Latitude Pharmaceuticals (United States)

With the ever-increasing realisation that measures against climate change have to be local, many cities opted to become NetZero (i.e., CO2-Neutral, emissions compensated) in the near future. Especially within the EU, a large-scale project takes place driven in close collaboration between the EU and cities. The “EU Cities Mission” facilitates urban transition via supporting actions and strategies towards neutrality by offering official labelling to cities that create successful climate city contracts and commit to achieve CO2-Neutrality by 2030. The Horizon project CLMS-Cities targets to support cities with quantifying and trenching their CO2 emissions based on existing and freely available Copernicus Services, in particular within CLMS (Copernicus Land Monitoring Service Cities) and in-situ data such as GNSS based mobility data. Within CLMS-Cities a CO2 exchange model for local-scale scope 1 CO2 emissions is developed at 10m resolution at hourly scale for the five sectors: mobility, buildings, industrial sources, AFOLU (Agriculture, Forestry and other land uses), and human respiration following closely typical city inventories. We here present first results and the background of the model for the case study city Vitoria-Gasteiz, Spain (Tier 1 city). The model is mainly based on the Urban Atlas and produces estimates of CO2 exchange by integrating relevant Copernicus services, satellite products and third-party mobility data. To ensure robustness, the model is paired with local-scale eddy covariance observations in the city centre of Vitoria-Gasteiz. Following this validation process, the model will be extended and rolled out to ten additional EU Mission cities to ensure that it accommodates a wide range of spatial, urban and environmental contexts, that is seen across the real cities in the EU. A co-design approach underpins this work, with continuous engagement with cities to ensure that their requirements are fully integrated in the design, development and operationalisation of the model.

The rapid proliferation of Large Language Models (LLMs) has revolutionized automated code auditing, yet frontier models like GPT-5.2 and Claude Opus 4.5 continue to struggle with niche, high-performance languages such as Sui Move. These generalist models frequently exhibit "Solidity Bias," hallucinating Ethereum-specific vulnerabilities (e.g., reentrancy) in Sui's objectcentric architecture. Furthermore, their reliance on cloud-based inference compromises developer privacy and intellectual property. To address these limitations, we introduce SuiAudit Pure1, a specialized 7B-parameter model explicitly engineered for two primary objectives: (1) enabling secure, real-time offline inference suitable for local development environments (e.g., VS Code plugins) to protect intellectual property, and (2) eliminating the "Solidity Bias" by mastering Sui Move's specific safety guarantees (e.g., absence of reentrancy or overflow issues). Our distinct contribution lies in our dataset design, which balances positive vulnerability instances (Classes A-F) against adversarial "Hard Negative" samples (Class NEG)-safe code patterns designed to trap generalist LLMs. By employing a progressive training pipeline, we first establish a robust baseline via Supervised Fine-Tuning (SuiAudit SFT) to master domain syntax, followed by Direct Preference Optimization (DPO) with Chain-of-Thought to refine reasoning. This yields our final SuiAudit Pure1 model, which achieves an accuracy of 31.4% on our rigorous benchmark, significantly surpassing Claude Opus 4.5 (26.6%) and GPT-5.2 (17.2%). To facilitate reproducibility while protecting intellectual property, we released our introductory SuiAudit Raw1 infrastructure on GitHub. We provide open access to the model weights for both stages of our pipeline: the intermediate SuiAudit SFT baseline and the fully aligned SuiAudit Pure1. The proprietary dataset used for training remains a closed asset.

Abstract Plant-based cheese alternatives (PBCAs) are considered sustainable substitutes for dairy-based cheese (DB); however, their consumer acceptance remains limited, particularly in dairy-dominant cultural contexts such as Uruguay, where specific consumer insights are scarce. This study investigated the influence of sensory experience, product information, and conceptual expectations on consumer perceptions of commercially available mozzarella-style PBCAs in Uruguay. Three sessions were conducted: blind and informed tastings (n = 110) and an expectation survey with a separate participant group (n = 236). Liking, purchase intention, and conceptual associations were evaluated using hedonic scales, CATA questions, and cluster analyses. Dairy-based cheese consistently achieved the highest liking and purchase intention scores. Positive sensory drivers for acceptance included a smooth mouthfeel, creaminess, and shiny appearance, whereas artificial flavors and strong aftertastes reduced acceptance. One PBCA showed an acceptable texture but lacked flavor. Crucially, providing product information did not enhance PBCA acceptance, underscoring the importance of sensory experiences. Cluster analysis revealed two consumer segments: "adopters" (n = 176), who are younger, have higher purchase intentions, and associate PBCAs with sustainability; and "non-adopters" (n = 60), who were older and perceived PBCAs as artificial and unappealing. PBCAs hold potential among sustainability-oriented consumers, but improving flavor authenticity and sensory quality is crucial. Addressing these sensory barriers and strategically positioning products around health and environmental benefits are crucial for broadening overall acceptance and facilitating sustainable dietary shifts in the population.

ABSTRACT By using hourly rain gauge records from 1961 to 2020, we find that the annual precipitation differences between highland stations and lowland stations in eastern China are reducing. Specifically, precipitation frequency has decreased significantly in the highlands while precipitation intensity has increased considerably in the lowlands, both contributing to a reduced elevation–dependency of precipitation. The decreasing precipitation frequency correlates with reduced convective available potential energy (CAPE), whereas the increasing precipitation intensity is linked to enhanced low‐level convergence.

<p>The work is devoted to the empirical analysis of age shifts within the framework of the factor model of autism for preschool children. In the 2020–2022 studies, we obtained a factor model of autism and identified 4 vectors of autism — typical subtypes of ASD in 3–4 years old children. Among them are: 1) difficulties in establishing emotional contact, expressing one's emotions and decoding other people's emotions in the context of social interaction; 2) sensory disintegration; 3) impairments in verbal and nonverbal communication and social skills; 4) hyperactivity, including excessive movements, motor disinhibition and restless behavior. It should be emphasized that the first three vectors correspond to the core symptoms of ASD in accordance with the DSM-5. While the hyperactivity factor goes beyond the main symptoms of ASD. In this paper, a comparative analysis of the severity and stability of symptoms was carried out within the framework of a 4-factor model of autism for 3–4 and 5–6-year-old children with autism. Sensory and communication impairments have been found to decrease with age, however, emotional impairments and hyperactivity remain at a high level. The theoretical foundations of emotional disorders and hyperactivity in children with ASD are analyzed in detail. Brief practical recommendations are presented for effective early intervention in order to improve the potential trajectory of development of preschool children with ASD.</p>

El objetivo de este estudio es el análisis estructural, a todas las escalas, de la terminación occidental de la rama Norte de la Falla de Merens. En esta zona, afloran cuarcitas y pizarras pre-caradocienses intruidas por el granito de Soulcem. En su parte septentrional, dominan los pliegues tumbados, vergentes al Norte y con la foliación varisca S1 asociada, desarrollada con metamorfismo de grado medio, Mientras que al sur abundan pliegues variscos E-O, derechos y desarrollados en condiciones metamórficas de grado bajo. Ambos dominios están separados por la Falla de Merens, interpretada como una estructura Varisca con escaso juego alpino.

Le présent rapport résume la méthode adoptée par le groupe de l’étude FCC pour élaborer un scénario d’emplacement équilibré selon les trois piliers du projet 1) l’excellence scientifique, 2) la compatibilité territoriale et 3) les risques liés à la mise en œuvre du projet. Il décrit les exigences et les contraintes du processus d’élaboration d’un scénario et illustre par des exemples concrets la manière dont elles sont prises en compte lors de la détermination de la configuration et de l’emplacement. Le présent rapport montre également l’évolution du scénario étudié, entre le début de l’étude exploratoire en 2014 et la proposition d’un scénario de base pour l’emplacement en 2021. Ce scénario optimisé servira de référence pour approfondir les diverses composantes de l’étude de faisabilité (par exemple, études de la stabilité souterraine, propositions d’accès au site pendant les phases de construction et d’exploitation, scénarios pour la fourniture d’électricité et d’eau, approches pour la gestion des matériaux excavés, développement de potentiels de synergie locale, questions d’intégration paysagère, propositions de mesures d’accompagnement et de compensation). Après huit années de travaux d’étude par une équipe multidisciplinaire d'environ 100 membres, il apparaît que le scénario le plus équilibré est celui d’un collisionneur circulaire d’une circonférence de l’ordre de 91 km, comprenant huit sites de surface. Le processus d’élaboration itératif des scénarios est documenté dans le présent document. L’existence d’une communauté d’utilisateurs suffisamment importante s’engageant à exploiter l’infrastructure pendant plusieurs décennies est une condition préalable pour justifier une telle infrastructure de recherche. Les scénarios prévoyant un collisionneur nettement plus petit, c’est-à-dire d’une circonférence inférieure à 90 km, ne répondent pas aux exigences de performance d’un tel programme de recherche devant attirer une masse critique de scientifiques. Les propositions d’emplacement territorial adapté à des scénarios prévoyant un collisionneur d’une circonférence nettement supérieure à 91 km et comprenant plus de huit sites de surface se heurtent à des impossibilités de compatibilité territoriale et risques de réalisiation. Enfin, seules deux classes de configuration et d’emplacement avec un ensemble très limité de scénarios entrent dans le périmètre des limites de faisabilité géologique : entre 89 à 91 km avec huit sites de surface et entre 97 et 98 km avec douze sites de surface. À ce jour, seuls des scénarios à 91 km et huit sites de surface semblent pouvoir satisfaire aux trois exigences suivantes: performances scientifiques acceptables, compatibilité avec les contraintes territoriales et compatibilité avec les contraintes géologiques et techniques. On verra ici que l’un des scénarios (PA31), se détache, sur la base d’une analyse multicritères. Il est retenu pour des études approfondies qui nécessitent des activités sur place, des échanges étroites avec des services compétents dans les deux États Hôtes et avec les parties prenantes dans le périmètre de l'implantation.

This article presents a study of an automatic speech recognition system in Portuguese applied to videos by the General Attorney of the Union of Brazil. As they are confidential videos, using proprietary software from large companies is not allowed for security reasons. Thus, constructing an artificial intelligence model capable of performing automatic speech recognition in Portuguese in the judicial context and making this model available for large-scale inference is critical to maintaining data security. For this purpose, a dataset in Brazilian Portuguese was used by a combination of 3 datasets already built. The system used TDNN Jasper and QuartzNet architectures for network training, obtaining promising preliminary results, having a word error rate (WER) of 56% without using a linguistic model.

Abstract In Malaysia, numerous offshore oil and gas platforms are approaching the end of their operational lifespans and will soon be scheduled for decommissioning. Traditional decommissioning typically involves the complete removal of the platform from the seabed, consequently resulting in the destruction of the established marine life communities present on the structure. A Rigs-to-Reefs strategy provides an alternative to the complete removal of obsolete, non-productive offshore oil and gas platforms, by converting the platform into a permanent artificial reef by utilizing one of the following three methods: partial removal or topple-in-place (in-situ), or tow and place (ex-situ). In-situ reefing provides a means of conserving the marine communities found on the platform by decommissioning the platform jacket in place as an artificial reef. However, not all platforms are good candidates for a Rigs-to-Reef conversion. Thus, pre-decommissioning biological assessments should be undertaken to determine the most appropriate decommissioning strategy on a case-by-case basis. In this study, a biological assessment was developed to catalog the marine life assemblages present on two offshore oil and gas platforms in Malaysia using remotely operated vehicles. Given the limited amount of biological data available on the marine ecosystems found on Malaysia’s platforms, this data may be useful for minimizing adverse impacts of platform removal, while enhancing benefits to the marine environment.