Explaining the lack of dynamics in the diffusion of small stationary fuel cells

Using the reaction of hydrogen with oxygen to water in order to produce electricity and heat, promises a high electrical efficiency even in small devices which can be installed close to the consumer. This approach seems to be an impressive idea to contribute to a viable future energy supply under the restrictions of climate change policy. Major reasons currently hampering the diffusion of such technologies for house energy supply in Germany are analysed in this paper. The barriers revealed, include high production costs as well as economic and legal obstacles for installing the devices so that they can be operated in competition to central power plants, beside others in tenancies.fuel cell, diffusion processes, valuation of environmental effects, technological innovation

The Neutralino Sector of the Next-to-Minimal Supersymmetric Standard Model

The Next-to-Minimal Supersymmetric Standard Model (NMSSM) includes a Higgs iso-singlet superfield in addition to the two Higgs doublet superfields of the minimal extension. If the Higgs fields remain weakly coupled up to the GUT scale, as naturally motivated by the concept of supersymmetry, the mixing between singlet and doublet fields is small and can be treated perturbatively. The mass spectrum and mixing matrix of the neutralino sector can be analyzed analytically and the structure of this 5-state system is under good theoretical control. We also determine decay modes and production channels in sfermion cascade decays to these particles at the LHC and pair production in e+e- colliders.Comment: 27 pages, 8 figure

Pragmatisch-kommunikative Störungen – Herausforderungen für Sprachheilpädagogik und Sprachtherapie in Schule und Berufsbildung

Die Frage nach der Partizipation/Teilhabe von Kindern und Jugendlichen mit sprachlichen Beeinträchtigungen ist häufig auch mit ihren pragmatisch-kommunikativen Fähigkeiten verknüpft. Dabei beinhaltet ein kompetentes Sprachhandeln unterschiedliche Teilfähigkeiten und Kompetenzen, welche sprachliche, aber auch soziale, kognitive, kulturelle und emotionale Aspekte beinhalten. Dieses interdisziplinäre Themenfeld verlangt nach einer multiprofessionellen Unterstützung von Kindern und Jugendlichen mit eingeschränkten pragmatisch-kommunikativen Fähigkeiten. (DIPF/Orig.

Removal of per- and polyfluoroalkyl substances (PFASs) in a full-scale drinking water treatment plant: Long-term performance of granular activated carbon (GAC) and influence of flow-rate

Per- and polyfluoroalkyl substances (PFASs) have been ubiquitously detected in drinking water whichposes a risk for human exposure. In this study, the treatment efficiency for the removal of 15 PFASs was examined in a full-scale drinking water treatment plant (DWTP) in the City of Uppsala, Sweden, over aperiod of two years (2015-2017). Removal of the five frequently detected PFASs was influenced by the total operation time of granular activated carbon (GAC)filters, GAC type and surface loading rate. The average removal efficiency of PFASs ranged from 92 to 100% for “young” GAC filters and decreased to 7.0-100% for “old” GAC filters (up to 357 operation days, 29 300 bed volumes (BV) treated). Flow-rates were adjusted in two full-scale GAC filters of different operational age to examine the removal of PFAS and organic matter depending on GAC operational age and operating flow. The decrease inflow-rate by10 L s(-1) from 39 to 29 L s(-1) led to an average increase of 14% and 6.5% in total PFAS removal efficiency for an “old”(264 operation days, 21 971 BV treated) and a “young” GAC filter (63 operation days, 5 725 BV treated), respectively. A cost-analysis for various operation scenarios illustrated the dominating effect of treatment goals and costs for GAC regeneration on overall GAC operation costs. The unit costs for GAC filters ranged from 0.08 to 0.10 E(-3) water treated and 0.020-0.025Vm E(-3) water treated for a treatment goal of 10 ng L(-1)and 85 ng L(-1), respectively, for Sigma(11)PFAS. Furthermore, it was concluded that prolonging the GAC service life by lowering the flow-rates after reaching the treatment goal could lead to a 26% cost-deduction. The results and methods presented in this study give drinking water providers valuable toolsfor the operation of a full-scale treatment train for the removal of PFAS in contaminated raw water

Dark matter constraints on the parameter space and particle spectra in the nonminimal SUSY standard model

We investigate the dark matter constraints for the nonminimal SUSY standard model (NMSSM). The cosmologically restricted mass spectra of the NMSSM are compared to the minimal SUSY standard model (MSSM). The differences of the two models concerning the neutralino, sfermion and Higgs sector are discussed. The dark matter condition leads to cosmologically allowed mass ranges for the SUSY particles in the NMSSM: m_{\tilde{\chi}^0_1} < 300 GeV, m_{\tilde{e}_R} < 300 GeV, 300 GeV < m_{\tilde{u}_R} < 1900 GeV, 200 GeV < m_{\tilde{t}_1} < 1500 GeV, 350 GeV < m_{\tilde{g}} < 2100 GeV and for the mass of the lightest scalar Higgs m_{S_1} < 140 GeV.Comment: revised version to appear in Phys. Lett. B, 18 pages, LaTeX, 3 figures, uses epsfig.sty and amssymb.st

Synthesis of separation processes with reinforcement learning

This paper shows the implementation of reinforcement learning (RL) in commercial flowsheet simulator software (Aspen Plus V12) for designing and optimising a distillation sequence. The aim of the SAC agent was to separate a hydrocarbon mixture in its individual components by utilising distillation. While doing so it tries to maximise the profit produced by the distillation sequence. All actions of the agent were set by the SAC agent in Python and communicated in Aspen Plus via an API. Here the distillation column was simulated by use of the build-in RADFRAC column. With this a connection was established for data transfer between Python and Aspen and the agent succeeded to show learning behaviour, while increasing profit. Although results were generated, the use of Aspen was slow (190 hours) and Aspen was found unsuitable for parallelisation. This makes that Aspen is incompatible for solving RL problems. Code and thesis are available at https://github.com/lollcat/Aspen-R

Normal values of distal radioulnar translation assessed by three-dimensional C-arm scans: a cadaveric study

We investigated whether mobile C-arm cone beam computer tomography (CBCT) could be used to measure radioulnar translation. The study was conducted on 31 Thiel-fixed intact cadaver arms. Three-dimensional scans of each wrist were carried out in pronation and supination. Four established measurement methods were used (radioulnar line, subluxation ratio, epicentre and radioulnar ratio methods) to measure radioulnar translation. The intraclass correlation coefficient for inter-observer and intra-observer reliability were excellent in three of four methods (>0.94). The reference ranges for physiological radioulnar translation were between -30% and 91% (radioulnar line method), -32% and 87% (subluxation ratio method), -40% and 23% (epicentre method), and 2% and 73% (radioulnar ratio method). Our results indicate that radioulnar translation in the distal radioulnar joint can be determined reliably using mobile C-arm CBCT. The normal values provide a basis for further experimental and clinical studies

A Comprehensive Approach for an Approximative Integration of Nonlinear-Bivariate Functions in Mixed-Integer Linear Programming Models

As decentralized energy supply units, microgrids can make a decisive contribution to achieving climate targets. In this context, it is particularly important to determine the optimal size of the energy components contained in the microgrids and their optimal operating schedule. Hence, mathematical optimization methods are often used in association with such tasks. In particular, mixed-integer linear programming (MILP) has proven to be a useful tool. Due to the versatility of the different energetic components (e.g., storages, solar modules) and their special technical characteristics, linear relationships can often only inadequately describe the real processes. In order to take advantage of linear solution techniques but at the same time better represent these real-world processes, accurate and efficient approximation techniques need to be applied in system modeling. In particular, nonlinear-bivariate functions represent a major challenge, which is why this paper derives and implements a method that addresses this issue. The advantage of this method is that any bivariate mixed-integer nonlinear programming (MINLP) formulation can be transformed into a MILP formulation using this comprehensive method. For a performance comparison, a mixed-integer quadratic constrained programming (MIQCP) model—as an MINLP special case—is applied and transformed into a MILP, and the solution of the transformed problem is compared with the one of the MIQCP. Since there are good off-the-shelf solvers for MIQCP problems available, the comparison is conservative. The results for an exemplary microgrid sizing task show that the method delivers a strong performance, both in terms of approximation error (0.08%) and computation time. The method and its implementation can serve as a general user-tool but also as a basis for further methodological developments and research