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The fact that neutrinos carry a non-vanishing rest mass is evidence ofphysics beyond the Standard Model of elementary particles. Their absolute massbears important relevance from particle physics to cosmology. In this work, wereport on the search for the effective electron antineutrino mass with theKATRIN experiment. KATRIN performs precision spectroscopy of the tritium$\beta$-decay close to the kinematic endpoint. Based on the first fiveneutrino-mass measurement campaigns, we derive a best-fit value of $m_u^{2} ={-0.14^{+0.13}_{-0.15}}~\mathrm{eV^2}$, resulting in an upper limit of $m_u <{0.45}~\mathrm{eV}$ at 90 % confidence level. With six times the statistics ofprevious data sets, amounting to 36 million electrons collected in 259measurement days, a substantial reduction of the background level and improvedsystematic uncertainties, this result tightens KATRIN's previous bound by afactor of almost two.

Racialized narratives of academic ability, perpetuated by ahistorical interpretations of student performance data, have led to educational policies focusing on short-term solutions, instead of the ongoing legacies of racism and settler colonialism. The aim of this paper is to show how the racially defined achievement gap operates within the structure of settler colonialism. Informed by theories of settler colonialism (Tuck & Yang, 2012, Veracini, 2010) and critical race theory (Harris, 1993; Ladson-Billings & Tate, 1995), I closely examine some Toronto District School Board documents that address the so-called achievement and opportunity gaps. Using critical discourse analysis, this paper shows how the notion of achievement is racialized to protect white settler property rights, and how the discourse of achievement gaps functions as a settler technology to concurrently include and exclude individuals from the settler project. Understanding the settler colonial constructions of race brings to the foreground the relations between Indigenous erasure, anti-Blackness, and othering of racialized communities within the contemporary multicultural nation (Haque, 2012; Tuck & Gorlewski, 2016).

1. INTRODUCTION Language is the most flexible and common symbolic device that can be used in the construction of a speaker's identity (Bucholtz and Hall 2004). Similarly, identity is a [...], Speakers can project different personae when engaging in stylistic practices, which can be characterised by a consistent or variable use of linguistic features. This becomes relevant when addressing how politicians attempt to position themselves in communicative interactions through their use of language. The present study takes a third-wave approach to the analysis of Donald Trump's sociolinguistic behaviour across various speech events by focusing on the indexical mutability of PRICE/PRIZE and R-Dropping. The results evidence intra-speaker variation in Trump's populist speech style used for interactional and political purposes in that he alters his use of mainstream and non-mainstream forms as he operates across speech events. Thus, Trump exhibits a different sociolinguistic performance across different contexts, where he also takes a different approach towards the management and projection of his public persona, and therefore, transmits different social meanings through his language use. The results further suggest that the context, format and audience of the political event and the social meanings indexed by the selected linguistic features are what condition Trump's sociolinguistic behaviour. We conclude that Trump's speech style is characterised by the meaningful choices he makes about the linguistic resource to be used in a specific context and its corresponding social meaning. Keywords: stylistic practices; persona management processes; speaker's agency; political identity; social meaning; indexing mutability Las y los hablantes pueden proyectar diferentes personalidades cuando participan en practicas estilisticas, que pueden caracterizarse por un uso constante o variable de rasgos linguisticos. Esto cobra relevancia cuando abordamos como las y los politicos intentan posicionarse en las interacciones comunicativas a traves del uso del lenguaje. Este estudio adopta una perspectiva de tercera ola para el analisis del comportamiento sociolinguistico de Donald Trump en diferentes contextos politicos centrandose en la mutabilidad indexical de PRICE/PRIZE y R-Dropping. Los resultados evidencian una variacion intra-hablante en el estilo de habla populista de Trump con fines interactivos y politicos, ya que su uso de variantes convencionales y no convencionales se ve alterado conforme cambia el contexto del evento de habla. Asi, Trump exhibe un comportamiento sociolinguistico diferente a traves de diferentes contextos, adopta un enfoque diferente hacia la gestion y proyeccion de su personalidad publica y, por lo tanto, transmite significados sociales diferentes a traves del uso del lenguaje. Los resultados sugieren que el contexto, el formato y la audiencia del evento politico y los significados sociales indexados por PRICE/PRIZE y R-Dropping condicionan el comportamiento sociolinguistico de Trump. Concluimos que el estilo de habla de Trump se caracteriza por las elecciones que hace sobre el recurso linguistico a utilizar en un contexto especifico y su correspondiente significado social. Palabras clave: practicas estilisticas; procesos de gestion de personalidad; agencia del hablante; identidad politica; significado social; mutabilidad de indexacion

Abstract Financial fraud negatively impacts organizational administrative processes, particularly affecting owners and/or investors seeking to maximize their profits. Addressing this issue, this study presents a literature review on financial fraud detection through machine learning techniques. The PRISMA and Kitchenham methods were applied, and 104 articles published between 2012 and 2023 were examined. These articles were selected based on predefined inclusion and exclusion criteria and were obtained from databases such as Scopus, IEEE Xplore, Taylor & Francis, SAGE, and ScienceDirect. These selected articles, along with the contributions of authors, sources, countries, trends, and datasets used in the experiments, were used to detect financial fraud and its existing types. Machine learning models and metrics were used to assess performance. The analysis indicated a trend toward using real datasets. Notably, credit card fraud detection models are the most widely used for detecting credit card loan fraud. The information obtained by different authors was acquired from the stock exchanges of China, Canada, the United States, Taiwan, and Tehran, among other countries. Furthermore, the usage of synthetic data has been low (less than 7% of the employed datasets). Among the leading contributors to the studies, China, India, Saudi Arabia, and Canada remain prominent, whereas Latin American countries have few related publications.

Vocabulary size is a crucial early indicator of language development, for both monolingual and bilingual children. Assessing vocabulary in bilingual children is complex because they learn words in two languages, and there remains significant controversy about how to best measure their vocabulary size, especially in relation to monolinguals. This study compared monolingual vocabulary with different metrics of bilingual vocabulary, including combining vocabulary across languages to count either the number of words or the number of concepts lexicalized and assessing vocabulary in a single language. Data were collected from parents of 743 infants and toddlers aged 8-33 months learning French and/or English, using the MacArthur-Bates Communicative Development Inventories. The results showed that the nature and magnitude of monolingual-bilingual differences depended on how bilinguals' vocabulary was measured. Compared with monolinguals, bilinguals had larger expressive and receptive word vocabularies, similarly sized receptive concept vocabularies and smaller expressive concept vocabularies. Bilinguals' single-language vocabularies were smaller than monolinguals' vocabularies. The study highlights the need to better understand the role of translation equivalents in bilingual vocabulary development and the potential developmental differences in receptive and expressive vocabularies.

Summary: Background: Surgical care holds significant importance in healthcare, especially in low and middle-income countries, as at least 50% of the 4.2 million deaths within the initial 30 days following surgery take place in these countries. The Lancet Commission on Global Surgery proposed six indicators to enhance surgical care. In Colombia, studies have been made using secondary data. However, strategies to reduce perioperative mortality have not been implemented. This study aims to describe the fourth indicator, perioperative mortality rate (POMR), with primary data in Colombia. Methods: A multicentre prospective cohort study was conducted across 54 centres (hospitals) in Colombia. Each centre selected a 7-day recruitment period between 05/2022 and 01/2023. Inclusion criteria involved patients over 18 years of age undergoing surgical procedures in operating rooms. Data quality was ensured through a verification guideline and statistical analysis using mixed-effects multilevel modelling with a case mix analysis of mortality by procedure-related, patient-related, and hospital-related conditions. Findings: 3807 patients were included with a median age of 48 (IQR 32–64), 80.3% were classified as ASA I or II, and 27% of the procedures had a low-surgical complexity. Leading procedures were Orthopedics (19.2%) and Gynaecology/Obstetrics (17.7%). According to the Clavien–Dindo scale, postoperative complications were distributed in major complications (11.7%, 10.68–12.76) and any complication (31.6%, 30.09–33.07). POMR stood at 1.9% (1.48–2.37), with elective and emergency surgery mortalities at 0.7% (0.40–1.23) and 3% (2.3–3.89) respectively. Interpretation: The POMR was higher than the ratio reported in previous national studies, even when patients had a low–risk profile and low-complexity procedures. The present research represents significant public health progress with valuable insights for national decision-makers to improve the quality of surgical care. Funding: This work was supported by Universidad del Rosario and Fundación Cardioinfantil-Instituto de Cardiología grant number CTO-057-2021, project-ID IV-FGV017.

Many bioinformatics tools are available for the quantitative analysis of proteomics experiments. Most of these tools use a dedicated statistical model to derive absolute quantitative protein values from mass spectrometry (MS) data. Here, we present iSanXoT, a standalone application that processes relative abundances between MS signals and then integrates them sequentially to upper levels using the previously published Generic Integration Algorithm (GIA). iSanXoT offers unique capabilities that complement conventional quantitative software applications, including statistical weighting and independent modeling of error distributions in each integration, aggregation of technical or biological replicates, quantification of posttranslational modifications, and analysis of coordinated protein behavior. iSanXoT is a standalone, user-friendly application that accepts output from popular proteomics pipelines and enables unrestricted creation of quantification workflows and fully customizable reports that can be reused across projects or shared among users. Numerous publications attest the successful application of diverse integrative workflows constructed using the GIA for the analysis of high-throughput quantitative proteomics experiments. iSanXoT has been tested with the main operating systems. Download links for the corresponding distributions are available at https://github.com/CNIC-Proteomics/iSanXoT/releases.

Diverse pathogenic fungi can produce severe infections in immunocompromised patients, thereby justifying intensive care unit (ICU) admissions. In some cases, the infections can develop in immunocompromised patients who were previously admitted to the ICU. Aspergillus spp., Pneumocystis jirovecii, Candida spp., and Mucorales are the fungi that are most frequently involved in these infections. Diagnosis continues to be challenging because symptoms and signs are unspecific. Herein, we provide an in-depth review about the diagnosis, with emphasis on recent advances, and treatment of these invasive fungal infections in the ICU setting.

Speakers can project different personae when engaging in stylistic practices, which can be characterised by a consistent or variable use of linguistic features. This becomes relevant when addressing how politicians attempt to position themselves in communicative interactions through their use of language. The present study takes a third wave approach to the analysis of Donald Trump’s sociolinguistic behaviour across various speech events by focusing on the indexical mutability of PRICE/PRIZE and R-Dropping. The results evidence intra-speaker variation in Trump’s populist speech style used for interactional and political purposes in that he alters his use of + mainstream and non-mainstream forms as he operates across speech events. Thus, Trump exhibits a different sociolinguistic performance across different contexts, where he also takes a different approach towards the management and projection of his public persona, and therefore, transmits different social meanings through his language use. The results further suggest that the context, format and audience of the political event and the social meanings indexed by the selected linguistic features are what condition Trump’s sociolinguistic behaviour. We conclude that Trump’s speech style is characterised by the meaningful choices he makes about the linguistic resource to be used in a specific context and its corresponding social meaning.

Julia Sabin,1 Elisa Salas,2 Jesús Martín-Martínez,3 Antonio Candeliere-Merlicco,4 Francisco Javier Barrero Hernández,5 Ana María Alonso Torres,6 José Luis Sánchez-Menoyo,7 Laura Borrega,8 María Rodríguez-Rodríguez,9 Montserrat Gómez-Gutiérrez,10 Sara Eichau,11 Miguel Ángel Hernández-Pérez,12 Carmen Calles,13 Eva Fernandez-Diaz,14 Olga Carmona,15 Aida Orviz,16 Ana López-Real,17 Pablo López-Muñoz,18 Amelia Mendoza Rodríguez,19 Eduardo Aguera-Morales,20 Jorge Maurino2 1Department of Neurology, Hospital Universitario Puerta de Hierro, Madrid, Spain; 2Medical Department, Roche Farma, Madrid, Spain; 3Department of Neurology, Hospital Universitario Miguel Servet, Zaragoza, Spain; 4Department of Neurology, Hospital Rafael Méndez, Lorca, Spain; 5Department of Neurology, Hospital Clínico Universitario San Cecilio, Granada, Spain; 6Department of Neurology, Hospital Regional Universitario de Málaga, Málaga, Spain; 7Department of Neurology, Hospital de Galdakao-Usansolo, Galdakao, Spain; 8Department of Neurology, Hospital Universitario Fundación Alcorcón, Alcorcón, Spain; 9Department of Neurology, Hospital Universitario Lucus Augusti, Lugo, Spain; 10Department of Neurology, Hospital San Pedro de Alcántara, Cáceres, Spain; 11Department of Neurology, Hospital Universitario Virgen Macarena, Sevilla, Spain; 12Department of Neurology, Hospital Universitario Nuestra Señora de Candelaria, Tenerife, Spain; 13Department of Neurology, Hospital Universitario Son Espases, Palma de Mallorca, Spain; 14Department of Neurology, Hospital Universitario de Albacete, Albacete, Spain; 15Department of Neurology, Fundació Salut Empordà, Figueres, Spain; 16Department of Neurology, Hospital Universitario Fundación Jiménez Díaz, Madrid, Spain; 17Department of Neurology, Complejo Hospitalario Universitario A Coruña, A Coruña, Spain; 18Department of Neurology, Hospital Arnau de Vilanova, Llíria, Spain; 19Department of Neurology, Complejo Asistencial de Segovia, Segovia, Spain; 20Department of Neurology, Hospital Universitario Reina Sofía, Córdoba, SpainCorrespondence: Jorge Maurino, Ribera del Loira 50, Madrid, 28042, Spain, Tel + 34 913 24 81 00, Email jorge.maurino@roche.comPurpose: Shared decision-making is critical in multiple sclerosis (MS) due to the uncertainty of the disease trajectory over time and the large number of treatment options with differing efficacy, safety and administration characteristics. The aim of this study was to assess patients’ decisional conflict regarding the choice of a disease-modifying therapy and its associated factors in patients with mid-stage relapsing-remitting multiple sclerosis (RRMS).Methods: A multicenter, non-interventional study was conducted. Adult patients with a diagnosis of RRMS (2017 revised McDonald criteria) and disease duration of 3 to 8 years were included. The level of uncertainty experienced by a patient when faced with making a treatment choice was assessed using the 4-item Decisional Conflict Scale. A battery of patient-reported and clinician-rated measures was administered to obtain information on symptom severity, illness perception, illness-related uncertainty, regret, MS knowledge, risk taking behavior, preferred role in the decision-making process, cognition, and self-management. Patients were recruited during routine follow-up visits and completed all questionnaires online using electronic tablets at the hospital. A multivariate logistic regression analysis was conducted.Results: A total of 201 patients were studied. Mean age (Standard deviation) was 38.7 (8.4) years and 74.1% were female. Median disease duration (Interquartile range) was 6.0 (4.0– 7.0) years. Median EDSS score was 1.0 (0– 2.0). Sixty-seven (33.3%) patients reported a decisional conflict. These patients had lower MS knowledge and more illness uncertainty, anxiety, depressive symptoms, fatigue, subjective symptom severity, a threatening illness perception, and poorer quality of life than their counterparts. Lack of decisional conflict was associated with MS knowledge (Odds ratio [OR]=1.195, 95% CI 1.045, 1.383, p=0.013), self-management (OR=1.049, 95% CI 1.013, 1.093, p=0.018), and regret after a healthcare decision (OR=0.860, 95% CI 0.756, 0.973, p=0.018) in the multivariate analysis.Conclusion: Decisional conflict regarding the selection of a disease-modifying therapy was a common phenomenon in patients with mid-stage RRMS. Identifying factors associated with decisional conflict may be useful to implement preventive strategies that help patients better understand their condition and strengthen their self-management resources.Keywords: multiple sclerosis, disease-modifying therapies, decision-making, decisional conflict, disease-related knowledge, self-management

We present the capabilities of a compact dual-wavelength depolarization lidar to assess the spatiotemporal variations in aerosol properties aboard moving vectors. Our approach involves coupling the lightweight Cimel CE376 lidar, which provides measurements at 532 and 808 nm and depolarization at 532 nm, with a photometer to monitor aerosol properties. The assessments, both algorithmic and instrumental, were conducted at ATOLL (ATmospheric Observatory of LiLle) platform operated by the Laboratoire d'Optique Atmosphérique (LOA), in Lille, France. An early version of the CE376 lidar co-located with the CE318-T photometer and with a multi-wavelength Raman lidar were considered for comparisons and validation. We developed a modified Klett inversion method for simultaneous two-wavelength elastic lidar and photometer measurements. Using this setup, we characterized aerosols during two distinct events of Saharan dust and dust smoke aerosols transported over Lille in spring 2021 and summer 2022. For validation purposes, comparisons against the Raman lidar were performed, demonstrating good agreement in aerosol properties with relative differences of up to 12 % in the depolarization measurements. Moreover, a first dataset of CE376 lidar and photometer performing on-road measurements was obtained during the FIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality) field campaign deployed in summer 2019 over the northwestern USA. By lidar and photometer mapping in 3D, we investigated the transport of released smoke from active fire spots at William Flats (northeast WA, USA). Despite extreme environmental conditions, our study enabled the investigation of aerosol optical properties near the fire source, distinguishing the influence of diffuse, convective, and residual smoke. Backscatter, extinction profiles, and column-integrated lidar ratios at 532 and 808 nm were derived for a quality-assured dataset. Additionally, the extinction Ångström exponent (EAE), color ratio (CR), attenuated color ratio (ACR), and particle linear depolarization ratio (PLDR) were derived. In this study, we discuss the capabilities (and limitations) of the CE376 lidar in bridging observational gaps in aerosol monitoring, providing valuable insights for future research in this field.

The research aims to assess the possibilities and challenges of artificial intelligence (AI) for the development of the teaching and learning of journalistic writing techniques in the university educational context. The main objective consists of analysing the abilities of AI to solve the composition of different journalistic texts¸ both informative and opinion, and the quality of the result, as well as other applications of AI in journalistic writing. The text tries to contribute to the knowledge on the use of AI by teachers and students in the teaching and learning process. A mixed methodology has been used to develop the research: on the one hand, descriptive and comparative, based on surveys to university professors in Spain specialised in this subject and to students taking related contents in their studies, also in this context; on the other hand, an experimental research is included among professors trained in the field of Journalistic Writing, who are asked for the qualified correction of an exam, anonymous, actually carried out with the AI system, ChatGPT. After weighing the results, each of them is interviewed in depth about the quality of the texts, their strengths, and weaknesses. The results show that AI is beginning to be used in the university context by students and professors. In the specific field of journalistic writing, its use for the moment is limited to assisting tasks in the writing process or suggesting topics, while the automatic generation of content is not widely accepted due to the ethical implications that it entails, especially those related to the originality of content. Teachers value the potential of this technology for writing simple and informative pieces but observe limitations at deeper levels of knowledge and in hybrid texts.

The increasing expansion and the rising demand for food require a greater intensification in the production of Nile tilapia (Oreochromis niloticus), and genetic improvement programs are essential to achieve this goal. In managing these programs, new genetic material is introduced after several generations of selections to reduce inbreeding and enhance genetic diversity. In this sense, analyzing the zootechnical parameters of these introductions, with an emphasis on the use of nutritional additives, is of great importance for understanding their impact on breeding programs. Thus, the aim of this study was to evaluate the zootechnical parameters and hepatosomatic index of two genetic strains of Nile tilapia from the genetic improvement program fed with β-Glucan + Mannan oligosaccharide (βG+MOS). This study utilized a 2 × 2 factorial design containing two genetic groups and two treatments with βG+MOS (Control, 0.2%). The groups were formed from the 12th generation of the Tilamax genetic improvement program (TILAMAX) and by crossing Tilamax with an introduced test strain (CBTILAMAX). In total, 96 tilapias (31.1 ± 5.73 g) were distributed into 16 aquariums, with 6 fish per aquarium, 24 per group, and four repetitions. The experimental period lasted for 41 days, and the water parameters were measured daily and maintained under ideal conditions. The condition factor and hepatosomatic index were analyzed. Final weight, total length, and standard length were measured, and other zootechnical parameters were calculated based on these data. The condition factor showed that the fish in both groups exhibited adequate health and growth during the experiment, with no differences in strain or use of additives. Similarly, the hepatosomatic index did not differ between the groups, indicating that liver size was proportional to fish body size. Similarly, no significant differences (P>0.05) were observed for the other zootechnical parameters evaluated (initial and final total and standard lengths, final weight, total weight gain, condition factor using total and standard lengths, and specific growth rate). Based on these results, it is concluded that there were no differences between TILAMAX and CBTILAMAX related to performance and health under the effect of feeding with βG+MOS. This result is positive regarding the introduction of the test strain into the Tilamax genetic improvement program and establishes a starting point for further research that may provide greater clarity on its future effects.

El web scraping es una técnica que se usa para recopilar datos en Internet y almacenarlos en una base de datos. Ese proceso se usa, entre otras cosas, para entrenar modelos de inteligencia artificial generativa y ha generado controversia alrededor del mundo debido a sus riesgos legales. En este artículo se analizará la viabilidad legal del uso de técnicas de web scraping y se abordarán tensiones relacionadas con asuntos contractuales de los términos de servicio de las páginas web, los riesgos legales que se desprenden de estas técnicas y, en particular, del uso de obras protegidas en el entrenamiento de modelos de inteligencia artificial generativa, de protección de datos personales y de implicaciones penales; las licencias open source, open access y de Creative Commons, así como también los datos de dominio público y en cabeza del Estado colombiano. Este artículo pretende ser un marco teórico inicial para la discusión del web scraping en modelos de inteligencia artificial generativa, dado que, a la fecha de elaboración de este artículo, el desarrollo normativo y jurisprudencial sobre este tema es aún incipiente.