Search Results (61,734)

Background: Glucose 6 phosphate dehydrogenase (G6PD) is a rate-limiting enzyme of the pentose phosphate pathway. The loss of G6PD activity in red blood cells increases the risk of acute haemolytic anaemia under oxidative stress induced by infections, some medications, or fava beans. More than 200 single missense mutations are known in the G6PD gene. A 41-year-old woman with a family history of favism coming from the Basilicata region (Italy) was evaluated at our hospital for G6PD abnormalities. Methods: DNA was extracted from a peripheral blood sample and genotyped for the most common G6PD pathogenic variants (PVs). Positive results obtained by Restriction Fragment Length Polymorphism (RFLP), as per practice in our laboratory, were then reconfirmed in Sanger sequencing. Results: RFLP analysis highlighted a variant compatible with the G6PD Cassano variant. Confirmatory testing by Sanger unexpectedly identified a novel variant: c.1357G>A, p.(Val453Met) (NM_001360016.2); the same variant was found in the patient’s mother. In silico models predicted a deleterious effect of this variant at the protein level. The novel G6PD variant was named “G6PD Potenza” on the basis of the patient’s regional origin. Conclusions: This case describes a novel G6PD variant. It also highlights how the Sanger sequencing technique still represents an indispensable confirmatory standard method for variants that could be misinterpreted by only using a “first-level” approach, such as the RFLP. We stress that the evaluation of clinical manifestations in G6PD-deficient patients is of primary importance for the classification of each new G6PD mutation, in agreement with the new WHO guidelines. Full article

Coal is an important fossil energy source in the world, which provides important support for the development of industry. However, the chemical composition of coal is complex, and it may cause harm to the human body and environment during the process of mining and utilization, especially some aromatic hydrocarbons in coal that are strongly carcinogenic to human beings; thus, it is necessary to analyze the organic chemical compositions of coal so as to realize the clean and harmless utilization of coal. In this article, three different coal samples were extracted by seven solvent-graded extractions, and then the extracts were tested by gas chromatography–mass spectrometry (GC-MS). According to the results of the GC-MS test, it was found that CS₂ could dissolve a large amount of aromatic hydrocarbons in the coal, n-hexane could dissolve a larger amount of aliphatic hydrocarbons, methanol could dissolve a larger amount of ketones, benzene could extract phenolic compounds in the coal, acetone could dissolve alcoholic compounds, and the mixed solvent methanol/THF could dissolve coal esters. Then, by analyzing these extracts, researchers can clearly understand the microscopic organic components of coal, which have a significant role in the development of the coal chemical industry and ecological environment protection. Full article

To improve energy savings and emission reduction in industrial heating furnaces, this study investigated the impact of various molar fractions of hydrogen on natural gas combustion and compared the results of the Non-Premixed Combustion Model with the Eddy Dissipation Combustion Model. Initially, natural gas combustion in an industrial heating furnace was investigated experimentally, and these results were used as boundary conditions for CFD simulations. The diffusion flame and combustion characteristics of natural gas were simulated using both the non-premixed combustion model and the Eddy Dissipation Combustion Model. The results indicated that the Non-Premixed Combustion Model provided simulations more consistent with experimental data, within acceptable error margins, thus validating the accuracy of the numerical simulations. Additionally, to analyze the impact of hydrogen doping on the performance of an industrial gas heater, four gas mixtures with varying hydrogen contents (15% H₂, 30% H₂, 45% H₂, and 60% H₂) were studied while maintaining constant fuel inlet temperature and flow rate. The results demonstrate that the Non-Premixed Combustion Model more accurately simulates complex flue gas flow and chemical reactions during combustion. Moreover, hydrogen-doped natural gas significantly reduces CO and CO₂ emissions compared to pure natural gas combustion. Specifically, at 60% hydrogen content, CO and CO₂ levels decrease by 70% and 37.5%, respectively, while NO emissions increase proportionally; at this hydrogen content, NO concentration in the furnace chamber rises by 155%. Full article

Pure tin oxide (SnO₂) as a typical conductometric hydrogen sulfide (H₂S) gas-sensing material always suffers from limited sensitivity, elevated operation temperature, and poor selectivity. To overcome these hindrances, in this work, hollow CuO-SnO₂ nanotubes were successfully electrospun for room-temperature (25 °C) trace H₂S detection under blue light activation. Among all SnO₂-based candidates, a pure SnO₂ sensor showed no signal, even toward 10 ppm, while the 1% CuO-SnO₂ sensor achieved a limit of detection (LoD) value of 2.5 ppm, a large response of 4.7, and a short response/recovery time of 21/61 s toward 10 ppm H₂S, as well as nice repeatability, long-term stability, and selectivity. This excellent performance could be ascribed to the one-dimensional (1D) hollow nanostructure, abundant p-n heterojunctions, and the photoelectric effect of the CuO-SnO₂ nanotubes. The proposed design strategies cater to the demanding requirements of high sensitivity and low power consumption in future application scenarios such as Internet of Things and smart optoelectronic systems. Full article

The increasing use of illicit drugs has become a major global concern. Illicit drugs interact with the brain and the body altering an individual’s mood and behavior. As the substance-of-abuse (SOA) crisis continues to spread across the world, in order to reduce trafficking and unlawful activity, it is important to use point-of-care devices like biosensors. Currently, there are certain conventional detection methods, which include gas chromatography (GC), mass spectrometry (MS), surface ionization, surface-enhanced Raman spectroscopy (SERS), surface plasmon resonance (SPR), electrochemiluminescence (ECL), high-performance liquid chromatography (HPLC), etc., for the detection of abused drugs. These methods have the advantage of high accuracy and sensitivity but are generally laborious, expensive, and require trained operators, along with high sample requirements, and they are not suitable for on-site drug detection scenarios. As a result, there is an urgent need for point-of-care technologies for a variety of drugs that can replace conventional techniques, such as a biosensor, specifically an immunosensor. An immunosensor is an analytical device that integrates an antibody-based recognition element with a transducer to detect specific molecules (antigens). In an immunosensor, the highly selective antigen–antibody interaction is used to identify and quantify the target analyte. The binding event between the antibody and antigen is converted by the transducer into a measurable signal, such as electrical, optical, or electrochemical, which corresponds to the presence and concentration of the analyte in the sample. This paper provides a comprehensive overview of various illicit drugs, the conventional methods employed for their detection, and the advantages of immunosensors over conventional techniques. It highlights the critical need for on-site detection and explores emerging point-of-care testing methods. The paper also outlines future research goals in this field, emphasizing the potential of advanced technologies to enhance the accuracy, efficiency, and convenience of drug detection. Full article

Nanofluids have gained significant attention as a promising solution to several challenges in drilling operations. Nanoparticles, due to their exclusive properties such as high specific surface area, strong adsorption potential, and excellent thermal conductivity, offer significant potential to improve the efficiency and performance of drilling processes. Regardless of the advancements in drilling fluids and techniques that have improved borehole stability, hole cleaning, and extreme operational condition (HTHP) management, limitations still persist. This review discusses a detailed summary of existing research on the application of nanofluids in drilling, exploring their types, properties, and specific uses in areas such as fluid loss control, wellbore stability, and thermal management. It also reports the challenges and future potential of nanotechnology in drilling, including nanoparticle stability, environmental considerations, and cost concerns. By synthesizing current research and highlighting gaps for further study, this review intends to guide researchers and industry professionals in effectively integrating nanofluid usage to optimize drilling practices and support a more sustainable energy future. Full article

The integrity of wellbores is essential for the safe and efficient operation of drilling activities. Cement plays a critical role in this process, serving as a primary barrier that isolates the casing from the surrounding formation. To ensure the proper application of cement in wells, a thorough understanding of its mechanical properties is essential. Latex-modified cement stone (LMCS) offers significant advantages due to its anti-channeling, anti-corrosion, and mechanical characteristics. This study examined the mechanical properties of LMCS through uniaxial and triaxial compression and Brazilian splitting tests. Under uniaxial compression, the elastic modulus, Poisson’s ratio, and compressive strength of LMCS were found to range from 4.08 to 8.29 GPa, 0.05 to 0.46, and 15.82 to 22.21 MPa, respectively. In triaxial compression tests with confining pressures of 2 MPa, 4 MPa, 6 MPa, 8 MPa, and 10 MPa, the elastic modulus ranged from 4.48 to 6.87 GPa, Poisson’s ratio from 0.05 to 0.16, and compressive strength from 27.38 to 39.58 MPa. The tensile strength of LMCS ranged from 2.34 to 3.72 MPa. Moreover, the compressive strength of LMCS increased with confining pressure, showing enhanced resistance to failure due to the confining effect. However, the rate of increase gradually diminished. Strength criteria for LMCS, including Mohr–Coulomb and Drucker–Prager parameters, were derived from the triaxial compression tests. These strength criteria parameters provide a useful reference for developing the constitutive model of LMCS and for simulating triaxial compression conditions. The findings of this research offer valuable insights that can guide the construction of oil and gas wells. Full article

Fruit wine production is a practical approach for extending the shelf life and enhancing the value of strawberries (Fragaria × ananassa). Fruit cultivars and juices are important sources of volatile organic compounds (VOCs) that determine fruit wine sensory quality. In this study, VOCs in the juices and wines of four strawberry cultivars were identified using two-dimensional gas chromatography-time-of-flight mass spectrometry, and a sensory analysis of the wines was performed. A total of 1028 VOCs were detected. PCA and OPLS-DA distinguished the four cultivars from which the juices and wines were made. Six VOCs with variable importance in projection values greater than one were the main aroma and flavor components of strawberry wines. ZJ wine had the highest sensory scores for coordination (9.0) and overall evaluation (8.9) among the 18 descriptors of strawberry wine evaluated. Overall, the ZJ wine had the highest alcohol content (13.25 ± 0.59%, v/v) and sensory evaluation score, indicating that the ZJ cultivar is more suitable for fermentation. This study reflects the differences between wines made from four strawberry cultivars and provides a reference for brewing fruit wines. Full article

Anaerobic digestion (AD) is one of the most significant processes for treating fecal sludge. However, a substantial amount of microplastics (MPs) have been identified in septic tanks, and it remains unclear whether they impact the resource treatment of feces. To investigate this, polyethylene terephthalate (PET) was used as an indicator of MPs to study their effect on the anaerobic digestion of fecal sludge (FS). Two digestion systems were developed: FS mono-digestion and FS co-digestion with anaerobic granular sludge. The results indicated that the effects of PET varied between the two systems. PET inhibited volatile fatty acid synthesis in both systems, but the inhibition period differed. During mono-digestion, PET slightly increased gas and methane production, in contrast to the co-digestion system, where PET reduced methane production by 75.18%. Furthermore, in the mono-digestion system, PET increased soluble chemical oxygen demand and ammonia nitrogen concentrations while blocking phosphorus release, whereas the co-digestion system showed the opposite effects. Ultimately, the choice of digestion method is crucial for the resource utilization of septic tank sludge, and the impact of MPs on AD cannot be ignored. Full article

This research paper explores the use of machine learning to relate images of flame structure and luminosity to measured NOx emissions. Images of reactions produced by 16 aero-engine derived injectors for a ground-based turbine operated on a range of fuel compositions, air pressure drops, preheat temperatures and adiabatic flame temperatures were captured and postprocessed. The experimental investigations were conducted under atmospheric conditions, capturing CO, NO and NOx emissions data and OH* chemiluminescence images from 27 test conditions. The injector geometry and test conditions were based on a statistically designed test plan. These results were first analyzed using the traditional analysis approach of analysis of variance (ANOVA). The statistically based test plan yielded 432 data points, leading to a correlation for NOx emissions as a function of injector geometry, test conditions and imaging responses, with 70.2% accuracy. As an alternative approach to predicting emissions using imaging diagnostics as well as injector geometry and test conditions, a random forest machine learning algorithm was also applied to the data and was able to achieve an accuracy of 82.6%. This study offers insights into the factors influencing emissions in ground-based turbines while emphasizing the potential of machine learning algorithms in constructing predictive models for complex systems. Full article

R&D in the area of high-temperature symmetrical electrochemical devices is needed to meet the challenges of hydrogen energy. In the present study, the effect of Fe₂O₃ and CuO sintering aids on the electrochemical properties of the highly conductive solid electrolyte La_0.8Sr_0.2Ga_0.8Mg_0.2O_3−δ and La_0.6Sr_0.4FeO_3−δ electrodes for symmetrical solid oxide fuel cells was investigated. It is shown that the use of sintering aids leads to an improvement in grain boundary conductivity and allows us to reduce the sintering temperature to obtain a dense electrolyte with the same level of conductivity. It is shown for the first time that the nature of the sintering aids and the sintering temperature affect the La_0.6Sr_0.4FeO_3−δ electrode activity differently depending on the gas environment (air or hydrogen). On the basis of the analysis of the impedance spectra by the distribution of relaxation times, assumptions were made about the nature of the rate-determining steps of hydrogen oxidation and oxygen reduction. It is shown that the nature of the rate-determining steps can change depending on the electrode sintering temperature. It was found that among the studied electrodes, La_0.6Sr_0.4FeO₃−_δ with 3 wt.% Fe₂O₃ sintered at 1050 °C is optimal in terms of activity in oxidizing and reducing atmospheres. Full article

This research work focuses on the development of an environmentally friendly wound dressing using natural polymers. The inclusion of cannabis in these hydrogels stems from its innovative potential in medicine, particularly for wound healing and pain relief. The hydrogels were prepared by a simple methodology using natural polysaccharides, and cannabis extract through electrostatic interactions and crosslinking with sodium tripolyphosphate (TPP). Several tests were carried out to analyze the morphological, physical, thermal, mechanical, barrier, and antimicrobial properties of these hydrogels. Different types of hydrogels were synthesized including chitosan- gum arabic hydrogel (ChiGA), hydrogel loaded with cannabis extract (ChiGACann), hydrogel crosslinked with TPP (ChiGATPP), and ChiGACann crosslinked with TPP (ChiGACannTPP). The impact of both cannabis extract and TPP crosslinking on the properties of chitosan hydrogels was investigated. The significant swelling capacity measured to the hydrogels, with ChiGACann exhibiting a 250–350% in physiological conditions, making them suitable for wound dressing applications due to their exudate absorption capacity. Antimicrobial activity evaluation demonstrated that the hydrogels acted as barriers against different microorganisms, with Gram-positive bacteria being more sensitive than Gram-negative bacteria. Mechanical testing showed improved mechanical properties in the presence of cannabis extract and TPP crosslinking (20–30 kPa of compression modulus). In conclusion, these results highlight the application of ChiGACann hydrogels as promising materials for manufacturing wound dressings. Full article

Geothermal wells are subjected to higher loads compared to conventional oil and gas wells due to the thermal cycles that occur during both production and non-production phases. These temperature variations can affect the cohesion of the cement within the formation and casing, creating micro-annuli channels that can ultimately compromise the integrity of the well. Therefore, this study employs an intensive finite element methodology to analyze the debonding criteria of casing–cement systems in geothermal wells by examining over 36 independent models. The wellbore cooling and heating processes were simulated using three cohesive zone models (CZM): Type I (tensile), Type II (shear), and mixed (Type I and II simultaneously). The analysis revealed that Type I debonding occurs first during cooling at a temperature of around 10 °C, while Type II is the primary failure mode during heating. Evaluations of interfacial bonding shear strength (IBSS) values indicated that the debonding of the cement would even occur at high IBSS values (3 and 4 MPa) at a differential temperature of 300 °C, while the other IBSS of 1 MPa withstands only 60 °C. However, achieving an IBSS of 4 MPa with current technology is highly unlikely. Therefore, geothermal well operation and construction must be modified to keep the differential temperature below the critical temperature at which the debonding of the cement initiates. The study also found that debonding during cooling happens at lower differential temperatures due to generally lower values for interfacial bonding tensile strength (IBTS), typically less than 1 MPa. The novelty of the study is that it provides new insights into how specific temperatures trigger different types of debonding, highlights that high IBSS values may not prevent debonding at high differential temperatures, and recommends operational adjustments to maintain temperatures below critical levels to enhance cement integrity. Additionally, this study reveals that debonding during cooling occurs at a lower differential temperature change due to the reduced value of the interfacial bonding tensile strength (IBTS). Full article

Optimization of land management and agricultural practices require precise classification of soil properties. This study presents a method to fine-tune deep neural network (DNN) hyperparameters for multiclass classification of soil properties using genetic algorithms (GAs) with knowledge-based generation of hyperparameters. The focus is on classifying soil attributes, including nutrient availability (0.78 ± 0.11), nutrient retention capacity (0.86 ± 0.05), rooting conditions (0.85 ± 0.07), oxygen availability to roots (0.84 ± 0.05), excess salts (0.96 ± 0.02), toxicity (0.96 ± 0.01), and soil workability (0.84 ± 0.09), with these accuracies representing the results from classification with variations from cross-validation. A dataset from the USA, which includes land-use distribution, aspect distribution, slope distribution, and climate data for each plot, is utilized. A GA is applied to explore a wide range of hyperparameters, such as the number of layers, neurons per layer, activation functions, optimizers, learning rates, and loss functions. Additionally, ensemble methods such as random forest and gradient boosting machines were employed, demonstrating comparable accuracy to the DNN approach. This research contributes to the advancement of precision agriculture by providing a robust machine learning (ML) framework for accurate soil property classification. By enabling more informed and efficient land management decisions, it promotes sustainable agricultural practices that optimize resource use and enhance soil health for long-term ecological balance. Full article

In order to further improve the oxidation resistance of SiC-coated C/C composites used in extreme environments, TaSi₂ coatings were deposited on the surfaces of SiC-coated C/C composites by supersonic air plasma spraying (SAPS) with different spraying power parameters, under other fixed parameter (gas flow, power feed rate, spraying distance and nozzle diameter) conditions. The micro-structures and phase characteristics of the TaSi₂ coatings prepared with the four kinds of spraying powers (40 kW, 45 kW, 50 kW and 55 kW) were analyzed. Also, the inter-facial bonding strengths and fracture modes between the four TaSi₂ coatings and the SiC coating were studied. The results showed that with an increase in the spraying power, the morphologies of the TaSi₂ coatings appeared from loose to dense to loose. When the spraying power was 50 kW, the deposition rate reached a maximum of 39.8%. The TaSi₂ coating presented an excellent micro-structure without obvious pores and microcracks, and its inter-facial bonding strength was 15.3 ± 2.3 N. Meanwhile, the fracture surface of the sample exhibited a brittle characteristic. Full article