Development Fund

Abstract. Climate change significantly threatens crop yields levels and stability. The complex interplay of factors at the local scale makes assessing these impacts difficult, requiring coupled climate-phenology models, which integrate climate data and crop information. Identifying suitable local management practices and crop varieties under future conditions becomes essential for developing effective adaptation strategies. This study presents the implementation and application of an integrated climate-phenology adaptation support modelling system. This is based on regional CORDEX climate models and the CERES Maize model from the DSSAT platform. Novel modules for optimal management and genotype identification under climate change have been developed in the system, employing a hybrid approach that combines deterministic modelling with machine learning (ML) techniques and genetic algorithms. This system was run as a regional pilot over Southern Romania, operating in real-time in interaction with users, performing agro-climate projections (combination of fertilization, sowing date, genotype) and providing best crop management simulated under climate change projections. Multi-model ensemble simulations were conducted for two radiative forcing scenarios RCP4.5 and RCP8.5 and twelve management scenarios, yielding novel results for the region. Results indicate a projected decrease in maize yields for the current genotype across all tested scenarios, primarily attributed to a shortened grain-filling period and reduced fertilization efficiency under warmer conditions. The analysis warns about a projected narrowing of the agro-management options for maintaining a high yield level. However, we find an added value from the impact of genotype selection in mitigating climate change impacts, even in extreme years. Genotype optimisation across six crossed cultivar dependent parameters revealed that while maximum yields decline, specific genotype windows exhibit increased intermediate yields under future climates compared to current conditions. Sensitivity analysis identified the thermal time requirements during juvenile and maturity stages as the most critical factors influencing genotype performance under warmer climates. This research demonstrates the added value of combining deterministic and data-driven modelling approaches within a coupled climate-crop system for developing effective adaptation strategies, including optimised fertilization pathways that contribute to climate change mitigation.

Clinicians have prescribed benzodiazepines for a range of symptoms and conditions since the Food and Drug Administration approved chlordiazepoxide in 1960. Between 1969 and 1982, the benzodiazepine diazepam was the most prescribed medication in the United States. Since then, recognition of benzodiazepine's risks-such as falls, psychomotor and cognitive impairment, withdrawal, benzodiazepine use disorder (BzUD), and suicidality-and limited data on long-term safety and efficacy have created challenges for clinicians and patients, including when and how to safely taper these medications. In 2025, 10 professional societies, including the American Society of Addiction Medicine (ASAM), released the Joint Clinical Practice Guideline on Benzodiazepine Tapering. This commentary explores implications for addiction treatment.

Financial due diligence requires intensive analysis of vast unstructured documents (e.g., contracts, statements, invoices). However, traditional manual processing is inefficient, costly, and prone to subjectivity, and the existing automation solutions primarily focus on single-modal text recognition, lacking the capacity for joint understanding of multimodal features (e.g., layout, seals, table structures) and deep risk reasoning. This study proposes an end-to-end framework based on a Multimodal Large Language Model (MLLM) to bridge this gap. The framework not only performs accurate multimodal information extraction but also, integrates domain-specific knowledge (e.g regulatory clauses) to emulate expert-like reasoning. By constructing a dynamic risk knowledge graph that captures entities and relations across documents, it enables cross-document correlation analysis and anomaly detection. We will validate the framework on curated financial datasets, assessing both its information processing accuracy and risk diagnosis capability. Our contributions are threefold: 1) providing a novel computational linguistics solution that addresses the semantic and pragmatic challenges in financial document understanding; 2) advancing financial AI from perceptual to cognitive intelligence through explainable, knowledge-integrated reasoning; 3) offering a transparent, automated decision-support tool for high-stakes due diligence.

Sunflower (Helianthus annuus L.) is generally considered moderately resistant to drought conditions. However, in years characterized by low rainfall and high air temperatures, significant reductions in seed yield can occur. At the Fundulea location in south eastern Romania, the year 2024 was marked by drought and extreme heat, resulting in low seed yields among the 15 tested sunflower hybrids. Yields ranged from 611 kg/ha for hybrid H5E in the ExpressSun system to 1,299 kg/ha for hybrid H10CLP in the Clearfield Plus system. In contrast, more favourable climatic conditions in 2025 led to substantially higher yields, ranging from 1,579 kg/ha for hybrid H2E (ExpressSun) to 3,046 kg/ha for hybrid H11CLP (Clearfield Plus). These results demonstrate the pronounced impact of extreme heat and drought, particularly during the flowering and seed-filling phenophases, which are the most sensitive stages of sunflower development. Stress occurring in these phases limits pollination efficiency, seed set, and oil accumulation, ultimately leading to significant yield reductions.

Cu-zinc oxide/PET nanofibers were synthesized using blended electrospinning of PET/Cu-ZnO/carrene. Polyester was employed as the substrate, and copper element was embedded into ZnO. Characterization of 337 nm as-spun fibers was conducted through SEM and EDX, and cleaning efficiency of BTEX (<i>E</i>_b) was evaluated using fluorescent lamp with 440 nm excitation. We attained the photochemical activity of Cu-ZnO/PET, and <i>E</i>_b revealed expectant effect within 1.5 h in the presence of plastic, paint and coking effluents. A simple and environmental means was recommend for removal of BTEX from industrial sewage under visible irradiation.

High levels of somatic symptom distress and health anxiety have been linked to difficulties in emotion generation, identification, and regulation. However, these findings stem largely from correlational studies using questionnaires. Mechanistic experimental evidence is scarce and inconclusive. The present study investigated associations between somatic symptom distress (SSS-8), health anxiety (MK-HAI), alexithymia (TAS-20), and experimental indicators of emotion generation in N=78 participants (Age: M=23.12, SD=3.50; Gender: 80.8% female, 19.2% male). An innovative experimental paradigm of emotion generation by Givon et al (2023) was used, which assesses emotional responses to normed negative or positive pictures. It allows the calculation of evidence accumulation parameters, that reflect emotion processing efficiency (drift-rate) and response bias in emotion reporting (threshold), based on a linear ballistic accumulator model. Somatic symptom distress was not associated with emotion processing efficiency (drift-rate) for negative emotions (BFinclusion=0.49). There was anecdotal evidence for an effect of health anxiety (BFinclusion=2.53), but the effect was small and inconclusive (b=-0.01, SD=0.004, 95% CI [-0.01, <0.001]), thus failing to support a strong association. Experimental indicators of emotion generation were also unrelated to self-reported alexithymia (0.14 <BF10 <0.18). The study did not provide evidence that somatic symptom distress or health anxiety are linked to a markedly reduced efficiency in processing of negative emotions. As this was a convenience sample with predominantly non-clinical symptom levels, future studies should test the generalizability of these findings to clinical samples.

To address the challenge of decision making in close-range air combat for fixed-wing unmanned air vehicle (UAV) swarms, this paper proposes a distributed Hierarchical Cooperative Soft Actor-Critic with maximum entropy (HC-SAC) framework. A top-level target decision-making and bottom-level maneuvering framework is designed to resolve convergence issues in traditional multi-agent reinforcement learning, typically for long mission durations and complex state spaces. Friendly tactics are incorporated into top-level decisions to enhance coordination, with both offensive and defensive sub-policies balanced for swarm confrontations. These policies are trained using the Soft Actor-Critic (SAC) deep reinforcement learning algorithm with specific reward functions, and the effectiveness of this method is verified through 5v5 swarm game confrontation simulations.

Num tempo em que a pressão sobre o solo adquire contornos políticos, económicos e ecológicos, a escolha, entre urbanizar solo rústico ou renaturalizar o espaço urbano, não pode ser binária. Este artigo defende que a Unidade de Execução (UE), enquanto instrumento contratual e flexível, assume um papel central na resolução dessa tensão. Esta visão ganha particular relevância face às recentes alterações legislativas introduzidas no Regime Jurídico dos Instrumentos de Gestão Territorial (RJIGT) que, embora procurem responder a necessidades prementes, levantam preocupações quanto à fragmentação da política de solo e à fragilização do planeamento estratégico. Assim, mais do que escolher entre urbanizar ou renaturalizar, impõe-se perguntar: conseguimos planear em conjunto para fazer ambas as coisas com visão, equidade e eficácia? Propõe-se, por isso, uma atualização crítica da figura da UE, demonstrando como esta pode articular reabilitação e expansão, justiça territorial e execução célere. Partindo de uma aplicação prática num município da região centro, no interior do país – no contexto das funções exercidas por técnico superior da administração pública local, nas áreas do urbanismo, planeamento e ordenamento do território, com conhecimento consolidado das dinâmicas territoriais e dos riscos associados à expansão urbana em detrimento da regeneração do edificado existente — o artigo apresenta uma proposta integrada: reabilitar um bairro urbano vulnerável articulando-o com uma zona contígua de solo rústico (a urbanizar). Argumenta-se que apenas com mecanismos de justa repartição e visão de conjunto é possível evitar tanto a paralisia do solo urbano expectante como a ocupação dispersa do solo rústico. A UE surge, assim, como resposta original e estratégica às exigências ambientais, habitacionais e legislativas atuais.