Search Results (27,422)

Eleven novel asymmetric pyrimidine derivatives were synthesized. The pyrimidine core was functionalized with a coumarin chromophore and a pro-mesogenic fragment bearing either chiral or linear alkyl chains of variable length and substitution patterns. The thermal properties were investigated using polarized optical microscopy, differential scanning calorimetry, and small-angle X-ray scattering, revealing that only selected derivatives exhibited liquid crystalline phases with ordered columnar or smectic organizations. Linear and nonlinear optical properties were characterized by UV–Vis absorption, fluorescence spectroscopy, two-photon absorption, and second-harmonic generation. Optical responses were found to be highly sensitive to the substitution pattern: derivatives functionalized at the 4 and 3,4,5 positions exhibited enhanced 2PA cross-sections and pronounced SHG signals, whereas variations in alkyl chain length exerted only a minor influence. Notably, compounds forming highly ordered non-centrosymmetric mesophases produced robust SHG-active thin films. Importantly, strong SHG responses were obtained without the need for a chiral center, as the inherent asymmetry of the linear alkyl chain derivatives was sufficient to drive self-organization into non-centrosymmetric materials. These results demonstrate that asymmetric pyrimidine-based architectures combining π-conjugation and controlled supramolecular organization are promising candidates for nonlinear optical applications such as photonic devices, multiphoton imaging, and optical data storage. Full article

Implementing environmental protection taxes implies a shift in environmental policy from government enforcement to market incentives, fostering long-term sustainability. Based on institutional theory, this study explores the nonlinear impact of environmental taxes on corporate green innovation and its influencing mechanism, by considering the complex interaction between innovation offsets and environmental costs. Utilizing data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges during 2012 and 2023, the study reveals an inverse U-shaped relationship between environmental taxes and green innovation performance, within which corporate environmental responsibility functions as a mediator. Furthermore, the results also reveal that the relationship between environmental taxes and green innovation is positively moderated by the development level of regional green finance. In addition, the heterogeneity analyses show that the inverse U-shaped relationship is more pronounced among heavily polluting and large-scale firms, and firms in more marketized areas and areas with higher levels of intellectual property protection. The research enriches the literature on the dual-edged effects of environmental taxes anchored in green innovation and unpacks the internal mechanism of the effectiveness of environmental protection tax policy. It also provides practical implications for the design of tiered taxes and green finance policies aimed at achieving sustainable development. Full article

This article describes a model for optimizing traffic flow control and generating traffic signal phases based on the stochastic dynamics of traffic and the percolation properties of transport networks. As input data (in SUMO), we use lane-level vehicle flow rates, treating them as random processes with unknown distributions. It is shown that the percolation threshold of the transport network can serve as a reliability criterion in a stochastic model of lane blockage and can be used to determine the control interval. To calculate the durations of permissive control signals and their sequence for different directions, vehicle queues are considered and the time required for them to reach the network’s percolation threshold is estimated. Subsequently, the lane with the largest queue (i.e., the shortest time to reach blockage) is selected, and a phase is formed for its signal control, as well as for other lanes that can be opened simultaneously. Simulation results show that when dynamic traffic signal control is used and a percolation-dynamic model for balancing road traffic is applied, lane occupancy indicators such as “congestion” decrease by 19–51% compared to a model with statically specified traffic signal phase cycles. The characteristics of flow dynamics obtained in the simulation make it possible to construct an overall control quality function and to assess, from the standpoint of traffic network management organization, an acceptable density of traffic signals and unsignalized intersections. Full article

Climate change causes unpredictable weather patterns, leading to more frequent and severe droughts. Investigating the effects of drought and irrigation on soil water status and the performance of various cassava genotypes can provide valuable insights for mitigating drought through designing appropriate genotypes and water management strategies. The objective of this research was to evaluate soil moisture, growth rates, and final yields (total dry weight, storage root dry weight, harvest index and starch yield) of six cassava genotypes cultivated under drought conditions during the late growth phase, as well as under full irrigation. The study utilized a split-plot randomized complete block design with four replications, conducted over two growing seasons (2022/2023 and 2023/2024). The main plots were assigned as two water regimes to prevent water movement between plots: full irrigation and drought treatments. The subplot consisted of six cassava genotypes. Measurements included soil properties before planting, weather data, soil moisture content, relative water content (RWC) in cassava leaves, and several growth rates: leaf growth rate (LGR), stem growth rate (SGR), storage root growth rate (SRGR), crop growth rate (CGR), relative growth rate (RGR), as well as final yields. The results revealed that low soil moisture contents for drought treatment led to variation in RWC, growth, and yield among cassava genotypes. Variations in soil and weather conditions between the 2022/2023 and 2023/2024 growing seasons resulted in differences in the performance of the genotypes. Kasetsart 50 (2022/2023) and CMR38–125–77 (2023/2024) were top performers under late drought stress regarding storage root dry weight and starch yield, showing vigorous recovery upon re-watering, evidenced by their significant increase in LGR (between 240 and 270 DAP) and their high RGR (240–360 DAP). Rayong 9 (2023/2024) demonstrated strong performance in both during the drought period (180–240 DAP), efficiently allocating resources under water scarcity, with SRGR and starch yield reduced by 26.4% and 9.5%, respectively, compared to full irrigation. These cassava genotypes are valuable genetic resources for cassava cultivation and can be used as parental material in breeding programs aimed at improving drought tolerance. Full article

The sonic log is a key tool for assessing the mechanical properties of rocks, identifying structural features, calibrating seismic data, and monitoring well integrity. However, sonic data are often incomplete due to time and cost constraints, tool failures, or unreliable measurements. Traditional approaches to generate synthetic sonic logs usually rely on empirical relationships or statistical methods. In this study, we applied an artificial intelligence approach in which a deep neural network was trained with real data from an oilfield in Mexico to reconstruct sonic logs based on their relationships with other geophysical well logs. Three models, each using different input logs, were trained to predict the sonic response. The models were validated on wells excluded from training, and performance was evaluated using the root mean square error (RMSE) and mean absolute percentage error (MAPE), showing satisfactory accuracy. The models achieved RMSE values between 1.4 and 1.7 [$\mathsf{\mu }$s/ft] and MAPE values between 2.1 and 2.6% on independent test wells, confirming robust predictive performance. We also generated synthetic sonic logs for wells where no sonic data were originally acquired, demonstrating the practical value of the proposed method. This work integrates convolutional (CNN) and recurrent (GRU) layers in a single deep-learning architecture, trained under strict well-level validation. The workflow is demonstrated on wells from the Tabasco Basin, representing a field-scale deployment not previously reported in similar studies. Full article

Given the increasing human exposure to electromagnetic radiation of various frequen-cies, mostly in the microwave range, awareness of potential health problems caused by this radiation has begun to grow. New building materials are being developed and tested to prevent or limit the penetration of microwave radiation, especially those frequencies that are used in mobile telephony. In contrast with the majority of the available literature on the investigation of concrete (cement) materials, in this paper, clay composite materials with the addition of nanoparticles of antimony(III)–tin(IV) oxide, zinc ferrite, iron(III) oxide, and two crystal modifications of titanium dioxide (rutile and anatase) were prepared in order to examine their effect on the absorption of electro-magnetic radiation. Nanomaterials are characterized by different physical and chemical methods. Specific surface area (B.E.T.), thermal properties (TGA/DSC), phase composition (PXRD), morphology (SEM), and chemical and mineralogical composition (EDX, and ED–XRF,) were determined. Thermal conductivity of clay composites was tested, and these materials showed a positive effect on the thermal conductivity (λ) of the composite: a reduction of 10–33%. The reflection and transmission coefficients of microwave radiation in the frequency range used in mobile telephony (1.5–4.0 GHz) were determined. From these data, the absolute value of radiation absorption in the materials was calculated. The results showed that the addition of the tested nanomaterials in a mass fraction of 3 to 5 wt.% significantly increases the absorption (reduces the penetration) of microwave radiation. Two nanomaterials, Sb₂O₃·SnO₂ and TiO₂ (rutile), have proven to be particularly effective: the reduction in transmission is 30–50%. The results of the test were correlated with the crystal structures of the examined nanomaterials. The inclusion of titanium dioxide and antimony-doped tin oxide into the clay led to a significant enhancement in microwave electromagnetic radiation absorption, which can be attributed to their interaction with the dielectric and conductive phases present in clay-based building materials. Full article

This paper presents an analytical study of the double modified exponentially weighted moving average (DMEWMA) control chart for monitoring autoregressive integrated (ARI) and autoregressive fractionally integrated (ARFI) processes, with emphasis on its symmetry properties. The explicit formulas for the average run length (ARL) are derived using Fredholm integral equations of the second kind, with existence and uniqueness established via Banach’s fixed-point theorem. The numerical approximations are obtained through the numerical integral equation (NIE) method, and simulations confirm that explicit ARL formulas and the NIE approach yield identical results, validating the theoretical derivations. The results show that symmetry plays a dual role: it ensures performance symmetry in detection across short- and long-memory processes. Comparative studies indicate that for ARI processes, DMEWMA outperforms EWMA and MEWMA for small and moderate shifts, while for ARFI processes, it remains superior to EWMA but shows parity or slight inferiority to MEWMA under certain long-memory conditions. The applications to environmental and economic data illustrate the value of symmetrical control structures in providing robust, unbiased monitoring. With ARL computations completed in under 0.001 s, the DMEWMA chart demonstrates efficiency, balance, and versatility. Full article

This study presents evaluation of biochar derived from silkworm cocoons for the adsorption of organic and inorganic contaminants from rainwater. The material was characterised using BET surface area analysis, scanning electron microscopy (SEM), and the point of zero charge (pH_PZC). The prepared biochar exhibited a well-developed surface area and demonstrated adsorption capacity toward both heavy metals and benzotriazole. The model rainwater was prepared by spiking real rainwater samples with Cu(II), Ni(II), Zn(II) ions, and benzotriazole (BT). Adsorption experiments were carried out under laboratory conditions to evaluate the effects of contact time, pH, and sorbent dosage. The experimental data were fitted to pseudo-first-order and pseudo-second-order kinetic models, as well as Langmuir/and Freundlich isotherms. The results showed that the adsorption of Cu(II) followed the Langmuir/Freundlich model, while the adsorption of Ni(II) benzotriazole was more consistent with the Freundlich model. Adsorption kinetics were best described by the pseudo-second-order model. The highest removal efficiencies were observed for Cu(II) (96%) and Ni(II) (88.8%), while Zn(II) removal was limited. Benzotriazole was also effectively adsorbed (97%), rapid adsorption occurred mainly within the first minute. Overall, the study highlights the selective adsorption behaviour of silkworm cocoon biochar and provides a comparative insight into the removal of organic and inorganic pollutants using a waste-derived adsorbent with surface properties comparable to those of activated carbon. Full article

Microplastics (MPs) are a ubiquitous marine pollutant, and their presence in bivalves is receiving increasing attention due to the associated risks to human health. The steps of pretreatment, detection, and quantification in the analysis of MPs depend on the type of polymer. Research on MPs is challenging because of the varying characteristics of these materials, such as the size, shape, and polymer type. Consequently, there are no standardized methods for their collection, separation, identification, or quantification. This review specifically examines the available bivalve digestion steps, focusing on efficient and time-reducing methods, such as the microwave-assisted (MAW) procedure and its advantages. Recent achievements in the application of pyrolysis gas chromatography–mass spectrometry (Pyr-GC-MS) are presented for the profiling of polymer mass-related microplastics data in marine bivalves. Here, we provide an overview of the abundance, properties, and polymer types of MPs in bivalve species, highlighting the polymer mass fractions. To date, the available mass-based concentrations have revealed nine types of MPs—polyethylene (PE), polypropylene (PP), polyvinyl chloride (PVC), polyethylene terephthalate (PET), polystyrene (PS), polymethyl methacrylate (PMMA), polyamide 66 (PA66), polycarbonate (PC), and polyamide 6 (PA6)—with PE, PP, and PVC being the most common. The total MP levels in bivalves were at ppm levels, ranging from 0.26 µg/g to 36.4 µg/g wet weight. The risk of human ingestion of MPs was assessed through the consumption of bivalves as seafood. The overall potential human health risk value (H) for marine bivalves was classified within the moderate to high hazard category. Full article

Line heating processes play a significant role in the fabrication of structural steel components, particularly in industries such as shipbuilding, aerospace, and automotive manufacturing, where dimensional accuracy and minimal defects are critical. Traditional methods, such as the finite element method (FEM) simulations, offer high-fidelity predictions but are hindered by prohibitive computational latency and the need for case-specific re-meshing. This study presents a physics-aware, data-driven neural network that delivers fast, high-fidelity temperature predictions across a broad operating envelope. Each spatiotemporal point is mapped to a one-dimensional feature vector. This vector encodes thermophysical properties, boundary influence factors, heatsource variables, and timing variables. All geometric features are expressed in a path-aligned local coordinate frame, and the inputs are appropriately normalized and nondimensionalized. A lightweight multilayer perceptron (MLP) is trained on FEM-generated induction heating data for steel plates with varying thickness and randomized paths. On a hold-out test set, the model achieves MAE = 0.60 °C, RMSE = 1.27 °C, and R2 = 0.995, with a narrow bootstrapped 99.7% error interval (−0.203 to −0.063 °C). Two independent experiments on an integrated heating and mechanical rolling forming (IHMRF) platform show strong agreement with thermocouple measurements and demonstrate generalization to a plate size not seen during training. Inference is approximately five orders of magnitude (~10⁵) faster than FEM, enabling near-real-time full-field reconstructions or targeted spatiotemporal queries. The approach supports rapid parameter optimization and advances intelligent line heating operations. Full article

Glaucoma continues to be a primary contributor to permanent vision loss worldwide, frequently advancing even when intraocular pressure management is clinically adequate. Accumulating research emphasizes the metabolic susceptibility of retinal ganglion cells (RGCs), specifically concerning the progressive depletion of nicotinamide adenine dinucleotide (NAD⁺), a pivotal coenzyme fundamental to mitochondrial energy production and cellular survival mechanisms. As a key biosynthetic precursor in NAD⁺ synthesis pathways, nicotinamide (NAM), a form of vitamin B3, has exhibited significant neuroprotective properties across various preclinical experimental models and preliminary clinical investigations, demonstrating enhanced preservation of RGC morphology and physiological function. This comprehensive review systematically examines the current body of evidence supporting NAM’s therapeutic utility in glaucomatous neuroprotection, focusing particularly on underlying metabolic pathways, obstacles in clinical translation, and prospective therapeutic applications. Through systematic integration of data from cellular and molecular research, animal experimental studies, and population-based epidemiological investigations, we establish a conceptual framework for repurposing NAM as an innovative complementary therapeutic strategy in comprehensive glaucoma care, addressing key considerations for future clinical development including optimal dosing strategies, delivery mechanisms, and patient selection criteria for maximizing therapeutic outcomes in this challenging neurodegenerative condition. Full article

Titanium dioxide (TiO₂) thin films sensitized with curcumin were fabricated to investigate the influence of sensitization on their spectroscopic, optical, and photocatalytic properties. TiO₂ films were prepared using different curcumin concentrations and characterized by FTIR, UV–Vis, and diffuse reflectance spectroscopy (DRS). The adsorption kinetics of curcumin on TiO₂ were analyzed, and the photocatalytic performance was evaluated through methylene blue (MB) photodegradation under visible-light irradiation. FTIR spectra confirmed the successful anchoring of curcumin onto the TiO₂ surface, while optical characterization revealed a significant enhancement in visible-light absorption. The band gap decreased from 3.2 eV (pure TiO₂) to 1.8 eV (curcumin-sensitized TiO₂). Furthermore, the curcumin adsorption onto semiconductor data fitted the pseudo-second-order kinetic model, yielding a maximum adsorption capacity of 12.0 mg·g⁻¹. Density Functional Theory (DFT) calculations indicated that ligand-to-metal charge transfer (LMCT) transitions are responsible for the improved visible-light response. Photocatalytic tests demonstrated that all curcumin-sensitized TiO₂ films were active under visible irradiation, confirming curcumin as an effective natural sensitizer for enhancing TiO₂-based photocatalytic coatings. Full article

Rankings drive consequential decisions in science, sports, medicine, and business. Conventional evaluation methods typically analyze rank concordance, dispersion, and extremeness in isolation, inviting biased inference when these properties co-move. We introduce the Concordance–Dispersion–Extremeness Framework (CDEF), a copula-based audit that treats dependence among these properties as the object of interest. The CDEF automatically detects forced versus non-forced ranking regimes, then screens dispersion mechanics via ${\chi }^2$ tests that distinguish independent multinomial structures from without-replacement structures and, for forced dependent data, compares Mallows structures against appropriate baselines. The framework estimates upper-tail agreement between raters by fitting pairwise Gumbel copulas to mid-rank pseudo-observations, summarizing tail co-movement alongside Kendall’s W and mutual information, then reports likelihood-based summaries and decision rules that distinguish genuine from phantom agreement. Applied to pre-season college football rankings, the CDEF reinterprets apparently high concordance by revealing heterogeneity in pairwise tail dependence and dispersion patterns that inflate agreement under univariate analyses. In simulation, traditional Kendall’s W fails to distinguish scenarios, whereas the CDEF clearly separates Phantom from Genuine and Clustered agreement settings, clarifying when agreement stems from shared tail dependence rather than stable consensus. Rather than claiming probabilities from a monolithic trivariate model, the CDEF provides a transparent, regime-aware diagnosis that improves reliability assessment, surfaces bias, and supports sound decisions in settings where rankings carry real stakes. Full article

The stability of pile foundation is influenced by many interacting factors, particularly geological conditions. Quantifying the impact of physical and mechanical soil properties on pile stability is critical for achieving optimal design outcomes. This study investigates the sensitivity of key soil parameters and validates the findings with a case study of a university building in Kashkar, Xinjiang, China. A three-dimensional pile–soil model was developed in Abaqus and calibrated with static load test data. Variable control and orthogonal experiments were conducted to examine settlement patterns and ultimate bearing capacity under varying soil parameters. Settlement and ultimate bearing capacity were adopted as stability indicators. Sensitivity analysis was performed through multi-factor variance analysis, sensitivity analysis of factors (SAF), and variance inflation factor (VIF) collinearity analysis. The results show that the most influential parameters are the friction coefficient of the soil above the pile tip, the Poisson’s ratio of the pile-end soil, the Poisson’s ratio of the soil above the pile tip, the friction coefficient of the pile-end soil, and the elastic modulus of the pile-end soil. These findings provide a quantitative basis for optimizing design parameters and improving the efficiency and reliability of pile foundation design in sandy soil regions. Full article

Tar-rich coal (with a tar yield ≥ 7%), as a special coal-based oil and gas resource, is of great significance for ensuring national energy security and promoting the clean conversion of coal. The selection of suitable geological sites represents a core challenge for the safe and efficient application of its in situ pyrolysis technology. Focusing on the tar-rich coal seams in the Santanghu Basin, this study constructed a comprehensive geological evaluation system for site selection by integrating numerical simulation, data mining, and laboratory experiments. The Analytic Hierarchy Process (AHP) and a fuzzy comprehensive evaluation method were employed to achieve a quantitative assessment and identify favorable areas within the study region. The results indicate that resource scale, coal seam conditions, and the properties of the roof and floor strata are the key controlling factors. One optimally comprehensive Class I favorable area (Tiao IV block) was successfully identified. This block exhibits a large resource scale, favorable coal seam conditions, a high tar yield, excellent geological sealing, and superior engineering compatibility, making it the recommended priority target for pilot testing. The evaluation system developed in this study can provide a theoretical basis and technical reference for the geological site selection of in situ pyrolysis of tar-rich coal in similar mining areas and advance its industrialization. Full article