Environmental Objectives Research Articles

Implications of Climate Change Litigation for Environmental Law and Policy in Ghana

Purpose: The aim of the study was to examine implications of climate change litigation for environmental law and policy in Ghana Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that the implications of climate change litigation for environmental law and policy in Ghana underscore the urgent need for robust legal frameworks and adaptive policy responses to address the multifaceted challenges posed by climate change. While Ghana has made strides in enacting environmental legislation and participating in international climate agreements, the increasing frequency and severity of climate-related impacts necessitate greater legal clarity, enforcement mechanisms, and stakeholder engagement to enhance climate resilience and adaptation efforts. Climate change litigation provides a crucial avenue for affected communities, civil society organizations, and environmental advocates to hold governments and corporations accountable for their contributions to climate change and their obligations to protect the environment and uphold human rights. Unique Contribution to Theory, Practice and Policy: Legal Mobilization Theory, Policy Diffusion Theory & Ecological Modernization Theory may be used to anchor future studies on implications of climate change litigation for environmental law and policy in Ghana. Encourage strategic litigation that targets key actors, industries, and policy arenas to maximize the impact of legal interventions on environmental protection and climate action. This involves identifying leverage points within existing legal frameworks and leveraging innovative legal strategies, such as public trust doctrines and rights-based approaches, to advance environmental objectives. Foster greater integration of climate change litigation outcomes into national and international environmental policy-making processes. Governments and intergovernmental organizations should proactively incorporate legal precedents, court decisions, and settlement agreements into policy development, implementation, and evaluation.

A Multivariate Analysis of the Interplay between Energy Resources, Economic Growth, and Financial Stability. Evidence from Azerbaijan

Abstract The aim of this research is to conduct an objective and predictive evaluation of Azerbaijan's economic growth from 1997 to 2022. Since Azerbaijan is a significant exporter and producer of energy resources, its economic growth is substantially influenced by the remarkable advancements in oil and gas extraction and production since the early 2000s. Methodologically, we have designed several models to ascertain the influence and impact of the following explanatory factors-oil reserves, natural gas reserves, net trade, current account balance, inflation rate, unemployment rate, interest rate and carbon dioxide emissions - on the economic growth rate. The study utilised a combination of uni- and multi-factorial linear regression techniques, with accuracy and robustness testing conducted on all eight models. Research hypotheses were tested and a predictive analysis was implemented and evaluated over the studied period. Our findings demonstrate that the growth of Azerbaijan's economy is positively impacted by the dynamics and development of energy product trade, particularly in oil. As a result, GDP increased by an average of 2.50%. It is also confirmed that inflation and unemployment have a negative impact which unavoidably leads to instability and an economic downturn. In contrast, the robustness indicators (namely, RMSE, MAE and MAPE) could assess the predictive analysis of economic growth. The validated, low values further endorse the credibility of the eight models in accurately forecasting the economic growth rate throughout the studied period. The study disproves the existence of a positive correlation between GDP and the quantity of carbon dioxide emissions. However, it has been demonstrated that Azerbaijan is taking significant measures to achieve its environmental objectives. These measures include the implementation of taxation, a reduction in CO2 emissions by up to 55% by 2030, and a shift towards renewable energy sources. Our research aims to enhance the utilisation of renewable energy resources, increase the efficiency of the domestic energy infrastructure and implement measures to moderate high levels of unemployment and inflation, thus ensuring sustained economic growth in Azerbaijan.

THE IMPORTANCE OF INVESTMENTS IN THE FORMATION OF THE "GREEN ECONOMY" IN INDUSTRY NETWORKS

The transition to a "green economy" necessitates significant investments across all sectors, particularly within industrial networks. This abstract examines the crucial role of these investments in fostering sustainable practices, promoting innovation, and driving economic growth. By exploring the multifaceted impact of green investments on industry networks, the abstract highlights the importance of public-private partnerships, policy incentives, and technological advancements in enabling a successful and equitable transition. Furthermore, the abstract emphasizes the need for a comprehensive framework that considers both economic and environmental objectives, ensuring that green investments contribute to a prosperous and sustainable future.

Nutrient and organic substances emissions from diffuse sources to the rivers of Ukrainian Carpathians

Formulation of the problem. The transition from territorial-administrative to basin-based water resources management in Ukraine requires an assessment of the load of water bodies with pollutants from diffuse and point sources. Among the various components of the chemical composition of water entering water bodies, organic matter and nutrients are the most important. The Danube is the second largest river in Europe, with a basin covering the territories of 19 countries and is an important transportation waterway. Within Ukraine, the Danube is divided into the Lower Danube sub-catchment and the Tisza, Prut, and Siret River basins within the Carpathian region. The scientific results presented in this paper were obtained during research within the framework of state budgetary research works of the UHMI, the implementation of which will contribute to the further development of knowledge in the field of hydrometeorology. The results presented in the publication are important for supplementing information when writing the Danube River Basin Management Plan, which is being developed in accordance with Ukraine's obligations under the Association Agreement with the European Union. Aim of the study. To calculate the supply of nutrients and organic matter from diffuse sources to the rivers of the Danube basin within the Ukrainian Carpathians. Methods. Monitoring data of organic substances and nutrients provided by the Danube Hydrometeorological Observatory (the state surface water monitoring network of the State Emergency Service of Ukraine) for 2018 were used for calculations. To assess the load of water bodies by diffuse sources, a conceptual scheme was developed that allowed to take into account the main pathways of substances supply, i.e precipitation; water runoff from arable land, forests, meadows and pastures, built-up areas, rock outcrops, as well as from the population of rural regions without sewage systems. Scientific novelty. For the first time: the load of nutrients and organic matter in the Danube rivers within the Ukrainian Carpathians by the sources of their income was evaluated; it was found that agricultural land is the main source of emissions of inorganic nitrogen and phosphorus compounds. Practical value. The analysis of the diffuse load by nutrients and organic matter in the Danube rivers can be used as an important part of the River Basin Management Plan. The results of the calculations can also be used to develop measures to achieve certain environmental objectives. Results. The main source of organic matter in the water of rivers of the Carpathian region ere agricultural enterprises locating within rural settlements that are not equipped with sewage systems. Surface water of Prut and Tisza River basins is the most polluted by organic matter. By source, the nutrient emissions are distributed as follows. For the Tisza and Prut rivers, more than 50% of the total nitrogen compounds emissions come from agricultural land, while for the Siret River the source of nitrogen compounds are forests (46% of the total nitrogen emissions). Accordingly, the total phosphorus runoff for the Tisza and Prut rivers was distributed as follows: the dominant share (up to 45%) comes from agricultural land, the load caused by population not connected to the sewerage systems is 36%. For the Siret River, agricultural land and forested areas are of equal shares (33%) among the sources of phosphorus compounds.

Optimizing smart grid performance: A stochastic approach to renewable energy integration

Smart grids offer numerous possibilities for developing and executing sustainable and efficient electricity supply chains that exhibit increased resilience to disturbances. The exploration of the Electric Supply Chain Network (ESCND) design problem using smart grids has been limited. This article aims to tackle this challenge through the application of a robust multi-objective optimization approach, encompassing three economic goals (maximizing profit), environmental goals (minimizing greenhouse gas emissions), and resilience goals (maximizing network resilience). Additionally, the optimization process takes into account the dual objectives of maximizing efficiency and minimizing energy loss by incorporating relevant cost considerations. The proposed methodology incorporates distinctive features of smart grids, such as demandside management programs, microgrid structures, bidirectional distribution lines, and consumer–supplier nodes. It addresses various interconnected decisions, including location placement, capacity expansion, load allocation, and pricing. To solve the formulated model, a potent combination of multi-objective optimization methods based on cutting-plane algorithms and AUGMECON2 is introduced. Subsequently, the proposed model and solution approach are applied to a practical case study, and the obtained results are comprehensively examined. The findings suggest that, despite potential contradictions between economic and environmental objectives, the implementation of smart grids can concurrently improve environmental performance and network flexibility.

Circular Business Models: Drivers and Barriers to SMEs in North Macedonia

Running a business in an era increasingly concerned with climate change poses challenges for all stakeholders. Governments and intergovernmental organizations are enacting new regulations, compelling businesses to adapt. While some companies have proactively shifted to eco-friendly production systems, others face pressure to change. To meet these evolving demands, businesses are exploring models that align with the circular economy. This study is aimed at exploring the drivers and barriers to circular business models as well as the challenges small and medium sized companies face to achieve the environmental and business objectives. Through a survey conducted among small and medium-sized enterprises in North Macedonia, both closed and open-ended questions were utilized to gather insights. The findings reveal a spectrum of engagement, ranging from incorporating circular principles in product design to active involvement in material recycling. These results underscore a growing willingness within the business community to embrace sustainable and circular business models.

Effect of different sizes of nanocopper particles on rainbow trout (Oncorhynchus mykiss W.) spermatozoa motility kinematics

In recent years, nanocopper (Cu NPs) has gained attention due to its antimicrobial properties and potential for industrial, agricultural, and consumer applications. But it also has several effects on the aquatic environment. Widespread use of various nanoproducts has raised concerns about impacts of different nanoparticle size on environment and biological objects. Spermatozoa is a model for studying the ecotoxic effects of pollutants on cells and organisms. This study aimed to investigate the effects of different sizes of copper nanoparticles on rainbow trout spermatozoa motility, and to compare their effects with copper ionic solution. Computer assisted sperm analysis (CASA) was used to detect movement parameters at activation of gametes (direct effect) with milieu containing nanocopper of primary particle size of 40–60, 60–80 and 100 nm. The effect of the elements ions was also tested using copper sulfate solution. All products was prepared in concentration of 0, 1, 5, 50, 125, 250, 350, 500, 750, and 1000 mg Cu L−1. Six motility parameters were selected for analysis.The harmful effect of Cu NPS nanoparticle was lower than ionic form of copper but the effect depends on the motility parameters. Ionic form caused complete immobilization (MOT = 0 %, IC100) at 350 mg Cu L−1 whilst Cu NPs solution only decreased the percentage of motile sperm (MOT) up to 76.4 % at highest concentration tested of 1000 mg Cu L−1 of 40–60 nm NPs. Cu NPs of smaller particles size had more deleterious effect than the bigger one particularly in percentage of MOT and for curvilinear velocity (VCL). Moreover, nanoparticles decrease motility duration (MD). This may influence fertility because the first two parameters positively correlate with fertilization rate. However, the ionic form of copper has deleterious effect on the percentage of MOT and linearity (LIN), but in some concentrations it slightly increases VCL and MD.

Unveiling the complex networks of urban tree diversity research: A global perspective.

Ecosystem services offered by urban forests must be proactively managed to remain diverse and sustainable. Recent research findings deserve a systematic synthesis to elucidate inherent knowledge structures and dynamics. This study focused on the urban tree diversity theme from 2000 to 2022. Web of Science Core Collection database provided bibliometric details on academic publications. The data-driven quantitative analysis explored research quantities, emphasis, trends, patterns, linkages, and impacts by countries, institutions, authors, journals, and citations. Publications and research topics have expanded continually, with accelerated growth in recent years. Research activities, outputs and interactions demonstrated conspicuous spatial clustering. A few countries, institutions and researchers generated a notable proportion of publications. Their scholarly contributions were visualized in knowledge graphs as complex networks of nodes and inter-node links. Keyword analysis generated a network to indicate research hotspots and frontiers to steer and prioritize future studies. Recent findings affirmed that cities can harbor substantial tree diversity due to enhanced habitat heterogeneity and successful species adaptation. Aligning tree traits with environmental conditions and management objectives can improve benefits. Urbanization can filter tree traits to shape community assemblages through stressors: habitat degradation, fragmentation and loss, in conjunction with pollution, climate change, and introduced species. Diversity preservation strategies include protecting remnant natural vegetation, connecting green spaces, and restoring complex canopy geometry and biomass structure. The emerging frontiers are marked by modeling future species distributions, leveraging technologies like remote sensing, linking ecology with human values, and committing to community-based stewardship. Management can be upgraded by interdisciplinary perspectives integrating ecological science and social engagement. The findings highlight the need for biodiversity enrichment anchored by native species, trait-matched assemblages, adaptive policies, and community participation to create livable-green cities. This review synthesizes key advances in urban tree ecology and biodiversity research to inform the planning and stewardship of resilient urban forests.

Sex-specific associations of the maturation locus vgll3 with exploratory behavior and boldness in Atlantic salmon juveniles.

Studies linking genetics, behavior and life history in any species are rare. In Atlantic salmon (Salmo salar), age at maturity is a key life-history trait and associates strongly with the vgll3 locus, whereby the vgll3*E allele is linked with younger age at maturity, and higher body condition than the vgll3*L allele. However, the relationship between this genetic variation and behaviors like boldness and exploration which may impact growth and reproductive strategies is poorly understood. The pace-of-life syndrome (POLS) framework provides predictions, whereby heightened exploratory behavior and boldness are predicted in individuals with the early maturation-associated vgll3 genotype (EE). Here, we tested these predictions by investigating the relationship between vgll3 genotypes and exploration and boldness behaviors in 129 juveniles using the novel environment and novel object trials. Our results indicated that contrary to POLS predictions, vgll3*LL fish were bolder and more explorative, suggesting a genotype-level syndrome including several behaviors. Interestingly, clear sex differences were observed in the latency to move in a new environment, with vgll3*EE males, but not females, taking longer to move than their vgll3*LL counterparts. Our results provide further empirical support for recent calls to consider more nuanced explanations than the pace of life theory for integrating behavior into life-history theory.

Exploring Entrepreneurial Intention for Sustainable Development: a Study of University Students in Kolea, Algeria

Abstract Research purpose Entrepreneurship's evolving role now extends beyond economic realms to encompass broader societal and environmental imperatives. Sustainable entrepreneurship emerges as a linchpin in addressing contemporary challenges, offering innovative solutions that harmonize economic resilience with environmental and social objectives. Yet, the determinants underpinning individuals' intentions towards sustainable entrepreneurship, particularly within the Algerian context, remain underexplored. Keeping this into consideration, our research endeavours to identify the motivational factors influencing the decision to engage in sustainable entrepreneurial activities among students at the Kolea University Pole. Design / Methodology / Approach Drawing on a quantitative approach, data from 370 student responses were analysed using linear regression analysis. Findings The findings reveal the significant influence of both internal and external determinants on entrepreneurial intention for sustainable development among students. Internally, factors such as perceived entrepreneurial feasibility, perceived behavioural control, and attitudes towards sustainability emerged as key drivers of entrepreneurial intention towards sustainability. Students with a strong inclination towards sustainability exhibited a heightened intention to engage in entrepreneurial activities aligned with sustainable development goals. Externally, sociological factors and social networks were found to exert a significant positive influence on sustainable entrepreneurship intention. This underscores the importance of familial, educational, and societal support structures in fostering an entrepreneurial mindset among students, shedding light on the role of information and communication technologies in shaping this intention. Yet, the study also highlights a concerning lack of awareness among students regarding the role of entrepreneurship in addressing environmental challenges underscoring the need for educational interventions aimed at cultivating an environmental ethos among students. Originality/Value/Practical Implications This study contributes to the discourse on sustainable entrepreneurship in developing countries, particularly in Algeria, by elucidating the factors influencing entrepreneurial intention among students. The findings underscore the importance of both internal and external determinants in shaping students' entrepreneurial aspirations, with implications for educational policy and practice.

RUSSIAN-UKRAINIAN DISPUTES OVER SOVIET LEGACY AFTER 1991. BULGARIAN DIPLOMATIC PERSPECTIVE

The article analyzes the possibility of introducing a law on protective forest curtains into the national normative framework, following the existing provisions for this category of natural resource elements and the gaps between the responsibilities and rights of different categories of subjects regarding the management of forest protective curtains. The need to harmonize the phrase „protective forest curtains” in the entire spectrum of normative acts is highlighted, as currently the legislator operates with several interchangeable terms that can create unnecessary confusion in solving the addressed problem. At the same time, a clear underlining of the attributions of the local public authorities is necessary in order to monitor the quality of the forest curtains in the managed perimeter, since the lack of clarity of the existing attributions does not allow the implementation of the environmental objectives established by the public policy documents of the Republic of Moldova in its international commitments in the field of environmental protection.

Multi-objective optimization of an integrated energy system based on enhanced NSGA-II

Abstract To solve the energy crisis, China has made great efforts to develop an integrated energy system to achieve multi-energy coordination, mutual aid, energy conservation, and carbon reduction. This article mainly studies the multi-objective optimization scheduling problem of a combined cooling, heating, and power system considering wind and solar energy storage. Firstly, from two different perspectives of economy and carbon emissions, an economic objective function and an environmental objective function are established, and a multi-objective optimization configuration model and corresponding constraint conditions for the combined cooling, heating, and power system considering wind and solar energy storage are constructed. Then, an enhanced non-dominated sorting genetic algorithm II (NSGA-II) is proposed, which enhances the efficiency and accuracy of the algorithm by introducing dominance strength and variance factors. Finally, a simulation analysis was conducted on a running cogeneration system in a certain area of western Liaoning to attest to the validity of the model and method proposed in this paper.

The inhibitory effect of a recent distractor: singleton vs. multiple distractors

In the complex interplay between sensory and cognitive processes, the brain must sift through a flood of sensory data to pinpoint relevant signals. This selective mechanism is crucial for the effective control of behaviour, by allowing organisms to focus on important tasks and blocking out distractions. The Inhibition of a Recent Distractor (IRD) Task examines this selection process by exploring how inhibiting distractors influences subsequent eye movements towards an object in the visual environment. In a series of experiments, research by Crawford et al. (2005a) demonstrated a delayed response to a target appearing at the location that was previously occupied by a distractor, demonstrating a legacy inhibition exerted by the distractor on the spatial location of the upcoming target. This study aimed to replicate this effect and to investigate any potential constraints when multiple distractors are presented. Exploring whether the effect is observed in more ecologically relevant scenarios with multiple distractors is crucial for assessing the extent to which it can be applied to a broader range of environments. Experiment 1 successfully replicated the effect, showing a significant IRD effect only with a single distractor. Experiments 2–5 explored a number of possible explanations for this phenomenon.

Applications of implementation science in integrated conservation + health programs: Improved learning to achieve environmental and health objectives

Applications of implementation science in integrated conservation + health programs: Improved learning to achieve environmental and health objectives

Smart platforming in automotive manufacturing for NetZero: Intelligentization, green technology, and innovation dynamics

Green technology innovation is integral to fostering sustainable economic development and environmental conservation. The application of smart product platform has emerged as a transformative force in shaping the trajectory of green technology innovation. Drawing on the foundation of knowledge theory and utilizing a sample of 1240 valid cases from listed Chinese automotive manufacturing enterprises between 2013 and 2022, this paper employs a mixed regression method to explore the relationship between smart product platform usage and green technology innovation. Additionally, it analyzes the mediating role of corporate innovation input in this relationship and the moderating effect of intelligentization level on the association between smart product platform usage and green technology innovation. The research reveals the following key findings: (1) Corporate smart product platform usage and innovation input significantly and positively drive green technology innovation. (2) Innovation input acts as a complete mediator in the relationship between smart product platform usage and green technology innovation. (3) Corporate intelligentization level positively moderates the relationship between smart product platform usage and innovation input. (4) Considering regional and ownership attribute disparities, the impact of smart product platform usage on green technology innovation is asymmetric. This study, as one of the few empirical examinations of the effects of smart product platform, enriches research in the areas of smart product platform and green technology innovation. The study, contributing to the empirical understanding of smart product platforms, offers valuable insights for automotive manufacturing enterprises to strategically leverage these platforms for advanced and flexible operations, aligning with the imperative of achieving global environmental goals such as NetZero. As indicated in COP28, the findings underscore the urgency of integrating smart technologies into the automotive industry to advance these crucial environmental objectives.

Harmony in Practice: A Case Study Approach in Exploring the Intersection of Corporate Social Responsibility and Environmental Stewardship

“Corporate Social Responsibility is a management concept whereby companies integrate social and environmental concerns in their business operations and interactions with their stakeholders.” The Companies Act, 2013, mandated companies meeting specific criteria to allocate a percentage of their profits towards socially responsible initiatives, reflecting a paradigm shift in acknowledging the role of businesses in contributing to social and environmental objectives. Key CSR activities in India focus on education, healthcare, and environmental sustainability, with corporations aligning with national priorities such as the Swachh Bharat Abhiyan. The article highlights successful case studies exemplifying the integration of CSR with environmental initiatives, including Tata Group's sustainable development initiatives, Infosys' green IT practices, and ITC Limited's Triple Bottom Line Approach. Furthermore, the challenges faced by companies in integrating CSR and environmental sustainability in India are elucidated, ranging from regulatory complexities to resource constraints and the need for continuous innovation. The article provides a comprehensive overview of the evolving landscape of corporate social responsibility and environmental stewardship in India, highlighting successful case studies, challenges faced, and the pivotal role of regulatory frameworks in shaping corporate behavior towards environmentally responsible practices.

SayNav: Grounding Large Language Models for Dynamic Planning to Navigation in New Environments

Semantic reasoning and dynamic planning capabilities are crucial for an autonomous agent to perform complex navigation tasks in unknown environments. It requires a large amount of common-sense knowledge, that humans possess, to succeed in these tasks. We present SayNav, a new approach that leverages human knowledge from Large Language Models (LLMs) for efficient generalization to complex navigation tasks in unknown large-scale environments. SayNav uses a novel grounding mechanism, that incrementally builds a 3D scene graph of the explored environment as inputs to LLMs, for generating feasible and contextually appropriate high-level plans for navigation. The LLM-generated plan is then executed by a pre-trained low-level planner, that treats each planned step as a short-distance point-goal navigation sub-task. SayNav dynamically generates step-by-step instructions during navigation and continuously refines future steps based on newly perceived information. We evaluate SayNav on multi-object navigation (MultiON) task, that requires the agent to utilize a massive amount of human knowledge to efficiently search multiple different objects in an unknown environment. We also introduce a benchmark dataset for MultiON task employing ProcTHOR framework that provides large photo-realistic indoor environments with variety of objects. SayNav achieves state-of-the-art results and even outperforms an oracle based baseline with strong ground-truth assumptions by more than 8% in terms of success rate, highlighting its ability to generate dynamic plans for successfully locating objects in large-scale new environments. The code, benchmark dataset and demonstration videos are accessible at https://www.sri.com/ics/computer-vision/saynav.

Uncertainty in Environmental Micropollutant Modeling.

Water pollution policies have been enacted across the globe to minimize the environmental risks posed by micropollutants (MPs). For regulative institutions to be able to ensure the realization of environmental objectives, they need information on the environmental fate of MPs. Furthermore, there is an urgent need to further improve environmental decision-making, which heavily relies on scientific data. Use of mathematical and computational modeling in environmental permit processes for water construction activities has increased. Uncertainty of input data considers several steps from sampling and analysis to physico-chemical characteristics of MP. Machine learning (ML) methods are an emerging technique in this field. ML techniques might become more crucial for MP modeling as the amount of data is constantly increasing and the emerging new ML approaches and applications are developed. It seems that both modeling strategies, traditional and ML, use quite similar methods to obtain uncertainties. Process based models cannot consider all known and relevant processes, making the comprehensive estimation of uncertainty challenging. Problems in a comprehensive uncertainty analysis within ML approach are even greater. For both approaches generic and common method seems to be more useful in a practice than those emerging from ab initio. The implementation of the modeling results, including uncertainty and the precautionary principle, should be researched more deeply to achieve a reliable estimation of the effect of an action on the chemical and ecological status of an environment without underestimating or overestimating the risk. The prevailing uncertainties need to be identified and acknowledged and if possible, reduced. This paper provides an overview of different aspects that concern the topic of uncertainty in MP modeling.

Mixture optimization for mechanical, environmental, and economic objectives in grouting slurry for repairing earthen sites

Anchor and fissure grouting are used to repair earthen sites. However, the common method to obtain the compressive strength of grouting slurry would cause material, labor, and time losses. In addition the material properties, environmental and economic benefits have gained increasing attention. This study proposes a design framework for multi-objective proportioning optimization based on machine learning and metaheuristics. The results indicated that the eXtreme Gradient Boosting (XGBoost) model, whose hyper-parameters were optimized by a genetic algorithm, can accurately predicted the compressive strength of the slurries. The impact of the variables on development of compressive strength can explain the internal reaction mechanisms. The analytical framework based on meta-heuristic and technique for order of preference by similarity to an ideal solution (TOPSIS) provided Pareto-optimal solutions in design scenario of each sub-dataset. The framework proposed in this study can efficiently achieve mechanical, environmental, and economic design objectives of anchor grouting and fissure grouting slurries for repairing earthen sites.

Avian eye-inspired perovskite artificial vision system for foveated and multispectral imaging.

Avian eyes have deep central foveae as a result of extensive evolution. Deep foveae efficiently refract incident light, creating a magnified image of the target object and making it easier to track object motion. These features are essential for detecting and tracking remote objects in dynamic environments. Furthermore, avian eyes respond to a wide spectrum of light, including visible and ultraviolet light, allowing them to efficiently distinguish the target object from complex backgrounds. Despite notable advances in artificial vision systems that mimic animal vision, the exceptional object detection and targeting capabilities of avian eyes via foveated and multispectral imaging remain underexplored. Here, we present an artificial vision system that capitalizes on these aspects of avian vision. We introduce an artificial fovea and vertically stacked perovskite photodetector arrays whose designs were optimized by theoretical simulations for the demonstration of foveated and multispectral imaging. The artificial vision system successfully identifies colored and mixed-color objects and detects remote objects through foveated imaging. The potential for use in uncrewed aerial vehicles that need to detect, track, and recognize distant targets in dynamic environments is also discussed. Our avian eye-inspired perovskite artificial vision system marks a notable advance in bioinspired artificial visions.