Example Of Such Application Research Articles

Intensified Tpx3Cam, a fast data-driven optical camera with nanosecond timing resolution for single photon detection in quantum applications

We describe a fast data-driven optical camera, Tpx3Cam, with nanosecond scale timing resolution and 80 Mpixel/sec throughput. After the addition of intensifier, the camera is single photon sensitive with quantum efficiency determined primarily by the intensifier photocathode. The single photon performance of the camera was characterized with results on the gain, timing resolution and afterpulsing reported here. The intensified camera was successfully used for measurements in a variety of applications including quantum applications. As an example of such application, which requires simultaneous detection of multiple photons, we describe registration of photon pairs from the spontaneous parametric down-conversion source in a spectrometer. We measured the photon wavelength and timing with respective precisions of 0.15 nm and 3 ns, and also demonstrated that the two photons are anti-correlated in energy.

Frequently Used Conceptual Frameworks and Design Principles for Extended Reality in Health Professions Education.

Health professions education (HPE) has witnessed a dramatic increase in the use of extended reality (XR), but there is limited evidence that conceptual frameworks are being effectively employed in the design and implementation of XR. This paper introduces commonly utilized conceptual frameworks that can support the integration of XR into the learning process and design principles that can be helpful for the development and evaluation of XR educational applications. Each framework and design principle is summarized briefly, followed by a description of its applicability to XR for HPE and an example of such application.

Gamma-ray spectroscopy using angular distribution of Compton scattering

We present a novel method to perform gamma-ray spectroscopy suitable for extreme pileup situations, wherein traditional pulse-height spectroscopy is infeasible or impractical. One example of such application is spectral characterization of intense laser-based radiation sources that employ laser wakefield acceleration, in which a large number of photons can be produced in a well-collimated beam on a picosecond or shorter timescale. The method relies on the angularly-resolved calorimetric measurement of Compton scattering. The probability for a photon to undergo Compton scattering into a given solid angle is a function of its energy and is described by the Klein–Nishina formula. By first Compton scattering the incident beam and then measuring the total energies deposited in multiple detectors placed at various scattering angles, the incident beam energy spectrum can be reconstructed without resolving the individual events in detectors. We compare the performance of an maximum likelihood expectation maximization algorithm with that of an artificial neural network to measure the energy spectrum of a beam of monoenergetic gamma rays from 137Cs decay. We demonstrate that the method can be used to reconstruct the characteristic inverse Compton scattering spectra.

Isotropic Atomic Layer Etching in High Aspect Ratio Structures

Isotropic Atomic Layer Etching can be used to remove materials such as high-k oxides or certain metals from high aspect ratio (HAR) structures from sidewalls and even non-line-of-site locations where access via reactive ion etching would be challenging or impossible. Those locations could be sites below the shelves in 3D-NAND stacks or around wires in GAA structures.The etch rate per cycle of Thermal Isotropic ALE should in principle be insensitive to aspect ratio and line-of-sight accessibility if both reaction steps are fully saturated. Deviations from the ideal behavior have been reported previously for Al2O3 ALE with alternating HF and DMAC cycles [1]. Without mitigation, this behavior would ultimately lead to performance differences in devices located at the bottom of the structure compared to those at the top.In this work we present a method to counteract the unwanted depth dependence of the etch rate when etching HfO2 with the HF/DMAC ligand exchange ALE process. To mitigate the depth dependence, we explored the use of operating the ALE process at ultra-high pressures up to 5 Torr and over a wide temperature range. We found that under these conditions, the modification step has been boosted such that it takes place near its saturation regime so that top-to-bottom etch rate differences could be reduced. We show that high pressure and temperature mostly target the fluorine profile along a structure and removal step times needed to be allowed sufficient time to clear the entire modified layer. We give an example of such application in a 50:1 aspect ratio 3D NAND test structure.

Linking Scalar Elastodynamics and Non-Hermitian Quantum Mechanics

Recent years have seen a fascinating pollination of ideas from quantum theories to elastodynamics---a theory that phenomenologically describes the time-dependent macroscopic response of materials. Here, we open route to transfer additional tools from non-Hermitian quantum mechanics. We begin by identifying the differences and similarities between the one-dimensional elastodynamics equation and the time-independent Schrodinger equation, and finding the condition under which the two are equivalent. Subsequently, we demonstrate the application of the non-Hermitian perturbation theory to determine the response of elastic systems; calculation of leaky modes and energy decay rate in heterogenous solids with open boundaries using a quantum mechanics approach; and construction of degeneracies in the spectrum of these assemblies. The latter result is of technological importance, as it introduces an approach to harness extraordinary wave phenomena associated with non-Hermitian degeneracies for practical devices, by designing them in simple elastic systems. As an example of such application, we demonstrate how an assembly of elastic slabs that is designed with two degenerate shear states according to our scheme, can be used for mass sensing with enhanced sensitivity by exploiting the unique topology near the exceptional point of degeneracy.

Geostatistical modelling of soil contamination with arsenic, cadmium, lead, and nickel: the Silesian voivodeship, Poland case study

The increasing number of spatial data sets permits their application for minimising the duration and cost of such research. An example of such application is geostatistical modelling. Data on the quality of atmospheric air can be used for the assessment of the quality of soil in a given area. The objective of the study was an attempt to apply geostatistical methods in the estimation of the degree of soil contamination with selected heavy metals resulting from deposition from atmospheric air. This paper uses data obtained from the State Environmental Monitoring (data on the quality of atmospheric air) and other collections of publicly available spatial data for the purpose of analysis of the state of quality of soils in the province of Silesia in Poland. Conducted analyses revealing that contamination with lead in atmospheric air in the Silesian voivodeship considerably exceeds acceptable values, and the load of lead deposition is largely transferred to the soil. The paper also presents geochemical maps necessary to understand sources of soil contamination, including their natural content.

Konstanz Method of Dilemma-Discussion (KMDD®) an its application in the process of ethical education of psychologists

Psychologist are the representatives of a profession in which a wellbeing of a person is the paramount. Helping activity requires of psychologists to follow not only professional ethics but also moral norms. Not rarely do psychologists face the necessity to consider moral dilemmas connected with the practice of delivering psychological services. In such cases, a psychologist should be able to use not only professional knowledge, but also a moral competency allowing him or her to put in practice the assumptions of autonomous morality which is in agreement with his or her personal and professional identity. It is hard to find formal programs of stimulation of moral competence dedicated directly for psychologists. However, there is a possibility of using Konstanz Method of Dilemma-Discussion (KMDD®) in order to achieve this goal. Konstanz Method of Dilemma-Discussion developed by professor Georg Lind from the University of Konstanz – a student and a critic of L. Kohlberg – is used in many countries all over the world in order to increase the level of moral development by developing moral competency mainly in the area of education. An increasing interest of researchers in the method also results in searching for new possibilities of applications of the method. An example of such application would be an area of psychologists’ work. The article aims to promote the KMDD® method in the course of ethical and professional education and self-development of psychologists.

Efficient algorithms to identify periodic patterns in multiple sequences

Periodic pattern mining is a popular data mining task, which consists of identifying patterns that periodically appear in data. Traditional periodic pattern mining algorithms are designed to find patterns in a single sequence. However, in several domains, it is desirable to discover patterns that are periodic in many sequences. An example of such application is market basket analysis. Given a database of sequences of transactions made by customers, discovering sets of items that are periodically bought by customers can help understand customer behavior. To discover periodic patterns common to multiple sequences, this paper extends the traditional problem of mining periodic patterns in a sequence. Two novel measures are defined called the standard deviation of periods and the sequence periodic ratio. Two algorithms are proposed to mine these patterns efficiently called MPFPSBFS and MPFPSDFS, which perform a breadth-first search and depth-first search, respectively. Because the sequence periodic ratio is neither monotone nor anti-monotone, these algorithms rely on a novel upper-bound called boundRa and two novel search space pruning properties to find periodic patterns efficiently. The algorithms have been evaluated on multiple datasets. Results show that they are efficient and can filter numerous non periodic itemsets to identify periodic patterns.

THz characterization and demonstration of visible-transparent/terahertz-functional electromagnetic structures in ultra-conductive La-doped BaSnO3 Films

We report on terahertz characterization of La-doped BaSnO3 (BSO) thin-films. BSO is a transparent complex oxide material, which has attracted substantial interest due to its large electrical conductivity and wide bandgap. The complex refractive index of these films is extracted in the 0.3 to 1.5 THz frequency range, which shows a metal-like response across this broad frequency window. The large optical conductivity found in these films at terahertz wavelengths makes this material an interesting platform for developing electromagnetic structures having a strong response at terahertz wavelengths, i.e. terahertz-functional, while being transparent at visible and near-IR wavelengths. As an example of such application, we demonstrate a visible-transparent terahertz polarizer.

Hybrid backward simulator for determining causal heater state with resolution improvement of measured temperature data through model conformation

<p class="Abstract">We are developing a backward simulator, which determines the unknown system input from the system output by using a system model. However, its processing time would increase enormously if the simulation model requires the multiple case branching, which is typical for backward simulations. In some target applications, we can use forward simulation processing in the backward data flow with significant reduction of processing time. This paper shows an example of such application to determine system input of heater operation from measured data of room temperature. Although the resolution of measurement restricts the performance of the simulation result, we also used the model to improve the resolution of measured data and show its effect to simulation. Furthermore, we show the result of reduction of noise caused by quantizing LSB jitters.</p>

3D Printed Electrophoretic Lab-on-chip for DNA Separation

In this paper we present for the first time inkjet 3D printed lab-on-a-chip for DNA analyse by on-chip gel electrophoresis. Separation of 50÷800bp DNA ladder was successfully performed. According to our best knowledge it is the first example of such application of 3D printed microfluidics structure. Thanks to advantages of 3D printing it is possible to develop lab-on-a-chip with user defined configuration with less than 3hours and estimated costs pre chip less than 1 EUR.

Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations.

The detrended cross-correlation coefficient ρ(DCCA) has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρ(DCCA) works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρ(DCCA) that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρ(q) not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρ(q) works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q-dependent counterpart of the correlation matrices and then to the network representation.

Norm--Free Radon--Nikodym Approach to Machine Learning

For Machine Learning (ML) classification problem, where a vector of 𝒙--observations (values of attributes) is mapped to a single 𝐲 value (class label), a generalized Radon--Nikodym type of solution is proposed. Quantum--mechanics like probability states ψ²(𝒙) are considered and Cluster Centers'', corresponding to the extremums of 〈𝐲ψ²(𝒙)〉/〈ψ²(𝒙)〉, are found from generalized eigenvalues problem. The eigenvalues give possible 𝐲 outcomes and corresponding to them eigenvectors ψ(𝒙) define the Cluster Centers''. The projection of a ψ state, localized at given 𝒙 to classify, on these eigenvectors define the probability of 𝐲 outcome, thus avoiding using a norm (L² or other types), required for a quality criteria in a typical Machine Learning technique. A coverage of each Cluster Center'' is calculated, what potentially allows to separate system properties (described by 𝐲 outcomes) and system testing conditions (described by 𝐂 coverage). As an example of such application 𝐲 distribution estimator is proposed in a form of pairs (𝐲,𝐂), that can be considered as Gauss quadratures generalization. This estimator allows to perform 𝐲 probability distribution estimation in a strongly non--Gaussian case.

Forward osmosis: understanding the hype

AbstractThe scientific interest in forward osmosis has increased dramatically over the last decade. The hype has resulted in a high scientific production, but research activities seem to go in all directions, and the real benefits of the process are not always well understood. This paper aims to give some directions based on the current state of the art. Without going into details about the process itself, the current research lines and their background are described. While some of these are important, others – notably the search for alternative draw solutions – have become the Holy Grail of forward osmosis. The further analysis of the process is based on suggested applications and uses the observations made on contemporary research topics in the field. At first, direct application of forward osmosis for potable water production is considered. This leads back to the research challenges of the reverse draw solute flux, concentration polarization, and the regeneration of the draw solution. Special attention is given to desalination, as forward osmosis is often incorrectly denoted as a desalination technology. It can be used in the context of desalination; however, the question remains in which applications this is of interest. Combining desalination and wastewater treatment is one such interesting application, which is further described in this paper for some types of wastewater found in the literature. In the last part, the paper emphasizes the need to develop processes in which the challenge of the draw solution is intrinsically solved. The foremost example of such application is the one for which forward osmosis was developed four decades ago: the use of impaired water sources diluted through a forward osmosis membrane by using a concentrated fertilizer solution to provide osmotic pressure. This application was suggested four decades ago but was never applied on any scale. Process economics and an insufficiently developed technology may have been the basis of this failure. However, a renewed focus on such applications would allow forward osmosis to come to its real potential and contribute to solving the global water challenge.

Time Delay Estimation in Two-Phase Flow Investigation Using theγ-Ray Attenuation Technique

Time delay estimation is an important research question having many applications in a range of technologies. Measurement of a two-phase flow in a pipeline or an open channel using radioisotopes is an example of such application. For instance, the determination of velocity of dispersed phase in that case is based on estimation of the time delay between two stochastic signals provided by scintillation probes. The proper analysis of such signals, usually in presence of noise, requires the use of advanced statistical signal processing. In this paper, the simulation studies of time delay estimation were carried out with the use of the following differential methods: average magnitude difference function, and average square difference function and proposed combined methods comprising the above-mentioned differential and cross-correlation functions are presented. Attached simulations have been carried out for models of stochastic signals corresponding to the signals obtained in gamma-ray absorption measurements of gas-liquid flow in a horizontal pipeline. The standard uncertainties of time delay estimations have been determined for each of the methods. Improved metrological properties have been stated in the combined methods in comparison with the classical cross-correlation procedure.

ENteric Immunity SImulator: A Tool for In Silico Study of Gastroenteric Infections

Clinical symptoms of microbial infection of the gastrointestinal (GI) tract are often exacerbated by inflammation induced pathology. Identifying novel avenues for treating and preventing such pathologies is necessary and complicated by the complexity of interacting immune pathways in the gut, where effector and inflammatory immune cells are regulated by anti-inflammatory or regulatory cells. Here we present new advances in the development of the ENteric Immunity SImulator (ENISI), a simulator of GI immune mechanisms in response to resident commensal bacteria as well as invading pathogens and the effect on the development of intestinal lesions. ENISI is a tool for identifying potential treatment strategies that reduce inflammation-induced damage and, at the same time, ensure pathogen removal by allowing one to test plausibility of in vitro observed behavior as explanations for observations in vivo, propose behaviors not yet tested in vitro that could explain these tissue-level observations, and conduct low-cost, preliminary experiments of proposed interventions/treatments. An example of such application is shown in which we simulate dysentery resulting from Brachyispira hyodysenteriae infection and identify aspects of the host immune pathways that lead to continued inflammation-induced tissue damage even after pathogen elimination.

On Practical Implementation and Generalizations of $ \max^{\ast}$ Operator for Turbo and LDPC Decoders

In this paper, we deal with practical implementation issues of the max* operation in generalized form used for decoding of both turbo and low-density-parity-check (LDPC) codes. In particular, first, a unified framework for the so-called generalized max* operation is established, which includes most of the previously published algorithms already known for turbo decoding. Next, the hardware architectures used for the practical implementation of the generalized max* operation, which is derived from this novel framework, are revealed for the first time and further analyzed, in terms of hardware complexity reduction. It is also shown how this generalized max8 operation can be adopted in LDPC decoding, achieving essentially optimal bit error rate performance with small computational complexity against other algorithms in joint turbo-LDPC architectures. This solution is useful in applications where joint decoding architectures are deployed to decode both turbo and LDPC codes. An important example of such application is in software radio receivers of 4G wireless communication systems, such as those proposed in conjunction with the WiMAX standard.

International Law and its Application: Biodiversity and International Obligations Derived from Natural Genetic Resources in Costa Rica

La distribución de los beneficios derivados de la utilización de los recursos naturales genéticos es uno de los principales problemas abordados por el Convenio sobre la Diversidad Biológica, aun cuando la obligación de los Estados miembros a adoptar medidas legales, administrativas y de política con respecto a su aplicación a nivel nacional, porque todos los Estados miembros (países en desarrollo y desarrollados) deben cumplir con el principio pacta sunt servanda. El no respetar esta obligación de derecho internacional derivada de un tratado internacional resulta en una violación de las obligaciones internacionales. Es posible encontrar un ejemplo de tal aplicación. Este artículo se centra en la interpretación del artículo 15. 7 de la Convención sobre la Diversidad Biológica para aplicar esta obligación internacional a derechos y obligaciones legales internos, para cumplir con la obligación y el segundo paso, la aplicación de esta normativa legal nacional en el territorio de un Estado, Costa Rica.

A program for the Bayesian Neural Network in the ROOT framework

We present a Bayesian Neural Network algorithm implemented in the TMVA package (Hoecker et al., 2007 [1]), within the ROOT framework (Brun and Rademakers, 1997 [2]). Comparing to the conventional utilization of Neural Network as discriminator, this new implementation has more advantages as a non-parametric regression tool, particularly for fitting probabilities. It provides functionalities including cost function selection, complexity control and uncertainty estimation. An example of such application in High Energy Physics is shown. The algorithm is available with ROOT release later than 5.29. Program summary Program title: TMVA-BNN Catalogue identifier: AEJX_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEJX_v1_0.html Program obtainable from: CPC Program Library, Queenʼs University, Belfast, N. Ireland Licensing provisions: BSD license No. of lines in distributed program, including test data, etc.: 5094 No. of bytes in distributed program, including test data, etc.: 1,320,987 Distribution format: tar.gz Programming language: C++ Computer: Any computer system or cluster with C++ compiler and UNIX-like operating system Operating system: Most UNIX/Linux systems. The application programs were thoroughly tested under Fedora and Scientific Linux CERN. Classification: 11.9 External routines: ROOT package version 5.29 or higher ( http://root.cern.ch) Nature of problem: Non-parametric fitting of multivariate distributions Solution method: An implementation of Neural Network following the Bayesian statistical interpretation. Uses Laplace approximation for the Bayesian marginalizations. Provides the functionalities of automatic complexity control and uncertainty estimation. Running time: Time consumption for the training depends substantially on the size of input sample, the NN topology, the number of training iterations, etc. For the example in this manuscript, about 7 min was used on a PC/Linux with 2.0 GHz processors.

Discrete and continuum methods for numerical simulations of non‐linear wave propagation in discontinuous media

AbstractThe main objective of this paper is to develop a methodology to model dynamic loading of various discontinuous media. Two methods for modeling non‐linear waves in a media with multiple discontinuities are considered. The first one, a discrete method, is based on the Simple Common Plane contact algorithm. This method can be applied both to compliant contacts characterized by finite thickness and elastic moduli (such as joints in geomechanics) as well as to non‐compliant frictional contacts traditionally described by the slide lines in finite element/finite difference codes. The second one, a continuum method, assumes that the contacts are not compliant and can be modeled as one or several weakness planes cutting through the elements of the computational mesh. Both discrete and continuum methods described in the paper can be applied to derive equivalent continuum properties for media with multiple discontinuities. An example of such application for a randomly jointed media is given in the paper. Copyright © 2010 John Wiley & Sons, Ltd.