220 research outputs found
State-of-the-art of Fly Ash Engineering Property I
Crucial properties of Fly ash such as Classification criteria, Grain size distribution, Specific gravity, Compaction behavior, Permeability, Consolidation test, and Direct Shear Tests are discussed in this paper. More details and features about fly ash in Unconfined Compression, Self-hardening, Unconsolidated Undrained Triaxial Compression Test, Drained triaxial tests, and CIU triaxial tests, will be presented in the next paper. Large amount of data shows that geotechnical properties of fly ash are correlated with chemical composition. Most fly ash can be classified as sandy silt to silty sand or fine sand, and the specific gravity of fly ash depends on fineness, loss on ignition (LOI), mineralogy, and iron content. Moreover, the residual carbon content controls the compaction characteristics, even though other factors like gradation, iron content, morphology, etc. are also important. Class C fly ash is less permeable but shows a higher consolidation pressure resistance than class F fly ash
IL28B is associated with outcomes of chronic HBV infection
Purpose
The role of IL28B gene variants and expression in hepatitis B virus (HBV) infections are not well understood. Here, we evaluated whether IL28B gene expression and rs12979860 variations are associated with HBV outcomes.
Materials and Methods
IL28B genetic variations (rs12979860) were genotyped by pyrosequencing of DNA samples from 137 individuals with chronic HBV infection [50 inactive carriers (IC), 34 chronic hepatitis B (CHB), 27 cirrhosis, 26 hepatocellular carcinoma (HCC)], and 19 healthy controls. IL28A/B mRNA expression in peripheral blood mononuclear cells was determined by qRT-PCR, and serum IL28B protein was measured by ELISA.
Results
Patients with IL28B C/C genotype had greater IL28A/B mRNA expression and higher IL28B protein levels than C/T patients. Within the various disease stages, compared to IC and healthy controls, IL28B expression was reduced in the CHB, cirrhosis, and HCC cohorts (CHB vs. IC, p=0.02; cirrhosis vs. IC, p=0.01; HCC vs. IC, p=0.001; CHB vs. controls, p<0.01; cirrhosis vs. controls, p<0.01; HCC vs. controls, p<0.01). When stratified with respect to serum HBV markers in the IC and CHB cohorts, IL28B mRNA and protein levels were higher in HBeAg-positive than negative individuals (p=0.01). Logistic regression analysis revealed that factors associated with high IL28B protein levels were C/C versus C/T genotype [p=0.016, odds ratio (OR)=0.25, 95% confidence interval (CI)=0.08-0.78], high alanine aminotransferase values (p<0.001, OR=8.02, 95% CI=2.64-24.4), and the IC stage of HBV infection (p<0.001).
Conclusion
Our data suggest that IL28B genetic variations may play an important role in long-term development of disease in chronic HBV infections.</p
Model Predictive Control for Connected Hybrid Electric Vehicles
This paper presents a new model predictive control system for connected hybrid electric vehicles to improve fuel economy. The new features of this study are as follows. First, the battery charge and discharge profile and the driving velocity profile are simultaneously optimized. One is energy management for HEV for Pbatt; the other is for the energy consumption minimizing problem of acc control of two vehicles. Second, a system for connected hybrid electric vehicles has been developed considering varying drag coefficients and the road gradients. Third, the fuel model of a typical hybrid electric vehicle is developed using the maps of the engine efficiency characteristics. Fourth, simulations and analysis (under different parameters, i.e., road conditions, vehicle state of charge, etc.) are conducted to verify the effectiveness of the method to achieve higher fuel efficiency. The model predictive control problem is solved using numerical computation method: continuation and generalized minimum residual method. Computer simulation results reveal improvements in fuel economy using the proposed control method
Exploring General Intelligence via Gated Graph Transformer in Functional Connectivity Studies
Functional connectivity (FC) as derived from fMRI has emerged as a pivotal
tool in elucidating the intricacies of various psychiatric disorders and
delineating the neural pathways that underpin cognitive and behavioral dynamics
inherent to the human brain. While Graph Neural Networks (GNNs) offer a
structured approach to represent neuroimaging data, they are limited by their
need for a predefined graph structure to depict associations between brain
regions, a detail not solely provided by FCs. To bridge this gap, we introduce
the Gated Graph Transformer (GGT) framework, designed to predict cognitive
metrics based on FCs. Empirical validation on the Philadelphia
Neurodevelopmental Cohort (PNC) underscores the superior predictive prowess of
our model, further accentuating its potential in identifying pivotal neural
connectivities that correlate with human cognitive processes
NHERF1 regulates the progression of colorectal cancer through the interplay with VEGFR2 pathway
The oncogenic role of ectopic expression of Na+/H+ exchanger regulatory factor 1 (NHERF1) was recently suggested in colorectal cancer, where it was implicated in playing a role in the tumor hypoxia microenvironment. Here we showed that a high level expression of NHERF1 was found in colorectal cancer tissues and that the expression of NHERF1 was positively correlated with VEGFR2 expression. The prognostic value of VEGFR2 expression in colorectal cancer relied on the expression of NHERF1. The up-regulation of NHERF1 induced by the exposure to hypoxia in colon cancer cells depended on the activation of VEGFR2 signaling. NHERF1 in turn inhibited the activation of VEGFR2 signaling which could be regulated by the interaction between NHERF1 and VEGFR2, resulting in the reduction of migration and invasion of colon cancer cells. These results suggest a dynamic interplay between NHERF1 and VEGFR2 signaling in colorectal cancer, which could explain the contribution of NHERF1 to the regulation of tumor cell responses to the hypoxia microenvironment
Multi-channel quantum noise suppression and phase-sensitive modulation in a hybrid optical resonant cavity system
Quantum noise suppression and phase-sensitive modulation of continuously
variable in vacuum and squeezed fields in a hybrid resonant cavity system are
investigated theoretically. Multiple dark windows similar to electromagnetic
induction transparency (EIT) are observed in quantum noise fluctuation curve.
The effects of pumping light on both suppression of quantum noise and control
the widths of dark windows are carefully analyzed, and the saturation point of
pumping light for nonlinear crystal conversion is obtained. We find that the
noise suppression effect is strongly sensitive to the pumping light power. The
degree of noise suppression can be up to 13.9 dB when the pumping light power
is 6.5 Beta_th. Moreover, a phase-sensitive modulation scheme is demonstrated,
which well fills the gap that multi-channel quantum noise suppression is
difficult to realize at the quadrature amplitude of squeezed field. Our result
is meaningful for various applications in precise measurement physics, quantum
information processing and quantum communications of system-on-a-chip
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