Estimating link-dependent origin-destination matrices from sample trajectories and traffic counts

In transport networks, Origin-Destination matrices (ODM) are classically estimated from road traffic counts whereas recent technologies grant also access to sample car trajectories. One example is the deployment in cities of Bluetooth scanners that measure the trajectories of Bluetooth equipped cars. Exploiting such sample trajectory information, the classical ODM estimation problem is here extended into a link-dependent ODM (LODM) one. This much larger size estimation problem is formulated here in a variational form as an inverse problem. We develop a convex optimization resolution algorithm that incorporates network constraints. We study the result of the proposed algorithm on simulated network traffic.

Amygdala-dependent learning increases the number of spinophilin-immunoreactive dendritic spines in the lateral amygdala

During Pavlovian auditory fear conditioning a previously neutral auditory stimulus (CS) gains emotional significance through pairing with a noxious unconditioned stimulus (US). These associations are believed to be formed by way of plasticity at auditory input synapses on principal neurons in the lateral nucleus of the amygdala (LA). One proposed form of cellular plasticity involves structural changes in the number and morphology of dendritic spines...

How European public sector agencies innovate: The use of bottom-up, policy-dependent and knowledge-scanning innovation methods

Factor and cluster analysis are used to identify different methods that public sector agencies in Europeuse to innovate, based on data from a 2010 survey of 3273 agencies. The analyses identify three types ofinnovative agencies: bottom-up, knowledge-scanning, and policy-dependent. The distribution of bottom-up agencies across European countries is positively correlated with average per capita incomes while thedistribution of knowledge-scanning agencies is negatively correlated with income. In contrast, there isno consistent pattern by country in the distribution of policy-dependent agencies. Regression resultsthat control for agency characteristics find that innovation methods are significantly correlated with thebeneficial outcomes of innovation, with bottom-up and knowledge-scanning agencies out-performingpolicy-dependent agencies.

Estimating link-dependent origin-destination matrices from sample trajectories and traffic counts

Origin-Destination matrices (ODM) estimation can benefits of the availability of sample trajectories which can be measured thanks to recent technologies. This paper focus on the case of transport networks where traffic counts are measured by magnetic loops and sample trajectories available. An example of such network is the city of Brisbane, where Bluetooth detectors are now operating. This additional data source is used to extend the classical ODM estimation to a link-specific ODM (LODM) one using a convex optimisation resolution that incorporates networks constraints as well. The proposed algorithm is assessed on a simulated network.

Bias-dependent effects in planar perovskite solar cells based on CH3NH3PbI3−xClx films

A unique bias-dependent phenomenon in CH3NH3PbI3−xClx based planar perovskite solar cells has been demonstrated, in which the photovoltaic parameters derived from the current–voltage (I–V) curves are highly dependent on the initial positive bias of the I–V measurement. In FTO/CH3NH3PbI3−xClx/Au devices, the open-circuit voltage and short-circuit current increased by ca. 337.5% and 281.9% respectively, by simply increasing the initial bias from 0.5 V to 2.5 V.

Carbon concentration dependent grain growth of Cu2ZnSnS4thin films

Organic solvents are commonly used in ink precursors of Cu2ZnSnS4 (CZTS) nanocrystals to make thin films for applications such as solar cells. However, the traces of carbon residual left behind by the organic solvents after high-temperature annealing is generally considered to restrict the growth of nanocrystals to form large grains. This work reported the first systematic study on the influence of carbon content of organic solvents on the grain growth of CZTS nanomaterial during high temperature sulfurization annealing. Solvents with carbon atom per molecule varying from 3 to 10 were used to made ink of CZTS nanocrystals for thin film deposition. It has been found that, after high temperature sulfurization annealing, a bilayer structure was formed in the CZTS film using organic solvent containing 3 carbon atoms per solvent molecule based on glycerol and 1,3-propanediol. The top layer consisted of closelypacked large grains and the bottom layer was made of as-synthesized nanoparticles. In contrast, the CZTS film made with the solvent molecule with more carbon atoms including 1,5-pentanediol (5 carbon atoms) and 1,7-heptanediol (7 carbon atoms) consisted of nanoparticles embedded with large crystals. It is believed that the carbon residues left behind by the organic solvents affected the necking of CZTS nanocrystals to form large grains through influencing the surface property of nanocrystals. Furthermore, it has also been observed that the solvent affected the thickness of MoS2 layer which was formed between CZTS and Mo substrate. A thinner MoS2 film (50 nm) was obtained with the slurry using carbon-rich terpineol as solvent whereas the thickest MoS2 (350 nm) was obtained with the film made from 1,3-propanediol based solvent. The evaluation of the photoactivity of the CZTS thin films has demonstrated that a higher photocurrent was generated with the film containing more large grains.

Light history-dependent respiration explains the hysteresis in the daily ecosystem metabolism of seagrass

Oxygen flux between aquatic ecosystems and the water column is a measure of ecosystem metabolism. However, the oxygen flux varies during the day in a “hysteretic” pattern: there is higher net oxygen production at a given irradiance in the morning than in the afternoon. In this study, we investigated the mechanism responsible for the hysteresis in oxygen flux by measuring the daily pattern of oxygen flux, light, and temperature in a seagrass ecosystem (Zostera muelleri in Swansea Shoals, Australia) at three depths. We hypothesised that the oxygen flux pattern could be due to diel variations in either gross primary production or respiration in response to light history or temperature. Hysteresis in oxygen flux was clearly observed at all three depths. We compared this data to mathematical models, and found that the modification of ecosystem respiration by light history is the best explanation for the hysteresis in oxygen flux. Light history-dependent respiration might be due to diel variations in seagrass respiration or the dependence of bacterial production on dissolved organic carbon exudates. Our results indicate that the daily variation in respiration rate may be as important as the daily changes of photosynthetic characteristics in determining the metabolic status of aquatic ecosystems.

Investigations of an electrochemical platform based on the layered MoS2-graphene and horseradish peroxidase nanocomposite for direct electrochemistry and electrocatalysis

The self-assembly of layered molybdenum disulfide–graphene (MoS2–Gr) and horseradish peroxidase (HRP) by electrostatic attraction into a novel hybrid nanomaterial (HRP–MoS2–Gr) is reported. The properties of the MoS2–Gr were characterized by X-ray diffraction (XRD), high-resolution transmission electron microscopy (TEM), electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). UV–vis and Fourier transform infrared spectroscopy (FT-IR) indicate that the native structure of the HRP is maintained after the assembly, implying good biocompatibility of MoS2–Gr nanocomposite. Furthermore, the HRP–MoS2–Gr composite is utilized as a biosensor, which displays electrocatalytic activity to hydrogen peroxide (H2O2) with high sensitivity (679.7 μA mM−1 cm−2), wide linear range (0.2 μM–1.103 mM), low detection limit (0.049 μM), and fast amperometric response. In addition, the biosensor also exhibits strong anti-interference ability, satisfactory stability and reproducibility. These desirable electrochemical properties are attributed to the good biocompatibility and electron transport efficiency of the MoS2–Gr composite, as well as the high loading of HRP. Therefore, this biosensor is potentially suitable for H2O2 analysis in environmental, pharmaceutical, food or industrial applications.

Physical mechanisms underlying the strain-rate-dependent mechanical behavior of kangaroo shoulder cartilage

Due to anatomical and biomechanical similarities to human shoulder, kangaroo was chosen as a model to study shoulder cartilage. Comprehensive enzymatic degradation and indentation tests were applied on kangaroo shoulder cartilage to study mechanisms underlying its strain-rate-dependent mechanical behavior. We report that superficial collagen plays a more significant role than proteoglycans in facilitating strain-rate-dependent behavior of kangaroo shoulder cartilage. By comparing the mechanical properties of degraded and normal cartilages it was noted that proteoglycan and collagen degradation significantly compromised strain-rate-dependent mechanical behavior of the cartilage. Superficial collagen contributed equally to the tissue behavior at all strain-rates. This is different to studies reported on knee cartilage and confirms the importance of superficial collagen on shoulder cartilage mechanical behavior. A porohyperelastic numerical model also indicated that collagen disruption would lead to faster damage of the shoulder cartilage than when proteoglycans are depleted.

Investigation of the mechanical behavior of kangaroo humeral head cartilage tissue by a porohyperelastic model based on the strain-rate-dependent permeability

Solid–interstitial fluid interaction, which depends on tissue permeability, is significant to the strain-rate-dependent mechanical behavior of humeral head (shoulder) cartilage. Due to anatomical and biomechanical similarities to that of the human shoulder, kangaroos present a suitable animal model. Therefore, indentation experiments were conducted on kangaroo shoulder cartilage tissues from low (10−4/s) to moderately high (10−2/s) strain-rates. A porohyperelastic model was developed based on the experimental characterization; and a permeability function that takes into account the effect of strain-rate on permeability (strain-rate-dependent permeability) was introduced into the model to investigate the effect of rate-dependent fluid flow on tissue response. The prediction of the model with the strain-rate-dependent permeability was compared with those of the models using constant permeability and strain-dependent permeability. Compared to the model with constant permeability, the models with strain-dependent and strain-rate-dependent permeability were able to better capture the experimental variation at all strain-rates (p<0.05). Significant differences were not identified between models with strain-dependent and strain-rate-dependent permeability at strain-rate of 5×10−3/s (p=0.179). However, at strain-rate of 10−2/s, the model with strain-rate-dependent permeability was significantly better at capturing the experimental results (p<0.005). The findings thus revealed the significance of rate-dependent fluid flow on tissue behavior at large strain-rates, which provides insights into the mechanical deformation mechanisms of cartilage tissues.

The electronic origin of contrast reversal in bias-dependent STM images of nanolines

Self-organized Bi lines that are only 1.5 nm wide can be grown without kinks or breaks on Si(0 0 1) surfaces to lengths of up to 500 nm. Constant-current topographical images of the lines, obtained with the scanning tunneling microscope, have a striking bias dependence. Although the lines appear darker than the Si terraces at biases below ≈∣1.2∣ V, the contrast reverses at biases above ≈∣1.5∣ V. Between these two ranges the lines and terraces are of comparable brightness. It has been suggested that this bias dependence may be due to the presence of a semiconductor-like energy gap within the line. Using ab initio calculations it is demonstrated that the energy gap is too small to explain the experimentally observed bias dependence. Consequently, at this time, there is no compelling explanation for this phenomenon. An alternative explanation is proposed that arises naturally from calculations of the tunneling current, using the Tersoff–Hamann approximation, and an examination of the electronic structure of the line.

In vivo mri-based estimation of time-dependent elastic modulus in healthy arteries

The elastic properties of the arterial wall have been the subject of physiological, clinical and biomedical research for many years. There is convincing evidence that the elastic properties of the large arteries are seriously impaired in the presence of cardiovascular disease (CVD), due to alterations in the intrinsic structural and functional characteristics of vessels [1]. Early detection of changes in the elastic modulus of arteries would provide a powerful tool for both monitoring patients at high cardiovascular risk and testing the effects of pharmaceuticals aimed at stabilizing existing plaques by stiffening them or lowering the lipids.

Robust estimation using the Huber function with a data-dependent tuning constant

Robust estimation often relies on a dispersion function that is more slowly varying at large values than the square function. However, the choice of tuning constant in dispersion functions may impact the estimation efficiency to a great extent. For a given family of dispersion functions such as the Huber family, we suggest obtaining the "best" tuning constant from the data so that the asymptotic efficiency is maximized. This data-driven approach can automatically adjust the value of the tuning constant to provide the necessary resistance against outliers. Simulation studies show that substantial efficiency can be gained by this data-dependent approach compared with the traditional approach in which the tuning constant is fixed. We briefly illustrate the proposed method using two datasets.

Growth curves with time-dependent explanatory variables

A class of growth models incorporating time-dependent factors and stochastic perturbations are introduced. The proposed model includes the existing growth models used in fisheries as special cases. Particular attention is given to growth of a population (in average weight or length) from which observations are taken randomly each time and the analysis of tag-recapture data. Two real data sets are used for illustration: (a) to estimate the seasonal effect and population density effect on growth of farmed prawn (Penaeus monodon) from weight data and (b) to assess the effect of tagging on growth of barramundi (Lates calcarifer)