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The FSLN and the Politics of Legitimation in the Cold War: Sandinista Revolutionaries and Transnational Activism
No full textIn 1979, Nicaraguan revolutionaries of the Sandinista National Liberation Front (FSLN), obtained the international legitimacy needed to defeat the Somoza dictatorship. This chapter examines the FSLN’s campaign for legitimacy in the late 1970s. It argues that activists in the Americas and Europe were at the heart of the Sandinistas’ international strategy. They influenced public opinion, introduced revolutionaries to journalists and civil society groups, and lobbied governments to recognize the FSLN as the legitimate representative of the Nicaraguan people. In doing so, these solidarity activists paved the road towards the Sandinistas’ transformation into a legitimate political actor on the global stage
Spatially compounding effects of cumulation and thresholds amplify urban inequality in megacities
Get PDFUrbanization often results in unequal outcomes in social well-being, particularly in rapidly growing megacities within developing countries. This study investigates spatial inequalities in urban public service accessibility across communities in Beijing, with a focus on migrant populations who often face systemic disadvantages. Using fine-scale spatial and census data, we identify a significant negative correlation between facility accessibility and the proportion of migrants. Among the lowest-income communities, those with higher migrant shares experienced accessibility distances 2.09 times greater than others. In high-migrant areas, inequality levels surpassed the city average by 14.57%, reflecting entrenched spatial disparities. Interpretable machine learning models reveal key threshold effects: when housing prices fall below 80,590 yuan/m² and migrant ratios exceed 32%, inequalities rise sharply. Furthermore, more than 18.98% of communities with high migrant population proportions exhibited cumulative inequality, where multiple disadvantage factors overlap and reinforce each other. These findings highlight how spatial, economic, and demographic vulnerabilities intersect, underscoring the urgent need for data-informed, equity-oriented urban planning to foster more inclusive, resilient, and sustainable cities
Going beyond compliance to build on the Researcher Development Concordat
Get PDFAn agreement between universities, research institutes and funders to support the career development of researchers in the UK has led to improvements in research culture since 2019, but there is still more to do
Developing an AI-assisted tool that identifies patients with multimorbidity and complex polypharmacy to improve the process of medication reviews: qualitative interview and focus group study
Get PDFBackground: Structured medication reviews (SMRs) are an essential component of medication optimization, especially for patients with multimorbidity and polypharmacy. However, the process remains challenging due to the complexities of patient data, time constraints, and the need for coordination among health care professionals (HCPs). This study explores HCPs’ perspectives on the integration of artificial intelligence (AI)–assisted tools to enhance the SMR process, with a focus on the potential benefits of and barriers to adoption. Objective: This study aims to identify the key user requirements for AI-assisted tools to improve the efficiency and effectiveness of SMRs, specifically for patients with multimorbidity, complex polypharmacy, and frailty.
Methods: A qualitative study was conducted involving focus groups and semistructured interviews with HCPs and patients in the United Kingdom. Participants included physicians, pharmacists, clinical pharmacologists, psychiatrists from primary and secondary care, a policy maker, and patients with multimorbidity. Data were analyzed using a hybrid inductive and deductive thematic analysis approach to identify themes related to AI-assisted tool functionality, workflow integration, user-interface visualization, and usability in the SMR process.
Results: Four major themes emerged from the analysis: innovative AI potential, optimizing electronic patient record visualization, functionality of the AI tool for SMRs, and facilitators of and barriers to AI tool implementation. HCPs identified the potential of AI to support patient identification and prioritizing those at risk of medication-related harm. AI-assisted tools were viewed as essential in detecting prescribing gaps, drug interactions, and patient risk trajectories over time. Participants emphasized the importance of presenting patient data in an intuitive format, with a patient interface for shared decision-making. Suggestions included color-coding blood results, highlighting critical medication reviews, and providing timelines of patient medical histories. HCPs stressed the need for AI tools to integrate seamlessly with existing electronic patient record systems and provide actionable insights without overwhelming users with excessive notifications or “pop-up” alerts. Factors influencing the uptake of AI-assisted tools included the need for user-friendly design, evidence of tool effectiveness (though some were skeptical about the predictive accuracy of AI models), and addressing concerns around digital exclusion.
Conclusions: The findings highlight the potential for AI-assisted tools to streamline and optimize the SMR process, particularly for patients with multimorbidity and complex polypharmacy. However, successful implementation depends on addressing concerns related to workflow integration, user acceptance, and evidence of effectiveness. User-centered design is crucial to ensure that AI-assisted tools support HCPs in delivering high-quality, patient-centered care while minimizing cognitive overload and alert fatigue
Perspectives from the 2025 ISCBI/ISCI joint workshop on genetic stability, clonal monitoring, ethical data governance, and global inclusion in stem cell banking
Get PDFTwo international stem cell consortia, the International Stem Cell Initiative (ISCI) and the International Stem Cell Biobanking Initiative (ISCBI, www.iscbi.org) held a workshop on June 15th 2025 in Hong Kong on genetic variants in human pluripotent stem cell (hPSC) lines and accurate and standardized documentation of donor/hPSC genetic information including ethnicity. The occurrence and detection of genetic variants is a key issue for assuring reproducible stem cell research data and the safety of stem cell derived medicinal products. Presentations by leading experts addressed the nature of hPSC genetic variants, their detection and accurate recording of genetic data and ethnicity. The audience of stem cell researchers, cell banking directors and experts in ethic, policy and stem cell databases, from 13 countries across the globe, discussed progression of the ISCI consortium’s efforts in providing further data and thought leadership on the management of genetic variants, and the challenges for standardizing biobanking approaches for hPSC genetic data including ethnicity. This paper records the key elements of this discussion and the conclusions and consensus reached and ongoing work to provide guidance for hPSC biobanks
Multi‐crystal x‐ray diffraction (MCXRD) bridges the crystallographic characterisation gap in chemistry and materials science: application to MOFs
Get PDFStructure determination by X-ray diffraction is limited by crystal size and can be compromised by radiation damage when using very intense X-ray radiation. X-ray structure determination from partial diffraction data sets combined from multiple crystals is a potential solution, but its exploitation in chemistry and materials science is largely unrealized. Here we report the use of synchrotron radiation for multi-crystal X-ray diffraction (MCXRD) adapted for structure determination of metal-organic framework (MOF) materials with crystal dimensions too small for conventional single-crystal diffraction studies. We further show that radiation-induced chemical changes and degradation of diffraction quality can be alleviated. Our approach encompasses both rotation- and stationary-MCXRD measurements for 10 to 1000s of crystals with software-optimized combination of the multiple data sets. We report the crystal structures of six MOFs: MOF-919(Sc/Cu), MET-2, MIL-88B(Cr)-1,4-NDC, PCN-260(Sc), UiO-66, and UiO-66-MoO4 with unit cell dimensions ranging from 18−114 Å and crystal sizes from 0.5−480 µm 3 . This approach can address the challenges of structure determination in a regime of particle size and sample radiation sensitivity that lies between existing single-crystal X-ray diffraction and the emerging field of electron diffraction. MCXRD can provide accurate atomic-resolution structure determination for some of the most challenging cases in chemistry and materials scienc
Decay of f(R) quintessence into dark matter: mitigating the Hubble tension?
Get PDFWe propose a revised cosmological scenario that extends the Λ cold dark matter (ΛCDM) framework by incorporating metric f(R) gravity in the Jordan frame. In this model, the dark energy component arises from a nonminimally coupled scalar field, decomposed into a smooth background [set to unity to recover general relativity (GR)] and a rapidly varying, massive fluctuation that decays into the dark matter sector. In the near-GR limit, this setup provides a phenomenological extension of ΛCDM characterized by two additional parameters: the present-day value of the scalar fluctuation and a normalized decay rate. Using a Markov chain Monte Carlo analysis of low-redshift cosmological data, comprising Type Ia supernovae, baryon acoustic oscillation (BAO), and cosmic chronometer measurements, we find that the proposed model achieves a better overall fit than ΛCDM, while the Bayesian evidence remains statistically inconclusive given the inclusion of two extra parameters. The model predicts a moderate increase in the inferred value of H0 and an improved consistency with Dark Energy Spectroscopic Instrument BAO data when adopting the SH0ES prior. Furthermore, describing dark matter particle creation as a transition phase in the late Universe offers an intriguing physical interpretation, potentially capturing features already present in current data and providing a promising avenue to explore extensions of the standard cosmological model within modified gravity frameworks
Solar-driven direct air capture to produce sustainable aviation fuel
Get PDFRenewable energy-powered direct air capture with subsequent utilisation offers a sustainable decarbonisation strategy for a circular economy. Whereas current liquid-based capture technology relies on natural gas combustion for high-temperature calcination, restricting the transition to fully renewable operation. In this study, we show a 1MtCO2/year solar-driven process that adopts a hydrogen fluidised solar calciner with onsite catalytic conversion of CO2 into sustainable aviation fuel. We find that replacing fossil-fuel heating with solar thermal energy lowers electricity consumption by 63% and reduces onsite CO2 emissions by 59%. The analysis shows that the production cost of sustainable aviation fuel is cost-effective (US$4.62/kg) compared to the conventional process. Geographical sensitivity analysis indicates favourable deployment locations are low-risk countries with high solar irradiance and low hydrogen cost. The predicted results also outline potential economic viability for policymakers and industry investors
High-spin state dynamics and quintet-mediated emission in intramolecular singlet fission
Get PDFHigh-spin states in molecular systems hold significant interest for applications ranging from optoelectronics to quantum technologies. Spin states generated in intramolecular singlet fission are of particular relevance, yet the mechanisms controlling triplet-pair formation are not fully understood – especially the involvement of quintet states in luminescence at room temperature remains experimentally elusive. Here, we investigate high-spin state formation and emission in dimers and trimers comprising multiple diphenylhexatriene units. We demonstrate the formation of pure quintet states in all these oligomers, with quintet-mediated emission dominating delayed fluorescence up to room temperature. By distinguishing between the formation of weakly exchange-coupled triplet pairs and triplet excitons generated by intersystem crossing, we identify the methylated trimer as the only oligomer exhibiting exclusively the desired singlet fission route. These findings establish quintet-mediated delayed emission as a distinct spin-selective pathway and show how molecular structure directs high-spin formation, opening opportunities for room-temperature molecular quantum technologies
A deep learning approach for automated total sunspot number estimation
Get PDFAccurate sunspot number estimation is essential for understanding the long-term evolution of solar activity and its impact on space weather. Sunspot numbers have been manually determined, leading to inconsistencies and observer-dependent biases. To address this, the World Data Center Sunspot Index and Long-term Solar Observations (WDC-SILSO) aggregates data from a global network of observatories to estimate the daily total sunspot number, enabling cross-validation and calibration across simultaneous observations. This study proposes a novel deep learning framework for automated total sunspot number calculation using solar full-disk continuum images from the Solar Dynamics Observatory. The method integrates U-Net for sunspot segmentation, K-means clustering for distinguishing umbrae from penumbrae, and You Only Look Once model for sunspot group detection. The selection of image-processing thresholds and neural network hyperparameters is optimized with respect to WDC-SILSO reference values during training. The results demonstrate a high correlation of 0.97 between the estimated and the WDC-SILSO daily total sunspot numbers. Furthermore, the framework offers a scalable approach suitable for future high-resolution solar observations
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