Abstract Reliable streamflow projections are essential for effective water‐resource management and climate adaptation. However, streamflow projections are associated with large uncertainties due to divergent precipitation projections from climate models, which directly propagate into hydrological estimates. Observation‐constrained approaches that condition future projections on past observations have been shown to reduce such uncertainties; however, they have not been applied to streamflow projections across the Indian rivers. Using long‐term streamflow and global mean surface temperature observations, climate model projections, hydrological modeling, and a Bayesian detection–attribution framework, we developed observational constrained streamflow projections for nine major Indian rivers. The method reduces the 5–95% confidence interval of future streamflow projections by nearly one‐third compared to raw multimodel ensembles, with constraint strength controlled by internal streamflow variability and inter‐model spread in the unconstrained ensemble. Projection uncertainty is further reduced to ∼20% when considering projections based only on skillful climate models. Constrained projections indicate significant increases in streamflow in the near‐, mid‐, and far‐future periods, except for the Cauvery basin, which shows a near‐term decline. Applying the method to raw precipitation projections reveals comparable constraint strength and increases confidence in the results, given the strong dependence of Indian river flows on precipitation. Our findings underscore the importance of combining skillful climate models with post‐processing constraint methods to substantially reduce model‐based uncertainty. Overall, our results provide critical insights into future streamflow changes across Indian rivers, supporting long‐term water‐resource planning and climate‐resilient management.
This chapter examines the policy implications of behavioural sciences insights for the regulation of privacy on the Internet, by focusing in particular on behavioural targeting. This marketing technique involves tracking people's online behaviour to use the collected information to show people individually targeted advertisements. Enforcing data protection law may not be enough to protect privacy in this area. I argue that, if society is better off when certain behavioural targeting practices do not happen, policymakers should consider banning them.
Widiyanto Widiyanto, Lestari Eny, Rusdiyana Eksa
et al.
The Climate Village Program (ProKlim) aims to strengthen community participation in local climate mitigation and adaptation. Although several areas in Surakarta have reached the Main Class category, sustaining community motivation remains a challenge. This study analyzes the sustainability of ProKlim by examining social, economic, and environmental factors influencing long-term engagement. Using a qualitative case study approach, data were collected through in-depth interviews, FGDs, observations, and documentation. The findings show that strong social capital and local leadership support sustainability, while fluctuating participation, dependence on external incentives, and limited cadre regeneration hinder continuity. Economic activities exist but remain small-scale. The results imply that continuous mentoring, strengthened community-based economic initiatives, and structured monitoring are essential to ensure sustained ProKlim implementation beyond assessment cycle. The result imply that continuous mentoring, strengthened community-base economic initiatives, and structured monitoring to maintain consistent ProKlim implementation beyond competition cycles. Strengthening these aspects is essential for ensuring the ling-term sustainability of Main Class ProKlim as a community-driven climate resilience initiative.
Elvis Frimpong Manso, Alfred Arthur, Joseph Osafo Eduah
et al.
Despite the differences in soil and fertilizer properties affecting fertilizer effectiveness, farmers often use nationwide blanket formulations, which may not optimize cocoa yield. Previous trials have shown that fertilizer application outcomes vary by soil type, prompting recommendations for site-specific fertilizer formulations. Nonetheless, the complexity of creating these models leaves farmers relying on available blanket fertilizers instead. To enable farmers to select fertilizer types that will best suit their soils, the effects of soil properties and fertilizer types on the solubility, availability of macronutrients, and pH in two cocoa soils were investigated. Five kilograms of ferralsol and acrisol were prepared in nursery bags, with five different fertilizers (A, B, C, D, and E) applied at rates of 375, 500, and 625 kg·ha−1 were set in factorial experiment laid in completely randomized design with four replicates each. Following a 3-week incubation, nutrient analysis was conducted weekly. Water solubility was assessed by weighing 1, 2, and 3 g of each fertilizer in 200 mL of distilled water and shaken for 3 hours. Results indicate that lower solute-to-solvent ratios decreased NPK, Ca, and Mg solubility. Fertilizer A increased soil pH from 6.81 to 7.45 in ferralsol and from 5.78 to 7.50 in acrisol. The different soils showed different release trends though the same fertilizers were applied. Available phosphorus rose from 4.76 to 166.69 mg·kg−1 in ferralsol and from 4.32 to 170.00 mg·kg−1 in acrisol, while total nitrogen rose from 0.22% to 0.30% in ferralsol and from 0.16% to 0.20% in acrisol. The findings highlight that soil properties influence fertilizer solubility and nutrient availability in cocoa soils.
Abstract Background Grain number (GN) is one of the key yield contributing factors in modern wheat (Triticum aestivum) varieties. Fruiting efficiency (FE) is a key trait for increasing GN by making more spike assimilates available to reproductive structures. Thousand grain weight (TGW) is also an important component of grain yield. To understand the genetic architecture of FE and TGW, we performed a genome-wide association study (GWAS) in a panel of 236 US soft facultative wheats that were phenotyped in three experiments at two locations in Florida and genotyped with 20,706 single nucleotide polymorphisms (SNPs) generated from genotyping-by-sequencing (GBS). Results FE showed significant positive associations with GN, grain yield (GY), and harvest index (HI). Likewise, TGW mostly had a positive correlation with GY and HI, but a negative correlation with GN. Eighteen marker-trait associations (MTAs) for FE and TGW were identified on 11 chromosomes, with nine MTAs within genes. Several MTAs associated with other traits were found within genes with different biological and metabolic functions including nuclear pore complex protein, F-box protein, oligopeptide transporter, and glycoside vacuolar protein. Two KASP markers showed significant mean differences for FE and TGW traits in a validation population. Conclusions KASP marker development and validation demonstrated the utility of these markers for improving FE and TGW in breeding programs. The results suggest that optimizing intra-spike partitioning and utilizing marker-assisted selection (MAS) can enhance GY and HI.
The objective of this paper was to investigate the landuse and landcover (LULC) changes in Anyigba, Dekina Local Government Area of Kogi State, Nigeria to evaluate the annual rate of change, predicts future trends, and examines the implications of these changes using Landsat imagery from 1998, 2010, and 2022 obtained from the United States Geological Survey (USGS) and processed by ArcGIS. The findings reveal significant shifts in LULC patterns between 1998 and 2022. Urban areas expanded dramatically by 84.56 km² (1289.02%), with an annual growth rate of 3.52%, while agricultural land, once the dominant category, declined by 52.15 km² (34.58%). Similarly, bare surfaces shrank by 11.30 km² (57.95%). Projections for 2035 indicate continued urban expansion to 176.14 km² (79.50%), coupled with significant reductions in forest/vegetation cover (6.68%), bare surfaces (1.35%), and agricultural land (12.46%).These changes have profound implications, including the loss of forest and vegetation, increased urbanization, declining agricultural land, and diminishing bare surfaces. Such trends pose challenges for sustainable development and necessitate effective planning. The study underscores the importance of regular monitoring, control, and evaluation of LULC dynamics to mitigate haphazard development and its adverse effects on local communities.
Arbor J. L. Quist, April Hovav, Alexander D. Silverman
et al.
Abstract Background In early October 2021, thousands of residents in Carson, California began complaining of malodors and headaches. Hydrogen sulfide (H 2 S), a noxious odorous gas, was measured at concentrations up to 7000 parts per billion (ppb) and remained above California’s acute air quality standard of 30 ppb for a month. Intermittent elevations of H 2 S continued for 3 months. After 2 months of malodor in this environmental justice community, a government agency attributed the H 2 S to environmental pollution from a warehouse fire. Research has yielded conflicting results on the health effects of H 2 S exposure at levels that were experienced during this event. This research fills a critical need for understanding how people perceive and experience emergent environmental health events and will help shape future responses. Methods Through a community-academic partnership, we conducted 6 focus groups with 33 participants who resided in the Carson area during the crisis. We sought to understand how this incident affected residents through facilitated discussion on topics including information acquisition, impressions of the emergency response, health symptoms, and ongoing impacts. Results The majority of participants were women ( n = 25), identified as Latina/o ( n = 19), and rent their homes ( n = 21). Participants described difficulty obtaining coherent information about the emergency, which resulted in feelings of abandonment. Most participants felt that local government and healthcare providers downplayed and/or disregarded their concerns despite ongoing odors and health symptoms. Participants described experiencing stress from the odors’ unknown health effects and continued fear of future odor incidents. Residents sought to take control of the crisis through information sharing, community networking, and activism. Participants experienced longer term effects from this event, including increased awareness of pollution and reduced trust in local agencies. Discussion This study demonstrates the necessity of clear, comprehensive, and prompt responses by relevant decisionmakers to chemical emergencies to appropriately address residents’ fears, curb the spread of misinformation, and minimize adverse health effects. Participant responses also point to the benefit of supporting horizontal community networks for improved information sharing. By engaging directly with community members, researchers and disaster responders can better understand the various and complex impacts of chemical disasters and can improve response.
Julio C. Rangel, Tarcisio Mendes de Farias, Ana Claudia Sima
et al.
The recent success of Large Language Models (LLM) in a wide range of Natural Language Processing applications opens the path towards novel Question Answering Systems over Knowledge Graphs leveraging LLMs. However, one of the main obstacles preventing their implementation is the scarcity of training data for the task of translating questions into corresponding SPARQL queries, particularly in the case of domain-specific KGs. To overcome this challenge, in this study, we evaluate several strategies for fine-tuning the OpenLlama LLM for question answering over life science knowledge graphs. In particular, we propose an end-to-end data augmentation approach for extending a set of existing queries over a given knowledge graph towards a larger dataset of semantically enriched question-to-SPARQL query pairs, enabling fine-tuning even for datasets where these pairs are scarce. In this context, we also investigate the role of semantic "clues" in the queries, such as meaningful variable names and inline comments. Finally, we evaluate our approach over the real-world Bgee gene expression knowledge graph and we show that semantic clues can improve model performance by up to 33% compared to a baseline with random variable names and no comments included.
Mohammad Hajiesmaili, Shaolei Ren, Ramesh K. Sitaraman
et al.
The skyrocketing demand for artificial intelligence (AI) has created an enormous appetite for globally deployed power-hungry servers. As a result, the environmental footprint of AI systems has come under increasing scrutiny. More crucially, the current way that we exploit AI workloads' flexibility and manage AI systems can lead to wildly different environmental impacts across locations, increasingly raising environmental inequity concerns and creating unintended sociotechnical consequences. In this paper, we advocate environmental equity as a priority for the management of future AI systems, advancing the boundaries of existing resource management for sustainable AI and also adding a unique dimension to AI fairness. Concretely, we uncover the potential of equity-aware geographical load balancing to fairly re-distribute the environmental cost across different regions, followed by algorithmic challenges. We conclude by discussing a few future directions to exploit the full potential of system management approaches to mitigate AI's environmental inequity.
Tehreem Arshad, Muhammad Shahid Rafique, Shazia Bashir
et al.
Lahore (Pakistan), being an industrial city, has high emission of aerosols that affects and contaminates the air quality. Therefore, the abatement/inactivation of aerosols is necessary to restrict their infectious activities. In this project, ionic wind isolated from dielectric barrier discharge plasma (DBD plasma) has been utilized to abate the aerosols trapped in the Surgical Mask and KN95 Respirator. To infer the chemical and elemental detection of ambient aerosols, FTIR and LIBS have been employed. “From the results, it is noteworthy that abatement/removal of aerosols has been successfully carried out by the ionic wind irradiation and highlights the potential of DBD plasma technology in removing the aerosols pollution.”
Environmental sciences, Public aspects of medicine
Alicja Kucharska, Beata Irena Sińska, Mariusz Panczyk
et al.
IntroductionDietary fiber is a key component of a healthy diet, associated with a reduced risk of cardiovascular disease, obesity, type 2 diabetes, certain cancers, chronic inflammation, or depression. The aim of the study was to perform an in-depth analysis of dietary fiber intake in the Polish population, taking account of the consumption of groups of products that are fiber sources and identify any age-related differences in the dietary fiber intake of the subjects.MethodsWe analyzed data obtained from two representative cross-sectional studies on the diet and nutritional status of adult Polish residents including the total of 4,000 individuals aged 19 years and more. Two 24-h recalls were used per individual to assess the diet using the computer-assisted personal interview (CAPI) technique. Total fiber content and fiber contained in cereal products, vegetables, fruits, legumes, nuts and seeds were calculated. Fiber intake was compared to the recommendations: 25 g/d for adults up to 65 years of age and 20 g/d for those aged 66 years and older. All statistical analyses, including the Pearson’s chi-squared test, the Student’s t-test, and the Analysis of Variance (ANOVA), were conducted using STATISTICA™ version 13.3, with the results being adjusted for demographic distribution biases to enhance the representativeness.ResultsThe average daily fiber intake was 17.83 ± 0.14 g/day (78% of the recommended intake), with 20.5% of respondents meeting the requirement. More men than women (27.05% vs. 14.3%;) met the requirement and men were characterized by a higher average intake (19.34 ± 0.20 g/day) than women (16.43 ± 0.19 g/day). The main fiber sources were cereals (44.1%), vegetables (23.6%), and fruits (16.0%). As regards men, the sources included refined bread (25.8%), vegetables (23.1%), and fruits (10.2%) and for women, they were vegetables (24.0%), fruits (17.2%), and refined bread (16.3%). Although refined bread is not recommended as a primary fiber source due to its lower fiber content compared to whole grain bread, its high consumption significantly contributed to the total fiber intake.ConclusionThe prevalence of widespread dietary fiber deficiency calls for the intensification of educational efforts that address the health advantages and sources of dietary fiber, as well as methods for its inclusion in daily meals.
Edoardo Bizzotto, Guido Zampieri, Laura Treu
et al.
Bioactive peptides are short amino acid chains possessing biological activity and exerting physiological effects relevant to human health. Despite their therapeutic value, their identification remains a major problem, as it mainly relies on time-consuming in vitro tests. While bioinformatic tools for the identification of bioactive peptides are available, they are focused on specific functional classes and have not been systematically tested on realistic settings. To tackle this problem, bioactive peptide sequences and functions were here gathered from a variety of databases to generate a unified collection of bioactive peptides from microbial fermentation. This collection was organized into nine functional classes including some previously studied and some unexplored such as immunomodulatory, opioid and cardiovascular peptides. Upon assessing their sequence properties, four alternative encoding methods were tested in combination with a multitude of machine learning algorithms, from basic classifiers like logistic regression to advanced algorithms like BERT. Tests on a total of 171 models showed that, while some functions are intrinsically easier to detect, no single combination of classifiers and encoders worked universally well for all classes. For this reason, we unified all the best individual models for each class and generated CICERON (Classification of bIoaCtive pEptides fRom micrObial fermeNtation), a classification tool for the functional classification of peptides. State-of-the-art classifiers were found to underperform on our realistic benchmark dataset compared to the models included in CICERON. Altogether, our work provides a tool for real-world peptide classification and can serve as a benchmark for future model development.
Patrick Ferris, Michael Dales, Sadiq Jaffer
et al.
We make a case for "planetary computing" -- infrastructure to handle the ingestion, transformation, analysis and publication of global data products for furthering environmental science and enabling better informed policy-making. We draw on our experiences as a team of computer scientists working with environmental scientists on forest carbon and biodiversity preservation, and classify existing solutions by their flexibility in scalably processing geospatial data, and also how well they support building trust in the results via traceability and reproducibility. We identify research gaps in the intersection of computing and environmental science around how to handle continuously changing datasets that are often collected across decades and require careful access control rather than being fully open access.
Ecosystems, which are intricate amalgams of biological communities and their surrounding environments, continually evolve under the influence of their myriad interactions. The world is currently facing intensifying environmental fluctuations. Understanding general trends in ecosystem transformations in response to environmental fluctuations and elucidating the underlying mechanisms are thus critical challenges. In this study, we used a model ecosystem approach to investigate ecosystem alterations caused by escalating environmental fluctuations. We analyzed two distinct models: a stochastic ecosystem model with a spatial structure, and a differential equation model for resource competition. We found that environmental fluctuations tend to shift multi-species coexistence toward the dominance of specific species. We also categorized biological species as specialists or generalists and discovered that which of these groups becomes the dominant species depends on the intensity and frequency of environmental fluctuations. We also determined that a qualitative change in the diversity-stability relationship depends on the period of environmental fluctuations. These results underscore the need to explicitly consider the type of perturbation when discussing ecological transitions and the stability of ecosystems. Our findings advance understanding of the mechanisms underlying how environmental changes reshape ecosystems and offer insights into ecosystem sustainability in the face of future environmental perturbations.
L’une des orientations de la charte du Parc national des Cévennes est de promouvoir une agriculture respectueuse de la biodiversité et des principes de l’agroécologie. Dans un contexte d’évolution globale du climat et de raréfaction de la ressource nectarifère, le Parc a lancé de 2020 à 2023 un programme d'envergure afin d’être un territoire pilote pour l’accueil des pollinisateurs sauvages et domestiques.