Yasushi Kawase, Bodhayan Roy, Mohammad Azharuddin Sanpui
A Latin square is an $n \times n$ matrix filled with $n$ distinct symbols, each of which appears exactly once in each row and exactly once in each column. We introduce a problem of allocating $n$ indivisible items among $n$ agents over $n$ rounds while satisfying the Latin square constraint. This constraint ensures that each agent receives no more than one item per round and receives each item at most once. Each agent has an additive valuation on the item--round pairs. Real-world applications like scheduling, resource management, and experimental design require the Latin square constraint to satisfy fairness or balancedness in allocation. Our goal is to find a partial or complete allocation that maximizes the sum of the agents' valuations (utilitarian social welfare) or the minimum of the agents' valuations (egalitarian social welfare). For the problem of maximizing utilitarian social welfare, we prove NP-hardness even when the valuations are binary additive. We then provide $(1-1/e)$ and $(1-1/e)/4$-approximation algorithms for partial and complete settings, respectively. Additionally, we present fixed-parameter tractable (FPT) algorithms with respect to the order of Latin square and the optimum value for both partial and complete settings. For the problem of maximizing egalitarian social welfare, we establish that deciding whether the optimum value is at most $1$ or at least $2$ is NP-hard for both the partial and complete settings, even when the valuations are binary. Furthermore, we demonstrate that checking the existence of a complete allocation that satisfies each of envy-free, proportional, equitable, envy-free up to any good, proportional up to any good, or equitable up to any good is NP-hard, even when the valuations are identical.
Miguel Romero-Arjona, Pablo Valle, Juan C. Alonso
et al.
The battle for AI leadership is on, with OpenAI in the United States and DeepSeek in China as key contenders. In response to these global trends, the Spanish government has proposed ALIA, a public and transparent AI infrastructure incorporating small language models designed to support Spanish and co-official languages such as Basque. This paper presents the results of Red Teaming sessions, where ten participants applied their expertise and creativity to manually test three of the latest models from these initiatives$\unicode{x2013}$OpenAI o3-mini, DeepSeek R1, and ALIA Salamandra$\unicode{x2013}$focusing on biases and safety concerns. The results, based on 670 conversations, revealed vulnerabilities in all the models under test, with biased or unsafe responses ranging from 29.5% in o3-mini to 50.6% in Salamandra. These findings underscore the persistent challenges in developing reliable and trustworthy AI systems, particularly those intended to support Spanish and Basque languages.
Silviana Fernandes Mariz, Francisco Thiago Rocha Vasconcelos
Elaboramos um levantamento da produção acadêmica em língua portuguesa, especialmente nas Ciências Sociais, sobre a participação de mulheres em redes de tráfico de drogas ilícitas entre América Latina, África e Europa, com o objetivo de analisar principalmente a situação das mulheres dos Países Africanos de Língua Oficial Portuguesa (PALOPs). De início, situamos o fenômeno em meio aos efeitos da globalização, resultando na fragilização dos Estados frente ao descontrole do fluxo ilegal de mercadorias e pessoas e à “colonização” de rotas prévias de emigração de africanos para Europa, Estados Unidos e Brasil pelas novas rotas do tráfico internacional. Por fim, enfocamos o lugar das mulheres africanas como migrantes, prisioneiras e “mulas” que são recrutadas para transportar drogas.
El texto gira alrededor de discusiones metodológicas sobre la participación de las mujeres en diferentes guerras, sobre sus procesos escriturales. Dichas reflexiones dan cuenta de cómo ciertas naciones moldean mecanismos generizados de exclusión e inclusión, que producen –al atravesar crisis sociales– experiencias, coyunturas, rupturas y permanencias en las fronteras que las personas y sociedades pueden/deben (o no), cruzar. Posteriormente, se analiza cómo ciertas investigaciones sobre guerras posicionan a las mujeres como sujetos que, a través de la palabra escrita, accionan y construyen estratégicamente sus identidades, entornos y narrativas en clave de lo personal y también de lo social, lo político y la lucha. Al problematizar la relación guerra-nación-género- escritura permite mostrar cómo se moldea, (re)produce y (re)define el género –lo masculino y lo femenino– y, cómo éste naturaliza, justifica y legitima la existencia de las guerras y las naciones.
History (General) and history of Europe, Latin America. Spanish America
Abstract Aims There is a lack of evidence related to the prevalence of mental health symptoms as well as their heterogeneities during the coronavirus disease 2019 (COVID-19) pandemic in Latin America, a large area spanning the equator. The current study aims to provide meta-analytical evidence on mental health symptoms during COVID-19 among frontline healthcare workers, general healthcare workers, the general population and university students in Latin America. Methods Bibliographical databases, such as PubMed, Embase, Web of Science, PsycINFO and medRxiv, were systematically searched to identify pertinent studies up to August 13, 2021. Two coders performed the screening using predefined eligibility criteria. Studies were assigned quality scores using the Mixed Methods Appraisal Tool. The double data extraction method was used to minimise data entry errors. Results A total of 62 studies with 196 950 participants in Latin America were identified. The pooled prevalence of anxiety, depression, distress and insomnia was 35%, 35%, 32% and 35%, respectively. There was a higher prevalence of mental health symptoms in South America compared to Central America (36% v. 28%, p < 0.001), in countries speaking Portuguese (40%) v. Spanish (30%). The pooled prevalence of mental health symptoms in the general population, general healthcare workers, frontline healthcare workers and students in Latin America was 37%, 34%, 33% and 45%, respectively. Conclusions The high yet heterogenous level of prevalence of mental health symptoms emphasises the need for appropriate identification of psychological interventions in Latin America.
Research on improving automatic speaker verification systems to detect speech spoofing has focused mainly on English, with little attention given to other languages creating a significant gap in language coverage. This paper introduces HABLA, the first voice anti-spoofing dataset in the Spanish language including Argentinian, Colombian, Peruvian, Venezuelan, and Chilean accents. The dataset provided by HABLA comprises over 22,000 authentic speech samples from male and female speakers hailing from five distinct Latin American nations as well as 58,000 spoof samples that were generated through the use of six different speech synthesis strategies, including recent voice conversion and text-to-speech algorithms. Finally, initial findings on the efficacy of pre-existing Antispoofing Systems models are presented along with concerns regarding their performance in languages other than English.
Philipp Koch, Gilary Vera Nuñez, Esteban Garces Arias
et al.
The Bavarian Academy of Sciences and Humanities aims to digitize its Medieval Latin Dictionary. This dictionary entails record cards referring to lemmas in medieval Latin, a low-resource language. A crucial step of the digitization process is the Handwritten Text Recognition (HTR) of the handwritten lemmas found on these record cards. In our work, we introduce an end-to-end pipeline, tailored to the medieval Latin dictionary, for locating, extracting, and transcribing the lemmas. We employ two state-of-the-art (SOTA) image segmentation models to prepare the initial data set for the HTR task. Furthermore, we experiment with different transformer-based models and conduct a set of experiments to explore the capabilities of different combinations of vision encoders with a GPT-2 decoder. Additionally, we also apply extensive data augmentation resulting in a highly competitive model. The best-performing setup achieved a Character Error Rate (CER) of 0.015, which is even superior to the commercial Google Cloud Vision model, and shows more stable performance.
Sanja Stajner, Daniel Ferres, Matthew Shardlow
et al.
Even in highly-developed countries, as many as 15-30\% of the population can only understand texts written using a basic vocabulary. Their understanding of everyday texts is limited, which prevents them from taking an active role in society and making informed decisions regarding healthcare, legal representation, or democratic choice. Lexical simplification is a natural language processing task that aims to make text understandable to everyone by replacing complex vocabulary and expressions with simpler ones, while preserving the original meaning. It has attracted considerable attention in the last 20 years, and fully automatic lexical simplification systems have been proposed for various languages. The main obstacle for the progress of the field is the absence of high-quality datasets for building and evaluating lexical simplification systems. We present a new benchmark dataset for lexical simplification in English, Spanish, and (Brazilian) Portuguese, and provide details about data selection and annotation procedures. This is the first dataset that offers a direct comparison of lexical simplification systems for three languages. To showcase the usability of the dataset, we adapt two state-of-the-art lexical simplification systems with differing architectures (neural vs.\ non-neural) to all three languages (English, Spanish, and Brazilian Portuguese) and evaluate their performances on our new dataset. For a fairer comparison, we use several evaluation measures which capture varied aspects of the systems' efficacy, and discuss their strengths and weaknesses. We find a state-of-the-art neural lexical simplification system outperforms a state-of-the-art non-neural lexical simplification system in all three languages. More importantly, we find that the state-of-the-art neural lexical simplification systems perform significantly better for English than for Spanish and Portuguese.
This manuscript extensively reviews applications, extensions, and models derived from the Bayesian ideal point estimator. We primarily focus our attention on studies conducted in the United States as well as Latin America. First, we provide a detailed description of the Bayesian ideal point estimator. Next, we propose a new taxonomy to synthesize and frame technical developments and applications associated with the estimator in the context of North American and Latin American governing bodies. The literature available in Latin America allows us to conclude that few legislatures in the region have been analyzed using the methodology under discussion. Also, we highlight those parliaments of Latin America embedded in democratic presidential systems as novel scenarios for operationalizing the electoral behavior of legislative bodies through nominal voting data. Our findings show some alternatives for future research. Finally, to fix ideas and illustrate the capabilities of the Bayesian ideal point estimator, we present an application involving the Colombian House of Representatives 2010-2014.
ABSTRACT This systematic review aims to summarize the prevalence of anxiety, depression, and insomnia in the general adult population and healthcare workers (HCWs) in several key regions worldwide during the first year of the COVID pandemic. Several literature databases were systemically searched for meta-analyses published by 22 September 2021 on the prevalence rates of mental health symptoms worldwide. The prevalence rates of mental health symptoms were summarized based on 388 empirical studies with a total of 1,067,021 participants from six regions and four countries. Comparatively, Africa and South Asia had the worse overall mental health symptoms, followed by Latin America. The research effort on mental health during COVID-19 has been highly skewed in terms of the scope of countries and mental health outcomes. The mental health symptoms are highly prevalent yet differ across regions, and such evidence helps to enable prioritization of mental health assistance efforts to allocate attention and resources based on the regional differences in mental health. HIGHLIGHTS The prevalence rates of mental health symptoms were summarized from 388 studies of 1,067,021 individuals in Africa, Asia, Eastern Europe, and Latin America. Mental health symptoms under COVID-19 pandemic were worst in Africa and South Asia followed by Latin America.
A quandle is an algebraic structure satisfying three axioms: idempotency, right-invertibility and right self-distributivity. In quandles, right translations are permutations. The profile of a quandle is the list of cycle structures, one per right translation in the quandle. In this note we prove that if, for each cycle structure in the profile of a quandle, no two cycle lengths are equal, then the quandle is latin -- this is the sufficient condition mentioned in the title.
An embedding of a code is a mapping that preserves distances between codewords. We prove that any code with code distance $ρ$ and length $d$ can be embedded into an MDS code with the same code distance and length but under a larger alphabet. As a corollary we obtain embeddings of systems of partial mutually orthogonal Latin cubes and $n$-ary quasigroups.
Introduction Cancer incidence and mortality in Latin America are rising. While effective cancer screening services, accessible to the whole population and enabling early cancer detection are needed, existing research shows the existence of disparities in screening uptake in the region. Objective We conducted a systematic review to investigate the socioeconomic determinants for the disparities in the use of breast, cervical and colorectal cancer screening services in Latin America. Methods We searched for studies reporting on socioeconomic determinants impacting on access to breast, cervical and colorectal cancer screening, published from 2009 through 2018. The studies that qualified for inclusion contained original analyses on utilisation of breast, cervical and colorectal cancer screening across socioeconomic levels in Latin America. For each study, paired reviewers performed a quality analysis followed by detailed review and data extraction. Results Twenty-four articles that met the eligibility criteria and were of sufficient quality were included in this review. Thirteen of the included articles were written in English, eight in Portuguese and three in Spanish, and they reported on the use of breast or cervical cancer screening. No studies were found on the socioeconomic determinants regarding the utilisation of colorectal cancer screening in Latin America. Low income, low education level, lack of health insurance and single marital status were all found to be determinants of underuse of breast and cervical cancer screening services. Conclusions Cancer screening programs in the region must prioritize reaching those populations that underuse cancer screening services to ensure equitable access to preventive services. It is important to develop national screening programmes that are accessible to all (including uninsured people) through, for example, the use of mobile units for mammography and self-screening methods.
As Venezuela’s leader, Hugo Chávez utilized the media intensively and innovatively to boost his radical political project. The broadcast talk-show Aló Presidente became the most important component of his communication strategy, followed by his use of blanket broadcast messages. Chávez’s flagship program subverted liberal tenets, and has to this day served as a template in Latin America for populist communication. This study examined the ways Venezuelan journalists and media professionals have understood Chávez’s hyper-mediatic leadership –with special emphasis on Aló Presidente– and the impact the program and the official blanket messages had on their practice. A wide array of journalists, media practitioners, and commentators were interviewed about their views regarding Chávez’s media strategies and Aló Presidente, and tensions arising between different ideals of normative journalistic practice. Opinions among local journalists about the above-mentioned issues, this study found, are divided within a highly-polarized frame. And normative media ideals of liberal trends were challenged by pro-Chávez journalists, while an important faction of media professionals maintained that such practices are non-democratic. Resumen En calidad de líder de Venezuela, Hugo Chávez utilizó los medios comunicacionales de manera intensa e innovadora, para así promover su radical proyecto político. El programa televisivo Aló Presidente llegó a convertirse en el componente más importante de su estrategia comunicacional, seguido del uso de sus ‘cadenas’ audiovisuales. Este programa insignia de Chávez subvertía ideales liberales, y hasta el día de hoy funciona como un modelo de comunicación populista en América Latina. El presente estudio examina las formas en las que periodistas y profesionales de medios venezolanos entienden el liderazgo híper-mediático de Chávez –con especial énfasis en Aló Presidente– y el impacto que dicho programa y los mensajes ‘en cadena’ han ejercido en su oficio. Una amplia gama de periodistas, profesionales y comentaristas de medios fueron entrevistados sobre sus opiniones en relación a las estrategias mediáticas de Chávez, Aló Presidente, y las tensiones que surgen entre variados ideales sobre la práctica de periodismo normativo. El estudio revela que las opiniones de los periodistas locales sobre los asuntos arriba mencionados se dividen dentro de un marco de alta polarización. Igualmente, los ideales mediáticos normativos de tendencias liberales son desafiados por periodistas pro–Chávez, al tiempo que una facción importante de profesionales de medios sostiene que tales prácticas son anti-democráticas. Palabras clave: estudios de periodismo; periodismo y práctica de los medios; normativa mediática; populismo; Venezuela; Hugo Chávez; Aló Presidente
Neste artigo, discutiremos o processo de naturalização instaurado no Império do Brasil a partir da Lei de 23 de outubro de 1823. Discorreremos, brevemente, sobre os motivos que estimularam os estrangeiros a buscarem o título de cidadão brasileiro e exporemos os trâmites e as dificuldades enfrentadas por aqueles que optavam por se tornar cidadãos. Buscaremos explorar tanto a perspectiva estatal quanto a dos indivíduos neste percurso. Daremos ênfase à documentação produzida no âmbito da Província de Santa Catarina embora tratemos de um problema presente em todo o Império. A análise e exposição dos termos de declaração e das cartas de naturalização registrados na Câmara Municipal de Desterro e disponíveis no Arquivo Histórico do Município de Florianópolis farão parte deste processo.
This paper deals with distinct computational methods to enumerate the set $\mathrm{PLR}(r,s,n;m)$ of $r \times s$ partial Latin rectangles on $n$ symbols with $m$ non-empty cells. For fixed $r$, $s$, and $n$, we prove that the size of this set is a symmetric polynomial of degree $3m$, and we determine the leading terms (the monomials of degree $3m$ through $3m-9$) using inclusion-exclusion. For $m \leq 13$, exact formulas for these symmetric polynomials are determined using a chromatic polynomial method. Adapting Sade's method for enumerating Latin squares, we compute the exact size of $\mathrm{PLR}(r,s,n;m)$, for all $r \leq s \leq n \leq 7$, and all $r \leq s \leq 6$ when $n=8$. Using an algebraic geometry method together with Burnside's Lemma, we enumerate isomorphism, isotopism, and main classes when $r \leq s \leq n \leq 6$. Numerical results have been cross-checked where possible.
In this paper, we consider the eigenproblems for Latin squares in a bipartite min-max-plus system. The focus is upon developing a new algorithm to compute the eigenvalue and eigenvectors (trivial and non-trivial) for Latin squares in a bipartite min-max-plus system. We illustrate the algorithm using some examples. Furthermore, we compare the results of our algorithm with some of the existing algorithms which shows that the propose method is more efficient.
We prove that a non-affine latin quandle (also known as left distributive quasigroup) of order $2^k$ exists if and only if $k = 6$ or $k \geq 8$. The construction is expressed in terms of central extensions of affine quandles.