A comparison study on jacket substructures for offshore wind turbines based on optimization

The structural optimization problem of jacket substructures for offshore wind turbines is commonly regarded as a pure tube dimensioning problem, minimizing the entire mass of the structure. However, this approach goes along with the assumption that the given topology is fixed in any case. The present work contributes to the improvement of the state of the art by utilizing more detailed models for geometry, costs, and structural design code checks. They are assembled in an optimization scheme, in order to consider the jacket optimization problem from a different point of view that is closer to practical applications. The conventional mass objective function is replaced by a sum of various terms related to the cost of the structure. To address the issue of high demand of numerical capacity, a machine learning approach based on Gaussian process regression is applied to reduce numerical expenses and enhance the number of considered design load cases. The proposed approach is meant to provide decision guidance in the first phase of wind farm planning. A numerical example for a National Renewable Energy Laboratory (NREL) 5&thinsp;MW turbine under FINO3 environmental conditions is computed by two effective optimization methods (sequential quadratic programming and an interior-point method), allowing for the estimation of characteristic design variables of a jacket substructure. In order to resolve the mixed-integer problem formulation, multiple subproblems with fixed-integer design variables are solved. The results show that three-legged jackets may be preferable to four-legged ones under the boundaries of this study. In addition, it is shown that mass-dependent cost functions can be easily improved by just considering the number of jacket legs to yield more reliable results.</p

Mechanical Properties of Boehmite Evaluated by Atomic Force Microscopy Experiments and Molecular Dynamic Finite Element Simulations

Boehmite nanoparticles show great potential in improving mechanical properties of fiber reinforced polymers. In order to predict the properties of nanocomposites, knowledge about the material parameters of the constituent phases, including the boehmite particles, is crucial. In this study, the mechanical behavior of boehmite is investigated using Atomic Force Microscopy (AFM) experiments and Molecular Dynamic Finite Element Method (MDFEM) simulations. Young's modulus of the perfect crystalline boehmite nanoparticles is derived from numerical AFM simulations. Results of AFM experiments on boehmite nanoparticles deviate significantly. Possible causes are identified by experiments on complementary types of boehmite, that is, geological and hydrothermally synthesized samples, and further simulations of imperfect crystals and combined boehmite/epoxymodels. Under certain circumstances, the mechanical behavior of boehmite was found to be dominated by inelastic effects that are discussed in detail in the present work. The studies are substantiated with accompanying X-ray diffraction and Raman experiments.DFG/FOR/202

Strong negative self regulation of Prokaryotic transcription factors increases the intrinsic noise of protein expression

Background Many prokaryotic transcription factors repress their own transcription. It is often asserted that such regulation enables a cell to homeostatically maintain protein abundance. We explore the role of negative self regulation of transcription in regulating the variability of protein abundance using a variety of stochastic modeling techniques. Results We undertake a novel analysis of a classic model for negative self regulation. We demonstrate that, with standard approximations, protein variance relative to its mean should be independent of repressor strength in a physiological range. Consequently, in that range, the coefficient of variation would increase with repressor strength. However, stochastic computer simulations demonstrate that there is a greater increase in noise associated with strong repressors than predicted by theory. The discrepancies between the mathematical analysis and computer simulations arise because with strong repressors the approximation that leads to Michaelis-Menten-like hyperbolic repression terms ceases to be valid. Because we observe that strong negative feedback increases variability and so is unlikely to be a mechanism for noise control, we suggest instead that negative feedback is evolutionarily favoured because it allows the cell to minimize mRNA usage. To test this, we used in silico evolution to demonstrate that while negative feedback can achieve only a modest improvement in protein noise reduction compared with the unregulated system, it can achieve good improvement in protein response times and very substantial improvement in reducing mRNA levels. Conclusions Strong negative self regulation of transcription may not always be a mechanism for homeostatic control of protein abundance, but instead might be evolutionarily favoured as a mechanism to limit the use of mRNA. The use of hyperbolic terms derived from quasi-steady-state approximation should also be avoided in the analysis of stochastic models with strong repressors

KLEIN: A New Family of Lightweight Block Ciphers

Resource-efficient cryptographic primitives become fundamental for realizing both security and efficiency in embedded systems like RFID tags and sensor nodes. Among those primitives, lightweight block cipher plays a major role as a building block for security protocols. In this paper, we describe a new family of lightweight block ciphers named KLEIN, which is designed for resource-constrained devices such as wireless sensors and RFID tags. Compared to the related proposals, KLEIN has advantage in the software performance on legacy sensor platforms, while in the same time its hardware implementation can also be compact

Interleukin-1β Maturation Triggers Its Relocation to the Plasma Membrane for Gasdermin-D-Dependent and -Independent Secretion

IL-1β requires processing by caspase-1 to generate the active, pro-inflammatory cytokine. Acute IL-1β secretion from inflammasome-activated macrophages requires caspase-1-dependent GSDMD cleavage, which also induces pyroptosis. Mechanisms of IL-1β secretion by pyroptotic and non-pyroptotic cells, and the precise functions of caspase-1 and GSDMD therein, are unresolved. Here, we show that, while efficient early secretion of endogenous IL-1β from primary non-pyroptotic myeloid cells in vitro requires GSDMD, later IL-1β release in vitro and in vivo proceeds independently of GSDMD. IL-1β maturation is sufficient for slow, caspase-1/GSDMD-independent secretion of ectopic IL-1β from resting, non-pyroptotic macrophages, but the speed of IL-1β release is boosted by inflammasome activation, via caspase-1 and GSDMD. IL-1β cleavage induces IL-1β enrichment at PIP2-enriched plasma membrane ruffles, and this is a prerequisite for IL-1β secretion and is mediated by a polybasic motif within the cytokine. We thus reveal a mechanism in which maturation-induced IL-1β trafficking facilitates its unconventional secretion

Evidence from comprehensive independent validation studies for smooth pursuit dysfunction as a sensorimotor biomarker for psychosis

Smooth pursuit eye movements are considered a well-established and quantifiable biomarker of sensorimotor function in psychosis research. Identifying psychotic syndromes on an individual level based on neurobiological markers is limited by heterogeneity and requires comprehensive external validation to avoid overestimation of prediction models. Here, we studied quantifiable sensorimotor measures derived from smooth pursuit eye movements in a large sample of psychosis probands (N = 674) and healthy controls (N = 305) using multivariate pattern analysis. Balanced accuracies of 64% for the prediction of psychosis status are in line with recent results from other large heterogenous psychiatric samples. They are confirmed by external validation in independent large samples including probands with (1) psychosis (N = 727) versus healthy controls (N = 292), (2) psychotic (N = 49) and non-psychotic bipolar disorder (N = 36), and (3) non-psychotic affective disorders (N = 119) and psychosis (N = 51) yielding accuracies of 65%, 66% and 58%, respectively, albeit slightly different psychosis syndromes. Our findings make a significant contribution to the identification of biologically defined profiles of heterogeneous psychosis syndromes on an individual level underlining the impact of sensorimotor dysfunction in psychosis

Nutritional, Health, and Technological Functionality of Lupin Flour Addition to Bread and Other Baked Products: Benefits and Challenges

Lupin is an undervalued legume despite its high protein and dietary fiber content and potential health benefits. This review focuses on the nutritional value, health benefits, and technological effects of incorporating lupin flour into wheat-based bread. Results of clinical studies suggest that consuming lupin compared to wheat bread and other baked products reduce chronic disease risk markers; possibly due to increased protein and dietary fiber and bioactive compounds. However, lupin protein allergy has also been recorded. Bread quality has been improved when 10% lupin flour is substituted for refined wheat flour; possibly due to lupin-wheat protein cross-linking assisting bread volume and the high water-binding capacity (WBC) of lupin fiber delaying staling. Above 10% substitution appears to reduce bread quality due to lupin proteins low elasticity and the high WBC of its dietary fiber interrupting gluten network development. Gaps in understanding of the role of lupin flour in bread quality include the optimal formulation and processing conditions to maximize lupin incorporation, role of protein cross-linking, antistaling functionality, and bioactivity of its γ-conglutin protein

Taking a more nuanced look at behavior change for demand reduction in the illegal wildlife trade

The illegal wildlife trade threatens the future of many species, and undermines economies and livelihoods. Conservationists have largely responded with supply‐side interventions, such as antipoaching patrols, but these often fail to stem the tide of wildlife trafficking. There is now increasing interest in demand‐side interventions, which seek to lower poaching pressure on sought‐after species by reducing consumer's desire for, and purchase of, specific wildlife products. Individual behavior change approaches, from environmental education to social marketing, have been widely advocated by academics, practitioners, and policy makers. However, this is an emerging field and we lack the breadth of evidence needed to understand and predict the potential outcomes of demand reduction interventions. To help us gain broader insights, we examine the literature from public health and international development on the effectiveness of behavior change interventions, and critique the current conceptualization of strategies for reducing consumer demand in the illegal wildlife trade. We show that behavior change is difficult to achieve and interventions may have unintended and undesirable consequences because of unaddressed systemic, cultural and environmental drivers, and limited resourcing. We conclude that some sections of the conservation community are advocating a shift from one reductionist approach based on limiting supply, to another based on limiting demand, and argue that conservationists should learn from the public health and international development projects that have integrated systems thinking. By accounting for the multiple interactions and synergies between different factors in the wildlife trade, we can develop more strategic approaches to protecting endangered species