University Carlos III de Madrid

Germanium is reemerging as a prominent material in the semiconductor field, particularly for electronic applications, photonics, photovoltaics, and thermophotovoltaics. Its combination with III‐V compound semiconductors through epitaxial growth by metal‐organic vapor phase epitaxy (MOVPE) is instrumental and thus, the comprehension of the sequential stages in such epitaxial processes is of great importance. During the deposition of GaAs on p‐type Ge, the formation of n/p junctions occurs when As diffuses into Ge. It is found that this formation begins in the so‐called AsH3 preexposure where Ge substrate is first exposed to AsH3. Also important is the fact that both free carrier profiles and As profiles indicate that prolonged AsH3 preexposure times lead to deeper diffusion depths for the same process time. This effect is concomitant with the degradation of the Ge surface morphology, characterized by higher roughness as the AsH3 preexposure duration is extended. Unlike ion‐implanted As in Ge, which shows a quadratic dependent diffusivity, this MOVPE investigation using AsH3 indicates a linear relationship, consistent with Takenaka et al.’s MOVPE study using TBAs. The analysis of As profiles alongside simulations, with and without subsequent GaAs epitaxy, suggests the generation of Ge vacancies during the process, contributing to deeper As diffusion.

The widespread availability of inexpensive mobile broadband has democratized access to digital services in developed countries. While this has supposedly closed digital divides among the population, more subtle inequalities may still be present that are not driven by the accessibility to mobile services, rather by the heterogeneous capability of individuals to take advantage from those services. This paper focuses on the existence of imbalances in the consumption of mobile services across France using mobile traffic measurement data. We unveil that per-capita mobile traffic demands follow in fact a power law of the local population size, or, equivalently, there exists an emergent behavior that prompts subscribers living in larger urban areas to exhibit higher individual usage of mobile services. The result holds for global traffic, but is consistent across various mobile services, although with varying intensity. Our findings reveal the presence of potential second-level digital divides in developed countries and, surprisingly, show that such divides have steadily increased in France between 2014 and 2019. Moreover, we show how the phenomenon defies explanation by potential confounding factors like broad-band coverage, socioeconomic status, commuting, or inhabitant’s age, but has been indirectly mitigated by the recent containment measures enacted to combat COVID-19.

This paper focuses on how Spain’s labour and employment law is dealing with technological disruption and, particularly, with algorithm management, looking for a harmonious equilibrium between traditional structures and profound changes. It pays special attention to the different actors affected and the most recent normative changes.

We propose the construction of conditional growth densities under stressed factor scenarios to assess the level of exposure of an economy to small probability but potentially catastrophic economic and/or financial scenarios, which can be either domestic or international. The choice of severe yet plausible stress scenarios is based on the joint probability distribution of the underlying factors driving growth, which are extracted with a multilevel dynamic factor model (DFM) from a wide set of domestic/worldwide and/or macroeconomic/financial variables. All together, we provide a risk management tool that allows for a complete visualization of the dynamics of the growth densities under average scenarios and extreme scenarios. We calculate growth‐in‐stress (GiS) measures, defined as the 5% quantile of the stressed growth densities, and show that GiS is a useful and complementary tool to growth‐at‐risk (GaR) when policymakers wish to carry out a multidimensional scenario analysis. The unprecedented economic shock brought by the COVID‐19 pandemic provides a natural environment to assess the vulnerability of US growth with the proposed methodology.

Miniaturized flow cytometry has significant potential for portable applications, such as cell‐based diagnostics and the monitoring of therapeutic cell manufacturing, however, the performance of current techniques is often limited by the inability to resolve spectrally‐overlapping fluorescence labels. Here, the study presents a computational hyperspectral microflow cytometer (CHC) that enables accurate discrimination of spectrally‐overlapping fluorophores labeling single cells. CHC employs a dispersive optical element and an optimization algorithm to detect the full fluorescence emission spectrum from flowing cells, with a high spectral resolution of ≈3 nm in the range from 450 to 650 nm. CHC also includes a dedicated microfluidic device that ensures in‐focus imaging through viscoelastic sheathless focusing, thereby enhancing the accuracy and reliability of microflow cytometry analysis. The potential of CHC for analyzing T lymphocyte subpopulations and monitoring changes in cell composition during T cell expansion is demonstrated. Overall, CHC represents a major breakthrough in microflow cytometry and can facilitate its use for immune cell monitoring.

This research note investigates how the voting behavior of middle-income citizens explains why right-wing parties tend to govern under majoritarian electoral rule. The growing literature that investigates the ideological effects of electoral systems has mostly focused on institutional explanations. However, whether the electoral rules overrepresent parties with some specific ideologies is also a matter of behavior. Building on Iversen and Soskice (2006), we test two arguments. First, middle-income groups are more likely to vote for the right under majoritarian rules because they fear the redistributive consequences of a victory of the left in these contexts. Second, middle-income earners particularly concerned with tax rates are particularly prone to vote differently across electoral systems. Combining survey evidence from the Comparative Study of Electoral Systems and the New Zealand Election Study, we show that the voting behavior of middle-income citizens is indeed responsible for the predominance of the right under majoritarian systems.

The online trend of the manosphere and feminist discourse on social networks requires a holistic measure of the level of sexism in an online community. This indicator is important for policymakers and moderators of online communities (e.g., subreddits) and computational social scientists, either to revise moderation strategies based on the degree of sexism or to match and compare the temporal sexism across different platforms and communities with real-time events and infer social scientific insights. In this paper, we build a model that can provide a comparable holistic indicator of toxicity targeted toward male and female identity and male and female individuals. Despite previous supervised NLP methods that require annotation of toxic comments at the target level (e.g. annotating comments that are specifically toxic toward women) to detect targeted toxic comments, our indicator uses supervised NLP to detect the presence of toxicity and unsupervised word embedding association test to detect the target automatically. We apply our model to gender discourse communities (e.g., r/TheRedPill, r/MGTOW, r/FemaleDatingStrategy) to detect the level of toxicity toward genders (i.e., sexism). Our results show that our framework accurately and consistently (93% correlation) measures the level of sexism in a community. We finally discuss how our framework can be generalized in the future to measure qualities other than toxicity (e.g. sentiment, humor) toward general-purpose targets and turn into an indicator of different sorts of polarizations.

This survey gives an overview of Monte Carlo methodologies using surrogate models, for dealing with densities that are intractable, costly, and/or noisy. This type of problem can be found in numerous real‐world scenarios, including stochastic optimisation and reinforcement learning, where each evaluation of a density function may incur some computationally‐expensive or even physical (real‐world activity) cost, likely to give different results each time. The surrogate model does not incur this cost, but there are important trade‐offs and considerations involved in the choice and design of such methodologies. We classify the different methodologies into three main classes and describe specific instances of algorithms under a unified notation. A modular scheme that encompasses the considered methods is also presented. A range of application scenarios is discussed, with special attention to the likelihood‐free setting and reinforcement learning. Several numerical comparisons are also provided.

Battery technologies based in multivalent charge carriers with ideally two or three electrons transferred per ion exchanged between the electrodes have large promises in raw performance numbers, most often expressed as high energy density, and are also ideally based on raw materials that are widely abundant and less expensive. Yet, these are still globally in their infancy, with some concepts (e.g. Mg metal) being more technologically mature. The challenges to address are derived on one side from the highly polarizing nature of multivalent ions when compared to single valent concepts such as Li⁺ or Na⁺ present in Li-ion or Na-ion batteries, and on the other, from the difficulties in achieving efficient metal plating/stripping (which remains the holy grail for lithium). Nonetheless, research performed to date has given some fruits and a clearer view of the challenges ahead. These include technological topics (production of thin and ductile metal foil anodes) but also chemical aspects (electrolytes with high conductivity enabling efficient plating/stripping) or high-capacity cathodes with suitable kinetics (better inorganic hosts for intercalation of such highly polarizable multivalent ions). This roadmap provides an extensive review by experts in the different technologies, which exhibit similarities but also striking differences, of the current state of the art in 2023 and the research directions and strategies currently underway to develop multivalent batteries. The aim is to provide an opinion with respect to the current challenges, potential bottlenecks, and also emerging opportunities for their practical deployment.

High quality laboratory results are critical for patient management. However, poor sample quality can impact these results and patient safety. To ensure reliable and accurate results laboratories must be aware of each analyte’s stability under various storage conditions and matrices to guarantee correct and dependable outcomes. This knowledge allows laboratories to define the allowable delay between sample collection and centrifugation/analysis for all analytes to guarantee appropriate results quality and interpretation. The EFLM WG-PRE therefore established a 4-step plan to tackle this issue, aiming to standardize and harmonize stability studies for improved comparison and meta-analysis. The plan included the development of checklists and how-to guides for performing and reporting stability studies as well as a central resource of stability data. This manuscript deals with the issue of evaluating publications and incorporating them into a central resource. To evaluate stability studies, the CRESS checklist was used to structure 20 sections used to judge the quality of studies. Each section has 4 levels of quality, with scores converted to numerical values and weighted based on expert opinion. Based on this, a final score ranging from A to D was determined. The procedure was then tested on six manuscripts and checked for agreement between expert judgements. The results demonstrated that the proposed evaluation process is a useful tool to distinguish between best in class manuscripts and those of lower quality. The EFLM WG-PRE strongly believes that the provided recommendations and checklists will help improving stability studies both in quality and standardisation.

Background Studies on switching to tenofovir alafenamide (TAF)‐based regimens raise concerns about a worse metabolic profile in people with HIV, even though most received tenofovir disoproxil fumarate (TDF) in their previous regimen. This study aims to evaluate changes in lipid fractions, glucose, and serum markers for hepatic steatosis (HS) after switching from a TDF‐ or TAF‐sparing regimen to bictegravir/emtricitabine/TAF (B/F/TAF). Methods We performed a retrospective cohort study of people with HIV who switched to B/F/TAF from TDF‐ or TAF‐sparing regimens between January 2019 and May 2022 with at least 6 months of follow‐up. The primary endpoint was the absolute change in lipid fractions at 6 months. Secondary outcomes were changes in lipid fractions at 12 months and changes in other metabolic parameters (glucose, creatinine, and HS based on the triglyceride‐to‐glucose [TyG] ratio at 6 and 12 months). Changes were analysed using mixed linear regression models with random intercept and time as a fixed effect. Results The study included 259 people with HIV (median age 55 [interquartile range (IQR) 47–60] years; 80% male; 88% Caucasian; CD4+ T‐cell count 675 [IQR 450–880] cells/mm ³ ; 84.3% HIV‐RNA <50 copies/mL). In total, 63 patients (30%) had hypertension, 93 (44%) dyslipidaemia, 30 (14%) diabetes, and 45% obesity/overweight. Most (60%) switched from integrase inhibitor‐based regimens, and 21% switched from a boosted regimen. At 6 months, significant reductions were observed in total cholesterol (−7.64 mg/dL [95% confidence interval (CI) −13.52 to −1.76; p = 0.002]), triglycerides (−23.4 [95% CI −42.07 to −4.65]; p = 0.003), and TyG ratio (−0.14 [95% CI −0.23 to −0.05]; p < 0.001). Conclusion In our real‐life cohort, the effect of switching TDF‐/TAF‐sparing regimens to triple therapy with B/F/TAF improved total cholesterol, triglycerides, and serum markers of HS at 6 months and was neutral for the remaining metabolic parameters at 12 months.

The emergence of Large Language Models (LLMs) has marked a significant change in education. The appearance of these LLMs and their associated chatbots has yielded several advantages for both students and educators, including their use as teaching assistants for content creation or summarisation. This paper aims to evaluate the capacity of LLMs chatbots to provide feedback on student exercises in a university programming course. The complexity of the programming topic in this study (concurrency) makes the need for feedback to students even more important. The authors conducted an assessment of exercises submitted by students. Then, ChatGPT (from OpenAI) and Bard (from Google) were employed to evaluate each exercise, looking for typical concurrency errors, such as starvation, deadlocks, or race conditions. Compared to the ground-truth evaluations performed by expert teachers, it is possible to conclude that none of these two tools can accurately assess the exercises despite the generally positive reception of LLMs within the educational sector. All attempts result in an accuracy rate of 50%, meaning that both tools have limitations in their ability to evaluate these particular exercises effectively, specifically finding typical concurrency errors.

Inequalities are essential in pure and applied mathematics. In particular, Opial’s inequality and its generalizations have been playing an important role in the study of the existence and uniqueness of initial and boundary value problems. In this work, some new Opial-type inequalities are given and applied to generalized Riemann-Liouville-type integral operators.

Thermal energy storage (TES) systems have been a subject of growing interest due to their potential to address the challenges of intermittent renewable energy sources. In this context, cementitious materials are emerging as a promising TES media because of their relative low cost, good thermal properties and ease of handling. This article presents a comprehensive review of studies exploring the use of cementitious materials, particularly concrete, as sensible heat storage media at varying scales, ranging from laboratory investigations to prototype evaluations. Starting from the different kinds of energy storage systems and applications where concrete has been used as a storage media, this article reviews the important properties which makes them a suitable material for the purpose. Reported observations are discussed and summarised based on concrete mix composition/design, aggregate/addition type, size gradation, etc., and performance of these materials. Finally, different cement-based prototypes are examined highlighting their strengths and weaknesses, and general conclusions are drawn.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, suddenly erupted in China at the beginning of 2020 and soon spread worldwide. This has resulted in an outstanding increase on research about the virus itself and, more in general, epidemics in many scientific fields. In this work we focus on the dynamics of the epidemic spreading and how it can be affected by the individual variability in compliance with social norms, i.e. in the adoption of preventive social norms by population’s members, which influences the infectivity rate throughout the population and through time. By means of theoretical considerations, we show how such heterogeneities of the infection rate make the population more resistant against the epidemic spreading. Finally, we depict possible empirical tests aimed to confirm our results.

Objectives This study aimed to evaluate discrepancies in potassium measurements between point-of-care testing (POCT) and central laboratory (CL) methods, focusing on the impact of hemolysis on these measurements and its impact in the clinical practice in the emergency department (ED). Methods A retrospective analysis was conducted using data from three European university hospitals: Technische Universitat Munchen (Germany), Hospital Universitario La Paz (Spain), and Erasmus University Medical Center (The Netherlands). The study compared POCT potassium measurements in EDs with CL measurements. Data normalization was performed in categories for potassium levels (kalemia) and hemolysis. The severity of discrepancies between POCT and CL potassium measurements was assessed using the reference change value (RCV). Results The study identified significant discrepancies in potassium between POCT and CL methods. In comparing POCT normo- and mild hypokalemia against CL results, differences of −4.20 % and +4.88 % were noted respectively. The largest variance in the CL was a +4.14 % difference in the mild hyperkalemia category. Additionally, the RCV was calculated to quantify the severity of discrepancies between paired potassium measurements from POCT and CL methods. The overall hemolysis characteristics, as defined by the hemolysis gradient, showed considerable variation between the testing sites, significantly affecting the reliability of potassium measurements in POCT. Conclusions The study highlighted the challenges in achieving consistent potassium measurement results between POCT and CL methods, particularly in the presence of hemolysis. It emphasised the need for integrated hemolysis detection systems in future blood gas analysis devices to minimise discrepancies and ensure accurate POCT results.

The feasibility of a novel 'magnetic arch' topology for controllecd contactless plasma beam acceleration is experimentally demonstrated using a pair of coaxial electron cyclotron resonance sources with opposing magnetic polarities, such that their respective magnetic nozzles connect to form a closed-line configuration. Retarding potential analyser measurements are taken for a single source and the two sources with same and opposing polarities, as well as no applied magnetic field, showing that the magnetic arch yields higher maximum ion current and lower plume divergence angle than other configurations, albeit the mean ion energy is lower, in agreement with existing models. This validation paves the way to clustering magnetic-nozzle-based plasma thrusters for space propulsion.

Research is a global enterprise underpinned by the general belief that findings need to be true to be considered scientific. In the complex system of scientific validation, editorial boards (EBs) play a fundamental role in guiding journals’ review process, which has led many stakeholders of sciences to metaphorically picture them as the “gatekeepers of knowledge.” In an attempt to address the academic structure that governs sciences through editorial board interlocking (EBI, the cross-presence of EB members in different journals) and social network analysis, the aim of this study is threefold: first, to map the connection between fields of knowledge through EBI; second, to visualize and empirically test the distance between social and general sciences; and third, to uncover the institutional structure (i.e., universities) that governs these connections. Our findings, based on the dataset collected through the Open Editors initiative for the journals indexed in the JCR, revealed a substantial level of collaboration between all fields, as suggested by the connections between EBs. However, there is a statistically significant difference between the weight of the edges and the path lengths connecting the fields of natural sciences to the fields of social sciences (compared to the connections within), indicating the development of different research cultures and invisible colleges in these two research areas. The results also show that a central group of US institutions dominates most journal EBs, indirectly suggesting that US scientific norms and values still prevail in all fields of knowledge. Overall, our study suggests that scientific endeavor is highly networked through EBs.