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Scientific Reports Jul 2024This work introduces and discusses the impacts of the water bridge on gas adsorption and diffusion behaviors in a shale gas-bearing formation. The density distribution...
This work introduces and discusses the impacts of the water bridge on gas adsorption and diffusion behaviors in a shale gas-bearing formation. The density distribution of the water bridge has been analyzed in micropores and meso-slit by molecular dynamics. Na and Cl have been introduced into the system to mimic a practical encroachment environment and compared with pure water to probe the deviation in water bridge distribution. Additionally, practical subsurface scenarios, including pressure and temperature, are examined to reveal the effects on gas adsorption and diffusion properties, determining the shale gas transportation in realistic shale formation. The outcomes suggest carbon dioxide (CO) usually has higher adsorption than methane (CH) with a water bridge. Increasing temperature hinders gas adsorption, density distribution decreases in all directions. Increasing pressure facilitates gas adsorption, particularly as a bulk phase in the meso-slit, whereas it restricts gas diffusion by enhancing the interaction strength between gas and shale. Furthermore, ions make the water bridge distributes more unity and shifts to the slit center, impeding gas adsorption onto shale while encouraging gas diffusion. This study provides updated guidelines for gas adsorption and transportation characteristics and supports the fundamental understanding of industrial shale gas exploration and transportation.
PubMed: 38951644
DOI: 10.1038/s41598-024-66055-4 -
The EMBO Journal Jul 2024Transposable elements (TEs) are mobile genetic modules of viral derivation that have been co-opted to become modulators of mammalian gene expression. TEs are a major...
Transposable elements (TEs) are mobile genetic modules of viral derivation that have been co-opted to become modulators of mammalian gene expression. TEs are a major source of endogenous dsRNAs, signaling molecules able to coordinate inflammatory responses in various physiological processes. Here, we provide evidence for a positive involvement of TEs in inflammation-driven bone repair and mineralization. In newly fractured mice bone, we observed an early transient upregulation of repeats occurring concurrently with the initiation of the inflammatory stage. In human bone biopsies, analysis revealed a significant correlation between repeats expression, mechanical stress and bone mineral density. We investigated a potential link between LINE-1 (L1) expression and bone mineralization by delivering a synthetic L1 RNA to osteoporotic patient-derived mesenchymal stem cells and observed a dsRNA-triggered protein kinase (PKR)-mediated stress response that led to strongly increased mineralization. This response was associated with a strong and transient inflammation, accompanied by a global translation attenuation induced by eIF2α phosphorylation. We demonstrated that L1 transfection reshaped the secretory profile of osteoblasts, triggering a paracrine activity that stimulated the mineralization of recipient cells.
PubMed: 38951609
DOI: 10.1038/s44318-024-00143-z -
Scientific Reports Jul 2024Electrical conductivity (EC) is widely recognized as one of the most essential water quality metrics for predicting salinity and mineralization. In the current research,...
Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm.
Electrical conductivity (EC) is widely recognized as one of the most essential water quality metrics for predicting salinity and mineralization. In the current research, the EC of two Australian rivers (Albert River and Barratta Creek) was forecasted for up to 10 days using a novel deep learning algorithm (Convolutional Neural Network combined with Long Short-Term Memory Model, CNN-LSTM). The Boruta-XGBoost feature selection method was used to determine the significant inputs (time series lagged data) to the model. To compare the performance of Boruta-XGB-CNN-LSTM models, three machine learning approaches-multi-layer perceptron neural network (MLP), K-nearest neighbour (KNN), and extreme gradient boosting (XGBoost) were used. Different statistical metrics, such as correlation coefficient (R), root mean square error (RMSE), and mean absolute percentage error, were used to assess the models' performance. From 10 years of data in both rivers, 7 years (2012-2018) were used as a training set, and 3 years (2019-2021) were used for testing the models. Application of the Boruta-XGB-CNN-LSTM model in forecasting one day ahead of EC showed that in both stations, Boruta-XGB-CNN-LSTM can forecast the EC parameter better than other machine learning models for the test dataset (R = 0.9429, RMSE = 45.6896, MAPE = 5.9749 for Albert River, and R = 0.9215, RMSE = 43.8315, MAPE = 7.6029 for Barratta Creek). Considering the better performance of the Boruta-XGB-CNN-LSTM model in both rivers, this model was used to forecast 3-10 days ahead of EC. The results showed that the Boruta-XGB-CNN-LSTM model is very capable of forecasting the EC for the next 10 days. The results showed that by increasing the forecasting horizon from 3 to 10 days, the performance of the Boruta-XGB-CNN-LSTM model slightly decreased. The results of this study show that the Boruta-XGB-CNN-LSTM model can be used as a good soft computing method for accurately predicting how the EC will change in rivers.
PubMed: 38951605
DOI: 10.1038/s41598-024-65837-0 -
Scientific Reports Jul 2024The application of terahertz time-domain spectroscopy (THz-TDS) in the quantitative analysis of major minerals in Bayan Obo magnetite ore was explored. The positive...
The application of terahertz time-domain spectroscopy (THz-TDS) in the quantitative analysis of major minerals in Bayan Obo magnetite ore was explored. The positive correlation between the optical parameters of the original ore and its iron content is confirmed. The detections of three main iron containing minerals, including magnetite, pyrite, and hematite, were simulated using corresponding reagents. The random forest algorithm is used for quantitative analysis, and FeS is detected with precision of R = 0.7686 and MAE = 0.6307% in ternary mixtures. The experimental results demonstrate that THz-TDS can distinguish specific iron containing minerals and reveal the potential application value of this testing method in exploration and mineral processing fields.
PubMed: 38951568
DOI: 10.1038/s41598-024-65772-0 -
Scientific Reports Jul 2024Energy consumption of constructed educational facilities significantly impacts economic, social and environment sustainable development. It contributes to approximately...
Energy consumption of constructed educational facilities significantly impacts economic, social and environment sustainable development. It contributes to approximately 37% of the carbon dioxide emissions associated with energy use and procedures. This paper aims to introduce a study that investigates several artificial intelligence-based models to predict the energy consumption of the most important educational buildings; schools. These models include decision trees, K-nearest neighbors, gradient boosting, and long-term memory networks. The research also investigates the relationship between the input parameters and the yearly energy usage of educational buildings. It has been discovered that the school sizes and AC capacities are the most impact variable associated with higher energy consumption. While 'Type of School' is less direct or weaker correlation with 'Annual Consumption'. The four developed models were evaluated and compared in training and testing stages. The Decision Tree model demonstrates strong performance on the training data with an average prediction error of about 3.58%. The K-Nearest Neighbors model has significantly higher errors, with RMSE on training data as high as 38,429.4, which may be indicative of overfitting. In contrast, Gradient Boosting can almost perfectly predict the variations within the training dataset. The performance metrics suggest that some models manage this variability better than others, with Gradient Boosting and LSTM standing out in terms of their ability to handle diverse data ranges, from the minimum consumption of approximately 99,274.95 to the maximum of 683,191.8. This research underscores the importance of sustainable educational buildings not only as physical learning spaces but also as dynamic environments that contribute to informal educational processes. Sustainable buildings serve as real-world examples of environmental stewardship, teaching students about energy efficiency and sustainability through their design and operation. By incorporating advanced AI-driven tools to optimize energy consumption, educational facilities can become interactive learning hubs that encourage students to engage with concepts of sustainability in their everyday surroundings.
Topics: Artificial Intelligence; Schools; Humans; Conservation of Energy Resources; Decision Trees; Models, Theoretical
PubMed: 38951562
DOI: 10.1038/s41598-024-65727-5 -
Environmental Science and Pollution... Jun 2024Aluminum electrolyte is a necessity for aluminum reduction cells; however, its stock is rising every year due to several factors, resulting in the accumulation of solid...
Aluminum electrolyte is a necessity for aluminum reduction cells; however, its stock is rising every year due to several factors, resulting in the accumulation of solid waste. Currently, it has become a favorable material for the resources of lithium, potassium, and fluoride. In this study, the calcification roasting-two-stage leaching process was introduced to extract lithium and potassium separately from aluminum electrolyte wastes, and the fluoride in the form of CaF was recycled. The separation behaviors of lithium and potassium under different conditions were investigated systematically. XRD and SEM-EDS were used to elucidate the phase evolution of the whole process. During calcification roasting-water leaching, the extraction efficiency of potassium was 98.7% under the most suitable roasting parameters, at which the lithium extraction efficiency was 6.6%. The mechanism analysis indicates that CaO combines with fluoride to form CaF, while Li-containing and K-containing fluorides were transformed into water-insoluble LiAlO phase and water-soluble KAlO phase, respectively, thereby achieving the separation of two elements by water leaching. In the second acid-leaching stage, the extraction efficiency of lithium was 98.8% from water-leached residue under the most suitable leaching conditions, and CaF was obtained with a purity of 98.1%. The present process can provide an environmentally friendly and promising method to recycle aluminum electrolyte wastes and achieve resource utilization.
PubMed: 38951394
DOI: 10.1007/s11356-024-34129-5 -
Odontology Jul 2024Odontogenic keratocysts (OKCs) are locally aggressive cysts that exhibit typical histopathological features and have a propensity for recurrence. Though histological...
Odontogenic keratocysts (OKCs) are locally aggressive cysts that exhibit typical histopathological features and have a propensity for recurrence. Though histological variations are observed in OKCs, hard tissue formation and metaplastic changes are rare, and the underlying pathogenesis is not well understood. This study aimed to characterize stromal calcifications and analyze their association with odontogenic components in non-syndromic and syndrome-associated cases of OKCs. We analyzed 153 cases of OKCs from healthcare institutes in India and Japan. The epithelial and stromal features were evaluated, and the relationship of calcifications with odontogenic rests was determined. Immunohistochemistry for cytokeratin-19 and special stains including Masson Trichrome and Van Gieson, were used for identification of odontogenic rests and calcifications respectively. Stromal calcifications were observed in 29.41% OKCs. The calcification patterns included irregular dystrophic, dentinoid with linear or calcospherite-type mineralization, and psammoma calcifications. Psammoma and dentinoid calcifications were found in the proximity of cytokeratin-19-positive odontogenic rests or satellite cysts, whereas majority cases with dystrophic calcifications did not exhibit co-localization with stromal odontogenic components. Distinct patterns of calcifications were observed in OKCs. Calcifications found in proximity of the odontogenic rests were possibly indicative of an inductive or host-mediated response.
PubMed: 38951299
DOI: 10.1007/s10266-024-00975-5 -
Nature Communications Jun 2024Keratoconus, a disorder characterized by corneal thinning and weakening, results in vision loss. Corneal crosslinking (CXL) can halt the progression of keratoconus. The...
Keratoconus, a disorder characterized by corneal thinning and weakening, results in vision loss. Corneal crosslinking (CXL) can halt the progression of keratoconus. The development of accelerated corneal crosslinking (A-CXL) protocols to shorten the treatment time has been hampered by the rapid depletion of stromal oxygen when higher UVA intensities are used, resulting in a reduced cross-linking effect. It is therefore imperative to develop better methods to increase the oxygen concentration within the corneal stroma during the A-CXL process. Photocatalytic oxygen-generating nanomaterials are promising candidates to solve the hypoxia problem during A-CXL. Biocompatible graphitic carbon nitride (g-CN) quantum dots (QDs)-based oxygen self-sufficient platforms including g-CN QDs and riboflavin/g-CN QDs composites (RF@g-CN QDs) have been developed in this study. Both display excellent photocatalytic oxygen generation ability, high reactive oxygen species (ROS) yield, and excellent biosafety. More importantly, the A-CXL effect of the g-CN QDs or RF@g-CN QDs composite on male New Zealand white rabbits is better than that of the riboflavin 5'-phosphate sodium (RF) A-CXL protocol under the same conditions, indicating excellent strengthening of the cornea after A-CXL treatments. These lead us to suggest the potential application of g-CN QDs in A-CXL for corneal ectasias and other corneal diseases.
Topics: Quantum Dots; Animals; Graphite; Oxygen; Riboflavin; Rabbits; Male; Cross-Linking Reagents; Nitrogen Compounds; Reactive Oxygen Species; Keratoconus; Ultraviolet Rays; Cornea; Humans; Photosensitizing Agents; Corneal Stroma
PubMed: 38951161
DOI: 10.1038/s41467-024-49645-8 -
Scientific Reports Jul 2024The formation of planets in our solar system encompassed various stages of accretion of planetesimals that formed in the protoplanetary disk within the first few million...
The formation of planets in our solar system encompassed various stages of accretion of planetesimals that formed in the protoplanetary disk within the first few million years at different distances to the sun. Their chemical diversity is reflected by compositionally variable meteorite groups from different parent bodies. There is general consensus that their formation location is roughly constrained by a dichotomy of nucleosynthetic isotope anomalies, relating carbonaceous (C) meteorite parent bodies to the outer protoplanetary disk and the non-carbonaceous (NC) parent bodies to an origin closer to the sun. It is a common idea, that in these inner parts of the protoplanetary disks, planetesimal accretion processes were faster. Testing such scenarios requires constraining formation ages of meteorite parent bodies. Although isotopic age dating can yield precise formation ages of individual mineral constituents of meteorites, such ages frequently represent mineral cooling ages that can postdate planetesimal formation by millions or tens of millions of years, depending on the cooling history of individual planetesimals at different depths. Nevertheless, such cooling ages provide a detailed thermal history which can be fitted by thermal evolution models that constrain the formation age of individual parent bodies. Here we apply state-of-the-art thermal evolution models to constrain planetesimal formation times particular in the outer solar system formation region of C meteorites. We infer a temporally distributed accretion of various parent bodies from Ma to Ma after solar system formation, with 3.7 Ma and Ma for the parent bodies of CR1-3 chondrites and the Flensburg carbonaceous chondrite, and and Ma for the parent bodies of differentiated achondrites NWA 6704 and NWA 011, respectively. This implies that accretion processes in the C reservoir started as early as in the NC reservoir and were operating throughout typical protoplanetary disk lifetimes, thereby producing differentiated parent bodies with carbonaceous compositions in addition to undifferentiated C chondrite parent bodies. The accretion times correlate inversely with the degree of the meteorites' alteration, metamorphism, or differentiation. The accretion times for the CM, CI, Ryugu, and Tafassite parent bodies of 3.8 Ma, 3.8 Ma, Ma, and 1.1 Ma, respectively, fit well into this correlation in agreement with the thermal and alteration conditions suggested by these meteorites. Our results indicate that individual planetesimals formed rapidly (i.e., within Ma), however, distinct planetesimals formed recurrently throughout the total lifetime of the protoplanetary disk. Rapid individual formation is consistent with streaming instabilities assisted by gravitational collapse. However, obviously not the total dust inventory was consumed at early disk evolution stages, so there must have been some delay mechanisms, e.g. collisional destruction of precursor aggregates due to high impact velocities induced by radial drift phenomena. This counterbalance enabled late ( Ma) accretion of C planetesimals beyond the snow line which escaped severe planetesimal heating and volatile loss, hence, preserving their volatiles, especially water. Only this delayed formation of water-rich planetesimals allowed Earth to accrete sufficient water to become a habitable planet, preventing it from being a bone dry planet.
PubMed: 38951135
DOI: 10.1038/s41598-024-63768-4 -
Advances in Biochemical... Jul 2024Iron is a common contaminant in source water and wastewater. The mining and metallurgical industries in particular can produce and discharge large quantities of...
Iron is a common contaminant in source water and wastewater. The mining and metallurgical industries in particular can produce and discharge large quantities of wastewater with high iron concentrations. Due to the harmful effects of iron on organisms and infrastructure, efficient technologies for iron removal from water and wastewater are needed. On the other hand, iron is a valuable commodity for a wide range of applications. Microorganisms can facilitate iron removal and recovery through aerobic and anaerobic processes. The most commonly utilized microbes include iron oxidizers that facilitate iron precipitation as jarosites, schwertmannite, ferrihydrite, goethite, and scorodite, and sulfate reducers which produce hydrogen sulfide that precipitates iron as sulfides. Biological iron removal has been explored in various suspended cell and biofilm-based bioreactors that can be configured in parallel or series and integrated with precipitation and settling units for an effective flow sheet. This chapter reviews principles for biological iron removal and recovery, the microorganisms involved, reactor types, patents and examples of laboratory- and pilot-scale studies, and full-scale implementations of the technology.
PubMed: 38951134
DOI: 10.1007/10_2024_255