The Uncertain Structure of Process Review in the EU: Beyond the Debate on the CJEU’s Weiss Ruling and the German Federal Constitutional Court’s PSPP Ruling

The obligation to provide reasons (e.g. in Art. 296 TFEU) may appear rather a simple and straightforward, but in actual practice—as the mutually antagonistic Weiss rulings of the CJEU and the German Bundesverfassungsgericht (“BVG”) amply demonstrate—is fraught with constitutional complication. On the one side, there lies the concern with a deeply intrusive form of judicial review which substitutes judicially determined “good” reasons for those of the reviewee decisionmaker—legislatures, administrative agencies, or, as in Weiss, the European Central Bank (ECB). On the other side lies the concern with judicial abdication in the face of technical expertise, uncertainty and complexity, turning the reason-giving requirement into a mere façade thereby placing democratic accountability in the modern administrative state beyond law’s remit. Either way, normatively and conceptually, we seem left with a half-way house only. Drawing on the recent US administrative law discourse—the neo-Fullerian concept of an “internal morality of law” (Sunstein / Vermeule) and democratic experimentalism (Sabel / Kessler)—this paper explores the concept of process review as tertium datur. Process review responds to concerns over the rule of law and administrative discretion through indirect, procedural safeguards, by imposing requirements of reasoned justification, rather than through wholesale invalidation or aggressive substantive review.

Adaptive Identification and Application of Flow Mapping and Inverse Flow Mapping for Electrohydraulic Valves

Good estimation of flow mapping (FM) and inverse flow mapping (IFM) for electrohydraulic valves are important in automation of fluid power system. The purpose of this paper is to propose adaptive identification methods based on LSM, BPNN, RBFNN, GRNN, LSSVM and RLSM to estimate the uncertain structure and parameters in flow mapping and inverse flow mapping for electrohydraulic valves. In order to reduce the complexity and improve the identification performance, model structures derived from new algorithm are introduced. The above identification methods are applied to map the flow characteristic of an electrohydraulic valve. With the help of novel simulation architecture via OPC UA, the accuracy and efficiency of these algorithms could be verified. Some issues like invertibility of flow mapping are discussed. At last, places and suggestions to apply these methods are made.

Dynamic Reliability Evaluation by First-Order Reliability Method Integrated with Stochastic Pseudo Excitation Method

The stochastic pseudo excitation method (SPEM), which is based on the principle of pseudo excitation method (PEM), is introduced to represent the randomness of dynamic input in which the amplitude of excitation is adopted as a random variable. Based on the mathematic definition of power spectral density, a physical interpolation of the SPEM is discussed. Even if one random variable is involved in calculation, the effects of the uncertainties are required to be investigated. The SPEM offers a simple but quite effective way to solve the dynamic reliability problem. Through integrating the new algorithm into first-order reliability method (FORM), the dynamic reliability of uncertain structure subjected to random excitation is studied. A linear oscillator with three types of white noise is adopted to verify the SPEM for dynamic reliability of linear random vibration analysis. Also, the accuracy and efficiency of SPEM to handle the multi-degree-of-freedom structure is investigated in this paper.

Shipyard location selection based on fuzzy AHP and TOPSIS

The shipyard facility location selection (FLS) decision is a critical process that involves conflicting, qualitative, and quantitative criteria. Multi-Attribute Decision Making (MADM) methods are used as a powerful tool to overcome this complex problem. Today, using these methods in an integrated way, more accurate, efficient, and systematic results are obtained in solving complex issues such as FLS, which contains an uncertain structure. This paper proposes a framework for the weighting of criteria and ranking potential feasible locations (alternatives) using the combination of fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) methods. While fuzzy AHP determines the importance values of the criteria by pairwise comparisons, fuzzy TOPSIS prioritizes the alternatives using the relative weights obtained with Fuzzy AHP. The integration of these two techniques provides a robust approach considering the results obtained for the shipyard FLS decision. The applicability of the proposed method is expressed in Turkey by a case study of the shipyard FLS decision.

Structural Dynamic Load and Parameter Identification Based on Dummy Measurements of Displacement

Structural load and parameter identification are the essential contents in the field of structural dynamics, and some studies pay attention to the coupled recognition of uncertain structure parameters as well as unacquainted loads. Gillijns and De Moor presented the Kalman-type filter, which was used in the work for coupled identification as the unabbreviated form of GDF. However, it has been demonstrated that it is unstable for the extended GDF (EGDF) method, drifting in the identified unacquainted loads as well as displacement, just like most previous identification methods based on the least-square algorithm. In order to deal with this unstable issue, this paper applied the dummy measurements of displacements on a position level and modifies the EGDF algorithm using the information integration method about the accelerated measurements with dummy measurements. Numerical example of a truss is used for validating the applicability of the method in the work, and an influence of covariance matrices in dummy displacements is also considered.

Distributed Load Identification for Uncertain Structure Based on LHS-GA and Improved L-Curve Method

In order to identify the upper and lower bounds of distributed force exciting on an uncertain structure, a comprehensive approach combining genetic algorithm based on Latin hypercube sampling (LHS-GA) and improved L-curve method is built up in this paper. For uncertain parameter expressed by interval form, LHS-GA is presented to seeking the maximum and minimum amplitudes of distributed load in the interval. Aiming at distributed load reconstruction for a specific sampling point in the interval, which is the objective function of LHS-GA, the traditional L-curve method is improved to weaken the ill-posedness problem and obtain accurate distributed force amplitude. Numerical example results indicate the comprehensive method is able to acquire precise bounds of distributed load. Meanwhile, it possesses a strong anti-noise performance.

Non-Probabilistic Robust Equilibrium Optimization of Complex Uncertain Structures

Robust optimization of complex uncertain structures usually involves multiple conflicting and competing structural performance indices. Present approaches for achieving the final design of such an optimization problem always involve a decision-making process, which is a demanding task that requires the rich experience and expert skills of designers. To overcome the difficulty, an interval robust equilibrium optimization approach is proposed to find the optimal design of complex uncertain structure based on the robust equilibrium strategy for multiple conflicting and competing structural performance indices. Specifically, a new concept of closeness and crossing coefficient between interval boundaries (CCCIBs) is proposed at first, based on which the tri-dimensional violation vectors of all interval constraints can be calculated and the feasibility of a design vector can be assessed. Then, the robust equilibrium assessment of multiple objective and constraint performance indices is investigated, based on the results of which the feasible design vectors can be directly ranked according to the robust equilibrium strategy for all structural performance indices. Subsequently, the algorithm for the robust equilibrium optimization of complex uncertain structures is developed by integrating the Kriging technique and nested genetic algorithm. The validity, effectiveness, and practicability of the proposed approach are demonstrated by two illustrative examples.

Force Reconstruction for Uncertain Structure Based on Interval Model and Second-Order Perturbation Theory

In order to reconstruct the upper and lower bounds of dynamic excitations applied on the uncertain structure, an algorithm based on interval model and second-order perturbation theory is presented in this paper. First, interval model is built up by expressing the uncertain parameters of structure in interval form. Next according to second-order perturbation theory, structure characteristic matrices and input force vector are approximated as second-order Taylor polynomial expansion at the midpoint of uncertain parameters. After that the input force’s midpoint, first-order and second-order partial derivatives are respectively calculated by existing step-by-step integration method. Then addition and subtraction of the three components obtained in previous step are operated. Ultimately the upper and lower bounds of dynamic load can be identified. Numerical simulation results demonstrate this method is with the characteristic of high efficiency and precision. In addition, it is able to remain a relatively strong robustness under noise turbulence.

Disentangling a Complex Response in Cell Reprogramming and Probing the Waddington Landscape by Automatic Construction of Petri Nets

We analyzed the developmental switch to sporulation of a multinucleate Physarum polycephalum plasmodial cell, a complex response to phytochrome photoreceptor activation. Automatic construction of Petri nets from trajectories of differential gene expression in single cells revealed alternative, genotype-dependent interconnected developmental routes and identified metastable states, commitment points, and subsequent irreversible steps together with molecular signatures associated with cell fate decision and differentiation. Formation of transition-invariants in mutants that are locked in a proliferative state is remarkable considering the view that oncogenic alterations may cause the formation of cancer attractors. We conclude that the Petri net approach is useful to probe the Waddington landscape of cellular reprogramming, to disentangle developmental routes for the reconstruction of the gene regulatory network, and to understand how genetic alterations or physiological conditions reshape the landscape eventually creating new basins of attraction. Unraveling the complexity of pathogenesis, disease progression, and drug response or the analysis of attractor landscapes in other complex systems of uncertain structure might be additional fields of application.