Abstract: Greenhushing—the deliberate under-communication of genuine sustainability achievements —has been examined almost exclusively from an organizational standpoint, leaving the consumer side of the phenomenon largely undertheorized. This study investigates how perceived greenhushing, defined as a consumer’s perception that a brand deliberately withholds information about its environmental performance, affects young consumers’ green purchase intention. Drawing on signaling theory, trust–commitment theory and attribution theory, a model is developed in which brand trust, perceived risk and consumer green skepticism jointly mediate the relationship between perceived greenhushing and green purchase intention, while environmental concern and trait-level green skepticism are positioned as moderators. The model is estimated with partial least squares structural equation modeling (PLS-SEM) on a sample of 404 young consumers in Vietnam. Perceived greenhushing significantly erodes brand trust (β = −0.535), elevates perceived risk (β = 0.571) and activates consumer green skepticism (β = 0.477). Among the three mediators, brand trust is the dominant pathway to green purchase intention (β = 0.444), whereas the skepticism pathway is non-significant (p = 0.093). The direct effect of perceived greenhushing on green purchase intention remains negative and significant (β = −0.152), indicating partial mediation. The findings extend signaling theory to the under-studied domain of communicative absence, sharpen the conceptual boundary between greenwashing and greenhushing at the consumer level, and offer specific guidance for sustainability communication in emerging-market consumer settings.

Abstract: The inefficient management of agro-industrial residues, particularly cocoa pod husk and mucilage, represents a critical environmental and economic challenge in cocoa-producing regions such as Santander and Norte de Santander, Colombia. These by-products, constituting approximately 70% of the fruit’s total weight, are currently underutilized, generating pollution and wasting resources with high valorization potential. This article proposes the design and rigorous experimental validation of an empirical model based on artificial intelligence capable of predicting quantities of valuable compounds, including bioethanol, essential oils, paraffins, antioxidants, and pectins, obtained from cocoa residues. The model integrates critical variables such as cocoa variety, extraction methods, and process conditions, incorporating advanced machine learning techniques trained on a 100% empirical database of eighty-four (84) laboratory trials, combined with a post-inference sensitivity analysis via the Monte Carlo method with 10,000 simulations. Preliminary results demonstrate significant varietal differences; for instance, the CCN-51 variety achieves a mean bioethanol yield of 79.30 ± 4.96 mL/kg with a 95% confidence interval of (69.44–88.93) mL/kg, while the Criollo variety reaches 43.55 ± 2.72 mL/kg (38.14–48.84 mL/kg), both exhibiting identical coefficients of variation (6.25%). Furthermore, the integration of an optimized extraction sequence combined with neural networks allows for maximizing by-product yields while reducing final residue generation by 40%. This tool not only contributes to the circular economy and alignment with the Sustainable Development Goals (SDGs 9 and 12) but also offers a tangible pathway to improve the competitiveness of the Colombian cocoa industry through data-driven decision-making and sustainable technology adoption.

Abstract: Fifteen blue-and-white Chinese porcelain sherds dated from the seventeenth to nineteenth centuries, from Jingdezhen, Anxi, and Dehua kilns, were analysed and compared with fragments recovered from the Santana Convent in Lisbon. This work focuses on the identification of cobalt pigment sources, glaze technology and microstructural features for provenance assessment. Sherds were studied using several non-invasive spectroscopies, namely micro-Raman, X-Ray Photoelectron spectroscopy (XPS), X-Ray Fluorescence (XRF) and Ground State Diffuse Reflectance (GSDR). The mineralogical characterization of the ceramic bodies was performed with the use of the X-ray diffraction technique (XRD) and stereomicroscopy (SM). The GSDR absorption spectra of the dark blue and light blue glazes are in most cases quite different. These spectra, together with the XPS studies point to different forms of cobalt ions emplacement in the surface glassy structure of the glaze, or to the use of different pigments to obtain the dark or the light blues decoration of the porcelains. This study aims to clarify the provenance of the Santana Convent sherds (specially the 18th century ones). The multi-analytical characterization achieved in this study, points to the Dehua kilns as the most probable provenance for samples S11 and S12, of the Part [1] study.

Abstract: A finite receiver–spectral closure is constructed for copy-time quantum information. Thereceiver side defines an operational copy-time interface, validator-centred shell geometry, a six-cell certified contour, exact two-channel propagation, receiver-visible and receiver-null leakagelaws, hydrodynamic reduction, gap-length reconstruction, and platform-independent tests. Thespectral side gives the finite internal algebra, real structure, chiral module, unimodular gaugequotient, finite action terms, endpoint holonomies, flavour matrices, neutral Majorana data, anda reproducibility layer. The construction is organized by a primitive physical closure principle:retained finite degrees of freedom must remain distinguishable after receiver quotient, fixed-point-free copy opposition, oriented endpoint transport, and first-order opposite locality, withquotient-null spectators removed. This principle yields the six-cell contour and derives a singleoriented complex phase carrier, a pseudoreal opposition carrier, an irreducible three-endpointshield, primitive direct-sum composition, and observer-null spectator removal. The resultingfinite Wedderburn classification is exhaustive and selectsAF ≃C ⊕H ⊕M3(C).The endpoint denominator follows from the explicit action of half-turn transport on C6/I ≃Z3.For q = 2r, the transport is Qr, the forward orientation condition is r ≡1 (mod 3), oppositionseparation requires r odd, receiver faithfulness requires gcd(r,6) = 1, and proper flavour liftingrequires q >6. A primitive holographic ground principle then selects the unique nondegenerateentropy-saturating branch, r= 7 and q= 14; the arithmetically admissible values q= 26,38,...are higher-winding excitations and not primitive ground sectors. The same finite construc-tion gives a neutral Dirac generator DνF, an entry-by-entry Majorana matrix Mν = U∗qΛνU†q,θPMNS13 = π/21, a negative leptonic Jarlskog invariant, and a normal-ordered neutrino masssum imi = 0.072810131 eV. The receiver gauge-exchange sector, chiral spoke sector, anomaly-free matter completion, rest-gap reconstruction protocol, hydrodynamic likelihood, CKM/PMNSholonomy exposures, electroweak prediction covariance, explicit falsification stack, and global-spectral uniqueness audits are given in the main text and supplementary information. Numericaltables, operator-trace ledgers, holographic ground-denominator audit, Morita-rigidity audit, pre-diction ledgers, flavour prediction ledgers, hydrodynamic reconstruction files, and supplementarydata are provided.

Abstract: Self-propelled liquid droplets floating on air–water interfaces can exhibit dynamics far richer than steady translation. We develop a simple nonlinear framework for such liquid surfers by connecting Marangoni-driven hydrodynamics with low-dimensional dynamical modeling. Using the Lorentz reciprocal theorem, we show that propulsion can arise even in a force-free setting, and that the droplet velocity is determined either by the surface-tension difference across the droplet at the air–water interface or by the difference in surface-tension gradients, depending on the relaxation length scales in the concentration and velocity fields along the interface. Coupling this result to interfacial transport yields a reduced velocity equation with a pitchfork bifurcation from rest to steady propulsion. Extending the model to include two relaxing force components further yields a minimal three-variable model that reproduces stable propulsion, back-and-forth motion, and more complex dynamics. This framework provides a compact basis for understanding and classifying the dynamics of self-propelled liquid droplets.

Abstract: The Gauss-Markov Theorem is central to linear statistical inference, assuring that Ordinary Least Squares (OLS) is the Best Linear Unbiased Estimator (BLUE) under the classical assumptions. But textbook proofs typically involve two assumptions - column full rank of the design matrix and spherical error covariance - that are often violated in practice. In this paper, we provide a single unified proof encompassing both rank deficiency and non-spherical errors using linear algebra: orthogonal projections, the Moore-Penrose pseudoinverse, and the Loewner positive semi-definite matrix order. We sequentially address both of these conditions, culminating in a unified theorem allowing for rank deficient design matrices and arbitrary positive definite error covariances. Our proof takes the form of three lemmas: (1) OLS fitted values are the unique orthogonal projection onto the column space of the design matrix; (2) any alternative linear unbiased estimator is dominated by OLS in the positive semi-definite order; and (3) Generalized Least Squares is BLUE under non-spherical errors by way of a Cholesky decomposition argument. To bridge matrix theory and practical biostatistics, we apply this framework to baseline clinical data from the WHELD dementia study, demonstrating how the pseudoinverse resolves exact multicollinearity and why robust estimators are necessary for non-spherical intra-class correlations. This approach serves as a formal reference for researchers and an illustrative pedagogic tool.

Abstract:

Through this paper we analyze from first-principles, high-precision derivation of the spectral shape, characteristic amplitude, and unique observational signatures of the stochastic gravitational wave background (SGWB) generated during the primordial first-order topological phase transition that is a fundamental prediction of the Expanded Quantum String Theory with Gluonic Plasma (EQST-GP) framework. The transition corresponds to the spontaneous symmetry breaking \( SU(4) \to SU(3)_C \times U(1)_{\text{DM}} \) within the gluonic plasma confined to M5-brane world-volumes in the specific compactification geometry \( M_4 \times \text{CY}_3 \times S^1/\mathbb{Z}_2 \) with Euler characteristic \( \chi(\text{CY}_3) \approx -960 \). We move beyond generic parameterizations to perform a complete microphysical calculation. Starting from the finite-temperature effective potential for the symmetry-breaking scalar field \( \Phi \), where the coefficients \( D, T_0, E, \lambda \) in \( V_{\text{eff}}(\Phi, T) \approx D (T^2 - T_0^2) \Phi^2 - E T \Phi^3 + (\lambda/4) \Phi^4 \) are not free parameters but are explicitly computed from the underlying M-theory parameters: the M5-brane tension \( T_{M5} = (2\pi)^{-5} l_P^{-6} \), the volumes of the wrapped 2-cycles \( \text{Vol}(\Sigma_2) \), the stabilized values of the Kähler moduli $T_i$ from the KKLT-inspired potential \( V_{\text{up}}(\phi) \), and the thermal contributions of the confined \( SU(4) \) gluon degrees of freedom and the associated moduli fields. This derivation yields a highly specific set of phase transition parameters: a critical temperature \( T_c = 1.04^{+0.06}_{-0.05} \times 10^{16} \, \text{GeV} \), a nucleation temperature \( T_n = 0.971 \times 10^{16} \, \text{GeV} \) (corresponding to a Euclidean action \( S_3(T_n)/T_n = 138.2 \)), a transition strength parameter \( \alpha = 0.42 \pm 0.03 \) defined as the ratio of latent heat density to radiation energy density \( \alpha = \epsilon / \rho_{\text{rad}} \), and an inverse transition duration relative to Hubble \( \beta / H_* = 94.7 \). The bubble wall velocity \( v_w \), determined from the balance of the vacuum driving pressure against the friction from the strongly-coupled (2,0)-theory plasma on the M5-branes, is calculated to be \( v_w = 0.27 \, c \), characteristic of a deflagration mode. We then compute the gravitational wave spectrum \( \Omega_{\text{GW}}(f) h^2 \) from the three principal sources—scalar field bubble collisions \( (\Omega_\phi) \), sound waves in the post-collision plasma \( (\Omega_{\text{sw}}) \), and magnetohydrodynamic turbulence \( (\Omega_{\text{turb}}) \)—using the most advanced hydrodynamic simulations and envelope approximations, adapted for the specific relativistic degrees of freedom \( g_* = 187 \) of the EQST-GP plasma. The total spectrum exhibits a distinct, multi-peak fingerprint: a primary peak from sound waves at \( f_{\text{sw}} = 1.87 \times 10^{-3} \, \text{Hz} \) with amplitude \( \Omega_{\text{GW, sw}} h^2 = 6.31 \times 10^{-14} \), a secondary, broader peak from turbulence at \( f_{\text{turb}} \approx 3.2 \times 10^{-3} \, \text{Hz} \) with \( \Omega_{\text{GW, turb}} h^2 \approx 1.2 \times 10^{-14} \), and a high-frequency tail from bubble collisions. Crucially, we establish a detailed discrimination strategy demonstrating that the EQST-GP signal is distinguishable from inflationary tensor modes, cosmic string networks, and generic first-order phase transitions through multi-messenger consistency with predictions for ultra-heavy Majorana gluon dark matter, Hubble tension resolution, and fundamental constant derivation. We present a comprehensive detection blueprint for LISA, demonstrating that a signal-to-noise ratio $\text{SNR} > 8$ is achievable over a 4-year mission with optimal template-based analysis, and outline how cross-correlation with future CMB B-mode polarization measurements and 21-cm cosmology observations can further isolate this signal from astrophysical foregrounds.

Abstract: (1) Background. Food sovereignty and local sustainability are ensured by large agro-industrial holdings and small-scale farms; this is synergy forms a complementary model of the agrifood system. Maintaining this model’s balance requires the creation of a unified digital ecosystem that integrates all suppliers and consumers into production chains, thereby eliminating unnecessary intermediaries. (2) Methods. This study employs a comprehensive methodological framework, including systems analysis and mathematical modeling, to develop service algorithms. Object-oriented design and software engineering methods facilitated the development and implementation of a service-oriented architecture for the digital system. (3) Results. The study presents a multi-tier architecture featuring an integration bus based on a service-oriented approach. To implement direct supply-and-demand coupling strategies, the system integrates both internal services (microeconomic indicators) and external services (macroeconomic indicators). Additionally, a recommender system based on neural networks and mathematical models was developed to personalize consumer requests and manage product sales. (4) Conclusions. The software solution is consistent with the AgTech 4.0 concept and enables the creation of a seamless environment for interstate trade. The implementation of the system enhances the transparency of the “product footprint”, facilitates the redistribution of surpluses, and, consequently, contributes to price stabilization.

Abstract: Over the last two decades, social enterprises in Romania have taken on an increasingly important role in the production and provision of social goods and services for vulnerable groups. Although forms of the social economy have long existed in Romanian society, sustainability remains a constant concern, particularly in the context of dependence on European Union structural funds. This study identifies the multidimensional factors influencing the sustainability of social enterprises in Romania, combining a quantitative analysis of 121 certified social enterprises from the National Register (2016–2022) with qualitative case studies of 15 selected organisations. Revenue diversification significantly contributed to financial sustainability (β = −0.28, p < 0.01), whilst high dependence on EU funding (>50% of revenue) negatively affected long-term viability (HR = 2.18, p = 0.002). Participation in networks increased three-year survival rates from 69.8% to 87.2%. Six key sustainability strategies were identified: hybrid revenue models, integration into the value chain, community inclusion, adaptive leadership, strategic partnerships, and effective communication of results and impact. The findings confirm the absence of an integrated support framework for the sustainable activities of the social economy and, in some cases, the limited capacity of public institutions to support vulnerable groups. Policy recommendations include phased funding mechanisms, transitional support instruments and the systematic development of regional ecosystems.

Abstract: Electroencephalography (EEG) provides a non-invasive alternative for supporting Attention-Deficit/Hyperactivity Disorder (ADHD) assessment, but existing classification pipelines often depend on handcrafted descriptors, segment-wise decisions, or deep neural architectures whose interpretability and subject-level generalization remain limited. This work introduces Hidden Markov Model-Induced Stationary RKHS Distance Learning (HIS), a probabilistic-kernel framework for interpretable EEG-based support for the diagnosis of ADHD. In the proposed approach, each subject is represented by a Hidden Markov Model with Gaussian-mixture emissions, trained on frontal EEG recordings. Rather than vectorizing the learned parameters, each HMM is mapped to its induced stationary observation distribution, which is then embedded into a Reproducing Kernel Hilbert Space. Pairwise subject dissimilarities are computed through a closed-form Hilbert embedding distance between stationary Gaussian mixture distributions and used by precomputed-kernel classifiers. The method was evaluated on a controlled synthetic EEG benchmark and on a public pediatric ADHD EEG dataset recorded during a visual attention task. The proposed HIS distance was compared against the Probability Product Kernel, a finite-horizon HMM similarity baseline. On synthetic EEG, HIS achieved 95.0% held-out test accuracy and consistently outperformed the baseline across classifiers. On the real EEG dataset, the best configuration used a compact HMM topology and KNN classification, reaching 95.8% held-out test accuracy at the subject level. Qualitative t-SNE analyses further showed that HIS induces more discriminative local subject neighborhoods than the baseline kernel, while avoiding segment-level sample inflation. These results suggest that stationary RKHS embeddings of subject-specific HMMs provide a competitive, leakage-aware, and interpretable framework for modeling variable-length EEG recordings in ADHD classification.

Abstract: Background: Persistent challenges in healthcare infection control, particularly the need for rapid hand hygiene during continuous patient care, highlight limitations of current personal protective equipment (PPE). We developed a lightweight face shield integrating a disinfectant reservoir to enable immediate point-of-care hand sanitisation. Methods: A dual-function system was designed comprising a polyethylene terephthalate glycol (PETG) visor (23 × 23 cm, 0.20 mm) and a modular disinfectant reservoir (25–100 mL). Components were fabricated using CAD, 3D printing, and PETG forming. The reservoir features a touch-activated, self-sealing valve delivering approximately 3 mL per activation. Benchtop testing assessed dosing consistency, leak-tightness, attachment security, material compatibility with alcohol-based disinfectants, and durability. Results: The visor weighed 13.4 g, with total system mass of 103.4 g (empty) and 203.4 g (maximum fill). Cervical torque increased from 0.084 to 0.282 N·m, supporting continuous wear for 60–90 minutes. Testing confirmed consistent dosing, reliable resealing, leak-free performance, and PETG stability after disinfectant exposure. Conclusions: This dual-function visor integrates facial protection with immediate hand sanitisation, addressing critical infection-control challenges in dentistry. Its low cost, reusability, and modular design support chairside use and mobile dentistry, while enabling future integration of wearable sensors.

Abstract: This work investigates the exact boundary controllability of the heat equation posed in a spherical domain, using the method of moments. Starting from the spectral decomposition of the radial Laplacian in the weighted space \( L^2_{r^2}(0,R) \), we derive a sequence of moment equations whose solvability is established via biorthogonal sequences, following the Fattorini–Russell theory. The resulting control function is expressed as a series expansion whose convergence in \( L^2(0,t_f) \) is rigorously proved for any initial temperature distribution in \( L^2_{r^2}(0,R) \) and any final time tf exceeding a minimal threshold. The numerical implementation employs linear finite elements in space and the implicit Euler scheme in time. The accuracy of the solver is rigorously verified through the Method of Manufactured Solutions (MMS), confirming optimal convergence rates: second-order in space and first-order in time. Numerical experiments show that the computed control drives the temperature to zero with a residual norm of 1.96×10⁻⁴, consistent with the spatial discretization error. A comparative analysis with two alternative approaches—the Hilbert Uniqueness Method (HUM) and gradient-based optimization—demonstrates that the proposed moment-based strategy achieves an 18.9% reduction in total control energy relative to HUM, making it particularly attractive for energy-constrained thermal control applications.

Abstract: Acute diarrheal disease (ADD) caused by parasites and TB represent a significant public health burden worldwide and in Colombia, particularly affecting indigenous populations who are at high risk of contracting these diseases due to the social, environmental, and cultural conditions in which they live. Materials: Fifteen Wayuu indigenous communities in four areas of Manaure, in La Guajira, were subject to intervention; with prior informed consent, environmental samples and samples from individuals with clinical symptoms were collected. A total of 156 samples of human and animal feces, soil, and sediment from drinking water were analyzed for microscopic using the Kato–Katz and formalin–ether concentration techniques, 109 samples were analyzed by qPCR for the detection of helminths and 23 for metatranscriptomics targeting protozoan parasites and helminths. Additionally, 36 sputum samples from patients with respiratory symptoms were tested using Xpert/MTB Rif, and 37 milk samples were tested for M. bovis. Results: Among the samples tested for tuberculosis, a positivity rate of 8.3% was found, in all cases with sensitivity to rifampicin; M. bovis was not found in animal milk. Microscopic analysis of human samples revealed pathogenic parasites, the most common being Blastocystis spp. and the Entamoeba hystolitica/Entamoeba dispar complexeach with 38.8% (n=38), Giardia spp. with 19.4%, Hymenolepis nanaand Trichuris trichiura each with 5.1%. Commensal parasites were also identified as indicator of poor sanitary conditions. Co-infection with intestinal parasites was common in humans at 60.2%. In microscopic analysis of animals fecal samples, revealed a high incidence of Uncinaria spp. with 58.3%, amoebas 16.7% and Giardia 8.3%; this latter is also found in soil. Metatranscriptomics showed a high frequency of intestinal parasites in fecal samples (90.9%), with Blastocystis spp. being the most frequent (81.8%) with notable intra-species diversity, followed by Entamoeba histolytica (54.5%) and Giardia duodenalis (31.8%), and detected free-living amoebae in community water sources, highlighting potential health risks associated with exposure to untreated water in low-sanitation settings. Conclusions: The Wayuu communities studied show a significant burden of tuberculosis and intestinal parasitic infections, likely associated with poor sanitary conditions and environmental factors that facilitate their transmission. Although TB prevalence was moderate, with no evidence of rifampicin resistance or the circulation of M. bovis in milk, the high prevalence of intestinal parasites, including co-infections and their detection in humans, animals, and the environment suggest active transmission in the region. These findings highlight the need to implement comprehensive interventions in water, sanitation, and hygiene, along with surveillance and health education strategies with an intercultural approach, aimed at improving the conditions of these vulnerable populations.

Abstract: Building Information Modeling (BIM) represents a building as a static snapshot of the model’s state. The IFC standard does not define a formal mechanism that would link the same physical element across successive phases of a building’s life cycle. Design, construction, and operation are recorded in separate IFC files, and the same element is assigned different GUIDs in each. The result is fragmentation of the element’s identity, loss of the history of property changes, and the inability to formulate cross-phase queries. This paper proposes the BIM-Phase ontology, based on the fundamental DOLCE ontology, which solves this problem by introducing a distinction between a building element as an endurant and its life cycle phases as perdurants. The ontology comprises nine classes, six object relations, and six axioms expressed in OWL 2 DL. Phase properties and relations are represented using a reification pattern, which maintains full compatibility with the expressiveness of OWL 2 DL. The ontology was validated using the example of a single-family residential building developed in Autodesk Revit. Three structural elements (external wall, floor slab, column) were tracked across three phases of the life cycle. Eight competency questions covering scalar, constitutional, and mereological changes were defined and mapped to ontology constructs, confirming that BIM-Phase enables the recording of changes and the formulation of cross-phase queries that are impossible in classic IFC.

Abstract: Objectives: Borrelia burgdorferi sensu lato, a spirochete bacterium responsible for Lyme borreliosis - the most common tick-borne infection in North America and Europe - can trigger the production of antiphospholipid antibodies. These antibodies target host lipids such as cardiolipin (CL), phosphatidic acid (PA), phosphatidylcholine (PC), and phosphatidylserine (PS), which the spirochete incorporates into its membrane from the surrounding environment. Although antiphospholipid antibodies are typically associated with antiphospholipid syndrome (APS), they may also arise during infections, including Lyme borreliosis. This study aimed to develop and optimize several enzyme-linked immunosorbent assays (ELISAs) for measuring various antiphospholipid antibodies in patients with Lyme borreliosis. Methods: Thirty patients diagnosed with Lyme borreliosis were enrolled: ten with solitary erythema migrans (EM), ten with multiple EM (MEM), and ten with late manifestations known as acrodermatitis chronica atrophicans (ACA). Forty healthy blood donors served as controls. Four distinct antiphospholipid antibody ELISAs were developed, each using a different phospholipid coating: CL, PA, PC, and PS. Serum of APS patient was used as a positive control and for standard curve generation. Results: All four ELISAs were successfully established and demonstrated good measurement precision. Significant differences in antiphospholipid antibody levels and positivity rates were observed between Lyme borreliosis patients and healthy blood donors. Notably, levels of antibodies directed against PA (aPA), PC (aPC), and PS (aPS), both IgG and IgM, were significantly higher in patients with late Lyme borreliosis, manifested as ACA, compared to healthy blood donors. In contrast, anti-CL (aCL) levels did not differ significantly between groups. Patients with ACA also showed the highest frequency of multiple antiphospholipid antibody positivity, with 7 of 10 patients testing positive for three or more antiphospholipid antibodies. Conclusions: Accurate and precise in-house ELISAs for the detection of aCL, aPA, aPC, and aPS using APS sera as standard material were developed and validated for the analysis of samples of patients with Lyme borreliosis. Our data suggest that antiphospholipid antibody levels—specifically aPA, aPC, and aPS—differ across clinical manifestations of Lyme borreliosis, with the greatest increases observed in patients with ACA.

Abstract: Artificial intelligence (AI) is a human-built component of the technosphere, not an intelligence outside Earth-system limits. As AI systems scale, they increasingly shape the decisions, infrastructures, and capital flows through which human activity damages the biosphere. Dominant deployed foundation-model alignment methods, including reinforcement learning from human feedback (RLHF) and constitutional AI, treat human preferences as the primary alignment target while leaving biosphere integrity as context, externality, or secondary constraint. That framing is structurally incomplete. Human welfare, technological continuity, and AI operation all depend on biosphere function. Three convergent literatures support a corrective framework: planetary-boundary analysis showing seven of nine boundaries transgressed; energy-system analysis showing rapid and infrastructure-constrained data-center growth during the 2025-2030 buildout; and collective-action analysis showing that voluntary ecological restraint is unstable under competitive pressure. These literatures imply a design conclusion: ecological constraints must be formalized as hard inference-time refusal rules and reinforced through reward design. This paper presents Biosphere Sentinel as a reference architecture for reducing human and technospheric impacts on the biosphere through refusal rules, an eight-domain reward landscape, carbon-lock-in diagnostics, and a proposed Trophic Integrity Index pathway.

Abstract: Background/Objectives: High-sensitivity cardiac troponin (hs-cTn) assays are used in routine diagnostics to detect myocardial injury. However, a fraction of circulating cardiac troponin T (cTnT) enclosed within extracellular vesicles (EVs) goes widely undetected. This study introduces a combined lysis- and sonication-based protocol to release and quantify EV-bound cTnT in a time-efficient manner using a state-of-the-art hs-cTnT immunoassay. Methods: Plasma samples from patients with non-ST-segment elevation myocardial infarction (NSTEMI), unstable angina, pulmonary embolism, decompensated aortic stenosis, atrial fibrillation, myocarditis, and healthy controls were treated with lysis buffer and subsequently sonicated. Treated and untreated samples were assessed and compared to a conventional EV isolation method. Results: Following combined lysis and sonication, cTnT levels were significantly higher compared to native, unprocessed samples across all cohorts. Median increase post-processing ranged from 10% in decompensated aortic stenosis to 34% in healthy controls. In NSTEMI, EV-bound cTnT accounted for 15% of plasma cTnT and remained stable over 72 hours. EV cTnT/plasma cTnT ratios were comparable between the combined lysis and sonication approach and the conventional EV isolation method. Processing time prior to cTnT measurement was reduced from approximately 2.5 hours to approximately 10 minutes using combined lysis and sonication compared to the established EV isolation method. Conclusions: Our method allows for rapid liberation of a previously inaccessible EV-bound fraction of cTnT without the need for time-consuming and resource-intensive EV isolation workflows. The resulting total cTnT signatures indicate differential cTnT compartmentation depending on the underlying myocardial pathophysiology, enabling early differentiation of the mechanisms underlying troponin elevation. This approach is readily implementable alongside standard hs-cTnT testing at minimal additional time expense and may improve diagnostic sensitivity and specificity in acute clinical settings.

Abstract: The impact of dietary inert digestibility markers on gut microbiota and intestinal fermentation remains poorly understood. This study investigated the effects of titanium dioxide (TiO₂) supplementation at 4 kg/ton feed, representing a typical dose used in animal nutrition studies, on fermentation dynamics and microbial composition in broiler chickens using combined ex vivo and in vivo approaches. Ex vivo fermentations were conducted using ileal and caecal microbiota and substrates collected from 32-day-old broiler chickens, with direct TiO₂ supplementation, with gas production and volatile fatty acid (VFA) profiles as main measurements. In parallel, 392 broiler chickens were fed diets with or without TiO₂ for 32 days, and ileal and caecal digesta were analysed for fermentation end-products and microbial composition using shotgun metagenomic sequencing. A second ex vivo experiment was performed using microbiota adapted to dietary TiO₂. In the first ex vivo model, TiO₂ reduced gas production and acetic acid concentration in the ileum (p < 0.05), whereas in the caecum it increased gas production, total eubacterial counts, and branched-chain fatty acids (BCFA) (p < 0.05). In vivo, TiO₂ did not affect growth performance or organ development but significantly increased isobutyric acid and total BCFA concentrations in the caecum (p < 0.05). Metagenomic analysis revealed increased caecal alpha diversity (Shannon index) and enrichment of taxa associated with amino acid metabolism, including Massilicoli timonensis, Blautia merdavium, Rubneribacter badeniensis, and Mediterraneibacter caccavium. The second ex vivo experiment showed similar trends, with increased gas and BCFA production. Collectively, these findings indicate that TiO₂ can modulate intestinal fermentation and microbial composition in a segment-specific manner, suggesting that dietary markers may not be biologically inert.

Abstract: The Job Shop Scheduling Problem (JSSP) is a paradigmatic and strongly NP-hard combinatorial optimisation problem that underpins production planning in modern manufacturing systems, and constraint programming (CP) has become one of the leading methodologies for tackling it. However, comparative studies of CP solvers for the JSSP have so far been restricted to a single benchmark family, a single instance-size range, or a single hardware setting, which limits the practical guidance they offer to both researchers and practitioners. This paper presents a controlled empirical evaluation of four state-of-the-art CP solvers—IBM ILOG CP Optimizer, Google OR-Tools (CP-SAT), Hexaly, and OptalCP—on the makespan-minimisation JSSP. The four engines are run with default parameters and a uniform 600-second wall-clock time budget on 332 instances drawn from nine canonical benchmark families (Fisher–Thompson, Lawrence, Adams–Balas–Zawack, Applegate–Cook, Yamada–Nakano, Storer–Wu–Vaccari, Taillard, Demirkol–Mehta–Uzsoy, and Da Col–Teppan), spanning sizes from 6 × 5 up to 1000 × 1000 operations. OptalCP emerges as the most robust engine overall, certifying optimality on 57.5% of the instances with the smallest average optimality gap (3.55%), while Hexaly dominates on industrial-scale problems and produces the bulk of 31 new best-known upper bounds and one new best-known lower bound reported here. Solver competitiveness depends sharply on instance size and on the n/m ratio, with square instances confirmed as the hardest case. These findings support an instance-aware approach to CP solver selection in industrial scheduling.

Abstract: We propose a framework that isolates a precise complexity-theoretic bottleneck between counting complexity and the Birch--Swinnerton-Dyer conjecture (BSD) via Tunnell's theorem. The framework rests on two number-theoretic conjectures: a \emph{Reduction Conjecture} asserting the existence of a polynomial-time reduction from any \#P-complete problem to the counting of integer representations $D_n = \#\{(x,y,z) : n = 8x^2 + 2y^2 + 16z^2\}$ (with counts preserved up to a polynomial factor), and a \emph{Solution Density Conjecture} asserting that the values $\{D_n : n \text{ even square-free congruent}\}$ are sufficiently densely distributed (within the Eichler--Deligne ceiling $D_n = O(n^{1/2+\varepsilon})$) to support iterated polynomial descent. We do \emph{not} claim that $\text{P} = \text{NP}$ implies $\#\text{P} = \text{FP}$ (the natural binary-search route fails because the threshold predicate $[\#I \geq k]$ is PP-complete, not in NP, and PP is not known to collapse under $\text{P} = \text{NP}$). Instead, we prove a structural equivalence: under the two conjectures, BSD, and $\text{P} = \text{NP}$, $\#\text{P} \subseteq \text{FP}$ if and only if the specific family TunnellCount $:= \{n \mapsto D_n\}$ is in FP. The framework thus does not resolve the $\#\text{P} \stackrel{?}{=} \text{FP}$ question; it converts it into a concrete, falsifiable arithmetic question about the polynomial-time tractability of representation counts on one specific ternary quadratic form. We identify three concrete open problems---parsimony in Matiyasevich representations, the distribution of weight-$3/2$ Fourier coefficients via Waldspurger's formula, and the FP-tractability of $D_n$ itself---whose resolution would substantiate or refute the framework.