Sexuality on the Internet: From sexual exploration to pathological expression.

A growing number of clients are presenting in therapy with problems related to their on-line sexual habits. Adults who had used the Internet for sexual pursuits at least once (N?=?9,177) completed a 59-item on-line survey. Men and women generally behaved differently, and most (92%) indicated their on-line sexual behaviors were not problematic. Heavy users (8%) reported significant problems typically associated with compulsive disorders. Problems were highly correlated with time spent on-line for sex. Results are discussed in terms of their research and practice implications, including diagnosis and treatment. Recommendations are made for outreach prevention programs and future policies. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Optimization of Inhibitors of Mycobacterium tuberculosis Pantothenate Synthetase Based on Group Efficiency Analysis

Ligand efficiency has proven to be a valuable concept for optimization of leads in the early stages of drug design. Taking this one step further, group efficiency (GE) evaluates the binding efficiency of each appendage of a molecule, further fine‐tuning the drug design process. Here, GE analysis is used to systematically improve the potency of inhibitors of Mycobacterium tuberculosis pantothenate synthetase, an important target in tuberculosis therapy. Binding efficiencies were found to be distributed unevenly within a lead molecule derived using a fragment‐based approach. Substitution of the less efficient parts of the molecule allowed systematic development of more potent compounds. This method of dissecting and analyzing different groups within a molecule offers a rational and general way of carrying out lead optimization, with potential broad application within drug discovery.     

Application of rough sets for environmental decision support in industry

Practical environmental decision-making in industry is a complex task that often entails a subtle interplay between alternatives and criteria. Quantitative tools are used to aid decision-makers to arrive at rational conclusions. However, conventional decision aids are often limited by the need to define a priori weights for the criteria being considered; identifying the correct weights to use is not a trivial task and has been the subject of considerable research. An alternative approach based on rough set methodology is described in this work. The procedure develops an empirical, rule-based model from example responses derived from an expert panel. The model can then be used for decision-making in cases resembling the example used previously. Rough set theory also provides numerical measures of the reliability of the rule-based model developed. The approach is illustrated with two case studies, the first involving comparison of alternative energy sources, and the second involving the ranking of pollution prevention strategies in manufacturing.     

Automated Quality Characterization for Composites Using Hybrid Ultrasonic Imaging Techniques

An enhanced technique using image processing has been developed for automated ultrasonic inspection of composite materials, such as glass/carbon-fibre-reinforced polymer (GFRP or CFRP), to ascertain their structural healthiness. The proposed technique is capable of identifying the abnormality features buried in the composite by image filtering and segmentation applied to ultrasonic C-Scan images. This work presents results performed on two composite samples with simulated delamination defects. A local gating scheme is applied to raw A-Scan data for improved contrast between defective and healthy regions in the produced C-Scan image. In this test campaign, different filtering and thresholding algorithms are evaluated and compared in terms of their effectiveness on defect identification. The accuracies of less than 3 mm and 1.11 mm were attained for the defect size and depth, respectively. The results demonstrates the applicability of the proposed technique for accurate defect localization and characterization of composite materials.     

Mixing Studies Related to the Cleaning of Molten Aluminium

Molten aluminium is traditionally “cleaned” by a chlorine‐based fluxing gas. This gas also has to provide the motive power for mixing. Recently, mechanical agitation with solid fluxes has been considered as a replacement for environmental reasons. Here, these two methods of mixing are compared using particle image velocimetry (PIV), decolourisation for homogenisation and power measurement for comparison of efficiencies. A geometrically scaled‐down vessel was used, with air to mimic “chlorine” fluxing and with water as the working fluid. At equivalent mean specific energy dissipation rates, _T, maximum velocities are higher and mixing times are shorter with an impeller. This improved performance is achieved with the impeller without causing surface gas entrainment, the latter being detrimental to fluxing.     

Microwave drying characteristics of microalgae (<Emphasis Type="Italic">Chlorella vulgaris</Emphasis>) for biofuel production

Algal biofuels serve as a promising alternative energy source for liquid fuels. However, one of the bottlenecks in the conversion of microalgae to biofuels is the drying process. A moisture content of at most 10 % is desired for algal biomass prior to oil extraction to maximise biofuel yield. Conventional means of drying results to longer drying time and uneven drying of algal biomass. This study investigated the drying characteristics of microwave for microalgae (Chlorella vulgaris). Three microwave intensity levels (300, 600, and 900 W) were considered to dry 10, 20, and 30 of algal mass. Page model gave a better fit on the moisture ratio with time of microwave drying than the exponential model. Furthermore, the specific energy requirement was computed, and a relationship was found between moisture ratio with power and mass. Fourier transform infrared spectroscopy results showed significant reduction of infrared signal intensities of the functional groups present in the algae after drying at higher microwave power level. It was concluded that the 20 W/g microwave drying setting gave a lower specific energy requirement with good quality of remaining high lipid content qualitatively. Furthermore, it was recommended to use gas chromatography mass spectroscopy to further quantify the algal lipids and other functional groups.     

Highly Conductive,Stretchable, and Cell‐Adhesive Hydrogel by Nanoclay Doping

Electrically conductive materials that mimic physical and biological properties of tissues are urgently required for seamless brain–machine interfaces. Here, a multinetwork hydrogel combining electrical conductivity of 26 S m^?1, stretchability of 800%, and tissue‐like elastic modulus of 15 kPa with mimicry of the extracellular matrix is reported. Engineering this unique set of properties is enabled by a novel in‐scaffold polymerization approach. Colloidal hydrogels of the nanoclay Laponite are employed as supports for the assembly of secondary polymer networks. Laponite dramatically increases the conductivity of in‐scaffold polymerized poly(ethylene‐3,4‐diethoxy thiophene) in the absence of other dopants, while preserving excellent stretchability. The scaffold is coated with a layer containing adhesive peptide and polysaccharide dextran sulfate supporting the attachment, proliferation, and neuronal differentiation of human induced pluripotent stem cells directly on the surface of conductive hydrogels. Due to its compatibility with simple extrusion printing, this material promises to enable tissue‐mimetic neurostimulating electrodes.     

On Non-Uniform Rational B-Splines Surface Neural Networks

This article presents a simulation study for validation of an adaptation methodology for learning weights of a Hopfield neural network configured as a static optimizer. The quadratic Liapunov function associated with the Hopfield network dynamics is leveraged to map the set of constraints associated with a static optimization problem. This approach leads to a set of constraint-specific penalty or weighting coefficients whose values need to be defined. The methodology leverages a learning-based approach to define values of constraint weighting coefficients through adaptation. These values are in turn used to compute values of network weights, effectively eliminating the guesswork in defining weight values for a given static optimization problem, which has been a long-standing challenge in artificial neural networks. The simulation study is performed using the Traveling Salesman problem from the domain of combinatorial optimization. Simulation results indicate that the adaptation procedure is able to guide the Hopfield network towards solutions of the problem starting with random values for weights and constraint weighting coefficients. At the conclusion of the adaptation phase, the Hopfield network acquires weight values which readily position the network to search for local minimum solutions. The demonstrated successful application of the adaptation procedure eliminates the need to guess or predetermine the values for weights of the Hopfield network.     

Performance generalization in biometric authentication using joint user-specific and sample bootstraps

Biometric authentication performance is often depicted by a detection error trade-off (DET) curve. We show that this curve is dependent on the choice of samples available, the demographic composition and the number of users specific to a database. We propose a two-step bootstrap procedure to take into account the three mentioned sources of variability. This is an extension to the Bolle et al.'s bootstrap subset technique. Preliminary experiments on the NIST2005 and XM2VTS benchmark databases are encouraging, e.g., the average result across all 24 systems evaluated on NIST2005 indicates that one can predict, with more than 75 percent of DET coverage, an unseen DET curve with eight times more users. Furthermore, our finding suggests that with more data available, the confidence intervals become smaller and, hence, more useful