A two-stage item recommendation method using probabilistic ranking with reconstructed tensor model

In a tag-based recommender system, the multi-dimensional correlation should be modeled effectively for finding quality recommendations. Recently, few researchers have used tensor models in recommendation to represent and analyze latent relationships inherent in multi-dimensions data. A common approach is to build the tensor model, decompose it and, then, directly use the reconstructed tensor to generate the recommendation based on the maximum values of tensor elements. In order to improve the accuracy and scalability, we propose an implementation of the -mode block-striped (matrix) product for scalable tensor reconstruction and probabilistically ranking the candidate items generated from the reconstructed tensor. With testing on real-world datasets, we demonstrate that the proposed method outperforms the benchmarking methods in terms of recommendation accuracy and scalability.

Synthesis, characterization and activity of an immobilized photocatalyst : natural porous diatomite supported titania nanoparticles

Diatomite, a porous non-metal mineral, was used as support to prepare TiO2/diatomite composites by a modified sol–gel method. The as-prepared composites were calcined at temperatures ranging from 450 to 950 _C. The characterization tests included X-ray powder diffraction (XRD), scanning electron microscopy (SEM) with an energy-dispersive X-ray spectrometer (EDS), high-resolution transmission electron microscopy (HRTEM), X-ray photoelectron spectroscopy (XPS), and nitrogen adsorption/desorption measurements. The XRD analysis indicated that the binary mixtures of anatase and rutile exist in the composites. The morphology analysis confirmed the TiO2 particles were uniformly immobilized on the surface of diatom with a strong interfacial anchoring strength, which leads to few drain of photocatalytic components during practical applications. In further XPS studies of hybrid catalyst, we found the evidence of the presence of Ti–O–Si bond and increased percentage of surface hydroxyl. In addition, the adsorption capacity and photocatalytic activity of synthesized TiO2/diatomite composites were evaluated by studying the degradation kinetics of aqueous Rhodamine B under UV-light irradiation. The photocatalytic degradation was found to follow pseudo-first order kinetics according to the Langmuir–Hinshelwood model. The preferable removal efficiency was observed in composites by 750 _C calcination, which is attributed to a relatively appropriate anatase/rutile mixing ratio of 90/10.

An interpretative structural modeling based network reconfiguration strategy for power systems

The network reconfiguration is an important stage of restoring a power system after a complete blackout or a local outage. Reasonable planning of the network reconfiguration procedure is essential for rapidly restoring the power system concerned. An approach for evaluating the importance of a line is first proposed based on the line contraction concept. Then, the interpretative structural modeling (ISM) is employed to analyze the relationship among the factors having impacts on the network reconfiguration. The security and speediness of restoring generating units are considered with priority, and a method is next proposed to select the generating unit to be restored by maximizing the restoration benefit with both the generation capacity of the restored generating unit and the importance of the line in the restoration path considered. Both the start-up sequence of generating units and the related restoration paths are optimized together in the proposed method, and in this way the shortcomings of separately solving these two issues in the existing methods are avoided. Finally, the New England 10-unit 39-bus power system and the Guangdong power system in South China are employed to demonstrate the basic features of the proposed method.

Stochastic ranking method for thermostatically controllable appliances to provide regulation services

Demand response can be used for providing regulation services in the electricity markets. The retailers can bid in a day-ahead market and respond to real-time regulation signal by load control. This paper proposes a new stochastic ranking method to provide regulation services via demand response. A pool of thermostatically controllable appliances (TCAs) such as air conditioners and water heaters are adjusted using direct load control method. The selection of appliances is based on a probabilistic ranking technique utilizing attributes such as temperature variation and statuses of TCAs. These attributes are stochastically forecasted for the next time step using day-ahead information. System performance is analyzed with a sample regulation signal. Network capability to provide regulation services under various seasons is analyzed. The effect of network size on the regulation services is also investigated.

Near infrared spectroscopy for rapid determination of Mankin score components : a potential tool for quantitative characterization of articular cartilage at surgery

PURPOSE The purpose of this study was to demonstrate the potential of near infrared (NIR) spectroscopy for characterizing the health and degenerative state of articular cartilage based on the components of the Mankin score. METHODS Three models of osteoarthritic degeneration induced in laboratory rats by anterior cruciate ligament (ACL) transection, meniscectomy (MSX), and intra-articular injection of monoiodoacetate (1 mg) (MIA) were used in this study. Degeneration was induced in the right knee joint; each model group consisted of 12 rats (N = 36). After 8 weeks, the animals were euthanized and knee joints were collected. A custom-made diffuse reflectance NIR probe of 5-mm diameter was placed on the tibial and femoral surfaces, and spectral data were acquired from each specimen in the wave number range of 4,000 to 12,500 cm(-1). After spectral data acquisition, the specimens were fixed and safranin O staining (SOS) was performed to assess disease severity based on the Mankin scoring system. Using multivariate statistical analysis, with spectral preprocessing and wavelength selection technique, the spectral data were then correlated to the structural integrity (SI), cellularity (CEL), and matrix staining (SOS) components of the Mankin score for all the samples tested. RESULTS ACL models showed mild cartilage degeneration, MSX models had moderate degeneration, and MIA models showed severe cartilage degenerative changes both morphologically and histologically. Our results reveal significant linear correlations between the NIR absorption spectra and SI (R(2) = 94.78%), CEL (R(2) = 88.03%), and SOS (R(2) = 96.39%) parameters of all samples in the models. In addition, clustering of the samples according to their level of degeneration, with respect to the Mankin components, was also observed. CONCLUSIONS NIR spectroscopic probing of articular cartilage can potentially provide critical information about the health of articular cartilage matrix in early and advanced stages of osteoarthritis (OA). CLINICAL RELEVANCE This rapid nondestructive method can facilitate clinical appraisal of articular cartilage integrity during arthroscopic surgery.

CORR Insights® : loss of cement-bone interlock in retrieved tibial components from total knee arthroplasties

Most surgeons cement the tibial component in total knee replacement surgery. Mid-term registry data from a number of countries, including those from the United Kingdom and Australia, support the excellent survivorship of cemented tibial components. In spite of this success, results can always be improved, and cementing technique can play a role. Cementing technique on the tibia is not standardized, and surgeons still differ about the best ways to deliver cement into the cancellous bone of the upper tibia. Questions remain regarding whether to use a gun or a syringe to inject the cement into the cancellous bone of the tibial plateau . The ideal cement penetration into the tibial plateau is debated, though most reports suggest that 4 mm to 10 mm is ideal. Thicker mantles are thought to be dangerous due to the risk of bone necrosis, but there is little in the literature to support this contention...

Improving treatment for obese women with early stage cancer of the uterus : rationale and design of the levonorgestrel intrauterine device ±Metformin ±weight loss in endometrial cancer (feMME) trial

Purpose Endometrial adenocarcinoma (EC) is the most common gynaecologic cancer. Up to 90% of EC patients are obese which poses a health threat to patients post-treatment. Standard treatment for EC includes hysterectomy, although this has significant side effects for obese women at high risk of surgical complications and for women of childbearing age. This trial investigates the effectiveness of non-surgical or conservative treatment options for obese women with early stage EC. The primary aim is to determine the efficacy of: levonorgestrel intrauterine device (LNG-IUD); with or without metformin (an antidiabetic drug); and with or without a weight loss intervention to achieve a pathological complete response (pCR) in EC at six months from study treatment initiation. The secondary aim is to enhance understanding of the molecular processes and to predict a treatment response by investigating EC biomarkers. Methods An open label, three-armed, randomised, phase-II, multi-centre trial of LNG-IUD ± metformin ± weight loss intervention. 165 participants from 28 centres are randomly assigned in a 3:3:5 ratio to the treatment arms. Clinical, quality of life and health behavioural data will be collected at baseline, six weeks, three and six months. EC biomarkers will be assessed at baseline, three and six months. Conclusions There is limited prospective evidence for conservative treatment for EC. Trial results could benefit patients and reduce health system costs through a reduction in hospitalisations and through lower incidence of adverse events currently observed with standard treatment.

Numerical studies on CFRP strengthened steel columns under transverse impact

Strengthening of metallic structures using carbon fibre reinforced polymer (CFRP) has become a smart strengthening option over the conventional strengthening method. Transverse impact loading due to accidental vehicular collision can lead to the failure of existing steel hollow tubular columns. However, knowledge is very limited on the behaviour of CFRP strengthened steel members under dynamic impact loading condition. This paper deals with the numerical simulation of CFRP strengthened square hollow section (SHS) steel columns under transverse impact loading to predict the behaviour and failure modes. The transverse impact loading is simulated using finite element (FE) analysis based on numerical approach. The accuracy of the FE modelling is ensured by comparing the predicted results with available experimental tests. The effects of impact velocity, impact mass, support condition, axial loading and CFRP thickness are examined through detail parametric study. The impact simulation results indicate that the strengthening technique shows an improved impact resistance capacity by reducing lateral displacement of the strengthened column about 58% compared to the bare steel column. Axial loading plays an important role on the failure behaviour of tubular column.

A new ambiguity acceptance test threshold determination method with controllable failure rate

The ambiguity acceptance test is an important quality control procedure in high precision GNSS data processing. Although the ambiguity acceptance test methods have been extensively investigated, its threshold determine method is still not well understood. Currently, the threshold is determined with the empirical approach or the fixed failure rate (FF-) approach. The empirical approach is simple but lacking in theoretical basis, while the FF-approach is theoretical rigorous but computationally demanding. Hence, the key of the threshold determination problem is how to efficiently determine the threshold in a reasonable way. In this study, a new threshold determination method named threshold function method is proposed to reduce the complexity of the FF-approach. The threshold function method simplifies the FF-approach by a modeling procedure and an approximation procedure. The modeling procedure uses a rational function model to describe the relationship between the FF-difference test threshold and the integer least-squares (ILS) success rate. The approximation procedure replaces the ILS success rate with the easy-to-calculate integer bootstrapping (IB) success rate. Corresponding modeling error and approximation error are analysed with simulation data to avoid nuisance biases and unrealistic stochastic model impact. The results indicate the proposed method can greatly simplify the FF-approach without introducing significant modeling error. The threshold function method makes the fixed failure rate threshold determination method feasible for real-time applications.

Natural convection heat transfer in a baffled triangular enclosure

To reduce the natural convection heat loss from enclosures many researchers used convection suppression devices in the past. In this study a single baffle is used under the top tip to investigate numerically the natural convection heat loss in an attic shaped enclosure which is a cost effective approach. The case considered here is one inclined wall of the enclosure is uniformly heated while the other inclined wall is uniformly cooled with adiabatic bottom wall. The finite volume method has been used to discretize the governing equations, with the QUICK scheme approximating the advection term. The diffusion terms are discretized using central-differencing with second order accuracy. A wide range of governing parameters are studied (Rayleigh number, aspect ratio, baffle length etc.). It is observed that the heat transfer due to natural convection in the enclosure reduces when the baffle length is increased. Effects of other parameters on heat transfer and flow field are described in this study.

Adaptive finite element analysis of elliptic problems based on bubble-type local mesh generation

A new mesh adaptivity algorithm that combines a posteriori error estimation with bubble-type local mesh generation (BLMG) strategy for elliptic differential equations is proposed. The size function used in the BLMG is defined on each vertex during the adaptive process based on the obtained error estimator. In order to avoid the excessive coarsening and refining in each iterative step, two factor thresholds are introduced in the size function. The advantages of the BLMG-based adaptive finite element method, compared with other known methods, are given as follows: the refining and coarsening are obtained fluently in the same framework; the local a posteriori error estimation is easy to implement through the adjacency list of the BLMG method; at all levels of refinement, the updated triangles remain very well shaped, even if the mesh size at any particular refinement level varies by several orders of magnitude. Several numerical examples with singularities for the elliptic problems, where the explicit error estimators are used, verify the efficiency of the algorithm. The analysis for the parameters introduced in the size function shows that the algorithm has good flexibility.

Bat colony size reduction coincides with clear-fell harvest operations and high rates of roost loss in plantation forest

Clear-fell harvest of forest concerns many wildlife biologists because of loss of vital resources such as roosts or nests, and effects on population viability. However, actual impact has not been quantified. Using New Zealand long-tailed bats (Chalinolobus tuberculatus) as a model species we investigated impacts of clear-fell logging on bats in plantation forest. C. tuberculatus roost within the oldest stands in plantation forest so it was likely roost availability would decrease as harvest operations occurred. We predicted that post-harvest: (1) roosting range sizes would be smaller, (2) fewer roosts would be used, and (3) colony size would be smaller. We captured and radiotracked C. tuberculatus to day-roosts in Kinleith Forest, an exotic plantation forest, over three southern hemisphere summers (Season 1 October 2006–March 2007; Season 2 November 2007–March 2008; and Season 3 November 2008–March 2009). Individual roosting ranges (100% MCPs) post harvest were smaller than those in areas that had not been harvested, and declined in area during the 3 years. Following harvest, bats used fewer roosts than those in areas that had not been harvested. Over 3 years 20.7% of known roosts were lost: 14.5% due to forestry operations and 6.2% due to natural tree fall. Median colony size was 4.0 bats (IQR = 2.0–8.0) and declined during the study, probably because of locally high levels of roost loss. Post harvest colonies were smaller than colonies in areas that had not been harvested. Together, these results suggest the impact of clear-fell harvest on long-tailed bat populations is negative.

A numerical method for the fractional Fitzhugh–Nagumo monodomain model

A fractional FitzHugh–Nagumo monodomain model with zero Dirichlet boundary conditions is presented, generalising the standard monodomain model that describes the propagation of the electrical potential in heterogeneous cardiac tissue. The model consists of a coupled fractional Riesz space nonlinear reaction-diffusion model and a system of ordinary differential equations, describing the ionic fluxes as a function of the membrane potential. We solve this model by decoupling the space-fractional partial differential equation and the system of ordinary differential equations at each time step. Thus, this means treating the fractional Riesz space nonlinear reaction-diffusion model as if the nonlinear source term is only locally Lipschitz. The fractional Riesz space nonlinear reaction-diffusion model is solved using an implicit numerical method with the shifted Grunwald–Letnikov approximation, and the stability and convergence are discussed in detail in the context of the local Lipschitz property. Some numerical examples are given to show the consistency of our computational approach.

DroplIT, an improved image analysis method for droplet identification in high-throughput crystallization trials

The application of robotics to protein crystallization trials has resulted in the production of millions of images. Manual inspection of these images to find crystals and other interesting outcomes is a major rate-limiting step. As a result there has been intense activity in developing automated algorithms to analyse these images. The very first step for most systems that have been described in the literature is to delineate each droplet. Here, a novel approach that reaches over 97% success rate and subsecond processing times is presented. This will form the seed of a new high-throughput system to scrutinize massive crystallization campaigns automatically. © 2010 International Union of Crystallography Printed in Singapore-all rights reserved.

A new approach to estimating trends in chlamydia incidence

Objectives Directly measuring disease incidence in a population is difficult and not feasible to do routinely. We describe the development and application of a new method of estimating at a population level the number of incident genital chlamydia infections, and the corresponding incidence rates, by age and sex using routine surveillance data. Methods A Bayesian statistical approach was developed to calibrate the parameters of a decision-pathway tree against national data on numbers of notifications and tests conducted (2001-2013). Independent beta probability density functions were adopted for priors on the time-independent parameters; the shape parameters of these beta distributions were chosen to match prior estimates sourced from peer-reviewed literature or expert opinion. To best facilitate the calibration, multivariate Gaussian priors on (the logistic transforms of) the time-dependent parameters were adopted, using the Matérn covariance function to favour changes over consecutive years and across adjacent age cohorts. The model outcomes were validated by comparing them with other independent empirical epidemiological measures i.e. prevalence and incidence as reported by other studies. Results Model-based estimates suggest that the total number of people acquiring chlamydia per year in Australia has increased by ~120% over 12 years. Nationally, an estimated 356,000 people acquired chlamydia in 2013, which is 4.3 times the number of reported diagnoses. This corresponded to a chlamydia annual incidence estimate of 1.54% in 2013, increased from 0.81% in 2001 (~90% increase). Conclusions We developed a statistical method which uses routine surveillance (notifications and testing) data to produce estimates of the extent and trends in chlamydia incidence.