A spatial econometric panel data examination of endogenous versus exogenous interaction in Chinese province-level patenting

We examine the provincial-level relationship between domestic Chinese intellectual property (IP) and knowledge stocks using a space–time panel model and data set covering monthly patent activity over the period 2002–2010. The goal of the modeling exercise is to explore the elasticity response of IP to knowledge stocks classified by type of creator (universities and research institutes, enterprises, and individuals). A focus is on spatial and time dependence in the relationship between knowledge stocks and IP, which implies spatial spillovers and diffusion over time. Many past studies of regional knowledge production have focused on patent applications as a proxy for regional output from the knowledge production process. However, this ignores the distinction between patent applications and patents granted, with the latter reflecting a decision and ability to convert knowledge produced into IP. This study differs in its focus on the regional relation between IP and knowledge stocks and the space–time dynamics of these. Using patents granted as a proxy for IP, and past patent applications as a proxy for regional knowledge stocks, allows us to explore the implied quality of knowledge production by various types of creators. Because Chinese patent applications have grown by 22 %, questions have been raised about the quantity versus quality of these applications. Our findings shed light on this issue.     

Flood tide circulation near beaufort inlet, North Carolina: Implications for larval recruitment

Drifter tracks and shipboard CTD observations have revealed a number of distinct features of the flood tide circulation carrying water through Beaufort Inlet, North Carolina. One of the most noteworthy of these features is a nearshore jet in the flow carrying water to the inlet on a flood tide. Characterized by a shoreward increase in longshore flow, the jet produces a narrow coastal zone over which water is carried into the inlet. The jet appears to be principally a tidal phenomenon, as it is closely reproduced by a tidally-driven barotropic numerical model. The model results also indicate the jet may be a near-inlet feature. Model simulations of spring tide conditions show the jet confined to within 4 km of the inlet mouth. Another observed phenomenon, which is reproduced by the tidal model, is a distinct splitting of the flow entering the inlet, in which water passing through a particular inlet segment tends to move up-estuary along a well-defined path. An observed flow feature not reproduced by the tidal model is an eastward skew of the region over which water is drawn into the inlet on a flood tide. This asymmetry is unrelated to the local wind. Modeling results from a previous study suggest it may be due to convergent flow at the edge of the low salinity plume issuing from the inlet. Taken together, the results of this and other recent studies in the Beaufort Inlet region reveal the importance of nearshore currents on the eastern side of the inlet in delivering oceanic-spawned larvae to the estuarine system connected to the inlet.     

Adaptations for scavenging by three diverse bathyla species, Eptatretus stouti, Neptunea amianta and Orchomene obtusus

Many deep-sea animals derive part of their nutrition from rare and unpredictable food falls. However, traits that allow organisms inhabiting the sea floor to exploit carrion are poorly understood. We found in laboratory experiments that hagfish (Eptatretus stouti), gastropods (Neptunea amianta) and amphipods (Orchomene obtusus) survived extended periods of starvation, in some cases for more than a year. When exposed to odors emitted from carrion, most individuals of E. stouti and O. obtusus began searching for food within seconds, whereas none responded to the scent of the live prey. In contrast, the slow crawling N. amianta readily consumed carrion but showed no apparent response to any odor solutions tested. Because more motile animals exhibited lower thresholds for response to signal molecules, sensitivity to chemical cues appears related to species mobility. Hagfish were also found to defend carrion from some competitors by releasing slime when feeding. Though varying dramatically in size, morphology, locomotive ability, and phylogeny, these three species all possess traits well suited for a scavenging lifestyle.     

The Optimal Design of TMD for Offshore Structures

This paper presents the optimal design procedure of Tuned Mass Damper(TMD)for re-ducing vibration of an actual steel jacket offshore platform excited by random wave loading.In this study,a frequency domain is taken.The force on the structure is determined by use of the linearized Morisonequation for an input Power Spectral Density(PSD)of wave elevation.The sensitivity of optimum valuesof TMD to characteristic parameters of random wave spectrum is analyzed.An optimized TMD designfor the modeled platform is given based on design conditions and the findings of the study.     

Data Analysis and Modeling to Optimize Thermal Treatment Cost and Performance

The objective of in situ thermal treatment is typically to reduce the contaminant mass or average soil concentration below a specified value. Evaluation of whether the objective has been met is usually made by averaging soil concentrations from a limited number of soil samples. Results from several field sites indicate large performance uncertainty using this approach, even when the number of samples is large. We propose a method to estimate average soil concentration by fitting a log normal probability model to thermal mass recovery data. A statistical approach is presented for making termination decisions from mass recovery data, soil sample data, or both for an entire treatment volume or for subregions that explicitly considers estimation uncertainty which is coupled to a stochastic optimization algorithm to identify monitoring strategies to meet objectives with minimum expected cost. Early termination of heating in regions that reach cleanup targets sooner enables operating costs to be reduced while ensuring a high likelihood of meeting remediation objectives. Results for an example problem demonstrate that significant performance improvement and cost reductions can be achieved using this approach.     

A model‐based data‐driven dictionary learning for seismic data representation

Planar waves events recorded in a seismic array can be represented as lines in the Fourier domain. However, in the real world, seismic events usually have curvature or amplitude variability, which means that their Fourier transforms are no longer strictly linear but rather occupy conic regions of the Fourier domain that are narrow at low frequencies but broaden at high frequencies where the effect of curvature becomes more pronounced. One can consider these regions as localised “signal cones”. In this work, we consider a space–time variable signal cone to model the seismic data. The variability of the signal cone is obtained through scaling, slanting, and translation of the kernel for cone‐limited (C‐limited) functions (functions whose Fourier transform lives within a cone) or C‐Gaussian function (a multivariate function whose Fourier transform decays exponentially with respect to slowness and frequency), which constitutes our dictionary. We find a discrete number of scaling, slanting, and translation parameters from a continuum by optimally matching the data. This is a non‐linear optimisation problem, which we address by a fixed‐point method that utilises a variable projection method with ?₁ constraints on the linear parameters and bound constraints on the non‐linear parameters. We observe that slow decay and oscillatory behaviour of the kernel for C‐limited functions constitute bottlenecks for the optimisation problem, which we partially overcome by the C‐Gaussian function. We demonstrate our method through an interpolation example. We present the interpolation result using the estimated parameters obtained from the proposed method and compare it with those obtained using sparsity‐promoting curvelet decomposition, matching pursuit Fourier interpolation, and sparsity‐promoting plane‐wave decomposition methods.     

Well tie for broadband seismic data

The seismic industry is increasingly acquiring broadband data in order to reap the benefits of extra low‐ and high‐frequency contents. At the low end, as the sharp low‐cut decay gets closer to zero frequency, it becomes harder for a well tie to estimate the low‐frequency response correctly. The fundamental difficulty is that well logs are too short to allow accurate estimation of the long‐period content of the data. Three distinctive techniques, namely parametric constant phase, frequency‐domain least squares with multi‐tapering, and Bayesian time domain with broadband priors, are introduced in this paper to provide a robust solution to the wavelet estimation problem for broadband seismic data. Each of these techniques has a different mathematical foundation that would enable one to explore a wide range of solutions that could be used on a case‐by‐case basis depending on the problem at hand. A case study from the North West Shelf Australia is used to analyse the performance of the proposed techniques. Cross‐validation is proposed as a robust quality control measure for evaluating well‐tie applications. It is observed that when the seismic data are carefully processed, then the constant phase approach would likely offer a good solution. The frequency‐domain method does not assume a constant phase. This flexibility makes it prone to over‐fitting when the phase is approximately constant. Broadband priors for the time‐domain least‐squares method are found to perform well in defining low‐frequency side lobes to the wavelet.     

Using Diurnal Temperature Signals to Infer Vertical Groundwater‐Surface Water Exchange

Heat is a powerful tracer to quantify fluid exchange between surface water and groundwater. Temperature time series can be used to estimate pore water fluid flux, and techniques can be employed to extend these estimates to produce detailed plan‐view flux maps. Key advantages of heat tracing include cost‐effective sensors and ease of data collection and interpretation, without the need for expensive and time‐consuming laboratory analyses or induced tracers. While the collection of temperature data in saturated sediments is relatively straightforward, several factors influence the reliability of flux estimates that are based on time series analysis (diurnal signals) of recorded temperatures. Sensor resolution and deployment are particularly important in obtaining robust flux estimates in upwelling conditions. Also, processing temperature time series data involves a sequence of complex steps, including filtering temperature signals, selection of appropriate thermal parameters, and selection of the optimal analytical solution for modeling. This review provides a synthesis of heat tracing using diurnal temperature oscillations, including details on optimal sensor selection and deployment, data processing, model parameterization, and an overview of computing tools available. Recent advances in diurnal temperature methods also provide the opportunity to determine local saturated thermal diffusivity, which can improve the accuracy of fluid flux modeling and sensor spacing, which is related to streambed scour and deposition. These parameters can also be used to determine the reliability of flux estimates from the use of heat as a tracer.     

A study of the geophysical response of distributed fibre optic acoustic sensors through laboratory‐scale experiments

In the past few years, distributed acoustic sensing has gained great interest in geophysics. This acquisition technology offers immense improvement in terms of efficiency when compared with current geophysical acquisition methods. However, the fundamentals of the measurement are still not fully understood because direct comparisons of fibre data with conventional geophysical sensors are difficult during field tests. We present downscaled laboratory experiments that enabled us to characterise the relationship between the signals recorded by conventional seismic point receivers and by distributed fibre optic sensors. Interrogation of the distributed optical fibre sensor was performed with a Michelson interferometer because this system is suited to compact test configurations, and it requires only a very simple data processing workflow for extracting the signal outputs. We show acoustic data that were recorded simultaneously by both the fibre optical interferometer and conventional three‐component accelerometers, thus enabling the comparison of sensor performance. We present results focused on the directionality of fibre measurements, on the amplitude variation with angle of incidence, and on the transfer function that allows accelerometer signals to be transformed into optical fibre signals. We conclude that the optical fibre response matches with the array of the displacement differences of the inline accelerometers deployed along the fibre length. Moreover, we also analysed the influence of various types of coupling and fibre cable coating on the signal responses, emphasising the importance of these parameters for field seismic acquisitions when using the distributed fibre optic technology.     

Microseismic events enhancement and detection in sensor arrays using autocorrelation‐based filtering

Passive microseismic data are commonly buried in noise, which presents a significant challenge for signal detection and recovery. For recordings from a surface sensor array where each trace contains a time‐delayed arrival from the event, we propose an autocorrelation‐based stacking method that designs a denoising filter from all the traces, as well as a multi‐channel detection scheme. This approach circumvents the issue of time aligning the traces prior to stacking because every trace's autocorrelation is centred at zero in the lag domain. The effect of white noise is concentrated near zero lag; thus, the filter design requires a predictable adjustment of the zero‐lag value. Truncation of the autocorrelation is employed to smooth the impulse response of the denoising filter. In order to extend the applicability of the algorithm, we also propose a noise prewhitening scheme that addresses cases with coloured noise. The simplicity and robustness of this method are validated with synthetic and real seismic traces.