University Carlos III de Madrid

Distributed Generation (DG) embedded with Distribution Networks (DNs) has been developed because its performance has become more efficient and sustainable. This reconfiguration mode increases the short-circuit current (SCC), and subsequently heightens the complexities involved in both the setting and operation of the overcurrent protection system. Therefore, it is necessary to develop a robust protection strategy for DNs integrated with DG to prevent the electrical equipment from collapsing during abnormal conditions. This study proposed one of the most important and reliable strategies for resetting and re-coordinating overcurrent relays (OCRs) that operate in the same protection zone of the distribution feeder. This methodology restricts the main variables and elements used in the protection device (PD) setting after DG is embedded to redesign a suitable setting and coordination. However, international, and national benchmark standards are used to specify suitable equations that satisfy high-protection system characteristics to ensure the reliability of DNs according to a real case study of a medium voltage level 33kV in the electrical distribution feeder of Baghdad, Iraq.

This study examined the differences between children and adolescents with autism spectrum disorder (ASD) and neurotypically developing (NTD) in terms of balance, postural control, and motor skills. It also examined which motor skills are most affected and whether scores on different assessment tests in ASD children are correlated. A cross‐sectional observational study with two research groups was conducted. Timed up and go test (TUG), short form of Bruininks‐Oseretsky test of Motor Proficiency version 2 (SFBOT‐2), and pediatric balance scale (PBS) were used. A total of 100 participants 50 with ASD and 50 with NTD engaged in the research. Statistically significant differences were obtained between control group and ASD group in TUG test and in SFBOT‐2 standard score and total score ( p ‐value = <0.01). A statistically significant difference ( p ‐value = <0.01) was seen between ASD group's and control group's PBS scores. Poor correlation was noted between TUG and SFBOT‐2, as well as between PBS and TUG. A moderate correlation was also found between SFBOT‐2 and PBS. Children with ASD present difficulties in motor skills and in static and dynamic balance compared to children with NTD. Differences were observed in the motor skills of strength followed by manual dexterity, running speed and agility, fine motor precision, fine motor integration, and balance. The PBS item that showed the greatest difference between the ASD group and control group was maintaining monopodial support with hands on hips. Finally, poor to moderate correlations were obtained between the different tests with statistically significant differences.

The continued advancement of electrochemical technologies requires an increasingly detailed understanding of the microscopic processes that control their performance, inspiring the development of new multi-modal diagnostic techniques. Here, we introduce a neutron imaging approach to enable the quantification of spatial and temporal variations in species concentrations within an operating redox flow cell. Specifically, we leverage the high attenuation of redox-active organic materials (high hydrogen content) and supporting electrolytes (boron-containing) in solution and perform subtractive neutron imaging of active species and supporting electrolyte. To resolve the concentration profiles across the electrodes, we employ the in-plane imaging configuration and correlate the concentration profiles to cell performance with polarization measurements under different operating conditions. Finally, we use time-of-flight neutron imaging to deconvolute concentrations of active species and supporting electrolyte during operation. Using this approach, we evaluate the influence of cell polarity, voltage bias, and flow rate on the concentration distribution within the flow cell and correlate these with the macroscopic performance, thus obtaining an unprecedented level of insight into reactive mass transport. Ultimately, this diagnostic technique can be applied to a range of (electro)chemical technologies and may accelerate the development of new materials and reactor designs.

This paper presents conditions to guarantee the convergence of simulations to a stochastic steady state, characterized by an invariant probability distribution, in an endowment economy with a finite number of heterogeneous agents, 1 period real assets offered in zero net supply, aggregate uncertainty, incomplete markets and uncountable shocks. The results are robust to the presence of multiple discontinuous equilibria and are numerically implementable. We work on a Markov environment with an enlarged state space to characterize ergodic equilibria and differentiate them with respect to time-independent and stationary ones. We show, by imposing a mild restriction on the discontinuity set, that every measurable time-independent selection approximates the stochastic steady state of the model. The results in this paper are constructive and based on assumptions imposed on the primitives of the model. Thus, they can help to design calibration and estimation methods for heterogeneous agent models based on unconditional moments.

This study endeavors to examine the Spanish adverb acaso through a diachronic lens, offering novel hypotheses to elucidate its etymological derivation, the intricacies of its grammaticalization process, and its progressive selection of the subjunctive mood within independent sentences. Etymologically, compelling evidence is presented, establishing a linguistic lineage with late Latin. Concerning its grammaticalization, intricate connections are posited with the expression por (a)ventura. Regarding the selection of the subjunctive mood, the study reveals a recent shift, notably gaining prominence since the 18th century and persisting to the contemporary era. Lastly, an analytical inquiry into the determinants behind the subjunctive mood’s modern trajectory is undertaken, comparing it with the traditional course of the indicative mood.

The most relevant features of FLIPEC (Free fLow Iterative Plasma Equilibrium Code) are presented. This new code iteratively calculates free-boundary, axisymmetric ideal MHD equilibria with arbitrary poloidal and toroidal plasma flows. FLIPEC is a mature code that has emerged from a complete overhaul of a previous version (F-Torija Daza 2022 et al Nucl. Fusion 62 126044). It uses a (inverse) curvilinear coordinate representation for the Grad–Shafranov–Bernoulli equation system, which allows FLIPEC to extend its free-boundary capabilities to arbitrary plasma shapes and removes many limitations with regards to the distance between plasma and external coils. Run-time stabilization of vertical modes has also been implemented by means of artificial feedback coils. Finally, active targeting schemes have also been included. These capabilities are illustrated on two very different cases: the ITER tokamak baseline configuration and a NSTX spherical tokamak equilibrium.

Bioabsorbable Mg wire‐reinforced poly‐lactic acid (PLA) matrix composites are potential candidate for load‐bearing orthopedic implants offering tailorable mechanical and degradation properties by stacking sequence, volume fraction and surface modification of Mg wires. In this study, we investigated the cytocompatibility, cell‐material interaction, and bone differentiation behavior of MC3T3‐E1 pre‐osteoblast cells for medical‐grade PLA, Mg/PLA, and PEO‐Mg/PLA (having PEO surface modification on Mg wires) composites. MTT and live/dead assay showed excellent biocompatibility of both composites while cell‐material interaction analysis revealed that cells were able to adhere and proliferate on the surface of composites. Cells on the longitudinal surface of composites showed a high and uniform cell density while those on transversal surfaces initially avoided Mg regions but later migrated back after the formation of the passivation layer. Bone differentiation tests showed that cells in extracts of PLA and composites were able to initiate the differentiation process as osteogenesis‐related gene expressions, alkaline phosphatase protein quantity, and calcium mineralization increased after 7 and 14 days of culture. Interestingly, the bone differentiation response of PEO‐Mg/PLA composite was found to be similar to medical‐grade PLA, proving its superiority over Mg/PLA composite.

In recent years, there has been a surge in the development of methods for cell segmentation and tracking, with initiatives like the Cell Tracking Challenge driving progress in the field. Most studies focus on regular cell population videos in which cells are segmented and followed, and parental relationships annotated. However, DNA damage induced by genotoxic drugs or ionizing radiation produces additional abnormal events since it leads to behaviors like abnormal cell divisions (resulting in a number of daughters different from two) and cell death. With this in mind, we developed an automatic mitosis classifier to categorize small mitosis image sequences centered around one cell as “Normal” or “Abnormal.” These mitosis sequences were extracted from videos of cell populations exposed to varying levels of radiation that affect the cell cycle’s development. We explored several deep-learning architectures and found that a network with a ResNet50 backbone and including a Long Short-Term Memory (LSTM) layer produced the best results (mean F1-score: 0.93 ± 0.06). In the future, we plan to integrate this classifier with cell segmentation and tracking to build phylogenetic trees of the population after genomic stress.

This article explores the challenges of translating the empirical data recorded in the microhistorical events documented in most archaeological sites into narratives that provide a deeper understanding of long-term historical processes. It specifically focuses on the importance of studying the history of subaltern communities through this microhistorical scale. Drawing on the concept of “subaltern debris,” the article proposes a new approach to analyzing archaeological deposits generated by the everyday life of subaltern communities. It argues that these deposits can offer valuable insights into the living conditions and agency of subaltern communities. The article presents two case studies from the late antique period in the Iberian Peninsula to illustrate the potential of this approach. It concludes by emphasizing the importance of recognizing the material agency of subaltern communities in reshaping historical narratives.

Within the evolving landscape of fifth‐generation (5G) wireless networks, the introduction of network‐slicing protocols has become pivotal, enabling the accommodation of diverse application needs while fortifying defences against potential security breaches. This study endeavours to construct a comprehensive network‐slicing model integrated with an attack detection system within the 5G framework. Leveraging software‐defined networking (SDN) along with deep learning techniques, this approach seeks to fortify security measures while optimizing network performance. This undertaking introduces network slicing predicated on SDN with the OpenFlow protocol and Ryu control technology, complemented by a neural network model for attack detection using deep learning methodologies. Additionally, the proposed convolutional neural networks‐long short‐term memory approach demonstrates superiority over conventional ML algorithms, signifying its potential for real‐time attack detection. Evaluation of the proposed system using a 5G dataset showcases an impressive accuracy of 99%, surpassing previous studies, and affirming the efficacy of the approach. Moreover, network slicing significantly enhances quality of service by segmenting services based on bandwidth. Future research will concentrate on real‐world implementation, encompassing diverse dataset evaluations, and assessing the model's adaptability across varied scenarios.

The limited availability of human bone samples for investigation leads to the demand for alternatives. Bone surrogates are crucial in promoting research on the intricate mechanics of osseous tissue. However, solutions are restricted to commercial brands, which frequently fail to faithfully replicate the mechanical response of bone, or oversimplified customised simulants designed for a specific application. The manufacturing and assessment of reliable bone surrogates made of polylactic acid via material extrusion-based additive manufacturing are presented in this work. An experimental and numerical study with 3D-printed dog-bone and prismatic specimens was carried out to characterise the polymeric feedstock and analyse the influence of process parameters under three-point bending and quasi-static conditions. Besides, three porcine rib samples were considered as a reference for the development of the artificial bones. Bone surrogates were manufactured from the 3D-scanned real bone geometries. In order to reproduce the trabecular and cortical bone, a lattice structure for the infill and a compact shell surrounding the core were employed. Infill density and shell thickness were evaluated through different printing configurations. Additionally, a computational analysis based on the phase-field approach was conducted to simulate the experimental tests and predict fracture. The modelling considered homogenisation of the infill material. Outcomes demonstrated the potential of the presented methodology. Maximum force and flexural stiffness were compared to real bone properties to find the optimal printing configuration, replicating the flexural mechanical behaviour of bone tissue. Certain configurations accurately reproduce the studied properties. Regarding the numerical model, strength and stiffness prediction was validated with experimental results. The presented methodology enables the manufacturing of artificial bones with accurate geometries and tailored mechanical properties. Furthermore, the described modelling strategy offers a powerful tool for designing bone surrogates.