Abstract: Rationale. Bioinformatics workflows increasingly need to integrate heterogeneous biomedical data, including experimental assay outputs, patient-derived model metadata, mechanistic models and molecular-pathology information. In glioblastoma (GBM), such integration can help connect treatment responses measured in patient-derived 3D cultures with molecular context and mechanistic representations of tumor metabolism, while maintaining a clear distinction between experimental observations and model-derived hypotheses. Results. We describe a standards-based workflow that integrates patient-derived GBM drug-response screens with a machine-readable QSP model, MGMT promoter methylation metadata and an explicit evidence-tier framework. MGMT-promoter methylation was confirmed in all patient-derived 3D cultures (Ge258, Ge518 and Ge904). Phenformin (PTF) showed the most pronounced single-agent activity, with a concentration-dependent reduction in viability, while 2-deoxy-D-glucose (2-DG) produced a more moderate effect. Among the higher-order combinations, MTF + BPTES + 2-DG + TMZ produced the most pronounced combination response and a statistically significant reduction in viability under the tested conditions. These findings are interpreted as treatment-response and prioritization signals rather than definitive evidence of pharmacological synergy or clinical efficacy. Availability and implementation. The workflow is designed around open and independently checkable data and model files, including raw plate exports, processed block-level tables, molecular metadata, an SBML/SED-ML/COMBINE model package, an evidence-tier table and a next-experiment protocol. Together, these components provide a reproducible framework for integrating computational predictions with experimental evidence and prioritizing testable drug-combination hypotheses.

Abstract: Stock movement prediction remains challenging because financial time series are nonstationary, noisy, and interdependent across heterogeneous information sources. Conventional multimodal forecasting methods often integrate price, text, and inter-firm relationships into a single representation, making it difficult to capture modality-pair-specific interactions and their varying relevance across market conditions. To address this issue, this study proposes Pairwise Cross-Modal Attention Fusion with Mixture-of-Experts (PaCMoE), which explicitly decomposes multimodal interactions into three modality pairs— price-text, price-graph, and text-graph pair. Each pair is modeled by an independent cross-modal attention expert, and a Mixture-of-Experts router adaptively integrates the resulting representations according to the input. On the ACL18 (StockNet) benchmark, PaCMoE is evaluated using chronological data splitting, validation-based model selection, and ten random seeds. The proposed method achieves an average accuracy of 60.69% and an MCC of 0.2200, outperforming the compared methods evaluated with multiple runs or random seeds in both metrics. These results demonstrate the effectiveness of explicitly modeling pairwise cross-modal interactions and adaptively integrating their contributions for robust stock movement prediction.

Abstract: This study aimed to evaluate the ability of microbes from the rumen contents of cattle as antagonists of pathogenic fungi and as liquid organic fertilizer (LOF) containing P-solubilizing bacteria in rice plants. The mixture consisting of 5 kg rumen contents of cattle, 2 kg of rice bran, 1 kg of molasses, and 10 L of tap water was fermented for 14 days. After fermentation, the mixture was filtered to separate the liquid from the solid components. The solid portion was collected for the isolation and screening of contained bacteria. Subsequent tests included biochemical tests, antagonistic activity tests, DNA extraction, PCR amplification, phosphate solubilization ability testing, inhibitory ability study, and application of LOF in a screen house. One bacterial isolate (PTK2TB code) exhibited the highest antagonistic activity against three tested pathogenic fungi (inhibits more than 50%). Subsequent 16SrDNA sequence analysis showed that this isolate belongs to the same group as the type strain and reference strain of Bacillus amyloliquefaciens. Furthermore, out of the 90 bacterial isolates obtained, 20 demonstrated a high capacity for phosphate solubilization. Additionally, LOF containing phosphate-solubilizing bacterial isolates positively impacted rice growth and yield.

Abstract:

We construct a systematic general-relativistic model of the spacetime generated by a slowly rotating, axially symmetric, self-gravitating clump of collisionless matter whose gravitational potential is of Miyamoto–Nagai type. The metric is taken in a three-function cylindrical gauge, \(ds^2=e^{a}\,dt^2-e^{b}(d\rho^2+dz^2)-\rho^2e^{c}d\phi^2\), with the frame-dragging function \(\omega\) added at the stationary level. We prove a no-go lemma of explicitly delimited scope (no pointwise relation \(c=F(a,b)\) can annihilate the off-diagonal Ricci component) and reduce the field equations, for a diagonal source, to an algebraic system for \(b_\rho,b_z\) valid wherever (∇W)2≠0, \(W=\rho e^{(a+c)/2}\). The integrability of the resulting quadrature is not automatic: we prove that the compatibility condition \(\partial_zb_\rho=\partial_\rho b_z\) is exactly equivalent to the meridional matter-conservation equations — one combination of which is an identity, the other being the equation that determines the remaining metric function — and that at second order in \(\beta=2GM/c^2\) it becomes the linear Poisson-type problem \(\mathcal{L}c_2=4\kappa P_m\). A barotropy criterion shows that a prescribed flattened potential with strictly isotropic pressure is inconsistent already at the Newtonian level, whereas the Miyamoto–Nagai potential admits a globally physical anisotropic solution: density, meridional pressure and stress anisotropy follow in closed form, \(\kappa P_m=\beta^2\varepsilon^2(A+\zeta)^2/(4\zeta^2S^3)\) and \(\kappa(P_\phi-P_m)=A\beta^2\varepsilon^2\rho^2/(2\zeta^3S^3)\), all of definite sign, so that \(P_\phi>P_m\) everywhere off the axis and the anisotropy vanishes identically in the spherical limit. Rotation is included to Hartle order: the dragging obeys a linear equation at all orders in our gauge, the second-order diagonal metric is degenerate under the dispersion–rotation partition of the azimuthal support, and the degeneracy is broken only by the gravitomagnetic sector; the fully rotational realization gives \(v_\phi/v_c\) in closed form, near-circular for thin discs. On this basis we assess detectability: the flattening layer is routinely observable, with a deflection anisotropy decaying anomalously slowly (as \(A/b\)); galactic frame dragging (\(\sim10^{-3}\,\mu\)as yr−1) is astrometrically hopeless, but the parity-odd rotational asymmetry of time delays between opposite-side images of strongly lensed transients, \(\Delta t\sim 8GJ/c^4b\sim10^3\)~s, is detectable in principle given VLBI-grade (\(\sim10\,\mu\)as) astrometry, the threshold being \(M\gtrsim2\times10^{9}M_\odot\) at disc-galaxy velocities; in the compact regime the model yields falsifiable energy-condition bounds (\(\beta_{\rm DEC}\approx3.8\,\varepsilon\), \(\beta_{\rm WEC}\approx6.8\,\varepsilon\)) and dragging frequencies in the QPO band.

Abstract: Despite the rise and wide spread of digital technology, analog circuits are experiencing a resurgence for specific applications due to their efficiency in processing physical signals with fewer transistors and lower energy requirements. They offer advantages in explainability and stability, particularly in sensor systems. However, designing these circuits poses challenges, particularly in optimizing them against issues like component aging and environmental dependence. Current research aims to enhance automation in analog circuit design using optimization methods, including stochastic algorithms like Genetic Algorithms (GA), Simulated Annealing (SA), and Particle Swarm Optimization (PSO). These methods improve convergence and fault tolerance while dealing with the high nonlinearity of analog circuits with transistors. The project's focus is on solving multivariate optimization problems with multiple objective functions for analog circuit design to achieve high performance with minimal energy use, combining various algorithmic strategies for better outcomes. We will evaluate and compare the component optimization of a small signal amplifier circuit using gradient and the different stochastic methods for bipolar junction (BJT) and organic electro-chemical transistors (OECT), differing in transistor transconductance and transfer curves. We can show that PSO outperforms all other optimization algorithms. The OECT components were manufactured with a drop-on-demand ink-jet process, experimentally characterized, finally deriving an electronic functional digital twin model from measuring data. This is a simulation study, but using data and models from real devices.

Abstract: We present a group-theoretic reconstruction of quantum mechanics in which the standard formalism emerges from the representation theory of symmetry groups rather than being introduced axiomatically. Starting from physically motivated symmetry principles, we show how the conventional postulates of quantum mechanics, including the Hilbert space structure of states, observables as generators of symmetry transformations, the Born probability rule, unitary time evolution, the composition of multipartite systems, and the measurement framework, can be recovered within a unified representation-theoretic framework. We then examine the measurement problem by interpreting wave-function collapse as the scattering of quantum states, thereby accounting for the apparent loss of information. This framework offers a conceptually unified perspective on the foundations of quantum mechanics, connecting its postulates, measurement theory, and the emergence of quantum phenomena to a common symmetry-based origin.

Abstract: This article explores the strategic pathways to achieve information technology sovereignty that Bangladesh can pursue. Digital sovereignty requires coordinated national capacity across data governance, secure infrastructure, software ecosystems, artificial intelligence policy, cybersecurity, supply-chain resilience, and human capital development. The article proposes a balanced model based on open standards, trusted international partnerships, selective self-reliance, and phased institutional investment. Bangladesh can leverage its youthful workforce, growing digital economy, fintech innovation, and emerging policy frameworks to progressively reduce structural dependency while strengthening national autonomy, resilience, and competitiveness within the global digital order.

Abstract: Large language models (LLMs) suffer from hallucinations—confidently generating false information when uncertain. Conventional token prediction provides no dedicated output action for abstention: uncertainty can be represented only indirectly through the output distribution, while the model is nevertheless trained to select ordinary vocabulary tokens. We investigate whether an explicit abstention state, combined with scalable supervision for when abstention is appropriate, improves selective prediction. We add a single ABSTAIN token to the vocabulary and train models to predict it using corruption augmentation—a scalable data augmentation technique where corrupted inputs are mapped back to the abstain token. In a simple feedforward network tasked with single-token prediction, this approach reduced the hallucination rate on unseen data from 95% to 0% while maintaining perfect accuracy on known examples. The same principle also scaled to a real question-answering (QA) model: a distilled Bidirectional Encoder Representations from Transformers (BERT) model fine-tuned on SQuAD abstained on 89% (±7.8) of nonsense questions at corruption level p = 0.10, rising to 94.5% (±7.8) at p = 0.20, while retaining approximately 95% of its baseline accuracy at both levels; this abstention transferred to natural text corruption (OCR errors, encoding artifacts, character damage) without any noise-specific training, and mining the model's own confident errors provided complementary supervision, extending abstention to fluent-but-unanswerable questions that mechanical corruption misses; combining the two supervision sources yielded broader abstention coverage across all evaluated failure modes.

Abstract: Long-duration human exploration beyond low-Earth orbit exposes crews to a convergent hazard field that includes galactic cosmic radiation, solar particle events, hypogravity, hypokinesia, immune dysregulation, microbiome disturbance, circadian disruption, psychological stress, and constrained habitat conditions. Current radioprotection strategies (exposure limitation, active dosimetry, space-weather forecasting, physical shielding, storm-shelter logic, ALARA-style dose management, and biomedical countermeasures) remain essential, but they will not fully solve the biological problem of cumulative radiation injury during Mars-class missions. This article proposes a hypoxia-centred integrated radioprotection framework in which habitat atmosphere composition and oxygen partial pressure are treated as active design variables rather than passive life-support parameters. Controlled normobaric hypoxic engineering may reduce oxygen-dependent fixation of radiation injury, lower oxidative pressure, support mitochondrial resilience, and improve fire safety in enclosed vehicles and habitats. This approach is not a replacement for shielding, monitoring, or pharmacological countermeasures. It is a missing environmental layer designed to integrate with them. The central operational concept is a two-level architecture: long-term adaptation to moderate habitat hypoxia, provisionally corresponding to approximately 16-12% O2 under carefully controlled normobaric conditions, combined with short, monitored, deeper hypoxic excursions to approximately 9-10% O2 during solar particle event sheltering, when crew are already in structurally protected niches with minimal physical activity and reduced oxygen consumption. These values are proposed research windows, not operational recommendations, and require staged validation before any mission use. The proposed framework integrates mechanistic rationale, operational architecture, safety objections, fire-safety co-benefits, adjunctive countermeasures, and a four-prototype validation pathway for controlled oxygen modulation. Controlled hypoxic habitat engineering emerges as a mission-critical countermeasure candidate for deep-space exploration and as a possible translational bridge to terrestrial geromedicine through mitochondrial resilience, hypoxic conditioning, and healthspan infrastructure.

Abstract: Anthropogenic prehistory may be divided into two subsequent phases, the first one from the Last Common Ancestor (LCA) between humans and great apes till the emergence of the genus Homo, and the second phase onwards from then. Until hominins appeared, LCA had lived predominantly on trees, while Homo finally lived only on the ground. After LCA and before Homo, the intermediate bimodal transition period from 7 to 2 Myr BP was coined by the emergence of systematic bipedal gait, breaking the previously uniform quadrupedal locomotion symmetry. By contrast to versions of the common savannah hypothesis, this paper suggests an alternative fictitious scenario of periodic migration between alternatingly inhabitable arboreal refuges. Possibly caused by regional climate change, yet tree-climbing hominins were additionally forced to genetically develop speedy and efficient bipedal locomotion for survival during their temporary but extended regular excursions across open territory. Increasingly upright locomotion resulted in offspring’s early weaning, and in turn in the emergence of childhood with enhanced lethal risks for toddlers. Related selective pressure caused transformations of reproductive traits from gradual sexual selection in apes to undulating sexual conflicts in hominins. Between LCA and Homo, consistent with fossil evidence, the evolutionary bimodal transition phase, with forelimbs for climbing and hind limbs for running, did not necessarily require enlarged brains for advanced mental capabilities, nor specific communication or new forms of social cooperation such as those successively found in Homo. After emigration from arboreal habitats, allotted food access caused previous promiscuous mating being replaced by sexual pair bonding with exclusive paternity of Homo. Assumingly, broken spatial and temporal environmental symmetry had induced related symmetry breaking of hominin behaviour, their anatomic structures and reproduction habits, with consequences lasting to the present day.

Abstract: This exploratory, uncontrolled study investigated whether objective tongue mobility measurements change immediately after a brief conservative intraoral intervention, given the clinical use of the Tongue Range of Motion Ratio (TRMR) in treatment and surgical decision-making. Anonymised clinical data were analysed from 20 consecutive participants (17 females and 3 males; aged 6–84 years) receiving routine care in two private orofacial myology and temporomandibular disorder practices. Maximal mouth opening (MMO), tongue tip-to-incisive papilla (TTIP), lingual–palatal suction (LPS), and anterior and posterior TRMR were measured immediately before and after a standardised intraoral myofascial intervention lasting approximately five minutes (YTM® Introductory Protocol) and compared using paired t-tests with Wilcoxon sensitivity analyses. MMO, TTIP, and LPS increased significantly (35.5±7.0 to 40.8±6.5 mm; 26.2±7.8 to 30.4±8.5 mm; 18.8±6.6 to 22.1±8.2 mm; all p< 0.001), with large effect sizes (Cohen's dz values ranging from 0.92 to 1.45). Group-level anterior and posterior TRMR showed minimal change (both p>0.4), although a small number of participants crossed published TRMR classification thresholds. These findings indicate that absolute tongue-mobility measurements can improve immediately after brief conservative intervention, while group-level TRMR remains largely stable, raising the possibility that objective tongue mobility assessment may be influenced by immediately modifiable functional components. As this study had no control group, larger controlled trials are needed to determine whether the changes reflect intervention effects, repeated testing, or participant familiarisation.

Abstract: Monitoring the progression of wildfires in near-real-time is essential for active-fire situational awareness and emergency response management. Current satellite-based wildfire monitoring systems face a trade-off between temporal and spatial resolution. Geostationary satellites such as the Geostationary Operational Environmental Satellite (GOES) offer frequent but coarse observations (~5–15 min, 2 km), while polar-orbiting satellites such as those carrying the Visible Infrared Imaging Radiometer Suite (VIIRS) provide fine spatial detail with limited temporal coverage (~12 h, 375 m). To bridge this gap, this study introduces a deep learning (DL) approach for sub-pixel fire segmentation and brightness temperature (BT) estimation from GOES imagery. The proposed approach consists of two steps, a segmentation step to distinguish active fire regions from background and a regression step to estimate the BT of active fire pixels. The model is developed using a dataset of 257 wildfires across the United States, consisting of multi-spectral GOES imagery paired with VIIRS-derived fire observations processed through parallax correction, reprojection, and resampling. The proposed approach processes data within approximately 5 min of observation, indicating near-real-time capability. Compared with a previously developed autoencoder-based model, the proposed method improves fire segmentation performance, increasing the average precision (AP) from 0.105 to 0.368 and reducing the fire-region root mean square error (RMSE) of BT estimation by 72.1% from 81.33 K to 22.69 K. Notably, the proposed approach reduces the omission error rate for medium-sized fires from 9.41% to 1.96% while maintaining zero omission errors for large fires. It also reduces the false positive rate on non-fire images from 66.86% to 8.48%. Ablation studies assess the impact of background values in the VIIRS reference data as well as the impact of loss functions and their weights. Overall, the proposed approach provides a practical solution for near-real-time sub-pixel fire segmentation and BT estimation using existing geostationary satellite systems.

Abstract: Background: Overweight and obesity are burgeoning health epidemics. Diets including alternate-day fasting (ADF) promote weight loss but risk significant muscle loss, posing health implications to seniors at risk of sarcopenia. Leucine, the key muscle protein synthesis (MPS) driver, effectively stimulates MPS with lower calorie intake than protein. However, the effects of body-mass-scaled protein and leucine intakes are unclear. Objectives: To evaluate body-mass-scaled leucine or protein supplementation on body composition, sarcopenic and cardiometabolic markers in older men during ADF. Methods: Sixty-one older men (BMI ≥ 23.0 kg/m²) underwent 28 days of ADF, randomized across three calorie-matched supplement groups: Control (C: 0.0 g/kg protein, 0.0 g/kg leucine), Leucine (L: 0.0 g/kg protein, 0.08 g/kg leucine), or Protein (P: 0.4 g/kg protein, 0.04 g/kg leucine), consuming three doses on feeding days and one on fasting days. Dual-energy X-ray absorptiometry, sarcopenic metrics, and blood markers (blood pressure, lipid panels, diabetic profiles) were measured. Results: There were no significant interactions (p > 0.05) in body composition, sarcopenic or health outcomes, except diastolic blood pressure (p = 0.016) and HDL cholesterol (p = 0.013). There were significant main effects of time (p £ 0.05) with reductions in all body composition measures (excluding bone mineral density, p = 0.274), systolic blood pressure and lipid profiles (total and LDL cholesterol, total/HDL cholesterol ratio, triglycerides), and improvements in all muscle strength and functional sarcopenic outcomes. Conclusions: Dietary interventions alone that increase leucine and/or protein intake do not further improve body composition, sarcopenic and cardiometabolic outcomes during weight loss.

Abstract:

We present AEGYPTI (v0.5.6), a combinatorial triangle-detection framework for an undirected simple graph \(G=(V,E)\) with \(n=|V|\) vertices and \(m=|E|\) edges. Execution is dynamically dispatched by density at the structural threshold \(\lceil n^{4/3}\rceil\). When \(m\le\lceil n^{4/3}\rceil\), an optimized Chiba–Nishizeki adjacency-intersection routine, sorted by non-decreasing degree, is invoked. For denser instances, the algorithm employs a randomized square-root partitioning strategy that isolates induced subgraphs and geometrically prunes intra-partition edges in \(\mathcal{O}(n^{2})\) time per iteration. Coupled with a linear-time Caro–Wei independent-set computation on the complement (and bipartite short-circuits), this strategy yields an expected runtime of \(\mathcal{O}(n^{2.5}\log n)\) for dense regimes. The randomness is drawn from a cryptographically secure source, guaranteeing a true Las Vegas algorithm whose expectation is taken solely over internal coin flips. We prove soundness, completeness, and the stated complexity bound in full detail. The resulting subcubic bound constitutes a randomized (Las Vegas) combinatorial counter-example to the generalized assumptions of the Combinatorial Boolean Matrix Multiplication (BMM) Conjecture. A public reference implementation is available in the aegypti Python package.

Abstract: Artificial intelligence systems now perform tasks once thought distinctively human, and this performance often shapes judgments about machine consciousness, agency, and personhood. Much of the literature evaluates these judgments by tracking what systems can do rather than by asking what a person is. This article treats that question as ontologically prior. It asks what conception of human personhood can explain why cognitive performance is insufficient for personhood, and can guide claims about artificial personhood and moral status. Using conceptual analysis, comparative engagement with recent philosophy of artificial intelligence, and dialogue with biblical anthropology, the article develops a four-dimensional relational ontology of the human person, built from embodied selfhood, constitutive relationality, responsible agency, and oriented dignity. It compares this ontology with functionalist, computationalist, capacity-based, relational, and embodied-cognition accounts, and defends the four dimensions as jointly addressing four distinct reductionist tendencies in existing theories. The contribution is this integrated ontology, together with the conclusion that artificial intelligence ethics requires a defensible account of the human person, not an expanding catalogue of machine capability.

Abstract: While current literature heavily relies on symmetric exponential kernels within the stress-driven nonlocal integral framework, these models are strictly limited to normal bending fields and exhibit a total architectural vacancy in describing independent shear mechanics. This paper establishes the first exact analytical, closed-form constitutive model for uncoupled nonlocal shear deformation using an anti-symmetric state-dependent integral kernel.By executing a rigorous mathematical decomposition, the spatial coordinate boundaries are isolated from the polynomial domain, transforming the integral equation into a well-posed second order ordinary differential equation. Under this anti-symmetric framework, the standard boundary layer pathologies and Dirac-delta singularity spikes that historically crippled Eringen’s strain-driven configurations are identically neutralized via cross-term cancellation at the regular singular interface.The mathematical derivations reveal a pioneering structural paradigm “Automatic Dual-Phase Mechanical Bifurcation”. It is algebraically, proved that the uncoupled nonlocal shear framework automatically toggles between microstructural softening and wave-stiffening configurations based exclusively on the spatial gradient of the applied loading field. The exact formulation is successfully, deployed to evaluate the torsional shear alignment of single-walled carbon nanotubes (SWCNTs), unlocking an accurate elastic scaling resolution that remains fully singularity-free and asymptotically collapses to classical Hookean macro-continuum mechanics as the nonlocal parameter approaches zero.

Abstract: Chlorophyll-a (Chl-a), the primary photosynthetic pigment in algae, is widely used as a proxy for phytoplankton biomass and trophic status in lakes. While machine learning (ML) methods have been used for simulating Chl-a concentrations, there have been few studies examining ML methods for lakes with scarce monitoring data of water quality. This study evaluated simulation performance of three commonly used ML methods (i.e., Random Forest, XGBoost, and a Long Short-Term Memory (LSTM) network) for 11 data-scarce lakes in Leon County, FL. Each lake has only 1 – 6 sampling locations with a quarterly monitoring schedule, and there are a total of 1,012 sets of observations (43 to 252 per lake) for the study period of 2014 – 2024. Each observation set includes 43 water quality variables, e.g., phosphorus, organic nitrogen, and dissolved oxygen. Evaluating the three ML methods was based on three cross-validation operations and three statistical metrics (i.e., root mean square error, mean absolute error, and coefficient of determination). In a five-fold cross-validation, XGBoost achieved the best simulation performance. In a chronological cross-validation, all the methods had a similar modest simulation performance. A spatial cross-validation revealed that it was challenging to simulate Chl-a concentrations for two lakes with high Chl-a concentrations and large temporal variations. A method-agnostic importance test consistently identified a subset of water quality variables as top predictors across all the methods, including phosphorus, organic nitrogen, and biochemical oxygen demand. These findings demonstrate that ML is an effective tool for simulating Chl-a concentrations even for data-scarce lakes, whereas more monitoring data are needed for simulating high Chl-a concentrations with large temporal variations.

Abstract: Soybean (Glycine max L.) seeds often exhibit poor germination, leading to uneven crop es-tablishment and delayed seedling emergence. A laboratory experiment was conducted to evaluate the efficacy of five biostimulants (Acadian, Appetizer, Manvert Ocean, Algaren Twin, and Muhit) at four concentrations (0, 25, 50, and 75 ml L⁻¹) in enhancing seed vital-ity and vigor. The study followed a Completely Randomized Design (CRD) with four rep-lications. Key parameters assessed included first and final germination counts, radicle and plumule lengths, seedling dry weight, seedling vigor index (SVI), and cold test per-formance. Results revealed significant effects of biostimulants, concentrations, and their interactions on all studied traits. Notably, Acadian at a concentration of 50 ml L⁻¹ yielded the superior performance, likely due to an optimized balance of nutrients and growth hormones that promote cell elongation and enhanced water and nutrient uptake. While concentrations generally exerted a more pronounced effect than the bio stimulant type, ex-cessive concentrations resulted in inhibitory effects. Among the indicators, the seedling vigor index proved to be the most comprehensive and reliable metric for assessing seed quality. Consequently, the application of Acadian at 50 ml L⁻¹ is recommended to enhance soybean seed quality and vigor for promoting sustainable agricultural production.

Abstract: The discrepancy between galactic rotation curves and visible baryonic mass persists despite empirical scaling relations like the Radial Acceleration Relation (RAR) and Baryonic Tully-Fisher Relation (BTFR). We explore a phenomenological framework where this discrepancy arises from the geometric misinterpretation of observables. Inspired by Painlevé-Gullstrand coordinates, we model the vacuum as a radially infalling compliant medium that induces an apparent compression mapping of radial coordinates for distant observers, the "Mezzi effect". Assuming Newtonian dynamics govern an undistorted "true frame", we developed a discrete shell reconstruction method parameterized by a single universal compliance constant, tested against photometric and kinematic data from 175 late type galaxies in the SPARC database. This single parameter model yields universal scaling relations of \(\Sigma_{\text{true}}\text{/}\Sigma_{\text{obs}} \propto \left( R_{\text{true}}\text{/}R_{\text{obs}} \right)^{- 0.5}\) and \(M_{\text{obs}}\text{/}M_{\text{true}} \propto r_{\text{obs}}\text{/}r_{\text{true}}\). The model reproduces observed rotation curves (RMS residual \(\sim 34\) km/s). The geometric projection recovers the empirical RAR and shifts the BTFR slope from \(\sim 2.8\ \)in the true frame to \(\sim 3.7\ \ \)in the observer frame, and eliminats the normalization offset. Furthermore, The Mezzi scale factor \(\zeta\) governs mass and lensing corrections via distinct power laws: \(M_{\text{true}}\text{/}M_{\text{obs}} \propto \zeta^{- 1.84}\) and \(\alpha_{\text{true}}\text{/}\alpha_{\text{obs}} \propto \zeta^{- 1.26}\), revealing that geometric scaling affects dynamical mass more strongly than lensing mass. These results indicate that geometric projection effects may offer a phenomenological explanation for galactic dynamics, acting as a propagation level transfer function that leaves the baryonic stress-energy content and the weak field metric of the source frame untouched. For reproducibility, the code used for this analysis is publicly available at https://github.com/Brahim-Benaissa/Zeta.

Abstract: Causal-model arguments establish that a classical causal model reproducing Bell correlations while exhibiting no-signalling must be unfaithful: its no-signalling independences are not entailed by d-separation in the causal graph. Applied to time-symmetric, retrocausal, and all-at-once models, this is the fine-tuning objection. The resulting debate has largely concerned whether faithfulness is the appropriate norm, without a criterion for deciding particular cases or an associated measurement.This paper supplies a proposed criterion and establishes a precise symmetry result for the balanced binary singlet sector. If a nonnegative \(2\times2\) compatibility table has the simultaneous-outcome-flip symmetry \[ m_{++}=m_{--}, \qquad m_{+-}=m_{-+}, \] then every common scalar entrywise map \[ m_{xy}\longmapsto f(m_{xy}) \] with nonnegative output and nonzero normalization preserves uniform local marginals. No monotonicity, continuity, differentiability, or power-law assumption is required. Within two-qubit quantum kinematics with ideal analyzer projectors, joint rotational invariance and perfect same-axis anticorrelation force the singlet state and hence this pairing symmetry. The theorem establishes robustness relative to the symmetry-restricted deformation class; it does not confer causal faithfulness or robustness against arbitrary symmetry-breaking cellwise perturbations.The same singlet-plus-common-map structure has a deformation-independent surplus consequence: \[ E^f(\pi-\Delta)=-E^f(\Delta), \qquad E^f(\pi/2)=0. \] These angular identities are distinct from no-signalling and can fail experimentally. They provide the surplus consequence required by the proposed criterion in the balanced sector.A separate constant-flux completion law predicts an exactly flat ideal joint completion rate. We compare it with a Bell-local sign--cosine model followed by a joint two-bin selection rule. The pointwise maximal acceptance envelope for reproducing the singlet correlator has symmetric minima \[ Z^\ast\simeq0.878567 \] near \(46.44^\circ\) and \(133.56^\circ\). A flat calibrated joint acceptance rate above this value excludes that two-bin class. More generally, total variation gives \[ S_{\mathrm{obs}} \le \min\left\{ 4,\, 2+2\sum_{q\in Q}(1-Z_q) \right\}, \] so a flat rate above \[ \frac{5-\sqrt2}{4}\simeq0.896447 \] excludes every Bell-local measurement-independent selection model covered by this bound when \(S_{\mathrm{obs}}=2\sqrt2\).Finally, an exact eight-state reconstruction of a published post-processing model has acceptance rate \(3/4\) in every setting context while attaining the algebraic CHSH value \(4\). Its accepted laws satisfy \[ \Delta_Q=1, \qquad D_Q=\frac13, \] saturating both the selection-inflation lower bounds and the upper bounds permitted by the absolute rate. Thus rate flatness is not a certificate of fair sampling, although the absolute rate remains quantitatively useful. The quantity requiring structural certification is the conditional acceptance function, or a sufficient experimentally accessible proxy for it.