Search Results (42,489)

Ammonia (NH₃) gas is prevalent in industrial production as a health hazardous gas. Consequently, it is essential to develop a straightforward, reliable, and stable NH₃ sensor capable of operating at room temperature. This paper presents an innovative approach to modifying SnO₂ colloidal quantum dots (CQDs) on the surface of Ti₃C₂T_x MXene to form a heterojunction, which introduces a significant number of adsorption sites and enhances the response of the sensor. Zero-dimensional (0D) SnO₂ quantum dots and two-dimensional (2D) Ti₃C₂T_x MXene were prepared by solvothermal and in situ etching methods, respectively. The impact of the mass ratio between two materials on the performance was assessed. The sensor based on 12 wt% Ti₃C₂T_x MXene/SnO₂ composites demonstrates excellent performance in terms of sensitivity and response/recovery speed. Upon exposure to 50 ppm NH₃, the frequency shift in the sensor is −1140 Hz, which is 5.6 times larger than that of pure Ti₃C₂T_x MXene and 2.8 times higher than that of SnO₂ CQDs. The response/recovery time of the sensor for 10 ppm NH₃ was 36/54 s, respectively. The sensor exhibited a theoretical detection limit of 73 ppb and good repeatability. Furthermore, a stable sensing performance can be maintained after 30 days. The enhanced sensor performance can be attributed to the abundant active sites provided by the accumulation/depletion layer in the Ti₃C₂T_x/SnO₂ heterojunction, which facilitates the adsorption of oxygen molecules. This work promotes the gas sensing application of MXenes and provides a way to improve gas sensing performance. Full article

Bioplastics are designed to degrade at the end of their lifecycle, but effective management of their end-of-life phase and integration into existing organic waste management systems remain significant challenges. Some bioplastics decompose under anaerobic conditions, with the anaerobic digestion (AD) process being a potential solution for their disposal. AD is a promising technology for valorising organic wastes, enabling biomethane production, reducing carbon footprints, and promoting product circularity. This study focuses on evaluating the continuous co-digestion of bioplastics with mixed sludge from an urban wastewater treatment plant (WWTP). Polyhydroxybutyrate (PHB) was the selected bioplastic, as various studies have reported its high and rapid degradation under anaerobic mesophilic conditions. PHB’s biodegradability under typical WWTP anaerobic digestion conditions (35 °C, 20-day retention time) was assessed in batch tests and the results indicate that PHB degradation ranged from 68 to 75%, depending on particle size. To further explore the potential of AD for PHB valorisation, the feasibility of anaerobic co-digestion of PHB with WWTP sludge was tested on a continuous laboratory scale using two digesters: a conventional digester (CSTR) and an anaerobic membrane bioreactor (AnMBR). The results indicated complete degradation of PHB, which led to higher biomethanisation percentages in both digesters, rising from 58% to 70% in the AnMBR and from 44% to 72% in the CSTR. The notable increase observed in the CSTR was attributed to changes in microbial populations that improved sludge biodegradability. Full article

Kale (Brassica napus) and collard (Brassica oleracea) are two leafy greens in the family Brassicaceae. The leaves are rich sources of numerous health-beneficial compounds and are commonly used either fresh or cooked. This study aimed to optimize the nutrient management of kale and collard in hydroponic production for greater yield and crop quality. ‘Red Russian’ kale and ‘Flash F1’ collard were grown for 4 weeks after transplanting in a double polyethylene-plastic-covered greenhouse using a nutrient film technique (NFT) system with 18 channels. Kale and collard were alternately grown in each channel at four different electrical conductivity (EC) levels (1.2, 1.5, 1.8, and 2.1 mS·cm⁻¹). Fresh and dry yields of kale increased linearly with increasing EC levels, while those of collard did not increase when EC was higher than 1.8 mS·cm⁻¹. Kale leaves had significantly higher P, K, Mn, Zn, Cu, and B than the collard at all EC levels. Additionally, mineral nutrients (except N and Zn) in leaf tissue were highest at EC 1.5 and EC 1.8 in both the kale and collard. However, the changing trend of the total N and NO3- of the leaves showed a linear trend; these levels were highest under EC 2.1, followed by EC 1.8 and EC 1.5. EC levels also affected phytochemical accumulation in leaf tissue. In general, the kale leaves had significantly higher total anthocyanin, vitamin C, phenolic compounds, and glucosinolates but lower total chlorophylls and carotenoids than the collard. In addition, although EC levels affected neither the total chlorophyll or carotenoid content in kale nor glucosinolate content in either kale or collard, other important health-beneficial compounds (especially vitamin C, anthocyanin, and phenolic compounds) in kale and collard leaves reduced with the increasing EC levels. In conclusion, the kale leaf had more nutritional and phytochemical compounds than the collard. An EC level of 1.8 mS·cm⁻¹ was the optimum EC level for the collard, while the kale yielded more at 2.1 mS·cm⁻¹. Further investigations are needed to optimize nitrogen nutrition for hydroponically grown kale. Full article

(1) Background: An alternative and understudied microbial mechanism that may influence demineralization is the microbially mediated ion exchange of Ca²⁺ and orthophosphate (P_i), which alters the saturation state of the mineral species within the surface enamel. There is a need to examine the ability of members of the oral microbiome to modulate Ca²⁺ and P_i, which control mineral solubility, in order to effectively evaluate mineralization therapies to improve oral health. (2) Methods: P_i uptake was measured using an ascorbic acid assay during a BHI liquid culture growth of Corynebacterium matruchotii and Streptococcus mutans for up to 20 h. The initial and endpoint medium Ca²⁺ levels were measured using ICP-OES. Bacterial cells were examined at different growth stages using DAPI/polyP binding emission at 525 nm to detect the presence of internalized macromolecules of polyphosphates (polyP) that could drive P_i uptake. (3) Results: C. matruchotii (p = 0.0061) substantially accumulated P_i (3.84 mmol/L), with a concomitant formation of polyP. In contrast, S. mutans did not take up P_i or accumulate polyP. No significant Ca²⁺ drawdown in the media was observed in either strain. (4) Conclusions: This study suggests that when examining the future efficacy of prevention technologies to improve, in vitro assays may consider including specific oral bacteria capable of substantial P_i uptake. Full article

This study addresses the control challenges associated with loading low-pressure liquid carbon dioxide carriers (LCO2Cs), which are crucial components of the carbon capture, utilization, and storage (CCUS) chain. It explores the need for stable pressure and temperature control to prevent dry ice formation and ensure efficient cargo handling. The research employed HYSYS dynamic simulations to assess three different control strategies. The simulations assessed each strategy’s effectiveness in maintaining stable operating conditions and preventing risks, such as dry ice formation and valve blockages. The study concluded by examining the necessity of pressurization for safe and efficient LCO₂ loading and by determining which control strategy is most effective and reliable based on the simulation outcomes. Among the three scenarios examined, Case A, which utilized two control valves, exhibited initial instability due to significant flow coefficient differences, resulting in temperature drops below the CO₂ triple point and increasing the risk of dry ice formation. Case C, operating without pressurization, experienced severe pressure fluctuations and prolonged exposure to temperatures below the triple point, posing risks of valve blockages. In contrast, Case B, which uses a remote pressure-reducing valve and a control valve, demonstrated the most stable performance, effectively avoiding dry ice formation and pressure fluctuations, making it the most reliable method for safe LCO₂ cargo loading. Full article

Silicone rubbers based on poly(dimethylsiloxane) (PDMS) are crosslinked elastomers commonly used in various branches of industry, especially as packing materials in elements for high-temperature service. In addition to high temperatures, mechanical loading may influence their structure during their work, and, as a consequence, their thermal properties may change. This study’s findings on the degradation mechanism under aging conditions are not just necessary, but also crucial for their satisfactory application. The aim of the study was a detailed and comprehensive evaluation of the aging processes of commercial ELASTOSIL^® LR 3842/50 A/B, considering structural changes based on thermal analysis accompanied by mass spectroscopy, X-ray analysis, and infrared spectroscopy. The aging process was carried out at 125 °C and 175 °C, without and with 11 kg of loading. The obtained results showed that the aging of PDMS increased their thermal stability. It was the most visible for PDMS aging at 175 °C under load. It was attributed to secondary crosslinking and the post-curing process. Observed changes in polymer structure did not indicate its degradation. This is a significant finding, especially considering that a temperature of 175 °C is close to the critical temperature given by the producer (180 °C), above which the use of stabilizing agents is recommended. Full article

Finding new molecules to prevent the growth of antimicrobial resistance is a hot topic for scientists worldwide. It has been reported that some raw bioproducts containing Monascus polyketides have antimicrobial activities, but extensive studies on this effect have not been conducted. In this context, our studies aimed to evaluate the antimicrobial properties of six raw bioproducts containing three classes of microbial polyketides biosynthesized by three Monascus strains through solid-state biosynthesis. As a methodology, we performed in silico predictions using programs such as PyMOL v3.0.4 and employed ESI-MS techniques to provide evidence of the presence of the six studied compounds in our bioproducts. The results obtained in silico were validated through in vitro studies using the Kirby-Bauer diffusion method on bacteria and fungi. The test performed in silico showed that Monascorubramine has the highest affinity for both Gram-positive and Gram-negative bacteria, followed by yellow polyketides such as Ankaflavin and Monascin. The estimated pharmacokinetic parameters indicated high gastrointestinal absorption and the potential to cross the blood-brain barrier for all studied compounds. However, the compounds also inhibit most enzymes involved in drug metabolism, presenting some level of toxicity. The best in vitro results were obtained for S. aureus, with an extract containing yellow Monascus polyketides. Predictions made for E. coli were validated in vitro for P. aeruginosa, S. enterica, and S. marcescens, as well as for fungi. Significant antibacterial properties were observed during this study for C. albicans, S. aureus, and fungal dermatophytes for crude bioproducts containing Monascus polyketides. In conclusion, the antimicrobial properties of Monascus polyketides were validated both in silico and in vitro. However, due to their potential toxicity, these bioproducts would be safer to use as topical formulations. Full article

This study aims to explore the efficacy of Bayesian Neural Networks (BNNs) in enhancing predictive modeling for healthcare applications. Advancements in artificial intelligence have significantly improved predictive modeling capabilities, with BNNs offering a probabilistic framework that addresses the inherent uncertainty and variability in healthcare data. This study demonstrates the real-world applicability of BNNs through three key case studies: personalized diabetes treatment, early Alzheimer’s disease detection, and predictive modeling for HbA1c levels. By leveraging the Bayesian approach, these models provide not only enhanced predictive accuracy but also uncertainty quantification, a critical factor in clinical decision making. While the findings are promising, future research should focus on optimizing scalability and integration for real-world applications. This work lays a foundation for future studies, including the development of rating scales based on BNN predictions to improve clinical outcomes. Full article

For the first time, carbon-particle-supported palladium-based cobalt composite electrocatalysts (abbreviated as Pd_xCo_y/CPs) were prepared using a calcination–hydrothermal process–hydrothermal process (denoted as CHH). The catalysts of Pd_xCo_y/CPs prepared using CoC₂O₄·2H₂O, (CH₃COO)₂Co·4H₂O, and metallic cobalt were named catalyst c₁, c₂, and c₃, respectively. For comparison, the catalyst prepared in the absence of a Co source (denoted as Pd/CP) was identified as catalyst c₀. All fabricated catalysts were thoroughly characterized by XRD, EDS, XPS, and FTIR, indicating that PdO, metallic Pd, carbon particles, and a very small amount of cobalt oxide were the main components of all produced catalysts. As demonstrated by the traditional electrochemical techniques of CV and CA, the electrocatalytic performances of Pd_xCo_y/CP towards the ethanol oxidation reaction (EOR) were significantly superior to that of Pd/CP. In particular, c₁ showed an unexpected electrocatalytic activity for EOR; for instance, in the CV test, the peak f current density of EOR on catalyst c₁ was 129.3 mA cm⁻², being about 10.7 times larger than that measured on Pd/CP, and in the CA test, the polarized current density of EOR recorded for c₁ after 7200 s was still about 2.1 mA cm⁻², which was larger than that recorded for Pd/CP (0.6 mA cm⁻²). In the catalyst preparation process, except for the elements of C, O, Co, and Pd, no other elements were involved, which was thought to be the main contribution of this preliminary work, being very meaningful to the further exploration of Pd-based composite EOR catalysts. Full article

Climate change has significant implications for agriculture, especially in viticulture, where temperature plays a crucial role in grapevine (Vitis vinifera) growth. Mendoza’s climate is ideal for producing high-quality wines, but 21st-century climate change is expected to have negative impacts. This study aimed to evaluate the effects of increased temperature on the phenology, physiology, and yield of Malbec, Bonarda, and Syrah. A field trial was conducted over two seasons (2019–2020 and 2020–2021) in an experimental vineyard with an active canopy heating system (+2–4 °C). Phenological stages (budburst, flowering, fruit set, veraison, harvest), shoot growth (SG), number of shoots (NS), stomatal conductance (gs), chlorophyll content (CC), chlorophyll fluorescence (CF), and water potential (ψa) were measured. Additionally, temperature, relative humidity, light intensity, and canopy temperature were recorded. Heat treatment advanced all phenological stages by approximately two weeks, increased SG and NS, and reduced gs and ψa during the hottest months. CC and CF remained unaffected. The treatment also resulted in lower yields, reduced acidity, and increased °Brix in both seasons. Overall, rising temperatures due to climate change advance the phenological phases of Malbec, Syrah, and Bonarda, leading to lower yields, higher °Brix, and lower acidity, although physiological variables remained largely unchanged. Full article

Slow pyrolysis was carried out in biosolids under three different temperatures (400, 500 and 600 °C) and two different carrier gases (CO₂ and N₂) on a fluidized bed reactor. The total concentration, chemical fractionation, and plant availability of the heavy metals in biochar were assessed by standard methods. The total concentration of Fe, Zn, Cu, Mn, Cr, Ni and Pb increased with the conversion of biosolids to biochar and with increasing pyrolysis temperature. The community’s Bureau of Reference (BCR) sequential extraction identified the migration of metals from toxic and bioavailable to potentially stable available or non-available forms at higher pyrolysis temperatures. Diethylenetriamine penta-acetic acid (DTPA)-extractable metals (Cu, Zn, Cd, Cu, Fe and Pb) were significantly lower in biochar compared to biosolids. By replacing N₂ with CO₂, the total metal concentration of heavy metals was significantly different for Mn, Ni, Cd, Pb and As. There were larger amounts of metals in the residual and oxidizable fractions compared to when N₂ was used as a carrier gas. Consequently, the biochar produced at higher temperatures (500 and 600 °C) in the N₂ environment exhibited lower potential ecological risks than in CO₂ environments (69.94 and 52.16, respectively, compared to values from 75.95 to 151.38 for biochars prepared in N₂). Overall, the results suggest that the higher temperature biochar can support obtaining environmentally safe biochar and can be effective in attenuating the ecological risks of biosolids. Full article

Forests play a key role in the global carbon (C) cycle through multiple interactions between above-ground and soil microbial communities. Deeper insights into the soil microbial composition and diversity at different spatial scales and soil depths are of paramount importance. We hypothesized that in a homogeneous above-ground tree cover, the heterogeneous distribution of soil microbial functional diversity and processes at the small scale is correlated with the soil’s chemical properties. From this perspective, in a typical Mediterranean holm oak (Quercus ilex L.) peri-urban forest, soil carbon dioxide (CO₂) emissions were measured with soil chambers in three different plots. In each plot, to test the linkage between above-ground and below-ground communities, soil was randomly sampled along six vertical transects (0–100 cm) to investigate soil physico-chemical parameters; microbial processes, measured using Barometric Process Separation (BaPS); and structural and functional diversity, assessed using T-RFLP and qPCR Real Time analyses. The results highlighted that the high spatial variability of CO₂ emissions—confirmed by the BaPS analysis—was associated with the microbial communities’ abundance (dominated by bacteria) and structural diversity (decreasing with soil depth), measured by H′ index. Bacteria showed higher variability than fungi and archaea at all depths examined. Such an insight showed the clear ecological and environmental implications of soil in the overall sustainability of the peri-urban forest system. Full article

Microtubules are the basic components of the eukaryotic cytoskeleton. We discuss a class of nonlinear waves traveling in microtubules. The waves are obtained on the basis of a kind of z-model. The model used is extended to account for (i) the possibility for nonlinear interaction between neighboring dimers and (ii) the possibility of asymmetry in the double-well potential connected to the external electric field caused by the interaction of a dimer with all the other dimers. The model equation obtained is solved by means of the specific case of the Simple Equations Method. This specific case is denoted by SEsM(1,1), and the equation of Riccati is used as a simple equation. We obtain three kinds of waves with respect to the relation of their velocity with the specific wave velocity $v_c$ determined by the parameters of the dimer: (i) waves with $v>v_c$, which occur when there is nonlinearity in the interaction between neighboring dimers; (ii) waves with $v<v_c$ (they occur when the interaction between neighboring dimers is described by Hooke’s law); and (iii) waves with $v=v_c$. We devote special attention to the last kind of waves. In addition, we discuss several waves which travel in the case of the absence of friction in a microtubule system. Full article

Background: Alzheimer’s disease (AD) is a progressive and irreversible neurodegenerative condition that increasingly impairs cognitive functions and daily activities. Given the incurable nature of AD and its profound impact on the elderly, early diagnosis (at the mild cognitive impairment (MCI) stage) and intervention are crucial, focusing on delaying disease progression and improving patients’ quality of life. Methods: This work aimed to develop an automatic sMRI-based method to detect AD in three different stages, namely healthy controls (CN), mild cognitive impairment (MCI), and AD itself. For such a purpose, brain sMRI images from the ADNI database were pre-processed, and a set of 22 texture statistical features from the sMRI gray-level co-occurrence matrix (GLCM) were extracted from various slices within different anatomical planes. Different combinations of features and planes were used to feed classical machine learning (cML) algorithms to analyze their discrimination power between the groups. Results: The cML algorithms achieved the following classification accuracy: 85.2% for AD vs. CN, 98.5% for AD vs. MCI, 95.1% for CN vs. MCI, and 87.1% for all vs. all. Conclusions: For the pair AD vs. MCI, the proposed model outperformed state-of-the-art imaging source studies by 0.1% and non-imaging source studies by 4.6%. These results are particularly significant in the field of AD classification, opening the door to more efficient early diagnosis in real-world settings since MCI is considered a precursor to AD. Full article

Recently, battery electric vehicles (BEVs) have faced various technical challenges, such as reduced driving range due to ambient temperature, slow charging speeds, fire risks, and environmental regulations. This numerical study proposes an integrated thermal management system (ITMS) utilizing R290 refrigerant and a 14-way valve to address these issues, proactively meeting future environmental regulations, simplifying the system, and improving efficiency. The performance evaluation was conducted under high-load operating conditions, including driving and fast charging in various environmental conditions of 35 °C and −10 °C. As a result, the driving efficiency was 4.82 km/kWh in high-temperature conditions (35 °C) and 4.69 km/kWh in low-temperature conditions (−10 °C), which demonstrated higher efficiency than the Octovalve-ITMS applied to the Tesla Model Y. Furthermore, in fast charging tests, the high voltage battery was charged from a 10% to a 90% state of charge in 26 min at 35 °C and in 31 min at −10 °C, outperforming the Octovalve-ITMS-equipped Tesla Model Y’s fast charging time of 27 min under moderate ambient conditions. This result highlights the superior fast-charging performance of the 14-way valve-based ITMS, even under high cooling load conditions. Full article