Abstract: Type 2 diabetes mellitus (T2DM) is a highly prevalent and devastating chronic metabolic disease worldwide, with its pathogenesis centrally characterized by insulin resistance and pancreatic β-cell dysfunction. Accumulating evidence has demonstrated that glucose metabolic reprogramming represents an adaptive metabolic shift from oxidative phosphorylation to aerobic glycolysis in cells in response to a hyperglycemic microenvironment, which acts as an upstream core event driving the initiation and progression of T2DM. This review systematically elaborates the characteristics of glucose metabolic reprogramming in insulin-sensitive target organs under T2DM conditions, including the liver, skeletal muscle, adipose tissue and pancreatic β-cells, and further dissects four major downstream effector mechanisms: mitochondrial energy metabolism disturbance, augmented oxidative stress, disruption of mitochondria-associated endoplasmic reticulum membranes (MAMs) coupled with calcium homeostasis imbalance, and systemic inflammatory response. On this basis, we summarize the intervention strategies targeting the above signaling pathways, including antioxidant therapy, restoration of MAMs integrity and calcium homeostasis, systemic anti-inflammatory intervention, and multi-target regulatory effects of traditional Chinese medicine. Current studies have indicated that early intervention in downstream stress events induced by glucose metabolic reprogramming, particularly the preservation of MAMs integrity, restoration of calcium homeostasis, and inhibition of NLRP3 inflammasome activation, is expected to block or delay the progression from prediabetes to clinical T2DM. Nevertheless, substantial gaps still remain in the understanding of the dynamic regulatory mechanisms of MAMs, tissue-specific therapeutic targets, and relevant clinical translational research. Future integration of multi-omics technologies will provide novel therapeutic strategies and theoretical foundations for the early prevention and treatment of T2DM.

Abstract: A numerical study of shock wave propagation through multiple raindrops is presented using a density-based compressible two-phase flow solver coupled with a sharp-interface volume-of-fluid (VoF) method. The piecewise linear interface calculation (PLIC) approach is employed to reconstruct gas–liquid interfaces and capture droplet deformation during shock interaction. The numerical framework is first validated using a one-dimensional gas–liquid shock tube problem and a shock–helium bubble interaction benchmark. The method is then applied to investigate shock interactions with single, double, and multiple raindrops under compressible flow conditions. Numerical results show that complex wave structures, including shock reflection, diffraction, and wave interference, develop during shock propagation through raindrop fields. Interactions between neighboring droplets lead to local pressure amplification and non-uniform flow structures.

Abstract: With the increasing penetration of wind power, the uncertainty of wind power generation poses greater challenges to the secure operation of power grids. This paper proposes WindPower-SAFusion, an improved Informer-based model for wind power forecasting. The proposed model optimizes long-sequence modeling from three aspects. First, ProbSparse self-attention is adopted to reduce the computational complexity from O(L2) to O(LlogL). Second, a convolutional distillation encoder is introduced to compress the input sequence and highlight key temporal features. Third, a multivariate fusion and recursive multi-step forecasting framework is constructed. Using historical power and wind speed information, experiments are conducted on measured data from the Daliang Wind Farm in Guazhou, Gansu Province, China. The results show that the proposed model significantly outperforms several mainstream forecasting models in 1-day, 3-day, and 7-day forecasting tasks. Ablation experiments further demonstrate that each core module plays a critical role in improving forecasting accuracy and generalization performance. Therefore, the proposed method provides a technically feasible solution with promising engineering application potential for power grid dispatching and wind power management.

Abstract: Three coherent wave sources at 120^◦ separation produce hexagonal interference patterns whose lattice constant reaches a minimum of a = 2λ/3, the rational fraction that also defines the charged-lepton Koide ratio Q = 2/3. Integer-wavelength resonances occur at sinθ = 2/(3N); at N = 3, exactly three wave lengths fit per cell, suggesting a geometric interpretation of the same rational value 2/9 that appears as Shulga’s compact-cycle offset in the charged-lepton spectrum. The geometric-mean interpolation between adjacent resonance scales is modeled on the Dykhne effective-medium theorem for two-phase Z₂-symmetric boundaries. These condensed-matter structures (C₃ phase cancellation, standing-wave resonance, and effective-medium interpolation) motivate a companion identity (the Fidentity) that reduces to the classical Descartes circle theorem at Q = 2/3. Applied to charged-lepton masses with a single input µ_⋆ = m_ℓ = 1883.1 MeV, the construction yields closed-form candidate expressions for three light-quark masses (m_s, m_d, m_u), with internal self-consistency at 0.06% and an up-quark value m_u = 2.22 MeV (+0.23σ from PDG, within current uncertainties). Whether these correspondences between wave interference geometry and the fermion mass spectrum reflect an underlying physical connection or are structural parallels between C₃ × Z₂ systems is an open question that we propose merits investigation.

Abstract: Maize is a major global crop; however, its production is affected by Fusarium verticillioides (Fv), which causes stalk, ear, and root rot (SERR). Bacillus cereus B25 is a maize bacterium that antagonizes Fv, likely through antifungal compounds and possibly by inducing of maize chitinase genes. Fv effectively infects maize by producing a chitinase-modifying protein (Cmp) that disrupts maize chitinases, preventing fungal cell wall degradation and evasion of plant immune responses triggered by PAMPs. The aim of this work was to analyze maize, B25, and Fv gene expression during bipartite and tripartite interactions at early stages (5, 7, 10, and 14 days post-inoculation). Physiological results showed increased root and shoot growth in maize seedlings under the tripartite interactions compared to Fv alone. B25 was demonstrated to grow endophytically and coexist with Fv in maize roots. Maize extracellular chitinase genes were induced, possibly due to chitin fragments released from the fungal cell wall, while Fv genes were also upregulated in response. Furthermore, the chitinase gene Zm00001eb317090 (bk4) may contribute to cell wall strengthening, as suggested by in silico co-expression analyses. Overall, these results support a coordinated interaction between maize and B25 that contributes to controlling Fv infection.

Abstract: This paper presents an Adaptive Quantum Fuzzy Logic (ALFQ) control strategy applied to an induction motor (IM) supplied by a hybrid renewable energy system integrating photovoltaic (PV), wind, and thermoradiative (TR) energy sources. Conventional Vector Control (VC) and classical Fuzzy Logic Control (FLC) approaches are not fully developed in this study; instead, their main limitations and performances reported in the literature are used as comparative references in order to focus on the proposed quantum-based control strategy. The main objective is to investigate the dynamic response, robustness against parameter uncertainties, harmonic performance, and adaptability of the proposed ALFQ controller under varying operating conditions. The ALFQ approach combines fuzzy inference mechanisms with quantum-inspired optimization algorithms capable of automatically adjusting the membership functions and minimizing the speed tracking error. Simulation results obtained under MATLAB/Simulink demonstrate that the proposed ALFQ controller significantly improves the dynamic behavior of the induction motor drive. The obtained results show fast response time, quasi-zero overshoot, negligible steady-state error, reduced current ripple, and lower Total Harmonic Distortion (THD). The controller also exhibits excellent robustness against rapid load disturbances, rotor resistance variations, and nonlinear operating conditions. A comparative analysis based on literature results confirms that the proposed ALFQ strategy outperforms conventional VC and classical FLC approaches in terms of tracking accuracy, robustness, harmonic reduction, and global dynamic stability. These results demonstrate the effectiveness of quantum-inspired fuzzy optimization for high-performance induction motor drives supplied by hybrid renewable energy systems.

Abstract: Multi-document summarization (MDS) under strict context budgets is acutely vulnerable to hallucination, cross-document contradiction, entity drift, and redundant paraphrasing. Existing models address these issues only implicitly through training objectives, leaving decoding as an ad-hoc pipeline layered on maximum-likelihood generation. Arguing that faithfulness is fundamentally a constraint satisfaction problem rather than a fluency optimization problem, we introduce FADCO (Faithfulness-Aware Decoding via Constrained Optimization). FADCO is a model-agnostic inference-time framework that encodes evidence grounding, non-contradiction, and redundancy control as explicit constraints within a Lagrangian-relaxed objective. To support this framework, we formally diagnose and resolve beam collapse, a failure mode in which standard beam search degrades constrained selection to greedy decoding, by employing a mixed candidate pool that increases verifier support diversity. Furthermore, we resolve log-probability scale dominance through rank-based multi-objective aggregation and introduce a bounded local repair operator with provable termination and edit minimality guarantees under a strict retry budget of R=3. Evaluated on MultiNews using MiniCheck-FlanT5, QA-F1, and NLI entailment, preliminary stratified validation demonstrates that bounded self-healing improves MiniCheck scores by 65.7 percent and NLI entailment by 59.0 percent, while reducing contradictions by 5.8 percent. These gains incur only a negligible 0.69 percent ROUGE-1 trade-off, demonstrating a highly favorable faithfulness-fluency Pareto frontier for inference-time decoding interventions.

Abstract: Low productivity in sub-Saharan Africa is closely linked to declining soil fertility and suboptimal fertilizer use. While balanced fertilization can improve yields and sustain soils, evidence for fertilizer optimization in smallholder maize systems remains limited and site-specific. This study evaluated maize yield responses to various of N, P, K, and secondary and micronutrients (SMN) combinations across agroecological zones (AEZs) in Uganda. Multi-location trials were conducted on 101 farms over two seasons using a randomized complete block design, with varying N and P rates in combination with K and SMN applications. Results indicate strong heterogeneity of maize yields across AEZs mostly due to soil properties. Nitrogen was the most dominant yield limiting nutrient. The N × P interaction was not significant (p > 0.05). Nitrogen response followed a quadratic trend, with strong yield gains (45–132%) at 30–80 kg N ha⁻¹ but gains beyond 120–160 kg N ha⁻¹, were not significant. Responses to K and SMN were inconsistent and site-specific. AEZ explained 77% of yield variation, fertilizer treatments 13%, with soil properties accounted for additional explanatory power. These findings highlight the emphasis on prioritizing N management with adequate P supply and guided, site-specific K and SMN applications.

Abstract: International Political Economy (IPE) confronts a moment of genuine intellectual reckoning. The theoretical frameworks that defined discipline during the three decades following the Cold War—anchored in liberal assumptions concerning convergence, institutionalized cooperation, and the pacifying logic of economic interdependence, are increasingly strained by a world they were not constructed to explain. The 2020s have delivered a compounding cluster of structural disruptions: systemic rivalry between liberal and non-liberal states, the existential imperatives of climate change and the distributional politics of the green energy transition, the deliberate weaponization of economic interdependence as an instrument of statecraft, the emergence of an intangible platform economy that defies established regulatory categories, and the deepening entanglement of geopolitics with international finance. Against this backdrop, this paper identifies and analyzes five foundational research gaps that collectively define the frontier of contemporary IPE scholarship: (a) the retreat of liberal ontology and the ascendance of non-liberal economic orders; (b) the material politics of climate change and the green transition; (c) the return of interstate war and the re-militarization of economics; (d) the analytical challenge of digital sovereignty and the intangible economy; and (e) the imperative to re-center politics in the study of global finance. Drawing on a systematic synthetic literature review and comparative conceptual analysis, the paper integrates twenty-three analytical tables and two original figures. These visual instruments function not as summaries but as structured devices for mapping conceptual terrain that prose description alone cannot fully render. The paper argues that none of these gaps can be addressed through incremental refinement of existing frameworks; each requires a more fundamental rethinking of the ontological and epistemological commitments that have shaped IPE over five decades. Addressing them demands genuine methodological pluralism—the productive integration of quantitative, formal, qualitative, and historical approaches. The crisis of relevance confronting IPE is real, yet it is simultaneously an opportunity to construct a discipline more intellectually honest and analytically adequate to the world it seeks to explain.

Abstract: The World Health Organization recognizes mosquito-borne viruses as a global public health threat with pandemic potential and has called on countries to prepare for the next pandemic. ZIKV is an important mosquito-borne virus with pandemic potential. Its unique neurotropism and vertical transmission capacity constitute special pathogenic and transmission risks. The prevention and control of ZIKV faces significant challenges due to the lack of vaccines and therapeutics. ZIKV entry into host cells is the initial step in establishing infection, and research on its entry mechanisms provides the fundamental theoretical basis for the development of anti-ZIKV entry inhibitory drugs. This review will summarize recent research findings from the perspectives of ZIKV receptor selection, membrane fusion mechanisms, and entry inhibitor research, aiming to provide concise information for a deeper understanding of ZIKV entry mechanisms.

Abstract: The rapid advancement of quantum computing poses a fundamental threat to classical public-key cryptographic systems, necessitating the transition to post-quantum cryp-tography (PQC). While significant progress has been made in the standardization of quantum-resistant algorithms, their practical deployment in heterogeneous environ-ments—particularly resource-constrained Internet of Things (IoT) devices—remains a critical challenge. This study presents a comprehensive experimental evaluation of four NIST-standardized PQC algorithms: CRYSTALS-Kyber (ML-KEM), CRYS-TALS-Dilithium (ML-DSA), FALCON, and SPHINCS+. The analysis is conducted across two distinctly different hardware platforms: a high-performance x86-64 system (AMD Ryzen 7 5700U) and a resource-constrained embedded microcontroller (ESP32-WROOM). Implementations were developed in C, Go, and Python to assess the influence of programming environments on algorithmic efficiency. The evaluation focuses on key performance indicators, including computational la-tency, memory consumption, communication overhead, and temporal determinism, based on extensive benchmarking over 1,000 iterations. Experimental results demon-strate significant trade-offs between security level, execution performance, and re-source utilization. Lattice-based schemes such as Kyber and Falcon exhibit superior ef-ficiency and scalability on embedded platforms, while Dilithium encounters stability limitations due to memory constraints. In contrast, SPHINCS+ provides strong security guarantees and architectural robustness at the cost of higher computational overhead. The findings highlight the critical role of hardware-specific optimizations and soft-ware design choices in enabling practical PQC deployment. This work provides ac-tionable insights for selecting and tuning post-quantum algorithms in real-world sce-narios, supporting the secure migration of IoT and distributed systems toward quan-tum-resilient infrastructures.

Abstract: 15% of all soft tissue tumors are located on the hand and wrist. Only 2% of lesions are malignant. Considering that most masses are benign, if clinical evaluation and ul-trasound show frankly benign features for lesions smaller than 3 cm, a primary exci-sional biopsy is justified. If the history and clinical evaluation or imaging show fea-tures suggestive of malignancy, a second-level imaging method is indicated. Treatment in a non-oncology center including unplanned excision does not influence the progno-sis. The primary objective of the study is to evaluate the effectiveness of our treatment method for wrist and hand tumors smaller than 3 cm in size, with primary excisional biopsy performed as an outpatient surgery procedure, following a clinical and anam-nestic assessment and ultrasound imaging, in terms of functional and aesthetic benefit and reduction of any painful symptoms. The secondary objectives are to demonstrate the advantages of treating these tu-mors with our procedure in limiting the overload of specialist oncology centers and to evaluate the outcomes of the excisional biopsy in terms of prognosis in patients who tested positive for malignant disease at histological examination. In the present study, we retrospectively analyzed 209 specimens from surgical ex-cision of masses with a diameter of less than 3 cm involving the wrist and hand from 01/01/2015 to 01/06/2024, from a patient aged over 18 years. In our clinic, during the first outpatient visit, the patient's medical history is collected, a clinical evaluation is performed, first-level tests such as X-rays are performed, and any ultrasound exami-nations are acquired. If no risk factors or red flags for malignant pathologies emerge, the patient is offered excision under outpatient surgery. On the day of surgery, ultrasound examinations are acquired, local anesthesia is performed with the WALANT technique, and the mass is excised. At the end of the procedure, the specimen is sent to pathology for histological examination. The most frequent histological diagnosis was ganglion cyst (44,98%) the second diagnosis in frequence was giant-cell tumor of the synovial sheath (15,32%). Only one case (0,48%) had a diagnosis of malignant disease. According to our method, in accordance with the literature, tumors < 3 cm in size can be treated with excisional biopsy, without necessarily overloading specialized on-cology centers for such tumors.

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.