Couchsurfing with Bateson: An ecology of digital platforms

Digital platforms radically alter socio-economic and organizational patterns. In an ecological sense, they enable the rapid extension of tolerance limits by digitally scaling variables such as the availability of accommodation or labour. However, such maximization of specific variables in a complex ecology bears the danger of pathological runaway patterns. In our paper we draw on the work of Gregory Bateson to outline an analytical approach for the study of digital platforms as ecological phenomena, focussing on the effects of digitalization on the context in which platforms operate. To study such meta-patterns, we elaborate three interrelated concepts: stress, adaptation and budgets of flexibility. We exemplify these ideas through a longitudinal study of the early digital platform Couchsurfing and develop implications for our understanding of technology and organization.

TAX SUPPORT EVALUATION FOR R&D ACTIVITIES OF COMPANIES

The article evaluates the impact of tax support for R&D on the volume of R&D outputs generated by companies. The number of patent applications was chosen as the R&D metric for business output. Both linear dependence using linear regression and non-linear dependence using decision trees were used within the research. The significance of indirect support in the context of other sources of funding R&D activities of companies was primarily assessed. The dependence of the number of patent applications on individual sources of financing of the Business Enterprise Expenditure on R&D was examined. Even after scaling variables, the research in the period under review confirmed the strongest dependence between the number of patent applications and the financial resources provided by the Business enterprise sector for all countries surveyed. Subsequently, the model reduced by the impact of Business enterprise sector resources was created. Of the three remaining variables considered, the analysis showed the strongest dependence of the number of patent applications on the amount of indirect support. The research points to the fact that impact of tax support on the volume of relevant R&D outputs is relatively significant.

Evaluation of Profiles of Standard Deviation of Vertical Wind in the Urban Area of Rome: Performances of Monin–Obukhov Similarity Theory Using Different Scaling Variables

The parametrizations of meteorological variables provided by the Monin–Obukhov similarity theory (MOST) is of major importance for pollutant dispersion assessment. However, the complex flow pattern that characterizes the urban areas limits the applicability of the MOST. In this work, the performance of different existing parametrizations of the standard deviation of vertical wind velocity were tested in the city of Rome. Results were compared with experimental data acquired by a sonic detection and ranging (SODAR) and a sonic anemometer. Different scaling variables estimated from the anemometer data by considering two coordinate systems—one aligned with the geodetic reference frame and the other following the flow streamlines—were used to evaluate the effects of flow distortion due to the presence of buildings. Results suggest that the MOST parametrizations perform better if the scaling variables obtained using the coordinate system following the flow streamlines are used. This estimation of the scaling variables would make it possible to overcome the difficulties in conducting measurements of turbulent fluxes, either at different altitudes or even in the constant flux layer.

Scaling of Phase Diagram and Critical Point Parameters in Liquid-Vapour Phase Transition of Metallic Fluids

The first objective of this paper is to investigate the scaling behavior of liquid-vapor phase transition in FCC and BCCmetals starting from the zero-temperature four-parameter formula for cohesive energy. The effective potentials between the atoms in the solid are determined while using lattice inversion techniques as a function of scaling variables in the four-parameter formula. These potentials are split into repulsive and attractive parts, as per the Weeks–Chandler–Anderson prescription, and used in the coupling-parameter expansion for solving the Ornstein–Zernike equation that was supplemented with an accurate closure. Thermodynamic quantities obtained via the correlation functions are used in order to obtain critical point parameters and liquid-vapor phase diagrams. Their dependence on the scaling variables in the cohesive energy formula are also determined. An equally important second objective of the paper is to revisit coupling parameter expansion for solving the Ornstein–Zernike equation. The Newton–Armijo non-linear solver and Krylov-space based linear solvers are employed in this regard. These methods generate a robust algorithm that can be used to span the entire fluid region, except very low temperatures. The accuracy of the method is established by comparing the phase diagrams with those that were obtained via computer simulation. The avoidance of the ’no-solution-region’ of the Ornstein-Zernike equation in coupling-parameter expansion is also discussed. Details of the method and complete algorithm provided here would make this technique more accessible to researchers investigating the thermodynamic properties of one component fluids.

Scaling of Phase Diagram and Critical Point Parameters in Liquid-Vapour Phase Transition of Metallic Fluids

The first objective of this paper is to investigate the scaling behavior of liquid-vapor phase transition in FCC and BCC metals starting from the zero-temperature four-parameter formula for cohesive energy. The effective potentials between the atoms in the solid are determined using lattice inversion techniques as a function of scaling variables in the above formula. These potentials are split into repulsive and attractive parts as per the Weeks-Chandler-Anderson prescription, and used in the coupling-parameter expansion for solving the Ornstein-Zernike equation supplemented with an accurate closure. Thermodynamic quantities obtained via the correlation functions are used to obtain critical point parameters and liquid-vapor phase diagrams. Their dependence on the scaling variables in the cohesive energy formula are also determined. Equally important second objective of the paper is to revisit coupling parameter expansion for solving the Ornstein-Zernike equation. The Newton-Armijo non-linear solver and Krylov-space based linear solvers are employed in this regard. These methods generate a robust algorithm that can be used to span the entire fluid region, except very low temperatures. Accuracy of the method is established by comparing the phase diagrams with those obtained via computer simulation. Avoidance of the 'no-solution-region' of Ornstein-Zernike equation in coupling-parameter expansion is also discussed. Details of the method and the complete algorithm provided here would make this technique more accessible to researchers investigating thermodynamic properties of one component fluids.

Pooled variable scaling for cluster analysis

Motivation Many popular clustering methods are not scale-invariant because they are based on Euclidean distances. Even methods using scale-invariant distances, such as the Mahalanobis distance, lose their scale invariance when combined with regularization and/or variable selection. Therefore, the results from these methods are very sensitive to the measurement units of the clustering variables. A simple way to achieve scale invariance is to scale the variables before clustering. However, scaling variables is a very delicate issue in cluster analysis: A bad choice of scaling can adversely affect the clustering results. On the other hand, reporting clustering results that depend on measurement units is not satisfactory. Hence, a safe and efficient scaling procedure is needed for applications in bioinformatics and medical sciences research. Results We propose a new approach for scaling prior to cluster analysis based on the concept of pooled variance. Unlike available scaling procedures, such as the SD and the range, our proposed scale avoids dampening the beneficial effect of informative clustering variables. We confirm through an extensive simulation study and applications to well-known real-data examples that the proposed scaling method is safe and generally useful. Finally, we use our approach to cluster a high-dimensional genomic dataset consisting of gene expression data for several specimens of breast cancer cells tissue obtained from human patients. Availability and implementation An R-implementation of the algorithms presented is available at https://wis.kuleuven.be/statdatascience/robust/software. Supplementary information Supplementary data are available at Bioinformatics online.

Sharp lifespan estimates of blowup solutions to semi-linear wave equations with time-dependent effective damping

We consider the initial value problem for a semi-linear wave equation with a time-dependent effective damping term. The interest is the behavior of lifespan of solutions in view of the asymptotic profile of the coefficient of damping as time tends to infinity. A simple case of effective damping and a threshold case in the sense of overdamping were discussed in Ikeda and Wakasugi (2015) and Ikeda and Inui (2019), respectively. We discuss here general damping terms under a certain assumption that is discussed. The result of this paper is the sharp lifespan estimates of blowup solutions including the typical cases treated in previous studies. The proof of the upper bound of lifespan is a modification of the test-function method by Ikeda–Sobajima (2019) and the one of lower bound is based on the technique of scaling variables introduced by Gallay and Raugel (1998) for the one-dimensional case and Wakasugi (2017) for the higher-dimensional case.