Abstract: Background/Objectives: Artificial intelligence (AI) tools for periodontal diagnosis are proliferating, yet little is known about what clinicians and patients in Central Asia expect from such systems. We elicited requirements for an AI-enabled periodontal decision-support system from three stakeholder groups in Kazakhstan and examined which patient-reported risk factors are associated with self-reported signs of periodontal disease. Methods: A cross-sectional online survey (July–September 2026) enrolled 33 dentists, 91 primary health care (PHC) physicians and medical specialists, and 455 patients with periodontal disease. Proportions were reported with Wilson 95% confidence intervals (CI); groups were compared with Fisher’s exact, χ², Mann–Whitney and Kruskal–Wallis tests with effect sizes; multivariable logistic regression identified factors associated with self-reported periodontal signs. Results: Dentists prioritised automation of history-taking (81.8%) and visual gingival assessment (72.7%), and named early gingivitis diagnosis as the stage where AI is most needed (69.7%). Only human-controlled autonomy levels were chosen; the most frequently cited barrier was the absence of a legal framework and liability insurance (60.6%), and dentists with >5 years of experience more often demanded mandatory verification or a prohibition of full autonomy (exact p = 0.045; Cramér’s V = 0.54). PHC physicians considered early gingivitis screening their most effective contribution (80.2%) but cited insufficient competence as the main barrier (53.8%). Self-reported periodontal signs were present in 49.0% of patients and were independently associated with high stress (adjusted odds ratio 2.11; 95% CI 1.14–3.89) and a positive family history (1.61; 1.02–2.55); six symptom items did not form a reliable scale (Cronbach’s α = 0.56). Conclusions: Stakeholders in Kazakhstan favour a low-autonomy, clinician-verified AI system focused on early gingivitis detection, interprofessional data sharing and clearly regulated accountability. These requirements provide an evidence base for the design and governance of periodontal AI in emerging health systems.

Abstract: Maintaining coherent agentic work becomes an architectural challenge as information, participants, commitments, execution components, and operating conditions change. This paper proposes Agentic AI 2.0, a system-level architectural framework that integrates established concepts to organize ongoing goal-directed work in foundation-model-based systems. Six constitutive properties characterize this organization: Maintained Process State, Collective Coordination, Shared Operational Knowledge, Governed and Grounded Action, Computational Continuity, and Feedback-Driven Adaptation. The framework connects these properties to role-bearing agents, shared operational objects, interface contracts, and interacting execution, coordination, and adaptation loops. A composition guard specifies how local acceptance decisions connect across operational boundaries, while a criterion-level codebook supports configuration-specific assessment from explicit evidence. We examine the framework through a constructed production-order trace, disruption and handoff branches, counterexamples, and static source profiles of three application configurations and one infrastructure boundary case. The analyses distinguish local feasibility from joint commitments, effect reconciliation from execution-right control, and retained skill versions from governed activation and reuse. They also separate scoped negative evidence from unresolved evidence when diagnosing architectural relationships. Candidate evaluation and later reuse remain conditional in the worked example. Prospective profiles for enterprise productivity, adaptive manufacturing, and distributed mobility identify domain-specific evidence needs and evaluation priorities. The contribution is a traceable basis for architectural analysis, comparison, and design. Independent assessor studies, comparative diagnosis, and controlled and longitudinal implementation studies are needed to establish its practical value and the relationship between architectural choices, operational outcomes, and cost.

Abstract: Background/Objectives: New data on the pathogenesis of recurrent urinary tract infections (rUTIs) and the growing level of bacterial resistance to antibiotics require a revision of patient treatment strategies and a search for non-antibiotic approaches to the treatment and prevention of UTIs. The aim of this study was to investigate the clinical and microbiological efficacy of a new, non-traditional antibacterial drug, Fluorothiazinone (FT). Methods: We conducted an open-label, randomized, multicenter cohort clinical trial, phase III, at 12 hospitals in Moscow and St. Petersburg. 280 patients were randomized into two groups in a 1:1 ratio to receive FT at a dose of 1200 mg/day for 14 days or furadoninat a dose of 400 mg/day for 7 days. Clinical and microbiological cure were assessed 7, 14 and 28 days after the start of therapy. Results: For the primary efficacy end-point, clinical cure at day 28, the recovery rate was 91.7% in patients receiving FT and 92.8% in patients receiving furadonin, the hypothesis of non-inferiority of FT compared to the standard furadonin regimen was confirmed by two-sided 95% confidence intervals. The proportion of patients with clinical cure on days 7 and 14 also did not differ in the two groups. An assessment of microbiological eradication at all observation times in our study demonstrated that FT, whose mechanism of action is associated with the suppression of pathogen virulence, possesses antibacterial activity comparable to that of the antibiotic furadonin leading to the eradication of pathogens causing rUTIs. The frequency of microbiological relapses after 28 days of treatment was 19.6% in the group receiving FT and 22.2% in the group receiving furadonin. Both study groups were comparable in the severity of adverse events (AEs). A definite relationship with the study drugs was identified for 1 (11.1%) AEs after taking FT and 8 (88.9%) AEs after taking furadonin.Conclusions: Clinical trials in patients with recurrent cystitis have demonstrated the intrinsic antibacterial activity of FT, equal clinical and microbiological efficacy compared to first-line drugs for the treatment of recurrent cystitis, as well as a high level of safety, indicating the potential for the use of drugs with a new mechanism of action in the context of growing antibiotic resistance.

Abstract: Urban Digital Twins (UDTs) increasingly combine heterogeneous geospatial data, real-time streams, analytics, and artificial intelligence (AI) to support urban governance, yet their reliability depends on how data quality, semantics, provenance, and uncertainty are handled architecturally. This study proposes a prescriptive, technology-agnostic reference architecture for AI-enabled UDT platforms covering GIS, BIM, IoT streams, imagery, and regulatory documents. The architecture combines presentation, logic, persistence, and cross-cutting support layers with reusable patterns for semantic mediation, data-type-specific persistence, spatiotemporal processing, scalable 3D visualisation, and explicit data-quality and provenance control. A four-stage methodology links stakeholder requirements to architectural patterns and validates their operational feasibility using the AQARI national real estate digital twin in Bahrain. The implementation demonstrates integration of spatial, transactional, sensor, 3D, and regulatory data and supports building management and zoning-compliance use cases. Operational tests show sub-second parcel-query response under typical conditions and scalable real-time ingestion. The results indicate that trustworthy AI-enabled UDTs require data-quality controls and interoperability mechanisms to be treated as architectural concerns rather than downstream application tasks. The proposed architecture provides reusable guidance for scalable spatial intelligence and digital-twin deployment, while quantitative uncertainty propagation and independent validation of AI models remain priorities for future work.

Abstract: We study the m-generalized group inverse of Banach elements and establish several new properties. The main result is a novel characterization via the right hybrid (b,c)-inverse, revealing an intrinsic link between the two notions. Additive properties and image-based characterizations are also derived. These results extend the theory of the m-weak group inverse to a broader class of Banach elements and shed new light on infinite-dimensional operators.

Abstract: Enterprise risk management (ERM) and risk governance require organizations to connect risk identification, assessment, monitoring, and response with planning, performance evaluation, accountability, and organizational resilience. This study examines the development and intellectual structure of research at the intersection of ERM, risk governance, management accounting, and management control systems. A bibliometric analysis was conducted on 1,042 Scopus-indexed publications using Bibliometrix, Biblioshiny, and VOSviewer. The findings show sustained growth in the field and identify risk management, management control systems, and performance management as its principal motor theme. Management accounting occupies a central position in the keyword network and is closely connected with risk assessment, enterprise risk management, and performance measurement. However, the literature remains fragmented across risk governance, corporate governance, resilience, and sector-specific applications. The study therefore positions ERM and risk governance as the primary framework and interprets management accounting, control mechanisms, and information systems as enabling infrastructures through which risk information is translated into responsibilities, limits, resource-allocation decisions, corrective action, and organizational learning. The resulting framework clarifies how organizations can embed enterprise and financial risk considerations in established managerial routines rather than treating risk management as a separate reporting exercise.

Abstract: Smart agricultural technologies can improve input efficiency and environmental performance, but their benefits depend on farmers’ knowledge and use. This study assessed knowledge and use of new agricultural technologies among Greek crop farmers, perceptions of sustainable agriculture and environmental impacts, and the usefulness of agricultural education. A cross-sectional survey was conducted from September 2023 to May 2024 among 1,054 crop farmers across all 13 Greek regions using convenience sampling. Pearson’s chi-square tests and Cramer’s V examined associations between technology knowledge and age, education, and agricultural experience. Overall, 56.8% reported knowledge of new technologies, 29.7% reported technologically equipped machinery, and 17.9% reported using such technologies. Knowledge was significantly associated with age (χ²(4) = 64.41, V = 0.249), education (χ²(5) = 204.02, V = 0.444), and experience (χ²(9) = 182.51, V = 0.420; all p < 0.001). Furthermore, 70.1% reported no knowledge of sustainable agriculture, while the perceived usefulness of agricultural education was very high (mean = 4.73/5). The findings indicate a gap between reported technological knowledge and actual use and support practical training in smart machinery, digital skills, environmental protection, and agronomic practices. Given the cross-sectional design, convenience sampling, and self-reported measures, the observed associations should not be interpreted causally.

Abstract: By allowing researchers to study and probe the mechanisms of various biological phenomena, animal models have aided greatly in advancing our understanding of neuroscience. Their continued use for laboratory research, however, has met with ethical hurdles as emerging evidence suggests that many vertebrate and animal species possess cognitive abilities once thought to be exclusive to humans. Buttressing these ethical concerns are the practical limitations of the high cost and protracted time scale of studies reliant on mammals and other vertebrates. These and other limitations have prompted an exploration of potential alternatives that could sustain the advancement of knowledge while also minimizing or preventing animal harm. In this review, we discuss the current state of the field, noting the strengths and weaknesses of the use of various animal models for neuroscience research. We highlight alternative approaches that make use of non-vertebrate models and various technological innovations that permit state-of-the-art investigations in neuroscience while simultaneously limiting the infliction of harm on vertebrate animals.

Abstract: Cultural tourism drives rural revitalization in China, yet traditional villages with comparable heritage resources differ sharply in the number of visitors they attract. Focusing on the single spatial variable of openness, this study examines nine comb-shaped Cantonese villages in the Pearl River Delta, classifies their layouts into typical-comb, curved-comb and mesh-comb types, and builds a three-tier openness evaluation system of ten AHP-weighted indicators covering external accessibility, internal connectivity and public-space configuration. External transportation accessibility dominates the weighting (0.653). Openness correlates strongly with annual tourist volume (r = 0.826, p < 0.01) and explains 63.7% of its variation (adjusted R² = 0.637), whereas layout type alone is not significant (p = 0.238). Mesh-comb villages attain the highest openness (0.683), and typical- and curved-comb villages the lowest. An interval correction coefficient [0.64, 1.285] converts point prediction into interval prediction, absorbing non-spatial influences. For Huitong Village, renovation raised openness from 0.576 to 0.675, and the observed 800,000 visitors fell within the predicted interval, a deviation of only 0.6%. These findings establish openness as a quantifiable predictor of cultural-tourism attractiveness and yield a “limited porosity” strategy for suitability evaluation, scheme comparison and management decisions.

Abstract: The construction of physically realistic analytical solutions of Einstein's field equations remains one of the central problems in relativistic astrophysics. Exact solutions provide important insight into the internal structure, stability, and observable properties of compact stellar objects, including neutron stars, strange quark stars, anisotropic compact stars, and exotic dark-energy-inspired configurations. The Thirukkanesh–Ragel– Malaver (TRM) ansatz has now typically specific mathematical assumption (or metric potential setup) used by within general relativity to find exact, analytical solutions to the Einstein field equations. It is widely used by astrophysicists to model the interior structure of highly dense compact objects, such as strange anisotropic quark stars, neutron stars, and dark energy stars. The TRM approach acts on the radial component of the metric potential. Initially proposed by S. Thirukkanesh and F. C. Ragel (2012) and that was later generalized by Manuel Malaver (2014) who introduced typical adjustable parameter (n) in the metric function, the TRM ansatz serves as an exact mathematical framework for modeling anisotropic stellar interiors, and that has recently gained prominent attention for its ability to explain the incredibly low mass of the compact object within the supernova remnant HESS J1731−347. Discovered by the High Energy Stereoscopic System, HESS J1731−347 contains a compact star whose exceptionally tiny mass has been defying traditional iron-core neutron star formation models. Instead, astrophysicists use the Thirukkanesh–Ragel–Malaver metric ansatz to model the star as a strange quark star. This review shows that the TRM metric potential provides a flexible analytical framework for studying equilibrium configurations as well as physical properties of typically relativistic compact objects.

Abstract: NEAT1 is among the most extensively studied lncRNA, classically recognized as the architectural scaffold of nuclear paraspeckles (PSs), membranelles nuclear bodies that assemble through liquid-liquid phase separation to sequester RNA-binding proteins and edited transcripts. Within this framework, NEAT1 was thought to regulate gene expression mainly indirectly, by trapping essential gene regulatory factors within these condensates. Here, we aim to review growing evidence that reposits NEAT1 from a scaffold to an active, highly context-dependent chromatin regulator that finely con-tribute to genome surveillance and cellular homeostasis. NEAT1 engages chromatin directly by occupying gene regulatory elements and DNA:RNA hybrids, recruiting epigenetic regulators and cooperating with lineage specific transcription factors. We further examine how such a regulatory NEAT1 activity varies across a broad spectrum of cancerous and non-cancerous diseases. The evidence discussed reframe NEAT1 as an adaptor molecule in transcriptional machinery whose function is deeply influenced by cellular stimuli, interacting partners and chromatin targets accessible in each con-text. This conceptual shift not only raises new mechanistic questions but also under-scores the challenges of therapeutically targeting NEAT1.

Abstract: Burned area mapping (BAM) provides essential spatial information for fire monitoring, emissions accounting, and ecological impact assessment, but reported accuracy cannot be interpreted independently of mapping targets, reference data, validation design, and application context. We systematically reviewed 1339 remote sensing BAM studies published from 1999 to 2026 to examine technological advances and the evidence supporting validation, transferability, and downstream use. Existing studies address multiple targets, including burned extent, total burned area, fire perimeter/event, burn date, and fire progression, each of which requires distinct evaluation criteria. High-spatial-resolution data, dense time series, multi-source fusion, and advanced learning methods have expanded mapping capabilities, yet small-fire omission, mixed pixels, cloud and smoke interference, confusion with non-fire agricultural disturbances, reference-data limitations, and long-term nonstationarity remain important sources of error. Most studies emphasize local validation, whereas explicit external-transfer tests are comparatively scarce, and random pixel or patch splits do not demonstrate transfer across fire events, regions, years, or sensors. Evidence that BAM errors alter downstream outcomes is even more limited. BAM reliability should therefore be interpreted in relation to the mapping target, tested conditions, transfer evidence, and task-specific fitness for use rather than a single accuracy metric.

Abstract: Modern jurisprudence faces a foundational crisis where the rejection of transcendent standards reduces justice to subjective preference. While Leo Strauss attempts to rescue modernity from this relativism by recovering classical natural right—relying on a teleological framework and a salutary myth to sustain political order—this paper argues that such a theoretical compromise harbors latent authoritarian potential. By applying Strauss’s framework to Albert Camus’s The Outsider, this analysis demonstrates how the courtroom actualizes the vulnerabilities of natural right. The prosecutor inverts teleology, transforming the salutary myth into a retroactive mechanism for social exclusion and spiritual subjugation, convicting the protagonist not merely for murder, but for refusing to perform conventional moral rituals. To resolve the ensuing normative vacuum without retreating into nihilism, this paper constructs an existentialist jurisprudence grounded in Camus’s concept of rebellion. By transitioning from the isolated absurd to shared human vulnerability (I rebel—therefore we exist), it establishes a horizontal contract. This framework delineates a restrained legal geometry: it provides an immanent justification for punishing physical murder while strictly prohibiting the judicial coercion of an individual’s internal consciousness, condemning the act on the beach without demanding the tear at the funeral.

Abstract: Obstructive sleep apnea (OSA) is a common yet underdiagnosed condition strongly linked to the cardiovascular-kidney-metabolic (CKM) syndrome continuum, a systemic disorder characterized by interconnected metabolic, renal, and cardiovascular abnormalities. Despite overlapping risk factors, particularly obesity, current CKM staging does not formally include OSA as a potential modifier of CKM progression from early stages. Here, we conducted a narrative review revealing that OSA shares demographic and biological substrates with CKM syndrome, independently associates with cardiovascular, metabolic, and renal dysfunction through multiple shared mechanisms, and responds to intervention, including lifestyle changes, positive airway pressure, and pharmacotherapy. Integrating systematic OSA screening and management into CKM assessment, especially at early stages, may enhance risk stratification and enable personalized preventive care. This approach shows potential in mitigating disease progression and improving quality of life across the CKM spectrum. These findings support recognizing OSA as an important factor in CKM progression and highlight the potential benefits of its early identification to mitigate disease burden and improve patient outcomes.

Abstract: This paper examines pedagogical approaches to teaching trademark law with a specific focus on the consumer confusion doctrine as a vehicle for developing legal reasoning skills in law students. The consumer confusion standard, particularly the likelihood of confusion test, represents one of the most complex and multifaceted doctrines in intellectual property law, requiring students to synthesize factual analysis, legal standards, and policy considerations. This paper explores how case-based and experiential learning methodologies can effectively teach the consumer confusion doctrine while simultaneously developing critical legal reasoning skills. Drawing on scholarship in trademark law pedagogy, cognitive theories of legal reasoning, and experiential education, this paper proposes an integrated framework for teaching consumer confusion through landmark cases such as Polaroid Corp. v. Polarad Electronics and AMF Inc. v. Sleekcraft Boats, supplemented by simulations, moot courts, and client counseling exercises. The paper argues that the multifactor tests for likelihood of confusion provide an ideal pedagogical platform for teaching students how to weigh competing factors, apply legal standards to complex facts, and develop sophisticated analytical frameworks. Assessment strategies including formative evaluation, reflective journals, and peer review are discussed as mechanisms for reinforcing learning outcomes. The paper concludes with implications for intellectual property curriculum design and recommendations for integrating consumer confusion doctrine throughout the law school experience.

Abstract: Isopentenyl diphosphate isomerase (IPPI) is a key enzyme catalyzing the interconversion between isopentenyl pyrophosphate (IPP) and dimethylallyl pyrophosphate (DMAPP), two isoprenyl C5 units that are precursors for terpenoid biosynthesis. Previous study has identified two IPPIs, namely AaIPPI1 and AaIPPI2 from Artemisia annua, and revealed the positive role of AaIPPI1 in regulating the biosynthesis of terpenoids. However, the role of AaIPPI2 in regulating terpenoid biosynthesis remains to be clarified. In this study, we explored the contribution of AaIPPI2 to terpenoid biosynthesis in Artemisia annua. Overexpression of AaIPPI2 in A. annua significantly enhanced the contents of diverse monoterpenes and sesquiterpenes. Suppression of AaIPPI2 by RNA interference (RNAi) in A. annua markedly reduced the biosynthesis of these sesquiterpenes, but only caused a modest decrease in several monoterpenes’ levels with no change in other monoterpenes’ levels, suggesting that AaIPPI2 plays a lesser part in the regulation of monoterpenes biosynthesis in plastids compared to AaIPPI1. Taken together, these results demonstrate that AaIPPI2 plays a positive role in regulating the biosynthesis of terpenoids. Our findings enhanced the understanding of the distinction between the roles of the two IPPIs in the regulation of terpenoid biosynthesis in A. annua and provided candidate genes for optimizing terpene production in plants.

Abstract: Soil salinity is a major abiotic constraint that severely limits crop production, whereas beneficial legume-rhizobia symbioses can alleviate stress effects and enhance crop yield performance. In this study, pre isolated Rhizobium phaseoli R9 and Mesorhizobium ciceri R6 strains were evaluated individually and in co inoculation on common bean (Phaseolus vulgaris L.) grown in saline soils (5.6 dS m⁻¹). The experiment was established using a randomized complete block design (RCBD) with three replications at the Experimental Station of the Institute of Agriculture and Agrotechnologies of Karakalpakstan during the 2024–2025 growing seasons. Bacterial inoculations showed potential to increase plant height, root and shoot biomass, grain yield, number of nodules per plant, nodule dry weight, and root length of common bean. Co-inoculation was particularly effective, increasing the dry weights of shoot, root, leaf, grain, and husk by 47.6%, 28.0%, 32.1%, 39.6%, and 22.2%, respectively, compared with the control. Likewise, the highest grain yield (1.85 Mg ha⁻¹) was produced under co inoculation, exhibiting a 44.5% increase compared with the uninoculated control. Chemical analysis showed that co inoculation (R6+R9) increased oil and protein content by 18.2% and 27.4%, respectively, over the control. The results show a strong correlation (R2=0.89) between increased nodule weight and common bean grain yield. The application of biological interventions markedly improved multiple indicators of soil fertility and biological activity, with the R6 + R9 co-inoculation treatment producing the highest concentrations of humus (0.85 g kg⁻¹), total N (1.05 g kg⁻¹), total P (1.15 g kg⁻¹), nitrate-N (6.72 mg kg⁻¹), available P₂O₅ (46.0 mg kg⁻¹), and exchangeable K₂O (180 mg kg⁻¹) compared with the control. It might be concluded that co-inoculation of Rhizobium strains could be the most effective nature-based solutions strategy for enhancing agricultural productivity and ecosystem restoration under saline conditions.

Abstract: How far can reservoir operation displace a river's calendar? We address the question with 92 years of monthly discharge on the Naryn, the transboundary artery of the Syr Darya basin, together with 46 years of release data and two years of daily reservoir balances. Annual flow shows no trend, yet the centre of timing of flow moved from late June to mid January, a displacement of 165 days (bootstrap 95% interval 158 to 173) that inverts the hydrograph and far exceeds the week-scale timing shifts reported for climate-driven change. A phase and concentration decomposition separates this rotation from an earlier flattening; change points near 1986, 1990 and 1994, confirmed by independent segmentation methods, coincide with the documented transition from irrigation-oriented to energy-oriented operation. Roughly 4.8 km³ per year (4.0 to 5.6) now arrives outside the growing season. The evidence identifies reservoir operation as the dominant driver of the inversion and quantifies the seasonal redistribution at the centre of a thirty year allocation dispute.

Abstract: Ibuprofen is among the most widely consumed non-steroidal anti-inflammatory drugs and is frequently detected in wastewater treatment effluents, is not efficiently removed by conventional biological processes. In this study, a physicochemical treatment train−acidification, homogeneous Fenton oxidation, neutralization, iron oxidation/precipitation, and solid-liquid separation−was simulated in Aspen Plus for ibuprofen degradation (150 mg/L; COD 385 mg/L; TOC 114 mg/L) at a design flow of 2.08 m³/h. The Fenton reactor (CSTR, ≈2.08 m³, 1 h residence time) operated at pH 3, following third-order power law kinetics with a rate constant of 1.1×10⁶ m⁶/(kmol²-s) and an activation energy of 56.5 kJ/mol. At the design point (Fe²⁺:H₂O₂≈1:2.4). The model predicted 85.99% ibuprofen removal alongside 46.8% COD and 39.6% TOC removal (mass-load basis), with H₂O₂ consumed almost completely; a higher-dose scenario (≈1:10) was evaluated for comparison. The effluent’s BOD5/COD ratio (≈0.50) reflects a residual dominated by benzoic acid, a partial-oxidation by-product indicating incomplete mineralization. Residual dissolved iron was oxidized with air and precipitated as ferric hydroxide before separation, and the simulated reagent operating cost was 0.62 USD/m³ of treated effluent. These findings demonstrate that Aspen Plus provides a reliable framework for simulating Fenton-based ibuprofen degradation together with downstream iron management and preliminary process economics.

Abstract: Complexity science has proposed many measures of complexity, structure, information, emergence and (self-)organisation, often in isolation and without systematic understanding of their relationships, redundancies or distinct properties. As new measures continue to appear, comparative assessment is increasingly needed. Here, we systematically compare classical and recent complexity measures, characterising their relationships and sensitivities in discriminating the qualitative behaviour of discrete and continuous dynamical systems. The primary analysis used an initial 11-system benchmark comprising four elementary cellular automata, Lorenz dynamics, Mandelbrot and Julia fractals, three Boolean-network topologies, and a yeast association network. Across the binarization threshold sweep, Block-level Algorithmic Information Dynamics (AID) (\( |\Delta\mathrm{BDM}| \)) preserved cross-system rankings with mean Spearman agreement 0.881 (95\% CI, 0.848--0.910), \( \mathrm{ICC}(3,1)=0.893 \), and Kendall's \( W=0.894 \). Independent validation comprised a five-regime ladder spanning trivial/ordered, periodic/ordered, critical, chaotic, and maximally random dynamics, together with a continuous logistic-map sweep. In the categorical analysis, 2-D cell and block AID ranked first and second, respectively, in the task-specific composite combining categorical discrimination, Lyapunov tracking, and assigned perturbation capability. Post-hoc, 1-D BDM and Epiplexity separated critical from chaotic dynamics. Epiplexity and expiplexity-derived coding statistics did not distinguish chaotic from maximally random endpoints, whereas AID additionally retained signed, localised, multiscale intervention effects. Sequential structural epiplexity \( S_T \) separated validation categories (\( \epsilon_H^2=0.626 \), 95\% interval 0.515--0.782), with a much lower point separation effect size than Cell and Block AID (BDM perturbation). We develop a proposed characterisation of Epiplexity as a functional over an AID information landscape, making explicit the sufficiency assumptions needed to identify it with the original bounded-MDL definition. Thus, CTM/BDM provide estimators of algorithmic information, AID provides the perturbational calculus, and explicitly constructed scalar observables project selected aspects of that landscape.