Search Results (131)

This paper develops a rigorous mathematical and computational framework for four-dimensional chess defined on the discrete hypercubic lattice $\{1,\dots , 8{\}}^4$. We formalize piece movement using displacement sets in ${\mathbb{Z}}^4$, define adjacency via the Chebyshev metric, and analyze the resulting move graphs for rooks, bishops, knights, queens, and kings. We establish exact mobility formulas, parity invariants, and connectivity properties, consolidating known product-graph results for rooks and kings while introducing a boundary-sensitive analysis of the four-dimensional knight verified by exhaustive enumeration. The mathematical framework is complemented by a fully implemented 4D chess engine and interactive visualization environment rendering all 64 (z,w)-slices of the hypercube simultaneously. The system supports full move legality, generalized special rules, multi-king checkmate detection, and reproducible state enumeration. Performance measurements and exploratory branching-factor estimates are obtained through reproducible random playouts using the publicly available implementation. We contextualize this ruleset within existing work on move graphs on ${\mathbb{Z}}_n^m$, higher-dimensional leapers, spectral properties of grid graphs, toroidal analogs, and multidimensional visualization. Exploratory qualitative feedback (N = 18) is included to examine whether the visualization design is interpretable and navigable in practice, providing feasibility-oriented observations on how slice-based 4D projection and layered board rendering are perceived by non-expert users in an exploratory context. Together, the mathematical results, implemented engine, and visualization form a coherent foundation for the study of strategy, complexity, and human interaction in four-dimensional game systems. The framework provides a basis for future investigations into spectral analysis of move graphs, symmetry-aware search, hierarchical planning, and educational applications in high-dimensional geometry. Full article

The energy transition represents a complex, multi-level system subject to profound uncertainty and recurrent shocks. Current policy design approaches predominantly rely on static optimization frameworks (centralized, calculative models that presume stable conditions and predictable technological trajectories). Yet evidence from the 2021–2023 energy crisis in Europe, coupled with structural challenges in market liberalization and renewable integration, demonstrates persistent challenges in policy implementation. Price interventions affect competitive dynamics; subsidies influence technology selection; capacity mechanisms create coordination tensions; and rigid tariff structures create misalignments with evolving grid needs. This paper argues that these recurrent policy tensions stem not from implementation gaps, but from an inadequate theoretical foundation: the treatment of energy systems as optimizable rather than as complex, adaptive systems operating under Knight–Mises uncertainty and Huerta de Soto dynamic efficiency. This work explores an alternative framework grounded in dynamic efficiency, complex–uncertain systems, decentralized incentives, and adaptive governance (international–domestic, public–private, etc.). This review uses the theoretical and methodological framework of the Heterodox Synthesis, an alternative to the Neoclassical Synthesis. There is a reinterpretation of some insights from Knight and Mises (uncertainty), Hayek (distributed knowledge), Huerta de Soto (dynamic efficiency) and contemporary complexity economics into operational criteria applicable to energy policy design: (1) robustness to deep uncertainty; (2) preservation of price signals and risk-bearing mechanisms; (3) alignment of incentives across distributed actors; (4) institutional adaptability; and (5) minimization of ex post policy corrections. Through illustrative application to four critical policy instruments (price caps, renewable subsidies, capacity mechanisms, and network tariff design), it is shown how this framework identifies systematic tensions and consequences that conventional analysis overlooks. The contribution is exploratory in a bootstrap way: theoretical, by integrating classical and contemporary economics into energy governance; methodological, by operationalizing dynamic efficiency into evaluable criteria distinct from existing adaptive governance frameworks; and sectorial, by providing policymakers and regulators with diagnostic tools for assessing design robustness in conditions of deep uncertainty and rapid transition. According to this review, improved energy policy design under uncertainty is not achieved through more sophisticated optimization (in a calculative way), but through institutional architectures that preserve creative and adaptive learning, maintain distributed decision-making capacity, and remain functional when assumptions prove incorrect or not well-known. Full article

This essay examines William Makepeace Thackeray’s Vanity Fair (1847–48) through the lens of nineteenth-century Anglican Evangelicalism, arguing that Thackeray’s portrayal of Pitt Crawley (Junior) crystallizes the paradoxes of Evangelical reform culture in early Victorian Britain. Building on the critical foundations laid by Elisabeth Jay, Mark Knight, and Catherine Hall, the study situates Pitt within the historical context of Evangelical social reform, moral discipline, and political conservatism. Through close examination of Pitt Crawley’s domestic reforms at Queen’s Crawley and his engagement in politics, it demonstrates how Thackeray appropriates Evangelical ideals—domestic propriety, moral earnestness, and reformist zeal—only to expose their susceptibility to self-interest and hypocrisy. In exploring Pitt’s political ascent and eventual collapse following the 1832 Reform Act, the essay further interprets his career as an allegory for the decline of the Evangelical Tory aristocracy amid the rise of bourgeois liberalism. As a disillusioned Evangelical, Thackeray renders Vanity Fair not simply a critique of religious hypocrisy but a meditation on the limits of moral reform in a self-interested age. Full article

During the years of the so-called Trente Glorieuses (1945–1975), with its economic recovery after World War II, France witnessed the development of a technologized consumer society and a technocratic approach to public planning, which fostered a futuristic outlook and a boom in paperback publishing. A major success story of this era was the Éditions Fleuve Noir science-fiction series, Anticipation, to which popular genre author Maurice Limat contributed numerous novels. Although marketed as science fiction and set far in the future and in outer space, Limat’s novels featuring the Chevalier Bruno Coqdor resemble more often those of a knight-errant from medieval romance. These works of space fantasy express medieval nostalgia but also engage the massive social changes occurring in France during this period while extrapolating France’s survival in the distant future. Full article

Since Reynolds’ work, turbulence has been one of the most important subjects in fluid dynamics. Although its complete understanding seems still out of reach, there is at least one established physical basis that turbulence is a phenomenon of a random but non-trivially correlated assembly of vortices. The knowledge of vortices has thus become a prerequisite for promoting our understanding of the nature of turbulence. In this article, we first review the simple, compact vortex solutions to the Navier–Stokes equations for incompressible viscous fluids and a unified view of a certain type of vortices including Burgers, Sullivan and Bellamy-Knights solutions. The non-equivalence of the inviscid limit of the Navier–Stokes equations and the Euler equations is emphasized. Introducing the notion of observational non-uniqueness, which differs from the non-uniqueness in a certain class of differential equations, of solutions to the Navier–Stokes equations, the observation problem associated with the dense distribution of non-equivalent solutions is argued. The origin of the extreme sensitivity of the solutions to the boundary conditions is clarified. A few examples of vortex phenomena in the real world are also surveyed. We next review the works of constructing turbulence as a random assembly of simple, compact vortices. An attempt to combine the vortex model of turbulence with the Kármán–Howarth equation for the velocity correlation functions of anisotropic turbulence is presented. It is pointed out that the studies in this direction suggested that Kolmogorov’s 2/3 scaling law was generally compatible with anisotropy. A few quantities are proposed as candidates to measure anisotropy in turbulence experiments. Full article

Uncertainty-aware decision-making increasingly relies on multimodal sensing pipelines that must fuse correlated measurements, propagate uncertainty, and trigger reliable control actions. This study develops a unified mathematical framework for multimodal data fusion and Bayesian decision-making under uncertainty. The approach integrates adaptive Covariance Intersection (aCI) for correlation-robust sensor fusion, a Gaussian state–space backbone with Kalman filtering, heteroskedastic Bayesian regression with full posterior sampling via an affine-invariant MCMC sampler, and a Bayesian likelihood-ratio test (LRT) coupled to a risk-sensitive proportional–derivative (PD) control law. Theoretical guarantees are provided by bounding the state covariance under stability conditions, establishing convexity of the aCI weight optimization on the simplex, and deriving a Bayes-risk-optimal decision threshold for the LRT under symmetric Gaussian likelihoods. A proof-of-concept agro-environmental decision-support application is considered, where heterogeneous data streams (IoT soil sensors, meteorological stations, and drone-derived vegetation indices) are fused to generate early-warning alarms for crop stress and to adapt irrigation and fertilization inputs. The proposed pipeline reduces predictive variance and sharpens posterior credible intervals (up to 34% narrower 95% intervals and 44% lower NLL/Brier score under heteroskedastic modeling), while a Bayesian uncertainty-aware controller achieves 14.2% lower water usage and 35.5% fewer false stress alarms compared to a rule-based strategy. The framework is mathematically grounded yet domain-independent, providing a probabilistic pipeline that propagates uncertainty from raw multimodal data to operational control actions, and can be transferred beyond agriculture to robotics, signal processing, and environmental monitoring applications. Full article

The mining industry faces the critical challenge of balancing economic profitability with environmental responsibility. Traditional mine planning models often prioritise financial gains, particularly Net Present Value (NPV), while placing less emphasis on environmental impacts, such as carbon emissions. This research presents a comprehensive multi-objective optimisation model for production scheduling in sublevel stoping operations. The model simultaneously aims to maximise NPV and minimise carbon emissions, providing a more sustainable framework for decision-making. The carbon emission objective comprehensively accounts for energy consumption across all key mining activities, including drilling, blasting, ventilation, transportation, crushing, and backfilling, using a “top-down” accounting method. The multi-objective problem is solved using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), which generates a set of Pareto-optimal solutions representing the trade-off between the two conflicting goals. The model is applied to a conceptual copper deposit with 200 stopes. The results demonstrate a clear trade-off: schedules with higher NPV inevitably lead to higher carbon emissions, and vice versa. For instance, one solution yields a high NPV of $312.94 million but with 23,602 tonnes of CO₂ emissions. In contrast, another, more environmentally friendly solution reduces emissions by 26.5% to 18,647 tonnes, resulting in only a 1.21% reduction in NPV. This research concludes that integrating environmental objectives into mine planning is not only feasible but essential for promoting sustainable mining practices, offering a practical tool for operators to make informed, balanced decisions. Full article

This essay follows the shifting interpretations of Don Quixote from Enlightenment satire to romantic idealism, Nietzschean self-mythmaking, and Camus’s absurdism, to track the growth of a tension between truth and meaning. While Enlightenment readers saw Cervantes’ knight as a pitiable fool at odds with reality, early German romantics recast him as a noble idealist resisting a fact-bound, spiritually thinned modernity. Nietzsche, both engaging with and departing from these romantic views, made Quixote both a warning about cruel disillusionment and a model for life-affirming self-creation—a “self-aware Quixotism” that turns fable into reality. Camus distilled this tradition into two absurd archetypes: La Palisse, embodying meaningless lucidity, and Don Quixote, embracing meaningful illusion. Doubting reconciliation, he urged a modest balance between evidence and lyricism. Today, with scientific lucidity racing ahead and meaning fracturing into curated feeds, the tension between romantic meaning-making and Enlightenment truth-telling endures. Confronting it without surrendering either reality or wonder remains a central philosophical challenge. Full article

This study presents a paleopathological analysis of individual T4.2 from the archaeological site of the castle of Zorita de los Canes (Guadalajara, Spain). The individual exhibits ultradolichocephaly and was dated between the 13th and 15th centuries. Based on the context, the individual could have been a member of the military–religious Order of Calatrava. Standard bioanthropological and paleopathological methods were applied. The results indicate a male aged between 45 and 49 years with a maximum cranial length and width of 230 mm and 122 mm, respectively. The cranial index (53%) allows him to be classified as ultradolichocephalic. The remains present craniosynostosis at the sagittal, squamosal and sphenofrontal sutures, together with underdevelopment of the skull base width and a dolichognathic mandible with the possible presence of type III prognathism. The left hemimandible and hemimaxilla display a large amount of tartar covering the occlusal, labial and lingual areas of the teeth completely. The right hemimandible and hemimaxilla exhibit almost no tartar, and some teeth were lost in vivo. In addition, two stab wounds—to the external occipital protuberance and to the left temple—as well as a contused injury in the left tibia, can be observed without evidence of bone remodeling. Differential diagnosis indicates a case consistent with Crouzon syndrome. This individual is of particular significance because he was a possibly knight of the Order of Calatrava who presents a syndromic craniosynostosis consistent with Crouzon syndrome and exhibits lesions, which may suggest that he could have died in battle. Full article

Background/Objectives: Liver cancer is an exceedingly heterogeneous malignancy with high mortality rates, and despite extensive research, there have been no significant improvements in treatment outcomes. In the process of navigating the complex landscape of liver cancer, AI has arisen as the “knight in shining armour”, sparking hope and offering invaluable insight into early detection, diagnosis, staging, treatment selection, and post-treatment surveillance. By integrating imaging, clinical, pathological, and molecular data, AI emerges as a transformative tool that offers unique opportunities to enhance patient care. Methods: A comprehensive literature search of PubMed and Scopus, was conducted using the terms “artificial intelligence,” “machine learning,” “deep learning,” “radiomics,” and “liver cancer.” Eligible studies included peer-reviewed original research applying AI to detection, diagnosis, prognosis, treatment planning, or surveillance of liver cancer. Key findings are organized along the clinical continuum. Results: Imaging-based AI models for tumor detection were the most advanced, with several achieving diagnostic accuracy above 90% in retrospective studies. Applications for treatment decision-making are emerging, but most remain at proof-of-concept stages. Generally, few of these innovations have progressed to large-scale clinical trials or received regulatory approval, slowing their integration into clinical practice. Conclusions: This narrative review highlights AI’s potential to transform liver cancer management and addresses the ethical, regulatory, and logistical barriers to its clinical adoption, serving as a call to action for integrating AI into practice to improve patient outcomes. Full article

This paper presents a mathematical modeling and numerical analysis of fluid-thermal processes in a two-stage steam turbine cascade, focusing on the application and comparative assessment of turbulence models in computational fluid dynamics (CFD) simulations. Using the finite volume method implemented in the ANSYS CFX-Task Flow (ANSYS CFX 2022 R2) workflow, the study investigates the performance of standard k-ε, k-ω, and SST turbulence models in predicting flow structures, pressure fields, and velocity distributions within the turbine flow passages. The governing equations, including the Reynolds-Averaged Navier–Stokes (RANS) equations and associated energy and constitutive relations, are solved in conservative form under compressible flow conditions. Experimental data from turbine tests performed at the Institute of Fluid Machinery at Lodz University of Technology are used for validation. Results demonstrate that turbulence modeling significantly influences the accuracy of predicted flow phenomena. The study identifies strengths and limitations of the models in capturing complex three-dimensional flow structures and provides quantitative error margins and practical guidance for their application in industrial turbine flow simulations. Full article

This paper examines the impact of symmetry and asymmetry on the dynamic modeling and nonlinear control of a mobile robot with Ackermann steering geometry. A neural network-based residual model is incorporated as a novel control enhancement. This study presents a control-oriented formulation that addresses both idealized symmetric dynamics and real-world asymmetric behaviors caused by actuator imperfections, tire slip, and environmental variability. Using the Euler–Lagrange formalism, the robot’s dynamic equations are derived, and a modular simulation framework is implemented in MATLAB/Simulink R2022a, that incorporates distinct steering and propulsion subsystems. Symmetric elements, such as the structure of the inertia matrix and kinematic constraints, are contrasted with asymmetries introduced through actuator lag, unequal tire stiffness, and nonlinear friction. A residual neural network term is introduced to capture unmodeled dynamics and improve the robustness. The simulation results show that the control strategy, originally developed under symmetric assumptions, remains effective when adapted to systems exhibiting asymmetry, such as actuator delays and tire slip. Explicitly modeling these asymmetries enhances the precision of trajectory tracking and the overall system robustness, particularly in scenarios involving varied terrain and obstacle-rich environments. Full article

This article reports the findings of an ethnographic and historical study into an ultras group called Melbourne Croatia Fans (MCF), a group of mostly Croatian–Australian young men in their twenties who support Melbourne Knights (formerly known as Melbourne Croatia) in the second-tier Victorian Premier League competition. The aim is to explore identity formation and negotiation, and how identity formation informs relations with outsider groups. The interviews with the football club president, football club secretary, two MCF leaders, and the participant observation date back to the 2010–12 period. The supporters perceive that the club has fallen on hard times for reasons not of their own making. They participated in the former National Soccer League (NSL) (1977–2004) from 1984 to 2004, which was the first-ever national competition in Australia to involve club rather than state teams. However, the club was effectively banned from the new A-League (2005–present), which began based on a private-equity ownership model and a one-team-one-city concept. Despite this, the club can play in the annual knockout competition, the Australia Cup (formerly the FFA Cup), that features both A-League and lower-league teams. We observe here a group of young Croatian–Australian men, part of the Diaspora of Croatians that left the country, mostly in the communist era and afterwards, who aim to construct workable hybrid identities for themselves in an Anglo-majority nation on the other side of the world. They fight on two fronts—against an Anglo, corporate-style administration that effectively bans their club for reasons of ethnicity from the new national league, and against the Serbian youth who often live in the who live in adjacent or nearby suburbs and follow Serbian-origin clubs. Full article

Honey is recognized as a nutritionally rich and functional option, often used as a natural sweetener due to its content of glucose, fructose, vitamins, minerals, enzymes and antioxidants. Its antioxidant, antibacterial and anti-inflammatory properties are well known. Recently, interest has grown in functional honey enriched with bioactive plant components, such as extracts of rosemary, lavender, oregano, and sage, which can enhance phenolic content and antioxidant capacity. However, such enrichment may alter honey’s sensory characteristics and introduce contaminants, including heavy metals, necessitating comprehensive quality assessment. This study aimed to evaluate the chemical and functional quality of honey enriched with aromatic plant extracts from Kosovo, Albania, and North Macedonia, using an integrated approach. The research included the quantification of total phenolic compounds (TPCs), analysis of heavy metal content, and the application of near-infrared (NIR) spectroscopy with two devices (laboratory and portable). The results showed that geographical origin and herbal additions significantly affect TPC and heavy metal concentrations. Honey from Kosovo had the highest TPC, while Albanian honey showed higher concentrations of iron and nickel. Enrichment with oregano and rosemary significantly increased TPC and, levels of heavy metals such as lead and nickel. These findings underscore both the nutritional potential and safety considerations of enriched honey products. Accurate, non-destructive techniques like NIR spectroscopy offer valuable tools for quality control; however, further work is needed to evaluate sensory acceptance and long-term safety of enriched honey. Full article

Background and Objectives: Congenital abnormalities are a leading cause of neonatal morbidity and mortality and are frequently detectable through prenatal ultrasound. While widely implemented in high-income countries, such screening remains inconsistently applied in low- and middle-income regions. This study aimed to estimate the prevalence of congenital abnormalities identified via prenatal ultrasound in Lebanon and to explore associated maternal, obstetric, and psychosocial factors. Methods: A multicenter retrospective observational study, supplemented by follow-up interviews, was conducted in five Order of Malta medical centers. Pregnant women in their second trimester underwent an obstetric ultrasound, and data were collected through structured questionnaires and follow-up phone interviews. Variables included maternal demographics, obstetric history, anxiety levels (GAD-7 scores), and ultrasound findings. Results: A total of 426 pregnant women were enrolled (mean age: 28.8 ± 5.9 years). The overall prevalence of congenital abnormalities was 13.1%. Growth abnormalities were observed in 8.5% of fetuses and were significantly associated with obstetric complications and the presence of multiple abnormalities. Morphological malformations were found in 10.1% of cases and were more common among women of advanced maternal age, those with a history of anomalies, and those reporting elevated anxiety scores. Combined abnormalities, as well as growth and morphological malformations, were significantly associated with higher parity, prior anomalies, and current pregnancy complications. Conclusions: Prenatal ultrasound is essential for early detection of congenital abnormalities, facilitating timely intervention and improved neonatal outcomes. These findings emphasize the need to integrate systematic screening into prenatal care in Lebanon and for ongoing research to identify context-specific risk factors. Full article