Abstract: To screen high-quality porcine-derived lactic acid bacteria for swine production, this study compared growth performance, acid production, acid and bile salt tolerance, and genome characteristics of Lactiplantibacillus plantarum (MRS002), Lactobacillus amylovorus (MRS003), and Ligilactobacillus salivarius (MRS004). All three strains showed typical anaerobic growth. L. amylovorus had a longer growth cycle and higher biomass, while L. plantarum and L. salivarius grew faster and produced more acid, with pH values reaching 4.2 and 4.3 at 24 h. L. plantarum and L. salivarius also exhibited higher survival rates under 0.3% bile salt and pH 2.0 stress. Genome annotation revealed that more than 50% of genes were related to metabolism in all strains. L. plantarum possessed the most comprehensive metabolic and stress-resistance gene networks; L. amylovorus was enriched in starch-degradation pathways; and L. salivarius showed unique advantages in aromatic amino acid metabolism. In summary, L. salivarius MRS004 displays superior probiotic traits, L. plantarum MRS002 has broad adaptability, and L. amylovorus MRS003 is suitable for high-starch feed fermentation. This study provides theoretical support and strain resources for probiotic development and antibiotic-free breeding.

Abstract: Understanding climate-streamflow dependencies is crucial for evaluating reservoir impacts and adaptive water management. This study analyzed streamflow in two key Brazilian reservoirs, Três Marias (São Francisco Basin) and Serra da Mesa (Tocantins Basin), using monthly records from 1979 to 2020. A 12-month moving average temporal filter enhanced low-frequency climate signals to assess hydrological variability and memory. Temporal smoothing substantially clarified climate–streamflow dependencies, with correlation gains reaching 106% for PDO, 204% for ENSO, and more than 4,200% for the Antarctic Oscillation (AAO) in Três Marias. The filtered analysis revealed contrasting hydrological memory structures: Três Marias exhibited multi-year memory with maximum correlations at approximately 22–27 months, while Serra da Mesa showed faster response times of 4–12 months. To evaluate predictive implications, streamflow forecasting was performed using two deep learning architectures: LSTM (recurrent neural network baseline) and TCN (temporal convolutional network). TCN substantially outperformed LSTM in Três Marias (R² = 0.95 vs. 0.05), demonstrating that convolutional architectures effectively exploit low-frequency persistence when scale-aware preprocessing reveals it. These findings show that temporal filtering provides an effective framework for detecting climate–streamflow dependencies and hydrological memory, with direct implications for seasonal-to-decadal forecasting and climate-informed reservoir management under changing conditions.

Abstract: Background: Postoperative hyperbilirubinemia is a serious complication after cardiac surgery and has been associated with increased perioperative morbidity and mortality. However, data specifically addressing patients undergoing redo valve surgery remain limited. This study aimed to determine the incidence and risk factors of postoperative hyperbilirubinemia after redo valve surgery, and evaluate its association with early postoperative outcomes. Methods: We retrospectively reviewed 259 adult patients who underwent elective redo valve surgery under cardiopulmonary bypass (CPB) between March 2018 and July 2024. Postoperative hyperbilirubinemia was defined as a serum total bilirubin level > 3 mg/dL at any time after surgery. Patients were divided into a hyperbilirubinemia group and a non-hyperbilirubinemia group. Perioperative variables were compared between groups. Univariable and multivariable logistic regression analyses were performed to identify risk factors for postoperative hyperbilirubinemia. Postoperative complications and in-hospital mortality were also compared. Results: Postoperative hyperbilirubinemia occurred in 101 of 259 patients (39.0%). Compared with patients without hyperbilirubinemia, those with hyperbilirubinemia had longer mechanical ventilation and intensive care unit stay, and higher rates of pneumonia, reintubation, tracheostomy, continuous renal replacement therapy, and in-hospital mortality. Univariable logistic regression showed that higher EuroSCORE II, higher preoperative total bilirubin and direct bilirubin levels, lower hemoglobin and platelet count, pulmonary hypertension, anemia, longer operative time, CPB duration, and aortic cross-clamp time, lower nasopharyngeal temperature, greater intraoperative blood loss, larger red blood cell and plasma transfusion volumes, and concomitant surgery on all three valves were associated with postoperative hyperbilirubinemia. Multivariable analysis identified elevated preoperative direct bilirubin, prolonged CPB duration, and more plasma transfusion as independent risk factors. Receiver operating characteristic analysis showed that peak postoperative total bilirubin was associated with in-hospital mortality, with an optimal cut-off value of 3.95 mg/dL (AUC 0.756, sensitivity 66.7%, specificity 80.2%, p = 0.003). Conclusions: Postoperative hyperbilirubinemia is common after redo valve surgery and is associated with worse early postoperative outcomes and higher in-hospital mortality. Elevated preoperative direct bilirubin, prolonged CPB duration, and more plasma transfusion are independent risk factors for postoperative hyperbilirubinemia in this high-risk population.

Abstract: Autocatalytic sets are chemical reaction networks in which the molecules mutually catalyze each other's formation supported by an ambient food set. They are believed to have played an important role in the origin of metabolism and life, and have been studied extensively both theoretically and experimentally. Autocatalytic sets often consist of a hierarchical structure of smaller and smaller autocatalytic subsets. Of particular interest are irreducible autocatalytic sets and closed autocatalytic sets. Previously, it has been shown that finding {\it all} such autocatalytic subsets is, in principle, intractable. Here, several algorithms are presented to enumerate irreducible and closed autocatalytic sets, either exhaustively (but only practical in limited cases) or in the form of a random sample. Their implementation in a C++ program, made available as a GitHub repository, is then tested on instances of a computational model of chemical reaction networks known as the binary polymer model.

Abstract: Containerized ornamental plant production requires efficient irrigation strategies to balance plant quality with water and nutrient conservation. This study evaluated the effects of different leaching fraction (LF) levels (0%, 20%, 40%, and 60%) on plant growth, ornamental quality, water use, and macronutrient leaching in off-season potted Curcuma cv. ‘Jasmine Pink’. Irrigation volumes were determined using crop coefficient (Kc)-based estimates derived from evaporation pan measurements. The results showed that the highest LF level (60%) significantly improved several ornamental quality traits, including flower number per cluster, leaf greenness, specific leaf area, and compactness index, while also increasing aerial dry weight and photosynthetic performance during the flowering stage. These improvements were associated with reduced substrate electrical conductivity, indicating that higher LF might effectively mitigated root-zone salt accumulation and promoted favorable physiological conditions for plant growth. However, increasing LF also resulted in greater irrigation water consumption and higher macronutrient losses through leachate, particularly for potassium. In contrast, lower LF treatments (0–20%) improved water use efficiency and reduced nutrient losses but showed moderate salt accumulation in the root zone, which slightly limited photosynthetic performance and ornamental development. Overall, the results indicate that a higher LF (60%) provides optimal plant growth and ornamental quality for off-season potted Curcuma production, although integrated strategies may be required to reduce water and nutrient losses. These findings provide practical insights for optimizing irrigation management in container-grown ornamental crops.

Abstract: Background. Alzheimer's disease (AD) is a progressive neurodegenerative disorder with a complex etiology, often diagnosed late in its course. Early detection of AD biomarkers could aid in timely intervention and management. Single-cell RNA sequencing (scRNA-seq) offers a powerful tool to unravel cellular heterogeneity and identify molecular signatures associated with disease states. Here, we employ scRNA-seq on peripheral blood samples to investigate potential predictive biomarkers for AD. Methods. We analyzed the publicly available scRNA-seq dataset GSE181279, comprising peripheral blood cells from three individuals with Alzheimer’s disease and two healthy controls. Single-cell RNA sequencing was performed on these samples to profile the transcriptomic landscape of individual cells. Bioinformatics analyses were employed to identify differentially expressed genes and cellular subtypes associated with AD pathology. Machine learning algorithms were utilized to develop predictive models based on gene expression patterns, aiming to discriminate between AD patients and healthy controls. Results. Our scRNA-seq (GSE181279) analysis revealed distinct gene expression profiles and cellular subtypes in peripheral blood samples from AD patients compared to healthy controls. We identified several dysregulated genes and cell populations associated with AD pathology, including immune cell activation and neuroinflammatory processes. Differential-expression and enrichment analyses identified candidate genes and pathways associated with immune activation, stress-response signaling, and altered cellular homeostasis in AD. In an exploratory leave-one-out analysis, a two-gene model incorporating BTG1 and DUSP1 separated AD from healthy controls within this very small dataset; these findings require validation in larger independent cohorts. Conclusions. This exploratory analysis suggests that peripheral-blood scRNA-seq may help identify candidate biomarkers associated with AD. The identified gene expression signatures and cellular subtypes associated with AD pathology provide valuable insights into the underlying molecular mechanisms of the disease. Furthermore, the development of accurate predictive models based on scRNA-seq data suggests a promising avenue for early diagnosis and intervention in AD. Further validation and prospective studies are warranted to assess the clinical utility and generalizability of these findings in larger cohorts.

Abstract: This study examines the role of entrepreneurship education quality in shaping students’ tourism development orientation through cognitive and capability-based mechanisms. In the context of developing countries such as Indonesia and Timor-Leste, strengthening entrepreneurial capacity is essential to support sustainable tourism growth. Using a quantitative cross-sectional design, data were collected from 348 university students enrolled in entrepreneurship-related programs across the two countries. The study employs Partial Least Squares Structural Equation Modeling (PLS-SEM), multi-group analysis (PLS-MGA), and fuzzy-set Qualitative Comparative Analysis (fsQCA) to test direct, mediating, and moderating relationships. The findings reveal that entrepreneurship education quality significantly enhances entrepreneurial self-efficacy, which in turn strengthens innovation capability, leading to higher entrepreneurial intention and ultimately tourism development orientation. However, no direct effect of education quality on entrepreneurial intention or tourism orientation was found, indicating full mediation. Entrepreneurship course experience positively moderates the relationship between education quality and self-efficacy, while prior entrepreneurial experience shows no significant moderating effect. Cross-national analysis indicates that the link between entrepreneurial intention and tourism orientation is stronger in Indonesia than in Timor-Leste. Overall, the study highlights the importance of fostering self-efficacy and innovation capability as key pathways through which entrepreneurship education contributes to tourism development.

Abstract: Urban areas are increasingly affected by geological and climate-driven processes that influence their safety, functionality, and long-term resilience. Conventional sustainability indicators mainly focus on anthropogenic impacts on the environment, while the role of subsurface conditions and physical processes shaping urban vulnerability remains underrepresented. To address this gap, the Urban Geo-climate Footprint (UGF) introduces an inverse perspective, assessing how geological and climatic factors exert pressure on urban systems. The methodology is based on the breakdown of geological effects into five drivers, Geology, Deep Geological Processes, Surface Processes, Exogenous and Climatic Processes, and Subsurface Anthropogenic Pressure. These drivers, in the derived tool, are articulated into 22 parameters evaluated from public datasets and expert judgment. These parameters are combined into a synthetic, standardised, reproducible and comparable index, the UGF Score Index (UGF-SI), ranging from 0 to 500 which enables direct comparison across cities and contexts. The application to 21 Italian cities highlights distinct spatial patterns, dominant drivers, and groups of cities facing similar geo-climatic challenges. The UGF framework represents a significant advancement in urban geoscience, supporting urban planning, risk awareness, and climate adaptation strategies by enhancing the understanding of subsurface-related pressures and promoting informed decision-making.

Abstract: Salinity represents a critical agricultural threat that reduces the productivity of several crops. Tomato (Solanum lycopersicum), recognized as the world´s second most significant horticultural commodity globally, is salt-sensitive. This research evaluated seed priming treatments (hydro, halo, bacterio, and halo-bacterio) at different phenological stages under two salinity conditions (0 and 16 mM NaCl) as a biotechnological alternative to mitigate salt stress and increase production. Using physiological variables and multivariate statistical analyses, this research demonstrated that priming treatments modified the physiological, nutritional, and productive metabolism of tomato plants. Bacteriopriming, using an endophytic and halophytic bacterial consortium isolated from halophytes, enhanced germination variables and N, P, Ca and Zn absorption in seedlings. In the vegetative and reproductive stage and under stress, halo-bacteriopriming consistently enhanced concentrations of K, Mg, and Zn in leaves and fruits, but decreased Na absorption. This nutritional balance allowed not only a higher concentration of chlorophyll but also a significant increase in yield and beta-carotene concentration in tomato fruits. For the first time, this research demonstrated that the halo-bacteriopriming with this kind of bacteria is a biotechnological strategy to mitigate saline stress, optimizing not only tomato growth, but also its nutraceutical quality. It significantly outperformed the plant response in all stages of development compared to those from control, hydro, and halo-primed treatments.

Abstract: Chirality has emerged as a critical determinant in the design, efficacy, and environmental behavior of modern insecticides. While a significant proportion of agrochemicals are inherently chiral, most are still commercialized as racemic mixtures, despite well-documented differences in biological activity, toxicity, and degradation pathways between enantiomers. In this review, we provide a comprehensive and critical analysis of advances in the stereoselective synthesis and resolution of chiral insecticides, with particular emphasis on neonicotinoids, pyrethroids, and oxadiazines, including indoxacarb. A systematic survey of the literature (1985–2025), including peer-reviewed articles and patents, reveals that multiple strategies have been developed to access enantiomerically enriched compounds, including asymmetric organocatalysis, transition-metal catalysis, chiral-pool approaches, biocatalytic transformations, and chromatographic resolution techniques. Among these, recent developments in photoredox catalysis, recyclable metal complexes, and enzyme-mediated processes have significantly improved enantioselectivity and scalability, bridging the gap between academic methodologies and industrial applications. Despite these advances, challenges remain in achieving cost-effective, sustainable, and universally applicable asymmetric processes. Importantly, the relationship between stereochemistry and biological performance underscores the need for integrating synthetic chemistry with toxicological and environmental studies. Future directions point toward the incorporation of green chemistry principles, continuous-flow processes, and computational tools, including machine learning and molecular modeling, to accelerate the rational design of enantiopure agrochemicals. This review highlights both the progress achieved and the critical gaps that must be addressed to realize the potential of stereoselective insecticide development fully.

Abstract: A carbon element exhibits complex behavior. It can be due to its various allotropes. From various carbon precursors, a carbon material can result. The published studies on carbon-based materials are not groundbreaking enough. The discussed results also lack the original science and engineering of carbon materials. The study of each carbon allotrope is a first need. It should follow the binding of the same-state atoms. Depending on the processing conditions of a carbon precursor, a carbon atom can change its state behavior. In the state conversion of a carbon atom, the energy bits shaped-like dashes transfer electrons to nearby unfilled states. The involved dash-shaped energy bit maintains partially conserved behavior. Atoms in the graphite state also study a one-dimensional structure under the execution of electron dynamics. A structure in the nanotube atoms is two-dimensional. A fullerene structure is four-dimensional. In the structural formation of diamond, lonsdaleite, or graphene, the energy bits shaped like a golf stick bind their atoms. The binding of the diamond atoms is from the surface to the south, whereas the formation of a diamond structure is from the south to the surface. In the structural formation of a glassy carbon, the layers of gaseous, graphitic, and lonsdaleite atoms bind simultaneously. The motivation behind this study is to explore the atomic structure in carbon, state conversion, binding in carbon atoms, the glassy carbon structure, and the hardness of carbon materials. It provides a new insight into the basic and applied science of carbon-based materials.

Abstract: Background/Objectives: Glioblastoma (GBM) remains a lethal primary CNS malignancy with limited response to immunotherapy. Adoptive cellular therapy (ACT) improves survival in preclinical models, yet tumors ultimately recur. While T cell exhaustion is a common mechanism of resistance, the contribution of dendritic cell (DC) dysfunction remains unclear. We aimed to define mechanisms of immune escape following ACT, focusing on DC function and the role of hypoxia. Methods: Using a murine glioma model (KR158B), mice were treated with ACT consisting of tumor RNA–pulsed DC vaccines and adoptively transferred T cells. Tumor-infiltrating immune populations were analyzed by flow cytometry. DC function was assessed using T cell activation assays. Bulk RNA sequencing and gene set enrichment analysis were performed on sorted DCs. Hypoxia was modeled in vitro, and HIF1α was perturbed using CRISPR-mediated knockout. Results: ACT significantly increased survival but did not prevent tumor recurrence. Escaped tumors contained abundant cytotoxic, non-exhausted T cells, indicating that T cell dysfunction was not the primary driver of resistance. Instead, tumor-associated DCs exhibited impaired T cell activation despite preserved antigen uptake. Transcriptomic analyses revealed reduced antigen presentation and co-stimulatory signaling, alongside increased expression of tolerogenic factors. ACT-treated tumors demonstrated heightened hypoxia pathway activation, with elevated HIF1α expression in DCs. Hypoxia induced DC tolerogenic programs and reduced their ability to activate T cells, an effect partially reversed by HIF1α disruption. Increased immune infiltration and inflammation following ACT further amplified hypoxia signaling. Conclusions: DC dysfunction is a key mechanism of immune escape following ACT in glioma. Hypoxia-driven tolerization of DCs impairs sustained anti-tumor immunity, highlighting the hypoxia–DC axis as a promising therapeutic target to enhance immunotherapy efficacy.

Abstract: Acute respiratory failure (ARF) often leads to ICU admission, ventilatory support, illness, and death. The usual classification into hypoxemic and hypercapnic types does not capture its full complexity. Precision medicine uses the idea of “treatable traits” to guide care based on traits that are clinically relevant, identifiable, measurable, and possibly changeable. Arterial carbon dioxide pressure (PaCO₂) reflects factors like alveolar ventilation, dead space, respiratory mechanics, and how patients respond to ventilatory support. This makes it a clinically relevant variable in selected situations in certain situations. We carried out a scoping review using PRISMA-ScR and JBI guidelines (OSF post hoc protocol https://osf.io/vszkg) to summarize evidence on hypocapnia and hypercapnia as prognostic, stratification, or clinically relevant variables during respiratory support. We searched PubMed/MEDLINE, ScienceDirect, and Web of Science (1994–2025), and checked references by hand. Thirty-four studies met our criteria and were grouped into four areas: pre-intubation or early acute presentation, non-invasive support (NIV/HFNC), invasive mechanical ventilation, and weaning or post-extubation. In summary, hypocapnia was linked to worse outcomes or failure of support in hypoxemic or cardiogenic cases. Hypercapnia helped identify patients who benefited from NIV, such as those with COPD or obesity-hypoventilation. For invasive mechanical ventilation, the effects depended on the presence and severity of acidosis and how long it lasted. We found that PaCO₂ is measurable and clinically important, but whether it can be targeted for treatment depends on the situation. More research is needed to set safe limits and practical targets.

Abstract:

Extracting high-molecular-weight (HMW) DNA from cactus tissues remains technically challenging due to the abundance of mucilage, pectins, polyphenols, and other metabolites that compromise DNA purity, increase viscosity, and reduce integrity, thereby limiting its suitability for long-read sequencing. This constraint is particularly relevant in Selenicereus megalanthus, a crop of increasing agronomic and genomic importance for which optimized protocols for third-generation sequencing remain limited. Here, we compared four CTAB-based DNA extraction protocols using dehydrated cladode tissue and evaluated DNA quality using NanoDrop spectrophotometry, Qubit fluorometry, agarose gel electrophoresis, and functional validation via sequencing on the Oxford Nanopore PromethION 2 Solo platform. Among the tested methods, our proposed optimized mucilage-adapted CTAB (MuCTAB) protocol, comprising 4% CTAB, 4% PVP-40, 0.5% β-mercaptoethanol, and proteinase K, showed the best overall performance. MuCTAB yielded the highest dsDNA concentration (239.63 ± 34.37 ng/µL), optimal purity ratios (A260/A280 = 1.96 ± 0.05; A260/A230 = 2.01 ± 0.01), and superior DNA integrity. Nanopore validation confirmed its effectiveness, producing the highest sequencing yield (84.2 Gbp), read count, N50 (40.3 kbp), and maximum read length (1.9 Mbp). Overall, MuCTAB represents a low-cost, reproducible, and efficient method for HMW DNA extraction from mucilage-rich pitahaya tissues and other recalcitrant plant species.

Abstract: Leveraging its exceptional ultra-low altitude flight capability and high economic effi-ciency, the unnamed Wing-in-Ground (WIG) craft offers unique advantages in mari-time missions such as island patrol and rapid replenishment. However, the path plan-ning for unnamed WIG crafts faces the dual challenge of precise obstacle avoidance and ultra-low altitude maintenance, due to the obstacle distribution in island regions and the altitude window constraints inherent to ground effect flight. To address this, this paper proposes a path planning method based on an improved hybrid Sparrow Search Algorithm and Grey Wolf Optimizer. This method integrates the swarm intel-ligence of the Sparrow Search Algorithm, employs a self-destruction mechanism to es-cape local optima. Furthermore, it combines the hierarchical guidance of the Grey Wolf Optimizer to enhance convergence accuracy. The algorithm integrates ground-effect maintenance constraints and a reef threat model, and smooths the final path using cubic B-spline curves. Simulation results demonstrate that the proposed algorithm outperforms the standard Sparrow Search Algorithm, Grey Wolf Optimizer, and Particle Swarm Optimization in terms of convergence speed, optimization accu-racy, and obstacle avoidance success rate. It is capable of generating a feasible, safe, and smooth path, thereby supporting the autonomous navigation of unmanned WIG crafts in island reef waters.

Abstract: Background/Objectives: Blast-crisis chronic myeloid leukemia (BC-CML) represents a genomically unstable, therapeutically refractory phase driven by clonal evolution beyond BCR::ABL1 dependence. Clinical outcomes remain poor, with median survival under one year. Mutation-level analyses inadequately resolve biological heterogeneity or inform rational patient-specific therapy. We therefore implemented a mutational process–anchored framework integrating genomics, machine learning (ML), and artificial intelligence (AI)–guided drug prioritization at single-patient resolution. Methods: Whole-exome sequencing, COSMIC mutational signature deconvolution, unsupervised ML clustering, and AI-guided pharmacogenomic prioritization were applied to 224 patients with CML (190 chronic phase, 15 accelerated phase, 19 blast crisis) and 19 healthy controls. Results: Mutation burden increased significantly with disease progression, and blast crisis exhibited complex co-mutation architectures involving TP53, BRCA2, IDH1/2, DNMT3A, JAK2, and CSF3R. While gene-level patterns were heterogeneous, dominant mutational processes converged across cases. COSMIC signature extraction stratified BC-CML into three biologically coherent clusters: homologous recombination deficiency/genomic instability (Signatures 3/5), epigenetic–metabolic dysregulation (Signatures 1/2), and oxidative stress–associated cytokine signaling mutagenesis (Signatures 13/18). These process-defined states mechanistically link DNA repair failure, chromatin remodeling, and inflammatory signaling to blast transformation. Integration with an AI-guided pharmacogenomic framework translated signature biology into rational, cluster-specific therapeutic prioritization, including PARP inhibition, IDH targeting, CDK4/6 blockade, JAK pathway inhibition, and redox-modulating strategies. Dominant signature resolution reduced multidrug ambiguity and supported single-patient therapeutic parsimony. External concordance assessment across independent pharmacogenomic datasets supported predicted vulnerabilities. Conclusions: This study establishes a mechanistically interpretable, process-anchored precision oncology framework for BC-CML linking genomic architecture to actionable therapeutic decision-making warranting clinical validation. The approach can further be implemented for AL-AI-prioritized precision treatment of other relapsed, refractory and metastatic cancers.

Abstract: Background/Objectives: This study describes the development and validation of the Danish Sentence Test (DAST), a Danish-language, adaptive speech-in-noise test constructed from a linguistically balanced corpus using a template-based method. This approach enables controlled linguistic variation while maintaining lexical consistency and may serve as a model for developing similar speech materials in other languages. Methods: Sentences spoken by one female talker from the DAST corpus were sorted into 44 balanced lists of 20 sentences using a psychometric optimization procedure. Speech reception thresholds (SRTs) were measured in 20 normal-hearing participants using headphone playback with speech-shaped noise. Results: The mean SRT across lists was −5.3 dB SNR, with list means within ±0.5 dB of the grand average. The average within-subject standard deviation was 0.7 dB, and the grand average psychometric slope was 18.5%/dB. A relatively small training effect was observed, consistent with the use of linguistically varied, low‑predictability material. Conclusions: DAST provides a linguistically rich and psychometrically well-controlled speech-in-noise test with substantially more material than existing Danish corpora. The template-based method and optimization approach may be of broader methodological interest for developing speech materials in other languages. DAST complements existing Danish-language tests and enables more extensive assessments of speech understanding, including studies requiring large numbers of non-repeated sentence lists.

Abstract: With the increasing availability of high-resolution (< 50m) space borne night time light imagery, it is now becoming more feasible to examine the correspondence between space borne and ground based measurements of night lights. However, so far there were very few studies that conducted a ground-based campaign of night time brightness measurements during the overpass of a night light sensitive satellite. Here we tested whether the correspondence between measurements is higher when ground-based are conducted at the same time of the satellite overpass. We conducted measurements using a LANcube photometer along the same route in two consecutive nights (27-28 Aug 2025) in Brisbane, Australia, and compared them with a SDGSAT-1 (10-40m) and Haishao-1 (10m) images acquired concurrently at the evening, and with an early morning ISS photo (8m) acquired three months earlier. We found the correlation between ground based and space-borne measurements was not higher for simultaneous measurements, and the explanatory power of our model predicting night time brightness as measured from space increased when including horizontal and upwards ground-based brightness measurements along-side variables of canopy height, land use and road hierarchy. We confirmed the importance of multi-directional ground measurements and urban structure for understanding night-time brightness levels measured from space.

Abstract: This paper explores a novel operator-theoretic framework for analyzing the zeros of the Riemann zeta function within the critical strip. By constructing a differential interaction operator $\Phi(s, \delta)$ on the Hilbert space $l^2(\mathbb{N})$, we investigate the geometric properties of the operator trace off the critical line $Re(s) = 1/2$.Our analysis utilizes a Master Inequality applied to the resulting phase torque $J(\delta, t)$, suggesting that a hyperbolic sine bias creates an analytical “floor” resistant to the interference of the infinite tail. Furthermore, by invoking Baker’s Theorem on Linear Forms in Logarithms, we examine the conditions under which the truncated Head ($N \approx t^{(A+1)/\sigma}$) maintains signal dominance. Within the specific constraints of this operator construct, the results provide evidence for the exclusion of zeros off the critical line, offering a potential path toward understanding the confinement of non-trivial zeros to $Re(s) = 1/2$.

Abstract: We investigate how the flow of energy across different scales affects the regularity of solutions to the three-dimensional Navier–Stokes equations, which describe the motion of viscous incompressible fluids. Using tools from harmonic analysis (the Littlewood–Paley decomposition and Bony’s paraproduct), we give a precise definition of the energy flux from one scale to the next and prove a new criterion for when a solution stays smooth. Our main result shows that if a weak solution belongs to a certain critical Besov space and, in addition, the weighted cumulative energy flux decays faster than the critical Onsager rate, then the solution can be extended smoothly past any potential blow‑up time. The proof uses a weighted dyadic estimate, Bernstein’s inequality, and an interpolation argument that leads to a Serrin‑type condition. The borderline case corresponds exactly to the Onsager threshold for energy dissipation; any improvement beyond that threshold guarantees regularity. This establishes a rigorous link between the turbulence energy cascade and the prevention of singularities. The criterion is physically transparent, quantifies how much kinetic energy is transferred to very small scales, and provides a new diagnostic for numerical simulations. Our work contributes to the long‑standing effort to understand the global regularity problem for the Navier–Stokes equations, one of the Clay Millennium Prize Problems.