Browse Articles

Study of multi-size proppant breakage mechanism under deep reservoir conditions for enhanced geothermal system development

Abstract Proppant breakage is a significant concern in fracturing treatments in deep reservoirs, reducing the efficiency of enhanced geothermal systems (EGS). However, little research has been conducted on the breakage process of proppants under high closure stress conditions. A visualization experiment was designed to investigate processes of proppant breakage and layer deformation in real-time under 100 °C and high closure stress (0–50 MPa) conditions. We observed significant non-uniform breakage in the multi-size proppant layer, which resulted in large-size pores with high connectivity in the regions of low breakage degree, potentially maintaining permeability. Moreover, the non-uniform breakage forms a composite structure in two stages. This process mitigates subsequent proppant breakage, thereby preserving the non-uniform breakage pattern and maintaining a locally high-connectivity porous structure. In addition, we discussed the nonlinear deformation and stiffness of the proppant layer under stress loading. Finally, the applicability of the conclusions has been demonstrated by comparing granite-proppant experiments with the same conditions. The non-uniform breakage characterization of multi-size proppant layer in the granite-proppant experiments was observed as well. This research reveals the breakage mechanism of the multi-size proppant, which is expected to facilitate the optimization of proppant placements in deep fracturing operations.

Flagellin co-expression potentiates mRNA vaccine-induced cytotoxic T lymphocyte responses but not anti-tumor immunity

Test-retest reliability and usability evaluation of a wearable plantar pressure monitoring system for linear and curved walking

The association between 24-hour urinary biomarkers and metabolic syndrome: A cross-sectional study in zhejiang, China

Brain temperature as proxy for brain state and oscillatory activity in the mouse

Abstract Brain temperature and brain activity are in a complex, bidirectional relationship. Changes in brain temperature impact brain functioning and, conversely, brain activity generates heat. The latter can be illustrated by the characteristic changes in brain temperature that accompany the transitions between the brain states wakefulness, NREM sleep, and REM sleep. Here we show in the mouse that these typical temperature changes are sufficiently consistent to predict brain state. To gain further insight into this relationship, we quantified the effects of specific EEG activity patterns characteristic of sleep-wake states on temperature. We found that occurrences of spindles (11–15 Hz) during NREM sleep and of theta (7–9 Hz) and gamma (55–85 Hz) activity during wakefulness and REM sleep, were followed by increases in cortical temperature with a 10–14 s delay. In contrast, temperature decreased during the theta-rich cataplexy-associated state (CAS) observed in mice lacking the hypocretin gene, shedding new light on this non-physiological state. Our results show that brain temperature can be used as a reliable and accessible proxy of brain state and the accompanying oscillatory activity.

Cervical cancer prediction using deformable kernel darknet-53 and depth wise separable convolutional neural networks

Direct FFT oversampling without zero-padding

Computational analysis of metal organic framework and covalent organic framework using degree based topological indices with QSPR validation

Enhanced brain tumor segmentation in medical imaging using multi-modal multi-scale contextual aggregation and attention fusion

Comprehensive profiling of plasma and exosomal microRNAs in medication-related osteonecrosis of the jaw

ABCD2 improves the diagnostic accuracy of carotid artery stenosis when combined with CT angiography

Real-time rotational speed control and EEDI reduction research of rotor sail via high-Re aerodynamics and power Rose graph

Thermodynamic properties of CrMnFeCoNi high entropy alloy at elevated electronic temperatures

Repulsive guidance molecule A in the resolution of inflammation from ischemic stroke-associated pneumonia in mice

Aggregated decision system for financial resilience and performance enhancement

Superconductivity in transparent amorphous indium tin oxide films deposited by RF magnetron sputtering

Transcriptomic profiling reveals neural–immune–stromal dysregulation and risk-associated gene signatures in advanced keratoconus

Dynamic small object feature enhancement and detection for remote sensing images

Artificial intelligence for predicting depression anxiety and stress using psychometric data

Abstract Mental health is a crucial aspect of overall well-being, yet it is often overlooked due to stigma and limited accessibility to care. This study investigates the ability of artificial intelligence (AI) to predict common psychological conditions, depression, anxiety, and stress, using validated psychometric data. We analyzed responses from the Depression Anxiety Stress Scales-42 (DASS-42) questionnaire, combined with demographic information, drawn from a large publicly available dataset of 39, 775 anonymized participants. Five machine learning models were evaluated: decision tree, random forest, k-nearest neighbor, naive Bayes, and support vector machine (SVM). Data preprocessing included handling missing values, demographic standardization, and validity checks. Model performance was assessed using stratified train-test splits and five-fold cross-validation. The SVM model achieved the highest accuracy (99.3% for depression, 98.9% for anxiety, 98.8% for stress). These findings highlight the potential of AI-based approaches for early mental health screening, although further clinical validation is necessary to ensure their real-world applicability.

A de novo FBN1 variant likely causes congenital bilateral ectopia lentis in a crossbred horse

Abstract Although several inherited ocular disorders have been extensively studied in horses, few reports of equine ectopia lentis exist and no genetic investigations have been reported. Ectopia lentis in humans and other species is reported to be caused by trauma, genetic variants, and systemic diseases. The most commonly reported genetic causes are dominant alleles in FBN1 . Here we examined a 3-day old Oldenburg x Thoroughbred colt due to concerns over bilateral ocular anomalies and hypothesized that either a recessively inherited allele or a dominant de novo allele was the genetic cause. Examination revealed bilateral microphakia and spherophakia with medioventral lens subluxation. Histopathology of the globes was consistent with ectopia lentis. Whole genome sequencing of the affected foal was conducted, and forty-six candidate genes were evaluated for SNVs and small INDELS. Testing both hypotheses, 82 variants were identified, of which 69 were present in publicly available data from 504 horses and not investigated further. Of the 13 remaining variants, two variants were found in 3’ UTRs ( ADAMTS17 and OAF ), ten were intronic, and one was a coding variant located in the FBN1 gene encoding fibrillin-1 (FBN1:p.(Ala882Val)). This variant was also computationally predicted to be deleterious to protein function, including in silico modelling of FBN1 which suggests that 882Val impacts disulfide bond formation by Van der Waals clashing in a hybrid domain of the protein. The affected foal was confirmed by Sanger sequencing to be heterozygous for this variant and his clinically unaffected dam, reportedly unaffected sire, and five paternal half-siblings were homozygous for the reference allele. Additionally, the homologous human substitution is reported to be pathogenic, causing Marfan syndrome with a dominant mode of inheritance, of which ectopia lentis is a common feature. These findings support the de novo hypothesis with FBN1 :p.(Ala882Val) as the likely cause of ectopia lentis in this foal, the first genetic explanation for this condition in the horse. Given the role of FBN1 in ectopia lentis in humans and other species, FBN1 should be evaluated as a potential candidate when other horses with this condition are identified.