Search Results (793)

Non-isocyanate polyurethanes (NIPUs) produced by the aminolysis of cyclic carbonates are often presented as safer and more sustainable alternatives to conventional polyurethanes. Their monomer sourcing and synthetic pathways are by now fairly well explored, but the physical principles controlling their properties remain much less understood. This perspective challenges the notion that these materials follow the paradigm of conventional polyurethanes. Emphasis is placed on the hydroxyl group formed next to the urethane moiety, which distinguishes these materials from conventional polyurethanes and makes them more precisely poly(hydroxy urethanes). The available evidence indicates that this pendent hydroxyl is not a minor structural detail but a central actor affecting hydrogen bonding, microphase separation, and through them, many macroscopic physical properties of NIPUs, such as glass transition, mechanical response, water uptake and reprocessability. In addition, it enables thermally activated bond-exchange reactions, which dynamically change chain connectivity and, in networks, topology. As a result, concepts borrowed from conventional segmented polyurethanes cannot be transferred directly to non-isocyanate ones. Instead, a new, physics-oriented predictive framework is the necessary next step for the rational design of non-isocyanate polyurethanes. Such a framework should take bond-exchange reactions into account and connect molecular structure and thermal history with the macroscopic physical properties. Full article

The redox behavior of nickel complexes with sulfur-containing ligands remains of considerable interest due to their significant value in coordination chemistry, catalysis, and bioorganic modeling. In this context, it is important to investigate how aqueous media and acid–base equilibria influence the stability and transformation pathways of such complexes. In this work, the electrochemical behavior of nickel complexes with phosphorylated dithiocarbamate was studied using cyclic voltammetry at various scan rates and pH values. Compared to similar systems in organic solvents, the complexes exhibited additional oxidation and reduction signals, indicating coupled chemical steps. The pH dependence of these peaks confirmed the role of hydroxo groups in the oxidation processes. Varying the scan rate revealed competition between ligand exchange pathways. At low and moderate scan rates, tris-dithiocarbamate nickel(III/IV) complexes are formed, whereas at higher scan rates, hydroxo-containing compounds make a greater contribution. Based on the experimental results and standard redox potentials derived from quantum chemical calculation data, a general scheme for the resulting electrochemical processes was proposed. The results demonstrate the key role of aqueous media and pH in regulating the redox process of nickel complexes with phosphorylated dithiocarbamate. Full article

Stock index price series are composed of superimposed multi-frequency components, including long-term trends, cyclical fluctuations, and stochastic noise. Effectively decoupling these heterogeneous components and modeling them separately is key to improving forecasting accuracy. Existing methods under the “decomposition–prediction” paradigm mostly employ fixed-scale decomposition, and the forecasting models are not specifically adapted to the non-stationary and high-noise characteristics of financial data, resulting in limitations in adaptivity and local dynamic capture. This paper proposes a frequency-aware adaptive multi-scale decomposition Transformer hybrid model (FAMS-Transformer). At the decomposition level, the fast Fourier transform is used to dynamically identify dominant cycles, thereby adaptively decoupling trends and fluctuations, overcoming the limitations of fixed-scale decomposition. At the forecasting level, a lightweight depthwise separable convolution is embedded between the self-attention and feedforward network of the Transformer encoder, enhancing the model’s ability to capture local temporal dynamics and achieving collaborative modeling of global dependencies and local information. Comparative experiments with 15 baseline models including LSTM, Transformer, TimesNet, and FreTS on three representative Chinese market indices—Shanghai Composite Index, Shenzhen Component Index, and Small and Medium Enterprises 100 Index—across four prediction horizons from one step to 15 steps demonstrate that FAMS-Transformer achieves the best forecasting accuracy in all scenarios. The coefficient of determination for 15-step prediction remains stably between 0.730 and 0.928. Moreover, the model still performs well on the S & P 500 dataset. Ablation studies and significance tests further validate the effectiveness of each core module and the statistical significance of the performance improvements. Full article

A capacitive screen-printed electrode immunosensor operating in non-faradaic mode by dispensing redox probes was developed for the Coronavirus 2 Spike (S) protein. This new strategy enabled direct detection of the S protein by measuring changes in the electrochemical capacitance resulting from antigen–antibody interactions on the electrode surface, altering interfacial dielectric properties. To enhance analytical sensitivity and provide an electrode surface with attractive capacitive and conductive properties, an in-house graphite ink-based screen-printed electrode was developed and subsequently modified with a polypyrrole (PPy) layer in bulk-synthesized in the presence of Cetyltrimethylammonium bromide (CTAB). CTAB acted as a dispersing and structure-directing agent, promoting homogeneous distribution and guiding the PPy polymerization, resulting in a composite with improved charge density storage and high conductivity. Analytical signals of the S proteins in spiked serum were detected by measuring the Specific Capacitances taken from cyclic voltammograms. This capacitive immunosensor achieved a linear range from 1 to 100 µg/mL (R² = 0.989, p < 0.05), with a limit of detection of 0.45 µg/mL of S protein, which falls within the clinical range for COVID-19 diagnostics. Probe-free detection without ferri/ferrocyanide steps minimizes errors by probe adsorptions and is easy to use as a point-of-care, unlike conventional immunosensors. Full article

Driven by the growing demand for sustainable polymers, polylactic acid (PLA) has attracted increasing attention due to its renewable origin and biodegradability. Lactide, the key cyclic monomer for PLA production via ring-opening polymerization (ROP), plays a decisive role in determining the molecular weight, stereoregularity, and final performance of PLA materials. However, current lactide synthesis processes still face significant challenges, including competing side reactions under high-temperature and high-vacuum conditions, difficulties in controlling stereochemical purity, and relatively high energy consumption. In this review, recent advances in lactide synthesis are systematically analyzed by examining the two principal industrial routes: the one-step process based on the direct dehydration–cyclization of lactic acid (LA), and the two-step process involving prepolymerization of LA followed by depolymerization/cyclization of oligomeric intermediates. The reaction mechanisms, key intermediates, and major side reactions—including racemization, transesterification, and deep polycondensation—are discussed, together with the regulatory roles of catalytic systems and reaction–separation coupling strategies. Comparative analysis reveals that the one-step route offers advantages in process integration and potential energy efficiency, whereas the two-step route provides superior control over stereochemical purity and process stability. Future research directions focusing on green catalysts, process intensification, and sustainable lactide production are also highlighted. Full article

The Gram-negative bacterium Pseudomonas aeruginosa produces a family of peptide siderophores called pyoverdines that play a vital role in the mechanisms by which it acquires iron from the environment. A key component of various pyoverdines is the presence of one or more copies of L-δ-N-formyl-δ-N-hydroxyornithine (fOHOrn) as an iron-binding residue. In this study, we have developed an improved preparation of a derivative of fOHOrn that is suitable for use in solid-phase peptide synthesis, incorporating a novel N-oxidation protocol and a mild final deprotection with HCl/hexafluoroisopropanol (HFIP) that circumvents the unexpected deformylation of the fOHOrn side chain under acidic conditions. We have also devised a synthesis of the cyclic peptide component of pyoverdine D exploiting a selective side-chain deprotection strategy with HCl/HFIP that allows the application of readily available amino acids with standard tert-butyl side-chain protection and which facilitates the cyclisation step. These innovations open the way towards the convergent preparation of various pyoverdines and also other natural products that contain fOHOrn residues. Full article

This study focuses on a 155 mm 32CrNi3MoV steel barrel and presents a thermochemically coupled phase transformation and diffusion dynamics model. The model leverages the significant disparity between radial and axial temperature gradients to simplify the heat conduction problem to a one-dimensional transient formulation. The temperature field distribution during firing sequences is solved analytically, accounting for the dynamic shift in critical phase transformation temperatures under high heating rates. The evolution of the martensitic layer thickness under repeated thermal shock is subsequently calculated. A numerical model for the pulsed diffusion of C and N is established based on Fick’s second law, incorporating the competitive diffusion–phase transformation mechanisms that govern martensite/austenite interface migration. To quantitatively evaluate the synergistic contribution of C and N to austenite stabilization, a carbon equivalent (Ceq) model is introduced, with the weight coefficient of N relative to C determined to be 0.68 and the critical Ceq required to lower the martensite start temperature below 25 °C calculated as 1.15 wt%. Concurrently, the microstructure and elemental distribution within the austenite layer of the retired barrel are systematically characterized using multi-scale techniques. The results indicate that the austenite layer on the inner bore surface arises from the synergistic effects of cyclic thermal-shock-induced phase transformation and elemental diffusion. Based on the Ceq criterion, the austenite layer thickness increases rapidly during the initial ~100 firing cycles, after which the growth rate slows significantly: it reaches approximately 1.27 μm after the first cycle and 2.94 μm after 1000 cycles, with only 0.2 μm of additional thickening between 100 and 1000 cycles—consistent with the experimentally observed range of 1.52–4.16 μm. The martensitic layer formed during the first firing cycle exhibits low thermal conductivity, which impedes subsequent heat transfer and leads to stabilization of its thickness at a characteristic depth. Grain refinement induced by repeated thermal shock provide short-circuit diffusion paths for elemental diffusion, accelerating compositional homogenization within the austenite layer and resulting in a stepped concentration profile at the interface. This study provides a representative example of non-equilibrium coupled phase transformation–diffusion phenomena under extreme transient loading. The established thickness prediction model can provide guidance for service life assessment of large-caliber barrels, offering both theoretical foundations and practical engineering guidance for their material design and performance optimization. Full article

The development of 3D-printable polymer–metal composites offers new opportunities for structured catalytic reactor design and process intensification. Here, cyclic olefin copolymer (COC) composites filled with micron-scale aluminum particles (1–15 wt%, 160 µm) were prepared via a two-step compounding and extrusion process to produce filaments suitable for fused filament fabrication (FFF). Thermal analysis confirmed that aluminum incorporation does not significantly alter the glass transition (T_g = 76–77 °C) or thermal stability of the polymer. Melt flow rate measurements indicated processable viscosity (MFR 3.82–4.57 g/10 min), while tensile testing revealed Young’s modulus of 1277 MPa–1783 MPa, maximum stress of 27 MPa–39 MPa, and enhanced strain at break for the 1 wt% Al composite (ε_B = 5.33%). Composites containing up to 15 wt% Al were successfully printed into mechanically robust static mixers, demonstrating complex geometries without particle sedimentation issues. The incorporation of aluminum particles introduces potential functionalities related to thermal management, surface modification, and future catalytic or photocatalytic applications. This work establishes a scalable polymer–metal platform integrating structural stability, geometric complexity, and prospective multifunctional behavior for advanced flow-reactor applications. Full article

Purpose: This study aims at the modification and psychometric evaluation of the “revised Illness Perception Questionnaire” (IPQ-R) for occupational dermatological rehabilitation. Methods: First, the questionnaire was modified for application in occupational dermatology. Subsequently, 254 patients of an inpatient rehabilitation programme participated in a cross-sectional survey. Afterwards, the dimensional analysis of the IPQ-R was conducted using principal component analysis. Separate analyses were conducted for the illness representations and the causal attribution scale. Results: A total of 228 participants were included in the analysis (age: M = 48.2 years; SD = 12.0; 53.9% female). The patient acceptance of the questionnaire was high (response rate 87.3%; rate of completion between 92.5% and 98.4%, N = 254). The IPQ-R for occupational dermatology consists of 29 items in the domain of illness representations, which include seven factors (illness coherence, emotional representations, consequences: implications for the structuring of own life, consequences: financial and social impacts, treatment control, personal control, and timeline acute/chronic). Six of these scales have acceptable-to-good internal consistency (Cronbach’s α 0.72–0.84); for one scale, the internal consistency is Cronbach’s α = 0.66. A separate analysis of the causes resulted in eight factors (psychological causes at work and during leisure time, attributions outside the workplace, skin cleansing and skin protection measures, behaviour-related risk factors, causes at work, other risk factors, external factors that cannot be influenced by the person, and climatic influences) with a total of 30 items. Five of the eight scales have an acceptable-to-good internal consistency (Cronbach’s α 0.71–0.83), and three scales are just below the acceptable range (Cronbach’s α 0.63–0.66). Conclusion: Overall, the initial psychometric results of the IPQ-R for occupational dermatology were satisfactory. However, additional validation steps are still required. The following differences to the original model should be considered when interpreting the available results: the factor “timeline cyclical” could not be replicated in this field of application. Additionally, two factors with different thematic emphases in the “consequences” section, besides effects on the personal way of life, social and financial consequences, became visible as well. Full article

This work presents advanced binder-free self-assembling Zn nanowire anodes synthesized by an easy-to-handle one-step low-pressure physical vapor deposition method. The morphology and structure of zinc nanowire networks are controlled and altered by the substrate temperature during deposition. Electrochemical performance of two types of Zn nanowire network samples of different morphology is studied in alkaline and mildly acidic aqueous electrolytes using cyclic voltammetry and electrochemical impedance spectroscopy techniques and compared to that of Zn foil electrodes. It is found that the morphology and structure of the Zn nanowire electrodes are directly related to their electrochemical performance and can be tuned for the type and concentration of the electrolyte to reach optimal electrochemical performance. The resulting binder-free self-assembled Zn nanowire anodes significantly outperform traditional Zn-based electrodes in both mild acidic and alkaline electrolytes, showing an areal capacitance of ~3.3 F/cm² and 3.5 F/cm² for acidic and alkaline electrolytes, respectively, and stability up to 1000 h of cycling in mild acidic electrolytes. These findings provide a pathway to fabricate and optimize binder-free zinc anodes for a variety of efficient and long-lasting aqueous zinc-based batteries and supercapacitors. Full article

This paper investigates solar energy production forecasting at a monthly temporal resolution using a pooled neural network framework applied to the Chikalov photovoltaic systems in southwestern Bulgaria. The study considers several related PV installations with unequal time-series lengths and formulates the forecasting task as one-step-ahead prediction of the next monthly total energy yield, measured in kWh, in a global pooled setting. Two complementary neural architectures are compared: a multilayer perceptron (MLP), which serves as a nonlinear feed-forward benchmark based on lagged observations and seasonal descriptors, and a gated recurrent unit (GRU), which explicitly models sequential temporal dependence. In both cases, seasonality is represented through cyclical calendar encodings, while model selection is performed by chronological hyperparameter search using a separate validation block. Forecast accuracy is assessed by RMSE, MAE, coefficient of determination (R²), MAPE, and sMAPE, and uncertainty is quantified through validation residual prediction intervals. The results show that the MLP achieves stronger validation performance, whereas the GRU provides better final out-of-sample generalization after refitting on the combined training and validation data. For both architectures, the best configurations are obtained with a 12-month input horizon, indicating that one full annual cycle contains the most informative memory for forecasting monthly aggregated photovoltaic energy yield in the considered dataset. After refitting on the combined training and validation data, the GRU achieved the best final out-of-sample performance, with RMSE = 296.38 kWh, MAE = 213.16 kWh, R² = 0.9231, MAPE = 7.52%, and sMAPE = 7.49%. Overall, the findings demonstrate that pooled neural modeling is an effective framework for monthly PV production forecasting and can provide practically useful support for sustainable energy planning, monitoring, and optimization. Full article

Industry 4.0 requires IoT ontologies that are interoperable, scalable, and adaptive in non-stationary industrial environments. This study combines methodological ontology optimization with a hybrid elastic framework for dynamic semantic updates and feedback-driven refinement. The methodological component systematizes literature and industrial practices to identify structural gaps and derive practical requirements. The engineering component integrates truth-table-based data structuring, vector–matrix automata for real-time classification and clustering, and in-memory event processing for low-latency operation. Experimental evaluation across no-drift, abrupt-drift, gradual-drift, and cyclic-drift scenarios shows a trade-off between semantic proximity and operational robustness: the rule-based approach reaches lower semantic distance in drift regimes, while the hybrid approach delivers higher stability and fewer false alarms in cyclic dynamics. All tested configurations preserve sub-millisecond processing latency, supporting edge/fog deployment. The results indicate that combining methodological analysis with elastic architecture is a practical pathway from static to adaptive IoT ontologies and a relevant step toward human-centric Industry 5.0 systems. Full article

The growing emphasis on environmental sustainability and the need for advanced manufacturing methods have accelerated progress in material processing. Aluminum powder metallurgy (APM) is particularly promising due to aluminum’s low density, high strength-to-weight ratio, and the inherent benefits of the powder metallurgy (PM) process. However, the corrosion resistance of sintered aluminum components remains a significant concern. In this study, shot peening (SP) was employed as a surface modification technique to improve the corrosion behavior of Alumix 321 PM alloy. Samples of the as-sintered and shot-peened Alumix 321 PM alloy, together with the wrought alloy counterpart AA6061, were characterized using non-contact optical profilometry, optical microscopy (OM), and scanning electron microscopy (SEM). Corrosion performance was evaluated in 3.5 wt.% NaCl solution using Tafel extrapolation (TE), cyclic polarization (CP), stair step polarization (SSP), and electrochemical impedance spectroscopy (EIS). The results revealed that shot peening increased surface roughness and significantly reduced the corrosion rate from 0.079 mmpy to 0.004 mmpy for the unpeened and peened samples, respectively. While pitting was the dominant corrosion mechanism in the wrought alloy, the PM alloy exhibited a combination of pitting, crevice, and intergranular corrosion. These findings highlight the potential of SP in enhancing the durability of aluminum-based PM components, offering valuable insights for industrial applications. Full article

Despite the rapid institutionalization of ESG reporting mandates worldwide, the empirical question of whether ESG disclosure constitutes a structural, long-run determinant of corporate financial performance—rather than a cyclical or spurious co-trending artifact—remains unresolved. The prior literature predominantly employs short-panel estimators that assume stationarity and conflate long-run equilibrium effects with transitory associations. This study addresses that gap by applying a five-step non-stationary panel econometric framework to a sample of 479 S&P 500 firms across eleven GICS sectors over 2010–2022 (5084 firm-year observations), a period chosen to capture the full institutionalization of Bloomberg ESG reporting standards and to encompass two major macroeconomic stress episodes (the 2015–2016 commodity downturn and the COVID-19 shock). Im–Pesaran–Shin panel unit root tests confirm that ESG disclosure scores and financial performance measures are both integrated of order one. Pedroni residual-based panel cointegration tests decisively reject the null of no long-run relationship (Z = −62.38 for the ROA equation), establishing a stable cointegrating equilibrium. Fully Modified OLS and Dynamic OLS group-mean estimators yield bias-corrected long-run coefficients, and a panel error correction model quantifies short-run adjustment dynamics. The key finding is that a ten-point improvement in ESG disclosure is associated with a permanent nine-to-ten percentage-point gain in return on equity (FMOLS β = +1.023, p < 0.01; DOLS β = +0.914, p < 0.01), while the effect on return on assets is positive but more modest and sensitive to estimator choice. Complementary fixed-effects regressions reveal an asymmetric moderating role of macroeconomic uncertainty: equity market volatility (VIX) amplifies the ESG performance premium, whereas acute credit market stress (TED spread) attenuates it. Board governance variables are statistically insignificant across all five specifications, indicating that H3 (board governance) is not supported; this outcome is attributed to limited within-firm governance variation in the large-cap S&P 500 universe rather than a genuine absence of governance effects. The results are robust to lagged ESG measurement, winsorization, and alternative interaction specifications. The findings provide strong econometric evidence for the structural, permanent nature of the ESG–financial performance link in large-cap U.S. equities, with direct implications for mandatory disclosure policy and ESG-integrated investment strategies. Full article

Cereulide is a heat-stable cyclic depsipeptide toxin produced by Bacillus cereus and is responsible for foodborne emetic syndrome. Recent reports of Bacillus cereus contamination and cereulide occurrence in infant formula have raised increasing food safety concerns. Due to the immature immune and metabolic systems of infants, exposure to cereulide through contaminated formula may lead to potential health risks. However, direct application of existing cereulide analytical methods to infant formula remains challenging because of the unique processing technologies, encapsulated nutrients, and variable matrix composition of this product category, which may hinder toxin release and cause significant matrix interference. In practical analysis, inter-laboratory comparisons revealed that existing methods exhibited relatively large deviations and insufficient sensitivity, making them not specifically optimized for infant formula matrices. The present study was motivated by the need for a matrix-specific, sensitive, and reliable analytical method for cereulide determination in infant formula. In this study, a method based on solid-phase extraction coupled with ultra-performance liquid chromatography–tandem mass spectrometry (SPE–UPLC–MS/MS) was developed and validated. To improve the applicability of cereulide analysis to infant formula, this method incorporates a hydration-assisted extraction step tailored to infant formula, which increased the detected cereulide response by approximately fourfold, together with optimized SPE clean-up and improved chromatographic conditions to reduce matrix effects and enhance quantitative reproducibility. The method showed good linearity (0.1–10 μg·L⁻¹, R² > 0.999), low values for limit of detection (LOD) (0.03 μg·kg⁻¹) and limit of quantification (LOQ) (0.1 μg·kg⁻¹), and acceptable recoveries (94.4–110.3%) with RSDs below 3.7%. The developed method was successfully applied to commercial infant formula samples, and cereulide-positive samples were identified. This method provides a reliable analytical tool for the monitoring of cereulide in infant formula and contributes to improved food safety surveillance and exposure risk assessment. Full article