Abstract: A neural model for the formation of visual engrams is proposed, operating according to a non-Hebbian principle — specifically, through the enhancement of inhibitory synapses, up to and including the formation of veto synapses. The model relies on two hypothetical mechanisms: (1) rapid, repetitive reactivation ("ripple-reverberation") and (2) high-frequency synchronization enabling the activation of inhibitory synapses, which consequently become veto synapses. Through such learning, "neural locks" for familiar patterns are formed in memory. This model constitutes a component of a more general top-down model of visual recognition described previously (Levashov & Safiulina, 2025). The problem of processing activity patterns in living neural networks is discussed, as these patterns are not holistic but rather manifest as a mosaic of activated and non-activated neurons.

Abstract: Westudy coupled geometric flows involving the metric, dilaton, and flux fields arising from worldsheet β-functions in string theory. Extending the Ricci flow formalism, we derive parabolic evolution equations governing these fields and prove short-time exis tence and uniqueness for SU(3)-structure compactifications. We establish monotonicity properties of flow functionals analogous to Perelman’s entropy and identify conditions for moduli stabilization in type II backgrounds. Our results unify Ricci-type flow techniques with flux compactifications and suggest new mathematical tools for analyzing dynamical string backgrounds and quantum gravity.

Abstract: Background and Objectives: Minimally invasive cervical spine surgery (MIS-CSS) re-lies heavily on intraoperative fluoroscopic imaging, raising concerns about radiation exposure to patients and surgical staff. Unlike lumbar MIS, cervical-specific radiation exposure has not been systematically reviewed, despite distinct anatomical considera-tions including proximity to the thyroid gland and lens of the eye. This review aims to quantify intraoperative radiation exposure during MIS cervical spine procedures and evaluate available dose-reduction strategies. Materials and Methods: A systematic literature search was conducted across Pub-Med/MEDLINE, Scopus, and Google Scholar in April 2026 following PRISMA 2020 guidelines. Studies reporting original quantitative radiation data during minimally invasive cervical spine procedures in adult patients (≥10 patients) were included. Quality was assessed using the MINORS tool and JBI checklist. Results: Seven studies encompassing 380 patients were included. Procedures com-prised ACDF (four studies), minimally invasive posterior cervical laminoforaminotomy (two studies), and CT-navigated cervical instrumentation (one study). Patient effective doses during ACDF ranged from 0.015 to 1.3 mSv, with thyroid doses of 0.194–0.290 mGy. Standalone ACDF reduced patient dose by 36–58% compared to plated ACDF (p < 0.001). Navigation-assisted posterior cervical foraminotomy achieved a median fluoroscopy time of 10 seconds with negligible staff exposure. Surgeon per-procedure exposure during cervical discectomy (chest 0.122 µSv, lens 3.1 µSv, hands 7.1 µSv) was approximately half that of lumbar discectomy. Conclusions: Radiation doses during individual MIS cervical procedures are generally within occupational safety limits; however, cumulative exposure warrants attention in high-volume surgeons. Standalone implant designs and intraoperative navigation represent effective, complementary dose-reduction strategies. Standardized prospec-tive research is needed to establish cervical-specific radiation safety benchmarks.

Abstract: Maximal symmetry of the conformal FLRW frame \( \bar{g}=a(t)^{-2}g \) only admits constant curvature solutions, where constant matter density \( \bar{\rho}_{\textrm{m}}=R_{0}^{-2} \) constrains cosmology to a hyperbolic de Sitter solution \( a(t)=\textrm{sinh}(2t/R_{0})^{\frac{1}{2}} \), including reparametrizations like the \( \Lambda\textrm{CDM} \) solution \( \hat{a}=a^{4/3} \). Equipartition of the nonlocal gravitational field energy at the horizon shows equilibrium of Ricci (matter) and Weyl(BAO) densities of \( 12R_{0}^{-2} \) each, or \( \bar{H}_{0}=\sqrt{24\bar{\rho}_{\textrm{m}}}\approx72.1\;\textrm{km/s/Mpc} \). The BAO half predicts a concordance \( \hat{H}_{0}=\frac{4}{3}\sqrt{12\bar{\rho}_{\textrm{m}}}\approx68.0\;\textrm{km/s/Mpc} \). Adaptation of the Stefan-Boltzmann law to symmetries and time-dilation at the horizon in \( \bar{g} \) relates the nonlocal field energy associated with \( \bar{\rho}_{\textrm{m}} \) to a constant CMB temperature \( \bar{T}_{\textrm{CMB}}=2.725\pm0.009\:\textrm{K} \), within FIRAS confidence limits. It also predicts a baryon/photon density ratio \( \frac{12^{4}}{23}-1=900.56.. \), within Planck 2018 confidence limits. The existence of \( \bar{g} \) by itself seems to make a strong case for a stationary universe, where one expects to find mature galaxies at high redshifts.

Abstract: Travel-associated Legionnaires’ disease (TALD) investigations in hotels generate extensive environmental monitoring data. However, the occupational implications for workers who operate, maintain, clean, or inspect the same systems are rarely assessed. We developed a hybrid framework integrating a semi-quantitative environmental hazard model with deterministic Quantitative Microbial Risk Assessment (QMRA). In the first model, culture concentration bands were combined with physicochemical deviation indicators (temperature, free residual chlorine, and pH) to derive point-level hazard (Hi) and zone-level hazard (Hz). In the second model, a job-based presence matrix was combined with zone-specific serogroup-based severity using a simplified World Health Organization (WHO)-style 3×3 likelihood–severity approach. L. pneumophila (≥50 CFU/L) was detected in 29.94% of water samples and was significantly associated with low chlorine (<0.2 mg/L; RR 2.90) and hot water temperature <50 °C (RR 3.00). To enhance precision, QMRA was applied to estimate the daily inhaled dose (d) for 15 worker groups, indicating variability in modeled biological exposure across occupational categories. These findings suggest that occupational risk is shaped by the combined effect of pathogen concentration and exposure time. Under the hazard model, the highest zone-level hazard estimate was observed in kitchens and food and beverage (F&B) areas (Hz = 2.607), followed by machinery rooms (Hz= 2.022) and guest rooms (Hz= 1.874). These findings support the integration of worker protection into water safety management, particularly in areas and groups overlooked in routine investigations.

Abstract: Hydrogen (H2) is regarded as a promising option for sustainable energy systems; however, its large-scale use in electricity supply remains limited. This study develops a stochastic network optimization model to examine the applicability of H2-based electricity generation. The proposed Hydrogen Supply Chain (HSC) model evaluates cost and emission performance under uncertainty by considering disaster conditions, transmission losses, depreciation, and the time value of money. The Marmara Region of Türkiye is divided into 24 grid nodes, and a single-period model for 2023 is solved using Mixed-Integer Linear Programming (MILP). The HSC is allowed to meet 10–40% of electricity demand and to replace collapsed grid lines by supplying critical public centers (CPCs) during disasters. The results show that the HSC can meet about 25% of demand, although at costs higher than power grid (PG) electricity, while keeping emissions near zero. The model is then extended to a multi-period structure (2023–2053) and solved by Variable Neighborhood Search (VNS). Over time, H2 costs decline, and its share rises from 19% to 35%. These findings suggest that H2 can support long-term sustainability, resilience, and energy security.

Abstract: Floating belt conveyor routes, consisting of serially arranged belt conveyors, the end parts of which are mechanically attached to floating bodies, are designed for the continuous transport of extracted granular materials from the water. The paper deals with the analytical determination of the position of the centre of gravity of the buoyancy force, the coordinates of which change depending on the longitudinal deflection of the floating body from the equilibrium state, which acts as a supporting element of individual conveyor belts. The analysis of the individual phases of deflection of the floating body, consisting of a pair of floats with a circular cross-section, shows that the complete submergence of one of the floats occurs at a higher value of the angle of inclination in the case when the floats are initially submerged under the surface to exactly half of their diameter. On the realized experimental device the buoyancy force was detected using strain gauges during the deflection of the floating body from the equilibrium position for three defined levels of immersion. The floating body of the experimental device consists of a pair of floats with a circular cross-section with a diameter of 80 mm. The output is a structured methodological procedure for determining the position of the centre of gravity of the displacement (centre of buoyancy) of a floating body when it deviates from the equilibrium position and a methodology for calculating the stability arm, which is a key parameter for assessing the buoyancy and stability of the body. On the basis of the laboratory measurements, the magnitude of the buoyancy force can be quantified as a function of the immersion depth of the floating body. It was found that the buoyancy force remains constant when the body deflects only when the immersion corresponds to half the diameter of a float with a circular cross-section. If the depth of the immersion is less than the radius of the float, the buoyancy force increases during deflection; on the contrary, if the immersion is greater than the radius of the float, the buoyancy force decreases.

Abstract: The vibroacoustic simulation of geared drivetrains has become increasingly important as electrified powertrains expose tonal gear noise and high-frequency structure-borne excitation more clearly than conventional internal-combustion vehicles. In this context, software choice is no longer a secondary implementation detail but a central engineering decision, because different platforms emphasize different parts of the excitation–transfer–radiation chain. This review therefore examines gearbox and geared-drivetrain NVH simulation from a software-specific perspective rather than a purely phenomenon-based one. The article critically compares dedicated gearbox CAE tools, general multibody dynamics platforms, integrated multiphysics and structural–acoustic finite-element environments, and early-stage 1D system simulation tools. The comparison covers major software ecosystems including KISSsoft/KISSsys, Romax Suite, SMT MASTA/DRIVA, MSC Adams, AVL EXCITE, RecurDyn/DriveTrain, Siemens Simcenter 3D Motion / Transmission Builder / Acoustics, SIMULIA Simpack, Ansys Motion with Mechanical/Acoustics and Motor-CAD, COMSOL Multiphysics, GT-SUITE, and Simcenter Amesim, while also considering relevant recent module extensions and workflow updates. The review shows that the current software landscape is structured around four main methodological layers: dedicated gearbox analysis tools that are strongest in gear-contact modeling and microgeometry iteration; high-fidelity multibody platforms that are strongest in system-level dynamic response and transmission-path representation; integrated structural–acoustic environments that provide the deepest access to housing vibration and radiated-noise prediction; and 1D or multidomain system tools that are most efficient for early concept evaluation and architecture-level trade-off studies. Recent developments since 2023 indicate a clear shift toward tighter support for electrified drivetrain NVH, measured manufacturing deviations, optimization workflows, and faster acoustic prediction, including reduced-order or embedded acoustic methods. At the same time, major gaps remain. Open literature still contains relatively few independent studies that validate the full chain from tooth contact and transmission error through dynamic transfer paths to housing vibration and radiated sound within a single commercial workflow. Likewise, interoperability for measured flank topography, wear-driven NVH evolution, and fully validated electro-magnetic–mechanical–acoustic simulation remains limited and uneven across platforms. For this reason, the review argues that current software ecosystems are best understood not as universally proven end-to-end solutions, but as partially overlapping toolchains with different strengths, evidence levels, and practical compromises.

Abstract: To address the challenge of separating fine-grained apatite from layered silicate gangue minerals (chlorite and biotite) in medium-low grade collophanite ores, this study systematically investigated the effect of carboxymethyl cellulose sodium (CMC-Na) as a selective depressant on flotation behavior of different particle size fractions and its underlying mechanism. Pure mineral and artificial mixed ore flotation experiments demonstrated that at pH 9 and collector dosage of 5 kg/t, CMC-Na enabled selective separation of apatite from gangue minerals, with optimal dosage showing significant particle size effects: for the -0.5+0.074 mm fraction, effective separation was achieved with collector alone; for the -0.074+0.023 mm fraction, the optimal CMC-Na dosage was 10~100 mg/L, yielding 87% apatite recovery for pure minerals and 41.8% recovery with 23.7% P₂O₅ grade for mixed ores; for the -0.023 mm fine fraction, the optimal dosage was 30~300 mg/L, achieving 24.8% recovery and 13.2% grade. Mechanism studies revealed that CMC-Na significantly enhanced the hydrophilicity of chlorite and biotite, enlarging their surface property differences with apatite. FTIR and XPS analyses indicated that CMC-Na adsorbed on biotite via ion exchange with interlayer K⁺ and coordination with octahedral Fe²⁺/Mg²⁺, and on chlorite through chemical coordination with octahedral Mg²⁺, whereas only weak physical adsorption occurred on apatite surface Ca²⁺. The adsorption strength followed the order: biotite > chlorite > apatite. This study provides an effective reagent scheme and theoretical basis for flotation separation of fine-grained phosphate ores.

Abstract: The preparation of high-performance radiation detector materials such as cadmium zinc telluride (CZT) relies on rigorous and efficient quality control to ensure the consistency of device performance. Traditional manual evaluation based on wafer-by-wafer inspection is time-consuming and makes it difficult to assess the downstream product yield at the ingot level in advance. This paper proposes a machine-learning-based prediction framework for CZT ingots, in which the product-level yield of test wafers from the same ingot is predicted using the double-sided electrical performance and spectral characterization data of a limited number of evaluation wafers. To address the limited number of ingot samples and the significant internal variability among wafers, statistical aggregate features, A/B-side difference features, threshold-ratio features, and intra-ingot Bootstrap resampling were combined, and multiple regression methods, including linear models, Random Forest, XGBoost, and neural networks, were systematically evaluated. The results show that the XGBoost model achieved the best overall performance, with the lowest mean squared error of 0.0352, a mean absolute error of 0.1448, and a Pearson correlation coefficient of 0.3187 on the test set. Furthermore, after combining model prediction with empirical rules, the true yield of test wafers for the top 22% candidate ingots increased from 61.50% to 63.59%. These results indicate that the proposed method can effectively support early ingot screening and processing-priority decisions. This study demonstrates the application potential of data-driven methods in early-stage quality evaluation of CZT crystals and provides a reference framework for yield prediction in similar multi-wafer crystalline materials.

Abstract: Agricultural waste accumulation offers potential for sustainable soil management in climate-resilient farming systems, but it also poses ongoing environmental challenges. This study examines the effects of vermicomposting, which turns agricultural waste into nutrient-rich organic fertilizer using Eisenia fetida, on crop productivity and soil fertility. Treatments were compared using a randomized experimental design that included many combinations of organic waste and a control. Crop growth and yield indices were examined in addition to soil physicochemical characteristics such as pH, organic carbon, total nitrogen, available phosphorus, and exchangeable potassium. Comparing vermicompost treatments to the control, the soil's nutritional content and structural quality significantly increased (p < 0.05). Mixed organic waste substrate trials outperformed single substrate trials, suggesting synergistic interactions that enhance microbial activity and nutrient cycling. Vermicompost application improved soil fertility indicators and increased crop growth and production. These findings show that vermicomposting is an effective waste valorization technique that supports the circular economy and sustainable agriculture. The study demonstrates how it can reduce environmental pollutants while enhancing soil health, agricultural yield, and fertilizer use efficiency. All factors considered, vermicomposting is a scalable and environmentally friendly way to increase the climate resilience of agricultural systems. More research should be done on long-term field performance, economic viability, and substrate combination optimization under different agroecological conditions.

Abstract: Background: Globally, over 2.1 billion people lack safe drinking water, leading to significant impacts, especially from diarrhea. This study evaluates the health and economic impacts of point-of-use water filter distribution in an urban setting with partial water infrastructure. Methods: In 2024 and 2025, households (N=7,973) in Ciudad Victoria, Mexico, re-ceived a hollow fiber membrane point-of-use water filter and basic WASH training. A pseudo-randomized study design was used to assign household to receive one of three different filter implementation systems (tap, bucket, or squeeze). Baseline and follow-up surveys with each household were conducted over an 8–14 week time frame. Results: Filter utilization was high across all three delivery types, with only minor differences in outcomes observed. Self-reported two-week diarrhea prevalence de-clined from 24.3% at baseline to 3.1% at 8–14 weeks, with similar reductions in oth-er health symptoms. Household water expenditures decreased by 56%, and work-days missed due to diarrhea declined by 94%. Impacts were similar in covariate ad-justed statistical models. Conclusions: This study suggests that point-of-use filtration combined with WASH training can substantially reduce illness and economic burden in urban contexts, with effectiveness comparable across different filter implementation approaches. Limitations include reliance on self-reported data and a short follow-up period, which should be explored in future studies.

Abstract: Polarimetric color cameras are a forefront technology that simultaneously capture polarimetric and color information by analyzing polarization states across different color channels, commonly red, green, and blue. In general, each of these color channels can carry different polarization information. Therefore, measuring the polarization Stokes vector at several discrete wavelengths simultaneously and with the highest possible resolution is of interest in multiple research areas. Nonetheless, this situation has not yet been investigated in specialized literature, where it is still commonly assumed that all color channels transport the same polarization information. In practice, polarimetric color cameras often come with the difficulty of color filter overlapping. For instance, the green filter partially transmits red and blue wavelengths, causing polarization-color crosstalk. In this work, we present a method to solve this problem. In addition, Fourier domain demosaicing techniques are applied to interpolate the data and reconstruct the images. The present study demonstrates how the proposed method leads to a successful recovery of chromatic and polarimetric information on both synthetic and real-world datasets. To test our approach, narrowband light beams at three wavelengths (470, 554, 630 nm), with different spatial polarization and degree of linear polarization distributions have been simulated and validated with experimental data. The results demonstrate the feasibility of the method for accurate three polarization channels measurements.

Abstract: University students face dietary transitions shaped by time constraints, campus food environments, and intensive exposure to food-related content on social media, yet the mechanisms linking digital exposure to observable food choices and overall diet quali-ty remain insufficiently modeled in Latin American contexts. This study examined whether social-media-driven food norms (NI) and in-restaurant food choices (CD) se-quentially mediate the effect of Instagram (IG) and TikTok (TK) exposure on overall diet quality (Y), while incorporating physical activity (PA) as an independent predic-tor. A cross-sectional survey was administered to 615 university students consuming in campus restaurants in La Libertad, Northern Peru. Data were analyzed through PLS-SEM (SmartPLS 4) with 5,000 bootstrap resamples and BCa 95% confidence in-tervals; Y was operationalized through a culturally adapted KIDMED index. All five structural hypotheses were supported: TK → NI (β = 0.479) exceeded IG → NI (β = 0.349); NI → CD (β = 0.473) and PA → CD (β = 0.216) operated as independent path-ways; and CD → Y (β = 0.255) confirmed the distal link. NI fully mediated both digital pathways toward food choices. Diet quality in university restaurants is reconfigured primarily through normative, not informational, digital mechanisms, suggesting norm-based interventions over nutrition-information campaigns.

Abstract: Both data utility and data privacy must be carefully considered when datasets containing users’ sensitive information are released for use beyond the scope of the data‑collecting organization. To achieve an appropriate balance between data utility and data privacy in such released datasets, a variety of privacy preservation models have been proposed, including k‑Anonymity, l‑Diversity, Anatomy, t‑Closeness, and Differential privacy. Unfortunately, these privacy preservation models can sufficiently address concerns of privacy violation issues in simple datasets. Moreover, to the best of our knowledge about them, they still have various vulnerabilities that must be improved such as data utility, complexity, and the new privacy violation techniques that are discovered after they are proposed. Furthermore, we found that they are not well-suited to address concern of privacy violation issues in datasets containing content-sensitive values (or sometimes they are called content-based datasets). To rid these vulnerabilities, a new privacy preservation model is proposed in this work, it is called (d, c, l)-Privacy. It is proposed to address concerns of privacy violation issues in content-sensitive datasets. It is based on expert and mechanism term document measurements. That is, the released datasets can reduce about the concern of privacy violation issues after they are satisfied by the d, c, and l parameters. To achieve (d, c, l)-Privacy constraints, there are three algorithms that are proposed in this work, i.e., SCFS, greedy, and optimal (d, c, l)-Privacy algorithms. The aim of SCFS (d, c, l)-Privacy is that aside from the released dataset is satisfied by the d, c, and l parameters, the execution time is maintained as much as possible. While the greedy (d, c, l)-Privacy will be mindful of both the execution time and data utility. Another proposed algorithm, the optimal (d, c, l)-Privacy algorithm, aims to maintain the meaning or usefulness of the data as much as possible.The experimental results show that the proposed algorithms are effective in mitigating privacy breaches in released datasets under the (d, c, l)-Privacy constraints. Among the evaluated algorithms, FCFS achieves the highest time efficiency, whereas the greedy algorithm offers a better balance by preserving data semantics within a reasonable computational cost. The optimal algorithm consistently maintains the highest level of data utility, albeit at increased computational expense. These findings indicate that the proposed algorithms are not only effective in preserving privacy data in released datasets but are also suitable for practical deployment in real‑world data‑releasing scenarios.

Abstract: Traumatic tracheal injuries and congenital defects can be life threatening. Regenerating the trachea through tissue engineered scaffolds has emerged as an innovative alternative to traditional therapies. At present time, challenges in tracheal regeneration preclude clinical adoption, such as revascularization and promotion of favorable paracrine and immune signaling responses. This review summarizes current advances in tracheal regeneration and highlights key biological and engineering barriers to address to achieve functional tracheal regeneration.

Abstract: The aim of this study was to evaluate whether edible coatings and plant derived ex-tracts can help maintain the quality and microbiological safety of fresh-cut sweet peppers during short-term refrigerated storage. Two bell pepper cultivars, Sunny F1 (yellow) and Yecla F1 (red), were sliced and subjected to five treatments: water wash-ing (control), washing with BioActiW 2000 Food sanitizer (BAW), BAW followed by carboxymethylcellulose (CMC) coating (BAW+CMC), CMC coating enriched with 3.5% alcoholic chokeberry pomace extract (CMC+AE), and soaking in 3.5% aqueous chokeberry pomace extract (AAE). Samples were stored at 5 °C for 7 days and evalu-ated for physicochemical analysis, microbiological contamination, postharvest quality, and sensory properties. The treatments influenced quality attributes in a cultivar de-pendent manner. All coating based treatments reduced polyphenol and L-ascorbic acid content relative to the control, although formulations containing chokeberry extract tended to limit these losses compared with BAW+CMC. Total sugar and carotenoid contents were not significantly affected. In both cultivars, BAW and BAW+CMC were the most effective treatments for reducing mesophilic bacteria and yeast counts, limit-ing softening, reducing weight loss, and maintaining marketable quality. By contrast, AAE applied without prior sanitization increased microbial counts in Sunny F1, indi-cating that the extract alone was not sufficient to control native microflora. Sensory analysis showed clear cultivar specific responses: Sunny F1 generally tolerated CMC+AE and BAW+CMC better, whereas Yecla F1 was more sensitive to off-flavors associated with the chokeberry extract. PCA analysis indicated that smell and taste at-tributes were the main drivers of perceived quality. These results suggest that CMC based coatings can support fresh-cut pepper quality, but their practical value depends strongly on prior sanitization. The addition of chokeberry pomace extract may be beneficial for some quality traits, yet its overall ef-fect depends on cultivar and treatment conditions, including extract concentration and pH.

Abstract: The diverse clinical manifestations of allergic skin diseases often overlap with other pathologies, posing significant diagnostic challenges. Allergen-specific IgE (sIgE) testing is essential for identifying triggers and personalizing treatments in allergic skin diseases. A retrospective study was conducted on 4,277 medical records of patients with allergic skin diseases who underwent sIgE testing at the HCMC Hospital of Dermato-Venereology, a tertiary referral dermatology center serving Southern Vietnam, from January to December 2024. The results revealed that 64.09% of the patients exhibited sIgE sensitization. House dust mites (D. farinae: 30.91%, D. pteronyssinus: 25.67%) and fire ants (24.06%) were the predominant allergens. Food sensitization was predominantly mild, with almond being the most common (10.26%). Significantly higher sensitization severity was observed in males, young adults (12–35 years), and non-urban residents (p &lt; 0.001). Correlation analysis demonstrated robust co-sensitization and cross-reactivity among aeroallergens, predominantly driven by house dust mites. In conclusion, allergen sensitization profiles are strongly influenced by demographic and geographic factors, with a characteristic pattern observed in Southern Vietnam. Multiplex sIgE testing provides substantial value in disease stratification, prognostic assessment, and the development of personalized treatment strategies in this tropical setting.

Abstract: Accurate evaluation of indoor daylighting performance is essential for improving visual comfort and reducing lighting energy use in office buildings. However, simulation-based daylighting analysis is often too time-consuming to support rapid comparison of multiple design options in early-stage design. To address this issue, this study proposes MTL-Light, an explainable chained multi-task learning framework for fast daylighting performance prediction in typical office units. A parametric simulation dataset was constructed, and multiple representative daylighting indicators were extracted from the spatial distribution of daylight factors on the work plane. MTL-Light was then developed to jointly predict these indicators by modeling their interdependencies within a lightweight multi-task learning architecture. In addition, SHAP was employed to interpret the prediction results by quantifying the marginal contributions of geometric design variables. The results show that, compared with single-task models, MTL-Light achieves higher accuracy and more stable performance across multiple indicators, particularly for metrics sensitive to spatial distribution. Moreover, it reduces daylighting evaluation from minute-level simulation to millisecond-level inference. The interpretability analysis further indicates that room depth and window geometry dominate daylighting performance, while different indicators exhibit different sensitivities to geometric variables.

Abstract: This paper investigates the oscillation properties of solutions to a second-order nonlinear difference equation in noncanonical form with bounded and unbounded neutral terms. By employing the monotonicity of the neutral term together with a linearization technique, we establish new conditions that guarantee all solutions of the equation oscillate. Our results are applicable to various nonlinear forms of the equation, and, notably, the oscillation of all solutions is ensured through a single condition. Consequently, the proposed oscillation criteria are straightforward to apply and distinct from existing results on nonlinear difference equations. Four examples are presented to demonstrate the novelty and significance of the main findings.