ALBERT

Description: This paper presents novel topologies for the design and realization of microwave filters combining dual-mode and single-mode cavities in all-inductive waveguide technology. Examples of orders three, four and five with one or two transmission zeros are synthesized and designed, in order to demonstrate the validity of the proposals. All the coupling schemes explored exhibit the zero-shifting property, so the transmission zeros can be easily placed above or below the passband. A four-pole dual bandpass filter is also designed to show the flexibility offered by the novel structures. A prototype of this dual-band filter has been manufactured and tested in order to provide experimental validation for these new structures. Important aspects of synthesis techniques, required to obtain the associated coupling topologies and to perform the final physical design of the waveguide filters, are also addressed in this paper.

Description: Spin dynamics on networks allows us to understand how a global consensus emerges out of individual opinions. Here, we are interested in the effect of heterogeneity in the initial geographic distribution of a competing opinion on the competitiveness of its own opinion. Accordingly, in this work, we studied the effect of spatial heterogeneity on the majority rule dynamics using a three-state spin model, in which one state is neutral. Monte Carlo simulations were performed on square lattices divided into square blocks (cells). Accordingly, one competing opinion was distributed uniformly among cells, whereas the spatial distribution of the rival opinion was varied from the uniform to heterogeneous, with the median-to-mean ratio in the range from 1 to 0. When the size of discussion group is odd, the uncommitted agents disappear completely after  3.30 ± 0.05 update cycles, and then the system evolves in a two-state regime with complementary spatial distributions of two competing opinions. Even so, the initial heterogeneity in the spatial distribution of one of the competing opinions causes a decrease of this opinion competitiveness. That is, the opinion with initially heterogeneous spatial distribution has less probability to win, than the opinion with the initially uniform spatial distribution, even when the initial concentrations of both opinions are equal. We found that although the time to consensus , the opinion’s recession rate is determined during the first 3.3 update cycles. On the other hand, we found that the initial heterogeneity of the opinion spatial distribution assists the formation of quasi-stable regions, in which this opinion is dominant. The results of Monte Carlo simulations are discussed with regard to the electoral competition of political parties.

Description: In many catchments the geographical demarcation does not coincide with the limits of the aquifers, so groundwater may be exchanged beyond their topographic boundaries. By studying groundwater exchanges, the natural resources of a catchment can be better assessed, and the divergences between hydrological models and measurements can be explained. The aim of this work is to reveal the importance of including groundwater exchanges in the hydrological modelling of some catchments, using a water balance model. For this purpose, a simple example is conducted. The so-called model Parent Model Scheme is modified to only allow groundwater exchanges, and it is applied to the headwater of the Segura River Basin District, located in the southeast of Spain. This area is selected because groundwater plays an important role in surface hydrology. The results reveal that groundwater exchanges cannot be neglected in some catchments when assessing water resources, since their integration in the hydrological model corrects errors in the water balance. Moreover, this paper proves that water balance models are a useful tool for estimating groundwater exchanges between catchments, which can be contrasted with more complex distributed models or isotopic tracers if there is enough information available. This article is protected by copyright. All rights reserved.

Description: High shear impellers (HSIs) are mixers used in industrial stirred tanks to incorporate powders into liquid and break down particle agglomerates. In this work, a detail numerical study of two commercial ring-style HSIs of laboratory scale (Hockmeyer® Equipment Corp. D-Blade of two and four rings) was carried out at 50≤ Re ≤75, and their performance was compared with the Rushton Turbine (RT). It was found that power and pumping numbers or their ratio, cannot be simply connected for selecting properly an impeller in applications where highly localized viscous dissipation is desirable. The ratio of the average viscous dissipation in the impeller swept volume, , to the mean in the entire volume, , at two constant values of power input, P , was found to be lower for HSIs to that evaluated for RT. However, when P increases from 4.25 to 12.92 W , the dimensionless average viscous dissipation in the blade swept volume, at the higher P was found to be similar for the HSI of two rings and the RT, corroborating the high local viscous dissipation of this HSI when operated at higher speeds.

Description: Street lighting has a big impact on the energy consumption of Spanish municipalities. To decrease this consumption, the Spanish government has developed two different regulations to improve energy savings and efficiency, and consequently, reduce greenhouse-effect gas emissions. However, after these efforts, they have not obtained the expected results. To improve the effectiveness of these regulations and therefore to optimize energy consumption, a study has been done to analyze the different devices which influence energy consumption with the intention of better understanding their behavior and performance. The devices analyzed were lamps, ballasts, street lamp globes, control systems and dimmable lighting systems. To improve their performance, they have been analyzed from three points of view: changes in technology, use patterns and standards. Thanks to this study, some aspects have been found that could be taken into account if we really wanted to use energy efficiently.

Description: The solutions to cope with new challenges that societies have to face nowadays involve providing smarter daily systems. To achieve this, technology has to evolve and leverage physical systems automatic interactions, with less human intervention. Technological paradigms like Internet of Things (IoT) and Cyber-Physical Systems (CPS) are providing reference models, architectures, approaches and tools that are to support cross-domain solutions. Thus, CPS based solutions will be applied in different application domains like e-Health, Smart Grid, Smart Transportation and so on, to assure the expected response from a complex system that relies on the smooth interaction and cooperation of diverse networked physical systems. The Wireless Sensors Networks (WSN) are a well-known wireless technology that are part of large CPS. The WSN aims at monitoring a physical system, object, (e.g., the environmental condition of a cargo container), and relaying data to the targeted processing element. The WSN communication reliability, as well as a restrained energy consumption, are expected features in a WSN. This paper shows the results obtained in a real WSN deployment, based on SunSPOT nodes, which carries out a fuzzy based control strategy to improve energy consumption while keeping communication reliability and computational resources usage among boundaries.

Description: Background: In cancer, large-scale technologies such as next-generation sequencing and microarrays have produced a wide number of genomic features such as DNA copy number alterations (CNA), mRNA expression (EXPR), microRNA expression (MIRNA), and DNA somatic mutations (MUT), among others. Several analyses of a specific type of these genomic data have generated many prognostic biomarkers in cancer. However, it is uncertain which of these data is more powerful and whether the best data-type is cancer-type dependent.Therefore, our purpose is to characterize the prognostic power of models obtained from different genomic data types, cancer types, and algorithms. For this, we compared the prognostic power using the concordance and prognostic index of models obtained from EXPR, MIRNA, CNA, MUT data and their integration for ovarian serous cystadenocarcinoma (OV), multiform glioblastoma (GBM), lung adenocarcinoma (LUAD), and breast cancer (BRCA) datasets from The Cancer Genome Atlas repository. We used three different algorithms for prognostic model selection based on constrained particle swarm optimization (CPSO), network feature selection (NFS), and least absolute shrinkage and selection operator (LASSO). Results: The integration of the four genomic data produced models having slightly higher performance than any single genomic data. From the genomic data types, we observed better prediction using EXPR closely followed by MIRNA and CNA depending on the cancer type and method. We observed higher concordance index in BRCA, followed by LUAD, OV, and GBM. We observed very similar results between LASSO and CPSO but smaller values in NFS. Importantly, we observed that model predictions highly concur between algorithms but are highly discordant between data types, which seems to be dependent on the censoring rate of the dataset. Conclusions: Gene expression (mRNA) generated higher performances, which is marginally improved when other type of genomic data is considered. The level of concordance in prognosis generated from different genomic data types seems to be dependent on censoring rate.

Description: Background: Klebsiella variicola was very recently described as a new bacterial species and is very closely related to Klebsiella pneumoniae; in fact, K. variicola isolates were first identified as K. pneumoniae. Therefore, it might be the case that some isolates, which were initially classified as K. pneumoniae, are actually K. variicola. The aim of this study was to devise a multiplex-PCR probe that can differentiate isolates from these sister species.ResultThis work describes the development of a multiplex-PCR method to identify K. variicola. This development was based on sequencing a K. variicola clinical isolate (801) and comparing it to other K. variicola and K. pneumoniae genomes. The phylogenetic analysis showed that K. variicola isolates form a monophyletic group that is well differentiated from K. pneumoniae. Notably, the isolate K. pneumoniae 342 and K. pneumoniae KP5-1 might have been misclassified because in our analysis, both clustered with K. variicola isolates rather than with K. pneumoniae. The multiplex-PCR (M-PCR-1 to 3) probe system could identify K. variicola with high accuracy using the shared unique genes of K. variicola and K. pneumoniae genomes, respectively. M-PCR-1 was used to assay a collection of multidrug-resistant (503) and antimicrobial-sensitive (557) K. pneumoniae clinical isolates. We found K. variicola with a prevalence of 2.1% (23/1,060), of them a 56.5% (13/23) of the isolates were multidrug resistant, and 43.5% (10/23) of the isolates were antimicrobial sensitive. The phylogenetic analysis of rpoB of K. variicola-positive isolates identified by multiplex-PCR support the correct identification and differentiation of K. variicola from K. pneumoniae clinical isolates. Conclusions: This multiplex-PCR provides the means to reliably identify and genotype K. variicola. This tool could be very helpful for clinical, epidemiological, and population genetics studies of this species. A low but significant prevalence of K. variicola isolates was found, implying that misclassification had occurred previously. We believe that our multiplex-PCR assay could be of paramount importance to understand the population dynamics of K. variicola in both clinical and environmental settings.

Description: Background: The cAMP-dependent protein kinase regulatory network (PKA-RN) regulates metabolism, memory, learning, development, and response to stress. Previous models of this network considered the catalytic subunits (CS) as a single entity, overlooking their functional individualities. Furthermore, PKA-RN dynamics are often measured through cAMP levels in nutrient-depleted cells shortly after being fed with glucose, dismissing downstream physiological processes. Results: Here we show that temperature stress, along with deletion of PKA-RN genes, significantly affected HSE-dependent gene expression and the dynamics of the PKA-RN in cells growing in exponential phase. Our genetic analysis revealed complex regulatory interactions between the CS that influenced the inhibition of Hsf1/Skn7 transcription factors. Accordingly, we found new roles in growth control and stress response for Hsf1/Skn7 when PKA activity was low (cdc25Δ cells). Experimental results were used to propose an interaction scheme for the PKA-RN and to build an extension of a classic synchronous discrete modeling framework. Our computational model reproduced the experimental data and predicted complex interactions between the CS and the existence of a repressor of Hsf1/Skn7 that is activated by the CS. Additional genetic analysis identified Ssa1 and Ssa2 chaperones as such repressors. Further modeling of the new data foresaw a third repressor of Hsf1/Skn7, active only in theabsence of Tpk2. By averaging the network state over all its attractors, a good quantitative agreement between computational and experimental results was obtained, as the averages reflected more accurately the population measurements. Conclusions: The assumption of PKA being one molecular entity has hindered the study of a wide range of behaviors. Additionally, the dynamics of HSE-dependent gene expression cannot be simulated accurately by considering the activity of single PKA-RN components (i.e., cAMP, individual CS, Bcy1, etc.). We show that the differential roles of the CS are essential to understand the dynamics of the PKA-RN and its targets. Our systems level approach, which combined experimental results with theoretical modeling, unveils the relevance of the interaction scheme for the CS and offers quantitative predictions for several scenarios (WT vs. mutants in PKA-RN genes and growth at optimal temperature vs. heat shock).