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Objectives: Despite the success of cochlear implant (CI) surgery for hearing restoration, reducing CI electrode insertion forces is an ongoing challenge with the goal to further reduce post-implantation hearing loss. While research in this field shows that both friction and quasistatic pressure forces occur during CI insertion, there is a lack of studies distinguishing between these origins. The present study was conducted to analyze the contribution of both force phenomena during automated CI insertion. Methods: Five MED-EL FLEX28 CI electrode arrays were inserted into both a regular and uncoiled version of the same average scala tympani (ST). Both ST models had a pressure release hole at the apical end, which was kept open or closed to quantify pressure forces. ST models were filled with different sodium dodecyl sulfate (SDS) lubricants (1, 5, and 10% SDS, water). The viscosity of lubricants was determined using a rheometer. Insertions were conducted with velocities ranging from v= 0.125 mm/s to 2.0 mm/s. Results: Viscosity of SDS lubricants at 20°C was 1.28, 1.96, and 2.51 mPas for 1, 5, and 10% SDS, respectively, which lies within the values reported for human perilymph. In the uncoiled ST model, forces remained within the noise floor (maximum: 0.049 × 10-3 N ± 1.5 × 10-3 N), indicating minimal contribution from quasistatic pressure. Conversely, forces using the regular, coiled ST model were at least an order of magnitude larger (minimum: Fmax = 28.95 × 10-3 N, v = 1 mm/s, 10% SDS), confirming that friction forces are the main contributor to total insertion forces. An N-way ANOVA revealed that both lubricant viscosity and insertion speed significantly reduce insertion forces (p < 0.001). Conclusion: For the first time, this study demonstrates that at realistic perilymph viscosities, quasistatic pressure forces minimally affect the total insertion force profile during insertion. Mixed friction is the main determinant, and significantly decreases with increaseing insertion speeds. This suggests that in clinical settings with similar ST geometries and surgical preparation, quasistatic pressure plays a subordinate role. Moreover, the findings indicate that managing the hydrodynamics of the cochlear environment, possibly through pre-surgical preparation or the use of specific lubricants, could effectively reduce insertion forces. [ABSTRACT FROM AUTHOR]

Optimization models can support decision-makers in the synthesis and operation of multi-sector energy systems. To identify the optimal design and operation of a low-carbon system, we need to consider high temporal and spatial variability in the electricity supply, sector coupling, and environmental impacts over the whole life cycle. Incorporating such aspects in optimization models is demanding. To avoid redundant research efforts and enhance transparency, the developed models and used data sets should be shared openly. In this work, we present the SecMOD framework for multi-sector energy system optimization incorporating life-cycle assessment (LCA). The framework allows optimizing multiple sectors jointly, ranging from industrial production and their linked energy supply systems to sector-coupled national energy systems. The framework incorporates LCA to account for environmental impacts. We hence provide the first open-source framework to consistently include a holistic life-cycle perspective in multi-sector optimization by a full integration of LCA. We apply the framework to a case-study of the German sector-coupled energy system. Starting with few base technologies, we demonstrate the modular capabilities of SecMOD by the stepwise addition of technologies, sectors and existing infrastructure. Our modular open-source framework SecMOD aims to accelerate research for sustainable energy systems by combining multi-sector energy system optimization and life-cycle assessment.

Over the past decade, the term bioeconomy has emerged in both policy and academic discourse. Implying a technology-driven approach to wealth generation from organic materials, the term has taken hold with so far limited critical engagement. It is a contestable rather than contested term. Noting the rise of numerous other ‘economies’ (blue, green, circular) on a similar timeframe, this paper undertakes a critical discourse analysis of academic literature and UK/EU policy documents using the term ‘bioeconomy’ to produce a contextualised understanding of how it is used in both theoretical and practical contexts. Our analysis shows that bioeconomy, as with the other ‘sustainability’ economies, which we term the ‘S-economies’, prioritises the economy and the markets as the solution brokers for the environmental and economic problems they seek to address. The apparent fragmentation of the theory and policy concerning the environmental sustainability of economic activity is expressed through the variability of terms that aspire to establish multiple economies functioning at the same time. Limited empirical analysis of the existing ‘bioeconomy’ is symptomatic of the dissociation between theory and practice, emphasizing technological approaches favouring capital intensive approaches over local solutions. The S-economies, including the bioeconomy, are an attempt to bypass economic structural realities that otherwise would need to be addressed.

Modern electrophysiological recordings simultaneously capture single-unit spiking activities of hundreds of neurons spread across large cortical distances. Yet, this parallel activity is often confined to relatively low-dimensional manifolds. This implies strong coordination also among neurons that are most likely not even connected. Here, we combine in vivo recordings with network models and theory to characterize the nature of mesoscopic coordination patterns in macaque motor cortex and to expose their origin: We find that heterogeneity in local connectivity supports network states with complex long-range cooperation between neurons that arises from multi-synaptic, short-range connections. Our theory explains the experimentally observed spatial organization of covariances in resting state recordings as well as the behaviorally related modulation of covariance patterns during a reach-to-grasp task. The ubiquity of heterogeneity in local cortical circuits suggests that the brain uses the described mechanism to flexibly adapt neuronal coordination to momentary demands.

Recently, the Hypervolume Newton Method (HVN) has been proposed as a fast and precise indicator-based method for solving unconstrained bi-objective optimization problems with objective functions. The HVN is defined on the space of (vectorized) fixed cardinality sets of decision space vectors for a given multi-objective optimization problem (MOP) and seeks to maximize the hypervolume indicator adopting the Newton–Raphson method for deterministic numerical optimization. To extend its scope to non-convex optimization problems, the HVN method was hybridized with a multi-objective evolutionary algorithm (MOEA), which resulted in a competitive solver for continuous unconstrained bi-objective optimization problems. In this paper, we extend the HVN to constrained MOPs with in principle any number of objectives. Similar to the original variant, the first- and second-order derivatives of the involved functions have to be given either analytically or numerically. We demonstrate the applicability of the extended HVN on a set of challenging benchmark problems and show that the new method can be readily applied to solve equality constraints with high precision and to some extent also inequalities. We finally use HVN as a local search engine within an MOEA and show the benefit of this hybrid method on several benchmark problems.