Fuzzy Inference System for VOLT/VAR control in distribution substations in isolated power systems

This paper presents a fuzzy inference system for voltage/reactive power control in distribution substations. The purpose is go forward to automation distribution and its implementation in isolated power systems where control capabilities are limited and it is common using the same applications as in continental power systems. This means that lot of functionalities do not apply and computational burden generates high response times. A fuzzy controller, with logic guidelines embedded based upon heuristic rules resulting from operators at dispatch control center past experience, has been designed. Working as an on-line tool, it has been tested under real conditions and it has managed the operation during a whole day in a distribution substation. Within the limits of control capabilities of the system, the controller maintained successfully an acceptable voltage profile, power factor values over 0,98 and it has ostensibly improved the performance given by an optimal power flow based automation system

The prediction of the operating conditions on the permeate flux and on protein aggregation during membrane processing of monoclonal antibodies

The lack of available material during early stage bioprocess development poses numerous processing challenges such as limiting the number of full-scale experiments. Extended fundamental process understanding could be gained with the use of an ultra scale-down (USD) device using as little as 1.7 mL per experimental run. The USD system is used to predict diafiltration and ultrafiltration/diafiltration (UF/DF) performance of a pilot-scale tangential flow filtration (TFF) system, fitted with a flat-sheet cassette, operating at 500-fold larger scale. Both systems were designed by maintaining a volumetric loading of 8.1 L of feed per m2. Permeate flux was predicted for monoclonal antibody solutions with the USD system across a range of transmembrane pressure drops, feed concentrations and flow conditions during diafiltration, and desired retentate concentrations during UF/DF operations. The resulting USD data were in good agreement with the pilot-scale TFF when scaled based on similar shear rates over the membrane surface. Little change in soluble aggregates was observed in both systems but there were significantly higher increases in product turbidity in the USD system. A correlation was established to relate turbidity increase based on the volume fraction of high shear stress zone for USD systems and various pilot-scale TFF systems. The correlation was extended to encompass the processing time and concentration for a wide range of membrane processing challenges in both scales

Subtleties in the trainability of quantum machine learning models

A new paradigm for data science has emerged, with quantum data, quantum models, and quantum computational devices. This field, called Quantum Machine Learning (QML), aims to achieve a speedup over traditional machine learning for data analysis. However, its success usually hinges on efficiently training the parameters in quantum neural networks, and the field of QML is still lacking theoretical scaling results for their trainability. Some trainability results have been proven for a closely related field called Variational Quantum Algorithms (VQAs). While both fields involve training a parametrized quantum circuit, there are crucial differences that make the results for one setting not readily applicable to the other. In this work we bridge the two frameworks and show that gradient scaling results for VQAs can also be applied to study the gradient scaling of QML models. Our results indicate that features deemed detrimental for VQA trainability can also lead to issues such as barren plateaus in QML. Consequently, our work has implications for several QML proposals in the literature. In addition, we provide theoretical and numerical evidence that QML models exhibit further trainability issues not present in VQAs, arising from the use of a training dataset. We refer to these as dataset-induced barren plateaus. These results are most relevant when dealing with classical data, as here the choice of embedding scheme (i.e., the map between classical data and quantum states) can greatly affect the gradient scaling.Comment: 12+12 pages, 8+2 figure

Fructose metabolism in Chromohalobacter salexigens: interplay between the Embden–Meyerhof–Parnas and Entner–Doudoroff pathways

Background The halophilic bacterium Chromohalobacter salexigens metabolizes glucose exclusively through the Entner–Doudoroff (ED) pathway, an adaptation which results in inefficient growth, with significant carbon overflow, especially at low salinity. Preliminary analysis of C. salexigens genome suggests that fructose metabolism could proceed through the Entner–Doudoroff and Embden–Meyerhof–Parnas (EMP) pathways. In order to thrive at high salinity, this bacterium relies on the biosynthesis and accumulation of ectoines as major compatible solutes. This metabolic pathway imposes a high metabolic burden due to the consumption of a relevant proportion of cellular resources, including both energy molecules (NADPH and ATP) and carbon building blocks. Therefore, the existence of more than one glycolytic pathway with different stoichiometries may be an advantage for C. salexigens. The aim of this work is to experimentally characterize the metabolism of fructose in C. salexigens. Results Fructose metabolism was analyzed using in silico genome analysis, RT-PCR, isotopic labeling, and genetic approaches. During growth on fructose as the sole carbon source, carbon overflow was not observed in a wide range of salt concentrations, and higher biomass yields were reached. We unveiled the initial steps of the two pathways for fructose incorporation and their links to central metabolism. While glucose is metabolized exclusively through the Entner–Doudoroff (ED) pathway, fructose is also partially metabolized by the Embden–Meyerhof–Parnas (EMP) route. Tracking isotopic label from [1-13C] fructose to ectoines revealed that 81% and 19% of the fructose were metabolized through ED and EMP-like routes, respectively. Activities of enzymes from both routes were demonstrated in vitro by 31P-NMR. Genes encoding predicted fructokinase and 1-phosphofructokinase were cloned and the activities of their protein products were confirmed. Importantly, the protein encoded by csal1534 gene functions as fructose bisphosphatase, although it had been annotated previously as pyrophosphate-dependent phosphofructokinase. The gluconeogenic rather than glycolytic role of this enzyme in vivo is in agreement with the lack of 6-phosphofructokinase activity previously described. Conclusions Overall, this study shows that C. salexigens possesses a greater metabolic flexibility for fructose catabolism, the ED and EMP pathways contributing to a fine balancing of energy and biosynthetic demands and, subsequently, to a more efficient metabolism.University of Murcia and University of Seville was supported by projects: BIO2015-63949-R, BIO2014-54411-C2-1-REuropa MINECO/FEDER RTI2018-094393-B-C21Fundación Séneca (Grant no. 19236/PI/14