Search Results (38,972)

This paper presents a further step in the development of scale invariant fully conformal cosmology (FCC), formulated in our previous study. Whereas the previous paper focused mainly on the global cosmological consequences of the fully conformal metric and their confrontation with selected astrophysical data, here we analyze its local gravitational and background consequences. On the background of the fully conformal metric we formulate an effective generalization of the weak Schwarzschild field in the corresponding FCC global coordinates and derive from it the associated modified intensity of the Newtonian central field. We further derive the cosmological state/constitutive equation p = − ε/3 as a direct consequence of the fully conformal metric rather than as an ad hoc additional postulate. Likewise, within the fully conformal metric, spatial flatness and the critical density ρ_crit are understood as direct consequences of this metric structure rather than as independently postulated inputs. From the condition of global equilibrium between negative cosmological pressure and the gravitational cohesive pressure of homogeneously distributed matter, the effective particulate fraction is obtained as β ≈ 0.45 of the total critical density ρ_crit. For the relatively well-confirmed baryonic matter fraction ${\overline{\mathrm{\Omega }}}^{bar} \approx 0.05$, this stable-equilibrium condition then leads to the corresponding particulate fraction of collisionless dark matter ${\overline{\mathrm{\Omega }}}_{FCC}^{dm} \approx 0.40$, which is in principle determined by the global cosmological equilibrium within this framework. Because direct identification of the entire dark fraction with standard collisionless cold dark matter would very probably be incompatible with the main structural observables, we discuss an effective phenomenological decomposition into a structuring cold dark matter component (cdm) and an almost homogeneous residual warm-dark-matter-like component (wdm). In this interpretation, the paper preserves the previously introduced global FCC framework while simultaneously providing a concrete background prediction for the matter content and a physically motivated basis for further testing of structure formation within scale invariant fully conformal cosmology. Full article

Train-induced vibrations pose a significant threat to foundation pit slopes adjacent to railways during parallel construction or line renovation projects. To address this issue, this paper proposes a periodic steel-sheet pile barrier for vibration mitigation in narrow construction sites. Firstly, field tests were conducted along the Qinbei Railway in China. The acceleration time history and dominant frequency (27.6 Hz) of ground vibrations were obtained. Secondly, based on periodic structure theory, the dispersion relations and band-gap characteristics of periodic steel-sheet piles were analyzed using the finite element method. Parametric studies were then performed to investigate the effects of key factors, including periodic constants, pile spacing and pile count per unit cell, and construction deviations, on the band-gap boundaries and width. Subsequently, frequency-domain, time-domain, and slope stability analyses were carried out to evaluate the isolation performance. The results show that the optimized barrier, with parameters of a = 1.6 m, D = 0.1 m, n₁ = n₂ = 4, and L = 2S, reduced the peak acceleration by 70% and achieved a vibration reduction of up to 88% at the dominant frequency. Furthermore, slope stability analysis revealed that the barrier increased the factor of safety from 1.16 to 1.46, exceeding the code-required minimum of 1.2–1.3. This study provides a potentially cost-effective and construction-friendly solution for protecting temporary foundation pit slopes from train-induced vibrations in railway-adjacent areas. Full article

Background: Post-traumatic growth (PTG) refers to positive psychological changes resulting from the struggle with highly challenging or traumatic life events. Psychosocial interventions have demonstrated efficacy in promoting psychological well-being in the aftermath of traumatic experiences. Cognitive Behavioral Therapy (CBT) is among the most extensively studied such interventions, aligning with the PTG model’s prerequisites for growth. Objective: The aim of this systematic review was to assess the efficacy of CBT and CBT-based interventions in promoting PTG. Methods: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, searching PubMed, Scopus, and Google Scholar databases from inception to December 2024. Eligibility criteria included: (a) the inclusion of a CBT or CBT-based intervention, (b) measurement of PTG using the Post-Traumatic Growth Inventory (PTGI), (c) study participants having experienced traumatic life events, and (d) articles written in English. Risk of bias was assessed independently by two reviewers. Due to the heterogeneity of included studies, a qualitative narrative synthesis approach was adopted. Risk of bias was assessed using the RoB-2 tool for RCTs, ROBINS-1 for quasi-experimental studies and Newcastle–Ottawa scale for cohort studies. Certainty of evidence, assessed using the GRADE framework, is considered low. Results: A total of 19 studies were included (13 randomized controlled trials, 3 quasi-experimental, and 3 longitudinal studies). While traditional CBT produced mixed results in fostering PTG, CBT-based therapeutic protocols—particularly those explicitly designed to target PTG or incorporating structured cognitive–emotional techniques—demonstrated more consistent benefits. Limitations of the included studies include measurement of PTG as a secondary outcome, small sample sizes, and the presence of confounding variables. Conclusions: Further high-quality, multicenter randomized controlled trials with standardized protocols are needed to clarify the role of CBT in promoting growth after trauma. Full article

Recidivism prediction is increasingly embedded in criminal justice decision-making, yet most deployed systems remain opaque and have been shown to exhibit discriminatory behavior against certain demographic groups. This paper presents a fairness-aware interpretable framework for recidivism prediction applied to three real-world datasets from Bulgaria, Greece, and Portugal. The classification core relies on a 1-Dimensional Convolutional Neural Network (1D-CNN), trained by a custom objective function that embeds the Equalized Odds fairness criterion as an L1-regularized penalty reflecting on gender-based disparities in false positive and false negative rates. Model-level interpretability is provided through Kernel SHAP, which decomposes individual predictions into additive feature attributions grounded in cooperative game theory. Experiments across prediction tasks, each evaluated over randomized runs, demonstrate that the baseline model exhibits statistically significant bias against the female group in all datasets. The fairness-constrained model substantially reduces these disparities across all tasks at a moderate and expected cost to classification accuracy. Kernel SHAP analysis reveals the relative contribution of static and dynamic offenders’ attributes to individual risk scores, supporting auditability and contestability. The proposed framework advances the integration of predictive performance, algorithmic fairness, and structural interpretability in criminal justice analytics. Full article

Removing mercury (Hg²⁺) from aqueous environments remains a major environmental challenge due to its high toxicity and bioaccumulation. Graphene quantum dots (GQDs) are adsorbents that show promise in removing these contaminants, but their yield is low in their pristine form. This study investigates the effect of phosphorus (P) doping on vacancy-containing GQDs to enhance Hg²⁺ absorption using density functional theory (DFT) calculations. These were performed at the M06-2X/def2-TZVP level of theory to optimize the structures of GQDs, 1P-GQDs, and 2P-GQDs to evaluate adsorption energies, frontier molecular orbitals, and dipole moments. The results show that GQDs with vacancy have an adsorption energy of −65.21 kcal mol⁻¹, which increases to −104.54 kcal mol⁻¹ for 1P-GQDs, indicating the strongest Hg²⁺ binding. However, 2P-GQD shows a lower value of −73.47 kcal mol⁻¹, suggesting lower efficiency due to electronic competition between dopants. Dipole moments increase from 0.8192 D (GQD) to 4.6729 D (1P-GQD) and 5.7557 D (2P-GQD), confirming strong polarization induced by P incorporation. The HOMO-LUMO gap decreases from 2.204 eV to 1.937 eV after single doping. At the same time, after Hg²⁺ adsorption, the values increase to 5.153 eV (GQD), 3.462 eV (1P-GQD), and 2.068 eV (2P-GQD), indicating configuration-dependent electronic stabilization. PDOS analysis confirms weak cation-π interaction in GQD and strong orbital hybridization in 1P-GQD, consistent with a coordination-type bond. Doping a single phosphate atom optimizes the electronic structure of GQDs with a vacancy site, thereby improving charge transfer and adsorption strength through electronic balance. Full article

The aim of this study is to develop and comprehensively evaluate the efficacy of an innovative formulation of a biological preparation consisting of a bacterial consortium (Serratia proteamaculans B5, Pseudomonas putida D7 and Lysinibacillus sp. S1), embedded in a pullulan polysaccharide matrix, as an agent for inducing systemic resistance in barley (Hordeum vulgare L.) to phytopathogenic stress caused by Fusarium graminearum. To optimize the product’s protective efficacy and minimize the pesticide load on the agroecosystem, a reduced dose of Fundazol (50% of the standard rate) was incorporated into the formulation. The constituent strains exhibited high indole-3-acetic acid production (53.29–69.2 μg·mL⁻¹) and strong antagonistic activity against phytopathogenic fungi, with inhibition zones reaching up to 32.5 mm. Pot and field trials were conducted to comprehensively assess the effect of the biological product on the stress tolerance of barley plants. Pre-sowing seed treatment reduced proline accumulation (by up to 2.3-fold), maintained photosynthetic pigment levels, and increased field germination to 79%. Under infectious field conditions, treatment with the biopreparation contributed to the stabilization of yield structure parameters (treated plants exhibited increases in height and biomass of 9–21%) and the improvement of grain quality indicators. Overall, the results obtained demonstrate the potential of the developed biopreparation as a component of comprehensive protection strategies and as an inducer of plant priming mechanisms. Full article

Recently, the Quality by Design (QbD) principle has been implemented in the pharmaceutical industry to enhance product and process understanding through a science- and risk-based approach. This study aimed to apply QbD principles to the formulation development of felodipine push–pull osmotic pump (PPOP) capsules. The quality target product profile (QTPP) and critical quality attributes (CQAs) were established. A Box–Behnken experimental design was employed to optimize the formulation variables, including the amounts of Polyox WSR N80, Polyox WSR Coagulant, and sodium chloride, selected based on the initial risk assessment. Four responses were monitored: lag time, release rate and R² based on zero-order release kinetics, and drug release at 24 h. Results indicated that the optimal formulation consisted of 125 mg Polyox WSR N80, 26 mg Polyox WSR Coagulant, and 30 mg sodium chloride. This formulation met the predefined criteria for lag time (≤6 h) and release kinetics (R² ≥ 0.95), while drug release at 24 h remained below the target value (≥80%). Because most fitted response surface models were not statistically significant, the generated regression equations and response surfaces were interpreted qualitatively to identify formulation trends rather than as predictive models. Experimental verification showed reasonable consistency in overall response trends, although substantial deviations between predicted and observed values were observed for some responses, particularly drug release at 24 h. Therefore, the present work should be considered a formulation-development and QbD feasibility study rather than a definitive optimization study. These findings demonstrate that the QbD-based approach enabled systematic, multivariate optimization and design space establishment, providing a more structured framework for formulation refinement compared with prior exploratory development and supporting controlled drug release characteristics of felodipine PPOP capsules. Full article

Reconstructing building models from urban SAR tomography (TomoSAR) point clouds is often constrained by limited resolution, low positioning accuracy in elevation, as well as data incompleteness and artifacts caused by microwave imaging mechanisms. These challenges seriously restrict the extraction of high-accuracy building models with structural details from TomoSAR point clouds. This paper proposes a refined urban building modeling method that effectively utilizes structural priors, including directionality, orthogonality, and potential symmetry. First, a piecewise fitting strategy integrated with density-based segmentation is employed to iteratively estimate the main directions of the buildings and capture finer geometric variations of complex façade footprints than simple-plane approximations. Second, a roof extraction algorithm combining an adaptive Doug-las–Peucker approach with symmetry evaluation and constraints is developed to regularize roof outlines and repair data defects. Crucially, to handle extreme cases where roof data are entirely missing, a novel building width estimation method based on building shadow analysis is proposed. Experiments conducted on the SARMV3D-1.0 and SARMV3D-3.0 point cloud datasets demonstrate that the proposed method significantly enhances reconstruction accuracy and geometric fidelity in urban regions compared to state-of-the-art approaches. Full article

To lower the water absorption capacity and enhance the anti-corrosion performance of geopolymer coatings, methyltrimethoxysilane (MTOS) was adopted as a hydrophobic modifier to synthesize hydrophobic geopolymer coatings, and their anti-corrosion behaviors were systematically investigated. The results reveal that increasing MTOS content gradually improves the fluidity and setting time of fresh coatings while reducing their bonding strength. MTOS effectively strengthens the surface hydrophobicity of the coatings, decreases the water absorption of coated concrete substrates, and remarkably boosts chloride ion penetration resistance. The modified coatings achieve the optimal anti-corrosion performance at an MTOS dosage of 8 wt.%. Under this optimal condition, the surface water contact angle reaches 135.1°. After 28 days of chloride ion erosion, the chloride ion concentration is 45.0% lower than that of the unmodified counterpart. Meanwhile, the coating exhibits the minimum water absorption rate of 2.06% and the lowest average chloride penetration rate of 0.41 × 10⁻³ mg/(cm²·d), which accounts for only 41% of the standard threshold value. This study demonstrates that MTOS-based hydrophobic modification can significantly upgrade the anti-corrosion capability of geopolymer coatings, which provides a valuable theoretical basis and practical guidance for improving the durability of concrete structures. Full article

Invasive infections caused by Aspergillus flavus are more common in tropical and subtropical countries. The emergence of azole resistance in A. flavus complicates the management of aspergillosis, as azoles are the first-line and empirical therapy. The aim of this study was to investigate the molecular mechanisms underlying azole resistance in A. flavus, focusing on the cyp51C gene. We screened 34 molecularly confirmed A. flavus isolates obtained from patients with invasive aspergillosis for cyp51C gene expression by real-time RT-qPCR and for mutations by PCR sequencing. Molecular modeling and docking studies were performed using SWISS-MODEL, SwissDock, and I-TASSER software. Susceptibility testing revealed that 14.71% and 8.82% of isolates were resistant to itraconazole and posaconazole, respectively, with 5.88% exhibiting cross-resistance. The mRNA expression of cyp51C was upregulated (>2.5-fold) in five of the six resistant strains (83.33%). Hyperexpression of cyp51C was significantly more frequent among resistant isolates than among susceptible isolates (Fisher’s exact test, p = 0.014). Sequencing identified ten point mutations, including six synonymous and four non-synonymous substitutions. The non-synonymous mutations M54T and S240A were detected in the protein sequences of both resistant and susceptible isolates. Notably, D254N and I285V were observed exclusively in resistant isolates and in susceptible isolates with itraconazole MICs near the epidemiological threshold. Homology modeling and 3D structure prediction of the mutated Cyp51C protein demonstrated interactions with itraconazole, posaconazole, and voriconazole. Importantly, I-TASSER analysis indicated that the I285V substitution is located near the itraconazole binding site. Simultaneous overexpression of the cyp51A, cyp51B and cyp51C genes was observed in 33.33% of resistant isolates. These findings suggest that multiple target genes and mechanisms may act concurrently to confer azole resistance in A. flavus. Overall, this study supports the hypothesis that azole resistance in A. flavus is multifactorial and highlights the potential value of combining mutation analysis, gene expression profiling, and structural modeling for improved molecular surveillance and antifungal resistance monitoring. Full article

Background: Cytarabine (Ara-C) remains the cornerstone of remission-induction and consolidation chemotherapy for acute myeloid leukemia (AML) and related hematological malignancies. Despite more than six decades of clinical use, its multi-organ toxicity continues to be managed almost exclusively through dose attenuation and supportive care, with no approved upstream pharmacological prevention strategy available. Objectives: This scoping review aimed to systematically map the breadth and nature of pharmacological agents tested in vivo for their capacity to mitigate cytarabine-induced multi-organ toxicity, to characterize their mechanisms of action and organ targets, and to identify evidence gaps and agents with translational potential. Methods: The review was designed and reported in accordance with the PRISMA-ScR checklist. A structured electronic search was conducted across PubMed/MEDLINE, Scopus, Cochrane Library and Embase, and Web of Science from database inception to 15 July 2025. Eligible studies were restricted to full-text, peer-reviewed, English-language research involving in vivo mammalian models administered cytarabine as the principal toxin, with at least one pharmacological co-intervention and at least one quantitative or histopathological organ-injury outcome. Results: From 5701 retrieved records, 36 eligible in vivo mammalian studies (spanning 1964–2024) were identified. Included studies addressed neurotoxicity (n = 6), gastrointestinal mucositis (n = 9), ocular toxicity (n = 3), hepatotoxicity (n = 3), bone marrow suppression (n = 4), chemotherapy-induced alopecia (n = 5), and reproductive and developmental toxicity (n = 4). Five recurring mechanistic strategies were identified across the heterogeneous agents tested: redox buffering (N-acetylcysteine, α-lipoic acid, rutin, swertiamarin, α-tocopherol), mitochondrial preservation (betanin, thymoquinone, vitamin D, sodium zinc dihydrolipoylhistidinate [DHLHZn]), tissue-microenvironment reprogramming (apraglutide, BADGE, plerixafor, short-chain fatty acids, β-glucan), molecular antagonism (deoxycytidine, dCMP), and immunomodulation (lienal peptide, IL-1β, AHCC). Conclusions: This scoping review provides the first systematic cartography of pharmacological mitigation strategies for cytarabine-induced multi-organ toxicity. Five mechanistic pathways converge across eight organ systems, with apraglutide and N-acetylcysteine representing the most clinically translatable candidates. Plerixafor and PPARγ blockade by BADGE constitute high-priority candidates for bone marrow niche protection, while the deoxycytidine antagonism principle warrants formal pharmacokinetic evaluation. The complete absence of cardiotoxicity mitigation data defines the most critical gap for future research. Full article

Industrial energy consumption in shift-based manufacturing exhibits pronounced temporal asymmetry—here defined as direction-dependent conditional dynamics in which the transition from production to shutdown states follows a systematically different temporal trajectory than the reverse transition. At the facility studied, this asymmetry also manifests in the marginal distribution of hourly consumption values: pooling all 4724 observations yields a bimodal, right-skewed histogram (skewness ≈ −0.4) comprising two sub-populations corresponding to production hours (14–19 kWh/h) and shutdown hours (0–2 kWh/h). Although individual hourly observations are serially dependent and therefore not i.i.d., the marginal distributional shape is consequential because ARIMA-class models assume approximately Gaussian innovations, and residuals from models fit to this bimodal series inherit its non-Gaussianity. More fundamentally, the conditional distribution P(E_t|E_{t − 1}, …) is direction-dependent: the production-to-shutdown transition is abrupt (1–2 h, 18:00–20:00), while the shutdown-to-production ramp is slower and more variable (2–4 h, 05:00–07:00). Symmetric ARMA models, applying identical autoregressive coefficients regardless of transition direction, cannot represent this directional asymmetry, rendering their assumptions and associated error metrics structurally unreliable for this class of data. This paper addresses this asymmetry directly by presenting and evaluating two hybrid forecasting architectures—Prophet+LSTM and SARIMA+LSTM—for 24 h-ahead energy prediction at an industrial bread factory in Kazakhstan, instrumented with 15 IoT energy meters. The two-stage design exploits the complementary asymmetry-handling properties of each component: the statistical model (Prophet or SARIMA) captures deterministic seasonal structure, while the LSTM corrects asymmetric residuals that the statistical model systematically misrepresents. In a rigorous 14-day holdout evaluation, Prophet+LSTM achieves an MAE of 3.39 kWh—outperforming the Seasonal Naïve baseline by 12.3% and reducing Prophet-alone error by 32.7%—with statistical significance at the 10% level confirmed via Diebold–Mariano testing (DM = +1.747, p = 0.081). The LSTM residual correction reduces Prophet’s systematic negative bias by 69% (from −3.60 to −1.13 kWh), as confirmed by ablation testing. In eight weeks of production operation with incremental retraining, MAE improved 35% (7.02 → 4.58 kWh). These results demonstrate that explicitly modelling temporal asymmetry through hybrid statistical-neural architectures substantially improves industrial energy forecasting accuracy. Full article

The reaction of either the L or D enantiomer of H₂N-C*H(R)CO₂⁻ (R = -CH₂SH cysteine, C; -C(SH)(CH₃)₂, penicillamine, PN; or -CH₂CH₂SH, homocysteine, HC) with an imidazole-4-carboxaldehyde and nickel(II) acetate in methanol yields a single stereoisomer of a thiazolidine (from C or PN) or a thiazine (from HC) nickel complex. Five pairs of enantiomeric products were prepared and characterized by IR, ESI MS, EA, and single crystal structure determination. There is retention of chirality for the thiazolidine and thiazine complexes on ring position 4, C_α of the parent amino acid, and transfer of chirality to the newly generated stereogenic centers, ring positions 3 (the amino acid nitrogen atom, N_AA) and 2 (the aldehyde carbon atom, C_ald). For the thiazolidines, the new stereogenic centers, N_AA, and C_ald, have identical stereochemical assignments to one another and to the assignment of the alpha carbon atom, either all R from the L enantiomers of C and PN or all S from the D enantiomers of C and PN. For the thiazine products from HC, the newly generated stereogenic centers, ring positions 3 (N_AA) and 2 (C_ald), are identical to one another but opposite to that of the retained stereogenic center (ring position 4, the alpha carbon atom). Regardless of stereochemical assignment (R or S), the hydrogen atoms of C_α, N_AA, and C_ald, ring positions 4, 3, and 2, are always all cis to one another for the five pairs of enantiomers examined. This is a consequence of the fact that the thiazolidine and thiazine rings are fused to two other chelate rings of the complexes, which seems to explain the high stereospecificity observed in these systems. Full article

The detection of bolt preload force is of vital importance for ensuring the structural reliability of equipment under extreme operating conditions. Traditional ultrasonic transducers based on bulk piezoelectric materials suffer from poor long-term coupling stability and high brittleness of the material, which limits their practical applications. In this work, AlN piezoelectric thin films were fabricated by RF magnetron sputtering, and the effects of RF power and target-to-substrate distance on film morphology, crystal structure, and ultrasonic response were investigated. The results show that increasing RF power increased the film thickness and deposition rate, reduced the detected O content on the film surface, and changed the XRD response. The film deposited at 900 W generated ultrasonic longitudinal wave echoes with a relatively high signal amplitude among the tested RF powers. Among the tested target-to-substrate distances, the film deposited at 60 mm showed a relatively higher deposition rate and generated an ultrasonic longitudinal wave echo with a relatively higher amplitude. The measured d₃₃ value of this film was approximately 4.8 pC/N. The AlN thin-film ultrasonic transducers prepared under the selected deposition conditions were directly deposited on bolts, and the effects of temperature and axial load were calibrated using the ultrasonic TOF measurement method. There was a linear correlation between the TOF and the temperature (R² > 99.99%), as well as between the TOF and the axial load. These results indicate that the deposited AlN thin-film transducer has potential for bolt preload measurement in wind turbine bolts. Full article

Predicting the evolution of microstructure and field quantities under varying processing and loading conditions is a central challenge in computational materials science and metal additive manufacturing (AM). While deep learning (DL) methods offer ultra-fast prediction capabilities post-training, existing models often struggle with poor spatial and temporal extrapolation, high parameter burdens, and an inability to effectively integrate diverse conditioning parameters alongside high-dimensional input fields. To address these bottlenecks, we propose a novel conditional generative adversarial network (CPGAN), which is designed to seamlessly ingest both initial fields and governing condition parameters. The CPGAN framework offers three distinct advantages: (1) it accurately maps the combined effects of initial states and process conditions onto evolved fields; (2) it demonstrates robust extrapolation capabilities across diverse spatial and temporal scales, including the unique ability to natively generate high-resolution rectangular domains; and (3) it achieves superior predictive accuracy and training stability compared to standard convolutional baselines by effectively suppressing spurious artifacts. We validate CPGAN’s performance against rigorous physics-based ground truths across three representative engineering applications: porosity evolution in selective laser sintering (SLS), spatial distribution of 2D von Mises stress fields in solid structures, and the spatiotemporal evolution of grain growth. The results confirm that CPGAN is a highly adaptable and efficient surrogate model, capable of simulating continuous structural and morphological evolutions even when driven by highly non-uniform spatial or temporal kinetics. Full article