Advancing Open Science

Straw return plays a pivotal role in sustaining soil fertility and crop production, but the interaction between straw return and consecutive fertilizer applications on yield sustainability and soil quality under climate change are unclear. Therefore, a long-term field experiment (2005–2022) was conducted to examine how straw return and fertilizer application improve soil properties, increase crop production, enhance the ability to resist climatic changes, and thus improve yield sustainability in a rice (Oryza sativa L.)–wheat (Triticum aestivum L.) cropping system. This study established five treatments, including the control, NPK treatment, S treatment, NPK + 1/2S treatment, and NPK + S treatment. Compared with the control, the treatments involving chemical fertilization combined with straw return increased on average rice and wheat yield by 52.9% and 95.4%, respectively, with higher values of the sustainable yield index (SYI) and lower values of the coefficient of variance (CV) for the two crops. Moreover, the treatments that combined chemical fertilization with straw return improved soil quality by increasing soil organic matter (SOM), total N, total P, and available K contents and presented a higher soil quality index (SQI) value compared to the other three treatments. The crop yield, SYI, and apparent nutrient balance increased with increasing SQI. The SOM and AP were identified as the most crucial soil fertility indices, exerting a significant impact on crop yields. Meanwhile, precipitation emerged as the key meteorological factor restricting the yield of winter wheat. The PLS-SEM suggested that fertilizer application, climatic conditions, and soil properties strongly influenced crop yield, and the magnitude of this influence varies between rice and wheat. In conclusion, the long-term fertilization combined with straw return represents an effective strategy to safeguard the sustainability of crop yields under climate change.

Cholera outbreaks are prevalent in coastal regions, where hydroclimatic factors play a critical role. However, evidence on their associations with different genotypes remains limited, and global projection remains lacking. We compiled cholera data from EnteroBase and WHO weekly reports covering 110 coastal countries from 1980 to 2022. A generalized additive model was used to examine the associations between hydroclimatic factors and different cholera serotypes and genotypes. We further projected future cholera occurrences for each coastal country under three climate change scenarios from 2025 to 2100. During the study period, Wave 3 of O1 replaced Wave 1 as the predominant genotype of cholera, while cholera O139 remained at low levels and only occurred in Asia. At the country–year level, each 1 °C increase in sea surface temperature (SST) was significantly associated with cholera occurrence (OR: 1.032, 95% CI: 1.023 to 1.040) and Wave 3 of O1 (OR: 1.149, 95% CI: 1.097 to 1.203). Drainage density (m/km²) and coastline ratio (%) were positively related to cholera, with ORs of 1.067 (95% CI: 1.046 to 1.087) and 1.022 (95% CI: 1.019 to 1.027). For future projections, five trend patterns were identified under different emission scenarios, with most countries showing increased cholera risk due to global hydroclimatic changes, peaking under the SSP585 scenario. Our findings reveal associations between hydroclimatic factors and different cholera genotypes and project future cholera risk across coastal countries, thereby providing evidence to inform genotype-specific surveillance and targeted prevention strategies at the global scale.

The business model canvas (BMC) is broadly used in entrepreneurship education as a trusted, practical tool for mapping out a company’s business model. Although the BMC helps students to obtain a quick overview of business operations, in practice, entrepreneurs need to adapt and change their business operations constantly in order to grow and remain viable. These changes in a business model are represented by business model innovation (BMI), but frameworks that capture changes in operations are not well developed. Hence, there is a need to present the dynamics of business model innovation through a dynamic business model framework. In this paper, we followed the experiential learning approach and focused on teaching BMI through applying and analyzing BMI in real start-up cases. We applied a two-phase research design by first asking students to apply and analyze the BMI of real start-ups using both the current business model canvas and the proposed dynamic business model framework. Following their analyses, master’s students were administered a survey to assess the benefits of the proposed dynamic business model framework. The results show that the current business model canvas has limitations in capturing the dynamics of BMI, which can be addressed by our proposed dynamic business model framework. The proposed framework can improve students’ level of understanding of BMI and, in particular, its dynamic nature.

Pain associated with routine husbandry procedures in sheep can persist for several days or even weeks, yet current analgesic options, such as the non-steroidal anti-inflammatory drug (NSAID) meloxicam, typically provide only 24–36 h of analgesia. This mismatch between pain duration and analgesic coverage represents a fundamental limitation of current pain-management strategies in sheep. Sustained-release (SR) formulations are emerging as a promising approach to deliver longer-lasting pain relief from a single dose, reducing the need for repeated handling, and improving both animal welfare and farm efficiency. Emerging evidence highlights both the promise and limitations of different strategies to extend therapeutic coverage beyond 72 h. While preliminary results are encouraging, challenges remain in achieving consistent pharmacokinetic profiles and optimal peak concentrations. Advancing SR meloxicam formulations could support widespread uptake of welfare-focused innovations in the sheep industry. Although not yet widely available, sustained-release meloxicam represent a promising step towards making routine husbandry procedures more humane and efficient.

Background: Breast cancer remains a leading cause of morbidity and mortality among women in Latin America. Mammography is the most effective population-based tool for early detection; however, its impact is limited by persistent social, geographic, and structural inequities. Evidence from the region indicates that ethnicity, rural residence, and health system organization play a central role in shaping unequal access to screening services. Methods: We conducted a narrative review informed by a systematic search strategy, following PRISMA 2020 recommendations. Searches were performed in 17 international and regional databases in English and Spanish, covering publications from 2015 to 2025. Eligible studies included non-interventional quantitative designs reporting mammography access, utilization, or coverage among women residing in Latin American countries. Three reviewers independently screened records, extracted data, and classified determinants of inequality into sociodemographic, geographic, and health-system domains. Results: Of 532 records identified, 12 studies met the inclusion criteria, primarily from Mexico, Brazil, Peru, and Chile. Most analyses were based on nationally representative surveys. Mammography coverage ranged from approximately 20% to 60%, with consistently lower uptake among Indigenous women, rural populations, and women without health insurance. Reduced screening was associated with low educational attainment, socioeconomic disadvantages, rural residence, ethnic self-identification, and fragmented health system affiliation. Structural barriers, including concentration of diagnostic infrastructure in urban areas, reliance on opportunistic screening models, and limited capacity for systematic follow-up, were recurrent across countries. Conclusions: Inequities in mammography access and utilization in Latin America reflect deeply rooted social and structural determinants rather than a lack of screening technology alone. Reducing preventable breast cancer mortality requires strengthening organized, population-based screening programs, decentralizing diagnostic services, improving continuity of care, and implementing culturally appropriate strategies tailored to Indigenous, rural, and uninsured populations.

This article provides a comprehensive analysis of long-term changes in the minimum river flow of the southern rivers of Western Kazakhstan (Temir, Oiyil, Zhem) for the period 1940–2022, with an emphasis on summer minimum and winter low flow as key indicators of water and environmental sustainability in conditions of increasing climate variability. The study combines a typology of the climate control mechanisms of minimum flow, analysis of structural homogeneity, and assessment of the internal organization of time series based on ITA and the integral IPTA method, which allow us to reveal the hidden fluctuations and stable phase states of the hydrological regime. The calculation of the climate sensitivity index (CSI_min) showed pronounced seasonal asymmetry: summer runoff is largely controlled by atmospheric precipitation, while winter minimum runoff is determined by temperature regime and soil freezing depth. Parametric and nonparametric tests (Pettitt, ADF, SNHT) revealed significant structural shifts in the 1960s–1990s period, corresponding to large-scale climatic anomalies in the region. Summer series are characterized by phases of prolonged low water levels and negative trends in the mid-20th century, while for the winter period, a steady increase in minimum flow has been established, due to regional warming and an increase in the share of underground recharge. IPTA confirmed the presence of long-term phases with high internal heterogeneity in the summer season and a more stable winter runoff structure. The results demonstrate the high climatic sensitivity of minimum runoff and confirm the need to move from static standards to dynamically adaptable methods of water resource assessment. The proposed approach can serve as a tool for developing adaptation strategies, assessing the risk profile of basins, and improving the sustainability of water management planning in arid regions.

This study investigates how Vision Language Models (VLMs) can be used and methodically configured to extract Environmental, Social, and Governance (ESG) metrics from corporate sustainability reports, addressing the limitations of existing text-only and manual ESG data-extraction approaches. Using the Design Science Research Methodology, we developed an extraction artifact comprising a curated page-level dataset containing greenhouse gas (GHG) emission-reduction targets, an automated evaluation pipeline, model and text-preprocessing comparisons, and iterative prompt and few-shot refinement. Pages from oil and gas sustainability reports were processed directly by VLMs to preserve visual–textual structure, enabling a controlled comparison of text, image, and combined input modalities, with extraction quality assessed at page and attribute level using F1-scores. Among tested models, Mistral Small 3.2 demonstrated the most stable performance and was used to evaluate image, text, and combined modalities. Combined text + image modality performed best (F1 = 0.82), particularly on complex page layouts. The findings demonstrate how to effectively integrate visual and textual cues for ESG metric extraction with VLMs, though challenges remain for visually dense layouts and avoiding inference-based hallucinations.

Food policies that respond to shocks and support nutritious diets for vulnerable populations can enhance resilience, support social equity, and reduce environmental damage. Using a simulation model, we evaluated the effectiveness of two food redistribution policies—Nourish New York, a program providing funds to food rescue organizations to purchase food directly from farmers, and the Food Donation and Food Scraps Recycling Law (an organics “waste ban”)—in response to a shock such as the COVID-19 pandemic. We assessed policy based on recovered food and life cycle carbon and water footprints over 10 years. Both policies improved produce donations during post-shock. The waste ban increased waste at feeding organizations; diverting unavoidable food waste to composting and anaerobic digestion mitigated its carbon footprint. Enhanced coordination and partnerships within the food redistribution network were crucial for ensuring that produce reached those in need, ultimately reducing long-term environmental impacts. Implementing multiple strategies that enhance recovery from farms and retail, while strengthening the organizational capacity of the food redistribution network, can simultaneously advance food security and environmental goals.