Search Results (778)

Non-human animals are systematically excluded from public narratives, rarely recognized as sentient subjects, and instead framed within anthropocentric narratives of production and consumption; efforts to challenge this pattern and make the more-than-human world visible often encounter editorial resistance and structural constraints. This study examines how anti-speciesist journalists in Spanish written media navigate such resistance to make non-human animals legitimate subjects of news. Drawing on semi-structured interviews with nine self-identified anti-speciesist journalists, analysed through reflexive thematic analysis, the study identifies strategies organized across four non-mutually exclusive categories, namely, discursive, relational, framing, and structural, ranging from self-censorship and strategic language use to coalition-building and the creation of independent platforms. Findings reveal a key distinction between visibility strategies, which succeed in securing publication, and root-level strategies, which challenge the carnist and anthropocentric assumptions structuring newsworthiness itself. These practices reveal the pragmatism, creativity, and resilience of journalists working under structural, ideological, and normative constraints, while also highlighting the limits of anti-speciesist reporting within mainstream media. The study contributes to Critical Animal Media Studies, environmental communication, and journalism research by illuminating the intersection of ethical advocacy, professional strategy, and counter-hegemonic practice and offers recommendations for expanding coverage of the more-than-human world across ideological, editorial, and structural divides. Full article

International shipping decarbonization has expanded beyond technical and operational regulation to include contested market-based bargaining. The proposed International Maritime Organization (IMO) Net-Zero Framework (NZF) combines a marine fuel standard with an economic compliance mechanism. Drawing on IMO submissions, voting records, official statements, and domestic and sectoral materials, this two-level game analysis examines why support sufficient to approve the draft for circulation in April 2025 did not translate into timely adoption later that year. The evidence suggests that the initial agreement space was not durable enough to support adoption on the planned timetable. At Level I, bargaining involved three linked dimensions: rule-making authority, responsibility allocation, and transition pathway design. At Level II, domestic, regional, and sectoral constraints included regulatory credibility and investment signals for the European Union; sovereignty and cost concerns for the United States; trade exposure and disproportionate impacts for trade-exposed emerging economies; ambition and revenue-supported transition for small island developing States; and fuel availability, fleet competitiveness, and legal certainty for energy exporters and open registries. A coalition sufficient at one procedural stage may therefore not remain sufficient at the next. A more durable agreement space would likely require an IMO-centered regulatory core, targeted enabling support, an ambition floor with compliance flexibility, and sequenced implementation and review. Full article

In view of the task allocation problem under communication constraints, this paper proposes a distributed performance impact (DPI) algorithm for heterogeneous multi-UAV cooperation. First, the task allocation problem is modelled, incorporating task requirements, heterogeneous flight performance and non-ideal networked communication. Then, a multi-phase DPI algorithm is designed in five stages: task inclusion, cluster generation, conflict resolution, coalition formation and task segmentation. Based on task inclusion, a communication-reachable networked cluster generation method is developed. The conflict resolution mechanism is improved based on the removal-performance-impact and task contribution rate. Further considering independently unachievable tasks, a dual-fallback mechanism is constructed by a pruning-redundancy coalition formation scheme and a task- segmentation scheme, thereby enhancing both system operational efficiency and task-completion certainty. Finally, simulations are conducted to demonstrate the effectiveness, superiority and robustness of the proposed DPI algorithm. Full article

For millennia, farmers in cassava’s homeland in the neotropics selected varieties suited to their climate, soils, biological environments, management systems, and nutritional needs. These actions were fundamental to the crop’s success as a reliable staple energy source. After the arrival of Europeans in the New World, these varieties spread first to Africa and later to Asia, where they were further selected for local conditions and needs. The founders of the International Center for Tropical Agriculture in Cali, Colombia, recognized the importance of legacy landrace varieties as sources of genetic diversity for breeding to support tropical production systems, improve nutrition, and boost income. One of earliest activities of the new center, beginning in 1969, was to organize the collection of cassava landraces to establish a genetic resource for breeding purposes at the center’s headquarters in the Cauca Valley. We describe the multifaceted understanding about this remarkable heritage through thorough evaluation over a diverse range of environments and the creation of new varieties aimed at adding value across the crop’s diverse agro-ecologies and uses. CIAT breeders, along with a broad coalition of partners, have targeted demands from growers, processors, and consumers throughout the tropics. Latin American germplasm remains the foundational source of novel, high-value traits that differentiate cassava products across markets, underpinning the continued gains in productivity, quality, and end-use performance. Full article

This conceptual paper examines how dominant frameworks of college access and equity in U.S. higher education marginalize undocumented and international students by anchoring inclusion to citizenship, legal eligibility, and institutional risk management. In the context of intensified anti-DEI and anti-immigrant politics, legally precarious students face overlapping yet distinct legal, financial, emotional, and symbolic forms of exclusion that conventional access and equity models do not fully capture. Institutional retreat, anticipatory obedience, and the re-coding of equity work can further make supports for these students harder to locate, defend, and sustain. Synthesizing scholarship on college access, undocumented and international student experiences, critical citizenship studies, legal status stratification, border theory, anticipatory obedience, and coalitional politics, the paper argues for moving “beyond legality” as the organizing framework of access. It advances a conceptual model of College Access Beyond Legality centered on four interlocking structures: emotional safety and trust, informal resource networks, campus and community organizing, and identity-based and status-conscious advocacy. The model conceptualizes cross-status coalition-building among students, institutional stakeholders, faculty, and community partners as both a survival strategy and a practice of institutional accountability. It also emphasizes that access beyond legality must begin before matriculation and extend through persistence, belonging, and post-graduation transitions. The model aims to reduce harm, strengthen belonging, expand access to material supports, support persistence, and deepen institutional accountability. The paper concludes with implications for institutional policy, equity practice, basic-needs and community-connection infrastructures, and future research aimed at expanding access for marginalized students in legally and politically hostile contexts. Full article

Social sustainability refers to the dimensions of sustainability that emphasize human well-being, equity, social justice, and access to essential services, including food security. Within this framework, ensuring access to safe and affordable food for individuals with celiac disease represents a critical yet underexplored policy challenge. This article examines how policy entrepreneurship contributes to advancing social sustainability in the context of food insecurity among individuals with celiac disease in Israel. It focuses on the Israeli Celiac Rights Organization (ICRO) as a case of civil society-driven policy entrepreneurship. Using a qualitative case study design, based on semi-structured interviews, media analysis, and policy documents, the study demonstrates how the ICRO has reframed celiac disease as a social rights issue, built cross-sectoral coalitions, and influenced both governmental and market actors. The findings show that, while state and market mechanisms provided only partial and fragmented responses, policy entrepreneurs played a significant role in transforming an invisible social problem into a recognized policy issue. The article contributes to the literature on social sustainability and policy entrepreneurship by highlighting the mechanisms through which non-state actors shape policy outcomes in contexts of institutional failure. Full article

Shared energy storage (SES) can mitigate the high investment cost and low utilization efficiency associated with independently configured energy storage in user-side integrated energy systems. This paper proposes a bi-level optimal configuration method for SES considering frequency regulation revenue and energy storage degradation costs. First, for a multi-park scenario in which several parks jointly construct and share an SES station, an upper-level investment and operation model is developed to minimize the comprehensive cost of the SES station, while considering its participation in the frequency regulation market and the degradation cost caused by charge–discharge cycling. A lower-level coordinated operation model is then established to optimize the joint operating economy of the parks. Second, the Karush–Kuhn–Tucker (KKT) conditions of the lower-level model and the Big-M method are used to reformulate the bi-level problem as a single-level mixed-integer linear programming (MILP) model. Third, a bilateral Shapley value method is introduced to fairly allocate the SES investment cost. Finally, case studies are conducted to verify the rationality and effectiveness of the proposed bi-level model. The results show that the optimal rated power and rated energy capacity of the SES are 22.00 MW and 44.00 MWh, respectively. Participation in frequency regulation increases the annual net profit of the SES operator by 7.31%, whereas ignoring the degradation cost increases the annual net profit to CNY 11.29 million, thereby overestimating the actual economic performance of the project. Compared with independently configured energy storage, the comprehensive cost of the three-park grand coalition is reduced by 16.96%. Overall, the proposed method can coordinate SES capacity configuration, frequency regulation revenue, and degradation cost, thereby reducing the comprehensive energy storage cost of multiple parks and improving project economics while providing a reference for the planning and operation of multi-park SES under high renewable energy penetration. Full article

This article will offer a comparative analysis between Latin American Liberation Theology (LALT) and Islamic Coalition Theology in the broader literature on liberation theology. The purpose of this comparison is to highlight a fundamental structural divergence in their political and theological orientations. The 1979 Islamic revolution in Iran is elaborated in this conceptual context to situate the debate in a recent practical example of the Islamic Coalition Theology that led to a political revolution. Whereas LALT developed as an autonomous Christian critique of structural injustice and Western capitalist domination, Islamic Coalition Theology, as also reverberated in the 1979 Islamic revolution in Iran evolved through a coalitional paradigm—what was contemporaneously described as the ‘red and the black reaction’ (ertejāʿ-e sorkh o siyāh in Persian)—in which Islamic, non-religious, and even irreligious ideologies temporarily converged to confront a shared adversary: Western imperialism and its domestic expansionism worldwide. Under the broader intellectual influence of twentieth-century global leftist movements, Iran’s revolutionary Islamism absorbed and adapted elements of Marxist and anti-capitalist discourse, and indeed merged with them without relinquishing its theological core. This study argues that such ideological hybridity reveals a distinctive pragmatism within Islamic political philosophy, wherein the pursuit of liberation is not confined to doctrinal purity but is instrumentally open to external alliances and ‘coalitions’ that lead to a common political goal. Through a comparative theological and political hermeneutic, the article will situate Islamic Coalition Theology within the global genealogy of liberationist thought, demonstrating how its strategic inclusiveness contrasts with LALT’s predominantly intra-Christian reformism. The article will build on the argument that Islam primarily encompasses a comprehensive normative and political and jurisprudential order grounded in the Quran; therefore, its coalition theology is charged with its political openness to be chaperoned with any political agenda that too pursues the common political goal. Full article

Central and Eastern Europe (CEE) carries some of the widest immunisation gaps in Europe, and improving coverage there is often treated as a problem of access infrastructure. On 14 May 2026, a multi-stakeholder meeting hosted at the Romanian Parliament brought together around twenty-five speakers, among some fifty participants in all, from Romania, Poland, the Czech Republic, and Bulgaria, together with international contributors, to agree which barriers to vaccine confidence matter most in the region, which interventions are deliverable within 12 to 24 months, and how responsibility for them should be divided among stakeholders. This Perspective synthesises that discussion as a set of strategies for coverage. Meeting-derived priorities are set against published coverage and confidence data for the region and against the published intervention literature. We argue that the central problem across the region is eroded trust rather than missing information, because misinformation succeeds mainly where trust has already broken down, a process deepened by a historically conditioned, post-communist distrust of public institutions. The two recommendations carried most strongly, as both high in expected impact and achievable within 12 to 24 months, were continuing professional education for primary care on vaccine communication and the resourcing of locally trusted community figures, including health mediators working with marginalised populations. We then show how system-design reforms already demonstrated in the region, in particular pharmacy-based vaccination, direct reimbursement, and targeted outreach to under-vaccinated and marginalised groups, turn restored confidence into measurable coverage while narrowing inequities. We close with a 12-to-24-month agenda for CEE, organised around a clear multi-stakeholder division of labour. These are stakeholder-derived priorities that now require implementation and evaluation. Full article

Distributed integrated energy microgrids support the low-carbon transition of regional energy systems. However, multi-agent trading among microgrids still faces insufficient cross-market coordination, weak low-carbon incentives, and difficulties in fair benefit allocation. To address these issues, this paper proposes a cooperative-game-based low-carbon optimal operation strategy for multi-microgrids using multi-agent deep reinforcement learning. First, an energy-carbon-green certificate peer-to-peer coordinated trading mechanism and a green-carbon offsetting-based dual-incentive model are developed to link energy exchange, carbon quota adjustment, and green certificate circulation. Second, a Nash bargaining-based cooperative game model is formulated for multi-commodity P2P trading to maximize coalition benefits and ensure a fair allocation of surplus. Finally, the cooperative game is transformed into a Markov decision process, and a centralized training and decentralized execution framework with homogeneous agents is constructed based on the multi-agent soft actor-critic algorithm. Case studies using data from the Yangtze River Delta region of China show that the proposed method achieves a 1.25% optimality gap compared with the centralized MILP benchmark and reduces the coalition operating cost by 8.19% relative to independent operation. The carbon trading costs of the three microgrids are reduced by 37.27%, 40.13%, and 33.82%, respectively, verifying the economic applicability of the proposed method. Full article

Existing data valuation methods assign value to individual data points, ignoring the workflow structure through which value is generated in machine learning (ML) pipelines. In practice, value emerges from a chain of interdependent actions—collection, preprocessing, feature engineering, and model training—performed by different agents with intertwined incentives. We propose a workflow-level data valuation framework that jointly addresses ownership attribution and compensation stability. We formalize the Data Chain (DC) and derive an ownership assignment rule from incomplete contract theory: The agents with the highest marginal contributions are retained in the compensation coalition. Under supermodular characteristic functions and a stated contextual-dominance condition, this choice does not increase the Least-core deficit relative to any competing retained set reachable by single-action swaps. Recognizing that workflow structures demand coalition stability over distributional fairness, we adopt the Least-core with contribution-aware coefficients to allocate compensation. We prove that the surplus game transformation preserves the core structure (core translation invariance), that the Data Chain Shapley value satisfies the efficiency axiom, and that our LP formulation with $W_i=\left|{\psi }_i\right|$ guarantees feasibility. Experiments on multiple datasets show that, with a linear base classifier, competitive integration achieves full or near-full coalition-constraint satisfaction while preserving per-agent feasibility. We also assess supermodularity empirically and identify a narrower stability regime when high-capacity models are substitutable. These results define the framework’s present scope and scalability limits. Full article

Irrigation water management in arid systems requires spatially distributed estimates of crop evapotranspiration (ET) that fixed crop coefficients cannot provide. The actual ET of flood-irrigated rice (Oryza sativa L.) on the arid northern coast of Peru was mapped with the METRIC surface energy balance model (Mapping EvapoTranspiration at high Resolution with Internalized Calibration) on Google Earth Engine (GEE). Ten cloud-free Landsat 8/9 scenes (January–July 2022) were processed over 113 ha at Ferreñafe (Lambayeque) on the 30 m product grid, onto which the 100 m native thermal observation was resampled, with internal calibration based on automatic anchor-pixel selection and hourly ERA5-Land data. Daily field-mean ET ranged from 4.2 to 8.1 mm d⁻¹, peaking during flooding and establishment and declining towards harvest. Because the same reference $E{T}_o$ underlies the METRIC internal calibration and the FAO-56 estimate, this is a comparison between two modelling approaches rather than an independent validation. Against the FAO-56 reference ET, METRIC showed a positive bias of $+0.65$ mm d⁻¹ (percent bias (PBIAS) $=+13\%$; root mean square error (RMSE) $=1.23$ mm d⁻¹; $r^2=0.57$; $n=9$, after excluding one date with anomalous reanalysis forcing), concentrated during flooding and after harvest, whereas at full canopy cover the two estimates converged. Two global ET products that share neither the METRIC formulation nor the ERA5-Land forcing reproduce the same seasonal decline once the canopy closes ($r=0.63$ and $0.91$) but stay far below in magnitude, as expected from their 500 m pixel. ET did not differ between sowing methods and varied only slightly among cultivars (∼0.3 mm d⁻¹), against marked intra-field variability. The METRIC–GEE workflow offers a low-cost, high-resolution tool for monitoring water use in data-scarce arid rice systems. Full article

The mathematical representation of discrete signals is classically governed by linear basis transforms, such as the Discrete Fourier Transform (DFT), which treat spectral projection as a rigid, deterministic geometric operation. Under this paradigm, signal compression and thresholding rely on heuristic error metrics like the Minimum Mean Squared Error (MMSE). To mathematically axiomatize these fundamental operations, this paper reformulates computational basis transforms through the lens of Cooperative Game Theory. By defining discrete signal reconstruction as a Grand Coalition of orthogonal frequency players, we establish a strict mathematical isomorphism between functional analysis and cooperative game theory. We prove that the spectral energy assigned to each frequency coefficient is exactly its Shapley Value and that classical MMSE minimization is mathematically equivalent to maximizing the retained Shapley payout. Furthermore, we extend this framework to physical hardware and linear shift-invariant (LSI) systems, modeling 8-bit quantization and the Modulation Transfer Function (MTF) as sub-additive “economic taxes” on the coalition. Finally, by intentionally violating the Shapley Symmetry Axiom to mimic the Contrast Sensitivity Function (CSF) of the human visual system, we propose a fundamentally new mathematical basis: the Perceptual Game-Theoretic Transform (PGTT). Unlike classical methods that rely on post hoc quantization for signal compression, the PGTT acts as an inherently efficient transform that structurally guarantees sub-Nyquist computational complexity and dynamic range reallocation prior to physical hardware saturation. Full article

An increasing number of special Internet of Things (IoT) applications are being deployed within federated and zero-trust (ZT) environments. These ad-hoc networks consist of heterogeneous, resource-constrained devices from various administrative domains, all of which are susceptible to compromise. The dynamic nature of these environments necessitates near-real-time Situational Awareness (SA), where processed data varies with its sensitivity and reliability, without dependence on a central authority. Examples include NATO and non-NATO coalitions engaged in hybrid military operations or humanitarian aid scenarios. To address the challenges of security, reliability, and context-aware data dissemination, we propose $FedM$, a multi-level formal model designed for context-aware and policy-driven data dissemination in federated IoT environments. This model is built upon various access control models and Denning’s research on information flow control (IFC), prioritizing the protection and reliability of data flows. A crucial element of this model is the distributed ledger, which facilitates the dynamic modification of label expressiveness, enhances resilience against disruption attacks, and separates policy logic from application functionality to mitigate risks associated with the benevolent developer. Additionally, we delineate a deterministic and history- and precedence-aware policy enforcement procedure to resolve conflicting actions and introduce processing primitives for the ongoing Data Quality Assessment (DQA) process. Our model also aligns with the concepts of Ubiquitous and Continuum Computing. Furthermore, in our paper we illustrate a policy-based dissemination pipeline, incorporating a bounded trustworthiness dimension. Additionally, we present a refined multi-layered framework that proposes the deployment of Information Flow Control (IFC) components, such as the Open Policy Agent decision engine, to facilitate policy-driven contextual data dissemination. We provide preliminary benchmarks for resource-constrained platforms, along with a formal threat model that addresses implicit flows, the benevolent developer problem, and the behavior of a distributed ledger under degraded network conditions. Finally, we conduct a formal verification of our model using the P framework. Full article

As the scale of renewable energy integration continues to expand, the uncertainty and variability of power system operation has increased. Meanwhile, peak regulation resources have become increasingly diverse, making the formation of peak regulation costs more complex. Existing allocation mechanisms therefore have difficulty directly linking the temporal power profile of each entity to its contribution to the optimized deep peak regulation cost and the corresponding cost responsibility. This paper applies the standard Shapley value framework to deep peak regulation cost allocation involving multiple peak regulation demand entities. An energy-preserving substitute scenario method is applied to heterogeneous demand entities. The actual profiles of coalition members are retained, whereas the profiles of nonmembers are replaced by their mean values, thereby removing temporal fluctuations while preserving total energy over the dispatch horizon. For each coalition-specific net load scenario, a dispatch optimization model considering the piecewise deep regulation capability of thermal units and the intertemporal constraints of pumped storage are re-solved, and the resulting minimum cost is used to construct the coalition cost function. The signed Shapley value is then used to calculate the average marginal cost effect of each entity across all coalitions, after which a practical positive contribution settlement rule converts the signed values into nonnegative and budget-balanced charges. A provincial system case study shows that, compared with energy proportional and peak power proportional allocation, the proposed method explicitly accounts for the temporal characteristics and interactions of heterogeneous power profiles and links them to changes in the optimized deep peak regulation cost through coalition-specific re-optimization. Full article