Search Results (1,129)

Herein, we rationally designed a molecular catalytic filter for effective micropollutants decontamination via peroxymonosulfate (PMS) activation. Specifically, iron phthalocanine (FePc) molecules with defined Fe–N₄ coordination were immobilized onto carbon nanotubes (CNTs), forming a hybrid catalyst that integrated molecular precision with heterogeneous catalytic properties. The resulting CNT-FePc filter achieved a 98.4% removal efficiency for bisphenol A (10 ppm) in a single-pass operation system, significantly outperforming the CNT/PMS system without FePc (41.6%). Additionally, the CNT-FePc/PMS system demonstrated remarkable resistance to performance inhibition by common water matrix components. Unlike typical radical-dominated PMS activation processes, mechanistic investigations confirmed that the CNT-FePc/PMS system selectively promoted singlet oxygen (¹O₂) generation as the primary oxidative pathway. Density functional theory (DFT) calculations revealed that PMS exhibited stronger adsorption on FePc (−3.05 eV) compared to CNT (−2.86 eV), and that FePc effectively facilitated O–O bond elongation in PMS, thereby facilitating ¹O₂ generation. Additionally, seed germination assays indicated a significant reduction in the biotoxicity of the treated effluents. Overall, this work presents a catalyst design strategy that merges molecular-level coordination chemistry with practical flow-through configuration, enabling rapid, selective, and environmentally benign micropollutant removal. Full article

Introduction: The sodium-to-potassium (Na:K) ratio in the diet is a critical biomarker for cardiovascular and metabolic health, yet global adherence to recommended levels remains poor. Objectives: The objective of this study was to identify dietary determinants of the dietary Na:K ratio and its associations with micronutrient intake and diet quality. Methods: An observational cross-sectional survey was conducted in a representative sample of manufacturing workers through a combined stratified proportional and two-stage probability sampling plan, with strata defined by company size and industrial sector from the state of Rio Grande do Norte, Brazil. Dietary intake was assessed using 24 h recalls via the Multiple Pass Method, with Na:K ratios calculated from quantified food composition data. Diet quality was assessed with the Diet Quality Index-International (DQI-I). Multiple linear regression was used to analyze associations of Na:K ratio with the study variables. Results: The survey was conducted in the state of Rio Grande do Norte, Brazil, in 921 randomly selected manufacturing workers. The sample mean age was 38.2 ± 10.7 years, 55.9% males, mean BMI 27.2 ± 4.80 kg/m². The mean Na:K ratio was 1.97 ± 0.86, with only 0.54% of participants meeting the WHO recommended target (<0.57). Fast food (+3.29 mg/mg per serving, p < 0.001), rice, bread, and red meat significantly increased the ratio, while fruits (−0.16 mg/mg), dairy, white meat, and coffee were protective. Higher Na:K ratios were associated with lower intake of calcium, magnesium, phosphorus, and vitamins C, D, and E, as well as poorer diet quality (DQI-I score: −0.026 per 1 mg/mg increase, p < 0.001). Conclusions: These findings highlight the critical role of processed foods in elevating Na:K ratios and the potential for dietary modifications to improve both electrolyte balance and micronutrient adequacy in industrial workers. The study underscores the need for workplace interventions that simultaneously address sodium reduction, potassium enhancement, and overall diet quality improvement tailored to socioeconomic and cultural contexts, a triple approach not previously tested in intervention studies. Future studies should further investigate nutritional consequences of imbalanced Na:K intake. Full article

An analytical study of the interaction of an ideal gas flow with a detonation wave was performed with account for the activation energy of chemical processes. Based on the modified Rankine-Hugoniot conditions, the effect of heat release on the limiting characteristics of detonation was analyzed. A dependence of the limiting value of the exponent Arrhenius number on the Mach number before the shock wave has been obtained. As the Mach number increases, the limiting value of the Arrhenius number decreases. An equation has been derived for determining the limiting value of the compression ratio in the shock wave. The effect of heat release intensity on the limiting compression ratio in a shock wave was elucidated. Also studied were effects of the Mach number and the Arrhenius number on the limiting compression ratio in a detonation wave. A condition for determining the critical value of the Arrhenius number necessary for the onset of detonation was obtained. Effects of the Mach number and the exponent of the Arrhenius number ${\mathrm{Ar}}_E$ on the critical value of the amplitude Arrhenius number ${\mathrm{Ar}}_A$ were discussed. The symmetry analysis of the gas flow parameters when passing through a detonation wave was performed. Full article

In this study, the possibility of using cement bypass dust as a cement additive was investigated. The utilization of cement bypass dust remains a major problem in cement production, as huge amounts of it are stored in landfills. In this study, a hydrothermal treatment is proposed to modify the properties of this dust and to expand its use. Hydrothermal treatment with pure bypass dust and quartz was carried out to achieve a CaO/SiO₂ ratio of 1 to 2. Samples were synthesized at 200 °C for 2, 4, 8, and 24 h. To examine the influence of the hydrothermal treatment on cement properties, a sample with a CaO/SiO₂ ratio of 1, hydrothermally treated for 8 h, was selected. This study employed XRD, XRF, DSC-TG, and isothermal calorimetry. Most of the target synthesis products, e.g., tobermorite and calcium silicate hydrates, formed after 8 h of sample synthesis, during which quartz was added to bypass dust and a CaO/SiO₂ ratio of 1 was achieved. An examination of the composition of the liquid medium following hydrothermal processing showed that almost all chlorine passed into the liquid medium, while some K₂O remained in the solid synthesis product. The synthesized additive is an effective catalyst for the hydration of Portland cement. After a 28-day curing period, specimens incorporating modified bypass dust replacing up to 10% of the Portland cement by weight demonstrated compressive strengths comparable to, or surpassing, those of specimens composed exclusively of Portland cement. Full article

Donepezil (DPZ) is an Alzheimer’s disease (AD) drug that promotes cholinergic neurotransmission and exhibits excellent acetylcholinesterase (AChE) selectivity. The current oral formulations of DPZ demonstrate decreased bioavailability, attributed to limited drug permeability across the blood–brain barrier (BBB). In order to overcome these limitations, various dosage forms aimed at delivering DPZ have been explored. This discussion will focus on the nose-to-brain (N2B) delivery system, which represents the most promising approach for brain drug delivery. Intranasal (IN) drug delivery is a suitable system for directly delivering drugs to the brain, as it bypasses the BBB and avoids the first-pass effect, thereby targeting the central nervous system (CNS). Currently developed formulations include lipid-based, solid particle-based, solution-based, gel-based, and film-based types, and a systematic review of the N2B research related to these formulations has been conducted. According to the in vivo results, the brain drug concentration 15 min after IN administration was more than twice as high those from other routes of administration, and the direct delivery ratio of the N2B system improved to 80.32%. The research findings collectively suggest low toxicity and high therapeutic efficacy for AD. This review examines drug formulations and delivery methods optimized for the N2B delivery of DPZ, focusing on technologies that enhance mucosal residence time and bioavailability while discussing recent advancements in the field. Full article

To analyze the hydrodynamic performance of the Voith–Schneider Propeller (VSP) under high eccentricity (e = 0.9), open-water performance numerical calculations were conducted for the VSP at different eccentricities. The results were compared with experimental data, revealing significant discrepancies at high eccentricity. Analysis identified that during the experiment, the VSP blades did not strictly move according to the prescribed “normal intersection principle” when passing near the eccentric point, which was the primary cause of the errors between the calculation and experiment. Further research demonstrated that when the blades pass near the eccentric point, both the individual blade and the overall propeller exhibit strong unsteady pulsation phenomena. The characteristics of these unsteady forces become more pronounced with increasing eccentricity. For the VSP under high eccentricity (e = 0.9), different Blade Steering Curves near the eccentric point were designed using a parametric method. The hydrodynamic performance of the VSP under these different curves was compared. The study demonstrates that rationally optimizing the motion of blades is a key approach to improving their hydrodynamic performance. At J = 2.4, the adoption of Opt-5 enables a 4.67% increase in thrust, a 25.19% reduction in thrust pulsation, a 12.74% reduction in torque, an 81.94% reduction in torque pulsation, and a 19.95% improvement in efficiency for the VSP. Full article

This study analyses the greenhouse gas reduction potential of different end-of-life (EoL) strategies based on a case study of light electric vehicles (LEVs). Using a shared electric moped scooter as a reference, four EoL scenarios are evaluated in a comparative life cycle assessment (LCA). The modelling of the scenarios combines different R-strategies (e.g., recycling, reusing, and repurposing) regarding both the vehicle itself and the battery. German and EU regulations for vehicle and battery disposal are incorporated, as well as EU directives such as the Battery Product Pass. The global warming potential (GWP₁₀₀) of the production and EoL life cycle stages ranges from 644 to 1025 kg CO₂ eq among the four analysed scenarios. Landfill treatment led to the highest GWP₁₀₀, with 1.47 times higher emissions than those of the base scenario (status quo treatment following EU directives), while increasing component reuse and repurposing the battery cells achieved GWP₁₀₀ reductions of 2.8% and 7.8%, respectively. Overall, the importance of implementing sustainable EoL strategies for LEVs is apparent. To achieve this, a product design that facilitates EoL material and component separation is essential as well as the development of political and economic frameworks. This paper promotes enhancing the circularity of LEVs by combining the LCA of EoL strategies with eco-design considerations. Full article

As high-speed electric multiple units (EMUs) advance in speed and complexity, quasi-static design methods may underestimate the fatigue risks associated with high-frequency dynamic excitations. This study quantifies the contribution of gear meshing-induced vibrations (2512 Hz) to fatigue damage in EMU gearbox housings, revealing resonance amplification of local stresses up to 1.8 MPa at 300 km/h operation. Through integrated field monitoring and bench testing, we demonstrated that gear meshing excites structural modes, generating sustained, very high-cycle stresses (>10⁸ cycles). Crucially, fatigue specimens were directly extracted from in-service gearbox housings—overcoming the limitations of standardized coupons—passing the very high-cycle fatigue (VHCF) test to derive S-N characteristics beyond 10⁸ cycles. Results show a continuous decline in fatigue strength (with no traditional fatigue limit) from 10⁸ to 10⁹ cycles. This work bridges the gap between static design standards (e.g., FKM) and actual dynamic environments, proving that accumulated damage from low-amplitude gear-meshing stresses (3.62 × 10¹¹ cycles over a 12 million km lifespan) contributes to a 16% material utilization ratio. The findings emphasize that even low-magnitude gear-meshing stresses can significantly influence gearbox fatigue life due to their ultra-high frequency, warranting design consideration beyond current standards. Full article

Microgrids have drawn attention due to their helpfulness in the development of renewable energy. It is necessary to make an optimal power dispatch scheme for each micro-source in a microgrid in order to make the best use of fluctuating and unpredictable renewable energy. However, the computational time of solving the optimal dispatch problem increases greatly when the grid’s structure is more complex. An improved parallel differential evolution (PDE) approach based on a message-passing interface (MPI) is proposed, aiming at the solution of the optimal dispatch problem of a microgrid (MG), reducing the consumed time effectively but not destroying the quality of the obtained solution. In the new approach, the main population of the parallel algorithm is divided into several small populations, and each performs the original operators of a differential evolution algorithm, i.e., mutation, crossover, and selection, in different processes concurrently. The gather and scatter operations are employed after several iterations to enhance population diversity. Some improvements on mutation, adaptive parameters, and the introduction of migration operation are also proposed in the approach. Two test systems are employed to verify and evaluate the proposed approach, and the comparisons with traditional differential evolution are also reported. The results show that the proposed PDE algorithm can reduce the consumed time on the premise of obtaining no worse solutions. Full article

Phenothiazines, mainly known for their antipsychotic activity, have recently attracted attention as potential compounds with anticancer and immunomodulatory activity In this study, 20 new quinobenzothiazines (MJ1–MJ20) were synthesized and their effects on normal cell lines (BEAS-2B, NHDF) and cancer cell lines (HCT116, MCF7, A549, SH-SY5Y, U2OS) were investigated. The studies included cytotoxicity assessment, analysis of the expression of genes (BCL2, AIFM2, MDM2) and pro-inflammatory cytokines (IL6, IL8) using the RT-qPCR method, and prediction of biological activity using the PASS platform. The results indicate that the compounds MJ19 and MJ20 have the greatest effect on the induction of pro-inflammatory (IL6, IL8) and antiapoptotic (BCL2, MDM2) genes, suggesting their potential use in therapies for inflammatory and autoimmune diseases. Gene expression analysis showed that compound MJ2 in BEAS-2B cells significantly induced the expression of AIFM2, a protein responsible for protecting against ferroptosis, while moderately increasing the expression of BCL2 and MDM2, suggesting a potential role for MJ2 in the modulation of protective mechanisms of healthy cells, e.g., avoiding apoptosis death. These results emphasize the potential of quinobenzothiazines as multifunctional bioactive compounds, which require further studies to determine their mechanisms of action and specificity. Full article

In this paper, a robust optimized controller is implemented in the photovoltaic generator system (PVGS). The PVGS is composed of individual photovoltaic (PV) cells, which convert solar energy to electrical energy. To optimize the efficiency of the PVGS under variable solar irradiance and temperatures, a maximum power point tracking (MPPT) controller is necessary. Additionally, the PVGS output voltage is typically low for many applications. To achieve the MPPT and to gain the output voltage, an increasing boost converter (IBC) is employed. Then, two issues should be considered in MPPT. At first, a smooth control signal for adjusting the duty cycle of the IBC is important. Another critical issue is the PVGS and IBC unknown sections, i.e., the total system uncertainty. Therefore, to address the system uncertainties and to regulate the smooth duty cycle of the converter, a robust dynamic sliding mode control (DSMC) is proposed. In DSMC, a low-pass integrator is placed before the system to suppress chattering and to produce a smooth actuator signal. However, this integrator increases the system states, and hence, a sliding mode observer (SMO) is proposed to estimate this additional state. The stability of the proposed control scheme is demonstrated using the Lyapunov theory. Finally, to demonstrate the effectiveness of the proposed method and provide a reliable comparison, conventional sliding mode control (CSMC) with the same proposed SMO is also implemented. Full article

Nowadays, the Metaverse is facing many challenges. In this context, Virtual Reality (VR) applications allowing voice-based human–3D object interactions are limited due to the current hardware/software limitations. In fact, adopting Automated Speech Recognition (ASR) systems to interact with 3D objects in VR applications through users’ voice commands presents significant challenges due to the hardware and software limitations of headset devices. This paper aims to bridge this gap by proposing a methodology to address these issues. In particular, starting from a Mel-Frequency Cepstral Coefficient (MFCC) extraction algorithm able to capture the unique characteristics of the user’s voice, we pass it as input to a Convolutional Neural Network (CNN) model. After that, in order to integrate the CNN model with a VR application running on a standalone headset, such as Oculus Quest, we converted it into an Open Neural Network Exchange (ONNX) format, i.e., a Machine Learning (ML) interoperability open standard format. The proposed system demonstrates good performance and represents a foundation for the development of user-centric, effective computing systems, enhancing accessibility to VR environments through voice-based commands. Experiments demonstrate that a native CNN model developed through TensorFlow presents comparable performances with respect to the corresponding CNN model converted into the ONNX format, paving the way towards the development of VR applications running in headsets controlled through the user’s voice. Full article

This article focuses on how rising nativism, manifested through immigrants’ experiences of everyday discrimination, and Florida’s legal context (ascertained through immigrants’ fears of deportation), are related to immigrants’ hesitation when seeking healthcare services. Hesitation to seek healthcare, or healthcare hesitancy, is examined in the context of Florida’s SB1718, a law passed in 2023 that criminalized many aspects of being an immigrant. Based on a survey of 466 Florida immigrants and U.S. citizen adult children of immigrants, logistic regression analysis reveals that everyday experiences with discrimination are associated with a reluctance to seek healthcare services among this population. In particular, those with insecure legal immigrant status (i.e., undocumented and temporary statuses), those with financial hardship, and women demonstrate reluctance to engage with healthcare systems when controlling for other sociodemographic factors. Findings from this study exemplify how immigration policies that restrict access to healthcare and social services not only create logistical barriers to seeking care but also foster a climate of fear and exclusion that deters even those with legal status from seeking medical attention. Full article

Repetitive DNA represents over 50% of the human genome and is an abundant component of circulating cell-free DNA (cfDNA). We previously showed that cfDNA levels and integrity can predict survival in elderly patients with cardiovascular disease. Here, we aimed to clarify whether a low-pass next-generation sequencing (NGS) approach can characterize the repeat content of cfDNA. Considering the bimodal distribution of cfDNA fragment lengths, we examined the occurrence of repetitive DNA subfamilies separately in dinucleosomal (>250 bp) and mononucleosomal (≤250 bp) cfDNA sequences from 24 patients admitted for heart failure. An increase in the relative abundance of Alu repetitive elements was observed in the longer fraction, while alpha satellites were enriched in the mononucleosomal fraction. The relative abundance of Alu, ALR, and L1HS DNA in the dinucleosomal fraction correlated with different prognostic biomarkers, and Alu DNA was negatively associated with the presence of chronic kidney disease comorbidity. These results, together with the observed inverse correlation between Alu DNA abundance and cfDNA integrity, suggest that the composition of plasma cfDNA could be determined by multiple mechanisms in different physio-pathological conditions. In conclusion, low-pass NGS is an inexpensive method to analyze the cfDNA repeat landscape and identify new cardiovascular disease biomarkers. Full article

The rapid progress of Large Language Models (LLMs) has greatly improved natural language tasks like code generation, boosting developer productivity. However, challenges persist. Generated code often appears “pseudo-correct”—passing functional tests but plagued by inefficiency or redundant structures. Many models rely on outdated methods like greedy selection, which trap them in local optima, limiting their ability to explore better solutions. We propose AnnCoder, a multi-agent framework that mimics the human “try-fix-adapt” cycle through closed-loop optimization. By combining the exploratory power of simulated annealing with the targeted evolution of genetic algorithms, AnnCoder balances wide-ranging searches and local refinements, dramatically increasing the likelihood of finding globally optimal solutions. We speculate that traditional approaches may struggle due to narrow optimization focuses. AnnCoder addresses this by introducing dynamic multi-criteria scoring, weighing functional correctness, efficiency (e.g., runtime/memory), and readability. Its adaptive temperature control dynamically modulates the cooling schedule, slowing cooling when solutions are diverse to encourage exploration, then accelerating convergence as they stabilize. This design elegantly avoids the pitfalls of earlier models by synergistically combining global exploration with local optimization capabilities. After conducting thorough experiments with multiple LLMs analyses across four problem-solving and program synthesis benchmarks—AnnCoder showcased remarkable code generation capabilities—HumanEval 90.85%, MBPP 90.68%, HumanEval-ET 85.37%, and EvalPlus 84.8%. AnnCoder has outstanding advantages in solving general programming problems. Moreover, our method consistently delivers superior performance across various programming languages. Full article