mRNA and/or protein induction) of androgen-regulated genes including prostate specific antigen and fatty acid synthase. Microarray gene expression analysis further revealed an up-regulation of bone markers and other genes associated with skeletal and vasculature development and a significant activation of transforming growth factor β1 downstream genes in LNCaP cells after co-culture with TEB. LNCaP cells co-cultured with TEB also unexpectedly showed similar changes in classical androgen-responsive genes under androgen-deprived conditions not seen in LNCaP monocultures. The molecular changes of LNCaP cells after co-culturing with TEBs suggest that osteoblasts exert a paracrine effect that may promote osteomimicry and modulate the expression of androgen-responsive genes in LNCaP cells. Taken together, we have presented a novel 3D in vitro model that allows the study of cellular and molecular changes occurring in PCa cells and osteoblasts that are relevant to metastatic colonization of bone. This unique in vitro model could also facilitate cancer biologists to dissect specific biological hypotheses via extensive genomic or proteomic assessments to further our understanding of the PCa-bone crosstalk.